Droplet microfluidics for high-throughput single-cell analysis

Abstract

Droplet microfluidics have been widely used for single-cell analysis. Coupled with high-throughput sequencing, droplet-based single-cell sequencing methods have been developed to analyze RNA, DNA and even proteins in individual cells. Barcoding beads are key components for single-cell sequencing in droplets. We first report a new approach to fabricate dissolvable polyacrylamide beads by cross linking acrylamide with disulfide bridges that can be cleaved with dithiothreitol, as well as a new method to cleave barcode primers from beads by using a Mg2+-dependent DNAzyme. The new barcode beads are easy to synthesize and the primer cost for the beads is significantly lower than that for the previous barcoding beads. In addition, while the existing droplet-based single-cell sequencing methods have been successfully used to identify new cell types in eukaryotic systems, the accurate quantification of variation in gene expression within each individual cell is still limited by low sensitivity and high technical noise. Moreover, the applications of these methods to study single bacterial cells have been hindered by their extremely low mRNA abundance, large percentage of ribosomal RNA, lack of mRNA polyadenylation and tough cell walls. We present a new droplet-based single-cell total-RNA sequencing method that is more sensitive than current methods and could be used for RNA sequencing in both eukaryotic cells and bacteria. We sequence HEK 293T human embryonic kidney cells and NIH/3T3 mouse fibroblasts cells as well as their nuclei to show that more genes and transcripts can be detected by our method than other methods. We then apply our method to sequence the nuclei from frozen human brain tissue samples, and identify eleven clusters of cells that are further classified as either neurons or glial cells. Furthermore, we demonstrate single-bacterium RNA sequencing by successfully detecting hundreds of genes from single E. coli and single B. subtilis. We expect that our single-cell total-RNA sequencing method will have broad impacts on biological and clinical research.