Time-resolved metabolomics reveals metabolic modulation in rice foliage

Shigeru Sato, Masanori Arita, Tomoyoshi Soga, Takaaki Nishioka, Masaru Tomita

Research output: Contribution to journalArticle

45 Citations (Scopus)

Abstract

Background: To elucidate the interaction of dynamics among modules that constitute biological systems, comprehensive datasets obtained from "omics" technologies have been used. In recent plant metabolomics approaches, the reconstruction of metabolic correlation networks has been attempted using statistical techniques. However, the results were unsatisfactory and effective data-mining techniques that apply appropriate comprehensive datasets are needed. Results: Using capillary electrophoresis mass spectrometry (CE-MS) and capillary electrophoresis diode-array detection (CE-DAD), we analyzed the dynamic changes in the level of 56 basic metabolites in plant foliage (Oryza sativa L. ssp. japonica) at hourly intervals over a 24-hr period. Unsupervised clustering of comprehensive metabolic profiles using Kohonen's self-organizing map (SOM) allowed classification of the biochemical pathways activated by the light and dark cycle. The carbon and nitrogen (C/N) metabolism in both periods was also visualized as a phenotypic linkage map that connects network modules on the basis of traditional metabolic pathways rather than pairwise correlations among metabolites. The regulatory networks of C/N assimilation/dissimilation at each time point were consistent with previous works on plant metabolism. In response to environmental stress, glutathione and spermidine fluctuated synchronously with their regulatory targets. Adenine nucleosides and nicotinamide coenzymes were regulated by phosphorylation and dephosphorylation. We also demonstrated that SOM analysis was applicable to the estimation of unidentifiable metabolites in metabolome analysis. Hierarchical clustering of a correlation coefficient matrix could help identify the bottleneck enzymes that regulate metabolic networks. Conclusion: Our results showed that our SOM analysis with appropriate metabolic time-courses effectively revealed the synchronous dynamics among metabolic modules and elucidated the underlying biochemical functions. The application of discrimination of unidentified metabolites and the identification of bottleneck enzymatic steps even to non-targeted comprehensive analysis promise to facilitate an understanding of large-scale interactions among components in biological systems.

Original languageEnglish
Article number51
JournalBMC Systems Biology
Volume2
DOIs
Publication statusPublished - 2008 Jun 18

Fingerprint

Metabolomics
Metabolites
Metabolic Networks and Pathways
Self organizing maps
Modulation
Self-organizing Map
Metabolome
Capillary Electrophoresis
Capillary electrophoresis
Cluster Analysis
Biological systems
Nitrogen
Carbon
Electrophoresis
Biological Systems
Metabolism
Module
Pathway
Spermidine
Data Mining

ASJC Scopus subject areas

  • Molecular Biology
  • Structural Biology
  • Applied Mathematics
  • Modelling and Simulation
  • Computer Science Applications

Cite this

Time-resolved metabolomics reveals metabolic modulation in rice foliage. / Sato, Shigeru; Arita, Masanori; Soga, Tomoyoshi; Nishioka, Takaaki; Tomita, Masaru.

In: BMC Systems Biology, Vol. 2, 51, 18.06.2008.

Research output: Contribution to journalArticle

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