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Author Spotlight: Advancing Metabolomics Analysis of Rare Hematopoietic Stem Cells
Published on: February 23, 2024
Minimally Invasive Single-Cell Metabolomics Analysis to Unveil Different Trajectories of Individual Cells in
Dandan Xia1, Rong Jin1, Le Tong1
1The State Key Lab of Analytical Chemistry for Life Science, School of Chemistry, Chemistry and Biomedicine Innovation Center (ChemBIC), Nanjing University, Nanjing, Jiangsu 210093, China.
Abstract:
Existing cellular heterogeneity necessitates continuous analysis in a single cell to capture dynamic information. However, current mass spectrometry-based single-cell metabolomics analysis is a destructive technique and cannot perform multiple samplings from the same cell, which complicates the accurate tracking of metabolite level alterations. In this study, we present a minimally invasive single-cell mass spectrometry technique that enables sampling of less than 10% of the total cell volume per iteration by using nanocapillaries. This minimally invasive process allows for repeated sampling from a single cell without compromising its essential physiological functions. The resulting time-resolved metabolomics analysis provides the alteration in metabolite levels in a single cell in a process of erastin-induced ferroptosis. As compared to the metabolite levels at certain time points, the alteration in metabolite levels exhibits a stronger correlation with the extent of mitochondrial lipid peroxidation. More importantly, by mapping the differentiation trajectory of individual cells during this process, two distinct groups─proliferating and quiescent cells─are identified. These two groups of cells exhibit different sensitivities to ferroptosis, with quiescent cells being more susceptible to ferroptosis, which could only be tracked by using the time-resolved single-cell metabolomics analysis. Ultimately, this technique overcomes the challenge in single-cell dynamic studies posed by cellular heterogeneity, providing more accurate biological insights into the diversity and complexity of cellular metabolic activities.
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