Evidence map›Paper›PMID 42227740›Full record

ArticlemSystems2026

Functional and ecological drivers of bacterial interactions in glacier-fed stream biofilms.

Martina Gonzalez Mateu, Hannes Peter, Grégoire Michoud, David Touchette, Florian Baier, Nicola Deluigi, Richard Jacoby, Michael Zimmermann, Tom J Battin

Abstract read
In one paragraph

Article in mSystems, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

9 authors.

Martina Gonzalez MateuRiver Ecosystems Laboratory, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.ORCID 0000-0003-4321-6875
Hannes PeterRiver Ecosystems Laboratory, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.ORCID 0000-0001-9021-3082
Grégoire MichoudRiver Ecosystems Laboratory, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.ORCID 0000-0003-1071-9900
David TouchetteRiver Ecosystems Laboratory, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.ORCID 0000-0002-1985-9224
Florian BaierRiver Ecosystems Laboratory, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
Nicola DeluigiRiver Ecosystems Laboratory, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
Richard JacobyMolecular Systems Biology Unit, European Molecular Biology Laboratory (EMBL), Meyerhofstrasse 1, Heidelberg, Germany.
Michael ZimmermannMolecular Systems Biology Unit, European Molecular Biology Laboratory (EMBL), Meyerhofstrasse 1, Heidelberg, Germany.
Tom J BattinRiver Ecosystems Laboratory, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.ORCID 0000-0001-5361-2033

Funding

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung 197325
6 · The paper itself

Abstract

Biofilms are the dominant bacterial lifestyle, consisting of matrix-embedded, spatially structured communities where bacteria closely interact and coordinate their behaviors. Despite their ecological significance, the interplay among bacterial taxa that shapes biofilm community dynamics remains poorly characterized. We assessed the nature and drivers of interactions among bacterial strains isolated from a glacier-fed stream biofilm, using phenotyping, genomics, and metabolic fingerprinting. Biofilm bacterial coexistence was frequent (37% of pairs) even among strains with overlapping resource use and close phylogenetic relatedness. Positive interactions were evidenced through metabolic cross-feeding, synergy in biofilm formation, and interspecific biofilm induction. In competitive interactions, where one strain outcompeted the other, the dominant bacteria exhibited oligotrophic traits, such as higher carbon use efficiency, substrate specialization, high-yield strategies, and the production of antagonistic molecules. Our integrated approach demonstrates that efficient growth traits confer a competitive advantage, while widespread metabolic cooperation can facilitate bacterial coexistence. These findings provide critical insights into the forces shaping bacterial interactions and community assembly in stream biofilms.IMPORTANCEBacterial isolates have been extensively used across many systems to investigate how their interactions and traits shape coexistence and competition patterns. However, stream biofilm bacteria, despite forming the foundation of fluvial microbial ecosystems, have rarely been studied beyond their taxonomic composition, although deciphering their interactions is key to understanding ecosystem functioning. Here, we leveraged biofilm isolates from a glacier-fed stream to examine both competitive and positive interactions in co-culture, revealing the nature and key bacterial traits that mediate these interactions. By linking co-culture outcomes to microbial traits, this study uncovers the drivers of bacterial interactions in stream biofilm communities.

Indexed as

BacteriaBacterial Physiological PhenomenaBiofilmsIce CoverMicrobial InteractionsRiversPhylogenybacterial interactionsbiofilmscoexistencecompetitionglacier-fed streamsmetabolic cross-feeding

Identifiers

PMID42227740
PMCPMC13288933

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.