TY - JOUR
T1 - An analytic and systematic framework for estimating metabolic flux ratios from 13C tracer experiments
AU - Rantanen, Ari
AU - Rousu, Juho
AU - Jouhten, Paula
AU - Zamboni, Nicola
AU - Maaheimo, Hannu
AU - Ukkonen, Esko
N1 - Funding Information:
This research has been supported by Academy of Finland (SYSBIO programme, grant 207436, SYSFYS project). We thank Uwe Sauer and Merja Penttilä for providing the data and for their comments to the work presented in the article; Markus Heinonen, Esa Pitkänen and Arto Åkerlund for the implementation of software tools supporting the presented framework; Roelco Kleijn, Sarah-Maria Fendt, Simon Tännler and Martin Rühl for providing the data and for fruitful discussions. We also thank the anonymous reviewers whose comments helped us to improve the manuscript substantially.
PY - 2008/6/6
Y1 - 2008/6/6
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=45749090110&partnerID=8YFLogxK
U2 - 10.1186/1471-2105-9-266
DO - 10.1186/1471-2105-9-266
M3 - Article
C2 - 18534038
AN - SCOPUS:45749090110
SN - 1471-2105
VL - 9
JO - BMC Bioinformatics
JF - BMC Bioinformatics
M1 - 266
ER -