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. 2024 May 8;14(1):10595.
doi: 10.1038/s41598-024-61451-2.

Construction of ceRNA regulatory networks for active pulmonary tuberculosis

Qifeng Li #  1 , Tao Xin #  2 , Zhigang Liu  3 , Quan Wang  4 , Lanhong Ma  5
Affiliations

Construction of ceRNA regulatory networks for active pulmonary tuberculosis

Qifeng Li et al. Sci Rep. .

Abstract

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.

Keywords: Helper T cell differentiation; Pulmonary tuberculosis; Transcriptome sequencing; ceRNA network.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Differentially expressed transcripts between lesions and adjacent healthy lung tissues. (A) Volcano plot of differentially expressed lncRNAs. Red dots represent up-regulated expression, green dots represent down-regulated, and blue dots represent non-differential expression. (B) Volcano plot of differentially expressed mRNAs. Red dots represent up-regulated expression, green dots represent down-regulated, and blue dots represent non-differential expression. (C) Volcano plot of differentially expressed miRNAs. Red dots represent up-regulated expression, green dots represent down-regulated, and blue dots represent non-differential expression.
Figure 2
Figure 2
Identification of the ceRNA regulator network in pulmonary tuberculosis. (A) Intersection between lncRNAs in ceRNA network and differentially expressed lncRNAs. (B) Intersection between mRNAs in ceRNA network and differentially expressed mRNAs. (C) Intersection between miRNAs in ceRNA network and differentially expressed miRNAs. (D) Heatmap of DElncRs, DEmRs, and DEmiRs of ceRNA regulator network.
Figure 3
Figure 3
Enrichment of GO and KEGG pathways for DEmRs. (A) Classification of top 20 significant GO terms for DEmRs. (B) Enrichment of significant KEGG pathways for DEmRs. (C) The comprehensive ceRNA regulatory networks in PTB.
Figure 4
Figure 4
Molecular experiments validate significant analytical results. (A) Expression changes of genes in ceRNA regulatory networks in lesions and adjacent healthy lung tissues of patients with PTB through qRT-PCR detection and analyzed by Student’s t-test. *P < 0.05, **P < 0.01, ***P < 0.001. (B) The proportion change of Th1, Th2, and Th17 cells in patients with PTB and controls detected using flow cytometry.
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