Gartman A, Findlay AJ. Impacts of hydrothermal plume processes on oceanic metal cycles and transport. Nat Geosci. 2020;13:396–402.
Google Scholar
Sander SG, Koschinsky A. Metal flux from hydrothermal vents increased by organic complexation. Nat Geosci. 2011;4:145–50.
Google Scholar
German CR, Casciotti KA, Dutay JC, Heimbürger LE, Jenkins WJ, Measures CI, et al. Hydrothermal impacts on trace element and isotope ocean biogeochemistry. Philos Trans R Soc A Math Phys Eng Sci. 2016;374:20160035.
Ardyna M, Lacour L, Sergi S, d’Ovidio F, Sallée JB, Rembauville M, et al. Hydrothermal vents trigger massive phytoplankton blooms in the Southern Ocean. Nat Commun. 2019;10:1–8.
Google Scholar
McCollom TM. Geochemical constraints on primary productivity in submarine hydrothermal vent plumes. Deep Res Part I Oceanogr Res Pap. 2000;47:85–101.
Google Scholar
Dick GJ, Tebo BM. Microbial diversity and biogeochemistry of the Guaymas Basin deep-sea hydrothermal plume. Environ Microbiol. 2010;12:1334–47.
Google Scholar
Nakamura K, Takai K. Theoretical constraints of physical and chemical properties of hydrothermal fluids on variations in chemolithotrophic microbial communities in seafloor hydrothermal systems. Prog Earth Planet Sci. 2014;1:1–24.
Dick GJ. The microbiomes of deep-sea hydrothermal vents: distributed globally, shaped locally. Nat Rev Microbiol. 2019;17:271–83.
Google Scholar
Sunamura M, Higashi Y, Miyako C, Ishibashi JI, Maruyama A. Two bacteria phylotypes are predominant in the Suiyo Seamount hydrothermal plume. Appl Environ Microbiol. 2004;70:1190–8.
Google Scholar
Lavik G, Stührmann T, Brüchert V, Van Der Plas A, Mohrholz V, Lam P, et al. Detoxification of sulphidic African shelf waters by blooming chemolithotrophs. Nature. 2009;457:581–4.
Google Scholar
Canfield DE, Stewart FJ, Thamdrup B, De Brabandere L, Dalsgaard T, Delong EF, et al. A cryptic sulfur cycle in oxygen-minimum-zone waters off the Chilean coast. Science. 2010;330:1375–8.
Google Scholar
Callbeck CM, Lavik G, Ferdelman TG, Fuchs B, Gruber-Vodicka HR, Hach PF, et al. Oxygen minimum zone cryptic sulfur cycling sustained by offshore transport of key sulfur oxidizing bacteria. Nat Commun. 2018;9:1.
Google Scholar
Glaubitz S, Kießlich K, Meeske C, Labrenz M, Jürgens K. SUP05 Dominates the gammaproteobacterial sulfur oxidizer assemblages in pelagic redoxclines of the central baltic and black seas. Appl Environ Microbiol. 2013;79:2767–76.
Google Scholar
Pjevac P, Korlević M, Berg JS, Bura-Nakić E, Ciglenečki I, Amann R, et al. Community shift from phototrophic to chemotrophic sulfide oxidation following anoxic holomixis in a stratified seawater lake. Appl Environ Microbiol. 2015;81:298–308.
Google Scholar
Zhou K, Zhang R, Sun J, Zhang W, Tian RM, Chen C, et al. Potential interactions between clade SUP05 sulfur-oxidizing bacteria and phages in hydrothermal vent sponges. Appl Environ Microbiol. 2019;85:1–20.
Duperron S, Nadalig T, Caprais JC, Sibuet M, Fiala-Médioni A, Amann R, et al. Dual symbiosis in a Bathymodiolus sp. mussel from a methane seep on the Gabon Continental Margin (Southeast Atlantic): 16S rRNA phylogeny and distribution of the symbionts in gills. Appl Environ Microbiol. 2005;71:1694–700.
Google Scholar
Ansorge R, Romano S, Sayavedra L, Porras MÁG, Kupczok A, Tegetmeyer HE, et al. Functional diversity enables multiple symbiont strains to coexist in deep-sea mussels. Nat Microbiol. 2019;4:2487–97.
Google Scholar
Anantharaman K, Breier JA, Sheik CS, Dick GJ. Evidence for hydrogen oxidation and metabolic plasticity in widespread deep-sea sulfur-oxidizing bacteria. Proc Natl Acad Sci USA. 2013;110:330–5.
Google Scholar
Wang W, Li Z, Zeng L, Dong C, Shao Z. The oxidation of hydrocarbons by diverse heterotrophic and mixotrophic bacteria that inhabit deep-sea hydrothermal ecosystems. ISME J. 2020;14:1994–2006.
Google Scholar
Spietz RL, Lundeen RA, Zhao X, Nicastro D, Ingalls AE, Morris RM. Heterotrophic carbon metabolism and energy acquisition in Candidatus Thioglobus singularis strain PS1, a member of the SUP05 clade of marine Gammaproteobacteria. Environ Microbiol. 2019;21:2391–401.
Google Scholar
Marshall KT, Morris RM. Isolation of an aerobic sulfur oxidizer from the SUP05/Arctic96BD-19 clade. ISME J. 2013;7:452–5.
Google Scholar
Shah V, Morris RM. Genome sequence of “Candidatus Thioglobus autotrophica” strain EF1, a chemoautotroph from the SUP05 clade of marine Gammaproteobacteria. Genome Announc. 2015;3:e01156–15.
Google Scholar
van Vliet DM, von Meijenfeldt FAB, Dutilh BE, Villanueva L, Sinninghe Damsté JS, Stams AJM, et al. The bacterial sulfur cycle in expanding dysoxic and euxinic marine waters. Environ Microbiol. 2021;23:2834–57.
Google Scholar
De Ronde CEJ, Baker ET, Massoth GJ, Lupton JE, Wright IC, Feely RA, et al. Intra-oceanic subduction-related hydrothermal venting, Kermadec volcanic arc, New Zealand. Earth Planet Sci Lett. 2001;193:359–69.
De Ronde CEJ, Baker ET, Massoth GJ, Lupton JE, Wright IC, Sparks RJ, et al. Submarine hydrothermal activity along the mid-Kermadec Arc, New Zealand: large-scale effects on venting. Geochem Geophys Geosyst. 2007;8:Q07007.
Kleint C, Bach W, Diehl A, Fröhberg N, Garbe-Schönberg D, Hartmann JF, et al. Geochemical characterization of highly diverse hydrothermal fluids from volcanic vent systems of the Kermadec intraoceanic arc. Chem Geol. 2019;528:119289.
Google Scholar
Baker ET, Resing JA, Haymon RM, Tunnicliffe V, Martinez F, Ferrini V, et al. How many vent fields? New estimates of vent field populations on ocean ridges from precise mapping of hydrothermal discharge locations. Prog Earth Planet Sci. 2016;449:186–96.
Google Scholar
Walker SL, Baker ET, Resing JA, Nakamura K, McLain PD. A new tool for detecting hydrothermal plumes: an ORP sensor for the PMEL MAPR. AGU Fall Meet Abstr. 2007;2007:V21D–0753.
Herlemann DPR, Labrenz M, Jürgens K, Bertilsson S, Waniek JJ, Andersson AF. Transitions in bacterial communities along the 2000 km salinity gradient of the Baltic Sea. ISME J. 2011;5:1571–9.
Google Scholar
Reintjes G, Tegetmeyer HE, Bürgisser M, Orlić S, Tews I, Zubkov M, et al. On-site analysis of bacterial communities of the ultraoligotrophic South Pacific Gyre. Appl Environ Microbiol. 2019;85:e00184–19.
Google Scholar
Martin M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J. 2011;17:10–2.
Schloss PD, Westcott SL, Ryabin T, Hall JR, Hartmann M, Hollister EB, et al. Introducing mothur: Open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl Environ Microbiol. 2009;75:7537–41.
Google Scholar
Bushnell B. BBMap (version 35.14) [Software]. 2015. https://sourceforge.net/projects/bbmap/.
Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, et al. The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools. Nucleic Acids Res. 2013;41:D590–6.
Google Scholar
Ludwig W, Strunk O, Westram R, Richter L, Meier H, Yadhukumar A, et al. ARB: a software environment for sequence data. Nucleic Acids Res. 2004;32:1363–71.
Google Scholar
Pernthaler A, Pernthaler J, Amann R. Fluorescence in situ hybridization and catalyzed reporter deposition for the identification of marine bacteria. Appl Environ Microbiol. 2002;68:3094–101.
Google Scholar
Andrews S. FastQC: a quality control tool for high throughput sequence data. Babraham Bioinformatics; 2010.
Rodriguez-R LM, Gunturu S, Tiedje JM, Cole JR, Konstantinidis KT. Nonpareil 3: fast estimation of metagenomic coverage and sequence diversity. mSystems. 2018;3:e00039–18.
Google Scholar
Li D, Luo R, Liu CM, Leung CM, Ting HF, Sadakane K, et al. MEGAHIT v1.0: a fast and scalable metagenome assembler driven by advanced methodologies and community practices. Methods. 2016;102:3–11.
Google Scholar
Strous M, Kraft B, Bisdorf R, Tegetmeyer HE. The binning of metagenomic contigs for microbial physiology of mixed cultures. Front Microbiol. 2012;3:410.
Google Scholar
Alneberg J, Bjarnason BS, De Bruijn I, Schirmer M, Quick J, Ijaz UZ, et al. Binning metagenomic contigs by coverage and composition. Nat Methods. 2014;11:1144–6.
Google Scholar
Eren AM, Kiefl E, Shaiber A, Veseli I, Miller SE, Schechter MS, et al. Community-led, integrated, reproducible multi-omics with anvi’o. Nat Microbiol. 2021;6:3–6.
Google Scholar
Meier DV, Bach W, Girguis PR, Gruber-Vodicka HR, Reeves EP, Richter M, et al. Heterotrophic proteobacteria in the vicinity of diffuse hydrothermal venting. Environ Microbiol. 2016;18:4348–68.
Google Scholar
Bankevich A, Nurk S, Antipov D, Gurevich AA, Dvorkin M, Kulikov AS, et al. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biol. 2012;19:455–77.
Google Scholar
Parks DH, Imelfort M, Skennerton CT, Hugenholtz P, Tyson GW. CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Res. 2015;25:1043–55.
Google Scholar
Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114–20.
Google Scholar
Kopylova E, Noé L, Touzet H. SortMeRNA: fast and accurate filtering of ribosomal RNAs in metatranscriptomic data. Bioinformatics. 2012;28:3211–7.
Google Scholar
Gomes AÉ, Stuchi LP, Siqueira NM, Henrique JB, Vicentini R, Ribeiro ML, et al. Selection and validation of reference genes for gene expression studies in Klebsiella pneumoniae using Reverse Transcription Quantitative real-time PCR. Sci Rep. 2018;8:1–4.
Kolde R. pheatmap: Pretty heatmaps. 2015. https://CRAN.R-project.org/package=pheatmap.
Garnier S. viridis: Default Color Maps from’matplotlib’. 2017. https://CRAN.R-project.org/.
R Core Team. R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2013.
Oksanen J, Blanchet FG, Friendly M, Kindt R, Legendre P, McGlinn D, et al. Vegan: Community ecology package. 2020.
Pena EA, Slate EH. gvlma: Global validation of linear models assumptions. R package version 1.0.0.3. 2019. https://CRAN.R-project.org/package=gvlma.
Anderson MJ. A new method for non parametric multivariate analysis of variance. Austral Ecol. 2001;26:32–46.
Waite DW, Chuvochina M, Pelikan C, Parks DH, Yilmaz P, Wagner M, et al. Proposal to reclassify the proteobacterial classes Deltaproteobacteria and Oligoflexia, and the phylum Thermodesulfobacteria into four phyla reflecting major functional capabilities. Int J Syst Evol Microbiol. 2020;70:5972–6016.
Google Scholar
Anantharaman K, Breier JA, Dick GJ. Metagenomic resolution of microbial functions in deep-sea hydrothermal plumes across the Eastern Lau Spreading Center. ISME J. 2016;10:225–39.
Google Scholar
Biller SJ, Berube PM, Dooley K, Williams M, Satinsky BM, Hackl T, et al. Data descriptor: marine microbial metagenomes sampled across space and time. Sci Data. 2018;5:1–7.
Meier DV, Pjevac P, Bach W, Hourdez S, Girguis PR, Vidoudez C, et al. Niche partitioning of diverse sulfur-oxidizing bacteria at hydrothermal vents. ISME J. 2017;11:1545–58.
Google Scholar
Chaumeil P-A, Mussig AJ, Hugenholtz P, Parks DH. GTDB-Tk: a toolkit to classify genomes with the Genome Taxonomy Database. Bioinformatics. 2019;36:1925–7.
Google Scholar
Zhou Z, Tran PQ, Kieft K, Anantharaman K. Genome diversification in globally distributed novel marine Proteobacteria is linked to environmental adaptation. ISME J. 2020;14:2060–77.
Google Scholar
Parks DH, Rinke C, Chuvochina M, Chaumeil PA, Woodcroft BJ, Evans PN, et al. Recovery of nearly 8,000 metagenome-assembled genomes substantially expands the tree of life. Nat Microbiol. 2017;2:1533–42.
Google Scholar
Blackburn NT, Clarke AJ. Identification of four families of peptidoglycan lytic transglycosylases. J Mol Evol. 2001;52:78–84.
Google Scholar
Hashimoto W, Ochiai A, Momma K, Itoh T, Mikami B, Maruyama Y, et al. Crystal structure of the glycosidase family 73 peptidoglycan hydrolase FlgJ. Biochem Biophys Res Commun. 2009;381:16–21.
Google Scholar
Ilbert M, Bonnefoy V. Insight into the evolution of the iron oxidation pathways. Biochim Biophys Acta Bioenerg. 2013;1827:161–75.
Google Scholar
Barco RA, Emerson D, Sylvan JB, Orcutt BN, Jacobson Meyers ME, Ramírez GA, et al. New insight into microbial iron oxidation as revealed by the proteomic profile of an obligate iron-oxidizing chemolithoautotroph. Appl Environ Microbiol. 2015;81:5927–37.
Google Scholar
Guo J, Bolduc B, Zayed AA, Varsani A, Dominguez-Huerta G, Delmont TO, et al. VirSorter2: a multi-classifier, expert-guided approach to detect diverse DNA and RNA viruses. Microbiome. 2021;9:1–13.
Duarte CM. Seafaring in the 21st century: the Malaspina 2010 circumnavigation expedition. Limnol Oceanogr Bull. 2015;24:11–14.
Sheik CS, Anantharaman K, Breier JA, Sylvan JB, Edwards KJ, Dick GJ. Spatially resolved sampling reveals dynamic microbial communities in rising hydrothermal plumes across a back-arc basin. ISME J. 2015;9:1434–45.
Google Scholar
Konstantinidis KT, Rosselló-Móra R, Amann R. Uncultivated microbes in need of their own taxonomy. ISME J. 2017;11:2399–406.
Google Scholar
Murray AE, Freudenstein J, Gribaldo S, Hatzenpichler R, Hugenholtz P, Kämpfer P, et al. Roadmap for naming uncultivated Archaea and Bacteria. Nat Microbiol. 2020;5:987–94.
Google Scholar
Shah V, Zhao X, Lundeen RA, Ingalls AE, Nicastro D, Morris RM. Morphological plasticity in a sulfur-oxidizing marine bacterium from the SUP05 clade enhances dark carbon fixation. MBio. 2019;10:e00216–19.
Google Scholar
Yamamoto M, Takai K. Sulfur metabolisms in Epsilon- and Gammaproteobacteria in deep-sea hydrothermal fields. Front Microbiol. 2011;2:192.
Google Scholar
White GF, Edwards MJ, Gomez-Perez L, Richardson DJ, Butt JN, Clarke TA. Mechanisms of bacterial extracellular electron exchange. Adv Micro Physiol. 2016;68:87–138.
Google Scholar
Findlay AJ, Estes ER, Gartman A, Yücel M, Kamyshny A, Luther GW. Iron and sulfide nanoparticle formation and transport in nascent hydrothermal vent plumes. Nat Commun. 2019;10:1–7.
Google Scholar
Gartman A, Luther GW. Oxidation of synthesized sub-micron pyrite (FeS2) in seawater. Geochim Cosmochim Acta. 2014;144:96–108.
Google Scholar
Bonnefoy V, Holmes DS. Genomic insights into microbial iron oxidation and iron uptake strategies in extremely acidic environments. Environ Microbiol. 2012;14:1597–611.
Google Scholar
Singh VK, Singh AL, Singh R, Kumar A. Iron oxidizing bacteria: insights on diversity, mechanism of iron oxidation and role in management of metal pollution. Environ Sustain. 2018;1:221–31.
He S, Barco RA, Emerson D, Roden EE. Comparative genomic analysis of neutrophilic iron(II) oxidizer genomes for candidate genes in extracellular electron transfer. Front Microbiol. 2017;8:1584.
Google Scholar
McAllister SM, Polson SW, Butterfield DA, Glazer BT, Sylvan JB, Chan CS. Validating the Cyc2 neutrophilic iron oxidation pathway using meta-omics of Zetaproteobacteria iron mats at marine hydrothermal vents. mSystems. 2020;5:e00553–19.
Google Scholar
Barco RA, Hoffman CL, Ramírez GA, Toner BM, Edwards KJ, Sylvan JB. In-situ incubation of iron-sulfur mineral reveals a diverse chemolithoautotrophic community and a new biogeochemical role for Thiomicrospira. Environ Microbiol. 2017;19:1322–37.
Google Scholar
Lesniewski RA, Jain S, Anantharaman K, Schloss PD, Dick GJ. The metatranscriptome of a deep-sea hydrothermal plume is dominated by water column methanotrophs and lithotrophs. ISME J. 2012;6:2257–68.
Google Scholar
Reed DC, Breier JA, Jiang H, Anantharaman K, Klausmeier CA, Toner BM, et al. Predicting the response of the deep-ocean microbiome to geochemical perturbations by hydrothermal vents. ISME J. 2015;9:1857–69.
Google Scholar
Maki JS. Bacterial intracellular sulfur globules: structure and function. J Mol Microbiol Biotechnol. 2013;23:270–80.
Google Scholar
Neuholz R, Kleint C, Schnetger B, Koschinsky A, Laan P, Middag R, et al. Submarine hydrothermal discharge and fluxes of dissolved Fe and Mn, and He isotopes at Brothers Volcano based on radium isotopes. Minerals. 2020;10:969.
Google Scholar
Waite DW, Vanwonterghem I, Rinke C, Parks DH, Zhang Y, Takai K, et al. Comparative genomic analysis of the class Epsilonproteobacteria and proposed reclassification to Epsilonbacteraeota (phyl. nov.). Front Microbiol. 2017;8:682.
Google Scholar
Waite DW, Vanwonterghem I, Rinke C, Parks DH, Zhang Y, Takai K, et al. Addendum: comparative genomic analysis of the class Epsilonproteobacteria and proposed reclassification to Epsilonbacteraeota (phyl. nov.). Front Microbiol. 2018;9:772.
Google Scholar
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