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Comprehensive Analysis of Short-, Medium-, and Long-Chain Acyl-Coenzyme A by Online Two-Dimensional Liquid Chromatography/Mass Spectrometry.

Shuangyuan WangZhichao WangLina ZhouXianzhe ShiGuo-Wang Xu
Published in: Analytical chemistry (2017)
Acyl-coenzyme A (CoA) is a pivotal metabolic intermediate in numerous biological processes. However, comprehensive analysis of acyl-CoAs is still challenging as the properties of acyl-CoAs greatly vary with different carbon chains. Here, we designed a two-dimensional liquid chromatography method coupled with high-resolution mass spectrometry (2D LC/HRMS) to cover all short-, medium-, and long-chain acyl-CoAs within one analytical run. Complex acyl-CoAs were separated into two fractions according to their acyl chains by the first dimensional prefractionation. Then, two fractions containing short-chain acyl-CoAs or medium- and long-chain acyl-CoAs were further separated by the two parallel columns in the second dimension. Nineteen representative standards were chosen to optimize the analytical conditions of the 2D LC/HRMS method. Resolution and sensitivity were demonstrated to be improved greatly, and lowly abundant acyl-CoAs and acyl-CoA isomers could be detected and distinguished. By using the 2D LC/HRMS method, 90 acyl-CoAs (including 21 acyl-dephospho-CoAs) were identified from liver extracts, which indicated that our method was one of the most powerful approaches for obtaining comprehensive profiling of acyl-CoAs so far. The method was further employed in the metabolomics study of malignant glioma cells with an isocitrate dehydrogenase 1 (IDH1) mutation to explore their metabolic differences. A total of 46 acyl-CoAs (including 2 acyl-dephospho-CoAs) were detected, and 12 of them were dysregulated in glioma cells with the IDH1 mutation. These results demonstrated the practicability and the superiority of the established method. Therefore, the 2D LC/HRMS method provides a robust and reproducible approach to the comprehensive analysis of acyl-CoAs in tissues, cells, and other biological samples.
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