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Microbial ecology of deep-sea hydrothermal vents : viruses, diversity and potential mortality Ortmann, Alice Catherine 2005

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MICROBIAL ECOLOGY OF DEEP-SEA HYDROTHERMAL VENTS: VIRUSES, DIVERSITY AND POTENTIAL MORTALITY B y A L I C E C A T H E R I N E O R T M A N N B . S c , Simon Fraser University, 1998 A THESIS S U B M I T T E D I N P A R T I A L F U L F I L M E N T O F T H E R E Q U I R E M E N T S F O R T H E D E G R E E O F D O C T O R O F P H I L O S O P H Y In T H E F A C U L T Y O F G R A D U A T E S T U D I E S (Oceanography) T H E U N I V E R S I T Y O F B R I T I S H C O L U M B I A January 2005 © Al ice Catherine Ortmann, 2005 Abstract Deep-sea hydrothermal vents have been intensely studied since their discovery almost 30 years ago. These environments have been shown to harbour previously unknown organisms, which depend on chemosynthetic prokaryotes for much of their nutrition. Although high abundances of free-living prokaryotes have been documented from many hydrothermal vent sites, the fate of prokaryotic biomass has not been well studied. The initial goal of this thesis was to determine the abundance and distribution of viruses in hydrothermal vent environments and to determine i f the abundances were high enough to support the occurrence of virus-mediated mortality of prokaryotes. This study clearly demonstrated that around active hydrothermal vent sites the virus abundance could be as high as values reported from coastal surface waters. Increased abundances within active hydrothermal fields and associated plumes above background seawater levels suggest that viruses are actively produced in these environments. The effects of viruses on a prokaryote community are dependent on the species composition of the microorganisms. Few studies have investigated the spatial distribution of prokaryote species around hydrothermal vents. In this study, several samples were collected and individually analysed using P C R - D G G E to determine the composition of the prokaryote communities, targeting both Bacteria and Archaea. From these fingerprints, it was demonstrated that the microbial communities around hydrothermal vents are extremely heterogeneous, with little similarity between samples collected from similar locations or environments. Sequencing of D G G E bands suggests common phylotypes among widespread hydrothermal vent sites. Through grazing, protists could cause mortality of prokaryotes. Because little is known about the presence of protists around hydrothermal vents, samples collected around a single sulphide structure were analysed using P C R - D G G E to determine the diversity of the eukaryote community in the water column. Sequencing of major bands was undertaken to determine the identity of the bands with the hopes of identifying previously unknown protists that could be grazers of prokaryotes. This study shows that D N A from the benthic invertebrate community dominates the eukaryote D N A around hydrothermal vents, suggesting viruses may be the main cause of mortality for free-living prokaryotes. Table of Contents Abstract . ii Table of Contents iv List of Figures vi List of Tables vii List of Abbreviations viii Acknowledgements . x Dedication xi CHAPTER 1: Introduction to deep-sea hydrothermal vents and potential fate of prokaryotic production 1 1.1 Summary : 2 1.2 The Hydrothermal Environment 4 1.3 Vent Biology 5 1.4 Prokaryote Production and the Microbial Loop 9 1.5 Protist Grazers 11 1.6 Marine Viruses 13 1.7 Potential Prokaryote Mortality '. 15 1.8 Aims of the Thesis 17 CHAPTER 2: High Abundances of Viruses in a Deep-Sea Hydrothermal Vent System Indicates Virus-Mediated Microbial Mortality 19 2.1 Summary 20 2.2 Introduction 21 2.3 Materials and Methods 23 2.4 Results 27 2.5 Discussion 36 CHAPTER 3: High Spatial Heterogeneity of Microbial Communities in Diffuse Flow Fluids at a Deep-Sea Hydrothermal Vent 43 3.1 Summary '. 44 3.2 Introduction 45 3.3 Material and Methods 47 3.4 Results 53 3.5 Discussion 67 iv CHAPTER 4: The 18S rDNA Diversity in the Water Column at a Hydrothermal Vent is dominated by Sequences from Benthic Invertebrates 71 4.1 Summary 72 4.2 Introduction 73 4.3 Materials and Methods 75 4.4 Results and Discussion 79 CHAPTER 5: Conclusions 88 5.1 Conclusions 89 5.2 Future Research 93 REFERENCES 96 APPENDIX A: Detailed Methods Employed 117 A . l Epifluorescence Microscopy 118 A . 2 P C R (Polymerase Chain Reaction) 121 A.3 D G G E (Denaturing Gradient Ge l Electrophoresis) 123 A . 4 Flame A A S (Flame Atomic Absorbtion Spectrometry) 125 v List of Figures Figure 2.1 Sample Locations 26 Figure 2.2 The Prokaryote and Virus Abundances from active Hydrothermal Vent Fields 33 Figure 2.3 Depth Profiles from Hydrothermal Plume Casts 34 Figure 3.1 Samples from the South Tower of Salut 57 Figure 3.2 Bacterial and Archaeal D G G E and Excised Bands 60 Figure 3.3 Cluster Analysis of Bacterial and Archaeal Fingerprints 61 Figure 3.4 Neighbour-Joining Tree of Bacterial 16S Sequences 64 Figure 3.5 Neighbour-Joining Tree of Archaeal 16S Sequences 66 Figure 4.1 D G G E and Cluster Analysis of 18S r D N A Fingerprints 85 Figure 4.2 Max imum Likelihood Tree of Eukaryotic 18S r D N A Sequences 87 Figure A . l Comparison of Stains 120 Figure A.2 Steps of P C R 122 Figure A.3 Separation of P C R Products with D G G E 124 Figure A.4 M g Standard Curve 126 List of Tables Table 2.1 Prokaryote and Virus Abundances from Active Hydrothermal Vent Fields.... 31 Table 2.2 Prokaryote and Virus Abundances from Hydrothermal Plumes and the Deep Sea 32 Table 2.3 Correlations from Profiles Collected Along the Hydrothermal Plume 35 Table 3.1 P C R primers used to amplify 16S r D N A from samples 52 Table 3.2 Sample Characteristics 58 Table 3.3 Bacterial 16S Sequence Matches 62 Table 3.4 Archaeal 16S Sequence Matches 65 Table 4.1 Eukaryote 18S Primers 78 Table 4.2 Samples collected for this study 84 Table 4.3 Eukaryote 18S Sequence Matches 86 v i i List of Abbreviations bp base pairs C F B Cytophaga, Flavobacterium, Bacteroides group C M G 1 Crenarchaeota marine group 1 C T D conductivity, temperature, depth D G G E denaturing gradient gel electrophoresis D H V E deep-sea hydrothermal vent Euryarchaeota group dNTP deoxynucleotide triphosphate D O C dissolved organic carbon D O M dissolved organic matter E D T A ethylenediaminetetraacetic acid E M G 2 Euryarchaeota marine group 2 E P R East Pacific Rise F I S H fluorescent in situ hybridization F l a m e A A flame atomic absorbtion spectrometry M A R Mid-Atlantic Ridge M E F Ma in Endeavour Field M H V G marine hydrothermal vent group nt nucleotide O T U operational taxonomic unit P C R polymerase chain reaction P F G E pulse-field gel electrophoresis v i i i P O C particulate organic carbon r D N A ribosomal deoxyribonucleic acid R F L P restriction fragment length polymorphisms R O P O S Remotely Operated Platform for Ocean Science R O V remotely operated vehicle r R N A ribosomal ribonucleic acid SDS sodium dodecyl sulphate T E M transmission electron microscopy U P G M A unweighted pair-group method using arithmetic means V B R virus bacteria (prokaryote) ratio ix Acknowledgements I would like to thank the many people who have helped me complete this thesis. First, I would like to thank Curtis for his assistance and direction during the years, as well as my other committee members, Steve and B i l l . Thanks to A m y for helping make the lab run more smoothly. Thanks also to Bert for the help with the F lameAA. Special thanks to those whose brains I have picked for minute details: Alex , Steve, Andre, Janice and Emma. Special thanks goes to Jessie for the ecological insight and beers. Everyone else who has been in the lab has also provided and shared encouragement, entertainment, heartache and fun at some time during my stay: thanks. I would also like to extend my thanks to the people who helped me collect samples, especially K i m Juniper and Rick Thomson. Without the assistance and guidance of both of you, this would have been much more difficult. Thanks also to the R O P O S team who never gave up and worked hard to make everything happen. Thanks to Karine and Amanda, the two best cabin-buddies in the world. Outside of the lab, I would like to thank my family, especially my parents who had to endure endless questions about when their k id was finally going to get out of school and get a real job. Maybe someday... Also to Nicole and Laura who besides providing support, encouragement and doses of reality, also endured editing of countless comma-abusing papers over the years. Thanks to the U A S B C folks who besides helping me drink beer, also provided an escape from the world of science into the world of underwater archaeology. Thanks Andrea, Dave and Peter, the best sea-hunters around. Special thanks to Darren. Y o u have been incredibly supportive of me over the years. Thanks for the distractions from hiking to travel to diving. Y o u made a huge difference in my life. Thanks to Isis and Zeus for not caring about any of it as long as there was food. Thanks also go to the Natural Science and Engineering Council of Canada for providing me with funding through two post-graduate awards and to the University of British Columbia for the Graduate Fellowship and travel awards. x Dedication To Maud. I hope your wings are carrying you to the Rockies and beyond. CHAPTER 1: Introduction to deep-sea hydrothermal vents and potential fate of prokaryotic production 1.1 Summary Deep-sea hydrothermal vents were discovered on the ocean floor almost thirty years ago. M u c h research has focused on trying to understand these environments as well as the diverse and dense communities of organisms that flourish around them. Arguably, one of the most important groups of organisms appears to be the prokaryotes. Prokaryotes are a group of unicellular organisms that lack membrane bound organelles. This group has traditionally encompassed the Bacteria, but has been expanded to include the Archaea. The Archaea are known as extremophiles, due in part to their initial discovery in inhospitable environments. Recently, Archaea have been identified in less extreme environments and may be much more prevalent than previously thought. In surface waters, many prokaryotes are heterotrophs that consume organic material, remineralize organic nitrogen and phosphorus and contribute to the cycling of carbon in the microbial loop. Prokaryotes (cyanobacteria and prochlorophytes) are also important photosynthetic primary producers. In the hydrothermal environment, heterotrophic prokaryotes are present, but chemosynthetic prokaryotes f i l l the role of primary producers. Using a variety of chemosynthetic pathways, prokaryotes fulfil the metabolic requirements of the dense communities associated with hydrothermal vents in the deep sea. In contrast, most of the deep sea is characterized by low levels of biomass. Because of the central role of prokaryotes at hydrothermal vents, understanding mechanisms and rates of prokaryotic mortality are fundamental to characterising hydrothermal systems. The two major causes of prokaryotic mortality in surface waters are grazing by protists and lysis by viruses. These two mortality agents have different effects. Protists, which graze on the prokaryotes, are consumed by zooplankton, resulting in some prokaryotic biomass being transferred to higher trophic levels. V i r a l lysis, however, releases biomass as dissolved organic matter, reducing biomass transfer to higher trophic levels. A s viruses are present in hydrothermal environments, it is l ikely they affect carbon and nutrient cycling in these ecosystems. Little is known about the abundance of viruses within hydrothermal systems or about the diversity of their potential 2 hosts. Less is known about the potential of pico- or nano-eukaryotes to graze on prokaryotes within these systems. 3 1.2 The Hydrothermal Environment Deep-sea hydrothermal vents were discovered in M a y 1976 along the Galapagos Rift (Lonsdale 1977). Since then, hydrothermal activity has been detected along most of the mid-ocean spreading ridges as well as at hot spots. A t these sites, the seafloor is porous and allows seawater to percolate downward. As the seawater moves through the crust, it moves closer to a magma chamber and the heat and pressure increases. The heat and pressure cause the seawater to react with the surrounding rocks and to form hydrothermal fluid. Hydrothermal fluid is seawater that has been altered by chemical reactions driven by increasing temperature and pressure deep in the crust of the earth. Chemical reactions result in a fluid that is acidic, reduced, enriched in heavy metals, low in magnesium, and high in ammonium, hydrogen sulphide, hydrogen gas and methane (Corliss et al. 1979). The hydrothermal fluid is released into the ocean where it mixes with ambient seawater to form a plume, which rises until it reaches neutral buoyancy and begins to spread laterally. The process of mixing between the vent fluid and ambient seawater results in the introduction of microorganisms into the fluid (Baross et al. 1984; Juniper et al. 1995; Kar l et al. 1988). Microorganisms have been suggested to be catalysts for some of the chemical changes that occur in the plume (Cowen et al. 1998). Hydrothermal fluid also affects the seawater immediately surrounding the sites of active venting through mixing. This mixture is not buoyant, but remains close to the seafloor. Thus, the deep-sea hydrothermal environment includes two different components: the vent field where venting of fluid occurs and the neutrally buoyant plume (Karl 1995; Winn et al. 1995). The vents are often transitory in nature (Shank et al. 1998; Tunnicliffe et al. 1997). Some vents have been actively discharging fluid for decades, whereas others cease to be active after only a few months. Variation is another characteristic of the hydrothermal environment. Temperature, chemical composition and flow rates vary among vents and even within a vent (Gundersen et al. 1996; Johnson et al. 1986; VonDamm et al. 1995). Temperature variations of 100°C within minutes at the same location have been measured at some hydrothermal vents (Karl et al. 1988). 4 Although some vents are little more than fissures in the basalt (Corliss et al. 1979), chimney structures have been observed to be associated with both warm and hot vents. The chimneys are formed, through the precipitation of anhydrite, barite and metal sulphides from the vent fluid. These chimneys are porous and provide many microhabitats for organisms because of the extreme temperature gradients which exist within the structures (Baross and Deming 1985; Harmsen et al. 1997; Jannasch and Wirsen 1985). L o w temperature chimneys can have an internal temperature of 15 to 30°C, while the external temperature can be as low as 2 to 3°C (Harmsen et al. 1997). The black smoker chimneys have stronger gradients with the internal temperature being as high as 300°C (Harmsen et al. 1997). 1.3 Vent Biology Most of the deep ocean is characterized by low levels of biomass (Smith and Hamilton 1983). In contrast, communities surrounding deep-sea hydrothermal vents have high levels of biomass (Grassle 1986). Vent-associated communities are diverse and contain representatives from most of the marine animal phyla. The species that compose the hydrothermal vent communities include organisms unique to the environment, as well as many closely related to known deep-sea or shallow-water non-vent species (Tunnicliffe 1991). Recent studies of newly formed vent sites have suggested that the communities develop quickly and with distinct successional stages (Shank et al. 1998; Tunnicliffe et al. 1997). These studies suggest that the organisms are well adapted to exploiting the rapidly changing environment at hydrothermal vents. M u c h research at hydrothermal vents has been focused on trying to generate an exhaustive inventory of the species that make up the vent communities. Although most of the macrofauna are now identified, some of the smaller organisms are less well known. Small zooplankton, such as copepods and amphipods, have been identified in animal collections, but protists are much more difficult to quantify and less effort has been directed at identifying this group. 5 Many species of macrofauna found in these communities have endosymbiotic associations with Bacteria (reviewed in Van Dover 2000). The symbionts are thought to convert inorganic chemicals, toxic to the invertebrates in high concentrations, into energy and nutrients that can be used by the hosts. Although none of the chemoautotrophic symbionts has been isolated, all organisms examined using molecular techniques appear to be Bacteria (Cary et al. 1997). Episymbionts have also been found on many invertebrates from these communities (Cary et al. 1997; Tunnicliffe and Fontaine 1987). These symbionts are thought to detoxify the immediate environment for the host, enabling the host to survive in conditions normally considered toxic (Jeanthon and Prieur 1990). Although the animals may provide surfaces for microbial colonisation, the nature of the relationship between the epibionts and the hosts is poorly characterized (Cary et al. 1997; Haddad et al. 1995). A s well as the symbiotic prokaryotes, microorganisms have been isolated from microbial mats (Nelson et al. 1989), rock surfaces (Harmsen et al. 1997), sediments (Antoine et al. 1995) and the water column (Huber et al. 1997; Pledger and Baross 1991) at hydrothermal vent sites. Although no prokaryotes have yet been isolated from the subsurface environment beneath hydrothermal vents, release of flocculates from within the seafloor suggests that this environment is also inhabited by prokaryotes (Tunnicliffe et al. 1997). The interactions between the hydrothermal fluid and the surrounding seawater result in many microenvironments that support chemosynthetic and heterotrophic prokaryotes. Isolations of thermophiles and hyperthermophiles from diffuse flow samples from both Endeavour Ridge (Summit and Baross 2001) and the Floe site at C o - A x i a l (Holden et al. 1998) suggests that these fluids must have been in contact with a thermophilic microbial community below the site of venting. M u c h of the microbiological work at hydrothermal vents has focused on the isolation of novel species, especially thermophiles, from high temperature samples (Antoine et al. 1995; Huber et al. 1997; Pledger and Baross 1991; Pledger et al. 1994). Other studies have focused on the isolation of chemosynthetic species (Nelson et al. 1989). These studies resulted in the characterisation of hydrothermal vent environments 6 as extreme. Although thermophiles and chemolithotrophs have been isolated, mesophiles and myxotrophs are commonly found. In fact the majority of species in the microbial hydrothermal vent communities are likely free-living obligate chemoautotrophs, obligate heterotrophs and myxotrophs (Karl 1995). More recently, complete community inventories have been attempted for select environments at hydrothermal vent sites. Three studies have attempted to determine the prokaryote diversity within four distinct locations using molecular techniques. These environments include a mat from the Lo ih i Seamount in Hawaii , vent fluid representing the subsurface environment at the A x i a l Volcano along the Juan de Fuca Ridge, a sulphide chimney recovered from the Mothra vent field along the Endeavour Segment, and samples from the western Pacific and Indian Oceans. Samples of mats collected from sites at Pele's Vent on the Loih i Seamount were analysed to determine the diversity of Bacteria (Moyer et al. 1994; Moyer et al. 1995; Moyer et al. 1998). Using clone libraries of 16S r D N A genes, the number of potential O T U ' s (operational taxonomic unit) was determined using R F L P (restriction fragment length polymorphisms) analysis. Based on rarefaction analysis, the diversity of the Archaea was estimated to be higher than that of Bacteria from the same samples (Moyer et al. 1998). Due to differences in the specificity of the primer sets and the lower number of archaeal clones considered, this may not be an accurate estimate. Unique clones were selected for sequencing from both Archaea and Bacteria. O f the four clones sequenced for Archaea, three clones were found to be closely related to the Crenarchaeota marine group 1 ( C M G 1 ) while the fourth was related to the Euryarchaeota marine group 2 (EMG2)(Moyer et al. 1998). The majority of the Bacterial clones was found to be most closely related to the Thiovulum group of the £-Proteobacteria (Moyer et al. 1995). The second largest group of clones were related to the y-Proteobacteria. A t A x i a l Volcano on the Juan de Fuca Ridge, samples of hydrothermal fluid emanating from the seafloor were sampled over time (Huber et al. 2002; Huber et al. 2003). This study used 16S sequences to document the changes in bacterial and archaeal diversity over three years following the 1998 eruption at A x i a l Volcano (Huber et al. 7 2002) . Because samples were collected from the orifice of the vent, it was presumed that the microbes originated from a sub-surface community. The study found higher diversity of both Bacteria and Archaea in the particle-attached fraction than in the free-living fraction (Huber et al. 2002; Huber et al. 2003), with the attached fraction defined as > 3 um. The diversity from the vent waters was compared to background water collected from overlying water. Although both samples included Archaea from the C M G 1 and E M G 2 , only the vent samples included sequences closely related to the thermophilic Methanoccocales and uncultured Euryarchaeota detected from other hydrothermal environments (Huber et al. 2002). The bacterial clone library was very diverse with more than 100 phylotypes detected in 17 groups, a- and y-Proteobacteria were detected in both the background seawater and the vent sample, but s-Proteobacteria were only found in the vent samples along with Gram positive and thermotolerant sequences (Huber et al. 2003) . The temperature and chemical composition of the fluid samples appeared to have the largest impact on the diversity of the microbial communities. Recently whole-cell hybridization and cloning of Archaeal 16S sequences has been used to look at community diversity and distribution of prokaryotes within an active chimney sampled from the Mothra vent field on theEndeavour Segment of the Juan de Fuca Ridge (Schrenk et al. 2003). In 1998 a chimney venting 302 °C fluid before collection (Delaney et al. 2001), was sampled and investigated to determine the distribution of microorganisms along a gradient from the outside to the inside of the chimney. The outer parts of the chimney were found to have a community composed of Bacteria and Archaea of the C M G 1 and E M G 2 (Schrenk et al. 2003). The inner, hotter part of the chimney had a community of mostly Archaea with sequences closely related to methanogens, Thermococcales, Archaeoglobales, and uncultured Crenarchaeota. Similar molecular studies have been carried out on black smoker chimneys and fluid samples to determine Archaeal diversity in western Pacific and Indian Ocean vent fields (Takai and Horikoshi 1999; Takai et al. 2001; Takai et al. 2004). These studies have also found differences in Archaeal communities from different parts of a sulphide chimney. Samples collected from a >250 °C chimney from the P A C M A N U S site near 8 Papua New Guinea were found to have representatives of the marine hydrothermal vent group ( M H V G ) and uncultured Euryarchaeota group from deep-sea hydrothermal vents. Sequences related to Igniococcales, Thermococcales, and Halobacteriales were also detected in some areas of the chimney (Takai et al. 2001). Vent samples from Kairei Vent on the Central Indian Ridge and Iheya North in the Okinawa Trough investigated for C M G 1 were found to have the highest numbers of the group in ambient seawater near the vents, but not within the actual hydrothermal plumes (Takai et al. 2004). These results were obtained by using a combination of quantitative P C R (polymerase chain reaction) and fluorescent in situ hybridization (FISH). A l l of these community-based studies have indicated that the hydrothermal environments are diverse, with many unknown and uncultured microorganisms. Although there appear to be similarities between vent environments and the surrounding seawater (Huber et al. 2002; Huber et al. 2003; Takai et al. 2004), there also appear to be microbes specific to the hydrothermal environments. A t this time, it is not known what percentage of these communities are active and which cells may not be viable within these environments. 1.4 Prokaryote Production and the Microbial Loop Abundances of free-living prokaryotic cells from water samples collected from vent sites are typically 10 6 mL" 1 (Winn et al. 1995), which is comparable to near-shore surface waters (Bratbak et al. 1994; Weinbauer and Suttle 1997). Other studies have found abundances as high as 10 9 mL" 1 (Corliss et al. 1979). In contrast, prokaryotic abundances found in deep-sea water samples are generally around 10 4 mL" 1 (Hara et al. 1996), although these estimates may be influenced by decay in aldehyde-fixed samples stored prior to enumeration (Gundersen et al. 1996; Turley C. M . 1993; Turley and Hughes 1992). The high abundances of prokaryotes at hydrothermal vents are significant because of their role as primary producers. 9 The flow of organic material from producers to consumers is usually considered in terms of carbon. Organic carbon in any ecosystem does not flow linearly from primary producers to the final consumer. As organic carbon that is not respired moves from one organism to another, some of it is lost as particulate or dissolved organic carbon (POC or D O C ) , which can re-enter the microbial food web via heterotrophic prokaryotes. The cycling of organic carbon in surface waters is described in terms of the "microbial loop" (Azam et al. 1983). The microbial loop represents the organic carbon that cycles from the primary producers through the prokaryotes rather than being transferred directly to higher-level consumers. M u c h of this organic carbon is eventually lost through respiration; however, some of the carbon re-enters the food chain through consumption of bacteria by protists. In surface waters, primary production in the form of D O C enters the microbial loop through sloppy feeding and excretion by zooplankton, cell lysis or exudation by phytoplankton. In contrast to the surface ocean, primary production in the deep-sea hydrothermal environment is prokaryotic. The high levels of biomass present at vent sites indicate that the flux of carbon from prokaryotic producers to higher trophic levels must be substantial. However, agents of prokaryotic mortality resulting in carbon being released into the microbial loop are also likely to be present in these environments. Although grazing by invertebrates has been suggested as a cause of mortality for prokaryotic mats (Grassle 1985), data on mortality of free-living microbes at hydrothermal vents is lacking. There are two potential causes of prokaryotic mortality, namely grazing by protists and viral lysis. Grazing of prokaryotes by heterotrophic flagellates in surface waters is an important step in moving prokaryote production to higher trophic levels. Viruses have been shown to be important factors affecting bacterial populations in surface waters (Bratbak et al. 1992; Suttle 1994; Thingstad et al. 1993), and may also have important effects in deep-sea hydrothermal environments. Although both grazing and viral lysis result in mortality for prokaryotes, the implications for carbon and energy flow are substantially different. In the case of grazers, much of the carbon and energy is 10 transferred up the trophic chain, while viral lysis moves that carbon and energy into the dissolved organic matter ( D O M ) pool, fuelling secondary prokaryotic production. 1.5 Protist Grazers In the early 1980's it was realized that the prokaryotic biomass in the ocean was not slow growing as previously thought. Measurements of prokaryote production using radioactive tracers demonstrated that the prokaryotic size-fraction was actively growing and its biomass must be controlled by other organisms (Pomeroy 1974). Grazing by protists was investigated as the major control of prokaryotic biomass in the ocean (Strom 2000). Although the protists consist of a morphologically and genetically diverse group, they share several common characteristics (Sherr and Sherr 2000). These organisms are single-celled eukaryotes that are usually defined as either heterotrophic or phototrophic. Although this appears to be a simple division between those with chlorophyll that photosynthesize and those that graze on other organisms, many of the protists fall in a myxotrophic category where they may consume organic matter as well as photosynthesize (Caron 2000). Genetically, the group does not divide into heterotrophs and phototrophs as many genetic groupings have representatives of both types. Most of the protists that are known to graze on prokaryotes fall into two main groupings, the ciliates and the flagellates. O f these two groups, the flagellates are thought to be the main grazers (Boenigk and Arndt 2000). Many of the ciliates are too large to graze effectively on single-cell, free-living prokaryotes, although smaller (<20 U.m) ciliates l ikely ingest prokaryotes (Sherr et al. 1986). The flagellates, often referred to as heterotrophic flagellates range in size from 1 um to > 20 um and are divided into three main groups. The microflagellates are the largest group and are traditionally considered to be > 20 um (Sieburth et al. 1978). More recently it has been suggested that this group should include all the flagellates > 15 um (Boenigk and Arndt 2002). This group ranges in 11 abundance from 0.1 to 10 2 mL" 1 . The most obvious members of this group are the heterotrophic dinoflagellates. The next group, the nanoflagellates, are the most abundant group of flagellates. Wi th surface water abundances from 10 2 to 10 4 mL" 1 , these organisms range in size from 2 to 15 or 20 urn (Boenigk and Arndt 2002). Recently, studies of marine systems using molecular techniques have detected a new and very diverse group of flagellates, the picoflagellates (Lopez-Garcia et al. 2001; Moon-Van Der Staay et al. 2001). This group includes protists < 2 | im , which using epifluorescence microscopy cannot be readily distinguished from prokaryotes (Massana et al. 2002). The abundance of this group in the ocean is unknown because they are difficult to identify for enumeration. It is the smaller two groups of flagellates that likely exert the most influence on the prokaryotes through grazing. From studies conducted in surface waters of the ocean, it appears that the majority of the organisms that graze on prokaryotes are < 5 | i m (Sherr and Sherr 1991; Wikner et al. 1990). Although the microflagellates, some microzooplankton (>20 | im), and some metazoans (larval forms (Rivkin et al. 1986) and some mucus web feeders (reviewed in Strom 2000)) also feed on prokaryotes, their low numbers reduce the impact they may have on large-scale nutrient cycling. These groups in the surface waters likely feed more often on phytoplankton or smaller heterotrophic flagellates. Through ingestion of the prokaryotic biomass, grazers influence the flow of nutrients by repackaging of prokaryotic carbon into larger packages. These larger packages then become available to the microflagellates and larger predators. This transfer of energy is not very efficient, as much of the ingested material is released as wastes by the grazers. Growth efficiencies for nanoflagellates are estimated to be about 30% (Strom 2000), suggesting that 70% of the consumed prokaryotic biomass is released back into the D O M pool (Strom et al. 1997) or released as inorganic nutrients (Nagata and Kirchman 1991). The material that enters the D O M pool may then be available to other prokaryotes, thus stimulating prokaryotic production through grazing. 12 Several studies have been conducted in surface waters of the ocean to determine i f grazing rates are capable of reducing prokaryote abundance by balancing production rates (reviewed in Strom 2000). Although the methods of measuring grazing and production contain uncertainties, it appears that in low nutrient conditions where the abundance of prokaryotes is < l . l x l O 6 cells mL" 1 , grazing rates are equivalent to production rates (Strom 2000). In high nutrient conditions, such as those found in coastal regions, prokaryote production is frequently greater than removal rates by grazing. Grazing on prokaryotes by protists has other effects besides reducing the prokaryote abundance. Incubations of grazers and prokaryotes have resulted in a decrease in the average size of the prokaryote community (Ammerman et al. 1984; Gasol et al. 1995; Kuuppo-Leinikki 1990). Due to hydrodynamics and physical forces, the size of prey available to grazers is limited. Studies have suggested that flagellates w i l l preferentially graze on larger prey, thus the reduction of prokaryote community size may be due to selective removal of larger cells (Andersson et al. 1986; Gonzalez 1996; Monger and Landry 1991). It is also suggested that prokaryote species with small cell size may be selected for through grazing pressures (Jurgens et al. 1999; Massana and Jurgens 2003), thus changing the composition of the microbial community, not just the size. 1.6 Marine Viruses For several years, viruses have been recognized as being abundant in the surface waters of the ocean, averaging ca. 10 7 mL" 1 (Bratbak et al. 1994; Fuhrman and Suttle 1993; Wommack and Colwel l 2000). Studies show that the abundance of viruses decreases with depth (Cochlan et al. 1993; Hara et al. 1996), although these estimates may be lower than the actual abundances due to methodological problems (Brussaard 2004; Wen et al. 2004). For example, a study in the Antarctic deep water detected higher abundances of viruses using Yo-Pro 1 staining without aldehyde fixation (Guixa-Boixereu et al. 2002) compared to most other studies, which have used aldehyde-fixed 13 samples (Cochlan et al. 1993, Hara et al. 1996). Although viruses that infect eukaryotic phytoplankton are present in high numbers and are important factors affecting eukaryotic phytoplankton dynamics (Cottrell and Suttle 1995), most of the viruses in the ocean appear to be pathogens of prokaryotes (Hara et al. 1996). A s agents of prokaryotic mortality, viruses affect the cycling of carbon through the microbial loop. In surface waters, the percentage of bacterial mortality due to viral lysis has been estimated to fall between 6 and 62% (Bratbak et al. 1994; Fuhrman 1999; Fuhrman and Suttle 1993; Suttle 1994). Carbon from prokaryotic cells that are lysed does not proceed to higher trophic levels, but enters the microbial loop through heterotrophic prokaryotes (Bratbak et al. 1992; Bratbak et al. 1994; Fuhrman 1992; Fuhrman 1999; Wi lhe lm and Suttle 1999). Other effects of viral infection act at the population or community level. High densities of host organisms provide conditions that favour the rapid spread of a virus throughout the population. A lytic virus operating in these conditions may be able to dramatically decrease the density of the host organism (Hennes and Suttle 1995; Maranger and Bi rd 1995; Wiggins and Alexander 1985). For example, viruses may be important agents in the termination of blooms of phytoplankton (Bratbak et al. 1993; Brussaard et al. 1996; Nagasaki and Yamaguchi 1997; Tarutani et al. 2000; Tomaru et al. 2004) where host densities can reach very high concentrations. B y controlling host populations, viruses can affect species diversity of the prokaryotic community (Hennes et al. 1995). Viruses may enable different species with similar niches to co-exist by preventing competitive exclusion. The same viral dynamics may work within a species by preventing the dominance of one strain over all other strains. Thus, viral lysis can help maintain the genetic diversity of a population as well as the diversity of the microbial community (Fuhrman and Suttle 1993; Wommack and C o l well 2000). Transduction is another method through which viruses affect the genetic diversity of a host species. Transduction is the transfer of genes from one host to another by a virus. For temperate viruses, the excision of the prophage from the host genome may not be exact, and a portion of the host's genome may be excised with the viral genome. The 14 segment of the host's genome could then be inserted into a new host following an infection. A l l of the host-virus interactions as well as the type of viral life cycle can contribute to the structuring of the prokaryotic community. 1.7 Potential Prokaryote Mortality Very little is presently known about types and rates of prokaryotic mortality at deep-sea hydrothermal vents. There are only a few reports of invertebrates grazing on prokaryotes at vent sites, but these were grazing on large prokaryotic mats, not free-living cells (Grassle 1985; Kar l 1995). Initial reports of the vent sites from the Galapagos suggested that the sites had abundant filter-feeding invertebrates that were capable of filtering the prokaryote cells out of the water column (Corliss et al. 1979). Nothing is presently known about the potential of prokaryotic mortality though flagellate grazing or viral infection. Only four previous studies have focused on protists at hydrothermal vents. One early study (Small and Gross 1985) examined fixed material from 9° N on the East Pacific Rise (EPR). Samples included particulates from within sample boxes that had been used to collect animals and rock samples. From these fixed samples, one flagellate and one amoeboid were identified along with several novel ciliates. Atkins et al. (2000) collected water samples from four different vent sites including M a i n Endeavour Field ( M E F ) , 9 and 21° N on the E P R and Guaymas Basin in order to isolate flagellates from around hydrothermal vents. Water samples were added to enrichment media and several different flagellates were isolated. The identity of the flagellates was determined using both microscopy and molecular methods. From these samples, several ubiquitous heterotrophic flagellates were isolated and identified. Many of these isolates represent widespread groups easily isolated from environmental samples. None of the isolates appeared to be novel and many could be identified to species level (Atkins et al. 2000). 15 Knowledge about the presence and molecular diversity of the pico- and nano-eukaryotes at deep-sea hydrothermal vents is limited to two studies. The first study collected sediment from the Guaymas Basin, extracted the D N A and cloned and sequenced 18S r D N A genes (Edgcomb et al. 2002). The other study collected sediment samples and microcolonizers from the Rainbow and Snake Pit fields on the Mid-Atlantic Ridge ( M A R ) and sequenced cloned 18S r D N A genes (Lopez-Garcia et al. 2003b). Both of the studies detected unknown 18S sequences that clustered deep within the eukaryotic tree. The Guaymas Basin samples yielded sequences closely related to phototrophs, suggesting that some surface-derived material was buried in the sediment. N o sequences closely related to phototrophs were detected from the M A R . This difference may be related to the much greater distance between the M A R and productive coastal water compared to the Guaymas Basin, which lies in the Gul f of California. The presence of novel eukaryotic sequences at the hydrothermal vent sites is not surprising as very few studies to date have looked at the diversity of the pico- and nano-eukaryotes within the deep sea (Lopez-Garcia et al. 2001; Moon-Van Der Staay et al. 2001). High numbers of sequences were detected that appear to be related to alveolates. These included the unknown marine Group I and II and unclassified groups. Ciliate sequences were also abundant in the clone libraries, but bodonid sequences were only detected from the M A R (Edgcomb et al. 2002; Lopez-Garcia et al. 2003b). Due to the low number of samples from non-hydrothermal sites in the deep sea, it is impossible to know whether these eukaryotes are specific to hydrothermal environments or are more cosmopolitan. Both of these studies looked at the diversity of eukaryotes within sediments while one of the studies did sample colonized surfaces. The study at the M A R did detect some eukaryotes from samples from the fluid-seawater interface, but small volumes restricted analysis (Lopez-Garcia et al. 2003b). Neither of these two studies suggests whether free-living pico- and nano-eukaryotes, specifically flagellates, are present in the water around hydrothermal vents. If there are free-living flagellates at these sites, they may have the 16 potential to graze on the free-living prokaryotes and may be both an important source of prokaryote mortality and a necessary link in the hydrothermal vent food web. Like grazers, very little is known about viruses within hydrothermal systems. One study looking at event plumes associated with the Gorda Ridge eruption in 1996 (Cowen and Baker 1998) detected increased abundances of viruses within the plume relative to the surrounding seawater (Juniper et al. 1998). The viral abundances from this study are very low compared to other estimates from the deep sea and may be underestimates due to fixation and storage of samples (Wen et al. 2004). The Gorda Ridge study does verify that viruses are present in the plumes associated with hydrothermal venting, suggesting that they may be a source of prokaryotic mortality. Another report of viruses from deep-sea hydrothermal vents comes from enrichment cultures (Geslin et al. 2003). Electron microscope studies of enrichment cultures from a hydrothermal vent site detected virus-like particles. Although attempts to purify these particles have not been successful, they appear to be replicating in the prokaryotes cultured from the hydrothermal samples, supporting the idea that virus-mediated mortality of prokaryotes occurs at vent sites. Recently, a study focused on the design of a large-volume sampler reported abundances of viruses in diffuse flow vents to be 3.13X10 5 to 1.48xl0 6 viruses mL" 1 (Wommack et al. 2004). 1.8 Aims of the Thesis This thesis represents an attempt to determine the potential sources of mortality of prokaryotes within a hydrothermal system. The first section (Chapter 2) begins by determining the abundance and distribution of viruses within a hydrothermal environment. Samples were collected from actively venting sites along the Endeavour Segment of the Juan de Fuca Ridge, as well as from the neutrally buoyant plume associated with vent sites. Because viruses are host-specific, the diversity of the potential hosts is an important factor affecting the ability of viruses to infect new cells. The second section (Chapter 3) looks at the diversity of free-living prokaryotes from different 17 samples collected from around a sulphide structure in the Ma in Endeavour Field as well as from the water column and a site at the Mothra field. This study uses P C R and D G G E (denaturing gradient gel electrophoresis) to obtain community fingerprints based on Bacterial and Archaeal 16S r D N A for each sample. Physical and chemical characteristics of the samples are compared with the fingerprints to determine factors that correlate with the presence of bands. Sequencing of bands excised from the D G G E gels provides more information, on the composition of the communities and the potential identities of some of the microorganisms present in the samples. The next section (Chapter 4) uses P C R , D G G E and sequencing methods to determine the diversity of the Eukaryotic community surrounding actively venting sulphide structures. This study is aimed at identifying novel organisms capable of grazing on free-living microorganisms. 18 CHAPTER 2 : High Abundances of Viruses in a Deep-Sea Hydrothermal Vent System Indicates Virus-Mediated Microbial Mortality 19 2.1 Summary M u c h higher abundances of viruses occurred throughout the 2200 m deep Endeavour Ridge hydrothermal-vent system off the west coast of North America than in the surrounding deep sea. The data, from hydrothermal-vent samples indicate that viral production is occurring at this vent system, and hence viruses are a source of microbial mortality. Samples collected from three actively venting sites, C lam Bed, S & M and Salut, had virus abundances ranging from 1.45 x 10 5 to 9.90 x 10 7 viruses mL" 1 , while the abundances of prokaryotes from the same samples ranged from 1.30 x 10 5 to 4.46 x 10 6 cells mL" 1 . Samples were also collected along the neutrally buoyant plume associated with the Ma in Endeavour Field. The abundances of viruses and prokaryotes in the plume were lower than at actively venting sites, with a mean of 5.3 x 10 5 cells mL" 1 (s.d. 2.9 x 10 5) and 3.50 x 10 6 viruses mL" 1 (s.d. 1.89 x 10 6). Prokaryotic and viral abundances in non-hydrothermal regions were as much as 10-fold higher than found in previous studies, in which sample fixation and storage likely led to large underestimates. This suggests that viral infection may be a greater source of prokaryotic mortality throughout the deep sea than previously recognized. Changes in abundances of prokaryotes and viruses within the neutrally buoyant plume suggest that viruses cause the daily lysis of 3.3-22% of the prokaryotic biomass. As well , large variability in the ratios of viruses to prokaryotes ( V B R ) among the samples indicates that production and removal rates of prokaryotes and viruses are not constant throughout the hydrothermal system. Overall, my results indicate that virus-mediated mortality of prokaryotes at these hydrothermal-vent environments is significant and would reduce energy flow to higher trophic levels. 20 2.2 Introduction Hydrothermal vents, typically associated with tectonically active mid-ocean ridges, are where chemically altered seawater is vented into the ocean at temperatures as high as 400°C. Unlike most life in the deep ocean which is dependent on the small amount of remaining low-quality photosynthetic production that rains down from the surface, the organisms at hydrothermal-vent environments are supported mostly by in situ production by chemosynthetic prokaryotes (Karl 1995). Hydrothermal vent environments are not limited to the immediate area of the active vent field. The buoyant, hot hydrothermal fluid rises and is entrained into the surrounding water. When diluted by about 10,000 fold (Lupton et al. 1985), the plume reaches neutral buoyancy, spreads laterally with the currents, and continues to be diluted by ambient seawater. Particulate and temperature anomalies can be used to trace vent plumes for several to tens of kilometres from the vent site. Plumes can be traced for >2000 km using chemical signatures such as 3 H e (Lupton and Craig 1981). Through the formation of a plume, hydrothermal venting can influence a far larger region than the area immediately around vent fields. The chemosynthetic prokaryotes within active hydrothermal-vent fields include attached, symbiotic and free-living species (Karl 1995). The abundances of free-living cells have been reported to be as high as 10 9 cells mL" 1 (Corliss et al. 1979), although most studies estimate prokaryote abundances to be 0.5-1.0 x 10 6 cell m L ' ^ K a r l et al. 1980; Winn et al. 1986). This value is approximately 100 fold greater than abundances reported for non-hydro thermal sites in the deep ocean (Hara et al. 1996; Taylor et al. 2003). Although primary production within a hydrothermal-vent environment is chemosynthetic, much of the microbial biomass likely consists of heterotrophic prokaryotes using organic matter released from animals and other microbes (Karl 1995). Abundances of prokaryotes within neutrally buoyant hydrothermal plumes have been reported to range from 10 3 to 10 6 cells mL" 1 (Cowen and L i 1991), and are often higher than in the surrounding seawater (Cowen et al. 1990; Cowen et al. 1998; Cowen et al. 2002; De Angelis et al. 1993; Juniper et al. 1998). Based on measurements of the 21 removal of H2, CH4 and NH4+ in the Endeavour Ridge plume, estimates of in situ 2 1 chemosynthetic production range from 1.7 to 9 mg C m" d" and are comparable to estimated surface fluxes of 1.4 to 4.4 mg C m" 2 d"1 (Cowen et al. 2002). One fate of this microbial production is consumption by the high biomass of animals at hydrothermal vents (Grassle 1985; Kar l 1995). A s well , zooplankton near vent fields and around the plume may graze on free-living microbes,-as indicated by the elevated abundances of zooplankton overlying the Endeavour Ridge plume (Burd and Thomson 1995; Thomson et al. 1992). Vi ra l lysis is a second source of microbial mortality. Virus abundances in the deep sea have been reported to be ca. 10 4 to 10 6 viruses mL" 1 , which is about 10 to 1000 fold lower than in surface waters (Cochlan et al. 1993; Hara et al. 1996). The reported abundances of prokaryotes and viruses in the deep sea (Weinbauer and Peduzzi 1994; Wi lcox and Fuhrman 1994) would imply that contact rates would be below the threshold required for high rates of lytic virus production (Murray and Jackson 1992). Moreover, low temperatures, low availability of nutrients and low growth rates suggest that rates of virus production w i l l generally be low in the deep sea. A n exception may be hydrothermal-vent environments, where relatively high microbial biomass and production may lead to hot spots of lytic viral production. The impact of virus-mediated mortality at hydrothermal-vent environments would affect carbon cycling and potentially community composition. Vi ra l lysis converts cellular components into D O M , making them unavailable for zooplankton grazing, but potentially stimulating secondary production of heterotrophic prokaryotes (Fuhrman 1999; Wi lhe lm and Suttle 1999). There is morphological evidence that prokaryotic communities change as hydrothermal plumes age (Cowen and L i 1991; Winn et al. 1995). This may be a change from a chemosynthetic, vent-field derived community to a more heterotrophic, deep-sea community that takes advantage of D O M in the plume. Subsequent lysis of these cells w i l l also release D O M , and further stimulate the growth of the heterotrophic community. 22 Viruses are recognized as being abundant and important components of the ecosystem in the surface waters of the World 's oceans, but little research has explored viruses and virus-mediated processes in the deep ocean. Over a 4-year period, my study examined the abundance and distribution of viruses within an active vent field and its associated plume to determine i f virus-mediated mortality was a factor affecting microbial dynamics in these systems. 2.3 Materials and Methods 2.3.1 Sampling Site The Endeavour Segment of Juan de Fuca Ridge extends approximately 300 k m in a north-south direction about 300 k m offshore from British Columbia, Canada (Figure 2.1a). The axial valley is about 100 m deep and 10 k m wide. Although the water depth in the area is generally ca. 2500 m, the ridge and axial valley are ca. 2100 and 2200 m deep, respectively (Delaney et al. 1992; Robigou et al. 1993; Thomson et al. 1992). Along the ridge are five documented venting sites. The more northerly sites are Sasquatch and Salty Dawg; they appear to be older, less vigorously venting fields (Thomson et al. 2003). To the south, High Rise, Ma in Endeavour and Mothra are younger sites with multiple black-smoker structures. Between the main fields are areas of diffuse venting (Thomson et al. 2003). 2.3.2 The Hydrothermal Fields Samples from within the hydrothermal vent fields were collected using the R O V (remotely operated vehicle), R O P O S , during cruises in M a y 2001, August 2002 and July 2003. The three active hydrothermal locations sampled (Figure 2.1b) had very different structures and communities. Two of the sites, S & M and Salut are sulphide structures in the M a i n Endeavour Field (MEF) . S & M has several black smokers as well as diffuse-flow vents; Salut has fewer smokers with more diffuse venting. Clam Bed lies approximately 1.3 k m to the N E of the M E F and is a diffuse-flow field with one white smoker. 23 Real-time video was used to position the sampling intake nozzles. Samples were then collected with a suction sampler capable of collecting seven 2-L samples. In most cases, temperature was obtained using probes mounted at intakes and outlets. Sampling hoses were flushed with water from the sample site before collection of each sample to reduce the likelihood of contamination. 2.3.3 The Neutrally Buoyant Plume During 2000 and 2001, the plume was sampled from the C G G S John P. Tully. Salinity, temperature and light transmission were determined using a rosette-mounted C T D and transmissometer. The plume was detected in real-time by light transmission and sampled on the up-cast using Niskin bottles. Samples were collected along transects beginning at the M E F (0 km) to approximately 23 km downstream from areas of active venting (Figure 2.1b). During 2000, the plume was detected along a transect S W of the M E F , with samples collected at 1.3, 8.8 and 23 km from the site of active venting. In 2001, the plume was detected west of the field and samples were collected at 0, 4.4 and 9.8 km. In 2000, a background sample was collected approximately 55 km N E of the M E F , where there was no hydrothermal signal based on temperature or absorbance data. Light transmission and temperature data were converted into anomalies to make the plume boundaries more evident. For each profile, the percent of light transmission was converted into an attenuation coefficient (1 - %Transmittance/100) and then converted into an anomaly by subtracting the attenuation coefficient for the water column overlying the plume. Samples were defined as being within the plume when the light attenuation anomaly was > 0.0055 m"1 and the potential temperature anomaly was > 0.006 °C. 2.3.4 Abundances Water samples were immediately processed for prokaryote and virus abundances using the method of Hennes and Suttle (1995). Briefly, 1 m L of sample was filtered through a 0.02 ixm pore size Anodisc filter (A10 3 , Whatman, Brentford, U K ) and placed on a drop of Yo-Pro 1 (Molecular Probes, Eugene, OR) . The filter was incubated for 48 h in the dark and mounted on a slide with 100% glycerol. The slides were stored at -20°C until counted using an Olympus A X - 7 0 microscope with a wide-blue filter. A t least 24 200 prokaryotes and 200 viruses were counted in 20 fields and converted into abundance estimates using the formula in Suttle (1993). Although the Yo-Pro 1 method was originally developed for viruses, it can also be used to accurately estimate the abundance of prokaryotes (Appendix A l ) . 2.3.5 Data Analysis The non-normal distributions of the prokaryote and virus abundance data required nonparametric statistical tests for analyses. Correlations were done using Spearman's Rho, calculated using J M P In (SAS Institute Inc., Cary, N C ) . Nonparametric comparisons were done using either the Wilcoxon (2 levels) or the Kruskal-Wallis Rank-sum test (>2 levels). Post-hoc analysis was performed following statistically significant results from the Kruskal-Wallis Rank-sum test using the Dunn's Test. 25 -132° -130' -128° -126° -124° -122° " 1 a — ' 11l Figure 2.1 Sample Locations a) Location of samples showing the Endeavour Segment in relation to the coast of B C . b) Close up view of the sample locations in close proximity to the M E F . The grey lines represent depth contours and increasing depth to the west. 26 2.4 Results Prokaryotes and viruses were found in all samples, which ranged in temperature from ambient (~1.8°C) to 90°C. The abundance of prokaryotes ranged from 1.30 x 10 5 to 4.46 x 10 6 cells mL" 1 , while virus abundances were typically higher and ranged from 1.45 x 10 5 to 9.90 x 10 7 mL" 1 (Table 2.1 and 2.2). 2.4.1 The Active Hydrothermal Fields The highest abundances of prokaryotes and viruses were in samples from the vent fields, although the data were highly variable (Figure 2.2). There was no significant difference in the prokaryote abundance among the three different vent sites (Kruskal-Wall is n=49, p=0.0821). The abundance of viruses varied among sites (Kruskal-Wallis n=49, p=0.0035), with Salut having a lower average abundance than both Clam Bed and S & M , which did not differ from each other (Dunn's post hoc test oc=0.05). Smoker and diffuse flow samples were collected from both Clam Bed and S & M . The abundance of both cells and viruses was greater for the diffuse flow samples than the smoker samples collected from within the same field (Wilcoxon Clam Bed n=10, pceiis = 0.0150, peruses =0.0550; S & M n=22, p c e i i s = 0.0290, p v i r u s e s =0.0002). The average temperature of the diffuse-flow samples compared to that of the smokers was 8.74°C (s.d. 10.34, n = 21) and 23.9°C (s.d. 28.24, n = 20), respectively. For all samples where temperature was available, prokaryote and virus abundances were negatively correlated with temperature (Spearman's Rho = -0.33809, -0.4934 and p = 0.0140, 0.0010 respectively), although viral and prokaryotic abundances were positively correlated with each other (Spearman's Rho = 0.6819, p < 0.0001). There was no significant difference in the abundances of prokaryotes among the three years of sampling (Kruskal-Wallis n=49, p c eiis = 0.2313), but virus abundances were significantly different (Kruskal-Wallis n=49, pviruses=0.0008). Post-hoc tests (Dunn's, oc=0.05) showed that virus abundance in samples from 2003 were significantly lower than samples from 2001. Samples from 2002 did not differ significantly from either 2001 or 2003. Samples collected in 2002 did not include any diffuse flow samples, but were all white- or black-smoker samples. The samples from 2003 were all diffuse-flow samples, but were 27 collected from Salut where some of the lowest abundances of both prokaryotes and viruses were detected. 2.4.2 The Neutrally Buoyant Plume The plume was identified by an increase in the light-attenuation anomaly and potential-temperature anomaly (Figure 2.3), which were correlated in all profiles sampled through the plume (Table 2.3). The magnitude of the potential-temperature and light-attenuation anomalies decreased as the distance from the source of venting increased. A background profile, collected 55 k m N E of the M E F , showed no temperature- or light-attenuation anomaly. The abundances of prokaryotes and viruses were significantly higher in 2001 than in 2000 for all profiles collected through the plume (Wilcoxon n=85, p c e u s <0.0001 and Pviruses <0.0001). For example, the abundances of cells and viruses were higher in the 0-k m profile from 2001 than in the 1.3-km profile from 2000 (Wilcoxon n=29, pceiis = 0.0002, pviruses = 0.0606), even though the light-attenuation (Atten) and potential-temperature anomalies (Temp) for each profile were not significantly different (Wilcoxon n=29, pAtten= 0.8786, pTemP= 0.3155). Similarly, the abundances of cells and viruses were higher in the 9.8-km profile from 2001 than in the 8.8-km profile from 2000 (Wilcoxon n=31, pceiis<0.0001, peruses = 0.0045), but there were no significant differences in the anomalies (Wilcoxon n=31, pAtten = 0.2293, pT emP = 0.4469). Because of the year-to-year differences, spatial changes along the plume were considered separately for each year. 2.4.3 Profiles from 2000 In 2000, the abundance of prokaryotes was positively correlated with both the light-attenuation and the potential-temperature anomalies for the profiles at 1.3 and 8.8 km, but only with the light-attenuation anomaly at 23 km (Table 2.3). In the background profile there was no indication of a hydrothermal influence, but the light-attenuation and potential-temperature anomalies were strongly correlated with depth (Spearman's RhoAtten = 0.7324, p = 0.0019; Rho T e mp = 0.7250, p = 0.0022), as was cell abundance (Rho = 0.8107, p = 0.0002). In this profile, the abundances of viruses and prokaryotes 28 were also correlated. No other profiles showed positive correlations between depth and anomalies or abundances, presumably because of the overriding influence of the plume. For most profiles, virus abundance was not correlated with any of the measured parameters, except for the 23-km profile where viral abundance and the potential temperature anomaly were positively correlated. The abundance of prokaryotes in the plume samples was significantly higher than in the non-plume samples (Wilcoxon n=60, p c e u s = 0.0030). The average abundance in the plume was 3.14 x 10 5 cells mL" 1 (s.d. 1.13 x 10 5, n = 32), while the average for the non-plume samples was 2.40 x 10 5 cells mL" 1 (s.d. 5.74 x 10 4, n = 28). There was no significant difference in the abundance of viruses within the plume (2.48x 10 6 viruses mL" 1 , s.d. 1.40 x 10 6, n = 32) compared to the non-plume samples (2.40 x 10 6 viruses mL" 1 , s.d. 1.01 x 10 6, n = 28) (peruses = 0.9645). 2.4.4 Profiles from 2001 Although the mean abundances of cells and viruses were higher in the plume from 2001 than from 2000, the patterns of distribution in the profiles were similar. A t 0 k m and 9.8 km the light-attenuation and potential-temperature anomalies were positively correlated with the abundance of prokaryotes. A s well , the abundance of viruses in the 0-k m profile was correlated with the two anomalies and the prokaryote abundance. The abundances of cells and viruses were highest in the 4.4-km profile, but were not significantly correlated with the plume indicators. In both years, the abundances of prokaryotes and viruses were lowest in the profile closest to the vents. The average abundances of prokaryotes (7.59 x 10 5 cells mL" 1 , s.d. 2.47 x 10 5, n = 30) in the plume were higher than their abundances (5.35 x 10 5 cells mL" 1 , s.d. 3.06 x 10 5, n = 10) above and below the plume (Wilcoxon n=40, p c e i i s =0.0423). There was no significant difference in the abundance of viruses within the plume (4.43 x 10 6 viruses mL" 1 , s.d. 1.76x 10 6, n = 30) compared to outside of the plume (3.95 x 10 6 viruses mL" 1 , s.d. 2.44 x 10 6, n = 10) ( p v i m s e s =0.5219). 29 2.4.5 VBR (Virus to prokaryote ratio) The ratio of viruses to prokaryotes varied considerably within the hydrothermal-vent field as well as within the plume (Table 2.1 and 2.2). The average V B R for the background plume sample was 10.9 (s.d. 3.0, n = 15). Within the hydrothermal-vent field, the V B R ranged from 1.1 to 247.5, with the highest ratios (247.5, 85.8, 78.2, and 66.8) being from diffuse-flow samples and a 3°C smoker sample from S & M . The V B R varied significantly among vent sites (Kruskal-Wallis n=49, p=0.0006) with Salut significantly lower than S & M (Dunn's test oc=0.05), but C lam Bed not differing significantly from either S & M or Salut. This relationship did not change i f the very high value of 247.5 was excluded from the analysis (Kruskal-Wallis n=48, p=0.0011). For fields where both diffuse flow and smoker samples were collected, there was no difference in V B R for Clam Bed, but diffuse flow samples from S & M were significantly higher than the smoker samples (Wilcoxon n=22, p=0.0116). Within the samples in the plume, the V B R was higher in samples collected in 2000 than in 2001 (Wilcoxon n=62, p = 0.0290). In 2000 the average V B R was 8.3 (s.d. 4.0, n = 32) compared to 6.1 (s.d. 1.8, n = 30) in 2001. Compared to the background profile, the plume samples from both years had significantly lower average V B R s (Wilcoxon n=47, p20oo = 0.0054, n=45, p 2 0 oi < 0.0001). 30 Table 2.1 Prokaryote and Virus Abundances from Active Hydrothermal Vent Fields The abundance of prokaryotes and viruses from samples collected within active hydrothermal vent fields. Mean values with standard deviations are presented from this study as well as previous studies. Location Type Number of Samples C e l l s , x l 0 6 mL" 1 Viruses, x l O 6 mL" 1 V B R Source S & M Black smoker 12 0.76 (0.97) 11.46(10.49) 26.6 (23.4) This study S & M Diffuse flow 8 1.20 (0.55) 61.89 (21.28) 73.5 (72.5) This study Clam White smoker 6 0.88 (0.72) 20.00 (19.07) 20.4 (10.9) This study Clam Bed Diffuse flow 4 3.79 (0.73) 45.02 (13.56) 12.8 (6.3)' This study Salut Diffuse flow 17 0.86 (0.87) 9.12(11.9) 10.4 (9.6) This study Galapagos Vent Field Diffuse flow n.d. a 0.5 to 1.0b n.d. n.d. Kar l et al. 1980 Main Endeavour Field Diffuse flow 2 0.13 and 0.074 c n.d. n.d. Winn et al. 1986 B i o 9 (EPR) Diffuse flow 1 0.264 (0.09 l ) d 0.313 (0.13) 1.19 Wommack et al. 2004 Q Vent (EPR) Diffuse flow 1 0.098 (0.023)d 0.364(0.12) 3.73 Wommack et al. 2004 M Vent (EPR) Diffuse flow 1 0.45 (0.11)d 1.48 (0.42) 3.45 Wommack et al. 2004 a n.d.=no data given b Method not given c Abundances determined using Acridine Orange on stored, fixed samples d Abundances determined using S Y B R Gold on stored, fixed samples Table 2.2 Prokaryote and Virus Abundances from Hydrothermal Plumes and the Deep Sea The abundance of prokaryotes and viruses from the plume samples collected in 2000 and 2001 with values from other studies of Location Samples Cells, x l O 6 mL" 1 Viruses, x l O 6 mL" 1 V B R Source Plume 0 k m 13 0.56 (0.19) 3.37(1.15) 6.4 (2.0) This study Plume 1.3 k m 12 0.29 (0.07) 2.92(1.86) 10.0 (5.3) This study Plume 4.4 km 8 1.03 (0.07) 6.18(2.13) 6.0 (1.9) This study Plume 8.8 km 15 0.31 (0.14) 2.03 (0.58) 7.2 (2.2) This study Plume 9.8 k m 9 0.81 (0.14) 4.41 (0.63) 5.6(1.6) This study Plume 23 km 5 0.38 (0.10) 2.78 (1.73) 7.5 (4.0) This study A l l Plume 64 0.53 (0.29) 3.50 (1.89) 7.3 (3.5) This study Background, 55 k m N E of M E F 15 0.27 (0.05) 2.94 (1.08) 10.9 (3.0) This study Endeavour Ridge plume 5 0.001-0.016 a n.d. n.d. Winn et al. 1986 Endeavour Ridge plume 19 0.14 to 1.3" n.d. n.d. De Angelis et al. 1993 Gorda Event Plume E P 9 6 A n.d. n.d. n.d. 1.0 (0.2) c Juniper et al. 1998 Gorda Event Plume G R 2 n.d. n.d. n.d. 2.2 (0.21) c Juniper et al. 1998 Gorda Event Plume G R 3 n.d. n.d. n.d. 2.0 (0.1 ) c Juniper et al. 1998 N E Pacific n.d. 0.14 b n.d. n.d. De Angelis et al. 1993 400-2000 m Pacific 2 0.11 0.49 4.4 b Hara et al. 1996 1310m Anoxic Cariaco Basin 2 0.08 0.1-6.0 1.2-75.0d Taylor et al. 2003 Antarctica (300-800 m) 5 0.18(0.03) 2.30 (0.67) 13.0(4.5) e Guixa-Boixereu et al. 2002 Water column 1500m E P R 1 0.54 (0.1)1 2.53 (0.46) 4.65 Wommack et al. 2004 0 Standard error. Prokaryotes with D A P I on stored, fixed samples. Viruses with modified Yo-Pro 1 on stored, fixed samples. d Prokaryotes with D A P I on stored, fixed samples. Viruses determined using S Y B R Green on stored, fixed samples. Prokaryotes with D A P I on stored, fixed samples. Viruses determined using Yo-Pro 1 on unfixed samples. f S Y B R Gold on stored, fixed samples. 1000 q 100 4 CO o CO CD CO 3 1 -J 0.1 0.1 • • ft A A • A A m • A A A A A 4 1 • A Clam Bed, diffuse flow • Clam Bed, white smoker A S&M, diffuse flow • S&M, black smoker A Salut, diffuse flow i—i—i—i—r - i — i — i — i — i 1 Cells ( x10 6 mf 1 ) 10 Figure 2.2 The Prokaryote and Virus Abundances from active Hydrothermal Vent Fields Abundances of prokaryotes and viruses from samples collected from Salut, S & M and Clam Bed hydrothermal vents. Samples are shown as being either diffuse-flow or smoker samples collected from one of the three sites. 33 Cells or Viruses (x 10° ml"') 0.1 1 10 -0.02 0.00 0.02 0.04 0.06 0.08 Light Attenuation Anomoly (m"^ ) or P o t e n t i a l T e m p e r a t u r e A n o m o l y (C) Cells (x 10 6mr 1) 0.1 1 10 -0.02 0.00 0.02 0.04 0.06 0.08 Light Attenuation Anomoly ( n r f 1 ) or P o t e n t i a l T e m p e r a t u r e A n o m o l y (C) Figure 2.3 Depth Profiles from Hydrothermal Plume Casts Profiles of light attenuation anomaly, potential temperature anomaly, prokaryote abundance and virus abundance from the seven stations sampled in 2000 and 2001. Light attenuation anomaly is shown in black, with the potential temperature anomaly in dark grey. Prokaryote cell abundances are shown with the o and virus abundances with the T . 34 Table 2.3 Correlations from Profiles Collected Along the Hydrothermal Plume Correlations (Spearman's Rho) between anomalies, prokaryotes, and viruses for the seven profiles sampled in 2000 and 2001. ^ Profile Attn a -Temp b Attn-Cells Temp-Cells Attn-Virus Temp-Virus Cells-Virus 1.3 k m 0.9679" 0.4893' 0.4857' n.s. n.s. n.s. 8.8 k m 0.9462" 0.9152" 0.8576" n.s. n.s. n.s. 23 k m 0.8021" 0.6140" n.s. n.s. 0.6154" n.s. Background n.s. 0.6185" 0.4964' n.s. n.s. 0 .5571" 0 k m 0.8889" 0.7819" 0.7767" 0.6689" 0.5516" 0.6117" 4.4 k m 0.9642" n.s. n.s. n.s. n.s. n.s. 9.8 k m 0.9157" 0.6307" 0.7802" n.s. n.s. n.s. p<0 .1 n.s.= p > 0.1 a Attn = light attenuation anomaly b Temp = potential temperature anomaly 35 2.5 Discussion This study adds to the very limited data on the abundances of viruses and prokaryotes in a hydrothermal-vent plume. In addition, this chapter presents the first data on viral abundances from black smokers and greatly extends the data for prokaryotes at deep-sea hydrothermal-vent sites. The abundances of prokaryotes adjacent to black smokers and white smokers were similar to previous reports for diffuse-flow areas in the Galapagos Vent Field, but up to 10-fold higher than reported for diffuse flow from the Main Endeavour Field ( M E F ) (Table 2.1). M y estimates for diffuse-flow environments, although highly variable, were greater than my estimates from the smokers, and consequently greatly exceeded previous estimates for the M E F (Winn et al. 1986). The. abundances of prokaryotes reported here are also higher than recent reports from diffuse flow vents on the East Pacific Rise (Wommack et al. 2004). Similarly, my estimates of the abundance of prokaryotes within the plume is about 2-fold and 100-fold higher than reported for the same plume by De Angelis et al. (1993) and Winn et al. (1986), respectively (Table 2.2). The abundances reported for the event plumes associated with the Gorda Ridge were 10- to 100-fold lower than reported here (Juniper et al. 1998). M y abundances from outside the plume are approximately 2-fold higher than most other deep-sea values reported for prokaryote abundances. There are two other reports of viral abundances within hydrothermal-vent environments. The first is for event plumes associated with an eruption at Gorda Ridge (Juniper et al. 1998), in which estimates were a tenth to a hundredth of those we observed for the Endeavour Ridge plume. The second, of virus abundance from diffuse flow at three different vent sites on the E P R (Wommack et al. 2004), also reports virus abundances a tenth of the values observed at Endeavour Ridge. The abundances we found for the background samples were generally 10-fold higher than previous reports for the deep ocean. One exception is a study in the deep waters off Antarctica (Guixa-Boixereu et al. 2002) that reported 2 .30x l0 6 viruses mL" 1 (s.d. 6 .7x l0 5 , n=5), similar to 36 the background abundance (2.38 x 10 6 viruses mL" 1 , s.d. 9.96 x 10 5, n = 29) reported here. The lower abundances reported previously likely result from virus decay during storage of aldehyde-fixed samples. Frequently, abundance estimates of viruses and prokaryotes have been made on samples fixed in glutaraldehyde or formaldehyde. Yet prokaryotes (Gundersen et al. 1996; Turley C . M . 1993; Turley and Hughes 1992) and especially viruses (Brussaard 2004; Wen et al. 2004) decay quickly in samples with these fixatives. Within a few hours, only a fraction of the viruses in preserved samples can be enumerated by epifluorescence microscopy (Wen et al. 2004). A s the Yo-Pro 1 method used in this study (Hennes and Suttle 1995) must be carried out on unfixed samples, fixation artefacts are not an issue. Another study (Guixa-Boixereu et al. 2002) that used the Yo-Pro 1 method also reported viral abundances similar to those found in my study, supporting my contention that most reports of viral abundance in the sea are greatly underestimated. 2.5.1 The Active Hydrothermal Fields The samples collected from actively venting sites included the highest and lowest abundances of prokaryotes and viruses. The lowest and most variable abundances were in the diffuse-flow samples from Salut. Because samples were not collected from Clam Bed or S & M in 2003, it is not known i f lower abundances occurred throughout the vent sites in 2003 or i f the low and highly variable abundances were specific to Salut. The distribution of prokaryotes and viruses around active hydrothermal vents appears to be strongly influenced by temperature rather than the type of field sampled. Temperature is directly influenced by mixing between the pure hydrothermal fluid and the surrounding vent water (Prieur 1997). It is unlikely that pure hydrothermal fluid contains many viable prokaryotes or viruses; hence, mixing not only reduces temperature to make the environment more favourable for the growth of prokaryotes, but also introduces prokaryotes and viruses from the surrounding environment (Karl et al. 1988). High abundances of prokaryotes and viruses at the diffuse-flow sites l ikely arise from lower temperatures caused by greater mixing associated with diffuse flow. Sub-37 seafloor mixing of hydrothermal fluid with seawater may also support a subsurface microbial community (De Angelis et al. 1993; Deming and Baross 1993; Juniper et al. 1995), which may be a source of the prokaryotes and viruses observed in the diffuse-flow fluids. High temperatures prevent animals from heavily colonizing smoker faces. In contrast, the lower temperatures at diffuse-flow vents allow for high animal biomass (Grassle 1986), which in turn provides more surfaces and substrates for microbial growth. A s well , turbulent mixing resulting from fluid flow may transport microbes from animals and the sub-seafloor, and inject them into the water column. This would result in a dilution of sub-seafloor microbe abundances, but higher abundances than in the surrounding water. The strong correlation between the abundance of prokaryotes and viruses within the hydrothermal fields is consistent with studies from other environments (reviewed in Wommack and Colwel l 2000). The relationship presumably results from the dependence of viruses on the cells they infect. It is clear that viral production and prokaryote growth occurred at the vents based on the 3.5- and 6.0-fold higher average abundances of prokaryotes and viruses, respectively, at the active vent sites, relative to abundances at similar depths from the background profile. 2.5.2 The Neutrally Buoyant Plume The entrainment of surrounding seawater dilutes the hydrothermal components of the vent fluid and results in a neutrally buoyant plume that is distinct from the seawater associated with the active vent sites. The abundances of prokaryotes and viruses are lower in plume samples overlying active vent sites compared to samples collected within active fields themselves. The relative decrease was less for cells than viruses, suggesting that the removal of viruses was proportionately greater in the newly formed plume. The higher removal rates of viruses may result from the high particulate loads found in young plumes (Kadko et al. 1990), which could adsorb the viruses (Juniper et al. 1998). The strong positive correlations between the abundance of prokaryotes and the temperature- and light attenuation-anomalies suggest microbial growth was higher in the vent plume than in the surrounding seawater. In contrast, the lack of a strong correlation 38 within the plume between virus abundance and either the anomaly data or prokaryote abundance suggests that viral production and loss were uncoupled from microbial production. This could occur i f prokaryotic community composition changed along the vent plume, as is suggested by changes in the morphology of cells when viewed by T E M (transmission electron microscopy) (Cowen and L i 1991; De Angelis et al. 1993). These community shifts could be driven by changes in substrate availability, and by mixing of the plume with the surrounding water, and would likely cause a mismatch between the prokaryotic and viral communities. This would decrease the contact rates between viruses and the specific cells they infect, and consequently lower viral production rates. The positive correlation between temperature anomaly and virus abundance in the 0-km and 23-km profiles (Table 2.3) suggests that in these two profiles virus production was coupled to prokaryotic production. The 0-km profile, directly over the M E F , likely represents a microbial community dominated by prokaryotes and viruses entrained from the vent field and surrounding seawater. As the plume ages, an uncoupling of the two communities may occur, but by 23 km, the virus community appears to have stabilized and become coupled to a new prokaryote community. Increases in the abundances of prokaryotes and viruses as the plume aged suggests an active microbial community. Although the plume meanders, current strengths vary from 1 k m d"1 (Roth and Dymond 1989) to 8.64 km d"1 (Thomson et al. 2003), and the hydrothermal signature may not be derived entirely from the M E F (Mihaly et al. 1998; Thomson et al. 1998). Virus-mediated mortality and prokaryote growth rates can be roughly approximated using average abundances for the entire depth of the plume. The approximations assume that the abundances of prokaryotes and viruses along the plume system are stable over short time periods of days to weeks, although stability over longer time-scales is not supported by the data. In the samples collected in 2000, the average number of prokaryotes in the plume between 1.3 and 8.8 k m from the M E F increased by 2 . 0 x l 0 4 cells mL" 1 , while virus abundance decreased by 8 .9x l0 5 viruses mL" 1 . This suggests that the prokaryotes were growing, but any viral production was countered by losses. From 8.8 to 23 km, the 39 / prokaryotes increased by 7 . 0 x l 0 4 cells mL" 1 and viruses by 7 . 5 x l 0 5 viruses mL"' . Assuming that ca. 25 viruses are produced for each cell lysed (Wommack and Colwel l 2000), then the increase in viral abundance represents the death by viral lysis of 3 . 0 x l 0 4 cells mL" 1 , or 10% of the standing stock of prokaryotes at 8.8 km. Assuming an average flow rate for the plume of 4.8 k m d"1, it would take ca. 3 d for water to travel from 8.8 to 23 km. Therefore, including cells lost by viral lysis, at least l . O x l O 5 cells mL" 1 were produced, which corresponds to a growth rate of 0.11 d"1. This is a minimum estimate and does not take into account dilution of cells or viruses entrained from surrounding seawater, or other sources of mortality such as protozoan grazing. In 2001, prokaryote and virus production appeared to be higher in the newly formed plume. From 0 to 4.4 k m from the M E F the. average abundance of cells increased by 4 . 7 x l 0 5 cells m L ' 1 and the viruses increased by 2 . 8 x l 0 6 viruses mL" 1 . This increase in viruses corresponds to the lysis of l . l x l O 5 cells mL" 1 , or ca. 20% of the standing stock at 0 km. If the plume water takes 0.9 d to move a distance of 4.4 km, the estimated net growth rate of the prokaryotes is 1.1 d"1. Differences between 2000 and 2001 were seen in the abundances of prokaryotes and viruses as well as in estimates of growth rates and viral production. Samples from 2001 have higher mean abundances of prokaryotes and viruses, fewer viruses relative to cells, and the estimated growth rates and viral production rates are higher than in 2000, suggesting a more active microbial community. One explanation for the differences between years is that sampling in 2001 may have been closer to the core of the plume than in 2000. The plume rises and spreads laterally, causing the edges of the plume to mix with the surrounding water, eventually diluting the plume so it is no longer detectable. The mixing and dilution is greatest at the edges of the plume and reduced within the core; hence, prokaryotic and viral abundances would be greatest in the plume core. A s no significant differences were detected in plume indicators between profiles collected at similar distances in 2000 and 2001, there is little support for this explanation. A second explanation is related to tectonic activity within the Endeavour Ridge system in 1999 that caused changes in fluid discharge temperature and particulates in the 40 water column within the M E F (Johnson et al. 2000). These changes suggest that the subsurface geology and seawater convection was altered during the earthquakes, which could have affected venting rates, fluid chemistry and ultimately the microbial community within the plume. Samples were not collected from the vent fields during 2000, precluding comparisons between the plume and the fields for these years. 2.5.3 The VBR Differences in prokaryote and virus abundances among profiles suggest that production relative to removal changed for both cells and viruses as the plume aged. This change is reflected in the variation in the V B R , which represents the sum of all production and removal of both prokaryotes and viruses. The average V B R reported for a variety of aquatic environments is 3-10 (Wommack and Colwel l 2000). The average V B R for the background profile in this study was 10.9, which is lower than for the vent field (26.7), but higher than the plume (7.3). It is l ikely that estimates of V B R in other studies have been underestimated, at least in part, because viral abundances were obtained by T E M (c.f. Hennes and Suttle 1995) or because samples were improperly fixed (c.f. Wen et al. 2004). The high V B R in the vent field can also imply a high net rate of viral production relative to removal. High rates of viral production can be the result of large burst sizes, where high numbers of virus particles are released from each lysed cell . Typical estimates of burst size in field samples range between 10 and 50 (Wommack and Colwel l 2000), although burst sizes of over 100 are common in rapidly growing cells (Borsheim 1993). The higher V B R could have resulted from low rates of virus removal relative to production, although high particulate concentrations around the vent sites suggest removal rates were high. Lower V B R s within the plume compared to the surrounding water were also found by Juniper et al. (1998) in the Gorda Ridge eruption plumes. This pattern could result from a number of factors including higher loss rates of viruses within the plume as viruses bind to particulates and sink. Alternatively, host-virus systems within the plume could have a low burst size, reduced virus production due to a mismatch in the 41 composition of the viral and prokaryotic communities, or increased prokaryote production relative to virus production. The high abundances of viruses relative to surrounding waters indicate the Endeavour Ridge hydrothermal-vent system is an area of active viral production and hence, virus-mediated microbial mortality. Moreover, the high abundances of viruses reported in this study in both hydrothermal and non-hydrothermal regions relative to abundances found in other studies imply that viral abundances have been underestimated in other studies, and their role in ecological and geochemical processes in the deep sea needs to be re-evaluated. 42 CHAPTER 3: High Spatial Heterogeneity of Microbial Communities in Diffuse Flow Fluids at a Deep-Sea Hydrothermal Vent 43 3.1 Summary The comrnunity composition of Bacteria and Archaea was investigated using P C R and D G G E in samples collected from deep-sea hydrothermal vent environments on the Endeavour Segment in the northeast Pacific. Samples collected represented a range of conditions from 75 to 95% ambient seawater and 1.8 to 42°C. D G G E analysis of 21 samples resulted in 4-21 bacterial and 3-22 archaeal bands. Cluster analysis of the D G G E fingerprints showed little similarity between the bacterial and archaeal communities, with no distinction between samples collected in close proximity to each other and those collected further away. Sequence analysis of selected D G G E bands shows the communities to have similarities to other deep-sea hydrothermal vent microbial communities. The sequences from the bacterial analysis had high numbers of y- and e-Proteobacteria. The archaeal sequences were composed of two groups: mesophilic, uncultured marine groups C M G 1 and E M G 2 representing the ambient seawater; and thermophilic Crenarchaeota and Euryarchaeota representing the hotter hydrothermal environment. The high heterogeneity in the microbial communities suggests differences in the sources of the microbial communities, likely due to variability in the subsurface environment. Heterogeneity of microbial communities may affect local mineralization of sulphide chimney structures and development of the invertebrate communities. 44 3.2 Introduction M u c h of the microbiological work at deep-sea hydrothermal vents has focused on isolating novel microorganisms. For the prokaryotes, this has resulted in more than 100 newly described Bacteria and Archaea isolated from sediments, chimney structures, vent fluids and water samples (Baross and Deming 1995; Miroshnichenko 2004). Many of these novel species are thermophiles or hyperthermophiles, with optimal growth temperatures above 45°C. One strain, strain 121 isolated from a water sample collected from the Mothra vent field on the Juan de Fuca Ridge, is capable of growth at 121°C (Kashefi and Lovley 2003). O f these thermophiles, 4 genera of Archaea and 14 genera of Bacteria have been identified that are believed to be endemic to deep-sea hydrothermal vents (Miroshnichenko 2004). Many other isolates have close relatives that have been isolated from shallow or terrestrial hot habitats. Even with new culturing techniques, including high-pressure and high-temperature incubations, many of the prokaryotes from deep-sea hydrothermal samples have resisted isolation to date. Because of limitations in culturing, sequence-based approaches have been used to determine the microbial community composition at deep-sea hydrothermal vents. Most of these studies have used P C R amplification of 16S r D N A to generate clone libraries for sequencing and phylogentic analyses. Vent sites have been sampled in the Atlantic(Lopez Garcia et al. 2003a; Nercessian et al. 2003; Schrenk et al. 2004), Pacific (Huber et al. 2002; Huber et al. 2003; Moyer et al. 1995; Moyer et al. 1998; Summit and Baross 1998), and Indian Oceans (Takai et al. 2004). These habitats include high temperature vent fluids (Reysenbach et al. 2000), chimney structures (Hoek et al. 2003; Schrenk et al. 2004; Schrenk et al. 2003), animal symbionts (Haddad et al. 1995) and sediments (Lopez-Garcia et al. 2003a; Teske et al. 2002). Some studies found relatively few prokaryote sequences (Alain et al. 2004; Polz and Cavanaugh 1995; Schrenk et al. 2004), while others recovered many different sequences (Huber et al. 2002; Huber et al. 2003; Moyer et al. 1995). Often, bacterial sequences were more diverse than archaeal sequences from the same samples (Moyer et al. 1998; Reysenbach et al. 2000). Although many sequences from deep-sea 45 hydrothermal samples are similar to those from cultured organisms, many more are most closely related to sequences from unknown organisms in samples from similar environments. Few studies at deep-sea hydrothermal vents have looked at microbial community composition in the seawater surrounding vent structures. One study at the " L H O S " field in the valley of the North Fi j i Back Arc Basin examined bacterial diversity at low-temperature, diffuse-flow vents and the surrounding hydrothermal plume (Podgorsek et al. 2004). Sequence analysis of 16S r D N A detected a- and y-Proteobacteria plus sequences similar to the C F B (Cytophaga, Flavobacterium and Bacteroides) group. These results differ from studies (Huber et al. 2003; Longnecker and Reysenbach 2001; Reysenbach et al. 2000) looking at higher temperature fluids and substrates where e-Proteobacteria were commonly detected. Many studies of 16S rDNA-based diversity at deep-sea hydrothermal vents have examined individual sample sites, but have not looked at the small-scale distribution of sequences throughout a vent site. A n exception is a study of a shallow hydrothermal vent site in the Aegean Sea (Brinkhoff et al. 1999; Sievert et al. 1999). On two occasions, sediment cores collected at 4 distances from the site of venting were sampled at 4 depths, and the diversity of the bacterial communities determined by 16S r D N A fingerprinting using denaturing gradient gel electrophoresis ( D G G E ) . These fingerprints showed variability with distance and depth. Overall, the number of OTUs decreased with depth in the sediment and increased with distance from the site of venting. Subsequent sequencing of some OTUs elucidated sequences similar to members of the C F B group as well as 8- and y-Proteobacteria and Acidobacterium. Several cyanobacteria and chloroplast sequences were also detected, although the site was only 8m deep (Sievert et al. 1999; Sievert et al. 2000). The present study examines the community composition of Bacteria and Archaea and their distribution in samples collected around a single sulphide structure, from a separate vent field and from buoyant hydrothermal plumes at deep-sea hydrothermal sites on the Endeavour Segment of the Juan de Fuca Ridge. The identity of these organisms 46 and environmental factors influencing their distributions was investigated in an effort to understand the mesoscale heterogeneity of microorganism composition at deep-sea hydrothermal vents. • 3.3 Material and Methods 3.3.1 Collection of Samples Samples were collected using either the R O V , R O P O S or a rosette of Nisk in bottles equipped with a C T D and transmissometer during an August 2003 cruise on the R / V Thomas G . Thompson to the Endeavour Segment of the Juan de Fuca Ridge (Thomson et al. 2003). The rosette was used to collect a sample from east of the M a i n Endeavour Field ( M E F ) where a small plume was detected using the transmissometer, another from directly over the M E F , and a third over Easter Island, a small diffuse-flow site south of the M E F . The M E F is approximately 350 m long and 180 m wide, consists of several active and inactive sulphide structures, and is the best-studied field on the segment (Delaney et al. 1992). Samples collected with R O P O S were collected from Salut, a sulphide structure in the southern portion of the M E F that is composed of two distinct tower structures and 2-3 black smokers. M u c h of the warm flow on Salut is associated with flange formations, although diffuse flow is also common throughout. The southern tower is more active than the northern structure which is partially inactive. One sample was collected from Giraffe, a sulphide tower in the Mothra vent field (Kelley et al. 2001), which is believed to be younger than the M E F and lies 2.7 k m S W of the M E F . Giraffe is part of the larger sulphide structure Fawlty Towers. During R O P O S dives 710, 711, 712 and 714, water samples were collected using either a suction sampler, capable of collecting 2 L samples, a syringe sampler manifold equipped with 300 m L syringes, or a submersible pump (McLane Research Labs Inc., Falmouth M A ) attached to a 20 L carboy. Sampling locations were selected using real-time video. When possible, temperatures were obtained using a thermistor on the intake valve. Once on board, samples were immediately processed. 47 3.3.2 Abundance of Prokaryotic Cells and Viruses The abundance of prokaryotes and viruses was determined by epifluorescence microscopy using the Yo-Pro 1 method (Hennes and Suttle 1995). Slides were prepared from unfixed samples immediately following collection. Samples prepared in this manner yield much more accurate results than those prepared with fixed samples (Wen et al. 2004) (Chapter 2 and Appendix A . l ) . The slides were stored at -20°C until counted using an Olympus A X - 7 0 microscope with a wide-blue filter. Counts were converted into abundances using the formula of Suttle (1993). 3.3.3 Concentration of Magnesium Sub-samples for M g determination were collected in acid-washed polyethylene bottles and acidified to a final concentration of 2% HC1 with trace-metal grade HC1 (Fisher Scientific, Ottawa, ON) and stored at room temperature until analysis. M g was determined using flame-atomic absorption spectroscopy (Perkin Elmer Inc., Wellesley, M A ) (VonDamm 1983). Samples were diluted 1:3000 with M i l l i Q water (Millipore, Bil lerica, M A ) and amended with 0.1% final concentration of LaCf} according to the recommendations of the manufacturer (Perkin-Elmer Corporation 1996). Triplicate determinations of M g concentration were averaged and compared to a standard curve generated using M i l l i Q water, 0.1% L a C ^ and a pure M g standard (Delta Scientific, Mississauga, ON) (Appendix A.4). 3.3.4 DNA Extraction D N A was collected by filtering 200 to 1000 m L of a seawater sample through a 47 mm diameter, 0.22 um pore-size Durapore (Millipore, Billerica, M A ) filter. The filter was placed in 2 m L of lysis buffer (40 m M E D T A , 50 m M Tr i s -HCl , 0.75 M sucrose) and stored at -86°C until extracted using standard methods (Massana et al. 1997). Briefly, the filters were thawed, lysozyme added to a final concentration of 1 mg/mL, and the tubes placed at 37°C for 45 min. SDS (1% final concentration) and protinase K (0.2 mg/mL final concentration) (Sigma-Aldrich Co. , St. Louis, M O ) were added and the samples incubated at 55°C for 1 h. D N A was extracted twice with 25:24:1 phenol:choloform:isoamly alcohol before a final extraction with 24:1 chloroform:isoamyl 48 alcohol. The DNA was then precipitated using ice-cold 100% ethanol and 3.0 M sodium acetate overnight at -20°C. Precipitated DNA was washed with 70% ethanol, dried, and then resuspended in 1 mL of autoclaved MilliQ water and stored at -20°C. Autoclaved MilliQ water was used to dilute the extracted DNA prior to PCR amplification to standardize the amount of DNA added to the PCR reaction to the volume of the initial sample. 3.3.5 PCR Amplification PCR amplification of the 16S rDNA gene fragments was carried out using primers specific for either Bacteria or Archaea (Table 3.1). Each 50 pL PCR reaction contained 1.5 niM of MgCl 2, 160 uM of each dNTP, 0.3 uM of each primer, 0.75 U of PLATINUM Taq (Invitrogen Life Technologies, Carlsbad, CA) and lx buffer supplied with the Taq. Reactions to amplify bacterial 16S were started with initial heating to 95°C for 30s followed by 35 cycles at 95°C for 60s, 55°C for 45s and 72°C for 60s. A final step of 72°C for 9 min ended the reaction. For archaeal 16S amplification, similar conditions were employed, but with an annealing temperature of 61°C. Presence of the expected product was verified by running 8 uL of the products on a 1.5% agarose gel. For DGGE, 3 separate reactions were run with each primer set and the products stored at -20 °C until the pooled PCR products were run on a denaturing gradient gel. 3.3.6 DGGE TM DGGE gels were run on a 6% polyacrylamide gel using a D-Code system (BioRad Laboratories, Hercules, CA). PCR products were run at 90 V and 62°C for 17 h using a denaturing gradient of 25 to 60% for Bacteria and 35 to 80% for Archaea, where 100% denaturant is defined as 7 M urea and 40% deionized formamide. The gels were stained in 0.01 X SYBR Gold (Molecular Probes, Eugene, OR) for 5 h followed by 1 h of de-staining in distilled water. The gels were photographed using an Alpahlmager 3400 (Alpha Innotech Corp., San Leandro, CA). The images were inverted and brightness and contrast modified using Adobe Photoshop 5.0 LE (Adobe, San Jose, CA) to improve detection of bands. The DGGE fingerprints were analysed with Gelcompar II (Applied-Maths BVBA, Sint-Martens-Latem, BEL). 49 3.3.7DNA Sequencing Individual bands were cut from the gels using a cleaned plastic blade and stored at -20°C before being sequenced. Sterile M i l l i Q water (200 uL) was added to the cut bands and the tubes were heated for 5 min at 60°C to elute the D N A . The D N A was reamplified using the same primers and conditions as the first round of P C R , but with only 20 cycles of amplification. Presence of a product was checked by running 5 uL of the reaction on an agarose gel. Reactions showing positive amplification were cleaned using the MinElute® P C R Clean-up Ki t (Qiagen, Valencia, C A ) and stored at -20°C until sequencing. Direct sequencing was carried out by amplifying clean products using the BigDye 1 " Terminator V3.1 sequencing chemistry (Applied Biosystems, Foster City, C A ) following recommendations of the manufacturer, with the reverse 16S r D N A primer used in the initial P C R reaction (Table 3.1). Sequences were obtained from an Applied Biosystems 3730S capillary sequencer operated by the Nucleic A c i d Protein Services ( NAP S ) Unit at the University of British Columbia. 3.3.8 Community Similarity Bacterial and archaeal P C R products were run on two separate gels each. Gelcompar II was used to adjust across and between gel images by using standards run at both ends of the gels. Bands within lanes were identified using Gelcompar and then checked manually. Bands that migrated the same distance in different lanes were identified using the Band-Matching function with a 0.5% tolerance. A Dice similarity matrix was calculated and cluster analysis performed using U P G M A (unweighted pair-group method using arithmetic means). 3.3.9 Phylogenetic Analysis Sequences were checked against GenBank (September 2004) (http://www.ncbi.nlm.nih.gov) and the closest sequences identified using blastn (Altschul et al. 1997) and included in further analyses. Sequences with poor matches were checked for chimeric sequences using the Chimera-check programme (Cole et al. 2003) available from the Ribosomal Database II project (http://rdp.cme.msu.edu/html). A l l sequences 50 were aligned using ClustalX 1.83 (Thompson et al. 1997) and checked by eye. Sequences were trimmed so that analyses were confined to the 569 bp and 449 bp fragments sequenced for Bacteria and Archaea, respectively. Neighbour-Joining trees were calculated using ClustalX with bootstrap values calculated from 1000 iterations. Maximum-Likel ihood trees were generated from the Clustal-aligned sequences using quartet puzzling (Strimmer and von Haeseler 1996) in T R E E - P U Z Z L E 5.3 (Schmidt et al. 2002). Phylogentic trees were reproduced using TreeView 1.6.6 (Page 1996). 51 Table 3.1 P C R primers used to amplify 16S r D N A from samples Primer sequences used to amplify Archaeal and Bacterial 16S r D N A genes from samples. Primer Primer Sequence 5'—• 3' Target Reference G M 5 F - G C C C T A C G G G A G G C A G C A G 3 Bacteria Muyzer et al. 1995 907R C C G T C A A T T C M b T T T G A G T T T Bacteria Muyzer et al. 1995 A R C 3 4 4 F - G C A C G G G G Y c G C A G C A G G C G a Archaea Casamayor et al. 2000 A R C 9 1 5 R G T G C T C C C C C G C C A A T T C C T Archaea Casamayor et al. 2000 a G C c l a m p = C G C C C G C C G C G C C C C G C G C C C G T C C C G C C G C C C C C G C C C G b M = A or C c Y = C or T 52 3.4 Results 3.4.1 Sample Characteristics Twenty-one samples were collected from different locations around Endeavour Ridge and represent different environments based on temperature, M g concentration, animal community and location (Figure 3.1 and Table 3.2). The temperatures of the samples ranged from ambient (~1.8°C) within the plume and at the bottom of Salut to 42°C over a flange with visible flow. Due to technical problems with the thermistor on the R O V , 12 temperatures were not measured. The measured M g concentration was used to estimate the amount of mixing between pure vent fluid and seawater, assuming seawater has an average M g concentration of 53 mmol/kg and pure, subsurface vent fluid is devoid of M g (Elderfield and Schultz 1996). The lowest percentage of seawater was 74.8% while the highest was 94.9% (Table 3.2). This range in mixing between vent fluid and seawater suggests that the chemistry of the samples was distinct, providing different environments for the microorganisms. Although temperature and M g should both mix conservatively, a regression of temperature against M g for the nine samples with temperature measurements yielded an r2=0.408 (not shown). Samples were collected from the vent plume and from water associated with several different animal communities, except for Sal-14 and Sal-15, where there was no evidence of animals and the substrates were covered with microbial mats. The animal communities ranged from ones dominated by sulphide worms (Paralvinella sulfincola) to bushes of dead or dying tubeworms (Ridgeia piscesae). The sulphide worms tend to inhabit areas with higher temperatures and flow (Sarrazin et al. 1999), while senescence in tubeworms suggests that flow has been dramatically reduced and temperatures are similar to ambient seawater (Sarrazin et al. 1999). Between these two extremes were communities dominated by limpets (Lepetodrilus fucensis), palm worms (Paralvinella palmiformis) and live tubeworms. These communities are found in areas with warm temperatures and medium flow rates. Increased numbers of palm worms tend to be found at higher flow, warmer areas with tubeworms increasing in areas of lower flow and cooler water (Sarrazin et al. 1999). 53 The abundances of prokaryotes and viruses were determined for each sample. The abundance of cells ranged from 0 .13x l0 6 to 2 . 9 x l 0 6 cells mL" 1 (Table 3.2). The highest abundance of prokaryotes was in a sample collected at the top of the south tower of Salut from over a community of limpets, palm worms and tubeworms. Other samples with high prokaryote abundances were from a low flow area on the north tower of Salut and a dead tubeworm bush at the base of Salut. The lowest abundance of prokaryotes was in a sample collected very near the sample with the highest abundance. Virus abundances showed a large range from 0 .15x l0 6 viruses mL" 1 in the sample with the lowest abundance of cells, to 38 .4x l0 6 viruses mL" 1 , in a sample collected over a sulphide-worm covered flange at the top of the south tower of Salut. The abundance, of viruses was positively correlated with the abundance of prokaryotes (Spearman's Rho=0.8636, p<0.0001, n=21), while the abundance of prokaryotes was negatively correlated to temperature (Rho=-0.8167, p=0.0072, n=9). N o other correlations between prokaryotes or virus abundances and environmental parameters were significant. 3.4.2 DGGE Fingerprints and Cluster Analysis D G G E fingerprint analyses indicated that the composition of the bacterial and archaeal communities was highly variable. Bacterial 16S r D N A fingerprints analysed with Gelcompar resulted in 4 to 21 bands per sample (Figure 3.2a) with 57 unique band positions. O f these, one band was detected in every sample, while 13 bands (23%) occurred only once. Archaeal 16S r D N A fingerprints revealed 3 to 22 bands per lane (Figure 3.2b). Fifteen samples had more bacterial bands than archaeal bands. There were 52 unique band positions in the archaeal fingerprints, with no single band present in all samples and 15 bands (29%) occurring only once. Cluster analysis of the fingerprints based on the Dice similarity index resulted in two distinct patterns, suggesting that archaeal community composition is not linked to bacterial community composition. The bacterial communities formed three large clusters (1, 2 and 3) with two of these containing sub-clusters (2a, 2b, 3a and 3b) (Figure 3.3a). Analysis of archaeal fingerprints resulted in four main clusters (I, II, III and IV) with only one cluster containing sub-clusters (Ha, l i b and lie) (Figure 3.3b). 54 Only four pairs of samples clustered together in both bacterial and archaeal community analyses ( C T D - B and C T D - M , Mothra and C T D - E , Sal-07 and Sal-13, Sal-02 and Sal-12). C T D - B and C T D - M were collected from the hydrothermal plume and clustered together in bacterial cluster 2a and archaeal cluster l ie . C T D - M was collected directly over the M E F , while C T D - B was collected from a weak plume signal east of the M E F . Due to the strength of venting at the M E F relative to other fields, the plume at C T D - B was likely derived from the M E F . In both fingerprint analyses, the sample from the Mothra vent field clustered with C T D - E from the diffuse-flow field at Easter Island (bacterial cluster 3a and archaeal cluster III). Mothra and C T D - E samples differed from the others in that they were not collected from the M E F , and in cluster analyses for both, Bacteria and Archaea were most similar to samples from Salut rather than each other. Sal-07 and Sal-13, which were collected from the base of Salut from dead or senescing tubeworm bushes, also clustered together in bacterial cluster 2a and archaeal cluster l i b . The last pair of samples that clustered together in both analyses is Sal-02 and Sal-12, in bacterial cluster 3a and archaeal cluster III. Both samples were collected from the south tower of Salut over limpet-dominated communities, although Sal-02 was collected from a higher flow site at the top of the tower, while Sal-12 was collected at the bottom. Temperature data were not available for Sal-02 and Sal-12, but M g concentrations suggest they were composed of - 85% seawater. 3.4.3 Sequence Analysis Bands in the D G G E gels were excised and sequenced to determine the identity of the dominant members of the microbial communities (Figure 3.2a and 3.2b). From the bacterial D G G E , 37 bands were sequenced of which 24 were used in further analyses, representing 20 unique band positions. Sequences obtained with greater than 30 ambiguous positions were not included in further analysis. Sequenced bands represented between 33 and 86% of identified bands in each sample. From the archaeal D G G E , 23 bands were sequenced of which 22 sequences were used in further analyses. 14 unique band positions were sequenced, representing between 14 and 100% of identifiable band locations in each sample. 55 Most of the bacterial sequences in this study were identified as e- and y-Proteobacteria (Table 3.3 and Figure 3.4). Four sequences were found to be related to the C F B with relations of a-Proteobacteria, Fusobacteria, 8-Proteobacteria and Chloroflexi represented by one sequence each. Most of the closest matches for the sequences were to other unidentified environmental sequences, while a few were closely related to known organisms in GenBank. Several sequences related to the y-Proteobacteria were related to symbionts, including two sequences related to a symbiont of Ridgeia piscesae, the tubeworm found on Endeavour Segment. Three of the sequences were closely related to Pseudomonas sp. The sequenced band visible in all of the samples was found to be closely related to an unknown y-Proteobacteria symbiont of the ant, Tetraponera binghami. The sequences obtained from the archaeal D G G E included both mesophilic and thermophilic groups of Archaea (Table 3.4 and Figure 3.5). Several sequences were related to C M G 1 (3 sequences) and E M G 2 (5 sequences, both ubiquitous groups in the marine environment (Bano et al. 2004; Karner et al. 2001; Massana et al. 2000). Three sequences were closely related to other marine environmental sequences (VTDL-38, Amsterdam 1A-29, and OuI-36), which were distantly related to the E M G 2 group. Other sequences from the Archaeal D G G E were more closely related to thermophilic organisms. These include sequences related to the Thermoproteales, Archaeoglobales, Methanosarcinales and two groups of deep-sea hydrothermal vent Euryarchaeota ( D H V E ) , D H V E 2 and D H V E 5 . Bands migrating the same distance in different lanes on the D G G E were sequenced to determine the potential for co-migration of bands. Sequences of two bands from each of four locations from the bacterial D G G E were obtained. Pair wise similarity of the four sets of sequences ranged from 0.29 to 0.98 indicating that co-migration of bands potentially occurred in some instances. On the archaeal D G G E gels, at least 2 bands from 7 unique locations were sequenced. Pair wise similarity for these sequences ranged from a low of 0.74 to 1.0, with 4 pair of sequences being identical. 56 -2.5 m -4.5 m Figure 3.1 Samples from the South Tower of Salut Schematic of the south tower of Salut facing north. This figure illustrates the spatial relationships between the samples collected around this structure. The distance from the base to the top is approximately 4.5 m and the width of the top is about 2.5-3m. The drawing was made based on photos captured by R O P O S during dives to the site. The northern tower is not shown, but is approximately 3 m away from the south tower. 57 Table 3.2 Sample Characteristics Samples collected for this study with temperature, chemical and biological characteristics. The volume filtered represents the amount Sample Community Location Temp M g (mmol/kg) Volume filtered (mL) Prokaryotes (x lO 6 mL" 1) Viruses ( x l O 6 mL" 1) C T D - B C T D 1975m E of M E F Water column 1.93 50.3 (3.3) 800 0.26 1.48 C T D - M C T D 1975m over M E F Water column 1.98 46.8(1.3) 800 0.35 2.10 C T D - E C T D 1950m over Easter Island Water column 1.99 50.0(1.3) 800 0.48 2.87 Sal-1 Limpets, palm worms, tubeworms, ambient C O M P O S I T E S A M P L E Top & bottom, S Tower 2.7 47.1 (1.3) 1000 0.51 11.78 Sal-2 Limpets and palm worms Top, S Tower 5.8 45.6 (1.2) 200 0.24 1.94 Sal-3 Limpets, palm worms, tubeworms Top, S Tower n.d. 44.3 (0.9) 200 0.25 1.76 Sal-4 Sulphide worms Top, S Tower n.d. 45.0 (0.8) 900 1.19 38.40 Sal-5 Limpets, palm worms, tubeworms Top, S Tower n.d. 48.2(1.4) 900 2.90 11.61 Sal-6 Limpets and palm worms Top, S Tower n.d. 49.4 (3.8) 900 0.93 9.27 Sal-7 Dead tubeworm bush Bottom, Back S Tower 1.8 47.3 (0.5) 900 1.76 35.91 Moth Mothra Vent Field, Giraffe Limpets and tubeworms Side 7.8 39.7 (1.1) 1000 0.22 2.38 Sample Community Location Temp M g (mmol/kg) Volume filtered (mL) Prokaryotes (x lO 6 mL- 1 ) Viruses ( x l O 6 mL ' 1 ) Sal-8 Limpets and palm worms Top, S Tower 42 41.0(1.4) 1000 0.20 1.34 Sal-9 Limpets and palm worms Top, S Tower 12.5 43.8 (0.9) 1000 0.19 0.62 Sal-10 Limpets, palm worms, tubeworms Top, S Tower n.d 47.8 (1.2) 1000 1.00 2.60 Sal-11 Limpets, palm worms, tubeworms Same as Sal-10 n.d. 44.6 (1.0) 400 0.13 0.15 Sal-12 Limpets and tubeworms Bottom, S Tower n.d. 44.9(1.1) 200 0.18 0.23 Sal-13 Dead tubeworm bush Bottom, S Tower 1.8 46.0(1.2) 1000 0.24 1.28 Sal-14 Bacterial mat on sediments Bottom, S Tower n.d. 42.2 (0.9) 1000 0.94 20.50 Sal-15 Bacterial mat on flange Side, N Tower n.d. 44.9(1.0) 800 1.04 7.15 Sal-16 Sulphide worms Side, N Tower n.d. 44.1 (1.0) 1000 0.28 6.06 Sal-17 Limpets, spiders and Side, N Tower n d n d 9 0 0 2.72 4.44 scale worms .d.=no data collected due to equipment malfunction 17 18* " ••• 09; 10*25 I I 11« 02* I B | 260 , \ • f itn 06D asa 130 O0D16 1415 05a 18(3 I 010311 • lao i 3ta l : | oel 1 26a 07i: 24D Sal-08 Sal-09 Sal-17 Mothra Sal-10 Sal-11 CTD-E Sal-13 Sal-07 CTD-M Sal-16 CTD-B Sal-05 Sal-06 Sal-14 Sal-02 Sal-03 Sal-04 Sal-01 Sal-12 Sal-15 Sal-01 Sal-13 Sal-09 Sal-15 Sal-07 CTD-B CTD-M Sal-14 Sal-11 Sal-03 Sal-08 Sal-16 Sal-17 Sal-05 Mothra Sal-02 Sal-12 CTD-E Sal-04 Sal-06 Sal-10 Figure 3.2 Bacterial and Archaeal D G G E and Excised Bands Negative images of D G G E gels of A ) Bacterial and B) Archaeal 16S r D N A amplicons. Strips of sample lanes analysed by Gelcompar are presented with sequenced bands indicated. Numbers refer to the name of the sequence as presented in Table 3 and 4. 60 • S a l - 1 5 • C T D - M - Sal-16 - C T D - B - Sal-07 - Sal-1_3 - Sal-10 - Molhra - Sal-17 - Sal-08 - Sal-09 - Sal-11 - C T D - E - Sal-12 - S a l - 0 1 - Sal-04 - Sal-03 - S a l - 0 2 _ - S a l - 1 4 - Sal-06 - Sal-05 2a 2b 3a 3b B • S a l - 0 4 _ • Sal-08 - S a l - 0 3 - S a l - 1 6 - Sal-17 - Sal-07 - Sal-01 - Sal-13 - S a l - 0 9 - S a l - 1 5 - Sal-11 - Sal-14 - C T D - M - C T D - B - C T D - E - Sal-12 - Sal-02 • Sal-05 - Mothra • Sal-10 • Sal-06 ] I Figure 3.3 Cluster analysis of Bacterial and Archaeal Fingerprints U P G M A clusters of samples based on the Dice similarity index calculated from D G G E fingerprints. A ) Bacterial B) Archael. The scale bar represents 10% similarity between samples. 61 Table 3.3 Bacterial 16S Sequence Matches Closest matches for Bacterial 16S sequences from D G G E bands. The closest match from the GenBank database is presented with the % similarity along with the phylogenetic groupings. Sequences names in bold were used in phylogenetic analysis. Sequence Phylogenetic Closest Match (GenBank Accession Number) % Group Match SalB02 C F B Chryseobacterium sp. JIP 16/96 (AY468460) 98 SalB07 C F B Uncultured clone IndB4-4 (AB100009) 97 Uncultured clone M L - l a (AF208985) 97 SalB15 C F B Cytophaga sp. 1545 (AB073573) 95 SalB40 C F B Bacteriodetes sp. C319aR8CD4 (AY678514) 95 SalB41 C F B Cytophaga sp. Dex80-37 (AJ431253) 88 SalBll oc-Proteobacteria Ice-glacier clone M 3 C 1 . 8 K - T D 1 (AF479378) 100 CTDB03 y-Proteobacteria Pseudomonas sp. B W 1 1 M 1 (AY118112) 100 MothB08 100 SalB14 99 C T D B 1 2 y-Proteobacteria Uncultured clone 33-FA121-B98 (AF469289) 84 SalB26 y-Proteobacteria Unidentified y-Proteobacteria BD3-15 85 (AB015555) SaIB27 y-Proteobacteria Pseudomonas sp. Fa2 (AY131214) 95 SalB29 y-Proteobacteria Endosymbiont of Ridgeia piscesae 95 SalB32 ( A Y 129120) 100 SalB38 y-Proteobacteria Symbiont of Tetraponera sp. (AF459797) 97 CTDB33 y-Proteobacteria Bathymodiolus puteoserpentis g i l l symbiont 92 (AY235677) SalB06 e-Proteobacteria Uncultured clone 88 C H 1 _ 1 _ B ac_ 16 S r R N A _ 9 N _ E P R (AY672491) SalB09 e-Proteobacteria Uncultured clone P1-RT201 (AY580421) 96 Arcobacter sp. PCIRB-73 ( A B 113184) 96 SalBlO e-Proteobacteria Uncultured clone 4 9 M Y (AB091293) 99 SalB17 e-Proteobacteria Uncultured clone PI 4z l0e (AY580424) 87 SalB35 SalB18 e-Proteobacteria Uncultured clone 33-FL76-B00 (AF468786) 98 SalB20 e-Proteobacteria Proteobacterium Dex80-90 (AJ431224) 93 SalB21 e-Proteobacteria? Uncultured clone 239 (AY172256) 81 SalB24 e-Proteobacteria Uncultured clone CS B016 (AF420352) 86 SalB25 e-Proteobacteria Uncultured clone T6-Ph-07073 (AJ576000) 86 SalB28 e-Proteobacteria Uncultured clone PS-B3 (AY280427) 83 CTDB42 e-Proteobacteria Uncultured clone 16W ( A B 154447) 98 62 Sequence Phylogenetic Group Closest Match (GenBank Accession Number) % Match SalB30 8-Proteobacteria Uncultured clone pBSB4.35 (AB0621652) 97 SalB31 Gram + ? Mycoplasma gypis (AFT25589) 81 SalB04 Unclassified Chloroflexi Dehalococoides sp. BH180-15 (AJ431246) 98 SalB19 Unclassified Uncultured clone CH8_2_Bac_16SrRNA_9N_EPR (AY672535) 93 SalB23 Unclassified Fusobacterium sp. H A W - E B 2 1 (AY579753) 81 SalB36 Unclassified Uncultured clone boneC3D6 (AY548985) 92 SalB37 Unclassified Uncultured clone mdl09f07 (AY538096) 90 63 Clone 1-20 C/A25-JfR Sal B 04 Dehalococ aides sp. BHI80-1S Acid nicrobium term oxidans Pseudomonas strarrinea Tharmomonas brevis Caulobacter segnis Aquanicrobium deft avium Roseobecter denitiiUcans T D1 - A ntarcticg laci ar Bdetlovi trio bacteriovorus Bactericides aadofaciens Aquff exum ba/ticum Chrysecbacterium nirecoia j - Sal B02 *— ChryseobacteriumspJIPl 096 Flexibarter echinicida Cytcphaga sp.i-545 Cytcphaga mannofiava • • Unclassified C Mo roflexi a-Proteobacteria Cryonvrpha i(pava UnlndB4-4-rndOknavw SalB07 VertMUa-Milos SalB41 Cytophaga sp.Dex80-37-EPR SalB40 Bactenooeles sp.C319aR8CD4 Mycoplasma gypis FusobactariumsptfAW-EBU Clone boneC3D6 Fusobactehum equorum Clone mdl09(07 Hydrogenmonas ther mophlus Arcobactar nitrofiglis 33-FL76800-SJIR Saline LakeClone16w CTDB42 Sal B18 | — sai l" 1 — l i Arcobaclarsp.pCIRB-73 ii Mar pwzioe ^ " l . PIRT201 I Sulfurimonas autotrophica L i CSB016Guaymas ~ — 33-PAHBOO-SJfR SalB06 SalB24 SalB20 Dex80-90-EPR Sutfurovum lithotrcphicum SalBIO SaiB2S T6-Ph07-973-9NEPR pBS84.3S-Cretacsous shale AcidotlvobaciHus catdus Alteromonas atvinel/ae Escharichi a coil Methylococcus Ihermopnlus Thiobacillus prosper us Riogeia piscasae endosvmbionl SalB32 SalB29 Marinosptrillum magatarium ^dic ptfacseipentssynbort Beggiatoa alba Marinobacter excallens SalB38 Tetraponera bi nghani syntxonl Pseudorrvnas sp.Fa2 SalB27 11— Pseudomonas extremocientalis 4r SalB14 * Moth BOS Pseudomonas sp.EM/11M1 SalB03 L- CloneBD3-1S Aquitex pyt ophilus CFB Mycobacteria Fusobacteria e-Proteobacteria 5-Proteo bacteria Theimocrinis ruber V-Proteo bacteria Aquifcae Figure 3.4 Neighbour-Joining Tree of Bacterial 16S Sequences Neighbour-joining tree showing affiliation of sequences from this study with other environmental and known sequences. Bootstrap values are given as percentages where support for the branch is greater than 70%. When the branch is supported by Maximum Likelihood analysis, Quartet values are also given. 64 Table 3.4 Archaeal 16S Sequence Matches Closest matches for Archaea 16S sequences from D G G E bands. The closest match from the GenBank database is presented with the % similarity along with the phylogenetic groupings. A l l sequences were used in phylogenetic analysis. Sequences Phylogenetic Group Closest Match (GenBand Accession % Number) Match M o t h A O l a Crenarchaeota, Uncultured clone pEPR853 (AF526983) 99 Sa lAOlb Cenarchaeaceae Uncultured clone 33-P3-A00 99 (AF355828) 99 Uncultured clone 33-FL40-A00 (AF355853) C T D A 0 3 a Crenarchaeota, Vulcanisaeta distributa (AB063641) 96 Thermoproteaceae SalA06 Crenarchaeota, Uncultured clone 98 SalA07 Thermoproteaceae CH8_14a_Arc_16SrRNA_9N_EPR 97 SalA18 (AY672486) 98 SalA02a Euryarchaeota Uncultured clone A E G E A N 5 5 99 SalA02b (AF290520) 98 SalA13 Uncultured clone W H A R N (M88078) SalA25 SalA14 Euryarchaeota Uncultured clone V J D L - 3 8 (AY380683) 83 SalA15 87 SalA16 87 SalA03b Euryarchaeota Uncultured clone 33-P39-AOO 100 (AF355857) SalA04 Euryarchaeota, D H V E 5 Uncultured clone pEPR127 (AF526960) 86 S a l A l O S a l A l l Euryarchaeota, Methanosarcinacea clone M R R 1 87 Methanosarcinacea (AY125676) SalA24 Euryarchaeota, Methanomicrobiaceae clone L D S 4 2 91 Methanomicrobiaceae (AY133935) SalA05 Euryarchaeota, Uncultured clone VC2.1_Arc8 99 SalA17 Archaeoglobaceae (AF068819) C T D A 2 0 SalA08 Euryarchaeota, D H V E 2 Uncultured clone pISA12 (AB019741) 99 SalA26 65 - DCM865 33-FL24A0O-SJdF pCIHA-3-HyperSUME 33-P39A0O-SJdF Sal AO: 5-72 4^  VIDL-38 _ll Sal/125 SalA13 Sal A02a Sal A02b AEGEAN 55 WHARN SalA14 SalA15 SalA16 Amst er da rr> 1 A-29-M ed. - Oul-36 Euryarchaeota Marine Group 2 lavas • HaJcbacterium sp.A1 Methanomicrobi um mobile tanosarcina therrmphila SalA24 pIVWAI 06-1 heya Basin Conarchaeota syirbios um TS235C306 Rcrophilus oshimae PVAOTU Ar Pels PEPR853- 13N EPR 33-FUOAOO-SJdF 33-P3A00-SJdF MothAOIa 2-Pele — PVAOTU 3-Pele ~ — MethanosarcinafesdondMBQl — SalAII 1 pEPR127-13N EPR HflJBil SalA04 1 SalA10 = pMC2A24-Myojin Knoil Thermoplasma acidophilum i_aa r-89/8 kf FT17A03-CIR SalA08 Sal A26 p£PR707-13N EPR pMC2A10-Myojin Knoll p!SA 12-1 heya Basin pPACMA-M-PACMANUS Metha noc occus j an nasc hit • Thermococcus barossii Unknown Euryarchaeota Methanomicrobi ales Crenarchaeota Marine Group 1 Metnanosarci rales DHVE5 Therm op lasmales DHVE2 lim/83J[ Archae oglcbus lithotro phicus VC2.1 ATC8-MAR SalA17 SalA05 Sal A20 pEPR870-13N EPR • CH84-9NEPR pEPR617-13N EPR Ther moproteus neutrophil us Archaeoglobales " 9 CH814a-9NEPR Sal A07 SalA18 CTD A03a SalA06 Thermodadium modestius Caldivirga maquilingensis Vutcanisaeta distnbuta Ac id an us in fern us Sutfolobusthuringi gnsis Caldsphaera lagunensis HOOf-Igniococcus pacificus Pyroiobus fumarius Staphylothermus marinus Korarchaeota pBA5 1011 Korarchaeota SRI-306 I— Korarchaeota pJP78 Thermophilic Crenarchaeota Korarchaeota Figure 3.5 Neighbour-Joining Tree of Archaeal 16S Sequences Neighbour-Joining tree showing phylogenetic affinity of sequences. Bootstrap values are given as percentages, showing support greater than 70%. Where Maximum Likelihood analysis also supports branching, Quartet values are given. 66 3.5 Discussion This study demonstrates that the microbial communities in waters surrounding active venting structures are extremely heterogeneous. Frequently, there was more similarity between samples collected from disparate vent sites or overlying plumes than between samples collected within metres of each other. The environmental heterogeneity is also reflected in high variability in the contribution of vent fluid to the samples as indicated by M g concentration. Abundances of viruses and prokaryotes were also highly variable, with 10-fold variations between samples collected from the same location within minutes of each other (eg. Sal-10 and Sal-11). The average abundances of prokaryotes and viruses in these samples were 0.76X10 6 mL" 1 (s.d. 0 .81x l0 6 , n=21) and 7 . 8 x l 0 6 mL" 1 (s.d. 1 2 x l 0 6 , n=21), respectively. Abundances of prokaryotes and viruses from the surrounding seawater, with no influence of hydrothermal venting, show much less variability, with average abundances of 0 .27x l0 6 mL" 1 (s.d. 0 .05xl0 6 , n=15) and 2.94X10 6 mL" 1 (s.d. 1.08xl0 6 , n=15), respectively (Chapter 2). The environmental variability is reflected in the microbial communities, as well . Cluster analyses of bacterial and archaeal fingerprints show few patterns; nonetheless, comparative analyses of archaeal and bacterial fingerprints and sequences suggest that the communities may be controlled by different factors around the hydrothermal vents. The archaeal sequences comprise two main groups, the widespread marine groups represented by C M G 1 and E M G 2 as well as the unknown environmental samples, and the thermophilic groups represented by Thermoproteales, Archaeoglobales and Methanosarcinales. Although little is known about the organisms whose sequences compose C M G 1 and E M G 2 , the cosmopolitan nature of the sequences suggests the organisms are mesophilic and likely heterotrophic. The sequences associated with thermophiles are likely derived from organisms l iving within the chimneys, in the subsurface environment of diffuse-flow vents, or on surfaces bathed by vent fluid. D H V E sequences have been detected in many marine hydrothermal environments (Reysenbach et al. 2000; Takai and Horikoshi 1999; Takai et al. 2001). N o members of these groups have yet been cultured, so nothing is known 67 about their metabolism or physiological characteristics; however, their association with hydrothermal activity suggests they are thermophilic. Sequence similarity between members of the D H V E groups and known thermophiles also supports this suggestion. In this study, sequences closely related to members of D H V E 5 were found to share similarity with the Methanosarcinales, while sequences similar to D H V E 2 shared similarity with species of the genus Picrophilus. Based on the known characteristics of these groups, it is possible to hypothesize that the D H V E 5 are composed of anaerobic methanogens that may be either meso- or thermophilic (Balch et al. 1979). The D H V E 2 may share characteristics of Picrophilus, which are known to be hyderacidophilic thermophiles that are aerobic heterotrophs (Schleper et al. 1995). Both of these groups have characteristics that would support their growth in hydrothermal environments. In Bacteria, large differences among related taxa prevent speculation on their metabolic capabilities based on 16S r D N A sequences. In contrast, archaeal groups tend to share environmental and metabolic requirements. For example, y-Proteobacteria include the common intestinal microbe E. coli, which grows at 37°C, as well as Vibrio diabolicus, an organism isolated from the hydrothermal vent worm Alvinella pompejana (Raguenes et al. 1997). However, evidence suggests that some of the Bacteria detected in this study were associated with the hydrothermal activity. Several of the y-Proteobacteria were related to symbiotic species, with two sequences, SalB29 and SalB32, related to a symbiont of Ridgeia piscesae, the tubeworm commonly found at the Juan de Fuca vents (Southward et al. 1995). It is possible that SalB38 and C T D B 3 3 also represent symbionts of vent invertebrates. e-Proteobacteria have been detected often near hydrothermal vents (Moyer et al. 1995), and recent cultivation of e-Proteobacteria associated with a hydrothermal vent were meso- or thermophilic chemolithoautotrophs (Takai et al. 2003). Sequences from the current study were closely related to those from three genera of e-Proteobacteria. Two of these genera, Sulfurovum and Sulfurimonas (Inagaki et al. 2003; Inagaki et al. 2004), have been isolated near hydrothermal vents and are mesophilic sulphur-oxidizers. 68 The D G G E fingerprints represent a minimum estimate of the total microbial community diversity. Because of potential biases in P C R and limits in detecting bands on the gel, not all 16S r D N A sequences present in the original sample may be represented on the D G G E . Studies have estimated that a population that is < 1% of the total community abundance is not detectable using D G G E (Muyzer and Smalla 1998). For the bacterial fingerprints, sequencing also demonstrated that bands migrating to the same distance in the gel were not always similar. This may be due to inaccuracies in identifying matching bands using Gelcompar II, or co-migration of different sequences. Sequences of bands from the same location on the archaeal D G G E were more similar, suggesting that less co-migration occurred, possibly due to the lower number of bands detected in most samples using Archaea-specific primers (Figure 3.2a and 3.2b). The heterogeneity of the bacterial and archaeal communities suggests that the microbial component of hydrothermal-vent ecosystems may be more complex than previously suggested. To date, environmental and biological data related to small spatial scales in these environments is extremely limited so the causes of variability in the abundance and diversity of the microorganisms within the water surrounding hydrothermal vents are difficult to measure and understand. One possibility is that the physical structure of sulphide edifices, combined with variability in flow rates of vent fluid, subsurface mixing and overlying animal communities, creates microhabitats, the longevity of which affects the ability of introduced microorganisms to survive and proliferate. Consequently, the dominant species differ among microhabitats depending on the temperature and chemical conditions, which is reflected in the community fingerprints that are generated. Because the fingerprints were generated with amplified D N A , it is not possible to determine the relative abundance of the different taxa, or which were actively growing. As a result of the potential for microbes to affect the growth of the animal communities through symbiotic associations (Alain et al. 2002; Campbell et al. 2003) and also to affect the growth of the sulphide structures and mineralization processes (Taylor and Wirsen 199.7), variability in the microbial communities could affect the development 69 of both the physical and biological structure of a hydrothermal vent site. Microhabitats formed by the interactions between fluid flow and turbulent mixing around hydrothermal vent structures result in highly variable microbial communities, with unknown physiological capabilities. This study is an important first step in identifying the complexity of microbial communities that exist around a single sulphide structure in one hydrothermal vent system. 70 CHAPTER 4: The 18S rDNA Diversity in the Water Column at a Hydrothermal Vent is dominated by Sequences from Benthic Invertebrates 4.1 Summary The high proportion of previously unknown animal species that have been discovered at deep-sea hydrothermal vents suggested that the surrounding water might also harbour unknown microeukaryotic taxa. Diffuse flow samples collected at an active sulphide structure, Salut, in the Ma in Endeavour hydrothermal vent field were investigated to determine the diversity and identity of 18S r D N A molecules. 18S r D N A was amplified from 0.22 um filters in 11 of 17 samples. Using D G G E , genetic fingerprints were generated and cluster analysis was used to determine similarities among samples. Clusters appeared to reflect the animal community from which samples were collected. The importance of the animal communities was further supported through sequencing of D G G E bands. The sequences were found to be most similar to known animal species in these communities, with only one occurrence of a ciliate sequence and four sequences likely belonging to a copepod. The dominance of benthic invertebrate 18S r D N A in the water column and paucity of protist-derived sequences suggest that protists may be in very low abundance in the water column around actively venting sulphide structures and grazing may not be a large source of mortality for free-living prokaryotes. 72 4.2 Introduction Deep-sea hydrothermal vents have been intensely studied since their discovery in 1976 (Corliss et al. 1979; Lonsdale 1977). One characteristic of these sites is the presence of lush animal communities that grow around areas of active venting. The diversity of the macroscopic organisms that compose these communities has been well documented, with many previously unknown species recorded (Grassle 1985; Shank et al. 1998; Tunnicliffe 1988; Tunnicliffe 1991). Symbiotic relationships with prokaryotes are believed to provide sustenance for their invertebrate hosts. A t these vent sites, chemically altered seawater is released that provides the substrates for the prokaryotic primary producers. Documenting the species present at hydrothermal vents is leading to a better understanding of the ecology of these systems. In particular, the isolation of bacteria and analysis of environmentally derived 16S r D N A sequences has begun to expose the diversity of prokaryotes at these vent sites (Moyer et al. 1995; Moyer et al. 1998; Schrenk et al. 2004; Schrenk et al. 2003; Takai and Horikoshi 1999; Takai et al. 2003; Takai and Sako 1999 and Chapter 3). In contrast, few studies have examined the free-living protists. Since the discovery of deep-sea hydrothermal vents, only four studies have specifically investigated the protist communities. One study, during the early stages of vent research at 21° N on the East Pacific Rise (EPR), used light microscopy to examine preserved samples collected from sampling boxes, rocks and artificial substrates (Small and Gross 1985). From these samples, an amoeba, a colonial chrysophyte and ciliates from six different classes were identified. Most contained prokaryotic cells, suggesting that these protists were grazers. A second study (Atkins et al. 2000) isolated heterotrophic nanoflagellates from the Ma in Endeavour Field (Juan de Fuca Ridge), Guaymas Basin and 21° and 9° N on the E P R . The flagellates were identified using light or electron microscopy and by sequencing of the 18S r D N A gene. From the 18 strains isolated, 9 species were identified; most were common species that have also been found in marine, freshwater and terrestrial ecosystems (Atkins et al. 2000). These groups are generally characterized by being 73 tolerant of a wide range of environmental conditions. A l l of these isolates are likely grazers, forming an important link between the prokaryotes at the vent sites and the macrofauna. The other two studies used sequence analysis to determine the diversity of eukaryotes in sediments collected from the Guaymas Basin (Edgcomb et al. 2002) and the Rainbow sites on the M A R (Lopez-Garcia et al. 2003b). Artificial surfaces exposed to vent fluids were also analysed from the Lucky Strike sites on the M A R . Both studies sequenced 18S r D N A fragments from clone libraries and revealed a wide diversity of unknown eukaryotic sequences. Many of the sequences were closely related to protist groups that are parasitic, suggesting that mass mortality of some vent fauna may be related to infections and not changing environmental conditions (Moreira and Lopez-Garcia 2003). The majority of the clones obtained in theses studies were identified as alveolates, suggesting they may dominate within hydrothermal vent sediments. Previous studies have not reported on the diversity of free-living eukaryotes in the water surrounding actively venting structures. The study on the M A R examined two samples collected at the interface between the vent fluid and the seawater (Lopez-Garcia et al. 2003b). These samples were limited by low sample volume and biomass, but ciliate, fungi, polychaete and copepod sequences were detected. The present study used D G G E analysis of 18S r D N A to determine i f the composition of the eukaryote community within water samples collected around a single hydrothermal-vent sulphide structure was related to the environmental and biological characteristics of the sample site. Extensive sequencing of 18S r D N A was carried out in an attempt to determine the origin of the eukaryotic D N A in the water surrounding a hydrothermal vent structure. 74 4.3 Materials and Methods 4.31 Sample Collection Samples were collected using the R O V , R O P O S during an August 2003 cruise on the R / V Thomas G . Thompson to the Endeavour Segment of the Juan de Fuca Ridge. Samples were collected from a sulphide structure, Salut, in the southern portion of the M E F (Delaney et al. 1992). Samples were collected during dives 710, 712 and 714 following the same protocols as described in Chapter 3. 4.3.2 Chemical Analysis Sub-samples were analyzed to determine the M g concentration. Because pure hydrothermal vent fluid contains no M g , the concentration of M g can be used as a proxy to measure the amount of mixing between vent fluid and seawater which has a concentration of 53 mmol/kg (Elderfield and Schultz 1996). Sub-samples for M g determination were collected in acid-washed polyethylene bottles and acidified to a final concentration of 2% HC1 (v/v) using trace-metal grade HC1 and stored at room temperature until analysis. M g was determined using F lameAA, following the methods of V o n Damm(1983). 4.3.3 DNA Extraction and Amplification D N A was extracted from 47 mm diameter, 0.22 um pore-size Durapore membrane filters through which 200 to 1000 m L of a seawater sample had been filtered. Following the methods of Massana et al. (1997), the filter was placed in 2 m L of lysis buffer (40 m M E D T A , 5 0 m M Tr i s -HCl , 0.75 M sucrose) and stored at -86 °C. For extraction, the filters were thawed, lysozyme added (1 mg/mL final concentration), and the tubes placed at 37°C for 45 min. SDS (1% final concentration) and protinase K (0.2 mg/mL final concentration) were added and the samples incubated at 55°C for 1 h. D N A was extracted twice using phenol:chloroform:isoamyl alcohol (25:24:1) followed by chloroform:isoamyl alcohol (24:1). The D N A was then precipitated overnight using ice-cold 100% ethanol and 3.0 M sodium acetate at -20°C. Precipitated D N A was washed 75 with 70% ethanol, dried, and resuspended in 1 m L of autoclaved M i l l i Q water and stored at -20°C. For P C R amplification, autoclaved M i l l i Q water was used to dilute the extracted D N A based on the original volume of sample filtered. This dilution standardized all samples, compensating for differences in sample volume and allowing comparisons between samples. P C R amplification of the 18S r D N A gene was carried out using the primers E u k l A and Euk519r-GC with a G C clamp (Diez et al. 2001a) (Table 4.1). Briefly, 5 pX of template were added to each of 3 independent 50 u L reactions. Each reaction contained 1.5 m M of M g C l 2 , 160uM of each dNTP, 0.3 p M of each primer, 0.75 U of Plat inum® Taq and the supplied buffer. The reaction conditions were 90s at 95°C followed by 35 cycles at 95°C for 60s, 56°C for 60s and 72°C for 60s, which was followed by 7 min at 72°C. Presence of the correct size product was verified by running 8 u L from each reaction on a 1.5% agarose gel. Products from replicate reactions were pooled and stored at -20 °C until analysis by D G G E . 4.3.4 DGGE and Cluster Analysis D G G E was run using the protocols of Short and Suttle (2003). A gradient of denaturants was used from 25-47.5% on a 6% polyacrylamide gel. The gel was run for 15 hours at 59°C at 100V. Thirty uL of P C R products in buffer were loaded into each lane. The gel was subsequently stained in 1% S Y B R Gold for 5 h followed by 1 h of destaining in distilled water. The gel was illuminated using a U V transilluminator and photographed using a Nikon Coolpix 950 digital camera. Brightness and contrast of the negative image were modified using Adobe Photoshop 5.0 L E . Gelcompar II was used to select the bands on the D G G E fingerprints, and edited to exclude obvious cases of misidentification. A Dice similarity index (Dice 1945) was calculated from pair-wise comparisons and cluster analysis was performed using U P G M A . Environmental characteristics were assigned to the clusters to determine what factors were associated with eukaryotic richness. 76 4.3.5 DNA Sequencing and Phylogenetic Analysis Bands were cut from the gels and stored at -20°C until sequencing. D N A was eluted by adding 200 uL of sterile M i l l i Q water to each band and heating for 5 min at 60°C. The D N A was reamplified using the same primers and conditions described above, but without the GC-clamp, and with only 20 cycles of amplification. Presence of a product was checked by running 5 uL of the reaction on an agarose gel. Reactions showing positive amplification were then cleaned using the QiaQuick P C R Clean-up K i t (Qiagen, Valencia, C A ) and stored at -20°C until sequencing. Direct sequencing was carried out using the BigDye™ Terminator V3.1 sequencing chemistry following recommendations of the manufacturer using the reverse primer without the G C clamp (Table 4.1). The Nucleic A c i d Protein Services (NAPS) Unit at the University of British Columbia completed the sequencing using an Applied Biosystems 3730S capillary sequencer. The sequences obtained were compared to those in GenBank (http://www.ncbi.nlm.nih.gov) using blastn (Altschul et al. 1997) and the most similar matches were downloaded. Sequences were aligned using ClustalX 1.83 (Thompson et al. 1997) and checked by eye. Sequences were trimmed to .539 nt so that analysis was confined to the section sequenced in this study. Maximum-Likel ihood trees were generated from the aligned sequences using quartet puzzling (Strimmer and von Haeseler 1996) in T R E E - P U Z Z L E 5.3 (Schmidt et al. 2002), while Neighbour-Joining trees were calculated in ClustalX 1.83. Phylogentic trees were reproduced using Tree View 1.6.6 (Page 1996). 77 Table 4.1 Eukaryote 18S Primers P C R primers used to amplify 18S r D N A from samples. Primer Primer Sequence 5'—» 3' E u k l A C T G G T T G A T C C T G C C A G Euk516R a A C C A G A C T T G C C C T C a For D G G E , G C clamp was added to the 5' end of the primer G C c l a m p = C G C C C G G G G C G C G C C C C G G G C G G G G C G G G G G C A C G G G G G G 4.4 Results and Discussion 18S r D N A sequences could be amplified from only 11 of 17 samples (Table 4.2), whereas 16S r D N A could be amplified from all 17 samples (Chapter 3). The lack of amplification of the 18S r D N A sequences was because of low target concentration, and not because of enzyme inhibition, although increasing the amount of template did not result in amplification from the 6 other samples. Equal volumes of the 18S r D N A P C R products from the 11 samples were examined using D G G E . Each sample contained from 3 to 19 bands (OTUs) (Figure 4.1a), with the fewest bands in Sal-15 and Sal-16, which were from areas with little animal colonization relative to the locations from which the other 9 samples were collected. The highest number of bands occurred in a sample collected near a colony of dead tubeworms (Sal-7). There was no band in common among all 11 samples; however, one band was detected in 9 samples, but absent in Sal-15 and Sal-16. Other bands were detected in 8 and 7 samples, respectively, while 15 bands were only detected once. Cluster analysis of the fingerprints resulted in groupings, which appeared to be based mainly on the animal communities from which the samples were collected (Figure 4.1b). For example, Sal-7 and Sal-13 clustered together (a) and were collected near bushes of dead tubeworms, suggesting these samples may have derived from a detritus-based community. Another main cluster (b) was composed of samples collected from the top of the south structure of Salut, except for Sal-9, which formed a separate cluster with Sal-15 (c). Sal-15 was collected over a bacterial mat on a flange structure with very little visible animal life. The warmest sample (Sal-8) in the main cluster grouped with samples collected from the sulphide chimney (Sal-16) and from over a flange with sulphide worms (Paralvinella sulfincola) (Sal-4) Qo2). These three samples had higher amounts of vent fluid compared to the other samples, with the exception of Sal-9. Although temperature data are not available for Sal-4 nor Sal-16, it is likely they were very warm as little animal life was detected except for sulphide worms. The other four samples (Sal-05, Sal-06, Sal-10, Sal-17) in the main cluster (bi) were collected over animal communities dominated by limpets (Lepetodrilus fucensis), tubeworms (Ridgeia 79 piscesae) and palm worms (Paralvinella palmiformis). These four samples had the lowest vent component, with the amount of seawater as estimated from M g concentration ranging from 90 to 100% (Table 4.2). Selected bands were excised from the D G G E gel and sequenced to determine the dominant eukaryotes (Table 4.3, Figure 4.2). Most bands that migrated the same distance on the gel were the same sequence (Figure 4.1a, Table 4.3); however some bands that migrated to different points on the gel were 98 to 100% similar (SalK08b and SalK56 compared to SalK47 or SalK48). This is not surprising as sequences that differ by a single base pair can denature under different conditions (Muyzer and Smalla 1998). Most of the intense bands were derived from limpets, tubeworms, and palm worms that dominate these communities (Table 4.3), and most sequences were similar to those from animals found at the Endeavour vent sites. Relatively few sequences belonged to protists or unknown organisms (Table 4.3). Many sequences were from polychaetes. The most obvious polychaetes on Salut were palm worms (Paralvinella palmiformis) and sulphide worms (Paralvinella sulfincola). Bands corresponding to P. palmiformis were identified in 8 of the samples, with sequences obtained from 7 different bands (Figure 4.2). Sal-9 had two bands (SalK20 and SalK21) that were most closely related to P. palmiformis. A second set of sequences (SalK02, S a l K l O , S a l K l l , SalK18 and SalK72) was found to be closely related to both P. palmiformis and P. grasslei, a related species identified from the Galapagos Rift (Figure 4.2). These are the only two Paralvinella sequences available in GenBank; however, this second set of sequences may represent P. sulfincola. This is supported by the occurrence of these sequences in Sal-4 and Sal-16, two samples collected where the only visible animals were P. sulfincola. Another sequence, SalK27, clusters separately from the two groups of Paralvinella sequences and may belong to one of the other two species of Paralvinella found at Endeavour Ridge vents, P. dela or P. pandorae (McHugh 1989; Tunnicliffe et al. 1993). Two other sequences (SalK42 and SalK51) that were only detected in Sal-7 and Sal-13, and which were collected around dead tubeworm colonies, were also likely from polychaetes. One sequence (SalK51) was 80 closely related to Clymenura clypeata, a deposit-feeding polychaete found in the Atlantic. The second (SalK42) was most similar to Sphaerosyllis hystrix, a benthic polychaete commonly reported from the Atlantic, although a novel species in this genus has been reported from the Juan de Fuca vent sites (Tunnicliffe 1988). Both of these sequences may represent organisms feeding on the detritus associated with senescent tubeworm bushes. The sequences SalK06 and SalK25 were 94 and 100% similar to Ridgeia piscesae, the dominant Vestimentifera (Pogonophora) species at the Endeavour vent sites (Southward et al. 1995). The bands from which these sequences were obtained had migrated to about the same distance into the gel, suggesting that other bands in samples Sal-07, Sal-13, Sal-10 and Sal-17 that were not sequenced, but which migrated the same distance were also related to R. piscesae. Four sequences (SalK04, SalK15, SalK24 and SalK60) were 99 or 100% similar to a sequence in GenBank for the limpet, Lepetodrilus elevatus, which has been reported from the EPR(McLean 1993), but not from northeast Pacific vent sites. A related species reported to occur at Endeavour Ridge vent sites (McLean 1993), L.fucensis, has two sequences in GenBank, but these sequences were only 98% similar to those from this study. A comparison of longer 18S sequences (1185 nt) for both of these species found them to be 98% similar. Based on morphological observations, the limpets found at Endeavour Ridge are L.fucensis (McLean 1993); however, based on 18S r D N A sequence analysis, they were indistinguishable from L. elevatus (Figure 4.2). Some of the D G G E bands appear to represent protists. A sequence obtained from Sal-9 was related to that of a ciliate, Pseudoplatyophyra nana. This ciliate has a small feeding tube with which it can puncture fungi and yeast (Aescht et al. 1991). A band in the same location was detected in fingerprints of Sal-4, Sal-7, Sal-8 and Sal-17, suggesting these samples may also have this ciliate present. Although most of the species related to P. nana are found in freshwater or soil, there are a few marine species. One specimen belonging to the class Colpodea was reported in samples collected from 21°N 81 on the E P R , however the condition of this specimen limited identification and description (Small and Gross 1985). A set of sequences was most closely related to unknown environmental clones obtained from water samples from the Bay of Fundy and the Sargasso Sea. The closest sequences in the database that belong to known organisms are from three different families of copepods. The matches include a cosmopolitan freshwater species (Eucyclops serrulatus), the sea lice infecting salmon (Lepeophtheirus salmonis) and a copepod found in both benthic and pelagic environments (Tisbefurcatd). The grouping of the unknown environmental clones and the sequences from this study with these three copepod species suggests that these may represent copepods. The sequences were obtained from Sal-7, Sal-13 and Sal-17. In one sample, Sal-13, copepods were visible in the water sample, supporting the contention that these sequences were derived from copepods. The 18S r D N A gene sequences obtained in this study were dominated by sequences from benthic animals present where the samples were collected. Previous studies (Edgcomb et al. 2002; Lopez-Garcia et al. 2003b), which examined sediments and vent fluids were dominated by sequences from micro- and pico-eukaryotes, so my results are surprising. Possibly, the high biomass of animals resulted in high numbers of sloughed cells in the water column. If these cells were in much higher abundance than protist cells, P C R would have favoured amplification of D N A from the animal cells. L o w abundances of protists may have resulted from high concentrations of hydrothermal chemicals. Unlike the animals, the protists are unlikely to have episymbiotic bacteria that have been hypothesised (Alayse-Danet et al. 1987) to detoxify compounds. Because of the fragility of protists cells they may have been lost during processing . During sampling, subsequent decompression, and filtration protists may have lysed, releasing D N A into solution that was not recovered with high efficiency. However, previous studies in which high numbers of protists were detected (Lopez-Garcia et al. 2001, Lopez-Garcia et al. 2003, Moon-Van Der Staay et al. 2001), also used similar filtration methods to collected D N A for analysis, suggesting loss of D N A in this study may be limited. 82 Most of the invertebrates living at the hydrothermal vent sites reproduce by releasing gametes into the water column (Van Dover 2000). The sequences detected in this study may be due to the presence of gametes. Plankton samples collected around the Ma in Endeavour Field in previous years, suggest that larval stages of the invertebrates may have been present in the water around venting structures (Metaxas 2004). Larvae were not observed in the samples collected for this study, but could have been present at low abundances. Most of the observed sequences were similar to, or the same as, others that have been reported from hydrothermal vent systems. This suggests that most of the eukaryotes around these vents belong to recognized groups of organisms. Larger sample sizes to compensate for low abundances, and sequencing of more identified bands would have increased the probability of detecting more protist sequences. Use of specific primers may have increased the likelihood of detecting protist sequences, however that would have decreased my ability to identify most of the eukaryotic community. The dominance in the water column of 18S r D N A sequences from benthic invertebrates found in the surrounding active communities has several possible implications. One possible cause for the high levels of D N A from benthic invertebrates could be from the release of gametes or the presence of larvae in the water column. Plankton tows conducted in previous years, at the same time of the year, along the Endeavour Segment detected several species of larvae including those represented by 18S r D N A in this study (Metaxas 2004). If the lack of protist sequences is due to low or negligible levels of protists in the water column, then grazing by free-living prokaryotes is not likely to affect prokaryote 7 1 abundances. This suggests that viruses, with abundances as high as 10 viruses mL" (Chapter 2), are l ikely the most important source of mortality for free-living prokaryotes around deep-sea hydrothermal vent sites. 83 Table 4.2 Samples collected for this study The community lists the dominant organism present from the area sampled based on observations during sampling as well as viewing dive logs. The temperature was determined for some samples, but equipment difficulties meant some values were not obtained. M g was determined from acidified samples using F lameAA. Sample Location Community Temp M g (mmol/kg) 18S Detected Sal-1 S Tower Limpets, palm worms, tubeworms, ambient C O M P O S I T E S A M P L E 2.7 47.1 (1.3) No Sal-2 S Tower, Top Limpets and palm worms 5.8 45.6 (1.2) N o Sal-3 S Tower, Top Limpets, palm worms, tubeworms n.d. 44.3 (0.9) N o Sal-4 S Tower, Top Sulphide worms n.d. 45.0 (0.8) Yes Sal-5 S Tower, Top Limpets, palm worms, tubeworms n.d. 48.2(1.4) Yes Sal-6 S Tower, Top Limpets and palm worms n.d. 49.4 (3.8) Yes Sal-7 S Tower, Base Dead tubeworm bush 1.8 47.3 (0.5) Yes Sal-8 S Tower, Top Limpets and palm worms 42 41.0(1.4) Yes Sal-9 S Tower, Top Limpets and palm worms 12.5 43.8 (1.0) Yes Sal-10 S Tower, Top Limpets, palm worms, tubeworms n.d 47.8 (1.2) Yes Sal-11 S Tower, Top Limpets, palm worms, tubeworms n.d. 44.6(1.0) N o Sal-12 S Tower, Base Limpets and tubeworms n.d. 44.9(1.1) N o Sal-13 S Tower, Base Dead tubeworm bush 1.8 46.0(1.2) Yes Sal-14 S Tower, Base Bacterial mat on sediments n.d. 42.2 (0.9) N o Sal-15 N Tower, Side Bacterial mat on flange n.d. 44.9(1.0) Yes Sal-16 N Tower, Side Sulphide worms n.d. 44.1 (1.0) Yes Sal-17 N Tower, Side Limpets, spiders and scale worms n.d. n.d. Yes Figure 4.1 D G G E and cluster analysis of 18S r D N A fingerprints A ) Negative image of D G G E gel for 11 samples positive for 18S r D N A amplification. Bands marked with numbers were excised and sequenced. B) U P G M A cluster analysis based on a Dice similarity matrix. The matrix was calculated based on the presence and absence of bands at the same location in the gel. Clusters a, b (bi and b 2), and c reflect the communities from which samples were collected. a=dead tubeworm bushes, b p limpet and tubeworm communities, b2=sulfide worm communities, c=flange and limpets with palm worms. 85 Table 4.3 Eukaryote 18S Sequence Matches Closest matches for Eukaryote 18S sequences from D G G E bands. The closest match from the GenBank database is presented with the % similarity along with the phylogenetic groupings. Phylogenetic Group Closest Match (GenBank Sequence Sample % Accession Number) Match Annelida, Paralvinella palmiformis Sa lKOl Sal-8 100 Alvinellidae (AF168747) SalK02 Sal-8 94 SalK07 Sal-5 100 S a l K l O Sal-16 96 S a l K l l . Sal-16 96 SalK16 Sal-4 100 SalK18 Sal-4 96 SalK20 Sal-9 100 SalK21 Sal-9 98 SalK27 Sal-6 93 SalK63 Sal-10 100 SalK70 Sal-17 100 Annelida, Paravinella grasslei (AY577886) SalK72 Sal-17 95 Alvinellidae Annelida, Syllidae Sphaerosyllis hystrix (AF474288) SalK42 Sal-7 93 Annelida, Clymenura clypeata (AF448152) SalK51 Sal-13 96 Maldanidae Annelida Uncultured polychaete AT7-8 SalK08 Sal-15 95 (AF530547) SalK39 Sal-7 95 SalK50 Sal-13 95 SalK59 Sal-10 93 SalK67 Sal-17 92 Pogonophora, Ridgeia piscesae (X79877) SalK06 Sal-5 94 Vestimentifera SalK25 Sal-6 100 Mollusca, Leptodrilus elevatus (AY145381) SalK04 Sal-5 100 Gastropoda SalK15 Sal-4 100 SalK24 Sal-6 99 SalK60 Sal-10 100 Alveolata, Pseudoplatyophrya nana SalK19 Sal-9 95 Ciliophora (AF060452) Unknown clone Uncultured clone SM27C52 SalK08b Sal-15 96 (AY665125) SalK47 Sal-7 94 SalK48 Sal-7 96 SalK56 Sal-13 96 86 Lemoniera aquatica — Choanoeca perplexa Cyclospora papionis 99/100 I — ' 99/75 Cafeteria roenbergensis 100/99,— SalK19 i — Pseudoplatyophyra nana Porodon viridis Uncultured clone IN2411 - Uncultured cloneATI -2 Lepeophtherirus salmonis Eucyclops serrulatus r- SalK47 SalK08b SalK56 SalK48 - Uncultured clone s721 - Uncultured clone SCM27C52 SalKIO SalK72 SalK18 SalK02 - Paralvinella grasslei i — SalK27 SalK07 SalK16 SalK63 SalKOI SalK20 SalK70 Paravlvinella palmiformis SalK21 Helicoradomenia sp. YJP-2002 — Anobothrus gracilis — Uncultured clone AT6-4 Uncultured clone AT7-8 SalK08 SalK39 SalK50 SalK59 SalK67 Acathochitona crinita Ancistrosyllis sp.AAN-2 SalK06 SalK04 SalK15 SalK60 Lepetodrilus elevatus Lepetodrilus fucensis SalK24 Lepetodrilus schrolli Littorina littorea 99-ioor—— SalK42 Sphaerosyllis hystrix Paraspadella gotoi Scutopus ventrolineatus oj— Clymenura clypeata "L- SalK51 [ Lamellibrachia barhami Oasisia alvinae SalK25 Ridgeia piscesae Nereis pelagica Atrina pectinata - Chlamys islandic 0.1 Figure 4.2 Max imum Likelihood tree of eukaryotic 18S r D N A sequences Maximum likelihood tree of sequences obtained in this study as well as sequences obtained from GenBank. Sequences determined in this study are identified by their sequence number (SalKxx). Quartet puzzling values are given for branches with greater than 70% support. Where two values are presented, Neighbour-Joining analysis supports the branch and bootstrap values are also shown. 87 CHAPTER 5 : Conclusions 5.1 Conclusions The research presented in this thesis was conducted to identify the main source of mortality for free-living prokaryotes within deep-sea hydrothermal environments. The fate of prokaryotic production is especially important at these sites, as prokaryotes are responsible for the primary production. Vi ra l lysis of prokaryotes would likely result in an increase in secondary production, due to conversion of cells into dissolved organic material. This could also result in a decrease in the amount of energy transferred to higher trophic levels. Grazing on prokaryotes by protists would have the opposite results. Energy from the prokaryotes would be taken up by the protists, which would be consumed by larger zooplankton or filter-feeding invertebrates. In order to better understand the source of mortality for prokaryotes, research was undertaken to investigate the potential for viral infection and protist grazing within a hydrothermal vent site. The initial aim of this research was to characterize the abundance and distribution of viruses within a hydrothermal vent environment, from the site of venting through a neutrally buoyant plume. The abundance of viruses was found to be higher within samples influenced by hydrothermal vents compared to background water samples, with the highest abundances found at sites of active venting. The highest variability was also found within active venting sites. Virus abundances were found to be higher within the neutrally buoyant plume when compared to ambient seawater samples. The increase in abundance of viruses above the background levels strongly suggests that viruses are produced within hydrothermal systems. The abundances of prokaryotes and viruses reported through this research are higher than most other reports for the deep-sea (Chapter 2). It is l ikely that methods utilizing aldehyde-fixation have resulted in an underestimation of abundances for both prokaryotes and viruses (see Appendix A . l ) . This finding is significant because low estimates of abundances have caused researchers to question whether lytic viral production can occur in the deep-sea due to low rates of contacts (Wommack and Colwel l 2000). If the abundances of both prokaryotes and viruses are as much as an order of 89 magnitude higher than previously reported, virus-mediated mortality of prokaryotes may have a much larger role in the ecology and geochemical cycling of the deep-sea. The abundance data for prokaryotes and viruses provides a first approximation of the potential for virus-mediated mortality of prokaryotes. Although contact rates and potential infection among prokaryote cells and viruses can be estimated using these estimates, true infection rates depend not only on the total abundance of potential host cells, but also the diversity of the potential hosts. Viruses have limited host ranges and are often limited to infecting a single species or even strain of prokaryotes, so the community composition can greatly influence the potential for viral lysis. A community dominated by a single strain can be much more susceptible to viral infection than a diverse community with evenly distributed abundances. Because of the high variability in the abundances of prokaryotes and viruses collected from around active venting structures, samples from these locations were analysed to determine the microbial community composition. Samples from around Salut had some of the highest and lowest abundances of both prokaryotes and viruses (Chapter 2). D G G E fingerprint analysis of these samples demonstrated that the distribution and composition of microorganisms around an active venting structure is extremely heterogeneous (Chapter 3). Samples collected from different vent fields or the within the plume were more similar to Salut samples than two samples collected beside each other. The use of P C R precludes any statements about the abundance of each phylotype detected by D G G E ; however, some general observations can be made about the communities. Wi th most of the samples having high numbers of O T U ' s , it is possible that viral infection is limited due to low numbers of potential hosts against a background of other species. The high abundance of viruses around the vent sites suggests that in some locations this is unlikely. It is more likely that the heterogeneity of both the microbial communities and the viral abundances is a result of localized hot spots with high rates of viral infection and lysis. These hot spots may be in areas of restricted water flow, within the subsurface or within the animal community, where groups of prokaryotes 90 are capable of growing rapidly and reach high enough numbers to allow viral infection to occur. The fingerprints of Bacteria and Archaea communities were compared using cluster analysis. This analysis demonstrated that these two communities are influenced by different factors. The main factor influencing these groups is l ikely the source of organisms in the environment. The samples collected in this study range from 5% vent fluid to as high at 25% vent fluid, and represent a range of chemical environments. Missing in this study are more pure samples of vent fluid, with little or no mixing with ambient seawater. The samples in this study are all composed of both vent fluid and ambient seawater. These two end member fluids are the two potential sources of the Bacterial and Archaeal cells. Sequence analysis of the D G G E bands supports the idea of two separate sources for members of the microbial communities. Some of the sequences are most likely derived from the hot environment, while others appear to be derived from ambient seawater entrained around the vents. The effects of two different sources of prokaryotes on virus infection can be seen in the changes in abundance of both prokaryotes and viruses in the neutrally buoyant plume. Along the length of the plume, there appears to be a decoupling of the prokaryote production from virus production. In the younger plume, close to the site of venting, the abundances of prokaryotes is strongly correlated to the strength of the plume as measured by the light attenuation and potential temperature anomalies, but is not correlated to the abundance of viruses. In background waters and within the active vent fields, prokaryote abundances are strongly correlated to virus abundances. Within the plume, the hydrothermal component is rapidly diluted as the plume rises and is then continually diluted as the plume moves laterally away from the site of venting. This dilution introduces more species from the ambient seawater and decreases the hydrothermal derived species as well as hydrothermal derived nutrient sources. The correlation between the prokaryotes and the plumes suggests that the prokaryotes are able to exploit the available nutrients in the plume and increase production. It is l ikely that many of 91 these organisms are heterotrophic mesophiles, which are able to grow on the increased D O M released by vent-derived prokaryotes. The lack of a correlation between the prokaryotes and viruses in the young plume suggests that virus abundance is not related to the abundance of prokaryotes and that viral lysis is reduced. This is supported by the lower V B R in the plume relative to the background seawater and the active hydrothermal fields. A s the plume moves away from the site of venting and becomes less dominated by hydrothermal vent-derived species, the virus community entrained from the ambient seawater would have increased the probability of contacting and infecting a host, resulting in a coupling between the prokaryotic and viral communities. While virus production is decoupled from prokaryote production, the abundance of prokaryotes can increase relative to the abundance of viruses due to a reduction in prokaryotic mortality. Once the communities are coupled, the V B R increases and becomes similar to background levels. Throughout the hydrothermal vent system, viruses appear to have the strongest effect on prokaryote abundance through lysis of cells. Protist grazers appear to be present at very low levels and were undetectable using 18S P C R techniques (Chapter 4). Wi th only one sequence being similar to a ciliate, and no flagellate sequences detected, it appears that grazing pressures from protists on free-living prokaryotes is very low. The sequences related to benthic invertebrates in the water column could be derived from three main sources. The first is that these sequences represent cells sloughed off adult organisms, either through normal growth, physical abrasion, or actions of predators. Dead or dying organisms could also contribute to the D N A in the water column. Two other possibilities are related to reproduction. The D N A may be derived from either gametes released into the water column or from larvae. There is evidence to support the occurrence of both gametes (see Van Dover 2000) and larvae (Metaxas 2004) in the water column. There is strong evidence that free-living prokaryotes contribute to the invertebrate biomass at hydrothermal vents. Stable C and N isotope analyses suggest that most of the food ingested by invertebrates is derived from free-living primary producers and not 92 symbiotic prokaryotes or surface derived photosynthetic material (see Van Dover 2000). The pathway between the prokaryotes and the invertebrates is not known, but the low diversity of protists detected around a hydrothermal vent suggests that direct consumption of prokaryotes by invertebrates may be likely. 5.2 Future Research The results of this research add to the small amount of information available about prokaryote mortality at deep-sea hydrothermal vents. However, many questions still remain and new questions arise from this work. The presence of high abundances of viruses around active hydrothermal vents strongly suggests that viral infection and lysis occurs at these sites. Although the abundances suggest viruses are actively produced, no information is available regarding the rates of virus production and cell lysis. Obtaining rates for virus-mediated processes requires measurements from incubation experiments. The logistics of incubations, such as dilution experiments for measuring virus production (Wilhelm et al. 2002) or radiotracer experiments for measuring prokaryote production (for example Fuhrman and Azam 1982), at depths >2000 m make in situ measurements at deep-sea hydrothermal vents very difficult. Some attempts have been made to measure prokaryote production at vent sites; however, the measurements have generally been made on organisms at surface pressures following decompression of the samples (Karl 1985). The application to the environment of measurements obtained under laboratory conditions is difficult, with most of the effects of a long holding time following sampling, decompression of samples, and variations in temperature completely unknown. The methods employed in this study have shown the virus community to be abundant, but have not demonstrated the diversity of the community. There are two main difficulties in addressing this issue. The first is the difficulty of obtaining a large enough sample for the application of pulse-field gel electrophoresis (PFGE) (Steward 2001). The second issue is the lack of isolates from which to obtain sequence information. Many of 93 the virus diversity studies in surface waters have used sequence information from isolated viruses to design degenerate P C R primers. These primers have then been used successfully to obtain new information about the virus community in the environment (Frederickson et al. 2003; Short and Suttle 2002). Wi th no isolated viruses available to indicate potential targets for P C R analysis, coupled with low sample volumes, elucidating virus diversity has not been successful. The design of a new large-volume sampler suggests that these obstacles may be overcome, and the application of molecular biology techniques to hydrothermal vent virus communities without virus isolation wi l l soon be possible (Wommack et al. 2004). The lack of evidence of protist grazers around a hydrothermal vent structure is surprising. Evidence exists (see Van Dover 2000) that suggests that the free-living prokaryotes are the source of most of the nutrition for the invertebrates that inhabit the vent sites, yet the connection between the prokaryotes and invertebrates is not clear. Most individual prokaryotes are too small to be consumed by metazoans, especially macrofauna. Because of this, small protist grazers are the usual connection between prokaryotes and larger animals. Further investigation into the abundance and distribution of protists around vent sites may provide evidence of potential grazers; however, pico-and nano-eukaryotes are very difficult to distinguish from prokaryotes using microscopy (Massana et al. 2002). The application of in situ hybridization using specific probes may help to identify members of this group. Although there are still many questions about the fate of prokaryotic production at deep-sea hydrothermal vents, this research has provided new information. Virus-mediated mortality appears to be an important component of the microbial ecology at hydrothermal vents, and may be more important in the rest of the deep sea than previously thought. The heterogeneous nature of deep-sea hydrothermal vent microbial communities adds a level of complexity to studies of vent ecology. Samples collected a short distance away from each other may result in widely different estimates of microbial processes. 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(1986) Microorganisms in deep-sea hydrothermal plumes. Nature 320:744-746. Woese, C .R. (1987) Bacterial evolution. Microbiological Reviews. 51:221-271. Wommack, K . E . and Colwel l , R .R. (2000) Virioplankton: Viruses in aquatic ecosystems. Microbiology and Molecular Biology Reviews 64:69-114. Wommack, K . E . , Will iamson, S.J., Sundbergh, A . , Helton, R.R. , Glazer, B .T . , Portune, K . , and Craig C S . (2004) A n instrument for collecting discrete large-volume water samples suitable for ecological studies of microorganisms. Deep Sea Research Part I: Oceanographic Research Papers 51:1781-1792. 116 APPENDIX A: Detailed Methods Employed A.l Epifluorescence Microscopy Enumeration of prokaryotes and viruses in natural seawater samples can be quickly and efficiently completed using epifluorescence microscopy (Hara et al. 1991; Hennes and Suttle 1995; Porter and Feig 1980). In this method, cells and viral particles in the samples are collected and concentrated on a filter, the nucleic acids are stained with a fluorescent stain, and the particles are counted using a microscope. Differentiation between cells and viruses is based mainly on the size and shape of the fluorescent particles. Prokaryote cells tend to appear larger than viruses, and are often elongated. Viruses, in contrast, appear at pinpoints of light. B y counting the number of fluorescing particles in a known area of the filter, the abundance of cells and viruses can be calculated (Suttle 1993). In this study, samples were counted using Yo-Pro 1 (Hennes and Suttle 1995). This dye is incompatible with aldehyde fixatives, so samples were stained, unfixed, immediately following collection. Although fixatives can be used with stains such as D A P I (Porter and Feig 1980) and S Y B R Green 1 (Noble and Fuhrman 1998) for counting both prokaryotes and viruses, studies have shown that both prokaryote (Gundersen et al. 1996; Turley C. M . 1993; Turley and Hughes 1992) and virus abundances (Wen et al. 2004) decrease in fixed samples stored at 4°C. Because of issues with decay, samples collected in 1999, which were fixed with glutaraldehyde and stored before slides were made, were not included in the results of this thesis. The Yo-Pro 1 method was originally developed for enumeration of viruses (Hennes and Suttle 1995); however, comparison between the abundance of prokaryotes determined using Yo-Pro 1 with abundances determined using S Y B R Green 1 showed similar values (Figure A . l ) . S Y B R Green 1 has previously been shown to obtain accurate abundances of prokaryotes when compared to Acridine Orange (Noble and Fuhrman 1998), the standard stain used to enumerate pokaryote cells (Hobbie et al. 1977). The positive correlation between prokaryote abundances determined with S Y B R Green 1 and Yo-Pro 1 supports the use of Yo-Pro 1 in determining prokaryote abundances. 118 Slides were made using the method of Hennes and Suttle (1995). For each sample, 1 m L of seawater was filtered onto a 0.02 pm pore size Anodisc filter (AIO3) under vacuum not exceeding 7 mm Hg. The Anodisc filter was backed by a 0.45 pm nitrocellulose filter (Millipore, Billerica, M A ) to regulate sample flow. The filter was then placed on 68 p i of Yo-Pro 1 solution, diluted 40x in 0.02 pm filtered M i l l i Q water with a final concentration of 2 m M N a C N . The filters were incubated in the dark at room temperature for 48 h. Following incubation, filters were placed on the filtration manifold, with the backing filter, and rinsed 2x with 800 p i of autoclaved M i l l i Q water. The filter was then mounted on a slide with 100% glycerol and stored at -20°C until being counted. A n Olympus A X - 7 0 epifluorescence microscope equipped with a wide-blue filter set (450-480 nm excitation, 515 nm cut-off) and an UPlanApo lOOx objective was used for enumerating particles. A minimum of 200 particles (cells or viruses) was counted for each filter in a minimum of 20 fields (Suttle 1993). The counts were converted into abundances mL" 1 . 119 7 = 6 A • • Spearman's Rho=0.90 (p>0.05, n=8) 4 5 6 7 SYBR Green I Abundance (x 10 s cells ml"1) Figure A . l Comparison of Stains Abundance of prokaryotes in water samples collected from the Guaymas Basin as determined by S Y B R Green 1 and Yo-Pro 1. Non-normal distribution of the data prevented regression analysis, but the non-parametric Spearman's correlation value shown. A.2 PCR (Polymerase Chain Reaction) P C R , or the polymerase chain reaction, has become a central tool of molecular biology. The method uses the double-stranded structure of D N A and complementary base pair to produce copies of a desired sequence of the target D N A . P C R makes use of a thermostable D N A polymerase, Taq, which can withstand temperatures high enough to melt double-stranded D N A (up to 95°C) m. This enzyme, obtained from the hot spring Bacteria Thermus aquaticus, is able to synthesis D N A at 72°C (Saiki et al. 1988). Using a pool of primers, oligonucleotides synthesized to be complementary to either end of the desired target, repeated cycles of heating and cooling of the reaction result in an exponential increase in the number of copies of the desired sequence (Figure A.2) . The products of a P C R reaction contain thousands of copies of a desired sequence and can be used for further analysis. Since the realization by Woese (1987) that the genes coding for the 16S r R N A molecule reflect evolutionary phylogeny, P C R has become an important tool in identifying microorganisms. Amplification and analysis of 16S r D N A genes can provide a more complete picture of the microbial community present in seawater as most organisms in seawater resist culturing in the lab environment (Amann et al. 1995). Application of 16S analysis to the marine environment has been widespread (Dang and Love l l 2002; Giovannoni et al. 1990; Karner et al. 2001; Massana et al. 1997), and has led to a better understanding of the diversity of prokaryotes that exist in the oceans. Use of the 18S r D N A gene found in Eukaryotes has also allowed investigators to determine presence of nano- and pico-eukaryote species which are difficult to determine otherwise (Diez et al. 2001b; Lopez-Garcia et al. 2001; Short and Suttle 2003). 121 Melting 95 °C • d s D N A Anneal ing -55 -60 °C Primers Extension 72 °C • Figure A . 2 Steps of P C R The reaction begins with double-stranded D N A (dsDNA) containing the desired sequence. The reaction is heated in a thermocycler to 95°C to melt the D N A apart. The annealing step allows for the primers, forward and reverse, to bind to the D N A at a specific site sharing the complementary sequence. The temperature of the annealing step depends on the specific sequences of the primers. The extension step follows at 72°C, when the Taq polymerase adds dNTPs to the primers, following the sequence of the target D N A . This cycle is repeated, usually 25-40 times, exponentially increasing the number of copies of the target sequence. 122 A.3 DGGE (Denaturing Gradient Gel Electrophoresis) The application of P C R to mixed communities results in products that contain multiple sequences depending on the initial community composition. One-way to determine which species are present in a sample is to apply P C R , clone the sequences into a plasmid which can be grown in a laboratory bacteria, and then harvest and sequence the clone. Alternatively, enzymes can digest the cloned fragment and banding patterns of different clones compared to determine similarity. In both instances, cloning becomes a limiting step requiring both time and money. Often, a clone library w i l l contain the more common sequences in a mixture of P C R products, but rare sequences are much less likely to be detected unless a large number of clones are screened. A n alternative to cloning is D G G E . This method uses denaturing chemicals to separate products from P C R based on their sequences. The resulting pattern of bands provides a fingerprint of the initial community, with each band assumed to represent a novel species. Multiple samples can be compared to determine what bands are present or absent, allowing for comparisons between time periods, environments or treatments. Application of P C R - D G G E to the marine environment has allowed for rapid determination of community diversity (Muyzer and Smalla 1998; Muyzer et al. 1995; Schafer and Muyzer 2001). Bands present in D G G E fingerprints can be excised reamplified using P C R and sequenced to determine phylogenetic affiliation of the species. D G G E uses varying concentrations of urea and formamide in a polyacrylamide gel to denature, or melt, double-stranded D N A . P C R products are loaded to the top and electrophoresed through the gel (Figure A.3) . The gel is usually warmed to around 55-60°C, and as the d s D N A moves to progressively higher concentrations of urea and formamide, the complementary base pairing between the two strands is interrupted and secondary structures start to form, inhibiting further movement through the gel. A sequence of several hundred base pairs w i l l have several melting domains, which w i l l melt at different times during electrophoresis, depending on the nucleotide sequence. A D G G E fingerprint w i l l then result, with multiple bands representing unique sequences. 123 Low % CD Q 03 CD High % State of P C R P r o d u c t s : Figure A . 3 Separation of P C R products with D G G E The samples are applied to the top of the gel at the lowest concentration of denaturants. The gel is pre-warmed to a specific temperature and a voltage is applied once the samples are loaded. As the P C R products move through the gel, they begin to melt apart depending on their sequence. Sequences with regions with high A / T content w i l l tend to melt first, stopping in the gel. After the gel is finished, a fingerprint of P C R products w i l l be generated for each sample. 124 A.4 Flame AAS (Flame Atomic Absorbtion Spectrometry) Flame atomic absorbtion spectrometry is a method used to determine the concentration of a selected element by measuring the amount of light of a given wavelength that is absorbed by an atomized sample. The Perkin-Elmer Model spectrophotometer used in this study, was an older model and uses a flame to atomize the sample. Using a single element light, one element at a time can be measured. Using Beer's Law, C=kA (C=concentration, k=constant, A=absorbance), the concentration of an element can be calculated from the absorbance under specific conditions using a standard curve. Samples were processed to measure M g following the methods of VonDamm (1983) and the recommendations in the Perkin-Elmer handbook (1996). 50 m L samples were collected in acid washed polyethylene bottles. Samples were acidified immediately after collection with trace-metal grade HC1 to a final concentration of 2% (v/v) and stored at room temperature until processing. M i l l i Q water was used for dilution of samples for measuring M g . Following the recommendations in the Perkin-Elmer handbook (1996), samples were diluted 1:3000 with M i l l i Q . Lanthanum chloride was added to final concentration of 0.1% to reduce interference from A l , S i , T i or K (Perkin-Elmer Corporation 1996). A standard curve was generated using M g solutions of 0, 0.1, 0.3 and 0.5 mg f 1 made from M i l l i Q water, a pure M g standard and 0.1% LaCl3 (Figure A.4) . The standard curve was used to calculate the concentration of M g in the samples from the average absorbance. Triplicate absorbance values were recorded for each sample at two separate times. These six values were averaged to calculate the concentration of the sample. The concentrations, in mg" 1, were converted into mmol kg" 1 for calculation of the percentage of seawater for each sample, assuming that pure hydrothermal fluid has no M g (Butterfield et al. 1994). Measurement of lithium was also planned for the samples, however difficulties in generating a stable standard curve prevented accurate determination of L i concentrations. 125 0.5 ! -0.1 J 1 —i 1 1 1 1 1 0.0 0.1 0.2 0.3 0.4 0.5 0.6 Mg Concentration (mg I"1) Figure A 4 M g Standard Curve Standard curve generated to calculate the concentration of M g in seawater samples. The error bars represent the standard deviation of 12 measurements made for each of the standards. The equation was calculated using least squares regression. 126 

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