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Mapping enzyme catalysis with metabolic biosensing

Enzymes are represented across a vast space of protein sequences and structural forms and have activities that far exceed the best chemical catalysts; however, engineering them to have novel or enhanced activity is limited by technologies for sensing product formation. Here, we describe a general an...

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Autores principales: Xu, Linfeng, Chang, Kai-Chun, Payne, Emory M., Modavi, Cyrus, Liu, Leqian, Palmer, Claire M., Tao, Nannan, Alper, Hal S., Kennedy, Robert T., Cornett, Dale S., Abate, Adam R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8611028/
https://www.ncbi.nlm.nih.gov/pubmed/34815408
http://dx.doi.org/10.1038/s41467-021-27185-9
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author Xu, Linfeng
Chang, Kai-Chun
Payne, Emory M.
Modavi, Cyrus
Liu, Leqian
Palmer, Claire M.
Tao, Nannan
Alper, Hal S.
Kennedy, Robert T.
Cornett, Dale S.
Abate, Adam R.
author_facet Xu, Linfeng
Chang, Kai-Chun
Payne, Emory M.
Modavi, Cyrus
Liu, Leqian
Palmer, Claire M.
Tao, Nannan
Alper, Hal S.
Kennedy, Robert T.
Cornett, Dale S.
Abate, Adam R.
author_sort Xu, Linfeng
collection PubMed
description Enzymes are represented across a vast space of protein sequences and structural forms and have activities that far exceed the best chemical catalysts; however, engineering them to have novel or enhanced activity is limited by technologies for sensing product formation. Here, we describe a general and scalable approach for characterizing enzyme activity that uses the metabolism of the host cell as a biosensor by which to infer product formation. Since different products consume different molecules in their synthesis, they perturb host metabolism in unique ways that can be measured by mass spectrometry. This provides a general way by which to sense product formation, to discover unexpected products and map the effects of mutagenesis.
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spelling pubmed-86110282021-12-01 Mapping enzyme catalysis with metabolic biosensing Xu, Linfeng Chang, Kai-Chun Payne, Emory M. Modavi, Cyrus Liu, Leqian Palmer, Claire M. Tao, Nannan Alper, Hal S. Kennedy, Robert T. Cornett, Dale S. Abate, Adam R. Nat Commun Article Enzymes are represented across a vast space of protein sequences and structural forms and have activities that far exceed the best chemical catalysts; however, engineering them to have novel or enhanced activity is limited by technologies for sensing product formation. Here, we describe a general and scalable approach for characterizing enzyme activity that uses the metabolism of the host cell as a biosensor by which to infer product formation. Since different products consume different molecules in their synthesis, they perturb host metabolism in unique ways that can be measured by mass spectrometry. This provides a general way by which to sense product formation, to discover unexpected products and map the effects of mutagenesis. Nature Publishing Group UK 2021-11-23 /pmc/articles/PMC8611028/ /pubmed/34815408 http://dx.doi.org/10.1038/s41467-021-27185-9 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Xu, Linfeng
Chang, Kai-Chun
Payne, Emory M.
Modavi, Cyrus
Liu, Leqian
Palmer, Claire M.
Tao, Nannan
Alper, Hal S.
Kennedy, Robert T.
Cornett, Dale S.
Abate, Adam R.
Mapping enzyme catalysis with metabolic biosensing
title Mapping enzyme catalysis with metabolic biosensing
title_full Mapping enzyme catalysis with metabolic biosensing
title_fullStr Mapping enzyme catalysis with metabolic biosensing
title_full_unstemmed Mapping enzyme catalysis with metabolic biosensing
title_short Mapping enzyme catalysis with metabolic biosensing
title_sort mapping enzyme catalysis with metabolic biosensing
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8611028/
https://www.ncbi.nlm.nih.gov/pubmed/34815408
http://dx.doi.org/10.1038/s41467-021-27185-9
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