323 research outputs found

    A Continuous Battle for Host-Derived Glycans Between a Mucus Specialist and a Glycan Generalist in vitro and in vivo

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    The human gastrointestinal tract is colonized by a diverse microbial community, which plays a crucial role in human health. In the gut, a protective mucus layer that consists of glycan structures separates the bacteria from the host epithelial cells. These host-derived glycans are utilized by bacteria that have adapted to this specific compound in the gastrointestinal tract. Our study investigated the close interaction between two distinct gut microbiota members known to use mucus glycans, the generalist Bacteroides thetaiotaomicron and the specialist Akkermansia muciniphila in vitro and in vivo. The in vitro study, in which mucin was the only nutrient source, indicated that B. thetaiotaomicron significantly upregulated genes coding for Glycoside Hydrolases (GHs) and mucin degradation activity when cultured in the presence of A. muciniphila. Furthermore, B. thetaiotaomicron significantly upregulated the expression of a gene encoding for membrane attack complex/perforin (MACPF) domain in co-culture. The transcriptome analysis also indicated that A. muciniphila was less affected by the environmental changes and was able to sustain its abundance in the presence of B. thetaiotaomicron while increasing the expression of LPS core biosynthesis activity encoding genes (O-antigen ligase, Lipid A and Glycosyl transferases) as well as ABC transporters. Using germ-free mice colonized with B. thetaiotaomicron and/or A. muciniphila, we observed a more general glycan degrading profile in B. thetaiotaomicron while the expression profile of A. muciniphila was not significantly affected when colonizing together, indicating that two different nutritional niches were established in mice gut. Thus, our results indicate that a mucin degrading generalist adapts to its changing environment, depending on available carbohydrates while a mucin degrading specialist adapts by coping with competing microorganism through upregulation of defense related genes.Peer reviewe

    Kemalettin - (Mimar) [1870-1927]

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    Taha Toros Arşivi, Dosya No: 134-Mimar Kemalettinİstanbul Kalkınma Ajansı (TR10/14/YEN/0033) İstanbul Development Agency (TR10/14/YEN/0033

    Developmental trajectory of the healthy human gut microbiota during the first 5 years of life

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    The gut is inhabited by a densely populated ecosystem, the gut microbiota, that is established at birth. However, the succession by which different bacteria are incorporated into the gut microbiota is still relatively unknown. Here, we analyze the microbiota from 471 Swedish children followed from birth to 5 years of age, collecting samples after 4 and 12 months and at 3 and 5 years of age as well as from their mothers at birth using 16S rRNA gene profiling. We also compare their microbiota to an adult Swedish population. Genera follow 4 different colonization patterns during establishment where Methanobrevibacter and Christensenellaceae colonize late and do not reached adult levels at 5 years. These late colonizers correlate with increased alpha diversity in both children and adults. By following the children through age-specific community types, we observe that children have individual dynamics in the gut microbiota development trajectory

    Curated and harmonized gut microbiome 16S rRNA amplicon data from dietary fiber intervention studies in humans

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    Next generation amplicon sequencing has created a plethora of data from human microbiomes. The accessibility to this scientific data and its corresponding metadata is important for its reuse, to allow for new discoveries, verification of published results, and serving as path for reproducibility. Dietary fiber consumption has been associated with a variety of health benefits that are thought to be mediated by gut microbiota. To enable direct comparisons of the response of the gut microbiome to fiber, we obtained 16S rRNA sequencing data and its corresponding metadata from 11 fiber intervention studies for a total of 2,368 samples. We provide curated and pre-processed genetic data and common metadata for comparison across the different studies

    Curated and Harmonized Gut Microbiome 16S rRNA Amplicon Data From Dietary Fiber Intervention Studies in Humans

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    Next generation amplicon sequencing has created a plethora of data from human microbiomes. The accessibility to this scientific data and its corresponding metadata is important for its reuse, to allow for new discoveries, verification of published results, and serving as path for reproducibility. Dietary fiber consumption has been associated with a variety of health benefits that are thought to be mediated by gut microbiota. To enable direct comparisons of the response of the gut microbiome to fiber, we obtained 16S rRNA sequencing data and its corresponding metadata from 11 fiber intervention studies for a total of 2,368 samples. We provide curated and pre-processed genetic data and common metadata for comparison across the different studies

    Intestinal Ralstonia pickettii augments glucose intolerance in obesity

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    An altered intestinal microbiota composition has been implicated in the pathogenesis of metabolic disease including obesity and type 2 diabetes mellitus (T2DM). Low grade inflammation, potentially initiated by the intestinal microbiota, has been suggested to be a driving force in the development of insulin resistance in obesity. Here, we report that bacterial DNA is present in mesenteric adipose tissue of obese but otherwise healthy human subjects. Pyrosequencing of bacterial 16S rRNA genes revealed that DNA from the Gram-negative species Ralstonia was most prevalent. Interestingly, fecal abundance of Ralstonia pickettii was increased in obese subjects with pre-diabetes and T2DM. To assess if R. pickettii was causally involved in development of obesity and T2DM, we performed a proof-of-concept study in diet-induced obese (DIO) mice. Compared to vehicle-treated control mice, R. pickettii-treated DIO mice had reduced glucose tolerance. In addition, circulating levels of endotoxin were increased in R. pickettii-treated mice. In conclusion, this study suggests that intestinal Ralstonia is increased in obese human subjects with T2DM and reciprocally worsens glucose tolerance in DIO mice.Peer reviewe

    Biogeography of the Relationship between the Child Gut Microbiome and Innate Immune System.

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    The gut microbiome is a well-recognized modulator of host immunity, and its compositions differ between geographically separated human populations. Systemic innate immune responses to microbial derivatives also differ between geographically distinct human populations. However, the potential role of the microbiome in mediating geographically varied immune responses is unexplored. We here applied 16S amplicon sequencing to profile the stool microbiome and, in parallel, measured whole-blood innate immune cytokine responses to several pattern recognition receptor (PRR) agonists among 2-year-old children across biogeographically diverse settings. Microbiomes differed mainly between high- and low-resource environments and were not strongly associated with other demographic factors. We found strong correlations between responses to Toll-like receptor 2 (TLR2) and relative abundances of Bacteroides and Prevotella populations, shared among Canadian and Ecuadorean children. Additional correlations between responses to TLR2 and bacterial populations were specific to individual geographic cohorts. As a proof of concept, we gavaged germfree mice with human donor stools and found murine splenocyte responses to TLR stimulation were consistent with responses of the corresponding human donor populations. This study identified differences in immune responses correlating to gut microbiomes across biogeographically diverse settings and evaluated biological plausibility using a mouse model. This insight paves the way to guide optimization of population-specific interventions aimed to improve child health outcomes.IMPORTANCE Both the gut microbiome and innate immunity are known to differ across biogeographically diverse human populations. The gut microbiome has been shown to directly influence systemic immunity in animal models. With this, modulation of the gut microbiome represents an attractive avenue to improve child health outcomes associated with altered immunity using population-specific approaches. However, there are very scarce data available to determine which members of the gut microbiome are associated with specific immune responses and how these differ around the world, creating a substantial barrier to rationally designing such interventions. This study addressed this knowledge gap by identifying relationships between distinct bacterial taxa and cytokine responses to specific microbial agonists across highly diverse settings. Furthermore, we provide evidence that immunomodulatory effects of region-specific stool microbiomes can be partially recapitulated in germfree mice. This is an important contribution toward improving global child health by targeting the gut microbiome

    Quantifying diet-induced metabolic changes of the human gut microbiome

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    The human gut microbiome is known to be associated with various human disorders, but a major challenge is to go beyond association studies and elucidate causalities. Mathematical modeling of the human gut microbiome at a genome-scale is a useful tool to decipher microbe-microbe, diet-microbe and microbe-host interactions. Here, we describe the CASINO (Community and Systems-level Interactive Optimization) toolbox, a comprehensive computational platform for analysis of microbial communities through metabolic modeling. We first validated the toolbox by simulating and testing the performance of single bacteria and whole communities in in vitro. Focusing on metabolic interactions between the diet, gut microbiota and host metabolism, we demonstrated the predictive power of the toolbox in a diet-intervention study of 45 obese and overweight individuals, and validated our predictions by fecal and blood metabolomics data. Thus, modeling could quantitatively describe altered fecal and serum amino acid levels in response to diet intervention
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