Atopic dermatitis (AD) is a common and multifactorial skin disease. Genetically determined skin barrier defects and a dysregulated immune system lead to chronic inflammation. It is known that atopic and healthy skin differ in bacterial colonization. Atopic skin is associated with a lower microbiota diversity and higher amounts of potentially pathogenic bacteria like Staphylococcus aureus. However, it is still subject of debate whether this different microbiota composition is mainly a result or a cause of the inflammatory state in AD. To investigate this question further, we started to analyze the influence of the skin microbiota of healthy individuals and AD patients on a 3D skin equivalent representing healthy skin. To this end, defined skin areas were rinsed with a saline/detergent solution to harvest the microbiota. Subsequently, the rinsing solution was sequentially centrifuged and stored at -80°C in a glycerol-pellet. These microbiota samples were then applied to the surface of a 3D skin equivalent. After stimulation, gene expression of inflammatory mediators, barrier and defense molecules was analyzed by real-time PCR. The microbiota of AD patients was compared with localization-, gender- and age-matched microbiota samples of healthy control persons. As a general result, we observed that the microbiota-treatment of the 3D skin equivalents induced the expression of several inflammatory and defense mediators (e.g. cytokines, antimicrobial peptides). The microbiota derived from lesional AD-skin induced higher levels of several inflammatory mediators as compared to the microbiota of healthy skin or non-lesional AD skin. Especially the expression of the AD-associated inflammatory mediator thymic stromal lymphopoietin (TSLP) was markedly increased by the microbiota derived from lesional AD skin. These findings indicate that the altered skin microbiota in AD may amplify the inflammation process through the induction of host inflammatory mediators such as TSLP.

The microbiota of atopic dermatitis lesions induces TSLP expression in a 3D skin equivalent