Bioinformatics and functional analysis of key genes and pathways in tuberculosis_West China Medical Journal

Authors：

WU Qian , SONG Xingbo , ZHONG Huiyu , WEN Yang ,  YING Binwu

Department of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, P. R. China;

Corresponding author：

YING Binwu, Email: docbwy@126.com

Keywords：

Bioinformatics; Tuberculosis; Gene Expression Omnibus database; National Center for Biotechnology Information

DOI：

10.7507/1002-0179.201907081

Video：

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Objective To explore the pathogenesis of tuberculosis and provide new ideas for its early diagnosis and treatment.Methods GSE54992 gene expression profile was obtained from the gene expression database. Differentially expressed genes (DEGs) were screened using National Center forBiotechnology Information platform, and GO enrichment analysis, pathway analysis, pathway network analysis, gene network analysis, and co-expression analysis were performed to analyze the DEGs.Results Compared with the control group, a total of 3 492 genes were differentially expressed in tuberculosis. Among them, 1 686 genes were up-regulated and 1 806 genes were down-regulated. DEGs mainly involved small molecule metabolic processes, signal transduction, immune response, inflammatory response, and innate immune response. Pathway analysis revealed chemokine signaling pathway, tuberculosis, NF-Kappa B signaling pathway, cytokine-cytokine receptor interaction, and so on; gene signal network analysis found that the core genes were AKT3, PLCB1, MAPK8, and NFKB1; co-expression network analysis speculated that the core genes were PYCARD, TNFSF13, PHPT1, COMT, and GSTK1.Conclusions AKT3, PYCARD, IRG1, CD36 and other genes and their related biological processes may be important participants in the occurrence and development of tuberculosis. Bioinformatics can help us to comprehensively study the mechanism of disease occurrence, which can provide potential targets for the diagnosis and treatment of tuberculosis.

Citation： WU Qian, SONG Xingbo, ZHONG Huiyu, WEN Yang, YING Binwu. Bioinformatics and functional analysis of key genes and pathways in tuberculosis. West China Medical Journal, 2019, 34(9): 1033-1041. doi: 10.7507/1002-0179.201907081 Copy

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1. World Health Organization. Global tuberculosis report 2018. (2018-09-18)[2019-07-01]. https://www.who.int/tb/publications/global_report/en/.
2. Abel L, Fellay J, Haas DW, et al. Genetics of human susceptibility to active and latent tuberculosis: present knowledge and future perspectives. Lancet Infect Dis, 2018, 18(3): e64-e75.
3. Vasava MS, Bnoi MN, Rathwa SK, et al. Drug development against tuberculosis: past, present and future. Indian J Tuberc, 2017, 64(4): 252-275.
4. Eshiwe C, Shahi F, Gordon N, et al. Rare and unusual case of hepatic and disseminated tuberculosis in an immunocompetent patient. BMJ Case Rep, 2019, 12(6): pii: e229384.
5. Hmama Z, Peña-Díaz S, Joseph S, et al. Immunoevasion and immunosuppression of the macrophage by Mycobacterium tuberculosis. Immunol Rev, 2015, 264(1): 220-232.
6. Cai Y, Yang Q, Tang Y, et al. Increased complement C1q level marks active disease in human tuberculosis. PLoS One, 2014, 9(3): e92340.
7. Ezzie ME, Crawford M, Cho JH, et al. Gene expression networks in COPD: microRNA and mRNA regulation. Thorax, 2012, 67(2): 122-131.
8. Liu Y, Xin ZZ, Zhang DZ, et al. Transcriptome analysis of yellow catfish (Pelteobagrus fulvidraco) liver challenged with polyriboinosinic polyribocytidylic acid (poly I:C). Fish Shellfish Immunol, 2017, 68: 395-403.
9. Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Statist Soc, 1995, 57(1): 289-300.
10. Yi M, Horton JD, Cohen JC, et al. Whole pathway scope: a comprehensive pathway-based analysis tool for high-throughput data. BMC Bioinformatics, 2006, 7: 30.
11. Huang H, Zheng J, Shen N, et al. Identification of pathways and genes associated with synovitis in osteoarthritis using bioinformatics analyses. Sci Rep, 2018, 8(1): 10050.
12. Hill AV. The genomics and genetics of human infectious disease susceptibility. Ann Rev Genomics Hum Genet, 2001, 2: 373-400.
13. Casanova JL, Abel L. Genetic dissection of immunity to mycobacteria: the human model. Annu Rev Immunol, 2002, 20: 581-620.
14. Kallmann FJ, Reisner D. Twin studies on the significance of genetic factors in tuberculosis. Am Rev Tuberc, 1943, 47(6): 549-571.
15. Newport MJ, Goetghebuer T, Weis HA, et al. Genetic regulation of immune responses to vaccines in early life. Genes Immun, 2004, 5(2): 122-129.
16. Jepson A, Fowler A, Banya W, et al. Genetic regulation of acquired immune responses to antigens of Mycobacterium tuberculosis: a study of twins in West Africa. Infect Immun, 2001, 69(6): 3989-3994.
17. Crevel R, Ottenhoff TH, van der Meer JW. Innate immunity to Mycobacterium tuberculosis. Clin Microbiol Rev, 2002, 15(2): 294-309.
18. Silverstein RL, Febbraio M. CD36, a scavenger receptor involved in immunity, metabolism, angiogenesis, and behavior. Sci Signal, 2009, 2(72): re3.
19. Li C, Zhou Y, Xiang X, et al. The relationship of HLA-DQ alleles with tuberculosis risk: a meta-analysis. Lung, 2015, 193(4): 521-530.
20. Nair S, Huynh JP, Lampropoulou V, et al. Irg1 expression in myeloid cells prevents immunopathology during M. tuberculosis infection. J Exp Med, 2018, 215(4): 1035-1045.
21. Ma Y, Pang Y, Shu W, et al. Metformin reduces the relapse rate of tuberculosis patients with diabetes mellitus: experiences from 3-year follow-up. Eur J Clin Microbiol Infect Dis, 2018, 37(7): 1259-1263.
22. Brodbeck D, Cron P, Hemmings BA. A human protein kinase Bgamma with regulatory phosphorylation sites in the activation loop and in the C-terminal hydrophobic domain. J Biol Chem, 1999, 274(14): 9133-9136.
23. Manning BD, Cantley LC. AKT/PKB signaling: navigating downstream. Cell, 2007, 129(7): 1261-1274.
24. Yang ZZ, Tschoop O, Hemmings-Mieszczak M, et al. Protein kinase B alpha/Akt1 regulates placental development and fetal growth. J boil Chem, 2003, 278(34): 32124-32131.
25. Wang L, Huang D, Jiang Z, et al. Akt3 is responsible for the survival and proliferation of embryonic stem cells. Biol Open, 2017, 6(6): 850-861.
26. McElvania Tekippe E, Allen IC, Hulseberg PD, et al. Granuloma formation and host defense in chronic Mycobacterium tuberculosis infection requires PYCARD/ASC but not NLRP3 or caspase-1. PLoS One, 2010, 5(8): e12320.

West China Medical Journal

Bioinformatics and functional analysis of key genes and pathways in tuberculosis

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