Aphthous stomatitis - computational biology suggests external biotic stimulus and immunogenic cell death involved

Abstract

Background: The exact cause of recurrent aphthous stomatitis is still unknown, making it a challenge to develop effective treatments. This study employs computational biology to investigate the molecular basis of recurrent aphthous stomatitis, aiming to identify the nature of the stimuli triggering these ulcers and the type of cell death involved.

Methods: To understand the molecular underpinnings of recurrent aphthous stomatitis, we used the Génie tool for gene identification, targeting those associated with cell death in recurrent aphthous stomatitis. The ToppGene Suite was employed for functional enrichment analysis. We also used Reactome and InteractiVenn for protein integration and prioritization against a PANoptosis gene list, enabling the construction of a protein-protein interaction network to pinpoint key proteins in recurrent aphthous stomatitis pathogenesis.

Results: The study's computational approach identified 1,375 protein-coding genes linked to recurrent aphthous stomatitis. Critical among these were proteins responsive to bacterial stimuli, especially high mobility group protein B1 (HMGB1), toll-like receptor 2 (TLR2), and toll-like receptor 4 (TLR4). The enrichment analysis suggested an external biotic factor, likely bacterial, as a triggering agent in recurrent aphthous stomatitis. The protein interaction network highlighted the roles of tumor necrosis factor (TNF), NF-kappa-B essential modulator (IKBKG), and tumor necrosis factor receptor superfamily member 1A (TNFRSF1A), indicating an immunogenic cell death mechanism, potentially PANoptosis, in recurrent aphthous stomatitis.

Conclusion: The findings propose that bacterial stimuli could trigger recurrent aphthous stomatitis through a PANoptosis-related cell death pathway. This new understanding of recurrent aphthous stomatitis pathogenesis underscores the significance of oral microbiota in the condition. Future experimental validation and therapeutic strategy development based on these findings are necessary.

Keywords: Aphthous stomatitis; Bacterial infections; Cell death; Computational biology; Immunogenic cell death.

Fig. 1

Comprehensive computational pipeline to elucidate stimulus nature and cell death mechanism in recurrent aphthous stomatitis. This figure outlines our step-by-step approach to studying recurrent aphthous stomatitis, starting with the Génie web server that ranks protein-coding genes associated with cell death in this condition. We then used ToppGene to characterize these genes based on gene ontology, which helped identify potential stimuli that trigger ulcer formation. Reactome further allowed us to examine specific types of cell death, improving our understanding of how these stimuli affect oral mucosa keratinocytes. Finally, using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database and the Integrated Value of Influence (IVI) application, we built a protein interaction network that revealed key proteins involved in the disease’s pathology. Alongside these tools, PubMed identifiers (PMIDs) provide unique reference numbers for tracking scientific articles, while the ToppGene Suite offers extensive capabilities for gene list analysis and prioritization. Voronoi diagrams show us how biological patterns can emerge, and Reactome aids in the visualization and analysis of complex biological pathways. The InteractiVenn tool allows for straightforward analysis of element lists using Venn diagrams, enhancing our grasp of data intersections. Protein-protein interaction maps give insight into how proteins interact within a cell, essential for understanding cellular functions and the impact of disruptions on disease. The STRING database compiles a wide array of protein interactions from experimental and predictive data, and the IVI app identifies the most influential nodes in our network, highlighting critical targets for potential therapy. This array of sophisticated tools and databases enables a detailed exploration of the molecular dynamics involved in recurrent aphthous stomatitis, offering insights into its underlying mechanisms and potential treatments

Fig. 2

Insight into programmed cell death in recurrent aphthous stomatitis through computational biology. This figure provides a view into how programmed cell death, including regulated necrosis, pyroptosis, and apoptosis, plays a role in recurrent aphthous stomatitis. (A) Through Reactome, a Voronoi diagram analysis reveals a notable overrepresentation of these cell death processes. (B) Additionally, an independent dataset analysis points to a significant involvement of proteins associated with external biotic stimuli, primarily those engaged in pyroptosis, apoptosis, and necroptosis, collectively known as PANoptosis. (C) We further constructed an interaction network that integrates proteins common to both the Génie and PANoptosis datasets (n = 150), uncovering a robust interactome with verifiable biological connectivity, evidenced by a significant protein-protein interaction (PPI) enrichment p-value. Prominent proteins within this network include TNF (tumor necrosis factor, Uniprot ID: P01375), IKBKG (NF-kappa-B essential modulator, Uniprot ID: Q9Y6K9), and TNFRSF1A (tumor necrosis factor receptor superfamily member 1A, Uniprot ID: P19438). The Uniprot IDs or primary (citable) accession numbers are stable identifiers for proteins. For a more detailed view, the original network is available at the STRING database https://string-db.org/cgi/network?taskId=bfq6HqRrmUrE&sessionId=bIODrGwGklyC