Incorporating In-Source Fragment Information Improves Metabolite Identification Accuracy in Untargeted LC–MS Data Sets

In-source fragmentation
occurs as a byproduct of electrospray ionization.
We find that ions produced as a result of in-source fragmentation
often match fragment ions produced during MS/MS fragmentation, and
we take advantage of this phenomenon in a novel algorithm to analyze
LC–MS metabolomics data sets. Our approach organizes coeluting
MS1 features into a single peak group and then identifies in-source
fragments among coeluting features using MS/MS spectral libraries.
We tested our approach using previously published data of verified
metabolites and compared the results to features detected by other
mainstream metabolomics tools. Our results indicate that considering
in-source fragment information as a part of the identification process
increases the annotation quality, allowing us to leverage MS/MS data
in spectrum libraries even if MS/MS scans were not collected.