Guided by Microbes: Applying Community Coalescence Principles for Predictive Microbiome Engineering
Every seed germinating in soils, wastewater treatment, and stream confluence exemplify microbial community coalescence-the blending of previously isolated communities. Here, we present theoretical and experimental knowledge on how separated microbial communities mix, with particular focus on managed...
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Published in: | mSystems Vol. 6; no. 4; p. e0053821 |
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Main Authors: | , , , , |
Format: | Journal Article |
Language: | English |
Published: |
United States
American Society for Microbiology
31-08-2021
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Subjects: | |
Online Access: | Get full text |
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Summary: | Every seed germinating in soils, wastewater treatment, and stream confluence exemplify microbial community coalescence-the blending of previously isolated communities. Here, we present theoretical and experimental knowledge on how separated microbial communities mix, with particular focus on managed ecosystems. We adopt the community coalescence framework, which integrates metacommunity theory and meta-ecosystem dynamics, and highlight the prevalence of these coalescence events within microbial systems. Specifically, we (i) describe fundamental types of community coalescences using naturally occurring and managed examples, (ii) offer ways forward to leverage community coalescence in managed systems, and (iii) emphasize the importance of microbial ecological theory to achieving desired coalescence outcomes. Further, considering the massive dispersal events of microbiomes and their coalescences is pivotal to better predict microbial community dynamics and responses to disturbances. We conclude our piece by highlighting some challenges and unanswered question yet to be tackled. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 PMCID: PMC8407356 Citation Rocca JD, Muscarella ME, Peralta AL, Izabel-Shen D, Simonin M. 2021. Guided by microbes: applying community coalescence principles for predictive microbiome engineering. mSystems 6:e00538-21. https://doi.org/10.1128/mSystems.00538-21. |
ISSN: | 2379-5077 2379-5077 |
DOI: | 10.1128/mSystems.00538-21 |