Evidence map›Paper›PMID 40838740›Full record

ReviewThe ISME journal2025

Individual-based modeling unravels spatial and social interactions in bacterial communities.

Jian Wang, Ihab Hashem, Satyajeet Bhonsale, Jan F M Van Impe

Abstract readReview
In one paragraph

Review in The ISME journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
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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

4 authors.

Jian WangBioTeC+, Chemical and Biochemical Process Technology and Control, Department of Chemical Engineering, Faculty of Engineering Technology, KU Leuven, 9000 Ghent, Belgium.
Ihab HashemBioTeC+, Chemical and Biochemical Process Technology and Control, Department of Chemical Engineering, Faculty of Engineering Technology, KU Leuven, 9000 Ghent, Belgium.
Satyajeet BhonsaleBioTeC+, Chemical and Biochemical Process Technology and Control, Department of Chemical Engineering, Faculty of Engineering Technology, KU Leuven, 9000 Ghent, Belgium.
Jan F M Van ImpeBioTeC+, Chemical and Biochemical Process Technology and Control, Department of Chemical Engineering, Faculty of Engineering Technology, KU Leuven, 9000 Ghent, Belgium.

Funding

European Union's Horizon 2020 research and innovation program 956126European Union's Horizon Europe research and innovation program 101058422
6 · The paper itself

Abstract

Bacterial interactions are fundamental in shaping community structure and function, driving processes that range from plastic degradation in marine ecosystems to dynamics within the human gut microbiome. Yet, studying these interactions is challenging due to difficulties in resolving spatiotemporal scales, quantifying interaction strengths, and integrating intrinsic cellular behaviors with extrinsic environmental conditions. Individual-based modeling addresses these challenges through single-cell-level simulations that explicitly model growth, division, motility, and environmental responses. By capturing both the spatial organization and social interactions, individual-based modeling reveals how microbial interactions and environmental gradients collectively shape community architecture, species coexistence, and adaptive responses. In particular, individual-based modeling provides mechanistic insights into how social behaviors-such as competition, metabolic cooperation, and quorum sensing-are regulated by spatial structure, uncovering the interplay between localized interactions and emergent community properties. In this review, we synthesize recent applications of individual-based modeling in studying bacterial spatial and social interactions, highlighting how their interplay governs community stability, diversity, and resilience. By linking individual-scale interactions with the ecosystem-level organization, individual-based modeling offers a predictive framework for understanding microbial ecology and informing strategies for controlling and engineering bacterial consortia in both natural and applied settings.

Indexed as

BacteriaBacterial Physiological PhenomenaMicrobial InteractionsMicrobiotaModels, BiologicalEcosystemHumansQuorum Sensingadaptive strategiesindividual-based modeling (IbM)individual variabilitymetabolic cooperationniche differentiationresource gradientsocial interactionsspatial heterogeneityspatial interactions

Identifiers

PMID40838740
PMCPMC12411854

What OpenQuestion holds

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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.