Dataset Information

Projection to latent pathways (PLP): a constrained projection to latent variables (PLS) method for elementary flux modes discrimination.

ABSTRACT: BACKGROUND: Elementary flux modes (EFM) are unique and non-decomposable sets of metabolic reactions able to operate coherently in steady-state. A metabolic network has in general a very high number of EFM reflecting the typical functional redundancy of biological systems. However, most of these EFM are either thermodynamically unfeasible or inactive at pre-set environmental conditions. RESULTS: Here we present a new algorithm that discriminates the "active" set of EFM on the basis of dynamic envirome data. The algorithm merges together two well-known methods: projection to latent structures (PLS) and EFM analysis, and is therefore termed projection to latent pathways (PLP). PLP has two concomitant goals: (1) maximisation of correlation between EFM weighting factors and measured envirome data and (2) minimisation of redundancy by eliminating EFM with low correlation with the envirome. CONCLUSIONS: Overall, our results demonstrate that PLP slightly outperforms PLS in terms of predictive power. But more importantly, PLP is able to discriminate the subset of EFM with highest correlation with the envirome, thus providing in-depth knowledge of how the environment controls core cellular functions. This offers a significant advantage over PLS since its abstract structure cannot be associated with the underlying biological structure.

SUBMITTER: Ferreira AR

PROVIDER: S-EPMC3750108 | biostudies-literature | 2011

REPOSITORIES: biostudies-literature

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Projection to latent pathways (PLP): a constrained projection to latent variables (PLS) method for elementary flux modes discrimination.

Ferreira Ana R AR Dias João M L JM Teixeira Ana P AP Carinhas Nuno N Portela Rui M C RM Isidro Inês A IA von Stosch Moritz M Oliveira Rui R

BMC systems biology 20111101

<h4>Background</h4>Elementary flux modes (EFM) are unique and non-decomposable sets of metabolic reactions able to operate coherently in steady-state. A metabolic network has in general a very high number of EFM reflecting the typical functional redundancy of biological systems. However, most of these EFM are either thermodynamically unfeasible or inactive at pre-set environmental conditions.<h4>Results</h4>Here we present a new algorithm that discriminates the "active" set of EFM on the basis o ...[more]

PMID: 22044634

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Project description:Background(13)C metabolic flux analysis is one of the pertinent ways to compare two or more physiological states. From a more theoretical standpoint, the structural properties of metabolic networks can be analysed to explore feasible metabolic behaviours and to define the boundaries of steady state flux distributions. Elementary flux mode analysis is one of the most efficient methods for performing this analysis. In this context, recent approaches have tended to compare experimental flux measurements with topological network analysis.ResultsMetabolic networks describing the main pathways of central carbon metabolism were set up for a bacteria species (Corynebacterium glutamicum) and a plant species (Brassica napus) for which experimental flux maps were available. The structural properties of each network were then studied using the concept of elementary flux modes. To do this, coefficients of flux efficiency were calculated for each reaction within the networks by using selected sets of elementary flux modes. Then the relative differences - reflecting the change of substrate i.e. a sugar source for C. glutamicum and a nitrogen source for B. napus - of both flux efficiency and flux measured experimentally were compared. For both organisms, there is a clear relationship between these parameters, thus indicating that the network structure described by the elementary flux modes had captured a significant part of the metabolic activity in both biological systems. In B. napus, the extension of the elementary flux mode analysis to an enlarged metabolic network still resulted in a clear relationship between the change in the coefficients and that of the measured fluxes. Nevertheless, the limitations of the method to fit some particular fluxes are discussed.ConclusionThis consistency between EFM analysis and experimental flux measurements, validated on two metabolic systems allows us to conclude that elementary flux mode analysis could be a useful tool to complement (13)C metabolic flux analysis, by allowing the prediction of changes in internal fluxes before carbon labelling experiments.

Dataset Information

Projection to latent pathways (PLP): a constrained projection to latent variables (PLS) method for elementary flux modes discrimination.

Publications

Projection to latent pathways (PLP): a constrained projection to latent variables (PLS) method for elementary flux modes discrimination.

Similar Datasets

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