Differential metabolic networks unravel the effects of silent plant phenotypes

Wolfram Weckwerth, Marcelo Ehlers Loureiro, Kathrin Wenzel, Oliver Fiehn

Research output: Contribution to journalArticle

272 Citations (Scopus)

Abstract

Current efforts aim to functionally characterize each gene in model plants. Frequently, however, no morphological or biochemical phenotype can be ascribed for antisense or knock-out plant genotypes. This is especially the case when gene suppression or knockout is targeted to isoenzymes or gene families. Consequently, pleiotropic effects and gene redundancy are responsible for phenotype resistance. Here, techniques are presented to detect unexpected pleiotropic changes in such instances despite very subtle changes in overall metabolism. The method consists of the relative quantitation of >1,000 compounds by GC/time-of-flight MS, followed by classical statistics and multivariate clustering. Complementary to these tools, metabolic networks are constructed from pair-wise analysis of linear metabolic correlations. The topology of such networks reflects the underlying regulatory pathway structure. A differential analysis of network connectivity was applied for a silent potato plant line suppressed in expression of sucrose synthase isoform II. Metabolic alterations could be assigned to carbohydrate and amino acid metabolism even if no difference in average metabolite levels was found.

Original languageEnglish (US)
Pages (from-to)7809-7814
Number of pages6
JournalProceedings of the National Academy of Sciences of the United States of America
Volume101
Issue number20
DOIs
StatePublished - May 18 2004
Externally publishedYes

Fingerprint

Metabolic Networks and Pathways
Phenotype
Genetic Pleiotropy
Genes
Solanum tuberosum
Isoenzymes
Cluster Analysis
Protein Isoforms
Genotype
Carbohydrates
Amino Acids

Keywords

  • Data mining
  • Functional genomics
  • Metabolomics
  • Metabonomics
  • Regulatory networks

ASJC Scopus subject areas

  • Genetics
  • General

Cite this

Differential metabolic networks unravel the effects of silent plant phenotypes. / Weckwerth, Wolfram; Loureiro, Marcelo Ehlers; Wenzel, Kathrin; Fiehn, Oliver.

In: Proceedings of the National Academy of Sciences of the United States of America, Vol. 101, No. 20, 18.05.2004, p. 7809-7814.

Research output: Contribution to journalArticle

Weckwerth, Wolfram ; Loureiro, Marcelo Ehlers ; Wenzel, Kathrin ; Fiehn, Oliver. / Differential metabolic networks unravel the effects of silent plant phenotypes. In: Proceedings of the National Academy of Sciences of the United States of America. 2004 ; Vol. 101, No. 20. pp. 7809-7814.
@article{73ab462280f0456f8e05425f7a0e5c12,
title = "Differential metabolic networks unravel the effects of silent plant phenotypes",
abstract = "Current efforts aim to functionally characterize each gene in model plants. Frequently, however, no morphological or biochemical phenotype can be ascribed for antisense or knock-out plant genotypes. This is especially the case when gene suppression or knockout is targeted to isoenzymes or gene families. Consequently, pleiotropic effects and gene redundancy are responsible for phenotype resistance. Here, techniques are presented to detect unexpected pleiotropic changes in such instances despite very subtle changes in overall metabolism. The method consists of the relative quantitation of >1,000 compounds by GC/time-of-flight MS, followed by classical statistics and multivariate clustering. Complementary to these tools, metabolic networks are constructed from pair-wise analysis of linear metabolic correlations. The topology of such networks reflects the underlying regulatory pathway structure. A differential analysis of network connectivity was applied for a silent potato plant line suppressed in expression of sucrose synthase isoform II. Metabolic alterations could be assigned to carbohydrate and amino acid metabolism even if no difference in average metabolite levels was found.",
keywords = "Data mining, Functional genomics, Metabolomics, Metabonomics, Regulatory networks",
author = "Wolfram Weckwerth and Loureiro, {Marcelo Ehlers} and Kathrin Wenzel and Oliver Fiehn",
year = "2004",
month = "5",
day = "18",
doi = "10.1073/pnas.0303415101",
language = "English (US)",
volume = "101",
pages = "7809--7814",
journal = "Proceedings of the National Academy of Sciences of the United States of America",
issn = "0027-8424",
number = "20",

}

TY - JOUR

T1 - Differential metabolic networks unravel the effects of silent plant phenotypes

AU - Weckwerth, Wolfram

AU - Loureiro, Marcelo Ehlers

AU - Wenzel, Kathrin

AU - Fiehn, Oliver

PY - 2004/5/18

Y1 - 2004/5/18

N2 - Current efforts aim to functionally characterize each gene in model plants. Frequently, however, no morphological or biochemical phenotype can be ascribed for antisense or knock-out plant genotypes. This is especially the case when gene suppression or knockout is targeted to isoenzymes or gene families. Consequently, pleiotropic effects and gene redundancy are responsible for phenotype resistance. Here, techniques are presented to detect unexpected pleiotropic changes in such instances despite very subtle changes in overall metabolism. The method consists of the relative quantitation of >1,000 compounds by GC/time-of-flight MS, followed by classical statistics and multivariate clustering. Complementary to these tools, metabolic networks are constructed from pair-wise analysis of linear metabolic correlations. The topology of such networks reflects the underlying regulatory pathway structure. A differential analysis of network connectivity was applied for a silent potato plant line suppressed in expression of sucrose synthase isoform II. Metabolic alterations could be assigned to carbohydrate and amino acid metabolism even if no difference in average metabolite levels was found.

AB - Current efforts aim to functionally characterize each gene in model plants. Frequently, however, no morphological or biochemical phenotype can be ascribed for antisense or knock-out plant genotypes. This is especially the case when gene suppression or knockout is targeted to isoenzymes or gene families. Consequently, pleiotropic effects and gene redundancy are responsible for phenotype resistance. Here, techniques are presented to detect unexpected pleiotropic changes in such instances despite very subtle changes in overall metabolism. The method consists of the relative quantitation of >1,000 compounds by GC/time-of-flight MS, followed by classical statistics and multivariate clustering. Complementary to these tools, metabolic networks are constructed from pair-wise analysis of linear metabolic correlations. The topology of such networks reflects the underlying regulatory pathway structure. A differential analysis of network connectivity was applied for a silent potato plant line suppressed in expression of sucrose synthase isoform II. Metabolic alterations could be assigned to carbohydrate and amino acid metabolism even if no difference in average metabolite levels was found.

KW - Data mining

KW - Functional genomics

KW - Metabolomics

KW - Metabonomics

KW - Regulatory networks

UR - http://www.scopus.com/inward/record.url?scp=2442647715&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=2442647715&partnerID=8YFLogxK

U2 - 10.1073/pnas.0303415101

DO - 10.1073/pnas.0303415101

M3 - Article

C2 - 15136733

AN - SCOPUS:2442647715

VL - 101

SP - 7809

EP - 7814

JO - Proceedings of the National Academy of Sciences of the United States of America

JF - Proceedings of the National Academy of Sciences of the United States of America

SN - 0027-8424

IS - 20

ER -