Diarrhoea-predominant irritable bowel syndrome distinguishable by 16S rRNA gene phylotype quantification - PubMed (original) (raw)

Diarrhoea-predominant irritable bowel syndrome distinguishable by 16S rRNA gene phylotype quantification

Anna Lyra et al. World J Gastroenterol. 2009.

Abstract

Aim: To study whether selected bacterial 16S ribosomal RNA (rRNA) gene phylotypes are capable of distinguishing irritable bowel syndrome (IBS).

Methods: The faecal microbiota of twenty volunteers with IBS, subdivided into eight diarrhoea-predominant (IBS-D), eight constipation-predominant (IBS-C) and four mixed symptom-subtype (IBS-M) IBS patients, and fifteen control subjects, were analysed at three time-points with a set of fourteen quantitative real-time polymerase chain reaction assays. All assays targeted 16S rRNA gene phylotypes putatively associated with IBS, based on 16S rRNA gene library sequence analysis. The target phylotypes were affiliated with Actinobacteria, Bacteroidetes and Firmicutes. Eight of the target phylotypes had less than 95% similarity to cultured bacterial species according to their 16S rRNA gene sequence. The data analyses were made with repeated-measures ANCOVA-type modelling of the data and principle component analysis (PCA) with linear mixed-effects models applied to the principal component scores.

Results: Bacterial phylotypes Clostridium cocleatum 88%, Clostridium thermosuccinogenes 85%, Coprobacillus catenaformis 91%, Ruminococcus bromii-like, Ruminococcus torques 91%, and R. torques 93% were detected from all samples analysed. A multivariate analysis of the relative quantities of all 14 bacterial 16S rRNA gene phylotypes suggested that the intestinal microbiota of the IBS-D patients differed from other sample groups. The PCA on the first principal component (PC1), explaining 30.36% of the observed variation in the IBS-D patient group, was significantly altered from all other sample groups (IBS-D vs control, P = 0.01; IBS-D vs IBS-M, P = 0.00; IBS-D vs IBS-C, P = 0.05). Significant differences were also observed in the levels of distinct phylotypes using relative values in proportion to the total amount of bacteria. A phylotype with 85% similarity to C. thermosuccinogenes was quantified in significantly different quantities among the IBS-D and control subjects (-4.08 +/- 0.90 vs -3.33 +/- 1.16, P = 0.04) and IBS-D and IBS-M subjects (-4.08 +/- 0.90 vs -3.08 +/- 1.38, P = 0.05). Furthermore, a phylotype with 94% similarity to R. torques was more prevalent in IBS-D patients' intestinal microbiota than in that of control subjects (-2.43 +/- 1.49 vs -4.02 +/- 1.63, P = 0.01). A phylotype with 93% similarity to R. torques was associated with control samples when compared with IBS-M (-2.41 +/- 0.53 vs -2.92 +/- 0.56, P = 0.00). Additionally, a R. bromii-like phylotype was associated with IBS-C patients in comparison to control subjects (-1.61 +/- 1.83 vs -3.69 +/- 2.42, P = 0.01). All of the above mentioned phylotype specific alterations were independent of the effect of time.

Conclusion: Significant phylotype level alterations in the intestinal microbiotas of IBS patients were observed, further emphasizing the possible contribution of the gastrointestinal microbiota in IBS.

Keywords: 16S ribosomal RNA; Diarrhoea-predominant irritable bowel syndrome; Intestinal microbiota; Irritable bowel syndrome; Quantitative real-time polymerase chain reaction.

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Figures

Figure 1

Figure 1

Principal component analysis (PCA) of fourteen 16S rRNA phylotypes quantified from faecal samples of irritable bowel syndrome (IBS) patients and healthy volunteers. A: The PCA plot with outermost data points within each sample group is outlined. The control samples are presented in green, the constipation-predominant IBS (IBS-C) in black, the diarrhoea-predominant IBS (IBS-D) in red and the mixed symptom-subtype IBS (IBS-M) in blue. Each time-point is presented as a separate point. To quantify the multivariate differences between the groups, linear mixed-effects models were applied to the first (x-axis) and the second (y-axis) principal component scores, which represent the dominant multivariate changes present in the data; B: The bars represent the relative contribution of each quantitative real-time PCR (qPCR) assay to the principal component 1 (PC1). On PC1 the IBS-D samples differed from the control (P ≤ 0.01), IBS-M (P ≤ 0.01), and IBS-C (P ≤ 0.05) samples; C: The bars represent the relative contribution of each qPCR assay to the principal component 2 (PC2). On PC2, the IBS-C patients diverged from the control subjects (P ≤ 0.05) and time-points. In addition, the second time-point (3 mo) diverged significantly from the first (0 mo, P ≤ 0.01) and the third (6 mo, P ≤ 0.01) time-points independent of sample group; The height of the bars in graphs in Figure 1B and C reflect the relative magnitude of the contribution and the direction the sign of the contribution (in relation to the other assays and to the axis in Figure 1A). For example, in PC1 (Figure 1B), the largest contributor is the Coprococcus eutactus 97% phylotype, while the samples on the right in Figure 1A (mostly IBS-D) tend to have higher concentrations of Ruminococcus torques 94% and lower concentrations of phylotypes with bars highly on the negative side. Similarly, on PC2 (Figure 1C) the samples with high PC2 value in the top part of the Figure 1A tend to have higher concentrations of the _Ruminococcus bromii_-like phylotype, and lower concentrations of the _Bifidobacterium catenulatum/Bifidobacterium pseudocatenulatum_-like phylotype. On PC2, the IBS-C patients diverged from the control subjects (P ≤ 0.05) and time-points. In addition, the second time-point (3 mo) diverged significantly from the first (0 mo, P ≤ 0.01) and the third (6 mo, P ≤ 0.01) time-points independent of sample group. qPCR: Quantitative real-time polymerase chain reaction; IBS-C: Constipation-predominant irritable bowel syndrome; IBS-D: Diarrhoea-predominant irritable bowel syndrome; IBS-M: Mixed-subtype irritable bowel syndrome.

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