4.6 Article

Synthetic microbial consortia with programmable ecological interactions

Journal

METHODS IN ECOLOGY AND EVOLUTION
Volume 13, Issue 7, Pages 1608-1621

Publisher

WILEY
DOI: 10.1111/2041-210X.13894

Keywords

cross-feeding; engineered microbial consortia; population dynamics; quorum sensing; species interaction; synthetic ecology

Categories

Funding

  1. National Natural Science Foundation of China [32025024, 32101246, 91951107]
  2. Fundamental Research Funds for the Central Universities [K20200026]

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This study developed a microbial experimental system that allows for rapidly generating microbial consortia with programmable ecological interactions. By using engineered microbial consortia, the researchers showed different population dynamics under different initial inoculation conditions and controlled the transitions between exploitation, competition, and synergy by tuning the engineered modules. Mathematical models were derived to quantitatively capture the experimentally observed population dynamics of these synthetic microbial consortia.
Central to the composition, structure and function of any microbial community is the complex species interaction web. But understanding the overwhelming complexity of ecological interaction webs has been challenging, owing at least partly to the lack of efficient tools for disentangling species interactions in natural or artificial microbial communities. In this study, we developed a microbial experimental system which allows for rapidly generating microbial consortia with programmable ecological interactions. We engineered the model organism Escherichia coli to construct metabolism- and quorum sensing-based modules. The two engineered modules were used to create synthetic microbial consortia of synergy, competition and exploitation. We showed that each of synthetic microbial consortia displayed the unique mode of population dynamics under certain initial inoculation conditions. We also demonstrated that the transitions between exploitation and the types of competition or synergy based on the same paired strains were plausible by tuning the two engineered modules. We lastly derived mathematical models to quantitatively capture the experimentally observed population dynamics of these synthetic microbial consortia. This approach offers a fresh angle to engineering microbial systems for experimentally testing ecological questions with a much greater control and manipulation.

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