Using single-cell analysis, researchers can cleave single cells out of a population, beyond analysis of traditional mass profiling methods. Single-cell RNA sequencing can detect rare cell populations, regulatory relationships between genes, and determine cell lines during development. A research team at Cornell University has developed an enhancement of existing single-cell RNA sequencing methods that makes the technology even more useful.
In 2015, researchers from Harvard University and the Massachusetts Institute of Technology Drop-seq introduced a method to simultaneously and efficiently characterize the identities of thousands of cells, use nanoliter-sized droplets, and provide a unique identifier to each cell's RNA attach. In Drop-seq, individual cells are encapsulated with labeled microparticles that initiate reverse transcription of cellular mRNA. "These technologies are very popular because they have lowered the cost of doing this kind of analysis and they are democratized to some extent, very cheap and easy to make for many labs," said Dr. Iwijn De Vlaminck, assistant professor in biomedical engineering at Cornell University.
However, the downside is that Drop-seq can only identify a certain type of messenger RNA (mRNA) molecule, limiting the scope of the analysis. Dr. De Vlaminck and his team have developed a simple, low-cost version of the existing Drop-Seq protocol that enables multiplex amplicon sequencing and transcriptome profiling into single cells. They call their new method droplet-assisted RNA targeting by single-cell sequencing (DART-seq).
Their recent work in Nature Methods entitled "Simultaneous Multiplexed Amplicon Sequencing and Transcriptome Profiling in Single Cells" demonstrates an effective method for enzymatic adaptation of the beads prior to performing conventional drop-seq analysis which enables the collection and analysis of a wider variety of molecules than are available through drop-seq sequencing.
In addition to the improved single-cell sequencing method, DART-seq may also lead to discoveries in infection and immunology used DART-seq to simultaneously identify the transcripts of a segmented dsRNA virus and the transcriptomes of the infected cell, and also used DART-seq to simultaneously label the natively paired variable region heavy and light chain amplicons and the transcriptome of B lymphocytes could be detected and the virus could be virus-infected Identify cells and quantify viral and host gene expression, allowing the host response to single cell infection to be examined.
"A single virus species can be very diverse and this diversity allows you to do extraordinary things," said Philip Burnham, a Ph.D. student at De Vlaminck's lab and co-author of the newspaper. "So, if you can zoom to the single-cell level, you can actually see how minor changes in the virus can potentially change the cell's response to this small mutation."
Mridu Saikia, Ph.D. , a postdoctoral fellow at the De Vlaminck lab and co-lead author of The Newspaper, believes DART-seq will also help identify new approaches to cancer therapy. "Cancer cells are a very heterogeneous population," she said, "and if you do not look at them at the single-cell level, you often miss out on important information, so our technology allows it."