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Model-driven design and evolution of non-trivial synthetic syntrophic pairs

C. Lloyd,Zachary A. King,Troy E. Sandberg,Y. Hefner,Connor A. Olson,P. Phaneuf,Edward J. O'Brien,Adam M. Feist

Published 2018 in bioRxiv

ABSTRACT

Synthetic microbial communities are attractive for applied biotechnology and healthcare applications through their ability to efficiently partition complex metabolic functions. By pairing auxotrophic mutants in co-culture, nascent E. coli communities can be established where strain pairs are metabolically coupled. Intuitive synthetic communities have been demonstrated, but the full space of cross-feeding metabolites has yet to be explored. A novel algorithm, OptAux, was constructed to design 66 multi-knockout E. coli auxotrophic strains that require significant metabolite cross-feeding when paired in co-culture. Three OptAux predicted auxotrophic strains were co-cultured with an L-histidine auxotroph and validated via adaptive laboratory evolution (ALE). Time-course sequencing revealed the genetic changes employed by each strain to achieve higher community fitness and provided insights on mechanisms for sharing and adapting to the syntrophic niche. A community model of metabolism and gene expression was utilized to predict the relative community composition and fundamental characteristics of the evolved communities. This work presents a novel computational method to elucidate metabolic changes that empower community formation and thus guide the optimization of co-cultures for a desired application.

PUBLICATION RECORD

  • Publication year

    2018

  • Venue

    bioRxiv

  • Publication date

    2018-05-21

  • Fields of study

    Biology, Computer Science, Engineering, Environmental Science

  • Identifiers
    DOI 10.1101/327270
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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