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2017 Characterizing and Accelerating Methanogenic Hydrocarbon Biodegradation

Toth, Courtney

Toth, C. (2017). Characterizing and Accelerating Methanogenic Hydrocarbon Biodegradation (Unpublished doctoral thesis). University of Calgary, Calgary, AB. doi:10.11575/PRISM/25297 http://hdl.handle.net/11023/3980 doctoral thesis

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UNIVERSITY OF CALGARY

Characterizing and Accelerating Methanogenic Hydrocarbon Biodegradation

Courtney Rose Afton Toth

A THESIS

SUBMITTED TO THE FACULTY OF GRADUATE STUDIES

IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE

DEGREE OF DOCTOR OF PHILOSOPHY

GRADUATE PROGRAM IN BIOLOGICAL SCIENCES

CALGARY, ALBERTA

JULY, 2017

Abstract

Microbial transformation of hydrocarbons to methane is an environmentally relevant but slow process taking place in a wide variety of electron acceptor-depleted environments, from oil reservoirs and coal deposits, to contaminated groundwater and deep sediments. Despite the prevalence of chemical evidence demonstrating methanogenic hydrocarbon metabolism in field investigations, there are significant gaps in our understanding of the anaerobic activation mechanisms of model substrates (particularly monoaromatic and polycyclic aromatic hydrocarbons, PAHs) and whole crude oil, as well as the degradation pathways and microorganisms governing oil transformation to methane. By studying the chemical and functional responses of methanogenic consortia to enrichment on model and mixed hydrocarbon substrates, we can gain a more complete understanding of the fate of hydrocarbon components in electron acceptor-depleted environments. In this dissertation, we sought to characterize the biodegradation of an expanded range of hydrocarbon substrates using a series of chemical and molecular approaches. We also explored cultivation-based strategies for optimizing rates of methanogenic hydrocarbon utilization, of which the most successful methods were adopted for future cultivation studies described here. Members of the Desulfosporosinus genus, known to catalyze methanogenic toluene biodegradation, were also found to co-metabolize other alkylbenzene substrates. Other members of the Firmicutes phylum, such as Desulfotomaculum, were shown to be functionally capable of activating toluene by addition to fumarate in a crude oil-degrading produced water consortium, and are proposed to play a key role in the formation of heavy oil in petroleum reservoirs. Microbial community sequencing, DNA-based stable isotope probing, and metagenomic surveys of previously established and novel methanogenic PAH- degrading cultures suggest that Clostridium may be important for degrading larger aromatic

structures by an unknown mechanism. Experimental evidence of a hypothetical energy conservation mechanism in Syntrophus was detected during alkylbenzene biodegradation, suggesting this organism plays a vital role in coordinating syntrophic hydrocarbon biodegradation in a bioenergetically favourable manner. In all, this research has gleaned new insights into the microorganisms and metabolic processes regulating methanogenic hydrocarbon biodegradation, and has produced a wealth of new research questions to be explored in future investigations.

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Acknowledgements

I find it surreal having reached the end of my graduate student career. Admittedly, I had grown quite content living day by day as a perpetual student, with no real concern for the future.

As I reflect upon these past years, however, I find comfort in knowing that I have all the tools I need to dive into the next chapter of my life head-first, ready and eager, and will always have the support of a close-knit group of friends, family and colleagues. As cliché as it sounds, I struggle to find words expressing my gratitude.

I begin by offering my sincerest thanks to my supervisor, mentor, and friend, Dr. Lisa

Gieg. I am truly inspired by everything you do. Though I will always credit you for helping me reach my (academic) potential, perhaps more importantly, your guidance has also helped to remind me to live life to the fullest. Thank you to my supervisory committee members Dr. Gerrit

Voordouw and Dr. Peter Dunfield for your invaluable advisement and assessment of my doctoral research, and to my external examiners Dr. Elizabeth Edwards and Dr. Steve Larter for your thoughtful feedback that has helped to improve this dissertation. Also, thank you to Dr. Marc

Strous and Dr. Douglas Storey for chairing my candidacy examination – I learned more about myself in those few weeks than I had in as many years. To the aptly named ‘Giegers,’ past and present, thank you for enriching my graduate student experience with your warmth and wisdom.

To the latter, I ask that you continue the traditions of laboratory shenanigans (in a safe manner) and to welcome incoming lab members with open arms. I’d like to give special recognition to Dr.

Jane Fowler, Dr. Carolina Berdugo-Clavijo, and Dr. Sandra Wilson, who patiently trained and supported me throughout my graduate studies – you are the real MVPs and friends for life. I would also like to personally recognize and thank former student-turned-technician Corynne

O’Farrell for her outstanding contributions supporting my research. Thank you to the Petroleum

Microbiology Research Group, the Energy Bioengineering and Geomicrobiology Research

Group, and the research team of Dr. Peter Dunfield for your mentorship and comradery during my graduate studies – it has been an absolute pleasure working and collaborating with you.

To Jaspreet and Jessica, I am so proud of the women you’ve become and am forever grateful for having taken this journey through graduate school with you. To my dearest friend

Lindsay – thank you for your unwavering friendship, your endless enthusiasm, and for always having time for tea. To Sean, Iain, and all patrons of ‘Whiskey Friday,’ I can’t thank you enough for all the laughs and adventures we’ve shared, and I hope there are more to come. Last, but first in my heart, thank you to my family who fostered my sense of wonder and for supporting me through many, many, years of post-secondary education. Cameron and Al – I couldn’t have done this without you.

Dedication

For Lisa,

Great leaders don’t tell you what to do;

They show you how it’s done.

Table of Contents

Abstract ...... ii Acknowledgements ...... iv Dedication ...... vi Table of Contents ...... vii List of Tables ...... xii List of Figures and Illustrations ...... xv List of Symbols, Abbreviations and Nomenclature ...... xxii Epigraph ...... xxiv

CHAPTER ONE: LITERATURE REVIEW ...... 1 1.1 Introduction ...... 1 1.2 Bioenergetic considerations of anaerobic hydrocarbon biodegradation ...... 3 1.3 Methanogenic hydrocarbon biodegradation – An overview ...... 6 1.4 Pathways of anaerobic hydrocarbon biodegradation ...... 13 1.4.1 Initial activation mechanisms ...... 13 1.4.1.1 Fumarate addition ...... 13 1.4.1.2 Hydroxylation ...... 15 1.4.1.3 Carboxylation ...... 17 1.4.1.4 Methylation ...... 19 1.4.2 Pathways following initial activation ...... 20 1.5 Tools for assessing anaerobic hydrocarbon biodegradation ...... 21 1.5.1 Geochemical monitoring ...... 22 1.5.2 Hydrocarbon metabolite analysis ...... 23 1.5.3 Molecular microbial analysis ...... 25 1.5.4 Biodegradative gene analysis ...... 27 1.5.5 Compound-specific/stable isotope analysis ...... 28 1.6 Research needs ...... 30

CHAPTER TWO: RESEARCH OBJECTIVES AND THESIS OVERVIEW ...... 33 2.1 Research objectives ...... 33 2.2 Organization of dissertation and contributions of co-authors ...... 34

CHAPTER THREE: SUMMARY OF COMMONLY USED MATERIALS AND METHODS ...... 39 3.1 Enrichment culture inoculum description ...... 39 3.1.1 TOLDC ...... 39 3.1.2 2MNDC, NDC, and 26DMNDC ...... 41 3.1.3 PHDC ...... 43 3.1.4 MHGC produced water ...... 43 3.1.5 Oil sands enrichment culture ...... 44 3.2 Cultivation parameters ...... 45 3.2.1 Growth media and cultivation strategies ...... 45 3.2.2 BTEX amendment ...... 48

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3.2.3 Alkane amendment ...... 49 3.2.4 PAH amendment ...... 49 3.3 Analytical procedures ...... 49 3.3.1 Methane measurements ...... 50 3.3.2 Hydrocarbon measurements ...... 51 3.3.3 Hydrocarbon metabolite extraction, identification and quantification ...... 51 3.4 Microbial community analysis ...... 55 3.4.1 DNA extraction ...... 55 3.4.2 16S rRNA amplification and sequencing ...... 56 3.4.2.1 Illumina MiSeq technology ...... 56 3.4.2.2 454 pyrosequencing ...... 57 3.4.3 16S rRNA gene sequencing analysis ...... 58 3.4.3.1 Assembly of Illumina reads (QIIME) ...... 58 3.4.3.2 Assembly of 454 pyrosequencing reads (Phoenix 2) ...... 59

CHAPTER FOUR: IDENTIFYING CULTIVATION STRATEGIES FOR ACCELERATING RATES OF TOLUENE BIODEGRADATION USING AN ESTABLISHED METHANOGENIC ENRICHMENT CULTURE ...... 61 4.1 Introduction ...... 61 4.2 Materials and Methods ...... 64 4.2.1 Standard cultivation and maintenance of TOLDC ...... 64 4.2.2 Preparation of experimental microcosms with TOLDC ...... 65 4.2.2.1 Reducing agents ...... 66 4.2.2.2 Trace elements and nutrients ...... 66 4.2.2.3 Carbon supplements ...... 67 4.2.2.4 Biomolecule supplements ...... 67 4.2.2.5 Modifications to incubation conditions ...... 68 4.2.2.6 Electron acceptor supplements ...... 68 4.2.2.7 Cell density ...... 69 4.2.2.8 Artificial enrichment of Syntrophus ...... 69 4.2.3 Analytical methods ...... 70 4.2.4 Microbial community sequencing ...... 73 4.3 Results and discussion ...... 73 4.3.1 Impact of different cultivation procedures on methanogenic toluene degradation ...... 73 4.3.2 Impact of cysteine on methanogenic toluene degradation ...... 74 4.3.3 Experimental verification of cysteine utilization ...... 77 4.3.4 Microbial community analysis of cysteine-amended incubations ...... 80 4.3.5 Evidence that cell density and ‘Syntrophus’ are important for regulating methanogenic toluene biodegradation ...... 83

CHAPTER FIVE: BIODEGRADATION AND CO-METABOLIC BIODEGRADATION OF BTEX AND OTHER HYDROCARBONS UNDER METHANOGENIC CONDITIONS ...... 89 5.1 Introduction ...... 89

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5.2 Materials and Methods ...... 91 5.2.1 Culture incubations ...... 91 5.2.1.1 Experimental hydrocarbon incubations with TOLDC, 2MNDC and 26DMNDC ...... 92 5.2.1.2 TOLDC incubations with toluene and BEX as co-substrates ...... 93 5.2.1.3 Secondary TOLDC incubations with individual BEX substrates ...... 93 5.2.1.4 26DMNDC incubations with phenanthrene ...... 94 5.2.2 Metabolite analysis ...... 94 5.2.3 Microbial community analysis ...... 95 5.3 Results ...... 95 5.3.1 Evidence of methanogenic activity on BTEX substrates and phenanthrene (experiment #1) ...... 95 5.3.2 Methanogenic activity in TOLDC co-enrichment cultures and on individual hydrocarbons (experiments #2 and 3) ...... 96 5.3.3 Metabolite evidence of fumarate addition reactions using BTEX substrates (experiments #2 and 3)...... 100 5.3.4 Microbial community structure of TOLDC in co-substrate enrichment cultures (experiment #2) ...... 103 5.3.5 Chemical and phylogenetic evidence of methanogenic phenanthrene biodegradation (experiment #4) ...... 105 5.4 Discussion ...... 107

CHAPTER SIX: ASSESSING CARBON FLOW THROUGH METHANOGENIC PAH- DEGRADING COMMUNITIES BY DNA-SIP AND METAGENOMIC APPROACHES...... 118 6.1 Introduction ...... 118 6.2 Experimental Procedures ...... 121 6.2.1 Culture incubations and analytical methods ...... 121 6.2.2 DNA extraction and density gradient formation ...... 122 6.2.3 Molecular community analysis ...... 123 6.2.4 Metagenomic sequencing, binning and genome annotation ...... 124 6.2.5 Identification of putative naphthalene-degrading genes ...... 125 6.2.6 Metabolite analysis ...... 126 6.3 Results and Discussion ...... 127 6.3.1 Methanogenic activity from PAH degradation ...... 127 6.3.2 Detection of 13C-enriched DNA ...... 131 6.3.3 Key PAH degraders in methanogenic cultures ...... 133 6.3.4 Other putative PAH degraders detected by DNA-SIP analysis ...... 135 6.3.5 Genomic insights of anaerobic naphthalene metabolism in NDC ...... 138 6.3.5.1 Metagenome overview and preparation of draft genomes ...... 138 6.3.5.2 Detection of protein-encoding genes tentatively involved in anaerobic naphthalene degradation ...... 140 6.3.6 Limitations and overall findings ...... 143

CHAPTER SEVEN: MICROBIAL COMMUNITY RESPONSE TO ENRICHMENT ON LIGHT AND HEAVY CRUDE OILS UNDER SIMULATED RESERVOIR CONDITIONS ...... 150 7.1 Introduction ...... 150 7.2 Experimental Procedures ...... 153 7.2.1 Sampling site description and sample collection ...... 153 7.2.2 Establishment of light and heavy oil-degrading enrichment cultures ...... 155 7.2.3 Chemical analyses ...... 155 7.2.4 Targeted functional gene analysis ...... 157 7.2.5 Quantification of fumarate addition genes ...... 158 7.2.6 Microbial community analysis ...... 159 7.3 Results ...... 159 7.3.1 Methanogenic activity on light and heavy crude oil ...... 159 7.3.1.1 Methane production ...... 159 7.3.1.2 Putative anaerobic hydrocarbon metabolites ...... 160 7.3.1.3 Oil analysis ...... 161 7.3.2 Detection of fumarate addition genes ...... 166 7.3.3 Time-resolved quantification of fumarate addition genes ...... 168 7.3.4 Microbial community dynamics in methanogenic cultures ...... 169 7.4 Discussion ...... 176

CHAPTER EIGHT: CONCLUSIONS AND FUTURE RESEARCH DIRECTIONS ...184 8.1 Summary of key findings and future directions ...... 184 8.1.1 Optimizing incubation conditions for cultivating a methanogenic toluene- degrading enrichment culture ...... 184 8.1.2 The importance of Syntrophus in methanogenic toluene biodegradation .....185 8.1.3 Co-metabolic biodegradation of alkylbenzenes under methanogenic conditions ...... 186 8.1.4 Physiological and functional evidence of methanogenic PAH biodegradation, and identification of putative PAH degraders ...... 187 8.1.5 Key players and anaerobic mechanisms of methanogenic crude oil biodegradation ...... 188 8.1.6 Other future research directions ...... 188

REFERENCES ...... 191

APPENDIX A: SUPPLEMENTARY INFORMATION FOR CHAPTER 4: IDENTIFYING CULTIVATION STRATEGIES FOR ACCELERATING RATES OF TOLUENE BIODEGRADATION USING AN ESTABLISHED METHANOGENIC ENRICHMENT CULTURE ...... 223

APPENDIX B: SUPPLEMENTARY INFORMATION FOR CHAPTER 5: BIOGRADATION AND COMETABOLIC BIODEGRADATION OF BTEX AND OTHER HYDROCARBONS ...... 227

APPENDIX C: SUPPLEMENTARY INFORMATION FOR CHAPTER 6: ASSESSING CARBON FLOW THROUGH METHANOGENIC PAH-DEGRADING COMMUNITIES BY DNA-SIP AND METAGENOMIC APPROACHES ...... 230

APPENDIX D: SUPPLEMENTARY INFORMATION FOR CHAPTER 7: MICROBIAL COMMUNITY RESPONSE TO ENRICHMENT ON LIGHT AND HEAVY CRUDE OILS UNDER SIMULATED RESERVOIR CONDITIONS ...... 233

APPENDIX E: SIGNATURE METABOLITE ANALYSIS TO DETERMINE IN SITU ANAEROBIC HYDROCARBON BIODEGRADATION ...... 237

APPENDIX F: ANAEROBIC BIODEGRADATION OF HYDROCARBONS: METAGNEOMICS AND METABOLOMICS ...... 268

APPENDIX G: COMMUNITY STRUCTURE IN METHANOGENIC ENRICHMENTS PROVIDES INSIGHT INTO SYNTROPHIC INTERACTIONS IN HYDROCARBON-IMPACTED ENVIRONMENTS ...... 300

List of Tables

Table 1-2. Overview of selected, phylogenetically-characterized methanogenic hydrocarbon- degrading enrichment cultures growing on alkanes, BTEX, PAHs, and crude oil...... 10

Table 3-1. General anaerobic mineral salts medium for cultivating of methanogenic hydrocarbon-degrading enrichment cultures (adapted from McInerney et al. 1979)...... 47

Table 3-2. Wolin’s trace metal solution...... 47

Table 3-3. Balch vitamin solution...... 47

Table 4-2. Theoretical stoichiometric conversion of various carbon-containing components of Pfennig’s Anaerobic Freshwater Medium to methane based on its availability in 10 mL culture volumes (assuming a 100% conversion rate)...... 76

Table 5-1. List of hydrocarbons queried as methanogenic substrates by TOLDC, 2MNDC, and 26DMNDC. Substrates were provided as HMN overlays (5 mg substrate in 1 mL HMN). A (+) designates that enhanced methane production was observed in microcosms during a 342 – 481 incubation period relative to unamended controls; a (-) indicates that equal or lesser amounts of methane were produced...... 97

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Table 6-1. Quantification of DNA extracted from harvested experimental microcosms over three months of incubation (T1-T3). Samples with < 0.5 ng DNA are marked (-), while shaded areas indicate that samples were not available for analysis...... 130

Table 6-2. Summary of draft genomes assembled from 13C-labeled NDC + naphthalene after two months of incubation...... 139

Table 6-3. Scaffold 1013 retrieved from Clostridium Bin 1 from the 13C-labeled NDC + naphthalene after two months of incubation. % Sequence identity/similarity of genes to the NaphS2 genome and the best BLASTP ortholog are shown. Genes of key interest are bolded...... 141

Table 7-3. Primers used for qPCR analysis of bssA and assA genes. Primer set assA2fq/assA2rq was designed by Aitken et al. (2013)...... 168

Table 7-4. Features of 16S rRNA sequencing and alpha diversity statistics based on species- level analysis (97% cutoff) for all samples analysed in this study...... 172

Table 7-5. Distribution of the 25 most abundant classified taxa (%) across both methanogenic crude oil-degrading enrichment cultures over 17 months of incubation, as determined by 16S rRNA illumina sequencing. Taxa are sorted by their inferred community role. Inset heat map denotes time points with the highest relative abundance of each taxon across both cultures...... 172

Table A-1. Redox potential (Eh) of reducing agents in growth medium at pH 7...... 224

Table A-2. Tanner’s trace metal solution...... 225

Table A-3. Tanner’s vitamin solution...... 225

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Table A-4. Culture medium 960 used for isolating Syntrophus from TOLDC...... 226

Table D-1. Water chemistry of PW samples collected May 20th, 2015. Data courtesy of Dr. Yin Shen...... 234

Table D-2. Time-course taxonomic distribution of bacterial and archaeal 16S rRNA gene sequences comprising at least 0.1% of total reads in the crude oil-amended enriched cultures...... 234

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List of Figures and Illustrations

Figure 1-1. Visualization of the 200 most frequently used words used in journal article titles yielded by a search on PubMed for the term “anaerobic hydrocarbon biodegradation.” Font size is directly proportional to the number of times each word appeared in source text; for example, the keyword “anaerobe” appeared 3361 times in 7490 article names (accessed March, 2017). Word cloud was generated in Tagul (https://tagul.com/)...... 3

Figure 1-2. Anaerobic biodegradation pathways of (A) model alkylbenzenes (B) proposed activation and subsequent degradation pathways for benzene. Metabolites are shown as free acids. Signature metabolites believed to be exclusively anaerobic are marked with an asterisk; theoretical metabolites are marked in brackets. Multiple arrows represent more than one enzymatic step; dashed arrows represent an unknown reaction. Structure nomenclature: 1, toluene; 2, benzylsuccinate; 3, E-phenylitaconate; 4, 2- [hydroxy(phenyl)methyl]succinate; 5, benzoylsuccinate; 6, xylene; 7, methylbenzylsuccinate; 8, E-(methylphenyl)itaconate; 9, toluate; 10, ethylbenzene; 11; 1-phenylethanol; 12, acetophenone; 13, benzoylacetate; 14, (1-phenylethyl)succinate; 15, (2-phenylpropyl)malonate; 16, 4-phenylpentanoate; 17, 2-phenylpropanoate; 18, benzoate; 19; cyclohex-1, 5-diene-1-carboxylate; 20, cyclohex-1-ene-1-carboxylate; 21, pimelate; 22, glutarate; 23, acetate; 24; benzene; and 25, phenol. From Gieg and Toth (2017b)...... 14

Figure 1-3. Proposed anaerobic biodegradation pathways of (A) naphthalene/2- methylnaphthalene and (B) other PAHs. Metabolites are shown as free acids. Signature metabolites believed to be exclusively anaerobic are marked with an asterisk; theoretical metabolites are marked in brackets. Multiple arrows represent more than one enzymatic step. ‘Cometabolic’ refers to metabolites observed under cometabolic conditions with naphthalene and/or 2-methylnaphthalene serving as main substrates (Safinowski et al. 2006). Structure nomenclature: 1, naphthalene; 2, 2-methylnaphthalene; 3, naphthyl-2- methylsuccinate; 4, naphthyl-2-methylenesuccinate; 5, naphthyl-2- hydroxymethylsuccinate; 6, naphthyl-2-oxomethylsuccinate; 7, 2-naphthoate; 8, 5,6- dihydro-2-naphthoate; 9, 5,6,7,8-tetrahydro-2-naphthoate; 10, 1,2,3,4-tetrahydro-2- naphthoate; 11; hexahydro-2-naphthoate (4 isomers possible); 12, 1-hydroxy-octahydro- 2-naphthoate; 13, cis-2-carboxylcyclohexylacetate; 14, decahydro-2-naphthoate; 15, glutarate; 16, phenanthrene; 17, phenanthrene carboxylate; 18, biphenyl; 19, biphenylcarboxylate; 20, indane; 21, indanoate; 22, indene; 23, indenoate; 24, acenaphthylene; 25, acenaphthylenoate; 26, acenaphthene; 27, acenaphthenoate; and 28, acenaphthylmethylsuccinate. From Gieg and Toth (2017b)...... 16

alkylmalonate; 6, cyclohexane; 7, cyclohexylsuccinate; 8, (cyclohexylmethyl)malonate; 9, cyclohexylpropanoate; 10, cyclohexanecarboxylate; 11; methylcyclohexane; 12, methylcyclohexylsuccinate; 13, cyclopentane; 14, cyclopentylsuccinate; 15, methylcyclopentane; 16, methylcyclopentylsuccinate; 17, ethylcyclopentane; 18, ethylcyclopentylsuccinate; 19; propane; 20, isopropylsuccinate; and 21, n- propylsuccinate. From Gieg and Toth (2017b)...... 18

Figure 3-1. Transfer history of methanogenic hydrocarbon-degrading consortia enriched from gas condensate-contaminated aquifer subsurface sediments collected from near Fort Lupton, CO. Cultures investigated in this dissertation are highlighted in bold...... 42

Figure 4-1. Toluene consumption in TOLDC incubations used to assess the impact of various reducing agents (A and B), carbon supplements (C), biomolecules (D), incubation conditions (E), and electron acceptors (F) against unmodified control replicates (designated by the black line). Toluene consumption in each set of duplicate incubations was quantitatively determined by GC-FID and corrected for abiotic loss observed in corresponding sterile controls. Bars indicate ± SEM...... 72

Figure 4-2. Average methane production from experimental toluene-amended, cysteine- reduced TOLDC microcosms over 124 days of incubation. Methane production for unamended replicates corresponding to the unmodified controls is also included. Error bars indicate ± SEM of duplicate incubations...... 76

Figure 4-3. Analytical measurements of methane production, toluene consumption, and sulfhydryl (-SH) concentrations in TOLDC incubations containing the following carbon and energy sources; 0.05% cysteine-HCl (yellow), ~4.7 μmol toluene (blue), cysteine- HCl + toluene (red), or carbon-free (tan). (A) Methane (closed circles) and toluene (open circles) were routinely monitored for up to 114 days. (B) -SH amounts in incubations with cysteine-HCl and cysteine-HCl + toluene, as well as in sterile controls reduced with cysteine-HCl (gray) was measured during the first 29 days of incubation. Error bars ± SEM of triplicate incubations...... 78

Figure 4-4. Degradation profile of one toluene-amended TOLDC replicate (reductant-free) continuously reamended with hydrocarbon substrate following experiments summarized in Figure 4-3. Closed circles depict methane production in the microcosm headspace; open circles indicate total μmol toluene in the incubation. After a 376-day incubation period (with a ~120-day lag period, not shown), the culture consumed ~32.9 µmol of toluene and produced 126 µmol of methane, indicating an 86% recovery of CH4 based on theoretical stoichiometric predictions...... 79

Figure 4-5. Taxonomic distribution of the most abundant genera (≥ 1%) present in methanogenic TOLDC incubations amended with cysteine-HCl and/or toluene. Taxon abundance is expressed as a percentage of total quality 454 pyrosequencing reads. The microbial composition of TOLDC previously reported by Fowler et al. (2012) is included for comparative analysis. Lineages belonging to the Proteobacteria phylum are

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shown in yellow; Firmicutes in green and Euryarchaeota in blue; other taxa are designated in red...... 81

Figure 4-6. Formation of visible cell aggregates in TOLDC enrichment cultures repeatedly amended with toluene over 1 to 3 years...... 83

Figure 4-7. Toluene consumption in TOLDC incubations (25% transfer v/v) inoculated with 1 – 10% pure Syntrophus. Rates of methanogenic toluene degradation (calculated based on 1-liter volumes containing ~300 µM toluene) are shown in the figure legend. Cultures were refed once the headspace concentration of toluene fell below detectable limits (< 5 µM). Here, we show that artificial enrichment of 2 – 3% Syntrophus increased rates of toluene utilization by ~208%...... 85

Figure 5-1. Methane production from TOLDC enrichment cultures amended with BTEX substrates. Average results are shown for duplicate measurements; bars indicate ± SEM. In the cases of benzene (Bz) and o-xylene (o-Xyl), only one incubation was able to produce methane by the end of the incubation period (342 days); the second replicates are not shown...... 98

Figure 5-2. Methanogenic biodegradation of BTEX substrates in co-substrate enrichment cultures (experiment #2) and on individual hydrocarbons (experiment #3), using toluene (Tol, gray) and o-xylene (o-Xyl, red) as an example. (A) Partial o-Xyl degradation is observed in TOLDC co-metabolic cultures containing toluene and o-xylene. (B) Methane production and (C) hydrocarbon loss in transferred enrichment cultures (on individual hydrocarbons) is only observed when toluene is added as a carbon and energy source...... 99

Figure 5-3. Detection of alkylsuccinates formed from (A) toluene, (B) o-xylene, (C) m- xylene, (D) p-xylene, and (E) ethylbenzene. Mass spectral patterns of the TMS- derivatized metabolites found in culture extracts on shown to the left; reference profiles for authentic standards are shown on the right...... 101

Figure 5-4. Mass spectral profiles of TMS-derivatives hydrocarbon metabolites corresponding to (A) E-phenylitaconate and (B) a putative E-(2-methylphenyl)itaconate product. A mass spectrum of an authentic standard of E-phenylitaconate matching (A) is available in Figure B-2)...... 103

Figure 5-5. Enhanced (A) methane production and (B) substrate loss in transferred PHDC cultures amended with phenanthrene. Phenanthrene loss in Phen + HMN live replicates on Day 142 was statistically significant compared to T0 and sterile control values (P values < 0.001; unpaired t-tests). Results are shown for the average of duplicate incubations (± SEM)...... 106

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the remaining 2% occupied by minor constituents, including Smithella sp. (0.068%) and Geobacter sp. (0.061%)...... 107

Figure 5-7. Proposed methanogenic degradation pathways of toluene and other alkylbenzene co-substrates by Desulfosporosinus sp. present in TOLDC. Metabolites are shown as free acids. Hydrocarbon metabolites found that are diagnostic of their parent hydrocarbon are marked (). Multiple arrows represent more than one enzymatic step; hypothetical intermediate products are shown in brackets. Structure nomenclature: 1, toluene; 2, benzylsuccinate; 3, E-phenylitaconate; 4, 2- [hydroxy(phenyl)methyl]succinate; 5, benzoylsuccinate; 6, benzoate; 7, xylene; 8, methylbenzylsuccinate; 9, E-(2-methylphenyl)itaconate; 10, toluate; 11, ethylbenzene; 12, (1-phenylethyl)succinate; 13, (2-phenylpropyl)malonate; 14, 4-phenylpentanoate; and 15, 2-phenylpropanoate...... 110

Figure 5-8. Proposed syntrophic oxidation and reduction pathways of benzoate (1) in TOLDC. Metabolites are shown as free acids. All hydrocarbon metabolites shown were detected in toluene-amended TOLDC incubations in this study or by Fowler et al. (2012) Multiple arrows represent more than one enzymatic step. Desulfosporosinus sp. is proposed to catalyze the oxidation branch of benzoate metabolism, leading to ring cleavage and subsequent formation of intermediates pimelate (3) and glutarate (4), generating acetyl-CoA. Desulfovibrio sp. is also thought to consume glutarate based on a previous study (Fowler et al. 2014). Synthophus sp. is proposed to couple anaerobic benzoate oxidation with the reduction of cyclohex-1, 5-diene-1-carboxylate (2), forming cyclohex-1-ene-1-carboxylate (5) and cyclohexane carboxylate (6). This could then be further degraded using a modified ß-oxidation pathway...... 113

Figure 6-1. Methane production in SIP incubations inoculated with (A) NDC, (B) 2MNDC, (C) PHDC, and (D) Oil Sands. 12C- and 13C-PAH replicates were each prepared in triplicate; unamended (PAH-free) controls shown were established in duplicate. Error bars indicate standard deviation. During the cultivation period, one 12C- and 13C replicate per culture was sacrificed monthly for molecular analysis; means and error bars were adjusted accordingly. Negligible amounts of methane (< 1 µmol) were reported in cultivations with 26DMNDC and 18PW, as well as in all 12C-PAH sterile controls, and are not shown...... 129

Figure 6-2. Relative distribution of total 16S rRNA gene fragments in SIP fractions containing 13C-DNA in (a) NDC, (b) PHDC, (c) Oil Sands amended with naphthalene, and (d) Oil Sands amended with phenanthrene. Fractions enriched with 13C-DNA were first detected after two months (NDC; PHDC) or three months of incubation (Oil Sands). All other cultures evaluated did not have a detectable “heavy” fraction and are not shown. The shaded areas indicate “light” fractions that were processed for 16S rRNA gene sequencing as control replicates; heavy fractions chosen for further analysis are marked with an arrow...... 132

Figure 5-3. Composition of the 10 most abundant taxa per culture in selected SIP fractions of (A) NDC + naphthalene after 2 months of incubation; (B) PHDC + phenanthrene, 2 xviii

months; (C) Oil Sands + naphthalene, 3 months; and (D) Oil Sands + phenanthrene, 3 months. Taxon abundance is expressed as percentage of quality 16S rRNA reads, with the lowest confident taxonomic level shown. Phylogenies belonging to Euryarchaeota are shown in blue; Firmicutes in green and Deltaproteobacteria in red/pink...... 136

Figure 6-4. Organization of genes in scaffold 1013 of Clostridium sp. Bin 1 tentatively encoding enzymes involved in methanogenic naphthalene degradation. Genes marked with blue bars contain ≥ 50% sequence similarity to enzymes upregulated in the presence of naphthalene in Desulfobacterium strains N47 and NaphS2 (Didonato et al. 2010; Bergmann et al. 2011a). Gene nomenclature: 1. hypothetical protein; 2. crotonobetainyl-CoA:carnitine-CoA transferase; 3. acetyl-CoA C-acetyltransferase; 4. 3-hydroxybutyryl-CoA dehydrogenase; 5. H+/gluconate symporter; 6. enoyl-[acyl- carrier protein] reductase II; 7. enoyl-CoA hydratase/isomerase/hydrolase; 8. enoyl-CoA hydratase/isomerase/ hydrolase; 9. 2-nitropropane dioxygenase precursor; 10. crotonobetainyl-CoA:carnitine-CoA transferase; 11. 2-(1, 2-epoxy-1, 2- dihydrophenyl)acetyl-CoA isomerase; 12. hypothetical protein...... 144

Figure 6-5. Hypothetical products and enzymatic reactions proposed for anaerobic naphthalene degradation by Meckenstock et al. (2016). Protein-encoding genes in Clostridium sp. Bin 1 orthologous to predicted dearomatization and ring cleavage enzymes encoded by the thn operon are shown (enzymes named)...... 144

Figure 7-1. Production water (PW) wells sampled from the Medicine Hat Glauconitic C (MHGC) field in May, 2015. The corresponding water plant (WP) for each production well surveyed (circled) are also included. Adapted from Voordouw et al. (2009)...... 154

Figure 7-2. Image of the light (left) and heavy (right) oil cultures prepared in modified 1-L serum bottles...... 156

Figure 7.3. Methane production from production water-derived incubations enriched on light (squares) and heavy (circles) oil relative to an unamended control (triangles)...... 160

Figure 7-4. Detection of putative alkylsuccinates in oil-amended enrichment cultures. (A) A portion of a GC total ion chromatogram showing larger peaks diagnostic of C1-C4 alkylsuccinates in the light oil culture (black) than in the heavy oil culture (red); peaks were not detected in the unamended control (not shown). (B) Mass spectral profiles indicative of propane and butane fumarate addition products at both the primary and secondary carbon atoms...... 167

Figure 7-5. Maximum likelihood tree showing the affiliation of recovered assA and bssA gene fragments (this study, bold) with previously published reference strains, enrichment cultures, and environmental samples. Evolutionary analyses of aligned nucleotide sequences (400 bp) were conducted in MEGA7 (Kumar et al. 2016); the consensus tree was constructed using the Tamura–Nei model (Tamura and Nei 1993) at all nucleotide positions and performing 500 bootstrap replicates (values below 50% are

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not shown). Pyruvate formate lyase (pfl) sequences were used as an outgroup (collapsed in figure)...... 170

Figure 7-6. Change in bssA gene abundances over time in the (A) light and (B) heavy oil- amended enrichment cultures. Statistical analyses were performed using repeated measure one-way ANOVA with the Greenhouse-Geisser correction. Post-hoc Tukey’s test was performed to assess mean differences between time point samples taken from the same culture; unmatched letters indicate significant differences (P value ≤ 0.05). Bars indicate ± SEM...... 171

Figure 7-7. Microbial community composition of methanogenic crude oil-degrading enrichment cultures over time at the phylum level based on 16S rRNA illumina sequencing...... 176

Figure 7-8. Proposed working model for the methanogenic hydrocarbon biodegradation of alkanes and aromatics by MHGC produced water-associated consortia based on the results of this study. Hydrocarbons are activated by addition to fumarate by Smithella (assA) or Desulfotomaculum (bssA), yielding corresponding alkylsuccinates and benzylsuccinates (not detected, though their production is inferred based on results from other tests, e.g. oil analyses, qPCR assays, and detection of downstream metabolite products such as benzoate and toluic acids). Members of the candidate phylum ‘Atribacteria’ may also participate in hydrocarbon activation; carboxylation of two- ringed PAHs may be catalyzed by an unknown organism. Subsequent degradation steps are proposed to be carried out by several putative syntrophic oxidizers (e.g. Peptococcaceae, Syntrophaceae, and candidate phyla) presumably yielding H2, CO2, and acetate that are consumed by hydrogenotrophic and acetotrophic methanogens. Figure schematic modeled from Jiménez et al. (2016)...... 180

Figure A-1. Methane production in 50 mL TOLDC incubations (15% transfer v/v) amended with 19 μmol toluene (closed circles) and in substrate-unamended controls (open circles). Error bars indicate standard deviation of triplicate incubations...... 223

Figure A-2. Methane production in transferred 20 mL TOLDC incubations (20 mL; 20 – 100% transfer v/v) containing 300 µM toluene. Figure prepared by Corynne O’Farrell. .. 223

Figure A-3. Linear relationship between the relative abundance of Syntrophus and rate of toluene consumption in four replicate incubations of TOLDC (black circles). Cultures (100 mL) were routinely refed 0.005% v/v toluene as needed over 450 days of incubation...... 224

Figure B-1. Methanogenic activity of transferred TOLDC co-substrate enrichment cultures on individual hydrocarbon substrates (benzene, Bz; o-xylene, o-Xyl; m-xylene, m-Xyl; ethylbenzene, EtBz). Methane production (left) and hydrocarbon loss (right) are shown for transfers of (A) Tol + Bz, (B) Tol + o-Xyl, (C) Tol + m-Xyl, and (D) Tol + EtBz. Hydrocarbon loss values were corrected for abiotic losses seen in sterile controls...... 227

Figure B-2 Mass spectrum of an authentic silylated standard of TMS-derivatized E- phenylitaconate. Reference spectrum was provided by Dr. Joe Suflita from the Department of Microbiology and Plant Biology at the University of Oklahoma in Norman, OK...... 228

Figure B-3. Detection and identification of TMS-derivatized toluene degradation products indicative of benzoyl-CoA dehydrogenation and subsequent metabolism. Mass spectral patterns of these products were confirmed to be indicative of (A) benzoate, (B) cyclohex-1, 5-diene-1-carboxylate, (C) cyclohex-1-ene-1-carboxylate, (D) cyclohexanoate and (E) glutarate...... 228

Figure B-4. Enhanced turbidity observed in (A) phenanthrene-amended replicates, as compared to (B) HMN-only, (C) carbon-free, and (D) sterile controls...... 229

Figure B-5. Tentative methanogenic phenanthrene metabolites detected in PHDC; (A) 2- methylbutanoic acid, (B) 3-methylbutanoic acid, (C) 4-methylvaleric acid, (D) p-cresol, and (E) decahydro-2-naphthoic acid. Mass spectral patterns and retention times were matched to authentic standards...... 229

Figure D-1. Hydrocarbon loss in light (blue) and heavy (red) crude oil-amended enrichment cultures relative to corresponding to sterile controls (gray). Hydrocarbon loss was determined as a function of n-alkane or hydrocarbon (HC) to pristane or phenanthrene peak area ratios, respectively. Unpaired t-tests were used to determine significance of hydrocarbon loss relative to sterile controls using unpaired t-tests; P values ≤ 0.05 (*), ≤ 0.01 (**), and ≤ 0.001 (***). Error bars indicate standard deviation of triplicate oil measurements...... 233

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List of Symbols, Abbreviations and Nomenclature

Symbol Definition AF Alignment factor AMP Adenosine monophosphate ANI Average nucleotide identity °API American Petroleum Institute gravity ASS/MAS Alkylsuccinate synthase/(1- Methyl)alkylsuccinate synthase assA/masD ATP Adenosine triphosphate BCR Benzoyl-CoA reductase BSS Benzylsuccinate synthase bssA BSTFA N, O-bis-trimethylsilylacetamide BTEX Benzene, toluene, ethylbenzene, xylenes Bz Benzene CoA Coenzyme A CSIA Compound specific isotope analysis DIET Direct interspecies electron transfer DNA Deoxyribonucleic acid DNTB 5, 5’-Dithio-bis-(2-nitrobenzoic acid) DSMZ Deutsche Sammlung von Mikroorganismen und Zellkulturen EtBz Ethylbenzene FID Flame ionization detector/detection GC Gas chromatograph(y) GC-FID Gas chromatography-flame ionization detector/detection GC-MS Gas chromatography-mass spectrometry HMN 2, 2, 4, 4, 6, 8, 8-Heptamethylnonane HPLC High performance liquid chromatograph(y) KEGG Kyoto Encyclopedia of Genes and Genomes kPa Kilopascal MHGC Medicine Hat Glauconitic C 2MNDC 2-Methylnaphthalene-degrading culture 26DMNDC 2, 6-Dimethylnaphthalene-degrading culture MS Mass spectrum/mass spectral m-Xyl m-Xylene NADP Nicotinamide adenine dinucleotide phosphate Naph Naphthalene NCBI National Center for Biotechnology Information Ncr 2-Naphthoyl-CoA reductase NMS Naphthylmethylsuccinate synthase nmsA

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NDC Naphthalene-degrading culture NTB 2-Nitro-5-thiobenzoic acid O/R Oxidation/reduction OTU Operational taxonomic unit o-Xyl o-Xylene Pa Pascal PAH Polycyclic aromatic hydrocarbon PHDC Phenanthrene-degrading culture Phen Phenanthrene p-Xyl p-Xylene PCR Polymerase chain reaction PLFA Phospholipid fatty acid PW Produced water qPCR Quantitative polymerase chain reaction Redox Reduction-oxidation RNA Ribonucleic acid RT-PCR Reverse transcription polymerase chain reaction SEM Standard error of the mean SIP Stable isotope probing Tol Toluene TOLDC Toluene-degrading culture TMS Trimethylsilyl T-RFLP Terminal-restriction fragment length polymorphism

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Epigraph

“But why, some say, the moon? Why choose this as our goal?

And they may well ask, why climb the highest mountain? Why, 35 years ago, fly the Atlantic?

Why does Rice play Texas?

We choose to go to the Moon!

We choose to go to the Moon in this decade and do the other things.

Not because they are easy, but because they are hard.”

- John F. Kennedy (1962)

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Chapter One: Literature Review

1.1 Introduction

Hydrocarbons were long believed to be recalcitrant to degradation in anoxic environments. It was therefore surprising to discover that many model hydrocarbons and their derivatives could be catabolized by anaerobic bacterial isolates (Widdel et al. 2010; Widdel and

Musat 2010; Head et al. 2014; Rabus et al. 2016b). Hydrocarbons, which in the strictest sense are defined as molecules containing only C and H atoms, are ubiquitous compounds found across the globe. They are naturally synthesized by some algal, plant, and animal species to serve a variety of functions (Harms et al. 1999), and are by-products of the incomplete combustion of natural and anthropogenic sources (Vergnoux et al. 2011). By far though, the Earth’s terrestrial and marine subsurfaces contain the largest inventory of hydrocarbons (including the smallest hydrocarbon, methane). These are found beneath the ocean floor where they are naturally emitted via cold seeps or generated within hydrothermal vent systems (Boetius and Wenzhöfer

2013; Teske et al. 2014) or entrained in crude oil, coal, or shale reservoirs where hydrocarbons were generated from ancient burial of biomass subjected to high temperatures and pressures over geological time. Due to humankind’s predominant use of petroleum-based energy, the recovery of gaseous and liquid hydrocarbons from such deposits (and their subsequent distribution, refining, storage, and combustion) have also led to widespread water and land contamination with hydrocarbons. Although hydrocarbons are considered chemically inert (Widdel and Musat

2010), it has now been definitely demonstrated that widespread naturally occurring microbial communities (across several distinct phylogenetic lineages) contain a multitude of enzymes that can readily biotransform hydrocarbons both in the presence and absence of oxygen (Widdel and

Musat 2010; Rabus et al. 2016b). Microbial hydrocarbon degradation can occur in surface soils

and sediments, shallow groundwater environments, subsurface fossil energy reservoirs, cold seeps, marine waters and sediments, and hydrothermal vent systems. This fact has many important implications for the remediation of hydrocarbon-contaminated areas (Techtmann and

Hazen 2016), for crude oil quality in reservoirs or for enhanced energy recovery (Head et al.

2014), and for minimizing greenhouse gas (methane) emissions from natural terrestrial and marine systems (Boetius and Wenzhöfer 2013).

Knowledge regarding anaerobic hydrocarbon biodegradation has been gained mainly from research conducted in the last 30 years. Such research has led to the isolation of dozens of anaerobic hydrocarbon-utilizing isolates (nitrate-reducing, metal-reducing, and sulfate-reducing bacteria and archaea) and enriched methanogenic consortia (Widdel et al. 2010; Jiménez et al.

2016; Gieg and Toth 2017a), along with the description of thousands of anaerobic hydrocarbon- degrading enrichment cultures or processes (Figure 1-1). Convincing evidence for methanogenic hydrocarbon biodegradation, however, was not reported until far more recently (Edwards and

Grbić-Galić 1994; Zengler et al. 1999; Gieg et al. 1999; Head et al. 2003), and the description of associated microbial communities and their degradation pathways is largely incomplete (Jiménez et al. 2016). As the topic of anaerobic hydrocarbon biodegradation is vast, this literature chapter will provide a high-level overview of the principles governing hydrocarbon utilization in the absence of O2, including bioenergetic considerations, mechanisms of hydrocarbon degradation, and tools for assessing anaerobic hydrocarbon utilization. Field evidence and laboratory evidence pertaining to methanogenic hydrocarbon biodegradation will be explored herein, which is the primary focus of this dissertation. Components of this literature review were adapted from recent publications by Gieg and Toth (2017a; 2017b).

1.2 Bioenergetic considerations of anaerobic hydrocarbon biodegradation

Hydrocarbons are highly reduced and relatively inert organic molecules that require an initial C–H bond activation by enzymatic reactions before they can be further utilized biologically (reviewed in detail by Boll and Heider 2010; Widdel and Musat 2010). To overcome the high-energy costs associated with C–H bond dissociation, the reducing equivalents generated during the transformation of hydrocarbons to metabolic intermediates need to be transferred to an electron acceptor with a more positive reduction-oxidation (redox) potential. This is crucial in order to conserve sufficient energy to drive ATP synthesis (–63 kJ/mol for most prokaryotes, albeit can proceed closer to thermodynamic equilibrium in syntrophic associations; Thauer et al.

1977; Schink 1997; McInerney et al. 2009; Sieber et al. 2012) and to allow for biomass production at a net zero or increasing rate (Harder 1997; Hoehler 2004). Some examples of theoretical free energy values from model hydrocarbons under different electron-accepting conditions are provided in Table 1-1. In aerobic microorganisms, the C–H bond activation energy is overcome using highly reactive oxygen species generated by oxygenase enzymes

(Lieberman and Rosenzweig 2004; Thauer and Shima 2008). For example, the formation of a free hydroxyl radical (•OH) from H2O by a monooxygenase enzyme releases 497 kJ/mol, which is sufficient to cleave any C-H bond in an exergonic reaction (Boll and Heider 2010). This activation mechanism sacrifices the least free energy of all known biologically relevant redox reactions, and is the main reason why oxygen becomes rapidly depleted in anoxic hydrocarbon- containing environments (Lüdemann et al. 2000; Boll and Heider 2010). The hydrocarbon energetic barrier can also be overcome using alternative electron acceptors present in the

- 3+ 4+ 2- environment, such as nitrate (NO3 ), ferric iron (Fe ), manganese (Mn ) or sulfate (SO4 ), but at the expense of decreasing free energy conservation, respectively (Table 1-1).

The types of reactions, enzymes, and cofactors employed for hydrocarbon activation by anaerobic bacteria (Section 1.4) can vary substantially, depending on the minimum dissociation energy required for C-H bond cleavage (Boll and Heider 2010; Widdel and Musat 2010). For example, the activation of the methyl-group of toluene (C-H bond dissociation of 376 kJ/mol) is catalyzed by a glycyl radical formed during the enzymatic addition to a fumarate co-substrate under all anaerobic electron accepting conditions, releasing ~ 440 kJ/mol of free energy

(Leuthner et al. 1998; Funk et al. 2014; Shisler and Broderick 2014). In principle, this reaction could also be initiated by a different enzymatic mechanism such as carboxylation, but at the expense of a higher initial microbial energy investment. Enzymatic reactions following initial

hydrocarbon activation also have unique redox potentials that can influence the energy gained from each process (reviewed by Thauer et al. 1977; Boll and Heider 2010; Widdel and Musat

2010; McInerney et al. 2011). This is particularly important for syntrophic microorganisms, wherein partners must tightly coordinate their metabolisms in a thermodynamically favourable, mutually beneficial manner (McInerney et al. 2009; Sieber et al. 2012; Gieg et al. 2014; Section

1.3).

Table 1-1. Example net stoichiometric calculations of microbial hydrocarbon oxidation coupled to the reduction of different electron acceptors and under methanogenic conditions. Equations adapted from Heider et al. 1999; Musat and Widdel 2010. Hydrocarbon Stoichiometric calculation ∆퐺°′ 표푟 ∆퐺° (kJ/mol)a Toluene 퐶7퐻8 + 9 푂2 + 3 퐻2푂 → 7 퐶푂2 + 4 퐻2푂 –3823 − + (C7H8) 퐶7퐻8 + 7.2 푁푂3 + 7.2 퐻 → 7 퐶푂2 + 3.6 푁2 + 7.6 퐻2푂 –3590 퐶7퐻8 + 36 퐹푒(푂퐻)3 + 29 퐶푂2 → 36 퐹푒퐶푂3 + 58 퐻2푂 –1689 2− + 퐶7퐻8 + 4.5 푆푂4 + 9 퐻 → 7 퐶푂2 + 4.5 퐻2푆 + 4 퐻2푂 –238 퐶7퐻8 + 5 퐻2푂 → 4.5 퐶퐻4 + 2.5 퐶푂2 –142 Naphthalene 퐶10퐻8 + 12 푂2 → 10 퐶푂2 + 4 퐻2푂 –5093 − (C10H8) 퐶10퐻8 + 9.6 푁푂3 + 9.6 퐻2푂 → 10 퐶푂2 + 4.8 푁2 + 8.8 퐻2푂 –4782 퐶10퐻8 + 48 퐹푒(푂퐻)3 + 38 퐶푂2 → 48 퐹푒퐶푂3 + 78 퐻2푂 –2247 2− + 퐶10퐻8 + 6 푆푂4 + 12 퐻 → 10 퐶푂2 + 6 퐻2푆 + 4 퐻2푂 –313 퐶10퐻8 + 10 퐻2푂 → 6 퐶퐻4 + 4 퐶푂2 –186 n- 퐶16퐻34 + 24.5 푂2 → 16 퐶푂2 + 17 퐻2푂 –10392 − + Hexadecane 퐶16퐻34 + 19.6 푁푂3 + 19.6 퐻 –9757 (C16H34) → 16 퐶푂2 + 9.8 푁2 + 26.8 퐻2푂 퐶16퐻34 + 102 퐹푒(푂퐻)3 + 86 퐶푂2 –3701 → 102 퐹푒퐶푂3 + 172 퐻2푂 2− + 퐶16퐻34 + 12.25 푆푂4 + 24.5 퐻 –632 → 16 퐶푂2 + 12.25 퐻2푆 + 17 퐻2푂 퐶16퐻34 + 7.5 퐻2푂 → 12.25 퐶퐻4 + 3.75 퐶푂2 –135 aIf protons are involved, ∆G°′ (where [H+] = 10-7 M, pH = 7) is given. ∆G° was calculated with the following values as suggested by McInerney et al. (2009): H2, 10 Pa; bicarbonate, 50 mM; ′ acetate, 50 mM; CH4, 50 kPa; substrates, 100 mM and based on the formula: ∆퐺′ = ∆퐺° + RTln[(C)c(D)d/(A)a(B)b], where R = 0.00831 kJ K-1 mol-1 and T = 298 K.

Indeed, each of these bioenergetic factors has an inherent consequence on net microbial growth rates and rates of hydrocarbon utilization, with doubling times ranging from approximately 6 hours (for the fastest toluene denitrifiers; Fries et al. 1994) to several months in the case for syntrophic methane-oxidizing consortia under sulfate-reducing conditions (Nauhaus et al. 2007). Doubling times for syntrophic bacteria in methanogenic consortia are rarely determined, but have been reported in the range of 6 to 30 days when amended with monoaromatic hydrocarbons (Edwards and Grbić-Galić 1994; Luo et al. 2016) and up to 36 days on alkanes (Gray et al. 2011). Reservoir studies suggest that the microbial degradation rates of hydrocarbons to methane at temperatures between 40 and 70 ℃ are in the order of 4 – 10 kg/m2/year at the oil-water interface (also known as the oil water transition zone; Head et al.

2003). Based on these estimates, hydrocarbon methanogenesis over geological time has driven the transformation of roughly 5.6 trillion barrels worth of oil resources to biodegraded forms that are of lower quality and are more difficult to recover (Jones et al. 2008; Hein et al. 2013; Head et al. 2014), releasing as much as 1.883 × 109 m3 of methane (Milkov 2010; Jiménez et al. 2016).

Perhaps partially in recognition of this, stimulating methane production has been proposed as a biological means to enhance energy recovery from residual oil energy assets (Suflita et al. 2004;

Jones et al. 2008; Gieg et al. 2008). Nevertheless, the thermodynamic landscape of methanogenic hydrocarbon degradation heavily impedes the pace at which cultivation-based laboratory research can be conducted.

1.3 Methanogenic hydrocarbon biodegradation – An overview

Methanogenic hydrocarbon biodegradation occurs in a series of steps and requires close syntrophic associations between fermentative bacteria and methanogenic archaea (Zengler et al.

1999; Gieg et al. 2014; Jiménez et al. 2016). In this process, fermentative bacteria (many affiliated to the Clostridiales and Deltaproteobacteria classes) first transform the hydrocarbon substrate into smaller molecules such as acetate, formate, and/or H2. Physiological and genomic evidence also suggest that additional syntrophic oxidizers such as Smithella and/or Syntrophus

(both belonging to the Syntrophaceae family) may be required to catabolize intermediate metabolic reactions to methanogenic substrates (Zengler et al. 1999; Gray et al. 2011; Fowler et al. 2014; Gründger et al. 2015; Embree et al. 2015). In either case, the anaerobic oxidation of the initial substrate is thermodynamically unfavorable under standard conditions, but becomes favourable when partners such as methanogens consume the intermediates, keeping them at low concentrations (Gieg et al. 2014). For example, Dolfing et al. (2008) estimate that the methanogenic transformation of alkanes is possible at hydrogen partial pressures lower than 4 ×

-5 10 atm. Although syntrophy is most frequently characterized by partnerships of fermentative

(syntrophic) bacteria with methanogenic archaea (e.g. Gray et al. 2010; Walker et al. 2012;

Sieber et al. 2012; Kleinsteuber et al. 2012), syntrophic interactions can also occur in the absence of methanogens, particularly in systems characterized by higher standard redox potentials such as under metal-reducing conditions (Lovley 2012; Luo et al. 2014).

Diverse groups of methanogenic archaea, mostly belonging to the class

Methanomicrobia, use the products formed from hydrocarbon fermentation and transform them to methane and CO2 through various pathways, mainly through hydrogenotrophic and acetoclastic methanogenesis. Hydrogenotrophic microorganisms across several genera (e.g.

Methanobacterium, Methanospirillum, Methanocalculus) use H2 as an electron donor while reducing CO2 to methane, whereas acetoclastic methanogens (e.g. Methanosarcina and

Methanosaeta) cleave acetate to form CH4 and CO2. Methylotrophic methanogens are also

thought to participate in hydrocarbon degradation, albeit to a lesser extent (Wawrik et al. 2012), and methanogenesis from methoxylated aromatic compounds in coal deposits was recently discovered (Mayumi et al. 2016).

In addition to the taxa described above, other members of diverse phyla (e.g. Chloroflexi,

Spirochaetes, Bacteroidetes) are usually associated with methanogenic hydrocarbon-impacted communities, but their functional roles have not yet been clearly defined (Strąpoć et al. 2011;

Kleinsteuber et al. 2012; Mouser et al. 2016). In hot environments, such as thermogenic oil reservoirs (> 50 ℃), bacterial members affiliating with Thermotogales, Synergistales,

Deferribacterales, or Thermoanaerobacterales and thermophilic methanogens including

Methanothermobacter are believed to be involved in anaerobic hydrocarbon degradation (Gieg et al. 2010; Orphan et al. 2000), but definitive evidence is still required.

The occurrence of methanogenesis and the predominance of one or another of the methanogenic pathways in the environment may depend on a combination of biogeochemical factors such as temperature, CO2 concentrations, salinity, pH, availability of electron acceptors and donors, nutrient availability, porosity, permeability, and so forth (Kotsyurbenko et al. 2007;

Waldron et al. 2007; Dolfing et al. 2008; Mayumi et al. 2011; Schlegel et al. 2011; Siegert et al.

2011). From the distribution of biodegraded oils worldwide, it seems that reservoirs buried to temperatures of more than 80 ℃ are effectively ‘sterilized’ with regards to hydrocarbon degraders (Head et al. 2003; Larter et al. 2003). However, in nutrient-rich environments such as hydrothermal vents, methanogens can survive at temperatures greater than 100 ℃ (Takai et al.

2008). In addition, temperature does appear to select for different methanogenic communities

(Blake et al. 2015). While it has been established that sulfate-reducing bacteria generally outcompete methanogenic consortia by using the same substrate(s) more efficiently, recent

2- reports suggest that adding SO4 at low concentrations (≤ 5 mM) may enhance methanogenesis

(Siegert et al. 2011; Oberding 2016). Presumably, the addition of sulfate stimulates the growth of metabolically versatile bacteria that can respire sulfate or switch to syntrophic metabolism in its absence, such as Desulfovibrio spp. (Mayber et al. 2013a; 2013b). Regardless of the prevailing pathway, the overall syntrophic reaction yields extremely low Gibbs free energy (Tables 1-1), and that energy must be shared between all syntrophic partners (Sieber et al. 2012; Gieg et al.

2014).

Interspecies electron transfer mechanisms underlie thermodynamically favorable syntrophic processes. The best understood electron transfer mechanism is via H2 or formate exchange between the syntrophic partners (Stams and Plugge 2009; Sieber et al. 2012; Morris et al. 2013). Physiological studies and genomic sequencing of several syntrophic microorganisms have shown that multiple enzymes and/or membrane-bound complexes function during

H2/formate-based syntrophic processes, and include reverse electron transfer mechanisms when energy input is required (Sieber et al. 2012). The close association of syntrophic partners via aggregation has been shown to be important for electron transfer via H2 and formate (Morris et al. 2013). Aligning with this concept, alternate mechanisms for electron transfer can also occur via direct cell-to-cell contact (direct interspecies electron transfer; Rotaru et al. 2014a; 2014b) pili (Lovley 2012; Kato et al. 2012a) or via flagella (Shimoyama et al. 2009). Electron transfer via shuttle molecules (e.g. sulfur compounds, humic substances and flavins) have also been suggested to facilitate the reduction of higher redox electron acceptors such Fe3+ and Mn4+

(Lovley et al. 1998; Lovley et al. 1999; Newman and Kolter 2000; Kaden et al. 2002; Marsili et al. 2008; von Canstein et al. 2008; Brutinel and Gralnick 2012), but are not believed to be energetically viable options under methanogenic conditions. In natural anaerobic environments

Table 1-2. Overview of selected, phylogenetically-characterized methanogenic hydrocarbon-degrading enrichment cultures growing on alkanes, BTEX, PAHs, and crude oil. Substrate Origin of Incubation Identified taxa Reference enrichment culture temperature (℃) n-Hexadecane Bremen, Germany; 28 Syntrophus, Methanosaeta, Methanoculleus, Zengler et al. 1999 freshwater ditch Methanospirillum Light oil, heavy oil, Dagang oil field, PR 30 Pseudomonas, Smithella, Syntrophorhabdus, Jiménez et al. 2012; n-hexadecane, China Syntrophobacter, Desulfobulbus, 2015; Cai et al. 2015 monoaromatics, 2- Methanosaeta, Methanoculleus, methylnaphthalene Methanofollis, Thermoplasmata Oil, n-hexadecane Gas condensate- 21 Clostridium, Desulfobulbus, Townsend et al. 2003; contaminated Desulfitibacillum, Desulfotomaculum, Gieg et al. 2008; groundwater Desulfovibrio, Syntrophus, Methanoculleus, Morris et al. 2012 sediments, Fort Methanospirillum, Methanosaeta, Lupton CO Methanosarcina 2- Gas condensate- 21 – 23 Clostridium, Desulfobulbus, Desulfovibrio, Townsend et al. 2003; Methylnaphthalene, contaminated Methanoculleus, Methanosaeta, Gieg et al. 2008; 2, 6- groundwater Methanosarcina Berdugo-Clavijo et al. dimethylnaphthalene sediments, Fort 2012 Lupton CO Toluene Gas condensate- 21 Desulfosporosinus, Syntrophaceae, Gieg et al. 1999; contaminated Desulfovibrionales, Chloroflexi, Fowler et al. 2012; groundwater Spirochaetes, Methanoculleus, 2014 sediments, Fort Methanolinea, Methanosaeta Lupton CO Light and heavy oil Glauconitic C low- 33 Smithella, Pseudomonas, Methanosaeta, Berdugo-Clavijo and temperature (30 ℃) Methanoculleus, Methanobacterium Gieg 2014 oil field subjected to nitrate injection in Medicine Hat, AB

Benzene Tsuchiura, Japan; 25 Clostridium, Methanoculleus, Sakai et al. 2009 lotus field soil Methanoregula, Methanosaeta, Thermoplasmata Benzene Decommissioned 21 Deltaproteobacterium ORM2, Nales et al. 1998; gasoline station on ‘Parcubacteria’ (formerly OD1), Ulrich and Edwards Cartwright Avenue Methanoregula 2003; Mancini et al. in Toronto, ON 2008; Luo et al. 2016 Crude Oil Newcastle, UK; 21 Smithella, Marinobacter, Thauera, Jones et al. 2008; Tyne River Methanocalculus, Methanogenium, Gray et al. 2011 sediments Methanomicrobiaceae n-alkanes (C14-C18), Mildred Lake 20 Syntrophus, Desulfuromonas, Siddique et al. 2006; BTEX, naphtha Settling Basin, AB; Desulfobacterales, Methanosaeta, 2011 oil sands tailings Methanoculleus ponds n-alkanes (C6-C10), Mildred Lake 28 Peptococcaceae, Anaeolineaceae, Siddique et al. 2006; 2-methylpentane, 2- Settling Basin, AB; Desulfobacteraceae, Smithella, Syntrophus, Tan et al. 2013; methylcyclopentane oil sands tailings Methanosaeta, Methanoculleus 2015b; Abu Laban et ponds al. 2014 Benzene, Baltimore Harbor, 30 Aquificae, Bacteroidetes, Thermotogae, Chang et al. 2005a; naphthalene, MD; harbor Clostridia, Pseudomonas, Methanosarcina, 2005b phenanthrene sediments Methanoculleus, Methanococcus Phenanthrene, Landfield leachate 20 Methylibium, Legionella, Rhizobiales Zhang et al. 2012a; anthracene contaminated 2012b sediments n-alkanes (C28-C50) San Diego Bay, CA; 31 Smithella, Methanoculleus, Methanosaeta Wawrik et al. 2016 bay sediment

comprised of diverse microbial communities and dynamic geochemical surroundings, all of these electron transfer mechanisms are likely occurring (Gieg et al. 2014).

To date, a limited number of studies have documented evidence of methanogenic consortia growing on coal, oil and single model hydrocarbons (Table 1-2). The majority of these are from enrichment cultures established on either saturates or monoaromatic hydrocarbons, with a few notable exceptions enriched on polycyclic aromatic hydrocarbons (PAHs; Chang et al.

2005b; Berdugo-Clavijo et al. 2012; Zhang et al. 2012a; 2012b). Linear alkanes, naturally, are the most readily degraded hydrocarbons, producing methane up to 28 times faster than other complex hydrocarbon substrates (Jiménez et al. 2016). The complete mineralization of n- hexadecane to methane has been documented numerous times (e.g. Anderson and Lovley 2000;

Siegert et al. 2011; Jiménez et al. 2012), including through the pioneering study of methanogenic hydrocarbon biodegradation led by Zengler et al. (1999). Other studies have observed the degradation of the diluent naphtha (containing C7-C9 n-alkanes; Siddique et al. 2006), iso- alkanes (C7-C8; Abu Laban et al. 2014), as well as medium-length (C10-C18; Townsend et al.

2003; Gieg et al. 2008; Feisthauer et al. 2010; Mbadinga et al. 2012) and long-length n-alkanes

(up to C50; Oberding 2016; Wawrik et al. 2016). The monoaromatic hydrocarbons toluene and o- xylene have also proven to be biodegradable under methanogenic conditions (Edwards and

Grbić-Galić 1994; Feisthauer et al. 2010; Siegert et al. 2011; Fowler et al. 2012; Fowler 2014;

Sun et al. 2014; Abu Laban et al. 2015). The biodegradation of more alkylated aromatic hydrocarbons such as trimethylbenzene has been confirmed in field studies (Gieg et al. 2009;

Parisi et al. 2009), but the mechanism behind its degradation remains outstanding.

1.4 Pathways of anaerobic hydrocarbon biodegradation

1.4.1 Initial activation mechanisms

Under anoxic conditions, it has now been shown that (1) fumarate addition, (2) carboxylation, (3) hydroxylation, and (4) methylation are possible mechanisms by which microorganisms may initially activate hydrocarbons in the absence of O2 (reviewed by Heider

2007; Boll and Heider 2010; Meckenstock and Mouttaki 2011; Meckenstock et al. 2016; Rabus et al. 2016b, and references therein). Recently, a novel mechanism has been proposed to activate n-butane (and n-propane) via an alkyl-coenzyme M mechanism by a thermophilic archaeal phylotype in a manner analogous to that demonstrated for anaerobic methane oxidation operating via reverse methanogenesis (based on the formation of butyl-CoM as a metabolic intermediate and metagenomic inferences; Laso-Pérez et al. 2016), attesting to current postulates that several alternative mechanisms of hydrocarbon activation have yet to be discovered (Boll and Heider

2010; Callaghan 2013; Rabus et al. 2016b).

1.4.1.1 Fumarate addition

Of these activation types, fumarate addition (also referred to as ‘addition to fumarate’) is the most widely reported mechanism used by diverse anaerobic taxa to activate alkyl-branched aromatic compounds (alkylbenzenes, methylnaphthalenes, etc.), as well as linear and cyclic alkanes (Heider and Schühle 2013). For a methyl-substituted aromatic hydrocarbon such as toluene or 2-methylnaphthalene, the methyl group is added via a glycyl radical driven C-C addition reaction to the double bond of fumarate, forming (R)-benzylsuccinic or naphthyl-2- methylsuccinate (Biegert et al. 1996; Beller and Spormann 1997a; Annweiler et al. 2000;

Figure 1-2. Anaerobic biodegradation pathways of (A) model alkylbenzenes (B) proposed activation and subsequent degradation pathways for benzene. Metabolites are shown as free acids. Signature metabolites believed to be exclusively anaerobic are marked with an asterisk; theoretical metabolites are marked in brackets. Multiple arrows represent more than one enzymatic step; dashed arrows represent an unknown reaction. Structure nomenclature: 1, toluene; 2, benzylsuccinate; 3, E-phenylitaconate; 4, 2- [hydroxy(phenyl)methyl]succinate; 5, benzoylsuccinate; 6, xylene; 7, methylbenzylsuccinate; 8, E-(methylphenyl)itaconate; 9, toluate; 10, ethylbenzene; 11; 1- phenylethanol; 12, acetophenone; 13, benzoylacetate; 14, (1-phenylethyl)succinate; 15, (2- phenylpropyl)malonate; 16, 4-phenylpentanoate; 17, 2-phenylpropanoate; 18, benzoate; 19; cyclohex-1, 5-diene-1-carboxylate; 20, cyclohex-1-ene-1-carboxylate; 21, pimelate; 22, glutarate; 23, acetate; 24; benzene; and 25, phenol. From Gieg and Toth (2017b).

Beller and Edwards 2000; Achong et al. 2001; Kane et al. 2002; Figures 1-2 A and 1-3 A). An overview of structural and functional properties of toluene-activating benzylsuccinate synthase

(BSS) and other related glycyl radical-forming enzymes (e.g. (1-methyl)alkylsuccinate synthase,

ASS/MAS; naphthylmethylsuccinate synthase, NMS) is provided by Heider et al. (2016).

Alkylsuccinate synthase was discovered concurrently by two different research groups

(Grundmann et al. 2008; Callaghan et al. 2008), hence its two enzyme designations (ASS and

MAS). Similarly, fumarate addition to xylenes and ethylbenzene produces methylbenzylsuccinates (Krieger et al. 1999; Achong et al. 2001) and (1-phenylethyl)succinate

(Elshahed et al. 2001; Kniemeyer et al. 2003), respectively (Figure 1-2 A). In the case of n- alkanes, fumarate addition typically occurs at the subterminal C2 position yielding the corresponding (1-methylalkyl)succinate (designated herein more simply as an alkylsuccinate;

Kropp et al. 2000; Rabus et al. 2001; Cravo-Laureau et al. 2005; Callaghan et al. 2006; Figure 1-

4 A). Fumarate addition to n-alkanes may also occur to a lesser extent at C3 (Rabus et al. 2001) and at the terminal (C1) position in the case for the gaseous alkane n-propane (Kniemeyer et al.

2007; Savage et al. 2010; Musat 2015; Figure 1-4 C). Iso-alkanes have also recently been reported to be susceptible to fumarate addition (Abu Laban et al. 2014), in addition to several cyclic alkanes studied to date (Rios-Hernandez et al. 2003; Wilkes et al. 2003; Gieg et al. 2009;

Musat et al. 2010; Jaekel et al. 2015; Tan et al. 2015b; Figures 1-4 B and C).

1.4.1.2 Hydroxylation

Hydroxylation as a hydrocarbon activation mechanism has been most well characterized for ethylbenzene metabolism under nitrate-reducing conditions (Ball et al. 1996; Heider 2007).

Here, the O atom arises from water, and the metabolism proceeds through a series of reactions

Figure 1-3. Proposed anaerobic biodegradation pathways of (A) naphthalene/2- methylnaphthalene and (B) other PAHs. Metabolites are shown as free acids. Signature metabolites believed to be exclusively anaerobic are marked with an asterisk; theoretical metabolites are marked in brackets. Multiple arrows represent more than one enzymatic step. ‘Cometabolic’ refers to metabolites observed under cometabolic conditions with naphthalene and/or 2-methylnaphthalene serving as main substrates (Safinowski et al. 2006). Structure nomenclature: 1, naphthalene; 2, 2-methylnaphthalene; 3, naphthyl-2- methylsuccinate; 4, naphthyl-2-methylenesuccinate; 5, naphthyl-2- hydroxymethylsuccinate; 6, naphthyl-2-oxomethylsuccinate; 7, 2-naphthoate; 8, 5,6- dihydro-2-naphthoate; 9, 5,6,7,8-tetrahydro-2-naphthoate; 10, 1,2,3,4-tetrahydro-2- naphthoate; 11; hexahydro-2-naphthoate (4 isomers possible); 12, 1-hydroxy-octahydro-2- naphthoate; 13, cis-2-carboxylcyclohexylacetate; 14, decahydro-2-naphthoate; 15, glutarate; 16, phenanthrene; 17, phenanthrene carboxylate; 18, biphenyl; 19, biphenylcarboxylate; 20, indane; 21, indanoate; 22, indene; 23, indenoate; 24, acenaphthylene; 25, acenaphthylenoate; 26, acenaphthene; 27, acenaphthenoate; and 28, acenaphthylmethylsuccinate. From Gieg and Toth (2017b).

yielding benzoate (benzoyl-CoA in its biological form; Figure 1-2). Hydroxylation has also been suggested for the activation of benzene to phenol (Caldwell and Suflita 2000; Chakraborty and

Coates 2005; Figure 1-2 B) and was recently confirmed for the Fe(III)-reducer Geobacter metallireducens using isotopically-heavy water and genetic analysis (Zhang et al. 2013). Note, however, that the enzyme responsible for catalyzing the hydroxylation of benzene remains elusive. Other reports have attributed the formation of hydroxylated species (e.g. phenol, cresols, hydroquinone, methylhydroquinones) to abiotic reactions (e.g. Kunapuli et al. 2008; Abu Laban et al. 2010; Fowler et al. 2012), thus multiple lines of geochemical and molecular evidence are required to confirm biological hydroxylation of hydrocarbons.

1.4.1.3 Carboxylation

For other benzene-degrading cultures (Phelps et al. 2001; Musat and Widdel 2008; Abu

Laban et al. 2010; Holmes et al. 2011) as well as for non-substituted polycyclic aromatics

(Zhang and Young 1997; Davidova et al. 2007; Mouttaki et al. 2012), carboxylation has been reported to be the primary mechanism of activation, giving rise to benzoate from benzene

(Figure 1-2 B), 2-naphthoate from naphthalene (Figure 1-3 A), or phenanthrene carboxylate from phenanthrene (Figure 1-3 B). The most common method to definitively attribute PAH activation to carboxylation is by incubating cultures with [13C] bicarbonate-buffered growth medium, then

13 analyzing extracted hydrocarbon metabolites for CO2 incorporation by gas chromatography– mass spectroscopy (Zhang et al. 1997; Phelps et al. 2001; Davidova et al. 2007). This technique was recently adapted for use in a methanogenic naphthalene-degrading consortium (Berdugo-

Clavijo 2015), but failed to detect evidence of a labeled intermediate. A separate study examining the co-metabolism of other PAHs by a highly enriched 2-methylnaphthalene-

Figure 1-4. Proposed anaerobic biodegradation pathways of (A) n-alkanes and (B) cyclohexane, and (C) fumarate addition of other cycloalkanes and propane. Metabolites are shown as free acids. Signature metabolites believed to be exclusively anaerobic are marked with an asterisk; theoretical metabolites are marked in brackets. Multiple arrows represent more than one enzymatic step. Structure nomenclature: 1, n-alkane; 2, (2- methyl)alkylsuccinate; 3, (2-methylalkyl)malonate; 4, 4-methylalkanoate; 5, 2- alkylmalonate; 6, cyclohexane; 7, cyclohexylsuccinate; 8, (cyclohexylmethyl)malonate; 9, cyclohexylpropanoate; 10, cyclohexanecarboxylate; 11; methylcyclohexane; 12, methylcyclohexylsuccinate; 13, cyclopentane; 14, cyclopentylsuccinate; 15, methylcyclopentane; 16, methylcyclopentylsuccinate; 17, ethylcyclopentane; 18, ethylcyclopentylsuccinate; 19; propane; 20, isopropylsuccinate; and 21, n-propylsuccinate. From Gieg and Toth (2017b).

degrading sulfate-reducing culture (N47) also revealed a variety of carboxylic acid metabolites from indane, indene, acenaphthene, and acenaphthylene, which may have arisen from carboxylation (Safinowski et al. 2006; Figure 1-3 B). It should be noted that carboxylation has yet to be confirmed as a mechanism for methanogenic PAH biodegradation.

It was also reported that a hexadecane-degrading sulfate-reducer (Desulfococcus oleovorans Hxd3) carboxylates the alkane molecule at the C3 position, followed by a two-carbon removal (‘de-ethylation’) rather than degrade this alkane by fumarate addition (So et al. 2003); studies with a C16-degrading nitrate-reducing culture also suggested this mechanism (Callaghan et al. 2006; Callaghan et al. 2009). Details behind this mechanism remain outstanding and may instead involve an alternate mechanism (Callaghan 2013).

1.4.1.4 Methylation

A final mechanism (the least reported or understood) is that of methylation, which has been suggested to occur for the activation of benzene (wherein [13C] toluene was detected from studies with fully labeled benzene (Ulrich et al. 2005; Figure 1-2 B). In co-metabolic studies using the sulfate-reducing N47 culture, fumarate addition metabolites of the heterocycles benzothiophene, benzofuran, and indole were detected, also suggesting their formation following a methylation reaction (Safinowski et al. 2006). To date, though, a gene responsible for the expression of a methylating enzyme has not been described. Safinowski and Meckenstock (2006) initially reported the detection of naphthyl-2-methyl-succinate from naphthalene by the N47 culture, presumably following methylation to 2-methylnaphthalene, but subsequent studies demonstrated that carboxylation was, in fact, the mechanism of naphthalene activation by this culture (Mouttaki et al. 2012; Meckenstock et al. 2016; Figure 1-3 A).

1.4.2 Pathways following initial activation

Following the addition of fumarate to toluene, benzylsuccinate is activated to benzylsuccinyl-CoA that is then degraded via modified -oxidation reactions leading to the formation of benzoyl-CoA (e.g., Leutwein and Heider 1999; 2001; 2002; Figure 1-2 A), a key central metabolite in anaerobic aromatic hydrocarbon metabolism. Benzoyl-CoA subsequently undergoes a series of ring reduction reactions, beginning with the conversion to cyclic 1,5- dienoyl-CoA by an ATP-dependent or independent reaction (Fuchs et al. 2011; Boll et al. 2014).

Here, the pathway can diverge depending on the microorganism, ultimately leading to ring opening (Harwood et al. 1999; Fuchs et al. 2011). For the xylene isomers, analogous pathways from the methylbenzylsuccinates presumably occur, leading to the formation of toluates (Krieger et al. 1999; Elshahed et al. 2001b; Morasch et al. 2004; Figure 1-2 A). Detailed studies with p- toluic acid (4-methylbenzoic acid) revealed that ring reduction and cleavage occurs in a manner that parallels that of benzoyl-CoA, with minor differences (Lahme et al. 2012; Rabus et al.

2016a). For 2-methylnaphthalene degradation, naphthyl-2-methylsuccinate is also activated to its

CoA derivative and undergoes similar reactions to that of the toluene pathway leading to 2- naphthoyl-CoA; naphthalene biodegradation by carboxylation converges at 2-naphthoyl-CoA as well (Annweiler et al. 2000; Annweiler et al. 2002; Meckenstock et al. 2016; Figure 1-3 A). One ring of 2-naphthoyl-CoA then undergoes a step-wise series of recently characterized ring reduction reactions (Eberlein et al. 2013b; Eberlein et al. 2013a; Estelmann et al. 2015), that are presumably followed by as-of-yet uncharacterized ring opening reactions (Annweiler et al. 2002;

Figure 1-3 A).

For subsequent alkane degradation reactions, the formed alkylsuccinates are also presumably activated to their CoA esters (Wilkes et al. 2002). It has been postulated that this

molecule then undergoes a carbon skeleton rearrangement, followed by a decarboxylation step, yielding 4-methyl-branched fatty acids that have been detected as metabolites in C3-C16 alkane- amended cultures (Wilkes et al. 2002; Wilkes et al. 2003; Kniemeyer et al. 2003; Cravo-Laureau et al. 2005; Callaghan et al. 2006; Figure 1-4 A). These fatty acids then undergo -oxidation to central metabolic intermediates such as acetyl-CoA. Interestingly, following the formation of (1- methylphenyl)succinate, ethylbenzene metabolism under sulfate-reducing conditions was hypothesized to occur in the same manner as for n-alkanes (rather than via the known toluene pathway) as the identified intermediate 4-phenylpentanoate (-CoA) was positively identified

(Kniemeyer et al. 2003; Figure 1-2 A). It is unclear whether benzoate (benzoyl-CoA) is subsequently formed from ethylbenzene as a central metabolic intermediate under sulfate- reducing conditions, although Elshahed et al. (2001b) did detect benzoate in ethylbenzene- amended sulfate-reducing aquifer sediment enrichments. Following the hydroxylation of ethylbenzene to 1-phenylethanol under nitrate-reducing conditions, further metabolism leads to the generation of aceophenone, benzoylacetate, and the central metabolic intermediate benzoate

(Ball et al. 1996; Heider et al. 2016; Figure 1-2 A).

1.5 Tools for assessing anaerobic hydrocarbon biodegradation

When assessing a culture or field site for evidence of anaerobic/methanogenic hydrocarbon biodegradation, it is critical that integration of several different approaches is implemented in order to gain a comprehensive assessment and understanding of the processes governing the microbial community, as well as to overcome inherent limitations association with each particular method (Gieg et al. 1999; Weiss and Cozzarelli 2008; Bombach et al. 2010;

Rabus et al. 2016b). In general, there is no universally applicable guide for designing integrative

biodegradation studies. Rather, the selection of appropriate techniques largely depends on the specific questions being asked and the applicability of the methods for the specific hydrocarbon(s) of interest. Commonly used techniques include geochemical monitoring (e.g. of available electron acceptors, products, gases, and redox conditions), detection of hydrocarbon metabolites, molecular microbial analysis, biodegradative gene analysis, and compound- specific/stable isotope analysis (reviewed by Weiss and Cozzarelli 2008; Bombach et al. 2010;

Musat et al. 2016; Vogt et al. 2016; von Netzer et al. 2016; Rabus et al. 2016b). A brief description of each approach is provided in this section and includes an overview of their applications and limitations; methods outlining procedures adapted for this dissertation can be found in Chapter 3.

1.5.1 Geochemical monitoring

As overviewed in Section 1.2, the different redox reactions catalyzed by different microorganisms influence the energy gained from each process, as well as rates of biological hydrocarbon utilization. Thus, analyzing geochemical parameters such as electron acceptor availability and hydrocarbon degradation over time is vital for understanding and assessing anaerobic microbial processes occurring in situ and in laboratory cultures (US EPA, 2016).

- 3+ 2- Documenting the consumption of available electron acceptors (e.g. NO3 , Fe , or SO4 ) as well

- 2+ - as the generation of their reduced redox species (NO2 , Fe , and HS , respectively) by colorimetric assays and/or high pressure liquid chromatography (HPLC) provides valuable information about the predominant redox processes in a microbial ecosystem, and can be used to estimate rates of hydrocarbon biodegradation using stoichiometric calculations (Wiedemeier et al. 1999; Christensen et al. 2000; McMahon and Chapelle 2008). Under methanogenic

conditions, this can also be achieved by measuring gas production (e.g. CH4, CO2) from metabolized hydrocarbon substrates by gas chromatography (Bombach et al. 2010; Sherry et al.

2010). A key limitation of geochemical monitoring becomes apparent when monitoring the degradation of more than one substrate, as the depletion of electron acceptors reflects the oxidation of all organic matter in a sample rather than a single component. This can make it difficult to track which component(s) are actively being utilized by microbial communities. This can be mitigated to some degree by monitoring hydrocarbon concentrations over time in addition to available electron acceptors. Note, however, that hydrocarbon loss can likewise result from abiotic processes such as dispersion (in environmental sites), sorption (e.g. to sediments, to rubber stoppers), and/or volatilization, thus surveying control sites/microcosms are essential for confirming biological hydrocarbon utilization.

1.5.2 Hydrocarbon metabolite analysis

A handful of landmark studies in the 1980s and 1990s initially reported on the detection of potential hydrocarbon degradation products in the anoxic zones of hydrocarbon-impacted groundwater (Reinhard and Goodman 1984; Cozzarelli et al. 1990; Wilson et al. 1990; Schmitt et al. 1996). These products, including aromatic acids (such as benzoate, toluates, tolylacetate, and phenylacetate), along with alicyclic and aliphatic acids, were not present in uncontaminated areas. With the discovery of fumarate addition as a novel mechanism of anaerobic activation for toluene, Beller et al. (1992; 1995) proposed that benzylsuccinates could serve as unique or signature metabolites indicative of anaerobic hydrocarbon degradation. These metabolites are considered ideal because they (i) have an unequivocal relationship to their parent hydrocarbon,

(ii) are not known to be present in hydrocarbon mixtures themselves or in other sources, (iii) are

reasonably stable so they can be detected in environmental or cultured samples, and (iv) are transient metabolites so they would not be expected to accumulate over time (Beller 2000).

Elshahed et al. (2001b) substantiated the proposal put forth by Beller and colleagues after detecting fumarate addition metabolites from m-xylene, p-xylene and ethylbenzene in contaminated groundwater samples. Alkylbenzylsuccinates have since been repeatedly sought and detected to pinpoint alkylbenzene utilization across a variety of anaerobic cultures (e.g.

Beller et al. 1996; Beller and Spormann 1997a; Kniemeyer et al. 2003; Kunapuli et al. 2010;

Fowler et al. 2012; Jarling et al. 2015) and hydrocarbon-laden anoxic ecosystems (e.g. Gieg et al.

1999; Elshahed et al. 2001b; Martus and Puttmann 2003; Alumbaugh et al. 2004; Gieg et al.

2009; Parisi et al. 2009; Wawrik et al. 2012). Following the discovery that alkanes and 2- methylnaphthalene were also susceptible to fumarate addition reactions (Annweiler et al. 2000;

Kropp et al. 2000; Rabus et al. 2001), their corresponding alkylsuccinates and naphthylmethylsuccinates were also successfully found in several hydrocarbon-containing sites

(e.g. Gieg and Suflita 2002; Griebler et al. 2004; Safinowski et al. 2006; Duncan et al. 2009;

Parisi et al. 2009; Gieg et al. 2010; Jobelius et al. 2011; Morasch et al. 2011; Agrawal and Gieg

2013; Kimes et al. 2013; Bian et al. 2015).

Note here that many of the intermediates resulting from reactions downstream of the initial hydrocarbon activation reaction can arise from several other sources. Benzoate, for one, is a common central metabolic intermediate resulting from the anaerobic decay of numerous aromatic substrates under aerobic and anaerobic conditions (Fuchs et al. 2011). Toluates, while related to their parent hydrocarbon (o-, m-, or p-xylene) can also be produced via aerobic pathways (Assinder and Williams 1990). Fatty acids resulting from subsequent biodegradation of alkylsuccinates can also be difficult to definitively attribute to active hydrocarbon metabolism

because these kinds of compounds are commonly found in sediment organic matter and are constituents of biomass. Similarly, 2-naphthoate can arise from naphthalene carboxylation or as a downstream metabolite following fumarate addition, and can form aerobically (Mahajan et al.

1994). Despite the limitations, seeking these other metabolites can still be useful in documenting hydrocarbon metabolism, especially when other lines of evidence point towards anaerobic microbial activity, and when these metabolites are not found in control cultures/sites (Duncan et al. 2009; Bian et al. 2015). Some downstream metabolites of naphthalene or 2- methylnaphthalene such as partially reduced 2-naphthoate (e.g. 5, 6, 7, 8-tetrahydro-2- naphthoate) and carboxylated heterocycles or PAHs (from benzothiophene, benzofuran, acenaphthene, acenapthylene, indane, and indene) are only known to be produced anaerobically, thus can serve as signature anaerobic metabolites for these compounds (Figure 1-3).

1.5.3 Molecular microbial analysis

Even though several anaerobic hydrocarbon-utilizing isolates and mixed consortia have been described within the last 30 years, establishing active cultures from environmental samples is a tedious and time-consuming process. Further, it is debatable as to whether laboratory cultures truly represent the diversity of hydrocarbon degraders that may be found in various natural environments. Genomics has since emerged as an invaluable field of science that examines the genetic material, or genomes, of a microbial community in a culture-independent manner and have greatly expanded upon existing knowledge of microbial processes occurring in diverse environments (Callaghan 2013; Heider and Schühle 2013; Kimes et al. 2013; Gieg and

Toth 2017a). Prior to ~ 10 years ago, cultivation-independent characterization of microbial diversity was usually performed using clone libraries and Sanger sequencing or techniques such

as denaturing gradient gel electrophoresis or terminal-restriction fragment length polymorphism

(T-RLFP) analysis. While these approaches are sometimes still used (especially T-RLFP; von

Netzer et al. 2013; Gründger et al. 2015; Luo et al. 2016), most publications now describe the use of amplicon sequencing (primarily based on the 16S rRNA gene for prokaryotes) to identify the phylogenetic taxa present in each sample and to predict the microbial community’s putative functions. Here, DNA is extracted from mixed samples and subjected to PCR amplification using a primer set that targets specific variable regions of the highly conserved 16S rRNA gene (often the V3–V4 or V6–V8 regions; Chakravorty et al. 2007; An et al. 2013; Mizrahi-Man et al. 2013).

Note that there are several inherent sources of representational bias during amplicon preparation

(e.g. DNA extraction protocol, primer bias, template concentration) that have been indicated in several studies (e.g. Suzuki and Giovannoni 1996; Martin-Laurent et al. 2001; Berry et al. 2011;

Pinto and Raskin 2012; Kennedy et al. 2014). Homopolymer formation and other sequencing ambiguities are also common problems in next-generation sequencing platforms (e.g. 454 pyrosequencing), but have been ameliorated following advances in massively parallel sequencing tools such as the Illumina MiSeq and HiSeq systems (Luo et al. 2012; Caporaso et al.

2012).

Reconstructing individual genomes within metagenomic datasets can also help to provide enormous valuable information regarding the potential functionalities and interactions between community members within an ecosystem and can also lead to the discovery of new, previously unclassified taxa (Anantharaman et al. 2016). Gieg and Toth (2017a) summarize the metagenomics datasets surveyed from diverse hydrocarbon-containing environments over the past decade, including fossil energy reservoirs, hydrocarbon seeps and hydrothermal vents, as well as contaminated marine and terrestrial environments. That said, it should be noted that while

metagenomics can provide enormous amounts of informative genetic information (Segata et al.

2014; Pérez-Wohlfeil et al. 2016), it is an approach that merely describes metabolic potential of a microbial community – experimentation is still required to observe this potential.

1.5.4 Biodegradative gene analysis

The discovery and functional identification of a number of key enzymes involved in anaerobic hydrocarbon degradation have led to the successful establishment of several specific functional marker gene assays now widely used to interrogate microbial communities for the genomic potential to degrade hydrocarbons of interest (reviewed by von Netzer et al. 2016).

Fumarate addition genes are arguably the most common targets used for detecting anaerobic hydrocarbon-degrading consortia because of their well-defined functional affiliation and widespread occurrence (Winderl et al. 2007; Callaghan et al. 2010; von Netzer et al. 2013). The key activation genes for BSS, ASS/MAS, and NMS, encoded by bssA, assA/masD, and nmsA, respectively, are often linked to conserved protein motifs, which facilitates the development of specific primer sets for PCR and quantitative PCR (qPCR) assays (von Netzer et al. 2016). Beller and colleagues (2002) had initially designed a primer set based on a Betaproteobacterial (nitrate reducer) bssA sequence and successfully probed anoxic hydrocarbon-contaminated aquifer sediments for toluene biodegradation potential. Similarly, following the discovery of the assA/masD genes responsible for alkane activation, Callaghan et al. (2010) designed several primer sets based on the Desulfatibacillum alkenivorans AK-01 assA and bssA gene sequences, which were used to successfully detect both genes in a variety of enrichment cultures, river sediments, and contaminated aquifer samples. Several studies have since refined available assA and bssA primer sets to be applicable for targeting a greater diversity of sequences associated

with a broader range of environments, including hydrocarbon-contaminated aquifers, cold seeps, and hydrothermal vent systems (Winderl et al. 2007; Washer and Edwards 2007; von Netzer et al. 2013; Aitken et al. 2013; Gittel et al. 2015; Stagars et al. 2016). For example, a broad- specificity bssA primer set optimized by von Netzer et al. (2013) also demonstrated the ability to capture nmsA homologs, leading to the development of two novel nmsA PCR assays. Apart from fumarate addition enzymes, functional markers targeting conserved enzymes of the benzoyl-CoA degradation pathway have also been successfully employed to detected anaerobic aromatic hydrocarbon degraders (von Netzer et al. 2016). Primers targeting 2-naphthoyl-CoA reductase

(Ncr), a protein that catalyzes the reduction of the bicyclic naphthalene ring system during anaerobic degradation, have also been recently designed based on three naphthalene-degrading isolates (under sulfate-reducing conditions) and the N47 culture (Morris et al. 2014).

1.5.5 Compound-specific/stable isotope analysis

Compound-specific isotope analysis (CSIA) is an analytical method frequently used to assess hydrocarbon degradation in situ by measuring the ratios of naturally occurring stable isotopes of substrates in environmental samples. Isotopes of elements such as carbon (12C and

13C) and hydrocarbon (1H and 2H) react at slightly dissimilar rates during mass-differentiating reactions. During biodegradation, bonds containing the lighter isotopes are preferentially broken, causing the remaining hydrocarbon to be enriched in the heavier isotopes compared to the original isotopic value (Meckenstock et al. 2004; Bombach et al. 2010). Measuring the isotopic fractionation effect is particularly useful for assessing in situ hydrocarbon biodegradation because it does not require the enrichment of exogenous isotopic elements. For example, CSIA has been used to demonstrate that methane formed in oil and coal reservoirs, or contaminated

aquifers, is primarily biogenic in nature (e.g. Horstad et al. 1992; Horstad and Larter 1997;

Weiner and Lovley 1998; Thielemann et al. 2004). In terms of anaerobic hydrocarbon degradation, CSIA has been most commonly used to characterize the degradation of short-chain n-alkanes (Vieth and Wilkes 2006; Kniemeyer et al. 2007; Mastalerz et al. 2009; Jaekel et al.

2014), benzene (Mancini et al. 2008) and ethylbenzene (Dorer et al. 2014a; Dorer et al. 2014b).

CSIA has also recently been explored as a means to distinguish different mechanisms of anaerobic ethylbenzene degradation (Dorer et al. 2014b) and could prove to be particularly useful for characterizing the activations of other hydrocarbons including benzene (Mancini et al.

2008).

Stable isotope probing (SIP) employs the artificial enrichment of growth substrates with isotopically heavy isotopes (e.g. 13C, 15N) to monitor biodegradation processes (Neufeld et al.

2007). This technique, which has garnered widespread popularity in microbial ecology over the past 10 years, allows for the targeted detection and identification of organisms, metabolic pathways and elemental fluxes active in specific processes within complex microbial communities (reviewed by Vogt et al. 2016), which is not possible using CSIA. Though it is worthwhile to consider how this method may be applied for monitoring natural attenuation or bioremediation (Manefield et al. 2004; Madsen 2006; Uhlik et al. 2013), CSIA is a more practical option for assessing the biodegradation of mixed components in large-scale field investigations. SIP approaches are better used for tracing the fate of single organic components in complex heterogenous environments or in microbial communities containing unculturable representatives. To date, 13C-labeled SIP investigations targeting DNA, RNA, proteins, and phospholipid-derived fatty acids have been used to probe anaerobic hydrocarbon biodegradation, with some studies offering unequivocal evidence of methanogenic utilization of benzene (Sakai

et al. 2009; Noguchi et al. 2014), toluene (Fowler et al., 2014; Sun et al., 2014; Abu Laban et al.,

2015), n-hexadecane (Cheng et al. 2013), and the three-ringed PAH anthracene (Zhang et al.

2012a). Data obtained by sequencing the metagenome of isotopically heavy DNA fractions in

SIP (or associated metaproteomes) is also a relatively new approach for screening samples for new functions and physiological interactions (Grob et al. 2015). A caveat arises, particularly for nucleic acids, when substrate incorporation and incubation time are insufficient, generating poorly labeled biomarker molecules that are not distinguishable above background levels of relatively abundant unlabeled molecules. Too much substrate and excessive incubations times can be equally problematic, as these may lead to enrichment bias unreflective of the natural microbial community, or potential cross-feeding of the labeled substrate.

1.6 Research needs

Though considerable progress has been made to uncover the principles governing methanogenic hydrocarbon degradation, including the characterization of key degraders and their associated degradation pathways (Jiménez et al. 2016), our understanding of this field remains far from complete. Significant gaps in our knowledge exist primarily due to the difficulty of establishing hydrocarbon-degrading enrichment cultures under methanogenic conditions. Ergo, an idealistic solution would be to implement cultivation strategies that improve rates of methanogenic hydrocarbon utilization. Most of the research exploring this topic was published prior to the proliferation of cultivation-independent technologies for studying microbial ecosystems (e.g. Bryant and Robinson 1961; Moench and Zeikus 1983; Edwards and Grbić-

Galić 1994). Given that the thermodynamic landscape of hydrocarbon degradation cannot significantly be resolved (without supplying alternative electron acceptors, e.g. Morris et al.

2009; Zhang et al. 2010; Siegert et al. 2011) the next best, albeit tedious, solution may be to optimize physiochemical conditions (e.g. temperature, pH, salinity, pressure) during microbial cultivation with the goal of reducing microbial energy demands. This proved to be effective for

Ünal et al. (2012), who doubled rates of methanogenic activity in subsurface coal bed produced water enrichment cultures after adjusting the concentration of eight trace elements in their standard media. Ultimately, however, it remains to be seen whether optimizing growth conditions for established mixed cultures will indeed improve rates of hydrocarbon utilization, or if they are already at their bioenergetic limits.

If growth rates cannot be improved, future progress disseminating methanogenic hydrocarbon degradation will greatly depend on integrating multiple cultivation-independent tools to characterize existing, actively-degrading consortia. This will become particularly important for describing the anaerobic degradation of highly stable chemical structures such as benzene and PAHs, where comparatively few pure isolates and enrichment cultures have been cultivated (Meckenstock et al. 2016). Though phylogenetic classification of hydrocarbon-using taxa has long been the standard molecular approach for identifying putative fermentative

(syntrophic) bacteria and methanogenic partners, this technique only offers clues as to how microbial communities may coordinate and regulate their metabolisms for hydrocarbon transformation. Considering their recent surge in popularity, stable isotope probing (and other fractionation approaches) and metagenomics analysis will likely become standard approaches for elucidating the methanogenic degradation of an expanded range of hydrocarbons. Note that proliferation of these techniques should not detract investigators from pursuing classical cultivation-based evidence of methanogenic hydrocarbon biodegradation to demonstrate actual

metabolism, in addition to proven strategies such metabolomic surveys and functional gene analysis.

In all, the characterization of methanogenic hydrocarbon biodegradation is vital for understanding the pathways and the factors controlling degradation processes in many anoxic environments. Likewise, biodegradation in oil reservoirs and other hydrocarbon sources affects the quantity and quality of fossil fuels, thus the elucidation of this metabolic process is also of fundamental geological and industrial interest. As new research aims to address the biochemistry and physiology of anoxic hydrocarbon biodegradation (Rabus et al. 2016b), many questions remain open, e.g. the scope of methanogenic PAH biodegradation, the role(s) of microbial community members (of which many have unknown functions), the elemental cycling and energy fluxes within the microbial communities, as well as the interactions between biogeochemical factors and regulation of methanogenic communities. However, answers to these questions are unlikely to be uncovered any time soon unless we can first identify and adopt efficient technologies for assessing and monitoring some of the slowest growing microorganisms known on Earth.

Chapter Two: Research Objectives and Thesis Overview

2.1 Research objectives

The overarching goal of this Ph.D. dissertation was to glean new insights into the physiology of methanogenic hydrocarbon biodegradation using a series of chemical and molecular approaches. By characterizing the chemical and functional responses of methanogenic consortia to enrichment on model hydrocarbon substrates (monoaromatic hydrocarbons, polycyclic aromatic hydrocarbons, and n-alkanes) and on whole crude oil, we can gain a more complete understanding of the fate of oil components in electron acceptor-depleted environments. It is also advantageous to elucidate strategies for improving rates of hydrocarbon methanogenesis: not only will this help proliferate the dissemination of knowledge in this slow- moving field, it has practical applications for the remediation of hydrocarbon-contaminated areas and for enhanced oil recovery technologies. With this in consideration, the following research objectives were set to direct research experiments:

1. Assess the feasibility of accelerating rates of methanogenic hydrocarbon (toluene)

biodegradation, which I hypothesized was possible by modifying the physicochemical

conditions used to cultivate a previously established toluene-degrading consortium

(TOLDC). Here, I also sought to determine whether modifying the microbial community

composition of TOLDC could also increase rates of toluene consumption.

2. Using a series of previously established hydrocarbon-degrading enrichment cultures (grown

on toluene or two-ringed PAHs) as well as production water from a heavy oil-producing field

site, assess their physiological capacity to metabolize an expanded range of hydrocarbon

substrates under methanogenic conditions and characterize their mechanism(s) of

biodegradation. Based on previous metagenomic inferences conducted by Fowler (2014) and

An et al. (2013), I hypothesized that these microbial communities evaluated were capable of

degrading monoaromatic hydrocarbons (BTEX), n-alkanes, and PAHs. This objective was

divided into three sections;

a. Identify putative mechanisms of methanogenic hydrocarbon activation by searching

for signature anaerobic hydrocarbon metabolites in active cultures,

b. Identify and quantify the expression of key functional genes involved in hydrocarbon

activation,

c. Identify key microorganisms present in selected cultures potentially responsible for

hydrocarbon activation and subsequent degradation.

2.2 Organization of dissertation and contributions of co-authors

This dissertation has been prepared as a series of manuscripts (Chapters 4 – 7) and a traditional-style materials and methods section (Chapter 3) overviewing the most commonly used procedures employed throughout this thesis. Each research chapter (or minimally components of each chapter) is intended to be submitted for publication. Some additional text has been included to build continuity across research chapters, as many of the conclusions drawn from individual studies have relevance to other studies conducted for this dissertation. The research presented here was carried out by myself and in collaboration with a number of other contributors, whose contributions are included here. Supplementary information accompanying chapter results are included as appendices (Appendices A-D). Additionally, I contributed as a co- author with Dr. Lisa Gieg to two book chapters for the Handbook of Hydrocarbon and Lipid

Microbiology series (Gieg and Toth 2017a; 2017b), components from which were adapted for my literature review (Chapter 1), and a manuscript published in Frontiers in Microbiology

(Fowler et al. 2016), where I assayed for and interpreted biodegradation gene results from a series of crude oil- and n-alkane-degrading enrichment cultures:

Appendix E: Gieg LM, Toth CRA (2017b) Signature metabolite analysis to determine in situ anaerobic hydrocarbon biodegradation. In: Timmis KN (Ed) Handbook of Hydrocarbon and

Lipid Microbiology Series: Anaerobic Utilization of Hydrocarbons, Oils, and Lipids. Springer

International Publishing, New York, NY, pp. 1–30.

Appendix F: Gieg LM, Toth CRA (2017a) Anaerobic biodegradation of hydrocarbons –

Metagenomics and metabolomics. In: Timmis KN (Ed) Handbook of Hydrocarbon and Lipid

Microbiology Series: Consequences of Microbial Interaction with Hydrocarbons, Oils and

Lipids: Biodegradation and Bioremediation Springer International Publishing, New York, NY, in production.

Appendix G: Fowler SJ, Toth CRA, Gieg LM (2016) Community structure in methanogenic enrichments provides insight into syntrophic interactions in hydrocarbon-impacted environments. Front Microbiol 7:562.

Chapter 3 provides a detailed overview of the most common materials and methods employed for research conducted for this dissertation, and is intended to eliminate some redundancy across thesis chapters. Other procedures used in preparation of this dissertation are summarized in their respective chapter(s).

Chapter 4 addresses Research Objective 1 and summarizes more than a dozen experiments used to evaluate putative cultivation strategies for accelerating rates of methanogenic hydrocarbon biodegradation. The impact of reducing agents, incubation conditions, and cell density, among other methods, were assessed using an established toluene-

degrading consortium (TOLDC; Fowler et al. 2012; 2014). The most effective methods tested were combined and adopted for cultivation of various methanogenic hydrocarbon-degrading cultures described in later chapters. We also acquired preliminary evidence disseminating the role of a presumed Syntrophus in TOLDC, which along with accompanying metabolic evidence

(described in Chapter 5) and future investigations is intended to be submitted for publication.

Chapter 5 summarizes physiological experiments used to characterize the substrate diversity of TOLDC, as well as two previously described enrichment cultures capable of degrading 2-ringed PAHs (2MNDC, 26DMNDC; Berdugo-Clavijo et al. 2012), in alignment with Research Objective 2a. The rationale behind this chapter stems from previous metagenomic evidence suggesting that TOLDC may be capable of degrading other aromatic hydrocarbons and possibly n-alkanes, despite almost 20 years of enrichment on toluene (Tan et al. 2015a), and was a future direction set by Dr. S. Jane Fowler as part of her Ph.D. research (Fowler 2014). The chapter details preliminary chemical evidence of co-metabolic conversion of xylenes and ethylbenzene by (presumed) toluene degraders in TOLDC, but confirmation is still required.

Likewise, further characterization of a putative phenanthrene-degrading enrichment culture

(from 26DMNDC) is needed before being considered for publication.

Chapter 6 consists of stable isotope probing and metagenomics experiments evaluating the feasibility of using [13C] DNA-SIP to pinpoint key organisms responsible for the degradation of naphthalene (a two-ringed PAH) and phenanthrene (a three-ringed PAH) metabolism under methanogenic conditions (Research Objectives 2a and 2c). This project was made possible in part by funding provided by the Deep Life Community as part of their Decadal Goal III, which aims to determine pathways of carbon transformations in the deep subsurface. Results

pinpointing Clostridium as a putative naphthalene degrader will be reformatted for publication in the coming months.

Chapter 7 summarizes time course experiments used to assess microbial community and functional dynamics of an oil field produced water consortium in response to light or heavy crude oil (Research Objective 2a – 2c). This research began as part of a collaborative effort between the Energy Bioengineering and Geomicrobiology Research Group (EBG; led by Dr.

Marc Strous) and Dr. Lisa Gieg in 2015 to investigate methanogenic biotransformation of crude oil in petroleum reservoirs using continuous flow bioreactors, but the intended project was unsuccessful. Parallel static incubations that I had prepared and monitored separately using analytical (GC-FID, GC-MS) and biochemical (16S rRNA gene sequencing, targeted functional gene analysis) approaches proved more fruitful and are the subject of this chapter. This manuscript was deemed worthy for publication by my examination committee and will be submitted immediately.

Chapter 8 summarizes the key findings of this dissertation, providing a high-level summary of key research findings and outlines future work suggested for the continuation of this research. I also offer future perspectives relevant to the dissemination of methanogenic hydrocarbon degradation based on current insights from published sources and from my own graduate student experience.

Preface

Chapter 3 provides a detailed overview of the most common procedures employed in this dissertation for characterizing methanogenic hydrocarbon biodegradation. This chapter describes the cultivation, maintenance, and experimentation of hydrocarbon-amended microcosms inoculated with heavily enriched methanogenic consortia or samples obtained from hydrocarbon- containing environments. Also, presented here are several analytical detection techniques and culture-independent molecular microbial ecology tools used to gain an integrative understanding of the key microorganisms and functional principles governing hydrocarbon biotransformation to methane. Any additional, specific experimental procedures are summarized in their respective thesis chapters.

Chapter Three: Summary of Commonly Used Materials and Methods

3.1 Enrichment culture inoculum description

The biodegradation of hydrocarbons is a near-ubiquitous process now known to occur across a wide array of anaerobic hydrocarbon-impacted environments (recently reviewed by

Rabus et al. 2016b). Many of the principles governing anaerobic hydrocarbon metabolism have been mainly determined by studying either highly enriched consortia or pure cultures isolated from hydrocarbon-bearing environments (Widdel et al. 2010; Heider and Schühle 2013; Stagars et al. 2016). Many of the cultures described herein were established from repeated transfer and enrichment of hydrocarbon-impacted groundwater aquifer sediments collected nearly 20 years ago (Figure 3-1). Others were enriched from oil-containing environments, including a shallow oil reservoir and from deep bituminous oil sands. While contemporary molecular tools in microbial ecology serve to provide enormous amounts of novel (meta)genomic information pertaining to anaerobic hydrocarbon biodegradation (Anantharaman et al. 2016; Gieg and Toth 2017a), experimentation is still required to help interpret and confirm genomics-based predictions.

3.1.1 TOLDC

TOLDC (toluene-degrading culture) was the first sediment-free consortium enriched on a model hydrocarbon under methanogenic conditions by the laboratory of L.M. Gieg. The culture was established from repeated transfer and enrichment of gas condensate-contaminated aquifer sediments actively undergoing intrinsic in situ bioremediation near Fort Lupton, CO (Gieg et al.

1999). This environment has been found to contain microorganisms with the ability to degrade a suite of hydrocarbons, including toluene, under sulfate-reducing and methanogenic conditions

(Gieg et al. 1999; Elshahed et al. 2001b; Gieg and Sulflita 2002; Rios-Hernandez et al. 2003;

Struchtemeyer et al. 2005).The community structure of TOLDC and its mechanism of toluene biotransformation to methane have both been described in previous publications by Fowler et al.

(2012; 2014), thus only brief details will be presented here. Time-resolved RNA stable isotope probing and reverse-transcription polymerase chain reaction (RT-PCR) assays identified a

Desulfosporosinus sp. (belonging to the Firmicutes phylum) to be chiefly responsible for the initial catabolic attack of toluene by an experimentally verified benzylsuccinate synthase enzyme, followed by subsequent metabolism by one or more proposed taxa (including

Clostridium, Desulfovibrio and Syntrophus). The roles of several abundant taxa thought to be uninvolved in toluene degradation (e.g. Geobacter) remain elusive, whereas others (e.g.

Pseudomonas, Lachnospiraceae) are now believed to participate in the metabolism of an alternative carbon source (Chapter 4).

In addition to targeted genomic surveys, TOLDC was also processed for metagenomic analysis using a combination of merged 454, Illumina and Sanger sequencing reads (Fowler

2014; Tan et al., 2015a). The final metagenome (~605 Mbp) revealed the presence of a bssA fragment homologous to the gene responsible for toluene activation (Fowler et al., 2012; 2014;

Tan et al., 2015a), as well as contigs harbouring three additional bssA gene fragments and two putative assA sequences (Fowler 2014). Tan et al. (2015a) expanded upon this initial search and detected several more gene fragments associated with the anaerobic degradation of monoaromatic hydrocarbons (benzene, toluene, ethylbenzene, and xylene; BTEX), two-ringed

PAHs, and n-alkanes. This functional evidence led Fowler and colleagues to postulate that

TOLDC may be capable of degrading other model hydrocarbons despite > 10 years of enrichment on toluene, and became a major focus of this dissertation (Chapter 5).

TOLDC is easily the fastest hydrocarbon-degrading culture maintained by our laboratory, metabolizing ~17 mg of toluene/week/L of culture, but to give this some perspective, it would require that same volume of culture approximately 1127 years to metabolize 1 kg of toluene.

Scaling up the volume of these cultures is also a tedious and time-consuming process that is wildly unpractical using conventional methods for cultivating anaerobic/methanogenic and hydrocarbon-degrading consortia. Therefore, several alternative cultivation approaches were explored for enhancing rates of methanogenic hydrocarbon metabolism, primarily using TOLDC as the source inoculum (Chapter 4).

3.1.2 2MNDC, NDC, and 26DMNDC

2MNDC is an active methanogenic 2-methylnapthalene-degrading enrichment culture that originated from the same site as TOLDC (Gieg et al. 1999). Retrieved aquifer sediments were enriched on whole crude oil (Townsend et al. 2003; Gieg et al. 2008) before being transferred onto 2-methylnaphthalene in 2010 (Berdugo-Clavijo et al. 2012). Methanogenic activity from 2-methylnaphthalene was confirmed by comparing multiple lines of analytical evidence (methane production, substrate loss, hydrocarbon metabolite detection) to substrate-free and sterile controls. After its successful enrichment, 2MNDC was transferred onto other two- ringed PAHs, including naphthalene (NDC) and 2, 6-dimethylnaphthalene (26DMNDC). In the first generation of enrichments, 2-methylnaphthalene and 2, 6-dimethylnaphthalene were found to be readily metabolized under methanogenic conditions, whereas naphthalene degradation was considerably slower (Berdugo-Clavijo et al. 2012). Upon an additional transfer, however,

improved rates of methanogenic activity were reported from NDC (Berdugo-Clavijo 2015).

Culture-independent molecular analysis of each culture revealed that the dominant community members belonged to methanogenic archaea (Methanosaeta and Methanoculleus) and

Clostridiaceae (Berdugo-Clavijo et al. 2012; Berdugo-Clavijo 2015), but their roles within each microbial community were not confirmed. To expand upon this existing information, new experiments were conducted with 2MNDC, NDC, and 26DMNDC to evaluate methanogenic biodegradation of larger molecular weight PAH substrates (Chapters 5 and 6) and to identify key

PAH degraders using 13C-labeled DNA-based stable isotope probing (DNA-SIP; Chapter 6).

3.1.3 PHDC

PHDC is a newly established enrichment culture reported to degrade the three-ringed

PAH phenanthrene under methanogenic conditions, which was derived from a 10% v/v transfer of 26DMNDC. Analytical and genomic evidence of methanogenic activity from phenanthrene is detailed in Chapter 5.

3.1.4 MHGC produced water

Several new enrichment cultures were prepared using produced water (PW) from the

Medicine Hat Glauconitic C (MHGC) field in the Western Canadian Sedimentary Basin located in southern Alberta, Canada. This field is a shallow (~1000 m), low-temperature (~30 ℃) glauconitic sandstone reservoir producing approximately 1000 m3/day of heavy oil (API° ~16) by water injection (Voordouw et al. 2009). This field has also served as an invaluable souring control test site (via pulsed nitrate injection) for the past 10 years (Voordouw et al. 2009;

Agrawal et al. 2012; Voordouw et al., in preparation). Routine 16S rRNA gene surveys of the

MHGC field have identified several PW locations to be comprised predominantly of methanogenic consortia, with up to 90% of total reads belonging to methanogenic archaea

(Voordouw et al., in preparation). Complementary microcosm investigations conducted by

Berdugo-Clavijo and Gieg (2014) reported that select PAHs (e.g. methylnaphthalenes, phenanthrene) present in MHGC oil were partially degraded under methanogenic conditions by an MHGC produced water consortium after 315 days of incubation (Berdugo-Clavijo and Gieg

2014; Berdugo-Clavijo 2015). Here, a similar mixture of produced water obtained from five production wells (PW; 4-PW, 7-PW, 18-PW, 32-PW, 33-PW; Figure 7-1) was probed for putative PAH-degrading microorganisms (18PW only; Chapter 6) and monitored for microbial/functional dynamics in response to enrichment on light and heavy oils (Chapter 7).

3.1.5 Oil sands enrichment culture

A series of active methanogenic cultures enriched on deep bituminous oil sands (∼500 m depth) were previously prepared using Cold Lake oil sands deposits in northeastern Alberta,

Canada. Cultures were established using a brackish (4.3 g/L NaCl) minimal medium and inoculated with 26MNDC to stimulate heavy oil degradation (Cowie 2013). Subcultures of these microcosms were enriched on model PAHs (2, 6-dimethylnaphthalene, phenanthrene) in 2013 and were found to produce elevated amounts of methane compared to substrate-free controls

(Montoya, unpublished results). Experimental microcosms studied in Chapter 6 were pre- exposed to PAHs (within the bitumen) for ~4 years before being queried for PAH degraders using DNA-SIP analysis.

3.2 Cultivation parameters

Techniques for growing anaerobic consortia vary in detail among laboratories, but the procedures stem from the methodology devised and perfected by R.E. Hungate (Hungate 1950;

1969). To this day, the preparation of pre-reduced medium includes three essential steps; the addition of (i) an inorganic buffering agent (e.g. sodium bicarbonate/CO2) to maintain a pH near neutrality, (ii) a reductant (e.g. cysteine sulfide, sodium sulfide) to maintain a oxidation/reduction potential suitable for strict anaerobic growth (typically below – 330 mV), and (iii) a redox indicator such as resazurin, which turns pink when oxidized and colourless when reduced to or below – 110 mV (Jacob 1970). Cultivation of oil-degrading microorganisms in anaerobic serum bottle microcosms requires additional technical measures to address (i) slow growth rates, (ii) the poor solubility of oils and many hydrocarbons in water, (iii) hydrocarbon volatilization and adsorption to stoppers (Widdel et al., 2010), and (iv) potential hydrocarbon toxicity (Sikkema et al. 1995). The following sections summarize the standard procedures used to cultivate and maintain most of the cultures described in this dissertation and remarks on the considerations above.

3.2.1 Growth media and cultivation strategies

A variety of anaerobic growth media were used to cultivate methanogenic hydrocarbon- degrading enrichment cultures and prokaryotic isolates, summarized in Tables 3-1 to 3-3.

For routine cultivation of methanogenic hydrocarbon-degrading enrichment cultures, 20–

50% v/v of active culture was inoculated into anoxic bicarbonate-buffered mineral salts medium containing sodium sulfide (0.005% w/v) as a reductant (McInerney et al. 1979; Tables 3-1 – 3-3).

Prior to 2014, a mixture of cysteine-HCl and sodium sulfide (0.005% w/v) was used to reduce

cultures in the laboratory of L. Gieg (Fowler et al. 2012; 2016; Berdugo-Clavijo et al. 2012;

Berdugo-Clavijo and Gieg, 2014) but was ceased upon the discovery that L-cysteine was being used as a growth substrate preferentially over hydrocarbons (Chapter 4). To prepare the growth medium, all ingredients (excluding NaHCO3 and the reductant) were dissolved in ‘ultrapure’ water (Milli-Q, Millipore) and its pH adjusted to 7.0 using 1 M NaOH. The medium was made anoxic by boiling, then cooling on ice while flushing the solution under a stream of 10% CO2 in

N2. NaHCO3 was added to the medium once cool, and the solution was promptly dispensed into serum bottles pre-flushed under a stream of N2/CO2 (100 mL/min) for 3 – 10 minutes, depending on the size of the serum bottle used. Microcosms were sealed with a rubber stopper and an aluminum crimp; conventional butyl rubber stoppers (Bellco Glass) were used for most applications, but were substituted for hydrocarbon sorption-resistant Viton rubber stoppers (part no. 7399; Rubber B.V.) in microcosms amended with PAHs or cultures with extensive incubation periods (>2 years). To prepare the reductant solution (2.5% w/v), Na2S·9H2O crystals were washed with dH2O, dried, weighed, and taken in an anaerobic chamber (Coy Laboratory

Products) where the crystals were dissolved in an anoxic 0.01 N NaOH solution (prepared by boiling and cooling under a stream of N2). Cultures were reduced with 2 mL of the reductant solution for every 100 mL of growth medium, resulting in a final concentration of 0.05% w/v.

Microcosms were incubated at room temperature (~21 ℃) under dark and static conditions unless otherwise specified. For BTEX-amended cultures, microcosms were also stored in an inverted position to reduce hydrocarbon adsorption to the butyl rubber stopper. Experimental culture volumes typically ranged between 10 – 100 mL per microcosm, whereas volumes of up to 350 mL were achieved for culture maintenance. Experimental microcosms were generally

Table 3-1. General anaerobic mineral salts medium for cultivating of methanogenic hydrocarbon-degrading enrichment cultures (adapted from McInerney et al. 1979). Component Amount / L water K2HPO4 0.50 g MgCl2·6H2O 0.33 g NaCl 0.40 g NH4Cl 0.40 g CaCl2·2H2O 0.05 g Wolin’s trace metal solution 1.00 mL Batch vitamin solution 1.00 mL Resazurin solution (0.1% w/v) 0.10 mL NaHCO3 0.35 g Na2S·9H2O solution (2.5% w/v) 2.00 mL

Table 3-2. Wolin’s trace metal solution. Component g/L water Ethylenediaminetetraacetic acid 0.50 MgSO4 3.00 MnSO4·2H2O 0.50 NaCl 1.00 CaCl2·2H2O 0.10 ZnSO4·7H2O 0.10 FeSO4·7H2O 0.10 CuSO4·5H2O 0.01 Na2MoO4·2H2O 0.01 H3BO3 0.010 Na2SeO4 0.005 NiCl2·6H2O 0.003

Table 3-3. Balch vitamin solution. Component mg/L water D(+)-Biotin 2.00 Folic acid 2.00 Pyridoxine-HCl 10.0 Thiamine-HCl 5.00 Riboflavin 5.00 Nicotinic acid 5.00 DL-calcium pantothenate 5.00 Vitamin B12 0.10 4-Aminobenzoic acid 5.00 Lipoic acid 5.00 Mecaptoethanesulfonic acid 5.00

prepared in duplicate or triplicate, depending on the volume of available source inoculum, in addition to substrate-free (unamended) and cell-free (sterile) control replicates.

3.2.2 BTEX amendment

Benzene, ethylbenzene, and xylene, among other hydrocarbons, were explored as putative monoaromatic hydrocarbon growth substrates for TOLDC (Chapter 5). In general,

BTEX-amended microcosms were inoculated with 0.005% w/v of the desired hydrocarbon (~300

µM in the aqueous phase) using a 10 µL glass syringe, achieving a suitable balance between substrate bioavailability for metabolism, while minimizing potential inhibitory effects on cellular growth (Sikkema et al. 1995). This benchmark concentration was previously established by

Fowler et al. (2012; 2014) and has since been applied to other methanogenic hydrocarbon- degrading cultures (Abu Laban et al., 2015).

BTEX, in addition to other volatile compounds, partition between the aqueous and gaseous phases of their environment (the ratio being referred to as Henry’s Law constant), which allowed for routine measurement of hydrocarbon loss by gas chromatography (Section 3.3.2).

Cultures were reamended with BTEX once the substrate had reached below-detectable levels in the microcosm headspace. For routine cultivation of BTEX-degrading enrichment cultures, incubations were reamended an average of 20 times before being transferred. It was necessary to accumulate sufficient amounts of biomass in each microcosm (>108 cells/mL) in order to maintain active hydrocarbon metabolism post-transfer. Without repeated amendment, lag phases of up to 100 – 150 days were reported with negligible rates of methanogenic activity (Chapter 4).

3.2.3 Alkane amendment

Four straight-chained alkanes (n-C6H14, n-C10H22, n-C16H34, and n-C18H38) were evaluated as hydrocarbon substrates for TOLDC in experiments outlined in Chapter 5. Because alkanes are virtually insoluble in water, a non-degradable carrier phase was required to obtain sufficient concentrations of substrate in each microcosm (0.025 – 0.1% w/v) and to reduce potential toxic effects. Hydrocarbons were dissolved in 1 mL of the nontoxic, inert carrier 2, 2, 4,

4, 6, 8, 8-heptamethylnonane (HMN) before being amended in select microcosms. Each hydrocarbon solution was prepared anaerobically by bubbling under a stream of N2 gas for 20 minutes, and was sterilized by autoclaving. A similar procedure was outlined by Fowler et al.

(2016) to prepare and establish a methanogenic n-octadecane-degrading consortium.

3.2.4 PAH amendment

Cultivation of microorganisms on two- and three-ringed PAHs was performed in an identical manner used to grow cultures on n-alkane substrates. Naphthalene (C10H8), 2- methylnaphthalene (C11H10), 2, 6-dimethylnaphthalene (C12H12), phenanthrene (C14H10) or anthracene (C14H10) dissolved in HMN were added to microcosms in concentrations of 0.020 –

0.025% w/v in accordance with Berdugo-Clavijo et al. (2012). Experiments exploring PAHs as growth substrates can be found in Chapters 5 and 6. Due to their slow growth rates, PAH- degrading enrichment cultures were rarely transferred (≤ 3 times over a period of 5 years).

3.3 Analytical procedures

Several methods exist to study anaerobic hydrocarbon-degrading microcosms (reviewed by Sherry et al. 2010; Jiménez et al. 2016; Rabus et al. 2016b), but most require an initial

physical disruption of experimental cultures, and are ill-advised for repeated measurements of methanogenic consortia. Therefore, the most common approach to monitor methanogenic activity is by measuring headspace gas production and hydrocarbon loss. Using these approaches, samples can be taken repeatedly and frequently in order to monitor differences between experimental microcosms and their respective controls. Such information is crucial for timing the sacrificial sampling of cultures for molecular analysis and metabolite surveys.

3.3.1 Methane measurements

Methane production was routinely monitored from all anaerobic cultures using a Hewlett

Packard 5890 Series gas chromatograph (GC) equipped with a flame ionization detector (200 ℃) with helium as the carrier gas (Fowler et al. 2012; Fowler et al. 2016). Briefly, a sample from the incubation headspace (0.2 mL) was sampled using a sterile 1-mL plastic syringe flushed with 0.2

µM filtered anaerobic gas (10% CO2 in N2) and injected from a 150 ℃ inlet onto a packed stainless steel column (18ʺ long × 1/8ʺ i.d., Poropak R, 80/100, Supelco) held isothermally at 100

℃. Methane amounts were determined using calibration curves prepared from standard methane concentrations (0.1 – 10% CH4). For enrichment cultures amended with a model hydrocarbon

(e.g. toluene, naphthalene), stoichiometric correlations were prepared to predict the theoretical methane production from each substrate (assuming 100% conversion to methane; Symons and

Buswell 1933), as shown in eqn 1;

푎 푏 푛 푎 푏 푛 푎 푏 퐶 퐻 푂 + (푛 − − ) 퐻 푂 → ( − + ) 퐶푂 + ( + − ) 퐶퐻 (eqn 1) 푛 푎 푏 4 2 2 2 8 4 2 2 8 4 4

3.3.2 Hydrocarbon measurements

BTEX loss was measured using an Agilent 7890A GC with an FID maintained at 250 ℃.

Injections of incubation headspace (50 µL) sampled using a gas-tight glass syringe were carried out at 250 ℃ onto a HP-5 capillary column (30 m × 320 µm × 0.25 µm film, Agilent

Technologies) held isothermally at 100 ℃. The total hydrocarbon concentration in BTEX- amended incubations was calculated with Henry’s Law constant at 25 ℃ (0.224 for benzene,

0.244 for toluene, 0.404 for ethylbenzene, and 0.176 – 0.294 for xylene; Heath et al. 1993). To measure the loss of hydrocarbons dissolved in HMN, 1 µL the overlay was injected onto the GC-

FID described above, but with the following oven parameters; a 2 min hold at 40 ℃, a temperature ramp of 7 ℃/min for 20 min, and a final hold at 180 ℃ for 3 min. The inlet and detector temperatures were also adjusted to 275 ℃ and 300 ℃, respectively. Hydrocarbon amounts were determined using calibration curves prepared from standards of known concentrations (prepared by dissolving components in ethyl acetate).

3.3.3 Hydrocarbon metabolite extraction, identification and quantification

The detection and identification of metabolites of anaerobic hydrocarbon degradation pathways was used to determine if biodegradation was occurring in many enrichment cultures.

Supernatants from select methanogenic hydrocarbon-degrading enrichment cultures (10 – 50 mL) were acidified with anoxic 6M HCl (pH < 2), which was prepared by flushing the acid with

N2 gas for 20 minutes. The acidified solution was extracted for metabolites using three equal volumes of ethyl acetate (25 mL), dried over anhydrous sodium sulfate, and concentrated to ~ 1 mL by rotary evaporation at 60 ℃. Samples were concentrated a second time under a stream of

N2 and heat (80 ℃) to obtain a final volume of 50 µL. Components in the concentrated extracts

Table 3-5. Mass spectral features (GC-MS, as trimethylsilyl esters) of authentic metabolite standards associated with anaerobic biodegradation of monoaromatic hydrocarbons, n-alkanes, and PAHs. Signature anaerobic metabolites are distinguished from other intermediates that may also be formed abiotically, through aerobic hydrocarbon degradation pathways, or by unrelated pathways. Parent Signature metabolite Diagnostic ions (m/z) m/z reference hydrocarbon Fumarate addition products of monoaromatic hydrocarbons, signature anaerobic Toluene Benzylsuccinate 352 (M), 337 (M-15), 235, 221, 205, 190, Gieg et al. 2009 147, 145, 132, 73

Xylene Methylbenzylsuccinate 366 (M), 351 (M-15), 248, 235, 204, 159, Elshahed et al. 2001b 145, 105, 73

Ethylbenzene (1-phenylethyl)succinate 366 (M), 351 (M-15), 248, 235, 204, 145, Elshahed et al. 2001b 105, 73

Downstream products of monoaromatic hydrocarbons, not uniquely anaerobic Xylene Methylbenzoate (Toluate) 208 (M), 193 (M-15), 149, 119, 91

Benzene Phenol 166 (M), 151 (M-15), 91, 77 Caldwell and Sulflita 2000

Toluene, Benzoate 194 (M), 179 (M-15), 135, 105, 73 benzene, xylene, ethylbenzene Cyclohex-1-ene-1-carboxylate 198 (M), 183 (M-15), 156, 139, 108, 75, 73 Elshahed et al. 2001a

Pimelate 304 (M), 289 (M-15), 245, 217, 186, 173, Elshahed et al. 2001a 155, 125, 117, 97, 73 Glutarate 276 (M), 261 (M-15), 233, 204, 186, 158, Elshahed et al. 2001a 147, 129, 97, 73

Fumarate addition products of n-alkanes, signature anaerobic Methane Methylsuccinate 276 (M), 261 (M-15), 217, 147, 73 Duncan et al. 2009

Octane 2-methylheptylsuccinate 374 (M), 359 (M-15), 262, 217, 172, 147, 73 Gieg and Sulflita 2002 Activation/early downstream products of PAHs, signature anaerobic Naphthalene, 5, 6, 7, 8-tetrahydro-2-napthoic 248 (M), 233 (M-15), 189, 159, 131, 115 Phelps et al. 2002 2-methyl- acid naphthalene Phenanthrene Phenanthrene carboxylate 294 (M), 279 (M-15), 235, 205, 176, 139, 88 Davidova et al. 2007 Activation/early downstream products of PAHs, not uniquely anaerobic Naphthalene, Naphthoate 244 (M), 229 (M-15), 201, 185, 155, 127 Gieg and Sulflita 2002 methylnaphthalene Decahydro-2-naphthoate 254 (M), 239 (M-15), 164, 136, 117, 73 Zhang et al. 2000

Dimethyl- Methylnaphthoate 258 (M), 243 (M-15), 199, 169, 141, 115 Phelps et al. 2002 naphthalene

were reacted with 50 µL of N, O-bis(trimethylsilyl)trifluoroacetamide (BSTFA; Pierce

Chemical) in a 65 ℃ water bath for 15 minutes to form trimethylsilyl (TMS) derivatives. The derivatized components were then separated on a HP-5MS column (50 m × 320 µm × 0.25 µm film; Agilent Technologies) using helium as the carrier gas and analysed on an Agilent 7890a

GC system equipped with a 5975C inert XL MSD (GC-MS) in splitless mode. The oven parameters used were as follows (adapted from Gieg and Sulflita, 2002); an initial temperature of

45 ℃ (5 min), a ramp of 4 ℃/min to 270 ℃, and a final hold at 270 ℃ (15 min). The inlet and mass transfer line were held isothermally at 270 ℃ and 280 ℃, respectively.

Putative hydrocarbon metabolites from the TMS-derivatized organic extracts were positively identified using MSD ChemStation software (version E.02.02.1431; Agilent

Technologies) by matching GC retention time and mass spectral patterns to authentic standards

(Table 3-4). All commercially available standards evaluated, apart from benzylsuccinic acid

(Alfa Aesar), were acquired from Sigma Aldrich (97 – ≥ 99.5% purity). Alkyl-substituted benzylsuccinc acids were chemically synthesized using reflux reactions described by Bickford et al. (1948). For example, a standard of o-methylbenzylsuccinic acid was prepared by refluxing

200 mL of o-xylene with 10 g maleic anhydride (99% purity; Sigma-Aldrich) at ~ 100 ℃ for 5 hours. The mixture was then cooled and transferred to a separatory funnel, and extracted with two 50-mL volumes of 2.5 M KOH (15% w/v). The extract was stored overnight at 4 ℃ to allow for the precipitation of o-methylbenzylsuccinic acid. The resulting crystals were washed with dH2O and assessed for purity by verifying its expected melting temperature using a MEL-TEMP capillary melting point apparatus and assessing its mass spectral profile (GC-MS). An authentic standard of n-octylsuccinic acid was prepared by base hydrolysis following the procedure outlined by Kropp et al. (2000). Finally, an authentic standard of phenanthrene-9-carboxylate

was synthesized by refluxing of 9-acetylphenanthrene with a 5% solution of sodium hypochlorite

(Dixon and Neiswender 1960).

3.4 Microbial community analysis

The most common genomic tool used by environmental microbiologists to profile microbial communities is based on amplifying a portion of the 16S rRNA gene for prokaryotic identification. Prior to ~10 years ago, assessing microbial diversity in a cultivation-independent manner was usually performed using clone libraries and Sanger sequencing, or techniques such as denaturing gradient gel electrophoresis and T-RFLP analysis. While these approaches are sometimes still used (e.g. von Netzer et al. 2013; Gründger et al. 2015; Luo et al. 2016), most publications regarding anaerobic hydrocarbon biodegradation now describe the use of 16S rRNA gene amplicon sequencing to determine microbial diversity.

3.4.1 DNA extraction

Subsamples from cultures (5 – 50 mL) were centrifuged at room temperature > 10,000 × gav for 10 – 20 minutes to form cell pellets, which were stored overnight at –80 ℃ in preparation for extraction. All DNA extractions were performed using the FastDNA SPIN Kit for Soils (MP

Biomedicals) following the manufacturer’s procedure. Prior to their final elution, samples

(suspended in 75-100 µL RNAse/pyrogen-free water; MP Biomedicals) were incubated for five minutes at 55 °C to enhance DNA recovery. Cultures enriched on crude oil or bituminous oil sands received additional wash steps with 5.5 M guanidine thiocyanate to remove residual oil components and humic substances, which risked interfering with downstream amplification steps

(Knief et al., 2003). Extracted genomic DNA was quantified using Qubit fluorometry

(Invitrogen) and often yielded less than detectable amounts of genetic material (< 0.5 ng/mL); this is to be expected given the notoriously low amounts of biomass associated with these cultures. Note, however, that DNA concentrations > 1.0 ng/µL were frequently obtained from

~10 mL of BTEX-degrading enrichment cultures (after repeated amendment; Chapter 5), and up to 11.9 ng/µL DNA was extracted from equal volumes of PAH-amended consortia (Chapters 6).

Quantifiable amounts of DNA (0.5 – 3.0 ng/µL) were also reported from all crude oil-enriched produced water subsamples (50 mL; Chapter 7).

3.4.2 16S rRNA amplification and sequencing

3.4.2.1 Illumina MiSeq technology

Amplification and sequencing analysis of extracted DNA was carried out by a two-step method targeting the V6-V8 regions of the 16S rRNA gene using universal primers 926F

(AAACTYAAKGAATTGACGG) and 1392R (ACGGGCGGTGTGTRC). In the first round of

PCR, the 926F and 1392R primers contained Illumina overhang adaptors at the 5' end

(TCGTCGGCAGCGTCAGATGTGTATAAGAGACAG or

GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAG, respectively). Reactions (25 µL) contained 12.5 µL 2x PCR Master Mix (Fermentas), 5 µL of each primer (1 µM) and 2.5 µL of gDNA template. PCR assays were performed using a three-step thermoprofile: initial denaturation at 95°C for 5 min; 25 cycles of 95°C (40s), 55.0°C (2 min), 72.0°C (1 min); final extension at 72°C for 7 min. These thermocycling conditions were selected specifically for generating higher amplicon yields from low concentrations of DNA template material

(Klindworth et al. 2013) from test samples in comparison to Illumina’s recommended library preparation protocol (Caporaso et al. 2012; https://support.illumina.com/content/dam/illumina-

support/documents/documentation/chemistry_documentation/16s/16s-metagenomic-library-prep- guide-15044223-b.pdf). Amplification of the target region was confirmed on a 1% agarose gel and purified using the Agencourt AMPure XP magnetic bead system (Beckman Coulter).

In the second round of PCR, Nextera XT Index Kit primers (Illumina) were added to amplicon ends. The forward primer contained a 29 nt 5’ adapter

(AATGATACGGCGACCGAGATCTACAC), an 8 nt primer index (S501 – S508), and a 14 nt forward primer overhang adapter (TCGTCGGCAGCGTC). The reverse primer contained a 24 nt

3’ adapter (CAAGCAGAAGACGCCATACGAGAT), an 8 nt primer index (N701 – N712), and a 15 nt overhang adapter (GTCTCGTGGGCTCGG). Reaction volumes were increased to 50 µL and contained 25 µL 2x PCR Master Mix, 5 µL of each primer (1 µM) and 10 µL of purified

PCR I amplicon. Reaction conditions were modified from round I PCR: 95°C 3 min; 8 cycles of

95°C (30s), 55.0°C (30 s), 72.0°C (30 s); 72°C 5 min. PCR II amplicons of expected size were purified and quantified as stated before. The final purified products were normalized and pooled into a 4 nM library, then verified for expected base pair length (600 bp) using the High

Sensitivity DNA Analysis Kit and 2100 Bioanalyzer System (Agilent Technologies). High- throughput sequencing of the 16S rRNA sample library was completed using 2 × 300-bp paired- end sequencing using a benchtop sequencer and the MiSeq Reagent Kit v3 (Illumina). The library accounted for 95 – 99% of the total DNA sequenced (depending on its sequence diversity), with the remaining 1 – 5% occupied by 4 nM phiX (Illumina) as an internal control.

3.4.2.2 454 pyrosequencing

Prior to use of the Illumina MiSeq system, 16S rRNA gene sequencing was performed using the pioneering Roche 454 pyrosequencing system. Round I PCR assays (25 µL, prepared

as per Illumina round I PCR) were prepared with unmodified 926F and 1392R primers; round II

PCR primers (454T-FB and 454T-R13A) contained FLX Titanium adaptors

CTATGCGCCTTGCCAGCCCGCTCAG and CGTATCGCCTCCCTCGCGCCATCAG at the

5’ end of 926F and 1392R, respectively, followed by a 10 nt barcode (reverse primer only). PCR cycling conditions were adapted from Ramos-Padrón et al. (2011); 95 °C for 3 min; 25 cycles

(PCR I) or 10 cycles (PCR II) of 95 °C for 30 s, 55 °C for 45 s, 72 °C for 90 s; 72 °C for 10 min.

The final amplicons were purified using the QIAquick PCR Purification Kit (Qiagen), normalized and pooled into a ~55 nM library (20 ng/µL), then sequenced by Genome Québec using a GS FLX Titanium Series Kit XLR70 (Roche Diagnostics Corporation). Support for

Roche’s 454 pyrosequencing platform ended in 2015.

3.4.3 16S rRNA gene sequencing analysis

3.4.3.1 Assembly of Illumina reads (QIIME)

Paired-end 16S rRNA gene library sequences were analyzed in QIIME, an open-source bioinformatics pipeline for comparison and analysis of microbiomes (Caporaso et al. 2010). Prior to assembly, raw sequencing data were visually inspected for base quality scores and nucleotide distribution in DADA2 (Callahan et al. 2015). Demultiplexed reads were assigned to samples based on their indices, and ambiguities or reads with an average quality score < 20 were eliminated. All quality-controlled sequences were clustered into operational taxonomic units

(OTUs) at the species level (3% distance) and classified by mapping reads against the SSU

SILVA 119 database (Quast et al. 2013). At the time of release (July 24th, 2014), the SSU

SILVA 119 database contained over 1.5 million reference sequences. Alpha diversity statistics

(species-level analysis) were also generated in QIIME.

3.4.3.2 Assembly of 454 pyrosequencing reads (Phoenix 2)

Data analysis for raw 454 pyrosequencing reads was conducted using an in-house 16S rRNA gene sequence analysis pipeline (Phoenix 2; Soh et al. 2013). After stringent quality control steps (described in detail by Fowler et al. 2012; Soh et al. 2013), reads were subjected to de-replication and multiple sequence alignment, partitioned based on their sequence identity, clustered into OTUs at a 3% distance, and assigned taxonomy by comparing all reoccurring species within 5% of the best bitscore from a BLAST search against the SSU SILVA 102 database (Pruesse et al. 2007).

Preface

Chapter 4 describes numerous experiments used to evaluate putative cultivation-based strategies for accelerating rates of methanogenic hydrocarbon biodegradation. Some of these strategies include modifications to the culture growth medium, the incubation conditions, cell density, and the relative abundance of Syntrophus. In all, we identified three sets of methodologies that can easily be implemented for increasing rates of hydrocarbon metabolism.

Chapter Four: Identifying cultivation strategies for accelerating rates of toluene biodegradation using an established methanogenic enrichment culture

4.1 Introduction

The study of methanogenic hydrocarbon degradation often delves into environmental and energetic considerations impacting the cultivation of the microorganisms with such metabolic capacity. Some of these aspects have already been introduced in Chapter 1. Generally, however, there are three key factors constraining cultivation of methanogenic hydrocarbon-degrading consortia; (i) slow growth rates, (ii) limited growth yields, and (iii) long lag periods following culture transfer. In addition to having doubling times ranging on the order of weeks to months, most of the available substrate is converted into metabolic products (e.g. CH4 and CO2; 90 – 99% yield) rather than being incorporated into biomass (Widdel and Musat 2010; Gray et al. 2011;

Luo et al. 2016). This presents a substantial bottleneck for studying metabolic reaction mechanisms, which require the purification of several mg of protein for experimental analysis

(e.g. Eberlein et al. 2013a). Some research groups such as the laboratory of Dr. Matthias Boll have accounted for this by harvesting cells from large (200-liter) fermenters after several months of incubation (e.g. Dörner and Boll 2002; Kung et al. 2013; Eberlein et al. 2013; Ebenau-Jehle et al. 2017), while Bize et al. (2015) were able to successfully conduct metaproteomic analysis from a 2-liter anaerobic sewage digester. For routine cultivation of methanogenic consortia on model hydrocarbon substrates, however, cultures are seldom prepared in volumes greater than

~100 mL, partially due to the difficulty of subculturing and maintaining active cultures. Lag periods of 50–150 days are frequently reported when an active culture is transferred into fresh medium, and occasionally, hydrocarbon degradation rates never fully recover or cease

completely (e.g. Edwards and Grbić-Galić 1994; Sakai et al. 2009; Berdugo-Clavijo et al. 2012;

Fowler et al. 2016; Luo et al., 2016): the reason(s) for this is not yet clear.

Several studies have previously explored methods of optimizing rates of methanogenic hydrocarbon degradation in established enrichment cultures (e.g. Edwards and Grbić-Galić 1994;

Luo 2016), which have experienced varying degrees of success. For example, Edwards and

Grbić-Galić (1994) reported that rates of toluene degradation were initially dependent on cell density, but that stimulating biomass production with accessory carbon sources failed to accelerate hydrocarbon utilization. Luo (2016) identified four minerals (Zn2+, Co3+, Ni2+, and

Cu2+) essential for methanogenic benzene degradation, and that doubling the amount of Co3+ in the growth medium increased rates of methanogenic activity by ~10%. Cobalt is found in the reactive center of vitamin B12, responsible for catalyzing a variety of transmethylation and rearrangement reactions (Martens et al. 2002) such as dechlorination of halogenated hydrocarbons (Shey and van der Donk 2000) and possibly benzene activation (Ulrich et al.

2005). Several enzymes essential for syntrophic hydrocarbon degradation contain W+ co-factors such as benzoyl coenzyme A reductase (Kung et al. 2009) and formate dehydrogenase

(Ljungdahl and Andreesen 1975; Ferry 1999), whereas Se2- participates in a full range of metabolic functions including assimilation, methylation, detoxification, and anaerobic respiration

(Stolz et al. 2002); both ions are common components of trace element solutions used for cultivating many microorganisms.

Other studies have also reported stimulating hydrocarbon-dependent methanogenesis using of a number of unconventional approaches. For example, adding electron acceptors such as

2- SO4 may accelerate rates of methanogenic hydrocarbon degradation when supplemented in low

(< 5 mM) concentrations (e.g. Zengler et al. 1999; Zhang et al. 2010; Siegert et al. 2011;

Oberding 2016). Mineralization of hydrocarbons under methanogenic conditions relies on the cooperative activities of metabolic intermediate producers and consumers linked by interspecies electron transfer in syntrophic consortia that may include sulfate-reducing taxa such as

Desulfovibrio and members of the Syntrophaceae family (e.g., Syntrophaceae; Zengler et al.

1999; Gray et al. 2011; Meyer et al. 2013a; 2013b; Cheng et al. 2013; Fowler 2014; Tan et al.

2014; Oberding 2016; Wawrik et al. 2016) and possibly Fe(III)-reducing bacteria such as members of the Geobacter (Rotaru et al. 2014a; 2014b; Fowler et al. 2014). Some anaerobic phylogenies such as toluene-degrading Desulfosporosinus genus are capable of coupling toluene oxidation with the reduction of multiple electron acceptors (arsenate, sulfate, thiosulfate, nitrate and ferric iron; reviewed by Spring and Rosenzweig 2006), in addition to methanogenic conditions (Fowler et al. 2014; Sun et al. 2014; Abu Laban et al. 2015). Thus, adding other anaerobic electron acceptors may serve to stimulate hydrocarbon degradation under methanogenic conditions. Trace amounts of oxygen may also help to partially oxidize hydrocarbon substrates (abiotically or biotically) without disrupting methanogenic activity

(Zitomer and Shrout 1998), thereby reducing some of the energetic costs associated with hydrocarbon activation.

Recently, the use of conductive minerals and (semi)conductive iron-oxide minerals have been explored as viable options for facilitating syntrophic interactions (Kato et al. 2012a; 2012b;

Zhuang et al. 2015). Conductive, multispecies aggregates (e.g. Geobacter spp., Methanosarcina) participating in direct interspecies electron transfer (DIET) attach themselves to the conductive material, alleviating the need to produce electrically conductive filaments or electron shuttle molecules (reviewed by Lovley 2017). Other abiotic conductive materials such as granular activated carbon (Liu et al. 2012), biochar (Chen et al. 2014c), and carbon cloth (Chen et al.

2014b) have all been successfully used to promote DIET across syntrophic partners and increase rates of methanogenesis 5 to 15-fold, albeit have not yet been explored for facilitating syntrophic hydrocarbon degradation.

In this chapter, we explored the use of various experimental cultivation strategies for a methanogenic toluene-degrading consortium (TOLDC), with the intended goal of accelerating rates of substrate utilization. This was achieved by modifying our standard cultivation procedure in one of eight categories, listed in Section 4.2.2 and in Table 4-1. The subject of reducing agents is a key focus of this chapter: at the time this experiment was conducted (in 2013), cysteine sulfide (McInerney et al. 1979) was used to cultivate methanogenic hydrocarbon-degrading consortia in our laboratory (Ramos-Padrón et al. 2011; Berdugo-Clavijo et al. 2012; Fowler et al.

2012; Gieg et al. 2014; Fowler et al. 2016) and is cited in dozens of other published manuscripts

(recent examples include Ding et al. 2015; Johnson et al. 2015; Xia et al. 2016). Replacing the use of cysteine with a carbon-free alternate, however, resulted in a key strategy for improving rates of methanogenic toluene biodegradation.

4.2 Materials and Methods

4.2.1 Standard cultivation and maintenance of TOLDC

The standard growth medium and cultivation procedure used for maintenance of TOLDC was previously described in Chapter 3.2.1, wherein cultures were reduced using an equal mixture of cysteine-HCl and sodium sulfide, referred to herein as cysteine sulfide (0.05% w/v). TOLDC has been maintained by routine transfer (20 – 50% v/v) and substrate amendment with toluene

(~380 µM) for ~15 years (Gieg et al. 1999; Fowler et al. 2012; 2014). Unexpectedly, lag periods expanding from ~50 days to >150 days were being reported in recent transfers of TOLDC into

fresh growth medium (Dr. S. Jane Fowler, unpublished results). What’s more, increasing amounts of methane were also being produced in parallel unamended (toluene-free) controls

(Figure A-1), but the cause of this had not yet been identified.

4.2.2 Preparation of experimental microcosms with TOLDC

An active subculture of TOLDC (150 mL, Fowler et al. 2012) was used as the experimental inoculum for a first set of trial experiments evaluating different reducing agents and other series of modifications to our standard cultivation procedure (Sections 4.2.2.1 –

4.2.2.6). The culture used to prepare new incubations was maintained by Dr. S. Jane Fowler and had been fed a total of 56 µmol of toluene over the course of one year. To generate as many experimental cultures as possible without overdiluting cells, new incubations of TOLDC (10 mL,

15% transfer v/v) were prepared in 30-mL serum bottles and contained approximately 4.7 µmol of toluene as a carbon and energy source. According to Henry’s Law, the concentration of toluene in aqueous phase was ~ 316 µM. Each set of experimental microcosms (made up of two active cultures, 1 – 2 substrate-unamended controls, and one sterile control) evaluated a single modification to the standard cultivation procedure, and was used to compare rates of methanogenic toluene degradation against a set of positive, unmodified replicates. Additional experiments were conducted ~ 3 years later after an optimized cultivation procedure had already been established (Sections 4.2.2.7 and 4.2.2.8). A description of each set of incubations is provided in Table 4-1.

4.2.2.1 Reducing agents

Here, the use of 0.05% w/v cysteine sulfide was substituted for equal concentrations of the selected reductants; cysteine hydrochloride, sodium sulfide, iron (III) chloride, titanium (III) chloride, or TiNTA (titanium (III) nitrilotriacetic acid). The redox potential of each reductant in growth medium is summarized in Appendix A (Table A-1). A set of reductant-free controls were also established. Two other concentrations of cysteine sulfide (0.025% w/v and 0.1% w/v) were also evaluated to determine the extent of sulfide toxicity in TOLDC. All reducing agent solutions were prepared in serum bottles by dissolving the reductant in anoxic Milli-Q water (boiled, N2- sparged) in an anaerobic chamber with a N2 headspace, and sealing with rubber butyl stoppers and aluminum crimps. A stock solution of TiNTA was prepared following the procedure described by Moench and Zeikus (1983). The final pH of most stock solutions was adjusted to

~7.0 prior to autoclaving, though the TiCl3 solution had to be kept below pH 3 to prevent precipitation of the reductant. Once added to the prepared growth medium, however, TiCl3 precipitated out of solution.

4.2.2.2 Trace elements and nutrients

In partial consideration of experiments performed by Ünal et al. (2012), alterations to the growth medium’s suggested vitamin and trace metals solutions were considered as methods for improving rates of methanogenic hydrocarbon degradation. For this, the use of Wolin’s trace metal solution or Balch vitamins solution (Tables 3-2 and 3-3, respectively) was substituted for equal volumes of the respective stock solution described by Tanner (2002). Tanner’s trace metal solution supplies W+, Co3+, and Se2- (Table A-2), all of which are unavailable in Wolin’s

solution. The defining feature of Tanner’s vitamin solution is that it supplies 50 times more vitamin B12 than the Balch vitamin solution (Table A-3).

In a separate set of experiments performed by an undergraduate project student (Sally

Cheung), selected components (Zn2+, Ni2+, or Fe2+) in the Wolin’s trace metal solution were removed, doubled in concentration, or increased by an order of magnitude (Table 3-2) to assess their impact to toluene degradation by TOLDC.

4.2.2.3 Carbon supplements

A series of unmodified incubations were supplemented with complex nutrient sources

(yeast extract, peptone, or casamino acids; 0.05% w/v) aimed to increase the biomass of the microorganisms present in TOLDC. The inherent risk of adding non-selective ingredients to the culture medium is that the high nutrient concentration may inadvertently promote the growth of peripheral organisms (Narihiro et al. 2015; Nobu et al. 2015), or stimulate the expression of non- hydrocarbon catabolic pathways (reviewed by Schink and Stams 2006; Morris et al. 2013). To account for this, one set of microcosms supplemented cells with 0.05% w/v sodium benzoate; a downstream intermediate of anaerobic toluene biodegradation.

4.2.2.4 Biomolecule supplements

A series of microcosms were supplemented with one of two biomolecules (0.005% w/v) hypothesized to improve the cultivation efficiency of TOLDC. Cyclic adenosine monophosphate

(cyclic AMP) is a secondary messenger used for various intracellular signal transduction pathways and regulatory mechanisms (Botsford and Harman 1992). Bruns et al. (2002) found that comparable amounts of cAMP doubled the cultivation efficiency of marine heterotrophic

microorganisms, albeit cells were grown on a polymer medium rather than with hydrocarbons.

Coenzyme M (2-mercaptoethanesulfonate) is required for methyl-transfer reactions in the penultimate step of methane formation by methanogens (Thauer 1998). Though 2- mercaptoethanesulfonate is already a component of the Balch vitamin solution (1 µg/10 mL growth medium; Table 3-3), the concentration of this component was increased by a factor of 5 in this set of experimental incubations (5 µg/10 mL).

4.2.2.5 Modifications to incubation conditions

To determine the impact of incubation conditions towards rates of methanogenic toluene biodegradation, three sets of unmodified TOLDC microcosms were incubated under different storage conditions; 32 ℃ under static conditions, room temperature (~21 ℃) under shaking conditions (100 rpm), or a combination of both (32 ℃ + shaking). Note that methanogenic cultures are rarely shaken because it risks uncoupling syntrophic associations, either due to the increased dispersion of metabolites or disaggregation of cells (Sieber et al. 2014).

4.2.2.6 Electron acceptor supplements

In accordance with Siegert et al. (2011), we sought to stimulate putative iron-reducing and sulfate-reducing syntrophic partners in TOLDC by supplementing unmodified incubations with 2 mM of FeCl3 or Na2SO4, respectively. Two parallel sets of reductant-free microcosms were also prepared with headspaces containing 0.01% or 0.1% O2 in N2/CO2.

4.2.2.7 Cell density

Based on a set of experiments conducted by Edwards and Grbić-Galić (1994), we sought to determine whether transferring TOLDC in more concentrated volumes would reduce the lag period times. Here, new incubations (20 mL) were prepared by a former undergraduate project student (Corynne O’Farrell) in growth medium containing 0.05% w/v sodium sulfide containing

20 – 100% v/v transfers of an active TOLDC culture fed a total of 50.5 µL toluene (474 µmol) over 2.5 years. Cultures were amended with toluene (~291 µM in the aqueous phase) and assessed for methanogenic activity by routine methane production and hydrocarbon loss measurements.

4.2.2.8 Artificial enrichment of Syntrophus

During culture maintenance of TOLDC using our optimized cultivation protocol, we performed routine 16S rRNA gene sequencing of active cultures (Section 4.2.4) and observed that rates of methane production positively correlated to the relative abundance of Syntrophus within the microbial community (Figure A-2). To determine whether we could improve rates of toluene utilization by artificially enriching the relative abundance of Syntrophus, we prepared a series of serial dilutions (10-1 to 10-7) of TOLDC on culture medium 960 (Deutsche Sammlung von Mikroorganismen und Zellkulturen, DSMZ) with Syntrophus-specific modifications (where crotonic acid serves as an electron donor; Table A-4) and incubated microcosms at 40 ℃ for one week. A pure culture of a tentatively-identified Syntrophus organism was successfully obtained after three rounds of serial dilutions and transfers, based on visual inspection (microscopy) and chemical measurements (e.g. GC-FID; no methane production was observed). We then inoculated TOLDC into fresh minimal medium (20 mL; 25% v/v) reduced with sodium sulfide

and containing ~ 300 µM toluene: cultures were then inoculated with 1 – 10% v/v of the presumed Syntrophus. Two unmodified TOLDC cultures were also prepared in addition to negative control replicates, and monitored for methanogenic activity for 124 days. Cultures were refed equal amounts of toluene when the concentration of toluene in the microcosm headspace fell below detectable limits (< 5 µM; Chapter 3.3.2).

4.2.3 Analytical methods

Methanogenic activity was routinely monitored in TOLDC incubations by measuring methane production and toluene loss from microcosm headspaces as described in Chapter 3.3.

A colorimetric assay was used for experimental evidence of cysteine degradation in select incubations (described in Section 4.3.3). The assay relies on the use of DTNB (5, 5’-dithio-bis‐

(2‐nitrobenzoic acid); also known as Ellman’s reagent) that reacts with free sulfhydryl groups (-

SH) in neutral aqueous solutions to yield a mixture of disulfide and 2-nitro-5-thiobenzoic acid

(NTB), a measurable yellow-pigmented product (Ellman 1958). Briefly, a 0.1 mM DTNB stock solution dissolved in dimethyl sulfoxide was aliquoted (950 µL) and vortexed with 50 µL of sampled culture medium. The absorbance was measured in a spectrophotometer (412 nm) after two minutes of incubation at room temperature. The concentration of -SH in each sample was calculated from the molar extinction coefficient of NTB (14.15 mM-1cm-1) and corrected for dilution. Calibration curves were prepared from sterile growth and standard concentrations of cysteine-HCl (0.1 – 10 mM). Cysteine recovery from calibration curves fell within a range of

92–102% of expected results (Ellman 1958; data not shown), confirming the efficacy of the assay for experimental use.

Table 4-1. Summary of modifications used to assess and compare rates of methanogenic toluene biodegradation by TOLDC. The standard cultivation procedure for TOLDC is provided in the first row. Incubations with improved rates of toluene consumption are designated with a (+) symbol; replicates with reduced rates (-) or no change to the rate of toluene degradation (0) are also shown. Description Results Unmodified minimal growth medium (Chapter 3.2.1) containing 0.05% cysteine sulfide; incubated at room temperature (21 ℃) under static conditions Alternative reducing agent (0.05%, unless otherwise noted) Cysteine sulfide (0.025%) 0 Cysteine sulfide (0.10%) 0 Cysteine-HCl 0 Sodium sulfide + Titanium (III) chloride - Titanium (III) nitrilotriacetic acid 0 Reductant-free + Modified trace elements/vitamin solution Tanner’s vitamin solution 0 Tanner’s trace metal solution 0 Wolin’s trace metal solution: 0, 2 or 10 Zn2+ 0 Wolin’s trace metal solution: 0, 2 or 10 Ni2+ 0 Wolin’s trace metal solution: 0, 2 or 10 Fe2+ 0 Carbon supplements (0.05% w/v) Yeast extract 0 Peptone 0 Casamino acids 0 Sodium benzoate 0 Biomolecule supplements (0.005% w/v) Cyclic AMP 0 Coenzyme M 0 Modified incubation conditions Static at 32 ℃ + Shaking (100 rpm) at 21 ℃ 0 Shaking (100 rpm) at 32 ℃ 0 Electron acceptor supplements Na2SO4 (2 mM) 0 FeCl3 (2 mM) 0 O2 (0.01% or 0.1% in reductant-free incubations) - Other Increasing cell density (% TOLDC v/v) during culture transfer + Increasing the relative abundance of Syntrophus +

Toluene(µmol)

Na2SO4 O2 O2

4.2.4 Microbial community sequencing

Select microcosms described in Section 4.2.2 were sacrificed for DNA extraction and processed for 16S rRNA pyrosequencing or Illumina sequencing (Chapter 3.4). Assembly and annotation of raw reads was performed as previously described in Chapter 3.4.3.

4.3 Results and discussion

4.3.1 Impact of different cultivation procedures on methanogenic toluene degradation

The results of each tested modification to TOLDC’s standard cultivation procedure are summarized in Table 4-1. An initial lag period of ~59 days was observed for most incubations before consistent rates of methane were produced, comparable to what was reported by Fowler et al. (2012) and in other transfers of TOLDC (Figure A-1). Despite this, negligible toluene consumption was reported for most microcosms after 124 days of incubation, including in the unmodified toluene-amended controls (Figure 4-1). Reductant-free controls and incubations reduced with sodium sulfide (Na2S) experienced 46–73% greater toluene loss than unmodified, toluene-amended controls (Figure 4-1 B). Microcosms with 0.5% peptone experienced an initial rapid decrease in toluene during the first week of incubation, but experienced a 70-day lag period before toluene consumption resumed (Figure 4-1 C). Presumably, the nutrient source temporarily facilitated hydrocarbon utilization before ultimately stimulating biomass production of peripheral organisms, inhibiting toluene metabolism until the exogenous carbon supplement was depleted.

This may have also been the case for cultures supplemented with biomolecules, as no toluene loss was observed (Figure 4-1 D) Further, we found that toluene degradation was not stimulated in cultures containing modified trace metal solutions or using Tanner’s vitamin solution (data not shown), while methanogenic activity was completely inhibited in cultures containing low

concentrations of O2 and in cultures reduced with TiCl3 (Table 4-1; Figure 4-1 B and F) presumably due to its precipitation in the culture medium (Moench and Zeikus 1983).

Increasing the incubation temperature of TOLDC from room temperature (~21 ℃) to 32

°C (grown statically) doubled the rates of methane production from ~0.73 µmol CH4/day to

~1.59

µmol CH4/day, and consumed toluene within 11 days after an initial 2-month lag period (Figure

4-1 E). The Gibbs-Helmholtz equation predicts that hydrocarbon-dependent methanogenesis becomes increasingly exergonic with increasing temperature (Dolfing et al. 2008), thus facilitating rates of substrate degradation. However, we are more inclined to believe that the higher incubation temperature was closer to the optimal cultivation conditions for many of the hydrocarbon-degrading consortia present in TOLDC, such as Desulfosporosinus (28 – 30 ℃, based on isolate cultivation conditions listed by DSMZ), Syntrophus (30 – 38 ℃) and

Desulfovibrio (35 – 37 ℃). Thus, we propose that modifying incubation conditions to optimal cultivation temperatures is a viable method for improving rates of methanogenic hydrocarbon biodegradation. Luo (2016) drew the same conclusion in cultivation surveys of a methanogenic benzene-degrading enrichment culture.

4.3.2 Impact of cysteine on methanogenic toluene degradation

A major concern during the preliminary round of TOLDC cultivation tests (Section 4.3.1) was that the amount of methane produced in toluene-free (unamended) incubations was similar to methane yields in most toluene-amended incubations, averaging around 28.0 ± 0.9 µmol CH4

(Figure 4-2). This led us to suspect that an alternative carbon source present in the standard growth medium was being preferentially metabolized over the hydrocarbon substrate. After

calculating the theoretical stoichiometric conversion of all putative carbon sources in the standard growth medium to methane (Table 4-2), cysteine was hypothesized to be the culpable agent;

+ + 4 퐶3퐻7푁푂2푆 + 6 퐻2푂 + 4 퐻 → 4 퐻2푆 + 4 푁퐻4 + 5 퐶퐻4 + 7 퐶푂2 (푒푞푛 2)

∆퐺°′ = −96.6 푘퐽/푚표푙

Complete mineralization of cysteine to CO2 can theoretically produce up to 51.7 µmol of methane (eqn 2). Based on theoretical stoichiometric predictions calculated from the amount of cysteine added to each microcosm, approximately 55% of the available cysteine was dissimilated for energy production, while the remaining carbon was incorporated into biomass. This finding was supported by parallel incubations reduced with half or double the amount of cysteine sulfide, producing similar yields of CH4 (61.1 ± 4.3% and 47.9 ± 4.8%, respectively) by the end of the incubation period (Figure 4-2). We remark that replacing cysteine sulfide with cysteine-HCl reduced the observed lag period by 40% (albeit toluene consumption was not observed). Lag periods exceeding several weeks or months have been reported for other methanogenic hydrocarbon-degrading cultures (e.g. Edwards and Grbić-Galić 1994; Townsend et al. 2003;

Berdugo-Clavijo and Gieg 2014; Fowler et al. 2016), and have been commonly attributed to toxic inhibition of microbes by hydrocarbon substrates (Sikkema et al. 1995). Our results suggest that rates of methanogenic activity may also be inhibited in part due to sulfide toxicity. Sulfide, present in TOLDC cultures as both a reducing agent component and as a by-product of cysteine metabolism (eqn 1), is known to hamper growth kinetics of a range of methanogens and syntrophic bacteria (O’Flaherty et al. 1998; Chen et al. 2014a). The precipitation of essential trace metals such as Co3+ or Ni2+ by sulfide is also an indirect form of inhibition to methanogenesis (Paulo et al. 2015). Thus, to overcome inhibition of methanogenesis by sulfide,

Component Available substrate Expected CH4 (µmol) Balch vitamins 5.00 µg N/A Resazurin 0.46 µg 0.17 - a HCO3 25.0 mg 6682 Cysteine 4.00 mg 51.7 aBased on complete hydrogenotrophic methanogenesis (Cord-Ruwisch et al. 1988)

60 UnmodifiedUnmodified (0.5% (0.05% Cys-SH) cysteine sulfide) 0.025%0.025% Cys-SH cysteine sulfide 50 0.1%0.1% Cys-SH cysteine sulfide 0.05%0.05% Cys-HCl cysteine-HCl Reductant-freeReductant-free 40

UnamendedUnamended (0.05% (0.05% Cys-SH) cysteine sulfide)

mol) μ 30

Methane( 20

0 0 20 40 60 80 100 120 140 Time (Days)

one suggestion would be to adopt the use of insoluble iron sulfide as a reductant (Brock and

O’Dea 1977), as has been previously used to cultivate some hydrocarbon-degrading consortia under denitrifying and methanogenic conditions (Edwards and Grbić-Galić 1994; Luo et al.

2014; 2016). Unamended controls containing TiNTA were also capable of producing up to 8

µmol during the incubation period (data not shown), suggesting that nitrilotriacetic acid can also serve as an unintended carbon and energy source.

4.3.3 Experimental verification of cysteine utilization

To confirm the use of L-cysteine as a carbon and energy source, a secondary round of

TOLDC incubations were prepared in triplicate containing the following carbon and energy source(s); cysteine-HCl only, toluene only (reductant-free), cysteine-HCl and toluene, or remained carbon-free. Equal amounts of methane were produced in microcosms amended with cysteine or a combination of cysteine and toluene after 103 days of incubation (30.2 ± 6.7 µmol and 33.8 ± 5.1 µmol, respectively), while replicates amended solely with toluene produced an average of 5.9 ± 0.8 µmol CH4 (Figure 4-3 A). To monitor cysteine loss, sulfhydryl (-SH) content was quantitatively determined from subsamples of cysteine-amended incubations and sterile controls using a colorimetric assay (Ellman 1958) during the first 29 days of incubation.

After a single day of incubation, sulfhydryl concentrations decreased by as much as 45% from T0 concentrations in TOLDC microcosms containing 0.05% cysteine-HCl (~3.2 mM), with up to

92% loss detected by Day 7 (Figure 4-3 B). The slower depletion of –SH in sterile controls is believed to have been caused by abiotic oxidation of cysteine to its redox dimer form, cystine, but was not experimentally confirmed. Nevertheless, there is sufficient evidence from these three

45 6 3.5 40 A B 5 3 35 2.5

30 4

mol)

mol) μ 25 μ 2 3

20 1.5

SH] SH] (mM) -

15 2 [ Toluene ( Methane ( Methane 1 10 1 0.5 5 0 0 0 0 30 60 90 120 1 7 22 29 Time (Days) Time (Days)

Figure 4-3. Analytical measurements of methane production, toluene consumption, and sulfhydryl (-SH) concentrations in TOLDC incubations containing the following carbon and energy sources; 0.05% cysteine-HCl (yellow), ~4.7 μmol toluene (blue), cysteine-HCl + toluene (red), or carbon-free (tan). (A) Methane (closed circles) and toluene (open circles) were routinely monitored for up to 114 days. (B) -SH amounts in incubations with cysteine- HCl and cysteine-HCl + toluene, as well as in sterile controls reduced with cysteine-HCl (gray) was measured during the first 29 days of incubation. Error bars ± SEM of triplicate incubations.

analytical methods to confirm that L-cysteine is immediately used by TOLDC as a preferential growth substrate and delays the degradation of toluene.

Only in replicates containing toluene as the sole carbon and energy source was toluene depletion detected during the 103-day incubation period, decreasing at a rate of ~0.05 µmol/day following a two-month lag period. Of the triplicate reductant-free incubations, one replicate was selected to be reamended with toluene six additional times; in all, ~32.9 µmol of toluene was consumed and 126 µmol of methane was produced over the course of 376 days, indicating an

86% recovery of the predicted methane (Figure 4-4). Although not measured, the remaining carbon was likely incorporated into biomass with a minor component lost in the formation of

140 7

120 6

100 5

mol)

mol) μ

80 4 μ

60 3 Toluene( Methane( 40 2

20 1

0 0 120 170 220 270 320 370 420 Time (Days)

detritus by-products or during headspace sampling, as has been reported in other methanogenic hydrocarbon-degrading studies (Edwards and Grbić-Galić 1994; Zengler et al. 1999; Fowler et al. 2012). Further, observed toluene degradation gradually accelerated after each refeed, increasing > 800% to a maximum rate of ~0.43 µmol/day, or roughly 21.5 µmol/day per liter of culture (Figure 4-4). This was the fastest rate of toluene consumption reported for any TOLDC culture described in this dissertation; the average rate of methanogenic toluene biodegradation

(reduced with 0.05% w/v sodium sulfide is closer to 13 5 µmol/day/L). Again, this may be due to inhibition of methanogenesis by sulfide, but experimental verification is required.

4.3.4 Microbial community analysis of cysteine-amended incubations

One replicate from each set of experimental microcosms described in Section 4.3.3 was sacrificed for microbial community analysis, as well as the refed toluene-degrading microcosm.

Four of the five modified TOLDC cultures were dominated by members of the Proteobacteria, comprising 23 – 75% of the quality pyrosequencing reads that made up greater than 1% of the total community abundance (Figure 4-5). Only in the culture reamended with toluene were

Proteobacteria found to represent a minor clade (8.2%) within the microbial community. At the genus level, a Pseudomonas sp. was the most abundant member of the Proteobacteria detected across the four aforementioned samples, comprising 20.4% to 65.4% of total reads. in culture. In contrast, previous 16S rRNA gene pyrosequencing analysis of TOLDC had affiliated less than

0.6% of total reads to Pseudomonas lineages (Fowler et al. 2012). Though some facultative species of Pseudomonas are known to utilize toluene in the presence of oxygen (reviewed in

Abbasian et al. 2016), previous metagenomic sequencing of TOLDC failed to detect a putative toluene monooxygenase gene (Tan et al. 2015a). Time resolved RNA-based stable isotope probing and RT-qPCR analysis of TOLDC also did not identify Pseudomonas as a participant in methanogenic toluene degradation (Fowler et al. 2014). Therefore, we propose that

Pseudomonas serves as a chief cysteine fermenter in TOLDC, and is clearly shown in Figure 4-5 to outcompete microorganisms directly involved in toluene transformation (e.g.

Desulfosporosinus). In Chapter 5, subsequent 16S rRNA gene sequencing of TOLDC maintained with sodium sulfide identified Pseudomonas sp. to comprise less than 0.1% of reads (Table 5-2), supporting that it does not participate in methanogenic toluene biodegradation.

Another bacterium that may participate in cysteine catabolism is Lachnospiraceae incertae sedis, as it is only detectable in incubations reduced with cysteine (11.5% to 21.5% read

abundance). Other minor clades (e.g. Sedimentibacter, Proteiniphilum, Rickenellaceae vadin

BC27, uncultured Anaerolineaceae sp., Spirochaeta) also decreased in abundance (< 1%) upon eliminating the use of cysteine. Uncultivated clades related to Firmicutes, Bacteroidetes, and

Chloroflexi are ubiquitously found in low abundance in anaerobic digesters and enrichment cultures (Narihiro et al. 2015), including in several methanogenic hydrocarbon-degrading enrichment cultures established by the laboratory of L. Gieg (e.g. Fowler et al. 2012; Berdugo-

Clavijo et al. 2012; 2014; Fowler et al. 2016; Oberding 2016) and in time course experiments of methanogenic crude oil biodegradation described in Chapter 7. Recent metabolic reconstruction of a methanogenic terephthalate-degrading bioreactor identified that several of these yet-to-be- cultivated organisms participate as protein scavengers (Nobu et al. 2015), expressing complementary metabolic pathways indicative of syntrophic and fermentative protein degradation to amino acids, branched-chain fatty acids, and propionate. Similarly, Fowler et al.

(2016) conducted a microbial co-occurrence analysis on five methanogenic enrichment cultures and demonstrated that several of these yet-to-be-cultivated organisms cluster strongly co-occur in a dense network separate from putative hydrocarbon fermenters and methanogenic archaea.

Therefore, these clades may participate in an intricate, interdependent ecosystem in TOLDC catabolizing by-products of cysteine fermentation and detritus.

The importance of Desulfosporosinus for methanogenic toluene activation has been described for several methanogenic hydrocarbon-degrading cultures including TOLDC (Fowler et al. 2012; Sun et al. 2014; Fowler et al. 2014; Tan et al. 2015a; Laban et al. 2015). The enrichment of Desulfosporosinus in the unreduced toluene-amended was possible after refeeding cultures several times with toluene (Figure 4-5), correlating with accelerated rates of methanogenic toluene consumption seen in Figure 4-4. Other studies have also remarked that accelerated rates of hydrocarbon degradation can be achieved with repeated substrate reamendment (Edwards and Grbić-Galić 1994; Weiner and Lovley 1998; Ulrich and Edwards

2003; Chakraborty and Coates 2005).

4.3.5 Evidence that cell density and ‘Syntrophus’ are important for regulating methanogenic toluene biodegradation

Following the discoveries made in Sections 4.3.1 to 4.3.4, we determined that the best approach to cultivate TOLDC was by replacing cysteine reducing agents with an equal concentration of sodium sulfide and by refeeding cultures as necessary without transfer events.

This allowed for visible biomass formation over 1 to 3 years of incubation (Figure 4-6), where cells tended to grow in tight aggregates. This led us to hypothesize that cell density may be

Figure 4-6. Formation of visible cell aggregates in TOLDC enrichment cultures repeatedly amended with toluene over 1 to 3 years.

important in the regulation of methanogenic toluene degradation, as previously suggested by

Edwards and Grbić-Galić (1994).

We transferred an active culture of TOLDC in fresh anaerobic medium at various concentrations (20 – 80% transfer v/v) and compared rates of toluene consumption against an undiluted (100% transfer v/v) control. All diluted cultures experienced a lag period of at least 85 days, whereas methanogenic activity immediately resumed in the undiluted control (Figure A-2).

Unfortunately, routine GC-FID measurements were not continued after Day 85, thus we do not

know whether methanogenic activity was re-established sooner in microcosms with higher cell densities. Nevertheless, it does appear that diluting cultures ≥ 20% impacts the utilization of toluene and results in a lag period. We propose that a future experiment should be designed to determine is there is a critical cell density required for methanogenic toluene metabolism. This could be achieved by monitoring the expression of key functional genes at different cell concentrations, or by time course messenger RNA extractions and 16S rRNA gene amplification by quantitative PCR analysis, similar to what was performed by Fowler et al. (2014) and

Oberding (2016).

4.2.2.8; Table A-4) and inoculated the pure culture (1 – 10% transfer v/v) into new 20-mL

TOLDC incubations (25% transfer v/v). A set of duplicate controls experienced a ~ 90-day lag period before toluene was actively consumed (Figure 4-7). In contrast, the lag time for cultures inoculated with 2 – 3% Syntrophus was reduced by half (data not shown), and the rate of toluene consumption increased 207 – 209% versus unmodified control replicates (Figure 4-7). Rates of toluene degradation were 27% slower in incubations with 5% v/v Syntrophus (as compared to 2

– 3% v/v) and decreased to control rates of toluene degradation at a 10% v/v enrichment (Figure

4-7). To our knowledge, this is the first physiological evidence showing accelerated rates of methanogenic hydrocarbon biodegradation coupled to the abundance of a syntrophic organism,

5 First refeed

4 µmol) 3

2 Toluene(

0 90 95 100 105 110 115 120 Time (Days)

TOLDC only (213 µmol/day/L) 1% (173 µmol/day/L) 2% (440 µmol/day/L) 3% (446 µmol/day/L) 5% (327 µmol/day/L) 10% (215 µmol/day/L)

and is an intriguing growth strategy that could easily be implemented for cultivating existing enrichment cultures. Inadvertently, we also have more clearly defined a role for Syntrophus in

TOLDC during studies summarized in Chapter 5. Briefly, we proposed that the syntroph catalyzes an oxidative branch of benzoate metabolism (a downstream intermediate formed during anaerobic toluene degradation) theoretically used to drive the favourable reduction of

+ NAD to NADH by reduced ferredoxin, and the production of H2 (Mcinerney et al. 2007; Buckel and Thauer 2013). This hypothetical reaction is presumably a rate-limiting step in methanogenic hydrocarbon metabolism, but essential for driving interspecies electron transfer in syntrophic consortia in a thermodynamically favourable manner (Sieber et al. 2012). Thus, increasing the

abundance of Syntrophus (and possibly other syntrophic bacteria such as Desulfovibrio) hypothetically increases rates of energy conservation in TOLDC ultimately leading to improved rates of toluene degradation. We are currently processing extracted DNA from this isolate and confirming its identity by Sanger sequencing of the full-length 16S rRNA gene; results should be available in the upcoming weeks.

Overall, we identified three key strategies for accelerating rates of methanogenic toluene biodegradation by TOLDC by: i) by eliminating the use of cysteine-containing reductants; ii) incubating microcosms at higher temperatures, and iii) artificially increasing the abundance of

Syntrophus. Supplementing cultures with external carbon sources or electron acceptors either had no effect or decreased rates of toluene utilization, nor did modifying the trace elements or vitamins solution in the growth medium. Results from the cell density test are inconclusive and would need to be repeated. We replaced the use of the reductant cysteine-sulfide with an equal concentration of sodium sulfide, despite its risk of partially inhibiting methanogenesis. A future experiment, however, should aim to explore the use of FeS as an optimal reducing agent, as this approach has been successfully adopted by other research groups for cultivating anaerobic hydrocarbon-degrading microorganisms (Edwards and Grbić-Galić 1994; Luo et al. 2014; 2016).

This study also sheds light on the community dynamics of TOLDC in response to the presence of cysteine. Over the course of several years of routine cultivation of TOLDC with cysteine reductants, peripheral organisms including Pseudomonas, Lachnospiraceae, and

Proteiniphilum became enriched and dominated the microbial community composition of

TOLDC. We are not, however, the first to show inhibition of methanogenic toluene degradation in the presence of cysteine (Edwards and Grbić-Galić 1994). Future studies could potentially

examine the evolution of cysteine degraders in TOLDC, but what we feel is of far greater significance is to investigate the energy conservation mechanism of Syntrophus in TOLDC. In order to begin this research, large culture volumes would first need to be generated in order to study the associated biochemical reactions (Boll et al. 2016; Rabus et al. 2016b). Fortunately, we now have a series of methodologies that can be used to begin scaling our enrichment cultures, ultimately leading to a greater understanding of syntrophic hydrocarbon metabolism.

Preface

Chapter 5 summarizes four sets of experiments used to determine the substrate range of three established methanogenic hydrocarbon-degrading enrichment cultures. Cultures were incubated with various classes of hydrocarbons (n-alkanes, BTEX, or PAHs) as sole carbon and energy sources, or in co-amendment with toluene, and monitored for evidence of methanogenic activity (e.g. methane production, hydrocarbon loss; metabolite production). In all, we determined that xylenes and ethylbenzene can be co-metabolized with toluene in a methanogenic toluene-degrading enrichment culture, and successfully established a methanogenic three-ringed

PAH-degrading enrichment culture.

Chapter Five: Biodegradation and co-metabolic biodegradation of BTEX and other hydrocarbons under methanogenic conditions

5.1 Introduction

Groundwater contamination with aromatic hydrocarbons, specifically BTEX compounds, is of major concern to water quality and aquifer ecosystem health. In addition to their relatively high water solubility, BTEX compounds are prominently placed amongst the US Agency for

Toxic Substances and Disease Registry’s list of priority pollutants, based on their frequency, toxicity and potential for human exposure (ATSDR 2007). This list expands to encompass several 2- and 3-ringed PAHs (Keith 2015), primarily due to their highly recalcitrant nature in anoxic environments (more information is available on anaerobic PAH biodegradation in

Chapter 6). Bioremediation is one approach that can be used to treat these fuel components in contaminated environments, relying on the abilities of naturally-occurring microorganisms to metabolize fuel components (Meckenstock et al. 2015). Under anaerobic conditions, toluene is the most readily degraded aromatic compound under all electron-accepting conditions

(Langenhoff et al. 1996; Phelps and Young 1999; Siddique et al. 2007), and much of our fundamental understanding of anaerobic hydrocarbon metabolism comes from studies investigating this model substrate. The degradation of other BTEX components under nitrate-, iron (III)-, and sulfate reducing conditions has also been frequently reported and their mechanisms of degradation are becoming increasingly understood (for reviews see Foght 2008;

Widdel et al. 2010; Widdel and Musat 2010; Meckenstock and Mouttaki 2011; Callaghan 2013;

Heider and Schühle 2013; Musat 2015; Rabus et al. 2016b).

Elucidating the pathways used by methanogenic hydrocarbon-degrading consortia has proven to be more challenging due to the syntrophic interactions integral for energy conservation

in the absence of an electron acceptor. As such, most studies describing the physiology of methanogenic aromatic hydrocarbon biodegradation have focused solely on toluene metabolism

(e.g. Grbić-Galić and Vogel 1987; Edwards and Grbić-Galić 1994; Beller and Edwards 2000;

Washer and Edwards 2007; Fowler et al. 2012; Sun et al. 2014; Fowler et al. 2014; Laban et al.

2015). In general, a model methanogenic toluene-degrading culture is postulated to comprise four physiological groups (Zwolinski et al. 2000): a syntrophic bacterium that initiates toluene oxidation, one or more homoacetogens that can reversibly oxidize acetate coupled to hydrogen generation, a hydrogenotrophic methanogen (e.g. Methanoculleus, Methanolinea), and an acetoclastic methanogen (e.g. Methanosaeta). This model is in agreement with molecular community studies conducted on separate methanogenic toluene-degrading enrichment cultures

(Ficker et al. 1999; Fowler et al. 2012; 2014). For example, Fowler et al. (2014) used RNA-SIP analysis and qPCR studies to identify Desulfosporosinus sp. as a chief toluene degrader in the enrichment culture TOLDC, wherein this phylotype catalyzes hydrocarbon activation by addition to fumarate and subsequently degrades the product to glutaryl-CoA or crotonyl-CoA in a stepwise manner. Subsequent metabolism was then proposed to be carried out by at least two putative acetate producers (Desulfovibrionales and Syntrophaceae), though their actual role(s) in methanogenic toluene degradation were not confirmed, followed by consumption of methanogenic substrates (e.g. H2/CO2 and acetate) by the aforementioned methanogens.

Several efforts have also been made to characterize methanogenic benzene biodegradation (e.g. Grbić-Galić and Vogel 1987; Nales et al. 1998; Ulrich and Edwards 2003;

Ulrich et al. 2005; Sakai et al. 2009; Masumoto et al. 2012; Luo et al. 2016) in enrichment cultures, wherein taxa related to Syntrophus are believed to initiate benzene degradation using a

UbiD-like (de)carboxylase. To our knowledge, however, there is only a single report

documenting methanogenic xylene biodegradation in an enrichment culture (Edwards and Grbić-

Galić 1994) and no physiological evidence yet exists for methanogenic ethylbenzene metabolism, despite repeated diagnostic (metabolite) evidence of their degradation in anaerobic/methanogenic hydrocarbon-contaminated groundwater environments (Gieg et al.

1999; Elshahed et al. 2001b; Martus and Puttmann 2003; Gieg et al. 2009; Parisi et al. 2009).

In this study, we assessed the substrate diversity of TOLDC using a series of culture incubations with the goal of characterizing the physiology of methanogenic BTEX biodegradation. Though this culture has been grown on toluene for almost 20 years (Gieg et al.

1999), recent metagenomic sequencing revealed the culture to contain multiple bssA gene fragments (unassociated with toluene degradation), as well as two putative assA sequences

(Fowler, 2014). Tan et al. (2015a) expanded upon this initial query and detected several more gene fragments associated with the anaerobic degradation of BTEX compounds, two-ringed

PAHs, and n-alkanes. Thus, there is compelling functional evidence to suggest that TOLDC may indeed be capable of degrading other model hydrocarbons. Though not the primary focus of this chapter, we also sought to determine the substrate diversity of two established PAH-degrading enrichment cultures (2MNDC and 26DMNDC) and also describe the establishment of a methanogenic phenanthrene-degrading enrichment culture.

5.2 Materials and Methods

5.2.1 Culture incubations

Four sequential experiments are described herein. Preliminary experiments inoculated with TOLDC, 2MNDC, or 26DMNDC were incubated with various hydrocarbon substrates

(Section 5.2.1.1). A second round of experiments examining the co-metabolic hydrocarbon

degradation by TOLDC were conducted based on preliminary evidence of enhanced methane production from alkylbenzenes (Section 5.2.1.2). These cultures were not transferred from incubations studied in preliminary experiments, but rather were set up as new incubations. In the third round of experiments, we transferred the co-metabolic enrichment cultures (from experiment #2; 20 – 40% v/v) onto individual hydrocarbon substrates (Section 5.2.1.3). In the final round of experiments, 26DMNDC cultures enriched with phenanthrene (from experiment

#1) were transferred into fresh medium to confirm whether the 3-ringed PAH was susceptible to methanogenic degradation (Section 5.2.1.4).

5.2.1.1 Experimental hydrocarbon incubations with TOLDC, 2MNDC and 26DMNDC

An overview of TOLDC, 2MNDC, and 26DMNDC is available in Chapter 3.1. To assess what additional hydrocarbon substrates may be susceptible to degradation by TOLDC and

2MNDC, a series of duplicate incubations (10 mL, 10% v/v culture transfers) were prepared in sterile 28-mL Balch tubes sealed with butyl rubber stoppers and aluminum crimps. Anoxic bicarbonate-buffered minimal medium was prepared as previously described (Chapter 3.2.1) and contained 0.05% cysteine sulfide – subsequent incubations prepared in this present chapter were reduced with 0.05% sodium sulfide upon insights gained from experiments summarized in

Chapter 4. Individual aromatic or aliphatic hydrocarbons (5 mg; listed in Table 5-1) were amended as dilutions in 1 mL of the inert carrier 2, 2, 4, 4, 6, 8, 8-heptamethylnonane (HMN).

Duplicate hydrocarbon-free cultures were prepared to serve as negative controls, in addition to sterile microcosms for each substrate evaluated; positive control replicates amended with toluene

(for TOLDC), 2-methylnaphthalene (for 2MNDC), or 2, 6-dimethylnaphthalene (for

26DMNDC) were also established. All cultures were incubated at room temperature under dark

and static conditions for 342 – 481 days, during which methanogenic activity was routinely monitored by measuring methane production in the microcosm headspaces as previously described (Chapter 3.3.1).

5.2.1.2 TOLDC incubations with toluene and BEX as co-substrates

Preliminary TOLDC incubations showed enhanced methane production in cultures containing toluene, xylenes or ethylbenzene. These substrates, along with benzene (completing the suite of BTEX compounds), were selected for further experimentation. In a whole new set of enrichment cultures (100 mL, 20% v/v TOLDC grown with toluene), microcosms were amended with a mixture of toluene (19 µmol) and 1 – 2 BEX co-substrates (~17 µmol). To enhance hydrocarbon availability in enrichment cultures, all BTEX substrates were added neat to culture medium (without an HMN overlay); this also allowed for routine measurement of hydrocarbon loss during the incubation period by headspace GC (Chapter 3.3.2). Co-metabolic cultures were continuously refed substrate once completely consumed or after partial hydrocarbon loss (and no further hydrocarbon degradation was observed; Figure 5-2 A).

5.2.1.3 Secondary TOLDC incubations with individual BEX substrates

After 400 – 800 days of refeeding active TOLDC microcosms with BEX co-substrates, a final set of enrichment cultures poised to assess methanogenic biodegradation of individual hydrocarbons were prepared by transferring TOLDC co-substrate enrichment cultures in fresh medium (final volume of 50 mL; 20 – 40% v/v). A minimum of five replicates were prepared from transferred cultures, depending on how much culture volume was available; 2 – 3 containing toluene only, 2 – 3 containing a BEX substrate, and 1 – 2 serving as hydrocarbon-free

controls. A TOLDC culture enriched on toluene and p-xylene experienced an extensive 700-day lag period (as opposed to < 50 days for most other co-metabolic cultures; Figure 5-2 A), and has yet to be transferred. Cultures continued to be monitored for methanogenic activity, refeeding incubations as necessary for a total of 213 days.

5.2.1.4 26DMNDC incubations with phenanthrene

Following an initial 481-day incubation period under dark and static conditions, elevated amounts of methane were detected in 26DMNDC cultures enriched on phenanthrene (relative to unamended control replicates). To confirm that phenanthrene was susceptible to methanogenic biodegradation by 26DMNDC, primary transfers (10 mL; 15% v/v) of the most active culture were prepared in sterile 30-mL serum bottles and incubated for an additional 384 days. A total of

8 bottles were established; two containing phenanthrene (5 mg dissolved in 1 mL HMN), two containing HMN only (to ensure HMN could not be used as a methanogenic substrate), two carbon-free unamended controls, and two sterile controls (with phenanthrene in HMN).

Microcosms were sealed with Viton rubber stoppers to reduce hydrocarbon absorption, which allowed for quantitative measurements of phenanthrene loss during the incubation period

(Chapter 3.3.2). This culture is herein referred to as PHDC (phenanthrene-degrading culture).

5.2.2 Metabolite analysis

Metabolite extractions in active BTEX and phenanthrene-amended incubations were routinely performed during culture transfer events to search for chemical evidence of hydrocarbon activation reactions and metabolic intermediate products (Chapter 3.3.3). Briefly, acidified supernatants (up to 20 mL, pH < 2) were extracted with three equal volumes of ethyl

acetate, dried over anhydrous Na2SO4, and concentrated by rotary evaporation and heat (80 ℃) to a volume of < 20 µl. Components in the concentrated extracts were reacted with 1-2 drops of

N, O-bis(trimethylsilyl)trifluoroacetamide (BSTFA; Pierce Chemical) to form trimethylsilyl

(TMS) derivatives before being analyzed by gas chromatography–mass spectrometry (GC-MS;

Chapter 3.3.3). Identification of putative hydrocarbon metabolites was based on comparison of

GC-MS profiles with authentic standards, chemically synthesized products, and published MS profiles (Chapter 3.3.3).

5.2.3 Microbial community analysis

Microbial community analyses of TOLDC co-metabolic enrichment cultures was performed using Illumina 16S rRNA gene sequencing as previously described (Chapter 3.4.2.1).

For PHDC, 454 pyrosequencing was used to sequence amplified 16S rRNA gene fragments

(Chapter 3.4.2.2). Corresponding quality control pipelines for each sequencing platform are described in Chapter 3.4.3.

5.3 Results

5.3.1 Evidence of methanogenic activity on BTEX substrates and phenanthrene (experiment #1)

To assess the hydrocarbon substrate diversity of TOLDC, 2MNDC, and 26DMNDC, a series of new incubations were prepared containing various individual hydrocarbons dissolved in the inert carrier HMN. Methane production in the microcosm headspaces was used as a proxy for substrate utilization, and was routinely monitored for 342 – 481 days. By the end of the incubation period, most new enrichment culture and hydrocarbon substrate combinations

produced equal or lesser amounts of CH4 relative to hydrocarbon-free (unamended) controls

(Table 5-1). Despite evidence that L-cysteine metabolism was occurring in cultures (unamended cultures produced an average of 65.94 ± 1.87 µmol CH4, equating to a ~64% CH4 yield), enhanced methane production was observed in TOLDC cultures amended with alkylbenzenes

(Figure 5-1). Following an initial ~ 150-day lag period, cultures with toluene (Tol), o-xylene (o-

Xyl), m-xylene (m-Xyl), p-xylene (p-Xyl), or ethylbenzene (EtBz) produced 33 – 50% more methane than control incubations (Figure 5-1). In contrast, cultures amended with benzene (Bz) produced 22% less CH4 than control replicates, which is comparable to other hydrocarbon substrates investigated (e.g. PAHs, n-alkanes; Table 5-1). Further, a set of 26DMNDC cultures enriched on phenanthrene (Phen) also produced 52% more CH4 than its corresponding control replicates (discussed further in Section 5.3.5). Thus, all TOLDC alkylbenzene combinations (and benzene, to complete the suite of BTEX substrates) and PHDC were selected for further investigation.

5.3.2 Methanogenic activity in TOLDC co-enrichment cultures and on individual hydrocarbons (experiments #2 and 3)

We attempted to transfer the BEX-amended TOLDC incubations into fresh medium, but were unable to restore methanogenic activity after one year of culture maintenance. Only when Tol was added as a carbon and energy source was methane production observed (data not shown).

Taking account of this observation, we postulated that co-metabolic degradation of BEX may be possible in the presence of Tol. To confirm this, we prepared a new set of incubations (from a separate TOLDC cultures fed with toluene) and amended microcosms with Tol and one other

BEX substrate. Over the course of 1.5 to 3 years, rates of BTEX biodegradation were assessed in

Hydrocarbon Chemical Enhanced CH4 production formula TOLDC 2MNDC 26DMNDC (Alkyl)benzenes Toluene C7H8 + + N/A Benzene C6H6 - - N/A o-Xylene C8H10 + N/A N/A m-Xylene C8H10 + - N/A p-Xylene C8H10 + N/A N/A Ethylbenzene C8H10 + - N/A Polycyclic aromatic hydrocarbons 2-Methylnaphthalene C11H10 - + N/A 1-Methylnaphthalene C11H10 N/A - N/A 2, 6-Dimethylnaphthalene C12H12 N/A - + Naphthalene C10H8 N/A - - Phenanthrene C14H10 N/A - + Anthracene C14H10 N/A - - 9-Methylanthracene C15H12 N/A - - n-Alkanes Short-chain n-alkanes (C6 and C10) C6H14 - N/A N/A C10H22 Long-chain n-alkanes (C16 and C18) C16H34 - N/A N/A C18H38 N/A = not available; test was not performed.

each incubation, refeeding cultures as needed. Methane production was also monitored over time

(data not shown).

We found that xylenes and ethylbenzene could be partially degraded by TOLDC in the presence of toluene. For example, in an enrichment culture containing Tol and o-Xyl, the amount of o-xylene amended after each refeed decreased from an average of 8.1 ± 1.4 µmol to 2.1 ± 0.7

µmol, corresponding to 57 – 86% substrate loss (Figure 5-2 A). In contrast, Tol was completely

consumed after being refed, degrading the aromatic hydrocarbon at an average rate of 13 ± 3.0

µM/day. At this rate, a 1-L culture of TOLDC could theoretically consume 504 µL of toluene a year. We remark that similar rates of o-Xyl consumption were observed in the first ~ 7 days after refeeds (10.6 ± 4.2 µM/day) before rates decreased, and that these trends were also observed for all other co-metabolic cultures containing xylene or ethylbenzene (data not shown). In agreement with our initial experiments, no evidence of benzene consumption was observed in TOLDC cultures after three years of incubation.

When co-metabolic cultures were transferred onto individual hydrocarbons, methanogenic activity only resumed in incubations containing toluene (Figure 5-2 B and C). For example, an average of 540 µmol CH4 was produced from duplicate incubations fed ~ 113 µmol

of Tol, corresponding to a 106% yield of the theoretical methane production from this substrate

(Figure 5.2B). No significant methane production was reported for incubations containing o-Xyl

(P value > 0.05), which is in accordance with negligible amounts of substrate loss observed after

213 days of incubation (Figure 5-2 C). Again, these trends were observed for all BEX substrates evaluated (Figure B-1 or in data not shown).

5.3.3 Metabolite evidence of fumarate addition reactions using BTEX substrates (experiments #2 and 3)

To assess what mechanism(s) of anaerobic hydrocarbon biodegradation catalyze BEX activation in the presence of toluene, TOLDC co-substrate enrichment cultures were extracted for putative anaerobic hydrocarbon metabolites at the end of their growth periods, silylated, and subjected to

GC-MS analysis. We detected and verified the formation of benzylsuccinate, the expected fumarate addition product of toluene (Fowler et al. 2012; Fowler et al. 2014) in all organic extracts, as well as the corresponding alkylbenzylsuccinates from ethylbenzene and all three isomers of xylene, by comparison peak retention time and mass spectral pattern to purchased and synthesized authentic standards (Figure 5-3). Toluic acids were also found in co-metabolic cultures containing their respective xylene isomer, presumably as a downstream product formed from modified β-oxidation reactions of methylbenzylsuccinate (Leutwein and Heider 1999;

2001; 2002). No metabolites indicative of anaerobic benzene biodegradation could be found, which is in accordance with previous methane and hydrocarbon measurements indicating a lack of benzene utilization (Figures 5-1 and B-1). Similarly, no evidence of fumarate addition product formation was detected in cultures containing individual BEX substrates.

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Figure 5-3. Detection of alkylsuccinates formed from (A) toluene, (B) o-xylene, (C) m- xylene, (D) p-xylene, and (E) ethylbenzene. Mass spectral patterns of the TMS-derivatized metabolites found in culture extracts on shown to the left; reference profiles for authentic standards are shown on the right.

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Remarkably, the dehydrogenation product of benzylsuccinate, E-phenylitaconate, was detected in TOLDC cultures repeatedly fed toluene (Figure 5-4 A), matching a mass spectral reference profile provided by Dr. Joe Suflita at the University of Oklahoma (Figure B-2). Key ions present in the TMS-derivatized standard (m/z 335, 306, 291, 229, 207, 147, 115, 73) were found in the experimental mass spectrum in similar intensities. We also detected a hydrocarbon metabolite tentatively identified as E-(2-methylphenyl)itaconate in cultures amended with o- xylene (Figure 5-4 B). Though there is no known reference profile available for the silylated product, the peak shares similar ion fragmentation patterns to E-phenylitaconate, offering clues to its identity. For example, m/z ions 364 (M+), 349 (M+ – 15), 319, 305, and 187 seen in the putative metabolite are 14 atomic mass units larger than corresponding fragments seen for E- phenylitaconate (Figure 5-4 A; Figure B-2), suggesting the presence of an extra methyl group.

No similar metabolites could be found in cultures amended with other xylene isomers, or in any other cultures investigated, thus the compound has likely been correctly identified. Also of key interest was the detection and identification of several degradation products of benzoyl-CoA

(detected in its free acid form, benzoate) in TOLDC cultures (co)amended with toluene (Figure

B-3), including cyclohex-1, 5-diene-1-carboxylate, cyclohex-1-ene-1-carboxylate, cyclohexane carboxylate, and glutarate.

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5.3.4 Microbial community structure of TOLDC in co-substrate enrichment cultures (experiment #2)

Illumina 16S rRNA gene sequencing was used to search for any changes in the microbial community composition of TOLDC when co-enriched on Tol and other alkylbenzenes. When compared to a TOLDC incubation grown solely on toluene, however, most of the changes seen were marginal and pertained primarily to the methanogenic archaea enriched in each culture

(Table 5-2). For example, hydrogenotrophic Methanobacterium proliferated from less than 0.1% of reads up to 7.2% of reads when grown with ethylbenzene as a co-substrate. Additionally, a 4 –

5% increase in reads belonging to the Bacteroidetes phylum in cultures co-amended with either xylene or ethylbenzene. However, the relative abundance of Desulfosporosinus sp. was near identical in each set of cultures (ranging from 9.0 to 10.1% with other alkylbenzenes), and enrichment of previously unidentified syntrophic hydrocarbon oxidizers was not observed. In

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Table 5-2. Taxonomic affiliations of 16S rRNA gene sequences comprising at least 0.1% of total quality reads (> 1% in bold) in TOLDC amended with toluene only (Tol only) or with benzene (Bz + Tol), ethylbenzene (Etbz + Tol) or xylenes (Xyl + Tol) as a co-substrate. Other phylogenies detected in TOLDC co-substrate enrichment cultures included candidate division ‘Clocimonetes’ (formerly known as WWE1) and unclassified Syntrophorhabdaceae. Total quality reads (%) Etbz + Taxon Tol only Bz + Tol Tol Xyl + Tol Euryarchaeota Methanobacterium 0.00 22.05 7.21 6.21 Methanoculleus 41.66 6.81 13.89 17.25 Methanoregula 1.61 0.00 1.97 5.92 Methanosaeta 35.95 26.46 39.12 37.71 Bacteroidetes Unclassified Bacteroidiales 0.40 0.21 2.73 2.93 Unclassified Porphyromonadaceae 0.00 0.67 2.09 1.74 Chloroflexi Unclassified Anaerolinaceae 0.85 0.42 4.67 6.25 Firmicutes Desulfosporosinus 9.07 20.53 10.17 10.09 Deltaproteobacteria Unclassified Deltaproteobacteria 0.00 1.07 0.00 0.00 Desulfovibrio 0.40 0.26 1.01 0.98 Geobacter 0.00 6.18 0.00 0.00 Syntrophus 0.55 0.14 0.40 1.88 Gammaproteobacteria Unclassified Pseudomonadaceae 0.00 2.79 0.00 0.00 Pseudomonas 0.00 0.53 0.00 0.00 Spirochaetes Treponema 1.44 0.53 0.60 0.25 Synergistetes Unclassified Synergistaceae 0.28 0.38 0.46 0.61 Thermotogae Kosmotoga 0.31 0.00 1.79 0.41 Other 2.33 1.37 1.46 1.40 Total 94.84 89.48 90.65 93.30 aValues are shown as an average of replicates amended with Tol and one of o-, m-, or p-xylene.

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addition to Desulfosporosinus sp. reads affiliated to all key toluene degraders in TOLDC

(Desulfovibrio, Syntrophus, Methanoculleus, and Methanosaeta) were detected in each culture evaluated and in similar abundances. Though more apparent microbial community shifts are seen for TOLDC cultures containing benzene, it is of less interest because no evidence of co- metabolic degradation was ever reported for these incubations.

5.3.5 Chemical and phylogenetic evidence of methanogenic phenanthrene biodegradation (experiment #4)

As introduced in Section 5.3.1, 26DMNDC cultures enriched on phenanthrene (Phen) produced elevated amounts of methane relative to unamended control replicates, reaching a maximum of 56.6 ± 2.3 µmol CH4 by day 481 (Figure 5-5). After transferring the most active culture into new microcosms, methanogenic activity persisted in live replicates containing the hydrocarbon substrate, producing 72.3 ± 15.6 µmol CH4 in duplicate incubations over 142 days. Control cultures that contained either a Phen-free HMN overlay or were carbon-free (unamended) produced less than 2 µmol CH4 during the incubation period, and no methane was detected in sterile controls (Figure 5-5). Additionally, an average of 19% of available Phen was consumed in live replicates after 142 days, corresponding to an experimental degradation rate of 3.7 µM Phen/day. At this rate, it would take ~ 2 years for 1 liter of culture to completely consume 500 mg of phenanthrene. We also remark that PHDC cultures amended with phenanthrene were visually more turbid than seen in control replicates (Figure B-4), offering evidence of biomass production from phenanthrene utilization.

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% Phenanthrene loss in HMN overlay HMN in loss Phenanthrene %

Due to limited available culture volume (10 mL), it was difficult to resolve putative hydrocarbon metabolites in organic extracts of PHDC. Nevertheless, mass spectral analyses revealed the presence of peaks corresponding to a handful of short-chain fatty acids, as well as decahydro-2-naphthoic acid and p-cresol as putative biodegradation products of phenanthrene

(Figure B-5). These products were not detected in the corresponding substrate-unamended or sterile controls. A carboxylation product of phenanthrene was sought during GC-MS analysis

(based on literature reports of sulfidic 2- and 3-ringed PAH activation products; e.g.

Meckenstock et al. 2000; Zhang et al. 2000; Annweiler et al. 2002; Davidova et al. 2007) but was not found.

Pyrosequencing analysis of the 16S rRNA genes amplified from PHDC (Figure 5-6) revealed the predominance of organisms belonging primarily to an uncultured Rikenallaceae

(14.8% of reads), a Clostridium sp. (14.8% of reads), and to Spirochaeta (13.2% of reads).

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Berdugo-Clavijo et al. (2012) had also identified a Clostridium sp. as a dominant organism in

PHDC’s parent culture, 26DMNDC. The phenanthrene-degrading enrichment culture was also dominated by hydrogenotrophic methanogens affiliating within the genera Methanobacterium and Methanoculleus (Figure 5-6) Acetotrophic methanogens were also found to be present in the microbial community, but in low abundance (2.1%). Interestingly, the enrichment of methylotrophic Methanomethylovorans was detected in the consortium (7.1% of reads); which was previously detected in low abundance (0.34% of reads) in 26DMNDC (Berdugo-Clavijo et al., 2012), No enrichment was observed for other putative syntrophic hydrocarbon-oxidizing bacteria previously identified in 26DMNDC (Figure 5-6; Berdugo-Clavijo et al. 2012).

5.4 Discussion

In this work, three established methanogenic aromatic hydrocarbon-degrading enrichment cultures were challenged on various model hydrocarbon substrates in order to

Figure 5-6. Percent distribution of bacterial (coloured) and archaeal (gray) sequences in PHDC as determined by 454 pyrosequencing, with the lowest confident taxonomic level shown. The ten phylogenies shown comprised 98% of total 16S rRNA gene reads, with the remaining 2% occupied by minor constituents, including Smithella sp. (0.068%) and Geobacter sp. (0.061%).

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determine their abilities to degrade diverse hydrocarbon substrates. We found that a methanogenic toluene-degrading enrichment culture was capable of co-metabolizing xylenes and ethylbenzene, while a 2, 6-dimethylnaphthalene-degrading consortium could successfully be enriched on the three-ringed PAH phenanthrene. These findings support in situ evidence of methanogenic aromatic hydrocarbon biodegradation in BTEX-contaminated groundwater

(reviewed by Gieg and Toth 2017b) and expands the range of model substrates experimentally verified to be utilized by methanogenic hydrocarbon-degrading consortia.

In incubations repeatedly fed toluene and either xylene or ethylbenzene, we identified signature anaerobic hydrocarbon metabolites corresponding to fumarate addition reactions of each substrate (Figure 5-3), as well as tentatively identified E-(2-methylphenyl)itaconate, metabolites derived from toluene and o-xylene, respectively (Figure 5-4). Despite their relatively stability, dehydrogenation products of (alkyl)benzylsuccinates have seldom been found in anaerobic enrichment cultures (e.g. Chee-Sanford et al. 1996; Beller and Spormann 1997a;

Morasch et al. 2004; Rotaru et al. 2010; Wöhlbrand et al. 2013) and, to our knowledge, have never previously been detected in a methanogenic enrichment culture, making this a novel result.

Under nitrate-, iron(III)-, and sulfate-reducing conditions, the degradation pathways for xylenes are believed to be analogous to that of toluene, with a few minor differences for p-xylene (Rabus et al. 2016a). Given that toluic acids were also detected in the extracted supernatants of xylene- amended cultures, we propose that methanogenic xylene co-metabolism proceeds in a manner analogous to other anaerobic electron accepting conditions, and parallels that of anaerobic toluene biodegradation (Figure 5-7). No ethylbenzene metabolites other than the fumarate addition could be identified, but its biodegradation may proceed in an identical or similar

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pathway to that proposed by Kniemeyer et al. (2003). It is also unclear whether benzoate

(benzoyl-CoA) is subsequently formed from ethylbenzene as a central metabolic intermediate, as the compound could not be detected in cultures solely enriched on this substrate. Elshahed et al.

(2001) detected benzoate in ethylbenzene-amended sulfate-reducing aquifer sediment enrichments, but this finding has never been repeated. We also remark that there was no chemical evidence to suggest than anaerobic ethylbenzene hydroxylation was occurring in

TOLDC, despite evidence of a near-complete gene pathway is present in its metagenome

(Fowler 2014; Tan et al. 2015a). This is reasonable, as the enzyme catalyzing toluene activation is also likely responsible for activating ethylbenzene.

Chemical and phylogenetic evidence of methanogenic xylene and ethylbenzene degradation suggests that the syntrophic oxidizer responsible for their activation is

Desulfosporosinus (Table 5-2), presumably by the same benzylsuccinate synthase enzyme (BSS) used to activate toluene (Fowler et al. 2012; 2014), though functional evidence is required for confirmation. Even though enzymes are typically selective for their intended substrate (due to steric and binding properties), structurally similar compounds (e.g. xylene, ethylbenzene) may occasionally enter and access the binding site (Rabus et al. 2011). Other studies have also proposed this following observations of anaerobic hydrocarbon co-metabolism in cultivation studies (Wilkes et al. 2003; Safinowski et al. 2006; Rabus et al. 2011; Abu Laban et al. 2015), including on alkylbenzenes (Jarling et al. 2015). This may also help to explain why xylene and ethylbenzene were only partially degraded in their respective co-enrichment cultures. In our experiments, ‘accidental’ hydrocarbon activation only appears to proceed above a threshold concentration (in the case of o-xylene, > 40 µM) and during active toluene consumption (Figure

5-2). Whether these compounds can be biodegraded as methanogenic substrates in the absence of

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To benzoyl-CoA degradation pathway

Figure 5-7. Proposed methanogenic degradation pathways of toluene and other alkylbenzene co-substrates by Desulfosporosinus sp. present in TOLDC. Metabolites are shown as free acids. Hydrocarbon metabolites found that are diagnostic of their parent hydrocarbon are marked (). Multiple arrows represent more than one enzymatic step; hypothetical intermediate products are shown in brackets. Structure nomenclature: 1, toluene; 2, benzylsuccinate; 3, E-phenylitaconate; 4, 2-[hydroxy(phenyl)methyl]succinate; 5, benzoylsuccinate; 6, benzoate; 7, xylene; 8, methylbenzylsuccinate; 9, E-(2- methylphenyl)itaconate; 10, toluate; 11, ethylbenzene; 12, (1-phenylethyl)succinate; 13, (2- phenylpropyl)malonate; 14, 4-phenylpentanoate; and 15, 2-phenylpropanoate.

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toluene in other cultures is unknown: our data suggests that they can only be co-metabolized with toluene. To our knowledge, there is only a single report to date demonstrating clear evidence of methanogenic degradation of xylenes (o-isomer, individually or in co-enrichment with toluene; Edwards and Grbić-Galić 1994) in an enrichment culture. Interestingly, Edwards and Grbić-Galić (1994) found that repeated amendment of cultures solely with toluene (>2 years) could no longer degrade o-xylene, and vice-versa. TOLDC has been amended with toluene as its sole carbon and energy source for almost 20 years (Gieg et al. 1999; Fowler et al. 2012; Fowler et al. 2014); though it is quite possible that the culture may have at one point been capable of degrading other hydrocarbon substrates prior to its repeated enrichment on toluene but lost its ability to do so over time. This is plausible, as several other enrichment cultures have been established from sediments of the original source inoculum of TOLDC on a number of other hydrocarbon substrates (e.g. Rios-Hernandez et al. 2003; Townsend et al. 2003; Gieg et al. 2008;

Berdugo-Clavijo et al. 2012).

We hypothesize that methanogenic benzene biodegradation did not occur by TOLDC because the activation energy required for C–H bond dissociation in benzene (473 kJ/mol) exceeds what can theoretically be generated by enzymatic addition of fumarate (–439 kJ/mol;

Boll and Heider 2010). Most studies have proposed carboxylation as the predominant mechanism of anaerobic benzene activation (Phelps et al. 2001; Musat and Widdel 2008;

Kunapuli et al. 2008; Abu Laban et al. 2010; Holmes et al. 2011; Luo et al. 2014), though hydroxylation (Zhang et al. 2013) and methylation (Ulrich et al. 2005) have been shown to occur under higher electron-accepting conditions (e.g. coupled to iron (III)- or nitrate reduction, respectively).

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Following the addition of fumarate to toluene, benzylsuccinate is activated to benzylsuccinyl-CoA that is then degraded via modified β-oxidation reactions leading to the formation of benzoyl-CoA (e.g. Leutwein and Heider 1999; 2001; 2002). Benzoyl-CoA (detected in its free acid form, benzoate) subsequently undergoes a series of ring reduction reactions, beginning with the formation of cyclic 1, 5-dienoyl-CoA by one of two classes of benzoyl-CoA reductases (BCR; Fuchs et al. 2011; Boll et al. 2014). Class I BCR (encoded by the conserved bcrABCD) couples the transfer of two electrons to the aromatic ring system with the hydrolysis of two ATP. Accordingly, this energetically ‘expensive’ strategy has been found to primarily be expressed in facultative organisms or anaerobic bacteria with higher energy yields such as denitrifying Thauera aromatica (Carmona et al. 2009; Boll et al. 2014), with the Euryarchaeon

Ferroglobus placidus as the only known exception (Holmes et al. 2011; Schmid et al. 2015). In contrast, Class II BCR (encoded by the bamBCDEFGHI gene cluster) are present in the vast majority of known obligately anaerobic bacteria able to degrade aromatic compounds (Löffler et al. 2011), including TOLDC’s Desulfosporosinus sp. (Fowler 2014), and are believed to catalyze ring reduction in an ATP-independent manner (Wischgoll et al. 2005; Buckel and Thauer 2013;

Boll et al. 2014). In the present study, the formation of cyclohex-1, 5-diene-1-carboxylate and glutarate in cultures (co)-amended with toluene was observed (Figures 5-8 and B-3).This supports genomic evidence of CoA-ligation to benzoate (bamY) and downstream steps prior to ring opening (bamRQ), and ring opening reactions steps (catalyzed by bamA) first reported by

Fowler (2014). Further, we identified two additional metabolites indicative of obligate anaerobic benzoyl-CoA transformation to cyclohexane carboxylate (Figures 5-8 and B-3). Fowler et al.

(2012) had previously detected cyclohexane carboxylate in TOLDC (in addition to pimelate, and glutarate), but did not delve into why this product was formed. We propose that the formation of

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Desulfosporosinus sp. Desulfovibrio sp. (?)

Syntrophus sp.

Figure 5-8. Proposed syntrophic oxidation and reduction pathways of benzoate (1) in TOLDC. Metabolites are shown as free acids. All hydrocarbon metabolites shown were detected in toluene-amended TOLDC incubations in this study or by Fowler et al. (2012) Multiple arrows represent more than one enzymatic step. Desulfosporosinus sp. is proposed to catalyze the oxidation branch of benzoate metabolism, leading to ring cleavage and subsequent formation of intermediates pimelate (3) and glutarate (4), generating acetyl- CoA. Desulfovibrio sp. is also thought to consume glutarate based on a previous study (Fowler et al. 2014). Synthophus sp. is proposed to couple anaerobic benzoate oxidation with the reduction of cyclohex-1, 5-diene-1-carboxylate (2), forming cyclohex-1-ene-1- carboxylate (5) and cyclohexane carboxylate (6). This could then be further degraded using a modified ß-oxidation pathway.

these metabolites is due to a reductive branch of benzoyl-CoA metabolism used for energy conservation in TOLDC. The formation of cyclohex-1-ene-1-carboxylate and subsequently cyclohexane carboxylate from benzoate was previously experimentally verified in a

Syntrophus acidotrophicus pure culture (Elshahed et al. 2001a) and its metabolic pathway elucidated (Mcinerney et al. 2007; Boll et al. 2016). The formation of cyclohexane carboxylate by S. acidotrophicus is thought to be coupled to electron transferring protein-mediated flavin- based electron bifurcation (Sieber et al. 2012; Kung et al. 2013; Buckel and Thauer 2013). Such a mechanism was proposed by Buckel and Thauer (2013) for regenerating ferredoxin(red) under sulfidic and methanogenic conditions, and therefore may be a key mode of conservation energy,

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in addition to substrate level phosphorylation and electron transport phosphorylation. The formed cyclohexane carboxylate would then be further degraded using a modified β-oxidation pathway to acetyl-CoA by Syntrophus (Figure 5-8; Mcinerney et al. 2007). This builds upon earlier evidence in Chapter 4 that the abundance of Syntrophus affects rates of methanogenic toluene biodegradation in TOLDC. In all, we hypothesize that the formation of cyclohexane carboxylate, coupled to this electron bifurcation mechanism, is a key rate-limiting step in methanogenic hydrocarbon metabolism, but essential for electron transfer in syntrophic consortia (Sieber et al.

2012). Thus, we propose that Syntrophus plays an essential role in allowing methanogenic toluene biodegradation to proceed in thermodynamically favourable manner, and that surveying the metabolic profile of TOLDC in this study inadvertently has helped us to resolve the role of

Syntrophus in this syntrophic community. Both the oxidative and reductive branches of fermentative utilization of benzoate are active in TOLDC, which we propose are catalyzed by

Desulfosporosinus sp. and Syntrophus sp., respectively (Figures 5-7 and 5-8), expanding upon a working model of methanogenic toluene biodegradation first devised by Fowler et al. (2014).

In the past decade, substantial headway has been made demonstrating the susceptibility of PAHs to methanogenic biodegradation (Chang et al. 2005a; Dolfing et al. 2009; Jiménez et al.

2012; Berdugo-Clavijo et al. 2012; Zhang et al. 2012a). Though PAHs have previously been shown to be activated by fumarate addition (for alkyl-substituted PAHs) and carboxylation (for unsubstituted PAHs) under sulfate-reducing conditions (e.g. Zhang and Young 1997;

Meckenstock et al. 2000; Davidova et al. 2007; Musat et al. 2009), the mechanism of methanogenic PAH biodegradation is unknown. In a methanogenic 2-methylnaphthalene- degrading enrichment culture (2MNDC), 2-naphthoic acid was formed in experimental incubations (Berdugo-Clavijo et al. 2012), with no evidence of fumarate addition products

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formed: attempts to identify carboxylation products using [13C] bicarbonate were also fruitless

(Berdugo-Clavijo 2015). We too were not able to determine what activation mechanism is responsible for catalyzing PAHs activation. From metabolite analysis surveys, a handful of putative metabolites were identified in organic extracts of PHDC (that were not present in the controls), but appear to be downstream products formed after several degradation steps (Figure

B-5). At this time, it is unclear how these metabolites were formed, though initial postulates suggest ring saturation and cleavage into organic acid products in a similar manner to 2-ringed

PAHs (Meckenstock et al. 2016). Based on the abundance of Clostridium sp. in PHDC, we suspect that the bacterium may participate in phenanthrene biodegradation in some capacity.

Berdugo-Clavijo et al. (2012) had previously come to this conclusion in cultivation studies of

2MNDC and 26DMNDC. This is in agreement with earlier research conducted by Chang et al.

(2005); 16S rRNA gene libraries prepared from 2- and 3-ringed PAH-degrading marine harbor sediments were also predominantly enriched with members of the phylum Firmicutes and class

Clostridia. Members of this phylum well known to play key roles in anaerobic and methanogenic hydrocarbon biodegradation, including Desulfosporosinus sp. in TOLDC. In Chapter 6, we will further explore the functional potential of Clostridium to participate in methanogenic PAH biodegradation using DNA-SIP analysis and metagenomic sequencing. Other (putative) methanogenic hydrocarbon degraders belonging to Firmicutes includes uncultured

Peptococcaceae and Desulfotomaculum (Gray et al. 2010; Jiménez et al. 2016)– these taxa were found to be enriched over time in methanogenic crude oil-degrading enrichment cultures described in Chapter 7. Hydrogenotrophic, acetotrophic, and (interestingly) methylotrophic methanogens also appear to serve in the syntrophic metabolism of the three-ringed PAH. Guo et al. (2012) found that this lesser characterized group of methanogens dominated archaeal reads in

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16S rRNA gene sequencing of water samples collected from a biogenic coal methane bed, suggesting that these microorganisms may play an important role in PAH degradation, and that our understanding of methanogenic PAH utilization remains far from complete. Additional exploration of PAH degradation is provided in Chapter 6.

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Preface

Chapter 6, we interrogated numerous enrichment cultures having the ability to utilize

PAHs using DNA-SIP in order to identify the key microorganisms associated with the biodegradation of these compounds under methanogenic conditions. To account for the low biomass present in these cultures (due to the bioenergetics constraining methanogenic PAH biodegradation), we devised a series of modifications to standard DNA-SIP protocols in order to fractionate and quantify low concentrations of genomic DNA (< 1 µg). Microbial 16S rRNA gene sequencing of fractionated DNA identified Clostridium as a putative naphthalene degrader, which was supported by metagenomics evidence of genes predicted to encode for enzymes facilitating ring reduction and cleavage steps of 2-naphthoyl-CoA.

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Chapter Six: Assessing Carbon Flow Through Methanogenic PAH-Degrading Communities by DNA-SIP and Metagenomic Approaches

6.1 Introduction

Polycyclic aromatic hydrocarbons (PAHs) are widely distributed in the environment through their presence in fossil fuels, refined fuel products, and their formation during combustion. Their high hydrophobicity and low bioavailability increase with their molecular masses, contributing to their persistence in the environment. As some PAHs are also mutagenic and/or carcinogenic (Sverdrup et al. 2002; Abdel-Shafy and Mansour 2016), their fate as environmental contaminants pose ecological and human health concerns (Keith 2015). Research conducted in the past two decades has firmly established that two- and three-ringed PAHs are susceptible to microbial degradation under anaerobic conditions (reviewed by Meckenstock et al.

2004; Foght 2008; Meckenstock and Mouttaki 2011; Meckenstock et al. 2016), with most reports characterizing the degradation of model two-ringed PAHs by the sulfate-reducing enrichment cultures (strains) N47 and NaphS2 (Meckenstock and Mouttaki 2011; Meckenstock et al. 2016).

Genomic and proteomic surveys identified that both organisms share sequence similarity across two gene clusters differentially expressed during the anaerobic degradation of naphthalene and 2- methylnaphthalene (DiDonato et al. 2010; Bergmann et al. 2011b; Bergmann et al. 2011a). One gene cluster contains a UbiD-like (de)carboxylase believed to be responsible for the carboxylation of naphthalene, while the second cluster codes for the fumarate adding catalytic subunit of naphthyl-2-methylsuccinate synthase (NmsA). Several of the enzymes facilitating downstream degradation steps of naphthalene and 2-methylnaphthalene have also been putatively and experimentally verified (Selesi et al. 2010; DiDonato et al. 2010; Bergmann et al.

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2011a; 2011b; Mouttaki et al. 2012; Buckel et al. 2014), including novel dearomatization enzymes such as 2-naphthoyl-CoA reductase and the proposed 5, 6-dihydro-2-naphthoyl CoA reductase (Eberlein et al. 2013a; 2013b; Estelmann et al. 2015). The partial elucidation of these pathways has helped to identify signature metabolites indicative of anaerobic PAH utilization that can serve as diagnostic markers of active biodegradation in PAH-contaminated sites (e.g.

Phelps et al. 2002; Ohlenbusch et al. 2002; Gieg and Suflita 2002; Griebler et al. 2004;

Safinowski et al. 2006; Parisi et al. 2009; Gieg et al. 2010; Jobelius et al. 2011; Morasch et al.

2011; Wawrik et al. 2012; Bian et al. 2015), and for designing PCR-based assays targeting PAH catabolic genes (von Netzer et al. 2013; Morris et al. 2014).

Unfortunately, cultivating anaerobic PAH-degrading enrichment cultures has been a tall order, though a few studies have successfully characterized novel PAH degraders (e.g. Musat et al. 2009; Kleemann and Meckenstock 2011; Kümmel et al. 2015; Martirani-Von Abercron et al.

2016). Both the kinetics and thermodynamic landscape of anaerobic PAH degradation impede the growth rates of PAH degraders (Dolfing et al. 2009; Meckenstock et al. 2016), requiring several months or even years to obtain sufficient biomass and culture volume for biochemical analysis (Galushko et al. 1999; Widdel et al. 2010; Meckenstock et al. 2016). Consequently, the organisms responsible for PAH catabolism are often poorly characterized and their mechanism(s) of degradation remain unknown. This is especially true for methanogenic incubations; though a handful of phylotypes affiliated with Proteobacteria and Firmicutes have been enriched on two- and three-ringed PAHs, along with Bacteroidetes, Chloroflexi, and

Spirochaetes as minor constituents (Chang et al. 2005; 2006; Berdugo-Clavijo et al. 2012; Zhang et al. 2012b), their biological roles remain elusive.

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Owing to the difficulty of cultivating anaerobic PAH-degrading microorganisms, the application of nucleic acid-based stable isotope probing (SIP) offers enormous potential for identifying novel PAH degraders as the method allows tracking of active organisms within natural and enriched complex microbial communities, as well as from extremely slow- to fast- growing microbes. DNA-SIP also requires significantly less biomass than proteomics analysis

(Vogt et al. 2016; Rabus et al. 2016b), thus is advantageous for assessing carbon flow in low biomass communities. Due to these key methodological advantages, SIP has already been successfully implemented for investigating anaerobic n-alkane and monoaromatic hydrocarbon- degrading microbial communities (reviewed by Head et al. 2014; Vogt et al. 2016). To our knowledge, however, only one study has used DNA-SIP to monitor PAH degradation (Zhang et al. 2012a), wherein the authors applied the molecular technique with T-RLFP analysis of 13C- labeled 16S rRNA gene sequences and identified a variety of unexpected Proteobacteria

(Methylibium, Legionella, Rhizobiales) participating in anthracene degradation in methanogenic leachate-containing microcosms.

Along with biomass limitations, two other key concerns impacting the successful application of SIP for tracking anaerobic PAH degradation are: i) incorporation of sufficient heavy isotope, which requires extensive incubation periods, which ii) can increase the risk of

13C-carbon cross-feeding to peripheral microorganisms. However, we hypothesize that coupling

SIP with metagenomic analysis can serve to amass convincing evidence of PAH degradation by identifying labeled organisms with putative PAH degradation genes. In this study, we evaluated the feasibility of using DNA-SIP and metagenomics to pinpoint key microorganisms responsible for the initial degradation steps of naphthalene (a two-ringed PAH) and phenanthrene (a three- ringed PAH) metabolism under methanogenic conditions.

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6.2 Experimental Procedures

6.2.1 Culture incubations and analytical methods

Five actively-maintained methanogenic cultures enriched on model PAHs (2MNDC,

NDC, 26DMNDC, PHDC; Chapter 3.1.2 – 3.1.3) or bituminous oil sands (Chapter 3.1.5) were selected as experimental inocula for DNA-based SIP analysis. We also chose to query oilfield produced water collected from a heavy crude oil reservoir previously described in Section 3.1.4

(MHGC field, well 18PW; Voordouw et al. 2009), but did not pre-enrich these samples on

PAHs. Prior to experimentation, we reviewed several articles detailing methods of methanogenic

[13C] hydrocarbon incubation and density gradient fractionation (Liou et al. 2008; Sakai et al.

2009; Morris et al. 2012; Zhang et al. 2012a; Cheng et al. 2013; Noguchi et al. 2014; Sun et al.

2014; Fowler et al. 2014; Abu Laban et al. 2015). Generally, these experimental cultures were prepared in large volumes (> 50 mL each; ~10% transfer v/v), though isotopically labeled nucleic acids could be fractionated and retrieved from volumes as low as 20 mL. With respect to incubation times, cell harvest times were chosen based on reported hydrocarbon loss and production of end products, ranging anywhere between 1 and 7 months. Notably, successful incorporation of [13C] anthracene was reported after four months of incubation (Zhang et al.

2012a). Thus, for this project we decided to sacrifice replicates in one-month intervals for a total of three months. To account for low amounts of biomass in available cultures, we chose to use undiluted cultures (100% v/v) for all experiments in relatively small volumes (10 mL).

Microcosms were prepared in 50-mL serum bottles in triplicate and amended with 4 mg 12C or fully 13C-labeled naphthalene or phenanthrene dissolved in 2 mL of HMN. Labeled PAHs were purchased from Sigma-Aldrich and contained no less than 99% 13C at all carbon positions.

Unamended (containing HMN only) and sterile control replicates (containing [12C] PAH) were

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also established, giving a minimum of 8 experimental microcosms per culture/PAH combination investigated (summarized in Table 6-1). SIP incubations were carried out at room temperature under dark and static conditions; methanogenic activity was monitored weekly by measuring

CH4 production in the microcosm headspace (Section 3.3.1).

6.2.2 DNA extraction and density gradient formation

Once a month, a [12C] and [13C] PAH replicate from each culture was sacrificed for SIP analysis following the procedures outlined by Neufeld et al. (2007b). Substrate-unamended replicates were harvested after three months of incubation. Following DNA extraction of sacrificed microcosms (Section 3.4.1), we observed that the concentrations of retrieved DNA were often below detectable limits (< 0.5 ng), though select samples contained up to 905 ng of

DNA (Table 6-1). To our knowledge, the least amount of DNA reported for successful density gradient fractionation was ~1 µg (Abu Laban et al. 2015), which is 5–10 times less than the amount of DNA recommended for density gradient fractionation (Neufeld et al. 2007b). Thus, our DNA extraction yields were presumably at or below the reported methodological limits of

DNA-SIP.

Extracted genomic DNA was combined with CsCl (dissolved in MilliQ water; density =

1.88 g/mL) and a gradient buffer (0.1 M Tris–HCl, 0.1 M KCl, 1 mM EDTA) in polyallomer

Quick-Seal centrifuge tubes (Beckman Coulter), and ultracentrifuged at 50,000 rpm (∼300,000 × gav) in a VTi 90 rotor (Beckman Coulter) at 20 ℃ with vacuum for 65 hours. The centrifugal force and centrifugation time exceeded the gradient formation parameters used by comparable

SIP studies (Cheng et al. 2013; Fowler et al. 2014; Abu Laban et al. 2015), but was considered a necessary precaution to help maximize banding efficiency of the presumably limited [12C] and

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[13C] DNA. DNA was retrieved by density fractionation resulting in an average of 12 fractions containing 425 µL each, where fraction 1 was the heaviest and fraction 12 was the lightest. The density of each fraction was measured with a refractometer (AR200, Reichert) to confirm proper gradient formation. Finally, DNA was precipitated from the CsCl with polyethylene glycol and glycogen, washed with 70% ethanol, and resuspended in 30 µL Tris-EDTA buffer.

6.2.3 Molecular community analysis

Following density gradient fractionation, most DNA concentrations could not be determined directly by fluorometry (< 0.5 ng/mL; below detection limits). A preliminary attempt to quantify the distribution of total 16S rRNA genes in SIP fractions was performed using a previously described qPCR assay (Cheng et al. 2013; Abu Laban et al. 2015), but most samples failed to amplify above threshold levels even after 40 cycles (data not shown). Instead, we sought to identify SIP fractions containing any detectable amount of DNA by amplifying the V6-

V8 regions of 16S rRNA gene fragments using a PCR assay adapted for low concentrations of

DNA (Klindworth et al. 2013). Here, PCR reactions (25 µL) contained 12.5 µL 2× PCR Master

Mix (Fermentas), 9 µL RNase-free water, 0.5 µL each of universal primers 926F and 1392R

(Chapter 3.4.2), and 2.5 µL gDNA template. PCR assays were performed using a three-step thermoprofile: an initial denaturation at 95°C for 5 min; 25 cycles of 95°C (40s), 55.0°C (2 min),

72.0°C (1 min); and a final extension at 72°C for 7 min. Amplification of the target region was confirmed on a 1% agarose gel, purified using the Agencourt AMPure XP magnetic bead system

(Beckman Coulter) according to the manufacturer’s protocol, and quantified using Qubit fluorometry (Invitrogen). The relative abundance of reportable 16S rRNA gene amplicons was then plotted against each fraction’s CsCl buoyant densities. [13C] PAH fractions with

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overlapping densities with either [12C] PAH or unamended fractions were considered enriched in

“light” 12C-labeled DNA. In contrast, “heavy” fractions exclusively detected in 13C-labeled enrichments were considered as candidates for having incorporated the isotopic label into their genetic material.

16S rRNA gene amplicons of the selected light and heavy fractions were pooled into separate volumes and processed for a second round of PCR amplification and purification

(Chapter 3.4.2). The final amplicons were normalized to a concentration of 2 nM and pooled in equal volumes (5 µL) generating a 16S rRNA amplicon library. High-throughput sequencing of the library was completed using 300–nt paired-end sequencing using a benchtop sequencer and the MiSeq Reagent Kit v3 (Illumina). The 2 nM amplicon library accounted for 95% of the total

DNA sequenced, with the remaining 5% occupied by an equal concentration of a sequencing control library (phiX Control v3; Illumina). The lane averaged a cluster density of 1216 K/mm2, a cluster performance of 85.83%, and an average alignment of 5.66%. Details describing 16S rRNA gene sequencing analysis are available in Section 3.4.4.1.

6.2.4 Metagenomic sequencing, binning and genome annotation

Following 16S rRNA gene analysis, we detected a minor enrichment of an unclassified

Clostridiales in pooled 13C “heavy” fractions of NDC after two months of incubation. In order to deduce whether this phylotype was a PAH degrader, the sample was processed for metagenomic sequencing. Briefly, 1 ng of 13C-labeled DNA was used to prepare a metagenomic sequencing library using the Nextera XT DNA Library Prep Kit (Illumina). Library quality was assessed using a Bioanalyzer High Sensitivity Chip (Agilent Technologies) and quantified using the Qubit dsDNA HS Assay (Invitrogen). The library was then sequenced using MiSeq technology

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(Illumina), obtaining a total of 12.85 million reads. Raw reads were processed with BBmap

(http://jgi.doe.gov/data-and-tools/bbtools/); phiX contaminants, residual adapters and low-quality ends were trimmed and removed with bbduk.sh set to the following parameters: k = 23, ktrim = r, kmin = 11, trimq = 20. Bulk assembly of the processed reads was performed using SPAdes v3.9.1 (Bankevich et al. 2012). The resulting scaffolds were analyzed and binned using

MetaBAT v0.32.4 under default parameters (Kang et al. 2015), recovering a total of 10 draft genomes. Each bin was then queried by BLASTN against the NCBI non-redundant database to validate functional identity and to provide taxonomic information. The BLASTN outputs were processed with MEtaGenome ANalyzer (MEGAN v.5.11.3) for taxonomic assignment (Huson et al. 2007), and matched to the dominant phylogenies appearing in the respective 16S rRNA microbial community analysis. We also used MEGAN to determine if any bins needed to be merged or reanalyzed—neither was required. Annotation of the complete metagenome and draft genomes was conducted by submission to the Integrated Microbial Genomes & Metagenomics

(IMG/M) system of the Joint Genome Institute (JGI) website (http://www.jgi.doe.gov/;

Markowitz et al. 2012).

6.2.5 Identification of putative naphthalene-degrading genes

The assembled NDC metagenome had over 100,000 genes, and each draft genome contained an average of 3136 genes. Gene pathways were identified using the KEGG pathways database (Kanehisa and Goto 2000); pathway completeness was judged by manual inspection to determine whether some or all pathway-specific enzymes were present.

Nearly all described KEGG pathways for PAH biodegradation are aerobic; matches to anaerobic genes were often single hits and were therefore not significant. To refine our search for

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scaffolds containing putative anaerobic naphthalene degradation gene sequences, a curated database was prepared for genes encoding predicted anaerobic naphthalene degradation enzymes. The database was constructed by retrieving protein sequences from the NCBI Gene database using GI numbers and gene names. The proposed naphthalene carboxylase gene cluster within the metagenomes of the Desulfobacterium strains N47 and NaphS2 were searched for

(DiDonato et al. 2010; Bergmann et al. 2011a), as were the benzene carboxylase gene clusters of the iron-reducing culture BF (Abu Laban et al. 2010) and a denitrifying benzene-degrading enrichment culture (Luo et al. 2014). Protein sequences predicted to encode for 2-naphthoyl CoA reductase (ncr) and the ring cleavage pathway of tetralin (thn) in the genomes of strains N47 and

NaphS2 were also sought, as well as fumarate addition genes belonging to nms (encoding naphthylmethylsuccinate synthase) and bns (encoding naphthylmethylsuccinate-CoA transferase) operons.

Gene detection in the prepared draft genomes with functional conserved homology to proteins compiled in the curated databases was conducted in BLASTP through the Integrated

Microbial Genomes website (minimum e-value cut-off = 1e-05). We manually identified scaffolds containing three or more orthologous genes to the curated database or encoding protein sequences orthologous to genes of interest, and manually assessed conserved gene synteny to neighbourhood regions of reference gene clusters in anaerobic PAH-degrading cultures.

6.2.6 Metabolite analysis

To help elucidate the mechanism of methanogenic naphthalene activation, we extracted and analyzed the supernatants from all sacrificed SIP incubations for putative 12C- and 13C- labeled metabolites by GC-MS (procedure summarized in Chapter 3.3.3).

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6.3 Results and Discussion

6.3.1 Methanogenic activity from PAH degradation

To evaluate the extent of PAH degradation and to predict [13C] incorporation, enrichment cultures were monitored weekly for methane accumulation over the course of three months.

However, with the exception of the Oil Sands-inoculated microcosms, we did not observe significant methane production in any enrichment cultures relative to their corresponding PAH- free (unamended) controls (Figure 6-1). Methane levels rarely exceeded 4 µmol, inferring that

PAH degradation had not yet reached methanogenesis. However, this does not exempt the possibility that early PAH degradation had occurred, wherein key fermentative (and syntrophic) bacteria incorporated the 12C– and 13C-carbon into their genetic material. Enhanced methane production was observed in the Oil Sands replicates amended with naphthalene or phenanthrene, producing an average of 77 ± 9 µmol CH4 and 96 ± 19 µmol CH4, respectively, after three months of incubation (Figure 6-2 D). Using stoichiometric predictions, it is estimated that up to

234 µmol and 101 µmol of methane can be produced from the complete methanogenic metabolism of 4 mg of naphthalene (eqn 3) and phenanthrene (eqn 4), respectively (Dolfing et al.

2009);

퐶10퐻8 + 8 퐻2푂 → 4 퐶푂2 + 6 퐶퐻4

푘퐽 ∆퐺°′ = −190 푛푎푝ℎ푡ℎ푎푙푒푛푒 (eqn 3) 푚표푙

퐶14퐻10 + 11.5 퐻2푂 → 5.75 퐶푂2 + 8.25 퐶퐻4

푘퐽 ∆퐺°′ = −177 푝ℎ푒푛푎푛푡ℎ푟푒푛푒 (eqn 4) 푚표푙

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After subtracting methane production from the PAH-free controls, methane production in the naphthalene and phenanthrene replicates equated to 12 µmol and 30 µmol, respectively, and a theoretical substrate loss of 0.2 mg (2 µmol) naphthalene and 0.7 mg (3.6 µmol) phenanthrene.

We predict that there may have been an additional 0.03 – 0.21 mg PAH loss (∼15 – 30%) in which carbon was incorporated into biomass and/or transformed into metabolic by-products, as observed in other methanogenic hydrocarbon-degrading studies (Zengler et al. 1999; Fowler et al. 2012; Abu Laban et al. 2015), though the actual PAH loss was not measured. Based on theoretical stoichiometric calculations, we estimate that 13C-carbon incorporation in the enrichment cultures reached a maximum of 5.25% atom%. Previous reports have suggested that the critical level of 13C-DNA enrichment measurable following density gradient fractionation is

≥ 20 atom% (Neufeld et al. 2007a; Lueders 2015), though a recent study by Lian et al. (2016) revised this value to be ~1.30 atom% 13C. Assuming this is true, our data suggests that 13C- carbon incorporation may have exceeded this threshold.

Putative anaerobic naphthalene and phenanthrene metabolites (such as 2-naphthoic acid,

2-naphthylmethylsuccinic acid, and phenanthrene carboxylic acid) were sought in extracted supernatants from harvested cells at all time points, but were not detected in any of the incubations. The difficulty of detecting anaerobic PAH metabolites (by GC-MS) is a reoccurring problem (e.g., as also reported in Chapter 5), where we could only detect tentative downstream metabolites of methanogenic phenanthrene utilization by PHDC (Figure B-2), and in other physiological studies of methanogenic PAH biodegradation (Berdugo-Clavijo et al. 2012;

Berdugo-Clavijo 2015). For example, Berdugo-Clavijo (2015) performed a series of labeled substrate experiments (using [13C] bicarbonate-buffered growth medium or deuterium-labeled 2-

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methylnaphthalene) but never detected evidence of a labeled product. Given that only limited culture volumes (10 mL) were available for chemical analysis, there are presumably insufficient concentrations of (putative) metabolites that can be resolved by low-resolution GC-MS technology. In future investigations, extracting larger culture volumes and/or using more sophisticated MS tools would allow for higher resolution of putative anaerobic PAH metabolites.

For example, use of a liquid chromatograph coupled with a tandem MS operated in the electrospray ion mode (LC-ESI-MS) or with a quadrupole time-of-time mass spectrometer (LC-

ESI-Q-TOF-MS) can achieve detection limits of 0.2 µg/L (Alumbaugh et al. 2004), while samples pre-concentrated using solid phase extraction allowed for the detection of metabolite concentrations one order of magnitude less (~ 0.01 µg/mL). The use of Q-TOF-MS also allows for exact mass determination and has been particularly useful when searching for higher molecular weight components such as anaerobic PAH metabolites (Jobelius et al. 2011).

T1 T2 T3 T1 T2 T3 T1 T2 T3 T3 NDC Naph - 93.1 23.9 3.5 227 15.4 26.6 - 2MNDC Naph - - - - - 10.7 - - 26DMNDC Phen - - - - - 4.1 - - PHDC Phen 484 663 103 905 519 133 111 - 18PW Naph - - - 6.3 - - 8.7 - Phen ------Oil Sands Naph - 23.9 6.4 - 17.4 10.4 - 20.4 32.6 - Phen - 9.2 69.1 - 230 109 -

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6.3.2 Detection of 13C-enriched DNA

During incubation, one set of replicates from each culture was sacrificed monthly for molecular analysis. Samples were subjected to genomic DNA extraction, quantification, density gradient fractionation, and PCR analysis to determine the relative abundance of 16S rRNA genes across a CsCl buoyant density. From our analysis, though, more than half of the extracted DNA samples were below detectable (quantifiable) limits (< 0.5 ng DNA) and consequently could not be quantified (Table 6-1). This became increasingly problematic following DNA density gradient fractionation, where the limited genetic material was separated across multiple fractions and could not be quantified with confidence using conventional qPCR analysis (Sun et al. 2014; Abu

Laban et al. 2015). We therefore chose to assess fractions for the presence of amplifiable 16S rRNA gene fragments using PCR as a substitute for quantitative analysis.

In all, we were able to detect 16S rRNA gene amplicons in 62 of a possible 72 extracted

DNA samples after fractionation. Samples wherein no amplification was observed belonged to

18PW, which was the only experimental inoculum tested not previously enriched on PAHs.

Although most sampling points and cultures did not yield a detectable heavy fraction, four instances were identified that had potential 13C incorporation by correlation with increased DNA density and relative 16S rRNA gene abundance (Figure 6-2). NDC, which had been previously enriched on naphthalene for ~5 years, had the greatest increase in DNA density (~0.02 g/mL) after two months of incubation relative to 12C and substrate-unamended controls (Figure 6-2 A).

In contrast, the Oil Sands cultures, which were exposed to mixed bituminous material but not previously challenged on specific PAHs, displayed minimal increases in DNA density after three months of incubation (Figure 6-2 C and D). Finally, a single heavy fraction was identified for

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PHDC after 2 months of incubation, though a shift in DNA density for most of the microbial community was not observed (Figure 6-2 B). We suspect that experimental incubations inoculated with 2MNDC and 26DMNDC were unsuccessful because they were not previously enriched on the specific hydrocarbon substrates evaluated. Other reports have postulated that the microorganisms responsible for naphthalene and phenanthrene metabolism under methanogenic conditions are distinct from those involved in methyl-substituted PAH degradation (Berdugo-

Clavijo et al. 2012; Jiménez et al. 2016), but this remains to be confirmed.

6.3.3 Key PAH degraders in methanogenic cultures

Given the limitations described above, selected light and heavy fractions with detectable

16S rRNA gene fragments were pooled separately and processed for microbial community sequencing by Illumina MiSeq technology. We evaluated each microbial community profile for

OTUs that were heavily enriched (> 50%) in 13C heavy fractions relative to 13C light fractions.

For added confidence, we compared the 13C-enriched OTUs to organisms present in the 12C light fractions, as well as ensuring that the relative abundance of 13C-enriched OTUs has decreased (or was absent) in the substrate-unamended controls. Assembly and phylogenetic classification of the most abundant bacterial and archaeal phylogenies (>0.1% total quality reads) were executed in QIIME against the SILVA SSU database (version 119).

Members of the Deltaproteobacteria and/or Firmicutes dominated the composition of quality sequenced reads in each set of cultures sequenced (Figure 6-3). However, only in the case of NDC was there a discernable shift in microbial community composition in the 12C and 13C- heavy fractions relative to 13C-light and unamended controls (Figure 6-3 A). Here, two key taxa affiliated with Geobacter and unclassified Clostridiaceae were the most abundant OTUs

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detected in the total quality reads of 13C “heavy” fractions, comprising 69.10% and 14.51%, respectively. However, Geobacter was also the prominent taxon detected in the corresponding

13C-light control (containing 12C-labeled DNA), comprising 75.89% of total quality reads, as was

Clostridiaceae in the unamended control (35.50%). Though several aromatic hydrocarbon- degrading Geobacter strains have been characterized under iron-reducing conditions (e.g. G. metallireducens, G. toluenoxydans; Geobacter strain Ben; Kunapuli et al. 2010; Zhang et al.

2012c; Zhang et al. 2013), few studies have enriched members of this genus under methanogenic conditions (Krüger et al. 2008; Beckmann et al. 2011). Further, this lineage has never been detected in abundance (< 0.7% total reads) in active methanogenic PAH-degrading enrichment cultures (for PHDC, see Figure 5-6; Berdugo-Clavijo et al. 2012; Berdugo-Clavijo 2015).

Previous time-resolved RNA-SIP and reverse-transcription polymerase chain reaction (RT-PCR) assays of a methanogenic toluene-degrading enrichment culture (Fowler et al., 2014) also failed to detect significant activity of an organism related to Geobacter sp. in the presence of toluene, despite its relatively high abundance as determined by 16S rRNA gene sequencing (up to

8.13%). At this time, it is unclear why Geobacter was enriched in the presence of PAHs, despite not appearing to have assimilated the substrate.

In contrast, members of the Clostridiaceae family such as Desulfosporosinus have been experimentally verified by SIP approaches to initiate methanogenic monoaromatic hydrocarbon activation (e.g. Fowler et al. 2014; Sun et al. 2014; Abu Laban et al. 2015), while other microorganisms (e.g. Clostridium) are predicted to participate in secondary metabolic pathways under methanogenic (Wawrik et al. 2014; Fowler et al. 2014; Fowler et al. 2016) and sulfate- reducing conditions (Galushko et al. 1999; Musat et al. 2009; Kümmel et al. 2015). A taxonomic lineage relating to Clostridium sp. was significantly enriched in 2MNDC and its derivatives

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(26DMNDC and NDC), comprising up to 43.58% of reads during their initial culture establishment. This may also explain why the unclassified Clostridiaceae comprised one-third of reads in the unamended control, as the culture was not diluted upon transfer and may have persisted over the incubation period. As we detected a 5× enrichment of Clostridium in putative

13C-labeled fractions, we hypothesize that this phylotype participates in methanogenic naphthalene degradation.

Two minor constituents of NDC (Desulfovibrio, 0.43% Methanoculleus, 0.72%) may have also been enriched with heavy isotope after two months of incubation, though their enrichment is difficult to confirm here by SIP analysis alone. Members of Desulfovibrio sp. appear to be ubiquitous constituents of a variety of strictly anaerobic oil-impacted environments such as oil reservoirs and enrichment cultures derived from contaminated sites and oil production waters (Grabowski et al. 2005; Fowler et al. 2012; Mbadinga et al. 2012; Berdugo-Clavijo and

Gieg 2014; Chen et al. 2017), and may participate in syntrophic fatty acid metabolism and/or the consumption of hydrogen in the absence of sulfate (Walker et al. 2009; Plugge et al. 2010;

Meyer et al. 2013a). Hydrogenotrophic Methanoculleus have long been known to partner in syntrophic associations with fermenters and/or syntrophic bacteria to transform hydrocarbons to methane (Gieg et al. 2014; Jiménez et al. 2016), thus this observation was unsurprising.

6.3.4 Other putative PAH degraders detected by DNA-SIP analysis

Other bacteria that may have incorporated the 13C-carbon into their genetic material include an unclassified Desulfuromonadales (5.28%; Oil Sands + phenanthrene), an unclassified

Actinobacteria (0.64%; Oil Sands + phenanthrene), and an unclassified Spirochaetaceae (1.37%;

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Figure 5-3. Composition of the 10 most abundant taxa per culture in selected SIP fractions of (A) NDC + naphthalene after 2 months of incubation; (B) PHDC + phenanthrene, 2 months; (C) Oil Sands + naphthalene, 3 months; and (D) Oil Sands + phenanthrene, 3 months. Taxon abundance is expressed as percentage of quality 16S rRNA reads, with the lowest confident taxonomic level shown. Phylogenies belonging to Euryarchaeota are shown in blue; Firmicutes in green and Deltaproteobacteria in red/pink.

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PHDC + phenanthrene). Members of the Desulfobacteraceae family, which includes sulfidogenic strains N47 and NaphS2, have been repeatedly identified during anaerobic PAH biodegradation under sulfate-reducing conditions (e.g. Galushko et al. 1999; Musat et al. 2009;

Selesi et al. 2010; DiDonato et al. 2010; Bergmann et al. 2011a; Kümmel et al. 2015), as revealed by 16S rRNA gene sequencing and metaproteomic analysis (without SIP). However, we did not obtain sufficient taxonomic resolution to determine whether the Desulfuromonadales taxon in question belonged to Desulfobacteraceae or to another family (e.g. Geobacteraceae).

Members of the Actinobacteria have been reported to aerobically degrade hydrocarbons in many soil environments (Hamamura et al. 2006), and were identified by SIP to participate in benzene degradation in an iron(III)-reducing enrichment culture (Kunapuli et al. 2007). Members of the

Spirochaetaceae family can grow chemoheterotrophically under anoxic conditions using carbohydrates and amino acids as carbon and energy sources (Paster 2011). Recently, a phylotype belonging to the Spirochaetaceae was identified in a stable toluene-degrading sulfate- reducing consortium (Müller et al. 2009) and in a handful of sulfidogenic naphthalene-degrading enrichments cultures including N47 (Selesi et al. 2010; Kümmel et al. 2015), suggesting that members of this family serve an unresolved function in anaerobic aromatic hydrocarbon degradation. Unfortunately, we cannot conclusively confirm their participation in methanogenic

PAH degradation due to their limited enrichment in our cultures. Owing to the slow growth rates of anaerobic PAH degraders, a longer incubation period may have helped improved assimilation of [13C] PAH by corresponding hydrocarbon degraders, at the risk of further labeling secondary degraders.

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6.3.5 Genomic insights of anaerobic naphthalene metabolism in NDC

6.3.5.1 Metagenome overview and preparation of draft genomes

Whole (meta)genome shotgun sequencing of the pooled 13C-labeled NDC fractions was performed to produce a preliminary metagenome from which 10 supporting draft genomes were constructed from binned contigs (Table 6-2). The full metagenome consisted of an estimated

51212 scaffolds encoding 103278 protein-coding genes, of which roughly one-third were not orthologous to known proteins. Unique genes are found in almost every novel microbial

(meta)genome; these could be either due to incorrect gene prediction or are genes responsible for specific adaptations of bacteria to their evolutionary niches (Bergmann et al. 2011a). To assess this, we compared the average nucleotide identity (ANI) and alignment fraction (AF) of each draft genome to closely related cultured representatives and to known anaerobic aromatic hydrocarbon-degrading organisms (Konstantinidis and Tiedje 2005; Konstantinidis et al. 2006).

We found that Clostridium sp. Bin 1 shared over 87% genome similarity to Youngiibacter fragilis across 54% of its predicted 5424 protein-encoding genes (Table C-1). This organism is a strictly anaerobic, Gram-negative member of the Clostridiaceae family isolated from a natural gas-producing coal bed system (Lawson et al. 2014). Genomic sequencing of Y. fragilis conducted by Wawrik et al. (2014), however, revealed no evidence of anaerobic hydrocarbon activation pathways; the authors suggested that the microbe may instead participate in secondary fermentation of carbon in the subsurface. Similarly, Clostridium sp. Bin 1 shared little-to-no genomic similarity (≤ 6%) to known anaerobic hydrocarbon-degrading isolates or enrichment culture strains (Table C-2). We remark here that there no known isolates of anaerobic hydrocarbon-degrading Firmicutes (Widdel et al. 2010; Gieg and Toth 2017a) and there are few

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Table 6-2. Summary of draft genomes assembled from 13C-labeled NDC + naphthalene after two months of incubation. Draft IMG Genome Gene Protein Scaffolds Scaffolds (meta)genome Genome ID size (bp) count coding containing containing genes ≥1 PAH- ≥3 PAH- with degrading degrading COGs gene gene (%) orthologs orthologs 13C-enriched DNA 3300013290 68705674 104254 64.54 804 73 metagenome of NDC Clostridium sp. 68.31 260 28 2724679696 5438132 5424 Bin 1 Geobacter sp. 56.80 90 9 2724679697 4390079 4104 Bin 1 Geobacter sp. 62.15 79 9 2724679723 3876684 3546 Bin 2 Geobacter sp. 65.58 58 7 2724679724 2526538 2519 Bin 3 Unclassified 60.81 88 2 Rhodospirillales 2724679720 3473168 3651 Bin 1 Desulfovibrio 65.12 71 7 2724679721 3088242 2959 sp. Bin 1 Anaerolinea sp. 56.87 52 4 2724679725 2333788 2249 Bin 1 Anaerolinea sp. 57.50 34 4 2724679726 2271625 2153 Bin 2 Sphaerochaeta 51.74 41 0 2724679727 1750954 1956 sp. Bin 1 Methanosaeta 58.26 31 3 2724679722 2683322 2798 sp. Bin 1

available draft genomes for members of this phylum retrieved from methanogenic hydrocarbon- degrading enrichment cultures for comparison (Tan et al. 2015a). Nevertheless, we considered this to be a positive result, inferring that Clostridium sp. Bin 1 may contain a multitude of genes unique to methanogenic naphthalene degradation. Other prepared draft genomes shared 8 – 43%

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alignment frequency to their closest cultured representative and up to 39% alignment frequency with known anaerobic hydrocarbon-degrading isolates and enrichment strains (Table C-2).

6.3.5.2 Detection of protein-encoding genes tentatively involved in anaerobic naphthalene degradation

In the prepared draft genomes, we sought to identify scaffolds containing orthologous gene sequences to gene clusters previously shown to be involved in anaerobic naphthalene biodegradation (DiDonato et al. 2010; Bergmann et al. 2011b; Bergmann et al. 2011a; Eberlein et al. 2013b; Eberlein et al. 2013a; Estelmann et al. 2015). Using a curated database of known protein-encoding gene sequences, a total of 804 genes of interest (with a minimum e-value cutoff = 1e-05) were detected across 453 scaffolds in the NDC metagenome; this value was reduced by roughly 85% after removing contigs with less than three orthologues (Table 6-2). The remaining candidate scaffolds were manually assessed for functional and structural consistency to known naphthalene-degrading strains N47 and NaphS2 (DiDonato et al. 2010; Bergmann et al. 2011a), in addition to other reference organisms.

Twenty-eight of the remaining 73 scaffolds of interest belonged to Clostridium sp. Bin 1

(Table 6-2). All other binned organisms contained fewer than 10 scaffolds of interest, some of which contained genes encoding predicted Fe-containing hydrogenases that may be important for syntrophic interactions in NDC (Sieber et al. 2012). However, as our main objective was to search for genes involved in ring activation and cleavage pathways, we did not interrogate the genomes of these organisms any further. After manually assessing Clostridium sp. Bin 1 scaffolds for functional and structural consistency to naphthalene-degrading gene clusters, we were unable to detect a evidence of genes orthologous to known gene clusters encoding

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Gene ID Protein annotation Length NaphS2 ortholog Locus % Identity Best BLASTP ortholog Accession No. % identity (aa) (% similarity) (% similarity)

2727804033 Hypothetical protein 60 N/A hypothetical protein [Clostridiales WP_024723634 43 (71) bacterium VE202-03]

2727804034 Crotonobetainyl- 412 CoA-transferase family III protein NPH_4605 31 (50) Formyl-coenzyme A transferase SCJ80195 55 (74) CoA:carnitine CoA- NPH_6726 24 (46) [uncultured Clostridium sp.] transferase CaiB NPH_5274 27 (44) 2727804035 acetyl-CoA C- 387 Acetyl-CoA C-acyltransferase NPH_3581 43 (61) MULTISPECIES: acetyl-CoA WP_074043744 51 (69) acetyltransferase NPH_6994 43 (62) acetyltransferase [Geobacillus] NPH_6993 38 (62) NPH_5273 38 (55) 2727804036 3-hydroxybutyryl- 288 3-hydroxybutyryl-CoA NPH_5812 38 (58) 3-hydroxyacyl-CoA KKM10089 53 (71) CoA dehydrogenase dehydrogenase NPH_5906 40 (56) dehydrogenase [Clostridiales NPH_5896 36 (53) bacterium PH28_bin88] NPH_7219 34 (53) 2727804037 H+/gluconate 444 N/A MULTISPECIES: hypothetical WP_007862308 43 (65) symporter protein [Clostridiales] 2727804038 enoyl-[acyl-carrier 315 2-nitropropane dioxygenase NPH_5508 35 (52) 2-nitropropane dioxygenase WP_066237624 52 (70) protein] reductase II NPH_6957 33 (53) [Anaerosporomusa subterranea] 2727804039 Enoyl-CoA 85 3-hydroxybutyryl-CoA NPH_5887 47 (61) MULTISPECIES: 3- WP_007862300 52 (74) hydratase/isomerase dehydratase NPH_5907 40 (56) hydroxybutyryl-CoA dehydratase [Clostridiales] 2727804040 Enoyl-CoA 78 3-hydroxybutyryl-CoA NPH_6695 39 (62) enoyl-CoA hydratase WP_072869855 55 (77) hydratase/isomerase dehydratase NPH_5897 38 (63) [Desulfotomaculum NPH_5898 45 (65) thermosubterraneum] 2727804041 2-nitropropane 321 2-nitropropane dioxygenase NPH_6957 38 (60) nitronate monooxygenase WP_083424018 71 (84) dioxygenase NPH_5508 31 (48) [Clostridium] citroniae] precursor 2727804042 Crotonobetainyl- 409 CoA-transferase family III protein NPH_4605 34 (52) MULTISPECIES: CoA transferase WP_007862305 48 (68) CoA:carnitine CoA- NPH_1868 26 (44) [Clostridiales] transferase CaiB 2727804043 2-(1,2-epoxy-1,2- 262 putative enoyl-CoA hydratase NPH_0885 31 (50) enoyl-CoA hydratase WP_071879306 47 (71) dihydrophenyl)acety NPH_5898 32 (54) [Enterococcus silesiacus] l-CoA isomerase NPH_5897 32 (52) 2727804044 Hypothetical protein 25 N/A ATP-dependent endonuclease OPA11549 72 (77) [Bacillus cereus]

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anaerobic naphthalene carboxylation enzymes (e.g. abc, ubiX, ubiD) or fumarate addition mechanisms (nms, bns, ncr). As previously mentioned, this may be due to the phylogenetic dissimilarity of the Clostridium and Deltaprobacterium genera, thus their protein-encoding genes may either share limited orthology or may encode for entirely different mechanisms of PAH activation. This could also explain why neither activation product has ever been detected in metabolite surveys of NDC (Berudgo-Clavijo 2015; this study).

That said, we identified a scaffold of key interest (scaffold 1013) wherein 7 of the 12 predicted proteins shared 44 – 65% sequence similarity to Deltaproteobacterium strain NaphS2

(Figure 6-4; Table 6-3), four of which were also orthologous to genes within the thn operon believed to encode ring reduction and ring cleavage pathways in the (methyl)naphthalene- degrading pathway (Meckenstock et al. 2016). Predicted protein annotations were checked and verified by determining the bidirectional best hits using BLASTP and best hits against IMG’s reference isolates. We also confirmed that the nucleotide sequence of scaffold 1013 contained no orthologous regions in the genome of Y. fragilis, offering our best functional evidence that some proposed anaerobic naphthalene degradation genes are tentatively present in the genetic material of NDC.

Predicted protein annotation of scaffold 1013 contains genes encoding for 3- hydroxybutyryl-CoA dehydrogenase and enoyl-CoA hydratase/isomerase/hydrolase, where their expression has been previously shown to significantly upregulated in proteomic surveys of

Deltaproteobacterium strains N47 and NaphS2 in the presence of naphthalene (DiDonato et al.

2010; Bergmann et al. 2011a; 2011b). Further, orthologous enzymes are known to catalyze the degradation of benzoate via CoA ligation steps and ring cleavage, respectively, in several anaerobic bacteria (Elshahed et al. 2001a; Carmona et al. 2009; Sieber et al. 2012; Boll et al.

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2016). Meckenstock et al. (2016) overviewed a similar ring cleavage pathway for 2-naphthoyl-

CoA degradation following a series of dearomatizing reduction steps. One ring of 2-naphthoyl-

CoA has been shown to undergo a step-wise series of recently characterized ring reduction reactions (Eberlein et al. 2013b; Estelmann et al. 2015), generating the formation of metabolic products such as 5, 6, 7, 8-tetrahydronaphthoyl-CoA (Figure 6-5). Reactions hypothesized to be catalyzed by enzymes including 3-hydroxybutyryl-CoA dehydrogenase and enoyl-CoA hydratase/isomerase/ hydrolase would then facilitate a series of additional ring reductions reactions, ultimately leading to cleavage of the first ring structure (Figure 6-5). Presumably, this would be followed by a second ring cleavage pathway, of which pimeloyl-CoA is proposed as a metabolic product (Figure 6-5). A hypothetical acyl-CoA dehydrogenase is proposed to be involved in this pathway, of which an orthologous protein-encoding sequence is present in scaffold 1013 (Figure 6-5; Meckenstock et al. 2016). The tentatively identified enoyl-[acyl- carrier protein] reductase and 2-(1, 2-epoxy-1, 2-dihydrophenyl)acetyl-CoA may also participate in unknown degradation steps.

6.3.6 Limitations and overall findings

Stable isotope probing (SIP) is an established cultivation-independent approach used to identify microorganisms directly involved in the metabolism of a given substrate enriched with stable isotope (Neufeld et al. 2007b; Neufeld et al. 2007a). The primary advantage of SIP is that it provides unequivocal evidence of substrate degradation by tracing the assimilation of carbon or other atoms using with stable isotopes. In particular, DNA, RNA and proteins are biomarkers of considerable taxonomic value, allowing for the establishment of fundamental links between structure and function within microbial communities. This key advantage has made SIP a

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Figure 6-4. Organization of genes in scaffold 1013 of Clostridium sp. Bin 1 tentatively encoding enzymes involved in methanogenic naphthalene degradation. Genes marked with blue bars contain ≥ 50% sequence similarity to enzymes upregulated in the presence of naphthalene in Desulfobacterium strains N47 and NaphS2 (Didonato et al. 2010; Bergmann et al. 2011a). Gene nomenclature: 1. hypothetical protein; 2. crotonobetainyl- CoA:carnitine-CoA transferase; 3. acetyl-CoA C-acetyltransferase; 4. 3-hydroxybutyryl- CoA dehydrogenase; 5. H+/gluconate symporter; 6. enoyl-[acyl-carrier protein] reductase II; 7. enoyl-CoA hydratase/isomerase/hydrolase; 8. enoyl-CoA hydratase/isomerase/ hydrolase; 9. 2-nitropropane dioxygenase precursor; 10. crotonobetainyl-CoA:carnitine- CoA transferase; 11. 2-(1, 2-epoxy-1, 2-dihydrophenyl)acetyl-CoA isomerase; 12. hypothetical protein.

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popular methodology over the past decade (Uhlik et al. 2013), and has more recently been adopted for monitoring hydrocarbon degradation in mixed communities (Vogt et al. 2016).

A problem arises, particularly for tracking nucleic acids, when substrate incorporation and incubation time are insufficient, generating poorly labeled biomarker molecules that are near indistinguishable from a background of (relatively abundant) unlabeled molecules. We found this to be the case for most of our methanogenic PAH-degrading cultures, wherein 13C heavy fractions of 16S rRNA gene fragments yielded minimal to no shift in DNA density relative to 13C light fractions (Figure 6-2). It also made it difficult to confirm the enrichment of key organisms enriched with 13C-DNA within 13C-labeled heavy fractions (Figure 6-3). The quantification of label incorporation in nucleic acid-SIP (and protein-SIP) can be challenging because it relies on indirect methods based on the separation of ‘light’ and ‘heavy’ nucleic acids by density gradient centrifugation. This determination by labeling via buoyant densities has only a limited resolution, with detection limits mainly depending on technical gradient fractionation, and is estimated to be

~20 atom% (Neufeld et al. 2007a; Lueders 2015; Vogt et al. 2016). Had we prolonged the incubation period and awaited enhanced methane production in each set of microcosms, we would have stood a better chance of detecting 13C-labeled DNA following density gradient fractionation (though at the risk of labeling peripheral community members). During the experimental design of this study, we had accounted for this by preparing microcosms with undiluted aliquots (10 mL) of active culture, and this appears to still have just been sufficient.

A second problem pertaining to DNA-SIP arises when low concentrations of genomic

DNA (< 5 µg) are used for density gradient fractionation. For one, sufficient DNA is required for proper banding efficiency of labeled and unlabeled nucleic acid species (Neufeld et al. 2007a).

Too little DNA does not sufficiently diffuse across the CsCl density gradient and consequently

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creates a DNA ‘smear’ instead of a clear banding pattern. We accounted for this by increasing ultracentrifugation conditions to ∼300,000 × gav for a total of 65 h, which we deemed more than sufficient to promote DNA diffusion. By comparison, Abu Laban et al. (2015) used roughly half the G-force to achieve DNA band separation using 1 – 4 µg DNA extracted from toluene- degrading enrichment cultures under sulfidic and methanogenic conditions. While this seems to have been partially successful for NDC, we were unable to detect clear evidence of 13C-DNA enrichment in other cultures evaluated.

The third obstacle we faced in this SIP study was detecting and quantifying low amounts of DNA (< 1 µg) after the fractionation step. In most cases, the extracted genomic DNA was already unquantifiable (below detectable limits, < 0.5 ng; Table 6-1) and could not be quantified by conventional qPCR analysis (Abu Laban et al., 2015). This required us to use PCR for the

16S rRNA gene as a semi-qualitative measurement of DNA concentrations across each SIP fraction. We defined ‘heavy’ fractions as having quantifiable 16S rRNA gene fragments in 13C replicates, but not in 12C or unamended controls. We achieved the most successful fractionation results when > 0.1 µg DNA was extracted from SIP incubations, thus this quantity is proposed to be the lower limit of what can be successfully fractionated using DNA-SIP.

A number of SIP methods have been described which differ considerably in terms of sensitivity, precision and requirements (Abraham 2014; Vogt et al. 2016). Most studies to date investigating anaerobic hydrocarbon-degrading microbial communities have been characterized by DNA- or RNA-SIP, probably due to the comparatively ‘low-tech’ approach and much earlier establishment compared to other SIP technologies. However, some of these newer methodologies prove to be particularly useful for identifying PAH degraders. For example, the quantification of label incorporation in other SIP techniques (e.g. phospholipid-derived fatty

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acids (PFLA) or amino acids) offer higher sensitivity (~0.1 atom%; Boschker et al. 1998), and requires roughly 101 – 103 fewer cells than conventional as nucleic acid-based SIP (Neufeld et al.

2007a; Jehmlich et al. 2010; Taubert et al. 2011; Taubert et al. 2012; Lueders 2015). Protein-SIP offers intermediate phylogenetic coverage of targeted proteins contained within the whole proteome, making it a more attractive candidate than PFLA-SIP. An alternative method to SIP known as nanoSIMS analysis allows for the quantification of label incorporation at natural abundance (< 0.1 atom%), but only holds a targeted phylogenetic resolution (Musat et al. 2012).

Indeed, this would be suitable for tracking carbon flow through a bacterial isolate (e.g. NaphS2) or a targeted organism within a heavily enriched consortium (e.g. N47), but would serve to be less practical for assessing substrate degradation through increasingly complex microbial communities. We propose that these technologies should be considered for future investigations of NDC and other methanogenic PAH-degrading communities, as they may allow for higher resolution of key degraders and identification of proteins expressed during active substrate metabolism.

In summary, we interrogated multiple established PAH-degrading enrichment cultures or

13 13 PAH-amended methanogenic cultures with C10-naphthalene or C14-phenanthrene in an attempt to evaluate the feasibility of tracking methanogenic PAH degradation using DNA-SIP.

Despite the methodological limitations encountered in this study, we found preliminary functional evidence of anaerobic naphthalene degradation genes encoding for enzymes facilitating ring reduction and cleavage steps of 2-naphthoyl-CoA in a Clostridium phylotype.

Through this project we have confirmed that an optimized DNA-SIP protocol can be coupled with metagenomic sequencing for improved detection of putative hydrocarbon-degrading taxa.

Ultimately, as we continue to scale-up promising methanogenic PAH-degrading enrichment

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cultures (to obtain more biomass), we envision that the approach can be used to assess carbon flow through hydrocarbon-rich environments. This knowledge will help to define the microbiological controls on anoxic hydrocarbon transformations in the Earth’s deep subsurface and at more shallow contaminated sites.

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Preface

Chapter 7 describes time course community and functional dynamics of MHGC produced water-associated consortia in response to enrichment on light oil (°API = 32) or heavy oil (°API

= 16) under methanogenic conditions. Methanogenic activity was routinely monitored using a series of analytical (CH4 production, oil analysis, metabolite analysis) and molecular approaches

(16S rRNA community sequencing, targeted genomic sequencing, quantitative PCR) over 17 months of incubation. Here, we summarize evidence that members of the Desulfotomaculum and

Smithella genera likely catalyze hydrocarbon activation by addition to fumarate, and propose a working model for methanogenic hydrocarbon degradation of alkanes and aromatics in these communities.

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Chapter Seven: Microbial Community Response to Enrichment on Light and Heavy Crude Oils under Simulated Reservoir Conditions

7.1 Introduction

The impact of the deep biosphere on crude oil composition is of interest to the petroleum industry since biodegradation transforms lighter oil components (e.g. saturates and aromatic hydrocarbons) to heavier forms that are of lower quality and are more challenging to recover

(Head et al. 2003; Larter et al. 2008; Head et al. 2014). Methanogenic hydrocarbon degradation is the leading model to explain the widespread occurrence of biodegraded oils and gas formation in oxidant-free reservoirs, with the number of reports detailing the susceptibility of whole crude oil to methanogenic biodegradation surging in recent years (e.g. Townsend et al. 2003; Jones et al. 2008; Feisthauer et al. 2010; Gieg et al. 2010; Siegert et al. 2011; Gray et al. 2011; Tan et al.

2013; Aitken et al. 2013; Sherry et al. 2013; Berdugo-Clavijo and Gieg 2014; Sherry et al. 2014;

Cai et al. 2015; Xia et al. 2016). Linear alkanes (e.g. Zengler et al. 1999; Anderson and Lovley

2000; Gray et al. 2011; Tan et al. 2015b) and alkyl-substituted aromatics (e.g. Grbić-Galić and

Vogel 1987; Edwards and Grbić-Galić 1994; Beller and Edwards 2000; Townsend et al. 2003;

Washer and Edwards 2007; Fowler et al. 2012; 2014) are the most readily biodegraded hydrocarbons in crude oil and in other fuel mixtures under anoxic conditions. This observation helps to explain the higher methanogenic yields commonly observed in cultures enriched on lighter crude oils as compared to other complex hydrocarbon substrates (Jiménez et al. 2016), as light crude oils contain a higher proportion of these hydrocarbon components.

Studies in the past two decades have demonstrated fumarate addition as a possible anaerobic activation mechanism for alkanes and alkyl-substituted aromatics (e.g. Beller and

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Spormann 1997; Annweiler et al. 2000; Kropp et al. 2000; Beller and Edwards 2000; Rabus et al.

2001; Kniemeyer et al. 2003; Rios-Hernandez et al. 2003; Wilkes et al. 2003; Cravo-Laureau et al. 2005; Davidova et al. 2005). Although fumarate addition genes (e.g. ass/mas for alkanes or bss for toluene) have been identified in methanogenic oil-degrading enrichment cultures (e.g.

Zhou et al. 2012; Tan et al. 2013; Aitken et al. 2013; Berdugo-Clavijo and Gieg 2014) and in oil- containing environments (e.g. Callaghan et al. 2010; von Netzer et al. 2013; An et al. 2014;

Stagars et al. 2016), their importance to the biotransformation of crude oil over geological time is unknown. However, some research has begun to assess key mechanisms of hydrocarbon biodegradation in crude oil systems by combining metabolite profiling and targeted functional gene analysis approaches. In one example, Aitken et al. (2013) performed a 686-day time-course experiment comparing the degradation of crude oil alkanes under sulfate-reducing and methanogenic conditions. While the authors detected an accumulation of (1-methylalkyl)- succinates over time in sulfate-reducing cultures, corresponding with an increase in assA gene abundance, no such evidence was observed in the methanogenic replicates. This led Aitken et al.

(2013) to postulate that an alternate pathway may be responsible for alkane activation under methanogenic conditions; a similar proposal was made for a denitrifying n-hexadecane- degrading enrichment culture (Callaghan et al. 2009). In contrast, Bian et al. (2015) obtained extensive metabolic and functional evidence of fumarate addition to alkanes from production fluids collected from three methanogenic oil fields, though assA gene abundance was not determined. Other putative activation mechanisms may include carboxylation, hydroxylation, or methylation, all of which have been reported to occur under other electron-accepting conditions

(reviewed in Foght 2008; Widdel et al. 2010).

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According to An et al. (2013), putative anaerobic hydrocarbon degraders in oil systems are found primarily in members of the Proteobacteria, Firmicutes and Actinobacteria; the first being the most well characterized. Among the Deltaproteobacteria, Smithella, Syntrophus and other related genera belonging to the Syntrophaceae are often observed in methanogenic microbial communities from hydrocarbon-bearing systems (e.g. Shimizu et al. 2007; Siddique et al. 2011; Cheng et al. 2013; Brown et al. 2013; Johnson et al. 2015) and are frequently enriched in methanogenic cultures (reviewed by Jiménez et al. 2016). Recently, Gründger et al. (2015) reported the proliferation of a Smithella sp. in parallel alkane degradation and methane production in oil-amended cultures enriched from coal-bearing sediments. Alkylsuccinate synthase genes (assA) assigned to Smithella spp. (or related species) are also being recovered from an increasing number of environments and enrichment cultures (e.g. Tan et al. 2015a;

Oberding 2016; Wawrik et al. 2016), inferring their importance to methanogenic alkane degradation. Firmicutes, specifically belonging to the Clostridiales have also been detected in several oil reservoirs and enrichment cultures (e.g. Mochimaru et al. 2007; Hu et al. 2016;

Jiménez et al. 2016) and are believed to participate in the initial activation of aromatic hydrocarbons (e.g. Fowler et al. 2012; 2014; Sun et al. 2014; Abu Laban et al. 2015; Hu et al.

2016) or to secondary degradation during anaerobic hydrocarbon metabolism (Imachi et al.

2006; Gieg et al. 2010; Kleinsteuber et al. 2012). Genera within the Actinobacteria

(Rhodococcus spp. and Gordonia spp.) may have a specific function in the degradation of cyclic alkanes (Kubota et al. 2008). Recent metagenomic insights into the functional roles of other oil- associated consortia, including several candidate phyla, has suggested that methanogenic hydrocarbon degraders are more diverse than previously known (An et al. 2013; Tan et al.

2015b; Hu et al. 2016; Shelton et al. 2016; Luo et al. 2016).

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Overall, a better understanding of the metabolic processes and key microorganisms involved in methanogenic crude oil degradation is necessary to understand the metabolic processes governing heavy oil formation over geological time. Time course metabolic experiments, such as those conducted by Aitken et al. (2013), can help offer valuable insight into characterizing the microbial metabolisms catalyzing crude oil biodegradation (more so than in single time-point experiments). We sought to take this one step further and evaluate the microbial community dynamics in order to correlate crude oil biodegradation with specific taxa.

In this study, we carried out a 17-month time-course experiment comparing the functional and microbial community response of an oil reservoir produced water consortium to enrichment on light and heavy crude oils. In addition to chemical and functional evidence of methanogenic crude oil biodegradation, we assessed the microbial community structure over time. Reservoir conditions were simulated as much as possible in order to determine whether crude oil degradation was more dependent on the microbial/genetic composition of the consortium, or the composition of the crude oil itself.

7.2 Experimental Procedures

7.2.1 Sampling site description and sample collection

Produced water was obtained from five production wells (PW; 4-PW, 7-PW, 18-PW, 32-

PW, 33-PW; Figure 7-1) in the Medicine Hat Glauconitic C (MHGC) field in the Western

Canadian Sedimentary Basin located in southern Alberta, Canada. This field is a shallow (~1000 m), low-temperature (~30 ℃) glauconitic sandstone reservoir producing approximately 1000 m3/day of heavy oil by water injection containing ~3 mM sulfate (Voordouw et al. 2009;

Voordouw et al., in preparation). This field has also been subjected to a ten-year effort evaluating

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sulfide remediation by nitrate injection; each PW sample collected (May 20, 2015) was from a well actively undergoing nitrate injection (0.17 – 1.24 mM; Voordouw et al. 2009; Agrawal et al.

2012; Voordouw et al., in preparation). Samples were collected in 1-L Nalgene bottles filled to the brim to minimize oxygen ingress during transportation. Upon arrival in the lab, samples were stored in an anaerobic chamber (10% CO2/90% N2) at room temperature. Water chemistry data for each PW sample is available in Table D-1. The PW samples contained 5−10% heavy oil (v/v) with an average °API of 16, which was separated from the production water by centrifugation

(25,000 × g for 20 min) and transferred into a sterile 1-L Schott flask. Both the oil-free produced water and oil samples were at 4 ℃ prior to use. We remark here that the recovered oil was not sterilized before use.

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7.2.2 Establishment of light and heavy oil-degrading enrichment cultures

Oil-free produced water from all five PW samples was combined in equal ratios and 500 mL aliquots were dispensed into sterile modified 1-L serum bottles. Each bottle was outfitted with two Balch tube ports; one near the neck of a 1-L Schott flask and the second near its base, and the neck of the bottle sealed in glass to create an air-tight container (Figure 7-2). This design allowed for routine sampling of the headspace and culture, respectively, without having to tilt microcosms and risk disrupting the oil-water transition zone. Cultures were amended with either a light oil (°API = 32; provided by the PRG at the University of Calgary) or heavy oil in excess

(20 mL), as would be the case in a petroleum reservoir, before sealing microcosms with butyl rubber stoppers and aluminum crimps. Cultures were incubated at MHGC reservoir temperatures

(~30 ℃) under dark and static conditions for 17 months. Note that no supplemental growth medium, reducing agents or other culturing agents were added to either culture so as best to simulate the minimal nutrient availability in petroleum reservoirs. An oil-free control and a sterile control was also prepared in parallel to account for any background production of methane, and were monitored for 12 months. Each culture was routinely monitored for methane production in the microcosm headspaces by GC-FID, as previously described (Fowler et al.

2012; Fowler et al. 2016; Chapter 3.3.1).

7.2.3 Chemical analyses

During the incubation period, subsamples (50 mL) from each crude oil enrichment culture were taken at designated time points (1, 2, 4, 8, 12, and 17 months). Supernatants were acidified with 6M HCl (pH < 2) and extracted for putative hydrocarbon metabolites using three volumes of 25 mL ethyl acetate (Chapter 3.3.3). Following concentration and trimethylsilyl

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Figure 7-2. Image of the light (left) and heavy (right) oil cultures prepared in modified 1-L serum bottles.

(TMS) derivatization steps, samples were separated and analysed by GC-MS (Chapter 3.3.3).

Putative hydrocarbon metabolites from the TMS-derivatized organic extracts were positively identified using MSD ChemStation software (version E.02.02.1431; Agilent Technologies) and by matching GC retention time and mass spectral patterns to authentic standards (Table 7-1). All commercially available standards tested were acquired from Sigma Aldrich (97 – ≥ 99.5% purity). An authentic standard of n-octylsuccinic acid was prepared by base hydrolysis following the procedure outlined by Kropp et al. (2000). Calibration curves of representative TMS- derivatized standards were used to determine the approximate concentrations of hydrocarbon metabolites; TMS-derivatized n-octylsuccinic acid was used to quantify all putative alkylsuccinates. Peak integration was performed on extracted ion chromatograms (M – 15+ fragment ion or m/z 262 for alkylsuccinates) using the following MS signal parameters; initial area reject = 0, initial peak width = 1.000, shoulder detection = off, initial threshold = 12.0.

These parameters are suitable for integration of TMS-derivatized compounds in concentrations as low as 10 nM.

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Oil samples (1 mL) were collected from oil-amended cultures and the sterile control after

17 months of incubation for hydrocarbon analysis. Samples were diluted 1:10 in dichloromethane and analyzed in triplicate by GC-MS with an injector operated in split mode

(50:1) and held at 250 ℃. The oven temperature was held 50 ℃ for 5 min, increased at a rate of

4 ℃/min up to 270 ℃, where it was held for 15 min. Hydrocarbon loss was determined as a function of alkane or aromatic hydrocarbon to pristane or phenanthrene peak area ratios, respectively, as these components naturally present in both crude oils were deemed to be recalcitrant to degradation. Unpaired t-tests were used to determine significance of hydrocarbon loss relative to sterile controls.

7.2.4 Targeted functional gene analysis

From the same subsamples used for hydrocarbon metabolite analysis, cells were harvested by centrifugation at 30,000 × g for 15 min and stored overnight at –80 ℃ in preparation for DNA extraction (Section 7.3.5). Briefly, genomic DNA was extracted using the

FastDNA SPIN Kit for Soils (MP Biomedicals) according to the manufacturer’s procedure. Prior to the final elution centrifuge step, samples (75 µL) were incubated for five minutes at 55 °C to enhance DNA recovery. Extracted genomic DNA was quantified using Qubit fluorometry

(Invitrogen) and normalized to 0.5 ng/µL.

Extracted genomic DNA was probed for the presence of anaerobic hydrocarbon activation genes using a series of established primer sets (Table 7-2). PCR reactions (25 µL) were prepared with 12.5 µL 2x Master Mix (Fermentas), 0.5 µL of each forward primer and corresponding reverse primer (10 µM), and 1 µL of template DNA. Amplicons of expected size were verified on a 1% agarose gel and purified using the QIAquick PCR Purification Kit

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(Qiagen) according to the manufacturer’s procedure. In instances where more than one band was observed, the QIAquick Gel Extraction Kit (Qiagen) was also used to obtain the desired PCR product. Select purified assA and bssA gene amplicons were cloned using a TOPO TA kit

(Thermo Fisher Scientific) according to the manufacturer’s protocol (Chapter 3.5.2). Positive transformants were verified by PCR and sequenced on a ABI 3730XL DNA Analyzer (Eurofins).

Consensus sequences were queried against the NCBI non-redundant nucleotide database using

BLASTn to identify homology to known sequences. Multiple alignments of the amplified sequences and representative sequences covering the same region (400 bp) were generated using the MUSCLE algorithm (Edgar 2004) within the European Bioinformatics Institute multiple sequence alignment tools database. Bootstrapped maximum likelihood trees (500 replicates) were constructed in MEGA7 (Kumar et al. 2016). A DNA consensus tree was constructed using the Tamura–Nei model (Tamura and Nei 1993) at all nucleotide sites, with a total of 536 positions evaluated in the final dataset.

7.2.5 Quantification of fumarate addition genes

Quantitative PCR (qPCR) primers specific for the assA and bssA gene sequences retrieved from the crude oil enrichment cultures were designed using Primer-BLAST (Ye et al.

2012). The binding sites for these primers, presented in Table 7-3, were selected by searching the gene alignments for conserved, distinctive regions common for the major gene clusters. qPCR reactions comprised SsoFast Evagreen Supermix (5 µl), PCR primers (1 µl of 10 pmoles/µl each), RNAse-free water (3 µl), and DNA template (1 µL). qPCR reactions were carried out using a BioRad CFX96 thermocycler as follows; an initial denaturation step (5 min at 94 ℃), up to 40 cycles of 1 min at 94 ℃ and 1 min at the specific primer annealing temperature (see Table

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7-3), and melt curve analysis (65 ℃ to 95 ℃ with an increase of 0.5 ℃ every 5 s). Optimal annealing temperatures were determined by performing a temperature gradient PCR with annealing temperatures in the range of 55–65 ℃. We also evaluated an established qPCR primer set (AssA2fq and AssA2fq, qPCR variants of AssA2f and AssA2r; Table 7-3) and reaction protocol described by Aitken et al. (2013). Statistical analyses used to assess gene abundance enrichment over time were performed using repeated measure one-way ANOVA with the

Greenhouse-Geisser correction. Post-hoc Tukey’s test was performed to assess mean differences between samples taken at different time points.

7.2.6 Microbial community analysis

Illumina sequencing of the V6-V8 region of 16S rRNA gene was carried out to examine and compare the microbial community dynamics in response to light or heavy oil over time.

Methods outlining amplification steps, Illumina sequencing, and read assembly in QIIME are described in Chapters 3.4.2.1 and 3.4.3.1.

7.3 Results

7.3.1 Methanogenic activity on light and heavy crude oil

7.3.1.1 Methane production

Methane production was monitored following establishment of two crude oil-degrading enrichment cultures from a heavy oil reservoir produced water mixture (Figure 7-3). The enrichment prepared with light oil produced near identical amounts of CH4 (1307 µmol) as the heavy oil enrichment (1352 µmol) in uniform rates across the 525-day incubation period (0.14

µmol CH4/day/g of oil vs 0.13 µmol CH4/day/g of oil, respectively). The only deviation in CH4

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Figure 7.3. Methane production from production water-derived incubations enriched on light (squares) and heavy (circles) oil relative to an unamended control (triangles).

production was in the first 60 days of incubation, where an apparent lag phase was observed in the light oil incubation.

7.3.1.2 Putative anaerobic hydrocarbon metabolites

To assess the formation and concentrations of putative anaerobic hydrocarbon metabolites formed over time, beginning from T0, silylated organic extracts from the oil- amended enrichment cultures were subjected to GC-MS analysis at regular time intervals; the corresponding unamended control was also assessed after 12 months of incubation. We identified and quantified various compounds in both oil-amended cultures that were not present in the oil-free control (Table 7-1). The concentration of hydrocarbon metabolites in oil-amended cultures peaked between two and four months of incubation, and included compounds with mass spectral profiles diagnostic of C1-C9 alkane fumarate addition (alkylsuccinates), aromatic acids 160

(e.g. benzoate, toluates and 2-methylnaphthoate), and cyclohexane carboxylate. No fumarate addition products for aromatic hydrocarbons could be detected in either culture at any time point.

Generally, the concentration of metabolites detected in the light oil-amended culture was greater than in the heavy oil-amended culture (Table 7-1). Trace amounts of C1-C4 alkylsuccinates (0.07

– 0.44 µM) were also predominantly detected in the light oil culture (Figure 7-4; Table 7-1).

Interestingly, we identified a total of four peaks in the light oil-amended enrichment culture with

MS fragment ions corresponding to propane or butane fumarate addition products (two each), suggesting that hydrocarbon activation was occurring at both the primary and secondary atom

(Figure 7-4; Kniemeyer et al. 2007). The mass spectral pattern of the putative n-propylsuccinate aligns with a previously published reference standard (Savage et al. 2010), but still requires verification with an authentic standard in our laboratory. Metabolite concentrations plummeted at

T8 and T12, inferring their active degradation the in oil-amended cultures, though select metabolites were again detected near the end of the incubation period (Table 7-1).

7.3.1.3 Oil analysis

Oil samples from each culture were recovered and assessed by GC-MS analysis after 17 months of incubation. Most hydrocarbons analyzed did not decrease in abundance relative to corresponding sterile controls (Figure D-1), with is attributed to adding an excess of oil in each enrichment culture. Nevertheless, statistically significant losses of C7-C8 n-alkanes (47 – 79%; P value ≤ 0.01), cyclohexane (22 – 71%; P value ≤ 0.05), and some monoaromatic hydrocarbons were measured in both cultures (Figure D-1). These results are in agreement with the higher susceptibility of these compounds to microbial attack (Leahy and Colwell 1990) and the corresponding hydrocarbon metabolites detected over time (Table 7-1).

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Table 7-1. Time-resolved quantification of alkane and aromatic hydrocarbon metabolites detected in crude oil-amended cultures. Characteristic ion fragments m/z 262 and (M – 15)+ were selected to probe and integrate TMS-derivatized alkylsuccinates and organic components, respectively. Identification and quantification of metabolites was performed using calibration curves prepared from authentic standards. Colour intensity indicates the relative concentration of each metabolite across both cultures over time. Metabolite Characteristic Metabolite concentration (µM) ion fragment Light Oil Heavy Oil T0 T1 T2 T4 T8 T12 T17 T1 T2 T4 T8 T12 T17 Putative alkylsuccinates from alkanes or cyclic alkanes, signature anaerobic C1 262 0.00 0.00 0.12 0.09 0.00 0.00 0.03 0.00 0.00 0.00 0.00 0.00 0.03 C2 262 0.00 0.00 0.19 0.14 0.00 0.00 0.08 0.00 0.07 0.07 0.00 0.00 0.03 C3 262 0.00 0.00 0.44 0.12 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 n-C3 262 0.00 0.01 0.25 0.09 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 C4 262 0.00 0.00 0.09 0.06 0.00 0.00 0.08 0.00 0.00 0.00 0.00 0.00 0.00 n-C4 262 0.00 0.00 0.18 0.07 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 C5 262 0.00 0.00 0.64 0.49 0.00 0.00 0.26 0.00 0.43 0.29 0.00 0.00 0.04 C5 (w/ 262 unsaturation) 0.00 0.00 1.12 1.08 0.00 0.00 0.81 0.02 1.06 0.85 0.00 0.00 0.16 C6 262 0.00 0.02 1.38 1.45 0.00 0.00 0.83 0.01 1.22 0.99 0.00 0.00 0.42 C6 (w/ 262 unsaturation) 0.00 0.03 1.76 1.75 0.01 0.00 1.58 0.01 1.69 1.39 0.00 0.00 0.35 C7 262 0.00 0.00 0.32 0.36 0.00 0.00 0.18 0.00 0.36 0.27 0.00 0.00 0.11 C7 (w/ 262 unsaturation) 0.00 0.00 0.71 0.89 0.00 0.00 0.61 0.00 0.77 0.60 0.00 0.00 0.46 C8 262 0.00 0.00 0.24 0.31 0.00 0.00 0.17 0.00 0.30 0.23 0.00 0.00 0.15 C8 (w/ 262 unsaturation) 0.00 0.01 0.62 0.71 0.00 0.00 1.00 0.00 0.68 0.46 0.00 0.00 0.67 C9 262 0.00 0.00 0.98 0.84 0.01 0.00 0.00 0.01 1.06 0.84 0.00 0.00 0.68

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C9 (w/ 262 unsaturation) 0.00 0.00 0.15 0.25 0.00 0.00 0.37 0.00 0.20 0.18 0.00 0.00 0.40 Aromatic and other hydrocarbon metabolites, not uniquely anaerobic Benzoic acid 179 0.87 5.31 105 44.9 2.11 0.00 75.1 4.26 49.1 28.49 1.11 0.59 30.44 o-Toluic acid 193 0.7 0.77 11.5 10.5 0.69 0.61 8.26 0.76 9.44 8.72 0.64 0.63 9.46 m-Toluic acid 193 0.74 0.85 16.7 15.8 0.61 0.61 1.32 0.85 15.3 13.69 0.00 0.69 0.9 p-Toluic acid 193 0.7 0.84 14.3 13.4 0.71 0.00 10.4 0.79 12.4 11.13 0.65 0.66 9.53 o-Cresol 165 0.44 0.57 7.53 2.91 0.45 0.00 6.28 0.45 1.3 3.07 0.42 0.00 0.47 m-Cresol 165 0.42 0.48 4.13 2.13 0.44 0.00 3.25 0.43 0.47 0.54 0.00 0.00 0.47 p-Cresol 165 0.43 0.51 5.28 0.95 0.42 0.00 1.37 0.43 0.6 0.65 0.00 0.00 0.79 2-Naphthoic acid 229 1.22 1.41 31.2 30.3 1.14 1.35 22.3 1.36 29.6 25.76 0.00 1.23 12.88 Succinic acid 247 0.01 0.01 0.02 0.02 0.01 0.00 0.03 0.00 0.02 0.02 0.00 0.00 0.03 Cyclohexane 185 carboxylic acid 1.02 1.29 41.4 32.7 0.97 0.00 34.8 1.23 36.2 44.39 0.00 0.00 15.58

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Table 7-2. Amplification results for primer sets screened for targeted functional gene analysis of oil-amended enrichment cultures. Sequence positions indicated for primers refer to the nucleotide position of the following references; Thauera aromatica K127 bss operon (Winderl et al. 2007; von Netzer et al. 2013), Azoarcus sp. strain T bssA (Washer and Edwards 2007), and Desulfatibacillum alkenivorans AK-01 (Callaghan et al. 2010; Aitken et al. 2013). ncr primers (Morris et al. 2014) were designed from 2-naphthoyl-CoA reductase sequences retrieved from PAH-degrading strains N47 and NaphS2 (Eberlein et al. 2013a; Boll et al. 2014). A (+) designates positive amplification using the specified primer, (-) for no amplification. Primer Target Primer sequence (5’ – 3’) Expected Light Heavy Reference name gene amplicon bp oil oil 7772f bssA s.l. GACATGACCGACGCSATYCT 774 + + Winderl et al. 8546r TCGTCGTCRTTGCCCCAYTT 2007 Primer BssA327f bssA CGAATTCATCNTCGGCTACC 1667 - - Washer and set 1 BssA2004r GTCGTCRTTGCCCCAYTTNGG Edwards 2007 Primer MBssA1516f bssA AGACCCAGAAGACCAGGTC 1008 - - set 2 BssA2524r ATGATSGTGTTYTGSCCRTAGGT Primer BssA327f bssA CGAATTCATCNTCGGCTACC 2119 - - set 3 MBssA2446r ATGCTTTTCAGGCTCCCTCT Primer BssA1985f bssA CNAARTGGGGCAAYGACGA 539 + + set 5 BssA2524r ATGATSGTGTTYTGSCCRTAGGT Primer 1294/1321f assA, TTTGAGTGCATCCGCCAYGGICT assA: 661 + + Callaghan et set 1 1933/1981r bssA TCGTCRTTGCCCCATTTIGGIGC bssA: 682 al. 2010 Primer 1213f bssA GACATGACCGAYGCCATYCT 793 + + set 2 1987r TCRTCGTCRTTGCCCCAYTT Primer 1294f (a) assA TTSGARTGCATCCGNCACGGN 661 - - set 3 1936r TCRTCATTNCCCCAYTTNGG Primer 1294f (a) assA TTSGARTGCATCCGNCACGGN 1180 + - set 4 2457r TTGTCCTGNGTYTTGCGG Primer 1294f (b) assA TTYGAGTGYATNCGCCASGGC 661 - - set 5 1936r TCRTCATTNCCCCAYTTNGG

Primer 1294f (b) assA TTYGAGTGYATNCGCCASGG 1180 + - set 6 2457r TTGTCCTGNGTYTTGCGG

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Primer 1432f assA CCNACCACNAAGCAYGG 523 - + set 7 1936r TCRTCATTNCCCCAYTTNGG Primer 1432f assA CCNACCACNAAGCAYGG 1042 - - set 8 2457r TTGTCCTGNGTYTTGCGG Primer 1432f assA, CCNACCACNAAGCAYGG 523 - - set 9 1933/1981r bssA TCGTCRTTGCCCCATTTIGGIGC FAE-B 7768f bssA s.l., CAAYGATTTAACCRACGCCAT 775 + + von Netzer et 8543r nmsA TCGTCRTTGCCCCAYTTNGG al. 2013 FAE-N 7363f nmsA TCGCCGAGAATTTCGAYTTG 1180 - - von Netzer et 7374f s.str. TTCGAYTTGACGGACAGCGT 1169 al. 2013 8543r TCGTCRTTGCCCCAYTTNGG FAE-Kf 7757f-1 assA TCGGACGCGTGCAACGATCTGA 786 - - von Netzer et 7757f-2 TCGGACGCGTGCAACGCCCTGA 786 al. 2013 7766f TGTAACGGCATGACCATTCT 777 8543r TCGTCRTTGCCCCAYTTNGG assA2 1359–1376f assA YATGWACTGGCACGGMCA 426 - + Aitken et al. 1785–1802r GCRTTTTCMACCCAKGTA 2013 assA3 1394–1409f assA CCGCACCTGGGTKCAYCA 440 - + 1843–1860r GKCCATSGTGTAYTTCTT Ncr2for Ncr TGGACAAAYAAAMGYACVGAT 320 - - Morris et al. Ncr2rev GATTCCGGCTTTTTTCCAAVT 2014

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7.3.2 Detection of fumarate addition genes

Twenty established primer sets targeting anaerobic hydrocarbon activation genes were used to probe genomic DNA from the light- and heavy oil-amended enrichment cultures. Of these, 11 sets of primers could amplify assA or bssA gene fragments in one or both cultures at least one timepoint (Table 7-3), with the most amplification detected using primer sets

7772f/8546r (Winderl et al. 2007) and FAE-B (von Netzer et al. 2013). Purified amplicons were subsequently cloned and sequenced with the aim of determining the taxonomic affiliation of each

PCR product and the total diversity of putative hydrocarbon degraders enriched from light and heavy oil-amended cultures. In all, a total of 3 unique assA and 12 bssA gene fragments were retrieved across both cultures, supporting the chemical evidence for alkane and aromatic hydrocarbon degradation (Section 7.4.1.2). PCR products for nmsA and ncr were not obtained at any time point.

Maximum likelihood trees of the recovered fumarate addition gene fragments revealed that all recovered assA gene sequences clustered within a Smithella subclade, whereas bssA sequences were distributed within a largely uncharacterized clade (Figure 7-5). The bssA clade was phylogenetically distinct from published fumarate addition gene sequences belonging to cultured aromatic hydrocarbon degraders (< 77% sequence similarity), thus we assessed their taxonomic affiliations to previously characterized enrichment cultures and environmental strains.

Most bssA gene fragments retrieved from the oil-degrading cultures were found to share 90 –

91% sequence similarity to a Desulfotomaculum sp. recovered from a methanogenic toluene- degrading enrichment culture (Bacterium bssA-1; Edwards and Grbić-Galić 1994; Washer and

Edwards 2007); the outlier (light oil bssA OTU4) shared 90% identity to a separate

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Table 7-3. Primers used for qPCR analysis of bssA and assA genes. Primer set assA2fq/assA2rq was designed by Aitken et al. (2013). Primer name Target Primer sequence (5’ – 3’) Annealing Expected gene temp (℃) amplicon bp MHGC_bssAfq bssA GACGACGGCTGCATGGA 59.5 708 MHGC_bssArq GCCTTCCCAGTTGGCGTA MHGC_assA1fq assA GGCCAACTGTGCCAAGAT 58.5 277 MHGC_assA1rq TGAAGGCGTCATTACATCCA MHGC_assA2fq assA ACGATGCGTGGATTACTCAGA 59.5 104 MHGC_assA2rq CAGGAAAGGCCGTGGTGTAA MHGC_assA3fq assA CGAAACGCCTGATCCTGCC 60.5 93 MHGC_assA3rq CGGGCCAGAATACTGAAAATGG assA2fq bssA ATGTACTGGCACGGACA 61.4 426 assA2rq GCGTTTTCAACCCATGTA

Desulfotomaculum sp. retrieved from metagenomic sequencing of an Alaskan oil reservoir (Hu et al. 2016). Notably, our bssA gene fragments clustered closely (92 – 99% sequence similarity) to uncultured prokaryotic clones recovered from a methanogenic short-chain alkane-degrading culture (SCADC; Tan et al. 2015b).

7.3.3 Time-resolved quantification of fumarate addition genes

To gain a better understanding of assA and bssA activity, fumarate addition gene abundances were estimated over time in the oil-amended cultures by qPCR analysis. Several attempts were made to design a working set of assA-specific primers and a corresponding qPCR assay, but each failed to significantly amplify the target above threshold levels. After repeating tests using published qPCR primers (AssA2fq/AssA2rq; Aitken et al. 2013), we experienced the same problem. Consequently, assA gene abundances in the oil-amended cultures could not be performed at this time.

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In contrast, bssA gene fragments were successfully quantified over the 17-month incubation period. Gene abundances were below detectable limits at T0, but became significantly enriched after only one month of incubation (Figure 7-6). In the light oil culture, bssA gene abundances significantly increased (> 25-fold) between T4 and T8, and continued increasing up to a maximum gene abundance of 6.92 × 105 (Figure 7-6 A). While the quantity of bssA in the heavy oil culture also significantly increased during the first ~ 8 months of incubation, gene abundances were found to plummet ~ 70% by T17 (Figure 7-6 B).

7.3.4 Microbial community dynamics in methanogenic cultures

Time-resolved sequencing of 16S rRNA gene fragments (V6–V8 region) was carried out to compare microbial community dynamics in response to enrichment on light and heavy oil

(Tables 7-4 and 7-5). Taxonomic assignment for microbial community members comprising ≥

0.1% of total quality 16S rRNA gene sequences is available in Appendix D (Table D-2); here we will focus on the most abundant organisms. The number of OTUs from each timepoint (observed and estimated using the Chao index) varied considerably; in general, species diversity in both cultures increased over the first eight months of incubation (T0 – T8), where it then experienced a

4-month plateau before dropping towards T0 values (Table 7-4). A similar trend was observed using the Shannon-Weiner and Simpson indices, though they predicted that the highest prokaryotic diversity was reached in both cultures around four months of incubation (Table 7-4).

Community evenness also decreased below T0 levels after four months of incubation, despite an initial increase of 0.04 – 0.10 when amended light and heavy oil, respectively, inferring that

OTU enrichment over time became heavily weighted towards a few dominant species. Notably, the heavy oil culture harboured an estimated 47 – 50% more OTUs than the light oil culture,

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Table 7-4. Features of 16S rRNA sequencing and alpha diversity statistics based on species-level analysis (97% cutoff) for all samples analysed in this study. Features/ Light oil Heavy oil Sample T0 T1 T2 T4 T8 T12 T17 T1 T2 T4 T8 T12 T17 Quality reads 92001 36621 23822 43057 51340 52722 257957 34607 19864 29379 79499 72530 125204 #OTUs 1649 1583 904 1736 1937 1926 1536 1393 1542 1884 2915 2678 1686 observed Shannon Index 4.04 4.13 4.01 4.38 3.77 3.78 3.10 4.47 4.74 5.01 4.37 4.28 3.58 Simpson Diversity 0.05 0.06 0.05 0.04 0.09 0.09 0.11 0.04 0.04 0.02 0.05 0.05 0.09 Index Evennessa 0.55 0.56 0.59 0.59 0.50 0.50 0.42 0.65 0.65 0.66 0.55 0.54 0.48 Chao Index 1790 2244 1404 1873 2888 3000 1892 1886 2408 2973 4252 3991 2182 aCalculated using the Shannon Index.

Light oil Heavy oil Taxon T0 T1 T2 T4 T8 T12 T17 T1 T2 T4 T8 T12 T17 Methanogens Methanocalculus 0.2 8.6 13.1 5.3 19.4 13.6 18.1 2.0 1.4 4.3 16.8 10.9 9.6 Methanosaeta 0.0 0.0 0.5 8.8 4.4 9.9 9.4 2.3 4.7 4.9 7.7 9.9 12.5 Methanoculleus 1.8 2.3 2.3 1.0 2.2 3.8 7.8 9.0 7.7 3.2 5.0 5.7 8.3 Uncultured Methanoregulaceae 0.0 0.1 0.1 0.3 7.2 4.2 0.0 0.5 0.0 1.5 5.9 6.2 1.3 Methanofollis 0.0 2.8 3.9 1.8 0.4 0.3 0.3 2.8 3.1 2.7 1.7 1.6 1.2

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Methanolinea 0.0 0.0 0.0 0.0 0.0 0.0 3.2 0.0 0.0 1.1 2.4 2.2 9.0 Hydrocarbon degradation-associated bacteria Desulfotomaculum 0.4 0.0 0.0 0.0 14.5 21.2 21.0 0.0 0.0 0.1 17.2 22.4 30.5 Uncultured Peptococcaceae 0.0 0.0 0.1 0.1 0.0 0.0 0.0 0.0 0.2 2.7 0.4 0.2 0.0 Uncultured Anaerolineaceae 0.2 0.9 1.9 5.3 2.5 3.5 0.9 0.9 1.1 2.9 2.6 3.1 0.6 Smithella 0.0 0.0 2.7 2.8 0.0 0.0 0.2 0.0 2.7 6.1 0.0 0.0 0.6 Uncultured Syntrophaceae 0.0 5.0 2.0 0.8 0.5 0.6 0.3 0.3 1.4 2.6 1.3 0.8 0.4 Syntrophus 0.4 1.3 0.1 0.2 0.4 0.4 0.00 1.3 0.3 1.0 1.8 1.4 0.1 Cell material/organic acid scavengers Pelobacter 3.3 15.9 6.6 3.9 0.1 0.1 0.0 12.0 4.0 0.8 0.3 0.2 0.0 Uncultured Spirochaetes 0.0 0.0 7.8 12.3 0.0 0.0 10.6 0.0 1.8 5.7 0.0 0.0 1.0 Uncultured Bacteroidales 0.5 12.3 0.5 1.0 0.9 0.5 0.0 8.6 0.0 0.0 0.7 0.4 0.0 Dethiosulfatibacter 0.0 8.8 8.1 7.2 0.5 0.3 0.0 0.0 0.0 0.1 0.0 0.0 0.0 Uncultured Deferribacteraceae 2.6 0.4 9.3 7.1 0.0 0.0 0.0 0.0 0.7 0.6 0.0 0.0 0.1 Moorella 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 10.1 8.7 0.0 0.0 0.1 Desulfomicrobium 3.6 1.8 1.4 0.9 0.1 0.0 0.0 3.0 1.7 1.5 0.2 0.1 0.0 NRB-associated Uncultured Rhodocyclaceae 13.8 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Flexistipes 0.5 5.7 0.0 0.0 2.3 1.9 0.0 0.7 0.0 0.0 0.5 0.4 0.0 Thauera 10.4 0.1 0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.4 0.0 Unknown ‘Cloacimonetes’ (WWE1) 0.0 3.2 0.0 0.0 19.4 15.4 0.0 1.4 0.0 0.0 2.5 1.6 0.0 ‘Atribacteria’ (OP9/JS1) 0.6 0.0 0.0 0.0 0.4 2.8 7.0 0.0 0.0 1.4 4.1 8.8 9.1 ‘Marinimicrobia’ (SAR406) 0.0 1.4 4.5 2.2 0.9 1.5 1.1 1.5 3.9 5.1 3.2 1.6 0.9 Total 38.3 70.7 64.9 61.0 76.1 80.0 79.9 46.4 44.8 57.0 74.3 77.9 85.3

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which may be (partially) attributed to a lower concentration of toxic oil components inhibiting microbial growth (Sikkema 1995; Sherry et al. 2014; Menon and Voordouw 2016).

Both the light and heavy oil enrichment cultures saw substantial shifts in microbial community composition during the 17-month incubation under simulated reservoir conditions: many of these shifts were similar across each culture, but key distinctions were also noted. The most apparent increase in abundance over time was seen within the Firmicutes and Euryarchaeota phyla, comprising 60% and 74% of quality sequence reads in both oil-amended cultures by T17, respectively (Figure 7-7). This represented a 20 to 25-fold increase in abundance from reported

T0 values, which collectively had comprised less than 3% of total reads (Figure 7-7). Members of the Firmicutes were dominated by the enrichment of a single OTU affiliated with

Desulfotomaculum after T4, making up to 30.5% of reads by the end of the 17-month incubation period (Table 7-5). Interestingly, this OTU shared > 97% sequence similarity to an uncultured

Peptococcaceae bacterium clone recovered from the Mildred Lake Settling Basin (accession no.

EU22655; Siddique et al. 2012), sediments from which were used to establish SCADC (Tan et al. 2013; Tan et al. 2015b). This trend also closely mirrored the increase in bssA gene abundances over time, particularly in the light oil-amended culture (Figure 7-6). Other members of the Firmicutes were also enriched (though to a lesser extent) during the first four months of incubation, including Dethiosulfatibacter (up to 8.8% of light oil reads) and Moorella (up to

10.0% of heavy oil reads), but their relative abundance fell < 0.1% immediately afterwards

(Table 7-5). Methanogenic Euryarchaeota became enriched after the first month of incubation and proliferated up to 39.1 – 43.3% of total reads by T17 (Figure 7-7). Among the most abundant methanogens were affiliates to hydrogenotrophic (Methanocalculus, Methanoculleus, and

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Methanolinea) and acetotrophic (Methanosaeta) representatives (Table 7-5). Though the ratios of methanogens are similar between both cultures, a greater proportion of reads belonging to

Methanocalculus were enriched over time in light oil-amended samples, whereas Methanolinea was up to three times as prevalent in the presence of heavy oil at T17. Other putative hydrocarbon fermenters and/or hydrocarbon degradation-associated bacteria were detected during the incubation period, including microorganisms affiliated with the Peptococcaecae,

Anaerolineaceae or Syntrophaceae families (averaging 2.5% of reads; Table 7-5). We also detected an OTU belonging to Smithella (up to 6.1% of reads), but unlike Desulfotomaculum, its read abundance declined after four months of incubation.Several of the T0 reservoir-associated

OTUs, consisting primarily of Proteobacteria, were reduced to < 0.5% of reads after just the first month of incubation (includes members of the Alpha-, Beta- and Gammaproteobacteria), while others saw a more gradual decrease in abundance over time (e.g. Deltaproteobacteria,

Deferribacteres; Figure 7-7; Table 7-5).

Other OTUs predominantly affiliated with known protein/or organic acid scavengers (e.g.

Pelobacter, Bacteroidales) saw a rapid increase in abundance (up to 39.4% of reads) at T1, presumably in response to cell material released from Proteobacteria, before falling off shortly afterwards. Interestingly, three candidate phyla were enriched at different times during the incubation period. Most notably, the proliferation of ‘Atribacteria’ (formerly OP9/JS1) closely resembled that of Desulfotomaculum, increasing by up to 7.0 – 9.1% over 17 months (Figure 7-7;

Table 7-5). In contrast, the enrichment of ‘Cloacimonetes’ (WWE1) peaked near T8, and

‘Marinimicrobia’ (SAR406) persisted between 1.1 – 5.1% after T0 (Table 7-5).

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Figure 7-7. Microbial community composition of methanogenic crude oil-degrading enrichment cultures over time at the phylum level based on 16S rRNA illumina sequencing.

7.4 Discussion

Crude oil degradation in deep reservoir environments over geological time has been attributed to methanogenesis, yet our understanding of the processes and organisms mediating oil transformation in situ remains far from complete. Here we assessed the functional and microbial community response of an oilfield produced water consortium over time following exposure to light or heavy oil. Unexpectedly, cultures were found to behave similarly to enrichment on either crude oil source, contributing to the degradation of available low molecular weight hydrocarbon substrates (e.g. short-chain n-alkanes, cyclohexane and monoaromatic hydrocarbons), building on initial reports of methanogenic hydrocarbon degradation from MHGC consortia (Berdugo-

Clavijo and Gieg 2014) and microbial communities enriched from other oilfield fluids (Gieg et al. 2010; Zhou et al. 2012; Mbadinga et al. 2012; Tan et al. 2013; Cheng et al. 2013).

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The detection of enhanced methane production in each oil-amended culture relative to the oil-unamended control (Figure 7-3), in addition to the increase in abundance of methanogenic archaea over time (Figure 7-7), indicates that incubations were rapidly depleted of any available anaerobic oxidants (e.g. nitrate and sulfate) and shifted towards syntrophic growth processes. We remark here that experimental rates of methane production from crude oil were 30 – 60 times slower than in a comparable study using MHGC production water (Berdugo-Clavijo and Gieg

2014), but this is attributed to the increased amount of crude oil used (25 – 45 times more) rather than the absolute rate of methane production. Volatile hydrocarbons present in light oils (e.g. n-

C5–n-C10 alkanes, methylcyclohexane, benzene, toluene, and xylenes) are known to partially inhibit methanogenic hydrocarbon biodegradation (Sherry et al. 2014) and may have contributed to the 2-month lag in methane production seen in the light oil culture (Figure 7-3).

The detection of known anaerobic hydrocarbon metabolites (including fumarate addition products) offers convincing evidence that biodegradation processes are occurring in anoxic environments, and can provide clues as to the mechanism(s) responsible for their transformation

(Gieg and Sulfita 2005; Gieg and Toth 2017b). Using a combined approach of metabolite analysis and targeted functional gene analysis, we present strong evidence that fumarate addition is a prominent mechanism of hydrocarbon degradation in petroleum reservoir-associated microbial community members, and that degradation of low molecular weight alkanes (≤ C8), monoaromatic hydrocarbons, and possibly cyclic alkanes was occurring simultaneously in each culture (Figures 7-3 to 7-8; Table 7-1). An accumulation of hydrocarbon metabolites (e.g. alkylsuccinates, aromatic acids) was observed by the second month of incubation, and persisted for at least two months before decreasing to trace- or below-detectable amounts (Table 7-1). We propose that the accumulation of metabolites was due to the microbial community adaption from

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predominantly denitrifiers (maintained by nitrate injection in the MHGC oil field, e.g. uncultured

Rhodocyclaceae and Thauera; Agrawal et al. 2012) to methanogenic consortia (Table 7-5), requiring several months of incubation to before active syntrophic hydrocarbon degradation finally proceeded. Research groups typically assess enrichment cultures for hydrocarbon metabolites well after methanogenic activity has already been established (e.g. Aitken et al.

2013; Tan et al. 2013; Berdugo-Clavijo and Gieg 2014), when these intermediates are rapidly being consumed. This approach can make it difficult to detect putative hydrocarbon metabolites using standard GC-MS approaches, as seen by Aitken et al. (2013), especially when extracting small culture volumes. Thus, it may be a better approach to look for metabolites early in a time- course experiment, when metabolites are at their highest concentrations (Table 7-1). Though we are not yet able to explain why metabolites may re-accumulate over time, this may have been due to natural fluctuations in structural community dynamics impacting the abundance of secondary syntrophic partners (e.g. Smithella, Syntrophus) at the time of sample collection, which at the time had comprised less than 2% of total 16S rRNA reads (Table 7-5). The quantitative significance of Syntrophaceae (e.g. Smithella spp., Syntrophus spp.), particularly in methanogenic alkane-degrading communities, has been a topic of interest in recent years (e.g.

Gray et al. 2011; Cheng et al. 2013; Embree et al. 2013; Oberding 2016; Wawrik et al. 2016).

Fowler et al. (2014) identified a Syntrophus sp. to be a key secondary syntroph in the methanogenic toluene-degrading culture TOLDC, consuming the intermediate benzoic acid produced by a Desulfosporosinus sp., but at a slower rate. This can also help to explain why downstream metabolites of aromatic hydrocarbon degradation could be detected in each oil- amended culture, but not a fumarate addition product corresponding to bssA genes recovered from extracted DNA (Figure 7-5; Table 7-1). Interestingly, we obtained putative mass spectral

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evidence that short chain n-alkanes propane and butane present in the light oil culture underwent hemolytic C-H bond cleavage by addition to fumarate at the C2 or terminal carbon position

(Figure 7-4). This has been reported in at least two other instances by microbiota enriched or isolated (strain BuS5) from hydrocarbon seeps (Kniemeyer et al. 2007; Savage et al. 2010).

Fumarate addition has also been reported to occur to a lesser extent at C3 for larger alkanes

(Rabus et al. 2001). It has been hypothesized that n-alkylsuccinates are formed accidentally during fumarate addition rather than as true intermediates (Rabus et al. 2001; Jarling et al. 2015).

Phylogenetic and functional gene evidence indicates that a Desulfotomaculum phylotype is a key aromatic hydrocarbon degrader in each oil-amended culture (Figures 7-5 to 7-8; Table 7-

5), which was previously enriched from MHGC produced water enriched on a light oil (°API =

37; Berdugo-Clavijo and Gieg 2014), but at a lower abundance (3.3% of reads after 10 months of incubation). Members of the genus Desulfotomaculum can be metabolically versatile. They are commonly found in the subsurface biosphere through culture-based and molecular approaches, and have been found to participate in the degradation of alkanes (Kniemeyer et al. 2007; Cheng et al. 2013), aromatic hydrocarbons (Ficker et al. 1999; Morasch et al. 2004; Abu Laban et al.

2009; Berlendis et al. 2010; Selesi et al. 2010) and biphenyl (Selesi and Meckenstock 2009).

Though commonly known as sulfate-reducers, some species are capable of oxidizing various substrates (e.g. carbohydrates, organic acids and H2, among others) using other sulfur-containing compounds or metals as electron acceptors (reviewed by Aüllo et al. 2013). Other members of the Desulfotomaculum (cluster I) have lost the ability for sulfate respiration and instead grow syntrophically in concert with methanogens (Imachi et al. 2006), and have been increasingly found in petroleum reservoirs and hydrocarbon-containing environments (Gieg et al. 2008; Tan et al. 2015b; Hu et al. 2016), behaving as either primary or secondary syntrophs (Imachi et al.

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CH4 (+ H2O or CO2)

Figure 7-8. Proposed working model for the methanogenic hydrocarbon biodegradation of alkanes and aromatics by MHGC produced water-associated consortia based on the results of this study. Hydrocarbons are activated by addition to fumarate by Smithella (assA) or Desulfotomaculum (bssA), yielding corresponding alkylsuccinates and benzylsuccinates (not detected, though their production is inferred based on results from other tests, e.g. oil analyses, qPCR assays, and detection of downstream metabolite products such as benzoate and toluic acids). Members of the candidate phylum ‘Atribacteria’ may also participate in hydrocarbon activation; carboxylation of two-ringed PAHs may be catalyzed by an unknown organism. Subsequent degradation steps are proposed to be carried out by several putative syntrophic oxidizers (e.g. Peptococcaceae, Syntrophaceae, and candidate phyla) presumably yielding H2, CO2, and acetate that are consumed by hydrogenotrophic and acetotrophic methanogens. Figure schematic modeled from Jiménez et al. (2016).

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2006; Kleinsteuber et al. 2012). Compared to published Desulfotomaculum cluster 1 sequences (Imachi et al. 2006), the Desulfotomaculum 16S rRNA and bssA genes recovered from the oil-amended enrichment cultures clustering with 1i (data not shown); a largely uncharacterized clade containing uncultured prokaryotic clones with the genetic potential to activate and subsequent degrade alkanes and monoaromatic hydrocarbons via fumarate addition

(Tan et al. 2015b; Hu et al. 2016). We also observed an increase in bssA gene abundances corresponding with the increase in Desulfotomaculum reads over time (particularly in the light oil-amended culture;Figures 7-5 and 7-6; Table 7-5). It is not currently known why the bssA gene abundance decreased in the heavy oil culture after 8 – 12 of incubation, despite the continuous increase in Desulfotomaculum reads (Figure 7-6; Table 7-5), but may have been attributed to

PCR primer/sequencing biases. There may also be other organisms enriched after these time points that also catalyze aromatic hydrocarbon degradation, such as members of candidate divisions (discussed below), but whose functional genes were not captured using the marker gene assays screened in this study (Table 7-2).

From our microbial community sequencing results, we also hypothesize that the candidate phylum ‘Atribacteria’ (formerly known as OP9/JS1) and other enriched candidate phyla play a chief role in methanogenic hydrocarbon based on their progressive enrichment or relative stability over time (Figures 7-7 and 7-8; Table 7-5). A recent study by Hu et al. (2016) discussed the role of candidate phyla in the biodegradation of crude oil, finding that

‘Atribacteria’ dominated samples retrieved from oil reservoirs that exhibited the most extensive crude oil biodegradation (while candidate phyla in the other, less-biodegraded samples ranged from 0 to 0.4% abundance in each sample). Sequence fragments orthologous to benzylsuccinate synthase (alpha, gamma subunits), (1-methyl)alkylsuccinate synthase (alpha subunit) and several

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glycyl radical enzyme activation proteins were identified from ‘Atribacteria’ bins recovered from metagenomic sequencing of the Alaskan oil reservoir samples interrogated (Hu et al. 2016). Carr et al. (2015) also found ‘Atribacteria’ in a methane-rich environment and suggested that it produced methanogenic substrates such as acetate and CO2. Interestingly, Hu et al. (2016) also prepared a draft genome for ‘Marinimicrobia’ (SAR406) and identified an Fe-containing hydrogenase within its genetic material, thus the microorganism may produce hydrogen and participate in syntrophic interactions with methanogens. Members of the phylum

‘Cloacimonetes’ (WWE1) was recently identified in fluids collected from coalbed methane wells

(Kirk et al. 2015) and in anaerobic sludge digesters (Limam et al. 2014), also indicating a putative hydrocarbon degrading role for these phylotypes. Most convincingly, Cheng et al.

(2013) identified members of the ‘Cloacimonetes’ to participate in 13C-hexadecane biodegradation in a methanogenic oilfield enrichment consortium (along with Syntrophaceae).

Indeed, there is much more we can uncover about the roles of candidate phyla in crude oil transformation from our enrichment cultures.

Overall, the results from the present study demonstrate that fumarate addition is a prevalent mechanism of methanogenic hydrocarbon degradation in methanogenic oilfield- associated consortia (Figure 7-8). Further, time course-based functional gene analyses and microbial community sequencing has identified Desulfotomaculum as a key aromatic hydrocarbon degrader under reservoir conditions, regardless of oil quality. Members of several candidate divisions may also play important roles in methanogenic hydrocarbon degradation, expanding on existing knowledge of the diversity of hydrocarbon-degrading consortia. We remark that a better method to have confirmed the role of Desulfotomaculum in aromatic hydrocarbon degradation would have been to compare the fold change in expression of 16S

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rRNA and bssA genes over time against the oil-free control, as was done by Fowler et al. (2014) and Oberding (2016), and is intended future work for characterizing these cultures. To assess the putative metabolic functions of ‘Atribacteria’ and other candidate phyla enriched in this study, the metagenome of the light oil-amended culture (from DNA extracted at T12) was recently sequenced using Illumina MiSeq technology; read assembly and analysis are intended future work. This metagenomic data will also help to uncover putative alkane degraders in these communities (e.g. Smithella), which have not yet been conclusively identified in this community, and to help design primers that can capture a greater diversity of anaerobic hydrocarbon degradation genes.

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Chapter Eight: Conclusions and Future Research Directions

The focus of this dissertation was to glean new insights into the physiology of methanogenic hydrocarbon-degrading communities in order to gain a more complete understanding of the fate of oil components in electron acceptor-depleted environments. To accomplish this, a series of enrichment culture experiments were carried out to characterize the utilization of an expanded range of hydrocarbon substrates under methanogenic conditions. We also sought to devise a number of cultivation-based strategies for accelerating rates of methanogenic hydrocarbon degradation, facilitating the rate of progress of research in this challenging field. Analytical, molecular biology, and metagenomic methods were applied to gain a deeper understanding of the metabolic processes and organisms converting BTEX, PAHs, and whole crude oil to methane, a process presumably carried out at the thermodynamic limits of microbial growth (Mcinerney et al. 2007; Dolfing et al. 2008; Head et al. 2014).

8.1 Summary of key findings and future directions

8.1.1 Optimizing incubation conditions for cultivating a methanogenic toluene-degrading enrichment culture

As described in Chapter 4, we assessed numerous modifications to the standard cultivation procedure used to maintain TOLDC with the goal of improving rates of toluene consumption and reducing lag periods following transfer events. We determined that cysteine present in the growth medium as a reducing agent was preferentially used as a carbon and energy source, leading to the inhibition of methanogenic toluene metabolism and progressive enrichment of tentative peripheral protein/organic acid scavengers such as Pseudomonas,

Lachnospiraceae, and Proteiniphilum over several years (Figures 4-3 and 4-5). Replacing the

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reductant with a carbon-free alternative (e.g. sodium sulfide) restored active methanogenic toluene biodegradation and the expected microbial community composition after several refeeds

(Figures 4-4; 4-5; Chapter 5). We also found that increasing incubation temperature conditions closer to the optimal conditions of key degraders present in TOLDC (e.g. Desulfovibrio,

Synthrophus, Desulfovibio; Fowler et al. 2012; 2014) helped to increase rates of substrate utilization (Figure 4-2). While we ended up carrying out most experiments described in this dissertation under room temperature conditions, we propose that all future cultivations of

TOLDC and other hydrocarbon-degrading consortia should adopt this simple strategy to accelerate rates of substrate metabolism.

8.1.2 The importance of Syntrophus in methanogenic toluene biodegradation

Inadvertently, we found chemical evidence of a reductive benzoyl-CoA degradation pathway in TOLDC, which may couple to a fundamental mechanism of biological energy conservation in syntrophic consortia (Mcinerney et al. 2007; Sieber et al. 2012; Kung et al. 2013;

Buckel and Thauer 2013; Boll et al. 2016; Chapters 4 and 5). The formation of cyclohexane carboxyl-CoA from cyclo-hex-1-ene carboxyl-CoA, both of which were identified as TMS- derivatized hydrocarbon metabolites in TOLDC (Figure B-3), have been predicted to drive the unfavorable reduction of ferredoxin with the oxidation of NADH with the energetically favourable production of hydrogen using flavin-based electron bifurcation (Buckel and Thauer

2013; Rabus et al. 2016b). This mechanism is essential for interspecies electron transfer across syntrophic partners in methanogenic communities, constituting what many researchers believe to be the missing link in understanding the anaerobic flow of carbon in anoxic environments (e.g.

Sieber et al. 2012; Head et al. 2014; Gieg et al. 2014). Previous genomic analysis of Syntrophus

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acidotrophicus confirmed that the metabolic and regulatory components for this hypothetical pathway were present in its genetic material (Mcinerney et al. 2007), thus we proposed that

Syntrophus in our methanogenic toluene-degrading enrichment culture also likely expresses this reductive pathway (Figure 5-8). Further, we found that artificially enriching the abundance of a presumed Syntrophus isolate in TOLDC significantly increased rates of toluene metabolism

(Figure 4-7), presumably by increasing rates of interspecies electron transfer in TOLDC, but this would need to be experimentally verified.

8.1.3 Co-metabolic biodegradation of alkylbenzenes under methanogenic conditions

In Chapter 5, we challenged three methanogenic hydrocarbon-degrading enrichment cultures on various model hydrocarbons, which we had hypothesized to be susceptible to degradation based on metagenomic investigations conducted by Fowler (2014) and Tan et al.

(2015a). We determined that co-metabolic degradation of xylenes and ethylbenzenes was possible in the presence of toluene, based on chemical measurements of hydrocarbon loss over time and the formation of fumarate addition products diagnostic of their parent hydrocarbon

(experiment # 2; Figures 5-2 – 5-4). We proposed that Desulfosporosinus sp., the organism chiefly responsible for the activation and subsequent degradation of toluene in TOLDC, also initiated the activation of alkylbenzenes ‘accidentally’ during toluene utilization, based on 16S rRNA gene sequencing (experiment #2; Table 5-2) and a lack of chemical evidence of methanogenic activity on individual xylene and ethylbenzene substrates (experiment #3; Figure

5-2). It is unknown whether degradation of these oil components in the environment is also due to co-metabolic reactions (Gieg and Toth 2017b), but would help to explain the scarcity of

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methanogenic cultures able to metabolize these compounds as sole substrates (Edwards and

Grbić-Galić 1994; Jiménez et al. 2016).

8.1.4 Physiological and functional evidence of methanogenic PAH biodegradation, and identification of putative PAH degraders

A tentative methanogenic phenanthrene-degrading enrichment culture was established from an active 2, 6-dimethylnaphthalene-degrading enrichment culture (Berdugo-Clavijo et al.

2012; Chapter 5). Enhanced methane production and hydrocarbon loss was observed in live, phenanthrene-amended incubations relative to substrate-free and sterile controls (Figure 5-5).

Microbial community sequencing revealed Clostridium as a prevalent taxon in the enrichment culture, also a dominant phylogeny in other methanogenic PAH-degrading communities

(Berdugo-Clavijo et al. 2012) but its role could only be speculated upon at the time. Using a combination of DNA-based stable isotope probing and metagenomics analysis (Chapter 6), however, we have assembled promising molecular biology and functional evidence that

Clostridium does indeed participate in methanogenic PAH biodegradation (Figures 6-2 – 6-5;

Table 6-3), tentatively catalyzing the dearomatizing and ring cleavage steps of 2-napthoyl-CoA, a central metabolic intermediate that may be formed from fumarate addition reactions or carboxylation of naphthalene (Meckenstock et al. 2016). A similar mechanism may also proceed during anaerobic phenanthrene metabolism. This study, to our knowledge, is the first to describe functional evidence of anaerobic naphthalene degradation pathways in a methanogenic PAH- degrading consortium. The available metagenome also serves as a blueprint for future investigations aiming to characterize the syntrophic interactions of microbial community members in PAH-containing environments.

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8.1.5 Key players and anaerobic mechanisms of methanogenic crude oil biodegradation

Finally, we sought to improve our understanding of the metabolic processes and key microorganisms that may be involved in the formation of heavy oil over geological time

(Chapter 7). To do this, a 17-month time course experiment was devised using multidisciplinary tools for monitoring the chemical, physiological, and functional responses to enrichment on light and heavy crude oils, and prepared a working model for methanogenic crude oil biodegradation in the MHGC oilfield (Figure 7-8). Based on metabolic and molecular evidence, fumarate addition was experimentally shown to play an important role in the degradation of n-alkanes

(Figures 7-4 and 7-5; Table 7-1) and possibly monoaromatic hydrocarbons (Figures 7-5 to 7-6), and was proposed to be a key mechanism for crude oil metabolism in electron acceptor-depleted oilfields. Several known hydrocarbon degradation-associated bacteria became enriched over the duration of the experiment, including Desulfotomaculum, Smithella, and Syntrophaceae (Figure

7-8; Table 7-5), as well as a number of candidate phyla that could participate in hydrocarbon activation steps or downstream syntrophic oxidation pathways (Hu et al. 2016), which we intend to survey in a future metagenomics sequencing project.

8.1.6 Other future research directions

The inherent challenges of studying methanogenic hydrocarbon biodegradation have always stemmed from not having enough volume of active enrichment cultures to conduct large- scale and robust experiments. Whether we are seeking hydrocarbon metabolites diagnostic of anaerobic hydrocarbon biodegradation, preparing molecular biology experiments, or extracting

DNA for phylogenetic inferences, several months or years are often required to cultivate enough

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cells for experimentation. Now that we have a series of methodologies that can be used for improving rates of hydrocarbon biodegradation, our first priority should be to begin scaling up available enrichment cultures to larger volumes. Not only will this allow for better resolution of active hydrocarbon degradation mechanisms (e.g. by metabolite analysis), more sophisticated tools could be adopted for characterizing the expression of genes encoding these pathways (e.g. using metatranscriptomic or proteomic analyses). This may ultimately be the best approach for identifying novel enzymes in largely uncharacterized pathways, as it provides unequivocal evidence of protein-encoding genes expressed during substrate degradation. For example, this approach has been successfully used to understand naphthalene degradation under sulfate- reducing conditions (DiDonato et al. 2010; Bergmann et al. 2011b; Bergmann et al. 2011a;

Eberlein et al. 2013b; Eberlein et al. 2013a; Estelmann et al. 2015; Meckenstock et al. 2016).

The characterization of genes and enzymes expressed during methanogenic hydrocarbon degradation, coupled with metabolite evidence of degradation intermediates, is what we project the next 10 years of research in this field to encompass.

In partial consideration of this, characterizing the genome of the Syntrophus genus in

TOLDC could shed light on the physiological and biochemical reactions involved in syntrophic energy conservation. We remark that similar surveys have been performed for cultured isolates and syntrophic cocultures grown with benzoate and crotonate (Mcinerney et al. 2007; Sieber et al. 2012; Boll et al. 2016). To our knowledge, however, this pathway has never been characterized in a hydrocarbon-degrading consortium, which we propose contains 4 or 5 key syntrophic hydrocarbon-degrading bacteria and methanogenic archaea. As such, TOLDC could also serve as a model consortium for investigating more complex syntrophic partnerships.

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Exploiting this mechanism would be a unique approach for cultivating methanogenic hydrocarbon-degrading consortia, as well as other slow-growing syntrophic communities.

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APPENDIX A: SUPPLEMENTARY INFORMATION FOR CHAPTER 4: IDENTIFYING CULTIVATION STRATEGIES FOR ACCELERATING RATES OF TOLUENE BIODEGRADATION USING AN ESTABLISHED METHANOGENIC ENRICHMENT CULTURE

160 140 120

mol) 100 μ 80 60

Methane( 40 20 0 0 100 200 300 400 Time (Days)

90 80 70

60 mol) μ 50 20% 40% 40 60% 30

Methane( 80% 20 100% 10 0 0 20 40 60 80 100 Time (days)

Figure A-2. Methane production in transferred 20 mL TOLDC incubations (20 mL; 20 – 100% transfer v/v) containing 300 µM toluene. Figure prepared by Corynne O’Farrell.

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Table A-1. Redox potential (Eh) of reducing agents in growth medium at pH 7.

Reducing Agent Eh Concentration in Reference(s) (mV) media Cysteine  HCl -210 0.025% (Costilow 1981) Titanium (III) -480 0.008 – 0.03% (Zehnder and chloride/nitrilotriacetic acid Wuhrmann 1976; Costilow 1981; Moench and Zeikus 1983) Na2S  9H2O -571 0.025% (Hungate 1969) Cysteine  HCl + Na2S  9H2O -571 0.025% + 0.025% (Hungate 1969)

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Table A-2. Tanner’s trace metal solution. Component g/L water Nitrilotriacetic acid (pH 6) 2.00 MnSO4·2H2O 1.00 Fe(NH4)2(SO4)2·6H2O 0.80 CoCl2·6H2O 0.20 ZnSO4·7H2O 0.20 FeSO4·7H2O 0.10 CuCl2·2H2O 0.02 NiCl2·6H2O 0.01 Na2MoO4·2H2O 0.02 Na2SeO4 0.02 Na2WO4 0.02

Table A-3. Tanner’s vitamin solution. Component mg/L water Pyridoxine-HCl 10.0 Thiamine-HCl 5.00 Riboflavin 5.00 DL-calcium pantothenate 5.00 Lipoic acid 5.00 4-Aminobenzoic acid (PABA) 5.00 Nicotinic acid 5.00 Vitamin B12 5.00 Mecaptoethanesulfonic acid (MESA) 5.00 D(+)-Biotin 2.00 Folic acid 2.00

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Table A-4. Culture medium 960 used for isolating Syntrophus from TOLDC. Component Amount/L water Growth medium KH2PO4 0.14 g MgCl2·6H2O 0.20 g CaCl2·6H2O 0.15 g NH4Cl 0.54 g Trace element solution (see below) 1.00 mL Na-resazurin solution (0.1% w/v) 0.50 mL NaHCO3 0.10 g Vitamins solution (see below) 10.0 mL Na-crotonate 0.86 g Yeast extract 0.50 g Cysteine-HCl 0.30 g NasS·9H2O 0.30 g Trace element solution Nitrilotriacetic acid (pH 6) 12.8 g FeCl3·6H2O 1.35 g MnCl2·4H2O 0.10 g CoCl2·6H2O 24.0 mg CaCl2·2H2O 0.10 g ZnCl2 0.10 g H3BO3 0.01 g CuCl2·2H2O 25.0 mg Na2MoO4·2H2O 24.0 mg NaCl 1.00 g Na2SeO3·5H2O 26.0 mg Vitamins solution Pyridoxine-HCl 10.0 mg Thiamine-HCl·2H2O 5.00 mg Riboflavin 5.00 mg DL-calcium pantothenate 5.00 mg Lipoic acid 5.00 mg 4-Aminobenzoic acid (PABA) 5.00 mg Nicotinic acid 5.00 mg Vitamin B12 0.10 mg D(+)-Biotin 2.00 mg Folic acid 2.00 mg

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APPENDIX B: SUPPLEMENTARY INFORMATION FOR CHAPTER 5: BIOGRADATION AND COMETABOLIC BIODEGRADATION OF BTEX AND OTHER HYDROCARBONS

227

228

Figure B-4. Enhanced turbidity observed in (A) phenanthrene-amended replicates, as compared to (B) HMN-only, (C) carbon-free, and (D) sterile controls.

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APPENDIX C: SUPPLEMENTARY INFORMATION FOR CHAPTER 6: ASSESSING CARBON FLOW THROUGH METHANOGENIC PAH-DEGRADING COMMUNITIES BY DNA-SIP AND METAGENOMIC APPROACHES

Table C-1. Genome sequence similarity of prepared draft genomes to their closest matching cultured representative or enriched strain. Pairwise average nucleotide identity (ANI) calculations were used to assess the bidirectional best hits (BBH) of genes having 70% or more identity to reference strains and at least 70% coverage of the shorter gene. Alignment fraction (AF) calculations were prepared to determine the % coverage of the draft genomes to reference strains. Genome1 Name Genome Gene count Genome2 Genome2 Name ANI ANI AF AF Total size (assembled) ID 12 21 12 21 BBH (assembled) Anaerolinea sp. Bin 1 649633005 Anaerolinea thermophila UNI-1 67.62 67.59 0.08 0.05 221 2333788 2249

Anaerolinea sp. Bin 2 649633005 Anaerolinea thermophila UNI-1 67.7 67.68 0.13 0.08 318 2271625 2153

Clostridium sp. Bin 1 2582580929 Youngiibacter fragilis 87.53 87.52 0.54 0.75 2904 5438132 5424

Desulfovibrio sp. Bin 1 2561511137 Desulfovibrio alcoholivorans 72.64 72.65 0.40 0.25 1337 3088242 2959 DSM 5433

Geobacter sp. Bin 1 640427115 Geobacter uraniireducens Rf4 72.35 72.35 0.29 0.25 1225 4390079 4104

Geobacter sp. Bin 2 640427115 Geobacter uraniireducens Rf4 72.23 72.23 0.35 0.26 1230 3876684 3546

Geobacter sp. Bin 3 642555130 Geobacter lovleyi SZ 77.01 76.99 0.69 0.43 1737 2526538 2519

Methanosaeta sp. Bin 1 650716054 Methanosaeta concilii GP-6 96.57 96.58 0.81 0.76 2209 2683322 2798

Sphaerochaeta sp. Bin 1 650377973 Sphaerochaeta globosa Buddy 80.53 80.53 0.70 0.37 1321 1750954 1956

Unclassified 2651870079 Unclassified Rhodospirillaceae 69.49 69.49 0.15 0.14 546 Rhodospirillales Bin 1 3473168 3651 Bin 35

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Table C-2. Genome sequence similarity of prepared draft genomes to anaerobic hydrocarbon-degrading isolates and enrichment strains. Pairwise average nucleotide identity (ANI) calculations were used to assess the bidirectional best hits (BBH) of genes having 70% or more identity to reference strains and at least 70% coverage of the shorter gene. Alignment fraction (AF) calculations were prepared to determine the % coverage of the draft genomes to reference strains. Genome1 ID Genome1 Name Genome2 ID Genome2 Name ANI ANI AF AF Total 12 21 12 21 BBH 2724679696 Clostridium sp. Bin 1 2617270891 Clostridium sp. 66.7 66.65 0.06 0.07 433 637000119 Geobacter metallireducens GS-15 65 64.99 0.01 0.02 120 2728369703 Geobacter toluenoxydans JCM 15764 65.87 65.71 0.01 0.01 112 2724679721 Desulfovibrio sp. Bin 1 637000012 Aromatoleum aromaticum EbN1 68.76 68.9 0.05 0.03 237 2648501830 Azoarcus sp. CIB 69.14 69.12 0.06 0.04 320 2518645585 Azoarcus toluclasticus ATCC 700605 69.27 69.31 0.06 0.03 326 2681812808 Azoarcus tolulyticus ATCC 51758 68.98 69.07 0.07 0.04 314 637000088 Dechloromonas aromatica RCB 68.13 68.21 0.05 0.03 240 648276759 Deltaproteobacterium NaphS2 67.57 67.43 0.05 0.03 253 2524023220 Desulfobacula toluolica Tol2 65.49 65.44 0.02 0.01 101 2619619282 Desulfobulbus sp. Tol-SR 69.75 69.81 0.11 0.08 431 637000119 Geobacter metallireducens GS-15 69.52 69.51 0.1 0.08 396

2728369703 Geobacter toluenoxydans JCM 15764 68.3 68.2 0.05 0.04 260

2724679697 Geobacter sp. Bin 1 637000012 Aromatoleum aromaticum EbN1 67.51 67.48 0.03 0.03 191 2648501830 Azoarcus sp. CIB 68.05 68.11 0.04 0.03 244 2518645585 Azoarcus toluclasticus ATCC 700605 68.12 67.98 0.04 0.03 246 2681812808 Azoarcus tolulyticus ATCC 51758 67.99 68.03 0.04 0.03 256 637000088 Dechloromonas aromatica RCB 67.44 67.36 0.04 0.04 236 648276759 Deltaproteobacterium NaphS2 66.07 66.06 0.04 0.03 238 2524023220 Desulfobacula toluolica Tol2 66.55 66.52 0.02 0.01 131 2619619282 Desulfobulbus sp. Tol-SR 68.35 68.33 0.06 0.07 368 637000119 Geobacter metallireducens GS-15 72.2 72.18 0.28 0.29 1160

2728369703 Geobacter toluenoxydans JCM 15764 71.8 71.79 0.18 0.19 985

2724679723 Geobacter sp. Bin 2 637000012 Aromatoleum aromaticum EbN1 67.49 67.44 0.03 0.03 188

2648501830 Azoarcus sp. CIB 67.78 67.74 0.04 0.03 231

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2518645585 Azoarcus toluclasticus ATCC 700605 67.33 67.34 0.04 0.03 238 2681812808 Azoarcus tolulyticus ATCC 51758 68.09 68.16 0.04 0.03 226 637000088 Dechloromonas aromatica RCB 67.41 67.33 0.05 0.04 247 648276759 Deltaproteobacterium NaphS2 66.2 66.09 0.04 0.03 235 2524023220 Desulfobacula toluolica Tol2 65.76 65.73 0.03 0.02 161 2619619282 Desulfobulbus sp. Tol-SR 67.7 67.64 0.07 0.07 338 637000119 Geobacter metallireducens GS-15 71.42 71.42 0.3 0.27 1058

2728369703 Geobacter toluenoxydans JCM 15764 71.43 71.43 0.22 0.2 1007

2724679724 Geobacter sp. Bin 3 637000012 Aromatoleum aromaticum EbN1 67.86 67.78 0.06 0.03 215 2648501830 Azoarcus sp. CIB 67.81 67.64 0.07 0.04 254 2518645585 Azoarcus toluclasticus ATCC 700605 67.92 67.92 0.08 0.03 266 2681812808 Azoarcus tolulyticus ATCC 51758 68.4 68.41 0.07 0.04 255 637000088 Dechloromonas aromatica RCB 68.16 68.08 0.07 0.04 277 648276759 Deltaproteobacterium NaphS2 66.27 66.27 0.06 0.02 210 2524023220 Desulfobacula toluolica Tol2 65.92 65.89 0.02 0.01 121 2619619282 Desulfobulbus sp. Tol-SR 68.23 68.26 0.1 0.06 344 637000119 Geobacter metallireducens GS-15 71.73 71.69 0.39 0.25 1000

2728369703 Geobacter toluenoxydans JCM 15764 71.54 71.5 0.27 0.17 860

2724679720 Unclassified 637000012 Aromatoleum aromaticum EbN1 69.78 69.84 0.08 0.05 375

Rhodospirillales Bin 1 2648501830 Azoarcus sp. CIB 70.1 70.14 0.09 0.06 423 2518645585 Azoarcus toluclasticus ATCC 700605 70.04 70.29 0.09 0.05 430 2681812808 Azoarcus tolulyticus ATCC 51758 70.07 70.04 0.09 0.06 435 637000088 Dechloromonas aromatica RCB 68.47 68.34 0.07 0.06 338 648276759 Delta proteobacterium NaphS2 68.32 68.35 0.02 0.01 121 2619619282 Desulfobulbus sp. Tol-SR 69.27 69.17 0.05 0.04 271 637000119 Geobacter metallireducens GS-15 69.03 69.18 0.05 0.04 227

2728369703 Geobacter toluenoxydans JCM 15764 68.39 68.51 0.03 0.03 194

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APPENDIX D: SUPPLEMENTARY INFORMATION FOR CHAPTER 7: MICROBIAL COMMUNITY RESPONSE TO ENRICHMENT ON LIGHT AND HEAVY CRUDE OILS UNDER SIMULATED RESERVOIR CONDITIONS

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Table D-1. Water chemistry of PW samples collected May 20th, 2015. Data courtesy of Dr. Yin Shen. Ammonium Site pH Sulfate (mM) Sulfide (mM) Nitrate (mM) Nitrite (mM) (mM) 4-PW 7.38 0.00 0.10 0.00 0.00 0.38 7-PW 7.66 0.00 0.03 0.00 0.02 0.36 18-PW 7.63 0.00 0.07 0.00 0.00 0.42 32-PW 7.82 0.00 0.02 0.00 0.01 0.40 33-PW 7.89 0.00 0.03 0.00 0.02 0.40

Table D-2. Time-course taxonomic distribution of bacterial and archaeal 16S rRNA gene sequences comprising at least 0.1% of total reads in the crude oil-amended enriched cultures.

Taxonomic Lineage Light Oil Heavy Oil

Phylum Class Order Family Genus T0 T1 T2 T4 T8 T12 T17 T1 T2 T4 T8 T12 T17 Euryarchaeota Methanobacteria Methanobacteriales WSA2 0.00 0.00 0.00 0.00 0.20 0.20 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Euryarchaeota Methanobacteria Methanobacteriales 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.17 0.00 0.00 0.21 0.23 0.00 Euryarchaeota Methanomicrobia Methanomicrobiales Methanocorpusculaceae Methanocalculus 0.20 8.64 13.1 5.32 19.4 13.6 18.1 1.97 1.43 4.28 16.8 10.9 9.62 Euryarchaeota Methanomicrobia Methanomicrobiales Methanomicrobiaceae Methanoculleus 1.77 2.34 2.28 0.97 2.16 3.80 7.80 9.04 7.72 3.23 5.04 5.69 8.32 Euryarchaeota Methanomicrobia Methanomicrobiales Methanomicrobiaceae Methanofollis 0.00 2.84 3.93 1.85 0.41 0.26 0.32 2.76 3.10 2.69 1.72 1.60 1.17 Euryarchaeota Methanomicrobia Methanomicrobiales Methanoregulaceae Methanolinea 0.00 0.00 0.00 0.00 0.00 0.00 3.21 0.00 0.00 1.14 2.42 2.15 9.02 Euryarchaeota Methanomicrobia Methanomicrobiales Methanoregulaceae 0.00 0.14 0.07 0.25 7.22 4.25 0.00 0.50 0.00 1.45 5.91 6.20 1.26 Euryarchaeota Methanomicrobia Methanomicrobiales 0.00 0.00 0.00 0.00 0.60 0.91 0.00 0.00 0.00 0.11 0.94 1.01 0.00 Euryarchaeota Methanomicrobia Methanosarcinales Methanosaetaceae Methanosaeta 0.00 0.00 0.51 8.83 4.36 9.91 9.38 2.35 4.72 4.91 7.72 9.91 12.5 Euryarchaeota Methanomicrobia Methanosarcinales Methanosarcinaceae Methanolobus 0.00 0.00 1.07 0.38 0.00 0.00 0.00 0.06 1.70 0.55 0.00 0.00 0.00 Euryarchaeota Methanomicrobia Methanosarcinales Methanosarcinaceae Methanomethylovorans 0.38 0.61 0.00 0.00 0.00 0.00 0.00 2.06 0.00 0.00 0.22 0.14 0.00 Euryarchaeota Methanomicrobia Methanosarcinales Methanosarcinaceae Methanosarcina 0.00 0.00 0.07 0.05 0.00 0.00 0.00 0.00 0.40 0.00 0.00 0.00 0.00 Euryarchaeota Methanomicrobia Methanosarcinales 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.13 0.18 0.00 Euryarchaeota Methanomicrobia 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.12 0.00 0.00 Euryarchaeota Thermoplasmata Thermoplasmatales 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.25 0.13 0.00 0.00 0.21 Euryarchaeota Thermoplasmata 0.00 0.00 0.00 0.29 0.00 0.00 0.25 0.08 0.20 0.28 0.22 0.21 1.28 [Caldithrix] KSB1 GW-22 0.00 0.00 0.00 0.00 0.15 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 ‘Cloacimonetes’ 0.00 3.17 0.00 0.00 19.4 15.4 0.00 1.39 0.00 0.00 2.45 1.56 0.00 AC1 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.56 0.29 0.00 Actinobacteria Actinobacteria Corynebacteriales Corynebacteriaceae Corynebacterium 0.00 0.00 0.00 0.11 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Actinobacteria Coriobacteriia Coriobacteriales Coriobacteriaceae 0.00 0.00 0.00 0.05 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Armatimonadetes 0.00 0.00 0.00 0.06 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 ‘Atribacteria’ (OP9/JS1) 0.62 0.00 0.00 0.00 0.45 2.84 7.04 0.00 0.00 1.43 4.12 8.85 9.10 Bacteroidetes Bacteroidia Bacteroidales 0.55 12.3 0.52 1.00 0.88 0.55 0.00 8.56 0.00 0.00 0.71 0.38 0.00 Bacteroidetes Bacteroidia Bacteroidales Porphyromonadaceae 1.39 1.31 0.00 0.00 0.00 0.00 0.00 2.54 0.00 0.00 0.17 0.05 0.00 Bacteroidetes Bacteroidia Bacteroidales Porphyromonadaceae Proteiniphilum 0.00 0.00 0.20 0.16 0.00 0.00 0.00 0.00 1.06 0.31 0.00 0.00 0.06 Bacteroidetes Bacteroidia Bacteroidales Rikenellaceae 0.00 0.00 0.00 0.00 0.00 0.31 0.00 0.00 0.49 0.16 0.00 0.00 0.00 Bacteroidetes BD2-2 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.31 0.21 0.00 0.00 0.00 Bacteroidetes SB-1 0.00 0.00 0.00 0.50 0.18 0.05 0.00 0.00 0.00 0.00 0.12 0.15 0.07 Bacteroidetes Sphingobacteriia Sphingobacteriales 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.35 2.07 0.00 0.00 0.00 Caldiserica Caldisericia Caldisericales 0.00 0.00 0.30 0.36 0.00 0.00 0.00 0.00 0.32 0.21 0.00 0.00 0.00 Chlorobi Ignavibacteria Ignavibacteriales IheB3-7 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.05 0.00 0.05 0.00 Chloroflexi Anaerolineae Anaerolineales Anaerolineaceae Leptolinea 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.05 0.39 0.00 0.00 0.00 Chloroflexi Anaerolineae Anaerolineales Anaerolineaceae 0.22 0.86 1.87 5.30 2.48 3.49 0.90 0.94 1.10 2.90 2.64 3.10 0.59 Chloroflexi Anaerolineae SHA-20 0.00 0.00 0.00 0.00 0.31 0.22 0.00 0.00 0.00 0.00 0.05 0.00 0.00 234

Chloroflexi Dehalococcoidetes GIF9 0.45 0.00 0.00 0.00 0.00 0.00 0.00 0.43 0.28 0.23 0.00 0.06 0.00 Chloroflexi 0.00 0.00 0.00 0.17 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Deferribacteres Deferribacteres Deferribacterales Deferribacteraceae 2.59 0.36 9.35 7.11 0.00 0.00 0.00 0.00 0.73 0.58 0.00 0.00 0.05 Deferribacteres Deferribacteres Deferribacterales Deferribacteraceae Flexistipes 0.47 5.65 0.00 0.00 2.30 1.90 0.00 0.71 0.00 0.00 0.47 0.39 0.00 Deferribacteres Deferribacteres Deferribacterales Deferribacteraceae Geovibrio 2.75 0.11 0.00 0.00 0.00 0.00 0.00 0.48 0.00 0.00 0.00 0.00 0.00 Deinococcus-Thermus Deinococci Deinococcales Trueperaceae Truepera 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.07 0.40 0.00 0.00 0.00 Firmicutes Clostridia Clostridiales 0.00 0.81 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Firmicutes Clostridia Clostridiales [Tissierellaceae] Tissierella 0.00 0.38 0.00 0.00 0.06 0.00 0.00 0.05 0.00 0.00 0.00 0.00 0.00 Firmicutes Clostridia Clostridiales Clostridiaceae 0.17 3.62 0.00 0.00 0.00 0.00 0.00 0.62 0.00 0.00 0.00 0.00 0.00 Firmicutes Clostridia Clostridiales Clostridiaceae Clostridium 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.07 0.00 0.00 0.00 0.00 0.00 Firmicutes Clostridia Clostridiales Incertae Sedis Dethiosulfatibacter 0.00 8.77 8.12 7.24 0.53 0.32 0.00 0.00 0.00 0.06 0.00 0.00 0.00 Firmicutes Clostridia Clostridiales Eubacteriaceae Acetobacterium 0.00 0.06 0.39 0.40 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Firmicutes Clostridia Clostridiales Eubacteriaceae 0.00 0.27 1.51 1.68 0.00 0.00 0.00 0.00 0.19 0.05 0.00 0.00 0.00 Firmicutes Clostridia Clostridiales Family XI 0.00 0.00 0.88 1.33 0.00 0.00 0.00 0.00 0.07 0.16 0.00 0.00 0.00 Firmicutes Clostridia Clostridiales Family XIII Anaerovorax 0.00 0.06 0.17 0.41 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Firmicutes Clostridia Clostridiales Peptococcaceae Dehalobacterium 0.00 0.12 0.26 0.19 0.00 0.00 0.00 0.76 0.00 0.00 0.00 0.00 0.00 Firmicutes Clostridia Clostridiales Peptococcaceae Desulfosporosinus 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.05 0.00 0.83 0.00 0.00 0.00 Firmicutes Clostridia Clostridiales Peptococcaceae Desulfotomaculum 0.39 0.00 0.00 0.00 14.5 21.2 0.00 0.00 0.00 0.06 17.2 22.4 0.00 Firmicutes Clostridia Clostridiales Peptococcaceae Niigata-25 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.20 0.00 0.00 0.00 0.00 0.00 Firmicutes Clostridia Clostridiales Peptococcaceae 0.00 0.00 0.06 0.06 0.00 0.00 21.0 0.00 0.21 2.66 0.42 0.22 30.5 Firmicutes Clostridia Clostridiales Ruminococcaceae 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.52 1.06 0.54 0.15 0.00 0.00 Firmicutes Clostridia Clostridiales Syntrophomonadaceae Syntrophomonas 0.00 0.13 0.14 0.50 0.00 0.00 0.00 0.00 0.14 0.00 0.00 0.00 0.00 Firmicutes Clostridia Clostridiales 0.00 0.06 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Firmicutes Clostridia D8A-2 0.00 0.00 0.00 0.21 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Firmicutes Clostridia Thermoanaerobacterales Thermoanaerobacteraceae Moorella 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 10.1 8.66 0.00 0.00 0.11 ‘Latescibacteria’ (WS3) 0.00 0.00 0.00 0.15 0.00 0.00 0.00 0.06 0.19 0.32 0.16 0.13 0.00 Lentisphaerae Lentisphaeria Victivallales Victivallaceae Victivallis 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.41 0.38 0.00 0.00 0.00 0.00 Lentisphaerae Oligosphaeria 0.00 0.19 0.00 0.16 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 ‘Marinimicrobia’ (SAR406) 0.00 1.41 4.48 2.20 0.85 1.47 1.08 1.49 3.91 5.13 3.16 1.55 0.91 ‘Mircogenomates’ OP11 0.00 0.00 0.00 0.06 0.36 0.29 0.00 0.00 0.00 0.52 0.00 0.06 0.00 ‘Omnitrophica’ (OP3) 1.30 0.08 0.00 0.00 0.00 0.00 0.00 0.46 0.23 0.35 0.29 0.15 0.11 ‘Parcubacteria’ (OD1) 0.00 0.00 0.29 0.46 0.00 0.00 0.00 0.00 0.07 1.85 0.36 0.21 0.11 Planctomycetes Phycisphaerae Phycisphaerales 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.06 0.00 0.00 0.00 Proteobacteria Alphaproteobacteria Rhizobiales Phyllobacteriaceae 0.26 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Proteobacteria Alphaproteobacteria Rhizobiales Rhizobiaceae 0.47 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Proteobacteria Alphaproteobacteria Rhodobacterales Rhodobacteraceae 1.44 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.36 0.00 Proteobacteria Alphaproteobacteria Rhodospirillales Rhodospirillaceae Magnetospirillum 3.14 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Proteobacteria Alphaproteobacteria Rhodospirillales Rhodospirillaceae Novispirillum 0.16 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Proteobacteria Alphaproteobacteria Rhodospirillales Rhodospirillaceae 7.87 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Proteobacteria Betaproteobacteria Rhodocyclales Rhodocyclaceae 13.8 0.07 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Proteobacteria Betaproteobacteria Rhodocyclales Rhodocyclaceae Thauera 10.4 0.06 0.00 0.00 0.00 0.00 0.00 0.12 0.00 0.00 0.00 0.37 0.00 Proteobacteria Deltaproteobacteria Incertae Sedis Syntrophorhabdaceae Syntrophorhabdus 0.00 0.00 0.60 0.59 0.00 0.00 0.26 0.00 0.71 0.29 0.00 0.00 0.05 Proteobacteria Deltaproteobacteria Desulfobacterales Desulfobacteraceae Desulfococcus 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.06 0.00 0.00 0.00 0.00 0.00 Proteobacteria Deltaproteobacteria Desulfobacterales Desulfobacteraceae 0.00 0.00 0.00 0.91 0.00 0.00 0.00 0.00 0.22 0.18 0.00 0.00 0.00 Proteobacteria Deltaproteobacteria Desulfobacterales Desulfobulbaceae Desulfobulbus 0.21 0.00 0.06 0.06 0.00 0.00 0.00 0.18 0.06 0.00 0.00 0.00 0.00 Proteobacteria Deltaproteobacteria Desulfovibrionales Desulfomicrobiaceae Desulfomicrobium 3.59 1.85 1.36 0.88 0.07 0.00 0.00 2.98 1.73 1.47 0.24 0.14 0.00 Proteobacteria Deltaproteobacteria Desulfovibrionales Desulfovibrionaceae Desulfovibrio 0.33 0.14 0.00 0.00 0.00 0.00 0.00 1.30 0.12 0.00 0.00 0.00 0.00 Proteobacteria Deltaproteobacteria Desulfuromonadales Desulfuromonadaceae Pelobacter 3.27 15.9 6.60 3.88 0.12 0.06 0.00 12.0 3.99 0.79 0.26 0.17 0.00 Proteobacteria Deltaproteobacteria Desulfuromonadales Desulfuromonadaceae 0.11 0.43 0.13 0.17 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Proteobacteria Deltaproteobacteria Desulfuromonadales Geobacteraceae Geobacter 4.00 0.00 0.00 0.00 0.00 0.00 0.00 0.39 0.00 0.00 0.00 0.00 0.00 Proteobacteria Deltaproteobacteria Desulfuromonadales 0.00 0.25 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Proteobacteria Deltaproteobacteria Syntrophobacterales Syntrophaceae Smithella 0.00 0.00 2.74 2.79 0.00 0.00 0.19 0.00 2.70 6.08 0.00 0.00 0.64 Proteobacteria Deltaproteobacteria Syntrophobacterales Syntrophaceae Syntrophus 0.43 1.33 0.14 0.18 0.40 0.43 0.00 1.31 0.32 0.97 1.76 1.43 0.12 Proteobacteria Deltaproteobacteria Syntrophobacterales Syntrophaceae 0.00 5.03 1.96 0.81 0.52 0.63 0.26 0.31 1.36 2.59 1.28 0.83 0.39 Proteobacteria Deltaproteobacteria Syntrophobacterales Syntrophobacteraceae Syntrophobacter 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.08 Proteobacteria Deltaproteobacteria Syntrophobacterales Syntrophorhabdaceae 0.00 0.00 0.00 0.00 0.31 0.42 0.00 0.00 0.00 0.00 0.05 0.16 0.00 Proteobacteria Deltaproteobacteria 0.00 0.36 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Proteobacteria Epsilonproteobacteria Campylobacterales Campylobacteraceae 1.23 0.00 0.00 0.00 0.37 0.17 0.00 0.08 0.00 0.00 0.05 0.00 0.00 Proteobacteria Epsilonproteobacteria Campylobacterales Campylobacteraceae Arcobacter 1.49 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Proteobacteria Epsilonproteobacteria Campylobacterales Campylobacteraceae Sulfurospirillum 1.51 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Proteobacteria Gammaproteobacteria Alteromonadales Shewanellaceae 1.34 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Proteobacteria Gammaproteobacteria Oceanospirillales Oceanospirillaceae 7.61 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Proteobacteria Gammaproteobacteria Oceanospirillales Oceanospirillaceae Marinobacterium 1.67 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Proteobacteria Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas 0.00 0.00 0.00 0.00 2.23 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Proteobacteria Gammaproteobacteria Pseudomonadales Pseudomonadaceae 3.80 0.29 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Proteobacteria Gammaproteobacteria Pseudomonadales 0.00 0.00 0.06 0.15 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Proteobacteria Gammaproteobacteria 0.00 0.00 0.00 0.00 0.11 0.00 2.69 0.00 0.00 0.00 0.31 0.20 0.46 Spirochaetae Spirochaetes Spirochaetales Leptospiraceae 0.00 0.32 0.83 0.24 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Spirochaetae Spirochaetes Spirochaetales Spirochaetaceae Spirochaeta 0.00 0.00 1.22 0.39 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Spirochaetae Spirochaetes 0.00 0.00 7.78 12.3 0.00 0.00 10.6 0.00 1.78 5.71 0.00 0.00 0.95

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Spirochaetes Spirochaetes Sphaerochaetales Sphaerochaetaceae Sphaerochaeta 0.00 2.42 0.00 0.00 0.00 0.00 0.00 0.71 0.16 0.00 0.00 0.00 0.00 Spirochaetes Spirochaetes Sphaerochaetales Sphaerochaetaceae 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.32 2.57 0.95 0.00 0.00 0.06 Spirochaetes Spirochaetes Spirochaetales Spirochaetaceae Treponema 0.00 0.15 0.00 0.00 0.06 0.00 0.00 3.95 0.00 0.00 0.38 0.21 0.00 Synergistetes Synergistia Synergistales Synergistaceae Thermovirga 0.00 0.13 0.30 1.03 1.11 0.82 1.48 0.06 0.07 0.32 1.04 0.81 0.61 Synergistetes Synergistia Synergistales Thermovirgaceae 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.06 0.07 0.32 1.04 0.81 0.61 TA06 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.06 0.34 0.00 0.00 0.11 Tenericutes Mollicutes 0.67 0.00 0.00 0.00 0.00 0.00 0.00 12.3 13.5 5.92 0.67 0.12 0.00 Tenericutes Mollicutes Acholeplasmatales Acholeplasmataceae 0.83 0.00 0.00 0.00 0.00 0.00 0.00 0.08 0.00 0.00 0.00 0.00 0.00 Tenericutes Mollicutes Acholeplasmatales Acholeplasmataceae Acholeplasma 0.64 0.00 0.00 0.00 0.00 0.00 0.00 4.65 3.71 0.86 0.00 0.00 0.00 Thermotogae Thermotogae Thermotogales Thermotogaceae Kosmotoga 0.16 0.00 0.00 0.00 0.20 0.38 0.00 0.33 0.00 0.00 1.77 1.18 0.00 Thermotogae Thermotogae Thermotogales Thermotogaceae 0.00 0.00 0.18 0.19 0.00 0.00 0.38 0.00 0.58 0.87 0.00 0.00 0.38 WS6 0.00 0.00 0.31 3.52 2.67 1.69 0.00 0.06 0.00 0.27 0.23 0.17 0.00 ‘Cloacimonetes’ 0.00 3.17 0.00 0.00 19.4 15.4 0.00 1.39 0.00 0.00 2.45 1.56 0.00 Unknown Bacteria 0.00 0.00 8.14 7.16 0.00 0.00 0.00 0.00 2.23 1.30 0.00 0.00 0.00 Unassigned 3.89 1.49 1.69 2.30 0.53 0.19 0.05 4.01 2.53 3.78 0.92 0.51 0.23 < 0.1% abundance 12.4 15.5 16.3 14.7 14.4 14.3 15.0 15.5 18.8 18.3 16.1 15.4 10.9

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APPENDIX E: SIGNATURE METABOLITE ANALYSIS TO DETERMINE IN SITU

ANAEROBIC HYDROCARBON BIODEGRADATION

Citation: Gieg LM, Toth CRA (2017b) Signature metabolite analysis to determine in situ anaerobic hydrocarbon biodegradation. In: Timmis KN (Ed) Handbook of Hydrocarbon and

Lipid Microbiology Series: Anaerobic Utilization of Hydrocarbons, Oils, and Lipids. Springer

International Publishing, New York, NY, pp. 1–30.

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METAGNEOMICS AND METABOLOMICS

Citation: Gieg LM, Toth CRA (2017a) Anaerobic biodegradation of hydrocarbons –

Metagenomics and metabolomics. In: Timmis KN (Ed) Handbook of Hydrocarbon and Lipid

Microbiology Series: Consequences of Microbial Interaction with Hydrocarbons, Oils and

Lipids: Biodegradation and Bioremediation Springer International Publishing, New York, NY, in production.

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APPENDIX G: COMMUNITY STRUCTURE IN METHANOGENIC ENRICHMENTS

PROVIDES INSIGHT INTO SYNTROPHIC INTERACTIONS IN HYDROCARBON-

IMPACTED ENVIRONMENTS

Cotation: Fowler SJ, Toth CRA, Gieg LM (2016) Community structure in methanogenic enrichments provides insight into syntrophic interactions in hydrocarbon-impacted environments. Front Microbiol 7:562.

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