Combining bioinformatics and machine learning to identify diagnostic biomarkers of TB associated with immune cell infiltration.

OBJECTIVE: The asymptomatic nature of tuberculosis (TB) during its latent phase, combined with limitations in current diagnostic methods, makes accurate diagnosis challenging. This study aims to identify TB diagnostic biomarkers by integrating gene expression screening with machine learning, evaluating their diagnostic potential and correlation with immune cell infiltration. METHODS: We analyzed GSE19435, GSE19444, and GSE54992 datasets to identify differentially expressed genes (DEGs). GO and KEGG enrichment characterized gene functions. Three machine learning algorithms identified potential biomarkers, validated with GSE83456, GSE62525, and RT-qPCR on clinical samples. Immune cell infiltration was analyzed and verified with blood data. RESULTS: 249 DEGs were identified, with PDE7A and DOK3 emerging as potential biomarkers. RT-qPCR confirmed their expression, showing AUCs above 0.75 and a combined AUC of 0.926 for TB diagnosis. Immune infiltration analysis revealed strong correlations between PDE7A, DOK3, and immune cells. CONCLUSION: PDE7A and DOK3 show strong diagnostic potential for TB, closely linked to immune cell infiltration, and may serve as promising biomarkers and therapeutic targets.

Prognostic risk model of LIHC T-cells based on scRNA-seq and RNA-seq and the regulation of the tumor immune microenvironment.

BACKGROUND: T-cell-related genes play a crucial role in LIHC development. However, a reliable prognostic profile based on risk models of these genes has yet to be identified. METHODS: Single-cell datasets from both tumor and normal tissue samples were obtained from the GEO database. We identified T-cell marker genes and developed a genetic risk model using the TCGA-LIHC dataset, which was subsequently validated with an independent GEO dataset. We also explored the relationship between risk model predictions and immune responses. RESULTS: We constructed a prognostic risk model using eight gene features identified through screening 860 T-cell marker genes via scRNA-seq and RNA-seq, which was subsequently integrated with the TCGA dataset. Its validity was independently confirmed using GEO and ICGC datasets. The TCGA dataset was stratified into high-risk and low-risk groups based on the risk model. Multivariate Cox regression analysis confirmed the risk score as an independent prognostic factor. GSEA indicated ribosomal transporter metabolism enrichment in the high-risk group and significant transcriptional activation in the low-risk group. ESTIMATE analysis showed higher ESTIMATE, immune, and stromal scores in the low-risk group, which also exhibited lower tumor purity than the high-risk group. Immunophenotyping revealed distinct patterns of immune cell infiltration and an immunosuppressive environment in the high-risk group. CONCLUSIONS: This study introduces a T-cell marker-based prognostic risk model for LIHC patients. This model effectively predicted survival outcomes and immunotherapy effectiveness in LIHC patients, aligning with diverse immune responses and the distinct immunological profiles observed in the high-risk group.

Effect and Mechanism of Mycobacterium avium MAV-5183 on Apoptosis of Mouse Ana-1 Macrophages.

To investigate the effects and mechanisms of Mycobacterium avium MAV-5183 protein on apoptosis in mouse Ana-1 macrophages. A pET-21a-MAV-5183 recombinant plasmid was constructed. The recombinant MAV-5183 protein was cloned, expressed, purified, and identified using an anti-His-tagged antibody. Rabbits were immunized to obtain antiserum, and its potency and immunoreactivity were assessed through WB. Mouse Ana-1 macrophages were incubated with varying concentrations of MAV-5183 protein. Flow cytometry, following ANNEXIN V-FITC/PI double staining, detected apoptosis. Western Blot analysis was conducted to identify apoptosis-related molecules Caspase-9/8/3 and vesicle-related molecules ASC, NLRP3, and Cleaved-casp1. ELISA measured TNF-α and IL-6 levels in the culture supernatant. LDH activity and ROS levels were analyzed separately. RT-qPCR measured mRNA levels of Caspase-9/8/3, ASC, NLRP3, Caspase-1, IL-1ß, Bax, MAPK-p38, Bcl-2, TNF-α, and IL-6. MAV-5183 protein was successfully cloned, purified, and identified. In in vitro studies on Ana-1 macrophages, MAV-5183 protein increased the expression of Caspase-9/8/3, ASC, NLRP3 (P < 0.01), induced ROS secretion (P < 0.05), and promoted inflammatory cytokine secretion (TNF-α, IL-6, P < 0.0001); however, it did not significantly affect LDH (P > 0.05). MAV-5183 also induced apoptosis in Ana-1 macrophages (P < 0.05). RT-qPCR results indicated a significant increase in mRNA expression of Caspase-9/8/3, ASC, NLRP3, TNF-α, IL-6, MAPK-p38, and pro-apoptotic factor Bax (P < 0.01), with no significant effect on Bcl-2 and IL-1ß mRNA (P > 0.05). The data indicate that MAV-5183 induces macrophage apoptosis through a caspase-dependent pathway and promotes inflammatory cytokine secretion via ROS.

NK-derived exosome miR-1249-3p inhibits Mycobacterium tuberculosis survival in macrophages by targeting SKOR1.

Murine Natural Killer cells were cultivated in vitro to isolate NK-derived exosomes. Subsequent quantification via qPCR confirmed enrichment of miR-1249-3p. Ana-1 murine macrophages were cultured in vitro and subsequently inoculated with Mycobacterium tuberculosis (MTB) strain H37Rv. NK-exo and NK-exo miR-1249-3p were separately applied to the infection model, followed by immunological assays conducted post-48-hour co-culture. Western blot analyses corroborated that NK-exo exhibited exosomal marker proteins Granzyme A (GzmA), Granzyme B (GzmB), and Perforin (PFN), alongside a notable enrichment of miR-1249-3p. Functionally, NK-exo augmented the expression levels of Caspase-9,-8, and -3, as well as PARP, while attenuating the expression of NLRP3, ASC, and Cleaved-Caspase-1. Furthermore, qPCR demonstrated an up-regulation of Caspase-9, -8, and -3, along with pro-apoptotic factors Bax and Bid, and a concomitant down-regulation of the anti-apoptotic factor Bcl-2. The expression levels of inflammatory markers ASC, NLRP3, Cleaved-Caspase-1, and IL-1ß were concomitantly decreased. ELISA findings indicated diminished levels of TNF-α and ROS secretion. NK-exo miR-1249-3p specifically targeted and attenuated the expression of SKOR-1, engendering up-regulation of apoptosis-associated proteins and down-regulation of inflammation-related proteins, consequently affecting cellular fate.Our empirical evidence substantiates that NK-exo induces macrophage apoptosis, thereby mitigating MTB survival. Furthermore, NK-exo miR-1249-3p directly targets and inhibits SKOR-1 expression, leading to macrophage apoptosis and consequently hampering the proliferation of MTB. The data implicate the potential therapeutic relevance of NK-exo and miR-1249-3p in managing drug-resistant tuberculosis.