研究揭示適用於微生物單細胞RNA測序的方法

研究揭示適用於微生物單細胞RNA測序的方法

作者：

小柯機器人

發布時間：2020/12/18 21:47:27

美國華盛頓大學Georg Seelig研究團隊利用split-pool條形碼技術對微生物進行了單細胞RNA測序（scRNA-seq）。2020年12月17日出版的《科學》雜誌發表了這項成果。

研究人員研發了microSPLiT，這是一種適用於革蘭氏陰性和革蘭氏陽性細菌的高通量scRNA-seq方法，可以解決異質轉錄問題。研究人員利用microSPLiT檢測了處於不同生長階段的25,000多個枯草芽孢桿菌細胞，繪製了其代謝和生活方式變化的圖集。

研究還揭示了與已知但罕見狀態（如適應性和原噬菌體誘導）相關的詳細基因表達譜，並鑑定了新的和未知基因表達狀態，包括細胞亞群中小生境代謝途徑的異質激活。MicroSPLiT為細菌群落中基因表達的高通量分析鋪平了道路，否則無法對細菌進行單細胞分析（例如天然微生物群）。

研究人員表示，scRNA-seq已成為揭示真核生物基因表達的重要工具，但當前的測序方法並不適用於細菌。

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

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