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Open Access Method

Model-independent fluxome profiling from 2H and 13C experiments for metabolic variant discrimination

Nicola Zamboni and Uwe Sauer*

Author Affiliations

Institute of Biotechnology, ETH Zürich, CH-8093 Zürich, Switzerland

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Genome Biology 2004, 5:R99  doi:10.1186/gb-2004-5-12-r99

Published: 16 November 2004

Abstract

We introduce a conceptually novel method for intracellular fluxome profiling from unsupervised statistical analysis of stable isotope labeling. Without a priori knowledge on the metabolic system, we identified characteristic flux fingerprints in 10 Bacillus subtilis mutants from 132 2H and 13C tracer experiments. Beyond variant discrimination, independent component analysis automatically mapped several fingerprints to their metabolic determinants. The approach is flexible and paves the way to large-scale fluxome profiling of any biological system and condition.