Department of Tuberculosis, Affiliated Hangzhou Chest Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Pol J Microbiol. 2023 Sep 20;72(3):223-238. doi: 10.33073/pjm-2023-022. eCollection 2023 Sep 1.
Tuberculosis (TB) caused by is one of the leading causes of morbidity and death in humans worldwide. Some autophagy genes associated with TB and some miRNAs regulating TB have been found, but the identification of autophagy-related genes in remains to be explored. Forty-seven autophagy-related genes differentially expressed in TB were identified in this study by analysis of TB-related datasets in the Gene Expression Omnibus (GEO) and autophagy-related genes in the Human Autophagy Database. The potential crucial genes affecting TB were found through the protein-protein interaction (PPI) network, and the possible pathways affected by these genes were verified. Analysis of the PPI network of miRNAs associated with infection and their target genes revealed that hsa-let-7, hsa-mir-155, hsa-mir-206, hsa-mir-26a, hsa-mir-30a, and hsa-mir-32 may regulate the expression of multiple autophagy-related genes (MAPK8, UVRAG, UKL2, and GABARAPL1) alone or in combination. Subsequently, Cytoscape was utilized to screen the differentially expressed genes related to autophagy. The hub genes (GABARAPL1 and ULK2) affecting TB were identified. Combined with Gene Set Enrichment Analysis (GSEA), the signaling pathways affected by the hub genes were verified. Finally, we divided TB patients into two subgroups based on autophagy-related genes, and the immune microenvironment of patients in different subgroups was significantly different. Our study found two autophagy-related hub genes that could affect TB and divide TB samples into two subgroups. This finding is of great significance for TB treatment and provides new ideas for exploring the pathogenesis of .
由 引起的结核病(TB)是全球导致发病率和死亡率的主要原因之一。已经发现了一些与 TB 相关的自噬基因和一些调节 TB 的 miRNAs,但 在 中的自噬相关基因的鉴定仍有待探索。本研究通过分析基因表达综合数据库(GEO)中与 TB 相关的数据集和人类自噬数据库中的自噬相关基因,鉴定出 47 个在 TB 中差异表达的自噬相关基因。通过蛋白质-蛋白质相互作用(PPI)网络发现了影响 TB 的潜在关键基因,并验证了这些基因可能影响的途径。分析与 感染相关的 miRNAs 及其靶基因的 PPI 网络表明,hsa-let-7、hsa-mir-155、hsa-mir-206、hsa-mir-26a、hsa-mir-30a 和 hsa-mir-32 可能单独或组合调节多个自噬相关基因(MAPK8、UVRAG、UKL2 和 GABARAPL1)的表达。随后,利用 Cytoscape 筛选与自噬相关的差异表达基因。确定了影响 TB 的枢纽基因(GABARAPL1 和 ULK2)。结合基因集富集分析(GSEA),验证了枢纽基因影响的信号通路。最后,我们根据自噬相关基因将 TB 患者分为两组,不同亚组患者的免疫微环境存在显著差异。我们的研究发现了两个可能影响 TB 并将 TB 样本分为两组的自噬相关枢纽基因。这一发现对 TB 的治疗具有重要意义,并为探索 的发病机制提供了新的思路。