Reporter pathway analysis from transcriptome data: Metabolite-centric versus Reaction-centric approach

Abstract

A systems-based investigation of the effect of perturbations on metabolic machinery is crucial to elucidate the mechanism behind perturbations. One way to investigate the perturbation-induced changes within the cell metabolism is to focus on pathway-level effects. In this study, three different perturbation types (genetic, environmental and disease-based) are analyzed to compute a list of reporter pathways, metabolic pathways which are significantly affected from a perturbation. The most common omics data type, transcriptome, is used as an input to the bioinformatic analysis. The pathways are scored by two alternative approaches: by averaging the changes in the expression levels of the genes controlling the associated reactions (reaction-centric), and by averaging the changes in the associated metabolites which were scored based on the associated genes (metabolite-centric). The analysis reveals the superiority of the novel metabolite-centric approach over the commonly used reaction-centric approach since it is based on metabolites which better represent the cross-talk among different pathways, enabling a more global and realistic cataloguing of network-wide perturbation effects.