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BSocial: Deciphering Social Behaviors within Mixed Microbial Populations
Jessica Purswani1,2, Rocío C Romero-Zaliz3, Antonio M Martín-Platero2
1Environmental Microbiology Group, Institute of Water Research, University of GranadaGranada, Spain.
Frontiers in Microbiology
|June 10, 2017
Summary
Understanding microbial social interactions is key for effective bioremediation. A new web-tool, BSocial, analyzes these interactions to identify beneficial strain combinations for improved ecosystem function and pollutant degradation.
Area of Science:
- Microbial Ecology
- Bioremediation
- Computational Biology
Background:
- Ecosystem functionality relies on complex population interactions beyond pairwise exchanges.
- Analyzing social behaviors in mixed microbial populations is challenging due to limitations in current tagging and sequencing technologies.
- Existing methods for studying microbial communities are often expensive and time-consuming.
Purpose of the Study:
- To develop a cost-effective and rapid method for analyzing social interactions in microbial communities.
- To introduce a web-tool, BSocial, for predicting and optimizing microbial community composition for specific functions.
- To assess the impact of microbial social behaviors on bioremediation efficiency.
Main Methods:
- Developed a tag-free approach using periodic optical density monitoring of full combinatorial tests of individual strains.
- Calculated growth rates and generations for each strain in various combinations.
- Utilized the BSocial web-tool to analyze community framework and determine social effects (positive, neutral, negative) based on fitness comparisons.
Main Results:
- Identified specific combinations of bacterial strains with positive and neutral social assignations that yielded optimal methyl tert-butyl ether (MTBE) bioremediation.
- Demonstrated that solely focusing on individual strain fitness does not guarantee the best community-level function.
- Showcased that combinations of positive and neutral strains achieved significantly higher MTBE degradation (1.75x) compared to combinations of negative strains.
Conclusions:
- Microbial social interactions significantly influence community productivity and function.
- The BSocial web-tool provides a valuable platform for selecting optimal microbial consortia for bioremediation and other applications.
- Positive and neutral social interactions among microbes enhance bioremediation processes, outperforming negative interactions.
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