ArticleISME communications2026
Microbial cohorts: bringing ecological meaning to the modularity concept of co-occurrence networks.
Article in ISME communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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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.
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Who cites it
1 citing paper in PubMed.
- Packing Density Governs Tobacco Quality Through Microbial Community Assembly and Metabolic Reprogramming.Microorganisms · 2026Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Microbial communities are structured through complex interactions that are difficult to observe directly. Co-occurrence networks offer a way to infer community structure, revealing (not exclusively) potential biotic interactions. Such networks have been inferred for diverse biomes and repeatedly found to be modular, yet the ecological significance of this modularity remains underexplored. We tested whether clusters within co-occurrence networks ("cohorts"), are universal and ecologically meaningful units by assessing their ubiquity, stability, and environmental specificity across diverse ecosystems. Our meta-analysis spans 25 previously published 16S rRNA gene amplicon sequencing datasets (14 160 samples) and covers high environmental variability ranging from aquatic, terrestrial to anthropogenic environments. Microbial co-occurrence networks consistently exhibited high modularity across biomes. Inferred cohorts were ubiquitous and represented up to 90% of the community composition. Our findings demonstrate that modularity is a fundamental and generalizable feature of microbial community organization, indicating the existence of stable subcommunities. Highly similar cohorts were inferred even across different, unconnected environments and datasets, and showed consistent responses to environmental gradients, indicating that their composition is to a large degree deterministic and predictable. The overall cohort structure and environmental preferences were independent of the sample size and the inference algorithm, underlining the robustness and applicability of the results. Recognizing these microbial cohorts as a meaningful level of microbial organization will refine microbial community ecology, cultivation strategies, and predictive modelling of microbial dynamics.
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