Planning optimal measurements of isotopomer distributions for estimation of metabolic fluxes.
BACKGROUND
Flux estimation using isotopomer information of metabolites is currently the most reliable method to obtain quantitative estimates of the activity of metabolic pathways. However, the development of isotopomer measurement techniques for intermediate metabolites is a demanding task. Careful planning of isotopomer measurements is thus needed to maximize the available flux information while minimizing the experimental effort.


RESULTS
In this paper we study the question of finding the smallest subset of metabolites to measure that ensure the same level of isotopomer information as the measurement of every metabolite in the metabolic network. We study the computational complexity of this optimization problem in the case of the so-called positional enrichment data, give methods for obtaining exact and fast approximate solutions, and evaluate empirically the efficacy of the proposed methods by analyzing a metabolic network that models the central carbon metabolism of Saccharomyces cerevisiae.
Rantanen
Ari
A
Department of Computer Science P.O. Box 68 (Gustaf Hällströmin katu 2b) 00014 University of Helsinki Finland. ajrantan@cs.helsinki.fi
Mielikäinen
Taneli
T
Rousu
Juho
J
Maaheimo
Hannu
H
Ukkonen
Esko
E
D000465:Algorithms; D002244:Carbon / Q000378:metabolism; D003198:Computer Simulation; D003947:Diagnostic Techniques, Radioisotope; D009682:Magnetic Resonance Spectroscopy / Q000379:methods*; D013058:Mass Spectrometry / Q000379:methods*; D008954:Models, Biological; D025941:Protein Interaction Mapping / Q000379:methods*; D012441:Saccharomyces cerevisiae / Q000378:metabolism*; D029701:Saccharomyces cerevisiae Proteins / Q000032:analysis / Q000378:metabolism*; D015398:Signal Transduction / Q000502:physiology*
D029701:Saccharomyces cerevisiae Proteins; D002244:Carbon