Reproducible untargeted metabolomics workflow for exhaustive MS2 data acquisition of MS1 features.

ABSTRACT: Unknown features in untargeted metabolomics and non-targeted analysis (NTA) are identified using fragment ions from MS/MS spectra to predict the structures of the unknown compounds. The precursor ion selected for fragmentation is commonly performed using data dependent acquisition (DDA) strategies or following statistical analysis using targeted MS/MS approaches. However, the selected precursor ions from DDA only cover a biased subset of the peaks or features found in full scan data. In addition, different statistical analysis can select different precursor ions for MS/MS analysis, which make the post-hoc validation of ions selected following a secondary analysis impossible for precursor ions selected by the original statistical method. Here we propose an automated, exhaustive, statistical

SUBMITTER: Yu M 

PROVIDER: S-EPMC8848943 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature