Evidence map›Paper›PMID 42502970›Full record

ReviewThe ISME journal2026

Influence of cell-cell distance on the ecology and evolution of microbial communities.

Ailin Huang, Divvya Ramesh, Yong Nie, Kun Zhao, Miaoxiao Wang

Abstract readReview
In one paragraph

Review 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

5 authors.

Ailin HuangInstitute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, China.ORCID 0009-0009-2541-0296
Divvya RameshDepartment of Environmental Microbiology, Eawag - Swiss Federal Institute of Aquatic Science and Technology, 8600  Dübendorf, Switzerland.
Yong NieSchool of Mechanics and Engineering Science, Peking University, Beijing 100871, China.ORCID 0000-0002-5940-1218
Kun ZhaoThe Sichuan Provincial Key Laboratory for Human Disease Gene Study and The Institute of Laboratory Medicine, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, China.ORCID 0000-0003-3928-1981
Miaoxiao WangInstitute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, China.ORCID 0000-0002-4636-0058

Funding

National Key R&D Program of China 2025YFA0921700
6 · The paper itself

Abstract

Microorganisms assemble into spatially structured communities in which neighboring cells are separated by highly heterogeneous cell-cell distances. These spatial distances are not merely geometric features but key ecological variables that determine whether cells can exchange metabolites, compete through toxins, sense one another, or transfer genes, thereby profoundly influencing community assembly, productivity, and the evolution of microorganisms residing in communities. In this review, we synthesize recent progress on how cell-cell distance in microbial communities is determined, as well as how it modulates microbial interactions that lead to diverse ecological and evolutionary consequences. Specifically, we propose several testable conceptual frameworks that help quantify complicated distance-interaction relationships. We discuss emerging imaging, automated analysis, and spatial engineering approaches that now make it possible to quantify and manipulate cell-cell distance with increasing precision. Viewing microbial communities through the lens of cell-cell distance provides a unifying framework for linking microscale spatial organization to microbiome function, offering new opportunities to predict and engineer microbial communities.

Indexed as

Biological EvolutionMicrobial InteractionsMicrobiotaBacteriaEcologycell–cell distancemicrobial communitiesmicrobial evolutionmicrobial interactionsspatial ecology

Identifiers

PMID42502970
PMCPMC13557118

What OpenQuestion holds

Textmetadata
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.