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Majority sensing in synthetic microbial consortia

Author

Listed:
  • Razan N. Alnahhas

    (Rice University)

  • Mehdi Sadeghpour

    (Rice University
    University of Houston)

  • Ye Chen

    (Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences)

  • Alexis A. Frey

    (Rice University)

  • William Ott

    (University of Houston)

  • Krešimir Josić

    (University of Houston
    University of Houston)

  • Matthew R. Bennett

    (Rice University
    Rice University)

Abstract

As synthetic biocircuits become more complex, distributing computations within multi-strain microbial consortia becomes increasingly beneficial. However, designing distributed circuits that respond predictably to variation in consortium composition remains a challenge. Here we develop a two-strain gene circuit that senses and responds to which strain is in the majority. This involves a co-repressive system in which each strain produces a signaling molecule that signals the other strain to down-regulate production of its own, orthogonal signaling molecule. This co-repressive consortium links gene expression to ratio of the strains rather than population size. Further, we control the cross-over point for majority via external induction. We elucidate the mechanisms driving these dynamics by developing a mathematical model that captures consortia response as strain fractions and external induction are varied. These results show that simple gene circuits can be used within multicellular synthetic systems to sense and respond to the state of the population.

Suggested Citation

  • Razan N. Alnahhas & Mehdi Sadeghpour & Ye Chen & Alexis A. Frey & William Ott & Krešimir Josić & Matthew R. Bennett, 2020. "Majority sensing in synthetic microbial consortia," Nature Communications, Nature, vol. 11(1), pages 1-10, December.
  • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-17475-z
    DOI: 10.1038/s41467-020-17475-z
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    Cited by:

    1. Joaquín Gutiérrez Mena & Sant Kumar & Mustafa Khammash, 2022. "Dynamic cybergenetic control of bacterial co-culture composition via optogenetic feedback," Nature Communications, Nature, vol. 13(1), pages 1-16, December.
    2. Wenwen Diao & Liang Guo & Qiang Ding & Cong Gao & Guipeng Hu & Xiulai Chen & Yang Li & Linpei Zhang & Wei Chen & Jian Chen & Liming Liu, 2021. "Reprogramming microbial populations using a programmed lysis system to improve chemical production," Nature Communications, Nature, vol. 12(1), pages 1-14, December.
    3. Xianglai Li & Zhao Zhou & Wenna Li & Yajun Yan & Xiaolin Shen & Jia Wang & Xinxiao Sun & Qipeng Yuan, 2022. "Design of stable and self-regulated microbial consortia for chemical synthesis," Nature Communications, Nature, vol. 13(1), pages 1-9, December.

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