Disentangling microbial networks across pelagic zones in the tropical and subtropical global ocean.


Journal

Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555

Informations de publication

Date de publication:
02 Jan 2024
Historique:
received: 10 04 2023
accepted: 18 12 2023
medline: 4 1 2024
pubmed: 4 1 2024
entrez: 3 1 2024
Statut: epublish

Résumé

Microbial interactions are vital in maintaining ocean ecosystem function, yet their dynamic nature and complexity remain largely unexplored. Here, we use association networks to investigate possible ecological interactions in the marine microbiome among archaea, bacteria, and picoeukaryotes throughout different depths and geographical regions of the tropical and subtropical global ocean. Our findings reveal that potential microbial interactions change with depth and geographical scale, exhibiting highly heterogeneous distributions. A few potential interactions were global, meaning they occurred across regions at the same depth, while 11-36% were regional within specific depths. The bathypelagic zone had the lowest proportion of global associations, and regional associations increased with depth. Moreover, we observed that most surface water associations do not persist in deeper ocean layers despite microbial vertical dispersal. Our work contributes to a deeper understanding of the tropical and subtropical global ocean interactome, which is essential for addressing the challenges posed by global change.

Identifiants

pubmed: 38168083
doi: 10.1038/s41467-023-44550-y
pii: 10.1038/s41467-023-44550-y
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

126

Subventions

Organisme : Ministerio de Economía y Competitividad (Ministry of Economy and Competitiveness)
ID : RYC-2013-12554
Organisme : Ministerio de Economía y Competitividad (Ministry of Economy and Competitiveness)
ID : CTM2015-69936-P
Organisme : Norges Forskningsråd (Research Council of Norway)
ID : 240904

Informations de copyright

© 2024. The Author(s).

Références

Falkowski, P. G., Fenchel, T. & Delong, E. F. The microbial engines that drive earth’s biogeochemical cycles. Science 320, 1034–1039 (2008).
pubmed: 18497287 doi: 10.1126/science.1153213
DeLong, E. F. The microbial ocean from genomes to biomes. Nature 459, 200–206 (2009).
pubmed: 19444206 doi: 10.1038/nature08059
Krabberød, A. K., Bjorbækmo, M. F. M., Shalchian-Tabrizi, K. & Logares, R. Exploring the oceanic microeukaryotic interactome with metaomics approaches. Aquat. Microb. Ecol. 79, 1–12 (2017).
doi: 10.3354/ame01811
Vellend, M. The Theory of Ecological Communities. (Princeton University Press, 2020).
Logares, R. et al. Disentangling the mechanisms shaping the surface ocean microbiota. Microbiome 8, 55 (2020).
pubmed: 32312331 pmcid: 7171866 doi: 10.1186/s40168-020-00827-8
Sunagawa, S. et al. Structure and function of the global ocean microbiome. Science 348, 1261359 (2015).
pubmed: 25999513 doi: 10.1126/science.1261359
Ibarbalz, F. M. et al. Global trends in marine plankton diversity across kingdoms of life. Cell 179, 1084–1097.e21 (2019).
pubmed: 31730851 pmcid: 6912166 doi: 10.1016/j.cell.2019.10.008
Salazar, G. et al. Gene expression changes and community turnover differentially shape the global ocean metatranscriptome. Cell 179, 1068–1083.e21 (2019).
pubmed: 31730850 pmcid: 6912165 doi: 10.1016/j.cell.2019.10.014
Milke, F., Wagner-Doebler, I., Wienhausen, G. & Simon, M. Selection, drift and community interactions shape microbial biogeographic patterns in the Pacific Ocean. ISME J. 16, 2653–2665 (2022).
pubmed: 36115923 pmcid: 9666467 doi: 10.1038/s41396-022-01318-4
Cram, J. A. et al. Cross-depth analysis of marine bacterial networks suggests downward propagation of temporal changes. ISME J. 9, 2573–2586 (2015).
pubmed: 25989373 pmcid: 4817623 doi: 10.1038/ismej.2015.76
Parada, A. E. & Fuhrman, J. A. Marine archaeal dynamics and interactions with the microbial community over 5 years from surface to seafloor. ISME J. 11, 2510–2525 (2017).
pubmed: 28731479 pmcid: 5649162 doi: 10.1038/ismej.2017.104
Mestre, M. et al. Sinking particles promote vertical connectivity in the ocean microbiome. Proc. Natl Acad. Sci. USA 115, E6799 (2018).
pubmed: 29967136 pmcid: 6055141 doi: 10.1073/pnas.1802470115
Peoples, L. M. et al. Vertically distinct microbial communities in the Mariana and Kermadec trenches. PLOS One 13, 1–21 (2018).
doi: 10.1371/journal.pone.0195102
Xu, Z. et al. Vertical distribution of microbial eukaryotes from surface to the Hadal Zone of the Mariana Trench. Front. Microbiol. 9, 2023 (2018).
pubmed: 30210485 pmcid: 6120995 doi: 10.3389/fmicb.2018.02023
Giner, C. R. et al. Marked changes in diversity and relative activity of picoeukaryotes with depth in the world ocean. ISME J. 14, 437–449 (2020).
pubmed: 31645670 doi: 10.1038/s41396-019-0506-9
Massana, R. & Logares, R. Eukaryotic versus prokaryotic marine picoplankton ecology. Environ. Microbiol. 15, 1254–1261 (2013).
pubmed: 23206217 doi: 10.1111/1462-2920.12043
Layeghifard, M., Hwang, D. M. & Guttman, D. S. Disentangling interactions in the microbiome: a network perspective. Trends Microbiol. 25, 217–228 (2017).
pubmed: 27916383 doi: 10.1016/j.tim.2016.11.008
Seymour, J. R., Amin, S. A., Raina, J.-B. & Stocker, R. Zooming in on the phycosphere: the ecological interface for phytoplankton–bacteria relationships. Nat. Microbiol. 2, 17065 (2017).
pubmed: 28555622 doi: 10.1038/nmicrobiol.2017.65
Bjorbækmo, M. F. M., Evenstad, A., Røsæg, L. L., Krabberød, A. K. & Logares, R. The planktonic protist interactome: where do we stand after a century of research? ISME J. 14, 544–559 (2020).
pubmed: 31685936 doi: 10.1038/s41396-019-0542-5
Baldauf, S. L. An overview of the phylogeny and diversity of eukaryotes. J. Syst. Evol. 46, 263 (2008).
Lewis, W. H., Tahon, G., Geesink, P., Sousa, D. Z. & Ettema, T. J. G. Innovations to culturing the uncultured microbial majority. Nat. Rev. Microbiol. 19, 225–240 (2021).
pubmed: 33093661 doi: 10.1038/s41579-020-00458-8
Steele, J. A. et al. Marine bacterial, archaeal and protistan association networks reveal ecological linkages. ISME J. 5, 1414–1425 (2011).
pubmed: 21430787 pmcid: 3160682 doi: 10.1038/ismej.2011.24
Chow, C.-E. T. et al. Temporal variability and coherence of euphotic zone bacterial communities over a decade in the Southern California Bight. ISME J. 7, 2259–2273 (2013).
pubmed: 23864126 pmcid: 3834854 doi: 10.1038/ismej.2013.122
Chow, C.-E. T., Kim, D. Y., Sachdeva, R., Caron, D. A. & Fuhrman, J. A. Top-down controls on bacterial community structure: microbial network analysis of bacteria, T4-like viruses and protists. ISME J. 8, 816–829 (2014).
pubmed: 24196323 doi: 10.1038/ismej.2013.199
Needham, D. M., Sachdeva, R. & Fuhrman, J. A. Ecological dynamics and co-occurrence among marine phytoplankton, bacteria and myoviruses shows microdiversity matters. ISME J. 11, 1614–1629 (2017).
pubmed: 28398348 pmcid: 5520149 doi: 10.1038/ismej.2017.29
Krabberød, A. K. et al. Long-term patterns of an interconnected core marine microbiota. Environ. Microbiome 17, 22 (2022).
pubmed: 35526063 pmcid: 9080219 doi: 10.1186/s40793-022-00417-1
Lima-Mendez, G. et al. Determinants of community structure in the global plankton interactome. Science 348, 1262073 (2015).
pubmed: 25999517 doi: 10.1126/science.1262073
Milici, M. et al. Co-occurrence analysis of microbial taxa in the atlantic ocean reveals high connectivity in the free-living bacterioplankton. Front. Microbiol. 7, 649 (2016).
pubmed: 27199970 pmcid: 4858663 doi: 10.3389/fmicb.2016.00649
Chaffron, S. et al. Environmental vulnerability of the global ocean epipelagic plankton community interactome. Sci. Adv. 7, eabg1921 (2021).
pubmed: 34452910 pmcid: 8397264 doi: 10.1126/sciadv.abg1921
Arístegui, J., Gasol, J. M., Duarte, C. M. & Herndld, G. J. Microbial oceanography of the dark ocean’s pelagic realm. Limnol. Oceanogr. 54, 1501–1529 (2009).
doi: 10.4319/lo.2009.54.5.1501
Kara, E. L., Hanson, P. C., Hu, Y. H., Winslow, L. & McMahon, K. D. A decade of seasonal dynamics and co-occurrences within freshwater bacterioplankton communities from eutrophic Lake Mendota, WI, USA. ISME J. 7, 680–684 (2013).
pubmed: 23051691 doi: 10.1038/ismej.2012.118
Sun, P. et al. From the sunlit to the aphotic zone: assembly mechanisms and co-occurrence patterns of protistan-bacterial microbiotas in the Western Pacific Ocean. mSystems 8, e00013–23 (2023).
pubmed: 36847533 pmcid: 10134807 doi: 10.1128/msystems.00013-23
Shade, A. & Handelsman, J. Beyond the Venn diagram: the hunt for a core microbiome. Environ. Microbiol. 14, 4–12 (2012).
pubmed: 22004523 doi: 10.1111/j.1462-2920.2011.02585.x
Coutinho, F. H. et al. Niche distribution and influence of environmental parameters in marine microbial communities: a systematic review. PeerJ 3, e1008 (2015).
pubmed: 26157601 pmcid: 4476133 doi: 10.7717/peerj.1008
Mandakovic, D. et al. Structure and co-occurrence patterns in microbial communities under acute environmental stress reveal ecological factors fostering resilience. Sci. Rep. 8, 5875 (2018).
pubmed: 29651160 pmcid: 5897386 doi: 10.1038/s41598-018-23931-0
Deutschmann, I. M. et al. Disentangling temporal associations in marine microbial networks. Microbiome 11, 83 (2023).
pubmed: 37081491 pmcid: 10120119 doi: 10.1186/s40168-023-01523-z
Deutschmann, I. M. et al. Disentangling microbial networks across pelagic zones in the tropical and subtropical global ocean. https://doi.org/10.5281/zenodo.10230073 (2023).
Junger, P. C. et al. Global biogeography of the smallest plankton across ocean depths. Sci. Adv. 9, 1–15 (2023).
doi: 10.1126/sciadv.adg9763
Villarino, E. et al. Global beta diversity patterns of microbial communities in the surface and deep ocean. Glob. Ecol. Biogeogr. 31, 2323–2336 (2022).
doi: 10.1111/geb.13572
Ruiz-González, C. et al. Higher contribution of globally rare bacterial taxa reflects environmental transitions across the surface ocean. Mol. Ecol. 28, 1930–1945 (2019).
pubmed: 30663830 doi: 10.1111/mec.15026
Ruiz-González, C. et al. Major imprint of surface plankton on deep ocean prokaryotic structure and activity. Mol. Ecol. 29, 1820–1838 (2020).
pubmed: 32323882 doi: 10.1111/mec.15454
Coyte, K. Z., Schluter, J. & Foster, K. R. The ecology of the microbiome: networks, competition, and stability. Science 350, 663–666 (2015).
pubmed: 26542567 doi: 10.1126/science.aad2602
McCann, K., Hastings, A. & Huxel, G. R. Weak trophic interactions and the balance of nature. Nature 395, 794–798 (1998).
doi: 10.1038/27427
May, R. M. Will a large complex system be stable? Nature 238, 413–414 (1972).
pubmed: 4559589 doi: 10.1038/238413a0
Tilman, D. Biodiversity: population versus ecosystem stability. Ecology 77, 350–363 (1995).
doi: 10.2307/2265614
Mougi, A. & Kondoh, M. Diversity of interaction types and ecological community stability. Science 337, 349–351 (2012).
pubmed: 22822151 doi: 10.1126/science.1220529
Tang, S., Pawar, S. & Allesina, S. Correlation between interaction strengths drives stability in large ecological networks. Ecol. Lett. 17, 1094–1100 (2014).
pubmed: 24946877 doi: 10.1111/ele.12312
Muller, E. E. L. et al. Using metabolic networks to resolve ecological properties of microbiomes. Curr. Opin. Syst. Biol. 8, 73–80 (2018).
doi: 10.1016/j.coisb.2017.12.004
Röttjers, L. & Faust, K. From hairballs to hypotheses–biological insights from microbial networks. FEMS Microbiol. Rev. 42, 761–780 (2018).
pubmed: 30085090 pmcid: 6199531 doi: 10.1093/femsre/fuy030
Tackmann, J., Rodrigues, J. F. M. & von Mering, C. Rapid inference of direct interactions in large-scale ecological networks from heterogeneous microbial sequencing data. Cell Syst. 9, 286–296.e8 (2019).
pubmed: 31542415 doi: 10.1016/j.cels.2019.08.002
Logares, R. et al. Metagenomic 16S rDNA Illumina tags are a powerful alternative to amplicon sequencing to explore diversity and structure of microbial communities. Environ. Microbiol. 16, 2659–2671 (2013).
pubmed: 24102695 doi: 10.1111/1462-2920.12250
Callahan, B. J. et al. DADA2: High-resolution sample inference from Illumina amplicon data. Nat. Methods 13, 581–583 (2016).
pubmed: 27214047 pmcid: 4927377 doi: 10.1038/nmeth.3869
Milke, F., Meyerjürgens, J. & Simon, M. Ecological mechanisms and current systems shape the modular structure of the global oceans’ prokaryotic seascape. Nat. Commun. 14, 6141 (2023).
pubmed: 37783696 pmcid: 10545751 doi: 10.1038/s41467-023-41909-z
Reid, J. On the mid-depth circulation of the world ocean. Evolution of Physical Oceanography BA Warren, C. Wunsch, 70–111 (1981).
Yesson, C., Clark, M. R., Taylor, M. L. & Rogers, A. D. The global distribution of seamounts based on 30 arc seconds bathymetry data. Deep Sea Res. Part I: Oceanogr. Res. Pap. 58, 442–453 (2011).
doi: 10.1016/j.dsr.2011.02.004
Hansell, D. A. & Carlson, C. A. Deep-ocean gradients in the concentration of dissolved organic carbon. Nature 395, 263–266 (1998).
doi: 10.1038/26200
Royo-Llonch et al. Compendium of 530 metagenome-assembled bacterial and archaeal genomes from the polar Arctic Ocean. Nat. Microbiol. 6, 1561–1574 (2021).
pubmed: 34782724 doi: 10.1038/s41564-021-00979-9
Schmidt, T. S. B., Matias Rodrigues, J. F. & Von Mering, C. A family of interaction-adjusted indices of community similarity. ISME J. 11, 791–807 (2017).
pubmed: 27935587 doi: 10.1038/ismej.2016.139
Sebastián, M. et al. Environmental gradients and physical barriers drive the basin-wide spatial structuring of Mediterranean Sea and adjacent eastern Atlantic Ocean prokaryotic communities. Limnol. Oceanogr. 66, 4077–4095 (2021).
doi: 10.1002/lno.11944
Lozupone, C. A. & Knight, R. Global patterns in bacterial diversity. Proc. Natl Acad. Sci. USA 104, 11436–11440 (2007).
pubmed: 17592124 pmcid: 2040916 doi: 10.1073/pnas.0611525104
Lambert, S., Lozano, J.-C., Bouget, F.-Y. & Galand, P. E. Seasonal marine microorganisms change neighbours under contrasting environmental conditions. Environ. Microbiol. 23, 2592–2604 (2021).
pubmed: 33760330 doi: 10.1111/1462-2920.15482
Berdjeb, L., Parada, A., Needham, D. M. & Fuhrman, J. A. Short-term dynamics and interactions of marine protist communities during the spring–summer transition. ISME J. 12, 1907–1917 (2018).
pubmed: 29599520 pmcid: 6052004 doi: 10.1038/s41396-018-0097-x
Richter, D. J. et al. Genomic evidence for global ocean plankton biogeography shaped by large-scale current systems. eLife 11, e78129 (2022).
pubmed: 35920817 pmcid: 9348854 doi: 10.7554/eLife.78129
Boeuf, D. 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 116, 11824 (2019).
pubmed: 31127042 pmcid: 6575173 doi: 10.1073/pnas.1903080116
McClain, C. R. & Schlacher, T. A. On some hypotheses of diversity of animal life at great depths on the sea floor. Mar. Ecol. 36, 849–872 (2015).
doi: 10.1111/maec.12288
Hessler, R. R. & Sanders, H. L. Faunal diversity in the deep-sea. Deep Sea Res. Oceanogr Abstr. 14, 65–78 (1967).
doi: 10.1016/0011-7471(67)90029-0
Acinas, S. G. et al. Deep ocean metagenomes provide insight into the metabolic architecture of bathypelagic microbial communities. Commun. Biol. 4, 604 (2021).
pubmed: 34021239 pmcid: 8139981 doi: 10.1038/s42003-021-02112-2
Bochdansky, A. B., Clouse, M. A. & Herndl, G. J. Eukaryotic microbes, principally fungi and labyrinthulomycetes, dominate biomass on bathypelagic marine snow. ISME J. 11, 362–373 (2017).
pubmed: 27648811 doi: 10.1038/ismej.2016.113
Sebastián, M. et al. The quality of dissolved organic matter shapes the biogeography of the active bathypelagic microbiome. bioRxiv 2021.05.14.444136. https://doi.org/10.1101/2021.05.14.444136 (2021).
Pelve, E. A., Fontanez, K. M. & DeLong, E. F. Bacterial succession on sinking particles in the ocean’s interior. Front. Microbiol. 8, 2269 (2017).
pubmed: 29225592 pmcid: 5706468 doi: 10.3389/fmicb.2017.02269
Fath, B. D. et al. Ecological network analysis metrics: the need for an entire ecosystem approach in management and policy. Ocean Coast. Manag. 174, 1–14 (2019).
doi: 10.1016/j.ocecoaman.2019.03.007
Krom, M. D., Kress, N., Brenner, S. & Gordon, L. I. Phosphorus limitation of primary productivity in the eastern Mediterranean Sea. Limnol. Oceanogr. 36, 424–432 (1991).
doi: 10.4319/lo.1991.36.3.0424
Coll, M. et al. The biodiversity of the Mediterranean Sea: estimates, patterns, and threats. PLoS One 5, e11842 (2010).
pubmed: 20689844 pmcid: 2914016 doi: 10.1371/journal.pone.0011842
Danovaro, R. et al. Deep-sea biodiversity in the Mediterranean Sea: the known, the unknown, and the unknowable. PLoS One 5, e11832 (2010).
pubmed: 20689848 pmcid: 2914020 doi: 10.1371/journal.pone.0011832
Haro-Moreno, J. M. et al. Ecogenomics of the SAR11 clade. Environ. Microbiol. 22, 1748–1763 (2020).
pubmed: 31840364 doi: 10.1111/1462-2920.14896
Yakimov, M. M., Cono, V. L. & Denaro, R. A first insight into the occurrence and expression of functional amoA and accA genes of autotrophic and ammonia-oxidizing bathypelagic Crenarchaeota of Tyrrhenian Sea. Deep Sea Res. Part II: Top. Stud. Oceanogr. 56, 748–754 (2009).
doi: 10.1016/j.dsr2.2008.07.024
Logares, R. et al. Phenotypically different microalgal morphospecies with identical ribosomal DNA: a case of rapid adaptive evolution? Micro. Ecol. 53, 549–561 (2007).
doi: 10.1007/s00248-006-9088-y
Větrovský, T. & Baldrian, P. The variability of the 16S rRNA gene in bacterial genomes and its consequences for bacterial community analyses. PLOS One 8, e57923 (2013).
pubmed: 23460914 pmcid: 3583900 doi: 10.1371/journal.pone.0057923
Fortin, M.-J., Dale, M. R. T. & Brimacombe, C. Network ecology in dynamic landscapes. Proc. Biol. Sci. 288, 20201889 (2021).
pubmed: 33906397 pmcid: 8080002
Cavicchioli, R. et al. Scientists’ warning to humanity: microorganisms and climate change. Nat. Rev. Microbiol. 17, 569–586 (2019).
pubmed: 31213707 pmcid: 7136171 doi: 10.1038/s41579-019-0222-5
Redford, K. H. Extending conservation to include Earth’s microbiome. Conserv. Biol. 37, e14088 (2023).
pubmed: 37009683 doi: 10.1111/cobi.14088
Duarte, C. M. Seafaring in the 21St century: the Malaspina 2010 Circumnavigation Expedition. Limnol. Oceanogr. Bull. 24, 11–14 (2015).
doi: 10.1002/lob.10008
Martínez-Pérez, A. M. et al. Molecular composition of dissolved organic matter in the Mediterranean Sea. Limnol. Oceanogr. 62, 2699–2712 (2017).
doi: 10.1002/lno.10600
Pernice, M. C. et al. Large variability of bathypelagic microbial eukaryotic communities across the world’s oceans. ISME J. 10, 945–958 (2016).
pubmed: 26451501 doi: 10.1038/ismej.2015.170
Salazar, G. et al. Global diversity and biogeography of deep-sea pelagic prokaryotes. ISME J. 10, 596–608 (2016).
pubmed: 26251871 doi: 10.1038/ismej.2015.137
Sanz-Sáez, I. et al. Top abundant deep ocean heterotrophic bacteria can be retrieved by cultivation. ISME Commun. 3, 92 (2023).
pubmed: 37660234 pmcid: 10475052 doi: 10.1038/s43705-023-00290-0
Parada, A. E., Needham, D. M. & Fuhrman, J. A. Every base matters: assessing small subunit rRNA primers for marine microbiomes with mock communities, time series and global field samples. Environ. Microbiol. 18, 1403–1414 (2016).
pubmed: 26271760 doi: 10.1111/1462-2920.13023
Stoeck, T. et al. Multiple marker parallel tag environmental DNA sequencing reveals a highly complex eukaryotic community in marine anoxic water. Mol. Ecol. 19, 21–31 (2010).
pubmed: 20331767 doi: 10.1111/j.1365-294X.2009.04480.x
Quast, C. et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 41, D590–D596 (2012).
pubmed: 23193283 pmcid: 3531112 doi: 10.1093/nar/gks1219
Guillou, L. et al. The Protist Ribosomal Reference database (PR
pubmed: 23193267 pmcid: 3531120 doi: 10.1093/nar/gks1160
Boyer, T. P. et al. World Ocean Database 2013. https://doi.org/10.7289/V5NZ85MT (2013).
Gloor, G. B., Macklaim, J. M., Pawlowsky-Glahn, V. & Egozcue, J. J. Microbiome datasets are compositional: and this is not optional. Front. Microbiol. 8, 2224 (2017).
pubmed: 29187837 pmcid: 5695134 doi: 10.3389/fmicb.2017.02224
Deutschmann, I. M. et al. Disentangling environmental effects in microbial association networks. Microbiome 9, 232 (2021).
pubmed: 34823593 pmcid: 8620190 doi: 10.1186/s40168-021-01141-7
Bastian, M., Heymann, S. & Jacomy, M. Gephi: an open source software for exploring and manipulating networks. ICWSM 3, 361–362 (2009).
Fruchterman, T. M. J. & Reingold, E. M. Graph drawing by force-directed placement. Softw. Pract. Exp. 21, 1129–1164 (1991).
doi: 10.1002/spe.4380211102
Csardi, G. & Nepusz, T. The igraph software package for complex network research. Int. J. Complex Syst. 1695, 1–9 (2006).
Espejo, R. et al. Exploiting graphlet decomposition to explain the structure of complex networks: the GHuST framework. Sci. Rep. 10, 12884 (2020).
pubmed: 32732972 pmcid: 7393148 doi: 10.1038/s41598-020-69795-1
Pržulj, N., Corneil, D. G. & Jurisica, I. Modeling interactome: scale-free or geometric? Bioinformatics 20, 3508–3515 (2004).
pubmed: 15284103 doi: 10.1093/bioinformatics/bth436
Yaveroǧlu, Ö. N. et al. Revealing the hidden language of complex networks. Sci. Rep. 4, 4547 (2014).
pubmed: 24686408 pmcid: 3971399 doi: 10.1038/srep04547
Prim, R. C. Shortest connection networks and some generalizations. Bell Syst. Tech. J. 36, 1389–1401 (1957).
doi: 10.1002/j.1538-7305.1957.tb01515.x
McInnes, L., Healy, J., Saul, N. & Grossberger, L. UMAP: uniform manifold approximation and projection. J. Open Source Softw. 3, 861 (2018).
doi: 10.21105/joss.00861
Wickham, H. ggplot2: Elegant Graphics for Data Analysis. (Springer-Verlag New York, 2016).

Auteurs

Ina M Deutschmann (IM)

Institute of Marine Sciences (ICM), CSIC, Barcelona, Spain. ina.m.deutschmann@gmail.com.

Erwan Delage (E)

Nantes Université, CNRS UMR 6004, LS2N, F-44000, Nantes, France.
Research Federation for the study of Global Ocean Systems Ecology and Evolution, FR2022/Tara Oceans GOSEE, Paris, France.

Caterina R Giner (CR)

Institute of Marine Sciences (ICM), CSIC, Barcelona, Spain.

Marta Sebastián (M)

Institute of Marine Sciences (ICM), CSIC, Barcelona, Spain.

Julie Poulain (J)

Génomique Métabolique, Genoscope, Institut François Jacob, CEA, CNRS, Univ Evry, Université Paris-Saclay, Evry, France.

Javier Arístegui (J)

Instituto de Oceanografía y Cambio Global, IOCAG, Universidad de Las Palmas de Gran Canaria, ULPGC, Gran Canaria, Spain.

Carlos M Duarte (CM)

King Abdullah University of Science and Technology (KAUST), Red Sea Research Center (RSRC), Thuwal, Saudi Arabia.

Silvia G Acinas (SG)

Institute of Marine Sciences (ICM), CSIC, Barcelona, Spain.

Ramon Massana (R)

Institute of Marine Sciences (ICM), CSIC, Barcelona, Spain.

Josep M Gasol (JM)

Institute of Marine Sciences (ICM), CSIC, Barcelona, Spain.

Damien Eveillard (D)

Nantes Université, CNRS UMR 6004, LS2N, F-44000, Nantes, France.
Research Federation for the study of Global Ocean Systems Ecology and Evolution, FR2022/Tara Oceans GOSEE, Paris, France.

Samuel Chaffron (S)

Nantes Université, CNRS UMR 6004, LS2N, F-44000, Nantes, France.
Research Federation for the study of Global Ocean Systems Ecology and Evolution, FR2022/Tara Oceans GOSEE, Paris, France.

Ramiro Logares (R)

Institute of Marine Sciences (ICM), CSIC, Barcelona, Spain. ramiro.logares@icm.csic.es.

Classifications MeSH