Patterns of metabolite changes identified from large-scale gene perturbations in arabidopsis using a genome-scale metabolic network

Taehyong Kim, Kate Dreher, Ricardo Nilo-Poyanco, Insuk Lee, Oliver Fiehn, Bernd Markus Lange, Basil J. Nikolau, Lloyd Sumner, Ruth Welti, Eve S. Wurtele, Seung Y. Rhee

Research output: Contribution to journalArticlepeer-review

25 Citations (Scopus)

Abstract

Metabolomics enables quantitative evaluation of metabolic changes caused by genetic or environmental perturbations. However, little is known about how perturbing a single gene changes the metabolic system as a whole and which network and functional properties are involved in this response. To answer this question, we investigated the metabolite profiles from 136 mutants with single gene perturbations of functionally diverse Arabidopsis (Arabidopsis thaliana) genes. Fewer than 10 metabolites were changed significantly relative to the wild type in most of the mutants, indicating that the metabolic network was robust to perturbations of single metabolic genes. These changed metabolites were closer to each other in a genome-scale metabolic network than expected by chance, supporting the notion that the genetic perturbations changed the network more locally than globally. Surprisingly, the changed metabolites were close to the perturbed reactions in only 30% of the mutants of the well-characterized genes. To determine the factors that contributed to the distance between the observed metabolic changes and the perturbation site in the network, we examined nine network and functional properties of the perturbed genes. Only the isozyme number affected the distance between the perturbed reactions and changed metabolites.

Original languageEnglish
Pages (from-to)1685-1698
Number of pages14
JournalPlant physiology
Volume167
Issue number4
DOIs
Publication statusPublished - 2015 Apr 1

Bibliographical note

Publisher Copyright:
© 2015 American Society of Plant Biologists. All rights reserved.

All Science Journal Classification (ASJC) codes

  • Physiology
  • Genetics
  • Plant Science

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