mBio (Feb 2019)

Host-Microbe Coevolution: Applying Evidence from Model Systems to Complex Marine Invertebrate Holobionts

  • Paul A. O’Brien,
  • Nicole S. Webster,
  • David J. Miller,
  • David G. Bourne

DOI
https://doi.org/10.1128/mBio.02241-18
Journal volume & issue
Vol. 10, no. 1

Abstract

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ABSTRACT Marine invertebrates often host diverse microbial communities, making it difficult to identify important symbionts and to understand how these communities are structured. This complexity has also made it challenging to assign microbial functions and to unravel the myriad of interactions among the microbiota. Here we propose to address these issues by applying evidence from model systems of host-microbe coevolution to complex marine invertebrate microbiomes. Coevolution is the reciprocal adaptation of one lineage in response to another and can occur through the interaction of a host and its beneficial symbiont. A classic indicator of coevolution is codivergence of host and microbe, and evidence of this is found in both corals and sponges. Metabolic collaboration between host and microbe is often linked to codivergence and appears likely in complex holobionts, where microbial symbionts can interact with host cells through production and degradation of metabolic compounds. Neutral models are also useful to distinguish selected microbes against a background population consisting predominately of random associates. Enhanced understanding of the interactions between marine invertebrates and their microbial communities is urgently required as coral reefs face unprecedented local and global pressures and as active restoration approaches, including manipulation of the microbiome, are proposed to improve the health and tolerance of reef species. On the basis of a detailed review of the literature, we propose three research criteria for examining coevolution in marine invertebrates: (i) identifying stochastic and deterministic components of the microbiome, (ii) assessing codivergence of host and microbe, and (iii) confirming the intimate association based on shared metabolic function.

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