Project description:Mucispirillum schaedleri is an abundant inhabitant of the intestinal mucus layer of rodents and other animals. To gain insights into its lifestyle, we analyzed the genome and transcriptome of M. schaedleri ASF 457 and tested for traits predicted by the genome using physiological experiments. Although thought to be a mucus degrader, its genome surprisingly predicts that M. schaedleri has limited capacity for degrading host-derived mucosal glycans or other complex polysaccharides. Rather, it may utilize small compounds such as peptides, amino acids, glycerol, and short chain fatty acids. Additionally, it can reduce nitrate and has systems for scavenging oxygen and reactive oxygen species, which accounts for its presence close to the mucosal tissue and during inflammation. Also of note, M. schaedleri harbors a type VI secretion system (T6SS) and several putative effector proteins containing eukaryotic domains, which suggest intimate interactions with the host and a role in inflammation. Examination of the individual phylogenies of all genes in the M. schaedleri genome revealed extensive horizontal gene transfer, primarily from intestinal Epsilon- and Deltaproteobacteria. Though M. schaedleri utilizes non-horizontally-transferred pathways (e.g. nitrate reduction), horizontally-acquired pathways from gut organisms (e.g. T6SS and glycerol-P utilization) are also likely also important for its survival in the intestine, suggesting that lateral gene transfer may have played a key role in facilitating its establishment in the gut ecosystem.
Project description:We used transcriptomics to investigate how Mucispirillum schaedleri ASF 457 interferes with the gene expression of Salmonella Typhimurium in the cecum of gnotobiotic mice
Project description:The inter-organ cross talk between liver and intestine has been focus of intense research. Key in this cross-talk are bile acids, which are secreted from the liver into the intestine and, via the enterohepatic circulation, reach back to the liver. Important new insights have been gained in the Farnesoid X receptor (Fxr)-mediated communication from intestine-to-liver in health and disease. However, liver-to-intestine communication and the role of bile acids and FXR in this cross talk remain elusive. Here, we analyse Fxr-mediated liver-to-gut communication, and its consequences in the colon. Mice in which Fxr was selectively ablated in intestine (Fxr-intKO), the liver (Fxr-livKO), or in the full body (Fxr-totKO) were engineered. The effects on colonic gene expression (RNA sequencing), on the microbiome (16S rRNA Gene Sequencing) and on mucus barrier were analyzed. Compared to Fxr-intKO and Fxr-totKO mice, more genes were differentially expressed in the colons of Fxr-livKO mice relative to control mice (731, 1824 and 3272 respectively), suggestive of a strong role of hepatic Fxr in liver-to-gut communication. The colons of Fxr-livKO showed increased expression of anti-microbial genes, such as Regenerating islet-derived 3 beta and gamma (Reg3β and Reg3γ), Toll-like receptors (Tlrs), inflammasome related genes and differential expression of genes belonging to the ‘Mucin-type O-glycan biosynthesis’ pathway. Compared to control mice, Fxr-livKO mice have decreased levels of the predicted mucin degrading bacterium Turicibacter and a concomitant increase in the thickness of the inner sterile mucus layer. In conclusion, ablation of Fxr in the liver has a major effect on colonic gene expression, the gut microbiome and on the permeability of the mucus layer. This stresses the importance of the Fxr-mediated liver-to-gut signaling.
Project description:Mucus produced by goblet cells in the gastrointestinal (GI) tract forms a biological barrier that protects the intestine from invasion by commensals and pathogens. However, the host-derived regulatory network that controls mucus secretion and thereby changing gut microbiota has not been well studied. We found Forkhead box protein O1 (Foxo1) regulates mucus secretion by goblet cells and determines intestinal homeostasis. Loss of Foxo1 in intestinal epithelial cells (IECs) results in a defect in goblet cell autophagy and mucus secretion, leading to impaired gut microenvironment and dysbiosis.
Project description:Background: The high number of heavy metal resistance genes in the soil bacterium Cupriavidus metallidurans CH34 makes it an interesting model organism to study microbial responses to heavy metals. Results: In this study the transcriptional response of this bacterium was measured after challenging it to a wide range of sub-lethal concentrations of various essential or toxic metals. Considering the global transcriptional responses for each challenge as well as by identifying the overlap in upregulated genes between different metal responses, the sixteen metals could be clustered in three different groups. Additionally, next to the assessment of the transcriptional response of already known metal resistance genes, new metal response gene clusters were identified. The majority of the metal response loci showed similar expression profiles when cells were exposed to different metals, suggesting complex cross-talk at transcriptional level between the different metal responses. The highly redundant nature of these metal resistant regions – illustrated by the large number of paralogous genes – combined with the phylogenetic distribution of these metal response regions within evolutionary related and other metal resistant bacteria, provides important insights on the recent evolution of this naturally soil dwelling bacterium towards a highly metal-resistant strain found in harsh and anthropogenic environments. Conclusions: The metal-resistant soil bacterium Cupriavidus metallidurans CH34 displays myriads of gene expression patterns when exposed to a wide range of heavy metals at non-lethal concentrations. The interplay between the different gene expression clusters points towards a complex cross-regulated regulatory network governing heavy metal resistance in C. metallidurans CH34. Keywords: Cupriavidus metallidurans CH34, transcriptional regulation, heavy metal resistance Two-condition experiments. Comparing samples after induction with heavy metals versus non-induced samples. Biological duplicate or triplicate. Each array contains 3 or 4 technical replicates.