美国华盛顿大学Georg Seelig研究团队利用split-pool条形码技术对微生物进行了单细胞RNA测序（scRNA-seq）。2020年12月17日出版的《科学》杂志发表了这项成果。

研究人员研发了microSPLiT，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，可以解决异质转录问题。研究人员利用microSPLiT检测了处于不同生长阶段的25,000多个枯草芽孢杆菌细胞，绘制了其代谢和生活方式变化的图集。

研究还揭示了与已知但罕见状态（如适应性和原噬菌体诱导）相关的详细基因表达谱，并鉴定了新的和未知基因表达状态，包括细胞亚群中小生境代谢途径的异质激活。MicroSPLiT为细菌群落中基因表达的高通量分析铺平了道路，否则无法对细菌进行单细胞分析（例如天然微生物群）。

研究人员表示，scRNA-seq已成为揭示真核生物基因表达的重要工具，但当前的测序方法并不适用于细菌。

附：英文原文

Title: Microbial single-cell RNA sequencing by split-pool barcoding

Author: Anna Kuchina, Leandra M. Brettner, Luana Paleologu, Charles M. Roco, Alexander B. Rosenberg, Alberto Carignano, Ryan Kibler, Matthew Hirano, R. William DePaolo, Georg Seelig

Issue&Volume: 2020/12/17

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, 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 Bacillus subtilis 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 novel and 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 otherwise not amenable to single-cell analysis such as natural microbiota.

DOI: 10.1126/science.aba5257

Source: https://science.sciencemag.org/content/early/2020/12/16/science.aba5257