Please use this identifier to cite or link to this item: https://doi.org/10.1021/ac801645t
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dc.titleData-driven optimization of metabolomics methods using rat liver samples
dc.contributor.authorParab, G.S.
dc.contributor.authorRao, R.
dc.contributor.authorLakshminarayanan, S.
dc.contributor.authorVon Bing, Y.
dc.contributor.authorMoochhala, S.M.
dc.contributor.authorSwarup, S.
dc.date.accessioned2014-04-23T07:07:53Z
dc.date.available2014-04-23T07:07:53Z
dc.date.issued2009-02-15
dc.identifier.citationParab, G.S., Rao, R., Lakshminarayanan, S., Von Bing, Y., Moochhala, S.M., Swarup, S. (2009-02-15). Data-driven optimization of metabolomics methods using rat liver samples. Analytical Chemistry 81 (4) : 1315-1323. ScholarBank@NUS Repository. https://doi.org/10.1021/ac801645t
dc.identifier.issn00032700
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/50686
dc.description.abstractThe 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 me-tabolomics 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. © 2009 American Chemical Society.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1021/ac801645t
dc.sourceScopus
dc.typeArticle
dc.contributor.departmentCHEMICAL & BIOMOLECULAR ENGINEERING
dc.contributor.departmentBIOLOGICAL SCIENCES
dc.contributor.departmentCIVIL ENGINEERING
dc.contributor.departmentSTATISTICS & APPLIED PROBABILITY
dc.description.doi10.1021/ac801645t
dc.description.sourcetitleAnalytical Chemistry
dc.description.volume81
dc.description.issue4
dc.description.page1315-1323
dc.description.codenANCHA
dc.identifier.isiut000263319000003
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