MIAMI UNIVERSITY

THE GRADUATE SCHOOL

CERTIFICATE FOR APPROVING THE DISSERTATION

We hereby approve the Dissertation of

Ryann Michelle Brzoska

Candidate for the Degree: Doctor of Philosophy

______Dr. Annette Bollmann, Director

______Dr. Mitchell F. Balish, Reader

______Dr. Rachael M. Morgan-Kiss, Reader

______Dr. Donald J. Ferguson

______Dr. Melany C. Fisk Graduate School Representative ! ABSTRACT

THE EFFECTS OF LONG-TERM EXPOSURE OF AN ARTIFICIALLY ASSEMBLED MICROBIAL COMMUNITY TO URANIUM OR LOW PH

by Ryann Michelle Brzoska

Uranium-contaminated environments contain microbial communities capable of immobilizing uranium. There is evidence that some bacterial communities are capable of immobilizing higher concentrations of uranium than individual species. However, the interactions between bacterial species contributing to increased uranium immobilization are not understood. Therefore, the goal of this study was to identify interactions between species in an artificial community and assess their influence on uranium immobilization. Bacterial species previously isolated from the uranium-contaminated subsurface at Oak Ridge, Tennessee, were characterized both individually and in a mixed community in the presence and absence of uranium or low pH. Growth of individual bacterial strains in the presence of uranium or low pH revealed two Sediminibacterium strains, Sediminibacterium spp. OR43 and OR53, with different degrees of tolerance towards uranium. The main physiological or genomic difference between the Sediminibacterium strains was the sensitivity of Sediminibacterium sp. OR43 to uranium concentrations ≥ 200 µM uranium. Sediminibacterium sp. OR53 was chosen along with Caulobacter sp. OR37, Ralstonia sp. OR214, and Rhodanobacter sp. OR444 to be a part of an artificially assembled community. The productivity of the community was assessed by monitoring the optical density and the abundance of each species in the community in the presence or absence of 200 µM uranium at pH 4.5 (pH4.5) or 7 (pH7) for 30 weeks (~300 generations). At pH7 and pH4.5, all strains were present, but the strain tolerant to the lowest pH, Ralstonia sp. OR214, was the most abundant. The presence of uranium selected for the uranium- tolerant strains, Sediminibacterium sp. OR53 and Caulobacter sp. OR37. Moreover, when a subculture of the consortium at pH 7 with uranium (pH7U) was transferred into pH7 without uranium, the uranium-sensitive strains did not recover. Re-isolated strains of Caulobacter spp. OR37 and Sediminibacterium spp. OR53 from the pH7U condition showed increased growth in coculture that did not correlate with an increase in uranium immobilization when compared to individual strains. Taken together, our results indicate that commensalistic and competitive interactions may develop between microbial species and impact growth and uranium immobilization, which are important for microbial communities considered for the purpose of bioremediation. THE EFFECTS OF LONG-TERM EXPOSURE OF AN ARTIFICIALLY ASSEMBLED MICROBIAL COMMUNITY TO URANIUM OR LOW PH

A Dissertation

Submitted to the Faculty of Miami University in partial fulfillment of the requirements for the degree of Doctor of Philosophy Department of Microbiology

by

Ryann Michelle Brzoska Miami University Oxford, OH 2015

Dissertation Director: Annette Bollmann, Ph.D. TABLE OF CONTENTS List of Tables iii List of Figures v Acknowledgements vii Introduction 1 Chapter 1. Physiological and genomic analysis of two novel Bacteroidetes strains Sediminibacterium spp. OR43 and OR53. 21 Chapter 2. The effects of uranium and low pH on the composition and productivity of an artificial community in a long-term growth experiment. 60 Chapter 3. Physiological and genomic comparison of strains re-isolated from an artificial community in the presence of uranium. 91 Summary 149 References 162 ! !

! ii! LIST OF TABLES Table Page 1. Genome sequencing project information for Sediminibacterium spp. OR43 and OR53. 29 2. Differential physiological characteristics of strains Sediminibacterium spp. OR43 and OR53T in comparison with type strains of closely related species. 36 3. Fatty acid profiles of Sediminibacterium spp. OR43 and OR53 strains in comparison with type strains of closely related species. 38 4. Influence of the nitrate concentration (mM) in the medium on the growth -1 rate (day ) and maximum biomass (max OD600) of Sediminibacterium spp. OR43 and OR53 after two days. 40 5. Influence of the pH in the medium on the growth rate (day-1), maximum biomass

(max OD600), and lag phase (days) of Sediminibacterium sp. OR43 after two days. 44 6. Influence of the pH in the medium on the growth rate (day-1), maximum biomass

(max OD600), and lag phase (days) of Sediminibacterium sp. OR53 after two days. 45 7. Influence of the uranium concentration (µM) in the medium on the growth rate -1 (day ), maximum biomass (max OD600), and lag phase (days) of Sediminibacterium sp. OR43 after two days. 46 8. Influence of the uranium concentration (µM) in the medium on the growth rate -1 (day ), maximum biomass (max OD600), and lag phase (days) of Sediminibacterium sp. OR53 after two days. 47 9. Genome properties of Sediminibacterium spp. OR43 and OR53. 48 10. Number of genes associated with the general COG functional categories. 49 11. Presence (+) and absence (-) of genes involved in nitrate metabolism in Sediminibacterium spp. OR43 and OR53. 50 12. Enumeration of genes potentially involved in the adaptation to low pH in Sediminibacterium spp. OR43 and OR53. 52 13. Heavy metal resistance genes in the genome of Sediminibacterium sp. OR53. 53 14. Membrane associated phospholipid phosphatases in the genome of Sediminibacterium sp. OR53 and the percent identity (%) of orthologous sequences in Sediminibacterium spp. OR43, C3, and S. salmoneum. 56

! iii! 15. Primers used for measuring the relative abundance of Caulobacter sp. OR37, Sediminibacterium sp. OR53, Ralstonia sp. OR214, and Rhodanobacter sp. OR444. 67 16. PCR conditions (temperature (°C)/time (s)) and validation of qPCR. 68 17. Maximum uranium concentration and minimum pH value in the MS medium that allowed growth of the bacterial species as pure cultures. 70 18. Influence of 0, 200, and 300 µM uranium on the growth rate (h-1) of the re-isolated and ancestral strains after two days of exposure. 104

19. Influence of 0, 200, and 300 µM uranium on the max OD600 of re-isolated and ancestral strains of Caulobacter spp. OR37 and Sediminibacterium spp. OR53 after two days of exposure. 105 20. Influence of 0, 200, and 300 µM uranium on the length of lag phase (hours) of the re-isolated and ancestral strains of Caulobacter spp. OR37 and Sediminibacterium spp. OR53 after two days of exposure. 106

21. Growth rate and maximum OD600 (biomass yield) of ancestral and re-isolated Caulobacter spp. OR37 and Sediminibacterium spp. OR53 as a coculture in the presence of 300 µM uranium. 110 22. Uranium concentration (µM) in the presence of re-isolated and ancestral strains of Caulobacter spp. OR37 and Sediminibacterium spp. OR53 either individually or in coculture after seven days exposure to 300 µM uranium. 111 23. Read mapping coverage of re-isolated strains to the ancestral genomes. 132 24. Genetic variations in the re-isolated strains of Sediminibacterium spp. OR53 compared to the ancestral strain. 133 25. Location of amino acid changes in re-isolated Sediminibacterium spp. OR53 strains. 134 26. Genetic variations in the re-isolated strains of Caulobacter spp. OR37 compared to the ancestral strain. 135 27. Location of amino acid changes in re-isolated Caulobacter spp. OR37 strains. 137

28. Positive effects (+) of the OD600 (growth) in cocultures of ancestral and re-isolated Caulobacter spp. OR37 and Sediminibacterium spp. OR53 in the presence of 300 µM uranium after two days. 139

! iv! LIST OF FIGURES Figure Page 1. Uranium speciation as a function of pH. 2 2. The S-3 ponds and the surrounding contaminated areas at Oak Ridge. 6 3. Schematic of efflux transporters involved in heavy metal resistance. 11 4. Mechanisms used by bacteria for immobilizing uranium. 13 5. Maximum likelihood phylogenetic tree based on 16S rRNA gene sequences of Sediminibacterium spp. OR43 and OR53. 32 6. Transmission electron micrographs of (A) Sediminibacterium sp. OR43; and (B) Sediminibacterium sp. OR53. 34 7. Growth rate (day-1) of Sediminibacterium spp. OR43 and OR53 in the presence of (A) different pH values; and (B) uranium concentrations. 41 8. Influence of 0-200 µM uranium on the growth rates (h-1) and length of lag phase (h) of Caulobacter sp. OR37, Sediminibacterium sp. OR53, Ralstonia sp. OR214, and Rhodanobacter sp. OR444. 71 9. Influence of pH on the growth rate (h-1) of Caulobacter sp. OR37, Sediminibacterium sp. OR53, Ralstonia sp. OR214, and Rhodanobacter sp. OR444. 73

10. OD600 (as a measure of the total biomass) at the end of each week during the long- term growth experiment. 75 11. Relative abundance (%) of the 16S rRNA genes of Caulobacter sp. OR37, Sediminibacterium sp. OR53, Ralstonia sp. OR214, and Rhodanobacter sp. OR444 in the artificial community at (A) pH7; (B) pH7->pH 4.5; (C) pH4.5; and (D) pH4.5->pH7. 78 12. Relative abundance (%) of the 16S rRNA genes of Caulobacter sp. OR37, Sediminibacterium sp. OR53, Ralstonia sp. OR214, and Rhodanobacter sp. OR444 in the artificial community at (A) pH7; (B) pH7->pH7U; (C) pH7U; and (D) pH7U->pH7. 80 13. Relative abundance (%) of the 16S rRNA genes of Caulobacter sp. OR37, Sediminibacterium sp. OR53, Ralstonia sp. OR214, and Rhodanobacter sp. OR444 in the artificial community under all conditions at the beginning of the

! v! experiment (week 0), at week 12, and at the end of the experiment (week 30). 82 14. Concentration of uranium (µM) in medium at pH7U and pH7->pH7U communities of the long-term growth experiment. 85

15. Influence of 0, 200, and 300 µM uranium on the change in OD600 over time (growth) of the ancestral strains of Caulobacter sp. OR37 (OR37A) and Sediminibacterium sp. OR53 (OR53A) and the re-isolated (OR37 Is8, OR37 Is14, OR37 Is28, OR53 Is7, OR53 Is18, OR53 Is70) strains. 102

16. Influence of 300 µM uranium on the OD600 over time (growth) of (A) ancestral (A); and (B) re-isolated (R) Caulobacter spp. OR37 and Sediminibacterium spp. OR53 strains grown individually and as a coculture. 108

17. The OD600 and the uranium concentration in the medium over time of individual ancestral and re-isolated strains. 112 18. Whole-cell transmission electron micrographs of re-isolated and ancestral strains of Sediminibacterium spp. OR53 in the absence of uranium. 115 19. Whole-cell transmission electron micrographs of ancestral and re-isolated strains of Sediminibacterium spp. OR53 in the presence of 300 µM uranium. 117 20. Whole-cell transmission electron micrographs of ancestral and re-isolated strains of Caulobacter spp. OR37 in the absence of uranium. 129 21. Whole-cell transmission electron micrographs of ancestral and re-isolated strains of Caulobacter spp. OR37 in the presence of 300 µM uranium. 121 22. Elemental analysis of the ancestral Sediminibacterium sp. OR53 strain grown in the presence of 300 µM uranium. 123 23. Elemental analysis of re-isolated Sediminibacterium sp. OR53 Is18 strain grown in the presence of 300 µM uranium. 125 24. Elemental analysis of ancestral Caulobacter sp. OR37 grown in the presence of 300 µM uranium. 127 25. Elemental analysis of re-isolated Caulobacter sp. OR37 Is14 strain grown in the presence of 300 µM uranium. 129 26. Micrograph of uranium associated with re-isolated Caulobacter sp. OR37 Is14. 145 27. Model of the development of the interactions between Sediminibacterium sp. OR53 and Caulobacter sp. OR37 in coculture. 158

! vi! ACKNOWLEDGEMENTS I must first and foremost thank my advisor, Annette Bollmann. I was accepted into the microbiology department with a passion for learning but without any previous research experience. Annette graciously accepted me into her lab and fostered my skills as a microbiologist. My progression in the graduate program was not always easy, and with her guidance I learned not only to be a stronger scientist but a stronger person. I am truly grateful for all the opportunities she gave me. I also must thank my committee members Rachael Morgan- Kiss, D.J. Ferguson, Mitch Balish, and Melany Fisk. Additionally, I would like to acknowledge Gary Janssen who filled in as a committee member during my oral comprehensive exam. I appreciate their commitment to challenging me to think critically about my research to become a better scientist. I couldn’t have gotten this far without the love and support from my parents. My mom, my dad, Steve, and Lisa have all been dedicated to supporting my pursuit for higher education. I didn’t always know what I wanted to do or how I was going to do it, but they were willing to do anything they could to help me. I owe my family so much for helping me become the person I am today. I love you all so much. I also owe a thank you as well to my extended family that have encouraged and supported me throughout my graduate career. I wish my grandma, Nana June, and Papa Bill were able to see me complete my journey, but I am thankful for all of their love and encouragement. Graduate school was a new and exciting challenge for me, but I could not have made it through without my lab mates, Chris and Liz. I was fortunate enough to form strong friendships with the people I worked with everyday. Although, I shouldn’t say too much to boast his ego, I must thank Chris for being patient with me. We both started in the lab on the same project and with his previous research experience, he took the initial command of the project and taught me a lot. I also owe a lot to Liz for showing me around the lab, helping me with protocols, and just being a great friend to talk to. Numerous undergraduates have also come through the lab, but I would especially like to thank Zack and Hannah for their contributions to my research. Additionally, I would like to acknowledge Teo, Rhea, Austin, and Britton. You all made working in lab an “interesting” experience in your own way but also an incredibly fun experience. Outside of the lab, I met an incredible number of awesome people. Although I could write so much about each of them, for the sake of space, I would like to thank altogether and in no

! vii! particular order: Heather, Amber T., Amber B., Jenna, Bill, Dan, Sarah “Mer”, Wei, Morgan, Jason, Ben, and Jamie. I also must thank friends that have supported me for what seems like forever: Stephanie, Kara, Cat, and Nikki. The one thing I never expected to find in graduate school was love, especially the love of my life. Last, but never least, I owe a huge thanks to Steven for being my support, my colleague, and my best friend. I cannot even come close to expressing everything he has done to help and encourage me throughout graduate school and life in general. Thank you for always being there for me.

! viii! INTRODUCTION Uranium and the environment Uranium characteristics, prevalence, and distribution Uranium is a naturally occurring element found at low levels in 5% of all known minerals

[1]. It is predominantly found in the form of uraninite (UO2). Uranium can also be found as coffinite (USiO4), which is the common form in uranium ore and exhumed during uranium mining. The major deposits of uranium were created during geological events forming the Earth’s crust and are distributed all around the world [2]. Uranium exists in two states: reduced as U(IV) or oxidized as U(VI). When associated with minerals, uranium is typically in its reduced form and is insoluble and immobile [3]. Like any mineral, uraninite is susceptible to erosion. Erosion and general weathering of uranium- containing minerals allows for oxidation to occur, which releases uranium as highly mobile U(VI) [1, 4]. As a result, uranium is leached from the mineral and distributed into water and soil. As an isotope, uranium is predominantly found in the form of U-238 (99.3%), but it also exists as U-235 (0.7%) [2]. Uranium undergoes radioactive decay until it eventually reaches the stable isotope lead-206 [4]. The half-lives of U-235 and U-238 are 7 x 108 and 4.5 x 109 years, respectively [2]. Both forms emit low levels of alpha radiation. This type of radiation is rarely harmful to humans unless ingested due to its short wavelength and inability to travel long distances. As a consequence, uranium is more toxic due to its characteristics as a heavy metal.

Uranium speciation and influence of pH 2+ The uranyl ion in its oxidized form (UO2 ) has binding preferences to oxygen-containing groups [3]. As a result, it commonly interacts with compounds like carbonates, phosphates, and hydroxyl and alcohol groups. The binding preference of uranyl ions for a particular substrate is driven by pH [3, 5, 6]. The exact pH at which uranium tends to interact with a specific substrate varies depending on the amount of uranium present as well as environmental properties like 2+ temperature and pressure [3, 6]. In aqueous solution at pH < 4.7, UO2 is the dominant form + (Figure 1). At pH 4-7, the (UO2)3OH5 species is the most prevalent, with a variety of other uranyl species that persist in low abundance but are also associated with hydroxyl groups. At pH < 6, anionic phosphate groups preferentially associate with the uranyl ion [5]. As the pH starts to - increase above pH 6, (UO2)2CO3OH3 complexes form [3]. This trend corresponds with studies

! 1!

Figure 1. Uranium speciation as a function of pH. (A) Uranium speciation (%) between pH 3-9 Diagram adapted from [7].

! 2!

! 3! showing the dissociation of phosphate from uranium at pH > 6 [5].

Depleted uranium A major consequence of uranium enrichment is the excessive amount of waste produced. The majority of natural uranium ore only contains about 0.7% U-235. U-235 is the substrate used for uranium enrichment because it rapidly creates a chain of fissionable products capable of releasing more energy than U-238 [8]. To purify U-235, uranium is milled to extract the uranium from uranium ore [9]. At a chemical processing plant, extremely acidic or basic compounds are used to leach the uranium from the ore to purify it as yellowcake (U3O8) [9-10]. U3O8 is further processed in a series of steps to ultimately fluorinate the compound and form uranyl hexafluoride

(UF6), which is used as the typical starting substrate during uranium enrichment. As a result, over 99% of the UF6 utilized for enrichment is depleted uranium waste and contains < 0.7% U- 235 [10]. The depleted uranium is often stored at facilities equipped to contain the uranium long- term [11]. Depleted uranium is also sold to military and civilian manufacturers [12]. Because depleted uranium is about 1.6 times more dense than lead, it is advantageous for military use as armor protection on vehicles. In addition, depleted uranium is used to make ammunition, as the high density of this metal allows for deep penetration into protective armor. Civilians can also use the density of uranium to protect themselves against harmful gamma radiation that is emitted from x-rays, and as a balancing agent for airplanes and ships [6, 13].

Health risks associated with uranium People are exposed to uranium on a regular basis. Annually, it is estimated that the average human consumes 0.46 mg of uranium, mostly from drinking water, and inhales about 0.6 µg of uranium from the air [14]. Ninety percent of the uranium is expelled from the body over a short period of time via human waste [13]. Most health problems do not originate from acute exposure to uranium. Uranium poisoning results from the accumulation of the heavy metal in the kidneys, which causes nephrotoxicity [15]. In addition, uranium can damage DNA, which places exposed individuals at an increased risk for cancer [12, 15]. However, the toxicity of uranium changes depending on the uranyl species, amount of uranium, portal of intake in the body, length

! 4! of exposure, and general biokinetics of the individual exposed [12, 14-15]. Uranium is present at higher concentrations in some environments like Oak Ridge, Tennessee.

Oak Ridge, Tennessee The start of World War II instigated the formation of the Manhattan project by the United States government [16]. The purpose of the Manhattan project was to industrialize the uranium enrichment and the plutonium production processes to design nuclear weapons. Oak Ridge, Tennessee became one of the three main sites involved in the Manhattan Project and contributed to the building of the atomic bombs that were dropped on Hiroshima and Nagasaki [16]. The environmental impacts of uranium enrichment at Oak Ridge were not realized until the 1970s. Hazardous waste was either buried in shallow graves or deposited in unlined trenches [17-18]. The evaporation ponds containing liquid waste from the uranium enrichment process were not properly lined and leached high concentrations of heavy metals, organic solvents, nitrates, and radioactive isotopes into the environment [17]. In 2007, the Oak Ridge Integrated Field-Research Challenge (IFRC) was established with the purpose of studying biogeochemical changes occurring in the subsurface sediment and groundwater to elucidate mechanisms to stimulate bioremediation [19]. Since the establishment of the IFRC the Oak Ridge National Laboratory has found that bacteria offer an inexpensive and effective way to immobilize many of the contaminants present in the environment [20-29]. However, much still needs to be elucidated regarding the mechanism behind bioremediation pathways that these bacteria are using as well as the effect that biotic and abiotic factors have on the efficiency of bioremediation.

S-3 ponds In 1951, four unlined ponds (122 m x 122 m and 5.2 m deep) were built for the purpose of storing liquid nitric acid and depleted uranium waste at Oak Ridge, Tennessee (Figure 2A) [17]. The ponds stored uranium and plutonium waste, as well as sludge from other nuclear manufacturing and national facilities [18]. The waste in the ponds was characterized as highly acidic, with high concentrations of aluminum, calcium, sodium, potassium, and magnesium. Trace metals, including radioactive isotopes of technetium and plutonium, were also found in moderately high concentrations. In accordance with the environmental movement in the 1970s, efforts were made to reduce the nitrate concentration in the ponds (Figure 2A). In 1983, usage of

! 5!

Figure 2. The S-3 ponds and the surrounding contaminated areas at Oak Ridge. (A) The S-3 waste ponds during denitrification and capping; and (B) diagram of areas surrounding the S-3 waste ponds and average concentrations of select compounds in each area. Images were reproduced from [30] and [31], respectively.

! 6! ! A

! ! ! B

!

! 7! the ponds ceased [17-18]. The ponds were treated to reduce the acidity and nitrate concentration. Following neutralization and denitrification, the ponds were allowed to settle and the liquid layer was pumped out, treated, and deposited into the local East Fork Poplar Creek [18]. The sludge remained in the ponds and they were filled and capped in 1988 [17]. The absence of a protective lining within the S-3 ponds to prevent leaching into the surrounding soil resulted in subsequent uranium contamination in areas surrounding the ponds [18]. The hydrology of the Oak Ridge site in combination with the acidity of the ponds enhanced the solubility of the uranium, facilitating its movement into the soil and groundwater. Currently, the ponds are no longer the primary source of contamination [30]. Uranium contamination continues to be a problem due to absorption to and subsequent leaching from minerals outside the ponds. The IFRC has designated study areas along the contamination pathway from the S-3 ponds [31]. In these areas, they have established wells and boreholes to analyze groundwater and mineral content for contaminants. In addition, the IFRC uses the wells for in situ stimulation of natural microbial communities for bioremediation [32].

Area 3 The area exhibiting the highest concentration of contaminants is adjacent to the S-3 waste ponds. Area 3 contains a 10 m x 10 m field plot with multiple sampling wells and boreholes for monitoring ground water at different depths (Figure 2B) [31]. It was established not only because of its proximity to the S-3 waste ponds but as a way to study the hydrology and geology of the contamination pathway from the ponds. As a result, the ground water in Area 3 is characterized by high nitrate (9,000 mg/L), uranium (50 mg/L), tetrachloroethylene (3.3 mg/L), and technetium-99 (40 pCi/L) concentrations (Figure 2B) [17-18, 31]. Other metals like sodium, calcium, manganese, and magnesium are present in concentrations > 100 mg/L [17]. Area 3 maintains a low pH of 3.5. The combination of these contaminants makes Area 3 a hazardous but unique environment for studying microbial driven bioremediation pathways.

Bacteria and uranium Many heavy metals occur naturally in the environment and bacteria have mechanisms to utilize metals such as copper, zinc, magnesium, iron, and nickel as micronutrients and cofactors in intracellular processes [33-35]. However, there are many heavy metals that have no known

! 8! biological function in the cell such as lead, mercury, cadmium, and uranium. High concentrations of essential or non-essential heavy metals can cause significant damage to the cell. Initial exposure to heavy metals can increase membrane permeability resulting in the release of cellular contents as well as exposure of the intracellular components to the heavy metal [34- 35]. Once inside the cell, metals are capable of inducing oxidative stress through the formation of reactive oxygen species [34, 36]. Heavy metals can also compete with essential ions for binding sites on enzymes that impact intracellular processes [35]. Mercury particularly favors binding to thiol groups in proteins, which impacts protein conformation and activity [37]. Bacteria are typically able to mineralize organic compounds to an inorganic form, but this is not possible for heavy metals [38]. As a result, bacteria have evolved ways to exclude, immobilize, or reduce heavy metals to less toxic forms [33-36, 38-39]. Bacteria have different mechanisms to tolerate heavy metals and additional mechanisms that are specific to uranium. Some bacteria are able to decrease the toxicity of uranium by reducing soluble U(VI) to insoluble U(IV) in the presence of an organic electron donor. However, uranium reduction is an anaerobic process, and this project will focus on the mechanisms involved in the aerobic immobilization of uranium because the uranium does not resolubilize as easily as reduced complexes [40-42]. The following sections will discuss how bacteria tolerate heavy metals using efflux pumps for the extrusion of many biologically relevant metals as well as using mechanisms like biosorption, bioaccumulation, and bioprecipitation for immobilizing non-essential heavy metals like uranium.

Efflux pumps Bacteria have acquired transporters to maintain a low internal heavy metal concentration because even biologically relevant heavy metals can accumulate to toxic levels [35]. Most efflux pumps use a chemiosmotic gradient to transport metals across the membrane, but some transporters with higher specificity for their substrate require energy [36]. Some efflux pumps can transport different metals using the same transporter if the metals are similar in size, structure, or valence state [39, 43-44]. The advantage is that these transporters conserve energy associated with protein synthesis because the cell does not need to produce a specific transporter for each metal. However, it is often difficult to determine if certain genes are involved in

! 9! resistance to heavy metals because many heavy metal efflux pumps can also serve as transporters of antibiotics [33]. The major efflux systems can be divided into five main protein families: (1) the resistance nodulation cell division (RND) family; (2) the major facilitator superfamily (MFS); (3) the major drug and toxic compound exclusion (MATE) family; (4) the small multidrug resistance family (SMR); and (5) the ATP-binding cassette (ABC) family [39, 44-51]. Only the RND and ABC families are involved in heavy metal tolerance (Figure 3) [39]. Although not a member of one of the major efflux families, P-type ATPases are also important for heavy metal tolerance [44]. Substrates transported by members of the RND family are non-specific, allowing this family of transporters to confer tolerance to heavy metals, organic solvents, and antibiotics [39]. This system is unique in that it is the only efflux system to transport compounds across the inner and outer membrane without ATP hydrolysis (Figure 3) [39, 44, 48]. Other efflux systems in gram-negative bacteria typically transport across the inner membrane and deposit compounds into the periplasmic space. The ABC family of transporters and P-type ATPases differ from all other transporters because they require ATP hydrolysis for transport across the membrane [50-51]. Since ABC transporters expend energy during transport, they tend to only transport specific substrates and biologically relevant compounds [51]. P-type ATPases also use energy for efflux, and class IB pumps are well described as being involved in heavy metal resistance [51-53]. Like ABC- transporters, they are located in the inner membrane and transport biologically relevant and some non-biological relevant metals from the cytoplasm to the periplasm. P-type ATPases are almost exclusively exporters. They are able to transport metals bound to thiol groups and cysteine residues as well as metals in their ionic form [51].

Biosorption A common energy-independent mechanism for uranium immobilization is biosorption, where heavy metals passively bind to compounds on the surface of living or dead cells (Figure 4) [54]. Biosorption contributes to cadmium resistance when bound to the cell surface of Pseudomonas stutzeri [55]. The cell surfaces of gram-negative bacteria offer multiple substrates for binding that are dependent on pH [56]. The lipopolysaccharide (LPS) is unique to gram- negative bacteria and consists of three main parts: the lipid A region, the core and the O-antigen

! 10!

Figure 3. Schematic of efflux transporters involved in heavy metal resistance. From left to right, the resistance nodulation cell division (RND) family, the ATP-binding cassette (ABC) family, and the P-type ATPase. The RND transporter expands across both membranes and can transport metals located in the cytoplasm or periplasm outside of the cell using proton motive force (PMF). The ABC transporter is located in the inner membrane and is not directly associated with an outer membrane transporter. The outer membrane transporter can transport a substrate like vitamin B12 into or out of the periplasm. Energy is required in the form of ATP for B12 to be transported into or out of the cytoplasm. P-type ATPases also require ATP and can only export metals into the periplasm. Diagram modified from [51].

! 11!

! 12!

Figure 4. Mechanisms used by bacteria for immobilizing uranium. Bioreduction is an anaerobic process that reduces soluble U(VI) to insoluble U(IV) using organic substrates as an alternative electron donor. Biomineralization (bioprecipitation) is when uranium initially binds the LPS and then phosphatases are used to form uranyl phosphate complexes outside the cell. Biosorption results in uranium passively binding to negatively charged compounds on the cell surface. Bioaccumulation is the result of increased membrane permeability of the cell, which passively transports uranium into the cytoplasm where it is immobilized in polyphosphate bodies. Diagram adapted from [54].

! 13!

Anaerobic Aerobic

Aerobic Aerobic

! 14! [57]. The core can have a lot of variability depending on the organism and is the region thought to contribute to be associated with uranium binding in some bacteria.

Bioaccumulation The toxicity of heavy metals can increase membrane permeability and allow metals to passively diffuse into the cell (Figure 4) [34-35]. Metals can also enter the cell by using outer membrane transporters used by other biologically relevant heavy metals [39, 48]. As a result, bacteria have developed ways to sequester heavy metals to maintain normal metabolic functions in a process known as bioaccumulation [55-59]. Bioaccumulation allows for uranium to be immobilized internally while the cell remains viable. Uranium is sequestered in chains of inorganic phosphate connected by phosphoanhydride bonds known as polyphosphate bodies. When uranium associates with polyphosphate bodies, it no longer interacts with other proteins or DNA inside the cell. Not all bacteria are capable of utilizing polyphosphate as a uranium tolerance mechanism, but it has been characterized in Acidithiobacillus ferroxidans, Sphingomonas sp. S15-S1 and Pseudomonas migulae [56, 60].

Bioprecipitation/Biomineralization Bacteria have an enzyme-dependent method of immobilizing uranium know as biomineralization or bioprecipitation (Figure 4) [54, 56]. The enzymes involved are phosphatases, which can cleave phosphate groups from organo-, pyro- and polyphosphate compounds [40, 42, 61-66]. The mechanism of uranium precipitation has been best described in Citrobacter sp. N14 [63, 65]. The Citrobacter strain precipitated uranyl phosphate complexes with an acidic phosphatase, PhoN. PhoN was located in the periplasm but is also associated with the outer membrane as well as secreted in the extracellular environment [65]. In the proposed mechanism, uranium initially reacts with nucleation sites associated with phosphate groups in the LPS (Figure 4) [63]. PhoN cleaves phosphate from exogenous glycerol-2-phosphate and the phosphate is transported outside the cell [63]. Secreted phosphate and uranium bind and form uranyl phosphate complexes that extend outwards from the LPS. Bioprecipitation occurs in numerous organisms under aerobic conditions [40, 42, 61-67]. Typically, these precipitated complexes are made of uranyl phosphate, however, uranyl carbonate and uranyl hydroxides have also been found [56]. From pH 2-6, the uranyl ion is the

! 15! predominant species and it favors bonding with the negatively charged phosphate-containing compounds (Figure 1) [5]. However, enzymatic activity can be impacted by the location of the phosphatase (i.e. intracellular or extracellular) and the pH of the environment [64, 66].

Bacterial Tolerance to Low pH Acidic environments are common as a result of natural and anthropogenic influences. At Oak Ridge, Tennessee, the pH of the subsurface sediment is low due to leaching of nitric acid from the S-3 ponds [17]. As a result, bacteria have mechanisms to tolerate the conditions in this area. Typically, the intracellular pH of a bacterium is 7 [68]. This pH is ideal because it is optimal for most enzymatic activity and allows for the development of a stable membrane potential, PMF, and ion gradients. When the extracellular pH is lowered, the cell is exposed to an excess of protons that interferes with membrane gradients and transporters, and ultimately could destroy the cell. In addition, low pH elicits a response from multiple outer membrane sensor proteins resulting in transcriptional variability between bacterial species [68-69]. There are different genetically encoded mechanisms for tolerating low pH in bacteria, but only F-type ATPases were identified in the genomes of bacterial strains used in this study and will be described in detail.

F-type ATPases F-type ATPases are important for the tolerance of Listeria monocytogenes to acidic conditions [70-71]. The F-type ATPases are mechanistically similar to P-type ATPases. Instead of exporting heavy metals, F-type ATPases export protons [69-70, 72-73]. The F-type ATPase utilizes energy from PMF and membrane potential to synthesize ATP [73]. Under certain conditions, F-type ATPases can function in reverse to pump protons out of the cell through ATP hydrolysis [70, 74]. However, continual extrusion of protons can create alterations in membrane potential, resulting in inhibition of further proton removal [68, 75]. Bacteria transport potassium ions inside the cell to counteract changes in membrane potential due to extracellular proton accumulation, which subsequently decreases the membrane potential and allows for continual proton extrusion. The ability of the F-type ATPase to regulate proton concentration makes it an advantageous tolerance mechanism for acidic conditions.

! 16! Microbial communities The physiochemical properties of an environment largely dictate the composition of the microbial community based on the fitness of the species in the community to that environment [76-77]. The fitness of an individual species in an environment contrasts with that of a community, because the interactions between populations in the community can drive emergent properties in response to environmental disturbances like temperature, salinity, and invasive species [77]. In general, two or more populations interacting with each other in an environment define a community [77]. In these communities positive and negative interactions occur between different populations [78-91]. The presence of strong, positive interactions is important for the long-term stability and productivity of a microbial community [90, 92].

Positive microbial interactions Positive interactions are interactions in which the organisms involved benefit from the presence of the other species [79-81, 93]. Positive interactions exist when the benefit to the species involved is greater than the cost of maintaining the interaction [79-81, 93-94]. It is not always evident what causes a positive interaction to initiate. Species can be introduced into a new niche and form beneficial relationships very quickly. However, some positive interactions between species require extended periods of time to develop [78, 90, 92]. Other models suggest that positive interactions develop through other types of interactions. Harcombe et al. showed commensalistic interactions between bacteria could develop over time to form mutualistic interactions [95]. Taken together, positive associations allow bacterial species to persist in environments where either species may not have been able to persist alone. Bacteria may produce metabolic compounds that can be utilized by neighboring organisms. Metabolic waste can contribute to a commensal relationship because there is no cost to the producer but the surrounding bacteria may benefit from the waste [96]. A commensal relationship is often susceptible to environmental changes because metabolic products are dependent on specific conditions. Environmental changes can result in mutualistic relationships or become parasitic. In one example, a coculture of a Salmonella enterica ser. Typhimurium strain and a methionine auxotrophic strain of Escherichia coli initially had a mutualistic relationship in which S. enterica consumed acetate produced by E. coli while E.coli consumed methionine secreted by S. enterica on lactose medium [95]. When the coculture was grown in

! 17! media containing acetate, S. enterica strains containing the methionine-secreting genotype decreased because producing methionine was costly and S. enterica no longer required acetate produced by E. coli.

Negative microbial interactions Negative interactions are those in which one species adversely affects the growth of another species [82-83]. Bacteria that occupy the same ecological niche compete for the same resources [82]. As a result, bacteria must develop ways to more efficiently consume a resource, hinder other bacteria from utilizing the same resource, or expend energy using another resource. Some bacteria have highly specific transporters for a substrate allowing for more efficient uptake when nutrients are in low abundance. For example, a cellulose degrader can outcompete other cellulose degraders in coculture because of its enhanced ability to adhere to cellulose [97]. Other bacteria can use antagonistic mechanisms during competition for a niche or nutrients by using antimicrobial compounds that are often toxic to competing species [98]. Overall, negative interactions lead to greater genetic and metabolic diversity by driving bacteria to evolve to utilize other resources [82, 99].

Communities and long-term growth There is not an established length of time in scientific literature for differentiating between short- or long-term growth experiments. For clarity in this discussion, microbial populations maintained for multiple successive transfers (>20 generations) will be defined as long-term. In the laboratory, the bacteria used in studies of microbe-microbe interactions within microbial communities may not be indicative of their native environment. Bacteria often interact with multiple species and the absence of an uncultured species can drastically impact other interactions within the community [86-87]. Long-term growth experiments give bacteria time to acclimate to the tested conditions and the other organisms present. The extended time also allows for a more accurate portrayal of how bacteria associate with one another in the environment. Hillesland et al. showed how two unrelated species could evolve over 45 weeks (300 generations) to form a mutualistic relationship based on cross-feeding [90]. However, the interaction prior to 45 weeks could be interpreted as competitive based on the fluctuations in biomass from the coculture. The interactions in microbial communities containing more than two

! 18! species increase in complexity because positive and negative interactions are very likely to co- occur. Therefore, comprehensive understanding of different microbial interactions can only be identified through long-term growth experiments.

Project goals Microbial communities in the uranium-contaminated subsurface sediment at Oak Ridge, TN are capable of decreasing the concentration of uranium in situ and therefore offer an inexpensive method for the bioremediation of uranium. However, not much is known about the interactions between species in these communities or the contributions of these interactions to community productivity. The goals of this project were to elucidate the physiological and genomic differences between two Sediminibacterium strains with different uranium tolerances and to evaluate the impact of low pH or uranium on the composition and productivity of an artificially assembled microbial community in a long-term growth experiment. We performed whole genome sequencing on two Sediminibacterium strains isolated from the uranium- contaminated subsurface at Oak Ridge, Tennessee. Using these genomic sequences we identified and quantified the genetic differences between these two strains. Our comparison focused on annotated genes with functions potentially advantageous for inhabiting uranium-containing sediment. In addition, we performed an array of physiological and biochemical tests to identify other potential differences that could help characterize these two strains. We predicted that the difference in uranium tolerance between the two Sediminibacterium strains was a result of the presence or absence of genes related to uranium tolerance. Additionally, we predicted that the genomes of both Sediminibacterium strains contained more genes for tolerating low pH, heavy metals, uranium, and nitrate than other closely related Sediminibacterium strains. For the second goal related to evaluating the impact of low pH or uranium on the composition and productivity of an artificially assembled microbial community, we constructed a community consisting of four bacterial species isolated from Oak Ridge with different tolerances to uranium or low pH. These bacteria were maintained in the presence or absence of uranium at pH 7 or 4.5. The abundance and composition of the microbial populations was monitored throughout the experiment using optical density measurements and qPCR. Changes in uranium tolerance and the development of interactions were assessed by re-isolating strains after 30 weeks of growth in coculture and then growing these re-isolated strains in new mixed cultures in

! 19! the presence or absence of uranium. The uranium tolerance of the re-isolated strains was then compared to the growth of the individual and mixed ancestral strains. The re-isolated strains were also assessed for their ability to immobilize uranium individually and in coculture to determine whether interactions influenced the ability of the community to immobilize uranium. To determine whether the uranium immobilization mechanism influenced uranium tolerance, we used scanning transmission electron microscopy to visualize uranium localization on the outside of ancestral and re-isolated strains. Identifying genomic alterations in re-isolated strains compared to ancestral strains assessed the impact of prolonged incubation on the community in the presence of uranium. We hypothesized that bacterial species sensitive to uranium or low pH would contribute to the overall productivity of an artificial community in their respective conditions.

! 20! CHAPTER 1

Physiological and Genomic Characterization of Two Novel Bacteroidetes Strains Sediminibacterium spp. OR43 and OR53

Brzoska R. M., Z. Troyer, and A. Bollmann

Abstract Sediminibacterium species are members of the family Chitinophagaceae and the phylum Bacteroidetes. Members of several genera in the family Chitinophagaceae are abundant in environments contaminated with hydrocarbons and heavy metals. Here, we characterized the physiological and genomic characteristics of Sediminibacterium spp. OR43 and OR53, which were both isolated from the uranium-contaminated subsurface sediment at Oak Ridge, Tennessee. These strains were characterized to elucidate their potential to grow in the presence of uranium in addition to other contaminants present in the subsurface at Oak Ridge. Overall, the physiological and genomic characteristics were very similar for Sediminibacterium spp. OR43 and OR53. Both strains were not able to grow at pH < 4.5 or at nitrate concentrations > 50 mM. The growth limitations of these strains corresponded with the absence of relevant genes for acid tolerance and nitrate reduction. However, different growth patterns were observed in the presence of uranium. Sediminibacterium sp. OR53 was able to grow in medium with uranium concentrations up to 300 µM uranium (VI), whereas Sediminibacterium sp. OR43 did not grow above 200 µM uranium (VI). The genomes of both strains were sequenced. The average nucleotide identity (ANI) was 96.4%, indicating that the two strains were the same species and very closely related. Genes coding for a variety of heavy metal resistance proteins were found in both genomes. In conclusion, Sediminibacterium spp. OR43 and OR53 likely have adaptations to the presence of uranium compared to other closely related strains. Future work will focus on elucidating the adaptive mechanisms.

! 22! Introduction Closely related sequences to the genus Sediminibacterium were detected in contaminated environments with high concentrations of organic compounds such as polyaromatic hydrocarbons, oil, and organic solvents with or without high concentration of heavy metals [100- 109]. In addition, many sequences related to Sediminibacterium and closely related strains have been detected in freshwater biofilms, eutrophic lakes, salt water, wastewater, and in the guts of beetles and cows [110-118]. The genus Sediminibacterium is classified in the recently described family Chitinophagacae in the phylum Bacteroidetes. Previously characterized strains belonging to this genus and other closely related genera were isolated from water and sediments (Vibrionimonas, Sediminibacterium, and Hydrotalea), soil (Sediminibacterium) and donkey milk powder (Asinibacterium) [119-125]. Therefore, the attributes allowing for Sediminibacterium and other closely related strains to survive in contaminated environments are unknown. Sediminibacterium spp. OR43 and OR53 were isolated from the highly contaminated subsurface sediment at the Integrated Field Research Challenge (IFRC) in Oak Ridge, TN [101]. The ground water at the sampling site is contaminated with many different heavy metals such as cadmium, chromium, cobalt, nickel, and uranium, has a pH around 3-3.5, and has a high nitrate concentration (http://www.esd.ornl.gov/orifrc). The presence of members of the genus Sediminibacterium in contaminated environments suggests these microbes have physiological and genomic characteristics that enable them to function in the presence of multiple stress factors including heavy metals, low pH, and nitrate [100-109]. Heavy metals can have damaging effects on the physiology of microbes [35, 39, 126]. Effects include impaired enzyme activity through binding of heavy metals to thiol groups in proteins, outcompeting other cations for their native binding sites, or the production of hydrogen peroxide (H2O2), which induces oxidative stress [36]. To avoid the damaging effects of heavy metals microbes have developed mechanisms to decrease intracellular heavy metal concentrations using efflux pumps or transforming metals into less toxic forms. Reduction as an electron acceptor (bioreduction), passive sorption to anionic groups in the cell wall (biosorption), and accumulation inside (bioaccumulation) or active precipitation outside (biomineralization) of the cell are possible mechanisms of uranium tolerance/detoxification in microorganisms [54]. A low external pH alters proton gradients, membrane potential, and intracellular ion concentrations important for cellular processes in bacteria, which can result in acidification of

! 23! the cytoplasm and is potentially fatal for cells [68-69]. Bacteria require proton transporters, like F-type ATPases, to decrease the intracellular proton concentration. F-type ATPases import protons into the cell to generate ATP, but under acidic conditions these transporters may use ATP to export protons outside the cell [68-70, 74]. F-type ATPases often work in congruence with potassium-transporters [68, 75]. When protons exit the cell, a membrane potential is created that prevents further proton extrusion. To remove the membrane potential, bacteria will transport potassium into the cell [68, 75]. Some bacteria are also capable of using nitrate as an electron acceptor to ultimately produce dinitrogen gas through denitrification, or to produce ammonia via dissimilatory nitrate reduction to ammonia (DNRA) or assimilatory nitrate reduction to ammonia (ANRA) [127-128]. Denitrification and DNRA are advantageous processes in the presence of high nitrate because they form a nitrogen substrate that can be secreted extracellularly to decrease nitrate concentrations inside the cell [128]. In all three pathways, a nitrate reductase is required to reduce nitrate to nitrite. A nitrite reductase reduces nitrite to ammonia in the DNRA and ANRA pathways and to nitric oxide in the denitrification pathway. Nitric oxide is further reduced using a nitric oxide reductase to nitrous oxide, and then to dinitrogen gas with a nitrous oxide reductase. Here we present a study of the physiological and genomic differences of Sediminibacterium spp. OR43 and OR53, two strains isolated from a uranium-contaminated subsurface sediment [101]. The growth of both strains was tested under a variety of environmentally relevant factors such as pH, nitrate, and uranium. The closed genome of Sediminibacterium sp. OR53 and the draft genome of Sediminibacterium sp. OR43 were analyzed and compared with an emphasis on the genes related to the resistance of uranium and other heavy metals.

! 24! Materials and Methods Medium All experiments were conducted in mineral salts (MS) medium unless otherwise noted.

The MS medium consisted of: 5 mM NH4Cl, 1 mM NaCl, 0.25 mM MgSO4 • 7H2O, 5 µM CaCl2

• 2H2O, 5 µM KH2PO4, 10 mM HEPES and 1 mL/L trace elements [129]. The pH was adjusted with NaOH to 7.0. After autoclaving, sterile solutions of glucose, tryptone, and yeast extract were added to obtain a final concentration of 0.05% (v/v) for each carbon source. DIFCO Bacto agar (15 g/L) was added for plates. To test the growth in the presence of different stress factors nitrate (0 – 500 mM) as potassium nitrate or uranium (VI) (0-400 µM) as uranyl acetate was added to the MS media. Growth at different pH values was tested in MS medium with 10 mM HEPES as the buffer at pH 5-8 or with HOMOPIPES as the buffer at pH 3.5-4.5. Growth under anaerobic conditions was tested in MS media with nitrate (200 mM

KNO3), uranium (100 µM uranyl acetate), or iron (400 mM FeCl3) as terminal electron acceptors. Agar plates with 2.5 g/L Luria Bertani (LB) broth and 15 g/L agar were used to grow biomass for DNA isolation for whole genome sequencing.

Strains and culture conditions Sediminibacterium spp. OR43 and OR53 were isolated from the highly contaminated subsurface sediment at Oak Ridge, TN [101]. The strains were maintained on MS agar plates. When liquid cultures were needed as inoculum for an experiment, each strain was inoculated into 5 mL of MS medium and incubated for two days at 27°C.

Growth in the presence of different stress factors Pre-cultivated bacteria (15 µL) were inoculated into 150 µL MS medium in 96-well plates at different pH values or increasing concentrations of uranium or nitrate. The plates were incubated at 27°C in a plate reader (Biotek Synergy HT, Biotek, Winooski, VT) for several days depending on the experiment. The optical density was measured every 10 min at 600 nm (OD600) after shaking the plate for 10 seconds. The growth rates were calculated from the slope of the

! 25! natural log-transformed OD600 data plotted against time. The lag phase was determined as time until the culture entered logarithmic growth.

Carbon utilization patterns Bacteria were grown to the end of the logarithmic phase in MS medium, centrifuged for 10 min at 24,328 x g, washed twice, and re-suspended in MS medium without carbon sources.

The OD600 of the culture was adjusted to approximately 0.3. The cells were inoculated into GN2 MicroPlatesTM (Biolog, Hayward, CA). The plates were incubated in the dark at 27°C for five days and measured every 24 hours in the plate reader (Biotek Synergy HT, Biotek, Winooski,

VT) at 590 nm (OD590). If the OD590 was ≥ 0.5 the strain was considered to be positive for the utilization of that particular carbon source.

Growth under anaerobic conditions Pre-cultivated bacteria were inoculated at a 1:10 dilution in each type of medium and observed for 5-9 days for growth. Denitrification was tested in MS medium supplemented with nitrate, iron reduction in MS medium with iron, uranium reduction in MS medium with uranium, and fermentation in MS medium without any additional supplements. All cultures were incubated under anaerobic conditions for ten days.

Motility Swimming, swarming, twitching, and gliding motility were assessed as previously described [130-131].

Optimum temperature The temperature range was determined in a custom-made temperature gradient block that was controlled by a water bath and a heating block. The temperatures were adjusted to values between 4°C and 42°C. The cultures were inoculated into liquid R2A medium in test tubes and incubated in the temperature block. Samples were taken in regular intervals to measure the

OD600.

Catalase activity

! 26! Bacteria colonies grown on MS agar were smeared with an inoculating loop onto a glass slide, 1 drop of 3% (v/v) H2O2 was added and the slide was observed for bubbles.

Oxidase activity A bacterial colony was picked using a sterile swab, a drop of 1% N,N,N,N-tetramethyl-p- phenylenediamine hydrochloride (oxidase reagent) was added and the swab was observed for purple color.

β-galactosidase activity Both strains were grown on MS agar with 0.1% (v/v) lactose instead of glucose for two days. Colonies of each strain were re-suspended in sterile tubes containing 1.1% (w/v) NaCl before adding 100 µL of sterile-filtered ONPG (5 µg/µL) and observing the development of yellow color over three hours.

H2S production Bacteria were inoculated into triple sugar iron (TSI) (Becton, Dickinson and Company, Franklin Lakes, New Jersey) agar deeps and slants. The tubes were observed for the development of a black iron sulfide precipitate over 4 days.

Fatty acid analysis Fatty acid methyl ester analysis was carried out by the Identification service of the Deutsche Sammlung von Mikroorganismen und Zellkulturen (DSMZ) (GmbH, Braunschweig, Germany). The bacteria were cultivated on R2A plates for four days at 28°C. Fatty acid methyl esters were analyzed using the Sherlock Microbial Identification System (MIDI) [132-134]. The peaks were identified using the library TSBA40 4.10.

Transmission electron microscopy (TEM) Copper mesh grids covered in a single layer of 3% Formvar (nitrocellulose) were lightly coated with carbon. Sediminibacterium spp. OR43 and OR53 were grown to late log phase in MS medium. Cells (5 µl) were added to the carbon-coated grids and allowed to sit for 3 minutes. The culture was blotted with filter paper to remove approximately half the culture media before

! 27! adding one drop of 1% (w/v) ammonium molybdate as a negative stain. After 5 minutes excess liquid was removed with filter paper. Grids were viewed in the JEM-1200 EX II (JEOL, Tokyo, Japan) transmission electron microscope operating at 100 keV.

Phylogenetic analysis DNA was isolated using the Qiagen Blood and Tissue Kit (Qiagen, Valencia, CA) according to the manufacturer’s recommendations. The DNA was amplified by PCR with the primers 27F and 1492R [135]. The PCR products were purified and sequenced using the BigDye Terminator V3.1 cycle sequencing kit (Life Technologies Corporation, Carlsbad, CA) on an Applied Biosystems 3730x1 DNA analyzer (Life Technologies Corporation, Carlsbad, CA) at the Center for Bioinformatics and Functional Genomics (CBFG) at Miami University using the internal primers 357F, 518R, or 518F [136]. All sequences were edited with 4Peaks (A. Griekspoor and T. Groothuis, The Netherlands Cancer Institute; http://nucleobytes.com/index.php/4peaks) and aligned using the program ARB [137]. The phylogenetic tree was constructed in MEGA (version 5.2.2) using the maximum likelihood algorithm.

DNA isolation for whole genome sequencing Cells were grown in 0.1X LB broth at 27°C until stationary phase. The DNA was isolated using the JetFlex kit (GenoMed, Löhne, Germany). Quality and size of the DNA was determined according to DOE-JGI guidelines. DNA size was larger than 23 kbp as determined by gel electrophoresis. The draft genome of Sediminibacterium spp. OR43 and OR53 were generated at the DOE Joint Genome Institute (JGI) using Illumina technologies (Table 1) [138]. For each genome we constructed and sequenced an Illumina Std PE library which generated 21,794,720 reads totaling 3,269.21 Mb of Illumina sequence information for Sediminibacterium sp. OR53 (data not provided for Sediminibacterium sp. OR43). All general aspects of library construction and sequencing performed at the JGI can be found at http://www.jgi.doe.gov/. The initial draft assembly contained 60 contigs in 60 scaffolds (Sediminibacterium sp. OR43) and 11 contigs in 1 scaffold (Sediminibacterium sp. OR53). Both genomes were assembled using Velvet version 1.1.05 as well as the Allpaths version r37654 (Sediminibacterium sp. OR43) and

! 28!

Table 1: Genome sequencing project information for Sediminibacterium spp. OR43 and OR53. Property OR43 OR53 Finishing quality Standard draft Improved high quality draft Libraries used Illumina (2 x150 bp) Ilumina (2 x 150 bp) Sequencing platforms Illumina HiSeq 2000 Not provided Sequencing coverage 253x 653x Assemblers Allpaths version r37654; Allpaths version r39750; Velvet version 1.1.05 Velvet version 1.1.05; Phrap version 4.24 Gene calling Prodigal 2.5 Prodigal 2.5 GOLD ID Gi05842 Gi05840 NCBI project ID 76969 82287 Database: IMG 2509887033 2516143025 Project relevance Bioremediation Bioremediation Biotechnology Biotechnology

! 29! Allpaths version r39750 and Phrap version 4.24 (Sediminibacterium sp. OR53) (Table 1). The final assembly is based on Illumina draft data (not provided), which provided an average coverage of 253x (Sediminibacterium sp. OR43) and 653x (Sediminibacterium sp. OR53).

Genome annotation Genes were identified using Prodigal 2.5 as part of the Oak Ridge National Laboratory genome annotation pipeline, followed by a round of manual curating using the JGI GenePRIMP pipeline [139]. The predicted CDSs were translated and used to search the National Center for Biotechnology Information (NCBI) nonredundant database, UniProt, TIGRFam, Pfam, PRIAM, KEGG, COG, and InterPro databases. These data sources were combined to assert a product description for each predicted protein. Non-coding genes and miscellaneous features were predicted using tRNAscan-SE, RNAmmer, Rfam, TMHMM, and signal P [140-144].

Genome analysis Further analysis of the genomes was conducted using the JGI-IMG database [145]. The genomes were compared to the genomes of the two closest cultured relatives Sediminibacterium salmoneum NBRC 103935 and Sediminibacterium sp. C3 [102]. Heavy metal resistance genes were identified using the Antibacterial Biocide and Metal Resistance Genes Database (Bac-Met) (bacmet.biomedicine.gu.se) [146]. The heavy metal resistance genes were identified in the genome of Sediminibacterium sp. OR53, and the orthologous sequences in the genomes of Sediminibacterium sp. OR43, S. salmoneum, and Sediminibacterium sp. C3 were determined.

Statistical analysis One-way ANOVA or T-test was conducted using the software SPSS (version 19).

! 30! Results Taxonomic identity Sediminibacterium spp. OR43 and OR53 were most closely related to Asinibacterium lactis and several strains of the genera Sediminibacterium, Hydrotalea, and Vibrionimonas based on 16S rRNA sequence (Figure 5).

Physiological characterization Sediminibacterium spp. OR43 and OR53 grew as small beige colonies on 0.1X LB and R2A plates. The cells of both strains were short rods with Sediminibacterium sp. OR43 measuring 1.2 µm long and 0.5 µm wide, and Sediminibacterium sp. OR53 measuring 2 µm long and 0.6 µm wide (Figure 6). Both strains produced oxidase and catalase and were aerobic since no fermentative or anaerobic growth with nitrate, iron, or uranium as an electron acceptor was observed (Table 2). The growth temperature ranged from 13°C - 32°C (OR53) and 13°C - 37°C (OR43) with optimal growth temperatures of 27°C (OR53) and 30°C (OR43). Neither strain grew in the presence of the lowest salt (NaCl) concentration tested (1%). Based on BIOLOG GN2 plates, Sediminibacterium spp. OR43 and OR53 utilized a large number of sugars (Table 2). In addition to the sugars utilized by Sediminibacterium sp. OR53, Sediminibacterium sp. OR43 also utilized L-arabinose, melibiose, turanose, D-fructose, raffinose, N-acetylglucosamine,

L-aspartate, and L-glutamine. iso-C15:0, iso-C15:1 G and iso-C17:0 3-OH were the dominant fatty acids in both strains (Table 3). These three fatty acids were also found in high concentrations in the closest related strains [119-125].

Growth in the presence of stress factors The nitrate concentration in the ground water around the borehole from which the organisms were isolated was 24.8-25.4 mM, the uranium concentration was 67.1-71.5 µM, and the pH was between 2.99 and 3.52 (http://www.esd.ornl.gov/orifrc). When both strains were grown under a range of nitrate concentrations, they grew only in the presence of the lowest concentration tested (50 mM) (Table 4). Higher nitrate concentrations inhibited the growth completely. Both strains had the highest growth rate at pH 5-7 and lower growth rates at pH 4.5 and pH 8 (Figure 7A). No growth was observed at pH lower than 4.5. The pH value had no impact on the biomass (max OD600) of Sediminibacterium sp. OR53 but reduced biomass was

! 31!

Figure 5. Maximum likelihood phylogenetic tree based on 16S rRNA gene sequences of Sediminibacterium spp. OR43 and OR53. Numbers at the nodes represent bootstrap values >50% after 100 replications.

! 32!

! 33!

!

Figure 6. Transmission electron micrographs of (A) Sediminibacterium sp. OR43; and (B) Sediminibacterium sp. OR53. Scale bar = 0.5 µm.

! 34!

! ! !

A B

! 35!

Table 2: Differential physiological characteristics of strains Sediminibacterium spp. OR43 and OR53T in comparison with type strains of closely related species. Strains: 1, Sediminibacterium sp. OR43; 2, Sediminibacterium sp. OR53; 3, Asinibacterium lactis LCJ02T; 4, Vibrionomonas magnilacihabitans MU-2T; 5, Sediminibacterium salmoneum NJ-44T; 6, Sediminibacterium ginsengisoli DTY13T; 7, Sediminibacterium goheungense HME7863T; 8, Hydrotalea flava CCUG51397T; 6, Hydrotalea sandarakina AF-51T. Data for reference strains were taken from [119-125]. Characteristic 1 2 3 4 5 6 7 8 9 Pigmentation beige beige pale none salmon orange- orange orange orange yellow pink yellow Cell morphology short short short curved rods rods thin rods short rods rods rods rods rods Production of Oxidase + + - + + + + + + Catalase + + - + + + + + + Urease - - - - - Hydrogen sulfide - - - + - - - ß-galactosidase + + + + + + + Motility + + - Swimming - - Swarming - - Twitching - - Gliding - - - + + - O2 tolerance aerobic aerobic aerobic aerobic aerobic aerobic aerobic aerobic Nitrate reduction ------Temperature range [°C] 13 - 37 13 - 32 20 – 30 15 - 40 18 - 37 15 - 40 20 - 42 20 - 37 25 - 52 Optimum temperature [°C] 30 27 25 22 - 28 30 37 45 NaCl tolerance [%] < 1.0 < 1.0 1.0 0.4 1.0 2.0 < 1.0 4.0 1.0 Opt. NaCl concentration [%] 0 0 0 0 1.0 0 0 ! !

! 36! ! ! Characteristic 1 2 3 4 5 6 7 8 9 pH range 4.5 - 8 4.5 - 8 5.5-6 6 - 7.5 4.5 - 10 5 - 7 4 - 9 Optimum pH 7 7 5.5 7.0 5.5 - 6 7 6 - 6.5 Assimilation of (growth on) D-Cellubiose + + + + + + D-Glucose + + + + + + - + Maltose + + + + + + - + D-Mannose + + - + + - + L-Arabinose + - + - - - - Trehalose + + + + - + Melibiose + - + + + + + Sucrose + + + + + + + + Turanose + - + + D-Galactose + + + + - + + D-Fructose + - + + - + + + Lactose + + + + + + Raffinose + - + + - + Gentibiose + + + + Lactulose + + N-acetylglucosamine + - - L-Aspartate + - - L-Glutamine + - - Growth on R2A + + + + + + + + TSA + + - - - + - + LB (0.1X) + + GC content [%] 45.6 45.4 49.2 45.2 40.6/43.4 47.5 40.5 42.0 35.2 !

! 37!

Table 3: Fatty acid profiles of Sediminibacterium spp. OR43 and OR53T strains in comparison with type strains of closely related species. Strains: 1, Sediminibacterium sp. OR43; 2, Sediminibacterium sp. OR53T; 3, Asinibacterium lactis LCJ02T; 4, Vibrionomonas magnilacihabitans MU-2T; 5, Sediminibacterium salmoneum NJ-44T; 6, Sediminibacterium ginsengisoli DTY13T; 7, Sediminibacterium goheungense HME7863T; 8, Hydrotalea flava CCUG51397T; 6, Hydrotalea sandarakina AF-51T. Data for reference strains were taken from [119-125]. Fatty acid 1 2 3 4 5 6 7 8 9 Straight chain C13:0 1.0 C15:0 8.9 4.9 4.0 C16:0 1.9 1.2 2.7 2.4 Branched iso-C13:0 2.4 2.3 2.2 2.9 1.5 4.1 4.2 2.0 iso-C14:0 1.4 1.0 1.8 2.5 3.6 1.8 iso-C15:0 20.5 24.0 26.3 29.2 17.5 21.8 20.3 34.8 26.2 anteiso-C15:0 3.0 3.6 4.8 4.4 9.5 2.4 2.7 1.7 5.2 iso-C16:0 1.7 3.0 3.1 6.0 1.1 1.6 8.4 iso-C17:0 1.0 3.1 Unsaturated iso-C15:1 G 15.1 11.6 8.0 14.8 24.1 19.4 25.3 8.2 anteiso-C15:1 A 1.0 7.4 1.6 C15:1ω5c 1.2 iso-C16:1 G 1.0 iso-C16:1 H 1.7 C17:1ω6c 1.3 1.1 1.6

! 38!

Fatty acid 1 2 3 4 5 6 7 8 9 Hydroxy iso-C15:0 3-OH 2.8 3.1 3.0 3.1 7.4 6.3 3.0 4.0 2.8 C15:0 2-OH 1.6 1.5 1.2 1.9 1.6 C15:0 3-OH 3.4 1.9 1.5 1.6 1.3 3.2 iso-C16:0 3-OH 6.2 6.2 4.4 10.2 7.7 3.4 6.6 1.2 4.2 C16:0 3-OH 3.0 3.4 3.8 1.7 1.8 3.3 2.4 1.5 iso-C17:0 3-OH 13.7 16.1 15.9 12.1 7.7 28.0 9.6 16.9 10.5 C17:0 2-OH 1.0 1.7 2.0 1.2 2.2 1.6 1.3 C17:0 3-OH 1.9 1.3 1.3 2.1 Unknown ECL 1.6 12.560 Unknown ECL 1.6 1.5 8.4 4.9 13.565 Unknown ECL 1.1 1.2 1.7 16.582 Summed feature 3 4.5 6.6 4.8 2.4 8.2 3.7 4.7 6.9 Summed feature 4 1.0 Summed feature 9 5.9 6.6 Summed feature 3 contains contains C16:1ω7c and/or C16:1ω6c; summed feature 4 contains iso-C17:1I and/or anteiso-C17:1B; summed feature 9 contains iso-C17:1ω9c and C16:0 10-methyl.

! 39!

Table 4: Influence of the nitrate concentration (mM) in the medium on the growth rate -1 (day ) and maximum biomass (max OD600) of Sediminibacterium spp. OR43 and OR53 after two days (mean ± SD, n=3). Different letters behind values indicate significant differences between growth rate or max OD600 values over the range of nitrate concentrations as determined by one-way ANOVA followed by Tukey (p < 0.05). Values with the same letter were not significantly different. -1 Growth rate (day ) Max OD600

NO3 (mM) OR43 OR53 OR43 OR53 0 5.77 ± 0.22 a 4.22 ± 0.11 a 0.25 ± 0.00 a 0.26 ± 0.00 a 50 4.97 ± 0.20 b 3.68 ± 0.06 b 0.25 ± 0.00 a 0.28 ± 0.00 b 100 No growth No growth 0.04 ± 0.01 b 0.03 ± 0.00 c 250 No growth No growth 0.02 ± 0.00 c 0.03 ± 0.00 c 500 No growth No growth 0.03 ± 0.01 bc 0.03 ± 0.00 c

! 40!

Figure 7: Growth rate (day-1) of Sediminibacterium spp. OR43 and OR53 in the presence of (A) different pH values; and (B) uranium concentrations (mean ± SD, n=3-6).

! 41!

! 42! observed for Sediminibacterium sp. OR43 at pH 4.5 and pH 5 (Table 5-6). The lag phases for both strains were shortest at pH 5-7 and longer at pH 4.5 and pH 8 (Table 7-8). The growth rate of Sediminibacterium spp. OR43 and OR53 decreased with increasing uranium concentrations (Table 7-8). The growth of Sediminibacterium spp. OR43 and OR53 after two days was completely inhibited by 300 µM and 400 µM uranium, respectively (Figure 7B; Table 7-8). The maximum biomass decreased and the lag phase increased with increasing uranium concentrations (Table 7-8).

Basic features from the genomes of Sediminibacterium spp. OR43 and OR53 The genome of Sediminibacterium sp. OR43 consisted of 3,768,016-bp containing 12 scaffolds, while the closed genome of Sediminibacterium sp. OR53 had a similar size of 3,715,967-bp on one scaffold (Table 9). Both genomes had a G+C content around 45.5%. Sediminibacterium sp. OR53 had two rRNA operons, whereas Sediminibacterium sp. OR43 likely only had two 5S and 23S rRNA genes and one 16S rRNA gene (data not shown). Both genomes have around 3,330 predicted genes of which a little more than 3,280 were protein- coding genes (Table 9). Putative functions were assigned to around 74% of all genes, and the remaining genes were annotated as hypothetical proteins. No CRISPR repeats were detected in the genome of Sediminibacterium sp. OR43, whereas one was detected in the genome of Sediminibacterium sp. OR53 (Table 9). The average nucleotide identity (ANI) calculated in the IMG database resulted in an identity between the two genomes of 96.4% indicating that the genomes belong to the same species [147]. The number of genes associated with COG functional categories showed only slight differences between the two genomes (Table 10).

Genes involved in nitrate metabolism The nitrate concentration in the sediments and the ground water at the IFRC are between 24.8-25.4 mM (http://www.esd.ornl.gov/orifrc). Sediminibacterium spp. OR43 and OR53 were missing the nitrate reductase necessary to use nitrate as a terminal electron acceptor in denitrification and/or DNRA pathways, but had an operon containing the genes for the large and small subunits of the nitrite reductases (nirBD) (Table 11). Both strains possessed genes for nitrite reductase (nirK), nitric oxide reductase (norBC), and the nitrous oxide reductase (nosZ) genes for denitrification (nitrite to dinitrogen gas). The nitrite extrusion protein (ntr) and the

! 43!

Table 5: Influence of the pH in the medium on the growth rate (day-1), maximum biomass

(max OD600), and lag phase (days) of Sediminibacterium sp. OR43 after two days (mean ± SD, n=4-6). Different letters behind values indicate significant differences between growth rate, max

OD600, or lag phase across a range of pH values as determined by one-way ANOVA followed by Tukey (p < 0.05). Values with the same letter were not significantly different. -1 pH value Growth rate (day ) Max OD600 Lag phase (days) 4.5 2.71 ± 0.12 a 0.12 ± 0.01 a 0.25 ± 0.08 a 5 5.49 ± 0.07 b 0.18 ± 0.02 b 0.09 ± 0.00 b 6 5.31 ± 0.11 b 0.24 ± 0.04 bc 0.09 ± 0.02 b 7 4.86 ± 0.16 c 0.27 ± 0.04 c 0.08 ± 0.01 b 8 3.39 ± 0.11 d 0.26 ± 0.02 c 0.14 ± 0.04 b ! !

! 44!

Table 6: Influence of the pH in the medium on the growth rate (day-1), maximum biomass (max OD600), and lag phase (days) of Sediminibacterium sp. OR53 after two days (mean ± SD, n=4-6). Different letters behind values indicate significant differences between growth rate, max OD600, or lag phase across a range of pH values as determined by one-way ANOVA followed by Tukey (p < 0.05). Values with the same letter were not significantly different. -1 pH value Growth rate (day ) Max OD600 Lag phase (day) 4.5 2.05 ± 0.06 a 0.24 ± 0.01 a 0.29 ± 0.05 a 5 4.89 ± 0.05 b 0.27 ± 0.00 b 0.10 ± 0.03 b 6 5.16 ± 0.05 c 0.28 ± 0.00 b 0.08 ± 0.02 b 7 5.04 ± 0.03 d 0.28 ± 0.00 b 0.09 ± 0.02 b 8 3.68 ± 0.04 e 0.25 ± 0.00 c 0.13 ± 0.02 b

! 45!

Table 7: Influence of the uranium concentration (µM) in the medium on the growth rate -1 (day ), maximum biomass (max OD600), and lag phase (days) of Sediminibacterium sp. OR43 after two days (mean ± SD, n=4-6). Different letters behind values indicate significant differences between growth rate, max OD600, or lag phase across a range of uranium concentrations as determined by one-way ANOVA followed by Tukey (p < 0.05). Values with the same letter were not significantly different. -1 Uranium concentration Growth rate (day ) Max OD600 Lag phase (days) (µM) 0 5.43 ± 0.27 a 0.24 ± 0.01 a 0.07 ± 0.00 a 25 4.21 ± 0.14 b 0.24 ± 0.00 ab 0.05 ± 0.01 a 50 3.41 ± 0.12 c 0.22 ± 0.01 b 0.06 ± 0.05 a 75 2.93 ± 0.20 cd 0.21 ± 0.01 c 0.10 ± 0.03 a 100 2.55 ± 0.52 d 0.18 ± 0.00 d 0.07 ± 0.04 a 200 1.04 ± 0.11 e 0.09 ± 0.00 e 0.29 ± 0.20 b 300 No growth No growth No growth ! !

! 46!

Table 8: Influence of the uranium concentration (µM) in the medium on the growth rate -1 (day ), maximum biomass (max OD600) and lag phase (days) of Sediminibacterium sp. OR53 after two days (mean ± SD, n=4-6). Different letters behind values indicate significant differences between growth rate, max OD600, or lag phase values as determined by one-way ANOVA followed by Tukey (p < 0.05). Values with the same letter were not significantly different. -1 Uranium concentration Growth rate (day ) Max OD600 Lag phase (days) (µM) 0 5.04 ± 0.08 a 0.29 ± 0.00 a 0.01 ± 0.01 a 25 3.11 ± 0.15 b 0.24 ± 0.01 b 0.17 ± 0.02 b 50 3.12 ± 0.04 b 0.24 ± 0.00 b 0.25 ± 0.02 b 75 3.37 ± 0.09 c 0.24 ± 0.00 b 0.18 ± 0.04 b 100 3.35 ± 0.05 c 0.23 ± 0.00 b 0.17 ± 0.02 b 200 1.98 ± 0.07 d 0.17 ± 0.01 c 0.23 ± 0.03 b 300 1.25 ± 0.09 e 0.10 ± 0.01 d 1.28 ± 0.12 c !

! 47!

Table 9: Genome properties of Sediminibacterium spp. OR43 and OR53. Values in parentheses represent the percent (%) of total genes. Attribute Sediminibacterium Sediminibacterium sp. OR43 sp. OR53 Genome size (bp) 3,768,016 3,715,967 DNA coding region (bp) 3,512,235 3,473,644 GC-content (%) 45.7 45.4 DNA scaffolds 12 1 Total genes 3327 (100%) 3332 (100%) RNA genes 43 (1.29%) 51 (1.53%) rRNA operons 1-2 2 tRNA genes 36 (1.08%) 42 (1.26%) Protein coding genes 3284 (98.71%) 3281 (98.5%) Pseudogenes 40 (1.20%) Genes with function prediction 2473 (74.33%) 2464 (73.95%) Genes assigned to COG’s 1965 (59.06%) 1970 (59.12%) Genes assigned Pfam domains 2709 (81.42%) 2668 (80.07%) Genes with signal peptides 532 (15.99%) 497 (14.92%) Genes with transmembrane helices 767 (23.05%) 737 (22.12%) Genes connected to transporter classification 343 (10.31%) 327 (9.81%) CRISPR repeats 0 1

! 48!

Table 10: Number of genes associated with the general COG functional categories. Description OR43 OR53 Amino acid transport and metabolism 186 182 Carbohydrate transport and metabolism 169 170 Cell cycle control, cell division, chromosome partitioning 19 19 Cell motility 17 13 Cell wall/membrane/envelope biogenesis 183 181 Chromatin structure and dynamics 1 1 Coenzyme transport and metabolism 135 140 Cytoskeleton 2 2 Defense mechanisms 82 80 Energy production and conversion 110 109 Extracellular structures 3 1 Function unknown 102 104 General function prediction 200 206 Inorganic ion transport and metabolism 129 126 Intracellular trafficking and secretion 18 16 Lipid transport and metabolism 92 90 Mobilome: prophages, transposons 10 18 Nucleotide transport and metabolism 66 65 Posttranslational modification, protein turnover, chaperones 94 96 Replication, recombination, and repair 79 80 Secondary metabolite biosynthesis, transport, and catabolism 46 44 Signal transduction mechanisms 92 97 Transcription 157 152 Translation, ribosome structure, and biogenesis 175 178 Unclassified 0 0

! 49!

Table 11: Presence (+) and absence (-) of genes involved in nitrate metabolism in Sediminibacterium spp. OR43 and OR53. Gene product name Gene symbol OR43 OR53 Nitrate/nitrite transporter Nitrite extrusion protein nrt + + ABC-type nitrate/sulfonate/bicarbonate transporter nrtABCD + - Assimilatory nitrate reduction Ferredoxin nitrate reductase narB + + Dissimilatory nitrate reduction Nitrite reductase nirBD + + Denitrification Nitrate reductase napAB - - Nitrite reductase nirK + + Nitric oxide reductase norBC + + Nitrous oxide reductase nosZ + +

! 50! ferredoxin nitrate reductase (narB) that is involved in ANRA were present in both strains (Table 11). Sediminibacterium sp. OR43 also had the genes encoding an ABC-type nitrate/sulfonate/bicarbonate transport system (ntrABCD).

Genes potentially involved in the adaptation to low pH values Sediminibacterium spp. OR43 and OR53 had all the genes necessary for a functional F- type ATPase (Table 12). Genes for a high affinity potassium transporter (kdpABCD) and two genes for a low affinity potassium transporter (kup) were present in both strains. Sediminibacterium sp. OR53 had two genes for a putative potassium-proton antiporter (kefBC) whereas Sediminibacterium sp. OR43 had only the kefC gene (Table 12). In addition, two RNA polymerase sigma factors (rpoS) were detected in both genomes that are potentially involved in pH homeostasis.

Genes potentially involved in resistance to heavy metals Genes with more than 40% nucleotide identity to experimentally verified heavy metal resistance genes were identified in the genome of Sediminibacterium sp. OR53 using the Bac- Met database (Table 13) [146]. In summary, genes for resistance to arsenic, copper, cadmium, silver, zinc, mercury, chromium, tellurium, selenium, cobalt, manganese, and nickel were detected in this genome (Table 13). The genes encode transcriptional regulators, efflux pumps, chaperone proteins, and DNA repair enzymes. Orthologous sequences to most genes in Sediminibacterium sp. OR53 were found in the genome of Sediminibacterium sp. OR43, whereas orthologous sequences for several genes were missing in the genomes of S. salmoneum and Sediminibacterium sp. C3 (Table 13). However, no arsenical resistance protein and only one transcriptional regulator and transport protein for mercury were detected in the Sediminibacterium sp. OR43 genome.

Genes involved in potential resistance to uranium The genome of Sediminibacterium sp. OR53 encoded 32 phosphatase genes, whereas the genome of Sediminibacterium sp. OR43 encoded 30 (Table 29). Most phosphatases are involved in lipid biosynthesis, purine and pyrimidine biosynthesis, amino acid biosynthesis, sugar metabolism, or the metabolism of secondary metabolites. The Sediminibacterium sp. OR43

! 51!

Table 12: Enumeration of genes potentially involved in the adaptation to low pH in Sediminibacterium spp. OR43 and OR53. Gene product name Gene OR43 OR53 symbol F-type proton translocating ATPase atpG 1 1 atpCD 1 1 atpBEFHA 1 1 High affinity potassium transporter kdpABCD 1 1 Putative potassium proton antiporter kefB 1 kefC 1 1 Low affinity potassium transporter kup 2 2 RNA polymerase sigma factor, sigma 70 rpoS 2 2

! 52!

Table 13. Heavy metal resistance genes in the genome of Sediminibacterium sp. OR53. The genome of Sediminibacterium sp. OR53 was compared to the closest experimental verified sequence in the Bac-Met database and is represented in the table by nucleotide identity (%). Orthologs of heavy metal resistance genes identified in Sediminibacterium sp. OR53 were identified in Sediminibacterium spp. OR43, C3, and S. salmoneum (Sal). Genome locus Gene Identity Identity of orthologous OR53 Gene product name symbol (%) sequences (%) OR43 C3 Sal Arsenic 2127 Arsenical resistance protein acr3 91 63.6 64.5 Copper 748 Copper exporting P-type ATPase copB 42 98.5 63.3 1900 Copper exporting P-type ATPase copB 57 81.5 2802 Copper exporting P-type ATPase copB 52 98.7 72.4 3009 Copper exporting P-type ATPase copB 57 2660 Copper homeostasis protein cutC 45 96.2 61.5 60.9 2288 Chaperone protein dnaK 61 99.4 89.3 89.8 3114 Chaperone protein dnaK 40 98.7 77.8 78.3 Copper, silver 2757 Cation efflux system cusA 43 1395-1396 Cation efflux system (Putative silver efflux pump) cusA 41-45 99.1 1874-1875 Cation efflux system (Putative silver efflux pump) cusA 40-46 2341 Transcriptional regulator protein cusR 47 99.1 2611 Transcriptional regulator protein cusR 44 100 2823 Transcriptional regulator protein cusR 47 100 3287 Transcriptional regulator protein cusR 42 99.5 66.4 66.4 Cobalt, zinc, cadmium 1904 Heavy metal efflux pump czcA 48 90.2 94.0 55.0 2142 Heavy metal efflux pump czcA 46 94.8 67.2 69.4 1913 Cation diffusion facilitator czcD 48 93.6

! 53!

Genome locus Gene Identity Identity of orthologous OR53 Gene product name symbol (%) sequences (%) OR43 C3 Sal Mercury 1924 Transcriptional regulator merR 54 85.6 68.8 1925 Mercury transporter merT-P 50 58.2 57.7 2695 Mercury transporter merT-P 39 99.5 Zinc 1915 Zinc transporting ATPase ziaA 49 59.9 58.1 61.2 509 Transcriptional regulator zraR 40 98.7 61.2 2409 Transcriptional regulator zraR 48 99.5 80.1 79.9 2909 Transcriptional regulator zraR 45 99.2 80.4 80.9 Chromium, tellurium, selenium 1765 ATP dependent DNA helicase recG 41 99.1 77.2 76.9 1338 Holliday junction DNA helicase ruvB 59 99.7 87.6 86.8 Magnesium, cobalt 2606 Magnesium transporting ATPase mgtA 53 100 Manganese, iron, cadmium, cobalt, zinc 2470 Divalent metal cation transporter mntH 41 97.6 73.6 72.7 Nickel 1151 Nickel transporter permease (ABC-type transporter) nikC 45 98.3 !

! 54! genome contained three membrane-associated phospholipid phosphatases and the Sediminibacterium sp. OR53 genome had four (Table 29).

! 55!

Table 14: Membrane associated phospholipid phosphatases in the genome of Sediminibacterium sp. OR53 and the percent identity (%) of orthologous sequences in Sediminibacterium spp. OR43, C3, and S. salmoneum. Genome locus Identity of orthologous sequences (%) OR53 OR43 C3 S. salmoneum 1659 97.5 51.8 49.8 2380 100 61.0 2773 57.1 3159 98.1 56.8

! 56! Discussion Based on 16S rRNA, Sediminibacterium spp. OR43 and OR53 are closely related to A. lactis, a strain isolated from donkey milk, V. magnilacihabitans isolated from the water of Lake Michigan, H. flava isolated from water samples, H. sandarakina isolated from hot spring runoff, S. ginsengisoli isolated from a soil of a ginseng field, S. salmoneum isolated from the sediment of the eutrophic reservoir, and S. goheungense isolated from a freshwater environment (Figure 5) [119-125]. With the exception of A. lactis all closely related strains were found in water, sediment, or soil environments. Additionally, the distribution of closely related 16S rRNA gene sequences have been found in both contaminated and uncontaminated environments suggesting that these bacterial isolates cluster with other environmentally relevant species [101-118]. Physiologically, Sediminibacterium spp. OR43 and OR53 are very similar to the closely related cultivated strains (Table 2-3). All strains were aerobic, did not reduce nitrate, had a low salt tolerance, and exhibited optimal growth at pH 5.5-7 (Table 2). The fatty acid profiles and the number of carbon sources utilized varied depending on the strain, but were generally consistent amongst all related strains (Table 2-3). These results correspond with the environmental conditions under which these microbes are commonly found [119-124]. The complete genome of Sediminibacterium sp. OR53 and draft genome of Sediminibacterium sp. OR43 were sequenced to identify genes predicted for tolerating heavy metals, nitrate, and low pH present in the subsurface sediment. In general, Sediminibacterium spp. OR43 and OR53 had average-sized genomes that were slightly larger than other sequenced Sediminibacterium genomes but comparable in the number of genes/Mb and the percentage of genes in each COG category (Table 9-10) [102]. The G+C content was similar to V. magnilacihabitans, but fell within the range (35.2-49.2) of other closely related strains (Table 9) [119-125]. The Sediminibacterium spp. OR43 and OR53 genomes did not contain a large number of genes related to tolerating the low pH conditions present in the subsurface at Oak Ridge (Table 12). This corresponded with the physiological data, which showed that these strains could not tolerate pH < 4.5 (Figure 7A; Table 5-6). The ability for Sediminibacterium spp. OR43 and OR53 to tolerate a decrease in pH is likely due to F-type ATPases (atp) and the low affinity potassium transporter (kup) used to balance membrane potential during proton extrusion [68-69]. Enteric bacteria are capable of withstanding pH < 3 with genes related to acid resistance such as

! 57! lysine-, glutamine, and arginine decarboxylases that were not present in the Sediminibacterium spp. OR43 and OR53 genomes (Table 12) [68-69, 148]. The results suggest that Sediminibacterium spp. OR43 and OR53 are neutrophilic organisms, which is in agreement with other closely related strains [119-125, 149]. Sediminibacterium spp. OR43 and OR53 also had similar physiological responses to nitrate as a stress factor and as a terminal electron acceptor (Table 2, Table 4). The absence of a nitrate reductase in the denitrification and DNRA pathway in the Sediminibacterium spp. OR43 and OR53 genomes limits the ability of these strains to grow in the presence of nitrate (Table 4, Table 11). However, genes in the denitrification and DNRA pathways were mostly absent from the genomes of other Sediminibacterium strains, suggesting that this is a unique adaptation of Sediminibacterium spp. OR43 and OR53 to the conditions at Oak Ridge [102]. Their genomes contained nitrite reductases in the denitrification and DNRA pathways suggesting that Sediminibacterium spp. OR43 and OR53 could complete these pathways with nitrite as the starting substrate (Table 11). Therefore, it is possible that Sediminibacterium spp. OR43 and OR53 cope with nitrate at Oak Ridge by associating with nitrate reducing bacteria capable of providing a nitrite source [150]. The number of characterized heavy metal resistance genes in Sediminibacterium sp. OR53 and corresponding orthologs in Sediminibacterium sp. OR43 suggest that these strains are adapted to the presence of heavy metals (Table 13). These data support earlier observations that both Sediminibacterium spp. OR43 and OR53 tolerate similar concentrations of cobalt, nickel, and cadmium and that these concentrations are comparable to other species with characterized tolerance mechanisms to heavy metals [67, 101]. Most of the genes involved in heavy metal tolerance and identified in Sediminibacterium sp. C3 and S. salmoneum were transcriptional regulators or efflux pumps essential to maintaining intracellular concentrations of biologically relevant metals (Table 13) [102]. The Sediminibacterium spp. OR43 and OR53 genomes contained multiple ATP-dependent heavy metal transporters, suggesting that the active extrusion of specific heavy metals is important for maintaining a low intracellular metal concentration in these strains compared to Sediminibacterium sp. C3 and S. salmoneum [102]. The growth rate of Sediminibacterium sp. OR43 was significantly lower (p < 0.001) than Sediminibacterium sp. OR53 in the presence of 200 µM uranium (Figure 7B; Table 7-8). However, the genes related to heavy metal transport and immobilizing uranium were similar in

! 58! these strains (Table 13-14). The presence of membrane-associated phosphatases in both genomes suggests that Sediminibacterium spp. OR43 and OR53 might actively biomineralize uranium in extracellular uranyl phosphate complexes [63, 65]. The activity of these enzymes in response to uranium may differ between these strains and contribute to the increased growth rate of Sediminibacterium sp. OR53 at most uranium concentrations. Additionally, other regulatory responses to stress could also increase the growth rate of Sediminibacterium sp. OR53 in the presence of uranium (Figure 7A; Table 3-6, Table 9). Sediminibacterium spp. OR43 and OR53 had very similar physiological and biochemical characteristics to closely related strains from other environments (Figure 5; Table 2-3). However, Sediminibacterium spp. OR43 and OR53 are unique in their ability to persist in the heavy metal contaminated subsurface at Oak Ridge. Persistence of these strains in the presence of heavy metals can partially be attributed to the number of energy-dependent efflux systems and phosphatases potentially involved in uranium immobilization compared to other sequenced Sediminibacterium strains (Figure 7B; Table 7-8, Table 13-14). Finally, genes were present in the Sediminibacterium spp. OR43 and OR53 genomes that explained how these strains endure an environment containing nitrate and a low pH (Table 11-12). It is likely that other environmental factors contribute to the persistence of Sediminibacterium spp. OR43 and OR53 in the subsurface at Oak Ridge [76]. Further studies are required to confirm that the genes identified in both strains for persisting in the presence of uranium, low pH, nitrate, and heavy metals are expressed in each of these conditions.

! 59! CHAPTER 2

The Effects of Uranium and pH on the Composition and Productivity of an Artificial Community in a Long-Term Growth Experiment

R. M. Brzoska and Bollmann A.

Submitted to FEMS Microbiology Ecology

Abstract Bacterial communities are capable of performing a variety of processes, such as processes that contribute to nutrient cycling and the remediation of complex compounds. The growth and composition of species within the community contribute to the efficiency or productivity of these processes. Artificially assembled communities maintained in long-term growth experiments have increased productivity (biomass or metabolic activity) over time, which suggests that community dynamics can change over time and are important for improving community productivity. In this study, we analyzed the impact of three different environmental conditions (pH 4.5, pH 7, and pH 7 with uranium) on the dynamics and productivity of an artificial microbial community. We used a community consisting of Sediminibacterium sp. OR53, Caulobacter sp. OR37, Ralstonia sp. OR214, and Rhodanobacter sp. OR444, all isolated from the Integrated Field Research Challenge area at Oak Ridge. Each strain responded differently to uranium and low pH. The community was maintained for 30 weeks (~300 generations) at pH 7 (pH7) or pH 4.5 (pH4.5) and in the presence of 200 µM uranium at pH 7 (pH7U). Biomass and community composition were monitored over time. The community stabilized within the first four weeks under all conditions. From weeks 12-30, there was a steady decrease in the level of microbial biomass in cultures at pH4.5. Ralstonia sp. OR214 was dominant in the pH7 and pH4.5 conditions and Caulobacter sp. OR37 and Sediminibacterium sp. OR53 were the most abundant in the pH7U condition. We tested the response of these communities to environmental changes by transferring cultures to new conditions at week 12 (pH7->pH4.5, pH7U->pH7, pH4.5->7, pH7->pH7U). Alterations to pH had minimal impact on the relative abundance of the strains. When the culture from pH7 was transferred to pH7U the community composition changed and was similar to the community of the original pH7U condition. However, the community did not revert back to the composition of the original pH7 community when a subculture from pH7U was transferred to pH7 without uranium. These results suggest that the strains that are best adapted to pH or uranium have the highest relative abundance in the respective artificial communities.

! 61! Introduction In the environment microorganisms live in communities that are important in many ecosystem functions, including nutrient cycling, oxygen production, and catabolism of complex compounds. Bacteria in these communities can form positive associations that improve the function of the community as well as negative interactions that limit the performance of the community [78, 86, 90, 151-153]. For example, different microbial communities can have different efficiencies in degrading organic compounds such as azo dyes or polycyclic aromatic hydrocarbons [103, 154]. However it is not well understood how the different bacterial populations in microbial communities evolve to form an efficient community. Artificially assembled microbial communities are important for studying how microbial populations form efficient communities in natural systems. Molecular methods have been used in recent studies to describe natural microbial communities [155-160]. While natural communities offer a realistic reflection of the community’s capabilities, it is often difficult to discern the contribution of an individual population in the community. Additionally, it is difficult to detect organisms present in low abundance or with low metabolic activity using molecular methods. Therefore, artificially assembled communities where all species can be detected and that can be manipulated under stringent conditions offer an alternative method for studying natural communities. Coculture experiments in the laboratory have been used to investigate the interactions in the development of productive microbial communities. Communities containing only two organisms have demonstrated that bacteria can form mutualistic or commensalistic interactions in a short period of time [95, 152, 161-162]. These interactions typically form as a result of cross-feeding related mechanisms but may be unstable associations that are disrupted by changing growth conditions [95]. Artificial multi-species communities containing more than two species have been used to study the degradation of organic pollutants or cellulose [86-87, 163- 165-166]. Short-term studies showed that communities with greater diversity tend to remove a larger array of substrates or remove a single substrate more quickly than individual populations [152, 164]. However, some studies reported no correlation or even a decrease in the degradation ability in multi-species communities relative to an individual population, indicating that factors other than microbial diversity are important in forming a stable and productive community [165, 167-168].

! 62! Short-term studies can give insights as to how certain populations interact under a given condition, but the results might not represent the functionally stable community that exists in the environment [78, 169]. Metabolically active populations that represent microorganisms with a low abundance in the natural system or are difficult to cultivate are often excluded from these studies, which can negatively impact community stability and productivity under certain conditions [169]. Long-term growth experiments are likely to be a better representative of natural systems because they allow interactions between culturable bacterial populations to stabilize and adjust to the growth conditions. Microbial communities at the end of long-term growth experiments are often more productive than the starting cultures [78, 90, 92, 170-171]. For example a synthetic mutualism between Desulfovibrio vulgaris and Methanococcus maripaludis that allowed the community to use lactate when neither species could metabolize it on their own was established in 300 generations [90]. Other communities showed an increased productivity after 60 generations [92]. Here we present a study investigating the change in the community composition and productivity (biomass) of an artificial community in a long-term growth experiment in the presence of different stress factors. Four bacterial species originally isolated from the Integrated Field Research Challenge (IFRC) at Oak Ridge, TN and with different tolerances towards uranium or low pH were chosen to create an artificial bacterial community in the presence of these conditions over extended generation times [101]. As a consequence of substandard practices in waste handling, the subsurface sediment at the Oak Ridge site contains high concentrations of uranium and a low pH. Bacteria isolates from this site and used in the current study could therefore represent an effective microbial community for the bioremediation of uranium. We hypothesized that species sensitive to low pH or uranium would contribute to community productivity in their respective conditions and that productivity would increase over time. The community was maintained in the presence or absence of uranium, as well as neutral or low pH for 30 weeks (~300 generations). Quantitative-PCR was used to measure community composition and optical density was used as an assessment of relative biomass and productivity under all treatments. The results indicated that species initially tolerant to high concentrations of uranium or low pH exhibited the ability to persist under the respective conditions.

! 63! Material and Methods Strains Four pure bacterial strains that were previously isolated from the contaminated subsurface sediment at the IFRC in Oak Ridge (TN, USA) were used for the experiment [101]. Three strains belong to the phylum Proteobacteria (Caulobacter sp. OR37, Ralstonia sp. OR214, and Rhodanobacter sp. OR444) and one to the phylum Bacteroidetes (Sediminibacterium sp. OR53) [101]. All strains were stored as glycerol stocks at -80oC until further analysis.

Media

Bacterial cultures were grown in mineral salts (MS) medium containing 5 mM NH4Cl, 1 mM NaCl, 0.25 mM MgSO4•7H2O, 5 µM CaCl2•2H2O, 5 µM KH2PO4, and 1 mL/L trace elements [129]. The medium was buffered with 10 mM HEPES (pH 5-8) or 10 mM HOMO- PIPES (pH 3.5-4.5). After autoclaving, sterile solutions of glucose, tryptone, and yeast extract were added to obtain a final concentration of 0.05% (v/v) for each carbon source. For agar plates the MS medium was solidified with 15 g/L Bacto agar. The MS medium was supplemented with uranium (as sterile filtered uranyl acetate) to obtain final concentrations between 25 and 200 µM uranium directly before the start of the experiment.

Characterization of the growth of the single strains All strains were inoculated from MS agar plates into liquid MS medium and incubated for two days at 27°C. MS medium (150 µL) at different pH (3.5-8) and with different uranium concentrations (0-200 µM) was distributed into 96-well plates. The plates were inoculated with 10% (v/v) of the two day cultures and incubated for two days in a plate reader (Biotek Synergy

HT, BioTek, Winooski, VT) at 27°C. The optical density (OD600) was measured every 10 min after shaking the plate for 10 seconds. The growth rates were determined by calculating the slope of the natural log-transformed OD600 data plotted against time. Lag phase was calculated as the time before the initiation of logarithmic phase.

Long-term growth experiment Pre-cultivated strains were diluted with MS medium to the same cell density based on

OD600 and inoculated in equal parts into 12-well plates with different media. Three different

! 64! media were used: MS medium at pH 7 (pH7), MS medium at pH 4.5 (pH4.5), and MS medium at pH 7 with 200 µM uranium (pH7U). Each medium was inoculated in six replicates. The plates were incubated without shaking for one week at 27°C. After one-week, the cultures were re- suspended by pipetting up and down several times, the OD600 was measured and the cultures (1% (v/v)) were inoculated into fresh medium. This procedure was repeated for 30 weeks. New culture conditions were added after 12 weeks to investigate how the cultures would react to a change in their growth environment. Therefore, the pH7 cultures were transferred to pH4.5 (pH7->pH4.5) and pH7U (pH7->pH7U), pH7U was transferred to pH7 (pH7U->pH7), and pH4.5 was transferred to pH7 (pH4.5->pH7). These culture conditions were treated in the same way as the other cultures until the end of week 30. At the end of each week samples for molecular analysis, glycerol stocks, and uranium assays were taken. For the molecular analysis of the starting culture the OD600 of each strain was adjusted and 250 µL of each culture was mixed, centrifuged, and treated in the same way as the original samples.

Uranium (VI) assay Cell cultures (1 mL) were centrifuged (24,328 x g, 10 min) and the supernatant was used to quantify the remaining uranium in the medium as previously described [172].

Community productivity Optical density was used as a measurement of biomass in the community and to assess community productivity based on previous studies [90, 92]. Productivity was defined as the growth and reproductive success of the mixed community. An increase or decrease in biomass over 30 weeks was attributed to an increase or decrease in productivity, respectively. Productivity in correlation with community composition under different conditions was used as an indication of the types of interactions present in the community.

Molecular analysis Cell cultures (1 mL) were spun down (24,328 x g, 10 min) at the end of each week and the cell pellet were stored at -80°C until further analysis. Cell pellets produced during the uranium assay were stored for samples containing uranium (pH7U and pH7->pH7U).

! 65! DNA isolation DNA was isolated using the DNeasy blood and tissue kit (Qiagen, Valencia, CA) according to the manufacturers recommendations. DNA concentration and quality was measured with a NanoDropTM 3300 Fluorospectrometer (Thermo Fisher Scientific, Willmington, DE). The DNA was diluted to 5 ng/µL stored in aliquots at -20°C until further analysis.

Primer design and optimization for quantitative PCR (qPCR) Primers to quantify the four different strains were used as previously published or designed using the NCBI blast primer tool (Table 15) [136, 173-174]. The optimal annealing temperatures (50-65°C) of the primers for each strain were determined on a PCR machine with a temperature gradient (Biorad, Hercules, CA) using GoTaq Green master Mix (Promega, Madison, WI) and the following protocol: initial denaturation 5 min at 95°C, 30 cycles of denaturation for 30 sec at 95°C, annealing for 30 sec at a temperature gradient of 50-65°C, extension for 45 sec at 72°C, and final extension for 5 min at 72°C. The size of the PCR products was determined using agarose electrophoresis. The specificity of the primers was determined by amplification of the DNA of each strain individually and in different mixtures with all four different primer sets. qPCR The qPCR reactions were performed using SensiFAST Sybr No-ROX PCR mix (Bioline, London, UK) on an Illumina Eco Real-Time PCR system (Illumina, San Diego, CA) with primers and under conditions presented in Table 15-16. Standard curves were constructed using plasmids containing the 16S rRNA gene sequence of the strain of interest (Table 15) [135]. The efficiency of the reactions ranged from 91% to 108% and R2 was in all experiments 0.99 (Table 16). The relative abundance was defined as the number of absolute copies for one species divided by the sum of the copies for all species multiplied by 100%. All samples were run as technical duplicates.

Statistical analysis One-way ANOVA was conducted using the software SPSS (version 19).

! 66!

Table 15: Primers used for quantification the different strains Primer Refs α-Proteobacteria EUB 357F: 5’-CCT ACG GGA GGC AGC AG-3’ Caulobacter sp. OR37 A685R: 5’-TAT CTA CGA ATT TCA CCT CTA C-3’ [136, 173]

β-Proteobacteria EUB 357F: 5’-CCT ACG GGA GGC AGC AG-3’ Ralstonia sp. OR214 B680R: 5’-TCA CTG CTA CAC GTG-3’ [136, 173]

γ-Proteobacteria G731F: 5’-TGA CGC TGA AGC ACG AAA-3’ Rhodanobacter sp. OR444 G817R: 5’-ACC ACC ATC CAG TTC GCA-3’ This study

Bacteroidetes CFB 798F: 5’-CAA ACA GGA TTA GAT ACC CT-3’ Sediminibacterium sp. OR53 CFB 967R: 5’-GGT AAG GTT CCT CGC GTA T-3’ [174]

Eubacteria 16S rRNA EUB 27F: 5’-AGA GTT TGA TCC TGC TGG CTC AG-3’ EUB 1492R: 5’-GGT TAC CTT GTT ACG ACT T-3’ [135]

! 67!

Table 16: PCR conditions (temperature (°C)/time (s)) and validation of qPCR. OR37 OR214 OR444 OR53 Denaturation (initial) 95/600 95/600 95/600 95/600 Denaturation 95/30 95/30 95/30 95/30 Annealing 62/30 55/30 55/30 58/30 Extension 72/45 72/45 72/45 72/45 Cycles 30 30 30 30 Melting curve 95 95 95 95 55 55 55 55 Efficiency (%) 90-102 94-108 93-108 91-108 R2 0.99 0.99 0.99 0.99 Concentration for calibration curve 104-108 104-108 104-108 104-108 16S rRNA gene copy number in genome 1 1 4 2

! 68! Results Growth of individual bacterial strains at different uranium concentrations and pH The maximum uranium concentration and the minimum pH that sustained growth were determined for all four bacterial strains (Table 17). Caulobacter sp. OR37 had the shortest lag phase (≤ 1 hour) across all uranium concentrations and the highest growth rate of all the strains in the presence of 200 µM (0.288 h-1) (Figure 8). There was no significant difference (p = 0.42) in the growth rate of Caulobacter sp. OR37 in the presence or absence of 200 µM uranium (Figure 8A). Ralstonia sp. OR214 had the longest lag phase, 16-34 hours, in the presence of uranium (Figure 8B). Sediminibacterium sp. OR53 was able to grow without a notable lag phase in the presence of 200 µM uranium, whereas the growth of Rhodanobacter sp. OR444 was completely inhibited (Figure 8). Caulobacter sp. OR37 and Ralstonia sp. OR214 had higher growth rates across most uranium concentrations compared to Sediminibacterium sp. OR53 and Rhodanobacter sp. OR444 (Figure 8A). Ralstonia sp. OR214 and Caulobacter sp. OR37 were able to grow at pH 3.5, while Sediminibacterium sp. OR53 and Rhodanobacter sp. OR444 were not able to grow below pH 4.5 (Figure 9). Ralstonia sp. OR214 had the highest growth rate at all pH values measured, while Rhodanobacter sp. OR444 had the lowest growth rates under most conditions (Figure 9). The growth of all species was significantly higher (p < 0.05) at pH 7 compared to lower pH values. None of the species exhibited a notable lag phase at any pH (data not shown).

Biomass (OD600) production during the long-term growth experiment The biomass of the mixed cultures grown at pH7 was stable at a value of 0.4 to 0.5 throughout the whole experiment (Figure 10A). The OD600 of the culture at pH7U increased over the first six weeks and stayed stable (0.4-0.5) for the rest of the 30-week period (Figure 10B).

The highest OD600 was measured at pH4.5 within the first 12 weeks, but it decreased significantly (p < 0.001) over time to the same level as the OD600 of the cultures incubated at pH7 and pH7U (Figure 10). Transferring the pH7 cultures to pH7U after 12 weeks caused an initial decline in the OD600 that stabilized near the values of the original pH7 and pH7U cultures

(Figure 10B). No changes in the OD600 were detected at pH7U->pH7. The OD600 during the pH7- >pH4.5 and pH4.5->pH7 transitions increased and decreased, respectively (Figure 10A).

! 69!

Table 17: Maximum uranium concentration and minimum pH value in the MS medium that allowed growth of the bacterial species as pure cultures. Values are based on the highest uranium concentration and lowest pH value showing an inhibition of growth by each species after two days. Minimum Uranium pH value (µM) Caulobacter sp. OR37 3.5 200 Sediminibacterium sp. OR53 4.5 200 Ralstonia sp. OR214 3.5 25 Rhodanobacter sp. OR444 4.5 100

! 70!

Figure 8. Influence of 0-200 µM uranium on the growth rates (h-1) and length of lag phase (h) of Caulobacter sp. OR37, Sediminibacterium sp. OR53, Ralstonia sp. OR214, and Rhodanobacter sp. OR444 (mean±SD; n=3). (A) Growth rates; and (B) length of lag phase. Different letters represent significant differences (p < 0.05) in growth rate or length of lag phase of a single species across a range of uranium concentrations as determined by one-way ANOVA and Tukey. Values with the same letter were not significantly different.

! 71!

! 72!

Figure 9. Influence of pH on the growth rate (h-1) of Caulobacter sp. OR37, Sediminibacterium sp. OR53, Ralstonia sp. OR214, and Rhodanobacter sp. OR444 (mean±SD; n=3). Different letters represent significant differences (p < 0.05) in growth rate across a range of pH values for a single species as determined by one-way ANOVA and Tukey. Values with the same letter were not significantly different.

! 73!

! 74!

Figure 10: OD600 (as a measure of the total biomass) at the end of each week during the long- term growth experiment. The amount of biomass was depicted for (A) pH7, pH4.5, pH7->pH 4.5, and pH4.5->pH7; and (B) pH7U, pH7, pH7->pH7U, and pH7U->pH7 (mean±SD, n=6). For the cultures transferred into new conditions, the total biomass in the original condition is shown at week 12 and the measurements in the new conditions are presented in weeks 13-29. Black arrow indicates the week of the transfer.

! 75!

! 76! Relative species abundance in different conditions in the long-term growth experiment The absolute abundance of the species in the community showed less than a two-fold difference in variance from the relative abundance (data not shown). At the beginning of the experiment the relative abundance of all four species under all conditions was between 12% and 48% (Figure 11-13). At pH7 all species were present during the 30 weeks (Figure 11A, Figure 13). Throughout the course of the experiment, Ralstonia sp. OR214 was the most abundant bacterium and consisted of 60% of the detected 16S rRNA genes. The relative abundance of the other three species ranged between 5% (Rhodanobacter sp. OR444) and 20% (Caulobacter sp. OR37 and Sediminibacterium sp. OR53) (Figure 11A, Figure 13). In contrast with the mixed community growth at pH7, at pH4.5 the community composition was stable for the duration of the experiment. Ralstonia sp. OR214 was the dominant species (80%) and Caulobacter sp. OR37 and Sediminibacterium sp. OR53 each made up about 10% of the community (Figure 11C, Figure 13). Rhodanobacter sp. OR444 was not detected at pH4.5. In the pH4.5->pH7 community, the relative abundance of Ralstonia sp. OR214 decreased significantly (p = 0.001) while Caulobacter sp. OR37 stayed constant and Sediminibacterium sp. OR53 increased significantly (p < 0.05) (Figure 10D). Rhodanobacter sp. OR444 was detectable at a low relative abundance. At pH7->pH4.5 the relative abundance of Ralstonia sp. OR214 significantly increased (p < 0.001), Caulobacter sp. OR37 and Sediminibacterium sp. OR53 significantly decreased (p < 0.02), and Rhodonobacter sp. OR444 was below detectable levels (Figure 11B, Figure 13). The pH7U condition had a different effect on the community compared to pH. Caulobacter sp. OR37 and Sediminibacterium sp. OR53 were the dominant members of the community while Rhodanobacter sp. OR444 and Ralstonia sp. OR214 made up less than 1% of the community (Figure 12C, Figure 13). By week 5, Caulobacter sp. OR37 was dominant with a relative abundance of more than 90%, while Sediminibacterium sp. OR53 had a relative abundance of less than 10% (Figure 12C). Over time the relative abundance of Caulobacter sp. OR37 showed a significant decrease (p = 0.028) to 60% while Sediminibacterium sp. OR53 significantly increased (p = 0.03) to 40%. In the pH7U->pH7 community, the relative abundance of Caulobacter sp. OR37 significantly decreased (p = 0.009) to around 40% of the total community and the relative abundance of Sediminibacterium sp. OR53 increased to 60% (Figure 12D, Figure 13). At pH7->pH7U, Ralstonia sp. OR214 and Rhodanobacter sp. OR444 decreased

! 77!

Figure 11: Relative abundance (%) of the 16S rRNA genes of Caulobacter sp. OR37, Sediminibacterium sp. OR53, Ralstonia sp. OR214, and Rhodanobacter sp. OR444 in the artificial community at (A) pH7; (B) pH7->pH 4.5; (C) pH4.5; and (D) pH4.5->pH7 (mean ± SD, n=3). For the cultures transferred into new conditions, the relative abundance in the original condition is shown for weeks 0-12 and the measurements in the new conditions are presented in weeks 14-30. Black arrow indicates the week of the transfer.

! 78!

A B

C D

! 79!

Figure 12: Relative abundance (%) of the 16S rRNA genes of Caulobacter sp. OR37, Sediminibacterium sp. OR53, Ralstonia sp. OR214, and Rhodanobacter sp. OR444 in the artificial community at (A) pH7; (B) pH7->pH7U; (C) pH7U; and (D) pH7U->pH7 (mean ± SD, n=3). For the cultures transferred into new conditions, the relative abundance in the original condition is shown for weeks 0-12 and the measurements in the new conditions are presented in weeks 14-30. Black arrow indicates the week of the transfer.

! 80!

A B

C D

! 81!

Figure 13: Relative abundance (%) of the 16S rRNA genes of Caulobacter sp. OR37, Sediminibacterium sp. OR53, Ralstonia sp. OR214, and Rhodanobacter sp. OR444 in the artificial community under all conditions at the beginning of the experiment (week 0), at week 12, and at the end of the experiment (week 30). Figure summarizes major trends in relative abundance as presented in Figure 11-12.

! 82!

! 83! in relative abundance and Sediminibacterium sp. OR53 and Caulobacter sp. OR37 became the dominant members of the community (Figure 12B, Figure 13).

Uranium concentration in the medium during the long-term growth experiment During the growth experiment, the amount of uranium in the pH7U and pH7->pH7U conditions were measured at the end of each week. The amount of uranium in the supernatant of each condition increased over time in each condition (Figure 14). The most notable increase was seen in the transition from pH7->pH7U, the amount of uranium measured at week 13 increased from 13 µM to 74 µM by week 30.

! 84!

Figure 14: Concentration of uranium (µM) in the medium at the end of select weeks in the pH7U and pH7->pH7U communities of the long-term growth experiment (mean ± SD, n=6).

! 85!

! 86! Discussion The overall goal of this study was to analyze the development of the community structure and productivity of an artificial community in the presence of three different conditions. We hypothesized that the species less tolerant to uranium or the low pH conditions would be present and contribute to the productivity of the community in the respective conditions. Our results did not support our hypothesis. We observed that the fitness of species to the tested conditions had a major impact on the community composition. Organisms with the highest individual growth rate for a given condition were consistently the most abundant in the microbial community in that respective condition, suggesting that negative interactions, like competition, dominate (Figure 11-13; Table 17). Bacteria with high growth rates typically produce less progeny than bacteria with low growth rates due to thermodynamic requirements [175]. However, bacteria with high growth rates are more likely to outcompete other bacteria with slow growth rates that are using the same resource for energy. Bacteria with slow growth rates have the potential of outcompeting organisms with high growth rates when they are able to consume alternative resources [175]. Compared to the other species under each condition, Ralstonia sp. OR214 had the highest growth rates at pH7 and pH4.5 (Figure 10; Table 4). Surprisingly, Ralstonia sp. OR214 was less abundant at pH7 than at pH4.5 (Figure 11A, Figure 11C, Figure 13). Since some species had a slower growth rate when growth was measured in single cultures, it is likely Ralstonia sp. OR214 was able to outcompete the other species for resources (Figure 8-9; Table 4). The sequenced genome of Ralstonia sp. OR214 contains over 100 ABC-transporters related to the uptake of amino acids and carbohydrates, which suggests that it can consume a broad range of substrates using high affinity transporters [176]. However, the absence of a selective pressure such as low pH or the presence of uranium, likely resulted in increased competition between all four species for nutrients that decreased the relative abundance of Ralstonia sp. OR214 at pH7 compared to pH4.5 (Figure 11A, Figure 11C, Figure 13). This is consistent with what was observed at week 14 when the abundance of Ralstonia sp. OR214 decreased at pH7 following the transfer from pH4.5 (Figure 11D, Figure 13). Any competition present at pH7 had no impact on community productivity. Ralstonia sp. OR214 was also the most abundant species at low pH (Figure 11C). A low pH results in an influx of protons for most neutrophilic bacteria that acidifies the cytoplasm and consequently kills the cell [68-69, 177]. The ability for Ralstonia sp. OR214 to dominate at

! 87! pH4.5 suggests that it has efficient mechanisms to extrude protons and outcompete the other species for nutrients. The genome of Ralstonia sp. OR214 contains multiple genes important for decreasing intracellular proton concentrations including F-type ATPases, multiple potassium transporters essential for balancing membrane potential during proton extrusion, and an arginine/lysine/ornithine decarboxylase [68, 148, 176]. The community composition at pH4.5 and pH7 were similar and stable, but the productivity showed a statistically significant (p < 0.001) decrease at pH4.5 (Figure 10A, Figure 11A, Figure 11C, Figure 13). Bacteria are capable of adapting to the presence of other bacteria in the community or to aspects of the environment in long-term growth experiments [78, 178-179]. Therefore, it is also possible that Ralstonia sp. OR214 adapted to the conditions at pH4.5 over time by increasing proton extrusion efficiency or nutrient transport. Improvements to these mechanisms would allow for an increase in growth rate, which could correspond with a decrease in biomass yield/productivity [175]. The community composition varied markedly between the pH conditions and the uranium conditions. Caulobacter sp. OR37 and Sediminibacterium sp. OR53 were the most abundant at pH7U (Figure 12C, Figure 13). Uranium as a heavy metal is often toxic to cells in small quantities and is capable of diminishing enzyme activity and damaging DNA inside the cell [39]. Bacteria have multiple mechanisms for tolerating uranium, but the mechanisms used by species in our community are not known [54]. Some Caulobacter species are able to precipitate uranium extracellularly as a uranyl phosphate complex [67]. The complex requires phosphatases that are present in the Caulobacter sp. OR37 genome [180]. Additionally, some Ralstonia species contain plasmids encoding heavy metal resistance genes, but there is no indication of plasmids being present in the Ralstonia sp. OR214 genome [176, 181]. The absence of a plasmid could explain the sensitivity of Ralstonia sp. OR214 to uranium. Additional research is required to identify potential heavy metal tolerance mechanisms in Rhodanobacter sp. OR444 and Sediminibacterium sp. OR53, but the ability for Sediminibacterium sp. OR53 to outcompete Ralstonia sp. OR214 and Rhodanobacter sp. OR444 at pH7U suggests it likely has effective mechanisms for uranium tolerance (Figure 12C, Figure 13). The relative abundance of Caulobacter sp. OR37 in the pH7U community appeared to influence community productivity at the level of both biomass production and uranium immobilization. Community biomass production increased over time with the relative abundance of Caulobacter sp. OR37 at pH7U and following the pH7->pH7U transition (Figure 10B, Figure

! 88! 12B-C). Over time, the relative abundance of Sediminibacterium sp. OR53 increased under both conditions and resulted in the stabilization of the community biomass, which suggests that the interaction between these species allowed for both species to co-exist. However, the amount of uranium detected in these conditions was lowest when the relative abundance of Sediminibacterium sp. OR53 was also low, suggesting that interactions between Sediminibacterium sp. OR53 and Caulobacter sp. OR37 negatively impacted the ability for the community to immobilize uranium over time (Figure 12C, Figure 14). The ability for Caulobacter species to precipitate uranium is highly dependent on phosphate availability. In a phosphate-limited environment, Caulobacter species are susceptible to uranium [182]. Therefore, the decrease in the amount of uranium immobilized by Sediminibacterium sp. OR53 and Caulobacter sp. OR37 could be attributed to a decrease in the amount of bioavailable phosphate as a result of competition between species or due to the formation of abiotic complexes between uranium and phosphate in the medium [182]. We also cannot eliminate the possibility that the increase in the amount of uranium measured in the medium is a result of increased tolerance to uranium by one or both of the species in the community. Tolerance could be attributed to uranium extrusion using heavy metal efflux systems. Overall, our results demonstrated that an artificial community consisting of Caulobacter sp. OR37, Rhodanobacter sp. OR444, Sediminibacterium sp. OR53, and Ralstonia sp. OR214 did not exhibit increased productivity over time at pH4.5 or pH7, or pH7U after 30 weeks (Figure 10). Our results are in contrast to other long-term growth experiments that have shown increased productivity based on biomass production under anaerobic conditions in the presence of lactate or aerobically in beech/spruce tea medium [90, 92]. The inability for the community to increase in productivity in these conditions can be attributed to the fitness of a strain for a particular environment or resources. However, our results agree with a long-term study demonstrating that a community of five cellulose-degrading bacteria could stably co-exist for over 20 transfers despite the presence of a dominating species and no increase in the ability of the community to degrade cellulose [86]. The ability for the cellulose-degrading community to coexist was a result of various interactions between populations that were predicted to influence different metabolic pathways. Analyzing the microbial composition allows for the speculation of large changes in population abundance that can impact net productivity, but does not give a direct insight into

! 89! how the interactions between populations change over time. Additional studies are required to assess the impact of the long-term growth experiment on interactions within the community under the tested conditions. The community composition differed in the uranium conditions compared to pH, and we predict that the interactions between strains will also vary in these conditions. We also cannot eliminate the possible role of less abundant strains contributing to interactions within the community [183-184]. In conclusion, this work gives insight into how different environmental conditions impact community composition and productivity. Community composition is mainly influenced by the fitness of each organism in the community to an environmental condition. In environments without a selective pressure, the organism that is the most competitive will flourish. Additionally, the composition of the community is important for increasing productivity. There was no predilection in the selection of the strains used in the artificial community for positive interactions, which explains the lack of change in productivity under most conditions. The future directions of this project will give much needed insight into how specific interactions evolve and increase the productivity of microbial communities in performing these important roles.

! 90! CHAPTER 3

Physiological and Genomic Comparison of Strains Re-Isolated from an Artificial Community in the Presence of Uranium

R. M. Brzoska and A. Bollmann

Abstract Microbial communities maintain a complex network of interactions that influence the productivity of the community. There are natural microbial communities capable of removing uranium from contaminated environments at rates superior to those of populations of individual organisms. Little is known about the influence of microbe-microbe interactions in these communities. It is important to understand the dynamics of the communities to ultimately allow for the assembly of artificial microbial communities that are optimized for the bioremediation of uranium. We performed physiological and genomic comparisons with several strains of Sediminibacterium spp. OR53 and Caulobacter spp. OR37 re-isolated from an artificially assembled community maintained in the presence of uranium (VI) for 30 weeks. The physiology of each of the individual re-isolated strains and cocultures were assessed. Individually, the re- isolated Caulobacter spp. OR37 and Sediminibacterium spp. OR53 strains produced less biomass compared to the ancestral strains. However, cocultures of these re-isolated strains exhibited increased growth rates and biomass production compared to cocultures of the ancestral strains, which was likely due to the development of a commensalistic cross-feeding mechanism between the two species. Conversely, none of the re-isolated cocultures were able to immobilize more uranium than the individual strains, which suggests that competitive interactions between Sediminibacterium sp. OR53 and Caulobacter sp. OR37 were still present. Our results show that long-term associations may result in the development of positive interactions in re-isolated strains compared to the ancestral strains. Additionally, commensalistic and competitive interactions may co-occur between microbial strains and impact growth and uranium immobilization, which are important for microbial communities considered for the purpose of bioremediation.

! 92! Introduction Bacteria in microbial communities contain complex interactions and the contributions of these interactions to community function are understudied. Microbial communities are also present in uranium-contaminated environments and are metabolically active [155]. Bacteria in these communities express unique phenotypic characteristics, including mechanisms of heavy metal resistance [21-22, 27, 157, 185-198]. Individual species have been studied for their ability to tolerate or immobilize uranium, but bacteria are rarely present as a single population in the environment [40, 58, 63, 84, 189-199]. In addition, communities often outperform individual cultures as a result of the large number of genes available from a diversity of species that enhance community activity in response to a number of biotic or abiotic factors [78, 86-87, 90, 103, 169, 171, 200-202]. Natural communities have been used in multiple studies to immobilize uranium in the absence of knowledge of all members of the community or how they interact with other species [26, 88, 103, 154, 202-205]. Understanding interactions between uranium-tolerant species could optimize community efficiency for the bioremediation of heavy metals. Long-term growth experiments were shown to be important in establishing stable interactions beneficial for increasing community productivity [78-79, 82, 90, 92-93]. To establish stable interactions, species must find ways to balance the energy costs and benefits of associating with other microorganisms. This energy balance is influenced by nutrient abundance, secretions, and waste products produced by other species as well as the fitness of each species in a niche [79, 82, 93]. During the adjustment period, either a species outcompetes another or they develop a way to coexist [78, 86, 90]. Prolonged exposure of a microbial community to a specific environmental stress can result in enhanced productivity of the evolved community compared to the ancestral community due to the development of interactions between the species [78, 83, 90, 92, 169]. Bacteria re- isolated from evolved communities often display different genotypes and phenotypes compared to the ancestral species in response to species-specific interactions [78, 206]. However, the productivity of individual re-isolated strains can be diminished compared to the ancestral strain as a result of cooperative relationships that evolved over time between different species [78]. We examined the interactions that developed between bacterial strains re-isolated from the long-term growth experiment described in Chapter 2. We focused on re-isolated strains from the pH 7 with uranium (pH7U) condition because we observed that the presence of uranium (VI)

! 93! stress influenced community composition to a greater extent than the community exposed to low pH. We characterized the physiological growth differences of the re-isolated and ancestral strains both individually and in coculture. The ability for cocultures to sequester uranium from the medium was also compared with ancestral strains. Transmission electron microscopy (TEM) was used to identify variations in uranium localization in re-isolated strains compared to ancestral strains. Finally, we used the Illumina MiSeq to sequence the genomes of re-isolated strains and identify potential alterations in their genotype compared to ancestral strains. These alterations may explain physiological differences between re-isolated and ancestral strains that could have resulted from microbe-microbe interactions or uranium exposure. We predicted that interactions between re-isolated strains would have a beneficial impact on growth in coculture and the ability of this community to immobilize uranium.

! 94! Materials and Methods Media All strains were maintained on mineral salts (MS) agar (15 g/L) or MS broth consisting of: 5 mM NH4Cl, 1 mM NaCl, 0.25 mM MgSO47H2O, 5 µM CaCl22H2O, 5 µM KH2PO4, 10 mM HEPES and 1 mL/L trace elements [129]. The pH was adjusted to 7.0 using NaOH. Sterile MS broth was supplemented with glucose, tryptone, and yeast extract added to final concentrations of 0.05% (v/v) for each carbon source. For media conditions containing uranium (VI), uranyl acetate from a 0.22-µm sterile-filtered stock (10 mM) was added to the MS media to a final concentration of 200 or 300 µM uranium.

Cultures The ancestral Sediminibacterium sp. OR53 and Caulobacter sp. OR37 strains were isolated from the uranium-contaminated subsurface at Oak Ridge, Tennessee [101]. Other strains were re-isolated from the pH7U condition at week 30 (~300 generations) in the long-term growth experiment previously described (Chapter 2). All strains were grown under static conditions at 27oC in the dark. Re-isolated and ancestral strains were maintained on MS medium with or without uranium, respectively. All experiments involving ancestral or re-isolated strains were performed using cultures freshly revived from glycerol. The strains were streaked on their respective MS agar (with or without 200 µM uranium) and grown for two days before being transferred to liquid media with the same composition.

Re-isolation of strains from pH7U Three replicate samples from the week 30 glycerol stocks at pH7U were serially diluted 1000-fold and plated on MS agar with or without 200 µM uranium. Colonies from the MS plates with uranium were picked at random and streaked onto fresh plates. Re-isolated and ancestral strains were transferred into 50% (v/v) glycerol stocks and stored at -80oC.

Uranium tolerance experiments with individual cultures The re-isolated and ancestral strains were inoculated into 5 mL MS medium with or without 200 µM uranium, respectively. The cultures were incubated for two days before being inoculated at a 1:10 dilution into a 96-well plate containing MS medium with uranium (0-500

! 95! µM). The OD600 was measured every 10 minutes following 10 seconds of shaking for two days using a plate reader (Biotek Synergy HT, Biotek, Winooski, VT). The OD600 of each bacterial strain under each condition was used to create growth curves by subtracting the OD600 of the medium blank from the OD600 of the bacterial strain. Growth rate was calculated by determining the slope of natural log-transformed OD600 values plotted against time. Lag phase was determined as the time before logarithmic growth in the cultures started.

Coculture growth experiments Re-isolated and ancestral strains of Caulobacter spp. OR37 and Sediminibacterium spp. OR53 were inoculated from MS agar plates into 5 mL MS media. After two days, re-isolated and ancestral strains were grown individually or in coculture in the presence or absence of 200 or 300 µM uranium. Bacterial strains were inoculated at a 1:100 dilution in a 48-well plate. For cocultures, equal volumes of each culture were added in a 1:100 dilution to maintain the same level of starting biomass as the individual cultures. The OD600 was measured every 10 minutes following 20 seconds of shaking using a plate reader (Biotek Synergy HT, Biotek, Winooski, VT). A duplicate plate for each culture was made and kept under static conditions at 27oC for the uranium assay. The uranium concentration in the medium was measured daily for a total of seven days. MS medium with or without uranium was used as the medium control.

Uranium (VI) assay A colorimetric assay based on the 1:1 association of the uranyl ion to 2-(2-Thiazolylazo)- p-cresol (TAC) was used to quantify the uranium concentration as previously described [172]. Cells (300 µL) were centrifuged at 24,328 x g for 10 min and the uranium concentration in the supernatant was measured. The plate was incubated in the dark for 10 min before being measured using a plate reader (Biotek Synergy HT, Biotek, Winooski, VT) at 588 nm. To determine the amount of uranium immobilized by the each strain, the amount of uranium measured in cell cultures was subtracted from the uranium concentration measured in the blank (MS medium with 300 µM uranium).

TEM

! 96! Copper mesh grids covered in a single layer of 3% Formvar (nitrocellulose) were lightly coated with carbon. Each of the strains was grown to mid-to-late log phase in MS medium with or without 300 µM uranium. Cells (1-3 mL) were centrifuged at 9,503 x g for three minutes and washed twice with MS medium containing no yeast extract, tryptone, glucose, or phosphate. Cells were re-suspended in 0.5-1 mL of the MS medium lacking carbon sources and phosphate. Washed cells (10 µL) were added to the carbon-coated grids and allowed to sit for two minutes. Excess media and cells were removed with filter paper. Grids were viewed in the JEM-1200 EX II TEM (JEOL, Tokyo, Japan) operating at 100 keV.

STEM elemental analysis Copper mesh grids previously prepared for TEM analysis were analyzed using the JEM- 2100 (JEOL, Tokyo, Japan) scanning transmission electron microscope (STEM) fitted with a Quantax silicon drift detector (SDD) and energy dispersive x-ray spectroscopy (EDS) detector (Bruker, Billerica, MA) at 200 keV. The electron beam from the STEM was used to generate x- rays across the sample. The SDD EDS detector was used to detect x-ray signals. Quantax software (Bruker, Billerica, MA) was used to convert x-ray data into elemental spectra or maps.

Colony PCR Colony PCR was used to identify re-isolated strains. Select colonies were resuspended in 100 µL 1X Tris-EDTA (TE) and cells were incubated at 65oC for 10 minutes to induce lysis. The lysate was then centrifuged at 24,328 x g for 3 min to pellet debris. One-microliter of the supernatant was mixed with GoTaq Green Master Mix (Promega, Madison, WI) and species- specific primers to identify the strains based on band size in a 1% agarose gel (Table 15).

Sequencing of re-isolated strains The identity of six re-isolated strains was confirmed by genomic sequencing of the 16S rRNA genes. DNA was obtained as described for colony PCR. The PCR was performed with GoTaq Green Master Mix (Promega, Madison, WI) and universal 16S rRNA primers, 27F and 1492R (Table 15) [135]. The PCR products were purified using the Wizard SV gel and PCR clean-up kit (Promega, Madison, WI) as described by the manufacturer. The sequencing reaction was set up using the BigDye Terminator v3.1 reaction kit (Applied Biosystems, Grand Island,

! 97! NY) and universal 16S rRNA primers, 357F or 518R (Table 15). Hi-Di formamide (Life Technologies, Grand Island, NY) was added immediately before sequencing on the 3130xl Genetic Analyzer (Applied Biosystems, Grand Island, NY). All sequences were trimmed and edited in 4Peaks (A. Griekspoor and T. Groothuis, The Netherlands Cancer Institute) and assembled into a phylogenetic tree using ARB [137].

DNA isolation Genomic DNA from the re-isolated strains was harvested using the Jetflex kit (Genomed, Löhne, Germany) according to the manufacturers’ instructions with modifications. Cells were grown to late stationary phase (4-10 days) in MS medium containing 200 µM uranium. Cells (1 mL) were centrifuged at 24,328 x g for 5 min. The pellet was resuspended in protein precipitation (PPT) mix and incubated on ice for 1.5 hours. All remaining centrifugation steps were carried out at 4oC. The PPT mixture was centrifuged for 12 min at 16,060 x g. The supernatant was transferred to a new tube and centrifuged for 5 min at 16,060 x g. A 400-µL aliquot was taken and added to an equal volume of ice-cold isopropanol and centrifuged for 25 minutes at 16,060 x g. The supernatant was discarded and after adding cold 70% ethanol, the sample was centrifuged for 5 min at 16,060 x g. The supernatant was discarded and the DNA was resuspended in 50 µL of 1X TE containing RNase at a final concentration of 4 mg/mL. Quality of the DNA was assessed using a nanodrop and electrophoresis with a 1% agarose gel. DNA from the same strain using multiple DNA isolations was combined using a speed vacuum (Jouan RC-1010, Winchester, VA).

Drop dialysis Following DNA isolation, drop dialysis was used to remove TE buffer from the concentrated DNA. Dialysis was performed on a 25-nm nitrocellulose membrane (Millipore, Darmstadt, Germany). The membrane was cut in half and gently placed on the surface of molecular grade water confined in a sterile Petri dish. The concentrated DNA was placed on the membrane and allowed to dialyze for 1 hour at room temperature.

Sybr green assay

! 98! The Sybr green I dsDNA assay (Thermo scientific, Florence, KY) was used to quantify genomic DNA according to the manufacturers instructions. Briefly, genomic DNA was diluted in 1X TE in order to fit onto a known standard consisting of lambda phage DNA (Promega, Madison, WI). Samples were centrifuged and Sybr Green was added to the DNA and lambda phage DNA standard. The samples were incubated in the dark for 5 minutes and then measured using the Nanodrop 3300 fluorometer (Life Technologies, Grand Island, NY).

DNA MiSeq The Nextera XT kit (Illumina, San Diego, CA) was used for tagmentation, fragmentation, and indexing of genomic DNA for the MiSeq (Illumina, San Diego, CA) according to the manufacturer’s instructions. In brief, 1 ng of genomic DNA from each strain was enzymatically fragmented and tagged with adapter sequences with a transposome into ~300-bp pieces. The tagged fragments were amplified using primers with unique index sequences for each re-isolated strain and specific for the adapter sequences. The DNA libraries were normalized using AMPure XP beads. Each library was separated from the beads and pooled before being loaded onto a MiSeq cartridge. The genomes of the re-isolated strains were sequenced using paired-end sequencing. Following sequencing, the sequences were automatically trimmed to remove adapter and index sequences.

MiSeq data analysis The CLC genomics workbench (CLC Bio, Boston, MA) was used to analyze the genomes of the re-isolated strains. The default settings were used in all analyses. When possible, sequences were trimmed based on quality. The minimum read length was set to 15 nucleotides. Sequences were mapped to the ancestral reference genome of Sediminibacterium sp. OR53 or Caulobacter sp. OR37. Mapping was done randomly and without masking. Paired distances for each strain were detected automatically during mapping. To optimize mapping results, unaligned ends were realigned using the local realignment tool. Variant analysis using the fixed ploidy variant detection tool was performed on the mapped reads to detect nucleotide substitutions, additions, and deletions in the re-isolated strains compared to the reference. The ploidy was set to 1 and variants were chosen based on a > 90% probability in regions containing 10-100,000

! 99! reads. Variants had to be observed in at least 2 reads and consist of at least 20% of all of reads. An algorithm was used to determine whether variants resulted in an amino acid change.

Statistical analysis of growth curves For tolerance growth curves, significant changes (p < 0.05) in growth rate, biomass production, and length of lag phase were calculated with SPSS Statistics (IBM, Armonk, NY) using one-way ANOVA and the Tukey test. The Student’s T-test was used to compare significant differences (p < 0.05) in growth rate or max OD600 (biomass yield) of individual strains compared to cocultures. The growth rate or biomass yield of each of the individual strains had to be significantly less than the growth rate or biomass yield of the coculture to be considered a positive interaction.

! 100! Results Re-isolation and identification of strains from the pH7U condition Bacteria strains were re-isolated from the pH7U condition in the long-term growth experiment to identify potential interactions using physiological and genomic methods (Chapter 2). Glycerol stocks from week 30 were serially diluted and 80 colonies were picked at random for identification by PCR and sequenced 16S rDNA using species-specific primers (Table 15). Ninety-one percent of the colonies were identified as Sediminibacterium spp. OR53 and 7.5% were identified as Caulobacter spp. OR37. One colony was not identified because there was not enough biomass. No colonies of Rhodanobacter spp. OR444 or Ralstonia spp. OR214 were isolated.

Characterization of individual re-isolated strains From the re-isolated strains, 6 strains (3 Caulobacter spp. OR37 and 3 Sediminibacterium spp. OR53 strains) were selected based on growth rate, max OD600 (biomass), and length of lag phase for further study (Table 18-20). None of the re-isolated Sediminibacterium spp. OR53 or Caulobacter spp. OR37 strains showed significantly (p < 0.05) higher growth rates or biomass production in medium with 0, 200, or 300 µM uranium when compared to the ancestral strains (Figure 15; Table 18-20). The majority of the re-isolated strains exhibited growth trends that were comparable to that of the ancestral strains (Figure 15). The amount of biomass produced was significantly less (p < 0.05) than the ancestral strain (Table 19). The length of the lag phase of the re-isolated Caulobacter spp. OR37 strains was not significantly different from the ancestral strain (Table 20). However, all of the re-isolated Sediminibacterium spp. OR53 strains had a longer lag phase in the presence of 200 µM uranium than the ancestral strain. The growth rate and length of lag phase for the Sediminibacterium strains in the presence of 300 µM uranium could not be calculated due to our inability to distinguish between the lag phase and the exponential growth phase (Table 18, Table 20).

Characterization of ancestral and re-isolated cocultures To determine the influence that long-term cocultivation had on interactions in the community, new cocultures containing Sediminibacterium spp. OR53 and Caulobacter spp. OR37 strains were analyzed for increased growth rate or biomass production compared to the

! 101!

Figure 15. Influence of 0, 200, and 300 µM uranium on the change in OD600 over time (growth) of the ancestral strains of Caulobacter sp. OR37 (OR37A) and Sediminibacterium sp. OR53 (OR53A) and the re-isolated (OR37 Is8, OR37 Is14, OR37 Is28, OR53 Is7, OR53 Is18, OR53 Is70) strains. The growth of Caulobacter spp. OR37 strains in (A) 0 µM uranium; (B) 200 µM uranium; and (C) 300 µM uranium. The growth of Sediminibacterium spp. OR53 strains in (D) 0 µM uranium; (E) 200 µM uranium; and (F) 300 µM uranium.

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! 103!

Table 18. Influence of 0, 200, and 300 µM uranium on the growth rate (h-1) of the re-isolated and ancestral strains after two days of exposure. Values represent mean±SD for Caulobacter spp. OR37 (n=6) and Sediminibacterium spp. OR53 (n=3). Different letters represent significant differences in growth rate between Caulobacter spp. OR37 strains or Sediminibacterium spp. OR53 strains at each uranium concentrations using one-way ANOVA and Tukey (p < 0.05). Values with the same letter were not significantly different. 0 µM U 200 µM U 300 µM U Caulobacter sp. OR37 0.273±0.064a 0.256±0.027a 0.229±0.022a (Ancestral) Caulobacter sp. OR37 Is8 0.252±0.039ab 0.212±0.075a 0.122±0.107b (Re-isolated) Caulobacter sp. OR37 Is14 0.231±0.031ab 0.203±0.003ab 0.152±0.005ab (Re-isolated) Caulobacter sp. OR37 Is28 0.182±0.035b 0.150±0.011b 0.103±0.079b (Re-isolated) Sediminibacterium sp. OR53 0.218±0.001a 0.182±0.002a NA* (Ancestral) Sediminibacterium sp. OR53 Is7 0.223±0.004a 0.150±0.000bc NA* (Re-isolated) Sediminibacterium sp. OR53 Is18 0.207±0.005b 0.141±0.005c NA* (Re-isolated) Sediminibacterium sp. OR53 Is70 0.196±0.00c 0.157±0.005b NA* (Re-isolated)

*Not available because lag phase could not be distinguished from exponential phase.

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Table 19. Influence of 0, 200, and 300 µM uranium on the max OD600 of re-isolated and ancestral strains of Caulobacter spp. OR37 and Sediminibacterium spp. OR53 after two days of exposure. Values represent mean±SD for Caulobacter spp. OR37 (n=6) and Sediminibacterium spp. OR53 (n=3). Different letters represent the significant differences in max OD600 between Caulobacter spp. OR37 strains or Sediminibacterium spp. OR53 strains at each uranium concentration using one-way ANOVA and Tukey (p < 0.05). Values with the same letter were not significantly different. 0 µM 200 µM 300 µM Caulobacter sp. OR37 0.240±0.005a 0.212±0.014a 0.152±0.016ab (Ancestral) Caulobacter sp. OR37 Is8 0.219±0.017ab 0.191±0.023ab 0.175±0.069a (Re-isolated) Caulobacter sp. OR37 Is14 0.200±0.007b 0.157±0.033b 0.0914±0.018c (Re-isolated) Caulobacter sp. OR37 Is28 0.216±0.012ab 0.166±0.034b 0.122±0.008bc (Re-isolated) Sediminibacterium sp. OR53 0.275±0.003a 0.221±0.001a 0.133±0.001a (Ancestral) Sediminibacterium sp. OR53 Is7 0.269±0.002b 0.192±0.001b 0.129±0.004a (Re-isolated) Sediminibacterium sp. OR53 Is18 0.267±0.002bc 0.199±0.003b 0.112±0.003b (Re-isolated) Sediminibacterium sp. OR53 Is70 0.263±0.002c 0.197±0.005b 0.118±0.004b (Re-isolated)

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Table 20. Influence of 0, 200, and 300 µM uranium on the length of lag phase (hours) of the re- isolated and ancestral strains of Caulobacter spp. OR37 and Sediminibacterium spp. OR53 after two days of exposure. Values represent mean±SD for Caulobacter spp. OR37 (n=6) and Sediminibacterium spp. OR53 (n=3). Different letters represent the significant difference in length of lag phase between Caulobacter spp. OR37 strains or Sediminibacterium spp. OR53 strains at each uranium concentrations using one-way ANOVA and Tukey (p < 0.05). Values with the same letter were not significantly different. 0 µM 200 µM 300 µM Caulobacter sp. OR37 1.30±1.07ab 0.80±0.71a 0.96±0.83ab (Ancestral) Caulobacter sp. OR37 Is8 0.42±0.46a 0.50±0.55a 2.42±1.73a (Re-isolated) Caulobacter sp. OR37 Is14 0.70±0.64a 0.59±0.64a 0.75±0.82b (Re-isolated) Caulobacter sp. OR37 Is28 2.75±1.73b 1.60±1.46a 0.27±0.37b (Re-isolated) Sediminibacterium sp. OR53 1.17±0.00 1.67±0.00 NA* (Ancestral) Sediminibacterium sp. OR53 Is7 1.50±0.00 2.67±0.00 NA* (Re-isolated) Sediminibacterium sp. OR53 Is18 1.67±0.00 3.33±0.00 NA* (Re-isolated) Sediminibacterium sp. OR53 Is70 1.67±0.00 2.83±0.00 NA* (Re-isolated) *Not available because lag phase could not be distinguished from exponential phase.

! 106! individual strains. No cocultures exhibited a higher growth rate compared to the individual cultures in the presence of 200 µM uranium (data not shown). However, a significant difference (p < 0.05) in growth rate and/or biomass production was observed for some of the cocultures compared to the individual cultures in the presence of 300 µM uranium (Figure 16B; Table 21). Re-isolated strains of Sediminibacterium spp. OR53 Is7 and Is18 showed significant increases in growth rate in coculture with all re-isolated Caulobacter strains (Table 21). Sediminibacterium spp. OR53 Is7 and Is18 also exhibited significant increases in biomass when in coculture with Caulobacter spp. OR37 Is14 and Is28. Sediminibacterium sp. OR53 Is70 did not have any significant increases in biomass while in coculture with any Caulobacter spp. OR37 strains (Table 21). However, Sediminibacterium sp. OR53 Is70 exhibited a significant increase in growth rate when in coculture with Caulobacter sp. OR37 Is8. The ancestral strain of Caulobacter sp. OR37 and Sediminibacterium sp. OR53 did not show a statistically significant increase in biomass or growth rate in coculture compared to the strains grown individually (Figure 16A; Table 21). In addition, the ancestral Caulobacter sp. OR37 did not show any significant increase in biomass or growth rate when grown in coculture with any of the re-isolated Sediminibacterium spp. OR53 strains (Table 21). However, the ancestral Sediminibacterium sp. OR53 strain did have an increased growth rate when in coculture with the re-isolated Caulobacter spp. OR37 Is14 and Is28 strains. Overall, some re-isolated strains in coculture showed significant increases in the amount of biomass and/or growth rate, while the ancestral coculture had no significant increases in either biomass or growth rate. The ability of the re-isolated strains to immobilize uranium was also assessed individually and in coculture. None of the re-isolated strains were able to individually immobilize more uranium than the ancestral Caulobacter sp. OR37 strain (Table 22). Almost all individual strains were able to immobilize more uranium than the ancestral Sediminibacterium sp. OR53 strain. All of the cocultures with re-isolated strains were able to immobilize more uranium than the ancestral Sediminibacterium sp. OR53 and Caulobacter sp. OR37 coculture. The majority of uranium immobilization occurred during lag phase in all Sediminibacterium spp. OR53 strains in the presence of 300 µM uranium (Figure 17). All Sediminibacterium spp. OR53 strains had an extended lag phase of 2-4 days. Once in log phase, the amount of detectable uranium remained constant. A different trend was observed with the ancestral and re-isolated

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Figure 16. Influence of 300 µM uranium on the OD600 over time (growth) of (A) ancestral (A); and (B) re-isolated (R) Caulobacter spp. OR37 and Sediminibacterium spp. OR53 strains grown individually and as a coculture (mean, n=3). The graph containing both ancestral strains represents an example of no increases in max OD600 (biomass yield) in coculture compared to individually grown strains, while the graph containing the re-isolated strains is a visual representation of an increase in biomass yield in the coculture compared to individually grown strains as enumerated in Table 21.

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A B

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Table 21. Growth rate and maximum OD600 (biomass yield) of ancestral and re-isolated Caulobacter spp. OR37 and Sediminibacterium spp. OR53 as a coculture in the presence of 300 µM uranium (mean±SD, n=3). Values in bold represent instances where the growth rate (GR) or biomass yield (Yield) of the cocultures were significantly higher than the GR or Yield of both individual cultures using the T-test (p < 0.05; n=3). Growth rates and biomass yields of the individual cultures are not present in table.

OR53 OR53 Is7 OR53 Is18 OR53 Is70 (ancestral) (re-isolated) (re-isolated) (re-isolated) GR Yield GR Yield GR Yield GR Yield OR37 0.28±0.01 0.16±0.02 0.13±0.00 0.069±0.004 0.12±0.00 0.079±0.004 0.14±0.01 0.089±0.008 (ancestral) OR37 Is8 0.13±0.01 0.072±0.008 0.23±0.01 0.11±0.01 0.19±0.01 0.15±0.01 0.19±0.00 0.12±0.01 (re-isolated) OR37 Is14 0.17±0.00 0.082±0.003 0.15±0.00 0.081±0.004 0.18±0.00 0.091±0.00 0.20±0.01 0.084±0.007 (re-isolated) OR37 Is28 0.18±0.00 0.12±0.00 0.097±0.004 0.12±0.01 0.099±0.003 0.098±0.003 0.13±0.01 0.089±0.010 (re-isolated)

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Table 22. Uranium concentration (µM) in the presence of re-isolated and ancestral strains of Caulobacter spp. OR37 and Sediminibacterium spp. OR53 either individually or in coculture after seven days exposure to 300 µM uranium. Uranium immobilization on day seven was calculated by subtracting the experimental value from the media blank containing uranium and computing the average (mean±SD; n=6). Values associated with each strain designation (dark boxes) represent the amount of uranium immobilized by the individual strains. Values in all other boxes represent the amount of uranium immobilized by cocultures containing a Sediminibacterium sp. OR53 strain and a Caulobacter sp. OR37 strain. Different letters represent a significant difference in the amount of uranium immobilized when re-isolated strains were compared to their respective ancestral strain (dark boxes), or when cocultures were compared to the ancestral coculture using one-way ANOVA and Tukey (p < 0.05). Values with the same letter were not significantly different.

OR53 OR53 Is7 OR53 Is18 OR53 Is70 (ancestral) (re-isolated) (re-isolated) (re-isolated) 17.48±37.96a 38.09±30.59a 16.62±14.77a 53.19±50.92a OR37 (ancestral) 20.44±48.88a 81.16±27.29bd 84.33±24.04bcd 132.90±27.92c 119.62±54.62a OR37 Is8 (re-isolated) 78.66±24.46bd 51.77±7.20ab 59.11±4.23abd 106.13±58.93cd 95.97±47.08ab OR37 Is14 (re-isolated) 44.57±5.25ab 75.07±18.64bd 56.63±5.17abd 55.69±9.72abd 69.91±19.22b OR37 Is28 (re-isolated) 38.05±10.35ab 39.74±7.11ab 41.29±8.97ab 68.57±23.59abd 68.69±28.15b

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Figure 17. The OD600 and the uranium concentration in the medium over time of individual ancestral and re-isolated Sediminibacterium spp. OR53 and Caulobacter sp. OR37 strains over seven days (mean±SD, n=3).

! 112!

! 113! Caulobacter spp. OR37 strains (Figure 17). Uranium concentrations in the medium decreased throughout the growth of Caulobacter spp. OR37 strains and independent of the growth phase.

Uranium localization for individual ancestral and re-isolated strains The mechanism of uranium immobilization in Caulobacter sp. OR37 and Sediminibacterium sp. OR53 are unknown. TEM was used to visualize uranium localization in whole cells, to help identify their mechanism of immobilization, and determine if these mechanisms were altered during the long-term growth experiment. There were no visual differences between the ancestral or re-isolated Sediminibacterium spp. OR53 strains in the presence or absence of uranium (Figure 18-19). All Sediminibacterium spp. OR53 cells were bacilli 1.5-2.0 µm in length and 0.5-0.75 µm wide with no visible extracellular structures (Figure 18). In the presence of uranium Sediminibacterium spp. OR53 cells were darker across the entire cell surface with no clear pattern of localization (Figure 19). There were no notable structural differences between the ancestral and re-isolated Caulobacter spp. OR37 strains in the presence or absence of uranium (Figure 20-21). In the absence of uranium, Caulobacter spp. OR37 cells were either crescent-shaped with a polar stalk or rod-shaped with a single flagellum (Figure 20). Cells undergoing asymmetric cell division maintained a stalk at one end and produced a flagellar cell at the opposing end. Caulobacter spp. OR37 strains were consistently 1.5-2.0 µm in length. In the presence of uranium, dark areas were localized in small circular masses associated with Caulobacter spp. OR37 cells (Figure 21). EDS was used in combination with STEM to visualize the distribution of chemical elements across ancestral and re-isolated strains. In ancestral and re-isolated Sediminibacterium strains, uranium and phosphorus were evenly distributed across the cell (Figure 22-23). Elemental analysis of Sediminibacterium sp. OR53 Is18 showed that the ratio of phosphate to uranium was almost 1:1 (P: 54.06%, U: 45.94%) (Figure 23D). Dark regions in the micrographs of Sediminibacterium sp. OR53 Is18 showed dense areas where sodium and sulfur appeared to colocalize (Figure 23A, Figure 23E-G). However, uranium did not colocalize with either sodium or sulfur (Figure 23H). In both Sediminibacterium strains, phosphorus was the only element that colocalized with uranium (Figure 22B, Figure 23D). Re-isolated and ancestral Caulobacter spp. OR37 strains had variations in the distribution of phosphorus and uranium (Figure 24-25). The ancestral Caulobacter sp. OR37 strain showed

! 114!

Figure 18. Whole-cell TEM micrographs of re-isolated and ancestral strains of Sediminibacterium spp. OR53 in the absence of uranium. (A) Ancestral Sediminibacterium sp. OR53; (B) re-isolated Sediminibacterium sp. OR53 Is7; (C) re-isolated Sediminibacterium sp. OR53 Is18; and (D) re-isolated Sediminibacterium sp. OR53 Is70. Scale bar = 1 µm.

! 115!

A B

C D

! 116!

Figure 19. Whole-cell TEM micrographs of ancestral and re-isolated strains of Sediminibacterium spp. OR53 in the presence of 300 µM uranium. (A) Ancestral Sediminibacterium sp. OR53; (B) re-isolated Sediminibacterium sp. OR53 Is7; and (C) re- isolated Sediminibacterium sp. OR53 Is18. No image available for Sediminibacterium sp. OR53 Is70. Scale bar = 0.5 µm.

! 117!

! 118!

Figure 20. Whole-cell TEM micrographs of ancestral and re-isolated strains of Caulobacter spp. OR37 in the absence of uranium. (A) Ancestral Caulobacter sp. OR37; (B) re-isolated Caulobacter sp. OR37 Is8; (C) re-isolated Caulobacter sp. OR37 Is14; and (D) re-isolated Caulobacter sp. OR37 Is28. Scale bar = 1 µm.

! 119!

A B

C D

! 120!

Figure 21. Whole-cell TEM micrographs of ancestral and re-isolated strains of Caulobacter spp. OR37 in the presence of 300 µM uranium. (A) Ancestral Caulobacter sp. OR37; (B) re-isolated Caulobacter sp. OR37 Is8; (C) re-isolated Caulobacter sp. OR37 Is14; and (D) re-isolated Caulobacter sp. OR37 Is28. Scale bar = 1 µm.

! 121! A B

C D

!

! 122!

Figure 22. Elemental analysis of the ancestral Sediminibacterium sp. OR53 strain grown in the presence of 300 µM uranium. STEM micrographs show whole-cell (A) Sediminibacterium sp. OR53; an EDS mapping of the distribution of elemental (B) phosphorus (green) and uranium (red); (C) the distribution of elemental phosphorus; and (D) uranium. White arrows indicate areas of colocalization of uranium and phosphorus (yellow). Scale bar = 200 nm.

! 123!

A B

C D

! 124!

Figure 23. Elemental analysis of re-isolated Sediminibacterium sp. OR53 Is18 strain grown in the presence of 300 µM uranium. STEM micrographs show whole-cell (A) Sediminibacterium sp. OR53 Is18; and an EDS mapping of the distribution of elemental (B) phosphorus (green); (C) uranium (red); (D) an overlay of phosphorus and uranium; (E) sodium (yellow); (F) sulfur (blue); (G) an overlay of sulfur and sodium; and (H) an overlay of sulfur and uranium. Scale bar = 400 nm.

! 125!

! 126!

Figure 24. Elemental analysis of ancestral Caulobacter sp. OR37 grown in the presence of 300 µM uranium. STEM micrographs show whole-cell (A) Caulobacter sp. OR37; and an EDS mapping of the distribution of elemental (B) phosphorus (green); (C) uranium (red); and (D) an overlay of phosphorus and uranium. White arrows indicate areas of colocalization of uranium and phosphorus (yellow). Scale bar = 1 µm.

! 127! A

B

C

D

! 128!

Figure 25. Elemental analysis of re-isolated Caulobacter sp. OR37 Is14 strain grown in the presence of 300 µM uranium. STEM micrographs show whole-cell (A) Caulobacter sp. OR37 Is14; an EDS mapping of the distribution of elemental (B) phosphorus (green); (C) uranium (red); and (D) an overlay of phosphorus and uranium. White arrows show areas of colocalization of uranium and phosphorus (yellow). Scale bar = 600 nm.

! 129!

! 130! uranium distributed across the cell and in small circular masses associated with the cell (Figure 24C-D). The distribution of uranium observed with Caulobacter sp. OR37 Is14, however, was different from the ancestral strain (Figure 25C). Elemental analysis of Caulobacter sp. OR37 Is14 primarily showed uranium localized to a dark area at the end of the stalk and the tangled mass associated with the cell (Figure 25D).

Genomic mapping and variation analysis of re-isolated strains The genomes of the re-isolated strains were sequenced and mapped back to the ancestral genome to look for nucleotide substitutions, deletions, and additions that could correspond to potential adaptations to uranium or bacterial interactions. The coverage of reads for Caulobacter spp. OR37 Is8, Is14, and Is28 to the ancestral genome was low compared to Sediminibacterium spp. OR53 (Table 23). As a result, the reads from Caulobacter spp. OR37 Is14 and Is28 did not cover the entire reference genome. The genomes of the re-isolated strains showed numerous nucleotide substitutions, deletions, and additions compared to the ancestral genomes (Table 24, Table 26). When re-isolated strains had a nucleotide change at the same position in an ancestral gene, the nucleotide substituted, deleted, or addition was the same in all strains. Most of the re- isolated strains contained at least one nucleotide substitution, deletion, or addition not found in other strains. The majority of the nucleotide changes in the re-isolated Sediminibacterium spp. OR53 strains were concentrated in genes encoding hypothetical proteins (Table 24). The hypothetical proteins were located in putative operons with other hypothetical proteins. Prediction of protein function could not be elucidated with BLAST. Out of the 37-nucleotide changes in the genome of Sediminibacterium sp. OR53 Is7, only 4 resulted in amino acid changes (Table 25). All amino acid changes were a result of single or multiple nucleotide substitutions. They occurred at positions 1972447, 3707220, 3711901, and 3712716-3712717 of the Sediminibacterium sp. OR53 reference genome. The amino acid change at 3707220 was unique to Sediminibacterium sp. OR53 Is7 and resulted in a change from threonine to alanine in hypothetical protein 1 (Table 26). The amino acid change at position 1972447 occurred in Sediminibacterium spp. OR53 Is70 and Is7 and introduced a premature stop codon at amino acid 175 of a 340 amino acid putative outer membrane protein. The other amino acid changes (positions 3711901 and 3712716-

! 131!

Table 23. Read mapping coverage of re-isolated strains to the ancestral genomes. Caulobacter spp. OR37 Sediminibacterium spp. OR53 Reference genome length 4,430,425 bp 3,715,967 bp Re-isolated strains Is8 Is14 Is28 Is7 Is18 Is70 Number of reads 351,524 206,740 134,858 669,928 610,168 922,664 Number of mapped reads 340,757 199,208 126,414 662,559 598,618 908,446 Fraction of reference covered 1.0 0.99 0.95 1.0 1.0 1.0 Average coverage 14.51 9.20 5.96 28.87 26.01 41.74 Coverage standard deviation 6.56 4.98 4.08 10.19 9.41 14.59

! 132!

Table 24. Genetic variations in the re-isolated strains of Sediminibacterium spp. OR53 compared to the ancestral strain. Values represent the number of nucleotide variations (deletions, substitutions, and additions) in the re-isolated strains.

Reference Gene Is 7 Is 18 Is 70 Gliding-associated ABC transporter 1 - 1

Putative outer membrane protein 1 - 1

tRNA_Val_TAC 5 - -

HAE efflux pump 1 - 1

Putative regulator of cell autolysis 1 - 1

Hypothetical protein 1 4 7 7

Hypothetical protein 2 1 1 1

Hypothetical protein 3 23 27 20

! 133!

Table 25. Location of amino acid changes in re-isolated Sediminibacterium spp. OR53 strains. The strain(s) containing a nucleotide change resulting in a subsequent amino acid change are indicated with an “X”. Reference Amino acid Original Amino Protein Position (nt) Is7 Is18 Is70 length amino acid acid change Putative outer membrane protein 1972447 X X 340 Gln Stop Hypothetical protein 1 3707220 X 969 Thr Ala Hypothetical protein 2 3711901 X X X 649 Leu Ser Hypothetical protein 3 3712716-3712717 X X X 1150 Thr Thr/Ser

! 134!

Table 26. Genetic variations in the re-isolated strains of Caulobacter spp. OR37 compared to the ancestral strain. Values represent the number of nucleotide variations (deletions, substitutions, and additions) in the re-isolated strains.

Reference Gene Is 8 Is 14 Is 28 No predicted CDS 4 7 1 Hypothetical protein 1 - - Signal transduction kinase 1 - - Deoxyhypusine synthase 1 1 - Xanthine dehydrogenase, small subunit 1 - - UDP-glucose dehydrogenase 2 - -

! 135! 3712717) appeared in all three re-isolated Sediminibacterium spp. OR53 strains and resulted in changes in hypothetical proteins 2 and 3, respectively (Table 25). In hypothetical protein 2, a leucine was changed to a serine. In hypothetical protein 3, there were two adjacent nucleotide substitutions that were predicted to either maintain the same amino acid, threonine, or change it to serine. Most of the nucleotide changes in the re-isolated Caulobacter spp. OR37 strains were not found in predicted coding regions (Table 26). Caulobacter sp. OR37 Is8 had the most amino acid changes of the re-isolated Caulobacter spp. OR37 strains (Table 27). Two of the nucleotide changes in Caulobacter sp. Is8 were deletions that resulted in frameshift mutations at positions 54255 and 11113 in genes encoding a signal transduction histidine kinase and deoxyhypusine synthase, respectively. The frame shift at position 11113 was also present in Caulobacter sp. OR37 Is14 (Table 27). Another amino acid change occurred at reference position 882 in Caulobacter sp. OR37 Is8 and changed an asparagine to aspartic acid in a putative UDP-glucose dehydrogenase gene. No amino acid changes were observed in Caulobacter sp. OR37 Is28.

! 136!

Table 27. Location of amino acid changes in re-isolated Caulobacter spp. OR37 strains. The strain(s) containing a nucleotide change resulting in a subsequent amino acid change are indicated with an “X”. Reference Amino acid Original Amino Protein Position (nt) Is8 Is14 Is28 length amino acid acid change Signal histidine kinase 54255 X 415 Arg FS* Deoxyhypusine synthase 11113 X X 963 Thr FS* UDP-glucose dehydrogenase 958 X 434 Asn Asp *FS: Frameshift

! 137! Discussion The development of interactions between two bacterial species can require long-term exposure of weeks to years between species to establish stable and productive communities [90, 92]. The contaminated subsurface at Oak Ridge, Tennessee maintains microbial communities capable of immobilizing uranium [155]. Few studies have addressed the interactions between microbial species that contribute to the stability of microbial communities in a uranium- contaminated environment [78, 86-87, 92, 200, 202]. The composition of species in microbial communities is important for the biodegradation of many toxic and complex compounds [86-87, 200-202]. Therefore, we examined the genotypic and phenotypic characteristics in strains re- isolated from a long-term community maintained in the presence of uranium. Re-isolated strains were tested under single strain as well as new coculture conditions. The new coculture experiments provided evidence for the development of specific interactions between members of the community in the presence of uranium. The ancestral Caulobacter sp. OR37 and Sediminibacterium sp. OR53 strains showed no significant increase in biomass production or growth rate in coculture compared to the individual cultures, which suggests that there are no interactions or there is competition between these strains (Table 21, Table 28). Additionally, the ancestral Caulobacter sp. OR37 strain was not able to increase the growth of any of the re-isolated Sediminibacterium spp. OR53 strains, whereas the ancestral Sediminibacterium sp. OR53 strain increased the growth rate of two re-isolated Caulobacter spp. OR37 strains in coculture. This suggests that Caulobacter sp. OR37 was likely competing with Sediminibacterium sp. OR53. However, the interactions between Sediminibacterium sp. OR53 and Caulobacter sp. OR37 changed throughout the long-term growth experiment. These changes resulted in several of the re-isolated Caulobacter spp. OR37 strains exhibiting significant increases in growth rate or biomass production in coculture with re-isolated Sediminibacterium sp. OR53 strains and suggests that Caulobacter sp. OR37 needed time to adapt to the presence of Sediminibacterium sp. OR53 (Table 21, Table 28). The re-isolated Sediminibacterium spp. OR53 and Caulobacter spp. OR37 strains individually had significantly lower growth rates and biomass production when compared to the ancestral strains (Table 18-19). The decrease in individual growth suggests that long-term exposure to uranium or interactions between species impacted the growth of the re-isolated strains. Organisms maintained in monoculture in long-term growth experiments typically adapt

! 138!

Table 28. Positive effects (+) of the OD600 (growth) in cocultures of ancestral and re-isolated Caulobacter spp. OR37 and Sediminibacterium spp. OR53 in the presence of 300 µM uranium after two days. Positive effects were determined by comparing the growth rates (GR) and biomass yield (yield) of the single cultures with the coculture using T-test (n=3, p < 0.05)

OR53 OR53 Is7 OR53 Is18 OR53 Is70 (ancestral) (re-isolated) (re-isolated) (re-isolated) GR Yield GR Yield GR Yield GR Yield OR37 (ancestral) OR37 Is8 + + + (re-isolated) OR37 Is14 + + + + + (re-isolated) OR37 Is28 + + + + + (re-isolated)

! 139! to the growth conditions and are able to outgrow the ancestral culture, which suggests that interactions between species likely impacted the growth of the re-isolated Sediminibacterium spp. OR53 and Caulobacter spp. OR37 strains [89, 178-179, 207-213]. Lawrence et al. showed that re-isolated strains from a long-term coculture that were grown individually had decreased growth compared to the ancestral strain, but growth was improved when the strain was provided with spent media from another strain from the coculture [78]. It is not clear whether the interactions between Sediminibacterium sp. OR53 and Caulobacter sp. OR37 were related to cross-feeding. However, cross-feeding mechanisms are sensitive to changes in conditions and no increases in growth rate or biomass production were observed for cocultures in the absence of uranium (data not shown) [95]. The nucleotide variations and subsequent amino acid changes in the re-isolated Sediminibacterium spp. OR53 and Caulobacter spp. OR37 could contribute to the increase in growth rate or biomass production of the cocultures. Nucleotide variations may arise from select pressures from other species and result in changes in gene expression [206]. Additionally, nucleotide variations resulting in amino acid changes may impact the function of the putative peptide. Most of the nucleotide variations in Sediminibacterium spp. OR53 and Caulobacter spp. OR37 were in hypothetical proteins or non-coding regions (Table 24, Table 26). The number of variations in some of these genes suggests they may be important in adapting to biotic and abiotic factors, but additional studies are required to elucidate their function because it is possible nucleotide changes can occur in response to uranium or as normal spontaneous mutations. It is unclear if nucleotide variations resulting in single amino acid changes had an impact on the protein activity. However, the nucleotide variation in a putative outer membrane protein in Sediminibacterium sp. OR53 introduced a premature stop codon, which likely results in a non-functional protein that could have been influenced by the presence of Caulobacter sp. OR37 (Table 25). The nucleotide changes in deoxyhypusine synthase and the signal transduction histidine kinase resulted in frameshift mutations that may have impacted the function of the protein and/or down-stream gene expression or protein production in Caulobacter sp. OR37 (Table 27). The frameshift in the signal transduction histidine kinase (415 amino acids) and deoxyhypusine synthase (DHS) (963 amino acids) potentially altered the last 83 and 386 amino acids in the protein, respectively. DHS is involved in post-translational modification of an initiation factor

! 140! described in eukaryotes and archaea [214]. Although bacterial DHS has high sequence identity to eukaryotic DHS, bacteria have a very distant homolog of the eukaryotic initiation factor that has not been shown to associate with the bacterial DHS. Therefore, DHS may have an unknown regulatory role in Caulobacter sp. OR37. The signal transduction histidine kinase is located in a putative operon with a gene containing a CheY-like receiver domain and winged-helix DNA binding domain, and a gene annotated as a chromate transporter (data not shown). A frameshift in the signal transduction histidine kinase might allow for the extrusion of uranium using the chromate transporter. However, it is not clear how the frameshift may have altered the function of the DHS or the signal transduction kinase so we cannot determine if activity of these enzymes was enhanced or inhibited by the nucleotide variations. Additionally, it is possible that other nucleotide variations may be present in the re-isolated Caulobacter spp. OR37 strains, but elucidating these changes requires re-sequencing of their genomes to improve read coverage (Table 23). Despite the development of interactions that resulted in increased growth rate and biomass of the cocultures there was not an obvious correlation with the ability to sequester uranium in the cultures (Table 21-22, Table 24). The ancestral Caulobacter sp. OR37 strain immobilized more uranium than any of the individual re-isolated Caulobacter spp. OR37 or Sediminibacterium spp. OR53 strains (Table 22). It is possible that the re-isolated Caulobacter spp. OR37 strains developed a tolerance to higher concentrations of uranium that resulted in a decrease in the amount of uranium immobilized by these strains. Since Caulobacter sp. OR37 has a short lag phase in the presence of uranium, we assessed tolerance to uranium by the initial uranium concentration in the media when each strain was grown individually in the presence of 300 µM uranium (Figure 17). Re-isolated strains would be expected to have higher growth rates at higher initial uranium concentrations if the re-isolated strains were more tolerant than the ancestral strains to uranium. These data suggest that there is no correlation with the growth of the re-isolated Caulobacter spp. OR37 strains and the initial uranium concentration (data not shown). Additionally, the presence of Sediminibacterium sp. OR53 in coculture with Caulobacter sp. OR37 resulted in decreased uranium immobilization in most cases, which suggests that Sediminibacterium spp. OR53 impacted the uranium immobilization of Caulobacter sp. OR37 (Table 22). The rate at which uranium decreased in the coculture was similar to the rate at which individual Caulobacter spp. OR37 strains immobilized uranium,

! 141! suggesting that Caulobacter spp. OR37 is primarily responsible for uranium immobilization (data not shown). Overall, it is more likely that re-isolated Caulobacter spp. OR37 strains were decreased in their ability to immobilize uranium and that this decrease was due to the presence of Sediminibacterium spp. OR53. The morphology of the re-isolated and ancestral strains in the presence of uranium, the distribution of uranium across the cell, and the amount of uranium immobilized by the strains over time support the hypothesis that Sediminibacterium sp. OR53 and Caulobacter sp. OR37 use different mechanisms for uranium immobilization. TEM images of the ancestral and re- isolated Sediminibacterium spp. OR53 strains grown in the presence of uranium revealed dark areas distributed across the cell that corresponded with the colocalization of uranium and phosphorus (Figure 19-20, Figure 22-23). Colocalization was especially evident around the cell periphery suggesting that uranium and phosphorus were similarly distributed. The electron-dense area in the interior of Sediminibacterium sp. OR53 Is18 primarily contained sodium and sulfur (Figure 23A, Figure 23E). Sodium is an essential element that bacteria require to maintain osmotic balance and pH [75]. Sodium is usually distributed throughout the cell interior. Therefore, the localized concentration of sodium observed in Sediminibacterium sp. OR53 Is18 is likely the result of a collapsed cytoplasm [R. Edelmann, personal communication]. Sodium was also found to colocalize with sulfur in these cells (Figure 23E-G). Sulfur is commonly associated with certain amino acids in proteins as well as iron- sulfur clusters. The amount of sulfur is most likely due to the high concentration of proteins in the cytoplasm [75]. Uranium and phosphorus did not colocalize with sodium or sulfur (Figure 23H). Overall, our results suggest that uranium did not accumulate inside Sediminibacterium spp. OR53 cells, and is likely interacting with phosphorus-containing compounds on the outside of the cell. Therefore, biosorption in which phosphate groups located in the lipopolysaccharide (LPS) bind uranium in an energy-independent manner is likely the primary mechanism of uranium immobilization in Sediminibacterium sp. OR53 [57, 217]. Biosorption of uranium also corresponds with uranium immobilization during lag phase, because the biosorption of heavy metals tends to decrease with increasing biomass due to cell agglomeration [193, 218-220]. We were unable to grow Sediminibacterium sp. OR53 Is70 for microscopy in the presence of 300 µM uranium. However, based on the similar growth patterns and decrease in uranium

! 142! concentration to the other re-isolated Sediminibacterium strains, the LPS is likely used to bind uranium in Sediminibacterium sp. OR53 Is70 (Figure 15, Figure 17; Table 18-20, Table 22). The micrographs and elemental analyses of ancestral and re-isolated Caulobacter spp. OR37 strains were different from Sediminibacterium spp. OR53 strains. In re-isolated and ancestral Caulobacter spp. OR37 strains grown in the presence of uranium, dark circular masses were visibly associated with the cell where uranium and phosphorus colocalized in ancestral Caulobacter sp. OR37 (Figure 21, Figure 24C). Phosphorus was also distributed across the cell, but the uranium and phosphorus colocalized more consistently within the circular masses (Figure 24). It was not clear from the images whether colocalization occurred intra- or extracellularly. Uranium can form intracellular complexes with phosphate known as polyphosphate bodies, but it can also be precipitated outside the cell as uranyl phosphate complexes [42, 61-67, 126, 193- 195]. Since the cells were washed prior to imaging, extracellular uranyl phosphate complexes were likely removed. However, it is possible that portions of the dense complexes may still be bound to the LPS resulting in the dark masses that were observed with Caulobacter spp. OR37 (Figure 21). There has been no evidence to date that Caulobacter species accumulate uranium intracellularly [67]. Uranium precipitation is also consistent with the distribution of uranium across the cell (Figure 25C). Uranium precipitation requires initial binding to the LPS prior to the activation of periplasmic phosphatases and subsequent precipitation [63, 65]. Additionally, the use of uranium precipitation as the mechanism for uranium immobilization supports the decrease in uranium concentration throughout the stages of growth observed in Caulobacter spp. OR37 strains (Figure 18). The micrographs and elemental analysis between ancestral and re-isolated Caulobacter spp. OR37 strains varied slightly, but re-isolated and ancestral Caulobacter spp. OR37 strains likely precipitated uranium. Caulobacter sp. OR37 Is14 did not exhibit uranium binding evenly across the cell like the ancestral strain (Figure 24-25). Although there were dark masses consistent with what was observed in the ancestral strain there was no colocalization of uranium and phosphorus associated with the dark spots detected using elemental mapping. The majority of the phosphorus and uranium detected was associated with an extracellular mass associated with the cell or the complex at the distal end of the stalk (Figure 25). Similar complexes were identified in the ancestral strain, but not necessarily associated with the stalk (data not shown).

! 143! An EDS spectrum produced by focusing on a region of a Caulobacter sp. OR37 Is14 cell containing a dark circular mass showed that uranium and phosphorus were both present in the dark mass, but they were present in low abundance (Figure 26). The low concentrations of uranium and phosphorus could explain why these elements were not detected during elemental mapping. In addition, the black complex at the distal end of the stalk not only showed colocalization of uranium and phosphorus, but also had similar morphology to precipitates observed in another Caulobacter species (Figure 25) [67]. The mass associated with the cell was most likely an abiotic complex from the media because it was observed in cells grown in the absence of uranium and in the medium controls (data not shown). There was no indication that any of the strains used alternative mechanisms compared to the ancestral Caulobacter sp. OR37 strain (Figure 21). Overall, our results indicate that the long-term growth experiment did not impact the mechanism of uranium immobilization used by Caulobacter sp. OR37. Our results suggest that there are commensalistic/mutualistic and competitive interactions present between Sediminibacterium sp. OR53 and Caulobacter sp. OR37 in the presence of uranium. The interactions initially present between the ancestral strains were likely a result of competition for space and nutrients in the media, which negatively impacted the ability of the ancestral coculture to immobilize uranium (Table 22). In the long-term growth experiment, a cross-feeding related mechanism developed that was commensalistic with only one species benefitted, or mutualistic with reciprocation by both species. Cross-feeding would explain the increased growth rate and biomass production by the re-isolated cocultures that may have also alleviated some of the competition between Sediminibacterium sp. OR53 and Caulobacter sp. OR37 (Table 21, Table 28). Additionally, it would correlate with the lower amounts of biomass produced by the re-isolated strains compared to the ancestral (Table 19). Competition was still present between the re-isolated strains because Caulobacter sp. OR37 in coculture with Sediminibacterium sp. OR53 was not able to immobilize as much uranium as individual Caulobacter spp. OR37 strains (Table 22). Phosphate is the substrate for which Sediminibacterium sp. OR53 and Caulobacter sp. OR37 would likely compete for and would impact uranium precipitation by Caulobacter spp. OR37 [42, 54, 61-67, 203]. The tolerance of Caulobacter species to uranium is dependent on the concentration of available phosphate [182]. However, the competition for phosphate between re- isolated Sediminibacterium spp. OR53 and Caulobacter spp. OR37 strains was not as prohibitive

! 144!

Figure 26. Micrograph of uranium associated with re-isolated Caulobacter sp. OR37 Is14. (A) Caulobacter sp. OR37 Is14 grown in the presence of 300 µM uranium. The area in the black box was analyzed with EDS. (B) EDS spectra of the boxed area.

! 145!

! 146! as the competition between the ancestral strains because all the re-isolated cocultures were able to immobilize more uranium than the ancestral coculture (Table 22). Additional research is required to determine whether the decrease in competition was a result of cross-feeding or the adaptation of either Sediminibacterium sp. OR53 or Caulobacter sp. OR37 to a phosphate- limited environment. Overall, our data demonstrate how positive interactions between unrelated species develop following long-term associations and the impact these interactions can have on growth and uranium immobilization. Further studies are required to eliminate the possibility that Rhodanobacter sp. OR444 and Ralstonia sp. OR214 could influence the interactions between Caulobacter sp. OR37 and Sediminibacterium sp. OR53 in the presence of uranium.

! 147! Acknowledgements The authors would like to acknowledge Brock Avirett for the preparation of the re-isolated strains for sequencing on the MiSeq. We thank the Center for Bioinformatics and Functional Genomics (CBFG) at Miami University for providing access to molecular tools such as the MiSeq and the CLC Workbench software used for analysis of the MiSeq data. We also would like to acknowledge the Center for Advanced Microscopy Imaging (CAMI) facility at Miami University for the materials and usage of the microscopes. Finally, we acknowledge Dr. Richard Edelmann for the training and guidance in the preparation of microscopy samples. Additionally, we thank Dr. Edelmann for obtaining all of the images using the scanning transmission electron microscope and corresponding elemental maps.

! 148! SUMMARY Uranium as a naturally occurring heavy metal is an environmental contaminant due to anthropogenic use. Uranium contamination at Oak Ridge, Tennessee was a result of leaching from the S-3 waste ponds [17]. For over 30 years, these ponds leached heavy metals, organic solvents, nitric acid, and radioactive isotopes into the surrounding soil and underground aquifers. However, there are bacteria that are able to persist in these environments. Some bacteria have mechanisms for decreasing the uranium concentration in the environment [35, 54, 56]. Although individual species can remove uranium, microbial communities are often more effective due to interactions between species [21-22, 26, 28, 91, 157, 186, 219-222]. An individual species can be limited by factors such as nutrient availability or the accumulation of toxic waste products that may impede the rate or amount of uranium immobilized. Associations with other species may result in interactions that alleviate these limitations. To date, little information is available about these interactions and how they influence the bioremediation of uranium in aerobic soils [42, 203]. The goals of this dissertation were to characterize the physiological and genomic differences between two Sediminibacterium strains isolated from the uranium-contaminated subsurface-sediment at Oak Ridge, Tennessee, and to determine the long-term impact of the presence or absence of uranium or low pH on populations within an artificial community.

Physiological and genomic comparison of Sediminibacterium spp. OR43 and OR53 In general, Sediminibacterium sequences and sequences from closely related strains were detected in a variety of contaminated environments, but their role in these environments has not been elucidated [101-109, 119-125]. Sediminibacterium spp. OR43 and OR53 were isolated from Oak Ridge, Tennessee [101]. Based on 16S rRNA Sediminibacterium spp. OR43 and OR53 had 96.4% sequence identity, but Sediminibacterium sp. OR53 was more tolerant of uranium than Sediminibacterium sp. OR43. We hypothesized that Sediminibacterium spp. OR43 and OR53 were adapted to the conditions at Oak Ridge based on the presence of genes for tolerating nitrate, heavy metals, uranium, and low pH. We also hypothesized that the physiological differences in uranium tolerance between Sediminibacterium spp. OR43 and OR53 were a result of the presence or absence of genes related to heavy metal tolerance. The subsurface sediment at Oak Ridge contains uranium (VI) concentrations up to 250 µM [17]. Sediminibacterium spp. OR43 and OR53 were grown in a range of uranium

! 149! concentrations to determine their tolerance. Sediminibacterium sp. OR43 could not grow in uranium concentrations above 200 µM. Sediminibacterium sp. OR53 grew in 200 and 300 µM uranium. Sediminibacterium sp. OR43 had an increased lag phase and slower growth rate than Sediminibacterium sp. OR53, suggesting that Sediminibacterium sp. OR53 was more tolerant to uranium concentrations ≥ 200 µM. The number of homologs of experimentally verified heavy metal resistance genes identified from the BacMet database in the genomes of Sediminibacterium spp. OR43 and OR53 was similar [146]. Sediminibacterium sp. OR53 had a few more genes putatively for resistance, but the presence of these genes did not result in a higher tolerance to other heavy metals [101]. Sediminibacterium sp. OR53 had more membrane-associated phosphatases than any other closely related strain, which suggested that it might precipitate uranium as uranyl phosphate complexes using phosphatases (Chapter 1). Although some bacteria use phosphatases for uranium immobilization, our results from TEM and elemental analyses (Chapter 3) did not provide evidence of phosphatases as a mechanism for uranium immobilization in Sediminibacterium sp. OR53 [40, 42, 62-63, 65-66, 225]. These results suggest that the uranium binds to phosphate groups in the lipopolysaccharide (LPS) in Sediminibacterium sp. OR53 [57, 215]. The hypothesis that the difference in uranium tolerance between Sediminibacterium spp. OR43 and OR53 was a result of the presence or absence of heavy metal-related genes was not supported. Although, there was a difference in the quantity of copper efflux P-type ATPases, cation efflux pumps, and phosphatases in Sediminibacterium sp. OR53 compared to Sediminibacterium sp. OR43, the presence of a gene did not necessarily confer tolerance. Bacteria can transport and bind substrates with different rates and this contributes to variations in heavy metal tolerance between bacterial strains [224]. Additionally, the TEM and elemental analysis do not support Sediminibacterium sp. OR53 precipitating uranium despite the identification of phosphatases in the genome. In addition to uranium, the subsurface sediment at Oak Ridge has a low pH and contains nitrate [17]. Sediminibacterium spp. OR43 and OR53 were unable to grow at pH < 4.5, which is in agreement with other closely related strains [101, 119-125]. The Sediminibacterium spp. OR43 and OR53 genomes contained the same genes for tolerating pH, but genes described as being important for adapting to extremely low pH (≤ 3) were absent from both genomes [148,

! 150! 177]. Neither strain was able to grow at nitrate concentrations > 50 mM. The genomes of both strains were missing the nitrate reductase essential for nitrate reduction, which explains their inability to transform nitrate under anaerobic conditions. However, once nitrate is reduced to nitrite, Sediminibacterium spp. OR43 and OR53 have the genes necessary to use nitrite as an alternative electron acceptor in the denitrification or dissimilatory nitrate reduction to ammonia (DNRA) pathways. Our second prediction relating to the adaptation of Sediminibacterium sp. OR43 and OR53 to the characteristics at Oak Ridge was partially supported. The Sediminibacterium spp. OR43 and OR53 genomes contained genes for persisting in the presence of low pH, nitrate, heavy metals, and uranium at Oak Ridge, but they were sensitive to in situ pH values (3.5) and nitrate concentrations (500 mM) [17]. Our results suggest that other environmental factors must contribute significantly to their persistence at Oak Ridge.

Impact of uranium and low pH on the dynamics of a long-term artificial community Understanding the dynamics of natural microbial communities often requires assembling artificial communities in the laboratory without less abundant organisms or organisms unable to be maintained in pure culture [167]. Long-term growth experiments allow for closer comparisons to natural communities because there is more time for the organisms in the community to form stable interactions and to adapt to the growth conditions. Very few studies have addressed the types of interactions and adaptions that develop in the community and how they impact the community productivity in performing a specific function [78, 90, 92]. We chose to characterize an artificially assembled community containing four species with varying tolerances to pH and uranium. We predicted that there would be an increase in productivity of an artificially assembled community exposed to uranium (200 µM) or low pH (4.5) in a long-term growth experiment maintained for 30 weeks. Productivity was measured using optical density at 600 nm and used as an assessment of biomass under all conditions. Additionally, the concentration of uranium measured in the medium was used to assess productivity at pH 7 in the presence of uranium (pH7U). The strains that individually had the highest growth rate at pH 4.5, pH 7, or pH 7 with uranium were the most abundant in their respective condition. The community composition at pH 4.5 (pH4.5) and pH 7 (pH7) were similar with Ralstonia sp. OR214 consisting of 79% and

! 151! 67% of the community, respectively. Sediminibacterium sp. OR53, Caulobacter sp. OR37, and Rhodanobacter sp. OR444 were all present at pH7, but Rhodanobacter sp. OR444 disappeared from the pH4.5 condition. Sediminibacterium sp. OR53 and Caulobacter sp. OR37 were both present in higher abundance at pH7 than at pH4.5. Despite the similar compositions, the productivity of the community at pH4.5 decreased, while exhibiting relatively few changes at pH7. The productivity of these communities was consistent even when culture was transferred from the pH 7 to pH 4.5 (pH7->pH4.5) condition or vice versa (pH4.5->pH7). Sediminibacterium sp. OR53 and Caulobacter sp. OR37 were the most abundant at pH7U. Ralstonia sp. OR214 and Rhodanobacter sp. OR444 consisted of < 1% of the community and did not increase in abundance during the transition from pH7U to pH7 (pH7U->pH7). Caulobacter sp. OR37 increased in abundance over the first 5 weeks and made up 95% of the community, which correlated with an increase in optical density (biomass). Community biomass decreased slightly but stabilized as Sediminibacterium sp. OR53 increased in abundance at week 12. A similar trend was observed following the transition from pH7 to pH 7U (pH7->pH7U). The concentration of uranium measured in the medium also decreased over time at pH7U and in the pH7->pH7U condition. Our hypothesis that community productivity would increase over time at pH4.5, pH7, and pH7U was not supported. At pH7 and pH7U, the productivity of the community in terms of biomass remained unchanged across all 30 weeks. At pH4.5, the biomass production decreased over time. At pH7U, the amount of uranium removed by the community decreased. Organisms with the highest individual growth rate for a tested condition dominated in the respective condition, suggesting that competition was prominent in the community [175]. Therefore, competition for resources and the fitness of the organism for the condition likely limited the ability for increased productivity within the community. However, the shift in the abundance of Sediminibacterium sp. OR53 and Caulobacter sp. OR37 at pH7U suggests that the interaction between these species changed over time. Uranium had a drastic impact on species abundance in the long-term growth experiment, which led to the characterization of the growth of re-isolated strains individually and in new cocultures from the pH7U community. In addition, re-isolated strains from week 30 were assessed individually and in coculture for uranium immobilization compared to the ancestral

! 152! strains. We predicted that interactions between re-isolated species would have a beneficial impact on the growth and ability of the community to immobilize uranium. Only the two most abundant species of the community, Sediminibacterium sp. OR53 and Caulobacter sp. OR37, were re-isolated from the pH7U condition. We observed that some cocultures of the re-isolated Sediminibacterium spp. OR53 and Caulobacter spp. OR37 strains showed increased growth rate or biomass production compared to the individual strains. When these re-isolated strains were grown individually, they were unable to outgrow the ancestral strains in the presence of 0, 200, or 300 µM uranium. The ancestral strains did not show an increase in growth rate or biomass production in coculture, suggesting that during the long-term growth experiment Sediminibacterium sp. OR53 and Caulobacter sp. OR37 developed interactions that allowed for increased growth in coculture in the presence of uranium. Nucleotide variations in the genes of the re-isolated strains may have contributed to the development of these interactions. However, additional studies are needed to address this and to elucidate the function of these genes. The amount of uranium removed by strains re-isolated from the pH7U condition corresponded to the presence of Caulobacter sp. OR37 in the community. Re-isolated and ancestral Caulobacter spp. OR37 strains, which were abundant in the pH7U condition, removed more uranium than ancestral or re-isolated Sediminibacterium spp. OR53 strains. However, re- isolated Caulobacter spp. OR37 strains were not able to immobilize as much uranium as the ancestral strains. Additionally, cocultures of Sediminibacterium sp. OR53 and Caulobacter sp. OR37 were unable to immobilize as much uranium as individual Caulobacter spp. OR37 strains, suggesting that the interactions between these species impacted the ability of Caulobacter sp. OR37 to immobilize uranium. Our hypothesis that interactions in cocultures contributed to an increase in uranium immobilization was not supported. Our results show that some re-isolated strains had increased growth rate or biomass production in coculture, but none of the cocultures were able to immobilize significantly more uranium than ancestral or re-isolated Caulobacter spp. OR37 strains. Consequently, our new hypothesis is that in cocultures of Sediminibacterium sp. OR53 and Caulobacter sp. OR37, increases in growth rate or biomass production and uranium immobilization are influenced by different interactions [78, 86, 201]. We predict that one

! 153! interaction drives increases in growth between the two species while another decreases the ability of Caulobacter sp. OR37 to immobilize uranium.

Outlook and Future Directions Characterization of Sediminibacterium spp. OR43 and OR53 and the genus Sediminibacterium Sediminibacterium spp. OR43 and OR53 and sequences of closely related strains were identified in a variety of contaminated environments, which suggests that this genus may have generic mechanisms for tolerating different toxic compounds [100, 103-107]. Genomic comparisons between Sediminibacterium spp. OR43, OR53, C3, and S. salmoneum revealed minimal differences. We also have independent data showing that a closely related species isolated from donkey milk powder, A. lactis, has similar growth patterns to Sediminibacterium sp. OR53 when grown in the presence of increasing uranium concentrations [125]. Additional studies are required to determine the physiological limitations and potential genes that allow for the Sediminibacterium genus, as well as closely related strains, to tolerate the presence of different contaminants. The use of transcriptomics or proteomics would identify potential mechanisms of tolerance based on gene expression or protein production in response to different contaminants between Sediminibacterium spp. OR43 and OR53 and other related strains. Identification and characterization of these mechanisms would allow for representatives of this genus to be utilized in the bioremediation of sites containing multiple toxic compounds. Transcriptomics and proteomics may also elucidate differences between Sediminibacterium spp. OR43 and OR53 that could not be identified through genomic comparisons or physiological studies. Transcriptional or translational differences could indicate a divergence in the adaptation of each strain to a specific contaminant even if they occupy a niche with similar properties. For example, the enhanced tolerance of Sediminibacterium sp. OR53 to uranium may be attributed to other mechanisms for tolerating heavy metals such as the efficiency of efflux pumps, DNA damage response, or response to oxidative stress [35-36]. Mutagenic studies on genes of interest could further characterize their role in uranium tolerance. It would also be relevant to perform microscopy studies and uranium assays previously conducted with Sediminibacterium sp. OR53 on Sediminibacterium sp. OR43 to determine whether Sediminibacterium sp. OR43 can immobilize uranium (Chapter 3). Overall, transcriptomics and proteomics would give insight into how strains diverge and adapt to environmental conditions.

! 154! Sediminibacterium spp. OR43 and OR53 are able to persist in a contaminated environment, but their role in these environments is still unknown. While both strains could potentially contribute to the bioremediation of uranium they may not preferentially immobilize uranium in situ. Our data suggest that Sediminibacterium sp. OR53 may limit uranium precipitation (biomineralization) by other organisms (Chapter 3). Metagenomic studies performed in situ in response to an external stimulus such as uranium, nitrate, and heavy metals could potentially identify what factors result in an increase in the abundance of Sediminibacterium sequences. It would be likely that if Sediminibacterium sequences increased in abundance in response to uranium, then they are contributing to uranium immobilization [22, 26, 28, 91, 186, 219, 221-222]. However, an increase in abundance in response to nitrate would raise the question of the role of the Sediminibacterium genus in the community when nitrate concentrations are low and require further investigation. Identifying potential organisms that increase in abundance in response to a stimulus in situ and studying how these organisms interact with Sediminibacterium spp. OR43 or OR53 in vitro may also elucidate their role in the community.

Caulobacter sp. OR37 and Sediminibacterium sp. OR53 developed commensalistic and competitive interactions during the long-term growth experiment Our results indicate that the re-isolated Caulobacter spp. OR37 and Sediminibacterium spp. OR53 strains developed a commensalistic relationship resulting in increased growth rate and/or biomass production of the coculture compared to the individual strains. When grown individually, some re-isolated Sediminibacterium spp. OR53 and Caulobacter spp. OR37 strains had significant decreases in biomass yield compared to the ancestral strain. The most likely explanation for this decrease in biomass is that Sediminibacterium sp. OR53 produces some substrate that is being consumed by Caulobacter sp. OR37. When bacteria become dependent on cross-feeding, their ability to grow individually is negatively impacted [78, 95]. Preliminary spent media experiments support a potential cross-feeding mechanism between Sediminibacterium sp. OR53 and Caulobacter sp. OR37. In the presence of uranium, Caulobacter sp. OR37 Is28 showed increased growth in media containing 10% of two-day old spent media from Sediminibacterium sp. OR53 Is7 (data not shown). However, the increase in growth of Caulobacter sp. OR37 Is28 on the spent media of Sediminibacterium sp. OR53 Is7

! 155! was not equivalent to the growth of Sediminibacterium sp. OR53 Is7 and Caulobacter sp. OR37 Is28 in coculture. This suggests that the substrate produced by Sediminibacterium sp. OR53 requires reciprocation from Caulobacter sp. OR37 or that Caulobacter sp. OR37 manipulates the excretion of the substrate from Sediminibacterium sp. OR53. Since the experiments were not performed with Sediminibacterium sp. OR53 growing on spent media from Caulobacter sp. OR37 it is not clear if Caulobacter sp. OR37 reciprocates by producing a substrate beneficial to Sediminibacterium sp. OR53. Overall, the data suggest that one of the interactions between Sediminibacterium sp. OR53 and Caulobacter sp. OR37 is commensalistic. It is likely that there is another interaction between Sediminibacterium sp. OR53 and Caulobacter sp. OR37 that is competitive. The competition has consequences related to the ability of Caulobacter sp. OR37 to immobilize uranium. The community in the pH7U condition and re-isolated Caulobacter sp. OR37 strains both showed a reduced ability to immobilize uranium over time. Re-isolated Caulobacter spp. OR37 strains were able to immobilize more uranium when grown individually, than in coculture with Sediminibacterium spp. OR53 strains, suggesting that Sediminibacterium sp. OR53 negatively impacts the ability of Caulobacter sp. OR37 to immobilize uranium. Similar results were observed during the biodegradation of 4- chlorosalicylate in a coculture of Pseudomonas reinekei sp. strain MT1 and Achromobacter xylosoxidans strain MT3 [201]. The presence of A. xylosoxidans relieved the accumulation of toxic intermediates that induced oxidative stress responses in P. reinekei, but the coculture could not degrade as much 4-chlorosalicylate as P. reinekei alone. Our transmission electron micrographs suggest that Caulobacter sp. OR37 immobilizes uranium by bioprecipitation. Caulobacter species grown in phosphate-limited medium are hindered in their ability to remove uranium [182]. However, phosphate in the medium also forms abiotic complexes with uranium. Although the amount of phosphate added to the mineral salts media as KH2PO4 was minimal, our medium contained 0.05% yeast extract that provide other sources of phosphate. Independent data indicate that abiotic complexes form between yeast extract components and uranium. Additionally, characterization of uranium immobilization in 200 µM uranium with ancestral and re-isolated Caulobacter spp. OR37 and Sediminibacterium spp. OR53 strains showed that the decrease in uranium concentration by either species was nearly indistinguishable from the media control, suggesting that during the long-term growth experiment uranium primarily associated in abiotic uranyl phosphate complexes and was not

! 156! available to the cells (data not shown). The implications of abiotic uranyl complexes are two- fold: (1) Sediminibacterium sp. OR53 and Caulobacter sp. OR37 were not consistently exposed to 200 µM uranium over the course of the long-term growth experiment; and (2) the amount of phosphate available to Caulobacter sp. OR37 for uranium precipitation was limited. Exposure of Sediminibacterium sp. OR53 and Caulobacter sp. OR37 to variable uranium concentrations correlates with our inability to distinguish the growth of the re-isolated and ancestral species in the presence of 200 µM uranium. However, constant exposure to uranium would likely have negative consequences on the ability for Caulobacter sp. OR37 to utilize phosphatases to precipitate uranium in a phosphate-limited environment. It also explains why cocultures of Sediminibacterium spp. OR53 and Caulobacter spp. OR37 strains removed less uranium than individual Caulobacter spp. OR37 strains. In coculture, Sediminibacterium sp. OR53 and Caulobacter sp. OR37 would be competing for phosphate. The phosphate utilized by Sediminibacterium sp. OR53 for biological processes would no longer be available to Caulobacter sp. OR37 for uranium precipitation using phosphatases. In summary, we propose a model that when grown individually, ancestral Caulobacter sp. OR37 immobilizes uranium through binding to the LPS and internalization of a phosphate source from the media (Figure 27A) [57, 63, 65, 215]. The phosphate gets cleaved from a phosphoric acid monoester by periplasmic phosphatases and transported to the outside of the cell to form a uranyl phosphate precipitate [65]. Through biosorption of uranium to the LPS, Sediminibacterium sp. OR53 immobilizes uranium (Figure 27A). In our model, when the community was placed in uranium, Sediminibacterium sp. OR53 and Caulobacter sp. OR37 became the dominant species because of their ability to tolerate or immobilize uranium. The phosphate concentration in the media decreased as a result of abiotic complexes with uranium. Sediminibacterium sp. OR53 and Caulobacter sp. OR37 competed for the remaining phosphate, which resulted in a low concentration of uranium being removed by the ancestral coculture (Figure 27B). In the long-term growth experiment, competition between Sediminibacterium sp. OR53 and Caulobacter sp. OR37 for phosphate was reduced as demonstrated by the ability of the re-isolated cocultures to remove more uranium than the ancestral coculture. The decrease in competition for phosphate could be a result of an unknown secreted substrate by Sediminibacterium sp. OR53 that enhanced the growth rate and/or biomass production of Caulobacter sp. OR37 (Figure 27B). Preliminary spent medium experiments suggested

! 157!

Figure 27. Model of the development of the interactions between Sediminibacterium sp. OR53 and Caulobacter sp. OR37 in coculture. The model contains a diagram of ancestral and re- isolated Caulobacter sp. OR37 and Sediminibacterium sp. OR53 strains covered by LPS. (A) The individual mechanisms of uranium immobilization for ancestral Caulobacter sp. OR37 and Sediminibacterium sp. OR53. (B) Mechanism of uranium immobilization in the ancestral and re- isolated coculture of Caulobacter sp. OR37 and Sediminibacterium sp. OR53. Orange circles: phosphate; yellow circles: uranium; green oval: periplasmic phosphatases; blue circle: secreted substrate; and black line: LPS. Red arrows indicate movement of a substrate.

! 158! ! 159! Sediminibacterium sp. OR53 does secrete a substrate that increases Caulobacter sp. OR37 biomass. Increasing the biomass of Caulobacter sp. OR37 would be advantageous for both species to increase the amount of uranium immobilized in the medium. The competition for phosphate was not completely diminished based on the observation that the amount of uranium immobilized by individual Caulobacter spp. OR37 strains over a 7-day period was always more than the re-isolated strains in coculture (data not shown). Overall, our results suggest that more than one interaction is capable of developing between two species, which adds an additional level of complexity in the formation of stable and productive microbial communities. Additional work is required to elucidate the circumstances that led to the change in the interaction between re-isolated Sediminibacterium spp. OR53 and Caulobacter spp. OR37 strains and the ancestral strains. It would be relevant to re-isolate Sediminibacterium spp. OR53 and Caulobacter spp. OR37 strains from earlier weeks in the pH7U condition, and identify when re-isolated strains started exhibiting increases in biomass production in coculture. A genomic comparison of strains with growth rate or biomass increases in coculture with those strains that did not show increases might elucidate any genomic changes contributing to the interaction between these strains [179]. Further more, spent media experiments in combination with transcriptomic or proteomic studies would give insight into how Sediminibacterium sp. OR53 and Caulobacter sp. OR37 respond to one another and how this response differs between ancestral and re-isolated strains. The identity of any metabolites produced by one strain in excess when it is in the presence of another strain would also indicate a basis for the interactions between strains in the pH7U condition. Long-term exposure of microbial communities to a condition can result in genomic changes within different populations as a result of adaptations to biotic or abiotic factors [179, 206]. Elucidating these changes are important for understanding how microbial populations evolve in a community. In general, the conclusions that could be drawn from our MiSeq data were limited by the inability to distinguish between genomic changes induced by microbe- microbe interactions, interactions with uranium, and neutral mutations. We are currently in the process of repeating the long-term growth experiment with individual species in the presence or absence of uranium. Differences in genomic changes between the individually grown strains and those found in re-isolated strains from the community could elucidate relevant changes in response to interactions with other populations. In addition, a more extensive genome analysis

! 160! from both the individually grown strains and strains re-isolated from the artificial community is needed to identify alterations to transcriptional start sites and the influence of nucleotide changes in non-coding regions in Caulobacter sp. OR37. Many of the nucleotide variations were observed in hypothetical proteins whose functions need to be investigated. The primary focus of this dissertation was on the community dynamics at pH7U even though the same community was grown long-term at pH4.5 and pH7. Analyzing the different interactions and genomic changes that arose between re-isolated strains under the different conditions would provide insight on how environmental conditions shape microbial communities. For example, it would elucidate whether interactions between Sediminibacterium sp. OR53 and Caulobacter sp. OR37 evolve in the absence of uranium and determine the role of these species in a condition where they do not dominate. Additionally, the transition conditions (pH7->pH7U, pH7U->pH7, pH4.5->pH7, pH7->pH4.5) would give insight into the stability of the associations between strains, which is important for forming a productive community. Understanding the types of associations between species and the stability of the associations under different conditions gives insight into the selection of specific species artificially assembled in microbial communities for bioremediation. Overall, our data have implications for how natural microbial communities form stable associations and how these associations influence community productivity. The presence or absence of a species is dependent on its fitness for that environment and/or its ability to respond to the presence of other species. Bacteria cannot coexist if they are in competition for the same resource. Therefore, the right combination of species is required to ensure community stability and productivity over time. Additionally, our data suggest that interactions between two species may not be classified simply as positive or negative but rather as a balance of more than one type of interaction. Multiple types of interactions between only two species increase the complexity in forming microbial communities and in the response of the community to environmental changes. Finally, our data emphasize the importance of time as a likely key factor in developing productive natural communities important to the environment and human health.

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