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Designing microbial consortia with defined social interactions

Nature Chemical Biology volume 14, pages 821–829 (2018)Cite this article

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Abstract

Designer microbial consortia are an emerging frontier in synthetic biology that enable versatile microbiome engineering. However, the utilization of such consortia is hindered by our limited capacity in rapidly creating ecosystems with desired dynamics. Here we present the development of synthetic communities through social interaction engineering that combines modular pathway reconfiguration with model creation. Specifically, we created six two-strain consortia, each possessing a unique mode of interaction, including commensalism, amensalism, neutralism, cooperation, competition and predation. These consortia follow distinct population dynamics with characteristics determined by the underlying interaction modes. We showed that models derived from two-strain consortia can be used to design three- and four-strain ecosystems with predictable behaviors and further extended to provide insights into community dynamics in space. This work sheds light on the organization of interacting microbial species and provides a systematic framework—social interaction programming—to guide the development of synthetic ecosystems for diverse purposes.

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Fig. 1: Modular pathway reconfiguration for engineering microbial consortia.
Fig. 2: Synthetic consortia with one-way social interactions.
Fig. 3: Synthetic consortia involving two-way social interactions.
Fig. 4: Model-predicted and experimentally measured population dynamics of three-strain ecosystems.
Fig. 5: Model-predicted and experimentally measured population dynamics of four-strain ecosystems.
Fig. 6: Spatial dynamics of three symmetrical communities.

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Acknowledgements

We thank M. Sivaguru, G. Fried and A. Cyphersmith for their help with colony imaging at the IGB Core Facilities at UIUC, and B. Pilas of the Roy J. Carver Biotechnology Center at UIUC for assistance with flow cytometry analysis in this study. We also thank H. Liu, W. van der Donk, X. Yang and A. Blanchard for stimulating discussions and help. This work was supported by the National Science Foundation (1553649, 1227034), the Office of Naval Research (N000141612525), the American Heart Association (12SDG12090025), the Center for Advanced Study at UIUC, National Center for Supercomputing Applications, the Paul G. Allen Frontiers Group, and the Defense Threat Reduction Agency (HDTRA1-14-1-0006).

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Authors and Affiliations

  1. Department of Bioengineering, University of Illinois at Urbana–Champaign, Urbana, IL, USA

    Wentao Kong & Ting Lu

  2. Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana–Champaign, Urbana, IL, USA

    Wentao Kong, David R. Meldgin & Ting Lu

  3. Department of Physics, University of Illinois at Urbana–Champaign, Urbana, IL, USA

    David R. Meldgin & Ting Lu

  4. Institute for Medical Engineering and Science, Department of Biological Engineering, and Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, USA

    James J. Collins

  5. Broad Institute of MIT and Harvard, Cambridge, MA, USA

    James J. Collins

  6. Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA

    James J. Collins

  7. Center for Biophysics and Quantitative Biology, University of Illinois at Urbana–Champaign, Urbana, IL, USA

    Ting Lu

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  1. Wentao Kong
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  2. David R. Meldgin
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Contributions

T.L. and J.J.C. designed the study; T.L. conceived the project; W.K. performed the experiments and collected the data; D.R.M. developed the computational models; W.K., D.R.M. and T.L. analyzed the data; T.L., J.J.C., W.K. and D.R.M. discussed the results and wrote the paper.

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Correspondence to James J. Collins or Ting Lu.

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Kong, W., Meldgin, D.R., Collins, J.J. et al. Designing microbial consortia with defined social interactions. Nat Chem Biol 14, 821–829 (2018). https://doi.org/10.1038/s41589-018-0091-7

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