Experimental flux measurements on a network scale

Jörg Schwender

doi:10.3389/fpls.2011.00063

Abstract

Metabolic flux is a fundamental property of living organisms. In recent years, methods for measuring metabolic flux in plants on a network scale have evolved further. One major challenge in studying flux in plants is the complexity of the plant’s metabolism. In particular, in the presence of parallel pathways in multiple cellular compartments, the core of plant central metabolism constitutes a complex network. Hence, a common problem with the reliability of the contemporary results of 13C-Metabolic Flux Analysis in plants is the substantial reduction in complexity that must be included in the simulated networks; this omission partly is due to limitations in computational simulations. Here, I discuss recent emerging strategies that will better address these shortcomings.

Highlights

Isotopic tracers have different but important uses in metabolic research
Among the various approaches to stoichiometrical modeling of cell metabolism (Llaneras and Pico, 2008), 13C-Metabolic Flux Analysis (13C-MFA) is a method that combines a knowledge of cell metabolism with 13C-tracer experiments to analyze the in vivo flux distribution in the network of central cellular primary metabolism
Various studies focused on the distribution of flux in central metabolism in the developing seeds and embryos of rapeseed and Arabidopsis (Schwender and Ohlrogge, 2002; Schwender et al, 2003, 2004a, 2006; Junker et al, 2007; Lonien and Schwender, 2009), soybean (Sriram et al, 2004; Iyer et al, 2008; Allen et al, 2009b), sunflower (Alonso et al, 2007a), and in developing maize endosperm or embryos (Ettenhuber et al, 2005; Spielbauer et al, 2006; Alonso et al, 2010, 2011)

Summary

Jörg Schwender *

Reviewed by: Alisdair Fernie, Max Planck Institute for Plant Physiology, Germany Lee Sweetlove, University of Oxford, UK Ganesh Sriram, University of Maryland, USA. Metabolic flux is a fundamental property of living organisms. Methods for measuring metabolic flux in plants on a network scale have evolved further. One major challenge in studying flux in plants is the complexity of the plant’s metabolism. In the presence of parallel pathways in multiple cellular compartments, the core of plant central metabolism constitutes a complex network. A common problem with the reliability of the contemporary results of 13C-Metabolic Flux Analysis in plants is the substantial reduction in complexity that must be included in the simulated networks; this omission partly is due to limitations in computational simulations. I discuss recent emerging strategies that will better address these shortcomings

INTRODUCTION

Stoichiometric network

CONCLUSION