Impact of Agaricus bisporus Mushroom Consumption on Gut Health Markers in Healthy Adults

Study information

Reviewed Marked as Reviewed by Shaimaa Elsafoury on 2021/02/09

study design

randomized controlled trial

Citation

PMID PubMed identifier for scientific articles.

30279332

DOI Digital object identifier for electronic documents.

10.3390/nu10101402

URI

Authors

Hess J, Wang Q, Gould T, Slavin J

Journal

Nutrients

Year

2018

Keywords:

fiber, gut health, laxation, microbiota, mushrooms, prebiotic

Eating Agaricus bisporus mushrooms may impact gut health, because they contain known prebiotics. This study assessed mushroom consumption compared to meat on gastrointestinal tolerance, short chain fatty acid (SCFA) production, laxation, and fecal microbiota. A randomized open-label crossover study was conducted in healthy adults (n = 32) consuming protein-matched amounts of mushrooms or meat twice daily for ten days. Breath hydrogen measures were taken on day one, and gastrointestinal tolerance was evaluated throughout treatments. Fecal sample collection was completed days 6⁻10, and samples were assessed for bacterial composition, SCFA concentrations, weight, pH, and consistency. There were no differences in breath hydrogen, stool frequency, consistency, fecal pH, or SCFA concentrations between the two diets. The mushroom diet led to greater overall gastrointestinal symptoms than the meat diet on days one and two. The mushroom-rich diet resulted in higher average stool weight (p = 0.002) and a different fecal microbiota composition compared to the meat diet, with greater abundance of Bacteroidetes (p = 0.0002) and lower abundance of Firmicutes (p = 0.0009). The increase in stool weight and presence of undigested mushrooms in stool suggests that mushroom consumption may impact laxation in healthy adults. Additional research is needed to interpret the health implications of fecal microbiota shifts with mushroom feeding.

Experiment 1

Edit History Delete

Flag for review

Your review change was submittedDuplicate this Experiment Add a new Signature

Reviewed Marked as Reviewed by Shaimaa Elsafoury on 2021/02/09

Curated date: 2021/01/10

Curator: WikiWorks

Revision editor(s): WikiWorks

Subjects

Location of subjects: United States of America

Host species Species from which microbiome was sampled (if applicable): Homo sapiens

Body site Anatomical site where microbial samples were extracted from according to the Uber Anatomy Ontology: Feces Cow dung,Cow pat,Droppings,Dung,Excrement,Excreta,Faeces,Fecal material,Fecal matter,Fewmet,Frass,Guano,Matières fécales@fr,Merde@fr,Ordure,Partie de la merde@fr,Piece of shit,Porción de mierda@es,Portion of dung,Portion of excrement,Portion of faeces,Portion of fecal material,Portion of fecal matter,Portion of feces,Portion of guano,Portion of scat,Portionem cacas,Scat,Spoor,Spraint,Stool,Teil der fäkalien@de,Feces

Condition The experimental condition / phenotype studied according to the Experimental Factor Ontology: diet Dietary,Diets,diet

Group 0 name Corresponds to the control (unexposed) group for case-control studies: mushroom
Group 1 name Corresponds to the case (exposed) group for case-control studies: Meat
Group 0 sample size Number of subjects in the control (unexposed) group: 16
Group 1 sample size Number of subjects in the case (exposed) group: 16
Antibiotics exclusion Number of days without antibiotics usage (if applicable) and other antibiotics-related criteria used to exclude participants (if any): 3 months

Lab analysis

Sequencing type: 16S

16S variable region One or more hypervariable region(s) of the bacterial 16S gene: V1-V3

Sequencing platform Manufacturer and experimental platform used for quantifying microbial abundance: Illumina

Statistical Analysis

Statistical test: Linear Regression

Significance threshold p-value or FDR threshold used for differential abundance testing (if any): 0.004
MHT correction Have statistical tests be corrected for multiple hypothesis testing (MHT)?: Yes
Confounders controlled for Confounding factors that have been accounted for by stratification or model adjustment: age, sex, body mass index