New Article in Lab Chip

Post date: Feb 6, 2018 5:37:17 AM

Hui-Sung Moon,* Kwanghwi Je, Jae-Woong Min, Donghyun Park, Kyung-Yeon Han, Seungho Shin, Woong-Yang Park, Chang Eun Yoo* and Shin-Hyun Kim,* "Inertial-Ordering-Assisted Droplet Microfluidic for High-Throughput Single-Cell RNA-Sequencing", Lab on a Chip, Accepted for publication (2018). (Moon & Je contributed equally, Co-corresponding author) [pdf]

Single-cell RNA-seq reveals the cellular heterogeneity inherent in the population of cells, which is very important in many clinical and research applications. Recent advances in droplet microfluidics have achieved the automatic isolation, lysis, and labeling of single cells in droplet compartments without complex instrumentation. However, barcoding errors occurring in the cell encapsulation process because of the multi-beads-in-droplet and insufficient throughput because of the low concentration of beads for avoiding multi-beads-in-a-droplet remain important challenges for precise and efficient expression profiling of single cell. In this study, we developed a new droplet-based microfluidic platform that significantly improved throughput while reducing barcoding error through deterministic encapsulation of inertially ordered beads. Highly concentrated beads containing oligonucleotide barcodes were spontaneously ordered in a spiral channel by an inertial effect, which was in turn encapsulated in droplets one-by-one, while cells were simultaneously encapsulated in the droplets. The deterministic encapsulation of beads resulted in a high fraction of single-bead-in-a-droplet and rare multi-beads-in-a-droplet although the bead concentration increased to 1000 μL-1, which diminished barcoding error and enabled accurate high-throughput barcoding. We successfully validated our device with single-cell RNA-seq. In addition, we found that multi-beads-in-a-droplet, generated using a normal drop-seq device with a high concentration of beads, underestimated transcript numbers and overestimated cell numbers. This accurate high-throughput platform can expand the capability and practicality of Drop-Seq in single-cell analysis.