Invasive fungal infections are a significant reason for morbidity and mortality among organ transplant recipients. Therefore, it is critical to investigate the host and candida niches to understand the epidemiology of fungal infections in transplantation. Candida albicans is an opportunistic fungal pathogen that causes fatal invasive mucosal infections, particularly in solid organ transplant patients. Therefore, identifying and characterizing these genes would play a vital role in understanding the complex regulation of host-pathogen interactions. Using 32 RNA-sequencing samples of human cells infected with C. albicans, we developed WGCNA coexpression networks and performed DESeq2 differential gene expression analysis to identify the genes that positively correlate with human candida infection. Using hierarchical clustering, we identified 5 distinct modules. We studied the inter- and intramodular gene network properties in the context of sample status traits and identified the highly enriched genes in the correlated modules. We identified 52 genes that were common in the most significant WGCNA turquoise module and differentially expressed genes in human endothelial cells (HUVEC) infection vs. control samples. As a validation step, we identified the differentially expressed genes from the independent Candida-infected human oral keratinocytes (OKF6) samples and validated 30 of the 52 common genes. We then performed the functional enrichment analysis using KEGG and GO. Finally, we performed protein-protein interaction (PPI) analysis using STRING and CytoHubba from 30 validated genes. We identified 8 hub genes (JUN, ATF3, VEGFA, SLC2A1, HK2, PTGS2, PFKFB3, and KLF6) that were enriched in response to hypoxia, angiogenesis, vasculogenesis, hypoxia-induced signaling, cancer, diabetes, and transplant-related disease pathways. The discovery of genes and functional pathways related to the immune system and gene coexpression and differential gene expression analyses may serve as novel diagnostic markers and potential therapeutic targets.
Endothelial and epithelial cells are morphologically different and play a critical role in host defense during Candida albicans infection. Both cells respond to C. albicans infection by activating various signaling pathways and gene expression patterns. Their interactions with these pathogens can have beneficial and detrimental effects, and a better understanding of these interactions can help guide the development of new therapies for C. albicans infection. To identify the differences and similarities between human endothelial and oral epithelial cell transcriptomics during C. albicans infection, we performed consensus WGCNA on 32 RNA-seq samples by relating the consensus modules to endothelial-specific modules and analyzing the genes connected. This analysis resulted in the identification of 14 distinct modules. We demonstrated that the magenta module correlates significantly with C. albicans infection in each dataset. In addition, we found that the blue and cyan modules in the two datasets had opposite correlation coefficients with a C. albicans infection. However, the correlation coefficients and p-values between the two datasets were slightly different. Functional analyses of the hub of genes from endothelial cells elucidated the enrichment in TNF, AGE-RAGE, MAPK, and NF-κB signaling. On the other hand, glycolysis, pyruvate metabolism, amino acid, fructose, mannose, and vitamin B6 metabolism were enriched in epithelial cells. However, mitophagy, necroptosis, apoptotic processes, and hypoxia were enriched in both endothelial and epithelial cells. Protein–protein interaction analysis using STRING and CytoHubba revealed STAT3, SNRPE, BIRC2, and NFKB2 as endothelial hub genes, while RRS1, SURF6, HK2, and LDHA genes were identified in epithelial cells. Understanding these similarities and differences may provide new insights into the pathogenesis of C. albicans infections and the development of new therapeutic targets and interventional strategies.
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