Literature DB >> 32425041

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

Xing Xu1, Qianqian Zhang1, Jia Song2, Qingyu Ruan1, Weidong Ruan1, Yujie Chen1, Jian Yang1, Xuebing Zhang1, Yanling Song1, Zhi Zhu1, Chaoyong Yang1,2.   

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.

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Year:  2020        PMID: 32425041     DOI: 10.1021/acs.analchem.0c01613

Source DB:  PubMed          Journal:  Anal Chem        ISSN: 0003-2700            Impact factor:   6.986


  3 in total

Review 1.  Chemical Analysis of Single Cells and Organelles.

Authors:  Keke Hu; Tho D K Nguyen; Stefania Rabasco; Pieter E Oomen; Andrew G Ewing
Journal:  Anal Chem       Date:  2020-12-07       Impact factor: 6.986

2.  Single-cell transcriptomics reveal the heterogeneity and dynamic of cancer stem-like cells during breast tumor progression.

Authors:  Guojuan Jiang; Juchuanli Tu; Lei Zhou; Mengxue Dong; Jue Fan; Zhaoxia Chang; Lixing Zhang; Xiuwu Bian; Suling Liu
Journal:  Cell Death Dis       Date:  2021-10-21       Impact factor: 8.469

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

Authors:  Yingfei Wang; Yanyun Fang; Yu Zhu; Shiyi Bi; Ying Liu; Huangxian Ju
Journal:  Chem Sci       Date:  2022-01-27       Impact factor: 9.825

  3 in total

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