Proceeding talk – Theme: Systems.
Abstract
Understanding the rerouting of metabolic reaction fluxes upon perturbations has the potential to link changes in molecular state of a cellular system to alteration of growth. Yet, differential flux profiling on a genome-scale level remains one of the biggest challenges in systems biology. Here we present a computationally and experimentally facile approach, termed iReMet-Flux, which integrates relative metabolomics data in a metabolic model to predict differential fluxes at a genome-scale level. We employ iReMet-Flux with publically available metabolic profiles to predict reactions and pathways with altered fluxes in photo-autotrophically grown Arabidopsis and four photorespiratory mutants undergoing high-to-low CO2 acclimation. We also provide predictions about reactions and pathways which are most strongly regulated in the investigated experiments. The robustness and variability analyses, tailored to the formulation of iReMet-Flux, demonstrate that the findings provide biologically relevant information that is validated with external measurements of net CO2 exchange and biomass production.
Authors
Kevin Schwahn, Max Planck Institute of Molecular Plant Physiology, Germany
Max Sajitz-Hermstein, Max Planck Institute of Molecular Plant Physiology, Germany
Nadine Töpferj, Weizmann Institute of Science, Israel
Sabrina Kleessen, Targenomix GmbH, Germany
Alisdair Fernie, Max Planck Institute of Molecular Plant Physiology, Germany
Zoran Nikoloski, Max-Planck Institute of Molecular Plant Physiology, Germany