Microbiological and Bioinformatics Investigation Into Acid Rock Drainage Phenomenon in Alberta Oil Sands Tailings

MICROBIOLOGICAL AND BIOINFORMATICS INVESTIGATION INTO ACID ROCK DRAINAGE PHENOMENON IN ALBERTA OIL SANDS TAILINGS

Masoud TaghinezhadNamini

A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF

MASTER OF APPLIED SCIENCE

The College of Graduate Studies

(Civil Engineering)

THE UNIVERSITY OF BRITISH COLUMBIA

(Okanagan Campus)

January 2017

The undersigned certify that they have read, and recommend to the College of Graduate Studies for acceptance, a thesis entitled:

MICROBIOLOGICAL AND BIOINFORMATICS INVESTIGATION INTO ACID ROCK DRAINAGE PHENOMENON IN ALBERTA OIL SANDS TAILINGS

Submitted by Masoud TaghinezhadNamini in partial fulfilment of the requirements of the degree of master of applied science.

Deborah Roberts (School of Engineering / Faculty of Applied Science) Supervisor, Professor

Curtis Suttle (Faculty of Science / Department of Earth, Ocean and Atmospheric Sciences) Co-supervisor, Professor

Sumi Siddiqua (School of Engineering / Faculty of Applied Science) Supervisory Committee member, Assistant Professor

Miranda Hart (School of Arts and Sciences / Faculty of Biology) University Examiner, Assistant Professor

January 20, 2017

Abstract

The Alberta oil sands have produced considerable revenue for Canada. However, the environmental effects associated with extracting the oil can be devastating if not understood and dealt with. One of the potential environmental hazards is acid rock drainage (ARD) from oil sand deposits. Acidification is a well-known destructive phenomenon from our mining industry that leads to the pollution of soil and surrounding water resources. Since microorganisms are major contributors in the onset and propagation of ARD, the successful approach to the problem should focus on the microorganisms. Five bacteria that are believed to be major contributors to ARD were isolated from raw and paraffinic thickened tailings at different temperatures. To gain a deeper insight into the isolated bacteria, their 16S rRNA genes were partially sequenced, Gram stains were performed, metabolic rates were determined using pH, sulfate, thiosulfate, ferric iron concentration changes. All of these were determined at 6 different temperatures 7, 12, 25, 30, 37 and 40°C. The results revealed that all of the isolates were capable of growth at 4°C but had maximum growth rates at 25 or 30°C. A significant attempt was made to isolate the phages capable of lysing isolated bacteria for the possibility of phage therapy. An in depth study was conducted regarding the CRISPR systems in the bacteria that are believed to be the major contributors to

ARD. The results revealed that there is evidence of lytic viral infections in the bacterial population capable of reducing the pH in ARD environments. This reveals that lytic viruses could be isolated under the right circumstances.

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Preface

All of the work for the isolation of bacteria and bacteriophage was performed in the

Biological Solutions Laboratory (BSL) on UBC’s Okanagan campus under Professor Roberts' supervision. Most of the work on bacterial acid production kinetics was also done in the BSL. The bioinformatics studies were done on UBC’s Vancouver campus under the supervision of Professor

Suttle.

None of the material in this thesis has been published. Figure 1 was used with permission from Nature magazine. All other figures and tables are original.

Table of Contents

Examination Committee...... ii Abstract ...... iii Preface ...... iv Table of Contents ...... v List of Tables ...... vii List of Figures ...... ix List of Abbreviations ...... xii Acknowledgments ...... xiv Introduction ...... 1

1.1 Oil sands tailings ...... 1 1.2 Acid rock drainage and its effect ...... 3

1.2.1 ARD reactions ...... 4

1.3 Microbial ecology of ARD ...... 5 1.4 Treatment of ARD ...... 7

1.4.1 Chemical treatment ...... 7 1.4.2 Biological treatment methods ...... 8

1.5 Prevention of ARD ...... 9 1.6 Phage therapy ...... 10

1.6.1 Bacteriophage life cycle ...... 11 1.6.2 Industrial applications of phage therapy ...... 12 1.6.3 Bacterial defense against viral infection ...... 15

1.7 Objectives ...... 20

Materials and Methods ...... 22

2.1 Tailings samples ...... 22 2.2 Microbial media ...... 23 2.3 Bacterial isolation ...... 24 2.4 Bacterial characterization ...... 27 2.5 Phage isolation ...... 29

2.6 Growth and acid production kinetics ...... 29

2.6.1 Sulfur oxidizing bacteria ...... 30 2.6.2 Iron oxidizing bacteria ...... 30

2.7 Phage isolation ...... 31

2.7.1 Isolation with enrichment ...... 31 2.7.2 Isolation without enrichment ...... 33 2.7.3 Phage concentration ...... 34 2.7.4 Phage enumeration ...... 35 2.7.5 Phage propagation ...... 36

2.8 Bioinformatics studies ...... 37

Results and Discussion ...... 40

3.1 Overview of Oil Sands metagenomics data ...... 40 3.2 Bacterial isolation and characterization ...... 42 3.3 Bacterial growth kinetics ...... 47

3.3.1 Sulfur-oxidizing bacteria ...... 47 3.3.2 Iron-oxidizing bacteria ...... 51

3.4 Phage isolation ...... 54 3.5 Bioinformatics studies ...... 55

3.5.1 CRISPR search...... 55 3.5.2 Characteristics of the repeats ...... 65 3.5.3 Characteristics of the spacers ...... 72 3.5.4 Cas genes ...... 77

Conclusions ...... 85

4.1 Conclusions ...... 85 4.2 Limitations ...... 87 4.3 Suggestions for future research ...... 87

Literature Cited ...... 88 Appendix A ...... 108

List of Tables

Table 1.1. Latest classification of CRISPR-Cas systems assembled from the current literature. The nomenclature system divides them into four types and several subtypes. Cas 1 and 2 are highly conserved and have been bolded...... 19 Table 2.1. Components of media used in the isolation experiments (Atlas 2005, 2010). TM, S6, S1, S2 and IOM are media names. The units for each ingredient are in g/L...... 24 Table 2.2. Buffers used for phage extraction in this study...... 29 Table 3.1. Summary of the isolated bacteria and their similarity to the closest hits in NCBI.* ...... 43 Table 3.2. Results of direct BLAST comparison of 16SrRNA of IOM isolates...... 44 Table 3.3 Results of direct BLAST comparison of 16SrRNA of SOM isolates...... 44 Table 3.4. Kinetic rates determined for HTP and HTBN according to the change in pH, absorbance, sulfate, and thiosulfate concentration...... 50 Table 3.5. pH reduction and ferric iron production rates of A. ferrooxidans and A. ferrivorans in 30, 25 and 13ºC...... 53 Table 3.6. Summary of CRISPRs found in the 17 full genomes of ARD organisms probed. Unless labelled as archaea, the taxa are bacterial...... 56 Table 3.7. Summary the 17 full genomes of ARD organisms probed in which a CRISPR was not found (first column is the genus and the next columns in a row are different species)...... 57 Table 3.8. Hits of the spacers of Acidiphilium cryptum JF5 to the environmental viral metagenomics of a hydrocarbon-contaminated ditch in Germany. PI is pairwise identity and QC is query coverage ...... 62 Table 3.9. Identity percentage vs overlap percentage of spacer matches to viral metagenomics databases...... 65 Table 3.10. Signature Cas proteins in the NCBI database. The number of amino acids in the database has also been presented. The minimum bitscores to infer homology have been rounded up...... 78 Table 3.11. Assigned CRISPR-Cas Type/Subtypes of the bacteria/archaea under study. Second column shows the Cas genes present in the locus. If they are presented by

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dash (-) they are in order in the locus; when presented by comma the order was not determined because the (putative) Cas genes were in contigs. Signature genes are in red...... 79

Table A. 1. CRISPRs present in ARD microorganisms ...... 108 Table A. 2. Matches of inferred amino-acid spacer sequences from Acidianus hospitalis to the viral database. Query coverage (QC) is the percentage of query sequence covered by the hit considering internal gaps as positive. Pairwise identity (PI) is the percentage of pairwise residues that are identical in the alignment, excluding gap versus gap residues...... 125 Table A. 3. Matches of H. neapolitanus C2 spacers to viral database...... 128

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List of Figures

Figure 1.1. Summary of the CRISPR system. (From Amitai and Sorek 2016 with permission)...... 17 Figure 2.1. Schematic of the procedure for the isolation of bacteria ...... 25 Figure 2.2. Images of the assembled batch system for the isolation of bacteria in psychrophilic conditions. Top – the entire system bottom - sterilized sponges were used to sterilized the air before entering the cultures...... 27 Figure 2.3. General procedure for phage isolation with enrichment ...... 32 Figure 2.4. General procedure for phage isolation without enrichment ...... 34 Figure 3.1. The phylogenetic tree of acid producing bacteria/archaea present in the databases PDSYNTPWS and 2012TP5 using their complete or partial 16SrRNA data. The alignment was done using MAFFT and the tree was drawn with RAxML with a bootstrapping value of 100. Iron oxidizers are distinguished from sulfur oxidizers by an I in front of their name. Ferroplasma acidarmanus was chosen as the outgroup since it had the least similarity to other sequences. The names in red show the phyla, class or domain that the organisms are in. The circled names were isolated in this study...... 41 Figure 3.2. Images of Gram stains of the isolated bacteria. A: A. ferrooxidans (top left) B: A. ferrivorans (top right) C: H. neapolitanus (bottom left) D: Acidiphilium species (bottom right). Images were captured using a 100x objective...... 45 Figure 3.3 Images of streak plates of sulfur and iron oxidizing bacteria. I (upper left). Acidophilium sp. II (upper right): H. neapolitanus III (bottom left): A. ferrivorans IV (bottom right right): Halothiobacillus species ...... 46 Figure 3.4. Results of incubation of in HTBN at 30°C. Top: pH and absorbance (● pH and Absorbance). Bottom: sulfate and thiosulfate concentration (mM/lit). The dots present the average value of three replicates. The error bars represent one standard deviation...... 48 Figure 3.5. Summary of thiosulphate consumption and sulfate production rates calculated for HTBN and HTP from experimental data...... 50

Figure 3.6. Ferric iron concentration and pH of medium during the growth of ACFE (blue color) and ACFO (red color) over time. The symbols represent the average of three replicates and the error bars represent one standard deviation...... 51 Figure 3.7. Effect of temperature on Ferric iron production and pH change rates...... 53 Figure 3.8. Alignment of spacer 24 and 25 of Acidiphilium cryptum JF-5 to the same phage tail fiber protein...... 62 Figure 3.9. Palindromic sequences (PS) from the CRISPRS in the 17 straions of bacteria that contained CRISPRS. The sequences were extracted using the methods of Bikandi et al. (2004), curated and annotated manually...... 67 Figure 3.10. Summary of repeats found in the 17 full genomes that had CRISPRS. Multiple sequence alignment and sequence logo of repeats were drawn using MAFFT aligner. Possible conserved motifs are shown with CM in the consensus sequence. CM1 (in blue) is the GAAA motif. CM2 (in orange) is the GGG/CCC motif...... 68 Figure 3.11. Phylogenetic tree for repeats. The tree was drawn using FastTree with a resampling value of 1000. The repeats of the same species were colored the same. The repeat of CRISPR 3 of A. caldus ATCC 51756 was chosen as an outgroup as it had the lowest average similarity to all other repeats. The support values (SV) are shown as node labels in the tree with the larger font than substitution per site (SPS) as branch label. Anytime that there was a possibility of confusing SV with SPS the support values have been put into an oval. Every species has been colored the same...... 70 Figure 3.12. Neighbor joining tree drawn using Fastree for 3600 repeats published by Alkhnbashi et al. (2014) plus the ones from this study. The red arrows show bacterial repeats from this study and pink colors show Archaeal repeats from this study. [16-20: Leptospirillum sp. 22-27: Acidianus sp. 2-7: A. caldus, 28-29: Acidimicrobium ferrooxidans, 9-11: A. ferrooxidans, 36: Thiomonas sp. 1. HTBN] ...... 71 Figure 3.13. Spacers with high similarity across species and strains of the bacteria and archaea. The identical nucleotides are shown in green and differences in red...... 74 Figure 3.14. Multiple sequence alignment of Acidiphilium cryptum JF5 spacers using the Geneious MSA tool...... 75

Figure 3.15. Similarity of two spacers in two strains of A. caldus. The identical nucleotides are shown in green and different ones in red...... 76 Figure 3.16. The distribution of CRISPR systems’ types and subtypes in bacteria (A) and archaea (B) using all the signature genes present in UniprotKB...... 82

List of Abbreviations

 Abs: Absorbance  Ac JF5/SM1/ATCC: Acidiphilium cryptum JF5/SM1/ATCC  ACFE: Acidithiobacillus ferrivorans  ACFO: Acidithiobacillus ferrooxidans  ACP: Acidiphilium species  ARD: Acid rock drainage  ASOM: Acidophilic sulfur oxidizing microorganism  ATCC: American type culture collection  BLAST: Basic local alignment search tool  BLOSUM: Blocks substitution matrix  Cas: CRISPR-associated  CM: Conserved motif  CRISPRs: Clustered regularly interspaced short palindromic repeats  crRNA: CRISPR RNA  D: Downstream  DNA: Deoxyribonucleic acid  DNase: deoxyribonuclease  DR: Direct repeat  dsDNA: Double stranded DNA  DSMZ: Deutsche Sammlung von Mikroorganismen und Zellkulturen  HGT: Horizontal gene transfer  HTBN: Halothiobacillus neapolitanus  HTP: Halothiobacillus species  IOM: Iron oxidizing microorganism  kDa: Kilo Dalton  Kpa: Kilo Pascal  Lepto: Leptospirillum  MAFFT: Multiple alignment using fast Fourier transform  MetaCRAST: Metagenomic CRISPR reference-aided search tool

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 MFT: Mature fine tailings  ML: Maximum likelihood  MSA: Multiple sequence alignment  MWCO: Molecular weight cut off  NCBI: National Center for Biotechnology Information  nr: non-redundant  NSOM: Neutrophilic Sulfur Oxidizing microorganism  nt: nucleotide  PAM: Point accepted mutation  PAM: Protospacer associated motif  PBS: Phosphate buffered saline  PCR: Polymerase chain reaction  PEG: Polyethylene glycol  PES: Polyethersulfone  ePRB: Permeable reactive barriers  PS: Palindromic sequences  RAxML: Randomized axelerated maximum likelihood  RMA: Read match archive  RNA: Ribonucleic acid  rRNA: Ribosomal RNA  SOM: Sulfur oxidizing microorganisms  T-Coffee: Tree-based consistency objective function for alignment evaluation  TM: Thiobacillus medium  tracrRNAs: trans-activating crRNA  U: Upstream  YNP: Yellowstone National Park

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Acknowledgments

I would like to thank Prof. Deborah Roberts, who provided me with the opportunity to continue my studies at a prestigious university in Canada. She showed me that there are other things than the number of publications for being a scientist to be remembered.

I would like to thank Prof. Curtis Suttle also who accepted to be my co-supervisor and made me learn bioinformatics. I have been an interdisciplinary student for a long time but taking this much of information in the short time that I had, was challenging.

I would also like to thank Courtney Dean for her help on getting the project started when I arrived in Canada; Shelir Ebrahimi, Taylor Liu, and Nusrat Jahan Urmi who helped me with gathering some data, especially when I was in Vancouver campus and had not access to Prof.

Roberts lab. I would like to thank Whitney Bannick and Hau Nguyen, two undergraduate students, who helped me with running some experiments. I also would like to thank Amy Chan for her help in providing material and space in Vancouver campus for doing some of the experiments. I would like to thank Christopher Deeg and Marli Vlok who helped me with the work environment as much as they could. I would definitely like to thank technicians, Michelle Tofteland and Ryan Mandau that helped me with many things.

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Introduction

This introduction presents a review of the oil sands tailings, their disposal and the environmental problems and concerns they raise. This is followed by a discussion of acid rock drainage (ARD), the crucial role of microorganisms in the onset and exacerbation of ARD and the current treatment and prevention methods, their strengths and limitations. The key role of microorganisms in ARD leads to the discussion of phage therapy, including an introduction to phage and current uses of the technique to kill off selected pathogens in medicine and industry.

Afterward, the bacterial response and defense to phage attack is presented, this leads to the role of

CRISPRs (clustered regularly interspaced short palindromic repeats) and their importance as clear evidence for phage attack is explained. It is concluded that the study of CRISPRs will lead to the better understanding of phages that have the potential to attack the bacteria and can give insight into the possible locations for the isolation of lytic phage from the environment.

1.1 Oil sands tailings

Canada has vast oil reserves, however, more than 97% of these are in the form of oil sands.

This stretches over an area of Alberta more than 150,000 Km2, which is larger than the country of

England (Alberta 2016). Oil sands extraction, especially surface mining have raised serious environmental concerns (Alex et al. 2009, Holowenko et al. 2000, Kelly et al. 2010, van den

Heuvel et al. 2000). Concerns regarding greenhouse gas emissions and acid-producing gasses like sulfur dioxide and nitrogen oxides have long been noted and the companies have been trying to alleviate or prevent the problem (Alex et al. 2009, Holowenko et al. 2000, McLinden et al. 2015).

The oil sands are a highly viscous mixture of sand, clay, water and bitumen. On average,

12% of oil sands by total mass is bitumen. Most of the bitumen is deep in the ground and is extracted using in situ extraction. However, 20% of oil sands are extracted using surface mining

1 from open pit mines. In this method first the oil sands are crushed into smaller parts to further expose the bitumen, then hot water is added to create a slurry mixture and it is moved to an extraction plant where more hot water is added and most of the bitumen floats to the top and is collected. The product of extraction is known as froth that is around 60% bitumen, 30% water and

10% solids. The froth is then mixed with paraffinic solvent in the tailing solvent recovery unit that reduces viscosity and leads to the better separation of bitumen from clay and water. Bitumen can then be upgraded to lighter hydrocarbon molecules that are easier for refineries to process.

For every liter of bitumen produced, up to 3 liters of water is used. Up to one million cubic meters of tailings liquid is produced daily that contains water, sand, clays, polymers and leftover bitumen. A majority of the water is recycled, however, there is still significant amount of tailings to be dealt with. The tailings are deposited into vast tailings ponds. One storage facility of Syncrude oil sands contained 300 million cubic meters of oil sand tailings as of 2012 and it is increasing rapidly (Dobchuk et al. 2013, Kaminsky et al. 2009, Kuznetsov et al. 2015). Fine tailings and water have to be separated so they can be reclaimed. The water content of the tailing slurry is 45% to

55% and after a few years of natural precipitation of solids it increases to around 70%, the precipitated solids in that state are called MFT (Mature Fine Tailings). However, it can take decades for the complete separation of liquid and solids, and it poses serious problems for reclamation of the site and recycling of water. Creation of anaerobic conditions in these ponds increases the activity of methane and hydrogen sulfide producing bacteria and that in turn leads to the production of methane and hydrogen sulfide in oil sand tailing ponds that are known as greenhouse gasses and have been a major concern for some time. There have been several studies on the presence of the microorganisms engaged in the production of these gasses (Lai et al. 1996,

Penner and Foght 2010, Ramos-Padrón et al. 2010, Stasik et al. 2014). These concerns have led to the investigation of several techniques such as thermal dewatering, filtration, and centrifugation of

2 fine tailings, for faster dewatering of oil sand tailings to reduce the size and number of tailings ponds, thus preventing the formation of greenhouse gases (Kasperski 1992). The result is dewatered but wet MFT that must be disposed of.

Further thickening of these tailings for safe discharge to environment was done in a pilot scale by adding an anionic polyacrylamide flocculent (SNF A3338) that increases the settling capacity and decreases segregation potential leading to the fast deposition of dewatered tailings

(Masala et al. 2011). The ultimate goal would be to deposit the tailings on the surface to complete the dewatering process. These tailing have been shown to contain up to 13.4% pyrite (Kuznetsov et al. 2015). This raises concerns for the production of acid drainage from the matieral once the pyritic materials are exposed to air. A study by Kuznetsov et al. (2015a) showed that both untreated and polymer treated tailings have the potential to produce acidic drainage (acid rock drainage, ARD) and the rate of production depends on the amount of ferrous sulfide present in the tailings (Kuznetsov et al. 2015). Considering the significant scale of tailings production, this can lead to serious environmental damage in the near future as described below.

Dean at al. (2016) started microbiological studies on the tailings to isolate acid producing bacteria and they successfully isolated one autotrophic and several heterotrophic sulfur-oxidizing bacteria from the oil sands tailing. However, this is the first comprehensive study conducted for the isolation of autotrophic sulfur and iron oxidizing bacteria that are responsible for the onset and perpetuation of ARD.

1.2 Acid rock drainage and its effect

Acid rock drainage (ARD) (also known as acid mine drainage) has been one of the most important environmental concerns of the mining industry for several decades (Hoffert 1947,

Lottermoser 2010). For commercial exploitation of earth’s resources, the solids need to be broken

down to very fine sizes so they can be processed, consequently, this leads to an increase in surface

area exposed to humidity and air. As a result, the exposure of sulfide minerals to air and water

increases dramatically and the process of sulfide oxidation accelerates significantly (Lottermoser

2010). ARD is the result of biotic/abiotic oxidation of sulfide minerals when exposed to air and

water and contains high concentrations of sulfates and metals in low pH leachate (-3.5 to 4.5)

(Bates and Jackson 1996, Nordstrom et al. 2000). Once started, ARD can turn the surrounding

environment to a wasteland, destroying all the vegetation and killing all of the aquatic life.

Remediation of current metal and acid generating sites cost tens of billions of dollars in

North America and a report by the government of BC in 1995 estimated the liability of already

active ARD sites in Canada to be up to 5 billion dollars (Feasby and Tremblay 1995, Price and

Errington 1998a, Price and Errington 1998b). Another concerning aspect of ARD environments is

their longevity; there are sites that have been producing metal contaminated acidic leachate for

thousands of years and will continue to do so for the foreseeable future. For instance, an abandoned

mine in northern Saskatchewan is predicted to continue discharging contaminants for another 400

years, while a small mine in Ontario will likely produce acid and contaminants for up to 3500

years (Kalin 2001).

Oil sands tailings have high pyrite concentrations (up to 13.4%), and they are crushed to

fine sizes for the extraction of bitumen. As explained above an objective is to dewater the tailings

as soon as possible to limit the size of enormous ponds and prevent greenhouse gas emissions and

this in turn exposes them to air and tailings start undergoing ARD (Kuznetsov et al. 2015).

1.2.1 ARD reactions

Sulfide minerals are chemically stable in the absence of oxygen and water. When they are

exposed to these, they start oxidizing spontaneously using oxygen or ferric ion as the electron

4 acceptor (Johnson and Hallberg 2003). The common pathways for the production of acid from mine tailings are as follows:

These reactions can happen chemically (abiotic) and/or biologically (biotic). Thiosulfate is the product of reaction 1 and ferrous sulfate is the product of reaction 2. Both of these products are the main nutrients for several chemolithotrophic microorganisms present in ARD environments, and their oxidation (reactions 3 and 4) leads to the production of much higher amounts of acid (Jacobs et al. 2014, Johnson and Hallberg 2003). In ARD environments microbial activity accelerates acid formation up to 5 orders of magnitude, so biotic reactions are viewed as the most important factors in ARD generation (Singer and Stumm 1970). Singer and Stumm showed that Acidithiobacillus ferrooxidans increased the ferrous iron oxidation rate from 3 ×

10 3 × 10 . All in all, the significant increase in oxidation by biological intervention is undisputed (Nordstrom and Alpers 1999).

1.3 Microbial ecology of ARD

Since extreme conditions like very low pH and high metal concentrations exist in ARD environments, the microbial diversity is not as high as many other systems. However, depending on several factors, there still is a diverse and very distinctive microbial community that is well adapted to the harsh environment (Baker and Banfield 2003, Kuang et al. 2013). As expected, the

5 microbial community changes and its diversity decreases as the pH of the system moves from neutral to acidic (Korehi et al. 2014, Sun et al. 2015).

Prokaryotes are the most prevalent life in ARD environments. chemolithotrophic and mixotrophic bacteria and archaea from the genera Acidithiobacillus, Acidiphilium, Leptospirillum, and Ferroplasma spp. are the most important contributors to ARD (Baker and Banfield 2003,

Edwards et al. 2000, Harrison 1981, Jimenez-Castaneda et al. 2016). Since they use sulfur and iron as their primary nutrient and main energy source, they have a direct role in iron and sulfur oxidation and consequently in acid production. Heterotrophic bacteria are found in these sites but do not play a direct role in the production of ARD, they mainly live on the metabolites produced by chemolithotrophs. However, this removal of organic compounds by the heterotrophs, in a way decontaminates the environment from potential inhibition that some organic compounds have on strict chemolithotrophic microbes, consequently increasing their activity (Leduc et al. 2002, Liu et al. 2011a). Liu et al. studied the synergy between the chemolithoautotrophic bacterium

Acidithiobacillus ferrooxidans and the heterotrophic bacterium Acidiphilium acidophilum that are present in ARD environments; they showed that A. ferrooxidans was more efficient in a co- cultured environment in oxidizing iron than pure culture and A.acidophilum could also grow heterotrophically in the presence of A. ferrooxidans without the need for heterotrophic nutrients

(Liu et al. 2011b). These observations show that even though heterotrophs are not directly engaged in acid production, they have an effect on the extent and perpetuation of the phenomenon.

Microbial richness of ARD environments and the extent of the problem differs among environments and it depends on several factors including pH, oxygen concentration, and temperature (Méndez-García et al. 2014).

1.4 Treatment of ARD

There are a few technologies that can be used for the treatment of ARD. These are typically

classed as chemical or biological and can be either passive or active technologies. Stringent

environmental regulations in some cases has made integrated and combined treatment methods

attractive. In most of the cases, a combination of methods leads to better results and they have been

used in some full scale cases successfully (Feng et al. 2000, Ngwenya et al. 2006).

1.4.1 Chemical treatment

Chemical treatment of ARD has been practiced for around 100 years (1929, Leitch et al.

1930, Singh and Rawat 1985). The whole point of chemical treatment is to neutralize acidity and

precipitate metal ions to the extent that they meet environmental requirements. Limestone,

hydrated lime, pebble quicklime, soda ash, caustic soda (liquid and solid), and ammonia are 6

major chemical forms that have been used for this purpose. Technical and economic aspects

determine the chemical to be used for treatment (Jacobs et al. 2014). These chemical methods have

been used successfully for years, however, they produce copious amounts of iron-rich sludge (2-

4% solid content) that makes their disposal a burden, moreover the operating cost of the processes

are also high and they need constant attention (Johnson and Hallberg 2005).

High iron concentration is of major concern in ARD environments. Since current chemical

ARD treatments lead to a contaminated sludge with high iron concentration which can be

considered a secondary pollutant, the use of iron-oxidizing bacteria (IOB) to effectively remove

and even reuse iron has been documented (Hedrich and Johnson 2012, Rowe and Johnson 2008,

Wang and Zhou 2012). In this method, ferrous iron is first oxidized to the ferric iron using iron

oxidizing bacteria like A. ferrooxidans, Leptospirillum ferrooxidans, Ferrovum myxofaciens or

mixtures of these organisms that are generally immobilized on synthetic packings. Afterward

controlled chemical increase of the pH leads to the precipitation of ferric iron in the different forms

of schwertmannite that can be recovered and reused. This also decreases the sludge production

significantly (Hedrich and Johnson 2012, Rowe and Johnson 2008, Wang and Zhou 2012).

Continuous input of chemicals and nutrients and maintenance are common characteristics

the methods mentioned above that are also called “active methods”. Passive methods on the other

hand try to treat ARD with no chemical input and very little maintenance and operating costs

(Kleinmann et al. 1998). One of the most successful passive chemical ARD treatments is the

anoxic limestone drain system. Limestone is one of the cheapest options for increasing alkalinity

and pH of the acidic waters, however, it tends to get armored in the presence of ferric iron. To

overcome this barrier, they are operated in anoxic conditions underground where ferrous iron does

not convert to ferric iron. The absolute anaerobic conditions required are difficult to maintain

(Hedin et al. 1994, Kleinmann et al. 1998).

1.4.2 Biological treatment methods

Sulfate reducing bacteria (SRB) are mostly anaerobic bacteria that use sulfate as their final

electron acceptor and organics as electron donors. Use of these bacteria to treat ARD effluent leads

to a reduction of sulfate, increase in pH and precipitation of heavy metals (Luptakova and

Kusnierova 2005). Since ARD generally contains low concentrations of organic carbon, adding

organic substrate to support microbial growth and activity of SRB would be necessary and the

choice would be influenced by cost, availability, effectiveness and longevity of the organic

material (Luptakova and Kusnierova 2005, Waybrant et al. 2002). These electron donors play a

major part in sulfate reduction, and their effect is different in different ARD environments. For

instance, using organic acids as electron acceptors for the removal of high concentrations of sulfate

8 in acidic environments resulted in low-efficiency removal, but it lead to high-efficiency removal under circumneutral pH (Klein et al. 2014, Maree et al. 2004).

Anaerobic compost bioreactors and permeable reactive barriers (PRBs) are two of the passive biological methods used for the remediation of ARD. These systems are covered to accommodate a better environment for anaerobic iron and sulfide reducing bacteria that reduce iron and sulfate. They increase pH and precipitate metal contaminants (Johnson and Hallberg 2005,

Waybrant et al. 2002).

All in all, selection of the most suitable method for ARD prevention and remediation depends on several factors that have to be considered to achieve a long lasting results. These include; technical factors like “treated water quality requirements”, “raw water/waste composition and flow rate”, scale, location and accessibility of the project; operational factors like maintenance, logistics, automation, utility requirements; environmental factors like regulatory regulations, climate conditions; financial factors like capital, operation and maintenance costs.(Verburg et al.

2009).

1.5 Prevention of ARD

Considering that water, oxygen, sulfide minerals, bacteria, and iron are the contributors to

ARD, excluding at least one of them is the objective of prevention methods. Wet and dry physical barriers, bactericides, microencapsulation, electrochemical cover, and desulfurization are ARD prevention methods that have been documented to date: wet and dry physical barriers have been tested in some experimental and full-scale studies (Fytas et al. 2000, Simms et al. 2000). Wet physical barriers such as flooding of underground mines creates anoxic conditions and limits the oxygen influx, therefore decreasing the oxidation and consequently acidification and metal release

(Yanful and Orlandea 2000). However, the efficacy of wet barriers has been questioned since some

9 mines cannot be flooded, and there have been reports of oxidation in flooded mines. Moreover, this technique needs meticulous design and requires high maintenance that makes it costly and less feasible (Vigneault et al. 2001).

Dry barriers have been created using synthetic or organic material, soil and vegetation, plastic and polymer liners, wood waste, sludge from paper-mill or municipal sludge, and wood chips. They have been used as dry cover to limit tailings’ access to oxygen and/or water, however, they were either too expensive to implement in full scale or could prevent oxidation only for a short time (Evangelou 1996, Yanful and Orlandea 2000, Yanful et al. 1999).

Bactericides such as anionic surfactants, organic acids, and food preservatives have been used for ARD prevention and in most of the cases they have been very successful in significantly preventing ARD. However, it has been shown that they cause toxicity to natural microbial and aquatic life in the environment (Cserháti et al. 2002, Kleinmann and Erickson 1983, Liwarska-

Bizukojc et al. 2005). A method that will target specific bacteria would be a better approach for the prevention of ARD. One method that has been demonstrate to target specific bacteria is phage therapy

1.6 Phage therapy

Phages are viruses that have bacterial hosts and do not affect eukaryotic cells. They cannot reproduce on their own and need their hosts to produce progeny. They are an essential part of ecosystems and are seen as agents that control the numbers of specific bacterial populations. With current molecular genetic tools, researchers have been able to estimate the number of viruses in the environment. They have reached the conclusion that viruses exceed the number of host population by 10-100 fold. They are the most abundant biological elements of environment. It has also been shown that they play a significant role in the ecosystem (Suttle 2007).

The main objective of phage therapy is to take advantage of the activity of lytic phages and

their specificity in lysing a certain strain or even species to eradicate pathogenic or undesirable

bacteria without harming natural habitat and beneficial bacteria. After the pioneering work of

d’Herelle, Twort and McKinley (d'Herelle 1921, McKinley 1923, Twort 1915) who administered

phages to people with bacterial infections and cured them; the Pasteur institute in France continued

isolating and administrating phage for a range of pathogens like Pseudomonas, Staphylococcus,

Escherichia coli, and Serratia, up until at least 1974 when the use of antibiotics consumed the

market (Golkar et al. 2014). Current applications of phage therapy are discussed in section 1.7.2.

1.6.1 Bacteriophage life cycle

Before a phage can replicate inside the bacteria, it must attach to the bacterial surface and

inject its genetic material inside the bacteria. Afterward, according to the nature of the phage and

the state of the host it usually enters into one of the two cycles: lytic infection cycle or lysogenic

infection cycle. In a lytic cycle, once the virus injects the nucleic acid into the cell it directs the

infected bacterium into producing and assembling new viruses by using the bacteria’s own

machinery. After producing enough progeny inside the bacteria (usually more than 100) it instructs

the cell to produce enzymes including holins, lysozymes, endopeptidase and amidases to degrade

the membrane, which burst open the bacteria and release the new viruses. With new viruses at

hand, another round of infection starts until all the bacteria hosts have been infected and eradicated

(Díaz-Muñoz and Koskella 2014, Hanlon 2013).

In the lysogenic cycle, however, the phage does not kill the host cell right away but

incorporates its genetic material into the bacterial genome and passes it along into daughter cells.

The viral genome, in this case, is called prophage and these kind of phages are called temperate

phages. These phages can, under certain conditions like DNA damage, start a lytic cycle thus

killing the host cell. These phages are not proper candidates for phage therapy as they do not kill

the host right away (Hanlon 2013).

1.6.2 Industrial applications of phage therapy

After a hiatus in phage therapy research in the west because of antibiotic discovery, there

has been a resurgence of interest in its application in many industries as a smart antibacterial agent

and several companies have started investing in it (Ampliphi 1989, Kuchment 2011, Novolytics

2002, Phage-international 2004, Viridax 1998).

The unique mode of action of phages in comparison with bactericides gives them several

advantages. One of the most important advantages of phages is their specificity as they typically

infect a particular species and sometimes even specific strains within a species while leaving others

intact. This characteristic can be very useful in that they will not affect other microflora.

Bactericides have much wider range and they can be highly indiscriminate affecting useful and

pathogenic bacteria to the same extent, disturbing the natural habitat, as has been observed

previously in bactericidal prevention of ARD (Hanlon 2013, Kleinmann and Erickson 1983).

When using bactericides like antibiotics, the level has to be kept constant until the bacteria

disappears, as failing to do so can lead not only to failure in treatment but to the rise of resistant

species. On the contrary phages can produce more progeny (100 or more) after killing each bacteria

and continue to increase in number until all of the bacteria have been decimated (Hanlon 2013).

There have not been reports of adverse reactions or side effects of phage therapy to date (Housby

and Mann 2009). There are quite a few environments like fisheries, aquacultures, coral reefs,

wastewater bioreactors, that introducing antimicrobials which work indiscriminately against

bacteria is next to impossible (Rao B. and Lalitha 2015). Withey et al. (2005) were one of the first

to recommend using phage therapy for waste water treatment plant to eradicate specific pathogens

(Withey et al. 2005). Later, Periasamy and Sundaram (2013) removed 100% of a pathogen (even antibiotic resistant ones) in just 14 hours after phage dosing to hospital wastewater and as expected the number of phages increased exponentially (Periasamy and Sundaram 2013).

One well-stablished application of phage therapy is postharvest control of foodborne pathogens: the first phage product to get FDA approval was Listshield produced by Intralytix in

2006 for the control of the foodborne pathogen Listeria monocytogenes (Intralytix 1998). Since this time, several other companies have been able to get Food and Drug Administration or

European Medicines Agency approval for their products on human health, food safety, agriculture, and animal health (Micreos 2010a, b, Omnilytics 1954).

Another area that has seen successful application of phage therapy is for research dealing with coral reef diseases that are mostly caused by the increased temperature of seawater and water pollution, which are becoming widespread and lead to the death of the reef (Efrony et al. 2007,

Kuntz et al. 2005, Rosenberg and Ben‐Haim 2002). Efrony and collegues isolated bacteriophages that were capable of lysing two important pathogens responsible for widespread coral reef diseases and successfully implemented them in a controlled aquaria experiment (Efrony et al. 2007). Cohen and colleagues also isolated phages capable of lysing Vibrio coralliilyticus that is an important coral pathogen (Cohen et al. 2013).

Biofilm control has always been a challenge in food industry and medicine mostly because of extracellular polysaccharide substances that these microbial communities produce and act as barriers against antibacterial agents (Motlagh et al. 2016). Phage therapy has the same obstacle also; however some phage produce enzymes to hydrolyze the extracellular polysaccharide substances and some phages can genetically be modified to synthesize the enzymes (Azeredo and

Sutherland 2008). Continuous addition of phages have shown to reduce microbial attachment to

13 form biofilm by 40 to 60% showing the importance of phages in prevention methods (Goldman et al. 2009). The success of phage therapy in industrial scale still needs to be seen.

With respect to bacterial populations in ARD environments, Andersson and Banfiled

(2008) assembled viral, bacterial and archaeal genomes from two natural acidophilic biofilms of

ARD sites in Iron Mountain, California and showed that there is an active interaction between viruses and the bacteria/archaea community (Andersson and Banfield 2008). Belnap et al. (2011) detected a phage bloom in their study of low pH ARD environments using quantitative proteomic analysis and reached the conclusion that Leptospirillum group III has undergone lytic infection confirming an active viral bacterial interaction even in extreme environments.

The microbial population in any environment is expected to be much richer in circumneutral pH than in acidic pH and there would be high number of bacteria that can work concurrently to perform the same function. This makes the implementation of phage therapy in rich environments difficult since when the target organisms are destroyed others will rise to take their place. However, as the pH of the environment declines, the microbial diversity decreases. In this situation, killing off one bacteria or a strain or species using a phage or a cocktail of phages can significantly disturb the environment and it will be difficult for the limited microbial community to compensate (Korehi et al. 2014, Sun et al. 2015). Although no studies have demonstrated that phage therapy in ARD environments, it has been shown that there is an active viral population in these extreme environments (Andersson and Banfield 2008, Belnap et al. 2011,

Johnson et al. 1973); and one study has successfully isolated phage for Thiobacillus novellus

(Andersson and Banfield 2008, Belnap et al. 2011, Johnson et al. 1973). These studies suggest that phage therapy could be developed for an ARD system. Therefore, one of the objectives of this

study was to isolate the lytic phages active against pH reducing bacteria in oil sand tailings in order

to use them for phage therapy for the prevention of microbial induced ARD.

1.6.3 Bacterial defense against viral infection

Bacteria are well known to gain abilities to defend themselves against antimicrobial agents.

Bacterial/viral interactions have been occurring since the dawn of time and so it is only natural

that bacteria have developed defense mechanisms against viral attack. This section introduces the

commonly understood bacterial defense mechanisms as well as presenting a significant review of

the newly developed information regarding one bacterial defense system, clustered regularly

interspaced short palindromic repeats or CRISPRs.

CRISPRS are interesting not only as a bacterial defense mechanism against viruses but also

because they are a record of the lytic phage that the bacteria has been exposed to and can be used

as a diagnostic tool to source phage infections. No one to date has investigated the possible origin

of phages that might be able to attack ARD bacteria. The report of one lytic attack on an ARD

population and the isolation of one lytic phage in a separate study are encouraging, but not definite

evidence of widespread occurrence of phage in these environments. CRISPRs are the most

important evidence of active and continuous phage and bacterial interaction (Tyson and Banfield

2008). No one to date has investigated the relationship between different CRISPRs and their

components in ARD systems. Therefore, a thorough study was conducted to investigate these

aspects. We have started it with a discussion on bacterial defense to introduce methods like

CRISPRs that bacteria use to resist the phage infection to make the importance of CRISPRs clearer

for the reader.

1.6.3.1 Bacterial defense

The first step in phage infection is the attachment of the phage to receptors on the surface of the cell. The first strategy for bacteria to resist phage infection is “adsorption-reduction or inhibition”. In this case, bacteria prevent phage from attaching to the receptors by eliminating the receptor or by preventing contact between the receptor and the phage by hiding the receptors behind newly produced extracellular polymers or by modifying the receptor structure (Barrangou et al. 2007, Hyman and Abedon 2010, Lomeli-Ortega and Martinez-Diaz 2014). The second step in phage invasion is “host takeover”. “Restriction” is a strategy used by bacteria to block phage replication. In this case, bacteria use restriction endonucleases to cut and degrade the nucleic acid of phage at the time of its entry (Hyman and Abedon 2010, Martinez-Diaz and Hipolito-Morales

2013).

1.6.3.2 Clustered regularly interspaced palindromic repeats or CRISPRs

Clustered regularly interspaced short palindromic repeats or CRISPRs are repetitive

(palindromic or partially palindromic) viral DNA sequences named direct repeats (DRs) (21 to 47 bp) that appear in bacterial DNA interspaced by spacer sequences. The CRISPR array is flanked by a leading sequence that is about 100-500 bp long and is accompanied by CRISPR-associated genes (Cas) (Figure 1.1). CRISPRs are present in nearly all sequenced archaea, half of the sequenced bacteria and some sequenced viruses (Chénard et al. 2016, Jansen et al. 2002, Seed et al. 2013). Makarova and colleagues (2006) observed that the spacers in CRISPRs contained phage

DNA and suggested that this system worked as “the mechanism of defense against invading phages and plasmids” from this information. The hypothesis was later confirmed by several experiments

(Barrangou et al. 2007, Bolotin et al. 2005, Horvath et al. 2008, Makarova et al. 2006).

Figure 1.1. Summary of the CRISPR system. (From Amitai and Sorek 2016 with permission).

Figure 1.1 shows an overview of the mode of action of the CRISPR-Cas system.

Acquisition (adaptation) (Figure 1.1b) of spacer sequences occurs at the first stage of phage infection when the Cas1-Cas2 protein complex cuts a small part of the foreign DNA (protospacers), possibly from defective phages. The proto-spacer is recognized by 2 to 5 bp protospacer- associated motifs (PAMs) that are attached to the proto-spacers. Then it integrates the spacer into the CRISPR array and adds another repeat in the process. In the next step (expression and maturation) (Figure 1.1c), the whole CRISPR array is transcribed and then it is processed into

17 mature CRISPR RNAs (crRNA) each containing one spacer. They then make ribonucleoprotein

(RNP) complexes with Cas proteins. In the interference step (Figure 1.1d) the crRNA-CAS RNP complex recognizes the foreign DNA and uses nuclease protein or domain to cut and degrade the

DNA (Amitai and Sorek 2016, Hynes et al. 2014, Shah 2013, Sorek et al. 2013).

The evolution of CRISPR arrays is fast, as evidenced from metagenomics data from an acidophilic microbial biofilm at an ARD site; it was observed that after five months, the number of spacers had increased significantly and few of the spacers matched previously observed spacers

(Tyson and Banfield 2008). Insertion of spacers is because of a viral attack, therefore rapid insertion and deletion of spacers, shows a continuous interaction between viruses and microbial community (Pourcel et al. 2005, Tyson and Banfield 2008).

1.6.3.3 CRISPR-Cas classification

CRISPR systems are classified based on Cas genes. There are three major types of

CRISPR-Cas systems (I, II and III) that are further divided into ten subtypes (Makarova et al.

2011, Sorek et al. 2013). Each possesses their own proteins; however, Cas1 and Cas2 proteins are the most conserved (Table 1). These proteins are believed to be involved in the integration process during the adaptation stage. Even though the exact mechanism of integration is not clear, it has been shown that the leader sequence and the adjacent repeat are necessary for completion (Yosef et al. 2012).

All of the Type I CRISPR-Cas systems contain the Cas3 gene that has two domains, a phosphohydrolase domain and a helicase domain (Sinkunas et al. 2011). These domains work together to cleave and unwind dsDNA targets. Cas proteins 5 to 7 have been shown to be necessary for the production and retention of a stable crRNA (Brendel et al. 2014).

Type Subtype Gene organization I-A cas1→cas4→csa5→cas8→cas7→cas5→cas2→cas3→cas8→cas6a I-B cas6b→cas8→cas7→cas5→cas3→cas4→cas1→cas2 I-C cas3→cas5d→cas8→cas7→cas4→cas1→cas2 I I-D cas3→cas10→csc2→cas7→cas6d→cas4→cas1→cas2 I-E cas3→cse1→cse2→cas7→cas5→cas6f→cas1→cas2 I-F cas1→cas3→csy1→csy2→cas7→cas6e II-A cas9→cas1→cas2→csn2 II II-B cas9→cas1→cas2→cas4 III-A cas6→cas10→csm2→csm3→csm4→csm5→csm6→cas1→cas2 III III-B cmr1→cas10→cmr3→cmr5→cas6→cmr6→cas1→cas2 IV IV cas2→cas4→cas7→csf1→cas6

Type II systems are only found in bacteria. They have only 2 sub-types consisting of Cas9,

Cas1, and Cas2 followed by Csn2 (type II-A) or Cas4 (type II-B). The hallmark of this system is

Cas9 that encodes a large protein engaged in both the interference and crRNA biogenesis step

(expression and maturation). For the biogenesis of crRNA in type II CRISPRs, the trans-activating crRNA (tracrRNA) protein is necessary, which perfectly matches a specific part of tracrRNA. The

Cas9-tracrRNA-crRNA complex looks for the DNA sequence, which is both complementary to the specific crRNA in the complex and is followed by PAM (Table 1). Then, Cas9 cleaves both strands and the complex unbinds (Deltcheva et al. 2011, Sorek et al. 2013).

Type III systems are divided into two subtypes according to their accessory genes (Csm or

Cmr) (Table 1.1). RNA/DNA targeting with one unified complex (Cas10-Csm3) has been shown in type III-A systems, and that they can cleave complementary DNA strands using Cas10 of the

19 complex, and RNA using Csm3 of the complex. Thus, type III systems may cleave RNA viruses as well as messenger RNA of the target DNA viruses, leading to greater fitness against DNA viruses (Samai et al. 2015). However, acquiring a CRISPR system to gain immunity against RNA viruses whose mutation rate is thousands of times higher than dsDNA viruses needs a fast evolving or less stringent CRISPR system that has not been shown to occur. There are two other putative groups of CRISPR systems (IV and V) that have been identified by bioinformatics, but which have not been shown experimentally.

1.7 Objectives

There are three main objectives in this thesis:

1. To isolate as many chemolithotrophic sulfur and iron oxidizing bacteria as possible using

several media and in different temperatures to cover possible psychrophiles, psychrotrophs and

mesophiles that might be present in the oil sand tailings.

The hypothesis behind this objective is that we will be able to isolate some organisms that are involved in ARD using the methods and media developed in the literature that have been sucesfully used to isolate these organisms from other environments.

2. To perform growth experiments to find the temperature range and acid production rate of the

isolated bacteria in wide range of temperatures.

The hypothesis behind this objective is that the organisms we find will be tolerant to low temperature since they are isolated from tailings produced in a cold environment. The research question is what will their growth rates be at the different temperatures tested.

3. To use several phage isolation methods to isolate lytic phages for the bacteria isolated in stage

one.

The hypothesis behind this objective is that there should be phage capable of infecting the bacteria present in the samples. The hypothesis is tempered by the fact that the phage may be in very low number, when the bacteria are not active as with the tailings that we received.

4. To examine sequence databases of known sulfur and iron oxidizing microorganisms to

determine if there are CRISPRs present.

The research question behind this objective are one. is there evidence of significant phage infection of the bacteria in question; and two. How widespread are the phage infections of acid producing bacteria.

This thesis documents efforts to achieve these objectives: Chapter 2 covers the “Materials and Methods” used in bacterial and phage isolation and in the bioinformatics section. Chapter 3 covers the results achieved in pursuit of all of the objectives and their respective discussions.

Chapter 4 covers the conclusions that can be drawn from the work and recommendation of possible future work.

Materials and Methods

This chapter documents the materials and experimental and bioinformatics methods that were used to carry out the objectives of the study. The experimental research was performed mostly in the Biological Solutions Laboratory on UBC’s Okanagan campus. Some experimental work was completed in the laboratory of Dr. Curtis Suttle on UBC’s Vancouver campus. The bioinformatics study was completed in the laboratory of Dr. Curtis Suttle on UBC’s Vancouver campus.

2.1 Tailings samples

Our tailings were provided by Total Exploration and Production Canada (TEPCA) from the pilot studies that were conducted at the Muskeg river mine site in Northern Alberta. The full description of the pilot study can be found in (Masala et al. 2011).

Although the study used multiple cells the study team determined that samples from cell 1 upstream and downstream (U1 and D1 that were raw) and cell 5 (U5 and D5 that were thickened) would be representative of all of the raw and thickened replicates. The term raw refers to the tailings solids separated using the separation process without the aid of a thickener. The term thickened refers to those solids that were obtained when a polymer was added to the solids separation process. Upstream refers to the top of the cell in relation to the natural slope and water flow in the site. Downstream would be the point at which the water would leave the cell. None of the samples had become acidic on site. The upstream samples were expected to have less microbial activity (acid production) than the downstream samples. The samples were stored at 4°C in sealed buckets. Over the two-year period of this study, (starting 1 year after the samples were received) the samples began acidifying in the sealed buckets.

2.2 Microbial media

The bacterial isolation was done using 5 different media, Thiobacilli medium (TM) (Atlas

2010) and S6 (Atlas 2010) for the isolation of neutrophilic sulfur oxidizing bacteria (NSOB), S1

(Atlas 2010) and S2 (Atlas 2010) for the isolation of acidophilic sulfur oxidizing bacteria (ASOB) and Iron Oxidizing Media (IOM) for the isolation of iron oxidizing bacteria (Table 2.1). TM and

S6 media had almost the same components. The only difference was large amount of potassium phosphate mono-basic in S6 medium that provided more K and increased the buffering capacity of S6 significantly. S1 medium, however was significantly different as it lacked sodium phosphate dibasic, ferric chloride and ammonium chloride. The media were made in either liquid form (no agar) in flasks or bottles or as solid form (with agar or agarose) in Petri dishes.

Plates for phage isolation were made similar to the plates used for bacterial isolation; however, 1, 5 or 10 mM of CaCl2 (or MgCl2) was added as the cofactor needed for phage attachment. Filter sterilized CaCl2 was added to the whole medium after it cooled following autoclaving.

For the purpose of precipitation and concentration of the phage, a mixture of polyethylene glycol 8000 (PEG 8000) and NaCl to the final concentration of 3, 5 and 10% and 0.6% respectively was used. Samples were centrifuged in a benchtop Centrifuge (Sorvall Legend XTR) or a microcentrifuge (Sorvall Legend Micro 21) and in some cases Viva Spin 10/30 kDa MWCO spin tubes were used to concentrate the phage.

Table 2.1. Components of media used in the isolation experiments (Atlas 2005, 2010). TM, S6, S1, S2 and IOM are media names. The units for each ingredient are in g/L.

Media TM S6 S1 S2 IOM Components 5 5 Na2S2O3 10 10 (or 10 g (or 10 g ----- Sulfur) Sulfur) KH2PO4.7H2O 1.80 11.80 3 3 0.5 (NH4)2SO4 0.10 0.10 0.10 0.20 0.5 CaCl2.2H2O 0.03 0.03 0.10 0.30 ----- Na2HPO4.7H2O 1.20 1.20 ------FeCl3 0.02 0.02 ----- 0.02 ----- MgCl2.6H2O 0.14 0.10 0.10 0.50 0.5 MnCl2 0.02 0.02 ----- 0.02 ----- FeSO4.7H2O ------30 Bacteriological grade agar 14 14 14 14 4 (if necessary) Agarose 7 7 7 7 2 (if necessary)

2.3 Bacterial isolation

Autotrophic bacterial isolation was done using five different media (Table 2.1) and at three different temperatures 7, 13 and 25°C (15 combinations). The media were chosen to represent the range of media that are used in the literature to grow these organisms. The temperatures were chosen to represent the minimum (4°C) median 13°C and maximum (25°C) temperatures expected in northern Alberta. Although the sediment may freeze in the winter producing temperatures below

4°C microbial growth is not expected in frozen material so lower temperatures were not attempted.

The isolations were performed with inoculum from all of the tailings samples including 1D, 1U,

5D, 5Uas outlined in Figure 2.1 from raw and thickened tailings. A new inoculation was carried out every time the pH of neutrophiles decreased from 7 to around 4, and the pH of acidophiles including both iron and sulfur oxidizers decreased from 4 to around 2.

Figure 2.1. Schematic of the procedure for the isolation of bacteria

To account for the possible contribution of chemical oxidation to the decrease in the pH during the period of isolation, the same procedure (Figure 2.1) was performed with sterilized tailings. The tailings were sterilized in an autoclave (Getinge) for 1 hour at 120°C and in 100 Kpa.

Sterilization was repeated three times on three consecutive days to ensure complete sterilization.

The change in chemical composition of the samples after sterilization was not determined.

As shown in Figure 2.1 the medium used for the first round of isolation was diluted 10 times to prevent nutrient shock. A sample of 100 g of tailings was mixed with 200 ml of the

25 appropriate medium (1/10 X), the pH was adjusted to 7 or 4 depending on the pH of the mixture and the desired result. It was shaken at 150 rpm at either 25, 13°C. The first two rounds of isolation at 4°C were performed in a 4°C walk-in using an aquarium pump to provide aeration through sterile tubing as shown in Figure 2.2. Subsequent rounds were incubated aerated using a table top shaker (120 rpm) in the walk in fridge.

After the pH of the cultures decreased to around 5 or 3 depending on the initial pH, 50 ml of the culture was mixed with 200 ml of a new medium and it was incubated as above until the desired decrease in pH was achieved. The same procedure was repeated twice, each time decreasing the transferred inoculum with 20 and 10 ml of previous culture added into 200 ml of fresh medium. In the last round of this procedure no tailings solids were distinguishable in the culture. At this point, streak plates were performed to pick individual colonies, followed by dilution to extinction or another streak plate. Since there were reports that acidophilic sulfur oxidizers and some iron oxidizers do not grow well on plates (de Bruyn et al. 1990), the procedure for the isolation of these bacteria consisted mainly of dilution to extinction. Streak plates for both iron and sulphur oxidizers were done when possible.

After choosing individual colonies from respected plates, dilution to extinction was done on all of the individual colonies and another round of streak plates was performed to show the purity of the cultures. In the cases where streak plates were not performed, the dilution to extinction was done twice to make sure that a pure culture was achieved before DNA extraction.

Figure 2.2. Images of the assembled batch system for the isolation of bacteria in psychrophilic conditions. Top – the entire system bottom - sterilized sponges were used to sterilized the air before entering the cultures.

2.4 Bacterial characterization

The pure cultures were characterized by performing Gram staining and DNA isolation.

Gram staining was carried out using the typical procedure (Bartholomew and Mittwer 1952).

Gram’s stains were observed using Zeiss Axioimager light microscope (100x) and motility was observed using the same microscope in phase contrast mode.

The DNA of neutrophilic sulphur oxidizing microorganisms (NSOM) was extracted using a Wizard® Genomic DNA Purification Kit as per manufacturer’s instruction. DNA of acidophilic sulphur oxidizing microorganisms (ASOM) and iron oxidizing microorganisms (IOM) was extracted using a Powersoil DNA Isolation Kit as per manufacturer’s instruction. A GE health care

Illustra GFX PCR DNA and gel band purification kit was used to purify the DNA product for sequencing.

The sequences of the 16SrRNA genes were used for identification of bacterial strains. After confirming the presence of pure DNA products following PCR amplification and spectrophotometry the product was sent for sequencing to the DNA sequencing service lab in

UBCO Fragment Analysis and DNA Sequencing Services center. The DNA was sequenced using

ABI 3130xl Genetic Analyzer with the ABI BigDye v3.1 Terminator chemistry (Applied

Biosystems, California, USA).

The primer used for PCR amplification of 16S rRNA was the universal bacterial 16S primer (Forward (D88 position 7-27): AGA GTT TGA TCC TGG CTC AG, Reverse: (E94 postion

1525-254) GAA GGA GGT GWT CCA RCC GC) (Paster et al. 2001). The amplification started with an initial denaturation at 94°C for 3 min, followed by 30 cycles of, denaturation at 94°C for

1 min, annealing at 58°C for 1min, and elongation at 72°C for 1 min, and a final extension step was performed at 72 °C for 10 min.

Comparison with known 16SrRNA sequences was done using BLASTn (Basic Local

Alignment Search Tool) (Altschul et al. 1990) on the NCBI Server (NCBI 2016). Similarities of

98 to 100 percent were considered as the same species. The commonly used cutoffs of 98 and above percent identity were considered the same species, 95 to 98 percent identity were considered as the same genus, and less than 95% as unknown.

2.5 Phage isolation

As seen in Table 2.2., four elution buffers (Table 2.2) were used for the extraction of phage from the tailings. These buffers were selected because they are commonly used in other phage isolation studies (Martha and Clokie 2008, Williamson et al. 2005, Williamson et al. 2003).

Table 2.2. Buffers used for phage extraction in this study.

Elution buffer Concentration Components (per liter) 5 g potassium citrate, 0.72 g Na HPO 7H O, Potassium Citrate buffer 1% 2 4 2 0.12 g KH2PO4, Adjust pH to 7 Sodium Pyrophosphate 10mM 4.46 g Na4P2O7 10H2O Phosphate Buffered 8g of NaCl, 0.2g of KCl, 1.44 g of Na2HPO4, 1X Saline (PBS Buffer) 0.24g of KH2PO4 , adjust pH to 7.4 For 10%, 100 g of powdered beef extract, 13.4 g 10% Beef Extract I of Na2HPO4, and 1.2 g of citric acid, adjusted (+ 5% and 1%) pH to 9 10% Beef Extract II Same as above, however adjusted pH to 7 (+ 5% and 1%)

2.6 Growth and acid production kinetics

The growth and acid production rate of four of the isolates at 6 different temperatures (7,

12, 25, 30, 37, 40°C) were determined. The temperature range was selected to provide data in the range of temperatures that the organisms would be exposed to which is from freezing to around

25°C. The lowest temperature (7°C) was chosen over 4°C due to the already observed very slow growth rate at 4°C. The temperatures of 12 and 25°C were representative of median and maximum temperatures for northern Alberta. Temperatures of 37 and 40°C were also tested to explore the maximum growth temperature of these organisms.

2.6.1 Sulfur oxidizing bacteria

The kinetics were performed for Halothiobacillus neapolitanus (HTBN), Halothiobacillus

species (HTP) as the two sulfur oxidizing bacteria, isolated from the tailings. All of the

experiments were done in triplicate.

During these experiments, both HTP and HTBN were grown in 6S medium and thiosulfate

was used as the main electron donor. The turbidity was measured using a spectrophotometer at

600 nm wavelength using un-inoculated medium as the blank. As these bacteria grow, they use

thiosulfate and produces sulfuric acid. The concentration of thiosulfate and sulfuric acid were

measured using ion chromatography (Dionex ICS 2100, using AN143 processing method). The

decrease in the pH as the result of sulfuric acid production was measured using Orion 5 star

multimeter pH meter.

2.6.2 Iron oxidizing bacteria

Growth experiments were performed on Acidithiobacillus ferrooxidans (ACFO),

Acidithiobacillus ferrivorans (ACFE) as the two autotrophic, Gram negative, iron oxidizing

bacteria which were isolated from the tailings. All of the experiments were done in triplicate.

During growth experiments both of the bacteria were grown in/on IOM medium. The initial pH

was adjusted to 3. Ferrous sulfate was used as the main electron donor in this medium.

Bacterial growth is directly related to the oxidation of ferrous to ferric iron. Ferrous and

ferric concentrations were determined using a colorimetric method (Karamanev et al. 2002). A

sample (0.1 ml) of the culture was mixed with 5 ml of 10% sulfosalicylic acid that lead to the

production of a red complex of ferric ion and the acid; after the addition of 95 ml of type one water

(resistivity of more than 18 m at 25C) the absorbance was measured at 500 nm and it was

proportionate to ferric iron concentration. Ammonium hydroxide (5 ml of 25%) was added to the

mixture to produce a yellow complex with the iron, the absorbance was measured at 425 nm and

it was proportionate to the total iron. The concentration of ferrous iron was calculated as the

difference between total iron and ferric iron.

2.7 Phage isolation

Phage isolation was attempted using both Acidithiobacillus ferrooxidans [ACFO] and

Halothiobacillus neapolitanus [HTBN] immediately after the first round of successful isolation at

25°C. All of the experiments were done in triplicate. All tailing samples (5D, 5U, 1D, 1U) were

used for the isolation of phage.

2.7.1 Isolation with enrichment

In this method the pure bacterial cultures (HTBN, Acidithiobacillus ferrooxidans) were

used to enrich the target phage. Figure 2.3 presents a summary of the phage isolation methods.

Initially one gram of the tailings (dried or wet) was added to a sterile 15 ml centrifuge tube, then

9 ml of medium specific to the target microorganism was added. In subsequent attempts the amount

of tailings was increased to 500 gram in attempts to concentrate phage with polyethylene glycol

and the volume of all the other components were changed accordingly. Since some references

recommend that phage isolation the use of overnight dried soil, both overnight dried and fresh

tailings were used (Martha and Clokie 2008).

Since the pH of the tailings was already lower than 5, in some attempts for the isolation of

phage for HTBN as the neutrophilic bacteria, the pH of the mixture of tailings and media was

increased to around seven incrementally in a period of one to two days and then the phage isolation

was carried out.

Figure 2.3. General procedure for phage isolation with enrichment

The samples were incubated at room temperature for 2 hours to allow free phage to be

suspended in the medium. The samples were inverted frequently during the incubation period

to increase the disruption of particulate material and to distribute the phage throughout the

solution. Some references recommend gentle inversion for phage suspension, while others used

vigorous shaking and even sonication for successful phage isolation (Clokie and Kropinski

2009, Williamson et al. 2005, Williamson et al. 2003). Both vigorous and gentle shaking were

used in this study.

The tailings were then separated by centrifugation at 1000g for 5 min. Then 6 ml of the

supernatant was removed and placed in a sterile 15 ml centrifuge tube and inoculated with 0.2

ml of the culture of bacterium in the middle of log phase (pH of around 4 for HTBN and around

2.5 for ACFO was considered as the middle of log phase).

This mixture was then incubated for at least 24 hours with shaking at 25°C to allow the

growth of the bacterium and specific phage enrichment. After enrichment, the mixture was

again centrifuged at 1000×g for 10 min and then the supernatant filtered using 0.22 µm pore-

size PES Millipore syringe filter. Afterwards, the permeate was placed in 4°C for storage

before enumeration as described in section 2.6.4.

2.7.2 Isolation without enrichment

Since the first method did not provide successful isolation of lytic phage and to be thorough in

our testing a second methods was attempted. In this method the tailings samples were used directly,

without the bacterial enrichment step. A tailings sample (5 grams) was placed in a 50 ml conical

centrifuge tube and 15 ml extraction buffer was added (Table 3) and it was shaken for 30, 60 or

120 mins. After incubation, the soil buffer mixture was centrifuged (3000g) for 30 min at 4°C.

After carefully removing the supernatant and filtering through a 0.22μm pore-size (PES, Millipore,

Corp.) syringe filter, then the enumeration step was performed on the eluent.

Figure 2.4. General procedure for phage isolation without enrichment

2.7.3 Phage concentration

Polyethylene glycol precipitation of phages is a two-phase separation method that works well

with both large and small phages, and is amenable to larger volumes (up to a few liters). It also

results in pellets that are easier to re-suspend (Colombet and Sime-Ngando 2012, Yamamoto et al.

1970).

Polyethylene glycol 8000 and NaCl were added to 500 mL of phage suspension obtained from

100 g of tailings to final concentrations of 10 and 0.6%, respectively (500 ml changed according

to the amount of tailings chosen). This mixture was incubated at 4°C in the dark for 10 hours to 1

week to observe haziness or viral precipitation. According to personal communication with Prof.

David Oppenheimer from the Biology Department of University of Florida, observing haziness or

precipitation is not necessary for successful concentration. and there still can be considerable

phage present and separable by centrifugation. Therefore, all of the following were done after

every incubation regardless of observation of haziness, in the meanwhile another sample was

prepared with longer incubation time. At the end of incubations, centrifugation was done for the

whole solution in 24000 x g for at least ten minutes.

2.7.4 Phage enumeration

Overall three enumeration methods were used to enumerate lytic phage in the preparations

form the isolation methods described above: 1) the MPN method, 2) the direct plating plaque assay

and 3) the small drop plaque assay. In each of these assays, 1, 5 or 10 mM of Ca2+ was added to

the media as a cofactor to aid in viral attachment to the host as recommended by (Martha and

Clokie 2008).

In the enumeration of phages using MPN method, the bacteria were grown to its log phase

and ten-fold serial dilutions of the phage isolate solution were prepared. A total of 10 tubes per

phage were prepared and 100 µl of the bacterial culture was added to every tube. Then 100 µl of

appropriate phage dilution was added to each tube. The phage/bacterial culture mixture was shaken

for 10 min then 600 µl of fresh media was added to every tube and it was shaken at 25°C with

continuous monitoring for lysis using spectrophotometer.

In the enumeration of phages using the direct plating plaque assay, the plates were made with

added Ca2+ and 8 dilution tubes for each phage preparation were considered, then 450 µl of fresh

media (+ Ca2+) was added to every tube. Fifty microliter of undiluted phage was added to the first

tube, mixed by pipetting at least twice, then 50 µl of the previous one was added to the next one.

One hundred microliter of the bacterium in its log phase was added to every tube and the mixture

was shaken gently at 25°C for 20 min for phage attachment. After the incubation 200 µl of every

mixture was spread on the respected plate (-1 to -8), and allowed to dry for 30 min in a biosafety

cabinet and incubated at 25°C to observe the plaques.

The enumeration of phages by small drop plaque assay is less time consuming but it is not as

precise. The preparation is practically the same as direct plating plaque assay; however instead of

adding 200 µl on the whole plate, 20 µl was added as droplets on the plate and all 8 dilutions were

applied to one plate. So every plate had all the dilutions as drops on it. They were incubated at

25°C to observe the plaques.

2.7.5 Phage propagation

In order to ensure that there were significant phage to enumerate, two methods were used to

increase the number of phage in the samples by propagation: In the propagation of phage in liquid

medium, 100 μl to 1000 μl of the host culture in the middle of log phase was added to 5 ml of fresh

medium (with Ca2+ in different concentrations) and incubated for about 30 min. At this time, 100μl

to 1000μl of highest concentration available phage lysate was added and the solution was incubated

in the shaker for the lysis to occur. Different concentrations of phage/media/bacterial culture were

36 used to achieve lysis. However, the pH was always adjusted to the optimized pH for the growth of the bacteria.

In an attempt to increase the absorption of phage to the bacteria, the bacteria were concentrated before combining with phage (as recommended by Prof. David Oppenheimer). For this purpose,

1 ml of culture in its log phase was added to a micro centrifuge tube. It was concentrated by centrifugation for 2 min in 20,000 g, then the supernatant was discarded and pellets were re- suspended in 50 µl of fresh medium. Phages were added and the mixture was incubated for 10-20 minutes at 25°C, then 1-3 ml of media was added (the final volume was equal to or a little bit more than the initial volume of bacterial culture in its log phase) and it was incubated to achieve phage propagation.

2.8 Bioinformatics studies

The failure to isolate lytic phage targeting the oil sands isolates lead to the development of objective 4, the examination of the current full length sequences of IOM and SOM from the literature to determine if evidence of phage infection could be documented. The NCBI database included seventeen full genome sequences for bacteria and archaea believed to be involved in

ARD. All of these full genome sequences, no matter the original source, were screened for

CRISPRs using “CRISPRfinder”, an online program developed by Grissa et al. (2007b) of Paris

University, and confirmed using the CRISPR Recognition Tool ver.1.1 (Bland et al. 2007, Grissa et al. 2007b). The criteria used to extract the CRISPRs were spacer and direct repeat (DR) lengths between 19 and 100 bp, with one nucleotide mismatch allowed between DRs (Grissa et al. 2007b).

MetaCRAST (Moller and Liang 2016) is another tool available for extracting CRISPR arrays from metagenomics data, but the software was not available in time for this study.

BLASTn (NCBI 2016) was used to compare spacers identified using the CRISPR software with the non-redundant (nr) bacterial-archaeal and viral databases to determine if these spacers can be idenitified with other organisms and infections.. The default nucleotide BLAST search will not lead to any results for spacers, because with an average nucleotide (nt) length of 35 ± 8 and 11 ±

3 for the translated amino acids, the e-value is too stringent and word size is too large for such short sequences. The default nt search recommended by NCBI is a word size of 7, an e-value of

1000, and the filter setting off. For amino acids the recommended values are a word size of 2 with the filter off, an e-value of 20,000, compositional based statistics set to off, and the score matrix changed to PAM30 from BLOSUM62 (Boutros 2005, Madden 2013). The word size for nucleotide searches was decreased to 4 in this study to be able to concentrate on the overall similarity of the sequences and have allow hand curation if necessary.

In another attempt to find better matches the database size was decreased, by restricting searches to “phage OR bacteriophage” in the NCBI nt database and limiting the results to viral species, then all of the results were saved as FASTA files (21842 entries). The term “virus” was also searched to capture archaeal virus sequences, then most viruses of medical significance were excluded. This search recovered 35316 sequences; those that met the criteria of at least 90% identity over 90% of the sequence were selected and analyzed.

The evolutionary relationship among microbial taxa active (directly or indirectly engaged in lowering the pH of the environment) in ARD environments was inferred by phylogenetic analysis of their 16Sr-RNA sequences. Sequences were aligned using MAFFT (Multiple

Alignment using Fast Fourier Transform) (Katoh and Standley 2013) and the tree was drawn using

RAxML with a bootstrapping value of 100 to assess confidence (Katoh and Standley 2013,

Stamatakis 2014).

Geneious (Kearse et al 2012), MAFFT (Katoh and Standley 2013), T-Coffee ((Notredame et al. 2000), and ClustalW (Thomson et al. 1994) were used to align the CRISPR repeats and spacers. Then RAxML (Liu et al. 2011c) was used to determine the likelihood values and the alignment with the maximum likelihood score (ML score) closest to 0 was chosen as the best one.

The alignments were also curated manually using the conserved regions and biological functions

(Katoh et al. 2002, Kearse et al. 2012, Larkin et al. 2007, Notredame et al. 2000, Stamatakis 2014)

Geneious (Kearse et al. 2012) was also used to generate the heat maps for the multiple alignments and to produce the sequence logo using the Geneious multiple seuqnce alignmnet MSA tool, imported from the standalone tool used in Linux-based systems. The palindromic sequences of repeats were extracted using “Palindromic sequences finder” (Bikandi 2016).

To compare spacer sequences with viral and bacterial metagenomic data, the standalone

BLASTn program and BreezyGUI interface on the Bugaboo server in Westgrid (Computer

Canada) was used. Matches to the spacers were chosen using “Blastgrabber” version 2 (Neumann et al. 2014). The correct strand of the repeats that is used in crRNA encoding was determined using

CRISPRstrand (Alkhnbashi et al. 2014, Lange et al. 2013). CRISPRstrand finds the orientation of repeats using an advanced machine-learning approach (Alkhnbashi et al. 2014).

An extensive search for Cas proteins in these microorganisms was done using the 38290 proteins in the refined and annotated CRISPR database downloaded from NCBI on 8 June 2016.

To achieve more precise results, all of the Cas genes were extracted and used as a BLAST database to search for missed sequences and remove spurious results. Therefore, the BLASTx search was done several times on different databases ranging in size from 38290 to four protein sequences

(Csf1).

Results and Discussion

This chapter has been divided into four sections; 1) Bacterial isolation presents the results for the isolation of bacteria from oil sand tailings; 2). Growth kinetics presents the growth and acid production kinetics of isolated bacteria, 3) phage isolation discusses the results of lytic phage isolation in this study, and 4) bioinformatics presents the genetics of the bacteria and the relationship between bacteria/archaea and their phage embedded into the CRISPRs present in the bacteria/archaea.

3.1 Overview of Oil Sands metagenomics data

The first objective of the thesis was to isolate as many organisms that are associated with

ARD as possible. An initial investigation of metagenomic data gathered from the literature was performed to determine if there is any evidence of the presence of organisms that are typically associated with ARD in these environments. An et al. (2013a), Ramos-Padrón et al. (2010) performed metagenomics studies on oil sands samples but examined the data concentrating on oil degradation and methane production rather than organisms that are associated with ARD. Two of the databases provided by studies “Syncrude tailing pond surface water” (PDSYNTPWS) and

“Suncor tailing pond 5 samples from 5mbs” (2012TP5) were pooled together from the RMA file provided by the study (An et al. 2013). Sequences corresponding with known sulphur and iron oxidizing microorganisms were extracted from the database and a phylogenetic tree presenting the organisms is presented in Figure 3.1. Sequences of several archaeal and bacterial sulphur and iron oxidizing organisms from different phyla of bacteria including Gamma, Beta, Alpha, Epsilon and

Zeta proteobacteria, Chlorobia, Nitrospira, Actinobacteria and also Acidithiobacillia.were found suggesting that attempts to isolate ARD organisms from the tailings samples should be possible.

Figure 3.1. The phylogenetic tree of acid producing bacteria/archaea present in the databases PDSYNTPWS and 2012TP5 using their complete or partial 16SrRNA data. The alignment was done using MAFFT and the tree was drawn with RAxML with a bootstrapping value of 100. Iron oxidizers are distinguished from sulfur oxidizers by an I in front of their name. Ferroplasma acidarmanus was chosen as the outgroup since it had the least similarity to other sequences. The names in red show the phyla, class or domain that the organisms are in. The circled names were isolated in this study.

3.2 Bacterial isolation and characterization

The procedures resulted in the isolation of 20 pure cultures presented in Table 3.1.

Analysis of 16SrRNA results revealed that the 20 isolates represent five microorganisms.

Similarities of 98 to 100 percent were considered as the same species, 95 to 98 percent were considered as the same genus and less than 95% were marked as unknown. Halothiobacillus neapolitanus (HTBN), and Halothiobacillus species (HTP) were identified as the two neutrophilic sulfur-oxidizing bacteria. Acidiphilium species (ACP) was recognized as the acidophilic sulfur- oxidizing bacteria. Acidithiobacillus ferrooxidans (ACFO) and Acidithiobacillus ferrivorans

(ACFE) were identified as two acidophilic iron-oxidizing bacteria (Table 3.1). Table 3.2 presents the 16SrRNA comparison of the IOM isolates that was used to determine that they represented two microorganisms to the species level. Table 3.3 presents the comparisons of the SOM isolates showing that they also represent two species. All of the isolated bacteria could grow in 4, 13 and

25°C temperatures.

Figure 3.3 shows that all of the isolated bacteria were distinguished as Gram negative. They were small, rod-shaped and roughly 1 to 1.2 µm in size and motile. Streak plates were performed with all of the five isolates to determined their phenotypic growth characteristics on solid media.

Figure 3.4 shows that both HTBN and HTP have creamy, opaque and smooth colonies. ACP possessed white, opaque and smooth colonies but much smaller than the ones from HTBN or HTP.

ACFO and ACFE produced orange but vague colonies, and the growth was distinguishable by the orange color resulting from iron oxidation at the beginning.

Table 3.1. Summary of the isolated bacteria and their similarity to the closest hits in NCBI.* Query No. Most closely Base E- % Name Accession Coverage of isolates related hit pairs Value identity (%) 1 (13C) IOT13 A. ferrooxidans KJ944318 639 99 0.0 99 18 (25C) 2 IOT4 A. ferrivorans LN650699 634 99 0.0 99 (4C) 14 (25C) IOR13 A. ferrivorans LN650699 627 99 0.0 99 6 (13C) 4 IOR4 A. ferrivorans LN650699 611 97 0.0 99 (4C)

20 NST25 H, neapolitanus AB308268 625 96 0.0 99 (25C) 7 H. sp. RA13 AY099401 615 98 0.0 99 NST4 (4C) H. neapolitanus HQ693550 594 95 0.0 95 8 NST13 H. neapolitanus AB308268 558 94 0.0 99 (13C) 10 (13C) 11 NSR4 H. neapolitanus NR_104929 615 97 0.0 99 (25C) 3 (4C) 9 (13C) 5 NST4P H. neapolitanus AB308268 613 97 0.0 99 (4C) 19 (25C) 12 (13C) ASR25P Acidiphilium sp. EU003879 624 98 0.0 99 17 (25C) 13 (4C) IOR4P A. ferrivorans LN650699 634 98 0.0 99 15 (13C) 16 IOT25P A. ferrooxidans KJ944318 625 97 0.0 98 (25C) *Explanation of nomenclature: the first two letters refer to the substrate and pH; IO = iron oxidizer; NS = neutrophilic sulfur oxidizer; AS = acidophilic sulfur oxidizer; the third letter refers to the source of the sample T = thickened tailings; R = raw tailings; the number refers to the temperature of isolation 4, 13, or 25 degrees. NST4P, IOR4P, IOT25P and ASR25P are the result of direct plating of thickened tailings on their respected media.

Table 3.2. Results of direct BLAST comparison of 16SrRNA of IOM isolates.

Isolates IOT4 IOT13 IOT25 IOR4 IOR25 IOR13 IOR4P IOT25P

IOT4 97% 97% 99% 99% 98% 97% 95% IOT13 100% 97% 97% 97% 96% 98% IOT25 97% 97% 97% 96% 98% IOR4 98% 100% 98% 96% IOR25 99% 98% 96% IOR13 98% 95%

IOR4P 97%

Table 3.3 Results of direct BLAST comparison of 16SrRNA of SOM isolates.

Isolates NST25 NST4 NST13 NSR4 NST4P ASR25P NST25 95% 99% 98% 98% 85% NST4 96% 95% 94% 84% NST13 99% 98% 85%

NSR4 98% 87%

NST4P 87%

The isolation of the two iron oxidizing Acidothiobacillus species is not surprising since organisms in this genus have been isolated and/or detected in many other ARD sites (Colmer and

Hinkle 1947, Johnson et al. 2001). As shown in Figure 3.1 the DNA from these organisms was found in the metagenomics studies performed previously. The isolation of the Halothiobacillus species is also as expected since it too is a commonly isolated NSOM. DNA for one species of this organism was also found in the metagenomics studies as summarized in Figure 3.1. The presence of Acidiphilium species is also expected due to their prevalence in other ARD sites and the fact that their DNA was found in the metagenomics studies.

The inability to isolate some of the other common SOM that are indicated as present in the system through isolation of DNA in the metagenomics studies such as Beggiatoa, Gallionella,

Chlorobium, Leptothrix, and Leptospirillum, could be due to the fact that these organisms are isolated predominantly from aqueous systems and this study used the solid tailings as inoculum.

Figure 3.2. Images of Gram stains of the isolated bacteria. A: A. ferrooxidans (top left) B: A. ferrivorans (top right) C: H. neapolitanus (bottom left) D: Acidiphilium species (bottom right). Images were captured using a 100x objective.

Figure 3.3 Images of streak plates of sulfur and iron oxidizing bacteria. I (upper left). Acidophilium sp. II (upper right): H. neapolitanus III (bottom left): A. ferrivorans IV (bottom right right): Halothiobacillus species

A unique aspect of this study is the focus on the temperature dependence of the isolates.

Even though cold environments account for a high portion of the biosphere, there has not been a significant study with a goal of the isolation of psychrophilic sulfur or iron-oxidizing bacteria

(Berthelot et al. 1994, Margesin et al. 2008). On the other side of the sulfur cycle, psychrophilic sulfur-reducing bacteria are common in low temperatures even in habitats with the temperature variations in the range of Alberta oil sands (Helmke and Weyland 2004).

3.3 Bacterial growth kinetics

Further characterization of the SOM and IOM isolated in this study involves the

determination of the growth and acid production by these isolates, which will provide valuable

information that, can be used to model the effects (growth and acid production) that these

organisms will have in at the temperatures expected in the environment. This study also adds

significantly to the scant literature base on the growth rates of these important organisms.

3.3.1 Sulfur-oxidizing bacteria

All of the currently cultured species of Halothiobacillus are known to be mesophilic

(Liljeqvist et al. 2015, Wu et al. 2013). Since HTBN and HTP were isolated at 4°C it is possible

that these isolates could be psychrotrophic or at least psychrotolerant. Growth studies were

performed for HTBN and HTP in six different temperatures (7, 12, 25, 30, 37, 40°C). The pH,

turbidity at 600 nm, and concentrations of thiosulfate and sulfate were also measured. As an

example of results from these studies Figure 3.4 top shows the change in pH (primary y-axis) and

absorbance at 600 nm (secondary y-axis) for HTBN. As is evident from the figure the decrease in

pH is accompanied by an increase in turbidity. Turbidity increases faster and has a higher slope

than the decline in the pH. This is expected due to the buffering capacity of the media that delays

the onset of the change in pH. The direct relationship between turbidity and bacterial numbers has

been established previously (Alsop et al. 1980, Holm and Sherman 1921). Once the buffering

capacity was exhausted the pH dropped rapidly, accompanied by the rapid decline in turbidity

suggesting death linked to acid toxicity.

Figure 3.4. Results of incubation of in HTBN at 30°C. Top: pH and absorbance (● pH and Absorbance). Bottom: sulfate and thiosulfate concentration (mM/lit). The dots present the average value of three replicates. The error bars represent one standard deviation.

Thiosulfate consumption is inversely proportional to sulfate production as shown in Figure

3.4 bottom. Ideally, consumption of one mole of thiosulfate should produce two moles of sulfate.

During maximal growth of bacteria (25-30 hrs), nearly 1.5 moles of sulfate was produced for every mole of thiosulfate consumed. Some of the sulfur was most likely used for biomass production and was not reflected by changes in sulfate concentration. It has also been shown that some bacteria from Thiobacillus species like HTBN and Thiobacillus thioparus partially oxidize reduced sulfur compounds like H2S and Na2S2O3 to sulfur under specific conditions such as starvation or oxygen limitation (Namini et al. 2012, Visser et al. 1997). However, in this case, there were no such limitations and no elemental sulfur was observed in the liquid culture. When grown on solid culture the sulfur smell was clearly distinguishable for the both HTP and HTBN. It has also been shown that Thiobacillus species are able to produce tetrathionate as an intermediate and that may be one of the reasons for the disparity in the thiosulfate consumption versus sulfate production (Friedrich et al. 2001, Kelly et al. 1997). By the end of the experiment, all of the thiosulfate was found as sulfate as all of the intermediates completely oxidize into sulfate.

Table 3.4 and Figure 3.5 present the summary of the maximum growth, sulfate production and thiosulfate oxidation rates at each temperature. As it can be seen, the of HTP occurs at

25ºC while it occurs at 30ºC for HTBN. As the temperature decreases their decreases and the rates converge. The growth rate of HTP drops quickly as the temperature increases above 30ºC; however, the decline for HTBN is slower and neither HTP nor HTBN grew at 40ºC. Even though they grow more or less in the same temperature range, their growth rates are not the same at all temperatures. These results suggest that although the organisms were isolated from 4°C they are not psychrophilic. They do show significant growth at 4°C and so are classed at as psychrotrophic, which refers to organisms that can survive and may thrive in cold environments.

Figure 3.5. Summary of thiosulphate consumption and sulfate production rates calculated for HTBN and HTP from experimental data.

Table 3.4. Kinetic rates determined for HTP and HTBN according to the change in pH, absorbance, sulfate, and thiosulfate concentration.

HTP Abs/hour pH/hr Sulfate Thiosulfate (mM/lit.hr) (mM/lit.hr) 37ºC 0.04 ± 0.01 0.21 ± 0.00 3.28 ± 0.13 1.53 ± 0.03 30 ºC 0.03 ± 0.00 0.33 ± 0.02 4.28 ± 0.01 2.27 ± 0.77 25 ºC 0.05 ± 0.01 0.50 ± 0.01 4.75 ± 0.03 2.46 ± 0.02 13 ºC ------0.08 ± 0.00 1.23 ± 0.09 0.63± 0.07 7 ºC 0.01 ± 0.00 0.09 ± 0.00 0.52 ± 0.06 0.29 ± 0.04 HTBN 37ºC 0.02 ± 0.00 0.36 ± 0.02 3.32 ± 0.07 2.04 ± 0.06 30 ºC 0.06 ± 0.00 0.49 ± 0.008 3.43 ± 0.51 2.48 ± 0.27 25 ºC 0.03 ± 0.00 0.27 ± 0.004 3.13 ± 0.04 1.92 ± 0.02 13 ºC ------0.07 ± 0.003 1.21 ± 0.06 0.54 ± 0.04 7 ºC 0.002 ± 0.00 0.05 ± 0.002 0.037 ± 0.01 0.20 ± 0.01

The fact that multiple species of microorganisms grow concurrently in the same environment is well-stablished and low extinction rates and high speciation rates of bacteria have been reported as two of the most important reasons (Dykhuizen 1998). In this experiment, both species of Halothiobacillus were active when the temperatures were higher than freezing (both

were isolated in 4ºC) and lower than 37ºC. The highest average temperature of Fort Mcmurray is

around 25ºC and HTP has its highest growth at that temperature. There have been few studies on

the thiosulfate oxidation rate of HTBN in cold environments; however, the growth data for 25-

30ºC of mesophilic strains are similar with the results of this study (Valdebenito-Rolack et al.

2011).

3.3.2 Iron-oxidizing bacteria

Growth studies were conducted on A. ferrooxidans (ACFO) and A. ferrivorans (ACFE) at

four different temperatures (13°C, 25°C, 30°C, 40°C). The pH and ferric ion concentrations were

measured over time (Figure 3.6). None of the bacteria were able to grow at 40°C.

Figure 3.6 illustrates that the ferric concentration increases with time for both of the species and the pH decrease can be observed immediately. The initial slight decrease in the pH of both

ACFO and ACFI was accompanied by a slight increase that was followed by a decline of the pH coupled with iron oxidation. The initial decrease in the pH and slight amount of iron oxidation was observed in control samples also. This can be attributed to the insignificant chemical oxidation; however the main oxidation happens when the biological activity starts.

Acid is consumed at the beginning of biological iron oxidaiton (Kupka et al. 2007):

4 + + → 4 + ( 1)

Then iron hydrolysis leads to schwertmannite and jarosite formation in the equations 2 and

3 respectively. Significant amount of acid is produced and some of it is used in the fourth equation:

8 + + 14 → () + ( 2)

3 + + 2 + 6 → ()() + ( 3)

() + + +

→ ()() + 5 + 8 ( 4)

As seen in the above equations, even though the equations finally lead to acid production, but the first and last step are acid consuming and that might be one of the reasons for the slight increase in the pH after the initial decline.

The growth of cells for the IOBs using turbidity could not be determined since the precipitation of oxidized iron interfered. Instead, the change in the ferric iron concentration was used as the indicator for growth. The growth rates for both of the IOBs isolated in this study for three different temperatures are presented in Table 3.5. The trend is visualized in Figure 3.8.

As shown in Figure 3.7 the trend for both species is the same, rates at 30ºC are highest followed by 25ºC and 13ºC. The rates for ACFI are lower than ACFO in all of the temperatures.

The rates show convergence and indicate that at low temperatures each organism will contribute to iron oxidation but ACFO may dominate at higher temperatures. The growth rates at 4°C were not studied due to the very low growth rate observed at 13°C.

Table 3.5. pH reduction and ferric iron production rates of A. ferrooxidans and A. ferrivorans in 30, 25 and 13ºC.

A. ferrooxidans pH/hr Ferric iron production Ferric iron production (mg/m3/hr) (mmol/lit/hr) 30 ºC 0.01 133.70 2.39 25 ºC 0.01 104.92 1.88 13 ºC 0.004 44.86 0.80 A. ferrivorans 30 ºC 0.007 94.71 1.70 25 ºC 0.006 60.95 1.09 13 ºC 0.003 36.15 0.65

Figure 3.7. Effect of temperature on Ferric iron production and pH change rates.

( ) Assuming that oxidation rate of iron is first order, a plot of versus ( ) time would give a straight line. The slope (k) will be the specific reaction rate constant and generation time will be (2/). It was calculated as 9.9 hours for iron oxidation of A. ferrooxidans and 13.9 hours for ACFE at 30C temperature. That is at least three times lower than what other studies had achieved at the same temperature for this organism (David et al. 2013,

Lacey and Lawson 1970). The mean generation time for ACFO and ACFE in 13C was 18 and 20 hours respectively that is in the range of other strains of ACFE from other studies (Mykytczuk et al. 2010). ACFO had a slightly better performance in lower temperatures, even though ACFE is known to be more cold resistant. Different studies have reported different generation times for iron oxidation of different strains of ACFE in temperatures of 4-5C ranging from 23 to 87 hours

(Kupka et al. 2009, Kupka et al. 2007, Mykytczuk et al. 2011, Mykytczuk et al. 2010). In a study conducted by Kupka and colleagues, the first order generation time for the oxidation of iron by a strain of psychrotrophic A. ferrivorans at 4C was 57.8 hours.

3.4 Phage isolation

To the best of our knowledge the majority of the methods for the isolation of lytic phages of the isolated bacteria were tested (Clokie and Kropinski 2009, Martha and Clokie 2008,

Williamson et al. 2005, Williamson et al. 2003). However, no consistent lysis was observed in this study. No results are presented documenting these numerous attempts to isolatepahge due to the immense space requirements for all of the tables and figures and the fact that all reuslts were negative.

Even though metagenomics studies suggest lytic phages should have active involvement in extreme environments (Belnap et al. 2011, Mueller et al. 2011, Sun et al. 2016b), there has been

only one successful isolation of lytic phage in low pH (Johnson et al. 1973). Moreover, there have

been several reports on the sharp decline in the activity of phages in low pH (Sykes et al. 1981,

Traving et al. 2014, Ward et al. 1993, Zhuang and Jin 2008). It could also be that since the samples

used in this study were only at the intiail stages of ARD there were insufficient phage to isolate,

wven though methdos to concentrate them were used. It could be possible that enriching the SOM

and IOM in the tailings samples to increase their populations could be used to increase the

population of phage that attack them before another isolation attempt. Obtaining samples form

sites that have active ARD populations may also be of use. It is also possible that successful

isolation of these phages may require the development of new methods. Developing new methods

of phage isolation is beyond the scope of this study.

3.5 Bioinformatics studies

In light of the inability to isolate phage targeting our specific isolates, and to determine if

there was any evidence that there are phage that can attack IOM or SOM, bioinformatics tools

were used to examine full DNA sequences of known IOM or SOM.

3.5.1 CRISPR search

CRISPRs are an indication of previous viral infection, and their presence and evolution

indicate continuous exposure to infection (Barrangou et al. 2007, Bolotin et al. 2005, Horvath et

al. 2008, Makarova et al. 2006, Tyson and Banfield 2008). The full genomic DNA sequences of

thirty-two bacterial and two archaeal strains that are known to participate in ARD or sulfur and

iron oxidation were collected from the NCBI database and investigated for the presence of

CRISPRs.

CRISPRs were found in 15 of the bacterial and 2 of the archaeal genomes believed to be engaged in ARD and therefore tested in this study. Table A.1 in Appendix A presents the nucleotide sequences of the CRISPRS found. Table 3.6 summarizes the numbers of CRISPRs and spacers, lengths of the CRISPRs and direct repeats, and the average length of the spacers in each

CRISPR for these organisms. Table 3.7 presents the 17 identification of the 17 bacterial genomes that lacked CRISPRs.

Table 3.6. Summary of CRISPRs found in the 17 full genomes of ARD organisms probed. Unless labelled as archaea, the taxa are bacterial.

Species Number of CRISPR Direct Number of Average CRISPRs Length repeat Spacers length of (nucleotides) Length spacers (nucleotides) (nucleotides) Acidianus 6 3341 25 52 40 ± 1 hospitalis 801 25 12 40 ± 3 (Archaea) 545 25 8 40 ± 5 2311 24 39 35 ± 2 544 24 8 41 ± 2 282 24 4 41 ± 0.5 Ferroplasma 2 904 30 13 37 ± 1 acidarmanus 498 30 7 37 ± 1 fer1. (Archaea) H. neapolitanus 1 2247 37 31 34 ± 1 C2 A. caldus 3 234 30 3 33 ± 0 ATCC 51756 997 29 16 36 ± 2 198 24 3 34 ± 15 A. caldus SM-1 3 1125 27 18 34 ± 2 686 28 11 32 ± 2 336 19 4 44 ± 0 A. ferrivorans 1 1065 29 17 35 ± 9 strain WGS A. ferrooxidans 3 333 28 5 33 ± 0.5 strain DLC-5 269 26 15 35 ± 0 1793 28 29 33 ± 2 A. ferrooxidans 2 263 31 4 27 ± 4 ATCC 23270 375 23 6 36 ± 3

Species Number of CRISPR Direct Number of Average CRISPRs Length repeat Spacers length of (nucleotides) Length spacers (nucleotides) (nucleotides) Leptospirillum 1 335 28 5 32 ± 0 sp. Group II 'C75' Leptospirillum 3 881 29 17 21 ± 5 sp. Group II 4426 29 72 32 ± 0 1190 29 19 32 ± 0 Leptospirillum 1 1124 28 18 33 ± 1 sp. Group III Leptospirillum 1 519 29 8 32 ± 0.5 sp. Group IV Thiomonas sp. 1 4829 28 79 32 ± 0 Acidimicrobium 2 1676 28 27 33 ± 0 ferrooxidans 2469 28 40 33 ± 0 DSM 10331 Acidiphilium sp. 1 5703 29 93 32 ± 0 PM, DSM 24941 Acidiphilium 1 1856 20 32 37 ± 12 cryptum JF-5 Acidiphilium 1 310 19 5 39 ± 19 angustum ATCC 35903

Table 3.7. Summary the 17 full genomes of ARD organisms probed in which a CRISPR was not found (first column is the genus and the next columns in a row are different species).

Genus Species Thiobacillus thioparus denitrificans denitrificans denitrificans novellus DSM 505 ATCC 25259 DSM 12475 Strain RG ATCC 8093 Acidothiobacillus ferrooxidans thiooxidans thiooxidans thiooxidans ferrivorans ATCC 53993 A01 ATCC 19377 SS3 Leptospirillum ferriphilum ferriphilum ferrooxidans YSK ML-04 C2-3 Acidiphilium multivorum Acidiphilium AIU301 sp. JA12-A1

Thiomonas intermedia Ferrimicrobium acidiphilum DSM 19497

CRISPRs were identified in both archaea, and in 47% (15 out of 32) of the bacteria. This

is consistent with about 40 to 50% of bacterial isolates having CRISPRs (1176/2612) (Godde and

Bickerton 2006, Grissa et al. 2007a). The genera represented in the pool of organisms that were

not found to have CRISPRS are all represented in the pool that were found to have CRISPRS so

the lack of CRISPRS seems to be species and even strain specific. CRISPRs were not detected in

the four full genomes for Thiobacillus sp. in the database (Table 3.7), including for Thiobacillus

novellus ATCC 8093, a strain for which a lytic phage has been isolated (Johnson et al. 1973). This

may indicate that these bacteria use other ways of protection against viral infection. On the other

hand, five out of ten bacteria in the genus Acidithiobacillus, one of the most important acidophilic

chemolithotrophic bacteria engaged in ARD, had CRISPRs. These results docuemtn that there are native phage that have acttaked organisms that are involved in ARD and strengthen the hypothesis that phage therapy to contorl the popolations of these organisms should be possible if the methods to isolate and propgate these phage are developed.

The length of the CRISPRs and number of spacers varies significantly (Table 3.6). The

length of spacers can also vary considerably, even within a CRISPR, and tend to be longer in

archaea. The average length of direct repeats and spacers in the archaea are 25 and 30, respectively,

and in the bacteria slightly longer, 28 and 34, respectively. Since spacers originate from the

genome of infecting viruses, sequences from the 740 spacers in this study were compared with the

viral database. Some research has shown that bacteria lose resistance even if there is one base-pair

mismatch between the spacer and viral sequences, however, other studies show that a few

mismatches may be fine, depending on where they occur in the spacer (Barrangou et al. 2007,

Gudbergsdottir et al. 2011). Mismatches at the beginning of spacer affect specificity more than

elsewhere (Gudbergsdottir et al. 2011). Microbes can acquire and lose spacers rapidly (Andersson

58 and Banfield 2008). As there can be considerable sequence variability within gene homologs from closely related viruses, because of codon wobble or other mutations, an average similarity of 90% over 90% of the length of the spacer was used as a cut-off for comparison. Ninety percent over

90% however was deemed as average similarity but not certain or fixed: biological significance and the location of mismatches were deemed more important as the similarity cut-off for spacers has not yet been well-established.

When the spacer and viral sequences were compared using BLASTx, some spacers in

Acidianus hospitalis W1 were a perfect or near perfect match to some proteins in Acidianus tailed spindle virus and Sulfolobus monocaudavirus (Table 2 Appendix A). Ten of the spacers best match different Sulfolobus and Acidianus tailed spindle viruses. Acidianus hospitalis and the tailed spindle virus were isolated from the hot, acidic Alice Springs (Hochstein et al. 2016). After isolating and sequencing the viruses, they identified the hosts by searching against CRISPRFinder spacer database (Grissa et al. 2007a, Hochstein et al. 2016). The Sulfolobales virus and the

Acidianus tailed spindle virus are spindle-shaped, double-stranded DNA archaeal viruses isolated from extreme environments (Xiang et al. 2005). Spindle-shaped viruses are exclusive to archaea, and are divided into the families Fuselloviridae and Bicaudaviridae. Acidianus tailed spindle virus, Sulfolobus virus STSV1, and Sulfolobus virus STSV2 are in the family Bicaudaviridae, which consists of enveloped, lemon-shaped particles with circular double-stranded DNA genomes.

Four of the six viruses identified in this study (Sulfolobus monocaudavirus SMV1, 2, 3 and

4) matched sequences found in viral metagenomic data from an acidic and high-temperature hot spring in Italy, but they have not been isolated to date (Gudbergsdottir et al. 2016). The matches of the spacers in Acidianus hospitalis to these viruses as shown in Table 10 suggests that it may be a potential host for these viruses, and can be used for viral isolation. Moreover, it suggests that

59 other viruses infecting Acidianus hospitalis, may have the same morphology as those in the

Bicaudaviridae. Of 123 spacers in Acidianus hospitalis only nine matched viruses other than the

Acidianus hospitalis tailed spindle virus, suggesting that closely related viruses are likely important pathogens in hot, acidic environments.

Even for the thermophilic viruses that have been sequenced, the function of many of the encoded proteins remains unknown. Spindle-shaped viruses cause lysis of their hosts and cause plaque formation; lysis can also be induced by UV radiation or mitomycin C treatment (Xiang et al. 2005). The fact that different spacers of one archaea are perfect or near perfect matches to one virus suggests a constant or recent interaction between the virus and host, or it might be that multiple spacers are acquired in some interactions.

For the bacteria, most spacers did not have any matches to the viral database, except for,

Halothiobacillus neapolitanus C2 that had several perfect and near perfect matches (Table A.3 in

Appendix A). In the one CRISPRs in HTBN, two of its 31 spacers (10 and 25) had significant matches to 16 viruses in the order Caudovirales, seven belonging to each of the families

Siphoviridae and Myoviridae, and two to the Podoviridae. Members of the Caudovirales are tailed viruses, with double-stranded DNA within their icosahedral heads. They either have long contractile tails (Myoviridae), short non-contractile tails (Podoviridae), or long non-contractile tails (Siphoviridae). As all of the viruses that match the spacers are in the Caudovirales, it suggests that the viruses infecting HTBN also belong to this order.

Of 601050 proteins listed in NCBI under “phage”, 518972 (86%) are from the order

Caudovirales; the rest are from Microviridae, Inoviridae, Leviviridae, as well as other orders.

Within the Caudovirales, 256336 (49%) are from the Myoviridiae, 202487 (34%) from the

Siphoviridae and 54326 (9%) from the Podoviridae, while 8% are from other families (Consortium

2015, NCBI 2016). Moreover, phages typically outnumber bacteria by about 10 to 100 times

(Ashelford et al. 2003, Suttle 2007, Wilson et al. 2016), and as of 9 May 2016 there were 41654 bacteria and 5580 viruses in the RefSeq database, the bacterial database is eight times richer than the viral database, even though viruses are much more abundant. Considering that the viral database is skewed towards viruses that are medically significant or infect relatively few bacterial taxa, only tentative conclusions are possible.

Next, spacers were compared to the “environmental metagenomics protein database”. Even though this database is not exclusive for viruses, spacer acquisition occurs through viral infection and comparing spacers with metagenomics databases might give insight into the evolution or acquisition of spacers. Four of the 32 spacers (Spacers 8, 16, 25 and 24) in Acidiphilium cryptum

JF-5 had several significant matches to the database. Acidiphilium cryptum JF-5 is an acidophilic, facultative anaerobe that is prevalent is acidic environments; this strain was isolated from a 12°C, pH of three of a coal-mine lake sediment in east central Germany (Kusel et al. 1999). This genus does not directly contribute to the decrease in the pH; however, it reduces Fe3+ to Fe2+, and in turn,

Fe2+ is oxidized to Fe3+ by other microorganisms such as A. ferrooxidans, A. ferrivorans and

Leptospirillum ferrooxidans, leading to acid production. These spacers also had perfect or near perfect matches to hypothetical proteins in metagenomic data from marine water and sediments

(Rusch et al. 2007, Spang et al. 2015, Yooseph et al. 2007). The sediments were retrieved from a mid-ocean ridge during summer, 15 km from an active venting site 3000 m below the surface

(Spang et al. 2015). The extreme nature of this environment suggests that these hits are not spurious. As well, Spacers 24 (61 bp) and 25 (70 bp) had meaningful hits to a phage tail-fiber protein (Figure 14) (650 bp) from a hydrocarbon-contaminated ditch in Germany, a similar environment from which the bacterium was isolated (Embree et al. 2015). These spacers were also

64% similar to each other, suggesting that they were acquired from closely related viruses. Spacer

24 had several hits to the same protein in the metagenomic data (3.8, Table A.3). A BLASTx analysis of the spacers in Acidiphilium cryptum showed that the spacers exclusively hit an L5-like

Mycobacterium phage in the family of Siphoviridae.

Figure 3.8. Alignment of spacer 24 and 25 of Acidiphilium cryptum JF-5 to the same phage tail fiber protein.

Table 3.8. Hits of the spacers of Acidiphilium cryptum JF5 to the environmental viral metagenomics of a hydrocarbon-contaminated ditch in Germany. PI is pairwise identity and QC is query coverage

Query Description PI% E Value Hit end Hit start QC % CRISPR.1 phage tail fiber protein 80.00 2.45 233 214 98.36% Spacer.24 [hydrocarbon metagenome] CRISPR.1 phage tail fiber protein 84.20 5.28 185 167 93.44% Spacer.24 [hydrocarbon metagenome] CRISPR.1 phage tail fiber protein 84.20 5.28 170 152 93.44% Spacer.24 [hydrocarbon metagenome] CRISPR.1 phage tail fiber protein 78.30 1.44 191 169 98.57% Spacer.25 [hydrocarbon metagenome]

Next, the spacers in the bacteria studied (Table 1. Appendix A) were compared with viral metagenomic data collected from a diversity of environments to reveal environments that might be a source for phage isolation. Viral metagenomic data collected from the following locations were analyzed: 1) 50 m depth in the Mediterranean, off the coast of Alicante, Spain (Mizuno et al.

2013); 2) Pooled data from untreated municipal sewage from the US, Nigeria, Thailand and Nepal

(Ng et al. 2012); 3) an acidic hot spring in Yellowstone National Park (Bolduc et al. 2015); 4)

Antarctic open soil from the Miers Valley in eastern Antarctica in summer (~5°C) (Zablocki et al.

2014); 5) pooled data from six hypersaline ponds (8% to 36% of salinity) from the coast of Senegal

(Roux et al. 2016).

Out of the 281 significant matches of the spacers to data from Yellowstone National Park

(at least 90% match over 90% coverage), 280 were to 21 spacers from Acidianus hospitalis W1

(data not shown). This strain was isolated in 2003 from Yellow Stone National Park and sequenced in 2011 (Rachel et al. 2002, You et al. 2011b). This result is consistent with archaea being abundant in hot acidic lakes. The number of hits to the viruses in those environments were also higher. Some spacers matched several contigs, further supporting the idea that viruses infecting A. hospitalis W1 are present in this hot spring. The average identity of the spacers to matches in the metagenomic data was estimated to be 26% using T-Coffee (Notredame et al. 2000). Considering that Acidianus hospitalis W1 was isolated in 2003 but only sequenced in 2011, it shows that spacers need not be shed quickly or that they might have other roles in the system (Tyson and Banfield 2008). This is consistent with spacers in Leptospirillum group II being conserved for longer than 5 years (Sun et al. 2016a, Tyson and Banfield 2008).

There were fewer matches to the viral data from Antarctic soil, and most of those were to

Acidiphilium spp. including matches to A. cryptum JF-5 (2 matches to spacers 9 and 11 of CRISPR

1), A. angustum ATCC 35903 (2 matches to spacers 1 and 2 of CRISPR 1) and one match to

Acidiphilium sp. PM (spacer 41). As discussed before, A. cryptum JF-5 was isolated from a low temperature environment (12°C), and close relatives of A. angustum ATCC 35903 are also common in low-temperature environments; both isolates are psychrotolerant. Even in the present study one strain of Acidiphilium was isolated. Acidiphilium spp. occur in Antarctica; hence the

63 phage likely do, as well (Blanco et al. 2012, Karr et al. 2003). However, the significant matches were much less than between the Yellowstone Hot Springs data and the spacers of Acidianus hospitalis. This is expected since the geographical distance between the Antarctica and the matched spacers of Acidiphilium species is not comparable with Yellowstone and Acidianus hospitalis as it has been isolated from Yellowstone. Spacers 9 and 11 in CRISPR 1 of Acidiphilium cryptum JF-5 are 76% identical, suggesting that they are from closely related viruses, as was also the case for spacers 24 and 25 in A. hospitalis, which matched one tail-fiber protein and which were >60% similar.

There were also significant matches to the viral metagenomic data from the hypersaline ponds and sewage. Spacer 22 in CRISPR two of Acidimicrobium ferrooxidans and spacer one in

CRISPR one of Acidiphilium angustum had a low number of matches to data from the hypersaline ponds even though these taxa are not prevalent in hypersaline environments. As well, there were

11 matches to the sewage viral metagenomic data for spacers 10, 11 and 13 in CRISPR 1 of

Acidiphilium cryptum, and nine matches for two spacers in A. caldus. There are reports of

Acidimicrobium ferrooxidans being isolated from sewage (Kishimoto and Tano 1987). There were also three significant matches between two spacers in Acidiphilium cryptum and viral contigs from metagenomic data from a mosquito.

Only the data from the acidic hot spring in Yellowstone National Park had perfect matches with the CRISPR spacers (Table 3.9). Although a sequence identity of less than 100% may result in spacers that are ineffective against viral infection (Barrangou et al. 2007), lower sequence identities could indicate the presence of related viruses. This is most evident in the Yellowstone data, where lower stringency resulted in a large increase in significant hits. Given that spacers

(Eloe-Fadrosh et al. 2016) and viruses can be shared across wide geographical distances (Chow

and Suttle 2015), it is not surprising that related sequences are wide spread, although the lower

stringency may result in a greater number of spurious hits, as well.

Table 3.9. Identity percentage vs overlap percentage of spacer matches to viral metagenomics databases. Study source 90% over 90% 95% over 95% 100% Yellowstone National Park 281 104 24 Sewage 11 1 0 Hypersaline pond 2 0 0 Antarctica open soil 6 0 0 Mosquito 3 0 0

Given the wide dispersal of cells and viruses, and the similarity between CRISPR spacer

sequences and viral metagenomic data from widely separated locations. It could be inferred that

infectious viruses can be isolated for hosts from separate but similar habitats. Moreover, shedding

of spacers over time may lead to less resistance to infection by viruses from different locations;

hence, a bacterium from oil-sand tailings may be susceptible to infection by viruses from another

environment.

3.5.2 Characteristics of the repeats

Unlike spacers, which are a history of exposure to infectious DNA, the repeats are a

characteristic of the host. Relative to spacers, less research has been published on repeats.

Although repeats are highly conserved within a CRISPR, they can be very diverse among cells.

Many are palindromic or partially palindromic, which may help in creating stable RNA structures,

and have a conserved (GAAA (C/G)) motif at the 3´ end that acts as binding site for Cas proteins.

GAAA is also a very conserved sequence in four-base hairpin loops (tetraloop) that are found in

RNA molecules (Godde and Bickerton 2006, Kunin et al. 2007). As well, tracrRNAs (89 to 171

65 nt) contain near perfect matches to the CRISPR repeats (24 out of 25) and even in some crRNAs, both ends contain repeat sequences (Deltcheva et al. 2011).

Several alignment tools (T-Coffee, Geneious, ClustalW, MAFFT) with different settings were used to align the repeats and spacers. These are presented in Figure 3.10. Hand curations were performed to preserve conserved motifs in the consensus sequence. Likelihood scores were calculated using RaXML. MAFFT aligner was the best option for 36 repeats and 730 spacers

(likelihood score of -732.6 for repeats and -2725.32 for the whole spacers). With the exception of

Thiomonas spp., the bacteria and archaea examined in this study had at least some palindromic or partially palindromic sequences in their CRISPR repeats. Out of 36 repeats, 29 (81%) were partially palindromic. Some repeats had several palindromic sequences, the longest of which was

10 bp although most were four bps. GAAA Conserved Motifs (CM1 in Figure 3.10) were present in 42% of the repeats in bacteria and all of the repeats in archaea. Fifty-four percent of bacteria

(regardless of the number of repeats in each bacteria) contained the motif. As well, there was

GGG/CCC (CM2 in Figure 16) motif in 10 out of 16 (61%) bacteria, and in 23 of 36 repeats in those bacteria; however, they only occurred in three of the 8 repeats from archaea, and in those repeats they were interspaced by AAAA or TTTT.

Since only 16 bacteria (at the strain level) and two archaea were investigated in this study, reaching a conclusion regarding the presence of such a motif (GGG/CCC) is not certain. However, it might be that in the acidophilic bacteria another motif is more prevalent than GAAA and it might have a role in the process. A GGGG motif has been shown to cooperate in silencing of specific exons in eukaryotic cells, however, closer investigation is needed to find if this motif has a function in prokaryotic cells if any (Han et al. 2005).

Figure 3.9. Palindromic sequences (PS) from the CRISPRS in the 17 straions of bacteria that contained CRISPRS. The sequences were extracted using the methods of Bikandi et al. (2004), curated and annotated manually. 67

Figure 3.10. Summary of repeats found in the 17 full genomes that had CRISPRS. Multiple sequence alignment and sequence logo of repeats were drawn using MAFFT aligner. Possible conserved motifs are shown with CM in the consensus sequence. CM1 (in blue) is the GAAA motif. CM2 (in orange) is the GGG/CCC motif.

Phylogenetic analyses of the repeats and spacers yielded very poor bootstrap support, because the sequences are very short, and consequently have very few, if any, informative sites.

None of the methods produced consistent results; however, FastTree produced a tree of the repeat sequences with reasonable support values for end branches (Figure 3.11). FastTree produces trees with similar topology and precision to RaXML but much faster (Liu et al. 2011c, Price et al. 2009,

2010a).

There is no correlation of the tree produced in Figure 3.11 with the evolutionary tree of bacteria. For example, the repeats in Acidithiobacillus caldus, even within the same strain, fall into widely separated sequence clusters (Figure 3.11). A similar result was obtained with a consensus tree of the repeats (not shown). One reason that repeats and even Cas systems are not well correlated with microbial evolution is because the cassettes evolve more rapidly under the pressure of pathogens than the rest of the genome. As well, horizontal gene transfer has a more important role than vertical gene transfer in the rapid evolution of defense mechanisms (Leplae et al. 2011, Westra et al. 2012). However, repeats can be grouped into clusters based on sequence similarity and these groups correspond to the Cas classification of CRISPR systems. This can be seen in an unrooted FastTree (Alkhnbashi et al. 2014, Price et al. 2010b) combining 3563 repeats from Alkhnbashi and colleagues work combined with those from this study (Figure 3.12). The support values for tree are not shown; however, they were more than 75% for most of the end branches. Although many repeats from the same taxa cluster together, others cluster with repeats from bacteria that are distantly related (e.g. Acidimicrobium ferrooxidans and Thermomonospora curvata). However they both had the same type of CRISPRs (Type I-E).

Figure 3.11. Phylogenetic tree for repeats. The tree was drawn using FastTree with a resampling value of 1000. The repeats of the same species were colored the same. The repeat of CRISPR 3 of A. caldus ATCC 51756 was chosen as an outgroup as it had the lowest average similarity to all other repeats. The support values (SV) are shown as node labels in the tree with the larger font than substitution per site (SPS) as branch label. Anytime that there was a possibility of confusing SV with SPS the support values have been put into an oval. Every species has been colored the same. 70

Figure 3.12. Neighbor joining tree drawn using Fastree for 3600 repeats published by Alkhnbashi et al. (2014) plus the ones from this study. The red arrows show bacterial repeats from this study and pink colors show Archaeal repeats from this study. [16-20: Leptospirillum sp. 22-27: Acidianus sp. 2-7: A. caldus, 28-29: Acidimicrobium ferrooxidans, 9- 11: A. ferrooxidans, 36: Thiomonas sp. 1. HTBN]

In contrast, most repeats from archaea cluster into two well-defined groups. Even repeats

from different strains of archaea cluster together. For example, repeats from Thermofilum pendens,

Sulfolobus islandicus, Nitrosopumilus maritimus, Methanosphaera stadtmanae, Archaeoglobus

fulgidus, Desulfurococcus mucosus, Thermoproteus neutrophilus, Pyrobaculum calidifontis,

Thermoproteus tenax and Pyrobaculum aerophilum cluster into the same broad evolutionary

branch. As well, some bacterial repeats also clustered within this broad evolutionary group,

including the Gram-negative Anaerolinea thermophile and Streptobacillus moniliformis, and

Gram Positive Lactobacillus casei that is commonly found in the human intestine and mouth.

Other bacterial repeats in this cluster include Lactobacillus rhamnosus, Ornithobacterium

rhinotracheale, Bacteroides rectalis, Candidatus Arthromitus and Paludibacter propionicigenes.

These phylogenetic conflicts in repeats are a sign of horizontal gene transfer (HGT) that is a main

force in CRISPR-Cas evolution (Godde and Bickerton 2006). Unlike spacers a minimum amount

of similarity is required for repeats as they play similar roles across CRISPR Cas systems.

Consequently, most carry conserved motifs such as GAAA or GGG/CCC, that regardless of family

or phyla are needed for the system to function. Unlike spacers, repeats are not acquired from other

organisms, but consist of conserved sequences with several motifs, such as GAAA that are

required to maintain functionality.

3.5.3 Characteristics of the spacers

Although matches among spacers and sequences in the viral database were identified and

discussed above, as were matches across bacterial taxa, the similarity of spacer sequences across

broad taxa were not investigated closely. In this section, the spacer similarity across taxa is

explored, with high similarity defined as more than 80% match across 80% overlap.

High similarity across spacers was observed only for Leptospirillum species, two spacers in Acidithiobacillus caldus SM1, and four spacers in Acidimicrobium ferrooxidans DSM 10331

(Figure 19). In the CRISPRs from Leptospirillum sp. Group II C75 and Leptospirillum sp. Group

II 5way CG, spacers 1, 2, 3, 4 and 5 were the same except for C75 having one nucleotide more than 5way CG (Figure 19). As well, the repeats (Figures 3.11/3.12) were 100% similar with one palindromic sequence and no GAAA motif. These bacteria are from a very acidic mine site and were assembled from metagenomic data at the same time (Goltsman et al. 2013, Liu et al. 2010b).

The similarity between their repeats shows that repeats play a significant role in the uptake of specific spacers. The similarity between consecutive spacers in two bacterial sequences from one place that were sequenced at the same time suggests that closely related phage infect both types of bacteria. It might also be an indication of rapid prey and predator adjustments.

An unusual observation is that in Leptospirillum sp. Group II 5way CG, spacers 35 and 36 have the same sequence, as do spacers 38 and 39 (Figure 19). Having the same spacers in close vicinity of each other indicates infection by two very closely related viruses at close time intervals and that uptake of viral sequences must be highly selective. For example, it may be as shown

Figure 14 that specific repetitive sequences, such as occur in phage tail proteins, might be preferentially acquired. This is in the case that sequences have correctly been assembled as misassembling in repeat regions happens quite often.

Figure 3.13. Spacers with high similarity across species and strains of the bacteria and archaea. The identical nucleotides are shown in green and differences in red.

None of the CRISPR spacers in the bacteria and archaea investigated in this study had conserved motifs and they were quite dissimilar to each other with average similarity of 30% ±

8%. This observation is expected since viruses do not benefit from keeping the proto-spacers; moreover, bacteria tend to lose them from the trailing end of the CRISPR over time. However,

Acidiphilium cryptum JF5 deviates significantly from this trend as demonstrated in Figure 3.14 which presents the multiple sequence alignment of the 32 spacers in this organism. The average identity of its 32 spacers is about 81% with 52% of identical sites across all of the spacers, demonstrating that acquisition might not be random.

Figure 3.14. Multiple sequence alignment of Acidiphilium cryptum JF5 spacers using the Geneious MSA tool.

The reason that Acidiphilium cryptum JF5 had more matches to the viral metagenomic databases (some results are in Table 3.8) is because of the high similarity between its spacers, so if one spacer has a significant match, the others will, as well. Acidiphilium cryptum JF5 is an

75 acidophilic psychrotroph, and a facultative anaerobe (Kusel et al. 1999). High similarity among spacers can suggest that it interacts with closely related viruses, and that spacer acquisition is targeted to specific sequences. Only four pairs of spacers (15-7, 14-21, 3-4, 20-26) matched each other with 100% identity over the entire spacer. The spacers in this bacterium had the greatest variation in length seen in this study, and varied from 25 to 70 bp, with an average length of 37 ±

11 bps. This shows that bacteria tend to acquire specific sequences from viruses, whether it is near a proto-spacer adjacent (associated) motif or another specific place. Hence, bacteria acquire sequences from specific parts of the viral genome irrespective of length. Another reason might be a high mutation rate caused by viruses causing insertions and deletions in protospacers that lead to the fast acquisition of new but slightly different spacers in the bacteria.

The last stage in the examination of spacers was comparing them across strains and species.

There were 703 spacers that other than some of them that had matches with Leptospirillum sp

Group II that were previously discussed, only spacer 9 of CRISPR 1 in A. caldus SM1 and spacer

4 of CRISPR 2 in A. caldus ATCC 51756 were near-perfect matches to each other (100% match over 95% coverage). The pattern of the matches was similar to those for Leptospirillum sp Group

II with one of them having a 100% match over 100% of its length, and the other with a 100% match except for some extra nucleotides at one end (Figure 3.15).

Figure 3.15. Similarity of two spacers in two strains of A. caldus. The identical nucleotides are shown in green and different ones in red.

The similarity between spacers of the bacteria that have been isolated from the same

environment can suggest the presence of some viruses with wider host range and show that spacer

acquisition is not random. A. caldus ATCC 51756 has been isolated from coal spoils in England

and A. caldus SM1 has been isolated from pilot bioleaching reactor in China (Hallberg and

Lindström 1994, Liu et al. 2010a). Even though similar environments can harbor these kinds of

bacteria, they are geologically far from each other. Spacers are reminiscent of previous phage

invasion, and in this case it might be that these two bacteria have encountered the same or very

similar viruses, and if this is true, the results obtained in the first part of the study regarding matches

of bacterial spacers and viruses in remote areas might be considered relevant. It could also be the

case that in specific strains, specific spacers are not shed, an indication that spacers might have

other roles in CRISPR systems or they might change their functionality in the course of time.

3.5.4 Cas genes

CRISPR-Cas types and subtypes can also shed insight into the role of viral infection. There

are several thousand known signature Cas proteins (Table 14). Some genes were nearly identical

across strains and were included in the analysis. The number of amino acids was extracted to

calculate the minimum bitscore to infer homology (Pearson 2013), as follows: There were

16,243,721 amino acids in the CRISPR database downloaded from NCBI on 8 June 2016. For

calculation purposes, the average number of amino-acid sequences in each bacterium was taken as

900,000.

Table 3.10. Signature Cas proteins in the NCBI database. The number of amino acids in the database has also been presented. The minimum bitscores to infer homology have been rounded up.

CRISPR Signature Number of Number of Minimum Distribution Type Gene proteins in amino acids bitscore to of the and Sub-type the database in the whole infer system (%) database homology Type I-A Cas5, Cas8a 203 86315 34 2.1 Type I-B Cas8b 240 140746 34 2.5 Type I-C Cas8c 822 138695 34 8.7 Type I-D Cas10d 95 93246 34 1.0 Type I-E Cse1, Cse2 2644 1001218 37 27.8 Type I-F Csy1, Csy2, 1827 662625 37 19.2 Csy3, Cas6f Type II-A Csn2 423 91428 34 4.5 Type II-B Cas9 1521 1813183 38 16.0 Type III-A Csm2 382 54860 33 4.0 Type III-B Cmr5 363 50270 33 3.8 Type III-C Cas10, Csx11 868 662023 37 9.1 Type III-D Csx10 55 23580 32 0.6 Type IV Csf1 6 1434 28 0.1 Type V Cpf1 46 55538 33 0.5

For the core proteins Cas1, Cas2, and Cas3, the minimum bitscore calculated was 37, 35 and 39. However, as some Cas genes are not well conserved it is difficult to infer homology and some genes may be missed. All of the Cas genes were extracted and BLASTx was run to eliminate spurious results.

The sub-type of CRISPR-Cas systems for the microorganisms in this study, and the source references for the signature genes that have been annotated (Table 3.11) were used to determine the subtypes. The order of possible Cas genes could not be determined for bacteria that were not fully assembled and were still as contigs. In those cases, a comma was used to show the putative

Cas genes. Twelve of 18 CRISPR systems were categorized as Type I, with Subtype I-E being most prevalent based on the 4474 signature genes in the bacteria and archaea from this study

(Tables 3.10 and 3.11). This is similar to what has been found in other studies.

Table 3.11. Assigned CRISPR-Cas Type/Subtypes of the bacteria/archaea under study. Second column shows the Cas genes present in the locus. If they are presented by dash (-) they are in order in the locus; when presented by comma the order was not determined because the (putative) Cas genes were in contigs. Signature genes are in red.

Bacteria/Archaea Cas genes/or signature Assigned Reference Cas genes in the locus system subtype H. neapolitanus C2 Cas3-Cas5- Cas8c- Type I-C (Makarova et al. Cas7- Cas4- Cas1- Cas2 2011) Leptospirillum sp. Cas3-Cse1-Cse2-Cas7 Type I-E (Sun et al. 2016a) group II UBA -Cas5-Cas6e-Cas1-Cas2 Leptospirillum sp. Cas3-Cse1-Cse2-Cas7- Type I-E (Sun et al. 2016a) Group II 5 way Cas5-Cas6e-Cas1-Cas2 Leptospirillum sp. Cas3-Cse1-Cse2-Cas6e Type I-E (Sun et al. 2016a) group III -Cas7-Cas5-Cas1-Cas2 Acidianus hospitalis W1 Cas10-Csm3-Csx10 TYPE III-C (You et al. 2011a) -Csm2-Cas4 (Makarova et al. Cas6-CsaX-Cas3-Cas5- Type I-(A) 2015) Csa2-Csa5-Cas3- CRISPR4-Csa1 -Cas1-Cas2-Cas4-Csa3- CRISPR5

Bacteria/Archaea Cas genes/or signature Assigned Reference Cas genes in the locus system subtype Acidimicrobium Cas3-Cas8e-Cse2-Cas7 Type I-E (Clum et al. 2009), ferrooxidans DSM-10331 -Cas5-Cas6e-Cas1-Cas2 (Makarova et al. 2015) Acidiphilium cryptum Cas3-Cas8e-Cse2 Type I-E (Copeland et al.) JF5 -Cas7-Cas5-Cas6e-Cas1 (Makarova et al. 2015) A. caldus SM1 Csf2, Cas6e, Csf3 partial Type (Acuña et al. 2013) IV-A (Makarova et al. A. caldus ATCC 51756 Csf2, Cas6e, Csf3 partial Type 2015) IV-A A. ferrooxidans ATCC Csf4-Csf1-Cas7-Cas5 Type IV (Makarova et al. 23270 2015) A. ferrooxidans DLC5 Cas8c, Cas7, Cas5, Cas4, Type I-C Cas3, Cas2, Cas1,Cas6, Type II-B Cas9 A. ferrivorans WGS Cas1, Cas2, Cas3, Type II-B Cmr6, Csf2, Cas4, Type II-C Cas9, Cse1 (Cas8e), Cas5 Acidiphilium angustum Cse2 (Casb), Cas3, Cas2, Type II-B Cas9, Cas4,Csm2 Ferroplasma Cas6-Cas8b1-Cas7b- Type I-B (Makarova et al. acidarmanus fer1. Cas5-Cas3-Cas4-Cas1- 2015) Cas2 Thiomonas sp. Cas4 - Cas2 - Cas1 Type I-F Cse1 - Csy4 - Csy3 Cas5 - Cas7 - Csy2 Csy1 - Cas3 Acidiphilium sp. Cas3, Cse1, Cse4, Cas1, Type II-B PM, DSM 24941 Cas2 Cas5e, Cse3, Cas6, Cas9

Figure 3.16 shows the overall distribution of CRISPR-Cas system types and subtypes from

4474 determined signature genes as of July 24, 2016. Type I and subtype I-E are the most prevalent types in bacterial population (Figure 3.16 A). Bacteria active in ARD systems seem to be no different from that point of view (prevalence of subtype I-E). The two archaea investigated in this

80 study contained two types and three subtypes of CRISPR systems with Acidianus hospitalis W1 having two types (You et al. 2011a); however, the number of archaea studied here are not enough to make a meaningful conclusion or comparison.

The Type I-E CRISPR system of Escherichia coli K12 consists of Cas3-Cse1-Cse2-Cas7-

Cas5-Cas6-Cas1-Cas2 genes. Cas1 and Cas2 are the most conserved proteins in these systems and act as a complex. The Cas1 protein is a deoxyribonuclease (DNase) that acts as integrase during the adaptation stage. Cas2 forms a stable complex with Cas1 at this stage, and has a non- enzymatic (probably structural) role at the adaptation stage (Nuñez et al. 2014). Cse1-Cse2-Cas7-

Cas5 and Cas6 form a ribonucleoprotein CRISPR-associated complex for antiviral defense or

Cascade. Cas6 acts as endoribonuclease and in the case of Pyrococcus furiosus, recognizes the first nine nucleotides of repeat RNA, cleaves pre-crRNA and generates crRNA (Carte et al. 2010,

Carte et al. 2008, Wang et al. 2011). Cse1 (previously known as Cas8e) and Cse2 are the signature genes of Type I-E. Cse1 with its loop structure in the Cascade is the PAM recognition subunit in

Type I-E systems (Sashital et al. 2012). Cse2 is believed to mediate stabilizing interactions with the loop, and at the end of the process, Cas3 degrades the invading DNA by its nuclease and helicase activity.

Type I-E CRISPR systems in Escherichia coli have the ability to recognize both partially and fully matching protospacers, although the efficiency in the case of fully matched protospacers is much higher. Moreover, a full match is necessary at the 3´ end of protospacer (seed region) for the CRISPR to function (Semenova et al. 2016). Type I-E systems also rely heavily on PAM recognition to prevent auto-immunity (Westra et al. 2013).

Figure 3.16. The distribution of CRISPR systems’ types and subtypes in bacteria (A) and archaea (B) using all the signature genes present in UniprotKB.

Both strains of A. caldus and A. ferrooxidans ATCC 23270 contain a newly classified putative subtype IV (Makarova et al. 2015). This subtype lacks the conserved Cas1 and/or Cas2 genes and encodes a minimal multi-subunit effector complex with Csf1 acting as the signature protein in this subtype. The current understanding of the mode of action in this subtype is limited

(Jung et al. 2016, Luo et al. 2015, Makarova et al. 2015).

In the case of A. ferrooxidans DLC-5, the genome is in 2090 contigs and contains at least four CRISPRs based on the bioinformatics methods used in this study. There was a significant match to Cas8c of H. neapolitanus, the signature gene of the Type I-C system. Comparing the genome with a small database of Csf1 genes (signature gene of Type I-V) did not lead to any significant matches. Type I-C systems usually lack Cas6 genes, and BLASTx did not return any results using the Cas6 database of 1446 protein sequences. The presence of a Type I-C system is likely, as all of the expected proteins have matches in the sequence. As well, a Type II-B system is likely present based on similarity to the signature gene (Cas9) as well as Cas1 and Cas4.

However, since the genome is in many contigs, the distances between the putative genes and their order is unknown; hence the types of CRISPR-Cas systems that are present is speculative, although it appears to contain two systems and has at least four repeats and spacers.

A. ferrivorans WGS, Acidiphilium angustum and Acidiphilium sp.PM, DSM 24941 all contain Cas9, as well as other putative genes including Cse1, Cas8b1, Cse2, Csm2 that are representative of Type I-E, Type I-B, Type I-E and Type III-A systems, respectively. As the genomes are not in single contigs, the position of the genes and their distance to the CRISPR arrays is unknown; therefore, the type is uncertain. Only the complete set of genes associated with a Type

II system were detected; however, because other signature genes are also present, there are likely other systems to be confirmed once the genome is complete, or by experiment.

Conclusions

4.1 Conclusions

The first objective was to isolate sulfur and iron oxidizing organisms from samples of oil sands tailings. The was achieved with the isolation of five psychrotrophic, sulfur and iron oxidizing bacteria. H. neapolitanus, and Halothiobacillus sp. were the two chemolithotrophic, neutrophilic sulfur oxidizing bacteria. A. ferrooxidans and A. ferrivorans were two chemolithotrophic, acidophilic iron oxidizing bacteria and one species of Acidiphilium (an acidophilic mixotroph) was also isolated.

These organisms are representatives of the major organisms that are expected to be present in the solid tailings used in this research. Other SOM such as Beggiatoa, Chlorobium, Thiothix etc. were not isolated. This is most likely due to the tendency of these organisms to only grow in dilute aqueous systems. The two NSOM and two IOM isolated in this study are good candidates for the isolation of lytic phage.

The second objective was to characterize the growth of these organisms to gain an understanding of the rate and magnitude of their effect on the environment at temperatures important to northern Alberta. The acid production rate for HTP was in its maximum at 25°C (2.46 mM/lit.hr) and for HTBN at 30°C (2.48 mM/lit.hr), both of them were able to grow at 7°C. Both

ACFO and ACFE were isolated at 4°C, but their maximum ferric iron production rate was at 30°C.

The Ferric iron production rate for ACFO was higher than ACFE’s in all of the temperatures examined, and none of the isolates could grow in media with a pH lower than two. This has not been reported for ACFO previously.

These results provide evidence that the organisms will be active in the environment throughout the year (except when the sediment is fully frozen). The most activity will be in the summer months, but there will be activity as long as the sediments are not frozen. This extends the season for acid production and thus the environmental hazard posed by the organisms.

The third objective was to isolate phage. Phage isolation through numerous methods was not successful. None of the samples were able to cause consistent bacterial culture lysis.

Several studies have shown there is a decline in phage activity as the pH decreases. Since our attempts were performed in media with the low pH as these bacteria require, and our samples had become acidic by the time we started isolating the phage ( 4) it may have made the task more difficult.

The final objective, developed to determine if there was evidence of phage that could attack

SOM and ION was to use bioinformatics tools to probe the full genome sequences for organisms know to be involved in ARD or were SOM or IOM. The presence of CRISPRs in these microorganisms shows that there is a constant interaction between viruses and the bacteria/archaea studied in this thesis. A very thorough search for the matches of spacers as the remnants of the previous phage attacks to viral, bacterial and also metagenomics database showed that phage isolation from different but similar environments is feasible. Another interesting finding was that contrary to previous findings, microorganisms tend to keep some spacers for a long time. The reason for that is unclear; however, it might be the case that specific spacers change functionality after some time or they might have lost those spacers in the past and gained it later because of a new attack by similar viruses.

4.2 Limitations

Several limitations hindered the progress of the project. The most important one was the lack of funding due to changes in the Alberta oil industry. This created financial restrains that limited the extent of the project dramatically. The lack of financial support also led to a change from further attempts at phage isolation to bioinformatics studies in Vancouver campus as recommended by Prof. Suttle. Learning and implementing bioinformatics in the short period for someone with an engineering background proved very challenging.

The poor and biased viral database was another important hindrance in reaching to a conclusive result for finding the possible kind of viruses that can lyse ARD microorganisms.

4.3 Suggestions for future research

The bioinformatics study showed that there is evidence supporting the hypothesis that a phage therapy methodology can be developed to prevent ARD in oil sands tailings. Since most of the standard methods for the isolation of phage were used in this study, it is suggested that the following be examined in future studies.

1. Develop new and more innovative approaches for the isolation of phage.

2. Perform phage isolation using fresh samples. According to the findings in the

bioinformatics section of this study, it is recommended to try isolating phage from

different but similar environments.

3. Perform phage isolation using sampled that have been enriched to increase the

number of SOM, which should also increase the number of phage.

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Appendix A

Table A. 1. CRISPRs present in ARD microorganisms

Bacterial Species comments No DR and Spacers Halothiobacillus 1 CRISPR 1 GTTTCAATCCGCGCCCGGCGGTTAGGCCGGGCGATTC neapolitanus C2 TCGAACTTATTTACGATACGATCCACACAAGTT TCCCATATACCGCATCCAGTCGGCTGATCTTGGG GGGTGCATGAGCAGCTGGCCATTCCAGAGCCACA GCCTGCCATACCACCTGCCCACATCGTTTTAATAAG GCTGCCGGTGGTGGCAACCGATGCCCACGGCTTT GAGAATTGGGCTGGTCATGAGGTAACCCATCGAT ATCCATCACCATTACTGCATTTGATGCAAAAATT GGCAAGTTGTGAATTGGTATAAAGCCCCAGAACA GATTGGAATGGTGACTTAAACTATGCCGGATATA CATCGTCCAATGTCACCCGGTGCAGGCTGTAATC GTGGTGTCCGAGCACGCTTCCCATGATTGCATGTT TTTCGCGGATGGAAAGTTACCTCGCGCGGGGGCC GCCAATCCAGACCAGCGCGTTCCCAATCACGTCA TCAAGCAAACTCAAACGCTTGTCATTCTGCGACT GTTTGTCTCATCGAACATCCGATCAGGCGCAACGG CATGCTGTGCAATCAAGGCCAATGGCCGAAAAA TTTGCTGATGTCGGCGGATCGGTCAAGTACTACCA GAACAGCACTGATTTTGCGCTGGCAGCCATCACCG GATAGCATTCAGCGCATCGATGACGGACTGGGCG CAGAAGGCCTGACCGTGGACGGTTGGCTGGATCTG TTGCGGGGGTGGAGGCATGACCCCAACCAATACAA CCGCCAGCTTCCTTGCGGTTGCTGGGCATGAACT TGAATCAATTTGCAAAGATGATAACAAGTACGCA TTCGGCTGCATCCGCATAGGCATCGCCAAGCTCTTT ATTCCGGCAAAGAAGTGGCACTGTGTGAATCCG CGCTTGCTGCACAGTGGTTGCATCTACCGACTGCT TCCAGCAAATCCTGCCCGACTATGATGCTTATATC CTTGGCTGGCCTGGGCCTTGTCGATCGATAGCTG GTCTGATGCCGCCGATGCCGCCACCGAGCTGATC AGCCCCTGGGTTGCGTTTTTAAGCGGCAAGTCGCT CGCCTGAGCATGTTGCGCTGCTACGCGAGGCGCT Acidithiobacillus 2 CRISPRs 1 GGTTTTCCCCCGCGCACGCGGGGACGAC caldus CCATCGCTGGAATGGTGTGCATGAGCCGCGTAC SM-1 TCCTCCACATGGCGGAATCCAGGGAGCTCAAGGCG GATGATTGACCGGCTTACGTCGGAACG CGGCTCAAGCTGCAAGGCCGCGGGCTGGACCCC

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ACGCCACCGGCTGCGTTCCGCGCCATACTGTAAGA GGTATTATTCAAGGTCGTAGACGCTTTCATGAC GGCTGGTGCTCGGTAAGAATTTCCCACAGTCGC AGTGCGTCGTCTGGACTTATCGCCTCATCTTCG AGAACAGAGACCCCAGAAACACCCTGATATCGC GCGGCAGATATTCCAGCGCCGCGGACTTGGGAC GGCATCCACCATGCTACAGAGGCTTGGTATGAC CCCAGATTCGTGTTGCCGGTGGCCGACTTGTGG GCAACCAGCCGTTAGCGCGGCCAGCCTGTCGGC TGGCCTGCGTGGTAGTCGCTGTCCAACTCGCTTC 2 GGTTTTCCCCCGTACGCGCGGGGACGAC CAGCGAAAAACGACAAGGAAATCGAGACCTGG CCCGACAGCCAGGTGGTTGCCGGTTTCTCGGAA GACGGATCCTTACGAGACCTGGCCGCCGGTGGA CGTTCCAGTCTGTCGCTCCCTCGGGGATCTCAA TAGCCCCGCTTGCCTGCCAGTCCTTGCGCCAGC CAGGAGCAGGCATGGCTATCTATCAC GGGTTATGGGCCTCGAGAATGTGCTCCTCGCCG CAAGGAAAATCTCGCGAGGAACCCTCTTTGATG CGGTATCTTTAGCCTTGGCAACCAGATA GCCCACGAAGTGGTAAACCACGAAGTGGACAGA CGCCAGAAACGCTGCGCGGACACGTATTTTCTG Bacterial Species comments No DR and Spacers Acidithiobacillus 3 CRISPRS 1 GTCGTCCCCGCGTACGCGGGGGAAAACCG caldus TGGGCATCTCCCAATCGCGCGCGCAGGTGTGC ATCC 51756 GCTTCGAGACCGACGCGACCGTGGTGCAGGCC GGATCAGCGGCGTACTCATCCACTTGTGGGCC TACAGTATGGCGCGGAACGCAGCCGGTGGCGT ATCACCGGGACAAAACCGGGCGGCG CTCCGGACTCCGCTCGTACCCGTCATTCACC CATCGCTATACCAATGCGCAAGGGGCGGACCC GCCTTGAGCTCCCTGTTCCGCCATGTGGAGGA GGCGCTGCGGTGGGGGATGACATTTCCCAAAA TACGCGGCTCATGCACACCATTCCAGCGATGG AGAAAGCAGGAGATTGGAGAGCGTTCTCTATT CGAGCCAGCACCCGACTCTTGATAGCGAATCT CAACCGTACCGGACCCCGCGCCGCCCACGCTA GTCGATATCAGCGGAAACGCTTCGGACATTGC CAAGCGGCCAGGTCTCCCGTCATGCTCAAGAA TACACCATGGCGCAAATAATCGACTTTCTGGCC 2 GCAAGGGGTTGCACCCTGCAAGGG GCAAGGGGTTGCACCCTGCAAGGG GTCCTGCGGACGGCACGTCTGCACCCT CACTTTGTCTTTACAGGTAT….. AGCCAGAGGCGTTCGTGATACGTCTTACAGAC

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3 GTCGTCCCCGCGTACGCGGGGGAAAACCG TGGGCATCTCCCAATCGCGCGCGCAGGTGTGC GCTTCGAGACCGACGCGACCGTGGTGCAGGCC GGATCAGCGGCGTACTCATCCACTTGTGGGCC TACAGTATGGCGCGGAACGCAGCCGGTGGCGT ATCACCGGGACAAAACCGGGCGGCG CTCCGGACTCCGCTCGTACCCGTCATTCACC CATCGCTATACCAATGCGCAAGGGGCGGACCC GCCTTGAGCTCCCTGTTCCGCCATGTGGAGGA GGCGCTGCGGTGGGGGATGACATTTCCCAAAA TACGCGGCTCATGCACACCATTCCAGCGATGG AGAAAGCAGGAGATTGGAGAGCGTTCTCTATT CGAGCCAGCACCCGACTCTTGATAGCGAATCT CAACCGTACCGGACCCCGCGCCGCCCACGCTA GTCGATATCAGCGGAAACGCTTCGGACATTGC CAAGCGGCCAGGTCTCCCGTCATGCTCAAGAA TACACCATGGCGCAAATAATCGACTTTCTGGC Bacterial Species comments No DR and Spacers Acidithiobacillus 2 CRISPRs 1 CCTTTCATCCCTGCGCGTGCAGGGCAGAC Ferrivorans ACTAGGACGCCGACGGGCACCCCAGAGTGTGG WGS GTAAACCTGCGCCACGTAGCGCCCCCGTCCAT AAGACAAGTTTGCTCCTGCCATGACCCCCGAG AGTCAAAGGCCAGGATAAGGAGTTCTTCACCA CAGCGGCTGGTAGAGCAGCTGCGCCGATCGTT ACAATAATCCACGTTTTCATTTCAGTTTCCTT TCAACCCCAGAAACCGCGGAAGATCAATATCC GGCCAGGGGGAAGGCGGGGCGTCCAACGCTTG GGTTTGATGGTCGCCCATACCACGCGGGCAAA CTTTGCGGGAAGAACGGTTGGCGCTCATCATC AAACGCAGGCCCGTGTTCCGGGTCAGCGCCTT ATTGCCTGCGATGGCGGAAGCCGTGCCGGTAT CAATCCGGCTCTACCGGAACGACCGCATCCTT GTATTCTGCCCGGATTCCAGGGGACCGCCATC GGATGAGGACCAACGCGATGCGCTGATGGATG GTAGGCAGGAACCGGGAAAGGAGGACCATAAG GCAGGCTGTGCTAATAATCGCTGTAGCCTTTA

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2 CCTTTCATCCCTGCGCGTGCAGGGCAGAC ACTAGGACGCCGACGGGCACCCCAGAGTGTGG GTAAACCTGCGCCACGTAGCGCCCCCGTCCAT AAGACAAGTTTGCTCCTGCCATGACCCCCGAG AGTCAAAGGCCAGGATAAGGAGTTCTTCACCA CAGCGGCTGGTAGAGCAGCTGCGCCGATCGTT ACAATAATCCACGTTTTCATTTCAGTTTCCTT TCAACCCCAGAAACCGCGGAAGATCAATATCC GGCCAGGGGGAAGGCGGGGCGTCCAACGCTTG GGTTTGATGGTCGCCCATACCACGCGGGCAAA CTTTGCGGGAAGAACGGTTGGCGCTCATCATC AAACGCAGGCCCGTGTTCCGGGTCAGCGCCTT ATTGCCTGCGATGGCGGAAGCCGTGCCGGTAT CAATCCGGCTCTACCGGAACGACCGCATCCTT GTATTCTGCCCGGATTCCAGGGGACCGCCATC GGATGAGGACCAACGCGATGCGCTGATGGATG GTAGGCAGGAACCGGGAAAGGAGGACCATAAG GCAGGCTGTGCTAATAATCGCTGTAGCCTTTA Bacterial Species comments No DR and Spacers Acidithiobacillus 4 CRISPRs 1 CTTTCATCCCCGCATACACGGGGCAACC ferrooxidans GTCTTTTTTTGCGGGTGGAGGCGCACACCTTGC strain DLC-5 AATGGCTTCAGCCCCATCGCCCAACCATTCAGC TCGGCCATGTGTCGACGGGCGTAGGCGTCGGCA TGACGGGCGTTGTGGACGCCCTGCGCCACTAACC CAGGCTCCTTGCTTGTATCAGGAGCCTTCATTG 2 GTATCGCCCGGCTTATAAACCGGGCGTGGATTGAAAC CAGTTTCCAGTTTGAGCATATAACTGAGCGTCATGT AATTGTATTAAGCACCGATTGCCCATAATTGGATTG CCGGTTGCATTCACGAATGCGCCGATCATTTCTCAA TCGGCTTCGGGCGCGTGGTATCCGCATTTCATCCC TCCGTATCACTGTCAAGCGCCAGAATCCCTAATAT AATTCGTGCCACTTTGAAAGCGACATTGGCAATCA AGCTTGGCCCTGAGAGCGTGTAAGGCGTCACGG TTGCTTGTCTTTCATATCGTGGCCATCCCCTTGG CAATCTCAGAGAAGATAAAGATAACCCCATTAGT AGAAAAACTCTTGAATATCTTCCAACCAAATAG GCGCTGAAGTATTGGCCACACTTGTTTGCCCGGCG ATGCCAGCGGCAGCCGTCGTCCTCAGCGTCGCAG AGATGGTGCGGCGGTGGCATCTGCCTGGGTGGTGA TGGGAAGCTGGCTCTGAGTTCACGTTGCCCGCTG TATTTGCAGGGACTGGGGGCGCTCAAGGCCAAGGTT ATCGGAACCACCAATGACGAAACGTGGAATCGA AAAGCGAACCTGGCGCAACTGGAGACCTATCTT 3 CCTTTCATCCCTGCTCGCACAGGGCA GACGGATACTCGGACTCCGCGCACTGGAGGCGTTA GACGTCAGCCCCAAACGGAAATCGGGGAAACGTTT AACAACAGGCAAAACTCCCGGTGCCCGCATTGTTG

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AACACGGGAACAGCGGTGCATTTCATGCTTACCAT 4 AACACGGGAACAGCGGTGCATTTCATGCTTACCAT CACGCACCGAAATACCCTGCTCCGTCTGCTTCC GCATTCCCATTAACTCAGCTCTGCTTCGTCCTC GCTGCTGGGTGGCGGCGTCACTATTCACAGCCCC GACCACATAACCCGTGCCGACCTGGTCATGATC ACCCACCAAGATCTACGACCT GCGGTGGAGCCTTTGGGCAAATGATCCACGAACC GGAGGGCTACGAGTTAGCCAATCGGATCGTCCTC CCGGAAATGTTGAAAGTTGCCAACCTGTTCTCAC TTTTATGCGCTCAAGCGGTTCGAGATCCGCAAC AAAACCGCACAGGTTTTGTGACTGTATCCATTGC GGAGCGCTTACCATCGACGATGCGGCGGGTTTG GTTAAAGCAGTGGCTTATTCAGCTACTCATTGG GGCGGTTGTGCCAGACGCACCAGAACCTATTAG GAGCGGGGGCAGCAGCCACGTCTGCCTGCCTCT CGTTTGCGGCTTTGCGCGCATTGGCGCAAGCCA CTTTTCGCAGCAATATGAAAGGAGTCAGTCATG TTCAGAACGCAAGCCAAGCTATGGCCACCATGC GCACCCCGCGAACCGGAGGCCACCCGCCCACC CGACCACTGGGCGCTGCGGAACCAAGGCATTAT AATACGACTTTTCCGAACGGCTCACCATGTCGC TCAGGTGATGGGGGAATGGCATAAAAGGCTTTC TTGGTGAAAAAGATCTTGGGGTTCCGGGTGTAG GGGAAAGAACCGGCCCCCAATGTCCGTACTGCC GACACGAACGAGTTTGAAACCGCGCCATGCATCC GTTAGGGCCAAATATTACGAGGAACTGACACAC Bacterial Species comments No DR and Spacers Leptospirillum sp. 4 CRISPRs 1 GTTTACGAGCCCGCTCAGTGGCGTGGTGACTGAGAC Group IV 'UBA BS' AAAGCATAGAGGCTTTTTAGAGCCTCGGGT CTAGAGGAGGTCGGGGAGAAGTGGGCATGT ATTCTTTCCCACCCAAGCCGCCGGAAGATG GCGAGAAGTTCCGGTCCGTTCTACATTGGG ATTTCGACCAGTGGGGCAAGGTGTGTATAA CTGTCTGTTGGTGAGGGTTCCGGTCAAACC CCGAGTGGCGCGAGAAGGACTACCTCTGAT 2 GTTTACGAGCCCGCTCAGTGGCGTGGTGACTGAGAC TATTGGACGTACGAGCAACTCACAGCAC CAGTTCCGGAAACCGGGCAACCTCCCGAAG CCCTCTTTTCGTATCCGGATACGTTTTATGG CAGTTTTTGAAATCGGGCAACCTCCCGAAG TCGCTGAAAACAGTACTGATTCCGTACCG AAAGAGTCGGCAACATGCCTTGGCTTGTCCT CCTCTTGGGAACACATGGGAACAATGGCGT CAGTTCCGGAAACCGGGCAACCTCCCGAAAG 3 GTTTTCCCCGCATGCGCGGGGGTGTTTCT CCGGTACCGGGAGTACATGTCAAAAGGACTGG

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ATTGCGTAACCAATTCGTCATATAACGACATG TTGATACGAGCTATCGGATAAGAGGCAATGTC GCTTCGCGACACAACCGTAGAGCGTTTGACGA TCAAGTGTCGAAAAAGAAAGACGGAACACATT CGTTGCAAGACGACGCCGGTCAGGTCTTTTCTG GACTGGCGGAAGAGAAAAGAGTGAAACTGCAA ATTTTTTGGAGAAATAAAGGATATATGCAAGAA 4 TTTCCCCGCATGCGCGGGGGTGTTTC CGATATTGCTGCCCTGGCGTATCCAAGTGCCAAGT TCTTGAAGCGTATCGTGAAGCGAAAGGACCAGGGT TCTTGAAGCGTATCGTGAAGCGAAAGGACCAGGGT TAATGGCCGGATTCAGATAATGGTAACGTCTTGGT Bacterial Species comments No DR and Spacers Leptospirillum sp. 2 CRISPRs 1 CGGTTCATCCCCACGAACGTGGGGAATAC Group II TTGAACTAGACGATACCATTTTCAATCACCCC TTCCATTCTCTGGACCCGGTTCAACCGTTCCTG GGCTTCCTGATTCTGGCCCAGGATTTCCAGTG ATGATCTTCGTCGCGCCGATCTTCCCGATAGA CACTTCCGGATGGCGTCCATGCGTTCCCCGTA TTTAACAGCATAATCCTTGATAAGAAACCCAT GAGGACAATCCCATGGCGCGGAGCGGTGCCTG CTCCGCACCTCCCGCACAGGCTGCAAAACCGG GGCTTCGACGTGCCCGACGTGGACATGCTCGT GAAGTCCGGTGGCACCAACACCCTCCAAGGAA ATCAAAATAGCGTCCCTGACATTGTTTCTTTC GCGATCTTATCTCGAAAGGAAAATAACCCATGT AATCCAATGCGAAGTTTATTCATAGACAATAT CATTTCCCGGACGATTCCGACCCGCTCGGAGG GACTTCCTGAATCCGGATGACCTGGGCACGGA TATATCAGCGAGCGGGAATTGTTCCTCATATC GCAGTTCGCTCGCGGGGGTGACGCAGGGGGTT TAATCCTCCCTTTCCTCGCAAAACCATTCCAG TCCCCCTCCCGCACCATCTCCGACCAGCCGGA GACCGGAGACGAGGTTCCCCAGATTGGTATTG GGCACAGAGTTCGAGCGGAGTTCCCTTGTGGT GATAATAATTTGAGCCAGTGCAGCTAACAAAA ACGATATGAAGGCCCGGGATCTCTCCGTAGAC ATATCAAACACACCGAACCGGAAGTTCTCTCG TCTCCGGCATACTGAAAATAACGGAGCTTGAT CCCGACAACTACAAGGCGGGCATTTATGACGG TGGTCGATGTCGTCGTAGTAGGGATTCGGTCC GGGGTCCGAAGACTTCAAGAAGAGTGCGACAA TCGTTCAAGTCATGGTTGTCCCCGACCTAATC GTTCATTCTGCGAAACACCGATGGCAACCATT GCCACAAGACGACCCCGAGCAGGGCCAGGGCG TTGGACATTAACCCTGCAGCAATACGCCAGACG GCAATTAAAATCAACCTCCTGTCGGTGTGACG GCGCCCGGCACCGTATGGAGCTCCCGTTGAAC

113

TCATACGGCCCTATCGCAGAAGGAACCCTCGA TCATACGGCCCTATCGCAGAAGGAACCCTCGA ATAATGGCTCGGAGATGAGGGAATCGAAGCTC GGAACCGGTTCTGACATCCTGGCCTGCTTCTG GGAACCGGTTCTGACATCCTGGCCTGCTTCTG GCCGCGTCATCCACGCGGCCCAGAATCATGAG ATTAATTACAGTCTGCGCTTGTTCCTGTTTGG CGAGTTTGGAGTTGTCAGACGTATCACAATAA GCCACCGGGAGGAGGCACGCATGATCCGCGAT TCCATCGTTTTACCCACCATTAATGATTAACTA TTCATGATTCGGAAAAGTATATCCTTCTATAA GGAATCCGGTTTTTCGCGGATTTCGACATATG GCGGCGGTTCCGGCGGTCAGCGTAAGAACACA TTCGCCTCCCGGTGTGCCGCGAAGTTCAGATC GACGCCAAGGTTACCCAGGTGAGCCTTGATAT GTATCCAGCGGCGGGGAATGCCGAGCAGTACG GACAAGAAGCGGTCTGTGCGGCATGACCTCGG TCTCGGACGAGGCGTACGGCTACAAGGTCGAA TATATTACTAGGATCTTCGGTCACCCACGCCT TTTTCCGTCGGGCAACTGTTTCTCCGGATACT GCTGTAATAACCGGGCTAGACATGGAGGCTCC GTGGCGGGAAGCACCACGGGAACCGCCTACGA GATGGACTATATCGCCCTGCCGCAGTGCGGGA ATCTGATTTTTCTTTCCGTATTGCGCATCTTC GTGAAGGGCTGGCAACGCCGCATTGAAATGGC TATGCCCCAGCCTGCCTCTATGCCCCGGCCTG CTCTTTCAAGAACCTGATCGATTTCTGGATGT TTCCCCAGATTCCAGCCATTGATGTGCAGAAG TCTTCGCGTGGGCAGACGCCAACGTCGCCCGG GTCGTCGACGAATGCTCCATGATCGACTCCATG TTTCTATCGCTCGAAAAGCATGGGCAAGATAT GCTCCCGTTGGTCCCAGCACCTCGATCTCGAG GTTGACGTTCTCCGTTTTCTCGGTGAACATGG TCCTTCCACCTGGGCCTGAAGCATCTTGTTCG GAAGGCGTCTTTGAGAGCATCGGTTGGGATGT TCTGCGAAGAAGAGGTTCCAATCGTCATCAGC GCCACGGAGGGGCCATATTTCTTTTCCAGTTC GAACTCCGTCAGGGGGTGGGAGTCGTGTAGCA 2 CGGTTCATCCCCACGAACGTGGGGAATAC TTGAACAGTTCCTTGCCGATGGAGAAGAGCGT TTTTACCGGAATTTCCGGAACAAGTCTCTCAG ACGCTCAAGTCACGAGAGGGTCAGGAAGTCGT ATTATTGTCCCCCCATATTTAATTTCCTGTTT CAGGACGGGCTGAATTTCCTTCGGATAGATGG AGCGTCGCACCCGAAAAAAACATTGACTGGAT GCTTTCAGCCTTGTACGAGAGAAAGGAGAAGA GATCTCGGCGAATACGGGACGAACGATTCTCT TTCAAATGCGGCTCCCATCGCCGGAAGATTTT

114

CTCCCAACCTTCCCCCGACGAACGCCCTTTCC GCTCCGAACATCTGGACAAACGGAGCGAGCGA GGTTGACCAGCCGTTCCGCCAGTTCTTTCCGG GCTCCCGTTGGTCCCAGCACCTCGATCTCTAA TCCATAAGCCGCCCGGGGATCTTTGGCGGACTT GCCGGTATCGTACTCCACGCGGAGGGAGTCGGG ATGGACTCGCCTGCCTCTATGCCCCCGGCTGA TCGTCAAAGCCTACGCCTGGTGTCTGTCCCAC GGTGGCATCCATCCAGTCCGTATACAAAAAAG TTCCGAGCTGGGAGAGAAATTACCCTGCGGTG Leptospirillum sp. 1 CRISPR 1 GAAACACCCCCACGGGCGTGGGGAAGAC Group III TATCAAGATCCCATCGACGACAGTCTCACAGTA CCAACGATGGATGCGAACCAAGAATGGGATTCG CCACTCCAGAGGGTTGAGGGCTTCGTTGGCCGC GAACGAGCAGCCCATCTGGATCCAGTGGACGGA TGCCTCGAATGCGGCCTCTGCCGTGGTCAAGAA GCCATATACCCTTGGGTATCGACGAGGAACGTG TGATCCCCTTTCCTGTCCTGGTGGGCCTTCTGG CACGGGATGGTTCTGGGGGGCAATATCAAG CGATCCGGACCAGGTCGAGAGGAAGGGCGATCA ATACGAGCGGACCGAAGCTGGCAAAATTTGCCA ATCGAGTTTCTCCGTATCGTCGGGTGGGACGAG CTGATAACCCAATTTTGGCTCTCTCTGCCCAGA CCACCGGAAATTTGCAGGCCTTCGGCTTCTTGG CCTGCTCCCGAGATGTGCTCGGACTGCTTCGAG TCCCTTCCACCTTCCGGCCTCCGGATCCATCCA CGCCCTTATTCGACCTGGACAGATCCAAAATGA CACCGTCACCGAGACATCCTTGGCGAGCGTCAGG CAAACTATTCTCACGGCCTTCAGGGACGGCTCG Bacterial Species comments No DR and Spacers Leptospirillum sp. 1 CRISPR 1 GGTTCATCCCCACGAACGTGGGGAATAC Group II 'C75'. TTGAACTAGACGATACCATTTTCAATCACCCCC TTCCATTCTCTGGACCCGGTTCAACCGTTCCTGC GGCTTCCTGATTCTGGCCCAGGATTTCCAGTGT ATGATCTTCGTCGCGCCGATCTTCCCGATAGAC CACTTCCGGATGGCGTCCATGCGTTCCCCGTAC

115

Acidiphilium sp. 1 CRISPR 1 GTGTTCCCCGCAGGCGCGGGGATGAACCG PM, ATTGACGGACTCAAGGAAGTTGCCCGCACCTG DSM 24941 GCATGCCGCGCTGATGCGACGGTCCCATTCGT GCCGATTAGTGCGATTCTGTTTTCAACGGAAG TTGAGCACGATGACGGTGCCCTGCGCGGTCGT GCGCGCAAGCGCAAGGGCAACAGTGGCACGCA CGCAATTTTCGTCCCATCCCTCGGCGCGGTCT ATCGCCCGACATAGATCATGCGGGCGCAATGC GTTGGGGGCAGCTTCCTCGAACGTGAAATAAT GCCGAACGCGACCGGAAACACGAGGAGGAACT GCGATCAACGCGATCAATGCGGTTGTTTCAAA GCATGAGCACGGTGGTCGCGCCGCTGCTCCTC GCGCCACAAGGGCGCTTTTGTCTGGGAAGGAT GCACTGCGGCGCTTACGATTGCTGCGCCCGCT CAGGATGTATGCGCCGTGCTGCTCGGCTGTGA GTTCACAATGGGAGTGGACGCTTCCATCGTAC CGCATTCGCGTCGATGCGCGGAAATGGCTGGT CCTCAGCCCGACCCGGTGACGTTTCCACACGA AAATTCGGCTTTTCTGCCACGTTGGCGCTCAA GTCACGGGTCGCCGCCTCCGGAAACCGCTCCG AAATCCCCGATGATAAGATCGGTTTCACAATC CAATGGAAGCCGAATGACCGTTCTCATCACCG AGCGATCCGCCGACGTGGAGGCCGTCCGGCAG GAACCGGCCGAGGTCGAGGAACAGGAGCAGAT CTGAAATTCCTTCGCCTGCGCGGCGTGCATCC GACAGCCGGACGGTGCTCGAGGTCCGGCGCAA AGCTTGCCCGCTCGCTGCAGCGCGACGCCAGG GCTCCTCGGTCAGGTTCGAGACCGCCTCGGTC TGATGCCGACGCGCCTCAACAACCCGTCGCAA CCGATGTCGGATCGGAGCCCGGGCCTGCGGCG GTCGCTTAGCCGCGTCGCACGCAAAGACGTGC TTTCAAAACGTAGGGGTTTCCATCATCATCCT CGGACCATCCGGCGATGGGAGACGGGCGAACA TATAGGCGGAGTCGGACAACTTTGGGCGTCGG CTGACGGGGCAGGCTGACGGTCCGTATGACGA TAAAAACGGAGATTTAAAATGCCCTACTGTGT GCTCGATATTTGAGCATTCGTCTGCGCCCCTA ATCAGCGGGCGCCGGGCGACCTGGCGCTGATG GAGGCGTTGATCGCATACGCGAGCGCCTGCAT CGTCAGTGCGGTCGTGGTGCCGAGAAACGCAT CGACTGGTATTCGCGGAGCCATGCTTCGGGCG GGCTGCGGCTTCTTGGCCTGCGCATGCAGGAA AGGAGGCTCGCCGAGTTCCCGCGCCCGCTTGT AATTCGGCCGGATTGCTGAACCCGAGCAGTCG ACAATGAAGCGGGCGATGGCCTCGGCCATGAA CCCGCAGCGGATGGGCCGCGATACAAAGCTAT TTCGCGTTCTGGCCGGCGTAGGCTTCGGTGAC CCGCGCATCTACGGCGCAGGCATCATGGTCAC

116

CCCTGAAAATGCTGCAGCAGGGCGACCCGGGC CACCCGCAGGACCGCGAGCCGTGCCCATTTCC GGCAATCTGGACCGGGGACATCGCGAACTGGAC ACCAACACGAACACGATCACGCTGGCGGACGC TGTCATGACGAAAGTGTCGGTGGCGAGGTTGA TCGCAGCGCGGTTCGTCGCGGCGGGCGGCCAG GTCGAGAGGCTGGCGCGCCCGGTGCTTGCCAG CGACAAATATTTCGCTGGGGCTGGCGCTCGAT CCGAGGATGCGCGGCGGCGGCGTGCTTCGGCG CTGGGCGTCTCGGTCGAGGCGGTGAAGCGGGC CGGATTGCCGCCTGCGCTCGTCCACGCGTTCA GTCGAGAATCTGCTCCTGTTCCTCGACCTCGG CGTAGGATTGAACCCGTAGTTCTGCTCATTCG TCAGAATTTACGGTAATGTCTACCATGTAGAT TGTCGAATGATATCGTAGGGTATAAACCATGC CATCACAACAAGCGCGGGGTAGTCAATCCGCG GGTTTGAGGGCAGTCAGGTAGCGCAGGGGCAC GATACGAAATCGGACCGGGCGCCAGTCTTCGC CGGACCGTGTCGGTTGCCTGGCAGACGGTCGC ACGAGTATTTCCCGTTGCTTGTCGTTCATTTC CGGCCTGAATCCGAATGCGGTGAATTCTGCCA AGCTCGTCGGCCTTTTCATTCCCGCGCAGGGG ATTAATATCGCGCGAAATAGCAGAAACAGTGT CCTCTTGATTCTTCCACCATTCCTTCGCGCCC TCGCGGTGCAGATCAATTCCATCTCCCACCGT CTGTCGCACCACACGGCGTGATAGCCCCATGA AGATGATCAATACGCCGGTGTTTTGGGTATTT AGAGGTTTCTGATAATGGCTCGTTATTTGTGG ACAAGAATTTCAAAGGTCTTCAGGACTATTTC GAGGACGCGCCGGAGGCCGTTCCCGCACCCGC GATCTCCGCACTGCTGGCCGGGATCTCCAGCA ATCGAGATCGACCCCTTTGGCGACATCCTTTT ACGAATTTGCATGAGAAGCGGCGAACTTAGAA TCCAGCGTCCAGCAGGAGTGCACCCCCAGAAG CGGCCTTCCGTCAAATCAGGGTCCTTCAATCG ATCGGTGCCGTAGTCGAATGAGGTTCCGTTAA GATAGACCGGGATATGGTCATCCGCCCGCCTT TAGCACGCGATGTATGCCACAAGTGGGAACGG GATCAGCAGCACAAAGAATGCGTATTCCCAAA GTCTGATTCTCTCGCAATTGCGATCTCGCCAT CCATCGTTTCTGCTACCGGCTTTCCCGAGGCG TTCTGAGTCGGAACGACTTCGGGGCCTGTCAG TTCTGGAGAGTGTGCCGAGTTCTTCGATCCCC ACGGGAGGGCCAATTCGGCAACGCCAAACAGG GTTTTTGATCGTCACAGAAAAACGCTGGATTG CGGGCGCAATCAATTCGCCATGCGCTTTGAAC

117

Bacterial Species comments No DR and Spacers Acidianus hospitalis 6 CRISPRs GTTGCATCCCAAAAGGGATTGAAAG TATAGCAATATTCCTCATTGTTTTAACACCTTCTTAGCA ACTTCTATGAAACTATTGCTACCCCATAGGTCATACTT TTGCATAAACACCGCCTGCCAGTATGAGGTTATTAGCCAG CCTATAGTGAAATAGTAATTTGCTATTTTACTCAATT ATATTGGAAGGGGCTTTGTCTTACCCAATCTTTAGAA TTGTTCCGCAAGTACGTTTGTCTTGCCTTCTTATATTAC TAATTATTGAATTATCGCGGTCAAAATGAACGGTAATAT AGAACAATTTCTCATCCTATCGGTTCCCGTTAAAATTTAA GGTTTTTTCACTTCTTCAGGAGTAGATAAAAAAATCTCC TTGAATTTCTCACCAGCGTCCTTAAGATTCATCGCTCTCATC AGACACTATATCCTTTTATTGAAAATATCGTCATTATGT CAAAGCACGCAAAGTCACTAATAGACATACCACTACCCA TCCCTAAGATTTTTAGCAATAAATTAAGGTATGTTGA TCGGTAGCGTCTATAGCAAAGCACATTCCATCAGAAG TAACGTATTGGTCAGGGCTAAGAACTTTCCTATATGCA AAGTTCGACCCGTACGCGGTATTCGGGAGGACATTTGC TTAACAGCATGCTTGTGATAGAATTGTTATGTTTTGCA AATAAAATCGGAATAGCAAAACCTATTGCACTCAATTCT GGTACTATCTCTACTTGGTCGCATACAGCGTTTATATCT TCTAATCTCTTCAAGAAGTTTCATCTTCACGCTTTCTGG ATGAACTCCCAGACCTTGACCTTAACACGTGCGTAGTC AGACAAGAACAATGGCATTGCCAACTTCATATAGGTAAAC ATGACGGTCTCAGATAACGGCTGTATCGTCACAACAGCA ATCTTAGCTTCAGCGTTATTTACAACGATTTTTATTTTC TAGAAAGCTACGGGATCCCCATGGAGCTAAGAGGAATC ATAACTCTACAATATTCCATTACACATTGACTTATCAT TAAAAAAATGTAATATCTATTCAGACCCATTGAAATAGT ATATTGTTGAAAAATAACGGAAAACCTCTTCAGAATAT AAAAGGTGATGCGAATGGATCCCCTAAATAAATCTAAATC ATACGAACTGTTTACAAGGTTAATTAGAGAATACAACAA AGATAGGAAACCTTGGTCTTGCTCCATAAAGTTCTGTGTCT CTCTCTCAAGATCGGTATATATCTTTTTGACCAAGCAAA TTGATGTAATGAAGTCAACGACTTTTTTGGCAACTGAAAATC AATACCAATGAGTGAGTGAAATAGAATATATCTCCTCT TGAAGGAATTACGTCGGTTTAAGCAAATATACGTGATG TTATAACAACCAGTAAAGACATTCTCTATTATTTTTGAAA TAAACCTCGACCTCCTGGGTTTAACAGTGCTGTTCTCAA AGTTTCCTCATATACGTAATCATATTCCGCCTCTAAGTCC TTAATTATAACATCTTCATTCTCTTCCTCATCATACCC ACTATTACTTTCGTTAAATTCTACTGCAGTAAGCTATC GCTTTTTCGATTTGCTTTTTAATCAATTCAACAAAGGT TAGAAGCGTGAAGAAAATCGTTGTAATTGATGAGGCT GGATTTAATTTATTTGGATATATGACTACTAATATATC TGTGAGAAATTGAGTATAAGTTGTACAACGCGATTAA GTGTAGTTCTCTGGGTCAGAGCAATATTCGCCAAATTTT TTTTCACTATAGAAAAGTACTGGATAGCCTTGAACTTCAT

118

ACTGTTGTTTAGCCTCTTCCTCCTTCTGAGCCCATTCCTC CTATACTTCCGTTTTCATCTTTAATCCTACTTCTAACCC ATAACTTTACAAGTTCTTCTAAATTCTTTTGAGTCTGC TTTATAGCTATTCTGTTAACCTTTATGTTGGTGTTGCACA ACCTATTTGCGTTAATAGAAAGGAGAAATTCCCGAATT TTACAGTAACGTTTATTGTTAATTCGTATTTATTGTCAT 2 CTTTCAATCCCTTTTGGGATGCAAC GGAGAGGGTGAAAAAAATGGGGAAAACGTATCTTGTAAA TCACTTACTTCAATATTTTTTGAAAGTGAAGAAACGCC CTTTAAAATCGCATAGCGAATTATTCTCAAGTTTGATC TGGAACATTTGTAAAAACAGGGCATTTTATGCCTTTACC TGGAAAGGGAGGCGGCGCATATTTTTGGGCCTTCAATTA GAAAATACGAAATCATTTATGCTGAATTTCCGCTTAATAA GGTTCAAAACCAGCCTGGTATAATGAACCAAACCAGGT AATTGAAGTGAATGGTACAAGATATTGGATAAACACGCC GAATTATCCGAAAGATGTACAAGATGTTTTTAACATT… AGATAAACACGCC TACTATTTGTGATGAACATGAGCTTTGTCTTTCAAAATA TCCCACTTAGGTTCGTCCAGGTTCATGAACCTCGGTGAT GCTTCTTTCAAATACTCCAGAAGTTTAGGGGAGTTGTCT 3 GTTGCATCCCAAAAGGGATTGAAAG CCGCTTAATATCACAATTGTTCCCAAATTTTCGACTT…. CAAATTCATAACTT CCGCTTAATATCTTAGTATTAACTGAACCTCTGTAACC GAAATAGACACTGAATAAGTATTGTCTGTTGTCGGTTA AATATATAGAAGAGTGGTACCAGTCCTAGTAATGTGGC TGGGATTGGGTTTCACTCACACCCATTCACCCCGATTT ATTTTTATTGTGACATTAGATAGCGTAATACTGTAATGA GCAGCTTTTGCAGCAGTAGCTTGGGATAATCGCAGTTT AATTCAATTTTACCTAACTCTCCTATTTTGACCTCTCTTTT 4 GTTGAAATAAGGAAGAACTGAAAG TCGACGACTATCTCATCTTTAAGTACTTGCCTTGCAGTCTTC TTCTCTTTTAGCCTTCTATCCCAGGGATTAAGTA AATCCAGTCAAACCAGCTAATAGTTTTCCTGAT TTCTTCTTACTGAACATGAAGAGACCGTATACCC GGATTGTTCTGGATCCATTGACTCTGAAGATTACTA AAAAACAAATCCCCAAATAAATCCCCAAAATAATAC GTATCCCTACTGGATTTGTCACCACGGTATAATTTC TCTTTATCCTCTTTTATCATTTGTATCCCCATAC CTTACCTTTATTCCTGCTATTTCCCCTTCTACCT CAATAGCTTTCGCCAATTATCAGCCACCGGATCAG TTCTCTTAGTATTTTTACATATCTCAACGAAAAA AACAAGGACGTATTGAACACCGTCAAGAGGGCAA ATCTTGCAACCTTGTTCTGCAGCTTGGCAATAA CAAAAGGAAGGTGGAGCATACCTGGGACTACAGTGT TATCAATATGCCGTTTTAGAGAATTTCCCATTAC TTTTTAAAGTCGTAATTAACGATTATTATCGCGT CTACGTTTCCGCCCTACTATCACTACAATATCAT

119

TAATGAGTTTATCAGGCTTAGTATGTCATCAACAG TCAACTGCTCTCCCTATATAGTAAGAAGCCTCTCTTT AGAGAACGTGAGGATAAAGGAAGTCGATGTTGA CACTTCTATAGAGCTGTAGCAGACAGCCTTTATAC CTAGGCTTTTAGGGCATAAACGGCGTGCTAACTGCT AAATCGGGAAAAAGCCCGGGTATTTTTGACGTGTT TATATAACGATATAATAACGCTCTAAACTAAGGG ATCACACGGAAAGAAAGTCGTAGTTACCACCTTA GGAACTCCAGAAAAGAATGAGGATCAGACAGTCC GCCCTGTGCTAATACAGGCGCTGCAAGAGTTTGC CTATTTGCCAAGTGGATTAAAACGAGTTGGACTA AAATATTATTTTAGAGGTGAGAAAAATAGACGAA TCTTGAAGGGCGAGGTTTGTCGTTCGTTCAGTCA ATTCCAGTCTATCAAGTAGGGGATCCCAAAGACC TGAGATATTGGTGTGGGATATGGGTTTAAAGCAAT TTTGCCGTCTTTTTCTTTATAGTTGTACACCAGT GCTACTGGACTTAAATACGTCGCTTCAATTAAAC CTGTTGTAGTTTTCGTGTTAGTATTATCCTTAACTA GTAGATTTGGACGTATTACTTAATATCGTGAAGA ATATACTGGACTAACCATGGTGCTTACTTCTTAAT TTCTAATCCATCATTTATTCTAACGCTAATAACTA GTGCTTGAGTCTATCAAATACCCTTCTCTGGAT 5 CTTTCAATTCTATAGTAGATTATC AATTCTTTGCTGATATATTTTTCAATCCATTGCCTTTCTCT TTCCCGTCGATCTCAATTGCGTTAGTGCCTGTGAGCGTACCAAC TATGATACAGCGGAACCAGAATTATTAGCACAGTTGGCTA TACGTTTCCTACTTCGGCGTCTCTCCAGCACCTTACGGTGG TTGTCTTCGGCGTAGAGAGTTACTTTAATCGTTTCAAATTG CTCTGTAAGTATCACACTGAAAGTGAACGGATAGTTGGGATT GCTGAGATACTTGTTCTTCTTTATGGCGCAGTTATTTCT CAAGAGAAAGCTTTTTAAACCCCCTTTCCCTTTTTCTCATG 6 GATAATCTACTATAGAATTGAAAG AACCAGTTGGGCAGAAAGTTTAAATACCAGTCCGCGAAGAG TATCTGTTACAGTATCCTTGAACTTTTCAAATCTAGTAAT AAAGATAAGAAGATTGTAATTAACGTTGCACATGATGAACC TTTTTCTTCGTTGACTTTATTCTCCATCTCAGTTTTATTTC Bacterial Species comments No DR and Spacers Acidimicrobium 2 CRISPRs 1 GGATCACCCCCGCCTGCGCGGGGAGCAC Ferrooxidans CTCGCCAGCAACGTCACGGACCACACCGAGGTC DSM 10331 CGAAATCCAGTTGAGCCAGGCGCAAGTTCAGGC CCCAACGCACTCCTCGTCCGCACGCCCGAGGAG TCAGTCAACGCGGCCAGCCGCGCGCAAGTACGG TCGACGGTGATCCCCTCAATCTCGGTCTGGCCG CAGAACCTGGCCATCCAGCAGTCGAGCGTCGCC TCCGTCATCGCGTCCTTTCTTGAGTCCTGCTGA CCCGCCGCGACCGACAGCCGCAGGCGATCTTCG GACGTGGGTGCCCCTCACCGACGCGAGCGGGTC

120

TATCTATCCACCGAACCTGGCGAGCGCCCAGGT AGCTTGCCCTCAATCTCCAGCAATCCACGTACC AGATCCCACACAAGGACGCCCTCGGGGAGCTGG ACGCGGGGTGGTACGGATCCATCCTCAACGCGC ACGACCACCACCACGTCGTCGGGCTTCGGCTTC CACGCGCGGATTGCTCATGTAACGCCACGCGGC CGACCATCAGAAGCTTCGGTTGGCGACCGAGAA CGCTTTGCAGCGGCGTGAGGCCGAAGGTACTGC AAAAGCCCGACGGGGAGTATTGCATGCGACGCC ACCCGTGAAGAGATGCGCTCGTGGGTAGAGCGC CGGTAATGCCCACTTCTGTCTCCTTTCTGCTCAC CTCACCTGCGCGGCGCGCTGAGCCAGGAATGTC TTGGGCAGCTCAGGACAGTAGACCTCCGCTGCG ATCGCCCTTGGCCTTGGCCTTGGCTGCCTCAGC TCGGCGTCCTTCGCCACCCAGTTCGGGAGGTGC ACGGTGGCCTGGGGGCTGTCGCCGGGCTGGATC TACTTGACCACCATGTGCAGCACACAGATACCA GGGTCGCCAGCGCGGAGGGCGTCGAGGATCGGG

121

2 GGATCACCCCCGCCTGCGCGGGGAGCAC TACTTGACCACCATGTGCAGCACACAGATACCA GGGTCGCCAGCGCGGAGGGCGTCGAGGATCGGG ACGTGGGACCTCCAGATCGCCGGACAGACGACC TTGAGGGTGGCGGGTGAGGTACCCCAATGCGAG GAGGGTGACGCTCTCGACCGGATCGCGGACCTC GGCTACTCAGTGGTCAGTCTTGAGGAGACCCCG CCGTCGGCGACCTCTCTGGTTGCCTTGTATATC TCGAACAGCACGAGCGACGAGCCGACCTGCAAC CTAACGTCACATGGTATGTGGTGATGCTCAGGA TGCGATAAGCCATGGGGAGCTGTCGACCAAGCGT GGCCTCACCGGCCTCACCACGACCCGCCAAGTC TGCTGAACTCGTGATCGTGTTCCCCGCCAAGTA CGAAGTCCCAGCTCAGGGGCACTGGGGGAAAAA TGCCCGCCGATCCCGTAGCCATCGACCGGATCG ACCTCGTTGACCCCGAGGTTCTCCACAATCGTC CTCGCTCCTCCCTCTTCGTCCTCTCGTCCCCAC GGTAGGGGCCGTGCTCATCGCTGAGGGCGCTGG CCGTTCGTTGCCCGGGGCAACGCAGCCCACTGG CGCCGTTACCGATCACGATCCAACCGGGAAGCA TCGCGTTGATGACCCGGACGAGCTCTGGCTGGC TTGATGCAGACCAGTGCTGATCCGCGCATCGAC TGCCGTGGCGACCTGCGCGTCGTCGGCGTTCAG ACCATAGCGTCGAGGGGGTACTGCGGATGAGCA CTGCTATCGATGACTGCTCTCATGCTCTTCAGA CAAGTTCAGCTTCAGAATGCGTACTGAGTCGGA GTCAGTTGACAGATCGACTACCTGAGGCGACTC CCGTCGTGATTCTGTCCTTCTTCGGCGTGGTGA GAGTTGTCGAGGTGCATGTGCTCCGAGCAAGGG AGCTCGCGTTGCGGGTCGTCACCAGGCACGAGG CCCCAGTCGCCCGAGAAGCTGAGCTTGTCCGAG TCAACCGCGTGCCCCCCACCCGCGAGGCCAAGC GGAATCTTGACTACTTCACCATCCACTGCCTCC TCAGCCTGAGACTCTCTGATGATGGATACCGCC TACATTGCCTTCACTGGCCCGTACCTGACCCAG TGCTCCCGTTGCTGTCGCAGTGCGTTGGCCATG CCGATAGTCCCGAAGATCGGAGAGTATCCCGAA GTCTCACTCGGGAAGAGCTCGAGGAGTCTCCGC CCAACCCACATGACCAACGTCGGCCCGGTTCGA TTCCGTGTGCGGCCCGTACTTACCAGTCATCCC ATGTCGTCTGTGTAGGTAGTCACTTCTGCCACC Bacterial Species comments No DR and Spacers Ferroplasma 2 CRISPRs 1 ATTTCAATTCCTATATGGAATTATTTTAAC acidarmanus TTATTAGACAAACCAACTAATATAAAAGAAATGCTTA fer1 CTAAAAAAAGATATAAAGCTCATTTACCTAATTTTTC GGTGCTGCTGGATTCGATTTAGGAGTTCCTGAAAGC TTGATGAACAACGTTGTAATGACGTTTAAATTATTTTAA

122

CTGAAAAATTAAGGGATTACAAAAACCAGCTTTTAAAAG TGAGGGATTACATTTCCCCGTATCTTTTCCCGCCAGGGC CTTCTCGTTGGAGGTTCTCCATGCCAGGATATATCCG AATATCTTATAGGTCTCACTGCAACCGTCAGGGAATA AAAAAGAGTATTGTTCTGGTAAACTGTTGCACTTGC CGTGCCTCAATGCCAAGGAACAGATCCCTTGTGCCAA TCTGCACAGGGAATATCATGCCCAGCAGGTCTCCGT AGAAAATTCAACGGTTTCATGAAGATGGCGAGATAAT GTTGATTTTTTAAATGATTATGCCTTTTTTTGGTCTAG 2 GTGTTTAGTCTATCTATAAGGGTTTGAAAT AAAATAGGTTTTTACGGTAATGAGGGTTGCTGTGGAAAT TTTTCATATCTTTTGCCACCTCCGAATTTGATAAAT CGTAAACGGGGGGGTAATTAATACCGTGTAGAATATA TTGTCCTAAATCCTATCAATTCCTTTGTTTCCATTTTA TAACACCAAGTCCTAATAAATTATTCCATGCCTCTAA TCTGAGGCCTGATTACCTGAGGATTCTTGACCTTG ATAAAATCCTGGACTGTAAACACAATCCGAGCTGCCG

Thiomonas sp. 1 CRISPR 1 CTTCTCAATCGCCTGTGCGGCGATGAAC GATTTCCGCAAGAAGGTGAGCGACTTCGCCTC CCTTCGATCTGCAGCACATCCCAATCCAGAAT TACTACTGGCTCCAGCACGGCTGCAACCGCAT CGCATCAAGCCCCAGCCGCAGCGCGTCTACGT CCTGACTTCGGCCTTCTGGCCCATGCGGGAGT CCCAGTGACCCACATGCAGCCCTGAATCTGCG ATTTCGCCTCTCTCGTCATCACCCGGGTTTCT ATGCAGATCGGAGCCGCGACCGTTGGCGTCGA CCCTGCGTCGGTGAGGCCGTATCTACACCACG AAAGCCCTTGATGACCGGCCTGCTCACGCACC GTCGCAAGCAAGCTCGGGAGTGCGGGAATTTT GGTCCCACTCGCGCCACAGACAATCTCCGCAG AGGGTCTTGGTGTTCCCGGCCCGGATGGTGAT GCGCCCACGGGAATACAGGCTTGATCCTGCGC TCTGCCAGCCCTCTGGCACCTGCGCGGGTTGC TCATGTTGCAAAGGTAGTCGCAAGCAAGCTCG ATCGACCCGAATGACAAACGCCGGATCGTGAT CTGCGGCGGCTGTGATCTGGGCAGCCATTCAT TTGAGGTTCGGCACCACCTGGATAAGCATGTT GCTTCTTGGCGGCATGCGAGGCCTTCGCTGAC GCCCTGCTGTGGCGGAATGGTTCCGGCTGGCC AGACCGGATTCGACCGCGCCCGGCGGGCAGCT GCACGGCGGAAGTTATGGCACCCGCTGCTGTG GGTGGCGAAGTCGCCGGCTGTTTCGACCTGGT TCCTGCATCTCGGCCCACGCTTGGTCTTCAAT GCCTGGTGCTCATTCCCGGTATCGCAGAAGAT GCGCTCAAGGCATCCGTGGCATTCCCGGCCTC CGGCGCTGGCGTTTCTTGTCATCTTCCTGCTC ATCGAGGATGATTTCGAGAGCTTCGTCAAAGTT

123

TACATCTTGCGTCAATGGCGCGCGCTGGCATT GCATAGAGCACAGAATTCGTGCCGCACTCCAA GTGCCCCCCGAATGGTTGACCTGTCCCACGAT TGCAGGGTGCCGGCGCCGATGGTTACATTGGA GGTCCCCGAGGCGGTGATCTGGCCAATGATCA GCGCAGCAGTGGGTCCACGATGCGCAGGCCCG GCGGTCTGCCGGCTTCGTTGCCGATCCATCGT GCGGCGCGAGGCCGCCAGCGGGCGTACGGGGG GGGTTCGCGTCTCGGCTGTTTGAGGGTGGGGT TTTTGGTTTGCGCAAGGTGTCGGAATTCAAGT GGCAGGGGCTCGTGGACCTTGTTTCACGCAGC AAGCAGGGCGACCCGATCCCCGCCTCCCGACT GTGTTGAGGCAGATCAGGCGGCCGATTTTTTT GTAGCGGCTGCGCTTGCCCTCCTTGTGTCTTC CATTCGTGGCACCGCGAGACGAATTGCGGGGA GTGCAGCGTGACGAAGCCGTCTGGTTCCTCTT TGGTCGATTTCTATACGGCGGCGTGTCCTAGT GTTCGCCATCGACGTCAAACGCGCCCGCGCTC TTCAGGGAATTTGCGGGTGCGGTGTCGCGGGT GGAATCCCCCCCAAACGAGGGGGCCATCCCAG TTCTCGCTCAGGCGCGTCAAGGTGAAGGTGAT GCATTGAATTTGCGATCCAGCACGAACCCGTT GGATCGCGATTTTTGCCGATGGCGACCTGTCG CAGAACGCGGCGCTTGGCCGGTTGTCCGATAC ACATGATCGCCTATCCAGATGCGATGGTTCTG CCCTTGAGCAAGCAAATCGCCGCGGCCTTCAA CCATCCTTGCCGGTCAGCTCAACCTTGCTCGG GATCCGCCAGCGTCTTGGACTGCGCCTGGTCG AGCATGGGGGGCGGTCATCGTCCGACCAGTAG TCAGCGTGTCCGGCGCCTCCGGATCCCATGTT ATCTACGACAAGAACGGCGAGCCGGACAAGTC TTTACGCGCCTCCGCCGTTGAGCAAGCCACCG CCGGCCCCGTCGCCACACCCGGCACCAACGGA CGGTCAGTAAGCCCGGCGACGTTTGGCTGCTT CTAGCGGCGCATGCGCAGAAGATCGGCGATGC GATTCGCAAGCTGCTGATCAATGTCCCGCCGG ACGGCGATGCCGAAGATGCCCACTGCAAGCCA CTGGCGTGGCATCAGACATGCCGCGAGCTGCT GCGTGCAACCGTCGGGCGCTCTCGTGGTATCC AAGGCCCAGGCGCTGAAGGTCGGCTTCATGGA TAGCGTGTCAGGTTCAATGCGGATCGTGCGCA AGCCCACATTCAAGCAGCTGGTTAAGGATGGA GCTGTGTCGGTTCACGGCACCATGCCATTCGT TCACAACTGCAGAACTTCGCGGGACGTCCGAG GGCGGTGCGAACCGGGCGAGGTGTTCGGCATG AAAGCCGAGCTAACCCCCCGTCTCTGTAACAC GCTCGGCGGCTGCTTTCCATGCGGTGCCTGCG GTTGGCATCAAGTACGACACCGTGATCGCCAA

124

GTTTCCCGTACTCCTCGAACTCAGCTTGCATT CGCTGCCCATTCCGGGGAATGCGTGCATTTCG Bacterial Species comments No DR and Spacers Acidiphilium 1 CRISPR 1 CGGCGGCGGCGGCTCGGGC angustum ATCC AACGGCATCCAAAGCGGCTA 35903 GGCAGTGGCGGCGGCGGGATCGTCAT TTCGGCGAAGGCAACGGCGGCGACTTTGGCAG ATCGCTATCGGCGGCGGCAGCGGTACTGTT…. GTCAAGGGCGGCGGCTCGGGCGGGAACTA GGCGGCTTTGGCATAGTTGGCAGCGGCTTT… ATTTTTCCCGGACCCACCACCTATTACTT

Table A. 2. Matches of inferred amino-acid spacer sequences from Acidianus hospitalis to the viral database. Query coverage (QC) is the percentage of query sequence covered by the hit considering internal gaps as positive. Pairwise identity (PI) is the percentage of pairwise residues that are identical in the alignment, excluding gap versus gap residues.

CRISPR-Spacer Description QC PI E-Value 5-6 conserved archaeal viral protein 100 100 5.62E-02 [Sulfolobus monocaudavirus SMV1] 5-6 hypothetical protein 100 100 6.01E-02 [Sulfolobus monocaudavirus SMV2] 5-6 hypothetical protein 100 100 6.70E-02 [Sulfolobus monocaudavirus SMV3] 1-34 hypothetical protein ATSV_C175 100 100 9.85E-02 [Acidianus tailed spindle virus] 2-11 Phosphatase 92 100 1.25E-01 [Acidianus tailed spindle virus] 5-6 hypothetical protein 100 93 2.26E-01 [Sulfolobus monocaudavirus SMV4] 5-6 hypothetical protein STSV1pORF54 100 93 2.61E-01 [Sulfolobus virus STSV1] 1-3 hypothetical protein ATSV_B343 95 100 3.06E-01 [Acidianus tailed spindle virus] 5-6 hypothetical protein STSV2_52 100 93 3.94E-01 [Sulfolobus virus STSV2] 5-3 hypothetical protein 97 100 6.31E-01 [Sulfolobus monocaudavirus SMV4] 5-6 hypothetical protein STSV1pORF54 100 86 6.48E-01 [Sulfolobus virus STSV1] 5-6 hypothetical protein STSV2_52 100 86 6.94E-01 [Sulfolobus virus STSV2] 5-6 hypothetical protein 100 93 7.39E-01 [Sulfolobus monocaudavirus SMV4] 5-3 conserved archaeal viral membrane protein 97 100 7.53E-01

125

[Sulfolobus monocaudavirus SMV1] 6-3 Glycosyltransferase 95 100 8.45E-01 [Acidianus tailed spindle virus] 5-3 hypothetical protein 97 100 8.46E-01 [Sulfolobus monocaudavirus SMV3] 1-48 hypothetical protein 90 100 8.67E-01 [Sulfolobus monocaudavirus SMV4] 4-14 Uncharacterized protein MJ0770 92 100 9.41E-01 [Sulfolobales virus YNP1] 5-6 hypothetical protein 100 79 9.47E-01 [Sulfolobales Virus YNP2] 5-6 hypothetical protein ATSV_D1241 100 86 9.52E-01 [Acidianus tailed spindle virus] CRISPR-Spacer Description QC PI E-Value 5-6 hypothetical protein 100 86 9.63E-01 [Sulfolobus monocaudavirus SMV4] 5-3 hypothetical protein 98 100 1.26E+00 [Sulfolobus monocaudavirus SMV2] 5-7 hypothetical protein ATSV_A138 100 92 1.40E+00 [Acidianus tailed spindle virus] 6-2 hypothetical protein ATSV_B2246 98 87 1.48E+00 [Acidianus tailed spindle virus] 1-31 AAA+ ATPase 93 77 1.64E+00 [Acidianus tailed spindle virus] 2-12 viral integrase 92 100 1.71E+00 [Acidianus tailed spindle virus] 2-12 hypothetical protein 92 100 1.76E+00 [Sulfolobus monocaudavirus SMV4] 6-4 hypothetical protein 95 85 2.25E+00 [Sulfolobus monocaudavirus SMV4] 2-11 hypothetical protein 92 83 2.62E+00 [Sulfolobus monocaudavirus SMV4] 5-6 hypothetical protein STSV2_52 100 79 2.73E+00 [Sulfolobus virus STSV2] 5-6 hypothetical protein 100 79 2.96E+00 [Sulfolobales virus YNP1] 5-6 hypothetical protein 100 79 3.10E+00 [Sulfolobus monocaudavirus SMV3] 1-23 hypothetical protein 98 100 3.19E+00 [Sulfolobales virus YNP1] 6-4 hypothetical protein 95 77 3.61E+00 [Sulfolobus monocaudavirus SMV3] 5-6 hypothetical protein ATSV_D1241 100 79 3.71E+00 [Acidianus tailed spindle virus] 4-14 Uncharacterized protein MJ0770 92 82 3.89E+00 [Sulfolobus monocaudavirus SMV3] 126

4-14 Uncharacterized protein MJ0770 92 82 4.29E+00 [Sulfolobales Virus YNP2] 1-3 hypothetical protein [Sulfolobales virus YNP1] 95 85 4.43E+00 2-12 hypothetical protein 92 92 4.69E+00 [Sulfolobus monocaudavirus SMV2] 4-14 conserved archaeal viral integrase 92 82 5.21E+00 [Sulfolobus monocaudavirus SMV1] 5-6 hypothetical protein STSV1pORF54 100 85 6.22E+00 [Sulfolobus virus STSV1] 1-24 hypothetical protein ATSV_C70 98 100 6.76E+00 [Acidianus tailed spindle virus] 1-23 hypothetical protein [Sulfolobales virus YNP2] 98 92 8.61E+00

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Table A. 3. Matches of H. neapolitanus C2 spacers to viral database.

Family E Spacer Description QC PI Normal host Value Podoviridae cytosine methylase 25 Salmonella 100 100 1.03 [Enterobacteria phage epsilon15] anatum putative C-specific methylase Siphoviridae 25 100 100 1.54 [Escherichia phage K1-ind(1)] Escherichia coli putative C-specific methylase Siphoviridae 25 100 100 1.60 [Escherichia phage K1-dep(4)] Escherichia coli hypothetical protein Siphoviridae 10 HMPREFV_HMPID9847gp0032 Pseudomonas 97 82 2.68 [Pseudomonas phage JBD25] aeruginosa Podoviridae methylase 25 Sulfitobacter sp. 91 90 3.09 [EBPR podovirus 2] Strain 2047 Siphoviridae terminase-like family protein 10 Pseudomonas 97 82 3.41 [Pseudomonas phage JBD67] aeruginosa Siphoviridae terminase-like family protein 10 Pseudomonas 97 82 3.41 [Pseudomonas phage JBD18] aeruginosa putative terminase, large subunit Siphoviridae 10 [Pseudomonas phage Pseudomonas 97 82 3.41 vB_PaeS_PM105] aeruginosa DNA-cytosine methyltransferase Myoviridae 25 91 100 3.58 [Salmonella phage SEN5] Salmonella sp. methyltransferase, partial [Salmonella Myoviridae 25 91 100 9.02 phage SEN5] Salmonella sp. Myoviridae methyltransferase, partial [Salmonella 25 Peduovirinae 91 100 8.91 phage SEN4] Salmonella sp. putative C-specific methylase [Escherichia phage K1-ind(3)] Siphoviridae 25 91 100 7.24 putative C-specific methylase Escherichia coli [Escherichia phage K1-ind(2)] putative C-specific methylase Siphoviridae 25 91 100 1.54 [Escherichia phage K1-ind(1)] Escherichia coli Myoviridae methyltransferase 25 Edwardsiella 82 100 4.27 [Edwardsiella phage eiAU-183] ictaluri Myoviridae phage methyltransferase [Edwardsiella 25 Edwardsiella 91 100 1.54 phage eiAU] ictaluri

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Family E Spacer Description QC PI Normal host Value Myoviridae hypothetical protein SfMu_28 10 Mulikevirus 97 82 5.67 [Enterobacteria phage SfMu] Shigella flexneri Myoviridae conserved hypothetical protein 10 Mulikevirus 97 82 5.25 [Escherichia phage D108] Escherichia coli Siphoviridae terminase-like family protein 10 Pseudomonas 97 82 3.41 [Pseudomonas phage JBD67] aeruginosa

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