An in-silico MS/MS library for automatic annotation of novel FAHFA lipids associated with type 2 diabetes
Yan Ma, Tobias Kind, Arpana Vaniya Ingrid Gennity, Johannes F. Fahrmann, Oliver Fiehn
Fatty Acid ester of Hydroxyl Fatty Acid (FAHFA) is a novel lipid class that was recently discovered as an endogenous lipid with anti-diabetic effects in mammalian system. Here we developed and validated an in-silico MS/MS library for FAHFAs based on the negative mode QTOF spectra of the external reference standards. The primary library contains 3267 MS/MS spectra at 10, 20 and 40 V CID from 1089 common FAHFA structures. We then took the FAHFAs with saturate hydroxyl fatty acid and generated another more fragment-rich library of 4290 MS/MS spectra at 40 V CID with longer acquisition time, to help identify the position of the hydroxyl group. This new library can be applied in the automatic annotation of FAHFAs in any biological samples.
The Excel template, MSP files and NIST format libraries can be downloaded here (2.7 MB).