4.6 Article

Metabolic Overlap in Environmentally Diverse Microbial Communities

期刊

FRONTIERS IN GENETICS
卷 10, 期 -, 页码 -

出版社

FRONTIERS MEDIA SA
DOI: 10.3389/fgene.2019.00989

关键词

bioinformatics; metagenomics; microbial communities; metagenome assembled genomes (MAGs); niche; functional redundancy

资金

  1. European Research Council (ERC AG ecomom) [339880]
  2. Netherlands Organisation for Scientific Research (NWO
  3. Gravitation Grant SIAM) [024.002.002]
  4. Netherlands Organisation for Scientific Research (NWO
  5. VIDI grant) [016.Vidi.189.050]

向作者/读者索取更多资源

The majority of microbial communities consist of hundreds to thousands of species, creating a massive network of organisms competing for available resources within an ecosystem. In natural microbial communities, it appears that many microbial species have highly redundant metabolisms and seemingly are capable of utilizing the same substrates. This is paradoxical, as theory indicates that species requiring a common resource should outcompete one another. To better understand why microbial species can coexist, we developed metabolic overlap (MO) as a new metric to survey the functional redundancy of microbial communities at the genome scale across a wide variety of ecosystems. Using metagenome-assembled genomes, we surveyed nearly 1,000 studies across nine ecosystem types. We found the highest MO in extreme (i.e., low pH/high temperature) and aquatic environments, while the lowest MO was observed in communities associated with animal hosts, the built/engineered environment, and soil. In addition, different metabolism subcategories were explored for their degree of MO. For instance, overlap in nitrogen metabolism was among the lowest in animal and engineered ecosystems, while species from the built environment had the highest overlap. Together, we present a metric that utilizes whole genome information to explore overlapping niches of microbes. This provides a detailed picture of potential metabolic competition and cooperation between species present in an ecosystem, indicates the main substrate types sustaining the community, and serves as a valuable tool to generate hypotheses for future research.

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