Identification of genetic biomarkers, drug targets and agents for respiratory diseases utilising integrated bioinformatics approaches

Comprehensive Review on the Virulence Factors and Therapeutic Strategies with the Aid of Artificial Intelligence against Mucormycosis

Mucormycosis, a rare but deadly fungal infection, was an epidemic during the COVID-19 pandemic. The rise in cases (COVID-19-associated mucormycosis, CAM) is attributed to excessive steroid and antibiotic use, poor hospital hygiene, and crowded settings. Major contributing factors include diabetes and weakened immune systems. The main manifesting forms of CAM─cutaneous, pulmonary, and the deadliest, rhinocerebral─and disseminated infections elevated mortality rates to 85%. Recent focus lies on small-molecule inhibitors due to their advantages over standard treatments like surgery and liposomal amphotericin B (which carry several long-term adverse effects), offering potential central nervous system penetration, diverse targets, and simpler dosing owing to their small size, rendering the ability to traverse the blood-brain barrier via passive diffusion facilitated by the phospholipid membrane. Adaptation and versatility in mucormycosis are facilitated by a multitude of virulence factors, enabling the pathogen to dynamically respond to various environmental stressors. A comprehensive understanding of these virulence mechanisms is imperative for devising effective therapeutic interventions against this highly opportunistic pathogen that thrives in immunocompromised individuals through its angio-invasive nature. Hence, this Review delineates the principal virulence factors of mucormycosis, the mechanisms it employs to persist in challenging host environments, and the current progress in developing small-molecule inhibitors against them.

Transcriptomic Analysis of Tight Junction Proteins Demonstrates the Aberrant Expression and Function of Zona Occludens 2 (ZO-2) Protein in Stanford Type A Aortic Dissection

OBJECTIVE

Thoracic aortic aneurysm dissection (TAAD) represents a cardiac surgery emergency characterized by the disrupted integrity of the aortic wall and is associated with poor prognosis. In this context, the identification of biomarkers implicated in the pathobiology of TAAD is crucial. Our aim in the present original in silico study is to assess the differential gene expression profile of the tight junction proteins (TJPs) in patients with TAAD and to propose novel biomarkers for the diagnosis and prognosis of this disease.

METHODS

We implemented bioinformatics methodology in order to construct the gene network of the TJPs family, identify the differentially expressed genes (DEGs) in pathologic aortic tissue excised from patients with TAAD as compared to healthy aortic tissue, and assess the related biological functions and the associated miRNA families.

RESULTS

Data regarding the transcriptomic profile of selected genes were retrieved and incorporated from three microarray datasets, including 23 TAAD and 20 healthy control samples. A total of 32 TJPs were assessed. The zona occludens 2 (ZO-2) protein encoded by the gene TJP2 was significantly under-expressed in patients with TAAD compared to the control group (p = 0.009). ZO-2 was associated with fair discrimination and calibration traits in predicting the TAAD presentation. CpG islands of ZO-2 were demonstrated. No important difference was found regarding ZO-2 expression between aneurysmal non-dissected and healthy control aortic tissue. Finally, we performed gene set enrichment analysis (GSEA) and uncovered the major biological functions and miRNA families (hsa-miR-155-5p, hsa-miR-1-3p, hsa-miR-2118-5p, hsa-miR-4691-3p, and hsa-miR-1229-3p) relevant to ZO-2.

CONCLUSIONS

These outcomes demonstrated the important role of ZO-2 in the pathobiology of TAAD.