Articles producció científica> Enginyeria Química

Stochastic block models reveal a robust nested pattern in healthy human gut microbiomes

  • Identification data

    Identifier: imarina:9280069
    Authors:
    Cobo-López, SergioGupta, Vinod KSung, JaeyunGuimerà, RogerSales-Pardo, Marta
    Abstract:
    Abstract A key question in human gut microbiome research is what are the robust structural patterns underlying its taxonomic composition. Herein, we use whole metagenomic datasets from healthy human guts to show that such robust patterns do exist, albeit not in the conventional enterotype sense. We first introduce the concept of mixed-membership enterotypes using a network inference approach based on stochastic block models. We find that gut microbiomes across a group of people (hosts) display a nested structure, which has been observed in a number of ecological systems. This finding led us to designate distinct ecological roles to both microbes and hosts: generalists and specialists. Specifically, generalist hosts have microbiomes with most microbial species, while specialist hosts only have generalist microbes. Moreover, specialist microbes are only present in generalist hosts. From the nested structure of microbial taxonomies, we show that these ecological roles of microbes are generally conserved across datasets. Our results show that the taxonomic composition of healthy human gut microbiomes is associated with robustly structured combinations of generalist and specialist species.
  • Others:

    Author, as appears in the article.: Cobo-López, Sergio; Gupta, Vinod K; Sung, Jaeyun; Guimerà, Roger; Sales-Pardo, Marta
    Department: Enginyeria Química
    URV's Author/s: Cobo Lopez, Sergio / Guimera Manrique, Roger / Sales Pardo, Marta
    Keywords: Stochastic block models Statistical inference Nestedness Human microbiome Ecological networks
    Abstract: Abstract A key question in human gut microbiome research is what are the robust structural patterns underlying its taxonomic composition. Herein, we use whole metagenomic datasets from healthy human guts to show that such robust patterns do exist, albeit not in the conventional enterotype sense. We first introduce the concept of mixed-membership enterotypes using a network inference approach based on stochastic block models. We find that gut microbiomes across a group of people (hosts) display a nested structure, which has been observed in a number of ecological systems. This finding led us to designate distinct ecological roles to both microbes and hosts: generalists and specialists. Specifically, generalist hosts have microbiomes with most microbial species, while specialist hosts only have generalist microbes. Moreover, specialist microbes are only present in generalist hosts. From the nested structure of microbial taxonomies, we show that these ecological roles of microbes are generally conserved across datasets. Our results show that the taxonomic composition of healthy human gut microbiomes is associated with robustly structured combinations of generalist and specialist species.
    Thematic Areas: Social sciences, interdisciplinary Multidisciplinary sciences Multidisciplinary
    licence for use: https://creativecommons.org/licenses/by/3.0/es/
    Author's mail: sergio.cobo@urv.cat roger.guimera@urv.cat marta.sales@urv.cat
    Author identifier: 0000-0002-3597-4310 0000-0002-8140-6525
    Record's date: 2024-10-19
    Papper version: info:eu-repo/semantics/publishedVersion
    Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
    Papper original source: Pnas Nexus. 1 (3): pgac055-
    APA: Cobo-López, Sergio; Gupta, Vinod K; Sung, Jaeyun; Guimerà, Roger; Sales-Pardo, Marta (2022). Stochastic block models reveal a robust nested pattern in healthy human gut microbiomes. Pnas Nexus, 1(3), pgac055-. DOI: 10.1093/pnasnexus/pgac055
    Entity: Universitat Rovira i Virgili
    Journal publication year: 2022
    Publication Type: Journal Publications
  • Keywords:

    Multidisciplinary Sciences,Social Sciences, Interdisciplinary
    Stochastic block models
    Statistical inference
    Nestedness
    Human microbiome
    Ecological networks
    Social sciences, interdisciplinary
    Multidisciplinary sciences
    Multidisciplinary
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