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

Ana R Ferreira,João Ml Dias,Inês A Isidro,Rui Mc Portela,Ana P Teixeira,Nuno Carinhas,Moritz Von Stosch,Rui Oliveira

doi:10.1186/1752-0509-5-181

Ana R Ferreira, João Ml Dias + Show 6 more

Open Access

https://doi.org/10.1186/1752-0509-5-181

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Abstract

BackgroundElementary 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.ResultsHere 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.ConclusionsOverall, 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.

Highlights

Elementary flux modes (EFM) are unique and non-decomposable sets of metabolic reactions able to operate coherently in steady-state
An elementary flux mode (EFM) can be defined as a minimal set of enzymes able to operate at steady state, with the enzymes weighted by the relative flux they need to carry for the mode to function [1]
Projection to Latent Pathways (PLP) Algorithm Problem statement By applying steady-state material balance equations to a metabolic network with m metabolites and q metabolic reactions, the following system of linear algebraic equations is obtained: N·r=0 (1a) rk > 0 (1b) with r a vector of q metabolic fluxes, rk the subset of fluxes associated to irreversible reactions and N a m×q stoichiometric matrix

Summary

Introduction

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. Most of these EFM are either thermodynamically unfeasible or inactive at pre-set environmental conditions. Any particular steady-state flux distribution can be expressed as a non-negative linear combination of EFM Motivated by these unique properties, EFM analysis has become a widespread technique for systems level metabolic pathways analysis [1,2,3,4,5,6,7,8]. This allowed the a priori reduction, without any experimental data, from the initial 369 to 35 EFM for a yeast metabolic network fermenting both glucose and xylose

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