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      Standardized multi-omics of Earth’s microbiomes reveals microbial and metabolite diversity

      research-article
      1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 3 , 1 , 9 , 10 , 1 , 9 , 1 , 11 , 12 , 13 , 9 , 14 , 15 , 1 , 2 , 3 , 16 , 16 , 17 , 2 , 3 , 18 , 2 , 3 , 19 , 11 , 1 , 1 , 1 , 1 , 1 , 9 , 1 , 3 , 10 , 20 , 21 , 1 , 11 , 1 , 1 , 22 , 23 , 24 , 1 , 1 , 25 , 2 , 11 , 26 , 27 , 8 , 9 , 8 , 9 , 2 , 3 , 8 , 1 , 11 , 1 , 7 , 9 , 28 , , the Earth Microbiome Project 500 (EMP500) Consortium
      Nature Microbiology
      Nature Publishing Group UK
      Microbial ecology, Chemical ecology, Metabolomics, Next-generation sequencing, Cheminformatics

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          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Despite advances in sequencing, lack of standardization makes comparisons across studies challenging and hampers insights into the structure and function of microbial communities across multiple habitats on a planetary scale. Here we present a multi-omics analysis of a diverse set of 880 microbial community samples collected for the Earth Microbiome Project. We include amplicon (16S, 18S, ITS) and shotgun metagenomic sequence data, and untargeted metabolomics data (liquid chromatography-tandem mass spectrometry and gas chromatography mass spectrometry). We used standardized protocols and analytical methods to characterize microbial communities, focusing on relationships and co-occurrences of microbially related metabolites and microbial taxa across environments, thus allowing us to explore diversity at extraordinary scale. In addition to a reference database for metagenomic and metabolomic data, we provide a framework for incorporating additional studies, enabling the expansion of existing knowledge in the form of an evolving community resource. We demonstrate the utility of this database by testing the hypothesis that every microbe and metabolite is everywhere but the environment selects. Our results show that metabolite diversity exhibits turnover and nestedness related to both microbial communities and the environment, whereas the relative abundances of microbially related metabolites vary and co-occur with specific microbial consortia in a habitat-specific manner. We additionally show the power of certain chemistry, in particular terpenoids, in distinguishing Earth’s environments (for example, terrestrial plant surfaces and soils, freshwater and marine animal stool), as well as that of certain microbes including Conexibacter woesei (terrestrial soils), Haloquadratum walsbyi (marine deposits) and Pantoea dispersa (terrestrial plant detritus). This Resource provides insight into the taxa and metabolites within microbial communities from diverse habitats across Earth, informing both microbial and chemical ecology, and provides a foundation and methods for multi-omics microbiome studies of hosts and the environment.

          Abstract

          This Resource combines amplicon sequencing, shotgun metagenomic sequencing and untargeted metabolomics to provide a global view of microbial–metabolite associations across Earth’s environments.

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          Most cited references152

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          Fast gapped-read alignment with Bowtie 2.

          As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
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            Cutadapt removes adapter sequences from high-throughput sequencing reads

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              KEGG: kyoto encyclopedia of genes and genomes.

              M Kanehisa (2000)
              KEGG (Kyoto Encyclopedia of Genes and Genomes) is a knowledge base for systematic analysis of gene functions, linking genomic information with higher order functional information. The genomic information is stored in the GENES database, which is a collection of gene catalogs for all the completely sequenced genomes and some partial genomes with up-to-date annotation of gene functions. The higher order functional information is stored in the PATHWAY database, which contains graphical representations of cellular processes, such as metabolism, membrane transport, signal transduction and cell cycle. The PATHWAY database is supplemented by a set of ortholog group tables for the information about conserved subpathways (pathway motifs), which are often encoded by positionally coupled genes on the chromosome and which are especially useful in predicting gene functions. A third database in KEGG is LIGAND for the information about chemical compounds, enzyme molecules and enzymatic reactions. KEGG provides Java graphics tools for browsing genome maps, comparing two genome maps and manipulating expression maps, as well as computational tools for sequence comparison, graph comparison and path computation. The KEGG databases are daily updated and made freely available (http://www. genome.ad.jp/kegg/).
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                Author and article information

                Contributors
                robknight@ucsd.edu
                Journal
                Nat Microbiol
                Nat Microbiol
                Nature Microbiology
                Nature Publishing Group UK (London )
                2058-5276
                28 November 2022
                28 November 2022
                2022
                : 7
                : 12
                : 2128-2150
                Affiliations
                [1 ]GRID grid.266100.3, ISNI 0000 0001 2107 4242, Department of Pediatrics, School of Medicine, , University of California San Diego, ; La Jolla, CA USA
                [2 ]GRID grid.266100.3, ISNI 0000 0001 2107 4242, Collaborative Mass Spectrometry Innovation Center, , University of California San Diego, ; La Jolla, CA USA
                [3 ]GRID grid.266100.3, ISNI 0000 0001 2107 4242, Skaggs School of Pharmacy and Pharmaceutical Sciences, , University of California San Diego, ; La Jolla, CA USA
                [4 ]GRID grid.260120.7, ISNI 0000 0001 0816 8287, Northern Gulf Institute, , Mississippi State University, ; Starkville, MS USA
                [5 ]GRID grid.436459.9, ISNI 0000 0001 2155 5230, Ocean Chemistry and Ecosystems Division, , Atlantic Oceanographic and Meteorological Laboratory, National Oceanic and Atmospheric Administration, ; Miami, FL USA
                [6 ]GRID grid.5386.8, ISNI 000000041936877X, Department of Ecology and Evolutionary Biology, , Cornell University, ; Ithaca, NY USA
                [7 ]GRID grid.266100.3, ISNI 0000 0001 2107 4242, Department of Bioengineering, , University of California San Diego, ; La Jolla, CA USA
                [8 ]GRID grid.451303.0, ISNI 0000 0001 2218 3491, Earth and Biological Sciences Directorate, , Pacific Northwest National Laboratory, ; Richland, WA USA
                [9 ]GRID grid.266100.3, ISNI 0000 0001 2107 4242, Center for Microbiome Innovation, Jacobs School of Engineering, , University of California San Diego, ; La Jolla, CA USA
                [10 ]GRID grid.481554.9, ISNI 0000 0001 2111 841X, IBM Research, , T.J. Watson Research Center, ; Yorktown Heights, NY USA
                [11 ]GRID grid.266100.3, ISNI 0000 0001 2107 4242, Scripps Institution of Oceanography, , University of California San Diego, ; La Jolla, CA USA
                [12 ]GRID grid.215654.1, ISNI 0000 0001 2151 2636, School of Life Sciences, , Arizona State University, ; Tempe, AZ USA
                [13 ]GRID grid.215654.1, ISNI 0000 0001 2151 2636, Biodesign Center for Fundamental and Applied Microbiomics, , Arizona State University, ; Tempe, AZ USA
                [14 ]GRID grid.266100.3, ISNI 0000 0001 2107 4242, Bioinformatics and Systems Biology Program, Jacobs School of Engineering, , University of California San Diego, ; La Jolla, CA USA
                [15 ]GRID grid.430264.7, ISNI 0000 0004 4648 6763, Center for Computational Biology, Flatiron Institute, , Simons Foundation, ; New York, NY USA
                [16 ]GRID grid.9613.d, ISNI 0000 0001 1939 2794, Chair for Bioinformatics, , Friedrich Schiller University, ; Jena, Germany
                [17 ]GRID grid.255168.d, ISNI 0000 0001 0671 5021, College of Pharmacy and Integrated Research Institute for Drug Development, , Dongguk University, ; Gyeonggi-do, Korea
                [18 ]GRID grid.63054.34, ISNI 0000 0001 0860 4915, Department of Chemistry, , University of Connecticut, ; Storrs, CT USA
                [19 ]GRID grid.5284.b, ISNI 0000 0001 0790 3681, Department of Computer Science, , University of Antwerp, ; Antwerp, Belgium
                [20 ]IBM Research Europe, Daresbury, UK
                [21 ]GRID grid.481551.c, IBM Research, , Almaden Research Center, ; San Jose, CA USA
                [22 ]GRID grid.184769.5, ISNI 0000 0001 2231 4551, Environmental Genomics and Systems Biology, , Lawrence Berkeley National Laboratory, ; Berkeley, CA USA
                [23 ]GRID grid.6203.7, ISNI 0000 0004 0417 4147, Department of Virus and Microbiological Special Diagnostics, , Statens Serum Institute, ; Copenhagen, Denmark
                [24 ]GRID grid.5117.2, ISNI 0000 0001 0742 471X, Department of Chemistry and Bioscience, , Aalborg University, ; Aalborg, Denmark
                [25 ]GRID grid.1005.4, ISNI 0000 0004 4902 0432, Centre for Marine Science and Innovation, School of Biological, Earth and Environmental Science, , The University of New South Wales, ; Sydney, New South Wales Australia
                [26 ]GRID grid.10392.39, ISNI 0000 0001 2190 1447, Interfaculty Institute of Microbiology and Infection Medicine, , University of Tübingen, ; Tübingen, Baden-Württemberg Germany
                [27 ]GRID grid.17088.36, ISNI 0000 0001 2150 1785, Department of Microbiology and Molecular Genetics, , Michigan State University, ; East Lansing, MI USA
                [28 ]GRID grid.266100.3, ISNI 0000 0001 2107 4242, Department of Computer Science and Engineering, Jacobs School of Engineering, , University of California San Diego, ; La Jolla, CA USA
                [29 ]GRID grid.10392.39, ISNI 0000 0001 2190 1447, University of Tübingen, ; Tübingen, Baden-Württemberg Germany
                [30 ]GRID grid.27860.3b, ISNI 0000 0004 1936 9684, University of California, Davis, ; Davis, CA USA
                [31 ]GRID grid.184764.8, ISNI 0000 0001 0670 228X, Boise State University, ; Boise, ID USA
                [32 ]GRID grid.261112.7, ISNI 0000 0001 2173 3359, Northeastern University, ; Boston, MA USA
                [33 ]GRID grid.412889.e, ISNI 0000 0004 1937 0706, University of Costa Rica, ; San José, Costa Rica
                [34 ]CENIBiot, San José, Costa Rica
                [35 ]GRID grid.49697.35, ISNI 0000 0001 2107 2298, University of Pretoria, ; Pretoria, South Africa
                [36 ]GRID grid.38142.3c, ISNI 000000041936754X, Harvard University, ; Cambridge, MA USA
                [37 ]Universidad Politécnica de Madrid, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria, Madrid, Spain
                [38 ]GRID grid.266100.3, ISNI 0000 0001 2107 4242, University of California San Diego, ; La Jolla, CA USA
                [39 ]GRID grid.497530.c, ISNI 0000 0004 0389 4927, Janssen Research and Development, ; San Diego, CA USA
                [40 ]GRID grid.64337.35, ISNI 0000 0001 0662 7451, Louisiana State University, ; Baton Rouge, LA USA
                [41 ]GRID grid.9681.6, ISNI 0000 0001 1013 7965, University of Jyväskylä, ; Jyväskylä, Finland
                [42 ]GRID grid.25879.31, ISNI 0000 0004 1936 8972, University of Pennsylvania, ; Philadelphia, PA USA
                [43 ]GRID grid.1013.3, ISNI 0000 0004 1936 834X, The University of Sydney, ; Sydney, New South Wales Australia
                [44 ]GRID grid.449768.0, Texas Technology University, ; Lubbock, TX USA
                [45 ]GRID grid.28803.31, ISNI 0000 0001 0701 8607, University of Wisconsin, ; Madison, WI USA
                [46 ]GRID grid.47894.36, ISNI 0000 0004 1936 8083, Colorado State University, ; Fort Collins, CO USA
                [47 ]GRID grid.226688.0, ISNI 0000 0004 0620 9198, Temasek Life Sciences Laboratory, ; Singapore, Singapore
                [48 ]GRID grid.4391.f, ISNI 0000 0001 2112 1969, Oregon State University, ; Corvallis, OR USA
                [49 ]GRID grid.15276.37, ISNI 0000 0004 1936 8091, University of Florida, ; Gainesville, FL USA
                [50 ]GRID grid.7870.8, ISNI 0000 0001 2157 0406, Pontificia Universidad Católica de Chile, ; Santiago, Chile
                [51 ]GRID grid.263081.e, ISNI 0000 0001 0790 1491, San Diego State University, ; San Diego, CA USA
                [52 ]GRID grid.451303.0, ISNI 0000 0001 2218 3491, Pacific Northwest National Laboratory, ; Richland, WA USA
                [53 ]GRID grid.164295.d, ISNI 0000 0001 0941 7177, University of Maryland, ; College Park, MD USA
                [54 ]GRID grid.266190.a, ISNI 0000000096214564, Department of Ecology and Evolutionary Biology, , University of Colorado at Boulder, ; Boulder, CO USA
                [55 ]GRID grid.4280.e, ISNI 0000 0001 2180 6431, National University of Singapore, ; Singapore, Singapore
                [56 ]University East Lansing, East Lansing, MI USA
                [57 ]GRID grid.11201.33, ISNI 0000 0001 2219 0747, University of Plymouth, ; Plymouth, UK
                [58 ]GRID grid.266683.f, ISNI 0000 0001 2166 5835, University of Massachusetts Amherst, ; Amherst, MA USA
                [59 ]GRID grid.41891.35, ISNI 0000 0001 2156 6108, Montana State University, ; Bozeman, MT USA
                [60 ]GRID grid.22319.3b, ISNI 0000000121062153, Plymouth Marine Laboratory, ; Plymouth, UK
                [61 ]GRID grid.1005.4, ISNI 0000 0004 4902 0432, University of New South Wales, ; Sydney, New South Wales Australia
                [62 ]GRID grid.451363.6, ISNI 0000 0001 2206 3094, National Energy Technology Laboratory, ; Pittsburgh, PA USA
                [63 ]GRID grid.134563.6, ISNI 0000 0001 2168 186X, University of Arizona, ; Tucson, AZ USA
                [64 ]GRID grid.1046.3, ISNI 0000 0001 0328 1619, Australian Institute of Marine Science, ; Townsville, Queensland Australia
                [65 ]GRID grid.1003.2, ISNI 0000 0000 9320 7537, University of Queensland, ; Brisbane, Queensland Australia
                [66 ]GRID grid.34477.33, ISNI 0000000122986657, University of Washington Bothell, ; Bothell, WA USA
                Author information
                http://orcid.org/0000-0002-9371-6336
                http://orcid.org/0000-0001-6711-6719
                http://orcid.org/0000-0002-3911-1280
                http://orcid.org/0000-0001-6077-4014
                http://orcid.org/0000-0003-0307-9343
                http://orcid.org/0000-0002-8663-1019
                http://orcid.org/0000-0001-6454-809X
                http://orcid.org/0000-0002-3568-6271
                http://orcid.org/0000-0001-9334-1258
                http://orcid.org/0000-0002-9304-8091
                http://orcid.org/0000-0002-3105-1359
                http://orcid.org/0000-0002-7872-5074
                http://orcid.org/0000-0002-4603-0235
                http://orcid.org/0000-0003-0876-9060
                http://orcid.org/0000-0002-6151-190X
                http://orcid.org/0000-0001-9557-3001
                http://orcid.org/0000-0002-6561-3022
                http://orcid.org/0000-0002-7189-3067
                http://orcid.org/0000-0001-6049-3968
                http://orcid.org/0000-0001-5655-8300
                http://orcid.org/0000-0002-3003-1030
                http://orcid.org/0000-0002-5487-4315
                http://orcid.org/0000-0001-7920-7001
                http://orcid.org/0000-0002-0975-9019
                Article
                1266
                10.1038/s41564-022-01266-x
                9712116
                36443458
                db30b48a-d8a6-4b89-b106-8f78040ff1e0
                © The Author(s) 2022

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 3 November 2021
                : 10 October 2022
                Funding
                Funded by: FundRef https://doi.org/10.13039/100005825, United States Department of Agriculture | National Institute of Food and Agriculture (NIFA);
                Award ID: 2019-67013-29137
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100000057, U.S. Department of Health & Human Services | NIH | National Institute of General Medical Sciences (NIGMS);
                Award ID: IRACDA K12 GM068524
                Award Recipient :
                Funded by: Metabolomics analyses at Pacific Northwest National Laboratory (PNNL) were supported by the Laboratory Directed Research and Development program via the Microbiomes in Transition Initiative and performed in the Environmental Molecular Sciences Laboratory, a national scientific user facility sponsored by the US Office of Biological and Environmental Research and located at PNNL
                Funded by: FundRef https://doi.org/10.13039/100008394, Natur og Univers, Det Frie Forskningsråd (Natural Sciences, Danish Council for Independent Research);
                Award ID: 9058-00025B
                Award Recipient :
                Funded by: Center for Microbiome Innovation, University of California, San Diego, California, United States
                Funded by: IBM Research AI through the AI Horizons Network
                Funded by: FundRef https://doi.org/10.13039/501100001659, Deutsche Forschungsgemeinschaft (German Research Foundation);
                Award ID: BO 1910/20
                Award ID: BO 1910/23
                Award ID: BO 1910/20
                Award ID: BO 1910/23
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100003130, Fonds Wetenschappelijk Onderzoek (Research Foundation Flanders);
                Award ID: 12W0418N
                Award Recipient :
                Funded by: U.S. Department of Energy Award No. DE-AC02-05CH11231.
                Funded by: FundRef https://doi.org/10.13039/100000936, Gordon and Betty Moore Foundation (Gordon E. and Betty I. Moore Foundation);
                Award ID: GBMF7622
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100000002, U.S. Department of Health & Human Services | National Institutes of Health (NIH);
                Award ID: R01-GM107550
                Award ID: R01-GM107550
                Award ID: 1RF1-AG058942-01
                Award ID: 1DP1AT010885
                Award ID: R01HL140976
                Award ID: R01DK102932
                Award ID: R01HL134887
                Award ID: U19AG063744
                Award ID: U01AI124316
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100000001, National Science Foundation (NSF);
                Award ID: CCFA-675191
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100000015, U.S. Department of Energy (DOE);
                Award ID: SRC/DARPA-GI18518
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100000005, U.S. Department of Defense (United States Department of Defense);
                Award ID: W81XWH-17-1-0589
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100000006, United States Department of Defense | United States Navy | Office of Naval Research (ONR);
                Award ID: N00014-15-1-2809
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100009453, Alberta Emerald Foundation (AEF);
                Award ID: 3022
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                © The Author(s), under exclusive licence to Springer Nature Limited 2022

                microbial ecology,chemical ecology,metabolomics,next-generation sequencing,cheminformatics

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