Planning optimal measurements of isotopomer distributions for estimation of metabolic fluxes

A. Rantanen (Corresponding Author), T. Mielikäinen, Juha Rousu, Hannu Maaheimo, Esko Ukkonen

Research output: Contribution to journalArticleScientificpeer-review

23 Citations (Scopus)

Abstract

Motivation: 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.
Original languageEnglish
Pages (from-to)1198-1206
Number of pages9
JournalBioinformatics
Volume22
Issue number10
DOIs
Publication statusPublished - 2006
MoE publication typeA1 Journal article-refereed

Fingerprint

Metabolites
Metabolic Networks and Pathways
Metabolic Network
Planning
Fluxes
Measurement Techniques
Saccharomyces Cerevisiae
Metabolism
Network Model
Saccharomyces cerevisiae
Efficacy
Pathway
Carbon
Computational Complexity
Approximate Solution
Maximise
Yeast
Optimization Problem
Computational complexity
Subset

Keywords

  • metabolites
  • metabolic flux analysis
  • isotopomer distribution
  • metabolic profiling
  • metabolomics

Cite this

Rantanen, A. ; Mielikäinen, T. ; Rousu, Juha ; Maaheimo, Hannu ; Ukkonen, Esko. / Planning optimal measurements of isotopomer distributions for estimation of metabolic fluxes. In: Bioinformatics. 2006 ; Vol. 22, No. 10. pp. 1198-1206.
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Planning optimal measurements of isotopomer distributions for estimation of metabolic fluxes. / Rantanen, A. (Corresponding Author); Mielikäinen, T.; Rousu, Juha; Maaheimo, Hannu; Ukkonen, Esko.

In: Bioinformatics, Vol. 22, No. 10, 2006, p. 1198-1206.

Research output: Contribution to journalArticleScientificpeer-review

TY - JOUR

T1 - Planning optimal measurements of isotopomer distributions for estimation of metabolic fluxes

AU - Rantanen, A.

AU - Mielikäinen, T.

AU - Rousu, Juha

AU - Maaheimo, Hannu

AU - Ukkonen, Esko

PY - 2006

Y1 - 2006

N2 - Motivation: 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.

AB - Motivation: 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.

KW - metabolites

KW - metabolic flux analysis

KW - isotopomer distribution

KW - metabolic profiling

KW - metabolomics

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DO - 10.1093/bioinformatics/btl069

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VL - 22

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JO - Bioinformatics

JF - Bioinformatics

SN - 1367-4803

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