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Automated design of protein-binding riboswitches for sensing human biomarkers in a cell-free expression system

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  • Grace E. Vezeau

    (Pennsylvania State University)

  • Lipika R. Gadila

    (Pennsylvania State University)

  • Howard M. Salis

    (Pennsylvania State University
    Pennsylvania State University
    Pennsylvania State University
    Pennsylvania State University)

Abstract

Cell-free genetically encoded biosensors have been developed to detect small molecules and nucleic acids, but they have yet to be reliably engineered to detect proteins. Here we develop an automated platform to convert protein-binding RNA aptamers into riboswitch sensors that operate within low-cost cell-free assays. We demonstrate the platform by engineering 35 protein-sensing riboswitches for human monomeric C-reactive protein, human interleukin-32γ, and phage MS2 coat protein. The riboswitch sensors regulate output expression levels by up to 16-fold with input protein concentrations within the human serum range. We identify two distinct mechanisms governing riboswitch-mediated regulation of translation rates and leverage computational analysis to refine the protein-binding aptamer regions, improving design accuracy. Overall, we expand the cell-free sensor toolbox and demonstrate how computational design is used to develop protein-sensing riboswitches with future applications as low-cost medical diagnostics.

Suggested Citation

  • 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.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-38098-0
    DOI: 10.1038/s41467-023-38098-0
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    References listed on IDEAS

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    1. Evan Amalfitano & Margot Karlikow & Masoud Norouzi & Katariina Jaenes & Seray Cicek & Fahim Masum & Peivand Sadat Mousavi & Yuxiu Guo & Laura Tang & Andrew Sydor & Duo Ma & Joel D. Pearson & Daniel Tr, 2021. "A glucose meter interface for point-of-care gene circuit-based diagnostics," Nature Communications, Nature, vol. 12(1), pages 1-10, December.
    2. James Chappell & Alexandra Westbrook & Matthew Verosloff & Julius B. Lucks, 2017. "Computational design of small transcription activating RNAs for versatile and dynamic gene regulation," Nature Communications, Nature, vol. 8(1), pages 1-12, December.
    3. 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.
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    Cited by:

    1. Heonjoon Lee & Tian Xie & Byunghwa Kang & Xinjie Yu & Samuel W. Schaffter & Rebecca Schulman, 2024. "Plug-and-play protein biosensors using aptamer-regulated in vitro transcription," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    2. Daniel P. Cetnar & Ayaan Hossain & Grace E. Vezeau & Howard M. Salis, 2024. "Predicting synthetic mRNA stability using massively parallel kinetic measurements, biophysical modeling, and machine learning," Nature Communications, Nature, vol. 15(1), pages 1-11, December.

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