Identification of unique key genes and miRNAs in latent tuberculosis infection by network analysis.

Affiliation

Department of Pathogenobiology, The Key Laboratory of Zoonosis, Chinese Ministry of Education, College of Basic Medicine, Jilin University, Changchun, Jilin, 130021, China; The Key Laboratory for Bionics Engineering, Ministry of Education, China, Jilin University, Changchun, Jilin, 130021, China; Engineering Research Center for Medical Biomaterials of Jilin Province, Jilin University, Changchun, Jilin, 130021, China; Key Laboratory for Biomedical Materials of Jilin Province, Jilin University, Changchun, Jilin, 130021, China; State Key Laboratory of Pathogenesis, Prevention and Treatment of High Incidence Diseases in Central Asia, Xinjiang, China. Electronic address: [Email]

Abstract

Tuberculosis (TB) is a chronic infectious disease caused by Mycobacterium tuberculosis (M.tb). New cases are now mainly caused by the progression of latent tuberculosis infection (LTBI). Thus, methods to diagnose and treat LTBI are urgently needed to prevent the development of active TB in infected individuals and the subsequent spread of the disease. In this study, a systems biology approach was utilized to obtain numerous microarray data sets for mRNAs and microRNAs (miRNAs) expressed in the peripheral blood mononuclear cells (PBMCs) of TB patients and individuals with LTBI. Within these data sets, we identified the differentially expressed mRNAs and miRNAs and further investigated which differentially expressed genes and miRNAs were uniquely expressed during LTBI. The Database for Annotation, Visualization and Integrated Discovery (DAVID) was employed to analyze the functional annotations and pathway classifications of the identified genes. To further understand the unique miRNA-gene regulatory network of LTBI, we constructed a protein-protein interaction (PPI) network for the targeted genes. The PPI network included 39 genes that were differentially and uniquely expressed in PBMCs of individuals with LTBI, and KEGG pathway enrichment analysis showed that these genes were predominantly involved in the PI3K-Akt signaling pathway, which plays an important role in chronic inflammation. DIANA TOOLs-mirPath analysis revealed that the identified miRNAs in the miRNA-gene regulatory network for LTBI were mainly associated with the Hippo signaling pathway, which functions in the development of inflammation. Quantitative real-time PCR verified the up expression of hsa-miR-212-3p and its predicted target gene -MAPK1 which had low expression and was a major component of the PPI network, and MAPK1 expression was correlated with the clinicopathological characteristics of LTBI by receiver operating characteristic (ROC) curve analysis. Therefore, MAPK1 has potential to be a new investigable marker during LTBI, which merits our further study and solution. The unique aberrant miRNA-gene regulatory network and the related PPI network identified in this study provide insight into the molecular mechanisms of the immune response to LTBI, and thus, may aid in the development of a novel treatment strategy.

Keywords

Latent tuberculosis infection (LTBI),Marker,Microarray data,PPI Network,miRNA–Gene network,

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