Department of Pediatric Pulmonology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, China.
Immunol Cell Biol. 2020 Oct;98(9):726-742. doi: 10.1111/imcb.12371. Epub 2020 Jul 20.
Streptococcus pneumoniae is a major causative agent of pneumonia worldwide and its complex interaction with the lung epithelium has not been thoroughly characterized. In this study, we exploited both RNA-sequencing and microRNA (miRNA)-sequencing approaches to monitor the transcriptional changes in human lung alveolar epithelial cells infected by S. pneumoniae in a time-resolved manner. A total of 1330 differentially expressed (DE) genes and 45 DE miRNAs were identified in all comparisons during the infection process. Clustering analysis showed that all DE genes were grouped into six clusters, several of which were primarily involved in inflammatory or immune responses. In addition, target gene enrichment analyses identified 11 transcription factors that were predicted to link at least one of four clusters, revealing transcriptional coregulation of multiple processes or pathways by common transcription factors. Notably, pharmacological treatment suggested that phosphorylation of p65 is important for optimal transcriptional regulation of target genes in epithelial cells exposed to pathogens. Furthermore, network-based clustering analysis separated the DE genes negatively regulated by DE miRNAs into two functional modules (M1 and M2), with an enrichment in immune responses and apoptotic signaling pathways for M1. Integrated network analyses of potential regulatory interactions in M1 revealed that multiple DE genes related to immunity and apoptosis were regulated by multiple miRNAs, indicating the coordinated regulation of multiple genes by multiple miRNAs. In conclusion, time-series expression profiling of messenger RNA and miRNA provides a wealth of information for global transcriptional changes, and offers comprehensive insight into the molecular mechanisms underlying host-pathogen interactions.
肺炎链球菌是全球范围内导致肺炎的主要病原体,但其与肺上皮细胞的复杂相互作用尚未得到充分描述。在本研究中,我们利用 RNA 测序和 microRNA (miRNA) 测序方法,以时间分辨的方式监测肺炎链球菌感染人肺泡上皮细胞的转录变化。在整个感染过程的所有比较中,共鉴定出 1330 个差异表达 (DE) 基因和 45 个 DE miRNA。聚类分析表明,所有 DE 基因分为六个簇,其中几个主要参与炎症或免疫反应。此外,靶基因富集分析鉴定出 11 个转录因子,预测至少有一个转录因子与四个簇中的一个相连,揭示了共同转录因子对多个过程或途径的转录共调控。值得注意的是,药理学处理表明,p65 的磷酸化对于上皮细胞中靶基因的最佳转录调控是重要的。此外,基于网络的聚类分析将受 DE miRNA 负调控的 DE 基因分为两个功能模块 (M1 和 M2),M1 中富集了免疫反应和凋亡信号通路。M1 中潜在调控相互作用的综合网络分析表明,多个与免疫和凋亡相关的 DE 基因受多个 miRNA 调控,表明多个 miRNA 对多个基因的协调调控。总之,信使 RNA 和 miRNA 的时间序列表达谱为全局转录变化提供了丰富的信息,并为宿主-病原体相互作用的分子机制提供了全面的见解。