The gut microbiota is essential for numerous aspects of human health. However, the underlying mechanisms of many host-microbiota interactions remain unclear. The aim of this study was to characterize effects of the microbiota on host epithelium using a novel ex vivo model based on mouse ileal organoids. We have explored the transcriptional response of organoids upon exposure to short-chain fatty acids (SCFAs) and products generated by two abundant microbiota constituents, Akkermansia muciniphila and Faecalibacterium prausnitzii. We observed that A. muciniphila metabolites affect various transcription factors and genes involved in cellular lipid metabolism and growth, supporting previous in vivo findings. Contrastingly, F. prausnitzii products exerted only weak effects on host transcription. Additionally, A. muciniphila and its metabolite propionate modulated expression of Fiaf, Gpr43, histone deacetylases (HDACs), and peroxisome proliferator-activated receptor gamma (Pparγ), important regulators of transcription factor regulation, cell cycle control, lipolysis, and satiety. This work illustrates that specific bacteria and their metabolites differentially modulate epithelial transcription in mouse organoids. We demonstrate that intestinal organoids provide a novel and powerful ex vivo model for host-microbiome interaction studies.

BackgroundMetabolic homeostasis in mammals critically depends on the regulation of fasting-induced genes by CREB in the liver. Previous genome-wide analysis has shown that only a small percentage of CREB target genes are induced in response to fasting-associated signaling pathways. The precise molecular mechanisms by which CREB specifically targets these genes in response to alternating hormonal cues remain to be elucidated.ResultsWe performed chromatin immunoprecipitation coupled to high-throughput sequencing of CREB in livers from both fasted and re-fed mice. In order to quantitatively compare the extent of CREB-DNA interactions genome-wide between these two physiological conditions we developed a novel, robust analysis method, termed the ‘single sample independence’ (SSI) test that greatly reduced the number of false-positive peaks. We found that CREB remains constitutively bound to its target genes in the liver regardless of the metabolic state. Integration of the CREB cistrome with expression microarrays of fasted and re-fed mouse livers and ChIP-seq data for additional transcription factors revealed that the gene expression switches between the two metabolic states are associated with co-localization of additional transcription factors at CREB sites.ConclusionsOur results support a model in which CREB is constitutively bound to thousands of target genes, and combinatorial interactions between DNA-binding factors are necessary to achieve the specific transcriptional response of the liver to fasting. Furthermore, our genome-wide analysis identifies thousands of novel CREB target genes in liver, and suggests a previously unknown role for CREB in regulating ER stress genes in response to nutrient influx.

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BackgroundThe effects of gut microbiota on human traits are expected to be small to moderate and adding the complexity of the human diseases, microbiome research demands big sample sizes. Fecal samples for such studies are mostly self-collected by participants at home. This imposes an extra level of complexity as sample collection and storage can be challenging. Effective, low-burden collection and storage methods allowing fecal samples to be transported properly and ensuring optimal quality and quantity of bacterial DNA for upstream analyses are necessary. Moreover, accurate assessment of the microbiome composition also depends on bacterial DNA extraction method. The aim of this study was to evaluate the reliability and efficiency of the OMNIgene•GUT kit as a participant-fecal friendly collection method (storage at room temperature for 24 h (O24h) or 7 days (O7d)) in comparison to the standard collection method (Fresh, storage at 4 °C for less than 24 h) in terms of amount of variability and information content accounting for two common DNA extraction methods.ResultsFourteen fecal samples were collected from healthy individuals (7 males, 7 females). Collection and storage methods did not differ significantly in terms of DNA concentration and Shannon diversity index. Phylum relative abundance showed significant differences for Bacteroidetes, Actinobacteria and Cyanobacteria. The differences were observed between control (Fresh) and O24h methods, but not between Fresh and O7d. These differences were not seen when performing bacterial DNA quantification based on three bacterial groups: Bacteroides spp., Bifidobacterium spp. and Clostridium cluster IV, which represent three major phyla: Bacteroidetes, Actinobacteria and Firmicutes respectively. The two DNA extraction methods differ in terms of DNA quantity, quality, bacterial diversity and bacterial relative abundance. Furthermore, principal component analysis revealed differences in microbial structure, which are driven by the DNA extraction methods more than the collection/storage methods.ConclusionOur results have highlighted the potential of using the OMNIgene•GUT kit for collection and storage at ambient temperature, which is convenient for studies aiming to collect large samples by giving participants the possibility to send samples by post. Importantly, we revealed that the choice of DNA extraction method have an impact on the microbiome profiling.Electronic supplementary materialThe online version of this article (10.1186/s12866-018-1249-x) contains supplementary material, which is available to authorized users.

We present TaxPhlAn, a new method and bioinformatics pipeline for design and analysis of single-locus sequence typing (SLST) markers to type and profile bacteria beyond the species-level in a complex microbial community background. TaxPhlAn can be applied to any group of phylogenetically-related bacteria, provided reference genomes are available. As TaxPhlAn requires the SLST targets identified to fit the phylogenetic pattern as determined through comprehensive evolutionary reconstruction of input genomes, TaxPhlAn allows for the identification and phylogenetic inference of new biodiversity. Here, we present a clinically relevant case study of high-resolution Staphylococcus profiling on skin of atopic dermatitis (AD) patients. We demonstrate that SLST enables profiling of cutaneous Staphylococcus members at (sub)species level and provides higher resolution than current 16S-based techniques. With the higher discriminative ability provided by our approach, we further show that the presence of Staphylococcus capitis on the skin together with Staphylococcus aureus associates with AD disease.