| Literature DB >> 30301795 |
Elizabeth Brunk1,2, Roger L Chang3,4, Jing Xia5, Hooman Hefzi1,2,6, James T Yurkovich1,4, Donghyuk Kim1,7, Evan Buckmiller8, Harris H Wang9,10,11, Byung-Kwan Cho12, Chen Yang5, Bernhard O Palsson1,2,13, George M Church14, Nathan E Lewis15,2,6.
Abstract
Understanding the complex interactions of protein posttranslational modifications (PTMs) represents a major challenge in metabolic engineering, synthetic biology, and the biomedical sciences. Here, 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. 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.Entities:
Keywords: metabolism; omics data; posttranslational modifications; protein chemistry; systems biology
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Year: 2018 PMID: 30301795 PMCID: PMC6205427 DOI: 10.1073/pnas.1811971115
Source DB: PubMed Journal: Proc Natl Acad Sci U S A ISSN: 0027-8424 Impact factor: 11.205