Edited by: Marloes Dekker Nitert, The University of Queensland, Australia
Reviewed by: Muriel Derrien, Nutricia Research (France), France; Claudio Cermelli, University of Modena and Reggio Emilia, Italy
*Correspondence: Lisa Vork,
This article was submitted to Microbiome in Health and Disease, a section of the journal Frontiers in Cellular and Infection Microbiology
†These authors have contributed equally to this work
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Stool consistency has been associated with fecal microbial composition. Stool consistency often varies over time, in subjects with and without gastrointestinal disorders, raising the question whether variability in the microbial composition should be considered in microbiota studies. We evaluated within-subject day-to-day variability in stool consistency and the association with the fecal microbiota in irritable bowel syndrome (IBS) and healthy subjects, over seven days.
Twelve IBS patients and 12 healthy subjects collected fecal samples during seven consecutive days. Stool consistency was determined by the patient-reported Bristol Stool Scale (BSS) and fecal dry weight percentage. 16S rRNA V4 gene sequencing was performed and microbial richness (alpha diversity; Chao1 index, observed number of species, effective Shannon index) and microbial community structure (beta diversity; Bray-Curtis distance, generalized UniFrac, and taxa abundance on family level) were determined.
Linear mixed-effects models showed significant associations between stool consistency and microbial richness, but no time effect. This implies that between-subject but not within-subject variation in microbiota over time can partially be explained by variation in stool consistency. Redundancy analysis showed a significant association between stool consistency and microbial community structure, but additional linear mixed-effects models did not demonstrate a time effect on this.
This study supports an association between stool consistency and fecal microbiota, but no effect of day-to-day fluctuations in stool consistency within seven days. This consolidates the importance of considering stool consistency in gut microbiota research, though confirms the validity of single fecal sampling to represent an individual’s microbiota at a given time point. NCT00775060.
Over the past decades, the gut microbiota has been studied extensively in the context of gastrointestinal (GI) function in health and disease. Stool consistency measured with the Bristol Stool Scale (BSS) or fecal moisture has been associated with gut microbiota diversity and composition (
While stool consistency can fluctuate from day to day in healthy subjects, fluctuations are often more pronounced in subjects with irritable bowel syndrome (IBS), a GI disorder characterized by abdominal pain and altered bowel habits. According to the Rome criteria, IBS is typically divided into four subtypes, often defined by BSS: diarrhea predominant (IBS-D), constipation predominant (IBS-C), a combination of both (IBS-M; mixed type), or unspecified in which both diarrhea and constipation are not predominantly present (IBS-U) (
So far, a few studies have focused on temporal (in)stability of the fecal microbiota and found a more unstable microbial composition in IBS patients compared to healthy volunteers over a period of months (
Therefore, we aimed to evaluate within-subject day-to-day variability in stool consistency and gastrointestinal symptoms, and the association with the fecal microbiota composition in IBS and healthy subjects, over a seven-day course.
This study was embedded in the Maastricht IBS Cohort. The study protocol has been approved by the Maastricht University Medical Center+ (MUMC+) Committee of Ethics (METC 08-2-066) and was executed according to the revised Declaration of Helsinki (64th WMA General Assembly, Brazil 2013). The study has been registered in the US National Library of Medicine (
Between January 2015 and March 2016, IBS patients aged 18-75 years were recruited at the outpatient department of Gastroenterology-Hepatology of MUMC+. All subjects fulfilled the Rome III criteria and were assigned to IBS subtypes based on predominant bowel habits (
Age- and sex-matched healthy controls (HC) were recruited
A seven-day symptom diary was used to record daily symptom scores and bowel habits using BSS [
The first fecal samples of each day, and one additional sample when subjects reported diarrhea, were collected. Subjects stored the samples at -20°C at home directly after collection. Following the seven-day study period, all samples were transported to MUMC+ on dry ice and stored at -80°C.
In addition to the BSS, the dry weight content of each fecal sample was determined, as a more objective measure of stool consistency. Therefore, an aliquot of 0.5 g (
Fecal microbiota profiling was achieved by next-generation sequencing of 16S rRNA V4-region gene amplicons. Detailed information on DNA extraction, sequencing, and data analysis can be found under
All statistical analyses were performed using QIIME version 1.9.1 and R version 3.4.2. Categorical patient characteristics are presented as proportions and differences between groups were tested using χ2 or Fisher’s exact test. Continuous characteristics are presented as mean and standard deviation (SD) or median with interquartile range in case of skewness. Differences between groups were tested using the independent t-test or the Mann-Whitney U test, depending on the normality of the distribution.
Alpha diversity data are expressed as Chao1 index, observed species, and effective Shannon index (exp[Shannon index]). To evaluate the within-subject variability in alpha diversity over time, inter-item (Pearson) correlations between the consecutively collected fecal samples, as well as intra-class correlations (ICC), were calculated for IBS and healthy subjects separately. Data from subjects that collected at least five consecutive samples were included in these analyses. The Bray-Curtis distance and generalized UniFrac (
To evaluate the correlation between stool consistency and the microbiota, a constrained redundancy analysis (RDA) was carried out, using routines from R package “vegan”. The zeros from the count data (summarized on family level) were imputed using R package “zCompositions” and data were clr (centered log ratio) transformed. In addition, two-level mixed-effects linear regression models (level 1: consecutive stool samples; level 2: subjects) were used to examine the association between stool consistency and microbiota using all longitudinal measurements. Separate models were used for different measures of microbial diversity and composition, with alpha diversity indices and clr transformed taxonomical abundance data (family level), respectively, as the dependent variables. The two-way interaction term “stool consistency*time” and stool consistency were used as independent variables and a random intercept was chosen to correct for clustering of multiple measurements within each participant. A p-value of ≤0.05 was considered statistically significant.
In all analyses, stool consistency was primarily based on fecal dry weight percentage, and additional analyses were performed using BSS.
Twelve IBS patients and 12 healthy subjects were included. Demographics are shown in
Demographic characteristics.
Healthy (n=12) | IBS (n=12) | |
---|---|---|
|
10 (83.3) | 10 (83.3) |
|
36.78 [30.09 – 47.19] | 45.0 [35.37 – 48.56] |
|
21.99 [21.80 – 23.25] | 23.65 [22.65 – 24.57] |
|
0 (0) | 4 (33.3) |
|
6 (50) | 7 (58.3) |
|
||
1 | - | - |
2 | - | 1 (8.3) |
3 | - | - |
4 | 1 (8.3) | - |
5 | - | 4 (33.3) |
6 | 4 (33.3) | 2 (16.7) |
7 | 6 (50.0) | 3 (25.0) |
8 | 1 (8.3) | 2 (16.7) |
|
||
Abdominal Pain | 1.67 [1.08-2.25] | 3.33 [2.00-4.67]$ |
Regurgitation Syndrome | 1.00 [1.00-1.00] | 2.50 [1.00-3.50]# |
Diarrhea Syndrome | 1.00 [1.00-1.33] | 3.33 [1.00-1.33]$ |
Indigestion Syndrome | 1.75 [1.50-2.50] | 4.75 [3.75-5.13]$ |
Constipation Syndrome | 1.67 [1.00-1.92] | 3.33 [2.33-4.67]$ |
|
||
PPI | - | 3 (25) |
NSAID | - | - |
Prokinetic | - | - |
Spasmolytic | - | 2 (16.7) |
Laxative | - | 1 (8.3) |
Antidiarrheal | - | - |
Antibiotic | - | - |
Probiotic | - | - |
Prebiotic | - | - |
Other | 7 (58.3) | 7 (58.3) |
Differences tested using Mann-Whitney U test for continuous data and χ2- or Fisher’s exact test for categorical data. Significances are shown for IBS versus healthy. *p < 0.05; #p < 0.01; $p < 0.001.
1Less than one fecal sample per day was collected in case of absence of bowel movement; more than one fecal sample per day was collected in case of diarrhea.
The day-to-day variability in stool consistency, measured by fecal dry weight percentage, was found to be high in the IBS group (ICC: 0.223) and moderate (ICC: 0.622) in the healthy population. BSS scores showed high day-to-day variability in both groups (ICC for IBS: 0.397; ICC for HC: 0.276). This variability in stool consistency is illustrated in
The predominant phyla in both healthy and IBS subjects were Firmicutes (average relative abundance of 79.5% and 81.9%, respectively), followed by Bacteroidetes, Actinobacteria, Verrucomicrobia, and Proteobacteria (
For both IBS and healthy subjects, microbial richness showed high correlations between subsequent samples, demonstrating low within-subject variability from day to day. Inter-item correlations between different samples were all above 0.800 and a high degree of agreement in microbial richness was found between the different samples of one subject (single measure ICCs all above 0.893). Inter-item matrices and ICCs for Chao1 index are shown in
Inter-item (Pearson) correlations between Chao1-index of consecutive samples, for healthy subjects and IBS patients.
Chao1 index | HEALTHY SUBJECTS | IBS PATIENTS | ||||||
---|---|---|---|---|---|---|---|---|
Intraclass Correlations Coefficient = 0.940 | Intraclass Correlations Coefficient = 0.893 | |||||||
Sample 1 | Sample 2 | Sample 3 | Sample 4 | Sample 1 | Sample 2 | Sample 3 | Sample 4 | |
|
0.967 | 0.923 | ||||||
|
0.866 | 0.922 | 0.870 | 0.882 | ||||
|
0.972 | 0.954 | 0.907 | 0.853 | 0.910 | 0.908 | ||
|
0.946 | 0.989 | 0.936 | 0.925 | 0.916 | 0.895 | 0.916 | 0.915 |
The microbial community structure clustered per individual, suggesting that the dissimilarity in microbiota between consecutive samples is larger between than within subjects, while no clear separation between IBS and healthy subjects was demonstrated (
A linear mixed-effects model with the Chao1 index as dependent variable demonstrated no significant effect of the two-way interaction “fecal dry weight*time” on microbial richness (B: 0.030, SE: 0.072, p=0.676), indicating that the association between stool consistency and microbial richness was not different between subsequent samples. After removal of this term from the model, stool consistency was found to be a significant predictor of microbial richness (B: 1.231, SE: 0.200, p<0.001) (
Results of linear mixed-effects models.
Dependent variable | Predictor | Regression coefficient [95%-CI] | SE | p-value |
---|---|---|---|---|
|
Fecal dry weight*time | 0.030 [-0.113; 0.173] | 0.072 | 0.676 |
Fecal dry weight1 | 1.231 [0.835;1.628] | 0.200 | <0.001 | |
BSS*time | 0.135 [-0.710; 0.980] | 0.426 | 0.752 | |
BSS1 | -2.518 [-4.728; -0.308] | 1.116 | 0.026 | |
Abdominal pain*time | -0.034 [-0.436; 0.368] | 0.203 | 0.869 | |
Abdominal pain1 | 0.473 [-1.188; 2.135] | 0.839 | 0.574 | |
Abdominal bloating*time | 0.471 [-0.019; 0.962] | 0.248 | 0.059 | |
Abdominal bloating1 | 0.182 [-1.572; 1.937] | 0.886 | 0.837 |
Linear mixed-effects models with random intercept, fixed slopes, and scaled identity covariance structure. Regression coefficient indicates the direction and strength of the association between the predictor and dependent variable.
1Insignificant interaction terms, respectively, “fecal dry weight*time”, “BSS*time” “abdominal pain*time”, and “abdominal bloating*time” were removed from the models. BSS, Bristol Stool Scale; SE, standard error.
A redundancy analysis, including data from both IBS and healthy subjects, showed a significant association between stool consistency and microbial composition on the family level, mainly driven by
Redundancy analysis plot based on clr transformed abundancies, and constrained on stool consistency (dry weight percentage), with individual variation partialled-out. Significant association between stool consistency and microbial composition (p = 0.001), mainly driven by bacterial families depicted in the figure.
Exploratory analysis showed no significant association between the fecal microbiota (
Redundancy analysis plot based on clr transformed abundancies, and constrained on individual, abdominal pain, and abdominal bloating. Each dot represents an individual sample; IBS patients are depicted by different colors. No significant association between both GI symptoms (p = 0.368 for abdominal pain; p = 0.521 for bloating) and microbial composition.
Previously described strong correlations between stool consistency and the fecal microbiota pointed towards the importance of stool consistency and/or gut transit time as confounding factors in microbiota analyses (
Stool consistency is known to vary within individuals over time (
Previous results on temporal stability of the microbial composition are contradictory. Particularly inter-individual differences have been demonstrated, but less is known about within-subject microbial variability (
We used fecal dry weight percentage and patient-reported BSS scores as measures of stool consistency. From day to day, moderate-to-high levels of variability in both measures were found in both groups. This confirms that our data should be suitable to detect any day-to-day changes in the microbiota related to variability in stool consistency. Previous findings demonstrated that looser stools, according to BSS, were associated with lower species richness (
Since previous studies suggested a link between the microbiota and abdominal symptoms in IBS (
Previous studies also showed rapid changes of microbial composition over the course of several days after dietary changes, especially on animal-based diet (
This is the first study to examine a short-term within-subject association between stool consistency and the gut microbiota, using repeated fecal sampling over one week. Both IBS and healthy subjects were evaluated in order to capture highly fluctuating as well as more stable day-to-day patterns of stool consistency, but this study was not designed to draw any conclusions on differences in the microbial composition between IBS and healthy subjects. Fecal dry weight percentage was used as an objective measure of stool consistency, which might have an advantage over the commonly used Bristol Stool Scale, since the latter was developed as a surrogate marker of whole-gut transit time and is subject to inter-individual differences in interpretation (
A sample size of 24 subjects might be relatively small, but the use of repeated measures increases statistical power (
In conclusion, this study supports an association between stool consistency and the fecal microbiota, but the overall microbial composition was not significantly related to day-to-day fluctuations in stool consistency. This consolidates the importance of considering stool consistency in gut microbiota research, but on the other hand, confirms the validity of the use of single fecal sampling for between-subject comparisons in the context of cross-sectional studies. Likewise, this indicates that in longitudinal studies evaluating within-subject microbial stability over longer periods (
Beate Niesler Chair COST-Action GENIEUR.
Department of Human Molecular Genetics, Institute of Human Genetics, Heidelberg University Hospital, Heidelberg, Germany.
nCounter Core Facility, Institute of Human Genetics, Heidelberg University Hospital, Heidelberg, Germany.
Interdisciplinary Center for Neurosciences (IZN), Heidelberg University, Heidelberg, Germany.
Gerard Clarke Department of Psychiatry and Alimentary Pharmabiotic Centre, University College Cork, Cork, Ireland.
Paul Enck Department of Psychosomatic Medicine and Psychotherapy, University Hospital Tuebingen, T̈übingen, Germany
Natasa Golic Laboratory for Molecular Microbiology, Institute of Molecular Genetics and Genetic Engineering, University of Belgrade, Belgrade, Serbia.
Kurt Hanevik Department of Clinical Science, University of Bergen, Bergen, Norway.
Fuad A. Iraqi Department of Clinical Microbiology and Immunology, Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel.
Elena Philippou Department of Life and Health Sciences, University of Nicosia, Cyprus.
Division of Diabetes and Nutritional Sciences, King’s College London, London, UK.
Jeroen Raes Department of Microbiology and Immunology, KU Leuven, Leuven, Belgium.
Robin C. Spiller Nottingham Digestive Diseases Biomedical Research Unit, University of Nottingham, Queens Medical Centre, Nottingham, UK.
The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below:
The studies involving human participants were reviewed and approved by Medisch-etische toetsingscommissie azM/UM. The patients/participants provided their written informed consent to participate in this study.
Study concept and design: JP, WV, and DJ. Collection study materials: LV and ZW. Data analysis: LV, JJ, SB, SK, AS, MR-S, MP, and CM. Manuscript writing: LV, JP, and DJ. Constructive review of manuscript: JJ, SB, AS, WV, MR-S, ZW, AM, MP, and CM. All authors contributed to the article and approved the submitted version.
This manuscript results in part from collaboration and network activities promoted under the frame of the international network GENIEUR (Genes in Irritable Bowel Syndrome Research Network Europe), which has been funded by the COST program (BM1106,
Part of the work of JP is financed by the Joint Programming Initiative A healthy diet for a healthy life (HDHL) Joint Action Intestinal Microbiomics (project number 50–52905–98–599). WV was partially supported by the SIAM Gravitation Grant 024.002.002 and Spinoza Award of the Netherlands Organization for Scientific Research. MR-S performed consultation services for Hemofarm AD, Serbia. ZW was supported to attend a scientific meeting by Will Pharma S.A. AM has received a ZonMw, The Netherlands Organization for Health Research and Development, health care efficiency grant to evaluate efficacy of peppermint oil in IBS, has received an unrestricted research grant from Will Pharma S.A., and received research funding from Allergan and Grünenthal on IBS topics. AM has given scientific advice to Bayer and Kyowa Kirin related to IBS and constipation, and received funding from Pentax Europe GmBH. Part of the work of CM is supported by the Instituto de Salud Carlos III, grant PI/17/00614 co-financed by the European Regional Development Fund (ERDF). Part of the work of DJ is financed by Grant Top Knowledge Institute (Well on Wheat), the Carbokinietics program as part of the NWO-CCC Partnership program and H2020 Nr. 848228/DISCOvERIE.
The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
The Supplementary Material for this article can be found online at:
Inter-item correlations (Pearson correlations) between observed species of consecutive samples, for healthy subjects and IBS patients separately.
Inter-item correlations (Pearson correlations) between effective Shannon index of consecutive samples, for healthy subjects and IBS patients separately.
Results from linear mixed-effects models (with random intercept, fixed slopes, and scaled identity covariance structure). Regression coefficient indicates the direction and strength of the association between the predictor and dependent variable.
Results from linear mixed-effects models (with random intercept, fixed slopes, and scaled identity covariance structure). Regression coefficient indicates the direction and strength of the association between the predictor and dependent variable.
Stool consistency for each sample and separately for all subjects (
Overview of the microbial composition of IBS and healthy subjects based on relative abundances on the phylum level.
Relative abundances for healthy subjects
Bray Curtis Dissimilarity for days 2-7 compared to day 1 for IBS patients