Literature DB >> 19422611

Metabolic flux analysis in plants: coping with complexity.

Doug K Allen1, Igor G L Libourel, Yair Shachar-Hill.   

Abstract

Theory and experience in metabolic engineering both show that metabolism operates at the network level. In plants, this complexity is compounded by a high degree of compartmentation and the synthesis of a very wide array of secondary metabolic products. A further challenge to understanding and predicting plant metabolic function is posed by our ignorance about the structure of metabolic networks even in well-studied systems. Metabolic flux analysis (MFA) provides tools to measure and model the functioning of metabolism, and is making significant contributions to coping with their complexity. This review gives an overview of different MFA approaches, the measurements required to implement them and the information they yield. The application of MFA methods to plant systems is then illustrated by several examples from the recent literature. Next, the challenges that plant metabolism poses for MFA are discussed together with ways that these can be addressed. Lastly, new developments in MFA are described that can be expected to improve the range and reliability of plant MFA in the coming years.

Mesh:

Substances:

Year:  2009        PMID: 19422611     DOI: 10.1111/j.1365-3040.2009.01992.x

Source DB:  PubMed          Journal:  Plant Cell Environ        ISSN: 0140-7791            Impact factor:   7.228


  36 in total

1.  IGERS: inferring Gibbs energy changes of biochemical reactions from reaction similarities.

Authors:  Kristian Rother; Sabrina Hoffmann; Sascha Bulik; Andreas Hoppe; Johann Gasteiger; Herrmann-Georg Holzhütter
Journal:  Biophys J       Date:  2010-06-02       Impact factor: 4.033

2.  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

3.  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 4.  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

Review 5.  Systems analysis of plant functional, transcriptional, physical interaction, and metabolic networks.

Authors:  George W Bassel; Allison Gaudinier; Siobhan M Brady; Lars Hennig; Seung Y Rhee; Ive De Smet
Journal:  Plant Cell       Date:  2012-10-30       Impact factor: 11.277

6.  High Flux Through the Oxidative Pentose Phosphate Pathway Lowers Efficiency in Developing Camelina Seeds.

Authors:  Lisa M Carey; Teresa J Clark; Rahul R Deshpande; Jean-Christophe Cocuron; Emily K Rustad; Yair Shachar-Hill
Journal:  Plant Physiol       Date:  2019-11-07       Impact factor: 8.340

7.  Kinetic isotope effects significantly influence intracellular metabolite (13) C labeling patterns and flux determination.

Authors:  Thomas M Wasylenko; Gregory Stephanopoulos
Journal:  Biotechnol J       Date:  2013-08-05       Impact factor: 4.677

8.  Novel Approach for High-Throughput Metabolic Screening of Whole Plants by Stable Isotopes.

Authors:  Lisa Maria Dersch; Veronique Beckers; Detlev Rasch; Guido Melzer; Christoph Bolten; Katina Kiep; Horst Becker; Oliver Ernst Bläsing; Regine Fuchs; Thomas Ehrhardt; Christoph Wittmann
Journal:  Plant Physiol       Date:  2016-03-10       Impact factor: 8.340

9.  Carbon and nitrogen provisions alter the metabolic flux in developing soybean embryos.

Authors:  Doug K Allen; Jamey D Young
Journal:  Plant Physiol       Date:  2013-01-11       Impact factor: 8.340

10.  Abscisic acid-responsive guard cell metabolomes of Arabidopsis wild-type and gpa1 G-protein mutants.

Authors:  Xiaofen Jin; Rui-Sheng Wang; Mengmeng Zhu; Byeong Wook Jeon; Reka Albert; Sixue Chen; Sarah M Assmann
Journal:  Plant Cell       Date:  2013-12-24       Impact factor: 11.277

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.