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Low-cost anti-mycobacterial drug discovery using engineered E. coli

Author

Listed:
  • Nadine Bongaerts

    (Université Paris Cité, Inserm, System Engineering and Evolution Dynamics
    CRI)

  • Zainab Edoo

    (Sorbonne Université, Université Paris Cité, Inserm, Centre de Recherche des Cordeliers (CRC))

  • Ayan A. Abukar

    (Université Paris Cité, Inserm, System Engineering and Evolution Dynamics
    CRI)

  • Xiaohu Song

    (Université Paris Cité, Inserm, System Engineering and Evolution Dynamics
    CRI)

  • Sebastián Sosa-Carrillo

    (Université Paris Cité, Inserm, System Engineering and Evolution Dynamics
    Institut Pasteur, Inria de Paris, Université Paris Cité, InBio)

  • Sarah Haggenmueller

    (Université Paris Cité, Inserm, System Engineering and Evolution Dynamics
    CRI)

  • Juline Savigny

    (Université Paris Cité, Inserm, System Engineering and Evolution Dynamics
    CRI)

  • Sophie Gontier

    (Université Paris Cité, Inserm, System Engineering and Evolution Dynamics
    CRI)

  • Ariel B. Lindner

    (Université Paris Cité, Inserm, System Engineering and Evolution Dynamics
    CRI)

  • Edwin H. Wintermute

    (Université Paris Cité, Inserm, System Engineering and Evolution Dynamics
    CRI)

Abstract

Whole-cell screening for Mycobacterium tuberculosis (Mtb) inhibitors is complicated by the pathogen’s slow growth and biocontainment requirements. Here we present a synthetic biology framework for assaying Mtb drug targets in engineered E. coli. We construct Target Essential Surrogate E. coli (TESEC) in which an essential metabolic enzyme is deleted and replaced with an Mtb-derived functional analog, linking bacterial growth to the activity of the target enzyme. High throughput screening of a TESEC model for Mtb alanine racemase (Alr) revealed benazepril as a targeted inhibitor, a result validated in whole-cell Mtb. In vitro biochemical assays indicated a noncompetitive mechanism unlike that of clinical Alr inhibitors. We establish the scalability of TESEC for drug discovery by characterizing TESEC strains for four additional targets.

Suggested Citation

  • Nadine Bongaerts & Zainab Edoo & Ayan A. Abukar & Xiaohu Song & Sebastián Sosa-Carrillo & Sarah Haggenmueller & Juline Savigny & Sophie Gontier & Ariel B. Lindner & Edwin H. Wintermute, 2022. "Low-cost anti-mycobacterial drug discovery using engineered E. coli," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-31570-3
    DOI: 10.1038/s41467-022-31570-3
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    References listed on IDEAS

    as
    1. Adam C. Palmer & Roy Kishony, 2014. "Opposing effects of target overexpression reveal drug mechanisms," Nature Communications, Nature, vol. 5(1), pages 1-8, September.
    2. Eachan O. Johnson & Emily LaVerriere & Emma Office & Mary Stanley & Elisabeth Meyer & Tomohiko Kawate & James E. Gomez & Rebecca E. Audette & Nirmalya Bandyopadhyay & Natalia Betancourt & Kayla Delano, 2019. "Large-scale chemical–genetics yields new M. tuberculosis inhibitor classes," Nature, Nature, vol. 571(7763), pages 72-78, July.
    3. Ramiz Daniel & Jacob R. Rubens & Rahul Sarpeshkar & Timothy K. Lu, 2013. "Synthetic analog computation in living cells," Nature, Nature, vol. 497(7451), pages 619-623, May.
    4. Towse, Adrian & Hoyle, Christopher K. & Goodall, Jonathan & Hirsch, Mark & Mestre-Ferrandiz, Jorge & Rex, John H., 2017. "Time for a change in how new antibiotics are reimbursed: Development of an insurance framework for funding new antibiotics based on a policy of risk mitigation," Health Policy, Elsevier, vol. 121(10), pages 1025-1030.
    5. Manica Balasegaram & Peter Kolb & John McKew & Jaykumar Menon & Piero Olliaro & Tomasz Sablinski & Zakir Thomas & Matthew H Todd & Els Torreele & John Wilbanks, 2017. "An open source pharma roadmap," PLOS Medicine, Public Library of Science, vol. 14(4), pages 1-7, April.
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