Fatty acyl-
coenzyme As (acyl-CoAs) are of central importance in lipid metabolism pathways. Short-chain acyl-CoAs are usually part of metabolomics, and medium- to (very) long-chain acyl-CoAs are focus of lipidomics studies. However, owing to the specific complex and amphiphilic nature contributed by fatty acyl chains and hydrophilic
CoA moiety, lipidomic analysis of acyl-CoAs is still challenging, especially in terms of sample preparation and chromatographic coverage. In this work, we propose a derivatization strategy of acyl-CoAs based on
phosphate methylation. After derivatization, full coverage (from free
CoA to C25:0-
CoA) and good peak shape in liquid chromatography were achieved. At the same time, analyte loss due to the high affinity of
phosphate groups to glass and metallic surfaces was resolved, which is beneficial for routine analysis in large-scale lipidomics studies. A sample preparation method based on mixed-mode SPE was developed to optimize extraction recoveries and allow optimal integration of the derivatization process in the analytical workflow. LC-MS/MS was performed with targeted data acquisition by SRM transitions, which were constructed based on similar fragmentation rules observed for all methylated acyl-CoAs. To achieve accurate quantification, uniformly 13C-labeled metabolite extract from yeast cells was taken as internal standards. Odd-chain and stable
isotope-labeled acyl-CoAs were used as surrogate calibrants in the same matrix. LOQs were between 16.9 nM (short-chain acyl-CoAs) and 4.2 nM (very-long-chain acyl-CoAs). This method was validated in cultured cells and was applied in HeLa cells and human platelets of
coronary artery disease patients. It revealed distinct
acyl-CoA profiles in HeLa cells and platelets. The results showed that this method can effectively detect acyl-CoAs in biological samples. Considering their central importance in many de novo
lipid biosynthesis and remodeling processes, this targeted method offers a valid foundation for future lipidomics analysis of
acyl-CoA profiles in biological samples, particularly those concerning
metabolic syndrome.