Evidence map›Paper›PMID 42221912›Full record

ArticleISME communications2026

Potential contribution of microbial interaction to stochasticity of microbiota assembly.

Zhong Yu, Yupeng Liu

Abstract read
In one paragraph

Article in ISME communications, 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

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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

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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

2 authors.

Zhong YuSchool of Environmental Science and Engineering, Sun Yat-sen University, Guangzhou 510275, PR China.ORCID https://orcid.org/0000-0001-9881-9708
Yupeng LiuDepartment of Cardiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou 510080,  China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microbial interaction has been widely acknowledged as the deterministic factor for microbiota assembly. However, in the microbial environment, such interactions are highly variable and may lead to the random birth, death, and reproduction of neighboring microbes, potentially contributing to stochastic assembly processes. We have developed a Go-board model to simulate and investigate how microbiota assembly is affected by different types of interacting species, interaction strength, and community structure. The infer Community Assembly Mechanisms by Phylogenetic-bin-based null model analysis (iCAMP) shows that the strong inhibitory effect of deterministic species on stochastic species can lead to a switch of the dominant assembly process from heterogeneous selection to drift. On the other hand, the effects of the inhibition of stochastic species on their deterministic neighbors enhances the relative importance of dispersal limitation in communities with small deterministic populations. The mutual inhibition between deterministic and stochastic species further enhances the stochasticity of microbiota assembly, but this effect is canceled out by the effects of interspecific facilitation and deterministic species with large phylogenetic distance. Our study sheds novel light on the role of microbial interaction in stochastic assembly processes, which is contradictory to the traditional niche-based theory. These findings highlight the importance of assessing interspecific interaction for predicting the true roles of different assembly processes in future studies.

Indexed as

community assemblyiCAMPrelative importancestochastic processvarying interaction

Identifiers

PMID42221912
PMCPMC13219740

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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.