Journal
METABOLIC ENGINEERING
Volume 41, Issue -, Pages 159-172Publisher
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.ymben.2017.03.008
Keywords
Metabolic control analysis; Quantitative metabolomics; Stimulus response experiment
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Funding
- Bundesministerium fur Bildung und Forschung (BMBF, Berlin, Germany) [0315867]
- Evonik Nutrition Care GmbH
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The identification of promising metabolic engineering targets is a key issue in metabolic control analysis (MCA). Conventional approaches make intensive use of model-based studies, such as exploiting post-pulse metabolic dynamics after proper perturbation of the microbial system. Here, we present an easy-to-use, purely data-driven approach, defining pool efflux capacities (PEC) for identifying reactions that exert the highest flux control in linear pathways. Comparisons with linlog-based MCA and data-driven substrate elasticities (DDSE) showed that similar key control steps were identified using PEC. Using the example of L-methionine production with recombinant Escherichia coli, PEC consistently and robustly identified main flux controls using perturbation data after a non-labeled C-12-L-serine stimulus. Furthermore, the application of full-labeled C-13-L-serine stimuli yielded additional insights into stimulus propagation to L-methionine. PEC analysis performed on the C-13 data set revealed the same targets as the C-12 data set. Notably, the typical drawback of metabolome analysis, namely, the omnipresent leakage of metabolites, was excluded using the C-13 PEC approach.
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