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A new technique (COMSPARI) to facilitate the identification of minor compounds in complex mixtures by GC/MS and LC/MS: tools for the visualization of matched datasets
Authors:Katz  Jonathan E.  Dumlao  Darren S.  Clarke  Steven  Hau  Jörg
Affiliation:Department of Chemistry and Biochemistry and the Molecular Biology Institute, Los Angeles, California 90095-1570, USA.
Abstract:In the rapidly growing field of metabolomics, it is common to analyze complex biological samples by chromatography coupled to mass spectrometry. While several techniques are available for the detection of significant peaks in individual samples, it is still difficult to determine small differences between similar samples. Using conventional software, visual inspections of individual chromatograms or individual mass spectra are often of little use because the differences in the composition of small molecules are too small to be recognizable. Thus, we developed a new approach to visualizing mass spectral datasets using a tool that allows one to easily detect these small differences between mass spectra and chromatograms derived from matched samples. Using these tools on extracts from wild-type and methyltransferase knockout strains of the yeast Saccharomyces cerevisiae, we were able to readily identify those mass spectra in our data sets that were different between the wild-type and the knockout extracts and to identify the molecules involved. The software was also successfully applied to a set of LC/MS data from peptide digests that were performed with identical substrates but different enzymes. We have named this visualization tool COMSPARI (COMparision of SPectrAl Retention Information) and are making the software publicly available via Internet at.
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