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Cell-in-the-loop pattern formation with optogenetically emulated cell-to-cell signaling

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Listed:
  • Melinda Liu Perkins

    (University of California)

  • Dirk Benzinger

    (ETH Zürich)

  • Murat Arcak

    (University of California)

  • Mustafa Khammash

    (ETH Zürich)

Abstract

Designing and implementing synthetic biological pattern formation remains challenging due to underlying theoretical complexity as well as the difficulty of engineering multicellular networks biochemically. Here, we introduce a cell-in-the-loop approach where living cells interact through in silico signaling, establishing a new testbed to interrogate theoretical principles when internal cell dynamics are incorporated rather than modeled. We present an easy-to-use theoretical test to predict the emergence of contrasting patterns in gene expression among laterally inhibiting cells. Guided by the theory, we experimentally demonstrate spontaneous checkerboard patterning in an optogenetic setup, where cell-to-cell signaling is emulated with light inputs calculated in silico from real-time gene expression measurements. The scheme successfully produces spontaneous, persistent checkerboard patterns for systems of sixteen patches, in quantitative agreement with theoretical predictions. Our research highlights how tools from dynamical systems theory may inform our understanding of patterning, and illustrates the potential of cell-in-the-loop for engineering synthetic multicellular systems.

Suggested Citation

  • Melinda Liu Perkins & Dirk Benzinger & Murat Arcak & Mustafa Khammash, 2020. "Cell-in-the-loop pattern formation with optogenetically emulated cell-to-cell signaling," Nature Communications, Nature, vol. 11(1), pages 1-10, December.
  • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-15166-3
    DOI: 10.1038/s41467-020-15166-3
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    Cited by:

    1. Jean-Baptiste Lugagne & Caroline M. Blassick & Mary J. Dunlop, 2024. "Deep model predictive control of gene expression in thousands of single cells," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    2. Michael B. Sheets & Nathan Tague & Mary J. Dunlop, 2023. "An optogenetic toolkit for light-inducible antibiotic resistance," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    3. Zachary R. Fox & Steven Fletcher & Achille Fraisse & Chetan Aditya & Sebastián Sosa-Carrillo & Julienne Petit & Sébastien Gilles & François Bertaux & Jakob Ruess & Gregory Batt, 2022. "Enabling reactive microscopy with MicroMator," Nature Communications, Nature, vol. 13(1), pages 1-8, December.

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