Mass Spectrometry-based Workflow for Accurate Quantification of Escherichia coli Enzymes: How Proteomics Can Play a Key Role in Metabolic Engineering

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. Molecular & Cellular Proteomics

Enzyme I facilitates reverse flux from pyruvate to phosphoenolpyruvate in Escherichia coli

“…When Δ ppsA strain was analysed, it was found to have the same back-flux as the wild type ( Fig. 2g ), a result consistent with the reports of minimal PpsA expression during growth on glucose 12 . Given the dual contribution of PpsA and EI to gluconeogenic flux under growth on acetate and pyruvate, it was suspected that EI may also be responsible for this back-flux on glucose.…”

“…The reverse reaction, PYR to PEP, is carried out by the gluconeogenic enzyme PEP synthetase (PpsA, encoded by ppsA in E. coli ). This enzyme is minimally expressed during growth on glycolytic substrates 12 , as significant activity would cause a wasteful futile cycle. However, PpsA is actively expressed under gluconeogenic conditions via transcriptional regulation by Cra 13 .…”

Inference of Quantitative Models of Bacterial Promoters from Time-Series Reporter Gene Data

“…As a consequence, inference of regulatory interactions from time-series transcriptome data alone may potentially lead to spurious results. Although quantitative proteomics techniques have much advanced recently [ 14 , 15 ], it is not yet possible to directly measure protein concentrations in vivo and in real time.…”

Metabolic profiling of recombinant Escherichia coli cultivations based on high‐throughput FT‐MIR spectroscopic analysis

“…However, to understand the complexity of the interrelationships between the genetic and physiological characteristics of the expression system and the cultivation general environment, cell metabolic information along the culture would be highly desired. Current metabolic information extraction from the recombinant cell along the bioprocess is usually performed by conventional cellular and molecular biology methods, which besides expensive are time‐ and labor‐intensive . Fourier Transform Infrared (FT‐IR) spectroscopy, an alternative and promising tool in the biomedical and pharmaceutical sciences, has emerged in the last decade as a powerful tool to obtain information about all stages of the production process in a simpler, rapid and economic mode.…”

“…Current metabolic information extraction from the recombinant cell along the bioprocess is usually performed by conventional cellular and molecular biology methods, which besides expensive are time-and labor-intensive. [16][17][18] Fourier Transform Infrared (FT-IR) spectroscopy, an alternative and promising tool in the biomedical and pharmaceutical sciences, has emerged in the last decade as a powerful tool to obtain information about all stages of the production process in a simpler, rapid and economic mode. FT-IR spectroscopy has been used to monitor recombinant cultivations, combined with multivariate data analysis such as partial least squares (PLS) regression, to quantitatively estimate from the spectrum the bioprocess critical variables, namely the biomass growth, the consumption of the main C-sources (e.g.…”