ArticleMolecular & cellular proteomics : MCP2014
Mass spectrometry-based workflow for accurate quantification of Escherichia coli enzymes: how proteomics can play a key role in metabolic engineering.
Article in Molecular & cellular proteomics : MCP, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Engineering yeast for sustainable bioproduction of tryptophan-derived aromatic compounds.FEMS yeast research · 2026Review
- HMicroorganisms · 2023Article
- WellInverter: a web application for the analysis of fluorescent reporter gene data.BMC bioinformatics · 2019Article
- Application of targeted mass spectrometry in bottom-up proteomics for systems biology research.Journal of proteomics · 2018Review
- Enzyme I facilitates reverse flux from pyruvate to phosphoenolpyruvate in Escherichia coli.Nature communications · 2017Article
- Inference of quantitative models of bacterial promoters from time-series reporter gene data.PLoS computational biology · 2015Article
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10 authors.
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Abstract
Metabolic engineering aims to design high performance microbial strains producing compounds of interest. This requires systems-level understanding; genome-scale models have therefore been developed to predict metabolic fluxes. However, multi-omics data including genomics, transcriptomics, fluxomics, and proteomics may be required to model the metabolism of potential cell factories. Recent technological advances to quantitative proteomics have made mass spectrometry-based quantitative assays an interesting alternative to more traditional immuno-affinity based approaches. This has improved specificity and multiplexing capabilities. In this study, we developed a quantification workflow to analyze enzymes involved in central metabolism in Escherichia coli (E. coli). This workflow combined full-length isotopically labeled standards with selected reaction monitoring analysis. First, full-length (15)N labeled standards were produced and calibrated to ensure accurate measurements. Liquid chromatography conditions were then optimized for reproducibility and multiplexing capabilities over a single 30-min liquid chromatography-MS analysis. This workflow was used to accurately quantify 22 enzymes involved in E. coli central metabolism in a wild-type reference strain and two derived strains, optimized for higher NADPH production. In combination with measurements of metabolic fluxes, proteomics data can be used to assess different levels of regulation, in particular enzyme abundance and catalytic rate. This provides information that can be used to design specific strains used in biotechnology. In addition, accurate measurement of absolute enzyme concentrations is key to the development of predictive kinetic models in the context of metabolic engineering.
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