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Abstract Background Darier’s disease (DD) is a genodermatosis caused by mutations of the ATP2A2 gene leading to disrupted keratinocyte adhesion. Recurrent episodes of skin inflammation and infections with a typical malodour in DD indicate a role for microbial dysbiosis. Here, for the first time, we investigated the DD skin microbiome using a metabarcoding approach of 115 skin swabs from 14 patients and 14 healthy volunteers. Furthermore, we analyzed its changes in the context of DD malodour and the cutaneous DD transcriptome. Results We identified a disease-specific cutaneous microbiome with a loss of microbial diversity and of potentially beneficial commensals. Expansion of inflammation-associated microbes such as Staphylococcus aureus and Staphylococcus warneri strongly correlated with disease severity. DD dysbiosis was further characterized by abundant species belonging to Corynebacteria, Staphylococci and Streptococci groups displaying strong associations with malodour intensity. Transcriptome analyses showed marked upregulation of epidermal repair, inflammatory and immune defence pathways reflecting epithelial and immune response mechanisms to DD dysbiotic microbiome. In contrast, barrier genes including claudin-4 and cadherin-4 were downregulated. Conclusions These findings allow a better understanding of Darier exacerbations, highlighting the role of cutaneous dysbiosis in DD inflammation and associated malodour. Our data also suggest potential biomarkers and targets of intervention for DD. Video Abstract

Abstract Background The identification of microbiota based on next-generation sequencing (NGS) of extracted DNA has drastically improved our understanding of the role of microbial communities in health and disease. However, DNA-based microbiome analysis cannot per se differentiate between living and dead microorganisms. In environments such as the skin, host defense mechanisms including antimicrobial peptides and low cutaneous pH result in a high microbial turnover, likely resulting in high numbers of dead cells present and releasing substantial amounts of microbial DNA. NGS analyses may thus lead to inaccurate estimations of microbiome structures and consequently functional capacities. Results We investigated in this study the feasibility of a Benzonase-based approach (BDA) to pre-digest unprotected DNA, i.e., of dead microbial cells, as a method to overcome these limitations, thus offering a more accurate assessment of the living microbiome. A skin mock community as well as skin microbiome samples were analyzed using 16S rRNA gene sequencing and metagenomics sequencing after DNA extraction with and without a Benzonase digest to assess bacterial diversity patterns. The BDA method resulted in less reads from dead bacteria both in the skin mock community and skin swabs spiked with either heat-inactivated bacteria or bacterial-free DNA. This approach also efficiently depleted host DNA reads in samples with high human-to-microbial DNA ratios, with no obvious impact on the microbiome profile. We further observed that low biomass samples generate an α-diversity bias when the bacterial load is lower than 105 CFU and that Benzonase digest is not sufficient to overcome this bias. Conclusions The BDA approach enables both a better assessment of the living microbiota and depletion of host DNA reads. Video abstract Graphical abstract

Introduction The pathogenesis of atopic diseases is highly complex, and the exact mechanisms leading to atopic dermatitis (AD) onset in infants remain mostly enigmatic. In addition to an interdependent network of components of skin development in young age and skin barrier dysfunction underlying AD development that is only partially understood, a complex interplay between environmental factors and lifestyle habits with skin barrier and immune dysregulation is suspected to contribute to AD onset. This study aims to comprehensively evaluate individual microbiome and immune responses in the context of environmental determinants related the risk of developing AD in the first 4 years of a child’s life.Methods and analyses The ‘Munich Atopic Prediction Study’ is a comprehensive clinical and biological investigation of a prospective birth cohort from Munich, Germany. Information on pregnancy, child development, environmental factors, parental exposures to potential allergens and acute or chronic diseases of children and parents are collected by questionnaires together with a meticulous clinical examination by trained dermatologists focusing on allergies, skin health, and in particular signs of AD at 2 months after birth and then every 6 months. In addition, skin barrier functions are assessed through cutometry, corneometry and transepidermal water loss at every visit. These measurements are completed with allergy diagnostics and extensive microbiome analyses from stool and skin swabs as well as transcriptome analyses using skin microbiopsies.The aim is to assess the relevance of different known and yet unknown risk factors of AD onset and exacerbations in infants and to identify possible accessible and robust biomarkers.Ethics and dissemination The study is approved by the Ethical Committee of the Medical Faculty of the Technical University of Munich (reference 334/16S). All relevant study results will be presented at national and international conferences and in peer-reviewed journals.