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May 31, 2026Nature Communications1 citationsOpen Access

Metabolic feedbacks drive population dynamics and can lead to oscillations among leaf bacteria

APAlan R. PachecoGUGiovanni Stefano UgoliniSRSimon H. Rüdisser

Key Points

  • This research aims to understand how metabolic interactions among leaf bacteria influence population dynamics and ecological outcomes.
  • Employed a microfluidic device for direct cell observation and quantitative metabolite detection.
  • Monitored interactions following plant oligosaccharide degradation by leaf-associated bacteria.
  • Used metabolic modeling to assess the impact of specific molecular mediators on population dynamics.
  • Identified metabolic feedbacks that can lead to either outcompetition or coexistence in bacterial populations.
  • Observed oscillatory population abundances among bacteria linked to specific metabolic interactions.
  • Validated predictions of interaction outcomes derived from metabolic modeling with experimental data.

Abstract

Abstract Metabolic interactions are fundamental to the assembly and function of microbiomes. Yet, our understanding of how specific interaction mechanisms can drive broader ecological outcomes and population dynamics remains limited. Here, we monitor interactions resulting from plant oligosaccharide degradation by leaf-associated bacteria using a microfluidic device that enables direct cell observation and quantitative metabolite detection. This approach enables the identification of key metabolic mediators, revealing recipient-specific patterns of carbon substrate and cofactor complementation. By linking these patterns to emergent dynamics observed between pairs of bacteria, we identify metabolically driven feedbacks that could lead to a variety of ecological outcomes – from outcompetition to coexistence characterized by oscillating population abundances. Investigating these observations with metabolic modeling allows us to systematically assess the impact of specific molecular mediators on population dynamics, yielding predictions of interaction outcomes that we validate experimentally. Our results provide a detailed mapping of metabolic mechanisms to emergent population trajectories among environmental microbes and help inform strategies for designing microbiomes with desired steady states.

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Cite This Study

Pacheco et al. (2026) studied this question.

synapsesocial.com/papers/6a1bd0df5783ba022b6fc979https://doi.org/10.1038/s41467-026-73686-w
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