Therefore, single cell sequencing developed alongside its necessity in research awarding it “method of the year” by Nature Methods in 2013 ( 2014). However, genomic studies rely on studying collective averages obtained from pooling thousands to millions of cells, precluding genome-wide analysis of cell to cell variability. On the other hand, high-throughput genomic analysis, such as DNA and RNA sequencing are now widely used. These techniques allow quantification of a limited number of parameters in single cells. In early times, researchers have applied low-throughput single cell analysis techniques, such as immunofluorescence, fluorescence in situ hybridization (FISH) and single cell PCR, to detect certain molecular markers of single cells ( Taniguchi et al., 2009 Citri et al., 2012). It is believed that single cell analyses have influences on various fields including life sciences and biomedical research ( Blainey and Quake, 2014). Therefore, new technologies to isolate individual single cells from a complex sample and study the genomes and proteomes of single cells could provide great insights on genome variation and gene expression processes.
These challenges make conventional analysis insufficient. Due to the variation in genetic and environmental factors, different kinds of cells have unique behaviors and present different implications in pathogenic conditions ( Schor and Schor, 2001). The stromal cells are composed of endothelial cells, fibroblasts, macrophages, immune cells, and stem cells. For example, the tumor microenvironment is a complex heterogeneous system that consists of multiple intricate interactions between tumor cells and its neighboring non-cancerous stromal cells.
However, in doing this important information about a small but potentially relevant subpopulation maybe lost, particularly in cases where that subpopulation determines the behavior of the whole population. Thus, the isolation of distinct cell types is essential for further analysis and will be valuable for diagnostics, biotechnological and biomedical applications.Ĭonventional cell-based assays mainly measure the average response from a population of cells, assuming the average response is representative of each cell.
For example, a developing embryo, brain, or tumor have intricate structures consisting of numerous types of cells that may be spatially separated. Despite the apparent synchrony in cellular systems, analyzed single cell results show that even the same cell line or tissue, can present different genomes, transcriptomes, and epigenomes during cell division and differentiation ( Schatz and Swanson, 2011). The cell is the fundamental unit of biological organisms. Here, we summarize the historical background, limitations, applications, and potential of single cell isolation technologies. In this review, we focus on the recent developments in single cell isolation and analysis, which include technologies, analyses and main applications. To better understand the variations from cell to cell, scientists need to use single cell analyses to provide more detailed information for therapeutic decision making in precision medicine. Conventional cell-based assays mainly analyze the average responses from a population of cells, without regarding individual cell phenotypes. Cell to cell differences in RNA transcripts and protein expression can be key to answering questions in cancer, neurobiology, stem cell biology, immunology, and developmental biology. Subpopulations studies with mixed mutants and wild types may not be as informative regarding which cell responds to which drugs or clinical treatments. Individual cell heterogeneity within a population can be critical to its peculiar function and fate. 4Division of Surgical Oncology, Stanford University School of Medicine, Stanford, CA, USA.3Yichang Research Center for Biomedical Industry and Central Laboratory of Yichang Central Hospital, Medical School, China Three Gorges University, Yichang, China.2Laboratory of Fear and Anxiety Disorders, Institute of Life Science, Nanchang University, Nanchang, China.1The Center for Biotechnology and Biopharmaceutics, Institute of Translational Medicine, Nanchang University, Nanchang, China.Ping Hu 1†, Wenhua Zhang 2†, Hongbo Xin 1 and Glenn Deng 1,3,4 *
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