Change search
ReferencesLink to record
Permanent link

Direct link
Nonlinear data alignment for UPLC-MS and HPLC-MS based metabolomics: quantitative analysis of endogenous and exogenous metabolites in human serum.
Department of Molecular Biology, Scripps Center for Mass Spectrometry, The Scripps Research Institute.
2006 (English)In: Analytical Chemistry, ISSN 0003-2700, E-ISSN 1520-6882, Vol. 78, no 10, 3289-95 p.Article in journal (Refereed) Published
Abstract [en]

A nonlinear alignment strategy was examined for the quantitative analysis of serum metabolites. Two small-molecule mixtures with a difference in relative concentration of 20-100% for 10 of the compounds were added to human serum. The metabolomics protocol using UPLC and XCMS for LC-MS data alignment could readily identify 8 of 10 spiked differences among more than 2700 features detected. Normalization of data against a single factor obtained through averaging the XCMS integrated response areas of spiked standards increased the number of identified differences. The original data structure was well preserved using XCMS, but reintegration of identified differences in the original data reduced the number of false positives. Using UPLC for separation resulted in 20% more detected components compared to HPLC. The length of the chromatographic separation also proved to be a crucial parameter for a number of detected features. Moreover, UPLC displayed better retention time reproducibility and signal-to-noise ratios for spiked compounds over HPLC, making this technology more suitable for nontargeted metabolomics applications.

Place, publisher, year, edition, pages
2006. Vol. 78, no 10, 3289-95 p.
National Category
Natural Sciences
URN: urn:nbn:se:umu:diva-48249DOI: 10.1021/ac060245fPubMedID: 16689529OAI: diva2:448494
Available from: 2011-10-17 Created: 2011-10-12 Last updated: 2011-11-10Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full textPubMed

Search in DiVA

By author/editor
Nordström, Anders
In the same journal
Analytical Chemistry
Natural Sciences

Search outside of DiVA

GoogleGoogle Scholar
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Altmetric score

Total: 37 hits
ReferencesLink to record
Permanent link

Direct link