Abstract
BackgroundAnalysis of multiple LC-MS based metabolomic studies is carried out to determine overlaps and differences among various experiments. For example, in large metabolic biomarker discovery studies involving hundreds of samples, it may be necessary to conduct multiple experiments, each involving a subset of the samples due to technical limitations. The ions selected from each experiment are analyzed to determine overlapping ions. One of the challenges in comparing the ion lists is the presence of a large number of derivative ions such as isotopes, adducts, and fragments. These derivative ions and the retention time drifts need to be taken into account during comparison.ResultsWe implemented an ion annotation-assisted method to determine overlapping ions in the presence of derivative ions. Following this, each ion is represented by the monoisotopic mass of its cluster. This mass is then used to determine overlaps among the ions selected across multiple experiments.ConclusionThe resulting ion list provides better coverage and more accurate identification of metabolites compared to the traditional method in which overlapping ions are selected on the basis of individual ion mass.
Highlights
Analysis of multiple liquid chromatography (LC)-Mass spectrometry (MS) based metabolomic studies is carried out to determine overlaps and differences among various experiments
Liquid chromatography coupled to mass spectrometry (LC-MS) data from case-control studies In this paper, we demonstrate the application of our proposed ion annotation-assisted method through two LC-MS datasets (Dataset 1 and Dataset 2) from our metabolomics biomarker discovery studies performed using Waters UPLC-QToF Premier instrument on human serum samples representing two distinct biological groups
LC-MS data preprocessing and difference detection The raw data obtained from the UPLC-QToF machine were converted into Network Common Data Form (NetCDF) format using the MassLynx software (Waters Corp, Milford, MA)
Summary
Analysis of multiple LC-MS based metabolomic studies is carried out to determine overlaps and differences among various experiments. The ions selected from each experiment are analyzed to determine overlapping ions. One of the challenges in comparing the ion lists is the presence of a large number of derivative ions such as isotopes, adducts, and fragments. These derivative ions and the retention time drifts need to be taken into account during comparison. There are two approaches to conduct a metabolomic experiment (targeted and untargeted). Spectral features from two or multiple sets of samples are processed chemometrically to select significant differences.
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