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基于拆分池条形码的微生物单细胞 RNA 测序。

Microbial single-cell RNA sequencing by split-pool barcoding.

机构信息

Department of Electrical and Computer Engineering, University of Washington, Seattle, WA, USA.

Department of Bioengineering, University of Washington, Seattle, WA, USA.

出版信息

Science. 2021 Feb 19;371(6531). doi: 10.1126/science.aba5257. Epub 2020 Dec 17.

Abstract

Single-cell RNA sequencing (scRNA-seq) has become an essential tool for characterizing gene expression in eukaryotes, but current methods are incompatible with bacteria. Here, we introduce microSPLiT (microbial split-pool ligation transcriptomics), a high-throughput scRNA-seq method for Gram-negative and Gram-positive bacteria that can resolve heterogeneous transcriptional states. We applied microSPLiT to >25,000 cells sampled at different growth stages, creating an atlas of changes in metabolism and lifestyle. We retrieved detailed gene expression profiles associated with known, but rare, states such as competence and prophage induction and also identified unexpected gene expression states, including the heterogeneous activation of a niche metabolic pathway in a subpopulation of cells. MicroSPLiT paves the way to high-throughput analysis of gene expression in bacterial communities that are otherwise not amenable to single-cell analysis, such as natural microbiota.

摘要

单细胞 RNA 测序(scRNA-seq)已成为描述真核生物基因表达的重要工具,但目前的方法与细菌不兼容。在这里,我们介绍了 microSPLiT(微生物分裂池连接转录组学),这是一种适用于革兰氏阴性和革兰氏阳性细菌的高通量 scRNA-seq 方法,可解析异质转录状态。我们将 microSPLiT 应用于在不同生长阶段采集的超过 25000 个细胞,创建了新陈代谢和生活方式变化的图谱。我们检索到与已知但罕见状态(如感受态和原噬菌体诱导)相关的详细基因表达谱,还确定了意想不到的基因表达状态,包括细胞亚群中生态位代谢途径的异质激活。microSPLiT 为高通量分析细菌群落中的基因表达铺平了道路,否则这些群落无法进行单细胞分析,例如自然微生物群。

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