Analysis of endogenous metabolites using multifunctional derivatization and capillary RPLC-MS

Heterogeneity in metabolite structure and charge state complicates their analysis in electrospray mass spectrometry (ESI-MS). Complications such as diminished signal response and quantitation can be reduced by sequential dual-stage derivatization and capillary RP LC-ESI-MS analysis. Our sequential dual-stage chemical derivatization reacts analyte primary amine and hydroxyl groups with a linear acyl chloride head containing a tertiary amine moiety. Analyte carboxylate groups are then coupled to a linear amine tag with a tertiary amine moiety. This increase in the number of tags on analytes increases analyte proton affinity and hydrophobicity. We derivatized 250 metabolite standards which on average improved signal to noise by >44-fold, with an average limit of detection of 66 nM and R-2 of 0.98. This system detected 107 metabolites from 18 BAECs, 111 metabolites from human urine, and 153 from human serum based on retention time, exact mass, and MS/MS matches from a derivatized standard library. As a proof of concept, aortic endothelial cells were treated with epinephrine and analyzed by the dual-stage derivatization. We observed changes in 32 metabolites with many increases related to energy metabolism, specifically in the TCA cycle. A decrease in lactate levels and corresponding increase in pyruvate levels suggest that epinephrine causes a movement away from glycolytic reliance on energy and a shift towards the more efficient TCA respiration for increasing energy.

Automated summary

The analysis of metabolites in electrospray mass spectrometry is complicated due to their structural and charge state heterogeneity. This study presents a sequential dual-stage derivatization and capillary RP LC-ESI-MS analysis method to reduce complications and improve the accuracy of signal response and quantitation. The derivatization process increases the proton affinity and hydrophobicity of analytes, resulting in improved detection and identification of metabolites in various samples.