Mapping enzyme catalysis with metabolic biosensing

Linfeng Xu, Kai-Chun Chang, Emory M. Payne, Cyrus Modavi, Leqian Liu, Claire M. Palmer, Nannan Tao, Hal S. Alper, Robert T. Kennedy, Dale S. Cornett and Adam R. Abate ()
Additional contact information
Linfeng Xu: University of California, San Francisco
Kai-Chun Chang: University of California, San Francisco
Emory M. Payne: University of Michigan
Cyrus Modavi: University of California, San Francisco
Leqian Liu: University of California, San Francisco
Claire M. Palmer: The University of Texas at Austin
Nannan Tao: Bruker Nano Surfaces
Hal S. Alper: The University of Texas at Austin
Robert T. Kennedy: University of Michigan
Dale S. Cornett: Bruker Daltonics
Adam R. Abate: University of California, San Francisco

Nature Communications, 2021, vol. 12, issue 1, 1-7

Abstract: Abstract 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.

Date: 2021
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-27185-9

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DOI: 10.1038/s41467-021-27185-9

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