Title
A functional genomics strategy that uses metabolome data to reveal the phenotype of silent mutations
Author
TNO Preventie en Gezondheid
Raamsdonk, L.M.
Teusink, B.
Broadhurst, D.
Zhang, N.
Hayes, A.
Walsh, M.C.
Berden, J.A.
Brindle, K.M.
Kell, D.B.
Rowland, J.J.
Westerhoff, H.V.
van Dam, K.
Oliver, S.G.
Publication year
2001
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. Chemicals/CAS: Adenine Nucleotides; Hexosephosphates; Pyruvates
Subject
Co-response analysis
Functional genomics
Metabolic control analysis
Metabolome
Phenotype analysis
Saccharomyces cerevisiae
Silent mutations
Yeast
controlled study
gene deletion
gene mutation
genome
metabolic regulation
nonhuman
phenotype
silent gene
Adenine Nucleotides
Cluster Analysis
Energy Metabolism
Genome, Fungal
Genomics
Genotype
Hexosephosphates
Mutation
Phenotype
Pyruvates
Saccharomyces cerevisiae
Fungi
Myxogastria
Saccharomyces cerevisiae
To reference this document use:
http://resolver.tudelft.nl/uuid:abacd131-628b-4866-b92e-a5c614518ddf
DOI
https://doi.org/10.1038/83496
TNO identifier
280376
ISSN
1087-0156
Source
Nature Biotechnology, 19 (19), 45-50
Document type
article