University of Calgary PRISM: University of Calgary's Digital Repository

Graduate Studies The Vault: Electronic Theses and Dissertations

2014-01-29 Characterization of Aerobic Methane Oxidizing in Oil Sands Tailings Ponds

Saidi-Mehrabad, Alireza

Saidi-Mehrabad, A. (2014). Characterization of Aerobic Methane Oxidizing Bacteria in Oil Sands Tailings Ponds (Unpublished master's thesis). University of Calgary, Calgary, AB. doi:10.11575/PRISM/25266 http://hdl.handle.net/11023/1313 master thesis

University of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission. Downloaded from PRISM: https://prism.ucalgary.ca UNIVERSITY OF CALGARY

Characterization of Aerobic Methane Oxidizing Bacteria in Oil Sands Tailings

Ponds

by

Alireza Saidi-Mehrabad

A THESIS

SUBMITTED TO THE FACULTY OF GRADUATE STUDIES

IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE

DEGREE OF MASTER OF SCIENCE

DEPARTMENT OF BIOLOGICAL SCIENCES

CALGARY, ALBERTA

January, 2014

Alireza Saidi-Mehrabad 2014

Abstract

The current study for the first time investigated the potential methane oxidation capacity of the surface layers of oil sands tailing ponds in Alberta, which are anthropogenic methane sources.

This research by the aid of recently developed molecular analysis tools such as 16S rRNA gene pyrotag sequencing, Stable Isotope Probing, 16S rRNA and pmoA gene sequence analysis highlighted the presence of methanotrophic bacteria (mainly Gammaproteobacteria), in these

- tailings ponds, with potential methane oxidation activity ranging from 75.6 – 135.6 nmol CH4 ml

1 d-1. 16S rRNA pyrotag sequencing and construction of phylogenetic trees detected OTUs affiliated to the genus Methylocaldum present in all sampling sites and times (July/2011-

December/2011).

Later investigations resulted in the isolation of a novel strain dubbed “Methylobacter oleiharenae”, which is able to thrive at optimum pH of 8 and contains 729 specific genes not detected in closely related reference strains.

ii Preface

Parts of this work has been published with the following title “Saidi-Mehrabad A, He Z, Tamas

I, Sharp CE, Brady AL, Rochman FF, Bodrossy L, Abell G CJ, Penner T, Dong X, Sensen CW,

Dunfield PF. (2012). Methanotrophic bacteria in oilsands tailings ponds of northern Alberta.

International Society of Microbial Ecology Journal. 7:908-92.”

The contribution of the thesis author in the mentioned publication is as follows;

Alireza Saidi-Mehrabad:

 Processing the tailing samples (from the samples provided between July/2011-

December/2011)

 Microbial community analysis of the tailing ponds surface layers (from the samples

provided between July/2011-December/2011) via DNA extraction, analysis of the data

produced from the16S rRNA gene based pyrotag sequencing, constructing 16S rRNA

gene and pmoA gene phylogenetic trees, DNA-based stable isotope probing, analysis of

the data resulted from the pyrotag sequencing of the heavy SIP fractions (16S rRNA gene

based)

 Measuring the potential methane (CH4) oxidation rates via gas chromatography (GC/FID)

(from the samples provided between July/2011-December/2011)

 Constructed Table 1 (Summary of methane oxidation rates and methanotrophic

communities detected in tailings ponds and other sites at multiple sampling dates), Figure

1 (Phylogenetic tree based on 16S rRNA gene sequences of methanotrophic

iii ), Figure 2 (Phylogenetic tree based on partial-derived PmoA sequences of

Proteobacteria), Supplementary Figure 1 (Methane oxidation rate of pond B sampled in

August, 2011), Supplementary Table 2A-D, 2B, 2C, 2D (The top 25 OTUs of each

sample site based on % of total reads in 16S rRNA gene pyrotag sequencing analysis).

And has been presented in the following presentations and posters:

 Presented at departmental microbiology seminars. Topic of the presentations:

“Methanotrophic Bacteria Residing in Oil Sands Tailings Waste. (Canada. 2011-2012)

 Presented in a poster titled “Methane Oxidizing Bacteria in Surface Layers of Oil Sands

Tailings Ponds” at Canadian Society of Microbiologists Conference (Canada, June 2012)

 Presented in a poster titled “Methanotrophic Bacteria in Oil Sands Tailings Ponds of

Northern Alberta” at 13th International Society of Microbial Ecology Conference

(Denmark, August 2012).

 Presented at Hydrocarbon Metagenomics 2012 Conference, Topic of the presentation:

“Methane Oxidizing Activity in Oil Sands Tailings Ponds”. (Canada, October 2012)

 Presented at Genome Canada/Genome Alberta 2013 Conference. Topic of the

presentation: “Methylobacter ferrophilum, sp . nov. an aerobic bacteria isolated from an

oil sands tailings pond”. (Canada 2013)

The final section of this study and the extracted data are planned to be published with the

following titles “Saidi-Mehrabad A, Tamas I, Kim JJ, Rijpstra IC, Damsté JS, Dunfield

PF. (2013). Methylobacter oleiharenae, sp. nov., an aerobic methanotroph isolated from an

oilsands tailings pond.”

iv The mentioned thesis author has also contributed in the following publication;

“An D, Caffrey SM, Soh J, Agrawal A, Brown D, Budwill K, Dong X, Dunfield PF, Foght J,

Gieg LM, Hallam SJ, Hanson NW, He Z, Jack TR, Klassen J, Konwar KM, Kuatsjah E, Li C,

Larter S, Leopatra V, Nesbø CL, Oldenburg T, Pagé AP, Ramos EP, Rochman FF, Saidi-

Mehrabad A, Sensen CW, Sipahimalani P, Song YC, Wilson S, Wolbring G, Wong ML,

Voordouw G. (2013). Metagenomics of Hydrocarbon Resource Environments Indicates

Aerobic Taxa and Genes to be Unexpectedly Common. Environmental Science & Technology.

47:10708-10717.

v Acknowledgements

Foremost I would like to thank GOD almighty who led me to my advisor Dr. Peter Dunfield and his wonderful lab members. I would like to express my sincere gratitude from the bottom of my heart to him for providing me an opportunity, which comes once in life to accomplish my master study and research under his guidance by sharing his immense knowledge. I could not have imagined having a better mentor and lab mates for my master study.

I would like to include my thesis committee members: Professor. Michael Hynes and Professor.

Gerrit Voordouw in this acknowledgment and thank them for their leadership and insightful comments.

My sincere thanks also goes to the fund providers: Institute for Sustainable Energy, Environment and Economy (ISEEE), Genome Alberta, Genome Canada, Hydrocarbon Metagenomics group and Syncrude Ltd, particularly Tara Prenner. Beside the funding groups I would like to thank all these fabulous people which made this research possible such as metagenome analysis group from University of Calgary Visual Genomics Center Xiaoli Dong and Christoph Sensen, people at Core DNA sequencing facility, Wei-Xiang Dong (TEM Expert) from microscopy and imaging facility, Wah Lai (Rebecca) Lee from preparation room and all the special people from the office of the graduate studies specially Karen Barron, Christine Goodwin, David Bininda and Sophia

George.

I thank my fellow lab mates in Dunfield lab, especially Dr. Joong-jae Kim who never said no to my requests and always was present whenever I needed him, Dr. Allyson Brady for her

vi encouragement, Fauziah Rochman for being a good friend, Xianqing (Emily) Wang for her good and cheerful nature, Dr. Ivica Tamas, Gareth Jones, Christine Sharp, Roshan Khadka, Ilona Ruhl, and Evan Haupt.

Last but not least, I would like to thank my wonderful family for their unquestionable support and love throughout my life. I would like to send my gratitude to all my friends in and out of university of Calgary.

I should finish this section by thanking GOD almighty again for his spiritual support and guidance throughout the darkest and happiest day of my life that without his grace everything was impossible.

vii Dedication

“ Read! In the Name of your Lord, Who has created (all that exists), He has created man from a clot (a piece of thick coagulated blood) Read! And your Lord is the Most Generous, Who has taught (the writing) by the pen. He taught man that which he knew not.” (Quran 96: 1-4)

I dedicate this work to my father Dr.Mohammad Saidi-Mehrabad, my mother Nasrin Amel, my

bother Amir Reza Saidi-Mehrabad and Dr. Mohammad Sadek Eid (GOD bless his soul) whom

have changed my life once and for all.

“At about twenty-four miles from the Fork, are some bitumenous fountains; into which a pole of

twenty feet long may be inserted without the least resistance. The bitumen is in a fluid state, and

when mixed with gum or the resinous substance collected from the Spruce Fir, serves to gum the

canoes. In its heated state it emits a smell like that of Sea Coal. The banks of the river, which are

there very elevated, discover viens of the same bitumenous quality”

Sir Alexander Mackenzie, 1788

Alexander Mackenzie, Voyages from Montreal Through the Continent of North America to the Frozen and Pacific Oceans in 1789 and 1793 Vol. I (1902 ed.) and Vol. II (1903 ed.)

viii Table of Content

Abstract……………………………………………………………………………………..ii

Preface……………………………………………………………………………………...iii

Acknowledgments………………………………………………………………………….vi

Dedication………………………………………………………………………………….viii

List of Tables………………………………………………………………………………xiv

List of Figures and Illustrations……………………………………………………………xv

List of Symbols, Abbreviations, Nomenclature…………………………………………...xvii

CHAPTER ONE: GENERAL INTRODUCTION……………………………..1

1.1 Hypothesis……………………………………………………………………………....5

1.2 Research Objectives…………………………………………………………………….5

1.3 Experimental Design…………………………………………………………………....7

1.4 Study Site………………………………………………………………………….…….8

CHAPTER TWO: LITERATURE REVIEW……………………………….….10

2.1 Methane Gas (CH4) Linked to Global Warming…………………………………….....10

2.2 Microbial Origin of the Emitted Methane Gas from Tailings Ponds……………….….11

2.3 Aerobic Methane-Oxidizing Bacteria (MOB) as Natural Microbial Biofilters for Methane

Gas……………………………………………………………………………………….....13

2.4 Type I ……………………………………………………………..…...19

2.5 Type II Methanotrophs……………………………………………………………..….24

ix 2.6 Methanotrophs Affiliated to Verrucomicrobia, Candidate Division NC10 and

Methanosarcinales Family (Order of Methanomicrobia) of Phylum Euryarchaeota……..26

2.7 Methane Monooxygenase Enzyme (MMO)……………………………………….…..29

2.8 Particulate Methane Monooxygenase (pMMO) or Membrane Bound Monooxygenase

Enzyme………………………………………………………………………………….…31

2.9 Soluble Methane Monooxygenase Enzyme (sMMO)………………………………....32

2.10 Identification of Active Methanotrophs Using Stable Isotope Probing (SIP)…….….34

2.11 Conclusion…………………………………………………………………………....37

CHAPTER THREE: FIELD STUDY OF MLSB AND

WIP TAILING PONDS...... 38

3.1 Introduction……………………………………………………………………………38

3.2 Methods………………………………………………………………………….…….38

3.2.1 Sampling and the Surface Tailing Water Chemistry (MLSB and WIP)…………….38

3.2.2 Filtering…………………………………………………………………………...…41

3.2.3 DNA Extraction Procedure……………………………………………………….…44

3.2.4 Determination of the Genomic DNA Concentrations……………………………….45

3.2.5 16S rRNA Gene Pyrotag Sequencing…………………………………………….…46

3.2.6 Quantitative Insights Into Microbial Ecology (QIIME) Software (Version 1.3.0)….47

3.2.7 16S rRNA Gene-Based Phylogenetic Tree………………………………………….48

3.2.8 Metagenomic Sequencing of WIP Surface Water……………………………….…..49

3.2.9 Potential Methane Oxidation Rates………………………………………….………49

3.2.10 Potential Methane Oxidation Rates at Different Temperatures…………………....50

x 3.2.11 Stable Isotope Probing (SIP)……………………………………………………….51

3.2.12 Time Course SIP…………………………………………………………………...56

3.2.13 Bacterial Cultures (Direct Plating)………………………………………………....57

3.3 Cloning of PCR Products Generated with Taq DNA Polymerase………………….…60

3.4 Results and Discussion………………………………………………………………...62

3.4.1 pH of the Surface Water…………………………………………………………..…62

3.4.2 Active Microbial Communities Detected via 454 Pyrotag Sequencing……………..62

3.4.3 Active Aerobic Methane Oxidizing Community Detected via 454 Pyrotag

Sequencing……………………………………………………………………………...…63

3.4.4 Neighbor-Joining (NJ) 16S rRNA Gene Based Phylogenetic Tree Constructed from 16S rRNA Gene Pyrotag Sequencing Data…………………………………………………….70

3.4.5 Identification of Active Methanotrophs Using Stable Isotope Probing (SIP)……….73

3.4.6 Time Course Stable Isotope Probing Experiment…………………………………...77

3.4.7 Potential Methane Oxidation Rates………………………………………………….80

3.4.8 Potential Methane Oxidation Rates at Different Temperature Ranges……………...90

3.4.9 Bacterial Cultures and Approaches for the Characterization of Novel

Methanotrophs…………………………………………………………………….….……91

3.4.10 Approaches for Isolating Methylocaldum/Methylococcus Species…………….…..98

CHAPTER FOUR: TAXONOMIC DESCRIPTION OF METHYLOBACTER

OLEIHARENAE, SP. NOV., AN AEROBIC METHANOTROPH FROM AN

OIL SANDS TAILINGS POND...... 102

4.1 Introduction……………………………………………………………………………102

xi 4.2 Methods………………………………………………………………………………..103

4.2.1 Isolation and Growth Conditions………………………………………………….…103

4.3 Morphological and Bright Field Microscopic Characterization…………………….…104

4.4 Transmission Electron Microscopy (TEM)……………………………………………105

4.5 Carbon and Nitrogen Sources……………………………………………………….…107

4.6 Optimum pH, Temperature, Ammonium, Iron, Copper and NaCl…………………….108

4.7 Genome Sequencing of Strain XLMV4T………………………………………………110

4.8 Results and Discussion……………………………………………………………....…111

4.8.1 Isolation and Growth Curve……………………………………………………….…111

4.8.2 Phylogenetic Analysis of the Strain XLMV4T……………………………………….113

4.8.3 Morphological Characterization of Strain XLMV4T…………………………………116

4.8.4 TEM Images of the Strain XLMV4T…………………………………………………122

4.8.5 Carbon and Nitrogen Sources……………………………………………………...…122

4.8.6 Strain XLMV4T pH, Temperature, Ammonium, Iron, Copper and NaCl

Response……………………………………………………………………………………125

4.8.7 Genome of Methylobacter oleiharenae XLMV4 T………………………………...…126

4.9 Description of Methylobacter oleiharenae sp. nov………………………………..……134

CHAPTER FIVE: CONCLUSIONS…………………………………………………136

References………………………………………………………………………………..…139

Appendix 1: Total genomic DNA concentrations………………………………………….155

Appendix 2: 16S rRNA gene based 454 Pyrotag PCR mastermix recipe…………….……156

Appendix 3: Claculation for the percentage of methane consumption in 120 ml serum vials ……………………...…………………………………………….….…157

xii Appendix 4: Determination of the methane oxidation rates based on linear regression of methane -1 -1 mixing ratios (mol CH4/mol gas) in headspace in nmol CH4 ml d .………………..……158

Appendix 5: Medium for methanotrophic bacteria (Heyer et al. 1984)………………...…159

Appendix 6: Medium for methanotrophic bacteria (Heyer et al. 1984)……………….…..161

Appendix 7: 16S rRNA gene based colony PCR mastermix recipe………………………163

Appendix 8: pmoA gene based colony PCR mastermix recipe……………………….…...165

Appendix 9: LB-agar Medium in 1 L……………………………………………….…….167

Appendix 10: Graphs representing the decrease in methane percentage from tailing ponds WIP and MLSB from different month of sampling …………………………………..…..….....168

Appendix 11: Extrapolation of the methane oxidation rates to the entire water surface area of the MLSB tailing pond…………………..…...... 175

Appendix 12: Pre-prepared LB Broth (Sigma Life Science); 20 g dissolved in 1 L of H2O………………………………………………………………………………………...176

Appendix 13: Pre-prepared Nutrient Broth (BD); 8.0 g dissolved in 1 L of H2O……...... 176

Appendix 14: Medium R2A (pH 7)…………………………………………………...... 177

Appendix 15: The composition of the API 50 CH strip is given below in list of tests…...178

Appendix 16: Genome analysis of Methylobacter oleiharenae strain XLMV4T………....183

Appendix 17: Growth rate calculation the of strain XLMV4T …………………….….....192

xiii List of Tables

Table 2-1: Characteristics of Type I and Type II methanotrophs in comparison to each other…………………………………………………………………………………………..23

Table 3-1: Chemical properties of both WIP and MLSB in more detail. ……….………….42

Table 3-2: Refractive index values of a CsCl gradient formed via ultragcentrifugation……55

Table 3-3: Tailing samples processed in the lab with the pH values measured upon receipt…………………………………………………………………………………….…..65

Table 3-4: Percentage of the total reads of methanotrophic bacteria detected via 454 Pyrotag sequencing………………………………………………. …………………………….….…69 . Table 3-5: Methane oxidation rates of tailing water samples (from August/2012) incubated at 45 o C with or without copper (CuSO4 in 1L) or vitamin B50 complex (50 mg/mcg of vitamin Bs) amendments. …………………………………….……………………………………….…100

Table 4-3: Summary genome statistics of strain XLMV4T available on the JGI/IMG web page…………………………………………………………………………………….……133

xiv List of Figures and Illustrations

Figure 1-1: The model illustrates our hypothesis surrounding potential activity of aerobic methanotrophic bacteria in surface oxic zones of WIP and MLSB. ……………..………….…6

Figure 1-2: A satellite image of the Syncrude’s largest tailings pond Mildred Lake Settling Basin (MLSB) and West In-Pit basin (WIP). ……………………..……………………………….…9

Figure 2-2: Schematic traditional chemistry of methanotrophic bacteria. ……….…………..15

Figure 2-3: Proposed conversion of formaldehyde to carbon dioxide via tetrahydromethanopterin (H4MTP) pathway in serine cycle dependent methanotrophs (Alpharoteobacteria)…….……16

Figure 2-4: Schematic view of nitrogen transformations in methanotrophic bacteria.…….....20

Figure 2-5: Proposed methane oxidation pathway of Candidatus Methylomirabilis oxyfera from Candidate division NC10. ………………………………..…………………………………...28

Figure 2-6: Stable Isotope Probing and gradient fractionation of isotopically heavy DNA from light DNA…………………………………………………………………………………..…36

Figure 3-1: Tailing water samples from the aerated zone (oxic zone) of the WIP and MLSB were collected in 4-L sterile polycarbonate containers……………………………………………..40

Figure 3-2: Filtering apparatus used in our experiment for concentrating the solid particles of the water on 0.22-μm polyvinylidene difluoride (PVDF) filters………………………...…...…..43

Figure 3-3: Fractionation step of the SIP experiment…………………………………..……54

Figure 3-4: Percentage of the bacterial communities versus archaeal communities within the surface tailing samples from July_2011 until December_2011. ………………………….…..66

Figure 3-5: Bar graphs of relative abundances of different classes of Proteobacteria within the surface tailing samples………………………………………………………………….…..…67

Figure 3-6: Neighbor-joining 16S rRNA gene based phylogenetic tree constructed based on 16S rRNA gene sequences …………………………….………………………………………..…72

Figure 3-7: Staple Isotope Probing analysis of the WIP_December_2011 Sample. …..…….74

Figure 3-8: Time course Stable Isotope Probing experiment on WIP (August/2012 sample). ……………………………………………………………………………..…………….……78

Figure 3-9: An example incubation showing the decrease in methane in the headspace of the WIP_August_2011 incubation over time. …………………………………………………....81

Figure 3-10: Potential methane oxidation rates of WIP and MLSB samples from July/2011 until

xv October/2011. …………………………………………………………………….…..….…...84

Figure 3-11: Temperature effect on methane oxidation rates. ..……………………….….…93

Figure 3-12: Theoretical rate of enzyme activity versus temperature. ………………...... …94

Figure 3-13: Comparison of methane oxidation rates at three different temperatures. ………………………………………………………………..………………………….....…95

Figure 3-14: A 16S rRNA based bootstrapped phylogenetic tree constructed based on the Treepuzzle method. ……………………………………………………………………...... …97

Figure 3-15: A pmoA/amoA gene tree built with NJ algorithm (built with the aid of distance matrix option of ARB) ……………………………………………..…………………..…....101

Figure 4-1: Growth curve obtained from strain XLMV4 T at 21oC………….…………...…112

Figure 4-2: 16S rRNA based NJ phylogenetic tree of the target strain XLMV4 T compared to reference methanotrophs. …………………………………………………………………...……....114

Figure 4-3: A pmoA/amoA gene based phylogenetic tree constructed using the NJ algorithm. …………………………………...………………………………………………………...…115

Figure 4-4: Methylobacter XLMV4 T cells stained with crystal violet and counterstained with safranin…………………... ………………………………………………………………….118

Figure 4-5: 1% Nile Blue staining of the heat-fixed cells …………….………..…………...119

Figure 4-6: XLMV4 T cells stained with waterproof black India ink (Pigment-based drawing ink). …………………….…………………………………………………………………....120

Figure 4-7: XLMV4 T cells negative for exospore formation after staining with 0.5% Malachite Green dye. …...…………………………………………………………………………..…..121

Figure 4-8: TEM image of XLMV4 T cell. ……………………………………………....…123

Figure 4-9: TEM image of XLMV4 T cell ………………………………….………..…..…124

Figure 4-10: Methylobacter XLMV4 T pH response. .………………………………...……128

T Figure 4-11: Methylobacter XLMV4 CuSO4 response. .…………………..………...……129

T Figure 4-12: Methylobacter XLMV4 FeSO4 response. .…………………..………...…….131

xvi List of Symbols, Abbreviations, Nomenclature

Symbol Definition

APIo American Petroleum Institute garvity AMO Ammonia Monooxygenase ANME Anaerobic Methanotroph AAM Ali_August_MLSB AAW Ali_August_WIP BTEX Benzene, Toluene, Ethylobenzene, and Xylenes BLAST Basic Local Alignment Search Tool -1 bpd barrels d CuMMO Copper containing monooxygenase enzyme CO2 Calvin-Benson Bassham cycle CH4 Carbon dioxide - CH3COO Methane CH3OH Acetate CH3NH2 Methanol CuMMO Methylamine CBB Copper containing monooxygenase enzyme CuSO4 Copper (II) sulfate C3H6O Propylene oxide DMSO Dimethyl sulfoxide DES DNase/Pyrogen-Free Water DAM December Sample_Ali_MLSB DAW December Sample_Ali_WIP d Day DSMZ Deutsche Sammlung von Mikroorganismen und Zellkulturen EDTA Ethylenediaminetetraacetic acid EC Enzyme Commission number FID Flame Ionization Detector FISH Fluorescence in Situ Hybridization Fae Formaldehyde Activating Enzyme Fhc formyl methanofuran:H4MPT formyltransferase complex FASTA FAST-All (a software) GHG Greenhouse Gas GC Gas Chromatography GAW Global Atmosphere Watch GB Gradient Buffer G Gauge GTC Guanidine Thiocyanate HPS 3-hexulose-6-phosphate synthase

xvii H4MTP Tetrahydromethanopterin - HCO 2 Formate HV High voltage HPR Hydroxypyruvate reductase IEA International Energy Agency ICUMSA International Comission for Uniform Methods of Sugur Analysis IMG Integrated Microbial Genomes JASW July_Ali_Surface water_WIP JAM July_Ali_MLSB JACW July_Ali_Center of the pond_WIP JGI Joint Genome Institute KEGG Kyoto Encyclopedia of Genes and Genomes KH2PO4 Monopotassium phosphate KACC Korean Agricultural Culture Collection KOH Potassium hydroxide KCl Potassium chloride MLSB Mildred Lake Settling Basin Mch Methenyl-H4MPT cyclohydrolase MDH Methanol Dehydrogenase MOB Methane Oxidizing Bacteria MMO Methane Monooxygenase Mt Mega tones MID Multiplex identifier MgSO4 Magnesium sulfate MLSBOALI MLSB_October_Ali MIF Microscopy and Imaging Facility MFT Maure Fine Tailings NO Dismutase Nitric oxide Dismutase Na2HPO4 Disodium phosphate NH4Cl Ammonium chloride NJ Neighbor Joining nD-TC Temperature-corrected refractive index reading OH Hydroxide

OTUs Operation Taxonomic Units OD Optical Density OsO4 Osmium tetroxide pMMO Particulate Methane Monooxygenase PLFA Phospholipid fatty acids PCR Polymerase Chain Reaction PHI 6-phospho-3-hexuloisomerase PQQ Pyrroloquinoline quinone PEG Polyethylene glycol PHB Polyhydroxybutyrate

xviii PVDF Polyvinylidene difluoride QIIME Quantitative Insights Into Microbial Ecology r.p.m Revolutions per minute RuMP Ribulose Monophosphate Pathway ROS Reactive Oxygen Species SCO Synthetic Crude Oil -2 SO4 Sulfate SAGD Steam Assisted Gravity Drainage sMMO Soluble Methane Monooxygenase SDS Sodium dodecyl sulfate SIP Stable Isotope Probing TM Culture Plates Made from MLSB Tailings Water TW Culture Plates Made from WIP Tailings Water TEM Transmission Electron Microscopy TCA Tricarboxylic Acid Cycle WCSB Western Canadian Sedimentary Basins WIP West In-Pit basin Wm-2 Watts per square meter WMO World Meteorological Organization WIPOALI WIP_October_Ali

xix

Chapter One: General Introduction

When for the first time European fur traders in 1778, led by Peter Pond, expanded their expeditions into pristine areas of Canadian boreal ecozones of the Athabasca territory, they noticed that first nation hunters were using some type of tar-like condensed black substance from the Athabasca river’s littoral zones in order to insulate their birch bark canoes [1 - 3]. At present this black condensed substance is technically known as bituminous sands, or colloquially oil sands and by comparison with non-degraded oil (> oAPI 30) is defined as naturally occurring semi-solid and heavily biodegraded hydrocarbons, which are comprised of 12 -20 % sands, 30 -

60% clay, 5 - 10% water and 2 -18% bitumen [4].

The bitumen is a mixture of high-molecular weight hydrocarbons such as asphaltenes (21%), aromatic compounds (21%) and cycloparaffins displaying high polarity (41%) and low API gravity (4-10o). These features indicate a high viscosity and density of the oil sands (compared to conventional crude oil), hence it is classified as an unconventional type of oil, which will not flow unless heated or diluted with lighter hydrocarbons. There are many theories surrounding the origin of the oil sands but geological evidence suggests that they originated in highly organic saturated Cretaceous shale and the underground pressure coated the oil with the surrounding sediments [5]. As many man-made technologies require coal, natural gas, and oil, these energy sources continue to play a vital and strategic role in driving the economy in North America and the world.

1 The largest oil sand deposit in the world is located within the Western Canadian Sedimentary

Basins (WCSB), covering an area approximately 1165494.65 km2 (450,000 mi2) of four Canadian western provinces and parts of southwest corner of the Northwest Territories (National Energy

Board of Canada. http://www.drummondconsulting.com/CSPG95.PDF). Southwest Manitoba, southern Saskatchewan, Alberta, and northeastern British Columbia are within the hydrocarbon- rich WCSB area, which includes 142,200 km2 of Canadian boreal forests

(http://www.oilsands.alberta.ca/). Venezuela’s Orinoco territory (Orinoco Belt) is recognized as the second most abundant oil sand deposit in the world. Due to discrepancy surrounding the true nature of Orinoco tar sands; it is not well categorized within the World Energy Council’s definition of natural bitumen. From the petroleum chemical perspective, Venezuela’s bitumen consist of 53% cycloparaffins, 12% aromatics, and 35% paraffins instead of complex cyclic and branched aliphatic compounds, with a low concentration of acyclic and straight chain paraffins, which are the characteristics of the Canadian Athabasca oil sands.

The International Energy Agency (IEA) recognizes and lists the Fort McMurray oil sands, located in the province of Alberta, as the largest petroleum mining project in world with an

10 3 estimated 169-178 billion barrels (2.83 × 10 m ) of recoverable bitumen, and a total amount of

2.5 trillion barrels in the WCSB area [6 - 13]. Based on the 2009 Alberta Energy report, synthetic crude oil production from Athabasca oil sands is expected to rise from the current value of 2 million bpd to 3 million bpd by the year 2018 [14].

Due to the viscous nature of bitumen, it is not useable prior to extraction, refining and upgrading processes such as coking and catalytic hydrotreating procedures [15]. These methods are intended to lower the viscosity of the natural bitumen and remove about 90% of O, S, N2 and heavy metals

2 in order to protect the equipment used during refining process from these detrimental contaminants [15]. The product of the processed oil sands bitumen is synthetic crude oil (SCO)

(lighter hydrocarbons), which will pass through further refining steps in order to be converted into transportation fuels where it is most needed [13].

Oil sands are recovered via two main methods in Alberta: 1) surface mining and 2) Steam

Assisted Gravity Drainage (SAGD), which involves continuous injection of hot high-pressure steam for the purpose of reducing the viscosity of bitumen and increasing its flow rate [16]. Based on the geological properties of the Athabasca oil sands (Fort McMurray formation) and the fact that they are mainly water wet and sufficiently accessible in the top 60 m (200 feet) of the ground, surface mining is economically feasible, however only 4,802 km2 (14 × 109 m3) of

Canadian oil sands are surface minable (10-20% of resource) [5, 6, 17, 18].

The surface mining technique, which is economically feasible up to a depth of 130 m, involves four main steps: 1) Remove muskeg, 2) Dig up oily sand with large trucks and shovels, 3)

Transfer oil sands into a crusher, 4) Add large volumes (15-20) of hot (79-93 oC) and caustic water containing 150-300 tones of naphtha compounds [21]. Naphtha compounds, which are mixture of hydrocarbons with 15-20 carbon atoms are used in order to separate the oil from sand particles in massive separation vessels (by increasing the pH). The latter extraction method is also referred to as Clark’s hot water digestion and flotation method mixed with chemical treatments [19 – 22].

At the end of the open pit extraction process large volumes of hot and caustic wastewater (slurry tailings) consisting of silt, clay, crystalline silica, quartz, unrecoverable bitumen, naphtha diluents and other types of mineral suspensions are produced [11, 23]. During extraction of one barrel of

3 bitumen mixed with 3 m3 of water, 4 m3 of tailings is produced. On a larger scale an approximate production rate of 250,000 barrels of bitumen day-1 will produce 1,000,000 m3 tailings day-1.

Currently there are no efficient applicable technologies for reducing tailings water (several methods are under investigation) and Canadian oil sands operators are obligated to follow a zero waste discharge policy [24]. This slurry water is pumped into massive settling basins, and during settling it gradually divides into different layers due to the settling of the fine solids [11, 24, 25].

Particles are allowed to settle in order to draw off the surface pond water for reuse in the extraction process, which will result in limiting the fresh water use from the river (mainly from

Athabasca river) [12].

In late 1999 and early 2000 methane emissions were observed from two tailing ponds managed by Syncrude Ltd. (http://www.syncrude.ca/users/folder.asp). Tailing ponds may have a large impact on greenhouse gas emissions, and they are classified as terrestrial methane sources by

[10] Environment Canada in their 2012 report . Methane is second only to carbon dioxide (CO2) as the most important greenhouse gas (GHG). However, in a scale of 100 years per mass has a heat- trapping pontential of 34 times higher than CO2 in trapping infrared waves in the stratosphere layer (IPCC fourth assessment report: climate change 2007 (AR4)) due to features such as its

[26] long atmospheric lifetime (shorter than CO2) .

4 1.1 Hypotheses

We hypothesized that oxic surface zones of tailing ponds Mildred Lake Settling Basin and West

In-Pit Settling Basin supports aerobic methane oxidizing bacteria (methanotrophs). As part our hypothesis we proposed that these bacteria are actively consuming some portion of the produced methane as their only source of cellular energy and moreover their community structure and methane oxidizing activity might vary due to change in environmental temperature. The potential mitigating effect of methanotrophs on the release of methane to the atmosphere from tailings ponds is not currently known [12] [Figure 1-1].

1.2 Research Objectives

This Master’s thesis will mainly focus on:

 Identification of the most abundant methanotrophic bacteria in the surface layers from

MLSB and WIP tailings ponds.

 Determining the rates of methane oxidation from both sites at various times of the year

 Identification of the active methanotrophic bacteria based on Stable Isotope Probing (SIP)

analysis [27].

 Isolation of methanotrophs within the surface layer of MLSB and WIP and

characterization of their physiology and genomes to potentially address the need for more

effective approaches in controlling anthropogenic emissions of CH4.

Characterization of the type and activity of aerobic methane oxidizing bacteria within the upper aerobic layer of tailings ponds will be the main subject of investigation in this study.

5

Figure 1-1. The model illustrates our hypothesis surrounding the potential activity of aerobic methanotrophic bacteria in surface oxic zones of WIP and MLSB. Methanotrophs may play an important role in mitigating methane efflux from the microbial anaerobic methanogenic system into the atmosphere. Zone one is the aerated recycled water cap and zone two is anoxic zone, primarily composed of Mature Fine Tailings (MFT). The figure was drawn based on data from reference; Siddique T et al. (2012) [25].

6 1.3 Experimental Design

The experimental design of this study consists of three main steps:

i) Molecular community analysis (via DNA fingerprinting methods)

Due to the limitations of traditional standard microbial culture techniques in accessing the actual microbial diversity and biomass in natural ecosystems, we employed cultivation-independent molecular methods based on the 16S rRNA gene and pmoA gene (gene encoding the alpha subunit of the particulate methane monooxygenase enzyme). The main fingerprinting technologies used in this study are DNA-based Stable Isotope Probing, and pyrosequencing analysis of PCR-amplified genes via 454 FLX instrument (FLX titanium Series Kit, XLR70).

ii) Potential methane oxidation rates

The methane oxidation rate was measured by incubating tailings pond water in closed bottles over several days and following the decline in methane via gas chromatography using a Flame

Ionization Detector (FID).

iii) Bacterial isolation and culturing for genomic studies

Tailing waters from both study sites were inoculated onto a series of mineral medium plates and were incubated in a large desiccator under an amended atmosphere of 20% CH4 (v/v) and 5-10%

CO2 (v/v) balanced in air. Methanotrophic bacteria were isolated and characterized, including by complete genome sequencing.

7 1.4 Study Site

The Mildred Lake Settling Basin (MLSB), approximately a 40-year-old pond, is Syncrude’s

(http://www.syncrude.ca) largest operational tailings pond, with a water surface area of 10-13 km2 and a volume of about 200 million m3 of tailings (Syncrude, 2010) [12] [Figure 1-2].

The MLSB is located in the Athabasca oil sands mining site near Fort McMurray in northeastern

Alberta about 60-km west of the Saskatchewan border and 435 km northeast of Edmonton [5].

The West In-Pit Settling Basin (WIP) is an approximately 20-year-old pond close to MLSB [28].

Both ponds showed ebullition of methane gas in the early 2000s [28].

Estimated methane emission rates from the surface of MLSB based on three separate studies in

2000 (Holowenko et al.), 2007 (Clearstone Engineering Ltd.), and 2008 (Siddique et al.)

-1 [22, 28, 29] respectively were reported within the range of 400 million L CH4 d .

8

Figure 1-2. A satellite image of the Syncrude’s largest tailings pond Mildred Lake Settling Basin

(MLSB) (Latitude: 57°03'N and Longitude: 111°38'W) and West In-Pit basin (WIP) (Latitude:

57°0033.14'N and Longitude: 111°3725.26'W). Image taken from Google Earth (Public Domain

Image).

9 Chapter Two: Literature Review

2.1 Methane Gas (CH4) Linked to Global Warming

Methane (CH4) is a simple tetrahedral molecule (simple alkane) with an average atmospheric lifetime of 10-11.1 years and in this time period it is removed via soil processes (5% of the total sink), and destruction via oxidation in the stratosphere and troposphere layers by hydroxyl radicals (OH) (95% of the total sink in the presence of intense sun light) [26, 30]. Methane has an ability to shift the Earth’s radiative balance from its equilibrium state by direct contribution of 0.5

Wm-2 (Watts per square meter) to total radiative forcing and plays a role both directly and indirectly in atmospheric chemistry, tropospheric ozone destruction, stratospheric water vapor production and ultimately climate forcing [26, 30].

Methane and carbon dioxide are two key players in global warming and have been monitored closely under the umbrella of the World Meteorological Organization (WMO) or Global

Atmosphere Watch (GAW) (http://www.wmo.int/pages/prog/arep/gaw/gaw_home_en.html), which directly report the global methane and carbon dioxide budget to the World Data Center for

Greenhouse Gases database (http://ds.data.jma.go.jp/gmd/wdcgg/index.html) [31, 32]. It is noteworthy that the atmospheric methane concentration increases about 1% every year [33].

10 2.2 Microbial Origin of the Emitted Methane Gas from Tailings Ponds

In 2000 Holowenko and colleagues demonstrated that methane emissions from tailings ponds are microbial in origin [28]. Their model suggests that after the formation of different layers within the tailings ponds, which form over a period of time as heavy particles (sands) sink to the bottom with a faster rate (based on molecular mass) compared to light compounds (such as clay), due to microbial activity the deeper portion of the basin becomes O2 depleted and provides an anoxic, organic-rich environment conducive for anaerobic methanogenic activity [Figure 1-1].

Enumeration revealed 105 – 106 methanogens g-1 tailings [28].

Siddique et al. (2008) applied zero-order and first-order kinetic models to estimate the methane flux. They concluded that the main methanogenic substrates were naphtha compounds (in Mature

Fine Tailings) instead of bitumen. Large concentrations of benzene, toluene, ethylbenzene, and xylenes (BTEX) are used in the naphtha diluent. They estimated the biologically active volume of

MLSB tailings at about 50 million m3 [22].

Microbial ecology studies identified microorganisms from both Archaea and Bacteria Domains, supporting methanogenesis activity within MLSB oil sands tailings ponds via a complex network of synthrophic associations [Figure 1-1] [11, 22, 28]. Syntrophy or syntrophic metabolism involves distinct microorganisms in a close beneficial contact for exchanging metabolites, and plays an essential role as an intermediary step in biodegradation of alcohols, fatty acids, aromatic compounds, amino acids and wide range of sugars [34]. Microorganisms in syntrophic consortia are believed to be well adapted to energetically stressed lifestyles (energy-yielding reactions used

[34] by methanogens is in the range of -130.4 - 36 kJ/mol CH4) .

11 Penner et al. (2010) highlighted the presence of sequences affiliated to anaerobic

Betaproteobacteria, a small fraction of Gammaproteobacteria, sulfate-reducing

Deltaproteobacteria, Firmicutes, and traces of acetoclastic Methanosaeta in MLSB tailing samples [11]. All these microbes could be grouped within three main metabolic groups, which are believed to be the fundamental structure of syntrophic associations in tailings ponds: i) Anaerobic hydrocarbon degraders, such as some members of the class Betaproteobacteria, initiate the metabolic pathway by oxidizing the naphtha compounds, ii) primary fermentative bacteria, such

- as Firmicutes ferment substrates produced by the first group to acetate (CH3COO ), CO2, formate

- (HCO 2), and hydrogen (H2). iii) Methanogens such as Methanosaeta complete the process in the absence of any electron acceptors by converting acetate, formate, hydrogen, and CO2 to CH4

[Figure 1-1] [11, 25, 35, 36].

Although in-depth studies are being conducted and recognize syntrophy as an essential element in complex hydrocarbon degradation, the key microorganisms are still not well characterized. The complexity of oil and naphtha components could possibly complicate the study of the syntrophic partners [37]. Methane produced in the anoxic lower regions of the tailings ponds diffuses into the upper layers or is emitted via ebullition [38].

12 2.3 Aerobic Methane-Oxidizing Bacteria (MOB) as Natural Microbial

Biofilters for Methane Gas

Methylotrophs are capable of obtaining energy from highly reduced 1-carbon sources (adapted to

C1 metabolism) such as methanol (CH3OH), methane (CH4), methylamine (CH3NH2), and

- formate (HCO2 ). One sub-group of methylotrophs are the methane oxidizing bacteria (MOB) or methanotrophs, originally isolated by Dutch microbiologist Söhngen in 1906 (recorded under the name of ‘Bacillus methanica’) [59, 62].

MOBs exist in oxic-anoxic interfaces of any system with methanogenesis activity such as wetlands, rice paddies and landfills, and also where methane is emitted via abiotic process such as hydrothermal vents and oceanic natural gas seeps. Methanotrophic bacteria are distinguished from other microorganisms by the ability to kinetically overcome the stability of highly reduced methane molecules and consume it as their only source of energy [39, 40, 41]. These microbes act as methane biofilters in the ecological niches they populate [42].

The majority of known methanotrophic bacteria belong to the phylum Proteobacteria and based on morphological, physiological and phylogenetic characteristics they are divided in to two main classes: type I methanotrophs (Gammaproteobacteria) and type II methanotrophs

(). Methane oxidizing bacteria have been recently discovered outside of the

Proteobacteria in the phylum Verrucomicrobia and candidate division NC10 [43, 44].

The basic biochemistry of proteobacterial methanotrophs is that methane monooxygenase enzymes (MMO) (in form of pMMO or sMMO, described in the section 2.7 below) initiate the

13 first step by converting methane (CH4) into methanol (CH3OH). Methanol is converted into formaldehyde via methanol dehydrogenase (MDH), which consists of a 67 kDa large subunit encoded by the mxaF gene and a 8.5 kDa small subunit encoded by mxaI gene. Together the subunits form an 22 tetramer, classified under the quinoprotein enzymes (the enzyme contains the pyrroloquinoline quinone [PQQ] cofactor) [45, 46]. Perplasmic soluble cytochrome cL (the specific electron acceptor of MDH encoded by mxaG) accepts the electron from MDH and is oxidized by another perplasmic soluble class I cytochrome cH. Formaldehyde enters into either the serine cycle (type II methanotrophs or Alphaproteobacteria) or ribulose monophosphate pathway (RuMP) (type I methanotrophs or Gammaproteobacteria), to be fixed into cell carbon,

- or it is directly converted into formate (HCO2 ) via the activity of formaldehyde dehydrogenase.

The final step of methanotrophy involves oxidation of formate coupled to reduction of NAD+ or

NAD(P)+ by formate dehydrogenase leading to the production of carbon dioxide [45] [Figure 2-2].

There have been some recent modifications of this traditional scheme. Recent transcriptomic studies of the model methanotrophs suggested that in contrast to previous models, formaldehyde is not the branching point for serine-cycle dependent methane oxidizers (type II methanotrophs or

Alphaproteobacteria); instead formate is the branching point [47, 48]. Instead of formaldehyde dehydrogenase necessary for formaldehyde oxidation in serine-cycle dependent methane oxidizing bacteria (type II methanotrophs or Alphaproteobacteria) , a tetrahydromethanopterin

(H4MTP) pathway was proposed to be the key pathway for formaldehyde oxidation and detoxification via a novel enzyme, Formaldehyde Activating Enzyme (Fae), which makes the

[49 - 51] conversion of cytoplasmic formaldehyde possible via H4MTP [Figure 2-3] .

14

Figure 2-2. Schematic traditional chemistry of methanotrophic bacteria. MMO initiates the first step by converting methane into methanol. Methanol is oxidized to formaldehyde via methanol dehydrogenase. Formaldehyde enters into either the serine cycle or RuMP cycle, at the end it will be converted into formate via the activity of formaldehyde dehydrogenase and finally formate deydrogenase leads to the production of carbon dioxide. In the graph; 1) Methane monooxygenase (pMMO or sMMO form of the enzyme). 2) Methanol Dehydrogenase 3)

Formaldehyde Dehydrogenase 4) Formate Dehydrogenase.

15 CH3OH MDH 1 CH2O

2 CH2O

H4MPT Fae

CH2=H4MPT + NAD(P) MtdB/MtdA

NAD(P)H + CH=H4MPT H2O Mch CHO-H MPT MFR 4 H MPT 4 CHO-MFR Ftr/hydrolase-complex (Fhc) H2O MFR HCOOH NAD+ FDH NADH CO2

16 Figure 2-3. Proposed conversion of formaldehyde to carbon dioxide via tetrahydromethanopterin

(H4MTP) pathway in serine cycle dependent methanotrophs (Alpharoteobacteria). In the figure, produced formaldehyde from the activity of methanol dehydrogenase (MDH), migrates from the periplasm (shown with star [1]) into the cytoplasm of the methanotroph (shown with star [2]). A novel enzyme, Formaldehyde Activating Enzyme (Fae) converts the cytoplasmic formaldehyde into methylene-H4MPT by the aid of dephosphorylated form of the H4MPT. Produced

+ Methylene-H4MPT by the aid of NADP -dependent Methylene-H4MPT dehydrogenase becomes

+ oxidized to methenyl-H4MPT . Later methenyl-H4MPT cyclohydrolase (Mch) hydrolyses the

+ methylenyl-H4MPT to formyl-H4MPT. The formyl group is then transferred to a postulated methanofuran via formyl methanofuran:H4MPT formyltransferase complex (Fhc) and at the end formate is formed. Resulting formate is then converted into CO2 via formate dehydrogenase. The figure was developed based on references; Vorholt et al. (2000) and Pomper et al. (2002) [50, 51].

17 Although methanotrophs and ammonia oxidizing bacteria group only distantly to each other in a

16S rRNA gene-based phylogenetic tree, which indicates their evolutionary distance, the methane and ammonia monooxygenase genes are closely related. pMMO and AMO (ammonia monooxygenase) both descended from a common ancestral copper containing monooxygenase enzyme (CuMMO) [52, 59]. sMMO does not share the same ancestor as pMMO and AMO but is instead affiliated to the soluble di-iron monooxygenase family of the enzymes [52].

Similar molecular structure of methane monooxygenase to ammonia monooxygenase in some

MOB species provides a window for these methane oxidizers to be considered as weak nitrifiers

[32, 53, 54] in the presence of CH4 (although they are not able to grow on NH3 alone) [Figure 2-4].

The existence of nitrogen metabolism genes haoB and cytL (encodes for enzymes involved in oxidation of hydoroxylamine to nitrite), cytS (encodes for enzymes involved in reduction of nitric oxide from hydroxylamine), nirS and nirK (encodes for enzymes involved in reduction of nitrite to nitric oxide), norB and norC (encodes for an enzyme involved in nitric oxide reductase activity) have been seen in some methane oxidizing bacteria [32, 53, 54].

This co-oxidation of ammonia has detrimental side effects on the microorganism’s activity due to increased concentration of toxic hydroxylamine in the cell (only ammonia oxidizers are able to use hydroxylamine as an energy source not methane oxidizers). Methanotrophs do not obtain energy from dissimilatory nitrogen metabolism, but some are able to produce homologues to hydroxylamine oxidoreductase [32, 52]. This beneficial detoxifying system guarantees their survival and confers a potential competitive advantage over other methanotrophs in high-ammonium environments [32, 52].

18 Based on a recently developed model by Criddle and colleagues (2013) it seems that the majority of Alphaproteobacteria methanotrophs are capable of reducing hydroxylamine to ammonium in high concentrations. Most of Gammaproteobacteria methanotrophs are unable to reduce hydroxylamine; instead they oxidize this toxic compound into nitrite, which is also an inhibitory compound [55].

2.4 Type I Methanotrophs

Gammaproteobacteria methanotrophs or type I methane oxidizing bacteria phylogenetically belong to the Methylococcaceae family. They possess complex internal membranes. Based on an old functional-taxonomic classification they were branched in two deeper groups of type Ia (e.g.

Methylobacter, Methylomicrobium, Methylomonas and Methylosarcina) and type Ib (or type X)

(e.g. Methylococcus and Methylocaldum) [39, 45]. 12 out of 16 of validly described genera of

MOBs are classified within type I group [39, 56]. Type I group contains ecologically diverse methanotrophs such as thermophilic Methylothermus, Methylococcus and Methylocaldum with optimal growth between 45-60 oC.

Methylococcus capsulatus strain Bath (discovered in hot springs of Bath, England) is the most widely used model for microbiological study of methanotrophy due to possession of both forms of the methane monooxygenase enzymes, which are described in later sections. M. capsulatus is highlighted as a potential microbe for single-cell protein production, particularly in Norferm

Danmark’s bioreactors with 8000 tons year-1 of bioprotein production. Norway has recently reported increase in production line up to 40,000 tons year-1 [57].

19

1 2 - NH3 NH2OH NO2

4 6

2 5

NO

3

N2O

Figure 2-4. Schematic view of nitrogen transformations in methanotrophic bacteria. There are variations in nitrogen uptake in isolated methanotrophs. Enzymes are as follows; 1) pMMO/sMMO, 2) Hydroxylamine oxidoreductase 3) Nitric oxide reductase 4) Nitrite reductase

5) Hydroxylamine reductase, 6) Assimilatory nitrite reductase. The figure was drawn based on data from reference; Stein LY et al. (2011) [32].

20 Siberian tundra soils reveled the presence of the most psychrophilic methanotroph yet described.

Methylobacter psychrophilus showed optimum growth at 5-10 oC [58]. Psychrotolerant and psychrophilic methanotrophs (Methylobacter psychrophilus, Methylosphaera hansonii,

Methylomonas scandinavica) are the only known strong biological sink for methane in salty

Antarctic lakes, which harbor substantial amounts of methane gas [59, 60].

Crenothrix spp, which has been observed for the first time by Ferdinand Cohn 142 years ago

(Crenothrix polyspora Cohn) and concerned microbiologists for a long time as a problem microbe in drinking water systems (production and supply), along with Clonothrix spp, discovered by Roze (117 years ago; Clonothrix fusca Roze) are two unusual filamentous methane oxidizers. These filamentous methanotrophs have been recently phylogenetically grouped as a subset of Methylococcaceae family although originally classified under a validated family name of Crenotrichaceae. They possess elaborate internal membranes and can use methane as the sole cellular energy source due to the activity of key enzymes for methanotrophy [39, 61 - 63].

Key features that separate the Gammaproteobacteria from Alphaproteobacteria methanotrophs are the carbon fixation route of Ribulose monophosphate pathway (RuMP) (including two key diagnostic enzymes 3-hexulose-6-phosphate synthase (HPS) as well as 6-phospho-3- hexuloisomerase (PHI)), GC content of 43-65 (mol%), and major PLFAs of 14 and 16 carbons,

[64] [Table 2-1]. The table has been modified from Semrau et al. (2010) and Dunfield et al. (2001)

[59, 64].

Initially it was believed that all the members of Methylococcaceae family are obligate methylotrophs unable to use multi carbon compounds as their sole cellular energy source, but

21 recent radio-labeling experiments identified Crenothrix polyspora as a non-obligate methanotroph with acetate uptake ability in the absence of methane [39][59][62].

Type I methanotrophs are the only characterized methanotrophs affiliated to endosymbiont associations detected in the gill tissue of cold seep mussels, and other hosts such as sponges, snails and tubeworms [45, 56, 65]. They are easily culturable from marine environments, especially

Methylomicrobium spp and Methylobacter spp [59, 66]. Dominance of Type I group over Type II group has been observed in soda lakes and recent 13C-DNA studies from two hypersaline lakes

(Lake Suduntuiskii Torom and Lake Gorbunka) suggested the probable role of type I methanotrophs as the main methane oxidizers in such environments (detected methanotrophs were mainly related to strains of Methylomicrobium, Methylobacter, Methylomonas and

Methylothermus) [166]. The first isolated alkaliphilic methanotroph (from Tuva soda lakes),

Methylomicrobium alcaliphilum is related to gammaproteobacterial methane oxidizers [167].

Methylohalobius crimeensis 4Kr (with 0.2-2.5 M of optimum NaCl) and Methylohalobius crimeensis 10KiT (with 0.2-2.5 M of optimum NaCl) species of Gammaproteobacteria class are the only known halophilic methanotrophs [186].

22 Table 2-1. Characteristics of Type I and Type II methanotrophs in comparison to each other.

Phylum and Class Proteobacteria (Gammaproteobacteria) Proteobacteria (Alphaproteobacteria)

Genera Methylococcus, Methylocaldum, Methylobacter, , Methylosinus, ,

Methylohalobius, Methylothermus, Methylosoma, Methylocapsa, Methyloferula

Methylomicrobium , Methylomonas,

Methylosarcina, Crenothrix, Clonothrix,

Methylosphaera

Lowest Reported Growth (pH) 5.0 (many species) 4.2 (Methylocapsa acidiphila)

Highest Reported Growth (pH) 11 (Methylomicrobium buryatense) 9.5 (Methylocystis sp. strain B3)

Lowest Reported Growth (oC) 0 (Methylosphaera hansonii) 4 (Methylocella silvestris)

Highest Reported Growth (oC) 72 (Methylothermus sp. strain HB) 40 (many species)

Highest Reported Growth (Salinity in M) 2.5 (Methylohalobius crimeensis) 0.3 (many species)

RuMP Pathway + _

Serine Pathway Varies Between Species +

Rubisco Rarely -

sMMO Varies Between Species Varies Between Species

pMMO + Varies Between Species

Nitrogen Fixation Varies Between Species Varies Between Species

Geometric Arrangement of Intracellular Membranes Bundles of disks perpendicular to cell periphery Membrane stacks parallel to cell periphery.

Methylocapsa – membrane vesicles parallel to one

side of cell membrane. Methylocella – cytoplasmic

membrane invaginations

Carboxysome-Like Structures or Vesicles - -

Signature PLFAs 14:0; 16:0; 16:15t; 16:16c; 16:17; 16:17c; 18:17c; 18:18c

16:18c; 18:17

Resting Stage Varies - Cysts or Non Varies – Cysts, Exospore or None

G+C Content (mol%) 43-65 60-63

Facultative Methanotroph Crenothrix Varies Between Species

23 2.5 Type II methanotrophs

Alphaproteobacteria methanotrophs are found in environments with pH ranging from neutral to mildly acidic. They are believed to be the most dominant methanotrophs populating terrestrial environments (especially Methylocystis spp) and they have been detected via cultivation- dependent and independent (metagenomic) approaches in diverse habitats [59, 64, 67]. They contain two families: and . Methylocystaceae contains the genera

Methylocystis and Methylosinus. The Beijerinkiaceae family includes the methanotrophs

Methylocella, Methylocapsa and Methyloferula. Methylosinus trichosporium OB3b is the model methanotroph representing the Alphaproteobacteria methane-oxidizing group.

Molecular surveys from four alkaline lakes; Mono Lake, USA with pH of 9.8 (8.5-9.5% salinity),

Lake Suduntuiski, Siberia with pH of 9.7 (0% salinity), Siberian Lake Gorbunka with pH of 9.5

(4% salinity) and Lake Khuzhirta, Siberia with pH of 10.2 (0% salinity), indicate that some

Alphaproteobacteria methanotrophs are adapted to halo/alkaliphilic waters [59, 68].

The discovery that Methylcella silvestris BL2 and some Methylocystis related species

(Methylocystis strain H2S) are not obligate methane oxidizers changed the concept of methanotrophs as only single-carbon utilizers [69].Methylocella silvestris is capable of incorporating multi-carbon compounds such as acetate, pyruvate, succinate, malate, and ethanol as energy sources [59, 69, 70, 71]. Most other methanotrophs can grow only on methane, methanol, and some methylated amines.

24 Alphaproteobactera methanotrophs use the Serine cycle or Calvin-Benson Bassham cycle (CBB)

(only Beijerinckiaceae family) for their carbon fixation. Based on this fact it was initially considered that in a complex methanotrophic community type II methane oxidizers will be outcompeted by methanotrophic type I microbes due to energetically less-efficient C-fixation pathway [39, 45, 72]. The evidence obtained from further studies conducted on oxic upland soils with high methane affinity, supports a blend of both classes (based on soil pH). Northern Sphagnum- dominated wetlands are mainly populated by the alphaproteobacterial Methylocystis (Number of cells per gram of wet peat detected via Fluorescence in Situ Hybridization [FISH] method with the aid of Mcyst-1273 probe) [67]. Henckel et al. (2000) demonstrated a constant population of alphaproteobacterial methanotrophs and a dramatic shift in gammaproteobacterial methane oxidizing population with methane fluctuations [73].

In general Alphaproteobacteria methanotrophs have a lower methane threshold for growth and survival compared to Gammaproteobacteria methanotrophs [52]. Type II methanotrophs also show N2 fixation capability, GC content of 60-67 mol%. A pH of 4.2-4.4 reported for the lowest pH for growth, pH of 7.5 reported for the highest pH for growth, 4-5 oC the lowest reported temperature for growth, 30-40 oC as the highest reported temperature for growth, PLFAs of 18 carbon in length, and the high ATP-demand Serine cycle or CCB cycle for carbon fixation [64]

[Table 2-1].

25 2.6 Methanotrophs Affiliated to Verrucomicrobia, Candidate Division NC10 and Methanosarcinales Family (Order of Methanomicrobia) of Phylum

Euryarchaeota

Newly discovered methanotrophic bacteria demonstrate different physiological properties from proteobacterial methanotrophs; however it seems that the main methane oxidation steps are still conserved in Verrucomicrobia and candidate division NC10 related methane oxidizers [52].

Candidatus Methylomirabillis oxyfera from Candidate division NC10 anaerobically initiates the methane oxidation pathway, but for the accomplishment of the pathway an oxygen molecule is required. Ettwig et al. (2008) proposed that a novel enzyme, NO dismutase was responsible for generating oxygen from nitric oxide (NO) and allowed the completion of methane oxidation aerobically via MMO enzyme [Figure 2-5] [44, 52].

Hallam, Thauer, Shima, and Chistoserdova argued that the only actual anaerobic methane oxidation process is carried out by the Methanosarcinales family of ANME-1, ANME-2, and

ANME-3, which were visualized for the first time via fluorescent in situ hybridization (FISH) method [52, 64, 74]. They proposed that anaerobic methane consumption proceeds via reverse

-2 methanogenesis using SO4 (sulfate) as the terminal electron acceptor. They indicated that

3+ 4+ - theoretically Fe , Mn , and NO 3 are also energetically suitable enough to act as electron

-2 [75 - 77] acceptors to provide a path for anaerobic methane oxidation instead of SO4 . Evidence obtained from methane seep sediments suggested a possibility of anaerobic oxidation of methane coupled to the reduction of iron and manganese [78].

26 Previous DNA based Stable Isotope Probing experiments on environmental samples using 13C methane as the main labeled substrate revealed the labeling of 16S rRNA gene sequences closely related to genera Acidobacteria, Flavobacterium and Verrucomicrobia. However the researchers involved in the mentioned experiments failed to assign any of the detected microorganisms to methanotrophy due to phylogenetic distance to known Alphaproteobacteria and

Gammproteobacteria methanotrophs or the possibility of cross feeding on isotopically labeled metabolites [79].

Three separate studies conducted by by Dunfield et al. (2007), Pol et al. (2007) and Islam et al.

(2008), reported characterization and isolation of unusual methanotrophs, with high activity at pH

1-2 [43, 80, 81]. These isolates did not belong to the phylum Proteobacteria. Discovery of these novel methanotrophs expanded the frame of methanotrophs beyond the Type I and Type II classes, into the diverse and widespread phylum Verrucomicrobia [82]. Initially isolated verrucomicrobial methanotrophs were named; Acidomethylosilex fumarolicum SolV,

Methylokorus infernorum strain V4 and Methyloacida kamchatkenesis strain Kam1. A later review of Op den Camp and colleagues (2009) classified these non-proteobacterial methanotrophs under the umbrella of a single proposed genus Methylacidiphilum [39]. As an example, Methylacidiphilum infernorum strain V4 (Methylokorus infernorum strain V4) demonstrates unusual methane oxidation activity such as favoring the autotrophic carbon fixation pathway, which might have made them hidden in previous studies such as 13C stable isotope probing surveys. It also contains unusual features such as; occupying extreme environments

(geothermal areas) with pH less than 1.0, 65 oC as the optimum temperature for growth, highly saturated membrane lipids, unusual carboxysome-like structures in the cytoplasm, and diverse groups of pmo operons [64, 72]

27

Figure 2-5. Proposed methane oxidation pathway of Candidatus Methylomirabilis oxyfera from

Candidate division NC10. Genes nirSJF/D/GH/L are all related to the nitrite reductase family and

MMO represents Methane monooxygenase enzyme. The question mark refers to NO dismutase, which paves the path for aerobic methanotrophy. The figure was drawn based on data from reference; Ettwig et al. (2008) [44].

28 Step by step investigation of carbon fixation pathways in Methyloacidiphilum infernorum strain

V4 revealed the absence of key enzymes for methanotrophs: hexulose-6-phosphate synthase (for producing hexulose 6-phosphate in RuMP cycle), hexulose-phosphate isomerase (plays a key role in RuMP cycle of formaldehyde fixation by producing D-ribulose 5-phosphate), 6- phosphogluconate dehydrogenase (an oxidative carboxylase capable of reducing 6- phosphogluconate into ribulose 5-phosphate via NADP), and phospho-3-keto 3 deoxygluconate aldolase (necessary enzyme for entering Entner-Doudoroff pathway for converting glucose to pyruvate) from the gene inventory, which results in the incapability of this non-proteobacterial methane oxidizer to fix carbon via the RuMP pathway. Further studies failed to detect Malyl coenzyme A lyase (involved in producing acetyl-CoA and glyoxylate from (3S)-3-carboxy-3- hydroxypropanoyl-CoA) and glycerate kinase enzyme (with two substrates ATP and R-glycerate produces 3-phospho-(R)-glycerate) of serine cycle in the genome of Methylacidiphilum infernorum strain V4 [39, 43, 59]. Complete genes necessary for the Calvin-Benson-Bassham cycle are present.

2.7 Methane Monooxygenase Enzyme (MMO)

The ability of methanotrophs to utilize methane is related to their methane specific enzyme methane monooxygenase (MMO) (Enzyme Entry: EC 1.14.13.25. ExPasy enzyme database) classified as a sub group of the oxidoreductase class of enzymes, which can catalyze the transfer of electrons from electron donor to electron acceptor by utilizing NADH (NADH is consumed by sMMO and pMMO uses cytochromes instead) as cofactor (CH4 + O2 + NAD(P)H  CH3OH +

+ [45, 83] NAD(P) + H2O) .

29 Methane monooxygenase in methanotrophs initiates the oxidation of methane by producing a highly reactive oxygen species (ROS; chemically reactive molecules containing oxygen) to overcome the molecular stability of methane C-H bonds, which are the strongest discovered aliphatic bonds in chemistry with bond dissociation energy of 104 kcal mol-1 (435.136 kJ mol-1)

[45, 84] . During the process two NADH are utilized in order to split the oxygen bounds in O-O

(dioxygen), the result is one atom is reduced to water by a 2e- reduction and the second one is

[45] incorporated into CH4 to form methanol (CH3OH) in the first step of methanotrophy .

There are two types of evolutionarily unrelated forms of MMO with similar functions, but with different molecular structures and kinetic properties: i) Particulate methane monooxygenase

(pMMO), which is located in the intracytoplasmic membrane present in most methanotrophic bacteria with the exception of genera Methylocella and Methyloferula and ii) Soluble methane monooxygenase (sMMO), which is located in the cytoplasm in a soluble form, and only occurs in a limited number of methanotrophic bacteria [85, 86].

pMMO shows a higher substrate specificity to CH4 with a more narrow substrate range (capable of oxidizing C5 alkanes group, trichloroethylene and propane) compared to sMMO (with lower substrate specificity to CH4 and a broader substrate range) and copper and iron are two key elements needed for its active site. Due to high dependency of the enzyme to copper ions, scientists suggest pMMO is a cuprous metalloenzyme [59, 84, 87 - 89].

On the other hand, sMMO may act as a secondary enzyme in some cases where there is limited copper available for the methanotroph (less than 0.8 M). sMMO has the ability to bind to

30 alkanes with C8 or less, ethers, cyclic form of alkanes, ethylene, chloroform and aromatic groups or halogenated derivatives [71][90][91][92][93].

2.8 Particulate Methane Monooxygenase (pMMO) or Membrane Bound

Monooxygenase Enzyme

The pMMO from M.capsulatus Bath has two major subunits of 45000 () and 26000-27000 () kDa, which are believed to be involved in the formation of the enzyme's active site and finally a third small 23000 () kDa subunit [94]. Three  subunits (pmoCAB genes as encoders) are in a form of a trimer with either mononuclear (an unlikely site for CH4 oxidation) or di-nuclear

(potential active site) copper centers, in close contact to the membrane-periplasm interface of the

 subunit and a metal-binding center, which is linked to both  and  subunits [45, 59, 94]. The exact nature of the enzyme’s active site is still not well characterized and there are three theories: Tri- nuclear, Di-nuclear and Mononuclear models [84].

2.5 iron atoms and 14.5 copper atoms (per 99,000 Da) are required for the pMMO of M. capsulatus Bath to remain active [59, 84]. Due to high dependency of pMMO on Cu ions, 10 fold higher than other microorganisms, methanotrophs use a capable Cu harvester from the immediate environment. Their scavenging molecules are effective enough to out-compete other organic Cu collecting complex agents [59, 89, 95, 96]. The potential candidate is a small chromopeptide, methanobactin, which is analogous to iron siderophores. Iron siderophores are the most resilient soluble Fe3+ chelating agents known to scientists [97]. A difference between these scavengers is that siderophores are synthesized and exported only when iron is insufficient in the immediate

31 surrounding environment of the microorganism but methanobactin is produced even when copper concentration is relatively high [98, 99].

The pmoA functional gene codes for a subunit of pMMO and is highly conserved. This conservation makes this gene a suitable alternative functional biomarker parallel to 16S rRNA gene for detecting methanotrophs with pMMO activity. Degenerate primer sets such as A189f-

A682r, A189f-mb661 and A189f-A650 have been designed for pmoA gene amplification in polymerase chain reaction assays [100]. The A189f-A682r primer set has the capability to amplify both pmoA and amoA genes (a high degree of sequence identity between pmoA and amoA genes is evident) [66].

2.9 Soluble Methane Monooxygenase Enzyme (sMMO) sMMO is a well characterized enzyme from the subclass of C-H activating oxygenases group

(together with several other oxygenases). Its expression is usually repressed by Cu (which act as inhibitory factor) [41, 88].

The sMMO enzymes from two model methanotrophs, Methylococcous capsulatus Bath and

Methylosinus trichosporium OB3b contain three subunits: hydroxylase, protein B (regulatory protein) and protein C (a reductase) [94]. The hydroxylase part of the enzyme is comprised of smaller units of  (approximately 60 kDa with mmoX as the encoder),  (45 kDa with mmoY as

[94] the encoder) and  (20 kDa with mmoZ as the encoder) in a 222 configuration respectively .

32 Methanol is formed in the alpha subunit of hydroxylase, which has a non-heme bis-()hydroxo- bridged binuclear iron center at the active site of the enzyme. Due to the non-heme nature of the alpha subunit the enzyme is classified as non-heme binuclear iron protein [94]. Nuclear Magnetic

Resonance Spectroscopy (NMR) based analysis of sMMO from M. capsulatus Bath and M. trichosporium OB3b revealed the structure of protein B, the second main subunit of sMMO with mmoB as the encoder, which is believed to be a small regulatory protein with an activity linked to hydroxylase [94, 101]. Protein C encoded by mmoC is also linked to hydroxylase by transferring electrons to the di-iron center of the hydroxylase and based on its activity it is a NADH dependent (2Fe and 2S) protein [94]. An unknown orfY (an open reading frame) known as mmoD plays a role, perhaps in the di-iron center between mmoY and mmoC [79].

The mmoX gene encoding a subunit of sMMO ( subunit of the hydroxylase part) , similarly to the pmoA gene of the pMMO, can be used as a functional biomarker and primers such as mmoX206F/mmoX886R and mmoXA/mmoXD have been designed for PCR-amplification of the gene from sMMO-containing methanotrophs in complex microbial communities [94, 102, 103].

Due to the broad spectrum of substrate specificity of sMMO in co-oxidizing a wide variety of compounds, methanotrophs that express this monooxygenase enzyme have been investigated for bioremediation purposes [94].

33 2.10 Identification of Active Methanotrophs Using Stable Isotope Probing

(SIP)

The stable isotope probing (SIP) technique was pioneered originally by Radajewski and

[27] 13 colleagues . SIP is performed by introducing an isotopically labeled substrate like CH4 to an active microbial community and identifying incorporation of this labeled carbon into biomass of the microbes actively assimilating the substrate [104, 105]. CsCl gradient ultracentrifugation is used to separate labeled and unlabeled DNA (heavy and light), and then labeled heavy DNA is extracted and analyzed to identify which microbes consumed the substrate [Figure 2-6].

The SIP technique is not limited to DNA. It is also applicable to different varieties of biological markers such as lipids, proteins and rRNA and mRNA [79, 106, 107]. DNA-SIP and rRNA-SIP are the most commonly used SIP protocols in microbial ecology for targeting the active microbes and their essential genes. mRNA-SIP has been only reported twice [104, 108].

DNA-SIP is capable of partial labeling the genome of the active microbial groups. Hence key functional genes (targeted by PCR) and metagenomic fragments can be analysed from the heavy

DNA in addition to the 16S rRNA gene [104, 105]. DNA-SIP has proven to be a powerful tool for detecting active methanotrophs in a variety of habitats. For example Morris and colleagues

(2002) reported 32% of sequenced genes in the heavy fractions of 13C exposed peat soils were from methanotrophs (from both classes of methanotrophs [mainly Methylobacter and

Methylocella]), Radajewski and colleagues (2002) reported 96% sequenced genes in the heavy fractions of 13C exposed forest soil were methanotrophs (Methylocella, Methylocapsa,

Methylocystis), Hutchens and colleagues (2004) reported 36% of the sequenced genes in the

34 heavy fractions of 13C exposed Movile cave water (located in Constanta County, Romania. Close to the black sea coast) were methanotrophs (Methylomonas, Methylococcus, Methylocystis,

Methylosinus), Lin and colleagues (2004) reported 50% of the sequenced genes in the heavy fractions of 13C exposed soda lake sediments were methanotrophs (Methylomicrobium,

Methylobacter, Methylomonas, Methylothermos) [102, 109 - 111].

35

CsCl Ultracentrifuga on Extracted DNA CsCl CsCl CsCl CsCl Light DNA

CsCl

CsCl CsCl Heavy DNA 13 13 CO2 CH4 CH4 CO2 CO2 CO2 13 CH4 CO 13 2 CH4 CO2 13CH 13 4 13 CH4 CH4 CO2 13CH 13 4 CH4 13 CH4 CO 2 13 13CH CH4 4 16S rRNA Based Pyrosequencing or Whole Genome Sequencing

Figure 2-6. Stable Isotope Probing and gradient fractionation of isotopically heavy DNA from

light DNA.

36 2.11 Conclusion

Estimated total greenhouse gas emissions generated from the recently established Canadian oil sands industry are approximately in the range of 48 Mt per year (Environment Canada 2012).

This is equivalent to about 6.9 % of Canada’s total greenhouse gas emissions, and accounts for 1

 10-4 of the global greenhouse gas budget (Environment Canada 2012).

Tailings ponds methane emissions are one part of the GHG emissions from oil sands.

Considering that Alberta cattle industry feeds 2.18 million cattle

(http://www.albertabeef.org/consumers/new-page/) with constant production rate of 200 L CH4

-1 -1 d from every cow and by assuming the release of about 100 million L CH4 d from the MLSB surface layer into atmosphere, tailings pond related methane production will be approximately equivalent to 500,000 cattle [12].

Methanotrophs are the only defined organisms that are a biological methane sink, which highlights their important role in the environment [59]. They also contribute to the global cycling of carbon, nitrogen, and oxygen due to their ubiquity. Methanotrophic byproducts such as single cell protein and biopolymers are applicable in medicine, industry, food packaging and agriculture

[113, 112].

37 Chapter Three: Field Study of MLSB and WIP Tailing Ponds

*The pipeline, Quantitative Insights Into Microbial Ecology (QIIME) software was used in this study by Dr.

Ivica Tamas and Christine Sharp in order to process the data. The output data was analyzed by Alireza Saidi-

Mehrabad for identifying indigenous methanotrophic bacteria in tailing waters.

*The assembly of the metagenome was done by bioinformatics support specialist Xiaoli Dong at the University of

Calgary Visual Genomics Centre (http://www.visualgenomics.ca/~xdong/projects.html).

3.1 Introduction

Open pit oil sand extraction produces large amounts of tailings comprised of hydrocarbons, chemical solvents and clay particles. This hydrocarbon affected wastewater is pumped into large basins, which are strongly methanogenic and capable of producing as much as 100,000,000 L of

-1 [12] CH4 d . After settling of the solid matter, the water cap zone of the tailings ponds can be oxic and provide oxygen molecules as electron acceptors for aerobic methananotrophic activity. This study focuses mainly on methanotrophic community analysis in the surface layers of Mildred

Lake Settling Basin (MLSB) and West in-Pit (WIP) tailings ponds via a series of molecular tools.

In addition potential methane oxidation rates were measured and attempts were made to isolate a novel group of methanotrophs.

3.2 Methods

3.2.1 Sampling and the Surface Tailing Water Chemistry (MLSB and WIP)

Tailing pond water samples were collected from the top 0 - 10 cm (oxic zone) of Syncrude’s

Mildred Lake Settling Basin (Latitude: 57°03'N and Longitude: 111°38'W. 10-15 m from the shore) and West in-Pit (WIP) Settling Basin (Latitude: 57°0033.14'N and Longitude:

111°3725.26'W_ 10-15 m from the shore). Samples were collected in 4-L sterile (rinsed a few

38 times with water) polycarbonate containers from the central section of the two mentioned tailing ponds with the aid of a floating barge (these samples are labeled with a suffix referred to as surface water), and shipped on ice to the University of Calgary where they were stored in the dark at 20 oC prior to analysis (within two days of the transportation to the lab) in order to mimic the natural tailing water conditions [Figure 3-1]. Some of the samples were collected from the center of the ponds with the aid of a cano (these samples are labeled with a suffix referred to as center of the pond).

All of the provided samples were measured upon receipt for pH via an Accumet Basic AB15 pH meter (Fisher Scientific, Ottawa, Ontario, Canada) attached to an Accumet electrode.

Syncrude officials provided partial chemical profile of the tailings ponds water from July 2011 and July 2012. [Table 3-1] summarizes the chemical properties of both WIP and MLSB. Both

MLSB and WIP tailing ponds were oxygen-poor at 30 cm and were saline, alkaline and rich in organic carbon ammonia and sulfides.

Samples had a discernible odor (bitumen or asphaltene odor) and the visual appearance of tailings liquid was a light yellow color, hazy or cloudy due to suspended clay particles in the water phase.

39

Figure 3-1. Tailing water samples from the aerated zone (oxic zone) of the WIP and MLSB were collected in 4-L sterile polycarbonate containers.

40 3.2.2 Filtering

In order to identify the indigenous methanotrophic population in the oxic layers of the tailings ponds, 200-mL of the tailings water was filtered through a 0.22-μm (47 mm in diameter. Filters contained 2-methoxyethanol with 0.001% - 0.8% weight) polyvinylidene difluoride (PVDF) filter

(Versapor-200, Pall Life Science, NY, USA) using a sterile low-extractable borosilicate glass filtering apparatus (VWR. Mississauga, Ontario, Canada), which included a 400-ml graduated funnel fixed to a 50-mm fritted glass support base (40-60 μm) filter holder with an anodized aluminum clamp, together connected to a 1-L (5%) flask attached to a vacuum line [Figure 3-

2].

Half of the filters containing the filtered material were preserved in 4% dimethyl sulfoxide

(DMSO) + fresh tailing water and stored at -80 oC for use in future experiments. The rest of the filters were carefully sheared with sterile scissors into impact-resistant 2-ml Lysing Matrix E tubes, available in the FastDNA  SPIN kit for soil (MP Biomedical, Santa Ana, CA, USA).

Lysing Matrix E tubes were stored for 48 h at -80 oC prior to genomic DNA extraction according to the manufacturer's instructions. This is a freeze-thawing method combined with mechanical cell disruption for enhanced cell lysis.

41 Table 3-1. Chemical properties of both WIP and MLSB in more detail. SE refers to standard

error of the mean of two measurements. Data courtesy of Syncrude (July 2011- July 2012).

WIP MLSB

Mean SE Mean SE pH (units) 8.0 0.0050 7.8 0.13

Conductivity (µS cm-1) 3610 20.0 3120 80.2

Temperature (oC) 20.0 21.9 1.10

Dissolved solids (%) 0.24 0.018 0.19 0.0033

Total solids content (%) 0.27 0.23

Alkalinity (mg l-1) 1010 338 840 311

-1 Chemical O2 demand (mg l ) 240 230

-1 Dissolved O2 at 30-cm depth (mg l ) 0.27 0.030

-1 O2 penetration depth (cm) (0.01 mg l ) 150 60

Redox potential (mV) 54 148

Sulphides (mg l-1) 0.012 0.012 0.090 0.020

Dissolved organic Carbon (mg C l-1) 40 1.0 46 2.0 o-Phosphate (mg P l-1) 0.015 0.0070 0.015 0.0045

Ammonia (mg N l-1) 7.8 2.0 17 6.9

Nitrate + Nitrite (mg N l-1) 0.015 0.0050 0.011 0.0010

Total Nitrogen (mg N l-1) 9.9 0.1 18 8.3

Total major ions (mg l-1) 2770 12.4 2290 27.2

42

Figure 3-2. Filtering apparatus used in our experiment for concentrating the solid particles of the water on 0.22-μm polyvinylidene difluoride (PVDF) filters.

43 3.2.3 DNA Extraction Procedure

Genomic DNA was collected from the filters in 2-ml Lysing Matrix E tubes via the FastDNA 

SPIN kit for soil, which employs a mechanical bead beating method. The protocol provided with the kit was amended with a few extra purification steps for obtaining high quality genomic DNA without the presence of humic or flavic acids [114]. The overall procedure was as follows: 978 μl of sodium phosphate buffer plus the filters were homogenized in a cell homogenizer (Precellys 24 instrument. Bertin Technology) for 80 sec at a speed setting of 6.0 m/s. Three types of beads are used in Lysing Matrix E tubes for homogenization of the resistant sample to lysis; 1.4 mm ceramic spheres, 0.1 mm silica spheres, and a 4 mm glass bead (http://www.mpbio.com). Samples were then centrifuged at 14,000 × g (13,000 r.p.m) (rotor F241.5P Microfuge 22R Centrifuge,

Beckman Coulter Inc.) for 10 min to pellet debris. Supernatants were transferred to clean 2-ml microcentrifuge tubes and 250 μl of Protein Precipitation Solution (PPS) was added. For pellet precipitation samples were centrifuged for second time at 14,000 × g for 10 min. Supernatants were transferred to sterile 15-ml Falcon tubes (VWR. Mississauga, Ontario, Canada). 500 μl of re-suspended binding matrix was mixed with 500 μl of 5.5 M Guanidine Thiocyanate (GTC) and added to collected supernatants. 15-ml Falcon tubes were inverted by hand for 2 min to allow binding of DNA. Tubes were placed in a rack for 3 min to allow settling of the silica matrix. 600

μl of the supernatant was carefully removed and discarded. Binding matrix was re-suspended in the remaining amount of supernatant. 600 μl of the mixture was added to set of spin filters and centrifuged at 14,000 × g for 5 min. Catch tubes were emptied and the remaining mixture was added to the spin filters and centrifuged as before. Catch tubes were emptied again. Binding matrix in the spin filters was gently re-suspended in 600 μl of 5.5 M GTC solution. Tubes were centrifuged at 14,000 × g for 5 min and the catch tubes were emptied. The washing step with 5.5

44 M GTC solution was repeated four times until the binding matrix was returned to its original color. Pellets were carefully re-suspended in 500 μl of prepared SEWS-M (prepared according to manufacturer's protocol) by using the force of the liquid from the pipette tip. Spin filters were centrifuged at 14,000 × g for 1 min and catch tubes were emptied. In order to dry the matrix of residual wash solution, without any addition of liquid a second centrifugation step at 14,000 × g for 10 min was performed. Catch tubes were replaced with new, clean catch tubes. In order to elute the extracted DNA, 50 μl of DNase/Pyrogen-Free Water (DES) was used to gently re- suspend the binding matrix. A final centrifugation at 14,000 × g for 10 min was performed in order to bring eluted DNA into the clean catch tubes. All the extracted DNAs were collected into a single sterile labeled 1.5-ml centrifuge tubes and stored at -80 oC for 24 h prior to any downstream applications.

3.2.4 Determination of the Genomic DNA Concentrations

DNA concentrations of extracts from each sample from different months were determined with a

Qubit Fluorometer device (Invitrogen. Burlington, Ontario, Canada) via Quant-iTTM dsDNA HS

Assay Kit (Invitrogen), calibrated based on the manufacturer's protocol. Genomic DNA concentrations of samples from random months used in this experiment are summarized in

[Appendix 1]. DNA concentrations ranged from 1.63 µg (34.1µg/mL) - 86.2 µg (461µg/mL) of

DNA.

45 3.2.5 16S rRNA Gene Pyrotag Sequencing

In order to gain high quality sequences via Pyrotag sequencing technology for microbial community analysis (capable of producing 1,000,000 sequences around 500-700 bp in a single 23 h run) and meet the requirements of the Genome Sequencer 454 FLX Instrument (miniumum 100-

150 ng in 30-20 l required, as designed by Roche Diagnostics Corporation) a PCR reaction was performed using 16S rRNA gene FLX Titanium amplicon reverse primer and 454_RA_X as well as forward primer 454T_RA [198, 199]. The 3 ends of these primers target the V8 hypervariable region of the 16S rRNA gene. They are the universal primers 926f (AAA CTY AAA KGA ATT

GAC GG) and 1392r (ACG GGC GGT GTG TRC) [198, 199]. These primers are capable of amplifying archeal 16S rRNA gene as well as bacterial 16S rRNA gene (PCR products are 466 -

500 base long) [12, 115, 116, 198, 199].

The 5ends of 454 FLX Titanium primers are mainly occupied by 25 nt Roche Titanium chemistry adaptors A (CGTATCGCCTCCCTCGCGCCATCAG, at 5 end of the 454T_RA prime) and B (CTATGCGCCTTGCCAGCCCGCTCAG, at 5 end of 454T_FB). The forward primer includes a 10-nt sequence multiplex identifier (MID), which makes the primers specific to each sample and provides the possibility to analyze multiple samples on a single sequencing chip, by separation of sequences from different samples based on MID sequences. The 10-nt barcode is located between the forward adaptor and 926f primer sequence [117]. The 16S rRNA gene PCR reaction master mix per each run in our study and the thermocycler program are explained in

[Appendix 2].

46 PCR products were run on a 1 % (w/v) agarose gel containing 3 µl of SYBR® Safe (Life

Technology, Burlington, ON, Canada) DNA gel stain at 100 V for 50 min and visualized under blue light (not UV light) to confirm correct product size (~ 500 bp). Amplified products were purified via the Molecular Biology Kit-EZ-10 Spin Column PCR Purification Kit using the manufacturer’s protocol (Bio Basic INC. Ontario, Canada). Concentrations of the purified amplified samples were measured using a Qubit Fluorometer device with Quant-iTTM dsDNA HS

Assay Kit. Samples were sequenced at Genome Quebec at the McGill University Innovation

Center (http://gqinnovationcenter.com/index.aspx) (Montreal, Quebec, Canada).

3.2.6 Quantitative Insights Into Microbial Ecology (QIIME) Software (Version

1.3.0)

The Sequence-read data sets obtained from the pyrosequencer (Genome Sequencer FLX instrument) were analyzed via QIIME software (Version 1.3.0) (http://qiime.org/) [118]. QIIME is a locally installed pipeline for interpreting large sets of sequences by filtering low quality reads and then grouping the sequences into Operation Taxonomic Units (OTUs) of 97% identity. The output of the program is a bacterial diversity table listing each detected OTU, its relative percentage in each sample, and a taxonomic assignment based on the SILVA database

(http://www.arb-silva.de/) via the Basic Local Alignment Search Tool (BLAST) [12, 118 – 120, 170].

The low quality score threshold was set at 25, the average quality was usually 35 and the

Singleton reads were removed for lowering the risk of chimera artifacts.

Produced data were captured in an Excel sheet and the total percentages of all detected Bacteria and Archaea in each sample were calculated. Key-words ‘Methylo’, ‘Crenothrix’, and ‘Clonotrix’

47 were used with search option of the Microsoft Excel for detecting the following methanotrophs;

Methylocaldum, Methylomicrobium, Crenothrix, Clonothrix, Methylobacter, Methylocella,

Methylocystis, Methylocapsa, and Methylomonas. Identified methanotrophs were checked on the

ARB SILVA automated aligner website (http://www.arb-silva.de/aligner/) using their advanced search and classification tools (ribosomal database project, greengene database project and living tree project) [168, 169, 171]. Representative sequences of all OTUs were incorporated into a 16S rRNA gene based phylogenetic tree (tree methodology will be explained in section 3.2.7). Some

OTUs that were identified as methanotrophs by BLAST in the QIIME software but did not cluster within known methanotrophic clades were removed.

Identified methanotrophic OTUs were sorted (Similar OTUs of methanotrophic genera were added together) and selected with the sorting option of the Microsoft Excel and the non- methanotrophs were removed in order to identify what percentage of methanotrophs are formed the total microbial structure in each particular sample (July_2011, August_2011, October_2011,

December_2011).

3.2.7 16S rRNA Gene –Based Phylogenetic Tree

A neighbor joining (NJ) 16S rRNA gene-based skeleton tree was constructed by selecting nearly complete sequences (> 1300 nt) from the ARB Silva database [121, 122]. Methanotroph–related sequences in our data were uploaded into the online ARB Silva automated aligner (part of ARB-

Silva project) (http://www.arbsilva.de/aligner/) tool. Aligned sequences in FASTA format

(approximately 400-410 nt) were imported into ARB and incorporated into the previously constructed skeleton tree using the parsimony-add function in the ARB software (www.arb-

48 home.de) (version 5.3-org-8209). ARB is capable of handling a large aligned reference database with various options for expanding and collapsing tree for easy data handling [123].

Sequences were manually inspected in the sequence editor option of the software for misalignments, chimeric segments and homopolymer errors [12][124]. Together newly added sequences and database reference sequences in the skeleton tree were used to construct a 16S rRNA gene based neighbor joining tree with the NJ method and a Jukes-Cantor (1969) distance correction filter (a simple model of DNA sequence evolution) [125]. The resulting topology was rigorously tested with bootstrap analysis of 1000 constructions and the tree was edited with options available in ARB and with CorelDraw X5 (Corel Corporation, version 15.2.0.661).

3.2.8 Metagenomic Sequencing of WIP Surface Water

11.8 g (11800 ng in 125 l) of genomic DNA was extracted from the WIP Surface water

(July/2011 sample) and was sent for metagenomic analysis via Roche 454 sequencing technology

[125][126][127].

3.2.9 Potential Methane Oxidation Rates

In order to investigate and compare methane oxidation rates from the tailing samples collected from different time periods, 200 ml of the tailings water was filtered (MLSB and WIP separately) as described in section 3.2.2. One filter was placed into an autoclaved 120-ml glass serum vial with an additional 20 ml of tailings water directly taken from the sampling containers. The total amount of the tailings in the serum vials was equivalent to that present in 220 ml of fresh tailings water, with a remaining 100 ml of headspace. 12.6 – 25.0 % of CH4 (v/v) plus 5.4-10.5% (v/v)

49 CO2 were injected (balanced with air) into stopped and crimp-sealed (gas- tight) bottles and they were incubated at 21.9 oC on a rotary shaker (Standard analog shaker. VWR) at 155 r.p.m for 12

– 48 d (based on the sample's methane oxidation activity).

The decline in methane mixing ratios (mol CH4/mol gas) was measured by taking 1.0 ml of the remaining head space with a precision analytical syringe (Pressure_Lok series A_2 syringe 2 ml. LA, USA) and injecting it into a Varian 450 gas chromatograph (GC) equipped with a 250 oC heated flame ionization detector (FID) and with 2 mm × 0.5 m Hayesep N and a 2 mm × 1.2 m

Molecular Sieve 16× columns in series (70 oC) (Agilent Technology, Mississauga, ON, Canada).

The methane in the headspace was calculated based on a reference gas of known CH4 mixing ratios (mol CH4/mol gas) (0.494% CH4, Praxair). Average of three injected standards (sample areas) were used for calculations [Appendix 3]. The oxidation rates were determined based on linear regression of methane mixing ratios (mol CH4/mol gas) in headspace for the first 14 d

[12][Appendix 4].

3.2.10 Potential Methane Oxidation Rates at Different Temperatures

In order to test the temperature effect on methane oxidation rates in tailings ponds and assess the optimum temperature for methanotrophic activity, a set of 46 (duplicates prepared from MLSB and WIP, each with leakage control [autoclaved tailing waters]) 120-ml serum vials were prepared from 150 ml of concentrated debris of tailings ponds on 0.22 m filters combined with

20 ml of tailing water directly taken from the sampling containers and distributed at -20, +4, +17,

+21, +30, +37, +45, +55 and +65 oC on rotary shakers at 120 r.p.m for 31 days without any light

50 source. Each vial initially contained 17.0% – 19.1% (v/v) CH4 and 5.1% – 6.0% (v/v) CO2 in the headspace (balanced with air).

3.2.11 Stable Isotope Probing (SIP)

The SIP protocol used in our lab was modified from Neufeld and colleagues [105].

For DNA based SIP, 200 ml of the tailings pond water samples was filtered through 0.22 μm filters (as described above) and the filters were distributed into four (two for WIP and two for

MLSB) 1-L glass bottles. Each bottle received four filters plus an additional 200 mL of natural tailings water (4 × 200 ml + 200 ml = 1 L). Bottles were capped with butyl rubber stoppers and

13 13 13 10.1– 11.4% of C-labeled methane (460 ml cylinder of CH4 – 99 % C atoms. Sigma

Aldrich) added. Approximately 5.3 – 10.0% CO2 (v/v) (balance with air) was provided to limit the cross feeding of non-methanotrophic autotrophs on labeled CO2 produced by active methane oxidizers [41, 105].

Samples were incubated for 22 days and the methane concentration monitored at two-day intervals by using a gas chromatograph equipped with a flame ionization detector (GC/FID) until the samples had demonstrated about 3% consumption of the provided labeled methane in the headspace.

The liquid phases of the bottles were aliquoted into a series of 50-ml screw cap Falcon tubes and were centrifuged at 10,000 r.p.m (Avanti J-E Series Centrifuge. Beckman Coulter) for 50 min with maximum acceleration and slow deceleration at 4 oC in a JA-14 (S/N 10U 9443) fixed angle

Beckman Coulter rotor. Supernatants were carefully discarded and the pellets were collected into

51 Lysing Matrix E tubes for genomic DNA extraction. At the end the entire genomic DNA was combined in their appropriate tubes. The final measured DNA concentrations prior to storage at -

20 oC were 15.9 g/ml for WIP and 28.1 g/ml for MLSB.

Extracted DNA obtained from WIP was mixed with 1004.6 l of gradient buffer (GB) in a series of 1.5-ml centrifuge tubes, which resulted in a total of 1.20 ml of DNA/GB. Mixture of DNA/GB was transferred to labeled 15-ml Falcon tubes and 4.8 ml of CsCl stock solution (7.163 M with final density of 1.89 g/ml at 20 oC) was added using sterile latex-free 10 ml syringes (BD, USA) with 22 G (1 ½) needles (BD Precision Glide needles, USA) [105]. The combined DNA/GB/CsCl was transferred into Polyallomer quick-seal ultracentrifuge tubes (13 × 51 mm. Beckman, USA) with the aid of lime glass disposable Pasteur pipettes (Size 9, VWR, USA) up to the neck of the ultracentrifuge tubes. Tubes were balanced within 10 mg.

The necks of the tubes were melted and sealed with a cordless tube topper (358312 Cordless tube topper. Beckman, USA) and the tubes squeezed forcefully by hand to test any probable leak.

Heads of the tubes were tested prior to the ultracentrifugation step with the metal caps

(ultracentrifuge tube stoppers) to make sure they fit in the rotor (NVT 90 rotor, S/N: 98U 1347.

Beckman Coulter, USA). Ultracentrifugation conditions were as follows; 50,000 r.p.m (173,000

× g) (maximum acceleration and slow deceleration without brake) in an Optima L-100K ultracentrifuge (Beckman Coulter, USA) at 20 oC for a minimum of 65 h under vacuum.

In order to fractionate the centrifuged DNA samples (according to Ethidium bromide -free method), the bottom of each ultracentrifuge tube was pierced with a 22 G needle and fixed to a

52 tube holder. 60 ml of Mineral oil was injected into the top of the tube (by attaching the syringe to a syringe pump as shown in the figure 3-3) in order to gradually force the mixture of separated

DNA (light and heavy DNA) and CsCl into 1.5-ml centrifuge tubes in one-minute intervals

[Figure 3-3]. Each tube received approximately 400 l in a designated one-minute interval (by the aid of the syringe pump and mineral oil). The gradient formation was tested with a refractometer (AR200 digital handheld refractometer. Reichert Technologies). The first tubes

(from the bottom of the gradient) were usually in the range of 1.4087 nD-TC – 1.4089 nD-TC and the last tubes were in the range of 1.3974 nD-TC – 1.3977 nD-TC [Table 3-5].

nD-TC is defined as temperature-corrected refractive index reading or temperature compensated per ICUMSA source temperature coefficient. DNA from each tube was precipitated by adding 1

l of glycogen (20 mg/ml. Roche) and 800 l (2 volumes) of polyethylene glycol (6000) solution

(PEG). Samples were mixed well by hand 10 times and incubated for 24 h at 21.9 oC. After the 24 h incubation samples were centrifuged at 13,000 × g at 20 oC for 40 min and the supernatant was discarded. Visible pellets were washed with 500 l of 70% ethanol and centrifuged at 13,000 × g at 20 oC for 10 min. Samples were aspirated and the pellets were dried at 21.9 oC for 20 min prior to addition of 30 l of TE buffer (10 mM Tris-HCl [pH 8.0] and 1 mM EDTA [pH 8.0] in autoclaved distilled water). Suspended pellets in TE buffer were dissolved on ice and mixed by gently tapping the tubes. Samples were stored at -80 oC.

53

Figure 3-3. Fractionation step of the SIP experiment. Each tube received about 400 l.

54 Table 3-2. Refractive index values of a CsCl gradient formed via ultragcentrifugation, using a

WIP sample from December_2011. The table indicates the successful gradient formation of the

SIP samples.

WIP Fraction (Tube Numbers) Refractive Index (nD-TC) Density values g/ml*

1 1.4087 1.788

2 1.4084 1.784

3 1.4073 1.771

4 1.4062 1.758

5 1.4052 1.747

6 1.4040 1.733

7 1.4030 1.721

8 1.4018 1.707

9 1.4008 1.695

10 1.3998 1.683

11 1.3989 1.673

12 1.3978 1.660

13 1.3974 1.655

* The formula X (Density g/ml) = Y (The refractive index value in nD-TC for each fraction ) -

1.256/0.0854 was used to convert refractive index to density. [105].

55 The formula X = Y- 1.256/0.0854 were used to convert refractive index to density [105]. Y is the refractive index value for each fraction, and X will give the density value in g/ml for that particular fraction, in our experiment mentioned values were ranged from 1.8 - 1.6 g/ml. Density values were plotted versus DNA concentrations in order to identify the heavy fractions with increased DNA concentrations as compared to the unlabeled control. Unlabeled control gradient samples contained DNA directly extracted from the tailings water prior to any incubation with

CH4 or CO2. Controls in our SIP experiment represent the entire natural microbial community in un-amended samples with no external CH4 or CO2, (which, when added act as selecting factors for particular microbes). In this experiment WIP December/2011 was chosen for in-depth analysis.

3.2.12 Time Course SIP

In order to check consistency of particular active methanotrophs in the heavy fractions and probable shift in active microbial community because of long SIP incubation periods, a time course SIP was performed on both MLSB and WIP, August 2012 tailing samples, with sampling after 1, 3, 12, and 24 h periods. 16 serum vials (120-ml) (2 for MLSB and 2 for WIP) were

13 prepared as explained in SIP methodology section (section 3.2.11) with 9.2%-14.6% (v/v) CH4

12 and 5.7%-7.2% (v/v) CO2 injected in the 100 ml headspace. Samples were shaken at 155 r.p.m and incubated at 21.9 oC without any light source.

56 3.2.13 Bacterial Cultures (Direct Plating)

In order to isolate active methanotrophs indigenous to tailings ponds and characterize them based on their physiology and genomes, 100 l of the tailings water was spread onto media (spread plate method), made directly from the 500 ml of filtered tailings water (Filtered through 0.22 μm PVDF filters by using sterile low extractable borosilicate glass filtering apparatus) and 15 g of Phytagel

(Sigma) as a gelling agent with 1 g of MgSO4.7H2O. The pH of the medium was adjusted to 8.6.

After 20 min of autoclaving the solution pH dropped to 8.4, close to the pH of the natural tailings water.

Plates were referred to as TM (plates made from MLSB tailing water) and TW (Plates made from

WIP tailing water) and were transferred to large glass desiccators under an atmosphere of 10.5%

o CO2 (v/v) and 20.3% CH4 (v/v), incubated at 21.9 C in a room without any light source.

Plates where checked weekly for any signs of colony formation and colonies were picked and transferred to freshly made defined M10 pH 8.4 media (Medium for methanotrophic bacteria) made with distilled water rather than filtered tailings water (via streak plate method)

[Appendix 5].

Because pMMO is a cuprous metalloenzyme, colonies originating from the TW and TM culture plates were also streaked onto copper-and-iron amended M10, named as M10 XCF (Medium 10 pH 8.3 with extra Cu and Fe), which contains large concentrations of Fe EDTA and CuSO4, suitable for the growth of methanotrophs with high Fe and Cu dependency [Appendix 6].

Possible methanotrophic colonies of interest (with similar colony morphology described in previous literature related to methanotrophic characterizations) were transferred into PCR cups

57 for amplification of 16S rRNA and pmoA genes via colony PCR. Colony PCR components for

16S rRNA gene and pmoA gene amplification are explained in [Appendix 7] and [Appendix 8] respectively.

Samples were purified as described in section 3.2.5 and were sent for DNA sequencing via an automated Applied Biosystems 3730xl 96-capillary DNA sequencer (based on Sanger chemistry) at the University of Calgary core DNA sequencing facility to confirm purity and to identify the bacteria [128, 129]. Purified amplicons were prepared for Sanger sequencing according to the protocol provided by University of Calgary Genetic Analysis Laboratory

(http://www.ucalgary.ca/dnalab/sequencing).

In addition to traditional Sanger sequencing, 5.17 g of genomic DNA from a novel methanotrophic isolate (Methylobacter oleiharenae strain XLMV4T described in chapter four) was sent for HiSeq2000 Illumina sequencing

(http://www.illumina.com/technology/solexa_technology.ilmn) in order to obtain a full genomic profile of the target methanotroph [130].

Four types of broth cultures were used in these studies in order to enrich mesophilic and thermophilic/ thermotolorant methanotrophs; i) Four (2 for WIP and 2 for MLSB) 1- L glass bottles containing 350 ml of 2× the concentration of M10 XCF with 0.122 g of CuSO4 (in 1 L).

An additional 150 ml of tailings waters was added into each bottle (total volume of 500 ml) and

3.9%-4.0% (v/v) CH4 and 5.6-6.0% (v/v) CO2 (balanced with air) were injected in the 500 ml of the remaining headspace. Bottles were shaken at 150 r.p.m in a dark room at 20 oC for 44 days. ii)

58 Two 1-L glass bottles containing 500 ml from MLSB and WIP (August/2012 sample) without addition of external carbon sources or metabolites and chemical components were separately prepared. 8.4-9.5% (v/v) CH4 and 5.2-10.4% (v/v) CO2 (balanced with air) were injected to 500 ml of the headspace and bottles were shaken for 32 d at 150 r.p.m at 21.9 oC in a dark room. iii) 10 fold serial dilutions were performed in 20 sets of 30-ml Hungate tubes for dilution to extinction

[41]. 3 ml of 1× M10 XCF were added into the first set and subsequently 300 l of tailing water

-1 -10 from MLSB August/2012 sample was transferred from 10 to 10 tubes. 9.7%- 12.5% (v/v) CH4 and 5.4% -7.2% (v/v) CO2 (balanced with air) were added into the headspace (26.7 ml). A second set was prepared with the same procedure described above except instead of 1×, 2× M10 XCF were used to isolate Cu dependent thermophilic/thermotolorant methanotrophs. Tubes were sealed

o with gas-tight stoppers and were incubated at 45 C with 13.0% -16.6% (v/v) CH4 and 5.4%-7.2%

(v/v) CO2 balanced with air in the headspace (at 120 r.p.m in a darkroom until they demonstrated methane consumption). iv) A series of six, 120-ml serum vials in duplicates were prepared. The first set included 10 ml of tailings + 10 ml of 1× M10 prepared with 0.02 mg of CuSO4 (in 1L) + vitamin B50 complex (1 capsule with 50 mg/mcg of vitamin Bs), the second set included 10 ml of tailing + 10 ml of 1× M10 prepared with 0.02 mg of CuSO4 and the third set contained mixture of both tailing waters WIP and MLSB in total volume of 10 ml. Headspaces were filled with a 2:1:1

o CH4/CO2/O2 gas mixture and incubated at 45 C on a rotary shaker (120 r.p.m).

In addition to the NCBI (http://blast.ncbi.nlm.nih.gov/Blast.cgi) database, generated data via

Sanger technology were also uploaded into a database free of any erroneous and mislabeled reference sequences, Ez Taxon-e (http://eztaxon-e.ezbiocloud.net/), in order to identify the targeted methanotrophs in a complete hierarchical (from species to phylum) system by employing

59 16S rRNA gene based comprehensive phylogenetic analysis, which is one of the noticeable features of this database compared to other public domain databasess such as PubMed and

GenBank [131].

Recent upgrades to the database in 2012 implemented a new function named percentage of completeness, which is the “degree of completeness of a 16S rRNA gene sequence with respect to full-length sequences”. This value could be shown as Completeness (%) = L  100/C where L is the length of the target sequence and C is the length of closest reference, which is a fully sequenced. The definition of the full-length sequence has been defined to the system in the range of the most commonly used bacterial 16S rRNA gene primers, 27F and 1492R and archeal 16S rRNA gene primers of A25F and U1492R [131 - 133].

3.3 Cloning of PCR Products Generated with Taq DNA Polymerase

Extracted DNA from mixed tailing waters incubated at 45 oC for 10 days for detecting thermophilic/thermotolerant methanotrophs [Table 3-5 in section 3.5.10] was used as a template in pmoA gene based PCR with primers 189f and 661b and the touchdown program. A bead beating method was employed for DNA extraction with the exact protocol described in section

3.2.3. For identification purpose, CloneJETTMPCR Cloning Kit (#K1231, #K1232. Fermentas Life

Science) was employed based on a sticky-end cloning protocol in which PCR product generated by Taq DNA polymerase (2 l) was blunt-ended prior to the cloning procedure. The blunting reaction contained 2× reaction buffer (10 l), nuclease free water (17 l), DNA blunting enzyme

(1 l) [134]. The mixture was vortexed briefly and centrifuged for 5 seconds and was incubated at

70 oC for 5 min, at the end the sample was chilled briefly on ice. The second step was the ligation

60 reaction (total volume of 20 l), which included the following components; pJET 1.2/blunt cloning vector (50 ng/l) 1 l and T4 DNA ligase (5u/l) 1 l [135]. The sample was vortexed and subjected to an additional centrifugation step for 5 sec. The final step included incubating the sample at room temperature for 5 min and using it directly for bacterial transformation.

For the transformation step 2.5 l of the ligation reaction mixture were used in order to transform

50 l of competent E.coli cells. Clone Jet PCR cloning kit used in this experiment was provided with One Shot® TOP 10 chemically competent E.coli cells (Invitrogen) with transformation efficiency of at least 1 × 106 transformants per l of supercoil plasmid DNA (cfu g-1 plasmid

DNA). For the screening procedure pre-warmed LB-ampicillin agar plates were spread with the mixture of 2.5 l of the ligation mixture (chilled for two min prior to the experiment) and 50- l of the prepared competent E.coli (strain TOP10) (incubated on ice five minutes prior to use).

Plates were incubated overnight at 37 oC [Appendix 9].

After 1 day four positive transformants were selected for colony PCR. 20 l of the PCR master mix was aliquoted into PCR tubes on ice and each individual colony was re-suspended in a tube.

Samples were subjected to PCR under the conditions of 95 oC for 3 min; 94 oC for 30 sec, 60 oC for 30 sec, 72 oC for 1 min; 25 cycles. At the final step samples were analyzed on an agarose gel

(1%) for the presence of PCR products. pmoA gene reference sequences of Methylococcus capsulatus, Methylocaldum szegediens and Methylocaldum gracile (thermophilic/thermotolerant methanotrophs) were obtained from NEB cutter website (http://tools.neb.com/NEBcutter2/) in

61 order to choose and match suitable enzymes for double digestion (with full capacity in matching conditions such as temperature) from the enzyme inventory of Dunfield lab.

Two restriction enzymes of NcoI and PaeI (Sphl) (Thermo Scientific) were chosen for the double digestion with full capacity for the pmoA gene. Master mix of the following components were prepared; 10× Tango buffer (2 l), Substrate DNA (15 l), Restriction enzyme NcoI (1 l),

Restriction enzyme PaeI (SphI) (2 l) in total volume of 20 l. Samples were incubated at 37 oC for overnight and all of the reaction mixture was used on an agarose gel. After the visual observation of the patterns, which all contained a similar pattern (total of 10 clones) three of them were selected and sent for fully automated capillary-based Sanger sequencing at Eurofins genomic center (http://www.eurofinsgenomics.eu/).

3.4 Results and Discussion

3.4.1 pH of the Surface Waters

As mentioned (in section 3.2.1) prior to any experiments pHs of the water samples were measured via an Accumet Basic AB15 pH meter (Fisher Scientific, Ottawa, Ontario, Canada) attached to an Accumet electrode (soaked in KCl solution) [Table 3-3]. The pH vales ranged from 8.74-7.35.

3.4.2 Active Microbial Communities Detected via 454 Pyrotag Sequencing

Raw sequencing data of WIP and MLSB surface layers generated via the 454 FLX instrument from July_2011, August_2011, October_2011 and December_2011 were uploaded into QIIME to

62 assign Bacteria and Archaea to OTUs with 97% similarity and remove the results affiliated to eukaryotic cells.

102363 total reads were obtained from the nine samples combined. Out of this total, 95977

(93.76%) of the reads were assigned to bacteria and 6386 (6.23%) of the reads belonged to the domain Archaea [Figure 3-4]. Proteobacteria OTUs comprised 71942 (74.95%) of the reads, including 2883 reads of Gammaproteobacteria (4.00%), 6527 reads of Alphaproteobacteria

(9.07%), 1570 reads of Deltaproteobacteria (2.18%), and 60962 reads of Betaproteobacteria

(84.73%) [Figure 3-5]. A more in depth analysis of the overall communities is not included here because this was part of another lab member's work. Further analysis will focus only on putative methanotrophs.

3.4.3 Active Aerobic Methane Oxidizing Community Detected via 454 Pyrotag

Sequencing

Potential methanotrophs formed as much as 3.84% (total of 468 reads) of the total 16S rRNA gene reads in any sample. Most of the OTUs identified were gammaproteobacterial methanotrophs.

OTU 12103 (which was always predominant and present in all sampling sites and sampling times) with a total of 389 reads (1 % of the total and 83.11 % of the detected methanotrophs) is linked to the genera Methylocaldum/Methylococcous [Table 3-4].

Methylocaldum related species are known to grow at high temperature (> 40oC) and are classified as thermotolerant to mild thermophiles. They have been isolated from completely different microbial habitats such as agricultural soils and hot springs [136]. Detecting Methylocaldum spp.

63 related OTUs in high percentages, particularly in cold and complex oil sand affected wastewaters is unexpected [12].

Crenothrix/Methylosoma was present in relatively high proportion in MLSB (December/2011 sample) at 33.3% second only to the predominant Methylocaldum/Methylococcus, but in the rest of the samples was lower in abundance. The presence of Methylomicrobium, and Methylomonas related OTUs were limited to WIP samples. The genus Methylomicrobium was detected only twice with low abundance in WIP August and October/2011 samples. Methylomonas related

OTUs were present in all processed WIP samples from July/2011 to December/2011.

64 Table 3-3. Tailing samples processed in the lab with the pH values measured upon receipt.

In table SEM is refereed to as standard error of mean of duplicate measures.

Sample pH

MLSB _July,2011 8.74

MLSB_August_2011 7.92

MLSB_October_2011 7.66

MLSB_December_2011 7.89

MLSB_August_2012 7.77

Min pH for MLSB 7.66

Max pH for MLSB 8.74

Average (MLSB) 7.99

SEM (MLSB) 0.2

WIP_Center of Pond_July_2011 8.69

WIP_Surface_July_2011 7.35

WIP_August_2011 8.01

WIP_October_2011 8.37

WIP_December_2011 7.89

WIP_August_2012 8.23

Min pH for WIP 7.35

Max pH for WIP 8.69

Average (WIP) 8.09

SEM (WIP) 0.1

Average of Tailings pH 8.04

SEM of Tailings pH 0.128

65

Figure 3-4. Percentage of the bacterial communities versus archaeal communities within the surface tailing samples from July_2011 until December_2011. The bar graph was based on the

QIIME processed results. Based on the bar graphs, it seems that in October/2011 WIP water cap was not very oxic and archaeal species (identified primarily as obligate anaerobic methanogens) were abundant.

66

Figure 3-5. Bar graphs of relative abundances of different classes of Proteobacteria within the surface tailing samples.

67 Interestingly, negligible numbers of OTUs were assigned to methanotrophs in the

Methylocystaceae and Beijerinckiaceae families of the class Alphaproteobacteria. Based on the data in table 3-6 the tailing water chemistry of MLSB and WIP is selecting for particular species of Gammaproteobacteria. Previous study conducted in Dunfield lab (by Dr. Zhiguo He) on samples collected from tailing affected fens, natural bitumen outcrops, and tailing waters from

WIP, MLSB (2010 samples), and other non-Syncrude tailings ponds detected potential obligate or facultative methanotrophs affiliated to the Beijerinckiaceae family only in WIP and MLSB/2010 samples (with total reads of 13) [12]. These could not be identified at the genus level because there is less than 4% 16S rRNA gene sequence divergence between different genera in this family.

None of the OTUs related to the Methylocaldum/Methylococcous cluster was detected in natural bitumen and tailing-affected fen samples. A large fraction of Methylobacter related OTUs were present only in tailing-affected fens and Crenothrix/Methylosoma species with 77.2 and 98.9 % of reads seems to be dominant in natural bitumen (not tailing water). A small trace of the genera

Methylocystis and Methylocella was detected in natural bitumen samples collected in 2009 [12].

Pyrotag data sets of the current study (samples from July/2011 – December/2011) are available under the accession number SRP013946 [12].

68 Table 3-4. Percentage of the total reads of putative methanotrophic bacteria detected via 454

Pyrotag sequencing in different samples of surface tailings water. The last column represents the

total percentage of methanotrophs in each sample collected from July/2011-December/2011.

Percentages have been obtained from results processed via QIIME. Based on the table

Methylocaldum is present with high percentage in all times and sites. No methanotrophic bacteria

were detected in MLSB_October/2011 sample, but the tailings water demonstrated methane

oxidation activity. N/A in the table indicates that no data are available.

Sample Methylocaldum Crenothrix/Methylosoma Methylomonas Methylomicrobium Total percentage of

methanotrophs

WIP_July_2011 83.0 0.94 16 0 0.33

WIP_July_2011 76.1 14.2 4.76 4.76 0.80

WIP_August_2011 78.2 6.95 13.8 0.86 0.84

WIP_October_2011 90.9 0 9.09 0 1.04

WIP_December_2011 79.7 13.0 7.14 0 0.75

MLSB_July_2011 100 0 0 0 0.02

MLSB_August_2011 100 0 0 0 0.01

MLSB_October_2011 N/A N/A N/A N/A N/A

MLSB_December_2011 66.6 33.3 0 0 0.05

69 3.4.4 Neighbor-Joining (NJ) 16S rRNA Gene Based Phylogenetic Tree

Constructed from 16S rRNA Gene Pyrotag sequencing Data

A neighbor-joining 16S rRNA gene based phylogenetic tree was constructed using our methanotroph-affiliated sequences aligned against the ARB SILVA database (used as the model) [Figure 3-6]. The tree consists of both known classes of

Gammaproteobacteria and Alphaproteobacteria methanotrophs with 1000 bootstaps used as a measure of support. The constructed tree illustrates the presence of a large proportion of methanotrophs evolutionary related to the known Gammaproteobacteria group within surface layers of MLSB and WIP and negligible traces of Alphaproteobacteria related methanotrophs.

According to the phylogenetic tree (Figure 3-7) the predominant OTUs 12103 and 4491 (shown in red) grouped within the known Methylococcaceae family, but they formed their own group close to the thermophilic genera of Methylococcus and Methylocaldum. OTU 19527 (shown in red), which has been identified as Crenothrix spp. by Greengenes database, demonstrated a close evolutionary relationship to its neighboring, recently discovered and isolated methanotroph,

Methylosoma difficile, which is also closely related to Methylobacter tundripaludum with 94% similarity [138]. In this study based on the location of OTU 19527 in the phylogenetic tree, it is referred to as Crenothrix/Methylosoma. OTU 3620 (shown in red) also groups distantly to not well-characterized Methylobacter marinus, which is no longer available in any culture collections.

OTU 3620 [Figure 3-6] represents an isolate that became a target methanotroph for characterization in this study. Characterization procedures are explained in the next chapter. Five

70 Methylobacter species have been reported so far, most of them described by Bowman and colleagues; Methylobacter luteus, Methylobacter marinus, Methylobacter psychrophilus,

Methylobacter tundripaludum, and

Methylobacter whittenburyi (http://www.bacterio.cict.fr/m/methylobacter.html) [58, 139, 140].

Distant clustering of OTUs 12103, 4491 and 3620 to their closest evolutionary relatives implies that these represent not previously characterized genera or species of methanotrophs within WIP and MLSB surface layers. Targeting them could expand our knowledge surrounding these natural methane biofilters particularly the thermophilic/thermotolorant Methylocaldum related species.

Only three species of Methylocaldum have been validated so far; Methylocaldum gracile,

Methylocaldum tepidum, Methylocaldum szegediense [136].

71 70% Methylococcus capsulatus (AJ563935) 99% OTU 12103 70% OTU 4491 97% Methylocaldum tepidum (U89297) Methylocaldum gracile (U89298) 78% Methylocaldum szegediense (U89300) G 97% Methylosoma difficile (DQ119050) a

m 78% OTU 19527 90% Crenothrix polyspora (DQ295889) m Methylomonas methanica (AF304196) a 57% p

Clonothrix fusca (DQ984190) r 99% OTU 3863 o 65% t Methylomonas scandinavica (AJ131369) e OTU 14708 o 61% b

79% Methylobacter luteus (AF304195) a

90% Methylobacter marinus (AF304197) c

t

OTU 3620 e

64% Methylomicrobium japanense (D89279) r

i 96% Methylomicrobium kenyense (AJ132384) a OTU 16215 61% Methylosarcina fibrata (AF177296) Methylosarcina quisquiliarum (AF177297) 74% Methylomicrobium agile (EU144026) 98% Methylomicrobium album (EU144025) A

l

Methylosphaera hansonii (U67929) p

Methylohalobius crimeensis (AJ581837) h 79% Methylocystis parvus (Y18945) a 99% p

Methylocystis hirsuta (DQ364433) r Methylosinus trichosporium (Y18947) o

t

56% Methylocella silvestris BL2 (CP001280) e Beijerinckia indica (CP001016) o 59% Methylocapsa sp. KYG (FN433469) b

a

Methylocapsa acidiphila (AJ278726) c

t

e

r

0.10 i

a

Figure 3-6. Neighbor-joining 16S rRNA gene based phylogenetic tree constructed based on 16S rRNA gene sequences shows methanotrophic bacteria in our tailings samples group within the known major Gammaproteobacteria class. Bootstraps are shown for 1000 constructions

(bootstraps less than 50% have been removed from the tree) and the scale bar represents 0.1 mutation per base position.

72 3.4.5 Identification of Active Methanotrophs Using Stable Isotope Probing (SIP)

We performed a DNA_SIP on the WIP December sample (2011), and identified heavy fractions with increased DNA concentrations as compared to the unlabeled control (incubated for 22 days).

Based on the SIP graph [Figure 3-7] fractions 6 and 9 from the 13C isotopically labeled samples and fractions 8 and 9 from un-amended control DNA directly extracted from fresh tailings water were chosen for further Pyrotag sequencing -based analysis. 16S rRNA gene Pyrotag sequencing of the fraction 6 (1.4040nD_Tc with DNA Density of 1.733 g/ml), which was the heaviest fraction selected for sequencing, showed that it was composed primarily of bacteria related to methanotrophs [Figure 3-7].

Methylocaldum/Methylococcus related OTUs comprise 51.1% of the heavy fraction and imply the incorporation of a large quantity of 13C into their DNA. This observation was an indicator that the main methanotroph detected in the raw tailing (Methylocaldum/Methylococcus) is active in the SIP experiment. Crenothrix/Methylosoma forms 7.40% only in the isotopically labeled fraction 6. In fraction 8 of the control, OTUs of Crenothrix/Methylosoma with 0.88% are more dominant compared to the main methanotroph, Methylocaldum/Methylococcus (0.13%). OTUs related to Comamonadaceae species are present in all labeled and unlabeled fractions, particularly in the unlabeled fraction 9, where it makes up 56.0 % of the microbial community

[141, 142]. These particular microorganisms are reduced dramatically to 2.60% in the 13C labeled fraction 6.

73

74 Figure 3-7. DNA-Staple Isotope Probing analysis of the WIP_December_2011 Sample.

Density values are plotted versus DNA concentrations in order to identify the heavy fractions with increased DNA concentrations as compared to the unlabeled control. The yellow and green

13 pie charts (fractions 9 and 6) represent the light and heavy fractions of the CH4 incubation, while the blue and grey pies (fractions 9 and 8) represent light fractions of control DNA from unincubated tailings water. Numbers in the stars are the fraction numbers analyzed by pyrotag sequencing (16S rRNA gene based). Relative DNA concentration values (calculated based on dividing each DNA concentration values to the highest concentration fraction in the column) were used in order to normalize the data for distinguishing the peaks and prevent the effect of fluctuations of DNA concentrations in the graph (for reducing the effect of minor errors).

75 Recently isolated (2004) Kaistia spp, affiliated to the Rhizobiaceae family of

Alphaproteobacteria, is present and forms 30.3% of the fraction 9 of the SIP incubated sample

(representing light, unlabeled DNA). Im et al. (2004) have reported this microorganism as a phenol resistant microbe when it is subjected to 4-chlorophenol or other derivatives of phenol with high concentrations (resistant to 1mM for one week), and consumes a wide range of hydrocarbons [143, 144].

QIIME failed to identify some OTUs in fraction 6 (heavy, labeled DNA) of the SIP incubation, because the BLAST database used did not include eukaryotes. Sequences were therefore compared to online NCBI database (http://blast.ncbi.nlm.nih.gov/Blast.cgi) via BLAST and were identified as an organism closely related to Vorticella spp. (with 98% BLAST identity) a genus of protozoan, which belongs to Eukarya domain. Vorticella is a common fresh water contaminant.

This organism grazes largely on bacteria, except the genus Vorticella campanula, and has a wide global distribution [145]. Feeding upon active methanotrophic microbes might have made them labeled and visible in large numbers in our experiment [79].

Non- methanotrophic species especially Comamonadaceae make up a large portion of the natural tailings. The identification of Methylocaldum/Methylococcus and Crenothrix/Methylosoma in the heavy SIP fraction is consistent with their dominance in the natural tailings water and confirms their role as active methane consumers. Metagenomic analysis of the heavy 13C-DNA in our sample (by Dr. Ivica Tamas) provided additional information about Methylocaldum at the genome level and valuable information at an evolutionary scale [85].

76 3.4.6 Time Course Stable Isotope Probing Experiment

In order to investigate how methanotrophic microbial community changes in SIP fractions in relation to the time of incubation, particularly the presence of the two dominant methanotrophs,

Methylocaldum/Methylococcous and Crenothrix/Methylosoma in the heaviest isotopically labeled fraction, we subjected WIP August/2012 samples to time course based 13C DNA-SIP, with samples harvested at 1, 3, 12, 24 h [Figure 3-8].

The 1 h, 3 h, 12 h SIP experiments (referred to as WIP_1H, WIP_3H, WIP_12H) did not demonstrate any noticeable shift in the DNA density (g/ml) for the labeled sample compared to raw control (WIP_1H). It seems enough labeling did not happen in these specific time courses.

On the contrary, 24 h SIP (referred to as 24 H) seems to be enough time for the active methanotrophs to incorporate labeled methane into their DNA (Fraction 7 demonstrates an obvious shift compare to 1 h control).

There are a few possible reasons for the failure of this experiment at one, three, twelve hours;

i) Methanotrophs require enough time to complete their growth cycle, which will result in their genome completion. ii) Radajewski et al. (2002) reported that oxidation of at least 0.2 mmol of labeled substrate was a minimal requirement for a successful SIP experiment in order to visually

13 [110] observe a DNA band from 1 g of soil sample subject to CH4 iii) Based on oxidation measurements, methanotrophs in some samples demonstrated long lag phases- in this stage microbes are adapting to the new system and are not capable of dividing, but are synthesizing

RNA, enzymes and other molecules.

77

78 Figure 3-8. Time course Stable Isotope Probing experiment on WIP (August/2012 sample). In figure WIP sample were subjected to 13C for 1 h, 3 h, 12 h, and 24 h. 1 h has been used as a control for comparison. Density values are plotted versus DNA concentrations in order to identify the heavy fractions with increased DNA concentrations as compared to the unlabeled control.

Relative DNA concentration values were used in order to normalize the data for distinguishing the peaks. Fraction 7 (counting order strats from the bottom to top part of graph) from the 24 h

SIP sample clearly demonstrates an obvious shift compare to 1 h control.

79 In conclusion for this experiment it seems that methanotrophs require a specific period of time and suitable conditions to incorporate enough 13C in their DNA and divide based on this labeled carbon source. The 24 h sample did demonstrate a mild shift compared to the earlier times, which indicates incorporation of methane-derived carbon [79]. Further investigation in time course SIP combined with pyrotag sequencing analysis of the heavy fractions are required in order to demonstrate activity beyond 24 h, which might elucidate the activity of different types of methanotrophs or the consistency of the dominant Methylocaldum/Methylococcous.

Unfortunately due to time and financial constraints this analysis was not yet made. It would be interesting to compare the results of the 24-h SIP to the 22-d SIP shown in [Figure 3-7].

3.4.7 Potential Methane Oxidation Rates

Duplicate samples with a leakage control were prepared from WIP and MLSB tailing waters during July/2011, August/2011, October/2011 for methane oxidation rate measurements

[Appendix 10]. The oxidation rates were determined based on linear regression of methane mixing ratios (mol CH4/mol gas) in headspace [Figure 3-9].

80

Figure 3-9. An example incubation showing the decrease in methane in the headspace of the

WIP_August_2011 sample over time. Linear regression lines of samples and a leakage control

(containing only sterile tailings water) versus time are shown. Sample was very active and formed a non-sigmoid, linear graph due to lack of lag phase and the possibility of no growth or equal rates of growth and death among the active methanotrophs.

81 The potential methane oxidation rates in surface tailing waters of WIP and MLSB are shown in

-1 -1 [Figure 3-10].Oxidation rates ranged from 75.6 nmol CH4 ml d (July_MLSB_2011) up to

-1 -1 135.6 nmol CH4 ml d (August_MLSB_2011). Most of the graphs are showing 2- 4 d of lag phase except WIP_August_2011 sample, which did not form a sigmoid graph due to lack of lag phase and the possibility of no growth or equal rates of growth and death among the active methanotrophs. CH4 was dramatically reduced, which is shown with linear regression up to point of 14-20 d. WIP_July/2011 samples were not active compared to the other samples and consumed only 10% of the available methane in the headspace in 10 days. MLSB _July/2011 samples were also weak in activity with an initial 6 d lag phase. The maximum methane oxidation activity was evident at the end of summer (August/2011) and mid autumn

(October/2011) in the Athabasca oil sand tailings ponds [12, 175].

Our rates are comparable to the methane oxidation rates measured from aquatic systems such as natural lakes and oceans [12]. In general soil methanotrophs demonstrate higher methane oxidation

-1 -1 -1 -1 capability, ranging from 0.17-80 mol CH4 g d (170 – 80,000 nmol of CH4 g d ) in the same geographical zone compared to tailing water methanotrophs [12]. We extrapolated the highest

-1 -1 methane oxidation rate of our samples (136 nmol CH4 ml d ) to the entire surface area of the

MLSB tailings pond (in 10 km2) by assuming an active depth of 60 cm (based on table 3-1). The

6 -1 result is a crude value of 18  10 L CH4 d , which is about 18% of the estimated methane emission rate of MLSB [12] [Appendix 11]. 60 cm mentioned in table 3-1 was the greatest depth detectable via electrodes of syncrude’s scientists (with 0.01 mg L-1 detection limit. Refer to table

3-1). This detection point is about 1 M, which is in the same order of magnitude close to the Ks values (oxygen affinity) of methanotrophs with 2-10 M (they are capable of outcompeting

82 [12] heterotrophs for O2 in an oxygen limited environment) . We assume this active zone of 60 cm is ideal for our experiments because in deeper portions of the ponds methanotrophs are not detectable due to the limit of the device used for measuring the oxygen.

Previous studies emphasized the dominance of type II methanotrophs over type I in freshwater systems, but in surface tailing waters, which are engineered alkaline aquatic systems , Type I are dominant and negligible numbers of type II methanotrophs were detected [12, 59]. At least five factors may contribute to the dominance of type I methanotrophs. Salinity, temperature, pH, the oxygen level as well as high nitrogen concentration in tailing waters may influence the methanotrophic community and select for particular genera of methanotrophs.

It is known that temperature is an important environmental variable that is able to affect physiological and biochemical activities in microbes [147, 148]. Temperature may act as selecting factor, which may ultimately favour different microbial populations in different environments

[146 – 148, 173, 176]. Early studies of methanotrophic physiology and distribution highlighted that most of the validly described methanotrophic bacteria were with optimal growth at 25 oC

[41, 45, 59]. Isolation of Methylococcus capsulatus Bath (growth at 45 oC), thermophilic to thermotolerant species of Methylocaldum (tepidum and gracile are themotolerant species of genus Methylocaldum with growth capability at 30 - 47 oC and 20 - 47 oC respectively)(Methylocaldum szegendiense is a thermophilic methanotroph with growth range of

37 – 62 oC), Methylothermus with growth between 62 – 65 oC, and Verrucomicrobia methanotrophs (with growth range of 37 - 65 oC) expanded the frame of methanotrophy from mesophiles into thermophiles/thermotolerants [136].

83

Figure 3-10. Potential methane oxidation rates of WIP and MLSB samples from July/2011 until

October/2011. Oxidation rates are means of duplicate incubations  1 standard error.

84 Based on results obtained from both cultivation-dependent and cultivation-indepenent approaches for studying methanotrophs in various terrestrial systems, scientists have demonstrated a dominance of Alphaprotebacteria over Gammaproteobacteria in cold environments (such as

Methylocella palustris and Methylocapsa acidophila) [67][59][137]. However, some methanotrophs isolated from cold environments are affiliated to the type I group including Omelchenko’s et al.

(1992) isolate (Methylobacter psychrophilus) from tundra soil (6 oC) and Bowman’s et al. (1999) isolate (Methylosphaera hansonii) from deep igneous rock [146][178]. Pacheco – Oliver et al. (2002) observed a group of unkown type II methanotrophs in Canadian arctic tundra soil, which grouped distantly to the known Methylosinus and Methylocystis species [177]. PLFA analysis of Börjesson and colleagues (2004) obtained from landfill cover soil indicated the dominance of Type I methanotrophs at 3 – 10 oC and growth of both classes (Type I and Type II) at 25 oC.

Vecherskaya et al. (1993) lab reported the dominance of Methylobacter and Methylomonas species (from Gammaproteobacteria class) than Methylocystis related species (from

Alphaproteobacteria class) in tundra soils (9 oC) [172]. Gebert and colleagues (2003) were successful in isolating Methylosinus related species (Type II) (at 28 oC) and Methylobacter species (Type I) (at 10 oC) from a biofilter [174].

WIP and MLSB water temperature has been reported at 20 oC, which is not cold compared to its surrounding environment but the heating of recycled water (60 oC) may be the main reason for

Methylocaldum/Methylococcus dominance due to their high temperature tolerance capability compared to the other species. When the water temperature cools down to 20 oC other methanotrophs such as Methylobacter and Methylomonas related species will have opportunity to thrive. Unfortunately there are no clear data regarding the water recycle schedule of the mentioned ponds, but the obtained data from 454 pyrosequencing of the surface waters highlights

85 the potential role of temperature in selecting particular gammaproteobacterial methanotrophs and elimination of the alphaproteobacterial methanotrophs.

Ammonium is an inhibitor of methane oxidation and another potential factor controlling the

[12] methanotrophs in tailing waters . This could be because of the competition between CH4 and

NH3 molecules for the enzyme’s active site, which generates toxic hydroxylamine in the cell

[52, 55, 59, 179]. Again there are contradictory findings regarding the nitrogen effect on methanotrophic bacteria and some reviews highlighted ammonium as beneficial nutrient, which stimulates methanotrophic activity [59]. Bodelier and Laanbroek (2004) explained these non- consistent reports that if methanotrophs are in an ammonium saturated environment the excess nitrogen will act as inhibitory factor and causes shift in the community, otherwise it is important for stimulating growth of methanotrophs [180].

Most of the known nitrogen-fixing methanotrophs belong to the alphaproteobacterial group and a small number of gammaproteobacterial methanotrophs including species of Methylococcus [53].

Results from a series of experiments performed by Mohanty et al. (2006) by subjecting ammonia to rice paddy and forest soil samples, Noll et al. (2008) by subjecting urea to rice paddy soil samples, and Lee et al. (2009) by subjecting ammonium to landfill samples, collectively revealed that ammonium is an important selecting factor and selects gammaproteobacterial class of methanotrophs over alphaproteobacterial class of methanotrophs [59, 18 - 183].

These findings match with our 16S rRNA based pyrotag sequencing profile of the WIP and

MLSB tailing waters by demonstrating the dominance of type I methanotrophs over type II. It

86 seems nitrogen is another important factor, which select for Methylocaldum/Methylococcus species of Gammaproteobacteria methane oxidizers that are unable fixing nitrogen.

Based on the data provided by Syncrude, dissolved O2 has a rapid turnover and limited in the surface layers [Table 3-1] [12]. This could be because of the high biological and chemical oxygen demand of the tailing water, which are the result of high concentration of chemical compounds

[12] and unused oil sand particles (generated after the extraction process) . O2 penetration depth defines the thickness of the oxic zone in any system and permits window of opportunity for aerobic microbial activity [153].

Amaral and Knowles (1995) demonstrated that oxygen and methane together act as selecting factors for particular groups of methanotrophs and they result in a major shift in aerobic methane oxidizing population [184]. In agar diffusion columns countergradients of oxygen, gammaproteobacterial methanotrophs were dominant in layers with low CH4 and high O2 mixing

[184] ratio (mol CH4/mol gas) . Alphaproteobacterial methanotrophs noticeably dominated the layers with high CH4 and low O2 mixing ratio (mol CH4/mol gas). This might be because of this fact that low O2 stimulates nitrogen fixation, which majority of Alphaproteobacteria methanotrophs are capable of fixing it or their direct adaptation to limited O2 and High CH4 concentrations [184].

Due to high sensitivity and major influence of oxygen on methanotrophic activity, researchers such as Rudd and Taylor (1980) coined the term ‘functional facultative microaerophils’ for methane oxidizers [45, 73, 185]. Henckel et al. (2000) detected Gammaproteobacteria methanotrophic bacteria as most active in high methane and low oxygen mixing ratio (mol

87 [73] CH4/mol gas) in ricefield soil . Retrieved data indicates that there are group of methanotrophs related to type I class, which are adapted to low amount of oxygen and high concentrations of

[73] CH4 .

It has been hypothesized by Vecherskaya et al. (1993) and Hanson and Hanson (1996) that

Gammaproteobacteria methanotrophs are dominant in environments that support methanotrophy with sufficient amount of methane, oxygen and nutrients, but in environments with limited growth factors eventually population structure will shift toward Alphaproteobacteria methanotrophs due to their capability to survive in such restricted conditions [45, 172].

It seems that the dominant Gammaproteobacteria methanotrophs in tailing waters are adapted to low oxygen and high methane concentrations, which is the opposite of Amaral and Knowle, and

Henckel’s observations [12]. Low oxygen and high ammonium concentrations might be responsible for elimination of type II methanotrophs and the main factors explaining the abundance of Methylococcus/Methylocaldum species [12]. Studies investigating the effect of oxygen and methane on methanotrophs and investigating their ecological niches under such conditions in tailing waters are required.

Salinity could also play a role in methanotrophic population by limiting the oxidation rates due to osmotic stress [188]. The majority of known halotolerant and halophilic methanotrophs belong to

Methylomicrobium (Methylomicrobium pelagicum AA-23T [with 0.3-0.8 M of optimum NaCl], and Methylomicrobium sp. IR1[with 0.2-0.7 M of optimum NaCl], Methylomicrobium hansonii

AM6T, AM11 [requires sea water up to 1.1], Methylomicrobium alcaliphilus 5Z, 20Z [with 0.09-

1.5 M of optimum NaCl], Methylomicrobium modestohalophilus [with 0.03-1.5 M of optimum

NaCl], Methylomicrobium buryatense 5BT,4G,5G,6G,7G [with 0-1.4 M of optimum NaCl]) and

88 Methylohalobius (Methylohalobius crimeensis 4Kr [with 0.2-2.5 M of optimum NaCl] and

Methylohalobius crimeensis 10KiT [with 0.2-2.5 M of optimum NaCl]) genera of

Gammaproteobacteria class [186]. It seems that majority of type I are capabale of surviving in saline environments [64, 186].

Soda lakes are an ideal sampling field for studing alkaliphilic methanotrophs because these lakes demostrate high salinity and very high pH ranges [64]. Studies on Siberian soda lake and Kenyan soda lake with pH 8.0-10.5 highlighted the dominace of Gammaproteobacteria methanotrophs specially Methylomicrobium burytense and Methylomicrobium alcaliphilum species (they are capabale of thriving at pH 10.5 -11.0) [64]. Acidic geothermal sites are mainly occupied by

Methylacidiphilum (methanotrophs from phlum Verrucomicrobia) , Methylocapsa and

Methylocella related species (related to Alphaproteobacteria methanotrophs). Later mentioned methanotrophs are able to thrive at pH 4.2, but Verrucomicrobial Methyloacidiphilum species are capable of growing at pH 0.8 (optimum 2.0 - 3.5) [64]. So far studies related to methanotrophs in extreme environments are supporting this fact that that the high pH is favouring

Gammaproteobacteria methanotrophs instead of Alphaproteobacteria methane oxidizers [64].

The methane oxidation rate and methanotrophic communites are consistent over time. Consistent occurrence of Methylocaldum/Methylococcus related OTUs in surface water suggests a minor shift in methanotrophic population. It seems the main limiting factors mentioned above are consistently favoring gammaproteobacterial methanotrophs, especially the

Methylocaldum/Methyloccous group instead of alphaproteobacterial methanotrophs.

89 3.4.8 Potential Methane Oxidation Rates at Different Temperature Ranges

Samples from MLSB and WIP were incubated on a rotary shaker at -20, +4, +17, +21, +30, +37,

+45, +55 and +65 oC and were monitored with GC/FID as explained in the methodology section.

-1 -1 o Mean oxidation rates in nmol CH4 ml d were plotted versus temperature ( C)) [Figure 3-11].

Temperature has a direct effect on the enzyme-catalyzed reaction rate [149]. As shown in the

[Figure 3-12] as temperature increases, the enzymatic reaction rate also increases exponentially, but at a certain point it will reach to its maximum, which defines its limit and above this point temperature increase will have no effect on the activity rate. After the optimum temperature point, denaturation of the enzyme takes place. The result will be a crooked bell shaped graph

[Figure 3-12] , while in our graph there is a broad range of near-optimal temperatures. 30 oC will be the main optimum temperature point for both samples, which means most of the methanotrophs in tailing waters are well adapted to this temperature, but there is also a large amount of activity above this point, suggesting that some of the bacteria present are thermotolerant, if not thermophilic.

Based on the available biokinetic temperature data, most isolated methanotrophs are classified as mesophiles thriving from 10 to 40 oC with optimum temperature at 30 oC [41]. The genera

Methylocaldum and Methylococcus from the Methylococcaceae family of Gammaprotebacteria methanotrophs are classified as thermotolorant/thermophilic microbes with growth at 20 – 55 oC with optimum temperature at 45- oC [41]. It is possible that the dominant methanotroph,

Methylocaldum/Methylococcous, detected in tailings water and SIP heavy fractions is present and responsible for methane oxidation at 45 oC.

90 To determine if there was any psychrotolerant methanotrophic activity, oxidation rates were measured at 4oC. Frozen -20 oC samples were used as negative control [Figure 3-13]. There was no detectable methane oxidation activity at less than 10 oC, which indicates the probable absence of the psychrophilic methanotrophs (0 – 22 oC) and a large presence of mesophilic and thermotolerant aerobic methane oxidizing bacteria (4 – 37 oC) [41].

3.4.9 Bacterial Cultures and Approaches for the Characterization of Novel

Methanotrophs

Growth was observed on the plates inoculated with WIP and MLSB tailing waters (referred to as

TW and TM respectively) after one week of incubation under amended atmosphere of 20.5% CH4

(v/v) and 5.06-10.7% CO2 (v/v) balanced with air.

Culture plates were screened visually using a SZ61 zoom stereomicroscope (Olympus, Tokyo

Japan) for observing the colony morphology and the selection of the colonies of interest with colony morphologies similar to known methanotrophs. Target methanotrophs were mainly screened based on colony pigmentation, for instance Methylococcus related colonies contain white or buff, orange and brown, Methylomonas related colonies red to pink and Methylobacter colonies yellow to brown, and Methylocaldum colonies light brown pigments [136, 139]. Selected colonies were serially transferred on TM, TW and later on to M10 plates for the single colony isolation. Their identities as methanotrophs were assured by 16S rRNA (primers 9f and 1492b) and pmoA (primers 189f and 661b) based PCR amplification of the colonies followed by detecting bands on a 1% agarose gel stained with SYBR® Safe (Life Technology, Burlington, ON, Canada)

DNA gel stain. Purified PCR products were sent for sequencing by Applied Biosystems 3730xl

91 96 capillary DNA sequencer (capillary-based automated Sanger sequencing) at the University of

Calgary Core DNA sequencing facility (Alberta, Canada).

Sequencing results were visually checked for any background noise (such as signs of impurity due to contamination) and mismatches (compared to the reference sequences) via Contig Express version 11.5.1 (component of Vector NTI Advanced, Invitrogen part of Life Science 2011).

Trimmed sequences were compared to the reference sequences in NCBI

(http://blast.ncbi.nlm.nih.gov/Blast.cgi) and Ez Taxon-e (http://eztaxon-e.ezbiocloud.net/) databases via nucleotide BLAST tool.

About 50% of the pure cultures matched with 100 – 98% similarity to Methylocystis and

Methylosinus related species of Alphaproteobacteria, which were not detected at high abundance in 454 pyrotag data nor in SIP heavy fractions. This suggests a strong nutritional bias introduced by the media and incubations (nutritional biases caused by tailing water components or the gelling agent used in culture plates). In addition to the Type II related methanotrophs, Methylomonas related species were detected with 97% maximum identity to Methylomonas scandinavica (16S ribosomal RNA gene, partial sequence) as the most abundant Gammaproteobacteria methanotroph on the culture plates [150]. An isolated Methylomonas was identified by Ez Taxon-e closely related to Methylomonas scandinavica, strain R5T with 97.65% pairwise similarity and

96.2 % completeness. In order to support our results from both databases (NCBI and Ez Taxon-e), a 16S rRNA gene phylogenetic tree with Treepuzzle method (based on a Maximum Likelihood algorithm) was constructed from the ARB SILVA database [151] [Figure 3-14].

92

Figure 3-11. Temperature effect on methane oxidation rates. Both samples demonstrate activity at 45oC. The optimum temperature is 30 oC. Oxidation rates are means of duplicate incubations 

1 standard error.

93

)

e o

t Optimum Temperature ( C)

a

r

g

o

L

(

y

t

i

v

i

t

c

A

e

m

y

z

n

E

f

o

e

t

a R

Temperature (oC)

Figure 3-12. Theoretical rate of enzyme activity versus temperature. The red star indicates the point of optimum temperature, beyond which there is a rapid decline in enzyme activity due to denaturation of the enzyme's active site.

94

Figure 3-13. Comparison of methane oxidation rates at three different temperatures. 37 oC is near the optimum temperature for tailing waters methanotrophs. No significant activity was detected at

4 oC within the 44 d of incubation.

95 Our isolated Methylomonas (shown in red) based on the figure (figure 3-16), taxonomically neighbored with Methylomonas scandinavica. Due to high 97% maximum identity of our target

Methylomonas to the reference sequence, we did not pursue this methanotroph for further analysis at physiological and biochemical levels, as it probably does not represent a new species.

Colonies cultured originally on M10 XCF plates were subjected to pmoA and 16S rRNA based

PCR amplification and purified amplicons were sent for automated capillary-based Sanger sequencing. Both forward and reverse sequences were combined (9f as the template primer and reverse sequence 1492b as the template primer in a total base pair of 1327) and visually checked for background noises or mismatches by ContigExpress (version 11.5.1) and Lasergene

(SeqMan Pro. Version 7.1.0[44.1]). The1365 bp sequence obtained was uploaded to NCBI and

Ez Taxon-e databases. Results were 96.54% similar to Methylobacter marinus (strain A45T).

Microbiologists agree on a general rule of a 97% identity boundary, suggested by Stackebrandt and Goebel in 1994 between unknown and known species of microbes [152]. Based on low identity percentage of 96.5, Methylobacter strain XLMV4 T was targeted for further characterizations, as it probably represents a new species (see next chapter).

None of the other methanotrophic genera such as Methylomicrobium, Methylococcus,

Methylocaldum, Methylosoma and Crenothrix were detected in the pmoA or 16S rRNA PCR assays from the enrichment cultures. Most of the selected colonies were affiliated to

Methylosinus, Methylocystis, Methylomonas, Sphingomonas, Agrobacterium, Pseudomonas,

Oceanibaculum, Phenylobacterium, Microcella, Pedobacter, Algoriphagus, Azospirillum,

96 98% Methylobacter marinus (AF304197) Methylobacter luteus (AF304195) Methylosoma difficile (DQ119050) Methylobacter psychrophilus (AF152597) 67% Methylobacter tundripaludum (AJ414655) Methylomicrobium buryatense (AF307138) Methylomicrobium japanense (D89279) 88% Methylomicrobium alcaliphilum (EF495157) 93% Methylomicrobium kenyense (AJ132384) Methylomicrobium pelagicum (X72775) 78% 54% Methylomicrobium agile (X72767) Methylomicrobium album (EU144025) Methylomicrobium agile (EU144026) 78% Methylosarcina fibrata (AF177296) 98% Methylosarcina quisquiliarum (AF177297) 83% Methylomonas Isolate Methylomonas scandinavica (AJ131369) 72% Methylomonas aurantiaca (X72776) 99% Methylomonas fodinarum (X72778) Methylomonas methanica (AF304196) 95% Methylosphaera hansonii (U67929) 96% Methylocaldum gracile (U89298) 95% Methylocaldum tepidum (U89297) Methylocaldum szegediense (U89300) 99% Methylococcus capsulatus (AJ563935) Methylococcus capsulatus (X72770) Methylohalobius crimeensis (AJ581837) Beijerinckia indica subsp. ATCC 9039 (CP001016) 92% Methylocella silvestris BL2 (CP001280) 80% Methylocella tundrae (AJ555244) Methylocapsa acidiphila (AJ278726) Methylocapsa sp. KYG (FN433469) 54% Methylosinus trichosporium (Y18947) Methylosinus trichosporium OB3b (ADVE01000118) 99% Methylosinus sporium (Y18946) Methylocystis rosea (AJ414656) 62% Methylocystis hirsuta (DQ364433) Methylocystis heyeri (AM283543) 99% Methylocystis echinoides (AJ458473) Methylocystis parvus (Y18945)

0.10

Figure 3-14. A 16S rRNA based bootstrapped (1000 construction as measure of support) phylogenetic tree constructed based on the Treepuzzle method. To construct the tree a nearly- complete 16S rRNA sequence of the Methylomonas isolate was generated from the combination of both forward and backward primed sequences. The scale bar represents 0.1 change per nucleotide position.

97 Devosia and Porphyrobacter genera. Non-methanotrophic bacteria may be growing on components of the tailings pond water added to the medium (such as residual bitumen or aromatic compounds), or on medium contaminants.

3.4.10 Approaches for Isolating Methylocaldum/Methylococcus Species

All of the incubated tailing waters with or without amendments at 45 oC, were inoculated onto the surface of TW, TM, M10 and M10 XCF culture plates. But none of plating culture methods were successful in isolating the thermotolerant/thermophilic methanotrophs detected by 454

Pyrotag sequencing or SIP heavy fractions, despite the fact that GC/FID demonstrated methane consumption at this temperature.

Based on this observation liquid enrichments were attempted in addition to plate cultures for further attempts to isolate the Methylocaldum/Methylococcus methanotroph. According to the

[Table 3-5], unamended tailings and tailings water stimulated with 0.02 mg of CuSO4 per L showed dramatic methane decline in the headspace. The natural tailing sample enriched with methane at 45 oC for 10 d was selected for further analysis via Cloning of pmoA gene PCR

Products (CloneJETTMPCR Cloning Kit, described in section 3.4). Obtained sequences were integrated into the NJ pmoA/amoA gene based skeleton tree generated via ARB software with the methods described in previous sections [Figure 3-15]. Based on the NCBI database our target sample was 99% Identical to the pmoA gene sequence of Methylocaldum gracile. A pmoA/amoA gene phylogenetic tree indicates that the isolate is distinct from the major species in tailings water.

98 There are at least two types of Methylocaldum related species in the tailings and for unknown reasons the culture conditions favored Methylocaldum gracile over the novel Methylocaldum spp. that dominated the pyrotag read sets from fresh tailings water.

Based on tree the detected Methylocaldum is not related to the novel Methylocaldum species detected in 16S rRNA profile of the WIP and MLSB tailings ponds (detected via pyrotag sequencing), which are shown in red (OTUs 113, 5 and 763). Methylobacter XLMV4 T (shown in red) is the recently characterized Methylobacter related species, which will be described in detail in the next chapter.

It seems that there are important chemical elements such as copper in tailing waters (which has been report 0.005 mg l-1) that are paving the path for the growth of the novel

Methylocaldum/Methylococcus species [12]. Low oxygen level might be another important factor, which could be considered in future experiments (countergradient based experiments). In general more amendments and incubation conditions at chemical levels on M10 XCF medium are required in order to mimic a growth system similar to tailing ponds and isolate the most abundant species into pure culture.

99 Table 3-5. Methane oxidation rates of tailing water samples (from August/2012) incubated at

o 45 C with or without copper (CuSO4 in 1L) or vitamin B50 complex (50 mg/mcg of vitamin Bs)

amendments. Samples were incubated for 10 d. headspace of the samples were filled with 15.4 –

15.73% CH4 (v/v) and 5.3 – 6.2% CO2 (v/v) balanced with air.

-1 -1 Sample CH4 Oxidation rates (nmol ml d )

Control (Autoclaved Tailings Water) 0

Natural Tailing Water 90.96

Tailing Water + Vitamin B50 Complex (1 capsule) +0.02 mg CuSO4 (in 1 L) 91.23

Tailing Water + 0.02 mg CuSO4 (in 1 L) 198.2

100

Figure 3-15. A pmoA/amoA gene tree built with NJ algorithm (built with the aid of distance matrix option of ARB) representing isolates from tailings ponds, sequences retrieved from tailings ponds via PCR, and reference sequences of methanotrophs [12]. Support values are based on 1000 constructions. Scale bar: 0.1 change per nucleotide position.

101 Chapter Four: Taxonomic Description of Methylobacter oleiharenae, sp. nov.,

an Aerobic Methanotroph from an Oil Sands Tailings Pond

*The draft genome was assembled by bioinformatics support specialist Xiaoli Dong at the Visual Genomics Center

(University of Calgary, Calgary, Alberta, Canada) (http://www.visualgenomics.ca/~xdong/projects.html) and annotation

was performed by submission to the IMG platform of the Joint Genome Institute (JGI) (http://www.jgi.doe.gov/) website.

*Dr.Ivica Tamas analyzed the metagenomic profile of strain XLMV4T.

* Nomenclature review of the Methylobacter oleiharenae was reviewed by professor Bernhard Schink,

([email protected])

* All of the characterization data of Methylobacter oleiharenae were reviewed by Dr. Joong-Jae Kim

4.1 Introduction

-1 0.27 mg L of dissolved O2 [Table 3-1] was detected in the surface layer of an oil sands tailings pond

(WIP), which permits a window of opportunity for aerobic methanotrophic microbes to thrive and actively consume some of the produced methane gas with the aid of methane monooxygenase enzymes

[12, 28, 153]. 16S rRNA gene based profile of methanotrophs in the mentioned tailing pond obtained via recently developed Pyrotag sequencing highlighted the presence of novel methanotrophs mainly affiliated to the Gammaproteobacteria class, including an isolated strain belonging to the genus

Methylobacter (strain XLMV4T) [12].

Currently there are five officially validated species of the genus Methylobacter; Methylobacter luteus,

Methylobacter whittenburyi, Methylobacter marinus, Methylobacter psychrophilus and Methylobacter tundripaludum [58, 139, 140]. Strain XLMV4T was isolated from surface water samples originally collected in 2011 from the top 10 cm of WIP oil sand tailing pond (10-15 m from the shore) (Latitude:

57°0033.14'N and Longitude: 111°3725.26'W) [12].

102 4.2 Methods

4.2.1 Isolation and Growth Conditions

A novel Methylobacter, Methylobacter oleiharenae (strain XLMV4 T) was isolated from aerated layers of Canadian West in-pit (WIP) tailings pond (top 10 cm). XLMV4 T colonies were detected on the surface of the culture medium M10 XCF with pH of 8.4, incubated for 7 d at

o 21 C in a room with no light source under a gas atmosphere of 20.6 % CH4 (v/v) and 5.5-10.7 %

CO2 (v/v) (balanced with air) in a closed desiccator. The strain was maintained by streaking single colonies on solid M10 XCF pH 8.4 or by inoculating single colonies into liquid M10 XCF pH 8.4.

The purity of the culture and the absence of heterotrophic satellite contaminants were assured by streaking the target cells on a series of nutritionally rich media such as; Luria-Bertani Broth (LB),

Nutrient Agar (NA), Reasoner’s 2A agar (R2A), mineral salts Medium 10 supplemented with various energy substrates [Appendix 5], as well as 50-well commercially available API plates with common bacterial carbohydrate sources (API 50 CH) [Appendix 12] [Appendix 13]

[Appendix 14] [Appendix 15]. pH of the test plates were adjusted to 7-7.5. Inoculated plates were incubated at room temperature under air for 96 h without detection of any colonies or change in the pH indicator used in API ampoules (0.17 g of Phenol Red dissolved in 10 ml of demineralized water).

Cultures were stored at -80 oC in 3% DMSO + M10 XCF (pH 8.4) for long-term storage. In all growth experiments plates of the bacterium were scraped into 10 ml of buffer (0.8% phosphate buffer saline) (NaCl 8.01 (g/L), KCl 0.2 (g/L), Na2HPO4.2H2O 1.78 (g/L), KH2PO4 0.27 (g/L),

103 adjusted to pH 7.4) and the suspension was used as inoculum. 80-ml flasks were used for growth experiments. These contained 30 ml of medium M10 XCF [Appendix 6] and 1 l of cell suspension (OD of the original cell suspension = 0.14 before adding to 80 ml flasks). Flasks were shaken on a rotary shaker at 150 r.p.m for suspending the cells uniformly prior to absorbance

(OD600) recording via an Ultraspec 10-cell density meter (Amersham Biosciences).

7-d-old colonies were subjected to pmoA gene (encodes for the alpha subunit of the membrane bound methane monooxygenase, which is common biomarker in majority of methanotrophs except genera Methylocella and Methyloferula) and 16S rRNA gene targeted polymerase chain reactions (PCR) [Appendix 7][Appendix 8]. The near-complete 16S rRNA gene of strain

XLMV4 T was obtained via Automated Sanger sequencing by assembling sequences (via

ContigExpress 11.5.1 assembling option) generated from primers 9f and 1492b. This generated a

1365-bp sequence after visual screening via Lasergene SeqMan Pro. Version 7.1.0(44.1) software for any mismatches and background noise. The sequence was incorporated into a 16S rRNA gene phylogenetic tree constructed based on NJ algorithm in ARB software (5.3-org-8209) with Jukes-Cantor (1969) distance correction filter and distance matrix algorithm.

4.3 Morphological and Bright Field Microscopic Characterization

Four-day-old colonies of strain XLMV4 T on culture medium M10 XCF pH 8.4 incubated at

21 oC were selected for morphological characterizations.

0.01%, 0.1%, 1% and 10% sodium dodecyl sulfate (SDS, NaC12H25SO4) were used for testing the cell wall durability. Seven-day-old samples were heat-fixed and stained with commercially

104 available Gram staining kit (BD, USA). For histological analysis (for detecting polyhydroxybutyrate granules) negative Nile Blue conjugated with fluorescence microscopy with

DAPI filter (100 objective) were employed. Duguid Negative Staining and hanging drop method and 0.5% Malachite Green dye was used for investigating the presence of the capsule, motility of cells and presence or absence of exospores respectively [154].

The microscope used in morphological Characterization of strain XLMV4T is an Olympus BX51 laboratory microscope equipped with a fluorescence illuminator, X-Cite Series (120Q EXFO).

The microscope is attached to a Retiga 2000R Q imaging camera (FAST 1394) with 1600  1200 pixels and Kodak sensor KAI-2020, capable of imaging in fluorescence microscopy.

4.4 Transmission Electron Microscopy (TEM)

The chemical fixation protocol used in this experiment for TEM preparation consists of two main steps; primary fixation and secondary fixation, which were intended to preserve the XLMV4T cells in as life-like conditions as possible. Fixation steps were necessary in order to stabilize the cellular ultrastructure without including any distortions or artifacts. The procedure is as follows;

1) for the primary fixation step primary components were added individually instead of fixative to cells pellets in 1.5-ml microfuge tubes obtained from both liquid and plate cultures. Cells were washed and centrifuged twice at 10,000 r.p.m (9400  g) for 50 min in 1× Phosphate Buffered

Saline (PBS) (pH 7.4. NaCl 0.8 g, KCl 0.02 g, Na2HPO4 0.144 g and KH2PO4 0.024 g all in 100 ml of filtered and autoclaved water). The components of the primary fixation were 0.16 ml of

25% glutaraldehyde, 0.34 ml autoclaved water, 0.5 ml of 0.2 M cacodylate buffer (Sodium

105 Cacodylate 0.2 M, pH 7.4. Electron Microscopy Sciences, Canada) and 0.02 ml of 0.1 M CaCl2.

Samples were fixed at room temperature in 2-ml microfuge tubes for 2 h.

Samples were washed for 5 min three times in 0.5 ml cacodylate buffer mixed with 0.5 ml of distilled water. Samples were centrifuged at 3000 r.p.m (840  g) for 10 min, just enough to pellet cells and pour off the supernatant. In order to stain the membrane structures especially its lipids, samples were post-fixed in 0.5 ml of 2% Osmium Tetroxide (OsO4) and 0.5 ml of cacodylate buffer. Secondary fixations in 4% OsO4 were performed. Cells became black in color after one hour post-fixation at room temperature, which indicates the activity of the fixative.

Cells were centrifuged for 1 min at 3000 r.p.m and OsO4: buffer solution was removed.

A series of ethanol dehydration steps was performed as water and most epoxy resins are not miscible. Water prevents the infiltration of the epoxy resin into the cells and must be removed prior to embedding. Ethanol solutions used in dehydration steps were 30%, 50%, 70%, 85%, 95% and 100% with two changes of 5 min for each concentration except 100%, which was 3 changes of 10 min each. In each change samples were centrifuged for 1 min at 3000 r.p.m.

Propylene oxide (C3H6O) was employed with 3 changes for 10 min each as a transitional solvent as it is miscible with both ethanol and the mixed, unpolymerized epoxy resin. Samples were infiltrated with 1:1 propylene oxide: epoxy resin overnight. Propylene oxide with equal volume of epoxy resin makes a gradual transition to pure epoxy and enhances infiltration of the cells.

Fluka Analytical 45359 Epoxy-Embedding kit was used in the previous step as embedding resin.

Samples were immersed in freshly made 100% epoxy resin for 2-4 h and this was repeated for another extra 1-2 h. Cells were polymerized at initial 45 oC for 12 h and a final polymerization at

60 oC for 24 h.

106 Samples were sent for thin sectioning and imaging at the University of Calgary Microscopy and

Imaging Facility (MIF) located at Foothills Medical Centre (http://www.ucalgary.ca/mif/).

Images were taken by a Hitachi H-7650 120kV Transmission Electron Microscopy (TEM) equipped with a 16 Megapixel camera with realistically achievable resolution of 2 nm

(http://www.ucalgary.ca/mif/h7650tem) [Figure 4-8][Figure 4-9]. [140]

4.5 Carbon and Nitrogen Sources

Published data for eleven methanotrophs and two methylotrophs; Methylobacter tundripaludum,

Methylocapsa acidiphila, Methylocella palustris, Methylocella silvestris, Methylocystis bryophila, Methylocystis heyeri, Methylocystis hirsuta, Methylocystis rosea, Methylobacterium oryzae, Methylohalobius crimeensis, Methylomonas koyamae, Methylorosula polaris,

Methylosoma difficile were used as reference for carbon and nitrogen concentrations used in their characterization, which were in the range of 0.05% - 0.5% (w/v) for the carbon sources and

0.05% - 0.1% (w/v) for the nitrogen sources [70, 138, 140, 188, 189, 190 - 196].

Separate liquid cultures of strain XLMV4T in M10 XCF medium amended with the target carbon and nitrogen sources were prepared in total volumes of 50 ml in series of 250-ml sealed glass bottles (with 12.5-16.6% CH4 (v/v) and 5.06-7.8% CO2 (v/v) balanced with air) and the turbidity

(Optical density) of the samples was measured in 1-d intervals via an Ultraspec 10 cell density meter at optical density of 600 nm for a total of 22 d of incubation at room temperature with no light source on rotary shaker (120 r.p.m). The following carbon sources were used for the characterization of Methylobacter XLMV4T strain; sodium acetate anhydrous (10 mM or 0.08% w/v), sodium pyruvate (10 mM or 0.11%), sodium succinate dibasic hexahydrate (10 mM or

107 0.27%), sodium formate (10 mM or 0.06%), sodium citrate tribasic dehydrate (10 mM or 0.29%).

Three concentrations of 10 mM, 100 mM, 1 M of methanol was used in 20-d of incubation.

XLMV4 T cultures were supplemented with eleven primary nitrogen sources; ammonium chloride

(10 mM or 0.05%), sodium nitrate (10 mM or 0.08%), sodium nitrite (10 mM or 0.06%), L- valine (10 mM or 0.11%), urea (10 mM or 0.06%), glycine (10 mM or 0.07%), L-alanine (10 mM or 0.08%), L-proline (10 mM or 0.11%), L-serine (10 mM or 0.1%), L-aspartate (10 mM or

0.1%) and nitrogen gas (12% balanced with air). Non of the common sugur sources were used in the characterization procedure dou to reports that non of the reference strains were able to consume sugurs. In addition pure isolate of strain XLMV4T did not show any growth in the presence of common bacterial carbohydrate sources in 50-well API plates incubated under the atmosphere amended with the mixture of CH4, CO2 and air.

4.6 Optimum pH, Temperature, Iron, Copper and NaCl

Strain XLMV4 T was inoculated into liquid M10 XCF medium adjusted to pH 6, 6.5, 7, 7.5, 8,

8.5 and 9 (adjusted with 10% sodium hydroxide [NaOH] and 1 M hydrochloric acid [HCl]).

Samples were prepared in 250-ml sealed bottles and were incubated at 21 oC on a rotary shaker

(120 r.p.m) for 27 d. The headspace of the bottles were filled with 17.5-20.8 % CH4 (v/v) and 5.4

% CO2 (v/v) balanced with air and the optical density was measured at 600 nm wave-length at 1-

2 d intervals (pH of the samples were not measured at the end of the experiment).

Strain XLMV4T was inoculated into series of 80-ml glass bottles filled with liquid M10 XCF (pH

8.4) and these were incubated at 4, 10, 15, 20, 25, 30, 37, 40, 45 oC on a rotary shaker (120 r.p.m) for 27 d. The headspaces of the bottles were filled with 17.9-21.05 % CH4 (v/v) and 5.4-9.2 %

108 CO2 (v/v) balanced with air and the optical density was measured at 600 nm wave-length at 2 d intervals.

50 ml of M10 XCF (pH 8.4) was aliquoted into series of 250 ml glass bottles and 12 concentrations of 0.01, 0.05, 0.1, 0.2, 0.5, 1, 10, 20, 30, 40, 50, and 100 mmol of cupric sulfate pentahydrate (CuSO4 . 5H2O. Technical grade crystalline) was prepared and strain XLMV4 cells were inoculated in order to test the cupper endurance capability. Headspace of the bottles were filled with 14.32 – 15.72% CH4 (v/v) and 5.3 – 6.2% CO2 (v/v) balanced with air. Samples were incubated at 21 oC on a rotary shaker (120 r.p.m) for 22 days in a dark room. The headspace methane was measured in 2-3 days intervals with GC/FID (due to cell aggregation methane oxidation activity was monitored instead of optical density).

Mentioned method was repeated with 11 different concentrations of 0.05, 0.2, 0.5,1, 5, 10, 20,

30, 40, 50, and 100 mmol of iron (II) sulfate heptahydrate (FeSO4 . 7H2O, 99 + % A.C.S. reagent). Samples were incubated under the atmosphere of 14.9 – 15.7% CH4 (v/v) and 5.3 -

o 6.9% CO2 (v/v) balanced with air on rotary shaker (120 r.p.m) for 22 days at 21 C with no light source. Due to cell aggregation methane oxidation via GC/FID was used instead of optical density measurement.

6 concentrations of 0, 100, 200, 400, 600, and 800 mM of sodium chloride (NaCl) in 50 ml of

M10 XCF (pH 8.4) were prepared in order to check the NaCl endurance of the strain XLMV4T cells. The liquid medium M10 XCF (pH 8.4) used in the salt experiment contains 9.36 mM of

NH4Cl and 0.068 mM of CaCl2. 2 H2O in addition to the added NaCl concentrations mentioned above and the liquid cultures were not amended or diluted for this test due to high dependancy of

109 the cells to these basic salts for growth (their elimination will result in no growth). The reason for selecting such high concentrations of NaCl is because of the high salt durability of the reference strain Methylobacter marinus, with optimum NaCl concentration of 100 mM [139].

Prerapred samples in 200 ml glass bottles were filled with 22.3% CH4 (v/v) and 5.6% CO2 (v/v) balanced with air. Samples were incubated on a rotary shaker (120 r.p.m) for 19 d. The optical density was measured at 600 nm wave-length at 1 d intervals.

4.7 Genome Sequencing of Strain XLMV4T

5.17 g of genomic DNA from the target strain XLMV4 T was prepared (based on the extraction method described at section 3.2.3) and was sent for HiSeq2000 Illumina sequencing in order to obtain a full genomic profile of the target methanotroph. The draft genome was assembled by

Xiaoli Dong at the University of Calagry Visual Genomics Center

(http://www.visualgenomics.ca/~xdong/projects.html) and annotation was performed by submission to the IMG platform of the Joint Genome Institute (JGI) (http://www.jgi.doe.gov/) website. The IMG/M is a recently developed (2007) integrated genome data management and comparative analysis system under the auspices of the Joint Genome Institute (JGI)

(http://www.jgi.doe.gov/) with high capability in targeting and predicting metabolic pathways, protein coding sequences as well as RNA-coding genes within the selected microorganisms from all domains of life (Eukarya, Bacteria and Archaea) [155].

The presence of all key type I methanotroph metabolic pathway was verified using the gene search option of the JGI/IMG/ER website or by blasting reference protein sequences obtained from the Entrez database (part of NCBI) (http://www.ncbi.nlm.nih.gov/protein/) against the

110 genome of XLMV4 T. Function pathways were studied using the KEGG pathway database

(http://www.genome.jp/kegg/pathway.html) by using enzyme EC numbers from Brenda Enzyme database (http://www.brenda-enzymes.org/). Methylosinus trichosporium OB3b was used as reference for searching important functional genes in methanotrophy and the Type I methanotrophic pathway of RuMP were investigated by using KEGG pathway and Entrez databases [47] [Appendix 16].

4.8 Results and Discussion

4.8.1 Isolation and Growth Curve

Obtained chromatograms of the 16S rRNA sequences of strain XLMV4 T generated via Sanger and Illumina sequencing profile of the strain did not reveal any traces of external DNA or background noises in the chromatogram.

A growth curve was obtained from strain XLMV4 T at 21oC by measuring optical density at 600 nm during 1-2 day intervals [Figure 4-1].

Based on the growth curve in the first 200 h, the doubling time (generation time) is 25 h

[Appendix 17], which is longer than the reference methanotroph, Methylobacter marinus with 3-

4 h [139]. There is a possibility that the laboratory conditions provided for the target strain, and the culture medium (due to turbidity or the absence of important chemical compounds) were not optimal [156]. Aggregation of the cell after three to four days of incubation might also play a role in our calculations for the generation time of the target strain.

111

Figure 4-1. Growth curve obtained from strain XLMV4 T at 21oC by measuring optical density at

600 nm during 1-2 day intervals. Error bars in the graph represent standard error of the mean for duplicate samples.

112 4.8.2 Phylogenetic Analysis of the Strain XLMV4T

Based on the constructed tree [Figure 4-2], the phylogenetic position of strain XLMV4 T was close to Methylobacter marinus with 96.5% gene sequence identity [139]. Strain XLMV4 T was also uploaded into the Ez Taxon-e database for comprehensive 16S rRNA analysis. 96.5% identity was shown by Ez Taxon-e to Methylobacter marinus strain A45T and 95.3-95.4% identity to Methylobacter luteus starin NCIMB 11914T and Methylobacter tundripaludum starin

SV96T respectively [139, 140].

ARB software is also capable of calculating similarity value between the selected sequence and references. The similarity value of strain XLMV4 T to Methylobacter marinus (starin NCIMB

11914T) matched exactly to similarity value shown by Ez Taxon-e (96.54% identity).

The pmoA gene of the strain XLMV4 T was also obtained from the genome to construct a tree based on pmoA/amoA genes using the NJ algorithm [Figure 4-3]. ARB positioned stain XLMV4 T close to Methylosoma difficile, which is the only isolated species from this genus.

The complete 16S rRNA gene of strain XLMV4 T is available at Genbank under the accession number of KC963966. Strain XLMV4 Thas been submitted to two international culture collections: DSMZ (https://www.dsmz.de/) and Korean Agricultural Culture Collection (KACC)

(http://www.genebank.go.kr/eng/microbe/gene_info.jsp). No accession number has been generated and deposit verifications are still in progress.

113

Figure 4-2. 16S rRNA based NJ phylogenetic tree of the target strain XLMV4 T compared to reference methanotrophs. Methylobacter XLMV4 T groups most closely with Methylobacter marinus. The scale bar represents 0.1change per nucleotide position. The tree was constructed with bootstrap values as measure of support (1000 constructions).

114

Figure 4-3. A pmoA/amoA gene based phylogenetic tree constructed using the NJ algorithm.

Strain XLMVT (in figure shown as Methylobacter XLMV4) grouped with the recently characterized Methylosoma difficile, but also closely with other known Methylobacter strains. .

Tree dose not contain Methylobacter marinus and Methylobacter tundripaludum, due to this reason that some pmoA gene sequences from Methylobacter related strains are not available for public use. The tree was built with 1000 bootstraps as measure of support and the scale bar represents 0.1change per nucleotide position.

115 The mean G+C ratio is 44.76 mol %, which was calculated by an online GC calculator, TUBIC

(http://tubic.tju.edu.cn/GC-Profile/) (data were obtained from the genomic analysis of the target strain) [152, 153].

The fatty acid profile of the strain XLMV4 T is still being analysed.

4.8.3 Morphological Characterization of Strain XLMV4T

The colony morphology of strain XLMV4 T on culture medium M10 XCF pH 8.4 at 21 oC after four days of incubation was as follows: colonies are less than 1 mm in size, round, opaque, low convex, of butyrous consistency with entire edges, rough and dull. Fresh colonies have beige/buff pigments and one-month-old colonies demonstrate weak diffusible yellow pigmentation. Cells are not evenly dispersed (they are aggregated) in liquid culture without any surface pellicle and are viable for about one month. Strain XLMV4 T did not require salt but its original habitat is somewhat saline (refer to table 3.1 in section 3.2.1- total major ions for WIP is 2770 mg/L, MLSB is 2290 mg/L and total solids content for WIP is 0.27% and for MLSB is 0.23%).

Cells were positive for both catalase and cytochrome c oxidase but showed poor to no lysis in 3%

(w/v) KOH [157, 158]. Cells were not stable in 0.01%, 0.1%, 1% and 10% sodium dodecyl sulfate

(SDS, NaC12H25SO4). The lysis phenomenon was observed with both direct microscopic observations and based on optical density measurement of 600 nm measured via Ultraspec 10 cell density meter (Armsham Biosciences). The reference strain Methylobacter marinus (A45T) demonstrates cell wall durability in the presence of 10% SDS (not 0.01%, 0.1% and 1%) and 3%

KOH [139].

116 Cells were Gram negative and had the shape of very short rods or cocci, 0.98 – 1.33 m in length, often occurring in straight chains or aggregates [Figure 4-4].

Granular particles are visible in the cells. It was originally thought they might be polyhydroxybutyrate inclusions (PHB), but the later histological analysis of the cells stained with

Nile Blue under fluorescence microscopy with DAPI filter (100 objective) failed to detect shiny yellow granules as a positive indicator of PHB [159] [Figure 4-5]. The genome profile of strain

XLMV4 T did not contain the phaC gene responsible for the expression of Poly-beta- hydroxybutyrate polymerase [Appendix 16]. This observation correlates with the findings of

Criddle’s lab (2013), which highlights the absence of phaC gene in Type I methanotrophs [160].

Based on hanging drop method cells were non-motile and Duguid Negative Staining with the aid of black India ink elucidated the presence of a capsule as halo rings around the cells [154]

[Figure 4-6]. Cells were not subjected to further investigations regarding the absence or presence of flagella.

Absence of exospores was ascertained by heating the XLMV4 T cells at 80 oC for 20 min using a

Themomixer (Eppendorf) and transferring the culture to freshly made M10 XCF culture plates

[139]. Two-month-old plates were also used for exospore screening test with 0.5% Malachite Green dye [Figure 4-7] [154]. The result did not demonstrate any exospore formation compared to the positive control (Bacillus subtilis).

117

Figure 4-4. Methylobacter XLMV4 T cells stained with crystal violet and counterstained with safranin. Under the bright field microscopic view cells are Gram negative in the shape of short rods. Cells contained dark granules. These are not polyhydroxybutyrate granules based on negative Nile Blue staining.

118

Figure 4-5. 1% Nile Blue staining of the heat-fixed cells did not demonstrate yellow glowing fluorescence under the 460 nm excitation wavelength.

119

Figure 4-6. XLMV4 T cells stained with waterproof black India ink (Pigment-based drawing ink).

The glowing halos surrounding the cells are positive indication for the presence of capsule.

120

Figure 4-7. XLMV4 T cells negative for exospore formation after staining with 0.5% Malachite

Green dye. The positive control, Bacillus subtilis demonstrated green particles stained with 0.5%

Malachite Green.

121 4.8.4 TEM Images of the Strain XLMV4 T

TEM Images of the strain XLMV4 T were obtained from University of Calgary Microscopy and

Imaging Facility (MIF) [Figure 4-8][Figure 4-9].

4.8.5 Carbon and Nitrogen Sources

Methylobacter XLMV4T strain did not show any growth in the presence of the following energy sources: sodium acetate anhydrous, sodium pyruvate, sodium succinate dibasic hexahydrate, sodium formate, sodium citrate tribasic dehydrate. In addition Methylobacter XLMV4T strain did not show any growth in the presence of the following nutritionally rich media such as; Luria-

Bertani Broth (LB), Nutrient Agar (NA), Reasoner’s 2A agar (R2A), mineral salts Medium 10 supplemented with various energy substrates [Appendix 5], as well as 50-well commercially available API plates with common bacterial carbohydrate source [Appendix 12] [Appendix 13]

[Appendix 14] [Appendix 15]. It seems that strain XLMV4 T is an obligate methanotroph, which only consumes methane as the primary energy source as well as methanol.

Two reference methanotrophs, Methylobacter luteus (ATCC 49878T) and Methylobacter marinus

(A45T) were strongly positive for methanol consumption as sole carbon source [139]. It seems that our target strain is very similar to reference methanotroph Methylobacter tundripaludum (SV96T) from the carbon utilization perspective due to weak to no growth in the presence of exogenous methanol as the energy source [140]. Most of the validly described methanotrophs are strongly positive for growth on methanol [139].

122

Figure 4-8. TEM image of XLMV4 T cell. The image clearly demonstrates the intracytoplasmic membrane at the left side of the cell with a group of uncharacterized white electron-diffuse inclusions. These granules are also present in the reference methanotrophs identified as the closest relatives to the XLMV4 T species. Image has been taken under a direct magnification of

30000 (HV 80.0 kv).

123

Figure 4-9. TEM image of XLMV4 T cell demonstrates the extensive intracytoplasmic membrane almost covering 2/3 of the cell. Image has been taken under a direct magnification of 20000

(HV 80.0 kv).

124 XLMV4 T cells demonstrated very weak to no growth in the presence of nine primary nitrogen sources used in this experiment with the exception of 10 mM ammonium chloride (NH4Cl). The nitrogen sources used were sodium nitrate, sodium nitrite, L-valine, urea, glycine, L-alanine, L- proline, L-serine, L-aspartate and nitrogen gas (12%).

Reference methanotrophs, Methylobacter marinus (A45T) and Methylobacter luteus (ATCC

49878T) are positive for ammonium sulfate and nitrate as sole nitrogen sources but negative for the following nitrogen compounds; L-valine, L-serine and glycine [139]. No information has been provided regarding Methylobacter tundripaludum (SV96T) sole nitrogen sources, except that it contains the nifH gnene, which allows fixation of nitrogen at atmospheric level (non of the other nif genes were mentioned) [140].

4.8.6 Strain XLMV4T pH, Temperature, Iron, Copper and NaCl Response

Strain XLMV4 T is active from pH 6.5-8.5 with no methane consumption at pH 6 and 9. The optimum pH is 8 and the best activity is within the range of 7-8.5 [Figure 4-10].

Strain XLMV4 T is capable to grow and remain active from 20-30 oC, but no growth were observed at 4, 10 ,15 ,37, 40 and 45 oC. The optimum temperature is 25 oC.

Strain XLMV4T cells did not show any methane oxidation activity in 100, 50, 40, 30, 20 and 10 mmol concentrations of CuSO4 . 5H2O, but methane consumption was evident in 0, 0.05, 0.2, 0.5 and 1 mmol concentrations. In general Strain XLMV4T is active and remains viable from 0.01 – 1 mmol with weak methane oxidation activity in 1 mmol. The optimum copper concentration is

125 0.05 mmol [Figure 4-11]. There are no reports regarding the optimum copper concentrations of the reference strains.

Methylobacter oleiharenae demonstrated methane oxidation activity only in 1mmol of FeSO4 and no activity in 0.05, 0.2, 0.5, 5, 10, 20, 30, 40, 50, and 100 mmol FeSO4 [Figure 4-12].

Reference starins were not tested for iron response.

XLMV4T cells demonstrated growth in 0 to 200 mM of NaCl and did not show any growth activity in the presence of 300 to 800 mM of NaCl.

4.8.7 Genome of Methylobacter oleiharenae XLMV4 T

A draft genome of strain XLMV4 T was obtained after illumina sequencing [161][Table 4-3].

Assembled contigs (322 contigs) were submitted to into JGI_IMG/M database for annotation.

Dr.Ivica Tamas analyzed the genome of strain XLMV4T.

By comparison with three reference methanotrophs (Methylobacter tundripaludum,

Methylobacter luteus, Methylobacter Marinus) strain XLMV4 T contains 729 specific genes specific for our target Methylobacter (data are not shown).

All the genes necessary for pMMO enzyme (pmoCAB) are available in gene inventory of the strain XLMV4 T but the genes (mmoX, mmoY, mmoZ) necessary for encoding sMMO are absent.

Genes for methanol dehydrogenase are also present. Also the key gene for initiating the H4MPT

126 pathway, fae encoding the formaldehyde activating enzyme (permits the formation of methylene-

[49][51] H4MPT) and key genes for formate oxidation have been detected . Genes (fhcC, fhcA ,fhcD) necessary for encoding formyltransferase/hydrolase complex are missing from the gene inventory, so it is not clear how this methanotroph completes formaldehyde oxidation via the

H4MPT pathway.

All the genes for the RuMP cycle are present but the genes for phosphoenolpyruvate carboxylase and hydroxypyruvate reductase (HPR) are missing, indicating that there is no serine cycle. Most of the key genes for PHB synthesis are absent. All the genes except ofr (encodes for 2-Oxoacid ferredoxin oxidoreductase) of the Tricarboxylic Acid Cycle (TCA) cycle have been detected.

Genes encoding 2-oxoglutarate dehydrogenase are present, but in general the TCA cycle is incomplete, which has been demonstrated in majority of type I methanotrophs [47][93].

127

Figure 4-10. Methylobacter XLMV4 T pH response. Strain XLMV4 T is active from pH 6.5 to pH

8.5 with no activity at pH 6 and 9. In the graph pH 9 overlaps with pH 6.

128

129 Figure 4-11. Decline of methane percentage in the headspace of samples prepared with different concentrations of CuSO4 .5H2O (cupric sulfate heptahydrate). Graph for 100, 50, 40, 30, 20 and

10 mmol of FeSO4 are not shown. The methane oxidation activity in 0 mmol sample might be because of the presence of trace amount of Cu in the glass bottle (transferred from the original plates or left in the bottle from the previous experiments. Non of the isolated methanotrophs are able to grow with no Cu in their environment. The optimum copper concentration is 0.05 mmol.

Strain XLMV4T cells did not demonstrate methane oxidation activity in 100, 50, 40, 30, 20 and

10 mmol concentrations of CuSO4 . 5H2O.

130

Figure 4-12. Decline of methane percentage in the headspace of samples prepared with different concentrations of FeSO4 .7H2O (iron (II) sulfate heptahydrate). Graph for 100, 50, 40, 30, 20 and

10 mmol of FeSO4 are not shown. The methane oxidation activity occurred only in the presence of 1 mmol of FeSO4 .7H2O.

131 All genes necessary for gluconeogenesis are avaibale in the genome of the Methylobacter oleiharenae.

Nitrate transport component genes such as nrtA are present but genes encoding of the large and small subunits of nitrite reductase are missing (nasD and nasA). Nitric oxide reductase genes

(norC and norB) have been detected. The haoAB genes responsible for encoding hydroxylamine oxidoreductase are present in strain XLMV4T, which might be part of the key survival factors of the target Methylobacter in ammonium-rich tailing waters. Total of 17 nitrogen fixing proteins

(out of 20 known nif genes) including nifH have been detected (nifZ, nifU, nifS, nifQ, nifB, nifD, nifK, nifL, nifV, nifE, nifN, nifX, nifW, nifM, nifF, and nifJ), but the nitrogen sensitive nif regulatory, nifA gene is missing (NifA protein is the product) [199]. It seems that presence of high oxygen in the experimental vials prevented the nitrogen fixation activity of Methylobacter oleiharenae, which might be the reason for the negative results for nitrogen sources mentioned above.

132 Table 4-3. Summary genome statistics of strain XLMV4T available on the JGI/IMG web page.

DNA, total number of bases 5722743 (100%)

DNA coding number of bases 4906683 (85.74%)

DNA G+C number of bases 2670858 (46.67%)

DNA scaffolds 322 (100%)

CRISPR Count 6

Genes total number 5456 (100%)

Protein coding genes 5394 (98.86%)

RNA genes 62 (1.14%)

rRNA genes 5 (0.09%)

5S rRNA 3 (0.05%)

16S rRNA 1 (0.02%)

23S rRNA 1 (0.02%)

tRNA genes 39 (0.71%)

Other RNA genes 18 (0.33%)

Protein coding genes with function prediction 3772 (69.13%)

Without function prediction 1622 (29.73%)

Number of chromosomal cassettes 797

COG clusters 1859 (0%)

KOG clusters 717 (0%)

Pfam clusters 2326 (0.01%)

TIGRfam clusters 1207 (0.01%)

133 4.9 Description of Methylobacter oleiharenae sp. nov.

Methylobacter oleiharenae (o. le. i. ha. Re ` nae . L. n. oleum oil; L. n. harena, sand; N. L. gen. n. oleiharenae, of (from) oil sand) starin XLMV4T was isolated from Syncrude’s West In pit

Settling Basin (Latitude: 57°0033.14’N and Longitude: 111°3725.26’W) from top 0-10 cm and

10-15 m from the shore.

Cells are Gram-negative, very short rods or cocci-shaped cells and are 0.98 – 1.33 m in length, in the form of straight chains or aggregates. Cells are non-motile with a capsule and no exospore.

Flagella machinery of the cell is not complete and only flagG gene was detected. Non of the reported reference starins contain flagella. Colonies are less than 1 mm in size, round, opaque, low convex, of butyrous consistency with entire edges, rough and dull. Fresh colonies have beige/buff pigments and one-month-old colonies demonstrate weak diffusible yellow pigmentation. Cells are aggregated in liquid culture with no surface pellicle and do not require

NaCl for growth. Target cells are lysed by 0.01%, 0.1%, 1% and 10% SDS. They are obligate methane oxidizers, but weak growth was observed in the presence of 10 mM methanol and no growth in 100 mM and 1 M methanol as the sole substrate. Also weak growth was observed in the presence of 10 mM ammonium chloride as sole nitrogen source. XLMV4T cells are both catalase and oxidase positive. Active from pH 6.5-8.5 with no methane consumption at pH 6 and

9. The optimum pH point is pH 8 and the best activity is within the range of 7-8.5. Strain

XLMV4 T grows from 20-30 oC with no methane consumption activity at 4, 10, 15, 37, 40 and 45 oC. The optimum temperature point is 25 oC. Cells possess the specific gammaproteobacterial

(type I) methanotrophs internal membranes. Key genes necessary for pMMO enzyme (pmoCAB) and methanol dehydrogenase (mxaF and mxaI) are present. Genes (mmoX, mmoY, mmoZ)

134 encoding sMMO were not detected. It is not clear how this methanotroph completes formaldehyde oxidation via the H4MPT pathway, due to absence of key genes (fhcC, fhcA, fhcD) necessary for encoding the formyltransferase/hydrolase complex of the pathway. All the genes for the RuMP cycle are present but the genes for phosphoenolpyruvate carboxylase and hydroxypyruvate reductase (HPR) of the serine cycle were not detected. nifH gene including 16 other nif genes responsible in codining proteins involved in nitrogen fixation were detected but regulatory gene nifA was absent.The DNA G+C content is 44.76 mol %. Based on BLAST results from Ez Taxon-e, NCBI and a 16S rRNA gene-based phylogenetic tree (ARB software)

Methylobacter oleiharenae strain XLMV4T is 96.5% identical to Methylobacter marinus strain

A45T, 95.3% to Methylobacter luteus starin NCIMB 11914T, and 95.4% to Methylobacter tundripaludum starin SV96T.

135 Chapter Five: Conclusions

Based on the current study, methanotrophic bacteria are present in the surface layers of tailing waters and are actively consuming an estimated 10-20% of the methane gas produced from the methanogenic microbial communities in deeper layers of the ponds. The actual methane oxidation capacity of the indigenous methanotrophs could be lower than the “potential” values estimated in this study. O2 could be the main limiting factor since our in vitro incubations had more oxygen compared to in situ methanotrophs.

The unique chemistry and limited oxygen of these engineered ponds are probably selecting for a few methanotrophic bacteria mainly related to the Methylococcaceae family of

Gammaproteobacteria, particularly a genus related to Methylocaldum/Methylococcus. It seems that the minor pH, temperature and nitrogen variations over the year are not dramatically affecting the methanotrophic communities and the predominant methanotroph was always present in all sites and sampling times in this study.

Performing 13C DNA-SIP at different temperatures might highlight the role of temperature on the methanotrophic species that are active. Cultivation approaches failed to isolate this

Methylocaldum-like methanotroph, but the 13C DNA-SIP heavy fraction proved the high activity of this microbe compared to other methane oxidizing bacteria. The reasons behind the survival of this target methanotroph are still unknown and require more intense study. Its isolation would allow for a clearer understanding of methane oxidation capacity in these engineered ponds as the

136 most active methanotroph, which could result in developing effective strategies for expanding the frame of methanotrophy and using it for reducing anthropogenic methane emissions.

Tailing waters of Alberta oil sand industries are unique and harsh environments with an active carbon cycle and large pollutant loads. Active methanotrophs must be able to survive high pH, salinity, iron, copper and ammonia concentrations.

The following study allowed the isolation of a novel strain Methylobacter oleiharenae

(XLMV4T), which will be published in the near future. In-depth study on the genome of this isolated strain or possibly the future isolates from tailing waters, might pave the path for a better understanding of methane oxidizing bacteria’s survival factors or growth capability in toxic waters.

This study provided a first glimpse of indigenous methanotrophs and their potential methane oxidation activity in oil sand wastewaters from the largest man-made tailings pond in North

America. Expanding our understanding regarding the inhibitory factors mentioned (such as weak oxygen cycle, high ammonium concentrations, high water turbidity and hot water discharge from the pump into the pond) in this study may provide an opportunity for limiting these factors in order to allow methanotrophs to reach their full methane oxidizing capacity. Further studies testing these limiting factors, on methanotrophs, temperature-vaiable DNA-SIP, altering copper and mineral concentrations of M10 XCF medium, testing the potential methane oxidizing capacity under limited oxygen levels and methane gas (<2%), 13C-DNA SIP with different concentrations of methane to test methanotrophic population consistency under methane

137 fluctuations, metagenome analysis of the surface waters, genome analysis of the dominant methanotroph are required to complete this study.

138 References

[1]: Mackenzie A. (1970). The journal and letters of Alexander Mackenzie. Lamb W. Kaye ed. Hakluyt Society.

[2]: Parlee B. (2011). Traditional knowledge overview for the Athabasca river watershed. University of Alberta.

[3]: Ordorica GG, Croiset E, Douglas P, Elkamel A, Gupta M. (2007). Modeling the Energy Demands and Greenhouse Gas Emissions of the Canadian Oil Sands Industry. Energy & Fuels. 21: 2098-211.

[4]: Brandt A R. (2012). Variability and uncertainty in life cycle assessment models for greenhouse gas emissions from 139ydroxyl oil sands production. Environmental Science & Technology 46, 1253-1261.

[5]: http://www.infomine.com/minesite/minesite.asp?site=syncrude

[6]: http://oilsands.alberta.ca/reclamation.html#JM-OilSandsArea

[7]: http://oilsands.infomine.com/countries/

[8]: Attanasi E D, Meyer R F. (2010). Natural bitumen and extra-heavy oil (PDF). Survey of energy resources (22 ed.).World Energy Council.

[9]: Dusseault M. B. (2001). Comparing Venezuelan and Canadian heavy oil and tar sands. Proceedings of Petroleum Society’s Canadian International Conference.

[10]: http://www.capp.ca

[11]: Penner TJ, Foght JM. (2010). Mature fine tailings from oil sands processing 139ydrox diverse methanogenic communities. Canadian Journal of Microbiology, 56:459-470

[12]: Mehrabad A, He Z, Tamas I, Sharp CE, Brady AL, Rochman FF, Bodrossy L, Abell G CJ, Penner T, Dong X, Sensen CW, Dunfield PF. (2012). Methanotrophic bacteria in oilsands tailings ponds of northern Alberta. International Society of Microbial Ecology. 7:908-92.

[13]: Chalaturnyk RJ, Don S J, Özüm B. (2002). Management of oil sands tailings. Petroleum Science and Technology. 20:1025-1046.

[14]: Timoney KP, Ronconi RA. (2010). Annual bird mortality in the bitumen tailings ponds in northeastern Alberta, Canada. The Wilson journal of ornithology. 122:569-576

[15]: Catalytic hydrotreating in petroleum refining (2011). Retrieved from http://www.eoearth.org/article/150953

139 [16]: Ancheyta J, Rana MS, Furimsky E. (2005). Hydroprocessing of heavy petroleum feeds: Tutorial. Catalysis Today, 109:3-15.

[17]: http://www.uofaweb.ualberta.ca/ccg/pdfs/Vol3- IntroSAGD.pdf?bcsi_scan_27D7EF85B9B9160A=4US+7bKiNWIHrV1tXmS1+QUAAAC7PFg d&bcsi_scan_filename=Vol3-IntroSAGD.pdf

[18]:http://www.total.com/MEDIAS/MEDIAS_INFOS/5777/FR/TOTAL_EP_CANADA_COM MITTED_TO_CSR.pdf.

[19]: Berkowitz N, Speight JG. (1975). The oil sands of Alberta. Fuel, 54:138-149.

[20]: http://www.canadianpetroleumhalloffame.ca/karl-clark.html

[21]: Energy resources conservation board (2012). ST98-2011:Alberta’s Energy Reserves 2011 and Supply/Demand Outlook 2012-2021. http://www.ercb.ca/RSS/yp-starter/401.aspx

[22]: Siddique T, Gupta R, Fedorak PM, MacKinnon MD, Foght JM. (2008). A first approximation kinetic model to predict methane generation from an oil sands tailings settling basin. Chemosphere 72, 1573-1580.

[23]: Mikula RJ, Munoz VA, Omotoso O. (2009). Centrifugation options for production of dry stackable tailings in surface mined oil sands tailings management. Journal of Canadian Petroleum Technology. 48: 19-23.

[24]: Lai JWS, Pinto LJ, Bendell-Young LI, Moore MM, Kiehlmann E. (1996). Factors that affect the degradation of naphthenic acids in oil sands wastewater by indigenous microbial communities. Environmental Toxicology and Chemistry, 15:1482-1491.

[25]: Siddique T, Penner T, Klassen J, Nesb C, Foght, J M. (2012). Microbial Communities Involved in Methane Production from Hydrocarbons in Oil Sands Tailings. Environmental Science & Technology 46, 9802-9810.

[26]: Boucher O, Friedlingstein P, Collins B, Shine KP. (2009). The indirect global warming potential and global temperature change potential due to methane oxidation. Environmental Research Letters. 4:044007.

[27]: Radajewski S, Ineson P, Parekh NR, Murrell JC. (2000). Stable-isotope probing as a tool in microbial ecology. Nature. 403:646–649.

[28]: Holowenko FM, MacKinnon MD, Fedorak PM. (2000). Methanogens and sulfate-reducing bacteria in oil sands fine tailings waste. Canadian Journal of Microbiology, 46:927-37.

[29]: Clearstone Engineering Ltd. (2007). Measurement of emissions from the tailings ponds at the mildred lake oil sands facility. Prepared for Syncrude Canada Ltd.

140 [30]: Watson RT, Meira Filho LG, Sanhueza E, Janetos A. (1992). Greenhouse gases: sources and sinks. In: Houghton JT. Callander BA, Varney SK (eds) Climate change 1992: the supplementary report to the IPCC scientific asse.

[31]: Dlugokencky E J, Nisbet EG, Fisher R, Lowry D. (2011). Global atmospheric methane: budget, changes and dangers. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences. 369:2058-2072.

[32]: Stein LY, Koltz MG. (2011). Nitrifying and denitrifying pathways of methanotrophic bacteria. Biochemical Society Transactions. 39:1826-31.

[33]: Lelieveld J, Crutzen PJ, Bruhl C.(1993). Climate effects of atmospheric methane. Chemosphere. 26:739-768.

[34]: McInerney MJ, Sieber JR, Gunsalus RP. (2009). Syntrophy in anaerobic global carbon cycles. Current opinion in biotechnology. 20.6: 623-632.

[35]: Dolfing J, Larter SR, Head IM. (2007). Thermodynamic constraints on methanogenic crude oil biodegradation. International Society of Microbial Ecology. 2:442-452.

[36]: http://www.northerngateway.ca/assets/pdf/General%20Project%20- %20Regulatory/NGP-FS-01-004_Diluent.pdf

[37]: McGenity TJ, Folwell BD, Mckew BA, Sanni GO. (2012). Marine crude-oil biodegradation: a central role for interspecies interactions. Aquatic Biosystems. 8:10

[38]: Grabarse W, Shima S, Mahlert F, Duin EC, Thauer RK, Ermler U. (2011). Methyl-coenzyme m reductase. In: Encyclopedia of Inorganic and Bioinorganic Chemistry. John Wiley & Sons, Ltd.

[39]: Op den Camp HJM, Islam T, Stott MB, Harhangi HR, Hynes A, Schouten S, Jetten MSM, Birkeland NK, Pol A, Dunfield PF. (2009). Environmental, genomic and taxonomic perspectives on methanotrophic Verrucomicrobia. Environmental Microbiology Reports. 1: 293-306.

[40]: Ho A, Luke C, Frenzel P. (2011). Recovery of methanotrophs from disturbance: population dynamics, evenness and functioning. International Society of Microbial Ecology. 5:750-758.

[41]: Bowman JP. (2011). Approaches for the Characterization and Description of Novel Methanotrophic Bacteria, Methods in Enzymology, Academic Press, AC Rosenzweig, SW Ragsdale (ed), New York.

[42]: Eshinimaev BT, Medvedkova KA, Khmelenina VN, Suzina NE, Osipov GA, Lysenko AM, Trotsenko YA. (2004). New thermophilic methanotrophs of the genus Methylocaldum. Microbiology. 73:448-456.

141 [43]: Dunfield PF, Yuryev A, Senin P, Smirnova AV, Stott MB, Hou S, Ly B, Saw JH, Zhou Z, Ren Y, Wang J, Mountain BW, Crowe MA, Weatherby TM, Bodelier PLE, Liesack W, Feng L, Wang L, Alam M. (2007). Methane oxidation by an extremely acidophilic bacterium of the phylum Verrucomicrobia. Nature. 6: 879-882.

[44]: Ettwig KF, Shima S, Pas-Schoonen KT, Kahnt J, Medema MH, Camp HJM, Jetten MSM, Strous M. (2008). Denitrifying bacteria anaerobically oxidize methane in the absence of archaea. Environmental Microbiology. 10: 3164-3173.

[45]: Hanson RS, Hanson TE. (1996). Methanotrophic bacteria. Microbial Review. 60:439-71.

[46]: McDonald IR, Kenna EM, Murrell JC .(1995). Detection of methanotrophic bacteria in environmental samples with the PCR. Applied and Environmental Microbiology. 61:116–121.

[47]: Matsen JB, Yang S, Stein LY, Beck DAC, Kalyuzhanaya MG. (2013). Global molecular analyses of methane metabolism in methanotrophic alphaproteobacterium, Methylosinus trichosporium OB3b. Part I: transcriptomic study, Volume 4. Frontiers in Microbiology. 4:40.

[48]: Crowther GJ, Kosály G, Lidstrom ME. (2008). Formate as the main branch point for methylotrophic metabolism in Methylobacterium extorquens AM1. Journal of Bacteriology .190:5057–5062.

[49]: Chistoserdova L, Vorholt JA, Thauer RK, Lidstrom ME. (1998). C1 transfer enzymes and coenzymes linking methylotrophic bacteria and methanogenic archaea. Science. 281:99–102.

[50]: Vorholt JA, Marx CJ, Lidstrom ME, Thauer RK. (2000). Novel formaldehyde-activating enzyme in Methylobacterium extorquens AM1 required for growth on methanol. Journal of Bacteriology. 182:6645–6650.

[51]: Pomper BK, Saurel O, Milon A, Vorholt JA. (2002). Generation of formate by the formyltransferase/hydrolase complex (Fhc) from Methylobacterium extorquens AM1. FEBS letters 523:133-7.

[52]: Stein LY, Roy R, Dunfield PF. (2001). Aerobic Methanotrophy and Nitrification: Processes and Connections. In eLS: John Wiley & Sons, Ltd.

[53]: Auman AJ, Speake CC, Lidstrom ME. (2001). nifH sequences and nitrogen fixation in type I and type II methanotrophs. Applied and Environmental Microbiology. 67:4009–4016.

[54]: Dedysh SN, Ricke P, Liesack W. (2004). NifH and NifD phylogenies: an evolutionary basis for understanding nitrogen fixation capabilities of methanotrophic bacteria. Microbiology .150:1301–1313.

[55]: Criddle CS, Rostkowski KH, Sundstrom ER. (2013). Process for the selection of PHB- producing methanotrophic culture. United States http://www.freepatentsonline.com/y2013/0052681.html

142 [56]: Rosenberg E, Stackebrandt E, Thompson F, DeLong EF, Lory S. (2006). The Prokaryotes- A Handbook on the Biology of Bacteria: Vol. 1: Symbiotic Associations, Biotechnology, Applied Microbiology, a comprehensive reference work from Springer.

[57]: Winder R. (2004). Methane to biomass. Chem Ind-London

[58]: OmelchenkoMB, Vasilieva LV, ZavarzinGAet al. (1996). Anovel psychrophilic methanotroph of the genus Methylobacter. Mikrobiologiya (English translation) 65: 339–343.

[59]: Semrau JD, DiSpirito AA, Yoon S. (2010). Methanotrophs and copper. FEMS Microbiology Reviews 34, 496-531.

[60]: Russell NJ, Harrisson P, Johnston IA, Jaenicke R, Zuber M, Franks F, Williams W. (1990). Cold adaptation of microorganisms. Philosophical Transactions of the Royal Society. 595-611.

[61]: Culpepper MA, Rosenzweig AC. (2012). Architecture and active site of particulate methane monooxygenase. Critical Reviews in Biochemistry and Molecular Biology. 47:483-492.

[62]: Stoecker K, Bendinger B, Schöning B, Nielsen PH, Nielsen JL, Baranyi C, Toenshoff ER, Daims H, Wagner M. (2006). Cohn’s Crenothrix is a filamentous methane oxidizer with an unusual methane monooxygenase. Proceeding of the National Academy of Science of the United State of America. 103:2363-2367.

[63]: Vigliotta, G, Nutricati E, Carata E, Tredici SM, Stefano M, Pontieri P, Massardo DR, Prati MV, Bellis L, Alifano P .(2007). Clonothrix fusca Roze 1896, a Filamentous, Sheathed, Methanotrophic  Proteobacterium. Applied and Environmental Microbiology. 73:3556-3565.

[64]: Dunfield PF. (2001). Methanotrophy in Extreme Environments. In eLS: John Wiley & Sons, Ltd.

[65]: Petersen JM, Dubilier N. (2009). Methanotrophic symbioses in marine invertebrates. Environmental Microbiology Reports.1: 319–335.

[66]: Holmes AJ, Owens NJP, Murrell JC. (1995). Detection of novel marine methanotrophs using phylogenetic and functional gene probes after methane enrichment. Microbiology. 141:1947–1955.

[67]: Belova SE, Baani M, Suzina NE, Bodelier PLE, Liesack W, Dedysh SN. (2010). Acetate utilization as a survival strategy of peat-inhabiting Methylocystis spp. Environmental Microbiology Reports. 3:36-46.

[68]: Eshinimaev BT, Khmelenina VN, Trotsenko YA.(2008). First isolation of a Type II methanotroph from a soda lake. Microbiology. 77: 628–631.

[69]: Dedysh SN, Knief C, Dunfield PF. (2005). Methylocella species are facultatively methanotrophic. Journal of Bacteriology. 187:4665-4670.

143 [70]: Dunfield PF, Khmelenina VN, Suzina NE, Trotsenko Y, Dedsyh SN. (2003). Methylocella silvestris sp. nov., a novel methanotroph isolated from an acidic forest cambisol. International Journal of Systematic Evolutionary Microbiology. 53: 1231–1239.

[71]: Theisen AR, Murrell JC .(2005). Facultative methanotrophs revisited. Journal of Bacteriology. 187: 4303–4305.

[72]: Sharp CE, Stott MB, Dunfield PF. (2012). Detection of autotrophic verrucomicrobial methanotrophs in a geothermal environment using stable isotope probing. Frontiers in Microbiology. 3:303.

[73]: Henckel T, Roslev P, Conrad R .(2000). Effects of O2 and CH4 on presence and activity of the indigenous methanotrophic community in rice field soil. Environmental Microbiology. 2:666– 679.

[74]: Valentine DL, Reeburgh WS. (2000). New perspectives on anaerobic methane oxidation. Environmental Microbiology. 2:477-484.

[75]: Hallam SJ, Putnam N, Preston CM, Detter JC, Rokhsar D, Richardson PM, DeLong EF. (2004). Reverse methanogenesis: testing the hypothesis with environmental genomics. Science. 305:1457-1462.

[76]: Shima S, Thauer RK. (2005). Methyl-coenzyme M reductase and the anaerobic oxidation of methane in methanotrophic archaea. Current Opinion Microbiology. 8:643-648.

[77]: Chistoserdova L, Vorholt JA, Lidstorm ME. (2005). A genomic view of methane oxidation by aerobic bacteria and anaerobic archaea. Genome Biology. 6:208.

[78]: Beal EJ, House CH, Orphan, VJ. (2009) Manganese- and iron-dependent marine methane oxidation. Science. 325: 184-187.

[79]: McDonald IR, Radajewski S, Murrell JC .(2005). Stable isotope probing of nucleic acids in methanotrophs and methylotrophs: A review. Organic Geochemistry. 36:779-787.

[80]: Pol A, Heijmans K, Harhangi HR, Tedesco D, Jetten MSM, Op den Camp HJM. (2007). Methylotrophy below pH 1 by a new Verrucomicrobia species. Nature. 450:874-878.

[81]: Islam T, Jensen S, Reigstad LJ, Larsen O, Birkeland NK. (2008). Methane oxidation at 55oC and pH 2 by a thermophilic bacteria belonging to the Verrucomicrobia phylum. PNAS. 105:300-304.

[82]: Wagner M, Horn M. (2006). The Planctomycetes, Verrucomicrobia, Chlamydiae and sister phyla comprise a superphylum with biotechnological and medical relevance. Current Opinion in Biotechnology. 17:241-249.

[83]: Hakemian AS, Rosenzweig AC. (2007). The biochemistry of methane oxidation. Annual Review of Biochemistry. 76:223-241.

144 [84]: Himes RA, Karlin KD. (2009). Copper-dioxygen complex mediated C-H bond oxygenation: relevance for particulate methane monooxygenase (pMMO). Current Opinion in Chemical Biology. 13:119-131.

[85]: Dunfield PF, Belova SE, Vorob’ev AV, Cornish SL, Dedysh SN. (2010). Methylocapsa aurea sp. nov., a facultative methanotroph possessing a particulate methane monooxygenase, and emended description of the genus Methylocapsa. International journal of systematic and evolutionary microbiology. 60:2659-2664.

[86]: Vorobev AV, Baani M, Doronina NV, Brady AL, Liesack W, Dunfield PF, Dedysh SN. (2011). Methyloferula 145ydroxyl gen. nov., sp. Nov., an acidophilic, obligately methanotrophic bacterium that possesses only a soluble methane monooxygenase. International Journal of Systematic and Evolutionary Microbiology. 61:2456-63.

[87]: Lontoh S, Semrau JD. (1998). Methane and trichloroethylene degradation by Methylosinus trichosporium OB3b expressing particulate methane monooxygenase. Applied Environmental Microbiology. 64:1106–1114.

[88]: Lontoh S. (2000). Substrate oxidation by methanotrophs expressing particulate methane monooxygenase (pMMO): a study of whole-cell oxidation of trichloroethylene and its potential use for environmental remediation. PhD Thesis. University of Michigan.

[89]: Choi DW, Kunz RC, Boyd ES, Semrau JD, Antholine WE, Han JI, Zahn JA, Boyd JM, de la Mora AM, DiSpirito AA. (2003). The membrane-associated methane monooxygenase (pMMO) and pMMO-NADH: quinine oxidoreductase complex from Methylococcus capsulatus Bath. Journal of Bacteriology. 185: 5755–5764.

[90]: Colby J, Stirling DI, Dalton H. (1977). The soluble methane mono-oxygenase of Methylococcus capsulatus (Bath). Biochemistry Journal. 165: 395–402.

[91]: Hou CT, Patel R, Laskin AI, Barnabe N. (1979). Microbial oxidation of gaseous hydrocarbons: epoxidation of C2 to C4 n-alkenes by methylotrophic bacteria. Applied Environmental Microbiology. 38: 127–134.

[92]: Burrows KJ, Cornish A, Scott D, Higgins IJ .(1984). Substrate specificities of the soluble and particulate methane monooxygenases of Methylosinus trichosporium OB3b. Journal of General Microbiology .130: 3327–3333.

[93]: Trotsenko YA, Murrell JC. (2008). Metabolic aspects of aerobic obligate methanotrophy. Advanced Applied Microbiology. 63:183-229.

[94]: Murrell JC, Gilbert B, McDonald IR. (2000). Molecular biology and regulation of methane monooxygenase. Archives of Microbiology. 173:325-332.

[95]: Nguyen HH, Shiemke AK, Jacobs SJ, Hales BJ, Lidstrom ME, Chan SI .(1994). The nature of the copper ions in the membranes containing the particulate methane monooxygenase from Methylococcus capsulatus (Bath). Journal of Biological Chemistry. 269: 14995–15005.

145 [96]: Zahn JA, DiSpirito AA .(1996). Membrane-associated methane monooxygenase from Methylococcus capsulatus (Bath). Journal of Bacteriology. 178: 1018–1029.

[97]: Neilands JB. (1995). Siderophores: Structure and function of microbial iron transport compounds. Journal of Biological Chemistry. 270:26723-26726.

[98]: Yoon S. (2010). Towards practical application of methanotrophic metabolism in chlorinated hydrocarbon degradation, greenhouse gas removal, and immobilization of heavy metals. Doctoral thesis.

[99]: Helland R, Fjellbirkeland A, Karlsen OA, Ve T, Lillehaug JR, Jensen HB. (2008). An oxidized Tryptophan Facilitates Copper Binding in Methylococcus capsulatus-secreted Protein MopE. Journal of Biological Chemistry. 283:13897-13904.

[100]: Wye AHK. (2010). Response and resilience of methanotrophs to disturbances. Doctoral Thesis.

[101]: Walters KJ, Gassner GT, Lippard SJ, Wagner G. (1999). Structure of the soluble methane monooxygenase regulatory protein B. PNAS. 96:7877–7882.

[102]: Hutchens E, Radajewski S, Dumont MG, McDonald, IR, Murrell JC. (2004). Analysis of methanotrophic bacteria in Movile Cave by stable-isotope probing. Environmental Microbiology. 6:111–120.

[103]: Auman AJ, Stolyar S, Costello AM, Lidstrom ME .(2000). Molecular characterization of methanotrophic isolates from freshwater lake sediment. Applied and Environmental Microbiology. 66:5259–5266.

[104]: Dumont MG, Pommerenke B, Casper P, Conrad R. (2011). DNA-, rRNA-and mRNA- based stable isotope probing of aerobic methanotrophs in lake sediment. Environmental Microbiology. 13:1153-67.

[105]: Neufeld J, Dumont M, Vohra J, Murrell J. (2007). Methodological considerations for the use of Stable Isotope Probing in microbial ecology. Microbial Ecology. 53:435-442.

[106]: Evershed RP, Crossman ZM, Bull ID, Mottram H, Dungait JAJ, Maxfield PJ, Brennand EL. (2006). 13C-labelling of lipids to investigate microbial communities in the environment. Current Opinion in Biotechnology. 17: 72–82.

[107]: Jehmlich N, Schmidt F, von Bergen M, Richnow HH, Vogt C. (2008). Protein-based stable isotope probing (Protein-SIP) reveals active species within anoxic mixed cultures. Multidisciplinary Journal of Microbial Ecology. 2: 1122–1133.

146 [108]: Huang WE, Ferguson A, Singer AC, Lawson K, Thompson IP, Kalin RM, Larkin MJ, Bailey MJ, Whiteley AS. (2009). Resolving genetic functions within microbial populations: in situ analyses using rRNA and mRNA stable isotope probing coupled with single-cell Raman- fluorescence in situ hybridization. Applied Environmental Microbiology. 75:234–241.

[109]: Morris SA, Radajewski S, Willison TW, Murrell JC. (2002). Identification of the functionally active methanotroph population in a peat soil microcosm by stable-isotope probing. Applied and Environmental Microbiology. 68:1446–1453.

[110]: Radajewski S, Webster G, Reay DS, Morris SA, Ineson P, Nedwell DB, Prosser JI, Murrell JC. (2002). Identification of active methylotroph populations in an acidic forest soil by stable-isotope probing. Microbiology. 148:2331–2342.

[111]: Lin JL, Radajewski S, Eshinimaev BT, Trotsenko YA, McDonald IR, Murrell JC. (2004). Molecular diversity of methanotrophs in Transbaikal soda lake sediments and identification of potential active populations by stable isotope probing. Environmental Microbiology. 6:1049- 1060.

[112]: Khosravi DK, Mokhtari ZB, Amai T, Tanaka K. (2013). Microbial production of poly (hydroxybutyrate) from C1 carbon sources. Applied microbiology and biotechnology 97.4: 1407- 1424.

[113]: Wendlandt KD, Jechorek M, Brühl E. (1993). The influence of pressure on the growth of methanotrophic bacteria. Acta Biotechnologica. 13:111-115.

[114]: Roose-Amsaleg CL, Garnier-Sillam E, Harry M. (2001). Extraction and purification of microbial DNA from soil and sediment samples. Applied Soil Ecology. 18:47-60.

[115]: Chakravorty S, Helb D, Burday M, Connell N, Alland D. (2007). Adetailed analysis of 16S ribosomal RNA gene segments for the diagnosis of pathogenic bacteria. Journal of Microbiological Methods. 69:330-339.

[116]: DeAngelis KM, Wu CH, Beller HR, Brodie EL, Chkraborty R, DeSantis TZ, Fortney JL, Hazen TC, Osman SR, Singer ME, Tom LM, Andersen GL. (2011). PCR amplification- independent methods for detection of microbial communities by the high-density microarray phylochip. Applied and Environmental Microbiology. 77.18:6313-6322.

[117]: Ramos PE, Bordenave S, Lin S, Bhaskar IM, Dong X, Sensen CW, Fournier J, Voordouw G, Gieg LM. (2011). Carbon and sulfur cycling by microbial communities in a gypsum-treated oil sands tailings pond. Environmental Science and Technology. 45: 439–446.

[118]: Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK, Fierer N, Pe [ntilde] a AG, Goodrich JK, Gordon JI, Huttley GA, Kelley ST, Knights D, Koenig JE, Ley RE, Lozupone CA, McDonald D, Muegge BD, Pirrung M, Reeder J, Sevinsky JR, Turnbaugh PJ, Walters WA, Widmann J, Yatsunenko T, Zaneveld J, Knight R. (2010). QIIME allows analysis of high-throughput community sequencing data. Nature Methods. 7: 335–336.

147 [119]: DeSantis TZ, Hugenholtz P, Larsen N, Rojas M, Brodie EL, Keller K, Huber T, Dalevi D, Hu P, Anderson GL. (2006). Greengenes, a chimerachecked 16S rRNA gene database and workbench compatible with ARB. Applied Environmental Microbiology. 72:5069–5072.

[120]: Altschul SF, Madden, TL, Schaeffer AA, Zhang J, Zhang Z, Miller W, Lipman DJ. (1997). Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Research .25:3389-3402.

[121]: Holder M, Paul OL. (2003). Phylogeny estimation: traditional and Bayesian approaches. Nature reviews genetics. 4.4: 275-284.

[122]: Saitou N, Nei M. (1987). The neighbor-joining method: a new method for reconstructing phylogenetic trees. Molecular Biology and Evolution. 4:406-425.

[123]: Ludwig W, Strunk O, Westram R, Richter L, Yadhukumar HM, Buchner A, Lai T, Steppi S, Jobb G, Förster W, Brettske I, Gerber S, Ginhart AW, Gross O, Grumann S, Hermann S, Jost R, König A, Liss T, Lüßmann R, May M, Nonhoff B, Reichel B, Strehlow R, Stamatakis A, Stuckmann N, Vilbig A, Lenke M, Ludwig T, Bode A, Schleifer KH. (2004). ARB: a software environment for sequence data. Nucleic Acid Research. 4:1363-1371.

[124]: Quince C, Lanzen A, Davenport RJ, Turnbaugh PJ. (2011). Removing noise from pyrosequenced amplicons. BMC bioinformatics. 12.1:38.

[125]: Jukes TH, Cantor CR. (1969). Evolution of protein molecules. In M. N. Munro, editor, Mammalian protein metabolism, volume III. Academic Press, N. Y.

[125]:http://gqinnovationcenter.com/services/sequencing/technoMPSIlluminaHiSeq.aspx?l=e

[126]: http://res.illumina.com/documents/systems/hiseq/datasheet_hiseq_systems.pdf

[127]: Shendure J, Hanlee J. (2008). Next-generation DNA sequencing. Nature Biotechnology. 26:1135-1145.

[128]: França LTC, Carrilho E, Kist TBL. (2002). A review of DNA sequencing techniques. Quarterly Reviews of Biophysics. 35:169-200.

[129]: Kim J, Alkawally M, Brady A, Rijpstra WIC, Damste JSS, Dunfield PF. (2013). Chryseolinea serpens gen. nov., sp. nov., a member of the phylum Bacteroidetes isolated from soil. International Journal of Systematic and Evolutionary Microbiology. 63:654-660.

[130]: http://lyle.smu.edu/~mhd/8330f11/NextGenerationSequencing.pptx

[131]: Kim OS, Cho YJ, Lee K, Yoon SH, Kim M, Na H, Park SC, Jeon YS, Lee JH, Yi H, Won S, Chun J. (2012). Introducing EzTaxon-e: a prokaryotic 16S rRNA Gene sequence database with phylotypes that represent uncultured species. International Journal of Systematic and Evolutionary Microbiology. 62:716–721.

148 [132]: Lane DJ. (1991). 16S/23S rRNA sequencing. In nucleic acid techniques in bacterial systematics, Edited by E. Stackebrandt & M. Goodfellow. Chichester: Wiley (ed).

[133]: Dojka MA, Hugenholtz P, Haack SK, Pace NR. (1998). Microbial diversity in a hydrocarbon- and chlorinated-solvent-contaminated aquifer undergoing intrinsic bioremediation. Applied Environmental Microbiology. 64, 3869–3877.

[134]: Tehrani SS, Lohroff BK, Scholven J, Einspanier R. (2008). Concatameric cloning of porcine microRNA molecules after assembly PCR, Biochemical and Biophysical Research Communications, Volume 375. ISSN 0006-291X.

[135]: http://www.bioinfo.pte.hu/f2/pict_f2/pJETmap.pdf

[136]: Bodrossy L, Holmes EM, Holmes AJ, Kovacs KL, Murrel JC. (1997). Analysis of 16S rRNA and methane monooxygenase gene sequences reveals a novel group of thermotolerant and thermophilic methanotrophs, Methylocaldum gen. nov. Archives of Microbiology. 168:493-503.

[137]: Dedysh SN. (2002). Methanotrophic bacteria of acid Sphagnum bogs. Mikrobiologia. 71:741-54.

[138]: Rahalkar M, Bussmann I, Schink B. (2007). Methylosoma difficile gen. nov., sp. nov., a novel methanotroph enriched by gradient cultivation from littoral sediment of Lake Constance. International Journal of Systematic and Evolutionary Microbiology. 57:1073-1080.

[139]: Bowman JP, Sly LI, Nichols PD, Hayward AC. (1993). Revised taxonomy of the methanotrophs: description of Methylobacter gen. nov., Emendation of Methylococcus, Validation of Methylosinus and Methylocystis species, and a proposal that the family Methylococcaceae includes only the group I methanotrophs.. International Journal of Systematic Bacteriology. 43:735-753.

[140]: Wartiainen I, Hestnes AG, McDonald IR, Svenning MM. (2006). Methylobacter tundripaludum sp. nov., a methane-oxidizing bacterium from Arctic wetland soil on the Svalbard islands, Norway (78° N). International Journal of Systematic Bacteriology. 56:109-113.

[141]: Sun W, Alison MC. (2012). Diversity of five anaerobic toluene-degrading microbial communities investigated using stable isotope probing. Applied and environmental microbiology. 78.4: 972-980.

[142]: Khan ST, Horiba Y, Yamamoto M, Hiraishi A. (2002). Members of the family Comamonadaceae as Primary Poly (3-Hydroxybutyrate-co-3-Hydroxyvalerate)-degrading denitrifiers in activated sludge as revealed by a polyphasic approach. Applied Environmental Microbiology. 68:3206-3214.

[143]: Im WT, Yokota A, Kim MK, Lee ST. (2004). Kiastia adipata gen. nov., sp. nov., a novel alpha-proteobacterium. Journal General and Applied Microbiology. 50:249-54.

149 [144]: Jin L, Kim KK, Baek SH, Lee ST. (2011) . Kaistia geumhonensis sp. nov. and Kaistia dalseonensis sp. nov., two members of the class Alphaproteobacteria. International journal of systematic and evolutionary microbiology. 61.11: 2577-2581.

[145]: Sun P, Clamp J, Xu D, Kusuoka Y, Miao W, Vorticella Linnaeus. (2012). 1767 (Ciliophora, Oligohymenophora, Peritrichia) is a grade not a clade: Redefinition of Vorticella and the families Vorticellidae and Astylozoidae using molecular characters derived from the gene coding for small subunit ribosomal RNA. Protist . 163:129-142.

[146]: Börjesson G, Sundh I, Svensson B. (2004). Microbial oxidation of CH4 at different temperatures in landfill cover soils. FEMS Microbiology Ecology. 48, 305-312.

[147]: Mohanty SR, Bodelier PLE, Conrad R. (2007). Effect of temperature on composition of the methanotrophic community in rice field and forest soil. FEMS Microbiological and Ecology. 62:24–31.

[148]: Urmann K, Lazzaro A, Gandolfi I, Schroth MH, Zeyer J. (2009). Response of methanotrophic activity and community structure to temperature changes in a diffusive CH4/O2 counter gradient in an unsaturated porous medium. FEMS Microbiological and Ecology. 69:202–212.

[149]: http://www.worthington-biochem.com/introbiochem/tempeffects.html

[150]: Kalyuzhnaya MG, Khmelenina VN, Kotelnikova S, Holmquist L, Pedersen K, Trotsenko YA. (1999). Methylomonas scandinavica sp. nov., a new methanotrophic psychrotrophic bacterium isolated from deep ingneous rock ground water of Sweden. Systematic and applied Microbiology. 22:565-72.

[151]: Schmidt HA, Strimmer K, Vingron M, Haeseler AV. (2002). Tree-puzzle: maximum likelihood phylogenetic analysis using quartets and parallel computing. Bioinformatics. 18: 502- 504.

[152]: Stackebrandt E, Goebel BM. (1994). A place for DNADNA reassociation and 16S rRNA sequence analysis in the present species definition in bacteriology. International Journal of Systematic Bacteriology. 44:846–849. [153]: Whitman WB, Coleman DC, Wiebe WJ. (1998). Prokaryotes: the unseen majority. PNAS. 95:6578-6583.

[154]: Beveridge T J, Lawrence JR, Murray RGE. (2007). Sampling and staining for light microscopy. In Methods for General and Molecular Bacteriology, 3rd edn. Edited by Beveridge TJ, Breznak JA,Marzluf GA, Schmidt TM, Snyder LR . Washington, DC: American Society for Microbiology.

[155]: Markowitz VM, Chen IMA, Chu K & other authors . (2012). IMG/M: the integrated metagenome data management and comparative analysis system. Nucleic Acids Research. 40:123-129.

150 [156]: Lidstrom ME. (1988). Isolation and characterization of marine methanotrophs. Antonie van Leeuwenhoek 54.3:189-199.

[157]: Powers EM. (1995). Efficacy of Ryu nonstaining KOH technique for rapidly determining gram reactions of food-borne and waterborne bacteria and yeast. Applied Environmental Microbiology. 61:3756-3758.

[158]: Buck JD. (1982). Nonstaining (KOH) method for determination of gram reactions of marine bacteria. Applied Environmental Microbiology. 44:992-993.

[159]: Ostle AG, Holt JG. (1982). Nile blue A as a fluorescent stain for poly-beta- hydroxybutyrate. Applied and Environmental Microbiology. 44:238-241.

[160]: Pieja A, Rostkowski K, Criddle C. (2011). Distribution and Selection of Poly-3- Hydroxybutyrate Production Capacity in Methanotrophic Proteobacteria. Microbial Ecology. 62: 564-573.

[161]:http://seqanswers.com/forums/showthread.php?p=46481%5d%5bDD%5d%5bFF6%5d%5b Kwqq%5d%5bBV77%5d%5bwoo%5d%5bfz%5d%5bz

[162]: Grasby SE, Richards BC, Sharp CE, Brady AL, Jones GM, Dunfield PF. (2013). The paint pots. Kootenay national park, Canada – a natural acid spring analogue for Mars. Canadian Journal of Earth Science. 50:94-108

[163]: Eden PA, Schmidt TM, Blakemore RP, Pace NR. (1991). Phylogenetic analysis of Aquaspirillum magnetotacticum using polymerase chain reaction-amplified 16S rRNA-specific DNA. International Journal of Systematic Bacteriology. 41.2:324-325.

[164]: Tamaki H, Hanada S, Sekiguchi Y, Tanaka Y, Kamagata Y. (2009). Effect of gelling agent on colony formation in solid cultivation of microbial community in lake sediment. Environmental Microbiology. 11:1827-1834.

[165]: Shuler ML, Kargi F. (2002) Bioprocess engineering. New York: Prentice Hall

[166]: Ju‐ Ling L, Radajewski S, Eshinimaev BT, Trotsenko YA, McDonald IR, Murell JC. (2004). Molecular diversity of methanotrophs in Transbaikal soda lake sediments and identification of potentially active populations by stable isotope probing. Environmental Microbiology. 6.10: 1049-1060.

[167]: Khmelenina VN, Kalyuzhnaya MG, Starostina NG, Suzina NE, Trotsenko YA. (1997). Isolation and characterization of halotolerant alkaliphilic methanotrophc bacteria from Tuva soda lakes. Current opinion of Microbiology 35:257-361.

[168]: DeSantis TZ, Hugenholtz P, Larsen N, Rojas M, Brodie EL, Keller K, Huber T, Dalevi D, Hu P, Andersen GL. (2006). Greengenes, a Chimera-Checked 16S rRNA Gene Database and Workbench Compatible with ARB. Applied Environmental Microbiology. 72:5069-72.

151 [169]: Cole JR, Wang Q, Cardenas E, Fish J, Chai B, Farris RJ, Kulam-Syed-Mohideen AS, McGarrell DM, Marsh T, Garrity GM, Tiedje JM. (2009). The Ribosomal Database Project: improved alignments and new tools for rRNA analysis. Nucleic Acids Research. 37:141-145.

[170]: Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, Peplies J, Glöckner FO .(2013). The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Research. 41:590-596.

[171]: Yarza P, Richter M, Peplies J, Euzeby J, Amann R, Schleifer KH, Ludwig W, Glöckner FO, Rossello-Mora R. (2008). The All-Species Living Tree project: A 16S rRNA-based phylogenetic tree of all sequenced type strains. Systematic and Applied Microbiology. 31:241- 250.

[172]: Vecherskaya MS, Galchenko VF, Sokolova EN, Samarkin, VA. (1993). Activity and species composition of aerobic methanotrophic communities in tundra soils. Current opinion in microbiology. 27:181–184.

[173]: Horz HP, Raghubanshi AS, Heyer J, Kammann C, Conrad R., Dunfield PF. (2002). Activity and community structure of methane-oxidising bacteria in a wet meadow soil. FEMS Microbiology Ecol.ogy. 41:247–257.

[174]: Gebert J, Groengroeft A, Miehlich G. (2003). Kinetics of microbial landfill methane oxidation in biofilters. Waste Management. 23:609–619.

[175]: B€orjesson G, Sundh I, Tunlid A, Svensson BH. (1998). Methane oxidation in landfill cover soils, as revealed by potential oxidation measurements and phospholipid fatty acid analyses. Soil Biology and Biochemistry. 30:1423–1433.

[176]: Jahnke L. (1992) The effects of growth temperature on the methyl sterol and phospholipid fatty acid composition of Methylococcus capsulatus (Bath). FEMS Microbiology Letters. 93:209– 212.

[177]: Pacheco-Oliver M, McDonald IR, Groleau D, Murrell JC, Miguez CB. (2002). Detection of methanotrophs with highly divergent pmoA genes from Arctic soils. FEMS Microbiology Letters. 209:313–319.

[178]: Bowman JP, McCammon SA, Skerratt JH. (1997). Methylosphaera hansonii gen. nov., sp. nov., a psychrophilic, group I methanotroph from Antarctic marine-salinity, meromictic lakes. Microbiology. 143:1451–1459.

[179]: Kightley D, Nedwell DB, Cooper M. (1995). Capacity for methane oxidation in landfill cover soils measured in laboratory-scale soil microcosms. Applied Environmental Microbiology. 61:592–601.

[180]: Bodelier PLE, Laanbroek HJ .(2004). Nitrogen as a regulatory factor of methane oxidation in soils and sediments. FEMS Microbiology Ecology. 47: 265–277.

152 [181]: Mohanty SR, Bodelier PLE, Floris V, Conrad R .(2006). Differential effects of nitrogenous fertilizers on methaneconsuming microbes in rice field and forest soils. Applied Environmental Microbiology. 72:1346–1354.

[182]: Noll M, Frenzel P, Conrad R .(2008). Selective stimulation of type I methanotrophs in a rice paddy soil by urea fertilization revealed by RNA-based stable isotope probing. FEMS Microbiology Ecology. 65: 125–132.

[183]: Lee SW, Im J, DiSpirito AA, Bodrossy L, Barcelona M, Semrau JD .(2009). Effect of nutrient and selective inhibitor amendments on methane oxidation, nitrous oxide production, and key gene presence and expression in landfill cover soils: characterization of the role of methanotrophs, nitrifiers and denitrifiers. Applied Microbiology Biotechnology. 85: 389–403.

[184]: Amaral JA, Knowles R. (1995). Growth of methanotrophs in methane and oxygen counter gradients. FEMS Microbiology Letters. 126: 215-220.

[185]: Rudd JWM, Taylor CD. (1980). Methane cycling in aquatic environments. Advanced Aquatic Microbiology. 2:77-150.

[186]: Heyer J, Berger U, Hardt M, Dunfield PF.(2005). Methylohalobius crimeensis gen. nov., sp. nov., a moderately halophilic, methanotrophic bacterium isolated from hypersaline lakes of Crimea. International journal of systematic and evolutionary microbiology. 55.5:1817-1826.

[187]: Dalal R, Allen D, Livesley S, Richards G .(2008). Magnitude and biophysical regulators of methane emission and consumption in the 153ydroxyl153t agricultural, forest, and submerged landscapes: a review. Plant Soil. 309: 43–76.

[188]: Dedysh SN, Khmelenina VN, Suzina NE, Trotsenko YA, Semrau JD, Liesack W, Tiedje JM. (2002). Methylocapsa acidiphila gen. nov., sp. nov., a novel methane-oxidizing and dinitrogen-fixing acidophilic bacterium from Sphagnum bog. International Journal of Systematic and Evolutionary Microbiology. 52.1: 251-261.

[189]: Dedysh SN, Liesack W, Khmelenina VN, Suzina NE, Trotsenko YA, Semrau JD, Bares AM, Panikov NS, Tiedje JM. (2000). Methylocella palustris gen. nov., sp. nov., a new methane- oxidizing acidophilic bacterium from peat bogs, representing a novel subtype of serine-pathway methanotrophs.International Journal of Systematic and Evolutionary Microbiology. 50.3: 955- 969.

[190]: Belova SE, Kulichevskaya IS, Bodelier PL, Dedysh SN. (2013). Methylocystis bryophila sp. nov., a facultatively methanotrophic bacterium from acidic Sphagnum peat, and emended description of the genus Methylocystis (ex Whittenbury et al. 1970) Bowman et al. 1993.” International Journal of Systematic and Evolutionary Microbiology. 63: 1096-1104.

[191]: Dedysh SN. Khmelenina VN, Chidthaisong A, Trotsenko YA, Liesack W, Dunfield PF. (2007). Methylocystis heyeri sp. nov., a novel type II methanotrophic bacterium possessing ‘signature’fatty acids of type I methanotrophs. International journal of systematic and evolutionary microbiology. 57.3: 472-479.

153

[192]: Lindner AS, Pacheco A, Aldrich HC, Costello SA, Uz I, Hodson DJ. (2007). Methylocystis 154ydroxy sp. nov., a novel methanotroph isolated from a groundwater aquifer. International journal of systematic and evolutionary microbiology. 57.8: 1891-1900.

[193]: Wartiainen I, Hestnes AG, McDonald IR, Sevenning MM. (2006). Methylocystis 154ydroxyl. nov., a novel methanotrophic bacterium from Arctic wetland soil, Svalbard, Norway (78 N). International journal of systematic and evolutionary microbiology. 56.3: 541-547.

[194]: Madhaiyan M, Kim BY, Poonguzhali S, Kwon SW, Song MH, Ryu JH, Go SJ, Koo BS, Sa TM. (2007). Methylobacterium oryzae sp. nov., an aerobic, pink-pigmented, facultatively methylotrophic, 1-aminocyclopropane-1-carboxylate deaminase-producing bacterium isolated from rice. International journal of systematic and evolutionary microbiology. 57.2: 326-331.

[195]: Ogiso T, Ueno C, Dianou D, Huy TV, Katayama A, Kimura M, Asakawa S. (2012). Methylomonas koyamae sp. nov., a type I methane-oxidizing bacterium from floodwater of a rice paddy field. International journal of systematic and evolutionary microbiology. 62: 1832-1837.

[196]: Berestovskaya JJ, Kotsyurbenko OR, Tourova TP, Kolganova TV, Doronina NV, Golyshin PN, Vasilyeva LV. (2012). Methylorosula polaris gen. nov., sp. nov., an aerobic, facultatively methylotrophic psychrotolerant bacterium from tundra wetland soil. International journal of systematic and evolutionary microbiology. 62:638-646.

[197]: http://454.com/downloads/GSFLXApplicationFlyer_FINALv2.pdf

[198]: Gilles A, Meglecz E, Pech N, Ferreira S, Malausa T, Martin JF. (2011). Accuracy and quality assessment of 454 GS-FLX Titanium pyrosequencing. BioMed central genomics. 12:245

[199]: Gussin GA, Ranson CW, Ausubel FM. (1986). Regulation of nitrogen fixation genes. Annual revie of genetics. 20:567-591.

154 Appendix

[Appendix 1] (Refer to section 3.2.4, page 45)

Total genomic DNA concentrations in ng and g from July_2011 until December_2011. All genomic DNAs were subjected to 454 pyrotag sequencing as part of the downstream analysis of the current study.

Sample g/mL Volum (L) Total Amount of DNA in g

WIP_July/2011 37.9 69 2.61 (2615.1 ng)

WIP_July/2011 461 187 86.2 (86207 ng)

MLSB_July/2011 34.1 48 1.63 (1636.8 ng)

WIP_August/2011 110 66 7.26 (7260 ng)

MLSB_August/2011 153 85 13.0 (13005 ng)

WIP_October/2011 110 30 3.30 (3300 ng)

MLSB_October/2011 67.4 30 2.02 (2022 ng)

WIP_December/2011 110 28 3.08 (3080 ng)

MLSB/December/2011 110 28 3.08 (3080 ng)

155 [Appendix 2] (Refer to section 3.2.5, page 46)

16S rRNA gene based 454 Pyrotag PCR mastermix recipe.

Component Per Each Run

Nuclease-free water (Qiagen, Maryland USA) 37.4 μl Bovine serum albumin (BSA) (20 mg/ml) 0.75 μl Deoxynucleotide (dNTP mix 25 mM) 0.40 μl

MgCl2 (25 mM) 3.00 μl 10× KCl taq buffer 5.00 μl 10 μM forward primer (FP) (0.04 μmol/L) 0.20 μl Taq DNA polymerase (5U/ μl) (Fermentas) 0.25 μl Unique barcoded reverse primer (0.04 μmol/L) 2.00 μl

Total Volume 50 μl

The thermocycler program is as follows: 35 cycles of 30 seconds at 95 °C, 45 seconds at 55 °C, and 90 seconds at 72 °C. The PCR reaction started with an initial denaturation step for 3 min at

95 °C and a 10 min final elongation at 72 °C [162].

156 [Appendix 3] (Refer to section 3.2.9, page 50)

For the purpose of calculating the percentage of methane consumption in a single 120 ml serum vial three injections were performed from the Praxair compressed tank with 0.98% CO2, 0.49%

CO, 0.49% CH4 standards (balanced with N2) into GC/FID in 2 min intervals (programed to analyze carbon-hydrogen bonds via two FID detectors). Each sample area obtained from the

GC/FID C-H analysis was multiplied to the standard CH4 0.5% (from the tank) and the result was divided by the mean value of the three injected standards (three sample areas injected from the standard tank).

157 [Appendix 4] (Refer to section 3.2.9, page 50)

Oxidation rates were determined based on linear regression of methane mixing ratios (mol

-1 -1 CH4/mol gas) in headspace in nmol CH4 ml d . For example if we consider 7.65% remaining methane in the headspace of a 120-ml serum vial, for calculating the oxidation rate in nmol CH4 ml-1 d-1 the following calculations were performed; 7.65/1000 = 0.00765 L then the ideal gas law formula (http://www.ajdesigner.com/idealgas/ideal_gas_law_mole_equation.php) was used for solving for number of the moles in the following sample; N=PV/RT, which N = number of the moles, P = 1 atm (room pressure based on atmosphere), V = 0.00765 (volume per L), R =

0.08206 L.atm mol-1.K-1 (universal gas constant) and T = 298.15 K (room temperature based on

Kelvin). By solving the equation 0.000307 moles was obtained, which it was later multiplied to

109 in order to convert mole into nmol and at the end nmol was divided to 220 ml (one filter which is equivalent to 200 ml of tailing water + 20 ml directly taken from the sample buckets.

-1 Refere to 3.2.2) the result is 1397 nmol of CH4 ml . By calculating all the percentage of CH4 in the headspace in different time intervals based on the equation described above, obtained results were plotted into a graph, which demonstrates x-axis as time vs y-axis as nmol of CH4 in the headspace. The data were plotted in an Excel sheet for automatic calculation of the slope and later were transferred into Sigma plot graphing software (version 12.3) for beautifying the graphs.

158 [Appendix 5] (Refer to section 3.2.13, section 4.2.1, and section 4.8.5 , page 57, page 103, and page 122 respectively)

Medium for methanotrophic bacteria (Heyer et al. 1984)

(Medium 10 pH 8.3)

Solution 1 in 500 ml;

MgSO4.7H2O 0.1 g

NH4Cl 0.5g

Na2HPO4 0.5g

CaCl2.6H2O 0.01g

FeSO4.7H2O 0.005g

Trace element solution JH 1ml

Carbonate Biocarbonate buffer

NaHCO3 0.756g

pH-value adjust with 10% NaOH and H2SO4 to 8.6 (after autoclaving and mixing all solutions pH drops to 8.4)

159

Solution 2 in 500 ml;

MgSO4.7H2O 1.0g

Phytagel 15.0g

May add 50 mg of cyclohexamide in 10 ml water, filter sterilized, to medium after autoclaving and cooling to 80 oC.

Trace Element Solution JH;

In 1 ml contained:

ZnSO4.7H2O 0.44 mg (0.1 mg Zn)

CuSO4.5H2O 0.20 mg (0.05 mg Cu)

MnSO4.2H2O 0.17 mg (0.05 mg Mn)

Na2MO4.2H2O 0.06 mg (0.024 mg MO)

H3BO3 0.10 mg (0.02 mg B)

CoCl2.6H2O 0.08 mg (0.02 mg Co)

160

[Appendix 6] (Refer to section 3.2.13 and section 4.2.1, page 57 and page 104 respectively)

Medium for methanotrophic bacteria (Heyer et al. 1984)

(Medium 10X CF pH 8.3)

Solution 1 in 500 ml;

MgSO4.7H2O 0.1 g

NH4Cl 0.5g

Na2HPO4 0.5g

CaCl2.6H2O 0.01g

FeSO4.7H2O 0.005g

Fe EDTA 0.05g

Trace element solution JH 1ml

Carbonate Biocarbonate buffer

NaHCO3 0.756g

CuSO4.5H2O 0.02 g

pH-value adjust with 10% NaOH and H2SO4 to 8.6 (after autoclaving and mixing all solutions pH drops to 8.4)

161

Solution 2 in 500 ml;

MgSO4.7H2O 1.0g

Phytagel 15.0g

May add 50 mg of cyclohexamide in 10 ml water, filter sterilized, to medium after autoclaving and cooling to 80 oC.

Trace Element Solution JH;

In 1 ml contained:

ZnSO4.7H2O 0.44 mg (0.1 mg Zn)

CuSO4.5H2O 0.20 mg (0.05 mg Cu)

MnSO4.2H2O 0.17 mg (0.05 mg Mn)

Na2MO4.2H2O 0.06 mg (0.024 mg MO)

H3BO3 0.10 mg (0.02 mg B)

CoCl2.6H2O 0.08 mg (0.02 mg Co)

162

[Appendix 7] (Refer to section 3.2.13 and section 4.2.1, page 58 and page 104 respectively)

16S rRNA gene based colony PCR mastermix recipe.

Component Per Each Run

Nuclease-free water (Qiagen, Maryland USA) 22.8 μl 2 × Premix F 25.0 μl Forward primer Eu9f 0.50 μl Reverse primer Eu1492b 0.50 μl Taq DNA polymerase (5U/ μl) (Fermentas) 0.20 μl

Total Volume 50 μl

Forward primer Eu9f (GAGTTTGATCMTGGCTCAG) (prepared 1:1 primer/water from 100M stock primer) [163].

Reverse primer Eu1492b (ACGGYTACCTTGTTACGACTT) (prepared 1:1 primer/water from

100M stock primer) [163].

163 PCR conditions includes; initial denaturation at 94 oC for 15 min, 33 cycles of 94 oC for 45 sec

(denaturation), 48 oC for 1 min (annealing), 72 oC for 2 min (elongation) and final elongation step at 72 oC for 5 min.

164 [Appendix 8] (Refer to section 3.2.13 and section 4.2.1, page 58 and page 104 respectively)

pmoA gene based colony PCR mastermix recipe.

Component Per Each Run

Nuclease-free water (Qiagen, Maryland USA) 22.8 μl 2 × Premix F 25.0 μl Forward primer 189 0.50 μl Reverse primer 661b 0.50 μl Taq DNA polymerase (5U/ μl) (Fermentas) 0.20 μl

Total Volume 50 μl

Forward primer189f (GGNGACTGGGACTTCTGG) (prepared 1:1 primer/water from 100M stock primer) [164].

Reverse primer 661b (CCGGMGCAACGTCYTTACC) (prepared 1:1 primer/water from 100M stock primer) [164].

165 Uploaded program in the thermal cycler consists of initial denaturation at 94oC for 5 minutes, 20 touchdown cycles 62-52oC (94oC for 1 minutes, 62-52oC for 30 seconds and 72oC for 45 seconds), 15 further cycles at annealing temperature of 52oC (94oC for 1 minutes, 52oC for 30 seconds, 72oC for 45 seconds), and final elongation at 72oC for 5 minutes.

166 [Appendix 9] (Refer to section 3.3, page 61)

LB-agar Medium in 1 L;

Bacto Tryptone 10 g

Bacto Yeast Extract 5.0 g

NaCl 5.0 g

Agar 15 g

2.5 g of ampicillin sodium salt was dissolved in 50 ml of deionized water and then filter sterilized and stored in aliquots at 4 oC. pH were adjusted to 7 with NaOH.

Before pouring LB-ampicillin agar plates, medium was cooled to approximately 55 oC. 2 ml of ampicillin stock solution (50 mg/ml) was to a final concentration of 100 g/ml. Solution was mixed gently before pouring the plates.

167 [Appendix 10] (Refer to section 3.4.7, page 80)

Graphs (a,b,c,d,e.f.g) represents decrease in methane percentage from tailing ponds WIP and

MLSB from different month of sampling except WIP_August 2011 sample, which has been represented as an example in section 3.3.7

168

Figure a. Decrease in methane percentage of WIP_July/2011 center of pond sample shown with linear regression line and leakage control versus time.

169

Figure b. Decrease in methane percentage of WIP_July/2011 surface of the pond sample shown with linear regression line and leakage control versus time.

170

Figure c. Decrease in methane percentage of MLSB_July/2011 sample shown with linear regression line and leakage control versus time.

171

Figure d. Decrease in methane percentage of MLSB_August/2011 sample shown with linear regression line and leakage control versus time.

172

Figure f. Decrease in methane percentage of WIP_October/2011 sample shown with linear regression line and leakage control versus time.

173

Figure g. Decrease in methane percentage of MLSB_October/2011 sample shown with linear regression line and leakage control versus time.

174 [Appendix 11] (Refer to section 3.4.7, page 82)

MLSB Tailings water surface area is 10 km2 and the methanotrophic active layer is reported 60 cm. In order to calculate the percentage of methane oxidation in the entire MLSB tailings pond the following calculation were performed; 10 km2 MLSB water surface area was converted to

10000000 m2 and the active methanotrophic layer 60 cm was converted to 6000000 m3 . 6000000 m3 was first converted to 6000000 tons and then into 6000000000 L and at the end into 6 × 1012

-1 -1 ml. 136 nmol CH4 ml d from August/2011 WIP sample was selected as the most active sample

12 based on the CH4 oxidation rates and this value was multiplied to 6 × 10 ml, which resulted in

12 -1 816 × 10 nmol CH4 d . Based on the ideal gas law equation N=PV/RT, 1 mole CH4 = 22.4 L.

12 -1 -1 -1 By converting 816 × 10 nmol CH4 d into L of CH4 d 18278400 L of CH4 d will be obtained, which is approximately 18% of the produced methane (18 × 106).

175

[Appendix 12] (Refer to section 4.2.1, and section 4.8.5 page 103, and page 122 respectively)

Pre-prepared LB Broth (Sigma Life Science); 20 g dissolved in 1 L of H2O.

[Appendix 13] (Refer to section 4.2.1, and section 4.8.5, page 103, and page 122)

Pre-prepared Nutrient Broth (BD); 8.0 g dissolved in 1 L of H2O.

176 [Appendix 14] (Refer to section 4.2.1, and section 4.8.5, page 103, and page 122 respectively)

Medium R2A (pH 7)

In 1 L;

Yeast Extract 0.5 g

Proteose Peptone 0.5 g

Casein Hydrolysate 0.5 g

Glucose 0.5 g

Soluble Starch 0.3 g

Dipotassium Hydrogenphosphate 0.3 ml

MgSO4.7H2O 0.05 g

Agar 15 g

Trace Element JH 1.0 ml

177 [Appendix 15] (Refer to section 4.2.1, and section 4.8.5, page 103, and page 122 respectively)

The composition of the API 50 CH strip is given below in list of tests

Tube Test Active Ingredients QTY (mg/cup)

0 Control -

1 GLY GLYcerol 1.64

2 ERY ERYthritol 1.44

3 DARA D-ARAbinose 1.40

4 LARA L-ARAbinose 1.40

5 RIB D-RIBose 1.40

6 DXYL D-XYLose 1.40

7 LXYL L-XYLose 1.40

8 ADO D-ADOnitol 1.36

9 MDX Methyl-D-Xylopyranoside 1.28

178

Tube Test Active Ingredients QTY (mg/cup)

10 GAL D-GALactose 1.40

11 GLU D-GLUcose 1.56

12 FRU D-FRUctose 1.40

13 MNE D-MaNnosE 1.40

14 SBE L-SorBosE 1.40

15 RHA L-RHAmnose 1.36

16 DUL DULcitol 1.36

17 INO INOsitol 1.40

18 MAN D-MANnitol 1.36

19 SOR D-SORbitol 1.36

179 Tube Test Active Ingredients QTY (mg/cup)

20 MDM Methyl-D-Mannopyranoside 1.40

21 MDG Methyl-D-Glucopyranoside 1.56

22 NAG N-AcetylClucosamine 1.40

23 AMY AMYgdaline 1.40

24 ARB ARButin 1.40

25 ESC ESCulin ferric citrate 1.36

26 SAL SALicin 1.36

27 CEL D-CELlobiose 1.40

28 MAL D-MALtose 1.36

29 LAC D-LACtose (Bovine Origin) 1.36

180 Tube Test Active Ingredients QTY (mg/cup)

30 MEL D-MELibiose 1.40

31 SAC D-SACcharose (Sucrose) 1.56

32 TRE D-TREhalose 1.40

33 INU INUlin 1.40

34 MLZ D-MeLeZitose 1.40

35 RAF D-RAFfinose 1.36

36 AMD AmiDon (Starch) 1.36

37 GLYG GLYcoGen 1.40

38 XLT XyLiTol 1.36

39 GEN GENtiobiose 1.36

181 Tube Test Active Ingredients QTY (mg/cup)

40 TUR D-TURanose 1.32

41 LYX D-LYXose 1.40

42 TAG D-TAGatose 1.40

43 DFUC D-FUCose 1.28

44 LFUC L-FUCose 1.28

45 DARL D-ArabitoL 1.40

46 LARL L-ArabitoL 1.40

47 GNT Potassium GlucoNaTe 1.84

48 2KG Potassium 2-KetoGluconate 2.12

49 5JG Potassium 5-KetoGluconate 1.80

182 [Appendix 16] (Refer to section 4.7 and section 4.8.3, page 111 and page 117 respectively)

Table a. Genes involved in methane and methanol oxidation in comparison with reference

Methylosinus trichosporium OB3b. In Table N/A refers to as no gene detection.

Locus Tag Predicted Function of strain XLMV4 Reference methanotroph Gene

draft_02100 Particulate methane monooxygenase subunit C Particulate methane monooxygenase subunit C pmoC draft_02099 Particulate methane monooxygenase subunit A Particulate methane monooxygenase subunit A pmoA draft_02098 Particulate methane monooxygenase subunit B Particulate methane monooxygenase subunit B pmoB N/A N/A Soluble methane monooxygenase alpha subunit mmoX N/A N/A Soluble methane monooxygenase beta subunit mmoY N/A N/A Soluble methane monooxygenase beta subunit mmoZ draft_00929 Methanol dehydrogenase (cytochrome) large subunit apoprotein PQQ-dependent methanol dehydrogenase mxaF draft_00926 Methanol dehydrogenase (cytochrome) small subunit PQQ-dependent methanol dehydrogenase mxaI draft_00927 Cytochrome cL apoprotein Cytochrome c class I mxaG draft_00928 Methanol oxidation system protein MoxJ Extracellular solute-binfing protein family 3 mxaJ N/A N/A Putative methanol utilization control sensor protein mxaY draft_00930 two component transcriptional regulator, LuxR family Putative two-cmponent response regulator mxaB draft_00931 Polyketide cyclase/dehydrase and lipid transport MxaD protein, involved in methanol oxidation mxaD N/A N/A MxaH protein, involved in methanol oxidation mxaH draft_00919 von Willebrand factor type A domine von Willebrand factor type A, involved in methanol oxidation mxaL draft_00920 Hypothetical protein Protein of unknown function, involved in methanol oxidation mxaK draft_00921 Uncharacterized protein containing a von Willebrand factor type A (vWA) domain von Willebrand factor type A, involved in methanol oxidation mxaC draft_00922 Hypothetical protein MxaA protein, involved in methanol oxidation mxaA draft_00923 Hypothetical protein MxaS protein, involved in methanol oxidation mxaS draft_00925 MoxR-like ATPase ATPase, involved in methanol oxidation mxaR N/A N/A Coenzyme PQQ biosynthesis protein A pqqA draft_02215 Coenzyme PQQ biosynthesis protein E Coenzyme PQQ biosynthesis protein E pqqE draft_02213 Coenzyme PQQ biosynthesis protein C Coenzyme PQQ biosynthesis protein C pqqC draft_02214 Coenzyme PQQ biosynthesis protein D Coenzyme PQQ biosynthesis protein D pqqD draft_02212 Coenzyme PQQ biosynthesis protein B Coenzyme PQQ biosynthesis protein B pqqB N/A N/A Coenzyme PQQ biosynthesis protein F pqqF N/A N/A Coenzyme PQQ biosynthesis protein G pqqG N/A N/A Aldehyde dehydrogenase aldh N/A N/A Aldehyde oxidase aor N/A N/A Aldehyde dehydrogenase aldh-F7

183 Table b. Genes involved in formaldehyde oxidation in comparison with reference Methylosinus

trichosporium OB3b. In Table N/A refers to as no gene detection.

Locus Tag Predicted Function of strain XLMV4 Reference methanotroph Gene

draft_04122 Methenyltetrahydromethanopterin cyclohydrolase Methenyltetrahydromethanopterin cyclohydrolase mch draft_04128 probable H4MPT-linked C1 transfer pathway protein Tetrahydromethanopterin-linked C1 transfer pathway protein orf5 or orf7,orf17, orf9 deaft_04125 Formaldehyde activating enzyme Formaldehyde activating enzyme fae 1 N/A N/A Tetrahydromethanopterin formyltransferase, subunit C fhcC N/A N/A Tetrahydromethanopterin formyltransferase, subunit D fhcD N/A N/A Tetrahydromethanopterin formyltransferase, subunit A fhcA N/A N/A Tetrahydromethanopterin formyltransferase, subunit B fhcD draft_05125 Methylene-tetrahydromethanopterin dehydrogenase,N-terminal Methylenetetrahydrofolate dehydrogenase (NAD) mtdB draft_04120 Beta-Ribofuranosylaminobenzene 5-phosphate synthase Ribofuranosylaminobenzene 5-phosphate synthase mptG

Table c. Genes involved in formate oxidation in comparison with reference Methylosinus

trichosporium OB3b. In Table N/A refers to as no gene detection.

Locus Tag Predicted Function of strain XLMV4 Reference methanotroph Gene

N/A N/A Transcriptional regulatory, LysR family fdsR draft_04420 Formate dehydrogenase delta subunit NAD_linked formate dehydrogenase, subunit D fdsD draft_04421 Formate dehydrogenase family accessory protein Formate dehydrogenase family accessory protein fdsC draft_04422 Formate dehydrogenase alpha subunit NAD_linked formate dehydrogenase, subunit A fdsA draft_04423 Formate dehydrogenase beta subunit NAD_linked formate dehydrogenase, subunit B fdsB draft_04424 Formate dehydrogenase gamma subunit NAD_linked formate dehydrogenase, subunit G fdsG

184 Table d. Genes involved in serine cycle (C1 assimilation) in comparison with reference

Methylosinus trichosporium OB3b. In Table N/A refers to as no gene detection.

Locus Tag Predicted Function of strain XLMV4 Reference methanotroph Gene

N/A N/A Phosphoenolpyruvate caboxylase ppc draft_03619 Glycerate 2-kinase Glycerate kinase gckA draft_02166 beta-methylmalyl-CoA/L-malyl-CoA lyase Malyl-CoA lyase/beta-methylmalyl-CoA lyase mclA draft_02164 Succinyl-CoA synthetase (DAP-forming) small subunit Malate thiokinase, small subunit mtkB draft_02165 Succinyl-CoA synthetase (DAP-forming) large subunit Malate thiokinase, large subunit mtkA draft_00462 methenyltetrahydrofolate cyclohydrolase Methenyltetrahydrofolate cyclohydrolase fch draft_03620 5,10-methylenetetrahydrofolate dehydrogenase (NADP+) Methylenetetrahydrofolate dehydrogenase (NADP+) mtdA N/A N/A 2-Hydroxy dehydrogenase NAD-binding hprA draft_02168 Serine-glyoxylate aminotransferase apoenzyme Serine-glyoxylate aminotransferase sga draft_03617 Formate-tetrahydrofolate ligase Formate-tetrahydrofolate ligase ftfL draft_03618 Glycine/Serine hydroxymethyltransferase Serine hydroxymethyltransferase glyA draft_04105 Enolase Enolase eno

185 Table e. Genes involved in ribulose monophosphate cycle (C1 assimilation) in comparison with

reference Methylosinus trichosporium OB3b. In Table N/A refers to as no gene detection. All

genes involved in RuMP cycle are absent in the model methanotroph genome.

Locus Tag Predicted Function of strain XLMV4 Reference methanotroph Gene draft_00756 3-hexulose-6-phosphate synthase N/A draft_00239 3-hexulose-6-phosphate synthase N/A draft_00757 6-phospho-3-hexuloisomerase N/A draft_02872 hexose kinase, 1- phosphofructokinase family N/A draft_00762 Fructose-bisphosphate aldolase (class II) N/A draft_01120 Fructose-bisphosphate aldolase (class I) N/A draft_03107 transketolase N/A draft_00758 transketolase, bacteria and yeast N/A draft_00761 transaldolase N/A draft_00599 Ribose-5-phosphate isomerase N/A draft_00299 Ribose-5-phosphate isomerase N/A draft_00310 ribulose-phosphate 3-epimerase N/A draft_04827 D-fructose 1,6-bisphosphatase N/A draft_03717 Phosphoketolase N/A draft_05285 Phosphoketolase N/A

186 Table f. Genes involved in EMP pathway and PHB cycle (C1 assimilation) in comparison with

reference Methylosinus trichosporium OB3b. In Table N/A refers to as no gene detection

Locus Tag Predicted Function of strain XLMV4 Reference methanotroph Gene

draft-00106 Acetyl-CoA acethyltransferase Acetyl-CoA acethyltransferase phaA N/A N/A Acetoacetyl-CoA reductase phaB N/A N/A Crotonase croR N/A N/A Crotonyl-CoA reductase ccr N/A N/A Ethylmalonyl-CoA mutase ecm N/A N/A Methylsuccinyl-CoA dehydrogenase ibd N/A N/A Mesaconyl-CoA hydratase meaC N/A N/A Methylmalonyl-CoA epimerase epm draft_02166 beta-methylmalyl-CoA/L-malyl-CoA lyase Malyl-CoA lyase/beta-methylmalyl-CoA lyase mclA2 draft_02800 Acetyl-CoA carboxylase, biotin carboxylase subunit Acetyl/propionyl-CoA carboxylase ppcA draft_02707 Acetyl-CoA carboxylase, biotin carboxylase subunit Propionyl-CoA carboxylase ppcB N/A N/A Methylmalonyl-CoA mutase, large subunit mcmA N/A N/A Methylmalonyl-CoA mutase, small subunit mcmB N/A N/A 3-Hydroxybutyrate dehydrogenase bdhA N/A N/A Poly-beta-hydroxybutyrate polymerase phaC N/A N/A Acetoacetate decarboxylase aad N/A N/A Acetoacetyl-coenzyme A synthase aas N/A N/A Polyhydroxyalkanoate depolymerase phaZ

187 Table g. Genes involved in TCA cycle in comparison with reference Methylosinus trichosporium

OB3b. In Table N/A refers to as no gene detection.

Locus Tag Predicted Function of strain XLMV4 Reference methanotroph Gene

draft_03621 Malate dehydrogenase Malate dehydrogenase mdh draft_01208 succinyl-CoA synthetase (ADP-forming) beta subunit Succinyl-CoA synthase, beta subunit sucC draft_01207 succinyl-CoA synthetase (ADP-forming) alpha subunit Succinyl-CoA synthase, Alpha subunit sucD draft_03853 2-Oxoglutarate dehydrogenase E1component 2-Oxoglutarate dehydrogenase E1 sucA draft_03852 2-Oxoglutarate dehydrogenase E2component 2-Oxoglutarate dehydrogenase E2 sucB draft_03881 succinate dehydrogenase and fumarate reductase iron-sulfur protein Succinate:ubiquinone oxidoreductase sdhB draft_03880 Succinate dehydrogenase subunit A Succinate:ubiquinone oxidoreductase sdhA draft_03878 Succinate dehydrogenase subunit C Succinate:ubiquinone oxidoreductase, cytochrome b556 subunit sdhC draft_02689 Fumarase, class I, homodimeric Fumarate hydratase fum draft_03817 Fumarase, class II N/A N/A N/A 2-Oxoacid ferredoxin oxidoreductase ofr

188 Table h. Genes involved in intermediary metabolism and anaplerotic CO2 – fixation comparison

with reference Methylosinus trichosporium OB3b. In Table N/A refers to as no gene detection

Locus Tag Predicted Function of strain XLMV4 Reference methanotroph Gene draft_04658 Phosphoenolpyruvate synthase Phosphoenolpyruvate synthase pps N/A N/A Pyruvate carboxylase pcx N/A N/A Acetyl-coenzyme A carboxylase subunit beta accD draft_01706 acetyl-CoA carboxylase carboxyltransferase subunit alpha Acetyl-CoA carboxylase subunit alpha accA N/A N/A Acetyl_CoA carboxylase, biotin carboxy carrier protein accB draft_03549 Pyruvate kinase Pyruvate kinase pyk1? draft-04486 Pyruvate kinase N/A Pyk2? N/A N/A Pyruvate dehydrogenase (acetyl-transferring) E1 pdhA N/A N/A Pyruvate dehydrogenase subunit beta pdhB N/A N/A Pyruvate dehydrogenase pdhC draft_00703 Pyruvate phosphate dikinase Pyruvate phosphate dikinase pdk draft_02326 Malic Enzyme Malic enzyme mae draft_00397 Phosphoglycerate mutase Phosphoglycerate mutase gpmA N/A N/A Phosphoglycerate mutase (modular protein) pgm N/A N/A Phosphoglycerate mutase (modular protein) pgm draft_01806 Phosphoglycerate kinase Phosphoglycerate kinase pgk draft_04485 Glyceraldehyde-3-phosphate dehydrogenase, type I Glyceraldehyde-3-phosphate dehydrogenase gpd draft_01158 Glyceraldehyde-3-phosphate dehydrogenase/erythrose-4-phosphate dehydrogenase N/A draft_00510 Sugar kinases, ribokinase family Ribokinase rik draft_00886 Sugar kinases, ribokinase family N/A N/A N/A Phosphoribulokinase prk draft_00758 Transketolase, bacteria and yeast Transketolase tkl draft_03107 Transketolase N/A tkl draft_00762 Fructose-bisphosphate aldolase Fructose-bisphosphate aldolase, class II fba N/A N/A 6-phosphofructokinase pkf draft-04827 D-fructose 1,6-bisphosphatase Fructose 1,6-bisphosphatase glp draft_02881 Glucose-6-phosphate isomerase Glucose-6-phosphate isomerase pgi draft_00310 ribulose-5-phosphate 3-epimerase Ribulose-phosphate 3-epimerase rpe

189 Table i. Genes involved in N2, Cu and Fe metabolism in comparison with reference Methylosinus

trichosporium OB3b. In Table N/A refers to as no gene detection

Locus Tag Predicted Function of strain XLMV4 Reference methanotroph Gene

draft_01951 ABC-type nitrate/sulfonate/bicarbonate transport systems, periplasmic components Nitrate transporter component nrtA draft_01955 NAD(P)H-nitrite reductase Nitrite reductase (NAD(P)H), large subunit nasB N/A N/A Nitrite reductase (NAD(P)H), small subunit masD N/A N/A Nitrate reductase, large subunit nasA draft_04574 Ammonium transporter Ammonium transporter amtB draft_04576 Ammonium transporter N/A draft_05124 Glutamate synthase domain 2 Glutamate synthase large subunit (NADPH/GOGAT)gltB draft_01223 NADPH-dependent glutamate synthase beta chain and related oxidoreductases Glutamate synthase small subunit (NADPH/GOGAT)gltD draft_01331 glutamate dehydrogenase (NAD) (EC 1.4.1.2) Glutamate dehydrogenase gdh N/A N/A Glutamate-ammonia ligase glnS draft_04575 Nitrogen regulatory protein P-Iifamily Nitrogen regulatory protein P-II glnK draft_04573 Nitrogen regulatory protein P-II family N/A draft_04572 L-glutamine synthetase (EC 6.3.1.2) Glutamin synthase, type I glnA draft_00421 L-alanine dehydrogenase (EC 1.4.1.1) Alanine dehydrogenase aldA draft_03521 phosphoserine aminotransferase apoenzyme (EC 2.6.1.52) Phosphoserine aminotransferase serC N/A N/A Cytochrome c-alpha cycA N/A N/A Putative oxygenase N/A N/A Hydroxylamine reductase hcp draft_01424 transcriptional regulator, TetR family Putative 190ydroxyl190tional regulator nsrR draft_04352 transcriptional regulator, TetR family N/A N/A N/A Putative FecR iron sensor protein fecR draft_00784 outer membrane transport energization protein TonB (TC 2.C.1.1.1) Putative TonB-dependent receptor protein tonB draft_00205 outer membrane transport energization protein TonB (TC 2.C.1.1.1) N/A N/A N/A Methanobactin precursor Mb draft_04684 Lysine/ornithine N-monooxygenase L-Ornithine 5-monooxygenase pvdA1 N/A N/A Putative 190ydroxyl-l-ornithine formylase pvdF N/A N/A L-Ornithine 5-monooxygenase pvdA2 N/A N/A Diaminobutyrate-2-oxoglutarate aminotransferasepvdH draft_00342 RNA polymerase, sigma-24 subunit, RpoE Sigma-24 (Fecl-like) pvdS N/A N/A Putative pyoverdine ABC export system, permeasepvdE draft_03728 TonB-dependant siderophore receptor TonB-dependant siderophore receptor fpvA N/A N/A FecR-like protein fecR N/A N/A Fecl-family sigma factor fecl N/A N/A Ferribactin synthase pvdL darft_04688 Probable taurine catabolism dioxygenase Pyoverdine biosynthesis regulatory protein-TauD/TfdA protein darft_04687 Predicted thioesterase involved in non-ribosomal peptide biosynthesi Pyoverdine synthetase, thioestrase componentpvdG N/A N/A Integral components of non-ribosomal peptideMbtH synthetase N/A N/A Putative pyoverdine peptide synthetase IV, d-Asppvdl/J-l- Ser draft_03648 non-ribosomal peptide synthase domain TIGR01720 Putative non-ribosomal peptide synthase pvdJ/D

190 draft_03642 Nitric Oxide Reductase, NorC subunit apoprotein N/A norC draft_03643 Nitric Oxide Reductase, NorB subunit apoprotein N/A norB N/A N/A N/A nirK N/A N/A N/A nirS N/A N/A N/A Cyts N/A N/A N/A CytL draft_04718 Aerobic Hydroxylamine Oxidoreductase Precursor N/A haoAB draft_00680 Nitrogen Fixation Protein_NifZ domain N/A nifZ draft_00682 Nitrogen Fixation Protein_Modular FeS cluster scaffolding protein NifU N/A nifU draft_00683 Nitrogen Fixation Protein_Cysteine desulfurase NifS N/A nifS draft_00869 Nitrogen Fixation Protein_NifQ N/A nifQ draft_00875 Nitrogen Fixation Protein_Nitrogenase cofactor biosynthesis protein NifB N/A nifB draft_00900 Nitrogen Fixation Protein_Mo_nitrogenase iron protein subunit NifH N/A nifH draft_00901 Nitrogen Fixation Protein_ Mo_nitrogenase MoFe protein subunit NifD N/A nifD draft_00902 Nitrogen Fixation Protein_ Mo_nitrogenase MoFe protein subunit NifK N/A nifK draft_01721 Nitrogen Fixation Protein_Nitrogen fixation negative regulator NifL N/A nifL draft_01762 Nitrogen Fixation Protein_Homocitrate synthase NifV N/A nifV draft_04547 Nitrogen Fixation Protein_Nitrogenase molybdenum-iron cofactor biosynthesis protein NifE N/A nifE draft_04548 Nitrogen Fixation Protein_ Nitrogenase molybdenum-iron cofactor biosynthesis protein NifN N/A nifN draft_04549 Nitrogen Fixation Protein_NifX N/A nifX draft_04554 Nitrogen Fixation Protein_NifW N/A nifW draft_04556 Nitrogen Fixation Protein_NifM N/A nifM draft_04559 Nitrogen Fixation Protein_Flavodoxin, long chain N/A nifF draft_04559 Nitrogen Fixation Protein_Pyruvate:ferredoxin(flavodoxin) oxidoreductase, homodimeric N/A nifJ

191 [Appendix 17] (Refer to section 4.8.1, page 111)

Calculating growth rate of strain XLMV4T [165];

Bacterial growth is an exponential pattern. Based on this reaction dN/dt = N where N is the concentration of the growting cells, t the time and  value is the specific growth rate. By integrating N1 (represents the cell concentration at the early exponential phase [according to the growth curve]), N2 (represents the cell concentration at the end of the exponential phase

[according to the growth curve]), t1 (time in the early exponential phase) and t2 (time in the end of the exponential phase) into the previous equation the result will be the following equation; ln(N2/N1) = (t2-t1), which ln is the natural log (loge).

Based on the obtained growth curve from the target strain; N1 = 0.085, N2 = 0.31, t1 = 120 h, and t2 = 168 h, by solving the equation  = 0.0269 h-1.

For calculating the generation time (g), since when N2 = 2N1, t2-t1 becomes equal to g

(generation time). By substituting values for t and N into the previous equation, we obtain the following; g=ln2/, which ln2 is equal to 0.693.

Solving the following equation g = 0.0693/0.02695669 generation time will be 25 h for the target strain XLMV4T.

192

193