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 coll. 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.