Single cell analysis technologies in biomedical research

Abstract

In recent years, we have seen an explosion of interest in the applications of single cell analysis technologies while seeking answers to biological and medical questions. In every field, from immunology, infectious disease, cancer to developmental biology, single cell analysis is providing answers that have eluded us in bulk analysis. The meteoric growth in adoption of single cell research is not possible without the technologies offered by lab automation. While in the past, single cell analysis was performed manually in laboratories with specialized expertise in mouth pipetting and cell micromanipulation, single cell analysis today is performed at scale for thousands or even millions of cells using fully automated equipment that are commonly available at core facilities. The development of new technologies not only for single cell isolation, but also for downstream processes such as imaging, functional assays and library preparation, promises to put single cell analysis capability in the hands of every laboratory. This special issue, Single-Cell Analysis Technologies, is a timely review of the landscape of technologies that have advanced considerably in the past few years. It also introduces new technology platforms and applications that would push the boundaries of single cell research. This special issue of SLAS Technology contains two review articles, three full length research papers and one short communication. The first review article by Yu and Scolnick [[1]Yu T. Scolnick J. Complex biological questions being addressed using single cell sequencing technologies.SLAS Technol. 2021; 27: 143-149Google Scholar] provides a comprehensive coverage of single cell analysis centered around sequencing analysis, which are among the most rapidly adopted recent methods. Single-cell sequencing provides unbiased, high-dimensional information that enables unprecedented resolution in measuring heterogeneity in cell states, as well as deciphering gene regulatory networks that underlie the transition between cell states. Furthermore, combination of single cell analysis with perturbation studies such as CRISPR screening showed great potential for drug discovery efforts. Finally, the authors discuss the recent technologies in spatial transcriptomics, to give a perspective on future promises of single cell sequencing for understanding biology and disease in the native tissue context. Following this, the second review article by Otterstrom et al. [[2]Otterstrom J.J. Lubin A. Payne E.M. Paran Y. Technologies bringing young Zebrafish from a niche field to the limelight.SLAS Technol. 2022; 27: 109-120Google Scholar] presents another facet of single cell analysis, focusing on image analysis at the single cell resolution in whole organisms as a method for high content screening. Various automation approaches are presented to increase the throughput, reproducibility and data quality of zebrafish high-content screening. Image analysis methodologies that capitalize on machine learning to extract features relevant to screening are also explored. The two reviews on single cell analysis technologies in this special issue highlight the progression in the use of single cell technologies in increasingly complex but also more physiological applications, from dissociated single cells to cells in tissue context and finally of cells in whole organisms. The maturation of single cell technologies heralds a new era, where single cell precision medicine could be a reality. Four original research papers in this special issue highlight how advances in laboratory automation can push the boundaries of single cell research. The work by Rutte et al. [[3]de Rutte J. Dimatteo R. Zhu S. Archang M.M. Di Carlo D. Sorting single-cell microcarriers using commercial flow cytometers.SLAS Technol. 2022; 27: 150-159Google Scholar] describes a method to sort single cells by their functional profile, a challenging feat where few have succeeded. This strategy utilizes “nanovial”, which