Project description:Gut microbiota dysbiosis characterizes systemic metabolic alteration, yet its causality is debated. To address this issue, we transplanted antibiotic-free conventional wild-type mice with either dysbiotic (“obese”) or eubiotic (“lean”) gut microbiota and fed them either a NC or a 72%HFD. We report that, on NC, obese gut microbiota transplantation reduces hepatic gluconeogenesis with decreased hepatic PEPCK activity, compared to non-transplanted mice. Of note, this phenotype is blunted in conventional NOD2KO mice. By contrast, lean microbiota transplantation did not affect hepatic gluconeogenesis. In addition, obese microbiota transplantation changed both gut microbiota and microbiome of recipient mice. Interestingly, hepatic gluconeogenesis, PEPCK and G6Pase activity were reduced even once mice transplanted with the obese gut microbiota were fed a 72%HFD, together with reduced fed glycaemia and adiposity compared to non-transplanted mice. Notably, changes in gut microbiota and microbiome induced by the transplantation were still detectable on 72%HFD. Finally, we report that obese gut microbiota transplantation may impact on hepatic metabolism and even prevent HFD-increased hepatic gluconeogenesis. Our findings may provide a new vision of gut microbiota dysbiosis, useful for a better understanding of the aetiology of metabolic diseases. all livers are from NC-fed mice only.
Project description:To compare the similarities and differences in species diversity of the gut microbiota between the patients with melasma and healthy subjects. The feces were collected for 16S rRNA sequencing analysis of the gut microbiota.
Project description:In the presented study, in order to unravel gut microbial community multiplicity and the influence of maternal milk nutrients (i.e., IgA) on gut mucosal microbiota onset and shaping, a mouse GM (MGM) was used as newborn study model to discuss genetic background and feeding modulation on gut microbiota in term of symbiosis, dysbiosis and rebiosis maintenance during early gut microbiota onset and programming after birth. Particularly, a bottom-up shotgun metaproteomic approach, combined with a computational pipeline, has been compred with a culturomics analysis of mouse gut microbiota, obtained by MALDI-TOF mass spectrometry (MS).
Project description:Fecal samples collected on day 5 from randomly selected colitic SD rats were analyzed for gut microbiota by sequencing the V4 region of the 16S rRNA gene. The orally administered Dex-P-laden NPA2 coacervate (Dex-P/NPA2) significantly restores the diversity of gut microbiota compared with colitic SD rats in the Dex-P/PBS group and the untreated colitic rats (Control).
Project description:Chronic acid suppression by proton pump inhibitor (PPI) has been hypothesized to alter the gut microbiota via a change in intestinal pH. To evaluate the changes in gut microbiota composition by long-term PPI treatment. Twenty-four week old F344 rats were fed with (n = 5) or without (n = 6) lansoprazole (PPI) for 50 weeks. Then, profiles of luminal microbiota in the terminal ileum were analyzed. Pyrosequencing for 16S rRNA gene was performed by genome sequencer FLX (454 Life Sciences/Roche) and analyzed by metagenomic bioinformatics.
Project description:The effect of oral microbiota on the intestinal microbiota has garnered growing attention as a mechanism linking periodontal diseases to systemic diseases. However, the salivary microbiota is diverse and comprises numerous bacteria with a largely similar composition in healthy individuals and periodontitis patients. Thus, the systemic effects of small differences in the oral microbiota are unclear. In this study, we explored how health-associated and periodontitis-associated salivary microbiota differently colonized the intestine and their subsequent systemic effects by analyzing the hepatic gene expression and serum metabolomic profiles. The salivary microbiota was collected from a healthy individual and a periodontitis patient and gavaged into C57BL/6NJcl[GF] mice. Samples were collected five weeks after administration. Gut microbial communities were analyzed by 16S ribosomal RNA gene sequencing. Hepatic gene expression profiles were analyzed using a DNA microarray and quantitative polymerase chain reaction. Serum metabolites were analyzed by capillary electrophoresis time-of-flight mass spectrometry. The gut microbial composition at the genus level was significantly different between periodontitis-associated microbiota-administered (PAO) and health-associated oral microbiota-administered (HAO) mice. The hepatic gene expression profile demonstrated a distinct pattern between the two groups, with higher expression of Neat1, Mt1, Mt2, and Spindlin1, which are involved in lipid and glucose metabolism. Disease-associated metabolites such as 2-hydroxyisobutyric acid and hydroxybenzoic acid were elevated in PAO mice. These metabolites were significantly correlated with Bifidobacterium, Atomobium, Campylobacter, and Haemophilus, which are characteristic taxa in PAO mice. Conversely, health-associated oral microbiota were associated with higher levels of beneficial serum metabolites in HAO mice. The multi-omics approach used in this study revealed that periodontitis-associated oral microbiota is associated with the induction of disease phenotype when they colonized the gut of germ-free mice.
Project description:Gut microbial profiling of uterine fibroids (UFs) patients comparing control subjects. The gut microbiota was examined by 16S rRNA quantitative arrays and bioinformatics analysis. The goal was to reveal alterations in the gut microbiome of uterine fibroids patients.
Project description:Increasing evidence indicates that gut microbiota plays an important role in cancer progression. We have employed RNA-seq or microarray for genome including mRNA, microRNA or circRNA profiling in an gut microbiota -dependent manner, as a discovery platform to identify target genes with the potential to involve in tumor regulation. The deep sequencing analysis reveals regulatory functions of microbiota-mediated circular RNA (circRNA)/microRNA networks that may contribute to cancer progression.