Construction of ceRNA regulatory networks for active pulmonary tuberculosis

• Published in: Scientific reports Vol. 14; no. 1; pp. 10595 - 9
• Main Authors: Li, Qifeng, Xin, Tao, Liu, Zhigang, Wang, Quan, Ma, Lanhong
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 08-05-2024; Nature Publishing Group; Nature Portfolio
• Subjects: 631/45/603; 692/699/1785; Adult; Cell differentiation; ceRNA network; Correlation analysis; Diagnosis; Female; Flow cytometry; Gene Expression Profiling; Gene Expression Regulation; Gene Regulatory Networks; Health problems; Helper cells; Helper T cell differentiation; Humanities and Social Sciences; Humans; Lesions; Lung - metabolism; Lung - pathology; Lungs; Lymphocytes T; Male; MicroRNAs - genetics; Middle Aged; multidisciplinary; Next-generation sequencing; Non-coding RNA; Nucleotide sequence; PCR; Public health; Pulmonary tuberculosis; RNA, Competitive Endogenous; RNA, Long Noncoding - genetics; RNA, Messenger - genetics; RNA, Messenger - metabolism; Science; Science (multidisciplinary); Th17 Cells - immunology; Th17 Cells - metabolism; Transcriptome; Transcriptome sequencing; Transcriptomes; Tuberculosis; Tuberculosis, Pulmonary - genetics; Transcriptome sequencing; ceRNA network; Helper T cell differentiation; Pulmonary tuberculosis
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-024-61451-2

Delayed diagnosis in patients with pulmonary tuberculosis (PTB) often leads to serious public health problems. High throughput sequencing was used to determine the expression levels of lncRNAs, mRNAs, and miRNAs in the lesions and adjacent health lung tissues of patients with PTB. Their differential expression profiles between the two groups were compared, and 146 DElncRs, 447 DEmRs, and 29 DEmiRs were obtained between lesions and adjacent health tissues in patients with PTB. Enrichment analysis for mRNAs showed that they were mainly involved in Th1, Th2, and Th17 cell differentiation. The lncRNAs, mRNAs with target relationship with miRNAs were predicted respectively, and correlation analysis was performed. The ceRNA regulatory network was obtained by comparing with the differentially expressed transcripts (DElncRs, DEmRs, DEmiRs), then 2 lncRNAs mediated ceRNA networks were established. The expression of genes within the network was verified by quantitative real-time PCR (qRT-PCR). Flow cytometric analysis revealed that the proportion of Th1 cells and Th17 cells was lower in PTB than in controls, while the proportion of Th2 cells increased. Our results provide rich transcriptome data for a deeper investigation of PTB. The ceRNA regulatory network we obtained may be instructive for the diagnosis and treatment of PTB.