Double Derivatization Strategy for High-Sensitivity and High- Coverage Localization of Double Bonds in Free Fatty Acids by Mass Spectrometry

: Xu SL, Wu BF, Oresic M, Xie Y, Yao P, Wu ZY, Lv X, Chen H, Wei F

Publisher: AMER CHEMICAL SOC

: 2020

: Analytical Chemistry

: ANALYTICAL CHEMISTRY

: ANAL CHEM

: 92

: 9

: 6446

: 6455

: 10

: 0003-2700

: 1520-6882

DOI: https://doi.org/10.1021/acs.analchem.9b05588

Free fatty acids (FFAs) are key intermediates of lipid metabolism that have a crucial role in many critical biological processes. The specific locations of carbon-carbon double bonds (C=C) in FFAs are often associated with distinct biological functions. Despite the rapid development of analytical techniques, identification of C=C locations in FFAs with more than three C=C bonds in complex biological matrices remains a challenge. Herein, we describe a double derivatization strategy, coupled with shotgun-mass spectrometry (MS), for unambiguous and sensitive determination of a high-coverage C=C bond (from 1 to 6) locations of FFAs. Our approach is based on combination of acetone labeling of C=C bonds and N,N-diethyl-1,2-ethanedi- amine (DEEA) labeling of carboxyl groups within FFAs. Acetone labeling of C=C bonds via photochemical reaction provides diagnostic ions, specific MS twaiysis to C=C locations, and DEEA labeling of carboxyl groups significantly enhances MS response of diagnostic ions, by invoking a readily protonated tertiary amine group on FFA analytes. By exploiting this double derivatization strategy, the assignment of C=C locations of FFAs with more than three C=C bonds was achieved with high sensitivity (limit of quantitation (LOQ) 0.1-1.5 nmol/L). In contrast, such assignments were not possible by acetone labeling alone, because of the low sensitivity of diagnostic ions in negative ionization mode of MS. The applicability of our method was demonstrated by profiling of FFAs, including unsaturated FFA C=C positional isomers, in liver samples from mice with nonalcoholic fatty liver disease (NAFLD) and their lean controls. The study showed that the high-specificity and high-sensitivity method developed here is promising for accurate identification and quantitation of a wide array of FFAs in biological samples.