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Inferring Resource Competition in Microbial Communities from Time Series

Xiaowen Chen1, Kyle Crocker2,3,4, Seppe Kuehn2,3,4,5,*,†, Aleksandra M. Walczak1,4,*,‡, and Thierry Mora1,4,*,§

  • *These authors contributed equally to this work.
  • †Contact author: seppekuehn@uchicago.edu
  • ‡Contact author: aleksandra.walczak@phys.ens.fr
  • §Contact author: thierry.mora@phys.ens.fr
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PRX Life 3, 023019 – Published 30 June, 2025

DOI: https://doi.org/10.1103/8gkj-rdzy

Abstract

The competition for resources is a defining feature of microbial communities. In many contexts, from soils to host-associated communities, highly diverse microbes are organized into metabolic groups or guilds with similar resource preferences. The resource preferences of individual taxa that give rise to these guilds are critical for understanding fluxes of resources through the community and the structure of diversity in the system. However, inferring the metabolic capabilities of individual taxa, as well as their competition with other taxa, within a community is challenging and unresolved. Here we address this gap in knowledge by leveraging dynamic measurements of abundances in communities. We show that simple correlations are often misleading in predicting resource competition. We show that spectral methods such as the cross-power spectral density and coherence that account for time-delayed effects are superior metrics for inferring the structure of resource competition in communities. We demonstrate this fact on synthetic data generated from consumer-resource models with time-dependent resource availability, where taxa are organized into groups or guilds with similar resource preferences. By applying spectral methods to oceanic plankton time-series data, we demonstrate that these methods detect interaction structures among species with similar genomic sequences. Our results indicate that analyzing temporal data across multiple timescales can reveal the underlying structure of resource competition within communities.

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PRX Life 3, 023019– Published 30 June, 2025
  • Received 17 January 2025
  • Accepted 28 May 2025
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Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.

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