Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6494550 | Metabolic Engineering | 2014 | 12 Pages |
Abstract
Advances in metabolic engineering are enabling the creation of a large number of cell factories. However, high-throughput platforms do not yet exist for rapidly analyzing the metabolic network of the engineered cells. To fill the gap, we developed an integrated solution for fluxome profiling of large sets of biological systems and conditions. This platform combines a robotic system for 13C-labelling experiments and sampling of labelled material with NMR-based isotopic fingerprinting and automated data interpretation. As a proof-of-concept, this workflow was applied to discriminate between Escherichia coli mutants with gradual expression of the glucose-6-phosphate dehydrogenase. Metabolic variants were clearly discriminated while pathways that support metabolic flexibility towards modulation of a single enzyme were elucidating. By directly connecting the data flow between cell cultivation and flux quantification, considerable advances in throughput, robustness, release of resources and screening capacity were achieved. This will undoubtedly facilitate the development of efficient cell factories.
Keywords
TSP-d4G6PDHPYROD600HCAFluxomicsTCAPPPHEPARSDCDWnuclear magnetic resonancePCAAutomationrelative standard deviationdissolved oxygenHigh-throughputhierarchical clustering analysisStatistical analysisPrincipal component analysisoptical density at 600 nmNMRHigh throughputLiquid handlingMass spectrometryFlux calculationpentose phosphate pathwaywild typecell dry weighttricarboxylic acid cycleglucose-6-phosphate dehydrogenase
Related Topics
Physical Sciences and Engineering
Chemical Engineering
Bioengineering
Authors
Stéphanie Heux, Juliette Poinot, Stéphane Massou, Serguei Sokol, Jean-Charles Portais,