Main metabolic pathways for the production of microbial metabolites.

<p>VOC are shown in bold <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0052387#pone.0052387-Welberg1" target="_blank">[52]</a>.</p

Enrollment of the volunteers.

<p>Enrollment of the volunteers.</p

Score plots showing clustering of the metabolite profiles analyzed using PLS-DA according to genotoxicity (A) and cytotoxicity (B).

<p>(A) High genotoxicity samples are located on the right side of the score plot, while low genotoxicity samples are present on the left side, indicating a difference in VOC profile between high and low genotoxicity samples. (B) High cytotoxicity samples are present on the upper right side of the score plot and low cytotoxicity samples on the lower left side, indicating a difference in VOC profile between high and low cytotoxicity samples.</p

Bland-Altman plot comparing energy intake measured using indirect calorimetry (kcal/d) and energy intake calculated from the dietary records (kcal/d).

<p>Mean energy intake measured by calorimetry and dietary record are plotted against the difference between energy intake measured by calorimetry and by dietary record.</p

Summary of the parameters of colonic metabolism and toxicity.

<p>All values are expressed as median (IQR) (n = 20). Parameters with different letters (a, b, c) in superscript were significantly different between the dietary interventions. Friedman and Wilcoxon tests were used to evaluate the results, except for urinary ¹⁵N and p-cresol, and fecal ¹⁵N. Due to missing values an unstructured linear mixed model was applied using treatment as fixed effect. P-values refer to Friedman tests.</p

Scatter plot in which cytotoxicity (IC50) is plotted against urinary p-cresol excretion (mg/24 h).

<p>The plot shows a negative correlation between both parameters (Spearman’s r = −0.435, p = 0.001).</p

Scatter plot of the comparison between urinary p-cresol excretion (mg/24 h) and absolute protein intake (g/24 h).

<p>Urinary p-cresol excretion correlated positively with absolute protein intake (Spearman’s r = 0.371, p = 0.007).</p

Summary of dietary records and validating measures in urine.

<p>All values are expressed as medians (IQR) (n = 20). Parameters with different letters (a, b, c) in superscript are significantly different between the dietary interventions, test. Friedman and Wilcoxon tests were used to evaluate the results, except for urinary N and urea. Due to missing, values an unstructured linear mixed model was applied using treatment as fixed effect. P-values refer to Friedman tests.</p

Integrated miRNA and mRNA Expression Profiling in Inflamed Colon of Patients with Ulcerative Colitis

<div><p>Background</p><p>Ulcerative colitis (UC) is associated with differential colonic expression of genes involved in immune response (e.g. <i>IL8</i>) and barrier integrity (e.g. cadherins). MicroRNAs (miRNAs) are regulators of gene expression and are involved in various immune-related diseases. In this study, we investigated (1) if miRNA expression in UC mucosa is altered and (2) if any of these changes correlate with mucosal mRNA expression. Integration of mRNA and miRNA expression profiling may allow the identification of functional links between dysregulated miRNAs and their target mRNA.</p><p>Methodology</p><p>Colonic mucosal biopsies were obtained from 17 UC (10 active and 7 inactive) patients and 10 normal controls. Total RNA was used to analyze miRNA and mRNA expression via Affymetrix miRNA 2.0 and Affymetrix Human Gene 1.0ST arrays, respectively. Both miRNA and gene expression profiles were integrated by correlation analysis to identify dysregulated miRNAs with their corresponding predicted target mRNA. Microarray data were validated with qRT-PCR. Regulation of <i>IL8</i> and <i>CDH11</i> expression by hsa-miR-200c-3p was determined by luciferase reporter assays.</p><p>Results</p><p>When comparing active UC patients <i>vs.</i> controls, 51 miRNAs and 1543 gene probe sets gave significantly different signals. In contrast, in inactive UC <i>vs.</i> controls, no significant miRNA expression differences were found while 155 gene probe sets had significantly different signals. We then identified potential target genes of the significantly dysregulated miRNAs and genes in active UC <i>vs.</i> controls and found a highly significant inverse correlation between hsa-miR-200c-3p and <i>IL8</i>, an inflammatory marker, and between hsa-miR-200c-3p and <i>CDH11</i>, a gene related to intestinal epithelial barrier function. We could demonstrate that hsa-miR-200c-3p directly regulates <i>IL8</i> and <i>CDH11</i> expression.</p><p>Conclusion</p><p>Differential expression of immune- and barrier-related genes in inflamed UC mucosa may be influenced by altered expression of miRNAs. Integrated analysis of miRNA and mRNA expression profiles revealed hsa-miR-200c-3p for use of miRNA mimics as therapeutics.</p></div

Heatmap of mRNA expression in mucosal colonic biopsies of UC patient and control cohorts.

<p>Unsupervised hierarchical clustering of all samples based on the log2 expression values of the top 20 most variable mRNAs. Samples are shown in the columns and mRNAs in the rows. The boxes in color indicate the log2 intensities of the mRNAs, with blue indicating low expression and yellow indicating high expression.</p