Authors: Yoshida R; Tamura T; Takaoka C; Harada K; Kobayashi A; Mukai Y; Fukusaki E
Abstract: Metabolomics - the comprehensive analysis of metabolites - was recently used to classify yeast mutants with no overt phenotype using raw data as metabolic fingerprints or footprints. In this study, we demonstrate the estimation of a complicated phenotype, longevity, and semi-rational screening for relevant mutants using metabolic profiles as strain-specific fingerprints. The fingerprints used in our experiments are profiled data consisting of individually identified and quantified metabolites rather than raw spectrum data. We chose yeast replicative lifespan as a model phenotype. Several yeast mutants that affect lifespan were selected for analysis, and they were subjected to metabolic profiling using mass spectrometry. Fingerprinting based on the profiles revealed a correlation between lifespan and metabolic profile. Amino acids and nucleotide derivatives were the main contributors to this correlation. Furthermore, we established a multivariate model to predict lifespan from a metabolic profile. The model facilitated the identification of putative longevity mutants. This work represents a novel approach to evaluate and screen complicated and quantitative phenotype by means of metabolomics.
Keywords: Genes, Fungal/genetics; Genetic Testing/*methods; Metabolome; Metabolomics/*methods; Models, Biological; Mutation/*genetics; Saccharomyces cerevisiae/*genetics/*metabolism; Time Factors|
Journal: Aging cell Volume: 9 Issue: 4 Pages: 616-25 Date: June 17, 2010 PMID: 20550517 |
Yoshida R, Tamura T, Takaoka C, Harada K, Kobayashi A, Mukai Y, Fukusaki E (2010) Metabolomics-based systematic prediction of yeast lifespan and its application for semi-rational screening of ageing-related mutants. Aging cell 9: 616-25.
Comment on This Data Unit