Evidence map›Paper›PMID 41711091›Full record

ArticleThe ISME journal2026

Sensitivity of microbial spatial self-organization to surface friction depends on metabolic interactions.

Philipp Tandler, David R Johnson, Guram Gogia

Abstract read
In one paragraph

Article in The ISME journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Philipp TandlerDepartment of Environmental Systems Science, Swiss Federal Institute of Technology (ETH), 8092 Zürich, Switzerland.
David R JohnsonDepartment of Environmental Microbiology, Swiss Federal Institute of Aquatic Science and Technology (Eawag), 8600 Dübendorf, Switzerland.ORCID 0000-0002-6728-8462
Guram GogiaDepartment of Environmental Systems Science, Swiss Federal Institute of Technology (ETH), 8092 Zürich, Switzerland.

Funding

Swiss National Science Foundation 310030_207471
6 · The paper itself

Abstract

Self-organizing spatial patterns are ubiquitous in microbial ecosystems, yet their sensitivity to environmental conditions remains poorly understood. Understanding spatial pattern sensitivity is particularly relevant for surface-associated microbial systems, as their functioning depends on how different cell-types self-organize across space as a consequence of their traits and environmental conditions. Here, we integrate principles from microbial systems ecology with self-organization theory to understand how environmental conditions and biotic interactions shape the sensitivity of emergent spatial intermixing, which is a critical feature of spatial patterns. Using denitrifying strains of the bacterium Stutzerimonas stutzeri that engage in negative (competitive) or positive (cross-feeding) interactions, we demonstrate that spatial intermixing emerging from positive interactions is more sensitive to environmental conditions than that emerging from negative interactions. We further develop and quantify the spatial intermixing strength as a key descriptor of spatial pattern sensitivity, revealing that high short-range dispersal and strong biotic interdependence promote persistent spatial intermixing. Our findings highlight that ecosystem sensitivity to environmental conditions can be inferred from features of emergent spatial patterns, providing a quantitative framework for understanding how environmental and biological factors jointly govern ecosystem assembly and dynamics.

Indexed as

Microbial InteractionsPseudomonas stutzeriEcosystemdispersalecosystem sensitivitymicrobial communitiesmicrobial interactionsself-organizationspatial patterns

Identifiers

PMID41711091
PMCPMC12978657

What OpenQuestion holds

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Registered trials

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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.