Single Cell Proteomics Analysis of Drug Response Shows its Potential as a Drug Discovery Platform

Single-cell analysis has clearly established itself in biology and biomedical fields as an invaluable tool that allows one to comprehensively understand the relationship between cells, including their types, states, transitions, trajectories, and spatial position. Scientific methods such as fluorescence labeling, nanoscale super-resolution microscopy, advances in single cell RNAseq and proteomics technologies, provide more detailed information about biological processes which were not evident with the analysis of bulk material. This new era of single-cell biology provides a better understanding of such complex biological systems as cancer, inflammation, immunity mechanism and aging processes, and opens the door into the field of drug response heterogeneity. The latest discoveries of cellular heterogeneity gives us an unique understanding of complex biological processes, such as disease mechanism, and will lead to new strategies for better and personalized treatment strategies. Recently, single-cell proteomics techniques that allow quantification of thousands of proteins from single mammalian cells have been introduced. Here we present an improved single-cell mass spectrometry-based proteomics platform called SCREEN (Single Cell pRotEomE aNalysis) for deep and high-throughput single-cell proteome coverage with high efficiency, less turnaround time and with an improved ability for protein quantitation across more cells than previously achieved. We applied this new platform to analyze the single-cell proteomic landscape under different drug treatment over time to uncover heterogeneity in cancer cell response, which for the first time, to our knowledge, has been achieved by mass spectrometry based analytical methods. We discuss challenges in single-cell proteomics, future improvements and general trends with the goal to encourage forthcoming technical developments

Single-cell transcriptomic profiling of the aging mouse brain

The mammalian brain is complex, with multiple cell types performing a variety of diverse functions, but exactly how each cell type is affected in aging remains largely unknown. Here we performed a single-cell transcriptomic analysis of young and old mouse brains. We provide comprehensive datasets of aging-related genes, pathways and ligand–receptor interactions in nearly all brain cell types. Our analysis identified gene signatures that vary in a coordinated manner across cell types and gene sets that are regulated in a cell-type specific manner, even at times in opposite directions. These data reveal that aging, rather than inducing a universal program, drives a distinct transcriptional course in each cell population, and they highlight key molecular processes, including ribosome biogenesis, underlying brain aging. Overall, these large-scale datasets (accessible online at https://portals.broadinstitute.org/single_cell/study/aging-mouse-brain) provide a resource for the neuroscience community that will facilitate additional discoveries directed towards understanding and modifying the aging process