Unknown

Dataset Information

0

Characterizing posttranslational modifications in prokaryotic metabolism using a multiscale workflow.


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.

SUBMITTER: Brunk E 

PROVIDER: S-EPMC6205427 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

altmetric image

Publications

Characterizing posttranslational modifications in prokaryotic metabolism using a multiscale workflow.

Brunk Elizabeth E   Chang Roger L RL   Xia Jing J   Hefzi Hooman H   Yurkovich James T JT   Kim Donghyuk D   Buckmiller Evan E   Wang Harris H HH   Cho Byung-Kwan BK   Yang Chen C   Palsson Bernhard O BO   Church George M GM   Lewis Nathan E NE  

Proceedings of the National Academy of Sciences of the United States of America 20181009 43


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;  ...[more]

Similar Datasets

| S-EPMC7896749 | biostudies-literature
| S-EPMC6035883 | biostudies-literature
| S-EPMC4713141 | biostudies-literature
| S-EPMC3981057 | biostudies-other
| S-EPMC4074372 | biostudies-literature
| S-EPMC3404735 | biostudies-literature
| S-EPMC5206544 | biostudies-literature
| S-EPMC5296278 | biostudies-literature
| S-EPMC4882250 | biostudies-literature
| S-EPMC5618787 | biostudies-literature