Multidimensional single-cell analysis: Diverse strategies and emerging applications in the life sciences

Abstract

Multidimensional single-cell analysis is an outstanding tool in life sciences, enabling the study of diverse biomolecules, including nucleic acids, epigenetic factors, proteins, and metabolites. The main strategies in this field are nucleic acid amplification-based sequencing and mass spectrometry (MS)-based molecule detection. With the commercialization of high-throughput sequencing platforms and advances in MS-based molecule detection, single-cell omics analyses have rapidly developed, enabling the exploration of single-cell metabolomics and proteomics. This work provides a comprehensive summary of the diverse strategies employed in multidimensional single-cell analysis, and particularly emphasizes the application of ultra-sensitive MS techniques, which provide new tools for single-cell nucleic acid analysis. It also highlights the discovery of functional nucleic acids, which offer novel alternatives for detecting metabolites and proteins at the single-cell level using amplification techniques. Additionally, the applications of these methods in life sciences, along with the prospects for multidimensional single-cell evaluation, are thoroughly discussed. It is anticipated that the continued evolution of multidimensional single-cell analysis will significantly advance the precision and depth of various research domains within life sciences.