bioRxiv · 10.64898/2025.12.19.695573
Low-temperature HILIC provides enhanced separations and stability for LC-MS-based metabolomics
Abstract
AbstractLiquid chromatography-mass spectrometry is a potent and robust tool for studying metabolism. However, conventional workflows can suffer from poor peak shapes, limited pressure tolerance, co-elution of polar metabolites, and unstable retention times. Here, we describe the development of a more stable HILIC method for LC-MS metabolomics of human plasma and cell extracts, optimizing a zwitterionic HILIC (Z-HILIC) column for improved untargeted performance. We found that using high-pH ammonium bicarbonate with 90% acetonitrile in mobile phase B (ABC B) can greatly improve peak shapes of select metabolites when compared to 100% acetonitrile (ACN B), but at the cost of poor retention time stability. We therefore focused on optimizing chromatography for the ACN B method and observed that cooling the column to 5 {degrees}C substantially enhanced peak shape. This low-temperature Z-HILIC (LT-ZHILIC) method provides high-resolution separation of metabolites from both cellular extracts and human plasma, is stable over days, and generally outperformed a standard method using the widely described ZIC-pHILIC column. Application of the untargeted LT-ZHILIC method to characterize the metabolic consequences of glutamine and pyruvate deficiency in human cells revealed a striking change in nucleotide phosphates; a perturbation that was not observed in the ZIC-pHILIC analysis of the same samples likely due to inadequate elution profiles. In sum, the LT-ZHILIC workflow offers a robust platform to advance untargeted metabolomics by improving metabolite coverage, resolution, and retention time stability, making it a promising technique for providing novel insights into cellular metabolic rewiring and the human plasma metabolome.
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Liu, Y., Jastrab, M. L., Xiao, M., Lisci, M., Bader, T. K., Jourdain, A. A., Wales, T. E., Skinner, O. S.. 2025-12-22. Low-temperature HILIC provides enhanced separations and stability for LC-MS-based metabolomics. https://doi.org/10.64898/2025.12.19.695573
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