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Reprogramming microbial populations using a programmed lysis system to improve chemical production

Author

Listed:
  • Wenwen Diao

    (State Key Laboratory of Food Science and Technology, Jiangnan University
    School of Biotechnology, Jiangnan University)

  • Liang Guo

    (State Key Laboratory of Food Science and Technology, Jiangnan University
    School of Biotechnology, Jiangnan University)

  • Qiang Ding

    (State Key Laboratory of Food Science and Technology, Jiangnan University
    School of Biotechnology, Jiangnan University)

  • Cong Gao

    (State Key Laboratory of Food Science and Technology, Jiangnan University
    School of Biotechnology, Jiangnan University)

  • Guipeng Hu

    (State Key Laboratory of Food Science and Technology, Jiangnan University
    School of Biotechnology, Jiangnan University)

  • Xiulai Chen

    (State Key Laboratory of Food Science and Technology, Jiangnan University
    School of Biotechnology, Jiangnan University)

  • Yang Li

    (State Key Laboratory of Food Science and Technology, Jiangnan University
    School of Biotechnology, Jiangnan University)

  • Linpei Zhang

    (School of Biotechnology, Jiangnan University)

  • Wei Chen

    (State Key Laboratory of Food Science and Technology, Jiangnan University)

  • Jian Chen

    (School of Biotechnology, Jiangnan University)

  • Liming Liu

    (State Key Laboratory of Food Science and Technology, Jiangnan University
    School of Biotechnology, Jiangnan University)

Abstract

Microbial populations are a promising model for achieving microbial cooperation to produce valuable chemicals. However, regulating the phenotypic structure of microbial populations remains challenging. In this study, a programmed lysis system (PLS) is developed to reprogram microbial cooperation to enhance chemical production. First, a colicin M -based lysis unit is constructed to lyse Escherichia coli. Then, a programmed switch, based on proteases, is designed to regulate the effective lysis unit time. Next, a PLS is constructed for chemical production by combining the lysis unit with a programmed switch. As a result, poly (lactate-co-3-hydroxybutyrate) production is switched from PLH synthesis to PLH release, and the content of free PLH is increased by 283%. Furthermore, butyrate production with E. coli consortia is switched from E. coli BUT003 to E. coli BUT004, thereby increasing butyrate production to 41.61 g/L. These results indicate the applicability of engineered microbial populations for improving the metabolic division of labor to increase the efficiency of microbial cell factories.

Suggested Citation

  • 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.
    • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-27226-3
    DOI: 10.1038/s41467-021-27226-3
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    References listed on IDEAS

    as
    1. Niels Klitgord & Daniel Segrè, 2010. "Environments that Induce Synthetic Microbial Ecosystems," PLOS Computational Biology, Public Library of Science, vol. 6(11), pages 1-17, November.
    2. Evan M. Zhao & Yanfei Zhang & Justin Mehl & Helen Park & Makoto A. Lalwani & Jared E. Toettcher & José L. Avalos, 2018. "Optogenetic regulation of engineered cellular metabolism for microbial chemical production," Nature, Nature, vol. 555(7698), pages 683-687, March.
    3. Cong Gao & Jianshen Hou & Peng Xu & Liang Guo & Xiulai Chen & Guipeng Hu & Chao Ye & Harley Edwards & Jian Chen & Wei Chen & Liming Liu, 2019. "Programmable biomolecular switches for rewiring flux in Escherichia coli," Nature Communications, Nature, vol. 10(1), pages 1-12, December.
    4. 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.
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