Literature DB >> 15727037

Revealing metabolic phenotypes in plants: inputs from NMR analysis.

R G Ratcliffe1, Y Shachar-Hill.   

Abstract

Assessing the performance of the plant metabolic network, with its varied biosynthetic capacity and its characteristic subcellular compartmentation, remains a considerable challenge. The complexity of the network is such that it is not yet possible to build large-scale predictive models of the fluxes it supports, whether on the basis of genomic and gene expression analysis or on the basis of more traditional measurements of metabolites and their interconversions. This limits the agronomic and biotechnological exploitation of plant metabolism, and it undermines the important objective of establishing a rational metabolic engineering strategy. Metabolic analysis is central to removing this obstacle and currently there is particular interest in harnessing high-throughput and/or large-scale analyses to the task of defining metabolic phenotypes. Nuclear magnetic resonance (NMR) spectroscopy contributes to this objective by providing a versatile suite of analytical techniques for the detection of metabolites and the fluxes between them. The principles that underpin the analysis of plant metabolism by NMR are described, including a discussion of the measurement options for the detection of metabolites in vivo and in vitro, and a description of the stable isotope labelling experiments that provide the basis for metabolic flux analysis. Despite a relatively low sensitivity, NMR is suitable for high-throughput system-wide analyses of the metabolome, providing methods for both metabolite fingerprinting and metabolite profiling, and in these areas NMR can contribute to the definition of plant metabolic phenotypes that are based on metabolic composition. NMR can also be used to investigate the operation of plant metabolic networks. Labelling experiments provide information on the operation of specific pathways within the network, and the quantitative analysis of steady-state labelling experiments leads to the definition of large-scale flux maps for heterotrophic carbon metabolism. These maps define multiple unidirectional fluxes between branch-points in the metabolic network, highlighting the existence of substrate cycles and discriminating in favourable cases between fluxes in the cytosol and plastid. Flux maps can be used to define a functionally relevant metabolic phenotype and the extensive application of such maps in microbial systems suggests that they could have important applications in characterising the genotypes produced by plant genetic engineering.

Entities:  

Mesh:

Year:  2005        PMID: 15727037     DOI: 10.1017/s1464793104006530

Source DB:  PubMed          Journal:  Biol Rev Camb Philos Soc        ISSN: 0006-3231


  15 in total

1.  Inference and Prediction of Metabolic Network Fluxes.

Authors:  Zoran Nikoloski; Richard Perez-Storey; Lee J Sweetlove
Journal:  Plant Physiol       Date:  2015-09-21       Impact factor: 8.340

2.  Capturing metabolite channeling in metabolic flux phenotypes.

Authors:  Thomas C R Williams; Lee J Sweetlove; R George Ratcliffe
Journal:  Plant Physiol       Date:  2011-09-06       Impact factor: 8.340

Review 3.  NMR analysis of plant nitrogen metabolism.

Authors:  F Mesnard; R G Ratcliffe
Journal:  Photosynth Res       Date:  2005       Impact factor: 3.573

4.  Dynamic phosphometabolomic profiling of human tissues and transgenic models by 18O-assisted ³¹P NMR and mass spectrometry.

Authors:  Emirhan Nemutlu; Song Zhang; Anu Gupta; Nenad O Juranic; Slobodan I Macura; Andre Terzic; Arshad Jahangir; Petras Dzeja
Journal:  Physiol Genomics       Date:  2012-01-10       Impact factor: 3.107

5.  Metabolic network fluxes in heterotrophic Arabidopsis cells: stability of the flux distribution under different oxygenation conditions.

Authors:  Thomas C R Williams; Laurent Miguet; Shyam K Masakapalli; Nicholas J Kruger; Lee J Sweetlove; R George Ratcliffe
Journal:  Plant Physiol       Date:  2008-07-30       Impact factor: 8.340

6.  Subcellular flux analysis of central metabolism in a heterotrophic Arabidopsis cell suspension using steady-state stable isotope labeling.

Authors:  Shyam K Masakapalli; Pascaline Le Lay; Joanna E Huddleston; Naomi L Pollock; Nicholas J Kruger; R George Ratcliffe
Journal:  Plant Physiol       Date:  2009-11-25       Impact factor: 8.340

7.  NMR (¹H) analysis of crude extracts detects light stress in Beta vulgaris and Spinacia oleracea leaves.

Authors:  Carmela Rosaria Guadagno; Marina Della Greca; Amalia Virzo De Santo; Nicola D'Ambrosio
Journal:  Photosynth Res       Date:  2013-05-10       Impact factor: 3.573

8.  Quantitative 1H nuclear magnetic resonance metabolite profiling as a functional genomics platform to investigate alkaloid biosynthesis in opium poppy.

Authors:  Jillian M Hagel; Aalim M Weljie; Hans J Vogel; Peter J Facchini
Journal:  Plant Physiol       Date:  2008-06-11       Impact factor: 8.340

Review 9.  18O-assisted dynamic metabolomics for individualized diagnostics and treatment of human diseases.

Authors:  Emirhan Nemutlu; Song Zhang; Nenad O Juranic; Andre Terzic; Slobodan Macura; Petras Dzeja
Journal:  Croat Med J       Date:  2012-12       Impact factor: 1.351

Review 10.  The use of metabolomics to dissect plant responses to abiotic stresses.

Authors:  Toshihiro Obata; Alisdair R Fernie
Journal:  Cell Mol Life Sci       Date:  2012-08-12       Impact factor: 9.261

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.