Metabolomics comprises the comprehensive analysis of metabolites in biological samples with respect to changes observed upon perturbation of the system. The metabolic profile gives information on distortion at any point in a metabolic pathway due to e.g. genetic failure, disease.
Information-rich analytical techniques like LC-MS and sophisticated data evaluation software for pattern recognition are mandatory for metabolomics.The micrOTOF ESI-TOF mass spectrometer provides two levels of confidence for identification: accurate mass and true isotopic pattern (SigmaFit algorithm) over a wide dynamic range. Superior data quality enables data evaluation with Principle Component Analysis (PCA) using the tailored ProfileAnalysis software.
LC-MS data from spiked urine samples were analyzed with ProfileAnalysis [1]. PCA visualizes the variance within a set of samples. The PCA scores plot demonstrates the clear separation of the spiked groups (A-C: phenylalanine; D-F: MVA/HVA) from no spike (black). The distance corresponds to the relative amount of spiked component, indicating that PCA is quantitative.The loadings plot indicates the compounds responsible for this separation. The elemental composition of the groups was identified using accurate mass and SigmaFit which significantly improved confidence of the results (fig. 1).Thus, accurate and robust micrOTOF data are superior for multivariate statistics and identification by the molecular formula.