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A progesterone biosensor derived from microbial screening

Bacteria are an enormous and largely untapped reservoir of biosensing proteins. We describe an approach to identify and isolate bacterial allosteric transcription factors (aTFs) that recognize a target analyte and to develop these TFs into biosensor devices. Our approach utilizes a combination of ge...

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Autores principales: Grazon, Chloé, Baer, R C., Kuzmanović, Uroš, Nguyen, Thuy, Chen, Mingfu, Zamani, Marjon, Chern, Margaret, Aquino, Patricia, Zhang, Xiaoman, Lecommandoux, Sébastien, Fan, Andy, Cabodi, Mario, Klapperich, Catherine, Grinstaff, Mark W., Dennis, Allison M., Galagan, James E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7062782/
https://www.ncbi.nlm.nih.gov/pubmed/32152281
http://dx.doi.org/10.1038/s41467-020-14942-5
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author Grazon, Chloé
Baer, R C.
Kuzmanović, Uroš
Nguyen, Thuy
Chen, Mingfu
Zamani, Marjon
Chern, Margaret
Aquino, Patricia
Zhang, Xiaoman
Lecommandoux, Sébastien
Fan, Andy
Cabodi, Mario
Klapperich, Catherine
Grinstaff, Mark W.
Dennis, Allison M.
Galagan, James E.
author_facet Grazon, Chloé
Baer, R C.
Kuzmanović, Uroš
Nguyen, Thuy
Chen, Mingfu
Zamani, Marjon
Chern, Margaret
Aquino, Patricia
Zhang, Xiaoman
Lecommandoux, Sébastien
Fan, Andy
Cabodi, Mario
Klapperich, Catherine
Grinstaff, Mark W.
Dennis, Allison M.
Galagan, James E.
author_sort Grazon, Chloé
collection PubMed
description Bacteria are an enormous and largely untapped reservoir of biosensing proteins. We describe an approach to identify and isolate bacterial allosteric transcription factors (aTFs) that recognize a target analyte and to develop these TFs into biosensor devices. Our approach utilizes a combination of genomic screens and functional assays to identify and isolate biosensing TFs, and a quantum-dot Förster Resonance Energy Transfer (FRET) strategy for transducing analyte recognition into real-time quantitative measurements. We use this approach to identify a progesterone-sensing bacterial aTF and to develop this TF into an optical sensor for progesterone. The sensor detects progesterone in artificial urine with sufficient sensitivity and specificity for clinical use, while being compatible with an inexpensive and portable electronic reader for point-of-care applications. Our results provide proof-of-concept for a paradigm of microbially-derived biosensors adaptable to inexpensive, real-time sensor devices.
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spelling pubmed-70627822020-03-18 A progesterone biosensor derived from microbial screening Grazon, Chloé Baer, R C. Kuzmanović, Uroš Nguyen, Thuy Chen, Mingfu Zamani, Marjon Chern, Margaret Aquino, Patricia Zhang, Xiaoman Lecommandoux, Sébastien Fan, Andy Cabodi, Mario Klapperich, Catherine Grinstaff, Mark W. Dennis, Allison M. Galagan, James E. Nat Commun Article Bacteria are an enormous and largely untapped reservoir of biosensing proteins. We describe an approach to identify and isolate bacterial allosteric transcription factors (aTFs) that recognize a target analyte and to develop these TFs into biosensor devices. Our approach utilizes a combination of genomic screens and functional assays to identify and isolate biosensing TFs, and a quantum-dot Förster Resonance Energy Transfer (FRET) strategy for transducing analyte recognition into real-time quantitative measurements. We use this approach to identify a progesterone-sensing bacterial aTF and to develop this TF into an optical sensor for progesterone. The sensor detects progesterone in artificial urine with sufficient sensitivity and specificity for clinical use, while being compatible with an inexpensive and portable electronic reader for point-of-care applications. Our results provide proof-of-concept for a paradigm of microbially-derived biosensors adaptable to inexpensive, real-time sensor devices. Nature Publishing Group UK 2020-03-09 /pmc/articles/PMC7062782/ /pubmed/32152281 http://dx.doi.org/10.1038/s41467-020-14942-5 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Grazon, Chloé
Baer, R C.
Kuzmanović, Uroš
Nguyen, Thuy
Chen, Mingfu
Zamani, Marjon
Chern, Margaret
Aquino, Patricia
Zhang, Xiaoman
Lecommandoux, Sébastien
Fan, Andy
Cabodi, Mario
Klapperich, Catherine
Grinstaff, Mark W.
Dennis, Allison M.
Galagan, James E.
A progesterone biosensor derived from microbial screening
title A progesterone biosensor derived from microbial screening
title_full A progesterone biosensor derived from microbial screening
title_fullStr A progesterone biosensor derived from microbial screening
title_full_unstemmed A progesterone biosensor derived from microbial screening
title_short A progesterone biosensor derived from microbial screening
title_sort progesterone biosensor derived from microbial screening
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7062782/
https://www.ncbi.nlm.nih.gov/pubmed/32152281
http://dx.doi.org/10.1038/s41467-020-14942-5
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