Weight management extends beyond counting calories, as we know that hormones, inflammation, digestive capacity, body composition, and even our gut microbiome can influence metabolism. The gut microbiome may influence how the body digests food, absorbs nutrients, and metabolizes macronutrients. Recent studies explore these connections, offering insight into how the gut microbiome may contribute to individual differences in energy metabolism and potentially inform approaches to weight management.
The Atwater system was developed in the late 19th century to convert food mass in grams into gross energy in calories (kcal) for proteins, carbohydrates, and fats. There are 4 kcal/g for protein, 4 kcal/g for carbohydrates, and 9 kcal/g for fats. This system is used to determine caloric contributions on food labels. While this is relatively accurate, it doesn’t account for microbiome influences such as fiber fermentation and methanogenesis. Each person’s microbiome composition is unique, and metabolic capacity can vary widely.
The microbiome ferments fiber to create beneficial short-chain fatty acids (SCFAs), which are then used by the microbiome and the host. SCFAs, therefore, supply calories/energy from the fiber in the meal, which is not typically accounted for on food labels. Methanobrevibacter smithii and other methanogens that create methane gas have been associated with obesity and anorexia. Methanogen abundance is associated with increased energy extraction from food, providing more calories for the host, through increased SCFA absorption.
The Studies
A group of researchers set out to understand the microbiome’s contribution to calorie metabolism through a series of studies. A clinical trial published in Nature Communications enrolled 17 participants in a randomized crossover study comparing a Western Diet (WD) with a Microbiome Enhancer Diet (MBD) under controlled conditions. Participants followed each diet for 23 days, with a 14-day washout period in between. This design allowed each participant to serve as their own control, helping researchers compare the effects of the two diets while accounting for individual differences.
The MBD consisted of dietary fiber, resistant starch, and whole, minimally processed foods. The WD was the opposite, with lower fiber and more processed foods. Researchers used multiple methods to evaluate energy intake, energy expenditure, and energy output (fecal and urinary).
The two groups had the same energy expenditure, hunger/satiety, and food intake. Compared to the WD, the MBD led to an additional 116 +/- 56 kcals lost through stool daily, and lower energy for the host. The MBD resulted in more energy to the microbes, increased microbial fermentation, increased fecal and serum SCFAs, and increased fecal weight due to bacterial biomass.
In contrast, the WD “starved” the gut bacteria because more metabolizable energy was absorbed by the host in the upper GI tract. Bacterial diversity also differed between the two diets.
An interesting trend was that those on the MBD lost more fat without a change in lean body weight compared with those on the WD.
A separate analysis in The ISME Journal examined methanogen dynamics and found that participants with higher methanogen abundance extracted more metabolizable energy from the MBD than from the WD. In addition, increased SCFA production on the MBD was associated with greater host absorption of SCFAs in the presence of methanogens.
In a subsequent article, researchers developed a mathematical model to quantify the microbiome’s contribution to calories absorbed by the host. The recent study, published in PLOS One, introduces the Digestion, Absorption, and Microbial Metabolism (DAMM) mathematical model as an accurate model compared to other prediction methods. The model incorporates a comprehensive description of macronutrients, kinetics of the microbial community, methanogenesis, and absorption of SCFAs by colonocytes.
The DAMM model helps to understand if a particular diet is starving or feeding the microbiota. The DAMM model was 96% accurate in predicting energy absorption compared to 88% for the Atwater system.
Conclusions
Despite the extra calories from SCFA absorption, changes in the gut microbiota from higher fiber diets contribute to a net negative energy balance. Overall, participants absorbed fewer calories on the high-fiber MBD as compared to the WD. However, those with higher methanogen abundance absorbed more calories from the high-fiber diet than those with fewer methanogens.
Although the DAMM model has not yet been validated, future research incorporating this framework may help guide the development of personalized dietary interventions for obesity, diabetes, and other metabolic conditions. While the model is not currently used in food labeling, clinicians should recognize that the gut microbiome may influence an individual’s metabolic responses to diet. In general, emphasizing plant-based foods, fiber, and minimally processed foods may support weight management and overall metabolic health.
Resources
→ Download the Nature Communications Full Text HERE.
→ Download the The ISME Journal Full Text HERE.
→ Download the PLOS One Full Text HERE.
