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High Resolution “Ultra Performance” Liquid Chromatography Coupled to oa-TOF Mass Spectrometry as a Tool for Differential Metabolic Pathway Profiling in Functional Genomic Studies

Journal of Proteome Research · 2005 · Vol. 4(2) · pp. 591–598
Ian D. WilsonJeremy K. NicholsonJosé Castro‐PerezJennifer H. GrangerKelly A. JohnsonBrian W. SmithRobert S. Plumb

Abstract

The combination of a new 1.7 mum reversed-phase packing material, and a chromatographic system, operating at ca. 12,000 psi, (so-called ultra performance liquid chromatography, UPLC) has enabled dramatic increases in chromatographic performance to be obtained for complex mixture separation. This increase in performance is manifested in improved peak resolution, together with increased speed and sensitivity. Here, we show that UPLC offers significant advantages over conventional reversed-phase HPLC amounting to a more than doubling of peak capacity, an almost 10-fold increase in speed and a 3- to 5-fold increase in sensitivity compared to that generated with a conventional 3.5 microm stationary phase. The first functional genomic application of UPLC-MS technology is illustrated here with respect to multivariate metabolic profiling of urines from males and females of two groups of phenotypically normal mouse strains (C57BL19J and Alpk:ApfCD) and a "nude mouse" strain. We have also compared this technology to conventional HPLC-MS under similar analytical conditions and show improved phenotypic classification capability of UPLC-MS analysis together with increased ability to probe differential pathway activities between strains as a result of improved analytical sensitivity and resolution.

Metabolomics and Mass Spectrometry StudiesAnalytical Chemistry and ChromatographyMass Spectrometry Techniques and ApplicationsChromatographyHigh-performance liquid chromatographyMass spectrometryMetabolomicsChemometricsChemistryResolution (logic)Analytical Chemistry (journal)

MeSH terms

AnimalsChromatography, LiquidFemaleMaleMice, Inbred C57BLMice, NudeMass SpectrometryGenomicsMice
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