Prokaryotic single-cell RNA sequencing by in situ combinatorial indexing.
Prokaryotic single-cell RNA sequencing by in situ combinatorial indexing.
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DOI：
10.1038/s41564-020-0729-6
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发表时间：
2020-10
影响因子：
28.3
通讯作者：
Tavazoie S
中科院分区：
文献类型：
--
作者：
Blattman SB;Jiang W;Oikonomou P;Tavazoie S
尽管对同基因细菌群体中基因表达异质性的认识由来已久，但用于研究单个细菌细胞的负担得起且可扩展的技术受到限制。虽然单细胞RNA测序（scRNA-seq）已经彻底改变了不同真核系统中转录异质性的研究，但scRNA-seq在原核生物中的应用受到其极低mRNA丰度，缺乏mRNA聚腺苷酸化和厚细胞壁的阻碍。在这里，我们提出了通过标记RNA原位和测序（PETRI-seq）进行的Proximity表达谱分析，这是一种低成本，高通量的原核scRNA-seq管道，可以克服这些技术障碍。PETRI-seq在一次实验中使用原位组合索引对来自数万个细胞的转录本进行条形码。PETRI-seq以高纯度和低偏倚捕获革兰氏阴性和革兰氏阳性细菌的单细胞转录组，对于指数生长的E.杆菌这些特征使得能够稳健地区分对应于不同生长阶段的细胞状态。当应用于野生型S.在金黄色葡萄球菌中，PETRI-seq揭示了经历原噬菌体诱导的罕见细胞亚群。我们预计PETRI-seq在定义复杂微生物群落中的单细胞状态及其动态方面具有广泛的实用性。
Despite longstanding appreciation of gene expression heterogeneity in isogenic bacterial populations, affordable and scalable technologies for studying single bacterial cells have been limited. While single-cell RNA sequencing (scRNA-seq) has revolutionized studies of transcriptional heterogeneity in diverse eukaryotic systems, application of scRNA-seq to prokaryotes has been hindered by their extremely low mRNA abundance, lack of mRNA polyadenylation, and thick cell walls. Here, we present Prokaryotic Expression-profiling by Tagging RNA In Situ and sequencing (PETRI-seq), a low-cost, high-throughput, prokaryotic scRNA-seq pipeline that overcomes these technical obstacles. PETRI-seq uses in situ combinatorial indexing to barcode transcripts from tens of thousands of cells in a single experiment. PETRI-seq captures single cell transcriptomes of Gram-negative and Gram-positive bacteria with high purity and low bias, with median capture rates >200 mRNAs/cell for exponentially growing E. coli. These characteristics enable robust discrimination of cell-states corresponding to different phases of growth. When applied to wild-type S. aureus, PETRI-seq revealed a rare sub-population of cells undergoing prophage induction. We anticipate broad utility of PETRI-seq in defining single-cell states and their dynamics in complex microbial communities.
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影响因子：
64.8
作者：
Cao, Junyue;Spielmann, Malte;Shendure, Jay
通讯作者：
Shendure, Jay
影响因子：
3.2
作者：
de Lange N;Tran TM;Abate AR
通讯作者：
Abate AR
影响因子：
12.3
作者：
Bose S;Wan Z;Carr A;Rizvi AH;Vieira G;Pe'er D;Sims PA
通讯作者：
Sims PA
影响因子：
14.9
作者：
Benson, Dennis A.;Karsch-Mizrachi, Ilene;Sayers, Eric W.
通讯作者：
Sayers, Eric W.
影响因子：
6.7
作者：
Balasubramanian, Sowmya;Osburne, Marcia S.;Leong, John M.
通讯作者：
Leong, John M.