Data-driven optimization of metabolomics methods using rat liver samples.
The aim of metabolomics is to identify, measure, and interpret complex time-related concentration, activity, and flux of metabolites in cells, tissues, and biofluids. We have used a metabolomics approach to study the biochemical phenotype of mammalian cells which will help in the development of a panel of early stage biomarkers of heat stress tolerance and adaptation. As a first step, a simple and sensitive mass spectrometry experimental workflow has been optimized for the profiling of metabolites in rat tissues. Sample (liver tissue) preparation consisted of a homogenization step in three different buffers, acidification with different strengths of acids, and solid-phase extraction using nine types of cartridges of varying specificities. These led to 18 combinations of acids, cartridges, and buffers for testing for positive and negative ions using mass spectrometry. Results were analyzed and visualized using algorithms written in MATLAB v7.4.0.287. By testing linearity, repeatability, and implementation of univariate and multivariate data analysis, a robust metabolomics platform has been developed. These results will form a basis for future applications in discovering metabolite markers for early diagnosis of heat stress and tissue damage.
Parab
Gauri S
GS
Department of Biological Sciences, National University of Singapore, 117543 Singapore.
Rao
Raghuraj
R
Lakshminarayanan
Samavedham
S
Bing
Yap Von
YV
Moochhala
Shabbir M
SM
Swarup
Sanjay
S
D000704:Analysis of Variance; D053000:Analytic Sample Preparation Methods; D000818:Animals; D008099:Liver / Q000166:cytology / Q000378:metabolism*; D008297:Male; D055432:Metabolomics / Q000379:methods*; D051381:Rats; D017207:Rats, Sprague-Dawley; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D021241:Spectrometry, Mass, Electrospray Ionization