A simulated strategy for analysis of Short- to Long- chain fatty acids in mouse serum beyond chemical standards

Broadening coverage in fatty acid (FA) analysis benefits the understanding of metabolic regulation in biological system. However, the limited access of chemical standards makes it challenging. In this work, we introduced a simulation assisted strategy to analyze short-, medium-, long- and very-long-chain fatty acids beyond the use of chemical standards. This targeted analysis in selected reaction monitoring (SRM) mode incorporated 3-nitrophenylhydrazine derivatization and mathematical simulation of ion transitions, collision energies, RF values and retention times to identify and quantify the fatty acids without chemical standards. Serum analysis using high resolution mass spectrometry coupled with paired labeling was employed to refine the computational retention times. Based on the simulation, 116 free fatty acids from C1 to C24 were covered in a single analysis on use of 34 standard chemicals. Background interference is commonly observed in fatty acid analysis. For certain fatty acids, e.g. acetic acid or palmitic acid, reliable quantitation is largely restricted by contamination level instead of detection limit. Therefore, the background interference and quantifiable serum volume required for each fatty acid were also evaluated. At least 20 µL serum was suggested to cover most molecules. Using this approach, a total of 66 free fatty acids with various chain lengths and saturations were detected in NTCP knockout mice serum, of which 34 FAs were confirmed by chemical standards and 32 FAs were potentially assigned based on the simulation. Gender dependent fatty acid regulation was observed by NTCP knockout. This work provides a unique strategy that enables to broaden the fatty acid coverage with the absence of chemical standards and is applicable to other derivatizations.