Quartet: Disentangling positive and negative components of microbial interactions.

Authors

Aamir Faisal Ansari, Gayathri Sambamoorthy, Thrisha C Alexander, Yugandhar B S Reddy, Janhavi Raut, Narendra M Dixit

Published in

PLoS computational biology. Volume 22. Issue 7. Pages e1014502. Jul 10, 2026. Epub Jul 10, 2026.

Abstract

Interspecies interactions are characterized conventionally by the net influence, positive or negative, a species exerts on another. Community ecology theories rely on these net interactions to describe the behaviour of multispecies communities. The net interactions in turn comprise positive and negative components, arising typically from cross-feeding metabolites and competition for resources. The components remain challenging to disentangle, compromising descriptions of community behaviour. Here, we devised a method to estimate the components when metabolic interactions predominate. We conceived a theoretical resource partitioning strategy which when applied to data on species growth rates disentangles the components. Consequently, the net influence a species has on another is decomposed into its positive and negative components. The interactions between a pair of species are thus defined by the 'quartet' of underlying components, specifically the positive and negative components of the net influence of each species on the other. We applied the method to 28 in silico species pairs from a representative oral microbiome and an experimental auxoptroph pair from the literature. We found that positive and negative components had comparable strengths on average. Interestingly, we found species pairs with similar net interactions but disparate components, highlighting the importance of the quartet. Further, weak net interactions could arise from cancellation of strong components. Estimating the quartet helped better understand the complex transitions in community behaviour observed upon varying resource supply in silico and in vitro. The quartet thus offers a more fundamental characterization of interspecies interactions and may help build more reliable community ecology theories, with implications for understanding and design of microbial communities.

PMID:
42430437
Bibliographic data and abstract were imported from PubMed on 11 Jul 2026.

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