Dataset Information

Fecal sample collection methods and time of day impact microbiome composition and short chain fatty acid concentrations.

ABSTRACT: Associations between the human gut microbiome and health outcomes continues to be of great interest, although fecal sample collection methods which impact microbiome studies are sometimes neglected. Here, we expand on previous work in sample optimization, to promote high quality microbiome data. To compare fecal sample collection methods, amplicons from the bacterial 16S rRNA gene (V4) and fungal (ITS2) region, as well as short chain fatty acid (SCFA) concentrations were determined in fecal material over three timepoints. We demonstrated that spot sampling of stool results in variable detection of some microbial members, and inconsistent levels of SCFA; therefore, sample homogenization prior to subsequent analysis or subsampling is recommended. We also identify a trend in microbial and metabolite composition that shifts over two consecutive stool collections less than 25 h apart. Lastly, we show significant differences in bacterial composition that result from collecting stool samples in OMNIgene·Gut tube (DNA Genotec) or Stool Nucleic Acid Collection and Preservation Tube (NORGEN) compared to immediate freezing. To assist with planning fecal sample collection and storage procedures for microbiome investigations with multiple analyses, we recommend participants to collect the first full bowel movement of the day and freeze the sample immediately after collection.

SUBMITTER: Jones J

PROVIDER: S-EPMC8263620 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature

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Fecal sample collection methods and time of day impact microbiome composition and short chain fatty acid concentrations.

Jones Jacquelyn J Reinke Stacey N SN Ali Alishum A Palmer Debra J DJ Christophersen Claus T CT

Scientific reports 20210707 1

Associations between the human gut microbiome and health outcomes continues to be of great interest, although fecal sample collection methods which impact microbiome studies are sometimes neglected. Here, we expand on previous work in sample optimization, to promote high quality microbiome data. To compare fecal sample collection methods, amplicons from the bacterial 16S rRNA gene (V4) and fungal (ITS2) region, as well as short chain fatty acid (SCFA) concentrations were determined in fecal mate ...[more]

PMID: 34234185

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Project description:BackgroundGut microbes produce short-chain fatty acids (SCFAs), which are associated with broad health benefits. However, it is not fully known how diet and/or the gut microbiome could be modulated to improve SCFA production.ObjectivesThe objective of this study was to identify dietary, inflammatory, and/or microbiome predictors of SCFAs in a cohort of healthy adults.MethodsSCFAs were measured in fecal and plasma samples from 359 healthy adults in the United States Department of Agriculture Nutritional Phenotyping Study. Habitual and recent diet was assessed using a Food Frequency Questionnaire and Automated Self-Administered 24-h Dietary Assesment Tool dietary recalls. Markers of systemic and gut inflammation were measured in fecal and plasma samples. The gut microbiome was assessed using shotgun metagenomics. Using statistics and machine learning, we determined how the abundance and composition of SCFAs varied with measures of diet, inflammation, and the gut microbiome.ResultsWe show that fecal pH may be a good proxy for fecal SCFA abundance. A higher Healthy Eating Index for a habitual diet was associated with a compositional increase in fecal butyrate relative to acetate and propionate. SCFAs were associated with markers of subclinical gastrointestinal (GI) inflammation. Fecal SCFA abundance was inversely related to plasma lipopolysaccharide-binding protein. When we analyzed hierarchically organized diet and microbiome data with taxonomy-aware algorithms, we observed that diet and microbiome features were far more predictive of fecal SCFA abundances compared to plasma SCFA abundances. The top diet and microbiome predictors of fecal butyrate included potatoes and the thiamine biosynthesis pathway, respectively.ConclusionsThese results suggest that resistant starch in the form of potatoes and microbially produced thiamine provide a substrate and essential cofactor, respectively, for butyrate synthesis. Thiamine may be a rate-limiting nutrient for butyrate production in adults. Overall, these findings illustrate the complex biology underpinning SCFA production in the gut. This trial was registered at clinicaltrials.gov as NCT02367287.

Project description:ObjectiveTo determine the longer-term effects of metformin treatment and behavioral weight loss on gut microbiota and short-chain fatty acids (SCFAs).Research design and methodsWe conducted a 3-parallel-arm, randomized trial. We enrolled overweight/obese adults who had been treated for solid tumors but had no ongoing cancer treatment and randomized them (n = 121) to either 1) metformin (up to 2,000 mg), 2) coach-directed behavioral weight loss, or 3) self-directed care (control) for 12 months. We collected stool and serum at baseline (n = 114), 6 months (n = 109), and 12 months (n = 105). From stool, we extracted microbial DNA and conducted amplicon and metagenomic sequencing. We measured SCFAs and other biochemical parameters from fasting serum.ResultsOf the 121 participants, 79% were female and 46% were Black, and the mean age was 60 years. Only metformin treatment significantly altered microbiota composition. Compared with control, metformin treatment increased amplicon sequence variants for Escherichia (confirmed as Escherichia coli by metagenomic sequencing) and Ruminococcus torques and decreased Intestinibacter bartlettii at both 6 and 12 months and decreased the genus Roseburia, including R. faecis and R. intestinalis, at 12 months. Effects were similar in comparison of the metformin group with the behavioral weight loss group. Metformin versus control also increased butyrate, acetate, and valerate at 6 months (but not at 12 months). Behavioral weight loss versus control did not significantly alter microbiota composition but did increase acetate at 6 months (but not at 12 months). Increases in acetate were associated with decreases in fasting insulin. Additional whole-genome metagenomic sequencing of a subset of the metformin group showed that metformin altered 62 metagenomic functional pathways, including an acetate-producing pathway and three pathways in glucose metabolism.ConclusionsMetformin, but not behavioral weight loss, impacted gut microbiota composition at 6 months and 12 months. Both metformin and behavioral weight loss altered circulating SCFAs at 6 months, including increasing acetate, which correlated with lower fasting insulin. Future research is needed to elucidate whether the gut microboime mediates or modifies metformin's health effects.

Dataset Information

Fecal sample collection methods and time of day impact microbiome composition and short chain fatty acid concentrations.

Publications

Fecal sample collection methods and time of day impact microbiome composition and short chain fatty acid concentrations.

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