MassIVE MSV000086551

Partial Public PXD022897

Formation and characterization of emergent microbial communities

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Description

Microbial communities colonize plant tissues and contribute to host function. How these communities form and how individual members contribute to shaping the microbial community are not well understood. Synthetic microbial communities, where defined individual isolates are combined, can serve as valuable model systems for uncovering the organizational principles of communities. Using genome-defined organisms, systematic analysis by computationally-based network reconstruction can lead to mechanistic insights and the metabolic interactions between species. In this study, 10 bacterial strains isolated from the Populus deltoides rhizosphere were combined and passaged in two different media environments to form a stable microbial community. The membership and relative abundances of the strains stabilized after around 5 growth cycles and resulted in just a few dominant strains. To unravel the underlying metabolic interactions, the KBase platform was used for constructing community-level models and for elucidating the metabolic processes involved in shaping the microbial communities. These analyses were complemented by growth curves of the individual isolates, pairwise interaction screens, and metaproteomics of the community. Flux balance analysis was used to model the metabolic potential in the microbial community and identify potential metabolic exchanges among the component species. Revealing the mechanisms of interaction among plant-associated microorganisms will provide insights into strategies for engineering microbial communities that can potentially increase plant growth and disease resistance. Further, deciphering the membership and metabolic potentials of a bacterial community will enable the design of synthetic co-cultures with desired biological functions. [doi:10.25345/C5G79P] [dataset license: CC0 1.0 Universal (CC0 1.0)]

Keywords: microbial community ; microbiome ; metaproteomics ; rhizosphere bacteria

Contact

Principal Investigators:
(in alphabetical order) 		Mitchel J. Doktycz, Oak Ridge National Laboratory, USA
Submitting User: pabraham_ornl
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Distinct protein accessions are counted across all files submitted in the "Statistical Analysis of Quantified Analytes" category having a "Protein" column in this dataset.

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Number of distinct proteins found to be differentially abundant in at least one comparison across all analyses (original submission and reanalyses) associated with this dataset.

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Distinct protein accessions are counted across all files submitted in the "Statistical Analysis of Quantified Analytes" category having a "Protein" column in this dataset.

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