Differential gene expression in HaCaT cells may account for the various clinical presentation caused by anthropophilic and geophilic dermatophytes infections

Abstract

Summary Background Despite the worldwide prevalence of dermatophyte infections, only a few genes are reported to be related to dermatophyte infections. In addition, the mechanism by which different ecological dermatophytes infection leads to varying intensity of inflammation remains unclear. Objectives To investigate the mechanism of varying intensity of skin inflammation caused by different ecological dermatophytes infection. Methods We infected HaCaT cells with anthropophilic and geophilic dermatophytes to mimic various ecological dermatophyte infections. RNA‐sequencing (RNA‐seq) was employed to identify the change in the gene expression of HaCaT cells. To verify the expression of differentially expressed genes (DEGs), we selected 18 HaCaT cells genes to conduct qPCR experiments. In addition, immunoblotting was conducted to validate key genes from the MAPK signalling pathway. Results After HaCaT cells were infected with the anthropophilic Trichophyton rubrum (T rubrum) and the geophilic Microsporum gypseum (M gypseum), 118 and 619 differentially expressed genes were identified in HaCaT cells, respectively. These genes may provide a clue as to how keratinocytes respond to anthropophilic and geophilic dermatophytes. We also found that JUN may play a critical role in keratinocytes infected with M gypseum. Conclusions Differential gene expression in HaCaT cells may account for the various clinical presentation caused by anthropophilic and geophilic dermatophytes infections. In addition, the intense inflammatory reaction of M gypseum infection may be triggered by activating the JNK‐JUN signalling pathway.

Immunopathogenesis of Dermatophytoses and Factors Leading to Recalcitrant Infections

“…[ 37 ] Another recent study conducted to distinguish the change in the gene expression of HaCaT (Cultured human keratinocyte) cell line following dermatophytic infection found that pro-inflammatory cytokines and chemokines triggered the infiltration of neutrophils and other immune cell to the infection site following zoophilic M gypseum infection due to the upregulated expression of genes related to immune response, while with T rubrum, metabolic pathway genes were upregulated instead immune response-related genes. [ 38 ] This corroborates with the clinical observations that in acute infections provoked by the zoophilic fungi T. mentagrophytes and M. gypseum, marked neutrophils are seen in the epidermis, whereas T. rubrum lead to chronic infections and are characterized by a mononuclear infiltrate. [ 11 ] Trichophyton-induced inflammation causes the proliferation of peripheral blood mononuclear cells (PBMC) and the production of IFN- γ and IFN- γ -positive CD4+ cells leading to a Th1 response[ 39 40 ] [ Figure 1 ].…”

Discovery of New Trichophyton Members, T. persicum and T. spiraliforme spp. nov., as a Cause of Highly Inflammatory Tinea Cases in Iran and Czechia

“…Because dermatophytosis is not a life-threatening infection and its health impact can be relatively low, it represents a rather neglected infection in many regions. The infections with mild or moderate symptoms and chronic course are mostly caused by anthropophilic dermatophytes, which are typically localized to body areas that have higher moisture levels or are less accessible for the host immune response, e.g., skin folds, feet, and nails ( 2 – 4 ). On the other hand, zoophilic dermatophytes, when transmitted to a human, usually cause highly inflammatory infections located in sites directly exposed to contact with an infected animal, typically the extremities, face, and trunk ( 5 , 6 ).…”

Polyopes affinis Suppressed IFN-γ- and TNF-α-Induced Inflammation in Human Keratinocytes via Down-Regulation of the NF-κB and STAT1 Pathways

“…Here, the definition of a contra-regulated gene is an average gene that increases by IFN-γ and TNF-α treatment and decreases by PAB compared to the control, i.e., showing the opposite trend. To identify the functional changes in DEGs, a gene-ontology (GO) analysis was performed using ExDEGA software (E-Biogen Inc. Seoul, Korea) [ 18 , 19 , 20 ]. In this study, the GO categories were divided into 15 functional groups ( Figure 4 B).…”