ReviewThe ISME journal2026
Influence of cell-cell distance on the ecology and evolution of microbial communities.
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.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
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
Identifiers
What OpenQuestion holds
Registered trials
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.