Evidence map›Paper›PMID 40244660›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2025

Dynamic coexistence driven by physiological transitions in microbial communities.

Avaneesh V Narla, Terence Hwa, Arvind Murugan

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Article
  2. Minimizing co-growth as a broad predictor of community robustness.bioRxiv : the preprint server for biology · 2026
    Article
  3. Review
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Avaneesh V NarlaDepartment of Physics, University of California, San Diego, La Jolla, CA 92093-0319.ORCID 0000-0002-9328-8271
Terence HwaDepartment of Physics, University of California, San Diego, La Jolla, CA 92093-0319.ORCID 0000-0003-1837-6842
Arvind MuruganDepartment of Physics, University of Chicago, Chicago, IL 60637.

Funding

Quantitative Systemic Studies of Bacterial PhysiologyR35GM152133 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI TERENCE HWA · 2024 to 2026
$1.8M
Revealing mechanisms of specificity and adaptability in molecular information processing through data-driven modelsR35GM151211 · NIGMS · UNIVERSITY OF CHICAGO · PI Arvind Murugan · 2023 to 2026
$1.5M
HHS | NIH | National Institute of General Medical Sciences (NIGMS) R35GM151211NIGMS NIH HHS R35 GM151211NIGMS NIH HHS R35 GM152133NSF | BIO | Division of Molecular and Cellular Biosciences (MCB) 2029480NSF | MPS | Division of Physics (PHY) 2317138Simons Foundation (SF) 542387
6 · The paper itself

Abstract

Microbial ecosystems are commonly modeled by fixed interactions between species in steady exponential growth states. However, microbes in exponential growth often modify their environments so strongly that they are forced out of the growth state into stressed, nongrowing states. Such dynamics are typical of ecological succession in nature and serial-dilution cycles in the laboratory. Here, we introduce a phenomenological model, the Community State Model, to gain insight into the dynamic coexistence of microbes due to changes in their physiological states during cyclic succession. Our model specifies the growth preference of each species along a global ecological coordinate, taken to be the biomass density of the community, but is otherwise agnostic to specific interactions (e.g., nutrient starvation, stress, aggregation), in order to focus on self-consistency conditions on combinations of physiological states, "community states," in a stable ecosystem. We identify three key features of such dynamical communities that contrast starkly with steady-state communities: enhanced community stability through staggered dominance of different species in different community states, increased tolerance of community diversity to fast growing species dominating distinct community states, and increased requirement of growth dominance by late-growing species. These features, derived explicitly for simplified models, are proposed here as principles aiding the understanding of complex dynamical communities. Our model shifts the focus of ecosystem dynamics from bottom-up studies based on fixed, idealized interspecies interaction to top-down studies based on accessible macroscopic observables such as growth rates and total biomass density, enabling quantitative examination of community-wide characteristics.

Indexed as

EcosystemMicrobial InteractionsMicrobiotaModels, BiologicalBacteriaBiomassbacterial physiologycommunity assemblyecological successionmicrobial ecology

Identifiers

PMID40244660
PMCPMC12037064

What OpenQuestion holds

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LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.