Single‐Cell Metabolomics by Mass Spectrometry: Opportunities and Challenges. Issue 1 (8th November 2021) - Dolatmoradi, Marjan; Samarah, Laith Z.; Vertes, Akos
Abstract: Cellular heterogeneity is an inherent property of cell populations with a wide spectrum of biological manifestations, ranging from barely observable variations that enhance organismal adaptation, to life‐threatening differences. Single‐cell metabolomics can reveal molecular information and variations in metabolite concentrations between cells that are masked in cell‐population studies. These differences are quantitatively captured by the abundance distributions for the population and their statistical analysis can reveal the presence of latent subpopulations. In recent years, mass spectrometry (MS), combined with novel sampling and ionization techniques, has become an important tool for single‐cell metabolomics. These new techniques must contend with significant challenges in the form of small cell sizes and volumes, ultratrace metabolite amounts per cell, and potentially interfering high turnover rates and rapid diffusion. Owing to the ultrasmall sample volume, low abundance of some metabolites, and poor ionization efficiencies, metabolite detection, identification, and accurate quantitation remain a major challenge. The ability of some techniques to analyze tissue‐embedded cells opens the door for spatial metabolomics, potentially revealing cellular synergism in organ level metabolism. In this Concept article, we present a bird's eye view of these major themes in single cell metabolomics and some of the relevant MS‐based methods. Abstract : Single‐cell mass spectra inform us of metabolite abundance variations in cell populations, enable the recognition of hidden phenotypes, the discovery of metabolic states, and the identification of rare cells. Comparing gene expression, protein function and metabolite levels in single cells can reveal a comprehensive view of cellular physiology. Metabolic analysis of tissue embedded single cells uncovers the spatial relationships of cell types and contributes to emerging cell atlases. This Concept article highlights the opportunities and challenges in this fast‐moving field.