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The intestinal microbiome is perturbed in patients with new-onset and chronic autoimmune inflammatory arthritis. Recent studies in mouse models suggest that development and progression of autoimmune arthritis is highly affected by the intestinal microbiome. This makes modulation of the intestinal microbiota an interesting novel approach to suppress inflammatory arthritis. Prebiotics, defined as non-digestible carbohydrates that selectively stimulate the growth and activity of beneficial microorganisms, provide a relatively non-invasive approach to modulate the intestinal microbiota. The aim of this study was to assess the therapeutic potential of dietary supplementation with a prebiotic mixture of 90% short-chain galacto-oligosaccharides and 10% long-chain fructo-oligosaccharides (scGOS/lcFOS) in experimental arthritis in mice. We here show that dietary supplementation with scGOS/ lcFOS has a pronounced effect on the composition of the fecal microbiota. Interestingly, the genera Enterococcus and Clostridium were markedly decreased by scGOS/lcFOS dietary supplementation. In contrast, the family Lachnospiraceae and the genus Lactobacillus, both associated with healthy microbiota, increased in mice receiving scGOS/lcFOS diet. However, the scGOS/lcFOS induced alterations of the intestinal microbiota did not induce significant effects on the intestinal and systemic T helper cell subsets and were not sufficient to reproducibly suppress arthritis in mice. As expected, we did observe a significant increase in the bone mineral density in mice upon dietary supplementation with scGOS/lcFOS for 8 weeks. Altogether, this study suggests that dietary scGOS/lcFOS supplementation is able to promote presumably healthy gut microbiota and improve bone mineral density, but not inflammation, in arthritis-prone mice.

Background. The microbiota in the small intestine relies on their capacity to rapidly import and ferment available carbohydrates to survive in a complex and highly competitive ecosystem. Understanding how these communities function requires elucidating the role of its key players, the interactions among them and with their environment/host. Methods. The genome of the gut bacterium Romboutsia ilealis CRIBT was sequenced with multiple technologies (Illumina paired-end, mate-pair and PacBio). The transcriptome was sequenced (Illumina HiSeq) after growth on three different carbohydrate sources, and short chain fatty acids were measured via HPLC. Results. We present the complete genome of Romboutsia ilealis CRIBT, a natural inhabitant and key player of the small intestine of rats. R. ilealis CRIBT possesses a circular chromosome of 2,581,778 bp and a plasmid of 6,145 bp, carrying 2,351 and eight predicted protein coding sequences, respectively. Analysis of the genome revealed limited capacity to synthesize amino acids and vitamins, whereas multiple and partially redundant pathways for the utilization of different relatively simple carbohydrates are present. Transcriptome analysis allowed identification of the key components in the degradation of glucose, L-fucose and fructo-oligosaccharides. Discussion. This revealed that R. ilealis CRIBT is adapted to a nutrient-rich environment where carbohydrates, amino acids and vitamins are abundantly available.

BACKGROUND: Perturbation of commensal intestinal microbiota has been associated with several autoimmune diseases. Mice deficient in interleukin-1 receptor antagonist (Il1rn -/- mice) spontaneously develop autoimmune arthritis and are susceptible to other autoimmune diseases such as psoriasis, diabetes, and encephalomyelitis; however, the mechanisms of increased susceptibility to these autoimmune phenotypes are poorly understood. We investigated the role of interleukin-1 receptor antagonist (IL-1Ra) in regulation of commensal intestinal microbiota, and assessed the involvement of microbiota subsets and innate and adaptive mucosal immune responses that underlie the development of spontaneous arthritis in Il1rn -/- mice.RESULTS: Using high-throughput 16S rRNA gene sequencing, we show that IL-1Ra critically maintains the diversity and regulates the composition of intestinal microbiota in mice. IL-1Ra deficiency reduced the intestinal microbial diversity and richness, and caused specific taxonomic alterations characterized by overrepresented Helicobacter and underrepresented Ruminococcus and Prevotella. Notably, the aberrant intestinal microbiota in IL1rn -/- mice specifically potentiated IL-17 production by intestinal lamina propria (LP) lymphocytes and skewed the LP T cell balance in favor of T helper 17 (Th17) cells, an effect transferable to WT mice by fecal microbiota. Importantly, LP Th17 cell expansion and the development of spontaneous autoimmune arthritis in IL1rn -/- mice were attenuated under germ-free condition. Selective antibiotic treatment revealed that tobramycin-induced alterations of commensal intestinal microbiota, i.e., reduced Helicobacter, Flexispira, Clostridium, and Dehalobacterium, suppressed arthritis in IL1rn -/- mice. The arthritis phenotype in IL1rn -/- mice was previously shown to depend on Toll-like receptor 4 (TLR4). Using the ablation of both IL-1Ra and TLR4, we here show that the aberrations in the IL1rn -/- microbiota are partly TLR4-de

Bacillus smithii is a facultatively anaerobic, thermophilic bacterium able to use a variety of sugars that can be derived from lignocellulosic feedstocks. Being genetically accessible, it is a potential new host for biotechnological production of green chemicals from renewable resources. We determined the complete genomic sequence of the B. smithii type strain DSM 4216T, which consists of a 3,368,778 bp chromosome (GenBank accession number CP012024.1) and a 12,514 bp plasmid (GenBank accession number CP012025.1), together encoding 3880 genes. Genome annotation via RAST was complemented by a protein domain analysis. Some unique features of B. smithii central metabolism in comparison to related organisms included the lack of a standard acetate production pathway with no apparent pyruvate formate lyase, phosphotransacetylase, and acetate kinase genes, while acetate was the second fermentation product.

The ability of bacteria to adapt to diverse environmental conditions is well-known. The process of bacterial adaptation to a niche has been linked to large changes in the genome content, showing that many bacterial genomes reflect the constraints imposed by their habitat. However, some highly versatile bacteria are found in diverse habitats that almost share nothing in common. Lactobacillus plantarum is a lactic acid bacterium that is found in a large variety of habitat. With the aim of unravelling the link between evolution and ecological versatility of L. plantarum, we analysed the genomes of 54 L. plantarum strains isolated from different environments. Comparative genome analysis identified a high level of genomic diversity and plasticity among the strains analysed. Phylogenomic and functional divergence studies coupled with gene–trait matching analyses revealed a mixed distribution of the strains, which was uncoupled from their environmental origin. Our findings revealed the absence of specific genomic signatures marking adaptations of L. plantarum towards the diverse habitats it is associated with. This suggests fundamentally similar trends of genome evolution in L. plantarum, which occur in a manner that is apparently uncoupled from ecological constraint and reflects the nomadic lifestyle of this species.

The lactic acid bacterium Lactobacillus plantarum is intensively studied as a model probiotic species. Here, we present the draft genome sequence of the exopolysaccharide-producing strain SF2A35B.

Lactobacillus plantarum strain WJL is a symbiont isolated from the Drosophila melanogaster gut. The genome of L. plantarum WJL, first sequenced in 2013, was resequenced and rescaffolded in this study. A combination of Sanger and Illumina sequencing allowed us to reduce the number of contigs from 102 to 13. This work contributes to a better understanding of the genome and function of this organism.

The aim of this study was to investigate the role of IL-1 receptor signalling and the involvement of Toll-like receptor (TLR) 2 and TLR4 in defining the intestinal microbiota and the associated mucosal and systemic immune response. Multiplex 454 pyrosequencing of V5 and V6 hyper-variable regions of fecal bacterial 16S rRNA was used to define intestinal microbial communities in BALB/c wild type (WT), IL-1Ra-/- and IL-1Ra/TLR double knock-out (DKO) mice.

Background: Simulation of DNA-microarray data serves at least three purposes: (i) optimizing the design of an intended DNA microarray experiment, (ii) comparing existing pre-processing and processing methods for best analysis of a given DNA microarray experiment, (iii) educating students, lab-workers and other researchers by making them aware of the many factors influencing DNA microarray experiments. Results: Our model has multiple layers of factors influencing the experiment. The relative influence of such factors can differ significantly between labs, experiments within labs, etc. Therefore, we have added a module to roughly estimate their parameters from a given data set. This guarantees that our simulated data mimics real data as closely as possible. Conclusions: We introduce a model for the simulation of dual-dye cDNA-microarray data closely resembling real data and coin the model and its software implementation SIMAGE which stands for simulation of microarray gene expression data. The software is freely accessible at: http://bioinformatics.biol.rug.nl/websoftware/simage

Background: In research laboratories using DNA-microarrays, usually a number of researchers perform experiments, each generating possible sources of error. There is a need for a quick and robust method to assess data quality and sources of errors in DNA-microarray experiments. To this end, a novel and cost-effective validation scheme was devised, implemented, and employed. Results: A number of validation experiments were performed on Lactococcus lactis IL1403 amplicon-based DNA-microarrays. Using the validation scheme and ANOVA, the factors contributing to the variance in normalized DNA-microarray data were estimated. Day-to-day as well as experimenter-dependent variances were shown to contribute strongly to the variance, while dye and culturing had a relatively modest contribution to the variance. Conclusion: Even in cases where 90 % of the data were kept for analysis and the experiments were performed under challenging conditions (e.g. on different days), the CV was at an acceptable 25 %. Clustering experiments showed that trends can be reliably detected also from genes with very low expression levels. The validation scheme thus allows determining conditions that could be improved to yield even higher DNA-microarray data quality.

Background: In research laboratories using DNA-microarrays, usually a number of researchers perform experiments, each generating possible sources of error. There is a need for a quick and robust method to assess data quality and sources of errors in DNA-microarray experiments. To this end, a novel and cost-effective validation scheme was devised, implemented, and employed. Results: A number of validation experiments were performed on Lactococcus lactis IL1403 amplicon-based DNA-microarrays. Using the validation scheme and ANOVA, the factors contributing to the variance in normalized DNA-microarray data were estimated. Day-to-day as well as experimenter-dependent variances were shown to contribute strongly to the variance, while dye and culturing had a relatively modest contribution to the variance. Conclusion: Even in cases where 90 % of the data were kept for analysis and the experiments were performed under challenging conditions (e.g. on different days), the CV was at an acceptable 25 %. Clustering experiments showed that trends can be reliably detected also from genes with very low expression levels. The validation scheme thus allows determining conditions that could be improved to yield even higher DNA-microarray data quality.

Background: Simulation of DNA-microarray data serves at least three purposes: (i) optimizing the design of an intended DNA microarray experiment, (ii) comparing existing pre-processing and processing methods for best analysis of a given DNA microarray experiment, (iii) educating students, lab-workers and other researchers by making them aware of the many factors influencing DNA microarray experiments. Results: Our model has multiple layers of factors influencing the experiment. The relative influence of such factors can differ significantly between labs, experiments within labs, etc. Therefore, we have added a module to roughly estimate their parameters from a given data set. This guarantees that our simulated data mimics real data as closely as possible. Conclusions: We introduce a model for the simulation of dual-dye cDNA-microarray data closely resembling real data and coin the model and its software implementation SIMAGE which stands for simulation of microarray gene expression data. The software is freely accessible at: http://bioinformatics.biol.rug.nl/websoftware/simage