Genome-Scale Modeling of Photorespiratory Pathway Manipulation

Abstract

Quantifying the redistribution of metabolic reaction fluxes under experimental scenarios that affect the photorespiratory pathway can provide insights about the coupling of this pathway with other parts of metabolism. However, differential flux profiling on a genome-scale level remains the biggest challenge in modern systems biology. Here we present a protocol for applying a constraint-based approach, termed iReMet-Flux, that integrates data about relative metabolite levels in a stoichiometric metabolic model to predict differential fluxes at a genome-scale level under mild modeling assumptions. We demonstrate how iReMet-Flux can be employed to investigate the interplay between photorespiration and other pathways at a genome-scale level, and complements flux profiling methods based on radioactive tracer labeling.