Quantitative approaches for analyzing fluxes through plant metabolic networks using NMR and stable isotope labeling
type: Dataset
description: The quantitative analysis of metabolic networks is a prerequisite for understanding the integration and regulation of plant metabolism and for devising rational approaches for manipulating resource allocation in plants. The analysis of steady state stable isotope labelling experiments using nuclear magnetic resonance (NMR) spectroscopy has developed into a powerful method for determining these fluxes in micro-organisms and its application to heterotrophic plant metabolism is increasing. After an introductory discussion of the well known role of stable isotopes in pathway delineation, the review considers their application to metabolic flux analysis in plants. These applications are divided into two groups – small scale analyses of fluxes through particular pathways and large scale analyses of multiple fluxes through metabolic networks – and the problems caused by the complexity of intermediary metabolism in plants are discussed. It is concluded that metabolic flux analysis provides a powerful method for defining the metabolic phenotype of wild type, mutant and transgenic plants and that its development should be pursued.
landing page: 1568-7767
keyword: 13c
keyword: carbohydrate-metabolism
keyword: compartmentation
keyword: fractional-enrichment
keyword: infoeu-reposemanticsarticle
keyword: isotopomer
keyword: journal-articles
keyword: metabolic-networks
keyword: nmr
keyword: sdvbbmbclife-sciences-q-biobiochemistry-molecular-biologybiochemistry-q-biobm
keyword: steady-state-analysis
issued: 2026-05-09T18:27:35.502961
modified: 2026-05-09T18:27:35.502965
language: en
contact point: Organization
  fn: CCSD

test_moissonnage_selune
type: Agent

Quantitative approaches for analyzing fluxes through plant metabolic networks using NMR and stable isotope labeling
type: Distribution
format: HTML
access URL: https://hal.science/hal-00086148
issued: 2026-05-09T18:27:35.509511
modified: 2026-05-09T18:27:35.490834