Bioinformatics analysis of microRNA expression between patients with and without latent tuberculosis infections

miR-29 as diagnostic biomarkers for tuberculosis: a systematic review and meta-analysis

Background

The timely diagnosis of tuberculosis through innovative biomarkers that do not rely on sputum samples is a primary focus for strategies aimed at eradicating tuberculosis. miR-29 is an important regulator of tuberculosis pathogenesis. Its differential expression pattern in healthy, latent, and active people who develop tuberculosis has revealed its potential as a biomarker in recent studies. Therefore, a systematic review and meta-analysis were performed for the role of miR-29 in the diagnosis of tuberculosis.

Methods

EMBASE, PubMed, CNKI, Web of Science, and Cochrane Library databases were searched utilizing predefined keywords for literature published from 2000 to February 2024.Included in the analysis were studies reporting on the accuracy of miR-29 in the diagnosis of tuberculosis, while articles assessing other small RNAs were not considered. All types of study designs, including case-control, cross-sectional, and cohort studies, were included, whether prospectively or retrospectively sampled, and the quality of included studies was determined utilizing the QUADAS-2 tool. Publication bias was analyzed via the construction of funnel plots. Heterogeneity among studies and summary results for specificity, sensitivity, and diagnostic odds ratio (DOR) are depicted in forest plots.

Results

A total of 227 studies were acquired from the various databases, and 18 articles were selected for quantitative analysis. These articles encompassed a total of 2,825 subjects, primarily sourced from the Asian region. Patient specimens, including sputum, peripheral blood mononuclear cells, cerebrospinal fluid and serum/plasma samples, were collected upon admission and during hospitalization for tuberculosis testing. miR-29a had an overall sensitivity of 82% (95% CI 77, 85%) and an overall specificity of 82% (95% CI 78, 86%) for detecting tuberculosis. DOR was 21 (95% CI 16-28), and the area under the curve was 0.89 (95% CI 0.86, 0.91). miR-29a had slightly different diagnostic efficacy in different specimens. miR-29a showed good performance in both the diagnosis of pulmonary tuberculosis and extrapulmonary tuberculosis. miR-29b and miR-29c also had a good performance in diagnosis of tuberculosis.

Conclusion

As can be seen from the diagnostic performance of miR-29, miR-29 can be used as a potential biomarker for the rapid detection of tuberculosis.

Systematic Review Registration

https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=461107.

Identification of Hub Genes and Typing of Tuberculosis Infections Based on Autophagy-Related Genes

Tuberculosis (TB) caused by Mycobacterium tuberculosis 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 M. tuberculosis 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 M. tuberculosis 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 M. tuberculosis.

miR-576-5p Promotes the Proliferation of Papillary Thyroid Carcinoma through the MAPK4-AKT Pathway

Background

MicroRNA-576-5p (miR-576-5p) plays an important role in different human cancers. However, the biological function of miR-576-5p in papillary thyroid carcinoma (PTC) is still unclear. In this study, we explored the function and specific role of miR-576-5p in PTC.

Methods

Expression levels of miR-576-5p in PTC patient tissues and cell lines were determined by reverse transcription-quantitative polymerase chain reaction (qRT‒PCR). Cell counting using cell counting kit-8 (CCK-8), wound healing, and Transwell assays were performed to evaluate the effect of miR-576-5p on the proliferation, migration, and invasion of TPC-1 cells. Expression levels of mitogen-activated protein kinase 4 (MAPK4) and phosphorylation levels of protein kinase B (AKT), extracellular regulated protein kinase (ERK), and P38 mitogen-activated protein kinase (P38) were detected by western blotting or immunohistochemistry (IHC).

Results

The expression level of miR-576-5p in PTC tissues and TPC-1 cells was significantly increased. In vitro, overexpression of miR-576-5p promoted the proliferation, migration, and invasion of TPC-1 cells. In addition, MAPK4 was highly expressed in PTC tissues, and miR-576-5p could upregulate the expression of MAPK4. Interestingly, MAPK4 knockdown reversed cell proliferation but not migration and invasion in TPC-1 cells after miR-576-5p was overexpressed. Moreover, overexpression of miR-576-5p induced activation of the AKT pathway in TPC-1 cells, and MAPK4 gene knockout reversed this AKT pathway activation.

Conclusion

In this study, we found that miR-576-5p was significantly overexpressed in PTC tissues and TPC-1 cells. In addition, miR-576-5p promoted the proliferation of TPC-1 cells by enhancing expression of MAPK4 and activating the AKT pathway.

Benefits and Challenges of Pre-clustered Network-Based Pathway Analysis

Functional analysis of gene sets derived from experiments is typically done by pathway annotation. Although many algorithms exist for analyzing the association between a gene set and a pathway, an issue which is generally ignored is that gene sets often represent multiple pathways. In such cases an association to a pathway is weakened by the presence of genes associated with other pathways. A way to counteract this is to cluster the gene set into more homogenous parts before performing pathway analysis on each module. We explored whether network-based pre-clustering of a query gene set can improve pathway analysis. The methods MCL, Infomap, and MGclus were used to cluster the gene set projected onto the FunCoup network. We characterized how well these methods are able to detect individual pathways in multi-pathway gene sets, and applied each of the clustering methods in combination with four pathway analysis methods: Gene Enrichment Analysis, BinoX, NEAT, and ANUBIX. Using benchmarks constructed from the KEGG pathway database we found that clustering can be beneficial by increasing the sensitivity of pathway analysis methods and by providing deeper insights of biological mechanisms related to the phenotype under study. However, keeping a high specificity is a challenge. For ANUBIX, clustering caused a minor loss of specificity, while for BinoX and NEAT it caused an unacceptable loss of specificity. GEA had very low sensitivity both before and after clustering. The choice of clustering method only had a minor effect on the results. We show examples of this approach and conclude that clustering can improve overall pathway annotation performance, but should only be used if the used enrichment method has a low false positive rate.