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Biological reduction of selenium oxyanions in the presence of nitrate anions using anaerobic microbes Subedi, Gaurav 2016

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Biological Reduction of Selenium Oxyanions in the Presence of Nitrate anions using Anaerobic Microbes  by Gaurav Subedi  B.Sc., Jacobs University Bremen, 2010  A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF  MASTER OF SCIENCE in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Chemical and Biological Engineering)  THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver)  July 2016  © Gaurav Subedi, 2016 ii  Abstract Biological selenium reduction has emerged as a viable solution for the removal of toxic selenium from the environment. However, the presence of nitrate hinders selenium reduction by acting as a competitive electron acceptor. The present thesis investigated the use of local mine-impacted sediment as an inoculum for selenium reduction and studied the affect of nitrate on the removal of selenium. Sediment samples, impacted by mining activities, were collected from two vastly different sites of the Elk River Valley. These sediments namely; Goddard Marsh and Mature Tailing Coal, were enriched for selenium reducing bacterial consortium under high selenium and varying nitrate concentrations to put additional selection pressure. Ultimately, two cultures from Goddard Marsh enriched under low and high nitrate condition as well as one culture from Mature Tailing Coal enriched under moderate nitrate condition were used to access the affect of nitrate on selenium reduction using central composite design matrix. The extent of Se reduction was highest in the Goddard Marsh enrichment with no nitrate while enrichment with moderate and high nitrate reduced selenium poorly. ANOVA results from the CCD experiment in Goddard Marsh enrichment with no nitrate indicated no affect of nitrate in Se reduction.  Two primer sets targeting the selenate redutase (serA) from Thauera selenatis and nitrite reductase (nirK) from denitrifying population were used to quantify the population of selenium reducing and denitrifying population in the CCD experiment. Q-PCR assay successfully quantified serA genes in the cultures and correlated well with the initial Se concentration. Furthermore, the selenium reducing ability of enrichment cultures were compared with the bio-stimulated native sediments. Native sediments efficiently removed selenium from the culture medium while enrichment cultures preferentially removed nitrate over selenium. Metagenomic sequencing revealed the presence of many putative selenium reducers in the native sediments while Pseudomonas were more prevalent in the enrichment cultures. Denitrification, sulfate reduction and selenium assimilation genes were abundant in most sequences indicating its role in the reduction of selenium and nitrate. Thus, our study shows that efficient reduction of selenium in the presence of nitrate is possible with biological system.    iii  Preface This dissertation is an original, independent work of the author, G. Subedi.   Materials (Soil Samples) for experiment was kindly sent to us by Dr. Alison Morrison from Teck Coal,  except Mount Polley Soil samples which was collected by Dr. Susan Baldwin, Jon Taylor and Myself. The design of experiment as well as experimentation was done by myself while Dr. Susan Baldwin was involved in supervision, and guidance. She has contributed to analysis and interpretation of data as well as largely contributed to editing and revision of chapters in the dissertation.  Most of  the measurements (including selenium and nitrate) were performed in  Civil Engineering Lab located at the University of British Columbia while some measurements of (nitrate and nitrite) were also done in the Baldwin Lab at Chemical and Biological Engineering. Primers (serA, srdBCA) used in Chapter 3 for Q-PCR  experiment was designed by Jon Taylor and myself. Sample preparation for Illumina Mi-seq sequencing was done by Jon Taylor and was sent to Genome Quebec (http://gqinnovationcenter.com/index.aspx) for sequencing. Illumina sequences were analyzed in Metapathways software provided freely by the Hallam Lab.   iv  Table of Contents  Abstract .......................................................................................................................................... ii Preface ........................................................................................................................................... iii Table of Contents ......................................................................................................................... iv List of Tables ..................................................................................................................................x List of Figures .............................................................................................................................. xii List of Symbols and Abbreviations ............................................................................................xv List of Units ............................................................................................................................... xvii Acknowledgements .................................................................................................................. xviii Dedication ................................................................................................................................... xix Chapter 1: Introduction ................................................................................................................1 Chapter 2: Background and literature review ............................................................................5 2.1 Background of Selenium................................................................................................. 5 2.2 Selenium occurrence in the environment ........................................................................ 6 2.3 Biological assimilation and essentiality of  Selenium .................................................... 8 2.4 Bioaccumulation and ecotoxicological impact of Selenium ........................................... 9 2.4.1 Places where Se occurrence has been or still is a problem ......................................... 9 2.5 Water quality guidelines in BC and USEPA ................................................................ 11 2.6 Biological cycling of Selenium ..................................................................................... 11 2.6.1 Selenium oxidation ................................................................................................... 14 2.6.2 Selenium reduction ................................................................................................... 16 2.6.3 Non-dissimilatory Selenium reduction ..................................................................... 21 v  2.6.4 Se(IV) reduction........................................................................................................ 23 2.7 Mechanisms of Selenium Oxyanion reduction ............................................................. 24 2.7.1 Selenium transport/uptake ........................................................................................ 24 2.7.2 Dissimilatory reduction and selenate reductase ........................................................ 25 2.7.3 Selenite reduction...................................................................................................... 27 2.7.4 Assimilation .............................................................................................................. 27 2.7.5 Methylation ............................................................................................................... 28 2.7.6 Formation of metal selenides .................................................................................... 28 2.8 Treatment technologies available for removing Se from mining water ....................... 28 2.8.1 Physical treatment ..................................................................................................... 30 2.8.1.1 Reverse osmosis and Nanofiltration ................................................................. 30 2.8.1.2 Ion Exchange .................................................................................................... 31 2.8.2 Chemical treatment ................................................................................................... 32 2.8.2.1 Reduction with Zero-valent Iron ....................................................................... 32 2.8.3 Biological treatment .................................................................................................. 32 2.8.3.1 Wetlands and Passive Biochemical Reactors ................................................... 33 2.8.3.2 Active Bioreactors ............................................................................................ 33 2.8.3.2.1 Upflow Anaerobic Sludge Bed (UASB) Bioreactors .................................. 34 2.8.3.2.2 BseR/ABMet technology ............................................................................ 34 2.8.3.2.3 Bioreactors with specific selenate- or selenite-reducing microbes ............. 35 2.9 Summary, motivation and hypotheses .......................................................................... 35 2.10 Hypothesis and motivation for the work ....................................................................... 36 Chapter 3: Materials and method ..............................................................................................38 vi  3.1 Background of the sites from where the samples were collected ................................. 38 3.1.1 Site background ........................................................................................................ 38 3.1.2 Coalmine drainage impacted sediment samples from Elk River Valley .................. 39 3.1.3 Sediment samples from pilot-scale passive treatment plant, Mount Polley ............. 40 3.2 Experiments performed ................................................................................................. 40 3.2.1 Experiment 1: Initial tests to determine the potential for selenate-reduction in different environmental sediment samples ........................................................................... 40 3.2.2 Experiment 2: Enrichment of selenate-reducing bacteria from coalmine impacted sediments (primary enrichment) ........................................................................................... 41 3.2.3 Experiment 3: Removal of selenate in the presence of nitrate by primary enrichment culture obtained in experiment 2........................................................................................... 42 3.2.4 Experiment 4: Selenate reduction over time for the most successful enrichment cultures and the organisms likely responsible for selenate-reduction .................................. 42 3.2.4.1 Statistical design of experiment 4  (Central Composite Design) ...................... 43 3.2.5 Experiment 5: Comparison of the kinetics of selenium reduction by native sediments and the enrichments .............................................................................................................. 46 3.3 Analytical procedures ................................................................................................... 46 3.3.1 Selenium analysis...................................................................................................... 47 3.3.2 Nitrate/Nitrite-N analysis .......................................................................................... 47 3.3.3 DNA extraction methods .......................................................................................... 48 3.3.3.1 Laboratory enrichments (experiments 4) .......................................................... 48 3.3.3.2 Environmental samples (GM and MTC sediments) ......................................... 48 3.3.4 Quantitative polymerase chain reaction (Q-PCR) .................................................... 49 vii  3.3.4.1 Primer design .................................................................................................... 49 3.3.4.2 Assay ................................................................................................................. 50 3.3.4.3 Q-PCR standards and analysis .......................................................................... 50 3.3.5 Metagenomic sequencing.......................................................................................... 51 3.3.5.1 Library preparation and sequencing.................................................................. 52 3.3.5.2 Metagenomic analysis and assembly ................................................................ 52 Chapter 4: Results........................................................................................................................54 4.1 Experiment 1: Determining the potential for selenate-reduction in different environmental sediments samples............................................................................................. 54 4.2 Experiment 2: Enrichment of selenate-reducing bacteria from coalmine impacted sediments................................................................................................................................... 54 4.3 Experiment 3: Adaptation of primary enrichment culture at various concentration of nitrate ....................................................................................................................................... 55 4.4 Experiment 3: Selenate reduction in the presence of nitrate by the GM and MTC enrichments ............................................................................................................................... 56 4.4.1 Total soluble selenium and nitrate reduction by GM 0 mM NO3- enrichment ......... 56 4.4.1.1 ANOVA for the selenium reduction in GM 0 mM NO3- innoculum ................ 64 4.4.2 Selenium-reduction in the presence of nitrate by the GM 8 mM-NO3- enrichment culture ................................................................................................................................... 69 4.4.3 Selenium reduction by the MTC 4 mM NO3- enrichment culture ............................ 72 4.5 Quantitative analysis of selenate-reductase and nitrate-reductase in the Se-reducing cultures ...................................................................................................................................... 74 4.5.1 Quantification of 16S rDNA, serA, and nirK in GM 0 mM NO3- samples .............. 74 viii  4.6 Comparison of the kinetics of selenium reduction by native sediments and the enrichments ............................................................................................................................... 77 4.6.1 Effect of nitrate on selenium reduction by the Goddard Marsh enrichment ............. 79 4.6.2 Effect of nitrate on selenium reduction by the native Goddard Marsh sediment ..... 80 4.6.3 Nitrate reduction in GM enrichments and GM soil .................................................. 80 4.6.4 Effect of nitrate concentration on selenium reduction using the Mature Tailings Coal enrichment............................................................................................................................. 81 4.6.5 Effect of nitrate concentration on selenium reduction using the native Mature Tailings Coal ......................................................................................................................... 81 4.6.6 Nitrate reduction in MTC enrichment and MTC coal .............................................. 82 4.7 Metagenomic sequencing.............................................................................................. 83 4.7.1 Sequencing coverage and analysis with Metapathways ........................................... 83 4.7.2 Taxonomic distribution in samples ........................................................................... 83 4.7.3 Top species along with selenium reducing microbes in the samples ........................ 87 4.7.4 Annotation of sequences to functional categories of KEGG .................................... 91 4.7.4.1 Nitrogen metabolism in samples ....................................................................... 93 4.7.4.2 Sulfur metabolism in samples ........................................................................... 96 4.7.4.3 Putative selenoproteins identified in the samples ............................................. 98 Chapter 5: Discussion ..................................................................................................................99 5.1 The potential for selenium-reduction in four mine sediments ...................................... 99 5.2 Enrichment of GM and MTC samples at various concentrations of nitrate ............... 101 5.3 Total selenium and nitrate reduction in GM and MTC enrichments .......................... 102 5.4 Q-PCR of GM enrichments ........................................................................................ 106 ix  5.5 Comparison of selenium reduction by enrichment and native sediment samples ...... 107 5.6 Metagenomic analysis of enrichment and native sediment samples .......................... 110 Chapter 6: Conclusions and future work ................................................................................114 Bibliography ...............................................................................................................................116 Appendices ..................................................................................................................................135 Appendix A Some pictures from the enrichment experiment ................................................ 135 Appendix B Statistical analysis of GM 0 mM NO3-  inoculated culture ................................. 136 B.1 Effect of summary using percentage reduction as response variable ..................... 136 B.2 Actual by predicted plot, RMSE ............................................................................. 136 B.3 Prediction profile .................................................................................................... 137 B.4 Interaction Plots ...................................................................................................... 137 B.5 Effect of summary using rate constant as response variable .................................. 138 B.6 Actual by predicted plot, RMSE ............................................................................. 138 B.7 Prediction profile .................................................................................................... 139 Appendix C Metagenomic sequence analysis......................................................................... 140 C.1 Protocols used ......................................................................................................... 140 C.2 Nitrogen metabolism KEGG ................................................................................... 142 C.3 Sulfur metabolism KEGG ....................................................................................... 143  x  List of Tables Table 1. Selenium concentrations in some common materials. ...................................................... 7 Table 2. Water quality guidelines for Selenium in British Columbia and the U.S.A. .................. 11 Table 3. Free energy calculations for the oxidation of selenium species by various agents. Adapted from (Wright, 1999) ....................................................................................................... 15 Table 4. Free energy for the reduction of some electron acceptors using H2 as electron donor. Adapted from (Newman, Ahmann, & Morel, 1998). ................................................................... 17 Table 5. Treatment technologies for selenium removal ................................................................ 29 Table 6. Experimental range and levels of the independent variables .......................................... 45 Table 7. Target gene along with the primers selected .................................................................. 51 Table 8. Samples used for metagenomic analysis ........................................................................ 52 Table 9. Initial selenate reduction tests for samples obtained from mine sites............................. 54 Table 10. Rate constants (k) for different runs of GM 0 mM NO3- CCD experiment .................. 57 Table 11. Rate constants (k') for different runs of GM 0 mM NO3- ............................................. 58 Table 12. Anova results using percentage Se reduction (%) over 14 day as response ................. 64 Table 13.  Anova results using rate constant (k'=day-1) response ................................................. 66 Table 14. Average copy number ( ×104) of 16S rRNA, selenate reductase gene (serA) and denitrification gene (nirK) for different run order (samples) of the CCD experiment with GM 0 mM NO3- innoculum. .................................................................................................................... 75 Table 15. Analysis of Se and NO3- reduction in different run order of GM 0 mM NO3- cultures 76 Table 16. Reduction rate and extent of reduction ......................................................................... 82 Table 17: Summary of Metagenomic data obtained from MiSeq and Metapathways ................. 83 Table 18. Taxonomic distribution at domain level for different samples in percentage .............. 85 xi  Table 19. Percentage composition of various species in the samples with red highlighting putative Se reducers ...................................................................................................................... 88 Table 20. Nitrogen and Sulfur metabolism in samples ................................................................. 93 Table 21. Hits (normalized reads) assigned for Sulphur metabolism in different samples through SEED............................................................................................................................................. 97 Table 22. Selenoproteins in the samples ....................................................................................... 98 Table 23. Summary of effect using percentage reduction as response variable ......................... 136 Table 24. Summary of effect using rate constant as response variable ...................................... 138  xii  List of Figures  Figure 1. Biochemical selenium cycle. Biological organisms play a crucial role in each part of this cycle. ...................................................................................................................................... 13 Figure 2. The Phylogenetic tree of some Se(VI) and Se(IV) reducing microbes based on 16S rRNA gene sequence..................................................................................................................... 19 Figure 3. Schematic representation of different pathways involved in selenium transformation in microorganisms. ............................................................................................................................ 25 Figure 4. Illustration of electron transport pathways in Thauera selenatis. Figure adapted from (Debieux et al., 2011; Lowe et al., 2010; Nancharaiah & Lens, 2015) ........................................ 26 Figure 5. Five major coal mines operated by Teck in Elk Valley (Teck, 2014) ........................... 38 Figure 6. The figure describing the central composite design in two factor experiment with red highlighting the experimental run in CCD while the red+black represents the full factorial experiment needed to be performed for a two factor at five level experiment. ............................ 44 Figure 7.  Precipitation of elemental selenium (red coloration) in inoculated bottles .................. 55 Figure 8. Total dissolved selenium concentrations (mM) in Goddard Marsh enrichments. Enrichment media adapted at different nitrate concentration (mM) ............................................. 56 Figure 9. Time course of selenium reduction in different run order of GM 0 mM NO3- inoculants....................................................................................................................................................... 61 Figure 10. Nitrate reduction in different run orders of GM 0 mM NO3- inoculants ..................... 63 Figure 11. Response surface plot of the extent of Se reduction as a function of total dissolved selenium and nitrate. ..................................................................................................................... 67 xiii  Figure 12. Contour plot of the extent of Se reduction as a function of total dissolved selenium and nitrate...................................................................................................................................... 68 Figure 13. Response surface plot of the rate constant (k') as a function of total dissolved selenium and nitrate...................................................................................................................................... 68 Figure 14. Contour plot of the rate constant (k') as a function of total dissolved selenium and nitrate. ........................................................................................................................................... 69 Figure 15. Time curve of total selenium in different run order of GM 8 mM NO3- inoculants. .. 71 Figure 16. Time course of total selenium in different run orders of MTC 4 mM-NO3- inoculants....................................................................................................................................................... 73 Figure 17. Relative abundance of different genes in different run order of GM 0 mM NO3- inoculants ...................................................................................................................................... 75 Figure 18. Correlation between serA and Se concentration in different cultures of GM 0 mM NO3- inoculants. . .......................................................................................................................... 76 Figure 19. Time course of selenium and nitrate reduction in GM enrichment and sediments. .... 78 Figure 20. Time course of selenium and nitrate reduction in MTC enrichment and sediments. .. 79 Figure 21. PCoA plot of taxonomic composition of different samples ........................................ 85 Figure 22. Taxonomic composition at phylum level in different samples ................................... 86 Figure 23. Taxonomic composition at genus level for different samples ..................................... 86 Figure 24. Bubble plot of top 12 normalized species in the samples ........................................... 88 Figure 25. Different categories of KEGG in samples ................................................................... 91 Figure 26. Different Sub-categories of metabolism in KEGG pathway ....................................... 93 Figure 27. Hits for Nitrogen metabolism in different samples KEGG ......................................... 95 Figure 28. Hits for denitrification process in different samples KEGG ....................................... 96 xiv  Figure 29. Hits for Sulfur metabolism in different samples SEED .............................................. 97 Figure 30. Pictures from enrichment culture. A. GM inoculated culture media with Se at t=0 B. Selenium reduction after few days C. Dense elemental Se precipitate at the bottom D. Extracted elemental Se ................................................................................................................................ 135 Figure 31. RMSE for GM 0 mM NO3- cultures using extent of reduction as response variable 136 Figure 32. Prediction profile for extent of reduction in GM 0 mM NO3- cultures ..................... 137 Figure 33. Interaction plots for extent of Se reduction ............................................................... 137 Figure 34. RMSE for GM 0 mM NO3- cultures using rate constant as response variable ......... 138 Figure 35. Prediction profile for rate constant in GM 0 mM NO3- cultures .............................. 139 Figure 36. Quality score of sequence generated from FastQC ................................................... 141 Figure 37. Nitrogen metabolism of different samples in the following order: GM, GM_6, GM_8, GM_17, GM_21, MTC, MTC_36, and MTC_38 ....................................................................... 142 Figure 38. Sulfur metabolism of different samples in the following order: GM, GM_6, GM_8, GM_17, GM_21, MTC, MTC_36, and MTC_38 ....................................................................... 143  xv  List of Symbols and Abbreviations  ABMet®) Advanced Biological Metals Removal Process ANOVA Analysis of Variance BC  British Columbia BCRs  Biochemical Reactors bp  Base Pair BSeR  Biofilm Selenium Reactor CCD  Central Composite Design CCME  Canadian Council of Ministers of the Environment CH3COO- Acetate CO2  Carbondioxide cytc4  Cytrochrome c4 DMDSe Dimethyldiselenide DMSE  Dimethylselenide DMSeS Dimethylselenylsulfide DNA  Deoxyribonucleic Acid dw   Dry Weight Fe(II)  Ferrous Fe(III)  Ferric FTC  Fresh Tailing Coal GAC  Granular Activated Carbon  GM  Goddard Marsh GPx  Glutathione peroxidase  GS-Se-SG Selenodiglutathione H2  Hydrogen H2O  Water H2O2  Hydrogen Peroxide H2Se  Hydrogen Selenide har  Hydroxylamine Reductase HQNO  2-n-heptyl-4-hydroxyquinoline N-oxide HSeO32- Hydrogen Selenite ICP-OES Inductive Coupled Plasma-Optical Emission Spectroscopy IX  Ion exchange KDa  Kilo Dalton LCA  Lowest Common Ancestor LOEL  Lowest Observed Effect Level M.O.E  Ministry of Environment MP  Mount Polley MTC  Mature Tailing Coal N2  Nitrogen nar  Nitrate Reductase NF  Nanofiltration xvi  nir  Nitrite Reductase nirK  nitrite reductase NO3-  Nitrate NO3-  Nitrite nor  Nitric Oxide Reductase nos  Nitrous Oxide Reductase nr  NCBI nucleotide non redundant NSMP  Nitrogen and Selenium Management Program O2  Oxygen ORF  Open Reading Frame PCoA  Principal Co-ordinate Analysis QCR  Quinol-Cytochrome c Oxidoreductase QDH  Quinol Dehydrogenase qPCR  Quantitative Polymerase Chain Reaction RO  Reverse osmosis rpm  Revolution Per Minute rRNA  Ribosomal Ribonucleic Acid Se  Selenium Se(0)  Elemental Selenium/ Selenium Se(-II)  Selenide Se-cys  Selenocysteine Se-met  Selenomethionine SeO32-  Selenite [Se(IV)] SeO42-  Selenate [Se(VI)] serABC Selenate reductase operon SeRB  Selenate Reducing Bacteria SO4-  Sulphate UASB  Upflow Anaerobic Sludge Bed UASB  Upflow Anaerobic Sludge Blanket  USEPA United States Environmental Protection Agency ZVI)  Zero valent iron  xvii  List of Units %   Percentage µg/g  Microgram per Gram µg/L  Microgram per Liter µL  Microliter µm  Micrometer µM  Micromolar cm  Centimeter day-1  Per Day g  Gram g/L  Gram per Liter KJ mol-1 Kilojoule Per Mole  mg   Milligram mg N/L Milligram of Nitrate as Nitrogen per Liter mg.(L.day)-1 Milligram Per Liter Per Day mg/L  Milligram per Liter mL  Milliliter mM  Millimolar ng  Nanogram ng/µL  Nanogram per Microliter ng/L  Nanogram per Liter oC  Degree Celsius ppb  Parts Per Billion  xviii  Acknowledgements I would like to thank Dr. Susan Baldwin for all the support she has given me throughout my time at UBC. I am really thankful for her guidance in my academics. In addition, I would also like to offer my gratitude to the faculty, staff, and friends at CHBE who have inspired me in this field.  I am thankful to Jon Taylor for his technical help in the laboratory.   I am thankful to the Environmental Engineering lab at University of British Columbia for letting me use their instrument. I am also thankful to Hallam Lab for Metapathways software which has helped me analyze most of my Illumina sequences.  I am also thankful to all Office and Lab mate (current and past) for their moral support.  Finally, I would like to thank Imperial Metals, Teck and NSERC for their funding in this project.   xix  Dedication  To everyone I Love... 1  Chapter 1: Introduction The Canadian environment is one of the most pristine in the world. It comprises numerous dense forests, mountains, rivers and lakes, which provide habitat to a large variety of wildlife. Alongside, intensive mining activities pose a threat to wildlife and habitats. Although mining has been practiced for a long time, new and advanced methods of mining; open-pit mining and advanced oxidation technologies (Carrillo-Pedroza et al., 2012), has allowed processing of low grade ores resulting in increased production of waste rock and tailings. According to Statistics Canada, mining activities (including only metal and non-metal mineral extracting industries) alone contributed to 473 million tonnes of waste rock and tailings in 2008 (Statistics Canada, 2012). In conjunction, there are several hundred to thousand million tonnes of waste rock existing as a result of past mining activities. This waste rock contributes to leaching of toxic chemicals when precipitation passes through them and then into nearby creeks and lakes. When untreated, these pollutants can lead to grave environmental disasters (A Dennis Lemly, 2002; A. Dennis Lemly, 1994; a. Dennis Lemly, 2004). Selenium is one such contaminant that leaches from waste rock and tailings, which is cause for concern in some locations of Canada. Selenium occurs, as a minor constituent, in ores of sulphide such as pyrite (R. S. Dungan & Frankenberger, 1999; Lussier, Veiga, & Baldwin, 2003). Although selenium has been implicated, when at elevated concentrations, in some environmental disasters, in trace amounts it is an essential nutrient and is being considered for health benefits in diseases such as AIDS, Alzheimer's, arthritis, asthma, reproductive problems, thyroid dysfunction, viral infection and cancer (Brozmanová, Mániková, Vlčková, & Chovanec, 2010; Duntas & Benvenga, 2014; Fairweather-Tait et al., 2011). In Canada, selenium concentrations in most water sources are at the ppb level (Beatty & Russo, 2014). However, dissolved selenium still needs to be monitored and controlled because Se bio-concentrates up the food chain. Se concentrations at only 5 µg/L is enough to result in fatal reproductive and teratogenic defects in aquatic birds and wildlife including fish (A Dennis Lemly, 1993; a. Dennis Lemly, 2004). Moreover, anthropogenic sources of selenium input into the environment are increasing. Thus, Se, even at low concentrations, can result in extinction of local fish and wildlife by directly affecting their reproduction (A Dennis Lemly, 2002; Presser & Ohlendorf, 1987; Presser, 1994). As a consequence, activities that could lead to increase of Se above 2  regulated concentrations (1-2 µg/L) must be monitored and, if needed, be regulated. In British Columbia, the Ministry of Environment (2014) has set a mean selenium concentration of 2 µg/L in water columns to protect aquatic wildlife from adverse affects of selenium (Beatty & Russo, 2014).  Because of the insidious effects of selenium bioaccumulation and the requirement to keep concentrations below microgram per liter concentrations,  there is a great need for cost effective methods of selenium removal from mine-affected wastewater. Although many technologies have been used for the treatment of selenium impacted wastewater, several issues have hampered their efficacy including the need to consistently meet low discharge concentrations (1-5 µg/L), high volumetric flow rates, low temperatures, multiple discharge sources spread out over the mine site, and the presence of other competing ions like sulphate and nitrate. In recent years, biological treatment; involving the use of microorganisms to reduce selenium oxyanions into elemental selenium, has emerged as a viable option for treatment of selenium impacted water in mining and wastewater industries. However, even biological treatments are not without disadvantages.  One of the key issues prevalent in biological treatment of selenium in the mining environment is the competitive inhibition from nitrate, which often exceeds selenium concentrations by factors of 100 to 1000. Nitrate is introduced into the mining environment through the use of explosives (Forsyth, Cameron, & Miller, 1995; Jermakka, Wendling, Sohlberg, Heinonen, & Vikman, 2014). Reduction of nitrate precedes any other electron acceptor in anaerobic microbial reduction processes (Steinberg, Blum, Hochstein, & Oremland, 1992). This means that microbes (such as denitrifiers) will preferentially reduce nitrate (present at milli-molar concentrations) instead of selenium (present in micro-molar concentrations). This increases the cost of biological selenium treatment as most of the organic carbon added to the system is used up in nitrate reduction. Although nitrate reduction is desired, the discharge limit of nitrate is significantly higher (13 mg-N/L) (CCME, 2012) than that for selenium.  Selenium oxyanion reduction can be performed by denitrifying microbes as the membrane bound and periplasmic nitrate reductases present in these microbes exhibit affinity for selenate (Sabaty, Avazeri, Pignol, & Vermeglio, 2001; Watts et al., 2005). However, both affinity and specific activities for selenate reduction in these reductases are low and hence selenate reduction 3  proceeds at only low nitrate concentrations (Sabaty et al., 2001; Watts et al., 2005). Therefore in order to eliminate preferential reduction of nitrate, the removal of nitrate is essential prior to selenium removal. Some treatment technologies have utilized algal-bacterial system to mitigate the competitive inhibition of nitrate. However, concerns of increased bio-availability of selenium after treatment (Amweg, Stuart, & Weston, 2003) as well as the increased costs caused by spatial separation of two processes (algal and bacteria), along with post-treatments (Lenz & Lens, 2009) have decreased its applicability. In recent years, several selenium reducing microbes,  including Thauera selenatis have been isolated, which have a very high affinity and selectivity for selenate reduction (DeMoll-Decker & Macy, 1993; J. Macy, Lawson, & DeMoll-Decker, 1993). These microbes can efficiently reduce selenium even in the presence of high concentrations of nitrate. Several selenate reductases, having high specificity for selenate, have been isolated from many other types of microorganisms over the past decade (T Krafft, Bowen, Theis, & Macy, 2000; Nancharaiah & Lens, 2015; Watts et al., 2005). Some of these selenate-reducing microbes, with specific selenate reductases, have been used at the pilot scale in wastewater treatment plants. For example, Thauera selenatis was used in a pilot-scale biological reactor to treat agricultural drainage water containing both selenium and nitrate (Cantafio et al., 1996). The influent Se and nitrate concentrations of 289 µg/L and 64.4 mg-N/L, respectively, were reduced to effluent concentrations of 12 µg/L and 5.6 mg-N/L, respectively, on average. Although out-competition with a rod-shaped indigenous microbe was noticed after 135 days hampering selenate and nitrate reduction, lowering the pH of the feed system to 6.9 solved the problem and thereafter selenate reduction proceeded efficiently. Out-competition of seed selenate reducers with indigenous microbes entering with the feed water from a mine site caused operational problems at another pilot plant (personal communication). Seed microorganisms typically used in Se removal bioreactors are either highly enriched cultures of only one or a few species that come from a supplier, or come from activated sludge systems treating completely different types of wastewater. It is the hypothesis of this thesis that the local mine-impacted environment will contain selenate-reducers and that these might be suitable for use in treatment bioreactors eliminating the need for external inoculum. 4  In addition, the major objective of this thesis was to determine the capability of indigenous microorganisms in sediments impacted by mining activities to reduce selenium oxyanions. Two vastly different mine sediments were used: one from a highly vegetated wetland receiving leachate from coal waste rock piles, and the other from a mature coal tailings pond devoid of plants. Since nitrate is present in mine-influenced water, the effect of nitrate at different concentrations on selenate-reduction by the enrichments was assessed. Moreover, the selenate reduction ability of bio-stimulated native sediments was compared with that of the enrichments. In addition to measuring kinetics, quantification of genes involved in nitrate and selenate reduction was used to quantify the population dynamics in the culture. The structure and function of the microbial communities present in the sediments and enrichments was determined through whole DNA shot gun sequencing.   5  Chapter 2: Background and literature review 2.1 Background of Selenium Selenium was discovered by a Swedish chemist, Jon Jakob Berzelius, in 1818. He named it after the Greek word "selene", meaning "moon". It is a naturally occurring element that has a wide, albeit scarce, distribution in the lithosphere (Shamberger, 1983).  It is placed in Group VI A of the Periodic Table along with other chalcogens like oxygen, tellurium and polonium. Selenium possesses properties of both a metal and a non-metal and is therefore classified as a metalloid. Selenium, in its inorganic forms, is structurally similar to sulphur with varying oxidation states of +6, +4, 0 and –2.  In addition, there is an identical resemblance of Se and sulphur with respect to atomic size, bond energies, ionization potential and electron affinities. However, selenium-containing compounds exhibit different properties and reactivity (Zannoni, Borsetti, Harrison, & Turner, 2007). This is apparent in the unique properties exhibited by the selenoproteins (Arnér, 2010; Johansson, Gafvelin, & Arnér, 2005) as well as toxicities exhibited by various selenium compounds. Selenium, being one column lower in the periodic table, is larger and more polarizable than sulphur. This increase in the polarizibility property as well as acidic strength gives higher dissociative power to selenol (R-Se-H) compounds at physiological pH (pKa of selenocysteine is much lower than cysteine), which are important for their catalytic roles as enzymes (Johansson et al., 2005; Tinggi, 2003). The most common Se oxyanions found in natural soil pore water and in surface waters are selenate, SeO42– (Se+6), and selenite, SeO32– (Se+4) (R. S. Dungan & Frankenberger, 1999).  Both oxyanions represent the most oxidized forms of Se commonly encountered in surface waters that get transported from rivers in particulate-associated colloidal form (Haygarth, 1994; Lenz & Lens, 2009). Moreover, these oxyanions are highly mobile, toxic and are known to bio-accumulate (R. S. Dungan & Frankenberger, 1999).  In contrast to the Se oxyanions, elemental selenium (Se(0)), is highly insoluble in aqueous solutions and occurs under more reducing conditions. The chemistry of elemental selenium is intricate due to the presence of several allotropic forms (Lenz & Lens, 2009). In general, three allotropic forms have been recognized: a red amorphous form, a black amorphous form and a grey hexagonal form, however other forms are described as well. Minaev et al. 2005 6  described seven crystalline forms including trigonal (grey), α and β-monoclinic (red), α and β-cubic, rhombohedric and ortho-rhombic forms (Minaev, Timoshenkov, & Kalugin, 2005). Inorganic Se, selenate and selenite, reduces biologically to give orange-red precipitate indicative of amorphous elemental selenium [Se(0)] (Doran, 1982). Selenide (Se(-II) ) is the most reduced form of selenium and can be present in soil and aqueous solutions  as inorganic metal selenides, organic selenium compounds, or as toxic hydrogen selenide (John F Stolz, Basu, Santini, & Oremland, 2006). Free selenide is very unstable due to its low reduction potential and hence gets oxidized to elemental selenium in the presence of oxygen in the soil. Hence, at pH lower than 9, very little selenide exists and the only stable selenide present in a system is either metal selenides or organic selenides (Doran, 1982). The inorganic reduced Se-forms include mineral selenides and hydrogen selenide (H2Se). Organic Se-containing compounds include volatile methyl species such as dimethylselenide (DMSe,[CH3]2Se), dimethyldiselenide (DMDSe, [CH3]2Se2), dimethylselenone ([CH3]2SeO2), methane selenol (CH3SeH), and dimethylselenylsulfide (DMSeS, ([CH3]2SeS), and Se-substituted amino acids such as selenomethionine (Se-met), selenocysteine (Se-cys) and selenocystine  (R. S. Dungan & Frankenberger, 1999).   2.2 Selenium occurrence in the environment Selenium occurs widely throughout the Earth's crust, however it ranks as the seventieth most abundant element and is usually present in most soils at a very low concentrations. The Earth's crust is composed of igneous rock and hence selenium’s mean concentration in igneous rock of 0.09 µg/g is taken as the abundance for the earth's crust (Shamberger, 1983). The concentration of selenium in soil is primarily dependent on the selenium content of the parent soil as well as the processes that have led to selenium mobilization or mineralization (Shamberger, 1983). Selenium is more concentrated in organic matter containing materials, such as coal and black shale, since plants and animals bioconcentrate selenium above levels in the surrounding environment by uptake through roots (Butterman & Brown, 2004). The world average selenium content in coal is taken to be 1.6 and 1.0 µg/g respectively (for hard and brown coal) (Yudovich & Ketris, 2006), which greatly concentrates in the remaining ash after 7  combustion to a value of 9.9 µg/g. Thus Se is considered to be a "coalphile element" (Yudovich & Ketris, 2006).  Selenium distribution in soils is heterogeneous with Se deficient soils (<0.1 µg Se g-1) existing in close proximity to seleniferous (>0.5 mg Se kg-1) soil (F. M. Fordyce, Guangdi, Green, & Xinping, 2000; Lenz & Lens, 2009).  Average Se concentrations in most un-contaminated soils range from 0.1 to 2 µg/g (Table 1).  Some soils have unusually high Se concentrations, sometimes as high as 100 µg/g  (F. Fordyce, 2007; Lenz & Lens, 2009). Most of these soils (especially in the Western USA) are derived from parent material deposited during the Cretaceous period (R. S. Dungan & Frankenberger, 1999). Although, geological formations determine the base concentration of selenium in the soil, bioavailability of selenium for plants and animals is determined by environmental factors including pH, redox, organic matter availability and the presence of competitive ions, such as nitrate and sulphate (F. Fordyce, 2007). Plants that grow in high Se containing soil can accumulate significant amounts of Se, which is one method proposed for remediating Se-contaminated soils called phyto-remediation (Bañuelos, Lin, Wu, & Terry, 2002). In aquatic systems, both freshwater and saltwater, Se content is usually lower than that found in terrestrial soils and ranges from 0.05 to 4 ppb (Doran, 1982).  Table 1. Selenium concentrations in some common materials. Material or waste source Se concentration References Earth's crust   0.09 µg/g (Shamberger, 1983)a Sedimentary rocks 0.08-1.0 µg/g (Shamberger, 1983)a Sandstone 0.05- 1.0 µg/g (Shamberger, 1983)a Shales 0.6 µg/g (Shamberger, 1983)a Carbonate 0.0-2.0 µg/g (Shamberger, 1983)a Non seleniferous soil 0.1-2.0 µg/g (Doran, 1982)b Seleniferous soil 2-200 µg/g (Doran, 1982)b Ocean water 0.0001-0.004 µg/L (Doran, 1982)b River water 0.0001-0.0004 µg/L (Doran, 1982)b Vegetation (Crop plants-low Se areas) <0.05  µg/g (Doran, 1982)b Coal 0.4-24 µg/g (a D Lemly, 1985)c Coal burner ash(bottom ash) 7.7 µg/g (a D Lemly, 1985) c Precipitator ash (fly ash) 0.2-500 µg/g (a D Lemly, 1985) c Scrubber ash (fly ash) 73-440 µg/g (a D Lemly, 1985) c 8  Crude shale oil 92-540 µg/liter (a D Lemly, 1985) c Crude oil 500-2200 µg/liter (a D Lemly, 1985) c Tables adapted from a) Shamberger, 1983, b)Doran, 1982, and C) Lemly,1985.  2.3  Biological assimilation and essentiality of  Selenium  Selenium displays a double-edged sword characteristic in animal nutrition acting both as an essential element needed in trace amounts and as a toxin at higher concentrations. Historically, selenium was considered to be the cause of "alkali disease" or selenosis that plagued livestock grazing on crops that naturally accumulated selenium from seleniferous soils (Mayland, 1994). However, selenium (as selenocysteine) forms a central component of  selenoprotein, which is important for different metabolic functions. A number of selenoproteins have been identified in all domains of life: bacteria, archaea, and eukaryotes (Heras, Palomo, & Madrid, 2011). However, some organisms like fungi, insects and higher plants lack selenoproteins and utilise cysteine-containing homologs instead (Lobanov, Hatfield, & Gladyshev, 2009). The majority of selenoproteins function as redox enzymes that protect the cell against harmful effects of free radicals formed during oxidation process, thus protecting cellular membrane and organelles against peroxidative damage. Selenoproteins have been found to be integral parts of mammalian enzymes such as Glutathione peroxidase (GPx), which similarly protects the cell against oxidative damage by reducing H2O2, lipid hydroperoxides, and various organic peroxides (F. Fordyce, 2013). Other selenoprotein containing enzymes are iodothyronine deiodinase, which is involved in metabolism of thyroid hormone, and thioredoxin reductase that is involved in a wide range of important antioxidant and redox regulatory roles in the cell (Johansson et al., 2005). Three redox enzymes that contain selenocysteine as the catalytic center have been studied extensively in the bacteria. These include formate dehydrogenase in Escherichia coli, Salmonella species and methane producing bacteria; glycine reductase in Clostridium sticklandii; and hydrogenase in Methanococcus Vannielii, Methanococcus voltae, and Desulfovibrio baculatus  (Stadtman, 1990).  The number of selenoproteins in different organisms has expanded with the use of bioinformatics along with the knowledge of the complete genome sequences of many organisms. However, the exact functions of many of these selenoproteins are still unknown. All together 25 9  selenoprotein genes have been identified in human (Kryukov et al., 2003), 24 in Rodents with high similarity to human selenoproteome (Kryukov et al., 2003), and at least 16 selenoprotein has been identified in the prokaryotic genome (Kryukov & Gladyshev, 2004). Aquatic organisms organisms such as fish and microalgae posses higher numbers of selenoproteins than terrestrial (Lobanov et al., 2009).  2.4 Bioaccumulation and ecotoxicological impact of Selenium  Microorganisms and multi-cellular organisms need selenium for the metabolism of important enzymes (selenoproteins) in their body. These organisms have evolved specific transport pathways that facilitate the uptake of this element. These specific cellular uptake pathways display differential specificity but high affinity for Se. As a result of this high-affinity transport pathway, uptake at low-ambient concentration is highly efficient while at higher concentration the uptake of Se is saturated (Stewart et al., 2010). Microorganisms and algae (primary producers) bioconcentrate Se at the base of the food web by 102- 106 fold from the ambient water (Stewart et al., 2010). The bioaccumulation of Se by primary consumers greatly increases the exposure of aquatic consumers higher up in the food web to Se toxicity. Moreover, the chain of Se concentration continues from the  benthic invertevrates (by 10 fold) to  fish which accumulates Se in tissue around 1-2 times the dietary intake (Stewart et al., 2010).   2.4.1 Places where Se occurrence has been or still is a problem The most notable case of selenium impact on the environment took place at Kesterson Reservoir, California, USA. A subsurface drain installed in west central San Joaquin valley collected saline water that included selenium oxyanions from weathered marine sedimentary rock and seleniferous soil that ultimately terminated at various wetlands in Kesterson reservoir (Presser & Ohlendorf, 1987). Dissolved concentrations of Se in some of these drains were up to 1400 µg/L that resulted in the increase of Se concentrations to as high as 300 µg/L in ponds that received this drainage (Presser, 1994). As a consequence, high concentrations of Se were taken up into the food web and this led to high incidents of embryonic deformities and death of many aquatic wildlife birds (Ohlendorf, H.M. & Santolo, 1994). Although the drain was halted in 1986 10  and the reservoir was capped with soil, Se concentrations in some of the ephemeral ponds remained high (up to 162 µg/L) putting aquatic as well as terrestrial animals at risk (Ohlendorf, H.M. & Santolo, 1994).  In Belews Lake, North Carolina, Se contamination from fly ash pond effluents released into the reservoir resulted in the elimination of the entire fish population from the reservoir (A Dennis Lemly, 2002). Episodes of selenium contamination are increasing worldwide with various anthropogenic activities such as coal mining and combustion; gold, silver, copper and nickel mining; metal smelting; oil transport, refining, and utilization; as well as agricultural irrigation (a. Dennis Lemly, 2004). Growing concern of selenium contamination in aquatic wildlife comes from the increasing mining activities such as coal and phosphate mining. Open pit mining practices produce "pit lakes" with elevated Se concentration. Moreover, Se leaching from overburden material to groundwater and surface water presents increasingly complex problem for remediation (Young et al., 2010).  The Elk River Valley in southeastern British Columbia is a major coal-producing region of Canada. Teck Coal Ltd. operates five coal mines within the Elk River Valley (Teck Coal, 2009). In these areas, large volumes of waste rock are created by removing hundred of cubic metres of overlying rocks and depositing them in the valley (Wellen, Shatilla, & Carey, 2015). These waste rock dumps contain selenium at a mean concentration of 3.12 mg/kg (Hendry et al., 2015). Weathering and leaching of Se from the waste rock has increased the concentration of Se downstream of these mines in the Elk River since 1990 and concentrations have been increasing ever since (Teck Coal, 2009). The Elk River downstream of all mines had an average Se concentration of 7.3 µg/L in 2009 (Teck Coal, 2009), whereas the Se concentration near the discharge locations can be as high as 300 µg/L (Young et al., 2010). The dissolved selenium present in the Elk River threatens to pose deleterious effects on the native fish population, especially Westslope Cutthroat trout (up to 60 µg/g dw Se was measured in fish tissue, which is well above the 10-15 µg/g when fish start experiencing Se poisoning) (A.D. Lemly, 2014). These incidents around the world underline the importance of developing cost-effective state-of-the-art technology for removing Se from contaminated sites.  11  2.5 Water quality guidelines in BC and USEPA Water quality guidelines developed by several jurisdictions are summarized in Table 2. In British Columbia (BC), the Ministry of Environment (MOE) has developed ambient water quality guidelines for selenium in order to protect aquatic resources (Beatty & Russo, 2014). The maximum acceptable Se concentration in drinking water has been set at 10 µg/L in order to protect against the adverse health effects of selenium. Similarly, ambient water concentration in both freshwater and marine water is set at 2 µg Se/L for protection of aquatic life. This guidelines differs from the Canadian Council of Ministers of Environment (CCME) guidelines of 1 µg/L and was based on the lowest observed effect level (LOEL) of 10 µg/L and a safety factor of 5 (CCME recommended safety factor is 10). The total allowable mean selenium concentrations have also been set for sediment and fish tissue by different jurisdictions. In the USA, the U.S. Environmental Protection Agency (USEPA) set higher concentrations for selenium than BC probably as input of Se into the body of organisms is more dependent on dietary source rather than the water selenium concentration itself.  Table 2. Water quality guidelines for Selenium in British Columbia and the U.S.A.  BCa USEPAa Drinking water 10 µg/L 50 µg/L Fresh water  2 µg/L 5 µg/L Marine water 2 µg/L 290 µg/L Sediment  2 µg/g dw  tissue 4-11 µg/g dw 5.8-7.91 µg/g dw a: values obtained from BCMOE, 2014.  2.6 Biological cycling of Selenium Selenium cycling in nature proceeds through the change in the redox state (Masscheleyn & Patrick, 1993) transforming selenium compounds  in different compartment of nature: soil, aquatic systems, atmosphere, through various physical, chemical, and biological reactions (Dungan & Frankenberger, 1999) (Figure 1). Although abiotic transformations such as reduction with green rust (Myneni, 1997), weathering, volatilization (Maher et al., 2010), and adsorption to 12  clay (Goldberg, 2014; Peak & Sparks, 2002) contribute to selenium flux in the environment, biologically mediated transformation of selenium is the predominant factor in the biochemical cycling of selenium (Doran, 1982; R. S. Dungan & Frankenberger, 1999).  Biological transformation of selenium spans across Bacteria, Archaea, Eukaryotes, and even viruses (Nancharaiah & Lens, 2015), which contribute to both oxidation and reduction of Se.  Although Se is sparsely distributed within the earth's crust (Lenz & Lens, 2009) and may not contribute significantly to the mineralization of organic compounds in the soil, selenium reducing microbes have been found in ubiquitous locations ranging from pristine (Ike, Takahashi, Fujita, Kashiwa, & Fujita, 2000) to contaminated soils (Frankenberger & Arshad, 2001; Knotek-Smith, Crawford, Möller, & Henson, 2006; Lenz & Lens, 2009) and appear to be phylogenetically and physiologically diverse (Narasingarao & Häggblom, 2007). Moreover, microbial reduction of soluble selenium oxyanions into less toxic and immobile elemental selenium or to volatile methylated compounds (Dimethylselenide) is an important mechanism for treatment of effluents from various Se emitting industries as stringent laws regulate the discharge of Se into the environment (R. S. Dungan & Frankenberger, 1999; Frankenberger & Arshad, 2001).  Biological Se transformation can be categorized into four reactions: 1) Reduction (assimilatory and dissimilatory), 2) Oxidation, 3) Methylation and 4) Demethylation (R. S. Dungan & Frankenberger, 1999). These reactions play a vital role in the transformation of Se compounds across different spheres and influence availability by either mobilizing or mineralizing Se.  13   Figure 1. Biochemical selenium cycle. Biological organisms play a crucial role in each part of this cycle. Adapted from (Lenz & Lens, 2009).  The reduction of selenium in microorganisms proceeds through either the use of selenate (SeO42– (Se+6)) or selenite (SeO32– (Se+4)) as terminal electron acceptors under anaerobic conditions by dissimilatory reduction or through incorporation of Se into the selenoproteins by assimilatory reduction (R. S. Dungan & Frankenberger, 1999). The common reduction product of dissimilatory reduction is elemental selenium (Se(0)). However, selenium oxyanions and elemental selenium can be further reduced to selenide that precipitate with metal cations in the solution (Herbel, Blum, Oremland, & Borglin, 2003). Dissimilatory reduction is a mechanism used by specialized microorganisms to eke out life using scantly available electron acceptors that are found in selenium-contaminated sites through the conservation of metabolic energy. Although other common electron acceptors like nitrate, sulfate, and iron supersede selenium in terms of abundance in the environment, dissimilatory reduction of selenium is important 14  industrially because of the bioremediation possibilities of using these organisms for treatment so as to protect aquatic ecosystems downstream of mine sites. Selenium oxyanions can also be reduced in oxic environments, however this reduction serves detoxification rather than respiratory purposes (Lortie, Gould, Rajan, McCready, & Cheng, 1992a). Assimilatory reduction either incorporates Se into selenoproteins or into Se-containing proteins . Similarly, reduced selenium species such as selenide or elemental selenium have been found to be oxidized by chemolithotrophic  and/or chemoautotrophic microorganisms in a biological reaction that completes the other half of the selenium cycle (M. E. Losi & Frankenberger, 1998; Nancharaiah & Lens, 2015). Methylation is another detoxification mechanism employed by microorganisms to remove harmful selenium oxyanions by converting them into volatile methylated products. Methylating groups of bacteria and fungi have been isolated and studied from numerous seleniferous soil and sediments (Doran, 1982). Lastly, demethylation of methylated selenium species is also carried out by microorganisms where DMSE (dimethylselenide) acts as a sole carbon source for the growth of certain microorganism (R. S. Dungan & Frankenberger, 1999).  Thus, microorganisms deploy various mechanisms and reactions that contribute significantly to the transformation and flux of selenium in the environment.  2.6.1 Selenium oxidation Although analogous to sulphur oxidation, which has been well studied, selenium [Se(0) and Se(-II)] oxidation has received very little attention. The oxidation of selenium can be classified into: abiotic and biotic. Although re-solubilization of precipitated elemental selenium is known to occur abiotically, it is very difficult to find any investigation of this in the literature. A calculation of free energy for the oxidation of Se(0) (Wright, 1999), in theory, support the abiotic dissolution/oxidation of Se(0) in oxygenated water:                                          Eqn. (1)     15  Table 3. Free energy calculations for the oxidation of selenium species by various agents. Adapted from (Wright, 1999) Redox pair Reaction                                                  -179    /                                 -525                                    -724       /                                -270  H2Se, a volatile selenium species, is known to oxidize rapidly into elemental selenium and water on exposure to air (Doran, 1982). The selenium present as selenide in pyritic rocks can also be oxidized by oxygen. This may occur abiotically or at a much higher rates with microbes acting as a catalyst much in the same way that sulphide oxidization is accelerated in the presence of Acidothiobacillus sp., for example (Gleisner, Herbert, & Frogner Kockum, 2006). Nitrate is a compound commonly found in mining water due to the application of explosives and in agricultural water due to the application of fertilizers. The free energy for oxidation of Se by NO3- indicates that NO3- can also act as an electron acceptor in oxidation of reduced Se species (Table 3). This possibly explains the positive correlation known to occur between high soluble Se and high NO3- concentration in surface water and ground water samples in irrigated cretaceous marine shale of Western Colorado (Wright, 1999). This indicates that nitrates must be applied judiciously in seleniferous areas by better managing the release of nitrate from explosives and controlling excessive use of fertilizers in Se rich agricultural areas. The use of Se as an energy source by microorganisms is speculated to occur in ways similar to sulphur oxidation. Microorganisms that respire on either reduced S or Se compounds co-occur in Se and S contaminated environments. For sulphur, the genera Thiobacillus, Thiomicrospira, and Sulfolobus  oxidize elemental sulphur or sulphides, which can lead to the production of sulphuric acid (acid rock drainage). For example, Thiobacillus ferroxidans oxidizes the sulphides present in the pyritic and pyrrhotitic rocks through oxidation of ferrous to 16  ferric iron (Fe(II) to Fe(III)). Ferric iron, a powerful oxidizing agent, can oxidize sulphide as well as selenide present in pyritic rocks (Brock & Gustafson, 1976). Selenium oxidation has been reported by Dowdle and Oremland (1998) in oxic soil slurries as well as in bacterial culture (Dowdle & Oremland, 1998).  The main product of this biotic oxidation was selenite (Se(IV)), while a small amount of selenate (Se(VI)) was also produced. Losi and Frankenberger (1998) also reported on Se oxidation in various soils taken from locations in the Western USA and reported that the process was largely biotic with relatively low oxidation rates (M. E. Losi & Frankenberger, 1998). Moreover, Oremland and co-workers also reported on the oxidation and re-solublization of precipitated elemental selenium with either nitrate or FeOOH while investigating dissimilatory selenate reduction, which indicates simultaneous occurrence of both processes: reduction and oxidation (R S Oremland et al., 1989) in soil. However, oxidation was much slower compared to the more significant contribution of reduction confirming the low reaction rate of Se oxidation reaction. Torma and Habashi (1972) reported on oxidation of copper selenide to Se(0) by Thiobacillus ferroxidans (Torma & Habashi, 1972) while  Sarathchandra and Watkinson (1981) reported on a heterotrophic bacteria Bacillus megaterium, which oxidized Se(0) into Se(IV) and Se(VI) (Sarathchandra & Watkinson, 1981). 2.6.2 Selenium reduction Selenate, SeO4-2 (Se(VI)), and selenite, SeO3-2 (Se(IV)), are highly soluble in water and do not easily undergo chemical reduction at neutral pH or room temperature (John F. Stolz & Oremland, 1999). Microbial reduction of selenium oxyanions into elemental selenium offers a cheap and viable option for treatment of selenium-impacted water. The oxidation/reduction potential of the Se(VI)/Se(IV) redox couple is +440 mv (Doran, 1982) and the use of its oxyanions as electron acceptors in microbial respiration is energetically favorable. The free energy associated with the reduction of common electron acceptors using H2 as the electron donor is presented in Table 4.    17  Table 4. Free energy for the reduction of some electron acceptors using H2 as electron donor. Adapted from (Newman, Ahmann, & Morel, 1998). Redox pair Reaction                O2/H2O                    -23.55      /                                   -22.48                                         -20.66                                                  -15.53                                         -13.42                                            -8.93  The free energy associated with the reduction of common electron acceptors including Se(VI) reveals that although the microbial reduction of Se(VI) can be energetically significant, other electron acceptors could compete for electrons. The Se(VI)/Se(IV) redox couple falls below the Mn(IV)/Mn(II) redox couple in terms of Gibbs free energy but lies above the NO3-/NH4+ pair. The NO3-/N2 redox pair is, however, above Se(VI)/Se(IV) and therefore thermodynamics slightly favours nitrate over selenate as electron acceptor in microbial reduction. The reduction of selenate to selenite theoretically provides -575 KJ mol-1 of acetate and  -343 KJ mol-1 of lactate (J. M. Macy, Michel, & Kirsch, 1989; John F. Stolz & Oremland, 1999). The complete reduction of Se(VI) to Se(0) is also possible and energetically favorable and provides -452.7 KJ mol-1 of acetate (calculated in appendix). The stoichiometric equation for these reductions are given below:                                       Eqn. (2)                                                      Eqn. (3)                                              Eqn. (4)  18  These energetically favorable reactions deployed by microorganisms to support their growth under anoxic conditions is referred to as dissimilatory reduction. Dissimilatory reduction of selenium oxyanions takes place in soils, sediments and water by phylogenetically and physiologically diverse bacteria (R. S. Dungan & Frankenberger, 1999; Narasingarao & Häggblom, 2007). Oremland et al. (1989) first reported the dissimilatory reduction of Se(VI) in sediment slurries and demonstrated this mechanism to be a major sink for selenium oxyanions in anoxic sediments (R S Oremland et al., 1989). Dissimilatory reduction of selenate was accelerated by the addition of electron donors and resulted in complete removal of Se(VI). The addition of other electron acceptors: O2, NO3-, and MnO2 inhibited the reduction process while SO4- and FeOOH did not interfere in the reaction. A bacterium, referred as SES, was isolated from the sediment collected from the San Joaquin valley (CA) and it demonstrated growth on acetate coupled to Se(VI) reduction with Se0 and CO2 as the end product (R S Oremland et al., 1989). This isolate was named as Sulfurospirillum barnesii (J F Stolz et al., 1999). It belongs to the   subgroup of the class Proteobacteria (Ronald S. Oremland et al., 1999). Subsequent experiments with Sulfurospirillum barnesii strain SES has revealed that it is able to grow with a number of electron acceptors including Se(VI), NO3-, SO4-, and even O2 under microaerophilic conditions (J F Stolz et al., 1999). Moreover, S. barnesii has been reported to have constitutive selenate reductase which is capable of reducing sub-millimolar level of selenate when grown on nitrate, thiosulfate or arsenate (Ronald S. Oremland et al., 1999). Simultaneous selenate and nitrate reduction occurred in both selenate and nitrate grown S. barnesii culture (Ronald S. Oremland et al., 1999).  19   Figure 2. The Phylogenetic tree of some Se(VI) and Se(IV) reducing microbes based on 16S rRNA gene sequence The evolutionary tree was inferred using the Neighbor-Joining method (Saitou & Nei, 1987). The optimal tree with the sum of branch length = 1.40848252 is shown. The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) are shown next to the branches (Felsenstein, 1985). The evolutionary distances were computed using the p-distance method (Nei & Kumar, 2000) and are in the units of the number of base differences per site. Evolutionary analyses were conducted in MEGA6 (Tamura, Stecher, Peterson, Filipski, & Kumar, 2013).  Macy et al. (1989) reported on anaerobic respiration of selenate by a Pseudomonas species that was isolated from agricultural drainage water in the San Joaquin valley of California (J. M. Macy et al., 1989). Subsequent classification identified this strain as the first member of genus Thauerea and named it as Thauerea selenatis. It belongs to the beta subclass of Proteobacteria (J. M. Macy et al., 1993). Thauerea selenatis couples oxidation of acetate to the reduction of Se(VI) with Se0 and CO2 as the end products. Reduction of Se(VI) occurs in two steps with selenate reductase first reducing the Se(VI) into Se(IV) while a periplasmic nitrite reductase finally converts Se(IV) into elemental Se (DeMoll-Decker & Macy, 1993). The selenate reductase is specific for Se(VI) and the NO3- is converted by a distinct and separate 20  nitrate reductase. Moreover, the complete reduction of Se(VI) into Se0 occurred only when NO3- was present in the media (DeMoll-Decker & Macy, 1993; J. M. Macy et al., 1993). Losi and Frankenberger (1997) isolated a gram negative facultative bacterium Enterobacter cloacae SLD1a-1 from San Luis Drain, California that used Se(VI) and NO3- as terminal electron acceptors under anaerobic growth conditions. The reduction of Se(VI) was uninhibited by the presence of NO3- and both of the anions were reduced concomitantly. Moreover, it was suggested that the reduction of Se(VI) occurred through a membrane-based reductase that led to a transitory intermediate, Se(IV), which was  subsequently reduced to Se0  and rapidly expelled from the cell (Mark E. Losi & Frankenberger Jr., 1997). However, the author failed to mention the exact mechanism of Se expulsion and the enzymes that reduced Se(IV) into Se0. Narasingarao and Haggblom (2007) isolated and characterized four novel anaerobic dissimilatory selenate-respiring bacteria from geographically distinct sediments of Chennai, India and New Jersey, USA. The four strains were phylogenetically distinct and belonged to different phyla in the bacterial domain including Deltaproteobacteria, Deferribacteres, Chrysiogenetes, and Gammaproteobacteria. Strain KM that was classified as Deltaproteobacteria  and strain s5 that belonged to Chrysiogenetes carried out complete reduction of selenate to selenium. However, both strains could not reduce selenite independently indicating the pre-requisite of selenate reduction. Although, NO3- could also be used as a terminal electron acceptors, it was not required for the reduction of selenite to elemental selenium (Narasingarao & Häggblom, 2007). Strains AK4OH1 and Ke4OH1 were isolated from Arthur Kill (New York, USA) and Kesterson Reservoir (California, USA) that had the surprising ability to couple growth of aromatic compounds to selenate reduction. The phylogenetic analysis classified these strains as gamma subgroups of Proteobacteria (Knight, Nijenhuis, Kerkhof, & Häggblom, 2002). Narasingarao & Häggblom(2006) further characterized the strain AK4OH1 and identified the capability to couple oxidation of aromatic compound benzoate, 4-hydroxybenzoate and 3-hydroxybenzoate to selenate reduction in anaerobic respiration. The strain also reduced nitrate via the denitrification pathway. Furthermore, it was classified into a new genus with the following name: Sedimenticola selenatireducens (Narasingarao & Häggblom, 2006). 21  Gram-positive bacteria have also been isolated from selenium-impacted environments, although most selenate reducers are gram-negative. Bacillus sp. strain SF-1 is a gram-positive facultative anaerobe that was isolated from selenium-polluted sediment. It grew with lactate as an electron donor and selenate as an electron acceptor along with the presence of yeast extract. The strain can completely reduce up to 1 mM selenate into elemental selenium while removal of up to 20 mM selenate into selenite was also observed. The strain was inhibited by nitrate and optimally grew at pH 8.0 and 30oC temperature (Fujita, Ike, Nishimoto, Takahashi, & Kashiwa, 1997).  Blum et al. (1998) isolated two strains of gram positive bacteria: Bacillus arsenicoselenatis strain E-1H and Bacillus selenitireducens strain MLS-10 from an alkaline and hypersaline Mono Lake (California). Strain E1H is a spore forming rod that grows by coupling oxidation of lactate to concomitant reduction of Se(VI) to Se(IV). Strain MLS10 is a non-spore forming rod that utilized lactate as a carbon source and reduced Se(IV) to Se0. These strains were both alkaliphiles having strong tolerance to both high pH and salinity and their co-culture completely reduced Se(VI) to Se0 (Switzer Blum, Burns Bindi, Buzzelli, Stolz, & Oremland, 1998). Moreover, Bacillus selenitireducens strain MLS-10 is the only known microbe that is capable of tolerating very high concentrations of Se(IV) (up to 10mM) and reducing all of it to Se0 (Switzer Blum et al., 1998). Enterobacter taylorae is a gram-negative bacteria isolated from rice straw that had the ability to reduce high concentrations of Se(VI) in a synthetic highly saline agricultural drainage water. The bacteria converted Se(VI) into Se0 and then further reduced it to Se(-II).  Moreover, a small percentage of Se(-II) was also volatilized by the bacteria (Zahir et al., 2003). Ferrimonas futtsuensis and Ferrimonas kyonanensis are two novel mesophilic facultative anaerobic selenate-respiring bacteria isolated from sediment and the alimentary tract of littleneck clam taken from Tokyo Bay in Japan. These strains have a metabolic versatility to reduce many electron acceptors including Se(VI) and are flexible in their use of carbon sources (Nakagawa, Iino, Suzuki, & Harayama, 2006). 2.6.3 Non-dissimilatory Selenium reduction Two members from the photosynthetic non-sulphur Proteobacteria: Rhodobacter sphaeroides and Rhodospirillum rubrum have been isolated that show high resistance to 22  transition metal oxyanions including  selenate through the regulation of redox equivalent (J Kessi, Ramuz, Wehrli, & Spycher, 1999; Moore & Kaplan, 1992). Moore and Kaplan (1992) identified a membrane bound FADH2 that resulted in high resistance to Se oxyanions.  Many microorganisms reduce selenium oxyanions as a part of their detoxification processes under aerobic conditions. Pseudomonas stutzeri reduced both oxyanions of selenium and is tolerant to high selenium concentration. The reduction occurred only during aeration and a pH between 7-9 at temperatures between 25-30oC were optimal for the reduction of selenium oxyanions (Lortie, Gould, Rajan, McCready, & Cheng, 1992b).  Stenotrophomonas maltophilia was isolated by Dungan and co-worker (2003) from a seleniferous agricultural evaporation pond sediment in Tulare Lake, California. This bacteria reduced 81.2 and 99.8% of the added Se(VI) and Se(IV), respectively, into Se0 after 48 h during aerobic growth, but was unable to use these oxyanions as electron acceptors under anaerobic conditions. Furthermore, experiments revealed that volatile dimethyl selenide (DMSe) was produced, which contributes to biogeochemical cycling of selenium in seleniferous environments (Robert S. Dungan, Yates, & Frankenberger, 2003). Tomei et al. (1992) reported that Wolinella succinogenes, although inhibited by Se(VI) and Se(IV), can be adapted to acquire resistance to 1 mM Se(IV) and 10 mM Se (VI). The resistant cultures were able to reduce both selenium oxyanions into amorphous elemental selenium that was deposited inside the cytoplasm. The mechanism of this culture was detoxification as it could not support growth on any of the oxyanions (TOMEI, BARTON, LEMANSKI, & Zocco, 1992). Similarly, Desulfovibrio desulfuricans is another SO4- reducing bacteria that was adapted to grow in the presence of high selenium oxyanions: Se(VI) and Se(IV) (F.A. Tomei et al., 1995). Selenium oxyanion reduction carried out by specific selenate reductases (ser) was investigated well in Thauera selenatis, Enterobacter cloacae SLD1a-1, and Bacillus selenatarsenatis SF-1 (Kuroda et al., 2011; Ridley, Watts, Richardson, & Butler, 2006; Schröder, Rech, Krafft, & Macy, 1997). However, non-specific reduction is also known to occur in sulfate-reducing bacteria (Lenz, Hullebusch, Hommes, Corvini, & Lens, 2008), and nitrate reducing bacteria (Rege et al., 1999), perhaps because the reductase of these microbes offer multiple specificity for different electron acceptors. Thus, selenate reductase activity is reported in the 23  membrane bound (NAR) and periplasmic (NAP) nitrate reductases of Rhodobacter sphaeroides, Paracoccus denitrificans and Paracoccus pantotrophus (Sabaty et al., 2001). However, the nitrate reductase in these organisms shows low selenate reducing activity consolidating the fact that a specific selenate reductase must be responsible for significant global selenium transformation (Sabaty et al., 2001). 2.6.4 Se(IV) reduction Selenite (Se(IV)) is more toxic than selenate (Se(VI)) and thus very few microorganisms have been isolated that can tolerate high concentrations of Se(IV). Detoxification is a strategy employed by some microorganisms to tolerate the toxicity of Se(IV). Some selenate reducing organisms can also reduce selenite. Resistance to high concentrations of selenite was observed in case of Bacillus selenitireducens strain MLS-10 (10 mM) (Switzer Blum et al., 1998) and Tetrathiobacter kashmirensis (64mM) (Hunter & Manter, 2008). However other microbes including Bacillus subtilis (C Garbisu et al., 1999), Ralstonia metallidurans (Roux, Sarret, Pignot-Paintrand, Fontecave, & Coves, 2001),  Rhodobacter spheroides (Van Fleet-Stalder, Chasteen, Pickering, George, & Prince, 2000), and Rhodospirillum rubrum (J Kessi et al., 1999) are inhibited by high concentration of selenite. In Rhodospirillum rubrum and Rhodobacter capsulatus, a distinct enzyme system (different from sulfite and nitrite reductase) operates to reduce selenite, and glutathione was found to be involved in the transformation of selenite to volatile selenium compounds (Janine Kessi, 2006). He and Yao (2010) used a versatile strain of Anaeromyxobacter dehalogens that are known for their potential in the bioremediation of heavy metals and radionuclides via anaerobic respiration to convert toxic Se(IV) into Se0. Se(IV) reducing capacity was hindered at high concentrations of Se(IV) (above 900 µM) in the medium (He & Yao, 2010).  Dhanjal and Cameotra (2010) isolated Bacillus cereus from a coalmine soil that biosynthesized selenium nanospheres through Se(IV) reduction. The strain had the ability to tolerate high concentration of sodium selenite (up to 10 mM) and the Se0 nanosphere was found to be present both inside and outside the cell. A hypothetical membrane-based selenite reductase was proposed to be involved in reduction of selenite that received electrons from NADPH/NADH electron carriers. Although the exact mechanism has yet to be elucidated, 24  intermediates react to produce volatile methylated and elemental selenium products which are expelled from the cell (Dhanjal & Cameotra, 2010). Several Se(VI) and Se(IV) reducing bacteria were isolated from a coalmine tailing pond sediment by Siddique and co-workers (2007). One Se(VI) reducing bacterium Enterobacter hormaechei and four Se(IV) reducing bacteria, Klebsiella pneumoniae, Pseudomonas fluorescens, Stenotrophomonas maltophilia, and Enterobacter amnigenus were reported to be isolated from the sediment (Siddique, Arocena, Thring, & Zhang, 2007). A similar experiment was also performed by Ghosh et al. (2007) where several bacterial strains belonging to  -Proteobacteria and Bacilli were isolated from the selenium contaminated sites in India(Ghosh, Mohod, Paknikar, & Jain, 2008). 2.7 Mechanisms of Selenium Oxyanion reduction 2.7.1 Selenium transport/uptake The precise mechanism in the uptake of selenium oxyanions is still unclear. A specific uptake system is expected, as selenium is an essential element for all microorganisms. Se(VI) is imported into E.coli through the sulphate permease system (cysA,cysU,cysW) and mutation of any of these genes results in  selenate resistance (Turner, Weiner, & Taylor, 1998). Selenite (Se(IV)) can also pass through the same transporter system. However, an alternative yet undefined carrier exists in addition to the sulphate permease system as repression of this system does not completely block Se(IV) import into the cell (Turner et al., 1998).  25   Figure 3. Schematic representation of different pathways involved in selenium transformation in microorganisms.  2.7.2 Dissimilatory reduction and selenate reductase  In T. selenatis, the mechanism of Se(VI) reduction by selenate reductase (ser) (Accession number AJ00774) has been elucidated (T Krafft et al., 2000). The selenate reductase (ser) that catalyzes Se(VI) reduction to Se(IV) is located in the periplasmic space and it is encoded by an operon serABC. The operon consists of four genes: serA encodes for a 96 KDa catalytic subunit which contains a molyybdenum cofactor (Mo(V)); serB encodes for a 40 KDa iron-sulfur protein (one [3Fe-4S] cluster and three [4Fe-4S] clusters); serC encodes for a 23 KDa heme b protein and  serD encodes for a system specific chaperone (T Krafft et al., 2000; Schröder et al., 1997). Lowe et al. (2010) has found that a 24-KDa protein (cytc-Ts4) donated electrons to the serABC in vitro and this protein was assigned as a member of cytrochrome c4 family through sequence similarity and mass spectrometry analysis. Furthermore, quinol-cytochrome c oxidoreductase 26  (QCR) was proposed to transfer electron to the periplasmic cytochrome c4. Additional experiments involving inhibition of quinol-cytochrome c oxidoreductase (QCR) with addition of  myxothiazol and antimycin revealed an alternate pathway for electron transfer as only partial inhibition of QCR was achieved (Lowe et al., 2010). This alternate pathway has been suggested to be through the quinol dehydrogenase (QDH) as complete inhibition of Se(VI) reduction was achieved only when both myxothiazol and HQNO (2-n-heptyl-4-hydroxyquinoline N-oxide) were used together (Lowe et al., 2010). The selenate reductase (serABC) in T. selenatis can only reduce Se(VI) to Se(IV) and further reduction of Se(IV) is accompanied by either the periplasmic nitrite reductase ((DeMoll-Decker & Macy, 1993) or through reactions with thiols  in the cytoplasm after Se(IV) enters the cell through either the sulphate transport pathway or through a unknown system. Elemental selenium is secreted as a nanosphere of roughly 150 nm diameter through an unknown mechanism but it is found to be stabilized by a protein sefA (Debieux et al., 2011).  Figure 4. Illustration of electron transport pathways in Thauera selenatis. Figure adapted from (Debieux et al., 2011; Lowe et al., 2010; Nancharaiah & Lens, 2015)  27  Losi and Frankenberger (1997) reported that the selenate reductase of Enterobacter cloacae SLD1a-1 is a membrane bound complex that rapidly expels the nanospere Se0 outside the cell once it is formed. The selenium nanospheres were <0.1 µm and were found in the extracellular medium (Mark E. Losi & Frankenberger Jr., 1997). Further characterization of the E. cloacae selenate-reductase enzyme has not been performed and the exact mechanism of the electron transfer is yet to be revealed. Kuroda and co-worker (2011) isolated a srdBCA operon from a Gram-positive bacterium Bacillus selenatarsenatis SF-1. The operon encoded genes necessary for Se(VI) reduction in the bacterium and also conferred selenate reduction when cloned in E. coli DH5α. SrdA is the molybdenum containing catalytic subunit that differed from the serA subunit of T. selenatis (type I molybdoenzyme in srdA vs type II in serA). SrdB is a iron-cluster protein that participates in the electron transfer between quinone and the catalytic subunit through a membrane anchor, SrdC (Kuroda et al., 2011). 2.7.3 Selenite reduction  Selenite reduction potentially takes place through periplasmic nitrite reductase as seen in T. selenatis (DeMoll-Decker & Macy, 1993) or through other reductases in the periplasm (such as sulfite reductase). In the cytoplasm, selenite can be reduced through the reaction with thiols. Selenite reacts with GSH to form selenodiglutathione (GS-Se-SG), which is further reduced by the enzyme glutathione reductase to form glutathione selenopersulfide (GS-Se-). A terminal reaction with a proton (H+) leads to the formation of elemental selenium (Se0) and regeneration of glutathione (Zannoni et al., 2007). 2.7.4 Assimilation  Both selenate and selenite are reduced in an assimilatory process into Se-2 and then incorporated as Se-cys(selenocysteine) or Se-met(selenomethionine) amino acid into a growing polypeptide. The Se-cys is incorporated co-translationally as described previously while Se-met is incorporated analogously to methionine (Böck, Forchhammer, Heider, & Baron, 1991; Stadtman, 1996). Only trace concentrations of selenium are required by microorganisms to synthesize important redox enzymes. Excess amounts of selenium in the environment would lead 28  to Se incorporation into mainly Se-met, which can lead to unstable proteins and pose a burden for the cell. 2.7.5 Methylation  The formation of methylated selenium compounds including DMSe and DMDSe through bacterial process is known to occur in sediment, soil and water and is thought to be a protective mechanism to detoxify their environment (R. S. Dungan & Frankenberger, 1999). Although the methylation of inorganic selenium involves reduction and methylation, the exact procedure is still debatable (Doran, 1982; R. S. Dungan & Frankenberger, 1999). A number of organisms from both bacteria and fungi have been isolated that perform methylation of selenium in both sediment and water (R. S. Dungan & Frankenberger, 1999). Recently, Debieux and co-workers (2011) reported the presence of sefB (SAM dependent methyltransferase) downstream of the sefA gene that potentially was involved in the methylation of selenium compound (Debieux et al., 2011). 2.7.6 Formation of metal selenides  Different processes could operate inside  microorganisms that lead to Se(VI) reduction to Se(-II) (selenide) inside the cell. The Se(-II) formed through microbial reduction can combine with metal cations outside the cell to form metal selenides. Recently, Fellowes and co-worker (2013) reported on the formation of CdSe and ZnSe quantum dots that were derived using bacterially reduced Se(-II). The quantum dots possess unique semiconducting properties that could be exploited in solar cells as well as in fluorescent labelling to screen cancer cells. The biologically produced quantum dots were more stable than the inorganic counterparts and could be exploited for further economic purposes from selenium contaminated waste streams (Fellowes et al., 2013).  2.8 Treatment technologies available for removing Se from mining water  Various treatment technologies have been developed for the removal of selenium from mine influenced water. Table 5 lists various physical, chemical and biological treatment systems available for the treatment of selenium-impacted water.  29   Table 5. Treatment technologies for selenium removal  Technology Techniques employed Advantages Disadvantages Costs $ References Physical Reverse Osmosis Membrane based separation process with high pressure  Demonstrated at full scale  high quality water in effluent  Concentrated Se that can be treated separately  high capital & operational cost  Pre-treatment, fouling, as well as pH, temp, & pressure regulation  disposal of brine 0.0027 per gallona (Frankenberger et al., 2004; NSMP, 2007)  Nano-filtration Membrane based filtration similar to RO but operated at one-third pressure relative to RO   Pressure requirement lower that reduces operational cost  Se reduced to 1 ppb and Nitrogen to 90 mg/L  high cost   pre-treatment required similar to RO  effluent quality not as high as RO  need to frequently monitor membrane 0.03 per gallona (Frankenberger et al., 2004; Kharaka, Ambats, Thordsen, & Davis, 1997; NSMP, 2007)  Ion Exchange Adsorption of contaminants in the resin  Nitrogen removal efficient   moderate space requirement  Se removal to 50 ppb  Competition with sulfate  Costs high as well 0.00024 per gallon (Golder, 2009; NSMP, 2007)  Evaporation Pond Concentration of salts through natural evaporation of water  use of solar energy saves energy costs  simple technology to implement in hot climate areas  large space requirement  potential exposure to wildlife  possible infiltration of contaminants into groundwater 0.019 per gallon (Golder, 2009; NSMP, 2007; Sandy & DiSante, 2010) Chemical Reduction with zero-valent Iron Reduction of soluble selenium species and adsorption in iron  proven technology  effectively reduces both selenate and selenite through green rust and ferrous iron  high use of iron  waste disposal is a concern  temp and pH dependent  not efficient consistently NA (Golder, 2009; Zhang, Wang, Amrhein, & Frankenberger, 2005)  Reduction with Ferrihydrite Adsorption of Se in ferrihydrite precipitate formed by addition of ferric salt in water  widely used and implemented  USEPA best demonstrate available technology for Se removal  sludge disposal  pH dependent (4-6)  high reagent needed and adsorption only effective for selenite 0.01571a per gallon for reagents only (NSMP, 2007; USEPA.United States Environmental Protection Agency, 2001) 30   Technology Techniques employed Advantages Disadvantages Costs $ References Biological Algal -Bacterial Removal Denitrification and reduction  Low cost   can be used in-situ  can also result in selenium volatilization  bioavailable form of selenium   excessive nutrient required and most spent in denitrification resulting in inefficient Se reduction 0.0008 per gallon (Frankenberger et al., 2004; NSMP, 2007; Sandy & DiSante, 2010)  Constructed wetland Use of plant, soil, rocks etc to promote the natural selenium transformation and immobilization  selnium reduction to low levels  minimal supervision  able to treat large volume of water  potential exposure to wildlife  potential for groundwater infiltration 0.01 per gallon (NSMP, 2007; Sandy & DiSante, 2010)  UASB Reactor Granular sludge suspended by the velocity of incoming wastewater. The effluent liquid and gas pass through the upper exit.  no attached growth media required   no pre-treatment required  can handle inorganic precipitation  long HRT results in big reactor sizes  high nitrate will require additional carbon source 0.00136-0.0016b per gallon (Frankenberger et al., 2004; Lenz, Enright, O’Flaherty, Van Aelst, & Lens, 2009; Sandy & DiSante, 2010)  ABMet Attached growth of microbes in granular activated carbon that reduces selnium oxyanions  commercially available and demonstrated in large scale  naturally occurring microbes and molasses as nutrient  backwash required for elemental selenium removal  large footprint 0.00132c per gallon operation cost only (Sandy & DiSante, 2010; USEPA.United States Environmental Protection Agency, 2001) a Cost predicted by NSMP for selenium and nitrate removal (NSMP, 2007) b Cost for treatment of 4000 m3 water per day in UASBR (Frankenberger et al., 2004) c Cost of pilot scale ABMet with flow rate of 1 US gpm (USEPA.United States Environmental Protection Agency, 2001)   2.8.1 Physical treatment 2.8.1.1 Reverse osmosis and Nanofiltration Both reverse osmosis (RO) and nanofiltration (NF) are membrane-based technologies that employ semi-permeable membranes for treating a wide range of contaminants. However, in 31  NF, size of the membrane pore is bigger than RO. The bigger pore size allows small sized ions to pass through the membrane limiting its applicability in the treatment of selenium (Sandy & DiSante, 2010). NF may also allow single charged nitrate ion to pass through the membrane and has been considered unsuitable for treatment of high nitrate containing waste stream (NSMP, 2007). NF has been shown to selectively reject up to 98% SO4 from hypersaline solution and this result has been extrapolated to estimate similar removal efficiency with selenate (Kharaka et al., 1997). RO can be effective for removing dissolved solids such as selenium, nitrate, sulphate as well as ions such as sodium and calcium from the treatment water (Frankenberger et al., 2004; NSMP, 2007; Sandy & DiSante, 2010). For example, RO has been used at the Barrick Richmond Hill Mine to treat water containing selenium. Influent water with Se concentration at 100 ppb was reduced by iron precipitation and RO to 2 ppb (Sobolewski, 2005).  Nanofiltration is advantageous as it is less expensive than RO since lower pressures are required for its operation. Unlike RO, there are no mines currently using this technology to treat  selenium impacted water (Sobolewski, 2005). However, laboratory scale NF system fed with agricultural drainage water containing up to 1000 µg Se/L demonstrated  greater than 95% selenium removal (Kharaka, Ambats, Presser, & Davis, 1996).  2.8.1.2 Ion Exchange Ion exchange (IX) uses different synthetic resins or naturally occurring materials like zeolite and activated alumina to reversibly exchange undesirable contaminant ions with a more desirable ones (Frankenberger et al., 2004).  Nishimura and Hashimoto (2007) used a polyamine-type weakly basic ion exchange resin to remove  both selenate and selenite over a wide range of pH (Nishimura, Hashimoto, & Nakayama, 2007). However, selenium adsorption was inhibited by sulphate. A Vancouver-based company, BioteQ, developed a novel ion exchange based technology called Selen-IXTM that uses strong base anion exchange resin (Mohammandi, Littlejohn, West, & Hall, 2014) that reportedly removed greater than 95% selenium. Their pilot plant (undisclosed location) treated influent water at 456 µg Se/L to the target level of single-digit  µg Se /L. They claim that their Selen-32  IXTM technology is cheaper than some of the incumbent technologies both in terms of the capital and operational cost.  2.8.2 Chemical treatment 2.8.2.1 Reduction with Zero-valent Iron Zero valent iron (ZVI) can be used in the treatment of selenium impacted mine water. ZVI reduces selenate into selenite, which are adsorbed (Sandy & DiSante, 2010). ZVI is an inexpensive and moderately strong reducing agent (Zhang & Frankenberger, 2006). ZVI has been used in the removal of many different types of heavy metals from water (NSMP, 2007). In the process, ZVI oxidizes to ferrous and ferric iron while selenate reduces to selenite in a redox reaction. Selenite reacts with ferric ion and adsorbs as ferrihydrite (Fe(OH)3. Se) or reduces completely to elemental selenium on the surface of the ZVI (Golder, 2009; Sandy & DiSante, 2010).  Zhang and co-worker (2005) demonstrated removal of 1,000 µg/L Se in a laboratory experiment with ZVI in the presence of various other ions including Cl-, SO4-2, NO3-, HCO3-, and PO4-3. It was reported that chloride and nitrate did not affect the removal efficiency. However, sulphate, bicarbonate and phosphate affected removal of selenate from water (Zhang et al., 2005). Another study perfomed by Zhang and Frankenberger (2006) suggested that the addition of ZVI along with biological reduction with Citrobacter braakii in highly saline drainage water significantly enhanced the removal of selenate by reducing it to organic Se (Zhang & Frankenberger, 2006).  2.8.3 Biological treatment Due to the expense of the previously described physio-chemical processes for selenium removal from mine influenced water, biological treatment is more attractive. This is because of the wide variety of microorganisms capable of selenate and selenite reduction, as were described earlier in this Chapter. 33  2.8.3.1 Wetlands and Passive Biochemical Reactors Constructed wetlands are engineered structures that mimic natural wetlands to perform biofiltration and bioremediation to remove contaminants from water (NSMP, 2007). They are relatively cheap and use naturally occurring vegetation, soil and microbial communities to remove nutrients and metals (Sandy & DiSante, 2010). A full-scale constructed wetland at San Joaquin Marsh operated by Irvine Ranch Water District consisting of five treatment cells (45 acres of open water and 11 acres of vegetated wetland) removed selenium and nitrate from 3,100 US gpm (11,900 Lpm) of San Diego Creek water (Sandy & DiSante, 2010).  Laboratory bioreactors with complex organic materials (wood, hay and manure), reduced sulphate and selenium from 600 mg/L and 15 µg/L to less than 100 mg/L and 5 µg/L, respectively. Based on these experiments, a passive biochemical reactor (subsurface flow) was constructed at Mount Polley Mine, BC, Canada to remove selenium and sulphate from their tailings pond water. Although sulphate was not completely removed, effluent selenium concentrations were below the detection limit (Baldwin, Mirjafari, Rezahdebashi, Subedi, & Taylor, 2015).  The kinetics of Se reduction in passive treatment systems is often slow. Moreover, effluent concentrations can often vary and fluctuate during operation. Although most passive reactors can reduce selenium to below discharge requirements (as seen for the cases above), there is a tendency to regard BCRs as black-boxes. A wide variety of microbial types thrive within passive systems, which makes troubleshooting difficult. Because of the lack of technological and scientific knowhow, small problems leading to decrease in system performance are often regarded as a complete system failure. 2.8.3.2 Active Bioreactors Active microbial treatment systems exploit the capability of selenate and selenite reducing bacteria mentioned earlier in this Chapter to treat selenium-containing mine wastewater under highly contained and controlled conditions using tanks, pumps, instrumentation etc. Due to the high degree of containment and control, these systems have shorter retention times and can treat larger flow rates than passive BCRs. Active systems require the continuous addition of a carbon source, which may be in the form of molasses, methanol, acetate, lactate, etc. and other 34  nutrients, whereas in passive BCRs these are supplied through biodegradation of natural organic matter (Golder, 2009). Reagent requirements constitute a large portion of the operating costs of active bioreactors. Different bioreactor configurations have been developed for selenium removal under active microbial treatment based on factors including flow rate, selenium concentration, and matrix of the treatment system (Golder, 2009). These reactors include Biofilm Selenium Reactor (BSeR), Upflow Anaerobic Sludge Bed (UASB) reactors, and Advanced Biological Metals Removal Process (ABMet®) (Nancharaiah & Lens, 2015).  2.8.3.2.1 Upflow Anaerobic Sludge Bed (UASB) Bioreactors  UASB reactors operate anaerobically with suspended granulated sludge particles. Microbial selenium reduction occurs within the sludge particles, which are suspended due to the velocity of the incoming wastewater from the bottom of the reactor. The effluent is collected from the top and goes through additional post-treatment to recover elemental selenium (Golder, 2009). The treatment has been used in pilot scale to treat agricultural drainage water containing selenium for three years during the early 90's (Owens, 1998). Influent selenium at concentrations of 500 µg/L was reduced effectively between 58% to 90% by feeding methanol at 250 mg/L as a carbon source. UASBR has also been used in a pilot scale to remove selenate from synthetic wastewater under methanogenic, sulfate-reducing (Lenz et al., 2008) and denitrifying conditions (Lenz et al., 2009).  2.8.3.2.2 BseR/ABMet technology  BseR technology was developed by General Electric that uses selenium-reducing bacterial biofilm developed on granular activated carbon (GAC). It is now referred to as ABMet process and uses special proprietary microorganisms along with molasses as carbon source (Golder, 2009). ABMet process has been used on a pilot scale by USEPA to reduce water containing influent selenium at 1950 µg/L to below 2 µg/L with only 5.5 hours of empty bed hydraulic retention time (USEPA.United States Environmental Protection Agency, 2001). The ABMet process has been used in two power plants to treat selenium at flue gas desulfurization (FGD) wastewater at Duke Energy and Process Energy in North Carolina (Sonstegard, Pickett, Harwood, & Johnson, 2008).  35   2.8.3.2.3 Bioreactors with specific selenate- or selenite-reducing microbes  Thauera selenatis has been used in a pilot-scale packed bed reactor consisting of hollow plastic spheres and silica sand to treat agricultural drainage water in California (Cantafio et al., 1996). This reactor reduced selenium present in the influent drainage water to concentration of 237 µg/L. Post-treatment with coagulation was performed to further reduced effluent selenium concentrations to 12 µg/L. Bacillus sp. SF-1 has been used primarily at the laboratory scale to treat extremely concentrated (41.8 mg/L) selenium containing synthetic wastewater. Organic carbon was provided in the form of lactate and higher retention time resulted in 99% selenate reduction while shorter retention led to accumulation of selenite (Fujita, Ike, Kashiwa, Hashimoto, & Soda, 2002). Sulfospirillum barnesii has mostly been used in laboratory studies with only one pilot scale system established by Lenz and Co-worker (2009) where immobilized S. barnesii was used in a UASB reactor to simultaneously treat selenium and nitrate (Lenz et al., 2009). Selenate was reduced by 97% even in conditions where nitrate and sulphate were fed in a high molar excess.  Currently, most bioreactors use mesophilic microorganisms (whose optimal growth occurs around 30o C) as inoculum for treatment of selenium in wastewater. This can be a challenge when the water temperature is below 15oC such as in winter and in colder climates. There is some suggestion that microorganisms in native soils are adapted to local climatic variations and environmental conditions can be adapted easily as inoculum for treatment of selenium in active bioreactors. Such efforts have been fruitful for the treatment of selenium in very cold regions of Alberta, Canada. For example, native sediment used in a bioreactor to treat non-acidic coal mine effluent (Se concentrations of 85 µg/L) successfully removed >95% selenium  even at temperatures below 15oC (Luek, Brock, Rowan, & Rasmussen, 2014).  2.9  Summary, motivation and hypotheses Treatment of selenium in mining wastewater is challenging due to the need to meet low discharge concentrations with minimal cost from huge volumetric flow rates. Despite the 36  multiple physical, chemical and biological treatment systems available,  costs are still prohibitive. Biological treatment has been deemed the most cost-effective method for abatement of selenium pollution from high flow rates that can also work under cold temperatures.  However, the presence of nitrate inhibits biological selenium reduction. One reason is, since nitrate is more readily available in the environment, there are more microbes capable of denitrification. Also, nitrate reduction is more energetically favorable compared with selenate or selenite as electron acceptor. Reduction of both nitrate and selenate/selenite simultaneously can only occur when enough electron donor is present for both processes or when microbes that specifically respire on selenate or selenite are present. Some of the Se-reducing microbes that have been isolated do selectively reduce selenate or selenite without inhibition from the presence of nitrate. Although many studies have been performed with isolated microbial species, very few have evaluated the selenate/selenite reduction by mixed microbial cultures, which are more likely to be present in practical bioreactors. Thus, in the present research, mixed microbial cultures enriched for selenate/selenite reducing bacteria were used to study the affect of nitrate on selenium reduction. Furthermore selenate-reducing enrichment cultures grown in the presence of nitrate were compared with native wetland sediment to see how the presence of nitrate affected selenate/selenite reduction.  2.10 Hypothesis and motivation for the work The motivation for this work was to test the ability of native selenate reducing microorganisms from mine affected water environments to reduce selenate in the presence of nitrate. The hypothesis was that selenate-respiring bacteria would be present on mines sites because dissolved selenium concentrations are higher there than in natural environments, and these local microbes would be more adept at removing total dissolved Se from mine water. The specific hypotheses are:   Se-reducing microbes are abundant in mining environments impacted by mine water containing both dissolved selenium and nitrate.  37   Enrichments can be obtained that can reduce selenium oxyanions selectively without inhibition from nitrate.   These enrichments can sustain their selenate-reducing capabilities despite the presence of nitrate.               38  Chapter 3: Materials and method 3.1 Background of the sites from where the samples were collected 3.1.1 Site background  Figure 5. Five major coal mines operated by Teck in Elk Valley (Teck, 2014)  The Elk Valley is situated in southeastern British Columbia and constitutes the Elk River that runs along the entire length of the region and into the United States. It is one of the major coal-producing regions of Canada. Teck Coal operates five open-pit coalmines in this region: Coal Mountain (CMO), Elkview (EVO), Line Creek (LCO), Greenhills (GHO), and Fording River (FRO) and produced 26.7 million metric tons of coal in 2014 ((Teck Coal, 2009; Teck, 2014)). The coal deposits come from the Mist Mountain Formation of the Jurassic Creataceous Kootenay group that was deposited between 150 to 130 million years ago. Coal mining produces 39  large volume of waste rock that is dumped into the mountain slopes and typically constitutes the overburden, interburden mudstone and siltstone as well as the low quality coal seams (Lussier et al., 2003). It is estimated that 140 million metric tons of waste rock is generated annually. Se, present in the waste rock associated with minerals such as pyrite and sphalerite, is oxidized and released into the nearby surface water and groundwater (Hendry et al., 2015). Recently, Se  concentrations in the waste rock was found to be an average of 3.12 mg/kg (mean digestible concentration) and there has been continuous increase in Se concentration in the Elk river since 1980's , sometimes exceeding the provincial guidelines of 2.0 µg/L (Dessouki & Ryan, 2010; Hendry et al., 2015). Mount Polley Mining Corporation, located in the central British Columbia, operates a copper and gold mine under Imperial Metals. It is an open pit mine that extracts copper from ores that were formed nearly 180 million years ago. The tailings, which are the leftover solids from processing plus wastewater, are stored in a large pond. The tailings water is still high in concentrations of different chemical species and has to be treated before being considered for discharge. The To this end, Mount Polley mine started a pilot-scale biological treatment facility to passively treat some of the chemicals including selenium, nitrate, and sulfate (Baldwin et al., 2015). Results have shown that the treatment facility is able to reduce these constituents and thus was a good site to collect sample for the enrichment of Se-reducing microorganisms. 3.1.2 Coalmine drainage impacted sediment samples from Elk River Valley  The original sediment samples used for enrichment culturing were collected from three different sites on a coalmine in the Elk River valley of southeastern British Columbia. One of the samples, designated Goddard Marsh (GM), was collected from a natural marsh impacted by coalmine waste rock seepage on the Elkview Coal Mine, while the other samples designated as Mature Tailing Coal (MTC) and Fresh Tailing Coal (FTC) were collected from a tailings pond near the Fording River Mine. FTC comprised relatively new waste, while MTC comprised of aged waste stored over a considerable time. These natural and man-made sediments obtained were impacted by seepage containing selenium, nitrate and sulphate and were sent by Dr. Alison Morrison (Environmental Scientist at Teck Coal) on 7th August 2013.  40  3.1.3 Sediment samples from pilot-scale passive treatment plant, Mount Polley Samples were also collected from a pilot-scale biological treatment plant at Imperial Metals’ Mount Polley Mine that received water from tailings pond for treatment of sulfate, nitrate and selenium. Sediment samples were collected from different corners of the treatment pond and are referred to as "Mount Polley" samples. Sediment samples along with the overlying water were collected in plastic containers filled to the brim to prevent any exposure to air and tightly sealed. Once collected, all sediment samples were kept in coolers and shipped to University of British Columbia. These samples were opened in an anaerobic box glove to prevent any exposure to oxygen. Once inside the anaerobic box glove, a portion of each sample was frozen at -80oC for subsequent DNA extraction and future use. 3.2 Experiments performed 3.2.1 Experiment 1: Initial tests to determine the potential for selenate-reduction in different environmental sediment samples  The purpose of this experiment was to qualitatively score the sediment samples obtained from various sites for selenate-reduction and then later use these samples for enrichment experiments. Sediment samples were inoculated directly into anaerobic enrichment medium in 70 ml glass bottles and incubated at 30oC. A qualitative screening test was performed by observing the appearance of red precipitation: an indication that selenate [Se(VI)] contained in the anaerobic enrichment medium was biologically reduced into insoluble elemental selenium [Se(0)]. The anaerobic enrichment medium used to enrich for selenate [Se(VI)] reducers was prepared according to Macy et al. 1989 (J. M. Macy et al., 1989). Minimal salt medium contained (g/L; pH 7.2): NaCl, 1.2;  KCl, 0.3; NH4Cl, 0.3; KH2PO4, 0.2; Na2SO4, 0.3; MgCl2.6H2O, 0.85; CaCl2.2H2O, 0.1. The following were added to the minimal salt medium (per litre of the MSM): 1 g NaHCO3, 1 g yeast extract. The medium was then autoclaved at 120oC for 20 min. The autoclaved medium was allowed to cool and the following were added:  1 ml of filter sterilized (0.45 micron filter) Trace Elements Solution SL-10  (FeCl2.4H2O, 1.5; CoCl2.6H2O, 0.19; MnCl2.4H2O, 0.1; ZnCl2, 0.07; Na2MoO4.2H2O, 0.036; NiCl2.6H2O,  0.024; 41  H3BO3, 0.006; CuCl2.2H2O, 0.002; HCl (25%)0.01 ml), 10 ml of filter sterilized (0.45 micron filter) vitamin solution (D-biotin, 0.02;  Folic acid, 0.02; Pyridoxine hydrochloride, 0.1; Thiamine hydrochloride, 0.05; Riboflavin, 0.05; Nicotinic acid, 0.05; DL- calcium pantothenate, 0.05; Vitamin B12, 0.001; p-aminobenzoic acid, 0.05; Lipoic acid(thiotic acid), 0.05).  Working stock solutions of sodium acetate (200mM), and sodium selenate (200 mM) were prepared separately by autoclaving at 120oC for 20 min. They were then added to the enrichment medium to the following final concentration: sodium acetate 20 mM, and sodium selenate 20 mM. The enrichment medium was then brought to a final volume of 1.0 liter following which the pH was adjusted to 7.2 by using either 1N HCl or 10N NaOH. The enrichment medium was then sparged with 100% N2 for at least 15 min. The medium also contained 0.03% ascorbate as a reducing agent. Following this, the enrichment medium along with the autoclaved serum bottles (70 ml) were taken to the anaerobic box glove and inoculated with 10%volume (~7 g) of the homogenized sediment samples. The serum bottles were filled to the brim with growth medium and capped with butyl rubber stoppers. They were taken out from the anaerobic glove box and sealed with aluminium crimp seals. The crimp sealed inoculated serum bottles were then incubated statically in the dark at 30oC. A bottle with autoclaved sediment and another bottle with growth medium but without sediment were used as negative controls to access the influence of any abiotic factors in selenate reduction.  3.2.2 Experiment 2: Enrichment of selenate-reducing bacteria from coalmine impacted sediments (primary enrichment) The purpose of this experiment was to develop a stable enrichment culture from Goddard Marsh (GM) and Mature Tailing Coal (MTC) sediments. Samples were chosen on the basis of the results obtained from the first experiment. As described in the previous section, the homogenized sediment samples were inoculated directly into anaerobic enrichment media. Once a stable enrichment culture (observer through fast color formation) was obtained, it was sequentially transferred into a fresh media every 10 days. A passage of 10 days was chosen to enrich for the most numerous bacteria during selenate-reduction growth that could subsequently be transferred to the next round. 42  3.2.3 Experiment 3: Removal of selenate in the presence of nitrate by primary enrichment culture obtained in experiment 2 The primary purpose of this experiment was to obtain a culture that had unhindered selenate-reduction activity in the presence of nitrate (NO3-). It was hypothesized that adapting a primary enrichment of selenate-reducing microbes to high concentration of nitrate would put a selection pressure on the microbial culture to perform anaerobic reduction (respiration) on both of the electron acceptors. The presence of high concentration of both of these constituents would thus establish consortium that reduced both selenate and nitrate concomitantly. Syntrophic communities of anaerobic bacteria and archea are found in nature that are known for interspecies electron transfer in methanogenic and sulphate-reducing environment (Stams & Plugge, 2009). Such syntrophy can also be hypothesized to occur in these enrichment cultures as selenite produced through reduction of selenate can easily be used by communities of nitrate-reducers. Stable enrichment culture in both GM and MTC, established in the experiment 2, were inoculated into fresh growth media with the following nitrate concentrations: 0 mM, 2 mM, 6 mM, and 8 mM. All the enrichments were performed in duplicate. Abiotic controls contained growth medium without any inocula from the primary enrichments. 3.2.4 Experiment 4: Selenate reduction over time for the most successful enrichment cultures and the organisms likely responsible for selenate-reduction The purpose of this experiment was to use three enrichment cultures obtained from experiment 3 to determine time-course kinetics of selenate-reduction and determine the organisms and mechanisms responsible for selenate reduction. In this regard, two cultures from GM: GM 0 mM NO3- (GM enrichment adapted to no nitrate) and GM 8 mM NO3- (GM enrichment adapted to very high nitrate) and one culture from MTC: MTC 4 mM NO3- were used to investigate the selenate-reduction over time. Q-PCR (Quantitative Polymerase Chain Reaction) was performed to quantify selenate-reduction and denitrification genes in cultures used in the time course. Metagenomic sequencing was performed by isolating genomic DNA from selected culture bottles:  43  3.2.4.1 Statistical design of experiment 4  (Central Composite Design) The central composite design (CCD) is an experimental design used with Response Surface Methodology (RSM) to optimize a system. It is a mathematical and statistical method used to determine the relationship between the independent variables (Se and NO3- concentrations) used in the experiment with the system response (extent of selenate-reduction or rate constants). By using the CCD, we can determine the statistical significance of the individual experimental factors as well as their interaction with each other (Demirel & Kayan, 2012; Draper & John, 1988; Dutka, Ditaranto, & Løvås, 2015).  The CCD allows us to build a quadratic polynomial regression model to the system response by using the minimum number of experimental runs. It consists of full/fractional factorial design, central points and axial points (α) which are at a distance α from the centre (Bezerra, Santelli, Oliveira, Villar, & Escaleira, 2008; Montgomery, 2001).  44   Figure 6. The figure describing the central composite design in two factor experiment with red highlighting the experimental run in CCD while the red+black represents the full factorial experiment needed to be performed for a two factor at five level experiment.  The full factorial design of a CCD consists of 2k treatments, where k is the number of factors/variables studied in the experiment (Montgomery, 2001). These factors are studied at two levels: +1 and -1 which represent the high and the low values, respectively, of the factors studied. The axial point is chosen at an equidistance of α from the centre in order to ensure rotatibility of the design (Montgomery, 2001). The axial point provides equal variation at all the points equidistant from the centre. This is critical in order to provide precise estimation of system response. The central point in the CCD is the average of the high and the low values of the factors.  Thus, all together there are five levels of each factor: - α,-1,0,+1, +α (Bezerra et al., 2008). 45  For the CCD experiment, the effects of two factors, selenate and nitrate concentrations, respectively, were to be determined. To carry out the full factorial experiment including interactions, a total of 25 different cultures would be required, each in triplicate. Since it would be impossible to sample all these cultures at the same time, the size of the experiment was reduced using a central composite design matrix (Barker, 1985; Montgomery, 2001). Using the central composite design (CCD), the number of treatment combinations was reduced to 9 with 5 replicates for the central combination making a total of 13 cultures. The number of treatment combinations in a CCD is given by the following equation(Barker, 1985):   Number of treatments = 2k-p +2*(k) + 1 Eqn. (5) where k = number of factors and p is the fractionalization element.  The number 1 accounts for the center point, which is usually replicated to estimate experimental error. Five replicates were chosen for the centre point. For this experiment, k = 2, p = 0 and the number of treatments equalled 13 (Eqn. 5). The percentage/extent of reduction (R) in soluble selenium concentration was used as the response metric (i.e. measured result):                      Eqn. (6)   where Sei = initial selenate concentration (mg/L) and Sef = final selenate concentration (mg/L).  Table 6. Experimental range and levels of the independent variables Run order Codes Treatment level (mg/L)  GM 0 mM GM 8 mM and MTC   Se NO3- SeO42--Se NO3--N SeO42--Se NO3--N 1 -1 -1 3.2 20 0.2 5 2 +1 -1 16 20 1.0 5 3 -1 +1 3.2 100 0.2 25 46  Run order Codes Treatment level (mg/L)  GM 0 mM GM 8 mM and MTC  4 +1 +1 16 100 1.0 25 5 -1.414 0 0.8 60 0.05 15 6 +1.414 0 19.2 60 1.2 15 7 0 -1.414 9.6 4 0.6 0.86 8 0 +1.414 9.6 120 0.6 29.14 9 0 0 9.6 60 0.6 15 10 0 0 9.6 60 0.6 15 11 0 0 9.6 60 0.6 15 12 0 0 9.6 60 0.6 15 13 0 0 9.6 60 0.6 15  3.2.5 Experiment 5: Comparison of the kinetics of selenium reduction by native sediments and the enrichments The purpose of this experiment was to compare the kinetics of the native sediments (GM and MTC) with that of cultures from the CCD experiment (experiment 4) that had highest extent of selenium reduction in experiment 4. In this regard, culture 8 from GM 0 mM NO3- (run order 8: Se- 9.6 and NO3--120 mg/L) and culture 8 from MTC 4 mM NO3- (run order 8: Se- 0.6 and NO3--29.14 mg/L) were chosen as inoculum for this experiment. Selenium reduction with different inoculums (sediments and cultures from CCD) were performed in triplicates in 70 ml sterile glass bottles with rubber stopper for 7 days. Each culture bottle contained 5 mg Se/L and varying concentration of nitrate: 0, 20, 60, 100 mg N/L. Samples were collected from the triplicate culture bottles on the following days: 0, 3, 5, 7 for measuring both Se and NO3- concentration. 3.3 Analytical procedures Thirteen samples each from the GM 0 mM NO3-, GM 8 mM NO3-, and MTC 4 mM NO3- enrichments were grown for 14 days in the CCD experiment (Experiment 4). Approximately 4-47  6 mL of  culture broth with suspended  solids was withdrawn from each of culture bottle on days: 0, 1, 2, 5, 8, 10 and 14. These samples were filtered through 0.22 µm filters to exclude biomass and any precipitates (including Se0). Of the filtrate, 1 ml was preserved for total dissolved selenium analysis by adding a drop of analytical grade nitric acid. The rest of the filtrate was used for nitrate/nitrite-N analysis with appropriate dilution. 3.3.1 Selenium analysis  Total soluble selenium concentration in the culture filtrate were analyzed using inductive coupled plasma optical emission spectroscopy (ICP-OES)- PerkinElmer Optima 7300, Civil Engineering Lab at the University of British Columbia. The detection limit for Se was 50 µgL-1 (50 ppb). 3.3.2  Nitrate/Nitrite-N analysis  Nitrate-N and nitrite-N were analyzed using a modified version of Standard Methods 4500-NO3- E. Cadmium Reduction Method. The color reagent was prepared by adding the following to 800 mL water (18.2 MΩ cm-1): 10 g sulfanilamide and 100 ml 85% phosphoric acid. This was followed by addition of 1 g N-(1-naphthyl)-ethylenediamine dihydrochloride and diluting the mixture to 1 L.  For nitrite-N analysis, 200 µl of the color reagent was added to 5 ml of diluted sample. After allowing 10 min for the reaction to occur and the final colour to stabilize, the optical density of the solution was measured at 543 nm on UV-VIS spectrophotometer GENESYSTM 10S. To measure nitrate-N, nitrate-N in the diluted sample was reduced to nitrite-N using elemental Zn (modified from the original protocol). Then nitrite-N concentration was measured as before. The amount of nitrate-N in the sample was determined by subtraction of nitrite-N from total nitrite and nitrate-N.  For experiment 5 (Comparison of selenium reduction in enrichment and native sediments), nitrate and nitrate was analyzed in the Environmental Engineering lab using automated sampler. The process was similar to the one described above. However, the nitrate reduction was performed by cadmium granules instead of zinc. 48  3.3.3 DNA extraction methods 3.3.3.1 Laboratory enrichments (experiments 4)  All the liquid suspension samples were frozen at either -20oC or -80oC prior to DNA extraction. DNA was extracted following a phenol-chloroform extraction procedure. Briefly, the samples were pelleted by centrifugation at 10,000 rpm. The pellets were then washed with TE buffer (10 mM Tris-HCL, 1 mM EDTA, pH adjusted to 8.0). The pellets were re-suspended in 0.5 ml TE buffer and lysozyme at a final concentration of 3 mg/ml was added.  The samples were then incubated in a water-bath maintained at 56oC for 1 hour. Then 75 µl of 10% SDS, 5 µl of Proteinase K at a final concentration of 20 mg/ml, and 5 µl of RNase A were added to the samples. The samples were incubated again in a water-bath at 56oC for 1 hour. The samples were briefly vortexed every 15 min to increase the efficiency of DNA extraction. Then, 400 µl of Tris (Tris (hydroxymethyl) aminomethane)-saturated phenol (pH 8.0) was added to the samples. The samples were centrifuged at 10,000 rpm for 10 min and 200 µl of tris saturated phenol as well as 200 µl of chloroform: isoamyl alcohol (24:1) was added to the supernatant. The samples were again centrifuged at 10,000 rpm for 10 min. The supernatant was taken and the previous step was repeated again. The supernatant was taken and 400 µl of chloroform: isoamyl alcohol (24:1) was added to it. These samples were centrifuged at 10,000 rpm for 10 min and the step was repeated again. The supernatant obtained from the previous step was then collected and 0.1 volume of 3M sodium acetate and 2 volumes of absolute ethanol (chilled at -20oC) were added to it. The samples were then mixed gently and incubated at -20oC for overnight DNA precipitation. Following overnight incubation at -20oC, the samples were centrifuged at 15,000 rpm at 0oC. The supernatant was decanted and the pellets were washed with 600 µl of 75% ethanol by centrifugation at 10,000 rpm for 15 min. The supernatant was decanted and the pellets were dried at room temperature. The pellets were then suspended in nanopure water and stored at -25oC for future use.  3.3.3.2 Environmental samples (GM and MTC sediments)  DNA was extracted from soil samples according to methods described earlier. However, as soil samples contain humic acid, the extraction buffer was prepared as described in Zhou et al. 1996 with some modifications (Zhou, Bruns, & Tiedje, 1996). Briefly, about 3-6 g of soil 49  samples were mixed with 1-2 ml of distilled H2O and pretreated with 0.5-1 ml of lysozyme (final concentration 50 mg/ml) at 25oC. The pretreated soil samples were then mixed with 13.5 ml of DNA extraction buffer (100 mM Tris-HCl pH 8.0, 100 mM sodium EDTA pH 8.0, 100 mM sodium phosphate pH 8.0, 1.5 M NaCl, 1% CTAB), and 100 µl of proteinase K (10mg/ml) by shaking horizontally at 225 rpm for 30 min at 37oC.  1.5 ml of 20% SDS was then added to these samples and they were incubated in a water bath at 65oC for about 2 hr with gentle end-over-end inversion every 15 min. The samples were then centrifuged at 6000 X g for 10 min and the supernatant was collected in a clean 50 ml falcon tube. Additionally, the soil pellets were sometimes extracted two more time with 4.5 ml of DNA extraction buffer, and 0.5 ml of 20% SDS followed by vortexing for 10 s, incubating in a water bath at 65oC for about 10 min, and centrifugation at 6000 X g for 10 min as before. The supernatants from multiple rounds of extraction were combined and then the DNA was extracted following the phenol-chloroform method described earlier. 3.3.4 Quantitative polymerase chain reaction (Q-PCR) 3.3.4.1 Primer design  Total bacteria (16S), selenate reductase (serABC), and nitrite reductase (nirK) genes were quantified in the cultures using QPCR. Total bacteria were quantified through the 16S gene using the primer pair BACT1369F (5'- CGGTGAATACGTTCYCGG-3') and BACT1492R (5'- GGWTACCTTGTTACGACTT-3') according to Suzuki et al. 2000 and Vigneron 2013 (Suzuki, Taylor, Delong, & Long, 2000; Vigneron et al., 2013). The primer pair for the amplification of nirK gene was nirK_876F (5'- ATYGGCGGVAYGGCGA-3') and nirK_1040R (5'- GCCTCGATCAGRTTRTGGTT-3') (Warneke et al., 2011). The primer pair for amplification of serABC gene was serA765F(5'-CACACCAAGGACGGCAAGTTC-3') and SerA975R(5'-CAATCTCGGCTTTCAGGCGTTC-3').The selenate reductase (serA) primers were designed from the selenate reductase gene sequence (ACCESSION NO. AJ007744) from Thauera selenatis (T Krafft et al., 2000). Product size was 210 bases and the forward and reverse primers targeted positions 765 to 785 and 954 to 975 of the serA gene segment, respectively. The SerA primers were checked for specificity using  A Plasmid Editor Software and by Primer-BLAST to the NCBI nucleotide non redundant (nr) database ((Pruitt, Tatusova, & Maglott, 2007)). To confirm that the amplicons produced by all the above primer pairs targeted the expected genes, 50  PCR products were run on a 1.5% agarose gel, gel-extracted and purified, cloned into E.coli using a TOPO TA cloning kit (Invitrogen), and then sequenced bi-directionally using the vector primers M13R and T7 at the University of British Columbia NAPS unit using Sanger sequencing. 3.3.4.2 Assay Quantitative PCR was performed and analyzed with CFX Connect Real-time PCR System (Bio-Rad) using 96-well plate. The optimum DNA concentration required for proper quantification of targeted genes was first performed by diluting the DNA, extracted from different run orders of the CCD experiment, between 1-10 ng/µl. After analysis, DNA concentrations around 1 ng/µl were found to be optimal for the three target genes used in this study. The QPCR reactions were performed in 15 µl reaction volumes which contained: 1µl each of the forward and reverse primers (5mM), 5 µl of template DNA (5 ng), 7.5 µl of 2X SSO Advanced SYBR® Green Supermix (Bio-Rad, Hercules, CA, USA), and 1.5 µl of RNAse free ddH2O. The reaction conditions for total bacteria and serA was following: Enzyme activation at 95°C for 3 min; followed by 40 cycles of denaturation at 95°C for 10 s, annealing at 55°C for 30 s, and extension at 72°C for 1 min; followed by a final extension step at 72°C for 10 min. The reaction condition for nirK included six touchdown cycles and conditions as described by Warneke et al. 2011. The fluorescence data acquisition was taken after the elongation step and furthermore the melt-curve analysis was performed in all samples with data taken after each 0.5°C between 55°C and 72°C. The product purity and specificity was noted using both a single melting curve as well as analyzing in a 1.5% electrophoresis gel. 3.3.4.3 Q-PCR standards and analysis  Standards were constructed by cloning the PCR products of 16S rRNA, serA, and nirK genes, respectively, obtained when amplifying targets from the enrichment cultures, into plasmids using the TOPO TA cloning kit (Invitrogen). Five to eight 10-fold serial dilutions, which contained 3.41*103 to 3.41*106 copies of 16S rRNA, 8.65*102 to 8.65*109 of SerA, and 2.87*102 to 2.87*108 of nirK gene fragments were used to generate standard curves. The QPCR assay consisted of triplicate sets of DNA standards, DNA samples extracted from the experimental runs and no-template control (sterilized deionised water). For quality control, a subset of experimental DNA samples were run in duplicate QPCR plates to check for the 51  consistency in the acquired copy numbers. The triplicate DNA samples were then averaged to give a single copy number.   Table 7. Target gene along with the primers selected Target gene /group Name Amplicon size (bp) Primer (5'-3') Q-PCR annealing temp (oC) Reference Total Bacteria BACT1369F BACT1492R 272 CGGTGAATACGTTCYCGG GGWTACCTTGTTACGACTT 55 (Suzuki et al., 2000); (Vigneron et al., 2013) Selenate reductase serA_765_F serA_975_R 210 CACACCAAGGACGGCAAGTTC CAATCTCGGCTTTCAGGCGTTC 55 This study This study Nitrite reductase nirK_876F nirK_1040R 164 ATYGGCGGVAYGGCGA GCCTCGATCAGRTTRTGGTT 58-62 (Warneke et al., 2011) (Warneke et al., 2011)  3.3.5 Metagenomic sequencing Based on the selenate reduction results obtained from the three CCD experiments (section 4.4), two samples with the highest and lowest selenium percentage reduction (extent of reduction) were chosen for metagenomic sequencing.  Along with this, native sediment samples obtained from Goddard Marsh (GM) and Mature Tailing Coal (MTC) were also used for Illumina sequencing. The samples named GM_6 (low Se reduction) and GM_8 (high Se reduction) were obtained from the CCD experiment with GM inoculum having no nitrate (GM 0 mM NO3- inoculum) and represented run order 6 and 8 respectively. Similarly, GM_17 (high Se reduction) and GM_21 (low Se reduction) represented the run order 2 and 5 from the CCD experiment performed with GM inoculum with high nitrate (GM 8 mM NO3- inoculum). MTC_36 (low Se reduction) and MTC_38 (high Se reduction) represented run order 6 and 8 performed in the CCD experiment with MTC 4 mM NO3-  inoculum. Samples labeled GM and MTC represented the native sediments obtained from the mining site.   52  Table 8. Samples used for metagenomic analysis Sample ID Source Concentration used in the CCD mg/L  Selenate reduction (%) Over 14 days SeO42--Se NO3--N GM Goddard March 0 0 na MTC Mature tailings coal 0 0 na GM_6 Goddard Marsh 0 mM NO3- 19.2 60 low (46.8) GM_8 Goddard Marsh 0 mM NO3- 9.6 120 high (94.6) GM_17 Goddard Marsh 8 mM NO3- 1.0 5 high (46.4) GM_21 Goddard Marsh 8 mM NO3- 1.2 15 low (oxidized) MTC_36 Mature tailings coal 4 mM NO3- 1.2 15 low (30.9) MTC_38 Mature tailings coal 4 mM NO3- 0.6 29.14 high (56.4)  3.3.5.1  Library preparation and sequencing  DNA was extracted as described before. The quality of extracted DNA was evaluated by running samples on a 1% agarose gel electrophoresis. DNA was purified from the high molecular weight band on the gel using excision and the QIAquick Gel Extraction Kit (Qiagen) and the extracted genomic DNA was quantified using qubit assay. Approximately 1 ng total DNA was used for library preparation. A DNA fragment library with an index at each end was generated for all samples using the Nextera XT DNA sample preparation kit (GA09115). For quality control and size evaluation, the sequencing library was analyzed on a Bioanalyzer 2100 (Agilent Technologies). The libraries were then sequenced to produce paired-end 150 base reads at the McGill University and Genome Quebec Innovation Centre (Montreal, Quebec) using Illumina MiSeq technology. The output of this sequencing was a generation of 1.3 gigabases(Gb) (average) of metagenomic data from 8 samples which were used for subsequent analysis (Table 17). 3.3.5.2  Metagenomic analysis and assembly The low quality sequences were excluded using FASTQ quality filter that removed reads shorter than 100 bp and quality score lower than 20 (q-20, P-100). These sequence reads were 53  then assembled into contigs using velvet and Metavelvet programs (Namiki, Hachiya, Tanaka, & Sakakibara, 2012; Zerbino & Birney, 2008). Taxonomic and functional analysis were performed using Metapathways 2.0 software (Konwar, Hanson, Pagé, & Hallam, 2013). This pipeline used PRODIGAL (Hyatt et al., 2010) to predict open reading frames (ORF), which were then annotated against KEGG (Kanehisa, Goto, Sato, Furumichi, & Tanabe, 2012), COG (Tatusov, Galperin, Natale, & Koonin, 2000), Refseq (Pruitt et al., 2007), and METACYC (Caspi et al., 2014) protein databases. The taxonomic assignments of 16S rRNA genes were done against Greengenes (DeSantis et al., 2006), and Silva (Quast et al., 2013) databases. The proteins predicted using PRODIGAL were used for taxonomic affiliation by performing LAST searches against the Refseq Non redundant (NR) database (e-value of 1e-6, maximum hits = 5, min length 60 and min score 20) and visualized on MEGAN software (version 5.10.5) (Huson, Auch, Qi, & Schuster, 2007). Megan uses Lowest Common Ancestor (LCA) algorithm to assign each reads to the lowest taxonomy it hits in the matches (LCA parameters: Min score 50; top 10% hits; Min support 1) (Huson et al., 2007). Similarly annotated sequences were also mapped to the KEGG and SEED pathways using modules available in MEGAN.   54  Chapter 4: Results 4.1 Experiment 1: Determining the potential for selenate-reduction in different environmental sediments samples The selenate reduction potentials of four mine-impacted sediments, Goddard Marsh (GM), Mature Tailings Coal (MTC), Fresh Tailings Coal (FTC) and Mount Polley ABR (MP), were assessed by incubating triplicate samples in a high selenate concentration growth medium under anaerobic conditions at 28oC. The average numbers of days before appearance of a red precipitate were recorded (Table 9). The control sample, growth medium without any of the sediments, appeared colorless and did not show any red precipitate indicating that the growth medium did not reduce selenate, suggesting that the red precipitate was due to constituents (likely microbial) in the mine sediment samples (R S Oremland et al., 1989; John F Stolz et al., 2006). A red precipitate was seen within 10 days in all of the mine sediments cultures. Based on the time taken for elemental Se to appear, selenate reduction potential in the sediment samples was ranked GM > MTC > FTC > MP (Table 9).   Table 9. Initial selenate reduction tests for samples obtained from mine sites Samples Average days when first red precipitate observed Goddard Marsh 3.33 Mature Tailing Coal 4.33 Fresh Tailing Coal 6 Mount Polley 7.67  4.2 Experiment 2: Enrichment of selenate-reducing bacteria from coalmine impacted sediments Sediment samples from Goddard Marsh and Mature Tailing Coal that indicated the highest selenium reduction potential were used to enrich for a consortium of microorganisms capable of selenate reduction. Cultures were serially transferred into the corresponding new 55  culture media within 10 days. This procedure was repeated at least few times to obtain a stable selenate-reducing consortium. Red precipitate of elemental Se was observed that increased with time and settled at the bottom of the culture bottle (Figure 7).    Figure 7.  Precipitation of elemental selenium (red coloration) in inoculated bottles  4.3 Experiment 3: Adaptation of primary enrichment culture at various concentration of nitrate In order to obtain a mixed consortium capable of reducing selenate and nitrate, primary enrichments obtained through experiment 2 were adapted at various concentration of nitrate. Initial and final total dissolved selenium concentrations in the Goddard Marsh (GM) enrichment cultures containing 0 to 8 mM nitrate concentrations are given in Figure 8. Reduction of total dissolved selenium was high (>= 50%) within the 10 day period for each of the passages. Selenium reductions were similar in nitrate adapted enrichment cultures (overlapping lines in the graph below). Subsequently, two of these enrichments, GM 0 mM NO3- (grown with no nitrate) 56  and GM 8 mM NO3- (grown with high nitrate) were used as inocula for the time curve experiment to measure Se reduction in the presence of different nitrate concentration.    Figure 8. Total dissolved selenium concentrations (mM) in Goddard Marsh enrichments. Enrichment media adapted at different nitrate concentration (mM)  4.4 Experiment 3: Selenate reduction in the presence of nitrate by the GM and MTC enrichments 4.4.1 Total soluble selenium and nitrate reduction by GM 0 mM NO3- enrichment  The reduction of total dissolved selenium and nitrate by the GM 0 mM NO3- enrichment culture under different concentrations of nitrate are presented in Figure 9. Runs 1 to 13 refer to the experimental conditions that were given in Table 6 of Section 3.2.4.1. Total dissoved selenium concentrations decreased over time for all of the experimental conditions, without any lag period, and despite different nitrate concentrations. Selenium concentration was reduced to below detection limit in runs with low selenium concentration (run 1: 3.2 mg Se/L and run 5: 0.8 mg Se/L at t=0). Selenium concentration was also reduced significantly in Run 3(low Se concentration: 3.2 mg Se/L at t=0) to 0.44 mg Se/L by day 10. However, it increased abruptly on day 14 to 1.25 mg Se/L. For runs with moderate Se 0 5 10 15 20 25 0 10 20 30 40 50 Selenium Concnetration (mM) Days GM Enrichments 0 mM NO3- 2 mM NO3- 6 mM NO3- 8 mM NO3- 57  concentration (run 7 to 13: 9.6 mg Se/L at t=0), Se concentration on the final day was between 0.6 -3.2 mg Se/L. Finally, for runs with high Se concentration (runs 2 and 4: 16 mg Se/L and run 6: 19.2 mg Se/L at t=0), Se concentration plateaued at 7-14 mg Se/L by day 14. For runs with low initial total dissolved Se concentration (run 1 and run 3), higher concentration of NO3- affected Se reduction. While Se  in run 1 (20 mg N/L at t=0) was reduced to below detection limit, Se concentration was still high in run 3 (100 mg N/L) on day 14. For runs with moderate initial total dissolved Se concentration (run 7 and run 8), Se was reduced to the same range despite different NO3- concentration and Se reduction was not affected by high nitrate concentration. Similarly, in runs with high Se concentration (run 2 and run 4), Se concentration on day 14 was similar and overall Se reduction was not affected by NO3- concentration. The Se reduction versus time graph for most run orders showed a linear reduction until day 3 which then gradually levelled-off by day 10 (similar to 1st  order reaction). In order to estimate the rate constants of selenium reduction in different run orders, a simple first-order kinetics was assumed. A logarithmic fit of the time-curve data for different run order was performed to calculate the rate constant k (Table 10).  Table 10. Rate constants (k) for different runs of GM 0 mM NO3- CCD experiment  Run order Rate constant (k) day-1 R2 1 0.783 0.99 2 0.056 0.93 3 0.062 0.31 4 0.076 0.90 5 0.81 1(with only 2 points) 6 0.049 0.94 7 0.15 0.99 8 0.199 0.95 9 0.149 0.74 10 0.158 0.96 11 0.121 0.92 12 0.105 0.85 13 0.211 0.66 58   Using the above method, a linear fit of data with high regression coefficient (R2>0.95) was only obtained for some run orders.  Moreover, for run orders with R2 < 0.95, a linear fit was only observed for some portions of data (t=5). As linear fit of data could not be obtained for full data set (Se concentration for t=14), an alternative method for determining Se reduction rate constant was sought using the initial/early data points ( t=2) and with the following equation:                  Eqn. (7)  Table 11. Rate constants (k') for different runs of GM 0 mM NO3- Run order Rate constant (k') day-1 1 0.40 2 0.09 3 0.26 4 0.16 5 0.80 6 0.078 7 0.16 8 0.13 9 0.12 10 0.17 11 0.14 12 0.17 13 0.14   The Nitrate reduction occured simultaneously with selenium reduction for most runs. In most runs nitrate reduction was continuous over 14 days, following a first order kinetics. 59  Denitrification was almost complete in runs with low nitrate concentration (run1 , run 2, run 7) in comparison to runs with high nitrate concentration (run 2, run 4). One distinction was observed in run 8 with very high nitrate concentration where denitrification was also almost complete (>80 percent) by day 14. In runs with moderate nitrate concentration (runs 9-13), nitrate reduction was similar with the same apparent first order kinetics. 60  0 2 4 6 8 1 0 1 2 1 401234R u n  1 : 2 0  m g  N /LD a y sTotal Selenium mgL-10 5 1 0 1 501234R u n  3 : 1 0 0  m g  N /LD a y sTotal Selenium mgL-10 5 1 0 1 5051 01 52 02 5 R u n  2 : 2 0  m g  N /LD a y sTotal Selenium mgL-10 5 1 0 1 5051 01 52 02 5 R u n  4 : 1 0 0  m g  N /LD a y sTotal Selenium mgL-15 1 0 1 5-0 .50 .00 .51 .01 .5 R u n  5 : 6 0  m g  N /LD a y sTotal Selenium mgL-10 5 1 0 1 501 02 03 0R u n  6 : 6 0  m g  N /LD a y sTotal Selenium mgL-10 5 1 0 1 5051 01 5R u n  7 : 4  m g  N /LD a y sTotal Selenium mgL-10 5 1 0 1 5051 01 5R u n  8 : 1 2 0  m g  N /LD a y sTotal Selenium mgL-1 61  0 5 1 0 1 5051 01 5R u n  9 : 6 0  m g  N /LD a y sTotal Selenium mgL-10 5 1 0 1 5051 01 5R u n  1 0 : 6 0  m g  N /LD a y sTotal Selenium mgL-10 5 1 0 1 5051 01 5R u n  1 1 : 6 0  m g  N /LD a y sTotal Selenium mgL-10 5 1 0 1 5051 01 5R u n  1 1 : 6 0  m g  N /LD a y sTotal Selenium mgL-10 5 1 0 1 5051 01 5R u n  1 2 : 6 0  m g  N /LD a y sTotal Selenium mgL-10 5 1 0 1 5051 01 52 02 5R u n  1 3 : 6 0  m g  N /LD a y sTotal Selenium mgL-1 Figure 9. Time course of selenium reduction in different run order of GM 0 mM NO3- inoculants 62  0 5 1 0 1 501 02 03 0R u n  1  N O 3-D a y sNitrate mg N/L0 5 1 0 1 501 02 03 04 0R u n  2  N O 3-D a y sNitrate mg N/L0 5 1 0 1 505 01 0 01 5 0R u n  3  N O 3-D a y sNitrate mg N/L0 5 1 0 1 505 01 0 01 5 02 0 0R u n  4  N O 3-D a y sNitrate mg N/L0 5 1 0 1 502 04 06 08 0R u n  5  N O 3-D a y sNitrate mg N/L0 5 1 0 1 502 04 06 08 01 0 0R u n  6  N O 3-D a y sNitrate mg N/L0 5 1 0 1 501234R u n  7  N O 3-D a y sNitrate mg N/L0 5 1 0 1 505 01 0 01 5 02 0 0R u n  8  N O 3-D a y sNitrate mg N/L 63  0 5 1 0 1 502 04 06 08 0R u n  9  N O 3-D a y sNitrate mg N/L0 5 1 0 1 502 04 06 08 0R u n  1 0  N O 3-D a y sNitrate mg N/L0 5 1 0 1 502 04 06 08 01 0 0R u n  1 1  N O 3-D a y sNitrate mg N/L0 5 1 0 1 502 04 06 08 01 0 0R u n  1 1  N O 3-D a y sNitrate mg N/L0 5 1 0 1 502 04 06 08 01 0 0R u n  1 2  N O 3-D a y sNitrate mg N/L0 5 1 0 1 502 04 06 08 0R u n  1 3  N O 3-D a y sNitrate mg N/L Figure 10. Nitrate reduction in different run orders of GM 0 mM NO3- inoculants 64  4.4.1.1 ANOVA for the selenium reduction in GM 0 mM NO3- innoculum Two response variables: percentage Se reduction(extent of reduction) over 14 day and rate constant (k' calculated in Table 11) of Se reduction, were used in the  CCD experiment to assess the influence of the two factors: selenate (x1) and nitrate (x2). Using percentage Se reduction over 14 days as a response variable, a second order polynomial equation along with its coefficient was obtained from the selenium reduction data (% Se reduction) in 13 runs.                                                                    Eqn. (8) where Sered is the total soluble selenium reduction in percentage over 14 days calculated from selenium concentration at time points t = 0 and t = 14 and x1, and 2 are the coded values (-α, -1, 0, +1, +α). ANOVA was performed on the model equation and p-value was derived to test the significance of regression. The details of the ANOVA analysis is presented in Table 12.  Table 12. Anova results using percentage Se reduction (%) over 14 day as response Source of Variation Degrees of Freedom Sum of Squares [partial] Mean Squares [partial] F Ratio P values Model 5 2451.87 490.37 8.89 0.0061 X1 1 416.78 416.78 7.56 0.0285 X2 1 16.87 16.87 0.30 0.5972 X1. X2 1 542.89 542.89 9.85 0.0164 X12 1 1299.69 1299.69 23.58 0.0018 X22 1 71.18 71.18 1.29 0.2931 Residual 7 385.69 55.09   Lack of Fit 3 270.1 90.03 3.11 0.1505 Pure Error 4 115.58 28.89   Total 12 2837.57     65  Fischer's test was calculated to test the significance of each variables for the reduction of selenium using GM 0 mM NO3- inoculum in the CCD experiment.  The ANOVA table shows that the quadratic model is statistically significant (p= 0.0061); however, the lack of fit is not significant  (p = 0.15). This shows that the model equation is appropriate for the experiment. Although the main aim was to find the significance of the factors involved in selenate reduction, model equation was also used to build a contour plot and Response surface plot (Figure 11 & Figure 12) for depicting the effect of variables, selenate and nitrate, on selenate reduction. The regression coefficient (R2) was calculated and gives a value of 86.4% which indicates that 14.6% of the variations in the data could not be explained by the model. Adjusted R2 (76.69%) calculated was smaller than the R2 but was within the reasonable differences. This  difference in the values between R2 and Adjusted R2 can occur with the inclusion of many terms in the model equation.  Based on the ANOVA analysis, p values for X1(Se), X12(Se2) , and X1. X2(Se × NO3-) are significant.  p value of NO3- (0.59) alone was insignificant. However, a combined effect of NO3- and Se seems to be significant suggesting that the effect of nitrate is dependent on the Se concentration. The affect of NO3- is two-fold depending on the concentration of Se: at low Se concentration, NO3- is inhibitory for Se reduction whereas at high Se concentration, high NO3- concentration promotes Se reduction. Hence, the most significant factor for the selenate reduction in range tested is the concentration of initial total dissolved selenium in the medium. Similarly, using rate constant as a response variable, a second order polynomial equation along with its coefficient was obtained from the 13 runs.                                                                        Eqn. (9)  where Serc is the selenium rate constant calculated in Table 11and x1, and 2 are the coded values (-α, -1, 0, +1, +α). ANOVA was performed on the model equation and p-value was derived to test the significance of regression. The details of the ANOVA analysis is presented in Table 13. 66  Table 13.  Anova results using rate constant (k'=day-1) response  Source of Variation Degrees of Freedom Sum of Squares [partial] Mean Squares [partial] F Ratio P values Model 5 0.38 0.077 9.1 0.0057 X1 1 0.25 0.25 29.7 0.001 X2 1 0.0017 0.0017 0.20 0.6677 X1. X2 1 0.01 0.01 1.18 0.3131 X12 1 0.11 0.11 13.5 0.0079 X22 1 0.0020 0.0020 0.23 0.6428 Residual 7 0.06 0.0084   Lack of Fit 3 0.057 0.019 46.0 0.0015 Pure Error 4 0.0017 0.00041   Total 12 0.44     The model equation, using rate constant as response variable, was significant (p value smaller than 0.05) while R2 value obtained was 86.7%. The model equation was also used to build response surface plot (Figure 13& Figure 14). Based on the ANOVA analysis, two terms X1(selenium) and X12 (Selenium2) were significant. The rate constant was highest at low Se concentration while NO3- had no significant affect on Se reduction rate.  67   Figure 11. Response surface plot of the extent of Se reduction as a function of total dissolved selenium and nitrate. 68   Figure 12. Contour plot of the extent of Se reduction as a function of total dissolved selenium and nitrate.  Figure 13. Response surface plot of the rate constant (k') as a function of total dissolved selenium and nitrate. 69   Figure 14. Contour plot of the rate constant (k') as a function of total dissolved selenium and nitrate.   4.4.2 Selenium-reduction in the presence of nitrate by the GM 8 mM-NO3- enrichment culture Concentrations of total dissolved Se over time for the GM 8mM NO3- enrichment culture are presented in Figure 15. The runs 1 to 13 represent the experimental condition as given in Table 6 of material and methods section (section 3.2.4.1) .  Total dissolved selenium increased in all cultures from day 0 to day 5. Thereafter, decrease in total selenium concentration was seen, for some some cultures (runs 1, 2, 3, 5, 6, 8, 9, 10, and 12), from day 5 to day 10. This decrease in selenium concentration, however, changed abruptly with an increase between day 10 and day 14 within the same runs. An interesting observation that can be seen is that the trends in the increase and decrease of selenium in most runs occurred during the same time frame.  70  The increase in the total dissolved selenium may be as a result of the oxidation of elemental selenium present within the inoculum. Due to this effect it was, unfortunately, not possible to use these data to examine the ability of selenate-enrichments to reduce total dissolved Se in the presence of nitrate.  In addition, ANOVA, which was originally planned for the experiment, could also not be performed for this experiment. However, quantitative analysis of genes present in the culture was still determined with q-PCR and two of the cultures were used for metagenomic sequencing. 71  0 5 1 0 1 50123R u n  1D a y sTotal Selenium mgL-10 5 1 0 1 501234R u n  2D a y sTotal Selenium mgL-10 5 1 0 1 50123R u n  3D a y sTotal Selenium mgL-10 5 1 0 1 50123R u n  4D a y sTotal Selenium mgL-10 5 1 0 1 501234R u n  5D a y sTotal Selenium mgL-10 5 1 0 1 5012345R u n  6D a y sTotal Selenium mgL-10 5 1 0 1 501234R u n  7D a y sTotal Selenium mgL-10 5 1 0 1 50123R u n  8D a y sTotal Selenium mgL-10 5 1 0 1 50123R u n  9D a y sTotal Selenium mgL-10 5 1 0 1 501234R u n  1 0D a y sTotal Selenium mgL-10 5 1 0 1 50123R u n  1 1D a y sTotal Selenium mgL-10 5 1 0 1 50123R u n  1 2D a y sTotal Selenium mgL-10 5 1 0 1 50123R u n  1 3D a y sTotal Selenium mgL-1 Figure 15. Time curve of total selenium in different run order of GM 8 mM NO3- inoculants. 72  4.4.3 Selenium reduction by the MTC 4 mM NO3- enrichment culture Concentration of total dissolved Se over time for the experiments using MTC 4 mM NO3- enrichment as the inoculum are presented in Figure 16. Runs 1 to 13 represent the experimental conditions as given in Table 6 of material and methods section (section 3.2.4.1). An ANOVA could not be performed for this experiment as the initial total selenium concentration is significantly different than the one planned in the CCD experiment. This difference in concentration probably occurred due to some residual selenium present in the inoculum. As the concentration of total dissolved selenium exceeds by 7-8 mg/L in all runs, it is hypothesized that ~ 80 mg/L of total dissolved Se must have been present in the pre-culture prepared from the MTC 4 mM NO32- enrichment. This is probably the result of re-oxidation and solubilization of elemental selenium present in the inoculums.. Nevertheless, reduction analysis was performed for this experiment as the total Se reduced in all runs. A sharp decrease in total dissolved selenium on day 1 followed by contrasting increase on day 2 was observed in all runs (1-13). Following this increase on day 2, total Se concentration decreased linearly till day 10 for most runs (1-13). Se concentration remained mostly unchanged during day 10 to day 14 time period. The extent of reduction determined through the overall percentage reduction on day 14 was similar in most runs with an average around 45 percentage. The extent of reduction over 14 days was highest in run 9 (60%) while the lowest was observed in run 6 (30%). Run 8 which had the highest nitrate concentration (30 mg N/L) also had a high extent of reduction (56%). The rate of Se reduction was lower in runs with lower nitrate concentration (Runs 1, 2, and 7) compared to all other runs with higher nitrate concentration. For most runs, the rate of total selenium reduction roughly followed a first order reaction with a linear change during day 2 to day 10 followed by a plateau during day 10 to day 14. 73  0 5 1 0 1 502468R u n  1D a y sTotal Selenium mgL-10 5 1 0 1 5456789R u n  2D a y sTotal Selenium mgL-10 5 1 0 1 5024681 0R u n  3D a y sTotal Selenium mgL-10 5 1 0 1 5024681 0R u n  4D a y sTotal Selenium mgL-10 5 1 0 1 502468R u n  5D a y sTotal Selenium mgL-10 5 1 0 1 54567891 0R u n  6D a y sTotal Selenium mgL-10 5 1 0 1 5024681 0R u n  7D a y sTotal Selenium mgL-10 5 1 0 1 5024681 0R u n  8D a y sTotal Selenium mgL-10 5 1 0 1 502468R u n  9D a y sTotal Selenium mgL-10 5 1 0 1 502468R u n  1 0D a y sTotal Selenium mgL-10 5 1 0 1 502468R u n  1 1D a y sTotal Selenium mgL-10 5 1 0 1 502468R u n  1 2D a y sTotal Selenium mgL-10 5 1 0 1 5024681 0R u n  1 3D a y sTotal Selenium mgL-1 Figure 16. Time course of total selenium in different run orders of MTC 4 mM-NO3- inoculants 74   4.5  Quantitative analysis of selenate-reductase and nitrate-reductase in the Se-reducing cultures  4.5.1 Quantification of 16S rDNA, serA, and nirK in GM 0 mM NO3- samples  Q-PCR assay was used to quantify the copies of 16S rDNA, serA, and nirK target genes in the culture samples with varying selenate and nitrate concentration using primer sets described in Table 7. The copies of 16S rDNA,  serA, and nirK genes across different samples (runs) of the  CCD experiment was first computed from the calibration curves (Table 14). The serA, and nirK gene copies were normalized with the16S rDNA gene copies for that sample. This normalized abundance was then converted to relative abundance by dividing with the highest normalized value across the 13 samples. Thus, a relative percentage abundance of serA and nirK gene across 13 CCD samples are presented in Figure 17.  In general, there was a variation in the relative abundance of serA and nirK genes across the 13 cultures (runs). The relative abundance of serA did not correlate with the selenate reduction extent for different samples. However, the serA gene in different cultures correlated with the initial Se concentration (Figure 18; R2= 0.72). Looking further, it can be observed that the absolute number of serA target gene copies varied between 1.72E+05 and 3.61E+05 copies per ng total DNA. Thus, it can be observed that the quantity of  serA gene did not change much across the 13 samples.  The number of nirK target gene copies in the samples were two order smaller than serA gene quantity and ranged between 9.67E+03(sample 5) to 1.06E+05 (sample 1) copies per ng total DNA. However, since nitrate reduction was almost complete in most samples, nirk gene must have failed to capture the total denitrifying population. Furthermore, since samples for DNA extraction was taken at the end of day 14 when most denitrification was complete, it could mean that denitrifying populations were low at that time. Alternatively, nirS gene possessing denitrifier might have been present in the samples which was failed to be captured in q-PCR reaction.  75   Table 14. Average copy number ( ×104) of 16S rRNA, selenate reductase gene (serA) and denitrification gene (nirK) for different run order (samples) of the CCD experiment with GM 0 mM NO3- innoculum. Samples 16S rDNA copies ng-1  total DNA serA copies ng-1 total DNA nirK copies ng-1 total DNA 1 4156.5 17.2 10.6 2 4959.6 31.4 2.9 3 6003.9 26.4 8.3 4 6928.3 25.1 4.3 5 9957.7 36.1 .967 6 3794.9 25.9 1.9 7 2091.6 17.4 2.0 8 3801.5 19.2 6.1 9 8627.7 20.0 7.8 10 7793.7 43.3 6.1 11 7245.4 20.5 3.0 12 8491.6 19.6 5.0 13 25540.8 35.4 6.90   Figure 17. Relative abundance of different genes in different run order of GM 0 mM NO3- inoculants 0 20 40 60 80 100 120 1 2 3 4 5 6 7 8 9 10 11 12 13 Relative Abundance (%) Run order/samples serA nirK 76   Figure 18. Correlation between serA and Se concentration in different cultures of GM 0 mM NO3- inoculants. . Table 15. Analysis of Se and NO3- reduction in different run order of GM 0 mM NO3- cultures  Run Order 1 2 3 4 5 6 7 8 9 10 11 12 13 Percentage Se reduction (%) 89.3 52.4 55.6 65.2 68.2 46.8 87.9 94.6 79.2 87.2 77.7 73.7 84.4 Se reduction rate (mgL-1day-1) 0.49 1.32 0.26 2.07 0.28 1.196 1.34 1.84 0.397 1.507 1.318 1.55 1.70 Percentage NO3-N reduction(%) 99.5 99.2 80.3 56.6 96.5 91.2 95.3 80.1 89.6 73.5 65.1 77.8 57.3 NO3-N reduction rate(mgL-1day-1)  4.4 5.5 13.5 10.1 9.1 10.3 0.5 13.0 6.8 7.2 2.8 6.0 4.5   y = 0.0479x + 1.1888 R² = 0.7268 0 0.5 1 1.5 2 2.5 3 0 5 10 15 20 25 serA percentage (%) Selenium concentration (mg/L) Correlation between serA and Se concentration 77  4.6 Comparison of the kinetics of selenium reduction by native sediments and the enrichments Having established that enrichment cultures GM 0 mM NO3- and MTC 4 mM NO3- were able to reduce selenate in the presence of nitrate, two of the cultures (run number 8 from both) were used for the next experiment. The objective of this experiment was two-fold: first to examine if the cultures retained their selenium reduction potential in subsequent passages and secondly to compare their performance with that of native sediment samples. The first objective tested if inoculum used in the bioreactor retained its selenate reduction potency even after continued operation in the presence of nitrate, or whether continuous culturing and addition of fresh selenate-reducing inoculum was necessary due to shifts in bacterial community caused by nitrate. The second objective tested the possibility of using stimulated soil samples around the mine sites as it is freshly and freely available. 78   Figure 19. Time course of selenium and nitrate reduction in GM enrichment and sediments. 79   Figure 20. Time course of selenium and nitrate reduction in MTC enrichment and sediments.  4.6.1 Effect of nitrate on selenium reduction by the Goddard Marsh enrichment  The Goddard Marsh enrichment that achieved the highest selenium reduction in the previous experiment was used as an inoculum for this experiment. The experiment was performed to assess the effect of nitrate concentration on selenium reduction by the GM enrichment and compare this with selenium reduction by microbes in the original Goddard Marsh sediment samples. Reduction of selenium in the cultures inoculated with enrichment with NO3- levels of 0, 20, 60 and 100 mg N/L is shown in Figure 19. The selenium concentrations at the end of the 7 day experiment for samples with 0, 20 60, and 100 mg N/L of nitrate were 2.76± 0.35, 4.09±0.12, 2.97±0.13,and  2.92±0.08 mg/L, respectively. Nitrate concentration has a negligible effect on the final extent of Se reduction.  However, the rates of selenium reduction 80  appeared to be affected by different nitrate concentrations. No discernible selenium reduction was observed during the first 3 days in the control sample with no nitrate. However, the reduction rate increased steeply thereafter to 0.54 mg.(L.day)-1 (taking t=3 to t=5 into account).  Cultures with nitrate achieved Se reduction rates faster than the no nitrate control initially, but this rate decreased and Se concentration with respect to time plateaued. In contrast, Se concentrations continued to decrease with time approximately linearly in the no nitrate control. Nitrate had an apparent stimulatory effect on Se reduction when increased from 20 to 60 mg N/L. However, the reduction of selenium in the 60 and 100 mg N/L NO3- cultures was very similar. The fastest Se reduction rate achieved by the Goddard Marsh enrichment was 0.4 mg.(L.day)-1 in cultures containing initial concentrations of nitrate of 60 and 100 mg N/L.  4.6.2 Effect of nitrate on selenium reduction by the native Goddard Marsh sediment Reduction of selenium in cultures inoculated with the native Goddard Marsh sediment in the presence of initial NO3- concentrations of  0, 20, 60,and 100 mg N/L, respectively, are shown in Figure 19. Selenium reduction proceeded rapidly for all samples despite the nitrate concentration. Final selenium concentrations at the end of the 7 day experiment for cultures with 0, 20 60, and 100 mg/L of nitrate were 0.98±0.13, 1.01±0.06, 1.32±0.05, and 1.86±0.15 mg/L, respectively. Selenium reduction rates were similar for the cultures with 0 – 60 mg/L nitrate, but were apparently slower for the cultures with 100 mg/L nitrate.  The selenium reduction rate for cultures with 0, 20 60, and 100 mg N/L of nitrate were 0.75, 0.55, 0.76, and 0.54 mg.(L.day)-1. Increasing the nitrate concentration up to 60 mg N/L did not seem to affect the rate or extent of selenium reduction. However, nitrate concentration at 100 mg N/L decreased both the rate and extent of selenium reduction. Compared with the cultures inoculated with Goddard Marsh enrichment, the rates of Se reduction measured when using the native sediment were much faster (1.5-2 times).  4.6.3 Nitrate reduction in GM enrichments and GM soil  Nitrate was completely reduced in all of the cultures when GM enrichment was used as an inoculant whereas denitrification was incomplete with native sediments. The rate of nitrate reduction in GM enrichment increased with increasing concentration of nitrate (from 0 to 100 mg 81  N/L) and an overall reduction of  ≥ 99 percentage was achieved by the 7th day in most culture bottles. In contrast, reduction of nitrate is incomplete in GM soil; the only sample to be completely reduced is the one with 20 mg N/L sample. The nitrate reduction in GM soil samples with 60, and 100 mg N/L is linear until the third day. However, the nitrate level remains unchanged and almost no reduction occurs until the last day. The reduction of nitrate in GM soil samples decreases with the increasing amount of nitrate in the samples. The overall reduction percentage in 20, 60, and 100 mg N/L of GM soil samples are 99.4, 40.0, and 7.83 percentage respectively. It seemed that the enrichment enriched for denitrifiers, but there were more selenate reducers in the GM native sediments. 4.6.4 Effect of nitrate concentration on selenium reduction using the Mature Tailings Coal enrichment   Reduction of total dissolved selenium by the MTC enrichment culture with increasing concentrations of  NO3- over 7 days is presented in Figure 20. Final selenium concentrations for cultures with 0, 20 60, and 100 mg N/L of nitrate were 5.68 ±0.32, 3.60±0.20, 4.12±0.24, and 3.80±0.11 respectively.  Reduction of selenium was fast for the initial 3 days, followed by an increase in selenium concentration for all cultures. For the no nitrate control, the final Se concentration was higher than that at the beginning of the experiment. Se reduction was apparently faster and greater when there was some nitrate present (20-100 mg N/L).  4.6.5 Effect of nitrate concentration on selenium reduction using the native Mature Tailings Coal  Selenium was reduced in all Mature Tailings Coal (MTC) cultures in an approximately linear fashion Figure 20. Rates were similar across all cultures: 0.15, 0.13, 0.06, and 0.16 mg.(L.day)-1  at nitrate concentrations of 0, 20, 60 and 100 mg N/L, respectively. These rates were slower than those observed when Goddard Marsh sediment was used as inoculum. Unlike the Mature Tailings Coal enrichment cultures, there was no leveling off or increase of Se concentration. Se reduction was incomplete at the end of 7 days with average concentrations for cultures with 0, 20 60, and 100 mg N/L of nitrate of 3.21±0.59, 4.02±0.33, 2.26±0.77, and 82  3.84±0.36 mg/L Se, respectively. The overall percent selenium reduction was 38.4, 22.4, 55.3, and 24.8 % for samples with 0, 20, 60, and 100 mg/L of nitrate, respectively. 4.6.6 Nitrate reduction in MTC enrichment and MTC coal  Compared to the nitrate reduction in MTC coal samples, reduction of nitrate in MTC enrichment proceeds rapidly. Although, nitrate is not completely reduced in MTC enrichment samples with 60 and 100 mg N/L nitrate, the reduction rate increases steeply after the third day. In contrast, the reduction of nitrate is slower in the MTC soil consortium with very little reduction of nitrate in all samples.. The overall reduction of nitrate in MTC enrichment samples with 20, 60, and 100 mg N/L were 96.0, 69.0, and 58.0% respectively. In comparison, the overall reduction of nitrate in MTC soil sample with 20, 60, and 100 mg N/L were 41.0, 8.5, and -40 % respectively.  Table 16. Reduction rate and extent of reduction  Cultures (mg N/L NO3-) Reduction rate (mg.(L.day)-1) Extent of Se reduction over 7 days (% Se reduction) GM Enriched (0) 0.01 43.4 GM Enriched (20) 0.24 16.0 GM Enriched (60) 0.42 36.7 GM Enriched (100) 0.41 37.4 GM Soil (0) 0.75 79.0 GM Soil (20) 0.55 77.8 GM Soil (60) 0.76 70.2 GM Soil (100) 0.54 59.5 MTC Enriched (0) 0.19 -17.4 MTC Enriched (20) 0.80 27.9 MTC Enriched (60) 0.63 15.5 MTC Enriched (100) 1.62 48.6 MTC Soil (0) 0.15 38.3 MTC Soil (20) 0.13 22.4 MTC Soil (60) 0.06 55.3 MTC Soil (100) 0.16 24.8 83   4.7 Metagenomic sequencing 4.7.1 Sequencing coverage and analysis with Metapathways Table 17 shows the numbers of raw reads as well as the length of the reads generated by Illumina MiSeq sequencing for different samples. The total number of protein annotated for each samples is given in the last column of the table and varied widely between samples. Interestingly, the native sediments, GM and MTC, had more ORFs and annotated proteins while the enriched cultures had fewer ORFs and  annotated proteins  possibly due to higher diversity in native samples.  Table 17: Summary of Metagenomic data obtained from MiSeq and Metapathways Sample name No. of reads a Total read lengths (bp) a No. of translated ORF b Average length of ORF  Total Annotated Protein b bps GM NA NA 218851 76 128651 MTC NA NA 547194 89 293837 GM_6 614,902 307,451,000 42982 165 37560 GM_8 2,744,894 1,372,447,000 85551  173 74204 GM_17 3,651,274 1,825,637,000 122337 158 105061 GM_21 3,844,722 1,922,361,000 121488 155 797 MTC 36 3,082,464 1,541,232,000 145671 175 125317 MTC 38 2,115,714 1,057,857,000 106404 184 94058  4.7.2 Taxonomic distribution in samples The annotated protein sequences from different samples were used for LAST searches against the Refseq NR database to obtain taxonomic affiliation. At the domain level, Bacteria comprised the largest taxa with greater than 97% assignment for all samples whereas Archaea were assigned to  ≤ 2% reads(Table 18). There were almost no reads assigned to viruses in most 84  samples (or negligible if assigned to any). A clustering analysis of the taxonomic  profiles was performed  using Bray-Curtis distances and Principal Co-ordinate Analysis (PCoA) to compare native sediments (GM and MTC) and enriched samples (GM_6, GM_8, GM_17, GM_21, MTC_36, MTC_38) (Figure 21). Three cluster of distribution was distinctly observed. MTC sediment samples was very different from GM sediment and enrichment cultures. Although enrichment cultures from MTC and GM 0 mM NO3- inoclum were clustured together, interestingly, enrichments inoculated with GM 8 mM NO3-  were similar to original GM sediment. More detailed taxonomic analysis was performed by analyzing the taxonomic distribution at the phylum level (Figure 22). A total of 28 bacterial and 5 archaeal phyla were identified in all 8 samples. However, only top 10 phyla were taken for analysis as they were found across all 8 samples and represented the most abundant taxa. Four  groups of Bacterial phyla dominated the taxa in all 8 samples.  Proteobacteria, Firmicutes, Actinobacteria, and Bacteriodetes were the most abundant phyla, representing greater than 90% reads, in most samples. Euryarcheota, a phyla from the Archaeal domain, was also among the abundant phyla (although only a small percentage≤ 0.5% of total reads). Although a high number of reads were assigned to Proteobacteia, the percentage composition revealed a contrasting picture (Figure 22). Among the four abundant phyla,  Proteobacteria were present at higher percentages in native soil samples (GM and MTC) compared to any of the enriched cultures (GM_6, GM_8, GM_17, GM_21, MTC_36 and MTC_38). Similarly, Actinobacteria was also abundant in native samples compared to the enriched samples. Interestingly, Firmicutes were less abundant in native samples but were dominant in the enriched samples. Bacteriodetes were equally represented in most samples. Within the phylum Proteobacteria, Gammaproteobacteria were the most abundant while Alpha and Betaproteobacteria were present in a smaller proportion. Similarly, Clostridia and Bacilli were the dominant class represented from the phylum Firmicutes.  At the genus level, four genera were predominant in most samples (Figure 23). These include Pseudomonas, Clostridium, Bacillus and Streptomyces. Pseudomonas were a high proportion of enriched GM samples (GM_6, 8, 17, 21) whereas enriched MTC samples(MTC_36, 38) had significantly lower percentage of it (average 10%). Clostridium was also abundantly present in most enriched samples (>15%) compared to native samples (<7%). 85  Native GM and MTC samples had competitive proportion of Pseudomonas present (>16% of total reads). Interestingly, Streptomyces were highly present in both native samples with percentage composition of 18.8% and 15.5% for GM and MTC respectively.   Table 18. Taxonomic distribution at domain level for different samples in percentage  GM MTC GM_6 GM_8 GM_17 GM_21 MTC_36 MTC_38 Bacteria 98.66 97.50 98.4 98.61 98.98 99.02 98.63 98.57 Archaea 1.34 2.51 1.62 1.38 1.01 0.97 1.36 1.43 Viruses 0 0 0.0001 0.0001 3.78E-05 1.89E-05 0.00017 0.000228   Figure 21. PCoA plot of taxonomic composition of different samples  86   Figure 22. Taxonomic composition at phylum level in different samples   Figure 23. Taxonomic composition at genus level for different samples  87  4.7.3 Top species along with selenium reducing microbes in the samples A number of microorganisms were detected at the species level and a list of top 12 species observed in our samples has been presented (Figure 24). An attempt was also made to identify any selenate reducing microbes among the taxa (species) observed in different samples. In doing so, species observed at very low abundance were neglected (even if they were selenate reducing microbes) as doing so would decrease the chances of analyzing false positive species (our experiment only allowed us to analyze highly abundant taxa). Bacillus cereus was the most abundant species in enriched samples while Pseudomonas fluorescens and Stenotrophomonas maltophilia was more abundant in native soil samples. These species have already been discovered for their exceptional ability to reduce selenium oxyanions and nitrate (Dhanjal & Cameotra, 2010; Robert S. Dungan et al., 2003; Carlos Garbisu, Ishii, Leighton, & Buchanan, 1996; Siddique et al., 2007) . Interestingly the native samples had high abundance of nitrogen fixing species, Rhizobium leguminosarum. There has been increasingly high evidence pointing towards the erroneous appearance of this genus in the metagenomic data due to contamination in DNA extraction kit or laboratory reagent (Salter et al., 2014). As these native soil samples had extremely small biomass, these results cannot be refuted. Most of the other abundant species either came from the Pseudomonas or Clostridium genus and include the following: Pseudomonas putida, Pseudomonas aeruginosa, Clostridium botulinum, Pseudomonas fluorescens, Peptoclostridium difficile, Pseudomonas syringae, Pseudomonas stutzeri etc.  A number of selenium reducing microbes reported in the literature were observed in the samples. From the list of 12 highest relative abundance species (Figure 24), almost 10 could be identified to be involved in selenium reduction in one way or another. Moreover, other hits of selenium reducing microbes along with their relative percentage abundance is presented in Table 19 (red highlights the potential selenium reducing microbes). A number of different species belonging to the genus Thauera were abundantly observed in native samples (GM and MTC) whereas their abundance decreased in enriched samples. This observation provided evidence that selenate reducing microbes were already abundant in the GM and MTC environment and could be used as a inoculum in bioreactors to treat selenium contamination. 88   Figure 24. Bubble plot of top 12 normalized species in the samples  Table 19. Percentage composition of various species in the samples with red highlighting putative Se reducers Microbes GM GM_6 GM_8 GM_17 GM_21 MTC MTC_36 MTC_38 References Bacillus cereus 3.61 6.40 5.12 4.04 3.45 4.23 5.92 6.43 (Dhanjal & Cameotra, 2010) Pseudomonas putida 4.55 5.02 6.46 6.31 6.82 4.44 3.49 3.26 (Adams & Pickett, 1997; Knotek-Smith et al., 2006) Pseudomonas aeruginosa 4.24 4.19 5.30 5.24 5.76 4.83 3.91 3.50  89  Microbes GM GM_6 GM_8 GM_17 GM_21 MTC MTC_36 MTC_38 References Clostridium botulinum 2.17 5.81 4.81 3.34 3.02 1.73 5.66 7.03  Pseudomonas fluorescens 5.15 4.25 4.75 5.46 5.82 5.31 3.28 3.22 (Ike et al., 2000) Peptoclostridium difficile 1.26 4.96 4.28 3.76 3.60 1.01 4.44 5.26  Stenotrophomonas maltophilia 6.16 2.27 2.98 5.54 4.68 6.71 2.91 2.87 (Robert S. Dungan et al., 2003) Pseudomonas syringae 4.20 3.60 4.02 4.71 5.04 4.98 2.75 2.52  Rhizobium leguminosarum 8.47 3.34 2.76 3.09 3.17 6.62 3.14 4.03  Bacillus subtilis 2.52 4.82 3.52 2.57 2.20 1.58 4.38 4.62 (Siddique, Zhang, Okeke, & Frankenberger, 2006) Escherichia coli 3.82 3.20 3.16 3.30 3.33 4.23 3.46 3.56  Pseudomonas stutzeri 3.33 3.83 3.90 3.65 4.07 2.18 3.06 2.91 (Ike et al., 2000) Enterococcus faecalis 2.84 4.07 3.16 3.13 2.87 3.10 3.48 3.92  Ralstonia solanacearum 3.19 2.23 2.66 3.08 3.23 3.07 4.75 3.41  Bacillus megaterium 1.58 2.90 1.75 1.34 1.18 1.61 2.54 2.71 (Mishra et al., 2011) Thauera phenylacetica 4.20 0.97 1.51 1.99 2.01 5.34 1.50 1.10  Thauera linaloolentis 4.03 0.95 1.50 2.02 2.08 5.10 1.50 1.18  Thauera sp. 63 4.13 0.99 1.54 2.02 2.02 5.22 1.51 1.06  Pseudomonas alcaligenes 0.00 1.62 2.27 2.86 3.11 0.00 1.37 1.24  Ralstonia sp. GA3-3 3.05 0.75 1.11 1.55 1.72 4.80 1.32 1.16  Enterobacter cloacae 0.95 1.64 1.48 1.45 1.51 0.95 1.63 1.93 (Mark E. Losi & Frankenberger Jr., 1997; Yee, Ma, Dalia, Boonfueng, 90  Microbes GM GM_6 GM_8 GM_17 GM_21 MTC MTC_36 MTC_38 References & Kobayashi, 2007) Nitrosospira sp. APG3 3.43 0.75 1.01 1.34 1.34 4.53 1.09 0.87  Thiobacillus denitrificans 3.19 0.99 1.44 1.74 1.73 0.00 1.50 1.17  Desulfovibrio desulfuricans 1.79 1.60 1.38 1.15 1.16 0.00 1.66 1.63  Pseudomonas nitroreducens 0.00 1.24 1.72 2.18 2.34 0.00 1.05 0.94  Ralstonia sp. AU12-08 0.00 0.85 1.28 1.82 1.92 0.00 1.73 1.28  Veillonella atypica 1.54 1.30 1.08 1.18 1.09 1.88 1.31 1.35 (Pearce et al., 2009) Pseudomonas syringae group genomosp. 3 0.74 1.58 1.26 1.37 1.46 0.98 1.16 1.09  Thauera terpenica 0.00 0.89 1.41 1.88 1.87 0.00 1.42 1.02  Thauera aminoaromatica 2.66 0.59 0.96 1.28 1.27 3.37 0.95 0.65  Geobacillus sp. JF8 0.00 1.62 1.43 1.45 1.27 0.00 1.38 1.43  Rhodobacter sphaeroides 1.05 1.34 1.34 0.86 0.86 1.04 1.58 1.41 (Moore & Kaplan, 1992) Desulfitobacterium sp. PCE1 1.86 1.28 1.19 1.29 1.19 0.00 1.22 1.29  Sulfuricella denitrificans 1.93 1.07 0.77 1.01 1.00 2.36 0.81 1.17  Rhodobacter sp. AKP1 2.80 0.67 0.77 0.98 1.01 2.95 0.82 0.73 (Janine Kessi, 2006) Geobacter metallireducens 1.68 1.03 1.07 0.73 0.68 1.73 1.10 1.03  Serratia fonticola 0.07 0.85 1.04 1.35 1.36 0.06 1.02 1.02 (Knotek-Smith et al., 2006) [Bacillus] selenitireducens 0.00 1.64 1.37 0.06 0.08 0.00 1.30 1.37 (Switzer Blum et al., 1998) Geobacter sulfurreducens 0.00 1.09 0.98 0.70 0.66 0.00 1.12 1.09 (Pearce et al., 2009) 91  Microbes GM GM_6 GM_8 GM_17 GM_21 MTC MTC_36 MTC_38 References Alcaligenes faecalis 0.04 0.99 0.40 0.61 0.66 0.12 0.81 1.39  Shewanella oneidensis 0.00 0.71 0.88 0.96 0.94 0.00 0.76 0.71 (Pearce et al., 2009) Pseudomonas denitrificans 0.00 1.24 1.68 0.02 0.03 0.00 1.03 0.90  Geobacter lovleyi 0.00 0.91 0.96 0.40 0.38 0.00 1.00 0.94  Thauera sp. 27 0.49 0.73 0.21 0.30 0.30 0.69 1.21 0.83   4.7.4 Annotation of sequences to functional categories of KEGG  Figure 25. Different categories of KEGG in samples The sequences from 8 different samples were annotated and visualized in KEGG pathways. After normalizing all datasets with square root normalization method, KEGG metabolism pathways were obtained for various samples (Figure 25). Sequences from enriched samples had higher annotated reads than native soil samples indicating a need to increase sequencing depth for samples with little biomass (most soil samples obtained were hard rocks and coal piles).The following were the sequences annotated: 20182, 71658, 93705, 65180, 92  66462, 27881, 139862, and 116482 from GM, GM_6, GM_8, GM_17, GM_21, MTC, MTC_36 and MTC_38 respectively.  Results from Kegg pathway showed "Metabolism" to be the highest among different categories of pathways across all samples. Although the number of reads annotated in the metabolism category varied among samples, their percentage composition revealed metabolism to be present within similar range (35-41% with higher in native GM and MTC samples). Almost half of the reads in each samples could not be annotated to any category indicating that the resources in metagenomics is still at its infancy.  Within the Metabolism category, Carbohydrate, Energy, and Amino acid Metabolism were the most abundant sub-category across all samples (Figure 26). Genes involved in nitrogen, sulfur and selenium metabolism were most interesting and  relevant for selenium reduction and were considered for further analysis. The native soil samples (GM and MTC) had the lowest hits assigned proportionally to nitrogen and sulfur metabolism category among all samples (Table 20). Among the enriched samples, GM_8, MTC_36 and MTC_38 had the most hits assigned to these categories.   93    Figure 26. Different Sub-categories of metabolism in KEGG pathway  Table 20. Nitrogen and Sulfur metabolism in samples #Series: GM GM_6 GM_8 GM_17 GM_21 MTC MTC_36 MTC_38 Nitrogen metabolism 591 1346 1897 1378 1436 722 3212 2324 Sulfur metabolism 140 372 482 293 310 189 850 695  4.7.4.1 Nitrogen metabolism in samples In the Nitrogen metabolism, four processes were most relevant to our study: Denitrification, Ammonification, Nitrogen fixation and Nitrification. These processes were analyzed in depth in the Kegg pathway by analyzing each reactions and enzymes involved in the process.  For denitrification, the following genes were accounted for the analysis: Nitrate reductase (nar-type gene that codes for enzymes in nitrate reduction to nitrite) that was analyzed through 94  EC 1.7.1.1 and  EC 1.7.99.4, Nitrite reductase (nir-type gene that encodes enzyme for nitrite reduction to nitric oxide) analyzed through EC 1.7.1.1, Nitric oxide reductase (nor-type gene that converts nitric oxide to dinitrogen oxide) analyzed through EC1.7.99.7, and Nitrous oxide reductase (nos-type gene that codes for enzyme that converts nitrous oxide to nitrogen gas) analyzed through EC1.7.99.6. For Ammonification, the following genes were accounted for analysis: Nitrite reductase (nir-type gene that codes for enzyme that reduce nitrite into ammonia) accounted for by EC1.7.1.4, EC1.7.7.1, and EC1.7.2.2 and Hydroxylamine reductase (har-type gene that codes for enzyme that converts hydroxylamine into ammonia). For Nitrogen Fixation enzyme, the following genes were accounted for in the Kegg pathway: Nitrogenase (nif-type gene that codes for enzyme that converts nitrogen gas into ammonia) accounted for by EC1.18.6.1. For Nitrification, the following gene were accounted for analysis: Ammonia monoxygenase (amo-type gene that codes for enzyme that converts ammonia into hydroxylamine) accounted for by EC1.13.12 and Hydroxylamine oxygenase (hao-type gene that codes for enzyme that converts hydroxylamine into nitrite) accounted for by EC1.7.3.4.  The number of hits in the four different processes of nitrogen metabolism that was accounted by different genes in the pathway were used to analyze the abundance in the different samples (Figure 27). For all samples present, denitrification had the highest hits among the four processes followed by ammonificaiton, nitrogen fixation and nitrification respectively. Denitrification accounted for almost 50% (or greater) of the hits associated with the four process used in the nitrogen metabolism in  most samples. The highest denitrificaiton hits was seen for MTC_36 followed by MTC_38 sample while native samples MTC and GM had the lowest hits. Ammonification hits were also abundant in MTC_36 and MTC_38 samples while it was comparably small in all other samples. Nitrogen fixation process had very few hits in GM, GM_6, GM_8, GM_17, GM_21, and MTC samples.  Nitrification hits were almost non-existent in most samples. In the denitrification process, nar-type gene was the most abundant followed by nos-type gene in most samples (Figure 28). This was followed by nor-type gene while nir-type gene was the least abundant in most samples. 95    Figure 27. Hits for Nitrogen metabolism in different samples KEGG 96   Figure 28. Hits for denitrification process in different samples KEGG    4.7.4.2 Sulfur metabolism in samples For "Sulphur Metabolism" analysis in different samples, sequences were annotated to SEED pathway and visualized in Megan using similar steps performed for Nitrogen metabolism in Kegg pathway. Table 21 lists the number of hits assigned to the sulfur metabolism in different samples. The native samples had lower hits assigned while the hits assigned to enriched samples were comparatively higher. The highest number of hits was assigned to MTC_36 from the MTC series while GM_8 had the highest hits from GM series.  97  Table 21. Hits (normalized reads) assigned for Sulphur metabolism in different samples through SEED #Series: GM GM_6 GM_8 GM_17 GM_21 MTC MTC_36 MTC_38 Sulfur metabolism 140 372 482 293 310 189 850 695  Different sub-categories within sulphur metabolism were analyzed in order to evaluate how they might have been involved in selenium reduction (Figure 29). Compared to the enrichments, the number of hits assigned to S metabolism in the native sediment samples were lower for almost all subprocesses. The two processes highly present in most samples were sulphur assimilation and thioredoxin- disulfide reductase. GM_8 from GM series and MTC_36 from MTC series had the highest hits assigned in both processes indicating its importance in selenium metabolism processes as well.  Figure 29. Hits for Sulfur metabolism in different samples SEED   98  4.7.4.3 Putative selenoproteins identified in the samples Using the SEED classification systems, the numbers of hits assigned to selenoproteins were analyzed. The most selenoproteins hits were in the GM_8 sample while MTC_36 and MTC_38 also had comparable number of hits (Table 22). The native soil samples GM and MTC had the least hits assigned to selenoprotein enzyme family. Within selenoprotein category, glycine reductase and selenocysteine metabolism were most prevalent. Table 22. Selenoproteins in the samples #Series: GM GM_6 GM_8 GM_17 GM_21 MTC MTC_36 MTC_38 Selenoproteins 21 151 203 124 128 13 202 182   99  Chapter 5: Discussion 5.1 The potential for selenium-reduction in four mine sediments Selenium is highly concentrated in coal (Yudovich & Ketris, 2006) and mining practices in the Elk River Valley has continually increased the Se concentration in the receiving environment (Dessouki & Ryan, 2010). Moreover, the oxidation and weathering of overburden coal and waste rock in the tailing facilities leads to leaching of compounds including selenium into nearby freshwater. Thus, environments that receive these seepages (leachates) are a good source of selenium-reducing microbes (in anaerobic zones) as microbial community dynamics must favor the establishment of selenium-reducing microbial population.  Although selenium reducing microbes have been isolated from fresh water environments devoid of selenium contamination (Ike et al., 2000), a large number of selenate reducers have been isolated from selenium contaminated environments (Fujita et al., 1997; J. M. Macy et al., 1989; Maiers, Wichlacz, Thompson, & Bruhn, 1988; J F Stolz et al., 1999). As a consequence, fresh sediment samples taken from mine impacted sites were expected to be good sources to test the Se-reduction potential.  In this regard, three sediment samples; Goddard Marsh (GM), Mature Tailings Coal (MTC), and Fresh Tailings Coal (FTC) were taken from Elk River Valley while one sample; Mount Polley ABR (MP) was taken from a pilot-scale biological treatment pond in Mount Polley that received tailings water containing sulphate, nitrate and selenium. The initial screening test showed that all the sediment samples possessed microbes that harbored potential to reduce selenate into elemental selenium. The abiotic control did not change color during the entire duration of the experiment indicating that the reduction was indeed biological. The qualitative screening test ranked the sediment samples on the basis of the fastest appearance of red coloration as GM > MTC > FTC > MP. All the sediment samples exhibited red coloration of elemental selenium within 10 days of inoculation.  Goddard Marsh is a natural marsh that receives seepage from the waste rock piles in the Elk River Valley. The concentration of Se in GM was reported to be 23.7 µgL-1(Martin et al., 2011) in surface water  and 20.5 mg/kg/dw (Teck Coal, 2009) in sediments. This concentration is significantly higher in GM than reference places (unaffected by mining). A recent report by 100  Martin and co-worker reported that the presence of copious vegetation (that provided organic matter for microbial oxidation) in GM dictated the redox condition and hence established anaerobic conditions which favor the presence of reduced forms of Se (Martin et al., 2011). Hence, it is not an overstatement to state that GM harbored microbial population that is well suited to reduction of Se-oxyanions. The change in the color of the growth medium within 3.3 days is an indication that microbes capable of selenate reduction is abundant in GM. MTC and FTC were samples from tailings at the coalmines in the Elk River Valley. Coal mine tailings are also a source of anaerobic microbes as they are sub-surface where conditions are anaerobic and it was expected that microbes adapted to the extreme chemical environment within the tailings with very diverse energy metabolisms including chemolithotrophy, chemotrophy, heterotrophy. Smith and co-worker (2006) found through analysis of sediment samples at Smoky Canyon phosphate mine (Idaho,USA) that increased selenium concentration changed the microbial population across the mining site. This study found that areas of high concentration of selenium particularly favored microbial members from the Enterobacteriaceae family that have high activities in selenium reduction (Knotek-Smith et al., 2006).  Although the microbial communities from MTC and FTC may not be as diverse as the sample from GM (as presence of organic substrate invites microbes activity from diverse communities), the initial screening test did verify that it harbored Se-reducing microbes. It can also be noted that MTC cultures reduced the selenium in the growth medium significantly faster than the FTC. This could have occurred as MTC were aged coal piles and microbial dynamics must have stabilized it towards selenium reducing community. An interesting observation was that Mount Polley samples undertook much longer  for selenate-reduction compared to other samples. This comes as a surprise as the anaerobic biological reactor receives tailings water containing sulphate, nitrate and selenate. A report conducted by SRK consulting for Mount Polley Mining Corporation following the infamous tailing dam breach on 4th August,2014 (resulting in discharge of tailings to Hazeltine Creek) reported that although the concentration of selenium in the tailing sediments were higher (1.5 mg/kg) than the reference values, it was still below the aquatic sediment quality guidelines (SRK, 2014). This means that selenium concentration resulting from mining practices at Mount Polley is significantly lower than that at the Elk River Valley probably as a consequence of the 101  geology of the two sites. Moreover, sulphate concentration measured once a year at this site for a time period of 2010-2014 showed incoming sulphate concentration at 430 to 520 mg/L and total N(total nitrogen) at <5 mg/L during the same period (Baldwin et al., 2015). Since sulphate and nitrate is high compared to selenium at this site, microbial communities must be inclined towards the group that obtain energy from reducing sulphate and nitrate rather than the latter.   5.2 Enrichment of GM and MTC samples at various concentrations of nitrate The enrichment cultures were successful in obtaining microbial consortium from GM and MTC that were tolerant to high concentration of selenate. By making repeated transfer to fresh media with high selenate concentration, microbial consortia were obtained that were able to produce a red precipitate within hours after inoculation. This indicated the formation of amorphous elemental Se, which turned darker in coloration over time. By itself, however, the formation of red coloration does not prove the lone presence of dissimilatory selenate reduction. It is possible that other mechanisms such as volatilization and assimilation also contributed to the removal of selenium as a detoxification mechanism. Nonetheless, serial dilution and transfer of enrichment culture into a corresponding fresh media ensured that the most abundant population (selenate reducers) were selected and enriched in the next culture.  These enrichment cultures were then adapted at various concentrations of nitrate in order to observe if a syntrophic interaction occurred in these microbial consortium. Selenium concentration measured at the end of each round of transfer showed that most cultures were successful in reducing up to 50 percent of the initial selenium. This result was really interesting as reduction of high selenate concentration (5-20 mM) has only been observed in some pure microbial strains. It is possible that the enrichment culture selected  isolates of selenate reducing communities that were tolerant to high selenate concentration. Uninhibited selenium reduction in enrichment cultures adapted to nitrate indicated a that the consortium were unaffected by nitrate concentration. Syntrophic communities that work by interspecies electron transfer are known to occur in methanogenic and sulphate-reducing environment (Stams & Plugge, 2009). Syntrophic communities work through utilization of metabolic products which are otherwise unutilized by 102  their partners. Electron acceptors, selenate and nitrate, commonly found in mining waters are utilized by anaerobic communities to sustain life through anaerobic respiration. Selenate reduction to selenite proceeds through specific reductase such as the selenate reductase (serABC) in Thauerea selenatis (T Krafft et al., 2000; Schröder et al., 1997), and srdBCA in Bacillus selenatarsenatis SF-1(Kuroda et al., 2011). However, non-specific reduction of selenate also occurs through sulfate and nitrate reductases (Lenz et al., 2008; Rege et al., 1999). Moreover, the selenite obtained through reduction of selenate has been found to be reduced by nitrite reductase and possibly by sulfite reductase (or by reacting with hydrogen sulfide) (DeMoll-Decker & Macy, 1993). Thus, a syntrophic interaction can be hypothesized to occur when both, selenate reducers and denitrifiers, communities are present in the media. Alternatively, communities could shift into denitrifying groups that solely catalyzed the reduction of nitrate, while reducing selenate through non-specific reduction. However, it is improbable that such high reduction occurred through non-specific reduction.  5.3 Total selenium and nitrate reduction in GM and MTC enrichments  Use of explosives in mining leads to input of nitrate into the receiving water. Some affects of nitrate in the water bodies are eutrophication, algae blooms and emissions of greenhouse gases like N2O (Rabalais, 2002). In addition, the presence of nitrate in the microbial treatment of selenium containing wastewater (including mining wastewater) can cause inhibition of Se(VI) reduction to Se(IV) by acting as a competitive electron acceptor (Masscheleyn & Patrick, 1993; Steinberg et al., 1992; John F. Stolz & Oremland, 1999). This competitive inhibition of Se(VI) reduction occurs due to higher redox potential of NO3-/N2 pair as well as the higher concentration of nitrate relative to Se(VI) (Masscheleyn & Patrick, 1993).  In the GM 0 mM NO3- inoculum, reduction of selenate proceeded concomitantly with reduction of nitrate in all cultures. There was no lag phase observed in the reduction of selenate which possibly indicates the presence of constitutive selenate reductase. Constitutive selenate reductase has been observed in Sulfurospirillum barnesii  cells grown in nitrate (Ronald S. Oremland et al., 1999). However, the selenate reductase in S. barnesii has not been characterized or sequenced. Moreover, taxonomic assignment of metagenomic sequences in GM 0 mM NO3- 103  cultures showed no presence of S. barnesii which  possibly indicates that other taxonomic species responsible for selenium reduction also possessed constitutive selenate reductase. Anova analysis of the CCD experiment, with GM 0 mM NO3- inoculum, using extent of Se reduction over 14 days as response revealed a two-fold affect of nitrate dependent on  selenium concentration. At low concentrations of selenium, high nitrate concentration was inhibitory whereas at high concentration of selenium the inhibitory affect of nitrate was reversed. The inhibitory affect of nitrate at low selenium concentration (1-2 mg/L) has been observed by numerous researchers working in selenium bioremediation. Steinberg et al. (1992) reported on preferential reduction of nitrate before selenate with anaerobic freshwater enrichment containing 20 mM each of nitrate and selenate (Steinberg et al., 1992). Zhang and Frankenberger (2003), in an experiment performed using rice straw as carbon source, reported an inhibition in the Se(VI) reduction when nitrate was present in high concentration (500 mg/L) (Zhang & Frankenberger, 2003). Furthermore, higher concentration of nitrate (above 100 mg/L) increased the duration for the reduction of selenate and it was found that selenate reduction occurred only when nitrate was completely eliminated from the system. An interesting observation was the increase in the redox potential of the sample (33 mV) with high nitrate concentration (500 mg/L). Similar observation was also seen when a selenium reducing microbe; Enterobacter taylorae, was used in an agricultural drainage water to assess the effect of nitrate among other factors in the reduction of Se(VI) to Se(0) (Zhang, Zahir, & Frankenberger, 2003). Low level of nitrate (5-50 mg/L) did not affect Se(VI) reduction whereas higher nitrate concentration (100 mg/L) decreased both the extent and rate of reaction. The Se concentration used by these authors (1 mg Se/L) corresponded to the low Se values used in our experiment and their observation of nitrate inhibition at high concentration of nitrate was similar to the observation seen through the ANOVA analysis. In contrast, stimulatory affect of nitrate was observed with high initial Se present in the media. This indicates that nitrate presence complicates the response of the cells depending on the concentration of Se. It may be possible that nitrate's presence as an electron acceptor results in the ability of cells to maintain high state of metabolic activity as observed by Oremland and co-worker (Ronald S. Oremland et al., 1999). As reduction of selenate results in the production of selenite oxyanion, which is several times more toxic to cells, the nitrate presence may help cell to obtain energy and resources to help eliminate selenite from the system by either reducing it to 104  elemental selenium or by assimilating it into seleno-proteins. This may explain the highest selenate reduction observed in case of run order 8 which had the highest nitrate concentration (120 mg-N/L) and a relatively high selenate concentration (9.6 mg/L).  ANOVA analysis using rate constant as the response variable indicated no affect of nitrate on Se reduction rate and showed the initial total Se concentration to be the most significant factor in Se reduction rate. This result is in confirmity to the one obtained for CCD analysis with extent of Se reduction as the response variable (in high initial Se concentration). However, rate constant is a better response variable than extent of Se reduction. This is because different factors could affect the extent of reduction unlike rate constant which was calculated using the initial points in the time-curve of Se reduction. Thus, overall no affect of nitrate was observed in the GM 0 mM NO3- inoculated samples. In the experiment performed with Goddard Marsh sediment enriched with selenate and 8 mM nitrate, we observed continuous increase of total selenium in almost all run orders. This increase in selenium concentration might have occurred through the re-solubilization and oxidation of elemental selenium present in the inoculum. Although several attempts were made to dissociate the elemental selenium present in the biomass, such as by addition of triton-X as a detergent, it was difficult to separate it from the biomass cells. Cells  treated with triton-X failed to survive in subsequent cultures even when exposed to a less concentrated selenium culture of  10 mgL-1. This meant that selenium preciptates were either attached to the cell surface or were inside the cell or close to membrane periphery due to which it lost viability when separated from the precipitate. Elemental selenium precipitate, obtained as a result of microbial selenate reduction, has been reported to occur both in the cytoplasm (TOMEI et al., 1992; Francisco A. Tomei et al., 1995) and outside the cell (Mark E. Losi & Frankenberger Jr., 1997). Although T. selenatis has specific proteins involved in the export of the elemental selenium outside the cell (Debieux et al., 2011), in the absence of such specialized mechanism the only way to release elemental selenium outside the cell is through cell lysis (Francisco A. Tomei et al., 1995) or having a membrane reductase and a efflux pump close to the cell membrane (Mark E. Losi & Frankenberger Jr., 1997). Thus, no further attempts were made to separate precipitate from the biomass and all inoculums contained elemental selenium precipitate from previous enrichment culture. Thus, it is hypothesized that selenium release from the inoculated GM 8 mM NO3- 105  biomass occurred and this accounts for the observed increases in total dissolved Se concentrations in the early part of this experiment.  The oxidation of elemental selenium may have occurred as high nitrate concentration can increase the redox potential of the media (Zhang & Frankenberger, 2003). Oxidation  of precipitated elemental selenium was also observed by Oremland and co-worker when experimenting in selenate reduction with anaerobic sediments from San Joaquin Valley's evaporation pond (R S Oremland et al., 1989). However, very little selenium was oxidized and he attributed this oxidation to the fact that nitrate acts as a competitive electron acceptor. Furthermore, free energy calculation for the oxidation of elemental selenium by nitrate supports this hypothesis in theory (              ) (Wright, 1999). Thus, nitrate can act as a electron acceptor in the oxidation of reduced selenium species (e.g. elemental selenium). In addition, it is possible that Se oxidation occurs through biotic means. Many authors have reported that the oxidation of elemental selenium is largely biotic and occurs at a relatively lower rate (Dowdle & Oremland, 1998; M. E. Losi & Frankenberger, 1998). Thus, although reduction of solubilized elemental selenium occurred in some run orders in later stages, the oxidation of elemental selenium was observed in most culture bottles. In the experiment performed with Mature Tailing Coal enriched with selenate and 4 mM nitrate, most samples reduced Se continuously until day 14. Although ANOVA could not be performed due to high initial Se present (different than that planned in the CCD) in the media (probably as a result of oxidation of elemental Se in the inoculum), most cultures were successful in reducing initial Se by 30-60%. In addition, no significant inhibition of nitrate was observed in the concentrations tested. Extent of reduction as well as rate of reduction were comparable in run orders with low (run 1,2,7) and high nitrate (3,4,8). Despite, high selenium concentration, these samples were able to reduce selenium significantly. With respect to the inoculums and based on the above experiments, GM enrichment with no nitrate (GM 0 mM NO3-) performed the best Se reduction  without inhibition of nitrate. Although Se reduction was also observed for MTC enrichment with moderate nitrate (cultures inoculated with MTC 4 mM NO3-), the extent of Se reduction as well as the reduction rate was lower than GM enrichments with no nitrate. GM enrichment with high nitrate (8 mM NO3-) performed the least reduction of all inoculums. Moreover, oxidation of dissolved Se, present in 106  the inoculum, was observed. This indicated that addition of nitrate in the enrichment culture should be avoided as it could promote microbes/ mechanisms by which precipitated elemental Se may oxidize during the later passage. 5.4 Q-PCR of GM enrichments The use of Q-PCR techniques to quickly discern the selenium reducing microbes from the denitrifying population is an important step in the development of specific tools for bioremediation of selenium oxyanions in both active and passive bioreactors. Although denitrifying population are regularly quantified through the use of specific genes (molecular marker) in the denitrification process, the quantification of selenium reducing microbes using specific selenate reductase enzyme has not been performed so far.  To date, selenate reductase enzyme has been reported in two gram-negative microbes; Enterobacter cloacae SLD1a-1(Ridley et al., 2006) and Thauera selenatis (Torsten Krafft, Bowen, Theis, & Macy, 2000; Schröder et al., 1997) and only one gram-positive microbe; Bacillus selenatarsenatis SF-1(Kuroda et al., 2011). While the selenate reductase of E.cloacae and B. selenatarsenatis SF-1is membrane-bound, the selenate reductase enzyme in Thauera selenatis is periplasmic (Watts et al., 2005). Due to the physiological and sequential diversity of selenate reductase enzyme expressed in phylogenetically diverse selenate reducing bacteria, a universal primer targeting all selenate reducing microbes could not be designed. Consequently, the periplasmic selenate reductase enzyme from Thauera selenatis was chosen as a target gene for the quantitative-PCR reaction to quantify selenate reducing microbes in our study. However, we are aware of the fact that other membrane bound and periplasmic selenate reductase from identified as well as unidentified microbes is missed in this process.  Compared to selenate reductase enzyme (encoded by serA gene), denitrifying population are monitored regularly by targeting nitrite reductase and nitrous oxide reductase genes from the denitrifying process. Two structurally different nitrite reductase encoded by nirK gene and nirS gene along with nitrous oxide reductase encoded by nosZ gene have been used in the literature to quantify denitrifying population (Henry et al., 2004; Warneke et al., 2011). The reduction of nitrite to nitrous oxide is performed by nitrite reductase genes: nirK that encodes a copper containing nitrite reductase and nirS gene that encodes cytochrome cd1-containing nitrite reductase (Zumft, 1997). Due to technical difficulty, nirS gene could not be included in the Q-107  PCR assay for our samples. Thus, only nirK primers were used in the Q-PCR for amplifying denitrifiers in the samples that contained only copper containing nitrite reductase. Both serA and nirk genes were quantified in all run order of GM 0 mM NO3- inoculants. Amplification of serA and nirk in most cultures were representative of the selenium and nitrate reduction in different cultures. SerA and nirK varied widely in all run orders and did not correlate well with the extent or the rate of  selenium reduction. However, correlation of serA with the initial Se concentration was observed. One possibility for this observation may be that selenate reductase induction and expression may be related to the Se concentration in the media. Along with serA based reduction,  other mechanisms/genes may have been prevalent for selenium reduction in the cultures. Various enzymes are responsible for selenium reduction in different microbial communities. However, a robust method for detection of selenium reducers (like T. selenatis)   has been developed which can easily be applied to bioreactors treating selenium. The failure to include both nirK and nirS did impact our studies as all denitrifiers could not be quantified.   5.5 Comparison of selenium reduction by enrichment and native sediment samples Selection of the appropriate inoculum to use for selenium reduction bioprocesses on a mine site is important since there are great differences in the Se reduction rate and extent depending on where the seed microorganisms came from. The environmental parameters within and around the sediment, such as the presence of organic matter, chemistry, exposure to mine drainage and so on determines the type of microorganism present. Both of the sites used to source inoculum for this experiment are impacted by mine drainage since they are located downstream of large waste rock piles. However, Goddard Marsh contains vegetation, whereas the mature tailings coal came from a tailings storage facility with no macro vegetation. This resulted in some differences in their potential to reduce selenium and nitrate, as discussed below: The native Goddard March sediments achieved the highest Se reduction rates and the greatest extent of Se reduction. One major difference between Goddard Marsh and the Mature Tailings Coal was the presence of copious vegetation at the former site. Martin and co-worker (2011) recently reported that the lower redox condition, which ultimately favors selenium reducing microbes, at GM was due to the presence of copious vegetation around that site which 108  provided unrestricted carbon source to the microbes thriving in that place (Martin et al., 2011). Therefore, one reason for greater selenate reduction by the Goddard Marsh sediments might be the presence of a wider diversity of microorganisms due to unrestricted supply of organic carbon from decaying vegetation. Selenate reducers were present in both sediments, but those coming from Goddard Marsh may have been more abundant or more diverse. Total Se concentrations were still decreasing at the end of the experiment in the Mature Tailings Coal cultures and Se reduction might have reached the same levels as those seen in the Goddard Marsh cultures had the experiment been conducted for longer.  Neither native sediment was able to completely reduce nitrate, suggesting that denitrifying bacteria were not well represented in the native microbial populations. It is possible that freshly stimulating native sediment samples with high selenium containing media prior to the inoculation might have enriched selenium reducers rather than denitrifiers in both native sediment samples (GM and MTC). The enrichment cultures performed poorly with respect to selenium reduction compared with the native sediments. Selenium introduced into the cultures with the inoculant may have interfered with the ability to measure Se reduction, and release of elemental Se from the biomass into solution might explain the increase in Se concentration seen for the Mature Tailings Coal enrichment cultures. Both of the enrichment cultures were much more successful at reducing nitrate. Presence of nitrate, in addition to selenate, might have shifted the microbial population towards denitrifies preferentially. This is furthermore confirmed by the presence of abundant Pseudomonas in the metagenomic sequences of the enrichment culture relative to native sediments. Moreover, as the inoculants for both the enrichment cultures were taken at the end of the previous experiment, it is possible that the microbial community shifted towards denitrifying communities rather than selenate reducing community. It seems that fresh inoculant addition is necessary for successfully reducing selenium in each cycle of operation. It was possible that the microbial community composition changed over the duration of the experiment with increasing prevalence of denitrifiers and decreasing prevalence of selenate-reducers. When the final culture taken at the end of a run was inoculated into fresh growth medium with selenate and nitrate, the selenate-reducers were not as prevalent or active as in the previous culture. This might explain one reason for decrease in the performance of bioreactors treating both selenium and nitrate. 109  Bioaugmentation with fresh inoculum containing selenate-reducers from a source such as Goddard Marsh periodically during operation might be useful in solving these issue in bioreactors.  Selenium reduction rate, calculated for various inoculants, was highest in GM soil samples. Within the GM soil samples, reduction rate was observed to be highest (0.76 mg. (L.day)-1  for sample with 60 mg N/L nitrate. This reduction is about 2-2.5 times higher than that determined for different microbes using molasses as the carbon source (Zhang, Okeke, & Frankenberger, 2008). The reduction rate for Enterobacter taylorae was determined to be 0.33 mg. (L.day)-1 (using 0.33 d-1 as rate constant value which was their highest value). However, Wan and co-worker found a selenite reduction rate of 3.6 mg. (L.day)-1  (about 5 times higher using 0.15 mg. (Lh)-1 as their data) using mixed microbes from chemostat culture (Wan, Hao, Fellow, & Kim, 2001).  Furthermore, our rate is comparable to acclimatized denitrifying sludge treating selenium-containing wastewater [calculated as ~1 mg. (L.day)-1] (Takada et al., 2008). Similarly, the reduction rate decreased for GM sediment samples when nitrate was increased to a concentration of 100 mg N/L indicating slight inhibition of nitrate for soil samples at this concentration. Similar inhibition of sediment samples at high concentration of nitrate have been obtained by various researchers (Fujita et al., 1997). Zhang and Frankenberger (2003) observed selenium reduction inhibition at nitrate concentration of 500 mg/L and found no reduction of selenium until day 14 when all the nitrate was removed from the bottles (Zhang & Frankenberger, 2003). Wan and co-worker (2001) also observed significant affect in selenite reduction when nitrate was present at high molar excess(Wan et al., 2001). Similarly, Zhang and co-worker also observed slight inhibition in selenium reduction with Enterobacter taylorae when nitrate was present at 100 mg/L(Zhang et al., 2003). Although GM enriched samples were stimulated by higher nitrate concentration, higher nitrate concentration inhibited GM sediments which meant GM sediment enriched selenium reducers while GM enrichment might have selected denitrifiers preferentially.   110  5.6 Metagenomic analysis of enrichment and native sediment samples Similar microbial communities and pathways (or genes) resulted in the reduction of soluble Se oxyanion (selenate) into elemental selenium and nitrate into gaseous products (N2O or N2) in different samples. The clustering of samples into three groups, as seen in the PCoA diagram, resulted from the different taxonomic composition in the samples. Both native sediments, MTC and GM, were more diverse than the enriched cultures. However, native sediment MTC was very different than rest of the samples. Although, MTC was similar to GM at the phylum level, some differences were significant at the genus level. MTC had higher number of reads assigned to Acinetobacter, Vibrio, and Pseudoalteromonas. These differences can be attributed to the different environmental conditions at these sites. As described in section 5.1, the presence of copious vegetation around GM site resulted in more microbial activity than at MTC. Moreover, the enrichment cultures with GM 0 mM NO3- inoculum: Gm_6 and GM_8 were in the same cluster as MTC 4 mM NO3- inoculum: MTC_36 and MTC_38. Interestingly, enrichments with GM 8 mM NO3- inoculum: GM_17 and GM_21 were similar to native GM sediments. These differences may be a result of the environmental parameters (selenium and nitrate concentrations) these cultures were exposed to. This indicates that even with all other parameters constant, selenium and nitrate concentrations are enough to change the microbial composition of the culture. Between samples from the same enrichment with high (GM_8, GM_17,  and MTC_38) and low (GM_6, GM_21, and MTC_36 ) extent of selenium reduction, a notable difference in taxonomic composition was not inferred. This is because taxa that were present in high selenate reducing group will also be present in low selenate reducing group to certain extent as they came from the same inoculum. However, notable difference in the percentage composition of taxa between native soil and enriched samples were observed. Proteobacteria and Actinobacteria were more dominant phylum observed in native samples (GM and MTC), whereas Proteobacteria and Firmicutes were more prevalent in enriched samples.  Based on the literature, many selenium-reducing microbes are classified within the phylum Proteobacteria. In particular members of the Beta, Gamma, and Epsilon- Proteobacteria are known to use selenate as terminal electron acceptor in anaerobic respiration (John F Stolz et al., 2006). Gammaproteobacteria have been known to couple growth through oxidation of 111  versatile carbon source; including aliphatic (acetate,lactate), and aromatic (benzoate), to the reduction of selenate(Knight et al., 2002; Narasingarao & Häggblom, 2007). Some members of the class Gammaproteobacteria that couple growth to the  reduction of selenium include Enterobacter cloacae SLD1a-1(Mark E. Losi & Frankenberger Jr., 1997), Pseudomonas stutzeri (Narasingarao & Häggblom, 2007), Sedimenticola selenatireducens(Knight et al., 2002; Narasingarao & Häggblom, 2006, 2007),and Shewanella oneidensis (Klonowska, Heulin, & Vermeglio, 2005).All except Sedimenticola selenatireducens were observed in our samples. Several species belonging to the class of Betaproteobacteria were also observed in our samples. Thauera selenatis is the most studied member of this group (J. M. Macy et al., 1993). Although this specific species was not observed, several others that belong to the genus Thauera were observed. Firmicutes were significantly more prevalent in enriched rather than in the native samples. Several selenate reducing members from the genus Bacillus and Clostridium are known to reduce selenium. These include Bacillus arseniciselenatis (Switzer Blum et al., 1998), Bacillus beveridgei (Baesman, Stolz, Kulp, & Oremland, 2009), Bacillus cereus (Dhanjal & Cameotra, 2010), Bacillus selenitireducens (Switzer Blum et al., 1998), and Clostridium species (Bao, Huang, Hu, H??ggblom, & Zhu, 2013). Bacillus cereus was the most abundant species while several species belonging to Clostridium were also observed. Moreover, Bacillus selenitireducens was also observed (0.06-1.64%) in the enriched samples (not present in the native samples at all). Siddique and co-worker (2005) also observed Bacillus strain to be the predominant taxa while characterizing sediment bacteria involved in selenium reduction (Siddique et al., 2006). The author mentioned Bacillus subtilis to be involved in selenate reduction to elemental selenium. This species was predominantly found in all of our samples (native and enrichment).  Thus in the present research,  phylogenetically diverse group of taxa, potentially involved in selenium reduction, was observed in different sample. Moreover, bioassesment of native soil samples indicated the presence of several selenate reducing taxa which indicated that the native soil samples could be stimulated and used as an inoculum in bioreactors. Several species of Thauera, known species of which have high potentiality for reduction of selenium oxyanions were unobserved in enriched sample, but were present in native sediment samples. Moreover species like Stenotrophomonas maltophilia (Robert S. Dungan et al., 2003), Pseudomonas 112  fluorescens (Ike et al., 2000), as well as Rhodobacter sp.(Janine Kessi, 2006; Moore & Kaplan, 1992) were more abundant in native sediment samples (both GM and MTC) than in enrichments. This potentially described why native soil samples performed better selenium reduction in the batch experiment (section 4.6). A lot of enrichments favored Pseudomonas over other taxa. Pseudomonas is known to perform selenate reduction through non-specific oxidoreductase present in their genome (example nitrate, nitrite reductase). However some author have pointed to high selenium reduction by some members of Pseudomonas including Pseudomonas fluorescens and Pseudomonas stutzeri (Ike et al., 2000). Nevertheless, Pseudomonas seems to reduce selenium through non-specific reductase and the resultant selenium reduction may be lower than species with specific selenate reductase. This observation provided evidence as to why enriched samples preferentially reduced nitrate over selenium in the reaction. The presence of Pseudomonas in both GM 0 mM NO3- and GM 8 mM NO3- inoculated cultures may be the result of exposing these enrichments to high nitrate condition and extracting the DNA at the end of the 14th day when more denitrifiers may be prevalent. It seems that microbial composition changed with the change in the concentration of selenium and nitrate at different time points. A change in the microbial communities can be hypothesized to occur either with the change in the environmental condition or with the competition between microbial species. Either way, this selects the best communities that can adapt to the environmental situation provided by the reactor. Furthermore, co-existence of communities is important for the long term stability of the reactor as indigenous microbes can easily outcompete and exclude specialized microbes from the reactor. One important hypothesis that could be made regarding this is that species relating closely to a particular microbe will co-occur with other closely related taxa while it will exclude others from distant taxa. This should be the principal theory behind selection of appropriate microbial species for selenium treatment in bioreactor. Such observations have also been made by some authors in the past (Ju & Zhang, 2014). In this regard, we observed that Pseudomonas and Actinobacteria genera, which were more prevalent in native soil samples, should be selected for use in bioreactor so as to minimize out-competition with other microbial species. This information from metagenomic study will be useful to not just select the right candidate for selenium reduction in bioreactor but to also minimize out-competition that is usually associated with using specific microbe in a bioreactor. 113  The functional category of metabolism based on KEGG and SEED metabolism allowed us to observe different relevant processes in the selenium reduction. Although selenate reductase could not be observed due to little knowledge available in the literature, other processes that occurred along with this were equally important. Two process that are of paramount importance were analyzed in this study: Nitrate metabolism and Sulfur metabolism. Both of these process impact selenete reduction as certain pathways are shared along the metabolism of these electron acceptors. In fact previously, selenate reduction was believed to occur through sulphate reductase of sulfur reducing microbes (Lenz et al., 2008). However, the efficiency and specificity of these enzyme for selenate reduction is usually low.  Denitrification was the most the important process observed in most samples as high number of reads were assigned to this process. Along with this, sulfate reductase (thioredoxin reductase) also seem to be important process in the metabolism of selenium compounds. The selenoprotein genes were also highly present in enriched samples compared to native soil samples as indicated by the high number of hits assigned to this process. Overall, denitrification, sulfate reduction, as well as selenium assimilation through selenocyteine enzyme formation seems to be important process in the metabolism of selenium.               114  Chapter 6: Conclusions and future work This thesis studied the influence of nitrate on selenium reduction by native sediments and enrichment cultures. The following conclusions can be made based on the results obtained: Local mine-impacted sediments can be used as cheaply and freely available sources of inoculum for selenium reduction. Moreover indigenous bacteria are apt for treatment of mine influenced water as they will not face out-competition.  Enrichment with high selenium and no nitrate was the best selection strategy for enrichment of selenium reducers as addition of high concentration of nitrate in the enrichment cultures allowed denitrifiers to outcompete selenium reducers as well as provided mechanism for oxidation of precipitated elemental selenium. It was possible to obtain an enrichment culture that was unaffected by nitrate in the growth medium. Selenium reduction without any lag period indicated possibility of constitutive selenate reductase or a specialized reductase specific for selenate reduction. Selenium reducers were quantified with serA genes and this correlated well with the initial Se concentration in the growth medium. Highest extent of selenium reduction in the culture with high nitrate concentration indicated that nitrate may have stimulated selenium reduction in this case. Bio-stimulated native sediment may be more suitable for selenium reduction as the selenium reduction potential in the enrichment culture decreased over time with changing environmental parameters. This probably was due to subsequent changes in the microbial composition induced by high nitrate in the medium. Metagenomic sequencing revealed important microbial groups as well as pathways relevant to selenium reduction. Numerous bacterial communities with diverse functions occurred in the culture that may have been involved in selenium and nitrate reduction. Many putative selenium reducers were identified in the cultures and the pathways relevant to selenium reduction was studied.  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Extracted elemental Se       A B  A C D 136  Appendix B  Statistical analysis of GM 0 mM NO3-  inoculated culture B.1 Effect of summary using percentage reduction as response variable Table 23. Summary of effect using percentage reduction as response variable Source LogWorth  PValue  Selenium*Selenium 2.735  0.00184  Selenium*Nitrate 1.785  0.01640  Selenium 1.545  0.02849 ^ Nitrate*Nitrate 0.533  0.29310  Nitrate 0.224  0.59724 ^   B.2 Actual by predicted plot, RMSE  Figure 31. RMSE for GM 0 mM NO3- cultures using extent of reduction as response variable       137  B.3 Prediction profile  Figure 32. Prediction profile for extent of reduction in GM 0 mM NO3- cultures  B.4 Interaction Plots  Figure 33. Interaction plots for extent of Se reduction    138  B.5 Effect of summary using rate constant as response variable  Table 24. Summary of effect using rate constant as response variable Source LogWorth  PValue  Selenium 3.020  0.00096  Selenium*Selenium 2.100  0.00794  Selenium*Nitrate 0.504  0.31306  Nitrate*Nitrate 0.192  0.64282  Nitrate 0.175  0.66771 ^  B.6 Actual by predicted plot, RMSE   Figure 34. RMSE for GM 0 mM NO3- cultures using rate constant as response variable  139  B.7 Prediction profile  Figure 35. Prediction profile for rate constant in GM 0 mM NO3- cultures               140  Appendix C  Metagenomic sequence analysis C.1 Protocols used  -Unzip sequence file using the following command:   unzip filename.zip -d~/another/folder  - Check the quality of the sequences in fastqc program  - Quality scores should be above 20. usually quality of calls in most platform goes down   as run progresses.  - When quality score below 20 use the following quality filtering command  /Users/jontaylor/Downloads/bin/fastq_quality_filter -q20  -p90 -Q33 -    iinputssequence.fastq -ooutputsequence_filter.fastq  - Use assember (velvet) with following command  velveth out-dirGM_8-15[give any file name] 31[this is the kmer hash length] -  fastq -shortPaired left.fastq right.fastq  -Use velvetg with:  velvetg out-dirGM_21-17(or the folder that you created with velveth) -exp_cov auto -  ins_length 500  -Use metavelvet with:  metavelvet(location)   out-dir [folder location] -ins_length 500 | tee logfile  - assembled sequences can be run in Metapathways.  -Output from Metapathways can be used in Megan. 141   Figure 36. Quality score of sequence generated from FastQC  142  C.2 Nitrogen metabolism KEGG  Figure 37. Nitrogen metabolism of different samples in the following order: GM, GM_6, GM_8, GM_17, GM_21, MTC, MTC_36, and MTC_38 143  C.3 Sulfur metabolism KEGG  Figure 38. Sulfur metabolism of different samples in the following order: GM, GM_6, GM_8, GM_17, GM_21, MTC, MTC_36, and MTC_38        

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