Background Atopic eczema (atopic dermatitis, AD) is characterized by disrupted skin barrier associated with elevated skin pH and skin microbiome dysbiosis, due to high Staphylococcus aureus loads, especially during flares. Since S aureus shows optimal growth at neutral pH, we investigated the longitudinal interplay between these factors and AD severity in a pilot study. Method Emollient (with either basic pH 8.5 or pH 5.5) was applied double‐blinded twice daily to 6 AD patients and 6 healthy (HE) controls for 8 weeks. Weekly, skin swabs for microbiome analysis (deep sequencing) were taken, AD severity was assessed, and skin physiology (pH, hydration, transepidermal water loss) was measured. Results Physiological, microbiome, and clinical results were not robustly related to the pH of applied emollient. In contrast to longitudinally stable microbiome in HE, S aureus frequency significantly increased in AD over 8 weeks. High S aureus abundance was associated with skin pH 5.7‐6.2. High baseline S aureus frequency predicted both increase in S aureus and in AD severity (EASI and local SCORAD) after 8 weeks. Conclusion Skin pH is tightly regulated by intrinsic factors and limits the abundance of S aureus. High baseline S aureus abundance in turn predicts an increase in AD severity over the study period. This underlines the importance and potential of sustained intervention regarding the skin pH and urges for larger studies linking skin pH and skin S aureus abundance to understand driving factors of disease progression.

Atopic eczema (AE) or atopic dermatitis (AD) is an inflammatory skin disease with involvement of genetic, immunological and environmental factors which are highly interconnected. 1,2 The heterogenic disease can be separated into different phenotypes and clinical presentations defined by the ethnicity, disease onset, disease severity, chronic vs acute, intrinsic vs extrinsic (IgE level), paediatric vs adult and inflammatory signature. [3][4][5] A common feature of all subtypes is a tremendous psychosocial burden for all patients with AE. 6 Prevalence varies by area and is reported to be 15-20% in children in Europe, persisting in up to 5-10% of adults. [7][8][9] Although severe cases are less abundant than mild or moderate disease pattern, 2% of affected children are severely suffering. 7,9 Therefore, AE remains to be a high and even increasing socio-economic burden in the United States and in Europe, 10,11 whereas slightly decreasing numbers were reported over the last few years in Japan. 12 Children often overcome atopic eczema, but set off on the so-called 'atopic march', that is begin a classic 'allergy career'. Scientifically, AE is a risk factor for the development of allergies. These are primarily type I allergies with clinical features such as hay fever and asthma. Allergies are increasingly becoming a widespread disease. Currently, almost every fourth person in Europe suffers from symptoms such as asthma or hay fever and the associated restrictions in everyday life or at work. For society, the reduced ability to perform at school, university and at work means great socio-economic damage.

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Atopic eczema (AE) is an inflammatory skin disease with involvement of genetic, immunological, and environmental factors. One hallmark of AE is a skin barrier disruption on multiple, highly interconnected levels: filaggrin mutations, increased skin pH, and a microbiome dysbiosis towards Staphylococcus aureus overgrowth are observed in addition to an abnormal type 2 immune response. Extrinsic factors seem to play a major role in the development of AE. As AE is a first step in the atopic march, its prevention and appropriate treatment is essential. Although standard therapy remains topical treatment, powerful systemic treatment options emerged in the last years. However, thorough endotyping of the individual patients is still required for ideal precision medicine approaches in the future. Therefore, novel microbial and immunological biomarkers were described recently for the prediction of disease development and treatment response. This review summarizes the current state of the art in AE research.

Introduction: Microbiome amplicon sequencing data are distorted by multiple protocol-dependent biases, originating from bacterial DNA extraction, contamination, sequence errors, and chimeras. In particular, extraction bias is a major confounder in sequencing-based microbiome analyses, with no correction method available to date. Here, we suggest using mock community controls to bioinformatically correct extraction bias based on morphological properties. Methods: We compared dilution series of 3 mock communities with an even or staggered composition. DNA was extracted with 8 different extraction protocols (2 buffers, 2 extraction kits, 2 lysis conditions). Extracted DNA was sequenced (V1-V3 16S rRNA gene) together with corresponding DNA mocks. Sequences were denoised using DADA2, and annotated by matching against mock reference genomes. Results: Microbiome composition was significantly different between extraction kits and lysis conditions, but not between buffers. Independent of the extraction protocol, chimera formation increased with high input cell number. Contaminants originated mostly from buffers, and considerable cross-contamination was observed in low-input samples. Comparison of microbiome composition of the cell mocks to corresponding DNA mocks revealed taxon-specific protocol-dependent extraction bias. Strikingly, this extraction bias per species was predictable by bacterial cell morphology. Morphology-based bioinformatic correction of extraction bias significantly improved sample compositions when applied to different samples, even with different taxa. Conclusions: Our results indicate that higher DNA density increases chimera formation during PCR amplification. Furthermore, we show that bioinformatic correction of extraction bias is feasible based on bacterial cell morphology.