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Bidirectional reaction steps in metabolic networks: II. Flux estimation and statistical analysis
Author(s) -
Wiechert Wolfgang,
Siefke Claudia,
de Graaf Albert A.,
Marx Achim
Publication year - 1997
Publication title -
biotechnology and bioengineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.136
H-Index - 189
eISSN - 1097-0290
pISSN - 0006-3592
DOI - 10.1002/(sici)1097-0290(19970705)55:1<118::aid-bit13>3.0.co;2-i
Subject(s) - flux balance analysis , metabolic flux analysis , nonlinear system , corynebacterium glutamicum , biological system , covariance , computer science , chemistry , mathematics , statistics , physics , biology , biochemistry , quantum mechanics , metabolism , gene
Metabolic carbon labelling experiments enable a large amount of extracellular fluxes and intracellular carbon isotope enrichments to be measured. Since the relation between the measured quantities and the unknown intracellular metabolic fluxes is given by bilinear balance equations, flux determination from this data set requires the numerical solution of a nonlinear inverse problem. To this end, a general algorithm for flux estimation from metabolic carbon labelling experiments based on the least squares approach is developed in this contribution and complemented by appropriate tools for statistical analysis. The linearization technique usually applied for the computation of nonlinear confidence regions is shown to be inappropriate in the case of large exchange fluxes. For this reason a sophisticated compactification transformation technique for nonlinear statistical analysis is developed. Statistical analysis is then performed by computing appropriate statistical quality measures like output sensitivities, parameter sensitivities and the parameter covariance matrix. This allows one to determine the order of magnitude of exchange fluxes in most practical situations. An application study with a large data set from lysine‐producing Corynebacterium glutamicum demonstrates the power and limitations of the carbon‐labelling technique. It is shown that all intracellular fluxes in central metabolism can be quantitated without assumptions on intracellular energy yields. At the same time several exchange fluxes are determined which is invaluable information for metabolic engineering. © 1997 John Wiley & Sons, Inc. Biotechnol Bioeng 55: 118–135, 1997.