Metabolic interactions affect the biomass of synthetic bacterial biofilm communities

Co-occurrence network analysis is an effective tool for predicting complex networks of microbial interactions in the natural environment. Using isolates from a rhizosphere, we constructed multi-species biofilm communities and investigated co-occurrence patterns between microbial species in genome-sc...

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Bibliographic Details
Published inmSystems Vol. 8; no. 6; p. e0104523
Main Authors Sun, Xinli, Xie, Jiyu, Zheng, Daoyue, Xia, Riyan, Wang, Wei, Xun, Weibing, Huang, Qiwei, Zhang, Ruifu, Kovács, Ákos T, Xu, Zhihui, Shen, Qirong
Format Journal Article
LanguageEnglish
Published United States American Society for Microbiology 21.12.2023
Subjects
Bacteria - genetics
Biofilms
Biomass
Community composition
Environment
Environmental Microbiology
Genomes
Keystone species
metabolic modeling
Metabolism
Microbial Interactions
network analysis
Pellicle
Research Article
Rhizosphere
soil microbiology
SynComs
Variance analysis
network analysis
soil microbiology
biofilms
SynComs
metabolic modeling
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Summary:Co-occurrence network analysis is an effective tool for predicting complex networks of microbial interactions in the natural environment. Using isolates from a rhizosphere, we constructed multi-species biofilm communities and investigated co-occurrence patterns between microbial species in genome-scale metabolic models and in vitro experiments. According to our results, metabolic exchanges and resource competition may partially explain the co-occurrence network analysis results found in synthetic bacterial biofilm communities.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
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The authors declare no conflict of interest.
Xinli Sun and Jiyu Xie contributed equally to this article. Author order was determined by seniority.
ISSN:2379-5077
2379-5077
DOI:10.1128/msystems.01045-23