Epidermal barrier impairment predisposes for excessive growth of the allergy‐associated yeast Malassezia on murine skin

Abstract

BackgroundThe skin barrier is vital for protection against environmental threats including insults caused by skin‐resident microbes. Dysregulation of this barrier is a hallmark of atopic dermatitis (AD) and ichthyosis, with variable consequences for host immune control of colonizing commensals and opportunistic pathogens. While Malassezia is the most abundant commensal fungus of the skin, little is known about the host control of this fungus in inflammatory skin diseases.MethodsIn this experimental study, MC903‐treated mice were colonized with Malassezia spp. to assess the host–fungal interactions in atopic dermatitis. Additional murine models of AD and ichthyosis, including tape stripping, K5‐Nrf2 overexpression and flaky tail mice, were employed to confirm and expand the findings. Skin fungal counts were enumerated. High parameter flow cytometry was used to characterize the antifungal response in the AD‐like skin. Structural and functional alterations in the skin barrier were determined by histology and transcriptomics of bulk skin. Finally, differential expression of metabolic genes in Malassezia in atopic and control skin was quantified.ResultsMalassezia grows excessively in AD‐like skin. Fungal overgrowth could, however, not be explained by the altered immune status of the atopic skin. Instead, we found that by upregulating key metabolic genes in the altered cutaneous niche, Malassezia acquired enhanced fitness to efficiently colonise the impaired skin barrier.ConclusionsThis study provides evidence that structural and metabolic changes in the dysfunctional epidermal barrier environment provide increased accessibility and an altered lipid profile, to which the lipid‐dependent yeast adapts for enhanced nutrient assimilation. Our findings reveal fundamental insights into the implication of the mycobiota in the pathogenesis of common skin barrier disorders.

Malassezia responds to environmental pH signals through the conserved Rim/Pal pathway

“…Atopy-like conditions were induced by repeated administration of the vitamin D analogue MC903 to the murine skin prior to fungal association [39]. WT M. sympodialis robustly colonized the murine skin by day 4 post-infection, with higher loads in the atopic dermatitis-like skin than in control skin, as previously shown [38] (Figure 5A). Importantly, under high pH, but not low pH conditions, colonization levels of both, the rim101∆ [KPY34] and rra1∆ [KPY36] mutants were reduced compared to those of the WT control strain, although differences did not reach statistical significance (Figure 5A).…”

“…All experiments were conducted at the Laboratory Animal Science Center of the University of Zurich under specific pathogen-free conditions. AD-like conditions were induced in the murine ear skin according to Moosbrugger-Martiz et al [37] and Ruchti et al [38]. Briefly, 1.125 nm of MC903 (calcipotriol hydrate, Sigma) diluted in pure ethanol was applied on the dorsal and ventral side of both ears for 5 consecutive days and again for 4 days after a resting period of 2 days.…”

“…After infection, MC903 treatment was continued on day 2 p.i. (for the 4 days infection experiment) or daily from day 2 to 5 (for the 7 days infection experiment) on the ventral side of the ear only to avoid interference of the EtOH solvent with fungal viability [38]. Ear thickness was continuously monitored using the Oditest S0247 0-5 mm measurement device (Kroeplin).…”

Card9 and MyD88 differentially regulate Th17 immunity to the commensal yeastMalasseziain the murine skin

“…To understand which PRRs may be involved in innate immune recognition of Malassezia, we explored a transcriptomic dataset of M. pachydermatis-colonized murine skin [22]. We checked for differential expression of PRR encoding genes in colonized vs. naïve skin using the GO term "pattern recognition receptor activation", GO:0038187.…”

“…The primers used for qPCR were Actb forward 5'-CCCTGAAGTACCCCATTGAAC-3', Actb reverse 5'-CTTTTCACGGTTGGCCTTAG-3'; Il23a forward 5'-CCAGCAGCTCTCTCGGAATC-3', Il23a reverse 5'-TCATATGTCCCGCTGGTGC- RNA-Sequencing data analysis. For RNA sequencing analysis we explored a published data set (NCBI GEO repository, accession number GSE253214 [22]. Data analysis was performed using the SUSHI framework [98], including differential expression using the generalized linear model as implemented by the DESeq2 Bioconductor R package [99], and Gene Ontology (GO) term pathway analysis using the hypergeometric over-representation and GSEA tests via the 'enrichGO' and `gseGO` functions respectively of the clusterProfiler Bioconductor R package [100].…”