Single-cell RNA-sequencing (scRNA-seq) is a powerful method to determine the cellular composition of healthy and diseased tissues. Sequencing RNA from individual cells can reveal a lot of information about what these cells do in the body. However, current scRNA-seq platforms usually show an inverse relationship between the number of cells that can be profiled at one time and the amount of biological information that can be recovered from each cell. Researchers from Massachusetts Institute of Technology (MIT) have now greatly increased the amount of information collected from each cell by modifying the commonly used Seq-Well technique. Researchers call Seq-Well S3 (for "Second-Strand Synthesis"), which incorporates the use of a randomly primed second-strand synthesis after reverse transcription to append a second oligonucleotide handle for whole transcriptome amplification (WTA).
Using their new method, the MIT team can extract 10 times more information from each unit in the sample. This increase should allow scientists to learn more about the genes expressed in each cell and help them discover subtle but critical differences between healthy and dysfunctional cells. In a recent study published in the journal Immunity, the team demonstrated the power of the Seq-Well S3 technology through analyzing about 40000 cells from patients with five different skin diseases. Their analysis of immune cells and other cell types revealed many differences and some common features among the five diseases.
In order to accurately report the expression of key phenotypic features of cells, scRNA-seq platforms are needed that are high fidelity and high throughput. Here, Hughes et al. created Seq-Well S3, a massively parallel scRNA-seq protocol. They hypothesized that the use of "template-switching" to append a second PCR handle during reverse transcription might limit the recovery of unique transcripts and genes from a single cell in some massively parallel scRNA-seq methods. Therefore, they incorporated a randomly primed second-strand synthesis following first-strand cDNA construction. S3 reclaims cDNA molecules that were successfully reverse transcribed but not labeled with a second oligonucleotide handle through template switching and thus would generally have been lost in common bead-based high-throughput scRNA-seq protocol such as Drop-Seq or Seq-Well.
Figure 1. Conceptual illustration of the molecular features that define immune phenotypes as well as the Seq-Well S3.
Using Seq-Well S3, researchers obtained a 5- to 10-fold increase in the number of unique genes and transcripts captured per cell at similar sequencing depth. In addition to an increase in the number of genes and transcripts recovered per cell, Seq-Well S3 facilitated enhanced detection of lineage-defining factors in immune and parenchymal cells, such as cytokines, cytokine receptors, and transcription factors, which are often transiently or lowly expressed among lymphocytes.
The researchers analyzed 19 patient skin biopsies, representing five different skin diseases -- psoriasis, leprosy, alopecia areata, acne, and granuloma annulare by using this technique. They uncovered some similarities between diseases, for example, in leprosy and granuloma annulare, similar populations of inflammatory T cells appeared active. Besides, they also found some features that were unique to a particular disease. In the cells of some patients with psoriasis, they found that cells called keratinocytes express genes that allow them to proliferate and drive the inflammation seen in the disease. In future studies, Seq-Well S3 will enhance the immune and parenchymal phenotypic characteristics of various inflammations across the tissue compartment and how their interactions influence the development of human disease, thus revealing actionable therapeutic and prophylactic axes.
In general, Seq-Well S3 offers a competitive alternative that is uniquely suited for clinical studies due to its efficiency, simplicity, compatibility with fragile cells, flexible stopping points, limited peripherals, ability to be parallelized, high degree of technical reproducibility, and open molecular biology (which allows targeted enrichment of molecules of interest). Besides, the technique could also be applied to many cell types and other diseases, including cancer and infectious diseases such as HIV, tuberculosis, malaria, and Ebola, et al.