Category: Automation and High-Throughput Technologies
Cells are the basic unit of living organisms, and molecular characterization of single-cells has revealed marvelous heterogeneity in cell populations. To explore single-cell heterogeneity, there have been increasing needs for analyzing each single-cell one by one, instead of observing average information of a cell population. One important example is that every cancer cells possess distinct somatic mutations such as SNV (single nucleotide variation) and CNV (copy number variation), which are key information to understand cancer. Moreover, genetic heterogeneity leads to distinct phenotypes of each cancer cells, which is deeply related to clinical outcomes such as drug resistance and cancer relapse.
Recent advances in single-cell genomics have uncovered import biological questions such as tumor evolution, metastasis, and therapeutic resistance. However, a critical hurdle to single-cell genomics technology is that the cost is proportional to the number of cells examined. A cubic millimeter of a tumor consists of a million heterogeneous tumor cells. Therefore, people have always dreamed of analyzing millions of single-cells one by one, but the cost is equivalent to analyzing millions of cancer patients, which is practically impossible. This is why the impact of single-cell genomics is limited, despite the potential to revolutionize cancer research.
The major source of cost in single-cell genomics is sequencing library construction. In conventional approach, library construction is performed separately for each single-cell so the cost is proportional to the number of cells. Because cell-specific DNA barcode used for sample de-multiplexing is added at this step, it is inevitable to construct sequencing library separately for each single-cells. If the barcode is tagged before library construction, we can pool the sample all together to perform one-pot library preparation.
Here, we demonstrate a method called mMDA (Multiplex Multiple Displacement Amplification). In mMDA, cell-specific DNA barcode is added while MDA process. After DNA amplification, barcoded gDNA can be pooled together to enable one pot library preparation. As a result, library construction step is reduced to 1/N, where N is the number of single-cells to be analyzed. We achieved a 10-fold reduction in library construction cost, and dramatically reduced labor-intensive library construction process compared to conventional methods, while technical performance such as amplification uniformity and genomic coverage remained same. Another important improvement was that each single-cell data showed a high depth of coverage, which was sufficient to analyze SNV and CNV mutations simultaneously in single-cell. Since mMDA can easily be scaled up to multiplex over 1000 single-cells, we envision that this technology will accelerate to find answers in cancer research with significantly higher throughput and lower cost.
Jinhyun Kim– Ph.D candidate, Seoul National University, Seoul, Seoul-t'ukpyolsi, Republic of Korea
Seoul National University
Seoul, Seoul-t'ukpyolsi, Republic of Korea
I'm Ph.D student in BiNEL (Biophotonics and NanoEngineering Laboratory), and my major is EE (Electrical and Computer Engineering). With engineering background, I'm currently working on biotechnology to help life scientist by means of technology. My research topics are Single cell genomics, Whole Genome Amplification, High-throughput cell isolation, Cancer, Next Generation Sequencing, and Bioinformatics. I'm also interested in High throughput screening, Reproductive test, Microbiome, Transcriptomics and Epigenetics.