coastal bivalve, *Solemya velum*: a blueprint for thriving in and out of symbiosis. *BMC Genomics* **15**:924. doi: 10.1186/1471-2164-15-924.

Dobrindt U, Hochhut B, Hentschel U, Hacker J. 2004. Genomic islands in pathogenic and environmental microorganisms. *Nature Reviews Microbiology* **2**:414–424. doi: 10.1038/nrmicro884.

Douglas AE. 2014. *The symbiotic habit*.

Dubilier N, Bergin C, Lott C. 2008. Symbiotic diversity in marine animals: the art of harnessing chemosynthesis. *Nature Reviews Microbiology* **6**:725–740. doi: 10.1038/nrmicro1992.

Duperron S, Bergin C, Zielinski F, Blazejak A, Perthaler A, McKiness ZP, DeChaine E, Cavanaugh CM, Dubilier N. 2006. A dual symbiosis shared by two mussel species, *Bathymodiolus azoricus* and *Bathymodiolus puteoserpentis* (Bivalvia: Mytilidae), from hydrothermal vents along the northern Mid-Atlantic Ridge. *Environmental Microbiology* **8**:1441–1447.

Duperron S, Halary S, Lorion J, Sibuet M, Gaill F. 2008. Unexpected co-occurrence of six bacterial symbionts in the gills of the cold seep mussel *Idas* sp. (Bivalvia: Mytilidae). *Environmental Microbiology* **10**:433–445. doi: 10.1111/j.1462-2920.2007.01465.x.

Duperron S, Gaudron SM, Rodrigues CF, Cunha MR, Decker C, Olu K. 2013. An overview of chemosynthetic symbioses in bivalves from the North Atlantic and Mediterranean sea. *Biogeosciences* **10**:3241–3267. doi: 10.5194/bg-10-3241-2013.

Elias JE, Gygi SP. 2007. Target-decoy search strategy for increased confidence in large-scale protein identifications by mass spectrometry. *Nature Methods* **4**:207–214. doi: 10.1038/nmeth1019.

Emanuelsson O, Brunak S, von Heijne G, Nielsen H. 2007. Locating proteins in the cell using TargetP, SignalP and related tools. *Nature Protocols* **2**:953–971. doi: 10.1038/nprot.2007.131.

Eng JK, McCormack AL, Yates JR III. 1994. An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database. *Journal of the American Society for Mass Spectrometry* **5**:976–989. doi: 10.1016/1044-0305(94)80016-2.

Eymann C, Dreisbach A, Albrecht D, Bernhardt J, Becher D, Gentner S, Tam le T, Büttner K, Buurman G, Scharf C, Venz S, Völker U, Hecker M. 2004. A comprehensive proteome map of growing *Bacillus subtilis* cells. *Proteomics* **4**:2849–2876. doi: 10.1002/pmic.200400907.

Finn RD, Clements J, Eddy SR. 2011. HMMER web server: interactive sequence similarity searching. *Nucleic Acids Research* **39**:W29. doi: 10.1093/nar/gkr367.

Fisher CR, Brooks JM, Vodenichar JS, Zande JM, Childress JJ, Burke RA Jr. 1993. The co-occurrence of methanotrophic and chemoautotrophic sulfur-oxidizing bacterial symbionts in a deep-sea mussel. *Marine Ecology* **14**:277–289. doi: 10.1111/j.1439-0485.1993.tb00001.x.

Florens L, Carozza MJ, Swanson SK, Fournier M, Coleman MK, Workman JL, Washburn MP. 2006. Analyzing chromatin remodeling complexes using shotgun proteomics and normalized spectral abundance factors. *Methods* **40**:303–311. doi: 10.1016/j.ymeth.2006.07.028.

Fontanez KM, Cavanaugh CM. 2014. Evidence for horizontal transmission from multilocus phylogeny of deep-sea mussel (Mytilidae) symbionts: horizontal transmission of mussel symbionts. *Environmental Microbiology* **16**:3608–3621. doi: 10.1111/1462-2920.12379.

Galagan JE. 2014. Genomic insights into tuberculosis. *Nature Reviews Genetics* **15**:307–320. doi: 10.1038/nrg3664.

Gardebrecht A, Markert S, Sievert SM, Felbeck H, Thürmer A, Albrecht D, Wollherr A, Kabisch J, Le Bris N, Lehmann R, Daniel R, Liesegang H, Hecker M, Schweder T. 2012. Physiological homogeneity among the endosymbionts of *Riftia pachyptila* and *Tevnia jerichonana* revealed by proteogenomics. *The ISME Journal* **6**:766–776. doi: 10.1038/ismej.2011.137.

Gebruk AV, Chevaldonné P, Shank T, Lutz RA, Vrijenhoek RC. 2000. Deep-sea hydrothermal vent communities of the Logatchev area (14'45'N, Mid-Atlantic Ridge): diverse biotopes and high biomass. *Journal of the Marine Biological Association of the UK* **80**:383–393. doi: 10.1017/S0025315499002088.

Goffredi SK, Yi H, Zhang Q, Klann JE, Struve IA, Vrijenhoek RC, Brown CT. 2014. Genomic versatility and functional variation between two dominant heterotrophic symbionts of deep-sea *Osedax* worms. *The ISME Journal* **8**:908–924. doi: 10.1038/ismej.2013.201.

Gogarten JP, Townsend JP. 2005. Horizontal gene transfer, genome innovation and evolution. *Nature Reviews Microbiology* **3**:679–687. doi: 10.1038/nrmicro1204.

Goodrich-Blair H, Clarke DJ. 2007. Mutualism and pathogenesis in *Xenorhabdus* and *Photorhabdus*: two roads to the same destination. *Molecular Microbiology* **64**:260–268. doi: 10.1111/j.1365-2958.2007.05671.x.

Haglund CM, Welch MD. 2011. Pathogens and polymers: microbe-host interactions illuminate the cytoskeleton. *The Journal of Cell Biology* **195**:7–17. doi: 10.1083/jcb.201103148.

Halary S, Riou V, Gaill F, Boudier T, Duperron S. 2008. 3D FISH for the quantification of methane- and sulphur-oxidizing endosymbionts in bacteriocytes of the hydrothermal vent mussel *Bathymodiolus azoricus*. *The ISME Journal* **2**:284–292. doi: 10.1038/ismej.2008.3.

Harada M, Yoshida T, Kuwahara H, Shimamura S, Takaki Y, Kato C, Miwa T, Miyake H, Maruyama T. 2009. Expression of genes for sulfur oxidation in the intracellular chemoautotrophic symbiont of the deep-sea bivalve *Calyptogena okutanii*. *Extremophiles* **13**:895–903. doi: 10.1007/s00792-009-0277-8.

Harmer TL, Rotjan RD, Nussbaumer AD, Bright M, Ng AW, DeChaine EG, Cavanaugh CM. 2008. Free-living tube worm endosymbionts found at deep-sea vents. *Applied and Environmental Microbiology* **74**:3895–3898. doi: 10.1128/AEM.02470-07.

Hart MM, Forsythe J, Oshowski B, Bücking H, Jansa J, Kiers ET. 2013. Hiding in a crowd—does diversity facilitate persistence of a low-quality fungal partner in the mycorrhizal symbiosis? *Symbiosis* **59**:47–56. doi: 10.1007/s13199-012-0197-8.
Heinz E, Williams TA, Nakjang S, Noël CJ, Swan DC, Goldberg AV, Harris SR, Weinmaier T, Markert S, Becher D, Bernhardt J, Dagan T, Hacker C, Lucocq JM, Schweder T, Rattei T, Hall N, Hirt RP, Embley TM. 2012. The genome of the obligate intracellular parasite *Trachipleistophora hominis*: new insights into microsporidian genome dynamics and reductive evolution. *PLOS Pathogens* 8:e1002979. doi: 10.1371/journal.ppat.1002979.

Hentschel U, Steinert M, Hacker J. 2000. Common molecular mechanisms of symbiosis and pathogenesis. *Trends in Microbiology* 8:226-231. doi: 10.1016/S0966-842X(00)01758-3.

Hopkins SH. 1957. B. Parasitism. *Geological society of america memoirs: Geological Society of America*. p. 413-428.

Hueck CJ. 1998. Type III protein secretion systems in bacterial pathogens of animals and plants. *Microbiology and Molecular Biology Reviews* 62:379-433.

Hunter S, Apweiler R, Attwood TK, Bairoch A, Bateman A, Binns D, Bork P, Das U, Daugherty L, Duquenne L, Finn RD, Gough J, Haft D, Hulo N, Kahn D, Kelly E, Laugraud A, Letunic I, Lonsdale D, Lopez R, Madera M, Maslen J, McAnulla C, McDowall J, Mistry J, Mitchell A, Mulder N, Natale D, Orengo C, Quinn AF, Selengut JD, Sigrist CJ, Thimma M, Thomas PD, Valentin F, Wilson D, Wu CH, Yeats C. 2009. InterPro: the integrative protein signature database. *Nucleic Acids Research* 37:D211-D215. doi: 10.1093/nar/gkn785.

Jackson AP, Thomas GH, Parkhill J, Thomson NR. 2009. Evolutionary diversification of an ancient gene family (rhs) through C-terminal displacement. *BMC Genomics* 10:584. doi: 10.1186/1471-2164-10-584.

Jiggins FM, Hurst GDD, Yang Z. 2002. Host-symbiont conflicts: positive selection on an outer membrane protein of parasitic but not mutualistic Rickettsiaceae. *Molecular Biology and Evolution* 19:1341-1349.

Kadar E, Bettencourt R, Costa V, Santos RS, Lobo-da-Cunha A, Dando P. 2005. Experimentally induced endosymbiont loss and re-acquirement in the hydrothermal vent bivalve *Bathymodiolus azoricus*. *Journal of Experimental Marine Biology and Ecology* 318:99-110.

Kaebernick M, Neilan BA, Börner T, Dittmann E. 2000. Light and the transcriptional response of the Microcystin biosynthesis gene cluster. *Applied and Environmental Microbiology* 66:3387-3392. doi: 10.1128/AEM.66.8.3387-3392.2000.

Käll L, Storey JD, MacCoss MJ, Noble WS. 2008. Assigning significance to peptides identified by tandem mass spectrometry using decoy databases. *Journal of Proteome Research* 7:29-34. doi: 10.1021/pr700600n.

Kanehisa M, Goto S, Sato Y, Furumichi M, Tanabe M. 2011. KEGG for integration and interpretation of large-scale molecular data sets. *Nucleic Acids Research* 40:D109-D114. doi: 10.1093/nar/gkr988.

Katoh K, Misawa K, Kuma K, Miyata T. 2002. MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform. *Nucleic Acids Research* 30:3059-3066. doi: 10.1093/nar/gkf436.

Kearse M, Moir R, Wilson A, Stones-Havas S, Cheung M, Sturrock S, Buxton S, Cooper A, Markowitz S, Duran C, Thierer T, Ashton B, Meintjes P, Drummond A. 2012. Geneious basic: an integrated and extendable desktop software platform for the organization and analysis of sequence data. *Bioinformatics* 28:1647-1649. doi: 10.1093/bioinformatics/bts199.

Kelley LA, Sternberg MJE. 2009. Protein structure prediction on the Web: a case study using the Phyre server. *Nature Protocols* 4:363-371. doi: 10.1038/nprot.2009.2.

Kleiner M, Petersen JM, Dubilier N. 2012a. Convergent and divergent evolution of metabolism in sulfur-oxidizing symbionts and the role of horizontal gene transfer. *Current Opinion in Microbiology* 15:621-631. doi: 10.1016/j.mib.2012.09.003.

Kleiner M, Wentrup C, Lott C, Teeling H, Wetzel S, Young J, Chang YJ, Shah M, VerBerkmoes NC, Zarzycki J, Fuchs G, Markert S, Hempel K, Voigt B, Becher D, Liebeke M, Lalk M, Albrecht D, Hecker M, Schweder T, Dubilier N. 2012b. Metaproteomics of a gutless marine worm and its symbiotic microbial community reveal unusual pathways for carbon and energy use. *Proceedings of the National Academy of Sciences of USA* 109:E1173-E1182. doi: 10.1073/pnas.1121198109.

Kobayashi I. 2001. Behavior of restriction-modification systems as selfish mobile elements and their impact on genome evolution. *Nucleic Acids Research* 29:3742-3756. doi: 10.1093/nar/29.18.3742.

Koskiniemi S, Lamoureux JG, Nikolakakis KC, t'Kint de Roodenbeke C, Kaplan MD, Low DA, Hayes CS. 2013. RHS proteins from diverse bacteria mediate intercellular competition. *Proceedings of the National Academy of Sciences of USA* 110:7032-7037. doi: 10.1093/pnas.1300627110.

Krogh A, Larsson B, von Heijne G, Sonnhammer EL. 2001. Predicting transmembrane protein topology with a hidden markov model: application to complete genomes1. *Journal of Molecular Biology* 305:567-580. doi: 10.1006/jmbi.2000.4315.

Kung VL, Khare S, Stehlik C, Bacon EM, Hughes AJ, Hauser AR. 2012. An rhs gene of *Pseudomonas aeruginosa* encodes a virulence protein that activates the inflammasome. *Proceedings of the National Academy of Sciences of USA* 109:1275-1280. doi: 10.1073/pnas.1109285109.

Kuwahara H, Yoshida T, Takaki Y, Shimamura S, Nishi S, Harada M, Matsuyama K, Takishita K, Kawato M, Uematsu K, Fujiwara Y, Sato T, Kato C, Kitagawa M, Kato I, Maruyama T. 2007. Reduced genome of the thioautotrophic intracellular symbiont in a deep-sea clam, *Calyptogena okutanii*. *Current Biology* 17:881-886. doi: 10.1016/j.cub.2007.04.039.

Kwak JS, Jeong H-G, Satchell KJF. 2011. Vibrio vulnificus rtxA1 gene recombination generates toxin variants with altered potency during intestinal infection. *Proceedings of the National Academy of Sciences of USA* 108:1645-1650. doi: 10.1073/pnas.1014339108.

Lagesen K, Hallin P, Rødland EA, Staerfeldt H-H, Rognes T, Ussery DW. 2007. RNAmmer: consistent and rapid annotation of ribosomal RNA genes. *Nucleic Acids Research* 35:3100-3108. doi: 10.1093/nar/gkm160.

Langmead B, Salzberg SL. 2012. Fast gapped-read alignment with Bowtie 2. *Nature Methods* 9:357-359. doi: 10.1038/nmeth.1923.
Heinz E, Williams TA, Nakjang S, Noël CJ, Swan DC, Goldberg AV, Harris SR, Weinmaier T, Markert S, Becher D, Bernhardt J, Dagan T, Hacker C, Lucocq JM, Schweder T, Rattei T, Hall N, Hirt RP, Embley TM. 2012. The genome of the obligate intracellular parasite *Trachipleistophora hominis*: new insights into microsporidian genome dynamics and reductive evolution. *PLOS Pathogens* **8:e1002979. doi: 10.1371/journal.ppat.1002979**.

Hentschel U, Steinert M, Hacker J. 2000. Common molecular mechanisms of symbiosis and pathogenesis. *Trends in Microbiology* **8**:226–231. doi: 10.1016/S0966-842X(00)01758-3.

Hopkins SH. 1957. B. Parasitism. *Geological society of america memoirs: Geological Society of America*. p. 413–428.

Hueck CJ. 1998. Type III protein secretion systems in bacterial pathogens of animals and plants. *Microbiology and Molecular Biology Reviews* **62**:379–433.

Hunter S, Apweiler R, Attwood TK, Bairoch A, Bateman A, Binns D, Bork P, Das U, Daugherty L, Duquenne L, Finn RD, Gough J, Haft D, Hulo N, Kahn D, Kelly E, Laugraud A, Letunic I, Lonsdale D, Lopez R, Madera M, Maslen J, McAnulla C, McDowall J, Mistry J, Mitchell A, Mulder N, Natale D, Orengo C, Quinn AF, Selengut JD, Sigrist CJ, Thimma M, Thomas PD, Valentin F, Wilson D, Wu CH, Yeats C. 2009. InterPro: the integrative protein signature database. *Nucleic Acids Research* **37**:D211–D215. doi: 10.1093/nar/gkn785.

Jackson AP, Thomas GH, Parkhill J, Thomson NR. 2009. Evolutionary diversification of an ancient gene family (rhs) through C-terminal displacement. *BMC Genomics* **10**:584. doi: 10.1186/1471-2164-10-584.

Jiggins FM, Hurst GDD, Yang Z. 2002. Host-symbiont conflicts: positive selection on an outer membrane protein of parasitic but not mutualistic Rickettsiaceae. *Molecular Biology and Evolution* **19**:1341–1349.

Kadar E, Bettencourt R, Costa V, Santos RS, Lobo-da-Cunha A, Dando P. 2005. Experimentally induced endosymbiont loss and re-acquirement in the hydrothermal vent bivalve *Bathymodiolus azoricus*. *Journal of Experimental Marine Biology and Ecology* **318**:99–110.

Kaebernick M, Neilan BA, Börner T, Dittmann E. 2000. Light and the transcriptional response of the Microcystin biosynthesis gene cluster. *Applied and Environmental Microbiology* **66**:3387–3392. doi: 10.1128/AEM.66.8.3387-3392.2000.

Käll L, Storey JD, MacCoss MJ, Noble WS. 2008. Assigning significance to peptides identified by tandem mass spectrometry using decoy databases. *Journal of Proteome Research* **7**:29–34. doi: 10.1021/pr700600n.

Kanehisa M, Goto S, Sato Y, Furumichi M, Tanabe M. 2011. KEGG for integration and interpretation of large-scale molecular data sets. *Nucleic Acids Research* **40**:D109–D114. doi: 10.1093/nar/gkr988.

Katoh K, Misawa K, Kuma K, Miyata T. 2002. MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform. *Nucleic Acids Research* **30**:3059–3066. doi: 10.1093/nar/gkf436.

Kearse M, Moir R, Wilson A, Stones-Havas S, Cheung M, Sturrock S, Buxton S, Cooper A, Markowitz S, Duran C, Thierer T, Ashton B, Meintjes P, Drummond A. 2012. Geneious basic: an integrated and extendable desktop software platform for the organization and analysis of sequence data. *Bioinformatics* **28**:1647–1649. doi: 10.1093/bioinformatics/bts199.

Kelley LA, Sternberg MJE. 2009. Protein structure prediction on the Web: a case study using the Phyre server. *Nature Protocols* **4**:363–371. doi: 10.1038/nprot.2009.2.

Kleiner M, Petersen JM, Dubilier N. 2012a. Convergent and divergent evolution of metabolism in sulfur-oxidizing symbionts and the role of horizontal gene transfer. *Current Opinion in Microbiology* **15**:621–631. doi: 10.1016/j.mib.2012.09.003.

Kleiner M, Wentrup C, Lott C, Teeling H, Wetzel S, Young J, Chang YJ, Shah M, VerBerkmoes NC, Zarzycki J, Fuchs G, Markert S, Hempel K, Voigt B, Becher D, Liebeke M, Lalk M, Albrecht D, Hecker M, Schweder T, Dubilier N. 2012b. Metaproteomics of a gutless marine worm and its symbiotic microbial community reveal unusual pathways for carbon and energy use. *Proceedings of the National Academy of Sciences of USA* **109**:E1173–E1182. doi: 10.1073/pnas.1121198109.

Kobayashi I. 2001. Behavior of restriction–modification systems as selfish mobile elements and their impact on genome evolution. *Nucleic Acids Research* **29**:3742–3756. doi: 10.1093/nar/29.18.3742.

Koskiniemi S, Lamoureux JG, Nikolakakis KC, t'Kint de Roodenbeke C, Kaplan MD, Low DA, Hayes CS. 2013. RHS proteins from diverse bacteria mediate intercellular competition. *Proceedings of the National Academy of Sciences of USA* **110**:7032–7037. doi: 10.1093/pnas.1300627110.

Krogh A, Larsson B, von Heijne G, Sonnhammer EL. 2001. Predicting transmembrane protein topology with a hidden markov model: application to complete genomes1. *Journal of Molecular Biology* **305**:567–580. doi: 10.1006/jmbi.2000.4315.

Kung VL, Khare S, Stehlik C, Bacon EM, Hughes AJ, Hauser AR. 2012. An rhs gene of *Pseudomonas aeruginosa* encodes a virulence protein that activates the inflammasome. *Proceedings of the National Academy of Sciences of USA* **109**:1275–1280. doi: 10.1073/pnas.1109285109.

Kuwahara H, Yoshida T, Takaki Y, Shimamura S, Nishi S, Harada M, Matsuyama K, Takishita K, Kawato M, Uematsu K, Fujiwara Y, Sato T, Kato C, Kitagawa M, Kato I, Maruyama T. 2007. Reduced genome of the thioautotrophic intracellular symbiont in a deep-sea clam, *Calyptogena okutanii*. *Current Biology* **17**:881–886. doi: 10.1016/j.cub.2007.04.039.

Kwak JS, Jeong H-G, Satchell KJF. 2011. Vibrio vulnificus rtxA1 gene recombination generates toxin variants with altered potency during intestinal infection. *Proceedings of the National Academy of Sciences of USA* **108**:1645–1650. doi: 10.1073/pnas.1014339108.

Lagesen K, Hallin P, Rødland EA, Staerfeldt H-H, Rognes T, Ussery DW. 2007. RNAmmer: consistent and rapid annotation of ribosomal RNA genes. *Nucleic Acids Research* **35**:3100–3108. doi: 10.1093/nar/gkm160.

Langmead B, Salzberg SL. 2012. Fast gapped-read alignment with Bowtie 2. *Nature Methods* **9**:357–359. doi: 10.1038/nmeth.1923.
Lauenstein G, Harmon M, Gottholm B. 1993. *National status and trends program: monitoring site descriptions* (1984–1990) for the national mussel watch and benthic surveillance projects: National Oceanic and Atmospheric Administration. NOAA technical memorandum NOS ORCA-70. 1–358.

Lavik G, Stührmann T, Brüchert V, Van der Plas A, Mohrholz V, Lam P, Mußmann M, Fuchs BM, Amann R, Lass U, Kuypers MM. 2009. Detoxification of sulphidic African shelf waters by blooming chemolithotrophs. *Nature* **457**:581–584. doi: 10.1038/nature07588.

Li W, Godzik A. 2006. Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences. *Bioinformatics* **22**:1658–1659. doi: 10.1093/bioinformatics/btl158.

Lindsay JA, Ruzin A, Ross HF, Kurepina N, Novick RP. 1998. The gene for toxic shock toxin is carried by a family of mobile pathogenicity islands in *Staphylococcus aureus*. *Molecular Microbiology* **29**:527–543. doi: 10.1046/j.1365-2958.1998.00947.x.

Linhartová I, Bumba L, Mašín J, Basler M, Osička R, Kamanová J, Procházková K, Adkins I, Hejnová-Holubová J, Sadílková L, Morová J, Sebo P. 2010. RTX proteins: a highly diverse family secreted by a common mechanism. *FEMS Microbiology Reviews* **34**:1076–1112. doi: 10.1111/j.1574-6976.2010.00231.x.

Liu X, Sheng J, lii RC. 2011. Fatty acid production in genetically modified cyanobacteria. *Proceedings of the National Academy of Sciences of USA* **108**:6899–6904. doi: 10.1073/pnas.1103014108.

Liu Z, Müller J, Li T, Alvey RM, Vogl K, Frigaard NU, Rockwell NC, Boyd ES, Tomsho LP, Schuster SC, Henke P, Rohde M, Overmann J, Bryant DA. 2013. Genomic analysis reveals key aspects of prokaryotic symbiosis in the phototrophic consortium "Chlorochromatium aggregatum". *Genome Biology* **14**:R127. doi: 10.1186/gb-2013-14-11-r127.

Lowe TM, Eddy SR. 1997. tRNAscan-SE: a program for improved detection of transfer RNA genes in genomic sequence. *Nucleic Acids Research* **25**:0955.

Ludwig W, Strunk O, Westram R, Richter L, Meier H, Yadhukumar, Buchner A, Lai T, Steppi S, Jobb G, Förster W, Brettske I, Gerber S, Ginhart AW, Gross O, Grumann S, Hermann S, Jost R, König A, Liss T, Lüssmann R, May M, Nonhoff B, Reichel B, Strehlow R, Stamatakis A, Stuckmann N, Vilbig A, Lenke M, Ludwig T, Bode A, Schleifer KH. 2004. ARB: a software environment for sequence data. *Nucleic Acids Research* **32**:1363–1371. doi: 10.1093/nar/gkh293.

Ma K, Vitek O, Nesvizhskii AI. 2012. A statistical model-building perspective to identification of MS/MS spectra with PeptideProphet. *BMC Bioinformatics* **13**:S1. doi: 10.1186/1471-2105-13-S1-S1.

Markert S, Arndt C, Felbeck H, Becher D, Sievert SM, Hügler M, Albrecht D, Robidart J, Bench S, Feldman RA, Hecker M, Schweder T. 2007. Physiological proteomics of the uncultured endosymbiont of *Riftia pachyptila*. *Science* **315**:247–250. doi: 10.1126/science.1132913.

Markert S, Gardebrecht A, Felbeck H, Sievert SM, Klose J, Becher D, Albrecht D, Thürmer A, Daniel R, Kleiner M, Hecker M, Schweder T. 2011. Status quo in physiological proteomics of the uncultured *Riftia pachyptila* endosymbiont. *Proteomics* **11**:3106–3117. doi: 10.1002/pmic.201100059.

Markowitz VM, Chen IM, Palaniappan K, Chu K, Szeto E, Grechkin Y, Ratner A, Jacob B, Huang J, Williams P, Huntemann M, Anderson I, Mavromatis K, Ivanova NN, Kyrpides NC. 2011. IMG: the integrated microbial genomes database and comparative analysis system. *Nucleic Acids Research* **40**:D115–D122. doi: 10.1093/nar/gkr1044.

McClure R, Balasubramanian D, Sun Y, Bobrovskyy M, Sumby P, Genco CA, Vanderpool CK, Tjaden B. 2013. Computational analysis of bacterial RNA-Seq data. *Nucleic Acids Research* **41**:e140–e140. doi: 10.1093/nar/gkt444.

McFall-Ngai M, Hadfield MG, Bosch TC, Carey HV, Domazet-Lošo T, Douglas AE, Dubilier N, Eberl G, Fukami T, Gilbert SF, Hentschel U, King N, Kjelleberg S, Knoll AH, Kremer N, Mazmanian SK, Metcalf JL, Nealson K, Pierce NE, Rawls JF, Reid A, Ruby EG, Rumpho M, Sanders JG, Tautz D, Wernegreen JJ. 2013. Animals in a bacterial world, a new imperative for the life sciences. *Proceedings of the National Academy of Sciences of USA* **110**:3229–3236. doi: 10.1073/pnas.1218525110.

McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A, Garimella K, Altshuler D, Gabriel S, Daly M, DePristo MA. 2010. The genome analysis toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. *Genome Research* **20**:1297–1303. doi: 10.1101/gr.107524.110.

Meyer F. 2003. GenDB–an open source genome annotation system for prokaryote genomes. *Nucleic Acids Research* **31**:2187–2195. doi: 10.1093/nar/gkg312.

Melvin JA, Scheller EV, Miller JF, Cotter PA. 2014. *Bordetella pertussis* pathogenesis: current and future challenges. *Nature Reviews Microbiology* **12**:274–288. doi: 10.1038/nrmicro3235.

Meusch D, Gatsogiannis C, Efremov RG, Lang AE, Hofnagel O, Vetter IR, Aktories K, Raunser S. 2014. Mechanism of Tc toxin action revealed in molecular detail. *Nature* **508**:61–65. doi: 10.1038/nature13015.

Minguez L, Buronfosse T, Giambérini L. 2012. Different host exploitation strategies in two zebra mussel-trematode systems: Adjustments of host life history traits. *PLOS ONE* **7**:e34029. doi: 10.1371/journal.pone.0034029.

Moebius N, Üzüm Z, Dijksterhuis J, Lackner G, Hertweck C. 2014. Active invasion of bacteria into living fungal cells. *eLife* **3**:e03007. doi: 10.7554/eLife.03007.

Moreira D, López-García P. 2003. Are hydrothermal vents oases for parasitic protists? *Trends in Parasitology* **19**:556–558. doi: 10.1016/j.pt.2003.09.013.

Murillo AA, Ramírez-Flandes S, DeLong EF, Ulloa O. 2014. Enhanced metabolic versatility of planktonic sulfur-oxidizing γ-proteobacteria in an oxygen-deficient coastal ecosystem. *Aquatic Microbiology* **1**:18. doi: 10.3389/fmars.2014.00018.

Muyzer G, Teske A, Wirsen CO, Jannasch HW. 1995. Phylogenetic relationships of *Thiomicrospira* species and their identification in deep-sea hydrothermal vent samples by denaturing gradient gel electrophoresis of 16S rDNA fragments. *Archives of Microbiology* **164**:165–172. doi: 10.1007/BF02529967.

Newton I, Girguis P, Cavanaugh C. 2008. Comparative genomics of vesicomyid clam (Bivalvia: Mollusca) chemosynthetic symbionts. *BMC Genomics* **9**:585. doi: 10.1186/1471-2164-9-585.
Lauenstein G, Harmon M, Gottholm B. 1993. *National status and trends program: monitoring site descriptions* (1984–1990) for the national mussel watch and benthic surveillance projects: National Oceanic and Atmospheric Administration. NOAA technical memorandum NOS ORCA-70. 1–358.

Lavik G, Stührmann T, Brüchert V, Van der Plas A, Mohrholz V, Lam P, Mußmann M, Fuchs BM, Amann R, Lass U, Kuypers MM. 2009. Detoxification of sulphidic African shelf waters by blooming chemolithotrophs. *Nature* **457**:581–584. doi: 10.1038/nature07588.

Li W, Godzik A. 2006. Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences. *Bioinformatics* **22**:1658–1659. doi: 10.1093/bioinformatics/btl158.

Lindsay JA, Ruzin A, Ross HF, Kurepina N, Novick RP. 1998. The gene for toxic shock toxin is carried by a family of mobile pathogenicity islands in *Staphylococcus aureus*. *Molecular Microbiology* **29**:527–543. doi: 10.1046/j.1365-2958.1998.00947.x.

Linhartová I, Bumba L, Mašín J, Basler M, Osička R, Kamanová J, Procházková K, Adkins I, Hejnová-Holubová J, Sadílková L, Morová J, Sebo P. 2010. RTX proteins: a highly diverse family secreted by a common mechanism. *FEMS Microbiology Reviews* **34**:1076–1112. doi: 10.1111/j.1574-6976.2010.00231.x.

Liu X, Sheng J, lii RC. 2011. Fatty acid production in genetically modified cyanobacteria. *Proceedings of the National Academy of Sciences of USA* **108**:6899–6904. doi: 10.1073/pnas.1103014108.

Liu Z, Müller J, Li T, Alvey RM, Vogl K, Frigaard NU, Rockwell NC, Boyd ES, Tomsho LP, Schuster SC, Henke P, Rohde M, Overmann J, Bryant DA. 2013. Genomic analysis reveals key aspects of prokaryotic symbiosis in the phototrophic consortium "Chlorochromatium aggregatum". *Genome Biology* **14**:R127. doi: 10.1186/gb-2013-14-11-r127.

Lowe TM, Eddy SR. 1997. tRNAscan-SE: a program for improved detection of transfer RNA genes in genomic sequence. *Nucleic Acids Research* **25**:0955.

Ludwig W, Strunk O, Westram R, Richter L, Meier H, Yadhukumar, Buchner A, Lai T, Steppi S, Jobb G, Förster W, Brettske I, Gerber S, Ginhart AW, Gross O, Grumann S, Hermann S, Jost R, König A, Liss T, Lüssmann R, May M, Nonhoff B, Reichel B, Strehlow R, Stamatakis A, Stuckmann N, Vilbig A, Lenke M, Ludwig T, Bode A, Schleifer KH. 2004. ARB: a software environment for sequence data. *Nucleic Acids Research* **32**:1363–1371. doi: 10.1093/nar/gkh293.

Ma K, Vitek O, Nesvizhskii AI. 2012. A statistical model-building perspective to identification of MS/MS spectra with PeptideProphet. *BMC Bioinformatics* **13**:S1. doi: 10.1186/1471-2105-13-S1-S1.

Markert S, Arndt C, Felbeck H, Becher D, Sievert SM, Hügler M, Albrecht D, Robidart J, Bench S, Feldman RA, Hecker M, Schweder T. 2007. Physiological proteomics of the uncultured endosymbiont of *Riftia pachyptila*. *Science* **315**:247–250. doi: 10.1126/science.1132913.

Markert S, Gardebrecht A, Felbeck H, Sievert SM, Klose J, Becher D, Albrecht D, Thürmer A, Daniel R, Kleiner M, Hecker M, Schweder T. 2011. Status quo in physiological proteomics of the uncultured *Riftia pachyptila* endosymbiont. *Proteomics* **11**:3106–3117. doi: 10.1002/pmic.201100059.

Markowitz VM, Chen IM, Palaniappan K, Chu K, Szeto E, Grechkin Y, Ratner A, Jacob B, Huang J, Williams P, Huntemann M, Anderson I, Mavromatis K, Ivanova NN, Kyrpides NC. 2011. IMG: the integrated microbial genomes database and comparative analysis system. *Nucleic Acids Research* **40**:D115–D122. doi: 10.1093/nar/gkr1044.

McClure R, Balasubramanian D, Sun Y, Bobrovskyy M, Sumby P, Genco CA, Vanderpool CK, Tjaden B. 2013. Computational analysis of bacterial RNA-Seq data. *Nucleic Acids Research* **41**:e140–e140. doi: 10.1093/nar/gkt444.

McFall-Ngai M, Hadfield MG, Bosch TC, Carey HV, Domazet-Lošo T, Douglas AE, Dubilier N, Eberl G, Fukami T, Gilbert SF, Hentschel U, King N, Kjelleberg S, Knoll AH, Kremer N, Mazmanian SK, Metcalf JL, Nealson K, Pierce NE, Rawls JF, Reid A, Ruby EG, Rumpho M, Sanders JG, Tautz D, Wernegreen JJ. 2013. Animals in a bacterial world, a new imperative for the life sciences. *Proceedings of the National Academy of Sciences of USA* **110**:3229–3236. doi: 10.1073/pnas.1218525110.

McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A, Garimella K, Altshuler D, Gabriel S, Daly M, DePristo MA. 2010. The genome analysis toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. *Genome Research* **20**:1297–1303. doi: 10.1101/gr.107524.110.

Meyer F. 2003. GenDB–an open source genome annotation system for prokaryote genomes. *Nucleic Acids Research* **31**:2187–2195. doi: 10.1093/nar/gkg312.

Melvin JA, Scheller EV, Miller JF, Cotter PA. 2014. *Bordetella pertussis* pathogenesis: current and future challenges. *Nature Reviews Microbiology* **12**:274–288. doi: 10.1038/nrmicro3235.

Meusch D, Gatsogiannis C, Efremov RG, Lang AE, Hofnagel O, Vetter IR, Aktories K, Raunser S. 2014. Mechanism of Tc toxin action revealed in molecular detail. *Nature* **508**:61–65. doi: 10.1038/nature13015.

Minguez L, Buronfosse T, Giambérini L. 2012. Different host exploitation strategies in two zebra mussel-trematode systems: Adjustments of host life history traits. *PLOS ONE* **7**:e34029. doi: 10.1371/journal.pone.0034029.

Moebius N, Üzüm Z, Dijksterhuis J, Lackner G, Hertweck C. 2014. Active invasion of bacteria into living fungal cells. *eLife* **3**:e03007. doi: 10.7554/eLife.03007.

Moreira D, López-García P. 2003. Are hydrothermal vents oases for parasitic protists? *Trends in Parasitology* **19**:556–558. doi: 10.1016/j.pt.2003.09.013.

Murillo AA, Ramírez-Flandes S, DeLong EF, Ulloa O. 2014. Enhanced metabolic versatility of planktonic sulfur-oxidizing γ-proteobacteria in an oxygen-deficient coastal ecosystem. *Aquatic Microbiology* **1**:18. doi: 10.3389/fmars.2014.00018.

Muyzer G, Teske A, Wirsen CO, Jannasch HW. 1995. Phylogenetic relationships of *Thiomicrospira* species and their identification in deep-sea hydrothermal vent samples by denaturing gradient gel electrophoresis of 16S rDNA fragments. *Archives of Microbiology* **164**:165–172. doi: 10.1007/BF02529967.

Newton I, Girguis P, Cavanaugh C. 2008. Comparative genomics of vesicomyid clam (Bivalvia: Mollusca) chemosynthetic symbionts. *BMC Genomics* **9**:585. doi: 10.1186/1471-2164-9-585.
Newton IL, Woyke T, Auchtung TA, Dilly GF, Dutton RJ, Fisher MC, Fontanez KM, Lau E, Stewart FJ, Richardson PM, Barry KW, Saunders E, Detter JC, Wu D, Eisen JA, Cavanaugh CM. 2007. The *Calyptogena magnifica* chemoautotrophic symbiont genome. *Science* **315**:998–1000. doi: 10.1126/science.1138438.

Ochman H, Lawrence JG, Groisman EA. 2000. Lateral gene transfer and the nature of bacterial innovation. *Nature* **405**:299–304. doi: 10.1038/35012500.

Ogier JC, Pagès S, Bisch G, Chiapello H, Médigue C, Rouy Z, Teyssier C, Vincent S, Tailliez P, Givaudan A, Gaudriault S. 2014. Attenuated virulence and genomic reductive evolution in the entomopathogenic bacterial symbiont species, *Xenorhabdus poinarii*. *Genome Biology and Evolution* **6**:1495–1513. doi: 10.1093/gbe/evu119.

Ohno M, Ménez R, Ogawa T, Danse JM, Shimohigashi Y, Fromen C, Ducancel F, Zinn-justin S, Le du MH, Boulain JC, Tamiya T, Ménez A. 1998. Molecular evolution of snake toxins: is the functional diversity of snake toxins associated with a mechanism of accelerated evolution? *Progress in Nucleic Acid Research and Molecular Biology* **59**:307–364.

Oliver KM, Russell JA, Moran NA, Hunter MS. 2003. Facultative bacterial symbionts in aphids confer resistance to parasitic wasps. *Proceedings of the National Academy of Sciences of USA* **100**:1803–1807. doi: 10.1073/pnas. 0335320100.

Oliver KM, Moran NA, Hunter MS. 2005. Variation in resistance to parasitism in aphids is due to symbionts not host genotype. *Proceedings of the National Academy of Sciences of USA* **102**:12795–12800. doi: 10.1073/pnas. 0506131102.

Oliver KM, Degnan PH, Burke GR, Moran NA. 2010. Facultative symbionts in aphids and the horizontal transfer of ecologically important traits. *Annual Review of Entomology* **55**:247–266. doi: 10.1146/annurev-ento-112408-085305.

Paerl H. 2008. Nutrient and other environmental controls of harmful cyanobacterial blooms along the freshwater-marine continuum. In: Hudnell HK, editor. *Cyanobacterial harmful algal blooms: state of the science and research needs*, Springer New York. p. 217–237.

Parks DH, Imelfort M, Skennerton CT, Hugenholtz P, Tyson GW. 2015. CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. *Genome Research* **25**:1043–1055. doi: 10. 1101/gr.186072.114.

Partida-Martinez LP, Groth I, Schmitt I, Richter W, Roth M, Hertweck C. 2007. *Burkholderia rhizoxinica* sp. nov. and *Burkholderia endofungorum* sp. nov., bacterial endosymbionts of the plant-pathogenic fungus *Rhizopus microsporus*. *International Journal of Systematic and Evolutionary Microbiology* **57**:2583–2590. doi: 10.1099/ijss.0.64660-0.

Pernthaler A, Pernthaler J, Amann R. 2002. Fluorescence in situ hybridization and catalyzed reporter deposition for the identification of marine bacteria. *Applied and Environmental Microbiology* **68**:3094–3101. doi: 10.1128/AEM. 68.6.3094-3101.2002.

Petersen J, Dubilier N. 2014. Gene swapping in the dead zone. *eLife* **3**. doi: 10.7554/eLife.04600.

Petersen JM, Dubilier N. 2009. Methanotrophic symbioses in marine invertebrates: methanotrophic symbioses in marine invertebrates. *Environmental Microbiology Reports* **1**:319–335. doi: 10.1111/j.1758-2229.2009.00081.x.

Petersen JM, Zielinski FU, Pape T, Seifert R, Moraru C, Amann R, Hourdez S, Girguis PR, Wankel SD, Barbe V, Pelletier E, Fink D, Borowski C, Bach W, Dubilier N. 2011. Hydrogen is an energy source for hydrothermal vent symbioses. *Nature* **476**:176–180. doi: 10.1038/nature10325.

Petersen JM, Wentrup C, Verna C, Knittel K, Dubilier N. 2012. Origins and evolutionary flexibility of chemosynthetic symbionts from deep-sea animals. *The Biological Bulletin* **223**:123–137.

Ponting CP, Schultz J, Milpetz F, Bork P. 1999. SMART: identification and annotation of domains from signalling and extracellular protein sequences. *Nucleic Acids Research* **27**:229–232. doi: 10.1093/nar/27.1.229.

Poole SJ, Diner EJ, Aoki SK, Braaten BA, t'Kint de Roodenbeke C, Low DA, Hayes CS. 2011. Identification of functional toxin/Immunity genes linked to contact-dependent growth inhibition (CDI) and rearrangement hotspot (Rhs) systems. *PLOS Genetics* **7**:e1002217. doi: 10.1371/journal.pgen.1002217.

Powell EN, Barber RD, Kennicutt MC II, Ford SE. 1999. Influence of parasitism in controlling the health, reproduction and PAH body burden of petroleum seep mussels. *Deep Sea Research Part I Oceanographic Research Papers* **46**:2053–2078. doi: 10.1016/S0967-0637(99)00035-7.

Pruesse E, Peplies J, Glöckner FO. 2012. SINA: accurate high-throughput multiple sequence alignment of ribosomal RNA genes. *Bioinformatics* **28**:1823–1829. doi: 10.1093/bioinformatics/bts252.

Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, Peplies J, Glockner FO. 2013. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. *Nucleic Acids Research* **41**:D590–D596. doi: 10.1093/nar/gks1219.

Quinlan AR, Hall IM. 2010. BEDTools: a flexible suite of utilities for comparing genomic features. *Bioinformatics* **26**:841–842. doi: 10.1093/bioinformatics/btq033.

R Development Core Team. 2011. R: a language and environment for statistical computing.

Rasko DA, Myers GS, Ravel J. 2005. Visualization of comparative genomic analyses by BLAST score ratio. *BMC Bioinformatics* **6**:2. doi: 10.1186/1471-2105-6-2.

Reams AB, Neidle EL. 2004. Selection for gene clustering by tandem duplication. *Annual Review of Microbiology* **58**:119–142. doi: 10.1146/annurev.micro.58.030603.123806.

Richter M, Lombardot T, Kostadinov I, Kottmann R, Duhaime MB, Peplies J, Glöckner FO. 2008. JCoast—a biologist-centric software tool for data mining and comparison of prokaryotic (meta)genomes. *BMC Bioinformatics* **9**:177. doi: 10.1186/1471-2105-9-177.

Riou V, Duperron S, Salary S, Dehairs F, Bouillon S, Martins I, Colaço A, Serrão Santos R. 2010. Variation in physiological indicators in *Bathymodiolus azoricus* (Bivalvia: Mytilidae) at the Menez Gwen Mid-Atlantic Ridge deep-sea hydrothermal vent site within a year. *Marine Environmental Research* **70**:264–271. doi: 10.1016/j. marenvres.2010.05.008.
Newton IL, Woyke T, Auchtung TA, Dilly GF, Dutton RJ, Fisher MC, Fontanez KM, Lau E, Stewart FJ, Richardson PM, Barry KW, Saunders E, Detter JC, Wu D, Eisen JA, Cavanaugh CM. 2007. The *Calyptogena magnifica* chemoautotrophic symbiont genome. *Science* **315**:998–1000. doi: 10.1126/science.1138438.

Ochman H, Lawrence JG, Groisman EA. 2000. Lateral gene transfer and the nature of bacterial innovation. *Nature* **405**:299–304. doi: 10.1038/35012500.

Ogier JC, Pagès S, Bisch G, Chiapello H, Médigue C, Rouy Z, Teyssier C, Vincent S, Tailliez P, Givaudan A, Gaudriault S. 2014. Attenuated virulence and genomic reductive evolution in the entomopathogenic bacterial symbiont species, *Xenorhabdus poinarii*. *Genome Biology and Evolution* **6**:1495–1513. doi: 10.1093/gbe/evu119.

Ohno M, Ménez R, Ogawa T, Danse JM, Shimohigashi Y, Fromen C, Ducancel F, Zinn-justin S, Le du MH, Boulain JC, Tamiya T, Ménez A. 1998. Molecular evolution of snake toxins: is the functional diversity of snake toxins associated with a mechanism of accelerated evolution? *Progress in Nucleic Acid Research and Molecular Biology* **59**:307–364.

Oliver KM, Russell JA, Moran NA, Hunter MS. 2003. Facultative bacterial symbionts in aphids confer resistance to parasitic wasps. *Proceedings of the National Academy of Sciences of USA* **100**:1803–1807. doi: 10.1073/pnas. 0335320100.

Oliver KM, Moran NA, Hunter MS. 2005. Variation in resistance to parasitism in aphids is due to symbionts not host genotype. *Proceedings of the National Academy of Sciences of USA* **102**:12795–12800. doi: 10.1073/pnas. 0506131102.

Oliver KM, Degnan PH, Burke GR, Moran NA. 2010. Facultative symbionts in aphids and the horizontal transfer of ecologically important traits. *Annual Review of Entomology* **55**:247–266. doi: 10.1146/annurev-ento-112408-085305.

Paerl H. 2008. Nutrient and other environmental controls of harmful cyanobacterial blooms along the freshwater-marine continuum. In: Hudnell HK, editor. *Cyanobacterial harmful algal blooms: state of the science and research needs*, Springer New York. p. 217–237.

Parks DH, Imelfort M, Skennerton CT, Hugenholtz P, Tyson GW. 2015. CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. *Genome Research* **25**:1043–1055. doi: 10. 1101/gr.186072.114.

Partida-Martinez LP, Groth I, Schmitt I, Richter W, Roth M, Hertweck C. 2007. *Burkholderia rhizoxinica* sp. nov. and *Burkholderia endofungorum* sp. nov., bacterial endosymbionts of the plant-pathogenic fungus *Rhizopus microsporus*. *International Journal of Systematic and Evolutionary Microbiology* **57**:2583–2590. doi: 10.1099/ijss.0.64660-0.

Pernthaler A, Pernthaler J, Amann R. 2002. Fluorescence in situ hybridization and catalyzed reporter deposition for the identification of marine bacteria. *Applied and Environmental Microbiology* **68**:3094–3101. doi: 10.1128/AEM. 68.6.3094-3101.2002.

Petersen J, Dubilier N. 2014. Gene swapping in the dead zone. *eLife* **3**. doi: 10.7554/eLife.04600.

Petersen JM, Dubilier N. 2009. Methanotrophic symbioses in marine invertebrates: methanotrophic symbioses in marine invertebrates. *Environmental Microbiology Reports* **1**:319–335. doi: 10.1111/j.1758-2229.2009.00081.x.

Petersen JM, Zielinski FU, Pape T, Seifert R, Moraru C, Amann R, Hourdez S, Girguis PR, Wankel SD, Barbe V, Pelletier E, Fink D, Borowski C, Bach W, Dubilier N. 2011. Hydrogen is an energy source for hydrothermal vent symbioses. *Nature* **476**:176–180. doi: 10.1038/nature10325.

Petersen JM, Wentrup C, Verna C, Knittel K, Dubilier N. 2012. Origins and evolutionary flexibility of chemosynthetic symbionts from deep-sea animals. *The Biological Bulletin* **223**:123–137.

Ponting CP, Schultz J, Milpetz F, Bork P. 1999. SMART: identification and annotation of domains from signalling and extracellular protein sequences. *Nucleic Acids Research* **27**:229–232. doi: 10.1093/nar/27.1.229.

Poole SJ, Diner EJ, Aoki SK, Braaten BA, t'Kint de Roodenbeke C, Low DA, Hayes CS. 2011. Identification of functional toxin/Immunity genes linked to contact-dependent growth inhibition (CDI) and rearrangement hotspot (Rhs) systems. *PLOS Genetics* **7**:e1002217. doi: 10.1371/journal.pgen.1002217.

Powell EN, Barber RD, Kennicutt MC II, Ford SE. 1999. Influence of parasitism in controlling the health, reproduction and PAH body burden of petroleum seep mussels. *Deep Sea Research Part I Oceanographic Research Papers* **46**:2053–2078. doi: 10.1016/S0967-0637(99)00035-7.

Pruesse E, Peplies J, Glöckner FO. 2012. SINA: accurate high-throughput multiple sequence alignment of ribosomal RNA genes. *Bioinformatics* **28**:1823–1829. doi: 10.1093/bioinformatics/bts252.

Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, Peplies J, Glockner FO. 2013. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. *Nucleic Acids Research* **41**:D590–D596. doi: 10.1093/nar/gks1219.

Quinlan AR, Hall IM. 2010. BEDTools: a flexible suite of utilities for comparing genomic features. *Bioinformatics* **26**:841–842. doi: 10.1093/bioinformatics/btq033.

R Development Core Team. 2011. R: a language and environment for statistical computing.

Rasko DA, Myers GS, Ravel J. 2005. Visualization of comparative genomic analyses by BLAST score ratio. *BMC Bioinformatics* **6**:2. doi: 10.1186/1471-2105-6-2.

Reams AB, Neidle EL. 2004. Selection for gene clustering by tandem duplication. *Annual Review of Microbiology* **58**:119–142. doi: 10.1146/annurev.micro.58.030603.123806.

Richter M, Lombardot T, Kostadinov I, Kottmann R, Duhaime MB, Peplies J, Glöckner FO. 2008. JCoast—a biologist-centric software tool for data mining and comparison of prokaryotic (meta)genomes. *BMC Bioinformatics* **9**:177. doi: 10.1186/1471-2105-9-177.

Riou V, Duperron S, Salary S, Dehairs F, Bouillon S, Martins I, Colaço A, Serrão Santos R. 2010. Variation in physiological indicators in *Bathymodiolus azoricus* (Bivalvia: Mytilidae) at the Menez Gwen Mid-Atlantic Ridge deep-sea hydrothermal vent site within a year. *Marine Environmental Research* **70**:264–271. doi: 10.1016/j. marenvres.2010.05.008.
Rissman AI, Mau B, Biehl BS, Darling AE, Glasner JD, Perna NT. 2009. Reordering contigs of draft genomes using the Mauve aligner. *Bioinformatics* **25**:2071-2073. doi: 10.1093/bioinformatics/btp356.

Robidart JC, Bench SR, Feldman RA, Novoradovsky A, Podell SB, Gaasterland T, Allen EE, Felbeck H. 2008. Metabolic versatility of the *Riftia pachyptila* endosymbiont revealed through metagenomics. *Environmental Microbiology* **10**:727-737. doi: 10.1111/j.1462-2920.2007.01496.x.

Rocha EPC, Danchin A. 2002. Base composition bias might result from competition for metabolic resources. *Trends in Genetics* **18**:291-294. doi: 10.1016/S0168-9525(02)02690-2.

Roig FJ, Gonzalez-Candelas F, Amaro C. 2010. Domain organization and evolution of multifunctional autoprocessing repeats-in-toxin (MARTX) Toxin in *Vibrio vulnificus*. *Applied and Environmental Microbiology* **77**:657-668. doi: 10.1128/AEM.01806-10.

Ronquist F, Huelsenbeck JP. 2003. MrBayes 3: bayesian phylogenetic inference under mixed models. *Bioinformatics* **19**:1572-1574. doi: 10.1093/bioinformatics/btg180.

Rouchet R, Vorburger C. 2014. Experimental evolution of parasitoid infectivity on symbiont-protected hosts leads to the emergence of genotype specificity. *Evolution* **68**:1607-1616. doi: 10.1111/evo.12377.

Russell JA, Weldon S, Smith AH, Kim KL, Hu Y, Lukasik P, Doll S, Anastopoulos I, Novin M, Oliver KM. 2013. Uncovering symbiont-driven genetic diversity across North American pea aphids. *Molecular Ecology* **22**:2045-2059. doi: 10.1111/mec.12211.

Sakiyama T, Ueno H, Homma H, Numata O, Kuwabara T. 2006. Purification and characterization of a hemolysin-like protein, Sll1951, a nontoxic member of the RTX protein family from the *Cyanobacterium Synechocystis* sp. Strain PCC 6803. *Journal of Bacteriology* **188**:3535-3542. doi: 10.1128/JB.188.10.3535-3542.2006.

Sakiyama T, Araie H, Suzuki I, Shiraiwa Y. 2011. Functions of a hemolysin-like protein in the cyanobacterium *Synechocystis* sp. PCC 6803. *Archives of Microbiology* **193**:565-571. doi: 10.1007/s00203-011-0700-2.

Sarrazin J, Sarradin P-M, Allais A-G, Momareto Cruise Participants X. 2006. MoMARETO: a cruise dedicated to the spatio-temporal dynamics and the adaptations of hydrothermal vent fauna on the Mid-Atlantic Ridge. *InterRidge News* **15**:24-33.

Satchell KJF. 2007. MARTX, multifunctional autoprocessing repeats-in-toxin toxins. *Infection and Immunity* **75**:5079-5084. doi: 10.1128/IAI.00525-07.

Satchell KJF. 2011. Structure and function of MARTX toxins and other large repetitive RTX proteins. *Annual Review of Microbiology* **65**:71-90. doi: 10.1146/annurev-micro-090110-102943.

Schmid M, Sieber R, Zimmermann Y-S, Vorburger C. 2012. Development, specificity and sublethal effects of symbiont-conferred resistance to parasitoids in aphids. *Functional Ecology* **26**:207-215. doi: 10.1111/j.1365-2435.2011.01904.x.

Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B, Ideker T. 2003. Cytoscape: a software environment for integrated models of biomolecular interaction networks. *Genome Research* **13**:2498-2504. doi: 10.1101/gr.1239303.

Snyder AK, Rio RVM. 2013. Interwoven biology of the Tsetse holobiont. *Journal of Bacteriology* **195**:4322-4330. doi: 10.1128/JB.00487-13.

Soucy SM, Huang J, Gogarten JP. 2015. Horizontal gene transfer: building the web of life. *Nature Reviews Genetics* **16**:472-482. doi: 10.1038/nrg3962.

Srinivasan M, Moon YB. 1999. A comprehensive clustering algorithm for strategic analysis of supply chain networks. *Computers & Industrial Engineering* **36**:615-633. doi: 10.1016/S0360-8352(99)00155-2.

Stamatakis A. 2006. RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models. *Bioinformatics* **22**:2688. doi: 10.1093/bioinformatics/btl446.

Steele-Mortimer O, Brumell JH, Knodler LA, Méresse S, Lopez A, Finlay BB. 2002. The invasion-associated type III secretion system of *Salmonella enterica* serovar Typhimurium is necessary for intracellular proliferation and vacuole biogenesis in epithelial cells. *Cellular Microbiology* **4**:43-54. doi: 10.1046/j.1462-5822.2002.00170.x.

Strous M, Kraft B, Bisdorf R, Tegetmeyer HE. 2012. The binning of metagenomic contigs for microbial physiology of mixed cultures. *Frontiers in Microbiology* **3**. doi: 10.3389/fmicb.2012.00410.

Sunamura M, Higashi Y, Miyako C, Ishibashi J, Maruyama A. 2004. Two bacteria phylotypes are predominant in the Suiyo Seamount hydrothermal plume. *Applied and Environmental Microbiology* **70**:1190-1198. doi: 10.1128/AEM.70.2.1190-1198.2004.

Takeuchi T, Kawashima T, Koyanagi R, Gyoja F, Tanaka M, Ikuta T, Shoguchi E, Fujiwara M, Shinzato C, Hisata K, Fujie M, Usami T, Nagai K, Maeyama K, Okamoto K, Aoki H, Ishikawa T, Masaoka T, Fujiwara A, Endo K, Endo H, Nagasawa H, Kinoshita S, Asakawa S, Watabe S, Satoh N. 2012. Draft genome of the pearl oyster pinctada fucata: a platform for understanding bivalve biology. *DNA Research* **19**:117-130. doi: 10.1093/dnares/dss005.

Tatusov RL. 2000. The COG database: a tool for genome-scale analysis of protein functions and evolution. *Nucleic Acids Research* **28**:33-36. doi: 10.1093/nar/28.1.33.

Van Dover C. 2000. The ecology of deep-sea hydrothermal vents. Princeton, NJ: Princeton University Press.

Van Dover CL, German CR, Speer KG, Parson LM, Vrijenhoek RC. 2002. Evolution and biogeography of deep-sea vent and seep invertebrates. *Science* **295**:1253-1257. doi: 10.1126/science.1067361.

Vogl K, Wenter R, Dreßen M, Schlichenrieder M, Plöscher M, Eichacker L, Overmann J. 2008. Identification and analysis of four candidate symbiosis genes from "Chlorochromatium aggregatum", a highly developed bacterial symbiosis. *Environmental Microbiology* **10**:2842-2856. doi: 10.1111/j.1462-2920.2008.01709.x.

von Cosel R. 2002. A new species of bathymodioline mussel (Mollusca, Bivalvia, Mytilidae) from Mauritania (West Africa), with comments on the genus *Bathymodiolus* Kenk & Wilson, 1985. *Zoosystema* **24**:259-272.

Wagner-Döbler I, Biebl H. 2006. Environmental biology of the marine Roseobacter lineage. *Annual Review of Microbiology* **60**:255-280. doi: 10.1146/annurev.micro.60.080805.142115.
Rissman AI, Mau B, Biehl BS, Darling AE, Glasner JD, Perna NT. 2009. Reordering contigs of draft genomes using the Mauve aligner. *Bioinformatics* **25**:2071-2073. doi: 10.1093/bioinformatics/btp356.

Robidart JC, Bench SR, Feldman RA, Novoradovsky A, Podell SB, Gaasterland T, Allen EE, Felbeck H. 2008. Metabolic versatility of the *Riftia pachyptila* endosymbiont revealed through metagenomics. *Environmental Microbiology* **10**:727-737. doi: 10.1111/j.1462-2920.2007.01496.x.

Rocha EPC, Danchin A. 2002. Base composition bias might result from competition for metabolic resources. *Trends in Genetics* **18**:291-294. doi: 10.1016/S0168-9525(02)02690-2.

Roig FJ, Gonzalez-Candelas F, Amaro C. 2010. Domain organization and evolution of multifunctional autoprocessing repeats-in-toxin (MARTX) Toxin in *Vibrio vulnificus*. *Applied and Environmental Microbiology* **77**:657-668. doi: 10.1128/AEM.01806-10.

Ronquist F, Huelsenbeck JP. 2003. MrBayes 3: bayesian phylogenetic inference under mixed models. *Bioinformatics* **19**:1572-1574. doi: 10.1093/bioinformatics/btg180.

Rouchet R, Vorburger C. 2014. Experimental evolution of parasitoid infectivity on symbiont-protected hosts leads to the emergence of genotype specificity. *Evolution* **68**:1607-1616. doi: 10.1111/evo.12377.

Russell JA, Weldon S, Smith AH, Kim KL, Hu Y, Lukasik P, Doll S, Anastopoulos I, Novin M, Oliver KM. 2013. Uncovering symbiont-driven genetic diversity across North American pea aphids. *Molecular Ecology* **22**:2045-2059. doi: 10.1111/mec.12211.

Sakiyama T, Ueno H, Homma H, Numata O, Kuwabara T. 2006. Purification and characterization of a hemolysin-like protein, Sll1951, a nontoxic member of the RTX protein family from the *Cyanobacterium Synechocystis* sp. Strain PCC 6803. *Journal of Bacteriology* **188**:3535-3542. doi: 10.1128/JB.188.10.3535-3542.2006.

Sakiyama T, Araie H, Suzuki I, Shiraiwa Y. 2011. Functions of a hemolysin-like protein in the cyanobacterium *Synechocystis* sp. PCC 6803. *Archives of Microbiology* **193**:565-571. doi: 10.1007/s00203-011-0700-2.

Sarrazin J, Sarradin P-M, Allais A-G, Momareto Cruise Participants X. 2006. MoMARETO: a cruise dedicated to the spatio-temporal dynamics and the adaptations of hydrothermal vent fauna on the Mid-Atlantic Ridge. *InterRidge News* **15**:24-33.

Satchell KJF. 2007. MARTX, multifunctional autoprocessing repeats-in-toxin toxins. *Infection and Immunity* **75**:5079-5084. doi: 10.1128/IAI.00525-07.

Satchell KJF. 2011. Structure and function of MARTX toxins and other large repetitive RTX proteins. *Annual Review of Microbiology* **65**:71-90. doi: 10.1146/annurev-micro-090110-102943.

Schmid M, Sieber R, Zimmermann Y-S, Vorburger C. 2012. Development, specificity and sublethal effects of symbiont-conferred resistance to parasitoids in aphids. *Functional Ecology* **26**:207-215. doi: 10.1111/j.1365-2435.2011.01904.x.

Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B, Ideker T. 2003. Cytoscape: a software environment for integrated models of biomolecular interaction networks. *Genome Research* **13**:2498-2504. doi: 10.1101/gr.1239303.

Snyder AK, Rio RVM. 2013. Interwoven biology of the Tsetse holobiont. *Journal of Bacteriology* **195**:4322-4330. doi: 10.1128/JB.00487-13.

Soucy SM, Huang J, Gogarten JP. 2015. Horizontal gene transfer: building the web of life. *Nature Reviews Genetics* **16**:472-482. doi: 10.1038/nrg3962.

Srinivasan M, Moon YB. 1999. A comprehensive clustering algorithm for strategic analysis of supply chain networks. *Computers & Industrial Engineering* **36**:615-633. doi: 10.1016/S0360-8352(99)00155-2.

Stamatakis A. 2006. RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models. *Bioinformatics* **22**:2688. doi: 10.1093/bioinformatics/btl446.

Steele-Mortimer O, Brumell JH, Knodler LA, Méresse S, Lopez A, Finlay BB. 2002. The invasion-associated type III secretion system of *Salmonella enterica* serovar Typhimurium is necessary for intracellular proliferation and vacuole biogenesis in epithelial cells. *Cellular Microbiology* **4**:43-54. doi: 10.1046/j.1462-5822.2002.00170.x.

Strous M, Kraft B, Bisdorf R, Tegetmeyer HE. 2012. The binning of metagenomic contigs for microbial physiology of mixed cultures. *Frontiers in Microbiology* **3**. doi: 10.3389/fmicb.2012.00410.

Sunamura M, Higashi Y, Miyako C, Ishibashi J, Maruyama A. 2004. Two bacteria phylotypes are predominant in the Suiyo Seamount hydrothermal plume. *Applied and Environmental Microbiology* **70**:1190-1198. doi: 10.1128/AEM.70.2.1190-1198.2004.

Takeuchi T, Kawashima T, Koyanagi R, Gyoja F, Tanaka M, Ikuta T, Shoguchi E, Fujiwara M, Shinzato C, Hisata K, Fujie M, Usami T, Nagai K, Maeyama K, Okamoto K, Aoki H, Ishikawa T, Masaoka T, Fujiwara A, Endo K, Endo H, Nagasawa H, Kinoshita S, Asakawa S, Watabe S, Satoh N. 2012. Draft genome of the pearl oyster pinctada fucata: a platform for understanding bivalve biology. *DNA Research* **19**:117-130. doi: 10.1093/dnares/dss005.

Tatusov RL. 2000. The COG database: a tool for genome-scale analysis of protein functions and evolution. *Nucleic Acids Research* **28**:33-36. doi: 10.1093/nar/28.1.33.

Van Dover C. 2000. The ecology of deep-sea hydrothermal vents. Princeton, NJ: Princeton University Press.

Van Dover CL, German CR, Speer KG, Parson LM, Vrijenhoek RC. 2002. Evolution and biogeography of deep-sea vent and seep invertebrates. *Science* **295**:1253-1257. doi: 10.1126/science.1067361.

Vogl K, Wenter R, Dreßen M, Schlichenrieder M, Plöscher M, Eichacker L, Overmann J. 2008. Identification and analysis of four candidate symbiosis genes from "Chlorochromatium aggregatum", a highly developed bacterial symbiosis. *Environmental Microbiology* **10**:2842-2856. doi: 10.1111/j.1462-2920.2008.01709.x.

von Cosel R. 2002. A new species of bathymodioline mussel (Mollusca, Bivalvia, Mytilidae) from Mauritania (West Africa), with comments on the genus *Bathymodiolus* Kenk & Wilson, 1985. *Zoosystema* **24**:259-272.

Wagner-Döbler I, Biebl H. 2006. Environmental biology of the marine Roseobacter lineage. *Annual Review of Microbiology* **60**:255-280. doi: 10.1146/annurev.micro.60.080805.142115.
Walsh DA, Zaikova E, Howes CG, Song YC, Wright JJ, Tringe SG, Tortell PD, Hallam SJ. 2009. Metagenome of a versatile chemolithoautotroph from expanding oceanic dead zones. *Science* **326**:578–582. doi: 10.1126/science.1175309.

Ward ME, Shields JD, Van Dover CL. 2004. Parasitism in species of *Bathymodiolus* (Bivalvia: Mytilidae) mussels from deep-sea seep and hydrothermal vents. *Diseases of Aquatic Organisms* **62**:1–16. doi: 10.3354/dao062001.

Wardle WJ. 1988. A Bucephalid Larva, *Cercaria pleuromerae* n. sp. (Trematoda: Digenea), parasitizing a deepwater Bivalve from the Gulf of Mexico. *The Journal of Parasitology* **74**:692–694. doi: 10.2307/3282191.

Waterfield NR, Bowen DJ, Fetherston JD, Perry RD, others. 2001. The tc genes of *Photorhabdus*: a growing family. *Trends in Microbiology* **9**:185–191. doi: 10.1016/S0966-842X(01)01978-3.

Wentrup C, Wendeberg A, Schimak M, Borowski C, Dubilier N. 2014. Forever competent: deep-sea bivalves are colonized by their chemosynthetic symbionts throughout their lifetime. *Environmental Microbiology* **16**:3699–3713. doi: 10.1111/1462-2920.12597.

West SA, Kiers ET, Pen I, Denison RF. 2002. Sanctions and mutualism stability: when should less beneficial mutualists be tolerated? *Journal of Evolutionary Biology* **15**:830–837. doi: 10.1046/j.1420-9101.2002.00441.x.

Wittkop T, Emig D, Lange S, Rahmann S, Albrecht M, Morris JH, Böcker S, Stoye J, Baumbach J. 2010. Partitioning biological data with transitivity clustering. *Nature Methods* **7**:419–420. doi: 10.1038/nmeth0610-419.

Won Y, Young C, Lutz R, Vrijenhoek R. 2003a. Dispersal barriers and isolation among deep-sea mussel populations (Mytilidae: *Bathymodiolus*) from eastern Pacific hydrothermal vents. *Molecular Ecology* **12**:169–184. doi: 10.1046/j.1365-294X.2003.01726.x.

Won YJ, Hallam SJ, O'Mullan GD, Pan IL, Buck KR, Vrijenhoek RC. 2003b. Environmental acquisition of thiotrophic endosymbionts by deep-sea mussels of the genus *Bathymodiolus*. *Applied and Environmental Microbiology* **69**:6785. doi: 10.1128/AEM.69.11.6785-6792.2003.

Wood AP, Aurikko JP, Kelly DP. 2004. A challenge for 21st century molecular biology and biochemistry: what are the causes of obligate autotrophy and methanotrophy? *FEMS Microbiology Reviews* **28**:335–352. doi: 10.1016/j.femsre.2003.12.001.

Wright JJ, Konwar KM, Hallam SJ. 2012. Microbial ecology of expanding oxygen minimum zones. *Nature Reviews Microbiology* **10**:381–394. doi: 10.1038/nrmicro2778.

Zhang D, de Souza RF, Anantharaman V, Iyer LM. Aravind L. 2012. Polymorphic toxin systems: comprehensive characterization of trafficking modes, processing, mechanisms of action, immunity and ecology using comparative genomics. *Biology Direct* **7**:18. doi: 10.1186/1745-6150-7-18.

Zhou J, Bruns MA, Tiedje JM. 1996. DNA recovery from soils of diverse composition. *Applied and Environmental Microbiology* **62**:316–322.

Zielinski FU, Pernthaler A, Duperron S, Raggi L, Giere O, Borowski C, Dubilier N. 2009. Widespread occurrence of an intranuclear bacterial parasite in vent and seep bathymodiolin mussels. *Environmental Microbiology* **11**:1150–1167. doi: 10.1111/j.1462-2920.2008.01847.x.

Zuleta LF, Cunha Cde O, de Carvalho FM, Ciapina LP, Souza RC, Mercante FM, de Faria SM, Baldani JI, Straliotto R, Hungria M, de Vasconcelos AT. 2014. The complete genome of *Burkholderia phenoliruptrix* strain BR3459a, a symbiont of *Mimosa flocculosa*: highlighting the coexistence of symbiotic and pathogenic genes. *BMC Genomics* **15**:535. doi: 10.1186/1471-2164-15-535.
Walsh DA, Zaikova E, Howes CG, Song YC, Wright JJ, Tringe SG, Tortell PD, Hallam SJ. 2009. Metagenome of a versatile chemolithoautotroph from expanding oceanic dead zones. *Science* **326**:578–582. doi: 10.1126/science.1175309.

Ward ME, Shields JD, Van Dover CL. 2004. Parasitism in species of *Bathymodiolus* (Bivalvia: Mytilidae) mussels from deep-sea seep and hydrothermal vents. *Diseases of Aquatic Organisms* **62**:1–16. doi: 10.3354/dao062001.

Wardle WJ. 1988. A Bucephalid Larva, *Cercaria pleuromerae* n. sp. (Trematoda: Digenea), parasitizing a deepwater Bivalve from the Gulf of Mexico. *The Journal of Parasitology* **74**:692–694. doi: 10.2307/3282191.

Waterfield NR, Bowen DJ, Fetherston JD, Perry RD, others. 2001. The tc genes of *Photorhabdus*: a growing family. *Trends in Microbiology* **9**:185–191. doi: 10.1016/S0966-842X(01)01978-3.

Wentrup C, Wendeberg A, Schimak M, Borowski C, Dubilier N. 2014. Forever competent: deep-sea bivalves are colonized by their chemosynthetic symbionts throughout their lifetime. *Environmental Microbiology* **16**:3699–3713. doi: 10.1111/1462-2920.12597.

West SA, Kiers ET, Pen I, Denison RF. 2002. Sanctions and mutualism stability: when should less beneficial mutualists be tolerated? *Journal of Evolutionary Biology* **15**:830–837. doi: 10.1046/j.1420-9101.2002.00441.x.

Wittkop T, Emig D, Lange S, Rahmann S, Albrecht M, Morris JH, Böcker S, Stoye J, Baumbach J. 2010. Partitioning biological data with transitivity clustering. *Nature Methods* **7**:419–420. doi: 10.1038/nmeth0610-419.

Won Y, Young C, Lutz R, Vrijenhoek R. 2003a. Dispersal barriers and isolation among deep-sea mussel populations (Mytilidae: *Bathymodiolus*) from eastern Pacific hydrothermal vents. *Molecular Ecology* **12**:169–184. doi: 10.1046/j.1365-294X.2003.01726.x.

Won YJ, Hallam SJ, O'Mullan GD, Pan IL, Buck KR, Vrijenhoek RC. 2003b. Environmental acquisition of thiotrophic endosymbionts by deep-sea mussels of the genus *Bathymodiolus*. *Applied and Environmental Microbiology* **69**:6785. doi: 10.1128/AEM.69.11.6785-6792.2003.

Wood AP, Aurikko JP, Kelly DP. 2004. A challenge for 21st century molecular biology and biochemistry: what are the causes of obligate autotrophy and methanotrophy? *FEMS Microbiology Reviews* **28**:335–352. doi: 10.1016/j.femsre.2003.12.001.

Wright JJ, Konwar KM, Hallam SJ. 2012. Microbial ecology of expanding oxygen minimum zones. *Nature Reviews Microbiology* **10**:381–394. doi: 10.1038/nrmicro2778.

Zhang D, de Souza RF, Anantharaman V, Iyer LM. Aravind L. 2012. Polymorphic toxin systems: comprehensive characterization of trafficking modes, processing, mechanisms of action, immunity and ecology using comparative genomics. *Biology Direct* **7**:18. doi: 10.1186/1745-6150-7-18.

Zhou J, Bruns MA, Tiedje JM. 1996. DNA recovery from soils of diverse composition. *Applied and Environmental Microbiology* **62**:316–322.

Zielinski FU, Pernthaler A, Duperron S, Raggi L, Giere O, Borowski C, Dubilier N. 2009. Widespread occurrence of an intranuclear bacterial parasite in vent and seep bathymodiolin mussels. *Environmental Microbiology* **11**:1150–1167. doi: 10.1111/j.1462-2920.2008.01847.x.

Zuleta LF, Cunha Cde O, de Carvalho FM, Ciapina LP, Souza RC, Mercante FM, de Faria SM, Baldani JI, Straliotto R, Hungria M, de Vasconcelos AT. 2014. The complete genome of *Burkholderia phenoliruptrix* strain BR3459a, a symbiont of *Mimosa flocculosa*: highlighting the coexistence of symbiotic and pathogenic genes. *BMC Genomics* **15**:535. doi: 10.1186/1471-2164-15-535.
# Appendix 1

## The role of the symbionts in the *Bathymodiolus* association

In their complement of toxin-related genes (TRGs), the *Bathymodiolus* symbiont genomes closely resemble those of pathogenic bacteria. In fact, it has a larger arsenal of these particular types of TRGs than any so far sequenced pathogen. Considering this, is it possible that their role in the association with their mussel hosts has been misunderstood? Could they in fact be pathogens of *Bathymodiolus* rather than beneficial symbionts? Chemosynthetic symbionts are widely assumed to benefit their hosts by contributing a source of organic matter for their nutrition and so far this was also thought to be true for the *Bathymodiolus* symbioses (Van Dover, 2000; Cavanaugh et al., 2006; Dubilier et al., 2008). There is a variety of evidence supporting that the *Bathymodiolus* symbionts are in fact an effective source of nutrition, including: (1) *Bathymodiolus* mussels can grow to densities two to five times higher than their shallow-water relatives that rely exclusively on filter-feeding for their nutrition (Gebruk et al., 2000), (2) *Bathymodiolus* mussels have a reduced feeding groove and digestive system compared to their filter-feeding relatives (Gustafson et al., 1998), (3) carbon transfer from sulfur-oxidizing (SOX) symbionts to *B. azoricus* has been demonstrated experimentally (Riou et al., 2010), and (4) based on their genomes, the symbionts are autotrophs (see below). These observations are all consistent with the hypothesis that the SOX symbionts benefit their *Bathymodiolus* hosts by providing them with a source of nutrition.

## Symbiont metabolism

The symbionts encode a modified version of the Calvin cycle that lacks the enzyme sedoheptulose-1,7-biphosphatase and fructose-1,6-bisphosphatase. Instead, the symbionts have a pyrophosphate-dependent phosphofructokinase (PPi-PFK) as described in other chemosynthetic symbioses (Markert et al., 2011; Kleiner et al., 2012b; Dmy trenko et al., 2014). In contrast to the clam symbionts and SUP05 that possess ribulose bisphosphate carboxylase/oxidase (RubisCO) form II, *Bathymodiolus* symbionts have RubisCO form I. RubisCO form I is better adapted to higher O₂ concentrations and has a medium to low affinity to CO₂, indicating an adaptation to environments with O₂ present (Cavanaugh and Robinson, 1996; Badger and Bek, 2008).

The genome did not provide sufficient evidence to determine whether the *Bathymodiolus* symbionts are obligate autotrophs or mixotrophs. None of the three essentially complete symbiont genomes encode the enzyme alpha-ketoglutarate dehydrogenase, which is often absent in the genomes of obligate autotrophs (Wood et al., 2004). Some other genes of the tricarboxylic acid (TCA) cycle were also missing, but this may be because the genomes are not yet closed. A few tripartite ATP-independent periplasmic (TRAP) transporters were present, and these could be involved in uptake of organic compounds.

To acquire the necessary energy to fuel carbon fixation, the *Bathymodiolus* symbionts can utilize reduced sulfur compounds and hydrogen (Petersen et al., 2011; Kleiner et al., 2012a). The pathways for sulfur oxidation present in the genomes are similar to those of other SOX symbionts of *R. pachyptila* tubeworms, or vesicomyid and solemyid clam symbionts (Figure 2—figure supplement 3) (Robidart et al., 2008; Harada et al., 2009; Kleiner et al., 2012a; Dmy trenko et al., 2014). We found the genes that encode SoxBXYZ and sulfide-quinone reductases (Sqr), which reduce cytochrome c and quinones using sulfide and/or thiosulfate as electron donor. The *Bathymodiolus* SOX symbionts might store elemental sulfur based on the absence of SoxCD sulfur dehydrogenase, although the symbionts lack the large intracellular inclusions typical of sulfur storage, and elemental sulfur has not yet been detected in mussel gills. Sulfide can be oxidized to sulfite with the reverse dissimilatory sulfite reduction pathway (rDsr), and sulfite can be further oxidized to sulfate with APS reductase and an ATP-generating ATP sulfurylase (Sat) (Dahl et al., 2008).
# Appendix 1

## The role of the symbionts in the *Bathymodiolus* association

In their complement of toxin-related genes (TRGs), the *Bathymodiolus* symbiont genomes closely resemble those of pathogenic bacteria. In fact, it has a larger arsenal of these particular types of TRGs than any so far sequenced pathogen. Considering this, is it possible that their role in the association with their mussel hosts has been misunderstood? Could they in fact be pathogens of *Bathymodiolus* rather than beneficial symbionts? Chemosynthetic symbionts are widely assumed to benefit their hosts by contributing a source of organic matter for their nutrition and so far this was also thought to be true for the *Bathymodiolus* symbioses (Van Dover, 2000; Cavanaugh et al., 2006; Dubilier et al., 2008). There is a variety of evidence supporting that the *Bathymodiolus* symbionts are in fact an effective source of nutrition, including: (1) *Bathymodiolus* mussels can grow to densities two to five times higher than their shallow-water relatives that rely exclusively on filter-feeding for their nutrition (Gebruk et al., 2000), (2) *Bathymodiolus* mussels have a reduced feeding groove and digestive system compared to their filter-feeding relatives (Gustafson et al., 1998), (3) carbon transfer from sulfur-oxidizing (SOX) symbionts to *B. azoricus* has been demonstrated experimentally (Riou et al., 2010), and (4) based on their genomes, the symbionts are autotrophs (see below). These observations are all consistent with the hypothesis that the SOX symbionts benefit their *Bathymodiolus* hosts by providing them with a source of nutrition.

## Symbiont metabolism

The symbionts encode a modified version of the Calvin cycle that lacks the enzyme sedoheptulose-1,7-biphosphatase and fructose-1,6-bisphosphatase. Instead, the symbionts have a pyrophosphate-dependent phosphofructokinase (PPi-PFK) as described in other chemosynthetic symbioses (Markert et al., 2011; Kleiner et al., 2012b; Dmytrenko et al., 2014). In contrast to the clam symbionts and SUP05 that possess ribulose bisphosphate carboxylase/oxidase (RubisCO) form II, *Bathymodiolus* symbionts have RubisCO form I. RubisCO form I is better adapted to higher $O_2$ concentrations and has a medium to low affinity to $CO_2$, indicating an adaptation to environments with $O_2$ present (Cavanaugh and Robinson, 1996; Badger and Bek, 2008).

The genome did not provide sufficient evidence to determine whether the *Bathymodiolus* symbionts are obligate autotrophs or mixotrophs. None of the three essentially complete symbiont genomes encode the enzyme alpha-ketoglutarate dehydrogenase, which is often absent in the genomes of obligate autotrophs (Wood et al., 2004). Some other genes of the tricarboxylic acid (TCA) cycle were also missing, but this may be because the genomes are not yet closed. A few tripartite ATP-independent periplasmic (TRAP) transporters were present, and these could be involved in uptake of organic compounds.

To acquire the necessary energy to fuel carbon fixation, the *Bathymodiolus* symbionts can utilize reduced sulfur compounds and hydrogen (Petersen et al., 2011; Kleiner et al., 2012a). The pathways for sulfur oxidation present in the genomes are similar to those of other SOX symbionts of *R. pachyptila* tubeworms, or vesicomyid and solemyid clam symbionts (Figure 2—figure supplement 3) (Robidart et al., 2008; Harada et al., 2009; Kleiner et al., 2012a; Dmytrenko et al., 2014). We found the genes that encode SoxABXYZ and sulfide-quinone reductases (Sqr), which reduce cytochrome c and quinones using sulfide and/or thiosulfate as electron donor. The *Bathymodiolus* SOX symbionts might store elemental sulfur based on the absence of SoxCD sulfur dehydrogenase, although the symbionts lack the large intracellular inclusions typical of sulfur storage, and elemental sulfur has not yet been detected in mussel gills. Sulfide can be oxidized to sulfite with the reverse dissimilatory sulfite reduction pathway (rDsr), and sulfite can be further oxidized to sulfate with APS reductase and an ATP-generating ATP sulfurylase (Sat) (Dahl et al., 2008).
Besides the use of oxygen as electron acceptor, we found in the most complete genome of the symbiont from *B. azoricus* the genes for the use of nitrate as electron acceptor (nitrate reductase—*narGHIJ*); however, we did not find these genes in the other two symbiont genomes. The genes required to convert nitrite to nitrous oxide were found in all three-draft genomes (nitrite reductase—*nirk* and nitrite oxidoreductase—*norCB*). We might have not found the nitrate reductase in the draft genomes of BspSym and BazSymB due to the incompleteness (Table 1). The use of an alternative electron acceptor could reduce the competition for oxygen with their host.
Besides the use of oxygen as electron acceptor, we found in the most complete genome of the symbiont from *B. azoricus* the genes for the use of nitrate as electron acceptor (nitrate reductase—*narGHIJ*); however, we did not find these genes in the other two symbiont genomes. The genes required to convert nitrite to nitrous oxide were found in all three-draft genomes (nitrite reductase—*nirk* and nitrite oxidoreductase—*norCB*). We might have not found the nitrate reductase in the draft genomes of BspSym and BazSymB due to the incompleteness (Table 1). The use of an alternative electron acceptor could reduce the competition for oxygen with their host.
# Appendix 2

## Other potential roles of the TRGs

### RTX toxins as nutrient-scavenging proteins

RTX genes were not preferentially found in host-associated bacteria but were also regularly found in free-living bacteria. Bloom-forming aquatic cyanobacteria had some of the highest numbers of RTX genes (Figure 5, Figure 5—figure supplement 3). Cyanobacteria are well-known producers of secondary metabolite toxins called cyanotoxins, but protein toxins of cyanobacteria have received far less attention (Kaebernick et al., 2000). A hemolysin-like protein from *Synechocystis* sp. PCC 6803 was shown to be located in the S-layer of *Synechocystis* cells, and its deletion causes cells to be more permeable and more sensitive to environmental toxins (Liu et al., 2011; Sakiyama et al., 2011). This hemolysin-like protein therefore seems to have a protective rather than a toxic function, although it did have slight hemolytic activity when tested against sheep erythrocytes (Sakiyama et al., 2006). However, the function of most cyanobacterial RTX toxins has not yet been investigated. Intriguingly, cyanobacterial blooms are tightly coupled to nutrient availability (Paerl, 2008). If free-living cyanobacteria can use RTX proteins as toxins to obtain nutrients by lysing other organisms, analogous to pathogens lysing host cells, they could gain access to additional sources of nutrients.

Members of the marine *Roseobacter* clade also had an unusually large number of RTX genes (Figure 5—figure supplement 3). *Roseobacter* are some of the most abundant bacteria in marine habitats. They commonly associate with a range of eukaryotic organisms from single-celled phytoplankton to vertebrate and invertebrate animals (Buchan et al., 2005; Wagner-Döbler and Biebl, 2006; Brinkhoff et al., 2008). Previous studies have shown that the RTX genes of *Roseobacter* are expressed, and that they can make up to 90% of the excreted proteome (Christie-Oleza et al., 2012). However, their function in *Roseobacter* is still unknown.

### Could strain variation of *Bathymodiolus* symbionts be promoted by a defensive role of TRGs?

A role for the *Bathymodiolus* SOX symbiont in host defense against pathogens could help to explain why the mussels seem to associate with multiple closely related SOX strains (Duperron et al., 2006). Associations with multiple very similar symbiont strains are considered evolutionarily unstable because they promote the emergence of 'cheaters', symbionts that benefit from the association but do not contribute to the cost (West et al., 2002; Hart et al., 2013). For example, a 'cheater' could be a SOX symbiont that occupies space within the host, thus gaining access to the electron donors and acceptors it needs for its growth, but passes on less organic matter to the host than neighboring 'cooperators'. Cheaters have a distinct growth advantage, and could easily outcompete cooperators, ultimately leading to the breakdown of the association. Despite this, multiple strains of SOX bacteria can occur in individual *Bathymodiolus* mussels (Won et al., 2003a; DeChaine et al., 2006). Intriguingly, the SOX symbiont strain variation identified in genetic markers such as the 16S-ITS-23S rRNA gene operon is similar to the strain variation seen in natural populations of defensive Ca. H. defensa symbionts (Russell et al., 2013). Moreover, we have shown that closely related SOX symbionts show extensive sequence variation in most TRGs, which is also the case for Ca. H. defensa (Russell et al., 2013). This large natural diversity is inconsistent with a role for the TRGs in host-symbiont recognition and communication, as genes mediating these processes should be conserved (Jiggins et al., 2002; Bailly et al., 2006). However, this diversity could be explained by antagonistic co-evolution between protective symbionts and their host's parasites. Indeed, experimental evolution shows that natural enemies quickly acquire resistance to Ca. H. defensa (Rouchet and Vorburger, 2014). However, this resistance is highly specific to the strain of Ca. H. defensa, the parasite is
# Appendix 2

## Other potential roles of the TRGs

### RTX toxins as nutrient-scavenging proteins

RTX genes were not preferentially found in host-associated bacteria but were also regularly found in free-living bacteria. Bloom-forming aquatic cyanobacteria had some of the highest numbers of RTX genes (Figure 5, Figure 5—figure supplement 3). Cyanobacteria are well-known producers of secondary metabolite toxins called cyanotoxins, but protein toxins of cyanobacteria have received far less attention (Kaebernick et al., 2000). A hemolysin-like protein from *Synechocystis* sp. PCC 6803 was shown to be located in the S-layer of *Synechocystis* cells, and its deletion causes cells to be more permeable and more sensitive to environmental toxins (Liu et al., 2011; Sakiyama et al., 2011). This hemolysin-like protein therefore seems to have a protective rather than a toxic function, although it did have slight hemolytic activity when tested against sheep erythrocytes (Sakiyama et al., 2006). However, the function of most cyanobacterial RTX toxins has not yet been investigated. Intriguingly, cyanobacterial blooms are tightly coupled to nutrient availability (Paerl, 2008). If free-living cyanobacteria can use RTX proteins as toxins to obtain nutrients by lysing other organisms, analogous to pathogens lysing host cells, they could gain access to additional sources of nutrients.

Members of the marine *Roseobacter* clade also had an unusually large number of RTX genes (Figure 5—figure supplement 3). *Roseobacter* are some of the most abundant bacteria in marine habitats. They commonly associate with a range of eukaryotic organisms from single-celled phytoplankton to vertebrate and invertebrate animals (Buchan et al., 2005; Wagner-Döbler and Biebl, 2006; Brinkhoff et al., 2008). Previous studies have shown that the RTX genes of *Roseobacter* are expressed, and that they can make up to 90% of the excreted proteome (Christie-Oleza et al., 2012). However, their function in *Roseobacter* is still unknown.

### Could strain variation of *Bathymodiolus* symbionts be promoted by a defensive role of TRGs?

A role for the *Bathymodiolus* SOX symbiont in host defense against pathogens could help to explain why the mussels seem to associate with multiple closely related SOX strains (Duperron et al., 2006). Associations with multiple very similar symbiont strains are considered evolutionarily unstable because they promote the emergence of 'cheaters', symbionts that benefit from the association but do not contribute to the cost (West et al., 2002; Hart et al., 2013). For example, a 'cheater' could be a SOX symbiont that occupies space within the host, thus gaining access to the electron donors and acceptors it needs for its growth, but passes on less organic matter to the host than neighboring 'cooperators'. Cheaters have a distinct growth advantage, and could easily outcompete cooperators, ultimately leading to the breakdown of the association. Despite this, multiple strains of SOX bacteria can occur in individual *Bathymodiolus* mussels (Won et al., 2003a; DeChaine et al., 2006). Intriguingly, the SOX symbiont strain variation identified in genetic markers such as the 16S-ITS-23S rRNA gene operon is similar to the strain variation seen in natural populations of defensive Ca. H. defensa symbionts (Russell et al., 2013). Moreover, we have shown that closely related SOX symbionts show extensive sequence variation in most TRGs, which is also the case for Ca. H. defensa (Russell et al., 2013). This large natural diversity is inconsistent with a role for the TRGs in host-symbiont recognition and communication, as genes mediating these processes should be conserved (Jiggins et al., 2002; Bailly et al., 2006). However, this diversity could be explained by antagonistic co-evolution between protective symbionts and their host's parasites. Indeed, experimental evolution shows that natural enemies quickly acquire resistance to Ca. H. defensa (Rouchet and Vorburger, 2014). However, this resistance is highly specific to the strain of Ca. H. defensa, the parasite is
experimentally challenged with and is useless against other closely related strains (Schmid *et al.*, 2012; Rouchet and Vorburger, 2014). Associating with diverse symbiont strains, each with its own unique arsenal of TRGs, could therefore protect the host in the face of rapidly evolving parasite resistance.
experimentally challenged with and is useless against other closely related strains (Schmid *et al.*, 2012; Rouchet and Vorburger, 2014). Associating with diverse symbiont strains, each with its own unique arsenal of TRGs, could therefore protect the host in the face of rapidly evolving parasite resistance.
Appendix 3

**Structure of *Bathymodiolus* symbiont TRGs and genomic regions**

In BsPSym, the 19 multifunctional autoprocessing RTX (MARTX)-like genes were clustered in two genomic regions that spanned 58.5 kb (MARTX1) and 46.3 kb (MARTX2). Genes predicted in these regions encoded many of the unique features of MARTX genes and other large repetitive RTX proteins including RTX repeats, cysteine protease domains (CPDs), hemagglutinin, and adhesion domains (Figure 4—figure supplement 2). Moreover, some of these genes were very large, which is typical of MARTX and MARTX-like genes (Satchell, 2007, 2011). BazSymA and BazSymB also encoded genes with characteristic signatures of MARTX genes, but these two draft genomes were highly fragmented, and the MARTX genes were found on very small genome fragments.

Both of the BsPSym MARTX regions contained genes encoding RTX repeats and RTX CPDs. The RTX CPD has so far only been found in MARTX genes. Its function is to cleave off effector domains, whose sequence and effects on eukaryotic hosts can vary substantially even in MARTX genes from different strains of the same bacterial species (Roig et al., 2010; Kwak et al., 2011). Beyond these shared features, MARTX1 and MARTX2 of the BsPSym had distinct differences. Genes in MARTX1 encoded six hemagglutinin domains, two adhesion domains, and a pectin lyase domain. Similar features are found in large repetitive RTX adhesins, except that the CPD domain is not usually found in this protein subfamily (Satchell, 2011). In fact, the combination of hemagglutinin, pectin lyase, and CPD domains has so far only been found in the filamentous hemagglutinin protein of the betaproteobacterial pathogens *B. pertussis* and *B. bronchiseptica*, which is a key determinant of epithelial cell attachment and immune response modulation in *Bordetella* infections (Melvin et al., 2014). In contrast to *Bordetella*, where these domains are all encoded in one very large ORF, these domains were encoded in neighboring ORFs in the *Bathymodiolus* symbiont. However, MARTX-encoding genes are notoriously difficult to predict due to their repetitive structure (Satchell, 2007, 2011). We therefore cannot exclude the possibility that these may in fact encode one large protein in the *Bathymodiolus* symbiont.

The second MARTX-like gene cluster in the BsPSym genome, MARTX2, resembles a 'typical' hemolysin operon. It contains all the necessary genes for type I secretion, and a gene annotated as *rtxA*, which encodes a hemolysin toxin. However, in contrast to typical hemolysin operons, it is missing the hemolysin activator gene. Interestingly, MARTX1, but not MARTX2, contains a gene annotated as a hemolysin activator. Moreover, the MARTX2 region contains four genes that each has up to five CPD domains. The CPD domain is typical for MARTX genes but not for known hemolysins. This region therefore has features characteristic of both RTX and MARTX genes.
Appendix 3

**Structure of *Bathymodiolus* symbiont TRGs and genomic regions**

In BsPSym, the 19 multifunctional autoprocessing RTX (MARTX)-like genes were clustered in two genomic regions that spanned 58.5 kb (MARTX1) and 46.3 kb (MARTX2). Genes predicted in these regions encoded many of the unique features of MARTX genes and other large repetitive RTX proteins including RTX repeats, cysteine protease domains (CPDs), hemagglutinin, and adhesion domains (Figure 4—figure supplement 2). Moreover, some of these genes were very large, which is typical of MARTX and MARTX-like genes (Satchell, 2007, 2011). BazSymA and BazSymB also encoded genes with characteristic signatures of MARTX genes, but these two draft genomes were highly fragmented, and the MARTX genes were found on very small genome fragments.

Both of the BsPSym MARTX regions contained genes encoding RTX repeats and RTX CPDs. The RTX CPD has so far only been found in MARTX genes. Its function is to cleave off effector domains, whose sequence and effects on eukaryotic hosts can vary substantially even in MARTX genes from different strains of the same bacterial species (Roig et al., 2010; Kwak et al., 2011). Beyond these shared features, MARTX1 and MARTX2 of the BsPSym had distinct differences. Genes in MARTX1 encoded six hemagglutinin domains, two adhesion domains, and a pectin lyase domain. Similar features are found in large repetitive RTX adhesins, except that the CPD domain is not usually found in this protein subfamily (Satchell, 2011). In fact, the combination of hemagglutinin, pectin lyase, and CPD domains has so far only been found in the filamentous hemagglutinin protein of the betaproteobacterial pathogens *B. pertussis* and *B. bronchiseptica*, which is a key determinant of epithelial cell attachment and immune response modulation in *Bordetella* infections (Melvin et al., 2014). In contrast to *Bordetella*, where these domains are all encoded in one very large ORF, these domains were encoded in neighboring ORFs in the *Bathymodiolus* symbiont. However, MARTX-encoding genes are notoriously difficult to predict due to their repetitive structure (Satchell, 2007, 2011). We therefore cannot exclude the possibility that these may in fact encode one large protein in the *Bathymodiolus* symbiont.

The second MARTX-like gene cluster in the BsPSym genome, MARTX2, resembles a 'typical' hemolysin operon. It contains all the necessary genes for type I secretion, and a gene annotated as *rtxA*, which encodes a hemolysin toxin. However, in contrast to typical hemolysin operons, it is missing the hemolysin activator gene. Interestingly, MARTX1, but not MARTX2, contains a gene annotated as a hemolysin activator. Moreover, the MARTX2 region contains four genes that each has up to five CPD domains. The CPD domain is typical for MARTX genes but not for known hemolysins. This region therefore has features characteristic of both RTX and MARTX genes.
# Appendix 4

## Supplementary materials and methods

### Symbiont and host separation via density gradient centrifugation for genomics and proteomics from gill tissue

To separate the SOX symbionts from gill tissues and to obtain a fraction enriched in host cytosolic proteins from the gill, a combination of differential and rate-zonal centrifugation was applied. All steps were carried out at 4°C. Around 1 g of gill tissue was removed from a mussel and transferred into a Duall homogenizer (Tissue grind pestle and tube SZ22, Kontes Glass Company, Vineland, New Jersey). The tissue was covered with 1x PBS and homogenized thoroughly with about 20 strokes. To remove host nuclei and large tissue fragments, the homogenate was filled into a 15 ml conical tube, 1x PBS added up to 15 ml, and centrifuged for 10 min at 700xg in a swing out rotor. The supernatant was carefully transferred into a new 15 ml tube and the pellet (first pellet) frozen at -80°C. The supernatant was centrifuged again for 10 min at 700xg in a swing out rotor to remove any remaining nuclei and tissue fragments. The resulting supernatant was transferred to a new tube and centrifuged in a fixed angle rotor for 10 min at 15.000xg to pellet all symbionts, mitochondria, and small tissue fragments. The supernatant from this centrifugation step, which contained the cytosolic host proteins, was frozen at -80°C. The pellet was resuspended in 1x PBS and the suspension was layered on top of a discontinuous density gradient made with HistoDenz (Sigma) dissolved in 1x PBS. The density gradient was set up in 5% steps from 5 to 25% (wt/vol) HistoDenz. The density gradient was centrifuged in a swing out rotor for 7 min at 3000xg and was then divided into equally sized fractions. The pellet in the gradient tube (gradient pellet) was frozen at -80°C until processing. The gradient fractions were washed twice with 1x PBS to remove the HistoDenz and the resulting pellets were frozen at -80°C. Subsamples for catalyzed reporter deposition-fluorescence in situ hybridization (CARD-FISH) analyses were taken from the homogenates, pellets, and gradient fractions prior to freezing for later analysis of sample composition.

### Analysis of symbiont composition in density gradient fractions using CARD-FISH

To determine the abundance and composition of host material and the different symbiont species in the homogenates, supernatants, pellets, and gradient fractions, we used CARD-FISH. Subsamples of gradient pellets were fixed overnight in 1% formaldehyde at 4°C, washed three times in 1x PBS, and stored at -20°C in 50% 1x PBS and 50% ethanol. In the home laboratory, cells were poured through 0.22-µm filters. CARD-FISH was done as described previously (Perthaler et al., 2002) with minor modifications. Endogenous peroxidases were inactivated with 0.01 M HCl for 10 min at room temperature. Double hybridization of rRNA was performed with the probes BMARt-193 for the SOX symbiont and BMARm-845 for the methane-oxidizing (MOX) symbionts (Duperron et al., 2006). Sections were hybridized at 46°C for 2 hr, followed by washing at 48°C for 20 min. Amplification was done for 10 min at 37°C, followed by inactivation of horseradish peroxidase (HRP) using methanol. Prior to microscopic evaluation, the cells were counterstained with 1 µg ml⁻¹ 4',6-diamidino-2-phenylindole (DAPI). Cells with a symbiont-specific signal were counted against at least 500 DAPI signals per filter section.

### Proteomic analysis

#### Extraction of cytosolic and membrane proteins

For the proteomic analyses, gradient pellets, host supernatant (described above), and frozen tissues from mussel gill and foot were processed in biological duplicates. For washing, the samples were resuspended in TE buffer (10 mM Tris pH 7.5, 10 mM EDTA pH 8.0, 1x complete Protease Inhibitor Cocktail [Roche Applied Science, Germany]) and centrifuged briefly (3 min, 4°C and 21,500xg). The resultant pellets were homogenized using a Duall homogenizer and the
# Appendix 4

## Supplementary materials and methods

### Symbiont and host separation via density gradient centrifugation for genomics and proteomics from gill tissue

To separate the SOX symbionts from gill tissues and to obtain a fraction enriched in host cytosolic proteins from the gill, a combination of differential and rate-zonal centrifugation was applied. All steps were carried out at 4°C. Around 1 g of gill tissue was removed from a mussel and transferred into a Duall homogenizer (Tissue grind pestle and tube SZ22, Kontes Glass Company, Vineland, New Jersey). The tissue was covered with 1x PBS and homogenized thoroughly with about 20 strokes. To remove host nuclei and large tissue fragments, the homogenate was filled into a 15 ml conical tube, 1x PBS added up to 15 ml, and centrifuged for 10 min at 700xg in a swing out rotor. The supernatant was carefully transferred into a new 15 ml tube and the pellet (first pellet) frozen at -80°C. The supernatant was centrifuged again for 10 min at 700xg in a swing out rotor to remove any remaining nuclei and tissue fragments. The resulting supernatant was transferred to a new tube and centrifuged in a fixed angle rotor for 10 min at 15.000xg to pellet all symbionts, mitochondria, and small tissue fragments. The supernatant from this centrifugation step, which contained the cytosolic host proteins, was frozen at -80°C. The pellet was resuspended in 1x PBS and the suspension was layered on top of a discontinuous density gradient made with HistoDenz (Sigma) dissolved in 1x PBS. The density gradient was set up in 5% steps from 5 to 25% (wt/vol) HistoDenz. The density gradient was centrifuged in a swing out rotor for 7 min at 3000xg and was then divided into equally sized fractions. The pellet in the gradient tube (gradient pellet) was frozen at -80°C until processing. The gradient fractions were washed twice with 1x PBS to remove the HistoDenz and the resulting pellets were frozen at -80°C. Subsamples for catalyzed reporter deposition-fluorescence in situ hybridization (CARD-FISH) analyses were taken from the homogenates, pellets, and gradient fractions prior to freezing for later analysis of sample composition.

### Analysis of symbiont composition in density gradient fractions using CARD-FISH

To determine the abundance and composition of host material and the different symbiont species in the homogenates, supernatants, pellets, and gradient fractions, we used CARD-FISH. Subsamples of gradient pellets were fixed overnight in 1% formaldehyde at 4°C, washed three times in 1x PBS, and stored at -20°C in 50% 1x PBS and 50% ethanol. In the home laboratory, cells were poured through 0.22-µm filters. CARD-FISH was done as described previously (Perthaler et al., 2002) with minor modifications. Endogenous peroxidases were inactivated with 0.01 M HCl for 10 min at room temperature. Double hybridization of rRNA was performed with the probes BMARt-193 for the SOX symbiont and BMARm-845 for the methane-oxidizing (MOX) symbionts (Duperron et al., 2006). Sections were hybridized at 46°C for 2 hr, followed by washing at 48°C for 20 min. Amplification was done for 10 min at 37°C, followed by inactivation of horseradish peroxidase (HRP) using methanol. Prior to microscopic evaluation, the cells were counterstained with 1 µg ml⁻¹ 4',6-diamidino-2-phenylindole (DAPI). Cells with a symbiont-specific signal were counted against at least 500 DAPI signals per filter section.

### Proteomic analysis

#### Extraction of cytosolic and membrane proteins

For the proteomic analyses, gradient pellets, host supernatant (described above), and frozen tissues from mussel gill and foot were processed in biological duplicates. For washing, the samples were resuspended in TE buffer (10 mM Tris pH 7.5, 10 mM EDTA pH 8.0, 1x complete Protease Inhibitor Cocktail [Roche Applied Science, Germany]) and centrifuged briefly (3 min, 4°C and 21,500xg). The resultant pellets were homogenized using a Duall homogenizer and the
homogenate was transferred to low binding 1.7 ml reaction tubes (Sorenson BioScience Inc., Salt Lake City, UT). Cells were lysed on ice using a sonicator (Bandelin Sonopuls ultrasonic homogenizer, Germany); 2 × 25 s at 30% power and a cycle of 0.5 s, with a 30 s pause. The lysate was centrifuged to remove cell debris (10 min, 4°C and 15,300×g). The resulting supernatants, that is, protein raw extracts, were further subjected to ultracentrifugation (100,000×g for 60 min at 4°C), allowing for the enrichment of membranes and membrane-associated proteins in the pellets and accumulation of soluble proteins in the supernatants. Protein concentrations in the soluble protein extracts were determined using the method described by **Bradford, 1976** and aliquots for all four sample types (symbiont-enriched gradient pellet, host supernatant, gill tissue, and foot tissue) were stored at -80°C until MS analysis. Additionally, for gill tissue and gradient pellet samples, membrane proteins were purified from the enriched membrane fraction (see above) according to the protocol of **Eymann et al. (2004)** as described by **Markert et al. (2007)**. The purified membrane protein fraction (in 30 µl of 50 mM triethylammonium bicarbonate buffer, pH 7.8) was transferred to low binding 1.7 ml tubes and immediately used for MS analysis. Due to sample scarcity, the biological duplicates for these membrane protein samples were pooled together to obtain enough protein for MS analysis.

## 1D-PAGE-LC-MS/MS

Approximately, 20 µg of protein of the membrane and soluble protein extracts, respectively, was dissolved in 20 µl of sample loading buffer (100 mM Tris-HCl (pH 6.8), 10% sodium dodecyl sulfate (SDS), 20% glycerol, 5% β-mercaptoethanol, 0.1% bromophenol blue). Proteins were separated by one-dimensional (1D) SDS PAGE in pre-cast 10% polyacrylamide gels (BioRad), fixed and stained with Coomassie Brilliant Blue (G250, Sigma-Aldrich, Germany). The gel lanes were cut into 10 equal sized pieces, destained with washing buffer (200 mM ammonium hydrogen carbonate, 30% acetonitrile), dried and proteins were subjected to overnight in-gel digestion with trypsin (Promega, Germany) (**Heinz et al., 2012**). Prior to mass spectrometric analysis, the peptides were purified using Ziptips (P10, U-C₁₈, Millipore).

Tryptic digests of the cytosolic samples were subjected to liquid chromatography performed on an EASYnLC (Proxeon, Denmark) with self-packed columns (Luna 3µ C18(2) 100A, Phenomenex, Germany) in a one-column setup. Following loading and desalting at a flow of 700 nl/min at a maximum of 220 bar of water in 0.1% acetic acid, separation of the peptides was achieved by the application of a binary non-linear 70 min gradient from 5 to 50% acetonitrile in 0.1% acetic acid at a flow rate of 300 nl/min. The LC was coupled online to an LTQ Velos Orbitrap mass spectrometer (Thermo Fisher, Germany) at a spray voltage of 2.4 kV. After a survey scan in the Orbitrap (R = 30,000), MS/MS data were recorded for the twenty most intensive precursor ions in the linear ion trap. Singly charged ions were not taken into account for MS/MS analysis. The lock mass option was enabled throughout all analyses.

Tryptic digests of the membrane samples were analyzed the same way as the cytosolic samples with the modification that the LC was coupled online to an LTQ Orbitrap Classic mass spectrometer (Thermo Fisher, Germany) and that only the five most intensive precursor ions were chosen for MS/MS analysis in the linear ion trap.

After mass spectrometric measurement, MS data were converted into the mzXML format by msconvert (**Chambers et al., 2012**) and subsequently subjected to database searching via Sorcerer (SageN, Milptas, CA) using SEQUEST (Thermo Fisher Scientific, San Jose, CA; version 27, revision 11) without charge state deconvolution and deisotoping performed (details below).

## Protein identification, validation, and quantitation

Two protein sequence databases were constructed to identify proteins. The first database—Reduced Database (RedDB)—contained a total of 52,546 protein sequences from *B. azoricus* and its symbionts. Of these, 7714 sequences were from the SOX symbiont, 5955 sequences from the MOX symbiont, and 38,877 from the host.

The second database—Incremented Database (IncDB)—contained a total of 242,947 protein sequences from *B. azoricus*, its symbionts, and from organisms phylogenetically related to the
homogenate was transferred to low binding 1.7 ml reaction tubes (Sorenson BioScience Inc., Salt Lake City, UT). Cells were lysed on ice using a sonicator (Bandelin Sonopuls ultrasonic homogenizer, Germany); 2 × 25 s at 30% power and a cycle of 0.5 s, with a 30 s pause. The lysate was centrifuged to remove cell debris (10 min, 4°C and 15,300×g). The resulting supernatants, that is, protein raw extracts, were further subjected to ultracentrifugation (100,000×g for 60 min at 4°C), allowing for the enrichment of membranes and membrane-associated proteins in the pellets and accumulation of soluble proteins in the supernatants. Protein concentrations in the soluble protein extracts were determined using the method described by **Bradford, 1976** and aliquots for all four sample types (symbiont-enriched gradient pellet, host supernatant, gill tissue, and foot tissue) were stored at -80°C until MS analysis. Additionally, for gill tissue and gradient pellet samples, membrane proteins were purified from the enriched membrane fraction (see above) according to the protocol of **Eymann et al. (2004)** as described by **Markert et al. (2007)**. The purified membrane protein fraction (in 30 µl of 50 mM triethylammonium bicarbonate buffer, pH 7.8) was transferred to low binding 1.7 ml tubes and immediately used for MS analysis. Due to sample scarcity, the biological duplicates for these membrane protein samples were pooled together to obtain enough protein for MS analysis.

## 1D-PAGE-LC-MS/MS

Approximately, 20 µg of protein of the membrane and soluble protein extracts, respectively, was dissolved in 20 µl of sample loading buffer (100 mM Tris-HCl (pH 6.8), 10% sodium dodecyl sulfate (SDS), 20% glycerol, 5% β-mercaptoethanol, 0.1% bromophenol blue). Proteins were separated by one-dimensional (1D) SDS PAGE in pre-cast 10% polyacrylamide gels (BioRad), fixed and stained with Coomassie Brilliant Blue (G250, Sigma-Aldrich, Germany). The gel lanes were cut into 10 equal sized pieces, destained with washing buffer (200 mM ammonium hydrogen carbonate, 30% acetonitrile), dried and proteins were subjected to overnight in-gel digestion with trypsin (Promega, Germany) (**Heinz et al., 2012**). Prior to mass spectrometric analysis, the peptides were purified using Ziptips (P10, U-C₁₈, Millipore).

Tryptic digests of the cytosolic samples were subjected to liquid chromatography performed on an EASYnLC (Proxeon, Denmark) with self-packed columns (Luna 3µ C18(2) 100A, Phenomenex, Germany) in a one-column setup. Following loading and desalting at a flow of 700 nl/min at a maximum of 220 bar of water in 0.1% acetic acid, separation of the peptides was achieved by the application of a binary non-linear 70 min gradient from 5 to 50% acetonitrile in 0.1% acetic acid at a flow rate of 300 nl/min. The LC was coupled online to an LTQ Velos Orbitrap mass spectrometer (Thermo Fisher, Germany) at a spray voltage of 2.4 kV. After a survey scan in the Orbitrap (R = 30,000), MS/MS data were recorded for the twenty most intensive precursor ions in the linear ion trap. Singly charged ions were not taken into account for MS/MS analysis. The lock mass option was enabled throughout all analyses.

Tryptic digests of the membrane samples were analyzed the same way as the cytosolic samples with the modification that the LC was coupled online to an LTQ Orbitrap Classic mass spectrometer (Thermo Fisher, Germany) and that only the five most intensive precursor ions were chosen for MS/MS analysis in the linear ion trap.

After mass spectrometric measurement, MS data were converted into the mzXML format by msconvert (**Chambers et al., 2012**) and subsequently subjected to database searching via Sorcerer (SageN, Milptas, CA) using SEQUEST (Thermo Fisher Scientific, San Jose, CA; version 27, revision 11) without charge state deconvolution and deisotoping performed (details below).

## Protein identification, validation, and quantitation

Two protein sequence databases were constructed to identify proteins. The first database—Reduced Database (RedDB)—contained a total of 52,546 protein sequences from *B. azoricus* and its symbionts. Of these, 7714 sequences were from the SOX symbiont, 5955 sequences from the MOX symbiont, and 38,877 from the host.

The second database—Incremented Database (IncDB)—contained a total of 242,947 protein sequences from *B. azoricus*, its symbionts, and from organisms phylogenetically related to the
symbionts and the host. 93,304 protein sequences were from relatives of the SOX symbiont, 26,622 from relatives of the MOX symbiont, and 123,021 from host-related bivalves. Redundant sequences were removed using the CD-hit-2D clustering algorithm (Li and Godzik, 2006) at 100% sequence clustering threshold. To determine false discovery rates (FDRs) of protein identification, both protein sequence databases were reversed and appended to the original databases as decoy sequences.

All MS/MS spectra from 1D-PAGE-LC-MS/MS experiments were searched against the two protein sequence databases using the SEQUEST (v.27, rev. 11) algorithm (Eng et al., 1994) with the following parameters: Parent Mass Tolerance, 0.0065 Da; Fragment Ion Tolerance, 1 Da; up to 2 missed cleavages allowed (internal lysine and arginine residues), fully tryptic peptides only, and oxidation of methionine as variable modification (+15.99 Da).

Scaffold (version 4.0.6.1, Proteome Software Inc., Portland, OR) was used for filtering and analysis of protein identifications. For the searches against the IncDB, protein identifications were filtered with the PeptideProphet and ProteinProphet algorithms implemented in Scaffold (Ma et al., 2012) using the following thresholds: 95% for peptides and 99% for proteins. For the searches against the RedDB, protein identifications were filtered at the peptide level using SEQUEST scores (XCorrs of at least 2.5 (charge +2) and 3.5 (charges >+2), DeltaCN >0.08) and by requiring that they contained at least two identified peptides.

Protein level FDRs for all database searches were determined according to the method of Käll et al. (2008) using the number of identified decoy sequences that passed the filtering thresholds. FDRs for searches against the IncDB were all <1.7% and for the RedDB <0.2%.

For relative quantitation of proteins, normalized spectral abundance factor values, which give the relative abundance of a protein in a sample in %, were calculated for each sample according to the method of Florens et al. (2006) (Supplementary file 1).
symbionts and the host. 93,304 protein sequences were from relatives of the SOX symbiont, 26,622 from relatives of the MOX symbiont, and 123,021 from host-related bivalves. Redundant sequences were removed using the CD-hit-2D clustering algorithm (Li and Godzik, 2006) at 100% sequence clustering threshold. To determine false discovery rates (FDRs) of protein identification, both protein sequence databases were reversed and appended to the original databases as decoy sequences.

All MS/MS spectra from 1D-PAGE-LC-MS/MS experiments were searched against the two protein sequence databases using the SEQUEST (v.27, rev. 11) algorithm (Eng et al., 1994) with the following parameters: Parent Mass Tolerance, 0.0065 Da; Fragment Ion Tolerance, 1 Da; up to 2 missed cleavages allowed (internal lysine and arginine residues), fully tryptic peptides only, and oxidation of methionine as variable modification (+15.99 Da).

Scaffold (version 4.0.6.1, Proteome Software Inc., Portland, OR) was used for filtering and analysis of protein identifications. For the searches against the IncDB, protein identifications were filtered with the PeptideProphet and ProteinProphet algorithms implemented in Scaffold (Ma et al., 2012) using the following thresholds: 95% for peptides and 99% for proteins. For the searches against the RedDB, protein identifications were filtered at the peptide level using SEQUEST scores (XCorrs of at least 2.5 (charge +2) and 3.5 (charges >+2), DeltaCN >0.08) and by requiring that they contained at least two identified peptides.

Protein level FDRs for all database searches were determined according to the method of Käll et al. (2008) using the number of identified decoy sequences that passed the filtering thresholds. FDRs for searches against the IncDB were all <1.7% and for the RedDB <0.2%.

For relative quantitation of proteins, normalized spectral abundance factor values, which give the relative abundance of a protein in a sample in %, were calculated for each sample according to the method of Florens et al. (2006) (Supplementary file 1).