转录组
生物
核糖核酸
基因
细菌
遗传学
计算生物学
基因表达
作者
Fabian Imdahl,Ehsan Vafadarnejad,Christina Homberger,Antoine‐Emmanuel Saliba,Jörg Vogel
出处
期刊:Nature microbiology
日期:2020-08-17
卷期号:5 (10): 1202-1206
被引量:140
标识
DOI:10.1038/s41564-020-0774-1
摘要
Bacteria respond to changes in their environment with specific transcriptional programmes, but even within genetically identical populations these programmes are not homogenously expressed1. Such transcriptional heterogeneity between individual bacteria allows genetically clonal communities to develop a complex array of phenotypes1, examples of which include persisters that resist antibiotic treatment and metabolically specialized cells that emerge under nutrient-limiting conditions2. Fluorescent reporter constructs have played a pivotal role in deciphering heterogeneous gene expression within bacterial populations3 but have been limited to recording the activity of single genes in a few genetically tractable model species, whereas the vast majority of bacteria remain difficult to engineer and/or even to cultivate. Single-cell transcriptomics is revolutionizing the analysis of phenotypic cell-to-cell variation in eukaryotes, but technical hurdles have prevented its robust application to prokaryotes. Here, using an improved poly(A)-independent single-cell RNA-sequencing protocol, we report the faithful capture of growth-dependent gene expression patterns in individual Salmonella and Pseudomonas bacteria across all RNA classes and genomic regions. These transcriptomes provide important reference points for single-cell RNA-sequencing of other bacterial species, mixed microbial communities and host–pathogen interactions. This study reports an improved poly(A)-independent single-cell RNA-sequencing protocol to capture growth-dependent gene expression patterns in individual Salmonella and Pseudomonas bacteria.
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