Gene expression profiling is a powerful approach that promotes a deeper understanding of the characteristics of cells at the transcriptional level and has broad implications for basic and clinical research. Historically, gene expression profiling has been performed on populations of cells, typically cell lysates, where observed expression levels represent an average of the unique expression states of each cell within the population. Such phenotypically similar populations can be purified in bulk by flow cytometry based cell sorting prior to RNA analysis. 1,2

There are several challenges with bulk analysis. For example, these approaches may not detect subtle, but potentially biologically meaningful differences between seemingly identical cells. It is now widely recognized that within a population, cells dramatically vary with respect to behavior during their lifespan and this variation is reflected in their transcriptome expression levels. The recent emergence of single cell RNA analysis (RNA- seq) has provided an important means to discern and profile cell-to-cell variability on a genomic scale. The isolation of single cells required for construction of genomic libraries can be performed using flow cytometry based cell sorting.

The Sony SH800 cell sorter has several features that support the isolation of single cells for RNA-seq. The Sony SH800 is an automated system that is used for efficiently sorting individual cells in a high throughput manner using 96 or 384 well formats with high precision. This system operates on different microfluidics sorting chips with orifice of 70, 100 and 130um enabling single cell sorting of a wide range of cell sizes from small nuclei3 and immune cells4) to large cylindrically shaped iPSC derived cardiomycocytes5 in addition to cryopreserved tissue derived from mouse disease models6. RNA-seq is a very sensitive application and therefore, care must be taken to avoid creating experimental artifacts while isolating cells. To achieve high sensitivity within a dynamic range of RNA expression, single cells isolated for RNA-seq must have low damage and intact RNA. The SH800 can be operated under low sheath and sample pressure to reduce shear stress on cells. Additionally, the sorting chip can be exchanged between samples to control for the presence of nucleases such as RNase enabling optimal sample integrity for downstream gene expression analysis.

The phenotypic data of individual cells sorted using SH800 can be indexed using software options so that it can be bioinformatically integrated with gene expression assays to produce a molecular dataset of each cell and linked to its functional activity.

References

  1. Genome-wide identification of inter-individually variable DNA methylation sites improves the efficacy of epigenetic association studies. Hachiya T, Furukawa R, Shiwa Y, Ohmomo H, Ono K, Katsuoka F, Nagasaki M, Yasuda J, Fuse N, Kinoshita K, Yamamoto M, Tanno K, Satoh M, Endo R, Sasaki M, Sakata K, Kobayashi S, Ogasawara K, Hitomi J, Sobue K and Shimizu A.
  2. Protein engineering of Cas9 for enhanced function. Oakes BL, Nadler DC, and Savage DF. Methods Enzymol. 2014; 546: 491–511.
  3. Sequencing thousands of single-cell genomes with combinatorial indexing. Nat Methods 2017, 14(3): 302-308. Vitak SA, Torkenczy KA, Rosenkrantz JL, Fields AJ, Christiansen L, Wong MH, Carbone L, Steemers FJ, and Adey A.
  4. Generation of Brain Microvascular Endothelial-Like Cells from Human Induced Pluripotent Stem Cells by Co-Culture with C6 Glioma Cells. Minami H, Tashiro K, Okada A, Hirata N, Yamaguchi T, Takayama K, Mizuguchi H, Kawabata K.  PLoS ONE 10(6): e0128890. doi:10.1371/journal.pone.0128890
  5. Neonatal Transplantation Confers Maturation of PSC-Derived Cardiomyocytes Conducive to Modeling Cardiomyopathy. Cell Reports 2017, 18: 571–582. Cho GS, Lee DI, Tampakakis E, Murphy S, Andersen P, Uosaki H, Chelko S, Chakir K, Hong I, Seo K, Chen HV, Chen X, Basso C, Houser SR, Tomaselli GF, O’Rourke B, Judge DP, Kass DA, and Kwon C.