inDrops-2: a flexible, versatile and cost-efficient droplet microfluidic approach for high-throughput scRNA-seq of fresh and preserved clinical samples

可扩展性 微流控 生物 工作流程 灵活性(工程) 吞吐量 计算生物学 仿形(计算机编程) 多路复用 单细胞分析 计算机科学 生化工程 纳米技术 生物系统 细胞 工程类 材料科学 遗传学 数学 电信 无线 统计 数据库 操作系统
作者
Simonas Juzėnas,Karolis Goda,Vaidotas Kiseliovas,Justina Žvirblytė,Alvaro Quintinal-Villalonga,Juozas Šiurkus,Juozas Nainys,Linas Mažutis
出处
期刊:Nucleic Acids Research [Oxford University Press]
卷期号:53 (2)
标识
DOI:10.1093/nar/gkae1312
摘要

Abstract The expansion of single-cell analytical techniques has empowered the exploration of diverse biological questions at the individual cells. Droplet-based single-cell RNA sequencing (scRNA-seq) methods have been particularly widely used due to their high-throughput capabilities and small reaction volumes. While commercial systems have contributed to the widespread adoption of droplet-based scRNA-seq, their relatively high cost limits the ability to profile large numbers of cells and samples. Moreover, as the scale of single-cell sequencing continues to expand, accommodating diverse workflows and cost-effective multi-biospecimen profiling becomes more critical. Herein, we present inDrops-2, an open-source scRNA-seq technology designed to profile live or preserved cells with a sensitivity matching that of state-of-the-art commercial systems but at a 6-fold lower cost. We demonstrate the flexibility of inDrops-2, by implementing two prominent scRNA-seq protocols, based on exponential and linear amplification of barcoded-complementary DNA, and provide useful insights into the advantages and disadvantages inherent to each approach. We applied inDrops-2 to simultaneously profile multiple human lung carcinoma samples that had been subjected to cell preservation, long-term storage and multiplexing to obtain a multiregional cellular profile of the tumor microenvironment. The scalability, sensitivity and cost efficiency make inDrops-2 stand out among other droplet-based scRNA-seq methods, ideal for large-scale studies on rare cell molecular signatures.

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