A Highly Sensitive, Accurate, and Automated Single-Cell RNA Sequencing Platform with Digital Microfluidics

Abstract

Single-cell RNA sequencing (scRNA-seq) is a powerful method in investigating single-cell heterogeneity to reveal rare cells, identify cell subpopulations, and construct a cell atlas. Conventional benchtop methods for scRNA-seq, including multistep operations, are labor intensive, reaction inefficient, contamination prone, and reagent consuming. Here we report a digital microfluidics-based single-cell RNA sequencing (digital-RNA-seq) for simple, efficient, and low-cost single-cell mRNA measurements. Digital-RNA-seq automates fluid handling as discrete droplets to sequentially perform protocols of scRNA-seq. To overcome the current problems of single-cell isolation in efficiency, integrity, selectivity, and flexibility, we propose a new strategy, passive dispensing method, relying on well-designed hydrophilic–hydrophobic microfeatures to rapidly generate single-cell subdroplets when a droplet of cell suspension is encountered. For sufficient cDNA generation and amplification, digital-RNA-seq uses nanoliter reaction volumes and hydrophobic reaction interfaces, achieving high sensitivity in gene detection. Additionally, the stable droplet handling and oil-closed reaction space featured in digital-RNA-seq ensure highly accurate measurement. We demonstrate the functionality of digital-RNA-seq by quantifying heterogeneity among single cells, where digital-RNA-seq shows excellent performance in rare transcript detection, cell type differentiation, and essential gene identification. With the advantages of automation, sensitivity, and accuracy, digital-RNA-seq represents a promising scRNA-seq platform for a wide variety of biological applications.

Single cell multi-miRNAs quantification with hydrogel microbeads for liver cancer cell subtypes discrimination

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Chemical Analysis of Single Cells and Organelles

“…Although several commercial platforms are available, improvements and new approaches are still being published. Xu et al reported a digital microfluidics platform for single-cell mRNA sequencing . In digital microfluidics, researchers move around aqueous droplets in a minute, oil-filled space between two parallel plates.…”

Atomic Force Microscopy Detects the Difference in Cancer Cells of Different Neoplastic Aggressiveness via Machine Learning

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