Transcriptional Analysis of lncRNA and Target Genes Induced by Influenza A Virus Infection in MDCK Cells

• Published in: Vaccines (Basel) Vol. 11; no. 10; p. 1593
• Main Authors: Liu, Geng, Pei, Mengyuan, Wang, Siya, Qiu, Zhenyu, Li, Xiaoyun, Ma, Hua, Ma, Yumei, Wang, Jiamin, Qiao, Zilin, Ma, Zhongren, Liu, Zhenbin
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01-10-2023; MDPI
• Subjects: Annotations; Cell lines; Development and progression; DNA testing; Gene expression; Gene regulation; Genes; Genetic aspects; Genetic engineering; Health aspects; IAV; Infections; Influenza; Influenza A; influenza vaccine; Kinases; lncRNAs; MDCK; Molecular modelling; Non-coding RNA; Post-transcription; Proteins; Ribonucleic acid; RNA; Severe acute respiratory syndrome coronavirus 2; Signal transduction; Technology; transcriptomics; Vaccines; Viral infections; Viruses; China
• ISSN: 2076-393X; 2076-393X
• DOI: 10.3390/vaccines11101593

Background: The MDCK cell line is the primary cell line used for influenza vaccine production. Using genetic engineering technology to change the expression and activity of genes that regulate virus proliferation to obtain high-yield vaccine cell lines has attracted increasing attention. A comprehensive understanding of the key genes, targets, and molecular mechanisms of viral regulation in cells is critical to achieving this goal, yet the post-transcriptional regulation mechanism involved in virus proliferation—particularly the effect of lncRNA on influenza virus proliferation—is still poorly understood. Therefore, this study used high-throughput RNA-seq technology to identify H1N1 infection-induced lncRNA and mRNA expression changes in MDCK cells and explore the regulatory relationship between these crucial lncRNAs and their target genes. Results: In response to H1N1 infection in MDCK cells 16 h post-infection (hpi) relative to uninfected controls, we used multiple gene function annotation databases and initially identified 31,501 significantly differentially expressed (DE) genes and 39,920 DE lncRNAs (|log2FC| > 1, p < 0.05). Among these, 102 lncRNAs and 577 mRNAs exhibited predicted correlations with viral response mechanisms. Based on the magnitude of significant expression differences, related research, and RT-qPCR expression validation at the transcriptional level, we further focused on 18 DE mRNAs and 32 DE lncRNAs. Among these, the differential expression of the genes RSAD2, CLDN1, HCLS1, and IFIT5 in response to influenza virus infection was further verified at the protein level using Western blot technology, which showed results consistent with the RNA-seq and RT-qPCR findings. We then developed a potential molecular regulatory network between these four genes and their six predicted lncRNAs. Conclusions: The results of this study will contribute to a more comprehensive understanding of the molecular mechanism of host cell non-coding RNA-mediated regulation of influenza virus replication. These results may also identify methods for screening target genes in the development of genetically engineered cell lines capable of high-yield artificial vaccine production.