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DOI 10.3791/60175

Медицинская библиотека · Journal of visualized experiments : JoVE · 2019

Infecting Mice with Malassezia spp. to Study the Fungus-Host Interaction.

Sparber Florian, LeibundGut-Landmann Salomé

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Аннотация

Animal models are crucial for infectious disease research. They provide an important basis for analyzing the full spectrum of interactions that occur between microbes and their host in vivo in a tissue-specific manner. Pathogenic fungi are increasingly recognized as a serious threat for humans and exploiting such infection models have greatly improved our understanding of fungal pathogenicity. Species of the genus Malassezia are the most abundant fungi of the human skin microbiota and they are also associated with the development of severe inflammatory skin disorders such as seborrheic dermatitis and atopic dermatitis. However, a causative link between Malassezia and disease pathogenesis remains unknown, a fact that can be attributed to the poor knowledge of the complex crosstalk of Malassezia with the skin immune system. This protocol describes the establishment of an experimental mouse model that allows studying the interaction of Malassezia with the mammalian skin in vivo. It outlines the method for cultivating Malassezia spp. under laboratory conditions, how to infect the murine skin with Malassezia spp. and how to assess the outcome of infection by means of the skin inflammation and fungal burden analyses. The model described here works in fully immunocompetent animals and does not rely on immune suppressive or antibiotic pretreatment of the animals. It is furthermore adaptable to virtually all genetically modified mouse strains and can be combined with other skin disease models. These features make this infection model a very powerful tool for studying in detail the innate and adaptive immune response of the host against Malassezia in the skin in vivo.

Для цитирования: Sparber Florian, LeibundGut-Landmann Salomé. Infecting Mice with Malassezia spp. to Study the Fungus-Host Interaction.. Journal of visualized experiments : JoVE. 2019. DOI: 10.3791/60175.

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