The impact of interactions on invasion and colonization resistance in microbial communities

PLoS Comput Biol. 2021 Jan 22;17(1):e1008643. doi: 10.1371/journal.pcbi.1008643. eCollection 2021 Jan.

Abstract

In human microbiota, the prevention or promotion of invasions can be crucial to human health. Invasion outcomes, in turn, are impacted by the composition of resident communities and interactions of resident members with the invader. Here we study how interactions influence invasion outcomes in microbial communities, when interactions are primarily mediated by chemicals that are released into or consumed from the environment. We use a previously developed dynamic model which explicitly includes species abundances and the concentrations of chemicals that mediate species interaction. Using this model, we assessed how species interactions impact invasion by simulating a new species being introduced into an existing resident community. We classified invasion outcomes as resistance, augmentation, displacement, or disruption depending on whether the richness of the resident community was maintained or decreased and whether the invader was maintained in the community or went extinct. We found that as the number of invaders introduced into the resident community increased, disruption rather than augmentation became more prevalent. With more facilitation of the invader by the resident community, resistance outcomes were replaced by displacement and augmentation. By contrast, with more facilitation among residents, displacement outcomes shifted to resistance. When facilitation of the resident community by the invader was eliminated, the majority of augmentation outcomes turned into displacement, while when inhibition of residents by invaders was eliminated, invasion outcomes were largely unaffected. Our results suggest that a better understanding of interactions within resident communities and between residents and invaders is crucial to predicting the success of invasions into microbial communities.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Computational Biology
  • Computer Simulation
  • Humans
  • Microbial Interactions / physiology*
  • Microbiota / physiology*
  • Models, Biological
  • Probiotics

Grants and funding

HMK and BM were supported by an Award for Excellence in Biomedical Research from the Smith Family Foundation (https://rssff.org/) and by a start-up grant from Boston College. (www.bc.edu) The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.