Relationship between microbiota of the colonic mucosa vs feces and symptoms, colonic transit, and methane production in female patients with chronic constipation
Open accessAbstract
Background & aims In fecal samples from patients with chronic constipation, the microbiota differs from that of healthy subjects. However, the profiles of fecal microbiota only partially replicate those of the mucosal microbiota. It is not clear whether these differences are caused by variations in diet or colonic transit, or are associated with methane production (measured by breath tests). We compared the colonic mucosal and fecal microbiota in patients with chronic constipation and in healthy subjects to investigate the relationships between microbiota and other parameters.Methods Sigmoid colonic mucosal and fecal microbiota samples were collected from 25 healthy women (controls) and 25 women with chronic constipation and evaluated by 16S ribosomal RNA gene sequencing (average, 49,186 reads/sample). We assessed associations between microbiota (overall composition and operational taxonomic units) and demographic variables, diet, constipation status, colonic transit, and methane production (measured in breath samples after oral lactulose intake).Results Fourteen patients with chronic constipation had slow colonic transit. The profile of the colonic mucosal microbiota differed between constipated patients and controls (P < .05). The overall composition of the colonic mucosal microbiota was associated with constipation, independent of colonic transit (P < .05), and discriminated between patients with constipation and controls with 94% accuracy. Genera from Bacteroidetes were more abundant in the colonic mucosal microbiota of patients with constipation. The profile of the fecal microbiota was associated with colonic transit before adjusting for constipation, age, body mass index, and diet; genera from Firmicutes (Faecalibacterium, Lactococcus, and Roseburia) correlated with faster colonic transit. Methane production was associated with the composition of the fecal microbiota, but not with constipation or colonic transit.Conclusions After adjusting for diet and colonic transit, the profile of the microbiota in the colonic mucosa could discriminate patients with constipation from healthy individuals. The profile of the fecal microbiota was associated with colonic transit and methane production (measured in breath), but not constipation.
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Among adults with chronic constipation, the overall makeup of colonic mucosa-associated microbiota separated patients from controls regardless of transit time.
“In a study of adults with chronic constipation, overall composition of the colonic mucosa-associated microbiota could discriminate patients with constipation from control subjects independent of transit time157.”
From The gut Microbiome in adult and pediatric functional gastrointestinal disorders (2019) · cites this paper as [157]
Altered mucosal and fecal microbiota have been linked to chronic constipation in the evidence.
“There is evidence supporting an association between the altered mucosal and fecal microbiota and chronic constipation156, 157.”
From The gut Microbiome in adult and pediatric functional gastrointestinal disorders (2019) · cites this paper as [157]
Metabolites of various gut microbiota, especially bacteria attached to the intestinal mucosa, cause intestinal smooth muscle contraction.
“The other explanation is that the ref lexivity of metabolites of various gut microbiota (especially the bacteria attached to the intestinal mucosa) causes intestinal smooth muscle contraction [14,17].”
From Chronic constipation and gut microbiota: current research insights and therapeutic implications (2024) · cites this paper as [17]
The gut microbiota can regulate the expression of genes involved in intestinal peristalsis.
“One explanation suggests that the gut microbiota can regulate the expression of genes involved in intestinal peristalsis.”
From Chronic constipation and gut microbiota: current research insights and therapeutic implications (2024) · cites this paper as [17]
When SCFA concentration surpasses a certain threshold, SCFAs stimulate electrolyte absorption, inhibit mucin secretion, and lead to the occurrence and development of constipation.
“When the concentration of SCFAs surpasses a certain threshold, they can stimulate electrolyte absorption, inhibit the secretion of mucin, and lead to the occurrence and development of constipation;”
From Chronic constipation and gut microbiota: current research insights and therapeutic implications (2024) · cites this paper as [17]
SCFAs, especially butyric acid, exhibit a biphasic effect on the secretion of mucin by colonic epithelial cells.
“SCFAs, especially butyric acid, exhibit a biphasic effect on the secretion of mucin by colonic epithelial cells.”
From Chronic constipation and gut microbiota: current research insights and therapeutic implications (2024) · cites this paper as [17]
Conversely, SCFAs can stimulate mucin secretion, regulate the neurochemical phenotype, and enhance the excitability of choline acetyltransferase-positive neurons, thereby improving constipation.
“conversely, they can stimulate mucin secretion, regulate the neurochemical phenotype, and enhance the excitability of choline acetyltransferase-positive neurons, thereby improving constipation [17,33,34].”
From Chronic constipation and gut microbiota: current research insights and therapeutic implications (2024) · cites this paper as [17]
In patients with functional constipation, methane production was associated with the gut microbial composition, but not with constipation or colonic transit.
“On the other hand, one study reported that in patients with FC, methane production was associated with the gut microbial composition, but not with constipation or colonic transit [ 77 ].”
From Role of gut microbiota in functional constipation (2021) · cites this paper as [77]
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- Authors
- Parthasarathy, G., Chen, J., Chen, X., Chia, N., O'Connor, H. M., Wolf, P. G., Gaskins, H. R., & Bharucha, A. E.
- Affiliations
- Mayo Clinic (US)
- University of Illinois Urbana-Champaign (US)
- Corresponding author
- Bharucha, Adil E.
- ORCID
- Venue
- Gastroenterology
- Publisher
- Elsevier BV
- Published
- 2016-02
- Volume
- 150
- Issue
- 2
- Pages
- 367-379.e1
- ISSN
- 0016-5085 (ISSN-L)
- PMC
- PMC4727996
- OpenAlex
- W1915385926
- Cited by
- 396
- References
- 66
- Citations by year
- 2026: 22 · 2025: 37 · 2024: 51 · 2023: 52 · 2022: 60 · 2021: 41 · 2020: 44 · 2019: 37 · 2018: 20 · 2017: 21 · 2016: 9 · 2015: 1
- FWCI
- 17.64
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Gastroenterology (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- U.S. Department of Health and Human Services
- National Institutes of Health (UL1TR000135, TR000135)
- National Cancer Institute (R01CA179243)
- National Institute of Diabetes and Digestive and Kidney Diseases (R01 DK78924, R01DK078924, P30DK084567)
- National Center for Advancing Translational Sciences (TR000135)
- Topics
- Health Sciences › Medicine › Gastroenterology › Gastrointestinal motility and disorders
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
- Health Sciences › Medicine › Epidemiology › Microscopic Colitis
- Keywords
- chronic constipation, fecal microbiota, colonic transit, methane production, breath test, Bacteroidetes, Firmicutes, Faecalibacterium, Roseburia, Lactococcus, women, 16S rRNA gene sequencing
- MeSH terms
- Gastrointestinal Microbiome, Adult, Algorithms, Bacteria, Breath Tests, Chronic Disease, Colon, Constipation, Feces, Female, Gastrointestinal Transit, Humans, Intestinal Mucosa, Methane, Middle Aged, Phylogeny, Multivariate Analysis, Case-Control Studies, Nonlinear Dynamics, Ribotyping
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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