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Plug-and-play metabolic transducers expand the chemical detection space of cell-free biosensors

Author

Listed:
  • Peter L. Voyvodic

    (University of Montpellier)

  • Amir Pandi

    (Université Paris-Saclay)

  • Mathilde Koch

    (Université Paris-Saclay)

  • Ismael Conejero

    (University of Montpellier
    Neuropsychiatry, Epidemiological and Clinical Research
    Caremeau Hospital, University Hospital of Nîmes)

  • Emmanuel Valjent

    (Institute of Functional Genomics, University of Montpellier)

  • Philippe Courtet

    (Neuropsychiatry, Epidemiological and Clinical Research
    Lapeyronie Hospital, CHRU Montpellier)

  • Eric Renard

    (Institute of Functional Genomics, University of Montpellier
    Montpellier University Hospital)

  • Jean-Loup Faulon

    (Université Paris-Saclay
    University of Manchester)

  • Jerome Bonnet

    (University of Montpellier)

Abstract

Cell-free transcription–translation systems have great potential for biosensing, yet the range of detectable chemicals is limited. Here we provide a workflow to expand the range of molecules detectable by cell-free biosensors through combining synthetic metabolic cascades with transcription factor-based networks. These hybrid cell-free biosensors have a fast response time, strong signal response, and a high dynamic range. In addition, they are capable of functioning in a variety of complex media, including commercial beverages and human urine, in which they can be used to detect clinically relevant concentrations of small molecules. This work provides a foundation to engineer modular cell-free biosensors tailored for many applications.

Suggested Citation

  • Peter L. Voyvodic & Amir Pandi & Mathilde Koch & Ismael Conejero & Emmanuel Valjent & Philippe Courtet & Eric Renard & Jean-Loup Faulon & Jerome Bonnet, 2019. "Plug-and-play metabolic transducers expand the chemical detection space of cell-free biosensors," Nature Communications, Nature, vol. 10(1), pages 1-8, December.
    • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-09722-9
    DOI: 10.1038/s41467-019-09722-9
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    Cited by:

    1. Antonio Baldassarre & Nicola Mucci & Luigi Isaia Lecca & Emanuela Tomasini & Maria Julia Parcias-do-Rosario & Carolina Tauil Pereira & Giulio Arcangeli & Paulo Antonio Barros Oliveira, 2020. "Biosensors in Occupational Safety and Health Management: A Narrative Review," IJERPH, MDPI, vol. 17(7), pages 1-10, April.
    2. Amir Pandi & Christoph Diehl & Ali Yazdizadeh Kharrazi & Scott A. Scholz & Elizaveta Bobkova & Léon Faure & Maren Nattermann & David Adam & Nils Chapin & Yeganeh Foroughijabbari & Charles Moritz & Nic, 2022. "A versatile active learning workflow for optimization of genetic and metabolic networks," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    3. Grace E. Vezeau & Lipika R. Gadila & Howard M. Salis, 2023. "Automated design of protein-binding riboswitches for sensing human biomarkers in a cell-free expression system," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    4. Bob Sluijs & Roel J. M. Maas & Ardjan J. Linden & Tom F. A. Greef & Wilhelm T. S. Huck, 2022. "A microfluidic optimal experimental design platform for forward design of cell-free genetic networks," Nature Communications, Nature, vol. 13(1), pages 1-11, December.

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