Research Article

Mahnoor Sajjad, Pirlepesov Daniyar Maratovich, Onaiba Khan

Published on : December 2025 | Volume : 2 Issue : 2

Abstract :

Tuberculosis (TB), caused by Mycobacterium tuberculosis, remains a major global health problem. Early diagnosis and effective treatment are still difficult due to complex host–pathogen interactions and increasing drug resistance. Identifying host gene expression biomarkers can help improve diagnosis and support the development of new therapeutic strategies. In this study, we performed an integrated bioinformatics analysis to identify key genes, pathways, and regulatory networks associated with TB infection. Gene expression microarray datasets GSE11199 (Affymetrix Human Genome U133 Plus 2.0 Array) and GSE34608 (Illumina HumanHT-12 V4.0 BeadChip) were obtained from the Gene Expression Omnibus (GEO) database. Differential gene expression analysis was performed using GEO2R based on the limma statistical method. Initial screening identified 1,608 candidate differentially expressed genes (DEGs) in GSE11199 and 2,214 candidate DEGs in GSE34608. After applying stringent statistical filtering criteria (adjusted p-value < 0.05 and quality control filtering), 115 significant DEGs from GSE11199 were retained for downstream analysis. GSE34608 was used for comparative biological interpretation but showed limited statistically significant genes under strict thresholds. Functional enrichment analysis was performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Protein–protein interaction (PPI) networks were constructed using STRING and visualized using Cytoscape to identify hub genes. Transcription factor and microRNA regulatory networks were also analyzed. Drug–gene interaction analysis was performed using DGIdb, and molecular docking validation was conducted using AutoDock Vina. Key immune-related genes identified included CCL1, CXCL10, GBP5, and IFITM3. Hub genes in the PPI network included IRF7, ISG15, and STAT1. Enrichment analysis showed strong involvement of interferon signaling, cytokine signaling, proteasome activity, and immune response pathways. Several candidate drug molecules showed strong predicted binding affinity with target proteins. These findings improve understanding of host immune mechanisms during TB infection. The identified genes and pathways may serve as potential diagnostic biomarkers and therapeutic targets. This study provides a systems-level view of host immune responses in TB and supports future development of host-directed therapies.