Designing microbial consortia with defined social interactions


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.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

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.


  1. 1.

    Brenner, K., You, L. & Arnold, F. H. Engineering microbial consortia: a new frontier in synthetic biology. Trends Biotechnol. 26, 483–489 (2008).

    CAS  Article  Google Scholar 

  2. 2.

    Großkopf, T. & Soyer, O. S. Synthetic microbial communities. Curr. Opin. Microbiol. 18, 72–77 (2014).

    Article  Google Scholar 

  3. 3.

    De Roy, K., Marzorati, M., Van den Abbeele, P., Van de Wiele, T. & Boon, N. Synthetic microbial ecosystems: an exciting tool to understand and apply microbial communities. Environ. Microbiol. 16, 1472–1481 (2014).

    Article  Google Scholar 

  4. 4.

    Bittihn, P., Din, M. O., Tsimring, L. S. & Hasty, J. Rational engineering of synthetic microbial systems: from single cells to consortia. Curr. Opin. Microbiol. 45, 92–99 (2018).

    CAS  Article  Google Scholar 

  5. 5.

    Weber, W., Daoud-El Baba, M. & Fussenegger, M. Synthetic ecosystems based on airborne inter- and intrakingdom communication. Proc. Natl Acad. Sci. USA 104, 10435–10440 (2007).

    CAS  Article  Google Scholar 

  6. 6.

    Balagaddé, F. K. et al. A synthetic Escherichia coli predator-prey ecosystem. Mol. Syst. Biol. 4, 187 (2008).

    Article  Google Scholar 

  7. 7.

    Chen, Y., Kim, J. K., Hirning, A. J., Josić, K. & Bennett, M. R. Emergent genetic oscillations in a synthetic microbial consortium. Science 349, 986–989 (2015).

    CAS  Article  Google Scholar 

  8. 8.

    Gore, J., Youk, H. & van Oudenaarden, A. Snowdrift game dynamics and facultative cheating in yeast. Nature 459, 253–256 (2009).

    CAS  Article  Google Scholar 

  9. 9.

    Chuang, J. S., Rivoire, O. & Leibler, S. Simpson’s paradox in a synthetic microbial system. Science 323, 272–275 (2009).

    CAS  Article  Google Scholar 

  10. 10.

    Mee, M. T., Collins, J. J., Church, G. M. & Wang, H. H. Syntrophic exchange in synthetic microbial communities. Proc. Natl Acad. Sci. USA 111, E2149–E2156 (2014).

    CAS  Article  Google Scholar 

  11. 11.

    Wintermute, E. H. & Silver, P. A. Emergent cooperation in microbial metabolism. Mol. Syst. Biol. 6, 407 (2010).

    Article  Google Scholar 

  12. 12.

    Zhou, K., Qiao, K., Edgar, S. & Stephanopoulos, G. Distributing a metabolic pathway among a microbial consortium enhances production of natural products. Nat. Biotechnol. 33, 377–383 (2015).

    CAS  Article  Google Scholar 

  13. 13.

    Minty, J. J. et al. Design and characterization of synthetic fungal-bacterial consortia for direct production of isobutanol from cellulosic biomass. Proc. Natl Acad. Sci. USA 110, 14592–14597 (2013).

    CAS  Article  Google Scholar 

  14. 14.

    Hood, L. Tackling the microbiome. Science 336, 1209 (2012).

    CAS  Article  Google Scholar 

  15. 15.

    Cho, I. & Blaser, M. J. The human microbiome: at the interface of health and disease. Nat. Rev. Genet. 13, 260–270 (2012).

    CAS  Article  Google Scholar 

  16. 16.

    Falkowski, P. G., Fenchel, T. & Delong, E. F. The microbial engines that drive Earth’s biogeochemical cycles. Science 320, 1034–1039 (2008).

    CAS  Article  Google Scholar 

  17. 17.

    Berendsen, R. L., Pieterse, C. M. & Bakker, P. A. The rhizosphere microbiome and plant health. Trends Plant Sci. 17, 478–486 (2012).

    CAS  Article  Google Scholar 

  18. 18.

    Faust, K. & Raes, J. Microbial interactions: from networks to models. Nat. Rev. Microbiol. 10, 538–550 (2012).

    CAS  Article  Google Scholar 

  19. 19.

    Shou, W., Ram, S. & Vilar, J. M. Synthetic cooperation in engineered yeast populations. Proc. Natl Acad. Sci. USA 104, 1877–1882 (2007).

    CAS  Article  Google Scholar 

  20. 20.

    Brenner, K., Karig, D. K., Weiss, R. & Arnold, F. H. Engineered bidirectional communication mediates a consensus in a microbial biofilm consortium. Proc. Natl Acad. Sci. USA 104, 17300–17304 (2007).

    CAS  Article  Google Scholar 

  21. 21.

    Hasty, J., McMillen, D. & Collins, J. J. Engineered gene circuits. Nature 420, 224–230 (2002).

    CAS  Article  Google Scholar 

  22. 22.

    Endy, D. Foundations for engineering biology. Nature 438, 449–453 (2005).

    CAS  Article  Google Scholar 

  23. 23.

    Andrianantoandro, E., Basu, S., Karig, D. K. & Weiss, R. Synthetic biology: new engineering rules for an emerging discipline. Mol. Syst. Biol. 2, 2006.0028 (2006).

    Article  Google Scholar 

  24. 24.

    Arkin, A. Setting the standard in synthetic biology. Nat. Biotechnol. 26, 771–774 (2008).

    CAS  Article  Google Scholar 

  25. 25.

    Brophy, J. A. & Voigt, C. A. Principles of genetic circuit design. Nat. Methods 11, 508–520 (2014).

    CAS  Article  Google Scholar 

  26. 26.

    Collins, J. J. et al. Synthetic biology: how best to build a cell. Nature 509, 155–157 (2014).

    Article  Google Scholar 

  27. 27.

    Purnick, P. E. & Weiss, R. The second wave of synthetic biology: from modules to systems. Nat. Rev. Mol. Cell Biol. 10, 410–422 (2009).

    CAS  Article  Google Scholar 

  28. 28.

    Hartwell, L. H., Hopfield, J. J., Leibler, S. & Murray, A. W. From molecular to modular cell biology. Nature 402, C47–C52 (1999).

    CAS  Article  Google Scholar 

  29. 29.

    Lubelski, J., Rink, R., Khusainov, R., Moll, G. N. & Kuipers, O. P. Biosynthesis, immunity, regulation, mode of action and engineering of the model lantibiotic nisin. Cell. Mol. Life Sci. 65, 455–476 (2008).

    CAS  Article  Google Scholar 

  30. 30.

    Stoddard, G. W., Petzel, J. P., van Belkum, M. J., Kok, J. & McKay, L. L. Molecular analyses of the lactococcin A gene cluster from Lactococcus lactis subsp. lactis biovar diacetylactis WM4. Appl. Environ. Microbiol. 58, 1952–1961 (1992).

    CAS  PubMed  PubMed Central  Google Scholar 

  31. 31.

    West, S. A., Diggle, S. P., Buckling, A., Gardner, A. & Griffin, A. S. The social lives of microbes. Annu. Rev. Ecol. Evol. Syst. 38, 53–77 (2007).

    Article  Google Scholar 

  32. 32.

    Foster, K. R. in Social Behaviour: Genes, Ecology and Evolution 331–356 (Cambridge Univ. Press, Cambridge, UK, 2010).

  33. 33.

    Xavier, J. B. Social interaction in synthetic and natural microbial communities. Mol. Syst. Biol. 7, 483 (2011).

    Article  Google Scholar 

  34. 34.

    Kong, W., Kapuganti, V. S. & Lu, T. A gene network engineering platform for lactic acid bacteria. Nucleic Acids Res. 44, e37 (2016).

    Article  Google Scholar 

  35. 35.

    Kong, W. & Lu, T. Cloning and optimization of a nisin biosynthesis pathway for bacteriocin harvest. ACS Synth. Biol. 3, 439–445 (2014).

    CAS  Article  Google Scholar 

  36. 36.

    Volterra, V. Variations and fluctuations of the number of individuals in animal species living together. ICES J. Mar. Sci. 3, 3–51 (1928).

    Article  Google Scholar 

  37. 37.

    Nadell, C. D., Drescher, K. & Foster, K. R. Spatial structure, cooperation and competition in biofilms. Nat. Rev. Microbiol. 14, 589–600 (2016).

    CAS  Article  Google Scholar 

  38. 38.

    Le Loir, Y., Gruss, A., Ehrlich, S. D. & Langella, P. A nine-residue synthetic propeptide enhances secretion efficiency of heterologous proteins in Lactococcus lactis. J. Bacteriol. 180, 1895–1903 (1998).

    PubMed  PubMed Central  Google Scholar 

  39. 39.

    Oh, J.-H. & van Pijkeren, J.-P. CRISPR-Cas9-assisted recombineering in Lactobacillus reuteri. Nucleic Acids Res. 42, e131 (2014).

    Article  Google Scholar 

  40. 40.

    Douglas, G. L. & Klaenhammer, T. R. Directed chromosomal integration and expression of the reporter gene gusA3 in Lactobacillus acidophilus NCFM. Appl. Environ. Microbiol. 77, 7365–7371 (2011).

    CAS  Article  Google Scholar 

  41. 41.

    Fernández, A., Horn, N., Gasson, M. J., Dodd, H. M. & Rodríguez, J. M. High-level coproduction of the bacteriocins nisin A and lactococcin A by Lactococcus lactis. J. Dairy Res. 71, 216–221 (2004).

    Article  Google Scholar 

Download references


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).

Author information




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.

Corresponding authors

Correspondence to James J. Collins or Ting Lu.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Text and Figures

Supplementary Table 1–7, Supplementary Figures 1–12, Supplementary Notes 1–4

Reporting Summary

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Kong, W., Meldgin, D.R., Collins, J.J. et al. Designing microbial consortia with defined social interactions. Nat Chem Biol 14, 821–829 (2018).

Download citation

Further reading


Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing