Deciphering Decomposition and the Effects of Disturbance in Forest Soil Microbial Communities with Metagenomics and Stable Isotope Probing by Roland Conrad Wilhelm BA.H, University of Guelph, 2010 MSc., McGill University, 2009 BSc.H., University of Guelph, 2007 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Microbiology and Immunology) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) October 2016 © Roland Conrad Wilhelm, 2016 Abstract Forest industries are expected to bolster the renewable resource economy, but must contend with ecological challenges in maintaining the long-term fertility of forest plantation soils, and technological challenges in converting forest biomass into industrially relevant sources of carbon and energy. This thesis advances research related to both, first by describing the broad changes in soil microbial communities in the decades following timber harvesting, their implications for soil processes and the influence of biomass retention for mitigation (Chapter 3) and, second, by conducting the first comprehensive culture-independent survey of lignocellulolytic organisms in forest soils to expand knowledge of their diversity and catabolic capabilities (Chapter 4). Analysis of over 1,300 bacterial (16S rRNA gene) and fungal (ITS region) pyrotag libraries demonstrated consistent changes in microbial communities at harvested sites across North America, such as i) the increase of desiccation- and heat-tolerant organisms, ii) the general decline of ectomycorrhizal (EM) fungi with a rise of select EM genera (Suillus and Thelephora), iii) the moderation of population shifts by organic matter retention and iv) changes in the functional character of harvested soils, including reduced methanotrophic populations and cellulolytic activity. Biogeographical differences in community structure revealed the potential for variation in the impacts of harvesting. Overall, a number of taxonomic groups were identified that may be important indicators for assessing the long-term impact of timber harvesting. Stable isotope probing revealed the degradation of model hemicellulose, cellulose and lignin substrates by specialized taxa, active on a sole substrate, and groups capable of degrading all three plant polymers, such as members of Burkholderiales and Caulobacteraceae. Bacterial lignin-degraders were more active than fungi in soil microcosms, represented by taxa with characterized lignolytic capability (Sphingobacteriaceae and Sphingomonadaceae) and novel taxa, such as members of Elusimicrobia and Acidobacteria. Differences in lignocellulolytic populations were observed among ecozones and soil layers. Mineral soils harboured a greater proportion of poorly characterized functional taxa and represent reservoirs of unexplored catabolic diversity. Metagenome assembly was ~3 to 20-fold higher as a result of SIP, providing a trove of sequence data containing carbohydrate- and lignin-active enzymes from lignolytic and cellulolytic taxa for future characterization. Résumé On s’attend des industries forestières qu’elles agissent comme un pilier de l’économie des ressources renouvelables. Pour y arriver, elles doivent d’abord adresser des défis écologiques en terme de maintien à long terme de la fertilité des sols des forêts de plantation, ainsi que des défis technologiques en terme de conversion de biomasse forestière comme source industrielle significative de carbone et d’énergie. La présente thèse avance la recherche sur ces deux défis : d’abord, en décrivant les changements généraux de communautés microbiennes durant les décennies suivant la récolte du bois, leur implication sur les processus de sol, et leur influence sur la rétention de biomasse à mitiger les changements (chapitre 3), ensuite, en menant la première campagne d’évaluation détaillée d’organismes lignicellulolytique de sols forestiers afin d’élargir les connaissances sur la diversité de taxa non-cultivés et sur les enzymes catalytiques qu’ils possèdent (chapitre 4). Des analyses de plus de 1300 banques pyrotags bactériennes (ARNr 16S) et fongiques (région ITS) ont démontré des changements réguliers des communautés microbiennes aux sites échantillonnés à travers l’Amérique du Nord, dont i) l’expansion des organismes tolérants à la sécheresse et la chaleur, ii) la chute accrue de champignons ectomycorhizes (EM) avec une augmentation de champignons spécifiques EM (Suillus et Thelephora), iii ) la régulation de changements de population par la rétention de matière organique et iv) des changements dans les caractéristiques fonctionnelles des sols récoltés, incluant une réduction des populations métanotrophes et de l’activité cellulolytique. Des différences biogéographiques dans les structures de communautés ont révélé le potentiel de variation des impacts de récolte. En somme, une variété de groupes taxonomiques pouvant servir d’importants indicateurs pour évaluer l’impact à long terme de la récolte forestière fut identifiée. L’utilisation de marquage isotopique stable (SIP) révéla que la dégradation d’hémicellulose modèle, de cellulose, et de substrats ligneux est entreprise par des taxa spécialisés, actifs sur un seul substrat, mais aussi par des groupes capables de dégrader les trois polymères végétaux, dont des membres des Burkholderiales et Caulobacteraceae. Les décomposeurs bactériens de lignine furent plus actifs que les champignons, représentés par des taxa possédant des capacités lignolytiques caractérisées (Sphingobacteriaceae et Sphingomonadaceae) ainsi que de nouveaux taxa, comme Elusimicrobia et Acidobacteria. Des différences de populations lignicellulotytiques furent observées parmi les zones biogeoclimatiques et couches de sol, avec les sols minéraux abritant une plus grande proportion de taxa de fonction peu caractérisée. L’utilisation de SIP mena à un assemblage métagénomique ~ trois à vingt fois plus élevé, fournissant une mine de données de séquences contenant des enzymes actives de carbohydrate et lignine provenant d’une variété de taxa putativement lignicellulolytiques. Preface The course of my thesis research was planned in consultation with Dr. William W. Mohn Material from a published paper (R., Wilhelm, A., Szeitz, T.L., Klassen, and W.W. Mohn. 2014. Appl. Environ. Microbiol. 80:7206-7211,) has been adapted and incorporated into the methods section of this thesis. With respect to my role in this work, I identified the need for a method to quantify 13C-enrichment of nucleic acids, devised the methodology in consultation with Auclair et al., (2011; Can. J. Microbiol., 58: 287-292), prepared and analyzed samples and wrote the paper. A. Szeitz operated the mass spectrometer, designed the UHPLC protocol and offered invaluable advice on how to improve sensitivity and accuracy. Klassen and Mohn provided comments on the final draft prior to publication. Other contributors to the work presented in this thesis include Lionel D. Jensen, who performed the respiration assays included in Section 3.3.1; Hilary Leung, whose SIP-hemicellulose bacterial pyrotag libraries were re-analyzed in Chapter 4 and who processed approximately one third of soil samples; Larissa McNeil processed the other third of soils and the majority of DNA extractions and PCR for samples described in Section 2.2.1; Dr. Erick Cardenas performed the first batch of draft genome binning, provided hidden Markov models for a number of lignin-modifying gene families and provided guidance for bioinformatic analyses throughout; Dr. Pedro Dimitriu provided guidance for statistical analyses and Dr. Kendra Maas facilitated the bulk sequencing of samples and collation of metadata used for the analyses in Section3.2. The custom synthesis of DHP-lignin by Dr. Rahul Singh was critical to research presented in Chapter 4. I am responsible for all other experimental design, data collection, analysis, research and writing presented in this thesis. Table of Contents Abstract / Résumé ................................................................................................................................ii Preface ................................................................................................................................................... v Table of Contents ................................................................................................................................ vi List of Tables ....................................................................................................................................... ix List of Figures ...................................................................................................................................... xi List of Abbreviations.......................................................................................................................... xv Acknowledgments ............................................................................................................................. xvi Dedication .........................................................................................................................................xvii Chapter 1: Introduction ...................................................................................................................... 1 1.1 Above and Belowground Perspectives on Timber Harvesting, Soil Microbial Communities and the Long-term Sustainability of Forest Plantations ............................................................................ 1 1.1.1 Current Context of the B.C. Forest Industry .......................................................................... 1 1.1.2 An Introduction to Forest Management and the Long-term Soil Productivity Study .......... 2 1.1.3 Soil Ecology and Long-term Soil Productivity ..................................................................... 4 1.1.4 Harvesting Impacts on Lignocellulose-degrading Populations ............................................. 7 1.1.5 Forests: A History of Disturbance ......................................................................................... 9 1.1.6 Contrasting Timber Harvesting with Natural Disturbances ................................................ 12 1.1.7 Long-term Impacts of Forest Fire on Soil Communities ..................................................... 14 1.1.8 Research Objectives for Assessment of Harvesting Impacts (Chapter 3) ........................... 16 1.2 Descriptions of Cellulolytic and Lignolytic Populations of Forest Soils: their Natural History and History of Industrial Use .......................................................................................................... 18 1.2.1 Valorization of Lignocellulosic Biomass ........................................................................... 18 1.2.2 Origins of Research into Cellulolytic and Lignolytic Organisms and Enzymes ................. 19 1.2.3 Natural History of Lignocellulose Synthesis and Degradation ........................................... 20 1.2.4 Lignocellulose-degrading Niches ........................................................................................ 23 1.2.5 Lignin-degrading Fungi and Bacteria .................................................................................. 24 1.2.6 Cellulose-degrading Fungi and Bacteria ............................................................................. 27 1.2.7 Lignocellulolytic Bacteria and Fungi in Forest and Other Soil Environments ................... 28 1.2.8 Symbioses of Lignocellulolytic Fungi and Bacterial .......................................................... 30 1.2.9 Stable Isotope Probing in Characterizing Lignocellulose-degrading Communities ............ 31 1.2.10 Overview of Classes of Ligninase and Cellulase Enzymes ............................................... 33 1.2.11 Cellulases and Accessory Enzymes ................................................................................... 33 1.2.12 Lignin-modifying and ‘Auxiliary Activity’ Enzymes ....................................................... 37 1.2.13 Research Objectives in the Survey of Cellulolytic and Lignolytic Taxa from Forest Soils Across North America (Chapter 4) ............................................................................................... 40 Chapter 2: Materials and Methods .................................................................................................. 43 2.1 Sample Collection from Long-term Soil Productivity Study Sites ............................................ 43 2.1.1 Site Descriptions .................................................................................................................. 43 2.1.2 Sample Collection ................................................................................................................ 43 2.2 Molecular Methods ..................................................................................................................... 44 2.2.1 Preparation of 16S rRNA gene and ITS region Pyrotag Libraries ...................................... 44 2.2.2 Preparation of and Sequencing of Shotgun Metagenome Libraries .................................... 47 2.2.3 Stable Isotope Probing ......................................................................................................... 48 2.2.3.1 Preparation and Properties of 13C-labeled Cellulose .................................................... 48 2.2.3.2 Preparation and Properties of 13C-labeled Lignin ........................................................ 50 2.2.3.3 Microcosm Preparation ................................................................................................ 50 2.2.3.4 Analysis of SIP-Phospholipid Fatty Acids (PLFA) ..................................................... 51 2.2.3.5 Quantitation of 13C-enriched DNA .............................................................................. 52 2.2.3.6 Recovery of 13C-enriched DNA ................................................................................... 55 2.2.3.7 Estimating Effects of GC Content on DNA Recovery from Heavy Fractions ............ 56 2.2.4 Methodology Exclusive to Study of Treatment Effects ...................................................... 56 2.2.4.1 Soil Respiration Microcosms ....................................................................................... 56 2.2.5 Methodology Exclusive to Survey of Cellulolytic and Lignolytic Organisms .................... 57 2.2.5.1 Fungicide Amended Microcosm Experiment .............................................................. 57 2.3 Bioinformatic Analyses .............................................................................................................. 58 2.3.1 General Statistical Approaches ............................................................................................ 58 2.3.2 Phylogenetics, Taxonomic and Ecological Classifications ................................................ 58 2.3.3 Diversity, Rarefaction, Ordination and perMANOVA ....................................................... 60 2.3.4 Indicator Species Analysis ................................................................................................... 60 2.3.5 Designating Cellulolytic and Lignolytic Taxa .................................................................... 60 2.3.6 Metagenome Assembly and Draft Genome Recovery ....................................................... 61 2.3.7 Characterization of Carbohydrate-Active Enzyme (CAZy) Content .................................. 62 Chapter 3: Long-term Impacts of Timber Harvesting on Soil Communities .............................. 64 3.1 Rationale ..................................................................................................................................... 64 3.2 Community Responses to Timber Harvesting ............................................................................ 65 3.2.1 Overview of Community Composition Across Ecozones ................................................... 66 3.2.2 Description of Harvesting Impacts on the Soil Properties .................................................. 70 3.2.3 Ecozone-wide, Global Responses to Harvesting ................................................................ 74 3.2.4 Ecozone-specific, Localized Responses to Harvesting ....................................................... 97 3.3 Impacts of Harvesting on Cellulolytic Populations .................................................................. 108 3.3.1 Effects of Harvesting on Respiration ................................................................................. 109 3.3.2 Characterization of SIP-Enrichment for Cellulose and Lignin .......................................... 109 3.3.3 Harvesting Effects on Cellulolytic Activity ..................................................................... 112 3.3.4 Harvesting Effects on Community Structure .................................................................... 115 3.3.5 Description of Cellulolytic Community ............................................................................ 130 3.4 Discussion ................................................................................................................................. 137 Chapter 4: Survey of Lignocellulolytic Populations of Forest Soils from Across North America with Stable Isotope Probing ............................................................................................................ 153 4.1 Rationale ................................................................................................................................... 153 4.2 Results ...................................................................................................................................... 153 4.2.1 13C-Enrichment by Substrate, Soil Layer and Ecozone ..................................................... 154 4.2.2 Comparison of Hemicellulolytic, Cellulolytic and Lignolytic Taxa ................................ 161 4.2.3 Carbohydrate Active Enzymes in Cellulolytic and Lignolytic Populations ...................... 181 4.2.4 Relative Contributions of Lignocellulose-degrading Taxa ............................................... 194 4.2.5 Ecozone-Specific Lignin and Cellulose-degrading Populations ...................................... 204 4.2.6 In situ Abundances of Lignocellulose-degrading Populations ......................................... 207 4.2.7 Impacts of Timber Harvesting on Lignocellulosic Taxa ................................................... 209 4.3 Discussion ................................................................................................................................. 211 Chapter 5: Conclusions ................................................................................................................... 225 References ......................................................................................................................................... 230 Appendix A – Synthesis of Coniferyl Alcohol ............................................................................... 262 Appendix B – Broad Ecological Impacts of Timber Harvesting ................................................. 263 Appendix C – Extended Characterization of Lignocellulolytic Taxa ......................................... 264 Appendix D – IsoLife 13C-Cellulose Purity Report ....................................................................... 276 Appendix E – Supplementary Tables ............................................................................................. 277 List of Tables Chapter 3 Table 3.1. Curated list of bacterial and fungal taxa showing population expansion or decline in response to harvesting....................................................................................................................90 Table 3.2. Curated list of bacterial and fungal taxa showing population expansion at intermediate intensities of OM removal.............................................................................................................98 Table 3.3. List of putatively cellulolytic bacterial and fungal taxa in Californian forest soil.....119 Chapter 4 Table 4.1. All putatively hemicellulolytic, cellulolytic and lignolytic taxa, indicating their prevalence among ecozones, number of putatively function OTUs and abundance ratio between 12C- and 13C-libraries...................................................................................................................169 Table 4.2. An overview of abundances of GH families containing characterized endoglucanases and all ‘Auxiliary Activity’ enzymes with known lignin-modifying activity.............................182 Appendix E - Supplementary Tables Table E.1. Summary of studies on the long-term impacts of timber harvesting on physicochemical properties of soil, forest productivity and soil biological................................277 Table E.2. An extensive compilation of all known lignolytic and cellulolytic bacteria, including both predicted function (based on genomic content) and validated function. Fungal degraders have been included in this list, but without a comprehensive effort............................................280 Table E.3. Overview of all sampling sites within the ecozones utilized in this study, including sampling information, climatic information and the date harvesting took place.........................291 Table E.4. Overview of the number of samples processed for each experiment for PLFA, pyrotag and metagenomic libraries..............................................................................................292 Table E.5. Differences in soil properties among all ecozones and soil layers according to harvesting treatment.....................................................................................................................295 Table E.6. Full list of bacterial and fungal taxa showing population expansion or decline in response to harvesting..................................................................................................................297 Table E.7. Full list of bacterial and fungal taxa showing population expansion in intermediate intensities of OM removal...........................................................................................................302 Table E.8. Differences in soil properties and microbial activity among Californian sites..............................................................................................................................................303 Table E.9. Differences in soil properties and microbial activity, particularly cellulolytic activity, among harvesting treatments in California..................................................................................304 Table E.10. Complete list of OTUs designated cellulolytic based on differential abundance between 13C- and 12C-pyrotag libraries for Californian soils.......................................................305 Table E.11. Full details of draft genomes recovered from SIP-cellulose from pooled metagenomic assemblies of all treatment from Californian soils (Chapter 3).............................311 Table E.12. Complete list of OTUs designated putatively hemicellulolytic, cellulolytic and/or lignolytic based on differential abundance between 13C- and 12C-pyrotag or metagenomic libraries at ecozones across North America (Chapter 4).............................................................312 Table E.13. Complete list of draft genomes recovered from 13C-cellulose and lignin metagenomic libraries from across North America (Chapter 4)..................................................314 Table E.14. Complete list of contigs containing clusters of three or more CAZymes recovered from draft genome bins and metagenome assemblies which contain genes known to be involved lignin-degradation........................................................................................................................322 List of Figures Chapter 1 Figure 1.1. Overview of sampling locations...................................................................................3 Figure 1.2. A census of studies on the impact of timber harvesting on forest regeneration...........5 Figure 1.3. Chronology showing natural history of major forest species.....................................10 Figure 1.4. Representations of the structure of cellulose, lignin and lignocellulose....................34 Chapter 2 Figure 2.1. Bar plot illustrating differences in soil properties among ecozones...........................45 Figure 2.2. Photographs of initial set up of Californian LTSP sites.............................................46 Figure 2.3. Examples of mass spectra for natural abundance and 13C-enriched DNA.................54 Chapter 3 Figure 3.1: Variation explained by abiotic and treatment factors (perMANOVA)......................67 Figure 3.2. Overlap of OTUs among ecozones and among treatments (Venn diagram)..............68 Figure 3.3: Rarefaction curves showing the sequencing depth obtained at each site...................69 Figure 3.4. Bar plots illustrating differences in soil properties among treatments.......................72 Figure 3.5: Mean daily soil temperature data for various sites across various time-scales..........73 Figure 3.6: Snowflake plots showing the most common abundance patterns of OTUs...............75 Figure 3.7. Richness and diversity estimates among harvesting treatments.................................76 Figure 3.8: Relative abundance of bacterial and fungal OTUs at the Phylum level.....................82 Figure 3.9. Contrasted abundances of Basidiomycota to Ascomycota..........................................83 Figure 3.10. Abundance pattern of unclassified fungal and bacterial sequences.........................84 Figure 3.11. Top OTUs from indicator taxa responding to harvesting (dot plot).........................86 Figure 3.12. Expansion of Terrabacteria and pyrophilous fungi..................................................88 Figure 3.13. Abundance patterns of methanotrophic bacteria (Methylocapsa)............................93 Figure 3.14. Abundance plots of ectomycorrhizal fungi..............................................................94 Figure 3.15. Richness and diversity estimates of ectomycorrhizal fungi.....................................95 Figure 3.16. Taxa with greatest abundances at intermediate intensities of OM removal.............99 Figure 3.17. Abundances patterns of ‘wood saprotroph’ fungi among harvesting treatments...100 Figure 3.18. Non-parametric multidimensional scaling of bacterial and fungal libraries..........102 Figure 3.19. Taxa responding differently to harvesting according to North – South axis..........103 Figure 3.20. Taxa responding differently to harvesting according to West – East axis.............104 Figure 3.21. Phylogenetic tree of fungal genus, Suillus, and bacterial genus, Kitasatospora....105 Figure 3.22. Phylogenetic tree of fungal genus, Rhizopogon.....................................................106 Figure 3.23. Responses to harvesting in EM fungi from the family Thelephoraceae................107 Figure 3.24. Overview of the samples, experiments and datasets utilized in studying the effects of timber harvesting on the cellulolytic community....................................................................108 Figure 3.25. Dot-plot showing soil respiration in mineral soils from reference and harvested treatments.....................................................................................................................................110 Figure 3.26. Time-course assay of cellulose enrichment of organic and mineral layer soils.....111 Figure 3.27. Comparison of organic and mineral layer soil characteristics and cellulolytic activity..........................................................................................................................................113 Figure 3.28. Trends in cellulolytic populations based on PLFAs...............................................114 Figure 3.29. Overview of 13C-enrichment of soil DNA and total DNA recovery by SIP..........116 Figure 3.30. NMDS of cellulolytic bacterial communities.........................................................117 Figure 3.31. Variation explained by treatment factors in SIP-cellulose (perMANOVA)..........118 Figure 3.32. Overview of draft genome bins and read mapping by treatment...........................122 Figure 3.33. Bar plots showing abundances of indicator taxa libraries......................................123 Figure 3.34. Abundance patterns of Gram-positive bacteria and fungi from Chaetomiaceae...124 Figure 3.35. Linear regressions of Sordariomycetes and C:N ratio............................................126 Figure 3.36. Linear regressions of Actinobacteria and C:N ratio...............................................127 Figure 3.37. Dot plot showing the differences in C:N ratio among harvesting treatments........128 Figure 3.38. Linear regressions of actinobacterial abundance with pH among ecozones..........129 Figure 3.39. Non-parametric multidimensional scaling of cellulolytic fungi.............................132 Figure 3.40. Classification of all unassembled metagenomic reads at the rank Phylum............133 Figure 3.41. Relative abundances of Basidiomycota to Ascomycota..........................................134 Figure 3.42. Taxonomic affiliations of CAZy genes enriched in SIP-metagenomes.................135 Chapter 4 Figure 4.1. Overview of the degree of enrichment of microbial biomass..................................156 Figure 4.2. Metagenome assembly according to substrate, ecozone and soil layer....................157 Figure 4.3. Mass of DNA recovered according to CsCl gradient fractions................................158 Figure 4.4. Comparison of ‘Nextera’ or ‘Nextera XT’ kits........................................................159 Figure 4.5. Heat map of delta-13C enrichment of PLFAs across time-course experiments........160 Figure 4.6. Venn diagrams showing overlap among SIP and in situ pyrotag libraries...............161 Figure 4.7. Principle components analysis of delta-13C enrichment of PLFAs..........................163 Figure 4.8. Abundances of Ascomycota and Basidiomycota in metagenomic libraries.............164 Figure 4.9. Abundances of bacterial phyla illustrating differences in hemicellulolytic, cellulolytic and lignolytic activity among taxa and ecozones.....................................................165 Figure 4.10. NMS plots showing differences in community composition of cellulolytic and lignolytic populations...................................................................................................................167 Figure 4.11. Abundant classes of bacteria in pyrotag libraries by substrate and soil layer........169 Figure 4.12. Abundances of lignocellulolytic genera of Caulobacteraceae...............................172 Figure 4.13. Phylogenetic tree of lignocellulolytic OTUs from Caulobacteraceae...................173 Figure 4.14. Overview of top quality draft genomes..................................................................176 Figure 4.15. Abundances of putatively multi-substrate utilizing OTUs.....................................178 Figure 4.16. Heat map of fungal orders and genera in metagenomic libraries...........................180 Figure 4.17. Overview of lignin-modifying Auxiliary Activity enzyme families......................183 Figure 4.18. Heat map showing abundant CAZy subfamilies in 13C-metagenomes..................185 Figure 4.19. Rank abundance and CAZyme density of CAZy clusters......................................187 Figure 4.20 Taxonomy of CAZy clusters containing lignin-modifying enzymes......................188 Figure 4.21 Taxonomy of scaffolds containing genes from the β-ketoadipate pathway............191 Figure 4.22. Differences in cellulolytic and lignolytic CAZy profiles for Caulobacteraceae...192 Figure 4.23. Taxonomy heat maps for fungi-exclusive families AA2, AA8 and AA9..............193 Figure 4.24. Correlation between 13C-enrichment of DNA and pyrotag abundance..................195 Figure 4.25. Classification of all unassembled metagenomic reads at the rank Order...............196 Figure 4.26. Box and whisker plots showing the average enrichment of PLFAs.......................198 Figure 4.27. Box and whisker plots showing the 13C-enrichment of fungi relative to bacteria normalized to pre-existing biomass.............................................................................................199 Figure 4.28. 13C-enrichment of PLFAs in samples incubated with or without antibiotic...........201 Figure 4.29. Barplots illustrating predominant families in metagenomic libraries derived from 13C-lignin incubations with and without the addition of fungicide..............................................202 Figure 4.30. Abundance patterns lignolytic taxa in fungicide treated soils................................203 Figure 4.31. Correlation between abundance in situ and enrichment in 13C-libraries................204 Figure 4.32. Venn diagram showing overlap of 13C-cellulose libraries among ecozones..........205 Figure 4.33. Localized patterns of abundance for cellulolytic or lignolytic taxa.......................206 Figure 4.34. Phylogenetic tree of lignolytic Solirubrobacterales...............................................208 Figure 4.35. Abundances of lignocellulolytic taxa according to OM removal...........................210 Appendix B Figure B.1. Barplots showing harvesting impacts on higher Eukaryotes and Lecanicillium.....263 Appendix C Figure C.1. Barplots of prominent hemicellulolytic taxa in pyrotag libraries............................265 Figure C.2. Barplots of prominent cellulolytic taxa in pyrotag libraries....................................266 Figure C.3. Barplots of prominent lignolytic taxa in pyrotag libraries.......................................269 Figure C.4. Barplots of prominent lignolytic taxa in whole shotgun metagenomes..................271 Figure C.5. Abundances of all genera within the family Ectothiorhodospiraceae in whole shotgun metagenomes..................................................................................................................272 Figure C.6. Abundances of hemicellulolytic, cellulolytic and lignolytic genera of Burkholderiales............................................................................................................................273 List of Abbreviations | symbol for “or” or “nor” as in ‘neither OM1|OM2 showed significant differences’ 12C most abundant (~98.9%) stable isotope of carbon 13C a heavier stable isotope of carbon (~1.1% natural abundance) AA ‘Auxiliary Activity,’ the category for lignin-modifying genes in the CAZy database BC British Columbia BS ‘Black Spruce’ ecozone with sites near Thunder Bay, Ontario CAZy a carbohydrate-active enzyme (also CAZyme) C:N ratio of total carbon to total nitrogen, ‘C:N ratio’ DHP dehydrogenatively polymerized DNA deoxyribonucleic acid enrOTU OTUs that have ‘enriched’ abundance in 13C- relative to 12C-sequencing libraries GH glycosyl hydrolase IDF ‘Interior Douglas Fir’ ecozone with sites near Kamloops, B.C. JP ‘Jack Pine’ ecozone with sites near Sault Ste. Marie, Ontario LCA lowest common ancestor – a classification method based on consensus of top BLAST hits LP ‘Loblolley Pine’ ecozone with sites near Kurth, Texas LPMO lytic polysaccharide monooxygenase MS mass spectrometry NCBI National Center for Biotechnology Information (United States of America) NMS | NMDS non-parametric multidimensional scaling OM organic matter, typically used in referring to organic matter removal or retention OTU operational taxonomic unit PCR polymerase chain reaction PCA principle components analysis PP ‘Ponderosa Pine’ ecozone in the Sierra Nevada Mountains of California SBS ‘Sub-Boreal Spruce’ ecozone in northern B.C. SIP stable isotope probing UHPLC ultra-high performance chromatography Acknowledgements This work was generously supported by a Large-Scale Applied Research Project Grant from Genome Canada and Genome British Columbia. I received personal funding in the form of an Alexander Graham Bell Canada Graduate scholarship (CGS) from the Natural Sciences and Engineering Research Council of Canada and a Four Year Fellowship from UBC. Together, the support from funding agencies encouraged my full commitment to research and, in the case of the large-scale grant, fostered a sense of common purpose among my colleagues and I. This work could not have been done without the intellectual oversight and magnanimity of my supervisor Dr. William Mohn. Dr. Mohn leads a diverse research group and has built a community of committed researchers in microbial ecology. He is an adroit teacher from whom I have gained valuable insights. I thank him for the opportunity to conduct my research as well as for giving me access to current research trends by supporting my attendance at conferences. The success of this research is indebted to the forward thinking scientists who devised and implemented the Long-term Soil Productivity Study and those who have sustained its operations. All soil samples used in this thesis were collected by collaborators in the Canadian Forestry Services (Dr. Paul Hazlett), the Ontario Ministry of Natural Resources (Dr. David Morris), and the U.S. Forest Service (Dr. Matt Busse and Dr. Andy Scott). These individuals also provided valuable data on soil conditions in the decade and half since harvesting. I thank Hilary Leung for his company at the bench and his readiness to discuss or assist in trouble-shooting all things lab-related; Andras Seitz for his valuable expertise in mass spectroscopy; Dr. Linoj Kumar for providing lignocellulosic substrates used in respiration experiments described in Section 3.3.1; Dr. Thomas Beatty for lending his vertical rotor for use in density gradient ultracentrifugation; Dr. Marie-Claude Fortin for effectively managing our project and ensuring my research received its budgeted funds; Gordon Stewart for being a dependable, well-organized and knowledgeable lab manager and Dr. Josh Neufeld for his valuable early work in SIP and for providing G. xylinus for producing bacterial cellulose. I would like to acknowledge the work of individuals whose passion for programming languages gave me the impetus to become a practitioner. I thank Dr. Rita McNamara, Dr. Keith Loese and Dr. Benjamin Purzycki, for facilitating an R group, Dr. David Williams-King for instruction on scripting, Dr. Haddock and Dr. Dunn for writing “Practical Computing for Biologists,” and Dr. Jenny Bryan for allowing me to audit her incredibly useful courses (STAT540 and STAT545). I would like to acknowledge the biologists, bioinformaticians and scientists around the world upon whose creative intelligence and hard work this research depends. In particular, the vision of public repositories and analytic tools such as those provided by NCBI, Argonne National Lab (MG-RAST), Schloss et al. (Mothur) and Joint Genome Institute (IMG-ER). This research was enabled by support from WestGrid (www.westgrid.ca) and Compute Canada Calcul Canada (www.computecanada.ca). In particular, the patient assistance of Dr. Doug Phillips, at the University of Calgary, in trouble-shooting the effective multi-threaded use of Ray-meta for metagenome assembly. Thanks to Dr. Guillaume Lamarche-Gagnon who translated my abstract into French under field conditions en route to Svalbard. Dedication I dedicate this work to my parents, Diane Bielicki and James Wilhelm, who gave so much and who cared deeply about me and about living an examined life. To my brother whose own curiousity and pluck enriched my life. To my family and the memory of my grandmothers, who patiently encouraged me as I focused on building a career in microbiology. To my companions over the past five years, including Jessie Saunders, Dr. Nikolaus Fortelny, Hilary Leung, Dr. Erick Cardenas, Dr. Yaseen Mottiar, Pauline Morand, Dr. Jackie Goordial, Patrick Conroy, Dr. Greg and Emma Gervalis, Dr. Tim Höllering, Camilo Cortes Aguirre, Dr. Thomas Hauch-Fenger, Cheryn Wong, Magdalena Grömer, Dr. Dan Brox, Dr. Stephen Hay, Mark Schutzbank and Tim Shaw, Dr. Alex Martin, Stacey Auld, Dr. Nagissa Mahmoudi, Christina Toms, Dr. Christina Turner, Dr. Ben Sylvester, Dr. Irwin Chang, Dr. Natalie Ceperely, Dr. Don Beith, Inti Dewey, Dr. Meike Singer, Eric and Linds Cole, Dr. Kim and Noel Ma-krakel, Greg Uchitel, Brandon Miliate, Ste. Anne’s Franchises everywhere, and Lucas at the Bike Kitchen et al. To Green College of UBC, where there exists a culture of learning and sharing that sets precedent for what the university experience should be. To Dr. Thomas Niederberger, Dr. Ofelia Rodriguez, Dr. Blaire Stevens, Dr. Nadia Mykytczuk and Dr. Lyle Whyte, who guided my earliest experiments in research. To those who endeavor to understand the complexity of soil microbial ecology and who will undertake research to answer questions posed here. And, to the revitalization and continuing legacy of forestry in B.C. and Canada of which future generations can be proud. To the journalists at the Canadian Broadcasting Corporation, in particular Anna-Maria Tremonti and Bob MacDonald, the Globe and Mail and the British Broadcasting Corporation and to other cultural icons who kept me engaged and entertained during my commute and long hours of lab work, in particular Gord Downie, Dr. Thomas King, Geoff Berner, and Rae Spoon. To Rita Laszlo, whose mutualism adds joy to my content. Chapter 1: Introduction 1.1 Above and Belowground Perspectives on Timber Harvesting, Soil Microbial Communities and the Long-term Sustainability of Forest Plantations 1.1.1 Current Context of the B.C. Forest Industry The forest industry remains a vital sector in British Columbia’s economy that sustains large manufacturers, thousands of small businesses and whole frontier towns. In 2011, wood products accounted for 22% of all goods sold in British Columbia (by volume) and a total of 5.5% of the GDP (B.C. Ministry of Forests, 2012). Canada-wide, the forest sector comprises 1.25% of Canada’s GDP (~$20 billion) also driven by industries in Ontario and Quebec. Yet, since the turn of the millennia, the B.C. forestry sector has seen job losses in the tens of thousands, the closure of mills and mass emigration from once thriving communities (B.C. Government and Service Employees Union Report, 2011). In 2012, the B.C. auditor general issued a report revealing large areas damaged by wildfire and mountain pine beetle had not been replanted and concluded that the future vitality of the industry lay in jeopardy (Office of the B.C. Auditor General, 2012). Both the Auditor General and public sector union stress the need to generate more value from forest products and commit to improved stewardship of the land. As stakeholders from business, government and local communities plan future development, there are still many unanswered questions about the basic nature of long-term forest management, such as how to maintain soil fertility under intensified land use. This research examines the belowground impacts of harvesting on microbial communities and processes related to forest ecology and soil fertility, providing a basis to develop principles of long-term stewardship (Chapter 3). At the same time, this research addresses the need to generate more value from forestry products, by surveying lignocellulolytic organisms in a search for industrially relevant biocatalysts (Chapter 4). 1.1.2 An Introduction to Forest Management and the Long-term Soil Productivity Study Logging rights in B.C. were first granted by the Crown in the 1800s, and logging practices were eventually regulated by B.C.’s first Forest Act in 1912 (Marchak, 1983). Despite periods of rapid growth of resource extraction, by the late 1990’s the amount of managed forested land in Canada and the United States had largely stabilized by reforestation and decades of improved forest management (Powers, 2006). Without the capacity to expand further, demands for shorter crop cycles, densified plantations and the harvesting of additional sources of woody biomass has increased (Fox, 2000; Allmer et al., 2009). Yet, the long-term sustainability of such land-use intensification is uncertain, since the consequences of harvesting (i.e. the removal of substantial amounts of organic nutrients) on soil fertility and forest regeneration remains poorly understood. Given the slow rate of forest regeneration, on average between 50-70 years (~ 25 years in more southern latitudes) before subsequent harvest, the science examining the effects of multiple crop cycles on forest soil fertility is a young science (Nambiar, 1996). Yet, there is a governmental mandate in both the U.S. (National Forest Management Act, 1976) and in Canada (Forestry Act, 1985 and Timber Regulations, 1993) to steward forested lands, though Canadian legislation does not explicitly provision for impacts on soil. Foreseeing the need to evaluate the long-term effects of biomass removal and other associated impacts of harvesting, such as compaction, the U.S. Forestry Service initiated the Long-term Soil Productivity Study in 1989, which was joined by Canadian counterparts soon after. The LTSP network includes over one hundred experimental sites across North America which have all implemented a similar experimental design assessing three intensities of organic matter removal and, in many cases, three intensities of soil compaction. The work detailed in this thesis was based on samples taken from LTSP sites in British Columbia, California, Ontario and Texas (Figure 1.1). Figure 1.1. Overview of six North American ecozones and LTSP sites where soil sampling occurred. Data on mean annual temperature and precipitation along with the Shannon diversity (H’) estimates for fungal and bacterial communities from data described in this thesis are provided. Each ecozone contained three sampling sites and, at each site, multiple experimental plots for each harvesting treatment as illustrated by the center panel providing an overview of the experimental design for Section 3.2. Note: the term ‘ecozone’ is not used in accordance with the classification system provided by Environment Canada (Ecological Stratification Working Group, 1996), but as a general descriptor of differences in local assemblages of organisms and in climatic factors. 1.1.3 Soil Ecology and Long-term Soil Productivity The long-term sustainment of any industry based on plant-based biomass, whether forest or agricultural, is contingent on prudent soil management. Nutrient depletion from biomass removal is one of many concerns for long-term soil fertility of forest plantations, others include: soil compaction, erosion, heating, drying, and changes in soil chemistry and prevailing microbial processes, including those related to carbon sequestration and greenhouse gases (Schoenholtz et al., 2000; Powers et al., 2005; Schulze et al., 2012; Merilä et al., 2014). Assessments of the ecological impact of timber harvesting and organic matter removal on soil communities near unanimously report impacts, while, in contrast, most studies on physicochemical properties of soil or forest productivity report neutral, variable and temporal responses (Figure 1.2; Table E.1). These findings suggest that forest regeneration may be broadly insensitive to variation in soil microbial communities, or that the community and concomitant biological processes are themselves variable or have forthcoming impacts. These suppositions remain largely untested due to historical overgeneralizations of microbial community structure and challenges overcoming the substantial diversity and variability of soil communities. Without sufficiently detailed knowledge of i) the prominent soil community members; ii) differences among forest soil communities; iii) the function of microbial processes in ecosystem maintenance and iv) how communities respond to long-term management practices, questions surrounding the impacts of harvesting on soil microbial processes remain in the realm of conjecture. To date, timber harvesting reportedly alters long-term ecological processes related to mycorrhizal symbioses and soil gas fluxes. Populations of type-II methanotrophs were found to decline in the decades following harvesting, resulting in the decreased uptake of methane by soils. Figure 1.2. A census of the conclusions from studies of the impact of timber harvesting on forest regeneration years and decades post-harvest. Studies were categorized by whether they were studying physicochemical properties of soil, the forest biomass (‘productivity’) or biological features of soil. Studies which showed variable responses among study sites were categorized with neutral findings due to typically small effect sizes even where effects were observed. Table E.1 contains information on every study consulted. The time until recovery to pre-harvest rates of methane consumption in pine plantations was estimated to be 47 years (Nazaries et al., 2011). Shifts in the composition of ectomycorrhizal fungi (EM), symbionts of Pinaceae, persist in the decades following harvest (Hartmann et al. 2009; Hartmann et al. 2012) and reportedly upwards of 50 years (McGuire et al. 2014). EM fungi dramatically improve host fitness, providing surplus water and scavenge inaccessible nutrients from mineral rock, such as phosphorus, copper, and iron, or nitrogen from organic matter (Cairney and Chambers, 1999). Shifts in EM populations have significant potential to impact forest regeneration, but the long-term impacts are not clear due to the poorly understood natural succession of EM fungi (Visser et al., 1995; Twieg et al., 2007). In a comprehensive meta-analysis of timber harvesting impacts on microbial communities, Holden et al., (2013a) concluded that harvesting broadly reduced microbial biomass and heterotrophic activity. These effects did not significantly differ between unharvested and partially logged forests, only in clear-cut sites. This raises questions about whether differences in timber harvesting strategies, such as the machinery used, degree of plant biomass removal and site-preparation for replanting, may mitigate changes in soil microbial community structure. The underlying cause of reduced heterotrophic activity and microbial biomass is not clearly understood, yet, recent studies have implicated the possible importance of organic matter removal. In a recent landmark LTSP-based study, the first to utilize high-throughput sequencing, the degree of organic matter removal had a greater impact than soil compaction, but both were less than differences in community composition among soil layers and geography in the ‘ecozones’ surveyed (Hartmann et al., 2012). The retention of some degree of organic matter onsite resulted in microbial communities that differed, albeit slightly, from both unharvested and intensely harvested sites. This was not altogether surprising, given that coarse woody debris selects for organisms with specialized capabilities, illustrated by the natural succession of decomposers as forest litter matures (Voriskova and Baldrian, 2013). In one instance, the retention of coarse woody debris following harvesting increased the diversity of wood-inhabiting fungi above that of unharvested sites (Brazee et al., 2014). Not only does the retention of woody debris shift the quality and quantity of organic matter input to soils, it mitigates other physical changes to the soil environment such changes in pH, aridity and temperature (Entry, 1986; Bååth et al., 1995). During the intervening years between harvesting and full canopy closure of reforested land, harvested soils experience substantial changes in physical conditions which include higher temperature and moisture extrema, diurnal fluctuation as well as higher average temperatures (Kranabetter et al., 1999; Kulmala et al., 2014) and lower average moisture availability throughout the soil column (Childs and Flint, 1987; Paz, 2001; Redding et al., 2003; Tan et al., 2005). Soil moisture can, however, increase over the short-term following harvesting (Adams et al., 1991) and occur only in near-surface layers (Fleming et al., 1997), reflecting the influence in the loss of transpiration from trees in deeper soils. Warmer, arid soil conditions are expected to be major factors influencing the composition of post-harvest communities, though there is a paucity of information about how soil communities respond to these changes. Long-term studies of regenerating forests destroyed by wildfire experience similar shifts in environmental conditions (described in Section 1.1.7). The retention of organic matter can affect these abiotic changes, mitigating increases in aridity and soil temperature (Paz, 2001) that, over the long-term, may influence microbial succession. Assessing the relative importance of organic matter retention as a nutritional substrate or in terms of moderating physical changes motivated this thesis research. The scope and scale of the effect of organic matter retention on soil microbial communities following harvesting may signal its value as a mitigation strategy against long-term disturbance. Questions about the impact of organic matter removal are of increasing importance as the production of biofuel, wood pellets and other materials incentivize the removal of more forest biomass, previously left onsite. Allmer et al., (2009) report that 38% of all fine woody debris is now being claimed for commercial use in Sweden, raising concerns about how to manage woody debris without depleting nutrient capital, altering soil processes or substantial habitat loss (Harmon, 2001). This thesis addresses such questions by contrasting long-term changes in microbial community structure at three intensities of biomass removal implemented in the LTSP Study experiment. 1.1.4 Harvesting Impacts on Lignocellulose-degrading Populations The decomposition of lignocellulosic biomass shapes soil structure, pH, carbon and nitrogen content and other properties which govern fertility. The composition and abundance of soil organic matter, particularly in the upper ‘organic’ horizon, affects the bioavailability of nutrients and energy flux through the heterotrophic food-web and also the sequestration of carbon (Merilä et al., 2010; Fontaine et al., 2011; Ge et al., 2013). The decomposition of lignocellulose is a rate-limiting step in the decomposition of plant biomass, in particular in coniferous forests, where carbon accumulates as soil detritus and humic compounds. Partially decomposed woody biomass accounts for an estimated 50% of all terrestrial carbon (Myneni et al., 2001), building a case for studying the conditions that govern the net storage of carbon in these environments, at the forefront of which are physiological and ecological traits of decomposers (Singh et al., 2010). Timber harvesting results in the loss of tree hosts and increase in belowground necrotic root tissue that generally shifts soil fungal communities from mycorrhiza-dominated to decomposition-dominated systems (Hartmann et al., 2012). Despite the shift towards saprobic populations, the consensus is that timber harvesting slows decomposition (Whitford et al., 1981; Yin et al., 1989; Prescott et al., 2000). Reduced microbial respiration has been observed upwards of 15 years after reforestation (Webster et al., 2016), suggesting that not only early-stage abiotic constraints, such as reduced water availability, but late-stage developments, likely relating to biological changes, affect the decline of heterotrophic activity. Long-term shifts in the composition of forest soil decomposers at harvested sites have been linked with a decreased potential to degrade complex carbohydrates like lignocellulose (Cardenas et al., 2015). Therefore, the decline in heterotrophic activity may be driven by both changes in quality of organic litter and the capacity of organisms that thrive in post-harvest conditions to decompose it. This is evidenced by the fact that not all populations of saprobes fare equally well following harvesting. Basidiomycota populations, such as brown and white-rot species, decline, while faster growing ascomycotal populations expand (Bader et al., 1995; Hartmann et al., 2012; Štursová et al., 2014; McGuire et al., 2014). Certain actinobacterial decomposers, such as Streptomycetaceae, decline in the face of an overall greater predominance of fungi (Hartmann et al., 2009; Hartmann et al., 2012; Lewandowski et al., 2015). Greater fluctuations in soil temperature and moisture, found at harvested soils, are also expected to select for hardier taxa such as those observed in arid environments, like yeasts and dark-septate fungi (Gallo et al., 2009) and bacterial phyla well-regarded for their tolerance to harsh conditions, such as Armatimonadetes, Firmicutes, Chloroflexi, Deinococcus-Thermus and Actinobacteria (Rastogi et al., 2009; Gabani et al., 2012; Soares et al., 2012). This thesis research is the first attempt to directly link the changes in the rate of decomposition, brought about from timber harvesting, with changes in cellulolytic community by means of stable isotope probing (SIP). SIP enables the concomitant measurement of the rate of cellulose decomposition along with in-depth, sequencing-based assessment of the cellulolytic community structure. This thesis examines whether long-term changes in temperature, aridity or decreased organic matter, brought about by timber harvesting, significantly alter cellulolytic community structure, diversity and activity (Section 3.3). One way in which these expectations may prove off the mark is that forest soil communities are adapted to disturbances and cope with changes in environmental conditions post-harvest and during maturation. The following sections describe the potential resiliency of forest soil communities and the potential similarity between the long-term impacts of timber harvesting and natural disturbances like wildfire. 1.1.5 Forests: A History of Disturbance A discussion of the impacts of timber harvesting would be incomplete without consideration of the role disturbance has played in the natural history of forest ecosystems. One of the central aims of forestry science is to design timber harvesting methods that emulate natural disturbance, based on evidence that many plant species, including many of the very trees we harvest, have evolved to punctuated large-scale disturbances (Bond and Keeley 2005). The earliest fossil preserve of a forest ecosystem is the Gilboa Fossil Forest in central New York State, dating to ~390 Mya (Stein et al., 2012). Softwood, conifer-like forests were the dominant forest type during the Mesozoic Era, surviving both Permian-Triassic and Cretaceous-Tertiary (K-T) extinctions (Thomas, 2014; Figure 1.3). Their prominence has been attributed to an ability to resist severe drought and colonize immature mineral-rich soils likely with the help of mycorrhizal fungi (Thomas, 2014). The evolutionary divergence of Pinaceae has been dated to ~150 Mya and the symbiotic partnership of Pinaceae with ectomycorrhizal fungi has been dated to ~130 Mya, suggesting the development of Pinaceae, and their hardiness, has been shaped by symbiosis (Berbee and Taylor, 1992; LePage et al., 1997; Wang et al., 2000). By the end of the Cretaceous period, hardwood species increasingly infringed on the territory of conifers owing to a warmer, moister global climate (Thomas, 2014). Figure 1.3. Natural history of major forest species relating to topics covered in this thesis. Molecular clock estimations for the original ancestral split for major lineages are shown with error estimates spanning the shaded area. The top plot presents the complete geological history of Earth. The bottom plot presents a more detailed account of the most recent 500 million years. All references appear in text. Of equal importance to the historical development of forests would be the natural history of soil, known as ‘paleopedology’ (Retallack 2008). The biosphere of ancient soils is not well understood, and is beyond the scope of this thesis. However, it is clear that early colonizers of mineral-rich terrestrial soils possessed extreme tolerances to radiation and desiccation as evidenced by the recent phylogenetic delineation of the major bacterial lineage: ‘Terrabacteria.’ The ancestors of Terrabacteria possessed extreme tolerances to desiccation, radiation and heat believed to have been necessary for the expansion and diversification of bacterial life on land approximately 3.5 – 2.6 Gya (Battistuzi et al., 2009). Members of this superphylum are, to this day, commonly abundant in soils, such as Actinobacteria, Armatimonadetes, Chloroflexi, Cyanobacteria, Firmicutes and Deinococcus-Thermus, and many taxa from these groups have the capacity to degrade cellulose and other plant polymers. It is, therefore, possible that endemic forest soil microorganisms have the capacity to adapt and endure a range of extremes and continue to fulfil functional roles important for ecosystem regeneration in the decades following harvesting. Mimicking natural disturbance has been a guiding principle of conventional forestry operations since the 1990s. These principles are founded on the observation that forested land are subject to continual disturbances and that numerous species that comprise forests have evolved to take advantage of these disturbances, such as pyrophilous or ruderal species. Management practices emulate disturbances through prescribed burns and ‘retention forestry,’ which aims to maintain biological refugia by retaining a greater number of living trees and plant detritus, such as coarse woody debris and snag trees (Gustafsson et al., 2012). Both burning and retention have been shown to mitigate a variety of harvesting impacts on macro-fauna, maintaining diversity and higher order trophic interactions, such as predator-prey relationships for beetle populations (Heikkala et al., 2016). How well these forestry principles extend to the belowground biosphere has not been studied, though the LTSP and others, such as the Ecosystem Management Emulating Natural Disturbance study (EMEND) are beginning to include belowground surveys in their data collection (Hannam et al., 2006; Hartmann et al., 2012). Overall, a better understanding of the similarities and differences of how soil communities are impacted by forestry and natural disturbance is needed before the full merits or shortfalls of such mimicry can be known. 1.1.6 Contrasting Timber Harvesting with Natural Disturbances For the most part, natural disturbances affect small areas of forest (<1 ha) producing a mosaic of forest with varying legacies resulting from the senescence of even-aged stands, physical damage by wind, localized fire or biological damage from pathogen or insect outbreaks. Minor disturbances are estimated to occur on an average cycle of 50 - 200 years at a given plot of land. In contrast, large-scale disturbances causing the destruction of forests on the order of ~10 to 100 ha occur on an average cycle of 800 to 10,000 years, typically resulting from wildfire, glaciation, hurricanes and insect or pathogen epidemics (Seymour et al., 2002). In comparison, the typical plot size of a managed forest plantation is between one and ten hectares and is harvested on a 50 to 70-year cycle. In terms of both frequency and scale, timber harvesting surpasses the magnitude of major natural disturbances in any one managed area of land, though not in terms of total land affected (see caveat below). A shortened interval between disturbances has the potential to create a long-term imbalance in the regeneration time for forest species in favour of ruderal, early colonizing taxa that thrive in the years immediately following disturbance (Roberts et al., 2016). For example, shorter intervals between prescribed burning of forested land increased the total effect size of changes in EM communities (Oliver et al., 2015). Shorter intervals between regeneration also increase the net time soil communities are exposed to warmer and drier ‘canopy-free’ conditions relative to natural disturbances. Further, under natural disturbance regimes, forests and forest soils would have hundreds of years to regenerate, making the accumulation of organic matter another major point of difference to timber harvesting regimes. These points of difference between managed and natural forest disturbances have the clear potential to broadly affect the long-term ecology of forest plantations and soil microbial processes. Conventional timber harvesting differs in other ways from large-scale natural disturbances that may have other long-term homogenizing effects on forest ecosystems. Soil compaction is unique to harvesting disturbance, resulting from the use of heavy machinery during harvesting, though it has been found to have a minor impact on soil communities (Hartmann et al., 2012). There are far reaching concerns that reforestation efforts have a homogenizing effect on genetic diversity, despite concerted efforts in breeding, on the genetic composition of mixed-aged stands (Friedman and Foster, 1997). Homogenization can lead to increased susceptibility to forms of disturbance (Fettig et al., 2014; Klapwijk et al., 2016) and will likely affect belowground organisms such as ectomycorrhizal fungi (EM), which demonstrate host-preference and even differences according to stand maturity (Visser, 1995; Twieg et al., 2007). Management strategies offers the possibility of mitigating undesirable changes in soil communities. Yet, the current lack of baseline and long-term monitoring data on the effects of repeated forest disturbance limit our understanding of the full extent of impacts. Studying similar canopy-removing disturbances, like wildfire, may augment the lack of long-term data. One caveat to aforementioned differences between harvesting and natural disturbances is that the total area of land affected by natural disturbance far surpasses the total land affected by the forest industry. In 2013 alone, Canadian forests were affected by insect and wildfire at a scale of 20 and 4.5 million hectares, respectively, dwarfing that of forestry activity (~0.75 million hectares) (Stats Canada Forest Inventory, 2013). However, natural disturbances do not match the frequency of disturbance at a given location under management. 1.1.7 Long-term Impacts of Forest Fire on Soil Communities Wildfire can remove a comparable amount of aboveground biomass to timber harvesting, but typically leaves subsurface soil organic matter intact. The complete loss of upper organic layer soils can occur in high-severity forest fires, though the occurrence is rare (Jurgensen et al., 1997). The initial combustion of both living and dead organic matter and extreme temperature alters subsurface communities and reduces microbial biomass and rates of decomposition (Dooley and Treseder, 2012; Holden et al., 2015). During forest renewal, soil inhabitants are exposed to a new baseline of environmental conditions which are analogous to those following harvesting, such as increased dryness, diurnal fluctuations and increase soil temperatures. Oliver et al., (2015) report that the diversity and richness of fungal communities had not declined eleven years on, but that the overall community structure had shifted towards heat-tolerant fungi, such pyrophilous taxa. Estimates for the return of microbial communities to pre-harvest or pre-fire composition are on the order of decades (Holden et al., 2013a; Holden et al., 2013b). Holden et al., (2013b) found the greatest differences in fungal composition between burned and unburned sites occurred in the first 10 to 20 years following fire, roughly the time till canopy closure, after which affected sites had begun to resemble unaffected sites. Oliver et al., (2015) found that disparate fire-affected soils shared similar compositional changes in fungi in the decade following disturbance, demonstrating a consistent selection pressure following disturbance. The decline of Basidiomycota at the expense of increased ascomycotal populations has been observed in decades following fire (Buscardo et al., 2015; Holden et al., 2013b), similar to what has been reported post-harvesting (Hartmann et al., 2012). An explanation for these differences is not clear, but both fire and harvesting can damage the fine hyphal networks of Basidiomycota, which typically have slower growth rates than Ascomycota (Strickland and Rousk, 2010; Holden et al., 2015). The fact that many Ascomycota are thermo-tolerant or that EM fungi (Basidiomycota) are sensitive to fire disturbance (Holden et al., 2013b) are also likely factors. Yet, some species of EM fungi are heat-tolerant and prosper in the years following fire, such as Rhizopogon, Suillus, Thelephoraceae, Tomentella and Wilcoxina among others (Buscardo et al., 2015; Glassman et al., 2015; Oliver et al., 2015). Arbuscular mycorrhiza (Glomeromycota) are resilient to fire disturbance, likely due to their dependence on understory vegetation which recovers rapidly post-fire (Xiang et al., 2015). Shifts in the bacterial community following fire are also pronounced and, similar to fungi, select for stress-tolerant taxa. Weber et al., (2014) studied bacterial communities at burned and unburned sites three-months after a fire and reported that ‘the presence of specific taxa may be more important in predicting community compositional shifts after exposure to high burn severity than overall community composition or physical and chemical parameters of unburned soils.’ They reported no significant differences in bulk soil community, suggesting disturbance did not turnover, but rather community structure was reorganized. The following taxa were identified as responding positively post-disturbance: Oxalobacteraceae (Oxalicibacterium, Naxibacter & Massilia), Bacteroidetes (Flavisolibacter, Pedobacter & Adhaeribacter), and Actinobacteria (Arthrobacter), while some taxa were more abundant in unburned forest soils: Verrucomicrobia (Spartobacteria & Opitutus), Acidobacteria (Granulicella and Groups 1,3 6, 7 and 16), Gemmatimonadetes, Planctomycetes (Zavarzinella), and Bacteroidetes (Mucilaginibacter). The report by Tas et al., (2014) on longer-term (7 years later) effects of fire on bacterial communities in tundra soil found similar responses at the phylum level, where Planctomycetes and Verrucomicrobia populations declined. However, the major group of bacteria that rose to prominence following fire were members of candidate phylum AD3, with virtually nothing known about these organisms. Bacterial diversity did not significantly differ between burned and unburned sites, following trends reported for fungi. From these studies, it is clear that a subset of organisms, likely stress-tolerators and ruderal species (Grime, 1977), are able to take advantage of the relatively harsher soil conditions in the period following disturbance, resulting in nuanced overall structural change without substantial effects on diversity. 1.1.8 Research Objectives for Assessment of Harvesting Impacts (Chapter 3) The research detailed in Chapter 3 seeks to improve understanding of the impacts of timber harvesting, and relative importance of organic matter retention, in shaping the long-term diversity and structure of microbial communities in general (Section 3.2), and specifically cellulolytic populations (Section 3.3). The LTSP framework afforded the opportunity to compare and contrast the effects of harvesting at three intensities of organic matter removal (‘OM removal’) among different biogeographic and climatic zones (‘ecozones’) in North America (Figure 1.1). Approximately 680 phylogenetic gene marker libraries for both 16S rRNA genes (bacteria) and ITS region (fungi) were made from a highly replicated experimental design which accounted for heterogeneity of soils within plots, and within ecozones. Multi-faceted sequencing and biochemical data were collected from microcosm experiments with 13C-cellulose to quantify changes in activity and identify corresponding composition changes in cellulolytic populations. Timber harvesting is expected to select for organisms adapted to changes in organic matter quality as well as the new post-harvest regime of warmer, drier soil conditions. The changes will likely feature a shift towards more generalist, stress-tolerant species, resulting in no net changes to microbial diversity. Cellulolytic members of Basidiomycota are expected to be negatively impacted, given reports of their decline post-harvest (Hartmann et al., 2012), while harsher conditions may favour bacterial degraders. Alternatively, cellulolytic fungi may predominate where coarse woody debris is retained, resulting from the selection of specialized wood-degrading fungi. While the impact of harvesting on the alpha-diversity of cellulolytic taxa has not been assessed, repeated prescribed burnings were shown to reduce the alpha-diversity of cellulolytic fungi (Bastias et al., 2009), suggesting that cellulolytic populations may possess fewer stress-tolerant taxa that succeed following disturbance. In accordance with the goals of the LTSP to ‘develop indices of soil quality practicable in monitoring’ (Powers, 2006), this research sought to document new phenomena of interest and identify specific taxonomic groups which may be relevant to monitoring efforts. The research was oriented to examine fine-scale differences occurring among all ecozones (‘globally’) and phenomena which are ecozone-specific (‘locally’) in order to contribute to a better understanding of whether variation in forest regeneration among LTSP sites may be attributed to differences in microbiota. A systematic assessment was made of the previous phenomena related to ectomycorrhizal, methanotroph and saprotroph populations, testing these observations across broadly different geographic zones, forests and soil types. These assessments, along with gauging the mitigating influence of varying amounts of organic matter retention, were made to help inform long-term forest management practices. Comparisons to the long-term effects of forest fire were included to relate features of anthropogenic and more natural forms of large-scale disturbance. Beyond the examination of harvesting impacts, there are few examples of comprehensive, molecular-based study comparing microbial communities from different coniferous forests at the scale and degree of replication as the research presented in Chapter 3. As such, this research also provides a general characterization of forest soil communities among different forest types and ecozones across North America. Similarly, in gauging the impacts of timber harvesting on the cellulolytic community using SIP, Chapter 3 attributes function to previously unknown and uncultured cellulolytic taxa. In this aspect, parts of Chapter 3 complement the aims of the research presented in Chapter 4. Section 3.3 provides the first part of a survey of cellulolytic taxa from organic and mineral soils and an assessment of the cellulose-degrading potential therein. Descriptions of Cellulolytic and Lignolytic Populations of Forest Soils: their Natural History and History of Industrial Use Chapter 4 focuses on a largely separate research topic than the effects of timber harvesting, though section 4.2.7 revisits the data collected for Chapter 3 and assesses harvesting impacts on taxa designated as putatively lignocellulolytic. 1.2.1 Valorization of Lignocellulosic Biomass The earliest studies on lignin and cellulose decomposition were carried out to understand threats posed to textile and wood-products by plant-degrading organisms. Commercial ethanol production from wood was attempted in 1898 by Simonsen using a non-biological method, and experiments with fermentative processes soon followed (Moore, 1914). As early as 1935, attempts were made to gasify lignin for energy (methane) and, at the same time, recover pure cellulose for ethanol fermentation (Levine et al., 1935). Following the outbreak of WWII, and subsequent wars like Vietnam, northern nations operated in tropical regions where the decay of plant fibre-based materials became a significant economic driver for research in both cellulose (Siu, 1951) and lignin-degrading (Gottlieb, 1951) organisms. The manufacture of vanillin was perhaps the earliest example of the successful valorization of lignin by Kürschner, who laid the foundations for commercial production of vanillin in 1928. In 1948, an editorial published in Scientific American stated the case for valorization of lignin waste, highlighting its potential as nature’s most abundant source of aromatic precursors (Gesinger, 1948). The steady growth in industrial processing of wood biomass since Gesinger’s time has prompted widespread attempts to valorize the correspondingly sizeable waste streams. In 2012, lignocellulosic biomass wastes were estimated at approximately 2 × 1011 t/year worldwide (Tuck et al., 2012). Cellulosic ethanol production is now a commercially viable enterprise exemplified by the Beta Renewables plant in Crescentino, Italy, generating 75 million L year–1. Given their structural role in plant tissues, is not surprising that both lignin and cellulose are being used to strengthen materials such as concrete (Ataie et al., 2014) and in the production of composite plastics (Chung et al., 2013; Kalia et al., 2011), foam (Li and Ragauskas, 2012) and carbon nanofibers (Dumanli et al., 2012; Li et al., 2015). Cellulose has the potential use in a wide variety of fermentative processes, however, as a fibre, cellulose has been functionalized for specific applications such as research in molecular biology (Araujo et al., 2012), medicine (Brinchini et al., 2013) and tissue culturing (Bodin et al., 2007). The number of applications of functionalized cellulose fibre are enormous given recent advancements in carbohydrate chemistry and widespread interest in carbohydrate-active enzymes (Xu et al., 2012). As nature's most abundant aromatic compound, lignin is a promising renewable source of aromatic precursors for a myriad of synthetic processes. It is expected to compete with a number of petrochemical products such as resins, lubricant and fuel additives, such as benzene, toluene, and xylene (Linger et al., 2014; Ragauskas et al., 2014). Recent applications include the anodic material for lithium ion batteries (Zhang et al., 2015) and air filters and respirators (Chang et al., 2016). The old adage that ‘you can make anything from lignin… but money’ is being tested under the current climate for renewable resources and a near 100-year history of research. 1.2.2 Origins of Research into Cellulolytic and Lignolytic Organisms and Enzymes The science of wood decay originated in 1833 with Hartig’s study of the fungal plant pathogen, Phellinus pini, commonly known as "red ring rot." It remained the domain of biology, mostly mycology, until the latter half of the 19th century when organic chemists began disassembling the chemical components of wood and analyzing the bi-products of wood rot. The structure of cellulose was first described by Payen in 1838, who also coined the name ‘cellulose,’ basing his observations on the remnants plant matter after treatment with strong acids. The first insight into the chemical composition of lignin was provided by Klason who described it, in 1896, as a coniferyl alcohol-based compound and later published a method for measuring lignin content that is commonly used today (Klason, 1910). The enzyme-mediated degradation of cellulose was first demonstrated by Sachs, in 1862, during his study of germinating grass seeds. The earliest studies to demonstrate the biologically-mediated degradation of lignin involved white-rot fungi (Bayliss, 1908; Zeller, 1916). Then, as now, the central challenge in characterizing catabolic capabilities hinged on how the cellulose or lignin was prepared, casting doubt, especially in the case of lignin, on the true nature of the microbial activity (early criticism by Gottlieb, 1951). By 1927, the activity of brown and white rot fungi had been delineated with a growing complement of knowledge on cellulase and phenol-oxidase enzymes (Falck, 1927). Yet, the definition of white-versus-brown rot has been eroded in the age of genomics, as canonical degradative capabilities have been found in the genomes of non-canonical members of each category (Riley et al., 2014; Floudas et al., 2015). This break from a near century old convention exemplifies the possibilities afforded by phylogenetics and comparative genomics to characterize how cellulolytic and lignolytic organisms, and the catabolic pathways they possess, have evolved. 1.2.3 Natural History of Lignocellulose Synthesis and Degradation The origins of cellulose and lignin biosynthesis predate terrestrial life, leaving no traces of its earliest development in today’s fossil record. The cellulose synthase genes common to plants are believed to originate from Cyanobacteria (photosynthetic bacteria), yet we find cellulose synthesis spread across a variety of bacterial phyla, including a number of Proteobacteria (Nobles et al., 2001). The closest common ancestor to land plants are marine Aerophyte green algae, which possess many features of the cellulose structure and overall carbohydrate complexity of modern forms of plant cell walls, though without any lignin (Mikkelsen et al., 2014; Domozych et al., 2012). The growth in lignin content in plant cell walls followed the colonization of land, which occurred around 470 million years ago and resulted in the diversification of plant cell wall architecture (consult Figure 1.3 for overview of natural history). The evolution of lignin biosynthesis began in early land plants with the shunting of phenylalanine pathway to synthesize hydroxylated aromatics for UV radiation protection (Weng and Chapple, 2010). This newly evolved form of phenylpropanoid synthesis led to the synthesis of lignin precursors, hydroxyphenyl and guaiacyl lignin. By the late Silurian period (416 Mya), vascular plants had evolved lignified tracheid tissue for conducting water and, by the end of the Middle Devonian (398 to 382 Mya), trees had evolved independently in several major groups, and an abundance of chemically stable, lignified plant matter began to accumulate (Robinson, 1990). The rate of accumulation reached a maximum during the Carboniferous and Permian, resulting in the formation of vast coal deposits derived primarily from lignin (Berner et al., 2003). Coal deposits from the Permian and Carboniferous period outweigh all other periods and were responsible for fueling the industrialization of modern civilization. Similarly, at the time of the Carboniferous, the accumulated mass of lignified plant matter was a rich resource to any organisms that developed the capability of exploiting it. The earliest ancestors of terrestrial decomposers of cellulose and aromatic polymers predate the colonization of land. The origin of terrestrial decomposers was believed to result from Earth’s changing climate, leading to shifting ocean water levels and the accumulation of ocean biomass on land. Our ability to reconstruct the ecology of this ancestral habitat is limited and, so too is our understanding of the early evolution of terrestrial decomposers (for a review see: Raven, 1997). Our understandings of the natural history of fungal lignocellulose decomposers has been aided by the recovery of fossils from filamentous fungi. The earliest Basidiomycetes have a fossil record that dates back to the Upper Devonian (382 – 372 Mya; Stubblefield and Taylor, 1986), which contain the class Agaricomycetes, widely considered the most successful degraders of lignocellulose. Both white and brown rot fungi are members of Agaricomycetes, whose earliest ancestor has been dated to the Permian period (298 - 252 Mya) from deposits in Antarctica and in tree trunks found in North America (Taylor and Osborn, 1996). The sharp decline in coal deposition by the end of the Permo-Carboniferous (~300 Mya) matches molecular clock estimates of when multiple gene duplications of catalase-peroxidases occurred in white-rot Agaricomycetes. These duplications are believed to underlie effective lignin decomposition, leading to the hypothesis that the early ancestors of white-rot fungi were the first to benefit from the growing surplus of lignified plant matter (Floudas et al., 2012). While prosperity may have been assured to any organism capable of modifying lignin, the catalase-peroxidases utilized by white-rot fungi evolved primarily to cope with oxidative stress (Benzie, 2000). During the late Carboniferous period, atmospheric oxygen concentrations reached the highest levels planet Earth had seen (~35%; Graham, 1995). Peroxidase activity became critical to detoxify oxidative compounds and the adaptation to utilize increasingly abundant lignin as reductant has bene hypothesized to be the indirect outcome (Morgenstern et al., 2008). Given that the coupling of catalase-peroxidase activity to lignin was a recent development, the peroxidase superfamily to which these catabolic enzymes belong (Class II) contains two other major classes of intracellular protective enzymes (Class I) and lignin biosynthetic enzymes (Class III), which likely predate the Class II catabolic homologs (Zámocký et al., 2015). As such, homology-based searches of lignin-degrading peroxidases requires careful phylogenetic discrimination between classes as well as supporting evidence through assays of lignin-modifying activity. White-rot fungi are highly successful lignin-degraders as a result of multiple gene duplications of Class II catalase-peroxidases, but also due to the physical ability of hyphae to penetrate through plant walls (Selosse and Tacon, 1998; James et al., 2006). Similarly, the majority of actinobacterial families exhibit mycelia-like growth, providing an example of convergent evolution believed to result from spatial complexity in the colonization of soils, though this physiology has not been directly correlated with growth on lignin (Ventura et al., 2007). Perhaps unsurprisingly, many of the best known bacterial lignocellulose decomposers are Actinobacteria. Streptomyces viridisporus T7A, was the first bacterium characterized to decompose lignin (Pasti, 1990). Notably, the split between Streptomycetaceae and other major actinobacterial families occurred at much the same period in time as the appearance of filamentous fungi, approximately 500 Mya (Embley and Stackebrandt, 1994). Substantial rates of lignin degradation have really only been observed by Basidiomycota, though a wide variety of fungi demonstrate less well-characterized degradation, like ‘soft rot’ or ‘brown rot’ (Worral et al., 1997; Riley et al., 2014; Floudas et al., 2015). The major focus of Chapter 4 is to expand the known diversity of lignin-degrading organisms; to assess the co-evolution of lignolytic with cellulolytic or hemicellulolytic traits, and to characterize the relative role of bacterial and fungal degraders. 1.2.4 Lignocellulose-degrading Niches What we know of the ecology and metabolic diversity of lignolytic and cellulolytic taxa is largely based on a number of model organisms studied in vitro. Collectively these organisms exhibit aerobic, facultative and anaerobic lifestyles for both cellulose and lignin decomposition and inhabit a broad range of environments such as marine, insect, ruminant, plant (pathogen), sediment, soil and compost (cellulose: Hanson et al., 2008; Scharf et al., 2008; Distel et al., 2002; Izquierdo et al., 2010; Hess et al., 2011; Dougherty et al., 2012 and lignin: Geib et al., 2008; Thevenot et al., 2010; DeAngelis et al., 2011). Co-culturing experiments demonstrate that decomposer communities exhibit high levels of syntrophic growth on lignocellulosic substrates (Leschine et al., 1995), and environmentally-derived cell slurries show higher rates of decomposition of lignocellulose sourced from co-endemic plants (Ayres et al., 2009; Prescott, 2010; Freschet et al., 2012). The critical role of lignolytic and cellulolytic organisms is supported by models of decomposition that show enzymes produced by small sub-populations drive overall decomposition in forest litter (Allison et al., 2012; Goldfarb et al., 2011). With modern tools in molecular biology, microbiologists can characterize the full variety of niches without the need for enrichment cultures, enabling a more accurate description of environment-specific taxa and catabolic mechanisms. For instance, a gut environment would select for organisms adapted to degrade physically altered, pre-digested substrates, whereas soil organisms likely possess a greater range of capabilities for gaining access (adhesion and penetration) to unaltered plant material, as well as a greater range of tolerances to environmental conditions and even interesting redox coupling. Ko et al., (2009) demonstrated lignin and cellulose co-metabolism coupled with sulfate reduction using inoculum sourced from landfill soil. Targeted characterization of specific niches and the consortia using molecular techniques, such as SIP, will drive future discoveries of novel lignocellulose-degrading consortia and catabolic machinery. 1.2.5 Lignin-degrading Fungi and Bacteria Wood-degrading fungi demonstrate a preference for the degradation of either cellulose, producing brown coloured wood rot, or lignin, producing a whitish colour of decaying wood. Both phenotypes share a common ancestor within the order Agaricomycetes. Specialization in lignin decomposition correlates with increased numbers of glycosyl hydrolase (GH) genes relative to non-specialized taxa and multiple gene duplications in GH and ‘auxiliary activity’ (AA), largely peroxidase, enzyme families (Floudas et al., 2012). Brown rot species modify lignin to access cellulose and have incurred substantial GH and AA gene loss, having only retained the capacity to abundantly express a reduced set of cellulose-degrading enzymes (Eastwood et al., 2011). Similar adaptive loss was reported in closely related ectomycorrhizal fungal genomes, demonstrating the phylogenomic basis for specialization and niche partitioning in the forest soil community (Martin and Selosse, 2008). However, mycorrhiza may partake in lignin and cellulose decomposition, albeit believed to be related to nitrogen and phosphorous scavenging (Baldrian et al., 2009; Rineau et al., 2012). Outside of well-studied Basidiomycota, some Ascomycota (Xylaria and Daldinia spp.) are also capable of lignin modification, generally known as soft-rot (Floudas et al., 2012). This capability depends on laccase-like activity and more closely resembles brown-rot (Liers et al., 2011). The study of lignin-degrading bacteria is a relatively young field of research, largely pioneered in the late 1970’s by Donald and Ronald Crawford. To date, the bacterial strains proposed to be capable of decomposing lignin polymers or lignin-related compounds occur in the following phyla (or sub-phyla): Actinomycetes, Bacteroidetes, Firmicutes, Alpha- Beta- and Gammaproteobacteria (see Table E.2 for a list of all known lignin and cellulose-degrading isolates). All of these organisms have been isolated and characterized in vitro through screening or enrichment culturing with polyaromatic compounds, kraft-lignin or lignin-related dimeric substrates. The most commonly cited organisms are Streptomyces viridisporus T7A (Pasti et al., 1990; Davis et al., 2013), Sphingobium sp. SYK-6 (Masai et al., 2007), Sphingobacterium sp. T2 (Taylor et al., 2012; Rashid et al., 2015), Enterobacter lignolyticus SCF1 (DeAngelis et al., 2011), Pseudomonas spp. (Zimmerman, 1990) and Amycolatopsis sp. 75iv2 (Brown et al., 2012). These taxa, and others, are described in detail in a number of reviews (Vicuna, 1988; Bugg et al., 2010; Zimmerman, 1990; Brown and Chang 2014; Tian et al., 2014). Consistent with the idea that lignocellulose degradation is performed by a specialized sub-set of microorganisms, many of the lignin-modifying genera also contain well-known cellulose-degraders, such as Streptomyces, Enterobacter, Sphingobacterium, Pseudomonas and Acinetobacter (Štursová et al., 2012; Pourramezan et al., 2012; Medie et al., 2012). The limited number of experimentally-verified, bacterially-produced lignin-modifying enzymes is insufficient to make generalizations about functional diversity. However, bacterial lignin-modifying mechanisms appear to be based on similar oxidative enzymes as fungi, such as peroxidase (DypAB) and laccase (bacterial laccase) enzymes. A unique set of glutathione-dependent enzymes that reductively cleave β-aryl bonds, termed the ‘Lig operon,’ was described by Masai et al., (1993). These bonds constituted the majority of inter-molecular bonds within lignin. Despite the culturing of bacteria with lignin-degrading capabilities, there have been few surveys describing their diversity within environmental lignin-degrading niches. There have been surveys of compost, deciduous forest (Pold et al., 2015) and tropical forest soil (DeAngelis et al., 2011; Woo et al., 2014) all originating from the same research group (see Section 1.2.7 for more details). The gut microbiome of wood-boring insects and termites (Harazono et al., 2003) have also been surveyed for lignin-degrading bacteria, implicating many familiar taxa (Streptomyces, Burkholderia and Pseudomonas) and some unique ones (Citrobacter, Escherichia, Paracoccus, Elusimicrobia and Yersinia). Studies of wood-ingesting mammalian gut microbiomes are underway for the beaver and moose (Dr. Keith Mewis and Dr. Kelly Wrighton, personal communication). Anaerobic lignin degradation has been reported in tropical forest soils, where lignolytic activity actually increased under fluctuating oxic conditions (Hall et al., 2015). The phenomenon reflected the relatively high catabolic rate of oligomeric forms of lignin under anaerobic conditions (coupled to iron reduction), combined with presumably necessary oxidative conditions to fuel oxidative catabolism of polymerized lignin (Hall et al., 2015). Anaerobic lignin degradation is supported by the recent description of Enterobacter lignolyticus, a facultative anaerobe capable of degrading model lignin compounds (DeAngelis et al., 2011). Lignin-degradation has also been observed in anaerobic or sub-oxic marine environments (Benner et al., 1984) based on the activity of Ascomycetes (Bucher et al., 2004), Streptomyces (Buraimoh et al., 2015), and Sagittula stellata (Gonzalez et al., 1997). Given the relatively new reconception of bacteria as contributors to lignin-degradation and the recent development of metagenomic-based research, environmental surveys of lignin-degrading bacteria are few and far between. One of the major goals of this research was to determine whether previously characterized bacterial lignin-degraders are active in situ in forest soils and expand our knowledge of their diversity. 1.2.6 Cellulose-degrading Fungi and Bacteria Few microorganisms possess the enzymes necessary to depolymerize cellulose and these are largely fungal and bacterial in origin, though invertebrates and higher eukaryotes possess some cellulase activity (Lo et al., 2003; Wilson et al., 2011). Bacteria that have evolved a specialization for growth on crystalline cellulose, present in plant cell walls (Figure 1.4), possess an overall greater number of CAZymes than their generalist counterparts (Berlemont and Martigny, 2013). They also possess a full complement of glycosyl hydrolase (GH) enzymes (endo- and exo- acting; Berlemont and Martigny, 2013) and often lytic polysaccharide monooxygenases (LPMO). These hardcore cellulose degraders are broadly distributed across 15 bacterial phyla, although closely related organisms (≤ 98% similar) do not necessarily, or even commonly, share the same capacity for cellulose degradation (Berlemont and Martigny, 2013). These characteristics suggest a significant role for horizontal gene transfer and convergent evolution in cellulose degradation, reflecting the diversity and abundance of cellulose-rich niches on Earth. Five phyla contain 89% of known bacterial cellulose-degraders (Actinobacteria, Firmicutes, Proteobacteria, CFB and Chlorobi), including model degraders like Cytophaga hutchinsonii and Clostridium cellulyticum. Decomposition of crystalline cellulose is relatively common across fungal saprophytes (i.e. non-parasitic fungi), which includes taxa from Basidiomycota, Ascomycota, Neocallismatigomycota (anaerobic fungi) and even the most ancestral lineage in fungi, Chytridiomycota (Gleason et al., 2011; Schneider et al., 2012; Štursová et al., 2012). A complete list of validated and predicted cellulose-degraders can be found in Table E.2. Unlike lignolytic populations, a number of environmental surveys of cellulolytic populations have been conducted in forests and in other environments. 1.2.7 Lignocellulolytic Bacteria and Fungi in Forest and Other Soil Environments Forest soils are generally more acidic than other commonly studied soil types and pH exerts a strong influence over microbial community composition (Lauber et al., 2008). The groups of cellulolytic taxa identified in agricultural soils were notably absent in the most comprehensive surveys of forest soil cellulose-degraders to date (Štursová et al., 2012; Eichorst and Kuske, 2012), such as Cellulomonas, Kitasatospora, Micrococcus and Streptomyces (Actinobacteria), Mesorhizobium and Sphingomonas (Alphaproteobacteria), and Firmicutes, such as Bacillus and Paenibacillus (El Zahar Haichar et al., 2007; Ulrich et al., 2008; Schellenberger et al., 2010). One shared characteristic between forest and agricultural soils in these studies was the predominance of Betaproteobacteria (Burkholderia) and CFB (Mucilaginibacter, Cytophaga, and Pedobacter). In contrast, Štursová et al. (2012) as well as Eichorst and Kuske (2012) identified cellulolytic populations of acidobacterial subdivision I, and cultured a representative cellulolytic isolate (Lladó et al., 2016), implicating members of this ubiquitous phylum as cellulolytic for the first time. The aforementioned surveys of forest soils also identified cellulolytic members of the following groups: Myxococcales, Asticcacaulis (Alphaproteobacteria), Cellvibrio (Gammaproteobacteria), Cohnella (Firmicutes), Armatimonadetes (formerly OP10) and Verrucomicrobia. The single forest soil sample considered in Wang et al., (2015) was dominated by Caulobacter, followed by Beta-, Delta- and Gammaproteobacteria and Bacteroidetes. Verastegui et al., (2014) found that Myxococcales were indicators of cellulose-decomposition in forest soils, while members of Caulobacterales (Phenylobacterium), and Actinomycetales were common cellulolytic taxa found in tundra, agricultural soil and forest. In fungi, members of Ascomycota predominate cellulose decomposition in soil. In proteomic data from forest litter, Agaricomycetes produced the fewest cellulases relative to ascomycotal groups, such Leotiomycetes, Eurotiomycetes and Sordariomycetes (Schneider et al., 2012). Agaricomycetes, and Basidiomycota in general, are more common wood-inhabiting organisms, though some cellulolytic yeast-like groups, such as Trichosporon and Cryptococcus, occur in soils (Štursová et al., 2012). In a survey of cellulolytic bacteria and fungi among five soil types, Eichorst and Kuske (2012) found cellulolytic chytrids and dinoflagellates along with ascomycotal groups, such as Arthrobotrys, Cladophialophora, Chaetomium, Dactylaria, Hypocrea and Trichocladium. Hemicellulolytic populations of forest soils were predominantly Burkholderia and Pseudomonas, with lesser populations of Duganella, Variovorax, Mucilaginibacter and Paenibacillus (Leung et al., 2016). A survey of lignin-degrading communities in temperate forest soil, using in situ enrichment and sequencing, identified putative activity in a number in vitro bacterial lignin degraders, such as Pseudomonas sp., Sphingobacterium sp., Rhodococcus sp., Sphingobium sp. and Ochrobactrum sp., as well as other taxa known to degrade lignocellulose, not previously implicated in lignin catabolism: Cytophaga sp., Paenibacillus sp. and Agrobacterium sp. (Pold et al., 2015). A similar study examining lignin-degrading bacteria in Puerto Rican rain forest soil identified lignolytic members of Alphaproteobacteria, Betaproteobacteria, Acidobacteria and Chloroflexi (DeAngelis et al., 2011). Surprisingly, in both environmental surveys by DeAngelis et al., canonical lignin-degraders from Streptomycetaceae were absent. These reports provide insight into the native, in situ communities actively decomposing lignocellulose in forest soils. Yet, of these studies, only Leung et al. (2016) and Eichorst and Kuske (2012) considered deeper mineral forest soil communities, the latter studying the ‘root zones.’ An oft overlook soil type, in favour of plant-matter rich upper layers, mineral soils represent a potential source for novel lignocellulolytic taxa and catabolism. It has been suggested that mineral soils may favour bacterial decomposers over fungal ones, given few wood-degrading fungi have been found in mineral soils (Hall et al., 2015) and all are aerobic, thus not well suited to deeper, anaerobic soils. Mineral soils were targeted in this thesis in order to capture a broader diversity of lignocellulolytic populations. 1.2.8 Symbioses of Lignocellulolytic Fungi and Bacterial General physiological differences exist between bacterial and fungal lignocellulose-degraders which impart advantages during different stages of decomposition and under varying conditions in forest soils. Fungi predominate in the upper organic and litter horizons, due to a greater capacity for dispersal, colonization and penetration of fresh plant matter; substantially higher metabolic rates, and more powerful oxidative enzymes (Moore-Kucera et al., 2008; Voriskova and Baldrian, 2013). In one proteomic study of forest litter, the main producers of extracellular hydrolytic enzymes were fungi with no bacterial hydrolases detected (Schneider et al., 2012). Bacteria tend to predominate in later stages of litter decomposition as they possess greater metabolic diversity; adaptation to low oxygen environments and resilience to broad environmental conditions (Berg et al., 2010). Yet, despite these predispositions, decomposition is a stochastic process performed by diverse populations of bacteria and fungi and a range of both antagonistic and mutualistic interactions have been reported (de Boer et al., 2005; Rousk et al., 2008). Fungal colonization of wood was shown to reduce bacterial abundance and diversity, but also consistently select for specific co-habiting bacteria, namely Burkholderia spp. and Xanthomonadas spp. (Folman et al., 2008). In a separate study, the rate of decomposition by mixed fungal and bacterial cultures demonstrated non-additive, synergistic effects (Romani et al., 2006). A variety of mechanisms for mutualism between wood-degrading fungi and bacteria have been proposed, but none well characterized, such as the syntrophic removal of metabolic by-products, detoxification, provision of nitrogen and the production of growth promoting compounds (Frey-Klett et al., 2007; Effmert et al., 2012; Martin et al., 2012). Conversely, the magnitude of antagonistic interactions in forest soil communities was exemplified in the reported five-fold greater abundance of antibiotic production and resistance genes in forest soils compared to more oligotrophic soils (Fierer et al., 2012). Antagonistic interactions include antibiotic production and resistance, cell-wall degradation (chitinase vs. peptidoglycanase), competition to sequester resources (ex. siderophore production), interference of growth strategies and the modification of quorum sensing molecules (Zhang and Dong, 2004). Tolonen et al., (2014) reported the co-metabolism of cellulose and fungal cell walls by Clostridium phytofermentans, where chitinases were actually produced in greater abundance than cellulases, revealing the co-evolution of competitive strategies for cellulose decomposition. In this thesis, the contributions and interactions between these two domains of life is considered and their relative cellulolytic and lignolytic activity described. 1.2.9 SIP in Characterizing Lignocellulose-degrading Communities Even as the culture-dependent constraints of early microbial ecology studies fade, high-throughput sequencing approaches are still challenged by the heterogeneity of soil and the rich diversity of microorganisms harboured therein. An indication of this is the poor metagenomic assembly from sequencing libraries derived from soil. In the case of one metagenomic study of forest soil, only 2% of reads could be assembled (Cardenas et al., 2015) in contrast to the near 30% assembly from a marine environment (Iverson et al., 2012). As a result, the diversity of lignocellulolytic groups has generally been underestimated and information on the ecological features of these communities is somewhat scarce. SIP offers the possibility of studying these populations by enriching for those organisms which assimilated carbon from a given substrate, thereby reducing the complexity of soil-derived sequencing data. However, even among studies which have successfully applied SIP to study cellulose decomposition, there are other pitfalls, such as the selection of substrate and the choice of incubation conditions, which makes SIP a hybrid between in vitro and in situ approaches. For example, there have been a number of recent SIP-cellulose studies (Bastias et al. 2009; Schellenberger et al. 2010; Štursová et al. 2012, Koranda et al. 2014; Torres et al., 2014) that made use of the commercially available 13C-cellulose manufactured by IsoLife which was found, here, to be unsuitably pure to target the exclusive activity of cellulolytic taxa (Section 2.2.3.1). The research described in this thesis represents a conservative SIP approach, which included the development of methods to optimize experimental conditions, to validate 13C-enrichment of DNA and assay the quality of substrate utilized. Recent ‘-omic’ and functional-based screening methods have provided a steady discovery of novel organisms and enzyme families possessing activity on lignin and cellulose (Bugg et al., 2010; DeAngelis et al., 2010; Hess et al., 2011; Levasseur et al., 2013). On one hand, these discoveries reflect our underestimation of the biochemical complexity required for decomposing lignocellulose and diversity of adaptations at the organismal level. On the other hand, many of the enzymes of interest catalyze a broad range of substrates and are involved in other cellular processes, exemplified by the various classes of catalase-peroxidases. One should expect that a major proportion of novel discoveries based on functional screening or other in vitro testing may be attributed to non-specific activity and may not translate into ecological significance, especially for those displaying low activity. SIP methods offer a unique solution to this problem by enabling functionally-oriented studies of microbial communities directly in an environmental and ecological context. SIP methods have a significant likelihood of novel discovery, having been successful in the targeted recovery of desired functional traits (Dumont et al., 2006; Pinnell et al., 2014) and the discovery of novel functional taxa (Buckley et al., 2007; Chen et al., 2008; Eichorst and Kuske, 2012). 1.2.10 Overview of Classes of Ligninase and Cellulase Enzymes The breakdown of lignocellulose is slow and energetically unfavourable because of chemical properties selected by plant evolution, such as the facilitation of transpiration (hydrophobic), the ability to withstand high pressures and support heavy structures like branches (rigid) and the ability to resist microbial attack (random, stable and racemic). The synthesis of lignocellulose requires over 1,000 genes (Somerville et al., 2004) and results in a complex, interwoven matrix of four major polymeric compounds: lignin, cellulose, hemicellulose and pectin. Of the four general components, lignin and cellulose are the most chemically inert and, due to the complexation of lignocellulose (Figure 1.4), impede overall decomposition (Ding et al., 2012). For example, the half-life of cellulose was estimated to be on the order of millions of years in the absence of biological activity (Wilson, 2011). The following sections summarize current knowledge about the enzymes and pathways utilized to breakdown cellulose and lignin. 1.2.11 Cellulases and Accessory Enzymes For many decades, the central paradigm for cellulose degradation revolved around the production of extracellular, ‘free’ (unbound) hydrolases that synergistically cleave within the crystalline inner stretches of polymer (endoglucanases) or at the termini (exoglucanase) producing oligosaccharides which are eventually cleaved into glucose by β-glucosidases. Many of the most prolific and best-characterized cellulolytic organisms employ this strategy (T. reesei and C. hutchinsonii). Exoglucanases are fast-acting, processive enzymes, unlike endoglucanases which adsorb and desorb at a much slower rate (Maurer et al., 2012). Exoglucanases also act in a unidirectional manner, either from the non-reducing (EC 3.2.1.91) or the reducing (EC 3.2.1.176) ends of cellulose polymers. Endoglucanases acting in a processive manner, though rare, have been reported (Wilson and Kostylev, 2012). Some cellulases exhibit both endo- and exocellulase activity, which is not too surprising given the differences between exo- and endo-activity can Figure 1.4. Representations of the structure of (A) lignin, crystalline cellulose and (B) their complexation with hemicellulose to form lignocellulose, the structural component of plant cell walls. The structural diagram for lignin was modified from Zakzeski et al. (2010) and the representation of lignocellulose was modified from Zeng et al. (2014). differ by slight structural changes near the active site (Oliviera et al., 2013). Exo- and endoglucanases from the GH family 6, which possess near identical structure and catalytic residues, differ in activity based on the presence or absence of a tunnel or loop conformation at the active site (Damude et al., 1996). Both endo- and exoglucanases show a rich diversity of structure and function that result from the paralogous expansions as well as convergent evolution (Lynd et al., 2002; Cantrel et al., 2012). This diversity is further multiplied by their modular associations with carbohydrate-binding modules (CBMs). The discovery of novel GH families has been aided by such modular associations, such as CBMs, conserved protein motifs (Busk and Lange, 2013) or signal peptides (Emanuelsson et al., 2007; Warnecke et al., 2007), that provide targets for homology searches. In 1983, Lamed et al., reported on a new paradigm in cellulose-degrading machinery, termed the ‘cellulosome,’ a self-assembling multi-enzyme scaffold capable of binding to lignocellulose substrates and catalyzing a number of catabolic reactions. The first cellulosome was characterized from the rumen-inhabiting anaerobe Clostridium thermocellum, and subsequently in other anaerobic bacteria and fungi (Bayer et al., 1994). The cellulosome revealed the degree of specialization possessed by decomposers and how evolution has addressed the complexity of heteropolymeric carbohydrate substrates. A cellulosome is constructed from a number of functional enzymes possessing ‘dockerin’ domains, which bind to ‘cohesin’ domains located on a large ‘scaffoldin’ protein, which is tethered to an anchor in the cellulolytic organism’s cell wall. These structural elements, namely cohesins, dockerins and scaffoldins, provide a target for metagenomics surveys of cellulosomes, termed “cellulosomics” (Bayer et al., 2008). Cellulosomes are significant to the metabolism of many ruminants and have recently been found in the human gut (Cann et al., 2016). In 2000, Shipman et al., described a multigene ‘starch utilization system’ (Sus operon), which was the first example of the ‘polysaccharide utilization loci’ (PUL) paradigm. A PUL refers to a syntactic gene cluster which encodes a set of proteins that bind a polysaccharide to the outer membrane, cleave it and transport oligosaccharides inwards. PULs were first described in Bacteroidetes, from which the best characterized examples originate. A number of PUL-like operons possess synergistic activity on both cellulose and a wide range of other polysaccharides, demonstrating the importance of the PUL-paradigm (Mackenzie et al., 2012; Koropatkin et al., 2012). The most current elaboration on cellulose-degrading machinery was the discovery, in 2013, of an unbound, extracellular enzyme that possessed multiple catalytic sites (both endo- and exo-glucanases) and multi-functional catalytic sites, acting on both xylose and cellulose (Brunecky et al., 2013). These proteins, produced by a thermophilic bacterium, exemplify a hybrid between the multi-functionality of a cellulosome and the classic ‘free’ extracellular cellulase. Hydrolysis may be the most common mechanism for the depolymerization of polysaccharides in nature and enzymes of this class, i.e. glycosyl hydrolases, comprise most of the best researched cellulolytic enzymes. Yet, there exists a growing number of non-hydrolytic enzyme classes which decompose polysaccharides or act synergistically to enhance breakdown. The discovery of lytic polysaccharide monooxygenases (LPMOs) represented a significant paradigm shift in understanding the decomposition of recalcitrant polymers like chitin and cellulose (Harris et al., 2010; Vaaje-Kolstad et al., 2010). LPMOs are believed to act synergistically to accelerate cellulose depolymerization, cleaving crystalline cellulose and providing hydrolytic enzymes access the substrate. LPMO redox reactions have been coupled to chlorophyll, yielding substantially elevated cellulose hydrolysis in an artificial thykaloid membrane containing LPMOs when exposed to light (Cannella et al., 2016). There are other non-hydrolytic cellulase-enhancing factors, such as expansins, which can disrupt or loosen crystalline cellulose and enhance substrate availability (Arantes and Saddler, 2010). Polysaccharide lyases are another class of non-hydrolytic enzymes, however they do not act on cellulose (Linhardt et al., 1986). Carbohydrate esterases also do not cleave cellulose, but perform reactions that accelerate decomposition, such feruloyl esterases which deacetylating cellulose (Biely, 2012; Kroon et al., 2000) and free carbohydrates bound to lignin (Blum et al., 2000; Benoit et al., 2006). The diversity of cellulolytic machinery results, in part, from the structural heterogeneity of plant polymers which requires highly adapted enzyme-substrate adsorption chemistry and diverse catalytic activity. To aid in unraveling this complexity, polysaccharide degrading enzymes are being organized into families by their primary sequences and folding topologies (Henrissat, 1991) and, subsequently, categorized and annotated in the publicly available ‘Carbohydrate-active Enzyme Database’ (CAZy db; Cantarel et al., 2009). This database is accompanied by ‘CAZypedia,’ which provides more detailed knowledge on the enzyme classes and families therein (http://www.cazypedia.org/). Most recently, the CAZy database released a tool for predicting PULs based on sequences from Bacteroidetes, which may prove useful in identifying PULs in the genomes of other species (http://www.cazy.org/PULDB/; Terrapon et al., 2015). The ‘dbCAN’ offers a complementary service for annotating CAZymes using hidden Markov models (www.csbl.bmb.uga.edu/dbCAN/; Yin et al., 2012). Despite spanning a full century of research, our understanding of the diversity of activity of cellulolytic enzymes continues steady growth. 1.2.12 Lignin-modifying and ‘Auxiliary Activity’ Enzymes The discovery that lignin decomposition is a fundamentally oxidative process is attributed to Bavendamm, who, in 1927, differentiated between white and brown-rot fungi based on colorimetric changes from the oxidation of phenolic compounds. Bose and Sarkar were the first to characterize the oxidative enzyme as a ‘laccase’ from white-rot fungi in 1937. Laccases were one of the earliest enzymes to ever be characterized (Bertrand, 1894), while peroxidases were described later (Reed, 1916). The work of Manskaya was the first to implicate free radical chemistry in lignin biosynthesis, by demonstrating the partial polymerization of coniferyl alcohol using a peroxidase (Manskaya, 1948). The evolution of lignolytic peroxidases was driven by the heterogeneous, hydrophobic and electrochemically stable structure of lignin, which resists direct enzymatic attack (Figure 1.4). To overcome steric resistance, class II catalase-peroxidases evolved surface exposed catalytic residues exemplified by lignin peroxidases (LiPs; Ruiz-Dueñas et al., 2009) or oxidized mediator compounds, like Mn2+ or veratryl alcohol, which could access and oxidize deeper structures within the lignin, exemplified by manganese peroxidases (MnP). Versatile peroxidases, as the name implies, are able to make use of both mechanisms (Camarero et al., 1999). Collectively, the class II catalase-peroxidases possess some of the strongest oxidation potentials of any characterized enzymes, which is not surprising given the need to oxidize lignin’s highly stable non-phenolic bonds. Both LiP (with a redox potential of +1500 mV) and horseradish peroxidase (+950 mV) can create phenoxy radicals, while laccases are reported to oxidize only phenolic bonds (< +800 mV) (Hayashi and Yamazaki 1979; Kersten et al., 1990; Li et al., 1999). Peroxidases and other lignin-modifying enzymes are categorized as ‘Auxiliary Activity’ enzymes in the CAZy database (Levasseur et al., 2013). However, ‘PeroxiBase’ offers the capability to more accurately compare and delineate catalase-peroxidase families (Fawal et al., 2013). A second class of peroxidases, known as ‘Dye-decolourizing peroxidases’ (DyP), show lignin-modifying activity, but belong to the peroxidase–chlorite dismutase superfamily (Zámocký et al., 2015). DyPs were first differentiated as novel peroxidases due to their ability to oxidize a range compounds which were poorly oxidized by other classes of peroxidase (Kim et al., 1995). As of January 2014, the DyP superfamily was comprised of mainly bacterial enzymes (~97%), with the remainder found in Eukaryotes and a handful present in Archaea (Colpa et al., 2014). DyP-like enzymes have been isolated and characterized in lignin-degrading bacteria (Ahmad et al., 2011; Brown et al., 2012; Davis et al., 2013). The best-characterized DyP enzymes, DypB and Dyp2, oxidize and decompose lignin and exhibit MnP-like activity by way of Mn2+ oxidation (Ahmad et al., 2010; Brown et al., 2012). The characterizations of DyP enzymes is relatively new and they have not been assigned an AA family in CAZy. However, a comprehensive phylogenetic analysis of DyPs was recently completed (Singh and Eltis, 2015), leading the way to better functional characterization and homology searches. Laccases exhibit the capacity to oxidize a remarkably diverse set of phenolic substrates. Their lignolytic activity, in the absence of peroxidases, has been demonstrated in both fungal (Ander and Eriksson, 1976) and bacterial systems (Majumdar et al., 2014). Laccases differ from peroxidases in their use of molecular oxygen to oxidize polyphenols (ex. tannins), but lack the oxidative power to readily cleave the predominantly non-phenolic bonds within lignin. Efficacious degradation of lignin has been demonstrated by coupling laccases with redox mediator compounds, similar to the activity of peroxidases (Munk et al., 2015). Lignin-degrading laccases are also challenging targets for bioinformatics analyses because their diverse functional roles in cell chemistry. Laccases are multicopper oxidases, which can be involved in intra- and extracellular developmental processes, morphogenesis, pigmentation and pathogenesis (Ausec et al., 2012). Their role is further complicated by their ability to act on a wide range of substrates and ambiguous coupling with redox mediators (Reiss et al., 2013). Identifying secreted laccases also does little to distinguish putative lignin-degrading activity, given that over 70% of all bacterial laccases contain signal peptides (Ausec et al., 2012). Laccases are deposited in the CAZy database under the AA family I, while HMMs for two- and three-domain laccases have been published (Ausec et al., 2012). The selection of bioinformatic approaches used to study ligninases and cellulases will differ according to what features are distinguishable at the sequence level. To date, lignin-degrading genes have not been found associated with other features which can, by proxy, suggest a functional role, unlike cellulases which can be identified by their association with PULs, cellulosomes, CBMs and in gene clusters (Bélaich et al., 1997; Morita et al., 2009; Dai et al., 2012). Identifying lignin-degrading genes is further complicated by the fact related genes are involved in a variety of core functions such as oxidative stress, detoxification and biosynthesis and, thus, conserved features of previously characterized lignolytic enzymes must be carefully delineated or enzyme activity validated. As a result, bioinformatics predictions of cellulolytic activity have shown promise (Hess et al., 2011), while most lignin-degrading enzymes have been discovered by functional assays. Bioinformatic approaches for identifying lignin-degrading genes have therefore gravitated to other ‘guilt-by-association’ methods, relying on organism-level traits which suggest adaptations to a lignin-degrading niche (Brown et al., 2012; Eastwood et al., 2011). One motivation for this thesis was to combine stable isotope probing with metagenomics provide an underlying functional basis for the bioinformatic identification of putative lignolytic enzymes. 1.2.13 Research Objectives in the Survey of Cellulolytic and Lignolytic Taxa from Forest Soils Across North America (Chapter 4) The major goal of research described in Chapter 4 was to survey the biodiversity of lignocellulolytic populations in forest soils from across North America. Decomposers of all three major components of lignocellulose, namely hemicellulose, cellulose and lignin, were surveyed, pioneering the use of SIP-lignin. Shotgun metagenomics enabled the recovery of draft genomes from lignin- and cellulose-degrading taxa, permitting the identification of catabolic genes and aromatic degradation pathways to validate putative function. Studies have already used SIP to survey cellulolytic communities, but have focused on a relatively small number of samples from a narrow range of sources given the cost and labour required for SIP experiments. Furthermore, a number of recent SIP-cellulose were compromised by the use of impure 13C-labeled maize cellulose (Bastias et al. 2009; Schellenberger et al. 2010; Štursová et al. 2012, Koranda et al. 2014, Torres et al., 2014). This research endeavoured to process a large number of samples in order to make broad, replicated comparisons among lignocellulolytic communities from a wide range of forest soils. The extent to which lignocellulolytic organisms have evolved the capacity to decompose all three major components of lignocellulose was assessed in Chapter 4. The presumption was that these traits would co-occur, given the example of certain wood-degrading fungi that can degrade all three substrates (Eastwood et al., 2011; Floudas et al., 2015). Thus, the identification of species (OTUs) which exhibit enrichment in 13C-libraries from all three substrates was attempted. SIP-hemicellulose data was included, but, as the data was not collected for this thesis and has been previously published (Leung et al., 2016), it was not the focus of Chapter 4. The characterization of active, in situ lignin-degrading bacteria would be a significantly novel contribution to our understanding of the process of decomposition. Comparisons of the activity of bacterial and fungal lignin-degraders was made. A SIP-lignin experiment with the addition of fungicide was used to confirm the degree of bacterial assimilation of carbon from lignin. The expectation is that fungi will predominate in the degradation of both lignin and cellulose, at least in organic layer soils. In addition to comparisons of taxa that degrade individual lignocellulosic polymers, the presented in this Chapter comprises a diversity of sample types from forests across North America and from upper organic and deeper mineral soil layers. The distribution and soil layer preference of lignocellulolytic taxa can inform our understanding of how differences in climate, soil-type and forest-type select for certain physiological traits. The relative abundances of putatively lignocellulolytic taxa in field samples (i.e. not microcosm based) was used as further evidence to support biogeographical trends and to relative abundance of lignocellulolytic populations relative to the community at large. Lignocellulolytic populations were expected to be a minority (Allison et al., 2012; Goldfarb et al., 2011), though recent research has suggested that one of the most abundant bacterial taxa in forest soils could potentially degrade lignin by-products (VanInsberghe et al., 2015). An assessment of whether putatively lignocellulolytic taxa were impacted by timber harvesting was made, given the overlap of samples used in Chapter 3, with the assumption that lignocellulolytic populations may be most abundant in OM1 where woody biomass was retained. Finally, a link between community composition and rate of decomposition was explored. In SIP-data, community or functional gene composition can be used to explain variation in the quantitative estimates of 13C-enrichment of DNA or PLFA. Chapter 4 investigated possible associations between the presence or absence of certain taxa and/or functional genes and higher or lower rates of lignolytic or cellulolytic activity. While informative, SIP microcosm- based estimations of activity may not reflect in situ rates, nor are culture-independent designation of lignocellulolytic activity without error. Thus, the strength of SIP evidence was weighed and caveats for the SIP method discussed. Chapter 2: Materials and Methods 2.1 Sample Collection from Long-term Soil Productivity Study Sites 2.1.1 Site Descriptions Soil samples were collected from reforested experimental plots within the Long-Term Soil Productivity (LTSP) Study from eighteen different sites spread across six prominent conifer-dominated North American ‘ecozones’ (Figure 1.1). The term ‘ecozone’ is a general descriptor that delineates differences in local assemblages of organisms and climatic factors. In this thesis, it is not used in accordance with the classification system provided by Environment Canada (Ecological Stratification Working Group, 1996). Ecozones were chosen to exemplify a broad range of climates and regions of North America where forestry is a major industry. Ecozones differed by a number of factors, including soil type, mean annual temperature and precipitation as well as predominant tree species reported in Table E.3. Ecozones also differed based on bulk soil chemistry, such as carbon and nitrogen content and pH (Figure 2.1). Each of the three sites within an ecozone contained triplicate plots for each of the four harvesting treatments: an unharvested reference plot, ‘REF,’ and three harvesting intensities resulting in varying degrees of organic matter removal: ‘OM1,’ where tree boles (stems) were debranched and woody debris left in situ; ‘OM2,’ where whole trees and branches were removed and, ‘OM3,’ where whole trees were removed and the upper organic layer of forest floor scraped away (Figure 2.2). Compaction was controlled at these sites and plots with minimum compaction were sampled. The age of forest varied from 11 to 17 years, with a majority over 15 years post-harvest. 2.1.2 Sample Collection Samples from all three sites within an ecozone were collected within, at most, three months of each other between March and September. Sampling occurred between 2008 and 2012, depending on the ecozone (Table E3). Each site in BSON and JPON had triplicate plots from which replicate samples were collected, while in the other four ecozones triplicate samples were collected from three separate transects in a single plot. In sampling, the litter layer was first removed and organic layer samples (~ 5 cm of the O-horizon) were collected with a trowel. Then, the top 20 cm of mineral soil (including the A and occasionally upper B-horizon) was collected using a Stoney auger (5 cm diameter). Sampling was performed to reflect consistent soil characteristics among treatments and sites. To account for heterogeneity at the plot level and ensure sufficient soil material, a single soil sample from a plot or transect was composited from between three to five sampling points. Samples were stored at 4°C during transport, sieved through 2-mm mesh and stored at -80°C until DNA was extracted within three months of sampling date. 2.2 Molecular Methods 2.2.1 Preparation of 16S rRNA gene and ITS region Pyrotag Libraries DNA was extracted from 0.5 g of soil using the FastDNA™ Spin Kit for Soil (MPBio, Santa Ana, CA) according to the manufacturer’s protocol. PCR amplification was performed on bacterial 16S rRNA gene (V1–V3) and fungal internal transcribed spacer region (ITS2) using barcoded primers according to methods described in Hartmann et al., (2012). PCR amplifications were performed in triplicate and pooled prior to purification and quantification. All DNA was quantified using Pico-Green fluorescent dye (ThermoFisher, MA, USA). Samples were sequenced using the Roche 454 Titanium platform (GS FLX+) at the McGill University and Genome Québec Innovation Centre, yielding on an average > 5,000 bacterial and fungal (200 bp) reads per sample. Read libraries were quality filtered and processed according to the Schloss “454 SOP” (accessed October 2013; Schloss et al., 2009). 16S rRNA gene libraries were clustered into operational taxonomic units (OTUs) at 1% dissimilarity to produce abundance matrices. Fungal sequences were clustered at 5.5% dissimilarity using CrunchClust according to Hartmann et al., (2012) due to the hypervariability of the ITS region. Taxonomic classification was performed using the RDP Classifier (Wang et al., 2007) with the Greengenes database for 16S rRNA genes (database gg_13_8_99; August 2013) and the Mothur-formatted release of UNITE for ITS (sh_mothur_release_08.12.2013; August 2013). All OTU counts were normalized to total counts per thousand reads. Figure 2.1. Bar plot of differences in total carbon, total nitrogen, soil moisture and pH among ecozones. Figure 2.2. Photographs capturing the initial set-up of the harvested Californian LTSP sites (A-C) and the appearance approximately 15 years after reforestation when sampling was conducted (D). Image A illustrates harvesting treatment ‘OM1’ as well as the efforts to minimize soil compaction. Image B and C illustrate harvesting treatment ‘OM2’ and ‘OM3’, respectively. [Photo credit: Matt Busse; mbusse@fs.fed.us] 2.2.2 Preparation of and Sequencing of Shotgun Metagenome Libraries All SIP-Cellulose metagenomic libraries were prepared from 40-50 ng of 13C-enriched DNA using the Nextera DNA Sample Preparation Kit (Illumina Inc., CA, USA), while all SIP-Lignin metagenomic libraries were prepared from 1 ng of 13C-enriched DNA using the Nextera XT DNA Sample Preparation Kit. The discrepancy was due to the difference in amount of 13C-enriched DNA recovered from each incubation. Preliminary tests comparing different library preparation methods from identical samples concluded that the 1 ng (Nextera XT) approach comparable to the 50ng (Nextera), if not better due to the ability to pool fewer fractions to achieve the library prep kit requirements (see Section 4.2.1). Four sample libraries were multiplexed per lane for all sequencing libraries and sequencing was performed on an Illumina HiSeq 2500 (2 x 100-bp). Samples were combined for multiplexing based on average fragment size not sample origin or soil type. Metagenomic data was collected in four major batches. The first batch of libraries were prepared for the SIP-cellulose investigation into treatment effects (Section 3.3.4) that included four libraries from 13C-DNA recovered from PPCA mineral soils corresponding to REF, OM1, OM3 and 12C-DNA from REF plots. Sufficient 13C-DNA was achieved by pooling all Californian sites, which was necessary due to the depletion of DNA stock from the creation of 16S rRNA gene and ITS pyrotag libraries. The second installment of libraries were prepared for the SIP biodiversity survey of cellulolytic taxa (Section 4.2) and included thirty-eight libraries from both organic and mineral soil for every REF plot for every site in all five ecozones: IDFBC, BSON, JPON, PPCA and LPTX, including one 12C-DNA control composited from comparable heavy factions of DNA from three sites from within each ecozone and for each layer (note: pyrotag libraries have fully paired controls, while metagenomic libraries have only one control per sample type). The third batch was for the SIP biodiversity survey of lignolytic taxa (Section 4.2) and included forty-six libraries from organic and mineral soil (composites OM1 and OM2 due to shortage of soil) for each site in Ontario (BSON & JPON), PPCA and LPTX. Fewer ecozones were covered due to limited availability of substrate and the intention of ensuring sufficient replication. Due to poor recovery of DNA and soil inhibitors, numerous additional library preparations failed and therefore all forty-six libraries represent unbalanced pairing of 13C- and 12C-samples (out of a total of 72 samples prepared). Each sample type is represented by at least one 12C-sample (for example: PPCA-organic layer or LPTX-mineral layer), with commonly more than one. The final batch of metagenomes were sequenced for the SIP-lignin antibiotics experiment (Section 2.2.5.1), where microcosms were incubated with or without fungi-specific antibiotics (Section 4.2.4), yielding a total of eight metagenomes corresponding to paired incubations of mineral soil (13C-lignin + antibiotic versus 13C-lignin w/o) for two sites in BSON (A7 & A8) and one each in PPCA (BR) and LPTX (TXA). 2.2.3 Stable Isotope Probing 2.2.3.1 Preparation and Properties of 13C-labeled Cellulose Bacterial cellulose was chosen as the substrate to target cellulolytic activity via SIP due to irremediable impurities in commercially available plant-derived 13C-cellulose from IsoLife (58% glucose + 4.4% lignin + unknown percentage of sugars from hemicellulose; Appendix D) which was initially tested and ultimately abandoned. Bacterial cellulose is more comparable to plant-derived cellulose than other preparations, such as Avicell, Sigmacell or filter paper, which are typically low molecular weight and less crystalline and, most importantly, are also not free of oligosaccharide contaminants. Plant cellulose is produced in the form of microfibrils which are fine, crystalline structures derived from the aggregation of 18 or 36 (still disputed) or more chains of β-(1,4)-D-glucose (Newman et al., 2013). The crystalline nature of cellulose is a key determinant of the rate of mineralization (amorphous regions decompose more rapidly) and type of enzymes required for hydrolysis, where specially evolved carbohydrate binding modules are necessary for effective hydrolysis of crystalline cellulose (Wilson, 2011). Bacterial cellulose is produced by homologous cellulose synthase proteins, but they are arranged in a linear array of single or multiple rows in contrast to plants which possess hexagonal conformations. As a result, bacterial cellulose microfibrils, termed “nanocellulose,” are around 100 times thinner than the average plant microfibril (~30 nm). Despite these clear differences, bacterial cellulose fares well in a comparison of traits correlated to enzymatic degradation: it has comparable polymer length (3000 – 9000 units) and crystallinity (80-90% crystalline) and demonstrates similar mechanical properties to plant cell walls (Chanliaud et al., 2002). Bacterial cellulose was produced by growing Gluconacetobacter xylinus str. KCCM 10100 with 13C-labeled glucose (99 atom % 13C, Cambridge Isotope Laboratories, MA, USA) in Yamanaka media under conditions outlined in Ruka et al., (2012). To ensure media was highly oxygenated, a requirement for the production of cellulose, cultures were grown in a 200 mL volume in a much larger 2 L Erlenmeyer flask with sponge tops tightly covered with aluminum foil to retard evapouration. Cellulose was purified according to Dunford (2011) but with longer boiling times (4 hrs) and three repetitions of boiling in 1% sodium hydroxide. Following purification and soaking the cellulose in a mildly acidic solution, contamination from DNA and protein was not detectable by spectrophotometry (A260 and A280). The carbohydrate composition of bacterial cellulose was assayed by HPLC after dissolving in strong sulfuring acid. The custom made bacterial cellulose was 100% glucose and nearly pure 13C% (only impurities would be from protein added to culture broth). 2.2.3.2 Preparation and Properties of 13C-labeled Lignin Plant lignin is synthesized by the coupling of free-radical phenylpropanoids after activation by plant peroxidases. Synthetic dehydrogentively polymerized (DHP) lignin emulates the plant mechanism using horseradish peroxidase to generate radicals of p-hydroxyphenyl, guaicyl and syringyl lignins. The DHP lignin which most resembles extracted “milled wood” lignin is prepared from coniferyl alcohol via the “zutropfen” method (Saake et al., 1996). DHP lignins typically have a lower molecular weight than plant lignin (~1600 – 9000 g · mol-1, or 8 - 50 units) and possess different frequencies of inter-linkages. DHP contains more β-5, β-β bonds and fewer β-O-4 bonds (Figure 1.4), which predominate in softwood lignin (~80%) (Brunow and Lundquist, 1980). DHP lignin is a reasonable surrogate for softwood lignin given the recent report demonstrating that native softwood lignin is oligomeric and minimally branched contrary to prevailing convention (Crestini et al., 2011). DHP lignin structurally resembles softwood lignin and has a long history of use as a model substrate for lignin-degrading activity. 13C-labeled DHP lignin was synthesized from ring-labeled coniferyl alcohol using horseradish peroxidase as described Kirk and Brunow (1988). Ring-labeled coniferyl alcohol was synthesized from 13C-ring labelled vanillin (Sigma Aldrich, CA) according to the procedure described in the Appendix. The resulting DHP lignin had a weight average molecular weight (Mw) of 2,624 g mol-1 which equates to polymer lengths of ~ 14 units. DHP lignin was washed once in distilled water to remove residual unpolymerized coniferyl alcohol and its purity verified by HPLC. The resulting labeled DHP lignin was 75% atom 13C. 2.2.3.3 Microcosm Preparation Microcosms were prepared by adding between 1-2 g dry wt organic or mineral soil to 30-mL serum vials, adjusting moisture content to 60% (mineral) and 125% (organic) (w/v). Moisture content was selected based on preliminary CO2 assays which identified maximal respiration rates for soil type (data not shown). Microcosms were pre-incubated for one week prior to the addition of substrate. Microcosms were amended with either 10% w/w of 13C- cellulose or 13C-lignin and paired with microcosms amended with identically prepared unlabeled, substrates (~1.1% atom 13C). These 12C-control microcosms were used to correct for natural, background 13C-carbon content in SIP-phospholipid fatty acid (PLFA) work and to control for background populations of organisms with naturally higher genomic GC content (i.e. heavier DNA) in SIP-DNA work. Microcosms were then incubated at 20° C for either 9 days (organic soils + cellulose), 14 days (mineral soils + cellulose) or 60 days (both soil layers + lignin). The incubation length was optimized by preliminary time-course experiments described in results Section 3.3.2. Due to poor enrichment of microbial biomass in organic soils from DHP-lignin, organic soils were mixed 1:3 with double-autoclaved mineral soil from corresponding samples in order to dilute preexisting organic matter. Following incubation, soil samples were lyophilized and stored at -80° C until processing. All SIP-PLFA, SIP-pyrotag and SIP-metagenomic data for a given sample and substrate were derived from the same set of microcosms. In contrast, ‘in situ’ sequencing data was derived from corresponding field samples that were not incubated. SIP-pyrotag libraries were taken from Leung et al., (2016) who incubated with 13C-hemicellulose in an identical fashion, except for a period of 48 hrs. 2.2.3.4 Analysis of SIP-Phospholipid Fatty Acids (PLFA) PLFAs were extracted from 0.75 g (organic) or 1.0 g (mineral) dry wt soil according to Bligh and Dyer (1959) and 13C-content was analyzed using ion ratio mass spectrometry (UBC Stable Isotope Facility) ported with gas chromatography as detailed in Churchland et al., (2013) with the following exceptions: (i) methyl undecanoate (c11:0) was used for the internal standard, and (ii) quantitation was based on an average of three serial dilutions of undecanoate, nonadecanoate (c19:0), and methyl cis-13-docosenoate (c22:1ω9). Peak identification was based on retention time compared against two reference standards: bacterial acid methyl-ester standard (47080-0; Sigma–Aldrich, St. Louis) and a 37-Component fatty acid methyl-ester mix (47885-U; Sigma–Aldrich, St. Louis). Unidentifiable enriched peaks, termed “unidentified fatty acids” (UFA), were included in analysis if they met the following conditions: i) detection in > 3 samples, ii) average δ 13C > +50 ‰ and iii) confirmed as long-chain alkane methyl esters by GC-MS using the identical instrumentation and method as in Leckie et al., (2004). Taxonomic affiliations of specific PLFAs were assigned according to Högberg et al., (2013), with c18:1ω9 and c18:3ω6 added as additional fungal PLFAs (Ruess and Chamberlain, 2010). All comparisons between taxonomic groups were performed using values normalized to total PLFA content. All SIP-PLFA raw data was processed identically in R using scripts that can be found at: https://github.com/roli-wilhelm. 2.2.3.5 Quantitation of 13C-enriched DNA Quantitation of the total mass and atom % 13C of DNA was measured with UHPLC-MS/MS. One nanogram of DNA was sufficient for quantitation, though typically 5 ng was used where possible to ensure a strong signal. DNA was diluted or concentrated to 5 µL and mixed with 95 µL of 88% formic acid in 250 µL PCR tubes and incubated at 70°C for 2 hrs to hydrolyze the DNA polymer. The acid solvent was completely evapourated using a Savant SpeedVac SC110A (Thermoscientific, U.S.) with a custom-made acid trap (a 500-mL air-tight container packed with soda lime) to prevent damage to equipment. The sample was suspended in 40 µL of UHPLC mobile phase (0.22 micron-filtered solution consisting of 98% solvent A, water with 0.1% v/v formic acid, plus 2% solvent B, methanol with 0.1% v/v formic acid) and run according to the details described in Wilhelm et al., (2014). Atom % 13C-carbon of DNA was calculated by summing the peak area for the various isotopic species of guanine and adenine. Both compounds contain five carbons, thus the incorporation of 13C produced incrementally heavier species, for adenine m/z 136.0/119.0 to m/z 141.0/124.0, and for guanine m/z 152.1/135.1 to m/z 157.1/140.1 (Figure 2.3). The mass of unlabeled and labeled DNA was proportioned according to the following summations of peak area: i) AllC12 + 5C121C13*0.077+ 3C122C13*0.0048; and ii) AllC13 + 1C125C13 + 2C124C13 + 3C123C13*0.9952 + 4C122C13*0.923. According to these formula, we observed average natural abundances of 5.9% (+/- 0.2% SE) from lambda DNA and 7.7% (+/- 0.2% SE) from DNA extracted from unlabeled soil samples. Given the natural abundance of 13C (1.11%), the theoretical amount of a six carbon compounds containing a single 13C isotope in a mixture is 5.9%. Figure 2.3. Examples of mass spectra for adenine and guanine for three samples: (a) unenriched DNA from a Gluconacetobacter sp. culture, (b) 13C-enriched DNA from Gluconacetobacter sp. grown on pure 13C-glucose, and (c) 13C-enriched DNA recovered from a high density fraction following the CsCl gradient ultracentrifugation of DNA extracted from soil fed 13C-cellulose. 2.2.3.6 Recovery of 13C-enriched Nucleic Acids 13C-enriched DNA was separated using cesium chloride density centrifugation according to the method outlined by Neufeld et al., (2007) with the following modifications: i) the amount of DNA applied to the column was standardized according to the degree of 13C-enrichment as determined by UHPLC, resulting in between 6 – 10 µg of DNA used per sample and ii) DNA was recovered from the cesium chloride solution (i.e. desalting) using Amicon Ultra-0.5 mL filters (EMD Millipore, MA, USA). Heavy fractions (1.727-1.735 g· mL-1; typically F1-F7) were pooled and concentrated in the 500 µL filter columns by centrifugation for 3 min at 14,000 rcf. Samples were then washed three times with 450 µL of PCR-grade water. The modification in DNA recovery (shortened processing time and reduced labour) was necessary for higher sample throughput and also resulted in 2-fold higher yields. During fractionation, a constant flow rate was maintained by pumping coloured water into the top of centrifuge tubes with a syringe pump (Model R-E; Razel Scientific, U.S.) and fractions were collected every 30 seconds, resulting in 20 fractions of approximately 250 µL. Density was measured using a refractometer and converted to g CsCl · mL-1 using the following formula: density = (refractive index)*10.927 - 13.593. DNA was suspended in 30 µL of pure water and quantified using Pico-Green fluorescent dye or UHPLC. The 12C-control DNA were treated identically, however typically insufficient DNA for PCR was recovered from heavy fractions, resulting in the need to pool additional fractions (~F1-F9). The successful recover of highly 13C-enriched DNA was verified by the previously described method for quantitation (Section 2.2.3.5). 2.2.3.7 Estimating Effects of GC Content on DNA Recovery from Heavy Fractions The efficacy of CsCl density gradient centrifugation at separating enriched DNA from high-GC bacteria was tested by artificially spiking in unlabeled genomic DNA from Nocardioides sp. (70% GC; IMG Taxon ID: 2519899648) in 13C-enriched soil DNA extract. Genomic DNA was spiked at 5, 10, 15 and 20% (v/v) of total DNA applied to the CsCl gradient. After purification, PCR amplification and sequencing of 16S rRNA libraries, the heavy fractions of DNA yielded fewer than 3% reads corresponding to the Nocardioides sp., though the number of reads that did match were roughly proportional to the amount of spiked DNA, 1.0%, 1.4%, 1.5% and 2.9%, respectively. Based on this data, we concluded that GC content would have marginal impact on recovering unlabeled DNA in heavier fractions. 2.2.4 Methodology Specific to Study of Treatment Effects 2.2.4.1 Soil Respiration Microcosms Organic and mineral layer soil samples from Californian LTSP treatments REF, OM1 and OM3 were incubated with or without one of three milled lignocellulosic substrates derived from Douglas-fir: (i) “lignocellulose,” from debarked, untreated Douglas-fir woodchips, (ii) “lignin + cellulose,” from steam treated woodchips, where hemicellulose was solubilized and removed and (iii) “cellulose,” from steam treated woodchips which were subsequently delignified (Kumar et al., 2012). Microcosms were prepared by adding 4.5 g dry wt soil to 30-mL serum vials, adjusting moisture content to 60% (mineral) and 125% (organic) (w/v) and pre-incubated for one week. Substrate was then added (0.45 g) along with CO2 traps, consisting of sterile glass vials containing 2 mL NaOH. Microcosms were incubated at 20 °C for an additional 14 days. Net respiration was determined by titration of the NaOH traps according to methods outlined by Haney et al. (2008). 2.2.5 Methodology Specific to Survey of Cellulolytic and Lignolytic Organisms The biodiversity survey described in Chapter 4 was completed subsequent to the research on the effects of timber harvesting. Having founds ITS (fungal) pyrotag libraries to be relatively uninformative in identifying differentially abundant taxa in 13C- vs. 12C-libraries (see Section 3.3.4), only 16S rRNA libraries were use in subsequent analyses. This decision was made to conserve 13C-enriched DNA, in particular for SIP-lignin experiments. Shotgun metagenomic data contained a much stronger signal for fungi and, therefore, was sufficient for the purposes of research. One caveat is that higher replication was achieved with pyrotag libraries and, while fungal reads were easily differentiated from bacterial reads by lowest common ancestor (LCA) analyses, the taxonomic resolution afforded by LCA was poor. SIP-lignin was performed on a subset of ecozones given the desire to conclude with significant replication any observation and the scarcity of 13C-enriched material. The synthesis of DHP-lignin was costly (~ $10,000 + labour) and yielded only ~ 800 mg of substrate. As a result, only LPTX, BSON and PPCA were selected for broadest coverage. 2.2.5.1 Fungicide Amended Microcosm Experiment To demonstrate the degree of bacterial involvement in the degradation of DHP-lignin, a select number of soils were incubated with anti-fungal compounds. Cycloheximide and fungizone (amphotericin B) were selected based on reports on the efficacy of anti-fungal soil amendments by Ingham et al., (1984). Mineral soil samples from two sites in BSON (A7 and A8) and one from both PPCA and LPTX were chosen based on their high levels of enrichment in prior SIP-lignin incubations. Soil microcosms were prepared as previously stated. Two parallel sets of microcosm were amended with 13C-DHP lignin with one set dosed with antibiotic cocktail on a weekly basis at 1 mg g-1 soil (cylcoheximide) and 1.2 mg · g-1 soil (fungizone). A 10 mg · mL-1 cylcoheximide solution was prepared in distilled, autoclaved water at pH 5.0 and a 30mg · mL-1 fungizone solution was prepared in DMSO. Both were stored at 4 °C and protected from light. Soil microcosms were dried out for 2 hrs in a flow-hood prior to the addition of antibiotics to prevent soils from becoming water-logged by the regular addition of moisture (140 µL per week). Samples were lyophilized, stored at -80 °C and analyzed for PLFA content and by shotgun metagenomic sequencing of 13C-enriched DNA. 2.3 Bioinformatic Analyses 2.3.1 General Statistical Approaches R (R Core Team, 2015; v. 3.1.0) was used for all statistical analyses with general reliance on the capabilities provided in the following packages: reshape2, ggplot2, plyr (Wickam, 2007; Wickam, 2009; Wickam, 2011), combinat (Chasalow, 2012), limma (Ritchie, 2015), Hmisc (Harrell and Dupont, 2015) and phyloseq (McMurdie and Holmes, 2014). Phyloseq proved highly useful in working with phylogenetic libraries as it kept OTU count matrices, taxonomic classifications and sample data as one easy-to-use object. Where necessary, P-values were adjusted according to the Benjamini & Hochberg (1995) false discovery rate (FDR) correction. All correlational testing was performed with ‘rcorr’ from the Hmisc package. The majority of graphs were made using ggplot2, saved as pdf and customized with vector graphics editing software. All raw data and R code used to process and analyze data was made available as Supplementary Data. 2.3.2 Phylogenetics, Taxonomic and Ecological Classifications Phylogenetic trees were prepared either by maximum likelihood (bootstrapping, n=500) with MEGA6 (Tamura et al., 2013) based on MUSCLE sequence alignment, trimmed to ensure complete alignment of all sequences (Chapter 3) or by parsimony in ARB (Westram et al., 2011), adding directly to the pre-aligned and curated SILVA tree (Pruesse et al., 2007; ‘SSURef_NR99_123_SILVA_12_07_15’). As previously mentioned, classification was performed using the RDP Classifier (Wang et al., 2007) using Greengenes for 16S rRNA genes (database gg_13_8_99; August 2013) and the Mothur-formatted release of UNITE for ITS (sh_mothur_release_08.12.2013; August 2013). Taxonomic classification of raw or assembled metagenomic data was based on lowest common ancestor analysis from MEGAN (Huson et al., 2007; v. 5.10.1) using the output from DIAMOND blastx (Buchfink et al., 2015; v. 0.7.9) against a local version of the ‘nr’ database from NCBI (downloaded October 2014). MEGAN classification was based on the consensus taxonomy of the top 10 valid hits to the ‘nr’ database. DIAMOND blastx searches were rapidly performed on the WestGrid system ‘Breezy.’ The designation of functional guilds of fungi was based on FUNGuild (Nguyen et al., 2015; v. 1.0). Radiation, desiccation, and heat-tolerance were assigned to a group if members were reportedly abundant in lithic or desert environments or if a cultured representative had been documented to have exceptional tolerance. The superphylum, ‘Terrabacteria,’ refers to the grouping of the following bacterial phyla: Actinobacteria, Armatimonadetes, Chloroflexi, Cyanobacteria, Deinococcus-Thermus, Firmicutes and Tenericutes. Ectomycorrhizal status was attributed to the following genera based on a broad literature review: Alpova, Amanita, Amphinema, Boletus, Cadophora, Cantharellus, Cenococcum, Chroogomphus, Clavulina, Cortinarius, Craterellus, Elaphomyces, Endogone, Entoloma, Genabea, Genea, Gilkeya, Gomphus, Hebeloma, Helvella, Hydnum, Hygrocybe, Hygrophorus, Hysterangium, Inocybe, Laccaria, Lactarius, Leccinum, Lycoperdon, Lyophyllum, Melanogaster, Otidea, Paxillus, Phlebopus, Phylloporus, Piloderma, Pisolithus, Pseudotomentella, Pulvinula, Ramaria, Rhizopogon, Russula, Schizophyllum, Scleroderma, Sebacina, Sistotrema, Suillus, Thelephora, Tomentella, Tomentellopsis, Tricholoma, Truncocolumella, Tuber, Tylospora, Wilcoxina and Xerocomus. 2.3.3 Diversity, Rarefaction, Ordination and perMANOVA Chao1 richness and Shannon diversity estimates were calculated on rarefied data using the ‘plot_richness’ function (phyloseq). Reported estimates represent the average of 500 random samplings. Simpson’s measure of evenness was calculated using ‘evenness’ (RAM; Chen et al., 2016) and was also calculated from the average of 100 rarefied random samples. Rarefaction curves were calculated using ‘rarecurve’ and permutational analysis of variance (perMANOVA) using ‘adonis’, both from the ‘vegan’ R-package (Oksanen et al., 2015). Non-parametric multi-dimensional scaling ordination was performed on Bray-Curtis dissimilarity matrices using ‘ordinate’ (phyloseq). 2.3.4 Indicator Species Analysis Indicator species analysis was performed using the R-package ‘indicspecies’ (De Cáceres and Legendre 2009). Two types of data were analyzed: OTU count data and count data binned by taxonomic classification. In the latter case, analysis was repeated at each taxonomic rank. In addition to running analysis on aggregated data, analysis was also performed on subsetted data according to individual ecozone and ecozone x soil layer. Results were compiled and de-replicated and can be found in the Supplementary Data. 2.3.5 Identifying Cellulolytic and Lignolytic Taxa Due to the nature of incomplete separation of 13C-enriched from unenriched DNA, particularly DNA with high GC content, a number of statistical methods were applied to identify OTUs and taxa differentially abundant between 13C- and 12C-libraries in both pyrotag and shotgun libraries. Two primary methods were used to identify differentially abundant OTUs or taxonomic bins: “DESeq” (Anders and Huber 2010) and indicator species (‘indicspecies), though two additional methods were used in characterizing SIP-cellulolytic communities in Chapter 3: “limma-voom” (Ritchie et al., 2015) and a custom script for calculating relative abundance. DESeq and limma-voom were used due to their statistical correction for the high variance among low abundance OTUs. Overall, for an OTU or taxa to be deemed 13C-enriched (enrOTU), and assigned a putative activity, it had to be on average 3-fold more abundant in 13C libraries according to at least one method and in at least one ecozone. Due to insufficient replication of shotgun metagenomes, differential abundance in them was based only on indicator species analysis and on average relative abundances and, where possible, supported by pyrotag library data. The influence of community composition on the total amount of 13C-enrichment in PLFAs was assessed using permutation-based regression tree analysis in the R package ‘Boruta’ (Kursa et al., 2010). 2.3.6 Metagenome Assembly and Draft Genome Recovery Shotgun metagenome libraries were preprocessed using Trimmomatic (Bolger et al., 2014; v. 0.32), to trim sequencing primers and low quality ends, and FastX Toolkit (Gordon and Hannon, 2010; v. 0.7), to quality filter short or low quality read. Paired end and orphaned reads were included in metagenome assembly using the default setting of software ‘Ray-meta’ on WestGrid’s high-memory node ‘Breezy’ (Boisvert et al., 2012). In order to recover draft genome, super assemblies were constructed by compositing shotgun metagenomic libraries from the same ecozone and soil layer and assembling with the low-memory assembler MEGAHIT (Li et al., 2015; v. 1.0.2). Two strategies were used to populate draft genome bins: i) Metawatt (Strous et al., 2012; v. 2.1), was used to bin scaffolds derived from the super assembly based on tetranucleotide frequency; and ii) MetaBAT (Kang et al., 2014; v. 0.18.6). MetaBAT required that reads from each of the composited libraries be mapped back to the super assembly and indexed using Bowtie2 (Langmead and Salzberg, 2012). Indexed files were subsequently fed into MetaBAT which binned based on both tetranucleotide frequency and covariance of read abundance among composite libraries. MetaBAT was the more successful of the two binning methods and was used exclusively for the binning described in Chapter 4. The quality of draft genome bins was assessed by scanning for essential single-copy, house-keeping genes with the hidden Markov model provided by Albertsen et al., (2013) and using CheckM (Parks et al., 2015). The efficacy of recovering draft genomes was compared between compositing with or without corresponding 12C libraries. Inclusion resulted in the recovery of the greatest number of draft genomes, likely due to the increase in sample number and increase variation in read abundances between 12C- and 13C libraries. Read mapping with Bowtie2 was also used to calculate the relative abundance of these draft bins across harvesting treatments in Chapter 3. 2.3.7 Characterization of Carbohydrate-Active Enzyme (CAZy) Content The complete CAZy database (Cantarel et al., 2008; www.cazy.org) was downloaded and formatted into a DIAMOND blastx searchable database (accessed 2014-05-06, for Chapter 3, and again on 2015-08-19 for Chapter 4). The database was downloaded with a script implemented in Metapathways 2.5 (Konwar et al., 2015) which is publicly available at https://github.com/nielshanson/CAZy_utils. Metagenomic reads were annotated by CAZy family based on the top hit of blastx searches with minimum e-value of 10-5, as described in Cardenas et al., (2015). The following glycosyl hydrolase (GH) families contain enzymes with endoglucanase activity: GH5, 6, 7, 8, 9, 12, 26, 44, 45, 48, 51, 61, 74, 81 and 131 (Yagüe et al., 1990; Hasper et al., 2002; Petersen et al., 2009; Harris et al., 2010; Vlasenko et al., 2010; Warner et al., 2011; Lafond et al., 2012; Boyce et al., 2015; Brumm et al., 2015). A custom python script was used to identification of clusters of CAZymes which first identified putative CAZyme sequences by a) blasting against the CAZy database, b) using ‘hmmscan’ (HMMER v. 3.1b1; Eddy, 2011) using hidden Markov models for CAZymes provided by dbCAN (Yin et al., 2012) and custom hidden Markov models for aryl and vanillyl alcohol oxidases, laccases, dye decolorizing peroxidases (Dyp2), and versatile peroxidases (Erick Cardenas, unpublished). The script then identifies groups of three or more CAZymes on assembled scaffolds and recovered these sequences. This script implemented gene-predicting software Prodigal (Hyatt et al., 2010; v. 2.6.2). Chapter 3: Long-term Impacts of Timber Harvesting on Soil Communities 3.1 Rationale To date, studies of harvesting impacts on soil communities report that edaphic and geographic differences among samples can obscure the effects of disturbance. Heterogeneity accorded to those factors accounted for between 4 and 14-fold more variation in community structure than harvesting (Hartmann et al., 2012; Cardenas et al., 2015; Leung et al., 2016). Yet, the majority of studies on harvesting disturbance report persistent, long-term shifts in microbial community composition resulting from timber harvesting, upwards of 50 years post-harvest (McGuire et al., 2014). While the list of potential impacts is relatively long, and likely to grow in coming years (see Section 1.1.3), there has yet to be an assessment of how robust and generalized these trends are across different geographic zones, forests and soil types. Further, in the face of growing incentive to harvest woody debris previously left onsite, the effect of organic matter removal on soil community structure needs to be assessed. This research provides a comprehensive study of the differences in bacterial and fungal communities from soils at reforested sites across North America where varying amounts of organic matter have been removed (or retained). This research used the highly replicated LTSP experimental design and both field samples (‘in situ’) and SIP-cellulose microcosms to assess impacts on community structure and function. Multiple datatypes were considered, including shotgun metagenomic and phylogenetic gene marker libraries (16S rRNA gene and ITS), respiration assays, and quantitative PLFA analysis. In accordance with the goals of the LTSP Study to ‘develop indices of soil quality practicable in monitoring’ (Powers, 2006), specific taxonomic groups were identified which may be relevant to monitoring efforts. 3.2 Community Responses to Timber Harvesting All raw sequencing data described in Section 3.2 can be retrieved from the European Nucleotide Archive under the study accession PRJEB12501 (all ITS + B.C. 16S rRNA gene libraries) and PRJEB8599 (majority of 16S rRNA gene libraries). All additional data, including sample metadata and representative FASTA sequences for indicator taxa can be found in the Supplementary Data. Figure 1.1 describes the overall experimental design and datasets utilized in Section 3.2. A total of 685 bacterial 16S rRNA gene and 696 fungal ITS region samples were analyzed (average library size = ~ 5,000 reads). A complete breakdown of sample totals according to ecozone, soil layer and treatment can be found in Table E.4. Additional samples were processed from LPTX and JPON ecozones due to the inclusion of plots that had been exposed to herbicide at the time of replanting. No differences in community composition were attributed to herbicide application (data not shown) and samples were included in analysis without special treatment. The following samples were removed due to insufficient sequencing depth (< 1,000 reads): TXA035 (ITS libraries) & JS061 (16S rRNA libraries). 3.2.1 Overview of Community Composition Across Ecozones The majority of variation in both bacterial and fungal community structure was attributable to biogeography and soil layer, while a minor, though significant (p < 0.01), portion was due to degree of OM removal (Figure 3.1). Of the total variation explained by experimental factors (i.e. excluding residual variation), ecozone accounted for 64% and 67% of variation, bacterial and fungal, respectively, followed by site (15 and 21%), soil layer (18 and 7%) and OM removal (3 and 5%). Despite the large variation in community between ecozones, the most abundant bacterial OTUs among all ecozones were cosmopolitan genera abundant at every site and in both soil layers. The core OTUs shared among all ecozones (~15% of total OTUs) accounted for 72% of all bacterial reads while a similar, but less pronounced, trend was observed for fungi, 5.5% and 37%, respectively (Figure 3.2). Variation in both fungal and bacterial communities among ecozones was driven by differences in composition of middle and lesser abundant taxa. Alpha-diversity significantly differed between ecozones (Figure 1.1), though community composition was more similar between proximal ecozones. The sampling depth obtained (~ 10 K per sampling site) did not exhaust either bacterial or fungal species richness according to rarefaction curves (Figure 3.3). While diversity was substantial, the rarity of certain taxa may be attributed to the fact sequencing libraries represent relative abundances. As such, cosmopolitan taxa occupy a large proportion of reads, causing other taxa to be overshadowed and creating the appearance of a long tail of relatively ‘rare’ taxa. Figure 3.1. Bar plots of the percent variance (R2) explained by each experimental variable based on perMANOVA (nperm=1000) using Bray-Curtis dissimilarities for either 16S rRNA gene (bacteria) or ITS gene (fungal) libraries. Only statistically significant (p < 0.01) factors were included. Panel A shows the variability in each library type according to soil layer, while panel B shows variability within each ecozone with both layers combined. Consult Figure 1.1 for ecozone codes. Figure 3.2. Venn diagrams displaying the number of overlapping OTUs overlap among ecozones and harvesting treatments for bacterial and fungal pyrotag libraries. The total number of OTUs is given followed by the percent abundance of all OTUs in brackets. Figure 3.3. Rarefaction curves showing the depth of sampling obtained at each site also grouped by Ecozone (colour). Cosmopolitan bacterial groups included Rhodoplanes (on average 5-7% of total proportion of library reads), Mycobacterium (0.4-4%), Burkholderia (0.5-3%), Reyranella (0.4-2%), and candidate acidobacterial genera: Koribacter (0.2-1.5%) and Solibacter (0.2-1%). Members of Bradyrhizobiaceae were by far the most abundant taxa in both soil layers, with the greatest abundance in western ecozones: IDFBC and SBSBC (~25% of all reads) and PPCA (~13%), and to a lesser extent in JPON, BSON and LPTX (~8%). Cosmopolitan fungal families included Atheliaceae (3 – 24%), Russulaceae (3.5 – 18%) and Suillaceae (3 – 9%) occurring at high abundances in most ecozones, while PPCA was dominated by Trichocomaceae (8-14%) and LPTX by Mortierellaceae (~15%). Broad differences between soil layers were observed in bacterial communities at higher taxonomic ranks with Alphaproteobacteria, Gammaproteobacteria, Bacteroidetes and Actinobacteria all more abundant in organic soil, while candidate phylum AD3, Chloroflexi, Betaproteobacteria, Deltaproteobacteria, Firmicutes and Acidobacteria more abundant in mineral soils. No significant differences between soil layers occurred for fungi at rank phylum, which was consistent with the lesser degree of variation explained in perMANOVA testing (Figure 3.1). 3.2.2 Harvesting Impacts on the Soil Properties The harvesting gradient achieved by the removal of between 40-70% of aboveground biomass in OM1, 70-90% in OM2 and nearly 100% in OM3 treatment plots (Powers et al., 2006), resulted in a clear gradation of soil organic matter at the time of sampling. Total carbon and nitrogen content per gram of soil was diminished according to the gradient in the organic layer of soil of all ecozones, but not in the mineral layer (Figure 3.4; full details in Table E.5). At time of sampling, organic layer soil development reflected the OM removal gradient with the average depth of organic soils in the BSON sites: 0.4 cm (OM3), 3.2 cm (OM2), 4.0 cm (OM1) and 4.8 (REF). Accurate data from other sites was missing, yet a similar depth gradient likely existed, exemplified by the lack of an organic layer in OM3 sites in JPON and both B.C. ecozones. Soil pH was slightly increased in harvested plots in northern ecozones, but remained similar to unharvested plots or decreased in southern ecozones (Table E.5). Mean daily soil temperature was significantly higher in harvested plots and increased with OM removal (Figure 3.5). Five years post-harvest at PPCA sites, soil temperatures were consistently warmer in OM1 (+1.5 °C) and OM3 (+6 °C) than unharvested plots (Figure 3.5B). At Ontario sites, where long-term soil temperature data was available, there were marked differences between OM2 and OM3 (Figure 3.5 A and C). After 5 years, OM3 soils were ~ 4 °C warmer during summer months than OM2 soils at 5 cm belowground. This difference was no longer observed ten to thirteen years after harvesting in BSON, and had diminished to ~ 2 °C in JPON. The diminishing differences in soil temperature over time illustrate the influence of ground cover and canopy development on soil conditions (Figure 3.5A). During summertime, the variation in temperature was on average ~ 60% greater in OM3 than in OM2 (t =-3.8; p<0.001), which, for example, amounted to differences in temperature extrema by an additional ± 1.8°C during the month of July. This increased variation in soil temperature did not diminish over time. Unfortunately, comparable long-term data for REF (unharvested reference plots) and OM1 was not collected. Soil moisture also reflected differences according to the OM removal gradient (Figure 3.4). While the data represents a single time-point, it is still informative that decreased moisture retention was found with increased OM-removal. These differences likely relate to the compounding effects of OM loss (absorptive material) and warmer soil temperatures (higher evapourative flux). Figure 3.4. Bar plot illustrating differences in total carbon, total nitrogen, soil moisture and pH among treatments in all ecozones. REF corresponds to unharvested reference plots. Error bars correspond to one standard error of the mean. Figure 3.5. Mean daily soil temperature data for JPON (A), PPCA (B) and BSON (C) ecozones. Panel A contains long-term temperature data at varying depths along the soil profile for the two highest intensities of OM removal. Multiple years were grouped and averaged over a 4 to 5-year window. Transparent dots correspond to all daily measurements at 5 cm for OM2 (yellow) and OM3 (red). Panel B depicts soil temperatures averaged across the entire soil profile for REF, OM1 and OM3 plots in PPCA (sourced from Paz 2001 and reprinted with permission from Dr. Lucas Paz). Panel C illustrates the convergence of mean yearly soil temperatures over 14 years at the interface of organic and mineral layers (upper 10cm) in OM2 and OM3 from 18 replicates per treatment. 3.2.3 Ecozone-wide, Global Responses to Harvesting Modeling of bacterial and fungal OTU abundance patterns revealed three main trends among harvesting treatments: i) expansion in relative abundance in harvested plots, OM3 > OM2 ≈ OM1 > REF, ii) decline in relative abundance from unharvested levels, REF > OM2 ≈ OM1 > OM3, and iii) a predominance at either intermediate intensity, OM1 ≈ OM2 > OM3 ≈ REF (Figure 3.6). Overall, the pattern of ‘expansion’ (i), a term used to describe this phenomenon throughout this chapter, was observed in 14.1% and 12.5% of bacterial and fungal OTUs, respectively, while the pattern of ‘decline’ (ii) was observed in 12.1% and 9.4% of OTUs, and the predominance of OM1 or OM2 in a total of 10.6% and 13%, respectively. Not all ecozones showed the third trend (JPON, BSON, PPCA and SBSBC), and some showed a stronger expansion than others (LPTX and IDFBC). These patterns demonstrated that, over a decade after harvesting, the harvesting gradient produced a comparable gradient in the abundance of bacterial and fungal communities. Further, the retention of OM had selected for taxa not necessarily abundant in REF or OM3, corroborated by the fact OM1 and OM2 shared the greatest percentage of overlap of any two treatments and, conversely, REF and OM3 the least (Figure 3.2). The alpha-diversity of bacterial and fungal communities significantly differed among harvesting treatments in a minority of ecozones and, depending on ecozone, exhibited increasing or decreasing trends in harvested plots (Figure 3.7). Five of the six statistically supported differences were indicative of increasing diversity in harvested plots. Fungal populations in mineral soils were consistently more diverse in harvested plots across all ecozones, though statistically significant in only SBSBC and JPON. On average, fungal diversity was greatest in OM1 mineral soils everywhere except for LPTX. Bacterial diversity was also greater in harvested plots in mineral soils in half of the six ecozones, but exhibited a reduction in diversity in the other half. Harvesting produced broad differences in community structure at the phylum level in both fungal and bacterial communities (Figure 3.8). Populations of Chloroflexi, candidate phylum AD3 and Gemmatimonadetes (mineral layer-associated) and Cyanobacteria (organic layer-associated) expanded with increasing OM removal across all ecozones. Conversely, populations of Acidobacteria, Actinobacteria and Gammaproteobacteria declined in harvested plots, though not always consistently across all ecozones. Samples from Texas (LPTX), in particular, did not exhibit any broad changes at the phylum level. Fungal communities exhibited a consistent decline in the ratio of Basidiomycota to Ascomycota, everywhere except for LPTX (Figure 3.9). Unclassifiable sequences increased with OM removal (Figure 3.10) with approximately double the amount of unclassified in OM3 compared to REF. Figure 3.6. Snowflake plots showing the most common abundance patterns of OTUs among harvesting treatments. Each possible permutation in pattern is apparent by moving from the outermost coloured squares (greatest abundance) inwards step-by-step (ex. bottom-left of figure). Circles are scaled to the frequency of the pattern occurring relative to randomized data. Solid circles indicate that the pattern is more likely to occur and hollow circles less likely. Figure 3.7. Box and whisker plots of Shannon diversity (H’), Chao1 richness and Simpsons’s Evenness estimates of bacterial and fungal communities among harvesting treatments according to ecozone and soil layer. The estimation for a given sample was based on an average of 500 calculations on OTU tables rarefied to an equal sequencing depth. Tukey HSD supported, pairwise differences are grouped by lettering. Figure 3.7 … continued. Figure 3.7 … continued. Figure 3.7 … continued. Figure 3.7 … continued. Figure 3.7 … continued. Figure 3.8. Barplots displaying the relative abundance (0 – 100%) of bacterial and fungal OTUs classified at the phylum level faceted by ecozone and harvesting treatments. The relative abundance of divisions within the phylum Proteobacteria are inset. Phyla with low abundances (< 0.075% of total reads) were filtered to reduce clutter. Figure 3.9. Relative abundances of Basidiomycota (top) to Ascomycota (bottom) according to ecozone and harvesting treatment. The log ratio of the ratio of their abundances is displayed by overlain patterned bars, illustrating the general decrease in Basidiomycota relative to Ascomycota according to OM-removal. Error bars correspond to one standard error of the mean. Figure 3.10. Abundance pattern of unclassified fungal and bacterial sequences at the rank order, exhibiting an increased proportion of sequences from poorly characterized or uncultured taxa in harvested plots. Error bars correspond to one standard error of the mean. Fine-scale, OTU-based differences in community composition were identified through indicator analysis. Among the OTUs showing the greatest expansion following harvesting were radiation, desiccation and heat-tolerant taxa (shaded orange; Figure 3.11). Bacteria from the ‘Terrabacteria group’ (Actinobacteria, Armatimonadetes, Chloroflexi, Cyanobacteria and Firmicutes) were all more abundant in harvested plots, though certain families of Actinobacteria declined in abundance relative to unharvested plots (Figure 3.12A). Many of the stress-tolerant taxa were highly abundant (0.2-3.3% of total bacterial community), and included endolithic Actinobacteria (Geodermatophilaceae) and other Actinobacteria (Gaiellaceae spp. and Arthrobacter), Firmicutes (Alicyclobacillus, Bacillus and Clostridium), Cyanobacteria (Nostoc), a number of Chloroflexi, and members of other genera such as Segetibacter, Flavisolibacter, Methylobacterium, Geothrix and Geobacter. Similar growth of stress-tolerant fungal taxa was observed, including known pyrophilous fungi (Figure 3.12B), lichenized fungi (Lecanorales), lichenicolous fungi, and melanized, rock-inhabiting fungi, such as members of the genus Phaeotheca (Sterflinger, 2000), and desert-adapted taxa such as Talaromyces (Stolk et al., 1965), Hormonema (Burford et al., 2004) and Preussia (Rao et al., 2016). Glomeromycota, a phylum containing arbuscular mycorrhiza, substantially expanded in harvested sites in BSON (undetected in REF and ~1% of total reads in OM3). A curated table of indicator taxa was prepared based on results from indicator analysis, representing taxa which responded most to harvesting (Table 3.1; full table in Table E.6). Indicator taxa with expanding populations were two-fold more common than taxa showing a decline in harvested plots. Fewer indicator taxa were observed for the mineral layer (n=38) than in the organic layer (n=51) and all but two showed patterns of expansion, whereas indicator taxa associated with organic layer showed relatively equal numbers of taxa indicative of expansion (n=24) or decline (n=27). Figure 3.11. Dot plot displaying taxa containing OTUs indicative of harvesting treatments of bacteria (Panel A) and fungi (Panel B). The response ratio represents the average relative abundance of an OTU in all three OM treatments divided by the relative abundance in REF. OTUs are ordered from left to right by average abundance in harvested plots. All dots correspond to indicator OTUs with an indicator value > 0.5 and p-value <0.01. Dot area is scaled to average counts. A red dots indicates that the OTU met the criteria across all ecozones. Orange labels indicate members of the taxa have reported tolerance to radiation, desiccation and/or heat. Green labels indicate ectomycorrhizal fungi (Panel B). OTUs are grouped by genus (x-axis). … continued on next page Figure 3.11 … continued. Figure 3.12. Expansion of stress-tolerant taxa evidenced by the increased abundances of phyla within the Terrabacteria group (Actinobacteria, Armatimonadetes, Chloroflexi, Cyanobacteria and Firmicutes) (A) and pyrophilous fungal genera (B). In (A), all phyla exhibited similar trends and were aggregated except for Actinobacteria which were plotted separately due to differences in response to harvesting at the family level. The following actinobacterial families exhibited declining populations (panel 1): Actinospicaceae, Micromonosporaceae, Solirubrobacteraceae, Streptosporangiaceae, Thermomonosporaceae, and Streptomycetaceae. The following actinobacterial families had expanded populations (panel 2): Gaiellaceae, Geodermatophilaceae and Micrococcaceae. … continued on next page Figure 3.12. ... continued Table 3.1. A list of bacterial (A) and fungal (B) taxa that consistently expanded or declined in relative abundance in four or more ecozones in response to harvesting. Classification refers to the lowest possible classification with a bootstrap value > 80. Each classification is prefaced with its associated rank (i.e. “o__” corresponds to Order, etc.). Ecozones displaying trends are given. Mineral layer and organic layer-associations are noted by shaded squares. Horizontal barplots display the response ratio, which corresponds to the average abundance in OM3 divided by the average abundance in REF. Bars are coloured according to the maximum observed relative abundance of each taxon. Table 3.1 … continued. Declining relative abundances were observed in three or more ecozones for the following bacterial taxa: Verrucomicrobia (Opitutus), Gammaproteobacteria (unclassified Sinobacteraceae, Rhodanobacter and Luteibacter), Alphaproteobacteria (Methylocapsa, see Figure 3.13; Rhodomicrobium and Ancylobacter) and Actinobacteria (Streptomycetaceae, Solirubrobacter and Dactylosporangium). Fungi were more likely to be indicators of declining abundance (27/69) than bacteria (17/63). Ectomycorrhizal (EM) fungi were highly abundant (~10 – 50% of total ITS libraries) and far more likely to decline compared to known saprotrophic taxa (odds ratio 7.1, p=0.002). A majority of EM genera declined post-harvesting, such as Russula, Cenoccocum, Cortinarius, Otidea, Piloderma, Hygrophorus, and Pseudotomentella. However, some EM populations expanded in OM1 and/or OM2 (Figure 3.14) and a minority of EM taxa were consistently and heavily expanded in harvested plots, such as Suillus (3 to 6-fold increases), Thelephora, Tomentella and Wilcoxina. The diversity of EM was generally reduced in harvested plots in both soil layers, though more so in organic layer soils. Diversity estimates based on OTU profiles or genus-level classifications both demonstrated a reduction in diversity of EM taxa in harvested plots, though the effect was more pronounced in classification-based estimations (Figure 3.15). All statistically supported differences exhibited decreases in the diversity of EM in harvested plots, except one instance in SBSBC mineral soil where OM1. Figure 3.13. Abundance patterns of the methanotrophic bacterial genus, Methylocapsa, exhibiting declining populations with increasing harvesting intensity. Error bars correspond to one standard error of the mean. Methylocapsa reads were originally classified as Methylocella using Green Genes, but further analysis of these sequences suggested they were more closely related to Methylocapsa based on best BLAST hits (97-98% match to NR_028923) as well as alignment and classification using both the Ribosomal Database Project and Silva ‘All-Species Living Tree Project.’ Figure 3.14. Relative abundances of ectomycorrhizal fungi according to soil layer, ecozone and harvesting treatment. Figure 3.15. Box and whisker plots showing the average Shannon diversity estimate for all ectomycorrhizal fungi by soil layer, ecozone and harvesting treatments based on OTU profiles (Panel A) or genus levels classifications (Panel B). Estimations were based on an average of 100 calculations on data rarefied to equal sequencing depth. Statistically supported differences are grouped by lettering. Figure 3.15 … continued. Modeling of the abundance patterns (Figure 3.6) revealed that a sizeable proportion of OTUs exhibited higher relative abundance at intermediate levels of OM removal. Twenty-four fungal taxa and three bacterial genera were identified to be maximally abundant in OM1 or OM2 (Table 3.2) and all but one was more abundant in the organic layer. However, the trend in any given taxa was less consistent across ecozones in comparison to taxa indicative of expansion or decline. One EM species, Thelephora sp. ECM1, demonstrated a consistent increase at intermediate OM treatments in all ecozones except LPTX (Figure 3.16A) and was positively correlated to C:N ratio (r=0.25, p < 0.001). Two other groups that were significantly correlated to C:N ratio showed predominance in OM1 and OM2 (Figure 3.16C and D): a group of unclassified Agaricales OTUs (r=0.30, p < 0.0001) and an OTU from Dermataceae (r=0.36, p < 0.0001). A species of unclassifiable Agaricomycotina demonstrated similar abundance patterns, but was not significantly correlated to C:N (Figure 3.16B). Each of these taxa exhibited the trend in both soil layers. The proportion of OTUs predominant at OM1 and OM2 was slightly higher among OTUs significantly correlated to C:N ratio, increasing by 4.4% and 3.5% in fungal and bacterial pyrotag libraries, respectively. A number of genera designated as ‘wood saprotrophs’ by FUNGuild had notably higher relative abundance in OM1 and/or OM2, including Serpula, Coniophora, Gymnopilus, Perenniporia and Trechispora (Figure 3.17). 3.2.4 Ecozone-specific Responses to Harvesting The extent of ecozone-specific effects of harvesting was in line with the broad differences in community composition among ecozones. LPTX shared the lowest overall overlap with other ecozones and, as one might expect, the fewest number of common taxa indicative of harvesting. In LPTX, Russula, an EM fungus, expanded in OM3 in contrast to all other ecozones. Similarly, the EM genus Amanita was increased solely in harvested plots in LPTX (Table E.6). Table 3.2. A curated list of bacterial and fungal taxa showing population expansion with intermediate intensities of OM removal (i.e. OM1 and OM2) in contrast to REF and OM3 plots. Classification refers to the lowest possible classification with a bootstrap value > 80. Each classification is prefaced with its associated rank (i.e. “o__” corresponds to Order, etc.). Mineral layer and organic layer-associations are noted by shaded squares. Horizontal barplots display the response ratio, which corresponds to the average abundance in OM1 and OM2 divided by the average abundance in REF and OM3. Bars are coloured according to the maximum observed abundance of each taxon in any single library. For a complete list of indicator taxa see Table E.7. Figure 3.16. Abundance profiles of OTUs which displayed increased abundance at intermediate intensities of OM removal. Plots B and C correspond to a single OTU, while plots A and D correspond to 20 and 17 OTUs, respectively, all exhibiting the same pattern of abundance. Error bars correspond to one standard error of the mean. Plot E illustrates the phylogenetic relationship of OTUs classified as ‘Thelephora sp. ECM1’ due to historic misclassification of putatively saprotrophic Odontia as Thelephora (sequences derived from Tedersoo et al., 2014). Figure 3.17. Aggregated abundances of all fungal genera designated ‘wood saprotrophs’ by FUNGuild, including plots for subsetted by genus for taxa associated with white rot (A), brown rot (B & D) or both (C). All exhibited characteristics of increased abundance in plots were a degree of organic matter has been retained. Similarly, a number of bacterial indicator taxa were exclusive to PPCA, such as Spirosoma and Rubrobacter, which have cultured representatives with extreme tolerances to radiation (Ferreira et al. 2009; Lee et al. 2014). The expansion of unclassifiable Syntrophobacteraceae (Deltaproteobacteria) was a strong feature in IDFBC, and, to a lesser extent, in the SBSBC, with two-fold greater relative abundance in harvested plots (TukeyHSD; p < 0.001). Common responses were typical of proximal ecozones presumably reflecting the similarity of environmental conditions (Figure 3.18). However, a number of taxa exhibited contrasting responses along a North-South axis, such as Terriglobus (bacteria) and Cladophialophora (fungi) which declined in B.C., but expanded in PPCA and LPTX (Figure 3.19). Conversely, fungi from the order Boletales, driven by increases of Suillus and Rhizopogon, expanded in northern and declined in southern harvested plots. Northern and southern sites exhibited marked differences in soil temperature, precipitation and soil moisture (Table E.5). Harvested plots in northern ecozones had slightly more basic soil pH, a trend not observed in southern sites. Other populations exhibited an East-West divide with some taxa exclusive to eastern (Cupriavidus and candidate phylum GAL15) or western sites (Limnohabitans, Nostoc and AKIW781) and other taxa exhibiting contrasting responses according to geography, such as Rudaea, Kitasatospora and members of Atheliales (Figure 3.20). A number of bacterial and fungal taxa exhibited patterns of both expansion and decline in response to harvesting (Figure 3.11). For a subset of these taxa, the variation could be attributed to different responses among closely related species. For example, fungal OTUs within the EM genus Suillus that increased in harvested plots formed a distinct clade (along with S. variegatus, S. luteus and S. pseudobrevipes) separate from OTUs that declined (grouping with S. lakei and S. caerulescens; Figure 3.21). Rhizopogon exhibited similar species-level differences in response to harvesting, notably according to northern and southern location (Figure 3.22). Species of Kitasatospora also exhibited different responses, which also differed in their distribution in eastern and western ecozones (Figure 3.21). Two EM genera within the same family, Tomentella and Pseudotomentella, also exhibited different responses to the impacts of timber harvesting (Figure 3.23). However, the majority of OTUs within taxa that showed both declining and expanding populations did not display a clear phylogenetic basis for their abundance pattern. Figure 3.18. Non-parametric multidimensional scaling of bacterial (left) and fungal (right) pyrotag libraries based on Bray-Curtis dissimilarities. Individual OTUs were mapped as black crosses (~44, 000 bacterial and 16,000 fungal OTUs). Samples were mapped as coloured circles. Samples from the organic layer in PPCA and LPTX were not mapped due to incomplete environmental data. Bacterial samples exhibit a clear split between organic (top) and mineral (bottom) layers. Experimental factors were fitted to ordination with the length of the arrow proportional to the correlation between variable and ordination. Figure 3.19. Abundances of four taxa with differing responses to harvesting (i.e. expansion or decline) between northern and southern sites. OM removal treatments are represented by conventional colours. Y-axis corresponds to average counts per thousand reads and error bars depict one standard error of the mean. For a more detailed phylogenetic breakdown of OTUs within genus Rhizopogon, consult Figure 3.22. Figure 3.20. Abundance patterns for eight taxonomic groups exhibiting contrasting responses to harvesting (i.e. expansion or decline) between western and eastern sites. Error bars depict one standard error of the mean. The order AKIW781 is within the phylum Chloroflexi. Figure 3.21. Phylogenetic tree of fungal genus, Suillus, and bacterial genus, Kitasatospora, accompanied by their abundances across OM removal treatments and ecozones. Inset barplots show the total counts for each genus, while barplots along the right-hand side show counts for each individual phylogenetic clades (marked with star). For simplification, the Y-axis of the right-hand plots, corresponds to percent relative abundance. On average, Suillus spp. accounted for 5% of ITS reads per library, while Kitasatospora spp. accounted for an average of 0.05% per library. Aligned sequences were trimmed to 355 bp (Suillus) and 250 bp (Kitasatospora) prior to tree building. Figure 3.22. Phylogenetic tree of fungal genus, Rhizopogon, accompanied abundance by data across OM removal treatments and ecozones. The inset bar plot shows the relative abundance of all reads classified as Rhizopogon, while barplots along the right-hand side correspond to the percent abundance of individual phylogenetic clades. These 10 OTUs account for 82% of all reads of the 51 OTUs classified as Rhizopogon. On average, Rhizopogon spp. accounted for 0.7% of ITS reads per library. Aligned sequences were trimmed to 420 bp prior to tree building. Figure 3.23. Differential responses to harvesting in two closely related ectomycorrhizal fungi from the family Thelephoraceae: Tomentella and Pseudotomentella. Error bars depict one standard error of the mean. 3.3 Impacts of Harvesting on Cellulolytic Populations Figure 3.24 provides an overview of the sampling regime, experiments and data collected for analysis in Section 3.3. A total of 48 bacterial 16S rRNA gene and 46 fungal ITS region pyrotag libraries (half 13C- and half 12C-libraries) plus pyrotag libraries from PPCA (section 3.2), 72 PLFA samples, 108 respiration assays, and 4 metagenomes were analyzed in this sub-chapter. All raw sequencing data described in Section 3.3 can be retrieved from the European Nucleotide Archive under the study accession (PRJEB9761) for 16S rRNA gene (ERS803692-ERS803739) and ITS pyrotag libraries (ERS803740-ERS803786), draft genomes (ERZ288956 - ERZ288966) and metagenomic libraries (ERS1099581- ERS1099584). All additional data, including sample metadata, other raw datasets, and representative FASTA sequences for putative cellulolytic taxa can be found in the Supplementary Data. Figure 3.24. Overview of the samples, experiments and datasets utilized in studying the effects of timber harvesting on the cellulolytic community. 3.3.1 Effects of Harvesting on Respiration The first test of whether timber harvesting affected microbial activity in PPCA was to measure net respiration among treatments with or without the addition of Douglas-fir lignocellulosic substrate. Despite considerable variability, respiration in mineral soils was significantly reduced by harvesting (ANOVA, p < 0.01), but was not different between soils from OM1 and OM3 harvesting treatments (Figure 3.25). Respiration was greatest with the addition of raw lignocellulose, while amendments of ‘cellulose + lignin’ and cellulose-only supported similarly low level increases in respiration. Respiration in cellulose-amended soil from OM3 was particularly low, suggesting that cellulose-degrading populations were disproportionately affected by OM-removal (t=-2.65; p=0.009). Respiration was positively correlated with pH (r=0.34; p < 0.001) and weakly with the total carbon content of soil (r=0.19; p=0.049), but not with the total nitrogen content or C:N ratio. Organic layer soils respired 3-fold more CO2 than mineral soils, but no significant harvesting treatment differences were observed in organic layer soils due to its highly variable background respiration, which confounded the detection of differences between microcosms with and without added substrate. 3.3.2 Characterization of SIP-Enrichment for Cellulose and Lignin Prior to testing for the impacts of harvesting, time-course experiments were performed to characterize the rate and quality of 13C-incorporation from labeled cellulose. Low-level enrichment was detected as early as four days into the incubation (Figure 3.26) and rose gradually with time (more details in Section 4.2.1). Despite the low amount of 13C relative to 12C (δ-13C) in PLFAs from organic soils, the total amount of 13C incorporated was comparable to mineral soils. Both DNA-based and PLFA-based quantitative methods revealed similar trends in enrichment (Figure 3.27). Figure 3.25. Dot-plot showing soil respiration in mineral soils from reference and harvested treatments (coloured lines are averages; n=9). Dot area is scaled to carbon to nitrogen ratio of individual soil samples. In all cases, respiration was significantly different between reference and harvested plots (t=16.9; p < 0.01), but not between OM1 and OM3. An arrow depicts the interaction between OM3 and respiration on cellulose, which was statistically supported (t=-2.65; p=0.01). Figure 3.26. Time-course assay of enrichment of organic and mineral layer soils from LPTX revealed by measurements of 13C-incorporation into DNA (A) and PLFA biomass (B) by both cellulose and lignin substrates. Microcosms were sacrificed at each time-point rather than sub-sampled (n=1 for all time points). Natural abundances of 13C in DNA are indicated by dotted lines. 3.3.3 Harvesting Effects on Cellulolytic Activity The incorporation of 13C into PLFAs was generally lower in soil from harvested plots (Figure 3.27; Table E.9). The trend was clearest in mineral soils, where REF had significantly higher δ-13C enrichment in PLFAs and DNA than harvested plots; though, in organic soils, OM2 had the highest levels followed by REF. The total number of PLFAs showing 13C-enrichment above natural abundance was reduced in harvested plots in both soil layers (Table E.9), though only statistically supported in the organic layer (Figure 3.28A; TukeyHSD, p < 0.01). Bacterial cellulolytic activity was higher in unharvested soils exemplified by the lower ratio of fungal to bacterial PLFAs relative to all harvested plots in both soil layers (Figure 3.28B; TukeyHSD, p < 0.01). This trend was evident in both 12C and 13C PLFA profiles, driven by an increase in fungal biomass in OM3 (1.8-fold higher than REF) as well as higher amounts of Gram-positive and Gram-negative bacterial biomass in the unharvested treatments, 1.4-fold and 1.3-fold higher than OM3, respectively. REF had the highest proportion of Gram-positive PLFAs (47%), relative to OM1 (35%) and OM2 (31%), followed by OM3 (28%). Overall, the organic layer was host to more microbial biomass, approximately 4-fold greater total abundance of PLFA biomass than mineral soils and exhibited greater total cellulolytic activity. Fungi showed double the amount of 13C-enrichment relative to Gram-negative bacteria and quadruple that of Gram-positive bacteria in both soil layers. Figure 3.27. Soil properties and microbial activity in microcosms incubated with 13C-cellulose with harvesting treatments indicated by bar colours. Panels are scaled according to the highest value in each and treatments are ordered descending from highest to lowest value. Within groups of four treatments, paired values which have asterisks (in bold) are significantly different (p < 0.05), whereas values denoted by different letters are significantly different based on Tukey’s Honest Significant Difference. Respiration data from organic layer soils was not included because of extreme variability. Table E.9 presents a more detailed version of these data, including standard error. Figure 3.28. Trends in PLFAs in organic layer soil incubations with 13C-cellulose: (A) average total number of 13C-enriched PLFAs and (B) the ratio of fungal versus bacterial 13C-PLFAs. Mineral soils showed similar, but less pronounced, trends (Table E.9). Statistically supported differences are grouped by lettering. 3.3.4 Harvesting Effects on Community Structure SIP-cellulose proved effective in recovering DNA from actively cellulolytic populations. This was illustrated by the elevated levels of 13C-carbon in total DNA extracted from soils incubated with 13C-cellulose and the resulting 2.5-fold higher concentrations of DNA in heavy CsCl gradient fractions (Figure 3.29). Ordination of OTU profiles from the resulting pyrotag libraries exhibited distinct clustering of samples according to 13C-enrichment and soil layer (Figure 3.30). Furthermore, shotgun metagenomes derived from 13C-enriched DNA had substantial improvements in assembly over the 12C-control library (Figure 4.1; next section). Harvesting significantly changed which bacterial populations incorporated 13C, accounting for ~9% of the total variation in 13C-pyrotag profiles (p < 0.05), comparable to the variation explained by soil layers (Figure 3.31). Harvesting alone was not a significant factor in explaining differences among fungal 13C-pyrotag profiles; rather, pH and harvesting had an interacting influence (p=0.053, R2=0.11). Harvesting treatments did not affect the alpha diversity (Shannon-Weaver diversity) or beta diversity (UniFrac) of 13C-pyrotag libraries. Harvesting did alter the predominant taxa incorporating 13C from cellulose but did not cause the complete loss or gain of cellulolytic taxa. Soil from harvested plots yielded 13C-libraries with significantly diminished abundances of cellulolytic Verrucomicrobia (Chthoniobacter and Opitutaceae), Streptomycetaceae, Burkholderia, unclassified Rhizobiaceae and Caulobacter (Table 3.3). Overall, populations of Verrucomicrobia, Streptomycetaceae and Caulobacter were sufficiently abundant and active (i.e. enriched by SIP) to yield partial or complete draft genomes (Table E.11). Figure 3.29. Comparisons of (A) 13C-enrichment of soil DNA extract and (B) total DNA recovery from fraction F1-F7 between microcosms fed 12C- and 13C-cellulose. Consult Wilhelm et al. 2014 for additional comparisons and characterizations of successful separation and recovery of enriched nucleic acids. Figure 3.30. Non-parametric multidimensional scaling of 16S rRNA gene pyrotag libraries based on Bray-Curtis dissimilarities. Ovals indicate the distribution of samples (grey crosses) that clustered according to 13C-enrichment (separated along x-axis) and soil layer (separated along y-axis). Blue and pink coloured circles represent the ordination of bacterial classes and are scaled to normalized abundances in 12C- (pink) and 13C-libraries (blue). Only classes with relative abundances greater than 0.15% are shown. Candidate taxa without designated classes are identified as FBP (division of Armatimonadetes) and WPS-2 (phylum). Figure 3.31. Bar plot of the percent variance (R2) explained by each factor based on perMANOVA (nperm=1000) using Bray-Curtis dissimilarities for either 16S rRNA gene or ITS pyrotag libraries. Only factors with statistical support (p < 0.05) factors were included in the plot. The full tabular perMANOVA results are included. Table 3.3. List of putatively cellulolytic bacterial and fungal taxa determined by differential abundance between 13C- and 12C-libraries 16S rRNA gene and ITS pyrotags (13C:12C). Harvested/reference indicates taxa significantly (p < 0.05) more abundant in microcosms with soil from harvested plots (right bar) or reference plots (left bar) based on log response ratio (the natural log of the mean abundance in soil from harvested plots divided by the mean abundance in soil from reference plots). Mineral layer and organic layer-associated taxa are noted by shaded squares. Taxa with isolates possessing previously described cellulolytic activity are denoted by solid circles. Classification refers to the lowest possible taxonomic rank for the group of OTUs with a bootstrap value of > 80. Each classification is prefaced with its associated rank (i.e. “o__” corresponds to Order, etc.). The “# enrOTU” represents the total number of 13C-enriched OTUs assigned to a corresponding taxon. A full list of enrOTUs with corresponding accession numbers can be found in Supplementary Data. Their reduced abundances in soil from harvested plots was supported by the proportion of metagenomic reads which mapped back to these genomes (Figure 3.32) as well as abundance patterns in 13C- and 12C- pyrotag libraries (Figure 3.33). Their reduced in situ abundances in harvested plots were also apparent (Figure 3.33). Conversely, a number of different cellulolytic taxa were enriched in soils from harvested plots, including a number of Betaproteobacteria and members of Myxococcales, Planctomycetes and the Basidiomycota Clitopilus (Table 3.3). The decline of Actinobacteria relative to fungi in soil from harvested treatments was corroborated in PLFA, 13C- and in situ pyrotag and shotgun metagenomic data. Abundances of the order, Actinomycetales, as well as the family Streptomycetaceae were reduced in harvested treatments (Figure 3.33 & Figure 3.34). Read mapping to the Kitasatospora draft genome (family Streptomycetaceae) further supported this trend (Figure 3.32). The predominant cellulolytic fungi, from the family Chaetomiaceae (Sordariomycetes), had expanded populations in soils from harvested plots in both 13C- and in situ pyrotag libraries (Figure 3.33). Chaetomiaceae were highly abundant in all ITS libraries with a total percent of 2%, 3%, and 9% in in situ, 12-C and 13C-libraries, respectively. Read mapping to the recovered fungal draft genome, most closely related to the genome of Myceliophthora thermophila (family Chaetomiaceae), supported the increased abundances of Chaetomiaceae in microcosms from harvested plots (Figure 3.33 & Figure 3.34). Both Sordariomycetes and Actinobacteria populations were consistently negatively correlated to C:N ratio, though not always supported by a strong p-value (Figure 3.35; Figure 3.36). C:N ratio did not significantly differ among harvested plots, suggesting that C:N ratio, as a proxy for litter quality, did not explain differences in these two populations (Figure 3.37). Abundances of Actinobacteria were positively correlated with pH (Figure 3.38), which could not be said for Sordariomycetes. Figure 3.32. Draft genomes recovered from metagenome assemblies from 13C-enriched DNA. Bars indicate the percentage of reads contributed by metagenomes from each treatment group. Genome size corresponds to size of bubble (also written) and completeness to the bubble fill. For additional details on completeness, taxonomic uniformity and accession numbers, consult Table E.11. Figure 3.33. The abundance in the three types of 16S rRNA gene or ITS pyrotag libraries (z-axis) that are indicators of either reference (beige) or harvested (red) treatments. Taxa were designated as either identified in this study as cellulolytic (blue) or previously reported to be desiccation and/or heat tolerant (pink). Abundances of taxa with asterix (*) represent per mil, rather than per cent abundance. Figure 3.34. Abundance patterns of Gram-positive bacteria (Firmicutes and Actinobacteria) and the main group of cellulolytic fungi from family Chaetomiaceae. The identical pattern is observed when data is aggregated at class Sordariomycetes (see Figure 3.33). Error bars correspond to one standard error of the mean. Indicator species analysis revealed bacterial taxa with consistently expanded populations in soils from harvested plots across all pyrotag libraries (Figure 3.33). These taxa were previously identified in Section 3.2.3, demonstrating consistency between broadly different datasets. As previously noted, the majority of these indicator taxa have been isolated from desert environments and are reported to be tolerant of heat, radiation and desiccation: Geodermatophilus (Montero-Calasanz et al., 2014; Sghaier et al., 2016), Sporichthya (Eppard et al., 1996), Ramlibacter (de Luca et al., 2011), Flavisolibacter (Joo et al., 2015), Methylobacterium (Nogueira et al., 1998; Romanovskaya et al., 2002) and Segetibacter (Liu et al., 2014). Figure 3.35. Linear regressions of Sordariomycetes abundance and carbon to nitrogen ratio (C:N). This figure contains six of the twelve possible plots (6 ecozone x 2 horizons) which showed notable statistical support. Plots that have not been shown had p-values ranging from 0.12 – 0.6 with no discernable positive or negative trends. Figure 3.36. Linear regressions of Actinobacteria abundance and carbon to nitrogen ratio (C:N). This figure contains five of the twelve possible plots which showed notable statistical support. Plots that have not been shown had p-values ranging from 0.35 – 0.93 with no discernable positive or negative trends. Figure 3.37. Dot plot showing the differences in C:N ratio among harvesting treatments at all ecozones. Lines correspond to the mean of each group. Few contrasts were statistically supported, so they were not plotted. The following contrasts within an ecozone were ‘significant’: OM2TX;Min-OM1TX;Min (p=0.04); OM2CA;Min-OM1CA;Min (p=0.01); OM3CA;Min-OM1CA;Min (p < 0.001) and OM2SBS;Org-REFSBS;Org (p=0.04). Figure 3.38. All possible linear regressions of actinobacterial abundance with pH among ecozones and soil layers. No statistically supported correlation occurred between pH and abundance of Sordariomycetes. 3.3.5 Description of Cellulolytic Taxa Chapter 4 provides a detailed description of lignocellulolytic taxa, yet, an initial characterization of cellulolytic populations in PPCA was needed to assess harvesting impacts. Therefore, a preliminary description based exclusively on Chapter 3 datasets is presented here. We identified a total of 234 bacterial 13C-enriched OTUs (enrOTUs) representing nine phyla. EnrOTUs were classified to Actinomycetales, Armatimonadetes, Cytophagales, Myxococcales, Planctomycetes, Rhizobiales, Opitutaceae and Oxalobacteraceae (Table 3.3). Non-metric dimensional scaling confirmed broad differences between 13C- and 12C-libraries as well as distinct cellulolytic communities in each soil layer (Figure 3.30). The organic-rich soil layer was comprised of previously known cellulose-degrading phyla, Cytophaga and Actinobacteria, while the mineral layer consisted of Betaproteobacteria and less characterized phyla such as Armatimonadetes (candidate division FBP and order FW68), Verrucomicrobia (classes Opitutae, Spartobacteria) and Candidatus Saccharibacteria (formerly TM7). The delineation of fungal enrOTUs was less successful due to sparse overlap amongst OTUs in ITS libraries, which were typically dominated by a few highly abundant OTUs. This is illustrated by the poor separation of samples by NMS (Figure 3.39) and the relatively small number of fungal enrOTU identified (n=16). These included unclassified Ascomycota and members of Agaricomycetes and Sordariomycetes (Table 3.3), though clustering in NMS suggest the involvement of Dothideomycetes and a large proportion of unclassified ITS sequences. The massive difference in proportion of reads classified as Ascomycota between 13C- versus 12C- metagenomes (0.8% and 10.6%, respectively) and enrichment of fungal PLFAs both suggested that Ascomycota were the predominant cellulose-degraders under our experimental conditions (Figure 3.40). Clitopilus was the only cellulolytic Basidiomycota to be identified. Basidiomycotal sequences were between ~103 and 104 times less abundant than Ascomycota in 13C-pyrotag libraries and the ratio between the two did not significantly vary according to harvesting treatment in either 12C- or 13C-libraries, but the relative abundance of Ascomycota did significantly expand in harvested plots in situ (Figure 3.41), as previously noted among other ecozones (Figure 3.9). One third of enrOTUs were detected in situ, demonstrating that low abundance cellulolytic populations were enriched for by SIP. enrOTUs occupied at most 1.4% of total reads and at least 0.08% with a median abundance of 0.42% among all samples. The most abundant single enrOTU (uncl. Streptomycetaceae) occupied, at most, 0.6% of a given sample with a mean abundance of 0.1%, followed by enrOTUs from Janthinobacterium (max: 0.5%), Burkholderia (0.4%), and uncl. Microbacteriaceae (0.3%). Of all enrOTU detected in situ, 90% were detected in the organic layer. For fungi, six out of the sixteen enrOTU were detected in situ with a surprisingly low maximum abundance of 0.3%, but based on taxonomic binning of OTUs, members of Chaetomiaceae averaged ~2% of in situ libraries. Metagenome assembly was greatly improved by SIP with the percentage of reads assembled in the 13C-metagenomes amounting to 17% (OM3), 23% (OM1), and 29% (REF) compared to less than 1% in the 12C-metagenome. Improved assemblies enabled the recovery of ten taxonomically uniform partial genomes of putatively cellulolytic bacteria (Figure 3.32; details in Table E.10). The most complete genomes were related to Myceliophthora thermophila (Ascomycota), Kitasatospora sp. (Actinobacteria), Opitutaceae spp. (Verrucomicrobia), Herbaspirillum sp. (Betaproteobacteria), Chthoniobacter sp. (Verrucomicrobia) and Caulobacteraceae spp. (Alphaproteobacteria). Figure 3.39. Non-parametric multidimensional scaling of ITS pyrotag libraries based on Bray-Curtis dissimilarities. Ovals indicate the distribution of samples (grey crosses) that clustered according to 13C-enrichment and soil layer. Coloured circles represent the ordination of fungal classes of greater than 0.15% overall relative abundance and are scaled to their normalized abundances in 12C- (pink) and 13C-libraries (blue). Figure 3.40. Lowest-common ancestor classification of all unassembled metagenomic reads at the phylum level. Phyla with an abundance of reads < 0.5% of the total were excluded. Figure 3.41. Relative abundances of Basidiomycota versus Ascomycota in pyrotag libraries. The y-axis corresponds to the log of the ratio of Basidiomycota to Ascomycota. Only in situ libraries showed a statistically significant trend. Unassembled 13C-metagenomes contained double the relative abundance of glycosyl hydrolase genes (GH) and three-fold more GH families with reported endoglucanase activity than the 12C-metagenome. Six endoglucanase-containing families and lytic polysaccharide monooxygenases (AA9) were among the most enriched CAZy gene families in 13C-metagenomes (Figure 3.42). Lignin-modifying enzymes, peroxidases (AA2) and iron reductase domains (AA8), were also highly enriched in 13C-metagenomes and were classified to the order Sordariales with the exception of one catalase-peroxidase identified in the Herbaspirillum sp. draft genome. The majority of differentially abundant GH enzymes were actinobacterial and fungal (Sordariales), while a lesser number were from Bacillales, Bacteroidales, Burkholderiales, Cytophagales, Opitutales, and Planctomycetes. Figure 3.42. Taxonomic affiliations of CAZy genes enriched in 13C- (blue) versus 12C-control (pink) metagenomes. Bubble area is scaled to counts per million among quality-filtered, unassembled reads, and the ratio corresponds to the relative counts between 13C and 12C metagenomes. CAZy gene families without a bubble had fewer than 0.5 counts per million reads. A beige square denotes lignin-modifying activity, while a red square denotes endoglucanase activity, based on www.cazy.org. Taxa comprising fewer than 5% of reads for any given family were binned as either ‘Other Bacteria’ or ‘Other Fungi.’ 3.4 Discussion A decade and a half after the initiation of the LTSP Study and harvesting, a clear gradient had formed in soil organic matter, temperature and moisture corresponding to the initial degree of OM removal. The existence of a corresponding gradient in the relative abundances of a number of bacterial and fungal taxa demonstrated the long-term influence of these environmental factors. Though the majority of cosmopolitan, and also most abundant, taxa appeared unaffected by harvesting, significant compositional changes were observed in both upper organic soil layers and in deeper mineral layers. In mineral soil, the absence of differences in organic content proved that the quantity and quality of organic matter were not the sole factors driving changes. The expansion of radiation, desiccation and heat-tolerant organisms reflected the increased dryness and temperature in the decades post-harvesting. These compositional shifts were shared among biogeographically distinct forest soils, demonstrating the generalizability of long-term selection pressures on certain taxa. Yet, local differences in community structure, and the corresponding ecozone-specific effects of timber harvesting, have the potential to influence how harvesting impacts microbial processes during forest regeneration. This discussion will weigh considerations of biogeography, the relative influence of OM removal on biotic versus abiotic parameters and highlight where results confirm and expand upon previous observations of long-term harvesting effects on saprotrophic, methanotrophic and ectomycorrhizal communities. To date, the LTSP Study has shown that rates of forest regeneration are highly variable and dependent on local conditions and, overall, that the effects of varying degrees of OM removal on primary productivity appear minor (Keenan and Kimmins, 1993; Page-Dumroese et al., 2006; Sanchez et al., 2006; Powers et al., 2005; Fleming et al., 2006; Thiffault et al., 2011; Ponder et al., 2012; Holub et al., 2013). Where harvesting impacted soil microbial communities, the effect was greatest at the highest level of organic matter removal (OM3), while the effects of intermediate levels (OM1 and OM2) were generally indistinguishable from one another, but distinct from unharvested controls (Hartmann et al., 2012; Cardenas et al., 2015; Leung et al., 2015). The present findings are in accordance with these reports, where patterns of expanding or declining abundances were clearest between REF and OM3, while OM1 and OM2 abundances were typically interchangeable and midway in-between. The most pronounced shifts in relative abundance were observed in taxa adapted to, or susceptible to, warmer and drier conditions or, in the case of EM fungi, the loss of tree hosts. Yet, a unique set of taxa had been selected for at intermediate harvesting treatments, and these populations have greater likelihood of responding to the trophic effects of retaining OM (i.e. nutritional), opposed to OM mitigating abiotic factors. The claim that organic matter retention was a significant factor in the long-term of distinct communities was supported by the number of uniquely overlapping OTUs (i.e. not present in REF or OM3) in OM1 and OM2 and a number of taxa indicative of intermediate harvesting intensities. Taxa indicative of OM1 and OM2 were largely associated with the organic layer, where differences in organic content were most pronounced. The predominance of saprotrophic groups and other strict wood-rot fungi in OM1 (and to a lesser extent OM2) reflected the influence of retaining coarse woody debris. Yet, despite the fact a large number of OTUs indicative of intermediate OM removal exhibited strong signals, their abundance patterns were less consistent across ecozones. These localized responses may have ecological meaning, since certain populations may be adapted to local sources of organic matter (Ayres et al., 2009; Prescott, 2010; Freschet et al., 2012). Yet, the sheer volume of individual, ecozone-specific cases that result made reporting and interpretation difficult, especially given the lack of knowledge regarding the ecological roles of the vast majority of taxa identified. The hypothesis that OM retention might stimulate decomposition by selecting for saprotrophs was a major motivation for characterizing the impact on cellulolytic populations with SIP. The well-documented adaptation of wood rot fungi to colonize coarse woody debris (Folman et al., 2008) led to the hypothesis that OM retention would select for higher abundances and diversity of cellulolytic fungi. However, contrary to these expectations, both organic matter rich OM1 and REF soils exhibited predominantly bacterial cellulolytic activity relative to OM2 and OM3, which were dominated by fungi. These differences were attributed to shifts in the relative abundance of members of Actinobacteria (Streptomycetaceae) and Sordariomycetes (Chaetomiaceae). The abundances of both Actinobacteria (positively) and Sordariomycetes (negatively) have previously been correlated to C:N ratio in litter and soil samples (Lauber et al., 2008; Strickland et al., 2009), revealing how OM quality can influence the decomposer community. Yet, in SIP and in situ pyrotag libraries, both Sordariomycetes and Actinobacteria populations were negatively correlated with C:N ratio, and C:N ratio did not significantly differ among treatments. Therefore, it is unlikely that differences in organic matter quality were driving the abundance of these groups and overall differences in cellulolytic activity. The more plausible cause for the expansion of cellulolytic fungi according to the OM removal gradient, were long-term changes in abiotic condition such as soil temperature and moisture. The fungi which expanded were members of Chaetomiaceae, either Chaetomium (ITS classification) or Myceliopthora (draft genome classification). Members of both groups are thermophilic, cellulolytic ‘dark septate’ (melanized) fungi reportedly abundant in hot, arid environments (Berka et al., 2011; Powell et al., 2012) and also possess the ability to decompose furans produced by forest fire (Rajulu et al., 2014). Though the decline in Streptomycetaceae in harvested plots was a robust trend in both SIP-cellulose and in situ pyrotag libraries (in B.C., PPCA and LPTX), it was unclear from the present data what the underlying cause might be. Streptomycetaceae are predominantly mesophilic organisms, with some thermophilic species (Kämpfer et al., 2014), and their sensitivity to desiccation could not be established in the literature. Streptomycetaceae were not the only family of Actinobacteria to exhibit declining populations in harvested plots, others included Actinospicaceae, Micromonosporaceae, Solirubrobacteraceae, Streptosporangiaceae, Thermomonosporaceae. Future studies of these groups may provide an explanation, but from the data gathered here, the role of OM quality or abiotic factors are unclear. The inclusion of OM3 treatment, where organic layer soil was removed and where abiotic changes were most pronounced, led to the identification of the strongest populations trends. Yet, the forestry practice mimicked by OM3, to remove the seed bank fast-growing shrubs that outcompete seedlings, was rare even in the early 1990’s when the LTSP was initiated. It was included as an extreme example of possible changes resulting from organic matter removal. Despite the limited comparison to current harvesting strategies, OM3 proved useful in identifying the rise in radiation, desiccation and heat-tolerant organisms, occurring even in OM1 and OM2. This phenomenon has largely gone unnoticed in previous surveys of harvesting impacts on soil communities (Hartmann et al., 2009; Hartmann et al., 2012; Holden et al., 2013a; Leung et al., 2016). However, the pronounced effects of OM3 may give the appearance that abiotic factors are of greater importance than biotic changes, as they were artificially most pronounced in the removal of topsoil. A closer examination of the character and size of effect between OM1 and OM2 may yield additional insights to the effects of harvesting, especially given that OM1 and OM2 treatments represent the most realistic management decisions regarding OM removal. The extent of ecological change brought about by harvesting was reflected in the consistent expansion of sequences corresponding to mitochondrial rRNA genes classified to mosses (Polytrichum and Trichostomum) and algae (Pavlova and Exanthemachrysis) as well as the expansion of plastid rRNA genes classified to a variety of higher plants in harvested plots (Appendix B; Figure B.1). The decline of fungi from the genus Lecanicillium, across all ecozones, further illustrated the scale of impact traceable through soil pyrotag libraries (Figure B.1). Lecanicillium are commonly entomopathic fungi with many nematophagous species (Goettel et al., 2008). Their decline suggests changes occurring at higher trophic levels, possibly related to the decline of nematode populations that has been observed in the years following harvest (Persiani et al., 1998; Forge and Simard, 2001). These observations reflect the broad differences in environmental conditions in harvested plots relating to a greater exposure to radiation, wind erosion, moisture loss, soil compaction, elevated temperatures, diurnal fluctuation and changes in soil chemistry/nutrients. Soil temperatures throughout the top 20-30 cm were 2 °C warmer between REF and the lowest organic matter removal treatment (OM1) and became progressively warmer with OM3 plot. Greater fluctuations in daily soil temperature were observed and soil moisture was correspondingly drier in all harvested plots. The rise of taxa from the ‘Terrabacteria group,’ well-regarded for their tolerance to desiccation, radiation and heat (Battistuzi et al., 2009; Sghaier et al., 2016), was evidence for the significant changes in microbial community brought about by the altered physical regime post-harvesting. The expansion of Terrabacteria phyla, specifically Actinobacteria, Armatimonadetes, Chloroflexi, Cyanobacteria and Firmicutes, has been reported following forest fire (Xiang et al., 2014; Tas et al., 2014) and in other exposed soil environments such as glacial forefelds (Rime et al., 2015). Populations of members within Terrabacteria broadly increased in harvested plots, including populations of endolithic, desert-dwelling Actinobacteria from the family Geodermatophilaceae (Sghaier et al., 2016). The response of all groups within Terrabacteria was not coherent, as noted with Streptomycetaceae, but the scale of expansion of groups that did respond was readily detectable even aggregated at the superphylum level. The increase in sequences recovered from both fungal (Cladonia sp. and Lecanorales) and cyanobacterial substituent of lichen, and lichenolous fungi, and desert or rock-inhabiting fungi further indicated the shift in harvested plots towards desiccation, radiation and heat-tolerant organism. Many taxa flourishing in harvested plots resembled those found in glacial forefelds, where mostly barren soil is exposed to high levels of UV radiation, temperature and moisture fluctuation, with even similarities in pH, total carbon and nitrogen (Rime et al., 2015). These taxa included Clostridium, Cupriavidus, Geobacter, and Massilia (bacteria) and Cryptococcus, Cladophialophora and Tetracladium (fungi). Shifts in the functional character of soil communities of stress-tolerant taxa has the potential to impact soil chemistry during the decades of forest renewal. This phenomenon has possibility to compound over multiple harvesting cycles given the capacity of hardier species to persist in soil. Sampling for this research occurred just prior to canopy closure, a moment during forest regeneration where conditions selecting for stress-tolerant taxa may begin to wane, but following a significant period of time during which populations could influence soil chemistry. The expansion of thermophilic sulfate reducers Syntrophobacteraceae (Kuever et al., 2014) was a major feature in BC ecozones, while populations of metal-reducing bacterial genera, Geothrix and Geobacter, expanded in the majority of all ecozones to sizeable population (~0.2% of total reads). Long-term changes in bulk soil chemistry may even result from differences in the quality of microbial biomass. Stress-tolerant taxa typically have unique cell envelope structures, such as Gram-positive bacteria, which persist longer in soils than their Gram-negative counterparts (Throckmorton et al., 2012). The functional character of cellulolytic populations was altered by the dramatic shift in relative abundance of Chaetomiaceae and Streptomycetaceae in OM2 and OM3, leading to reduced cellulolytic activity. Similar long-term changes in relative abundance of saprotrophic fungi and Gram-positive bacteria were observed in regenerating forests seven (Lewandowski et al., 2015), fifteen (Hartmann et al., 2009; Hartmann et al., 2012) and forty years after timber harvesting (Chatterjee et al., 2008) and following forest fire (Xiang et al., 2014). Populations of Sordariales, including the family Chaetomiaceae expanded in logged forests in Southeast Asian tropical forests (McGuire et al., 2014), as well as following large-scale tree die back due to insect herbivory (Štursová et al., 2014), revealing these trends may be broadly applicable to forest disturbance. The conclusion that an increase in relative abundance of cellulolytic fungi resulted in decreased cellulolytic activity is at odds with the conventional view that fungi predominate the breakdown of recalcitrant plant polymers. However, there are a number of cases in which soil properties, nutrient availability and litter quality influence whether decomposition is predominantly fungal or bacterial. The following studies demonstrated bacterial decomposition can predominate with changes in the N:P ratio (Güsewell and Gessner 2009), minimization of disturbance (Jastrow et al., 2007), and at higher soil pH (Strickland and Rousk 2010). The inverse relationship between cellulolytic activity of Streptomycetaceae and Chaetomiaceae (family of Sordariomycetes) populations, and an overall reduction in respiration, reported here was not without precedent. Strickland et al., (2009) demonstrated that the abundance of Sordariomycetes was negatively correlated with net respiration during litter decomposition, while the reverse was true for Actinobacteria. These observations suggest that the underlying cause of the reduction in respiration and rate of decomposition commonly found in harvested plots (Whitford et al., 1981; Yin et al., 1989; Prescott et al., 2000; Webster et al., 2016), may result from biological changes, not solely abiotic constraints. The decline of more susceptible taxa may also alter the functional character of soil communities. Ectomycorrhiza were the most prominent group of fungi, occupying between 10 to 50% of ITS libraries, and were also one of the populations most clearly impacted by harvesting. The decreased relative abundance and diversity of EM populations in harvested plots was consistent with expectations, given the removal of tree hosts and previous characterizations of harvesting impacts at B.C. LTSP sites (Hartmann et al., 2012). So, too, was the strong expansion of a small minority of EM taxa, namely Rhizopogon, Suillus, Wilcoxina, Tomentella and Thelephora that are commonly observed as early-colonizers of young conifer stands (Visser, 1995) and in the years and decades following forest fire (Buscardo et al., 2015; Glassman et al., 2015; Oliver et al., 2015) and timber harvesting (Hartmann et al., 2012; McGuire et al., 2014). The success of these EM fungi may be due to their ability to outcompete other EM species during root colonization (Cairney and Chambers 1999) or their resistance to high temperatures (Horton et al., 1998; Baar et al., 1999; Peay et al., 2009). One EM species of Thelephora was consistently more abundant at OM1 sites, lending evidence to the claim that some EM may function as facultative decomposers (Lindahl and Tunlid, 2015). Yet, the recent re-classification of a number of Thelephora sp. as Odontia, a non-EM, putatively saprobic group (Tedersoo et al., 2014), suggests that the phylogenetic delineations of saprobic and EM lifestyles between Thelephora and Odontia are not yet clear. Thelephora represent an interesting lifestyle, documented as cryptic, epiphytic by Ramírez-López et al., (2013). Compositional shifts in EM community have clear implications for the long-term ecology of forest plantations, especially given that, of all EM genera observed to expand, only Rhizopogon are known to stimulate host growth (Cairney and Chambers 1999). Yet, mycorrhizal communities demonstrate successional changes according to stand maturity (Visser, 1995; Twieg et al., 2007), and early-stage EM may fulfill nutritional needs of young plantations (Kranabetter, 2004), exemplified by the nitrogen fixing activity in Suillus tomentosus tubers (Paul et al., 2012). Thus, the potential long-term consequences of changes in EM abundance and diversity need to be studied in greater detail and in relation to planned harvesting cycles. The decline of a number of rhizospheric bacteria also has the potential to alter the functional character of regenerating forest soils. All but one of the indicator taxa classified as Alphaproteobacteria and Gammaproteobacteria were indicative of population decline and nearly all of the genera identified (Ancylobacter, Caulobacter, Labrys, Luteibacter, Rhodanobacter and Sphingobium) have isolates characterized from the rhizosphere. These taxa were consistently more abundant in organic layer soils, revealing that they are exposed the greatest changes in terms of exposure to heat and desiccation. Yet, similar to the phenomenon observed with EM fungi, the population of a common rhizospheric genus, Methylobacterium (Alphaproteobacteria), was drastically expanded in organic layer soils from harvested plots across all ecozones (26-fold in PPCA). Some members of Methylobacterium possess extreme radiation and desiccation tolerance, such as Methylobacterium radiotolerans (Noguiera et al., 1998; Rokitko et al., 2003). Members of Methylobacterium also possess plant-growth promoting (Abanda-Nkpwatt et al., 2006; Kutschera et al., 2007) and nitrogen fixing capabilities (Renier et al., 2008), revealing that shifts in the composition of rhizospheric bacteria have the possibility to be neutral or even have positive effects on plant regeneration. A previous LTSP study found no differences in the rhizospheric bacterial populations of lodgepole pine seedlings in a comparison of OM2 and OM3 (Chow et al., 2002), though this study may have missed the larger effect between unharvested and harvested plots. Future study of the impacts of harvesting on EM fungi may be complemented by considerations of the potential impacts on rhizospheric bacteria. Given the scale of forestry operations in North America and threat of greenhouse gas-induced climate change, one of the most serious consequences of timber harvesting may be the sizeable reduction of methane oxidation by soil-borne methanotrophs. Temperate forest soils are significant atmospheric methane sinks due to these populations (Henckel et al., 2000; Kolb et al., 2005) and harvesting has been widely reported to decrease methane uptake over the short (Castro et al., 2000; Zerva and Mencuccini, 2005; Takakai et al., 2008; Kulama et al., 2014) and long term (Wu et al., 2011; Nazaries et al., 2011). In one case, this phenomenon was attributable to declining abundances of Methylocapsa-related, type-II methanotrophs (Nazaries et al., 2011), which was a major trend in harvested plots across all ecozones in the present research. No explanation for this phenomenon has yet been proposed, though analysis performed for this thesis revealed that Methylocapsa were more abundant in upper organic layer soil and negatively correlated with pH (r=-0.39, p < 0.001). It is reasonable to suspect that these populations may be adversely affected by exposure to the warmer, drier soils and compounded by the slight increase of pH found at harvested plots. Notably, in two ecozones, PPCA and JPON, the retention of woody debris in OM1 had a net positive effect on population sizes, and, overall, retention was seen to mitigate the decline of Methylocapsa. Further research is needed to understand what is driving the decline of Methylocapsa and whether biomass retention may be a viable mitigation strategy. The long-term rise of stress-tolerant groups in harvested plots, reported here, resembled the compositional shifts found in the decades following forest fire. Both types of disturbance did not alter overall diversity, as the expansion of heat-tolerant taxa did not dominate communities, nor did susceptible taxa disappear altogether, as evidenced in repeated burnings of forests plots (Oliver et al., 2015). Further, the decline in relative abundance of Basidiomycota in favour of Ascomycota was consistent with long-term changes in fire-affected soils (Buscardo et al., 2015; Holden et al., 2013b). The expansion of arbuscular mycorrhiza, from phylum Glomeromycota, in BSON (undetected in REF and ~1% of total reads in OM3) was consistent with their rapid rebound post-fire (Xiang et al., 2015). The decrease in Verrucomicrobia (Spartobacteria & Opitutus) observed among a majority of ecozones was consistent with their decreased abundances in fire-affect soils upwards of seven-years post-fire (Tas et al., 2014; Weber et al., 2014). One of the most notable similarities between the two disturbances was the sizeable expansion of populations of candidate phylum AD3, which quadrupled in OM3 of JPON (~ 8% of the total library) and was a major finding of Tas et al., (2014) where AD3 populations had expanded by ~ 68% seven years after forest fire. Nothing is known about the ecology or physiology of AD3, but this research suggests they may possess adaptations to post-disturbance conditions or may be associated with the rhizosphere of ruderal plant species, given the similar pattern of expansion in plant mitochondrial and chloroplast DNA in JPON (Figure B.1). Soil microbial diversity decreased in forested land converted to agricultural use (Rodrigues et al., 2013; Paula et al., 2014), yet comparisons between primary and secondary forests typically note no discernible changes in diversity (Lauber et al., 2008; Paula et al., 2014; Štursová et al., 2014; Oliver et al., 2015). The impacts of timber harvesting on microbial diversity reported here were also not striking. The only consistent trend was the increased diversity of fungal populations in mineral soils at all harvesting intensities for five out of six ecozones. In every case, the increase in diversity was driven by an increase in both species richness and the evenness of populations. McGuire et al., (2014) found a similar, though slight, increase in fungal diversity in a 50-year-old secondary forest relative to unharvested controls, but there is a paucity of data on this potential phenomenon and no proposed explanation as of yet. Globally, biodiversity is strongly correlated with temperature purportedly due to the kinetics of biochemical reactions (Allen et al., 2002). In one study of fungal populations, higher mean annual temperature was the main driver of increased diversity in forest soils along an altitudinal gradient (Bahram et al., 2011). It is possible that the increased diversity in mineral soil fungal populations may be driven by increased temperature, though it is unclear why organic layer populations do not exhibit a similar trend. Hartmann et al., (2012) hypothesized that increased fungal evenness in harvested plots (diversity was not described) may relate to a loss of functional organization, due to the loss of EM and expansion of more diverse saprotrophic populations. Yet, the two ecozones exhibiting the greatest increase in overall fungal diversity in mineral soils (SBSBC and JPON) did not exhibit significant or exceptionally strong changes in EM abundance or diversity among harvested plots. In cellulose incubations, the decreased richness of 13C-enriched fatty acids with increasing organic matter removal was another indication that harvesting can reduce the diversity of other sub-populations than just EM fungi. However, this trend may or may not reflect the actual diversity of cellulolytic taxa given that lower richness of 13C-labeled PLFAs could also result from a reduced interdependency of organisms feeding on cellulolytic organisms or their by-products, suggesting, rather, a degree of decreased trophic complexity. Trends in diversity have unclear implications on the long-term impacts of timber harvesting, though diversity has been linked to the robustness of soil processes (Griffiths and Philippot, 2013), and may be of secondary importance to studying the nature of change brought about by shifts in specific taxa. The distinct composition of microbial communities among ecozones was a source of ecozone-specific responses to harvesting. Localized responses were mainly the result of differences in the relative abundance, even presence or absence, of taxa among ecozones. The irregular distribution of many taxa was expected given the large differences in edaphic factors, historical soil development and plant overstory among ecozones. A recent biogeographical survey of Streptomyces, part of the same family as Kitasatospora, found species distributions were affected by latitude, which was attributed to the last glaciation (Choudoir et al., 2016). This study reveals geography can play a major role in species distribution across the continent, a feature which was evident in our data. Kitasatospora exhibited variation in species and response to harvesting according to east and west populations, perhaps resulting from the boundary presented by the Columbian mountain range. The impacts of harvesting on any given population may also vary depending on changes in local environmental conditions (climate, soil type etc.) brought about from harvesting. For example, populations of Boletales showed stark increased in harvested plots in northern ecozones, yet declined in southern locations. A plausible explanation for this pattern might be that soil warming in northern climes had a positive effect on organisms with higher temperature growth optima, but temperature extrema rose above tolerance thresholds in southern sites. Differences in response to harvesting between closely-related species suggests that ecotypic variation may be factor in localized responses. Ecotypic variation in genome content may confer different tolerance traits and has been commonly observed among organisms sharing highly similar (Rocap et al., 2003) or even identical copies of the 16S rRNA gene (VanInsberghe et al., 2015). However, the impacts of such variation are rarely considered in broad characterizations of disturbance on microbial communities. Youngblut et al., (2012) found that species and strain level responses to disturbance played an important role in the potential ecological impacts of disturbance. Timber harvesting produced different responses among a number of closely related genera (Pseudotomentella spp. and Tomentella spp.) and species (within Kitasatospora, Rhizopogon and Suillus), demonstrating the necessity of both fine-scale and broad characterizations of community structure. Focusing attention on resolving fine-scale phylogenetic has the secondary benefit of identifying novel phenotypes, aiding both our understanding of the physiology of forest soil microorganisms and disturbance ecology. The degree to which biogeographical differences may limit generalizations about the long-term effects of harvesting was evident in the absence of many common trends in LPTX. No remarkable differences in the abundance or diversity of EM fungi or relative abundances of Basidiomycota and Ascomycota were observed in LPTX, which were major features of all other ecozones. LPTX was the only ecozone in which harvesting treatments were insignificant in explaining variation in fungal populations. LPTX was an outlier in terms of other broad trends such as the expansion of candidate phylum AD3 and unclassified sequences as well as the decline of Verrucomicrobia. The distinctive lack of common trends observed in LPTX mirrors the general distinctiveness of its community which had double the number of unique bacterial taxa (7,400) relative to other ecozones and the second highest number of unique fungal taxa. Lignocellulolytic populations, described in Chapter 4, were also largely unique in LPTX. Conditions in LPTX soils were markedly different, containing less than half the total C and total N found at other sites and had the most acidic of any mineral layer soil. The conditions, coupled with the fact LPTX had the lowest soil moisture content and highest mean annual temperature, suggest that the microbial community may be composed of taxa already adapted to the harsher conditions caused by harvesting. Another critical consideration is that LPTX REF plots were the only plots that had been previously harvested (~75 years prior to sampling), and still exhibited signs of past disturbance such as skid roads (Andrew Scott, USDA, personal communication). Historically, the LPTX forests have been managed with fire for many hundreds of years by humans and are also prone to lightning fires (Andrew Scott, USDA, personal communication). The lack of clear distinction between REF plots and harvested plots in LPTX may exemplify the equilibration of soil communities to long-term exposures to disturbance (i.e. a perpetual disturbed state). A third explanation, none of which are mutually exclusive, may be that microbial communities have rebounded more quickly to a pre-harvest conditions due to the faster forest regeneration observed at LPTX sites (Ponder et al., 2012), where trees reach maturity in approximately half the time (~ 25 year cycles). Thus, LPTX exemplifies how biogeographical factors and land-use legacy can influence the potential impacts of harvesting. As a case study, LPTX may help reveal which organisms and microbial process have the greatest effect on regeneration by correlating differences in community composition with measures of forest productivity in perpetually disturbed and less disturbed sites. One important caveat to consider when interpreting data presented in Chapter 3 is that OM removal affected the depth of organic layer soil development. Therefore, abundances in organic soils from harvested plots were unavoidably weighted towards surficially abundant taxa. This distortion would likely favour taxa adapted to radiation, desiccation and heat which would thrive in surficial soil. Yet, stress-tolerant taxa also flourished in mineral layer soils including a number of desert-dwelling taxa, such as Ramlibacter, Lysobacter, Rubrobacter and Clostridium, and thermophilic fungi. Soil temperature was elevated along the full depth profile and, presumably, so too was higher degree of dryness, though the mineral samples processed did not notably differ in moisture content. In future, this bias may be avoided by sampling more finely along the soil profile. Substantiating the SIP method, the majority of taxa we identified (~75%) had previously documented cellulolytic activity, including well-characterized groups such as Actinobacteria, Bacteroidetes, Cytophaga Myxococcales and Sordariomycetes. The greatest number of novel cellulolytic taxa were associated with mineral layer soil, which, in our microcosms, demonstrated comparable cellulolytic activity to organic layer populations. These novel taxa included Armatimonadetes from candidate division FBP, with no representative genome or isolate, and members of the ubiquitous, yet poorly characterized phylum, Candidatus Saccharibacter (formerly TM7), of which we were able to recover a partial draft genome (~0.4 Mb). Other members of Armatimonadetes, as well as members of Verrucomicrobia and Planctomycetes, were also designated cellulolytic and associated with the mineral layer. These three groups have few cultured representatives, but at least one of each is known to degrade cellulose (Sangwan et al., 2004; Dedysh et al., 2013; Lee et al., 2014). Populations of fungal of cellulose-degraders were represented by largely well-known saprotrophic fungi, such as Clitopilus, Humicola, Myceliopthora and Chaetomium. The identification of members of Sebacinaceae, a group of saprobic and mycorrhizal fungi, as cellulolytic was novel, but consistent with circumstantial evidence that Sebacinaceae played a role in decomposition of maize lignocellulose in agricultural soils (Kuramae et al., 2013). Our research builds upon previous studies that demonstrated a consistent long-term impact of timber harvesting on forest soil microbial communities. Here, we provide evidence that organic matter removal during harvesting impacted soil populations, in particular at the extreme in OM3, and that changes in soil physical properties, such as temperature and moisture content, may be equal to or more important than changes in organic matter quality in mediating this impact. Canopy closure had occurred in the years immediately prior to sampling in most ecozones. Thus, sampling occurred at a time just after soils experienced the longest period of heightened exposure to solar radiation, soil drying and temperature. Outside of groups with known importance to forest ecology, such as EM fungi, the impacts of shifting microbial populations during these first decades of regeneration are unknown. In the case of stress-tolerant taxa, any impact will likely depend on their sustained activity as forests mature and whether they persist across harvesting cycles. The potential legacy effect could be strong. For example, in cellulolytic populations, the early colonization of decaying woody debris can influence succession and ultimately the quality of decomposition (Song et al., 2015). Further, the totality of the changes brought about by timber harvesting are far from clear, exemplified by the expansion of unclassifiable sequences in harvested plots. As such, this work contributes a foundation upon which future research can build towards better understanding the impacts of forest disturbance and what soil processes underlie variation in forest regeneration across North America. Chapter 4: Survey of Lignocellulolytic Populations of Forest Soils from Across North America with Stable Isotope Probing 4.1 Rationale The following section describes a broad survey of hemicellulolytic, cellulolytic and lignolytic populations from soil layers and ecozones previously described in Chapter 3. Samples were selected to maximize the diversity of lignocellulolytic taxa observed in order to i) attribute activity to an array of novel uncultured taxa, ii) assess the prevalence of previously characterized taxa in an environmental context; iii) determine if the overall rate of decomposition during incubations was correlated with community composition; and iv) study the biogeography of the decomposer communities. The contributions of bacterial and fungal degraders were contrasted given the recent evidence that bacterial lignin-degrading activity may be underestimated (Bugg et al., 2011). All three major polymers of lignocellulose were tested in hope of identifying taxonomic groups that possess specialization for the degradation of recalcitrant plant matter. 4.2 Results SIP-microcosms amended with 13C-labeled bacterial cellulose (99 atom % 13C) were performed on samples from all ecozones except SBSBC, while SIP-lignin (DHP-lignin; 75 atom % 13C) was performed only on PPCA, BSON and LPTX and SIP-hemicellulose only on IDFBC and PPCA. All datasets utilized in Chapter 4 are summarized in Table E.4. In brief, DNA from SIP-cellulose and SIP-lignin microcosms was sequenced to produce: i) 59 cellulose and 64 lignin pyrotag libraries (~ half 12C-controls) averaging 8,400 high-quality 250-bp reads per sample; ii) 100 corresponding PLFA profiles (including 12C-controls); iii) 38 cellulose and 46 lignin shotgun metagenomic libraries with an average of 86 million and 56 million quality filtered 100 bp reads per library, respectively, and iv) eight shotgun metagenomic libraries from mineral soil incubated with 13C-lignin with or without fungicide, averaging 63 million reads per library. All raw sequencing libraries can be found at the European Sequencing Archive under the project accession PRJEB12502. Pyrotag libraries were supplemented with 50 SIP-hemicellulose libraries (~ half 12C-controls) from Leung et al., (2016) and 94 ‘in situ’ libraries from corresponding reference field samples from Chapter 3. 4.2.1 Characterization of 13C-Enrichment by Substrate, Soil Layer and Ecozone Time-course experiments revealed low-level enrichment as early as four days into incubations with labeled cellulose and lignin (Figure 3.26). The enrichment of microbial biomass (DNA and PLFA) was comparable between organic and mineral layers in cellulose (~ 15% atom C% in DNA), while enrichment occurred more gradually from lignin and was lower in the modified organic soils than in mineral soils, at 8 and 11 atom C% DNA, respectively (Figure 4.1). Measures of enrichment in DNA and PLFA were in close agreement, demonstrating that organisms assimilating 13C were growing and replicating. Improved assembly of metagenomes derived from 13C-enriched DNA demonstrated a reduced diversity of genomic content, indicative of a selection for sub-populations (Figure 4.2). The 13C-enrichment of microbial biomass was comparable among ecozones except for a few stand-out cases. The assimilation of cellulose was considerably greater in IDFBC than in any other organic layer soil. Cellulolytic and lignolytic taxa from LPTX mineral soil had the highest activities of any lignocellulolytic populations. Notably, the quality of assembly for these stand-out samples was lower than other samples (Figure 4.2), possibly resulting from the higher proportion of fungi found at these sites whose larger, more complex genomes were less readily assembled (see section 4.2.4). Of the initial eighty-four microcosms incubated with 13C-lignin, approximately ¼ of lignin samples did not yield sufficient DNA or sufficiently clean DNA for PCR amplification and approximately half of metagenomic library preparations failed. Texan soils, in particular, contained high levels of inhibitory compounds which were partly remedied for PCR by diluting template DNA. However, this was not an option in preparing metagenomic libraries due to concentration requirements. A polyvinylpyrrolidone treatment was attempted, but did not help. Despite comparable levels of enrichment in soil DNA extracts from both cellulose and lignin microcosms, the net recovery of 13C-enriched DNA from lignin was far lower than from cellulose (Figure 4.3). Low DNA yields for lignin samples necessitated the use of Nextera XT library preparation which required only 1 ng of DNA. A comparison between the Nextera and Nextera XT prep kits demonstrated the two methods were comparable and that the ability to pool fewer fractions, afforded by the XT kit, resulted in greater differentiation between 12C- and 13C-libraries (Figure 4.4). The assimilation of 13C-carbon by non-functional populations (i.e. cross-feeding) was not apparent in preliminary time-course experiments. Assuming that PLFAs lacking enrichment at Day 4, when the active community had already become slightly enriched, represent the non-functional community (also likely the slow growing functional community), the total enrichment of ‘non-functional’ PLFAs was less than 5% by the end of the time course. Select PLFAs showed increasing enrichment over-time, while a broad pattern of progressive enrichment, what might be indicative of cross-feeding, was not observed (Figure 4.5). However, in experimentation with fungicide, the co-decline of fungal and bacterial enrichment suggested cross-feeding (see section 4.2.4 for more details). Figure 4.1. Overview of the 13C-enrichment of microbial biomass according to substrate, ecozone and soil layer in delta-13C in PLFA (A) and % atom 13C in soil DNA extract (B). In panel A, control microcosms incubated with 12C-compounds are shaded pink. Figure 4.2. Comparison of metagenome assembly according to substrate, ecozone and soil layer as evidence for the selection of lignocellulolytic subpopulations and decrease in overall complexity in SIP metagenomes. Figure 4.3. Average mass of DNA recovered from the densest CsCl gradient fractions according to substrate. Identical patterns were observed in both mineral and organic soil layers. Pyrotag and metagenomic libraries were created from DNA recovered from F1-7, though additional fractions had to be pooled to recover sufficient DNA for the occasional 12C-control library. Figure 4.4. Comparison of metagenomic libraries prepared using either ‘Nextera’ (50 ng DNA) or Nextera ‘XT’ (1 ng DNA) kits based on LCA classification of unassembled reads at the rank order. Two samples incubated with lignin were arbitrarily selected and fractions heavy fractions were sequenced from 12C and 13C-pairs. In order to recover 50 ng of DNA for ‘Nextera’ prep, fractions F1-F9 were pooled, while fractions F1-F7 were used for ‘XT’. Only taxa occupying greater than 0.5% of total library are shown. Taxa found in both 12C and 13C-libraries are coloured solid, while taxa only found in 13C-libraries in black and white pattern. Figure 4.5. Heat map of the normalized delta-13C enrichment of PLFAs across time-course experiments for both soil layers and substrates. Each time-point is represented by a single sample. Samples were sacrificed, not repeatedly sampled. 4.2.2 Comparison of Hemicellulolytic, Cellulolytic and Lignolytic Taxa Among 16S rRNA gene pyrotag libraries, 13C-cellulose and 13C-lignin libraries shared few common OTUs with in situ libraries and even fewer with 13C-hemicellulose libraries based on clustering at 0.01% (Figure 4.6A). Conversely, in situ and 13C-hemicellulose libraries shared substantial overlap. More overlap was observed based on taxonomic classifications of genera (Figure 4.6B). The alignment of all pyrotag libraries was manually validated and, while sequencing libraries were prepared by different people, the same methods, primer stocks, and sequencing facility were used and raw files were processed concurrently in Mothur. Differences may be explicable given the substantially shorter incubation period used for hemicellulose (2 days) versus cellulose (~14 days) versus lignin (~60 days), as well as the possibility that SIP substrates enriched for largely different functional populations. Figure 4.6. Venn diagrams depicting overlapping OTUs (A) and genera (B) among 13C- and in situ pyrotag libraries for all lignocellulose substrates. Differences existed between populations decomposing lignin and cellulose polymers based on profiles of PLFA 13C-enrichment (Figure 4.7; hemicellulose data not available). The most discriminating feature between cellulose and lignin-degrading populations was the enrichment of fungal PLFAs (c18:1Ω9 and c18:2Ω6) and a number of longer chain PLFAs associated with eukaryotes (likely fungal) in cellulose microcosms. The prominence of fungi in SIP-cellulose samples, and relative absence in SIP-lignin samples, was supported by metagenomic data (Figure 4.8). Markers for Gram-positive bacteria (branched PLFAs i16:0 and i17:0) were also correlated to 13C-cellulose PLFA profiles, whereas one Gram-negative PLFA (3OH-c14:0) was correlated to 13C-lignin profiles in organic soils. These differences in the utilization of cellulose and lignin were reflected in the prevalence of Actinobacteria (Gram-positives) in 13C-cellulose pyrotag libraries and Betaproteobacteria and Alphaproteobacteria (Gram-negatives) in 13C-lignin pyrotag libraries (Figure 4.9). Cellulolytic and lignolytic populations were also discriminated by unidentifiable PLFAs (‘UF’; i.e. PLFAs not present in the standard used for peak identification). Lignin-degrading taxa from LPTX soils were substantially different than degraders from other ecozones, consistent with observations throughout this thesis of the unique community therein. NMS of pyrotag libraries reinforced a number of differences between cellulolytic and lignolytic populations and helped further identify which groups were driving differences (Figure 4.10). 13C-cellulose libraries demonstrated greater clustering and diverged more clear from their paired 12C-libraries in contrast to lignin libraries. Burkholderiales and Caulobacterales were clearly associated with, and more abundant in, both 13C-cellulose and 13C-lignin libraries. Other groups that clustered with 13C-cellulose libraries included Cytophagales, Opitutales (Verrucomicrobia), FW68 (Armatimonadetes), BD7-3 (Planctomycetes), Myxococcales (Deltaproteobacteria) and Actinomycetales. Groups that clustered with 13C-lignin libraries (left side and bottom of Figure 4.10) included Elusimicrobiales and FAC88 (Elusimicrobia), Solibacterales and iii1-15 (Acidobacteria), Gaiellales and Solirubrobacterales (Actinobacteria) and Sphingomonadales (Alphaproteobacteria). Figure 4.7. Principal components analysis of delta-13C enrichment of PLFAs for cellulose and lignin and both soil layers. All included samples were amended with a 13C-labeled substrate (i.e. controls not included). Vectors were fitted for individual PLFAs to illustrate the relative contributions to the differentiation of enrichment profiles. Figure 4.8. Abundances of Ascomycota and Basidiomycota in metagenomic libraries. Error bars correspond to one standard error of the mean. Figure 4.9. Abundances of prominent bacterial phyla (classes) according to differential abundance in 12C- and 13C-pyrotag libraries for hemicellulose, cellulose and lignin among ecozones. Error bars correspond to one standard error of the mean. Figure 4.9 continued… Figure 4.10. Non-parametric multidimensional scaling plots depicting differences in composition of 12C- and 13C- pyrotag libraries for cellulose and lignin. Bray-Curtis dissimilarities among samples were calculated from OTU count matrices and plotted with coloured x’s corresponding to samples (blue: 13C; pink 12C) and with taxa corresponding to circles scaled to average abundances in 12C (pink) or 13C (blue) libraries. 12C- and 13C-cellulose libraries were delineated by a single dotted line. All 13C-pyrotag libraries were enriched in a number of bacterial classes not common in 12C-libraries with notable differences among these groups according to substrate and soil layer (Figure 4.11). Yet, a large number of putatively lignocellulolytic bacterial classes were common in both 12C- and 13C- libraries and differed only at lower taxonomic ranks. For example, the differential abundance of certain families of Alphaproteobacteria, such as Caulobacteraceae, was obscured by the widespread abundance of Bradyrhizobiaceae in all samples, a group which was not implicated in decomposition of any lignocellulosic substrate. A combination of DESeq2 and indicator species analysis was used to assign putative lignocellulolytic function to differentially abundant taxonomic groups in 13C-pyrotag and metagenomic libraries (Table 4.1). Members of Burkholderiales and family Caulobacteraceae exhibited marked assimilation of 13C-label from all three substrates. All three major families of Burkholderiales, namely Burkholderiaceae, Comamonadaceae and Oxalobacteraceae, possessed taxa differentially abundant in 13C-pyrotag libraries (Appendix Figure C.6). In the family Caulobacteraceae, the genus Asticcacaulis exhibited activity on both hemicellulose and cellulose, while Caulobacter demonstrated the capacity to degrade all three (Figure 4.12). Putatively cellulolytic OTUs were spread throughout the Asticcacaulis clade (not shown), whereas OTUs assigned to Caulobacter and other unclassified Caulobacteraceae formed relatively cohesive clades (Figure 4.13). Lignolytic Caulobacteraceae grouped into four clades (‘L1’ - ‘L4’), while one cluster of cellulose and hemicellulose-degrading Caulobacter was identified (‘CH’). Lignolytic clades were more abundant in mineral soils (µorg=6.0, µmin=21.5; p=0.02), whereas their outgroups (i.e. closely related clusters of OTUs that did not show any or, in some cases mixed, enrichment) were more abundant in organic soils (µorg=3.0, µmin=1.4; p < 0.001). Figure 4.11. Abundant classes of bacteria in pyrotag libraries according to substrate and soil layer. Taxa are organized into groups based on whether they were common to 12C-libraries (muted, solid colour), common to 13C-libraries (patterned), or specific to either organic and mineral horizon (solid colour). Only classes occupying more than 0.5% of the total library are displayed. Table 4.1. All putatively hemicellulolytic, cellulolytic and lignolytic taxa based on differential abundance between 13C and 12C-pyrotag or metagenomic libraries. Best classifications have been given with the prefix corresponding to taxonomic rank. The in situ abundance of each taxon is represented by a scaled circle which has been coloured according to whether the taxon was differentially abundant for a given substrate in that ecozone. White circles indicate data was not gathered for that ecozone (both SIP-hemicellulose and SIP-lignin experiments use a subset of ecozones) and grey circles indicate data existed, but the taxon was not enriched in 13C-libraries from microcosms in that ecozone. The total number of enriched OTUs are given as well as the averaged ratio of abundance in 13C- by 12C-libraries for each taxon (not each OTU) and each substrate where differentially abundance was observed. Additional information can be found in Table E.12. Table 4.1 continued… Figure 4.12. Abundances of all prominently hemicellulolytic, cellulolytic and lignolytic genera of Caulobacteraceae based on differential abundance between 12C- and 13C-pyrotag libraries. Figure 4.13. Maximum parsimony tree showing phylogenetic distribution of lignocellulolytic OTUs within the family Caulobacteraceae. Clades are named based on SILVA tree and custom names were assigned to putatively functional clades. Branches were coloured to indicate membership to broader clades inset at the top left. The closest cultured represtatives were included where possible. Partial draft genomes classified to Caulobacteraceae accounted for over half of all drafts recovered from 13C-lignin and approximately a quarter from 13C-cellulose libraries (Figure 4.14). Of the drafts recovered for cellulolytic Caulobacteraceae, 40% were classified as Asticcacaulis, 53% as Caulobacter, while drafts recovered from lignolytic taxa were 95% Caulobacter. Similar differences between cellulolytic and lignolytic Caulobacteraceae were found based on CAZy content (section 4.2.3). The bacterial genera with the greatest enrichment in 13C-hemicellulose libraries were Agrobacterium, Bacillus, Paenibacillus, TM7-3 and Streptomyces and included taxa also active on cellulose, such as Cellvibrio, Janthinobacterium, Cytophagaceae and Salinibacterium. The most notable cellulose-degraders were from candidate division FBP and order FW68 within Armatimonadetes, which were highly enriched across all ecozones, though were low abundance in situ. Novel putatively lignolytic bacteria were classified to poorly characterized taxonomic groups, such as acidobacterial groups 2 (Ellin6531), 3 (Solibacterales) and 6 (iii1-15), Elusimicrobia, and Sinobacteraceae, as well as to a number of taxa available in culture collections, such Bradyrhizobium canariense (‘Bosea’ in Table 4.1), Altererythrobacter dongtanensis (‘Erythrobacteraceae’), Aquaspirillum polymorphum (‘Telmatospirillum’), and Cystobacter gracilis (‘Cystobacteraceae’). Descriptions and detailed phylogenetic affiliations of lignocellulolytic taxa can be found in Appendix C. No single OTU possessed activity on all three substrates, which reflects the low degree of overlap with hemicellulolytic libraries. A custom search for OTUs differentially abundant for multiple substrates within a given ecozone yielded a total of five OTUs putatively active on lignin and cellulose, which were related to Simplicispira (Burkholderiaceae), Aquincola (Comamonadaceae), Caulobacteraceae spp. (clade ‘LH3_1’) and two Sinobacteraceae spp. (Figure 4.15). Figure 4.14. Overview of information on top quality draft genomes recovered from 13C-cellulose and lignin libraries, including a list of all top quality genomes recovered (< 40% ‘contamination’ and >80% ‘completeness’), an overview of bin characteristics derived from CheckM, and the LCA taxonomic classifications of all draft genome bins. Points shaded red in the scatterplots correspond to the listed top quality drafts. The following colours were used to code substrate, ecozone and horizon: off-white (cellulose), dark gold (lignin); purple (BCIDF), blue (O.N. ecozones), yellow (PPCA), orange (LPTX); dark brown (organic layer) and light brown (mineral layer). [Figure Appears on Next Page] Figure 4.15. Abundances plots of OTUs enriched in both lignin and cellulose 13C-pyrotag libraries within the same ecozone. Plots are labeled with the lowest taxonomic classification supported and with representative read names. Where two OTUs were combined, both independently exhibited the trend in multiple substrate use. Fungal taxa were characterized using metagenomic libraries (ITS pyrotag libraries were no prepared) based on LCA classification. Distinct clustering of 12C- and 13C-libraries as well as cellulose- and lignin-degrading taxa occurred based on taxonomic profiles at both the rank order and genus (Figure 4.16). Ophiostomatales and Magnaporthales (Ascomycota) and Agaricales (Basidiomycota) were enriched in 13C-cellulose libraries, while Malasseziales and Ustilaginales (both Basidiomycota from class Ustilaginomycotina) were enriched for in 13C-lignin libraries. Members of the order Hypocreales were abundant in both 12C- and 13C-libraries (0.04% and 0.2% of total metagenomes, respectively), but genera within Hypocreales, such as Trichoderma, Verticillium, Ophiocordyceps and Fusarium, were differentially abundant in 13C-cellulose libraries. Ascomycota were highly abundant in 13C-cellulolytic libraries, including members of the Sordariales, such as Chaetomium, Myceliophthora and Neurospora, as well as other groups, such as Arthrobotrys and Cladophialophora (Table 4.1). While Ascomycota were far more differentially abundant than Basidiomycota in 13C-cellulose libraries, a number of putatively cellulolytic Basidiomycota were identified, namely: Piriformospora, Trichosporon, Cryptococcus, Coprinopsis, Schizophyllum and Laccaria. The only fungal family differentially abundant in 13C-lignin libraries was Saccharomycetaceae (Appendix C; Figure C.3). Saccharomycetaceae were not differentially abundant in cellulose libraries and were the only fungal group to be associated with mineral soil (~2-fold more abundant therein). A necessary caveat regarding LCA-based classifications is that reads originating from a single genome may be artificially classified to separate genera due to the lack of specificity of BLAST-based homology searches used in LCA classification. This phenomenon was apparent in closely related genera (i.e. within a family) which frequently had nearly identical abundance patterns across ecozones and between 12C- and 13C-libraries, making it difficult to positively identify to which genus the reads actually belong (Appendix C; Figure C.5). Figure 4.16. Heat map of the relative abundance of the most populous fungal orders (A) and genera (B) based on LCA classification of unassembled metagenomic libraries. Clustering was performed on Bray-Curtis dissimilarity of samples (x-axis) and taxa (y-axis). Read counts were normalized prior to clustering. 4.2.3 Carbohydrate Active Enzymes in Cellulolytic and Lignolytic Populations CAZyme genes related to cellulose and lignin degradation were expanded in unassembled 13C-metagenomes. All endoglucanase containing GH families were between 1.3 and 32-fold more abundant in 13C- than in 12C-cellulose libraries (Table 4.2). A substantial number of ‘Auxiliary Activity’ families containing lignin-modifying enzymes were also enriched in 13C-cellulose libraries, such as iron reductase domains (AA8) and lytic polysaccharide monooxygenases (AA9, AA10, A11, & AA13). For DHP-lignin libraries, the majority of all endoglucanases and AA families were actually depleted in 13C- relative to 12C-libraries, with genes from only three endoglucanases (GH7, GH12 & GH26), and vanillyl-alcohol oxidases (AA4) more abundant in 13C-libraries (Table 4.2). However, when read sets annotated to AA families were subsetted to contain only families previously designated as lignolytic (Table 4.1), a number of AA families were more abundant in 13C-libraries (Figure 4.17). Laccases (AA1), oxidases (AA3, AA4 & AA7) and quinone-dependent oxidoreductases (AA6 & AA12) were largely bacterial, while peroxidases, iron reductase domains and most lytic polysaccharide monooxygenase families were fungal (Figure 4.17). CAZy family abundance profiles differed between 13C-cellulose and 13C-lignin metagenomic libraries (ANOSIM: R=0.08, p=0.004), but not between soil layers or among ecozones. CAZy composition did not significantly covary with taxonomic composition according to a Mantel test on Bray-Curtis dissimilarities (r=-0.07; p-value=0.91). However, a variety of samples formed distinct groups based on substrate, ecozone and horizon when samples were clustered (Figure 4.18a). The clustering revealed the co-occurrence of a number of CAZymes within certain ecozones (see ‘hotspots’ in Figure 4.18b) indicative of the prevalence of certain functional taxa present there. Table 4.2. Overview of abundances of GH families containing characterized endoglucanases and ‘Auxiliary Activity’ enzymes with known lignin-modifying activity. Abundances correspond to the average counts per million reads (RCPM) in unassembled metagenomic libraries. The percentage of libraries in which a given GH or AA family were detected is given. The rounded ratio of counts in 13C- relative to 12C is provided. 12C-lib % lib 13C-lib % lib 13C:12C 12C-lib % lib 13C-lib % lib 13C:12CAA1 0.96 ±0.3 100 1.33 ±0.2 100 1.0 7.22 ±1.4 100 3.21 ±0.5 100% 0.5AA2 0.02 ±0.0 50 0.2 ±0.1 82 13.0 0.72 ±0.6 38 0.03 ±0.0 39% 0.04AA3 4.57 ±0.6 100 9.3 ±1.2 100 2.0 15.27 ±2.4 100 14.84 ±4.6 100% 1.0AA4 0.29 ±0.1 100 0.85 ±0.2 100 3.0 4.86 ±1.5 100 16.02 ±3.1 100% 3.3AA5 0.24 ±0.1 100 0.37 ±0.1 93 1.6 0.39 ±0.1 75 0.13 ±0.1 84% 0.3AA6 1.15 ±0.1 100 3.14 ±0.4 100 2.7 5.65 ±1.0 100 6.18 ±1.8 100% 1.0AA7 3.05 ±0.3 100 2.53 ±0.4 100 0.8 8.73 ±1.8 100 2.72 ±0.6 97% 0.3AA8 - 6 0.36 ±0.1 39 - - 0 - 5% -AA9 0.04 ±0.0 40 1.93 ±0.7 75 55.0 0.88 ±0.8 31 0.03 ±0.0 32% 0.04AA10 0.26 ±0.1 100 0.74 ±0.3 100 2.8 1.79 ±0.5 94 0.38 ±0.1 97% 0.2AA11 - 10 0.4 ±0.2 57 38.7 1.19 ±1.6 13 0.03 ±0.0 11% 0.03AA12 1.49 ±0.2 100 3.13 ±0.4 100 2.1 8.28 ±1.8 100 4.55 ±0.7 97% 0.6AA13 - 0 0.21 ±0.1 43 - 0.13 ±0.1 19 0.02 ±0.0 5% 0.1GH5 0.68 ±0.2 100 1.88 ±0.4 100 2.8 1.87 ±0.4 100 0.77 ±0.1 97% 0.4GH6 0.62 ±0.1 100 1.66 ±0.6 96 2.7 1.23 ±0.3 94 0.35 ±0.1 92% 0.3GH7 0.03 ±0.0 40 0.88 ±0.3 86 28.3 0.02 ±0.1 19 0.04 ±0.0 24% 1.6GH8 0.45 ±0.1 100 1.55 ±0.3 100 3.4 3.67 ±2.3 88 3.19 ±2.7 100% 0.9GH9 1.41 ±0.4 100 4.69 ±0.6 100 3.3 10.61 ±3.2 100 2.28 ±0.5 97% 0.2GH12 0.16 +0.1 100 0.67 ±0.1 100 4.2 0.23 ±0.1 63 0.37 ±0.1 95% 1.6GH26 0.65 ±0.1 100 0.83 ±0.2 100 1.3 2.18 ±0.6 94 4.02 ±3.7 100% 1.8GH44 0.25 ±0.1 100 0.42 ±0.1 100 1.6 3.14 ±1.0 100 0.71 ±0.1 97% 0.2GH45 - 10 0.11 ±0.1 75 10.4 0.34 ±0.4 13 0.01 ±0.0 11% 0.04GH48 0.06 ±0.0 100 0.09 ±0.0 79 1.3 0.26 ±0.2 56 0.06 ±0.0 63% 0.2GH51 2.84 ±0.8 100 7.54 ±0.9 100 2.7 20.31 ±4.3 100 5.68 ±0.8 97% 0.3GH74 1.89 ±0.4 100 2.48 ±0.4 100 1.3 11.42 ±2.2 100 3.08 ±0.8 97% 0.3GH81 0.19 ±0.1 100 1.0 ±0.4 100 5.4 0.42 ±0.1 81 0.05 ±0.0 66% 0.1GH131 - 10 0.33 ±0.1 61 32.7 - 0 - 0% -CAZy FamilyCellulose Lignin Figure 4.17. Characterization of metagenomic reads annotated as lignin-modifying, ‘Auxiliary Activity’ (AA) families illustrating (A) the differential abundance of AA families summed for all putatively lignolytic families identified in pyrotag analysis (Table 4.1) and (B) the largely bacterial classification of all AA genes found in SIP-cellulose or SIP-lignin metagenomes. [Note: In Panel A, lignin families AA2, AA8, AA9 and AA13 are present at low abundances and exclusively in 13C-libraries.] The taxonomic profiles of CAZymes clustered in ‘hot spot 1’, namely CBM41, CBM12, GH6 (a family of strict endoglucanases) and CBM16, were consistently assigned to Actinomycetales (Streptomycetaceae) in Californian samples BR067, BR068 and LH020 (Figure 4.18b). In contrast, these families were classified to groups of Proteobacteria in samples comprising ‘hotspot 2.’ However, not all CAZymes that clustered within a given hotspot were taxonomically uniform, such as CBM18 and CBM1 (‘hotspot 1’), which were largely from Ascomycota (Figure 4.18b). The BSON sample treated with fungicidal compounds, “A7 (Antibiotic)” had a distinct CAZy profile (far right Figure 4.18a) from all others and was comprised nearly exclusively of sequences from Burkholderiaceae (see Figure 4.39; section 4.2.4). The major AA enzymes identified in this sample were ‘benzoquinone reductases’ (AA6), which were one of the AA families frequently more abundant in 13C-lignin libraries (highlighted row in Figure 4.18a). The search for clusters of three or more CAZy genes on a scaffold recovered a total of ~11,500 clusters containing ~51,000 putative CAZymes. A number of longer scaffolds containing over 50 CAZymes were found and were largely classified to Verrucomicrobiales (Figure 4.19A). Longer scaffolds typically had lower clustering density of CAZymes, in particular large scaffolds which stretched the notion of a ‘cluster.’ However, scaffolds containing between 10 – 15 CAZymes exhibited an unexpected increased clustering density (Figure 4.19B), which were fungal in origin. A number of CAZy clusters contained lignin-modifying genes (Figure 4.20). Clusters containing lignin-modifying genes were predominantly bacterial in origin and all corresponded to taxa previously identified as putatively lignolytic with Burkholderiales, Caulobacterales and Sordariales exhibiting characteristic predominance. Figure 4.18a. Heat map of CAZy family profiles for metagenomic libraries including only the most discriminating GH, PL, CBM and AA families (>1 sample with z-score > 1.5). Clustering was based on Bray-Curtis dissimilarity of samples (x-axis) and CAZy subfamilies (y-axis). Figure 4.18b. Taxonomic profiles of CAZymes grouping in ‘hotspots’ in Figure 4.18a displayed as heat maps. Backgrounds are coloured according to the taxonomic affiliation of California samples BR067, BR068 and LH020 (13C-cellulose) classified as either Actinomycetales (turquoise) or Ascomycota (pale orange). Differences among ecozone are also evident. Figure 4.19. Characterization of scaffolds containing clusters of three or more putative CAZymes based on rank abundance of CAZy cluster size (Panel A) and CAZyme cluster density (scaffold length / number of CAZymes; Panel B). Clusters were derived from both cellulose and lignin 13C-libraries. Figure 4.20. Taxonomic classification of CAZy clusters from 13C-metagenomes which contain lignin-modifying enzymes: Dyp2, laccases, peroxidases and alcohol oxidases (aryl alcohol and vanillyl alcohol). Only orders which contained more than one CAZy cluster with a given lignin-modifying enzyme are displayed. Full details can be found in Table E.14. The majority of putative bacterial peroxidases (AA2) were classified by PeroxiBase as Class I – catalase-peroxidases. One putative AA2 classified to Actinomycetales had 31% identity to a lignin peroxidase (Class II – catalase-peroxidase). All fungal AA2 genes were classified to hybrid ascorbate cytochrome C peroxidases. CAZy clusters encoding putatively lignin-modifying genes were recovered from all three families of Burkholderiales implicated in lignin-degradation with each containing at least one peroxidase (either DyP2 or AA2), laccase and oxidase (Table E.14). DyP2-like peroxidases were found in putatively novel lignolytic taxa, namely Acidobacteriales, Ktedonobacterales (Chloroflexi), and Cystobacteraceae (Myxoccocales). The recovery of Nocardiaceae clusters encoding Dyp2-like and vanillyl alcohol oxidase genes from LPTX was consistent with their expanded populations following antibiotic treatment (Figure 4.29; section 4.2.4). Clusters containing Dyp genes were mainly actinobacterial: Microbacteriaceae (4 clusters), Frankiaceae (1) and Streptomycetaceae (5). Other novel lignolytic groups, such as Chromatiales, Rhodospirillales and Rhodobacterales possessed clusters containing laccase genes. One cluster, containing multiple laccase genes, was classified by LCA to Enterobacter lignolyticus, which possess characterized lignolytic capabilities. Clusters containing ligninase genes from Streptomycetaceae, Pseudomonadaceae and Bradyrhizobiaceae were unexpectedly abundant given the absence of differential abundance in pyrotag libraries. Sphingobacteriaceae were underrepresented in CAZy clusters with only a single cluster containing an aryl oxidase gene found. Forty-seven percent of CAZy clusters contained a putative CBM and, of those, ~ 1% contained a laccase, ~0.5% an aryl or vanillyl oxidase, and ~0.2% some form of peroxidase. To assimilate 13C from the ring-labeled DHP-lignin organisms would need to possess the capability to cleave and transform aromatic compounds into central metabolites. The paradigm for oxic degradation of aromatic compounds involves peripheral pathways which convert degradation products into protocatechuate or catechol intermediates which then feed into the β-ketoadipate pathway, though additional oxic and anoxic pathways have recently been reported (Fucks et al., 2011). The presence of genes in the KEGG Orthology (KO) β-ketoadipate module (M00568) was assessed in partial genome bins and in 13C-lignin metagenome assemblies. Nine partial genomes contained homologous genes for the entire KO module and were classified as Burkholderia, Sphingomonas, Caulobacter and Sorangium. Upon closer examination, the specific scaffolds encoding the genes in the two Caulobacter bins were classified as Sphingomonadaceae (all other genome classifications matched their scaffold classifications). Assemblies from a diverse array of organisms possessed homologs of catA, encoding catechol 1,2-dioxygenase (Figure 4.21), including Caulobacteraceae. The catC gene, encoding muconolactone D-isomerase, was absent in all 13C-lignin assemblies. Fourteen scaffolds contained neighbouring homologs for at least three of the four β-ketoadipate pathway genes and were classified to Burkholderiaceae, Oxalobacteraceae, Enterobacteriaceae, Rhodobiaceae, Methylobacteriaceae, Rhizobiaceae and Sphingomonadaceae. CAZyme family profiles further substantiated differences in cellulolytic and lignolytic groups within Caulobacteraceae. Their CAZy profiles exhibited greater differentiation between cellulose and lignin libraries (ANOSIM; R=0.202; p<0.001) than overall metagenome profiles (R=~ 0.08) and also grouped by ecozone (ANOSIM; R=0.09, p=0.02). The distinction between lignolytic and cellulolytic Caulobacteraceae was supported by PCA and by hierarchical clustering using Bray-Curtis dissimilarities (Figure 4.22). A number of CAZy families were differentially abundant in lignolytic Caulobacteraceae populations, including the oxidase family AA3, and in cellulolytic populations, such as the endoglucanase-containing family GH9 (Figure 4.22B). Taxonomic classifications also differed, with CAZymes classified as Asticcacaulis more abundant in 13C-cellulose libraries and Brevundimonas and Caulobacter more abundant in 13C-lignin libraries (Figure 4.22C), consistent with results from pyrotag analysis. Fungi possessed far higher proportions of peroxidases (AA2), iron reductase domains (AA8) and lytic polysaccharide monooxygenases (AA9) in unassembled 13C- libraries. These AA families were most abundant in southern ecozones, PPCA and LPTX, where members of the order Sordariales were most abundant (Figure 4.23). LPMOs were also classified to Sebacinales, supporting their designation as cellulolytic in analysis of pyrotag libraries as well as their endemicity in western ecozones (Figure 4.23; details in section 4.2.5). Figure 4.21. Taxonomic classifications of assembled scaffolds from 13C-lignin metagenomes containing genes from the β-ketoadipate pathway: catechol 1,2-dioxygenase (catA; K03381), muconate cycloisomerase (catB; K01856) and 3-oxoadipate enol-lactonase (pcaD; K01055). Only families with >3 scaffolds are shown. Figure 4.22. Cellulolytic and lignolytic CAZy family profiles for Caulobacteraceae exemplified by (A) principle components analysis, (B) a heatmap showing the most discriminatory CAZymes families clustered by Bray-Curtis similarities and (C) bar plots of the taxonomic classification of CAZymes at the Genus level. Average read counts per million are inscribed bottom-right of each bar plot in panel C. Figure 4.23. Heat maps showing the relative abundance of fungal taxa in fungi-exclusive CAZyme families AA2, AA8 and AA9. 4.2.4 Relative Contributions of Lignocellulose-degrading Taxa The importance of any given taxon in the rate of 13C-assimilation from labeled substrate was assessed using ‘Boruta’ to test whether specific taxa were predictors of delta-13C enrichment in both DNA and PLFA. A number of taxa were identified that were correlated with enrichment levels across all samples, namely Caulobacteraceae (r=0.49, p=0.006) and Sphingomonadales (r=0.44, p=0.02) for lignin, and Opitutacaeae (r=0.48; p=0.01) and Planctomycetaceae (r=0.53, p=0.004) for cellulose (Figure 4.24). Other lignolytic taxa were also selected, such as Rhodospirillales and iii1-15, though these groups exhibited a narrower distribution across samples. No fungal taxa were selected, but this could also be due to their inconsistent distribution among samples. Notably, the majority of samples with the highest average enrichment had greater proportions of fungi (Figure 4.25AB) from classes Sebacinales, Helotiales, Sordariales, Orbilliales and Pseudogymnoascus (Figure 4.25C). Total bacterial incorporation of 13C into PLFAs surpassed that of fungi for both cellulose and lignin substrates. Fungi and Gram-negative bacteria had comparable levels of enrichment on cellulose, whereas fungi had surprisingly low activity on lignin except in LPTX (Figure 4.26). Fungal activity was more apparent when 13C-enrichment was normalized to pre-existing biomass (Figure 4.27). Gram-negative bacteria had the highest delta-13C enrichment from both substrates in 51 of 73 PLFA samples, while fungi and Gram-positive bacteria were comparable at 18 and 14, respectively. The total enrichment in samples dominated by fungi was not significantly greater than those dominated by Gram-negative bacteria (t-test; p=0.89), nor was 13C-enrichment of PLFA or DNA correlated to the total number of bacterial or fungal metagenomic reads. The enrichment of fungal PLFAs had greater overall variability, between 2 and 10-fold greater variance, relative to Gram-negative and Gram-positive bacteria, respectively. Figure 4.24. Linear regression of 13C-enrichment of DNA and abundance for taxa selected by Boruta analysis as indicators of overall enrichment on either cellulose (off-white) or lignin (brown-gold). Spearman’s rank correlation coefficients and p-values derived from randomization are given. Figure 4.25. Total 13C-enrichment of DNA (A) and corresponding ratio of Fungi:Bacteria (B) and overall taxonomic composition of metagenomic libraries (C) among ecozones and soil horizons. Barplots correspond to the proportion of unassembled metagenomic reads classified at the domain (B) and order (C) level. Taxa occupying fewer than 0.5% of reads were not shown. Figure 4.25… continued Figure 4.26. Box and whisker plots showing the average 13C-enrichment of PLFAs indicative of fungal (brown), Gram-positive (yellow) and Gram-negative bacterial biomass among soil layers and ecozones (A) as well as aggregated enrichment for each substrate and horizon for delta-13C (B) and total 13C (C). Figure 4.27. Box and whisker plots showing the relative enrichment of fungal relative to bacterial PLFAs (13C-fungi:13C-bacteria) normalized to pre-existing PLFA biomass (12C-fungi:12C-bacteria). Fungicide treatment reduced the overall 13C-enrichment of PLFAs by 70% and produced a steep decline in the enrichment of both fungi and Gram-positive bacteria during incubations with labeled lignin. Fungicide reduced 13C-enrichment of fungal PLFAs by ~90%, reducing fungal enrichment in PPCA to levels comparable to incubations with unlabeled substrate, -9 ‰ versus -28 ‰ delta-13C, respectively (Figure 4.28). The enrichment of Gram-positive and Gram-negative bacteria was also reduced by fungicide treatment, ~90 and ~50%, respectively, but by only 2% for Gram-negative bacteria in soils from LPTX. The major taxonomic groups active in fungicide treated microcosms were distinct from untreated incubations (Figure 4.29). The sustained activity of Gram-negative groups was evident in the increased relative abundance of families from Burkholderiales. In the case of BSON (site A7), the entire metagenomic library was classified as Burkholderiaceae (99%), demonstrating unprecedented recovery of DNA from functional subpopulations from a SIP experiment. Notably, Burkholderiaceae spp. showed the highest differential abundance in BSON between 13C- and 12C-lignin pyrotag libraries (Appendix Figure C.6). In contrast Burkholderiaceae populations were unaffected by fungicide treatment in PPCA and were also not differentially abundant in pyrotag libraries. Despite the reduction in Gram-positive PLFA 13C-enrichment, the relative abundance of Actinobacteria increased in metagenomes from fungicide treatments (Figure 4.30). Certain families of Actinobacteria were negatively impacted by fungicidal treatment, such as Acidimicrobiales and Conexibacteraceae, while others increased in abundance, such as Nocardiaceae Microbacteriaceae and Micrococcaceae. Figure 4.28. Enrichment of PLFAs in soil samples incubated with 13C-lignin with or without the addition of anti-fungal cocktail. Each bar represents a single sample, except for in BSON where n=2. Figure 4.29. Abundances of predominant families in unassembled metagenomic libraries derived from 13C-lignin incubations treated with ‘fungicide’ and without (‘paired’). The averaged abundances of 12C- and 13C-lignin metagenomes from separate incubations were also included. Figure 4.30. Abundances of select taxa previously identified as lignolytic in unassembled metagenomic libraries from soils amended 13C-lignin with or without antibiotic. Each bar represents a single sample, except for in BSON where n=2. Taxa were selected which exhibited notable trends of expansion or decline in antibiotic or control libraries. 4.2.5 Ecozone-Specific Lignin and Cellulose-degrading Populations Of the total OTUs identified as differentially abundant between 12C- and 13C-pyrotag libraries (503), only 41 were abundant enough to be detected in situ, indicating a strong enrichment by SIP for low abundant OTUs. The majority of enrOTU found in situ were hemicellulose-degraders (90%), while only six lignolytic (Solibacterales, iii1-15, Myxococcales and Gaiellales) OTUs were found (no cellulolytic OTUs were found). This was consistent with the observation that hemicellulolytic and in situ libraries shared a majority of OTUs, in contrast to other libraries (Figure 4.6). Of the OTUs found in situ, their abundances in SIP-libraries was strongly correlated with in situ abundances (Figure 4.31). JPON and BSON sites had the greatest percentage of overlapping OTUs of any two ecozones (23%), while PPCA and IDFBC shared the second highest degree of overlap (17%). LPTX had the lowest proportion of overlap with other ecozones (Figure 4.32). Figure 4.31. Linear regression between in situ abundance of OTU deemed lignocellulolytic and their abundance in corresponding 13C-pyrotag libraries. Figure 4.32. Venn diagram showing overlapping OTUs in 13C-cellulose libraries among ecozones. One of the most notable biogeographical features was the domination of bacterial cellulose-degraders in the IDFBC ecozone and by a broadly different set of taxa than in others. Cellulolytic populations of Deltaproteobacteria (MIZ46), Gammaproteobacteria (Cellvibrio), Planctomyces, Bacteroidetes and Verrucomicrobia (Opitutaceae) were highly enriched in SIP-libraries from IDFBC, but not elsewhere (Figure 4.9 and Appendix Figure C.2). Cellulolytic Ascomycota, prominent among all other ecozones, were also largely absent in IDFBC (Figure 4.8; pg. 129). In contrast, cellulolytic Piriformospora (Sebacinales; Basidiomycota) were highly abundant, and to a lesser extent abundant in the other western ecozone PPCA (Figure 4.33). The presence of cellulolytic Sebacinales in western ecozones was corroborated by the abundance pattern of LPMO family AA9 (Figure 4.23; pg. 158). Conversely, southern ecozones shared a predominance of cellulolytic Ascomycota, such as Humicola, Arthrobotrys, Myceliopthora and Chaetomium (Figure 4.33) also illustrated in LPMO family AA9 (Figure 4.23). Biogeographical differences in lignolytic taxa were less pronounced than cellulolytic populations. A number of actinobacterial groups were specific to BSON, namely: Gaiellaceae, Figure 4.33. Localized patterns of putatively cellulolytic or lignolytic taxa in either unassembled metagenomic (Piriformospora, Myceliopthora & Nocardiaceae) or pyrotag libraries (uncl. Xanthomonadales, Azospirillum & Erythrobacteraceae). ACK-M1 and members of Solirubrobacterales clade ‘TM146.’ The prevalence of TM146 OTUs in BSON was notable given that soils there were blanketed with Sphagnum moss, not found at other ecozones. The clade TM146 was named for a bacterial isolate from Sphagnum moss and contains a number of sequences from similar environments (Figure 4.34). Lignolytic populations in LPTX were distinct from other ecozones in both organic and mineral soils based on PLFA enrichment profiles (Figure 4.7; pg. 128). The majority of lignolytic OTUs exclusive to LPTX (n=64) were members of genera common to all ecozones, illustrating fine-scale phylogenetic differences of localized populations. LPTX also possessed a number of genera uncommon to other ecozones of which Azospirillum and Nocardiaceae were most abundant (Figure 4.33) and other exceptions included: Ellin6513 (Acidobacteria), Uliginosibacterium, a number of Actinobacteria (Salinispora, Nocardiopsaceae, Geodermatophilaceae, Pseudonocardiaceae and Gordoniaceae), and Holosporaceae. 4.2.6 In situ Abundances of Lignocellulose-degrading Populations Due to the poor overlap of OTUs between in situ, cellulose and lignin pyrotag libraries, the in situ abundances of lignocellulosic taxa could not be reliably assessed. During analyses performed in Chapter 3, one third of cellulolytic OTUs were detected in situ and, of those detected, their abundances were modest. Cellulolytic OTUs constituted between 0.08% and 1.4% of total reads with a median abundance of 0.42% among all samples. The most abundant single OTU (uncl. Streptomycetaceae) occupied, at most, 0.6% of a given sample with a mean abundance of 0.1%, followed by OTUs from Janthinobacterium (max: 0.5%), Burkholderia (0.4%), and uncl. Microbacteriaceae (0.3%). Of all enrOTU detected in situ, 90% were detected in the organic layer, suggesting SIP-incubations selected for low abundance taxa in mineral soils below the sequencing depth of in situ libraries. Figure 4.34. Maximum parsimony phylogenetic tree for lignolytic OTUs classified to Solirubrobacterales (Actinobacteria) predominant in BSON. OTUs clustered in the ‘TM146’ clade (SILVA), named after a peat bog clone. Inset - Picture of sampling site in BSON with Sphagnum as predominant ground cover. For fungi, six out of the sixteen enrOTU were detected in situ in low abundance (maximum 0.3% of any given sample), though, when binned by taxonomic classification, members of Chaetomiaceae occupied an average of ~2% of total in situ libraries. Consistent with observations in Chapter 3, taxa lacking reported lignocellulolytic activity were more common in mineral soils, including Armatimonadetes (hemicellulose | cellulose), Candidatus Saccharibacter (formerly TM7; hemicellulose), Delta- and Gammaproteobacteria (all three substrates) and Acidobacteria (lignin). In contrast, known cellulolytic and lignolytic taxa were more common in the organic layer, including an array of fungi, Actinobacteria, Alpha- and Betaproteobacteria (Table 4.1). 4.2.7 Impacts of Timber Harvesting on Lignocellulosic Taxa Given the observations of fine-scale phylogenetic differences in response to harvesting reported in Chapter 3, the poor overlap between SIP and in situ OTUs make any characterization of harvesting impacts on lignocellulosic taxa highly speculative. In addition to the cellulolytic taxa affected by harvesting identified in section 3.3, namely, Chaetomium, Opitutaceae, Streptomycetaceae and Caulobacteraceae, the populations of a number of putatively lignocellulosic taxa may be affected. In situ populations of Janthinobacterium, Paenibacillus, Cryptococcus and Leptothrix all expanded in harvested plots (Figure 4.35; coloured red). Conversely, populations of putatively lignolytic taxa declined in harvested plots, such as Pelomonas, Ellin6513 (Acidobacteria) and Sinobacteraceae, and cellulosic taxa, such as Hypocrea and Sebacinaceae (not shown) (Figure 4.35; coloured brown-grey). Notably, populations of Pelomonas and Ellin6513 exhibited clearest declines in LPTX, the only ecozone where they were identified as lignolytic. Three lignocellulosic groups had slight and consistent increased relative abundance at intermediate harvesting intensities, in particular in OM1: unclassified Conexibacteraceae and Solirubrobacterales (both Actinobacteria) and Neurospora (Fungi), (Figure 4.35; coloured green). Clitopilus sp., previously identified as cellulolytic in PPCA in Chapter 3, exhibited higher relative abundance at intermediate harvesting intensities, though appeared to also favour conditions in OM3 in LPTX (Figure 4.35; coloured green). Figure 4.35. Abundances of taxa designated putatively on one or more substrate among harvesting treatments in in situ pyrotag libraries coloured by whether populations expanded in harvested sites (shaded red), declined (shaded brown-grey) or peaked in OM1 or OM2 plots (shaded green). 4.3 Discussion SIP surveying lignocellulolytic taxa in forest soils across North America expanded the diversity of putative degraders and provided evidence that, in many cases, contradicted or tempered conventional views of decomposer populations. Hemicellulolytic, cellulolytic and lignolytic microorganisms were identified in fourteen bacterial phyla and two fungal divisions, which were largely evident among all ecozones studied. Some of these groups exhibited exclusive activity on a single substrate, while others the capacity to degrade all three lignocellulosic polymers. The decomposition of DHP lignin in soil microcosms was largely bacteria-driven, predominated by Gram-negative groups, while fungi were substantial contributors to cellulose decomposition. Putatively lignocellulolytic taxa included a sizeable contingent of taxonomic groups with previously characterized in vitro activity, revealing their activity in soils and expanding knowledge of their phylogenetic diversity. This thesis reports, for the first time, the potential capacity to depolymerization lignin, and/or catabolize lignin bi-products, by members of Acidobacteria, Chloroflexi, Elusimicrobia and Deltaproteobacteria as well as novel groups within Actinobacteria and Gammaproteobacteria. The attribution of lignolytic activity was supported by the recovery of CAZy gene clusters encoding AA genes classified to the aforementioned groups. Similarly, for cellulose depolymerization, the substantial enrichment for Planctomycetes, Armatimonadetes and Verrucomicrobia revealed hereto unrecognized populations of decomposers in forest soils. The ability of Caulobacteraceae spp. to degrade all three lignocellulosic substrates was unexpected, though, in retrospect, a number of lines of evidence suggest their involvement. The earliest evidence originates from work done by Henrici and Johnson (1935), who grew the first cultures of Caulobacter in cellulose-amended liquid culture. After their initial characterization, Caulobacter quickly became better known as model organisms for dimorphism and for possessing strong adhesive ‘holdfast’ proteins (Poindexter, 1964). Recent attention has been given to their potential role in breakdown of lignocellulosic substrates after an array of CAZy genes were identified in the first sequenced genome (Nierman et al., 2001). Subsequently, the capability of C. crescentus to degrade xylose was shown along with its expression of an unexpectedly high diversity of TonB-dependent sugar transporters (Hottes et al., 2004; Blanvillain et al., 2007). More recently, C. crescentus was shown to catabolize a broad range of carbohydrates, including cellobiose, both aerobically (Presley et al., 2014) and anaerobically at temperatures up to 45°C (Song et al., 2013). The capacity for lignin catabolism by C. crescentus is further supported by its growth on vanillic acid, benzoate and other aromatics as well the presence of a vanillate-inducible promoter in its genome (Chatterjee and Bourquin, 1987; Thanbichler et al., 2007). Al-Thukair and Malik (2016) reported a Caulobacter sp. isolated from an oil-contaminated site that could degrade pyrene, while a laccase gene was previously identified in the C. crescentus genome based on homology, but has not been characterized (Li et al., 2009). The potential role of Caulobacter species in decomposition in environmental samples has been shown in SIP-cellulose experiments in forest soil (Wang et al., 2015) and a range of soils (Verastegui et al., 2014), and in lignin-degrading cultures in tropical and temperate forest soils incubations (DeAngelis et al., 2011; Pold et al., 2015), though no study as conclusively or as explicitly as this research. This thesis firmly solidifies the importance of genera within Caulobacteraceae as major lignocellulolytic groups. Caulobacteraceae were one of the few taxonomic groups significantly correlated with the degree of 13C-enrichment from labeled lignin and their activity endured in fungicide treated soils. Lignin-degrading Caulobacteraceae were members of largely uncultured clades, which were more abundant in the mineral soil layer, supporting the existence of relatively unknown degraders of recalcitrant compounds in deeper, low nutrient soils. The differentiation among cellulolytic/hemicellulolytic and lignolytic clades within Caulobacter and between its highly cellulolytic relative, Asticcacaulis, was supported by 16S rRNA gene libraries as well as CAZy content, suggesting the study of Caulobacteraceae may provide an interesting case study of niche partitioning. Asticcacaulis were originally differentiated from Caulobacter based on differences in stalk angle and localization of holdfast protein (Poindexter, 1964). So, while speculative, the differences in substrate utilization (lignin vs. cellulose) between these close relatives may relate to differences in cell structure and attachment. The observation of cellulolytic activity by Asticcacaulis was relatively novel with only one study reporting a cellulolytic Asticcacaulis isolate (Kim et al., 2013) and another predicting activity based on genome content (Medie et al., 2012). Notably, the closely related genus, Phenylobacterium, which possess large number of laccases and characterized phenol oxidase activity (Muller and Lingens, 1983; Lu et al., 2015), were not enriched on any substrate in this study. Comparative studies of these genera, as well as species within uncultured clades of Caulobacteraceae, may yield insights into the evolutionary and natural history of what may become a new model group for the degradation of lignocellulose. Caulobacteraceae were one of the taxonomic groups whose populations declined in the decades following timber harvesting (Chapter 3) and also in a study of soil warming on lignolytic populations (Pold et al., 2015). Sensitivity to changes in moisture regime may be the most likely cause of population declines given Caulobacter are famously cultivable from oligotrophic fresh water habitats that include distilled water (Poindexter, 1964). Information to confirm such a sensitivity is limited, though Caulobacter populations were found to be one of the microbial populations to respond most rapidly to re-wetting of dry river sediments (Fazi et al., 2008). Speculatively, moisture may play an important role in their dimorphic lifestyle in which colonization of plant biomass may occur during periods of wetness, followed by a strong adherence to the substrate during drying. This may ensure proximity of the cell to the resource and confer greater benefit from secreted extracellular catabolic enzymes. Further research is necessary to uncover why Caulobacteraceae populations decline in warmer, drier soils and whether the ability to adhere to a substrate may be implicated in their efficacious decomposition of lignocellulosic polymers. Many of the taxa designated here as lignocellulolytic have been observed in previous SIP studies, in enrichment cultures or have characterized lignocellulolytic isolates and enzymes. The predominance of Alphaproteobacteria, Betaproteobacteria, Bacteroidetes, Firmicutes and Actinobacteria in decomposition in soil has been widely reported in culture-independent surveys (Lee et al., 2011; Štursová et al., 2012; DeAngelis et al., 2015; Leung et al., 2016). In the forest soils studied here, Alpha- and Betaproteobacteria exhibited the most prolific differential abundance in 13C-libraries for all three lignocellulose polymers as well as in the recovery of CAZymes. Metatranscriptomic profiling of forest and grassland soil communities indicated that Burkholderia (Betaproteobacteria) and Azospirillum (Alphaproteobacteria) were far more abundant in forest soils and were correlated with increased abundances of aromatic and xenobiotic degradation genes (Nacke et al., 2014). Members of both these genera were identified as lignolytic in the present research and have previously characterized lignolytic activity (Faure et al., 1996; Woo et al., 2014). Other prominent lignolytic Alphaproteobacteria identified were members of Sphingomonadaceae, from which novel lignin degradation genes (the lig genes of S. paucimobilis SYK-6) have been characterized (Masai et al., 2007). Sphingomonadaceae were one of the most common groups from which genes encoding peroxidases and oxidases were recovered. Sphingomonadaceae were also one of the few taxonomic groups found to degrade hemicellulose and lignin, but not cellulose, others included Micrococcaceae (Actinobacteria) and Sphingobacteriaceae (Bacteroidetes). Betaproteobacteria have been identified as the major degraders of cellulose (Štursová et al., 2012) and hemicellulose (Leung et al., 2016) in SIP-surveys of forest soils. All lignocellulolytic Betaproteobacteria identified in this thesis were members of Burkholderiales and represent relatively unknown taxa. Of the two major cellulolytic genera, Leptothrix and Janthinobacterium, both associated with mineral soils, only Janthinobacterium has previously reported evidence for cellulolytic activity (Avellaneda-Torres et al., 2014). Pelomonas and Variovorax, found here to assimilate carbon from DHP-lignin, have never been implicated in lignin degradation, though Pelmonas saccharophila (formerly Pseudomonas saccharophila) can degrade polyaromatic hydrocarbons (Chen and Aitken 1999) and a species of Variovorax reportedly grows on homovanillate (Allison et al., 1995), and close relatives able to degrade kraft lignin (Chen et al., 2012). Pelomonas populations were also enriched in microcosms fed hemicellulose and cellulose, consistent with previous characterizations (Shil et al., 2014). The predominance of Alpha- and Betaproteobacteria in degrading lignocellulose in forest soils was a major feature of this study and was broadly supported, though incomplete, in the literature. Members of Ascomycota and Basidiomycota were the only fungi to exhibit cellulolytic or lignolytic activity. Ascomycota were the primary fungal degraders of cellulose, which has been reported in other SIP-cellulose experiments in forest soils (Štursová et al., 2012) and longitudinal studies of decomposition (Voriskova and Baldrian, 2013). The minor proportion of reads classified to fungi in 13C-lignin metagenomes was unexpected and was at odds with the levels of 13C-enrichment observed in PLFA, comparable in some samples to bacterial enrichment. This discrepancy suggests that fungi assimilating 13C into PLFAs were not replicating DNA at sufficient levels to be recovered during density gradient ultracentrifugation, resulting in their underrepresentation in sequencing data. This explanation is indirectly supported by the observation that fast-growing fungi and yeasts, with short doubling times, were the predominant type of fungal taxa found in SIP-cellulose libraries, such as Trichoderma, Neurospora and Chaetomium. The sole putatively lignolytic fungi was also a yeast (Saccharomycetaceae spp.). Slow-growing Agaricomycetes would be the most likely fungal taxa to degrade lignin, and while reported to assimilate carbon from DHP-lignin (Haider and Trojanowki, 1975), may do so at a rate unamenable to SIP-DNA experiments. Gram-negative taxa drove lignin decomposition in soil microcosms and were largely unaffected by fungicide, which dramatically reduced 13C-enrichment of fungal and Gram-positive PLFAs. The relative importance of Gram-negative taxa in lignin decomposition (3-fold higher than fungi) was also reported in decomposers in semi-arid soils (Torres et al., 2014). However, the same study reported 5- to 10-fold higher enrichment from lignin than cellulose, likely the result of using impure commercial 13C-substrates. Burkholderiaceae exhibited the greatest growth in 13C-assimilation following fungicide treatment, along with Sphingobacteriaceae (Bacteroidetes), Sphingomonadaceae, and Xanthomonadaceae. Lignolytic Xanthomonas, a common plant pathogen, have been characterized (Kern and Kirk, 1987). A Sphingobacterium isolate from deciduous woodland soil had notable lignolytic activity (Taylor et al., 2012), leading to discovery of two novel superoxide dismutases potentially able to degrade lignin (Rashid et al., 2015). This novel mechanism may help explain the surprising lack of lignin-modifying genes recovered from Sphingobacteriaceae, despite their clear enrichment in 13C-lignin pyrotag libraries, most closely related to Mucilaginibacter. The steep decline in 13C-enrichment of Gram-positive PLFAs in fungicide treatments suggests some form of syntrophy between Gram-positive bacteria and fungi. Metagenomic data corroborated PLFA data, but showed a more modest decrease in fungal reads and expansion of bacteria. Overall, reads classified to Actinobacteria actually increased in antibiotic treatment, but two major groups of putatively lignolytic Actinobacteria decreased, namely Acidimicrobiales and Conexibacteraceae (Solirubrobacterales). The increase in Actinobacteria was driven by populations of Microbacteriaceae, Micrococcaceae and Nocardiaceae, all in the order Actinomycetales, which expanded prodigiously in LPTX soil following fungicide treatment. Members of the latter three families possess isolates with lignin-degrading capabilities and include the characterization of dypB genes in Rhodococcus (Taylor et al., 2012; Ahmad et al., 2011). The identification of dyp genes classified to Nocardiaceae from fungicide treated LPTX soil underlines the potential relevance of DyP peroxidases in bacterial, soil-based lignin-degradation. The decline in 13C-enrichment of Gram-positive PLFAs may have been driven by the substantial decline in Firmicutes population, yet no putatively lignolytic taxa were identified from this phylum. The possibility of non-targeted effects of the fungicides used is unlikely given that both cycloheximide (targets eukaryotal 60S ribosome) and amphotericin B (targets ergesterol) are produced by Streptomyces, and are routinely used in culturing Actinobacteria (Gontang et al., 2007). There is also the possibility that Gram-positive PLFA markers are not exclusive and may be produced by fungi, though there is no evidence for this in the literature. PLFA enrichment profiles in the antibiotic experiments strongly suggest some degree of cross-feeding, yet the balance of evidence still supports a substantial capacity of bacteria to degrade lignin in forest soils, which was the central purpose for conducting the fungicidal treatments. A number of lignin-modifying gene families were mainly comprised of bacterial reads, such as laccases, alcohol oxidases, benzoquinone reductases, quinone-dependent oxidoreductases and Dyp-type peroxidases, keeping with the near exclusivity of Dyp-type peroxidases in the bacterial domain (Colpa et al., 2014). The sizeable increase of vanillyl alcohol oxidase genes in 13C-lignin metagenomes was consistent with the chemical composition of DHP-lignin, comprised of oligomers of ring-labeled vanillyl alcohol. Laccases and benzoquinone reductases were also enriched in 13C-libraries, but only after subsetting to taxa designated putatively lignolytic from pyrotag analysis. Without subsetting, the abundance of AA genes in 13C-lignin libraries was at parity or depleted relative to 12C-libraries, revealing the ubiquity of oxido-reductase enzymes with homology to AA families and the challenge it presents to targeting specific lignolytic homologs. The sole hemicellulolytic activity of Streptomyces was unexpected given their reputation as both cellulose and lignin-degraders. Streptomyces were one of the first characterized bacterial degraders of lignin (Crawford et al., 1978), leading to the characterization of Streptomyces viridosporus T7A (Pasti et al., 1990) and eventual discovery of small laccases (Majumdar et al., 2014) and a Dyp-type peroxidase encoded in its genome (Davis et al., 2013). This ground breaking work, partly inspired by the similarity in hyphal morphology to fungi, garnered Streptomyces attention. However, the lack of lignolytic Streptomyces in this study corroborates other reports of modest lignolytic activity. In one study, only a small subset of Streptomyces isolates exhibited relatively weak lignolytic activity on DHP lignin (Vetrovsky et al., 2014). In another case, forest soil enrichments for lignolytic taxa were actually depleted in Streptomyces (Pold et al., 2015). In this thesis, Streptomyces were only identified as hemicellulolytic, while Kitasatospora and other unclassified Streptomycetaceae were significantly active on both hemicellulose and cellulose. Yet, Streptomycetaceae had the highest proportion of CAZy clusters encoding putative Dyp genes and also the sole potential bacterial Class II peroxidase. This discrepancy may indicate an overrepresentation of Streptomycetaceae in databases used for annotating peroxidase genes, but also the possibility of more complex trophic requirements in Streptomycetaceae. Streptomycetaceae exhibited substantial activity in SIP experiments using 13C-labeled whole plant tissue (Lee et al., 2011), suggesting that lignin-degrading gene expression may depend on the presence of plant carbohydrates. Similarly, Bacillus possess characterized cellulolytic and lignolytic taxa (Tian et al., 2014; Menendez et al., 2015), yet were only identified here as hemicellulolytic. It could be that Bacillus were identified as the earliest organisms to respond to xylose amendments in a similar SIP experiment, but were eventually overtaken by the slower-growing but more active Bacteroidetes, then Micrococcales (Pepe-Ranney et al., 2016). Discrepancies between SIP studies and in vitro characterization are likely the result of both technical and ecological factors, stressing the necessity of complementary approaches. The characterization of mineral soil provided evidence for distinct and novel lignocellulolytic populations in a largely overlooked niche for microbial decomposition. Cellulolytic populations were highly active in mineral soils, incorporating far more carbon relative to pre-existing biomass than populations in organic soils. Strong enrichment for long-established cellulolytic taxa, such as Cellvibrio (Berg et al., 1972), Cytophaga (Stanier, 1942), Sorangium (Imsenecki and Solntzeva, 1936) and a long list of fungi, was evident in organic soils, while most mineral-associated cellulolytic taxa were implicated in cellulose-degradation for the first time, including the following bacterial groups: candidate division FBP (Armatimonadetes), FW68 (Armatimonadetes), Leptothrix (Betaproteobacteria), Janthinobacterium (Betaproteobacteria) and DH61 (Planctomycetes), and MIZ46 (Myxococcales). The pronounced cellulolytic activity from members of Armatimonadetes was corroborated by a recent SIP-cellulose experiment (Wang et al., 2015) and by the cellulolytic activity of one of the three cultured representatives of Armatimonadetes (Lee et al., 2014). Lignolytic Acidobacteria were also more abundant in mineral soils, including members of poorly characterized subgroup 2 (Ellin6531) and 6 (iii1-15). All three Dyp2-type genes classified as acidobacterial were recovered from mineral soil metagenomes. This is the first assignment of lignolytic activity to members of these groups, though microarray profiling of lignin-bead amended tropical forest soil enrichments had suggested the involvement of Acidobacteria (DeAngelis et al., 2011). SIP- cellulose-based discovery of cellulolytic Acidobacteria (subgroup 1) by Eichorst and Kuske (2012) and Štursová et al., (2012) was not observed in this study, resulting either from biogeographical differences or their use of impure 13C-maize cellulose. SIP shines light on the multitude of uncultured taxa, commonly described as ‘microbial dark matter,’ which proved effective in identifying a number of uncultured, putatively lignolytic bacteria. OTUs belonging to the myxobacterial family Cystobacteraceae showed a twenty-fold enrichment in 13C-lignin libraries. Two CAZy clusters were recovered from Cystobacteraceae encoding a putative Dyp and laccase, respectively. OTUs clustered with Cystobacter gracilis, a species commonly isolated from decaying plant material that lacks the capacity to degrade cellulose (Reichenback, 2005), a phenotype consistent with our findings. A close relative of Cystobacter, Stigmatella aurantiaca, reportedly degrades phenolic compounds (dos Santos et al., 2014). This suggests a putative role for C. gracilis in lignin degradation, recently proposed to represent its own genus within Cystobacteraceae (Garcia et al., 2010). Another newly designated phylum, Elusimicrobia, originally named ‘Termite Group 1,’ was roughly eight-fold enriched in 13C-lignin pyrotag libraries. Sequences classified to Elusimicrobia occupied as much as 20% of bacterial 16S rRNA libraries in a study of lower termite guts (Boucias et al., 2013) and have been found in a number of lignin-rich environments, such as leaf-cutter ant fungus gardens (Suen et al., 2011) and peatlands (Urbanova and Barta 2014), as well other environments like ocean sediments (Oni et al., 2015). Huang et al., (2013) reported that termites fed woody diets were particularly populated by Elusimicrobia, with the highest populations occurring in termites fed pine, as opposed to poplar, maize or sorghum. Despite extensive circumstantial evidence for their role in lignin-degradation, there is no direct evidence of lignolytic activity. The sole cultured representative from the phylum, isolated from the gut of a beetle larva, is strictly anaerobic and ferments sugars using typical anaerobic pathways and possessed no noteworthy AA or CAZyme gene content (Herlemann et al., 2009). Two novel groups of Gammaproteobacteria were designated as putatively lignolytic in addition to Enterobacteriaceae, which has two isolates with characterized lignin-degrading activity: E. lignolyticus (DeAngelis et al., 2011) and E. soli (Manter et al., 2011). The recovery of a CAZy cluster containing multiple laccase genes classified to E. lignolyticus is noteworthy. The putative lignolytic capability of members of purple sulfur bacteria (PSB), Ecothiorhodospiraceae, was evidenced in the differential abundance in 13C-lignin metagenomes in all three ecozones assayed. While PSB are unlikely candidates as lignin degraders, the designation was weakly supported by the recovery of a CAZy cluster encoding an Ecothiorhodospiraceae CBM and laccase. The other novel group within Gammaproteobacteria was represented by a single OTU that clustered with uncultured ‘Xanthomonadales incertae sedis Acidibacter’ in SILVA and was classified as Piscirickettsiaceae, a fish pathogen, with GreenGenes. Piscirickettsiaceae was among the top most differentially abundant families for AA4 (4.8-fold) and AA6 (2.9-fold) in unassembled 13C-lignin metagenomes. The capacity to degrade multiple lignocellulosic substrates strongly suggests an organism’s involvement in the decomposition of plant matter. In this study, approximately 35% of putatively lignocellulolytic taxonomic groups were capable of degrading more than one substrate. This may be an underestimate given the incomplete coverage of ecozones for SIP-hemicellulose and lignin. However, few individual species exhibited multi-substrate use, with only five examples of OTUs degrading cellulose and lignin and also the minimal overlap between hemicellulose pyrotags and the other two SIP libraries. These findings suggest that few bacterial species have co-evolved metabolism of lignocellulosic polymers, implying that decomposition may be structured by a division of labour. This hypothesis was put forward by Berlemont and Martiny (2013), whose comparative genomic study demonstrated that the genetic capacity to degrade crystalline cellulose was occurred in clusters of closely related species (~0.013% dissimilarity), while the capacity to degrade oligomeric forms of cellulose was more widely distributed within and among lineages. The findings reported here, that few OTUs based on a cutoff of 0.01% utilized more than one substrate, is in agreement with the degree of functional specialization suggested by Berlemont and Martiny. Similarly, Vetrovsky et al., (2014), concluded that the co-metabolism of polysaccharides and DHP-lignin by Streptomycetes was negligible. On the other hand, the recovery of fungal draft genomes containing endoglucanases, lytic polysaccharide monooxygenases, oxidases and peroxidases was evidence for the multi-substrate degradative capacity of fungi, consistent with the long-established understanding of their life histories. Similar to observations reported in Chapter 3, biogeographical differences in the composition of lignocellulolytic populations were evident among ecozones. These differences were related to differences in in situ abundances, but also commonly the presence or absence of a taxa. Lignocellulolytic populations from proximal ecozones, such as in Ontario, shared the greatest similarity, while LPTX communities were most distinct. Cellulolytic populations exhibited the greatest differences according to the East-West divide, exemplified by the relative involvement of Basidiomycota, and also a North-South divide, based on increasing participation of Chaetomiaceae in southern sites. The western distribution of Sebacinaceae was a notable biogeographical feature as well as novel feature of the SIP-metagenomic data. Sebacinaceae are known for ectomycorrhizal associations and, while a few saprobic species have been described, cellulolytic activity has not previously been shown (Oberwinkler et al., 2013; Weiß et al., 2016). Differences between North American and European cellulose-degrading populations was apparent in the broad differences in cellulolytic taxa reported in Czech forest soils, namely Collimonas, Alkanindiges, Streptacidiphilus and Herminiimonas (Štursová et al., 2012). These genera were present in low abundances in situ in all ecozones studied here, but were not enriched in any 13C-libraries. Similarly, Myxococcales were reportedly unique to forest soils in a SIP-cellulose survey of soils performed by Verastigui et al., (2014) and, while Myxococcales were prominent cellulolytic taxa in some ecozones, they were not equally prominent in soil incubations among all ecozones. Biogeographical differences can be useful for the study of the physiology and ecology of the decomposer community. Such differences are likely to account for meaningful variation in the rate of decomposition among forests, demonstrated here by the correlation of the rate of enrichment with the abundances of a number of taxa. Despite the overall success of SIP in addressing the goals of the research, there are notable limitations and caveats to the method. SIP microcosm experiments require conditions that encourage detectable levels of enrichment and favour certain taxa over others, such as faster growing Ascomycota over Basidiomycota. This might help explain why Paenibacillus sp. were not identified as putatively cellulolytic in SIP experiments despite being highly abundant in culture collections of cellulolytic taxa from the same soils (unpublished) and being detected in situ (~0.03% of total library). Yet, SIP may be the best approach to discriminate functional and non-functional populations relative to other environmental context-focused characterizations, as evidenced by the detailed phylogenetic analysis of Caulobacteraceae, and SIP offers a far less biased approximation to in situ conditions than conventional culturing-based surveys. The most common criticism of SIP is the possibility of misattributing function due to cross-feeding that results from the assimilation of carbon by predators, parasites or opportunists. This is a particularly relevant concern given the extracellular nature of lignocellulose depolymerization. The clearest suggestion that cross-feeding had occurred in this study was the steep decrease in enrichment of Gram-positive PLFAs in soils incubated with fungicide. While this is a relatively unambiguous indication that cross-feeding was occurring, the observation that the abundances of many Gram-positive taxa deemed putatively lignolytic actually increased in antibiotic treatments suggests the possibility of other, as of now, unknown explanations for this phenomenon. Cross-feeding may also have led to the putative designation of members of Candidatus Saccharibacter (formerly TM7) as cellulolytic in Chapter 3. This group contains obligate parasites, including the recent cultivation of a TM7 parasite of Actinobacteria (He et al., 2015). While this specific TM7 parasite had only 85% 16S rRNA similarity to putatively cellulolytic OTUs, misattribution through tightly interdependent parasitism of Actinobacteria is a distinct possibility given the substantial cellulolytic activity of Actinobacteria observed. Similarly, in Chapter 4, a draft genome classified as Parcubacterium, suspected to be obligate symbionts (Nelson and Stegen, 2015), was recovered. In a previously published SIP-cellulose experiment, OTUs classified as Xiphinematobacter met the criteria for cellulolytic designation, yet are also obligate cytoplasmic symbionts of nematodes (El Zahar Haichar et al., 2007). While the evidence for cross-feeding is noteworthy, time-course experiments showed that the same subset of PLFAs enriched on Day 4 remained the predominant enriched PLFAs and that the enrichment of other PLFAs was minimal. Štursová et al., (2012) reported a similar lack of evidence for widespread cross-feeding, comparing incubations with cellulose at eight and fifteen days. Most importantly, confidence in SIP data should stem from the accuracy in which previously characterized lignocellulolytic taxa are found to occur. Chapter 5: Conclusions The research described in this thesis contributes new knowledge and perspective along with valuable data and methodology for understanding forest soil decomposers and post-harvesting selection pressures on soil microbial communities. This work is one of few studies to employ SIP to study broader ecological phenomena, rather than solely as a tool to target and identify novel functional taxa. SIP linked, for the first time, changes in cellulolytic populations with changes in overall activity. In that experiment, the increased relative abundance of Chaetomiaceae, and other bacteria associated with desert-environments, led to the discovery that desiccation, radiation and heat-tolerant taxa were thriving in soils. Not completely surprising, given the exposed nature of clear-cut forest soils, this phenomenon was documented in detail in this thesis, highlighting specific taxa relevant for monitoring and posing questions about the long-term implications of such a change. What might be the persistence and legacy of these stress-tolerant taxa across multiple harvesting cycles? Will their influence compound or dissipate over time? The commonalities identified between taxa thriving post-harvesting and following wildfire suggest that chronosequences from fire-affected forests may be reasonable analog systems for studying microbial succession in the decades following timber harvesting. The potential long-term functional consequences of timber harvesting were apparent in a number of experimental results. The previously mentioned reductions in cellulolytic activity and net respiration in microcosms according to treatment (section 3.3) or, the decline of populations Caulobacteraceae and Opitutaceae, each correlated with total levels of enrichment from lignin and cellulose, respectively (section 4.2.7). The overall decline of methanotrophic populations was consistent with a growing body of research showing significant impacts on methane-uptake following harvest. The functional impact of the shifts in ectomycorrhizal fungi and decline of rhizospheric bacteria are less clear, and these organisms represent populations of key interest for future research. Varying the degree of organic matter removal (or retention) influenced the relative abundance of a number of populations in the decades following harvesting. OM retention had two major observable effects i) mitigating abiotic factors and the corresponding degree of population expansion or decline; and ii) fostering saprotrophic populations, including those specialized in wood decay. The potential of OM retention to mitigate abiotic changes and population shifts appeared to be the stronger of the two effects, given the modeling of abundance patterns. As such, this research found that OM retention may be a pragmatic tool in broadly managing the abiotic effects of disturbance on soil communities, of particular interest on methanotrophic populations. Yet, assessing the impact of intermediate levels of OM retention was more challenging given the lack of environmental data and the generalizability of patterns across ecozones. Therefore, the extent of differences between OM1 and OM2 treatments, most relevant to modern forestry practices, may not be fully clear and closer attention to differentiate the two should be made in future LTSP studies. Comparisons of forest soils communities from across North America revealed the scope of variation in community structure. The degree of variation observed raises the possibility that soil management may require monitoring and assessment of soil ecology at the local level. Bacterial species were far more cosmopolitan than fungi and, thus, had a greater likelihood of demonstrating generalized responses to harvesting. The more discrete, localized distribution of fungi strongly supports the need to perform regional or local assessments, given their major role in forest soil ecology. Studying the sources of biogeographical variation, whether due to environmental conditions or ecotypic variation within closely related populations, can reveal aspects of the physiology, evolution and dispersal of forest soil microorganisms. Similarly, the abundance patterns of species (OTUs) may inform understanding of physiology. For example, evidence for a saprobic, wood-degrading lifestyle of members of Thelephora may be inferred by their sizably expanded populations in OM1 and OM2. Despite broad biogeographical variation in community structure, a number of phyla were consistently associated with organic (Alphaproteobacteria and Bacteroidetes) and mineral layer soils (Delta- and Gammaproteobacteria, TM7, Firmicutes, Armatimonadetes and Chloroflexi). The lack of knowledge of taxa endemic to mineral soils should be a major focus in future studies of both harvesting impacts, given substantive expansion of Chloroflexi and AD3, as well as the unique cellulolytic (Armatimonadetes, Planctomycetes and Verrucomicrobia) and lignolytic taxa therein (Acidobacteria and Sinobacteraceae). The potential of bacteria to degrade lignin has become more established in recent years through culture-based screening and enzyme characterization, but only a handful of studies have examined their activity from an environmental perspective. As such, this research offers the most extensive characterization of bacterial lignin-degraders from a wide range of forest soils to date. The work confirmed that a number of previously characterized genera were active in soil and implicated a number of novel taxa in an attempt to direct the search for novel lignin-modifying enzymes. This research marks an end to speculation on the involvement of Caulobacter and Caulobacteraceae spp. in the decomposition of all three major lignocellulose polymers. In doing so, it may open an interesting case-study in the evolutionary history and lignocellulolytic adaptation of a bacterial lineage with notably unique methods of dispersal and adhesion. The relatively diminutive role of fungi in lignin degradation in SIP microcosm experiments challenges the conventional perspective on the role of fungi as the most prominent members of the soil decomposer community. A similar break from convention was the finding that cellulolytic activity decreased when populations of fungi (Chaetomiaceae) expanded. These results draw attention to the involvement of bacteria in degrading recalcitrant forms of carbon below the surface. Given the aim of the LTSP network to study forest regeneration in the decades to come, this research provides comprehensive data on the state of microbial community structure prior to canopy closure. The data has been carefully curated, and made publicly available to facilitate the longitudinal study. The scope and scale of SIP work is unprecedented with replicated PLFA, pyrotag and whole shotgun metagenomic data from over one hundred soil samples. The recovery of 13C-labeled DNA alone required over 70 ultracentrifugation runs, amounting 140 days of ultracentrifugation. To ensure the quality of research, a highly sensitive and accurate method for quantifying 13C-content in DNA was developed along with a high-throughput method for recovering DNA from the CsCl gradient. Both were critical to optimize experiments and process the high volume of fractions recovered in processing so many samples. The improved assembly of metagenomic data illustrates the utility of SIP methods for culture-independent studies of highly diverse soil communities. Without the 3 to 20-fold increase in percentage of read assembled, considerable information about the CAZy content of lignocellulolytic taxa could not have been obtainable. And, given the quality and abundance of assembled data, this thesis may be just the beginning of a wealth of discovery by those prospecting for novel CAZymes. Even with the efforts documented in this thesis to better understand the impacts of timber harvesting on soil communities, forest researchers are a far from a conceptual understanding of what microbial processes are occurring and what effects shifts in microbial communities might have. In this study, 30% of taxa impacted by harvesting were unclassifiable beyond the family level, and the total number of unclassified reads increased with increasing harvesting intensity. These stats reveal how far we are from a clear assessment of the ecology of forest soil communities and timber harvesting disturbance. For plant communities, timber harvesting increased the richness of ground cover species, driven by the colonization of r-strategists even over the long-term (Roberts et al., 2016). Microbial studies may borrow such broad ecological categorizations to begin inferring consequences of harvesting without knowledge of the ecology of all taxa. For example, metagenomics makes it possible to infer the relative abundance of microbial r-strategist versus K-strategists based on estimations of average genome size (Nayfach and Pollard, 2015). The concept of function-oriented phylogenetic databases, such as FUNGuild, may also prove useful in building towards a relevant functional characterization of microbial communities. Amidst the vast complexity and considerable unknowns of soil microbial ecology, long-term studies like the LTSP provide stable, comprehensive data collection, which leads to the discovery and formulation of valuable new perspectives. Combining the study of forest soil microbial ecology with bioprospecting for commercially relevant biocatalysts is a shrewd strategy for advancing interests in the forest industry. Properly paired, they can improve forest management practices and contribute to basic research that can create new revenue streams for forest products. 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Appendix A Synthesis of Coniferyl Alcohol from 13C-ring labelled Vanillin Written and performed by Dr. Rahul Singh Aldol condensation of vanillin in the presence of malonic acid Aldol condensation of 1:1 molar ratio of malonic acid and vanillin in the presence of catalytic amounts of piperidine and aniline (~6 drops) in pyridine. Thus, in a 3-neck flask (100 ml), 10 ml pyridine, 2.5 g vanillin and 2 g malonic acid were added and the mix was reflux at 55 °C for ~16 h. Working up the reaction Post reflux, the mix was removed from the flask and 60 ml chloroform was added (rinsed the flask with that as well). This mixture was extracted 6 times with acidic water (pH ~2). Essentially, ferulic acid precipitates in acidic water. Ferulic acid can be recovered as precipitate as well as extraction by ethyl acetate. After recovery, the yield was ~ 87%. Check on TLC (1:1 ethyl acetate/hexane) for the leftover vanillin (salvage in the case of labeled material). Esterification of ferulic acid Esterification eases the reduction of ferulic acid to coniferyl alcohol. In a 3 neck flask, 2.5 g ferulic acid was mixed with 10 ml methanol and ~ 50 l conc. HCL. This mixture was refluxed at 65-70 °C for 5-6 h. Test the progress of the reaction on TLC, if required add more HCL. Once finished, recover the sample using ethyl acetate and dry under vacuum. Expected yield is ~ 95% Reduction with Lithium Aluminium Hydride (LiAlH) A 2 neck flask was set up with an add funnel under positive nitrogen pressure. The flask was pre-weighed with 0.732 g of LiAlH, to which 60 ml of freshly distill THF was added slowly, while stirring. Methyl ester of ferulic acid (~ 2.5 g) was mixed with 14 ml of freshly distill dry THF and placed in the add funnel. The flask was kept on ice and ester was added drop wise really slowly. Towards the end, some additional THF was used to rinse the add funnel. The solution was stirred at room temperature for additional 2 h and then bought back at 0 °C. At this point, 12 ml ethyl acetate was added drop wise, followed by 70 ml of 2 N HCl. These were added slowly as the residual LiAlH was reactive initially. Also, note that stirring also gets difficult towards the end due to accumulation of salts. Finally, the product was extracted in ethyl acetate and dried under vacuum. Following drying, the product can be purified using silica chromatography. Appendix B – Broad Ecological Impacts of Timber Harvesting Figure B.1. Abundance pattern of taxa that illustrate the broad character of environmental change detectable in soil pyrotag libraries. Taxa from 16S rRNA libraries reveal the expansion of plant ground cover (Chloroplast and Mitochondrial rRNA genes). The decline of entomopathic fungi (Lecanicillium spp.) reveal potential changes in insect host populations. Error bars correspond to one standard error of the mean. Appendix C – Detailed Descriptions of Lignocellulolytic Bacterial Populations The most prominent bacterial hemicellulolytic genera were Agrobacterium, Bacillus, Paenibacillus, and Streptomyces (Figure C.1) and included taxa also active on cellulose, such as Cellvibrio, Janthinobacterium, Cytophagaceae and Salinibacterium (Figure C.2). The most prominent cellulose-degraders were members of the candidate division ‘FBP’ within Armatimonadetes (Figure C.2). Sequences annotated as FBP were, at best, 80% similar to any sequence in NCBI’s curated rRNA database and clustered with sequences from uncultured organisms, distantly related to Fimbriimonas ginsengisoli in the SILVA tree. Other groups of the Armatimonadetes (FW68) were also designated cellulolytic (Figure C.2). Exclusively cellulolytic bacterial taxa included Kitasatospora and other unclassified Streptomycetaceae; DH61 (Planctomycetes); MIZ46 and Polyangiaceae (Deltaproteobacteria), and Leptothrix (Burkholderiales) (Figure C.2). Binning assembled metagenomic data from 13C-cellulose libraries yielded one high-quality, and numerous lower quality, draft genomes classified as Sorangium (Polyangiaceae), as well as lower quality drafts classified by LCA as Myxococcus, Cytophaga, Chthonomonas (Armatimonadetes), and Chthoniobacter and Pedosphaera (Verrucomicrobia) (Figure 4.14). A number of high-quality draft genomes were recovered for cellulolytic fungi, including Chaetomium, Neurospora and Pseudogymnoascus. Lignolytic bacterial taxa were typically from novel and uncultured clades or uncultured clades within better known families. Taxa originating from poorly characterized clades included Acidobacteria from Grp-2 (Ellin6531), Grp-3 (Solibacterales; SILVA clade ‘Unknown Family_Candidatus Solibacter’) and Grp-6 (iii1-15) (Figure C.3). These clades Figure C.1. Abundance barplots of prominent hemicellulolytic taxa depicting differential abundance between 12C- and 13C-pyrotag libraries including in situ abundances across ecozones. Figure C.2. Abundance barplots of prominent cellulolytic taxa depicting differential abundance between 12C- and 13C-pyrotag libraries including in situ abundances across ecozones. Figure C.2. continued… possess a prodigious number of sequences in the SILVA repository (493, 1,466 and 3,817, respectively), but possess no cultured representatives. These groups were not related to the predominant groups of Acidobacteria common among in 12C-libraries. Three low-quality draft genomes of Acidobacteria were recovered from 13C-lignin libraries (Table E.13). Lignolytic Actinobacteria were identified from novel clades within Conexibacteraceae (SILVA clade ‘YNPFFP1’) and Gaiellaceae, as well as clades with cultured representatives such as Conexibacter (closest representative: C. woesi), Lysinimonas (Microbacteriaceae: L. soli), Arthrobacter (Micrococcaceae; A. soli), and Jatrophihabitans (Frankinaceae; J. endophyticus). Two low quality draft genomes classified to Conexibacter were recovered from 13C-lignin libraries. Putatively lignolytic members of Bacteroidetes grouped with a clade of environmental sequences in the family Cytophagaceae (SILVA clade ‘Cyotphagaceae_1) and with Mucilaginibacter (SILVA clade ‘Mucilaginibacter_1’), which were closely related to cultured taxa M. frigoritolerans and M. herbaticus. Low-quality draft genomes classified as Mucilaginibacter and Chitinophagaceae were recovered from 13C-lignin libraries. Other lignolytic OTUs from poorly characterized clades included Elusimicrobia, formerly Termite Group1, (FAC88; SILVA clade ‘Lineage IIa’); Sinobacteraceae (SILVA clade ‘Xanthomonadales Intercetae Sedis_Acidibacter’); Cystobacteraceae (SILVA clade ‘uncultured’ within Myxococcales) and Piscirickettsiaceae (SILVA clade ‘uncultured’ within Xanthomonadales). Lignolytic OTUs also clustered with a number of taxa available in culture collections, such Bradyrhizobium canariense (‘Bosea’ in Table 4.1), Altererythrobacter dongtanensis (Erythrobacteraceae), Novosphingobium lentum and Sphingomonas echinoides (Sphingomonadaceae), Aquaspirillum polymorphum (Telmatospirillum), Azospirillum doebereinerae (Alphaproteobacteria) and Cystobacter gracilis (Cystobacteraceae). Figure C.3. Abundance barplots of prominent lignolytic taxa depicting differential abundance between 12C- and 13C-pyrotag libraries including in situ abundances across ecozones. ‘Cytophagaceae_1’ was classified as Clostridium (Firmicutes) by GreenGenes, but placed in the ‘Cytophagaceae_1’ clade in SILVA (Bacteroidetes). Additional lignolytic taxa were identified from metagenomic libraries corresponding to Cardiobacteriaceae, Enterobacteriaceae, Ectothiorhodospiraceae, Hyphomonadaceae and Pseudomonadaceae (Figure C.4). Attempts to identify which genera within these families were differentially abundant were unsuccessful due to the lack of specificity of LCA classification, an example of which is provided for family Ectothiorhodospiraceae (Figure C.4). Another notable and problematic result of using LCA classification was illustrated by the classification of Pantholops, a Tibetan antelope from the ruminant family Bovidae, as differentially abundant in 13C-lignin libraries (12-fold) among all ecozones. Given the nature of samples used, it is unlikely that the genome assembly frequently the top blast hit used in LCA (Accession: GCA_000400835) was the real source of these sequences. Instead, the Pantholops genome may contain contamination from lignolytic microorganisms or, though improbable, horizontally transferred genes from lignolytic organisms. The genus Burkholderia and members of unclassified Burkholderiaceae were active on all three substrates. Lignolytic Burkholderia clustered with B. nodosa and B. tropica in SILVA. Members of Variovorax and unclassified Comamonadaceae were active on lignin, while Leptothrix and Polaromonas, both from family Comamonadaceae, were cellulolytic and hemicellulolytic. One unclassified Comamonadaceae OTU showed considerable cellulolytic activity across all ecozones and grouped with Aquincola in SILVA (Figure C.6). Metagenomic binning recovered one high quality draft genome classified as Comamonadaceae (Figure C.6) and a lower-quality draft from Variovorax (Table E.13). Cellulolytic Oxalobacteraceae related to Janthinobacterium and other unclassified groups within Oxalobacteraceae, while members of Pelomonas were active on all three substrates. Lignolytic OTUs from Pelomonas grouped with Chlorochromatium (C. aggregatum) in SILVA. A draft genome classified as Collimonas sp. (Oxalobacteraceae) was recovered from 13C-lignin libraries. Figure C.4. Abundances of prominent lignolytic taxa identified by differential abundance between 12C- and 13C-whole shotgun metagenomes for cellulose and lignin. These taxa were not identified in analyses of pyrotag libraries. Figure C.5. Abundances of metagenomic reads classified to all genera within the family Ectothiorhodospiraceae. Each genus shows a nearly identical abundance pattern in which 13C-lignin libraries are differentially more abundant than 12C-lignin libraries. The consistency of this pattern is unlikely biological, but rather related to the use of LCA to classify metagenomic reads. These graphs demonstrate why genus-level classification with LCA is putative at best. Figure C.6. Abundances of all prominently hemicellulolytic, cellulolytic and lignolytic genera of Burkholderiales based on differential abundance between 12C- and 13C-pyrotag libraries. Figure C.6 … continued Figure C.6 … continued Appendix D Table E.1. Summary of studies on the long-term impacts of timber harvesting on physicochemical properties of soil, forest productivity and soil biological. Appendix E – Supplementary Tables Impact Since Harvest Major Conclusions Geographic Location Forest Response Variable(s) Focus ReferenceAffected 1 year Forest f loor removal affects nitrogen content.Northern British Columbia, CanadaConiferous Stable isotope analysis Chemical Choi 2005Affected 5 - 7 yearsDifferences in soil carbon pools w ith depth on account of organic matter removal.Washington State, USA Coniferous Soil carbon Chemical Strahm 2009Affected 4 yearsReduced methane uptake in clear-cut forest; no effect in selective cut.Bavaria, Germany Coniferous Methane flux; soil properties Chemical Wu 2011Affected 1 - 8 years Decomposition rates slow ed post-harvesting. British Columbia, Canada Coniferous Mass lossChemical & EcologicalPrescott 2000Affected 1 year Arthrobacter populations increase w ith harvesting.Northern British Columbia, CanadaConiferous PLFA; bacterial culturing Ecological Axelrood 2002Affected 1 yearReduction in Pseudomonas populations from harvesting.Northern British Columbia, CanadaConiferous 16S Library Ecological Axelrood 2002Affected 13 years Change in microbial community structure.Northern British Columbia, CanadaConiferousBacterial, archael and fungal phylogenetic genesEcological Hartmann 2009Affected 10 years Change in microbial community structure.Northern British Columbia, CanadaConiferousBacterial and fungal phylogenetic genesEcological Hartmann 2012Affected 12 - 16 yearsModest changes in hemicellulolytic microbial populations.LTSP - Broadly Distributed Across USA and CanadaConiferousStable isotope probing; bacterial and fungal phylogenetic genesEcological Leung 2015Affected 30 yearsReduced respiration and changes in microbial community.Wyoming, USA Coniferous PLFA; CO2 flux; soil properties Ecological Chatterjee 2008Affected 20 yearsChanges in fungal abundance and microbial community structure.Northern Alberta, Canada ConiferousPLFA; bacterial and fungal phylogenetic genesEcological Hynes 2012Affected 1 & 8 yearsDiversity of omnivorous and predacious nematodes low ered in clearcuts.British Columbia, Canada Coniferous Nematode populations Ecological Forge and Simard 2001Affected 2 yearsSoil microbial communities w ere altered by harvesting, but intensif ication did not cause further disturbance.Northern Ontario Coniferous Bacterial and fungal phylogenetic genes; microbial biomassEcological Smenderovac 2014Affected 4 years OM removal altered community structure. Missouri, USA Coniferous PLFA Ecological Ponder 2002Affected 5 - 11 yearsNo loss in species richness, but shift in community by harvesting.Borneo Palm Bacterial phylogenetic genes Ecological Lee-Cruz (2013)Affected 1 - 42 yearsPartial cutting reduced biomass; signif icant variation unexplained by cutting intensity.Global Mixed Tree biomass Productivity Zhou 2013 Impact Since Harvest Major Conclusions Geographic Location Forest Response Variable(s) Focus ReferenceAffected | Negative2 - 4 years CO2 flux reduced by organic matter removal. Northern Ontario Coniferous Soil CO2 flux; soil properties Chemical Fleming 2006aAffected | Negative40 years Soil respiration reduced from organic matter removal. Northern Ontario Coniferous Soil CO2 flux; soil properties Chemical Webster 2016 Affected | Negative6 - 10 yearsDecreaes in microbial biomass and protease, phosphatase and dehydrogenase activities.Northern British Columbia, CanadaConiferous Microbial C & N; enzyme activity Ecological Tan 2008Affected | Negative12 years Lignocellulose degrading gene abundance reduced.Northern British Columbia, CanadaConiferous Metagenomic DNA libraries Ecological Cardenas 2015Affected | Negative1 - 20 years Net decrease in microbial biomass and activity. Global Mixed Biomass and respiration Ecological Holden 2013Affected | Positive2 yearsMinor increase in decomposition w ith harvesting, likely due to physical rather than biological changesNorthern British Columbia, CanadaConiferousLitter mass; mesofauna; soil propertiesChemical & EcologicalKranabetter 1999Neutral 3 - 7 yearsNo negative impact of forest f loor removal on N transformation ratesNorthern British Columbia, CanadaConiferous Microbial C & N Chemical Tan 2005Neutral 10 yearsCO2 flux unaffected, slight soil C increase w ith harvestingNorth Carolina, USA Coniferous Soil CO2 flux; soil properties Chemical Butnor 2006Neutral 5 yearsOrganic removal had negatively affected by harvestingLTSP - Broadly Distributed Across USA and CanadaConiferous Total C & N Chemical Sanchez 2005Neutral 3 - 7 years No net changes microbial CN content or respirationNorthern British Columbia, CanadaConiferousMicrobial C & N; respiration; soil propertiesChemical Mariani 2006Neutral 1 - 10+Harvesting had little to no effect on soil C and N in meta-analysisGlobal Mixed Total C & N ChemicalJohnson and Curtis 2001Neutral 10 years No net differences in tree biomassLTSP - Broadly Distributed Across USA and CanadaConiferous Tree biomass; soil properties Productivity Sanchez 2006Neutral 10 years Few consistent effects on planted tree biomassLTSP - Broadly Distributed Across USA and CanadaConiferous Tree biomass; foliar nutrients Productivity Ponder 2012Neutral 10 years Tree biomass unaffected by organic matter removal Washington State, USA Coniferous Tree biomass Productivity Holub 2013Tempoeral | Variable3 yearsIncreased rate of tree grow th after 1 year, follow ed by reductionsBritish Columbia, Canada Coniferous Tree biomass Productivity Kneeshaw 2002Temporal | Affected1, 2, 4, 5 & 7 yearsLong-term shift in ratio of bacterial and fungal abundanceWisconsin, USA Deciduous PLFA Ecological Lew andow ski 2015Temporal | Affected20, 40 & 40+ yearsDiversity of fungi reduced in harvested sites Northern Alberta, Canada Mixed Culturable fungi Ecological Lumley 2001Temporal | Affected2 yearsLignocellulose mineralization initially increased, then decreated as w ell as reductions in other soil elments like S, and KMissouri, USA Coniferous14-C lignocellulose mineralization; soil propertiesEcological & ChemicalSpratt 2000 Impact Since Harvest Major Conclusions Geographic Location Forest Response Variable(s) Focus ReferenceTemporal | Affected | Negative3 & 10 years Nutrient depletion over time Vancouver Islanc, Canada ConiferousFoliar and microbial C & N; soil propertiesChemical & EcologicalChang et al 1995Temporal | Neutral10 yearsSoil CO2 flux w as impact follow ing harvesting, but returned to near pre-harvested state after 10 yearsCentral Ontario, Canada Deciduous Soil CO2 flux; soil properties Chemical Peng and Thomas 2006Temporal | Neutral3 - 6 years N mineralization unaffected by organic matter removal North Carolina, USA Deciduous Nitrogen contents Chemical Lee 2003Temporal | Neutral10-11 years Soil chemistry unaffected by harvesting Northern Alberta, Canada Coniferous Foliar nutrients; soil propertiesChemical & ProductivityKishchuk et al. 2015Temporal | Variable1 - 20 yearsImpacts on soil properties variable by time post-harvesting, soil depth and geographyLTSP - Broadly Distributed Across USA and CanadaConiferous Soil properties Chemical Thiffault 2011Variable 40 + yearsSoil N replenished under stem-only harvesting, uncertain under w hole-treeNorw ay Coniferous N contents Chemical Merila 2014Variable 4 - 8 yearsElemental concentrations w ere variably impacted post-harvestinSouthern Sw eden Coniferous Soil properties Chemical Gronflaten 2008Variable 5 yearsImpacts on tree survival and biomass variable by geography & tree speciesLTSP - Broadly Distributed Across USA and CanadaConiferous Tree survival, biomass Chemical & ProductivityFleming 2006bVariable 2 yearsOrganic removal had variable influence on tree biomassNorthern British Columbia, CanadaConiferous Tree biomass,;foliar NChemical |& ProductivityKamaluddin 2005Variable 1 yearNitrifying communities unaffected; reduction in soil respiration; no impact on tree grow thOttaw a, Canada MixedCulturing; CO2 flux; nitrogen contentsEcological & ProductivityHendrickson 1985 S o urc e S ub s t ra t e A c t iv it y P hy lum C las s Ord e r F amily Ge nus F ull N ameTian 2014 Aromatics Validated Actinobacteria Actinobacteria Corynebacteriales Mycobacteriaceae Mycobacterium Mycobacterium smegmatisTian 2014 Aromatics Validated Actinobacteria Actinobacteria Corynebacteriales Mycobacteriaceae Mycobacterium Mycobacterium tuberculo s isTian 2014 Aromatics Validated Actinobacteria Actinobacteria Corynebacteriales Nocard iaceae Rhodococcus Rhodococcus erythropo lis TA421Taylo r 2012 Aromatics Validated Actinobacteria Actinobacteria Corynebacteriales Nocard iaceae Rhodococcus Rhodococcus erythropo lis A5.1Tian 2014 Aromatics Validated Actinobacteria Actinobacteria Corynebacteriales Nocard iaceae Rhodococcus Rhodococcus fasciansTian 2014 Aromatics Validated Actinobacteria Actinobacteria Corynebacteriales Nocard iaceae Rhodococcus Rhodococcus equiTaylo r 2012 Aromatics Validated Actinobacteria Actinobacteria Micrococcales Microbacteriaceae Microbacterium Microbacterium phyllo sphaerae A1.1Taylo r 2012 Aromatics Validated Actinobacteria Actinobacteria Micrococcales Microbacteriaceae Microbacterium Microbacterium marinilacus A1.2Tian 2014 Aromatics Validated Actinobacteria Actinobacteria Strep tomycetales Strep tomycetaceae Strep tomyces Strep tomyces cyaneus CECT 3335Tian 2014 Aromatics Validated Actinobacteria Actinobacteria Strep to spo rang iales Nocard iopsaceae Thermob ifida Thermob ifida fuscaTian 2014 Aromatics Validated Firmicutes Bacilli Bacillales Bacillaceae Bacillus Bacillus haloduransTian 2014 Aromatics Validated Firmicutes Bacilli Bacillales Bacillaceae Bacillus Bacillus sub tilisTian 2014 Aromatics Validated Pro teobacteria Betap ro teobacteria Burkho lderiales Burkho lderiaceae Burkho lderia Burkho lderia cepaciaTian 2014 Aromatics Validated Pro teobacteria Betap ro teobacteria Burkho lderiales Burkho lderiaceae Burkho lderia Burkho lderia sp . VE22Tian 2014 Aromatics Validated Pro teobacteria Gammapro teobacteria Enterobacteriales Enterobacteriaceae Escherichia Escherichia co li JM109Tian 2014 Aromatics Validated Pro teobacteria Gammapro teobacteria Enterobacteriales Enterobacteriaceae Klebs iella Klebs iella pneumoniaeGhodake 2009 Aromatics Validated Pro teobacteria Gammapro teobacteria Pseudomonadales Moraxellaceae Acinetobacter Acinetobacter calcoacet icus NCIM 2890Tian 2014 Aromatics Validated Pro teobacteria Gammapro teobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas fluo rescens GcM5-1ATian 2014 Aromatics Validated Pro teobacteria Gammapro teobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas aerug inosa BCHMedie 2012 Cellulo se Pred icted Acidobacteria Acidobacteriia Acidobacteriales Acidobacteriaceae Acidobacterium Acidobacterium capsulatum ATCC 51196 Med ie 2012 Cellulo se Pred icted Acidobacteria Acidobacteriia Acidobacteriales Acidobacteriaceae Acidobacterium Acidobacterium sp . MP5ACTX9 Med ie 2012 Cellulo se Pred icted Acidobacteria Acidobacteriia Acidobacteriales Acidobacteriaceae Koribacter Cand idatus Koribacter versat ilis Ellin345 Med ie 2012 Cellulo se Pred icted Acidobacteria Acidobacteriia Acidobacteriales Acidobacteriaceae Terrig lobus Terrig lobus saanens is SP1PR4 Med ie 2012 Cellulo se Pred icted Acidobacteria So libacteres So libacterales So libacteraceae So libacter So libacter us itatus Ellin6076 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Acido thermales Acido thermaceae Acido thermus Acido thermus cellulo lyt icus 11B ATCC 43068 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Bifidobacteriales Bifidobacteriaceae Bifidobacterium Bifidobacterium ado lescentis ATCC 15703 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Bifidobacteriales Bifidobacteriaceae Bifidobacterium Bifidobacterium animalis subsp . lact is AD011 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Bifidobacteriales Bifidobacteriaceae Bifidobacterium Bifidobacterium animalis subsp . lact is Bb12 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Bifidobacteriales Bifidobacteriaceae Bifidobacterium Bifidobacterium animalis subsp . lact is DSM 10140 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Bifidobacteriales Bifidobacteriaceae Bifidobacterium Bifidobacterium animalis subsp . lact is V9 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Bifidobacteriales Bifidobacteriaceae Bifidobacterium Bifidobacterium dentium Bd1 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Bifidobacteriales Bifidobacteriaceae Bifidobacterium Bifidobacterium longum subsp . BBMN68 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Bifidobacteriales Bifidobacteriaceae Bifidobacterium Bifidobacterium longum subsp . JDM301 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Bifidobacteriales Bifidobacteriaceae Bifidobacterium Bifidobacterium longum subsp . JCM 1217 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Bifidobacteriales Bifidobacteriaceae Bifidobacterium Bifidobacterium longum NCC2705 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Bifidobacteriales Bifidobacteriaceae Bifidobacterium Bifidobacterium longum subsp . infantis 157F Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Bifidobacteriales Bifidobacteriaceae Bifidobacterium Bifidobacterium longum subsp . longum F8 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Bifidobacteriales Bifidobacteriaceae Bifidobacterium Bifidobacterium longum DJO10A Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Bifidobacteriales Bifidobacteriaceae Bifidobacterium Bifidobacterium longum subsp . infantis JCM 1222 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Bifidobacteriales Bifidobacteriaceae Bifidobacterium Bifidobacterium pseudocatenulatum D2CA Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Catenulispo rales Catenulispo raceae Catenulispo ra Catenulispo ra acid iphila DSM 44928 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Corynebacteriales Mycobacteriaceae Mycobacterium Mycobacterium sp . JLS Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Corynebacteriales Mycobacteriaceae Mycobacterium Mycobacterium sp . KMS Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Corynebacteriales Mycobacteriaceae Mycobacterium Mycobacterium sp . MCS Table E.2. Extensive compilation of all known lignolytic and cellulolytic bacteria, including both predicted function (based on genomic content) and validated function. Fungal degraders have been included in this list, but without a comprehensive effort. Table ordered by substrate, activity, then according to descending taxonomic rank. S o urc e S ub s t ra t e A c t iv it y P hy lum C las s Ord e r F amily Ge nus F ull N ameMedie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Corynebacteriales Mycobacteriaceae Mycobacterium Mycobacterium vanbaalenii PYR-1 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Corynebacteriales Nocard iaceae Rhodococcus Rhodococcus equi 103S Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Corynebacteriales Tsukamurellaceae Tsukamurella Tsukamurella paurometabo la DSM 20162 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Frankiales Frankiaceae Frankia Frankia alni ACN14a Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Frankiales Frankiaceae Frankia Frankia sp . EAN1pec Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Geodermatophilales Geodermatophilaceae Geodermatophilus Geodermatophilus obscurus DSM 43160 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Glycomycetales Glycomycetaceae Stackeb rand tia Stackeb rand tia nassauens is DSM 44728 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Kineospo riales Kineospo riaceae Kineococcus Kineococcus rad io to lerans SRS30216 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Micrococcales Beutenberg iaceae Beutenberg ia Beutenberg ia cavernae DSM 12333 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Micrococcales Cellulomonadaceae Cellulomonas Cellulomonas fimi ATCC 484 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Micrococcales Cellulomonadaceae Cellulomonas Cellulomonas flavigena DSM 20109 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Micrococcales Dermabacteraceae Brachybacterium Brachybacterium faecium DSM 4810 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Micrococcales Jones iaceae Jones ia Jones ia denitrificans DSM 20603 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Micrococcales Microbacteriaceae Clavibacter Clavibacter michiganens is subsp . michiganens is NCPPB 382 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Micrococcales Microbacteriaceae Clavibacter Clavibacter michiganens is subsp . sepedonicus ATCC33113 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Micrococcales Microbacteriaceae Leifsonia Leifsonia xyli subsp . xyli s tr. CTCB07 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Micrococcales Microbacteriaceae Microbacterium Microbacterium tes taceum StLB037 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Micrococcales Micrococcaceae Arthrobacter Arthrobacter phenanthrenivo rans Sphe3 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Micrococcales Promicromonospo raceae Xylanimonas Xylanimonas cellulo s ilyt ica DSM 15894 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Micrococcales Sanguibacteraceae Sanguibacter Sanguibacter kedd ieii DSM 10542 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Micromonospo rales Micromonospo raceae Micromonospo ra Micromonospo ra aurantiaca ATCC 27029 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Micromonospo rales Micromonospo raceae Micromonospo ra Micromonospo ra sp . L5 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Micromonospo rales Micromonospo raceae Salinispo ra Salinispo ra arenico la CNS-205 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Micromonospo rales Micromonospo raceae Salinispo ra Salinispo ra trop ica CNB-440 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Micromonospo rales Micromonospo raceae Verrucos ispo ra Verrucos ispo ra maris AB-18 -032 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria None None Thermob ispo ra Thermob ispo ra b ispo ra DSM 43833 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Prop ionibacteriales Nocard io idaceae Kribbella Kribbella flavida DSM 17836 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Prop ionibacteriales Nocard io idaceae Nocard io ides Nocard io ides sp . JS614 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Pseudonocard iales Pseudonocard iaceae Actinosynnema Actinosynnema mirum DSM 43827 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Pseudonocard iales Pseudonocard iaceae Amyco latops is Amyco latops is med iterranei U32 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Pseudonocard iales Pseudonocard iaceae Saccharopo lyspo ra Saccharopo lyspo ra erythraea NRRL 2338 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Strep tomycetales Strep tomycetaceae Strep tomyces Strep tomyces avermit ilis MA-4680 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Strep tomycetales Strep tomycetaceae Strep tomyces Strep tomyces b ingchenggens is BCW-1 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Strep tomycetales Strep tomycetaceae Strep tomyces Strep tomyces coelico lo r A3(2 ) Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Strep tomycetales Strep tomycetaceae Strep tomyces Strep tomyces flavog riseus ATCC 33331 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Strep tomycetales Strep tomycetaceae Strep tomyces Strep tomyces g riseus subsp . g riseus NBRC 13350 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Strep tomycetales Strep tomycetaceae Strep tomyces Strep tomyces scab iei 87.22 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Strep to spo rang iales Nocard iopsaceae Nocard iops is Nocard iops is dassonvillei subsp . dassonvillei DSM 43111 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Strep to spo rang iales Nocard iopsaceae Thermob ifida Thermob ifida fusca YX Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Strep to spo rang iales Strep to spo rang iaceae Strep to spo rang ium Strep to spo rang ium roseum DSM 43021 Med ie 2012 Cellulo se Pred icted Actinobacteria Actinobacteria Strep to spo rang iales Thermomonospo raceae Thermomonospo ra Thermomonospo ra curvata DSM 43183 Med ie 2012 Cellulo se Pred icted Actinobacteria Coriobacteriia Coriobacteriales Coriobacteriaceae Coriobacterium Coriobacterium g lomerans PW2 Med ie 2012 Cellulo se Pred icted Actinobacteria Thermo leophilia So lirub robacterales Conexibacteraceae Conexibacter Conexibacter woesei DSM 14684 Med ie 2012 Cellulo se Pred icted Bactero idetes Bactero idetes incertae sed is Rhodo thermaceae Rhodo thermus Rhodo thermus marinus DSM 4252 Med ie 2012 Cellulo se Pred icted Bactero idetes Bactero id ia Bactero idales Bactero idaceae Bacteriodes Bacteriodes xylaniso lvens XB1A Med ie 2012 Cellulo se Pred icted Bactero idetes Bactero id ia Bactero idales Bactero idaceae Bactero ides Bactero ides frag ilis 638R Med ie 2012 Cellulo se Pred icted Bactero idetes Bactero id ia Bactero idales Bactero idaceae Bactero ides Bactero ides frag ilis YCH46 Med ie 2012 Cellulo se Pred icted Bactero idetes Bactero id ia Bactero idales Bactero idaceae Bactero ides Bactero ides helcogenes P 36 -108 ATCC 35417 Med ie 2012 Cellulo se Pred icted Bactero idetes Bactero id ia Bactero idales Bactero idaceae Bactero ides Bactero ides salanitronis DSM 18170 Med ie 2012 Cellulo se Pred icted Bactero idetes Bactero id ia Bactero idales Po rphyromonadaceae Palud ibacter Palud ibacter p rop ionicigenes WB4 S o urc e S ub s t ra t e A c t iv it y P hy lum C las s Ord e r F amily Ge nus F ull N ameMedie 2012 Cellulo se Pred icted Bactero idetes Bactero id ia Bactero idales Prevo tellaceae Prevo tella Prevo tella dentico la F0289 Med ie 2012 Cellulo se Pred icted Bactero idetes Bactero id ia Bactero idales Prevo tellaceae Prevo tella Prevo tella ruminico la 23 Med ie 2012 Cellulo se Pred icted Bactero idetes Bactero id ia Bactero idales Rikenellaceae Alis t ipes Alis t ipes shahii WAL 8301 Med ie 2012 Cellulo se Pred icted Bactero idetes Cytophag ia Cytophagales Cytophagaceae Cytophaga Cytophaga hutchinsonii ATCC 33406 Med ie 2012 Cellulo se Pred icted Bactero idetes Cytophag ia Cytophagales Cytophagaceae Dyadobacter Dyadobacter fermentans DSM 18053 Med ie 2012 Cellulo se Pred icted Bactero idetes Cytophag ia Cytophagales Cytophagaceae Leadbetterella Leadbetterella byssophila DSM 17132 Med ie 2012 Cellulo se Pred icted Bactero idetes Cytophag ia Cytophagales Cytophagaceae Sp iro soma Sp iro soma linguale DSM 74 Med ie 2012 Cellulo se Pred icted Bactero idetes Flavobacteriia Flavobacteriales Flavobacteriaceae Capnocytophaga Capnocytophaga ochracea DSM 7271 Med ie 2012 Cellulo se Pred icted Bactero idetes Flavobacteriia Flavobacteriales Flavobacteriaceae Cellulophaga Cellulophaga alg ico la DSM 14237 Med ie 2012 Cellulo se Pred icted Bactero idetes Flavobacteriia Flavobacteriales Flavobacteriaceae Cellulophaga Cellulophaga lyt ica DSM 7489 Med ie 2012 Cellulo se Pred icted Bactero idetes Flavobacteriia Flavobacteriales Flavobacteriaceae Flavobacterium Flavobacterium johnsoniae UW101 Med ie 2012 Cellulo se Pred icted Bactero idetes Flavobacteriia Flavobacteriales Flavobacteriaceae Zunongwang ia Zunongwang ia p ro funda SM-A87 SMA-87 Med ie 2012 Cellulo se Pred icted Bactero idetes Flavobacteriia Flavobacteriales None Flavobacteriales Flavobacteriales bacterium HTCC2170 Med ie 2012 Cellulo se Pred icted Bactero idetes Sphingobacteriia Sphingobacteriales Chit inophagaceae Chit inophaga Chit inophaga p inens is DSM 2588 Med ie 2012 Cellulo se Pred icted Bactero idetes Sphingobacteriia Sphingobacteriales Sphingobacteriaceae Pedobacter Pedobacter heparinus DSM 2366 Med ie 2012 Cellulo se Pred icted Bactero idetes Sphingobacteriia Sphingobacteriales Sphingobacteriaceae Pedobacter Pedobacter saltans DSM 12145Med ie 2012 Cellulo se Pred icted Bactero idetes Sphingobacteriia Sphingobacteriales Sphingobacteriaceae Sphingobacterium Sphingobacterium sp . 21 Med ie 2012 Cellulo se Pred icted Chlo ro flexi Chlo ro flexia Chlo ro flexales Roseiflexaceae Roseiflexus Roseiflexus cas tenho lzii DSM 13941 Med ie 2012 Cellulo se Pred icted Chlo ro flexi Chlo ro flexia Herpeto s iphonales Herpeto s iphonaceae Herpeto s iphon Herpeto s iphon aurantiacus ATCC 23779 Med ie 2012 Cellulo se Pred icted Deinococcus-thermusDeinococci Deinococcales Deinococcaceae Deinococcus Deinococcus geo thermalis DSM 11300 Med ie 2012 Cellulo se Pred icted Deinococcus-thermusDeinococci Deinococcales Trueperaceae Truepera Truepera rad iovictrix DSM 17093 Med ie 2012 Cellulo se Pred icted Fib robacteres Fib robacteria Fib robacterales Fib robacteraceae Fib robacter Fib robacter succinogenes subsp . succinogenes S85 Med ie 2012 Cellulo se Pred icted Firmicutes Bacilli Bacillales Alicyclobacillaceae Alicyclobacillus Alicyclobacillus acidocaldarius subsp . DSM 446 Med ie 2012 Cellulo se Pred icted Firmicutes Bacilli Bacillales Bacillaceae Bacillus Bacillus amylo liquefaciens FZB42 Med ie 2012 Cellulo se Pred icted Firmicutes Bacilli Bacillales Bacillaceae Bacillus Bacillus cellulo s ilyt icus DSM 2522 Med ie 2012 Cellulo se Pred icted Firmicutes Bacilli Bacillales Bacillaceae Bacillus Bacillus claus ii KSM-K16 Med ie 2012 Cellulo se Pred icted Firmicutes Bacilli Bacillales Bacillaceae Bacillus Bacillus halodurans C-125 Med ie 2012 Cellulo se Pred icted Firmicutes Bacilli Bacillales Bacillaceae Bacillus Bacillus lichenifo rmis ATCC 14580 / DSM13 Med ie 2012 Cellulo se Pred icted Firmicutes Bacilli Bacillales Bacillaceae Bacillus Bacillus pumilus SAFR-032 Med ie 2012 Cellulo se Pred icted Firmicutes Bacilli Bacillales Bacillaceae Bacillus Bacillus sub tilis BSn5 Med ie 2012 Cellulo se Pred icted Firmicutes Bacilli Bacillales Bacillaceae Bacillus Bacillus sub tilis subsp . sub tilis s tr. 168 Med ie 2012 Cellulo se Pred icted Firmicutes Bacilli Bacillales Bacillaceae Bacillus Bacillus sub tilis subsp . sp izizenii s tr. W23 Med ie 2012 Cellulo se Pred icted Firmicutes Bacilli Bacillales Bacillaceae Bacillus Bacillus sub tilis subsp . nat to BEST195 Med ie 2012 Cellulo se Pred icted Firmicutes Bacilli Bacillales Paenibacillaceae Paenibacillus Paenibacillus po lymyxa SC2 Med ie 2012 Cellulo se Pred icted Firmicutes Bacilli Bacillales Paenibacillaceae Paenibacillus Paenibacillus po lymyxa E681 Med ie 2012 Cellulo se Pred icted Firmicutes Bacilli Bacillales Paenibacillaceae Paenibacillus Paenibacillus sp . JDR-2 Med ie 2012 Cellulo se Pred icted Firmicutes Bacilli Bacillales Paenibacillaceae Paenibacillus Paenibacillus sp . Y412MC10 Med ie 2012 Cellulo se Pred icted Firmicutes Bacilli Lactobacillales Lactobacillaceae Lactobacillus Lactobacillus b revis ATCC 367 Med ie 2012 Cellulo se Pred icted Firmicutes Bacilli Lactobacillales Lactobacillaceae Lactobacillus Lactobacillus crispatus ST1 Med ie 2012 Cellulo se Pred icted Firmicutes Bacilli Lactobacillales Strep tococcaceae Lactococcus Lactococcus lact is subsp . cremoris NZ9000 Med ie 2012 Cellulo se Pred icted Firmicutes Bacilli Lactobacillales Strep tococcaceae Lactococcus Lactococcus lact is subsp . cremoris MG1363 Med ie 2012 Cellulo se Pred icted Firmicutes Bacilli Lactobacillales Strep tococcaceae Lactococcus Lactococcus lact is subsp . lact is KF147 Med ie 2012 Cellulo se Pred icted Firmicutes Bacilli Lactobacillales Strep tococcaceae Lactococcus Lactococcus lact is subsp . cremoris SK11 Med ie 2012 Cellulo se Pred icted Firmicutes Bacilli Lactobacillales Strep tococcaceae Strep tococcus Strep tococcus gallo lyt icus subsp . ATCC BAA-2069 Med ie 2012 Cellulo se Pred icted Firmicutes Bacilli Lactobacillales Strep tococcaceae Strep tococcus Strep tococcus gallo lyt icus UCN34 Med ie 2012 Cellulo se Pred icted Firmicutes Clos trid ia Clos trid iales Clos trid iaceae Clos trid ium Clos trid ium acetobutylicum ATCC 824 Med ie 2012 Cellulo se Pred icted Firmicutes Clos trid ia Clos trid iales Clos trid iaceae Clos trid ium Clos trid ium acetobutylicum EA 2018 Med ie 2012 Cellulo se Pred icted Firmicutes Clos trid ia Clos trid iales Clos trid iaceae Clos trid ium Clos trid ium cellulo lyt icum H10 Med ie 2012 Cellulo se Pred icted Firmicutes Clos trid ia Clos trid iales Clos trid iaceae Clos trid ium Clos trid ium cellulovo rans 743B Med ie 2012 Cellulo se Pred icted Firmicutes Clos trid ia Clos trid iales Clos trid iaceae Clos trid ium Clos trid ium lentocellum DSM 5427 S o urc e S ub s t ra t e A c t iv it y P hy lum C las s Ord e r F amily Ge nus F ull N ameMedie 2012 Cellulo se Pred icted Firmicutes Clos trid ia Clos trid iales Clos trid iaceae Clos trid ium Clos trid ium phyto fermentans ISDg95 Med ie 2012 Cellulo se Pred icted Firmicutes Clos trid ia Clos trid iales Clos trid iaceae Clos trid ium Clos trid ium saccharo lyt icum WM1 Med ie 2012 Cellulo se Pred icted Firmicutes Clos trid ia Clos trid iales Clos trid iaceae Clos trid ium Clos trid ium thermocellum ATCC 27405 Med ie 2012 Cellulo se Pred icted Firmicutes Clos trid ia Clos trid iales Clos trid iaceae Clos trid ium Clos trid ium thermocellum DSM 1313 Med ie 2012 Cellulo se Pred icted Firmicutes Clos trid ia Clos trid iales Eubacteriaceae Eubacterium Eubacterium eligens ATCC 27750 Med ie 2012 Cellulo se Pred icted Firmicutes Clos trid ia Clos trid iales Eubacteriaceae Eubacterium Eubacterium rectale ATCC 33656 Med ie 2012 Cellulo se Pred icted Firmicutes Clos trid ia Clos trid iales Eubacteriaceae Eubacterium Eubacterium rectale DSM 17629 Med ie 2012 Cellulo se Pred icted Firmicutes Clos trid ia Clos trid iales Eubacteriaceae Eubacterium Eubacterium rectale M104 /1 Med ie 2012 Cellulo se Pred icted Firmicutes Clos trid ia Clos trid iales Eubacteriaceae Eubacterium Eubacterium s iraeum 70 /3 Med ie 2012 Cellulo se Pred icted Firmicutes Clos trid ia Clos trid iales Eubacteriaceae Eubacterium Eubacterium s iraeum V10Sc8a Med ie 2012 Cellulo se Pred icted Firmicutes Clos trid ia Clos trid iales Lachnosp iraceae Butyrivib rio Butyrivib rio fib riso lvens 16 /4 Med ie 2012 Cellulo se Pred icted Firmicutes Clos trid ia Clos trid iales Lachnosp iraceae Butyrivib rio Butyrivib rio p ro teoclas t icus B316 Med ie 2012 Cellulo se Pred icted Firmicutes Clos trid ia Clos trid iales Lachnosp iraceae Coprococcus Coprococcus sp . ART55/1 Med ie 2012 Cellulo se Pred icted Firmicutes Clos trid ia Clos trid iales Lachnosp iraceae Roseburia Roseburia intes t inalis XB6B4 Med ie 2012 Cellulo se Pred icted Firmicutes Clos trid ia Clos trid iales Lachnosp iraceae Roseburia Roseburia intes t inalis M50 /1 Med ie 2012 Cellulo se Pred icted Firmicutes Clos trid ia Clos trid iales None Anaerocellum Anaerocellum thermophilum DSM 6725 Med ie 2012 Cellulo se Pred icted Firmicutes Clos trid ia Clos trid iales Ruminococcaceae Ruminococcus Ruminococcus albus DSM 20455Med ie 2012 Cellulo se Pred icted Firmicutes Clos trid ia Clos trid iales Ruminococcaceae Ruminococcus Ruminococcus sp . 18P13 Med ie 2012 Cellulo se Pred icted Firmicutes Clos trid ia Thermoanaerobacteralesincertae sed is Cald icellulo s irup to r Cald icellulo s irup to r hyd ro thermalis 108 Med ie 2012 Cellulo se Pred icted Firmicutes Clos trid ia Thermoanaerobacteralesincertae sed is Cald icellulo s irup to r Cald icellulo s irup to r kris t janssonii 177R1B Med ie 2012 Cellulo se Pred icted Firmicutes Clos trid ia Thermoanaerobacteralesincertae sed is Cald icellulo s irup to r Cald icellulo s irup to r krono tskyens is 2002 Med ie 2012 Cellulo se Pred icted Firmicutes Clos trid ia Thermoanaerobacteralesincertae sed is Cald icellulo s irup to r Cald icellulo s irup to r obs id ians is OB47 Med ie 2012 Cellulo se Pred icted Firmicutes Clos trid ia Thermoanaerobacteralesincertae sed is Cald icellulo s irup to r Cald icellulo s irup to r owensens is OL Med ie 2012 Cellulo se Pred icted Firmicutes Clos trid ia Thermoanaerobacteralesincertae sed is Cald icellulo s irup to r Cald icellulo s irup to r saccharo lyt icus DSM 8903 Med ie 2012 Cellulo se Pred icted Firmicutes Clos trid ia Thermoanaerobacteralesincertae sed is ThermoanaerobacteriumThermoanaerobacterium thermosaccharo lyt icum DSM 571 Med ie 2012 Cellulo se Pred icted Firmicutes Clos trid ia ThermoanaerobacteralesThermoanaerobacteraceae Thermoanaerobacter Thermoanaerobacter italicus Ab9 Med ie 2012 Cellulo se Pred icted Firmicutes Clos trid ia ThermoanaerobacteralesThermoanaerobacteraceae Thermoanaerobacter Thermoanaerobacter mathranii A3 DSM11426 Med ie 2012 Cellulo se Pred icted Firmicutes Clos trid ia ThermoanaerobacteralesThermoanaerobacteraceae Thermoanaerobacter Thermoanaerobacter mathranii subsp . mathranii s tr. A3 Med ie 2012 Cellulo se Pred icted Firmicutes Clos trid ia ThermoanaerobacteralesThermoanaerobacteraceae Thermoanaerobacter Thermoanaerobacter tengcongens is MB4 Med ie 2012 Cellulo se Pred icted Planctomycetes Planctomycetia Planctomycetales Planctomycetaceae Planctomyces Planctomyces b ras iliens is DSM 5305 Med ie 2012 Cellulo se Pred icted Planctomycetes Planctomycetia Planctomycetales Planctomycetaceae Rhodop irellula Rhodop irellula balt ica SH 1 Med ie 2012 Cellulo se Pred icted Pro teobacteria Alphap ro teobacteriaC ulobacterales Caulobacteraceae Asticcacaulis Asticcacaulis excentricus CB 48Med ie 2012 Cellulo se Pred icted Pro teobacteria Alphap ro teobacteriaC ulobacterales Caulobacteraceae Caulobacter Caulobacter crescentus CB15 Med ie 2012 Cellulo se Pred icted Pro teobacteria Alphap ro teobacteriaC ulobacterales Caulobacteraceae Caulobacter Caulobacter crescentus NA1000 Med ie 2012 Cellulo se Pred icted Pro teobacteria Alphap ro teobacteriaC ulobacterales Caulobacteraceae Caulobacter Caulobacter segnis ATCC 21756 Med ie 2012 Cellulo se Pred icted Pro teobacteria Alphap ro teobacteriaC ulobacterales Caulobacteraceae Caulobacter Caulobacter sp . K31 Med ie 2012 Cellulo se Pred icted Pro teobacteria Alphap ro teobacteriaRhizob iales Bradyrhizob iaceae Bradyrhizob ium Bradyrhizob ium japonicum USDA 110 Med ie 2012 Cellulo se Pred icted Pro teobacteria Alphap ro teobacteriaRhizob iales Methylobacteriaceae Methylobacterium Methylobacterium rad io to lerans JCM 2831 Med ie 2012 Cellulo se Pred icted Pro teobacteria Alphap ro teobacteriaRhizob iales Methylobacteriaceae Methylobacterium Methylobacterium sp . 4 -46 Med ie 2012 Cellulo se Pred icted Pro teobacteria Alphap ro teobacteriaRhizob iales Rhizob iaceae Agrobacterium Agrobacterium rad iobacter K84 Med ie 2012 Cellulo se Pred icted Pro teobacteria Alphap ro teobacteriaRhizob iales Rhizob iaceae Agrobacterium Agrobacterium sp . H13-3 Med ie 2012 Cellulo se Pred icted Pro teobacteria Alphap ro teobacteriaRhizob iales Rhizob iaceae Agrobacterium Agrobacterium tumefaciens s tr. C58 Med ie 2012 Cellulo se Pred icted Pro teobacteria Alphap ro teobacteriaRhizob iales Rhizob iaceae Agrobacterium Agrobacterium vit is S4 Med ie 2012 Cellulo se Pred icted Pro teobacteria Alphap ro teobacteriaRhizob iales Rhizob iaceae Rhizob ium Rhizob ium et li CFN 42 Med ie 2012 Cellulo se Pred icted Pro teobacteria Alphap ro teobacteriaRhizob iales Rhizob iaceae Rhizob ium Rhizob ium et li CIAT 652 Med ie 2012 Cellulo se Pred icted Pro teobacteria Alphap ro teobacteriaRhizob iales Rhizob iaceae Rhizob ium Rhizob ium leguminosarum bv. t rifo lii WSM1325 Med ie 2012 Cellulo se Pred icted Pro teobacteria Alphap ro teobacteriaRhizob iales Rhizob iaceae Rhizob ium Rhizob ium leguminosarum bv. t rifo lii WSM2304 Med ie 2012 Cellulo se Pred icted Pro teobacteria Alphap ro teobacteriaRhizob iales Rhizob iaceae Rhizob ium Rhizob ium leguminosarum bv. viciae 3841 Med ie 2012 Cellulo se Pred icted Pro teobacteria Alphap ro teobacteriaRhizob iales Rhizob iaceae Rhizob ium Rhizob ium sp . NGR234 Med ie 2012 Cellulo se Pred icted Pro teobacteria Alphap ro teobacteriaRhizob iales Rhizob iaceae Sino rhizob ium Sino rhizob ium med icae WSM419 S o urc e S ub s t ra t e A c t iv it y P hy lum C las s Ord e r F amily Ge nus F ull N ameMedie 2012 Cellulo se Pred icted Pro teobacteria Alphap ro teobacteriaRhodobacterales Hyphomonadaceae Hirschia Hirschia balt ica ATCC 49814 Med ie 2012 Cellulo se Pred icted Pro teobacteria Alphap ro teobacteriaRhodosp irillales Rhodosp irillaceae Azosp irillum Azosp irillum sp . B510 Med ie 2012 Cellulo se Pred icted Pro teobacteria Alphap ro teobacteriaSphingomonadales Sphingomonadaceae Sphingob ium Sphingob ium japonicum UT26S UT26S (= NBRC 101211) Med ie 2012 Cellulo se Pred icted Pro teobacteria Betap ro teobacteriaBurkho lderiales Burkho lderiaceae Burkho lderia Burkho lderia amb ifaria MC40-6 Med ie 2012 Cellulo se Pred icted Pro teobacteria Betap ro teobacteriaBurkho lderiales Burkho lderiaceae Burkho lderia Burkho lderia amb ifaria AMMD Med ie 2012 Cellulo se Pred icted Pro teobacteria Betap ro teobacteriaBurkho lderiales Burkho lderiaceae Burkho lderia Burkho lderia cenocepacia HI2424 Med ie 2012 Cellulo se Pred icted Pro teobacteria Betap ro teobacteriaBurkho lderiales Burkho lderiaceae Burkho lderia Burkho lderia cenocepacia J2315 Med ie 2012 Cellulo se Pred icted Pro teobacteria Betap ro teobacteriaBurkho lderiales Burkho lderiaceae Burkho lderia Burkho lderia cenocepacia AU 1054 Med ie 2012 Cellulo se Pred icted Pro teobacteria Betap ro teobacteriaBurkho lderiales Burkho lderiaceae Burkho lderia Burkho lderia g lad io li BSR3 Med ie 2012 Cellulo se Pred icted Pro teobacteria Betap ro teobacteriaBurkho lderiales Burkho lderiaceae Burkho lderia Burkho lderia g lumae BGR1 Med ie 2012 Cellulo se Pred icted Pro teobacteria Betap ro teobacteriaBurkho lderiales Burkho lderiaceae Burkho lderia Burkho lderia mult ivo rans ATCC 17616 Med ie 2012 Cellulo se Pred icted Pro teobacteria Betap ro teobacteriaBurkho lderiales Burkho lderiaceae Burkho lderia Burkho lderia phymatum STM815 Med ie 2012 Cellulo se Pred icted Pro teobacteria Betap ro teobacteriaBurkho lderiales Burkho lderiaceae Burkho lderia Burkho lderia sp . CCGE1002 Med ie 2012 Cellulo se Pred icted Pro teobacteria Betap ro teobacteriaBurkho lderiales Burkho lderiaceae Rals tonia Rals tonia so lanacearum CFBP2957 Med ie 2012 Cellulo se Pred icted Pro teobacteria Betap ro teobacteriaBurkho lderiales Burkho lderiaceae Rals tonia Rals tonia so lanacearum GMI1000 Med ie 2012 Cellulo se Pred icted Pro teobacteria Betap ro teobacteriaBurkho lderiales Burkho lderiaceae Rals tonia Rals tonia so lanacearum IPO1609 Med ie 2012 Cellulo se Pred icted Pro teobacteria Betap ro teobacteriaBurkho lderiales Burkho lderiaceae Rals tonia Rals tonia so lanacearum PSI07 Med ie 2012 Cellulo se Pred icted Pro teobacteria Betap ro teobacteriaBurkho lderiales Burkho lderiaceae Rals tonia Rals tonia so lanacearum MolK2 Med ie 2012 Cellulo se Pred icted Pro teobacteria Betap ro teobacteriaBurkho lderiales Burkho lderiaceae Rals tonia Rals tonia so lanacearum CMR15 Med ie 2012 Cellulo se Pred icted Pro teobacteria Betap ro teobacteriaBurkho lderiales Comamonadaceae Acidovo rax Acidovo rax avenae subsp . cit rulli AAC00-1 Med ie 2012 Cellulo se Pred icted Pro teobacteria Betap ro teobacteriaBurkho lderiales Comamonadaceae Ramlibacter Ramlibacter tataouinens is TTB310 Med ie 2012 Cellulo se Pred icted Pro teobacteria Deltap ro teobacteriaMyxococcales Cys tobacteraceae Stigmatella Stigmatella aurantiaca DW4/3 -1 Med ie 2012 Cellulo se Pred icted Pro teobacteria Deltap ro teobacteriaMyxococcales Myxococcaceae Myxococcus Myxococcus xanthus DK 1622 Med ie 2012 Cellulo se Pred icted Pro teobacteria Deltap ro teobacteriaMyxococcales Po lyang iaceae Sorang ium Sorang ium cellulo sum 'So ce 56 ' Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaAeromonadales Aeromonadaceae Aeromonas Aeromonas salmonicida subsp . salmonicida A449 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaAlteromonadales Co lwelliaceae Co lwellia Co lwellia p sychrerythraea 34HMed ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaAlteromonadales Pseudoalteromonadaceae Pseudoalteromonas Pseudoalteromonas at lant ica T6c Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaAlteromonadales Shewanellaceae Shewanella Shewanella vio lacea DSS12 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaCellvib rionales Cellvib rionaceae Cellvib rio Cellvib rio japonicus Ueda107 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaCellvib rionales Cellvib rionaceae Saccharophagus Saccharophagus deg radans 2 -40 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaCellvib rionales Cellvib rionaceae Tered inibacter Tered inibacter turnerae T7901 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Citrobacter Citrobacter rodentium ICC168 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Cronobacter Cronobacter turicens is Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Dickeya Dickeya dadantii 3937 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Dickeya Dickeya dadantii Ech586 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Dickeya Dickeya dadantii Ech703 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Dickeya Dickeya zeae Ech1591 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Enterobacter Enterobacter cloacae subsp . cloacae ATCC 13047 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Enterobacter Enterobacter cloacae NCTC 9394 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Enterobacter Enterobacter sakazakii ATCC BAA-894 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Enterobacter Enterobacter sp . 638 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Erwinia Erwinia amylovo ra ATCC 49946 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Erwinia Erwinia amylovo ra CFBP1430 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Erwinia Erwinia amylovo ra IL-5 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Erwinia Erwinia pyrifo liae DSM 12163 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Erwinia Erwinia pyrifo liae Ep1/96 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Erwinia Erwinia sp . Ejp617 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Erwinia Erwinia tasmaniens is Et1/99 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Klebs iella Klebs iella pneumoniae NTUH-K2044 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Klebs iella Klebs iella pneumoniae 342 S o urc e S ub s t ra t e A c t iv it y P hy lum C las s Ord e r F amily Ge nus F ull N ameMedie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Klebs iella Klebs iella pneumoniae subsp . pneumoniae MGH 78578 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Klebs iella Klebs iella variico la At-22 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Pantoea Pantoea ananatis AJ13355 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Pantoea Pantoea ananatis LMG 20103 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Pantoea Pantoea sp . At-9b Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Pantoea Pantoea vagans C9-1 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Pectobacterium Pectobacterium atro sep ticum SCRI1043 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Pectobacterium Pectobacterium caro tovo rum subsp . caro tovo rum PC1 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Pectobacterium Pectobacterium wasab iae WPP163 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Rahnella Rahnella sp . Y9602 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Yers inia Yers inia enteroco lit ica subsp . enteroco lit ica 8081 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Yers inia Yers inia enteroco lit ica subsp . palearct ica 105.5R(r) Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Yers inia Yers inia enteroco lit ica subsp . palearct ica Y11 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Yers inia Yers inia pes t is Antiqua Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Yers inia Yers inia pes t is b iovar Med ie 2012valis s tr. Harb in 35 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Yers inia Yers inia pes t is D106004 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Yers inia Yers inia pes t is D182038 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Yers inia Yers inia pes t is KIM Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Yers inia Yers inia pes t is Nepal516 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Yers inia Yers inia pes t is b iovar Micro tus s tr. 91001 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Yers inia Yers inia pes t is Pes to ides F Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Yers inia Yers inia pes t is Z176003 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Yers inia Yers inia p seudo tuberculo s is IP 31758 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Yers inia Yers inia p seudo tuberculo s is IP 32953 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Yers inia Yers inia p seudo tuberculo s is PB1/+ Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Yers inia Yers inia p seudo tuberculo s is YPIII Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaL g ionellales Leg ionellaceae Leg ionella Leg ionella longbeachae NSW150 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaOceanosp irillales Hahellaceae Hahella Hahella chejuens is KCTC 2396 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaPseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas fluo rescens SBW25 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaPseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas putida BIRD-1 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaPseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas putida F1 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaPseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas syringae pv. phaseo lico la 1448A Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaPseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas syringae pv. tomato s tr. DC3000 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaPseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas syringae pv. syringae B728a Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaVib rionales Vib rionaceae Pho tobacterium Pho tobacterium p ro fundum SS9 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaVib rionales Vib rionaceae Vib rio Vib rio furniss ii NCTC 11218 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaXanthomonadales Xanthomonadaceae Pseudoxanthomonas Pseudoxanthomonas suwonens is 11-1 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaXanthomonadales Xanthomonadaceae Xanthomonas Xanthomonas alb ilineans Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaXanthomonadales Xanthomonadaceae Xanthomonas Xanthomonas axonopod is pv. cit ri s t r. 306 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaXanthomonadales Xanthomonadaceae Xanthomonas Xanthomonas campes tris pv. Campes tris B100Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaXanthomonadales Xanthomonadaceae Xanthomonas Xanthomonas campes tris pv. campes tris s tr. 8004 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaXanthomonadales Xanthomonadaceae Xanthomonas Xanthomonas campes tris pv. campes tris s tr. ATCC 33913 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaXanthomonadales Xanthomonadaceae Xanthomonas Xanthomonas campes tris pv. ves icato ria s tr. 85-10 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaXanthomonadales Xanthomonadaceae Xanthomonas Xanthomonas o ryzae pv. o ryzae MAFF 311018 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaXanthomonadales Xanthomonadaceae Xanthomonas Xanthomonas o ryzae pv. o ryzae KACC10331 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaXanthomonadales Xanthomonadaceae Xanthomonas Xanthomonas o ryzae pv. o ryzae PXO99A Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaXanthomonadales Xanthomonadaceae Xylella Xylella fas t id io sa M23 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaXanthomonadales Xanthomonadaceae Xylella Xylella fas t id io sa Temecula1 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaXanthomonadales Xanthomonadaceae Xylella Xylella fas t id io sa M12 Med ie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaXanthomonadales Xanthomonadaceae Xylella Xylella fas t id io sa subsp . fas t id io sa GB514 S o urc e S ub s t ra t e A c t iv it y P hy lum C las s Ord e r F amily Ge nus F ull N ameMedie 2012 Cellulo se Pred icted Pro teobacteria Gammapro teobacteriaXanthomonadales Xanthomonadaceae Xylella Xylella fas t id io sa 9a5c Med ie 2012 Cellulo se Pred icted Sp irochaetes Sp irochaetia Sp irochaetales Sp irochaetaceae Sp irochaeta Sp irochaeta thermophila DSM 6192 Med ie 2012 Cellulo se Pred icted Sp irochaetes Sp irochaetia Sp irochaetales Sp irochaetaceae Treponema Treponema succinifaciens DSM 2489 Med ie 2012 Cellulo se Pred icted Thermo togae Thermo togae Thermo togales Thermo togaceae Thermo toga Thermo toga let t ingae TMO Med ie 2012 Cellulo se Pred icted Thermo togae Thermo togae Thermo togales Thermo togaceae Thermo toga Thermo toga marit ima MSB8 Med ie 2012 Cellulo se Pred icted Thermo togae Thermo togae Thermo togales Thermo togaceae Thermo toga Thermo toga naphthophila RKU-10 Med ie 2012 Cellulo se Pred icted Thermo togae Thermo togae Thermo togales Thermo togaceae Thermo toga Thermo toga neapo litana DSM 4359 Med ie 2012 Cellulo se Pred icted Thermo togae Thermo togae Thermo togales Thermo togaceae Thermo toga Thermo toga petrophila RKU-1 Med ie 2012 Cellulo se Pred icted Thermo togae Thermo togae Thermo togales Thermo togaceae Thermo toga Thermo toga sp . RQ2 Med ie 2012 Cellulo se Pred icted Verrucomicrob ia Op itutae Op itutales Op itutaceae Op itutus Op itutus terrae PB90-1 Med ie 2012 Cellulo se Pred icted Verrucomicrob ia Op itutae Puniceicoccales Puniceicoccaceae Coraliomargarita Coraliomargarita akajimens is DSM 45221 Koeck 2014 Crys talline Validated Actinobacteria Actinobacteria Acido thermales Acido thermaceae Acido thermus Acido thermus cellulo lyt icusKoeck 2014 Crys talline Validated Actinobacteria Actinobacteria Micrococcales Cellulomonadaceae Cellulomonas Cellulomonas b iazo teaKoeck 2014 Crys talline Validated Actinobacteria Actinobacteria Micrococcales Cellulomonadaceae Cellulomonas Cellulomonas cellaseaKoeck 2014 Crys talline Validated Actinobacteria Actinobacteria Micrococcales Cellulomonadaceae Cellulomonas Cellulomonas fimiKoeck 2014 Crys talline Validated Actinobacteria Actinobacteria Micrococcales Cellulomonadaceae Cellulomonas Cellulomonas flavigenaKoeck 2014 Crys talline Validated Actinobacteria Actinobacteria Micrococcales Cellulomonadaceae Cellulomonas Cellulomonas gelidaKoeck 2014 Crys talline Validated Actinobacteria Actinobacteria Micrococcales Cellulomonadaceae Cellulomonas Cellulomonas iranens isKoeck 2014 Crys talline Validated Actinobacteria Actinobacteria Micrococcales Cellulomonadaceae Cellulomonas Cellulomonas pers icaKoeck 2014 Crys talline Validated Actinobacteria Actinobacteria Micrococcales Cellulomonadaceae Cellulomonas Cellulomonas terraeKoeck 2014 Crys talline Validated Actinobacteria Actinobacteria Micrococcales Cellulomonadaceae Cellulomonas Cellulomonas udaKoeck 2014 Crys talline Validated Actinobacteria Actinobacteria Micrococcales Microbacteriaceae Curtobacterium Curtobacterium flaccumfaciensKoeck 2014 Crys talline Validated Actinobacteria Actinobacteria Micrococcales Promicromonospo raceae Cellulo s imicrob ium Cellulo s imicrob ium cellulansKoeck 2014 Crys talline Validated Actinobacteria Actinobacteria Micrococcales Promicromonospo raceae Cellulo s imicrob ium Cellulo s imicrob ium cellulansKoeck 2014 Crys talline Validated Actinobacteria Actinobacteria Micrococcales Promicromonospo raceae Xylanimonas Xylanimonas cellulo s ilyt icaKoeck 2014 Crys talline Validated Actinobacteria Actinobacteria Micromonospo rales Micromonospo raceae Micromonospo ra Micromonospo ra aurantiacaKoeck 2014 Crys talline Validated Actinobacteria Actinobacteria Micromonospo rales Micromonospo raceae Micromonospo ra Micromonospo ra chalceaKoeck 2014 Crys talline Validated Actinobacteria Actinobacteria Micromonospo rales Micromonospo raceae Micromonospo ra Micromonospo ra melanospo raKoeck 2014 Crys talline Validated Actinobacteria Actinobacteria Micromonospo rales Micromonospo raceae Micromonospo ra Micromonospo ra p rop ioniciKoeck 2014 Crys talline Validated Actinobacteria Actinobacteria Micromonospo rales Micromonospo raceae Micromonospo ra Micromonospo ra ruminantiumKoeck 2014 Crys talline Validated Actinobacteria Actinobacteria None None Thermob ispo ra Thermob ispo ra b ispo raKoeck 2014 Crys talline Validated Actinobacteria Actinobacteria Pseudonocard iales Pseudonocard iaceae Actinosynnema Actinosynnema mirumKoeck 2014 Crys talline Validated Actinobacteria Actinobacteria Strep tomycetales Strep tomycetaceae Strep tomyces Strep tomyces albog riseo lusKoeck 2014 Crys talline Validated Actinobacteria Actinobacteria Strep tomycetales Strep tomycetaceae Strep tomyces Strep tomyces aureo faciensKoeck 2014 Crys talline Validated Actinobacteria Actinobacteria Strep tomycetales Strep tomycetaceae Strep tomyces Strep tomyces cellulo lyt icusKoeck 2014 Crys talline Validated Actinobacteria Actinobacteria Strep tomycetales Strep tomycetaceae Strep tomyces Strep tomyces flavog riseusKoeck 2014 Crys talline Validated Actinobacteria Actinobacteria Strep tomycetales Strep tomycetaceae Strep tomyces Strep tomyces lividansKoeck 2014 Crys talline Validated Actinobacteria Actinobacteria Strep tomycetales Strep tomycetaceae Strep tomyces Strep tomyces nitro spo reusKoeck 2014 Crys talline Validated Actinobacteria Actinobacteria Strep tomycetales Strep tomycetaceae Strep tomyces Strep tomyces o livochromogenesKoeck 2014 Crys talline Validated Actinobacteria Actinobacteria Strep tomycetales Strep tomycetaceae Strep tomyces Strep tomyces ret iculiKoeck 2014 Crys talline Validated Actinobacteria Actinobacteria Strep tomycetales Strep tomycetaceae Strep tomyces Strep tomyces rocheiKoeck 2014 Crys talline Validated Actinobacteria Actinobacteria Strep tomycetales Strep tomycetaceae Strep tomyces Strep tomyces thermovulgarisKoeck 2014 Crys talline Validated Actinobacteria Actinobacteria Strep tomycetales Strep tomycetaceae Strep tomyces Strep tomyces viridospo rusKoeck 2014 Crys talline Validated Actinobacteria Actinobacteria Strep to spo rang iales Nocard iopsaceae Thermob ifida Thermob ifida albaKoeck 2014 Crys talline Validated Actinobacteria Actinobacteria Strep to spo rang iales Nocard iopsaceae Thermob ifida Thermob ifida cellulo lyt icaKoeck 2014 Crys talline Validated Actinobacteria Actinobacteria Strep to spo rang iales Nocard iopsaceae Thermob ifida Thermob ifida fuscaKoeck 2014 Crys talline Validated Actinobacteria Actinobacteria Strep to spo rang iales Strep to spo rang iaceae Strep to spo rang ium Strep to spo rang ium sub roseumKoeck 2014 Crys talline Validated Actinobacteria Actinobacteria Strep to spo rang iales Thermomonospo raceae Thermomonospo ra Thermomonospo ra curvataKoeck 2014 Crys talline Validated Bactero idetes Bactero idetes incertae sed is Rhodo thermaceae Rhodo thermus Rhodo thermus marinusKoeck 2014 Crys talline Validated Bactero idetes Bactero id ia Bactero idales Bactero idaceae Bactero ides Bactero ides cellulo s ilyt icus S o urc e S ub s t ra t e A c t iv it y P hy lum C las s Ord e r F amily Ge nus F ull N ameKoeck 2014 Crys talline Validated Bactero idetes Bactero id ia Bactero idales Bactero idaceae Bactero ides Bactero ides sp . P-1Koeck 2014 Crys talline Validated Bactero idetes Cytophag ia Cytophagales Cytophagaceae Cytophaga Cytophaga aurantiacaKoeck 2014 Crys talline Validated Bactero idetes Cytophag ia Cytophagales Cytophagaceae Cytophaga Cytophaga halo flavaKoeck 2014 Crys talline Validated Bactero idetes Cytophag ia Cytophagales Cytophagaceae Cytophaga Cytophaga hutchinsoniiKoeck 2014 Crys talline Validated Bactero idetes Cytophag ia Cytophagales Cytophagaceae Cytophaga Cytophaga krzemieniewskaKoeck 2014 Crys talline Validated Bactero idetes Cytophag ia Cytophagales Cytophagaceae Cytophaga Cytophaga ro seaKoeck 2014 Crys talline Validated Bactero idetes Cytophag ia Cytophagales Cytophagaceae Sporocytophaga Sporocytophaga myxococco idesKoeck 2014 Crys talline Validated Bactero idetes Flavobacteriia Flavobacteriales Flavobacteriaceae Flavobacterium Flavobacterium johnsoniaeKoeck 2014 Crys talline Validated Fib robacteres Fib robacteria Fib robacterales Fib robacteraceae Fib robacter Fib robacter succinogenesKoeck 2014 Crys talline Validated Firmicutes Bacilli Bacillales Alicyclobacillaceae Cald ibacillus Cald ibacillus cellulovo ransKoeck 2014 Crys talline Validated Firmicutes Bacilli Bacillales Bacillaceae Bacillus Bacillus circulansKoeck 2014 Crys talline Validated Firmicutes Bacilli Bacillales Bacillaceae Bacillus Bacillus pumilisKoeck 2014 Crys talline Validated Firmicutes Bacilli Bacillales Thermoactinomycetaceae Thermoactinomyces Thermoactinomyces sp . YXKoeck 2014 Crys talline Validated Firmicutes Clos trid ia Clos trid iales Clos trid iaceae Clos trid ium Clos trid ium cellulo fermentansKoeck 2014 Crys talline Validated Firmicutes Clos trid ia Clos trid iales Clos trid iaceae Clos trid ium Clos trid ium cellulovo ransKoeck 2014 Crys talline Validated Firmicutes Clos trid ia Clos trid iales Clos trid iaceae Clos trid ium Clos trid ium chartatab idumKoeck 2014 Crys talline Validated Firmicutes Clos trid ia Clos trid iales Clos trid iaceae Clos trid ium Clos trid ium long ispo rumKoeck 2014 Crys talline Validated Firmicutes Clos trid ia Clos trid iales Clos trid iaceae Clos trid ium Clos trid ium sp . C7Koeck 2014 Crys talline Validated Firmicutes Clos trid ia Clos trid iales Clos trid iaceae Clos trid ium Clos trid ium thermopapyro lyt icumKoeck 2014 Crys talline Validated Firmicutes Clos trid ia Clos trid iales Clos trid iaceae Lachnoclo s trid ium Lachnoclo s trid ium phyto fermentansKoeck 2014 Crys talline Validated Firmicutes Clos trid ia Clos trid iales Clos trid iaceae Ruminiclo s trid ium Ruminiclo s trid ium alkalicellulo s iKoeck 2014 Crys talline Validated Firmicutes Clos trid ia Clos trid iales Clos trid iaceae Ruminiclo s trid ium Ruminiclo s trid ium cellulo lyt icumKoeck 2014 Crys talline Validated Firmicutes Clos trid ia Clos trid iales Clos trid iaceae Ruminiclo s trid ium Ruminiclo s trid ium cellulo s iKoeck 2014 Crys talline Validated Firmicutes Clos trid ia Clos trid iales Clos trid iaceae Ruminiclo s trid ium Ruminiclo s trid ium clariflavumKoeck 2014 Crys talline Validated Firmicutes Clos trid ia Clos trid iales Clos trid iaceae Ruminiclo s trid ium Ruminiclo s trid ium jo suiKoeck 2014 Crys talline Validated Firmicutes Clos trid ia Clos trid iales Clos trid iaceae Ruminiclo s trid ium Ruminiclo s trid ium papyroso lvensKoeck 2014 Crys talline Validated Firmicutes Clos trid ia Clos trid iales Clos trid iaceae Ruminiclo s trid ium Ruminiclo s trid ium s terco rariumKoeck 2014 Crys talline Validated Firmicutes Clos trid ia Clos trid iales Clos trid iaceae Ruminiclo s trid ium Ruminiclo s trid ium s traminiso lvensKoeck 2014 Crys talline Validated Firmicutes Clos trid ia Clos trid iales Clos trid iaceae Ruminiclo s trid ium Ruminiclo s trid ium termit id isKoeck 2014 Crys talline Validated Firmicutes Clos trid ia Clos trid iales Clos trid iaceae Ruminiclo s trid ium Ruminiclo s trid ium thermocellumKoeck 2014 Crys talline Validated Firmicutes Clos trid ia Clos trid iales Eubacteriaceae Eubacterium Eubacterium cellulo so lvensKoeck 2014 Crys talline Validated Firmicutes Clos trid ia Clos trid iales Lachnosp iraceae Butyrivib rio Butyrivib rio fib riso lvensKoeck 2014 Crys talline Validated Firmicutes Clos trid ia Clos trid iales Lachnosp iraceae Cellulo s ilyt icum Cellulo s ilyt icum lentocellumKoeck 2014 Crys talline Validated Firmicutes Clos trid ia Clos trid iales Lachnosp iraceae Cellulo s ilyt icum Cellulo s ilyt icum ruminico laKoeck 2014 Crys talline Validated Firmicutes Clos trid ia Clos trid iales Lachnosp iraceae Lachnoclo s trid ium Lachnoclo s trid ium celerecrescensKoeck 2014 Crys talline Validated Firmicutes Clos trid ia Clos trid iales Lachnosp iraceae Lachnoclo s trid ium Lachnoclo s trid ium herb ivo ransKoeck 2014 Crys talline Validated Firmicutes Clos trid ia Clos trid iales Lachnosp iraceae Lachnoclo s trid ium Lachnoclo s trid ium populet iKoeck 2014 Crys talline Validated Firmicutes Clos trid ia Clos trid iales None Thermoanaerobacter Thermoanaerobacter cellulo lyt icusKoeck 2014 Crys talline Validated Firmicutes Clos trid ia Clos trid iales Ruminococcaceae Acetivib rio Acetivib rio cellulo lyt icusKoeck 2014 Crys talline Validated Firmicutes Clos trid ia Clos trid iales Ruminococcaceae Acetivib rio Acetivib rio cellulo so lvensKoeck 2014 Crys talline Validated Firmicutes Clos trid ia Clos trid iales Ruminococcaceae Pseudobactero ides Pseudobactero ides cellulo so lvensKoeck 2014 Crys talline Validated Firmicutes Clos trid ia Clos trid iales Ruminococcaceae Ruminiclo s trid ium Ruminiclo s trid ium ald richiiKoeck 2014 Crys talline Validated Firmicutes Clos trid ia Clos trid iales Ruminococcaceae Ruminiclo s trid ium Ruminiclo s trid ium caenico laKoeck 2014 Crys talline Validated Firmicutes Clos trid ia Clos trid iales Ruminococcaceae Ruminiclo s trid ium Ruminiclo s trid ium cellob ioparumKoeck 2014 Crys talline Validated Firmicutes Clos trid ia Clos trid iales Ruminococcaceae Ruminiclo s trid ium Ruminiclo s trid ium hungateiKoeck 2014 Crys talline Validated Firmicutes Clos trid ia Clos trid iales Ruminococcaceae Ruminiclo s trid ium Ruminiclo s trid ium sufflavumKoeck 2014 Crys talline Validated Firmicutes Clos trid ia Clos trid iales Ruminococcaceae Ruminococcus Ruminococcus albusKoeck 2014 Crys talline Validated Firmicutes Clos trid ia Clos trid iales Ruminococcaceae Ruminococcus Ruminococcus flavefaciensKoeck 2014 Crys talline Validated Firmicutes Clos trid ia Halanaerob iales Halanaerob iaceae Halocella Halocella cellulo s ilyt icaKoeck 2014 Crys talline Validated Firmicutes Clos trid ia Thermoanaerobacteralesincertae sed is Cald icellulo s irup to r Cald icellulo s irup to r bescii S o urc e S ub s t ra t e A c t iv it y P hy lum C las s Ord e r F amily Ge nus F ull N ameKoeck 2014 Crys talline Validated Firmicutes Clos trid ia Thermoanaerobacteralesincertae sed is Cald icellulo s irup to r Cald icellulo s irup to r hyd ro thermalisKoeck 2014 Crys talline Validated Firmicutes Clos trid ia Thermoanaerobacteralesincertae sed is Cald icellulo s irup to r Cald icellulo s irup to r kris t janssoniiKoeck 2014 Crys talline Validated Firmicutes Clos trid ia Thermoanaerobacteralesincertae sed is Cald icellulo s irup to r Cald icellulo s irup to r krono tskyens isKoeck 2014 Crys talline Validated Firmicutes Clos trid ia Thermoanaerobacteralesincertae sed is Cald icellulo s irup to r Cald icellulo s irup to r lactoacet icusKoeck 2014 Crys talline Validated Firmicutes Clos trid ia Thermoanaerobacteralesincertae sed is Cald icellulo s irup to r Cald icellulo s irup to r obs id ians isKoeck 2014 Crys talline Validated Firmicutes Clos trid ia Thermoanaerobacteralesincertae sed is Cald icellulo s irup to r Cald icellulo s irup to r saccharo lyt icusKoeck 2014 Crys talline Validated Firmicutes Clos trid ia ThermoanaerobacteralesThermoanaerobacteraceae Thermoanaerobacter Thermoanaerobacter thermocopriaeKoeck 2014 Crys talline Validated Pro teobacteria Betap ro teobacteriaBurkho lderiales Alcaligenaceae Achromobacter Achromobacter p iechaud iiKoeck 2014 Crys talline Validated Pro teobacteria Deltap ro teobacteriaMyxococcales None Myxobacter Myxobacter sp . AL-1Koeck 2014 Crys talline Validated Pro teobacteria Gammapro teobacteriaCellvib rionales Cellvib rionaceae Cellulomonas Cellulomonas g ilvusKoeck 2014 Crys talline Validated Pro teobacteria Gammapro teobacteriaCellvib rionales Cellvib rionaceae Cellvib rio Cellvib rio japonicusKoeck 2014 Crys talline Validated Pro teobacteria Gammapro teobacteriaCellvib rionales Cellvib rionaceae Cellvib rio Cellvib rio mixtusKoeck 2014 Crys talline Validated Pro teobacteria Gammapro teobacteriaCellvib rionales Cellvib rionaceae Cellvib rio Cellvib rio vulgarisKoeck 2014 Crys talline Validated Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Dickeya Dickeya dadantiiKoeck 2014 Crys talline Validated Pro teobacteria Gammapro teobacteriaXanthomonadales Xanthomonadaceae Rudaea Rudaea cellulo s ilyt icaKoeck 2014 Crys talline Validated Pro teobacteria Gammapro teobacteriaXanthomonadales Xanthomonadaceae Xanthomonas Xanthomonas sp .Koeck 2014 Crys talline Validated Thermo togae Thermo togae Thermo togales Fervidobacteriaceae Fervidobacterium Fervidobacterium is land icumKoeck 2014 Crys talline Validated Thermo togae Thermo togae Thermo togales Thermo togaceae Thermo toga Thermo toga marit imaKoeck 2014 Crys talline Validated Thermo togae Thermo togae Thermo togales Thermo togaceae Thermo toga Thermo toga neapo litanaVicuna 1988 Lignin Validated Actinobacteria Actinobacteria Corynebacteriales Corynebacteriaceae Corynebacterium Corynebacterium sp .Zimmermann 1990Lignin Validated Actinobacteria Actinobacteria Corynebacteriales Corynebacteriaceae Corynebacterium Corynebacterium sp .Woo 2014 Lignin Validated Actinobacteria Actinobacteria Corynebacteriales Gordoniaceae Gordonia Gordonia sp .Tian 2014 Lignin Validated Actinobacteria Actinobacteria Corynebacteriales Nocard iaceae Nocard ia Nocard ia sp . DSM 1069Tian 2014 Lignin Validated Actinobacteria Actinobacteria Corynebacteriales Nocard iaceae Rhodococcus Rhodococcus jo s t ii RHA1Bugg 2011 Lignin Validated Actinobacteria Actinobacteria Micrococcales Micrococcaceae Arthrobacter Arthrobacter g lob ifo rmisTian 2014 Lignin Validated Actinobacteria Actinobacteria Micrococcales Micrococcaceae Micrococcus Micrococcus luteusTaylo r 2012 Lignin Validated Actinobacteria Actinobacteria Micrococcales Micrococcaceae Micrococcus Micrococcus luteus E1.1Taylo r 2012 Lignin Validated Actinobacteria Actinobacteria Micrococcales Micrococcaceae Micrococcus Micrococcus luteus B5.3Zimmermann 1990Lignin Validated Actinobacteria Actinobacteria Prop ionibacteriales Nocard io idaceae Arthrobacter Arthrobacter s imp lexTian 2014 Lignin Validated Actinobacteria Actinobacteria Pseudonocard iales Pseudonocard iaceae Amyco latops is Amyco latops is sp . 75iv2Tian 2014 Lignin Validated Actinobacteria Actinobacteria Pseudonocard iales Pseudonocard iaceae Nocard ia Nocard ia auto trophicaTian 2014 Lignin Validated Actinobacteria Actinobacteria Strep tomycetales Strep tomycetaceae Strep tomyces Strep tomyces viridospo rus T7ATian 2014 Lignin Validated Actinobacteria Actinobacteria Strep tomycetales Strep tomycetaceae Strep tomyces Strep tomyces flavovirensTian 2014 Lignin Validated Actinobacteria Actinobacteria Strep tomycetales Strep tomycetaceae Strep tomyces Strep tomyces bad ius ATCC 39117Tian 2014 Lignin Validated Actinobacteria Actinobacteria Strep tomycetales Strep tomycetaceae Strep tomyces Strep tomyces p sammoticusZimmermann 1990Lignin Validated Actinobacteria Actinobacteria Strep tomycetales Strep tomycetaceae Strep tomyces Strep tomyces rimosusBugg 2011 Lignin Validated Actinobacteria Actinobacteria Strep tomycetales Strep tomycetaceae Strep tomyces Strep tomyces coelico lo rZimmermann 1990Lignin Validated Actinobacteria Actinobacteria Strep to spo rang iales Strep to spo rang iaceae Thermomonospo ra Thermomonospo ra mesophilaZimmermann 1990Lignin Validated Actinobacteria Actinobacteria Strep to spo rang iales Thermomonospo raceae Actinomadura Actinomadura sp .Zimmermann 1990Lignin Validated Bactero idetes Flavobacteriia Flavobacteriales Flavobacteriaceae Flavobacterium Flavobacterium sp .Tian 2014 Lignin Validated Bactero idetes Sphingobacteriia Sphingobacteriales Sphingobacteriaceae Sphingobacterium Sphingobacterium sp . CKTN2Goran 2015 Lignin Validated Bactero idetes Sphingobacteriia Sphingobacteriales Sphingobacteriaceae Sphingobacterium Sphingobacterium sp . T2Duan 2014 Lignin Validated Bactero idetes Sphingobacteriia Sphingobacteriales Sphingobacteriaceae Sphingobacterium Sphingobacterium sp . HY-HTian 2014 Lignin Validated Firmicutes Bacilli Bacillales Bacillaceae Bacillus Bacillus megateriumTian 2014 Lignin Validated Firmicutes Bacilli Bacillales Bacillaceae Bacillus Bacillus pumilusTian 2014 Lignin Validated Firmicutes Bacilli Bacillales Bacillaceae Bacillus Bacillus atrophaeusTian 2014 Lignin Validated Firmicutes Bacilli Bacillales Bacillaceae Bacillus Bacillus lichenifo rmisBugg 2011 Lignin Validated Firmicutes Bacilli Bacillales Paenibacillaceae Aneurinibacillus Aneurinibacillus aneurinilyt icusTian 2014 Lignin Validated Firmicutes Bacilli Bacillales Paenibacillaceae Paenibacillus Paenibacillus sp . ITRC-S6Tian 2014 Lignin Validated Firmicutes Bacilli Bacillales Paenibacillaceae Paenibacillus Paenibacillus sp . CBMAI 868 S o urc e S ub s t ra t e A c t iv it y P hy lum C las s Ord e r F amily Ge nus F ull N ameZimmermann 1990Lignin Validated Pro teobacteria Alphap ro teobacteriaRhizob iales Beijerinckiaceae Beijerinckia Beijerinckia sp .Taylo r 2012 Lignin Validated Pro teobacteria Alphap ro teobacteriaRhizob iales Brucellaceae Ochrobactrum Ochrobactrum pseudogrignonense A4 .3Taylo r 2012 Lignin Validated Pro teobacteria Alphap ro teobacteriaRhizob iales Brucellaceae Ochrobactrum Ochrobactrum rhizosphaerae C4 .1Si 2015 Lignin Validated Pro teobacteria Alphap ro teobacteriaRhizob iales Rhizob iaceae Agrobacterium Agrobacterium sp . S5-1Gonzalez 1997Lignin Validated Pro teobacteria Alphap ro teobacteriaRhodobacterales Rhodobacteraceae Sag it tula Sag it tula s tellata E-37Zimmermann 1990Lignin Validated Pro teobacteria Alphap ro teobacteriaSphingomonadales Sphingomonadaceae Pseudomonas Pseudomonas paucimob ilisTian 2014 Lignin Validated Pro teobacteria Alphap ro teobacteriaSphingomonadales Sphingomonadaceae Sphingomonas Sphingomonas paucimob ilis SYK-6Zimmermann 1990Lignin Validated Pro teobacteria Betap ro teobacteriaBurkho lderiales Alcaligenaceae Achromobacter Achromobacter sp .Woo 2014 Lignin Validated Pro teobacteria Betap ro teobacteriaBurkho lderiales Burkho lderiaceae Burkho lderia Burkho lderia sp . LIG30Tian 2014 Lignin Validated Pro teobacteria Betap ro teobacteriaBurkho lderiales Burkho lderiaceae Pandoraea Pandoraea sp . B-6Zimmermann 1990Lignin Validated Pro teobacteria Betap ro teobacteriaBurkho lderiales Burkho lderiaceae Pseudomonas Pseudomonas cepaciaZimmermann 1990Lignin Validated Pro teobacteria Betap ro teobacteriaBurkho lderiales Burkho lderiaceae Pseudomonas Pseudomonas mult ivo ransChen 2012 Lignin Validated Pro teobacteria Betap ro teobacteriaBurkho lderiales Comamonadaceae Comamonas Comamonas sp . B-9Zimmermann 1990Lignin Validated Pro teobacteria Betap ro teobacteriaBurkho lderiales Comamonadaceae Pseudomonas Pseudomonas acidovo ransWoo 2014 Lignin Validated Pro teobacteria Betap ro teobacteriaNeisseriales Chromobacteriaceae Aquitalea Aquitalea sp .Tian 2014 Lignin Validated Pro teobacteria Gammapro teobacteriaAeromonadales Aeromonadaceae Aeromonas Aeromonas sp .Tian 2014 Lignin Validated Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Citrobacter Citrobacter freund ii IITRL1Harazono 2003Lignin Validated Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Citrobacter Citrobacter sp . VA53Tian 2014 Lignin Validated Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Citrobacter Citrobacter sp . IITRSU7Tian 2014 Lignin Validated Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Enterobacter Enterobacter aerogenesTian 2014 Lignin Validated Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Enterobacter Enterobacter ligno lyt icus SCF1Tian 2014 Lignin Validated Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Enterobacter Enterobacter so liTian 2014 Lignin Validated Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Enterobacter Enterobacter cloacae KBH3Zimmermann 1990Lignin Validated Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Erwinia Erwinia sp .Zimmermann 1990Lignin Validated Pro teobacteria Gammapro teobacteriaPseudomonadales Moraxellaceae Acinetobacter Acinetobacter sp .Zimmermann 1990Lignin Validated Pro teobacteria Gammapro teobacteriaPseudomonadales Moraxellaceae Pseudomonas Pseudomonas cruciviaeTian 2014 Lignin Validated Pro teobacteria Gammapro teobacteriaPseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas putida mt-2Tian 2014 Lignin Validated Pro teobacteria Gammapro teobacteriaPseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas putida GB-1Zimmermann 1990Lignin Validated Pro teobacteria Gammapro teobacteriaPseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas ovalisZimmermann 1990Lignin Validated Pro teobacteria Gammapro teobacteriaPseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas p seudoalcaligenesKern 1987 Lignin Validated Pro teobacteria Gammapro teobacteriaXanthomonadales Xanthomonadaceae Xanthomonas Xanthomonas sp .Tambo li 2011 Pheno ls Validated Bactero idetes Sphingobacteriia Sphingobacteriales Sphingobacteriaceae Sphingobacterium Sphingobacterium sp . ATMTian 2014 Pheno ls Validated Pro teobacteria Alphap ro teobacteriaRhizob iales Brucellaceae Brucella Brucella sp . GXY-1Tian 2014 Pheno ls Validated Pro teobacteria Alphap ro teobacteriaSphingomonadales Sphingomonadaceae Sphingob ium Sphingob ium chlo ropheno licumTian 2014 Pheno ls Validated Pro teobacteria Gammapro teobacteriaEnterobacteriales Enterobacteriaceae Enterobacter Enterobacter cloacae DG-6Tian 2014 Pheno ls Validated Pro teobacteria Gammapro teobacteriaPseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas sp . SUK1JGI Cellulo se Validated Bas id iomyco ta Agaricomycetes Agaricales Cort inariaceae Gymnop ilus Gymnop ilus chrysopellus PR-1187JGI Cellulo se Validated Bas id iomyco ta Agaricomycetes Agaricales Fis tulinaceae Fis tulina Fis tulina hepaticaJGI Cellulo se Validated Bas id iomyco ta Agaricomycetes Agaricales Schizophyllaceae Schizophyllum Schizophyllum commune H4-8JGI Cellulo se Validated Bas id iomyco ta Agaricomycetes Agaricales Schizophyllaceae Schizophyllum Schizophyllum commune Loenen DJGI Cellulo se Validated Bas id iomyco ta Agaricomycetes Agaricales Schizophyllaceae Schizophyllum Schizophyllum commune Tattone DJGI Cellulo se Validated Bas id iomyco ta Agaricomycetes Bo letales Coniopho raceae Coniopho ra Coniopho ra puteanaJGI Cellulo se Validated Bas id iomyco ta Agaricomycetes Bo letales Paxillaceae Hydnomerulius Hydnomerulius p inas triJGI Cellulo se Validated Bas id iomyco ta Agaricomycetes Bo letales Serpulaceae Serpula Serpula lacrymans S7.3JGI Cellulo se Validated Bas id iomyco ta Agaricomycetes Bo letales Serpulaceae Serpula Serpula lacrymans S7.9JGI Cellulo se Validated Bas id iomyco ta Agaricomycetes Bo letales Serpulaceae Serpula Serpula lacrymans var shas tens is SHA21-2JGI Cellulo se Validated Bas id iomyco ta Agaricomycetes Cort iciales Cort iciaceae Schizopo ra Schizopo ra paradoxa KUC8140JGI Cellulo se Validated Bas id iomyco ta Agaricomycetes Geas trales Sphaerobo laceae Sphaerobo lus Sphaerobo lus s tellatusJGI Cellulo se Validated Bas id iomyco ta Agaricomycetes Gloeophyllales Gloeophyllaceae Gloeophyllum Gloeophyllum trabeumJGI Cellulo se Validated Bas id iomyco ta Agaricomycetes Gloeophyllales Gloeophyllaceae Neo lentinus Neo lentinus lep ideus S o urc e S ub s t ra t e A c t iv it y P hy lum C las s Ord e r F amily Ge nus F ull N ameJGI Cellulo se Validated Bas id iomyco ta Agaricomycetes Gomphales Gomphaceae Ramaria Ramaria rubella (R. acris ) UT-36052-TJGI Cellulo se Validated Bas id iomyco ta Agaricomycetes Jaap iales Jaap iaceae Jaap ia Jaap ia arg illaceaJGI Cellulo se Validated Bas id iomyco ta Agaricomycetes Po lypo rales Corio laceae Daedalea Daedalea quercinaJGI Cellulo se Validated Bas id iomyco ta Agaricomycetes Po lypo rales Corio laceae Laetipo rus Laetipo rus sulphureus var. sulphureusJGI Cellulo se Validated Bas id iomyco ta Agaricomycetes Po lypo rales Corio laceae Pos t ia Pos t ia p lacenta MAD 698-RJGI Cellulo se Validated Bas id iomyco ta Agaricomycetes Po lypo rales Corio laceae Pos t ia Pos t ia p lacenta MAD-698-R-SB12JGI Cellulo se Validated Bas id iomyco ta Agaricomycetes Po lypo rales Corio laceae Wolfipo ria Wolfipo ria cocos MD-104 SS10JGI Cellulo se Validated Bas id iomyco ta Agaricomycetes Po lypo rales Fomitops idaceae Antrod ia Antrod ia s inuosaJGI Cellulo se Validated Bas id iomyco ta Agaricomycetes Po lypo rales Fomitops idaceae Fomitops is Fomitops is p inico la FP-58527 SS1JGI Cellulo se Validated Bas id iomyco ta Agaricomycetes Po lypo rales Po lypo raceae Fib ropo ria Fib ropo ria rad iculo sa JGI Cellulo se Validated Bas id iomyco ta Agaricomycetes Po lypo rales Po lypo raceae Po lypo rus Po lypo rus arculariusJGI Cellulo se Validated Bas id iomyco ta Agaricomycetes Trechispo rales Hydnodontaceae Sis to tremas trum Sis to tremas trum niveocremeum HHB9708 ss -1 1.0JGI Cellulo se Validated Bas id iomyco ta Agaricomycetes Trechispo rales Hydnodontaceae Sis to tremas trum Sis to tremas trum suecicumJGI Cellulo se Validated Bas id iomyco ta Dacrymycetes NA Dacrymycetaceae Calocera Calocera co rneaBucher 2004 Lignin Validated Ascomyco ta Do thideomycetes Pleospo rales Aig ialaceae Ascocratera Ascocratera mang lico laBucher 2004 Lignin Validated Ascomyco ta Do thideomycetes Pleospo rales Pleospo rales incertae sed is Astro sphaeriella Astro sphaeriella s triat ispo raBucher 2004 Lignin Validated Ascomyco ta So rdariomycetes Xylariales Diatrypaceae Cryp tovalsa Cryp tovalsa halo sarceico laBucher 2004 Lignin Validated Ascomyco ta So rdariomycetes Xylariales Xylariales incertae sed is Linocarpon Linocarpon b ipo larisJGI Lignin Validated Bas id iomyco ta Agaricomycetes Agaricales Agaricales incertae sed is Plicaturops is Plicaturops is crispaJGI Lignin Validated Bas id iomyco ta Agaricomycetes Agaricales Omphalo taceae Gymnopus Gymnopus and rosaceus JB14JGI Lignin Validated Bas id iomyco ta Agaricomycetes Agaricales Pleuro taceae Pleuro tus Pleuro tus o s treatus PC15JGI Lignin Validated Bas id iomyco ta Agaricomycetes Agaricales Pleuro taceae Pleuro tus Pleuro tus o s treatus PC9JGI Lignin Validated Bas id iomyco ta Agaricomycetes Agaricales Strophariaceae Galerina Galerina marg inataJGI Lignin Validated Bas id iomyco ta Agaricomycetes Agaricales Tricho lomataceae Panellus Panellus s t ip t icus KUC8834JGI Lignin Validated Bas id iomyco ta Agaricomycetes Auriculariales Auriculariaceae Auricularia Auricularia subg lab raJGI Lignin Validated Bas id iomyco ta Agaricomycetes Auriculariales Exid iaceae Exid ia Exid ia g landulosaJGI Lignin Validated Bas id iomyco ta Agaricomycetes Cort iciales Cort iciaceae Phleb ia Phleb ia b revispo ra HHB-7030 SS6JGI Lignin Validated Bas id iomyco ta Agaricomycetes Hymenochaetales Hymenochaetaceae Fomitipo ria Fomitipo ria med iterraneaJGI Lignin Validated Bas id iomyco ta Agaricomycetes Po lypo rales Corio laceae Trametes Trametes ljubarskyi CIRM1659JGI Lignin Validated Bas id iomyco ta Agaricomycetes Po lypo rales Corio laceae Trametes Trametes vers ico lo rJGI Lignin Validated Bas id iomyco ta Agaricomycetes Po lypo rales Ganodermataceae Ganoderma Ganoderma sp . 10597 SS1JGI Lignin Validated Bas id iomyco ta Agaricomycetes Po lypo rales Lentinaceae Lentinus Lentinus t ig rinus ALCF2SS1-6JGI Lignin Validated Bas id iomyco ta Agaricomycetes Po lypo rales Lentinaceae Lentinus Lentinus t ig rinus ALCF2SS1-7JGI Lignin Validated Bas id iomyco ta Agaricomycetes Po lypo rales Lentinaceae Lentinus Lentinus t ig rinusJGI Lignin Validated Bas id iomyco ta Agaricomycetes Po lypo rales Meruliaceae Bjerkandera Bjerkandera adus taJGI Lignin Validated Bas id iomyco ta Agaricomycetes Po lypo rales Meruliaceae Ceripo riops is Ceripo riops is (Gelatopo ria) subvermispo ra BJGI Lignin Validated Bas id iomyco ta Agaricomycetes Po lypo rales Meruliaceae Obba Obba rivulo sa 3A-2JGI Lignin Validated Bas id iomyco ta Agaricomycetes Po lypo rales Phanerochaetaceae Phanerochaete Phanerochaete carnosa HHB-10118-SpJGI Lignin Validated Bas id iomyco ta Agaricomycetes Po lypo rales Phanerochaetaceae Phanerochaete Phanerochaete chrysospo rium RP-78 v2 .2JGI Lignin Validated Bas id iomyco ta Agaricomycetes Po lypo rales Phanerochaetaceae Phleb iops is Phleb iops is g iganteaJGI Lignin Validated Bas id iomyco ta Agaricomycetes Po lypo rales Po lypo raceae Arto lenzites Arto lenzites elegans CIRM1663JGI Lignin Validated Bas id iomyco ta Agaricomycetes Po lypo rales Po lypo raceae Cerrena Cerrena unico lo rJGI Lignin Validated Bas id iomyco ta Agaricomycetes Po lypo rales Po lypo raceae Dichomitus Dichomitus squalensJGI Lignin Validated Bas id iomyco ta Agaricomycetes Po lypo rales Po lypo raceae Pycnoporus Pycnoporus cinnabarinus BRFM 137JGI Lignin Validated Bas id iomyco ta Agaricomycetes Po lypo rales Po lypo raceae Pycnoporus Pycnoporus coccineus BRFM 310JGI Lignin Validated Bas id iomyco ta Agaricomycetes Po lypo rales Po lypo raceae Pycnoporus Pycnoporus coccineus CIRM1662 JGI Lignin Validated Bas id iomyco ta Agaricomycetes Po lypo rales Po lypo raceae Pycnoporus Pycnoporus sanguineus BRFM 1264JGI Lignin Validated Bas id iomyco ta Agaricomycetes Po lypo rales Po lypo raceae Trichap tum Trichap tum ab iet inumJGI Lignin Validated Bas id iomyco ta Agaricomycetes Russulales Stereaceae Stereum Stereum hirsutum FP-91666 SS1JGI Lignin Validated Bas id iomyco ta Dacrymycetes NA Dacrymycetaceae Calocera Calocera viscosaJGI Lignin Validated Bas id iomyco ta Tremellomycetes Tremellales Tremellaceae Tremella Tremella mesentericaBucher 2004 Lignin Validated NA NA NA NA NA Rhizophila marina Name SiteSample CollectionLat. Long.Elevation (m)Soil Classification Tree Cover Climatic ZoneAnnual Temp (°C)Precipitation (mm)Year Est. CountryFensom A7 7/3/2011 49.07 -89.41 445Orthic Dystric BrunisolBlack SpruceDfb, Humid Continental w arm summer 2.4 266 1995 CANADAFensom A8 7/4/2011 49.08 -89.38 450Orthic Dystric BrunisolBlack SpruceDfb, Humid Continental w arm summer 1.8 266 1995 CANADAFensom A9 7/5/2011 49.07 -89.39 442Gleyed Dystric BrunisolBlack SpruceDfb, Humid Continental w arm summer 1.5 266 1995 CANADABrandy City BR 6/22/2011 39.55 -121.04 1135Mesic Ultic HaploxeralfsPonderosa pine, sugar pine, w hite f ir, giant sequoiaCsa, Mediterranean hot summer 11.2 55 1995 USABlodgett BL 9/16/2011 38.88 -120.64 1350Mesic Ultic HaploxeralfsPonderosa pine, sugar pine, w hite f ir, giant sequoiaCsa, Mediterranean hot summer 11.2 55 1994 USALow ell Hill LH 9/16/2011 39.26 -120.78 1268Mesic Ultic HaploxeralfsPonderosa pine, sugar pine, w hite f ir, giant sequoiaCsa, Mediterranean hot summer 11.2 55 1995 USAWells JW 7/7/2011 46.42 -83.37 228Orthic Humo-Ferric PodzolJack Pine, Black Spruce, Red PineDfb, Humid Continental cool summer 4.4 248 1993-1994 CANADASuperior JS 8/4/2011 47.57 -82.85 426Orthic Dystric BrunisolJack Pine, Black SpruceDfb, Humid Continental cool summer 1.7 250 1993-1994 CANADAEddy JE 8/3/2011 46.75 -82.25 490 NAJack Pine, Balsam fir, White birchDfb, Humid Continental cool summer 2.8 242 1993-1994 CANADAKurth TXA 3/12/2012 31.11 -95.15 88 Aquic GlossudalfsLoblolly Pine, Beautyberry, Yaupon, Sw eetgum, OaksCfa, Humid subtropical19.0 253 1997 USAKurth TXB 3/12/2012 31.11 -95.15 88 Aquic GlossudalfsLoblolly Pine, Beautyberry, Yaupon, Sw eetgum, OaksCfa, Humid subtropical19.0 253 1997 USAKurth TXC 3/12/2012 31.11 -95.15 88 Aquic GlossudalfsLoblolly Pine, Beautyberry, Yaupon, Sw eetgum, OaksCfa, Humid subtropical19.0 253 1997 USAO'Connor Lake OC 6/26/2010 50.88 -120.35 1075Brunisolic Gray LuvisolDouglas f irDfb, Humid Continental w arm summer 2.5 300 1999 CANADABlack Pines BP 6/22/2010 50.93 -120.28 1180Brunisolic Gray LuvisolDouglas f ir, Lodgepole pineDfb, Humid Continental w arm summer 2.5 300 1999 CANADADairy Creek DC 6/25/2010 50.85 -120.42 1150Brunisolic Gray LuvisolDouglas f ir, Subalpine f ir, Lodgepole pineDfb, Humid Continental w arm summer 2.5 300 1999 CANADALog Lake LL 7/9/2008 54.35 -122.61 780Orthic Humo-Ferric PodzolSubalpine f ir, Douglas f ir, Interior SpruceDfc, Boreal cool summer 2.2 415 1994 CANADATopley TO 7/11/2008 52.32 -126.31 1100Orthic Gray Luvisol, Gleyed Gray LuvisolLodgepole pine, Subalpine f ir, Interior spruceDfc, Boreal cool summer 2.2 415 1994 CANADASkulow Lake SL 8/14/2009 52.32 -121.92 1050 Orthic Gray LuvisolLodgepole pine, Interior spruceDfc, Boreal cool summer 2.2 415 1994 CANADATable E.3. Overview of all sampling sites within the ecozones utilized in this study, including sampling information, climatic information and the date harvesting took place. Data was sourced from collaborators (Dr. Matt Busse, Dr. Andy Scott, Dr. Paul Hazlett and Dr. David Morris) and Ponder et al. 2012 and Hartmann et al. 2012 Table E.4. Overview of all PLFA, pyrotag and metagenomic libraries collected from ecozones, substrates and soil layers. Experiment Ecozone Horizon Treatment16S rRNA LibrariesITS LibrariesREF 9 9OM1 27 27OM2 27 27OM3 0 0REF 9 9OM1 27 27OM2 27 27OM3 27 27REF 12 12OM1 30 30OM2 30 30OM3 0 0REF 12 12OM1 30 30OM2 31 33OM3 32 33REF 9 7OM1 8 8OM2 9 9OM3 9 9REF 9 9OM1 9 9OM2 9 9OM3 9 9REF 7 9OM1 18 17OM2 16 17OM3 1 1REF 9 9OM1 18 18OM2 17 15OM3 18 18REF 9 9OM1 9 9OM2 9 9OM3 9 8REF 9 9OM1 9 9OM2 9 9OM3 9 9REF 8 7OM1 18 19OM2 15 20OM3 12 15REF 8 7OM1 15 21OM2 19 17OM3 13 12CaliforniaOrgMin'in situ' Harvesting Effects (Chapter 3)British Columbia (IDF)OrgMinBritish Columbia (SBS)OrgMinOntario (BS)OrgMinTexasOrgMinOntario (JP)OrgMin Table E.4... continued Experiment Library Horizon Treatment PLFA16S rRNA LibrariesITS LibrariesREF 9 3 3OM1 9 3 2OM2 9 3 3OM3 9 3 3REF 9 3 3OM1 9 3 3OM2 9 3 3OM3 9 3 3REF 1 3 3OM1 - 3 2OM2 - 3 2OM3 - 3 2REF 1 3 3OM1 - 3 3OM2 - 3 3OM3 - 3 3SIP-Cellulose Harvesting Effects (Chapter 3)13C-LibraryOrgMin12C-LibraryOrgMin Table E.4... continued Ecozone Horizon Substrate PLFA13C-Pyro12C-Pyro 13C-Meta13C-Anti 12C-Meta'in situ ' - - 12 - - -Hemicellulose - 3 4 - - -Cellulose 3 6 3 3 - 1Lignin - - - - - -'in situ' - - 12 - - -Hemicellulose - 6 4 - - -Cellulose 3 3 3 3 - 1Lignin - - - - - -'in situ' - - 9 - - -Hemicellulose - - - - - -Cellulose 3 3 3 3 - 1Lignin 10 4 8 4 - 3'in situ' - - 9 - - -Hemicellulose - - - - - -Cellulose 0 2 3 3 - 1Lignin 10 8 7 8 4 4'in situ' - - 7 - - -Hemicellulose - - - - - -Cellulose 1 3 3 3 - 1Lignin 0 - - - - -'in situ' - - 9 - - -Hemicellulose - - - - - -Cellulose 2 3 3 3 - 1Lignin 0 - - - - -'in situ' - - 9 - - -Hemicellulose - 8 4 - - -Cellulose 9 3 3 3 - 1Lignin 10 6 9 5 - 3'in situ' - - 9 - - -Hemicellulose - 15 3 - - -Cellulose 9 3 3 3 - 1Lignin 10 9 6 9 2 4'in situ' - - 9 - - -Hemicellulose - - - - - -Cellulose 3 3 3 3 - 1Lignin 3 2 - 1 - 0'in situ' - - 9 - - -Hemicellulose - - - - - -Cellulose 0 3 3 1 - 1Lignin 5 3 2 3 2 2SIP-Biodiversity (Chapter 4)British Columbia (IDF)OrgMinOntario (BS)OrgMinOntario (JP)OrgMinCaliforniaOrgMinTexasOrgMin Table E.5. Overview of soil properties among ecozones, soil layers and harvesting treatments. Within groups of treatments, significantly different values (p < 0.05) have been denoted by lettering based on Tukey’s Honest Significant Difference. mean std. error n sig mean std. error n sig mean std. error n sig mean std. error n sigSBS 63.81 13.91 12 a 57.21 8.11 30 b 56.84 9.63 30 b - - - -IDF 68.13 11.08 9 ns 67.12 12.64 27 ns 68.13 13.30 27 ns - - - -BS 65.28 8.01 9 a 52.50 11.12 9 b 51.36 12.10 9 b 50.24 12.43 9 bJP 48.08 14.74 9 a 37.47 8.11 18 b 40.75 11.62 16 ab - - - -CALIFORNIA 33.17 18.20 9 ns 29.73 19.61 9 ns 29.28 16.81 9 ns 27.96 15.07 9 nsTEXAS 29.71 7.44 9 b 28.16 5.37 25 b 19.36 9.15 21 a 26.25 6.97 17 bSBS 4.72 0.49 9 ns 4.93 0.26 27 ns 4.89 0.33 27 ns - - - -IDF 5.25 0.19 9 b 5.48 0.23 27 a 5.56 0.25 27 a - - - -BS 4.45 0.29 9 b 4.87 0.33 9 ab 4.84 0.41 9 ab 5.16 0.39 9 aJP 3.83 0.23 9 ns 3.97 0.23 18 ns 3.92 0.23 16 ns - - - -CALIFORNIA 5.30 0.55 9 ab 4.40 0.61 9 b 5.11 0.60 9 ab 5.28 0.37 9 aTEXAS 4.46 0.27 9 b 4.83 0.37 24 a 4.69 0.47 21 ab 4.45 0.19 15 bSBS - - - - 1.58 0.14 27 ns 1.63 0.10 27 ns - - - -IDF - - - - 1.29 0.15 27 a 1.37 0.13 27 b - - - -BS 0.13 0.02 9 b 0.19 0.03 9 a 0.22 0.03 9 a 0.19 0.03 9 aJP 7.43 1.47 9 ns 6.77 0.98 18 ns 7.48 1.64 16 ns - - - -CALIFORNIA - - - - - - - - - - - - - - - -TEXAS - - - - - - - - - - - - - - - -SBS 33.83 11.64 9 a 27.78 6.32 27 b 26.07 6.28 27 b - - - -IDF 44.29 0.09 9 a 36.18 2.32 27 b 31.22 11.03 27 c - - - -BS 44.42 1.54 9 a 38.72 4.81 9 a 42.00 4.23 9 a 31.53 8.22 9 bJP 40.53 4.06 9 ns 40.18 4.31 18 ns 39.48 2.75 16 ns - - - -CALIFORNIA 38.23 4.87 6 a 41.28 2.43 6 a 29.66 3.89 6 b 27.72 10.20 5 bTEXAS 17.98 4.81 9 a 11.32 1.77 9 b 10.97 5.44 8 b 12.21 2.40 8 bSBS 0.89 0.25 9 ns 0.78 0.18 27 ns 0.77 0.21 27 ns - - - -IDF 1.24 0.14 9 ns 1.13 0.18 27 ns 1.03 0.36 27 ns - - - -BS 1.08 0.08 9 a 1.00 0.16 9 ab 1.13 0.12 9 a 0.84 0.27 9 bJP 1.24 0.10 9 ns 1.16 0.08 18 ns 1.17 0.13 16 ns - - - -CALIFORNIA 1.26 0.19 6 a 1.24 0.26 6 ab 1.02 0.19 6 ab 0.88 0.21 5 bTEXAS 0.63 0.16 9 a 0.44 0.08 9 b 0.43 0.19 8 b 0.43 0.06 8 bSBS 37.44 3.82 9 a 35.72 3.86 27 ab 34.13 2.78 27 b - - - -IDF 36.23 4.20 9 a 32.81 6.01 27 ab 30.45 8.38 27 b - - - -BS 41.44 2.72 9 a 39.29 5.93 9 ab 37.24 2.94 9 b 38.43 3.50 9 abJP 32.89 2.97 9 ns 35.33 3.69 18 ns 34.59 4.55 16 ns - - - -CALIFORNIA 30.67 3.78 6 ns 34.84 8.87 6 ns 29.73 5.20 6 ns 31.05 7.10 5 nsTEXAS 28.60 1.95 9 a 25.69 1.90 9 b 25.42 1.95 8 b 28.02 2.14 8 aC:N RatioMoisture Content (w /w )pHBulk Density (g/cm3)Total Carbon (%)Total Nitrogen (%)Organic LayerEcozoneREF OM1 OM2 OM3 mean std. error n sig mean std. error n sig mean std. error n sig mean std. error n sigSBS 21.73 7.50 11 ns 23.86 5.87 31 ns 24.11 6.02 29 ns 23.30 6.20 30 nsIDF 31.63 10.81 9 ns 33.66 10.17 27 ns 31.91 10.37 27 ns 30.02 12.91 27 nsBS 25.96 4.12 9 a 22.79 3.17 9 a 21.61 5.28 9 ab 17.98 2.95 9 bJP 15.42 3.09 9 a 9.97 4.51 18 b 12.89 3.40 17 ab 11.73 4.07 18 bCALIFORNIA 22.49 7.07 9 ns 26.54 6.99 9 ns 24.99 8.43 9 ns 24.19 7.60 9 nsTEXAS 14.70 3.19 9 ns 14.60 5.14 24 ns 17.16 6.87 21 ns 15.87 5.19 16 nsSBS 5.15 0.41 8 ns 5.18 0.38 28 ns 5.15 0.28 26 ns 5.31 0.33 27 nsIDF 5.48 0.23 9 b 5.59 0.26 27 b 5.60 0.13 27 b 5.75 0.12 27 aBS 5.33 0.27 9 b 5.39 0.30 9 b 5.48 0.24 9 ab 5.74 0.28 9 aJP 4.97 0.41 9 b 5.18 0.14 18 ab 5.20 0.14 17 ab 5.27 0.16 18 aCALIFORNIA 6.11 0.44 9 a 5.54 0.31 9 b 5.86 0.28 9 ab 5.62 0.39 9 bTEXAS - - - - 4.94 0.25 24 a 4.97 0.43 21 a 4.60 0.27 16 bSBS - - - - 1.57 0.14 28 ns 1.64 0.10 26 ns 1.60 0.14 27 nsIDF - - - - 1.29 0.15 27 b 1.37 0.13 27 b 1.50 0.14 27 aBS 1.08 0.25 9 b 1.16 0.20 9 ab 1.27 0.20 9 ab 1.32 0.26 9 aJP 7.43 1.47 9 ns 6.77 0.98 18 ns 7.51 1.59 17 ns 7.30 1.31 18 nsCALIFORNIA - - - - - - - - - - - - - - - -TEXAS - - - - 1.30 0.02 24 a 1.27 0.05 21 b 1.32 0.01 16 aSBS 1.22 0.30 8 b 1.50 0.55 28 b 1.76 0.84 26 a 1.44 0.42 27 bIDF 2.19 0.29 9 ns 2.42 0.59 27 ns 6.69 12.66 27 ns 1.99 0.32 27 nsBS 2.00 0.68 9 ab 2.42 1.02 9 a 1.47 0.74 9 b 1.39 0.54 9 bJP 1.92 0.82 9 ns 2.13 0.95 18 ns 2.14 0.87 17 ns 2.80 3.68 18 nsCALIFORNIA 6.12 1.20 9 a 6.11 1.30 9 a 4.90 0.96 9 b 5.14 1.05 9 abTEXAS - - - - 0.92 0.11 24 a 0.95 0.20 21 ab 0.80 0.11 16 bSBS 0.06 0.01 8 a 0.07 0.02 28 ab 0.09 0.04 26 b 0.07 0.02 27 abIDF 0.10 0.00 9 ns 0.12 0.02 27 ns 0.27 0.45 27 ns 0.10 0.01 27 nsBS 0.09 0.02 9 ns 0.10 0.04 9 ns 0.07 0.03 9 ns 0.07 0.03 9 nsJP 0.13 0.06 9 ns 0.14 0.09 18 ns 0.19 0.15 17 ns 0.17 0.16 18 nsCALIFORNIA 0.29 0.06 9 ns 0.25 0.06 9 ns 0.23 0.06 9 ns 0.26 0.06 9 nsTEXAS - - - - 0.05 0.00 24 a 0.05 0.00 21 a 0.04 0.00 16 bSBS 21.03 2.24 8 ns 20.16 2.20 28 ns 19.77 1.22 26 ns 20.53 2.15 27 nsIDF 21.90 2.87 9 ns 20.82 3.35 27 ns 21.28 4.10 27 ns 20.42 2.55 27 nsBS 21.77 2.82 9 ns 23.65 2.73 9 ns 20.76 2.59 9 ns 20.60 1.76 9 nsJP 17.84 3.29 9 ns 18.19 4.94 18 ns 17.86 5.65 17 ns 18.79 6.82 18 nsCALIFORNIA 21.10 1.42 9 b 24.69 4.50 9 a 21.28 0.77 9 b 19.62 0.99 9 bTEXAS - - - - 16.90 1.17 24 b 18.95 3.20 21 a 17.83 1.48 16 abC:N RatioMoisture Content (w /w )pHBulk Density (g/cm3)Total Carbon (%)Total Nitrogen (%)Mineral LayerEcozoneREF OM1 OM2 OM3Table E.5... continued Table E.6 Full list of bacterial and fungal taxa showing clear expansion or decline in response to harvesting. Phylum Order Family Taxa EcozonesSoil Layer ResponseMean AbundanceMax. AbundanceResponse ratioAcidobacteria Acidobacteriales Acidobacteriaceae Edaphobacter BC, JP, CA, TX Org Variable 0.58 13.22 0.7Acidobacteria Acidobacteriales Acidobacteriaceae Acidopila ON, BC, CA - Expanded 0.26 1.49 10.1Acidobacteria Acidobacteriales Acidobacteriaceae Granulicella BC, ON Org Variable 0.82 40.33 0.6Acidobacteria Acidobacteriales Acidobacteriaceae Telmatobacter TX Org Expanded 0.20 1.27 15.7Acidobacteria Acidobacteriales Koribacteraceae Candidatus Koribacter ON, BC, TX - Variable 0.52 18.02 1.5Acidobacteria Holophagales Holophagaceae Geothrix All Org Expanded 0.35 2.25 14.2Actinobacteria Actinomycetales Geodermatophilaceae Blastococcus BC, CA - Expanded 0.28 10.62 31.8Actinobacteria Actinomycetales Geodermatophilaceae Modestobacter BC, CA Org Expanded 0.69 23.06 25.3Actinobacteria Actinomycetales Geodermatophilaceae Geodermatophilus SBS, CA , TX Org Expanded 0.24 1.37 3.0Actinobacteria Actinomycetales Kineosporiaceae Kineosporia BC, CA Org Declined 0.28 4.27 0.7Actinobacteria Actinomycetales Microbacteriaceae Subtercola CA Org Expanded 0.33 1.15 11.7Actinobacteria Actinomycetales Micrococcaceae Arthrobacter ON, BC, CA - Expanded 0.35 11.12 1.7Actinobacteria Actinomycetales Micromonosporaceae Dactylosporangium BC, CA, TX Org Declined 0.25 2.14 0.7Actinobacteria Actinomycetales Mycobacteriaceae Mycobacterium BC, BS, CA, TX Org Variable 1.03 92.86 0.8Actinobacteria Actinomycetales Nocardiaceae Rhodococcus BC, ON, TX - Expanded 0.34 3.03 3.7Actinobacteria Actinomycetales Nocardioidaceae Kribbella BC, TX - Variable 0.29 6.42 0.6Actinobacteria Actinomycetales Pseudonocardiaceae Amycolatopsis BC, CA, TX Min Expanded 0.56 13.31 0.7Actinobacteria Actinomycetales Pseudonocardiaceae Actinomycetospora CA, TX Org Expanded 0.46 17.85 3.2Actinobacteria Actinomycetales Streptomycetaceae Streptacidiphilus BC, CA, TX - Declined 0.49 18.48 0.3Actinobacteria Actinomycetales Streptomycetaceae Streptomyces BC, CA, TX Org Declined 0.31 13.90 0.8Actinobacteria Rubrobacterales Rubrobacteraceae Rubrobacter CA Min Expanded 0.16 0.33 7.3Actinobacteria Gaiellales Gaiellaceae Gaiellaceae All Min Expanded 0.39 20.48 2.0Actinobacteria Solirubrobacterales unclassif ied Solirubrobacter BC, JP, CA, TX Org Declined 0.25 5.97 0.3AD3 NA NA ABS-6 All Min Expanded 0.86 26.41 1.6Armatimonadetes NA NA 0319-6E2 ON, BC, CA Min Expanded 0.20 1.76 2.2Bacteroidetes Cytophagales Cytophagaceae Spirosoma CA Org Expanded 0.16 0.90 4.1Bacteroidetes Saprospirales Chitinophagaceae Flavisolibacter IDF, ON, CA, TX - Expanded 0.25 1.69 2.4Bacteroidetes Saprospirales Chitinophagaceae Segetibacter ON, CA Min Expanded 0.23 0.90 2.4Chloroflexi H39 NA H39 ON, BC, CA Min Expanded 0.24 8.84 2.4Chloroflexi SBR1031 oc28 oc28 ON, BC, TX - Expanded 0.21 1.86 2.6Chloroflexi AKIW781 NA AKIW781 BC, CA Org Expanded 0.21 1.38 6.8Chloroflexi NA NA Gitt-GS-136 BC, BS, CA Min Expanded 0.46 7.70 2.6 Table E.6... continued Phylum Order Family Taxa EcozonesSoil Layer ResponseMean AbundanceMax. AbundanceResponse ratioChloroflexi B12-WMSP1 NA B12-WMSP1 SBS, ON, CA Min Expanded 0.20 1.87 6.1Chloroflexi Thermogemmatisporales Thermogemmatisporaceae Thermogemmatisporaceae SBS, JP, CA, TX Min Expanded 0.32 7.88 1.7Chloroflexi NA NA P2-11E All Min Expanded 0.77 22.54 2.5Chloroflexi Ellin6537 NA Ellin6537 All - Expanded 0.17 0.85 4.5Cyanobacteria Nostocales Nostocaceae Nostoc BC Org Expanded 0.33 5.22 7.6Firmicutes Bacillales Alicyclobacillaceae Alicyclobacillus BC, CA, TX Min Expanded 0.59 9.84 2.0Firmicutes Bacillales Bacillaceae Bacillus BC, TX Min Expanded 0.28 5.83 1.4Firmicutes Bacillales Bacillaceae Geobacillus BC Min Expanded 0.37 3.86 3.9Firmicutes Bacillales Thermoactinomycetaceae Thermoactinomycetaceae BC Min Expanded 0.33 3.61 5.3Firmicutes Clostridiales Clostridiaceae Clostridium BC, JP, CA, TX Min Expanded 0.25 3.52 2.8GAL15 NA NA GAL15 ON, TX Min Expanded 0.20 2.50 4.5Proteobacteria Xanthomonadales Rhodanobacteraceae Luteibacter BC, ON, TX Org Declined 0.62 18.97 0.5Proteobacteria Caulobacterales Caulobacteraceae Caulobacter BC, ON Org Declined 0.44 5.38 0.4Proteobacteria Rhizobiales Beijerinckiaceae Methylocella All Org Declined 0.25 4.08 0.7Proteobacteria Rhizobiales Hyphomicrobiaceae Rhodomicrobium IDF, JP, CA, TX Min Declined 0.97 9.23 0.8Proteobacteria Rhizobiales Hyphomicrobiaceae Rhodoplanes JP, CA, TX Min Variable 1.01 86.45 1.0Proteobacteria Rhizobiales Methylobacteriaceae Methylobacterium ON, CA, TX Org Expanded 0.38 10.75 6.2Proteobacteria Rhizobiales Rhizobiaceae Ensifer IDF, CA, TX - Expanded 0.14 0.22 Harv.OnlyProteobacteria Rhizobiales Xanthobacteraceae Ancylobacter BC, CA, TX Org Declined 0.24 1.71 0.2Proteobacteria Rhizobiales Xanthobacteraceae Labrys BC, CA, TX Org Declined 0.34 5.59 0.7Proteobacteria Rhodospirillales Acetobacteraceae Acidocella BC, JP, CA, TX Org Variable 0.78 31.58 0.6Proteobacteria Rhodospirillales Acetobacteraceae Acidiphilium BC, JP, TX Org Variable 0.48 10.42 0.9Proteobacteria Rhodospirillales Rhodospirillaceae Skermanella IDF Org Expanded 0.51 1.39 Harv.OnlyProteobacteria Sphingomonadales Sphingomonadaceae Sphingobium BC, CA, TX Org Declined 0.23 6.41 0.2Proteobacteria Burkholderiales Comamonadaceae Ramlibacter BC, BS, CA, TX Min Expanded 0.48 8.26 2.7Proteobacteria Burkholderiales Comamonadaceae Limnohabitans BC, CA Org Declined 0.25 0.90 0.0Proteobacteria Burkholderiales Comamonadaceae Pelomonas CA, TX Org Declined 0.30 3.59 0.4Proteobacteria Burkholderiales Oxalobacteraceae Massilia BC, BS, CA - Expanded 0.34 4.00 5.6Proteobacteria Burkholderiales Oxalobacteraceae Janthinobacterium BC, CA, TX - Expanded 1.07 34.07 2.3Proteobacteria Burkholderiales Oxalobacteraceae Cupriavidus JP, TX Min Expanded 0.28 4.27 2.5Proteobacteria Ellin6067 NA Ellin6067 ON, BC, TX Min Expanded 0.51 13.28 1.7Proteobacteria Desulfuromonadales Geobacteraceae Geobacter IDF, BS, CA, TX Min Expanded 0.34 15.16 2.1 Phylum Order Family Taxa EcozonesSoil Layer ResponseMean AbundanceMax. AbundanceResponse ratioProteobacteria Myxococcales Cystobacteraceae Cystobacter JP, CA, TX - Expanded 0.24 1.92 2.5Proteobacteria Nevskiales Sinobacteraceae Sinobacteraceae All - Declined 1.16 66.63 0.7Proteobacteria Alteromonadales Alteromonadaceae Cellvibrio TX Min Expanded 0.30 1.82 8.8Proteobacteria Xanthomonadales Rhodanobacteraceae Rhodanobacter BC, BS, CA, TX Org Declined 0.29 3.27 0.2Proteobacteria Xanthomonadales Xanthomonadaceae Lysobacter IDF Min Expanded 0.47 0.82 Harv.OnlyVerrucomicrobia Opitutales Opitutaceae Opitutus ON, BC, CA Org Declined 0.23 11.56 0.5Chloroplast Trebouxiophyceae Coccomyxa Coccomyxa SBS, ON, CA, TX Org Expanded 0.24 1.25 7.9Chloroplast NA NA Chloroplast All - Expanded 0.55 49.81 3.4Chloroplast NA NA Stramenopiles BC Org Expanded 0.23 1.27 11.2Proteobacteria Rickettsiales mitochondria mitochondria All - Expanded 0.36 15.83 7.9Ascomycota Capnodiales Incertae sedis Phaeotheca fissurella BC, CA Org Expansion 0.29 1.71 8.8Ascomycota Dothideales Dothioraceae Hormonema CA Org Expansion 0.60 52.23 10.5Ascomycota Microthyriales Microthyriaceae Tothia BC, CA Org Decline 0.91 16.25 0.0Ascomycota Pleosporales NA Pleosporales sp 2 MU 2012 BC Org Expansion 1.80 52.00 13.9Ascomycota Pleosporales Sporormiaceae Preussia CA Org Expansion 0.54 23.89 0.7Ascomycota Pleosporales Venturiaceae Venturia CA | BC Org Decline 1.47 210.98 1.1Ascomycota Pleosporales Venturiaceae Rhizosphaera CA Org Expansion 1.20 31.32 5.0Ascomycota Pleosporomycetidae Gloniaceae Cenococcum BC, ON, CA - Decline 4.69 331.43 0.3Ascomycota Chaetothyriales Herpotrichiellaceae Cladophialophora BC, BS Org Variable 0.78 56.67 0.5Ascomycota Chaetothyriales Herpotrichiellaceae Capronia BC Org Variable 2.18 159.86 0.2Ascomycota Chaetothyriales Herpotrichiellaceae Rhinocladiella BC Org Decline 0.77 3.19 0.0Ascomycota Chaetothyriales NA Chaetothyriales sp EXP0559F BC, CA Org Decline 1.95 162.09 0.0Ascomycota Eurotiales Elaphomycetaceae Elaphomyces ON, CA, TX - Decline 14.44 334.23 0.0Ascomycota Eurotiales Trichocomaceae Sagenomella BC, ON Min Expansion 3.07 102.85 2.1Ascomycota Eurotiales Trichocomaceae Penicillium arenicola BC, ON Min Expansion 1.92 44.97 1.4Ascomycota Eurotiales Trichocomaceae Talaromyces BC, ON Org Expansion 2.02 60.00 1.4Ascomycota Lecanorales Cladoniaceae Cladoniaceae ON, BC Org Expansion 0.81 26.42 65.3Ascomycota Lecanorales NA Lecanorales BC, ON, CA - Expansion 0.74 26.42 37.5Ascomycota Helotiales Dermateaceae Cryptosporiopsis BC - Expansion 0.48 19.14 2.4Ascomycota Helotiales Dermateaceae Mollisia CA Org Expansion 0.78 20.81 14.8Ascomycota Helotiales Helotiaceae Crocicreas BC,ON, CA Org Decline 1.10 150.27 0.6Ascomycota Helotiales Helotiaceae Rhizoscyphus ericae BC, ON - Expansion 2.56 263.51 5.3Table E.6... continued Phylum Order Family Taxa EcozonesSoil Layer ResponseMean AbundanceMax. AbundanceResponse ratioAscomycota Helotiales Hyaloscyphaceae Hyaloscyphaceae sp I GK 2010 BC, ON Org Decline 0.78 6.76 0.0Ascomycota Helotiales Hyaloscyphaceae Mycoarthris SBS, CA Org Decline 0.94 21.91 0.1Ascomycota Helotiales Incertae sedis Cadophora f inlandica BC, ON, CA Min Expansion 3.05 322.32 2.7Ascomycota Helotiales Incertae sedis Rhexocercosporidium BC, BS, CA Min Expansion 1.03 50.12 4.5Ascomycota Helotiales Incertae sedis Tetracladium BC, ON Org Expansion 0.52 14.22 3.5Ascomycota Incertae sedis Incertae sedis Leohumicola incrustata BC, ON, Min Expansion 4.14 73.63 7.8Ascomycota Leotiales Leotiaceae Leotiaceae SBS, BS - Expansion 6.20 190.66 159.7Ascomycota NA NA Ascomycota sp F45 BC, ON, CA - Decline 1.32 20.23 0.0Ascomycota Rhytismatales Rhytismataceae Lophodermium molitoris ON - Expansion 0.49 4.88 15.7Ascomycota Thelebolales Thelebolaceae Thelebolus IDF Org Decline 2.38 432.70 0.1Ascomycota NA NA fungal sp TRN36 BC, ON, CA - Expansion 0.80 16.15 49.4Ascomycota NA NA ascomycete sp olrim916 BC, BS Min Expansion 1.14 59.16 13.0Ascomycota NA NA Ascomycete CR 2004 BC, CA Org Decline 0.49 4.90 0.0Ascomycota NA NA Ascomycota sp X33 BC - Expansion 1.93 118.72 11.8Ascomycota NA NA ascomycete sp CH Co24 ON Org Expansion 0.60 121.94 10.3Ascomycota NA NA Ascomycota sp PIMO 418 CA Org Expansion 1.14 74.68 46.9Ascomycota Pezizales Pyronemataceae Otidea BC, CA - Decline 8.16 85.16 0.0Ascomycota Hypocreales Bionectriaceae Clonostachys rosea catenulata TX Min Decline 1.89 500.00 0.0Ascomycota Hypocreales Cordycipitaceae Lecanicillium All Org Decline 0.82 14.22 0.2Ascomycota Hypocreales Cordycipitaceae Lecanicillium sp. BESC 246b ON, BC - Expansion 0.35 3.15 24.7Ascomycota Hypocreales Hypocreaceae Hypocrea SBS, ON, CA, TX Org Decline 1.13 37.29 0.4Ascomycota Hypocreales Nectriaceae Gibberella BC, CA, TX Org Expansion 0.74 21.22 16.7Ascomycota Hypocreales Nectriaceae Cylindrocarpon sp JAT1366 BC, BS - Expansion 0.84 32.31 4.8Ascomycota Sordariales Chaetomiaceae Trichocladium opacum BC, ON Min Expansion 0.66 14.59 6.0Basidiomycota Agaricales Amanitaceae Amanitaceae TX - Decline 10.07 290.76 0.4Basidiomycota Agaricales Cortinariaceae Cortinarius BC, ON, CA - Decline 5.27 427.35 0.3Basidiomycota Agaricales Hydnangiaceae Laccaria ON, CA - Expansion 5.13 185.14 1.6Basidiomycota Agaricales Hygrophoraceae Hygrophorus BC, ON, CA - Decline 17.59 316.98 0.1Basidiomycota Agaricales Inocybaceae Inocybe impexa SBS, ON Min Expansion 5.34 183.45 24.3Basidiomycota Agaricales Lyophyllaceae Lyophyllum BC Org Decline 1.27 36.95 0.0Basidiomycota Agaricales Mycenaceae Mycena corynephora TX - Expansion 2.14 62.74 7.5Basidiomycota Agaricales Tricholomataceae Tricholoma triste IDF - Decline 1.06 12.71 0.0Table E.6... continued Phylum Order Family Taxa EcozonesSoil Layer ResponseMean AbundanceMax. AbundanceResponse ratioBasidiomycota Atheliales Atheliaceae Piloderma All - Decline 18.70 907.86 0.2Basidiomycota Boletales Gomphidiaceae Gomphidiaceae BC, CA Min Expansion 0.98 6.85 38.5Basidiomycota Boletales Gomphidiaceae Chroogomphus BC - Expansion 0.72 6.85 45.7Basidiomycota Boletales Rhizopogonaceae Rhizopogon fuscorubens TX - Decline 0.83 25.78 0.5Basidiomycota Boletales Suillaceae Suillus pseudobrevipes BC, ON Min Expansion 60.18 1000.00 111.0Basidiomycota Boletales Suillaceae Suillus tomentosus BC - Expansion 4.62 403.77 36.2Basidiomycota Gomphales Gomphaceae Ramaria IDF, TX - Decline 1.73 14.94 0.0Basidiomycota Russulales Russulaceae Russula BC, ON, CA Min Decline 17.15 514.38 0.4Basidiomycota Sebacinales Sebacinaceae Sebacina BC Org Decline 1.65 78.74 0.5Basidiomycota Thelephorales Thelephoraceae Pseudotomentella BC, ON - Decline 4.24 238.57 0.0Basidiomycota Trechisporales NA uncultured Trechisporales BC, BS, TX - Expansion 3.56 116.62 3.5Basidiomycota NA NA Agaricomycotina sp BC, ON - Expansion 4.34 84.19 106.4Basidiomycota Filobasidiales Filobasidiaceae Cryptococcus SBS, ON - Expansion 2.48 99.67 1.5Chytridiomycota Monoblepharidales Oedogoniomycetaceae Oedogoniomyces CA - Expansion 0.46 3.22 17.3Chytridiomycota NA NA Monoblepharidomycetes CA, ON Min Expansion 0.65 4.60 4.3Uncl. Fungi NA NA fungal sp aurim625 ON, BC Min Expansion 1.62 67.77 6.7Zygomycota Mortierellales Mortierellaceae Mortierella sp WD35C BC, ON Min Expansion 0.75 8.85 2.5Zygomycota Mucorales Umbelopsidaceae Umbelopsis vinacea BC, BS, CA Org Decline 0.39 2.51 0.0Table E.6... continued Table E.7. Full list of bacterial and fungal taxa showing population expansion in intermediate intensities of OM-removal. Phylum Order Family Taxa EcozonesSoil Layer Max Abundance OM1|OM2Mean AbundanceMax Abundance REF|OM3Response ratioProteobacteria Rhizobiales Phyllobacteriaceae Phyllobacterium IDF None 20.96 0.52 8.50 2.4Proteobacteria Rhizobiales Methylobacteriaceae Methylobacterium BC Org 10.75 0.38 9.90 1.1Proteobacteria Rhizobiales Methylobacteriaceae Microvirga IDF Org 2.54 0.33 0.70 4.7Basidiomycota Agaricales Clavariaceae Ramariopsis BC None 16.32 5.25 67.99 2.0Basidiomycota Agaricales Entolomataceae Clitopilus sp. 1_T_778 TX Org 9.22 0.72 0.53 8.7Basidiomycota Agaricales Hygrophoraceae Hygrocybe sp SBS, JP None 145.08 4.30 16.88 13.3Basidiomycota Agaricales NA Agaricales sp. IDF Org 53.88 1.50 10.88 3.8Basidiomycota Atheliales Atheliaceae Piloderma sphaerosporum SBS, BS Org 907.86 23.70 344.53 3.4Basidiomycota Atheliales Atheliaceae Piloderma olivaceum SBS, JP Org 614.16 21.51 363.71 3.1Basidiomycota Boletales Gomphidiaceae Chroogomphus vinicolor SBS None 2.32 0.36 1.24 5.1Basidiomycota Boletales Suillaceae Suillus cothurnatus JP None 19.67 0.98 10.66 1.8Basidiomycota Hymenochaetales Schizoporaceae Hyphodontia aspera BC None 547.24 8.52 35.76 20.7Basidiomycota Thelephorales Thelephoraceae Thelephora sp. ECM1 BC, ON, CA Org 212.67 2.46 22.03 11.7Ascomycota Hypocreales Incertae sedis Myrothecium TX None 13.96 0.96 1.88 3.8Ascomycota Microascales Microascaceae Doratomyces stemonitis BC None 35.20 1.11 0.20 81.2Ascomycota Sordariales Lasiosphaeriaceae Podospora BC, TX Org 53.91 2.01 10.47 3.8Ascomycota Xylariales Amphisphaeriaceae Discosia sp.1_KT_2010 TX None 5.01 0.21 1.65 4.6Ascomycota Pezizales Tuberaceae Tuber sp. 17_KA_2010 CA Min 106.17 20.44 0.00 OM 1|OM 2 onlyAscomycota Geoglossales Geoglossaceae Geoglossum BC None 117.42 4.47 25.92 4.1Ascomycota Helotiales Incertae sedis Tetracladium IDF Org 14.22 0.52 5.68 3.3Ascomycota Rhytismatales Rhytismataceae Colpoma sp. PDD_91607 ON Org 6.72 1.91 8.83 1.1Ascomycota Eurotiales Trichocomaceae Penicillium adametzii JP Org 123.47 2.09 72.22 1.5Ascomycota Verrucariales NA Verrucariales BC, ON None 234.90 1.92 58.45 1.7Ascomycota Capnodiales Incertae sedis Elasticomyces elasticus BC Org 10.44 0.92 3.35 5.1Ascomycota Capnodiales Mycosphaerellaceae Mycosphaerella sp. AM_2006c BC Org 38.64 0.82 2.98 8.0Unclassif ied NA NA Fungal sp. AB22 IDF, CA Org 8.72 0.52 2.51 5.0Unclassif ied NA NA Fungal sp. OTU_084 TX None 0.39 0.12 0.13 6.8 Blodgett Brandy City Lowell HillYear Established 1994 1995 1995Lat / Long 38.88N / 120.64W 39.55N / 121.04W 39.26N / 120.78WElevation 1350 m 1135 m 1268 m Soil typeAverage Percent Carbon 8A ± 0.36 7B ± 0.15 4.7C ± 0.14Average Percent Nitrogen 0.37A ± 0.019 0.32B ± 0.007 0.2C ± 0.004Average C:N Ratio 22.1 ± 0.45 22.2 ± 0.42 23.5 ± 0.77Average pH 5.69 ± 0.04 5.77 ± 0.08 5.81 ± 0.09Respiration (n=36) Average mg CO2 per g soil 1.13A ± 0.05 1.02 ± 0.04 0.97B ± 0.05 Average delta-13C 1400A ± 100 3300B ± 400 2500B ± 300Total 13C Biomass (umols C per g soil) 0.33A 0.63B 0.53Total 12C Biomass (umols C per g soil) 46.5A 25.8B 21.3BTechnical error (S.D.) for delta-13C is 80, which is equivalent to an average of ± 0.0003 umols CSite DataMesic Ultic Haploxeralfs (Loamy)Soil composition (n=9)PLFA Biomass (n = 12)Table E.8. Overview of site characteristics for environmental and soil parameters and microbial activity. Values denoted by letters are statistically significant (p < 0.05) by lettering group based on Tukey’s Honest Significant Difference. REF OM1 OM2 OM3 REF OM1 OM2 OM3Average Percent Carbon37.0 ± 2.2 41.5A ± 1.0 33.0 ± 2.4 31.5B ± 3.6 5.9 ± 0.5 7.6 ± 0.7-6.4 ± 0.8Average Percent Nitrogen1.21 ± 0.09 1.34 ± 0.11 1.21 ± 0.13 1.10 ± 0.13 0.26 ± 0.02 0.31 ± 0.04-0.32 ± 0.04Average C:N Ratio31.1 ± 1.5 32.5 ± 3.3 28.2 ± 1.7 29.5 ± 2.2 22.3 ± 0.9 25.4A ± 1.3-20.0B ± .03Average pH5.47 ± 0.2 4.35A ± 0.2 5.1 ± 0.2 5.2B ± 0.1 6.1 ± 0.2 5.5 ± 0.1-5.6 ± 0.1Repiration (n=36) Average mg CO2 per g soil - - - -1.20A ± 0.04 1.01B ± 0.04-0.90C ± 0.05Average Delta 13C1,600 ± 110 1,100 ± 130 2,300 ± 170 1,400 ± 70 6,400A ± 870 4,800 ± 650 4,800 ± 700 3,200B ± 540Total 13C carbon (umols 13C per g soil) 0.96A 0.45B 0.62 0.68 0.42A 0.43A 0.41A 0.24BTotal 12C carbon (umols 13C per g soil) 32.2A 19.0B 16.6B 25.8A 5.0A 6.6B 6.2 5.0Median number of enriched FA 33A ± 0.9 27C ± 1.2 27B ± 0.7 25C ± 0.5 29 ± 1.2 29 ± 0.7 29 ± 0.6 27 ± 0.7Fungal:Bacteria Ratio (13C)0.78A ± 0.07 0.95A ± 0.05 1.68B ± 0.21 1.95B ± 0.48 0.64 ± 0.13 0.71 ± 0.15 0.92 ± 0.13 1.03 ± 0.23 DNA enrichment (n=3)Atom % 13C above natural abundance 4.8 ± 1.0 4.5 ± 1.5 5.6 ± 1.1 3.3 ± 0.5 14.6A ± 2.2 9.9 ± 1.1 10.3 ± 0.6 9.1B ± 1.1Technical error (S.D.) for Delta-values is 80, which is equivalent to an average of ± 0.0003 umols COrganic Layer Mineral LayerSoil composition (n=9)PLFA Biomass Measures (n= 9)Table E.9. Overview of soil properties and cellulolytic activity (i.e. 13C-enrichment of PLFA or DNA) among soil layers and harvesting treatments. All values correspond to the mean ± standard error. Within groups of treatments, significantly different values (p < 0.05) have been denoted by lettering based on Tukey’s Honest Significant Difference. Table E.10. Complete list of OTUs designated putatively cellulolytic based on differential abundance between 13C- and 12C-pyrotag libraries. Representative Sequence ID PhylumLowest taxonomic classificationGenBank AccessionSoil Layer AffiliationRatio (13C:12C)Mean Counts 13C LibrariesIIKFCBR01BZTGT FBP - KM391432 Min 380.4 86.46IIKFCBR01BFFL6 FBP - KM391438 Min 138.8 63.08HN7PONR02H7VJP FBP - KM391441 None 95.8 52.25IIKFCBR01AO3YU FBP - KM391442 Min 86.0 50.83HIGEX0001DHO1H FBP - KM391496 Min 104.0 9.46IIKFCBR01DEH19 FBP - KM391570 Min 13C-only 2.71IIKFCBR01D1LXB FBP - KM391612 Min 13C-only 1.5IIKFCBR01D3UQS FBP - KM391623 None 13C-only 1.21IIKFCBR01EFACT FBP - KM391624 Min 13C-only 1.21IIKFCBR01CSGER FBP - KM391628 Org 24.8 1.12IIKFCBR01A1GBU Chloroflexi c__Anaerolineae KM391569 Min 9.2 2.5HN7PONR02GQXBE Chloroflexi c__Anaerolineae KM391607 Min 33.0 1.5IIKFCBR01BMT7K TM7 c__SC3 NA Min 9.7 8.33IIKFCBR01B8I79 TM7 c__TM7-3 KM391459 Min 16.8 23.67IIKFCBR01CC1CG TM7 c__TM7-3 KM391535 Min 5.4 3.92IIKFCBR01AVU5M TM7 c__TM7-3 KM391552 Min 4.0 2.92IIKFCBR01A3FLV TM7 c__TM7-3 KM391555 Min 76.1 3.46HIGEX0001AOCX6 TM7 c__TM7-3 KM391631 Min 23.8 1.08IIKFCBR01EEO74 Acidobacteria f__Acidobacteriaceae KM391499 Org 8.3 7.88IIKFCBR01DRU3P Betaproteobacteria f__Burkholderiaceae KM391469 Org 8.6 16.33IIKFCBR01CIYUN Alphaproteobacteria f__Caulobacteraceae KM391466 Min 3.8 16.67IIKFCBR01DYD22 Alphaproteobacteria f__Caulobacteraceae KM391477 Min 11.1 13.67IIKFCBR01CIUIN Verrucomicrobia f__Chthoniobacteraceae KM391501 Min 13C-only 8.08IIKFCBR01ERXIS Betaproteobacteria f__Comamonadaceae KM391426 Org 6.0 463IIKFCBR01DS94Y Betaproteobacteria f__Comamonadaceae KM391457 Org 8.9 24.12IIKFCBR01C43J2 Betaproteobacteria f__Comamonadaceae KM391482 Min 32.0 13.08IIKFCBR01A7C7S Betaproteobacteria f__Comamonadaceae KM391506 Org 81.6 7.42IIKFCBR01A1YGP Betaproteobacteria f__Comamonadaceae KM391536 None 9.6 3.92IIKFCBR01ANKGB Betaproteobacteria f__Comamonadaceae KM391609 None 16.0 1.46IIKFCBR01C5N8I Betaproteobacteria f__Comamonadaceae KM391633 Org 11.5 1.04IIKFCBR01EGBTI Betaproteobacteria f__Comamonadaceae KM391634 None 11.5 1.04IIKFCBR01BU6ZQ Actinobacteria f__Microbacteriaceae KM391455 Org 4.9 23.17IIKFCBR01C2U0N Actinobacteria f__Microbacteriaceae KM391529 Org 9.3 4.62IIKFCBR01B6QL0 Actinobacteria f__Microbacteriaceae KM391557 Org 37.6 3.42IIKFCBR01APJE8 Actinobacteria f__Microbacteriaceae KM391584 Org 8.3 1.88IIKFCBR01BYZFY Actinobacteria f__Micrococcaceae KM391440 Min 7.4 49 Representative Sequence ID PhylumLowest taxonomic classificationGenBank AccessionSoil Layer AffiliationRatio (13C:12C)Mean Counts 13C LibrariesIIKFCBR01BCOEN Actinobacteria f__Micrococcaceae KM391458 Min 9.4 24.04IIKFCBR01DDYRU Actinobacteria f__Micrococcaceae KM391474 Min 8.7 15IIKFCBR01BJ93C Actinobacteria f__Micrococcaceae KM391475 Min 11.7 14.88HN7PONR01BR35E Actinobacteria f__Micrococcaceae KM391480 Min 5.3 12.12IIKFCBR01BDZM0 Actinobacteria f__Micrococcaceae KM391487 Min 6.9 10.92IIKFCBR01BE44L Actinobacteria f__Micrococcaceae KM391493 Min 6.1 8.62IIKFCBR01C7YA6 Actinobacteria f__Micrococcaceae KM391494 Min 6.7 8.5IIKFCBR01A57Z2 Actinobacteria f__Micrococcaceae KM391516 Min 11.9 5.96IIKFCBR01B332I Actinobacteria f__Micrococcaceae KM391527 Min 16.0 5.08IIKFCBR01BLXQH Actinobacteria f__Micrococcaceae KM391575 Min 5.7 2.08IIKFCBR01B0YQ8 Actinobacteria f__Micrococcaceae KM391576 Min 16.2 2.21IIKFCBR01AWDW0 Actinobacteria f__Micrococcaceae KM391579 Min 47.7 2.17IIKFCBR01BFXK4 Actinobacteria f__Micrococcaceae KM391586 None 9.9 1.79IIKFCBR01AEE5B Actinobacteria f__Micrococcaceae KM391608 Min 10.4 1.42IIKFCBR01BKECV Actinobacteria f__Micrococcaceae KM391616 None 13C-only 1.42IIKFCBR01CUHF7 Verrucomicrobia f__Opitutaceae KM391546 Min 13C-only 3.92IIKFCBR01DZQMM Betaproteobacteria f__Oxalobacteraceae KM391434 None 3.2 62.17IAJCH1401CBT2J Betaproteobacteria f__Oxalobacteraceae KM391436 Min 25.1 66.12IIKFCBR01BAN8Z Betaproteobacteria f__Oxalobacteraceae KM391449 Min 8.2 28.29IIKFCBR01A76N2 Betaproteobacteria f__Oxalobacteraceae KM391451 Min 31.6 28.75HNWQNZC02JYSX7 Betaproteobacteria f__Oxalobacteraceae KM391452 Min 7.6 26.04IIKFCBR01BCCJU Betaproteobacteria f__Oxalobacteraceae KM391484 Min 7.8 11.67IIKFCBR01C2P23 Betaproteobacteria f__Oxalobacteraceae KM391497 Min 27.0 8.58IIKFCBR01B6UNX Betaproteobacteria f__Oxalobacteraceae KM391531 Min 8.7 4.33IIKFCBR01CXGLN Betaproteobacteria f__Oxalobacteraceae KM391532 Min 4.6 4IIKFCBR01A2C6E Betaproteobacteria f__Oxalobacteraceae KM391540 None 21.8 3.96IIKFCBR01CHYHE Betaproteobacteria f__Oxalobacteraceae KM391542 Min 43.5 3.96IIKFCBR01EYBXG Betaproteobacteria f__Oxalobacteraceae KM391549 None 9.1 3.29IIKFCBR01B4BRK Betaproteobacteria f__Oxalobacteraceae KM391581 Min 6.7 1.83IIKFCBR01CHZ6D Betaproteobacteria f__Oxalobacteraceae KM391615 None 31.2 1.42IIKFCBR01B2HLT Betaproteobacteria f__Oxalobacteraceae KM391625 None 13C-only 1.21IIKFCBR01CPZBH Betaproteobacteria f__Oxalobacteraceae KM391644 None 11.0 0.5IIKFCBR01BXH5Y Deltaproteobacteria f__Polyangiaceae KM391587 None 13.1 1.79IIKFCBR01DEHMO Deltaproteobacteria f__Polyangiaceae KM391594 Min 13C-only 1.75IIKFCBR01DMDVI Deltaproteobacteria f__Polyangiaceae KM391617 None 14.2 1.29IIKFCBR01BYX3V Alphaproteobacteria f__Rhizobiaceae KM391503 Min 9.2 7.12IAJCH1401C9UV8 Alphaproteobacteria f__Rhizobiaceae KM391533 Org 4.5 3.71IAJCH1401A7YMK Alphaproteobacteria f__Sphingomonadaceae KM391488 None 6.7 10.29IIKFCBR01C0549 Alphaproteobacteria f__Sphingomonadaceae KM391518 Org 20.8 5.67IAJCH1401AEXIJ Actinobacteria f__Streptomycetaceae KM391421 Min 10.9 1048.58IIKFCBR01BYUBL Actinobacteria f__Streptomycetaceae KM391422 Org 11.9 1039.96IAJCH1401BBVVT Actinobacteria f__Streptomycetaceae KM391425 Org 52.8 628.71IIKFCBR01D5T95 Actinobacteria f__Streptomycetaceae KM391430 Org 15.9 101.46IIKFCBR01AZO3D Actinobacteria f__Streptomycetaceae KM391435 Org 20.1 75.75IIKFCBR01ECL7T Actinobacteria f__Streptomycetaceae KM391489 Org 4.8 9.58Table E.10... continued Representative Sequence ID PhylumLowest taxonomic classificationGenBank AccessionSoil Layer AffiliationRatio (13C:12C)Mean Counts 13C LibrariesIIKFCBR01CGLNH Actinobacteria f__Streptomycetaceae KM391490 Org 11.8 10.17IAJCH1401BOAMR Actinobacteria f__Streptomycetaceae KM391512 Org 5.0 5.62IIKFCBR01CLDHG Actinobacteria f__Streptomycetaceae KM391539 Org 90.8 4.12IIKFCBR01AXDQT Actinobacteria f__Streptomycetaceae KM391547 Org 41.7 3.79IIKFCBR01E0MN1 Actinobacteria f__Streptomycetaceae KM391548 None 26.3 3.58IIKFCBR01DMD0B Actinobacteria f__Streptomycetaceae KM391554 None 76.1 3.46IIKFCBR01B5BIG Actinobacteria f__Streptomycetaceae KM391556 Org 12.1 3.29IIKFCBR01DXW8W Actinobacteria f__Streptomycetaceae KM391558 Org 6.7 3.04IIKFCBR01B7AGX Actinobacteria f__Streptomycetaceae KM391559 Org 74.3 3.38IIKFCBR01CGADV Actinobacteria f__Streptomycetaceae KM391566 Org 14.9 2.71IIKFCBR01EPBWF Actinobacteria f__Streptomycetaceae KM391567 Org 62.3 2.83IIKFCBR01BOVHS Actinobacteria f__Streptomycetaceae KM391573 Org 28.4 2.58IIKFCBR01AU6O6 Actinobacteria f__Streptomycetaceae KM391574 Org 56.8 2.58IIKFCBR01D7QZF Actinobacteria f__Streptomycetaceae KM391597 Org 11.6 1.58IAJCH1401BKC7U Actinobacteria f__Streptomycetaceae KM391627 Org 24.8 1.12IIKFCBR01AID29 Actinobacteria f__Streptomycetaceae KM391637 Org 13C-only 0.96IIKFCBR01DVIF8 Actinobacteria f__Streptomycetaceae KM391638 Org 13C-only 0.79IIKFCBR01CPO5D Verrucomicrobia f__Verrucomicrobiaceae KM391614 Min 31.2 1.42IIKFCBR01EWOZA Alphaproteobacteria g__Asticcacaulis KM391431 Org 9.3 92.92IIKFCBR01DL1OD Alphaproteobacteria g__Asticcacaulis NA Min 249.7 56.75IIKFCBR01CMBQF Alphaproteobacteria g__Asticcacaulis KM391445 Min 6.2 33.38HS30DLI03GTYPT Alphaproteobacteria g__Asticcacaulis KM391453 Org 11.2 26.92HTIQ2CV02D5F0W Alphaproteobacteria g__Asticcacaulis KM391486 Org 17.5 11.96HTIQ2CV02EMOB8 Alphaproteobacteria g__Asticcacaulis KM391491 Min 3.6 8.54IIKFCBR01B3UOM Alphaproteobacteria g__Asticcacaulis KM391504 None 2.5 5.71IIKFCBR01C57G0 Alphaproteobacteria g__Asticcacaulis KM391509 Org 10.0 6.38IAJCH1401CIS09 Alphaproteobacteria g__Asticcacaulis KM391515 Org 2.8 4.88IAJCH1401AWMYF Alphaproteobacteria g__Asticcacaulis KM391596 Org 8.0 1.46IIKFCBR01DHW5N Alphaproteobacteria g__Asticcacaulis KM391604 Min 13C-only 1.58IIKFCBR01DXYAY Alphaproteobacteria g__Bosea KM391478 Min 9.7 13.25IIKFCBR01ETHS5 Alphaproteobacteria g__Bradyrhizobium KM391485 None 2.9 9.71HN5XJPU01A522S Betaproteobacteria g__Burkholderia KM391468 Org 8.1 16.5IAJCH1401C0K4M Betaproteobacteria g__Burkholderia KM391476 None 6.0 13.46IIKFCBR01C5DL9 Betaproteobacteria g__Burkholderia KM391498 Org 9.3 8.04IIKFCBR01AX8JN Betaproteobacteria g__Burkholderia KM391578 Org 22.9 2.08IIKFCBR01DE6JJ Alphaproteobacteria g__Caulobacter KM391429 None 10.6 101.71IIKFCBR01DW3ZT Alphaproteobacteria g__Caulobacter KM391463 None 10.7 20.88IIKFCBR01D0O4W Alphaproteobacteria g__Caulobacter KM391583 Org 8.3 1.88IIKFCBR01DE6JJ Alphaproteobacteria g__Caulobacter KM391429 None 13C-only 0.62IIKFCBR01DWA8V Verrucomicrobia g__Chthoniobacter KM391602 None 11.0 1.5HNWQNZC01E81FU Actinobacteria g__Cryocola KM391444 Min 3.0 33.83IIKFCBR01CKQ7J Actinobacteria g__Cryocola KM391461 None 5.0 20.04IIKFCBR01DE9YX Actinobacteria g__Cryocola KM391481 None 4.6 11.58IIKFCBR01AYG8N Actinobacteria g__Cryocola KM391483 None 13.1 12.54IIKFCBR01ATR7O Actinobacteria g__Cryocola KM391528 None 6.4 4.67Table E.10... continued Representative Sequence ID PhylumLowest taxonomic classificationGenBank AccessionSoil Layer AffiliationRatio (13C:12C)Mean Counts 13C LibrariesIIKFCBR01BOI04 Actinobacteria g__Cryocola KM391551 None 3.0 2.75IIKFCBR01AGJ26 Actinobacteria g__Cryocola KM391565 Min 5.5 2.5IIKFCBR01D19UA Bacteroidetes g__Cytophaga KM391534 Org 6.3 4IIKFCBR01DRRUD Alphaproteobacteria g__Devosia KM391525 Min 5.5 4.71IIKFCBR01EWZMX Betaproteobacteria g__Janthinobacterium KM391423 Min 5.7 853.88IIKFCBR01CGTHF Betaproteobacteria g__Janthinobacterium KM391427 Min 9.1 290.62IAJCH1401AD6I5 Betaproteobacteria g__Janthinobacterium KM391428 Min 5.2 122.12IIKFCBR01AZ0B7 Betaproteobacteria g__Janthinobacterium KM391433 None 6.1 72.54IIKFCBR01EOLME Betaproteobacteria g__Janthinobacterium KM391446 None 4.9 29.79IIKFCBR01B7Z4O Betaproteobacteria g__Janthinobacterium KM391454 Org 15.2 26.92IIKFCBR01DKN65 Betaproteobacteria g__Janthinobacterium KM391471 None 7.6 15.83IAJCH1401B0CT5 Betaproteobacteria g__Janthinobacterium KM391502 Min 2.7 5.88HNWQNZC01AW5S8 Betaproteobacteria g__Janthinobacterium KM391537 Min 2.7 3.17IIKFCBR01ATT4K Betaproteobacteria g__Janthinobacterium KM391560 None 17.4 3.17IIKFCBR01CSF10 Betaproteobacteria g__Janthinobacterium KM391563 Org 22.0 3IIKFCBR01B7NTC Betaproteobacteria g__Janthinobacterium KM391580 Org 10.8 1.96IIKFCBR01DPHE6 Betaproteobacteria g__Janthinobacterium KM391595 Min 11.6 1.58IIKFCBR01EL7PJ Betaproteobacteria g__Janthinobacterium KM391598 Min 6.4 1.46HNWQNZC01DF0MN Betaproteobacteria g__Janthinobacterium KM391622 None 8.3 1.12IIKFCBR01BHM2D Actinobacteria g__Kitasatospora KM391437 None 10.8 62.71IIKFCBR01A92N7 Actinobacteria g__Kitasatospora KM391450 None 35.2 30.38IIKFCBR01CPH7B Actinobacteria g__Kitasatospora KM391524 Org 29.3 5.33IIKFCBR01BNMKB Betaproteobacteria g__Leptothrix KM391424 None 8.8 644.5IIKFCBR01CBLMK Betaproteobacteria g__Leptothrix KM391460 None 17.8 22.62IIKFCBR01DDITR Betaproteobacteria g__Leptothrix KM391513 None 4.3 5.46IIKFCBR01DBPL1 Betaproteobacteria g__Leptothrix KM391635 Org 21.1 0.96IIKFCBR01D9FYH Betaproteobacteria g__Leptothrix KM391640 None 13C-only 0.71IIKFCBR01CTV7M Alphaproteobacteria g__Mesorhizobium KM391517 Min 4.0 4.96IIKFCBR01EIWNB Alphaproteobacteria g__Mesorhizobium KM391541 None 3.2 3.17IIKFCBR01BMHDJ Gammaproteobacteria g__Nevskia KM391467 Org 6.4 17.71IIKFCBR01D4HTE Verrucomicrobia g__Opitutus KM391654 Min 115.7 21.04IIKFCBR01BJI11 Betaproteobacteria g__Paucibacter KM391448 None 4.7 27.08IAJCH1401CKQZM Betaproteobacteria g__Paucibacter KM391456 None 10.6 24.5IIKFCBR01BZE2Q Betaproteobacteria g__Pelomonas KM391465 None 10.6 19.83IIKFCBR01EBDC6 Betaproteobacteria g__Pelomonas KM391530 Min 105.4 4.79IIKFCBR01AQLQI Betaproteobacteria g__Pelomonas KM391639 None 13C-only 0.75IIKFCBR01BJ8KD Alphaproteobacteria g__Phenylobacterium KM391462 Min 5.8 19.83IIKFCBR01DVJID Alphaproteobacteria g__Phenylobacterium KM391585 Min 6.3 1.71HVPQ45002GZ4LA Actinobacteria g__Phycicoccus KM391505 Min 5.9 6.75IIKFCBR01A5WQO Betaproteobacteria g__Polaromonas KM391521 Min 5.6 4.88HPPSXLA04JDLB2 Betaproteobacteria g__Ralstonia KM391470 Min 129.9 17.71IIKFCBR01ENIXV Betaproteobacteria g__Rubrivivax KM391508 Min 4.3 5.83IIKFCBR01CS2O2 Actinobacteria g__Salinibacterium KM391514 Org 5.7 5.71IIKFCBR01CF4HA Alphaproteobacteria g__Sphingomonas KM391443 Min 3.8 41.04IAJCH1401ANLMS Alphaproteobacteria g__Sphingomonas KM391619 Org 14.7 1.33Table E.10... continued Representative Sequence ID PhylumLowest taxonomic classificationGenBank AccessionSoil Layer AffiliationRatio (13C:12C)Mean Counts 13C LibrariesIIKFCBR01AP3GS Alphaproteobacteria g__Telmatospirillum KM391561 Org 9.3 2.96HNWQNZC01DTU7D Betaproteobacteria g__Variovorax KM391492 Org 3.3 8.08IIKFCBR01AK29F Actinobacteria o__Actinomycetales KM391519 Min 17.7 5.62HN7PONR02G9M87 Actinobacteria o__Actinomycetales KM391523 Min 11.4 5.17IIKFCBR01DDQMW Actinobacteria o__Actinomycetales KM391577 None 4.7 1.92IIKFCBR01BDV50 Actinobacteria o__Actinomycetales KM391591 None 4.0 1.46IIKFCBR01DKQLI Betaproteobacteria o__Burkholderiales NA Min 19.7 5.38IIKFCBR01EGDAL Betaproteobacteria o__Burkholderiales KM391522 None 8.5 5.04IIKFCBR01DEFOY Bacteroidetes o__Cytophagales KM391439 Min 142.1 58.12IIKFCBR01AZQYV Bacteroidetes o__Cytophagales KM391447 Min 21.3 33.83HN5XJPU01C054O Bacteroidetes o__Cytophagales KM391473 None 20.6 15.92IIKFCBR01EUQP0 Bacteroidetes o__Cytophagales KM391495 Min 16.7 9.08IIKFCBR01CGUSV Bacteroidetes o__Cytophagales KM391510 Min 13C-only 6.96IIKFCBR01D0ZL6 Bacteroidetes o__Cytophagales KM391562 Min 13C-only 3.25IIKFCBR01BFRBV Bacteroidetes o__Cytophagales KM391605 None 33.0 1.5IIKFCBR01BID66 Bacteroidetes o__Cytophagales KM391620 None 29.3 1.33IIKFCBR01DUERY Bacteroidetes o__Cytophagales KM391621 None 27.5 1.25IIKFCBR01CHWQH Planctomycetes o__DH61 KM391479 Min 13C-only 14.25IIKFCBR01DSIAC Planctomycetes o__DH61 KM391572 Min 57.8 2.62IIKFCBR01EN49F Alphaproteobacteria o__Ellin329 KM391511 Org 4.5 5.75IIKFCBR01BGW6K Alphaproteobacteria o__Ellin329 KM391520 Org 5.1 4.83IIKFCBR01DYEEF TM7 o__EW055 KM391544 None 3.1 3.12IIKFCBR01A2CCO Armatimonadetes o__FW68 KM391550 None 13C-only 3.58IIKFCBR01ER26I Armatimonadetes o__FW68 KM391553 Org 8.8 3.21IIKFCBR01DFO06 Armatimonadetes o__FW68 KM391590 Min 12.5 1.71IIKFCBR01BKF9Q Verrucomicrobia o__Methylacidiphilales KM391646 None 13C-only 0.46IIKFCBR01B9OL1 Deltaproteobacteria o__MIZ46 KM391472 Min 37.9 17.21IAJCH1401DPXDE Deltaproteobacteria o__MIZ46 KM391507 Min 19.7 7.17IIKFCBR01C6K44 Deltaproteobacteria o__MIZ46 KM391526 Min 8.2 4.83IIKFCBR01BRR15 Deltaproteobacteria o__MIZ46 NA None 8.0 1.46IIKFCBR01CBA0U Deltaproteobacteria o__MIZ46 KM391613 None 32.1 1.46IIKFCBR01DMVF6 Deltaproteobacteria o__MIZ46 KM391632 Min 23.8 1.08IIKFCBR01BM6WY Deltaproteobacteria o__Myxococcales KM391582 None 22.0 2IIKFCBR01CAP7T Deltaproteobacteria o__Myxococcales KM391599 None 11.3 1.54IIKFCBR01BF99Q Deltaproteobacteria o__Myxococcales KM391626 Min 13C-only 1.21IIKFCBR01C50P4 Deltaproteobacteria o__Myxococcales KM391636 None 19.3 0.88IIKFCBR01DXTPR Deltaproteobacteria o__Myxococcales KM391643 None 13C-only 0.58IIKFCBR01C17DJ Deltaproteobacteria o__Myxococcales KM391645 None 13C-only 0.5IIKFCBR01DRG3U Alphaproteobacteria o__Rhizobiales KM391545 Min 20.4 3.71IIKFCBR01EHNDT Alphaproteobacteria o__Rhizobiales KM391589 Min 39.4 1.79IIKFCBR01BEDM7 Planctomycetes o__WD2101 KM391653 Min 11.0 2IIKFCBR01DJ6HG Planctomycetes o__WD2101 KM391588 None 7.3 1.67IIKFCBR01DVO2Q Planctomycetes o__WD2101 KM391593 Min 37.6 1.71HN7PONR02HB4QW Planctomycetes o__WD2101 KM391601 Min 11.3 1.54IIKFCBR01EHYT4 Planctomycetes o__WD2101 KM391603 Min 7.8 1.42Table E.10... continued Representative Sequence ID PhylumLowest taxonomic classificationGenBank AccessionSoil Layer AffiliationRatio (13C:12C)Mean Counts 13C LibrariesIIKFCBR01A4L7J Planctomycetes o__WD2101 KM391610 Min 10.4 1.42IIKFCBR01DONLF Planctomycetes o__WD2101 KM391611 Min 13C-only 1.5IIKFCBR01BPA0N Planctomycetes o__WD2101 KM391618 None 30.3 1.38HN7PONR02FP5QD Planctomycetes o__WD2101 KM391629 None 23.8 1.08IIKFCBR01C0JKL Planctomycetes o__WD2101 KM391630 None 11.5 1.04IIKFCBR01DS8OU Bacteroidetes Unclassified KM391464 Min 242.5 22.04IIKFCBR01AELU7 Unclassified Unclassified KM391652 Min 47.1 10.71IIKFCBR01BUBLL Bacteroidetes Unclassified KM391500 Min 29.9 8.17IIKFCBR01BHPNL Bacteroidetes Unclassified NA Min 29.2 7.96IIKFCBR01E1K9Q Alphaproteobacteria Unclassified KM391538 None 5.2 3.54HN7PONR02JXI1W Betaproteobacteria Unclassified KM391543 Org 13.9 3.79IIKFCBR01BBGJU Bacteroidetes Unclassified KM391564 Org 8.6 2.75IIKFCBR01EI8BP Unclassified Unclassified KM391568 Min 13C-only 2.79IIKFCBR01ANT35 Bacteroidetes Unclassified KM391571 Min 58.7 2.67IIKFCBR01CL9KO Unclassified Unclassified NA None 13C-only 2.25IIKFCBR01D9WAN Bacteroidetes Unclassified KM391592 Min 18.8 1.71IIKFCBR01EPMN9 Verrucomicrobia Unclassified KM391600 Org 13C-only 1.67IIKFCBR01CIOT3 Unclassified Unclassified KM391606 Org 33.0 1.5IIKFCBR01BGI0P Proteobacteria Unclassified NA None 13C-only 0.71Table E.10... continued Taxonomic Affiliation of Draft Genome BinMEGAN Classif ication (% of bases assigned)Scaffold Accession Numbers (E.N.A.)Size of Partial Genome (Mb)Number of ContigsLargest Scaffold (Kb)% Complete% RedundantControl (%)OM1 (%)OM3 (%)Reference (%)Myceliophthora thermophila Ascomycota (99%) FJWA01000001-FJWA01010187 46.2 10187 32.1 100 24 0.47 14.07 9.67 7.97Kitasatospora sp. Actinobacteria (79%) FJVZ01000001-FJVZ01001553 8.1 1553 31.7 100 21 0.08 0.54 0.28 6.05Opitutaceae spp. Verrucomicrobia (78%) FJVV01000001-FJVV01001035 5.7 1035 46.9 100 18 0.00 0.03 0.03 1.71Herbaspirillum sp. β - Proteobacteria (100%) FJVX01000001-FJVX01001352 4.3 1352 19.3 89 24 0.00 1.73 0.02 0.06Chthoniobacter sp. 1 Verrucomicrobia (74%) FJVU01000001-FJVU01000901 4.0 901 21.9 66 24 0.00 0.09 0.05 1.11Caulobacteraceae spp. α - Proteobacteria (96%) FJVW01000001-FJVW01001105 3.3 1105 14.8 76 19 0.00 0.06 0.04 0.72Heterogeneous Bin Cand. Saccharibacteria (27%) FJVY01000001-FJVY01000803 2.4 103 37.7 94 32 0.01 0.27 0.18 0.64Arthrobacter sp. Actinobacteria (60%) FJVT01000001-FJVT01000548 0.8 548 5.3 10 0 0.01 0.07 0.15 0.06Oxalobacteraceae spp. β - Proteobacteria (96%) FJVS01000001-FJVS01000283 0.4 283 3.4 0 NA 0.00 0.03 0.01 0.08Candidatus Saccharibacteria Cand. Saccharibacteria (56%) FJVR01000001-FJVR01000103 0.4 803 16.0 38 34 0.00 0.01 0.02 0.15Chthoniobacter sp. 2 Verrucomicrobia (65%) NA 0.4 119 6.0 5 0 0.00 0.01 0.00 0.11Table E.11. Full details of draft genomes recovered from metagenomics assemblies. ‘Completeness’ is a measure of the total number of housekeeping genes present from a list of single copy ‘essential’ genes (Albertsen et al. 2013). ‘Redundancy’ refers to the number of times those house-keeping genes recurred. The final four columns correspond to the percentage of reads mapped to each draft genome from the respective metagenomic samples. Note: ‘CheckM’ was not used in this analysis, in contrast to Chapter 4. Table E.12. Complete list of OTUs designated putatively hemicellulolytic, cellulolytic and/or lignolytic based on differential abundance between 13C- and 12C-pyrotag or metagenomic libraries at ecozones across North America. Taxa identified exclusively in metagenomic libraries are denoted with an asterix (*). Phylum Class Order Family Genus EcozonesSoil Assoc.Substr.Acidobacteria Acidobacteria-6 iii1-15 Unclassif ied Unclassif ied BS;CA;TX None LigAcidobacteria DA052 Ellin6513 unclassif ied unclassif ied TX None LigAcidobacteria Solibacteres Solibacterales Unclassif ied Unclassif ied BS;CA;TX None LigActinobacteria Acidimicrobiia Acidimicrobiales unclassif ied unclassif ied BS,TX None LigActinobacteria Actinobacteria Actinomycetales ACK-M1 Unclassif ied JP None LigActinobacteria Actinobacteria Actinomycetales Frankiaceae Unclassif ied BS,TX None LigActinobacteria Actinobacteria Actinomycetales Microbacteriaceae Unclassif ied All None Cell;LigActinobacteria Actinobacteria Actinomycetales Microbacteriaceae Salinibacterium BC;BS;CA;TX None Hemi;CellActinobacteria Actinobacteria Actinomycetales Micrococcaceae Unclassif ied BC;CA Min Hemi;LigActinobacteria Actinobacteria Actinomycetales Streptomycetaceae Streptomyces BC;CA None HemiActinobacteria Actinobacteria Actinomycetales Streptomycetaceae Unclassif ied CA;BS;JP None Hemi;CellActinobacteria Thermoleophilia Gaiellales Gaiellaceae Unclassif ied TX None LigActinobacteria Thermoleophilia Solirubrobacterales Conexibacteraceae Conexibacter BS;TX Org Cell;LigActinobacteria Thermoleophilia Solirubrobacterales Conexibacteraceae Unclassif ied BS;TX None LigArmatimonadetes Armatimonadia FW68 Unclassif ied Unclassif ied BC;CA;BS;TX None CellBacteroidetes Bacteroidetes Sphingobacteriales Sphingobacteriaceae Unclassif ied BC;CA;TX None Hemi;LigBacteroidetes Cytophagia Cytophagales Cytophagaceae Cytophaga BC;CA;TX None CellChloroflexi C0119 Unclassif ied Unclassif ied Unclassif ied CA Org LigElusimicrobia Elusimicrobia FAC88 Unclassif ied Unclassif ied BS None LigFBP Unclassif ied Unclassif ied Unclassif ied Unclassif ied All None CellFirmicutes Bacilli Bacillales Bacillaceae Bacillus BC Min HemiFirmicutes Bacilli Bacillales Paenibacillaceae Unclassif ied CA Min HemiFirmicutes Clostridia Clostridiales Clostridiaceae Clostridium TX;CA;BS None LigPlanctomycetes vadinHA49 DH61 Unclassif ied Unclassif ied BC;CA None CellProteobacteria Alphaproteobacteria Caulobacterales Caulobacteraceae Caulobacter BC;CA;BS;TX None AllProteobacteria Alphaproteobacteria Caulobacterales Caulobacteraceae Asticcacaulis All None Hemi;CellProteobacteria Alphaproteobacteria Caulobacterales Caulobacteraceae Unclassif ied All None LigProteobacteria Alphaproteobacteria Caulobacterales Caulobacteraceae Woodsholea BC;CA;TX None LigProteobacteria Alphaproteobacteria Rhizobiales Bradyrhizobiaceae Bosea CA;TX None Cell;LigProteobacteria Alphaproteobacteria Rhizobiales Hyphomicrobiaceae Devosia BC;CA;TX Org Hemi;CellProteobacteria Alphaproteobacteria Rhizobiales Rhizobiaceae Agrobacterium BC;CA None HemiProteobacteria Alphaproteobacteria Rhodobacterales Hyphomonadaceae Oceanicaulis BC;CA;TX None LigProteobacteria Alphaproteobacteria Rhodobacterales Hyphomonadaceae Hyphomonas BC;CA;TX None LigProteobacteria Alphaproteobacteria Rhodobacterales Hyphomonadaceae Henriciella BC;CA;TX None LigProteobacteria Alphaproteobacteria Rhodobacterales Hyphomonadaceae Maricaulis BC;CA;TX None LigProteobacteria Alphaproteobacteria Rhodobacterales Hyphomonadaceae Hirschia BC;CA;TX None LigProteobacteria Alphaproteobacteria Rhodospirillales Rhodospirillaceae Telmatospirillum JP;TX None Cell;LigProteobacteria Alphaproteobacteria Sphingomonadales Erythrobacteraceae Porphyrobacter BC;CA;TX None LigProteobacteria Alphaproteobacteria Sphingomonadales Sphingomonadaceae Unclassif ied CA;BS None Hemi;LigProteobacteria Alphaproteobacteria Sphingomonadales Sphingomonadaceae Zymomonas BC;CA;TX None LigProteobacteria Alphaproteobacteria Sphingomonadales Sphingomonadaceae Citromicrobium BC;CA;TX None LigProteobacteria Alphaproteobacteria Sphingomonadales Sphingomonadaceae Novosphingobium BC;CA;TX None LigProteobacteria Alphaproteobacteria Sphingomonadales Sphingomonadaceae Blastomonas BC;CA;TX None LigProteobacteria Betaproteobacteria Burkholderiales Burkholderiaceae Burkholderia BC;CA;BS;TX None Hemi;CellProteobacteria Betaproteobacteria Burkholderiales Burkholderiaceae Cupriavidus BC;CA;TX Min LigProteobacteria Betaproteobacteria Burkholderiales Comamonadaceae Pelomonas BC;CA;TX None AllProteobacteria Betaproteobacteria Burkholderiales Comamonadaceae Leptothrix All None CellProteobacteria Betaproteobacteria Burkholderiales Comamonadaceae Unclassif ied All None Hemi;CellProteobacteria Betaproteobacteria Burkholderiales Comamonadaceae Variovorax BS;TX None LigProteobacteria Betaproteobacteria Burkholderiales Oxalobacteraceae Unclassif ied CA;JP;TX None CellProteobacteria Betaproteobacteria Burkholderiales Oxalobacteraceae Janthinobacterium All None Hemi;CellProteobacteria Deltaproteobacteria MIZ46 Unclassif ied Unclassif ied BC;CA None Cell Table E.12... continued Phylum Class Order Family Genus EcozonesSoil Assoc.Substr.Proteobacteria Deltaproteobacteria Myxococcales Cystobacteraceae Unclassif ied BS Org LigProteobacteria Deltaproteobacteria Myxococcales Polyangiaceae Unclassif ied BC;BS;JP None CellProteobacteria Gammaproteobacteria Alteromonadales Alteromonadaceae Cellvibrio BC;CA None Hemi;CellProteobacteria* Gammaproteobacteria Cardiobacteriales Cardiobacteriaceae Cardiobacterium BC;CA;TX None LigProteobacteria* Gammaproteobacteria Chromatiales Ectothiorhodospiraceae Ectothiorhodospira CA;BS None LigProteobacteria* Gammaproteobacteria Chromatiales Ectothiorhodospiraceae Nitrococcus BC;CA;TX None LigProteobacteria* Gammaproteobacteria Chromatiales Ectothiorhodospiraceae Alkalilimnicola BC;CA;TX None LigProteobacteria* Gammaproteobacteria Chromatiales Ectothiorhodospiraceae Spiribacter BC;CA;TX None LigProteobacteria* Gammaproteobacteria Chromatiales Ectothiorhodospiraceae Halorhodospira BC;CA;TX None LigProteobacteria Gammaproteobacteria Enterobacteriales Enterobacteriaceae Morganella BC;CA;TX LigProteobacteria Gammaproteobacteria Enterobacteriales Erythrobacteraceae Unclassif ied BC;CA;TX None LigProteobacteria Gammaproteobacteria Nevskiales Sinobacteraceae Nevskia BC;CA;TX None LigProteobacteria* Gammaproteobacteria Nevskiales Sinobacteraceae Hydrocarboniphaga BC;CA;TX None LigProteobacteria* Gammaproteobacteria Nevskiales Sinobacteraceae Solimonas BC;CA;TX None LigProteobacteria Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas BC;CA None HemiProteobacteria Gammaproteobacteria Salinisphaerales Salinisphaeraceae Salinisphaera BC;CA;TX None LigProteobacteria Gammaproteobacteria Thiotrichales Piscirickettsiaceae Unclassif ied CA Min LigProteobacteria* Gammaproteobacteria Xanthomonadales Rhodanobacteraceae Dyella BC;CA;TX None LigProteobacteria* Gammaproteobacteria Xanthomonadales Rhodanobacteraceae Frateuria BC;CA;TX None LigProteobacteria Gammaproteobacteria Xanthomonadales Sinobacteraceae Unclassif ied CA None LigTM7 TM7-3 Unclassif ied Unclassif ied Unclassif ied BC; CA None HemiVerrucomicrobia Opitutae Opitutales Opitutaceae Unclassif ied BC;BS;JP None CellVerrucomicrobia* Unclassif ied Unclassif ied Unclassif ied Unclassif ied BC;CA;BS;JP None CellAscomycota* Dothideomycetes Incertae_sedis Pseudeurotiaceae Pseudogymnoascus BC;CA None CellAscomycota* Leotiomycetes Helotiales Sclerotiniaceae Botrytis CA;BS;JP;TX None CellAscomycota* Orbiliomycetes Orbiliales Orbiliaceae Arthrobotrys CA;TX Org CellAscomycota* Saccharomycetes Saccharomycetales Saccharomycetaceae Unclassif ied CA;BS Min LigAscomycota* Sordariomycetes Glomerellales Plectosphaerellaceae Verticillium CA;BS;JP;TX Org CellAscomycota* Sordariomycetes Hypocreales Hypocreaceae Trichoderma CA;BS;JP;TX Org CellAscomycota* Sordariomycetes Hypocreales Hypocreaceae Hypocrea BC;CA;BS;TX None CellAscomycota* Sordariomycetes Hypocreales Nectriaceae Fusarium CA;BS;JP;TX Org CellAscomycota* Sordariomycetes Hypocreales Ophiocordycipitaceae Ophiocordyceps CA;BS;JP;TX None CellAscomycota* Sordariomycetes Sordariales Chaetomiaceae Chaetomium CA;TX None CellAscomycota* Sordariomycetes Sordariales Chaetomiaceae Humicola CA;TX None CellAscomycota* Sordariomycetes Sordariales Chaetomiaceae Myceliophthora BC;CA;TX Org CellAscomycota* Sordariomycetes Sordariales Sordariaceae Neurospora CA;BS;JP;TX Org CellAscomycota* Sordariomycetes Incertae_sedis Magnaporthaceae Magnaporthe CA;BS;JP;TX Org CellBasidiomycota* Agaricomycetes Agaricales Pleurotaceae Pleurotus BC;CA;BS;JP None CellBasidiomycota* Agaricomycetes Agaricales Psathyrellaceae Coprinopsis BC;CA None CellBasidiomycota* Agaricomycetes Agaricales Schizophyllaceae Schizophyllum BC;CA;TX Org CellBasidiomycota* Agaricomycetes Agaricales Tricholomataceae Laccaria BC;CA None CellBasidiomycota* Agaricomycetes Sebacinales Sebacinales group B Piriformospora BC;CA None CellBasidiomycota* mitosporic Basidiomycota NA NA Trichosporon BC;CA;BS;JP Org CellBasidiomycota* Tremellomycetes Filobasidiales Filobasidiaceae Cryptococcus All Org CellBilateria* Polychaeta Annelida Siboglinidae Osedax BC;CA;TX None LigChordata* Mammalia Bovidae Antilopinae Pantholops BC;CA;TX None Lig Table E.13. Complete list of draft genomes recovered from cellulose and lignin metagenomic libraries from across North America. Bins were made using both 12C and 13C-libraries and, therefore, not all bins correspond to taxa designated as cellulolytic or lignolytic, some correspond to generally abundant taxa. Substr Phylum Order Family Genus Ecozone SoilBin #Total Bases (Mb)Percent ClassifiedCell Acidobacteria Acidobacteriales Acidobacteriaceae Granulicella ON Org 26 0.41 76%Cell Acidobacteria Acidobacteriales Acidobacteriaceae Granulicella ON Org 18 0.25 81%Cell Acidobacteria Acidobacteriales Acidobacteriaceae Unclassif ied ON Org 10 0.36 97%Cell Acidobacteria Acidobacteriales Acidobacteriaceae Granulicella ON Org 38 0.39 92%Cell Acidobacteria Acidobacteriales Acidobacteriaceae Unclassif ied TX Min 34 0.32 75%Cell Acidobacteria Acidobacteriales Acidobacteriaceae Granulicella ON Org 5 0.42 77%Cell Acidobacteria Acidobacteriales Acidobacteriaceae Unclassif ied TX Min 47 0.63 98%Cell Acidobacteria Acidobacteriales Acidobacteriaceae Granulicella ON Org 52 0.35 73%Cell Acidobacteria Acidobacteriales Acidobacteriaceae Granulicella ON Org 9 0.67 69%Cell Acidobacteria Acidobacteriales Acidobacteriaceae Unclassif ied ON Org 13 1.50 98%Cell Acidobacteria Acidobacteriales Acidobacteriaceae Granulicella ON Org 46 6.15 35%Cell Acidobacteria Acidobacteriales Acidobacteriaceae Unclassif ied ON Org 36 1.91 96%Cell Acidobacteria Acidobacteriales Acidobacteriaceae Granulicella ON Org 25 0.32 71%Cell Actinobacteria Corynebacteriales Mycobacteriaceae Mycobacterium ON Min 33 0.20 90%Cell Actinobacteria Corynebacteriales Mycobacteriaceae Mycobacterium ON Org 54 0.56 58%Cell Actinobacteria Corynebacteriales Mycobacteriaceae Mycobacterium ON Min 29 0.19 93%Cell Actinobacteria Corynebacteriales Mycobacteriaceae Mycobacterium ON Org 48 0.66 93%Cell Actinobacteria Micrococcales Microbacteriaceae Leifsonia ON Org 11 1.94 42%Cell Actinobacteria Micrococcales Microbacteriaceae Leifsonia CA Org 27 1.48 26%Cell Actinobacteria Micrococcales Microbacteriaceae Leifsonia CA Org 9 0.47 34%Cell Actinobacteria Micrococcales Microbacteriaceae Leifsonia ON Org 16 0.21 26%Cell Actinobacteria Micrococcales Microbacteriaceae Leifsonia ON Min 15 1.87 52%Cell Actinobacteria Micrococcales Microbacteriaceae Leifsonia CA Min 21 4.45 51%Cell Actinobacteria Micrococcales Microbacteriaceae Leifsonia TX Min 19 0.17 28%Cell Actinobacteria Micrococcales Microbacteriaceae Leifsonia TX Org 31 0.31 32%Cell Actinobacteria Micrococcales Microbacteriaceae Leifsonia BC Min 15 0.08 33%Cell Actinobacteria Micrococcales Microbacteriaceae Microbacterium ON Org 20 0.06 24%Cell Actinobacteria Micrococcales Microbacteriaceae Leifsonia BC Org 7 0.14 24%Cell Actinobacteria Micrococcales Microbacteriaceae Leifsonia TX Org 20 0.37 23%Cell Actinobacteria Micrococcales Micrococcaceae Arthrobacter CA Min 4 2.83 80%Cell Actinobacteria Micrococcales Micrococcaceae Arthrobacter ON Min 22 2.34 79%Cell Actinobacteria Micrococcales Micrococcaceae Arthrobacter TX Min 6 3.82 78%Cell Actinobacteria Propionibacteriales Nocardioidaceae Nocardioides TX Min 29 3.85 43%Cell Actinobacteria Propionibacteriales Nocardioidaceae Nocardioides BC Min 16 1.22 56%Cell Actinobacteria Streptomycetales Streptomycetaceae Streptomyces ON Org 1 1.21 56%Cell Actinobacteria Streptomycetales Streptomycetaceae Streptomyces ON Org 22 0.25 34%Cell Actinobacteria Streptomycetales Streptomycetaceae Streptomyces ON Org 7 0.23 75%Cell Actinobacteria Streptomycetales Streptomycetaceae Streptomyces ON Org 55 0.17 60%Cell Actinobacteria Streptomycetales Streptomycetaceae Streptomyces ON Org 42 0.25 52%Cell Actinobacteria Streptomycetales Streptomycetaceae Streptomyces CA Org 7 0.16 71%Cell Actinobacteria Streptomycetales Streptomycetaceae Streptomyces ON Org 37 0.18 23%Cell Actinobacteria Streptomycetales Streptomycetaceae Streptomyces ON Org 35 2.34 33%Cell Actinobacteria Streptomycetales Streptomycetaceae Streptomyces ON Org 17 6.00 33%Cell Actinobacteria Streptomycetales Streptomycetaceae Streptomyces ON Org 27 1.48 55%Cell Actinobacteria Streptomycetales Streptomycetaceae Streptomyces ON Org 38 0.11 21%Cell Actinobacteria Streptomycetales Streptomycetaceae Streptomyces ON Org 34 0.07 23%Cell Actinobacteria Streptomycetales Streptomycetaceae Streptomyces CA Org 3 2.61 57%Cell Actinobacteria Streptomycetales Streptomycetaceae Streptomyces CA Org 25 0.47 55%Cell Actinobacteria Solirubrobacterales Conexibacteraceae Conexibacter TX Org 39 0.21 33%Cell Actinobacteria Solirubrobacterales Conexibacteraceae Conexibacter ON Org 17 0.09 39%Cell Actinobacteria Solirubrobacterales Conexibacteraceae Conexibacter ON Min 15 1.45 55%Cell Actinobacteria Solirubrobacterales Conexibacteraceae Conexibacter ON Org 35 0.13 61% Substr Phylum Order Family Genus Ecozone SoilBin #Total Bases (Mb)Percent ClassifiedCell Actinobacteria Solirubrobacterales Conexibacteraceae Conexibacter ON Min 22 0.15 52%Cell Actinobacteria Solirubrobacterales Conexibacteraceae Conexibacter TX Min 20 1.59 56%Cell Actinobacteria Solirubrobacterales Conexibacteraceae Conexibacter ON Min 16 1.49 44%Cell Actinobacteria Solirubrobacterales Conexibacteraceae Conexibacter BC Min 17 0.68 46%Cell Actinobacteria Solirubrobacterales Conexibacteraceae Conexibacter ON Org 14 0.06 28%Cell Actinobacteria Solirubrobacterales Conexibacteraceae Conexibacter ON Org 44 0.38 31%Cell Actinobacteria Solirubrobacterales Conexibacteraceae Conexibacter ON Org 26 0.18 46%Cell Actinobacteria Solirubrobacterales Conexibacteraceae Conexibacter BC Org 3 0.28 27%Cell Armatimonadetes Chthonomonadales Chthonomonadaceae Chthonomonas TX Min 25 1.05 23%Cell Bacteroidetes Bacteroidales Bacteroidaceae Bacteroides TX Min 44 0.06 22%Cell Bacteroidetes Cytophagales Cytophagaceae Cytophaga ON Org 21 0.16 32%Cell Bacteroidetes Cytophagales Cytophagaceae Cytophaga TX Org 37 2.70 95%Cell Bacteroidetes Cytophagales Cytophagaceae Cytophaga TX Min 10 0.14 26%Cell Bacteroidetes Cytophagales Cytophagaceae Cytophaga TX Min 12 1.36 38%Cell Bacteroidetes Cytophagales Cytophagaceae Cytophaga ON Org 22 0.26 54%Cell Bacteroidetes Cytophagia Cytophagales Cytophagaceae BC Min 12 0.07 25%Cell Bacteroidetes Sphingobacteriia Sphingobacteriales Sphingobacteriaceae ON Org 24 0.21 63%Cell Chloroflexi Anaerolineales Anaerolineaceae Anaerolinea BC Min 11 0.67 39%Cell Firmicutes Clostridiales Peptococcaceae Unclassif ied ON Org 6 0.29 23%Cell Proteobacteria Caulobacterales Caulobacteraceae Asticcacaulis TX Org 15 0.10 38%Cell Proteobacteria Caulobacterales Caulobacteraceae Unclassif ied TX Min 33 23.30 69%Cell Proteobacteria Caulobacterales Caulobacteraceae Asticcacaulis TX Org 2 0.87 79%Cell Proteobacteria Caulobacterales Caulobacteraceae Caulobacter ON Min 24 0.11 56%Cell Proteobacteria Caulobacterales Caulobacteraceae Asticcacaulis TX Org 17 10.16 54%Cell Proteobacteria Caulobacterales Caulobacteraceae Caulobacter BC Min 2 0.13 36%Cell Proteobacteria Caulobacterales Caulobacteraceae Asticcacaulis CA Min 5 3.55 87%Cell Proteobacteria Caulobacterales Caulobacteraceae Caulobacter BC Min 9 1.49 78%Cell Proteobacteria Caulobacterales Caulobacteraceae Asticcacaulis TX Org 30 1.05 58%Cell Proteobacteria Caulobacterales Caulobacteraceae Caulobacter CA Min 29 2.69 66%Cell Proteobacteria Caulobacterales Caulobacteraceae Asticcacaulis TX Min 15 0.32 55%Cell Proteobacteria Caulobacterales Caulobacteraceae Caulobacter ON Min 11 5.86 50%Cell Proteobacteria Caulobacterales Caulobacteraceae Caulobacter ON Org 45 0.15 54%Cell Proteobacteria Caulobacterales Caulobacteraceae Caulobacter ON Org 28 0.20 73%Cell Proteobacteria Caulobacterales Caulobacteraceae Caulobacter BC Org 15 0.62 74%Cell Proteobacteria Caulobacterales Caulobacteraceae Unclassif ied TX Min 5 0.44 67%Cell Proteobacteria Caulobacterales Caulobacteraceae Caulobacter BC Min 18 1.38 58%Cell Proteobacteria Caulobacterales Caulobacteraceae Asticcacaulis CA Min 12 2.72 87%Cell Proteobacteria Caulobacterales Caulobacteraceae Caulobacter ON Min 9 0.40 23%Cell Proteobacteria Caulobacterales Caulobacteraceae Caulobacter ON Org 10 2.10 48%Cell Proteobacteria Caulobacterales Caulobacteraceae Unclassif ied ON Org 4 0.17 55%Cell Proteobacteria Caulobacterales Caulobacteraceae Asticcacaulis TX Org 29 5.24 80%Cell Proteobacteria Caulobacterales Caulobacteraceae Caulobacter ON Org 19 0.54 38%Cell Proteobacteria Caulobacterales Caulobacteraceae Caulobacter ON Org 2 0.73 57%Cell Proteobacteria Caulobacterales Caulobacteraceae Caulobacter BC Org 4 0.10 40%Cell Proteobacteria Caulobacterales Caulobacteraceae Asticcacaulis BC Min 21 1.06 87%Cell Proteobacteria Caulobacterales Caulobacteraceae Caulobacter ON Min 20 0.17 63%Cell Proteobacteria Caulobacterales Caulobacteraceae Caulobacter ON Org 39 2.24 50%Cell Proteobacteria Caulobacterales Caulobacteraceae Asticcacaulis CA Org 17 2.68 86%Cell Proteobacteria Caulobacterales Caulobacteraceae Asticcacaulis ON Org 11 1.44 68%Cell Proteobacteria Caulobacterales Caulobacteraceae Caulobacter CA Min 28 0.13 41%Cell Proteobacteria Caulobacterales Caulobacteraceae Asticcacaulis CA Org 22 0.18 79%Cell Proteobacteria Caulobacterales Caulobacteraceae Asticcacaulis ON Min 18 1.24 57%Cell Proteobacteria Caulobacterales Caulobacteraceae Caulobacter ON Org 27 2.56 37%Cell Proteobacteria Caulobacterales Caulobacteraceae Asticcacaulis CA Org 1 4.38 94%Cell Proteobacteria Caulobacterales Caulobacteraceae Asticcacaulis BC Org 6 1.25 83%Cell Proteobacteria Caulobacterales Caulobacteraceae Caulobacter BC Min 1 0.28 46%Cell Proteobacteria Caulobacterales Caulobacteraceae Caulobacter ON Min 9 5.47 48%Table E.13... continued Substr Phylum Order Family Genus Ecozone SoilBin #Total Bases (Mb)Percent ClassifiedCell Proteobacteria Caulobacterales Caulobacteraceae Caulobacter ON Org 31 0.80 40%Cell Proteobacteria Caulobacterales Caulobacteraceae Caulobacter ON Min 13 0.19 47%Cell Proteobacteria Caulobacterales Caulobacteraceae Caulobacter CA Org 28 1.57 74%Cell Proteobacteria Caulobacterales Caulobacteraceae Asticcacaulis ON Org 37 0.39 54%Cell Proteobacteria Caulobacterales Caulobacteraceae Caulobacter CA Min 6 3.04 36%Cell Proteobacteria Caulobacterales Caulobacteraceae Asticcacaulis CA Org 19 0.31 74%Cell Proteobacteria Caulobacterales Caulobacteraceae Asticcacaulis TX Min 17 0.38 76%Cell Proteobacteria Caulobacterales Caulobacteraceae Caulobacter ON Min 28 0.22 60%Cell Proteobacteria Rhizobiales Hyphomicrobiaceae Pelagibacterium TX Min 53 0.09 32%Cell Proteobacteria Rhizobiales Hyphomicrobiaceae Pelagibacterium BC Org 18 0.17 40%Cell Proteobacteria Rhizobiales Hyphomicrobiaceae Pelagibacterium BC Org 11 0.18 21%Cell Proteobacteria Rhizobiales Methylobacteriaceae Methylobacterium TX Min 52 0.06 22%Cell Proteobacteria Rhizobiales Phyllobacteriaceae Mesorhizobium CA Org 4 0.08 35%Cell Proteobacteria Rhizobiales Rhizobiaceae Rhizobium CA Org 16 0.05 23%Cell Proteobacteria Rhodospirillales Acetobacteraceae Unclassif ied ON Org 40 1.82 43%Cell Proteobacteria Rhodospirillales Rhodospirillaceae Unclassif ied TX Org 18 0.06 25%Cell Proteobacteria Rhodospirillales Rhodospirillaceae Magnetospirillum TX Org 1 0.54 28%Cell Proteobacteria Rhodospirillales Rhodospirillaceae Azospirillum TX Min 39 0.75 44%Cell Proteobacteria Rhodospirillales Rhodospirillaceae Azospirillum TX Org 23 0.10 42%Cell Proteobacteria Rhodospirillales Rhodospirillaceae Azospirillum TX Org 38 0.15 42%Cell Proteobacteria Sphingomonadales Sphingomonadaceae Sphingomonas TX Min 41 0.32 72%Cell Proteobacteria Sphingomonadales Sphingomonadaceae Unclassif ied TX Org 4 0.23 64%Cell Proteobacteria Sphingomonadales Sphingomonadaceae Sphingomonas CA Org 23 0.34 43%Cell Proteobacteria Sphingomonadales Sphingomonadaceae Novosphingobium ON Min 17 0.32 56%Cell Proteobacteria Sphingomonadales Sphingomonadaceae Sphingomonas CA Org 8 0.23 49%Cell Proteobacteria Sphingomonadales Sphingomonadaceae Sphingomonas TX Min 24 17.47 29%Cell Proteobacteria Sphingomonadales Sphingomonadaceae Sphingomonas CA Min 10 3.05 64%Cell Proteobacteria Sphingomonadales Sphingomonadaceae Sphingomonas TX Org 10 1.19 61%Cell Proteobacteria Burkholderiales Burkholderiaceae Burkholderia ON Org 15 7.52 63%Cell Proteobacteria Burkholderiales Burkholderiaceae Burkholderia ON Org 5 0.57 81%Cell Proteobacteria Burkholderiales Burkholderiaceae Burkholderia TX Org 21 0.05 23%Cell Proteobacteria Burkholderiales Burkholderiaceae Cupriavidus TX Min 38 1.00 56%Cell Proteobacteria Burkholderiales Burkholderiaceae Burkholderia ON Org 43 0.32 98%Cell Proteobacteria Burkholderiales Burkholderiaceae Unclassif ied ON Min 14 1.15 27%Cell Proteobacteria Burkholderiales Burkholderiaceae Unclassif ied ON Min 19 0.17 31%Cell Proteobacteria Burkholderiales Burkholderiaceae Burkholderia TX Min 18 0.15 52%Cell Proteobacteria Burkholderiales Burkholderiaceae Burkholderia ON Org 32 1.11 83%Cell Proteobacteria Burkholderiales Burkholderiaceae Unclassif ied TX Org 16 0.66 24%Cell Proteobacteria Burkholderiales Burkholderiaceae Unclassif ied CA Min 30 0.20 22%Cell Proteobacteria Burkholderiales Burkholderiaceae Burkholderia ON Org 39 7.35 59%Cell Proteobacteria Burkholderiales Burkholderiaceae Cupriavidus TX Min 37 1.16 54%Cell Proteobacteria Burkholderiales Burkholderiaceae Burkholderia ON Org 31 0.10 24%Cell Proteobacteria Burkholderiales Burkholderiaceae Unclassif ied TX Org 11 0.10 20%Cell Proteobacteria Burkholderiales Burkholderiaceae Unclassif ied ON Min 1 0.61 24%Cell Proteobacteria Burkholderiales Comamonadaceae Acidovorax TX Min 50 1.69 23%Cell Proteobacteria Burkholderiales Comamonadaceae Unclassif ied ON Min 2 0.08 30%Cell Proteobacteria Burkholderiales Comamonadaceae Unclassif ied TX Org 24 0.19 23%Cell Proteobacteria Burkholderiales Comamonadaceae Unclassif ied BC Min 4 0.54 23%Cell Proteobacteria Burkholderiales Comamonadaceae Variovorax BC Org 16 0.42 77%Cell Proteobacteria Burkholderiales Comamonadaceae Polaromonas CA Min 23 0.38 78%Cell Proteobacteria Burkholderiales Comamonadaceae Unclassif ied CA Org 2 1.32 22%Cell Proteobacteria Burkholderiales Comamonadaceae Unclassif ied ON Min 10 0.19 34%Cell Proteobacteria Burkholderiales Comamonadaceae Unclassif ied ON Min 14 0.20 25%Cell Proteobacteria Burkholderiales Comamonadaceae Unclassif ied CA Org 10 0.14 20%Cell Proteobacteria Burkholderiales incertae sedis Rubrivivax BC Min 7 0.17 20%Cell Proteobacteria Burkholderiales incertae sedis Rubrivivax ON Org 6 0.06 27%Cell Proteobacteria Burkholderiales incertae sedis Rubrivivax TX Min 13 0.65 48%Table E.13... continued Table E.13... continued Substr Phylum Order Family Genus Ecozone SoilBin #Total Bases (Mb)Percent ClassifiedCell Proteobacteria Burkholderiales Unclassif ied Unclassif ied CA Org 5 0.92 49%Cell Proteobacteria Burkholderiales Unclassif ied Unclassif ied ON Min 1 0.10 50%Cell Proteobacteria Burkholderiales Unclassif ied Unclassif ied TX Min 1 8.20 49%Cell Proteobacteria Burkholderiales Oxalobacteraceae Herbaspirillum ON Org 23 1.63 41%Cell Proteobacteria Burkholderiales Oxalobacteraceae Janthinobacterium BC Min 19 0.23 59%Cell Proteobacteria Burkholderiales Oxalobacteraceae Collimonas ON Min 21 0.19 68%Cell Proteobacteria Burkholderiales Oxalobacteraceae Unclassif ied ON Org 3 0.79 81%Cell Proteobacteria Burkholderiales Oxalobacteraceae Unclassif ied ON Org 40 0.19 70%Cell Proteobacteria Burkholderiales Oxalobacteraceae Herbaspirillum ON Org 23 0.18 30%Cell Proteobacteria Burkholderiales Oxalobacteraceae Unclassif ied CA Min 19 0.48 46%Cell Proteobacteria Burkholderiales Oxalobacteraceae Herbaspirillum ON Org 13 0.22 43%Cell Proteobacteria Burkholderiales Oxalobacteraceae Janthinobacterium ON Min 30 3.20 63%Cell Proteobacteria Burkholderiales Oxalobacteraceae Herbaspirillum ON Org 8 0.33 47%Cell Proteobacteria Burkholderiales Oxalobacteraceae Janthinobacterium ON Min 7 0.39 24%Cell Proteobacteria Burkholderiales Oxalobacteraceae Herbaspirillum ON Min 16 0.14 40%Cell Proteobacteria Burkholderiales Oxalobacteraceae Janthinobacterium CA Org 12 0.54 61%Cell Proteobacteria Burkholderiales Oxalobacteraceae Unclassif ied ON Min 12 7.15 76%Cell Proteobacteria Burkholderiales Oxalobacteraceae Unclassif ied TX Org 34 0.24 33%Cell Proteobacteria Burkholderiales Oxalobacteraceae Janthinobacterium TX Min 49 0.31 62%Cell Proteobacteria Burkholderiales Oxalobacteraceae Unclassif ied CA Min 18 0.90 64%Cell Proteobacteria Burkholderiales Oxalobacteraceae Herbaspirillum ON Org 21 0.08 32%Cell Proteobacteria Myxococcales Myxococcaceae Myxococcus ON Min 21 1.08 24%Cell Proteobacteria Myxococcales Myxococcaceae Myxococcus TX Org 35 0.99 30%Cell Proteobacteria Myxococcales Myxococcaceae Myxococcus TX Min 48 0.40 22%Cell Proteobacteria Myxococcales Polyangiaceae Sorangium BC Min 13 0.87 42%Cell Proteobacteria Myxococcales Polyangiaceae Sorangium TX Min 55 0.40 79%Cell Proteobacteria Myxococcales Polyangiaceae Sorangium CA Org 21 10.44 40%Cell Proteobacteria Myxococcales Polyangiaceae Sorangium TX Org 12 6.12 67%Cell Proteobacteria Myxococcales Polyangiaceae Sorangium TX Org 26 2.02 38%Cell Proteobacteria Myxococcales Polyangiaceae Sorangium BC Org 8 1.80 45%Cell Proteobacteria Myxococcales Polyangiaceae Sorangium TX Org 19 4.08 38%Cell Proteobacteria Myxococcales Polyangiaceae Sorangium CA Min 16 1.39 42%Cell Proteobacteria Myxococcales Polyangiaceae Sorangium BC Min 10 4.07 41%Cell Proteobacteria Myxococcales Polyangiaceae Sorangium TX Min 32 4.23 20%Cell Proteobacteria Myxococcales Polyangiaceae Sorangium ON Min 18 1.12 33%Cell Proteobacteria Myxococcales Sorangiineae Polyangiaceae CA Min 11 0.10 24%Cell Proteobacteria Myxococcales Sorangiineae Polyangiaceae BC Org 14 5.90 76%Cell Proteobacteria Cellvibrionales Cellvibrionaceae Cellvibrio BC Org 9 0.43 61%Cell Proteobacteria Chromatiales Ectothiorhodospiraceae Unclassif ied ON Min 25 0.15 21%Cell Proteobacteria Nevskiales Sinobacteraceae Unclassif ied ON Min 4 0.26 27%Cell Proteobacteria Nevskiales Sinobacteraceae Unclassif ied ON Min 2 0.91 27%Cell Proteobacteria Nevskiales Sinobacteraceae Hydrocarboniphaga ON Min 6 0.05 23%Cell Proteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas CA Org 24 0.08 24%Cell Proteobacteria Xanthomonadales Rhodanobacteraceae Rhodanobacter ON Org 3 0.45 29%Cell Proteobacteria Xanthomonadales Xanthomonadaceae Unclassif ied ON Org 33 0.28 79%Cell Proteobacteria Xanthomonadales Xanthomonadaceae Unclassif ied ON Org 20 0.72 91%Cell Proteobacteria Xanthomonadales Xanthomonadaceae Unclassif ied ON Org 47 2.02 88%Cell Verrucomicrobia Opitutales Opitutaceae Opitutus TX Org 9 2.65 65%Cell Verrucomicrobia Opitutales Opitutaceae Unclassif ied CA Min 13 0.10 30%Cell Verrucomicrobia Opitutales Opitutaceae Unclassif ied BC Org 12 1.91 73%Cell Verrucomicrobia Chthoniobacterales Chthoniobacteraceae Chthoniobacter TX Min 14 0.39 50%Cell Verrucomicrobia Chthoniobacterales Chthoniobacteraceae Chthoniobacter TX Min 8 8.51 30%Cell Verrucomicrobia Chthoniobacterales Chthoniobacteraceae Chthoniobacter TX Min 40 5.71 59%Cell Verrucomicrobia Chthoniobacterales Chthoniobacteraceae Chthoniobacter TX Min 16 1.03 59%Cell Verrucomicrobia Chthoniobacterales Chthoniobacteraceae Chthoniobacter BC Org 13 1.81 65%Cell Verrucomicrobia Chthoniobacterales Chthoniobacteraceae Chthoniobacter TX Min 35 0.25 22%Cell Verrucomicrobia Chthoniobacterales Chthoniobacteraceae Chthoniobacter TX Min 22 4.72 51% Table E.13... continued Substr Phylum Order Family Genus Ecozone SoilBin #Total Bases (Mb)Percent ClassifiedCell Verrucomicrobia Chthoniobacterales Chthoniobacteraceae Chthoniobacter TX Min 11 0.21 46%Cell Verrucomicrobia Chthoniobacterales Chthoniobacteraceae Chthoniobacter CA Min 26 0.75 67%Cell Verrucomicrobia Chthoniobacterales Chthoniobacteraceae Chthoniobacter ON Org 7 0.11 26%Cell Verrucomicrobia Chthoniobacterales Chthoniobacteraceae Chthoniobacter TX Min 43 0.25 70%Cell Verrucomicrobia Methylacidiphilales Methylacidiphilaceae Methylacidiphilum CA Org 13 0.05 21%Cell Verrucomicrobia Methylacidiphilales Methylacidiphilaceae Methylacidiphilum ON Org 53 0.13 20%Cell Verrucomicrobia Methylacidiphilales Methylacidiphilaceae Methylacidiphilum CA Min 3 0.54 26%Cell Verrucomicrobia Verrucomicrobiales Subdivision 3 Pedosphaera ON Org 32 0.24 43%Cell Verrucomicrobia Verrucomicrobiales Subdivision 3 Pedosphaera TX Min 23 0.07 21%Cell Verrucomicrobia Verrucomicrobiales Verrucomicrobiaceae Unclassif ied TX Min 9 4.00 48%Cell Ascomycota incertae sedis Pseudeurotiaceae Pseudogymnoascus CA Min 24 0.56 91%Cell Ascomycota Sordariales Sordariaceae Chaetomium CA Min 8 0.31 25%Cell Ascomycota Sordariales Sordariaceae Chaetomium TX Min 2 0.47 91%Cell Ascomycota Sordariales Sordariaceae Chaetomium CA Min 1 0.14 57%Cell Ascomycota Sordariales Sordariaceae Neurospora ON Org 36 0.23 22%Cell Ascomycota Sordariales Sordariaceae Chaetomium CA Min 17 0.37 21%Cell Ascomycota Sordariales Sordariaceae Chaetomium TX Org 8 0.24 45%Cell Ascomycota Sordariales Sordariaceae Chaetomium TX Org 22 27.82 44%Cell Ascomycota Sordariales Sordariaceae Neurospora TX Org 33 0.39 21%Cell Ascomycota Sordariales Sordariaceae Chaetomium CA Min 9 0.09 36%Cell Ascomycota Sordariales Sordariaceae Chaetomium TX Min 4 18.64 48%Cell Ascomycota Sordariales Sordariaceae Chaetomium TX Min 3 0.16 58%Cell Ascomycota Sordariales Sordariaceae Chaetomium TX Org 6 1.29 48%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied TX Min 28 0.32 53%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied CA Org 6 0.30 90%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Org 9 0.62 79%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied TX Org 5 0.37 96%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Min 23 1.03 76%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Org 30 0.66 97%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Org 50 0.15 62%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied TX Min 7 3.30 100%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Org 2 0.80 25%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied TX Min 27 0.68 91%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Org 34 3.61 91%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Min 32 0.76 76%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied CA Org 18 0.17 43%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied TX Org 28 0.10 22%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Org 12 1.93 78%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied TX Min 54 0.41 91%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Min 25 0.16 77%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied CA Min 14 0.05 20%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Min 8 2.86 99%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied CA Min 2 2.11 55%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Min 1 0.06 28%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Org 14 7.78 88%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Org 49 0.20 94%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied BC Min 20 0.09 38%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Org 25 1.81 95%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Min 12 8.14 96%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied TX Org 7 1.59 99%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Org 29 4.13 91%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Min 7 0.22 99%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied BC Org 5 3.52 97%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Org 18 0.99 99%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Min 24 0.24 71%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied BC Org 10 0.22 62%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Org 15 0.41 58% Table E.13... continued Substr Phylum Order Family Genus Ecozone SoilBin #Total Bases (Mb)Percent ClassifiedCell Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Org 24 0.25 84%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied TX Min 1 4.50 27%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Min 19 1.21 98%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied BC Org 17 0.47 98%Lig Acidobacteria Acidobacteriales Acidobacteriaceae Unclassif ied ON Org 9 0.14 23%Lig Acidobacteria Acidobacteriales Acidobacteriaceae Unclassif ied ON Min 30 0.22 20%Lig Acidobacteria Acidobacteriales Acidobacteriaceae Unclassif ied ON Min 27 0.30 30%Lig Actinobacteria Solirubrobacterales Conexibacteraceae Conexibacter ON Org 13 0.09 34%Lig Actinobacteria Solirubrobacterales Conexibacteraceae Conexibacter CA Min 26 0.37 29%Lig Bacteroidetes Sphingobacteriales Chitinophagaceae Chitinophaga ON Org 3 0.09 29%Lig Bacteroidetes Sphingobacteriales Sphingobacteriaceae Mucilaginibacter ON Org 15 0.17 42%Lig Bacteroidetes Sphingobacteriales Chitinophagaceae Unclassif ied ON Org 10 0.84 57%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter CA Org 3 3.36 47%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter ON Min 32 0.60 37%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter ON Min 33 0.40 44%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter ON Min 14 0.67 26%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter ON Min 19 0.64 36%Lig Proteobacteria Caulobacterales Caulobacteraceae Unclassif ied ON Min 29 0.92 26%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter ON Min 2 2.49 44%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter ON Min 4 6.66 49%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter CA Min 38 0.15 45%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter ON Org 1 4.58 48%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter TX Min 2 0.18 53%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter CA Org 4 0.37 54%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter CA Min 33 0.88 49%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter CA Min 9 1.06 44%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter ON Org 7 2.38 58%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter ON Min 24 1.29 39%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter ON Min 5 1.19 44%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter CA Org 6 1.94 47%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter ON Org 4 0.25 56%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter CA Min 20 0.98 35%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter CA Min 11 1.45 42%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter ON Min 25 0.44 48%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter CA Min 21 0.38 44%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter ON Min 13 0.86 40%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter CA Min 36 0.81 41%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter ON Min 12 3.09 33%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter ON Org 8 2.78 49%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter ON Min 9 0.95 35%Lig Proteobacteria Caulobacterales Caulobacteraceae Unclassif ied ON Min 6 0.76 24%Lig Proteobacteria Rhizobiales Bradyrhizobiaceae Bradyrhizobium CA Org 5 0.10 33%Lig Proteobacteria Burkholderiales Burkholderiaceae Cupriavidus ON Min 35 0.98 50%Lig Proteobacteria Burkholderiales Comamonadaceae Acidovorax CA Org 1 0.08 24%Lig Proteobacteria Burkholderiales Comamonadaceae Unclassif ied ON Org 12 3.72 75%Lig Proteobacteria Burkholderiales Comamonadaceae Acidovorax ON Org 6 0.07 29%Lig Proteobacteria Burkholderiales Comamonadaceae Unclassif ied ON Min 28 0.80 67%Lig Proteobacteria Burkholderiales Comamonadaceae Acidovorax CA Org 7 0.55 24%Lig Proteobacteria Burkholderiales Oxalobacteraceae Collimonas ON Min 18 2.74 46%Lig Proteobacteria Myxococcales Polyangiaceae Sorangium ON Min 11 1.36 30%Lig Parcubacteria Unclassif ied Unclassif ied Unclassif ied ON Min 3 0.38 42%Lig Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Min 16 0.67 49%Lig Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Org 11 0.56 87%Lig Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Org 16 0.62 69%Lig Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Min 34 1.88 46%Lig Unclassif ied Unclassif ied Unclassif ied Unclassif ied CA Min 22 0.15 32%Lig Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Min 26 2.05 64% Table E.13... continued Substr Phylum Order Family Genus Ecozone SoilBin #Total Bases (Mb)Percent ClassifiedLig Unclassif ied Unclassif ied Unclassif ied Unclassif ied CA Org 8 0.41 97%Cell Verrucomicrobia Chthoniobacterales Chthoniobacteraceae Chthoniobacter CA Min 26 0.75 67%Cell Verrucomicrobia Chthoniobacterales Chthoniobacteraceae Chthoniobacter ON Org 7 0.11 26%Cell Verrucomicrobia Chthoniobacterales Chthoniobacteraceae Chthoniobacter TX Min 43 0.25 70%Cell Verrucomicrobia Methylacidiphilales Methylacidiphilaceae Methylacidiphilum CA Org 13 0.05 21%Cell Verrucomicrobia Methylacidiphilales Methylacidiphilaceae Methylacidiphilum ON Org 53 0.13 20%Cell Verrucomicrobia Methylacidiphilales Methylacidiphilaceae Methylacidiphilum CA Min 3 0.54 26%Cell Verrucomicrobia Verrucomicrobiales Subdivision 3 Pedosphaera ON Org 32 0.24 43%Cell Verrucomicrobia Verrucomicrobiales Subdivision 3 Pedosphaera TX Min 23 0.07 21%Cell Verrucomicrobia Verrucomicrobiales Verrucomicrobiaceae Unclassif ied TX Min 9 4.00 48%Cell Ascomycota incertae sedis Pseudeurotiaceae Pseudogymnoascus CA Min 24 0.56 91%Cell Ascomycota Sordariales Sordariaceae Chaetomium CA Min 8 0.31 25%Cell Ascomycota Sordariales Sordariaceae Chaetomium TX Min 2 0.47 91%Cell Ascomycota Sordariales Sordariaceae Chaetomium CA Min 1 0.14 57%Cell Ascomycota Sordariales Sordariaceae Neurospora ON Org 36 0.23 22%Cell Ascomycota Sordariales Sordariaceae Chaetomium CA Min 17 0.37 21%Cell Ascomycota Sordariales Sordariaceae Chaetomium TX Org 8 0.24 45%Cell Ascomycota Sordariales Sordariaceae Chaetomium TX Org 22 27.82 44%Cell Ascomycota Sordariales Sordariaceae Neurospora TX Org 33 0.39 21%Cell Ascomycota Sordariales Sordariaceae Chaetomium CA Min 9 0.09 36%Cell Ascomycota Sordariales Sordariaceae Chaetomium TX Min 4 18.64 48%Cell Ascomycota Sordariales Sordariaceae Chaetomium TX Min 3 0.16 58%Cell Ascomycota Sordariales Sordariaceae Chaetomium TX Org 6 1.29 48%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied TX Min 28 0.32 53%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied CA Org 6 0.30 90%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Org 9 0.62 79%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied TX Org 5 0.37 96%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Min 23 1.03 76%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Org 30 0.66 97%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Org 50 0.15 62%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied TX Min 7 3.30 100%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Org 2 0.80 25%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied TX Min 27 0.68 91%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Org 34 3.61 91%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Min 32 0.76 76%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied CA Org 18 0.17 43%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied TX Org 28 0.10 22%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Org 12 1.93 78%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied TX Min 54 0.41 91%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Min 25 0.16 77%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied CA Min 14 0.05 20%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Min 8 2.86 99%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied CA Min 2 2.11 55%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Min 1 0.06 28%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Org 14 7.78 88%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Org 49 0.20 94%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied BC Min 20 0.09 38%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Org 25 1.81 95%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Min 12 8.14 96%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied TX Org 7 1.59 99%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Org 29 4.13 91%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Min 7 0.22 99%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied BC Org 5 3.52 97%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Org 18 0.99 99%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Min 24 0.24 71%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied BC Org 10 0.22 62%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Org 15 0.41 58% Substr Phylum Order Family Genus Ecozone SoilBin #Total Bases (Mb)Percent ClassifiedCell Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Org 24 0.25 84%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied TX Min 1 4.50 27%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Min 19 1.21 98%Cell Unclassif ied Unclassif ied Unclassif ied Unclassif ied BC Org 17 0.47 98%Lig Acidobacteria Acidobacteriales Acidobacteriaceae Unclassif ied ON Org 9 0.14 23%Lig Acidobacteria Acidobacteriales Acidobacteriaceae Unclassif ied ON Min 30 0.22 20%Lig Acidobacteria Acidobacteriales Acidobacteriaceae Unclassif ied ON Min 27 0.30 30%Lig Actinobacteria Solirubrobacterales Conexibacteraceae Conexibacter ON Org 13 0.09 34%Lig Actinobacteria Solirubrobacterales Conexibacteraceae Conexibacter CA Min 26 0.37 29%Lig Bacteroidetes Sphingobacteriales Chitinophagaceae Chitinophaga ON Org 3 0.09 29%Lig Bacteroidetes Sphingobacteriales Sphingobacteriaceae Mucilaginibacter ON Org 15 0.17 42%Lig Bacteroidetes Sphingobacteriales Chitinophagaceae Unclassif ied ON Org 10 0.84 57%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter CA Org 3 3.36 47%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter ON Min 32 0.60 37%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter ON Min 33 0.40 44%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter ON Min 14 0.67 26%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter ON Min 19 0.64 36%Lig Proteobacteria Caulobacterales Caulobacteraceae Unclassif ied ON Min 29 0.92 26%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter ON Min 2 2.49 44%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter ON Min 4 6.66 49%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter CA Min 38 0.15 45%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter ON Org 1 4.58 48%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter TX Min 2 0.18 53%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter CA Org 4 0.37 54%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter CA Min 33 0.88 49%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter CA Min 9 1.06 44%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter ON Org 7 2.38 58%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter ON Min 24 1.29 39%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter ON Min 5 1.19 44%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter CA Org 6 1.94 47%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter ON Org 4 0.25 56%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter CA Min 20 0.98 35%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter CA Min 11 1.45 42%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter ON Min 25 0.44 48%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter CA Min 21 0.38 44%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter ON Min 13 0.86 40%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter CA Min 36 0.81 41%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter ON Min 12 3.09 33%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter ON Org 8 2.78 49%Lig Proteobacteria Caulobacterales Caulobacteraceae Caulobacter ON Min 9 0.95 35%Lig Proteobacteria Caulobacterales Caulobacteraceae Unclassif ied ON Min 6 0.76 24%Lig Proteobacteria Rhizobiales Bradyrhizobiaceae Bradyrhizobium CA Org 5 0.10 33%Lig Proteobacteria Burkholderiales Burkholderiaceae Cupriavidus ON Min 35 0.98 50%Lig Proteobacteria Burkholderiales Comamonadaceae Acidovorax CA Org 1 0.08 24%Lig Proteobacteria Burkholderiales Comamonadaceae Unclassif ied ON Org 12 3.72 75%Lig Proteobacteria Burkholderiales Comamonadaceae Acidovorax ON Org 6 0.07 29%Lig Proteobacteria Burkholderiales Comamonadaceae Unclassif ied ON Min 28 0.80 67%Lig Proteobacteria Burkholderiales Comamonadaceae Acidovorax CA Org 7 0.55 24%Lig Proteobacteria Burkholderiales Oxalobacteraceae Collimonas ON Min 18 2.74 46%Lig Proteobacteria Myxococcales Polyangiaceae Sorangium ON Min 11 1.36 30%Lig Parcubacteria Unclassif ied Unclassif ied Unclassif ied ON Min 3 0.38 42%Lig Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Min 16 0.67 49%Lig Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Org 11 0.56 87%Lig Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Org 16 0.62 69%Lig Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Min 34 1.88 46%Lig Unclassif ied Unclassif ied Unclassif ied Unclassif ied CA Min 22 0.15 32%Lig Unclassif ied Unclassif ied Unclassif ied Unclassif ied ON Min 26 2.05 64%Lig Unclassif ied Unclassif ied Unclassif ied Unclassif ied CA Org 8 0.41 97%Table E.13... continued Table E.14. List of contigs containing clusters of three or more hits based on BLAST or hmmscan to CAZymes. All CAZyme annotations are putative and have not been validated (i.e. most AA2 hits were to Class II catalase-peroxidases). Taxonomic classification was based on LCA for the full length of the cluster. Partial open-reading frames, as predicted by Prodigal, were not included. The following column names have been abbreviated: ‘ecozone’ (eco.), ‘substrate’ (subs.) and ‘horizon’ (hor.). Some CAZyme clusters may repeat if multiple lignin-modifying genes were present, or if the cluster appeared on multiple contigs within the same library. CAZyme SampleID Source Eco. Subs. Hor. Cazyme Cluster Phylum Order Family Genus Contig Locationdyp2 A8056 Assem. BS Cell M inCBM 50;GH35;GH42;GH42;dyp2;AA3;GT4 Acidobacteria Acidobacteriales uncl. Acidobacteriaceae Acidobacteriaceae scaffo ld-1518 514-18981dyp2 TXA37 Assem. Tex Cell M indyp2;GT2;GT2;GH36;GT4;GT4;GH63;GH19;GH88 Acidobacteria Acidobacteriales uncl. Acidobacteriaceae Acidobacteriaceae k99_542889 4101-94289dyp2 Bin.14 Draft BS Cell M in GH3;GT2;dyp2 Acidobacteria Acidobacteriales uncl. Acidobacteriaceae Acidobacteriaceae k99_414325 2702-32487dyp2 BR_Antib Assem. CA Lig M in CE10;GT4;dyp2;GH74 Actinobacteria Actinomycetales Frankiaceae Frankia scaffo ld-147 1692-17328dyp2 Bin.11 Draft BS Cell Org dyp2;GT2;GT2;AA3;2 Actinobacteria Actinomycetales M icrobacteriaceae Leifsonia k99_262087 4089-13763dyp2 A9086 Assem. BS Cell M in GT2;CBM 2;dyp2 Actinobacteria Actinomycetales M icrobacteriaceae Leifsonia scaffo ld-1717 4036-13615dyp2 Bin.21 Draft CA Cell M in PL9;AA6;dyp2 Actinobacteria Actinomycetales M icrococcaceae Arthrobacter k99_1594532 8107-18322dyp2 DC578 Assem. BC Cell M inGT51;GT30;dyp2;CE1;GH16;CE14 Actinobacteria Actinomycetales M ycobacteriaceae M ycobacterium scaffo ld-4838 1734-32891dyp2 TXA_Antib Assem. Tex Lig M in GT53;CE5;dyp2;CBM 51;CE11 Actinobacteria Actinomycetales Nocardiaceae Nocardia scaffo ld-186 2012-27483dyp2 JS080 Assem. JP Cell M inGH13;26;CBM 48;dyp2;CE4;CE11 Actinobacteria Actinomycetales Streptomycetaceae Kitasatospora scaffo ld-250 1497-23907dyp2 LH020 Assem. CA Cell M in CE14;AA5;dyp2;GH3 Actinobacteria Actinomycetales Streptomycetaceae Streptomyces scaffo ld-488 689-12473dyp2 JS080 Assem. JP Cell M in dyp2;AA5;CE14;GH32 Actinobacteria Actinomycetales Streptomycetaceae Streptomyces scaffo ld-455960 5416-22058dyp2 JS080 Assem. JP Cell M indyp2;GH1;GT5;GT2;CBM 50;CBM 14;GH23;CBM 13 Actinobacteria Actinomycetales Streptomycetaceae Streptomyces scaffo ld-3202 4767-40835dyp2 A8055 Assem. BS Cell Org GH65;GH65;dyp2;GH92 Actinobacteria Actinomycetales Streptomycetaceae Streptomyces scaffo ld-5450 871-14240dyp2 JS080 Assem. JP Cell M in GT51;GH16;dyp2;AA5 Actinobacteria Actinomycetales Streptomycetaceae Streptomyces scaffo ld-1901 5192-25468dyp2 JS080 Assem. JP Cell M in GT51;GT2;dyp2;AA5 Actinobacteria Actinomycetales Streptomycetaceae Streptomyces scaffo ld-457701 4606-18455dyp2 JS080 Assem. JP Cell M in GT51;GT2;dyp2;AA5 Actinobacteria Actinomycetales Streptomycetaceae Streptomyces scaffo ld-448968 9547-23396dyp2 JE121 Assem. JP Cell Org GT41;dyp2;GT4 Proteobacteria Burkholderiales Burkholderiaceae Burkholderia scaffo ld-1555 1675-10729dyp2 JE122 Assem. JP Cell M inCBM 35;GH109;CE11;CBM 48;GT2;GH32;GH32;GH1;CE11;GT2;GH39;GH36;CBM 2;CE1;GH3;GT2;GH65;PL9;4;CE1;CBM 2;GT2;GH128;GT2;GT2;GH3;GT2;GT51;CBM 61;CBM 50;GH35;GH42;dyp2;AA3;GT4;CBM 50;GT2;GH13;26;GT4;CBM 50;GT2;GT51Proteobacteria Burkholderiales Comamonadaceae Acidovorax scaffo ld-798 1799-396092dyp2 TXA37 Assem. Tex Cell M in dyp2;PL1;GT5 Proteobacteria Burkholderiales Comamonadaceae Acidovorax k99_562108 6054-14556dyp2 Bin.12 Draft JP Cell M in dyp2;GT2;CBM 50 Proteobacteria Burkholderiales Oxalobacteraceae Herminiimonas k99_130551 1930-16536dyp2 JE121 Assem. JP Cell OrgCBM 50;GT2;GT80;GT4;CBM50;GT2;dyp2;GT4;GH23 Proteobacteria Burkholderiales Oxalobacteraceae Janthinobacterium scaffo ld-1209578 12648-55728dyp2 TXA37 Assem. Tex Cell M in GH125;GT4;dyp2 Proteobacteria Caulobacterales Caulobacteraceae Asticcacaulis k99_282716 2677-48679dyp2 A7M 1_13C Assem. BS Lig M in CE1;GH16;dyp2;GT4;GH78 Proteobacteria Caulobacterales Caulobacteraceae Caulobacter scaffo ld-895 219-63108dyp2 DC578 Assem. BC Cell M in CE14;dyp2;GT4 Proteobacteria Caulobacterales Caulobacteraceae Caulobacter scaffo ld-191 1176-13442dyp2 OC458 Assem. BC Cell M inGH37;dyp2;GT2;CE1;GH19;GT4;GH13;31 Proteobacteria Caulobacterales Caulobacteraceae Caulobacter scaffo ld-797 2837-70504dyp2 Bin.11 Draft BS Cell M in GT2;dyp2;GH78 Proteobacteria Caulobacterales Caulobacteraceae Caulobacter k99_450390 11800-49618dyp2 A8056 Assem. BS Cell M in GT35;GH78;dyp2;GT2 Proteobacteria Caulobacterales Caulobacteraceae Caulobacter scaffo ld-462 13479-53223dyp2 Bin.21 Draft CA Cell Org dyp2;GH16;CBM 48;CBM 2 Proteobacteria M yxococcales Cystobacteraceae Stigmatella k99_528071 216-12505dyp2 DC578 Assem. BC Cell M in CE2;CBM 13;dyp2 Proteobacteria M yxococcales M yxococcaceae M yxococcus scaffo ld-1088 2732-15238dyp2 A7026 Assem. BS Cell M inCBM 61;CBM 50;GH35;GH42;dyp2;AA3;GT4 Proteobacteria Rhizobiales Rhizobiaceae Rhizobium scaffo ld-256 5796-30437dyp2 BRM 2_13C Assem. CA Lig M in dyp2;AA3;ary.oh.oxi;AA3 Proteobacteria Rhodobacterales Rhodobacteraceae Thalassobacter scaffo ld-1303 5267-10995dyp2 DC578 Assem. BC Cell M in CE10;GT41;dyp2 Proteobacteria Rhodospirillales Rhodospirillaceae Nitrospirillum scaffo ld-954 4536-24275dyp2 Bin.50 Draft Tex Cell M inCBM 13;GT2;CE10;CE1;CE10;GT5;PL1;dyp2 Proteobacteria uncl. Burkholderiales uncl. Rubrivivax k99_734139 11513-35776dyp2 JS080 Assem. JP Cell M in PL9;dyp2;GT2;GH65 uncl. uncl. uncl. uncl. scaffo ld-5687 856-12441laccase Bin.14 Draft BS Cell Org CE10;CBM 2;AA1;GH53 Acidobacteria Acidobacteriales Acidobacteriaceae Candidatus k99_393656 806-22240laccase BRM 2_13C Assem. CA Lig M in AA4;AA1;AA1 Acidobacteria Acidobacteriales Acidobacteriaceae Candidatus scaffo ld-8911 346-5363laccase Bin.14 Draft BS Cell Org GH105;GH109;AA1 Acidobacteria Acidobacteriales uncl. Acidobacteriaceae Acidobacteriaceae k99_1926388 3111-7912laccase Bin.37 Draft CA Lig M in GT4;AA1;GT2;CBM 5;CE1 Acidobacteria Acidobacteriales uncl. Acidobacteriaceae Acidobacteriaceae k99_154957 17646-52187laccase TXA37 Assem. Tex Cell M in GT2;GH73;AA1 Acidobacteria Acidobacteriales uncl. Acidobacteriaceae Acidobacteriaceae k99_433354 1-5823 CAZyme SampleID Source Eco. Subs. Hor. Cazyme Cluster Phylum Order Family Genus Contig Locationlaccase BRO1_13C Assem. CA Lig Org AA1;AA1;sm.lacc Acidobacteria Acidobacteriales uncl. Acidobacteriaceae Acidobacteriaceae scaffo ld-909 66-1735laccase BRM 2_13C Assem. CA Lig M in AA1;sm.lacc;AA1 Acidobacteria Acidobacteriales uncl. Acidobacteriaceae Acidobacteriaceae scaffo ld-6478 1548-3484laccase BRM 3_13C Assem. CA Lig M in AA1;sm.lacc;AA1 Actinobacteria Actinomycetales Frankiaceae Frankia scaffo ld-357 1005-2848laccase BR_Antib Assem. CA Lig M in AA1;lacc;sm.lacc;AA1 Actinobacteria Actinomycetales M ycobacteriaceae M ycobacterium scaffo ld-336 586-2265laccase BRO1_13C Assem. CA Lig Org AA1;AA1;lacc Actinobacteria Actinomycetales M ycobacteriaceae M ycobacterium scaffo ld-1020 498-2270laccase JS080 Assem. JP Cell M in CBM 2;GH92;AA1 Actinobacteria Actinomycetales Streptomycetaceae Kitasatospora scaffo ld-3196 28554-36408laccase Bin.45 Draft Tex Cell M in GT2;AA1;GH18 Bactero idetes Cytophagales Cytophagaceae Emticicia k99_70244 2923-9264laccase OC458 Assem. BC Cell M in GH30;1;GH43;AA1;AA1 Firmicutes Bacillales Paenibacillaceae Paenibacillus scaffo ld-71980 1776-14333laccase Bin.16 Draft Tex Cell M inAA1;GT2;CBM 6;CBM 6;GT4;CBM 50 Planctomycetes Planctomycetales Planctomycetaceae Gemmata k99_772951 690-35445laccase Bin.12 Draft JP Cell M in GH13;GT41;AA1 Proteobacteria Burkholderiales Burkholderiaceae Burkholderia k99_1039102 2419-19963laccase JE121 Assem. JP Cell Org GH65;GT41;AA1 Proteobacteria Burkholderiales Burkholderiaceae Burkholderia scaffo ld-138654 98-16625laccase TXA37 Assem. Tex Cell M in CBM 13;AA1;AA1 Proteobacteria Burkholderiales Burkholderiaceae Burkholderia k99_1267288 765-3222laccase A8055 Assem. BS Cell Org CE16;AA1;AA1 Proteobacteria Burkholderiales Burkholderiaceae Burkholderia scaffo ld-7250 10463-20720laccase A7026 Assem. BS Cell M in cohesin;CBM 35;CBM 5;AA1 Proteobacteria Burkholderiales Comamonadaceae Polaromonas scaffo ld-3510 15182-29445laccase BRM 2_13C Assem. CA Lig M in GH3;GH3;GH15;AA1;lacc;AA1 Proteobacteria Burkholderiales Comamonadaceae Variovorax scaffo ld-10184 7046-29625laccase A7026 Assem. BS Cell M in CE11;GT2;GT2;AA1;AA1 Proteobacteria Burkholderiales Oxalobacteraceae Herminiimonas scaffo ld-349135 1932-10189laccase BRM 3_13C Assem. CA Lig M in GH1;GH1;GH1;AA1;AA1 Proteobacteria Caulobacterales Caulobacteraceae Asticcacaulis scaffo ld-2048 2458-9179laccase A9085 Assem. BS Cell OrgGH27;CE6;GH55;GH97;GH39;GH120;GH11;GH9;GH51;GH43;GH95;GH3;CE6;CBM 13;CE1;GH31;CE10;GH3;GH51;GH36;GH92;AA1;lacc;GH130;GH2;CBM 32;CE1;GH43;GH5;13;CBM 13;GT2Proteobacteria Caulobacterales Caulobacteraceae Asticcacaulis scaffo ld-4490 11105-178981laccase Bin.11 Draft BS Cell M in GT2;GT2;AA1;GH2;GH53 Proteobacteria Caulobacterales Caulobacteraceae Caulobacter k99_630852 5818-25520laccase TXA37 Assem. Tex Cell M in GT51;AA7;AA1;AA1;lacc Proteobacteria Caulobacterales Caulobacteraceae Caulobacter k99_410057 13757-20114laccase A9M 2_13C Assem. BS Lig M in AA1;AA1;lacc Proteobacteria Caulobacterales Caulobacteraceae Caulobacter scaffo ld-1394 3598-5737laccase A8056 Assem. BS Cell M in GT2;GT2;CBM 32;AA1;AA1 Proteobacteria Caulobacterales Caulobacteraceae Caulobacter scaffo ld-109 1830-14549laccase Bin.40 Draft Tex Cell M in CBM 51;AA1;CBM 48 Proteobacteria Chromatiales Ectothiorhodospiraceae Nitrococcus k99_1587968 3187-10845laccase Bin.10 Draft BC Cell M inGH19;GT51;lacc;CBM 56;CBM 2Proteobacteria Desulfobacterales Desulfobacteraceae Desulfobacter k99_2309801 1172-25857laccase BRM 2_13C Assem. CA Lig M in AA1;sm.lacc;AA1;CE11 Proteobacteria Enterobacteriales Enterobacteriaceae Enterobacter scaffo ld-4442 3422-7929laccase A8O2_12C Assem. BS Lig OrgCBM 50;CE14;GT51;GH2;GT2;AA1;AA1Proteobacteria Legionellales Legionellaceae Legionella scaffo ld-17 21640-83058laccase TXA37 Assem. Tex Cell M in AA1;AA1;AA1 Proteobacteria M ethylococcales M ethylococcaceae M ethylobacter k99_802051 248-5945laccase Bin.21 Draft CA Cell Org GH65;GH65;AA1 Proteobacteria M yxococcales Cystobacteraceae Stigmatella k99_710181 1701-11075laccase A8M 3_13C Assem. BS Lig M inCE7;GT2;GT2;GH23;CE14;cohesin;AA1Proteobacteria M yxococcales M yxococcaceae Corallococcus scaffo ld-139 697-30917laccase A8056 Assem. BS Cell M in GT2;CBM 50;AA1 Proteobacteria Pseudomonadales M oraxellaceae Acinetobacter scaffo ld-452078 764-24395laccase LHO3_13C Assem. CA Lig Org AA1;AA1;AA1 Proteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas scaffo ld-563 634-2779laccase A8055 Assem. BS Cell Org CE4;GT41;AA1 Proteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas scaffo ld-156 735-10054laccase Bin.37 Draft CA Lig M in lacc;GH23;CE11;GT41;CBM 2 Proteobacteria Rhizobiales Bradyrhizobiaceae Bradyrhizobium k99_288891 8799-52380laccase TXA37 Assem. Tex Cell M in GT2;GT2;GT4;AA1 Proteobacteria Rhizobiales Bradyrhizobiaceae Bradyrhizobium k99_51393 24292-38289laccase A7M 2_13C Assem. BS Lig M in CBM 32;AA1;AA1 Proteobacteria Rhizobiales M ethylocystaceae M ethylopila scaffo ld-3314 1855-4974laccase Bin.12 Draft JP Cell M in AA1;AA1;lacc Proteobacteria Rhizobiales Rhizobiaceae Sinorhizobium k99_4257 75-2310laccase JW014 Assem. JP Cell M in AA1;AA1;lacc Proteobacteria Rhizobiales Rhizobiaceae Sinorhizobium scaffo ld-5331 1577-3794laccase JE122 Assem. JP Cell M in AA1;AA1;lacc;CBM 16 Proteobacteria Rhizobiales Rhizobiaceae Sinorhizobium scaffo ld-489 75-7513laccase LHO3_13C Assem. CA Lig Org AA1;lacc;AA1;lacc;AA1 Proteobacteria Rhodospirillales Acetobacteraceae Acidiphilium scaffo ld-1142 630-2906laccase A7026 Assem. BS Cell M in AA1;AA1;sm.lacc Proteobacteria Rhodospirillales Acetobacteraceae Gluconacetobacter scaffo ld-1190 2748-4934laccase Bin.39 Draft CA Lig M in GH53;GH53;lacc;GT83 Proteobacteria Xanthomonadales Xanthomonadaceae Dyella k99_91797 848-22665laccase A7O2_13C Assem. BS Lig Org AA1;AA1;AA1 Proteobacteria Xanthomonadales Xanthomonadaceae Rhodanobacter scaffo ld-1779 971-2934laccase A7025 Assem. BS Cell Org CE3;GT1;GH78;AA1 Proteobacteria Xanthomonadales Xanthomonadaceae Rhodanobacter scaffo ld-2524 7368-30232laccase Bin.1 Draft CA Lig M in CBM 35;AA1;AA1 Proteobacteria Xanthomonadales Xanthomonadaceae Xanthomonas k99_696794 721-4014laccase Bin.16 Draft Tex Cell M in lacc;CBM 32;GT51 Verrucomicrobia Chthoniobacterales Chthoniobacteraceae Chthoniobacter k99_44625 581-7869laccase TXA37 Assem. Tex Cell M in CE1;CE1;sm.lacc;sm.lacc Verrucomicrobia Chthoniobacterales Chthoniobacteraceae Chthoniobacter k99_1318568 2262-24587laccase TXA37 Assem. Tex Cell M in GT2;GH8;CBM 51;AA1;AA1 Verrucomicrobia Chthoniobacterales Chthoniobacteraceae Chthoniobacter k99_223923 558-14475laccase TXA37 Assem. Tex Cell M in sm.lacc;CBM 32;GT2 Verrucomicrobia Chthoniobacterales Chthoniobacteraceae Chthoniobacter k99_137018 8120-20693laccase TXA37 Assem. Tex Cell M in GH53;GT35;AA1 Verrucomicrobia Chthoniobacterales Chthoniobacteraceae Chthoniobacter k99_181593 3893-9957laccase Bin.40 Draft Tex Cell M in GH53;GT35;AA1 Verrucomicrobia uncl. Chthoniobacter k99_971100 4879-10943laccase Bin.22 Draft Tex Cell Org AA1;lacc;AA1;3 Ascomycota Pseudogymnoascus Pseudeurotiaceae Pseudogymnoascus k99_1532366 4603-6745laccase JW013 Assem. JP Cell Org AA1;3;AA1;AA1 Ascomycota Onygenales Ajellomycetaceae Blastomyces scaffo ld-56842 290-1929Table E.14... continued CAZyme SampleID Source Eco. Subs. Hor. Cazyme Cluster Phylum Order Family Genus Contig Locationlaccase Bin.22 Draft Tex Cell Org AA1;AA1;3;AA1;3 Ascomycota Onygenales Arthrodermataceae Trichophyton k99_1558275 8285-10049laccase Bin.22 Draft Tex Cell Org CE1;CBM 1;lacc;GH3;GH3 Ascomycota Sordariales Chaetomiaceae Chaetomium k99_824021 7588-29529laccase Bin.22 Draft Tex Cell Org AA1;2;sm.lacc;AA1;2;AA1;2 Ascomycota Sordariales Chaetomiaceae Chaetomium k99_29332 438-2259laccase Bin.22 Draft Tex Cell Org AA1;2;AA1;2;AA1;2 Ascomycota Sordariales Chaetomiaceae Chaetomium k99_110531 1656-2937laccase Bin.22 Draft Tex Cell OrgGH23;AA1;2;AA1;2;AA1;2;AA1;2 Ascomycota Sordariales Chaetomiaceae Chaetomium k99_336935 385-6893laccase Bin.22 Draft Tex Cell Org AA1;2;AA1;2;AA1;2 Ascomycota Sordariales Chaetomiaceae Chaetomium k99_965275 707-1996laccase Bin.22 Draft Tex Cell Org AA1;3;AA1;3;AA1;3 Ascomycota Sordariales Chaetomiaceae Chaetomium k99_349944 1160-2814laccase TXA40 Assem. Tex Cell Org AA1;2;sm.lacc;AA1;2;AA1;2 Ascomycota Sordariales Chaetomiaceae Chaetomium scaffo ld-31345 89-2192laccase TXA40 Assem. Tex Cell Org AA1;2;sm.lacc;AA1;2;AA1;2 Ascomycota Sordariales Chaetomiaceae Chaetomium scaffo ld-20528 397-2009laccase Bin.22 Draft Tex Cell Org AA1;2;AA1;2;AA1;2 Ascomycota Sordariales Chaetomiaceae Thielavia k99_1360305 2801-4831laccase Bin.22 Draft Tex Cell Org AA1;AA1;AA1 Ascomycota Sordariales Chaetomiaceae Thielavia k99_1263514 843-2867laccase TXA40 Assem. Tex Cell Org AA1;AA1;AA1 Ascomycota Sordariales Chaetomiaceae Thielavia scaffo ld-369338 9-2125laccase TXA37 Assem. Tex Cell M in AA1;AA1;AA1 Ascomycota Sordariales Chaetomiaceae Thielavia k99_379059 2446-4578laccase TXA37 Assem. Tex Cell M inAA1;lacc;CBM 2;CBM 2;CBM2;GH55;GH55;CBM 18 Ascomycota Sordariales Chaetomiaceae Thielavia k99_122719 16637-44890laccase Bin.22 Draft Tex Cell OrgAA1;3;AA1;3;AA1;3;AA1;3;AA1;3;AA1;3 Ascomycota Sordariales Sordariaceae Neurospora k99_125672 1667-4748laccase Bin.22 Draft Tex Cell OrgPL1;10;PL1;10;PL1;10;CE5;CE5;AA1;3 Ascomycota Sordariales Sordariaceae Neurospora k99_1445522 2060-31698laccase TXA37 Assem. Tex Cell M in CBM 2;CBM 2;AA1;lacc Ascomycota Sordariales Sordariaceae Neurospora k99_595818 56-9101laccase Bin.22 Draft Tex Cell Org GH43;AA1;3;AA1;3 Ascomycota Sordariales Sordariaceae Sordaria k99_440136 6533-26357laccase Bin.22 Draft Tex Cell OrgGH13;5;GH13;5;GH43;AA1;3;AA1;3;AA1;3 Ascomycota Sordariales Sordariomycetidae M elanocarpus k99_524124 651-8035laccase JW013 Assem. JP Cell Org AA1;AA1;AA1 Ascomycota Xylariales Xylariaceae Daldinia scaffo ld-2085 1312-3222laccase A9085 Assem. BS Cell Org AA1;AA1;AA1;AA1 Ascomycota Xylariales Xylariaceae Daldinia scaffo ld-239 671-3409laccase Bin.9 Draft CA Cell M in AA1;3;AA1;3;AA1;3 uncl. uncl. uncl. uncl. k99_298110 239-2698oxidase A9085 Assem. BS Cell OrgCBM 32;AA3;CBM 18;CBM 50;GH43;GH10;GT2;GT22;GH27;CE10;van.oh.oxi;CE6;CE7;GT9;GH3;GH2;CE1;CE10;CBM 32;GH108;GT2;GT19;GH23;GH23;GT2;CE4;GT41;CE9;GH20;GH1Acidobacteria Acidobacteriales Acidobacteriaceae Granulicella scaffo ld-1955 2623-210198oxidase Bin.12 Draft BS Cell M in GT4;GH92;van.oh.oxi Actinobacteria Actinomycetales M icrobacteriaceae M icrobacterium k99_353450 11026-18644oxidase LH020 Assem. CA Cell M inAA3;GT2;ary.oh.oxi;GT2;GT2;GT2Actinobacteria Actinomycetales M icromonosporaceae M icromonospora scaffo ld-581 1-18361oxidase TXA_Antib Assem. Tex Lig M inGH1;GT9;AA2;GH15;van.oh.oxi;GT2Actinobacteria Actinomycetales M ycobacteriaceae M ycobacterium scaffo ld-2307 1358-70445oxidase TXA_Antib Assem. Tex Lig M inGT8;GH23;GT4;van.oh.oxi;GT2Actinobacteria Actinomycetales Nocardiaceae Nocardia scaffo ld-444 14052-81553oxidase A8M 3_13C Assem. BS Lig M in AA3;2;ary.oh.oxi;AA3;2 Actinobacteria Actinomycetales Pseudonocardiaceae Amycolatopsis scaffo ld-8167 18-1436oxidase A7026 Assem. BS Cell M in GT2;GH33;CBM 32;van.oh.oxi Actinobacteria Actinomycetales Ruaniaceae Ruania scaffo ld-14 4518-16378oxidase Bin.16 Draft JP Cell M in CE1;CBM 50;van.oh.oxi Actinobacteria Solirubrobacterales Conexibacteraceae Conexibacter k99_265676 1245-11720oxidase DC578 Assem. BC Cell M in CE1;CBM 50;van.oh.oxi Actinobacteria Solirubrobacterales Conexibacteraceae Conexibacter scaffo ld-1323143 493-11106oxidase DC578 Assem. BC Cell M inCE1;van.oh.oxi;CBM 32;GT9;GT2;GT2;GT2;GT2;GT2;GT4;GT4;GT2;GT83;GT2;GT2;GT4;CBM 50;GT2;GT2;GT4;GT2;GT4;GT34;GT2;GT4;GT2;GT2;GT32;GT32;GT2;GT2;GT2;GT2;AA11Actinobacteria Solirubrobacterales Conexibacteraceae Conexibacter scaffo ld-4847 11682-96970oxidase TXA37 Assem. Tex Cell M in CBM 50;van.oh.oxi;GT51 Actinobacteria Solirubrobacterales Conexibacteraceae Conexibacter k99_1401118 280-12942oxidase DC578 Assem. BC Cell M in van.oh.oxi;GT9;GT4;GT4 Actinobacteria Solirubrobacterales Patulibacteraceae Patulibacter scaffo ld-11046 27326-68977oxidase A8_Antib Assem. BS Lig M in GH29;CBM 9;ary.oh.oxi Bactero idetes Cytophagales Cyclobacteriaceae M ariniradius scaffo ld-3548 1042-8993oxidase BRO3_13C Assem. CA Lig Org CBM 51;CE1;van.oh.oxi Bactero idetes Cytophagales Cytophagaceae Spirosoma scaffo ld-402 7662-10934oxidase BRO3_13C Assem. CA Lig Org CE9;ary.oh.oxi;CE4;CBM 6 Bactero idetes Sphingobacteriales Chitinophagaceae Segetibacter scaffo ld-765 5327-12507oxidase Bin.11 Draft CA Cell OrgGH2;CE3;CE1;CE10;CE1;van.oh.oxiChloroflexi Ktedonobacterales Ktedonobacteraceae Ktedonobacter k99_271091 144-10487oxidase JS080 Assem. JP Cell M inCBM 14;CE1;GH2;CE3;van.oh.oxi;CE1;CE1Chloroflexi Ktedonobacterales Ktedonobacteraceae Ktedonobacter scaffo ld-3182 2048-25260Table E.14... continued CAZyme SampleID Source Eco. Subs. Hor. Cazyme Cluster Phylum Order Family Genus Contig Locationoxidase BLM 1_13C Assem. CA Lig M in AA3;AA3;ary.oh.oxi Cyanobacteria Nostocales Rivulariaceae Calothrix scaffo ld-406 503-2947oxidase Bin.15 Draft BS Cell Org ary.oh.oxi;GT2;GH16 Proteobacteria Burkholderiales Burkholderiaceae Burkholderia k99_805993 2307-10761oxidase JE121 Assem. JP Cell Org AA3;AA3;ary.oh.oxi Proteobacteria Burkholderiales Burkholderiaceae Burkholderia scaffo ld-2058 15-2128oxidase TXA37 Assem. Tex Cell M in CE10;GH95;CE1;van.oh.oxi Proteobacteria Burkholderiales Burkholderiaceae Burkholderia k99_70196 1142-6851oxidase TXA37 Assem. Tex Cell M in AA4;van.oh.oxi;CBM 32 Proteobacteria Burkholderiales Burkholderiaceae Burkholderia k99_309180 11601-19514oxidase A7O2_13C Assem. BS Lig Org AA4;AA4;van.oh.oxi;AA4 Proteobacteria Burkholderiales Burkholderiaceae Burkholderia scaffo ld-2132 3865-6110oxidase A9085 Assem. BS Cell Org GT4;CE1;AA6;van.oh.oxi Proteobacteria Burkholderiales Burkholderiaceae Burkholderia scaffo ld-109 835-14080oxidase Bin.11 Draft CA Cell Org CE1;CE1;CE1;van.oh.oxi;CE1 Proteobacteria Burkholderiales Burkholderiaceae Cupriavidus k99_127628 5142-13440oxidase A8M 3_13C Assem. BS Lig M in GH39;AA3;2;van.oh.oxi Proteobacteria Burkholderiales Burkholderiaceae Pandoraea scaffo ld-1186 1016-8680oxidase JS080 Assem. JP Cell M in CE1;CE1;CE1;GT2;van.oh.oxi Proteobacteria Burkholderiales Comamonadaceae Acidovorax scaffo ld-72749 3719-22575oxidase JW014 Assem. JP Cell M in AA3;AA3;2;ary.oh.oxi Proteobacteria Burkholderiales Comamonadaceae Acidovorax scaffo ld-2826 2110-3374oxidase A8056 Assem. BS Cell M in CE1;CE1;GT2;van.oh.oxi Proteobacteria Burkholderiales Comamonadaceae Acidovorax scaffo ld-452765 6108-21565oxidase JE122 Assem. JP Cell M inGH18;GT2;GH51;CBM 5;CBM50;GH53;GT4;AA6;van.oh.oxi;GT9;AA1;AA1;GH2;GT2;GT2;GT2;GT2;GT4;GH73;GH53;GT26;CBM 5;CBM 13;CBM 32;GT51;GH28;GT2;CBM 3;GT41;GT4;GT4Proteobacteria Burkholderiales Oxalobacteraceae Collimonas scaffo ld-6 13429-216098oxidase JW014 Assem. JP Cell M in GT51;GT2;ary.oh.oxi;GH109 Proteobacteria Burkholderiales Oxalobacteraceae Duganella scaffo ld-388931 3321-21104oxidase Bin.12 Draft JP Cell M inCE1;GH18;AA7;van.oh.oxi;GH84;GT9Proteobacteria Burkholderiales Oxalobacteraceae Herbaspirillum k99_973203 11698-105574oxidase Bin.12 Draft JP Cell M in GT9;van.oh.oxi;AA6 Proteobacteria Burkholderiales Oxalobacteraceae Herbaspirillum k99_798008 711-4629oxidase JW013 Assem. JP Cell OrgGT2;GH28;CE11;GT4;GT51;GH2;GH3;GH78;GT2;AA6;van.oh.oxi;GT2;GH23;GH39;GT2;GT2;GH17;GH6;CE11;CBM 48;GT2;CE11;GT2;CBM 2;GH2;GT4;AA3;2;GT1;GT1;PL9;2;GT2;GT2;GT2;CBM 50;CBM 50;GH28;GH53Proteobacteria Burkholderiales Oxalobacteraceae Herbaspirillum scaffo ld-843346 13569-320703oxidase BRM 2_13C Assem. CA Lig M inCE1;CE8;PL9;AA3;2;AA3;2;ary.oh.oxiProteobacteria Burkholderiales Oxalobacteraceae Janthinobacterium scaffo ld-156 328-16328oxidase Bin.17 Draft CA Cell Org van.oh.oxi;GH3;GH5;4;GH17 Proteobacteria Caulobacterales Caulobacteraceae Asticcacaulis k99_528430 1228-18527oxidase TXA40 Assem. Tex Cell OrgAA3;GH3;ary.oh.oxi;GT4;CE1;GT19;GT2;GT2;CE16 Proteobacteria Caulobacterales Caulobacteraceae Asticcacaulis scaffo ld-751922 1239-43941oxidase BL043 Assem. CA Cell OrgCBM 35;ary.oh.oxi;GH130;CE12;GH109;CE6 Proteobacteria Caulobacterales Caulobacteraceae Asticcacaulis scaffo ld-217 2874-16284oxidase DC575 Assem. BC Cell OrgCBM 35;ary.oh.oxi;CE12;GH109 Proteobacteria Caulobacterales Caulobacteraceae Asticcacaulis scaffo ld-1120 5835-13449oxidase TXA37_12C Assem. Tex Cell M inCBM 35;ary.oh.oxi;CE12;GH109Proteobacteria Caulobacterales Caulobacteraceae Asticcacaulis scaffo ld-1121 5835-13449oxidase Bin.7 Draft BS Lig Org van.oh.oxi;GT41;CBM 50;GT4 Proteobacteria Caulobacterales Caulobacteraceae Caulobacter k99_17159 219-19680oxidase OC458 Assem. BC Cell M inCBM 51;GT28;GT4;AA7;GT4;GT51;CBM 50;van.oh.oxi;GT2Proteobacteria Caulobacterales Caulobacteraceae Caulobacter scaffo ld-381 7222-62784oxidase A7M 1_13C Assem. BS Lig M in GT26;AA3;ary.oh.oxi;AA3 Proteobacteria Caulobacterales Caulobacteraceae Caulobacter scaffo ld-7 1436-4774oxidase A7M 2_13C Assem. BS Lig M in AA3;ary.oh.oxi;AA3 Proteobacteria Caulobacterales Caulobacteraceae Caulobacter scaffo ld-3812 101-2110oxidase DC578 Assem. BC Cell M in van.oh.oxi;GT2;GT83 Proteobacteria Caulobacterales Caulobacteraceae Phenylobacterium scaffo ld-1323141 2248-13994oxidase TXA37 Assem. Tex Cell M inGT51;GH103;van.oh.oxi;GT41;CE14;CBM 32;GH72;AA3Proteobacteria Chromatiales Ectothiorhodospiraceae Alkalilimnico la k99_1136228 30147-103107oxidase Bin.10 Draft BC Cell M inGT2;GT4;ary.oh.oxi;GT2;GT2;GT4Proteobacteria M yxococcales M yxococcaceae M yxococcus k99_629962 2290-18595oxidase TXA37 Assem. Tex Cell M inGT26;van.oh.oxi;CE11;CBM 13;GH18;GH1 Proteobacteria M yxococcales M yxococcaceae M yxococcus k99_616522 6810-54880oxidase BRM 2_13C Assem. CA Lig M in GH2;GT2;van.oh.oxi;GH109 Proteobacteria Oceanospirillales Halomonadaceae Halomonas scaffo ld-10837 319-11365oxidase Bin.9 Draft BC Cell Org ary.oh.oxi;GH26;GT30;CE1 Proteobacteria Pseudomonadales Pseudomonadaceae Cellvibrio k99_433757 1-11744oxidase BRM 2_13C Assem. CA Lig M in GT4;AA3;ary.oh.oxi Proteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas scaffo ld-8160 5603-9762oxidase TXA37 Assem. Tex Cell M in GT4;van.oh.oxi;CBM 50 Proteobacteria Rhizobiales Bradyrhizobiaceae Bradyrhizobium k99_813141 26128-35395oxidase TXA37 Assem. Tex Cell M inCBM 14;van.oh.oxi;AA4;GT51;CE4Proteobacteria Rhizobiales Bradyrhizobiaceae Bradyrhizobium k99_160060 3195-16649oxidase BRM 2_13C Assem. CA Lig M in van.oh.oxi;CE10;AA2 Proteobacteria Rhizobiales Bradyrhizobiaceae Bradyrhizobium scaffo ld-3102 4263-15793oxidase A7O2_13C Assem. BS Lig Org AA3;2;AA3;2;AA3;2;ary.oh.oxi Proteobacteria Rhizobiales Rhizobiaceae Rhizobium scaffo ld-3261 2368-4695oxidase Bin.1 Draft CA Lig M in GT2;PL1;van.oh.oxi Proteobacteria Rhizobiales Rhodobiaceae Lutibaculum k99_798473 5956-16637Table E.14... continued CAZyme SampleID Source Eco. Subs. Hor. Cazyme Cluster Phylum Order Family Genus Contig Locationoxidase BRO3_13C Assem. CA Lig OrgCE10;GH39;GH3;GH3;van.oh.oxi Proteobacteria Rhizobiales Rhodobiaceae Parvibaculum scaffo ld-1106 4272-10273oxidase TXA37 Assem. Tex Cell M inGT4;GT2;van.oh.oxi;GH31;CBM 13 Proteobacteria Rhizobiales Xanthobacteraceae Starkeya k99_269685 6840-17977oxidase BRM 2_13C Assem. CA Lig M in dyp2;AA3;ary.oh.oxi;AA3 Proteobacteria Rhodobacterales Rhodobacteraceae Thalassobacter scaffo ld-1303 5267-10995oxidase A7M 1_13C Assem. BS Lig M in GH75;van.oh.oxi;GH53 Proteobacteria Rhodospirillales Rhodospirillaceae Azospirillum scaffo ld-353206 1772-12716oxidase TXA37 Assem. Tex Cell M inGT2;GT2;CE11;CBM 13;ary.oh.oxiProteobacteria Sphingomonadales Sphingomonadaceae Blastomonas k99_727174 5169-11347oxidase TXA37 Assem. Tex Cell M in ary.oh.oxi;GH3;AA6;GH92 Proteobacteria Sphingomonadales Sphingomonadaceae Novosphingobium k99_166369 1184-15132oxidase TXA37 Assem. Tex Cell M inGH92;GH109;CBM 35;ary.oh.oxi;GH2 Proteobacteria Sphingomonadales Sphingomonadaceae Novosphingobium k99_248725 1147-22803oxidase A7M 1_13C Assem. BS Lig M in GH2;van.oh.oxi;AA3;2 Proteobacteria Sphingomonadales Sphingomonadaceae Sphingobium scaffo ld-112 11595-36855oxidase A7O1_13C Assem. BS Lig Org AA4;AA4;van.oh.oxi Proteobacteria Sphingomonadales Sphingomonadaceae Sphingobium scaffo ld-693 171-2081oxidase BRM 2_13C Assem. CA Lig M in AA3;2;AA3;2;ary.oh.oxi Proteobacteria Sphingomonadales Sphingomonadaceae Sphingobium scaffo ld-1298 1785-4135oxidase BRM 2_13C Assem. CA Lig M in AA3;2;ary.oh.oxi;AA3;2 Proteobacteria Sphingomonadales Sphingomonadaceae Sphingobium scaffo ld-9300 305-2347oxidase A9M 2_13C Assem. BS Lig M in AA4;AA4;van.oh.oxi Proteobacteria Sphingomonadales Sphingomonadaceae Sphingobium scaffo ld-1897 1174-3131oxidase A9M 2_13C Assem. BS Lig M invan.oh.oxi;AA3;2;AA3;2;ary.oh.oxi;GT9Proteobacteria Sphingomonadales Sphingomonadaceae Sphingobium scaffo ld-1228 674-32478oxidase A9086 Assem. BS Cell M in AA3;AA3;ary.oh.oxi Proteobacteria Sphingomonadales Sphingomonadaceae Sphingobium scaffo ld-574 3027-5011oxidase Bin.7 Draft CA Cell M in GH32;GH109;ary.oh.oxi Proteobacteria Sphingomonadales Sphingomonadaceae Sphingomonas k99_522714 5152-14423oxidase OC458 Assem. BC Cell M inGH74;GH74;GT2;GT2;GT4;GT4;ary.oh.oxiProteobacteria Sphingomonadales Sphingomonadaceae Sphingomonas scaffo ld-1416 962-15150oxidase DC578 Assem. BC Cell M in GT4;GT28;van.oh.oxi;GT41 Proteobacteria Sphingomonadales Sphingomonadaceae Sphingomonas scaffo ld-1845 11006-28720oxidase OC458 Assem. BC Cell M inAA11;CE14;GT51;van.oh.oxi;CBM 13;GT2Proteobacteria uncl. Burkholderiales uncl. Rubrivivax scaffo ld-713 2854-81867oxidase DC578 Assem. BC Cell M inCBM 50;CBM 51;CBM 20;van.oh.oxiProteobacteria Xanthomonadales Xanthomonadaceae Dyella scaffo ld-1306171 2190-24584oxidase BRM 2_13C Assem. CA Lig M in AA3;2;ary.oh.oxi;AA3;2;GT35 Proteobacteria Xanthomonadales Xanthomonadaceae Xanthomonas scaffo ld-11 22109-28583oxidase DC578 Assem. BC Cell M in GT4;GT2;van.oh.oxi;GT83 uncl. Bacteria uncl. uncl. uncl. scaffo ld-1323154 12358-25225oxidase Bin.40 Draft Tex Cell M in CBM 14;GT9;ary.oh.oxi Verrucomicrobia Chthoniobacterales Chthoniobacteraceae Chthoniobacter k99_1017246 3011-9565oxidase Bin.45 Draft Tex Cell M inCBM 27;van.oh.oxi;CBM 32;CBM 48Verrucomicrobia Opitutales uncl. Opitutaceae Opitutaceae k99_116819 2087-13205oxidase TXA37 Assem. Tex Cell M inCBM 32;CBM 32;CBM 35;CBM 13;CBM 26;CBM 40;GH18;GT2;GH97;PL11;2;PL4;1;GH93;GT41;PL8;CBM 47;CBM 47;PL4;1;GH39;van.oh.oxi;GH109;CBM 32;PL11;2;CBM 32;GH38;CBM 32;GT83;CE11;GT2;CBM 6;CBM 62;CBM 62;CBM 62;GH10;GH109;CE1;GH10;GH43;GH25;GT2;GT2;GT2;GT2;GT2;GT2;CBM 66;GH127;CBM 35;CBM 5;GH43;GT2Verrucomicrobia Verrucomicrobiales uncl. Pedosphaera k99_260195 2693-310068oxidase TXA37 Assem. Tex Cell M inGT2;van.oh.oxi;CBM 13;GH13;CE11Verrucomicrobia Verrucomicrobiales Verrucomicrobiaceae Akkermansia k99_193390 10277-48642oxidase TXA37 Assem. Tex Cell M in CBM 48;van.oh.oxi;GT83 Verrucomicrobia Verrucomicrobiales Verrucomicrobiaceae Verrucomicrobium k99_1062264 763-6837oxidase TXA37 Assem. Tex Cell M in PL4;PL11;2;ary.oh.oxi Verrucomicrobia uncl. Chthoniobacter k99_383562 22-13016oxidase TXA37 Assem. Tex Cell M in CBM 32;CBM 6;CBM 6;GT19;van.oh.oxi;GH13;16Verrucomicrobia uncl. Chthoniobacter k99_797249 4272-40194oxidase TXA37 Assem. Tex Cell M in CBM 14;GT9;ary.oh.oxi Verrucomicrobia uncl. Chthoniobacter k99_227527 3011-9565oxidase TXA40 Assem. Tex Cell OrgAA3;2;AA3;2;ary.oh.oxi;AA3;2;AA3;2 Ascomycota Glomerellales Plectosphaerellaceae Verticillium scaffo ld-87 3589-5618oxidase TXA37 Assem. Tex Cell M in AA3;2;AA3;2;AA3;2;ary.oh.oxi Ascomycota Glomerellales Plectosphaerellaceae Verticillium k99_1426652 1842-3647oxidase JW013 Assem. JP Cell Org AA3;2;AA3;2;AA3;2;ary.oh.oxi Ascomycota Hypocreales Hypocreaceae Trichoderma scaffo ld-767073 1-1925oxidase JW013 Assem. JP Cell Org AA3;2;AA3;2;ary.oh.oxi Ascomycota Hypocreales Hypocreaceae Trichoderma scaffo ld-456930 3794-5630oxidase Bin.22 Draft Tex Cell OrgAA4;AA4;van.oh.oxi;AA4;AA4 Ascomycota mitosporic Onygenales Eurotiomycetidae Coccidio ides k99_78246 433-2339Table E.14... continued CAZyme SampleID Source Eco. Subs. Hor. Cazyme Cluster Phylum Order Family Genus Contig Locationoxidase Bin.22 Draft Tex Cell OrgAA3;2;AA3;2;AA3;2;ary.oh.oxi;AA3;2;GH31;GH31 Ascomycota Sordariales Chaetomiaceae Chaetomium k99_469555 2585-14254oxidase TXA37 Assem. Tex Cell M in GH76;van.oh.oxi;GT2 Ascomycota Sordariales Chaetomiaceae Chaetomium k99_1289398 8931-38076oxidase TXA37 Assem. Tex Cell M inGH109;GH51;GH51;GH51;van.oh.oxi Ascomycota Sordariales Chaetomiaceae Thielavia k99_414188 29216-45953peroxi DC578 Assem. BC Cell M inCBM 32;CBM 32;CBM 32;AA2 Actinobacteria Actinomycetales Frankiaceae Frankia scaffo ld-354 70-6228peroxi TXA_Antib Assem. Tex Lig M inGH1;GT9;AA2;GH15;van.oh.oxi;GT2Actinobacteria Actinomycetales M ycobacteriaceae M ycobacterium scaffo ld-2307 1358-70445peroxi TXC148 Assem. Tex Cell Org ver.perox;GH35;GT2 Actinobacteria Actinomycetales Promicromonosporaceae Xylanimonas scaffo ld-103129 410-8446peroxi Bin.1 Draft JP Cell Org GH32;AA2;GT2;GT2;CE4 Actinobacteria Actinomycetales Streptomycetaceae Streptomyces k99_423361 2688-18835peroxi Bin.17 Draft BS Cell Org GH13;26;CBM 48;GH20;AA2 Actinobacteria Actinomycetales Streptomycetaceae Streptomyces k99_178235 3568-13274peroxi BR_Antib Assem. CA Lig M inGT4;GT2;CBM 32;AA2;AA2;CBM 4;CBM 50 Actinobacteria Actinomycetales Streptomycetaceae Streptomyces scaffo ld-179 30319-63022peroxi DC578 Assem. BC Cell M in GT4;AA2;GH2;GH53;CE14 Actinobacteria Actinomycetales Streptomycetaceae Streptomyces scaffo ld-4846 3278-34214peroxi A8M 3_13C Assem. BS Lig M in AA2;AA2;AA2 Actinobacteria Actinomycetales Streptomycetaceae Streptomyces scaffo ld-5768 240-2770peroxi DC578 Assem. BC Cell M inGT83;CE8;GT4;GT2;GT83;AA2;CBM 50 Firmicutes Bacillales Alicyclobacillaceae Alicyclobacillus scaffo ld-5408 172-33467peroxi A7026 Assem. BS Cell M in AA2;CE14;GH65 Proteobacteria Burkholderiales Burkholderiaceae Burkholderia scaffo ld-224 1714-27222peroxi OC458 Assem. BC Cell M in PL11;2;GH128;GH128;AA2 Proteobacteria Burkholderiales Burkholderiaceae Burkholderia scaffo ld-414 4410-16251peroxi JE121 Assem. JP Cell OrgGH28;GT51;CBM 5;AA2;GH3;CBM 53;CE10Proteobacteria Burkholderiales Burkholderiaceae Burkholderia scaffo ld-47 328-75445peroxi A7M 2_13C Assem. BS Lig M in CE1;GH39;CBM 2;AA2 Proteobacteria Burkholderiales Burkholderiaceae Burkholderia scaffo ld-401 777-20133peroxi A8055 Assem. BS Cell Org AA2;GH23;GH23 Proteobacteria Burkholderiales Burkholderiaceae Burkholderia scaffo ld-5535 4597-9679peroxi Bin.11 Draft JP Cell M inCBM 13;CBM 13;CBM 5;GH5;AA2;CE10;GT35;GH78;CBM 50Proteobacteria Burkholderiales Comamonadaceae Polaromonas k99_366491 20251-57297peroxi JS080 Assem. JP Cell M in GH23;AA2;GH12 Proteobacteria Burkholderiales Comamonadaceae Polaromonas scaffo ld-3043 4363-12183peroxi TXA37 Assem. Tex Cell M inAA2;AA2;GH102;CBM 14;GT1;GT4;GT4;GT1;GT1Proteobacteria Burkholderiales Comamonadaceae Polaromonas k99_373252 7468-44019peroxi JW014 Assem. JP Cell M in GH3;GH3;GH78;AA2 Proteobacteria Burkholderiales Comamonadaceae Polaromonas scaffo ld-3189 10878-24752peroxi A8056 Assem. BS Cell M in GT4;GH12;AA2;GH51 Proteobacteria Burkholderiales Comamonadaceae Polaromonas scaffo ld-295 3692-16860peroxi JE122 Assem. JP Cell M inCBM 50;GH78;GT35;CE10;AA2;CBM 13;CBM 13;CBM 5;GH5Proteobacteria Burkholderiales Comamonadaceae Polaromonas scaffo ld-407992 5342-42388peroxi OC458 Assem. BC Cell M inGH92;GH92;AA3;GT2;AA2;CBM 50;CBM 50Proteobacteria Caulobacterales Caulobacteraceae Caulobacter scaffo ld-1346 11375-80365peroxi TXA37 Assem. Tex Cell M inGH3;GT2;GH3;GH78;GT35;AA2;GH43;GH43;GH32Proteobacteria Caulobacterales Caulobacteraceae Caulobacter k99_279297 11487-47415peroxi A9085 Assem. BS Cell OrgGH24;AA2;GH132;CBM 50;GH13;23;CE6;GH4;CE1;GT51;CE1;CBM 50;CBM 18;AA10;CBM 13;GT4;CE1;GT41;GT2;CE6;GT2;GH18;GT41;GT32;GT32;GH28;GT2;GH3;GT4;CBM 57;CE10;GT2;GH29;GH1Proteobacteria Caulobacterales Caulobacteraceae Caulobacter scaffo ld-9 133-263677peroxi BRM 2_13C Assem. CA Lig M in van.oh.oxi;CE10;AA2 Proteobacteria Rhizobiales Bradyrhizobiaceae Bradyrhizobium scaffo ld-3102 4263-15793peroxi TXA_Antib Assem. Tex Lig M in AA3;AA2;AA2 Proteobacteria Rhizobiales Bradyrhizobiaceae Nitrobacter scaffo ld-398 52-5641peroxi TXA37 Assem. Tex Cell M in GT90;AA2;GT4;GH3 Proteobacteria Sphingomonadales Sphingomonadaceae Novosphingobium k99_978139 384-31846peroxi TXA37 Assem. Tex Cell M inGH12;GT51;AA2;AA12;CBM 2;AA9;CE14;GH3Proteobacteria Sphingomonadales Sphingomonadaceae Sphingomonas k99_444936 8022-76017peroxi A9086 Assem. BS Cell M in GH2;AA2;AA2 Proteobacteria Sphingomonadales Sphingomonadaceae Sphingomonas scaffo ld-73 4353-12388peroxi A7M 2_13C Assem. BS Lig M in AA2;AA2;GT2 Proteobacteria Sphingomonadales Sphingomonadaceae Sphingopyxis scaffo ld-810 5285-8158peroxi TXA37 Assem. Tex Cell M inAA2;CBM 32;CBM 50;GH128;PL11;2 Verrucomicrobia Verrucomicrobiales uncl. Pedosphaera k99_680169 1678-32259peroxi Bin.22 Draft Tex Cell Org ver.perox;AA5;1;AA5;1 Ascomycota Glomerellales Plectosphaerellaceae Verticillium k99_231870 2465-4926peroxi JW013 Assem. JP Cell Org GH88;GH28;ver.perox Ascomycota Hypocreales Hypocreaceae Trichoderma scaffo ld-843429 2919-11503peroxi Bin.22 Draft Tex Cell Org GT4;AA2;CBM 50;CBM 50 Ascomycota Sordariales Chaetomiaceae Chaetomium k99_1470342 5281-15115peroxi Bin.22 Draft Tex Cell Org CE10;GT4;CBM 1;AA2;CBM 50;CBM 50 Ascomycota Sordariales Chaetomiaceae Chaetomium k99_414950 20866-38194peroxi TXA37 Assem. Tex Cell M inGH13;40;CBM 50;CBM 50;AA2;GT4;CE10;AA7;GT4;GT4 Ascomycota Sordariales Chaetomiaceae Chaetomium k99_204014 8277-61013peroxi TXA37 Assem. Tex Cell M in AA5;1;AA5;1;AA5;1;AA2 Ascomycota Sordariales Chaetomiaceae Chaetomium k99_253334 1-3086peroxi TXA37 Assem. Tex Cell M in AA2;AA2;AA2 Ascomycota Sordariales Sordariaceae Neurospora k99_638427 491-1782Table E.14... continued