奥地利科学院分子医学CeMM研究中心Christoph Bock课题组开发了具有组合流体索引的超高通量单细胞 RNA 测序和扰动筛选技术。这一研究成果发表在2021年5月31日出版的国际学术期刊《自然-方法学》。

为了对数百万个单个细胞进行经济高效的单细胞测序，他们开发了“单细胞组合流体索引”（scifi）技术。scifi-RNA-seq 分析将透化细胞内整个转录组的一步组合预索引与随后使用微流体的单细胞 RNA-seq 相结合。预索引允许他们为每个液滴加载多个细胞，并通过计算解复用它们的单个表达谱。因此，scifi-RNA-seq 大大提高了基于液滴的单细胞 RNA-seq 的吞吐量，并提供了一种在单个实验中复用数千个样本的直接方法。

与多轮组合索引相比，scifi-RNA-seq 提供了简单高效的工作流程。与标记和丢弃包含多个细胞的液滴的细胞散列方法相比，scifi-RNA-seq 解析并保留来自过载液滴的单个转录组。他们在各种人类和小鼠细胞系上对 scifi-RNA-seq 进行了基准测试，对原代人类 T 细胞进行了验证，并将其应用于具有 T 细胞受体激活的单细胞转录组读数的高度多重 CRISPR 筛选。

据了解，细胞图谱项目和高通量扰动筛选需要以当前技术具有挑战性的规模进行单细胞测序。

附：英文原文

Title: Ultra-high-throughput single-cell RNA sequencing and perturbation screening with combinatorial fluidic indexing

Author: Paul Datlinger, Andr F. Rendeiro, Thorina Boenke, Martin Senekowitsch, Thomas Krausgruber, Daniele Barreca, Christoph Bock

Issue&Volume: 2021-05-31

Abstract: Cell atlas projects and high-throughput perturbation screens require single-cell sequencing at a scale that is challenging with current technology. To enable cost-effective single-cell sequencing for millions of individual cells, we developed ‘single-cell combinatorial fluidic indexing’ (scifi). The scifi-RNA-seq assay combines one-step combinatorial preindexing of entire transcriptomes inside permeabilized cells with subsequent single-cell RNA-seq using microfluidics. Preindexing allows us to load several cells per droplet and computationally demultiplex their individual expression profiles. Thereby, scifi-RNA-seq massively increases the throughput of droplet-based single-cell RNA-seq, and provides a straightforward way of multiplexing thousands of samples in a single experiment. Compared with multiround combinatorial indexing, scifi-RNA-seq provides an easy and efficient workflow. Compared to cell hashing methods, which flag and discard droplets containing more than one cell, scifi-RNA-seq resolves and retains individual transcriptomes from overloaded droplets. We benchmarked scifi-RNA-seq on various human and mouse cell lines, validated it for primary human T cells and applied it in a highly multiplexed CRISPR screen with single-cell transcriptome readout of T cell receptor activation.

DOI: 10.1038/s41592-021-01153-z

Source: https://www.nature.com/articles/s41592-021-01153-z