Azam F, Malfatti F. Microbial structuring of marine ecosystems. Nat Rev Microbiol. 2007;5:782–91.
Google Scholar
Lechtenfeld OJ, Hertkorn N, Shen Y, Witt M, Benner R. Marine sequestration of carbon in bacterial metabolites. Nat Commun. 2015;6:6711.
Google Scholar
Buchan A, LeCleir GR, Gulvik CA, Gonzalez JM. Master recyclers: features and functions of bacteria associated with phytoplankton blooms. Nat Rev Microbiol. 2014;12:686–98.
Google Scholar
DeLong E (ed). Microbial Metagenomics, Metatranscriptomics, and Metaproteomics, 1st edn. San Diego, CA, USA: Academic Press; 2013.
White RA III, Callister SJ, Moore RJ, Baker ES, Jansson JK. The past, present and future of microbiome analyses. Nat Protoc. 2016;11:2049.
Google Scholar
Hanson CA, Fuhrman JA, Horner-Devine MC, Martiny JB. Beyond biogeographic patterns: processes shaping the microbial landscape. Nat Rev Microbiol. 2012;10:497–506.
Google Scholar
Gilbert JA, Steele JA, Caporaso JG, Steinbruck L, Reeder J, Temperton B, et al. Defining seasonal marine microbial community dynamics. ISME J. 2012;6:298–308.
Google Scholar
Needham DM, Fuhrman JA. Pronounced daily succession of phytoplankton, archaea and bacteria following a spring bloom. Nat Microbiol. 2016;1:16005.
Google Scholar
Lindh MV, Sjostedt J, Andersson AF, Baltar F, Hugerth LW, Lundin D, et al. Disentangling seasonal bacterioplankton population dynamics by high-frequency sampling. Environ Microbiol. 2015;17:2459–76.
Google Scholar
Fuhrman JA, Cram JA, Needham DM. Marine microbial community dynamics and their ecological interpretation. Nat Rev Microbiol. 2015;13:133–46.
Google Scholar
Ruiz‐González C, Logares R, Sebastián M, Mestre M, Rodríguez‐Martínez R, Galí M, et al. Higher contribution of globally rare bacterial taxa reflects environmental transitions across the surface ocean. Mol Ecol. 2019;28:1930–45.
Google Scholar
Sunagawa S, Coelho LP, Chaffron S, Kultima JR, Labadie K, Salazar G, et al. Ocean plankton. Struct Funct Glob Ocean Microbiome Sci. 2015;348:1261359.
Ibarbalz FM, Henry N, Brandao MC, Martini S, Busseni G, Byrne H, et al. Global trends in marine plankton diversity across kingdoms of life. Cell. 2019;179:1084–97 e21.
Google Scholar
Salazar G, Paoli L, Alberti A, Huerta-Cepas J, Ruscheweyh HJ, Cuenca M, et al. Gene expression changes and community turnover differentially shape the global ocean metatranscriptome. Cell. 2019;179:1068–83 e21.
Google Scholar
Boeuf D, Edwards BR, Eppley JM, Hu SK, Poff KE, Romano AE, et al. Biological composition and microbial dynamics of sinking particulate organic matter at abyssal depths in the oligotrophic open ocean. Proc Natl Acad Sci USA. 2019;116:11824–32.
Google Scholar
Ghiglione JF, Galand PE, Pommier T, Pedros-Alio C, Maas EW, Bakker K, et al. Pole-to-pole biogeography of surface and deep marine bacterial communities. Proc Natl Acad Sci USA. 2012;109:17633–8.
Google Scholar
Frias-Lopez J, Shi Y, Tyson GW, Coleman ML, Schuster SC, Chisholm SW, et al. Microbial community gene expression in ocean surface waters. Proc Natl Acad Sci USA. 2008;105:3805–10.
Google Scholar
Acinas SG, Sánchez P, Salazar G, Cornejo-Castillo FM, Sebastián M, Logares R, et al. Metabolic architecture of the deep ocean microbiome. bioRxiv. 2019:635680. https://doi.org/10.1101/635680.
Martin JH, Gordon RM, Fitzwater SE. Iron in Antarctic waters. Nature. 1990;345:156–8.
Google Scholar
Church MJ, Hutchins DA, Ducklow HW. Limitation of bacterial growth by dissolved organic matter and iron in the Southern ocean. Appl Environ Microbiol. 2000;66:455–66.
Google Scholar
Obernosterer I, Fourquez M, Blain S. Fe and C co-limitation of heterotrophic bacteria in the naturally fertilized region off the Kerguelen Islands. Biogeosciences. 2015;12:1983–92.
Google Scholar
Fourquez M, Obernosterer I, Blain S. A method for the use of the radiotracer 55Fe for microautoradiography and CARD-FISH of natural bacterial communities. FEMS Microbiol Lett. 2012;337:132–9.
Google Scholar
Koedooder C, Gueneugues A, Van Geersdaële R, Vergé V, Bouget F-Y, Labreuche Y, et al. The role of the glyoxylate shunt in the acclimation to iron limitation in marine heterotrophic bacteria. Front Mar Sci. 2018;5:435.
Google Scholar
Blain S, Tagliabue A (eds). Iron Cycle in Oceans, 1st edn. London, UK: ISTE Ltd and John Wiley & Sons, Inc.; 2016.
Dittmar T, Arnosti C. An inseparable liaison: marine microbes and nonliving organic matter. In: Gasol JM, Kirchman DL, editors. Microbial Ecology of the Oceans, 3rd edn. Hoboken NJ, USA: John Wiley and Sons, Inc.; 2018, pp 189–229.
Blain S, Queguiner B, Armand L, Belviso S, Bombled B, Bopp L, et al. Effect of natural iron fertilization on carbon sequestration in the Southern Ocean. Nature. 2007;446:1070–4.
Google Scholar
Lasbleiz M, Leblanc K, Armand LK, Christaki U, Georges C, Obernosterer I, et al. Composition of diatom communities and their contribution to plankton biomass in the naturally iron-fertilized region of Kerguelen in the Southern Ocean. FEMS Microbiol Ecol. 2016;92:fiw171.
Google Scholar
Obernosterer I, Catala P, Lebaron P, West NJ. Distinct bacterial groups contribute to carbon cycling during a naturally iron fertilized phytoplankton bloom in the Southern Ocean. Limnol Oceanogr. 2011;56:2391–401.
Google Scholar
Blain S, Capparos J, Guéneuguès A, Obernosterer I, Oriol L. Distributions and stoichiometry of dissolved nitrogen and phosphorus in the iron-fertilized region near Kerguelen (Southern Ocean). Biogeosciences. 2015;12:623–35.
Google Scholar
d’Ovidio F, Della Penna A, Trull TW, Nencioli F, Pujol M-I, Rio M-H, et al. The biogeochemical structuring role of horizontal stirring: Lagrangian perspectives on iron delivery downstream of the Kerguelen Plateau. Biogeosciences. 2015;12:5567–81.
Google Scholar
Landa M, Blain S, Christaki U, Monchy S, Obernosterer I. Shifts in bacterial community composition associated with increased carbon cycling in a mosaic of phytoplankton blooms. ISME J. 2016;10:39–50.
Google Scholar
Landa M, Blain S, Harmand J, Monchy S, Rapaport A, Obernosterer I. Major changes in the composition of a Southern Ocean bacterial community in response to diatom-derived dissolved organic matter. FEMS Microbiol Ecol. 2018;94:8.
Google Scholar
Fourquez M, Beier S, Jongmans E, Hunter R, Obernosterer I. Uptake of Leucine, chitin, and iron by prokaryotic groups during spring phytoplankton blooms induced by natural iron fertilization off Kerguelen Island (Southern Ocean). Front Mar Sci. 2016;3:256.
Google Scholar
Debeljak P, Toulza E, Beier S, Blain S, Obernosterer I. Microbial iron metabolism as revealed by gene expression profiles in contrasted Southern Ocean regimes. Environ Microbiol. 2019;21:2360–74.
Google Scholar
Christaki U, Gueneugues A, Liu Y, Blain S, Catala P, Colombet J, et al. Seasonal microbial food web dynamics in contrasting Southern Ocean productivity regimes. Limnol Oceanogr. 2021;66:108–22.
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
Uritskiy GV, DiRuggiero J, Taylor J. MetaWRAP-a flexible pipeline for genome-resolved metagenomic data analysis. Microbiome. 2018;6:158.
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
Wu YW, Simmons BA, Singer SW. MaxBin 2.0: an automated binning algorithm to recover genomes from multiple metagenomic datasets. Bioinformatics. 2016;32:605–7.
Google Scholar
Kang DD, Li F, Kirton E, Thomas A, Egan R, An H, et al. MetaBAT 2: an adaptive binning algorithm for robust and efficient genome reconstruction from metagenome assemblies. PeerJ. 2019;7:e7359.
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
Bendall ML, Stevens SL, Chan LK, Malfatti S, Schwientek P, Tremblay J, et al. Genome-wide selective sweeps and gene-specific sweeps in natural bacterial populations. ISME J. 2016;10:1589–601.
Google Scholar
Hyatt D, Chen GL, Locascio PF, Land ML, Larimer FW, Hauser LJ. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinforma. 2010;11:119.
Google Scholar
Huerta-Cepas J, Szklarczyk D, Forslund K, Cook H, Heller D, Walter MC, et al. eggNOG 4.5: a hierarchical orthology framework with improved functional annotations for eukaryotic, prokaryotic and viral sequences. Nucleic Acids Res. 2016;44:D286–93.
Google Scholar
Huerta-Cepas J, Forslund K, Coelho LP, Szklarczyk D, Jensen LJ, von Mering C, et al. Fast genome-wide functional annotation through orthology assignment by eggNOG-Mapper. Mol Biol Evol. 2017;34:2115–22.
Google Scholar
El-Gebali S, Mistry J, Bateman A, Eddy SR, Luciani A, Potter SC, et al. The Pfam protein families database in 2019. Nucleic Acids Res. 2019;47:D427–D32.
Google Scholar
Eddy SR. Accelerated profile HMM searches. PLoS Comput Biol. 2011;7:e1002195.
Google Scholar
Kanehisa M, Goto S. KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 2000;28:27–30.
Google Scholar
Kanehisa M, Sato Y. Morishima K. BlastKOALA and GhostKOALA: KEGG tools for functional characterization of genome and metagenome sequences. J Mol Biol. 2016;428:726–31.
Google Scholar
Aramaki T, Blanc-Mathieu R, Endo H, Ohkubo K, Kanehisa M, Goto S, et al. KofamKOALA: KEGG ortholog assignment based on profile HMM and adaptive score threshold. Bioinformatics. 2019;36:2251–2.
Google Scholar
Saier MH Jr., Reddy VS, Tsu BV, Ahmed MS, Li C, Moreno-Hagelsieb G. The transporter classification database (TCDB): recent advances. Nucleic Acids Res. 2016;44:D372–9.
Google Scholar
Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. J Mol Biol. 1990;215:403–10.
Google Scholar
Cantarel BL, Coutinho PM, Rancurel C, Bernard T, Lombard V, Henrissat B. The Carbohydrate-Active EnZymes database (CAZy): an expert resource for Glycogenomics. Nucleic Acids Res. 2009;37:D233–8.
Google Scholar
Zhang H, Yohe T, Huang L, Entwistle S, Wu P, Yang Z, et al. dbCAN2: a meta server for automated carbohydrate-active enzyme annotation. Nucleic Acids Res. 2018;46:W95–W101.
Google Scholar
Rawlings ND, Barrett AJ, Thomas PD, Huang X, Bateman A, Finn RD. The MEROPS database of proteolytic enzymes, their substrates and inhibitors in 2017 and a comparison with peptidases in the PANTHER database. Nucleic Acids Res. 2018;46:D624–D32.
Google Scholar
Garber AI, Nealson KH, Okamoto A, McAllister SM, Chan CS, Barco RA, et al. FeGenie: a comprehensive tool for the identification of iron genes and iron gene neighborhoods in genome and metagenome assemblies. Front Microbiol. 2020;11:37.
Google Scholar
Dupont CL, Yang S, Palenik B, Bourne PE. Modern proteomes contain putative imprints of ancient shifts in trace metal geochemistry. Proc Natl Acad Sci USA. 2006;103:17822–7.
Google Scholar
Chaumeil PA, 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
Emms DM, Kelly S. OrthoFinder: phylogenetic orthology inference for comparative genomics. Genome Biol. 2019;20:238.
Google Scholar
Katoh K, Standley DM. MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol Biol Evol. 2013;30:772–80.
Google Scholar
Capella-Gutierrez S, Silla-Martinez JM, Gabaldon T. trimAl: a tool for automated alignment trimming in large-scale phylogenetic analyses. Bioinformatics. 2009;25:1972–3.
Google Scholar
Nguyen LT, Schmidt HA, von Haeseler A, Minh BQ. IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol Biol Evol. 2015;32:268–74.
Google Scholar
Menzel P, Ng KL, Krogh A. Fast and sensitive taxonomic classification for metagenomics with Kaiju. Nat Commun. 2016;7:11257.
Google Scholar
Liao Y, Smyth GK, Shi W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics. 2014;30:923–30.
Google Scholar
Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods. 2012;9:357–9.
Google Scholar
Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 2014;15:550.
Google Scholar
Rodriguez RL, Gunturu S, Tiedje JM, Cole JR, Konstantinidis KT. Nonpareil 3: fast estimation of metagenomic coverage and sequence diversity. mSystems. 2018;3:3.
Google Scholar
Pearson WR An introduction to sequence similarity (“homology”) searching. Curr Protoc Bioinformatics. 2013;Chapter 3:Unit3 1.
Jain C, Rodriguez RL, Phillippy AM, Konstantinidis KT, Aluru S. High throughput ANI analysis of 90K prokaryotic genomes reveals clear species boundaries. Nat Commun. 2018;9:5114.
Google Scholar
Satinsky BM, Gifford SM, Crump BC, Moran MA. Use of internal standards for quantitative metatranscriptome and metagenome analysis. Methods Enzymol. 2013;531:237–50.
Google Scholar
Louca S, Polz MF, Mazel F, Albright MBN, Huber JA, O’Connor MI, et al. Function and functional redundancy in microbial systems. Nat Ecol Evol. 2018;2:936–43.
Google Scholar
Kuhaudomlarp S, Patron NJ, Henrissat B, Rejzek M, Saalbach G, Field RA. Identification of Euglena gracilis beta-1,3-glucan phosphorylase and establishment of a new glycoside hydrolase (GH) family GH149. J Biol Chem. 2018;293:2865–76.
Google Scholar
Ho A, Di Lonardo DP, Bodelier PL. Revisiting life strategy concepts in environmental microbial ecology. FEMS Microbiol Ecol. 2017;93:3.
Rodionov DA, Gelfand MS, Todd JD, Curson AR, Johnston AW. Computational reconstruction of iron- and manganese-responsive transcriptional networks in alpha-proteobacteria. PLoS Comput Biol. 2006;2:e163.
Google Scholar
Rincon-Enriquez G, Crete P, Barras F, Py B. Biogenesis of Fe/S proteins and pathogenicity: IscR plays a key role in allowing Erwinia chrysanthemi to adapt to hostile conditions. Mol Microbiol. 2008;67:1257–73.
Google Scholar
Py B, Barras F. Building Fe–S proteins: bacterial strategies. Nat Rev Microbiol. 2010;8:436–46.
Google Scholar
Zappa S, Bauer CE. Iron homeostasis in the Rhodobacter genus. Adv Bot Res. 2013;66:289–326.
Google Scholar
Jaggavarapu S, O’Brian MR. Differential control of Bradyrhizobium japonicum iron stimulon genes through variable affinity of the iron response regulator (Irr) for target gene promoters and selective loss of activator function. Mol Microbiol. 2014;92:609–24.
Google Scholar
Grote J, Thrash JC, Huggett MJ, Landry ZC, Carini P, Giovannoni SJ, et al. Streamlining and core genome conservation among highly divergent members of the SAR11 clade. mBio. 2012;3:e00252–12.
Google Scholar
McAdams HH, Srinivasan B, Arkin AP. The evolution of genetic regulatory systems in bacteria. Nat Rev Genet. 2004;5:169–78.
Google Scholar
Fourquez M, Devez A, Schaumann A, Guéneuguès A, Jouenne T, Obernosterer I, et al. Effects of iron limitation on growth and carbon metabolism in oceanic and coastal heterotrophic bacteria. Limnol Oceanogr. 2014;59:349–60.
Google Scholar
Wilson DN, Nierhaus KH. The weird and wonderful world of bacterial ribosome regulation. Crit Rev Biochem Mol Biol. 2007;42:187–219.
Google Scholar
Wei Y, Lee JM, Richmond C, Blattner FR, Rafalski JA, LaRossa RA. High-density microarray-mediated gene expression profiling of Escherichia coli. J Bacteriol. 2001;183:545–56.
Google Scholar
Hendrickson EL, Liu Y, Rosas-Sandoval G, Porat I, Soll D, Whitman WB, et al. Global responses of Methanococcus maripaludis to specific nutrient limitations and growth rate. J Bacteriol. 2008;190:2198–205.
Google Scholar
Gifford SM, Sharma S, Booth M, Moran MA. Expression patterns reveal niche diversification in a marine microbial assemblage. ISME J. 2013;7:281–98.
Google Scholar
Sonnenburg ED, Zheng H, Joglekar P, Higginbottom SK, Firbank SJ, Bolam DN, et al. Specificity of polysaccharide use in intestinal bacteroides species determines diet-induced microbiota alterations. Cell. 2010;141:1241–52.
Google Scholar
Gregg KJ, Zandberg WF, Hehemann JH, Whitworth GE, Deng L, Vocadlo DJ, et al. Analysis of a new family of widely distributed metal-independent alpha-mannosidases provides unique insight into the processing of N-linked glycans. J Biol Chem. 2011;286:15586–96.
Google Scholar
Matulewicz M, Cerezo A. Water-soluble sulfated polysaccharides from the red seaweed Chaetangium fastigiatum. Analysis of the system and the structures of the α-D-(1→3)-linked mannans. Carbohydr Polym. 1987;7:121–32.
Google Scholar
Kolender AA, Pujol CA, Damonte EB, Matulewicz MC, Cerezo AS. The system of sulfated α-(1→3)-linked D-mannans from the red seaweed Nothogenia fastigiata: structures, antiherpetic and anticoagulant properties. Carbohydr Res. 1997;304:53–60.
Google Scholar
Le Costaouëc T, Unamunzaga C, Mantecon L, Helbert WJAR. New structural insights into the cell-wall polysaccharide of the diatom Phaeodactylum tricornutum. Algal Res. 2017;26:172–9.
Google Scholar
Teeling H, Fuchs BM, Becher D, Klockow C, Gardebrecht A, Bennke CM, et al. Substrate-controlled succession of marine bacterioplankton populations induced by a phytoplankton bloom. Science. 2012;336:608–11.
Google Scholar
Teeling H, Fuchs BM, Bennke CM, Kruger K, Chafee M, Kappelmann L, et al. Recurring patterns in bacterioplankton dynamics during coastal spring algae blooms. Elife. 2016;5:e11888.
Google Scholar
Chen J, Robb CS, Unfried F, Kappelmann L, Markert S, Song T, et al. Alpha‐and beta‐mannan utilization by marine Bacteroidetes. Environ Microbiol. 2018;20:4127–40.
Google Scholar
Biersmith A, Benner R. Carbohydrates in phytoplankton and freshly produced dissolved organic matter. Mar Chem. 1998;63:131–44.
Google Scholar
Sichert A, Corzett CH, Schechter MS, Unfried F, Markert S, Becher D, et al. Verrucomicrobia use hundreds of enzymes to digest the algal polysaccharide fucoidan. Nat Microbiol. 2020;5:1026–39.
Google Scholar
Beja O, Aravind L, Koonin EV, Suzuki MT, Hadd A, Nguyen LP, et al. Bacterial rhodopsin: evidence for a new type of phototrophy in the sea. Science. 2000;289:1902–6.
Google Scholar
DeLong EF, Beja O. The light-driven proton pump proteorhodopsin enhances bacterial survival during tough times. PLoS Biol. 2010;8:e1000359.
Google Scholar
Olson DK, Yoshizawa S, Boeuf D, Iwasaki W, DeLong EF. Proteorhodopsin variability and distribution in the North Pacific Subtropical Gyre. ISME J. 2018;12:1047–60.
Google Scholar
Kim SY, Waschuk SA, Brown LS, Jung KH. Screening and characterization of proteorhodopsin color-tuning mutations in Escherichia coli with endogenous retinal synthesis. Biochim Biophys Acta. 2008;1777:504–13.
Google Scholar
von Lintig J, Vogt K. Filling the gap in vitamin A research. Molecular identification of an enzyme cleaving beta-carotene to retinal. J Biol Chem. 2000;275:11915–20.
Google Scholar
Korotkov KV, Sandkvist M, Hol WG. The type II secretion system: biogenesis, molecular architecture and mechanism. Nat Rev Microbiol. 2012;10:336–51.
Google Scholar
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