A functional genomics strategy that uses metabolome data to reveal the phenotype of silent mutations

Léonie M. Raamsdonk; Bas Teusink; David Broadhurst; Nianshu Zhang; Andrew Hayes; Michael C. Walsh; Jan A. Berden; Kevin M. Brindle; Douglas B. Kell; Jem J. Rowland; Hans V. Westerhoff; Karel Van Dam; Stephen G. Oliver

doi:10.1038/83496

A functional genomics strategy that uses metabolome data to reveal the phenotype of silent mutations

Léonie M. Raamsdonk, Bas Teusink, David Broadhurst, Nianshu Zhang, Andrew Hayes, Michael C. Walsh, Jan A. Berden, Kevin M. Brindle, Douglas B. Kell, Jem J. Rowland, Hans V. Westerhoff, Karel Van Dam, Stephen G. Oliver

Research output: Contribution to journal › Article › peer-review

Abstract

A large proportion of the 6,000 genes present in the genome of Saccharomyces cerevisiae, and of those sequenced in other organisms, encode proteins of unknown function. Many of these genes are "silent," that is, they show no overt phenotype, in terms of growth rate or other fluxes, when they are deleted from the genome. We demonstrate how the intracellular concentrations of metabolites can reveal phenotypes for proteins active in metabolic regulation. Quantification of the change of several metabolite concentrations relative to the concentration change of one selected metabolite can reveal the site of action, in the metabolic network, of a silent gene. In the same way, comprehensive analyses of metabolite concentrations in mutants, providing "metabolic snapshots," can reveal functions when snapshots from strains deleted for unstudied genes are compared to those deleted for known genes. This approach to functional analysis, using comparative metabolomics, we call FANCY - an abbreviation for functional analysis by co-responses in yeast.

Original language	English
Pages (from-to)	45-50
Number of pages	5
Journal	Nature biotechnology
Volume	19
Issue number	1
DOIs	https://doi.org/10.1038/83496
Publication status	Published - 2001

Keywords

Co-response analysis
Functional genomics
Metabolic control analysis
Metabolome
Phenotype analysis
Saccharomyces cerevisiae
Silent mutations
Yeast

Research Beacons, Institutes and Platforms

Manchester Institute of Biotechnology

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10.1038/83496

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@article{052ae9b6f00c40bfbbe4cd2cb166ca6d,

title = "A functional genomics strategy that uses metabolome data to reveal the phenotype of silent mutations",

abstract = "A large proportion of the 6,000 genes present in the genome of Saccharomyces cerevisiae, and of those sequenced in other organisms, encode proteins of unknown function. Many of these genes are {"}silent,{"} that is, they show no overt phenotype, in terms of growth rate or other fluxes, when they are deleted from the genome. We demonstrate how the intracellular concentrations of metabolites can reveal phenotypes for proteins active in metabolic regulation. Quantification of the change of several metabolite concentrations relative to the concentration change of one selected metabolite can reveal the site of action, in the metabolic network, of a silent gene. In the same way, comprehensive analyses of metabolite concentrations in mutants, providing {"}metabolic snapshots,{"} can reveal functions when snapshots from strains deleted for unstudied genes are compared to those deleted for known genes. This approach to functional analysis, using comparative metabolomics, we call FANCY - an abbreviation for functional analysis by co-responses in yeast.",

keywords = "Co-response analysis, Functional genomics, Metabolic control analysis, Metabolome, Phenotype analysis, Saccharomyces cerevisiae, Silent mutations, Yeast",

author = "Raamsdonk, {L{\'e}onie M.} and Bas Teusink and David Broadhurst and Nianshu Zhang and Andrew Hayes and Walsh, {Michael C.} and Berden, {Jan A.} and Brindle, {Kevin M.} and Kell, {Douglas B.} and Rowland, {Jem J.} and Westerhoff, {Hans V.} and {Van Dam}, Karel and Oliver, {Stephen G.}",

year = "2001",

doi = "10.1038/83496",

language = "English",

volume = "19",

pages = "45--50",

journal = "Nature biotechnology",

issn = "1546-1696",

publisher = "Springer Nature",

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TY - JOUR

T1 - A functional genomics strategy that uses metabolome data to reveal the phenotype of silent mutations

AU - Raamsdonk, Léonie M.

AU - Teusink, Bas

AU - Broadhurst, David

AU - Zhang, Nianshu

AU - Hayes, Andrew

AU - Walsh, Michael C.

AU - Berden, Jan A.

AU - Brindle, Kevin M.

AU - Kell, Douglas B.

AU - Rowland, Jem J.

AU - Westerhoff, Hans V.

AU - Van Dam, Karel

AU - Oliver, Stephen G.

PY - 2001

Y1 - 2001

N2 - A large proportion of the 6,000 genes present in the genome of Saccharomyces cerevisiae, and of those sequenced in other organisms, encode proteins of unknown function. Many of these genes are "silent," that is, they show no overt phenotype, in terms of growth rate or other fluxes, when they are deleted from the genome. We demonstrate how the intracellular concentrations of metabolites can reveal phenotypes for proteins active in metabolic regulation. Quantification of the change of several metabolite concentrations relative to the concentration change of one selected metabolite can reveal the site of action, in the metabolic network, of a silent gene. In the same way, comprehensive analyses of metabolite concentrations in mutants, providing "metabolic snapshots," can reveal functions when snapshots from strains deleted for unstudied genes are compared to those deleted for known genes. This approach to functional analysis, using comparative metabolomics, we call FANCY - an abbreviation for functional analysis by co-responses in yeast.

AB - A large proportion of the 6,000 genes present in the genome of Saccharomyces cerevisiae, and of those sequenced in other organisms, encode proteins of unknown function. Many of these genes are "silent," that is, they show no overt phenotype, in terms of growth rate or other fluxes, when they are deleted from the genome. We demonstrate how the intracellular concentrations of metabolites can reveal phenotypes for proteins active in metabolic regulation. Quantification of the change of several metabolite concentrations relative to the concentration change of one selected metabolite can reveal the site of action, in the metabolic network, of a silent gene. In the same way, comprehensive analyses of metabolite concentrations in mutants, providing "metabolic snapshots," can reveal functions when snapshots from strains deleted for unstudied genes are compared to those deleted for known genes. This approach to functional analysis, using comparative metabolomics, we call FANCY - an abbreviation for functional analysis by co-responses in yeast.

KW - Co-response analysis

KW - Functional genomics

KW - Metabolic control analysis

KW - Metabolome

KW - Phenotype analysis

KW - Saccharomyces cerevisiae

KW - Silent mutations

KW - Yeast

U2 - 10.1038/83496

DO - 10.1038/83496

M3 - Article

C2 - 11135551

SN - 1546-1696

VL - 19

SP - 45

EP - 50

JO - Nature biotechnology

JF - Nature biotechnology

IS - 1

ER -

A functional genomics strategy that uses metabolome data to reveal the phenotype of silent mutations

Abstract

Keywords

Research Beacons, Institutes and Platforms

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