929 resultados para GUT MICROBIOTA
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AIM To characterize the subgingival microbiota within a cohort of adult males (n = 32) naïve to oral hygiene practices, and to compare the composition of bacterial taxa present in periodontal sites with various probing depths. MATERIAL AND METHODS Subgingival plaque samples were collected from single shallow pocket [pocket probing depth (PPD)≤3 mm] and deep pocket (PPD≥6 mm) sites from each subject. A polymerase chain reaction based strategy was used to construct a clone library of 16S ribosomal RNA (rRNA) genes for each site. The sequences of ca. 30-60 plasmid clones were determined for each site to identify resident taxa. Microbial composition was compared using a variety of statistical and bioinformatics approaches. RESULTS A total of 1887 cloned 16S rRNA gene sequences were analysed, which were assigned to 318 operational taxonomic units (98% identity cut-off). The subgingival microbiota was dominated by Firmicutes (69.8%), Proteobacteria (16.3%), and Fusobacteria (8.0%). The overall composition of microbial communities in shallow sites was significantly different from those within deep sites (∫-Libshuff, p < 0.001). CONCLUSIONS A taxonomically diverse subgingival microbiota was present within this cohort; however, the structures of the microbial communities present in the respective subjects exhibited limited variation. Deep and shallow sites contained notably different microbial compositions, but this was not correlated with the rate of periodontal progression.
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von E. Flanter
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BACKGROUND Understanding the composition and dynamics of the upper respiratory tract microbiota in healthy infants is a prerequisite to investigate the role of the microbiota in patients with respiratory diseases. This is especially true in early life, when the immune system is in development. OBJECTIVE We sought to describe the dynamics of the upper respiratory tract microbiota in healthy infants within the first year of life. METHODS After exclusion of low-quality samples, microbiota characterization was performed by using 16S rDNA pyrosequencing of 872 nasal swabs collected biweekly from 47 unselected infants. RESULTS Bacterial density increased and diversity decreased within the first year of life (R(2) = 0.95 and 0.73, respectively). A distinct profile for the first 3 months of life was found with increased relative abundances of Staphlyococcaceae and Corynebacteriaceae (exponential decay: R(2) = 0.94 and 0.96, respectively). In addition, relative bacterial abundance and composition differed significantly from summer to winter months. The individual composition of the microbiota changed with increasing time intervals between samples and was best modeled by an exponential function (R(2) = 0.97). Within-subject dissimilarity in a 2-week time interval was consistently lower than that between subjects, indicating a personalized microbiota. CONCLUSION This study reveals age and seasonality as major factors driving the composition of the nasal microbiota within the first year of life. A subject's microbiota is personalized but dynamic throughout the first year. These data are indispensable to interpretation of cross-sectional studies and investigation of the role of the microbiota in both healthy subjects and patients with respiratory diseases. They might also serve as a baseline for future intervention studies.
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Neutropenia is probably the strongest known predisposition to infection with otherwise harmless environmental or microbiota-derived species. Because initial swarming of neutrophils at the site of infection occurs within minutes, rather than the hours required to induce "emergency granulopoiesis," the relevance of having high numbers of these cells available at any one time is obvious. We observed that germ-free (GF) animals show delayed clearance of an apathogenic bacterium after systemic challenge. In this article, we show that the size of the bone marrow myeloid cell pool correlates strongly with the complexity of the intestinal microbiota. The effect of colonization can be recapitulated by transferring sterile heat-treated serum from colonized mice into GF wild-type mice. TLR signaling was essential for microbiota-driven myelopoiesis, as microbiota colonization or transferring serum from colonized animals had no effect in GF MyD88(-/-)TICAM1(-/-) mice. Amplification of myelopoiesis occurred in the absence of microbiota-specific IgG production. Thus, very low concentrations of microbial Ags and TLR ligands, well below the threshold required for induction of adaptive immunity, sets the bone marrow myeloid cell pool size. Coevolution of mammals with their microbiota has probably led to a reliance on microbiota-derived signals to provide tonic stimulation to the systemic innate immune system and to maintain vigilance to infection. This suggests that microbiota changes observed in dysbiosis, obesity, or antibiotic therapy may affect the cross talk between hematopoiesis and the microbiota, potentially exacerbating inflammatory or infectious states in the host.
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Segmented filamentous bacterium (SFB) is a symbiont that drives postnatal maturation of gut adaptive immune responses. In contrast to nonpathogenic E. coli, SFB stimulated vigorous development of Peyer's patches germinal centers but paradoxically induced only a low frequency of specific immunoglobulin A (IgA)-secreting cells with delayed accumulation of somatic mutations. Moreover, blocking Peyer's patch development abolished IgA responses to E. coli, but not to SFB. Indeed, SFB stimulated the postnatal development of isolated lymphoid follicles and tertiary lymphoid tissue, which substituted for Peyer's patches as inductive sites for intestinal IgA and SFB-specific T helper 17 (Th17) cell responses. Strikingly, in mice depleted of gut organized lymphoid tissue, SFB still induced a substantial but nonspecific intestinal Th17 cell response. These results demonstrate that SFB has the remarkable capacity to induce and stimulate multiple types of intestinal lymphoid tissues that cooperate to generate potent IgA and Th17 cell responses displaying only limited target specificity.