Lotka-Volterra pairwise modeling fails to capture diverse pairwise microbial interactions

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Abstract

Pairwise models are commonly used to describe many-species communities. In these models, an individual receives additive fitness effects from pairwise interactions with each species in the community ('additivity assumption'). All pairwise interactions are typically represented by a single equation where parameters reflect signs and strengths of fitness effects ('universality assumption'). Here, we show that a single equation fails to qualitatively capture diverse pairwise microbial interactions. We build mechanistic reference models for two microbial species engaging in commonly-found chemical-mediated interactions, and attempt to derive pairwise models. Different equations are appropriate depending on whether a mediator is consumable or reusable, whether an interaction is mediated by one or more mediators, and sometimes even on quantitative details of the community (e.g. relative fitness of the two species, initial conditions). Our results, combined with potential violation of the additivity assumption in many-species communities, suggest that pairwise modeling will often fail to predict microbial dynamics.

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Babak Momeni

Division of Basic Sciences, Fred Hutchinson Cancer Research Center, Seattle, United States

For correspondence
momeni@bc.edu

Competing interests
No competing interests declared.

"This ORCID iD identifies the author of this article:" 0000-0003-1271-5196
Li Xie

Division of Basic Sciences, Fred Hutchinson Cancer Research Center, Seattle, United States

Competing interests
No competing interests declared.
Wenying Shou

Division of Basic Sciences, Fred Hutchinson Cancer Research Center, Seattle, United States

Competing interests
Wenying Shou, Reviewing editor, eLife.

Funding

Boston College

Babak Momeni

NIH Office of the Director

Babak Momeni
Li Xie
Wenying Shou

W. M. Keck Foundation

Babak Momeni
Wenying Shou

Fred Hutchinson Cancer Research Center

Li Xie
Wenying Shou

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

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This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.