Retention-Time Variations Minimized Using UPLC-MS

Scientists from Fudan University in Shanghai, China developed a method for reducing retention-time variations in metabolomic analysis using ultrahigh-performance liquid-chromatography coupled with mass spectrometry (UPLC-MS). The team’s research was published in Talanta (1).

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Reliable metabolite identification must involve reproducible data for MS and retention-time (t_R). However, inter-experiment t_R variations are usually found due to column deterioration. To compare analytes’ t_R from different experiments, retention index (RI) is often used. In this study, the scientists created an endogeneous retention-index (endoRI) from straight-chain acylcarnitines in biological samples. This allowed for a quantitative relationship between acylcarnitines’ t_R and chain-length (L_C) for t_R prediction. Additionally, the effectiveness of endoRI-corrections of t_R variations was evaluated alongside multiple factors, including changes in mobile phase, elution time, flow-rates, and column temperatures were tested along multiple biological samples, including human plasma, serum, urine, and animal liver samples.

The endoRI-corrections were found to reduce t_R variations caused by the changes by up to 5.1min–0.2min for most metabolites. In the above biological samples, inter-batch and inter-platform variations were reduced from 1.5 min to 0.15 min for 95% of detected features. The results of this study enabled the establishment of a quantitative model between t_R and L_C for predicting t_R values of acylcarnitines outside of samples. This allows data from different databases and batches to be compared to each other.

Reference

(1) Chen, Q.; Lu, Q.; Zhang, L.; Zhang, C.; Zhang, J.; Gu, Y.; Huang, Q.; Tang, H. A Novel Endogenous Retention-Index for Minimizing Retention-Time Variations in Metabolomic Analysis with Reversed-Phase Ultrahigh-Performance Liquid-Chromatography and Mass Spectrometry. Talanta 2024, 268 (1), 125318. DOI: https://doi.org/10.1016/j.talanta.2023.125318