Abstract
Mass spectrometry combined with related tandem techniques has become the most popular method for plant secondary metabolite characterization. We introduce a new strategy based on in-database searching, mass fragmentation behavior study, formula predicting for fast profiling of glucosinolates, a class of important compounds in brassica vegetables. A MATLAB script-based expert system computer program, "GLS-Finder", was developed. It is capable of qualitative and semi-quantitative analyses of glucosinolates in samples using data generated by ultrahigh-performance liquid chromatography-high-resolution accurate mass with multi-stage mass fragmentation (UHPLC-HRAM/MS(n)). A suite of bioinformatic tools was integrated into the "GLS-Finder" to perform raw data deconvolution, peak alignment, glucosinolate putative assignments, semi-quantitation, and unsupervised principal component analysis (PCA). GLS-Finder was successfully applied to identify intact glucosinolates in 49 commonly consumed Brassica vegetable samples in the United States. It is believed that this work introduces a new way of fast data processing and interpretation for qualitative and quantitative analyses of glucosinolates, where great efficacy was improved in comparison to identification manually.
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