Stability of Cross-Feeding Polymorphisms in Microbial Communities
PLoS Computational Biology
Public Library of Science for International Society for Computational Biology (ISCB)
Copyright: © 2016 Gudelj et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Cross-feeding, a relationship wherein one organism consumes metabolites excreted by another, is a ubiquitous feature of natural and clinically-relevant microbial communities and could be a key factor promoting diversity in extreme and/or nutrient-poor environments. However, it remains unclear how readily cross-feeding interactions form, and therefore our ability to predict their emergence is limited. In this paper we developed a mathematical model parameterized using data from the biochemistry and ecology of an E. coli cross-feeding laboratory system. The model accurately captures short-term dynamics of the two competitors that have been observed empirically and we use it to systematically explore the stability of cross-feeding interactions for a range of environmental conditions. We find that our simple system can display complex dynamics including multi-stable behavior separated by a critical point. Therefore whether cross-feeding interactions form depends on the complex interplay between density and frequency of the competitors as well as on the concentration of resources in the environment. Moreover, we find that subtly different environmental conditions can lead to dramatically different results regarding the establishment of cross-feeding, which could explain the apparently unpredictable between-population differences in experimental outcomes. We argue that mathematical models are essential tools for disentangling the complexities of cross-feeding interactions.
IG was supported by a Natural Environment Research Council (NERC) Advanced Fellowship NE/E013007/3 and a European Research Council (ERC) Consolidator grant MathModExp 647292, MK was funded by a National Aeronautics and Space Administration (NASA) NPP Fellowship and NASA NNX12AD87G, IG and PR were funded by a Biotechnology and Biological Sciences Research Council (BBSRC) grant BB/J010340/1, KS was supported by National Human Genome Research Institute (NHGRI) 2R01HG003328 - 07A1 and FR was supported by NASA NNX12AD87G. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
This is the final version of the article. Available from Public Library of Science via the DOI in this record.
Vol. 12 (12), article e1005269
Place of publication