Effect of Dermaseptin S4 on C. albicans Growth and EAP1 and HWP1 Gene Expression.
Johan SamotMahmoud RouabhiaPublished in: Probiotics and antimicrobial proteins (2021)
Increasing resistance and changes in the spectrum of Candida infections have generated considerable interest in the development of new antifungal molecules. The use of antimicrobial peptides (AMPs) appears to be a promising approach. Frog skin AMPs (such as dermaseptins) have shown antimicrobial activity against several pathogens. In this study, we aimed to test the antimicrobial efficacy of dermaseptin S4 (DS4) against C. albicans. We determined the minimal inhibitory concentration (MIC) of DS4, and investigated the effects of the DS4 at low concentrations on human primary gingival fibroblasts. Additionally, we evaluated the effect of DS4 on C. albicans growth, form changes, and biofilm formation, as well as the expression of certain virulent genes. Our data show that DS4 completely inhibits C. albicans growth at a concentration of 32 μg/mL referring to the MIC of DS4. It should be noted that even with low concentrations (below 16 μg/mL), DS4 still have significant growth reduction of C. albicans, but were not toxic to human gingival fibroblasts. DS4 inhibited the transition from yeast to hyphae, and decreased the biofilm formation by reducing the biofilm mass weight. Surface morphological changes in the yeast cell membrane were observed following exposure to DS4. The gene expression analyses revealed that DS4 significantly decreased the expression of EAP1 and HWP1 genes. Overall results suggest the potential use of DS4 as an antifungal therapy to prevent C. albicans pathogenesis.
Keyphrases
- candida albicans
- biofilm formation
- gene expression
- pseudomonas aeruginosa
- staphylococcus aureus
- endothelial cells
- poor prognosis
- escherichia coli
- dna methylation
- genome wide
- body mass index
- single cell
- long non coding rna
- big data
- gram negative
- extracellular matrix
- physical activity
- weight loss
- mass spectrometry
- artificial intelligence
- antimicrobial resistance
- wound healing
- soft tissue
- deep learning
- climate change