Department of Food Science, Cornell University, Ithaca, NY, USA.
BMC Genomics. 2009 Dec 30;10:641. doi: 10.1186/1471-2164-10-641.
Identification of specific genes and gene expression patterns important for bacterial survival, transmission and pathogenesis is critically needed to enable development of more effective pathogen control strategies. The stationary phase stress response transcriptome, including many sigmaB-dependent genes, was defined for the human bacterial pathogen Listeria monocytogenes using RNA sequencing (RNA-Seq) with the Illumina Genome Analyzer. Specifically, bacterial transcriptomes were compared between stationary phase cells of L. monocytogenes 10403S and an otherwise isogenic DeltasigB mutant, which does not express the alternative sigma factor sigmaB, a major regulator of genes contributing to stress response, including stresses encountered upon entry into stationary phase.
Overall, 83% of all L. monocytogenes genes were transcribed in stationary phase cells; 42% of currently annotated L. monocytogenes genes showed medium to high transcript levels under these conditions. A total of 96 genes had significantly higher transcript levels in 10403S than in DeltasigB, indicating sigmaB-dependent transcription of these genes. RNA-Seq analyses indicate that a total of 67 noncoding RNA molecules (ncRNAs) are transcribed in stationary phase L. monocytogenes, including 7 previously unrecognized putative ncRNAs. Application of a dynamically trained Hidden Markov Model, in combination with RNA-Seq data, identified 65 putative sigmaB promoters upstream of 82 of the 96 sigmaB-dependent genes and upstream of the one sigmaB-dependent ncRNA. The RNA-Seq data also enabled annotation of putative operons as well as visualization of 5'- and 3'-UTR regions.
The results from these studies provide powerful evidence that RNA-Seq data combined with appropriate bioinformatics tools allow quantitative characterization of prokaryotic transcriptomes, thus providing exciting new strategies for exploring transcriptional regulatory networks in bacteria.
确定对细菌存活、传播和发病机制至关重要的特定基因和基因表达模式，对于开发更有效的病原体控制策略至关重要。使用 Illumina Genome Analyzer 的 RNA 测序 (RNA-Seq) 技术，定义了人类细菌病原体李斯特菌的静止期应激转录组，包括许多依赖 sigmaB 的基因。具体来说，比较了李斯特菌 10403S 的静止期细胞和另一个同基因 DeltasigB 突变体的细菌转录组，后者不表达替代 sigma 因子 sigmaB，sigmaB 是应激反应基因（包括进入静止期时遇到的应激）的主要调控因子。
总体而言，李斯特菌的所有基因中有 83%在静止期细胞中转录；在这些条件下，目前注释的李斯特菌基因中有 42%显示出中等至高转录水平。共有 96 个基因在 10403S 中的转录水平明显高于 DeltasigB，表明这些基因依赖 sigmaB 转录。RNA-Seq 分析表明，在静止期李斯特菌中有 67 个非编码 RNA 分子（ncRNA）转录，包括 7 个以前未被识别的推定 ncRNA。动态训练的隐马尔可夫模型的应用，结合 RNA-Seq 数据，在 96 个依赖 sigmaB 的基因和一个依赖 sigmaB 的 ncRNA 的上游鉴定了 65 个推定的 sigmaB 启动子。RNA-Seq 数据还能够注释推定的操纵子，并可视化 5'-和 3'-UTR 区域。
这些研究的结果提供了有力的证据，表明 RNA-Seq 数据与适当的生物信息学工具相结合，可以定量描述原核转录组，从而为探索细菌中的转录调控网络提供了令人兴奋的新策略。
