PLoS Biology (Jun 2019)

Neutrality in the Metaorganism.

  • Michael Sieber,
  • Lucía Pita,
  • Nancy Weiland-Bräuer,
  • Philipp Dirksen,
  • Jun Wang,
  • Benedikt Mortzfeld,
  • Sören Franzenburg,
  • Ruth A Schmitz,
  • John F Baines,
  • Sebastian Fraune,
  • Ute Hentschel,
  • Hinrich Schulenburg,
  • Thomas C G Bosch,
  • Arne Traulsen

DOI
https://doi.org/10.1371/journal.pbio.3000298
Journal volume & issue
Vol. 17, no. 6
p. e3000298

Abstract

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Almost all animals and plants are inhabited by diverse communities of microorganisms, the microbiota, thereby forming an integrated entity, the metaorganism. Natural selection should favor hosts that shape the community composition of these microbes to promote a beneficial host-microbe symbiosis. Indeed, animal hosts often pose selective environments, which only a subset of the environmentally available microbes are able to colonize. How these microbes assemble after colonization to form the complex microbiota is less clear. Neutral models are based on the assumption that the alternatives in microbiota community composition are selectively equivalent and thus entirely shaped by random population dynamics and dispersal. Here, we use the neutral model as a null hypothesis to assess microbiata composition in host organisms, which does not rely on invoking any adaptive processes underlying microbial community assembly. We show that the overall microbiota community structure from a wide range of host organisms, in particular including previously understudied invertebrates, is in many cases consistent with neutral expectations. Our approach allows to identify individual microbes that are deviating from the neutral expectation and are therefore interesting candidates for further study. Moreover, using simulated communities, we demonstrate that transient community states may play a role in the deviations from the neutral expectation. Our findings highlight that the consideration of neutral processes and temporal changes in community composition are critical for an in-depth understanding of microbiota-host interactions.