Characterizing posttranslational modifications in prokaryotic metabolism using a multiscale workflow

Brunk, Elizabeth; Chang, Roger L.; Xia, Jing; Hefzi, Hooman; Yurkovich, James T.; Kim, Donghyuk; Buckmiller, Evan; Wang, Harris H.; Cho, Byung-Kwan; Yang, Chen; Palsson, Bernhard O.; Church, George M.; Lewis, Nathan E.

doi:10.1073/pnas.1811971115

Title: Characterizing posttranslational modifications in prokaryotic metabolism using a multiscale workflow

Journal Article · Tue Oct 09 00:00:00 EDT 2018 · Proceedings of the National Academy of Sciences of the United States of America

DOI:https://doi.org/10.1073/pnas.1811971115· OSTI ID:1528919

^[1]; Chang, Roger L. ^[2]; Xia, Jing ^[3]; Hefzi, Hooman ^[1];

^[1]; Kim, Donghyuk ^[4]; Buckmiller, Evan ^[5];

^[6]; Cho, Byung-Kwan ^[7]; Yang, Chen ^[3]; Palsson, Bernhard O. ^[8]; Church, George M. ^[9]; Lewis, Nathan E. ^[1]

University of California, San Diego, La Jolla, CA (United States)
Harvard Medical School, Boston, MA (United States); University of California, San Diego, La Jolla, CA (United States)
Chinese Academy of Sciences, Shanghai (China)
University of California, San Diego, La Jolla, CA (United States); Kyung Hee Univ., Yongin (Korea)
Brigham Young Univ., Provo, UT (United States)
Columbia University Medical Center, New York, NY (United States); Harvard Medical School, Boston, MA (United States)
Korea Advanced Institute of Science and Technology, Daejeon (Korea)
University of California, San Diego, La Jolla, CA (United States); Technical Univ. of Denmark, Lyngby (Denmark)
Harvard Medical School, Boston, MA (United States)

Understanding the complex interactions of protein posttranslational modifications (PTMs) represents a major challenge in metabolic engineering, synthetic biology, and the biomedical sciences. In this work, we present a workflow that integrates multiplex automated genome editing (MAGE), genome-scale metabolic modeling, and atomistic molecular dynamics to study the effects of PTMs on metabolic enzymes and microbial fitness. This workflow incorporates complementary approaches across scientific disciplines; provides molecular insight into how PTMs influence cellular fitness during nutrient shifts; and demonstrates how mechanistic details of PTMs can be explored at different biological scales. As a proof of concept, we present a global analysis of PTMs on enzymes in the metabolic network of Escherichia coli. Based on our workflow results, we conduct a more detailed, mechanistic analysis of the PTMs in three proteins: enolase, serine hydroxymethyltransferase, and transaldolase. Finally, application of this workflow identified the roles of specific PTMs in observed experimental phenomena and demonstrated how individual PTMs regulate enzymes, pathways, and, ultimately, cell phenotypes.

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Research Organization:: Harvard Medical School, Boston, MA (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER). Biological Systems Science Division

Contributing Organization:: National Energy Research Scientific Computing Center and XSEDE computer facilities (MCB140152)

Grant/Contract Number:: FG02-02ER63445

OSTI ID:: 1528919

Journal Information:: Proceedings of the National Academy of Sciences of the United States of America, Vol. 115, Issue 43; ISSN 0027-8424

Publisher:: National Academy of Sciences, Washington, DC (United States)Copyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 27 works

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59 BASIC BIOLOGICAL SCIENCES
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multiplex automated genome engineering
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