Abstract
Due to a growing interest in the life sciences community for single-cell metabolomics, there is a need for sensitive analytical tools that maximise metabolite coverage and annotation confidence from limited sample material. Here, we report an optimised microflow liquid chromatography-mass spectrometry (LC-MS) workflow for untargeted metabolomic analysis of single eukaryotic cells. Solvent composition, ion source parameters, data-dependent acquisition (DDA) cycle time, and separate positive and negative ionisation methods were systematically optimised to improve both feature detection and metabolite annotation at the single-cell level. Our optimised method has significantly enhanced coverage of features (4-fold) and named features with MS2 spectra (5-fold) compared with our previously reported workflow. The increased sensitivity allowed complementary positive and negative ionisation analyses to be performed on the same single cell, to maximise coverage. The stability of metabolite profiles during live-cell sampling was evaluated, demonstrating that extended incubation in phosphate buffered saline (PBS) had minimal impact on the metabolomics measurement. Our method provides a robust and accessible workflow for high-coverage single-cell metabolomics and supports future investigations of metabolic processes in living cells.