1H NMR-based metabolic profiling reveals inherent biological variation in yeast and nematode model systems
The application of metabolomics to human and animal model systems is poised to provide great insight into our understanding of disease etiology and the metabolic changes that are associated with these conditions. However, metabolomic studies have also revealed that there is significant, inherent bio...
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Veröffentlicht in: | Journal of biomolecular NMR 2011-04, Vol.49 (3-4), p.245-254 |
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Sprache: | eng |
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Zusammenfassung: | The application of metabolomics to human and animal model systems is poised to provide great insight into our understanding of disease etiology and the metabolic changes that are associated with these conditions. However, metabolomic studies have also revealed that there is significant, inherent biological variation in human samples and even in samples from animal model systems where the animals are housed under carefully controlled conditions. This inherent biological variability is an important consideration for all metabolomics analyses. In this study, we examined the biological variation in
1
H NMR-based metabolic profiling of two model systems, the yeast
Saccharomyces cerevisiae
and the nematode
Caenorhabditis elegans
. Using relative standard deviations (RSD) as a measure of variability, our results reveal that both model systems have significant amounts of biological variation. The
C. elegans
metabolome possesses greater metabolic variance with average RSD values of 29 and 39%, depending on the food source that was used. The
S. cerevisiae
exometabolome RSD values ranged from 8% to 12% for the four strains examined. We also determined whether biological variation occurs between pairs of phenotypically identical yeast strains. Multivariate statistical analysis allowed us to discriminate between pair members based on their metabolic phenotypes. Our results highlight the variability of the metabolome that exists even for less complex model systems cultured under defined conditions. We also highlight the efficacy of metabolic profiling for defining these subtle metabolic alterations. |
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ISSN: | 0925-2738 1573-5001 |
DOI: | 10.1007/s10858-011-9492-6 |