Artikel
Distinct intestinal microbiota phenotypes identify chronic inflammatory diseases
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Veröffentlicht: | 31. August 2022 |
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Gliederung
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Introduction: A hallmark of chronic inflammatory diseases (CID) and autoimmune diseases is an alteration of the intestinal microbiota, also called dysbiosis. Experimental animal models strongly suggest that such a dysbiosis contributes to the disease. In clinical studies microbial 16S rRNA gene profiling by next generation sequencing has greatly contributed to our understanding of taxonomic alterations of the microbiome in disease, but has failed so far to conclusively identify bacteria or bacterial communities contributing to disease pathogenesis.
Methods: We are using multi-parametric flow cytometry to analyze the human intestinal microbiota from stool samples on the single cell level and assess phenotypic properties of the bacteria, which may be important for the microbe-host interaction. We analyze the coating of patient’s intestinal microbiota by isotype-specific staining of the host´s immunoglobulins IgA1, IgA2, IgM, IgG to capture the immunological context of their recognition by the host immune system. In addition, we characterize microbial surface sugars with specific plant lectins, which may indicate metabolic conditions, adhesive ability and bacteria-host-crosstalk.
Results: Using our method, we can discriminate distinct microbial community phenotypes in patients with different chronic inflammatory diseases (Crohn’s disease, ulcerative colitis, IgG4-related disease, juvenile idiopathic arthritis, rheumatoid arthritis). Further by the application of machine-learning approaches, we can delineate phenotypic clusters that allow robust classification of disease entities.
Conclusion: Our approach suggests that we can use multi-parametric microbiota flow cytometry of stool samples for diagnosis and disease-monitoring but also to identify intestinal microbial communities specific for certain diseases and potentially playing a role in disease pathogenesis.