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Updated: Jun 10, 2025

Absolute Quantification of Cell-Free Protein Synthesis Metabolism by Reversed-Phase Liquid Chromatography-Mass Spectrometry
Published on: October 25, 2019
A charge reversal approach for the sensitive quantification of dicarboxylic acids using Liquid chromatography-tandem
1Biomarker and Neuro-disease Mechanism Lab, Neuroscience Department, Huntington Medical Research Institutes, Pasadena, CA, USA.
Abstract:
Dicarboxylic acids (DCAs) are essential for intermediate metabolism and are implicated in multiple processes associated with various diseases. Several DCAs contribute to energy metabolism, impact mitochondrial function, and play a crucial role in body function. However, the low abundance of some DCAs in various body fluids makes their quantification particularly challenging. Therefore, an extremely sensitive method is required to determine DCA level fluctuations in biological samples in different diseases. We developed and optimized an LC-MS/MS method to quantify DCAs. We achieved charge reversal of the compounds from negative to positive ionization through chemical derivatization with dimethylaminophenacyl bromide (DmPABr) targeting the carboxyl group (R-COOH) under mild basic conditions. Derivatization enhanced sensitivity, mass fragmentation, and chromatographic separation for LC-tandem mass spectrometric quantification. The method was analytically optimized and demonstrated excellent linearity for individual DCAs (R2>0.99), as well as an exceptionally lower limit of detection (LLOD<266 fg) and lower limit of quantification (LLOQ<805 fg) for all DCAs. Furthermore, most derivatized DCAs were stable at room temperature and after ten repeated freeze-thaw cycles. After DCA extraction and quantification detection, we found differences in their distribution in plasma and urine. The rank order for DCAs in plasma is C4>C6>C7>C9>C5>C8>C22, whereas in the urine sample, the order is C4>C7>C6>C9>C5>C8>C10. For longer chains (C > 16), their proportions were >10x higher in plasma than in urine. Our optimized method using LC-MS/MS enables the quantification of DCAs with excellent sensitivity. The method will help in future studies investigating dicarboxylic acids' crucial role in health and biomarker discovery studies using targeted metabolomics.
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