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Deep model predictive control of gene expression in thousands of single cells

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  • Jean-Baptiste Lugagne

    (Boston University, Boston
    Boston University, Boston)

  • Caroline M. Blassick

    (Boston University, Boston
    Boston University, Boston)

  • Mary J. Dunlop

    (Boston University, Boston
    Boston University, Boston)

Abstract

Gene expression is inherently dynamic, due to complex regulation and stochastic biochemical events. However, the effects of these dynamics on cell phenotypes can be difficult to determine. Researchers have historically been limited to passive observations of natural dynamics, which can preclude studies of elusive and noisy cellular events where large amounts of data are required to reveal statistically significant effects. Here, using recent advances in the fields of machine learning and control theory, we train a deep neural network to accurately predict the response of an optogenetic system in Escherichia coli cells. We then use the network in a deep model predictive control framework to impose arbitrary and cell-specific gene expression dynamics on thousands of single cells in real time, applying the framework to generate complex time-varying patterns. We also showcase the framework’s ability to link expression patterns to dynamic functional outcomes by controlling expression of the tetA antibiotic resistance gene. This study highlights how deep learning-enabled feedback control can be used to tailor distributions of gene expression dynamics with high accuracy and throughput without expert knowledge of the biological system.

Suggested Citation

  • 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.
  • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-46361-1
    DOI: 10.1038/s41467-024-46361-1
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    References listed on IDEAS

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    1. Sant Kumar & Marc Rullan & Mustafa Khammash, 2021. "Rapid prototyping and design of cybergenetic single-cell controllers," Nature Communications, Nature, vol. 12(1), pages 1-13, December.
    2. Sydney M. Shaffer & Margaret C. Dunagin & Stefan R. Torborg & Eduardo A. Torre & Benjamin Emert & Clemens Krepler & Marilda Beqiri & Katrin Sproesser & Patricia A. Brafford & Min Xiao & Elliott Eggan , 2017. "Rare cell variability and drug-induced reprogramming as a mode of cancer drug resistance," Nature, Nature, vol. 546(7658), pages 431-435, June.
    3. Om Patange & Christian Schwall & Matt Jones & Casandra Villava & Douglas A. Griffith & Andrew Phillips & James C. W. Locke, 2018. "Escherichia coli can survive stress by noisy growth modulation," Nature Communications, Nature, vol. 9(1), pages 1-11, December.
    4. 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.
    5. Remy Chait & Jakob Ruess & Tobias Bergmiller & Gašper Tkačik & Călin C. Guet, 2017. "Shaping bacterial population behavior through computer-interfaced control of individual cells," Nature Communications, Nature, vol. 8(1), pages 1-11, December.
    6. Andreas Milias-Argeitis & Marc Rullan & Stephanie K. Aoki & Peter Buchmann & Mustafa Khammash, 2016. "Automated optogenetic feedback control for precise and robust regulation of gene expression and cell growth," Nature Communications, Nature, vol. 7(1), pages 1-11, November.
    7. 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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