Deciphering functional redundancy in the human microbiome View Full Text


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Article Info

DATE

2020-12-04

AUTHORS

Liang Tian, Xu-Wen Wang, Ang-Kun Wu, Yuhang Fan, Jonathan Friedman, Amber Dahlin, Matthew K. Waldor, George M. Weinstock, Scott T. Weiss, Yang-Yu Liu

ABSTRACT

Although the taxonomic composition of the human microbiome varies tremendously across individuals, its gene composition or functional capacity is highly conserved — implying an ecological property known as functional redundancy. Such functional redundancy has been hypothesized to underlie the stability and resilience of the human microbiome, but this hypothesis has never been quantitatively tested. The origin of functional redundancy is still elusive. Here, we investigate the basis for functional redundancy in the human microbiome by analyzing its genomic content network — a bipartite graph that links microbes to the genes in their genomes. We find that this network exhibits several topological features that favor high functional redundancy. Furthermore, we develop a simple genome evolution model to generate genomic content network, finding that moderate selection pressure and high horizontal gene transfer rate are necessary to generate genomic content networks with key topological features that favor high functional redundancy. Finally, we analyze data from two published studies of fecal microbiota transplantation (FMT), finding that high functional redundancy of the recipient’s pre-FMT microbiota raises barriers to donor microbiota engraftment. This work elucidates the potential ecological and evolutionary processes that create and maintain functional redundancy in the human microbiome and contribute to its resilience. More... »

PAGES

6217

References to SciGraph publications

  • 2014-07-06. Identification and assembly of genomes and genetic elements in complex metagenomic samples without using reference genomes in NATURE BIOTECHNOLOGY
  • 2008-12-03. A simple model of bipartite cooperation for ecological and organizational networks in NATURE
  • 1994. Redundancy in Ecosystems in BIODIVERSITY AND ECOSYSTEM FUNCTION
  • 2012-06-13. Structure, function and diversity of the healthy human microbiome in NATURE
  • 2015-04-08. Associations between host gene expression, the mucosal microbiome, and clinical outcome in the pelvic pouch of patients with inflammatory bowel disease in GENOME BIOLOGY
  • 2012-09-12. Diversity, stability and resilience of the human gut microbiota in NATURE
  • 2007-06. Importance of species abundance for assessment of trait composition: an example based on pollinator communities in COMMUNITY ECOLOGY
  • 2017-06-19. The resilience of the intestinal microbiota influences health and disease in NATURE REVIEWS MICROBIOLOGY
  • 2011-09-14. Strong contributors to network persistence are the most vulnerable to extinction in NATURE
  • 2010-03. A human gut microbial gene catalogue established by metagenomic sequencing in NATURE
  • 2008-11-30. A core gut microbiome in obese and lean twins in NATURE
  • 2017-10-16. The microbiome beyond the horizon of ecological and evolutionary theory in NATURE ECOLOGY & EVOLUTION
  • 2007-08. Non-random coextinctions in phylogenetically structured mutualistic networks in NATURE
  • 2015-10-30. Diversity of key players in the microbial ecosystems of the human body in SCIENTIFIC REPORTS
  • 1999-05. Nested species subsets, gaps, and discrepancy in OECOLOGIA
  • 2012-06-13. A framework for human microbiome research in NATURE
  • 2016-06-13. Species–function relationships shape ecological properties of the human gut microbiome in NATURE MICROBIOLOGY
  • 1993-12. The measure of order and disorder in the distribution of species in fragmented habitat in OECOLOGIA
  • 2018-04-16. Function and functional redundancy in microbial systems in NATURE ECOLOGY & EVOLUTION
  • 2017-08-03. The evolution of the host microbiome as an ecosystem on a leash in NATURE
  • 2017-02-08. Revised computational metagenomic processing uncovers hidden and biologically meaningful functional variation in the human microbiome in MICROBIOME
  • 2016-12-05. High taxonomic variability despite stable functional structure across microbial communities in NATURE ECOLOGY & EVOLUTION
  • 2017-09-20. Strains, functions and dynamics in the expanded Human Microbiome Project in NATURE
  • 2012-07-16. Microbial interactions: from networks to models in NATURE REVIEWS MICROBIOLOGY
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/s41467-020-19940-1

    DOI

    http://dx.doi.org/10.1038/s41467-020-19940-1

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1133092776

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/33277504


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    356 grid-institutes:grid.9619.7 schema:alternateName Faculty of Agriculture, Food and Environment, Department of Plant Pathology and Microbiology, The Hebrew University of Jerusalem, Jerusalem, Israel
    357 schema:name Faculty of Agriculture, Food and Environment, Department of Plant Pathology and Microbiology, The Hebrew University of Jerusalem, Jerusalem, Israel
    358 rdf:type schema:Organization
     




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