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Removal of soluble selenium in the presence of nitrate from coal mining-influenced water Nkansah-Boadu, Frank 2019

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Removal of Soluble Selenium in the Presence of Nitrate from Coal Mining-Influenced Water   by Frank Nkansah - Boadu BSc., Kwame Nkrumah University of Science and Technology, 2003 MASc., The University of British Columbia, 2013  A DISSERTATION SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF  DOCTOR OF PHILOSOPHY in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Chemical and Biological Engineering)  THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver)   December 2019   © Frank Nkansah - Boadu, 2019     ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the dissertation entitled:  Removal of Soluble Selenium in the Presence of Nitrate from Coal Mining-Influenced Water   submitted by        Frank Nkansah-Boadu  in partial fulfillment of the requirements for the degree of              Doctor of Philosophy In             Chemical and Biological Engineering  Examining Committee: Susan Baldwin, Chemical and Biological Engineering Supervisor  Vikramaditya Yadav, Chemical and Biological Engineering Supervisory Committee Member  Troy Vassos, Adjunct Professor, Civil Engineering Supervisory Committee Member Anthony Lau, Chemical and Biological Engineering University Examiner Scott Dunbar, Mining Engineering University Examiner        iii Abstract Biological treatment to remove dissolved selenium from mining-influenced water (MIW) is inhibited by co-contaminants, especially nitrate. It was hypothesized that selenium reducing microorganisms can be obtained from native mine bacteria at sites affected by MIW due to the selection pressure from elevated selenium concentrations at those sites. Enrichment of these microorganisms and testing of their capacity to remove dissolved selenium from actual coal MIW was the objective of this dissertation. Fifteen sediments were collected from eleven different vegetated or non-vegetated seepage collection ponds and one non-impacted natural wetland. Nine sediments achieved greater than 90% dissolved selenium removal within 72 hours when inoculated into selenate-reducing bacteria growth medium. To find microorganisms capable of removing dissolved selenium in the presence of nitrate, six of the sediments were inoculated into two different types of growth media; one with selenate as the sole electron acceptor and the other with both nitrate and selenate as electron acceptors. Both media were otherwise identical and contained lactate as the electron donor. Decrease in dissolved selenium concentration was observed in all enrichments, but the effect of nitrate on the rate and extent of removal was variable. Nitrate inhibited dissolved selenium removal rates in four of the enrichments. However, in one instance, microorganisms enriched from a natural vegetated marsh receiving coal MIW (Goddard Marsh) were not inhibited by nitrate and the dissolved selenium removal rates were similar in both media. In another instance, the presence of nitrate enhanced dissolved selenium removal by enrichments from a pond receiving coal mine waste seepage (Lagoon A). When enrichments from Lagoon A and Goddard Marsh, respectively, were tested for dissolved selenium removal from actual coal MIW, the former achieved greater (40%) than the latter (10%). Through 16S and whole genome sequencing studies, species capable of removing selenate in the enrichments were classified as Bacteroides, Serratia, Clostridium and Methanosarcina. However, most of these species did not survive in the MIW. The dominant species in the MIW were classified as Sulfurospirillium, Veillonella, Pseudomonas and Bacteroides, which were shown to be capable of reducing selenium, based on putative metagenome assembled genomes (MAGs) obtained for these species.    iv Lay Summary Some mining-influenced water (MIW) contains elevated concentrations of dissolved selenium that could be harmful to downstream ecosystems. Biological treatment to remove dissolved selenium through reduction to insoluble forms is the current preferred method. Its effectiveness is challenged by the presence of competing constituents, especially nitrate, which is a common co-contaminant in MIW because of explosives used in mining. In this dissertation, consortia of bacteria were enriched from different sites impacted by coal mine waste seepage. These enriched bacteria were tested for their capacity to remove dissolved selenium from actual MIW. The study found that, even though bacteria with the capability to remove dissolved selenium survived in the MIW, the extent of dissolved selenium removal was lower in the actual MIW than in the enrichment media. Possibly, other constituents of the MIW negatively affected the selenium reducing bacteria or essential nutrients for these bacteria were missing from the MIW.              v Preface This research project would not have been completed without the invaluable support from my research advisors. The supervisory team greatly assisted in the overall completeness of the research scope, identification of the broad research objectives, examination and interpretation of the data and revisions of the chapters.  The Chapters 2 - 6 have been revised into three manuscripts for publication. The manuscripts prepared for publication have been strengthened by contribution from the supervisory team, Dr. Susan Baldwin, Dr. Troy David Vassos and Dr. Vikramadiyta Yadav. I critically reviewed relevant literature, designed and performed the experiments, conducted laboratory analyses, analyzed the data, organized and presented the results and prepared draft manuscripts. Jon Taylor performed the sequencing of DNA from the early experiments. David Gurr, Ido Hatam and Susan Baldwin performed the bioinformatic analyses of the 16S and whole genome sequencing data.             vi  Table of Contents Abstract……………………………………………………………………………………... iii Lay Summary ………………………………………………………………………………..iv Preface ………………………………………………………………………………………...v Table Contents ………………………………………………………………………………vi List of Tables ………………………………………………………………………………...xi List of Figures ………………………………………………………………………………xiv List of Abbreviations ……………………………………………………………………...xvii Acknowledgements …………………………………………………………………………xx Dedication. …………………………………………………………………………………xxii  Chapter 1 : Introduction ..................................................................................... 1 1.1 Background .................................................................................................. 1 1.2 Research Goal .............................................................................................. 5 1.2.1 Research Questions .....................................................................................................5 1.3 Structure of the Dissertation ......................................................................... 6 1.4 Literature Review ......................................................................................... 7 1.4.1 Selenium Chemistry ....................................................................................................7 1.4.2 Biogeochemical Selenium Cycle .................................................................................9 1.4.3 Selenium Oxyanion Reduction Pathways by Bacteria ................................................ 14 1.4.4 The Effect of Nitrate on  Dissimilatory Selenate Reduction ....................................... 15 1.4.5. Effect of Salinity on Nitrate Reduction and Selenate Reduction ................................ 18 1.4.6 Microbial Species Capable of  Selenium Oxyanion Reduction and the Enzymes involved ............................................................................................................................. 20 1.4.7 Specific Dissimilatory Selenate Reductase Enzyme ................................................... 24   vii 1.4.8: Denitrification Pathway ............................................................................................ 27 1.4.9 Dissimilatory Sulfate Reduction Pathway .................................................................. 29 1.4.10 Bioreactors used for Removal of Dissolved Selenium .............................................. 31 1.4.11 Challenges with using Bioreactors for Removal of Dissolved Selenium from MIW . 35 1.4.12 Sources of Inocula used to Achieve Dissolved Selenium Removal in Bioreactors .... 37 1.4.13 Microbial Diversity in Selenate Reduction Bioreactors ............................................ 39 Chapter 2 : Assessment of  Dissolved Selenium Removal Potential of Mine Site Sediment Bacteria ...............................................................................................41 2.1 Synopsis ......................................................................................................41 2.2 Materials and Methods ................................................................................43 2.2.1 Sites, Sampling and Chemical Characteristics ............................................................ 43 2.2.2 Growth Medium and Culturing .................................................................................. 46 2.3 Results ........................................................................................................48 2.3.1 Sample Location Characteristics ................................................................................ 48 2.3.2 Batch Studies of  Dissolved Selenium Removal ......................................................... 52 2.3.3 Correlation of Dissolved Selenium Removal with Chemical Characteristics .............. 53 2.4 Discussion ...................................................................................................55 2.4.1 Possible Mechanisms for Observed Dissolved Selenium Removal ............................. 55 2.4.2 Performance of the Different Sediments for Dissolved Selenium Removal ................ 57 Chapter 3 : Enriching of Microbial Consortia from Mine- Affected Sediments with the Capacity for Removing Dissolved Selenium .......................................60 3.1 Synopsis ......................................................................................................60 3.2 Materials and Methods ................................................................................61 3.2.1 Enrichment of  Microbial Consortia from Sediments ................................................. 61   viii 3.2.2 Analytical Methods ................................................................................................... 63 3.2.3 DNA Extraction and Illumina Sequencing of 16S rRNA Gene Amplicons. ................ 64 3.2.4 Theoretical Considerations for Selenate Removal through Microbial Reduction ........ 65 3.3 Results ........................................................................................................71 3.3.1 Total Dissolved Selenium Removal in the Presence  and Absence of Nitrate ............. 71 3.3.2 Microbial Community Structure ................................................................................ 79 3.4 Discussion ...................................................................................................89 3.4.1 Removal of Total Dissolved Selenium in the Growth Medium with Selenate as the sole Electron Acceptor .............................................................................................................. 89 3.4.2 Soluble Selenium Reduction in the Presence of Nitrate by Native Microbial Consortia .......................................................................................................................................... 92 Chapter 4 : Removal of Soluble Selenium from Mining-Influenced Water Batch 1 using Selenate-Reducing Bacteria Enriched from Native Mine Site.. 95 4.1 Synopsis ......................................................................................................95 4.2 Materials and Methods ................................................................................96 4.2.1 Batch Sequential Culturing Experiments ................................................................... 96 4.2.2 Analytical Methods ................................................................................................... 98 4.2.3 DNA Extraction and Illumina Sequencing of 16S rRNA Gene Amplicons ................. 99 4.3 Results ...................................................................................................... 100 4.3.1 Chemical Composition of the Coal MIW ................................................................. 100 4.3.2 Total Nitrate plus Nitrite Reduction ......................................................................... 101 4.3.3 Total Dissolved Selenium Removal ......................................................................... 103 4.3.4 Soluble Chemical Oxygen Demand (SCOD) Removal............................................. 105 4.3.5 Microbial Population Compostion in the Cultures .................................................... 109 4.3.6 DNA Concentration ................................................................................................. 116   ix 4.4 Discussion ................................................................................................. 117 Chapter 5 : Removal of Soluble Selenium from Mining-Influenced Water Batch 2 using Enriched Cultured Indigenous Inocula .................................... 122 5.1 Synopsis .................................................................................................... 122 5.2 Materials and Methods .............................................................................. 123 5.2.1 Batch Treatment of Actual MIW 2 .......................................................................... 123 5.2.2 Analytical Methods ................................................................................................. 124 5.3 Results ...................................................................................................... 125 5.3.1 Compositional Characteristics of Coal MIW 1 and 2 ............................................... 125 5.3.2 Total Nitrate plus Nitrite  Removal .......................................................................... 126 5.3.4 Total Dissolved Selenium Removal ......................................................................... 128 5.4 Discussion ................................................................................................. 129 Chapter 6 : Functional Characterization of the Microorganisms in the Enrichment Cultures ........................................................................................ 131 6.1 Synopsis .................................................................................................... 131 6.2 Materials and Methods .............................................................................. 132 6.2.1 Sample Collection ................................................................................................... 132 6.2.2 DNA Extraction and Illumina Metagenomic Sequencing ......................................... 133 6.2.3 Metagenome Assembly and Binning ....................................................................... 133 6.3 Results ...................................................................................................... 136 6.3.1 Number of Reads and Base pairs ............................................................................. 136 6.3.2  Taxonomic Classification of the Bins ..................................................................... 140 6.3.3: Functional Genes Present in Putative Genome Bins ................................................ 147 6.4 Discussion ................................................................................................. 153   x 6.4.1 Microorganisms Capable of Performing Denitrification and or Selenate Reduction . 153 6.4.2 Possible Mechanisms for Selenate Reduction .......................................................... 155 Chapter 7 : Conclusions and Recommendations............................................. 159 7.1 Conclusions............................................................................................... 159 7.2 Recommendations ..................................................................................... 162 References ...................................................................................................... 166 Appendices ..................................................................................................... 184 Appendix A: Standard Procedure for Cultivation of Facultative Anaerobes………...........184   Appendix B: Raw Data.........................................................................................................187                xi List of Tables Table 1.1: List of selenium species commonly found in the environment.....................................8 Table 1.2: Overview of selenium, nitrate and sulfate concentrations in different selenium contaminated waters. .......................................................................................................... 11 Table 1.3: Thermodynamic reduction potentials and standard Gibb’s free energy of anions commonly found in MIW ................................................................................................... 17 Table 1.4: Selenate/selenite-reducing microorganisms ............................................................... 21 Table 1.5: Theoretical calculations of Gibbs free energy for nitrate, sulfate and selenate reduction using lactate as electron donor at pH 7 and concentration of 1M......................................... 30 Table 1.6: Overview of biological treatment processes used for selenate reduction in selenium-contaminated wastewater ................................................................................................... 33 Table 1.7: Advantages and disadvantages of pure and mixed cultures........................................ 38 Table 2.1: Description of sample collection sites ....................................................................... 45 Table 2.2:  Chemical characteristics of sampling location .......................................................... 49 Table 2.3: Chemical characteristics of sampled sediments – Total metals concentration ............ 50 Table 2.4: Spearman’s rank correlation coefficient table for extent of total dissolved selenium removal and chemical charateristics of the sediment sample locations. ............................... 54 Table 3.1: Experimental design for enrichment of selenate-reducing bacteria ............................ 63 Table 3.2: Kinetic parameters for denitrifiers ............................................................................ 70 Table 3.3: Total nitrate plus nitrite and total dissolved selenium removal rate for growth medium with both selenate and nitrate as electron acceptors. ........................................................... 75 Table 3.4: Rate constant (k) and correlation coefficients (r2) of pseudo first order kinetic model for selenate only and selenate plus nitrate enrichments. ...................................................... 79 Table 3.5: Otus dominant in both the selenate only and selenate plus nitrate growth media ....... 88 Table 3.6:  Putative selenate/selenite reducing bacteria present in the enrichments .................... 94 Table 4.1: Experimental design for treatment of actual MIW with enriched mine-affected sediments ........................................................................................................................... 97   xii Table 4.2: Anion and total metal constituents and their concentrations in the coal MIW. ......... 101 Table 4.3: Amount of nitrate and total dissolved Se removed and SCOD consumed for each passage. ........................................................................................................................... 108 Table 4.4: Diversity of the microbial populations at the start of the experiment ....................... 110 Table 4.5: DNA concentration for cultures in each passage ..................................................... 116 Table 5.1: Experimental design ............................................................................................... 124 Table 5.2: Anions and metals composition of MIW 1 and 2..................................................... 126 Table 6.1: Samples used for metagenomic sequencing ............................................................ 132 Table 6.2: Enzymes of interest and the reaction pathways ....................................................... 135 Table 6.3: Total number of reads and base pairs in each metagenome...................................... 138 Table 6.4: Characteristics of draft genomes for Goddard Marsh enrichment culture................. 138 Table 6.5: Characteristics of draft genomes in the nutrient-amended MIW inoculated with Goddard Marsh enrichment. ............................................................................................. 139 Table 6.6: Characteristic of draft genomes in the Lagoon A enrichment culture ....................... 139 Table 6.7: Characteristics of draft genomes for the nutrient-amended MIW inoculated with Lagoon A enrichment. ...................................................................................................... 140 Table 6.8: Phylogenetic analysis for Goddard Marsh enrichment ............................................. 141 Table 6.9: Phylogenetic analysis for Goddard Marsh enrichment inoculated into nutrient - amended MIW. ................................................................................................................ 142 Table 6.10: Phylogenetic analysis for Lagoon A enrichment ................................................... 144 Table 6.11: Phylogenetic analysis for Lagoon A enrichment inoculated into nutrient-amended MIW ................................................................................................................................ 145 Table 6.12: Absence and presence analysis of nitrate, selenate and sulfate reductases enzyme in Goddard Marsh enrichment.. ............................................................................................ 148 Table 6.13: Absence and presence analysis of nitrate, selenate and sulfate reductase enzyme in Goddard Marsh enrichment in amended MIW.. ................................................................ 149 Table 6.14: Absence and presence analysis of nitrate reductase, selenate reductase and sulfate reductase enzyme in Lagoon A enrichment.. .................................................................... 151   xiii Table 6.15: Absence and presence analysis of nitrate reductase, selenate reductase and sulfate reductase enzyme in Lagoon A enrichment inoculated into amended MIW. ..................... 152 Table 6.16: Genomic bins with putative selenate reductase SerA, their taxonomic assignment and whether they were identified in 16S rRNA sequencing for enrichments and nutrient-amended MIW. ................................................................................................................ 155                    xiv List of Figures Figure 1-1: Schematic diagram showing the release of selenium from coal waste and its impact on aquatic environment.. .................................................................................................... 13 Figure 1-2: Simplified diagram for dissimilatory selenate reduction to elemental selenium ....... 24 Figure 1-3:  Schematic diagram showing the enzymes and electron transport pathway for selenate reduction for perisplasmic and membrane bound reductases.. ............................... 26 Figure 1-4:  Schematic diagram showing the steps in dissimilatory nitrate reduction. ................ 27 Figure 1-5:  Schematic diagram showing the steps in dissimilatory sulfate reduction. ................ 29 Figure 2-1: Map showing the location of the sampling sites, Fording River (FRO), Elkview (EVO), and Cardinal River (CRO).. ................................................................................... 44 Figure 2-2: Extents of total dissolved selenium removal after 72 hours measured in sediment slurries inoculated into growth medium. ............................................................................. 52 Figure 3-1a: Total dissolved selenium (blue diamonds and red squares) and nitrate plus nitrite concentrations (mg/L) (green triangles) versus time (in hours) measured in the selenate only (blue diamonds) and selenate plus nitrate growth media (red squares) for sediments sourced from A) Goddard Marsh, B) Bodie Creek, C) Lagoon A, and D) Smithe Pond. .................. 73 Figure 3-1b: Total dissolved selenium (blue diamonds and red squares) and nitrate plus nitrite concentrations (mg/L) (green triangles) versus time (in hours) measured in the selenate only (blue diamonds) and selenate plus nitrate growth media (red squares) for sediments sourced from E) West Jarvis Pond and F) Eagle Pond……………………………………………….......74 Figure 3-2: Total dissolved selenium removal rate in growth medium with both selenate and nitrate as electron acceptors normalized with nitrate plus nitrite reduction rate in selenate and nitrate growth medium. ................................................................................................ 76 Figure 3-3a: First order kinetic model fitted to total dissolved selenium concentration versus time for sediment from A) Goddard Marsh, and B) Bodie Creek, C) Lagoon A, and D) West Jarvis Pond in growth medium with selenate only (dashed line) and growth medium with both selenate and nitrate as electron acceptor (solid line).. .................................................. 77 Figure 3 -3b: First order kinetic model fitted to total dissolved selenium concentration versus time for sediment from E) Eagle Pond in growth medium with selenate only (dashed line) and growth medium with both selenate and nitrate as electron acceptor (solid line). ……...78   xv Figure 3-4: Otu relative abundances in the Goddard Marsh enrichment cultures. Relative abundance is calculated as the number of 16S rRNA reads for each Otu divided by the total number of 16S rRNA reads in each library (or sample).. .................................................... 82 Figure 3-5: Otu relative abundance in Lagoon A enrichment cultures. Relative abundance is calculated as the number of 16S rRNA reads for each Otus divided by the total number of 16S rRNA reads in each sample.. ....................................................................................... 83 Figure 3-6: Otu relative abundance in Smithe Pond enrichment cultures. Relative abundance is calculated as the number of 16S rRNA reads for each Otus divided by the total number of 16S rRNA reads in each sample.. ....................................................................................... 84 Figure 3-7: Otu relative abundance in West Jarvis Pond enrichment cultures. Relative abundance is calculated as the number of 16S rRNA reads for each Otus divided by the total number of 16S rRNA reads in each sample.. ....................................................................................... 85 Figure 3-8: Otu relative abundances in Bodie Creek enrichments. Relative abundance is calculated as the number of 16S rRNA reads for each Otus divided by the total number of 16S rRNA reads in each sample. . ...................................................................................... 86 Figure 3-9: Otu relative abundance in Eagle Pond enrichment cultures. Relative abundance is calculated as the number of 16S rRNA reads for each Otus divided by the total number of 16S rRNA reads in each sample. ........................................................................................ 87 Figure 4-1: Time course of nitrite- + nitrate-N concentrations (mg/L) for the enrichments in nutrient-amended MIW during anoxic incubation for passages 1-5.. ................................. 102 Figure 4-2: Total dissolved Se concentrations (initial and final) for passages 3, 4, and 5 in nutrient-amended MIW. Points represent the mean total dissolved Se measurements in triplicate culture bottles for each treatment.. ..................................................................... 104 Figure 4-3: Time course of SCOD concentration for enrichments in nutrient-amended MIW during anoxic incubation.. ................................................................................................ 106 Figure 4-4: Percentage relative abundance of dominant species (Otus) in the cultures at the beginning (time zero) of the treatment of MIW with Denitrifying Sludge, Goddard Marsh and Lagoon A enrichments. .............................................................................................. 111 Figure 4-5: Dominant Otus in MIW inoculated with Goddard Marsh enrichment for each passage. Percentage read counts was calculated as the number of Otus for that genera divided by total Otus. ....................................................................................................... 113   xvi Figure 4-6: Dominant Otus in in the nutrient-amended MIW inoculated with Lagoon A enrichment. Percentage read counts was calculated as the number of Otus for that genera divided by total Otus.. ...................................................................................................... 114 Figure 4-7:  Dominant Otus in the nutrient-amended MIW inoculated with Denitrifying Sludge. Percentage read counts was calculated as the number of read counts for that Otu divided by total read counts . ............................................................................................................. 115 Figure 5-1: Total nitrate plus nitrite concentration for actual coal MIW using enrichments with both selenate and nitrate as electron acceptors as inoculum for passages 1- 4.. ................. 127 Figure 5-2: Total dissolved selenium concentration for actual coal MIW using enrichments with both selenate and nitrate as electron acceptors as inocula for passages 1- 4.. ..................... 128 Figure 6-1: Nitrate reduction pathways: nitrogen compounds are indicated between arrows, the processes are indicated as arrows and the enzymes next to the arrows. ............................. 135 Figure 6-2: Selenate reduction pathways: selenium compounds are indicated between arrows, the processes are indicated as arrows and the enzymes indicated next to the arrows. .............. 136 Figure 6-3: Sulfate reduction pathways: sulfur compunds are indicated between the arrows, processes are indicated as arrows and the enzymes next to the arrows. ............................. 136      xvii List of Abbreviations  ABBREVIATION MEANING ABMet® Advanced Biological Metal Treatment ABSeR Algal-Bacteria Selenium Removal ADP Adenosine Diphosphate APS Adenosine Phosphosulfate ATP Adenosine Triphosphate BOD Biochemical Oxygen Demand Ca Calcium CCME Canadian Council of Ministers of the Environment CHBE Chemical and Biological Engineering COD Chemical Oxygen Demand CRO Cardinal River Operation DNA                            Deoxyribonucleic Acids DO Dissolved Oxygen DRNA Dissimilatory Reduction of Nitrate to Ammonium EVO Elkview Operation FBR Fluidized Bed Reactor FRO Fording River Operation GE General Electric GM Growth Medium HRT  Hydraulic Retention Time    xviii ABBREVIATION MEANING ICP- MS Inductively Coupled Plasma Mass Spectrophometer MAG Metagenome Assembled Genome MBBR Moving Bed Biofilm Reactor MBfR Membrane Biofilm Reactor mg/L Milligram per Litre µg/l Microgram per Litre MIW Mining-Influenced Water NA Not Available ND Not Determined NSMP Nitrogen and Selenium Management Program OD Optical Density ORP Oxidizing and Reduction Potential Out Operational Taxonomic Unit QCR Quinol Cytochrome c Oxidoreductase SCOD Soluble Chemical Oxygen Demand SeRB Selenium Reducing Bacteria Setot Total Selenium SRB Sulfate Reducing Bacteria SRT Solids Retention Time TDS Total Dissolved Solids TS Total Solids   xix ABBREVIATION MEANING UASB  Upflow Anaerobic Sludge Blanket  UBC  University of British Columbia  USEPA United States Environmental Protection Agency VS  Volatile Solids  WHO  World Health Organization                  xx Acknowledgements I would like to express my heartfelt appreciation to the following people that contributed immensely to the completion of this research work.  My uttermost appreciation goes to the Almighty God for His goodness and mercies, which has sustained me this far. He gave me the life, strength and wisdom to come this far in my academic journey. He lifted me up when I was down. All through the storms of academic life, His love was the anchor that sustained me.    I would also like to extend my heartfelt gratitude to the Chemical and Biological Engineering (CHBE) Department at University of British Columbia (UBC) for organizing this program and supporting me financially. I am especially indebted to my supervisor, Dr Susan Baldwin for admitting me into this program and supporting me throughout the program. My supervisor provided me with immense support, guidance and encouragements which helped me to successfully complete this program but also her mentoring in my life that went far beyond the academic research work. I also like to thank all the professors at the CHBE for the knowledge they imparted to me throughout the period I spent on the program.    I also thank Drs. Vikramadiyta G Yadav and Troy Vassos for their close supervision, guidance, technical support in the set-up, designs and analysis of the experiment, which enabled me to successfully complete this research project on schedule.   I am also indebted to Dr. Ido Hatam, Jon Taylor and David Gurr for their invaluable support in DNA sequences and also providing me with all the necessary resources needed to carry out my experiments.   I thank the staffs at Teck Fording River, Elkview and Cardinal River mines for helping with samples collection and providing background information. Special thanks go to Clememte Miranda from TECK Applied Research and Technology (ART) Department for facilitating my   xxi stay at the Fording River Operations Active Selenium Treatment Plant to gain a deeper appreciation of the pilot treatment system.  Coming this far in my educational journey would not have been possible without the unflinching support of my beloved mother, sisters and friends abroad and back home in Ghana who have always been there for me throughout this long academic journey.  My mother, Elizabeth Ataa Gyaamah sacrificed her comfort of life to bring me this far in my academic journey. Mummy, I say “ayeekoo” I owe all that I am and have to you.   I also thank my church family at Liberty House of Worship, Vancouver, Canada for all the fervent prayers, support and encouragements throughout the duration of the program. I am also grateful to Dr. and Mrs. Sackey for accepting me to be part of their family and helping me to settle down when I first moved to Canada in 2011, their invaluable advice, encouragements and guidance throughout the period I lived with them is very commendable.                  Dedication    xxii      To my mother    1 Chapter 1 : Introduction  1.1 Background Selenium is a naturally occurring element in the Earth’s crust, which can substitute for sulfur due to its similar chemical properties. Selenium is present in some coal seams, where it substitutes for sulfur in metal sulfides coexisting with the coal (Hendry et al., 2015) or is chemically bound with the carbonaeous material in the coal (Lussier et al., 2003). Operations from open-pit coal mining can generate neutral pH mining-influenced water (MIW), which contains elevated concentrations of constituents such as sulfate, nitrate, trace metals and metalloids, such as selenium in some instances. Selenium, which typically occurs at concentrations lower than those of nitrate and sulfate in this complex MIW is a constituent of concern as it can have a disproportionate effect on receiving environments due to its extreme toxicity. In Canada, over the past several years, dissolved selenium levels in water bodies located downstream of coal mines located in the Elk Valley, for example, have been increasing over time. According to a report by the mining company, Teck Coal Ltd., since the 1990’s, selenium levels in the Elk and Fording rivers located downstream of the coal mines have increased to about 50 times the background concentration (Teck, 2013).  When selenium is oxidized through exposure to air and water, it exists as oxyanions; selenate (SeO42-) or selenite (SeO32-) depending on the level of oxidation, and these species constitute the bioavailable (and thereby the most toxic) forms of selenium. Bioavailable selenium can bio-accumulate in aquatic organisms with the potential to bio-magnify up the food chain. For example, lethal and teratogenic effects of selenium in waterfowl (Ohlendorf et al., 1986) were attributed to selenium bioaccumulation in aquatic life in the San Joaquin Valley, Western United States (Lemly et al., 1985).    2 Not only is selenium a threat to the environment at coal mines in British Columbia, Canada, it is also a challenge in many other parts of the world and for a wide range of industries. For instance, metal mining (e.g. gold and zinc) is also associated with elevated selenium concentrations in their effluents (Khamkhash et al., 2017). In other parts of the world, selenium contamination resulting in serious negative impacts to aquatic life have been reported in many countries, such as China, Australia, Japan, South Africa, Russia, Argentina and France. This is as a result of activities conducted by a wide variety of industries such as mining (coal, hard rock, uranium, phosphate), power generation (coal-fired power plants, oil refineries) and also agriculture (CH2M HILL, 2010; Lemly, 2004). In many of these places, biological treatment processes have been implemented to remove selenium from their wastewater. However, there is a wide range of methods for selenium removal reviewed by CH2M HILL, (2010).  The removal of dissolved selenium compounds from some coal MIW is particularly challenging when: 1) dissolved selenium occurs at relatively dilute concentrations (for example, less than 1 mg/L) and must be removed to much lower concentrations (below ~1 µg/L in Canada, for instance), (CCME, 2009), 2) it has a complex chemistry due to the possibility that it exists in several oxidation states, and 3) other contaminants in the MIW, such as nitrate and sulfate, occur at concentrations much higher than those for dissolved selenium and thereby interfere with its removal.  Dissimilatory reduction of soluble selenium oxyanions, the most common forms of dissolved selenium found in coal MIW, to the less soluble elemental selenium through microbial biochemical metabolic pathways constitutes a promising approach to removal of dissolved selenium from coal MIW (Tan et al., 2016; Nanchariah and Lens, 2015; Lenz and Lens, 2009). Some laboratory-scale and pilot-scale biological systems have been developed using pure cultures, anaerobic sludge or anaerobic sludge with added pure culture as inoculum to remove selenium from a variety of selenium-contaminated waste waters (Ji and Wang, 2015; Satoshi et al., 2012; Lenz et al., 2008a; Cantafio et al., 1996). In some microbial metabolisms, selenium oxyanions serve as terminal electron acceptors for anoxic microbial respiration, which contributes to the natural biogeochemical cycling of selenium in aquatic environments (Maiers et al., 1988).   3 Denitrifying microorganisms are commonly used for the removal of soluble selenium in the presence of nitrate in MIW because of the ability of denitrifying microorganisms to reduce selenate as well as nitrate (Rege et al., 1999; Steinberg et al., 1992). However, it has been found that denitrifying reductases have a higher preference for nitrate compared to selenate when both substrates are present.  For example, Sabaty et al., (2001) reported that the substrate affinity constant (KM) of nitrate reductase for selenate was 140 fold lower than for nitrate. Watts et al., (2005) reported that the specific activities of nitrate reductase for selenate reduction are between 15 - 518 times lower.  Additionally, Lai et al., (2014) reported that, the presence of nitrate re-modeled the microbial community in a hydrogen-based biofilm reactor and in subsequent stages, the ability of the microbial community to reduce soluble selenium was diminished. Rege et al., (1999) reported that denitrifying microorganisms were able to remove selenate but only after a lag period of about 150 hours. All these observations point to the fact that nitrate reductase enzymes of denitrifying microorganisms cannot effectively catalyze the reduction of trace levels of soluble selenium oxyanions in the presence of much higher nitrate concentrations normally present in MIW. Thus, there is much motivation in the industrial wastewater treatment field to find microorganisms with enzymes that have a high degree of specificity for dissolved selenium compounds such as selenate and selenite.  Dissimilatory selenate reduction to elemental selenium in diverse natural anoxic sediments has been widely investigated and cultures of dissimilatory selenate reducers have been isolated from these sediments having different physical and chemical properties (Zhang et al., 2008; Siddique et al., 2007, 2006; Knotek-Smith et al., 2006; Ike et al., 1999). Oremland et al., (1989) and Zehr and Oremland, (1987) reported that dissimilatory nitrate and selenate reduction proceeded by similar mechanisms in the surficial sediment whilst sulfate reduction occurred at greater sediment depths. Therefore, it is possible theoretically to achieve selenate reduction without interference from sulfate if the redox potential is managed. Since nitrate and selenium reduction occur within the similar redox zones of natural sediments, there might exist within these sediments, microorganisms with a high specificity towards selenium oxyanions depending on the redox condition within the sediment environment. If this was the case, then it may be   4 possible to reduce selenium oxyanions without inhibition by nitrate if such microorganisms are enriched and used for removal of dissolved selenium from MIW. Indeed, Oremland et al., (1999) reported that the species Sulfurospirillum barnesii originally isolated from a selenium-contaminated fresh water marsh in Neveda could simultaneously reduce both selenate and nitrate. Other microorganisms isolated from natural sediments and grown as pure cultures that have been found to be capable of removing soluble selenium oxyanions without inhibition from interfering anions include; Thauera selenatis (Decker and Macy, 1993), Enterobacter taylorae (Zhang et al., 2007), Rhizobium sp. (Hunter and Kuykendall, 2007), Azospira oryzene (Hunter, 2007) and Bacillus sp. (Fujita et al., 2002). To use these pure cultures in MIW treatment, the challenge will be to maintain them in the bioreactors throughout the treatment process as they may be easily outcompeted by other microbial species entering with the feedwater (El Fantroussi and Agathos, 2005). One strategy to overcome this was tested in a laboratory study by Lenz et al., (2009) where selenate-reducing bacteria (Sulfurospirillum barnesii) were retained inside the bioreactor through immobilization in polyacrylamide gel beads. Another strategy would be to leverage the capability of the native microorganisms that already inhabit the selenium, nitrate and sulfate concentrated seeps on the mine site. Since these organisms would be already adapted to the MIW, there might be a greater chance of successfully maintaining them in bioreactors treating the MIW. In contrast to the work done on natural sediments, very few studies have been done characterizing microbial consortia capable of reducing selenium on coal mine sites. A research program in partnership with the mining company, Teck Metals Ltd., was established in the Department of Chemical and Biological Engineering at the University of British Columbia to investigate the potential of using native bacteria sourced from coal mine sediments for removal of dissolved selenium from MIW in various types of bioreactors. Baldwin and Hodaly, (2003), studied selenium uptake by organic-rich sediments sourced from a coal mine-affected marsh and found that selenite but not selenate was adsorbed onto the wetland sediments in the short term and that both selenite and selenate were removed from the aqueous phase over the long term. Subedi et al., (2017) enriched selenium reducing bacteria from a coal mine site in the Elk Valley that   5 were capable of removing selenate and nitrate simultaneously. Liu et al. (2018) enriched for sulfate-reducing bacteria from a coal mine site that were capable of removing selenate and nitrate from a concentrated reverse osmosis brine. The work in this thesis expands up on these previous studies.  The hypothesis of this thesis is that aquatic sediments affected by seepage with high concentrations of selenium provide suitable locations to source microbial consortia that can be used to remove dissolved selenium from MIW containing nitrate. Candidate microbial consortia for testing were enriched from fifteen different aquatic sediment environments including marshes, creeks, tailing ponds (active and inactive) and pristine wetlands located on three different coal mines using two types of growth media; one with selenate as the only terminal electron acceptor and the other with both selenate and nitrate as terminal electron acceptors. Enrichments that demonstrated the capability of removing dissolved selenium without inhibition from nitrate were then tested for removal of dissolved selenium from actual coal MIW that came from one of the same mine sites as those that were sampled. This work provides new information on which sediments and bacteria sourced from different aquatic environments on a coal mine site can be used for treating coal MIW. Also, this work provides new information about the selenate-reducing microbial species within these consortia and the putative pathways by which they might be reducing selenate.  1.2 Research Goal To select and test microbial consortia from coal mine-affected sediments for their capability to remove total dissolved selenium in the presence of nitrate from coal MIW. 1.2.1 Research Questions The research questions were 1. Which sediments sourced from different aquatic environments on coal mine sites have microorganisms with the capability of removing selenium from the aqueous (soluble) phase?   6 2. How does the presence of nitrate affect the ability of selenium-reducing microorganisms enriched from these sediments to remove total dissolved selenium under optimum growth conditions? 3. Which microorganisms were responsible for removal of total dissolved selenium in the enriched sediments? 4. Were the enrichment cultures that demonstrated total dissolved selenium removal without inhibition from nitrate capable of removing total dissolved selenium from actual coal MIW contaminated with selenate and nitrate? 5. What was the metabolic potential of the microorganisms growing in the enrichment growth media and in the actual coal MIW inoculated with enriched microorganisms and which of these microorganisms had the metabolic potential for selenium oxyanions reduction?    1.3 Structure of the Dissertation The structure of this dissertation follows the research objectives, and consists of seven chapters:   Chapter 1 presents background to the research problem and the key questions as well as a review of relevant literature on selenium chemistry, selenium removal technologies and pathways for microbial selenium oxyanion reduction. A critical review of previous research on challenges associated with treatment of Se containing wastewater is presented as well.  Chapter 2 reports on the screening of coal mine-affected sediments from several seep collection ponds for their potential to remove total dissolved selenium. (Research Question 1)  Chapter 3 reports on the enrichment of selenate-reducing bacteria from selected sediments in two different types of growth media to select for microbial consortia that can remove soluble selenium without inhibition from nitrate. (Research Questions 2 & 3)   7  Chapters 4 and 5 report on the removal of soluble selenium from two batches of actual coal MIW collected from the same source but with different total dissolved solids concentrations. (Research Question 4)   Chapter 6 reports on a metagenomics study of the microbial community composition and function of the selected enrichment cultures and how this evolved when those enrichment cultures were used to treat actual coal MIW. (Research Question 5)  Chapter 7 presents the dissertation conclusions and recommendations for future work.   1.4 Literature Review 1.4.1 Selenium Chemistry Selenium is a member of group 16 (Chalcogen group) of the periodic table along with oxygen, sulfur, tellurium and polonium and is situated between sulfur and tellurium. It thus displays similarity in chemical behavior to sulfur. Selenium has been classified as metalloid because of having properties of both a metal and non-metal. Selenium exists in several oxidation states +6, +4, 0 and −2 and is available in both organic and inorganic forms, and in solid, liquid and gas phases. The element occurs as six stable isotopes, 74Se, 76Se, 77Se, 78Se, 80Se and 82Se, of which 80Se and 78Se are the most abundant forms on Earth (Nancharaiah and Lens, 2015). Selenium oxyanions (SeO42− and SeO32− ), which constitute the soluble, stable and mobile forms of selenium, are formed upon exposure to oxygen in an environment such as surface waters (Dungan and Frankenberger, 1999). The elemental form of selenium is formed in more reducing environments. Thus, redox conditions govern the formation of different species of selenium in the environment (Table 1.1).         8 Table 1.1: List of selenium species commonly found in the environment modified from (Tan et al., 2016; Fernandez-Martinez and Charet, 2009).  Species Oxidation state Occurrence Selenate (SeO42-) HSeO4-, H2SeO4 +VI Common form of Se in surface water. Very soluble in water (Ksp for sodium selenate, 58.5 g /100 g H2O at 25oC) (Lide, 2007) Selenite (SeO32-)  Hydrogen selenite Selenous acid +IV Soluble, found in mildly oxidizing environment (Ralston et al., 2008) Easily adsorbed or sorbed onto mineral surfaces e.g. iron hydro (oxide) minerals (Zhang and Moore, 1997; White and Dubrovsky, 1994) Elemental (Se) 0 Insoluble, fairly stable, unweathered mineral form of Se. Formed from biological reduction of selenate/selenite or oxidation of H2Se Selenide (S2-) Inorganic selenide  Hydrogen selenide Organic selenide Volatile organic selenide: Dimethyl selenide Dimethyl diselenide Dimethyl selenosulfide Biochemical intermediates        -II Found in reducing environment. sorbed onto soil / minerals. e.g ferrilite (FeSe2), Chalcopyrite (Cu FeSe2) Unstable highly toxic gas  Gas, volatilization from soil/sediment bacteria and plants  Many forms, but most common ones are the amino acids, selemethionine (SeMet) and selenocysteine (SeCys)          9 Because selenium has similar chemical properties as sulfur, it can substitute for / or interact with sulfur in several biochemical and mineralogical reaction processes (Navarro-Alarcon and Cabrera-Vique, 2008; Lussier et al., 2003). Regarding mineralogical forms, selenium is often found associated with natural sulfide minerals such as pyrite (FeS2), chalcopyrite (CuFeS2) and sphalerite (ZnS) mainly in trace amounts (Lenz and Lens, 2009). In biochemical compounds, selenium can substitute for sulfur in sulfur containing proteins. As well, selenium is an essential trace element for most living organisms as small amounts are required to synthesize the amino acid selenocysteine that is present in a few selenoproteins. Selenium has a complex chemistry with the elemental selenium occurring in three allotropic forms, metallic, crystalline and amorphous.  Elemental selenium is considered the biologically unavailable form in the natural environment due to its low solubility. However, colloidal forms of elemental selenium can still be transported in the environment and become bioavailable to aquatic organisms (Buchs et al., 2013). Even though selenium is essential for human and other animal nutritional requirements (at least 0.04 mg Se/day), it can be toxic at concentrations above 0.4 mg Se/day (Fordyce, 2007). There have been reported incidences of selenium toxicity that caused extensive ecological damage, such as in the Kesterson reservoir, in the San Joaquin Valley, California, USA, where high selenium bioaccumulation has resulted in extensive deformities and deaths in waterfowl and other wildlife (Ohlendorf et al., 1986).  1.4.2 Biogeochemical Selenium Cycle Both natural and anthropogenic activities contribute to the release of selenium in the environment. Natural release of selenium originates from weathering of seleniferous soils and rocks. Selenium is often present at very low levels in soils in the range of 0.01 to 2 mg kg-1 (Nancharaiah and Lens, 2015). However, in seleniferous soils, selenium occurs at much higher levels and concentration up to 1,200 mg kg-1 has been reported (Fordyce, 2013). Selenium levels in soils are primarily dependent on the geologic origin of the parent rock formation. In natural waters, dissolved selenium concentrations in the range   10 of < 0.1 to 100 µg/L have been reported (Nancharaiah and Lens, 2015). In Canada, typical selenium concentrations in natural waters range from 0.01– 4 µg/L (CCME, 2009).   Once released into the aquatic environment, microorganisms play a pivotal role in the biochemical selenium cycling. Several mechanisms are involved, which are categorized as assimilatory and dissimilatory reduction, alkylation, dealkylation and oxidation reactions (Lenz and Lens, 2009). Selenium can be methylated by microorganisms and plants to form alkylselenium compounds (for example (CH3)2Se and (CH3)2Se2 ), which are volatilized into the atmosphere as a detoxification mechanism. Alkylation and dealkylation are important reactions in the biochemical selenium cycles mediated by microorganisms in water and on land. Alkylated selenium species can react with sulfur by a disproportionation reaction to form a mixed selenium-sulfur species (Lenz and Lens, 2009). Even though selenium speciation is similar to that of sulfur, the biogeochemical transformations of selenium species differ. In contrast to the biogeochemical sulfur cycle, in which sulfate is reduced by sulfate-reducing bacteria to sulfide as the end product, some selenate-reducing bacteria can reduce selenate to elemental selenium as the end product. Further reduction of elemental selenium to selenide is possible and is mediated by other types of selenate-respiring bacteria (Lenz and Lens, 2009). The availability of selenium for plant uptake is dependent on other soil characteristics such as pH, alkalinity and sulfur content (CCME, 2009). Soil microbes play a role in transforming elemental, organic and inorganic forms of selenium into more available forms for plant uptake. Wet and dry deposition of biogenic selenium from the atmosphere is thought to be the major source in the cycling and re-distribution of selenium back to soil, surface and ground water (CCME, 2009).   Commonly, selenium oxyanion contamination occurs concomitantly with sulfate and nitrate in different wastewater streams (Table 1.2). The release of selenium from land to aquatic environment occurs directly through natural discharges or indirectly through discharges from industrial activity such as coal mining, combustion of coal and oil, non-ferrous metal melting and utilization of agricultural products. Water is the main vehicle   11 that transports selenium once released into the aquatic environment. In surface waters, the most oxidized species; selenium oxyanions (selenate and selenite) are frequently formed from where they are transported mostly in particulate-associated form (Haygarth, 1994).   Table 1.2: Overview of selenium, nitrate and sulfate concentrations in different selenium contaminated waters. Waste water Se,  mg/L NO3−, mg/L SO42−, mg/L Reference Mining -Influenced Water  0.002 – 12 255 525 – 6837 Tan et al., (2016) 0.492 NA 1146 Simmon et al., (2002) 0.188 - 0.354 244 1100 – 2030 This study Agricultural Drainage  0.5 217 NA Oremland et al., (1999) 0.35 3.2 – 234 607 – 10100 Tan et al., (2016) 0.57 48 4730 Cantafio et al., (1996) and Presser et al., (1994) Oil Refinery 0.5 22 – 133 879 – 2393 Lawson and Macy, (1995) Flue Gas Sulfurization 0.54 2 815 Castaldi et al., (2001) 0.0015 – 16 1– 400 3000 – 20000 Tan et al., (2016) Selenium Compound Industry  620  NA NA Fujita et al., (2002)   NA:  Not Available   Soluble selenium oxyanions released into the aquatic environment can be reduced to insoluble elemental selenium, due to anaerobic microbial respiration. Members of both the archaea and bacteria domains can use selenium oxyanions as terminal electron acceptors (Huber et al., 2000). Reduction of selenate to elemental selenium represents the major sink for selenium oxyanions in anoxic sediments. This reduction of selenium oxyanions is coupled to the oxidation of organic matter in anaerobic or anoxic sediments. However, some strains can also reduce selenium oxyanions to elemental selenium under aerobic or micro-aerophilic conditions (Ike et al., 1999). Microbial reduction of selenium oxyanions to elemental selenium is often detected by the orange-red colour of the freshly precipitated amorphous form of selenium and this offers promising approach to its bioremediation.    12  Elemental selenium can be reduced further to soluble selenide [Se (-II)] (Herbel et al., 2003) under strongly reducing conditions, which in turn reacts with metals and organic matter to form metal selenides and / or organoselenides, respectively (Seby et al., 2001). Under strongly reducing conditions, selenide can also form highly toxic and volatile H2Se. Insoluble elemental selenium and selenide can be mobilized by microbial re-oxidation to soluble oxyanions (mostly selenite) in oxic conditions but with a much lower reaction rate compared to microbial reduction (Dowdle and Oremland, 1998). Metal selenide can be oxidized back to elemental selenium by various selenium oxidizing bacteria. A review of the activities of selenium oxidizing bacteria is provided in (Nancharaiah and Lens, 2015).   Coal mining activities in the Elk Valley of British Columbia, Canada have increased the selenium levels in receiving water bodies located downstream of the mines. The selenium concentrations in surface water bodies have increased by about 10 - 50 times the background concentration (Teck, 2013; Lussier et al., 2003). Coal, a sedimentary material, develops from the settling of plant and organic material and their subsequent transformation under the pressure of accumulating overburden. Since selenium is an essential element, it is assimilated by plants and microbes, eventually accumulating in coal seams. Surface coal mining operation generates large volumes of waste rock and depending on the mineralogy of selenium in these waste rocks, selenium can be released into the aquatic environment when the waste rock is oxidized and leached upon exposure to air and water (Figure 1-1). Both organic and inorganic forms of selenium are present in the waste rock. The inorganic form of Se occurs when the selenium substitutes for sulfur (S) and is present as Se2− in sulfidic minerals, most commonly pyrite (Lussier et al., 2003). The organic form of Se is usually present as Se0 and is present in the coal seams, by either covalent bonding in the molecular structure or ionic bonding onto the surface.        13   Figure 1-1: Schematic diagram showing the release of selenium from coal waste and its effect on aquatic environment. This forms part of the global selenium cycle.    Studies by Hendry et al., (2015) into the mineralogy of Se of coal waste in the Elk Valley found that, 21% of Se is present as selenide (Se2− ) in pyrite and sphalerite, 19% of Se is present as selenite (Se4+) in barite, 21% of Se is present as exchangeable Fe oxyhydroxide and clay-adsorbed (Se4+), and 39% of Se is present as organoselenium associated with organic matter. MIW affected by surface coal mining activities in the Elk Valley has a neutral pH and is saline (up to 2750 mg/L TDS at some sites) (Wellen et al., 2018).     14 1.4.3 Selenium Oxyanion Reduction Pathways by Bacteria  There is ample evidence in the literature that microorganisms can reduce selenium oxyanions for a variety of purposes (Pearce et al., 2008). Certain heterotrophic bacteria are capable of dissimilatory selenium oxyanion reduction, in which they couple reduction of selenate or selenite as electron acceptors to oxidation of organics compounds as electron donors for respiration, and this is an important contribution to natural biogeochemical cycling of selenium. Microorganisms that can grow anaerobically or micro-aerobically by linking oxidation of organic substances to reduction of selenium oxyanions can be used for the bioremediation of selenium-contaminated environments. Oremland et al., (1990) first reported evidence for dissimilatory selenate reduction, in experiments performed using sediment slurries sourced from a selenium-contaminated aquatic environment. The dissimilatory reduction of selenate that he measured was linked to the production of stoichiometric amounts of elemental selenium, meaning that this was the only product of selenate reduction. Following this, Oremland et al., (2004) reported that dissimilatory reduction of soluble selenium oxyanions was performed by the bacterial species: Sulfurospirillum barnesii, Bacillus selenitireducens and Selenihalanaerobacter shriftii, which formed nano-sized elemental selenium particles that achieved removal of Se from soluble forms to an insoluble and immobilized form. Assimilatory reduction of selenate and selenite occurs via a different mechanism than dissimilatory reduction when Se is associated with cell biosynthesis of selenoproteins (Nanchariah and Lens, 2015). Thus assimilatory selenium reduction results in accumulation of Se inside the cell biomass. Reduction of selenate and selenite by living organisms is also performed in order to reduce the toxicity of these chemical compounds. In this case, the methylated forms of Se as previously described are produced to reduce the toxicity of the selenium oxyanions and, in some cases, cause them to be volatilized. From a bioremediation perspective, dissimilatory selenate reduction to elemental Se would be preferred since this produces a more stable product that can potentially be recovered and stored safely or re-used.      15 Microorganisms use a variety of electron donors for selenium oxyanion reduction that include sugars (Zhang et al., 2008), hydrogen (Chung et al., 2006), organic acids (Kashiwa et al., 2000), or even complex carbon compounds such as molasses, humic substances (Lovley et al., 1999). In organic-rich natural environments such as vegetated wetlands or marshes, these electron donors are produced from the decay of plant matter and other primary producers. However, most MIW contains only low concentrations of dissolved organic carbon that are insufficient or not suitable for supporting selenate-reducing bacteria. Thus, in most bioreactors treatment processes for MIW contaminated with selenium, addition of an appropriate carbon source is required and this constitutes a major portion of the operating costs.    1.4.4 The Effect of Nitrate on  Dissimilatory Selenate Reduction Both nitrate and sulfate often are also present in MIW containing selenium. Nitrate is a residual from the use of explosives in blasting, and sulfate results from oxidative leaching of sulfide minerals. Typical nitrate concentrations in coal MIW are much greater (on the order of 10s to 100s mg/L) than those for selenium (on the order of µg/L) (Tan et al., 2016; Lenz and Lens, 2009; Oremland et al., 1999). To design an effective biological treatment for removal of dissolved Se from coal MIW, we must consider competition from nitrate and sulfate as these anions can also serve as electron acceptors for microbial respiration and growth (Lenz and Lens, 2009; Frankenberger et al., 2004).  Previous studies have focused on either the effect of nitrate or sulfate on selenium oxyanion reduction. Some of these studies differ in their findings regarding the effects of nitrate on microbial selenium oxyanion reduction processes. On the one hand, some researchers reported that nitrate is reduced first before selenium oxyanion reduction (Steinberg et al., 1992; Oremland et al., 1990 and Oremland et al., 1989). Thus, the presence of nitrate has inhibitory effects on selenate reduction. For instance, in a study conducted by Lai et al., (2014) to investigate the effect of nitrate on selenate reduction using hydrogen-based membrane biofilm bioreactor (H2-MBfR), they found that the reduction of selenate was inhibited by the presence of nitrate at the membrane surface   16 loading rates greater than 1.14 g NO3−- N m-2 day-1. The NO3− to SeO42− ratio in the feed to this bioreactor was 56.2 with nitrate concentration of 714 μM, which is typical of concentrations in mining and agricultural drainage waters. However, another study by Dessi et al., (2016) reported that nitrate did not inhibit selenate reduction in a UASB reactor operated under both mesophilic and thermophilic conditions even though the NO3− to SeO42− ratio for this reactor was approximately two times greater than that in the Lai et al., (2014) study.  One notable difference between these two studies was that the reactor in Dessi et al., (2016) study was supplied with electron donor (lactate) in excess of the stoichiometric requirement whereas in the Lai et al., (2014) study, stoichiometric amount of electron donor (hydrogen) was used. Another study conducted by Bao et al., (2012) also found that, nitrate inhibits selenate reduction in a Clostridium BXM strain isolated from paddy soil. Also, studies by Lenz et al., (2009) reported that reduction of selenate happened in a UASB bioreactor bio-augumented with Sulfurospirillum barnesii only after complete denitrification of the nitrate present.   One reason for nitrate inhibition of selenate reduction is because the reduction potential for NO3− to N2 is +0.75 V, which is higher than that for SeO42− to elemental Se, +0.69 V giving a competitive advantage to bacteria utilizing nitrate as their terminal electron acceptor (Table 1.3). However, studies conducted by Oremland et al., (1999) revealed that the inhibitory effect of nitrate on selenate reduction was enzymatic and might be due to nitrate suppressing the activity of selenate reductase enzymes in some microorganisms. Oremland et al., (1999) made that conclusion after discovering that, Sulfurospirillum barnesii SES-3 strain grown in a medium with nitrate as the sole terminal electron acceptor did not respire SeO42−, and when the strain was grown in a medium with selenate as the sole terminal electron acceptor, the strain did not respire NO3−. Oremland et al., (1999) further argues that when the actual concentrations of nitrate and sulfate present in selenium-contaminated waters are factored into the Nernst equation for the calculation of Gibbs free energy, it can change the thermodynamic reduction potentials of these anions, so any nitrate inhibition on selenate reduction might be due to enzymatic factors such as substrate affinity, repression of selenate reductase enzyme by nitrate, expression and regulation.   17 Table 1.3: Thermodynamic reduction potentials and standard Gibb’s free energy of anions commonly found in MIW Redox couple Oxidation state Half reaction E0', V ΔGo, kJ/mol NO3−/N2 +5/0 2NO3− + 10e− + 12H+                     N2 + 6H2O +0.75 −72.20 SeO42−/SeO32− +6/+4 SeO42− + 2e− +  2H+                        SeO32- + H2O +0.48 −46.31 NO3−/NH4+ +5/−3 NO3− + 8e− + 10H+               NH4 + 3H2O +0.36 −35.11 SeO32−/Se0 +4/0 SeO32−  + 4e− + 6H+                Se0  +  3H2O +0.21 −20.26 SO32−/HS− +4/−2 SO32− + 6e−  + 7H+                    HS− + 3H2O −0.12 +11.58 SO42−/SO32− +6/+4 SO42− + 2e− + 2H+                 SO32− + H2O −0.52 +50.17 Se0/HSe− 0/−2 Se0  +  2e−  + H+                      HSe−  −0.73 +70.43   On the other hand, some researchers found that the presence of nitrate stimulate selenate reduction. For instance, Chung et al., (2006) reported that a small amount of NO3− improved SeO42− reduction in an MBfR. Another study conducted by Hunter et al., (2007) found that nitrate was necessary for selenate reduction by Rhizobium sp. The stimulatory effect of nitrate on selenate reduction in some microrganisms can be explained by the fact that, the presence of other anions such as nitrate keeps the microbial cells at a higher metabolic activity to be able to reduce selenate.  Other studies have reported that both NO3− and SeO42− can be simultaneously reduced by the same microorganism.  For example, studies by Macy et al., (1993) found that NO3− and SeO42− were simultaneously reduced by the selenium-respiring bacterium, Thauera selenatis. The possible reason why nitrate and selenate were simultaneously reduced by   18 these microorganisms was due to the fact that, both nitrate and selenate reductases can exist in the same microorganism and which is the case for Thauera selenatis (Rech and Macy, 1992).  Thus, there is evidence in the literature that competing anion such as nitrate can affect selenate reduction, and there is a need to study this effect further to enable efficient removal of selenate in MIW treatment bioreactors. For instance, Tan et al., (2016) reported that there is the need to carefully control the concentration ratios of SeO42− to NO3−   to avoid any inhibitory effects of nitrate and sulfate on selenate reduction.   1.4.5. Effect of Salinity on Nitrate Reduction and Selenate Reduction Salinity or total dissolved solids (TDS) is the measure of the total ionic concentration of dissolved minerals in water. Principal ions that contribute to TDS in many waters are cations, calcium (Ca2+), magnesium (Mg2+), sodium (Na+), potassium (K+) and anions, sulfate (SO42−), chloride (Cl−), carbonate (CO32−), and bicarbonate (HCO3−). The International Network for Acid Prevention (INAP), (2009), classifies MIW with sulfate concentrations greater than 1000 mg/L as saline, which is often the case for coal MIW. High dissolved solids affect the growth and activity of microorganisms. When microorganisms adapted to fresh water are exposed to saline waters, they experience osmotic stress, which results in water flowing out of the cell into the surrounding environment. If the microbial cells cannot counter this effect they become dehydrated, which interrupts their cellular functioning, growth, or even may lead to cell lysis (Mark et al., 2016).   Some studies investigated the effect of salinity on specific microbial consortia, such as denitrifying bacteria. For example, Dinçer and Kargi (1999) reported that salt concentrations above 2% w/v resulted in lowering the denitrification efficiency due to loss of activity of the microorganisms. As a result of this, Dinçer and Kargi, (1999) reported on the limitations associated with biological treatment of saline waters. They mentioned that conventional cultures used in denitrification could not be used to treat saline waters (3 - 5% w/v) effectively because the microorganisms do not easily adapt to   19 the salt medium. It was noted that shifts in salts concentration between 0.5 - 2% w/v caused significant disruption in wastewater treatment system performance. On the other hand, Yoshie et al., (2006) demonstrated an increase in denitrification efficiency at high salinity when the sludge was acclimatized to a saline metal refinery wastewater using acetate as carbon source.  Another study by Osaka et al., (2008) showed that the type of carbon source affected the effectiveness of denitrification in saline waters.  Mark et al., (2016) reported that in-situ denitrification was significantly higher in freshwater marsh and soil sites than in a salt marsh. Mark et al., (2016) also found that shifts in salinity caused disruptions in in-situ denitrification. Whilst several studies have been conducted on the effect of salinity on denitrifying microbial consortia, limited studies have been conducted on the effect of salinity on selenate respirers. And even most of the studies conducted on the effect of salinity on denitrification have focused on NaCl as the main contributor to salinity, which is not directly related to the ions that contribute to salinity in MIW. The principal ions that contribute to salinity in MIW are Ca2+, Mg2+ and SO42−. There is the need to investigate the effects of these ions on selenate and nitrate reduction in MIW. A few studies have been carried out on the effect of calcium on denitrification. Fernandez-Nava et al., (2008) reported that increased calcium concentration (>150 mg/L) in stainless steel manufacturing water caused decreased denitrification rates and reduced biomass growth rate. Yu et al., (2000) also reported that increased Ca2+ concentration decreased the activity of anaerobic sludge at any concentration.  One of the few studies conducted on the effect of Ca2+ and Mg2+ ions on selenate reduction was conducted by van Ginkel et al., (2008). They reported that in the treatment of flue-gas desulfurization brine using a membrane biofilm reactor, increased Ca2+ and Mg2+ concentrations caused MgCO3 and CaCO3 precipitation of fibres, which blocked the transfer of hydrogen to the biofilm. The few studies related to the effect of salinity on selenate reduction have focussed on the isolation of halophile or halotorelant bacteria (Mishra et al., 2011; Blum et al., 2001; Blum et al., 1998). This is because effective treatment of saline selenium-contaminated waters could be achieved if halotorelant or halophilic selenate-reducing bacteria are used or are members of the microbial consortia   20 used to seed the bioreactors. Blum et al., (2001) successfully isolated haloalkaliphilic anaerobic selenate-respiring bacterium, Selenihalanaerobacter shriftii from sediments of Dead Sea. Blum et al., (1998) isolated two moderate haloalkaliphiles, Bacillus arsenicoselenatis and Bacillus selenitireducens from the anoxic sediments of Mono Lake, California with salinity of 90 g/L. Mishra et al., (2011) isolated halotorelant Bacillus megaterium from saline mangrove habitat with selenium contamination.   1.4.6 Microbial Species Capable of  Selenium Oxyanion Reduction and the Enzymes involved  Microorganisms through their metabolic pathways mediate biological reduction of selenate to elemental selenium under aerobic and anaerobic conditions. The microbial reduction of Se oxyanions is widespread in a diversity of natural environments including selenium polluted and pristine environments.  The first microorganism that was identified as one that uses selenate as its preferred electron acceptor is Thauera selenatis (Macy et al., 1993). T. selenatis achieves selenate reduction through the selenate reductase enzyme SerABC that has been isolated, purified and characterized (Butler et al., 2012; Schroder et al., 1997). Other selenate-respiring bacteria with putative selenate reductases that have been identified include Sulfurospirillum barnesii, Bacillus selenatarsenatis SF-1, Bacillus arsenicoselenatis, Selenihalanaerobacter shriftii, Enterobacter cloacae SLD1a-1, Bacillus sp SF-1 and Enterobacter taylorae. In addition, non-specific reduction of selenate can be achieved by nitrate reductases (Sabaty et al., 2001; Steinberg et al., 1992), and is also possible via dissimilatory sulfate reducing pathway (Hockin and Gadd, 2006; Stolz and Oremland, 1999). Details about microorganisms capable of selenate and selenite reduction and the enzymes used to achieve this are presented (Table1.4)  21   Table 1.4: Some selenate/selenite-reducing microorganisms  Bacteria Characteristics Reference Thauera selenatis Grows anoxically using SeO42−, NO3−, and NO2−. Reduction of SeO42− occurs by way of a SeO42− reductase. SeO42− is completely reduced to Se0 only when NO3− is present. Selenate reductase is soluble and located in the periplasm. Cantafio et al., (1996), DeMoll-Decker and Macy, (1993)  Serratia fonticula SeO42− is reduced to Se0 under anoxic condition. Knotek-Smith et al., (2006) Pseudomonas putida Enterobacter taylorae  Respires SeO42− completely reduced to Se0  Zhang et al., (2008); Zhang et al., (2007) Enterobacter cloacae SLD1a-1 Respires SeO42− and NO3−, and reduces SeO42− to Se0 only in the presence of NO3− Selenate reductase is a membrane-bound heterotrimeric complex that faces the periplasmic side of the cytoplasmic membrane. Zhang et al., (2008); Losi and Frankenberger (1997) Rhizobium sp. Reduces selenite but not selenate to Se0 under aerobic and denitrifying conditions. Does not use selenate and selenite as terminal electron acceptor. Hunter and Kuykendall, (2007) Azospira oryzae Reduces SeO42− and SeO32− to elemental Se0 under micro-aerophilic and denitrifying conditions but does not respire selenate and selenite as terminal electron acceptors Hunter, (2007) Bacillus sp. SF-1 Respire anoxically (facultative) using SeO42− and NO3−. SeO42− is completely reduced to Se0 but is inhibited by nitrate. Fujita et al., (2002) Desulfovibrio desulfuricans SeO42− and SeO32− were reduced to Se0 under anoxic conditions, but both Se oxyanions could not support growth.  Tucker et al., (1998)    22 Bacteria Characteristics Reference Dendrosporobacter quercicolus SeO42− and SeO32− were reduced to Se0 under anoxic (methanogenic) conditions, selente-reductase is independently of sufate but inhibited by sulfide.  Lenz et al., (2008a) Sulfurospirillum barnesii Reduction of SeO42− occurs by way of a SeO42− reductase under anoxic conditions. SeO42− is completely reduced to Se0 in the presence of NO3−. Selenate reductase is insoluble and membrane bound. Also reduces arsenate but cannot use sulfate as terminal electron acceptor. Oremland et al.,(1999), Stolz et al., (1999) Bacillus selenitireducens Respires only SeO32− to Se0 under anoxic conditions but cannot reduce SeO42− Lenz and Lens, (2009), Oremland et al., (2004)  Bacillus arsenicoselenatis SeO42− respiring halo-alkaliphile reduces SeO42− and NO3− simultaneously.  Oremland et al., (1999) Selenihalanaerobacter shriftii Grow strictly under anoxically condition. NO3− and SeO42− support good growth. Only glucose and glycerol supported growth of the strain Lenz and Lens, (2009), Oremland et al., (2004)  Ralstonia metallidurans Reduces SeO32− but not SeO42− to Se0 under anoxic conditions.  Diels et al., (2003) Pseudomonas fluorescens Reduction of SeO32− to Se0 by a NO2− and SO32− independent enzyme system Tirez et al., (2000) Reduction of SeO42− to Se0 in sediments samples from environment free from selenium contamination. Ike et al., (2000) Reduction of SeO42− to Se0 in selenium-contaminated sediment slurries from coal mines under static anoxic incubation Siddique et al., (2007) Bacillus subtilis Reduction of SeO32− to Se0 reduction under anoxic conditions Garbisu et al., (1996) Reduction of SeO42− and SeO32− to Se0 in sediment slurries under anoxic condition  Siddique et al., (2006)   23 Bacteria Characteristics Reference Pseudomonas stutzeri Reduction of SeO42− and SeO3− to Se0 under aerobic conditions Knotek-Smith et al., (2006) Reduction of SeO42− to Se0 in sediments samples from environment free from selenium contamination. Ike et al., (2000) Desulfomicrobium sp. Lactate-grown biofilm culture reduced SeO42− to elemental Se0 in the presence of sulfate. Sulfate limited conditions resulted in the formation of selenide.     Hockin and Gadd (2006) Citrobacter braakii Reduces SeO42− to Se0 and organic Se under anoxic conditions. NO3− inhibits the reduction process. Salinity reduces the reduction process. Zhang and Frankenberger (2006) Wolinella succinogenes Adapted cultures able to reduce SeO42− and SeO32− to Se0 under anoxic condition Tomei et al., (1992) Enterobacter hormaechei Reduces SeO42− to Se0 under static anoxic incubation Siddique et al., (2007)     24 1.4.7 Specific Dissimilatory Selenate Reductase Enzyme  Dissimilatory selenium respiring bacteria that possess enzymes that are highly specific for selenium oxyanions are not competitively inhibited by the presence of competing anions such as nitrate, nitrite and sulfate. Microorganisms containing these enzymes are the most desirable to use in bioremediation of MIW co-contaminated with nitrate and sulfate. Additionally, purely selenate or selenite respiring bacteria are more tolerant to high selenium concentrations than other microorganisms, which is another beneficial attribute of their use for the treatment of concentrated waste waters (Fujita et al., 2002).   Generally, dissimilatory reduction of selenium oxyanions can be divided into a two-step enzymatic process involving reduction of selenate to selenite and then reduction of selenite to elemental selenium (Eswayah et al., 2016; Nancharaiah and Lens, 2015). The overall process of microbial SeO42− reduction leading to the formation of Se0 is given in the schematic diagram (Figure 1-2).       Figure 1-2: Simplified diagram for dissimilatory selenate reduction to elemental Selenium  The first step, which involves the reduction of selenate to selenite, is mediated by membrane bound or periplasmic selenate reductase. The second step, which involves the reduction of selenite to elemental selenium, is not very well understood (Bao et al., 2012). It has been reported that selenite reduction might be catalysed by a periplasmic nitrite reductase (DeMoll-Decker and Macy, 1993), hydrogenase (Yanke et al., 1995) or through a non-enzymatic reaction mediated by the thiol group of glutathione and thioredoxin as detoxification strategy (Tomei et al., 1992). The enzymes and electron transport pathways involved in SeO42− reduction have been investigated primarily in two SeO4 2−  Selenate reductase  SeO32− Hydrogenase Nitrite reductase  Se0 Thiol of glutathione and thioredoxin   25 Gram-negative bacteria (Thauera selenatis and Enterobacter cloacae SLD1a-1) and one Gram-positive bacterium (Bacillus selenatarsenatis SF-1).    Thauera selenatis is a Gram-negative betaproteobacteria that was first isolated from selenium-contaminated waters in the San Joaquin Valley in California. Its selenate reductase (SerA) is located in the perisplasm and has an apparent molecular weight of 180kDa (Bebién et al., 2002). Selenate to selenite reduction is catalyzed by a trimeric molybdoenzyme, SerABC selenate reductase. The enzyme consists of a catalytic unit (SerA; 96 kDa), iron-sulfur protein (SerB; 40kDa), a heme b protein (SerC; 23kDa), with molybdenum as a cofactor. Electron transport to perisplasmic cytochrome c4 is proposed to be via quinol cytochrome c oxidoreductase (QCR) (Lowe et al., 2010). SeO32− formed in the perisplasm is presumed to be transported to the cytoplasm through a sulfate transporter and is reduced to elemental selenium in the cytoplasm. The second step of reduction of selenite to Se0 is believed to be catalyzed by the nitrite reductase in T. selenatis (Butler et al., 2012; DeMoll-Decker and Macy, 1993). The reduced Se is finally deposited inside the cell in the cytoplasm.     For the case of Enterobacter cloacae SLD1a-1, Losi and Frankenberger, (1997) observed that there was no accumulation of reduced selenium species inside the cell during selenate respiration. Unlike Thauera selenatis, the selenate reductase enzyme of E. cloacae SLD1a-1 is membrane-bound trimeric complex with a catalytic subunit of 100 kDa (Ridley et al., 2006). The selenate reductase is a molybdoenzyme, like SerA, with the active site located in the perisplasm. Selenate reduction to elemental selenium occurs in the perisplasm, and the elemental selenium nanospheres are expelled into the extracellular environment by membrane-associated efflux pump (Losi and Frankenberger, 1997). Perisplasmic and membrane-bound selenate reductase is shown below (Figure 1-3).     26  Figure 1-3:  Schematic diagram showing the enzymes and electron transport pathway for selenate reduction for perisplasmic and membrane bound reductases. The periplasmic reductase for Thauera selenatis is shown in light blue whilst the membrane-bound reductase for Enterobacter cloacae SLD1a-1 is shown in orange.  The green shows the protein, cytochrome, which transfer electrons to the enzyme SerABC (Adapted from Nancharaiah and Lens et al., 2015).   The selenate reductase of Gram-positive microorganism Bacillus selenatarsenatis SF-1 has been studied in detail; its selenate reductase enzyme SrdABC is membrane-bound.  SrdA, which is a molybdenum unit, is the active site of the enzyme and SrdB, SrdC are iron-sulfur proteins, which transport electrons to the enzyme for selenate reduction. Selenate is reduced by the molybdenum unit, SrdA (Kuroda et al., 2011). Similar to the case for the membrane-bound reductase for Enterobacter cloacae SLD1a-1, the bio-reduced selenium nanoparticles are released into the extracellular medium.     27 1.4.8: Denitrification Pathway In dissimilatory biological denitrification by heterotrophic bacteria, nitrate (NO3−) reduction proceeds through a series of intermediate products, nitrite (NO2−), nitric oxide (NO), and nitrous oxide (N2O) to nitrogen gas (N2) (Figure 1.4).    Figure 1-4:  Schematic diagram showing the steps in dissimilatory nitrate reduction. Some microorganisms are known to reduce NO3− to NH4+  Presence of the NO2− reductases (NirK and NirS) and N2O reductase (NosZ) are normally used to identify and quantify denitrification bacteria (Lu et al., 2014). Nitrate can also be transformed by heterotrophic bacteria to ammonium through a process called Dissimilatory Nitrate Reduction to Ammonium (DRNA) pathway. The ecology of (DRNA) bacteria is not well understood (Kraft et al., 2011) but DRNA is catalyzed by facultative, obligately fermentative bacteria (Nijburg et al., 1997; Bonin, 1996) and occurs under strongly reducing conditions involving the transfer of eight electrons. The calculated free energies for denitrification and DRNA are +0.75 V and +0.36 V respectively (Table 1.3, Section 1.4.4) (Nanachariah and Lens, 2015). Another factor that favours DRNA pathway is a high ratio of available carbon to nitrate (Fazzolari et al., 1998). The enzyme NrfA, which catalyzes the DRNA pathway, is pentaheme cytochrome c nitrite reductase (Kraft et al., 2011). However, unlike, the denitrification/nitrate reductases, DRNA reductase is not known to catalyze selenate reduction.     28 It has been reported that most denitrifying bacteria can also reduce selenate (Zumft et al., 1997). This association of denitrification with selenate reduction was based initially on the observation by Oremland et al., (1994) that, in-situ nitrate and selenate reduction had similar profiles as a function of depth in natural sediments. Nitrate reduction is achieved via two different types of nitrate reductases, membrane-bound (NarG) and periplasmic (NapA), which are analogous to selenate reductases, for which there are also membrane bound and periplasmic forms. The occurrence of a membrane-bound nitrate reductase enzyme has been shown and studied in detail in a large number of denitrifiers (Zumft, 1997). This enzyme is synthesized under anaerobic conditions and is composed of three subunits: a 112-to-140 kDa catalytic unit α subunit (NarG) with a molybdopterin cofactor, a soluble 52-to-64 kDa β subunit (NarH) with one [3Fe-4S] and three [4Fe-4S] centres, and a 19-to-25 kDa membrane diheme b quinol-oxidizing γ subunit (NarI) (Sabaty et al., 2001). The other nitrate reductase, NapA, is located in the periplasm and is also a molydopterin reductase like SerA.  Avazeri et al., (1997) found that the soluble or membrane bound denitrifying reductases (NarG) of different bacterial species posses also selenate reductase activity. The ability of denitrifying enzymes to also reduce selenate might be due to homology between the two enzymes as both are molybdoenzymes with iron sulfur electron transport chains (McEwan et al., 2002). Additionally, selenite reduction can be achieved by nitrite reductase, as is the case for T. selenatis.  Despite the functional flexibility of nitrate and nitrite reductases, as mentioned earlier, the nitrate reductases have a low affinity for the selenium oxyanions (Watts et al., 2005; Sabaty et al., 2001). Consequently, in a bioreactor composed of denitrifying microorganisms with the absence of specifically selenate-respiring bacteria, nitrate will be reduced first and then selenate reduction will occur only at very low nitrate concentrations or when nitrate is depleted. In practice, this may require a two-stage process where denitrification occurs in the first stage and selenate reduction in the second stage. Such an operation would come with high operation and maintenance costs as well as high spatial requirements. Therefore, it would be preferable if specifically, selenate- respiring bacteria, like T. selenatis, were also members of the bioreactor microbial community.    29 1.4.9 Dissimilatory Sulfate Reduction Pathway  From the thermodynamics reduction potential, SeO42− reduction is more favourable than SO42− reduction. However, in MIW where sulfate concentrations are much greater than those for selenate or selenite, sulfate-reducing bacteria (SRB) could have a competitive advantage due to the fact that Nernst equation used to predict the reduction potential is a function of concentration. The reduction of SO42− to H2S requires eight electrons and proceeds through a number of intermediate stages. The overall simplified schematic diagram is provided below (Figure 1-5). The DsrA gene, which catalyzes sulfite reduction to H2S, can be used to identify and quantify SRB (Dar et al., 2007).        Figure 1-5:  Simplified schematic diagram for dissimilatory sulfate reduction.  It has been hypothesised that SRB have a broad spectrum of activity on reduction of metal and metal (oid) ions, which makes them suitable for bioremediation of several industrial waste waters especially MIW (Sheoran et al., 2010; Muyzer and Stams, 2008; Kaksonen and Puhaka, 2007). Dissimilatory selenate reduction was found to occur simultaneously with sulfate reduction by sulfate-reducing bacteria (Lenz and Lens, 2008a; Qian et al., 2008; Hockin and Gadd, 2006; Tucker et al., 1998). Qian et al., (2008) reported that more than 75% selenate at a concentration of 0.2 mg/L was effectively removed in the presence of 1000 mg/L sulfate in a laboratory-scale sulfate reducing column bioreactor. Lenz et al., (2008a) were also able to achieve selenate reduction in a sulfate-reducing UASB bioreactor. Although this was not possible when the selenate concentration exceeded 1 mM (Chung et al., 2006), above which selenate inhibits the activity of SRB (Hockin and Gadd, 2006).   SO42− ATP sulfurylase + APS reductase SO32− H2S Sulfite reductase   30 Table 1.5: Theoretical calculations of Gibbs free energy for nitrate, sulfate and selenate reduction using lactate as electron donor at pH 7 and concentration of 1M. Reaction ΔGfo, kJ/mol Enzyme  CH3CHOHCOO− + 12/5NO3− + 2/5H+     3HCO3− + 6/5N2 + 6/5 H2O   −1291.55 Nitrate Reductase (Nar and Nap) Nitrite Reductase (Nir) NO Reductase (Nor) N2O Reductase (Nos)  CH3CHOHCOO− + 3SeO32− +4H+      3HCO3− +3Se +3H2O  −844.43 Nitrite Reductase (Nir) Hydrogenases (H2 ase) and  other molybdoenzymes   CH3CHOHCOO− + 2SeO42− +2H+     3HCO3- +2Se +2H2O   −834.15 Selenate Reductase (Ser) Nitrate Reductase (Nar) Sulfite reductase (Dsr) Hydrogenases (H2ase) and other molybdoenzymes CH3CHOHCOO− + 6SeO42− +2H+     3HCO3− + 6SeO32− + 2H+  −813.59 Selenate Reductase (Ser) Nitrate reductase (Nar)  CH3CHOHCOO− + SO42−               3HCO3− + 3/2HS− + 1/2H+  −107.62 Adenosine phosphosulfate (APS) reductase   and Sulfite reductase (Dsr)    The values for the Gibbs free energy changes (ΔGo) for microbial reduction of contaminants commonly found in MIW under standard conditions (pH 7, temperature 25 oC, pressure of 1 atm and total ion concentration 1M) using lactate as the electron donor are shown in Table 1.5 above. The contaminants serve as terminal electron acceptors during microbial respiration. However, under normal conditions, the free energy change (ΔG) is related to the standard free energy by the Nernst equation: ΔG = ΔGo + RTln [products] a / [Reactants] b where R is a constant (8.29 J/mol/K), T is the absolute temperature (in K), a, b represent the number of moles and the bracket represent concentration. Since the Nernst equation is dependent on concentration, when we applied it to the nominal concentration of the contaminants, it might change the Gibbs free energy. Taken together, these factors suggest that, in a bioreactor treating MIW, denitrification is more favourable than selenate reduction, which is more favourable than sulfate reduction.   31 1.4.10 Bioreactors used for Removal of Dissolved Selenium Biological reduction was identified as the preferred technology for removal of dissolved selenium oxyanions from industrial effluents versus other physical or chemical methods (USEPA 2014; CH2M HILL 2010; NSMP 2007). Biological treatment technologies are broadly classified as passive or active processes. Passive or semi-passive treatments rely on natural biogeochemical processes on the site and require few if any chemical reagents, special equipment, energy, maintenance or operation. Active treatment processes are highly engineered, high capital cost installations needing special reagents, energy and personnel to operate and maintain. Active treatment systems include process control to maintain optimum conditions, while passive treatment systems are subject to seasonal and other types of variability.   These biological treatment systems were successful in achieving selenium removal at extents ranging from 56 – 99% for incoming total dissolved selenium concentrations ranging from 20 to 41800 μg Se L-1 (Table 1.6). However, many of them were pilot- or laboratory-scale studies, with only a couple of commercial full-scale operations (i.e. ABMet® and Envirogen, FBR). Notably, these bio-treatment systems required pretreatment to remove co-contaminants, most importantly nitrate and post treatment to remove organic and inorganic residues especially, biogenic colloidal Se0 from the effluent. Nitrate inhibits selenate reduction because microorganisms derive more energy from nitrate reduction compared to selenate. Biogenic Se0 has the potential to re-oxidize to selenate and selenite when discharged into aquatic environment thus reverting Se back to toxic valence states (Zhang et al., 2004).    Most active treatment processes consist of several reactors in series so as to deal with interferences from co-contaminants, such as nitrate, and to remove metabolic byproducts, such as ammonia. To remove nitrate, a pretreatment bioreactor is used as the first stage followed by selenium removal in subsequent bioreactors(s), which are then followed by aerobic bioreactors to eliminate metabolic byproducts produced in the upstream bioreactors. The number of bioreactors required for treatment of selenium containing MIW could be reduced if the bioreactor supports a microbial community with enzymatic   32 systems that are specific for selenate reduction and not inhibited by the presence of nitrate.       33  Table 1.6: Overview of biological treatment processes used for selenium removal from selenium-contaminated wastewater Bioreactor Type Se, influent μg Se L-1 Se, effluent μg Se L-1 % Se Removal Operating conditions Reference  ABMet® and BSeR (PBR Microbial consortium)   1950   < 2  97 Gold MIW; Pilot-scale, Flow rate, 4 L/min and HRT 5.5 hours MSE, (2001) CH2M HILL, (2010)  43 5 88 Coal MIW, Pilot -scale, 3.8 – 11.4 L/min, Flow rate and HRT not available. CH2M HILL, (2010) Envirogen  (FBR)  15 – 20 4.7 – 8.2  59 – 69  Coal MIW; Full-scale, Flow rate, 11.4 – 5.7 L/min, HRT, 60  – 120 mins, Temperature, 16 oC, NO3− - N, 3.5 mg-N/L Sirinvasan et al. (2014) 155 – 558  (SeO42−) 2 – 4.6    (SeO42−) 98 – 99  Pilot-scale, Flow rate 7949 L/min, Temperature, 10 oC, HRT, 60 – 120 mins, NO3−- N, 31 mg-N/L, SO42−, 800 mg/L. Gay et al., (2012) Packed bed  (Thauera selenatis) 160 – 640  5 –12 98 Agricultural drainage, Pilot- scale, HRT, 3.25 hrs.  Cantafio et al., (1996)   34 Bioreactor Type Se, influent μg Se L-1 Se, effluent μg Se L-1 % Se Removal Operating conditions Reference Chemostat (Bacillus sp. SF-1) 41,800  (SeO42−) 50 (SeO42−) 99 Laboratory scale, HRT, 95.2 hrs  Fujita et al., (2002) H2-MBfR 260 –1000 12 – 50 95  Laboratory scale, hollow-fiber membrane Chung et al., (2006) Constructed wetlands 1,500 > 7 > 99 Microcosm water column of 72 hrs HRT NSMP,  (2007) Algal-bacterial  402 – 422  32 – 77 82 – 92 Pilot scale, High rate aerobic-anoxic ponds for algae and anaerobic bacteria. HRT, 38 – 66 days. Quinn et al., (2000)   UASB  790                  (SeO42−)  8 – 24 (SeO42−) 97 – 99 Laboratory scale operated under both methanogenic and sulfate reducing conditions, HRT, 6 hrs. Lenz et al., (2008a)    35 Regarding the process conditions that are required for selenium removal down to regulated levels, most active treatment bioreactors need HRTs ranging from 6 – 48 hours. The required HRT is dependent on the selenium loading rate into the bioreactor and the loading rate of co-contaminants that could interfere with the rate of selenium removal. Another important parameter to control is pH, which must be near neutral since this is optimal for microbial selenate/selenite reduction. For instance, Lortie et al., (1992) reported that no selenate reduction occurred at pH below 6.5 or above 9.5. These bioreactors also use mesophilic bacteria, which operate within the temperature range of 15 – 35 oC and any changes in temperature could affect bioreactor performance. For instance, it was found that a drop in temperature from 15 to 7 oC reduced selenate removal from 88% to 35% in a UASB reactor (CH2M HILL, 2010). However, the ABMet® system has been operated successfully over a wide temperature range (3 – 38 oC) (Staicu et al., 2017). An important concern regarding bio-treatment of selenium-containing MIW is the formation of colloidal Se that needs to be removed from the effluent before it can be discharged into the receiving environment. Different post-treatment steps for solid-liquid separation of colloidal Se0 have been proposed including, media-filtration, coagulation and electrocoagulation (Staicu et al., 2017).    1.4.11 Challenges with using Bioreactors for Removal of Dissolved Selenium from MIW  Most of the bioreactors used for selenate reduction have been tested at the laboratory - or pilot-scale, and a few are operating at full-scale. However, these processes still experience performance deterioration and instability. As is typical for most biological processes, the success in reducing the contaminant of interest is dependent on creating the optimal conditions for the desired functional microorganisms to flourish, and maintaining these microbes throughout the treatment processs. Briones and Raskin, (2003) reported that the stability of biological wastewater treatment systems is dependent on the functional redundancy of microbial communities in the bioreactor. Functional redundancy is having a diversity of functionally important groups of microorganisms that can perform desired treatment under a wide range of conditions. For MIW treatment, the   36 challenge is being able to maintain the functionally important microbial community members that can simultaneously remove selenate and nitrate in MIW treatment bioreactors. Selecting and maintaining the selenate-respiring specialists that can selectively remove selenium in the presence of other competing anions could even reduce the amount of electron donor required for microbial respiration. This is because the microbial reduction of the competing anions increases the electron donor usage proportionally. For instance, each mole of nitrate co-reduced with selenium oxyanions requires an additional five electron equivalence from the electron donor to be reduced to N2 gas. Organic carbon requirements are a significant operating cost for MIW treatment bioreactor operation. Another challenge that can be resolved through selecting and maintaining selenate-respiring specialist microorganisms in bioreactors, is the possibility of reducing selenium into the form of colloidal elemental Se nanoparticles and alkylated selenium compounds in bioreactors. Constructed wetlands are sensitive to seasonal temperature fluctuations and variations in the type of vegetation. There is also the concern about gradual accumulation of selenium in vegetation and sediments in these wetlands. In practice, algal-bacterial processes are associated with inconsistent selenate reduction to low levels unless nitrate is removed first (NSMP, 2007; CH2M HILL, 2010). The main operational limitation associated with ABMet® bioreactor process is its susceptibility to clogging (CH2M HILL, 2010). When implementing FBR for full-scale mine water treatment, Sirivasan et al., (2014) reported that, the main operational challenges encountered was difficulty in controlling bed height in order to maintain bed expansion for selenium removal. For UASB bioreactor configuration, the challenges reported are; long acclimatization of the sludge, short-circuiting caused by accumulation of gas in the sludge, and variability in selenium removal efficiencies due to temperature sensitivity of the process (CH2M HILL, 2010). When treating synthetic MIW under sulfate-reducing conditions in a UASB reactor, Lenz et al., (2008) observed that the removal of selenium is dependent of sulfate/selenate ratio with ratio greater than 8x10-4 being the most effective for selenate removal. However, this sulfate/selenate ratio is impossible to achieve in actual MIW. The main challenge associated with the use of pure cultures e.g. Thauera selenatis and Bacillus sp. SF-1 as   37 inoculum in bioreactors is out-competition by other microorganisms entering with the feedwater since a sterile environment is impossible to maintain. The challenges associated with H2-MBfR bioreactor are the expensive electron donor (hydrogen) membrane fouling especially from colloidal Se (Nancharaiah and Lens, 2015) and presence of nitrate has inhibitory effect on selenate reduction (Lai et al., 2014). 1.4.12 Sources of Inocula used to Achieve Dissolved Selenium Removal in Bioreactors  Microorganisms used to inoculate bioreactors in previous studies to carry out selenate and or selenite reduction to insoluble elemental selenium were either pure cultures of known selenate or selenite-reducing bacteria or mixed cultures containing many different types of microorganisms. Since in MIW, dissolved selenium is present together with other contaminants such as nitrate and sulfate, it may be advantageous to use mixed cultures as inoculum. This will increase functional diversity as well as foster potentially co-operative relationships that could allow for simultaneous selenate and nitrate reduction.  Although, single species with the capacity for both denitrification and selenate reduction exist e.g. Pseudomonas stutzeri (Zhang and Frankenberger, 2006; Oremland et al., 2004; Cantafio et al., 1996), the use of pure cultures is not suitable for pilot or large-scale treatment of selenium-contaminated waters since they can be easily outcompeted by mixed microbial populations entering with the feed water.   In some instances, inocula for pilot- or industrial-scale water treatment plants are sourced from local wastewater treatment plants that may or may not be treating similar types of wastewater as MIW. Use of municipal wastewater treatment sludge as suitable inoculum for selenium oxyanions reduction has been confirmed in several studies (Soda et al., 2011; Lens et al., 2008b; Astratinei et al., 2006). Other inocula sources used as seed for selenium oxyanions reducing microbial communities include horse manure and pulp and paper mill effluent (Hageman et al., 2013; Qian et al., 2008). Summary of the advantages and disadvantages of using pure or mixed cultures for inoculating MIW treatment bioreactors is discussed below (Table 1.7).    38 Table 1.7: Advantages and disadvantages of pure and mixed cultures Pure Culture Mixed Culture (+)  Specific for SeO42− reduction (+) Robust and resilent to changing influent properties (+) Can remove high concentrations of selenium oxyanions (+) Can remove selenium oxyanions as well as other contaminants in the MIW  (-) Are often outcompeted by unwanted species entering with the influent water (-)  Can be difficult to select for and control the functionally important microorganisms, and prevent proliferation of unwanted microorganisms (-) May be difficult to isolate from the environment and grow in bioreactors (-) Will require higher concentrations of carbon source due to wider diversity of metabolisms  (-) May be inhibited by nitrate since this is a more favourable electron acceptor (+) Advantage (-) Disadvantage  Denitrifying sludge is often preferred as a source of inoculum for reduction of selenium oxyanions because of the ability of denitrifying bacteria to reduce both nitrate and selenium oxyanions using their reductase enzymes.  For instance, Takada et al., (2008) successfully prepared sludge with the capacity to reduce selenium oxyanions from denitrifying sludge by acclimatizing the sludge with selenate in a synthetic wastewater with methanol as the sole carbon substrate. But, nitrate was found to inhibit selenite reduction to elemental selenium but not selenate reduction, which may result in intermediary selenite accumulation in the treatment tank. Rege et al., (1999) used denitrifying sludge sourced from a local wastewater treatment plant as the source of inoculum for the removal of selenium oxyanions from synthetic oil refinery water. However, this study reported a lag period of about 150 hours before increased selenium oxyanions reduction was observed. This confirms earlier reports that denitrifying bacteria prefer nitrate compared to selenate when both are present, this might be one pitfall of using denitrifying sludge as inoculum for bioreactors treating MIW. However, there have   39 been few attempts to use native mine site bacteria to inoculate industrial bioreactors instead of denitrifying sludge or customized pure cultures. Presumably, native microbial communities at several locations on the mine site that have been exposed to MIW seepage over long periods contain microbial communities adapted to elevated levels selenium and nitrate. Due to this strong selective pressure, the local mine site may provide microorganisms that can reduce selenate in the presence of nitrate. This was supported in a study by Maier et al., (1988) that investigated the use of indigenous inoculum sourced from a selenium polluted environment for soluble selenium oxyanion reduction in a synthetic waste water and found that the indigenous microorganisms were capable of reducing unusually high concentrations (up to 100 mg/L) of selenium oxyanions without any measurable toxicity effects. These specialist microorganisms that are highly selenium tolerant are very effective at removing high levels of selenium from water since dissolved selenium is toxic to the other competing bacterial groups especially sulfate-reducing bacteria (Hockin and Gadd, 2006). Identifying mine site locations that contain known specialized selenate-reducing bacteria, such as Thauera selenatis, Sulfurospirillum barnesii, Bacillus sp. SF-1 and others as described in Table 1.4 (section 1.4.6) as members of the microbial community will be useful as sources of inoculum for selenium removal in the presence of nitrate in MIW bioreactors.   1.4.13 Microbial Diversity in Selenate Reduction Bioreactors Few previous studies have identified microorganisms present in bioreactors removing dissolved selenium oxyanions with or without the presence of nitrate and or sulfate. Lai et al., (2014) found that the dominant genera present in an H2-MBfR reactor that was reducing selenate with acetate as carbon source when nitrate was absent were Methyloversatilis and Hydrogenophaga. Methyloversatilis has been classified as an incomplete denitrifier (reducing nitrate or nitrite to nitrogen oxide intermediates instead of N2 (Lu et al., 2012). When nitrate was introduced into the bioreactor, the microbial community shifted and was dominated by species in the genus Dechloromonas. Some species of Dechloromonas genus are known to reduce nitrate and perchlorate (Coates et al., 2001).  None of the aforementioned species found in Lai et al.’s bioreactor contain   40 species known to preferentially reduce selenium oxyanions, thus it was postulated that selenate reduction must have been carried out through nitrate and or nitrite reductases.  A study conducted by Navaro et al., (2015) on selenium oxyanion reduction using acetate as carbon source during anoxic biological treatment of Se (IV) amended soil also found Dechloromonas as the dominant genus. Lenz et al., (2008a) reported the proliferation of a selenate-respiring specialist capable of reducing selenate in the presence of high concentrations of sulfate in a UASB reactor treating selenium-contaminated synthetic water under methanogenic conditions. This specialist was identified as Dendrosporobacter quercicolus. This same species was isolated from a subsurface passive bioreactor system treating mining seeps contaminated with 250 – 1000 μg L-1 selenium as selenate (Knotek-Smith et al., 2006). Knotek-Smith et al., (2006) identified 27 different selenate-reducing bacteria from mine-affected environments. Sixteen of them were newly (at the time of publication) identified selenium reducers. Some of these species included, Aeromonas salmonicida, Bacteroides forsythus, Trichococcus pasteurii, Aquaspirillum delicatum, Rhodoferax fermentans, Acetobacterium malicum, Enterobacter amnigenus, Klebsiella pheumoniae, Morganella morganii, Serratia fonticola and Pseudomonas putida. Other bioreactor studies identified some species from the genera, Klebsiella and Citrobacter as capable of reducing selenate as a preferred electron acceptor (Lenz et al., 2009; Zhang and Frankenberger, 2006). The Citrobacter species was capable of reducing both 34 mg/L nitrate and 338 μg/L Se using molasses as the carbon source (Zhang and Frankenberger, 2006). Overall, there is evidence for a wide variety of microorganisms with the capability of selenate reduction. Despite this, most active bioreactors developed for removal of dissolved selenium have used a restricted group of microorganisms as inocula, including either pure cultures or a few strains or mixed microbial communities from other bioreactors treating very different types of wastewater. In general, dissolved selenium removal and utilization of dissolved selenium species by bacteria is under-explored and coal mine sites affected by seepage with elevated concentrations of selenium provide an opportunity to discover new selenate-reducing consortia that can be used on the mine site for mine water treatment.    41 Chapter 2 : Assessment of  Dissolved Selenium Removal Potential of Mine Site Sediment Bacteria   2.1 Synopsis  The Elk Valley located in British Columbia and Cardinal River located in west-central Alberta are regions with major coal mining activities. Open-pit coal mining creates large volumes of waste rock. Samples of waste rock collected from some Elk Valley coal mine sites were found to contain selenium at a mean concentration of 3.12 mg/kg (Hendry et al., 2015). Oxidative weathering of these waste rocks results in the release of selenium and other constituents such as nitrate and sulfate into receiving aquatic environments where they pose potentially serious environmental effects. Removal of selenium from waste rock seepage is a priority for mining companies to prevent the migration of contaminating compounds from the mine site. Various mine water treatment approaches, including active and passive bioreactors, have been developed for the removal of soluble selenium from MIW.  However, the success of water treatment is dependent on seeding these reactors with microbial communities that can effectively transform selenate in the presence of other contaminants to the less bioavailable elemental selenium. Use of sludge sourced from wastewater treatment plants might not be effective since the microbes capable of removing selenium in the presence of competing anions might not be present. The hypothesis of this study was that, soluble selenium reducing microorganisms could be obtained from local sediments on the coal mine sites affected by seepage from the waste rock piles. The hypothesis was that the presence of high levels of dissolved selenium in these environments would select for high numbers of microorganisms capable of removing selenate.  This study investigated the dissolved selenium removal potential of anoxic sediments collected from different vegetated and non-vegetated aquatic environments receiving coal mine seepage water from three different coal mining sites (Fording River & Elkview) in the Elk Valley, British Columbia and Cardinal River in Alberta for screening in order to   42 determine which of these sites are suitable sources of dissolved selenium reducing bacteria. The sites sampled included natural or constructed marshes, creeks and tailings ponds into which waste rock seepage flowed, as well as one natural pristine site that historically had not received any seepage from the mine site. The sites with vegetation were expected to have a greater availability of dissolved organic carbon and therefore support a larger number and diversity of microorganisms including potentially those capable of dissolved selenium removal.  The experimental strategy was to inoculate the sediments into a growth medium containing necessary basal salts and trace elements for selenate-reducing bacteria and the main consitituents of concern (selenate, nitrate and sulfate) at environmentally relevant concentrations with lactate as an efficient carbon source and electron donor. Those sediments that demonstrated a reduction in the concentration of dissolved selenium after a fixed period of time were deemed to harbour bacteria that can remove dissolved selenium in the presence of competing electron acceptors nitrate and sulfate. A denitrifying sludge obtained from a sewage treatment plant on the University of British Columbia, Vancouver campus was used a control.  To determine the potential of microorganisms enriched from these sediments for removal of selenium compounds from the dissolved (aqueous) phase, total dissolved selenium was measured using inductively coupled plasma mass spectrometry (ICP-MS) (USEPA method 6020A-SW-846). This method measures the total dissolved selenium concentration of all dissolved selenium compounds combined in the aqueous phase and cannot distinguish between the different chemical forms of dissolved selenium. This analytical method was used because it is highly sensitive (detection limits in the order of ng/l) for measuring total dissolved selenium at low concentrations, which were typical of the MIW (i.e. less 1 mg/L), without interferences from the many other anions present at much higher concentrations in the medium.    43 2.2 Materials and Methods 2.2.1 Sites, Sampling and Chemical Characteristics Anoxic sediment samples were collected from different aquatic environments located in or close to TECK Coal Limited mines in the Elk Valley, Canada. These mines included; Fording River Operations (FRO), Elkview Operations (EVO) located in British Columbia province and Cardinal River Operations (CRO), located in Alberta province of Canada (Figure 2-1). In total, fifteen (15) samples were collected as grab samples from the surficial sediments at the water sediment interface (at a depth of about 10 - 30 cm below the water/air interface) of different water bodies; natural marshes, wetlands, creeks, ponds and impoundments that have been receiving seepage from coal mine waste rock storage piles (Table 2-1). At each sampling location, before the sediment samples were taken, field water quality parameters were measured at the water sediment interface using YSI Sonde model 600QS (YSI international, Yellow Springs, OH). The measured parameters included; pH, temperature, conductivity, total dissolved solids (TDS), dissolved oxygen (DO), and oxidation-reduction potential (ORP). Afterwards, samples of sediments were removed and put in small wide-mouthed jars with overlying water on top to keep them anoxic. Before the sediment samples were removed, samples of water overlying the sediments were also collected for measuring water chemistry parameters. The water chemistry parameters such as nitrate, nitrite, ammonia, and iron were measured on-site using CHEMets field kits, with catalog numbers; K-6905 Zinc reduction method for nitrate and nitrite, K-1510D direct Nesslerization for ammonia and K-1610D Phenanthroline for iron (CHEMetrics Inc. Midland, VA). Some of the overlying water samples were preserved with nitric acid and stored in a cooler for subsequent total metals analyses at ALS laboratory, Burnaby, Canada. Total metals were measured using inductively coupled plasma mass spectrometry (ICP-MS) (USEPA method 6020A-SW-846). Sulfate was analyzed in UBC laboratory according to standard procedure using turbidemetric method (APHA 4500-SO42− E). The sulfate (SO42−) was precipitated with barium chloride (BaCl2) in acetic acid medium to form barium sulfate (BaSO4) crystals of uniform size. The light absorbance of the barium sulfate suspension   44 was measured at 420 nm using UV-VIS spectrophotometer lambda 25 (PerkinElmer, Waltham, USA). All samples were stored in a cooler with ice whilst en route to the laboratory for further experiments.    Figure 2-1: Map showing the location of the sampling sites, Fording River (FRO), Elkview (EVO), and Cardinal River (CRO). Five samples were collected from Fording River Operation, five samples from Elkview Operation and six samples from Cardinal River Operation.           45 Table 2.1: Description of sample collection sites Site Name Mine GPS Coordinates Sampling Date Description STP South Seep Fording River 50’’17’3’’N and 114”87’3”W June 16, 2014 Mine tailings storage facility Eagle Pond Fording River 50”19’9”N and 114”87’9”W June 16, 2014 Settling pond with input from rock drains and surface runoff Clode Pond Fording River 50’21’2 N and 114’88’2 W June 16, 2014 Settling pond with input from rock drains, direct pit dewatering and some surface runoff.   Smith Pond Fording River 50”17’8”N and 114”88’6”W June 16, 2014 Seepage collection pond at the toe of a waste rock pile Lake Mountain Lake Fording River 50’’22’0’’N and 114’’89’5’’W June 16, 2014 Natural wetland not known to be impacted by mine seepage Bodie Creek Elkview 49’’43’8’’N and 114”50’26”W June 17, 2014 Natural creek that receives surface runoff and drainage of waste rock pile Bodie Downstream Elkview 49”42'51"N and 114”50'17"W June 17, 2014 Lagoon A Elkview 49”45'9"N and 114”52'26"W June 17, 2014 Pond used for fine tailings storage that is not currently active.     Goddard Marsh # 1 Elkview 49”45'36"N and 114”52'27"W June 17, 2014 Natural marsh that receives seepage from waste rock and sediment-pond discharge. Goddard Marsh # 2 Elkview 49”45'36"N and 114”52'31"W June 17, 2014 West Jarvis Pond Cardinal River NA June 18, 2014 Tailing ponds receiving seepage from waste rock Luscar Seep # 1 Cardinal River NA June 18, 2014 Vegetated pond receiving seepage from waste rock Luscar Seep # 2 Cardinal River NA June 18, 2014 A4 spring #1 Cardinal River NA June 18, 2014 Vegetated pond receiving seepage from waste rock A4 Spring # 2 Cardinal River NA June 18, 2014   46 2.2.2 Growth Medium and Culturing After collection, each sediment sample was aseptically inoculated in a sterile basal salt growth medium containing the following constituents of interest; total dissolved Se concentration (0.3 mg/L), total nitrate concentration (40 mg-N/L) and sulfate (500 mg/L) in culture bottles. These concentrations were chosen since they are representative of typical coal MIW. The cultures were prepared by the addition of 10% (w/v) sediment slurry as inoculum into the basal medium. Before inoculation into the culture medium, the sediments were gently stirred with a spatula to achieve homogeneity and then withdrawn into a 10 mL pipet tip with the pointed ends removed. The culture medium was prepared according to Stams et al., (1992), but omitting selenite. Instead of sodium sulfide, ascorbic acid was used to scavenge oxygen from the medium to stimulate reducing condition in the culture medium (Appendix A). The composition of the basal medium included; MgSO4 (0.5 g/L), CaCl2.2H2O (0.11 g/L), Na2HPO4 (0.434 g/L), KH2PO4 (0.128 g/L) and 1 mL trace element solution containing FeSO4.7H2O (0.01 g/L), ZnSO4.7H2O (100 mg/L), CoCl2.6H2O (200 mg/L), MnCl2.4H2O (30 mg/L), Na2MoO4.2H2O (30 mg/L), NiCl2.6H2O (10 mg/L), CuCl2.2H2O (10 mg/L), H3BO3 (300 mg/L). The culture medium was supplemented with 10 mL of a vitamin mixture solution containing, pyridoxamine (500 mg/L), cyanocobalamine (Vitamin B12) (100 mg/L), riboflavin (100 mg/L), biotin (20 mg/L), nicotiamide (200 mg/L), p-aminobenzoic acid (100 mg/L), thiamin (Vitamin B1) (200 mg/L) and panthotenic acid (100 mg/L) as well 1 g/L of yeast extract. Lactate was used as the carbon source with the concentration of 600 mg/L based on the reaction stoichiometry for microbial metabolism (Equations 2.1- 2.4). The resulting solution was sparged with nitrogen gas for 10 mins to remove any oxygen present. After inoculation of the sediments in culture bottles, the bottles were filled to the brim and sealed with butyl rubber. Afterwards, the cultures were subjected to static incubation at 25 oC in the dark. The medium without any sediment served as the negative control. Denitrifying sludge from a pilot biological denitrifying reactor located at UBC south campus was used as a positive control for denitrification. Duplicate cultures were grown for each sediment sample.      47 Respiration reactions:  CH3CHOHCOO− + 12/5NO3− +2/5H+            3 HCO3− + 6/5 N2 + 6/5 H2O …………..2.1                                      ΔGfo = −1291 kJ/mol CH3CHOHCOO− + 2SeO42− +2H+             3HCO3− +2Se0 +2H2O ……………….........2.2                                      ΔGfo  = −834 kJ/mol CH3CHOHCOO− + SO42−                 3HCO3− + 3/2HS− + 1/2H+ ……………………....2.3 ΔGfo  = −107.62kJ/mol   Cell synthesis reaction: 1/12 CH3CHOHCOO− + 1/20 NH4+ + 1/30 CO2            1/30 HCO3− + 1/20 C5H7O2N + 7/60 H2O ……………….2.4                    C5H7O2N is assumed to be the empirical formula for bacterial cells (Rittman and McCarty 2001).     2.2.3 Analytical Methods Samples were collected for total dissolved selenium concentration analysis levels after three days. Total dissolved selenium concentration was measured by inductively coupled plasma mass spectrometry (ICP-MS) at the ALS Laboratory at Burnaby, BC (USEPA method 6020A-SW-846).       48 2.3 Results  2.3.1 Sample Location Characteristics The results revealed that the sediments were collected from diverse environments with different physical and chemical properties (Tables 2.2 and 2.3). Temperatures within the sediments at the time of sampling ranged from 7.1 to 18.8 oC (Mean 11.5 oC, standard deviation 3.0 oC). This shows that there was a wide variation in the temperatures of these locations. A4 spring #1 had the lowest temperature whilst West Jarvis Pond had the highest temperature, both of which are located on the Cardinal River Operations (CRO) coalmine. The pH of the sediment pore water was circum-neutral for all sites, ranging from 6.8 to 8.2. The TDS concentrations in the water just above the water sediment interface ranged from 0.005 to 1.669 g/L with a mean of 0.77 g/L and standard deviation of 0.65 mg/L, which reflects a wide range of salinities of the sediments.  The second sample taken from the natural marsh on the Elk View mine, Goddard Marsh #2, had the lowest TDS concentration, whilst A4 Spring, a vegetated pond receiving seepage from waste rock on CRO, had the highest TDS concentration.  The dissolved oxygen concentration varied widely and ranged from 0.61 mg/L to 13.24 mg/L with a mean of 6.19 mg/L and standard deviation 5.25 mg/L.  Goddard Marsh #2 had the lowest dissolved oxygen concentration and A4 spring #2 had the highest DO concentration.    49      Table 2.2:  Chemical characteristics of sampling location  N.D: Not Determined      Site/Parameters Temp.,  oC Cond., ms/cm TDS, g/L Salinity, ms/cm DO, % DO, mg/L pH ORP,mV Nitrate, mg-N/L Sulfate, mg/L Tot. Dissolved Se, mg/L Fording River Operations (FRO) Eagle Pond 13.3 1.99 1.67 N.D 69.7 7.23 7.15 -11 30 1141 0.34 Lake Mountain Lake 12 0.14 0.12 N.D 17 1.6 7.03 -25 0 16 0.00046 STP, South West Seep 9.79 0.85 0.78 0.6 22.3 2.32 6.96 -107 0 335 N.D Clode Pond N.D N.D N.D N.D N.D N.D N.D N.D 30 174 0.051 Cardinal River Operations (CRO) Lanscar Seep 11.47 0.58 0.50 0.38 104.6 11.38 8.2 130 0.4 135 0.016 A4 Spring #1 7.09 2.00 1.98 1.59 100.8 12.1 6.8 175.4 2.5 792 0.14 A4 Spring #2 11.1 0.93 0.82 N.D 120.8 13.24 7.56 25 0.4 ND 0.083 West Jarvis Pond 18.78 0.34 0.25 0.19 17.2 1.48 7.62 27.2 0 189 N.D Elkview Operations (EVO) Goddard Marsh #1 9.78 0.61 0.57 N.D 5.4 0.61 7.08 -120 0 244 0.030 Goddard Marsh #2 8.88 0.01 0.005 N.D 38 4.27 7.14 -35 0 278 0.0019 Lagoon A 11.85 0.43 0.37 N.D 10 1.08 7.04 -107 0 58 0.0029 Bodie Creek 12.83 1.65 1.40 N.D 121 12.78 7.81 73.8 150 779 0.33   50            Table 2.3: Chemical characteristics of sampled sediments – Total metals concentration   Sample sites Calcium (Ca)-Total,  mg/L Iron (Fe)-Total,  mg/L     Magnesium    (Mg)- Total, mg/L Phosphorus (P)-Total, mg/L Potassium (K)-Total,  mg/L Sodium (Na)-Total, mg/L Fording River Operations (FRO) Eagle Pond 308 0.27 262 <0.30 6.11 15.7 Lake Mountain Lake 320 25.2 37.6 2.31 5.05 1.02 STP, South West seep 206 0.064 74.6 <0.30 9.42 8.66 Clode Pond 117 2.47 47.3 <0.30 9.18 15.6 Cardinal River Operations (CRO) Lanscar Seep 132 42.8 36.4 4.15 2.47 127 A4 Spring #1 292 36.7 58.6 4.90 6.75 396 A4 Spring #2  172 1.67 78.2 <0.60 4.89 357 Elk View Operation (EVO) Goddard Marsh #1 187 30.4 58.6 1.06 3.84 6.89 Goddard Marsh #2 144 28.7 57.4 1.06 2.56 7.81 Bodie Creek 272 0.366 162 <0.30 6.64 12.7 Bodie Downstream 194 0.439 101 <0.30 3.07 6.14   51  Chemical analyses of the overlaying water for nitrate were done at the time of sampling, whilst total dissolved selenium and sulfate were analyzed on samples shipped to the commercial laboratory, ALS and UBC laboratory respectively. The nitrate concentration ranged from 0 – 150 mg/L. Bodie Creek had the highest nitrate level of 150 mg/L with eight of the sites having nitrate concentration less than 1 mg/L. Sulfate concentration in the overlying waters ranged from 16 mg/L to 1141 mg/L. Lake Mountain Lake, which was the location not known to be affected by coal MIW, had the lowest sulfate concentration and Eagle Pond had the highest sulfate concentration. The total dissolved selenium concentrations ranged from 0.00046 mg/L to 0.36 mg/L. Again, Lake Mountain Lake had the lowest concentration and Eagle Pond water had the highest concentration of total dissolved selenium. Overall, Eagle Pond and Bodie Creek had the highest concentrations of selenium, nitrate and sulfate in the overlying water at sediment water interface. The overlying water from Eagle Pond had 0.36 mg/L total dissolved Se, 30 mg/L nitrate and 1141 mg/L sulfate whilst Bodie Creek had 0.329 mg/L of total dissolved selenium, 150 mg/L nitrate concentration and 779 mg/L of sulfate. Of all the total metals measured, Ca was present in the highest concentrations, followed by Mg, Na, Fe, K and P. Calcium concentrations ranged from 124 – 320 mg/L, with the natural wetland, Lake Mountain Lake having the highest calcium concentration and Lagoon A with the lowest concentration. Eagle pond had the highest concentration of magnesium ions. Sodium concentration in the overlying waters ranged from 1.2 – 396 mg/L with the highest levels in A4 spring #1 and A4 spring #2 but lowest in Lake Mountain Lake. Potassium concentrations ranged from 2.47– 9.42 mg/L. Phosphorus concentration was below the detection limit in five samples, with the highest levels in A4 spring #2, 4.90 mg/L. Total dissolved iron concentrations ranged from 0.064 – 42.8 mg/L.     52 2.3.2 Batch Studies of  Dissolved Selenium Removal The results indicated that all fifteen sediments sourced from different aquatic environments removed total dissolved Se from the aqueous phase to some extent (Figure 2-1). The sediments from Bodie Creek, Lagoon A and Smith Pond removed total dissolved selenium to below the detection limit (0.00010 mg/L) of the analytical method within 72 hours and achieved removal extents higher than that achieved by the Denitrifying Sludge (95%).    Figure 2-2: Extents of total dissolved selenium removal after 72 hours measured in sediment slurries inoculated into growth medium. (Raw total dissolved selenium concentration data is provided in Appendix B, Table A.2.1.)   0%10%20%30%40%50%60%70%80%90%100%% Dissolved selenium removedInocula source  53 Six other sediments achieved between 90 – 95% total dissolved selenium removals, which indicated that most of these aquatic sediments affected by coal mining harbor the potential to remove soluble selenium under optimal conditions. Although only one non-impacted site was included in the study, it is interesting that the sediment from Lake Mountain, a natural pristine wetland, had the lowest total dissolved selenium removal extent (23%). The field chemistry data indicated that Lake Mountain Lake had the lowest concentrations of TDS and the contaminants of interest; nitrate, sulfate and total dissolved Se. There was no change in total dissolved selenium concentration in the negative control growth medium without any inoculum indicating that the sediments contributed to selenium removal.   2.3.3 Correlation of Dissolved Selenium Removal with Chemical Characteristics  To see if there were any relationships between the extents of total dissolved selenium removal and the chemical characteristics of the sampling locations, correlations were evaluated using Spearman’s rank correlation coefficient (Table 2.4). Most correlations were week (less than 0.50). Positive correlations were detected between total dissolved selenium removal extent and pH > Fe > ORP, whilst negative correlations were found between total selenium removal extent and Ca > TDS > Mg > Na, DO > K > SO42− > total NO3− and NO2−.       54  Table 2.4: Spearman’s rank correlation coefficient table for extent of total dissolved selenium removal and chemical charateristics of the sediment sample locations.   % Total Diss. Se Removal Extent Tot. Diss. Se  TDS  Tot. Nitrate and Nitrite  Sulfate DO pH ORP Calcium Iron Magnesium Potassium Sodium % Tot. Diss. Se Removal 1.00                         Tot. Diss. Se -0.05 1.00                       TDS  -0.23 0.95 1.00                     Tot. Nitrate and Nitrite  -0.02 0.85 0.78 1.00                   Sulfate  -0.11 0.82 0.76 0.48 1.00                 DO -0.17 0.58 0.57 0.79 0.55 1.00               pH 0.47 0.25 -0.06 0.38 -0.05 0.33 1.00             ORP 0.03 0.47 0.40 0.67 0.24 0.72 0.40 1.00           Calcium -0.52 0.23 0.28 0.09 0.46 0.26 -0.30 0.26 1.00         Iron 0.30 -0.53 -0.35 -0.24 -0.35 -0.13 0.01 0.25 -0.28 1.00       Magnesium -0.20 0.77 0.64 0.48 0.91 0.56 0.17 0.18 0.52 -0.63 1.00     Potassium -0.13 0.72 0.67 0.47 0.63 0.41 -0.26 0.16 0.03 -0.53 0.55 1.00   Sodium -0.17 0.72 0.80 0.68 0.50 0.73 0.26 0.73 -0.05 0.04 0.35 0.41 1.00    55 2.4 Discussion 2.4.1 Possible Mechanisms for Observed Dissolved Selenium Removal Since there was no measureable difference between the total dissolved selenium concentrations in the negative control at the beginning and end of the culture period, it was assumed that the removal of Se was due to the presence of sediments. Selenium can be removed through biotic and abiotic mechanisms. Possible abiotic mechanisms of removal of selenium species from the aqueous phase include sorption, precipitation or reduction by inorganic particles found in anaerobic sludge (Astratinei et al., 2006) and sediments. Abiotic adsorption of selenate under anoxic conditions in sediments (Baldwin and Hodaly, 2003; Frankenberger and Hanna, 1998; Zhang and Moore, 1997) and anaerobic granular sludge (Astratinei et al., 2006; Kuan et al., 1998) removes only a small amount of selenate from aqueous phase compared to selenite (Bruggman et al., 2005; Bruggman et al., 2002). Also, inorganic particles such as sediment oxides bind relatively little selenate (Zhang and Moore, 1997) and Fe2+ and Mn2+ do not directly reduce selenate (White and Dubrovsky, 1994). It is possible that the mechanism for removal of dissolved selenium were biological, which involved microbial transformation of selenium species through metabolic pathways. Possible mechanisms for biological removal of selenium from the aqueous phase included dissimilatory selenate reduction, assimilatory selenate reduction, and detoxification. Selenate can be used by some microorganisms for dissimilatory reduction to selenite for generation of energy for cell maintenance and growth. Examples of microorganisms known to perform dissimilatory selenate reduction are T. selenatis (Macy, 1993) and Sulfurospirillum barnesii (Oremland et al., 1999). Many of the microorganisms previously demonstrated to respire on selenate or selenite were found to produce elemental Se as the end product (Lenz et al., 2008a; Fujita et al. 2002; Losi and Frankenberger, 1997). However, it is also possible that selenate was assimilated into the cells of selenium-dependent microorganisms growing in the sediment cultures where it was used for production of selenocysteine and selenoproteins, such as glutathione peroxide, thioredoxin reductase, and selenophosphate synthetase (Nancharaiah and Lens,   56 2015; Labunskyy et al., 2014). Another potential pathway for biological transformation of selenate is through detoxification. Even though selenium is an essential element, there is a fine line between concentration levels considered to be essential and toxic. The concentration of selenium in the culture media used throughout the experiment ranged between 1 – 0.3 mg/L, which can be toxic to some microorganisms. Selenate/selenite concentration in the range of 100 μg/L can be toxic to aquatic organisms (Chapman, 2010). Detoxification is often reported in the case for aerobic transformation of selenite and methylation of elemental selenium species to volatile compounds (dimethylselenide or dimethyldiselenide) (Eswayah et al., 2016). Alkylation of dissolved selenate/selenite leads to the formation of volatile dimethylselenide and dimethyldiseleinde or selenides that react with metals to form insoluble metal selenide (Lenz et al., 2008c). Anaerobic granular sludge has been reported to form alkylated selenium compounds that remained dissolved in aqueous phase before volatilization (Lenz et al., 2008d). These dissolved methylated Se species can contribute to the measurement of total dissolved selenium, as well as selenate and selenite. Several bioreactor studies on selenium removal from the aqueous phase found that using environmental sediments as inoculum resulted in selenate removal from the dissolved phase under anoxic conditions, and this was attributed to selenate reduction to elemental selenium by microbial consortia (Siddique et al., 2007, 2006; Lucas and Hollibaugh, 2001; Steinberg and Oremland, 1990). The mechanisms of dissolved Se removal were deemed to be biological because there was no significant change in selenate concentration in autoclaved sediments for these experiments. Other bioreactors studies using mixed microbial consortia from anaerobic sludge also found that selenate was reduced to elemental selenium under anoxic, ambient temperature, neutral pH conditions (Lenz at al., 2008a; Astratinei et al., 2006; Rege et al., 1998). Of the three potential biotic transformation mechanisms, dissimilatory selenate reduction to elemental (insoluble) selenium through selenite intermediary is considered to be a major mechanism for selenate removal in this experiment. However, it was not possible to verify this experimentally since access to the appropriate instrumentation for   57 determining speciation of soluble selenium was not available, and analysis of the sediment solids after culturing was not possible due the interference from coal particles.   Nevertheless, the results demonstrate that selenium was removed from the aqueous phase and likely most of the removed selenium ended up in the solid phase associated with cell biomass or precipitates.  2.4.2 Performance of the Different Sediments for Dissolved Selenium Removal  The initial screening experiment showed that the potential for soluble selenium removal was widespread in diverse aquatic environments on the coal mine sites.  Selenium removal was observed for sediments from both contaminated and pristine aquatic environments, but the extents of reduction were higher in the coal mine-affected sediments compared to the sediment from the one non-affected environment. Variability between percent reductions of total dissolved selenium might have been due to both the numbers of organisms in those sediments and the types of organisms. For instance, due to the presence of selenium in the coal MIW, the affected sediments might have more abundant and more active microorganisms than non-affected sediment. All the sediments that achieved high (greater than 90%) removal extents were sourced from mine seepage impacted aquatic environments where the concentrations of total dissolved selenium at the sediment water interface were above 1 µg/L. The total dissolved selenium concentration in the non-impacted site was less (1 µg/L) than that measured in the impacted sites. However, it is possible that, given more incubation time, the non-impacted sediments would achieve higher levels of dissolved selenium removal. Only weak correlations were found between the extents of total dissolved selenium reduction and chemical properties of the water at the sediment water interface. Based on concentrations of total dissolved selenium, nitrate and sulfate, the most contaminated sites, Bodie Creek and Eagle Pond, achieved similar total dissolved selenium removal extents as the least impacted sites (Goddard Marsh and Lagoon A).  It was not possible to sample the influent into any of the impacted sites, but it is possible that the seepage water entering these impacted sites contained total dissolved selenium concentrations   58 well above 1 µg/L and this was enough to promote the presence of dissolve selenium reducing bacteria. Our observations are consistent with findings of the study by Ike et al., (1999), where selenate-reducing activities of bacteria isolated from pristine aquatic environments were much lower than those for bacteria isolated from Se-contaminated environments. Despite the Bodie Creek and Eagle Pond sediments having the potential for dissolved selenium removal, the concentrations of total dissolved selenium were high in these environments, versus Goddard Marsh, for example. This might be due to the availability of more organic carbon in Goddard Marsh or due to the retention times within these aquatic environments that would affect the rates and extents of dissolved selenium reduction in them. Unfortunately, total dissolved carbon was not measured in any of the sites, and retention times were unknown. The capability of dissolved selenium removal within all sediments of these receiving environments could make the case for the use of them as passive treatment systems with the appropriate amendments and retention times to support active soluble selenium removal. There were strong positive correlations between the concentrations of nitrate, sulfate and selenate (as well as total dissolved solids) within the sediment water. This is due to these chemical compounds being co-contaminants that are released from coal mine waste rock through similar mechanisms.  It is also possible that sites where sediment bacteria are more active are capable of achieving denitrification, selenate reduction and sulfate reduction.  Since whole sediments were inoculated into growth medium containing three electron acceptors: nitrate, selenate and sulfate, the dissolved selenium removal capabilities of the sediments were most likely as a result of the combined activities of many different types of bacteria including denitrifiers, selenate-respiring bacteria, or sulfate-reducing bacteria, either working in parallel or syntrophically. All of these groups of bacteria are known to have the capability to reduce soluble selenium oxyanions. The sediments sourced from STP South Seep removed less soluble selenium than the other mine-affected sediments.  The pore water collected from STP South Seep had no   59 nitrate or total dissolved selenium present at the time of sample collection. Perhaps, this seep is not affected by heavily contaminated minewater and thus there has been little selection pressure to encourage the growth of microorganisms that use nitrate or selenate. Since the duration of the experiment was only 72 hours, it is possible that, given more time, enrichment of soluble selenium reducing bacteria and complete soluble selenium removal would be achieved by STP south sediments.   The results of this experiment showed that most aquatic environments receiving coal mine seepage water have the potential for the removal of total dissolved selenium and can be considered for use as inoculum for coal MIW treatment. Subsequent experiments investigated the capability of selected sediment bacteria to remove soluble selenium species in the presence of nitrate, and determined which taxonomic groups within the microbial enrichments were responsible for selenium removal, with or without nitrate. The sediments chosen for the subsequent experiments were: 1) Smithe Pond (FRO, non-vegetated; 2) West Jarvis Pond (CRO, non-vegetated); 3) Bodie Creek (EVO, non-vegetated); 4) Lagoon A (EVO, non-vegetated); 5) Eagle Pond (FRO, non-vegetated) and 6) Goddard Marsh (EVO, vegetated). The factors used for the selection included, extent of soluble selenium removal, mine location (at least an inoculum from each of the three mines) and attribute of the environment (whether vegetated or non-vegetated).           60 Chapter 3 : Enriching of Microbial Consortia from Mine- Affected Sediments with the Capacity for Removing Dissolved Selenium    3.1 Synopsis The objective of the experiment described in this chapter was to enrich for microbial consortia from a few selected sediments shown in the previous chapter to achieve high extents of removal of total dissolved selenium from the aqueous phase. Nitrate is a co-contaminant of coal MIW water and is known to inhibit dissolved selenium removal in previous attempts to biologically treat these waters. To overcome this, one hypothesis is that bacteria using selenate as their preferred electron acceptor would not be inhibited by nitrate and these would be suitable organisms to use in treatment systems for coal MIW containing both selenate and nitrate. Some example candidates were mentioned in Chapter 1, such as T. selenatis, which has a selenate reductase, SerABC, as well as a separate nitrate reductase (Rech and Macy, 1992). To enrich for such organisms from the coal mine sediments, growth medium containing selenate as the sole terminal electron acceptor was used. This would reveal organisms that can use selenate as an electron acceptor. Additionally, a second growth medium with both selenate and nitrate as terminal electron acceptors and the same electron donor/carbon source concentration ratio as in the previous medium was used. Comparing the rates of total dissolved selenium removal between the two media was done in order to determine if organisms present in any of the sediments were capable of reducing total dissolved selenium without inhibition from nitrate. The experiments also revealed the types of microorganisms that were enriched, and how this was affected by the presence of nitrate.  The overall goal was to select sediment enrichments capable of removing soluble selenium in the presence of nitrate with no or little inhibition to use in subsequent experiments for removal of soluble selenium from actual coal MIW (Chapters 4 & 5).   61 The inocula used were those sourced from: 1) Smithe Pond; 2) West Jarvis Pond; 3) Bodie Creek; 4) Lagoon A; 5) Eagle Pond and 6) Goddard Marsh. These sediments were selected based on the initial results of the screening experiment conducted in Chapter 2.   3.2 Materials and Methods  3.2.1 Enrichment of  Microbial Consortia from Sediments Six of the fifteen sediments from the previous experiment sourced from mine seep locations, which had been stored under anoxic conditions at room temperature (~20 oC) in the laboratory, were used to prepare enrichments for the purpose of identifying and selecting consortia capable of removing soluble selenium in the presence of nitrate. Duplicate experiments for each sediment and growth medium were performed. The growth medium was prepared according to Stams et al., (1992), but omitting selenite and using phosphate instead of carbonate as the buffer (Appendix A). The six inocula were cultivated in two different types of growth media: one growth medium contained selenate as the sole terminal electron acceptor (GM1) and the second growth medium contained both selenate and nitrate as terminal electron acceptors (GM2). The growth medium was a defined mineral medium with the following composition (g/L): MgSO4 0.5, CaCl2.2H2O 0.001, KHPO4 1, KH2PO4 0.2, FeSO4.7H2O 0.001, yeast extract 1g/L and 10 mL of trace element solution containing (mg/L) ZnSO4.7H2O, 100 CoCl2.6H2O, 200, MnCl2.4H2O, 30, Na2MoO4.2H2O, 30, NiCl2.6H2O, 10, CuCl2.2H2O, 10, H3BO3, 300. The nominal influent concentrations of the contaminants of interest were NO3-, 40 mg-N/L, and SeO42-, 1 mg-Se/L. These concentrations were chosen as typical environmentally relevant concentrations. After autoclaving, the basal medium was supplemented with 600 mg/L lactate and 10 mL of filter-sterilized vitamins solution mixture with the following composition (mg/L); biotin 20, nicotiamide 200, p-aminobenzoic acid 100, thiamin 200, panthotenic acid 100, pyridoxamine 500, cyanocobalamine 100, riboflavin 500. A 0.5 g/L L-cysteine and 1 mL of resazurin filter sterilized solution were added to the growth medium as the reducing agent and redox indicator respectively. The resulting solution was sparged with nitrogen gas for about 10   62 minutes to remove any oxygen present. Twenty-five mL of sediment slurry (inocula) were first pipetted into a 250 mL of autoclaved culture bottles and then filled with the growth medium to the brim.    In some related experiments reported in the literature (Zhang et al., 2008; Kashiwa et al., 2000), optical density (OD) measurements at wavelength greater than 600 nm were used to determine whether each starting culture bottle received the same biomass concentration. For this experiment, because of the high concentrations of both organic and inorganic suspended solids, which readily settles, the OD measurement could not be used to satisfactorily estimate the biomass concentration. Instead, the same volume of homogenous sediment slurry was transferred into the culture bottles making up 10% of the working volume (Nassingaro and Häggblom, 2007).  Also, measuring the VSS concentration was also not satisfactory since it was found that the VSS concentration measured for all the samples were lower that the negative control sample without any biomass. This is because in heating samples containing high concentration of organic and inorganic solids from 103 oC to 560 oC, some of the inorganic compounds experience weight loss through actual decomposition or loss of waters of hydration (Middleton and Lawrence, 1977). Thus, the experimentally measured VSS was found to be inaccurate estimator of bacterial mass concentration.  The bottles were sealed with butyl septa caps and then wrapped with aluminium foil before being subjected to static incubation at 30 oC. Samples were collected at time intervals 0, 4, 8, 12, 24 and 48 hours for nitrate-plus nitrate-N analysis and time intervals 0, 4, 8, 12, 24, 48 and 72 hours for total dissolved selenium concentration analysis. The samples were removed from the culture bottles using a syringe and needle to draw 10 mL samples of the gently mixed medium (by turning the bottled upside down a couple of times) and filtering it through 0.45 μm nitrate cellulose membrane syringe filter (GE Health Care Life Sciences, USA). Six mL of filtered sample volume were preserved with one drop of analytical grade nitric acid and stored in the fridge at 4 oC until total dissolved selenium analysis. Fifteen mL of unfiltered samples were collected and stored in the freezer at -20 oC for DNA extraction and sequencing.      63 After 72 hours, the culture bottles were decanted into a beaker and finally discarded and 25 mL of biomass was pipetted and transferred into freshly prepared growth medium. This was repeated twice resulting in a total of three passages. The experimental design is shown below (Table 3.1).  Table 3.1: Experimental design for enrichment of selenate-reducing bacteria Treatment Number Sediment Source Growth Medium Number of Replicate Cultures Number of Passages 1 Goddard Marsh Selenate only 2 3 2 Goddard Marsh Selenate and Nitrate 2 3 3 Lagoon A Selenate only 2 3 4 Lagoon A Selenate and Nitrate 2 3 5 Bodie Creek Selenate only 2 3 6 Bodie Creek Selenate and Nitrate 2 3 7 Smith Pond Selenate only 2 3 8 Smith Pond  Selenate and Nitrate 2 3 9 West Jarvis Pond Selenate only 2 3 10 West Jarvis Pond Selenate and Nitrate  2 3 11 Eagle Pond Selenate only 2 3 12 Eagle Pond Selenate and Nitrate 2 3   3.2.2 Analytical Methods Total dissolved selenium concentration was measured by inductively coupled plasma mass spectrometry (ICP-MS) at ALS Laboratory in Burnaby, BC (USEPA method 6020A-SW-846). Total nitrate plus nitrite concentrations were measured using Hach 8171- Cadmium reduction method (Hach company, Loveland, CO). The Hach method (NitraVer 5TM high range) is a modification of the cadmium reduction method (APHA   64 4500 – NO3− E) but using gentistic acid in place of 1-naphthylamine. The intermediate diazonium salt formed reacts with genistic acid to form an amber-coloured compound. The absorbance was read at 400 nm using the UV-VIS spectrophotomer lambda 25 (PerkinElmer, Waltham, USA). All the reagents have been combined in a single powder that is added to the samples, which are then shaken for 1 min followed by waiting for 5 min for color development before reading the absorbance.   3.2.3 DNA Extraction and Illumina Sequencing of 16S rRNA Gene Amplicons.   Genomic DNA was extracted using the Fast DNA spin kit by following the manufacturer’s protocol. After the extraction, the DNA was quantified by using a Qubit 3.0 fluorometer (ThermoFisher, USA). The extracted DNA was stored at -20 oC until subsequently use in 16S rRNA and whole DNA sequencing (the latter results are reported in Chapter 6). Amplicons for the V4 variable region of the 16S rRNA gene were produced from target DNA by polymerase chain reaction (PCR) with primers: 515f 50 GTGCCAGCMGCCGCGGTAA 30, 806r 50 GGACTACHVGGGTWTCTAAT 30 using methods described in (Caporaso et al., 2012). These primers were designed to target the bacterial community. Amplicons were sequenced using Illumina MiSeq technology by microbiome INSIGHTS, Vancouver, BC, Canada. For the 16S rRNA amplicon sequences, all pre-processing and sequence quality control steps were performed using USEARCH (v 9.0.2132, 32 bit for Linux) according to the UPARSE pipeline (http://drive5.com/usearch/manual/uparse_pipeline.html;date accessed 1Oct 2016) (Edgar, 2013). Briefly, paired end reads were combined as suggested by the uparse pipeline and unpaired reads or reads with a maximum expected error probability >1 were removed from the analysis. As suggested by (Huse et al., 2010), the remaining sequences were pre-clustered using the furthest neighbour algorithm with 1% sequence dissimilarity as the threshold to prevent over estimation of OTU richness, using the cluster_smallmem command. OTUs were assigned using the UPARSE greedy algorithm for an OTU definition of 97% sequence similarity. Although this step also removes   65 chimeras, a dedicated chimera removal step was used additionally post OTU clustering using the UCHIME 2 algorithm with SILVA gold dataset as reference (Edgar, 2016; Edgar et al., 2011). Global singleton OTUs (those that are represented by a single sequence in the entire dataset) were removed due to their unknown nature. The bacterial OTUs were classified to phylum, class, family, and or genus level using the Ribosomal Database Project Bayesian classifier (train set 14) with a 60% confidence threshold (RDP; http://rdp.cme.msu.edu/). Following classification, sequences not classified as bacteria were removed from the dataset. All samples were subsampled to the same total number of reads (30,000) per sample using the MOTHUR subroutine subsample to eliminate biases of alpha diversity estimations (Schloss et al., 2009).  3.2.4 Theoretical Considerations for Selenate Removal through Microbial Reduction  3.2.4.1. Stoichiometry Dissimilatory selenate and nitrate reduction can be represented by chemical equations that describe the oxidation of an organic carbon source and the synthesis of bacterial cells. For this study, the carbon source used was lactate. Equations 3.1 and 3.2 give denitrification and selenate reduction reactions for production of energy.  1/12 CH3CHOHCOO− + 1/5 H+ + 1/5 NO3− ⟶ 1/6 CO2 + 1/10 N2  + 1/12 HCO3− + 4/15 H2O  …..……………………(3.1) ΔGfO = −104.49 kJ/mol 1/12 CH3CHOHCOO− + 1/3H+ + 1/6 SeO42−  ⟶ 1/6 CO2 + 1/6 Se + 1/12 HCO3− + 1/3 H2O         ………...........................(3.2) ΔGfO = −63.93 kJ/mol The overall energy equation (summation of Equations 3.1 and 3.2) based on the theoretical reaction stoichiometry is given by:   66 0.167 CH3CHOHCOO−  + 0.167 SeO42− + 0.2 NO3− + 0.533 H+ ⟶ 0.333 CO2 + 0.167 HCO3− + 0.167 Se + 0.1 N2 + 0.60 H2O .....……………………..(3.3) ΔGfO = −168.43 kJ/mol  The synthesis of bacterial cells from lactate is given by the equation: 1/12 CH3CHOHCOO−  + 1/20 NH4+   + 1/30 CO2   ⟶  1/30 HCO3−  + 1/20 C5H7O2N** + 7/60 H2O    .……………………...(3.4)                     The formula C5H7O2N is an empirical chemical formula for bacterial cells.  Assuming 40% electron equivalents are used for cell synthesis and 60% used for energy, the overall equation becomes (Rittman and McCarty, 2001 Page 141). It was assumed that the electron equivalence from lactate was distributed equally for selenate and nitrate reduction.  0.10 CH3CHOHCOO−  + 0.1 SeO42− + 0.12 NO3− + 0.32 H+ ⟶ 0.20 CO2 + 0.1 HCO3− + 0.1 Se + 0.06 N2 + 0.36 H2O ……………………….(3.5)  ΔGfO = −168.43 kJ/mol 0.0332 CH3CHOHCOO−  + 0.02 NH4+ + 0.0132 CO2  ⟶ 0.0132 HCO3−  + 0.02 C5H7O2N**  + 0.0468 H2O   …………………………(3.6) The overall energy and cell synthesis equation is given by: 0.133 CH3CHOHCOO−  + 0.1 SeO42− + 0.12 NO3− + 0.32 H+ + 0.02 NH4+ ⟶ 0.187 CO2 + 0.113 HCO3−  + 0.02 C5H7O2N** + 0.1 Se + 0.06 N2 + 0.407 H2O …………………..(3.7)  **  Equations 3.4, 3.6 and 3.7 do not have net Gibbs free energy because the Go value for microbial cells is not available in the literature.     67 3.1.4.2 Kinetic Models for Rates of Nitrate and Total Dissolved Selenium Removal  Since nitrate and selenate are electron acceptors for microbial growth, the rates of their removal are tied to the rate of microbial growth, rX = dX/dt, where X is the concentration of microorganisms in M/L3. Since microorganisms grow by doubling, their growth rate is exponential: rX = µX, where µ is defined as the cell-specific cell growth rate (M/M T). In practice, microbial growth is constrained by the availability of substrate or the major limiting nutrient. In most instances, this is the electron donor, which in this case is lactate. The Monod kinetic expression relates the rate of substrate utilization, rS, to the concentration of substrate, S, and the concentration of the microorganisms (X):   rs = −μm SXKs+S                                                                                                                    ……(3.8)  rs = rate of substrate utilization, M/L3.T;  μm  = maximum cell-specific substrate uptake rate, T-1;  S = soluble organic carbon concentration, M/L3;  X = bacteria concentration, M/L3; and Ks = half-velocity coefficient, M/L3.   The Monod kinetic expression is neither zero nor first order with respect to the substrate concentration, but something inbetween. At high S, such as at the beginning of the growth experiment, and depending on the value of KS, the Monod expression tends towards zero order. When S decreases to much less than KS, such as at the end of a batch growth experiment, the Monod expression tends towards first order with respect to S.  The cell growth rate is linked to the rate of substrate uptake, and also depends on the rate of cell decay. Cell decay occurs due to endogenous metabolism and cell death. The equation that describes the relationship between bacterial growth and substrate utilization is given by: rx = −Yrs − bX                                               ………………………………………………(3.9)    68 rx = Y (μmSXKs+S) − bX                                         ………………………………………………(3.10)  Where rx = volumetric rate of bacterial cell growth, M/L3.T; Y = yield coefficient of cells produced per unit substrate consumed, M/M; and b = decay coefficient, T-1.   The rates of nitrate and selenate removal are tied to the rate of substrate uptake due to their relationship in the stoichiometric Equation 3.7 above.  𝑟𝑁𝑂3- = 𝑌𝑁𝑂3-𝑆 𝑟𝑆                                            …………………………………………(3.11) Where, the yield coefficient, YNO3−/ S, of the mass or moles of nitrate reduced per mass or moles of lactate used is derived from Equation 3.5 or 3.7. The rate expression for reduction of nitrate according to the standard model of cell growth and Monod kinetics has the following form: 𝑟𝑁𝑂3- = 𝑌𝑁𝑂3-𝑆 𝜇𝑚𝑆𝐾𝑆+𝑆𝑋               ……………………………………………………(3.12)  The maximum cell-specific growth rate, µm, and the Monod constant, KS, depend on the nature of the substrate, S, and the types of microorganisms and will differ between different electron donors. A similar equation can be derived for the rate of selenate reduction. 𝑟𝑆𝑒 =  𝑌𝑆𝑒𝑆 𝜇𝑚𝑆𝐾𝑆+𝑆𝑋                   ……………………………………………………(3.13) The Monod rate expression above is valid only when lactate is limiting the growth rate of selenate-reducing bacteria and denitrifiers. However, there is a concentration at which the electron acceptor, such as selenate or nitrate, can begin to limit the growth. This so- called critical electron acceptor concentration must be considered in determining the limits of applicability for the carbon limited growth model. In other words, that lactate was the limiting substrate in these batch experiments was an assumption. It is possible   69 that nitrate or total dissolved selenium were limiting the rate of denitrification and selenate reduction.  By performing mass balances on the substrate and bacteria in a batch reactor, the following equations describe the change in concentration of substrates and bacterial concentration with time in the batch reactor (Rittman and McCarty, 2001; Middleton and Lawrence, 1977).  dSdt = −μm S XKs+S                                               ………………………………………………(3.14)   dXdt =  −YdSdt− bX                                     ………………………………………………(3.15)  dCdt=  α (dSdt) +  β (dXdt)                            …………………………………………........(3.16)  Where S = organic carbon concentration, M/L3; X = bacterial mass concentration, M/L3; and C = electron acceptor concentration, M/L3; α = mass of electron acceptor consumed to oxidize one unit mass of organic carbon, M/M; β = mass of organic carbon required to synthesize one unit mass of bacterial cells, M/M.  By fitting concentration of cells (X), lactate (S) and total nitrate plus nitrite or total dissolved selenium versus time to the kinetics model, kinetics parameters (μm and Ks) can be determined. The table below shows the kinetic parameters for denitrification obtained from the literature (Table 3.2).           70 Table 3.2: Kinetic parameters for denitrifiers   Carbon source μm , d-1 Ks, mg /L Reference Glucose 5.7 - 6.8 17.4 mg glucose/L Shah and Coulman, 1978 L-Glutamic acid 2.40 0.28 mgNO2– - N/L 0.77 mg NO3- - N/L Kornaros et al., 1996 Methanol 6.9 9.1mg methanol /L Rittman and McCarty, 2001   Less kinetic information is available for microbial selenate reduction in the literature. One study discovered that the ambient concentrations of selenium oxyanions (13 nM to 500 nM) are of orders of magnitude less than the KS (7.9 to 720 μM) for in-situ selenate reduction in sediments (Steinberg and Oremland, 1990). However, this study assumed that selenate reduction by the native bacteria followed Michaelis-Menten kinetics, which has the same form as Equation 3.14. If this situation applies to the sediment bacteria used in this study, then the Monod equation can be approximated to first order (KSe >> Se concentration). Dissolved selenium concentration was assumed to be limiting since it had much lower concentration compared to lactate. For a batch reactor, the reaction equation can be written as (from Equation 3.13):   −d[Se ]dt =  k[Se] ………………………………………………….(3.17)  where k is a pseudo first order rate constant, which is equal to α or 𝑌𝑆𝑒𝑆 , the yield coefficient for Se uptake over substrate (carbon) uptake, times µm, the maximum cell-specific substrate uptake rate, times X, the cell concentration and times 1/KSe. The kinetics of dissolved selenium removal is only pseudo first order when X is constant, such as in the stationary phase of bacterial growth (i.e. when the growth rate equals the death rate). Thus, the kinetic model presented here is a simplistic attempt to quantify the rate of dissolved selenium removal by the enrichments. The concentration of bacteria, X, will depend on the initial concentration of bacteria in the batch cultures. Since the initial concentrations of bacteria were not the same in all the sediments that were inoculated   71 into the growth media, first order kinetic rate constants can only be compared within cultures inoculated with the same sediment, and not between cultures inoculated with different sediments.   To determine the pseudo first order rate constant for Se removal, integration with the initial condition [Se] = [Se]0   at   t = 0 gives   ln[Se]0[Se] = kt …………………………………………………….......(3.18)  If a plot of ln{[Se]0  / [Se]} as a function of time is linear, then the reaction kinetics with respect to total dissolved selenum concentration can be assumed to be first order with the slope equal to k (Xμm/KSe).   3.3 Results  3.3.1 Total Dissolved Selenium Removal in the Presence  and Absence of Nitrate The decrease in total dissolved selenium concentration versus time in the selenate only growth medium, for all the enrichments except Goddard Marsh, proceeded with an initial lag period ranging between 10 to 24 hours, after which the rate of total dissolved selenium removal increased (raw data are provided in Appendix B, Table B.3.1). For Goddard Marsh enrichment cultures, there was no apparent lag period that could be detected with the sampling frequency. The percentage extents of total dissolved selenium removal in all the enrichments ranged from 25% to 100%. The sediments from Lagoon A had the lowest total dissolved selenium removal extent. The total dissolved selenium removal rate in the selenate only growth medium did not increase markedly after the lag period. Similar observations were made with the growth medium containing both nitrate and selenate. The extent of total dissolved selenium removal ranged from 25 – 100%. Smithe Pond enrichments had the lowest total dissolved selenium removal percentage   72 extent of 25%, followed closely by West Jarvis Pond, which had 30%. For these two enrichments, total dissolved selenium removal rate did not increase markedly after the lag period.  Regarding the extents of nitrite-plus nitrate-N reduction, Smithe Pond and Lagoon A enrichments achieved (100%) total nitrate reduction in 12 hours (below the detection limit). However, all the remaining four inocula sources achieved between 90 – 95% extent of total nitrate reduction after 24 hours. Decreases in total nitrite- plus nitrate-N concentrations with respect to time exhibited initial lag phases lasting between 0 and 4 hours in the case of four inoculum sources: Goddard Marsh, Lagoon A, Bodie and Eagle Pond, which was then followed by maximum rates of decrease over the period from 4 to 12 hours (Figure 3-1a,b). No lag phases were observed for cultures inoculated with sediments from Smith Pond and West Jarvis Pond, at least as far as can be discerned from the frequency of sampling. Raw data for the total nitrite-plus-nitrite concentration is provided in Appendix B, Table B.3.2.              73 A                                                                                B    C                                                                                   D  Figure 3-1a: Total dissolved selenium (blue diamonds and red squares) and nitrate plus nitrite concentrations (mg/L) (green triangles) versus time (in hours) measured in the selenate only (blue diamonds) and selenate plus nitrate growth media (red squares) for sediments sourced from A) Goddard Marsh, B) Bodie Creek, C) Lagoon A, and D) Smithe Pond. Data points are averages from duplicate culture bottles. Error bars represent the standard deviation of duplicate culture bottles (n=2). 010203040506000.20.40.60.811.20 20 40 60 80Total Nitrate + Nitrite conc., mg-N/lTotal Dissolved Se conc., mg/lTime, hoursTot Diss. Se (Selenate onlygrowth medium)Tot. Diss Se (Selenate +Nitrate growth medium)Tot. Nitrate + Nitrite010203040506000.20.40.60.811.20 20 40 60 80Total Nitrate +Nitrite conc., mg-N/lTotal Dissolved Se conc., mg/lTime, hoursTot Diss. Se (Selenateonly growth medium)Tot. Diss Se (Selenate +Nitrate growth medium)Tot. Nitrate + Nitrite010203040506000.20.40.60.811.20 20 40 60 80Total Nitrate + Nitrite conc., mg-N/lTotal Dissolved Se conc., mg/lTime, hoursTot Diss. Se (Selenateonly growth medium)Tot. Diss Se (Selenate +Nitrate growth medium)Tot. Nitrate + Nitrite010203040506000.20.40.60.811.20 20 40 60 80Total Nitrate + Nitrite conc.,mg-N/lTotal Dissolved Se conc., mg/lTime, hoursTot Diss. Se (Selenateonly growth medium)Tot. Diss Se (Selenate +Nitrate growth medium)Tot. Nitrate + Nitrite  74 E                                                                                  F  Figure 3-1b: Total dissolved selenium (blue diamonds and red squares) and nitrate plus nitrite concentrations (mg/L) (green triangles) versus time (in hours) measured in the selenate only (blue diamonds) and selenate plus nitrate growth media (red squares) for sediments sourced from E) West Jarvis Pond and F) Eagle Pond. Data points are averages from duplicate culture bottles. Error bars represent the standard deviation of duplicate culture bottles (n=2).   Rates of total dissolved selenium removal could not be compared directly among the different sediments since they did not all receive the identical concentration (or count) of microorganisms at the beginning of the experiment. If it can be assumed that the denitrification kinetic parameters (mu and KS) are the same in all enrichments and the only differences in denitrification rate among the enrichments is due to different initial cell concentrations, then normalization of the total dissolved selenium removal rate with the rate of denitrification for each enrichment culture can allow for a comparison of the enrichments with each other in terms of their ability to remove dissolved selenium in the presence of nitrate (Table 3.3).  The points from the concentration versus time curves used for determining dissolved selenium and total nitrite- plus nitrate-N removal rates were taken from time points (4 – 010203040506000.20.40.60.811.20 20 40 60 80Total Nitrate + Nitrite conc., mg-N/lTotal Dissolved Se conc., mg/lTime, hoursTot Diss. Se (Selenateonly growth medium)Tot. Diss Se (Selenate +Nitrate growth medium)Tot. Nitrate + Nitrite010203040506000.20.40.60.811.20 20 40 60 80Total Nitrate + Nitrite conc., mg-N/lTotal Dissolved Se conc., mg/lTime, hours Tot Diss. Se (Selenateonly growth medium)Tot. Diss Se (Selenate +Nitrate growth medium)Tot. Nitrate + Nitrite  75 12 hours) where the change in concentration with respect to time was the highest (i.e. maximum growth rate). These points were assumed to be the exponential phase for the bacterial growth curve.  The maximum nitrite- plus nitrate-N reduction rates ranged from 2.89 to 4.72 mg/L per hour with sediments from Lagoon A achieving the highest rate (Table 3.3). The sediments from West Jarvis Pond had the lowest nitrite- plus nitrate-N reduction rate.  The total dissolved selenium removal rates ranged from 0.0057 to 0.0424 mg/L per hour. With the enrichment inoculated with Goddard Marsh sediments achieving the highest rate and Smithe Pond achieving the lowest rate.   Table 3.3: Total nitrate plus nitrite and total dissolved selenium removal rate for growth medium with both selenate and nitrate as electron acceptors.  Source of Inoculum dNO3−- N / dt  dSe / dt  (dSe / dt )/(dNO3−- N /dt) Goddard Marsh 3.59 0.0424 0.01181 Lagoon A  4.49 0.0068 0.00151 Bodie 4.72 0.0223 0.00472 West Jarvis Pond 2.89 0.0061 0.00211 Eagle Pond 3.15 0.0141 0.00448 Smith Pond 3.23 0.0057 0.00176   The normalized total dissolved selenium removal rate in the selenate plus nitrate growth medium ranged from 0.0015 – 0.0118 mg-Se per mg-nitrate N. The Goddard Marsh enrichment had the highest normalized total dissolved selenium removal rate whilst Lagoon A enrichments had the lowest (Figure 3.2).   76  Figure 3-2: Total dissolved selenium removal rate in growth medium with both selenate and nitrate as electron acceptors normalized with nitrate plus nitrite reduction rate in selenate and nitrate growth medium.  To compare the rates of total dissolved selenium removal between the two growth media for each of the enrichment to see if nitrate had an effect, the total dissolved selenium concentration versus time data were fitted to first order reaction kinetics models (Figure 3.3a,b).  The resulting rate constants were similar in both growth media for the Goddard Marsh enrichments only. Except for Lagoon A, for the rest of the enrichments, the rate constants for first order total dissolved selenium removal in the nitrate plus selenate growth medium were lower than those observed in the selenate only growth medium. The reverse was observed for the Lagoon A enrichment, in which case the removal rate of total dissolved selenium increased in the presence of nitrate (Table 3.4).   0.01180.00150.00470.00210.00450.00180.00000.00200.00400.00600.00800.01000.01200.0140GoddardMarshLagoon A Bodie West JarvisPondEagle Pond Smith Pond(dSe/dt) / (dNO3- /dt)Inocula source   77 A                                                                                  B  C                                                                                     D  Figure 3-3a: First order kinetic model fitted to total dissolved selenium concntration versus time for sediment from A) Goddard Marsh, and B) Bodie, C) Lagoon A, and D) West Jarvis Pond in growth medium with selenate only (dashed line) and growth medium with both selenate and nitrate as electron acceptor (solid line). The red square represents data points for selenate plus nitrate growth medium whilst the blue diamonds represents data points for selenate only growth medium. The equations on each trendline represent the rate equation as shown in Equation 3.18 and the slope represent rate constant k. Data points are averages from duplicate culture bottles. Error bars represent the standard deviation of duplicate culture bottles (n=2). For most of the data points, the error bars are smaller that the data point symbols and therefore cannot be seen. y = 0.0405xR² = 0.9532y = 0.0378xR² = 0.935700.511.522.533.544.550 20 40 60 80ln {[Se] 0/ [Se]}Time (t), hoursSelenateSelenate+NitrateLinear (Selenate  )Linear (Selenate+Nitrate) y = 0.0642xR² = 0.9471y = 0.018xR² = 0.99300.511.522.533.544.550 20 40 60 80ln { [Se] 0/ [Se] }Time (t), hoursSelenateSelenate+NitrateLinear (Selenate  )Linear (Selenate+Nitrate)y = 0.0041xR² = 0.9717y = 0.0215xR² = 0.906700.511.522.533.544.550 20 40 60 80ln {[Se] 0/ [Se]}Time (t), hoursSelenateSelenate + NitrateLinear (Selenate)Linear (Selenate + Nitrate)y = 0.0368xR² = 0.8777y = 0.006xR² = 0.963400.511.522.533.544.550 20 40 60 80ln {[Se] 0/ [Se]}Time (t), hoursSelenateSelenate+ NitrateLinear (Selenate)Linear (Selenate+ Nitrate)  78 E  Figure 3-3b: First order kinetic model fitted to total dissolved selenium concentration versus time for sediment from E) Eagle Pond in growth medium with selenate only (dashed line) and growth medium with both selenate and nitrate as electron acceptor (solid line). The red square represents data points for selenate plus nitrate growth medium whilst the blue diamonds represents data points for selenate only growth medium. The equation on the trendline represent the rate equation as shown in Equation 3.18 and the slope represent rate constant k. Data points are averages from duplicate culture bottles. Error bars represent the standard deviation of duplicate culture bottles (n=2). For most of the data points, the error bars are smaller that the data point symbols and therefore cannot be seen.   It can be observed from Figures 3-3a and b that the first order kinetic model assumption did not adequately fit the dissolved selenium and time data for most of the enrichments as shown by the low correlation coefficient < 99% (Table 3.4). Only the selenate plus nitrate growth medium for Bodie Creek enrichments had a perfect fit (r2 = 99%) for the pseudo first order kinetic model.  All the data points were used in deriving the first order kinetics model for all the enrichments since there were few data points. Therefore, the first order kinetic model accounts for the lag period observed in some of the enrichments.  y = 0.0123xR² = 0.938y = 0.0096xR² = 0.921900.511.522.533.544.550 20 40 60 80ln {[Se] 0 / [Se]}Time, hoursSelenateSelenate + NitrateLinear (Selenate)Linear (Selenate + Nitrate )  79 Table 3.4: Rate constant (k) and correlation coefficients (r2) of pseudo first order kinetic model for selenate only and selenate plus nitrate enrichments.  S/N Source of Inoculum Selenate only growth medium  Selenate plus Nitrate growth medium k, hr-1 r2 k, hr-1 r2 1 Goddard Marsh 0.041 0.95 0.038 0.94 2 Bodie Creek 0.064 0.95 0.0180 0.99 3 Lagoon A 0.0041 0.97 0.022 0.91 4 West Jarvis Pond 0.037 0.88 0.006 0.96 5 Eagle Pond  0.012 0.94 0.0096 0.92   3.3.2 Microbial Community Structure  The microbial species that grew in each enrichment culture were identified through sequencing of the 16S rRNA biomarker gene. This gene is present in almost all bacteria and is highly conserved making it a convenient marker gene for classifying bacteria. 16S rRNA marker genes that were greater than 97% similar to each other were grouped into so called operational taxonomic units (Otus), each of which is equivalent to a species. The taxonomy (identity) of each Otu was found by comparing a representative sequence from the Otu to those in a curated database. The lowest taxonomic level achievable was genus, but many Otus were unclassified at the genus level and could only be taxonomically classified to higher phylogenetic levels (e.g family, order, class). When naming the species in this subsection, they are referred to by the Otu number followed by the lowest level of taxonomic assignment obtained. The number of 16S rRNA marker reads in an Otu gives a representation of the relative abundance of that Otu in the overall microbial population.  A total of 236321 Otus were identified in the entire datasets. Out of this, 19962 Otus were identified in Goddard Marsh selenate only enrichments with 19997 Otus identified   80 in both selenate and nitrate growth medium. For Lagoon A enrichments, a total of 20014 Otus were identified in selenate only growth medium whilst 20006 Otus were identified in both selenate and nitrate growth medium. For Smith Pond, Bodie Creek, West Jarvis Pond, and Eagle Pond enrichments, 20026, 20015, 19977 and 16420 Otus were respectively identified in selenate only enrichment medium whilst for the selenate and nitrate growth medium, the Otus respectively identified were 20013, 20025, 20040 and 20006. However, only the dominant Otus (Top 20 most abundant Otus) were considered. The presence of nitrate in the growth medium influenced the types of microorganisms that were enriched in all of the sediments. The Otus dominant in the Eagle Pond selenate only and selenate plus nitrate growth media respectively, were the most distinct with only two dominant Otus common to both growth media. Five Otus were dominant in both growth media in the Goddard Marsh and Lagoon A enrichments. In the Smith Pond and West Jarvis Pond enrichments, eight Otus were dominant in both growth media. Bodie Creek enrichments had the highest number (11) of Otus common to the selenate only and selenate plus nitrate growth media (Figures 3-4 to 3-8). A total of 58 different Otus were dominant in all sediment selenate only growth medium enrichments taken together. Of these, Otu2_Trichococcus, Otu232_Macellibacteroides and Otu4_Veillonellaceae_unclassified were present in all sediment enrichments. Otu1_Enterobacteriaceae_unclassified and Otu5_Sulfurospirillum were dominant in five sediment enrichments. Otu10_Paracoccus, Otu11_Clostridium sensu stricto 13, Otu8_Proteocatella and Otu814_Macellibacteroides were dominant in four sediment enrichments. The dominant Otus with the highest relative abundance in each sediment were different for each sediment: Otu9_Pseudomonas (Goddard Marsh), Otu8_Proteocatella (Lagoon A), Otu10_Paracoccus (Smith Pond), Otu5_Sulfurospirillium (West Jarvis Pond), Otu1_Enterobacteriaceae_unassigned (Bodie Creek) and Otu2_Trichococcus (Eagle Pond). There were a total of 61 different Otus in the growth medium containing selenate plus nitrate for all sediment enrichments taken together. Only Otu11_Clostridium sensu stricto 13 was dominant in all sediments. Otu2_Trichococcus, Otu3_Macellibacteriodes,   81 Otu4_Veillonellaceae_unclassified, Otu6_Clostridium sensu stricto 13, Otu7_Romboutsia, Otu16_Bacteroides and Otu23_Clostridium sensu stricto 1 were dominant in five of the sediment enrichments. Highest relative abundance Otus in each sediment enrichment were Otu7_Romboutsia (Goddard Marsh), Otu1_Enterobacteriaceae_unclassified (Lagoon A), Otu6_Clostridium sensu stricto 13 (Smith Pond), Otu12_Pseudomonas (West Jarvis Pond), Otu6_Clostridium sensu stricto 13 (Bodie Creek) and Otu3_Macellibacteriodes (Eagle Pond).      82  Figure 3-4: Otu relative abundances in the Goddard Marsh enrichment cultures. Relative abundance is calculated as the number of 16S rRNA reads for each Otu divided by the total number of 16S rRNA reads in each library (or sample). Error bars represent mean Otu percentage ± the standard deviation of duplicate samples. The lowest taxonomic level affiliation assigned to each Otu is written after the Otu ID number.    0% 10% 20% 30% 40%Otu9_PseudomonasOtu13_SedimentibacterOtu1_EnterobacteriaceaeOtu4_VeillonellaceaeOtu8_ProteocatellaOtu17_PlanococcaceaeOtu22_DesulfomicrobiumOtu232_MacellibacteroidesOtu26_SerratiaOtu2_TrichococcusOtu14_SedimentibacterOtu3_MacellibacteroidesOtu25_ExiguobacteriumOtu5_SulfurospirillumOtu29_Clostridium sensu strictoOtu33_AcidaminobacterOtu46_LongilineaOtu53_MagnetospirillumOtu27_TyzzerellaOtu10_ParacoccusOtu7_RomboutsiaOtu18_Pseudomonadaceae…Otu16_BacteroidesOtu11_Clostridium sensu stricto 13Otu6_Clostridium sensu stricto 13Otu23_Clostridium sensu stricto 1Otu37_DesulfosporosinusOtu34_unculturedOtu20_TerrisporobacterOtu41_Clostridium sensu stricto 3Otu12_PseudomonasOtu43_MethanosarcinaOtu70_Clostridiaceae 1 unassignedOtu59_Lachnospiraceae unassignedOtu39_Lachnospiraceae assignedPercentage of Total Read CountsOTU Number Selenate+NitratemediumSelenate medium  83  Figure 3-5: Otu relative abundance in Lagoon A enrichment cultures. Relative abundance is calculated as the number of 16S rRNA reads for each Otus divided by the total number of 16S rRNA reads in each sample. Error bars represent mean Otus ± the standard deviation of duplicate samples. The lowest taxonomic level affiliation assigned to each Otu is written after the Otu ID number.   0% 5% 10% 15% 20% 25% 30% 35%Otu8_ProteocatellaOtu9_PseudomonasOtu5_SulfurospirillumOtu17_Planococcaceae unassignedOtu75_PseudomonasOtu10_ParacoccusOtu232_MacellibacteroidesOtu21_SulfurospirillumOtu2_TrichococcusOtu4_Veillonellaceae unassignedOtu29_Clostridium sensu stricto 12Otu1_Enterobacteriaceae assignedOtu25_ExiguobacteriumOtu18_Pseudomonadaceae unassignedOtu36_JGI-0000079-D21Otu814_MacellibacteroidesOtu11_Clostridium sensu stricto 13Otu12_PseudomonasOtu33_AcidaminobacterOtu31_AnaerovoraxOtu6_Clostridium sensu stricto 13Otu3_MacellibacteroidesOtu16_BacteroidesOtu26_SerratiaOtu15_Clostridium sensu stricto 7Otu32_Clostridium sensu stricto 1Otu23_Clostridium sensu stricto 1Otu51_Closridium sensu stricto 12Otu35_unculturedOtu43_MethanosarcinaOtu34_unculturedPercentage of Total Read Counts OTU NumberSelenate+NitratemediumSelenate medium  84  Figure 3-6: Otu relative abundance in Smithe Pond enrichment cultures. Relative abundance is calculated as the number of 16S rRNA reads for each Otus divided by the total number of 16S rRNA reads in each sample. The lowest taxonomic level affiliation assigned to each Otu is written after the Otu ID number.    0% 5% 10% 15% 20% 25% 30% 35%Otu10_ParacoccusOtu232_MacellibacteroidesOtu5_SulfurospirillumOtu2_TrichococcusOtu6_Clostridium sensu stricto 13Otu4_Veillonellaceae_ unassignedOtu8_ProteocatellaOtu27_TyzzerellaOtu814_MacellibacteroidesOtu9_PseudomonasOtu48_TissierellaOtu1_Enterobacteriaceae_unassignedOtu11_Clostridium sensu stricto 13Otu30_Lachnoclostridium 5Otu60_TissierellaOtu21_SulfurospirillumOtu58_FonticellaOtu15_Clostridium sensu stricto 7Otu39_unculturedOtu7_RomboutsiaOtu20_TerrisporobacterOtu26_SerratiaOtu23_Clostridium sensu stricto 1Otu43_MethanosarcinaOtu16_BacteroidesOtu3_MacellibacteroidesOtu35_unculturedOtu22_DesulfomicrobiumOtu34_unculturedOtu31_AnaerovoraxPercentage of Total Read CountsOTU NumberSelenate+NitratemediumSelenate medium  85  Figure 3-7: Otu relative abundance in West Jarvis Pond enrichment cultures. Relative abundance is calculated as the number of 16S rRNA reads for each Otus divided by the total number of 16S rRNA reads in each sample. The lowest taxonomic level affiliation assigned to each Otu is written after the Otu ID number.    -5% 5% 15% 25% 35%Otu5_SulfurospirillumOtu1_Enterobacteriaceae_unassignedOtu19_AcetoanaerobiumOtu4_Veillonellaceae_unassignedOtu8_ProteocatellaOtu232_MacellibacteroidesOtu2_TrichococcusOtu30_Lachnoclostridium5Otu13_SedimentibacterOtu14_SedimentibacterOtu28_Peptostreptococcaceae_unassignedOtu21_SulfurospirillumOtu26_SerratiaOtu36_JGI-0000079-D21Otu44_GottschalkiaOtu11_Clostridium sensu stricto 13Otu814_MacellibacteroidesOtu22_DesulfomicrobiumOtu9_PseudomonasOtu65_BacteroidesOtu12_PseudomonasOtu3_MacellibacteroidesOtu24_AcetobacteriumOtu7_RomboutsiaOtu198_unculturedOtu6_Clostridium sensu stricto 13Otu18_Pseudomonadaceae_assignedOtu40_unculturedOtu31_AnaerovoraxOtu23_Clostridium sensu stricto 1Otu2064_ParaclostridiumOtu16-BacteroidesPercentage of Total Read Counts OTU NumberSelenate+NitratemediumSelenate medium  86  Figure 3-8: Otu relative abundances in Bodie Creek enrichment cultures. Relative abundance is calculated as the number of 16S rRNA reads for each Otus divided by the total number of 16S rRNA reads in each sample. The lowest taxonomic level affiliation assigned to each Otu is written after the Otu ID number.   0% 5% 10% 15% 20% 25% 30% 35%Otu1_Enterobacteriaceae_ unassignedOtu14_SedimentibacterOtu4_Veillonellaceae_ unassignedOtu232_MacellibacteroidesOtu25_ExiguobacteriumOtu2_TrichococcusOtu5_SulfurospirillumOtu15_Clostridium sensu stricto 7Otu3_MacellibacteroidesOtu22_DesulfomicrobiumOtu38_ProteiniclasticumOtu30_LachnoclostridiumOtu7_RomboutsiaOtu13_SedimentibacterOtu11_Clostridium sensu stricto 13Otu814_MacellibacteroidesOtu28_Peptostreptococcaceae_ unassignedOtu46_LongilineaOtu31_AnaerovoraxOtu12_PseudomonasOtu9_PseudomonasOtu6_Clostridium sensu stricto13Otu16_BacteroidesOtu23_Clostridium sensu stricto 1Otu39_unculturedOtu41_Clostridium sensu stricto 3Otu17_Planococcaceae_ unassignedOtu27_TyzzerellaOtu67_RomboutsiaOtu78_BacillusOtu51_Clostridium sensu stricto 12Percentage of Total Read Count OTU NumberSelenate+NitratemediumSelenate medium  87  Figure 3-9: Otu relative abundance in Eagle Pond enrichment cultures. Relative abundance is calculated as the number of 16S rRNA reads for each Otus divided by the total number of 16S rRNA reads in each sample. The lowest taxonomic level affiliation assigned to each Otu is written after the Otu ID number.  Eighteen Otus were dominant in both the selenate only and selenate plus nitrate growth media. Some of these were also those present at the highest relative abundances in the enrichments, and some were found in both growth media for several sediment 0% 5% 10% 15% 20% 25% 30% 35%Otu2_TrichococcusOtu10_ParacoccusOtu84_Candidatus NitrosoarchaeumOtu102_unculturedOtu6_Clostridium sensu stricto 13Otu101_UnassignedOtu94_MND1Otu163_UnassignedOtu93_MND1Otu82_UnclassifiedOtu232_MacellibacteroidesOtu87_UnassignedOtu95_UnassignedOtu99_LegionellaOtu98_unculturedOtu106_unculturedOtu110_Xanthobacteraceae_unassignedOtu4_Veillonellaceae_unassignedOtu1376_Hyphomicrobiaceae_unassignedOtu116_UnassignedOtu3_MacellibacteroidesOtu1_Enterobacteriaceae_unassignedOtu7_RomboutsiaOtu9_PseudomonasOtu56_SporomusaOtu224_AzotobacterOtu47_ RuminiclostridiumOtu23_Clostridium sensu stricto 1Otu11_Clostridium sensu stricto 13Otu41_Clostridium sensu stricto 3Otu71_AnaerovoraxOtu2064_ParaclostridiumOtu30_Lachnoclostridium 5Otu69_EnterococcusOtu13_SedimentibacterPercentage of Total Read CountsOTU NumberSelenate+NitratemediumSelenate medium  88 enrichments (Table 3.5), most notably Otu1_Enterobacteriaceae_unclassified, Otu2_Trichococcus and Otu4_Veillonellaceae_unclassified.  Table 3.5: Otus dominant in both the selenate only and selenate plus nitrate growth media Otu ID Enriched Sediments with this Otu Taxonomic Assignment Otu1 Lagoon A; Smith Pond; West Jervis Pond Enterobacteriaceae _unassigned Otu2 Bodie Creek; Lagoon A; West Jervis Pond; Goddard Marsh; Smith Pond Trichococcus Otu3 Bodie Creek; Goddard Marsh Macellibacteroides Otu4 Bodie Creek; Lagoon A; Goddard Marsh; Smith Pond; Eagle Pond Veillonellaceae _unassigned Otu6 Smith Pond; Eagle Pond Clostridium sensu stricto 13 Otu7 Bodie Creek Romboutsia Otu8 Lagoon A Proteocatella Otu11 Bodie Creek; Lagoon A; West Jervis Pond Clostridium sensu stricto 13 Otu12 Bodie Creek Pseudomonas Otu14 Bodie Creek Sedimentibacter Otu15 Bodie Creek Clostridium sensu stricto 7 Otu22 Bodie Creek; Goddard Marsh Desulfomicrobium Otu27 Goddard Marsh Tyzzerella   89 Otu ID Enriched Sediments with this Otu Taxonomic Assignment Otu28 Bodie Creek Peptostreptococcaceae unassigned Otu38 Bodie Creek Proteiniclasticum Otu52 Smith Pond Bacteroidia unassigned Otu232 Lagoon A; Smith Pond Macellibacteroides Otu814 Lagoon A; Smith Pond Macellibacteroides   3.4 Discussion 3.4.1 Removal of Total Dissolved Selenium in the Growth Medium with Selenate as the sole Electron Acceptor  The selenate only growth medium (GM1) was expected to select for microorganisms from the native sediment that can reduce soluble selenium oxyanions as their electron acceptors since no other electron acceptors were present in this growth medium. This was expected to include selenate-specific respiring bacteria, selenite-specific respiring bacteria, denitrifying bacteria that can also reduce selenate using their nitrate-reductase enzyme in the absence of the more preferable nitrate, and facultative bacteria that assimilate and/or reduce selenate as a nutrient (for selenium-containing enzymes) or as a detoxification mechanism. The decrease in concentration of the dissolved forms of selenium observed in all enrichments was attributed largely to the combined activities of these microorganisms acting in parallel or sequentially. It is possible that some selenite produced through reduction of the selenate initially present was adsorbed to the surfaces of sediment particles still present in the cultures (Neal et al., 1987). Selenium removed   90 from the aqueous phase was assumed to be retained in the culture solids, consisting of biomass, sediment particles and precipitates. Chemical speciation of Se in the culture solids was not performed and it is not known what these were. Enrichments from four sediments, Goddard Marsh, Bodie, Smithe Pond and West Jarvis Pond, were able to remove 90 – 100% of total dissolved selenium within 48 – 72 hrs, with the Bodie enrichment achieving soluble selenium removal to below the detection limit within 48 hours. The first order rate constant for total dissolved selenium removal for the six sediments in growth medium with only selenate as electron acceptor ranged from 0.0041 – 0.0642 per hour. The correlation coefficient (r2) for pseudo first order reaction kinetic model ranged from 0.88 – 0.97 with the lowest correlation coefficient being the kinetic model for West Jarvis Pond enrichment data. This shows that the pseudo first order kinetic model assumption did not adequately fit for the rate of dissolved selenium removal from selenate only growth medium. These low correlation coefficients were also found in other microbial selenate removal kinetic models reported in the literature (Sabaty et al., 2001; Steinberg and Oremland, 1990). This may be due to complexities inherent in bacterial reactions or the assumption made that, dissolved selenium was limiting the bacterial reaction was not valid for most of the enrichments. The k values were a reflection of the combined activity of the entire selenate-reducing microbial population in each enrichment culture. The differences in the apparent k values for total dissolved selenium removal in the sediment enrichments might be due to the types of microorganisms in each enrichment and the different enzymatic processes taking place, the concentration of microorganisms in each enrichment, or other physicochemical processes that might have taken place. The k values could not be compared with the few kinetic studies on biological selenate removal found in the literature due to differences in the approach used. For example, Rege et al., (1999) used numerial optimatization with generalized reduced gradient algorithm procedure to estimate the first order kinetic model parameters in an experiment to test for selenium removal from synthetic refinery wastewater using denitrifying sludge as inoculum. The rate constant, r was reported in L/(g mol.min). Also, Steinberg and Oremland, (1990) assumed selenate reduction by mine-affected sediments sourced from diverse selenium-contaminated aquatic   91 environment follows Michealis-Menten enzymatic kinetics and the rate constant, Ks was reported in μM.    It appears that enrichment of the sediments was successful for selecting putative selenate/selenite-reducing bacteria as several of the dominant Otus that were enriched have relatives that are known to be capable of reducing selenium oxyanions. Otu 4 that grew in both growth media in five of the sediment enrichments was a species from the Veillonellaceae family. Veillonella atypical, a strict anaerobe is known to reduce selenite to elemental selenium in a non-dissimilatory process with lactate as electron donor (Pearce et al., 2009). Species classified in the Veillonellaceae family were the most abundant microorganisms in anaerobic granules that reduced selenium oxyanions to elemental Se (Gonzalez-Gil et al., 2016).  Otu1 was an unclassified species from the Enterobacteriaceae family that has several members known to reduce selenium oxyanions. Enterobacter cloacae SLD1a-1 was reported to be capable of non-dissimilatory reduction of selenate to elemental selenium using non-fermentable electron donors under aerobic conditions (Ridley et al., 2006). Enterobacter cloacae is known to reduce selenium oxyanions (Losi and Frankenberger, 1997). It was found to have two membrane-bound nitrate reductases, one with the affinity for nitrate under anoxic conditions, and the other with an affinity for selenate under aerobic conditions. The latter was also active on chlorate and bromate (Ridley et al., 2006). Enterobacter hormaechei capable of reducing selenate to elemental selenium was isolated from sediments of coal tailings pond (Siddique et al., 2007).  Paracoccus are well-known denitrifiers and one species, Paracoccus denitrificans, was found to be capable of reducing selenite but not selenate. But when it was combined with a Pseudomonas species, both selenate and nitrate reduction occurred simultaneously (Morita et al., 2007).  Several strains belonging to Pseudomonas genus are known to be involved in selenium oxyanions reduction. Pseudomonas stutzeri strain pn1 was reported to be capable of growing under anaerobic conditions using acetate and selenate (Narasingarao and Häggblom, 2007), whilst another species Pseudomonas putida (Avendano et al., 2016) and Pseudomonas fluorescens can reduce selenite to elemental   92 selenium (Siddique et al., 2007; Ike et al., 2000). Most of the members of the Sulfurospirillum species are members of the Epsilonproteobacteria and have been reported to grow on substrates such as selenate, as well as nitrate and sulfur compounds. Species Sulfurospirillum barnesii SES3 have been reported to be involved in respiratory selenium oxyanions and nitrate reduction to elemental selenium (Oremland et al., 1994). Some dominant Otus in the selenate only growth medium were members of genera that do not have species known to respire on selenate. These genera included Trichococcus, Macellibacteroides, Proteocatella and Clostridium. Members of a closely related clade in the Clostridia class, including the Peptostreptococcaceae family genera Proteocatella, Romboutsia and Clostridium species, are known to be selenium growth dependent (Self, 2003). Thus, this might be another mechanism for removal of dissolved selenium.  Species within the Trichococcus and Macellibacteroides genera are not known to reduce nitrate or selenate, and they are fermenters that produce organic acids from sugars (Seviour et al., 2002). These species might be selenium resistant bacteria and they might be syntrophic partners for selenate-reducing bacteria (Hao et al., 2015). For instance, Trichococcus pasteurii was isolated from selenium-contaminated mine site (Knotek-Smith et al., 2006). It is not unexpected that microorganisms that tolerate the total dissolved selenium concentrations of the growth medium without metabolizing selenium for any reason would also be enriched. These might include heterotrophic fermenters that do not need an external electron acceptor for growth.   3.4.2 Soluble Selenium Reduction in the Presence of Nitrate by Native Microbial Consortia  The purpose of the selenate plus nitrate enrichment culturing was to identify which sediments harboured bacteria capable of removing total dissolved selenium in the presence of nitrate. Most sediment enrichments removed total dissolved selenium, but only in the Goddard Marsh sediment enrichment was the pseudo first order dissolved selenium removal rate similar in both media.    93 Of the four Otus that were dominant in both growth media for Goddard Marsh sediment enrichments, Otu4_Veillonelllaceae and Otu22_Desulfomicrobium are associated with selenium oxyanion reducing bacteria (Hockin and Gadd, 2006). But these were dominant also in other sediment enrichments.  It is also possible that members of the Goddard Marsh microbial community were removing dissolved selenium for assimilation into selenoproteins and / or for detoxification. These taxonomic groups might not grow on selenate as an electron acceptor and therefore were absent from the selenate only growth medium, but they would grow on nitrate as their electron acceptor, consuming selenium oxyanions for reasons other than growth.  Interestingly, the most predominant Otu in the Goddard Marsh enrichment was Otu7_ Romboutsia, which is not known to be a selenate or nitrate reducer (Gerritsen et al., 2014).  The total dissolved selenium removal for Bodie Creek enrichments shows that the presence of nitrate had inhibitory effect on total dissolved selenium removal.  However, the extent of nitrate inhibition was not as high as that observed for the three other sediment sources (Smith Pond, West Jarvis Pond and Eagle Pond). There were more dominant Otus (11) common to both growth media for Bodie Creek compared with the three other inocula sources. Three of these were associated with known selenate and nitrate reducers. Four were related to Se-dependent organisms (Self, 2003).  The removal of total dissolved selenium in the growth medium with nitrate and selenate for the Lagoon A enrichments was particularly interesting in that the presence of nitrate appeared to enhance rather than inhibit total dissolved selenium removal.  Since the growth medium without nitrate did not result in any considerable removal of total dissolved selenium, it might be that some bacteria from Lagoon A were nitrate - dependent selenate reducers, or they were versatile denitrifiers that rapidly removed most nitrate and then consumed selenate. Otu1_Enterobacteriaceae_unassigned (14%) and Otu2_Trichococcus (14%) were the dominant Otus in the Lagoon A enrichment that also were dominant in the selenate only growth medium.    94 Taken together, the putative selenate-reducing bacteria found in the enrichments are listed below (Table 3-6). The Goddard Marsh sediments contained all of those listed, whereas only two were present in the Eagle Pond sediments.   Table 3.6:  Putative selenate/selenite reducing bacteria present in the enrichments Putative selenate/selenite reducing bacteria Goddard Marsh Lagoon A Smith Pond West Jarvis Pond Eagle Pond Bodie Creek Otu9&12_Pseudomonas + + − + + + Otu1_Enterobacteriaceae + + + + + + Otu4_Veillonellaceae + + + + − + Otu18_Pseudomonadaceae + + − + − − Otu5&21_Sulfurospirillum + + + + − + Otu22_Desulfomicrobium + − + + − + Otu25_Exiguobacterium + + − − − + Otu26_Serratia + + + + − − +  Present   − absent           95 Chapter 4 : Removal of Soluble Selenium from Mining-Influenced Water Batch 1 using Selenate-Reducing Bacteria Enriched from Native Mine Site.   4.1 Synopsis The results of the experiment in Chapter 3 highlighted two enrichments with the capacity to remove dissolved selenium in the presence of nitrate.  One achieved similar dissolved selenium removal rates in growth media with and without nitrate, whereas in the other, nitrate stimulated dissolved selenium removal rate, but only once the nitrate had been depleted. The aim of the experiment described in this Chapter was to test the capabilities of these two enrichments to remove dissolved selenium from actual MIW. Since two different mechanisms of dissolved selenium removal seemed to be at play in these two enrichments, this work also studied the total dissolved selenium removal rate of an enrichment culture capable of simultaneously removing dissolved selenium and nitrate with that of an enrichment culture that removes nitrate and dissolved selenium sequentially in the treatment of actual MIW contaminated with selenate and nitrate.  The enrichments that simultaneously removed total dissolved selenium without nitrate inhibition (Goddard Marsh) and enrichments that removed total dissolved selenium sequentially after nitrate reduction (Lagoon A) were inoculated, respectively, into actual MIW with the following concentrations of constituents of interest; total dissolved Se (0.354 mg/L), total nitrate (51.29 mg-N/L) and sulfate (2030 mg/L) with Denitrifying Sludge from a sewage treatment system as a positive control. In some situations, municipal wastewater sludge is used to seed mine water treatment bioreactors.  This experiment tested the ability of the enriched microorganisms to survive and flourish in the actual MIW. It was hypothesized that the types of microorganisms that flourish in the actual MIW might be different from those that fluorished in the enrichment growth media due to differences in their chemical compositions. If this were the case, it is   96 unknown if dissolved selenium removal in the presence of nitrate would also occur in the actual MIW.  To address this question, the extent of dissolved selenium and nitrate removal and the microbial community composition were measured over five batch cycles, to determine if dissolved selenium reduction could be achieved with these enrichments and to chart changes in the microbial community composition.    4.2 Materials and Methods 4.2.1 Batch Sequential Culturing Experiments Two of the enriched cultures, which were capable of removing dissolved selenium in the presence of nitrate, were used to treat actual MIW in batch culture bottles. The MIW was initially filtered using a 0.45 µm nitrate cellulose membrane filter (GE Health Care Life Sciences, USA) to remove any particulates including any microorganisms that were present in the MIW. The filtered MIW was supplemented with the following nutrients, phosphate buffer (K2HPO4 1 g/L / KH2PO4 0.2 g/L) and 0.3 g/L ammonium chloride to compensate for essential nutrients deficiency. The MIW was sterilized by autoclaving at 120 oC for 20 mins after which 1 mL per litre of 60% w/w filter-sterilized lactate was added as the carbon source. 0.5 g/L L-cysteine solution was added as a reducing agent and 0.5 mL of the redox indicator, rezasurin solution was added. The resulting filtered and nutrient-amended MIW was sparged with nitrogen gas to remove any oxygen present. The amended MIW was dispensed into previously autoclaved 250 mL culture bottles and inoculated with 50 mL of the enrichment cultures.  The enrichment cultures used for these experiments were prepared from fresh sediment samples grown in the same growth medium with both nitrate and selenate as used in Chapter 3 and passaged three times into fresh medium before being used as inocula for these experiments. After inoculation, the bottles were filled to the brim to eliminate any headspace and then capped with butyl rubber septa before incubating statically in the dark at 30 oC. The medium without any sediment served as the negative control. Denitrifying sludge from a   97 pilot-scale biological denitrifying reactor located at UBC South campus was used as a positive control for denitrification. After incubation for 3 days, the supernatant liquid in the culture bottles were decanted from the sediment into a beaker and finally discarded and 50 mL of the remaining sediments transferred into new 250 mL bottles containing fresh nutrient supplemented MIW. This was repeated for 5 times (5 passages). For sample collection, 10 mL of sample was withdrawn daily using a syringe and needle and then filtered through 0.45 μm membrane filter for chemical analyses (total nitrite-plus nitrate-N analysis, total dissolved selenium and soluble chemical oxygen demand (SCOD). Six milliliters of the sample volume were preserved with a drop of analytical grade nitric acid and stored in the fridge at 4 oC for total dissolved selenium concentration analysis later. The pH of the nutrient-amended MIW was 7. Fifteen mL of unfiltered samples were taken for DNA extraction and subsequent 16S rRNA sequencing. Before these samples were taken, the culture bottles were gently agitated to resuspend the particles and mix the contents. The 15 mL of gently suspended biomass were filtered through 0.45 μm nitrocellulose membrane filter and DNA extracted from biomass concentrated on the filter. The experimental design is shown below (Table 4.1).  Table 4.1: Experimental design for treatment of actual MIW with enriched mine-affected sediments         Treatment Number Enriched Sediment Source Number of Replicates Number of Passages 1 Denitrifying Sludge 3 5 2 Goddard Marsh 3 5 3 Lagoon A 3 5       98 4.2.2 Analytical Methods Total dissolved selenium concentration was measured by inductively coupled plasma mass spectrometry (ICP-MS) at ALS Laboratory at Burnaby, BC (USEPA method 6020A-SW-846).  Due to the high cost of the selenium analysis, only samples for the final three passages were analyzed for total dissolved Se. The samples for total dissolved Se analysis were taken at time points, t = 0 and t = 72 hours for passages 3, 4 and 5. Total nitrite- plus nitrate-N concentration was measured using Hach 8171-Cadmium reduction method (Hach company, Loveland, CO). The method, called high range NitraVer 5TM, is a modification of the standard cadmium reduction method (APHA 4500-NO3−E) where the cadmium, which is provided in powdered pillows, first reduces the nitrate to nitrite. The nitrite reacts with sulfanilic acid to form an intermediate diazonium salt, which then reacts with genistic acid to form an amber-coloured compound. The absorbance was read at 400 nm using the UV-VIS spectrophotomer lambda 25 (PerkimElmer, USA). All the reagents needed for the test have been combined into a single stable powder.     The soluble chemical oxygen demand (SCOD) was measured according to standard methods using the closed reflux colorimetric method 5220D (APHA, 2017). Two mL of diluted sample was mixed with 1.2 mL of potassium dichromate solution (prepared by adding 10.216 g K2Cr2O7, 167 mL of concentrated H2SO4, 33.3 g of HgSO4 and diluting to 1000 mL) and 2.8 mL of sulfuric acid containing 5.5 g of Ag2SO4. The vials containing COD samples were digested in a Hach heating block at 150 oC for 2 hours. Then, the optical density was measured at 600 nm using a Hach UV-VIS spectrophotomer (Hach company, Loveland, CO).        99 4.2.3 DNA Extraction and Illumina Sequencing of 16S rRNA Gene Amplicons Microbial genomic DNA was extracted using the FastDNA® SPIN kit for soil (MoBio Laboratories Inc. USA) according to the manufacturer’s protocol. After the extraction, the DNA was quantified by using a Qubit 3.0 fluorometer (Thermo Fisher, USA). The extracted DNA was stored at -20 oC until subsequent use for 16S rRNA and whole DNA sequencing. Amplicons for the V4 variable region of the 16S rRNA gene were produced from target DNA by polymerase chain reaction (PCR) with primers: 515f 50 GTGCCAGCMGCCGCGGTAA 30, 806r 50 GGACTACHVGGGTWTCTAAT 30 using methods described in (Caporaso et al., 2012). These primers were designed to target the bacterial community. Amplicons were sequenced using Illumina MiSeq technology by microbiome INSIGHTS, Vancouver, BC, Canada. For the 16S rRNA amplicon sequences, all pre-processing and sequence quality control steps were performed using USEARCH (v 9.0.2132, 32 bit for Linux) according to the UPARSE pipeline (http://drive5.com/usearch/manual/uparse_pipeline.html; date accessed 1Oct 2016) (Edgar, 2013). Briefly, paired end reads were combined as suggested by the uparse pipeline and unpaired reads or reads with a maximum expected error probability >1 were removed from the analysis. As suggested by (Huse et al., 2010), the remaining sequences were pre-clustered using the furthest neighbour algorithm with 1% sequence dissimilarity as the threshold to prevent over estimation of OTU richness, using the cluster_smallmem command. OTUs were assigned using the UPARSE greedy algorithm for an OTU definition of 97% sequence similarity. Although this step also removes chimeras, a dedicated chimera removal step was used additionally post OTU clustering using the UCHIME 2 algorithm with SILVA gold dataset as reference (Edgar, 2016; Edgar et al., 2011). Global singleton OTUs (those that are represented by a single sequence in the entire dataset) were removed due to their unknown nature. The bacterial OTUs were classified to phylum, class, family, and or genus level using the Silva database with a 97% confidence threshold (https://www.arb-silva.de/aligner/). Following classification sequences not classified as bacteria were   100 removed from the dataset. All samples were subsampled to the same total number of reads (15,000) per sample using the MOTHUR subroutine subsample to eliminate biases of alpha diversity estimations (Schloss et al., 2009).  4.3 Results  4.3.1 Chemical Composition of the Coal MIW  The concentrations of contaminants of interest in coal mine-affected water were total dissolved selenium, 0.354 mg/L and total nitrite- plus nitrate-N, 54.9 mg/L. The MIW also had high total dissolved solids contributed by high concentrations of sodium (14.4 mg/L), chloride (19 mg/L), calcium (404 mg/L), sulfate (2030 mg/L), CaCO3 (2670 mg/L) and magnesium (390 mg/L) (Table 4.2). The major trace elements found in the MIW were nickel (0.0327 mg/L) and strontium (0.250 mg/L) (Table 4-2).                         101  Table 4.2: Anion and total metal constituents and their concentrations in the coal MIW.              4.3.2 Total Nitrate plus Nitrite Reduction  The time course total nitrate plus nitrite reduction curves for all five passages for each of the inoculum sources (Goddard Marsh GM2 enrichment, Lagoon A GM2 enrichment and the denitrifying sludge) are shown in Figure 4.1. Total nitrate plus nitrite reduction was measured from 0 to 48 hours and was observed as a decrease in total nitrite plus nitrate-N concentration over time within each passage.   Constituent Concentration mg/L CaCO3 2670 Chloride (Cl) 19 Nitrate (as N) 54.9 Nitrite (as N) 0.029 Sulfate (SO4) 2030 Barium (Ba)-Total 0.0092 Calcium (Ca)-Total 404 Lithium (Li)-Total 0.124 Magnesium (Mg)-Total 390 Nickel (Ni)-Total 0.0327 Potassium (K)-Total 6.2 Selenium (Se)-Total 0.354 Silicon (Si)-Total 2.21 Sodium (Na)-Total 14.4 Strontium (Sr)-Total 0.250 Uranium (U)-Total 0.0310   102  Figure 4-1: Time course of nitrite- + nitrate-N concentrations (mg/L) for the enrichments in nutrient-amended MIW during anoxic incubation for passages 1-5. Points represent means and error bars the standard deviations for triplicate nitrate plus nitrite measurements for triplicate culture bottles for each treatment (n = 9).  When the nutrient-amended MIW was inoculated with the Goddard Marsh GM2 enrichments, the observed extent of nitrate reduction over the duration of each passage increased and decreased with each alternate passage, respectively. For instance, 85% of nitrate was reduced within the first 48 hours of the first passage. In the subsequent passage, only 60% nitrate reduction occurred within 48 hours of that passage. The extent of nitrate reduction again increased back to 85% within 48 hours in passage 3 and then decreases back to 67% in passage 4. Finally, the percentage nitrate reduction increased to 86% within 48 hours in the last passage.   01020304050600 24 48 0 24 48 0 24 48 0 24 48 0 24 48Total Nitrate + Nitrite conc. mg-N/lTime , hours Negative ControlDenitrifying SludgeGoddard MarshLagoon A  103 When the nutrient-amended MIW was inoculated with the Lagoon A GM2 enrichment culture, 90% of nitrate was reduced within 48 hours in passage 1. This extent of nitrate reduction after 48 hours remained the same for passages 2, 3, and 4 except for the last passage where the extent was lower at 80% in 48 hours (Figure 4.1). Raw data for the total nitrate plus nitrite concentration is provided in Appendix B, Table B.4.2. When the nutrient-amended MIW was inoculated with denitrifying sludge, 90% of the initial nitrate-N was removed within the first 24 hours of the first passage, which was the greater than that observed for the cultures inoculated with enrichments from Goddard Marsh and Lagoon A. In the second passage, nitrate was reduced by 90% within a longer period of time, ~48 hours. In subsequent passages 3 and 4, 85% of nitrate was removed within 48 hours and in the final passage 5, only 80% of the nitrate was reduced within 48 hours. This indicates a slight decrease in the rate of nitrate reduction with increasing number of passages.  4.3.3 Total Dissolved Selenium Removal The initial and final concentrations of total dissolved selenium were measured for passages 3, 4 and 5 (Figure 4.2). For all cultures and passages, the extents of total dissolved selenium removed were less than those observed over the same time period for the enrichments in growth medium 2 (Chapter 3, Figure 3.1). The percentage removal of total dissolved selenium was less than 10% for all cases compared with over 80% and almost complete removal in total dissolved selenium observed when Lagoon A and Goddard Marsh sediments, respectively, were enriched in growth medium 2 (with nitrate and selenate).     104  Figure 4-2: Total dissolved Se concentrations (initial and final) for passages 3, 4, and 5 in nutrient-amended MIW. Points represent the mean total dissolved Se measurements in triplicate culture bottles for each treatment. Error bars represent the standard deviation of total dissolved Se measurements in triplicate culture bottles (n=3).   When the nutrient-amended MIW was inoculated with GM2 enriched bacteria from Goddard Marsh, no improvement in the extent of total dissolved selenium removal was observed with increased passaging. The percentage total dissolved selenium removal was lower than (less than or equal to 8%) what was observed for denitrifying sludge for all the three passages.  In contrast, when the nutrient-amended MIW was inoculated with Lagoon A enrichment bacteria, the extents of total dissolved selenium removed over each passage were all greater than those observed for Goddard Marsh and denitrifying sludge enrichment bacteria cultures (Figure 4.2). As well, the performance of the Lagoon A enrichment bacteria to remove selenium improved with subsequent passages. In the third passage, 10% of the total dissolved selenium was removed. This increased to 19% removal in the 00.050.10.150.20.250.30.350.40 72 0 72 0 72Total Dissolved Selenium conc. mg/lTime, hours Negative ControlDenitrifying SludgeGoddard MarshLagoon A  105 fourth passage. The large range for the error bar for the Lagoon A enrichment at the last time point for passage 5 reflects the variation in performance of the triplicate cultures. Lagoon A culture performed particularly well, removing over 50% of the total dissolved selenium in the last passage. Total dissolved selenium concentration data is provided in Appendix B, Table B.4.2.  4.3.4 Soluble Chemical Oxygen Demand (SCOD) Removal  Soluble chemical oxygen demand was measured to estimate how the concentration of the carbon source changed over the duration of the experiment (Figure 4.3). Based on the amount of lactate added to the MIW, a SCOD concentration of 514 mg/L was expected. However, other organic compounds were also present in the nutrient-amended MIW (i.e. L-cysteine and rezasurin), and these were expected to contribute also to the SCOD. Therefore, the total theoretical SCOD concentration from the main organics (Lactate and L-cysteine) was expected to be 1100 mg/L, which was calculated as shown in Equations 4.1 & 4.2 below.   CH3CHOHCO2Na + 3O2 → 3CO2 + 2H2O + NaOH     …………..(4.1)                     112.06 g of sodium lactate require 96 g of oxygen 600 mg will require (600 ÷112.06) × 96 = 514 mg/L SCOD  SCOD contributed by the L-cysteine, the reducing agent was determined as follows,  C3H7O2NS + 9 2⁄ O2 → 3CO2 + NH3 + H2SO4 + H2O …………(4.2) 121.16 g of L-cysteine require 144 g/mol of oxygen 500 mg will require (500÷121.16) × 144 = 594 mg/L Total SCOD contribution by the two major carbon sources = 514 + 594 = 1109 mg/L   106   Figure 4-3: Time course of SCOD concentration for enrichments in nutrient-amended MIW during anoxic incubation. Points represent means and error bars the standard deviations for triplicate SCOD measurements for triplicate culture bottles for each treatment (n = 9).  The intial SCOD concentration that was measured was slightly higher than the calculated theoretical SCOD concentration for the nutrient-amended MIW and was different for each treatment. This might have been due to additional SCOD contributed by the enrichment cultures used as inocula, since these were added as mixed liquor suspended solids. The enrichment cultures were prepared in growth medium containing lactate, yeast extract, and vitamins. Some of these compounds might be remaining in the culture broth at the time that the cells were harvested for inoculation into the nutrient-amended 02004006008001000120014001600180020000 24 48 72 0 24 48 72 0 24 48 72 0 24 48 72 0 24 48 72SCOD concentration, mg/lTime, hours Negative ControlDenitrifying SludgeGoddard MarshLagoon A  107 MIW. Consumption of SCOD was observed in the negative control even though little or no nitrate or selenate removal was observed in these cultures. The presence of increasing amounts of white precipitation was observed visually in the control bottles, which might be associated with the reduction in SCOD. The initial SCOD concentrations measured in subsequent passages after the first passage decreased with increased passaging.  For the cultures inoculated with Goddard Marsh enrichment, the SCOD consumed over each passage varied from 94.17 to 450.52 mg/L, whilst the nitrate-N removed ranged from 31.05 – 43.70 mg-N/L. For the Lagoon A enrichment inoculated cultures, SCOD consumed over each passage ranged from 107.10 – 234.50 mg/L, and the total nitrate-plus-nitrite removed ranged from 38.37 to 43.32 mg/L.  For the nutrient-amended MIW inoculated with denitrifying sludge, the amount of SCOD consumed in all the passages varied from 124.46 – 479.14 mg/L, whilst the amount of total nitrate-plus-nitrite removed ranged from 40.83 – 43.35 mg-N/L (Figure 4-3; Table 4-3). Even though the same amount of nitrate-plus-nitrite was removed (41 mg-N/L) in passages 3, 4 and 5, the amounts of SCOD consumed in these passages varied widely 271.47, 124.46 and 479.14 mg/L respectively.  Overall, there were no significant correlations between the amounts of SCOD consumed and nitrite- plus nitrate-N and total dissolved Se removed. The measured SCOD amounts that were consumed ranged widely from 94.14 - 479.14 mg/L.  However, there was no consistency in the amounts of total nitrate-plus-nitrite and total dissolved selenium removed and the SCOD consumed. For instance, for the same amount of total nitrate-plus-nitrite removed in passages 1 and 3 for Lagoon A, the SCOD consumed was markedly different at 234.50 and 161.26 mg/L respectively (Table 4.3). Raw SCOD concentration data is provided in Appendix B, Table B.4.3.      108 Table 4.3: Amount of nitrate and total dissolved Se removed and SCOD consumed for each passage (Actual total nitrate, dissolved Se and SCOD removed were determined from the initial and final concentrations of the experimental data. Theoretical SCOD required was calculated using Equations 4.1 and 4.3).   Inoculum source Passage Actual Nitrate removed, mg-N /L Actual Dissolved Se removed, mg-Se/L Actual SCOD consumed, mg/L Theoretical SCOD required, mg/L Goddard Marsh  1 39.27 ND 209.15 ND 2 32.48 ND 94.17 ND 3 41.60 0.0118 279.49 188.95 4 31.05 0.0287 153.27 141.08 5 43.70 0.0253 450.52 198.52 Lagoon A 1 42.03 ND 234.50 ND 2 41.68 ND 234.50 ND 3 42.94 0.0365 161.26 195.10 4 43.32 0.062 107.10 196.89 5 38.37 0.1309 195.71 174.58 Denitrifying Sludge 1 43.35 ND 405.57 ND 2 43.09 ND 396.99 ND 3 41.13 0.0365 271.49 186.88 4 40.83 0.062 124.46 185.58 5 41.09 0.1309 479.14 186.93 ND: Not Determined  Based on theoretical reaction stoichiometry described in section 3.1.4.1, Chapter 3 the theoretical SCOD (lactate) consumed for nitrate and selenate reduction is calculated as: 0.10 CH3CHOHCOO− + 0.10 SeO42− + 0.12 NO3− + 0.32H+  → 0.20 CO2 + 0.1HCO3−  +0.1Se + 0.06N2 + 0.36H2O ……….(4.3) It was assumed that the selenate initially present in the enrichment medium was reduced to elemental selenium and the electron equivalence from lactate was equally distributed for selenate and nitrate reduction.      109 Assuming 100% nitrate removal;  0.10 mols × (89.06 g) CH3CHOHCOO−   will require 0.12 mols (62.0049 g) NO3− 8.906 g of CH3CHOHCOO-will require 7.44 g NO3− for 50.4 mg -N/L (223.22 mg/L NO3−) (223.22÷7.44) × 8.906 = 267.20 mg/L Lactate (SCOD)  For 100% selenate removal;   0.1× (89.06 g) CH3CHOHCOO−   will require 0.10 (142.96 g) SeO42− 8.906 g CH3CHOHCOO− reqiure 14.296 g SeO42− for 0.354 mg/L –Se (0.641 SeO42−) (0.641÷ 8.906) ×14.296 =  1.029 mg/L Lactate (SCOD).  Total carbon (Lactate) required = (267.20 +1.029) = 268.29 mg/L  Using Equation 4.1, the theoretical SCOD equivalent for the total amount of lactate required for complete total nitrate and total dissolved selenium removal  = 229.79 mg/L.   4.3.5 Microbial Population Compostion in the Cultures   The diversities of the microbial populations at the start of the nutrient-amended MIW treatment experiments were estimated using the Shannon and Simpsons species diversity indices (Table 4.4). These indices consider both the number of species and the evenness of the population.        110 Table 4.4: Diversity of the microbial populations at the start of the experiment  Source of Inoculum Shannons Index Simpsons Index Goddard Marsh Enrichments 2.74 ± 0.14 0.884 ± 0.008 Lagoon A Enrichments 3.34 ± 0.03 0.929 ± 0.003 Denitrying Sludge 3.36 ± 0.03 0.884 ± 0.003    According to Shannons Index, Lagoon A enrichment and the denitrifying sludge were slightly more diverse than the Goddard Marsh enrichment, whereas Simpsons Index suggested that the Lagoon A enrichment was more diverse than the other two enrichments used to inoculate the nutrient-amended MIW.  Negative controls containing only nutrient-amended MIW and no inocula did not contain measurable amounts of DNA indicating that the risk of cross contamination was low. A total of 2609 species (Otus) were identified in all of the cultures combined. There were 711 Otus in the Goddard Marsh enrichments at the beginning of the experiment, 717 in the Lagoon A enrichments and 991 in the denitrifying sludge. The dominant species at the start of the experiment, defined as those that comprised at least 2% of the total population, in each of the nutrient-amended MIW cultures were restricted to eight OTUs in the Goddard Marsh enrichments, ten in the Lagoon A enrichments and seven in the denitrifying sludge (Figure 4.4). Interestingly, four Otus were dominant in all treatments at the start of the experiment: Otu1 (Sulfurospirillum), Otu2 (uncultured Enterobacteriaceae), Otu6 (Macellibacteroides) and Otu7 (uncultured Veillonellaceae). Species Otu9 (Sedimentibacter), Otu11 (Pseudomonas) and Otu15 (uncultured Planococcaceae) were dominant in the Goddard Marsh enrichments, but not in the other cultures. Only species Otu3 (Veillonella) and Otu13 (Acetoanaerobium) were dominant in the denitrifying sludge, but not in the others. Although the denitrifying sludge contained more Otus than the other cultures, these were unevenly distributed since there were fewer dominant ones than in the other two cutures. There were more unique dominant species in Lagoon A enrichments: Otu4 (Paracoccus), Otu10 (Youngiibacter),   111 Otu12 (Proteocatella), Otu14 (Sulfurospirillum), Otu16 (Trichococcus), and Otu26 (Clostridium sensu stricto).    Figure 4-4: Percentage relative abundance of dominant species (Otus) in the cultures at the beginning (time zero) of the treatment of MIW with Denitrifying Sludge, Goddard Marsh and Lagoon A enrichments.  Otu1 (Sulfurospirillum) remained the most dominant Otu in all the subsequent passages for all three of the treatments (Figures 4-5, 4-6 & 4-7). Its relative abundance in the populations of the Goddard Marsh and Lagoon A enrichment treatments increased more 0510152025303540Percentage of the Population in each treatmentDominant species (OtuID_lowest taxonomic classification)Denitrifying_SludgeGoddard_MarshLagoon_A  112 than two fold by the end of the first passage. The relative abundance of Otu2 (uncultured Enterobacteriaceae) also remained high during all passages for the Goddard Marsh and Lagoon A enrichment treatments, plus it increased with passaging in the treatments inoculated with denitrifying sludge. Otu6 (Macellibacteroides) was not dominant in the subsequent passages, except in the Lagoon A treatments where it was present at greater than 10% relative abundance. The relative abundance of Otu7 (uncultured Veillonellaceae) declined rapidly in the treatments with Goddard March enrichments and denitrifying sludge, but remained at between 4 and 5% of the total population in the Lagoon A enrichment treatment.   Otus 9 (Sedimentibacter), 11 (Pseudomonas) and 15 (uncultured Planococcaceae) that were uniquely dominant in the Goddard Marsh enrichments at the beginning of the treatment declined in relative abundance steadily with increasing passaging, becoming rare in the final passage. At the end of the second passage and thereafter, previously rare Otus 3 (Veillonella) and 8 (Bacteroides) became dominant bacteria in the nutrient- amended MIW inoculated with Goddard Marsh enrichments (Figure 4.5).    113  Figure 4-5: Dominant Otus in MIW inoculated with Goddard Marsh enrichment for each passage. Percentage read counts was calculated as the number of Otus for that genera divided by total Otus. Bar height represents the mean percentage of three replicate cultures for each treatment and error bars represent the standard deviation of the triplicate cultures (n=3)  All Otus that were initially dominant in all three starting populations (Otus 1, 2, 6 & 7), remained dominant in the Lagoon A enrichment inoculated MIW cultures.  Otu1 (Sulfurospirillum) increased almost 4 fold in relative abundance at the end of passage 1. Otu4 (Paracoccus) that was initially dominant increased over four fold in relative abundance by the end of the first passage. Most of the other Otus that were initially dominant in the Lagoon A enrichment inoculated cultures declined in relative abundance 0%10%20%30%40%50%60%Percenatage of Mean Total Count Dominant species (OtuID_taxonomic classification)P0 t=0, P1P1 t=24, P1P2 t=24,P2P3 t=24, P3P4 t=24, P4P5 t=24, P5  114 (Otus 12, 14, 16 & 26), except for Otu10 (Youngiibacter) that did not increase or decrease markedly in relative abundance over time (Figure 4.6). As in the Goddard Marsh cultures, Otu3 (Veillonella) appeared in the cultures in passage 2 and then remained dominant in the rest of the passages. Although it did not reach above 5% of the total population, the Otu17 (Desulfomicrobium), which was rare initially, but increased in relative abundance.   Figure 4-6: Dominant Otus in in the nutrient-amended MIW inoculated with Lagoon A enrichment. Percentage read counts was calculated as the number of Otus for that genera divided by total Otus. Bar height represents the mean percentage of three replicate cultures for each treatment and error bars represent the standard deviation of the triplicate cultures (n=3).     0%10%20%30%40%50%60%Percentage of Mean Total CountDominant species (OtuID_taxonomic classification)P0 t=0, P1P1 t=24, P1P2 t=24,P2P3 t=24, P3P4 t=24, P4P5 t=24, P5  115 Fewer Otus were dominant in the MIW cultures inoculated with denitrifying sludge than were observed for the two sediment enrichment cultures. Two of the Otus that were initially dominant in all cultures, Otus 1 & 2, increased in relative abundance and remained dominant reaching relative abundances of 34.8% and 27.8%, respectively, in the final passage. Otu3 (Veillonella) initially increased in relative abundance, but then declined steadily with each passage. The other bacterium that was initially dominant, Otu13 (Acetoanaerobium) steadily decreased in relative abundance. Otu8 (Bacteriodes) that was initially rare increased in relative abundance (Figure 4.7).   Figure 4-7:  Dominant Otus in the nutrient-amended MIW inoculated with Denitrifying Sludge. Percentage read counts was calculated as the number of read counts for that Otu divided by total read counts (15,000). Bar height represents the mean percentage of three replicate cultures for each treatment and error bars represent the standard deviation.     0%10%20%30%40%50%60%Percentage of Mean Total Count Dominant species (OtuID_taxonomic classification)P0 t=0, P1P1 t=24, P1P2 t=24,P2P3 t=24, P3P4 t=24, P4P5 t=24, P5  116 4.3.6 DNA Concentration It was not possible to directly measure the actual concentrations of microorganisms in each of the culture bottles. The standard methods of optical density at 600 nm and volatile suspended solids (VSS) could not be applied accurately. Therefore, the concentration of microorganisms was estimated from the DNA concentration obtained from a fixed volume (15 mL) of suspended culture (Table 4.5). For Goddard Marsh cultures, the DNA concentration increased after the start-up but started decreasing after passage 1, but increased again after passage 4 to the last passage.  The DNA concentrations obtained from the Lagoon A enrichment inoculated MIW treatment cultures consistently increased with increased passaging. For the MIW inoculated with denitrifying sludge, the DNA concentration increased from the initial start up until passage 3 after which it decreased till the last passage.  Table 4.5: DNA concentration for cultures in each passage  Inocula source Time /hrs Passage Avg. Qubic Conc, ng/μL StDev Goddard Marsh  0 1 13.40 0.85 Goddard Marsh  24 1 52.83 5.25 Goddard Marsh 24 2 9.57 4.43 Goddard Marsh 24 3 33.93 9.73 Goddard Marsh  24 4 116.00 0.42 Goddard Marsh 24 5 134.50 10.61 Lagoon A 0 1 2.87 1.34 Lagoon A 24 1 57.53 13.48 Lagoon A 24 2 188.67 52.25 Lagoon A 24 3 205.00 66.47 Lagoon A 24 4 285.50 95.46 Lagoon A 24 5 349.33 96.80 Denitrifying Sludge  0 1 32.63 10.01 Denitrifying Sludge 24 1 112.00 14.14 Denitrifying Sludge 24 2 139.50 41.72 Denitrifying Sludge  24 3 116.00 0.42 Denitrifying Sludge 24 4 97.15 25.24 Denitrifying Sludge 24 5 102.70 45.56   117 4.4 Discussion The extents of total dissolved selenium removal observed over each passage for all the nutrient-amended MIW cultures were lower than those observed when the same enrichments were inoculted into growth media (Chapter 3 Results). The extents of total dissolved selenium removal for the MIW cultures inoculated with denitrifying sludge and Goddard Marsh enrichment were consistently less than 10% within each passage. The total dissolved selenium removal extent trend differed for the cultures inoculated with Lagoon A enrichment. In the growth media enrichment experiments (Chapter 3), bacteria enriched from Lagoon A preferentially reduced nitrate first before dissolved selenium removal. In the MIW experiments inoculated with enriched Lagoon A bacteria, the extent of total dissolved selenium removal increased steadily with each passage. One possible reason for the difference in performance between the inocula might be due to the numbers of microorganisms present in each culture, which may have differed. Using DNA concentration as a proxy for cell biomass concentration, it appeared as if the Goddard Marsh cultures had less biomass that the other two. Even though Goddard Marsh cultures had a higher DNA concentration than Lagoon A at the start up of the experiment, Lagoon A cultures had a consistent increase in DNA concentration with each passage, reaching two to three times as much as DNA than was measured in the Goddard Marsh and denitrifying sludge inoculated MIW cultures. This explanation is somewhat supported by the results for denitrification, where it appeared that nitrate was reduced earlier within each passage in the Lagoon A enrichment inoculated MIW cultures than the others. But there was little difference between the nitrate reduction rates for all cultures over the last passage where the greatest difference in DNA concentrations between cultures was observed. Overall, there are too few data points for nitrate versus time to make accurate comparisons between the cultures. Additionally, the SCOD concentration versus time measurements that were assumed to be proportional to the bacterial activity in each culture did not coincide with the trends in DNA concentrations.    118  One explanation for the poor performance of the cultures inoculated into MIW versus that observed when they were inoculated into the growth media might be due to the additional chemical constituents in the MIW that were not present in the growth media. The high concentration of sulfate (2030 mg/L), which was much greater than the concentration of selenate, in the MIW could have contributed to the low dissolved selenium removal observed in the MIW. Unfortunately, no sulfate concentration measurements were made to see if there was any activity of sulfate reducing bacteria. However, a rotten egg smell was detected, which indicated that there was some sulfate reduction occuring.  Even though sulfate is a less thermodynamically favourable electron accepter than selenate or selenite, its presence may have influenced the microbial community structure. The presence of high relative abundance of Otu (Sulfurospirillum) which is related to sulfur bacteria in all the MIW cultures suggests that sulfate reduction might be occurring in the cultures. Some species from the Sulfurospirillum genus are also capable of reducing selenate probably due to the structural similarities between selenate and sulfate.  Addionally, the presence of such high concentrations of sulfate contributes to the salinity of the MIW, which is toxic to microorganism. Additionally, the high concentrations of Mg2+ and Ca2+ in the MIW (Table 4.2, Section 4.3.1) might have caused the precipitation of essential micro (e.g the trace elements such Nickel, Zinc) and macronutrients (e.g potassium, sodium). The precipitation of these essential minerals from the MIW could cause a reduction of their availability in the MIW for use as nutrients by the microbial community. The TDS of the MIW was calculated to be 3106.7 mg/L compared to 1184.0 mg/L for the growth media. Although the MIW entering Goddard Marsh was likely high in TDS since it came from waste rock seepage, the aqueous environment within Goddard Marsh was extremely low in TDS. Saline water can be toxic to bacteria (Marks et al., 2013; Magdigan et al., 2006). Previous studies have reported that salinity reduces the rate of nitrate reduction and denitrification (Hirata et al., 2001; Dinçer and Kargi, 1999). However, nitrate reduction occured within all of the MIW cultures indicating that it was not inhibited by the MIW, at least not to the extent that can be observed with the few data points that were collected for nitrate concentration. Of all the cultures, those inoculated with Goddard Marsh enrichments had the highest lingering nitrate concentrations towards the end of each passage, and it is   119 possible that these were high enough to inhibit dissolved selenium removal due to the higher affinity of nitrate reductases for nitrate over selenate. Unlike what was observed for the Goddard Marsh enrichments in growth media where they reduced nitrate and selenate apparently simultaneously, nitrate might be inhibiting dissolved selenium removal in the MIW. Whereas, if Lagoon A enriched bacteria reduced nitrate faster, due to higher cell numbers or because different types of bacteria with a better affinity for denitrification were present, there was enough time, during the three-day passage, for them to also remove dissolved selenium after nitrate was depleted to non-inhibitory levels.  The amended MIW was missing certain essential minerals (i.e. iron and molybdenum) that are required for the proper functioning of the enzymes involved in selenate and nitrate reduction. Iron plays a major role in cellular respiration and is a key component of cytochromes and iron-sulfur proteins involved in electron transport reactions to enzymes for selenate and nitrate reduction. Mo is a cofactor for the enzymes involved in selenate and nitrate reduction (Bèbien et al., 2002; Sabaty et al., 2001). The absence of these key trace elements in the MIW could affect the activity of enzymes required for selenate and nitrate reduction.  It might be that inhibitors to microbial activity and growth are present in the MIW and therefore a longer residence time would be required for removal of total dissolved selenium compared with growth media that provide optimal environments for bacterial growth. A previous study reported that bacterial growth on dissimilatory selenate reduction in sediments at ambient concentrations is limited by the low selenate concentration (Steinberg and Oremland, 1990). Indeed, the total dissolved selenium concentrations in the MIW were less than 400 µg/L. Also, it is possible that the selenate was reduced to the intermediate chemical species selenite, which might have accumulated in the aqueous medium and still be measured as total dissolved selenium. The rate for selenate reduction to selenite is higher than that for selenite reduction to elemental selenium (Ike et al., 2000). Selenium speciation assays were not done due to the high cost of this analysis.   120 Although, by the final passage, the dominant bacterial species in all cultures were Otu1 (Sulfurospirillum), Otu2 (uncultured Enterobacteriaceae) and Otu3 (Veillonella), there were more dominant Otus that were specific to Lagoon A than Goddard Marsh and denitrifying sludge. These were Otu17 (Desulfomicrobium), Otu10 (Youngiibacter), Otu16 (Trichococcus), Otu12 (Proteocatella) and Otu14 (Sulfurospirillum). Three of these, Otu14 (Sulfurospirillum), Otu17 (Desulfomicrobium) and Otu16 (Trichococcus), are known to be selenate reducers (Knotek-Smith et al., 2006; Hockin and Gadd, 2003; Oremland et al., 1994). In the later passages (3 – 5), when there was a steady increase in total dissolved selenium reduction, the dominant genera that were restricted to Lagoon A cultures were Otu4 (Paracoccus), Otu6 (Macellibacteroides), Otu17 (Desulfomicrobium) and Otu6 (Macellibacteroides). Paracoccus, a denitrifying bacterium has the capability of reducing selenate (Sabaty et al., 2001). Macellibacteroides, which is an obligate anaerobe, has not been reported to reduce nitrate or selenate (Jabari, 2012). In the enrichment cultures experiment (Chapter 3), a Macellibacteroides species was found in both the selenate and selenate plus nitrate growth media but was more predominant in the selenate plus nitrate growth medium for all the six different enrichment cultures. The dominant Otus that were restricted to Goddard Marsh cultures, for the later passages were Otu5 (Escherichia-Shigella) and Otu8 (Bacteroides) for passages 3 and 4 and solely Otu5 in passage 5. E.coli, a species from the genus, Escherichia-Shigella, have been well studied for the assimilatory selenate reduction and incorporation into seleno-proteins (Turner et al., 1998).  The nitrate reductase gene of E.coli has been reported to be capable of dissimilatory selenate reduction (Sabaty et al., 2001). There were no dominant Otus that were specific to the denitrifying sludge cultures. A comparison of the microbial population compositions of the MIW cultures with those in the enrichment cultures (Chapters 3) revealed that significant shifts in the microbial community occurred when the enriched cultures were used to inoculate the actual MIW.  This, as well as the factors discussed previously, might have accounted for the differences in the dissolved selenium and nitrate removal rates in the enrichment medium and the actual MIW.    121 Overall, the enriched bacteria sourced from Lagoon A appeared to be more promising than those from Goddard Marsh or the denitrifying sludge for the removal of total dissolved selenium from this particular MIW. However, it is not known if these extents would continue to increase with further passaging as the microorganisms continue to adapt the chemical environment of the nutrient-amended MIW. These results indicate that the microorganisms from Lagoon A were more capable of reducing selenate in the MIW either due to their greater abundance or the metabolic traits of the species unique to that enrichment.     122 Chapter 5 : Removal of Soluble Selenium from Mining-Influenced Water Batch 2 using Enriched Cultured Indigenous Inocula   5.1 Synopsis In the previous experiment described in Chapter 4, mine-affected sediments enriched in growth medium containing nitrate and selenate were used as inocula for dissolved selenium removal in actual MIW with the following concentrations of the contaminants of interest; total dissolved selenium, 0.3 mg/L, nitrate plus nitrite 50 mg-N/L and sulfate 2030 mg/L. It was found that both dissolved selenium and nitrate reduction in the MIW were less than that measured in the growth medium. Possible reasons for this observation were lower concentrations of active microbial cells in the MIW, higher total dissolved solids (TDS) concentration of the MIW, inhibitory compounds in the MIW, missing essential micronutrients not present in the MIW and not enough hydraulic retention time. Another key finding of the previous experiment (Chapter 4) was that the microbial communities that were enriched from the sediments shifted in relative abundance in the actual MIW with some species persisting, some decreasing and a few rare species becoming dominant. As a result, the sediments that performed well in the enrichment cultures did not necessarily perform well in the actual MIW in terms nitrate and dissolved selenium removal rates.  The aim of the experiment described in the Chapter was to change the factors (inocula source, hydraulic retention time, MIW chemical constituents) used in the Chapter 4 experiment to further understand how these factors could improve the removal of dissolved selenium from actual MIW.  The experiment was performed with actual MIW from the same source but with different chemical composition with overall lower TDS. The total dissolved selenium and total nitrate and nitrite concentrations were spiked to 2 mg/L and 50 mg-N/L, respectively. The greater concentration of total dissolved selenium, compared to what was used previously, was hypothesized to improve the   123 kinetics of selenate reduction. Two other inocula sources, (Bodie Creek and Eagle Pond) which achieved high total dissolved selenium removal in the growth medium with both nitrate and selenate in the enrichment experiments (Chapter 3) were tested together with the two inocula sources (Goddard Marsh and Lagoon A) used for the previous experiment (Chapter 4). The hydraulic retention time was increased from 3 to 12 days between each batch cycle. To maintain higher numbers of microbial cells in the MIW at the beginning of each passage, all cells were recovered at the end of the previous passage and transferred into fresh nutrient-amended MIW for the next passage.    5.2 Materials and Methods 5.2.1 Batch Treatment of Actual MIW 2 Four of the enriched cultures, which achieved the highest soluble selenium reduction rate in growth medium with both nitrate and selenate, were used to inoculate the new batch of actual MIW in culture bottles. The MIW was initially filtered using 0.45 µm nitrate cellulose membrane filter to remove any debris and microorganisms present in the MIW before using it for the experiment. At the start of the experiment, the filtered MIW was amended with the following amounts of nutrients; phosphate buffers K2HPO4 (1 g/L) and KH2PO4 (0.2 g/L) and ammonium chloride (0.3 g/L).  The nutrient-amended water was sterilized by autoclaving at 100 oC for 20 mins after which, the following chemicals were filter sterilized before adding to the MIW; 1.8 mg-Se /L as sodium selenate, 30 mg-N/L as sodium nitrate, 0.6 g/L lactate as the carbon source, 0.5 g/L L-cysteine as the reducing agent and 0.5 mL of rezasurin solution as redox indicator. The resulting solution was sparged with nitrogen gas to remove any oxygen present. The pH of the resulting solution was 7 so no pH correction was done. The amended MIW was dispensed in an autoclaved 250 mL culture bottles and the inoculum added. Thereafter, the bottles were filled to the brim to remove any headspace and then capped with butyl rubber septa caps before incubating statically in the dark at 30 oC for 12 days for the first passage. The inoculum, was first grown in fresh medium with both selenate and nitrate from glycerol stock prepared in 1:1 ratio of 50% glycerol stock solution with the enrichment cultures   124 and stored at -80 oC. At the end of passage 3, the cells were centrifuged at 10,000 rpm using Eppendorf centrifuge 5810R (Eppendorf AG, Germany) for 10 min. Each pellet was resuspended in 5 mL of amended MIW and the entire volume added to the culture bottles. Each inoculum had triplicate culture bottles (Table 5.1). Nutrient-amended MIW without any inoculum served as the negative control and nutrient-amended MIW with denitrifying sludge as inoculum served as a positive control. For sample collection, 10 mL of gently mixed culture broth was drawn from the culture bottles every two days using a syringe and needle and then filtered through 0.45-μm cellulose nitrate membrane filter (GE Health care Life sciences, USA) for chemical analyses (total nitrite-plus nitrate-N and total dissolved selenium concentrations). Six mL of the filtered samples were preserved with a drop of nitric acid and stored in the fridge at 4 oC for subsequent total dissolved selenium concentration analysis. After a 12-day incubation period, all the cells in the culture bottles were pelleted, resuspended into fresh nutrient-amended MIW and the entire volume added to a new 250 mL culture bottles containing freshly prepared nutrient-amended MIW solution. This was repeated for four times (i.e. for four passages).   Table 5.1: Experimental design  Treatment number Enriched Sediment Source Number of Replicates Number of Passages 1 Denitrifying Sludge 3 4 2 Goddard Marsh 3 4 3 Lagoon A 3 4 4 Bodie Creek 3 4 5 Eagle Pond 3 4   5.2.2 Analytical Methods Total dissolved selenium concentration was measured by inductively coupled plasma mass spectrometry (ICP MS) at ALS Laboratory at Burnaby, BC (USEPA 6020A-SW-846). Due to high cost of the selenium analysis in a commercial laboratory, three passages were analyzed and only samples taken at the time points, t = 0, 4, 8 and 12 days   125 for each of the passages were sent to ALS laboratory for the analysis. Total nitrite - plus nitrate - N concentrations were measured using Hach 8171-Cadmium reduction method (Hach company, Loveland, CO). The method called high range NitraVer5TM is a modification of the standard cadmium reduction method (APHA 4500-NO3- E) where the cadmium first reduces the nitrate to nitrite and then the nitrite reacts with sulfanilic acid to form an intermediate diazonium salt, which then reacts with genistic acid to form an amber-coloured compound. The absorbance, which is proportional to the nitrate plus nitrite concentration, is read at 400 nm using a UV-VIS spectrophotomer lambda 25 (PerkimElmer, USA). All the reagents have been combined into a single stable powder in the NitraVer5TM method. After diluting the sample to the appropriate level in a Falcon tube, the contents of one powder pillow was added to the diluted sample and then the Falcon tube was shaken for exactly 5 mins, followed by waiting for 1 minute, before the optical density was read at 400 nm with the UV-VIS spectrophotometer lambda 25 (PerkimElmer, USA). Samples of the actual coal MIW were also shipped to ALS Burnaby, B.C for total metals and anions analysis.   5.3 Results 5.3.1 Compositional Characteristics of Coal MIW 1 and 2 The major contaminants of concern in the new batch of MIW were total dissolved selenium (0.188 mg/L), total nitrate plus nitrate (19.4 mg-N/L) and sulfate (1100 mg/L). The total dissolved selenium and nitrate concentrations were spiked to the 2 mg/L and 50 mg/L respectively. The concentrations of major ions include, sodium (19 mg/L), calcium (139 mg/L) and magnesium (225 mg/L) (Table 5.2). The concentration of chloride, nickel and silicon were below the detection limits. The pH for MIW was neutral, 7.        126 Table 5.2: Anions and metals composition of MIW 1 and 2                 5.3.2 Total Nitrate plus Nitrite  Removal Overall, total nitrate plus nitrite reduction in the MIW cultures inoculated with the four enrichments (Lagoon A, Goddard Marsh, Bodie, and Eagle Pond) and the denitrifying sludge was slower than that measured in the previous experiment in the first passage, but it improved with increased passaging. Nitrate plus nitrite reduction measured in the negative control did not change significantly throughout the passages compared with the MIW with the same inoculum (Figure 5.1), which shows that total nitrate plus nitrite reduction might be biotic process.  In passage 1, nitrate plus nitrite reduction extent achieved by the enrichments ranged from 51 - 77% over the 12 days. The denitrifying sludge and Goddard Marsh enrichment achieved only 55% and 56% nitrate plus nitrite reduction extents, respectively. Lagoon Constituent MIW 1 (Previous experiment.), mg/L MIW 2  (This experiment), mg/L CaCO3 2610 1270 Chloride (Cl) 19 <1 Nitrate (as N) 54.9 19.4 Nitrite (as N) 0.029 0.147 Sulfate (SO4) 2030 1100 Barium (Ba)-Total 0.0092 0.0083 Calcium (Ca)-Total 404 139 Lithium (Li)-Total 0.124 0.077 Magnesium (Mg)-Total 390 225 Nickel (Ni)-Total 0.0327 <0.0050 Potassium (K)-Total 6.2 4.2 Selenium (Se)-Total 0.354 0.188 Silicon (Si)-Total 2.21 <0.50 Sodium (Na)-Total 14.4 19 Strontium (Sr)-Total 0.250 0.227 Uranium (U)-Total 0.0310 0.00819 Zinc (Zn) – Total - 0.033   127 A, Eagle Pond and Bodie Creek enrichments achieved similar nitrate reduction extents of 77%. In the subsequent passage, the extents of nitrate plus nitrite reduction increased to between 81 – 83%. The reduction extent of nitrate reduction was similar in the third passage but increased in the last passage to 93 – 95% over 6 days. As observed in the previous experiment (Chapter 4), the amounts of nitrate plus nitrite reduction achieved for each enrichment culture and the denitrifying sludge were not markedly different from each other. Raw total nitrate plus nitrite concentration data is provided in Appendix B, Table B.5.2.   Figure 5-1: Total nitrate plus nitrite concentration for actual coal MIW using enrichments with both selenate and nitrate as electron acceptors as inoculum for passages 1- 4. Points represent means and error bars the standard deviations for triplicate nitrate plus nitrite measurements for triplicate culture bottles for each treatment (n = 9).   0102030405060700 2 4 6 8 10 12 0 2 4 6 0 2 4 6 0 2 4 6Total Nitrate + Nitrite conc. mg/l Time , days ControlDenitrifying SludgeGoddard MarshLagoon ABodieEagle Pond  128 5.3.4 Total Dissolved Selenium Removal Except for the MIW cultures inoculated with Lagoon A enrichments, total dissolved selenium concentrations were removed to some extent (24 – 59%) in passage 2 in all four other treatments with enriched sediment bacteria (Figure 5.2). The inocula from Bodie Creek achieved the highest total dissolved selenium extent. This was not sustained and the extents of selenium removal decreased with increased passaging. In contrast to the experimental results in the previous MIW, Lagoon A enrichments did not achieve the best selenium removal extent. Raw total dissolved selenium concentration is provided in Appendix B, Table B.5.1.   Figure 5-2: Total dissolved selenium concentration for actual coal MIW using enrichments with both selenate and nitrate as electron acceptors as inocula for passages 1- 4. Data points are average of triplicate total dissolved selenium measurements. Error bars represent standard deviation. 00.511.522.530 4 8 12 0 4 8 12 0 4 8 12 0 4 8 12Total Dissolved Selenium conc., mg/lTime, daysControlDenitrifying sludgeGoddard MarshLagoon ABodieEagle Pond  129 5.4 Discussion The rates of nitrate reduction were much slower than those observed in the previous experiment for the same sources of inocula, Goddard Marsh and Lagoon A enrichments. This slow nitrate reduction might have been the case if the fractions of viable cells inoculated into the nutrient-amended MIW were very low. The inocula were prepared from glycerol stocks, which had been stored in the fridge at -80 oC for more than year, unlike the previous inocula that were prepared from the actual sediments. The activation period might not have been long enough to resuscitate the glycerol stock microbes to the levels of viability achieved in the previous experiment inocula preparation. Nevertheless the cultures did adapt to the nutrient-amended MIW with greater than 90% nitrate reduction achieved at least within 24 hours for each treatment from passage 2 onwards.  Although the results for total dissolved selenium removal were promising in passage 2, it appears as if the cultures lost the dissolved selenium reduction straight thereafter. The lag period observed in the cultures that were able to reduce total dissolved selenium in passage 2 might have been due to the persistance of nitrate. Once most of the nitrate was reduced, denitrifying bacteria could metabolize selenate instead. The 12-day retention time was still not long enough to achieve removal of all dissolved selenium. Since greater than 90% nitrate removal was achieved in passage 2, there must have been enough denitrifying bacteria present in the cultures to reduce selenium since it was present at much lower concentrations. It was surprising that the Lagoon A enrichments did not achieve as much selenium reduction as the other enrichments as was seen in the previous experiments. Likely differences in the concentration of cells within each culture account for the differences in reduction rate observed. Unfortunately, cell concentrations were not measured in this experiment.  The slow dissolved selenium removal rates compared with the observed nitrate removal rates, suggest that there was either the presence of chemical constituents in the MIW that inhibited dissolved selenium removal, or that some micronutrients essential for selenate reducion were not supplied (such as molybdenum and iron).    130 It is difficult to explain why reduction of dissolved selenium decreased in passages 3 and 4 despite nitrate removal to greater than 90% within at least 24 hours.                         131 Chapter 6 : Functional Characterization of the Microorganisms in the Enrichment and Actual Mine water Cultures    6.1 Synopsis In the previous experiments described in Chapters 3 and 4, sequencing of biomarkers based on the 16S rRNA V4 variable region was used to identify the microbial community composition of the enrichments (Chapter 3) and MIW treatment cultures (Chapter 4). This provided information about the microorganisms present in those cultures and their taxomony (i.e. identity). From this, functional information had to be inferred based on published information for closely related known culturable species. Thus, based on 16S rRNA, identification of the species responsible for denitrification and dissolved selenium reduction was speculative. To overcome this shortcoming and identify the actual species with the capacity for nitrate and / or dissolved selenium reduction, functional biomarker genes were identified from whole DNA sequencing and metagenomic assembled genome (MAG) binning.  Some samples used for this functional metagenomics study came from the Goddard Marsh and Lagoon A GM2 enrichments (Chapter 3) since these were the two enrichments that achieved the most promising performance of dissolved selenium removal in the presence of nitrate, and were used to inoculate the nutrient-amended MIW. Additionally, samples collected from cultures at the beginning of passage 1 and at the end of each of the five passages in the nutrient-amended MIW experiments (Chapter 4) were also used for functional metagenomic analysis. Whole DNA extracted from all these samples, with the methods described in Chapters 3 and 4, was used to assemble genomes for the dominant microbial species. Having the almost complete genome for a microorganism informs us of its metabolic potential, from which we can identify putative species capable of denitrification and selenate reduction.  The types of   132 enzymes present in the organism can help to identify the pathways, and thus potential mechanisms, for selenate reduction. 6.2 Materials and Methods 6.2.1 Sample Collection The samples used for this study were collected from two different experiments; 1) the enrichments in GM2 of Goddard Marsh and Lagoon A sediments (Chapter 3) that were also used as inocula for the MIW treatment experiments, and 2) the MIW treatment experiments performed with these two enrichments (Chapter 4). The DNA used for whole DNA sequencing was the same as the DNA that was used for amplification and sequencing of the 16S rRNA V4 region (Table 6.1).    Table 6.1: Samples used for metagenomic sequencing   S/N Origin of Sample Experiment Passage Metagenome Assembly 1 Goddard Marsh GM2 Enrichment (Chapter 3) 3 1 2 Lagoon A GM2 Enrichment (Chapter 3) 3 2 3 Goddard Marsh Mining-influenced water (Chapter 4) 1 3 4 Goddard Marsh Mining-influenced water (Chapter 4) 3 5 Goddard Marsh Mining-influenced water (Chapter 4) 4 6 Goddard Marsh Mining-influenced water (Chapter 4) 5 7 Lagoon A Mining-influenced water (Chapter 4) 1 4 8 Lagoon A Mining-influenced water (Chapter 4) 3 9 Lagoon A Mining-influenced water (Chapter 4) 4 10 Lagoon A Mining-influenced water (Chapter 4) 5    133 6.2.2 DNA Extraction and Illumina Metagenomic Sequencing Microbial genomic DNA was extracted from the 10 samples using the FastDNA® SPIN kit for soil (MoBio Laboratories Inc. USA) according to the manufacturer’s protocol. Extracted DNA concentrations were determined with a Qubit 3.0 fluorometer (Thermo Fisher, USA). These DNA samples were used for the 16S rRNA V4 variable region amplification and sequencing as described in Chapters 3 and 4. DNA for the whole DNA sequencing libraries was prepared using the NexteraXT kit according to the manufacturer’s protocol. Paired-end sequencing was performed with Illumina NextSeq technology at the Sequencing and Bioinformatics Consortium (UBC Faculty of Pharmaceutical Sciences) to yield 150 bp paired-end reads.   6.2.3 Metagenome Assembly and Binning   Reads were trimmed using the software trim_galore (https://www.bioinformatics. babraham.ac.uk/projects/trim_galore/) to remove any adapters, as well as all reads shorter than 150 bp and those with an average quality score below 25. All trimmed reads were combined for multiple samples in each culture and co-assembled into contigs using the Megahit assembler (Li et al., 2015). Following this, the good quality raw reads were mapped back onto the assembled contigs using BWA-MEM software (Li, 2013), which resulted in output as a SAM file with information on coverage of the contigs. The SAM file was converted to a BAM file using Samtools (Li et al., 2009). The metagenomic contigs were sorted into genome bins based on coverage and tetranucleotide frequency using the software MetaBat (https://bitbucket.org/berkeleylab/metabat) with minimum contig length of 2500 base pairs and superspecific and supersensitive settings to optimize completeness and minimize contamination.      134 6.2.4 Bin Completeness Check, Contamination, Taxonomy Assignment and Annotation  The contamination and completeness of the obtained genome bins were assessed using the software CheckM (Parks et al., 2014). Bins with completeness greater than 40% and contamination less than 10% were used for further downstream analyses. Taxonomy was assigned to each genome bin based on homology of open reading frames (ORFs) to a curated library of single copy genes using the software Phylosift version 1.0.0_02 (Darling et al., 2014). The open reading frames (ORFs) for functional proteins in each of the genome bins were identified and annotated using Metapathways software (Konwar et al., 2013) and the Uniprot90 database (http://www.uniprot.org/). Specific functional protein databases for the enzymes of interest were extracted from Uniprot90 for the nitrate reduction pathways (NapA, NarGHI, NirK, NirS, NosZ, NrfA and NorB) and sulfate reduction pathway (DsrAB) were used for the annotation with Metpathways (Table 6.2) with the reaction pathways for these enzymes illustrated below (Figure 6.1 – 6.3). A custom database of DMSO (dimethyl sulfoxide) reductases that include selenate reductases was used for identification and annotation of putative selenate reductases in the genome bins.              135 Table 6.2: Enzymes of interest and the reaction pathways Enzyme Abbreviation Reaction Pathway Perisplasmic nitrate reductase NapA Respiratory reduction of nitrate to nitrite Membrane bound complex nitrate reductase NarGHI Copper containing-nitrite reductase  NirK Respiratory reduction of nitrite to nitric oxide Cytochrome nitrite reductase NirS Nitric oxide reductase NorB Respiratory reduction of nitric oxide to nitrous oxide Nitrous oxide reductase NosZ Respiratory reduction of nitrous oxide to dinitrogen Nitrite reductase NrfA Respiratory reduction of nitrite to ammonia Selenate reductase SerA Respiratory selenate reduction to selenite Sulfite reductase DsrAB Respiratory reduction of sulfite to hydrogen sulfide    Figure 6-1: Nitrate reduction pathways: nitrogen compounds are indicated between arrows, the processes are indicated as arrows and the enzymes next to the arrows.    136  Figure 6-2: Selenate reduction pathways: selenium compounds are indicated between arrows, the processes are indicated as arrows and the enzymes indicated next to the arrows.    Figure 6-3: Sulfate reduction pathways: sulfur compunds are indicated between the arrows, processes are indicated as arrows and the enzymes next to the arrows.   6.3 Results  6.3.1 Number of Reads and Base pairs After trimming and filtering out the low quality reads, the number of high quality reads obtained for each sample ranged from 6.016 million to 26.14 million reads (mean 19.060 million and standard deviation 5.884 million) (Table 6.3). The overall number of base pairs for each sample ranged from 781.27 Mbp to 2.956 Gbp (mean 2.197 Mbp and standard deviation 631.473 Mbp). The most reads were obtained from the Lagoon A enrichments and the least from the Goddard Marsh enrichments inoculated into the MIW (Table 6.3).  After assembling the high quality reads into contigs combining samples as indicated in Table 6.3, the contigs in each of the four metagenome assemblies were binned into   137 putative genomes (Tables 6.4 – 6.7). Six draft genomes (bins) were obtained for the Goddard Marsh sediments enriched in the selenate plus nitrate growth medium with percentage completeness ranging from 61.68 to 98.73%, and contamination ranging between 0 – 9.77% (Table 6.4). Twelve draft genomes were obtained from the nutrient-amended MIW cultures inoculated with the Goddard Marsh enrichment with percentage completeness ranging between 49.14 – 100% and contamination from 0 – 8.51% (Table 6.5). Eleven draft genomes were obtained from the DNA sequenced from the Lagoon A sediment GM2 enrichments (Table 6.6). Eleven draft genomes were recovered from the nutrient-amended mining-influenced water cultures inoculated with Lagoon A enrichment with percentage completeness ranging between 44.51 and 99.37% and contamination ranging between 0 and 9.67% (Table 6.7).                138 Table 6.3: Total number of reads and base pairs in each metagenome S/N Sample Name Total Number of Reads Total Base Pairs (bp) 1 Goddard-Marsh-1-EP-P4_S5_R1 25,523,646 2,865,853,930 2 Goddard-Marsh-1-EP-P4_S5_R2 25,523,646 2,879,759,487 3 Goddard-Marsh-2-EP-P5_S7_R1 6,015,746 781,267,716 4 Goddard-Marsh-2-EP-P5_S7_R2 6,015,746 783,365,098 5 Goddard-Marsh-Enrichment_S9_R1 25,266,199 2,765,430,657 6 Goddard-Marsh-Enrichment_S9_R2_ 25,266,199 2,776,466,819 7 Goddard-Marsh-EP-P1_S1_R1 17,426,028 2,005,955,147 8 Goddard-Marsh-EP-P1_S1_R2 17,426,028 2,012,026,187 9 Goddard-Marsh-EP-P3_S3_R1 15,325,162 1,716,566,432 10 Goddard-Marsh-EP-P3_S3_R2 15,325,162 1,704,934,331 11 Lagoon-A-Enrichment_S10_R1_ 26,146,033 2,956,669,273 12 Lagoon-A-Enrichment_S10_R2 26,146,033 2,942,882,058 13 Lagoon-A-EP-P1_S2_R1 17,846,828 2,085,013,795 14 Lagoon-A-EP-P1_S2_R2 17,846,828 2,075,557,352 15 Lagoon-A-EP-P4_S6_R1_ 20,713,950 2,487,465,073 16 Lagoon-A-EP-P4_S6_R2 20,713,950 2,462,192,868 17 Lagoon-A-EP-P5_S8_R1 16,462,214 1,982,120,984 18 Lagoon-A-EP-P5_S8_R2_ 16,462,214 1,964,862,306 19 Lagoon-A-EP-P3_S4_R1 19,876,959 2,349,762,889 20 Lagoon-A-EP-P3_S4_R2 19,876,959 2,334,348,336   Average 18,288,702 2,106,006,895  Table 6.4: Characteristics of draft genomes for Goddard Marsh enrichment culture. (Information provided in Tables 6.4 to 6.7 was obtained from the checkm software output). Bin Id Lineage Completeness Contamination Strain Heterogeneity GM_Enrich_1 p__Firmicutes 98.73 2.06 0 GM_Enrich_3 p__Bacteroidetes 82.86 2.46 42.86 GM_Enrich_4 k__Bacteria 82.76 0 0 GM_Enrich_5 o__Bacteroidales 82.74 3.29 54.55 GM_Enrich_7 o__Bacteroidales 69.31 9.77 33.33 GM_Enrich_8 o__Clostridiales 61.68 1.9 33.33   139 Table 6.5: Characteristics of draft genomes in the nutrient-amended MIW inoculated with Goddard Marsh enrichment. Bin Id Lineage Completeness Contamination Strain Heterogeneity GM_EP_1 o__Selenomonadales 100 0 0 GM_EP_2 f__Enterobacteriaceae 98.48 1.02 30.77 GM_EP_3 f__Enterobacteriaceae 98.03 8.51 45.26 GM_EP_4 c__Gammaproteobacteria 97.9 0.14 0 GM_EP_5 o__Bacteroidales 96.54 0.87 25 GM_EP_6 o__Clostridiales 95.57 1.4 0 GM_EP_7 o__Bacteroidales 95.16 2.47 50 GM_EP_8 p__Proteobacteria 89.93 2.38 70 GM_EP_9 p__Proteobacteria 88.71 0.85 33.33 GM_EP_10 p__Firmicutes 69.18 1.9 0 GM_EP_11 c__Bacilli 52.97 0 0 GM_EP_12 k__Bacteria 49.14 1.72 100   Table 6.6: Characteristics of draft genomes in the Lagoon A enrichment culture Bin Id Lineage Completeness Contamination Strain Heterogeneity LA_Enrich_2 p__Firmicutes 99.37 2.37 0 LA_Enrich_3 o__Bacteroidales 98.89 1.73 80 LA_Enrich_4 f__Enterobacteriaceae 98.31 1.27 0 LA_Enrich_5 o__Lactobacillales 98.09 5.1 12 LA_Enrich_6 f__Enterobacteriaceae 98.08 0 0 LA_Enrich_7 o__Clostridiales 97.16 0 0 LA_Enrich_9 p__Bacteroidetes 73.68 1.83 20 LA_Enrich_10 o__Selenomonadales 72.9 7.49 17.39 LA_Enrich_11 o__Clostridiales 70.98 0 0 LA_Enrich_13 g__Clostridium 66.99 1.6 0 LA_Enrich_15 o__Bacteroidales 44.51 9.67 46.88     140 Table 6.7: Characteristics of draft genomes for the nutrient-amended MIW inoculated with Lagoon A enrichment. Bin id Lineage Completeness Contamination Strain Heterogeneity LA_EP_1 p__Proteobacteria 99.49 0.65 33.33 LA_EP_2 p__Proteobacteria 99.33 0.85 25 LA_EP_3 p__Firmicutes 99.28 2.37 0 LA_EP_4 o__Bacteroidales 99.23 0.32 0 LA_EP_5 f__Enterobacteriaceae 99.01 0.91 20 LA_EP_6 f__Rhodobacteraceae 98.16 1.63 0 LA_EP_7 c__Clostridia 88.12 2.36 23.26 LA_EP_8 o__Clostridiales 87 3.38 0 LA_EP_9 o__Selenomonadales 81.42 0 0 LA_EP_10 p__Bacteroidetes 71.56 0.95 0 LA_EP_11 o__Clostridiales 67.31 0 0   6.3.2  Taxonomic Classification of the Bins The taxonomic classification of the genome bins for the enrichment and MIW cultures are shown in Tables 6.8 – 6.15. Four of the Goddard Marsh enrichment bins were assigned to known genera:  Pelosinus, Parabacteroides, Bacteroides and Coprococcus, respectively. One bin was classified to family-level only: Peptostreptococcaceae. Only one of these genera, Bacteroides, was among the dominant Otus identified through 16S rRNA sequencing (i.e. Otu16 in Figure 3-4, Chapter 3).  More genome bins were obtained from the four MIW cultures inoculated with Goddard Marsh enrichment due to the greater amount of DNA overall and the multiple time points sampled. Bins with taxonomic assignment to the genera Pelosinus and Bacteroides, were found in both the enrichment culture and the nutrient-amended MIW cultures. Most of the bins were assigned to the same genus-level taxonomy as the dominant Otus identified through 16S rRNA sequencing. Exceptions included Citrobacter-, Parabacteroides-, Pelosinus- and Lysinibacillus-related bins that were not among the dominant Otus identified with 16S rRNA sequencing. Dominant Otus assigned to Macellibacteroides   141 and Enterobacteraceae were not identifiable in any of the bins. Veillonella and Sulfurospirillum were identified in the nutrient-amended MIW cultures by both 16S and whole DNA sequencing.   Table 6.8: Phylogenetic analysis for Goddard Marsh enrichment. Bin Id Genus % Of Single Copy Genes Species % Of Single Copy Genes GM_Enrich_1 Pelosinus 43 Pelosinus fermentans 67 Pelosinus_ unassigned 33 Unassigned 32    Acetonema 18 Acetonema longum  67 Acetonema_ unassigned 33 Thermosinus 5 Thermosinus carboxydivorans 67 Thermosinus _unassigned 33 Anaeromusa 2 Anaeromusa acidaminophila 67 Anaeromusa _unassigned  33 GM_Enrich_4 Unclassified_ Peptostreptococcaceae 76     GM_Enrich_5 Bacteroides 50     Unassigned_Bacteroides 50     GM_Enrich_7 Unassigned 44     Parabacteroides 27 Parabacteroides goldsteinii 79 Parabacteroides_Unassigned  21 Bacteroides 15    Unassigned_Bacteroides 14    GM_Enrich_8 Coprococcus 100 Coprococcus catus 100    142 Table 6.9: Phylogenetic analysis for Goddard Marsh enrichment inoculated into nutrient - amended MIW. Bin Id Genus % Of Single Copy Genes Species % Of Single Copy Genes GM_EP_1 Veilloneila 100  Vellloneila _unassigned 97 Velloneila ratti 3 GM_EP_2 Citrobacter 100 Citrobacter freundii complex 73 Unassigned citrobacter 16 Citrobacter sp. 30_2 6 Citrobacter sp. UC1CIT 5 GM_EP_3 Escherichia 100 Escherichia hermanii  100 GM_EP_4 Pseudomonas 100 Pseudomonas sp Chol1 70 Pseudomonas putida group 12 Pseudomonas stutzeri group 12 Pseudomonas_ unassigned  6 GM_EP_5 Parabacteroides 91 Parabacteroides goldsteinii  99 Parabacteroides _unassigned  1 Tannerella 9 Tannerella forsythia 100 GM_EP_6 Sedimentibacter 96 Sedimentibacter sp.B4  50 Sedimentibacter_ unassigned 50 Unassigned  4     GM_EP_7 Bacteroides 65 Bacteroides _unassigned 55 Bacteroides fragils 29 Bacteroides salyersiae 16 Unassigned  35     GM_EP_8 Sulfurospirillum 100 Sulfurospirillum_unassigned 61 Sulfurospirillum deleyianum 26 Sulfurospirillum barnessi 12 GM_EP_9 Sulfurospirillum 100 Sulfurospirillum_unassigned 62 Sulfurospirillum barnessi 28 Sulfurospirillum deleyianum 10 GM_EP_10 Pelosinus 38 Pelosinus fermentans  50 Pelosinus_ unassigned  50 Unassigned  25     Acetonema 20 Acetonema longum  67 Acetonema_ unassigned 33 Thermosinus 14 Thermosinus carboxydivorans  67   143 Bin Id Genus % Of Single Copy Genes Species % Of Single Copy Genes  Thermosinus_unassigned 33 Anaeromusa 3 Anaeromusa acidaminophila 67 Anaeromusa _unassigned 33 GM_EP_11 Lysinibacillus 100 Lysinibacillus fusiformis 100 GM_EP_12 Escherichia 80 Escherichia coli 100 Shigella 14     Salmonella 2     Unassigned 4       For the Lagoon A enrichment, nine bins with greater than 40% completion and less than 8% contamination were identified. Two of these were from the archaeal domain. Comparison with the 16S rRNA sequencing revealed that only the genera Serratia, Methanosarcina, and Clostridium were identified with both 16S and whole DNA sequencing. In the nutrient-amended MIW inoculated with Lagoon A enrichment, bins LagoonA_EP_1 and LagoonA_EP_2 were classified in the same genus, Sulfurospirillum and may represent two strains. This genus was also identified in bins GM_EP_8 and GM_EP_9 from the MIW cultures inoculated with Goddard Marsh enrichment. The 16S rRNA sequencing revealed the genus; Sulfurospirillum was the most predominant genus when Goddard Marsh and Lagoon A enrichments were inoculated into the MIW. Other genera such as Veillonella and Paracoccus were also identified using 16S sequencing.          144 Table 6.10: Phylogenetic analysis for Lagoon A enrichments  Bin Id Genus % Of Single Copy Genes Species % Of Single Copy Genes LA_Enrich_3 Parabacteroides 94 Parabacteroides goldsteinii 90 Parabacteroides_ unassigned 10 Tannerella 6 Tannerella forsythia 100 LA_Enrich_4 Escherichia 100 Escherichia hermannii 100 LA_Enrich_5 Carnobacterium 42    Unassigned 8    LA_Enrich_6 Serratia 65 Serratia marcessen 100 Citrobacter 19 Citrobacter sp. UC1CIT 100 Unassigned 16    LA_Enrich_7 Eubacterium infirmum 47 Eubacterium infirmum F0142 50 Eubacterium infirmum_unassigned 50 Unassigned 30    Mogibacterium 23 Mogibacterium sp. CM50 50 Mogibacterium _unassigned 50 LA_Enrich_8 Methanosarcina 100 Methanosarcina mazei 90 Methanosarcina_ unassigned 8 Methanosarcina barkeri 1 LA_Enrich_10 Acidaminococcus 42 Acidaminococcus acidaminophila 67 Acidaminococcus _unassigned 33 LA_Enrich_11 Falifacter 89 Falifacter alocis 67 Falifacter_unassigned 33 Clostridium sticklandii 11 Clostrium sticklandii DSM 519 50  Clostrium sticklandii DSM 519_unassigned 50 LA_Enrich_13 Clostridium 100 Clostridium tunisiense  80 Clostridium sp. JC 122 20    145  Table 6.11: Phylogenetic analysis for Lagoon A enrichments inoculated into nutrient-amended MIW Bin Id Genus % Of Single Copy Genes Species % Of Single Copy Genes LA_EP_1 Sulfurospirillium 100 Sulfurospirillum _unassigned 56 Sulfurospirillum deleyianum 26 Sulfurospirillum barnesii 18 LA_EP_2 Sulfurospirillium 100 Sulfurospirillum _unassigned 56 Sulfurospirillum deleyianum 26 Sulfurospirillum barnesii 18 LA_EP_3 Pelosinus 40 Pelosinus fermentas 50 Pelosinus_unassigned 50 Acetonema 23 Acetonema longum 67 Acetonema_unassigned 33 Thermosinus 7 Thermosinus_carboxydivorans 67 Thermosinus_unassigned 33 Anaeromusa 3 Anaeromusa acidaminophilia 67 Anaeromusa_unassigned 33 LA_EP_4 Parabacteroides 89 Parabacteroides goldsteinii 85 Parabacteroides_ unassigned 15 Tannerella 11 Tannerella forsythia 100 LA_EP_5 Citrobacter 100 Citrobacter sp. UC1C1T 50 Citrobacter sp. 30_2 17 Citrobacter freundii complex 17 Citrobacter_unassigned 17   146 Bin Id Genus % Of Single Copy Genes Species % Of Single Copy Genes LA_EP_6 Paracoccus 92 Paracoccus denitrificans 66 Paracoccus _unassigned 19 Paracoccus sp. TRP 8 Paracoccus sp. N5 7 Rhodobacter 8 Rhodobacter sphaeroides 100 LA_EP_7 Unassigned 30   Helibacterium 20 Helibacterium modesticaldum 67 Helibacterium_unassigned 33 Unassigned Peptococcaceae 10   Coprococcus 10 Coprococcus catus 100 Unclassified Clostriadale msc 10 Clostriadale Genomo SP. BVA B3 100 Clostriadale family XIII incertae sedis 9 Eubacterium infirmum 100 Unassigned Helibacteriaceae 7   LA_EP_8 Clostridium 60 Clostridium _unassigned 51 Clostridium_perfringens 46 Clostridium celatum 3 Candidatus arthromitus 30   Unassigned 10   LA_EP_9 Veillonella 100 Veillonella_unassigned 97 Veillonella ratti 3    147 6.3.3: Functional Genes Present in Putative Genome Bins Genome bins containing genes encoding enzymes relevant to nitrate, selenate and sulfate reduction (Tables 6.12 – 6.15) were identified. The Goddard Marsh enrichment culture bin GM_enrich_8 (Coprococcus) genome encoded an enzyme for dissimilatory selenate reduction SerA (Brenda E.C. 1.97.1.9) and the genomes of the two bins LA_Enrich_4 (Escherichia) and LA_Enrich_6 (Serratia) from the Lagoon A enrichment also encoded for selenate reductase enzyme SerA (Brenda E.C. 1.97.1.9) (Tables 6.12 – Table 6.13). None of the draft genomes retrieved from the two enrichment cultures encoded for the complete denitrification pathway enzymes all the way from nitrate to dinitrogen gas. No bins from the enrichment cultures encoded the nitrite reductases NirK and NirS or nitrous oxide (NosZ) reductase enzymes. Both enrichments had draft genomes that encoded the same enzymes (SerA, NapA, NorB, NrfA, DsrAB) that were screened for in this experiment. The pentaheme nitrate reductase (NrfA) gene for dissimilatory nitrite reduction to ammonia was found in the Lagoon A enrichment bins in the putative species: LA_Enrich_3 (Parabacteroides), and LA_Enrich_4 (Escherichia).              148 Table 6.12: Absence and presence analysis of nitrate, selenate and sulfate reductases enzyme in Goddard Marsh enrichment. Green indicates presence of nitrate reductase gene, orange indicate the presence of selenate reductase gene and light blue indicate the presence of sulfate reductase gene. Light grey indicates the absence of genes. Bin id NapA NarGHI NirK NirS NorB NosZ NrfA   SerA (Brenda E.C. 1.97.1.9)    Dsr AB GM_Enrich_1                       GM_Enrich_4                       GM_Enrich_5                       GM_Enrich_7                       GM_Enrich_8                                              149 Table 6.13: Absence and presence analysis of nitrate, selenate and sulfate reductase enzyme in Goddard Marsh enrichment in amended MIW. Green indicates presence of nitrate reductase gene, orange indicate the presence of selenate reductase gene and light blue indicate the presence of sulfate reductase gene. Light grey indicates the absence of genes. Bin id NapA NarGHI Nir K Nir  S NorB Nos Z NrfA   SerA (Brenda E.C.1.97.1.9)   Dsr AB GM_EP_1                       GM_EP_2                       GM_EP_3                       GM_EP_4                       GM_EP_5                       GM_EP_6                       GM_EP_7                       GM_EP_8                       GM_EP_9                       GM_EP_10                       GM_EP_11                       GM_EP_12                            150 For the MIW inoculated with Goddard Marsh enrichments, six bins, GM_EP_1 (Veillonella), GM_EP_2 (Citrobacter), GM_EP_3 (Escherichia), GM_EP_4 (Pseudomonas), GM_EP_8 (Sulfurospirillum) and GM_EP_12 (Escherichia) encoded for a selenate reductase enzyme.  Five bins from the MIW cultures inoculated with Lagoon A enrichment encoded for the selenate reductase, SerA (Brenda E.C 1.97.1.9). For both of the MIW cultures inoculated with enrichments, the bins GM_EP_4 (Pseudomonas) and Lagoon A_EP_6 (Paracoccus) encoded the enzymes for complete denitrification (NapA, NarGHI, NirK or NirS, NorB and NosZ) (Tables 6.14 – 6.15).  Each culture had bins with capabilities for both membrane-bound (NarGHI) and perisplasmic (NapA) nitrate reductases. Only the copper containing nitrite reductase (NirK) enzyme was not encoded in any of the bins for the four cultures. More genome bins were obtained from the MIW cultures due to the overall greater amount of sequenced DNA read that were obtained for these cultures and because multiple time point samples were processed, which improves genome binning.     151 Table 6.14: Absence and presence analysis of nitrate reductase, selenate reductase and sulfate reductase enzyme in Lagoon A enrichment. Green indicates presence of nitrate reductase gene, orange indicates the presence of selenate reductase gene and light blue indicates the presence of sulfate reductase gene. Light grey indicates the absence of genes.  Bin id NapA NarGHI Nir K NirS Nor B Nos Z Nrf A   SerA (Brenda E.C.1.97.1.9)   Dsr AB LA_Enrich_3                       LA_Enrich_4                       LA_Enrich_5                       LA_Enrich_6                       LA_Enrich_7                       LA_Enrich_8                       LA_Enrich_10                       LA_Enrich_11                       LA_Enrich_13                                     152 Table 6.15: Absence and presence analysis of nitrate reductase, selenate reductase and sulfate reductase enzyme in Lagoon A enrichment inoculated into amended MIW. Green indicates presence of nitrate reductase gene, orange indicates the presence of selenate reductase gene and light blue indicates the presence of sulfate reductase gene. Light grey indicates the absence of genes. Bin Id NapA NarGHI Nir K NirS Nor B Nos Z Nrf A   SerA (Brenda E.C.1.97.1.9)   Dsr AB LA_EP_1                       LA_EP_2                       LA_EP_3                       LA_EP_4                       LA_EP_5                       LA_EP_6                       LA_EP_7                       LA_EP_8                       LA_EP_9                             153 6.4 Discussion 6.4.1 Microorganisms Capable of Performing Denitrification and / or Selenate Reduction  One genome bin from the Goddard Marsh enrichment had a gene for selenate reductase. This bin was classified, with highest probability, to Coprococcus catus (100%). A search through the KEGG database (https://www.kegg.jp/dbget-bin/www_bget?cct:CC1_06320, date accessed July 21st, 2018) for species known to have selenate reductases (Brenda E.C. 1.97.1.9) found that the Coprococcus catus GD/7 (accession number FP929038.1) genome has a putative selenate reductase gene. Surprisingly, no Otus classified as Coprococcus were identified by 16S rRNA sequencing, even though both sequencing methods used the DNA from the same extraction. Lin et al., (2015) reported about assimilatory selenate reduction for the synthesis of selenoproteins in Coprococcus species.   In the Lagoon A enrichment, two genome bins classified as Serratia marcessen and Esherichia hermanii, respectively contained sequences for putative selenate reductase (Brenda E.C. 1.19.7.1). In the Goddard Marsh enrichment inoculated MIW, Escherichia hermanii, Citrobacter freundii complex, Pseudomonas sp., Escherichia coli, Sulfurospirillum_unassigned and Veillonella _unassigned encoded the selenate reductase enzyme (Brenda E.C. 1.19.7.1). Zhang et al., (2008) reported that Citrobacter freundii was capable of reducing selenate with molasses as the electron donor. Pearce et al., (2008) reported that the species, Veillonella atypical reduce selenite to elemental selenium. Bins from the MIW inoculated with Lagoon A enrichment that had selenate reductase genes SerA (Brenda E.C. 1.19.7.1) were; Paracoccus denitrificans, Citrobacter sp. UC1CIT, Pelosinus fermentans (50%), Pelosinus_unassigned (50%), and Sulfurospirillum_unassigned. The genus, Sulfurospirillum was found to be the most dominant genus when the inoculum from Goddard Marsh was used to inoculate the actual MIW as revealed by the 16S rRNA sequencing. Bacterial strain from this genus, Sulfurospirillum barnesii SES3 has been reported to be capable of respiring selenate and selenite (Stolz et al., 1999; Oremland et al., 1994). The perisplasmic (NapA) and   154 membrane-bound nitrate reductase enzyme (NarGHI) of Paracoccus denitrificans and Escherichia coli can reduce selenate (Sabaty et al., 2001). The bacterium, Escherichia coli has been well studied as an example of assimilatory selenium reduction to elemental selenium (Turner et al., 1998). However, it has not been reported whether the bacteria Escherichia hermanii and Pelosinus fermentans are capable of reducing selenate.  However, a search through the KEGG database (https://www.kegg.jp/kegg-bin/show_organism?org=pft, date accessed July 20th 2018) found the organism Pelosinus fermentans JBW45 with (accession number CP010978.1) posses the putative selenate reductase SerA (Brenda EC.1.97.1.9).  Complete denitrification and dissimilatory nitrate reduction to ammonia (DRNA) were the nitrate reduction pathways when the enrichments were inoculated into the amended MIW.  A closely related species to this genome bin (Sulfurospirillum barnesii) have been reported to be capable of simultaneously reducing nitrate and selenate (Oremland et al., 1999). The species Pseudomonas sp, encoded the complete denitrification pathway from nitrate to dinitrogen gas enzymes (NapA, NarGHI, NorB and NosZ) in the Goddard Marsh enrichment inoculated MIW cultures. Subedi et al., (2017) identified Pseudomonas as one of the dominant species involved in denitrification in an enrichment culture.  A bin recovered from the Lagoon A enrichment inoculated MIW cutlures classified as Paraccocus denitrificans encoded the complete denitrification enzymes (NapA, NarGHI, NirK, NorB and NosZ). This species is a well-studied denitrifying bacterium (Zumft, 1997). It’s been reported that the NapA or NarGHI enzymes of most denitrifiers are capable of reducing selenate (Sabaty et al., 2001). The results of the experiments show that the microbial community in the enrichments and the MIW were able to use nitrogen compounds in different ways and that contributed together as nitrogen sink. Taken together, the species identified with whole DNA sequencing that was also identified using the 16S rRNA sequencing is provided in Table 6-16.     155 Table 6.16: Genomic bins with putative selenate reductase SerA, their taxonomic assignment and whether they were identified in 16S rRNA sequencing for enrichments and nutrient-amended MIW.  Bin Id Taxonomic Assignment Dominant Otu in Enrichments Dominant Otu in nutrient - amended MIW GM_Enrich_8 GM_EP_1 Coprococcus Veillonella               −               +           −           + GM_EP_2 LA_EP_5 Citrobacter               −            − GM_EP_3 GM_EP_12 LA_Enrich_4  Escherichia                             −                    +  GM_EP_4 Pseudomonas             +         + GM_EP_8 LA_EP_2 Sulfurospirillum                          +                 + LA_Enrich_6 Serratia             +         − LA_Enrich_3 Pelosinus             −         − LA_EP_6 Paracoccus            +         + LA_EP_7 Unassigned Clostridiales           −         − + Present, − absent  6.4.2 Possible Mechanisms for Selenate Reduction  Based on the nitrate and selenate reductases identified in the enrichments and the actual MIW cultures and the microbial species containing these genes, possible mechanisms for total dissolved selenium reduction can be identified. The first step in dissimilatory selenate reduction pathway is the reduction of selenate to selenite. Depending on the microbial community, the intermediate selenite is either released or further reduced to elemental selenium. The first step of the dissimilatory selenate reduction can be catalyzed by either nitrate (NapA or NarGHI) or selenate SerA  (Brenda E.C. 1.97.1.9) reductase. The reduction of selenite to elemental selenium can be catalyzed by nitrite reductase (NirK or NirS) (DeMoll-Decker and Macy, 1993).     156 For the two enrichment cultures and nutrient-amended MIW cultures, no gene encoding nitrite reductase (NirK or NirS) enzymes were detected in any of the assembled genome bins. This suggests that other microorganisms in the cultures were capable of nitrite reduction.  Regarding selenate reduction in the Goddard Marsh enrichments, two species were identified with the potential for selenate reduction, one (Pelosinus related) containing the NapA gene and another, classified as Coprococcus catus, with a putative selenate reductase, SerA (Brenda E.C. 1.97.1.9). It is not known if the NapA enzyme had an affinity for selenate, but it is also a dimethyl sulfoxide enzyme like selenate reductases. Surprisingly, no Pelosinus or Coprococcus genera were identified in the 16S rRNA sequencing for the Goddard Marsh enrichments. The depth of sequencing for the whole DNA metagenomic analysis was not great enough to capture all the genomes of all the dominant organisms in the Goddard Marsh enrichment. Additionally, the binning procedure works more efficiently if there are more samples (at different time points, for instance) available for the culture. For both the Goddard Marsh and Lagoon A enrichments, only one sample from the last timepoint was available for whole DNA sequencing. In contrast more DNA sequence data were available for the MIW cultures since several time points taken at the end of several passages were used for binning. For Lagoon A enrichment, several speices were identified with the potential for selenate reduction: Citrobacter sp. UC1C1T, Escherichia hermanii and Serratia marcessen. All the organisms contained thioredoxin reductases, which enable selenite reduction to selenide. It is not known whether, the selenate was reduced to elemental selenium because none of the bacteria identified in the two enrichment cultures are known to reduce selenate to elemental selenium. Also no gene encoding nitrite reductase enzyme (NirK or NirS) was detected. It is possible that selenate was reduced for assimilation into selenoproteins. Further investigation of the actual selenate reductases identified is needed so as to speculate on the cellular utilization of selenate. Although reduction of total dissolved selenium was not successful in all of the passages when the enrichment cultures were inoculated into the MIW, the metagenomic study revealed several species with the potential for selenate reduction, either through nitrate   157 reductases or through selenate-specific reductases. The three dominant species in the MIW cultures had both nitrate and selenate reductases. Therefore we speculate that it was not the microbial population composition that limited selenate reduction in the MIW. Even though nitrate was removed efficiently to verify bacterial activity, something else in the MIW was inhibiting selenate reduction.  Since many of the organisms identified in the metagenomic analyses had the potential, or had demonstated the ability in culturing studies, for only parts of the dissimilatory denitrification and selenate reduction pathways, this suggests that different bacteria species interacting with each other can in concert reduce nitrate and selenate all the way to N2 gas and elemental Se. This supports the notion of a microbial consortium for effective removal of several contaminants and their intermediates, and the use of mixed cultures rather than pure cultures for coalmine wastewater treatment. Based on the metagenomic analysis of the MIW cultures inoculated with Goddard Marsh enrichments, one hypothetical scenario could be; the selenate reductase enzyme SerA (Brenda E.C. 1.97.1.9) of Pseudomonas sp catalyzes selenate reduction to selenite. This is because closely related strain of Pseudomonas, Pseudomonas sp. strain CA-5 (Hunter and Manter, 2009) and Pseudomonas sp strain RB (Ayano et al., 2014) have been reported to capable of reducing selenate to selenite. Then the species Veillonella atypical further reduces the selenite to elemental selenium to complete the selenate reduction mechanism, since this organism was shown to grow on selenite as its electron acceptor. Direct selenate reduction to elemental selenium through one organism is another mechanism for selenium removal that the communities in the MIW cultures showed the potential for. Selenate reduction all the way to elemental Se is a known mechanism for species closely related to the Citrobacter freudii complex and Sulfurospirillum_unassigned bins found in the Goddard Marsh and Lagoon A enrichements inoculated into the nutrient-amended MIW. The species Citrobacter freudii (Zhang et al., 2008) and Sulfurospirillum barnesii SES-3 (Stolz and Oremland, 1999; Oremland et al., 2004) were shown to reduce selenate to elemental selenium in culturing studies. The reduction of selenite to elemental selenium can also be a detoxification mechanism since selenite is toxic to microorganisms. All the organisms in the enrichments and MIW cultures contained   158 thioredoxin reductases that mediate selenite reduction to selenide. These selenides might be assimilated into selenoproteins or methylated to reduce the toxicity of selenium.                159 Chapter 7 : Conclusions and Recommendations  7.1 Conclusions Sediment samples were collected from different aquatic environments (vegetated marsh, creeks, tailings pond, wetlands) and tested for their capacity for removal of dissolved selenium when inoculated into a selenate reducing growth medium and incubated under anoxic conditions. At the end of the incubation period, all fifteen sediment cultures achieved dissolved selenium removal from 23 to 100%. The sediments that were sourced from aquatic environments receiving coal mine waste rock seepage achieved total dissolved selenium removal ranging from 41 to 100% whilst the selenium removal extents for a sediment from a pristine unimpacted environment was 23%. Selenium removal did not correlate with any of the field water chemistry parameters that were measured (i.e. total dissolved solids, sulfate, nitrate, total dissolved selenium concentration). This study concluded that any of the mine-affected sites sampled are suitable for sourcing microbial communities with the capability for dissolved selenium removal in a growth medium. .  Selected sediments were inoculated into two different types of growth media, one with selenate as the sole electron acceptor and the other with both selenate and nitrate as electron acceptors to test the presence of nitrate on dissolved selenium removal. Nitrate inhibition of total dissolved selenium removal rate was dependent on the source of the inoculum. Nitrate inhibited total dissolved selenium removal rate to a varying extent in four enrichment cultures with sediments sourced from Bodie Creek, Smithe Pond, West Jarvis Pond and Eagle Pond as inocula. In contrast, the presence of nitrate did not have any inhibitory effect on the rate of dissolved selenium removal from enrichment cultures inoculated with sediments from Goddard Marsh (a vegetated natural marsh receiving coal mine-affected water). For another inoculum sourced from Lagoon A (an inactive tailing pond), the rate of dissolved selenium removal was greater in the presence of nitrate than observed in the growth medium without nitrate. This study concluded that,   160 the effect of nitrate on dissolved selenium removal is mixed (stimulatory, inhibitory and no effect) depending on the types of microorganisms enriched. .  16S rRNA sequencing analysis revealed that, the dominant species that grew in selenate plus nitrate growth medium with Goddard Marsh sediments were Romboutsia, Pseudomonadaceae_unassigned, Bacteroides, Veillonellaceae_unassigned and Macellibacteroides. This microbial community might be responsible for dissolved selenium removal in the enrichment medium without inhibition from nitrate. Several species from the family, Pseudomonadaceae and Veillonellaceae are known to be capable of reducing selenate or selenite. However, these species were also found in other enrichments in different relative abundance. Metagenomics sequencing analysis revealed that the microorganism with specific selenate reductase enzyme (SerA, Brenda EC 1.97.1.9) in the Goddard Marsh enrichment was Coprococcus catus, which is a novel bacterium not already known in the literature to reduce selenate or selenate. When selected enrichment cultures (Lagoon A and Goddard Marsh) with both nitrate and selenate as electron acceptors were used as inocula for the removal of dissolved selenium from actual coal MIW containing nitrate and sulfate, total nitrite- plus nitrate-N were successfully removed but not the dissolved selenium. The measured total dissolved selenium removal was lower than that observed in the enrichment cultures over the same period of time. This was observed for two different strengths of coal MIW. Goddard Marsh and Lagoon A sediments achieved 92% and 83% total dissolved selenium removal respectively in nitrate plus selenate growth medium after 72 hours. Whilst in the actual MIW, the dissolved selenium removal was 9% and 19% respectively in the first MIW and both achieved less than 5% in the second MIW. The result of this study shows that the mine-affected sediment that was able to remove dissolved selenium without nitrate inhibition in enrichment medium was not able to effectively remove dissolved selenium in actual MIW. Metagenomic sequencing analysis revealed the microorganisms with specific selenate (SerA) and nitrate reductase genes (NarG) that were dominant in the enriched sediments were different from those that flourished in the actual MIW. The microorganism with both selenate (SerA) and nitrate reductase genes (NarG) identified in the Goddard Marsh enrichments was Coprococcus catus and when the enrichment was   161 used as inoculum for the removal of dissolved selenium in actual coal MIW, the dominant microorganisms with selenate and nitrate reductases identified were Veilloneilla_unassigned, Citrobacter freundii, Escherichia hermanii and Pseudomonas sp Chol1, Sulfurospirillum_unassigned and Escherichia coli. In the Lagoon A enrichment, the microorganisms with selenate and nitrate reductase genes identified were Escherichia hermannii and Serratia marcessen. When Lagoon A enrichment was inoculated into the actual MIW, the microorganisms with nitrate and selenate reductases identified were Sulfurospirillum_unassigned, Pelosinus fermentas, Citrobacter sp. UC1C1T, and Paracoccus denitrificans. Thus, metagenomics sequencing analysis revealed that species with metabolic potential for selenate and selenite reduction survived in the MIW cultures but surprisingly, dissolved selenium removal was low. Only the enriched Lagoon A microbial community achieved the most promising results for dissolved selenium removal from MIW since dissolved selenium removal increased steadily with increased passaging reaching 40% in the fifth passage.  The fact that the mine-affected sediments achieved high dissolved selenium removal rates in the enrichments but low dissolved selenium removal rates in the actual MIW and the fact that 16S and whole genome sequencing studies revealed that selenate-reducing bacteria survived in the actual MIW, suggest that the absence or presence of chemical constituents in the actual MIW might have inhibited the growth and activity of the selenium-reducing microorganisms. It was found that, the actual MIW was missing some essential micronutrients such as iron or the cofactors, molybdenum, nickel, zinc which are required for proper functioning of selenate reductase enzyme. Also, macronutrients such as potassium, sodium that are required for microbial growth, were missing from the actual MIW. Further experiments are required to investigate the optimal conditions required to achieve complete (100%) dissolved selenium removal in MIW using microorganism from mine-affected sediments.      162 7.2 Recommendations The following recommendations are made: There is the need to optimize the current treatment process regarding the use of native mine site bacteria to effectively remove dissolved selenium from actual coal MIW. Even though 16S and whole DNA metagenomic sequencing identified putative selenium-reducing microorganisms in the MIW cultures, the extent of dissolved selenium removal in the MIW was low (less than 50%). This suggests that some constituents present or missing in the MIW were inhibiting the growth and activity of selenate/selenite reducing bacteria. Further experiments are required to test the hypothesis: Dissolved selenium removal was low in the actual coal MIW due to the presence of inhibiting compounds or missing nutrients. These experiments could be conducted by adding the missing essential micronutrients such as iron or cofactor molybdenum, nickel, zinc and the macronutrients such as potassium, sodium to the actual coal MIW and testing for dissolved selenium removal by the mine-affected sediments.  Also, further experiments are required to investigate the effect of salinity or TDS on dissolved selenium removal from actual coal MIW by native mine site bacteria. This would provide information about the salinity tolerance levels of microbial consortia sourced from the local mine site. Its been reported that salinity or high TDS is toxic to microorganisms including denitrifying bacteria unless microorganisms are tolerant to high salinity.  Having salinity tolerant microorganisms as part of microbial consortia used to inoculate MIW treatment bioreactors could enhance the effectiveness of dissolved selenium removal from MIW, since some of the coal MIWs are saline.  The focus of this research was to investigate the removal of dissolved selenium in the presence of nitrate from MIW in a passive batch reactor without considering the influence of sulfate. I recommend further studies to test the hypothesis: High sulfate concentration interferes with selenate reduction from coal MIW. Even though it’s been reported that it’s possible to reduce selenate in the presence of sulfate, at high sulfate concentration (> 2000 mg/L), it is necessary to consider the influence of high sulfate   163 concentration on selenate reduction. There was some evidence that sulfate was reduced in the Chapters 4 and 5 experiments because of the smell of rotten eggs detected during sampling and the high relative abundance of Otus related to sulfur bacteria (Sulfurospirillum) found in all the MIW cultures. High sulfate concentration also contributes to high salinity in MIW, which is toxic to microorganisms. From chemical reaction perspective, sulfate could form species that can react with selenium or sulfur to form compounds that may inhibit or enhance microbial activities.  In general, there is the need to investigate the potential role the chemistry of the solution contributes to remediating selenium-contaminated waters.  This experiment tested for dissolved selenium removal in the presence of nitrate from coal MIW in a passive batch reactor. Further experiments are required to test for the dissolved selenium removal in active batch reactor. This experiment can be done by incubating the batch reactor in a shaker to constantly mix the contents of the reactor. The result of these experiments could also contribute to finding the optimal reactor conditions required for the effective dissolved selenium removal from MIW. Identifying microbial consortia from mine sites such as Goddard Marsh that are capable of removing dissolved selenium in enrichment cultures without inhibition from interfering electron acceptors such as nitrate or sulfate can reduce the amount of carbon required for selenium removal. This is because microorganisms that reduce selenate/selenite using non-specific enzymes such as nitrate reductase or sulfate reductases are inhibited by the presence of nitrate or sulfate. The preference for nitrate or sulfate to selenate/selenite as electron acceptor means that, these electron acceptors would be reduced first before selenate/selenite reduction and these reduction reactions consumes carbon. For instance, when nitrate is reduced with selenate, each mole of nitrate will requires 5 electron equivalent from an electron donor to be reduced to nitrogen gas.  Reduction in the amount of carbon can contribute to significant reduction in the operating cost of removing selenium from MIW in full-scale treatment plants due to the low available carbon content of MIW necessitating the addition of more exogenous carbon. I recommend that further experiment be conducted to test the   164 hypothesis: Microbial consortia in cultures that can remove selenate without inhibition from nitrate or sulfate utilize less carbon.   Also, I recommend that, the microbial consortia in the enrichment culture that removed dissolved selenium without nitrate inhibition (Goddard Marsh) be isolated as pure cultures and physiologically characterized, such as purifying the reductase enzymes and measuring the kinetics of selenate reduction in the presence of other electron acceptors (nitrate and sulfate). This will give more fundamental knowledge about these new selenium-reducing bacteria that can remove dissolved selenium without inhibition from nitrate identified in this study. This experiment was conducted using lactate as the carbon source, which is expensive and not used in industry. Further experiments are required to test the hypothesis; dissolved selenium removal rates and extents in actual coal MIW are affected by the carbon source.  This experiment could be done by testing different carbon sources, for example, methanol/ethanol, micro CTM, molasses, acetate etc. to determine how the type of carbon source affects the microbial community structure and function. This study tested the capability of different mine-affected sediments for dissolved selenium removal from coal MIW. These sediments were first enriched in growth medium before testing for dissolved selenium removal from actual coal MIW.  It was found that, there was no correlation between the inoculum that achieved higher dissolved selenium and nitrate removal in the enrichment medium and the inoculum that achieved higher dissolved selenium and nitrate removal in the actual coal MIW. For example, the microbial consortia from Goddard Marsh which was able to remove dissolved selenium without nitrate inhibition in the enrichment medium was not capable of removing dissolved selenium from the actual MIW. I recommend that further experiments be conducted to test the capabilities of native mine-affected sediments for dissolved selenium removal from MIW without first enriching them in growth media.  This study was not able to establish the mechanism for selenium removal by the mine-affected sediments. Possible mechanisms for selenium removal were discussed in Section 2.4.1 of this dissertation and were speculated to be biological. However, further   165 experiments are required to determine the specific biological mechanisms for selenium removal whether dissimilatory, assimilatory or detoxification. These experiments could be done by determining the selenium species (selenate, selenite, elemental selenium and organoselenium) present or formed during the bioremediation process.  Also, adsorption and chemical precipitation processes could also play a role in selenium removal process by the sediment in this experiment. To explore the contribution of adsorption, experiments can be done with autoclaved sediments to destroy the microorganisms, and determine the dissolved selenium removal and loadings of selenium in the sediments. To assess the potential for chemical precipition with the MIW, chemical speciation diagrams (Pourbaix or Eh versus pH diagrams) can be constructed from chemical equilibria.  A more complete kinetic study of selenium removal by microorganisms is needed. An attempt was made in Chapter 3 of the dissertation to measure the rate of selenium removal but determination of the kinetic model and its parameters was hindered due to the difficulty of quantifying biomass concentrations, and because only a few selenium and nitrate concentration versus time points were obtained.  A kinetic model is important for scaling up bioprocesses for selenium removal and calculating the hydraulic retention times need to achieve the required effluent concentrations.  These recommendations will contribute to deeeper understanding of the process conditions and the environmental variables that affect the removal of dissolved selenium in the presence of nitrate from MIW.  This will improve the effectiveness of biological treatment processes used for the treatment of MIW.         166 References APHA, AWWA, A., and WEF, (2017). Standard method for the examination of water and wastewater 23rd edition.  Edited by Baird, R.B., Eaton, A.D., and Rice, E.W. 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Rev. 61(4), 533 – 616.                       184 Appendices Appendix A: Standard operating procedure for cultivation of facultative anaerobes (Adapted from Stams et al., 1992)  Step 1: Prepare stock solutions  Mineral salt solutions (10x) per litre  Solution 1:  5g of MgSO4  Solution 2: 1.1g of CaCl2.2H2O Solution 3:  4.34g of K2HPO4 Solution 4: 1.28g of KH2PO4  Solution 5:  0.01g of FeSO4.7H2O Trace element mixture solution per litre                                  ZnSO4.7H2O             100 mg             CoCl2.6H2O              200 mg MnCl2.4H2O             30 mg Na2MoO4.2H2O        30 mg NiCl2.6H2O               10 mg CuCl2.2H2O              10 mg H3BO3                      300 mg  Vitamins mixture solution Biotin                                               20 mg Nicotiamide                                     200 mg  p-Aminobenzoic acid                      100 mg Thiamin (Vitamin B1)                     200 mg Panthotenic acid                              100 mg   185 Pyridoxamine                                  500 mg Cyanocobalamine (Vitamin B12)   100 mg  Riboflavine                                     100 mg  Solution 6:  KNO3 stock solution, 100 mg/L Solution 7:  Na2SeO4 stock solution, 1 mg/L Solution 8: L-cysteine                     0.5 g /L   Solution 9:  Resazurin                      0.5 g/L Step 2: Add before autoclaving in an Erlenmeyer flask:              100 mL each of solutions 1 - 5                 1 mL solution 9               1 mL trace element solution mixture               500 mL deionized water                 1 g yeast extract Step 5: Autoclave the mineral salt solution and stoppered and sealed culture bottles  Step 6: After autoclaving the mineral salt solution, add filter sterilized 1 mL vitamins solution Carbon source (Lactate)  KNO3 solution Na2SeO4 solution  Step 8: Add filter sterilized reducing solution (L-cysteine 0.5 g/L) to reduce the medium Step 9: Make up the solution to 1000 mL with autoclave deionized water  Step 10: Disperse into the culture bottles (always least 10% of the bottle volume for addition of inocula) Step 11: Add the inocula  Step 12: Seal the culture bottles and wrap with aluminum foil.   186 Step 13: Place the culture bottles into an incubator  Step 14: Take 10 mL samples at t=0 and at regular time intervals (1- 4 hrs) for chemical analyses (nitrate, nitrite ammonia and volatile fatty acids) and 5 mL sample preSerAved with nitric acid for total dissolved selenium analysis.  Step 15: Take biomass sample for DNA extraction. Prepare glycerol stock of inocula before and after the experiment. (To prepare glycerol stock, add the inocula to a sterilized glycerol solution with a final concentration of 25% glycerol and stored at -80 oC). Step 16: Replace the medium everyday and repeat step 14                     187 Appendix B: Raw Experimental Data Chapter 2: Table B.2.1: Total Dissolved Selenium Concentration Data  Sample Analyte Time Point, hours Concentration, mg/L Negative Control Tot. Dissolved Se  0 0.32 Denitrifying Sludge Tot. Dissolved Se  0 0.334 Bodie Creek Tot. Dissolved Se  0 0.295 Bodie Creek Downstream  Tot. Dissolved Se  0 0.31 Lagoon A  Tot. Dissolved Se  0 0.269 Goddard Marsh # 1 Tot. Dissolved Se  0 0.302 Goddard Marsh # 2 Tot. Dissolved Se  0 0.298 Lanscar Seep #1 Tot. Dissolved Se  0 0.32 Lanscar Seep #2 Tot. Dissolved Se  0 0.31 STP South Seep  Tot. Dissolved Se  0 0.335 A4 Spring #1  Tot. Dissolved Se  0 0.3152 A4 Spring #2 Tot. Dissolved Se  0 0.315 West Jarvis Pond  Tot. Dissolved Se  0 0.287 Smithe Pond  Tot. Dissolved Se  0 0.285 Eagle Pond  Tot. Dissolved Se  0 0.298 Clode Pond  Tot. Dissolved Se  0 0.288 Lake Mountain  Tot. Dissolved Se  0 0.282 Negative Control Tot. Dissolved Se  72 0.32 Denitrifying Sludge Tot. Dissolved Se  72 0.0178 Bodie Creek Tot. Dissolved Se  72 0 Bodie Creek Downstream  Tot. Dissolved Se  72 0.062 Lagoon A  Tot. Dissolved Se  72 0 Goddard Marsh # 1 Tot. Dissolved Se  72 0.0208 Goddard Marsh # 2 Tot. Dissolved Se  72 0.019 Lanscar Seep #1 Tot. Dissolved Se  72 0.0254 Lanscar Seep #2 Tot. Dissolved Se  72 0.0186 STP South Seep  Tot. Dissolved Se  72 0.1982 A4 Spring #1  Tot. Dissolved Se  72 0.0412 A4 Spring #2 Tot. Dissolved Se  72 0.0396 West Jarvis Pond  Tot. Dissolved Se  72 0.015 Smithe Pond  Tot. Dissolved Se  72 0 Eagle Pond  Tot. Dissolved Se  72 0.041   188 Sample Analyte Time Point, hours Concentration, mg/L Clode Pond  Tot. Dissolved Se  72 0.0256 Lake Mountain  Tot. Dissolved Se  72 0.216   Chapter 3: Table B.3.1: Total Dissolved Selenium Concentration Data S/N Sample Growth Medium Analyte Time, hours Conc. mg/L Stev Dev 1 Negative Control Se only Tot. Dissolved Se  0 1.137 0.0580 2 Goddard Marsh Se only Tot. Dissolved Se  0 0.918 0.0057 3 Lagoon A Se only Tot. Dissolved Se  0 1.018 0.0255 4 Smith Pond Se only Tot. Dissolved Se  0 1.104 0.0184 5 Bodie Se only Tot. Dissolved Se  0 1.041 0.0198 6 West Jarvis Pond Se only Tot. Dissolved Se  0 1.032 0.0198 7 Eagle Pond Se only Tot. Dissolved Se  0 1.075 0.0283 8 Negative Control Se only Tot. Dissolved Se  4 1.103 0.0269 9 Goddard Marsh Se only Tot. Dissolved Se  4 0.836 0.0113 10 Lagoon A Se only Tot. Dissolved Se  4 1.014 0.0184 11 Smith Pond Se only Tot. Dissolved Se  4 1.070 0.0170 12 Bodie Se only Tot. Dissolved Se  4 0.978 0.0806 13 West Jarvis Pond Se only Tot. Dissolved Se  4 0.983 0.0198 14 Eagle Pond Se only Tot. Dissolved Se  4 1.022 0.0127 15 Negative Control Se only Tot. Dissolved Se  8 1.094 0.0028 16 Goddard Marsh Se only Tot. Dissolved Se  8 0.706 0.0877 17 Lagoon A Se only Tot. Dissolved Se  8 0.997 0.0424 18 Smith Pond Se only Tot. Dissolved Se  8 1.064 0.0283 19 Bodie Se only Tot. Dissolved Se  8 0.946 0.0085 20 West Jarvis Pond Se only Tot. Dissolved Se  8 0.982 0.0240 21 Eagle Pond Se only Tot. Dissolved Se  8 1.010 0.0537 22 Negative Control Se only Tot. Dissolved Se  12 1.026 0.0311 23 Goddard Marsh Se only Tot. Dissolved Se  12 0.563 0.0750 24 Lagoon A Se only Tot. Dissolved Se  12 0.962 0.0453 25 Smith Pond Se only Tot. Dissolved Se  12 1.011 0.1188 26 Bodie Se only Tot. Dissolved Se  12 0.819 0.0020 27 West Jarvis Pond Se only Tot. Dissolved Se  12 0.962 0.0594   189 S/N Sample Growth Medium Analyte Time, hours Conc. mg/L Stev Dev 28 Eagle Pond Se only Tot. Dissolved Se  12 1.001 0.0269 29 Negative Control Se only Tot. Dissolved Se  24 1.021 0.0184 30 Goddard Marsh Se only Tot. Dissolved Se  24 0.341 0.0693 31 Lagoon A Se only Tot. Dissolved Se  24 0.958 0.0198 32 Smith Pond Se only Tot. Dissolved Se  24 0.904 0.0170 33 Bodie Se only Tot. Dissolved Se  24 0.454 0.0600 34 West Jarvis Pond Se only Tot. Dissolved Se  24 0.737 0.0438 35 Eagle Pond Se only Tot. Dissolved Se  24 0.823 0.0721 36 Negative Control Se only Tot. Dissolved Se  48 1.040 0.0000 37 Goddard Marsh Se only Tot. Dissolved Se  48 0.087 0.0424 38 Lagoon A Se only Tot. Dissolved Se  48 0.842 0.0339 39 Smith Pond Se only Tot. Dissolved Se  48 0.425 0.0524 40 Bodie Se only Tot. Dissolved Se  48 0.031 0.0010 41 West Jarvis Pond Se only Tot. Dissolved Se  48 0.280 0.0000 42 Eagle Pond Se only Tot. Dissolved Se  48 0.503 0.0184 43 Negative Control Se only Tot. Dissolved Se  72 1.008 0.0339 44 Goddard Marsh Se only Tot. Dissolved Se  72 0.068 0.0064 45 Lagoon A Se only Tot. Dissolved Se  72 0.740 0.0057 46 Smith Pond Se only Tot. Dissolved Se  72 0.022 0.0006 47 Bodie Se only Tot. Dissolved Se  72 0.009 0.0010 48 West Jarvis Pond Se only Tot. Dissolved Se  72 0.041 0.0011 49 Eagle Pond Se only Tot. Dissolved Se  72 0.485 0.0127 50 Negative Control Se + NO3-  Tot. Dissolved Se  0 1.137 0.1057 51 Goddard Marsh Se + NO3-  Tot. Dissolved Se  0 0.976 0.0157 52 Lagoon A Se + NO3-  Tot. Dissolved Se  0 1.014 0.0220 53 Smith Pond Se + NO3-  Tot. Dissolved Se  0 1.052 0.0063 54 Bodie Se + NO3-  Tot. Dissolved Se  0 1.089 0.0094 55 West Jarvis Pond Se + NO3-  Tot. Dissolved Se  0 1.008 0.0097 56 Eagle Pond Se + NO3-  Tot. Dissolved Se  0 1.141 0.0053 57 Negative Control Se + NO3-  Tot. Dissolved Se  4 1.054 0.0932 58 Goddard Marsh Se + NO3-  Tot. Dissolved Se  4 0.782 0.0424 59 Lagoon A Se + NO3-  Tot. Dissolved Se  4 1.011 0.0230 60 Smith Pond Se + NO3-  Tot. Dissolved Se  4 0.989 0.0194 61 Bodie Se + NO3- Tot. Dissolved Se  4 1.078 0.1033   190 S/N Sample Growth Medium Analyte Time, hours Conc. mg/L Stev Dev 62 West Jarvis Pond Se + NO3-  Tot. Dissolved Se  4 0.981 0.0375 63 Eagle Pond Se + NO3-  Tot. Dissolved Se  4 1.079 0.0279 64 Negative Control Se + NO3-  Tot. Dissolved Se  8 1.047 0.0438 65 Goddard Marsh Se + NO3-  Tot. Dissolved Se  8 0.575 0.1061 66 Lagoon A Se + NO3-  Tot. Dissolved Se  8 0.965 0.0000 67 Smith Pond Se + NO3-  Tot. Dissolved Se  8 0.988 0.0141 68 Bodie Se + NO3-  Tot. Dissolved Se  8 0.945 0.0189 69 West Jarvis Pond Se + NO3-  Tot. Dissolved Se  8 0.966 0.0654 70 Eagle Pond Se + NO3-  Tot. Dissolved Se  8 1.051 0.0459 71 Negative Control Se + NO3-  Tot. Dissolved Se  12 1.020 0.0393 72 Goddard Marsh Se + NO3-  Tot. Dissolved Se  12 0.467 0.0184 73 Lagoon A Se + NO3-  Tot. Dissolved Se  12 0.933 0.0177 74 Smith Pond Se + NO3-  Tot. Dissolved Se  12 0.984 0.0801 75 Bodie Se + NO3-  Tot. Dissolved Se  12 0.900 0.0721 76 West Jarvis Pond Se + NO3-  Tot. Dissolved Se  12 0.935 0.0263 77 Eagle Pond Se + NO3-  Tot. Dissolved Se  12 0.972 0.0157 78 Negative Control Se + NO3-  Tot. Dissolved Se  24 1.008 0.0198 79 Goddard Marsh Se + NO3-  Tot. Dissolved Se  24 0.298 0.0735 80 Lagoon A Se + NO3-  Tot. Dissolved Se  24 0.907 0.0410 81 Smith Pond Se + NO3-  Tot. Dissolved Se  24 0.788 0.0283 82 Bodie Se + NO3-  Tot. Dissolved Se  24 0.753 0.0184 83 West Jarvis Pond Se + NO3-  Tot. Dissolved Se  24 0.863 0.0468 84 Eagle Pond Se + NO3-  Tot. Dissolved Se  24 0.962 0.0226 85 Negative Control Se + NO3-  Tot. Dissolved Se  48 0.980 0.0177 86 Goddard Marsh Se + NO3-  Tot. Dissolved Se  48 0.138 0.0147 87 Lagoon A Se + NO3-  Tot. Dissolved Se  48 0.378 0.0509 88 Smith Pond Se + NO3-  Tot. Dissolved Se  48 0.779 0.0770 89 Bodie Se + NO3-  Tot. Dissolved Se  48 0.424 0.0742 90 West Jarvis Pond Se + NO3-  Tot. Dissolved Se  48 0.712 0.0453 91 Eagle Pond Se + NO3-  Tot. Dissolved Se  48 0.823 0.0028 92 Negative Control Se + NO3-  Tot. Dissolved Se  72 0.968 0.0047 93 Goddard Marsh Se + NO3-  Tot. Dissolved Se  72 0.084 0.0020 94 Lagoon A Se + NO3-  Tot. Dissolved Se  72 0.173 0.0016 95 Smith Pond Se + NO3-  Tot. Dissolved Se  72 0.766 0.0127   191 S/N Sample Growth Medium Analyte Time, hours Conc. mg/L Stev Dev 96 Bodie Se + NO3-  Tot. Dissolved Se  72 0.290 0.0099 97 West Jarvis Pond Se + NO3-  Tot. Dissolved Se  72 0.682 0.0062 98 Eagle Pond Se + NO3-  Tot. Dissolved Se  72 0.515 0.0088  Chapter 3: Table B.3.2 : Total Nitrate plus Nitrite Concentration Data Sample Growth Medium Passage Analyte Time Point, hrs Conc. (mg-N/L) Stev Dev Negative Control Se + NO3- 3 Total Nitrate-plus-Nitrite 0 43.073 3.854 Goddard Marsh Se + NO3- 3 Total Nitrate-plus-Nitrite 0 45.685 3.231 Lagoon A Se + NO3- 3 Total Nitrate-plus-Nitrite 0 42.676 0.709 Smith Pond Se + NO3- 3 Total Nitrate-plus-Nitrite 0 39.763 1.417 Bodie Se + NO3- 3 Total Nitrate-plus-Nitrite 0 39.196 3.447 West Jarvis Pond Se + NO3- 3 Total Nitrate-plus-Nitrite 0 44.552 0.536 Eagle Pond Se + NO3- 3 Total Nitrate-plus-Nitrite 0 46.493 0.419 Negative Control Se + NO3- 3 Total Nitrate-plus-Nitrite 4 40.395 4.571 Goddard Marsh Se + NO3- 3 Total Nitrate-plus-Nitrite 4 42.998 1.059 Lagoon A Se + NO3- 3 Total Nitrate-plus-Nitrite 4 42.791 3.961 Smith Pond Se + NO3- 3 Total Nitrate-plus-Nitrite 4 29.145 0.283 Bodie Se + NO3- 3 Total Nitrate-plus-Nitrite 4 32.317 1.181 West Jarvis Pond Se + NO3- 3 Total Nitrate-plus-Nitrite 4 23.927 0.538 Eagle Pond Se + NO3- 3 Total Nitrate-plus-Nitrite 4 41.324 0.023 Negative Control Se + NO3- 3 Total Nitrate-plus-Nitrite 8 41.624 4.590 Goddard Marsh Se + NO3- 3 Total Nitrate-plus- 8 27.634 1.431   192 Sample Growth Medium Passage Analyte Time Point, hrs Conc. (mg-N/L) Stev Dev Nitrite Lagoon A Se + NO3- 3 Total Nitrate-plus-Nitrite 8 19.063 2.443 Smith Pond Se + NO3- 3 Total Nitrate-plus-Nitrite 8 1.533 0.024 Bodie Se + NO3- 3 Total Nitrate-plus-Nitrite 8 3.236 0.118 West Jarvis Pond Se + NO3- 3 Total Nitrate-plus-Nitrite 8 16.594 0.803 Eagle Pond Se + NO3- 3 Total Nitrate-plus-Nitrite 8 25.625 7.479 Negative Control Se + NO3- 3 Total Nitrate-plus-Nitrite 12 41.288 2.450 Goddard Marsh Se + NO3- 3 Total Nitrate-plus-Nitrite 12 14.284 1.805 Lagoon A Se + NO3- 3 Total Nitrate-plus-Nitrite 12 5.060 0.427 Smith Pond Se + NO3- 3 Total Nitrate-plus-Nitrite 12 0.543 0.315 Bodie Se + NO3- 3 Total Nitrate-plus-Nitrite 12 0.000 0.000 West Jarvis Pond Se + NO3- 3 Total Nitrate-plus-Nitrite 12 9.901 1.381 Eagle Pond Se + NO3- 3 Total Nitrate-plus-Nitrite 12 8.673 0.757 Negative Control Se + NO3- 3 Total Nitrate-plus-Nitrite 24 41.365 2.967 Goddard Marsh Se + NO3- 3 Total Nitrate-plus-Nitrite 24 3.039 0.330 Lagoon A Se + NO3- 3 Total Nitrate-plus-Nitrite 24 2.340 0.693 Smith Pond Se + NO3- 3 Total Nitrate-plus-Nitrite 24 0.341 0.142 Bodie Se + NO3- 3 Total Nitrate-plus-Nitrite 24 0.000 0.000 West Jarvis Pond Se + NO3- 3 Total Nitrate-plus-Nitrite 24 4.952 0.204 Eagle Pond Se + NO3- 3 Total Nitrate-plus-Nitrite 24 4.656 0.501    193 Chapter 4: Table B.4.1: Total Dissolved Selenium Concentration Data Sample Medium Analyte Passage Time Point, hrs Conc. mg/L Stev Dev Negative Control MIW Tot. Dissolved Se 3 0 0.360 0.009 Denitrifying Sludge MIW Tot. Dissolved Se 3 0 0.359 0.005 Goddard Marsh MIW Tot. Dissolved Se 3 0 0.369 0.008 Lagoon A MIW Tot. Dissolved Se 3 0 0.349 0.008 Negative Control MIW Tot. Dissolved Se 3 72 0.359 0.014 Denitrifying Sludge MIW Tot. Dissolved Se 3 72 0.333 0.005 Goddard Marsh MIW Tot. Dissolved Se 3 72 0.357 0.002 Lagoon A MIW Tot. Dissolved Se 3 72 0.313 0.011 Negative Control MIW Tot. Dissolved Se 4 0 0.331 0.009 Denitrifying Sludge MIW Tot. Dissolved Se 4 0 0.330 0.011 Goddard Marsh MIW Tot. Dissolved Se 4 0 0.341 0.008 Lagoon A MIW Tot. Dissolved Se 4 0 0.321 0.014 Negative Control MIW Tot. Dissolved Se 4 72 0.329 0.008 Denitrifying Sludge MIW Tot. Dissolved Se 4 72 0.297 0.005 Goddard Marsh MIW Tot. Dissolved Se 4 72 0.313 0.025 Lagoon A MIW Tot. Dissolved Se 4 72 0.259 0.017 Negative Control MIW Tot. Dissolved Se 5 0 0.344 0.004 Denitrifying Sludge MIW Tot. Dissolved Se 5 0 0.328 0.006 Goddard Marsh MIW Tot. Dissolved Se 5 0 0.332 0.012 Lagoon A MIW Tot. Dissolved Se 5 0 0.325 0.006 Negative Control MIW Tot. Dissolved Se 5 72 0.335 0.004 Denitrifying Sludge MIW Tot. Dissolved Se 5 72 0.297 0.028 Goddard Marsh MIW Tot. Dissolved Se 5 72 0.307 0.020 Lagoon A MIW Tot. Dissolved Se 5 72 0.194 0.050    194 Chapter 4 : Table B.4.2 : Total Nitrate plus Nitrite Concentration Data  Sample  Medium Analyte Passage Time Point, hrs Conc. mg-N/L Stev Dev Negative Control MIW Nitrate-plus-Nitrite 1 0 46.243 1.368 Denitrifying Sludge MIW Nitrate-plus-Nitrite 1 0 47.499 1.683 Goddard Marsh MIW Nitrate-plus-Nitrite 1 0 45.708 1.908 Lagoon A MIW Nitrate-plus-Nitrite 1 0 47.860 1.381 Negative Control MIW Nitrate-plus-Nitrite 1 24 45.981 2.095 Denitrifying Sludge MIW Nitrate-plus-Nitrite 1 24 5.861 2.240 Goddard Marsh MIW Nitrate-plus-Nitrite 1 24 23.765 1.959 Lagoon A MIW Nitrate-plus-Nitrite 1 24 10.799 2.825 Negative Control MIW Nitrate-plus-Nitrite 1 48 45.172 3.474 Denitrifying Sludge MIW Nitrate-plus-Nitrite 1 48 4.152 0.552 Goddard Marsh MIW Nitrate-plus-Nitrite 1 48 6.435 1.123 Lagoon A MIW Nitrate-plus-Nitrite 1 48 5.831 0.552 Negative Control MIW Nitrate-plus-Nitrite 2 0 48.952 1.945 Denitrifying Sludge MIW Nitrate-plus-Nitrite 2 0 49.127 2.142 Goddard Marsh MIW Nitrate-plus-Nitrite 2 0 49.509 2.931 Lagoon A MIW Nitrate-plus-Nitrite 2 0 48.744 2.441 Negative Control MIW Nitrate-plus-Nitrite 2 24 49.859 1.163 Denitrifying Sludge MIW Nitrate-plus-Nitrite 2 24 21.823 1.978 Goddard Marsh MIW Nitrate-plus-Nitrite 2 24 20.979 0.875   195 Sample  Medium Analyte Passage Time Point, hrs Conc. mg-N/L Stev Dev Lagoon A MIW Nitrate-plus-Nitrite 2 24 9.286 0.808 Negative Control MIW Nitrate-plus-Nitrite 2 48 49.640 2.373 Denitrifying Sludge MIW Nitrate-plus-Nitrite 2 48 6.036 0.704 Goddard Marsh MIW Nitrate-plus-Nitrite 2 48 17.031 0.652 Lagoon A MIW Nitrate-plus-Nitrite 2 48 7.060 0.545 Negative Control MIW Nitrate-plus-Nitrite 3 0 46.855 0.995 Denitrifying Sludge MIW Nitrate-plus-Nitrite 3 0 48.886 2.449 Goddard Marsh MIW Nitrate-plus-Nitrite 3 0 49.738 3.633 Lagoon A MIW Nitrate-plus-Nitrite 3 0 47.445 1.245 Negative Control MIW Nitrate-plus-Nitrite 3 24 49.800 3.463 Denitrifying Sludge MIW Nitrate-plus-Nitrite 3 24 37.087 5.964 Goddard Marsh MIW Nitrate-plus-Nitrite 3 24 42.782 4.790 Lagoon A MIW Nitrate-plus-Nitrite 3 24 15.313 1.171 Negative Control MIW Nitrate-plus-Nitrite 3 48 51.300 1.282 Denitrifying Sludge MIW Nitrate-plus-Nitrite 3 48 7.752 0.332 Goddard Marsh MIW Nitrate-plus-Nitrite 3 48 8.140 0.905 Lagoon A MIW Nitrate-plus-Nitrite 3 48 4.504 0.458 Negative Control MIW Nitrate-plus-Nitrite 4 0 47.204 0.433 Denitrifying Sludge MIW Nitrate-plus-Nitrite 4 0 48.013 0.855 Goddard Marsh MIW Nitrate-plus-Nitrite 4 0 45.751 0.478   196 Sample  Medium Analyte Passage Time Point, hrs Conc. mg-N/L Stev Dev Lagoon A MIW Nitrate-plus-Nitrite 4 0 49.531 2.399 Negative Control MIW Nitrate-plus-Nitrite 4 24 42.769 0.605 Denitrifying Sludge MIW Nitrate-plus-Nitrite 4 24 24.793 2.110 Goddard Marsh MIW Nitrate-plus-Nitrite 4 24 19.096 1.577 Lagoon A MIW Nitrate-plus-Nitrite 4 24 6.121 1.485 Negative Control MIW Nitrate-plus-Nitrite 4 48 41.477 1.443 Denitrifying Sludge MIW Nitrate-plus-Nitrite 4 48 7.181 0.695 Goddard Marsh MIW Nitrate-plus-Nitrite 4 48 14.700 1.230 Lagoon A MIW Nitrate-plus-Nitrite 4 48 6.209 1.343 Negative Control MIW Nitrate-plus-Nitrite 5 0 49.375 2.156 Denitrifying Sludge MIW Nitrate-plus-Nitrite 5 0 51.087 1.530 Goddard Marsh MIW Nitrate-plus-Nitrite 5 0 50.821 3.595 Lagoon A MIW Nitrate-plus-Nitrite 5 0 48.956 2.122 Negative Control MIW Nitrate-plus-Nitrite 5 24 51.049 2.996 Denitrifying Sludge MIW Nitrate-plus-Nitrite 5 24 29.895 1.829 Goddard Marsh MIW Nitrate-plus-Nitrite 5 24 22.753 1.435 Lagoon A MIW Nitrate-plus-Nitrite 5 24 28.309 1.379 Negative Control MIW Nitrate-plus-Nitrite 5 48 48.588 3.326 Denitrifying Sludge MIW Nitrate-plus-Nitrite 5 48 9.997 0.857 Goddard Marsh MIW Nitrate-plus-Nitrite 5 48 7.120 0.755   197 Sample  Medium Analyte Passage Time Point, hrs Conc. mg-N/L Stev Dev Lagoon A MIW Nitrate-plus-Nitrite 5 48 10.590 0.717   Chapter 4: Table B.4.3: Soluble COD Concentration Data  Sample Medium Analyte Passage Time Point, hrs Conc. mg/L Stev Dev Negative Control MIW SCOD 1 0 1689.973 61.730 Denitrifying Sludge MIW SCOD 1 0 1600.855 64.896 Goddard Marsh MIW SCOD 1 0 1546.293 27.099 Lagoon A MIW SCOD 1 0 1586.305 90.096 Negative Control MIW SCOD 1 24 1600.855 140.667 Denitrifying Sludge MIW SCOD 1 24 1275.302 55.643 Goddard Marsh MIW SCOD 1 24 1355.326 30.607 Lagoon A MIW SCOD 1 24 1389.882 67.856 Negative Control MIW SCOD 1 48 1544.474 22.541 Denitrifying Sludge MIW SCOD 1 48 1195.278 47.649 Goddard Marsh MIW SCOD 1 48 1337.139 39.647 Lagoon A MIW SCOD 1 48 1373.513 55.392 Negative Control MIW SCOD 1 72 1388.163 117.404 Denitrifying Sludge MIW SCOD 1 72 854.535 72.366 Goddard Marsh MIW SCOD 1 72 843.456 90.458 Lagoon A MIW SCOD 1 72 976.401 64.853 Negative Control MIW SCOD 2 0 1497.844 65.730 Denitrifying Sludge MIW SCOD 2 0 1369.699 194.358 Goddard Marsh MIW SCOD 2 0 1281.068 103.613 Lagoon A MIW SCOD 2 0 1290.301 117.177 Negative Control MIW SCOD 2 24 1432.479 171.835 Denitrifying Sludge MIW SCOD 2 24 1133.351 204.373 Goddard Marsh MIW SCOD 2 24 1266.297 168.517 Lagoon A MIW SCOD 2 24 1164.741 142.166 Negative Control MIW SCOD 2 48 1349.388 81.538 Denitrifying Sludge MIW SCOD 2 48 972.708 67.813   198 Sample Medium Analyte Passage Time Point, hrs Conc. mg/L Stev Dev Goddard Marsh MIW SCOD 2 48 1186.899 119.682 Lagoon A MIW SCOD 2 48 1055.799 83.202 Negative Control MIW SCOD 2 72 1288.454 231.297 Denitrifying Sludge MIW SCOD 2 72 933.933 57.957 Goddard Marsh MIW SCOD 2 72 1111.193 80.197 Lagoon A MIW SCOD 2 72 911.775 78.782 Negative Control MIW SCOD 3 0 1433.586 95.625 Denitrifying Sludge MIW SCOD 3 0 1051.491 41.984 Goddard Marsh MIW SCOD 3 0 1089.651 143.289 Lagoon A MIW SCOD 3 0 1026.871 43.067 Negative Control MIW SCOD 3 24 1370.271 151.365 Denitrifying Sludge MIW SCOD 3 24 996.712 135.762 Goddard Marsh MIW SCOD 3 24 1085.343 149.201 Lagoon A MIW SCOD 3 24 974.555 105.433 Negative Control MIW SCOD 3 48 1257.064 154.628 Denitrifying Sludge MIW SCOD 3 48 780.005 97.342 Goddard Marsh MIW SCOD 3 48 810.166 87.422 Lagoon A MIW SCOD 3 48 865.613 67.813 Negative Control MIW SCOD 3 72 1109.347 136.911 Denitrifying Sludge MIW SCOD 3 72 748.917 16.619 Goddard Marsh MIW SCOD 3 72 780.676 79.901 Lagoon A MIW SCOD 3 72 856.870 75.171 Negative Control MIW SCOD 4 0 1279.326 62.283 Denitrifying Sludge MIW SCOD 4 0 826.909 45.638 Goddard Marsh MIW SCOD 4 0 873.074 42.044 Lagoon A MIW SCOD 4 0 845.375 40.508 Negative Control MIW SCOD 4 24 1270.093 37.736 Denitrifying Sludge MIW SCOD 4 24 806.597 35.558 Goddard Marsh MIW SCOD 4 24 773.358 52.360 Lagoon A MIW SCOD 4 24 819.523 39.897 Negative Control MIW SCOD 4 48 972.791 68.449 Denitrifying Sludge MIW SCOD 4 48 702.449 55.949 Goddard Marsh MIW SCOD 4 48 719.807 60.685 Lagoon A MIW SCOD 4 48 738.273 93.161   199 Sample Medium Analyte Passage Time Point, hrs Conc. mg/L Stev Dev Negative Control MIW SCOD 4 72 928.472 85.152 Denitrifying Sludge MIW SCOD 4 72 658.130 113.424 Goddard Marsh MIW SCOD 4 72 609.934 118.384 Lagoon A MIW SCOD 4 72 594.238 44.549 Negative Control MIW SCOD 5 0 1715.225 88.250 Denitrifying Sludge MIW SCOD 5 0 1580.486 302.098 Goddard Marsh MIW SCOD 5 0 1407.252 57.186 Lagoon A MIW SCOD 5 0 1467.746 59.455 Negative Control MIW SCOD 5 24 1563.639 16.629 Denitrifying Sludge MIW SCOD 5 24 1210.399 50.625 Goddard Marsh MIW SCOD 5 24 999.404 44.225 Lagoon A MIW SCOD 5 24 1325.143 50.891 Negative Control MIW SCOD 5 48 1535.190 66.414 Denitrifying Sludge MIW SCOD 5 48 1101.346 83.266 Goddard Marsh MIW SCOD 5 48 956.731 88.336 Lagoon A MIW SCOD 5 48 1272.039 39.896 Negative Control MIW SCOD 5 72 1453.163 92.367 Denitrifying Sludge MIW SCOD 5 72 1049.190 79.453 Goddard Marsh MIW SCOD 5 72 937.765 43.843 Lagoon A MIW SCOD 5 72 1115.570 42.831      200 Chapter 5: Table B.5.1: Total Dissolved Selenium Concentration Data Sample Medium Analyte Passage Time Point, hrs Conc. mg/L Stev Dev Negative Control MIW Tot. Dissolved Se 1 0 2.371 0.024 Denitrifying Sludge MIW Tot. Dissolved Se 1 0 2.425 0.035 Goddard Marsh MIW Tot. Dissolved Se 1 0 2.350 0.094 Lagoon A MIW Tot. Dissolved Se 1 0 2.383 0.024 Bodie MIW Tot. Dissolved Se 1 0 2.400 0.047 Eagle Pond MIW Tot. Dissolved Se 1 0 2.392 0.082 Negative Control MIW Tot. Dissolved Se 1 4 2.367 0.071 Denitrifying Sludge MIW Tot. Dissolved Se 1 4 2.331 0.003 Goddard Marsh MIW Tot. Dissolved Se 1 4 2.283 0.071 Lagoon A MIW Tot. Dissolved Se 1 4 2.325 0.106 Bodie MIW Tot. Dissolved Se 1 4 2.365 0.092 Eagle Pond MIW Tot. Dissolved Se 1 4 2.379 0.030 Negative Control MIW Tot. Dissolved Se 1 8 2.350 0.059 Denitrifying Sludge MIW Tot. Dissolved Se 1 8 2.279 0.053 Goddard Marsh MIW Tot. Dissolved Se 1 8 2.243 0.073 Lagoon A MIW Tot. Dissolved Se 1 8 2.277 0.000 Bodie MIW Tot. Dissolved Se 1 8 2.333 0.094 Eagle Pond MIW Tot. Dissolved Se 1 8 2.321 0.071 Negative Control MIW Tot. Dissolved Se 1 12 2.350 0.030 Denitrifying Sludge MIW Tot. Dissolved Se 1 12 2.177 0.033 Goddard Marsh MIW Tot. Dissolved Se 1 12 2.191 0.021 Lagoon A MIW Tot. Dissolved Se 1 12 2.185 0.044 Bodie MIW Tot. Dissolved Se 1 12 2.208 0.033 Eagle Pond MIW Tot. Dissolved Se 1 12 2.215 0.087 Negative Control MIW Tot. Dissolved Se 2 0 2.250 0.030 Denitrifying Sludge MIW Tot. Dissolved Se 2 0 2.196 0.006 Goddard Marsh MIW Tot. Dissolved Se 2 0 2.221 0.030 Lagoon A MIW Tot. Dissolved Se 2 0 2.279 0.010 Bodie MIW Tot. Dissolved Se 2 0 2.250 0.000 Eagle Pond MIW Tot. Dissolved Se 2 0 2.279 0.021   201 Sample Medium Analyte Passage Time Point, hrs Conc. mg/L Stev Dev Negative Control MIW Tot. Dissolved Se 2 4 2.250 0.030 Denitrifying Sludge MIW Tot. Dissolved Se 2 4 2.271 0.061 Goddard Marsh MIW Tot. Dissolved Se 2 4 2.186 0.040 Lagoon A MIW Tot. Dissolved Se 2 4 2.348 0.028 Bodie MIW Tot. Dissolved Se 2 4 2.157 0.020 Eagle Pond MIW Tot. Dissolved Se 2 4 2.264 0.071 Negative Control MIW Tot. Dissolved Se 2 8 2.264 0.030 Denitrifying Sludge MIW Tot. Dissolved Se 2 8 1.943 0.081 Goddard Marsh MIW Tot. Dissolved Se 2 8 1.721 0.192 Lagoon A MIW Tot. Dissolved Se 2 8 2.221 0.071 Bodie MIW Tot. Dissolved Se 2 8 1.359 0.320 Eagle Pond MIW Tot. Dissolved Se 2 8 1.807 0.071 Negative Control MIW Tot. Dissolved Se 2 12 2.143 0.081 Denitrifying Sludge MIW Tot. Dissolved Se 2 12 1.679 0.131 Goddard Marsh MIW Tot. Dissolved Se 2 12 1.500 0.343 Lagoon A MIW Tot. Dissolved Se 2 12 2.243 0.061 Bodie MIW Tot. Dissolved Se 2 12 0.926 0.428 Eagle Pond MIW Tot. Dissolved Se 2 12 1.464 0.051 Negative Control MIW Tot. Dissolved Se 3 0 2.371 0.010 Denitrifying Sludge MIW Tot. Dissolved Se 3 0 2.443 0.000 Goddard Marsh MIW Tot. Dissolved Se 3 0 2.400 0.020 Lagoon A MIW Tot. Dissolved Se 3 0 2.336 0.071 Bodie MIW Tot. Dissolved Se 3 0 2.329 0.061 Eagle Pond MIW Tot. Dissolved Se 3 0 2.329 0.081 Negative Control MIW Tot. Dissolved Se 3 4 2.350 0.030 Denitrifying Sludge MIW Tot. Dissolved Se 3 4 2.229 0.020 Goddard Marsh MIW Tot. Dissolved Se 3 4 2.293 0.051 Lagoon A MIW Tot. Dissolved Se 3 4 2.279 0.010 Bodie MIW Tot. Dissolved Se 3 4 2.093 0.131 Eagle Pond MIW Tot. Dissolved Se 3 4 2.279 0.010 Negative Control MIW Tot. Dissolved Se 3 8 2.350 0.010   202 Sample Medium Analyte Passage Time Point, hrs Conc. mg/L Stev Dev Denitrifying Sludge MIW Tot. Dissolved Se 3 8 1.986 0.000 Goddard Marsh MIW Tot. Dissolved Se 3 8 2.229 0.020 Lagoon A MIW Tot. Dissolved Se 3 8 2.279 0.030 Bodie MIW Tot. Dissolved Se 3 8 1.943 0.141 Eagle Pond MIW Tot. Dissolved Se 3 8 2.243 0.081 Negative Control MIW Tot. Dissolved Se 3 12 2.314 0.010 Denitrifying Sludge MIW Tot. Dissolved Se 3 12 2.050 0.051 Goddard Marsh MIW Tot. Dissolved Se 3 12 2.171 0.040 Lagoon A MIW Tot. Dissolved Se 3 12 2.271 0.061 Bodie MIW Tot. Dissolved Se 3 12 1.764 0.192 Eagle Pond MIW Tot. Dissolved Se 3 12 2.171 0.020 Negative Control MIW Tot. Dissolved Se 4 0 2.321 0.051 Denitrifying Sludge MIW Tot. Dissolved Se 4 0 2.271 0.020 Goddard Marsh MIW Tot. Dissolved Se 4 0 2.343 0.020 Lagoon A MIW Tot. Dissolved Se 4 0 2.229 0.020 Bodie MIW Tot. Dissolved Se 4 0 2.264 0.010 Eagle Pond MIW Tot. Dissolved Se 4 0 2.257 0.020 Negative Control MIW Tot. Dissolved Se 4 4 2.150 0.051 Denitrifying Sludge MIW Tot. Dissolved Se 4 4 2.079 0.010 Goddard Marsh MIW Tot. Dissolved Se 4 4 2.186 0.000 Lagoon A MIW Tot. Dissolved Se 4 4 2.200 0.040 Bodie MIW Tot. Dissolved Se 4 4 2.086 0.020 Eagle Pond MIW Tot. Dissolved Se 4 4 2.171 0.020 Negative Control MIW Tot. Dissolved Se 4 8 2.093 0.051 Denitrifying Sludge MIW Tot. Dissolved Se 4 8 1.914 0.040 Goddard Marsh MIW Tot. Dissolved Se 4 8 2.164 0.010 Lagoon A MIW Tot. Dissolved Se 4 8 2.193 0.030 Bodie MIW Tot. Dissolved Se 4 8 2.050 0.010 Eagle Pond MIW Tot. Dissolved Se 4 8 2.129 0.020 Negative Control MIW Tot. Dissolved Se 4 12 2.107 0.091   203 Sample Medium Analyte Passage Time Point, hrs Conc. mg/L Stev Dev Denitrifying Sludge MIW Tot. Dissolved Se 4 12 1.893 0.010 Goddard Marsh MIW Tot. Dissolved Se 4 12 1.986 0.000 Lagoon A MIW Tot. Dissolved Se 4 12 2.179 0.010 Bodie MIW Tot. Dissolved Se 4 12 1.900 0.000 Eagle Pond MIW Tot. Dissolved Se 4 12 1.993 0.030  Chapter 5: Table B.5.2: Total Nitrate plus Nitrite Concentration Data Sample Medium Analyte Passage Time Point, hrs Conc. mg-N/L Stev Dev Negative Control MIW Nitrate-plus-Nitrite 1 0 57.568 1.898 Denitrifying Sludge MIW Nitrate-plus-Nitrite 1 0 57.568 4.103 Goddard Marsh MIW Nitrate-plus-Nitrite 1 0 51.817 4.177 Lagoon A MIW Nitrate-plus-Nitrite 1 0 57.355 4.112 Bodie MIW Nitrate-plus-Nitrite 1 0 57.461 4.613 Eagle Pond MIW Nitrate-plus-Nitrite 1 0 58.058 5.781 Negative Control MIW Nitrate-plus-Nitrite 1 2 58.991 2.802 Denitrifying Sludge MIW Nitrate-plus-Nitrite 1 2 58.590 3.604 Goddard Marsh MIW Nitrate-plus-Nitrite 1 2 51.751 2.353 Lagoon A MIW Nitrate-plus-Nitrite 1 2 58.036 4.353 Bodie MIW Nitrate-plus-Nitrite 1 2 55.779 2.063 Eagle Pond MIW Nitrate-plus-Nitrite 1 2 57.130 1.511 Negative Control MIW Nitrate-plus-Nitrite 1 4 53.174 1.446 Denitrifying Sludge MIW Nitrate-plus-Nitrite 1 4 52.006 5.576 Goddard Marsh MIW Nitrate-plus-Nitrite 1 4 49.359 2.016 Lagoon A MIW Nitrate-plus-Nitrite 1 4 55.042 0.542 Bodie MIW Nitrate-plus-Nitrite 1 4 35.451 3.464 Eagle Pond MIW Nitrate-plus-Nitrite 1 4 49.609 1.925 Negative Control MIW Nitrate-plus-Nitrite 1 6 55.092 0.542   204 Sample Medium Analyte Passage Time Point, hrs Conc. mg-N/L Stev Dev Denitrifying Sludge MIW Nitrate-plus-Nitrite 1 6 39.606 6.165 Goddard Marsh MIW Nitrate-plus-Nitrite 1 6 46.147 1.901 Lagoon A MIW Nitrate-plus-Nitrite 1 6 37.230 0.316 Bodie MIW Nitrate-plus-Nitrite 1 6 13.526 1.497 Eagle Pond MIW Nitrate-plus-Nitrite 1 6 34.140 2.053 Negative Control MIW Nitrate-plus-Nitrite 1 8 53.111 5.514 Denitrifying Sludge MIW Nitrate-plus-Nitrite 1 8 36.639 3.584 Goddard Marsh MIW Nitrate-plus-Nitrite 1 8 46.871 2.740 Lagoon A MIW Nitrate-plus-Nitrite 1 8 27.301 3.251 Bodie MIW Nitrate-plus-Nitrite 1 8 12.834 1.881 Eagle Pond MIW Nitrate-plus-Nitrite 1 8 24.265 2.401 Negative Control MIW Nitrate-plus-Nitrite 1 10 54.901 0.633 Denitrifying Sludge MIW Nitrate-plus-Nitrite 1 10 30.050 1.191 Goddard Marsh MIW Nitrate-plus-Nitrite 1 10 44.357 6.670 Lagoon A MIW Nitrate-plus-Nitrite 1 10 14.549 1.116 Bodie MIW Nitrate-plus-Nitrite 1 10 12.589 0.748 Eagle Pond MIW Nitrate-plus-Nitrite 1 10 14.229 0.317 Negative Control MIW Nitrate-plus-Nitrite 1 12 50.490 1.085 Denitrifying Sludge MIW Nitrate-plus-Nitrite 1 12 28.111 3.357 Goddard Marsh MIW Nitrate-plus-Nitrite 1 12 22.710 3.526 Lagoon A MIW Nitrate-plus-Nitrite 1 12 13.356 1.621 Bodie MIW Nitrate-plus-Nitrite 1 12 11.470 1.695 Eagle Pond MIW Nitrate-plus-Nitrite 1 12 13.079 1.702 Negative Control MIW Nitrate-plus-Nitrite 2 0 56.897 0.247 Denitrifying Sludge MIW Nitrate-plus-Nitrite 2 0 53.276 6.278 Goddard Marsh MIW Nitrate-plus-Nitrite 2 0 49.232 5.915 Lagoon A MIW Nitrate-plus-Nitrite 2 0 52.608 6.529   205 Sample Medium Analyte Passage Time Point, hrs Conc. mg-N/L Stev Dev Bodie MIW Nitrate-plus-Nitrite 2 0 56.703 5.232 Eagle Pond MIW Nitrate-plus-Nitrite 2 0 49.484 5.406 Negative Control MIW Nitrate-plus-Nitrite 2 2 58.488 4.331 Denitrifying Sludge MIW Nitrate-plus-Nitrite 2 2 23.830 1.944 Goddard Marsh MIW Nitrate-plus-Nitrite 2 2 35.686 2.369 Lagoon A MIW Nitrate-plus-Nitrite 2 2 35.783 3.369 Bodie MIW Nitrate-plus-Nitrite 2 2 53.743 2.727 Eagle Pond MIW Nitrate-plus-Nitrite 2 2 41.168 4.345 Negative Control MIW Nitrate-plus-Nitrite 2 4 58.662 3.404 Denitrifying Sludge MIW Nitrate-plus-Nitrite 2 4 22.501 1.630 Goddard Marsh MIW Nitrate-plus-Nitrite 2 4 8.966 0.452 Lagoon A MIW Nitrate-plus-Nitrite 2 4 10.334 0.479 Bodie MIW Nitrate-plus-Nitrite 2 4 9.131 0.247 Eagle Pond MIW Nitrate-plus-Nitrite 2 4 12.585 0.625 Negative Control MIW Nitrate-plus-Nitrite 2 6 57.479 2.246 Denitrifying Sludge MIW Nitrate-plus-Nitrite 2 6 10.353 1.070 Goddard Marsh MIW Nitrate-plus-Nitrite 2 6 8.878 1.078 Lagoon A MIW Nitrate-plus-Nitrite 2 6 9.082 1.151 Bodie MIW Nitrate-plus-Nitrite 2 6 9.005 1.083 Eagle Pond MIW Nitrate-plus-Nitrite 2 6 8.510 1.356 Negative Control MIW Nitrate-plus-Nitrite 3 0 52.757 4.469 Denitrifying Sludge MIW Nitrate-plus-Nitrite 3 0 53.455 4.638 Goddard Marsh MIW Nitrate-plus-Nitrite 3 0 45.845 4.873 Lagoon A MIW Nitrate-plus-Nitrite 3 0 50.225 4.524 Bodie MIW Nitrate-plus-Nitrite 3 0 53.219 5.710 Eagle Pond MIW Nitrate-plus-Nitrite 3 0 52.886 2.628 Negative Control MIW Nitrate-plus-Nitrite 3 2 49.088 4.121   206 Sample Medium Analyte Passage Time Point, hrs Conc. mg-N/L Stev Dev Denitrifying Sludge MIW Nitrate-plus-Nitrite 3 2 17.204 2.476 Goddard Marsh MIW Nitrate-plus-Nitrite 3 2 17.287 2.088 Lagoon A MIW Nitrate-plus-Nitrite 3 2 23.027 3.079 Bodie MIW Nitrate-plus-Nitrite 3 2 9.803 1.154 Eagle Pond MIW Nitrate-plus-Nitrite 3 2 12.933 1.262 Negative Control MIW Nitrate-plus-Nitrite 3 4 51.104 4.771 Denitrifying Sludge MIW Nitrate-plus-Nitrite 3 4 10.355 1.232 Goddard Marsh MIW Nitrate-plus-Nitrite 3 4 9.373 1.297 Lagoon A MIW Nitrate-plus-Nitrite 3 4 9.838 0.649 Bodie MIW Nitrate-plus-Nitrite 3 4 8.812 0.685 Eagle Pond MIW Nitrate-plus-Nitrite 3 4 11.592 1.240 Negative Control MIW Nitrate-plus-Nitrite 3 6 49.254 1.966 Denitrifying Sludge MIW Nitrate-plus-Nitrite 3 6 9.566 0.937 Goddard Marsh MIW Nitrate-plus-Nitrite 3 6 9.092 1.002 Lagoon A MIW Nitrate-plus-Nitrite 3 6 9.198 0.804 Bodie MIW Nitrate-plus-Nitrite 3 6 8.479 0.872 Eagle Pond MIW Nitrate-plus-Nitrite 3 6 9.487 1.114 Negative Control MIW Nitrate-plus-Nitrite 4 0 55.433 2.382 Denitrifying Sludge MIW Nitrate-plus-Nitrite 4 0 49.618 2.536 Goddard Marsh MIW Nitrate-plus-Nitrite 4 0 52.947 3.297 Lagoon A MIW Nitrate-plus-Nitrite 4 0 48.575 4.324 Bodie MIW Nitrate-plus-Nitrite 4 0 51.322 4.358 Eagle Pond MIW Nitrate-plus-Nitrite 4 0 52.265 5.379 Negative Control MIW Nitrate-plus-Nitrite 4 2 49.387 2.175 Denitrifying Sludge MIW Nitrate-plus-Nitrite 4 2 16.239 1.971 Goddard Marsh MIW Nitrate-plus-Nitrite 4 2 10.993 1.304 Lagoon A MIW Nitrate-plus-Nitrite 4 2 22.493 2.515   207 Sample Medium Analyte Passage Time Point, hrs Conc. mg-N/L Stev Dev Bodie MIW Nitrate-plus-Nitrite 4 2 19.150 1.986 Eagle Pond MIW Nitrate-plus-Nitrite 4 2 10.201 0.844 Negative Control MIW Nitrate-plus-Nitrite 4 4 46.791 2.734 Denitrifying Sludge MIW Nitrate-plus-Nitrite 4 4 4.497 0.608 Goddard Marsh MIW Nitrate-plus-Nitrite 4 4 5.890 0.723 Lagoon A MIW Nitrate-plus-Nitrite 4 4 10.121 0.877 Bodie MIW Nitrate-plus-Nitrite 4 4 5.970 0.517 Eagle Pond MIW Nitrate-plus-Nitrite 4 4 5.690 0.482 Negative Control MIW Nitrate-plus-Nitrite 4 6 47.823 2.817 Denitrifying Sludge MIW Nitrate-plus-Nitrite 4 6 3.504 0.104 Goddard Marsh MIW Nitrate-plus-Nitrite 4 6 2.827 0.334 Lagoon A MIW Nitrate-plus-Nitrite 4 6 4.888 0.255 Bodie MIW Nitrate-plus-Nitrite 4 6 2.451 0.128 Eagle Pond MIW Nitrate-plus-Nitrite 4 6 2.752 0.213  

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