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Updated: Jan 14, 2026

A Hydroponic Co-cultivation System for Simultaneous and Systematic Analysis of Plant/Microbe Molecular Interactions and Signaling
Published on: July 22, 2017
Strong pairwise interactions do not drive interactions in a plant leaf associated microbial community
Franziska Höhn1,2, Vasvi Chaudhry3, Caner Bağci1
1Translational Genome Mining for Natural Products, Interfaculty Institute of Microbiology and Infection Medicine and Institute for Bioinformatics and Medical Informatics, University of Tübingen, 72076 Tübingen, Germany.
Abstract:
Microbial communities that promote plant growth show promise in reducing the impacts of climate change on plant health and productivity. Understanding microbe-microbe interactions in a community context is paramount for designing effective microbial consortia that enhance plant resilience. In this study, we investigated the dynamics of a synthetic microbial community (SynCom) assembled from Arabidopsis thaliana leaves to elucidate factors shaping community composition and stability. We found notable disparities between in vitro pairwise interactions and those inferred from correlation networks in planta. Our findings suggested that secondary metabolites, particularly antimicrobials, might mediate interactions in vitro, but are not key drivers of microbial interactions in a community context. Through co-cultivation experiments, we identified the siderophore pseudobactin as a potent antimicrobial agent against several SynCom members, but its impact on community composition in planta was negligible. Notably, dominant SynCom members, such as Pseudomonas koreensis, Flavobacterium pectinovorum, and Sporobolomyces roseus, exhibited only positive correlations, suggesting synergism based on factors such as exopolysaccharides and biotransformation might drive community dynamics rather than competition. Two correlations between SynCom members in the co-abundance network corresponded to their pairwise in vitro interactions, highlighting the potential for further research and demonstrating the usefulness of correlation networks in identifying key microbe-microbe interactions. Our findings highlight the importance of considering microbiome-wide interaction studies and synthetic communities in understanding and manipulating plant microbiomes.
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