Use of Coulometric Array HPLC in Metabolomics
RP-64 Metabolomics is a necessary complement to genomics and proteomics in diagnostic marker and therapeutic target identification, drug discovery and development. A primary application within the pharmaceutical industry has been in early assessment of compound toxicity to reduce late-stage attritio...
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Veröffentlicht in: | Journal of biomolecular techniques 2010-09, Vol.21 (3 Suppl), p.S41-S41 |
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Sprache: | eng |
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Zusammenfassung: | RP-64
Metabolomics is a necessary complement to genomics and proteomics in diagnostic marker and therapeutic target identification, drug discovery and development. A primary application within the pharmaceutical industry has been in early assessment of compound toxicity to reduce late-stage attrition. H′-NMR and LCMS are common techniques in metabolomic toxicological testing due to their multi-component and structural identification capabilities. Coulometric array-HPLC is widely used for high resolution multi-component analyses of small redox-active molecules. Our studies include development of multi-component methods for specific redox-active analyte classes, determination of solvent, fluidic and electrical requirements for integration of coulometric array into high-throughput, LC-MS compatible formats and in mining of multi-component coulometric array data for pattern recognition analysis. Methods were developed for multi-component analyses of hydrophobic metabolites (vitamins, anti-oxidants) and for more hydrophilic metabolites (estrogens, diet-derived polyphenols) using MS-compatible ammonium acetate mobile phases. A serial coulometric array of eight to sixteen microporous carbon-based electrochemical sensors maintained at fixed potentials allowed selective detection based on analytes' relative ease of oxidation or reduction. LODs for tocopherols, retinoids, carotenoids and co-enzyme Q10 were typically in the low pg range. A software utility was developed to facilitate 1) marker selection and chromatographic adjustment to allow correction for changes in retention; 2) data compression and binning to simplify output and 3) data formatting for export to pattern recognition software. Details of methodology, system integration, principle component analysis and cluster analysis of data with regards to redox active metabolite changes from drug exposure will be presented. |
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ISSN: | 1524-0215 1943-4731 |