Effects of bowel preparation on intestinal bacterial associated urine and faecal metabolites and the associated faecal microbiome.

BACKGROUND: Urinary and faecal metabolic profiling have been extensively studied in gastrointestinal diseases as potential diagnostic markers, and to enhance our understanding of the intestinal microbiome in the pathogenesis these conditions. The impact of bowel cleansing on the microbiome has been investigated in several studies, but limited to just one study on the faecal metabolome. AIM: To compare the effects of bowel cleansing on the composition of the faecal microbiome, and the urine and faecal metabolome. METHODS: Urine and faecal samples were obtained from eleven patients undergoing colonoscopy at baseline, and then at day 3 and week 6 after colonoscopy. 16S rRNA gene sequencing was used to analyse changes in the microbiome, and metabonomic analysis was performed using proton nuclear magnetic resonance (1H NMR) spectroscopy. RESULTS: Microbiomic analysis demonstrated a reduction in alpha diversity (Shannon index) between samples taken at baseline and three days following bowel cleansing (p = 0.002), and there was no significant difference between samples at baseline and six weeks post colonoscopy. Targeted and non-targeted analysis of urinary and faecal bacterial associated metabolites showed no significant impact following bowel cleansing. CONCLUSIONS: Bowel cleansing causes a temporary disturbance in bacterial alpha diversity measured in faeces, but no significant changes in the faecal and urine metabolic profiles, suggesting that overall the faecal microbiome and its associated metabolome is resistant to the effects of an induced osmotic diarrhoea.

Analysis of Exhaled Breath Volatile Organic Compounds in Inflammatory Bowel Disease: A Pilot Study.

BACKGROUND AND AIMS: Distinguishing between the inflammatory bowel diseases [IBD], Crohn's disease [CD] and ulcerative colitis [UC], is important for determining management and prognosis. Selected ion flow tube mass spectrometry [SIFT-MS] may be used to analyse volatile organic compounds [VOCs] in exhaled breath: these may be altered in disease states, and distinguishing breath VOC profiles can be identified. The aim of this pilot study was to identify, quantify, and analyse VOCs present in the breath of IBD patients and controls, potentially providing insights into disease pathogenesis and complementing current diagnostic algorithms. METHODS: SIFT-MS breath profiling of 56 individuals [20 UC, 18 CD, and 18 healthy controls] was undertaken. Multivariate analysis included principal components analysis and partial least squares discriminant analysis with orthogonal signal correction [OSC-PLS-DA]. Receiver operating characteristic [ROC] analysis was performed for each comparative analysis using statistically significant VOCs. RESULTS: OSC-PLS-DA modelling was able to distinguish both CD and UC from healthy controls and from one other with good sensitivity and specificity. ROC analysis using combinations of statistically significant VOCs [dimethyl sulphide, hydrogen sulphide, hydrogen cyanide, ammonia, butanal, and nonanal] gave integrated areas under the curve of 0.86 [CD vs healthy controls], 0.74 [UC vs healthy controls], and 0.83 [CD vs UC]. CONCLUSIONS: Exhaled breath VOC profiling was able to distinguish IBD patients from controls, as well as to separate UC from CD, using both multivariate and univariate statistical techniques.