An 8-(Diazomethyl) Quinoline Derivatized Acyl-CoA in Silico Mass Spectral Library Reveals the Landscape of Acyl-CoA in Aging Mouse Organs

Abstract

Acyl-Coenzyme As (acyl-CoAs) are essential intermediates to incorporate carboxylic acids into the bioactive metabolic network across all species, which play important roles in lipid remodeling, fatty acids, and xenobiotic carboxylic metabolism. However, due to the poor liquid chromatographic behavior, the relatively low mass spectrometry (MS) sensitivity, and lack of authentic standards for annotation, the in-depth untargeted profiling of acyl-CoAs is challenging. We developed a chemical derivatization strategy of acyl-CoAs by employing 8-(diazomethyl) quinoline (8-DMQ) as the labeling reagent, which increased the detection sensitivity by 625-fold with good peak shapes. By applying the MS/MS fragmentation rules learned from the MS/MS spectra of 8-DMQ-acyl-CoA authentic standards, an 8-DMQ-acyl-CoA in silico mass spectral library containing 33,344 high-resolution tandem mass spectra of 8,336 acyl-CoA species was created. The in silico library facilitated the high-throughput and automatic annotation of acyl-CoA using multiple metabolomic data processing tools, such as NIST MS Search and MSDIAL. The feasibility of the in silico library in a complex sample was demonstrated by profiling endogenous acyl-CoAs in multiple organs of an aging mouse. 53 acyl-CoA species were annotated, including 12 oxidized fatty acyl-CoAs and 3 novel nonfatty acyl-CoAs. False positive annotations were further screened by developing an eXtreme Gradient Boosting (XGBoost) based retention time prediction model. The organ distribution and the aging dynamics of acyl-CoAs in a mouse model were discussed for the first time, which helped to elucidate the organ-specific function of acyl-CoAs and the role of different acyl-CoA species during aging.