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5. Ocean-wide comparisons of mesopelagic planktonic community structures

Author

Rigonato, Janaina, Budinich, Marko, Murillo, Alejandro A., Brandão, Manoela C., Pierella Karlusich, Juan J., Soviadan, Yawouvi Dodji, Gregory, Ann C., Endo, Hisashi, Kokoszka, Florian, Vik, Dean, Henry, Nicolas, Frémont, Paul, Labadie, Karine, Zayed, Ahmed A., Dimier, Céline, Picheral, Marc, Searson, Sarah, Poulain, Julie, Kandels, Stefanie, Pesant, Stéphane, Karsenti, Eric, Bork, Peer, Bowler, Chris, de Vargas, Colomban, Eveillard, Damien, Gehlen, Marion, Iudicone, Daniele, Lombard, Fabien, Ogata, Hiroyuki, Stemmann, Lars, Sullivan, Matthew B., Sunagawa, Shinichi, Wincker, Patrick, Chaffron, Samuel, and Jaillon, Olivier

Published
2023
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7. Differential global distribution of marine picocyanobacteria gene clusters reveals distinct niche-related adaptive strategies

Author

Doré, Hugo, Guyet, Ulysse, Leconte, Jade, Farrant, Gregory K., Alric, Benjamin, Ratin, Morgane, Ostrowski, Martin, Ferrieux, Mathilde, Brillet-Guéguen, Loraine, Hoebeke, Mark, Siltanen, Jukka, Le Corguillé, Gildas, Corre, Erwan, Wincker, Patrick, Scanlan, David J., Eveillard, Damien, Partensky, Frédéric, and Garczarek, Laurence

Published
2023
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8. A community perspective on the concept of marine holobionts: state-of-the-art, challenges, and future directions

Author

Dittami, Simon, Arboleda, Enrique, Auguet, Jean-Christophe, Bigalke, Arite, Briand, Enora, Cárdenas, Paco, Cardini, Ulisse, Decelle, Johan, Engelen, Ashwin, Eveillard, Damien, Gachon, Claire, Griffiths, Sarah, Harder, Tilmann, Kayal, Ehsan, Kazamia, Elena, Lallier, François, Medina, Mónica, Marzinelli, Ezequiel, Morganti, Teresa, Pons, Laura, Prado, Soizic, Valverde, José Pintado, Saha, Mahasweta, Selosse, Marc-Andre, Skillings, Derek, Stock, Willem, Sunagawa, Shinichi, Toulza, Eve, Vorobev, Alexey, Leblanc, Catherine, and Not, Fabrice

Subjects
Quantitative Biology - Populations and Evolution
Abstract

Host-microbe interactions play crucial roles in marine ecosystems, but we still have very little understanding of the mechanisms that govern these relationships, the evolutionary processes that shape them, and their ecological consequences. The holobiont concept is a renewed paradigm in biology that can help describe and understand these complex systems. It posits that a host and its associated microbiota, living together in a long-lasting relationship, form the holobiont, and have to be studied together, as a coherent biological and functional unit, in order to understand the biology, ecology and evolution of the organisms. Here we discuss critical concepts and opportunities in marine holobiont research and identify key challenges in the field. We highlight the potential economic, sociological, and environmental impacts of the holobiont concept in marine biological, evolutionary, and environmental sciences with comparisons to terrestrial science whenever appropriate. A deeper understanding of such complex systems, however, will require further technological and conceptual advances. The most significant challenge will be to bridge functional research on simple and tractable model systems and global approaches. This will require scientists to work together as an (inter)active community in order to address, for instance, ecological and evolutionary questions and the roles of holobionts in biogeochemical cycles., Comment: PeerJ Preprints, Computer Science Preprints., 2019

Published
2019
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9. Roadmap for naming uncultivated Archaea and Bacteria

Author

Murray, Alison E, Freudenstein, John, Gribaldo, Simonetta, Hatzenpichler, Roland, Hugenholtz, Philip, Kämpfer, Peter, Konstantinidis, Konstantinos T, Lane, Christopher E, Papke, R Thane, Parks, Donovan H, Rossello-Mora, Ramon, Stott, Matthew B, Sutcliffe, Iain C, Thrash, J Cameron, Venter, Stephanus N, Whitman, William B, Acinas, Silvia G, Amann, Rudolf I, Anantharaman, Karthik, Armengaud, Jean, Baker, Brett J, Barco, Roman A, Bode, Helge B, Boyd, Eric S, Brady, Carrie L, Carini, Paul, Chain, Patrick SG, Colman, Daniel R, DeAngelis, Kristen M, de los Rios, Maria Asuncion, Estrada-de los Santos, Paulina, Dunlap, Christopher A, Eisen, Jonathan A, Emerson, David, Ettema, Thijs JG, Eveillard, Damien, Girguis, Peter R, Hentschel, Ute, Hollibaugh, James T, Hug, Laura A, Inskeep, William P, Ivanova, Elena P, Klenk, Hans-Peter, Li, Wen-Jun, Lloyd, Karen G, Löffler, Frank E, Makhalanyane, Thulani P, Moser, Duane P, Nunoura, Takuro, Palmer, Marike, Parro, Victor, Pedrós-Alió, Carlos, Probst, Alexander J, Smits, Theo HM, Steen, Andrew D, Steenkamp, Emma T, Spang, Anja, Stewart, Frank J, Tiedje, James M, Vandamme, Peter, Wagner, Michael, Wang, Feng-Ping, Yarza, Pablo, Hedlund, Brian P, and Reysenbach, Anna-Louise

Subjects
Microbiology, Biological Sciences, Ecology, Archaea, Bacteria, DNA, Bacterial, Metagenome, Phylogeny, Prokaryotic Cells, Sequence Analysis, DNA, Terminology as Topic, Medical Microbiology
Abstract

The assembly of single-amplified genomes (SAGs) and metagenome-assembled genomes (MAGs) has led to a surge in genome-based discoveries of members affiliated with Archaea and Bacteria, bringing with it a need to develop guidelines for nomenclature of uncultivated microorganisms. The International Code of Nomenclature of Prokaryotes (ICNP) only recognizes cultures as 'type material', thereby preventing the naming of uncultivated organisms. In this Consensus Statement, we propose two potential paths to solve this nomenclatural conundrum. One option is the adoption of previously proposed modifications to the ICNP to recognize DNA sequences as acceptable type material; the other option creates a nomenclatural code for uncultivated Archaea and Bacteria that could eventually be merged with the ICNP in the future. Regardless of the path taken, we believe that action is needed now within the scientific community to develop consistent rules for nomenclature of uncultivated taxa in order to provide clarity and stability, and to effectively communicate microbial diversity.

Published
2020

10. Community‐Level Responses to Iron Availability in Open Ocean Plankton Ecosystems

Author

Caputi, Luigi, Carradec, Quentin, Eveillard, Damien, Kirilovsky, Amos, Pelletier, Eric, Pierella Karlusich, Juan J, Rocha Jimenez Vieira, Fabio, Villar, Emilie, Chaffron, Samuel, Malviya, Shruti, Scalco, Eleonora, Acinas, Silvia G, Alberti, Adriana, Aury, Jean‐Marc, Benoiston, Anne‐Sophie, Bertrand, Alexis, Biard, Tristan, Bittner, Lucie, Boccara, Martine, Brum, Jennifer R, Brunet, Christophe, Busseni, Greta, Carratalà, Anna, Claustre, Hervé, Coelho, Luis Pedro, Colin, Sébastien, D'Aniello, Salvatore, Da Silva, Corinne, Del Core, Marianna, Doré, Hugo, Gasparini, Stéphane, Kokoszka, Florian, Jamet, Jean‐Louis, Lejeusne, Christophe, Lepoivre, Cyrille, Lescot, Magali, Lima‐Mendez, Gipsi, Lombard, Fabien, Lukeš, Julius, Maillet, Nicolas, Madoui, Mohammed‐Amin, Martinez, Elodie, Mazzocchi, Maria Grazia, Néou, Mario B, Paz‐Yepes, Javier, Poulain, Julie, Ramondenc, Simon, Romagnan, Jean‐Baptiste, Roux, Simon, Salvagio Manta, Daniela, Sanges, Remo, Speich, Sabrina, Sprovieri, Mario, Sunagawa, Shinichi, Taillandier, Vincent, Tanaka, Atsuko, Tirichine, Leila, Trottier, Camille, Uitz, Julia, Veluchamy, Alaguraj, Veselá, Jana, Vincent, Flora, Yau, Sheree, Kandels‐Lewis, Stefanie, Searson, Sarah, Dimier, Céline, Picheral, Marc, Bork, Peer, Boss, Emmanuel, Vargas, Colomban, Follows, Michael J, Grimsley, Nigel, Guidi, Lionel, Hingamp, Pascal, Karsenti, Eric, Sordino, Paolo, Stemmann, Lars, Sullivan, Matthew B, Tagliabue, Alessandro, Zingone, Adriana, Garczarek, Laurence, d'Ortenzio, Fabrizio, Testor, Pierre, Not, Fabrice, d'Alcalà, Maurizio Ribera, Wincker, Patrick, Bowler, Chris, Iudicone, Daniele, Gorsky, Gabriel, and Jaillon, Olivier

Subjects
Genetics, Life Below Water, Atmospheric Sciences, Geochemistry, Oceanography, Meteorology & Atmospheric Sciences
Abstract

Predicting responses of plankton to variations in essential nutrients is hampered by limited in situ measurements, a poor understanding of community composition, and the lack of reference gene catalogs for key taxa. Iron is a key driver of plankton dynamics and, therefore, of global biogeochemical cycles and climate. To assess the impact of iron availability on plankton communities, we explored the comprehensive bio-oceanographic and bio-omics data sets from Tara Oceans in the context of the iron products from two state-of-the-art global scale biogeochemical models. We obtained novel information about adaptation and acclimation toward iron in a range of phytoplankton, including picocyanobacteria and diatoms, and identified whole subcommunities covarying with iron. Many of the observed global patterns were recapitulated in the Marquesas archipelago, where frequent plankton blooms are believed to be caused by natural iron fertilization, although they are not captured in large-scale biogeochemical models. This work provides a proof of concept that integrative analyses, spanning from genes to ecosystems and viruses to zooplankton, can disentangle the complexity of plankton communities and can lead to more accurate formulations of resource bioavailability in biogeochemical models, thus improving our understanding of plankton resilience in a changing environment.

Published
2019

11. Probabilistic Modeling of Microbial Metabolic Networks for Integrating Partial Quantitative Knowledge Within the Nitrogen Cycle

Author

Eveillard, Damien, Bouskill, Nicholas J, Vintache, Damien, Gras, Julien, Ward, Bess B, and Bourdon, Jérémie

Subjects
Microbiology, Biological Sciences, modeling, microbial ecology, ammonia oxidizing bacteria, probabilistic simulation, nitrogen, Environmental Science and Management, Soil Sciences, Medical microbiology
Abstract

Understanding the interactions between microbial communities and their environment sufficiently to predict diversity on the basis of physicochemical parameters is a fundamental pursuit of microbial ecology that still eludes us. However, modeling microbial communities is problematic, because (i) communities are complex, (ii) most descriptions are qualitative, and (iii) quantitative understanding of the way communities interact with their surroundings remains incomplete. One approach to overcoming such complications is the integration of partial qualitative and quantitative descriptions into more complex networks. Here we outline the development of a probabilistic framework, based on Event Transition Graph (ETG) theory, to predict microbial community structure across observed chemical data. Using reverse engineering, we derive probabilities from the ETG that accurately represent observations from experiments and predict putative constraints on communities within dynamic environments. These predictions can feedback into the future development of field experiments by emphasizing the most important functional reactions, and associated microbial strains, required to characterize microbial ecosystems.

Published
2019

13. Ecological associations distribution modelling of marine plankton at a global scale.

Author

Gaudin, Marinna, Eveillard, Damien, and Chaffron, Samuel

Subjects
*BIOGEOCHEMICAL cycles, *MARINE plankton, *CLIMATE & biogeography, *STATISTICAL learning, *FOOD chains
Abstract

Marine plankton communities form intricate networks of interacting organisms at the base of the food chain, and play a central role in regulating ocean biogeochemical cycles and climate. However, predicting plankton community shifts in response to climate change remains challenging. While species distribution models are valuable tools for predicting changes in species biogeography under climate change scenarios, they generally overlook the key role of biotic interactions, which can significantly shape ecological processes and ecosystem responses. Here, we introduce a novel statistical framework, association distribution modelling (ADM), designed to model and predict ecological associations distribution in space and time. Applied on a Tara Oceans genome-resolved metagenomics dataset, the present-day biogeography of ADM-inferred marine plankton associations revealed four major biogeographic biomes organized along a latitudinal gradient. We predicted the evolution of these biome-specific communities in response to a climate change scenario, highlighting differential responses to environmental change. Finally, we explored the functional potential of impacted plankton communities, focusing on carbon fixation, outlining the predicted evolution of its geographical distribution and implications for ecosystem function. This article is part of the theme issue 'Connected interactions: enriching food web research by spatial and social interactions'. [ABSTRACT FROM AUTHOR]

Published
2024
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14. Compendium of 530 metagenome-assembled bacterial and archaeal genomes from the polar Arctic Ocean

Author

Royo-Llonch, Marta, Sánchez, Pablo, Ruiz-González, Clara, Salazar, Guillem, Pedrós-Alió, Carlos, Sebastián, Marta, Labadie, Karine, Paoli, Lucas, M. Ibarbalz, Federico, Zinger, Lucie, Churcheward, Benjamin, Chaffron, Samuel, Eveillard, Damien, Karsenti, Eric, Sunagawa, Shinichi, Wincker, Patrick, Karp-Boss, Lee, Bowler, Chris, and Acinas, Silvia G.

Published
2021
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15. Probabilistic Modeling of Microbial Metabolic Networks for Integrating Partial Quantitative Knowledge Within the Nitrogen Cycle.

Author

Eveillard, Damien, Bouskill, Nicholas J, Vintache, Damien, Gras, Julien, Ward, Bess B, and Bourdon, Jérémie

Subjects
ammonia oxidizing bacteria, microbial ecology, modeling, nitrogen, probabilistic simulation, Microbiology, Environmental Science and Management, Soil Sciences
Abstract

Understanding the interactions between microbial communities and their environment sufficiently to predict diversity on the basis of physicochemical parameters is a fundamental pursuit of microbial ecology that still eludes us. However, modeling microbial communities is problematic, because (i) communities are complex, (ii) most descriptions are qualitative, and (iii) quantitative understanding of the way communities interact with their surroundings remains incomplete. One approach to overcoming such complications is the integration of partial qualitative and quantitative descriptions into more complex networks. Here we outline the development of a probabilistic framework, based on Event Transition Graph (ETG) theory, to predict microbial community structure across observed chemical data. Using reverse engineering, we derive probabilities from the ETG that accurately represent observations from experiments and predict putative constraints on communities within dynamic environments. These predictions can feedback into the future development of field experiments by emphasizing the most important functional reactions, and associated microbial strains, required to characterize microbial ecosystems.

Published
2018

16. On the Power of Uncertainties in Microbial System Modeling: No Need To Hide Them Anymore

Author

Delahaye, Benoit, Eveillard, Damien, and Bouskill, Nicholas

Subjects
Theory Of Computation, Information and Computing Sciences, Biological Sciences, modeling, simulation, uncertainty
Abstract

For decades, microbiologists have considered uncertainties as an undesired side effect of experimental protocols. As a consequence, standard microbial system modeling strives to hide uncertainties for the sake of deterministic understanding. However, recent studies have highlighted greater experimental variability than expected and emphasized uncertainties not as a weakness but as a necessary feature of complex microbial systems. We therefore advocate that biological uncertainties need to be considered foundational facets that must be incorporated in models. Not only will understanding these uncertainties improve our understanding and identification of microbial traits, it will also provide fundamental insights on microbial systems as a whole. Taking into account uncertainties within microbial models calls for new validation techniques. Formal verification already overcomes this shortcoming by proposing modeling frameworks and validation techniques dedicated to probabilistic models. However, further work remains to extract the full potential of such techniques in the context of microbial models. Herein, we demonstrate how statistical model checking can enhance the development of microbial models by building confidence in the estimation of critical parameters and through improved sensitivity analyses.

Published
2017

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

Author

Ministerio de Economía y Competitividad (España), Ministerio de Ciencia e Innovación (España), European Commission, Agencia Estatal de Investigación (España), Deutschmann, Ina, Delage, Erwan, Giner, Caterina R., Sebastián, Marta, Poulain, Julie, Arístegui, Javier, Duarte, Carlos M., Acinas, Silvia G., Massana, Ramon, Gasol, Josep M., Eveillard, Damien, Chaffron, Samuel, Logares, Ramiro, Ministerio de Economía y Competitividad (España), Ministerio de Ciencia e Innovación (España), European Commission, Agencia Estatal de Investigación (España), Deutschmann, Ina, Delage, Erwan, Giner, Caterina R., Sebastián, Marta, Poulain, Julie, Arístegui, Javier, Duarte, Carlos M., Acinas, Silvia G., Massana, Ramon, Gasol, Josep M., Eveillard, Damien, Chaffron, Samuel, and Logares, Ramiro

Abstract

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

Published
2024

18. Plankton networks driving carbon export in the oligotrophic ocean

Author

Guidi, Lionel, Chaffron, Samuel, Bittner, Lucie, Eveillard, Damien, Larhlimi, Abdelhalim, Roux, Simon, Darzi, Youssef, Audic, Stephane, Berline, Léo, Brum, Jennifer R, Coelho, Luis Pedro, Espinoza, Julio Cesar Ignacio, Malviya, Shruti, Sunagawa, Shinichi, Dimier, Céline, Kandels-Lewis, Stefanie, Picheral, Marc, Poulain, Julie, Searson, Sarah, Stemmann, Lars, Not, Fabrice, Hingamp, Pascal, Speich, Sabrina, Follows, Mick, Karp-Boss, Lee, Boss, Emmanuel, Ogata, Hiroyuki, Pesant, Stephane, Weissenbach, Jean, Wincker, Patrick, Acinas, Silvia G, Bork, Peer, de Vargas, Colomban, Iudicone, Daniele, Sullivan, Matthew B, Raes, Jeroen, Karsenti, Eric, Bowler, Chris, and Gorsky, Gabriel

Subjects
Aquatic Organisms, Carbon, Chlorophyll, Dinoflagellida, Ecosystem, Expeditions, Genes, Bacterial, Genes, Viral, Geography, Oceans and Seas, Photosynthesis, Plankton, Seawater, Synechococcus, Tara Oceans coordinators, General Science & Technology
Abstract

The biological carbon pump is the process by which CO2 is transformed to organic carbon via photosynthesis, exported through sinking particles, and finally sequestered in the deep ocean. While the intensity of the pump correlates with plankton community composition, the underlying ecosystem structure driving the process remains largely uncharacterized. Here we use environmental and metagenomic data gathered during the Tara Oceans expedition to improve our understanding of carbon export in the oligotrophic ocean. We show that specific plankton communities, from the surface and deep chlorophyll maximum, correlate with carbon export at 150 m and highlight unexpected taxa such as Radiolaria and alveolate parasites, as well as Synechococcus and their phages, as lineages most strongly associated with carbon export in the subtropical, nutrient-depleted, oligotrophic ocean. Additionally, we show that the relative abundance of a few bacterial and viral genes can predict a significant fraction of the variability in carbon export in these regions.

Published
2016

21. Tara Oceans: towards global ocean ecosystems biology

Author

Sunagawa, Shinichi, Acinas, Silvia G., Bork, Peer, Bowler, Chris, Eveillard, Damien, Gorsky, Gabriel, Guidi, Lionel, Iudicone, Daniele, Karsenti, Eric, Lombard, Fabien, Ogata, Hiroyuki, Pesant, Stephane, Sullivan, Matthew B., Wincker, Patrick, and de Vargas, Colomban

Published
2020
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23. Towards modeling genome-scale knowledge in the global ocean

Author

Regimbeau, Antoine, primary, Aumont, Olivier, additional, Bowler, Chris, additional, Guidi, Lionel, additional, Jackson, George A, additional, Karsenti, Eric, additional, Memery, Laurent, additional, Tagliabue, Alessandro, additional, and Eveillard, Damien, additional

Published
2023
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26. Integrating heterogeneous knowledges for understanding biological behaviors: a probabilistic approach

Author

Bourdon, Jérémie, Eveillard, Damien, Gabillard, Samuel, and Merle, Theo

Subjects
Quantitative Biology - Quantitative Methods
Abstract

Despite recent molecular technique improvements, biological knowledge remains incomplete. Reasoning on living systems hence implies to integrate heterogeneous and partial informations. Although current investigations successfully focus on qualitative behaviors of macromolecular networks, others approaches show partial quantitative informations like protein concentration variations over times. We consider that both informations, qualitative and quantitative, have to be combined into a modeling method to provide a better understanding of the biological system. We propose here such a method using a probabilistic-like approach. After its exhaustive description, we illustrate its advantages by modeling the carbon starvation response in Escherichia coli. In this purpose, we build an original qualitative model based on available observations. After the formal verification of its qualitative properties, the probabilistic model shows quantitative results corresponding to biological expectations which confirm the interest of our probabilistic approach., Comment: 10 pages

Published
2007

27. Toll Based Measures for Dynamical Graphs

Author

Bourdon, Jérémie and Eveillard, Damien

Subjects
Quantitative Biology - Quantitative Methods, Mathematics - Probability
Abstract

Biological networks are one of the most studied object in computational biology. Several methods have been developed for studying qualitative properties of biological networks. Last decade had seen the improvement of molecular techniques that make quantitative analyses reachable. One of the major biological modelling goals is therefore to deal with the quantitative aspect of biological graphs. We propose a probabilistic model that suits with this quantitative aspects. Our model combines graph with several dynamical sources. It emphazises various asymptotic statistical properties that might be useful for giving biological insights, Comment: 11 pages

Published
2007

29. AtlantECO deliverable D5.2 Report on the All-Atlantic interactome

Author

Chaffron, Samuel, Eveillard, Damien, Gaudin, Marinna, and Regimbeau, Antoine

Abstract

The main goals of WP5 for Advances in Systems Ecology are to develop cutting-edge network analysis methods, to define an all-Atlantic interactome and ecological niches, and to provide indicators of ecosystem stability and sensitivity to environmental stressors and drivers. The main goal of D5.2, associated with Task 5.2, was to deliver a report on the all-Atlantic interactome by constructing cross-kingdom interaction networks for marine microbiome and plastisphere communities. In this task, we examined the (functional) community organisation of microbiomes and the plastisphere at the scale of the global ocean, using metabarcodes, metagenomes, and metatranscriptomes, and specific traits such as genome size and metabolic potential. In particular, we resolved the global-ocean cross-kingdom interactome of viruses, prokaryotes, and eukaryotes, that is, the viral-host interactome, a crucial regulator of carbon fluxes and plankton community dynamics. We also investigated the diversity and community structure in the North Pacific gyre and the Mediterranean Sea to reveal a niche partitioning of plastics-associated microbial communities. In addition, we leveraged metagenomes and metatranscriptomes into a computational workflow to reconstruct the community metabolic landscape and phenotypes of global ocean microbiomes and demonstrate how they can be used to estimate ecosystem-scale marine biogeochemistry. Finally, we also developed a computational framework, integrating metagenomic and metatranscriptomic information at the genome-scale through ecological and metabolic modelling to improve our functional and mechanistic understanding of microbial interactions driving ecosystem functionsin situ.

Published
2023
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31. Disentangling temporal associations in marine microbial networks

Author

European Commission, Ministerio de Economía y Competitividad (España), Agencia Estatal de Investigación (España), Ministerio de Ciencia, Innovación y Universidades (España), Centre National de la Recherche Scientifique (France), Deutschmann, Ina, Krabberød, Anders K., Latorre, Fran, Delage, Erwan, Marrasé, Cèlia, Balagué, Vanessa, Gasol, Josep M., Massana, Ramon, Eveillard, Damien, Chaffron, Samuel, Logares, Ramiro, European Commission, Ministerio de Economía y Competitividad (España), Agencia Estatal de Investigación (España), Ministerio de Ciencia, Innovación y Universidades (España), Centre National de la Recherche Scientifique (France), Deutschmann, Ina, Krabberød, Anders K., Latorre, Fran, Delage, Erwan, Marrasé, Cèlia, Balagué, Vanessa, Gasol, Josep M., Massana, Ramon, Eveillard, Damien, Chaffron, Samuel, and Logares, Ramiro

Abstract

Background: Microbial interactions are fundamental for Earth’s ecosystem functioning and biogeochemical cycling. Nevertheless, they are challenging to identify and remain barely known. Omics-based censuses are helpful in predicting microbial interactions through the statistical inference of single (static) association networks. Yet, microbial interactions are dynamic and we have limited knowledge of how they change over time. Here, we investigate the dynamics of microbial associations in a 10-year marine time series in the Mediterranean Sea using an approach inferring a time-resolved (temporal) network from a single static network. Results: A single static network including microbial eukaryotes and bacteria was built using metabarcoding data derived from 120 monthly samples. For the decade, we aimed to identify persistent, seasonal, and temporary microbial associations by determining a temporal network that captures the interactome of each individual sample. We found that the temporal network appears to follow an annual cycle, collapsing, and reassembling when transiting between colder and warmer waters. We observed higher association repeatability in colder than in warmer months. Only 16 associations could be validated using observations reported in literature, underlining our knowledge gap in marine microbial ecological interactions. Conclusions: Our results indicate that marine microbial associations follow recurrent temporal dynamics in temperate zones, which need to be accounted for to better understand the functioning of the ocean microbiome. The constructed marine temporal network may serve as a resource for testing season-specific microbial interaction hypotheses. The applied approach can be transferred to microbiome studies in other ecosystems

Published
2023

32. Ocean-wide comparisons of mesopelagic planktonic community structures

Author

Fonds Français pour l'Environnement Mondial, Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Brasil), European Commission, Centre National de la Recherche Scientifique (France), European Molecular Biology Laboratory, Ministère de la Recherche et des Technologies (France), Agencia Estatal de Investigación (España), Rigonato, Janaina, Budinich, Marko, Murillo, Alejandro A., Brandão, Manoela C., Pierella Karlusich, Juan J., Soviadan, Yawouvi Dodji, Gregory, Ann C., Endo, Hisashi, Kokoszka, Florian, Vik, Dean, Henry, Nicolas, Frémont, Paul, Labadie, Karine, Zayed, Ahmed A., Dimier, Céline, Picheral, Marc, Searson, Sarah, Poulain, Julie, Kandels‐Lewis, Stefanie, Pesant, Stéphane, Karsenti, Eric, Tara Oceans Coordinators, Acinas, Silvia G., Bork, Peer, Bowler, Chris, Vargas, Colomban de, Eveillard, Damien, Gehlen, Marion, Iudicone, Daniele, Lombard, Fabien, Ogata, Hiroyuki, Stemmann, Lars, Sullivan, Matthew B., Sunagawa, Shinichi, Wincker, Patrick, Chaffron, Samuel, Jaillon, Olivier, Fonds Français pour l'Environnement Mondial, Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Brasil), European Commission, Centre National de la Recherche Scientifique (France), European Molecular Biology Laboratory, Ministère de la Recherche et des Technologies (France), Agencia Estatal de Investigación (España), Rigonato, Janaina, Budinich, Marko, Murillo, Alejandro A., Brandão, Manoela C., Pierella Karlusich, Juan J., Soviadan, Yawouvi Dodji, Gregory, Ann C., Endo, Hisashi, Kokoszka, Florian, Vik, Dean, Henry, Nicolas, Frémont, Paul, Labadie, Karine, Zayed, Ahmed A., Dimier, Céline, Picheral, Marc, Searson, Sarah, Poulain, Julie, Kandels‐Lewis, Stefanie, Pesant, Stéphane, Karsenti, Eric, Tara Oceans Coordinators, Acinas, Silvia G., Bork, Peer, Bowler, Chris, Vargas, Colomban de, Eveillard, Damien, Gehlen, Marion, Iudicone, Daniele, Lombard, Fabien, Ogata, Hiroyuki, Stemmann, Lars, Sullivan, Matthew B., Sunagawa, Shinichi, Wincker, Patrick, Chaffron, Samuel, and Jaillon, Olivier

Abstract

For decades, marine plankton have been investigated for their capacity to modulate biogeochemical cycles and provide fishery resources. Between the sunlit (epipelagic) layer and the deep dark waters, lies a vast and heterogeneous part of the ocean: the mesopelagic zone. How plankton composition is shaped by environment has been well-explored in the epipelagic but much less in the mesopelagic ocean. Here, we conducted comparative analyses of trans-kingdom community assemblages thriving in the mesopelagic oxygen minimum zone (OMZ), mesopelagic oxic, and their epipelagic counterparts. We identified nine distinct types of intermediate water masses that correlate with variation in mesopelagic community composition. Furthermore, oxygen, NO3− and particle flux together appeared as the main drivers governing these communities. Novel taxonomic signatures emerged from OMZ while a global co-occurrence network analysis showed that about 70% of the abundance of mesopelagic plankton groups is organized into three community modules. One module gathers prokaryotes, pico-eukaryotes and Nucleo-Cytoplasmic Large DNA Viruses (NCLDV) from oxic regions, and the two other modules are enriched in OMZ prokaryotes and OMZ pico-eukaryotes, respectively. We hypothesize that OMZ conditions led to a diversification of ecological niches, and thus communities, due to selective pressure from limited resources. Our study further clarifies the interplay between environmental factors in the mesopelagic oxic and OMZ, and the compositional features of communities

Published
2023

33. AtlantECO Deliverable 2.1: AtlantECO-BASE1

Author

Vogt, Meike, Sarmento, Hugo, Benedetti, Fabio, Huber, Paula, Arboleda-Baena, Clara, Bader, Ruby Rose, Eriksson, Dominic, Knecht, Nielja, Chénier, Noémy, Jaillon, Olivier, Frémont, Paul, Lombard, Fabien, Guidi, Lionel, Ricour, Florian, Van Sebille, Erik, Schmiz, Sophie, Manral, Darshika, Clerc, Corentin, Santos, Gleice, Maiorano, Luigi, De Angelis, Daniele, Chaffron, Samuel, Eveillard, Damien, Amaral-Zettler, Linda, Gehlen, Marion, Benard, Germain, and Frölicher, Thomas

Subjects
marine plankton data, plastisphere observations, microplastics observations, optical imaging observations, omics observations, traditional microscopy observations, carbon flux data observations
Abstract

This deliverable reports on Task 2.2 ‘Assembly of observations about microbiomes, plastics, the plastisphere and carbon fluxes’. It used protocols established in task 2.1 ‘Definition of common standards for the assembly of spatially explicit data’ to compile, quality-control and grid existing high-quality observations into a knowledge base of observations (D2.1). Data included into AtlantECO-BASE1 consisted of contributions from the five following data sources and tasks: Task 2.2.1 ‘Microbiome data from traditional microscopy (presence-absence, abundance and biomass)’, Task 2.2.2 ‘Microbiome data from state-of-the-art optical/imaging analysis’, Task 2.2.3 ‘Microbiome and plastisphere data from state-of-the-art genetic analyses’, Task 2.2.4 ‘Nano-, micro and macroplastics data from state-of-the-art sampling methods’, and Task 2.2.5 ‘Carbon flux data from estimated from high resolution bio-optical sensors’. Additional data contributions and mapping efforts from other partners and work packages (Task 2.3) are also included. A comprehensive list and description of all data sets collected can be found in the Appendix Tables to this document.

Published
2023
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34. Author Correction: Roadmap for naming uncultivated Archaea and Bacteria

Author

Murray, Alison E., Freudenstein, John, Gribaldo, Simonetta, Hatzenpichler, Roland, Hugenholtz, Philip, Kämpfer, Peter, Konstantinidis, Konstantinos T., Lane, Christopher E., Papke, R. Thane, Parks, Donovan H., Rossello-Mora, Ramon, Stott, Matthew B., Sutcliffe, Iain C., Thrash, J. Cameron, Venter, Stephanus N., Whitman, William B., Acinas, Silvia G., Amann, Rudolf I., Anantharaman, Karthik, Armengaud, Jean, Baker, Brett J., Barco, Roman A., Bode, Helge B., Boyd, Eric S., Brady, Carrie L., Carini, Paul, Chain, Patrick S. G., Colman, Daniel R., DeAngelis, Kristen M., de los Rios, Maria Asuncion, Estrada-de los Santos, Paulina, Dunlap, Christopher A., Eisen, Jonathan A., Emerson, David, Ettema, Thijs J. G., Eveillard, Damien, Girguis, Peter R., Hentschel, Ute, Hollibaugh, James T., Hug, Laura A., Inskeep, William P., Ivanova, Elena P., Klenk, Hans-Peter, Li, Wen-Jun, Lloyd, Karen G., Löffler, Frank E., Makhalanyane, Thulani P., Moser, Duane P., Nunoura, Takuro, Palmer, Marike, Parro, Victor, Pedrós-Alió, Carlos, Probst, Alexander J., Smits, Theo H. M., Steen, Andrew D., Steenkamp, Emma T., Spang, Anja, Stewart, Frank J., Tiedje, James M., Vandamme, Peter, Wagner, Michael, Wang, Feng-Ping, Yarza, Pablo, Hedlund, Brian P., and Reysenbach, Anna-Louise

Published
2021
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36. Predictive ecology in a changing world

Author

Mouquet, Nicolas, Lagadeuc, Yvan, Devictor, Vincent, Doyen, Luc, Duputié, Anne, Eveillard, Damien, Faure, Denis, Garnier, Eric, Gimenez, Olivier, Huneman, Philippe, Jabot, Franck, Jarne, Philippe, Joly, Dominique, Julliard, Romain, Kéfi, Sonia, Kergoat, Gael J., Lavorel, Sandra, Le Gall, Line, Meslin, Laurence, Morand, Serge, Morin, Xavier, Morlon, Hélène, Pinay, Gilles, Pradel, Roger, Schurr, Frank M., Thuiller, Wilfried, and Loreau, Michel

Published
2015

37. An ASP Application in Integrative Biology: Identification of Functional Gene Units

Author

Bordron, Philippe, Eveillard, Damien, Maass, Alejandro, Siegel, Anne, Thiele, Sven, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Goebel, Randy, editor, Siekmann, Jörg, editor, Wahlster, Wolfgang, editor, Cabalar, Pedro, editor, and Son, Tran Cao, editor

Published
2013
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38. Extending the Metabolic Network of Ectocarpus Siliculosus Using Answer Set Programming

Author

Collet, Guillaume, Eveillard, Damien, Gebser, Martin, Prigent, Sylvain, Schaub, Torsten, Siegel, Anne, Thiele, Sven, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Goebel, Randy, editor, Siekmann, Jörg, editor, Wahlster, Wolfgang, editor, Cabalar, Pedro, editor, and Son, Tran Cao, editor

Published
2013
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39. Including Ordinary Differential Equations Based Constraints in the Standard CP Framework

Author

Goldsztejn, Alexandre, Mullier, Olivier, Eveillard, Damien, Hosobe, Hiroshi, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, and Cohen, David, editor

Published
2010
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40. Comparing Bacterial Genomes by Searching Their Common Intervals

Author

Angibaud, Sébastien, Eveillard, Damien, Fertin, Guillaume, Rusu, Irena, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Istrail, Sorin, editor, Pevzner, Pavel, editor, Waterman, Michael S., editor, and Rajasekaran, Sanguthevar, editor

Published
2009
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41. Genomic evidence for global ocean plankton biogeography shaped by large-scale current systems

Author

Richter, Daniel J., Watteaux, Romain, Vannier, Thomas, Leconte, Jade, Frémont, Paul, Reygondeau, Gabriel, Maillet, Nicolas, Henry, Nicolas, Benoit, Gaëtan, da Silva, Ophélie, Delmont, Tom O., Fernández-Guerra, Antonio, Suweis, Samir, Narci, Romain, Berney, Cedric, Eveillard, Damien, Gavory, Frederick, Guidi, Lionel, Labadie, Karine, Mahieu, Eric, Poulain, Julie, Romac, Sarah, Roux, Simon, Dimier, Céline, Kandels‐Lewis, Stefanie, Picheral, Marc, Searson, Sarah, Oceans, Tara, Pesant, Stéphane, Aury, Jean-Marc, Brum, Jennifer R., Lemaitre, Claire, Pelletier, Eric, Bork, Peer, Sunagawa, Shinichi, Lombard, Fabien, Karp-Boss, Lee, Bowler, Chris, Sullivan, Matthew B., Karsenti, Eric, Mariadassou, Mahendra, Probert, Ian, Peterlongo, Pierre, Wincker, Patrick, Vargas, Colomban de, Ribera d’Alcalà, Maurizio, Iudicone, Daniele, Jaillon, Olivier, Tara Oceans Coordinators, Centre National de la Recherche Scientifique (France), European Molecular Biology Laboratory, Centre National de Séquençage (France), National Fund for Scientific Research (Belgium), Stazione Zoologica Anton Dohrn, Università degli Studi di Milano, Université Paris Sciences & Lettres, Agence Nationale de la Recherche (France), National Science Foundation (US), Veolia Foundation, Région Bretagne, World Courier, Illumina, Cap L’Orient, Fondation EDF, Fondation pour la Recherche sur la Biodiversité, Fondation Prince Albert II de Monaco, Ministère de l'Europe et des Affaires étrangères (France), Adaptation et diversité en milieu marin (ADMM), Institut national des sciences de l'Univers (INSU - CNRS)-Station biologique de Roscoff (SBR), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Stazione Zoologica Anton Dohrn (SZN), Institut méditerranéen d'océanologie (MIO), Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS), Institut de Génomique d'Evry (IG), Université Paris-Saclay-Institut de Biologie François JACOB (JACOB), Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Genoscope - Centre national de séquençage [Evry] (GENOSCOPE), Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), University of British Columbia (UBC), Hub Bioinformatique et Biostatistique - Bioinformatics and Biostatistics HUB, Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Max Planck Institute for Marine Microbiology, Max-Planck-Gesellschaft, Dipartimento di Fisica e Astronomia 'Galileo Galilei', Università degli Studi di Padova = University of Padua (Unipd), Consorzio Nazionale Interuniversitario per le Scienze FIsiche della Materia (CNISM), Mathématiques et Informatique Appliquées du Génome à l'Environnement [Jouy-En-Josas] (MaIAGE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Station biologique de Roscoff (SBR), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Laboratoire des Sciences du Numérique de Nantes (LS2N), Université de Nantes - UFR des Sciences et des Techniques (UN UFR ST), Université de Nantes (UN)-Université de Nantes (UN)-École Centrale de Nantes (ECN)-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Combinatoire et Bioinformatique (LS2N - équipe COMBI), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Nantes - UFR des Sciences et des Techniques (UN UFR ST), Laboratoire d'océanographie de Villefranche (LOV), Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV), Institut de Biologie François JACOB (JACOB), Ohio State University [Columbus] (OSU), Institut de biologie de l'ENS Paris (IBENS), Département de Biologie - ENS Paris, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Center for Marine Environmental Sciences [Bremen] (MARUM), Universität Bremen, Ecology and Evolutionary Biology [Tucson] (EEB), University of Arizona, Scalable, Optimized and Parallel Algorithms for Genomics (GenScale), Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-GESTION DES DONNÉES ET DE LA CONNAISSANCE (IRISA-D7), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes 1 (UR1), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), European Molecular Biology Laboratory [Heidelberg] (EMBL), University of Maine, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), Fédération de recherche de Roscoff (FR2424), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), French National Research Agency (ANR)HYDROGEN/ANR-14CE23-0001, National Science Foundation (NSF)OCE-1536989, OCE-1829831, Commissariat a l'Energie Atomique et aux Energies Alternatives, Graphene Flagship, European Project: 634486,H2020,H2020-BG-2014-2,INMARE(2015), European Project: 287589,EC:FP7:KBBE,FP7-OCEAN-2011,MICRO B3(2012), Adaptation et diversité en milieu marin (AD2M), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Universita degli Studi di Padova, Université de Nantes (UN)-Université de Nantes (UN)-École Centrale de Nantes (ECN)-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Combinatoire et Bioinformatique (COMBI), Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Département de Biologie - ENS Paris, École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Centre National de la Recherche Scientifique (CNRS)-Station biologique de Roscoff (SBR), Centre de Mathématiques et de Leurs Applications (CMLA), École normale supérieure - Cachan (ENS Cachan)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Université de Toulon (UTLN)-Aix Marseille Université (AMU)-Institut de Recherche pour le Développement (IRD), Centre National de la Recherche Scientifique (CNRS)-Institut Pasteur [Paris], Infectiologie Santé Publique (ISP-311), Institut National de la Recherche Agronomique (INRA)-Université de Tours, Institut Pprime (PPRIME), Université de Poitiers-ENSMA-Centre National de la Recherche Scientifique (CNRS), Institut National de la Recherche Agronomique (INRA), Laboratoire d'Informatique de Nantes Atlantique (LINA), Mines Nantes (Mines Nantes)-Université de Nantes (UN)-Centre National de la Recherche Scientifique (CNRS), Institut de biologie de l'ENS Paris (UMR 8197/1024) (IBENS), École normale supérieure - Paris (ENS Paris)-École normale supérieure - Paris (ENS Paris)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Université de Bretagne Sud (UBS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National de Recherche en Informatique et en Automatique (Inria)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-CentraleSupélec-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Université de Nantes (UN)-Université de Nantes (UN)-École Centrale de Nantes (ECN)-Centre National de la Recherche Scientifique (CNRS), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Bretagne Sud (UBS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), and Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1)

Subjects
010504 meteorology & atmospheric sciences, Biogeography, Oceans and Seas, Context (language use), 01 natural sciences, General Biochemistry, Genetics and Molecular Biology, 03 medical and health sciences, plankton biogeography, genomics, Ecosystem, genetics, 14. Life underwater, microbial oceanography, 030304 developmental biology, 0105 earth and related environmental sciences, Seascape, [SDV.EE]Life Sciences [q-bio]/Ecology, environment, 0303 health sciences, metagenomics, General Immunology and Microbiology, Geography, General Neuroscience, Ocean current, fungi, Community structure, General Medicine, 15. Life on land, Plankton, Oceanography, 13. Climate action, Metagenomics, metabarcoding, ecology, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM]
Abstract

Biogeographical studies have traditionally focused on readily visible organisms, but recent technological advances are enabling analyses of the large-scale distribution of microscopic organisms, whose biogeographical patterns have long been debated. Here we assessed the global structure of plankton geography and its relation to the biological, chemical, and physical context of the ocean (the ‘seascape’) by analyzing metagenomes of plankton communities sampled across oceans during the Tara Oceans expedition, in light of environmental data and ocean current transport. Using a consistent approach across organismal sizes that provides unprecedented resolution to measure changes in genomic composition between communities, we report a pan-ocean, size-dependent plankton biogeography overlying regional heterogeneity. We found robust evidence for a basin-scale impact of transport by ocean currents on plankton biogeography, and on a characteristic timescale of community dynamics going beyond simple seasonality or life history transitions of plankton., We thank the commitment of the following people and sponsors who made this expedition possible: CNRS (in particular Groupement de Recherche GDR3280), European Molecular Biology Laboratory (EMBL), Genoscope/CEA, Fund for Scientific Research – Flanders, VIB, Stazione Zoologica Anton Dohrn, UNIMIB, Paris Sciences et Lettres (PSL) Research University (ANR-11-IDEX-0001–02), the French Government ANR (projects FRANCE GENOMIQUE/ANR-10-INBS-09, MEMO LIFE/ANR-10-LABX-54, POSEIDON/ANR-09-BLAN-0348, PROMETHEUS/ANR-09-PCS-GENM-217, MAPPI/ANR-2010-COSI-004, TARA-GIRUS/ANR-09-PCS-GENM-218), US NSF grant DEB-1031049, FWO, BIO5, Biosphere 2, Agnès b., the Veolia Environment Foundation, Région Bretagne, World Courier, Illumina, Cap L’Orient, the EDF Foundation EDF Diversiterre, FRB, the Prince Albert II de Monaco Foundation, Etienne Bourgois, the Tara schooner and its captain and crew. We thank MERCATOR-CORIOLIS and ACRI-ST for providing daily satellite data during the expedition. The bulk of genomic computations were performed using the Airain HPC machine provided through GENCI- [TGCC/CINES/IDRIS] (grants t2011076389, t2012076389, t2013036389, t2014036389, t2015036389 and t2016036389). We are also grateful to the French Ministry of Foreign Affairs for supporting the expedition and to the countries who granted us sampling permissions.

Published
2022

42. Diversity and ecological footprint of Global Ocean RNA viruses

Author

Dominguez-Huerta, Guillermo, Zayed, Ahmed, Wainaina, James, Guo, Jiarong, Tian, Funing, Pratama, Akbar Adjie, Bolduc, Benjamin, Mohssen, Mohamed, Zablocki, Olivier, Pelletier, Eric, Delage, Erwan, Alberti, Adriana, Aury, Jean-Marc, Carradec, Quentin, da Silva, Corinne, Labadie, Karine, Poulain, Julie, Bowler, Chris, Eveillard, Damien, Guidi, Lionel, Karsenti, Eric, Kuhn, Jens, Ogata, Hiroyuki, Wincker, Patrick, Culley, Alexander, Chaffron, Samuel, Sullivan, Matthew, Department of Microbiology [Columbus], Ohio State University [Columbus] (OSU), Global Oceans Systems Ecology & Evolution - Tara Oceans (GOSEE), Université de Perpignan Via Domitia (UPVD)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Aix Marseille Université (AMU)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université d'Évry-Val-d'Essonne (UEVE)-Université de Toulon (UTLN)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut de Recherche pour le Développement (IRD [France-Nord])-Ecole Normale Supérieure Paris-Saclay (ENS Paris Saclay)-European Molecular Biology Laboratory (EMBL)-École Centrale de Nantes (Nantes Univ - ECN), Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ)-Université australe du Chili, Génomique métabolique (UMR 8030), Genoscope - Centre national de séquençage [Evry] (GENOSCOPE), Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université d'Évry-Val-d'Essonne (UEVE)-Centre National de la Recherche Scientifique (CNRS), Laboratoire des Sciences du Numérique de Nantes (LS2N), Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-École Centrale de Nantes (Nantes Univ - ECN), Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ)-Nantes université - UFR des Sciences et des Techniques (Nantes univ - UFR ST), Nantes Université - pôle Sciences et technologie, Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ)-Nantes Université - pôle Sciences et technologie, Nantes Université (Nantes Univ), Institut de biologie de l'ENS Paris (IBENS), Département de Biologie - ENS Paris, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Combinatoire et Bioinformatique (LS2N - équipe COMBI), Nantes Université (Nantes Univ)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Laboratoire d'océanographie de Villefranche (LOV), Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Integrated Research Facility at Fort Detrick (IRF-Frederick), National Institute of Allergy and Infectious Diseases [Bethesda] (NIAID-NIH), National Institutes of Health [Bethesda] (NIH)-National Institutes of Health [Bethesda] (NIH), Institute for Chemical Research, Kyoto University, Département de Biochimie, de Microbiologie et de Bio-informatique, Université Laval, Université Laval [Québec] (ULaval), and Department of Civil, Environmental and Geodetic Engineering [Columbus]

Subjects
Multidisciplinary, Virome, Oceans and Seas, [SDV.BBM.MN]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Molecular Networks [q-bio.MN], Plankton, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], Carbon Cycle, [SDV.EE.ECO]Life Sciences [q-bio]/Ecology, environment/Ecosystems, [SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN], RNA Viruses, Seawater, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, Ecosystem, [SDV.EE.IEO]Life Sciences [q-bio]/Ecology, environment/Symbiosis
Abstract

International audience; DNA viruses are increasingly recognized as influencing marine microbes and microbe-mediated biogeochemical cycling. However, little is known about global marine RNA virus diversity, ecology, and ecosystem roles. In this study, we uncover patterns and predictors of marine RNA virus community- and “species”-level diversity and contextualize their ecological impacts from pole to pole. Our analyses revealed four ecological zones, latitudinal and depth diversity patterns, and environmental correlates for RNA viruses. Our findings only partially parallel those of cosampled plankton and show unexpectedly high polar ecological interactions. The influence of RNA viruses on ecosystems appears to be large, as predicted hosts are ecologically important. Moreover, the occurrence of auxiliary metabolic genes indicates that RNA viruses cause reprogramming of diverse host metabolisms, including photosynthesis and carbon cycling, and that RNA virus abundances predict ocean carbon export.

Published
2022

43. Differential global distribution of marine picocyanobacteria gene clusters reveals distinct niche-related adaptive strategies

Author

Doré, Hugo, primary, Guyet, Ulysse, additional, Leconte, Jade, additional, Farrant, Gregory K., additional, Alric, Benjamin, additional, Ratin, Morgane, additional, Ostrowski, Martin, additional, Ferrieux, Mathilde, additional, Brillet-Guéguen, Loraine, additional, Hoebeke, Mark, additional, Siltanen, Jukka, additional, Corguillé, Gildas Le, additional, Corre, Erwan, additional, Wincker, Patrick, additional, Scanlan, David J., additional, Eveillard, Damien, additional, Partensky, Frédéric, additional, and Garczarek, Laurence, additional

Published
2022
Full Text
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45. AtlantECO deliverable 5.1- Reference catalogue of network reconstruction methods

Author

Budinich Marko, Eveillard Damien, and Chaffron Samuel

Abstract

The main computational goals of WP5 for Advances in Systems Ecology are to develop cutting edge network analysis methods, to define an all-Atlantic interactome and ecological niches, and to provide indicators of ecosystem stability and sensitivity to environmental stressors and drivers. Here, we reviewed the literature for ecological network reconstruction methods from several disciplines (microbiology, ecology, bioinformatics). We built a computational pipeline for the inference of species ecological networks from heterogeneous data types, combining statistical and ecological metrics, as well as probabilistic and machine learning algorithms. Reference databases of known ecological interactions obtained from the literature can be used to benchmark and validate inferred networks. This review of network inference algorithms is accompanied by a computational workflow:AtlantEcoNet(publicly available at:https://gitlab.univ-nantes.fr/mbudinich/atlanteconet), which builds upon existing software by integrating a selection of complementary methods for ecological network inference, analysis, and validation. This workflow will be used in Task 5.2 to build an all-Atlantic plankton ecological network from omics data compiled within WP2.

Published
2022
Full Text
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46. Contribution of genome‐scale metabolic modelling to niche theory

Author

Régimbeau, Antoine, Budinich, Marko, Larhlimi, Abdelhalim, Pierella Karlusich, Juan José, Aumont, Olivier, Memery, Laurent, Bowler, Chris, Eveillard, Damien, Jordan, Ferenc, Régimbeau, Antoine, Budinich, Marko, Larhlimi, Abdelhalim, Pierella Karlusich, Juan José, Aumont, Olivier, Memery, Laurent, Bowler, Chris, Eveillard, Damien, and Jordan, Ferenc

Abstract

Standard niche modelling is based on probabilistic inference from organismal occurrence data but does not benefit yet from genome-scale descriptions of these organisms. This study overcomes this shortcoming by proposing a new conceptual niche that resumes the whole metabolic capabilities of an organism. The so-called metabolic niche resumes well-known traits such as nutrient needs and their dependencies for survival. Despite the computational challenge, its implementation allows the detection of traits and the formal comparison of niches of different organisms, emphasising that the presence–absence of functional genes is not enough to approximate the phenotype. Further statistical exploration of an organism's niche sheds light on genes essential for the metabolic niche and their role in understanding various biological experiments, such as transcriptomics, paving the way for incorporating better genome-scale description in ecological studies.

Published
2022
Full Text
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47. Genomic evidence for global ocean plankton biogeography shaped by large-scale current systems

Author

Centre National de la Recherche Scientifique (France), European Molecular Biology Laboratory, Centre National de Séquençage (France), National Fund for Scientific Research (Belgium), Stazione Zoologica Anton Dohrn, Università degli Studi di Milano, Université Paris Sciences & Lettres, Agence Nationale de la Recherche (France), National Science Foundation (US), Veolia Foundation, Région Bretagne, World Courier, Illumina, Cap L’Orient, Fondation EDF, Fondation pour la Recherche sur la Biodiversité, Fondation Prince Albert II de Monaco, Ministère de l'Europe et des Affaires étrangères (France), Richter, Daniel J., Watteaux, Romain, Vannier, Thomas, Leconte, Jade, Frémont, Paul, Reygondeau, Gabriel, Maillet, Nicolas, Henry, Nicolas, Benoit, Gaëtan, da Silva, Ophélie, Delmont, Tom O., Fernández-Guerra, Antonio, Suweis, Samir, Narci, Romain, Berney, Cedric, Eveillard, Damien, Gavory, Frederick, Guidi, Lionel, Labadie, Karine, Mahieu, Eric, Poulain, Julie, Romac, Sarah, Roux, Simon, Dimier, Céline, Kandels‐Lewis, Stefanie, Picheral, Marc, Searson, Sarah, Oceans, Tara, Pesant, Stéphane, Aury, Jean‐Marc, Brum, Jennifer R., Lemaitre, Claire, Pelletier, Eric, Bork, Peer, Sunagawa, Shinichi, Lombard, Fabien, Karp-Boss, Lee, Bowler, Chris, Sullivan, Matthew B., Karsenti, Eric, Mariadassou, Mahendra, Probert, Ian, Peterlongo, Pierre, Wincker, Patrick, Vargas, Colomban de, Ribera d’Alcalà, Maurizio, Iudicone, Daniele, Jaillon, Olivier, Tara Oceans Coordinators, Centre National de la Recherche Scientifique (France), European Molecular Biology Laboratory, Centre National de Séquençage (France), National Fund for Scientific Research (Belgium), Stazione Zoologica Anton Dohrn, Università degli Studi di Milano, Université Paris Sciences & Lettres, Agence Nationale de la Recherche (France), National Science Foundation (US), Veolia Foundation, Région Bretagne, World Courier, Illumina, Cap L’Orient, Fondation EDF, Fondation pour la Recherche sur la Biodiversité, Fondation Prince Albert II de Monaco, Ministère de l'Europe et des Affaires étrangères (France), Richter, Daniel J., Watteaux, Romain, Vannier, Thomas, Leconte, Jade, Frémont, Paul, Reygondeau, Gabriel, Maillet, Nicolas, Henry, Nicolas, Benoit, Gaëtan, da Silva, Ophélie, Delmont, Tom O., Fernández-Guerra, Antonio, Suweis, Samir, Narci, Romain, Berney, Cedric, Eveillard, Damien, Gavory, Frederick, Guidi, Lionel, Labadie, Karine, Mahieu, Eric, Poulain, Julie, Romac, Sarah, Roux, Simon, Dimier, Céline, Kandels‐Lewis, Stefanie, Picheral, Marc, Searson, Sarah, Oceans, Tara, Pesant, Stéphane, Aury, Jean‐Marc, Brum, Jennifer R., Lemaitre, Claire, Pelletier, Eric, Bork, Peer, Sunagawa, Shinichi, Lombard, Fabien, Karp-Boss, Lee, Bowler, Chris, Sullivan, Matthew B., Karsenti, Eric, Mariadassou, Mahendra, Probert, Ian, Peterlongo, Pierre, Wincker, Patrick, Vargas, Colomban de, Ribera d’Alcalà, Maurizio, Iudicone, Daniele, Jaillon, Olivier, and Tara Oceans Coordinators

Abstract

Biogeographical studies have traditionally focused on readily visible organisms, but recent technological advances are enabling analyses of the large-scale distribution of microscopic organisms, whose biogeographical patterns have long been debated. Here we assessed the global structure of plankton geography and its relation to the biological, chemical, and physical context of the ocean (the ‘seascape’) by analyzing metagenomes of plankton communities sampled across oceans during the Tara Oceans expedition, in light of environmental data and ocean current transport. Using a consistent approach across organismal sizes that provides unprecedented resolution to measure changes in genomic composition between communities, we report a pan-ocean, size-dependent plankton biogeography overlying regional heterogeneity. We found robust evidence for a basin-scale impact of transport by ocean currents on plankton biogeography, and on a characteristic timescale of community dynamics going beyond simple seasonality or life history transitions of plankton.

Published
2022

49. Priorities for ocean microbiome research

Author

Tara Ocean Foundation, Abreu, Andre, Bourgois, Etienne, Gristwood, Adam, Troublé, Romain, Tara Oceans, Acinas, Silvia G., Bork, Peer, Boss, Emmanuel, Bowler, Chris, Budinich, Marko, Chaffron, Samuel, de Vargas, Colomban, Delmont, Tom O., Eveillard, Damien, Guidi, Lionel, Iudicone, Daniele, Kandels, Stephanie, Morlon, Hélène, Lombard, Fabien, Pepperkok, Rainer, Pierella Karlusich, Juan José, Piganeau, Gwenael, Régimbeau, Antoine, Sommeria-Klein, Guilhem, Stemmann, Lars, Sullivan, Matthew B., Sunagawa, Shinichi, Wincker, Patrick, Zablocki, Olivier, European Molecular Biology Laboratory (EMBL), Arendt, Detlev, Bilic, Josipa, Finn, Robert, Heard, Edith, Rouse, Brendan, Vamathevan, Jessica, European Marine Biological Resource Centre - European Research Infrastructure Consortium (EMBRC-ERIC), Casotti, Raffaella, Cancio, Ibon, Cunliffe, Michael, Kervella, Anne Emmanuelle, Kooistra, Wiebe H.C.F., Obst, Matthias, Pade, Nicolas, Power, Deborah M., Santi, Ioulia, Tsagaraki, Tatiana Margo, Vanaverbeke, Jan, European Commission, Agencia Estatal de Investigación (España), Tara Ocean Foundation, Tara Expéditions, Institute of Marine Sciences / Institut de Ciències del Mar [Barcelona] (ICM), Consejo Superior de Investigaciones Científicas [Madrid] (CSIC), European Molecular Biology Laboratory [Heidelberg] (EMBL), University of Maine, Institut de biologie de l'ENS Paris (IBENS), Département de Biologie - ENS Paris, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Global Oceans Systems Ecology & Evolution - Tara Oceans (GOSEE), Université de Perpignan Via Domitia (UPVD)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Aix Marseille Université (AMU)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université d'Évry-Val-d'Essonne (UEVE)-Université de Toulon (UTLN)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut de Recherche pour le Développement (IRD [France-Nord])-Ecole Normale Supérieure Paris-Saclay (ENS Paris Saclay)-European Molecular Biology Laboratory (EMBL)-École Centrale de Nantes (Nantes Univ - ECN), Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ)-Université australe du Chili, Combinatoire et Bioinformatique (LS2N - équipe COMBI), Laboratoire des Sciences du Numérique de Nantes (LS2N), Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-École Centrale de Nantes (Nantes Univ - ECN), Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ)-Nantes université - UFR des Sciences et des Techniques (Nantes univ - UFR ST), Nantes Université - pôle Sciences et technologie, Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ)-Nantes Université - pôle Sciences et technologie, Nantes Université (Nantes Univ)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Nantes Université (Nantes Univ), Station biologique de Roscoff (SBR), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Genoscope - Centre national de séquençage [Evry] (GENOSCOPE), Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Laboratoire d'océanographie de Villefranche (LOV), Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), and Stazione Zoologica Anton Dohrn (SZN)

Subjects
Microbiology (medical), Genome, Marine, Bacteria, Ecology, Immunology, [SDV.BBM.MN]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Molecular Networks [q-bio.MN], Cell Biology, Terrestrial, Plankton, Applied Microbiology and Biotechnology, Microbiology, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], [SDV.EE.ECO]Life Sciences [q-bio]/Ecology, environment/Ecosystems, [SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN], Sequence, Viruses, Genetics, Phages, Biomass, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, [SDV.EE.IEO]Life Sciences [q-bio]/Ecology, environment/Symbiosis
Abstract

This article is contribution number 131 of Tara Oceans.-- 11 pages, 5 figures, 1 table, 1 box, Microbial communities have essential roles in ocean ecology and planetary health. Microbes participate in nutrient cycles, remove huge quantities of carbon dioxide from the air and support ocean food webs. The taxonomic and functional diversity of the global ocean microbiome has been revealed by technological advances in sampling, DNA sequencing and bioinformatics. A better understanding of the ocean microbiome could underpin strategies to address environmental and societal challenges, including achievement of multiple Sustainable Development Goals way beyond SDG 14 ‘life below water’. We propose a set of priorities for understanding and protecting the ocean microbiome, which include delineating interactions between microbiota, sustainably applying resources from oceanic microorganisms and creating policy- and funder-friendly ocean education resources, and discuss how to achieve these ambitious goals, We thank R. Zaayman-Gallant, T. Rauscher and F. Ibarbalz for preparation of the figures, and the European Union’s Horizon 2020 research and innovation project AtlantECO, under grant agreement no. 862923, With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S)

Published
2022

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