Ecology of marine bacteroidetes: a genomics approach

Beatriz Fernández Gómez Marzo 2012 Ecology of Marine Bacteroidetes: A Genomics Approach D. Juan Luís Gómez Pinchetti SECRETARIO DEL DEPARTAMENTO DE BIOLOGÍA DE LA UNIVERSIDAD DE LAS PALMAS DE GRAN CANARIA, CERTIFICA, Que el Consejo de Doctores del Departamento en su sesión extraordinaria tomó el acuerdo de dar el consentimiento para su tramitación a la tesis doctoral titulada “Ecology of Marine Bacteroidetes: A genomics approach” presentada por la doctoranda Dª Beatriz Fernández Gómez y dirigida por los Doctores Carlos Pedrós-Alió y José M. González Hernández. Y para que así conste, y a efectos de lo previsto en el Artº 73.2 del Reglamento de Estudios de Doctorado de esta Universidad, firmo la presente en Las Palmas de Gran Canaria, a .... de .................... de 2012 Ecology of Marine Bacteroidetes: A Genomics Approach (Ecología de los Bacteroidetes Marinos: Una aproximación genómica) Beatriz Fernández Gómez Tesis Doctoral presentada por Da Beatriz Fernández Gómez para obtener el grado de Doctora en Oceanografía por la Universidad de Las Palmas de Gran Canaria. Directores: Dr. Carlos Pedrós-Alió y Dr. José M. González Universidad de Las Palmas de Gran Canaria, Departamento de Biología Institut de Ciències del Mar (ICM-CSIC) DOCTORADO EN OCEANOGRAFÍA Bienio 2006-2008. Con Mención de Calidad de la ANECA La Doctoranda El Director El Co-director Beatriz Fernández Gómez Carlos Pedrós-Alió José M. González En Barcelona, a de de 2012 “Somewhere, something incredible is waiting to be known” Carl Sagan A mis padres y Victor A mi abuela, A Pedro Cover: Water, origin of life. This is an homage to the life-creating power of water. Life begins at the center, where the first cells and the microscopic universe are represented (Diego Rivera, 1951). Back-cover: The Biodiversity Mandala. Representation of all living creatures of our Planet in proportion of the number of currently described species. Created by Stéphan Daigle by request of National Geographic Magazine (1999). Portada: El agua, origen de la vida. Homenaje al poder creador del agua. La vida comienza en el centro, donde están representadas las primeras células y el universo microscópico (Diego Rivera, 1951). Contraportada: El Mandala de la Biodiversidad. Representación de todas las criaturas vivas en nuestro Planeta en proporción al número de especies actualmente descritas. Creado por Stéphan Daigle a petición de National Geographic Magazine (1999). AGRADECIMIENTOS/ACKNOWLEDGMENTS Me gustaría empezar esta tesis dando las GRACIAS a todas las personas que la han hecho posible y a todas aquellas que me han apoyado y dado ánimos en el transcurso de todo el doctorado. ¡Qué guay! Unas cuantas páginas para poder expresarme a mis anchas, sin tener que preocuparme por el lenguaje científicamente correcto! Uff, espero que no se me olvide nadie! Voy a empezar nombrando a mis dos jefes, la cara y la cruz de la misma moneda, dos polos opuestos, pero que sin embargo se acaban atrayendo para formar un ente excepcional. Carles, en el mismo instante en que Ricard me habló de ti pensé.. wow.. el pupilo de Brock! El creador de ese libro gruesísimo que me acompañó durante toda la carrera, que tenía subrayadísimo y lleno de notas y que además me encantaba, entonces me dije… ese tiene que ser mi jefe!. Qué te puedo decir boss, mil gracias por estos “ajium ajium...” años de doctorado, en los cuales he disfrutado a tope cada curso, cada congreso, la campaña al Ártico.., tantos sitios maravillosos que, como me las mando a mi misma, me han llenado la pared de postales!! Gracias por transmitirme ese entusiasmo por la ciencia y su divulgación y ese interés por lo desconocido y lo místico. Jose, sin ti creo que hubiera fallado en la primera etapa de mi doctorado. Gracias por enseñarme y ayudarme tanto con la bioinformática y con los cultivos, por “Skypearme” para animarme y preocuparte de cómo estaban yendo las cosas. Aunque hemos estado trabajando en la distancia, siempre te has preocupado y me has ayudado en todo lo que he necesitado. Y gracias por la acogida en Tenerife y por la excursión al Teide! Y ahora, y no por eso menos importante, el resto de personajes maravillosos! Sílvia Acinas, para mí, mi segunda codirectora. Qué puedo decir de ti bella, mi más sincera gratitud por estar siempre ahí, por tener siempre una idea o consejo para todo. Por transmitir ese positivismo, por hacerme reír, por la oportunidad de ir al TARA, en fin... por ser como eres, una tía genial! Gracias también al resto de jefazos. Cèlia (espero que ahora ya puedas distinguirme de Raquel, jeje), Dolors, Pep, Ramon, Montse S. y Rafel por estar siempre ahí para un consejo, para ofrecer ayuda. A Miquel Alcaráz y Albert Calbet que me abrieron las puertas del ICM cuando todavía era una universitaria en prácticas (nunca pensé que me quedaría tanto!). Disfruté y aprendí mucho con los copepoditos. Muy especialmente estos agradecimientos van para mis chicas, mis niñas (y algún que otro niño!). Gracias por cada uno de los momentos vividos a vuestro lado, buenos o malos, por reírnos tanto juntas y por apoyarnos las unas a las otras. Mi recuerdo más especial es para mi Lore, mi mayor motivación y confidente. Gracias por darme calma, por escuchar todos mis problemas y frustraciones. Por compartirlo todo conmigo, por hacerme reír, por tus “sipos”, “puchas” y “chutas”, que ya forman parte de mi vocabulario. Fue un privilegio poder estar mesa con mesa y tenerte siempre a mi ladito. Ay! Cuanto te estoy echando de menos! Te quiero mucho! Raquel, mi Reich, gracias por las excursioncillas y viajes tan guapos que nos hemos marcado juntas, gracias por tu sonrisa constante y contagiosa. Qué iba a hacer yo (y el resto) sin tu perfecta organización y planificacion! Ah, y de tu coordinación en Bollywood (ahora eres todo un referente para mi! jiji). Montse, simplemente gracias por ser como eres, nunca cambies. Me encanta tu espontaneidad, tu risa picaresca y tu arte de hacer que todo tipo de conversación acabe en el mismo tópico de siempre! Ets la millor! Eli la más cuerda y sensata de todas, gracias por emanar tanta serenidad que contraresta mi nerviosismo. Ero, otra nerviosilla, cada sonrisa tuya vale por mil, ves? tanto que decías y al final el momento llegó y has sido doctora antes que yo! a qué mereció la pena? Gracias por haberte quedado con nosotras un poquito más. Y ahora mi niño, el gran Massimo. Grazie mile por tus divertidas conversaciones, por los cafés matutinos, por tus “coco-colos” a media tarde y por compartir conmigo las frustraciones que da trabajar delante del ordenador (viva el copypaste!), me has hecho reír muchísimo y no sabes cuanto te lo agradezco. Y a Juanlu, porque no se cómo lo haces pero siempre estás (o te veo) de buen humor y transmitiendo buena onda. Y como no, recordar a mi Verito, mi guaji asturiana, aixxx cuánto hemos vivido junticas. Fuiste la primera en marchar pero siempre estás conmigo, vuelveeeee!!!! A mis otras niñas del despacho, Cris, Elena y Ana (fofinhaaa). Gracias por hacerme sentir que estoy en el mejor despacho del instituto, por aguantar mis momentos de locura, mis histerias, mis voces y portazos que a veces desconcentran un poquito, verdad?. Gracias por hacerme reír, por nuestros momentos de cotis, …, pero no me voy a despedir demasiado porque todavía nos quedan algunos meses juntas eh, todavía muchas risas que compartir y… vuestras defensas!! A mis ex-compis de despacho, Javi y Clara L., que empezaron esta aventura conmigo, en aquel lindo y soleado despacho (aixx, como molaba eh!). Espero que os vaya muy bien con vuestros respectivos post-docs. A los “post-docs”, por su gran ayuda: Hugo S., Bea D., Isabel F. y Marta S., gracias, habéis sido un gran apoyo y una referencia, sois magníficos! Y a ti Ramiro, boludo, gracias por resolver mis dudas acerca de como hacer arbolitos, por tu ayuda y los buenos momentos en Hawaii y por los whatever-day beer! Gracias Vane, Irene y Clara C. por vuestra dedicación y por cuanto me hayáis ayudado en el laboratorio y por estar cuando os necesitaba. Y a Mara por su paciencia al contarme las ampollitas para el DOC! Y qué decir de las nuevas generaciones que han ido apareciendo, a Guillem (SalaTZar!), Ana Mari, Fran, Sarah-Jeanne, por hacerme rejuvenecer y por transmitirme ese entusiasmo y alegría con la que empezáis. Seguid así chicos que este es un camino muy largo y lo importante es disfrutarlo! A todos aquellos con los que he compartido momentos de histeria, ánimo mútuo, alegría, frustración, etc., por los pasillos del instituto: Clara R., Arancha, Cris R., Lorenzo, Juancho, Claudio, Mireia, Pati, Julia B., Sílvia A., Bego, Rodrigo A., Martí, Thomas L., Eli S., Suso, Mariona, Sofia K., Marco T., Marc, Miriam, Meri, Xavi Leal, aiss que todavía se me olvidará gente.. A mis colegas del CEAB, a Emilio Casamayor por sus consejos y recomenaciones, al Barbe (cuántos bio-momentos vividos!), a Toni, “the geek”, porque la ciencias no es todo en la vida, a veces hace falta un poco de fiesta, eh? To my colleagues from MPI, my German family, who made unforgettable my stay in the cold and dark Bremen. Danke schön Michi, Daniel (“el pinche”), Julia, Francesca, Ilaria, Paola, Ivolito, Elmar, Thierry, Renzo and Christian (Thanks to keep the “Genoma Pitufo” and “Bea was here”- post-it still in my desk!). Je dois aussi remercier Thomas Pommier, bien qu´il ne soit plus chez ICM, merci pour m´avoir aidé au tout début de mon doctorat. Je veux te remercier pour tes conseils qui, même si tu sais que je ne les prenais pas trop bien, étaient pour mon bien et pour me permettre d´arriver là où je suis aujourd´hui. Je voudrais aussi te remercier pour ces moments de franches rigolades que nous avons eu ensemble. Merci beaucoup chico! To F.O Glöckner and Marga Schüler for the chance of working in their microbial group. To Jarone Pinhassi and Laura G-C for their sympathy and help with the cultures. To Connie Lovejoy for the wonderful experience in the Arctic. To Kriss Rokkan for giving me the opportunity to be at 78ºN!. To Dave Karl, Matt Church, Greig Steward and Mike Rappé for the magnificent “Microbial Oceanography Course” in Hawaii (it was so great!), and all the people who made possible my attendance to courses and congresses and all the nice people I met there. A toda mi gente, que ha sufrido tanto como yo mi doctorado, por aguantar mis batallitas de científica loca (o profesora bacteria) y por hacer que me olvidara por un momento de la ciencia y disfrutara de la vida: Estrella, mi Star, linda, gracias por tus ánimos, por nuestras fiestas y viajes juntas y porque aún estando lejos siempre has estado ahí con tu risa, jo jo jo, te quiero un montón nena (Asere, esa mecánica de doctora!). Dani, gracias por escucharme aunque nunca te enteraras de exactamente con qué bacterias trabajo ni qué hacen. To Souzana for being a magnificent person and take care of me, thank you so so much (you can’t believe it’s done, aren’t you?). Y no me puedo dejar a Xavi de seguridad (que sino se me enfada!) Con la de conversaciones que hemos tenido cuando salia a horas intempestivas del instituto... pues para que veas que me he acordado de ti y espero poder traerte muchas más arenas de los lugares a los que vaya en el futuro. Y en el último momento tengo que añadir a estos agradecimientos a Aridane, ya que sin su ayuda nunca hubiera sido capaz de tramitar el depósito de esta tesis, la cual habría naufragado en su camino hasta la ULPGC. A toda mi familia. A mis padres por su paciencia, por su apoyo incondicional a lo largo de todo este tiempo, por sus ánimos y por hacerme sentir que realmente lo podía conseguir. A mi abuela, por estar tan orgullosa y presumir tanto ante todo el pueblo de nieta científica y viajera (aunque realmente no tiene mucha idea, ella presume!) Y a todo el resto de primos y tíos que se han preocupado por mi trabajo. Por fin existe una respuesta para vuestra eterna pregunta de.. pero tú acabarás ya o qué? Siiii, acabo yaaaa!! Mi último y más especial agradecimiento es para Pedro (“The physicist”). Gracias por tu apoyo incondicional, por no dejarme caer en los momentos de crisis, por intentar resolver todas mis dudas (a veces pregunto demasiando, verdad?), por animarme con mis experimentos y darme siempre nuevas ideas, por tu ayuda con el ODV (maestro!), por todo lo que nos hemos reído (Bazinga!), por los viajes que nos hemos pegado (para cuándo el próximo?). Acaba una parte de la aventura pero lo bueno está por llegar, prepárate.. it’s gonna be LE-GEN-DA-RY!  GRACIAS, GRÀCIES, THANK YOU, DANKE, MERCI, GRAZIE, OBRIGADA!! “La gratitud en silencio no sirve a nadie” Pray that the road is long. May there be many a summer morning, when, with such pleasure, with such joy you enter ports seen for the first time. (Ithaca, K. Kavafis) CONTENTS RESUMEN/RESUM/ABSTRACT LIST OF PUBLICATIONS PRESENTACIÓN DE LA TESIS/THESIS PREVIEW INTRODUCTION OBJECTIVES OF THE THESIS METHODOLOGY Chapter 1. Genome analysis of the proteorhodopsin-containing marine bacterium Polaribacter sp. MED152 (Flavobacteria). Chapter Comparative genomics of marine Bacteroidetes with and without proteorhodopsin. Chapter 3. Patterns and architecture of genomic islands in marine Chapter Chapter 5. Seasonal changes in substrate utilization patterns by bacterioplankton in the Amundsen Gulf (Western Arctic). SYNTHESIS OF RESULTS AND GENERAL DISCUSSION RESUMEN EN ESPAÑOL/SPANISH SUMMARY REFERENCES (Introduction, Discussion and Spanish Summary) AND ANNEXES 25 49 91 149 195 217 241 261 315 44 43 21 19 15 29 2. 4. Culture medium influences the response to light of PRcontaining marine Flavobacteria. Bacteria. “Nothing in life is to be feared, it is only to be understood. Now is the time to understand more, so that we may fear less” Marie Curie 27 General Introducction Introduction 31 ECOLOGICAL GENOMICS OF MARINE BACTERIA If Life had a yearbook, bacteria would win all of the awards, especially “most likely to succeed”. (…) By contrast, humans have occupied a narrow range of environmental conditions—and for only about 0.003 percent of the Earth’s existence. If we even made it into the yearbook, the caption would have read “photo not available”. Lynn Margulis, “The Germs of Life”. THE MARINE ENVIRONMENT The oceans are the largest body of water on Earth. With 1.37x109 km3 and approximately 3.61x1014 m2, the oceans cover about 71% of the Earth’s surface (Davis Jr., 1972). More than half of this area is over 3,000 meters deep, the deepest point being the Mariana Trench, close to 11,000 meters deep. Salinity of seawater is in the range of 33 to 37 with an average around 35. The pH at the surface averages 8.1 and it is becoming more acidic since the industrial revolution began (Orr et al., 2005). The average temperature of the ocean surface waters is about 17°C, changing mainly with latitude. The polar seas can be as cold as -2°C while the Persian Gulf can be as warm as 36°C. Oceans significantly influence the Earth’s climate (Stewart, 2008) by redistributing heat from the tropics to the polar regions (wind-driven and thermohaline circulation), exchanging heat and water vapor with the atmosphere (influencing rainfall patterns and atmospheric circulation), and acting both as sources and sinks of CO2. Disruptions in the thermohaline circulation are thought to have considerable impacts on the Earth’s climate (Bryden et al., 2005). The marine environment contains a vast amount of carbon. One part of it is present in the form of organic carbon, either as dissolved organic carbon (DOC) or as particulate organic carbon (POC). Carbon fuels life in the oceans as it is fixed through photosynthesis by phytoplankton, providing the basis of the marine food webs. Despite their relatively low concentrations, nutrients such as nitrogen (N) and phosphorus (P) are particularly important to the biology of the oceans, and they are the limiting nutrients in most productive regions. In some cases, iron (Fe) or silica (Si) may also act as limiting nutrients (particularly in open ocean regions). The ratio of the concentrations of carbon to nitrogen to phosphorous in phytoplankton is 106:16:1, which is the classic “Redfield ratio” (Redfield, 1934). Ecological Genomics of Marine Bacteria 32 BACTERIOPLANKTON AND ITS ROLE IN THE OCEAN Life within the oceans evolved at least 3 billion years earlier than on land. Microbes were the only kinds of life on Earth for around 80% of the Planet’s history and all multicellular life depends upon microbial processes (Amaral-Zettler et al., 2010). Bacterioplankton includes the bacterial and archaeal members of the plankton (Thurman, 1997), comprising the smallest and most abundant organism in the ocean (Whitman et al., 1998). The ecological function of marine bacteria and archaea is crucial for life on Earth by controlling the ecology of the marine environment as producers and consumers of dissolved organic matter (DOM) (Kirchman, 2008). They are the oldest life forms, the primary catalysts of energy transformations, and fundamental to the biogeochemical cycles that shape our Planet (Falkowski et al., Figure 1. (A) Taxonomic breakdown of the top 20 most abundant bacterial sequences found across 583 bacterial datasets. (B) Taxonomic breakdown of the top 20 most abundant archaeal sequences found in 120 bacterial datasets. The rankings for both pies are based on the sum of the relative abundances of individual sequences from each sample. Taxonomies are base on the Global Alignment for Sequencing Taxonomy (GAST) procedure (Huse et al., 1997). Figure from A Global Census of Marine Microbes (Amaral-Zettler et al., 2010). Introduction 33 2008). They are remarkably abundant, around 105 cells per cm3 (Hobbie et al., 1977; Porter and Feig, 1980; Zimmerman R. and Meyer-Reil, 1974) and when extrapolating to the whole ocean, considering a volume of 1.4x109 km3, they amount to approximately 1029 prokaryotic cells (Whitman et al., 1998). To put this number in perspective, one can consider that there are only 1011 neurons in a human brain or stars in the galaxy. The ocean harbors numerous and diverse groups of bacteria and archaea (Fig. 1). Several of them are autotrophs, including the phytoplankton, and derive energy from photosynthesis. Primary producers in the open ocean are responsible for about half of the Planet’s total primary production (Falkowski et al., 1998; Field et al., 1998). They comprise the Cyanobacteria, that include the two most abundant genera in the ocean: Prochlorococcus (Waterbury et al., 1979) and Synechococcus (Chisholm et al., 1988). Nevertheless, the largest part of marine bacteria consists of heterotrophs that acquire energy by consuming DOM and POM, mostly derived from phytoplankton (Fogg, 1958; Sharp, 1977) but also from grazers (Nagata, 2000). Viruses also contribute to the OM pool by inducing cell lysis (Wilhelm and Suttle, 1999). Heterotrophic bacteria oxidize approximately one-half of the labile carbon fixed by photosynthesis (Azam et al., 1983b; Fenchel, 1988; Robinson, 2008), although this proportion can be significantly higher in oligotrophic waters (del Giorgio et al., 1997). As a consequence, carbon dioxide is released to the ocean and a portion of the organic matter is remineralized into essential inorganic nutrients. This biomass can be reintroduced in the Figure 2. Diagram of the microbial food web. The “microbial loop” refers to losses of DOC from all organisms and their reintroduction into the food web by heterotrophic bacteria and protists. Ecological Genomics of Marine Bacteria 34 food web and represents an additional source of organic substrates for higher trophic levels (protists), while limiting the loss of organic matter via sedimentation and deep burial. Hence, bacteria play a crucial role in pelagic food webs by controlling much of the carbon fluxes in the open ocean (Azam, 1998). This particular food chain is known as the “microbial loop” (Azam et al., 1983a; Ducklow, 1983; Pomeroy, 1974) (Fig. 2). At present, with increasing levels of atmospheric CO2, understanding the function of microbes in marine food webs is an essential issue since the microbial loop determines, in part, the response of oceanic ecosystems and the carbon cycle to climate change (Falkowski et al., 2000; Kirchman et al., 2009). Bacterioplankton also play significant roles in other biogeochemical cycles such nitrogen, phosphorous, or sulfur and anaerobic processes such as fermentation (Kirchman, 2000). MARINE HETROTROPHIC BACTERIA: The phylum Bacteroidetes Different groups of heterotrophic bacteria are present in the ocean (Fig. 1). The most abundant groups belong to the phylum Proteobacteria, particularly the classes Alphaproteobacteria and Gammaproteobacteria (Giovannoni and Rappé, 2000), which represent 3040% of the prokaryotic cells; and the phylum Bacteroidetes, representing between 10-30% (Cottrell and Kirchman, 2000a; Glöckner et al., 1999). The phylum Bacteroidetes, formerly know as Cytophaga-Flavobacterium-Bacteroides (CFB) group, is diverse and is composed mainly by three large classes of bacteria widely distributed in the environment, including soils, sediments, hydrothermal vents, freshand sea water, and the gut and skin of animals: Bacteroidia, Flavobacteria, and Sphingobacteria (Fig. 3 and Fig. 4). Class Bacteroidia is the best studied in general microbiology because of its implications for human health (Finegold et al., 1983). It includes the genus Bacteroides (the most abundant in the intestine of warm-blooded animals including humans) and Porphyromonas, a group of organisms inhabiting the human oral cavity. However, the Flavobacteria and Sphingobacteria classes, whose representatives are mostly from marine and soil habitats, have only received attention in the last decades. Flavobacteria, the most abundant class of the Bacteroidetes phylum in the sea (Alonso et al., 2007), are assumed to be specialized in the degradation of polymers and particulate organic matter (POM) (Pinhassi et al., 2004; Riemann et al., 2000). Many representatives have gliding motility and are important inhabitants of marine aggregates (DeLong et al., 1993; Kirchman, 2002), having the capability to use polymeric substances as carbon and Introduction 35 energy sources. During algal blooms Flavobacteria members are overrepresented with respect to other bacteria as a response to the organic carbon present, denoting their predilection for large molecules, which corresponds to their assumed role as major mineralizers of organic matter (Cottrell and Kirchman, 2000b). Figure 3. Phylogenetic tree of the main classes within the phylum Bacteroidetes (G. & B. Moore Foundation webpage). This feature contrasts with that of the other major group of marine bacteria: the Proteobacteria. Both Alphaand Gammaproteobacteria seem to prefer monomers rather than polymers and carry out a free-living existence in the water column, a fact that suggests complementary roles for the complete degradation of organic matter (Cottrell and Kirchman, 2000b). FLAVOBACTERIA SPHINGOBACTERIA BACTEROIDIA Ecological Genomics of Marine Bacteria 36 Figure 4. Diversity of marine Bacteroidetes. a-c: Flavobacteria; d-e: Bacteroidia; f-i: Sphingobacteria. a. Scanning electron microscopy image of cells of L. blandensis MED217 in the exponential growth phase. b. Electron micrographs of negatively stained cells of Robiginitalea biformata HTCC2501 in exponential phase. c. Colonies of Flavobacterium psychrophilum. d. Gram strain of Bacteroides fragilis, an obligate gut microbe. e. Bacteroides thetaiotaomicron in association with food particle in the mouse gut. f. Identification by FISH of Salinibacter ruber. g. Flexibacter sp. h. Scanning electron micrograph of the cellulolytic gliding bacterium Cytophaga hutchinsonii, showing cells gliding on and digesting a cellulose fiber. i. Scanning electron micrograph of Spirosoma linguale. Introduction 37 Despite their abundance, Flavobacteria have received much less attention than Proteobacteria and Cyanobacteria. Thus, the main objective of this dissertation was to study the ecology and physiology of some representatives of the Flavobacteria. MAIN CARBON SOURCES FOR BACTERIOPLANKTON Although it is known that seawater contains organic matter in a size continuum of discrete units (Sharp, 1973) and these units are interconnected (Verdugo et al., 2004), organic matter in the ocean has traditionally been divided into two groups (dissolved and particulate) pragmatically based on filtration through GF/F filters (Fig. 5). Figure 5. The size range of organic matter and microbial interactions in the ocean (Azam and Malfatti 2007). The main form of organic carbon (>97%) in seawater is represented by DOM (Benner, 2002) which is mainly produced by algal exudation (Nagata, 2000) and cell lysis (viral infections) (Weinbauer and Peduzzi, 1995). However, bacteria also produce cell-surface mucus that can be released to the medium. A large fraction of this DOM consists of refractory molecules that bacteria are not able to assimilate, and it may remain in the ocean for thousands of years (Bauer et al., 1992; Bauer, 2002; Williams and Druffel, 1987). But there is also a small fraction (<10%) of available (labile) molecules (monoand polysaccharides, proteins, peptides and aminoacids) (Benner, 2002) that bacteria can easily utilize. DOM is mainly released in the form of high-molecular-weight DOM (HMW-DOM, >1kDa), which is preferred by bacteria for its high bioreactivity compared with refractory low-molecular-weight-DOM (Amon and Benner, 1994). However, bacteria can only incorporate small molecules into the cell through transmembrane channels. In order to assimilate large molecules they first need Ecological Genomics of Marine Bacteria 44 OBJECTIVES OF THE THESIS The overall goal of this thesis was to characterize one important group of marine bacteria both genetically and physiologically, and to try to understand their life strategies in the ocean. The specific objectives of this thesis are the answers to the following questions: How is the genome of • Polaribacter sp. MED152 ? What does the analysis of its genome tell us about the life strategy of this organism? Chapter 1 Is there any pattern in the genome composition among marine Bacteroidetes? Could • similar characteristics to those of Polaribacter be found in other representatives? Chapter 2 Do the genomic islands present in some groups of bacteria provide advantages for • ecological fitness? Are those different from other groups of bacteria? Chapter 3 What is the actual function of the predicted genes (and more specifically the PR gene) • in their environment? Can the traditional pure cultures techniques help to clarify this point? Chapter 4 Is it possible to determine the metabolic capabilities of bacterioplankton in a natural • environment? Chapter 5 Introduction 45 Fig. 9. Different approaches to study the microbial community used in this thesis. (A) An organism can be isolated in pure culture. Sequencing of its genome allows to study DNA, mRNA, and proteins to obtain information about: i) phylogeny, ii) metabolism and transport, iii) existence of lateral gene transfer, and iv) similarities with organisms from other environments. (B) Similar information can be obtained studying the entire microbial community through metagenomics, bypassing the need to culture the organisms (in the present thesis chose pathway A). (C) BIOLOG microplates allow studying some metabolic capabilities in samples taken directly from the community. Some of the traits found by means of genomics and metagenomics can also be tested using these plates. METHODOLOGY In the present work, bioinformatics tools have been used to reach most of the objectives cited above (Chapters 1-3) in silico. Culture experiments have also been carried out in vivo (Chapter 4) in order to test some of the hypotheses emerged from the former genomic analysis. Finally, a metabolic fingerprint technique (Biolog microplates) was used to characterize the microbial community in situ (Chapter 5). Although the particular methodologies are detailed in each chapter, a general overview of the different techniques is presented here. The following diagram shows the different approaches used in the study of marine bacteria and their interconnections. Ecological Genomics of Marine Bacteria 46 In silico approaches: BIOINFORMATICS Genome annotation and analysis Genome annotation is the process of assigning biological information to gene sequences and their protein products (Stein, 2001). During the last years a large number of genomes have been sequenced (Overbeek et al., 2004) and manual annotation of the genomes is a very time consuming task. To solve this bottle neck, automatic annotation pipelines have been developed. Pipelines perform similarity searches, followed by automatic evaluation of the results and generation of functional annotation. Automatic annotation speeds up the process. However, a high quality genome annotation relies on the accuracy of the annotations, and manual curation is necessary. There are several portals that offer the tools and services for automatic annotation and curation. In this thesis (Chapter 1), we used GenDB from the Center for Biotechnology (CeBiTec), at the University of Bielefeld (Germany) for this purpose. Figure 10 shows the data flow in genome annotation. The process starts with the finished sequence of the genome and the automatic prediction of genes and their function. There is a feedback from gene identification to correction of sequencing errors. After the automatic prediction of genes, a similarity search done with the Basic Local Alignment Search Tool (BLAST) (Altschul et al., 1990) identifies the sequences with high similarity with other proteins in data bases (typically NCBI NR), and, therefore, their function can be predicted. A more detailed annotation can be carried out using other tools in combination with specialized databases such as KEGG (Kanehisa and Goto, 2000) or Pfam (Finn et al., 2008). Genome comparison Comparative genomics is the study of the relationships of genome structure and function among different organisms. While analysis of a single genome provides tremendous biological insights on any given organism, comparative analysis of multiple genomes provides significantly more information on the physiology and evolution of microbial species and expands the capacity to better assign putative function to predicted coding sequences. Comparative analysis offers a qualitatively new perspective on homologous relationships between genes (Koonin et al., 2005). By comparing the sequences of all genes between genomes and within each genome it is possible to reconstruct the evolutionary history of each gene. This, in turn, allows to better understand the specific adaptations of the genomes (Koonin et al., 2005). Introduction 47 Comparative genomics involves the use of computer programs that can line up numerous genomes and look for regions of resemblance among them. Some of these sequencesimilarity tools are accessible to the public over the Internet, the most widely used is the already mentioned BLAST. In Chapter 2 we used the so-called Reciprocal Best Match (RBM) criterion to find orthologs (homologous genes with the same function related via speciation) and paralogs (homologous genes related via duplication and evolving new functions) among and within different marine Bacteroidetes representatives. This is nothing but BLAST performed in two ways, gene a against gene b and viceversa and if the similarity is good enough in both comparisons (according to the parameters defined) they are then considered to be homologous. In order to explore and easily visualize the results, the software JCoast, www.jcoast.net (Richter et al., 2008) was used, allowing to quickly find a gene of interest and compare it with its orthologs in other genomes. Figure 10. Generalized flow chart of genome annotation. Ecological Genomics of Marine Bacteria 48 Prediction of Genomic Islands It is possible to detect genomic islands (GIs) within genomes thanks to the several programs that have been developed recently. In Chapter 3 we chose IslandViewer, an integrated interface for computational identification and visualization of genomic islands (Langille and Brinkman, 2009; Langille et al., 2010). IslandViewer incorporates three different methods: SIGI-HMM (measures codon usage), IslandPath-DIMOB (measures dinucleotide bias), and IslandPick (automated comparative genomics based method). This web site contains precomputed results for a large number of sequenced genomes and allows the user to submit genomes to be analyzed. In vivo experiments Culturing As a complement to genomics, in Chapter 4, a considerable effort was conducted to develop a defined growth medium where the Bacteroidetes could grow in order to test questions regarding their physiological adaptations. BIOLOG MT plates These microplates were created for community analysis and microbial ecology studies (Garland and Mills, 1991; Insam, 1997), allowing the determination of the physiological characteristics of communities and to discern spatial and temporal changes. They consist on 96-well plates containing a carbon source and tetrazolium violet as a redox indicator of carbon source utilization. When bacteria oxidize the compound the indicator turns purple. We used them in Chapter 5 as an attempt to detect the polymeric degradation activities of a microbial community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hapter 1 Chapter 1 51 ABSTRACT Analysis of marine cyanobacteria and proteobacteria genomes has provided a profound understanding of the life strategies of these organisms, their ecotype differentiation and metabolisms. However, a comparable analysis of the Bacteroidetes, the third major bacterioplankton group, is still lacking. In the present manuscript we report on the genome of Polaribacter sp. strain MED152. On the one hand, MED152 contains a substantial number of genes for attachment to surfaces or particles, gliding motility, and polymer degradation. This agrees with the currently assumed life strategy of marine Bacteroidetes. On the other hand, it contains the proteorhodopsin gene, together with a remarkable suite of genes to sense and respond to light, which may provide a survival advantage in the nutrient-poor, sun-lit ocean surface when in search of fresh particles to colonize. Furthermore, an increase in CO2 fixation in the light suggests that the limited central metabolism is complemented by anaplerotic inorganic carbon fixation. This is mediated by a unique combination of membrane transporters and carboxylases. This suggests a dual life strategy that, if confirmed experimentally, would be notably different from what is known of the two other main bacterial groups (the autotrophic cyanobacteria and the heterotrophic proteobacteria) in the surface oceans. The Polaribacter genome provides new insights into the physiological capabilities of proteorhodopsin-containing bacteria. The genome will serve as a model to study the cellular and molecular processes in bacteria that express proteorhodopsin, their adaptation to the oceanic environment, and their role in carbon-cycling. Genome analysis of the PR-containing Polaribacter sp. MED152 52 INTRODUCTION Bacteroidetes are successful in the degradation of particulate organic matter in the ocean (1-2) and at least one molecular study showed them to be more abundant on particles that free-living in the water column (3). Many representatives have gliding motility and the capacity to degrade polymers, possibly allowing them to grow on detritus particles or algal cells using the polymeric substances as carbon and energy sources. Using microautoradiography combined with FISH, for example, Cottrell and Kirchman (4) showed that these bacteria are better adapted to the consumption of proteins over that of amino acids. Functional analysis of the genome of Gramella forsetii indicated that this marine Bacteroidetes has a substantial number of hydrolytic enzymes and a predicted preference for polymeric carbon sources (5). Although the diversity of Bacteroidetes is large, the adaptation to the degradation of polymeric substances seems a common theme. This trait contrasts that of another major group of marine bacteria, the proteobacteria: both alphaand gammaproteobacteria seem to be better adapted to use monomers rather than polymers (4) and to a free-living existence in the water column. Therefore, the study of Bacteroidetes promises to reveal novel life strategies for successfully populating the surface ocean different from those of the proteobacteria whose complete genomes have been analyzed thus far (6-7). Here we present the genome of Polaribacter sp. MED152. This genome was chosen for manual annotation and analysis for two reasons. In the first place it is representative of marine Bacteroidetes. Direct counts by fluorescence in situ hybridization repeatedly show Bacteroidetes to account for about 10-20% of the prokaryotes in seawater (8-9), most belonging to the flavobacteria (10-11). In 2004 there were a total of 864 16S rRNA gene sequences from marine Bacteroidetes in GenBank, of which 76 (9%) belonged to the genus Polaribacter (12). Out of the Polaribacter sequences 27 (36%) were most closely related to Polaribacter dokdonensis. Thus, Polaribacter is one of the major genera of Bacteroidetes found in the marine environment. In the second place, screening of the draft genome revealed the proteorhodopsin gene. The gene for this membrane protein was first found in DNA fragments directly obtained from seawater and functions as a light-driven H+ pump in the ocean (13). Subsequent work has demonstrated a wide diversity and distribution of proteorhodopsin in the surface ocean bacterioplankton. Escherichia coli transformed with the proteorhodopsin gene can in fact use light energy for photophosphorylation (14) and cellular activities such as flagellar motion (15). Recently proteorhodopsin genes have been found in some cultured isolates (7, 16), a few belonging to the Bacteroidetes phylum (17). The presence of the proteorhodopsin gene in cultured bacteria opens the possibility to study the function of proteorhodopsin in vivo. Chapter 1 53 We have recently shown that Dokdonia sp. MED134 (a relative of Polaribacter) can use light energy gathered through proteorhodopsin to grow better in the light than in the dark (17). This is different from the light response of the alphaproteobacteria Pelagibacter ubique and gammaproteobacterium strain HTCC2207, neither one of which has been shown to grow better in the light despite the presence of a functional proteorhodopsin gene; refs. 10, 16). Accordingly, genome analysis of proteorhodopsin-containing flavobacteria opens a unique window to understand evolutionary adaptations to grow in a sun-lit environment. Our present genome analysis indicates that the strategy of Polaribacter sp. MED152 to grow in sea-water is different from that of other groups of abundant marine bacteria. RESULTS AND DISCUSSION Genome properties MED152 forms bright orange colonies on agar plates and tends to aggregate into large flocks in liquid culture (Fig. 1). The genome contains 2,967,150 base pairs with 2692 predicted genes. This is a relatively small genome size for a marine bacterium. For example, 75% of the genomes in the Gordon and Betty Moore Foundation Marine Microbiology Initiative (total of 116 sequenced prokaryotes so far) have genomes larger than MED152 (with primarily SAR11 and Prochlorococcus genomes being smaller). Moreover, this is among the smallest genomes of Bacteroidetes isolates sequenced until now. The reduced genome size of MED152 is a consequence of a reduced number of protein coding genes and gene families compared to most other marine bacteria, in combination with a low number of paralogs in each family. General genome features are presented in SI Table 1. Although not completely closed the genome sequence is on a single contig. G+C skew analysis indicates that the chromosome A B C Figure 1. Images of MED152. A) Colonies on marine agar showing the characteristic orange color. B) SEM image of a typical aggregate showing abundant extracellular material. C) SEM image showing individual cells and extracellular material. Genome analysis of the PR-containing Polaribacter sp. MED152 54 is circular (data not shown). The largest protein families are peptidases (93 ORFs), glycosyl hydrolases (30 ORFs), TonB-dependent outer membrane channels (27 ORFs), response regulators (25 ORFs), glycosyl transferases (25 ORFs), ABC transporters (22 ORFs) and His kinases (21 ORFs). Most peptides annotated as conserved hypothetical or as functional proteins are most similar to peptides in the closely related Polaribacter irgensii 23-P (1506 genes; based on BLASTP). Remaining peptides had homologues in other members of the Bacteroidetes phylum. It does not contain any IS element or peptides related to lysogenic phages, but five genes encode phage integrase family proteins that could allow for site-specific recombination. Central metabolism The metabolic pathways identified in the genome of MED152 are shown in SI Fig. 1-3, and SI Table 2. As expected in a bacterium living in surface waters, the genome of MED152 has adaptations for protection against stress from reactive oxygen species and repair of DNA damage (SI Tables 3-4). Consistent with its life in the ocean MED152 has a Na+ rather than a H+-translocating NADH:quinone oxidoreductase as a part of the respiratory chain to establish a Na+ gradient for energy coupling (18). There are two main characteristics of the central metabolism of MED152: one is logical and the other intriguing. The first one is logical considering the relatively small size of the genome: MED152 has a modest number of metabolic capabilities. It can only grow by aerobic respiration, although it does have a cbb3 type cytochrome oxidase mainly found in microaerophiles; it is unable to use fermentation or anaerobic respiration for energy conservation. Its genome also lacks the Entner-Doudouroff pathway; ammonia and sulfate are the single inorganic sources of nitrogen and sulfur respectively (SI Table 2). MED152 cannot use DMSP, or common products in algal exudates such as glycolate, taurine or polyamines, and it cannot oxidize inorganic sulfur compounds or carbon monoxide. We could only identify the metabolic pathways for the main cellular components (SI Table 2), but none of the rich variety of pathways found for example in Silicibacter pomeroyi (6). The second characteristic is the remarkable number of genes potentially involved in anaplerotic metabolism (SI Table 2). First, MED152 has two types of putative bicarbonate importer genes similar to those found in cyanobacteria. The first one, bicA (MED152_09030, a SulP type, Na+-dependent bicarbonate transporter) has a relatively low affinity for the substrate but a high flux rate (19); while the second one, sbtA (MED152_03855, also a Na+- Chapter 1 61 polysaccharides, rather than monomers, are important carbon and nitrogen sources for at least certain marine flavobacteria. Moreover, MED152 has a complete set of genes involved in gliding motility (15 genes), which could be beneficial in the exploration of solid surfaces. Suspended particles are particularly abundant during and following algal blooms, providing a potentially abundant source of food in the form of particulate organic matter. Flavobacteria are typically associated with the decay phase of phytoplankton blooms (1-2, 10). Further, up to 26 ORFs contained domains that are involved in attachment to surfaces (SI Table 9). Several of these ORFs were located within hydrolytic clusters that included susCD (SI Fig. 7). MED152 has a large array of genes involved in the synthesis and export of extracellular polysaccharide material (e.g. 25 glycosyl transferases). Indeed, MED152 cells grown in liquid medium have a strong tendency to aggregate and form large visible flocks (Fig. 1B). Flavobacteria might also benefit from biofilm formation on particles, such as protection against grazing or against compounds that inhibit their growth and that are synthesized by competitors (33-34). Sigma factors As seen so far, MED152 has several sensors for light, possibly allowing regulation of gene expression under light and dark conditions. Further, it is reasonable to assume that the genome contains regulatory mechanisms for life attached to aggregates/particles compared to a free-living existence. As expected, the genome of MED152 encodes one RpoD type σ-70 transcription factor (MED152_11764) but has as many as 15 alternative σ-70 family of σ factors. Whereas P. ubique has only two and E. coli has six, the number of such transcription factors in other marine bacteria is as high as in MED152. Alternative sigma factors regulate the synthesis of particular sets of genes in response to different environmental stimuli. Thus, genes in the vicinity of the alternative σ-70 transcription factors could give clues as to the type of positively regulated genes and the type of signals MED152 might respond to. For example, MED152_02685 is next to a predicted transmembrane peptide, and both are next to a transcriptional regulator of the MerR type and genes involved in the synthesis of carotenoids and retinal. Both important features of Polaribacter metabolism, light utilization and polymer degradation, appear to be regulated by this mechanism since other σ-70 transcription factor genes are next to peptidase, glycosyl hydrolase, transporter and lipase genes. Genome analysis of the PR-containing Polaribacter sp. MED152 62 Transporters Membrane transporters play critical roles in making use of available nutrients as well as responding to variations in the environment. Genome analysis identified only 106 cell membrane transporters in MED152 (Table 1, SI Table 8). Our comparative analysis showed that this is a remarkably low number (see SI Methods for analysis details). For example, marine Roseobacter or gammaproteobacteria can harbor up to 330. The number of transporters in MED152 is only marginally higher than that in P. ubique, which has 88, despite the genome size of MED152 being more than double that of P. ubique (Table 1). A large number of transporters is typically found in versatile, and generalist bacteria. In contrast, a low number of transporters can be expected in specialized bacteria or bacteria living in a stable and predictable environment (35). Thus, it seems that MED152 is a relatively specialized bacterium when it comes to transporters, which is in accordance with its constrained cell metabolism and small genome size. Transporters PELAGIBACTER MED152 ROSEOBACTER E. coli Total 88 106 210-330 ~350 ATP-dependent 28 28 69-107 72 ABC superfamily 24 22 65-102 67 Ion channels 1 12 7-12 15 PTS 0 0 2-4 29 Secondary 57 62 112-156 233 DMT 20 6 17-37 16 MFS 7 10 14-25 70 MOP 3 7 4-7 8 PELAGIBACTER is P. ubique HTCC1062; ROSEOBACTER includes Loktanella sp. SKA53, Roseobacter sp. MED193, Jannashia sp. CCS1, Roseovarius nubinhibens ISM, Sulfitobacter sp. TM1040, and S. Pomeroyi DSS-3; and E. coli is strain K12-MG1655. Table 1. Summary of transporters detected in the MED152 genome and selected genomes. Chapter 1 63 CONCLUSION The general features of the MED152 genome are consistent with life in the surface ocean, including both utilization of, and protection from, light and oxygen, and a significant number of Na+ dependent proteins. We propose that the more specific features of the genome are related to the need of Polaribacter to alternate between two life styles. On the one hand, MED152 is very well equipped to attach to surfaces, glide in search for polymers and degrade them for carbon, nutrients and energy. On the other hand, once suitable polymeric substrates have been exhausted, MED152 needs to find new particles to colonize. This forces the bacterium to carry on a free-living existence in a carbon poor environment where it cannot move and is not prepared to take up most of the simple carbon compounds available. Thus, MED152 needs to somehow survive through the potentially long “traverse of the desert.” MED152 seems to solve the problem by using proteorhodopsin to capture light energy, increase anaplerotic bicarbonate fixation, and use the few carbon compounds it can get hold of exclusively for biosynthesis. In addition, proteorhodopsin phototrophy could be useful in providing energy for the degradation of complex/recalcitrant organic matter. This strategy is completely different from that of proteobacteria and may be common to many of the other marine flavobacteria accounting for up to 30% of the prokaryotic cells in surface oceans. Analysis of the genome of MED152 has been extremely helpful in generating hypotheses about the life strategy for Polaribacter that can now be tested experimentally. MATERIALS AND METHODS  Isolationofflavobacteria. Bacteria were isolated from Northwestern Mediterranean Sea surface water (0.5 m depth), collected 1 km off the Catalan coast at the Blanes Bay Microbial Observatory (41º 40’ N, 2º 48’ E; Spain). Strain MED152 was isolated on Marine Agar 2216 (Difco; Fig. 1A). 16S rRNA sequence analysis indicated that it belongs to the genus Polaribacter and its sequence is 99.6% similar to that of P. dokdonensis (SI Fig. 8). However, there are a few phenotypic differences between the two: unlike P. dokdonensis, MED152 is ß-galactosidase positive and is able to degrade gelatin. Genomic sequencing and annotation. Whole-genome sequencing was carried out by the J. Craig Venter Institute through the Gordon and Betty Moore Foundation initiative in Marine Microbiology (www.moore.org). A Sanger/pyrosequencing hybrid method was used (36). Large (40 Kb) and small (4 Kb) insert random libraries were sequenced with an average success rate of 95% (large insert) and 93% (small insert) and an average high- Genome analysis of the PR-containing Polaribacter sp. MED152 64 quality read length of 837 (large insert) and 860 (small insert) nucleotides. The completed genome sequence of MED152 contains 30,151 reads, achieving an average of 10-fold sequence coverage per base. ORFs were predicted and autoannotated using GenDB (37). All predicted genes were used to query the TransportDB database (38) and matches were assigned to transporter families within the TransportDB database (http://www.membranetransport.org/). Further, a comparison to 19 genomes of marine bacteria in TransportDB was done (see SI Methods). All automatic annotations were curated manually. All predicted proteins from this genome were compared to selected genomes by using the basic local alignment search tool (BLAST). When necessary, analysis was carried out by using ad hoc Perl scripts. Bacteria used in comparisons were members of the Bacteroidetes phylum in Genbank and genomes in the Gordon and Betty Moore Foundation Marine Microbiology Initiative. Gene content was also compared with available genomes of marine proteobacteria whose members are known to be abundant in sea water, such as the SAR11 and Roseobacter clades, as well as proteobacteria that contain the proteorhodopsin gene. Bicarbonate uptake. MED152 was grown at 16°C in Marine Broth (Difco) diluted 1:8 with artificial seawater (35 practical salinity units, prepared from Sea Salts; Sigma) in light (180 µmol photons m-2 s-1) or dark conditions. Bicarbonate uptake rates were determined by the radioactive carbon assimilation technique (39) after 50 hours incubation (during exponential growth; Fig. 3, inset): subsamples from each incubation condition were then placed in four 25 ml glass bottles (duplicates in both transparent and dark bottles), and incubation continued for 2 hours with 20 µl of H14CO3 - (3 µCi). For details see SI Methods. Pigment analysis. Pigments were identified and quantified using HPLC analysis as described in SI Methods. Chapter 1 65 ACKNOWLEDGEMENTS We thank Folker Meyer, Jomuna Veronica Choudhuri, Daniela Bartels, Andreas Wilke and Tobias Paczian, then at the University of Bielefeld, Germany, for their help with GenDB and José Manuel Fortuño of ICM for help with electron microscopy. The genome was sequenced through the Marine Microbial Initiative of the Gordon and Betty Moore Foundation. This work was supported by the European Union (contract EUFP6-505403 NoE Marine Genomics Europe), the Spanish Ministry of Education and Science (grant CTM2004-02586/MAR) and the Swedish Research Council (grant 621-2003-2692). Genome analysis of the PR-containing Polaribacter sp. MED152 66 REFERENCES 1. Pinhassi J, Sala MM, Havskum H, Peters F, Guadayol Ò, Malits A, Marrasé C (2004) Changes in bacterioplankton composition under different phytoplankton regimens. Appl. Environ. Microbiol. 70:6753-6766. 2. Riemann L, Steward GF, Azam F (2000) Dynamics of bacterial community composition and activity during a mesocosm diatom bloom. Appl. Environ. Microbiol. 66:578-587. 3. DeLong E, Franks DG, Alldredge AL (1993) Phylogenetic diversity of aggregate-attached versus free-living marine bacterial assemblages. Limnol. Oceanog. 38:924-934. 4. Cottrell MT, Kirchman DL (2000) Natural assemblages of marine Proteobacteria and members of the Cytophaga-Flavobacter cluster consuming lowand high-molecularweight dissolved organic matter. Appl. Environ. Microbiol. 66:1692-1697. 5. Bauer MM, Kube H, Teeling M, Richter, Lombardot T et al. (2006) Whole genome analysis of the marine Bacteroidetes ‘Gramella forsetii’ reveals adaptations to degradation of polymeric organic matter. Environ. Microbiol. 8:2201-2213. 6. Moran MA, Buchan A, González JM, Heidelberg JF, Whitman WB et al. (2004) Genome sequence of Silicibacter pomeroyi reveals adaptations to the marine environment. Nature 432:910-913. 7. Giovannoni SJ, Bibbs L, Cho JC, Stapels MD, Desiderio R et al. (2005) Proteorhodopsin in the ubiquitous marine bacterium SAR11. Nature 438:82-85. 8. Cottrell MT, Kirchman DL (2000) Community composition of marine bacterioplankton determined by 16S rRNA gene clone libraries and fluorescence in situ hybridization. Appl. Environ. Microbiol. 66:5116-5122. 9. Glöckner F-O, Fuchs BM, Amann RI (1999) Bacterioplankton compositions of lakes and oceans: a first comparison based on fluorescence in situ hybridization. Appl. Environ. Microbiol. 65:3721-3726. 10. Abell GCJ, Bowman JP (2005) Ecological and biogeographic relationships of class Flavobacteria in the Southern Ocean. FEMS Microbiol. Ecol. 51:265-277. 11. Alonso C, Warnecke F, Amann RI, Pernthaler J (2007) High local and global diversity of Flavobacteria in marine plankton. Environ. Microbiol. 9:1253-1266. 12. Pommier T, Pinhassi J, Hagström Å (2005) Biogeographic analysis of ribosomal RNA clusters from marine bacterioplankton. Aquat. Microb. Ecol. 41:79-898. 13. Béjà O, Aravind L, Koonin EV, Suzuki MT, Hadd A et al. (2000) Bacterial rhodopsin: evidence for a new type of phototrophy in the sea. Science 289:1902-1906. 14. Martinez A, Bradley AS, Waldbauer JR, Summons RE, DeLong EF (2007) Proteorhodopsin photosystem gene expression enables photophosphorylation in a heterologous host. Proc. Natl. Acad. Sci. USA 104: 5590-5595. Chapter 1 67 15. Walter JM, Greenfield D, Bustamante C, Liphardt J (2007) Light-powering Escherichia coli with proteorhodopsin. Proc. Natl. Acad. Sci. USA 104:2408-2412. 16. Stingl U, Desiderio RA, Cho JC, Vergin KL, Giovannoni SJ (2007) The SAR92 clade: an abundant coastal clade of culturable marine bacteria possessing proteorhodopsin. Appl. Environ. Microbiol. 73:2290-2296. 17. Gómez-Consarnau L, González JM, Coll-Lladó M, Gourdon P, Pascher T et al. (2007) Light stimulates growth of proteorhodopsin-containing marine Flavobacteria. Nature 445:210-213. 18. Unemoto T, Hayashi M (1993) Na+-translocating NADH-quinone reductase of marine and halophilic bacteria. J. Bioenerg. Biomembr. 25:385-391. 19. Price GD, Woodger FJ, Badger MR, Howitt SM, Tucker L (2004) Identification of a SulPtype bicarbonate transporter in marine cyanobacteria. Proc. Natl. Acad. Sci. USA 101:18228-18233. 20. Shibata M, Katoh H, Sonoda M, Ohkawa H, Shimoyama M et al. (2002) Genes essential to sodium-dependent bicarbonate transport in cyanobacteria. J. Biol. Chem. 277:1865818664. 21. Van der Horst MA, Key J, Hellingwerf KJ (2007) Photosensing in chemotrophic, nonphototrophic bacteria: let there be light sensing too. Trends Microbiol. 15:554-562. 22. Taylor BL, Zhulin IB (1999) PAS domains: internal sensors of oxygen, redox potential, and light. Microbiol. Mol. Biol. Rev. 63:479-506. 23. Fankhauser C (2001) The phytochromes, a family of red/far-red absorbing photoreceptors. J. Biol. Chem. 276:11453-11456. 24. Ashby MK, Houmard J (2006) Cyanobacterial two-component proteins: structure, diversity, distribution, and evolution. Microbiol. Mol. Biol. Rev. 70:472-509. 25. Hitomi K, Okamoto K, Daiyasu H, Miyashita H, Iwai S et al. (2000) Bacterial cryptochrome and photolyase: characterization of two photolyase-like genes of Synechocystis sp. PCC6803. Nucleic Acids Res. 28:2353-2362. 26. Kanai S, Kikuno R, Toh H, Ryo H, Todo T (1997) Molecular evolution of the photolyaseblue-light photoreceptor family. J. Mol. Evol. 45:535-548. 27. Gomelsky M, Klug G (2002) BLUF: a novel FAD-binding domain involved in sensory transduction in microorganisms. Trends Biochem. Sci. 27:497-500. 28. Kirchman DL (2002) The ecology of Cytophaga-Flavobacteria in aquatic environments. FEMS Microbiol. Ecol. 39:91-100. 29. Anderson KL, Salyers AA (1989) Biochemical evidence that starch breakdown by Bacteroides thetaiotaomicron involves outer membrane starch binding sites and periplasmic starch-degrading enzymes. J. Bacteriol. 171:3192-3198. 30. Anderson KL, Salyers AA (1989) Genetic evidence that outer membrane binding of Genome analysis of the PR-containing Polaribacter sp. MED152 68 starch is required for starch utilization by Bacteroides thetaiotaomicron. J. Bacteriol. 171:3199-3204. 31. Reeves AR, Wang G-R, Salyers AA (1997) Characterization of four outer membrane proteins that play a role in utilization of starch by Bacteroides thetaiotaomicron. J. Bacteriol. 179:643-649. 32. Blanvillain S, Meyer D, Boulanger A, Lautier M, Guynet C et al. (2007) Plant carbohydrate scavenging through TonB-dependent receptors: a feature shared by phytopathogenic and aquatic bacteria. PLoS ONE 2:e224. 33. Long RA, Azam F (2001) Antagonistic interactions among marine pelagic bacteria. Appl. Environ. Microbiol. 67:4975-4983. 34. Grossart HP, Schlingloff A, Bernhard M, Simon M, Brinkhoff T (2004) Antagonistic activity of bacteria isolated from organic aggregates of the German Wadden Sea. FEMS Microbiol. Ecol. 47:387-396. 35. Ren Q, Paulsen IT (2005) Comparative analyses of fundamental differences in membrane transport capabilities in Prokaryotes and Eukaryotes. PLoS Comput. Biol. 1:e27. 36. Goldberg MD, Johnson J, Busam D, Feldblyum T, Ferriera S et al. (2006) A Sanger/ pyrosequencing hybrid approach for the generation of high-quality draft assemblies of marine microbial genomes. Proc. Natl. Acad. Sci. USA 103:11240-1124. 37. Meyer F, Goesmann A, McHardy AC, Bartels D, Bekel T et al. (2003) GenDB – an open source genome annotation system for prokaryote genomes. Nucleic Acids Res. 31:2187-2195. 38. Ren Q, Kang KH, Paulsen IT (2004) TransportDB: a relational database of cellular membrane transport systems. Nucleic Acids Res. 32:D284-D288. 39. Parsons TR, Maita Y, Lalli CM (1984) A manual of chemical and biological methods for seawater analysis. Pergamon Press, Oxford, UK. Chapter 1 69 SUPPORTING INFORMATION SI METHODS Transporters. The low number of transporters was apparent in most of the main transporters families. Thus, together with Pelagibacter ubique, MED152 has the lowest number of ATP-dependent transporters (a majority belonging to the ATP-binding Cassette [ABC] superfamily) of the marine bacteria sequenced so far (Table 1). The same holds true for the secondary transporters, which account for 50 to 70% of the transporters in the marine bacterial genomes sequenced until now. MED152 has only a total of 62 secondary transporters – similar to the number found in Pelagibacter ubique – while other bacteria may have from 100-200. In particular, the number of transporters in the drug/metabolite transporter (DMT) superfamily and in the major facilitator superfamily (MFS; used for transport of a diverse set of “small solutes in response to chemiosmotic ion gratients”; Pao et al., 1998) transporters was low, while the number of multidrug/oligosaccharidyl-lipid/ polysaccharide (MOP) flippase superfamily transporters was similar to that in other marine bacteria (despite its smaller genome). Like Pelagibacter ubique, MED152 (and other marine flavobacteria) lacks phosphotransferase system (PTS) genes for active transport of sugars. PTS genes are present in all major bacterial groups except cyanobacteria and epsilonproteobacteria (Barabote and Saier, 2005). The lack thereof is consistent with the aerobic life style of MED152 (PTS are particularly important for sugar uptake under anaerobic conditions). Comparative analysis of transporters. Transporter families in MED152 were compared to the following marine genomes in the TransportDB database (details on transporter families and substrate specificity of particular transporters in specific bacteria are available at http://www.membranetransport.org/): alphaproteobacteria Bradyrhizobium japonicum USDA 110, “Candidatus Pelagibacter ubique” HTCC1062, Caulobacter crescentus CB15, Hyphomonas neptunium ATCC 15444, Jannaschia sp. CCS1, Loktanella vestfoldensis SKA53, Maricaulis maris MCS10, Roseobacter sp. MED193, Roseobacter sp. TM1040, Roseovarius nubinhibens ISM, and Silicibacter pomeroyi DSS-3; gammaproteobacteria Aeromonas hydrophila subsp. hydrophila ATCC 7966, E. coli K12-MG1655, Marinomonas sp. MED121, Photobacterium profundum SS9, Pseudoalteromonas haloplanktis TAC125, Pseudomonas aeruginosa PAO1, Shewanella oneidensis MR-1, and Vibrio sp. MED222; Bacteroidetes/Chlorobi phylum Bacteroides fragilis NCTC9343, Bacteroides fragilis YCH46, Bacteroides thetaiotaomicron VPI-5482, Chlorobium tepidum TLS, Dokdonia sp. MED134, Genome analysis of the PR-containing Polaribacter sp. MED152 70 Leeuwenhoekiella blandensis MED217, and Polaribacter sp. MED152; and Firmicutes Bacillus subtilis 168. Bicarbonate uptake. For the bicarbonate uptake experiment, MED152 was grown at 16°C in Marine Broth (Difco) diluted 1:8 with artificial seawater (35 practical salinity units, prepared from Sea Salts; Sigma) in light (180 µmol photons m-2 s-1) or dark conditions (duplicate 200 ml cultures in each condition). Cultures were maintained without shaking to reduce aggregation and flock formation. After 50 hours incubation (during exponential growth), four subsamples from one culture of each incubation condition (light and dark) were transferred to 25 ml glass bottles. From each original incubation condition, two subsamples (treated as duplicates) were placed in transparent bottles and two subsamples were placed in dark bottles (bottles covered with aluminum foil and black plastic). All bottles were then incubated under white light (180 µmol photons m-2 s-1; no light entered the dark bottles) for 2 hours with 20 µl of H14CO3 - (3 µCi; DHI, Denmark). Controls from each treatment were treated with 10% trichloroacetic acid (final concentration). After incubation, 3 ml aliquots from each replicate bottle were filtered through 0.2 µm pore size filters (25 mm diameter, Supor-200, Pall), and the filters were exposed to HCl 0.7 M fumes for 2 hours. Finally, the filters were placed in vials with 10 ml scintillation cocktail (Perkin Elmer) and kept at least 24 hours in the dark before counting. Bicarbonate uptake rates were calculated according to the standard radioactive carbon assimilation technique procedure (Parsons et al., 1984). At the time of the experiment, bacterial abundance was approximately 5.1 ×108 cells ml-1, as determined by epifluorescence microscopy of SYBR Gold stained cells. Pigment analysis. MED152 was grown in Marine Broth 2216 (Difco) and filtered onto Whatman GF/F filters. Pigments were extracted by placing the filters in 3 mL of 90% acetone (with 0.01% of butylated hydroxytoluene to prevent chlorophyll allomerization) and vortexing them vigorously for 45 s. After 24 h at -20ºC, samples were sonicated for 1 min and vortexed again for 45 s. The extracts were cleared by filtration through Poretics 0.8 µm polycarbonate filters. For pigment chromatography, 150 µL of a mixture of 0.5 mL extract plus 0.1 mL H2O was injected into a Thermo HPLC system and run under the conditions described in Latasa et al. (2001). Standards of myxoxanthophyll, zeaxanthin and β-carotene (DHI, Denmark) were used for pigment identification and quantification. 1. Pao SS, Paulsen IT, Saier MH (1998) Major facilitator superfamily. Microbiol. Mol. Biol. Rev. 62:1-34. 2. Barabote RD, Saier MH (2005) Comparative genomic analyses of the bacterial phosphotransferase system. Microbiol. Mol. Biol. Rev. 69:608-634. Chapter 1 77 Cytophaga hutchinsonii ATCC 33406 (ABG59224) Bdellovibrio bacteriovorus HD100 (NP_969047) Polaribacter sp. MED152 (EAQ42129) Polaribacter irgensii 23-P (EAR12306) Gramella forsetii KT0803 (CAL66792) Leeuwenhoekiella blandensis MED217 (EAQ50655) Dokdonia sp. MED134 (EAQ37912) Robiginitalea biformata HTCC2501 (EAR15388) Flavobacteria bacterium BBFL7 (EAS18882) Flavobacteriales bacterium HTCC2170 (EAQ99722) Flavobacteria bacterium BAL38 (EAZ94886) Flavobacterium johnsoniae UW101 (EAS59613) Tetrahymena thermophila SB210 (XP_001014668) Croceibacter atlanticus HTCC2559 (EAP86619) Psychroflexus torquis ATCC 700755 (EAS70891) Microscilla marina ATCC 23134 (EAY26370) Chromobacterium violaceum ATCC 12472 (NP_903151) Dechloromonas aromatica RCB (YP_287092) Escherichia coli K12 (P00914) Synechocystis sp. PCC 6803 (Q55081) Lyngbya sp. PCC 8106 (ZP_01619085) Flavobacteria bacterium BAL38 (EAZ96444) Leeuwenhoekiella blandensis MED217 (EAQ50817) Psychroflexus torquis ATCC 700755 (EAS70877) Gramella forsetii KT0803 (CAL67671) Croceibacter atlanticus HTCC2559 (EAP85920) Dokdonia sp. MED134 (EAQ39857) Polaribacter sp. MED152 (EAQ42116) Polaribacter irgensii 23-P (EAR12320) Flavobacteria bacterium BBFL7 (EAS20023) Robiginitalea biformata HTCC2501 (EAR14251) Cytophaga hutchinsonii ATCC 33406 (ABG58330) Microscilla marina ATCC 23134 (EAY27653) Crocosphaera watsonii WH 8501 (ZP_00519034) Lyngbya sp. PCC 8106 (ZP_01620550) Trichodesmium erythraeum IMS101 (YP_723991) Danio rerio (AAH98514) Xenopus laevis (Q75WS4) Arabidopsis thaliana (AB062926) Vibrio cholerae O1 biovar eltor str. N16961 (NP_231036) Pseudoalteromonas haloplanktis TAC125 (YP_340698) Pseudoalteromonas atlantica T6c (YP_659737) Polaribacter irgensii 23-P (EAR12948) Dokdonia sp. MED134 (EAQ39859) Flavobacteria bacterium BAL38 (EAZ94885) Polaribacter irgensii 23-P (EAR12318) Synechocystis sp. PCC 6803 (P77967) Polaribacter sp. MED152 (EAQ42118) gamma proteobacterium KT 71 (ZP_01103850) Microscilla marina ATCC 23134 (EAY31164) Homo sapiens (AB014558) Idiomarina baltica OS145 (ZP_01042359) class I CPD photolyase cryptochromes, DASH family animal cryptochromes and (6-4) photolyases 100 61 57 62 82 84 100 96 86 94 87 52 84 92 100 97 71 78 64 50 53 98 0.1 Figure S6. Evolutionary relationships of cryptochrome/photolyase protein family from the marine Bacteroidetes and representatives from other organisms. Subfamilies are indicated on the right. A multiple alignment was constructed with the software package CLUSTAL W 1.74 (Thompson et al., 1994). The alignment was edited with Gblocks (Version 0.91b) to identify conserved regions (Castresana, 2000) with a minimum block of ten and without gaps. The tree was constructed based on a Kimura’s distance matrix and the Neighbour-Joining method using the PHYLIP package (Version 3.2) (Felsenstein, 1989). The statistical significance of the tree topology was evaluated by bootstrap analysis with 1000 iterative constructions of the neighbour-joining tree. The numbers at the nodes are bootstrap values higher than 50%. The scale bar represents the Kimura distance. Genome analysis of the PR-containing Polaribacter sp. MED152 78 1000 bp alpha-amylase conserved hypothetical protein conserved hypothetical protein outer membrane protein SusD TonB dependent/ligand-gated channel SusC transcriptional regulator, LacI family sugar (GPH):cation symporter beta-phosphoglucomutase glycosyl hydrolase family 6 sulfatase alpha-amylase putative esterase glycosyl hydrolase family 31 alpha-amylase alpha-amylase conserved hypothetical protein TonB dependent/ligand-gated channel SusC outer membrane protein SusD conserved hypothetical protein (contains one PKD domain) hypothetical protein conserved hypothetical protein conserved hypothetical protein glycosyl hydrolase family 17 O-glycosyl hydrolase family 30 sugar (GPH):cation symporter TonB dependent/ligand-gated channel SusC outer membrane protein SusD conserved hypothetical protein (contains four FG-GAP repeats, one ASPIC and UnbV domain) pfkB family carbohydrate kinase putative sodium/myo-inositol symporter oligo-1,6-glucosidase major facilitator superfamily permease glycosyl hydrolase family 65 glycosyl hydrolase family 5 trehalase major facilitator superfamily permease sugar (GPH):cation symporter conserved hypothetical protein (contains one FG-GAP repeat) conserved hypothetical protein (contains one FG-GAP repeat) hypothetical protein TonB dependent/ligand-gated channel SusC outer membrane protein SusD TonB dependent/ligand-gated channel SusC outer membrane protein SusD short chain dehydrogenase hexuranate transporter transcriptional regulator, GntR family conserved hypothetical protein (contains two PKD domains) conserved hypothetical protein heparinase II/III-like protein hypothetical protein short chain dehydrogenase alginate lyase transporter, NRAMP family 6-phosphogluconate dehydrogenase gluconokinase alginate lyase alginate lyase conserved hypothetical protein conserved hypothetical protein (contains one cupin domain) Figure S7. Clusters of genes putatively involved in the attachment and degradation of polymeric compounds. Only those that contain the tandem TonB dependent/ligand-gated channel genes and susD homologs are represented. Chapter 1 79 Tenacibaculum maritimum (AB078057) Tenacibaculum ovolyticum (AB032506) Tenacibaculum amylolyticum (AB032505) Tenacibaculum skagerrakense (AF469612) Tenacibaculum litopenai (DQ822567) Tenacibaculum aestuarii (DQ314760) Tenacibaculum lutimaris (AY661691) Tenacibaculum litoreum (AY962294) Tenacibaculum mesophilum (AB032501) Polaribacter glomeratus (M58775) Polaribacter filamentus (U73726) Polaribacter franzmannii (U14586) Polaribacter irgensii (M61002) Polaribacter butkevichii (AY189722) Polaribacter dokdonensis (DQ004686) Polaribacter sp. MED152 (DQ481463) Kordia algicida (AY195836) Cellulophaga lytica (M62796) Psychroserpens burtonensis (U62913) 94 81 100 100 97 100 100 100 91 0.05 Figure S8. Neighbour-joining phylogenetic tree based on 16S rRNA gene sequences of MED152 and closely related type strains for each species. A multiple alignment was constructed with the software package CLUSTAL W (Version 1.83; Thompson et al., 1994). The alignment was edited with Gblocks (Version 0.91b) to identify conserved regions (Castresana, 2000) with a minimum block of ten and without gaps. The tree was constructed based on a Jukes-Cantor distance matrix and the Neighbour-Joining method using the PHYLIP package (Version 3.2) (Felsenstein, 1989). The sequence of Cytophaga hutchinsonii (M58768) served as the outgroup. Bootstrap values greater than 70% confidence are shown at branching points (percentage of 1000 resamplings). GenBank accession numbers are given in parentheses. The scale bar represents Jukes-Cantor distance. Genome analysis of the PR-containing Polaribacter sp. MED152 80 Supplementary Table 1. Summary of MED152 genome. Parameter Value No. of bp 2,967,150 GC content (%) 30.61 Coding density (%) 92.6 No. of predicted protein coding genes 2,646 No. of predicted proteins with putative function 1,750 No. of conserved hypothetical proteins 593 No. of unknown proteins unique to MED152 303 No. of tRNA’s 37 No. of rrn 3 Chapter 1 81 Table S2. Key enzymes and metabolic pathways identified in MED152 sFRO)enonahtretaergnehwypoceneg(emyzne/yawhtaP Mainpathways 251DEMyawhtapcitorelpanA.esalyxobracetavuryP 04060 251DEMyawhtapcitorelpanA.esalyxobracPEP 09950 251DEMyawhtapcitorelpanA.ssapybetalyxoylG 00580 (aceA ), MED15200575 (aceB) 251DEMyawhtapcitorelpanA.emyznecilaM 06685 251DEMmsilobatemetatecA.esarefsnartlytecaetahpsohP 00555 251DEMmsilobatemetatecA.esaniketatecA 00550 251DEMmsilobatemetatecA.esagilAoCetatecA 13179 Acyl-CoAdehydrogenase.251DEM)8(noitadixO01705,MED15204870,MED15205285,MED15205295, MED15205785,MED15207525,MED15207535,MED15210560 Enoyl-CoAhydratase.251DEM)4(noitadixO05285,MED15206790,MED15209440,MED15211649 Electrontransferprotein.251DEMnoitadixO11949 (etfA ), MED15211944 (etfB ) 251DEMnoitadargeddipiL.esaniklorecylG 08680 Glycerol-3-phosphatedehydrogenase(NAD(P)+) MED15205430,MED15208715 FAD-linkedglycerol-3-phosphatedehydrogenase. MED 152 08690 251DEMsisehtnysoibnegocylG 05855 (glgA ), MED15205860 (glgC ), MED15205865, MED15205870,MED15205875 (glgB ), MED15205880, MED15205885 Electrontransportchain Na 251DEMesatcuderodixoenoniuq:HDANgnitacolsnart11704 (nqrA ), MED15211709 (nqrB), MED15211714 (nqrC), MED15211719 (nqrD), MED15211724 (nqrE), MED15211729 (nqrF) 251DEM)tnedneped-DAF(esanegordyhedHDANIIepyT 12814 251DEMesanegordyhedetaniccuS 08110 (sdhA), MED15208115 (sdhB), MED15208105 (sdhC) 251DEMesadixocemorhcotyC 10275 (coxM ), MED15210280 (coxN), MED15206775 (coxO ), MED15206770 (coxP) 251DEMepyt3bbc,esadixoemorhcotyC 03190 (ccoNO ), MED15203195 (ccoS) 251DEMIssalccemorhcotyC 10265 251DEMcemorhcotyC 10245 251DEMnietorpylbmessacemorhcotyC 05520 251DEMnietorpylbmessaesadixoemorhcotyC 06660 251DEMrotcafylbmessaesadixoemorhcotyC 06780 251DEMgolomohAaxOnietorpenarbmemrenniDK06 13299 SenC(3)MED15203785,MED15206550,MED15206755 Nitrogenassimilation 251DEMesahtnysetamatulG 05815 (gltB), MED15205820 (gltD ) Ammoniumchannel ( amtB 251DEM)2() 05800,MED15205810 251DEMII-PnietorpyrotalugernegortiN 05805 251DEMIIepyt,esatehtnysenimatulG 05925 251DEMIIIepyt,esatehtnysenimatulG 05920 251DEMesanegordyhedetamatulG 08660 Phosphatemetabolism 251DEMesaemrepetahpsohP 09510 251DEM)3(esaniketahpsohpyloP 00300,MED15200305,MED15205065 251DEMesatahpsohpylopoxE 04590 H251DEMesatahpsohporypgnitacolsnart11924 251DEMesatahpsohporypelbuloS 11929 Sulfurassimilation 251DEMyawhtapSPAP/SPA 06170 (cysD), MED15206175 (cysH), MED15206165 (cysN), MED15206160 (cysI), MED15209765 (cysJ), MED15200895 (cysK), MED15206130 (cysM), MED15206135 (cysE) 251DEM)3(esaemrepetahpluS 09030,MED15210290,MED15212914 Ironassimilation Fe 3 251DEM)2(nietorpcimsalpirepgnidnib01595,MED15211574 ABC-type Fe 3 251DEM)2(retropsnarterohporedis00690,MED15200695 Mn 2 /Fe 2 251DEM)2(ylimafPMARN,retropsnart 03840,MED15211859 251DEM)2(nietorpekil-nitirreF 01695,MED15203075 ATP-dependent Fe 2 251DEMBAoeFmetsystropsnart 06540,MED15206545 Fur(2)MED15200170,MED15201940 RepressorMED15210760 Bicarbonateuptake 251DEM)AciB(retropsnartepytPluS 09030 SbtAMED15203855 251DEMesardyhnacinobraC 09035 Thefollowingadditionalpathwayswerecompleteandarenotshownonthetable: glycolysis, gluconeogenesis,TCAcycle,pentosephosphatepathway, purine biosynthesis and salvage, pyrimidine biosynthesis and salvage, thimidylate biosynthesis, amino acid metabolism, fatty acid biosynthesis, NAD biosynthesis, riboflavinandFADbiosynthesis,sirohemebiosynthesis,quinonebiosynthesis,H -ATPase,pyridoxalphosphatebiosynthesis,pantothenateandCoAbiosynthesis. Complete cobalamine, biotin and thiamine biosynthetic pathways were not found. Entner–Doudoroff pathway is incomplete. Genome analysis of the PR-containing Polaribacter sp. MED152 82 Table S3. Key stress response-related genes in MED152 Pathway/protein (copy number when greater than sFROssertsfoepyT)eno 251DEMcitomsOsisehtnysoibeniatebenicylG 05190 (betA ), MED15204445 (betB ) 251DEMcitomsO)2(CmsO 04480,MED15207905 LargeConductanceMechanosensitiveIonChannel (MscL)family(2) 251DEMcitomsO 07755 * ,MED15208290 * SmallConductanceMechanosensitiveIonChannel (MscS)family(6) 251DEMcitomsO 03080 * ,MED15205265 * ,MED15206730 * , MED15210700 * ,MED15211349 * ,MED15212279 * Voltage-Gated K 251DEMcitomsO)2(ylimafrepuslennahC 01430 * ,MED15204890 * K 251DEMcitomsOHkrTnietorpekatpu 12369 * MonovalentCation:ProtonAntiporter-2(CPA2)family Ktransporter 251DEMcitomsO 02125 * Cl - 251DEMcitomsOylimaf)ClC(lennahC 07855 * ATP-BindingCassette(ABC)type Na 251DEMcitomsO)3(retropsnart 05270 * ,MED15205275 * ,MED15213214 * 251DEMnoitcetorpoyrc/citomsO)CpsP(CnietorpkcohsegahP 03405 251DEMnoitcetorpoyrC)3(esarutaseddicayttaF 06405,MED15206505,MED15209405 NhaC Na :H Antiporter(NhaC)family(2)Internal pH regulation/NaextrusionMED15206020 * ,MED15208675 * NhaD Na :H Antiporter(NhaD)familyInternal pH regulation/NaextrusionMED15205770 * Monovalent Na /H Antiporter-1(CPA1)family(2)Internal pH regulation/NaextrusionMED15202960 * ,MED15203050 * 251DEMnoitcetorpoyrC)3(esarutasedloretS 02375,MED15207040,MED15210110 251DEMnoitcetorpoyrC)21(esacilehANRxobDAED 00240,MED15201675,MED15201850, MED15202405,MED15202435,MED15202810, MED15203055,MED15203355,MED15207660, MED15208085,MED15210165,MED15213039 251DEMnoitcetorpoyrC)3(nietorpgnidnib-ANDkcohs-dloC 01260,MED15202750,MED15206655 251DEMnoitavratSEruSesatahpsohpdicalavivrusesahp-yranoitatS 06290 Guanosinepolyphosphate(ppGpp) pyrophosphohydrolase/synthetase 251DEMnoitavratS 01945 251DEMnoitavratSHohP,nietorpelbicudni-noitavratsetahpsohP 13139 251DEMevitadixOesalataC 05245 251DEMevitadixOesatumsidedixorepusnZ/uC 04650 251DEMevitadixOesatumsidedixorepusnM/eF 07780 251DEMevitadixO)2(esadixorepc-emorhcotyC 03805,MED15208020 251DEMevitadixO)3(Aepyt,esatcuderedixo-S-teM-nietorP 03040,MED15207435,MED15207450 251DEMevitadixO)2(Bepyt,esatcuderedixo-S-teM-nietorP 01175,MED15207430 251DEMevitadixOesadixorepenoihtatulG 05385 251DEMevitadixO)3(nietorpylimafAST/CphA 02100,MED15205240,MED15209055 251DEMevitadixO)61(nixodeR 00520,MED15200525,MED15201395, MED15201805,MED15201910,MED15203415, MED15205235,MED15206110,MED15206230, MED15206900,MED15207620,MED15208425, MED15210120,MED15210405,MED15210550, MED15211584 251DEMslateM)3(CsrAesatcuderodixoetanesrA 00320,MED15202710,MED15207715 251DEMslateMBsrAnietorpecnatsiseretinesrA 02140 251DEMslateM)2(nietorpnoitacfiixoted/tropsnartlatemyvaeH 09525,MED15211224 MerTPMercuricIon(Hg 2 )Permease(MerTP)family transporter 251DEMslateM 00110 * 251DEMslateMretropsnartylimaf)3RCA(3-ecnatsiseRlacinesrA 02140 * Mn 2 251DEMslateM)2(ylimaf)pmarN(retropsnarT 03840 * ,MED15211859 * 251DEMslateM)2(ylimafCreTnietorpenarbmemlargetnI 01215,MED15213169 251DEMsgurD)8(esamatcaL03350,MED15203530,MED15207260, MED15207965,MED15208005,MED15209070, MED15210295,MED15210385 251DEMsgurDesarefsnartlytecalocinehpmarolhC 03570 251DEMsgurD)4(retropsnartepyt)CBA(ettessaCgnidniB-PTA 00590 * ,MED15200620 * ,MED15211514 * , MED15213184 * 251DEMsgurD)2(retropsnart)SFM(ylimafrepuSrotatilicaFrojaM 08705 * ,MED15211639 * Multidrug/Oligosaccharidyl-lipid/Polysaccharide (MOP)Flippasesuperfamilytransporter(3) 251DEMsgurD 01915 * ,MED15202820 * ,MED15209425 * Resistance-Nodulation-CellDivision(RND)superfamily transporter 251DEMsgurD 08525 * ORFs with an asterisk also appear in Table S8 showing transporters. Chapter 1 83 Table S4. Genes coding for replication, repair, and recombination mechanisms in MED152 yawhtap;noitpircsednietorPsFROemaneneG uvrAMED15201780,MED152 riapernoisicxeeditoelcun;gnidnibAND,esaPTA00940 uvrBMED152riapernoisicxeeditoelcun;esacileH55430 uvrCMED152riapernoisicxeeditoelcun;esaelcuN00590 uvrDMED15201615,MED152 riapernoisicxeeditoelcun;esacilehPER/DrvU57701 mfdMED152riapernoisicxeeditoelcun;rotcafgnilpuocriaper-noitpircsnarT04701 ungMED152riapernoisicxe-esab;esalysocylgANDlycarU00800 nthMED15201800,MED152 riapernoisicxeesab;ylimafrepusDPG-HhH04690 tagMED152riapernoisicxeesab;Iesadisocylgeninedalyhtem-3-AND98911 xthMED152riapernoisicxeesab;IIIesaelcunobiryxoedoxE05401 MED152;ylimaf1MAH/Bgdr,esatahpsohporypPTNeniruplacinonac-noN00700 DNArepair radAMED152smS/AdaRnietorpriaperAND54280 radCMED152CdaRnietorpriaperAND97321 mutLMED152nietorpriaperhctamsimAND52310 mutSMED15200795,MED15208905,MED152 nietorpriaperhctamsimAND02690 recAMED152noitanibmocerAND;esanibmoceR53780 recDMED152AND;tinubusahpla,)Vesaelcunoxe(esANDoxetnedneped-PTA09200 recombination recFMED152noitanibmocerAND;noitacilperAND54310 recJMED152noitadargedAND;esaelcunoxecfiiceps-AND-dednarts-elgniS01970 recNMED152NceRnietorpriaperAND95231 recOMED152OceRnietorpnoitanibmoceR00501 recRMED152RceRnietorpnoitanibmoceR06540 ruvAMED152noitanibmocerAND;AvuResacilehAND09660 ruvBMED15210285,MED152 noitanibmocerAND;BvuResacilehAND42421 ruvCMED152noitanibmocerAND;CvuResaelcunobiryxoedodnE42021 MED15200210,MED15201115,MED15202515,MED15204860, MED15207400,MED15209890 DNArecombination cinAMED152AniCnietorpelbicudni-egamadAND/ecnetepmoC58930 MED15200230,MED15202730,MED15205735,MED15207035, MED15209645 DNAbindingprotein polAMED152IesaremylopAND50101 holAMED152tinubusatled,IIIesaremylopAND57600 dnaAMED152AanDnietorprotaitininoitacilperlamosomorhC40431 dnaBMED152esacilehANDevitacilperBanD58910 dnaEMED15207245,MED152 tinubusahpla,IIIesaremylopAND41811 dnaGMED152esamirpAND47011 dnaNMED152tinubusateb,IIIesaremylopAND07640 dnaQMED15201490,MED15205060,MED152 tinubusnolispe,IIIesaremylopAND45711 dnaXMED152uat/ammagtinubus,IIIesaremylopAND54030 holBMED152tinubus’atled,IIIesaremylopAND09190 ligAMED152tnedneped-DAN,esagilAND45431 topAMED152IesaremosiopotAND48211 excMED152IIIesaremosiopotAND55510 parCMED152Atinubus,VIesaremosiopotAND09510 parEMED152Btinubus,VIesaremosiopotAND58510 gyrAMED152Atinubus,esarygAND09740 gyrBMED152Btinubus,esarygAND93121 ssbMED15209160,MED152 nietorpgnidnib-ANDdednarts-elgniS53690 rnhBMED152IIHesaelcunobiR59950 MED152ylimafgnR/enR,esaelcunobiR55690 mfdMED152rotcafgnilpuocriaper-noitpircsnarT04701 dcmMED152noitacfiidom/noitcirtser;esarefsnartlyhtem-)-5-enisotyc(AND58370 ogtMED152esarefsnartlyhtemsyCnietorp-ANDdetalyhteM07670 MED152esarefsnartlyhtemANDeninauglyhtem-O-604390 MED152esacileH02970 cspDMED15201260,MED15202750,MED152 nietorpgnidnib-AND’kcohs-dloC’55660 MED15201310,MED15204910,MED15207835,MED15209660, MED15211354 Endonuclease/exonuclease/phosphatasefamilyprotein MED15200240,MED15201675,MED15201850,MED15202405, MED15202435,MED15202810,MED15203055,MED15203355, MED15207660,MED15208085,MED15210165,MED15213039 DEAD/DEAHboxhelicase MED15205340,MED15205350,MED152 emorhcotpyrc/esaylotohpAND50450 MED15212919,MED152 riapernoisicxe-esab;esalordyhXIDUN49131 Genome analysis of the PR-containing Polaribacter sp. MED152 84 Table S5. Distribution of the anaplerotic enzymes pyruvate and PEP carboxylases, as well as carbonate anhydrase in cultured marine heterotrophic bacteria that contain the proteorhodopsin gene Organism Genbank accession no. Genome size, bp Taxonomy Pyruvate carboxylase PEP carboxylase Carbonate anhydrase Polaribacter sp. MED152 2,967,150 Bacteroidetes Polaribacter irgensii 23-P AAOG00000000 2,745,458 Bacteroidetes Dokdonia sp. MED134 AAMZ00000000 3,301,953 Bacteroidetes Flavobacterium BAL38 AAXX00000000 2,806,989 Bacteroidetes Pelagibacter ubique HTCC1002 AAPV00000000 1,328,618 Alphaprot. Pelagibacter ubique HTCC1062 CP000084 1,308,759 - Octadecabacter antarcticus 307 Moore F. 4,909,025 Alphaprot. - -059,261,600000000CHBA991LAB Methylophilales HTCC2181 AAUX00000000 1,304,428 Betaprot. Vibrio harveyi ATCC BAA-111 CP000789 6,058,377 Vibrio -.torpammaG412,961,500000000JOAA41S.ps -.torpammaG926,529,300000000TVAA3412CCTH --.torpammaG078,026,200000000IPAA7022CCTH Photobacterium sp. SKA34 AAOU00000000 4,991,572 Gammaprot. Marinobacter sp. ELB17 AAXY00000000 4,928,595 Gammaprot. The presence of the proteorhodopsin gene is based on hits against PF01036. Further, only those peptides that contained an Asp85 and Asp96, oradifferent carboxylate residue, were considered (Asp85 and Asp96 functions as the H acceptor and donor, respectively, during the rhodopsin photocycle in the H pump type of rhodopsins). Number of pluses indicates the number of genes withthe same putative function. Pyruvate carboxylase (EC 6.4.1.1) catalyzes the following reaction: pyruvate ATP HCO 3ADP phosphate oxaloacetate. PEP carboxylase (EC 4.1.1.31) catalyzes the reaction: PEP HCO 3H 2 O phosphate oxaloacetate. Carbonate anhydrase (EC 4.2.1.1) catalyzes the reaction: HCO 3CO 2 H 2 O. AANA00000000 - - - - - - - -- - Alphaprot. Alphaprot. .torpammaG Chapter 1 85 Table S6. Domains and peptides withaputative role in light absorption and response noitcnuFsFROeditpep/niamoD Light sensing 251DEMnoigeremorhcotyhP asierohpomorhc;rosnesthgilder-rafdnadeR00100 linear tetrapyrrole bound viaaCys residue 251DEMsniamodCAPdnaSAP 00100, MED152 03150, MED152 04250, MED152 06325 Flavin-binding; component of phytochromes; sensor of oxygen, redox and light 251DEMniamodFAG 00100, MED152 02465, MED152 03150, MED152 05910, MED152 11204 Binds small-molecules (cAMP or cGMP) that act as second messengers; component of phytochromes DNA photolyase/cryptochrome, animal cryptochrome and (6–4) photolyase family MED152 foshtgnelevawtrohssesnes;gnidnib-nivalF05350 visible light Cryptochrome, DASH family foshtgnelevawtrohssesnes;gnidnib-nivalF04350 visible light Deoxyribodipyrimidine photo-lyase, class I foshtgnelevawtrohssesnes;gnidnib-nivalF50450 visible light 251DEMniamodFULB rosnesthgileulb;gnidnib-nivalF06980 Synthesis of -carotene Isopentenyl-diphosphate delta-isomerase ( idi) MED152 fosisehtnyS50630 -carotene from isopentenyl diphosphate and dimethylallyl diphosphate Farnesyl-diphosphate synthase ( ispA) MED152 07135 or MED152 08510 Geranylgeranyl diphosphate synthase ( crtE) MED152 07135 or MED152 08510 Phytoene synthase ( crtB 251DEM) 02670 Phytoene desaturase ( crtI 251DEM) 02575 or MED152 02675 Lycopene -cyclase (crtY 251DEM) 02660 15,15’- -Carotene dioxygenase ( blh) MED152 morflaniterfosisehtnysehtnipetslaniF94821 -carotene Synthesis of proteorhodopsin apoprotein 251DEMnispO 12844 Additional carotenoids Spheroidene monooxygenase ( crtA) MED152 02580 Methoxyneurosporene dehydrogenase ( crtD) MED152 02575 or MED152 02675 -Carotene hydroxylase ( crtZ) MED152 02565 or MED152 02665 Synthesis of zeaxanthin from ß-carotene MED152 MED152 Table S5. Distribution of the anaplerotic enzymes pyruvate and PEP carboxylases, as well as carbonate anhydrase in cultured marine heterotrophic bacteria that contain the proteorhodopsin gene Organism Genbank accession no. Genome size, bp Taxonomy Pyruvate carboxylase PEP carboxylase Carbonate anhydrase Polaribacter sp. MED152 2,967,150 Bacteroidetes Polaribacter irgensii 23-P AAOG00000000 2,745,458 Bacteroidetes Dokdonia sp. MED134 AAMZ00000000 3,301,953 Bacteroidetes Flavobacterium BAL38 AAXX00000000 2,806,989 Bacteroidetes Pelagibacter ubique HTCC1002 AAPV00000000 1,328,618 Alphaprot. Pelagibacter ubique HTCC1062 CP000084 1,308,759 - Octadecabacter antarcticus 307 Moore F. 4,909,025 Alphaprot. - -059,261,600000000CHBA991LAB Methylophilales HTCC2181 AAUX00000000 1,304,428 Betaprot. Vibrio harveyi ATCC BAA-111 CP000789 6,058,377 Vibrio -.torpammaG412,961,500000000JOAA41S.ps -.torpammaG926,529,300000000TVAA3412CCTH --.torpammaG078,026,200000000IPAA7022CCTH Photobacterium sp. SKA34 AAOU00000000 4,991,572 Gammaprot. Marinobacter sp. ELB17 AAXY00000000 4,928,595 Gammaprot. The presence of the proteorhodopsin gene is based on hits against PF01036. Further, only those peptides that contained an Asp85 and Asp96, oradifferent carboxylate residue, were considered (Asp85 and Asp96 functions as the H acceptor and donor, respectively, during the rhodopsin photocycle in the H pump type of rhodopsins). Number of pluses indicates the number of genes withthe same putative function. Pyruvate carboxylase (EC 6.4.1.1) catalyzes the following reaction: pyruvate ATP HCO 3ADP phosphate oxaloacetate. PEP carboxylase (EC 4.1.1.31) catalyzes the reaction: PEP HCO 3H 2 O phosphate oxaloacetate. Carbonate anhydrase (EC 4.2.1.1) catalyzes the reaction: HCO 3CO 2 H 2 O. AANA00000000 - - - - - - - -- - Alphaprot. Alphaprot. .torpammaG Genome analysis of the PR-containing Polaribacter sp. MED152 86 Table S7. Distribution of putative light sensors in proteorhodopsin-containing marine bacteria (as defined in Table S5) emorhcotyhPFULBmsinagrO Animal cryptochrome and (6–4) photolyase family Cryptochrome, DASH family Photolyase, class I Polaribacter sp. MED152 Polaribacter irgensii 23-P - - Dokdonia sp. MED134 Flavobacterium BAL38 P. ubique ----2001CCTH P. ubique ----2601CCTH Octadecabacter antarcticus 307 - - - ---1812CCTHselalihpolyhteM Vibrio harveyi ATCC BAA-1116 Vibrio --41S.ps --3412CCTH ---7022CCTH Photobacterium sp. SKA34 Marinobacter sp. ELB17 - - Presence o�light sensors are predicted by hits to specific PFAMs or TIGRFAMs. DNA photolyase/cryptochrome subfamilies are based on phylogenetic analysis as in Fig. S6, as well as on custom-built PFAMs. Of 80 Moore genomes, 30 contain at least one BLUF domain, 18 contain at least one phytochrome domain, and 12 contain three cryptochrome/photolyase peptides (most contain one or two and no other contain four cryptochrome/photolyase peptides). - - - - - - Chapter 2 95 organism would grow optimally attached to particles or other surfaces where it could move by gliding motility searching for polymeric substances, and degrade them using its large array of peptidases and glycoside hydrolases. When labile organic matter were exhausted on a particle, Polaribacter would be forced to float passively in the nutrient poor water column in search of another particle. Under these conditions, it would use light to obtain energy and, thus, optimize the use of whatever little organic matter it could find. The genome of another marine flavobacterium, Dokdonia sp. MED134 (González et al., 2011), suggests that this PRcontaining bacterium has similar characteristics to those of Polaribacter. Several more genomes have been sequenced since these studies were published and it should now be possible to test whether the assumed role of Bacteroidetes as degraders of polymers can be confirmed. We also wanted to check wether the strategy proposed for Polaribacter holds with other PR-containing bacteria. In this paper we present a comparative genome analysis using the available genomes of marine Bacteroidetes but focusing on four cultured coastal Bacteroidetes strains, Gramella forsetii KT0803 from the North Sea, and Polaribacter sp. MED152, Dokdonia sp. MED134 and Leeuwenhoekiella blandensis MED217 from the Mediterranean Sea. Polaribacter and Dokdonia have a gene coding for proteorhodopsin (PR) while the other two do not. We analyzed which genetic features identified in Polaribacter are restricted to PR-containing bacteria (around 15 genomes), which ones are common to marine Bacteroidetes (21 genomes), and which ones are present in all Bacteroidetes (28 genomes). Comparative genomics of marine Bacteroidetes 96 MATERIAL AND METHODS Isolation of Bacteroidetes Polaribacter sp. MED152, Dokdonia sp. MED134 and L. blandensis MED217 were isolated in 2001 from Northwest Mediterranean Sea surface water (0.5 m depth) collected 1 km off the coast at the Blanes Bay Microbial Observatory (BBMO, http://www. icm.csic.es/bio/projects/icmicrobis/bbmo/), Spain (41o 40’ N, 2o 48’ E). All three were isolated on ZoBell agar plates. Gramella forsetii KT0803 was isolated in 1999 in the North Sea surface water (1 m depth) collected 1 km off the coast of the island of Helgoland, Germany (54o 09’ N, 7o 52’ E). It was isolated on MPM medium plates (Schut et al., 1993). Genome sequencing and assembly Whole-genome sequencing of Polaribacter sp. MED152, Dokdonia sp. MED134 and L. blandensis MED217 was carried out by the J. Craig Venter Institute through the Gordon and Betty Moore Foundation initiative in Marine Microbiology. A Sanger/pyrosequencing hybrid method was used (Goldberg et al., 2006). The complete genome sequence of Polaribacter sp. MED152 contained 30,151 reads, with an average of 9.6-fold sequence coverage and has been described in González et al. (2008). The complete genome sequence of Dokdonia sp. MED134 contained 33,882 reads, with an average of 9.8-fold sequence coverage (González et al., 2011). The complete genome sequence of L. blandensis MED217 contained 47,494 reads, with an average of 10-fold sequence coverage. Sequencing of Gramella forsetii KT0803 was carried out at the Max Planck Institute for Molecular Genetics (Berlin). It consists of 64,653 high quality reads with 9.8-fold sequence coverage and has been described in (Bauer et al., 2006). Gene prediction and annotation Data mining was carried out with GenDB v2.2 (Meyer et al., 2003), supplemented by the tool JCoast (Richter et al., 2008). For each predicted ORF observations were collected from similarity searches against sequence databases NCBI-nr, Swiss-Prot, KEGG and genomes DB (Richter et al., 2008), and for protein databases Pfam (Finn et al., 2008) and InterPro (Hunter et al., 2009). SignalP was used for signal peptide predictions (Bendtsen et al., 2004) and TMHMM for transmembrane helix-analysis (Krogh et al., 2001). The annotation of Polaribacter sp. MED152 (González et al., 2008), Gramella forsetii KT0803 (Bauer et al., 2006), and Dokdonia sp. MED134 (González et al., 2011) genomes was manually curated and refined for Chapter 2 97 each ORF, while the L. blandensis MED217 genome remains automatically annotated. Comparative analysis Comparative analysis and data mining were carried out using JCoast (Richter et al., 2008). Paralogous protein families within each of the four genomes were identified by BLASTP (Altschul et al., 1990) all-against-all similarity comparisons at a significance cut-off level of 10-10. Extracted proteins were grouped into families and functional proteins were classified according to Pfam and Cluster of Orthologous Genes, COG (Tatusov et al., 1997). Comparison of the shared gene content by reciprocal best matches (RBMs) Determination of the shared gene content was done by a pair-wise BLASTp all versus all search between investigated organisms. Reciprocal best matches were counted by a BLASTP result with an expectation values of E<10-5 each, and a subject coverage of over 65%. Searching for genes and domains in the genomes Signal transduction proteins, transporters, domains related to surface adhesion and other genes needed for comparison were found using the Pfam search included in JCoast (Richter et al., 2008), with a threshold of E≤10-4. Phylogenetic analysis Maximum likelihood trees were constructed with full-length 16S rRNA sequences from forty-seven completed genomes of Bacteroidetes. After the alignment of these sequences using SINA Aligner offered by the Silva database (Pruesse et al., 2007), the poorly aligned positions and divergent regions of the alignment were eliminated with the computer program Gblocks (Castresana 2000). The trees were constructed using RAxML server (Stamatakis et al., 2008) with the GTR nucleotide substitution model. The online tool Interactive Tree of Life (iTOL) (Letunic and Bork 2007, 2011) was used for editing and presentation of the tree. Accession Numbers The complete Gramella forsetii KT0803 sequence is available under GenBank accession number CU207366. Polaribacter sp. MED152, Dokdonia sp. MED134 and L. blanden- Comparative genomics of marine Bacteroidetes 98 Table 1. General features of the four Bacteroidetes genomes analyzed. a Manually annotated genome published in González et al. (2008) b Manually annotated genome published in González et al. (2011) c Manually annotated genome published in Bauer et al. (2006) d Bacterium described in Pinhassi et al. (2006). The automatically annotated genome is available in GenBank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and genome size The basic properties of the four genomes are shown in Table 1. Several tables in supplementary information summarize a comparison of the genes or domains identified in the four genomes concerning nitrogen, phosphorous, or sulfur acquisition (Suppl. Tables 1, 2 and 3), sodium transporters (Suppl. Table 4), oneand two-component systems (Suppl. Tables 5 and 6), adhesion (Suppl. Table 7), paralogous families (Suppl. Table 8), and clusters of polymer degradation genes (Suppl. Table 9). sis MED217 sequences are available under GenBank accession numbers AANA00000000, AAMZ00000000 and AANC00000000, respectively. : Chapter 2 99 ! !"#$%&' ()*+*,' !"#%,-' !"#%.$' !"#$%&' ! "#""! #$%&! #'(#! ()*+*,' ! ! #%%%! #)$"! !"#%,-' ! ! ! #')"! Table 2. Genes shared between each pair of the four Bacteroidetes genomes analyzed based on reciprocal best matches. Figure 1. Percentage of genes in paralogous families versus genome size for a number of bacteria. The four PR-Bacteroidetes genomes smaller than 2Mb correspond to endosymbionts of arthropods. The four genomes ranged in size between 2.97 and 4.24 Mb (Table 1). The two bacteria without PR (PRfrom now on) had larger genomes (G. forsetii and L. blandensis) than the two with PR (PR+ from now on). The four genomes were compared pairwise by reciprocal best matches. The two larger genomes shared 2122 orthologous genes while the two smaller genomes shared 1762 (Table 2). In all cases, shared genes accounted for between 50 and 59% of the genome. There were at least three reasons why two of the genomes were larger. First, they had more paralogous families and a larger percent of genes in such families (Table 1 and Fig. 1). Gene duplication and subsequent modifications to carry out novel functions by paralogous proteins is a well-known mechanism of bacterial evolution (see a recent review in Andersson et al., 2009). Comparative genomics of marine Bacteroidetes 100 Second, the larger genomes also had more transposases and at least one conjugative transposon (Table 1). In effect, we tested the presence of genomic islands (GIs) in a large set of marine bacteria (Fernández-Gómez et al., submitted) with the software IslandViewer (Languille and Brinkman 2009, Languille et al., 2010), and the MED217 genome had eight, three of them larger than 9.5 kb with a total of 70.5 kb, representing 1.18% of the genome. Gramella forsetii had five GIs with a total of 105 kb)MED134 and MED152, on the other hand, only had two and one GIs (with a total of 39 kb and 12 kb respectively). Some of the genes present in MED217 and missing in the two smaller genomes were actually located within genomic islands. Thus, missing areas labeled A to H in Figure 2A corresponded to genomic islands detected in MED217 (Fig. 2B). Genomic island H, for example, had integrases and transposases at both ends of the island, and CRISPRs at one end. The latter are repetitive palindromic sequences that, in association with genes cas7, cas5 and two cas3 (also present), serve a defensive function against phages and can be mobilized by horizontal gene transfer (HGT) (Haft et al., 2005). Most of the annotated genes within the island coded for hypothetical proteins (up to 55% of the genes within GIs) as previously reported for other marine bacteria (Hsiao et al., 2005). However, a regulatory sigma factor and a putative nitrite reductase were also found in the H genomic island of MED217. Interestingly, a nitrite reductase has been found in the deep-sea marine flavobacterium Zunongwangia profunda SM-A87 (Qin et al., 2010). A comparison between the nitrite reductases of MED217 and Zunongwangia showed a low percentage of amino acid identity (24%). Actually, the best hits of the MED217 nitrite reductase sequence were against gammaproteobacterial proteins genes, suggesting a HGT origin of this function in MED217 (data not shown). The coincidence of GIs with genes absent from the smaller genomes indicates that one of the mechanisms responsible for the differences in size among the genomes was HGT. Third, some genes were present in the larger genomes that code additional functions absent from the smaller ones. The area labeled Z in Fig. 2, for example, was present in the two large genomes and absent from both small genomes, but it did not coincide with any GI. The genes in this area were mostly involved in the metabolism of sugars, particularly arabinose (Fig. 3): they included the three structural genes of the arabinose operon (araA, araD, and araB, that are responsible for converting arabinose into D-xylulose-5P), galM (codes an epimerase capable of interconverting Land Darabinose as well as other sugars), and a few genes also related to sugar metabolism, including a sodium/glucose co-transporter. Presence of these genes should allow the bacterium to use arabinose by converting it to D-xylulose-5P, which is then transformed into D-ribulose-5P by a widely distributed enzyme (pentose-5phosphate 3-epimerase) and can then enter the pentose phosphate pathway (present in the four genomes). In effect, when utilization of arabinose was experimentally tested with the Chapter 2 101 Figure 2. The blue ring shows the genome of Leeuwenhoekiella blandensis MED217 ordered from 0 to 4.24 Mb. The next outer ring shows the G+C content along the genome. The outermost ring shows the areas identified as genomic islands with the IslandViewer software. Red, blue, and yellow indicate the three different tools used for island prediction in this package. The inner colored rings are the genomes of Dokdonia sp. MED134, Polaribacter sp. MED152, and Gramella forsetii compared to that of MED217. Each one of these genomes has been compared to that of MED217 by reciprocal best matches and, whenever a match was found, the gene of these genomes was placed next to the position of MED217 best match. That is, these three genomes do not keep their original topology so that genomes can be compared gene to gene. The letters A to H indicate genes present in MED217 and absent from some or all the other genomes, that were identified as genomic islands. Rectangle labeled Z and double arrow labeled W show areas in MED217 that were absent from some of the other genomes, but were not genomic islands. Comparative genomics of marine Bacteroidetes 102 Figure 3. Genes identified in section Z of the Leeuwenhoekiella blandensis MED217 genome. They include the structural genes of the arabinose operon (red), plus other genes involved in sugar metabolism (blue and green) and transport (yidK). three MED strains, MED217 could use arabinose while the two other bacteria could not (O. I. Nedashkovskaya, personal communication). The region labeled W is quite extensive and most of it is missing in the other three genomes. This region contained approximately 218 ORFs, about half of these were hypothetical proteins and 25 more were only identified putatively. Among the remaining ORFs the number of genes involved in sugar metabolism was remarkable. For example, four copies of beta-galactosidase, one arabinosidase and several regulatory proteins including two of the arabinose operon were found. This suggests that MED217 is capable of utilizing a large number of sugars that the other three are not. The lack of genomic islands, the absence of certain metabolic pathways, and the reduced number of paralogous families and genes within such families, are three important mechanisms accounting for the reduced size of the genomes of the PR+ Bacteroidetes. Chapter 2 103 Whether the PR+ genomes have experienced streamlining or whether, on the contrary, the PRgenomes have increased in size cannot be determined. However, it is remarkable that all the Bacteroidetes PR+ genomes are small. The percentage of genes in paralogous families followed the well-known (Pushker et al., 2004; Woyke et al., 2009) linear relationship with genome size for a large selection of bacteria (small dots corresponding to “other” bacteria in Fig. 1). The seven PR+ Bacteroidetes (yellow triangles) had genomes smaller than the around 50 PRBacteroidetes (pink triangles). Among the eight PR+ Proteobacteria (pink circles), only the Pelagibacter-like genomes were smaller than those of the PR+ Bacteroidetes, while other PR+ Proteobacteria (e.g Gammaproteobacteria) had larger genomes. The number of known PR+ marine bacteria is still very low and this pattern needs to be confirmed with more genomes. However, the environmental Bacteroidetes genomes MS024-2A and MS0243C also followed this trend (see the two smallest genomes labeled as PR+ Bacteroidetes in Fig. 1): they had the PR gene and their genomes were estimated to be smaller than that of Polaribacter sp. MED152, adding strength to the argument of PR+ Bacteroidetes having small genomes. It is tempting to conclude that possession of PR allows bacteria to reduce their genomes. Perhaps the extra mechanism for energy conservation allows the cells to be less versatile in their carbon source preferences. In other words, they may not need to carry the genes for many different carbon utilization pathways because light energy makes them more independent from organic compounds as energy sources. The small number of transporters is consistent with this idea. Unlike the PR+ Bacteroidetes, the PR+ Gammaproteobacteria varied more widely in their genome sizes (Fig. 1). It has been suggested that PR plays several roles in different marine bacteria (Fuhrman et al., 2008; DeLong and Béjà 2010). So far, higher cell yields in the light than in the dark have been demonstrated only in Dokdonia sp. MED134 (Gómez-Consarnau et al., 2007; Kimura et al., 2011) and in Polaribacter sp. MED152 (Férnandez-Gómez et al., in preparation). Enhanced growth in the light has not been seen in Pelagibacter (Giovannoni et al., 2005) or in Gammaproteobacteria (Stingl et al., 2007). On the other hand, the usefulness of PR under starvation conditions has been demonstrated in one Gammaproteobacteria (Gómez-Consarnau et al., 2010) and in Pelagibacter (Steindler et al., 2011). So far, the two Bacteroidetes mentioned are the only bacteria that have been found to show higher growth yields more in the light than in the dark under low carbon concentration conditions. Comparative genomics of marine Bacteroidetes 104 Figure 4. Phylogenetic tree of the Bacteroidetes emphasizing the marine bacteria (blue), those with the whole genome sequenced (green), with PR (red) and those belonging to the culture collection from the Blanes Bay Microbial Observatory (yellow). 1 00 1 00 Complele Genome PR+ ME D slrain Marine microorganism Fla v obacleria baclerium MSO¿4·JC ····· ,---- Fla v obacleriales baclerium HTCCmO _ Robiginilalea bilormala HTCC¿50l · .... ...... ...... ....... ....... ...... _ Leeuwenhoekiella aequorea .. ..... . ...... • II ! Leeuwenhoekiella blandensis MED217 _ .- - Gramella s~. MEDJol 100 Gramella forse6i KT~~~3 .................................. ... _ Aquimarina inlermedia . Dokdonia s~. MEDJ¿9 ... 1 00 Krokinobacler diaphorus 4 -J-ó 11 Dokdonia donghaensis sir. D SW-l ...................................................................................................... • Dokdon ia donghaensis sir. DSW - ¿l .................................................................................................. • Dokdonia donghaensis sir. PR 095 ............................................. ... _ Krokinobacler genikus . Dokdonia sp , MED134 .... ... - - - -1 ,---- Psychroflexus lorquis _ L-__ Flavobacleria baclerium BBFll ................................................................................................ • F lavobacleriaceae baclerium lPK5 ... ....... .... ...... ... ...... .... ...... ... ...... .... ..... ..... ... ....... ... ...... .... ..... .... • Gaelbulibacler saemankumensis ......................................................................................... • Fla v obacleriaceae baclerium Al Cl _ Biz io nia parago~iae .... ...... ...... • ~-F lavobacleria baclerium MSO¿4 - LA ... . _ _ _ L--- KorrJiaalgicidaOT -1 ................................................................................................. _ Fl avobacleria baclerium BU Fla v obaclerium johnsoniae UW 10l .................................................................. • F lavobaclerium psychrophilum JIPOV~o ........................................................... _ Tenacibaculum aesluarii SMK -4 .... ...... ... ...... .... ...... ... ....... ... ..... ... ....... ... ...... .... ...... .. • Polaribaclerw M E D50~ 1 00 PolaribaclerdokdonensisDSW.5 .............................................................................. • Marine baclerium JlS lO • ! Polaribactersp, MED152 ... - - -._1 Po laribaclers~ . P ICOoJ ............................................................................. • Polaribacler franzmannii • Po laribacler irgensH ¿J R _ _ _ Polaribacler glomeralus . Polaribacler filamenlus ............................................................................. • '----- Croceibacler a tl anlicus sir. HTCC¿559T. ........................................................................................................... _ Bacleroides fragilis YCH40 ................................................................................. • 1 Bacleroides fragilis NCTC 9J4J ........................................................................... • Bacleroides Ihela i olaom i cron V PI - 54~2 .. ..... ..... .... .... ...... .... ...... ... ....... ... ..... .... • L-- __ Baclero i des vul galus AT CC M~¿ .... ..... • L_____ Porphyromonas gingi v alis W~J ........................................................................ • .------- Microscilla marina ATCC¿J1J4 ..................................................................................... _ L------- C~ophaga hulchinsonii ATCC JJ400 ................................................................... • L__________ SpirosomalingualeDSMl4 . . ... . _ alinibacler ruber DSM1J~55 : : : L---------- -;; l oo ¡-----------1SalinibaclerruberM8 .... --- no! FLAVOBACTERIA BACTEROIDIA SPHINGOBACTERIA Chapter 2 111 Figure 8. Numbers of different enzymes per megabase of genome for a selection of bacteria: Marine Bacteroidetes (orange) Polaribacter sp. MED152, Dokdonia sp. MED134, Gramella forsetii, and Leeuwenhoekiella blandensis MED217; Bacteroides thetaiotaomicron (pink); Rhodopirellula baltica (maroon); the Alphaproteobacteria (yellow) Pelagibacter ubique and Ruegeria pomeroyi; and the Gammaproteobacteria (green) Idiomarina loihiensis and Vibrio parahaemolyticus. The marine Bacteroidetes also had two to three times more glycosyl transferases per Mb than the Proteobacteria (with the exception of P. ubique, Fig. 8B). These proteins are usually positioned in the outer membrane and generate polysaccharides for e.g., attachment. Altogether, this clearly indicates that attachment to particles is an important feature of marine Flavobacteria in general (independently of possession or absence of PR), while this is not the case for common planktonic Proteobacteria such as Pelagibacter, Ruegeria, or Vibrio. Flagella are not commonly used to move on surfaces (Jarrell and McBride 2008). Most motile bacteria living on surfaces use gliding motility, a name that actually includes several different molecular mechanisms of movement on surfaces (Jarrell and McBride 2008). The four marine Flavobacteria had the full complement of 15 genes for gliding motility. Moreover, the three MED strains were shown to have gliding motility under the microscope (O. I. Nedashkovskaya, personal communication). Again this is a characteristic common to many marine Flavobacteria and it is not specific of PR+ species. Comparative genomics of marine Bacteroidetes 112 Polymer degrading enzymes: Peptidases and Glycoside hydrolases Our analysis showed that, in general, the number of peptidases and glycoside hydrolases (GH) increased with the size of the genome in all bacteria (Fig. 9A and C). Most Bacteroidetes, however, tended to have more of these enzymes than the average bacterium, irrespectively of the genome size (Fig. 9). This is one of the major observations that indicates the dedicated role of marine Bacteroidetes as polymer degraders. Marine Flavobacteria had more GHs per Mb than other planktonic bacteria (Fig. 9D). The difference was statistically significant. Dokdonia sp. MED134 had a lower number of GHs, similar to those of V. parahaemolyticus and R. baltica, but still higher than those of other planktonic bacteria such as Pelagibacter, Ruegeria or Idiomarina (Fig. 8D and 9D). B. thetaiotaomicron had the largest number of GHs per Mb in accordance with its specialization on polysaccharide degradation in the Figure 9. A. Number of peptidases versus genome size. B. Peptidases per Mb of genome. C. Glycoside hydrolases versus genome size. D. Glycoside hydrolases per Mb. PR+ Bacteroidetes are in purple, PRBacteroidetes in blue. Chapter 2 113 Figure 10. Peptidases or glycoside hydrolases per Mb for marine and non-marine Baceroidetes. vertebrate digestive tract. In the case of peptidases, the marine Flavobacteria had the largest numbers of genes per Mb (Fig. 8C and 9B). Again, the difference between Bacteroidetes and other marine bacteria was also significant. Moreover, the PR+ Bacteroidetes had significantly larger numbers of peptidases per Mb than PRBacteroidetes. As expected, B. thetaiotaomicron had a lower number of peptidases, since it is a polysaccaride specialist (Martens et al., 2009). The relatively high number of peptidases per Mb in P. ubique is remarkable, especially combined with its low number of GHs, suggesting a preference for proteins over polysaccharides. Finally, the gammaproteobacterium Idiomarina loihiensis also had a large number of peptidases per Mb, in accordance with its putative specialization in the fermentation of aminoacids and proteins (Hou et al., 2004). In summary, marine Flavobacteria had a relatively large complement of both GHs and peptidases compared to other marine bacteria and, moreover, they had as many peptidases as other protein specialists. Another striking observation was that marine Bacteroidetes had many more peptidases than GHs (Fig. 10). This was not the case for the non-marine Bacteroidetes examined. This strongly suggests a specialization of marine bacteroidetes on the degradation of proteins. This is consistent with the experimental studies using microautoradiography, in which a preference for proteins has been demonstrated (Cottrell and Kirchman 2000). Gómez-Pereira et al. (2011) analyzed Bacteroidetes fosmids from two regions in the North Atlantic Ocean. They found many polysaccharide degrading enzymes in the phytoplankton rich polar waters and an abundance of protein degrading enzymes in the subtropical North Atlantic. More isolates from polar waters will have to be examined to see if the relationship in Figure 6 holds for all marine Bacteroidetes or only for those in temperate regions. Comparative genomics of marine Bacteroidetes 114 Figure 11. Diversity of peptidases (A) and glycoside hydrolases and sulfatases (B) in the four marine Bacteroidetes analyzed. A PEPTIDASES MED152 MED134 KT0803 MED217 B CARBOHYDRATE -ACTIVE ENZYMES (Glycoside hydrolases and sulfatases) MED152 MED134 KT0803 MED217 111 Zn _peptid as e_2 III Zn _pept ida se IIlV anY II Trypsin mTran sg lu t_cor e . S ubti li si n_N o Rh o mb oid .Pmb A_ TldD . PepX_C • Pepti dase _S9_N • Pe pt id ase_S9 • Pe ptida se_S8 • Pe ptid ase _S 66 O Pep tidase_S5 1 • Pe pti dase_S 41 O Pe ptid ase_S24 • Pe ptida se_S 15 O Pep tidase _S13 • Pep tidase _S 10 O Pe pti da se_ M61 • Pe pti dase_M 56 • Pepti dase_M 50 • Pepti dase _ M4 9 • Pep tid ase_ M48 • Pept idase_M42 • Pe pti dase _ M41 • Pepti dase _ M36 • Pe pt idase_M3 • Pep tid ase_M28 O Pep tidase _ M2 4 • Pe pt idase _ M23 I:I S LT • T re ha l ase o S ulf at ase O Pe ptida se_ M22 O Pe ptid ase_ M20 O Pe ptid ase_ M 19 O Pe ptida se_ M1 6_C O Peptidase_M 16 • Pept ida se _M 15 O Pe ptida se _M 14 O Pe ptid ase_ M 13 _N O Pept ida se_M 13 O Pept ida se _M 1 O P epti d ase_C26 O Pe ptid ase_ Cl4 O Pe pt idase_C1_2 O P epti d ase _A8 .NLPC_P 60 .M2 0_ dimer • Lo n_ C . LON OFTP DDUF 955 • DPPI V_ N • C LP _prot ease O B etaI acta m ase • B ac t_ tr ans glu _N o Astacin . AM P_N DAmi dase _3 DAmi dase_2 .AAT O Pepti dase _ Cl • Po l ysacc_deac_ 1 .OprB . l soamy l ase _ N • G l yco _ hydro _ 92 • G l yco _ h yd ro_ 88 • G l yco _ h yd ro _8 1 • G l yco _ h yd ro_ 65 N • G l yco_ h ydro_65 m • G lyco _ h yd ro_ 65C o G l yco _ h ydro _ 63 • G l yco _ hydro _ 53 1:1 G l yco _ h yd ro_ 43 o G l yco _ h yd ro_ 39 o G l yco _ h yd ro_ 35 o G l yco_ h ydro_32 N CJ G ly co _ h yd ro_ 32C • G l yco _ h ydro _ 31 o G l yco _ hydro _ 30 o G l yco _ h yd ro_ 3_ C o G l yco _ h ydro _ 3 o G l yco_ h ydro_28 o G l yco_ h yd r o_20b o G l yco _ h ydro _ 20 o G l yco _ h ydro _ 2_ N o G ly co _ h yd ro_ 2_ C • G l yco _ h ydro _ 2 • G l yco _ h ydro _ 16 . G l yco_ h yd r o_ 15 • G lu cosam in idase DD U F 377 D D U F 1 87 • DUF1 68 0 . Ce llul ase O CBM _ 6 . CB M_4 _9 o B gaLsma lL N • Bac _ rh a mn osid D A l phaL -A F _ C D A lph a-a m y l ase _ C • A lp haamy l ase e A lp ha _ L_ fucos Chapter 2 115 Despite these general characteristics, each one of the four bacteria showed a different suite of GHs and peptidases (Fig. 11). This indicates variations on a shared theme. Probably, in combination with other genes, these differences allow the various species to occupy slightly different niches. We calculated diversity indices for these enzymes and found that the four bacteria had very similar values. In the case of peptidases the indices varied between 3.57 and 3.68 and in the case of GHs between 2.82 and 3.20. These indices show that not only do these bacteria have more peptidases than GHs, but that there is a larger diversity of the former. Thus, the conclusion that protein degradation is the main specialty of marine Bacteroidetes is robust. 4. Families of paralogous genes A fruitful approach to ascertain the principal way of life of bacteria is to look at the main families of paralogous genes (Suppl. Table 8). The three largest families were the same for the four Flavobacteria: Two-component systems (between 30 and 54 genes), TonBdependent receptors (18-50), and ABC transporters (22-30). These numbers are in striking contrast to those of two common Proteobacteria such as E. coli or Ruegeria pomeroyi. The latter bacteria had ABC transporters as the largest family, followed by LysR one-component systems, and two-component systems in the third place. Moreover, the Bacteroidetes had twice the number of TonB dependent receptors per Mb than the Proteobacteria. These large differences are surely related to the different life styles of these bacteria. The Bacteroidetes had between one half and one third of the ABC transporters per Mb than Proteobacteria. This lower number of ABC transporters is in line with the generally low number of transporters for low molecular weight compouds that were found in the genomes of both Polaribacter and Dokdonia. This feature is now seen to be general to other marine Bacteroidetes. Finally, the abundance of TonB dependent receptors also suggests a specialization in degradation of polymers. In particular, the four bacteria have between 6 and 17 susC plus susD-like pairs of genes. In Bacteroides thetaiotaomicron, SusC is a member of the TonB receptor family specialized in the transport of oligosaccharides from the outer membrane into the periplasmic space. SusD, in turn, is necessary to bind polysaccharides to the outer cell membrane. These two genes alone are enough to account for 60% of the polysaccharide degrading ability of B. thetaiotaomicron (Martens et al., 2009). This is likely the role of the many susC plus susD pairs in the four Bacteroidetes. Moreover, these pairs are always next to genes encoding polymer degrading enzymes: sulfatases, amylases, glycoside hydrolases, Comparative genomics of marine Bacteroidetes 116 peptidases, and alkaline phosphatases among other enzymes (Fig. 12). In B. thetaiotaomicron there are 101 individual pairs of “susC-like” and “susD-like” genes, with the former always positioned immediately upstream of the latter. This bacterium is a polysaccharide specialist of the distal digestive tract of mammals and has a large genome of 6.26 Mb (resulting in 16 susC-susD pairs per Mb). In Flavobacterium johnsoniae, a soil organism specialized in degradation of polysaccharides, there are 50 TonB dependent receptors and 10 of these also have the susC plus susD combination (McBride et al., 2009). This represents only 1.7 pairs per Mb. In the four marine Bacteroidetes, with much smaller genomes, we found 5, 4, 17, and 21 such pairs in Polaribacter, Dokdonia, Leeuwenhoekiella, and Gramella respectively (1.7, 1.2, 4.5 and 5 per Mb respectively) (Suppl. Table 9). This is in line with the hypothesis of an adaptation to the use of polymers in the marine Bacteroidetes. Figure 12. Clusters of genes putatively involved in the attachment and degradation of polymeric compounds and containing TonB dependent/ligand-gated channel genes and SusD. One example from each of the four bacteria is shown. The complete list can be found in Suppl. Table 9. GH: Glycoside hydrolase; HP: Hypothetical protein; HK: Histidine kinase; RR: Response regulator. Chapter 2 117 CONCLUSIONS Analysis of the Polaribacter sp. MED152 genome suggested a dual life style (González et al., 2008): a) growth attached to particles degrading poymers and b) dispersal through the water column obtaining energy from light through proteorhodopsin. Each one of these two states was supported by a series of functions. The attached phase would require genes involved in adhesion, glycosyl transferases, gliding motility, a large number of peptidases and glycoside hydrolases for degradation of polymers, and SusC-SusD pairs for attachment and degradation of polymers. The free-living phase, in turn, would rely on proteorhodopsin, a large number of light sensing proteins, and an enhanced anaplerotic fixation of CO2. Our comparative study has shown that this whole complement of genes is shared with Dokdonia sp. MED134 but, interestingly, not by the close relative Polaribacter irgensii 23-P. The two characteristics shared by all known PR+ Bacteroidetes are small genome size and a higher number of genes involved in CO2 fixation per Mb than the PRBacteroidetes. Within the PR+ Proteobacteria, analysis of their genomes identified at least two different strategies corresponding to Pelagibacter-like bacteria on the one hand, and Gammaproteobacteria on the other. Independently of the presence or absence of PR, the marine Bacteroidetes share the capacity for adhesion and gliding motility, the presence of abundant glycosyl transferases, a large number of polymer degrading enzymes including glycoside hydrolases and, especially, peptidases, and a large relatively number of SusC-SusD pairs associated to many different degrading enzymes. This confirms the role of this abundant group of marine bacteria as degraders of particulate matter, especially of proteins. ACKNOWLEDGEMENTS B. F.-G. was a recipient of a I3P grant from CSIC. The genomes of the three MED strains were sequenced by the JCVI through the Marine Microbial Initiative of the Gordon and Betty Moore Foundation. We thank Thierry Lombardot for bioinformatic analysis. This work was supported by Grant “GEMMA” CTM2007-63753-C02-01/MAR from the Spanish Ministerio de Ciencia e Innovación. Comparative genomics of marine Bacteroidetes 118 REFERENCES Alonso C, Warnecke F, Amann R, Pernthaler J. (2007). High local and global diversity of Flavobacteria in marine plankton. Environ Microbiol 9: 1253-1266. Alonso-Sáez L, Gasol J. (2007). Seasonal variations in the contributions of different bacterial groups to the uptake of low-molecular-weight compounds in Northwestern Mediterranean Coastal waters. Appl Environ Microbiol 73: 3528-3535. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. (1990). Basic local alignment search tool. J Mol Biol 215: 403-410. Amaral-Zettler L, Artigas LF, Baross J, P.A. LB, Boetius A, Chandramohan D et al., (2010). A Global Census of Marine Life. In: Alasdair D. McIntyre, Ed. Life in the World’s Oceans. Blackwell Publishing Ltd., pp 223-245. Andersson DI, Hughes D. (2009). Gene amplification and adaptative evolution in bacteria. Annu Rev Genet 43:167-195. Bauer M, Kube M, Teeling H et al., (2006). Whole genome analysis of the marine Bacteroidetes Gramella forsetii reveals adaptations to degradation of polymeric organic matter. Environ Microbiol 8: 2201-2213. Bendtsen JD, Nielsen H, von Heijne G, Brunak S. (2004). Improved prediction of signal peptides: SignalP 3.0. J Mol Biol 340: 783-795. Castresana J. (2000). Selection of conserved blocks from multiple alignments for their use in phylogenetic analysis. Mol Biol Evol 17: 540-552. Cottrell MT, Kirchman DL. (2000). Natural assemblages of marine proteobacteria and members of the Cytophaga-Flavobacteria Cluster consuming Lowand High-MolecularWeight dissolved organic matter. Appl Environ Microbiol 66: 1692-1697. DeLong EF, Franks DG, Alldredge AL. (1993). Phylogenetic diversity of aggregate-attached vs. free-fiving marine macterial assemblages. Limnol Oceanogr 38: 924-934. Chapter 2 119 DeLong EF, Béjà O. (2010). The light-driven proton pump proteorhodopsin enhances bacterial survival during tough times. PLoS Biol 8: e1000359. Finn RD, Tate J, Mistry J, Coggill PC, Sammut SJ, Hotz H-R et al., (2008). The Pfam protein families database. Nucleic Acids Res 36: D281-D288. Fuhrman JA, Schwalbach MS, Stingl (2008). Proteorhodopsins: an array of physiological roles? Nat Rev Micro 6: 488-494. Giovannoni SJ, Tripp HJ, Givan S, Podar M, Vergin KL, Baptista D et al., (2005). Genome streamlining in a cosmopolitan oceanic bacterium. Science 309: 1242-1245. Glöckner FO, Fuchs BM, Amann R. (1999). Bacterioplankton compositions of lakes and oceans: a first comparison based on fluorescence in situ hybridization. Appl Environ Microbiol 65: 3721-3726. Goldberg SMD, Johnson J, Busam D, Feldblyum T, Ferriera S, Friedman R et al., (2006). A Sanger/pyrosequencing hybrid approach for the generation of high-quality draft assemblies of marine microbial genomes. Proc Natl Acad Sci USA 103:11240-11245. Gómez-Consarnau L, González JM, Coll-Lladó M, Gourdon P, Pascher T, Neutze R et al., (2007). Light stimulates growth of proteorhodopsin-containing marine Flavobacteria. Nature 445: 210-213. Gómez-Consarnau L, Akram N, Lindell K, Pedersen A, Neutze R, Milton DL et al., (2010). Proteorhodopsin phototrophy promotes survival of marine bacteria during starvation. PLoS Biol 8: e1000358. Gómez-Pereira PR, Schüler M, Fuchs BM, Bennke C, Teeling H, Waldmann J et al., (2011) Genomic content of uncultured Bacteroidetes from contrasting oceanic provinces in the North Atlantic Ocean. Environ Microbiol 14:52-66 Gómez-Pereira PR, Fuchs BM, Alonso C, Oliver M, van Beusekon J, Amann R. (2010). Distribution patterns and diversity of planktonic Flavobacterial clades in contrasting water masses of the North Atlantic Ocean. ISMEJ 4: 472-487 Comparative genomics of marine Bacteroidetes 120 Gónzalez JM, Fernández-Gómez B, Fernàndez-Guerra A, Gómez-Consarnau L, Sánchez O, CollLladó M et al., (2008). Genome analysis of the proteorhodopsin-containing marine bacterium Polaribacter sp. MED152 (Flavobacteria). Proc Natl Acad Sci USA 105:8724-8729. González JM, Pinhassi J, Fernández-Gómez B, Coll-Lladó M, González-Velázquez M, Puigbó P et al., (2011). Genomics of the proteorhodopsin-containing marine flavobacterium Dokdonia sp. MED134. Appl Environ Microbiol 77:8676-8686 Haft DH, Selengut J, Mongodin EF, Nelson KE. (2005). A guild of 45 CRISPR-associated (Cas) protein families and multiple CRISPR/Cas subtypes exist in prokaryotic genomes. PLoS Comput Biol 1: e60. Hou S, Saw JH, Lee KS, Freitas TA, Belisle C, Kawarabayasi Y et al., (2004). Genome sequence of the deep-sea gamma-proteobacterium Idiomarina loihiensis reveals amino acid fermentation as a source of carbon and energy. Proc Natl Acad Sci USA 101: 18036-18041. Hunter S, Apweiler R, Attwood TK, Bairoch A, Bateman A, Binns D et al., (2009). InterPro: the integrative protein signature database. Nucleic Acids Res 37: D211-D215. Jarrell KF, McBride MJ. (2008). The surprisingly diverse ways that prokaryotes move. Nat Rev Micro 6: 466-476. Kimura H, Young CR, Martínez A, DeLong EF. (2011). Light-induced transcriptional responses associatd with proteorhodopsin-enhanced growth i marine flavobacterium. ISMEJ 5: 1641– 1651 Kirchman D. (2002). The ecology of Cytophaga-Flavobacteria in aquatic environments. FEMS Microbiol Ecol 39: 91-100. Krogh A, Larsson Br, von Heijne G, Sonnhammer EL. (2001). Predicting transmembrane protein topology with a hidden markov model: application to complete genomes. J Mol Biol 305: 567-580. Langille MGI, Brinkman FSL. (2009). IslandViewer: an integrated interface for computational identification and visualization of genomic islands. Bioinformatics 25: 664-665. Chapter 2 127 !"#$%&"' ()*+,-' ()*+./' 01232.! ()*-+4' !"#$%&#"'(")*+,-%(#'./' -0"1#"+2"#' 34'567' 38'597' :8'5;<7' :9'567' =>#'?>&,#"#'./'-0"1#"+2"#' 3;'587' 3:'587' 34'587' 38'5@7' =/.(>A'-B%'C%1$%&"&-' #/#-"1#' 4'537' 4'537' 8'537' ;;'5:7' D%-,+'=>#'?>&,#"#' 3@'567' 39'567' :3'567' :9'567' 15$#6'' ,+' ,,' 78' 47' Table 5SM. Predicted number of two component histidine kinases and response regulators. Number is based on hits to specific PFAMs at the Microbial Signal Transduction Database (http://genomics.ornl.gov/mist/; E-value lower than 10-4). Number per megabase is shown between parentheses. Comparative genomics of marine Bacteroidetes 128 ! !"#$%&'()'*+,-' *"./".'0(#123-' 456789' 4567:;' <=>?>:! 45697@' "#"$%&'(! )%&'(!*'+,-.!/&012,34! 55! 56! 56! 57! 82&9!! ):;<=!*'+,-.!/&012,34! >! 5! ?! @! %A3($1&'3A$&2B! )%A3(C:&/!*'+,-.!/&012,34! D! >! >! >! 831=! )831=!*'+,-.!/&012,34! 6! 5! 5! 5! (&/! )(&/!*'+,-.!/&012,34! 5! 5! 6! D! "#"$5! E! E! 5! 5! "#"$D! F! F! 5D! 5>! "#"$>! 5! 6! D! D! "#"$F! 5! 5! 5! 5! "#"$55! 5! E! E! 5! :.1#=! >! 5! E! 5! G'&=! )G'&=!*'+,-.!/&012,34! 6! 6! D! @! G2&=! )G2&=!*'+,-.!/&012,34! 6! 6! 6! 6! H'I=! 6! 5! 5! E! #21=$J! )#21=!*'+,-.!/&012,34! 6! >! 6! @! #&'3A$&2B$(! E! 5! E! E! "K! 7! 7! L! ?! 8;'3.-'12$M.M! E! 5! 5! 5! =&*6! 5! 5! D! 5! A3/".B*"./".'0(#123-' ! ! ! ! :'MNOH2&,/-'$PH$5! ):'MN!*'+,-.!/&012,34! @! 5! @! ?! "#"$5O:.A=! :.A=!*'+,-.!/&012,3! D! 5! 5! 6! (&/OMJGH$Q,3I,3B! 5! 5! 6! 5! R2$I2$&2/&2AAOR2$I2/$&2/&$(! 5! 5! 5! 5! "#"$55OK20=! E! E! E! 5! "#"$%&'(OP:SR! 5! E! E! E! H%T$DO82&9! E! E! E! 5! =(.1C' D;' 8D' @:' ?7' Table 6SM. Detection of signal transduction proteins (one-component system) detected in the four Bacteroidetes (E-value ≤ 10-4). Chapter 2 129 !"#$%&'()'*+,-' .(#/01' 23.456' 23.478' 9:;<;7' 23.64=' ,/->0>?01' 6' 7' 7' 5' :@&(#$(-A(1B01'CDA%'7' &%A%/C' 4' 6' 6' 4' ,0$&(1%>C01'CDA%EEE'' 4' 7' 7' 4' ,FGFHI' 8' 8' 7' =' J/B@%&01' ;' ;' 4' ;' KL+' 6' 4' 8' ;' M/>N-"&)/>%NHO' <' <' 5' <' M0ON4' ;' ;' ;' ;' M0ON7' ;' ;' ;' ;' .(>P%&01N4' ;' ;' ;' ;' J(@%-01' ;' ;' ;' ;' ,5N,<N:DA%NJ' 7' 4' 4' 5' K%NIEF' ;' ;' 4' ;' !"#$%& '(& ''& ''& ')& Table 7SM. Genes and domains with a potential role in adhesion (E-value ≤ 10-4). Comparative genomics of marine Bacteroidetes 130 Table 8SM. The twenty most abundant paralogous families of the four Bacteroidets and two Proteobacteria (E-value ≤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hapter 2 131 Table 9SM. Clusters of genes putatively involved in the attachment and degradation of polymeric compounds for the four Bacteroidetes. Only those that contain the tandem TonB dependent/ligand-gated channel genes and SusD are represented. Notice the amount of genes involved in degradation, adhesion, carbohydrate metabolism, secretion and transport within the clusters. Cells with a minus sign have no Pfam assigned at E-value ≤ 10-4. Empty cells mean no information available. ORF MED152 Annotation Pfam domain Direction SigP TMHMM 109 Alpha-amylase Alpha-amylase ⇐yes 0 110 HP -⇐yes 0 111 HP -⇐no 0 112 Outer membrane protein SusD_RagD ⇐yes 0 113 TonB-dependent outer membrane receptor TonB_dep_Reg ⇐yes 0 114 Transcriptional regulator, LacI family Peripla_BP_1 ⇐no 0 115 Major Facilitator Superfamily MSF_1 ⇒no 11 116 ß-phosphoglucomutase Hydrolase ⇒0 117 Trehalase/maltose phosphorylase Glyco_hydro_65m ⇒0 118 N-acetylglycosamine-6sulfatase Sulfatase ⇒no 0 119 Alpha-amylase Alpha-amylase ⇒0 120 Putative esterase Esterase ⇒yes 0 121 Glycosyl hydrolase, family 31 Glyco_hydro_31 ⇒yes 0 122 Alpha-amylase Alpha-amylase ⇒no 0 123 Alpha-amylase Alpha-amylase ⇒yes 0 124 Conserved HP Y_Y_Y ⇒yes 1 125 TonB-dependent outer membrane receptor TonB_dep_Reg ⇒yes 0 126 Outer membrane protein SusD_RagD ⇒yes 0 127 Conserved HP -⇒no 0 128 HP -⇒yes 0 129 Conserved HP -⇒yes 0 130 Conserved HP -⇒0 131 Conserved HP -⇒no 0 132 Glycosyl hydrolase family 30 Glyco_hydro_30 ⇒yes 0 133 Major Facilitator Superfamily MSF_1 ⇒no 12 Comparative genomics of marine Bacteroidetes 132 1050 Major Facilitator Superfamily MSF_1 ⇐no 12 1051 Trehalase/maltose hydrolase Glyco_hydro_65m ⇐yes 0 1052 HP Cellulase ⇐yes 0 1053 Alpha-trehalase Trehalase ⇐0 1054 Sugar transporter MSF_1 ⇐no 12 1055 Sucrose transporter MSF_1 ⇐no 12 1056 Conserved HP -⇐no 0 1057 Conserved HP UnbV_ASPIC ⇐yes 0 1058 Conserved HP UnbV_ASPIC ⇐no 0 1059 HP -⇐yes 1 1060 Conserved HP UnbV_ASPIC ⇐no 0 1061 Outer membrane protein SusD_RagD ⇐yes 0 1062 TonB-dependent outer membrane receptor TonB_dep_Reg ⇐yes 1 1063 Conserved HP DUF1080 ⇐yes 0 1064 Conserved HP AP_endonuc_2 ⇐no 0 1065 Oxidoreductase GFO_IDH_MocA ⇐no 0 1066 HP Nuc_H_symport ⇐no 12 1067 Conserved HP AP_endonuc_2 ⇐yes 0 1068 Transcriptional regulator, AraC HTH_AraC ⇐0 1963 S-adenosylhomocysteine hydrolase AdoHcyase ⇒0 1964 Putative sulfite reductase -⇒yes 4 1965 Putative sodium/sulphate symporter Na_sulph_symp ⇒no 13 1966 Putative alginate lyase precursor -⇒no 0 1967 Putative alginate lyase precursor -⇒yes 0 1968 Gluconate lyase, SKI family SKI ⇒0 1969 6-phosphogluconate dehydrogenase 6PGD ⇒no 0 1970 Putative Mn+2 Fe+2 transporter Nramp ⇒yes 11 1971 Putative alginate lyase precursor -⇒no 0 1972 HP adh_short ⇒no 0 1973 HP -⇒yes 0 1974 HP Hepar_II_III ⇒no 0 1975 HP Cupin_2 ⇒0 Chapter 2 133 1976 TonB-dependent outer membrane receptor TonB_dep_Reg ⇒yes 0 1977 Outer membrane protein SusD_RagD ⇒no 0 1978 HP -⇒no 0 1979 HP PKD ⇒yes 1 1980 Transcriptional regulator, GntR FCD ⇒0 1981 Major Facilitator Superfamily protein MSF_1 ⇒no 11 1982 Short-chain dehydrogenase/ reductase adh_short ⇒no 0 1983 TonB-dependent outer membrane receptor TonB_dep_Reg ⇒yes 0 1984 Outer membrane protein SusD_RagD ⇒yes 0 2482 Putative tRNA/rRNA methyltransferase SpoU_methylase ⇐0 2483 HP -⇐no 0 2484 Outer membrane protein SusD_RagD ⇐yes 0 2485 TonB-dependent outer membrane receptor TonB_dep_Reg ⇐yes 1 2486 HP -⇐no 0 ORF MED134 Annotation Pfam domain Direction SigP TMHMM c1_1083 HP -⇐ c1_1084 HP Peptidase_M56 ⇐no 4 c1_1085 Transcriptional regulator Penicillinase_R ⇐0 c1_1086 Putative hydrolase Peptidase_M20 ⇐yes 0 c1_1087 Outer membrane protein SusD_RagD ⇐no 0 c1_1088 TonB-dependent outer membrane receptor TonB_dep_Reg ⇐yes 0 c1_1089 Putative hydrolase Peptidase_M20 ⇐yes 0 c1_1090 Probable aminopeptidase Peptidase_M28 ⇐yes 0 c1_1091 HP DUF1083 ⇐yes 0 c1_1092 HP -⇐yes 1 c1_1093 HP -⇐yes 0 c1_1094 HP -⇐no 2 c1_1095 UvrABC system protein A ABC_tran ⇐no 0 c2_32 TonB-dependent outer membrane receptor TonB_dep_Reg ⇒yes 1 c2_33 Outer membrane protein SusD_RagD ⇒yes 0 Comparative genomics of marine Bacteroidetes 134 c2_34 Putative multidrug resistance protein ACR_tran ⇐no 14 c2_35 Putative HlyD-like secretion protein HlyD ⇐yes 0 c2_36 Putative outer membrane efflux protein OEP ⇐yes 0 c2_37 Transcriptional regulator, TetR TetR_N ⇐0 c2_668 HP -⇐yes 0 c2_668 HP -⇐no 0 c2_670 HP MS_channel ⇐no 5 c2_671 HP Peptidase_M56 ⇐yes 3 c2_672 Putative antibiotic resistancerelated regulatory protein Penicillinase_R ⇐0 c2_673 Putative succinyldiaminopimelate desuccinylase Peptidase_M20 ⇐0 c2_674 2-keto-3-deoxy-6phosphogluconate aldolase Aldolase ⇐0 c2_675 2-dehydro-3deoxygluconokinase Pfk ⇐no 0 c2_676 Short-chain dehydrogenase/ reductase adh_short ⇐yes 0 c2_677 Putative hexuronate transport protein MSF_1 ⇐no 11 c2_678 Transcriptional regulator GntR family FCD ⇐0 c2_679 Putative lyase -⇐yes 0 c2_680 Cell surface protein PKD ⇐yes 0 c2_681 Outer membrane protein SusD_RagD ⇐yes 0 c2_682 TonB-dependent outer membrane receptor TonB_dep_Reg ⇐yes 1 c2_683 Putative pectin degradation protein Cupin_2 ⇐0 c2_684 Putative chondroitin AC/ alginate lyase -⇐no 0 c2_685 Putative chondroitin AC/ alginate lyase -⇐yes 0 c2_686 Putative chondroitin AC/ alginate lyase -⇐yes 0 c2_687 HP -⇐no 0 Chapter 2 135 c2_696 Putative two-component system sensor (hydrid) His_kinase ⇒no 4 c2_697 Response regulator receiver protein Response_reg ⇒0 c2_698 HP -⇒yes 0 c2_699 Putative carbohydrate kinase PfkB ⇐0 c2_700 Xylose transporter Sugar_tr ⇐no 12 c2_701 Glycoside hydrolase, family 32 Glyco_hydro_32N ⇐no 0 c2_702 Transcriptonal regulator, LacI Peripla_BP_1 ⇒no 0 c2_703 Beta-phosphoglucomutase Hydrolase ⇒0 c2_704 Trehalase/maltose hydrolase Glyco_hydro_65m ⇒0 c2_705 HP -⇐no 0 c2_706 HP Pentapeptide ⇐0 c2_707 HP AraC_E_bind ⇐no 1 c2_708 HP -⇐yes 0 c2_709 ASPIC-like protein UnbV_ASPIC ⇐no 0 c2_710 ASPIC-like protein UnbV_ASPIC ⇐no 0 c2_711 ASPIC-like protein UnbV_ASPIC ⇐yes 0 c2_712 Outer membrane protein SusD_RagD ⇐yes 0 c2_713 TonB-dependent outer membrane receptor TonB_dep_Reg ⇐yes 0 ORF KT0803 Annotation Pfam domain Direction SigP TMHMM 9Major Facilitator Superfamily permease Sugar_tr ⇒yes 12 10 Glycosyl hydrolase, family 32 Glyco_hydro_32N ⇒yes 0 11 TonB-dependent outer membrane receptor TonB_dep_Reg ⇒yes 0 12 Outer membrane protein SusD_RagB ⇒yes 0 13 Carbohydrate kinase PfkB ⇒no 0 14 Multidrug resistance protein Multi_Drug_Res ⇒no 0 15 Metal-dependent membrane protease Abi ⇒no 8 16 Hyaluronan synthase Glycos_transf_2 ⇐5 17 HP -⇐0 18 Membrane protein -⇒no 2 19 Secreted protein Guanylate_cyc ⇐yes 1 20 Secreted protein -⇐yes 0 21 Major Facilitator Superfamily permease MSF_1 ⇒no 11 Comparative genomics of marine Bacteroidetes 136 22 Secreted protein -⇒yes 1 23 Conserved HP -⇐yes 1 24 Secreted protein -⇐yes 0 25 Heavy metal-(Cd/Co/Hg/ Pb/Zn)-translocating P-type ATPase E1_E2_ATPase ⇐8 26 Secreted protein Cation_efflux ⇐no 5 27 Conserved HP -⇐0 28 Fur family transcriptional regulator protein -⇐0 29 HlyD family secretion protein -⇐no 0 30 Heavy metal cation efflux protein ACR_tran ⇐no 13 31 HP -⇐no 1 32 Beta-galatosidase Glyco_hydro_2_N ⇐yes 0 33 Arabinogalactan 1,4-betagalactosidase Glyco_hydro_53 ⇐yes 0 34 Secreted protein -⇐yes 0 35 Outer membrane protein SusD_RagB ⇐no 0 36 TonB-dependent outer membrane receptor TonB_dep_Reg ⇐yes 1 37 Two-component system sensor (hydrid) HATPase_c ⇐yes 1 38 Membrane protein -⇒no 4 39 Short-chain dehydrogenase/ reductase adh_short ⇒no 0 357 Sensor/regulator hydrid GerE ⇒yes 1 358 TonB-dependent outer membrane receptor TonB_dep_Reg ⇒yes 0 359 Outer membrane protein SusD_RagB ⇒no 0 360 Conserved HP -⇒yes 0 361 Conserved HP -⇒no 0 362 Secreted alpha/beta fold hydrolase Abhydrolase_2 ⇒yes 1 363 Fibronectin III containing domain GH43 F5_F8_type_C ⇐yes 0 364 Glycosyl hydrolase family 43 Glyco_hydro_3 ⇒yes 1 365 Glycosyl hydrolase family 2 Glyco_hydro_2_N ⇐yes 0 366 Secreted protein -⇐yes 0 367 Secreted lipase/esterase -⇐yes 0 Chapter 2 143 356 Predicted permease FtsX ⇒yes 8 357 Predicted permease FtsX ⇒8 358 Predicted permease FtsX ⇒yes 8 359 Predicted permease FtsX ⇒8 360 Predicted permease FtsX ⇒yes 8 361 ABC transporter, AT-binding protein ABC_tran ⇒0 362 Outer membrane efflux protein OEP ⇒0 363 Pirin family protein Pirin ⇒0 364 Bacterial regulatory protein GerE ⇒no 0 365 HP Peptidase_S41 ⇒0 366 Two-component sensor histidine kinase HATPase_c ⇒1 614 ASPIC-like protein UnbV_ASPIC ⇐0 615 ASPIC-like protein UnbV_ASPIC ⇐0 616 ASPIC-like protein UnbV_ASPIC ⇐0 617 Outer membrane protein SusD_RagB ⇐no 0 618 TonB-dependent outer membrane receptor TonB_dep_Reg ⇐yes 0 683 TonB-dependent outer membrane receptor TonB_dep_Reg ⇒0 684 Outer membrane protein SusD_RagB ⇒0 685 TonB-dependent outer membrane receptor TonB_dep_Reg ⇒no 0 686 Outer membrane protein SusD_RagB ⇒no 0 687 HP -⇒0 0 922 HP DUF718 ⇐0 923 HP -⇐0 924 Sulfatase Sulfatase ⇐0 925 Outer membrane protein SusD_RagB ⇐0 926 TonB-dependent outer membrane receptor TonB_dep_Reg ⇐0 927 Transforming growth factor Fasciclin ⇐0 928 Transforming growth factor Fasciclin ⇐0 929 Outer membrane protein SusD_RagB ⇐yes 1 930 TonB-dependent outer membrane receptor TonB_dep_Reg ⇐no 0 931 Transforming growth factor Fasciclin ⇐ Comparative genomics of marine Bacteroidetes 144 1069 TonB-dependent outer membrane receptor TonB_dep_Reg ⇒0 1070 Outer membrane protein SusD_RagB ⇒yes 0 1071 HP -⇒0 1072 Glycosyl hydrolase, family 16 Glyco_hydro_16 ⇒0 1073 HP -⇒0 1074 HP -⇒0 1075 Beta-glucosidase Glyco_hydro_3C ⇒0 1076 Glycosyl hydrolase, family 16 Glyco_hydro_16 ⇒yes 0 1193 Endonuclease Exo_endo_phos ⇐0 1194 Endonuclease Exo_endo_phos ⇐0 1195 Outer membrane protein SusD_RagB ⇐0 1196 TonB-dependent outer membrane receptor TonB_dep_Reg ⇐yes 0 1197 Two-component system sensor histidine kinase HATPase_c ⇐1 1198 TonB-dependent outer membrane receptor TonB_dep_Reg ⇒0 1199 Outer membrane protein SusD_RagB ⇒0 1200 HP -⇒0 1201 HP -⇒0 1202 Xylosidase Glyco_hydro_43 ⇒no 0 1327 Alpha/beta hydrolase fold Abhydrolase_1 ⇒8 1328 Bacterial regulatory family LuxR protein GerE ⇒0 1329 Probable TonB-dependent outer membrane receptor -⇒0 1330 TonB-dependent outer membrane receptor TonB_dep_Reg ⇒no 1 1331 Outer membrane protein SusD_RagB ⇒0 1332 Carboxyesterase COesterase ⇒0 1333 Alpha-L-rhamnosidase Bac_rhamnosid ⇒0 1334 Two-component system response regulator Response_reg ⇒0 1335 Two-component system sensor histidine kinase His_kinase ⇐no 2 1336 Phosphatase Metallophos ⇐1 Chapter 2 145 1337 Beta-glucuronidase Glyco_hydro_2N ⇒1 1338 Hydrolase Lactamase_B ⇐0 1543 Outer membrane protein SusD_RagB ⇐0 1544 TonB-dependent outer membrane receptor TonB_dep_Reg ⇐0 1545 Putative beta-xylosidase Glyco_hydro_43 ⇐0 1546 Two-component system sensor histidine kinase HATPase_c ⇒0 1547 HP Glyco_hydro_43 ⇐0 1548 TonB-dependent outer membrane receptor TonB_dep_Reg ⇐1 1549 Outer membrane protein SusD_RagB ⇐0 1550 HP -⇐0 1551 HP -⇐yes 0 1552 HP -⇐0 1553 HP -⇐0 1554 Beta-galactosidase Glyco_hydro_2C ⇐0 1555 Alpha-galactosidase -⇐yes 0 1556 Putative secreted hydrolase Glyco_hydro_16 ⇐0 1557 Putative glycosyl hydrolase Glyco_hydro_88 ⇐yes 0 1558 HP -⇐0 1559 Beta-galactosidase Glyco_hydro_2C ⇐0 1560 HP -⇐1 1561 Aldo/keto reductase family protein Aldo_ket_red ⇐no 0 1562 Endo-1,4-beta-xylanase A -⇒no 0 1563 Putative membrane protein MSF_1 ⇒12 1572 TonB-dependent outer membrane receptor TonB_dep_Reg ⇒0 1573 Outer membrane protein SusD_RagB ⇒no 0 1998 HP -⇐no 0 1999 HP -⇐yes 0 2000 Outer membrane protein SusD_RagB ⇐0 2001 TonB-dependent outer membrane receptor TonB_dep_Reg ⇐0 2002 HP -⇐0 2003 Two-component system (hybrid) HATPase_c ⇐no 1 Comparative genomics of marine Bacteroidetes 146 2318 Aldolase 1-epimerase Aldolase_epim ⇒0 2319 L-arabinose isomerase Arabinose_isome ⇐0 2320 Sodium/glucose contransporter 1 SSF ⇐no 14 2321 L-ribulose-5-phosphate 4-epimerase Aldolase_II ⇐0 2322 L-ribulokinase FGGY_C ⇐0 2323 Alpha-N-arabinofuranosidase AAlpha_L_AF_C ⇐0 2324 HP DUF1680 ⇐0 2325 Arabinan endo-1,5-alpha-Larabinosidase A Glyco_hydro_43 ⇐0 2326 Xylosidase/arabinosidase Glyco_hydro_44 ⇐yes 0 2327 Arabinan endo-1,5-alpha-Larabinosidase A Glyco_hydro_43 ⇐0 2328 Alpha-L-arabinosidase Alpha_L_AF_C ⇐0 2329 ASPIC-like protein UnbV_ASPIC ⇐0 2330 Outer membrane protein SusD_RagB ⇐no 0 2331 TonB-dependent outer membrane receptor TonB_dep_Reg ⇐1 2587 Mannonate dehydratase UxuA ⇐0 2588 Short-chain dehydrogenase/ reductase adh_short ⇐0 2589 Outer membrane protein SusD_RagB ⇐0 2590 TonB-dependent outer membrane receptor TonB_dep_Reg ⇐yes 0 2591 Trascriptional regulator, LacI Peripla_BP_1 ⇐0 2592 Hypotethical oxidoreductase GFO_IDH_MocA ⇐0 2593 HP Aminohydro_2 ⇐0 2594 Two-component system sensor histidine kinase HATPase_c ⇒no 2 2595 Probable transcriptional regulator Response_reg ⇒0 2596 Xylosidase/arabinosidase Glyco_hydro_43 ⇒0 2665 Glucokinase ROK ⇐1 2666 Esterase Abhydrolase_3 ⇐0 2667 Putative alpha-glucosidase -⇐0 2668 HP Glyco_hydro_92 ⇐yes 0 2669 HP DUF1237 ⇐0 Chapter 2 147 2670 HP -⇐0 2671 HP F5_F8_type_C ⇐no 0 2672 Outer membrane protein SusD_RagB ⇐0 2673 TonB-dependent outer membrane receptor TonB_dep_Reg ⇐0 (…) HP -⇐ 2681 Putative alpha-1,2mannosidase Glyco_hydro_92 ⇐0 2682 L-fucose-proton symporter MSF_1 ⇐12 2683 Putative esterase Esterase ⇐1 2684 Arylsufatase Sulfatase ⇐no 0 2685 Beta-galactosidase Glyco_hydro_2 ⇐0 2686 Beta-galactosidase Glyco_hydro_2_N ⇐0 2687 Two-component system (hybrid) HATPase_c ⇒yes 1 2688 Rhamnogalacturonan acetylesterase precursor Lipase_GDSL ⇒yes 0 2689 Beta-galactosidase Glyco_hydro_2_N ⇐1 2690 HP Lipase_GDSL ⇐0 2691 Acetylesterase DUF303 ⇐0 2692 Arabinose metabolism trascriptional repressor GntR ⇐0 2693 Hypothetical oxidoreductase adh_short ⇒0 2694 Putative sugar isomerase -⇒0 2695 Glycerol kinase FGGY_N ⇒0 2696 L-lactate dehydrogenase FMN_dh ⇒0 2697 Transmembrane protein -⇒11 2698 Exo-poly-alpha-Dgalacturonidase precurson Glyco_hydro_28 ⇒0 2699 HP -⇒1 2700 HP -⇒yes 0 2701 HP -⇒0 2702 HP -⇒0 2703 Arabinosidase -⇐0 2704 Xylanase Peptidase_S9 ⇐yes 1 2705 Beta-galactosidase Glyco_hydro_2_N ⇐0 2706 Glycosyl hydrolase, family 88 Glyco_hydro_88 ⇐0 2707 Conserved HP Glyco_hydro_2_N ⇐yes 0 2708 TonB-dependent outer membrane receptor TonB_dep_Reg ⇒0 Comparative genomics of marine Bacteroidetes 148 2709 Outer membrane protein SusD_RagB ⇒0 2710 Two-component system sensor histidine kinase HATPase_c ⇒0 2711 HP -⇒0 2712 HP -⇒0 2713 HP -⇒no 0 2714 HP Response_reg ⇐0 2715 Two-component system sensor histidine kinase HATPase_c ⇐0 2716 HP -⇐0 2717 Aminotransferase Aminotran_1_2 ⇐0 2718 HP -⇒0 2719 Transcriptional regulator, AraC HTH_AraC ⇒0 2720 HP -⇒5 2721 HP -⇒1 2722 HP Peptidase_S9 ⇐0 2723 Outer membrane protein SusD_RagB ⇐no 0 2724 TonB-dependent outer membrane receptor TonB_dep_Reg ⇐1 3416 Ribonucleoside-diphosphate reductase alpha chain Ribonuc_red_IgC ⇐0 3417 Ribonucleoside-diphosphate reductase beta chain ATP-cone ⇐no 0 3418 Alpha-glucosidase Glyco_hydro_31 ⇐0 3419 Alpha-amylase Alpha_amylase ⇐yes 0 3420 Alpha-amylase Alpha_amylase ⇐yes 0 3421 HP -⇐0 3422 Outer membrane protein SusD_RagB ⇐0 3423 TonB-dependent outer membrane receptor TonB_dep_Reg ⇐no 1 3424 Serine/threonine-protein kinase -⇐1 Chapter 3 !"#$%&'()"%*+*,"'-./0"'1(2*$3*&()"%*4*,"'-.5"%%#1(( 60&7&3(89(:#;#0#<3%1(=3;>(?9(.3*'+7"'1(:#%73;(@",%/;-27&/1( (#*,(A&7B&#(.9(2C&*#;( @#$$"%*;(#*,(#%CD&$"C$5%"(3E(F"*30&C(&;7#*,;(&*(( 0#%&*"(G#C$"%&#( Chapter 3 151 ABSTRACT Genomic Islands (GIs) have an important role in modulating the bacterial genome structure and size displaying a diverse set of laterally transferred genes. However, GIs in marine bacterial genomes have not been explored systematically to uncover possible trends and to analyze their putatively ecological significance. In this study, we performed a comprehensive analysis of GIs in 70 selected marine bacterial genomes to explore the distribution, patterns and functional gene content in these genomic regions. We detected 438 GIs containing a total of 8152 genes. We showed that the GI number per genome was strongly and positively correlated with the total GI size. In 50% of the genomes analyzed the GIs accounted for approximately 3% of the genome length, with a maximum of 12%. Interestingly, we found transposases particularly enriched within Alphaproteobacteria GIs, and site-specific recombinases in Gammaproteobacteria GIs. We described specific Homologous Recombination GIs (HRGIs) in several genera of marine Bacteroidetes and in Shewanella strains among others. In these HR-GIs we recurrently found housekeeping genes such as β-subunit of DNA-directed RNA polymerase, regulatory sigma factors, the elongation factor Tu, and ribosomal protein genes typically associated with the core genome. Our results indicate that both horizontal gene transfer mediated by phages, plasmids and other mobile genetic elements, and HR by site-specific recombinases or plasmids, play important roles in the mobility of clusters of genes between taxa and within closely related genomes, modulating the flexible pool of the genome. Our findings suggest that GIs may increase bacterial fitness under environmental changing conditions by acquiring novel foreign genes and/or modulating gene transcription and/or transduction. Patterns and Architecture of Prokaryotic Genomic Islands 152 INTRODUCTION Bacterial comparative genomics is providing a unique opportunity to retrieve valuable information regarding genome structure, functional diversity and evolution of marine microorganisms. Bacterial genomes are dynamic entities with a known pool of conserved housekeeping genes at the core genome that remain similar and comparable at different taxonomic levels, and the flexible (or adaptive) genome, with a number of genes that are not comparable among closely related strains (Hacker and Carniel 2001; Ochman et al., 2005). Horizontal gene transfer (HGT) is one of the evolutionary mechanisms enlarging the flexible genome pool of bacterial populations, facilitating their adaptation to new ecological niches (Doolittle 1999; Boucher et al., 2003). The flexible genome pool has been analyzed for a few bacterial taxa by comparative genome analysis (Hacker and Carniel 2001). In well-known marine bacteria such as Prochlorococcus, Synechococcus, and Shewanella comparative genome analysis has revealed a substantial number of species-specific genes (Kettler et al., 2007; Dufresne et al., 2008; Konstantinidis et al., 2009). Those studies revealed an unsaturated pangenome size, reflecting the existence of new lineages and the heterogeneity among the flexible genome pool. Species-specific genes are commonly found in genomic islands (GIs), that are defined as laterally transferred clusters of genes linked to the flexible pool of the genome (Hacker and Kaper 2000; Hacker and Carniel 2001). GIs are important genomic regions causing significant genetic differences between closely related genomes, and they may reveal particular ecologically relevant features of the genomes (Cuadros-Orellana et al., 2007), and virus-bacteria interactions (Coleman et al., 2006; Avrani et al., 2011). GIs may harbor a large set of genes with different origins. However, using a hypothesis-free approach for identification of GIs some common features can be recognized suggesting that GIs could be perceived as a superfamily of mobile elements (Vernikos and Parkhill 2008). Genes found within GIs are very diverse: from key genes for survival in specific environments to virulence, and/or antibiotic resistance genes. In fact, GIs enriched in virulence genes and in Clustered Regularly Interspaced Palindromic Repeats (CRISPRs) confer resistance to exogenous genetic elements such as plasmids and phages (Ho Sui et al., 2009). Thus, GI content may hold clues about the lifestyle or survival strategies of bacteria (Read and Ussery 2006). Another common characteristic of the GIs is the enrichment in novel genes without any orthologous groups detected in the COG database or any other known functional gene families (Hsiao et al., 2005). Extensive literature exists on GIs in pathogenic bacterial strains (referred to as pathogenic islands) where their relevance is known for antibiotic resistance or virulence Chapter 3 153 stages (Hacker and Carniel 2001; Schmidt and Hensel 2004; Gal-Mor and Finlay 2006). In environmental microorganisms GIs have been associated with the presence of catabolic pathways for organic pollutants, thus conferring adaptive traits in some Pseudomonas sp. strains (van der Meer and Sentchilo 2003). Other ecological features associated with GIs are the presence of genes for magnetite biomineralization in what is called the magnetosome island in the Alphaproteobacterium Magnetospirillum gryphiswaldense (Ullrich et al., 2005), or secondary metabolism in marine Actinobacteria strains (Penn et al., 2009). Another case is the acquisition of a capsular polysaccharide biosynthesis gene cluster by the non-pathogenic soil inhabitant Burkholderia thailandensis with similar characteristics to the virulence gene cluster of the pathogenic Burkholderia pseudomallei (responsible for the melioidosis disease) (Sim et al., 2010). In Cyanobacteria GIs from several strains of Prochlorococcus marinus (Coleman et al., 2006; Kettler et al., 2007) and Synechococcus sp. strains (Dufresne et al., 2008) have been reported. Also, the GIs of two freshwater filamentous toxin-producing cyanobacteria were found with diverse comparative approaches (Stucken et al., 2010). For Gammaproteobacteria GIs were described for the high pressure adapted Photobacterium profundum SS9 strain (Campanaro et al., 2005), the marine coastal Vibrio vulnificus (Cohen et al., 2007), Alteromonas macleodii (Ivars-Martínez et al., 2008) and Shewanella baltica strains (Caro-Quintero et al., 2011). In Alphaproteobacteria GIs were found in SAR11 (Candidatus Pelagibacter ubique strain HTCC1062) referred to as hypervariable regions (HVR) in the original study (Wilhelm et al., 2007). In aquatic Bacteroidetes GIs or HVR were described in Salinibacter ruber, a highly abundant bacterium in solar salterns, (Pasic et al., 2009; Peña et al., 2010). Finally, virulence genes of typically pathogenic island were reported in marine bacteria genomes in a comparative study (Persson et al., 2009). However, GIs in marine bacterial genomes have not been explored systematically and a comparative analysis is still lacking. In this study we performed a comprehensive analysis of GIs in 70 selected marine bacterial genomes that represented abundant and ecologically relevant bacteria in the ocean. We assembled a database of 8152 genes found in GIs of marine bacteria and screened it for possible patterns and clues about the ecological relevance of GIs in marine bacteria. Patterns and Architecture of Prokaryotic Genomic Islands 160 for the researcher (and usually they are not). Thus, IslandViewer should be more efficient at detecting these GIs than manual annotation. In conclusion, IslandViewer detects only a subset of the islands annotated manually. Reasons for this are the different criteria used by different authors to define GIs. In many cases the GIs detection is based only on one approach; either comparison of two genomes or differences of the tetranucleotide frequency and occurrence of mobility genes (Table 1). IslandViewer seeks several characteristics and, therefore, we can expect a more robust and more conservative detection of GIs. The important conclusion for the present work, however, is that the functional representation of genes is not significantly different between the manual and automated procedures. Therefore, our conclusions will be representative of all GIs. This conclusion is important for other authors seeking to use IslandViewer for GI detection in other environmental bacteria. Quantitative importance of GIs in marine bacterial genomes The 70 selected marine bacterial genomes represent the four major prokaryotic taxa in the ocean: Cyanobacteria (16 genomes), Gammaproteobacteria (17), Alphaproteobacteria (16) and Bacteroidetes (21) (Table 2SM). These four bacterial taxa account for up to 80% of total marine bacterioplankton (Barberán and Casamayor 2010). Bacteroidetes genomes included 14 Flavobacteria and 7 non-marine Bacteroidetes (Bacteroides spp.) used as outgroups. Several genomes of closely related bacterial strains from each phylogenetic group were included to investigate the rate of variability of GIs at intra-specific level and explore their relevance as main contributors for strain-specific genes. GIs were detected in 66 out of the 70 bacterial genomes (Table 2SM). No GIs were detected in the genomes of Pelagibacter ubique HTCC1062 and the marine Bacteroidetes Flavobacteria bacterium BBFL7, Flavobacteriales bacterium ALC-1, and Flavobacterium psychrophilum JIP02/86. The absence of GIs in these genomes may be related to the small genome size of some of them (between 1.4 and 3.8 Mb), as well as to the lack of sensitivity of the GI predictor when suitable genomes were not available for comparison. Overall, we detected 438 GIs spanning a total of 8.87 Mb (Table 2SM). The size of individual GIs ranged between 10 and 436 kb (389 kb per genome on average, considering the marine genomes only). As expected, the total GI size was strongly and positively correlated with the number of GIs per genome (R=0.93, p <0.001) (Fig. 2A). Significant correlations (p <0.001) were observed between genome size and both GI size and number of GIs per genome (Fig. 2B and Chapter 3 161 Figure 2. Patterns of GIs in marine bacterial genomes. A) Relationship between number of GIs per bacterial genome with GIs size. B) Relationship between bacterial genome and GIs size. C) Relationship between genome size and number of GIs (≥9 kb). 2C). When the data were analyzed separately for each of the four classes, Cyanobacteria (R= 0.69, p < 0.05) and Bacteroidetes (R=0.78, p <0.001) showed significant correlations (Figure 1A and 1D SM) while the Proteobacteria did not (Fig. 1B and 1C SM). For any given range of genome sizes, there was a large variability in the length of GIs (data not shown). The fraction of the bacterial genome represented by GIs ranged between 0 and 12% (Fig. 3). Most genomes showed a ratio between 2 and 5%. The Cyanobacteria showed a significantly lower average ratio than the other three classes. However, this is likely due to the low GI detection rate of Island Viewer in the case of several Cyanobacteria (Table 1). Otherwise, Patterns and Architecture of Prokaryotic Genomic Islands 162 there were no significant differences among classes, although the Gammaproteobacteria showed a lower variability than Bacteroidetes and Alphaproteobcteria (Fig. 3). The genomes with the highest ratios for each main bacterial class were the alphaproteobacterium Rhodobacter sphaeroides ATCC1705 (12%), the cyanobacterium Synechococcus sp. CC9605 (7%), the gammaproteobacterium Psychrobacter sp. PRwf-1 (6.8%), and the flavobacterium Robiginitalea biformata HTCC2501 (4.5%; Table 2SM). In a previous study, Synechococcus GIs were shown to form between 10 and 31% of their genomes (Dufresne et al., 2008) and similar percentages, and up to 17%, have been found also for pathogenic islands in Escherichia coli (Ochman et al., 2000). The marine bacteria examinated have a lower percentage of their genome in GIs. Interestingly, high intra-specific variability in GIs size was observed in some members of every group. Two Synechococcus sp. strains, for example, with genomes of 2.2 and 2.6 Mb respectively, showed very different GI ratios (15 kb and 175 kb respectively). Similarly, small differences in genome size between two Shewanella baltica strains (MR-4 and OS155, with 4.7 and 5.12 Mb respectively) contrasted with marked differences in their GIs ratios (3.7 and Figure 3. Boxand whiskers graphic of the GI ratio (in %) for the 70 marine bacteria. Genomes are ranked from highest (12%) to lowest (0) and grouped in 4 main phylogenetic affiliation represented as follow: C (Cyanobacteria), G (Gammaproteobacteria), A (Alphaproteobacteria) and B (Bacteroidetes). The graph shows the median (thick horizontal line), the upper and lower quartile (rectangle), the maximum and minimum values excluding outliers (discontinuous line), and finally circle represents an outlier. Chapter 3 163 6.3% respectively) (Table 2SM and Fig. 1SM). Architecture of marine bacterial GIs As a common characteristic we found that 70% of the described GIs contained mobile genetic elements (MGE), mostly transposases, conjugative transposons, integrons or phage integrase-related genes in accordance with previous GIs revisions (Dobrindt et al., 2004, Juhas et al., 2008). In addition, we observed that at least 27% of the GIs were flanked by or contained tRNAs, probably acting as the integration sites for GIs (Reiter et al., 1989; Williams 2002). Most GIs in marine bacterial genomes could be assigned to one of two architectures. First, many of these GIs exhibited a high content of hypothetical proteins (HP), as well as different sets of genes in different genomes, suggesting that they had originated through Figure 4. Structure (5´-3´) of the Horizontal Gene Transfer (HGT)-GIs representative of four marine bacteria. Genomes belonged to Cyanobacteria, Gammaproteobacteria, Alphaproteobacteria and marine Bacteroidetes. The hypothetical origin of HGT (via prophage, transposon or other MGE), the length of the GI (in kb) and the number of genes integrated are shown in brackets. Colors indicate the variety of genes observed within the GIs. Numbers in brackets under the genes indicate the HPs and other genes not considered for the figure. Patterns and Architecture of Prokaryotic Genomic Islands 164 horizontal gene transfer (HGT) by phages, conjugative transposons or other MGEs. From now on, we will refer to these GIs as HGT-GIs. One example from each bacterial class examined is shown in Figure 4. The cyanobacterium Anabaena variabilis ATCC 29413 displayed a gene related to Photosystem I, four cas genes related to CRISPRs system and three Tn7 transposition proteins in a single GI of 13 kb. The gammaproteobacterium Pseudoalteromonas atlantica T6c presented a GI of 62.7 kb mostly constituted by a prophage with many phage related proteins genes. Also, in the alphaproteobacteria Roseobacter denitrificans Och 114 we detected a GI of 16 kb with many flagellar proteins and MGE elements. Finally, the marine bacteroidetes Leeuwenhoekiella blandensis MED217 had a GI of 26.8 kb with multiple genes of MGE, cas genes, and a nitrite reductase. This gene has been only described in marine bacteroidetes in the deep sea flavobacterium Zunongwangia profunda SM-A87 with capacity to hydrolize organic nitrogen (Qin et al., 2010). Many other GIs presented ecologically interesting genes but specific details for each one are out of scope of this paper although a summary of 16 biological categories is shown in Figure 10. And second, we found many GIs that contained site-specific recombinases and tRNAs. Interestingly, these GIs were characterized by harboring many housekeeping (or core) genes, almost no hypothetical proteins, and had a structure that could be repeatedly detected in genomes of different genera or even different classes (Fig. 5). We hypothesized that such genomic fragments were likely transferred via homologous recombination (HR). We will refer to these as HR-GIs. Quite likely these genomic cassettes may be also mobilized within the same genome by the transposases that some of them have at their flanks. Flavobacteria was one of the classes with more conspicuous HR-GIs. Figure 5 shows an example of one the HR-GI named as HR1-GI. This GI was found in many Bacteroidetes (Fig. 2SM) of which five were specifically detected in our dataset and are shown in Figure 5 as an example. Despite differences in the total length of the island (from 15.9 to 44 kb), synteny was maintained for a cassette consisting of a substantial number of genes (see black rectangle in Fig. 5). It is notorious that the genes observed upstream of the cassette were quite different in every genome (Fig. 5). Surprisingly, housekeeping genes as important as the β-subunit of DNA-directed RNA polymerase, the elongation factor Tu, sigma factors, transcription termination factors, and ribosomal proteins were recurrently detected in this HR-GIs, and they also contained site-specific recombinases and tRNAs. The HR1-GI detected in five marine Flavobacteria (Fig. 5) was further examined in other Bacteroidetes representatives. We observed identical synteny in nine Flavobacteria, three Sphingobacteria and three Bacteroides (Fig. 2SM). The only variants were a few gene insertions in Capnocythophaga ochracea DSM 7271 and some deletions in sphingobacterial genomes. This particular HR1GI, therefore, was well conserved throughout the Bacteroidetes phylum. Chapter 3 165 Some of the genes present in these particular HR-GIs coded for ribosomal proteins, Figure 5. Structure (5´-3´) of the Homologous Recombination GIs (HR-GIs) in marine bacterial genomes. HR1-GI detected in five different genera of marine Bacteroidetes. The synteny and the gene cassette shared by these genomes are within the black box. Red line indicates the length of the GI detected which varied among the genomes. which are known to be highly expressed genes, usually with a sequence composition very different from the rest of the genome (Karlin 2001). As a consequence, these genome fragments might appear as false-positive predictions of GIs if sequence composition bias (% GC content) were used as the only criterion to identify GIs. IslandViewer integrated the three most accurate GI prediction programs (Langille et al., 2008; Waack et al., 2006; Hsiao et al., 2005), each using different approaches to predict GIs and, in effect, both HR-GIs were Patterns and Architecture of Prokaryotic Genomic Islands 166 detected by more than one tool. However, we looked for additional evidence that these genecassettes were not false positives, that is, that they were in a true genomic island. For this purpose, we built phylogenetic trees, with sequences from 20 Bacteroidetes genomes, of two genes found in HR1-GIs (rpoB and EF-Tu) and 16S rRNA. If these GIs were false positives, we would expect the phylogenies of rpoB and EF-Tu to match that of 16S rRNA. If these were true GIs subject to HR, however, we would expect somewhat different phylogenies for 16S rRNA on the one hand and rpoB and EF-Tu on the other (Fig. 3SM). Although the general topology among Flavobacteria, Sphingobacteria and Bacteroides branches was conserved with the three genes, several discrepancies could be detected between the 16S phylogeny on the one hand and those of the other two genes on the other (see black triangles and circles in Fig. 3SM). This is in accordance with the two functional genes following similar evolutionary trends and belonging to a GI. A second line of evidence in support of the HR1 being true islands comes from a plasmid found in Shewanella baltica OS155 (pSbal03), containing the same gene-cassette of HR1-GI (except for one gene). The genes in this cassette were absent from the corresponding chromosome, further showing that HR1-GI is in fact laterally transferred (Fig. 6A). Interestingly, identical gene structure to this plasmid with a translocation of six ribosomal proteins was observed in 20 other Shewanella strains (Fig. 6A). Plasmid integration in the host chromosome by HR is a well known phenomenon in bacteria such E.coli, Bacillus subtilis, Enterococcus faecalis and others (Casey et al., 1991). Usually, the site of integration in the genome corresponds to the chromosome location of the fragment shared with the plasmid. In our case, the hypothetical insertion of the plasmid in the Shewanella baltica OS155 chromosome is located next to the chromosome EF-Tu gene shared by the plasmid and next to a large cluster of 15 ribosomal proteins and the rpoA (Fig. 6A). This cluster of ribosomal protein genes is considered to be a locally collinear block (LCB) meaning a contiguous segment of genes with low rearrangements (Dikow, 2011). The fact that most of the Shewanella strains harbor two copies of EF-Tu genes fits with the idea of one of them belongs to this or a similar Shewanella plasmid. We conducted phylogenetic reconstruction of EF-Tu genes in these 19 Shewanella strains and linked to the HR1-GI revealing certain anomalies in the tree topology (Fig. 4SM). For instance, both EF-Tu gene copies of Shewanella sp. MR-4 and MR-7, two isolates retrieved from different depths of the Black Sea (Venkateswaran et al., 1999), clustered with each other instead of with the other EF-Tu gene copy of their genome (Fig. 6B). This finding suggests HR events and it is consistent with a recent study in which high level of HR has been discovered among co-occurring Shewanella baltica isolates (Caro-Quintero et al., 2011). In summary, we are confident that this homologous recombination GIs are true genomic islands that in the case of Shewanella strains this HR1-GI was first transferred to Chapter 3 167 the genome by a plasmid and mobilized after by the site-specific recombinases within the GI. This finding is consistent with a recent study in which high level of HR has been discovered among co-occurring Shewanella baltica isolates (Caro-Quintero et al., 2011). It is known that recombination plays a cohesive role in bacteria within closely related lineages, because HR is rare between different taxa. (Caro-Quintero et al., 2011, Fraser et al., 2007, Fraser et al,. Figure 6. Zoom of two sections of the phylogenic tree of the EF-Tu in Shewanella strains. The phylogenetic tree show the two gene copies of the EF-Tu of 19 Shewanella strains linked to the hypothetical HR1-GI marked as a black box. A) The insertion location of the plasmid pSbal03 of Shewanella baltica OS155 in its chromosome (both labeled in red) is shown in grey and the most representative genes are indicated within HR1-GI. B) Shewanella strains labeled in red show discrepancies in the EF-Tu phylogeny when both EF-Tu genes were compared. Patterns and Architecture of Prokaryotic Genomic Islands 168 Figure 7. Percentage of hypothetical proteins (HP) within the GIs and on average for each bacterial genome. Each bacterial taxa is represented by different colors. Solid circles show statistically significant differences using the corrected P value (Bonferroni) < 0.05 after Fisher Exact Test, while empty circles did not show significant differences. 2009). However, HR and other mechanisms such genomic rearrangements have been also identified as a key role driving speciation in several aquatic bacterial populations. (Papke et al., 2004, Zehr et al., 2007). We have observed identical HR-GIs not only within strains but also across genera in Bacteroidetes and this reinforces this latter possibility. In summary, we are confident that this homologous recombination GIs are true genomic islands that in the case of Shewanella strains this HR1-GI was first transferred to the genome by a plasmid and mobilized after by the site-specific recombinases within the GI. Functional Annotation of the Prokaryotic Genomic Islands One of the reported characteristic features of prokaryotic genomic islands is a higher concentration of genes coding for hypothetical proteins than in other genome regions (Hsiao et al., 2005). In effect, we found significantly higher percentage of hypothetical proteins within GIs than the average for the whole genome in 71% of the genomes (Fisher’s test with the Bonferroni correction: p <0.05) (Fig. 7). The 19 genomes with non-significant differences of HP within and outside the GIs were mostly marine Bacteroidetes or Cyanobacteria (Fig. 7). These two bacterial classes were the ones with largest % HP in their genomes (Fig. 7). We believe this is due to the lower number of well studied strains compared to Proteobacteria. Thus, the %HP is larger throughout the genome and therefore no significant differences were Chapter 3 169 expected within and outside GIs. Around 55-60% of the genes in GIs coded for hypothetical proteins. In this respect, therefore, the GIs of marine bacteria are like those described before in pathogenic bacteria, where hypothetical proteins constituted 53% of the genes within GIs versus 28% in the rest of the genome (Hsiao et al., 2005). Next, we annotated the genes within GIs assigning them to functional categories with two approaches: Clusters of Orthologous Groups (COG) and GeneOntology (GO) with a total of 3725 and 3360 genes respectively to which a function could be assigned. Their distribution in the 22 COG categories appears in Figure 8. As expected category L (replication, recombination, and repair) contained over 20% of the total in agreement with the high proportion of transposases, integrases, and other recombinase related enzymes found in GIs. The next category was R, “general prediction only” with 11%. This basically includes proteins for which a more specific function could not be assigned and is, thus, not informative. Cell wall/membrane/envelope biogenesis (M) with 10% and the translation/ ribosomal structure and biogenesis (J) with 9% were especially well represented. Cell motility (N), defense mechanisms (E), and inorganic ion transport and metabolism (P) were also represented (3-4%). Figure 8. Distribution of annotated genes within the GIs according to their COG category. Percentage shown for those categories accounting for ≥3%. Resumen en español 277 OBJETIVOS DE LA TESIS El objetivo principal de la presente tesis es el de ampliar el conocimiento que se tenía de los Bacteroidetes marinos (o Flavobacterias), un grupo bacteriano muy abundante e importante en el océano pero quizás uno de los menos estudiados hasta el momento. Pretendemos profundizar más en el estudio de su genética (analizando su genoma y investigando sus rutas metabólicas y genes de interés ecológico), fisiología (realizando experimentos para ver su respuesta frente a determinados factores) y de entender sus estrategias de supervivencia en el océano (pudiéndolas comparar con otros grupos bacterianos importantes). Con el fin de llegar a responder a todas nuestras preguntas, hemos llevado a cabo análisis y experimentos tanto in silico como in vivo, combinando técnicas bioinformáticas con experimentos de crecimiento. Esta tesis consta de cinco trabajos diferentes organizados en cinco capítulos que tratan de responder preguntas más específicas enumeradas a continuación: ¿Cuál es la composición genómica de Polaribacter sp. MED152, un representante de los Bacteroidetes marinos? ¿Qué nos dice el análisis de su genoma acerca de sus estrategias de vida? En el Capítulo 1 titulado Análisis del genoma de Polaribacter sp. MED152, una bacteria marina que contine la protorodopsina, se analizó el genoma completo de esta flavobacteria aislada en el Observatorio Microbiano de la Bahía de Blanes (BBMO) y que consideramos de interesante estudio por el hecho de poseer el gen de la proteorodopsina. El análisis de genomas completos de cianobacterias y proteobacterias nos habían llevado a comprender sus estrategias de vida y metabolismos. Sin embargo, estudios similares en Bacteroidetes todavía no se habían llevado a cabo. Así, el genoma de MED152 podría proporcionarnos nuevos conocimientos sobre las capacidades fisiológicas de bacterias con proteorodopsina, convirtiéndose en un genoma modelo para el estudio de procesos celulares y moleculares en bacterias que expresan este gen, su adaptación al medio marino y su papel en el ciclo del carbono. Spanish Summary 278 ¿Hay algún patrón entre los Bacteroidetes marinos? Podrían encontrarse características similares a las de Polaribacter en otros representantes? Posteriormente, en el Capítulo 2 titulado Genómica comparativa de Bacteroidetes marinos con y sin proteorodopsina, quisimos saber si las características halladas en el genoma de Polaribacter sp. MED152 y en otra flavobacteria cuyo genoma también había sido completamente descrito anteriormente, Gramella forsetii KT0803, aislada en el Mar del Norte y que no contiene la proteorodopsina, eran comunes entre ellos y a otros representantes de las flavobacterias y diferentes a otros grupos de bacterias marinas. Para ello seleccionamos otras dos flavobacterias cuyos genomas también habían sido secuenciados, Dokdonia sp. MED134 (con proteorodopsina) y Leewenhoekiella blandensis MED217 (sin proteorodopsina). Analizamos estos genomas con el objetivo principal de ver qué rasgos genéticos identificados en MED152 estaban restringidos a bacterias que poseen la proteorodopsina, cuales eran comunes a Bacteroidetes marinos y cuales estaban presentes en todos los Bacteroidetes (incluyendo los simbiontes del tracto intestinal de mamíferos). ¿Proporcionan las islas genómicas presentes en algunos grupos de bacterias ventajas para su capacidad ecológica adaptativa? Hay variación en el número y naturaleza de estas islas entre diferentes grupos de bacterias? Seguidamente, en el Capítulo 3 que lleva por título Patrones y arquitectura de la islas genómicas de bacterias marinas, quisimos ir más allá y decidimos hacer un análisis exhaustivo de las islas genómicas (fragmentos de DNA permiten la movilización del material genético) de los Bacteroidetes marinos, comparándolas con las de otros grupos de bacterias tales como las cianobacterias, las alfay gamma-proteobacterias y los Bacteroidetes no marinos. Usando la base de datos IslandViewer y los programas de detección de islas que tiene integrados en su interfaz, llevamos a cabo el análisis de las islas genómicas de 70 genomas y construimos una base de datos con un total de 8152 genes presentes en las 436 islas genómicas detectadas. En este estudio exploramos la distribución, patrones y función de los genes presentes en las islas, lo cual nos ha proporcionado una nueva visión de la relevancia ecológica de estos elementos móviles en los genomas procariotas marinos. Resumen en español 279 ¿Cuál es la función real de los genes predichos (concretamente la del gen de la PR) en el medio ambiente natural? ¿Pueden las técnicas tradicionales de cultivos puros ayudarnos a descubrir esto? En el Capítulo 4 que lleva por título El medio de cultivo influencia la respuesta a la luz de Flavobacterias marinas que contienen proteoprodopsina, quisimos centrarnos en la posible ventaja adaptativa que proporcionaría el hecho de poseer el gen de la proteorodopsina. Anteriormente, en el Capítulo 1, ya habíamos formulado hipótesis de los posibles beneficios de poseer este gen pero hasta el momento muy pocos estudios se habían realizado para comprobarlo experimentalmente. Los objetivos de este capítulo eran determinar la influencia de la luz en el crecimiento y en la incorporación de bicarbonato en MED152 y en MED134. Para ello diseñamos una serie de medios pobres en materia orgánica, con diferentes concentraciones de carbono orgánico disuelto para ver si se producía estimulación del crecimiento y de la asimilación de carbono inorgánico en presencia de luz con respecto a la oscuridad. ¿Cómo es posible determinar la capacidad metabólica del bacterioplancton en el medio natural? Finalmente, en el Capítulo 5 llamado Cambios estacionales en los patrones de utilización de substratos por el bacterioplancton en el Golfo de Amundsen (Ártico Occidental), quisimos estudiar el patrón de utilización de substratos de la comunidad microbiana el Golfo de Amundsen (Mar de Beaufort) de invierno (febrero) a verano (julio). El área de estudio es una zona muy dinámica y con unas condiciones de hielo muy heterogéneas, conocida como polynya. Para ello diseñamos e inoculamos microplacas BIOLOG MT2 con diferentes fuentes de carbono (polímeros, carbohidratos, aminacidos, y otros substratos) las cuales nos proporcionaron información sobre los substratos más utilizados por el bacterioplankton heterotrófico. Estas microplacas constan de 96 pocillos vacios que contienen violeta de tetrazolio, que se reduce de forma irreversible a formazán como consecuencia de la actividad metabólica bacteriana dando un color violeta en el pocillo que facilita la lectura visual de los resultados. Spanish Summary 280 Nuestros resultados los pudimos comparar con los obtenidos en un estudio anterior que se realizó en la misma zona pero en un área con una hidrografía completamente diferente, mostrando una capa de hielo estable a lo largo de todo el año. Resumen en español 281 Figura 8. Diferentes enfoques para el estudio de la comunidad microbiana utilizada en esta tesis. (A) Un organismo puede ser aislado en cultivo puro. La secuenciación de su genoma permite estudiar el DNA, mRNA y proteínas para obtener información acerca de: i) filogenia, ii) metabolismo y transporte, iii) existencia de transferencia lateral de genes, y METODOLOGÍA En el presente trabajo, se han utilizado herramientas in silico para llegar a la mayoría de los objetivos anteriormente citados (Capítulos 1-3). También se han realizado experimentos in vivo con cultivos (Capítulo 4) para comprobar algunas de las hipótesis que surgieron a partir del análisis genómico previamente realizado. Por último, se utilizó una técnica de huella digital metabólica (microplacas Biolog) para caracterizar la comunidad microbiana in situ (Capítulo 5). Aunque la metodología particular de cada capítulo está detallada en los mismos, en esta sección se presenta una visión global de las diferentes técnicas. El siguiente diagrama muestra los diferentes criterios utilizados en el estudio de bacterias marinas y sus interconexiones. Spanish Summary 282 iv) similitudes con organismos de otros ambientes. (B) Una información similar puede ser obtenenida estudiando toda la comunidad microbiana a través de metagenómica, evitando la necesidad de cultivar los organismos (en la presente tesis hemos elegido la vía A). (C) Las microplacas BIOLOG permiten estudiar algunas funciones metabólicas en muestras tomadas directamente de la comunidad. Algunos de los rasgos que se encuentran por medio de la genómica y metagenómica también se pueden probar usando estas placas. Aproximanciones “in silico”: HERRAMIENTAS BIOINFORMÁTICAS Anotación genómica y análisis La anotación genómica es el proceso de asignación de la información biológica a las secuencias de genes y sus productos proteicos (Stein, 2001). Durante los últimos años, se han secuenciado un gran número de genomas (Overbeek et al., 2004) y la anotación manual de estos genomas es una tarea que consume mucho tiempo. Para resolver este cuello de botella, se han desarrollado cadenas de procesos (pipelines) para automatizar la anotación; estas cadenas realizan búsquedas de similitud seguidas de una evaluación automática de los resultados y la generación de una anotación funcional. La anotación automática acelera el proceso. Sin embargo, una anotación de alta calidad requiere un refinado manual de las anotaciones. Hay varios portales que ofrecen herramientas y servicios para la anotación automática y su revisión manual. En la presente tesis (Capítulo 1), se utilizó el portal GenDB del Centro de Biotecnología (CeBiTec) de la Universidad de Bielefeld (Alemania). El gráfico siguiente muestra el flujo de datos en la anotación genómica. El proceso comienza con la secuencia terminada del genoma y la predicción de genes y sus funciones. Hay una retroalimentación entre la identificación de genes y la corrección de errores de secuenciación. Después de la predicción automática de genes, la búsqueda de similitud entre genes se lleva a cabo mediante herramientas de alineamiento de secuencias (Basic Local Alignment Search Tool, BLAST) (Altschul et al., 1990), que identifica los casos con alta similitud con otras proteínas en bases de datos (normalmente NCBI NR), de modo que se puede predecir la función. Se puede realizar una anotación más detallada utilizando otras herramientas en combinación con la búsqueda de bases de datos especializadas como KEEG (Kyoto Encyclopedia of Genes and Genomes, Kanehisa and Goto, 2000) o Pfam (familia de parálogos, Finn et al., 2008). Resumen en español 283 Figura 9. Diagrama de flujo generalizado del proceso de anotación genómica. Comparación genómica Si bien el análisis de un genoma único ofrece enormes conocimientos biológicos sobre cualquier organismo, el análisis comparativo de múltiples genomas proporciona mucha más información sobre la fisiología y la evolución de las especies microbianas y amplía la capacidad para asignar una mejor función putativa a los genes predichos. El análisis comparativo ofrece una nueva perspectiva en las relaciones entre los genes homólogos (Koonin et al., 2005). Comparando secuencias de genes entre los genomas y dentro de cada genoma, es posible reconstruir la historia evolutiva de cada gen. Esto, a Spanish Summary 284 su vez, permite una mejor comprensión de las adaptaciones específicas de los genomas (Koonin et al., 2005). La genómica comparativa implica el uso de programas que puedan alinear numerosos genomas y buscar regiones semejantes entre ellos. Algunas de estas herramientas de similitud de secuencias son accesibles al público a través de Internet, el más utilizado es el ya mencionado BLAST. En el Capítulo 2 se utilizó el criterio denominado Reciprocal Best Match (RBM) para encontrar ortólogos (genes homólogos con la misma función relacionados a través de la especiación) y parálogos (genes homólogos relacionados a través de la duplicación y que evolucionan originando nuevas funciones) entre y dentro de diferentes representantes de Bacteroidetes marinos. Esto no es más que un BLAST en dos sentidos, el gen a contra el gen b y viceversa, y si la similitud es buena (según los parámetros introducidos) en ambas comparaciones, entonces se consideran genes homólogos. Con el fin de explorar y visualizar fácilmente los resultados, se utilizó el programa JCoast, www.jcoast.net (Richter et al., 2008), que permite encontrar rápidamente un gen de interés y compararlo con sus ortólogos en otros genomas. Predicción de Islas Genómicas Es posible detectar islas genómicas (IG) gracias a los diversos programas que recientemente se han desarrollado. En el Capítulo 3 elegimos IslandViewer, una interfaz integrada para la identificación y la visualización de las islas genómicas (Langille y Brinkman, 2009; Langille et al., 2010). IslandViewer reúne tres métodos diferentes: SIGI-HMM (mide el uso de codones), IslandPath-DIMOB (detecta en la irregularidades en composición de la secuencia o la presencia de elementos móviles), e IslandPick (utiliza la genómica comparativa). Este sitio en la red contiene los resultados pre-calculados para un gran número de genomas secuenciados y permite al usuario enviar genomas para ser ananlizados. Resumen en español 285 Experimentos “in vivo” Cultivos Como complemento a la genómica, en el Capítulo 4, se realizó un considerable esfuerzo para desarrollar un medio de cultivo definido donde los Bacteroidetes pudiesen crecer con el fin de examinar sus adaptaciones fisiológicas. Microplacas BIOLOG MT Estas placas se crearon para análisis de comunidades microbianas y estudios de ecología microbiana (Garland y Mills, 1991; Insam, 1997), permitiendo determinar las características fisiológicas de la comunidad y distinguir cambios espaciales y temporales. Las placas tienen 96 pocillos y contienen una fuente de carbono y l violeta de tetrazolio como un indicador redox de utilización de la fuente de carbono. Cuando las bacterias oxidan el compuesto, el indicador cambia a color púrpura. Los usamos en el Capítulo 5 en un intento de detectar las actividades de degradación de polímeros de una comunidad microbiana. Spanish Summary 286 RESUMEN Y RESULTADOS CAPÍTULO 1 Análisis del genoma de Polaribacter sp. MED152, una bacteria marina que contine la proteorodopsina El análisis de genomas de cianobacterias y proteobacterias marinas ha proporcionado un profundo conocimiento acerca de las estrategias de vida de estos organismos, su diferenciación en ecotipos y su metabolismo. Sin embargo, todavía falta un análisis comparable para los Bacteroidetes, el tercer mayor grupo de microorganismos del plancton marino. En este capítulo presentamos el análisis completo del genoma de Polaribacter sp. MED152. Encontarmos que, por un lado, MED152 contiene un número importante de genes para la adhesión a superficies o partículas, motilidad por reptación y degradación de polímeros. Esto concuerda con la estrategia de vida que en la actualidad se le da a los Bacteroidetes marinos. Por otro lado, también observamos que este microorganismo contiene el gen de la proteorodopsina, junto con un notable conjunto de genes para detectar y responder a la luz, que podría proporcionar una ventaja para su supervivencia en la superfície iluminada de océanos pobres en nutrientes, en la búsqueda de nuevas partículas que colonizar. Por otra parte, vimos aumento en la fijación de CO2 en presencia de luz, cosa que indicaba que el metabolismo central limitado podría complementarse con la fijación anaplerótica de carbono inorgánico, mediante una combinación única de transportadores de membrana y carboxilasas. Esto sugiere una estrategia de doble vida que, si se confirma experimentalmente, sería notablemente diferente de lo que se conoce en los otros dos grupos principales de bacterias (cianobacterias autótrofas y proteobacterias heterótrofas) en la superficie del océano. El genoma de Polaribacter ha proporcionado nuevos conocimientos sobre las capacidades fisiológicas de las bacterias que contienen proteorodopsina. Este genoma Resumen en español 293 Figura 10. Número de genomas completos de los grupos marinos más abundantes en NCBI (GenBank) y la Fundación G. & B. Moore (actualizada 07052011). SÍNTESIS DE RESULTADOS Y DISCUSIÓN GENERAL Los Bacteroidetes marinos desde una perspectiva genética y fisiológica El propósito de la presente tesis es el de aumentar la comprensión acerca de la genómica y la ecofisiología de los Bacteroidetes marinos usando aproximaciones genómicas y cultivos bacterianos. Los Bacteroidetes son uno de los tres grupos más abundantes de bacterias en el océano (Alonso et al., 2007, Alonso-Sáez and Gasol 2007). En los últimos años, el número de genomas bacterianos completos ha ido aumentando en bases de datos tales como GenBank. Actualmente, el número de genomas completos de Bacteroidetes representa la mayor proporción (8,9%) después de las Proteobacterias (29,4% gamma17,8% y alphaproteobacteria 11,6%) y Firmicutes (22,9%)(Fig. 10A). Además, la Fundación Gordon y Betty Moore ha secuenciado 16 Bacteroidetes marinos de un total de 182 genomas bacterianos marinos (Fig. 10B). Spanish Summary 294 En la presente tesis se han estudiado diferentes características de las Flavobacterias, la clase más abundante entre los Bacteroidetes marinos, centrándonos sobre todo en dos rasgos principales: respuesta a la luz y la degradación de polímeros. Como representante modelo de las Flavobacterias escogimos Polaribacter sp. MED152. El género Polaribacter es uno de los más abundantes en el océano. En 2004, el 9% del total de secuencias del gen del 16S depositadas en GenBank de Bacteroidetes marinos pertenecía al género Polaribacter (Pommier et al., 2005), y de éstas, el 36% estaban estrechamente relacionadas con MED152. También se ha observado que MED152 es el décimo aislado que recupera más secuencias en estudios de metagenomas marinos (Yooseph et al., 2010). Además, usando FISH se ha encontrado que el género Polaribacter una muestra una abundancia media del 17% del total de células contadas en el océano Ártico (Nikrad et al., 2012). Por lo tanto, su elevada abundancia en el bacterioplancton marino junto con el hecho de poseer la proteorodopsina hacían de MED152 un genoma muy atractivo para ser estudiado. Así, en el Capítulo 1, el estudio del genoma de MED152 abrió una ventana a la comprensión de la adaptación evolutiva de estos organismos para crecer en entornos oligotróficos iluminados. Con el fin de comprobar si se podrían encontrar patrones comunes en otras Flavobacterias y compararlos con otros grupos de bacterias, se analizaron genomas adicionales de Flavobacterias en los Capítulos 2 y 3, incluyendo algunos representantes de los grupos bacterianos más abundantes del océano como las Proteobacterias y las Cianobacterias. Se examinaron posibles patrones debido a la presencia del gen de la PR, en la degradación polímeros y en el contenido de islas genómicas. Se intentó comprobar experimentalmente algunas de las hipótesis derivadas de estos estudios in silico en los Capítulos 4 y 5 por medio de cultivos puros y pruebas bioquímicas en las comunidades microbianas naturales. La Figura 11 muestra la relación entre los capítulos. Resumen en español 295 Alternancia de estilos de vida para sobrevivir en la escasez Es arriesgado hablar de la ecología de un organismo simplemente mediante el análisis de su genoma, pero los genes que se encuentran en un genoma pueden proporcionar una gran cantidad de información sobre las posibles estrategias de estos organismos. En el Capítulo 1, el genoma de Polaribacter sp. MED152 sugirió una posible Figura 11. Relación entre los capítulos de esta tesis. El genoma Polaribacter sp. MED152 fue analizado en el Capítulo 1. En el Capítulo 2 se compararon más Flavobacterias buscando patrones comunes que podrían estar presentes en sus genomas y en el Capítulo 3 se añadieron todavía más genomas para el estudio de los patrones en las islas genómicas en el bacterioplancton marino. Como algunas de estas Flavobacterias habían sido aisladas, en el Capítulo 4 las pudimos utilizar para llevar a cabo experimentos in vivo tratando de resolver algunas de las preguntas que aparecieron cuando analizamos sus genomas. Por último, en el Capítulo 5 nos fuimos directamente al medio natural y estudiamos la comunidad microbiana in situ. Spanish Summary 296 Figura 12. Modelo simplificado para el procesado los polisacáridos basado en el Sistema Sus en Bacteroides thetaiotaomicron. Adaptado de Martens EC et al., J. Biol Chem (2009). alternancia de estilos de vida de acuerdo a los niveles de materia orgánica en el océano. Cuando las partículas de alto peso molecular (HMW-DOM) fueran abundantes, MED152 podría colonizarlas y moverse sobre su superficie por reptación. Pero una vez que todos los sustratos poliméricos hubieran sido consumidos, MED152 podría llevar una existencia de vida libre gracias a su capacidad para responder a la luz. Por otra parte, un aumento en la fijación de CO2 en presencia de luz sugiere que su metabolismo central limitado podría complementarse con la fijación anaplerótica de carbono inorgánico. a) La vida en abundancia: adhesión y degradación de los polímeros En general, los Bacteroidetes son conocidos como consumidores eficientes de los polímeros tales como polisacáridos y proteínas (Cottrell y Kirchman 2000;. Woyke et al., 2009). Siendo así, deberíamos encontrar en el genoma de Polaribacter evidencias que corroborasen este hecho. Y así fue, MED152 poseía un gran potencial glicolítico, debido a sus 29 glicosil hidrolasas y 81 peptidasas. También es posible que MED152 pudiera producir exopolisacáridos involucrados en la fijación no específica a partículas, ya que su genoma codifica 32 glicosil transferasas (Corpe et al., 1976; Sutherland et al., 1985). Resumen en español 297 Se sabe también que la materia orgánica polimérica puede estar unida por complejos de membrana externa (Figura 12), formados por SusC, un canal de ligando, y SusD, una proteína de membrana externa (complejos SusCD), que actuan como entidades de unión a polisacáridos antes de iniciar su degradación (Anderson y Salyers 1989; Shipman et al., 2000; Blanvillain et al., 2007). En estos complejos, las enzimas hidrolíticas se encuentran en la superficie de la bacteria, pero también hay proteínas de membrana externa que unen los polisacáridos a la superficie bacteriana (SusD) (Reeves et al., 1997). Se encontraron cinco complejos SusCD en MED152 (Capítulo 1, Fig. S7; Capítulo 2, Tabla SM9). Esta es una clara evidencia de que la adherencia y la degradación están estrechamente unidas a la utilización eficiente de polímeros. Estudios recientes han encontrado que los transportadores dependientes de TonB eran muy abundantes en las comunidades microbianas marinas y, más aún, que la energía para el transporte de solutos podría estar proporcionada por la PR (Morris et al., 2010). De hecho, los transportadores dependientes de TonB son, junto con los transportadores ABC, el tipo de transportadores más abundante en MED152, representando 3,9% del total de transportadores. Por otra parte, MED152 tiene un conjunto completo de genes (15) que participan en la motilidad por reptación, lo que sería beneficioso para la exploración de superficies sólidas. A pesar de que no se comprende totalmente, parece que la capacidad de deslizarse sobre la superficie podría proporcionar a las células una ventaja selectiva para la utilización de polímeros. Este es el mecanismo predicho para C. hutchinsonii (Xie et al., 2007) y F. johnsoniae (Braun et al., 2005) para la utilización de celulosa y quitina, respectivamente. Además, hasta 26 genes contienen dominios involucrados en la adherencia a superficies (Capítulo 1, Tabla SM9), algunos de ellos en complejos hidrolíticos que incluyen SusC y SusD (Capítulo 1, Fig. SM7). Spanish Summary 298 b) Cuando se agota el DOM: sistema de captación de la luz La luz en un factor ambiental importante y la principal fuente de energía en la biosfera. Por tanto, los organimos han evolucionado para responder a ella para optimizar su crecimiento y metabolismo. Uno de los puntos clave del genoma de MED152 es la presencia del gen de la proteorodopsina (PR) y genes para la síntesis del retinal (cromóforo de la PR). Además contiene bastantes genes relacionados con respuestas de regulación a la luz (Capítulo 1, Tabla SM6). Fue interesante descubrir que MED152 posee un fitocromo, una proteína que responde a las regiones del rojo o rojo lejano del espectro de luz visible que también está presente en cianobacterias y en plantas, donde la activación del fitocromo regula aproximadamente el 10% de los genes presentes en plantas (Sharrok, 2008) . A pesar de que la vía completa de transducción de señales de la respuesta del fitocromo aún no ha sido descrita, existe evidencia de que en las plantas los fitocromos tienen actividad en la transducción de señales (Sharrok, 2008). Por lo tanto, su presencia en MED152 sugiere que esta proteína contribuye a la regulación de la síntesis de proteínas que responden a la luz. La fototrofía mediada por la PR había sido sugerida para complementar las necesidades energéticas de las células en presencia de luz, disminuyendo la cantidad de carbono respirado. Sin embargo, esto representa un desafío para la célula, resultando en un desequilibrio del ciclo de Krebs, que MED152 podría resolver con la fijación anapleróticade CO2, generando oxaloacetato a partir de bicarbonato a través de las enzimas PEP y piruvato carboxilasas (Capítulo 1, Fig. SM4). Cuando la luz es la única fuente de ATP, el ciclo de Krebs es supuestamente utilizado para fines biosintéticos y no para la generación de energía (como en los organismos autótrofos). El ciclo del glioxilato (que también está presente en MED152, Capítulo 1, Fig. SM3) permite el crecimiento con algunos compuestos que entran en la parte derecha del ciclo de Krebs, como lípidos o acetato. Pero en MED152, que puede obtener energía de la luz, esta vía metabólica podría jugar un papel importante en la regeneración de oxalacetato. La vía alternativa del glioxilato no está presente en las bacterias autotróficas, pero sí en plantas y muchas otras bacterias. Resumen en español 299 La Figura 13 compara Prochlorococcus marinus y Polaribacter sp. MED152. Se observa el tipo de ciclo de Krebs en herradura en Prochlorococcus. Esto es típico de autótrofos estrictos, ya que no necesitan completar el ciclo por no ser oxidativo. Por lo tanto carecen de una de las enzimas: la alfa-cetoglutarato deshidrogenasa. Figura 13. Comparación entre (A) Polaribacter sp. MED152 y (B) Prochlorococcus marinus str. SS120. Nótese que los transportadores son similares porque incorporan los mismos nutrientes y también se basan en el gradiente de Na+. Algunas diferencias importantes son el ciclo de Calvin y la parte derecha de la célula donde aparecen los fotosistemas y la cadena de transporte de electrones. MED152 no tiene el ciclo de Calvin ni cualquier otro ciclo para fijar CO2 autotróficamente. Spanish Summary 300 Encontramos que MED152 fija mayor cantidad de bicarbonato en la luz que en la oscuridad cuando crece en un medio relativamente rico (Marine Broth® 8 veces diluido) (Capítulo 1, Fig. 3 y Capítulo 4, Fig. 7). Esto sugiere que la fijación anaplerótica de carbono inorgánico estimulada por la luz podría permitir a las Flavobacterias que contienen proteorhodopsina utilizar eficientemente la materia orgánica para biosíntesis. Por lo tanto, teniendo la capacidad de unirse a partículas, degradarlas e incorporar las moléculas pequeñas resultantes al interior de la célula, MED152 sería capaz de sobrevivir mientras haya materia orgánica presente en el océano. Una vez que estas partículas se han agotado, la PR podría proporcionar la energía necesaria para sobrevivir sin necesidad de respirar compuestos orgánicos. La Figura 14 muestra un modelo hipotético de las estrategias de MED152 en el océano. Figura 14. Modelo sobre las estratégias de vida de Polaribacter sp. MED152 en el océano. Resumen en español 301 Patrones entre Bacteroidetes marinos El primer genoma íntegro de Bacteroidetes marino que se analizó fue el de Gramella forsetii KT0803 (sin PR) (Bauer et al., 2006), indicando una clara adaptación a la degradación de compuestos de alto peso molecular. Polaribacter sp. MED152 fue el segundo genoma de esta clase taxonómica que se analizó y resultó tener las mismas adaptaciones para la degradación de polímeros (Capítulo 1). Dado que esta habilidad de degradación parece ser un patrón recurrente e independiente al hecho de poseer la PR, la comparación con más genomas de Bacteroidetes marinos, con (PR +) y sin (PR-) proteorodopsina, nos ayudaría a identificar los patrones generales entre representantes de esta clase taxonómica. a) Correlación entre la posesión del gen PR y el tamaño del genoma. Es curioso que todos los genomas de Bacteroidetes PR+ son pequeños (Capítulo 2, Fig. 1). Como se vio en el Capítulo 1, el genoma de MED152 es muy pequeño (2,9 Mb). MED134 también posee el gen de la PR y los dos tienen genomas más pequeños que los otros dos genomas PR-, Gramella forsetii y MED217 (Capítulo 2, Tabla 1). Es tentador pensar que de alguna manera la PR permite a las bacterias reducir sus genomas, de modo que no sería necesario poseer los genes de muchas vías metabólicas diferentes para la utilización de carbono porque la energía de la luz haría que fuesen más independientes de compuestos orgánicos como fuente de energía. b) ¿Están las bacterias PR+ mejor adaptadas a vivir en condiciones oligotróficas? En el Capítulo 1 propusimos que la PR, junto con otros genes de detección a la luz y fijación anaplerótica de carbono, representaban adaptaciones para sobrevivir en la superficie del océano cuando las concentraciones de materia orgánica eran bajas. El siguiente paso fue probar si la capacidad de responder a la luz y la existencia de la fijación de CO2 en otras Flavobacterias eran características compatibles con la presencia o ausencia de la PR. En cuanto a los dominios de respuesta a la luz, no se observaron diferencias significativas en número al comparar bacterias PR + y PR- (Capítulo 2, Fig. 5). Sin embargo, con la incorporación de más grupos bacterianos para el análisis, Spanish Summary 302 como cianobacterias o proteobacterias, aparecieron diferentes patrones de dominios de respuesta a la luz (Capítulo 2, Tabla 3), lo que sugiere una ligera diferencia en la estrategia de su uso. Respecto a las enzimas que intervienen en la fijación de CO2 (comentadas en el Capítulo 1: piruvato y la PEP carboxilasa, isocitrato liasa, malato sintasa), hubo una clara correlación entre la posesión de PR y el número de genes antes mencionados (Capítulo 2, Fig. 6B). c) ¿Siguen las bacterias PR + la misma estrategia que MED152 cuando están limitados de materia orgánica? Las adaptaciones a la adhesión y degradación de partículas de MED152 fueron mencionadas en el Capítulo 1. Se observó que las cuatro Flavobacterias tenían un gran número de proteínas con dominios de adhesión a superficies (Capítulo 2, Tabla SM1). Esto también es cierto para otras Flavobacterias, sin embargo, este rasgo no aparecía en otros grupos de bacterias marinas (Capítulo 2, Fig. 8A y 8B). Esto parece una característica en común entre flavobacterias independientemente de la capacidad de responder a la luz, ya que no se observaron diferencias entre especies PR + y PR-. El potencial de degradación observado en el Capítulo 1 también fue corroborado con Flavobacterias adicionales añadidas al estudio (Capítulo 2, Fig. 8C y 8D) que, en general (con algunas excepciones) presentaban la mayor cantidad de glicosil hidrolasas y peptidasas por megabase en comparación con otros grupos. Además, los Bacteroidetes PR+ mostraban significativamente más peptidasas por megabase que los Bacteroidetes PR-, sugiriendo una especialización en la degradación de proteínas (Capítulo 2, Fig. 10) y todos ellos mostraron diferentes conjuntos de estas enzimas, lo que indica una especialización para determinados tipos de proteínas (Capítulo 2, Fig. 11). Así, cada Flavobacteria estaría adaptada a nichos ligeramente diferentes lo que haría dismunir la competencia entre ellos. La Figura 15 muestra la cantidad de glicosil hidrolasas, peptidasas, glicosil transferasas y proteínas de adhesión en grupos como Bacteroidetes, Planctomycetes y Proteobacterias. Nuestras cuatro Flavobacterias tienen la mayor cantidad de glicosil hidrolasas por megabase (Mb), después de los dos Bacteroides spp. que son bien conocidos Resumen en español 309 Figura 17. Número de resultados positivos para los sustratos en microplacas Biolog MT2 durante CFL (A) y en microplacas Eco durante CASES (B). Otra diferencia con CASES fue la época del año con más actividad. Mientras que la parte más activa del año en CFL fue a partir de la primavera, siguiendo el mismo patrón que la clorofila a, en CASES el invierno fue el período del año más activo y la disminución de la actividad comenzó la primavera (Fig. 18). Es difícil dar una respuesta a la posible causa de estas diferencias observadas entre los dos estudios, pero una posible razón se deba probablemente a las diferentes condiciones hidrográficas que presentan la Bahía de Franklin y el Golfo de Amundsen. Spanish Summary 310 Figura 18. Número de sustratos usados a lo largo del año, separados en categorias para CFL (A) y CASES (B). Resumen en español 311 CONCLUSIONES 1. Las características generales del genoma de Polaribacter sp. MED152 son consistentes con una vida en la superficie del océano, incluida la utilización de la luz y un número significativo de proteínas dependientes de Na+. 2. Características más específicas de Polaribacter sp. MED152 revelan adaptaciones para alternar entre la adhesión a partículas y la vida libre. 3. Utilizando la proteorodopsina, Polaribacter sp.MED152 es capaz de capturar la energía que proviene de la luz, aumentar la fijación anaplerótica de bicarbonato y probablemente utilizará los pocos compuestos de carbono que puede conseguir exclusivamente para la biosíntesis. 4. Los Bacteroidetes marinos comparten la capacidad de adhesión, motilidad por repatación, y un gran número de enzimas degradadoras de polímeros. 5. Los Bacteroidetes marinos que contienen PR tienen genomas especialmente pequeños, con más genes implicados en la fijación de CO2 por Mb que los Bacteroidetes sin PR. 6. Las islas genómicas son una característica común en la mayoría de los genomas bacterianos marinos examinados. Cada grupo de bacterias marinas posee un conjunto diferente de genes, indicando posibles diferentes estrategias en el papel que juegan las islas genómicas en la ecología de cada grupo. 7. La transferencia horizontal de genes y la recombinación homóloga tienen un papel importante en la movilidad de fragmentos de DNA entre diferentes taxones y en genomas estrechamente relacionados, respectivamente, modulando el “pool” flexible del genoma. 8. La anotación funcional de los genes presentes en las islas genómicas reveló una ámplia gama de genes biológicamente relevantes . Spanish Summary 312 9. La luz estimula el crecimiento Polaribacter sp. MED152, Flavobacteria que contiene la proteorodopsina, en ambientes limitados por la materia orgánica. 10. La composición del medio de cultivo influye en la probabilidad de encontrar diferencias de crecimiento entre condiciones de luz y oscuridad. 11. La proteorodopsina incrementa la incorporación de bicarbonato en Polaribacter sp. MED152 cuando crece en diferentes medios pobres. 12. Los hidratos de carbono, particularmente moléculas poliméricas, son una fuente importante de carbono para el bacterioplancton ártico. Los aminoácidos también son consumidos, pero su incorporación es bastante variable dependiendo de las áreas y la época del año. Resumen en español 313 PERSPECTIVAS DE FUTURO El interés por las Flavobacterias está aumentando cada día, junto con el número de microoorganismos de este grupo que estan siendo aislados en cultivo puro y los genomas que estan siendo secuenciados. Basándonos en los resultados obtenidos en esta tesis, el examen de algunos de los siguientes aspectos aumentaría la comprensión del papel de los microorganismos (en nuestro caso los Bacteroidetes marinos) en el océano: 1. Secuenciación completa y anotación de más miembros de los Bacteroidetes marinos y no marinos. Aunque el número de aislados es alta, para su estudio sería necesario tener sus genomas completos y todos los genes anotados con el fin de entender y compararlos con otros representantes del mismo o diferentes grupos. 2. Se debe hacer un gran esfuerzo para tratar de descubrir las funciones de las proteínas hipotéticas, que siempre representan un alto porcentaje del genoma y, probablemente, estas proteínas contienen la esencia que hace a cada organismo único. 3. Mejora y desarrollo de técnicas bioinformáticas para el análisis y comparación de varios genomas a la vez. Cada día, hay más y más información para procesar y cada vez más se necesitan máquinas más sofisticadas y poderosas para hacer frente a miles de gigabytes de datos. Además, se requerirían nuevos porgramas de ordenador que permitiesen análisis eficientes en un tiempo relativamente corto. 4. Se necesitan más esfuerzos para desarrollar un medio de cultivo completamente definido para Polaribacter y Dokdonia. Asimismo, serían necesarios más estudios para determinar por qué la luz produce diferencias en el crecimiento de estas bacterias con ciertas fuentes de carbono y no con otras. 5. Por último, se deben diseñar placas BIOLOG nuevas, más específicas y probando con nuevos sustratos no utilizados hasta ahora y que pudieran aumentar nuestra comprensión de la diversidad metabólica del bacterioplancton heterotrófico. References (Includes Introduction, Discussion and Spanish Summary) & Annexes References 317 REFERENCES (includes Introduction, Discussion, and Spanish Summary) Alldredge, A.L., Cole, J.J. and Caron, D.A., 1986. Production of feterotrophic Bacteria inhabiting macroscopic organic aggregates (marine snow) from surface waters. Limnol Oceanogr, 31(1): 68-78. Alonso, C., Warnecke, F., Amann, R. and Pernthaler, J., 2007. High local and global diversity of Flavobacteria in marine plankton. Environ Microbiol, 9(5): 1253-1266. Alonso-Sáez, L. and Gasol, J., 2007. Seasonal variations in the contributions of different bacterial groups to the uptake of low-molecular-weight compounds in Northwestern mediterranean coastal waters. Appl Environ Microbiol, 73(11): 3528-3535. Anderson, K.L. and Salyers, A.A., 1989. Genetic evidence that outer membrane binding of starch is required for starch utilization by Bacteroides thetaiotaomicron. J Bacteriol, 171(6): 3199-3204. Altschul, S.F., Gish, W., Miller, W., Myers, E.W. and Lipman, D.J., 1990. Basic local alignment search tool. J Mol Biol, 215(3): 403-410. Amaral-Zettler, L., Artigas, L.F., Baross, J., Loka Bharathi, P.A., Boetius, A., Chandramohan, D., et al., 2010. A Global Census of Marine Life, in: Alasdair D. McIntyre, Ed., Life in the World’s Oceans. Blackwell Publishing Ltd., 223-245 pp. Amon, R.M.W. and Benner, R., 1994. Rapid cycling of high-molecular-weight dissolved organic matter in the ocean. Nature, 369(6481): 549-552. Amon, R.M.W. and Benner, R., 1996. Bacterial utilization of different size classes of dissolved organic matter. Limnol Oceanogr, 41(1): 41-51. Arnosti, C., Durkin, S. and Jeffrey, W.H., 2005. Patterns of extracellular enzyme activities among pelagic marine microbial communities: implications for cycling of dissolved organic carbon. Aquat Microb Ecol, 38(2): 135-145. Azam, F., 1998. Microbial control of oceanic carbon flux: The plot thickens. Science, 280(5364):694-696 Azam, F., Fenchel, T., Field, J. G., Gray, J. S. and Meyer-Reil, L. A., 1983. The ecological role of water-column microbes in the sea. Mar Ecol Prog Ser, 10: 257-263. Bauer, J.E., Williams, P. M. and Druffel, E. R. M., 1992. 14C activity of dissolved organic carbon fractions in the north-central Pacific and Sargasso Sea. Nature, 357(6380): 667-670. Bauer, J.E., 2002. Carbon isotopic composition of DOM, in: Dennis A. Hansell and Craig A. Carlson Eds., Biogeochemistry of Marine Dissolved Organic Matter. Academic Press, San Diego, 405-453 pp. Bauer, M., Kube, M., Teeling, H., Richter, M., Lombardot, T., Allers, E., et al., 2006. Whole genome analysis of the marine BacteroidetesGramella forsetii reveals adaptations to References 318 degradation of polymeric organic matter. Environmental Microbiology, 8(12): 22012213. Béjà, O., Aravind, L., Koonin, E.V., Suzuki, M.T., Hadd, A., Nguyen, L. et al., 2000. Bacterial rhodopsin: evidence for a new type of phototrophy in the sea. Science, 289(5486): 1902-1906. Benner, R., 2002. Chemical composition and reactivity, in: Dennis A. Hansell and Craig A. Carlson Eds., Biochemistry of Marine Dissolved Organic Matter. Academic Press, San Diego, 59-90 pp. Blanvillain, S., Meyer, D., Boulanger, A., Lautier, M., Guynet, C., Denancé, N. et al ., 2007. Plant carbohydrate scavenging through TonB-dependent receptors: a feature shared by phytopathogenic and aquatic bacteria. PLoS ONE, 2. Boucher, Y., Douady, C.J., Papke, R.T., Walsh, D. A., Boudreau, M.E.R., Nesbø, C. L. et al., 2003. Lateral gene transfer and the origins of prokaryotic groups. Ann Rev Genet, 37(1): 283-328. Braun, T.F., Khubbar, M.K., Saffarini, D.A. and McBride, M.J., 2005. Flavobacterium johnsoniae gliding motility genes identified by mariner Mutagenesis. J Bacteriol, 187(20): 69436952. Bryden, H.L., Longworth, H. R. and Cunningham, S. A., 2005. Slowing of the Atlantic meridional overturning circulation at 25° N. Nature, 438(7068): 655-657. Campbell, B.J., Waidner, L.A., Cottrell, M.T. and Kirchman, D.L., 2008. Abundant proteorhodopsin genes in the North Atlantic Ocean. Environ Microbiol, 10(1): 99-109. Chen, K. and Pachter, L., 2005. Bioinformatics for whole-genome shotgun sequencing of microbial communities. PLoS Comput Biol, 1(2): e24. Chin, W.-C., Orellana, M.V. and Verdugo, P., 1998. Spontaneous assembly of marine dissolved organic matter into polymer gels. Nature, 391(6667): 568-572. Chisholm, S.W., Olson, R.J., Zettler, E.R., Goericke, R., Waterbury, J.B. and Welschmeyer, N. A., 1988. A novel free-living prochlorophyte abundant in the oceanic euphotic zone. Nature, 334(6180): 340-343. Coleman, M., Sullivan, M., Martiny, A., Steglich, C., Barry, K., Delong. E. et al., 2006. Genomic islands and the ecology and evolution of Prochlorococcus. Science, 311(5768): 17681770. Corpe, W.A., Matsuuchi, L. and Armbruster, B., 1976. Secretion of adhesive polymers and attachment of marine bacteria to surface, in: J. M Sharpley and A. M. Kaplan, Ed., Proceedings of the Third International Biodegradation Symposium, 433-442 pp, London References 319 Cottrell, M.T. and Kirchman, D.L., 2000a. Community composition of marine bacterioplankton determined by 16S rRNA gene clone libraries and fluorescence in situ hybridization. Appl Environ Microbiol, 66(12): 5116-5122. Cottrell, M.T. and Kirchman, D.L., 2000b. Natural assemblages of marine Proteobacteria and members of the Cytophaga-Flavobacteria cluster consuming lowand high-molecularweight dissolved organic matter. Appl Environ Microbiol, 66(4): 1692-1697. Cottrell, M.T., Yu, L. and Kirchman, D.L., 2005. Sequence and expression analyses of Cytophagalike hydrolases in a Western Arctic metagenomic library and the Sargasso Sea. Appl Environ Microbiol, 71(12): 8506-8513. Davis Jr., R A., 1972. Principles of Oceanography. Addison-Wesley Publishing Company, Philippines. de la Torre, J R., Christianson, L.M., Béjà, O., Suzuki, M.T., Karl, D M., Heidelberg, J. et al., 2003. Proteorhodopsin genes are distributed among divergent marine bacterial taxa. Proc Natl Acad Sci U.S.A, 100(22): 12830-12835. DeLong, E F., Franks, D.G. and Alldredge, A.L., 1993. Phylogenetic diversity of aggregateattached vs. free-Living marine bacterial Assemblages. Limnol Oceanogr, 38(5): 924934. Dobrindt, U., Hochhut, B., Hentschel, U. and Hacker, J., 2004. Genomic islands in pathogenic and environmental microorganisms. Nat Rev Microbiol, 2(5): 414-424. Doolittle, W.F., 1999. Lateral genomics. Trends Cell Biol, 9(12): M5-M8. Ducklow, H.W., 1983. Production and fate of bacteria in the oceans. BioScience, 33(8): 494501. Dufresne, A., Garczarek, L. and Partensky, F., 2005. Accelerated evolution associated with genome reduction in a free-living prokaryote. Genome Biol, 6(2). Engel, A., Thoms, S., Riebesell, U., Rochelle-Newall, E. and Zondervan, I., 2004. Polysaccharide aggregation as a potential sink of marine dissolved organic carbon. Nature, 428(6986): 929-932. Falkowski, P., Scholes, R.J., Boyle, E., Canadell, J., Canfield, D., Elser, J. et al., 2000. The global carbon cycle: a test of our knowledge of earth as a system. Science, 290(5490): 291296. Falkowski, P G., Barber, R.T. and Smetacek, V., 1998. Biogeochemical controls and feedbacks on ocean primary production. Science, 281(5374): 200-206. Falkowski, P.G., Fenchel, T. and Delong, E.F., 2008. The Microbial engines that drive Earth’s biogeochemical cycles. Science, 320(5879): 1034-1039. Fenchel, T., 1988. Marine plankton food chains. Ann Rev Ecol Syst, 19(1): 19-38. References 320 Field, C.B., Behrenfeld, M.J., Randerson, J.T. and Falkowski, P., 1998. Primary production of the biosphere: integrating terrestrial and oceanic components. Science, 281(5374): 237-240. Finegold, S., Sutter, V. and Mathisen, G., 1983. Normal indigenous intestinal flora, in: Hentges D.J (ed.), Human intestinal microflora in health and disease. Academic Press, New York, 3-31 pp. Finn, R.D. Tate, J., Mistry, J., Coggill, P. C., Sammut, S J., Hotz, H.-R. et al., 2008. The Pfam protein families database. Nucleic Acids Res, 36(suppl 1): D281-D288. Fogg, G.E., 1958. Extracellular products of phytoplankton and the estimation of primary production. Rapp. P.-r. Réun. Cons. perm. int. Explor. Mer. , 144: 56-60 Frigaard, N.-U., Martínez, A., Mincer, T.J. and DeLong, E.F., 2006. Proteorhodopsin lateral gene transfer between marine planktonic Bacteria and Archaea. Nature, 439(7078): 847850. Fuhrman, J.A., Schwalbach, M.S. and Stingl, U., 2008. Proteorhodopsins: an array of physiological roles? Nat Rev Microbiol, 6(6): 488-494. Garland, J. and Mills, A., 1991. Classification and characterization of heterotrophic microbial communities on the basis of patterns of community-level sole-carbon-source utilization. Appl Environ Microbiol, 57(8): 2351-2359. Giovannoni, S. and Rappé, M., 2000. Evolution, diversity and molecular ecology of marine prokaryotes, in: Kirchman, D. L., (Ed.), Microbial Ecology of the Ocean. Wiley-Liss, New York, 47-84 pp. Giovannoni, S.J., Foster, R.A., Rappé, M.S. and Epstein, S., 2007. New cultivation strategies bring more microbial plankton species into the laboratory. Oceanography, 22(2): 6269. Giovannoni, S.J., Tripp, H.J., Givan, S., Podar, M., Vergin, K.L., Baptista, D. et al., 2005. Genome streamlining in a cosmopolitan oceanic bacterium. Science, 309(5738): 1242-1245. Glöckner, F.O., Fuchs, B. M. and Amann, R., 1999. Bacterioplankton compositions of lakes and oceans: a first comparison based on fluorescence in situ hybridization. Appl Environ Microbiol, 65(8): 3721-3726. Glöckner, F.O., Kube, M., Bauer, M., Teeling, H., Lombardot, T., Ludwig, W. et al., 2003. Complete genome sequence of the marine planctomycete Pirellula sp. strain 1. . Proc Natl Acad Sci U.S.A, 100(14): 8298-8303. Gómez-Consarnau, L., González, J.M., Coll-Lladó, M., Gourdon, P., Pascher, T., Neutze, R. et al., 2007. Light stimulates growth of proteorhodopsin-containing marine Flavobacteria. Nature, 445(7124): 210-213. González, J.M. and Moran, M.A., 1997. Numerical dominance of a group of marine bacteria in the alpha-subclass of the class Proteobacteria in coastal seawater. Appl Environ ABBREVIATIONS INDEX List of the abbreviations and acronyms used in this thesis: AAnP: Aerobic Anoxygenic Photosynthesis ABC transporters: ATP-binding cassette transporters ATP: Adenosine triphosphate BBMO: Blanes Bay Microbial Observatory Bchl a: Bacteriochlorophyll a BLAST: Basic Local Alignment Search Tool CAZy: Carbohydrate-Active enzymes database CFB: Cytophaga-Flavobacteria-Bacteroidetes Chl a: Chlorophyll a COG: Cluster of Orthologous Groups CTD: Conductivity, temperature, depth DAPI: 4,6-diamidino-2-phenylindole DMSO: Dimethyl sulfoxide DMSP: Dimethylsulfoniopropionate DOC: Dissolved organic carbon DOM: Dissolved organic matter EPS: Exopolysaccharides ExPASy: Expert Protein Analysis System FISH: Fluorescence in situ hibridization GH: Glycoside hydrolases GI: Genomic Island GO: Gene Ontology GOS: Global Ocean Survey HGT: Horizontal Gene Transfer HMW-DOM: High molecular weight DOM HP: Hypothetical protein KEGG: Kyoto Encyclopedia of Genes and Genomes NCBI: National Center for Biotechnology Information OM: Organic matter ORF: Open reading frame PR: Proteorhodopsin TOC: Total Organic Carbon Annexes 327 SERVERS, DATABASES AND INSTITUTIONS NCBI (National Center for Biotechnology Information): http://www.ncbi.nlm.nih.gov EMBL (The European Molecular Biology Laboratory): http://www.embl.de/ JGI (Joint Genome Institute): http://www.jgi.doe.gov/ KEGG (Kyoto Encyclopedia of Genes and Genomes): http://www.genome.jp/kegg/ ExPASy (Expert Protein Analysis System): http://expasy.org/ CAZy database (Carbohydrate-Active Enzymes): http://www.cazy.org/ MEROPS, the Peptidase Database: http://merops.sanger.ac.uk/ GenDB: http://www.cebitec.uni-bielefeld.de/groups/brf/software/gendb_info/ Silva: http://www.arb-silva.de/ BLAST (Basic Alignment Search Tool): http://blast.ncbi.nlm.nih.gov/Blast.cgi JCoast (Comparative Analysis and Search Tool): http://www.jcoast.net/ IslandViewer: http://www.pathogenomics.sfu.ca/islandviewer/query.php CAMERA database (Community Cyberinfrastructure for Advanced Microbial Ecology Research and Analysis): http://camera.calit2.net/ Pfam (Protein family database): http://pfam.sanger.ac.uk/ Gen Ontology database: http://www.geneontology.org/ COG (Cluster of Orthologous Genes) database: http://www.ncbi.nlm.nih.gov/COG/ MAFFT: http://mafft.cbrc.jp/alignment/software/ RaxML Server: http://phylobench.vital-it.ch/raxml-bb/ iTOL: http://itol.embl.de/ gBlocks Server: http://molevol.cmima.csic.es/castresana/Gblocks.html Betty and Moore Foundation: http://www.moore.org/ Craig Venter Institute: http://www.jcvi.org/ BBMO: http://www.icm.csic.es/bio/projects/icmicrobis/bbmo/ Annexes 328 “Science will always be a search, never a real discovery. It is a journey, never a finish” Karl Popper