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Diagnostic and Therapeutic Microbial Circuit with Application to Intestinal Inflammation
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    Research Article

    Diagnostic and Therapeutic Microbial Circuit with Application to Intestinal Inflammation
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    • Liana N. Merk
      Liana N. Merk
      Department of Molecular and Cellular Biology, Harvard University, Cambridge, Massachusetts 02138, United States
    • Andrey S. Shur
      Andrey S. Shur
      Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California 91125, United States
    • Smrutiti Jena
      Smrutiti Jena
      Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana 47907, United States
    • Javier Munoz
      Javier Munoz
      Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana 47907, United States
      More by Javier Munoz
    • Douglas K. Brubaker
      Douglas K. Brubaker
      Center for Global Health and Diseases, Department of Pathology, School of Medicine, Case Western Reserve University, Cleveland, Ohio 44106, United States
      Blood Heart Lung Immunology Research Center, University Hospitals Cleveland Medical Center, Cleveland, Ohio 44106, United States
    • Richard M. Murray
      Richard M. Murray
      Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California 91125, United States
      Control and Dynamical Systems, California Institute of Technology, Pasadena, California 91125, United States
    • Leopold N. Green*
      Leopold N. Green
      Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California 91125, United States
      Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana 47907, United States
      *Email: [email protected]
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    ACS Synthetic Biology

    Cite this: ACS Synth. Biol. 2024, 13, 12, 3885–3896
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    https://doi.org/10.1021/acssynbio.3c00668
    Published November 28, 2024
    Copyright © 2024 American Chemical Society

    Abstract

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    Bacteria genetically engineered to execute defined therapeutic and diagnostic functions in physiological settings can be applied to colonize the human microbiome, providing in situ surveillance and conditional disease modulation. However, many engineered microbes can only respond to single-input environmental factors, limiting their tunability, precision, and effectiveness as living diagnostic and therapeutic systems. For engineering microbes to improve complex chronic disorders such as inflammatory bowel disease, the bacteria must respond to combinations of stimuli in the proper context and time. This work implements a previously characterized split activator AND logic gate in the probiotic Escherichia coli strain Nissle 1917 (EcN). Our system can respond to two input signals: the inflammatory biomarker tetrathionate and a second input signal, anhydrotetracycline (aTc), for manual control. We report 4–6 fold induction with a minimal leak when the two chemical signals are present. We model the AND gate dynamics using chemical reaction networks and tune parameters in silico to identify critical perturbations that affect our circuit’s selectivity. Finally, we engineer the optimized AND gate to secrete a therapeutic anti-inflammatory cytokine IL-22 using the hemolysin secretion pathway in the probiotic E. coli strain. We used a germ-free transwell model of the human gut epithelium to show that our engineering bacteria produce similar host cytokine responses compared to recombinant cytokine. Our study presents a scalable workflow to engineer cytokine-secreting microbes driven by logical signal processing. It demonstrates the feasibility of IL-22 derived from probiotic EcN with minimal off-target effects in a gut epithelial context.

    Copyright © 2024 American Chemical Society

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    Supporting Information

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    The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acssynbio.3c00668.

    • Supplementary Tables contain (1) chemical reactions governing the two-component system model, (2) parameters for this model, (3) a generalized linear model all pairwise comparison, and (4) compared to control. The remaining Supporting Information pertains to two-component model sensitivity analysis Figure S1, design space exploration and RNAP binding tuning Figure S2, AND gate screening Figure S3, optimization of EcN secreting IL-22 Figure S4, coupled to the AND gate Figure S5, Caco2 culturing Figure S6, and cytokine analysis of the transwell model (PDF)

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    ACS Synthetic Biology

    Cite this: ACS Synth. Biol. 2024, 13, 12, 3885–3896
    Click to copy citationCitation copied!
    https://doi.org/10.1021/acssynbio.3c00668
    Published November 28, 2024
    Copyright © 2024 American Chemical Society

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