Your gut microbiota is like a fingerprint – unique to you. Yet even within you, it varies significantly. Day to day, your microbiota responds to your diet, medications and some lifestyle influencers. Your microbiota composition also changes in response to the different environments along the length of your alimentary canal. Differences in transit time, water content, nutrient sources, pH, mucin, digestive enzymes, bile and other factors create different niches throughout the GI tract. However, most of what we know about gut microbiota comes from fecal sample analysis, mostly because these samples are non-intrusive to obtain from study subjects, whereas samples from other parts of the gut are not.
Because the environments, and consequently the microbiota, through the length of GI tract differ, we need to recognize that what determines the microbiota composition of feces may be different than what determines microbiota composition in other regions of the gut. This is important because we need to exercise caution in interpreting results from fecal sample analysis.
Some interesting insights into interpreting microbiota of fecal samples were provided in two papers from researchers at the University of Leuven, Belgium. In a 2016 study, Falony et al published an analysis of fecal samples from close to 4000 healthy subjects from different cohort studies. Their goal was to identify the key drivers (i.e., covariates) of fecal microbiota composition. Surprising to me, the largest influencer of microbiota composition was stool consistency. This means that the microbiota of loose stools were different from compact stools. In addition to stool consistency, other important drivers of microbiota composition were age, BMI, diet and medication usage.
The 2018 commentary by this same lead author provides additional insight into understanding microbiota information obtained from fecal samples. They consider the issue of stool samples in an ecological framework, noting that microbiota differences are a result of ecological niche changes. The most important factors include the loss of water and depletion of nutrients. These factors drive changes in what specific microbial groups are present, the concentration of microbes and the metabolic activities of microbes. Increased proteolytic compared to saccharolytic activity characterizes firm stool compared to loose stool. Harder stools were found to be associated with increase bacterial richness and differences in relative abundances of several taxa. In contrast, watery stool displayed reduced microbial density (lower number of microbial cells per gram feces) to an extent beyond a simple dilution effect. (Figure 1 of this paper nicely depicts these factors.)
The authors suggest that clinical microbiome research must view samples of gut contents through the lens of ecological succession of the microbial communities therein. They caution that gut contents over the length of the GI tract are heterogeneous and unstable, but that feces reflect a mature community characterized by lower water, reduced nutrients and greater microbial stability. Importantly, this microbial stability should not be interpreted as a measure of resilience (which could also be considered a measure of health), but as a measure of a mature community.
As the authors conclude: “Adopting the concept of the faecal microbiome as a snapshot of an aging ecosystem in both study design and interpretation of microbiome studies will allow us to distinguish relevant clinical features from a background of ecological succession.”
The association of microbiota compositions that differ between healthy people and different disease states is widely touted. However, certain disease states are also associated with differences in stool consistency, medication use and diet so perhaps it’s not the disease that is driving the composition differences, but the nature of the stool sample being analyzed. So we do not know if the disease drives the microbiota changes or if medications, stool consistency or diet differences do.
The Faloney et al. papers serve as caution to us that conclusions from associative studies should not be misconstrued as causal. If there is no directly causal relationship between microbiota variation and disease, then research efforts to change disease-associated microbiota are unlikely to lead to clinical improvement.