Modulation of faecal metagenome in Crohn’s disease: Role of microRNAs as biomarkers

Figure 1 Ecological and metagenomic analysis. A: Number of readings for each sample using the 16S massive sequencing technique in GS Junior. See methods section for details. B: Principal components analysis. The control samples and Crohn’s disease are observed in well-defined groups. The data was selected with the Ribosomal Project database using a maximum e-value of 10^-5, a minimum identity of 75%, and a minimum length alignment of 15 bp. PC: Principal components; CD: Crohn’s disease sample.

Figure 2 Box plot showing a significant difference in the Clostridia class between control group (blue) and Crohn’ disease (green).

Figure 3 Bar graph with the mean of each group (Crohn’s disease and control population) and family taxon (95% confidence level).

Figure 4 Bar chart with the mean of each taxonomic group (gender) according to group (control vs Crohn’s disease) and differences with 95% confidence level.

Figure 5 Functional analysis of the microbiota. Significant differences (P < 0.05) in biosynthesis and glycan metabolism, carbohydrate metabolism, lipid metabolism, catabolism, digestive system, amino acid metabolism and immune system were found. C: Control sample; CD: Crohn’s disease sample.

Figure 6 Three microRNAs were found increased in samples from patients with Crohn’s disease. Individual microRNA levels in 10 patients with Crohn’s disease are represented. miRNA: MicroRNA.