How gut transit and pH shape the microbiome’s role in metabolism and health, offering insights for personalized nutrition strategies.

Study: Gut physiology and environment explain variations in human gut microbiome composition and metabolism. Image Credit: New Africa / Shutterstock

In a recent study published in the journal Nature Microbiology, researchers investigated how gut physiology and environmental factors contribute to the variations in human gut microbiome composition and metabolism.

Background

Diet influences gut microbiome composition and metabolism, but even with identical diets, significant variation remains, suggesting additional contributing factors.

Gut transit time has been shown to impact microbiome composition, with longer transit associated with increased microbial protein degradation and methane production.

Short-chain fatty acids (SCFAs) are generally beneficial, while metabolites from proteolysis, such as hydrogen sulfide and ammonia, are linked to adverse health outcomes. Changes in gut pH also affect microbial communities.

Understanding these dynamics is critical for designing effective personalized dietary strategies that enhance gut health. Further research is needed to explore how physiological factors like transit time and pH interact with diet to influence gut microbiota and host health, enabling personalized dietary strategies.

About the Study

A nine-day observational study, “Personalized Dietary Recommendations based on the Interaction between Diet, Microbiome, and Abiotic Conditions in the Gut (PRIMA),” was conducted at the University of Copenhagen between April and December 2021. It enrolled 63 healthy participants from Denmark.

Participants provided written informed consent, adhering to ethical guidelines. Of the initial group, 61 completed the study, with two excluded due to illness and antibiotic use.

Participants (ages 18-75, body mass index (BMI) 18.5-29.9 kg/m²) were excluded if they had conditions like inflammatory bowel disease or took antibiotics recently. They were compensated with gift cards and asked to maintain their usual diet while avoiding sweet corn, alcohol, smoking, and intense exercise before sample collection.

Daily stool samples, dietary records, urine samples, and other measurements like defecation patterns, gastrointestinal symptoms, and fasting blood and breath tests were collected. Participants ingested a wireless motility capsule (SmartPill), which provided detailed data on luminal pH, temperature, and pressure to measure gut transit times.

Anthropometric measurements and a standardized meal test were also conducted. Metabolic profiling was performed on urine and fecal samples, and microbiome profiling used 16S ribosomal RNA (rRNA) sequencing.

Study Results

Participants, aged 39 ± 13.5 years with an average BMI of 23.6 ± 2.8 kg/m², were instructed to maintain their usual diet and lifestyle throughout the study period. The study included two visits, during which fasting blood samples were taken to measure glucose, insulin, and C-peptide levels. Breath samples were collected to assess hydrogen and methane concentrations.

On the first visit, participants were provided with a standardized breakfast, accounting for 25% of their daily energy needs, to ensure consistency before a subset (n = 50) ingested a SmartPill. The SmartPill measured whole-gut and segmental transit times and pH. Unlike previous studies using simple meals for transit monitoring, this study employed a complex meal to better reflect real-life diet-microbiota interactions. Postprandial urine and breath samples were collected to provide further insight into participants’ metabolic responses.

Participants also recorded daily 24-hour dietary records using the Myfood24 platform and noted bowel habits such as stool consistency (using the Bristol Stool Form Scale), stool frequency, and time of defecation.

Daily urine (first-morning sample) and fecal samples (first bowel movement) were collected. Fecal water content, a proxy marker of transit time and stool moisture, was assessed for all samples.

Urine and fecal metabolomes were profiled using untargeted liquid chromatography-mass spectrometry (LC-MS), and gut microbiome composition was determined using 16S rRNA gene sequencing, adjusted for microbial load to ensure quantitative accuracy.

The study revealed intra- and inter-individual variations in gut environment stability, as observed in daily fluctuations of factors like stool pH, stool moisture, and microbial load.

Segmental transit time and pH measurements provided by the SmartPill showed a wide range of values, highlighting substantial variability in gastrointestinal dynamics among participants.

The findings indicated that stool moisture and pH were significant contributors to both intra-individual and inter-individual variations in the gut microbiome and metabolomes. These insights emphasize the central role of gut transit time and colonic pH as key determinants of microbial composition and metabolic activity.

Untargeted metabolomics identified several microbial, host, and food-derived metabolites correlated with transit time and pH. For example, microbial fermentation products like SCFAs were linked to shorter transit times, while proteolytic byproducts were more prevalent with longer transit times.

Conclusions

To summarize, this study demonstrated significant variability in transit time and pH among healthy individuals, explaining differences in microbiome composition and host–microbiota metabolism.

Factors such as transit time and pH influenced microbial activity, highlighting the importance of the gut environment in shaping microbiota responses. Specific metabolites were linked to longer transit times, with potential clinical implications for managing conditions like constipation.

These findings pave the way for future research into tailored dietary interventions that consider both physiological and microbial factors for optimizing gut health.