caa a22 4500 528785273 20200328032311.0 cr unu---uuuuu 180924e200806 xx s 000 0 eng 10.3929/ethz-a-005752017 doi 10.1186/1471-2105-9-266 doi (ETHRESEARCH)oai:www.research-collection.ethz.ch:20.500.11850/287441 An analytic and systematic framework for estimating metabolic flux ratios from ¹³C tracer experiments [Elektronische Daten] [Ari Rantanen, Juho Rousu, Paula Jouhten, Nicola; id_orcid 0000-0003-1271-1021 Zamboni, Hannu Maaheimo, Esko Ukkonen] Open access ethresearch Background Metabolic fluxes provide invaluable insight on the integrated response of a cell to environmental stimuli or genetic modifications. Current computational methods for estimating the metabolic fluxes from 13C isotopomer measurement data rely either on manual derivation of analytic equations constraining the fluxes or on the numerical solution of a highly nonlinear system of isotopomer balance equations. In the first approach, analytic equations have to be tediously derived for each organism, substrate or labelling pattern, while in the second approach, the global nature of an optimum solution is difficult to prove and comprehensive measurements of external fluxes to augment the 13C isotopomer data are typically needed. Results We present a novel analytic framework for estimating metabolic flux ratios in the cell from 13C isotopomer measurement data. In the presented framework, equation systems constraining the fluxes are derived automatically from the model of the metabolism of an organism. The framework is designed to be applicable with all metabolic network topologies, 13C isotopomer measurement techniques, substrates and substrate labelling patterns. By analyzing nuclear magnetic resonance (NMR) and mass spectrometry (MS) measurement data obtained from the experiments on glucose with the model micro-organisms Bacillus subtilis and Saccharomyces cerevisiae we show that our framework is able to automatically produce the flux ratios discovered so far by the domain experts with tedious manual analysis. Furthermore, we show by in silico calculability analysis that our framework can rapidly produce flux ratio equations - as well as predict when the flux ratios are unobtainable by linear means - also for substrates not related to glucose. Conclusion The core of 13C metabolic flux analysis framework introduced in this article constitutes of flow and independence analysis of metabolic fragments and techniques for manipulating isotopomer measurements with vector space techniques. These methods facilitate efficient, analytic computation of the ratios between the fluxes of pathways that converge to a common junction metabolite. The framework can been seen as a generalization and formalization of existing tradition for computing metabolic flux ratios where equations constraining flux ratios are manually derived, usually without explicitly showing the formal proofs of the validity of the equations. Creative Commons Attribution 2.0 Generic http://creativecommons.org/licenses/by/2.0 ethresearch STOFFWECHSELWEGE UND STOFFWECHSELZYKLEN (BIOCHEMIE) ethresearch ZELLMETABOLISMUS + ZELLERNÄHRUNG (CYTOLOGIE) ethresearch KOHLENSTOFF-13-ISOTOP ethresearch GLUKOSE (BIOCHEMIE) ethresearch BACILLUS SUBTILIS (MIKROBIOLOGIE) ethresearch METABOLIC PATHWAYS + METABOLIC CYCLES (BIOCHEMISTRY) ethresearch CELL NUTRITION + CELL METABOLISM (CYTOLOGY) ethresearch CARBON-13 ISOTOPE ethresearch GLUCOSE (BIOCHEMISTRY) ethresearch BACILLUS SUBTILIS (MICROBIOLOGY) ethresearch SACCHAROMYCES (MYKOLOGIE) ethresearch SACCHAROMYCES (MYCOLOGY) ethresearch Metabolic Network ethresearch Metabolic Flux ethresearch Flux Distribution ethresearch Flux Ratio ethresearch Flux Balance Analysis ethresearch Life sciences ethresearch Rantanen Ari joint author Rousu Juho joint author Jouhten Paula joint author Zamboni Nicola; id_orcid 0000-0003-1271-1021 joint author Maaheimo Hannu joint author Ukkonen Esko joint author BMC Bioinformatics London : BioMed Central 9, p. 266 1471-2105 http://hdl.handle.net/20.500.11850/287441 text/html WWW-Backlink auf das Repository (Open access) 1 Journal Article ethresearch ETHRESEARCH 856 40 http://hdl.handle.net/20.500.11850/287441 text/html WWW-Backlink auf das Repository (Open access) ETHRESEARCH 700 1- Rantanen Ari joint author ETHRESEARCH 700 1- Rousu Juho joint author ETHRESEARCH 700 1- Jouhten Paula joint author ETHRESEARCH 700 1- Zamboni Nicola; id_orcid 0000-0003-1271-1021 joint author ETHRESEARCH 700 1- Maaheimo Hannu joint author ETHRESEARCH 700 1- Ukkonen Esko joint author ETHRESEARCH 773 0- BMC Bioinformatics London : BioMed Central 9, p. 266 1471-2105 BK010053 XK010053 XK010000 ETHRESEARCH ETHRESEARCH ETHRESEARCH Journal Article Open access