Literature DB >> 17355439

Estimation of metabolic fluxes, expression levels and metabolite dynamics of a secondary metabolic pathway in potato using label pulse-feeding experiments combined with kinetic network modelling and simulation.

Elmar Heinzle1, Fumio Matsuda, Hisashi Miyagawa, Kyo Wakasa, Takaaki Nishioka.   

Abstract

In this paper we present a method that allows dynamic flux analysis without a priori kinetic knowledge. This method was developed and validated using the pulse-feeding experimental data obtained in our previous study (Matsuda et al., 2005), in which incorporation of exogenously applied l-phenylalanine-d(5) into seven phenylpropanoid metabolites in potato tubers was determined. After identification of the topology of the metabolic network of these biosynthetic pathways, the system was described by dynamic mass balances in combination with power-law kinetics. After the first simulations, some reactions were removed from the network because they were not contributing significantly to network behaviour. As a next step, the exponents of the power-law kinetics were identified and then kept at fixed values during further analysis. The model was tested for statistical reliability using Monte Carlo simulations. Most fluxes could be identified with high accuracy. The two test cases, control and after elicitation, were clearly distinguished, and with elicitation fluxes to N-p-coumaroyloctopamine (pCO) and N-p-coumaroyltyramine (pCT) increased significantly, whereas those for chlorogenic acid (CGA) and p-coumaroylshikimate decreased significantly. According to the model, increases in the first two fluxes were caused by induction/derepression mechanisms. The decreases in the latter two fluxes were caused by decreased concentrations of their substrates, which in turn were caused by increased activity of the pCO- and pCT-producing enzymes. Flux-control analysis showed that, in most cases, flux control was changed after application of elicitor. Thus the results revealed potential targets for improving actions against tissue wounding and pathogen attack.

Entities:  

Mesh:

Year:  2007        PMID: 17355439     DOI: 10.1111/j.1365-313X.2007.03037.x

Source DB:  PubMed          Journal:  Plant J        ISSN: 0960-7412            Impact factor:   6.417


  8 in total

1.  On the discordance of metabolomics with proteomics and transcriptomics: coping with increasing complexity in logic, chemistry, and network interactions scientific correspondence.

Authors:  Alisdair R Fernie; Mark Stitt
Journal:  Plant Physiol       Date:  2012-01-17       Impact factor: 8.340

2.  Identification of genes in the phenylalanine metabolic pathway by ectopic expression of a MYB transcription factor in tomato fruit.

Authors:  Valeriano Dal Cin; Denise M Tieman; Takayuki Tohge; Ryan McQuinn; Ric C H de Vos; Sonia Osorio; Eric A Schmelz; Mark G Taylor; Miriam T Smits-Kroon; Robert C Schuurink; Michel A Haring; James Giovannoni; Alisdair R Fernie; Harry J Klee
Journal:  Plant Cell       Date:  2011-07-12       Impact factor: 11.277

Review 3.  Fluxomics: mass spectrometry versus quantitative imaging.

Authors:  Wolfgang Wiechert; Oliver Schweissgut; Hitomi Takanaga; Wolf B Frommer
Journal:  Curr Opin Plant Biol       Date:  2007-05-03       Impact factor: 7.834

4.  Flux-balance modeling of plant metabolism.

Authors:  Lee J Sweetlove; R George Ratcliffe
Journal:  Front Plant Sci       Date:  2011-08-11       Impact factor: 5.753

5.  Application of stable isotope-assisted metabolomics for cell metabolism studies.

Authors:  Le You; Baichen Zhang; Yinjie J Tang
Journal:  Metabolites       Date:  2014-03-31

6.  A 13C isotope labeling method for the measurement of lignin metabolic flux in Arabidopsis stems.

Authors:  Peng Wang; Longyun Guo; Rohit Jaini; Antje Klempien; Rachel M McCoy; John A Morgan; Natalia Dudareva; Clint Chapple
Journal:  Plant Methods       Date:  2018-06-23       Impact factor: 4.993

7.  Shoot tip culture: a step towards 13C metabolite flux analysis of sink leaf metabolism.

Authors:  Somnath Koley; Manish L Raorane; Björn H Junker
Journal:  Plant Methods       Date:  2019-05-20       Impact factor: 4.993

Review 8.  Bidirectionality and compartmentation of metabolic fluxes are revealed in the dynamics of isotopomer networks.

Authors:  David W Schryer; Pearu Peterson; Toomas Paalme; Marko Vendelin
Journal:  Int J Mol Sci       Date:  2009-04-17       Impact factor: 6.208

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.