Time‐resolved mRNA and miRNA expression profiling reveals crucial coregulation of molecular pathways involved in epithelial–pneumococcal interactions. Issue 9 (20th July 2020)

• Record Type: Journal Article
• Authors: Li, Haiyan; Lin, Li; Chong, Lei; Gu, Shuge; Wen, Shunhang; Yu, Gang; Hu, Xiaoguang; Dong, Lin; Zhang, Hailin; Li, Changchong
• Is Part Of: Immunology and cell biology. Volume 98:Issue 9(2020)
• Page Start: 726
• Page End: 742
• Publication Date: 2020-07-20
• Subjects: expression profiling -- host–pathogen interactions -- immune response -- lung epithelial cells -- network analysis -- Streptococcus pneumoniae; Immunology -- Periodicals; Cytology -- Periodicals; 616.079
• DOI: 10.1111/imcb.12371
• Languages: English
• ISSNs: 0818-9641

Abstract

Abstract: 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. Abstract : In this study, we applied RNA‐sequencing technology to investigate the time‐resolved gene expression profiles of microRNAs (miRNAs) and messenger RNAs (mRNAs) in human lung alveolar epithelial cells in response to Streptococcus pneumoniae up to 8 h postinfection. Through a range of bioinformatics and function‐related analyses, we found several functional clusters and key regulators associated with inflammatory and immune responses. Finally, we built a regulatory network among differentially expressed miRNAs and differentially expressed target mRNAs to investigate the potential biological function or relevance during infection of miRNA–mRNA interactions.