7 research outputs found

    Community-Level Responses to Iron Availability in Open Ocean Plankton Ecosystems

    Get PDF
    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

    Méta-omique et méta-données environnementales : vers une nouvelle compréhension de la pompe à carbone biologique

    No full text
    The biological carbon pump encompasses a series of processes including the primary production of organic matter in the surface ocean, its export to deeper waters and its remineralization. The common highlighted actors are diatoms because of their contribution to primary production and carbon export and copepods for their production of fecal pellets. However, the biological pump is the result of complex interactions among organisms rather than their independent actions. Besides, although size distribution and mineral composition of phytoplankton in surface was shown to significantly influence the strength of carbon export, it is unknown whether meta-omic data can efficiently predict the processes of the biological carbon pump. In this thesis, I first propose to revisit the study of the biological carbon pump in the oligotrophic ocean by defining biogeochemical states of the ocean based on the relative contribution of primary production, carbon export and flux attenuation in Tara Oceans sampling stations. The analysis of the states in terms of microbial composition and interactions inferred from metabarcoding data revealed that variation in associations rather than lineages presence seems to drive the states of the biological carbon pump. Then, by using meta-omics and environmental parameters from the Tara Oceans expeditions, I propose the first study trying to predict biogeochemical states from biological abundances derived from environmental DNA, with the goal of providing a list of biomarkers.La pompe Ă  carbone biologique comprend la production primaire de matiĂšre organique dans la zone euphotique, son export vers les profondeurs et sa reminĂ©ralisation. Les acteurs les plus frĂ©quemment citĂ©s sont les diatomĂ©es en raison de leur contribution Ă  la production primaire et Ă  l’export de carbone et les copĂ©podes pour la production de pelotes fĂ©cales. Cependant, la pompe biologique est le rĂ©sultat d'interactions complexes entre organismes plutĂŽt que de leurs actions indĂ©pendantes. En outre, bien qu'il ait Ă©tĂ© montrĂ© que la distribution de taille et la composition minĂ©rale du phytoplancton en surface ont une influence significative sur l'intensitĂ© de l'export de carbone, on ne sait pas si les donnĂ©es mĂ©ta-omiques peuvent prĂ©dire efficacement les processus de la pompe Ă  carbone biologique. Dans cette thĂšse, je propose d’abord de revisiter l’étude de la pompe Ă  carbone biologique dans l’ocĂ©an oligotrophe en dĂ©finissant des Ă©tats biogĂ©ochimiques de l’ocĂ©an sur la base de la contribution relative de la production primaire, de l’export de carbone et de l’attĂ©nuation du flux dans les stations d’échantillonnage Tara OcĂ©ans. L'analyse des Ă©tats en termes de composition et d'interactions microbiennes infĂ©rĂ©es Ă  partir de donnĂ©es de mĂ©tabarcoding a rĂ©vĂ©lĂ© que les associations plutĂŽt que la composition microbienne semblent caractĂ©riser les Ă©tats de la pompe Ă  carbone biologique. Ensuite, en utilisant les donnĂ©es mĂ©ta-omiques et environnementales des expĂ©ditions Tara Oceans, je propose pour la premiĂšre fois de prĂ©dire ces Ă©tats biogĂ©ochimiques Ă  partir d'abondances biologiques dĂ©rivĂ©es d'ADN environnemental, dans l'objectif de fournir une liste de biomarqueurs

    Meta-omics and environmental meta-data : towards a new comprehension of the biological carbon pump

    No full text
    La pompe Ă  carbone biologique comprend la production primaire de matiĂšre organique dans la zone euphotique, son export vers les profondeurs et sa reminĂ©ralisation. Les acteurs les plus frĂ©quemment citĂ©s sont les diatomĂ©es en raison de leur contribution Ă  la production primaire et Ă  l’export de carbone et les copĂ©podes pour la production de pelotes fĂ©cales. Cependant, la pompe biologique est le rĂ©sultat d'interactions complexes entre organismes plutĂŽt que de leurs actions indĂ©pendantes. En outre, bien qu'il ait Ă©tĂ© montrĂ© que la distribution de taille et la composition minĂ©rale du phytoplancton en surface ont une influence significative sur l'intensitĂ© de l'export de carbone, on ne sait pas si les donnĂ©es mĂ©ta-omiques peuvent prĂ©dire efficacement les processus de la pompe Ă  carbone biologique. Dans cette thĂšse, je propose d’abord de revisiter l’étude de la pompe Ă  carbone biologique dans l’ocĂ©an oligotrophe en dĂ©finissant des Ă©tats biogĂ©ochimiques de l’ocĂ©an sur la base de la contribution relative de la production primaire, de l’export de carbone et de l’attĂ©nuation du flux dans les stations d’échantillonnage Tara OcĂ©ans. L'analyse des Ă©tats en termes de composition et d'interactions microbiennes infĂ©rĂ©es Ă  partir de donnĂ©es de mĂ©tabarcoding a rĂ©vĂ©lĂ© que les associations plutĂŽt que la composition microbienne semblent caractĂ©riser les Ă©tats de la pompe Ă  carbone biologique. Ensuite, en utilisant les donnĂ©es mĂ©ta-omiques et environnementales des expĂ©ditions Tara Oceans, je propose pour la premiĂšre fois de prĂ©dire ces Ă©tats biogĂ©ochimiques Ă  partir d'abondances biologiques dĂ©rivĂ©es d'ADN environnemental, dans l'objectif de fournir une liste de biomarqueurs.The biological carbon pump encompasses a series of processes including the primary production of organic matter in the surface ocean, its export to deeper waters and its remineralization. The common highlighted actors are diatoms because of their contribution to primary production and carbon export and copepods for their production of fecal pellets. However, the biological pump is the result of complex interactions among organisms rather than their independent actions. Besides, although size distribution and mineral composition of phytoplankton in surface was shown to significantly influence the strength of carbon export, it is unknown whether meta-omic data can efficiently predict the processes of the biological carbon pump. In this thesis, I first propose to revisit the study of the biological carbon pump in the oligotrophic ocean by defining biogeochemical states of the ocean based on the relative contribution of primary production, carbon export and flux attenuation in Tara Oceans sampling stations. The analysis of the states in terms of microbial composition and interactions inferred from metabarcoding data revealed that variation in associations rather than lineages presence seems to drive the states of the biological carbon pump. Then, by using meta-omics and environmental parameters from the Tara Oceans expeditions, I propose the first study trying to predict biogeochemical states from biological abundances derived from environmental DNA, with the goal of providing a list of biomarkers

    Mixotrophic protists display contrasted biogeographies in the global ocean

    No full text
    International audienceMixotrophy, or the ability to acquire carbon from both auto- and heterotrophy, is a widespread ecological trait in marine protists. Using a metabarcoding dataset of marine plankton from the global ocean, 318,054 mixotrophic metabarcodes represented by 89,951,866 sequences and belonging to 133 taxonomic lineages were identified and classified into four mixotrophic functional types: constitutive mixotrophs (CM), generalist non-constitutive mixotrophs (GNCM), endo-symbiotic specialist non-constitutive mixotrophs (eSNCM), and plastidic specialist non-constitutive mixotrophs (pSNCM). Mixotrophy appeared ubiquitous, and the distributions of the four mixotypes were analyzed to identify the abiotic factors shaping their biogeographies. Kleptoplastidic mixotrophs (GNCM and pSNCM) were detected in new zones compared to previous morphological studies. Constitutive and non-constitutive mixotrophs had similar ranges of distributions. Most lineages were evenly found in the samples, yet some of them displayed strongly contrasted distributions, both across and within mixotypes. Particularly divergent biogeographies were found within endo-symbiotic mixotrophs, depending on the ability to form colonies or the mode of symbiosis. We showed how metabarcoding can be used in a complementary way with previous morphological observations to study the biogeography of mixotrophic protists and to identify key drivers of their biogeography

    Mare Incognitum: A Glimpse into Future Plankton Diversity and Ecology Research

    Get PDF
    With global climate change altering marine ecosystems, research on plankton ecology is likely to navigate uncharted seas. Yet, a staggering wealth of new plankton observations, integrated with recent advances in marine ecosystem modeling, may shed light on marine ecosystem structure and functioning. A EuroMarine foresight workshop on the “Impact of climate change on the distribution of plankton functional and phylogenetic diversity” (PlankDiv) identified five grand challenges for future plankton diversity and macroecology research: (1) What can we learn about plankton communities from the new wealth of high-throughput “omics” data? (2) What is the link between plankton diversity and ecosystem function? (3) How can species distribution models be adapted to represent plankton biogeography? (4) How will plankton biogeography be altered due to anthropogenic climate change? and (5) Can a new unifying theory of macroecology be developed based on plankton ecology studies? In this review, we discuss potential future avenues to address these questions, and challenges that need to be tackled along the way

    A global metagenomic map of urban microbiomes and antimicrobial resistance

    No full text
    We present a global atlas of 4,728 metagenomic samples from mass-transit systems in 60 cities over 3 years, representing the first systematic, worldwide catalog of the urban microbial ecosystem. This atlas provides an annotated, geospatial profile of microbial strains, functional characteristics, antimicrobial resistance (AMR) markers, and genetic elements, including 10,928 viruses, 1,302 bacteria, 2 archaea, and 838,532 CRISPR arrays not found in reference databases. We identified 4,246 known species of urban microorganisms and a consistent set of 31 species found in 97% of samples that were distinct from human commensal organisms. Profiles of AMR genes varied widely in type and density across cities. Cities showed distinct microbial taxonomic signatures that were driven by climate and geographic differences. These results constitute a high-resolution global metagenomic atlas that enables discovery of organisms and genes, highlights potential public health and forensic applications, and provides a culture-independent view of AMR burden in cities.Funding: the Tri-I Program in Computational Biology and Medicine (CBM) funded by NIH grant 1T32GM083937; GitHub; Philip Blood and the Extreme Science and Engineering Discovery Environment (XSEDE), supported by NSF grant number ACI-1548562 and NSF award number ACI-1445606; NASA (NNX14AH50G, NNX17AB26G), the NIH (R01AI151059, R25EB020393, R21AI129851, R35GM138152, U01DA053941); STARR Foundation (I13- 0052); LLS (MCL7001-18, LLS 9238-16, LLS-MCL7001-18); the NSF (1840275); the Bill and Melinda Gates Foundation (OPP1151054); the Alfred P. Sloan Foundation (G-2015-13964); Swiss National Science Foundation grant number 407540_167331; NIH award number UL1TR000457; the US Department of Energy Joint Genome Institute under contract number DE-AC02-05CH11231; the National Energy Research Scientific Computing Center, supported by the Office of Science of the US Department of Energy; Stockholm Health Authority grant SLL 20160933; the Institut Pasteur Korea; an NRF Korea grant (NRF-2014K1A4A7A01074645, 2017M3A9G6068246); the CONICYT Fondecyt Iniciación grants 11140666 and 11160905; Keio University Funds for Individual Research; funds from the Yamagata prefectural government and the city of Tsuruoka; JSPS KAKENHI grant number 20K10436; the bilateral AT-UA collaboration fund (WTZ:UA 02/2019; Ministry of Education and Science of Ukraine, UA:M/84-2019, M/126-2020); Kyiv Academic Univeristy; Ministry of Education and Science of Ukraine project numbers 0118U100290 and 0120U101734; Centro de Excelencia Severo Ochoa 2013–2017; the CERCA Programme / Generalitat de Catalunya; the CRG-Novartis-Africa mobility program 2016; research funds from National Cheng Kung University and the Ministry of Science and Technology; Taiwan (MOST grant number 106-2321-B-006-016); we thank all the volunteers who made sampling NYC possible, Minciencias (project no. 639677758300), CNPq (EDN - 309973/2015-5), the Open Research Fund of Key Laboratory of Advanced Theory and Application in Statistics and Data Science – MOE, ECNU, the Research Grants Council of Hong Kong through project 11215017, National Key RD Project of China (2018YFE0201603), and Shanghai Municipal Science and Technology Major Project (2017SHZDZX01) (L.S.
    corecore