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Projekt
Identification of TLR patterns and TLR-mediated epithelial protection mechanisms during localised candidosis
Antragsteller
Professor Dr. Martin Schaller
Fachliche Zuordnung
Parasitologie und Biologie der Erreger tropischer Infektionskrankheiten
Förderung
Förderung von 2004 bis 2011
Projektkennung
Deutsche Forschungsgemeinschaft (DFG) - Projektnummer 5426737
Candida albicans (C. albicans) is usually considered a harmless commensal habitant in the digestive tract of healthy individuals, but may cause severe, life-threatening systemic infections with an attributable mortality rate of up to 35% among hospitalised and immunocompromised patients. Recognition of the invading fungi by the innate immune system is the first approach to activate a rapid immunological response and to ensure survival from infections. An important element of the innate immune system are germ line-encoded proteins such as pattern recognition receptors (PRR), e.g. Toll-like receptors (TLR). They are a protein family of cellular receptors specifically interacting with conserved pathogen-associated molecular patterns (PAMP), that represent broad groups of microbial species rather than a single specific species. TLR signalling pathway activates the subsequent inflammatory response which is crucial for successful host defense against mucosal and systemic candidosis. In this study we will use an established model of oral candidosis based on reconstituted oral epithelium and supplemented by immune cells to investigate in co-operation with other applicants which TLR are involved in sensing C. albicans during localised infection by keratinocytes, and polymorphonuclear leukocytes (PMN). Moreover, we will characterise the downstream signalling pathway involved in activation of the transcription factors NF-kB and AP-1. Using the model, we intend to investigate the influence of several virulence factors such as hydrolytic enzymes, dimorphism, phenotypic switching and adhesion factors on the TLR expression profile. Results will be compared with data from patient samples.
DFG-Verfahren
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