Sequence data description

Fecal samples were collected from 66 healthy controls and from 113 IBS patients. Of the 179 participants, 94 provided two fecal samples 1-month apart. We therefore analyzed the microbiome of a total of 273 samples, from which we produced 20.5 million high quality sequence reads of 314 bp in length, using the default Quantitative Insights Into Microbial Ecology (QIIME) pipeline parameters and a quality Phred score >20. Additionally, we removed singletons and taxa with very low abundance that could represent false positive taxa, as described in the method section. We finally recovered a total of 14 million sequences with a mean of 48,409 sequences per sample. In order to compare microbial community between samples, we normalized the sequences at 16,800 per sample (fitting to a sample with the lowest sequence number).

Microbiota of the healthy controls

Of the 66 healthy controls, we detected 12 known phyla, 43 families, 84 genera (Supplementary Figure S1) and 2,126 operational taxonomic units (OTUs), with a mean of 629 OTUs (SD = 132) per sample. Firmicutes and Bacteroidetes accounted for 91% of the sequences and Proteobacteria, Verrucomicrobia and Actinobacteria 4.9%. At the family level, 85% of the sequences were assigned, 65% at the genus level and only 0.6 % at the species level. This observation indicates that although databases of 16S rRNA sequences are increasing exponentially, the lack of annotation continues to be a bottleneck for the scientific community. Our findings thus revealed the predominance of Firmicutes in the proportion of sequences per subject and in the proportion of the healthy population. Two OTUs, Faecalibacterium prausnitzii and an unknown Ruminococcaceae, were detected in all individuals and at the two sampling points (88 samples in total), thereby indicating that these OTUs were not only highly prevalent but also stable over time. They were found at the average proportions of 5.3% and 0.23%, respectively.

Level of dysbiosis among IBS patients

At a global level, the microbial communities of healthy controls and patients did not cluster separately, according to Unifrac metrics in a principal coordinate analysis (PCoA, Supplementary Figure S2). However, distance-based redundancy analysis showed that the microbiome of IBS patients, as well as that of IBS subtype patients, clustered separately from that of healthy controls (P = 0.002 and P = 0.001, respectively)(Fig. 1A,B), although only 1 and 3% of the data explained the variation observed in IBS and IBS subtypes, respectively.

Figure 1 Unweighted UniFrac data redundancy analysis on the first time point samples constrained by (A) controls and IBS patients groups and (B) constrained by the four groups of participants: controls (n = 66), IBS-C (n = 32), IBS-D (n = 54) and IBS-M (n = 27). Full size image

Using the Kruskal Wallis test to compare healthy controls (n = 66) with IBS patients (n = 113), dysbiosis was indeed present at various phylogenetic levels. At the phylum level, there is a tendency for IBS patients to harbour a higher average count of Bacteroidetes compared to healthy controls (52.6% versus 42.7%; P = 0.02, q = 0.09) and a lower count of Firmicutes (39.8% versus 49%; P = 0.02, q = 0.09). Furthermore, 41% of IBS patients (versus 50% in healthy subjects) harboured a higher relative abundance of Firmicutes than Bacteroidetes (Fig. 2). Compared to healthy controls, IBS patients also showed a lower count of Tenericutes (P = 0.004; q = 0.05). At the family level, two Firmicutes groups, Erysipelotrichaceae and Ruminococcaceae, were found significantly in a higher proportion in healthy controls than in patients (Fig. 3A) (P = 4.7 e-5, q = 0.002 and P = 0.002, q = 0.06, respectively). At the species level, one OTU from the Lachnobacterium genus (Lachnospiraceae, Firmicutes) differentiated healthy subjects from IBS patients (P = 5.9 e-6, q = 0.04). This OTU, which belongs to the Lachnospiraceae family and the Firmicutes phylum, was detected in 15 out of 66 controls (22%) and in only 2 out of 113 patients (1.7%) at a very low proportion of sequences, 0.0001 and 0.00002 respectively. Faecalibacterium prausnitzii present in all 66 healthy controls, were also detected in at least 95% of the 113 patients and did not show significant differences in abundance. This observation indicates that this bacterium is highly prevalent but probably not involved in IBS, as proposed by others13.

Figure 2 Higher relative abundance of Bacteroidetes. Proportion of Firmicutes and Bacteroidetes are plotted for each healthy subject (A) and for each IBS patient (B). Patients are characterized by a relatively higher proportion of Bacteroidetes than healthy controls (P = 0.02, q = 0.09). Full size image

Figure 3 Higher relative abundance of two bacterial families and higher alpha-diversity in healthy controls compared to IBS patients. (A) Erysipelotrichaceae and Ruminococcaceae were found in significantly higher abundance in healthy subjects (n = 66) compared to IBS patients, regardless of their IBS subtype (Kruskal Wallis test, P = 4.7 e-5, q = 0.002 and P = 0.002, q = 0.06, respectively). The two bacterial families belong to the Firmicutes phylum. (B) The Chao1 index based on species-level OTUs was estimated for healthy controls, IBS, IBS-M, IBS-C and IBS-D. Significance (*P = 0.04, **P < 0.003) was determined by Monte Carlo permutations, a non-parametric test. Full size image

Microbiota and IBS subtypes

The diversity analysis showed that, overall, patients presented a lower diversity of gut microbiota than healthy controls (P < 0.01), especially as a result of a reduction in the diversity of the IBS-D subtype (P < 0.05; Fig. 3B). This result suggests that the microbial species that contribute to maintaining homeostasis may be missing in patients with a diarrheic symptom. Therefore, we compared the microbial communities of healthy participants (n = 66) with those of each IBS subtype using the Kruskal Wallis test. Patients with IBS-D (n = 54) showed dysbiosis at various phylogenetic levels. Figure 4A shows the lower abundant groups at the family (Ruminococcaceae, unknown Clostridiales, Erysipelotrichaceae, Methanobacteriaceae; P < 0.006; q < 0.06) and genus levels (unknown Ruminococcocaceae; P = 0.0001, q = 0.009), respectively.

Figure 4 Dysbiosis at the family and genus level in IBS subtypes. (A) Four microbial families and one genus discriminate the 66 healthy controls from the 54 patients with IBS-D (Kruskal Wallis test, P < 0.006; q < 0.06). (B) One bacterial family was found in a lower proportion in the 27 IBS-M patients compared to the 66 controls (P = 0.0001, q = 0.006). (C) Comparing the healthy control group with the three IBS subtypes, four genera were enriched in healthy subjects and IBS-C patients compared to IBS-M and IBS-D patients (Kruskal Wallis test, P < 0.003, q ≤ 0.05). Full size image

The microbiome of IBS-C patients did not show significant differences at any phylogenetic level with that of healthy controls. However, IBS-M patients, who alternate diarrhea and constipation, were associated with a 4.7-fold lower abundance of Erysipelotrichaceae (P = 0.0001, q = 0.006; Fig. 4B), sharing this difference with IBS-D patients. Our findings suggest that this bacterial group, which is absent in IBS-M and IBS-D, is associated with a non-diarrheic phenotype.

Comparing the healthy control group with the three IBS subtypes, we found that four genera were significantly different between healthy subjects/IBS-C patients and IBS-M/IBS-D patients. Indeed, an unknown Ruminococcaceae, an unknown Christensenellaceae, Akkermansia and Methanobrevibacter were present in a higher proportion in healthy controls and IBS-C patients (P < 0.003, q ≤ 0.05; Fig. 4C).

IBS patients and treatment

Regarding treatment, the inclusion criteria for all participants was only that they had not taken any antibiotics during the 3 months prior to stool collection. However, among the 113 patients with IBS, 69 of them reported following a treatment for IBS symptoms during the study. These treatments included laxatives (n = 13), proton pump inhibitors (n = 25), pre/probiotics (n = 6) (Supplementary Table S2) and other medications, such as anti-depressants or anxiolytic drugs (n = 29). Since medications could have an effect, we explored their potential role on modulating the gut microbiome. For this, we re-analyzed the whole dataset, on the one hand, discarding the patients who were under treatment that could affect the microbiome composition and on the other hand, grouping them according to the treatment type that could directly affect the microbial composition (laxative, proton pump inhibitors, or probiotics/prebiotics) or indirectly (anti-depressants or anxiolytic drugs) affect the microbial composition. We were unable to take into account the effect of other drugs, since the number of patients for each of the drugs was too small and did not allow statistical analysis.

Removing patients who were under treatment that could affect the gut microbiome composition such as laxative, proton pump inhibitors, or probiotics/prebiotics, we re-analyzed a cohort of 73 patients (25 patients with IBS-C, 35 patients with IBS-D, 13 patients with IBS-M). Alpha-diversity analysis using the Chao1 index showed that IBS patients without treatment and without classification in subtypes continued to present a lower diversity of microbes compared to healthy controls (P = 0.002) (Supplementary Figure S3). However, significance was not reached when comparing healthy controls with each of the IBS subtypes and only IBS-D showed a trend towards a lower diversity (P = 0.09). Stability analysis also confirmed that neither the microbiome of healthy controls nor that of the IBS patients as a whole group or as subtypes differed significantly over the one-month sampling period. Distance-based redundancy analysis showed that, although only 3% of the data explained the variation, the microbiome of patients still clustered separately on the basis of their subtypes and also separately from that of the healthy controls (P = 0.001) (Fig. 5). Also, as shown in the data without discarding patients under treatment, we confirmed that Erysipelotrichaceae was in lower relative abundance in patients (P = 0.001; q = 0.04). Ruminococcaceae was also found in lower relative abundance in patients, although the difference was not significant (P = 0.03; q = 0.4). Interestingly, Methanobacteriaceae was in lower abundance (10 fold) in patients with IBS-D and IBS-M compared to healthy controls (P = 0.004; q = 0.05), which was not observed when the patients under treatment were not discarded for the analysis.

Figure 5 Unweighted UniFrac data redundancy analysis (dbRDA) on the first time point samples constrained by (A) the controls and IBS patients and constrained by (B) the four groups of participants: controls (n = 66), IBS-C (n = 14), IBS-D (n = 24) and IBS-M (n = 6), discarding patients under treatment. Full size image

Among the medications, we uncovered a significant effect only for the proton pump inhibitors. Indeed, patients taking proton pump inhibitors such as omeprazole (n = 25), during the study presented a 37-fold higher proportion of Pasteurellales (P = 0.002, q = 0.05), a Gammaproteobacteria group, compared to those who did not receive any treatment. At the genus level, Haemophilus (belonging to Pasteurellaceae) maintained this effect (P = 0.001, q = 0.08). When we compared controls (n = 66) with patients without treatment (n = 44), Methanobacteriales at the class level was also enriched in healthy controls by 10-fold (P = 0.005; q = 0.05) (Fig. 6). This group of microbes remains significantly in higher abundance in controls when compared with IBS-D patients without treatment (n = 24; P = 0.0019; q = 0.038). In the same group of patients, microbes from the Erysipelotrichi also showed a tendency of decrease (P = 0.0019; q = 0.13). IBS-C patients without treatment (n = 14) presented a higher level of Methanomassiliicoccaceae, belonging to methanogenic Archeae (P = 0.0001; q = 0.015). No significant differences were found between healthy subjects and IBS-M patients (n = 6), probably due to a too small sample size.

Figure 6 Methanobacteria from the Euryarchaeota phylum is enriched in controls (n = 66) compared to IBS patients (n = 44) who did not follow any medical treatment (Kruskal Wallis test, P = 0.005, q = 0.05). Full size image

Stability of the microbiota of IBS patients

Previous studies have reported the instability of the gut microbiome of IBS patients as a signature of the disease. Comparing fecal samples from patients (the whole cohort (n = 77) or without patients under treatment (n = 47)) taken one month apart, we did not detect significant differences in the microbial composition between the two time points for the IBS subtypes and as for the 22 healthy controls and no changes in microbiome associated with changes in symptoms, suggesting a stable gut microbiota over a relatively short time, which is in agreement with a previous comprehensive study by Faith et al.22. Indeed, in a previous work, we showed that instability of the gut microbiota was only conditioned by a challenge with diet enriched in fibers23.

Correlation with symptoms

Taking into account only patients who did not take any medication (n = 44), we examined the correlation between microbial composition and IBS symptoms, such as sensation of flatulence and abdominal pain. Subjective sensations of flatulence are defined as anal gas evacuation, abdominal bloating (pressure/fullness), abdominal distension (girth increment), borborygmi and abdominal discomfort/pain, as described in our previous work23. The highest level of sensation of flatulence (level 6 in a scale of 0 to 6) was positively correlated with three OTUs from Lachnospiraceae, one belonging to the Blautia genus (r from 0.40 to 0.48, P < 0.006). The highest level of abdominal pain (level 6 in a scale of 0 to 6) was moderately and positively correlated with three bacterial genera, specifically Bacteroides (r = 0.46, P = 0.002) and Ruminoccocus (r = 0.42, P = 0.004) and an unknown Barnesiellaceae (r = 0.30, P = 0.041). Abdominal pain was also moderately and negatively correlated with three other genera, namely Prevotella (r = −0.44, P = 0.003) and Catenibacterium (r = −0.35, P = 0.019), a genus from the Erysipelotrichaceae family. The latter was also observed in a higher proportion in healthy controls compared to IBS patients.