METLIN Neutral Loss Database Enhances Similarity Analysis

Abstract

Tandem mass spectrometry (MS2) data is an effective resource for the identification of known molecules and the putative identification of novel, previously uncharacterized molecules (unknowns). Yet, MS2 data alone is limited in characterizing structurally closely related molecules with different masses. Neutral loss data is key in retrieving this structural similarity. To facilitate unknown identification and complement METLIN fragment ion data for characterizing structurally related molecules, we have created the METLIN neutral loss database (https://metlin-nl.scripps.edu).

Identification of Pseudomonas aeruginosa exopolysaccharide Psl in biofilms using 3D OrbiSIMS

“…Loss analysis has been shown to be an efficient way of annotating mass spectra in tandem MS data derived from soft ionization sources such as electron spray ionization. 21–23 It has also been used for annotating predictable and unpredictable metabolic features in untargeted metabolomics. 24 Recently, this approach was applied to the OrbiSIMS analysis of proteins for the first time.…”