Literature DB >> 18257707

Metabolic flux analysis in plants: from intelligent design to rational engineering.

Igor G L Libourel1, Yair Shachar-Hill.   

Abstract

Metabolic flux analysis (MFA) is a rapidly developing field concerned with the quantification and understanding of metabolism at the systems level. The application of MFA has produced detailed maps of flow through metabolic networks of a range of plant systems. These maps represent detailed metabolic phenotypes, contribute significantly to our understanding of metabolism in plants, and have led to the discovery of new metabolic routes. The presentation of thorough statistical evaluation with current flux maps has set a new standard for the quality of quantitative flux studies. In microbial systems, powerful methods have been developed for the reconstruction of metabolic networks from genomic and transcriptomic data, pathway analysis, and predictive modeling. This review brings together the recent developments in quantitative MFA and predictive modeling. The application of predictive tools to high quality flux maps in particular promises to be important in the rational metabolic engineering of plants.

Mesh:

Year:  2008        PMID: 18257707     DOI: 10.1146/annurev.arplant.58.032806.103822

Source DB:  PubMed          Journal:  Annu Rev Plant Biol        ISSN: 1543-5008            Impact factor:   26.379


  29 in total

1.  Musings about the effects of environment on photosynthesis.

Authors:  David W Lawlor
Journal:  Ann Bot       Date:  2009-02       Impact factor: 4.357

Review 2.  Metabolic networks: how to identify key components in the regulation of metabolism and growth.

Authors:  Mark Stitt; Ronan Sulpice; Joost Keurentjes
Journal:  Plant Physiol       Date:  2009-12-11       Impact factor: 8.340

3.  Adding biotic complexity alters the metabolic benefits of mutualism.

Authors:  William R Harcombe; Alex Betts; Jason W Shapiro; Christopher J Marx
Journal:  Evolution       Date:  2016-06-24       Impact factor: 3.694

4.  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

5.  A Genome-Scale Metabolic Model of Soybean (Glycine max) Highlights Metabolic Fluxes in Seedlings.

Authors:  Thiago Batista Moreira; Rahul Shaw; Xinyu Luo; Oishik Ganguly; Hyung-Seok Kim; Lucas Gabriel Ferreira Coelho; Chun Yue Maurice Cheung; Thomas Christopher Rhys Williams
Journal:  Plant Physiol       Date:  2019-06-06       Impact factor: 8.340

Review 6.  Plant metabolic modeling: achieving new insight into metabolism and metabolic engineering.

Authors:  Kambiz Baghalian; Mohammad-Reza Hajirezaei; Falk Schreiber
Journal:  Plant Cell       Date:  2014-10-24       Impact factor: 11.277

7.  Quantifying the labeling and the levels of plant cell wall precursors using ion chromatography tandem mass spectrometry.

Authors:  Ana P Alonso; Rebecca J Piasecki; Yan Wang; Russell W LaClair; Yair Shachar-Hill
Journal:  Plant Physiol       Date:  2010-05-04       Impact factor: 8.340

Review 8.  The importance of accurately correcting for the natural abundance of stable isotopes.

Authors:  Firas S Midani; Michelle L Wynn; Santiago Schnell
Journal:  Anal Biochem       Date:  2017-01-11       Impact factor: 3.365

9.  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

10.  Sulphur flux through the sulphate assimilation pathway is differently controlled by adenosine 5'-phosphosulphate reductase under stress and in transgenic poplar plants overexpressing gamma-ECS, SO, or APR.

Authors:  Ursula Scheerer; Robert Haensch; Ralf R Mendel; Stanislav Kopriva; Heinz Rennenberg; Cornelia Herschbach
Journal:  J Exp Bot       Date:  2009-11-18       Impact factor: 6.992

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