Gut Microbes Shape How Many Calories We Really Absorb, New Model Suggests
Key Takeaways:
- Researchers at Arizona State University have developed a mathematical model, DAMM, that links human digestion with gut microbial metabolism to estimate how much energy the body actually absorbs from food.
- In a controlled diet study, people following a typical Western diet absorbed approximately 116 more calories per day than those following a high-fibre “microbiome-enhancer” diet, and participants on the higher-fibre plan did not report feeling hungrier.
- Short-chain fatty acids produced by gut bacteria supplied an average of around 140 calories per day, roughly 7.4% of total usable energy, a contribution that conventional food-label calculations do not explicitly measure.
Rethinking the number on the label
The calorie count printed on food packaging might appear to be a simple measure of how much energy a person will gain from eating it. However, that figure does not necessarily reflect the calories the body actually absorbs. One reason for this is that digestion involves far more than the breakdown of food by the body alone – it also relies on the trillions of microorganisms living within the digestive system.
Researchers at Arizona State University (ASU) have developed a mathematical model to explore this often overlooked aspect of digestion. Known as DAMM, short for digestion, absorption and microbial metabolism, the model tracks how food moves through the digestive tract, how much energy the body absorbs directly, and how gut microbes process whatever remains. It also estimates which products of digestion are absorbed and which leave the body as waste.
By accounting for the relationship between diet, human digestion and gut bacteria, the researchers hope to improve understanding of obesity, diabetes and other metabolic disorders. With further development, the approach could eventually help healthcare professionals design diets tailored to individual patients.
“Digestion is not just a human process – it is a collaboration between our bodies and trillions of microbes living in the gut,” said Professor Rosa Krajmalnik-Brown. “DAMM gives us a powerful new way to quantify how those microbial partners contribute to human health and energy balance, and also point at the importance of properly feeding our gut microbes.”
Professor Krajmalnik-Brown is director of ASU’s Biodesign Center for Health Through Microbiomes and a professor in the university’s School of Sustainable Engineering and the Built Environment.
The research team also included ASU Professor Bruce Rittmann, director of the Biodesign Swette Center for Environmental Biotechnology and a Regents Professor of environmental engineering, alongside first author Taylor Davis, an ASU graduate research assistant. Scientists at the AdventHealth Translational Research Institute in Orlando, Florida, also collaborated on the project.
The findings were published in PLOS One.
Why traditional calorie counts miss part of the picture
For more than 100 years, scientists have relied on a system based on Atwater parameters to estimate how much energy people can obtain from food. This method assigns average calorie values to each gram of fat, carbohydrate and protein, and then uses those values to calculate the total energy available.
While this approach is practical and widely used, it cannot fully explain what happens during digestion. In particular, it does not account for how different foods nourish gut bacteria, or how those bacteria transform undigested material into substances the body can use for energy.
Short-chain fatty acids offer an important example. These compounds are produced when microbes in the colon break down fibre and other food components that pass through the upper digestive tract without being absorbed. Some of these fatty acids can then enter the bloodstream and provide additional calories.
To better understand these interactions, the researchers built on an earlier controlled diet study that investigated how the gut microbiome influences human energy balance. The gut microbiome refers to the vast community of bacteria and other microorganisms that inhabit the digestive system.
A high-fibre diet led to 116 fewer calories absorbed per day
In the clinical study, healthy adults followed one of two carefully designed eating plans. The first was a microbiome-enhancer diet containing substantial amounts of fibre and resistant starch, made up of less processed foods and foods with a larger particle size. Resistant starch is a type of carbohydrate that escapes much of the usual digestion in the small intestine, allowing it to reach the colon, where microbes can break it down.
The second eating plan resembled a typical Western diet, with lower amounts of fibre and resistant starch, made up of more processed foods with a smaller particle size.
Although both diets were designed specifically for the study, participants absorbed noticeably different amounts of energy. Those following the Western diet absorbed approximately 116 more calories per day than those following the fibre-rich diet.
Perhaps just as notably, participants following the higher-fibre eating plan did not report feeling hungrier.
The findings suggest that the amount of energy people obtain from food depends partly on its composition and on how it moves through the digestive system. Differences in food processing, fibre content and microbial activity can all influence the final outcome.
For healthcare professionals supporting patients with their diet and weight, findings such as these highlight how food quality and composition – not just calorie totals – may shape energy balance. Understanding the evidence behind nutritional advice is a central theme of The College of Contemporary Health’s Nutrition & Weight Management Essentials CPD course, which supports clinicians in applying nutrition science to everyday practice.
“What is truly unique about the DAMM model is that it quantitatively links human metabolism to the metabolism of the microorganisms in the colon in a way that matches the results from the clinical study and provides fundamental insight into how the microbial community works in partnership with the human host,” Professor Rittmann said.
Gut bacteria can supply about 140 calories a day
The DAMM model offers a more detailed way of following the energy contained in food from the moment it enters the digestive system.
First, it examines the protein, carbohydrate and fat content of a person’s diet and estimates how much usable energy is absorbed in the upper gastrointestinal tract.
It then tracks the remaining material as it moves into the colon. Here, gut microbes break down nutrients that escaped earlier digestion, producing compounds such as short-chain fatty acids. The body can absorb some of these compounds through the colon and use them as an additional source of energy.
The model also accounts for methane production by certain microorganisms known as methanogens, which generate methane as part of their metabolism.
According to the researchers’ calculations, short-chain fatty acids absorbed from the colon supplied an average of approximately 140 calories per day. This represents around 7.4% of the total usable energy obtained from food.
More broadly, the model estimated that roughly 85% of usable energy came from the upper gastrointestinal tract, while approximately 15% came from the lower gastrointestinal tract, where microbes play a particularly important role.
These findings highlight why traditional calorie calculations cannot fully describe human digestion. A meaningful share of the energy available to the body is influenced by microbial processes that conventional food-label calculations do not explicitly measure.
DAMM outperformed the conventional approach
When the team compared DAMM’s predictions with actual measurements from the controlled diet study, the model produced estimates that were closer to the observed calorie absorption than those generated using the conventional Atwater approach.
The older method generally underestimated how many calories participants absorbed. By incorporating microbial metabolism, DAMM provided a more accurate estimate of the energy obtained from the different diets.
How fibre changes the calorie equation
One of the model’s most revealing features is its ability to account for differences between diets.
The microbiome-enhancer diet delivered more fibre and other fermentable material to the colon. This gave gut microbes additional substances to break down, increasing their production of short-chain fatty acids.
DAMM predicted this increase, consistent with the pattern observed in the controlled clinical trial. Participants following the microbiome-enhancer diet had higher levels of short-chain fatty acids in measurements taken from their blood serum and faeces.
These compounds are significant because they illustrate how closely microbial activity and human metabolism are connected. Gut bacteria can transform food components that would otherwise pass straight through the digestive system into molecules the body can absorb and use for energy.
However, producing more of these compounds does not necessarily mean absorbing more calories overall.
In fact, participants following the microbiome-enhancer diet absorbed fewer net calories than those following the Western diet, even though the higher-fibre diet supported greater microbial activity and increased short-chain fatty acid production.
This apparent contradiction becomes easier to understand when the different stages of digestion are examined separately. Although gut microbes can generate additional usable energy, the amount absorbed directly from food in the upper digestive tract also matters.
DAMM helps researchers distinguish between these contributions. It estimates how much energy the body extracts before food reaches the colon, how much energy microbes produce from the remaining material, and how much is ultimately absorbed or eliminated.
Towards more personalised diets and better nutrition
By bringing human digestion and microbial metabolism together within a single mathematical framework, the researchers have created a tool that could help explain why different diets have different effects on the body’s energy balance.
The approach may eventually improve scientific understanding of how diet influences obesity, diabetes and other metabolic conditions. It also raises the possibility of designing nutrition plans that consider not only the nutrients in food, but also how those nutrients interact with the microbes living in each person’s gut.
For now, the model provides a research framework rather than a ready-to-use method for prescribing personalised diets. Further studies will be needed to determine how well it performs across different populations, eating patterns and microbiome compositions.
The researchers also expect the model to become more sophisticated as scientists uncover further detail about how microorganisms and the human body exchange nutrients and energy.
“The DAMM model is more than just a tool for characterizing diet,” Davis said. “It’s a framework designed to evolve. As we discover more on how diet, metabolism and the microbes interact, the new insights can be incorporated into the model, allowing it to grow with us as we learn.”
CCH insight
Research like the DAMM model shows that the conversation around diet and weight is moving beyond simple calorie counting towards a fuller understanding of food composition, fibre and the gut microbiome. If you support patients with nutrition and weight management, our Nutrition & Weight Management Essentials CPD course can help you translate emerging evidence into confident, practical advice.
Explore Nutrition & Weight Management Essentials →
Source: PLOS One
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Gut Microbiome May Shape Responses to GLP-1 Therapies in Obesity and Type 2 Diabetes
Key Takeaways:
- The gut microbiome may contribute to why people respond differently to GLP-1 receptor agonists, although causality remains unproven
- GLP-1 therapies and associated weight loss can alter gut microbial composition, but findings are inconsistent
- Dietary and behavioural changes during treatment are likely key drivers of microbiome shifts rather than direct drug effects
Emerging link between the gut microbiome and GLP-1 treatment response
A recent review published in the Canadian Journal of Physiology and Pharmacology highlights growing interest in the role of the gut microbiota in shaping responses to glucagon-like peptide-1 receptor agonists, commonly referred to as GLP-1 RAs. These medications are widely used in the management of people living with type 2 diabetes and those living with overweight or obesity.
The analysis suggests that gut microbial communities and their metabolites may contribute to the variability observed in treatment responses. At the same time, GLP-1 receptor agonists may themselves influence the composition of the gut microbiota. This bidirectional relationship positions the microbiome as both a potential contributor to treatment variability and a possible future target for more personalised metabolic therapies.
The gut microbiome as a regulator of metabolic health
There is increasing evidence that gut microbes play an active role in metabolic regulation. Preclinical studies using faecal microbiota transplantation have demonstrated that microbial communities can transfer traits such as glucose regulation and body mass. However, findings in human studies have been less consistent.
Despite the widespread use of GLP-1 receptor agonists, research exploring their interaction with the human gut microbiome remains limited. This is particularly notable given the considerable variation in how individuals respond to these treatments. Differences in microbial composition may partly explain this variability, although a definitive causal relationship has not yet been established.
In the review, researchers examined potential interactions between GLP-1 therapies, diet, gastrointestinal symptoms, body weight, and gut microbial composition.
Interactions between GLP-1 signalling and gut microbes
GLP-1 is a naturally occurring hormone that regulates appetite and blood glucose levels by binding to the GLP-1 receptor. It is released by L-cells in the intestine following nutrient intake. Because this release occurs in the lower intestine, GLP-1 operates in close proximity to the gut microbiota, raising the possibility of direct interaction.
Microbial metabolites such as bile acid derivatives and short-chain fatty acids can influence endogenous GLP-1 secretion and activity. These findings suggest that gut microbes may play a role in modulating GLP-1 signalling pathways. However, direct evidence demonstrating that microbial composition determines treatment response to GLP-1 receptor agonists in humans remains limited.
GLP-1 therapies may also indirectly affect the microbiome through changes in appetite, gastrointestinal motility, and dietary intake.
Clinical effectiveness of GLP-1 receptor agonists and variability in response
GLP-1-based therapies including liraglutide, semaglutide, and tirzepatide are now well established in the treatment of type 2 diabetes and obesity. Clinical trials have demonstrated significant weight loss outcomes:
- Tirzepatide – approximately 11.9–17.8% greater weight loss than placebo over 72 weeks
- Semaglutide – approximately 12.4% greater weight loss over 68 weeks
- Liraglutide – approximately 8.0% weight reduction compared with placebo over 56 weeks
Despite these results, individual responses vary widely. Differences in the gut microbiome have been proposed as one potential contributing factor, although this remains an area of ongoing investigation.
Microbiome changes associated with GLP-1 therapies
GLP-1 receptor agonists may influence gut microbial composition in people living with type 2 diabetes and obesity. Historically, obesity has been associated with a higher Firmicutes-to-Bacteroidetes ratio. Some studies suggest that weight loss is linked to increased microbial diversity and a greater abundance of beneficial genera such as Akkermansia.
Clinical observations include:
- Increased Akkermansia levels after six weeks of liraglutide therapy
- Increased levels of Bacteroidota, Actinobacteriota, and Proteobacteria following 12 weeks of semaglutide
- A reduction in Firmicutes in some cohorts
However, these findings are based on a limited number of heterogeneous studies. Many have involved people living with type 2 diabetes who were also taking other medications such as metformin, which is known to independently influence the gut microbiome.
GLP-1 receptor agonists, when combined with lifestyle modification, can lead to approximately 8–20% body weight reduction over several months to one year. Nevertheless, reported microbiome changes remain inconsistent. Some studies show increased diversity, while others report minimal or no significant changes.
Dietary changes during treatment and their microbiome impact
Evidence suggests that observed microbiome shifts may largely reflect downstream effects of weight loss and metabolic improvement rather than direct drug–microbiome interactions.
GLP-1 therapies are associated with changes in eating behaviour, including reduced appetite, increased satiety, and altered taste perception. People using these medications often improve their dietary patterns, with reduced consumption of refined grains, processed foods, beef, and sugar-sweetened beverages. Caloric intake may decrease by approximately 16–39%.
In 2025, organisations including The Obesity Society, American College of Lifestyle Medicine, American Society for Nutrition, and Obesity Medicine Association issued clinical guidance emphasising the importance of nutritional assessment and management of gastrointestinal side effects during GLP-1 therapy.
This guidance recommends prioritising nutrient-dense foods such as vegetables, fruits, whole grains, lean proteins, seeds, and nuts, while limiting refined carbohydrates, sugar-sweetened beverages, red and processed meats, fast foods, and highly processed snacks. Given the strong influence of diet on gut microbial composition, these dietary changes are likely to play a significant role in shaping the microbiome during treatment.
Future directions and research priorities
The review concludes that current evidence points towards behavioural and dietary changes, alongside weight loss, as the primary drivers of microbiome alterations observed during GLP-1 receptor agonist therapy.
However, the gut microbiome remains a promising area for future research. Microbiome profiling could eventually help predict treatment response more accurately in people living with obesity and type 2 diabetes.
Future studies should include:
- Larger and more diverse populations
- Longitudinal monitoring of microbiome changes
- Inclusion of people living with obesity who do not have diabetes
- Detailed tracking of dietary intake, gastrointestinal symptoms, and treatment adherence
Emerging therapies such as oral GLP-1 receptor agonists and new agents like orforglipron may offer further insight into direct interactions between medications and gut microbes, particularly as orally administered drugs come into direct contact with the gastrointestinal tract.
Understanding these relationships may ultimately support more personalised and effective approaches to obesity and diabetes care.
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Big Breakfast Study Shows Protein Reduces Appetite While Fibre Supports Gut Microbiome Health
Key Takeaways:
- Within a calorie-restricted big-breakfast eating pattern, a higher-protein breakfast improved satiety, while a higher-fibre breakfast produced more favourable gut microbiota and short-chain fatty acid profiles.
- Both dietary approaches led to clinically meaningful short-term weight loss and improvements in metabolic markers, but with distinct physiological effects.
- Fibre-rich breakfasts were linked to greater abundance of beneficial butyrate-producing bacteria, whereas protein-rich breakfasts may better support appetite control and dietary adherence.
Background and rationale
A recent study published in the British Journal of Nutrition examined how breakfast composition influences appetite regulation, energy balance and markers of gut microbiota health when consumed as part of a calorie-restricted, big-breakfast weight-loss diet.
There is growing evidence that meal timing, in addition to dietary composition, plays an important role in healthy weight management. Previous research has shown that people who eat earlier in the day tend to lose more weight than those who eat later. Morning calorie intake has also been associated with improved blood glucose control and lower hunger levels compared with evening intake.
Larger breakfasts have been shown to improve appetite control, while late eating patterns have been linked to increased hunger and greater fat storage. Despite public health advice emphasising the importance of breakfast for weight management, relatively little is known about what people typically consume in the morning. Moreover, evidence explaining how meal timing, calorie distribution and macronutrient composition interact to influence appetite remains limited.
Study design and dietary interventions
The researchers used a randomised crossover design to compare two calorie-restricted weight-loss diets with identical big-breakfast calorie distribution but differing macronutrient profiles. The primary outcomes were appetite, energy balance and gut microbiota composition and metabolites, rather than clinical gastrointestinal outcomes.
Healthy adults with overweight or obesity, aged 18–75 years, were recruited. The protocol consisted of:
- a four-day ad libitum diet
- a four-day maintenance diet
- a 28-day high-fibre weight-loss diet or high-protein weight-loss diet
These phases were separated by a washout period, with participants acting as their own controls. Resting metabolic rate was measured by indirect calorimetry during screening.
The maintenance diet provided 15% of energy from protein, 55% from carbohydrate and 30% from fat, and was set at 1.5 times resting metabolic rate to maintain body weight. Both weight-loss diets were set at 100% of resting metabolic rate to induce a calorie deficit.
Participants consumed three meals per day, with 45% of daily calories at breakfast, 20% at lunch and 35% in the evening. Lunch intake was allowed ad libitum within the provided calorie allowance.
- High-fibre weight-loss diet – 50% carbohydrate, 15% protein and 35% fat, incorporating both soluble and insoluble fibre sources such as lentils, fava beans, buckwheat and wheat bran.
- High-protein weight-loss diet – 30% protein, 35% carbohydrate and 35% fat, using foods including fish, poultry, eggs, red meat and dairy.
Measurements and outcomes assessed
Body density, waist and hip circumference, resting metabolic rate, total body water and blood pressure were measured. The thermic effect of food was assessed every 30 minutes for four hours after breakfast. Subjective appetite was evaluated using visual analogue scales.
Blood samples collected after an overnight fast were used to assess glucose, lipid profile and insulin as metabolic biomarkers rather than clinical disease outcomes. Insulin and glucose values were used to calculate HOMA-IR, HOMA-β and the insulin-to-glucose ratio. Total body water was measured using deuterium dilution, and faecal samples were collected to analyse gut microbiota composition.
Weight loss, energy expenditure and metabolic markers
Nineteen participants completed the study, including two women. The mean age was 57.4 years and the mean body mass index was 33.3 kg/m², indicating a predominantly male cohort and limiting generalisability to broader populations.
Energy intake did not differ significantly between the two weight-loss diets. Average weight loss was 4.87 kg with the high-fibre diet and 3.87 kg with the high-protein diet. Both diets significantly reduced fat mass and fat-free mass compared with the maintenance diet, although loss of fat-free mass was greater with the high-fibre approach.
Total body water was reduced following the high-fibre diet but not after the high-protein diet. Waist and hip circumferences, as well as waist-to-hip ratio, were significantly reduced with both weight-loss diets compared with the maintenance diet.
The high-protein breakfast maintained postprandial satiety, whereas the high-fibre breakfast was associated with reduced satiety after meals. Resting metabolic rate declined significantly after both weight-loss diets. The thermic effect of food was lower following the high-fibre diet than after the high-protein or maintenance meals.
Both weight-loss diets improved lipid profiles relative to baseline, with no significant difference between the two approaches. Fasting and postprandial glucose levels were reduced by around 10% following the high-fibre diet and by 8–7% following the high-protein diet compared with the maintenance diet. Fasting insulin, HOMA-IR and the insulin-to-glucose ratio were significantly lower after both weight-loss diets.
HOMA-β decreased significantly more after the high-protein diet than after the maintenance diet, with no significant change observed after the high-fibre diet.
Gut microbiota composition and short-chain fatty acids
Total bacterial load in faecal samples did not differ significantly between the two weight-loss diets. However, microbial diversity was lower following the high-protein diet compared with the high-fibre diet.
Distinct differences in microbiota composition were observed between the dietary patterns, although individual variation remained a major determinant of microbiota profiles and diet explained only part of the observed variability.
The high-fibre diet was associated with a greater abundance of butyrate-producing bacteria, including Anaerostipes hadrus, Roseburia faecis and Faecalibacterium prausnitzii. At the genus level, Bifidobacterium, Faecalibacterium and Roseburia were linked to the high-fibre diet, while Streptococcus was associated with the high-protein diet.
Total short-chain fatty acids and key faecal short-chain fatty acids, including acetate, butyrate and propionate, were significantly lower with the high-protein diet compared with the high-fibre diet.
Interpretation and clinical implications
Overall, the findings suggest that within a calorie-restricted big-breakfast eating pattern, breakfast composition meaningfully influences short-term weight loss, metabolic health markers and gut microbiota characteristics.
Both dietary approaches led to significant weight reduction and metabolic improvements. The high-protein breakfast produced greater satiation, which may support long-term adherence in some people. In contrast, the high-fibre breakfast promoted a more favourable gut microbiota profile and higher short-chain fatty acid production, which may be beneficial for long-term gut health, although this was inferred from microbial and metabolic markers rather than direct clinical outcomes.
The authors emphasised that longer-term studies are needed to determine whether these differences are sustained over time and how they translate into long-term health outcomes.
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Maternal Obesity Linked to Early Changes in Infant Gut Microbiome, Study Suggests
Key Takeaways:
- Infants born to mothers with obesity show distinct differences in gut bacteria during the first six months of life, including reduced microbial diversity.
- These early microbial changes are associated with pathways linked to fat metabolism, particularly in the first three months after birth.
- Researchers suggest that early-life interventions targeting the gut microbiome may help reduce longer-term metabolic risks for children.
Maternal obesity and the infant gut microbiome
Babies born to mothers with obesity may begin life with a markedly different gut microbiome, a factor that could influence their metabolism and long-term health, according to new research from Nazarbayev University (NU).
The study, led by researchers Almagul Kushugulova and Samat Kozhakhmetov, explored how maternal obesity may shape the early development of the gut microbiome in infants. The research team followed 24 mothers and their babies from birth to six months of age, analysing stool samples using advanced DNA sequencing techniques.
By comparing infants born to mothers with obesity with those born to mothers without obesity, the researchers identified clear differences in the composition and diversity of gut bacteria during early life.
Reduced microbial diversity and altered metabolic pathways
The analysis showed that infants of mothers with obesity had significantly lower gut microbial diversity. In addition, these infants had a higher abundance of bacterial species associated with fat metabolism.
These differences were most pronounced during the first three months of life, a period widely recognised as critical for the establishment of the gut microbiome and for metabolic programming.
“During the first three months of life, we observed what appears to be a shift in how gut bacteria process nutrients – with a tendency toward fat storage pathways rather than breaking down carbohydrates for energy,” Kozhakhmetov explained.
He noted that this early metabolic pattern may have implications for how energy balance is regulated later in life.
Opportunities for early intervention
The researchers suggest that their findings open the door to preventive strategies during infancy. Kozhakhmetov highlighted that understanding these early microbial shifts could inform interventions aimed at promoting healthier metabolic outcomes.
This discovery, he said, “opens up possibilities for early intervention”, including approaches such as targeted probiotics or tailored dietary guidance designed to support a more balanced gut microbiome and potentially reduce future metabolic risk.
Beyond metabolism – immune and appetite regulation
The implications of the findings may extend beyond metabolism alone. The researchers propose that maternal obesity could also influence immune system development and appetite regulation in children through microbial transmission.
“We tend to think that we only pass on our genes to our children. But our research suggests that we may also pass on our bacteria – and the type of bacteria a child inherits could have important effects on their long-term health, potentially influencing their health trajectory as they grow,” Kushugulova said.
This perspective reinforces the idea that early-life exposures play a significant role in shaping health across the life course.
Placing the findings in context
The study, published in the journal Biomedicines, adds to a growing body of research highlighting the importance of the early-life microbiome. Previous studies have linked maternal weight status and gut dysbiosis to disrupted nutrient metabolism, inflammation, and changes in immune, metabolic, or neurodevelopmental outcomes in children.
As obesity during pregnancy becomes increasingly common worldwide, the authors argue that maternal health should be viewed as a key determinant not only of pregnancy outcomes, but also of a child’s longer-term metabolic health.
Implications for future research and practice
The researchers conclude that interventions targeting the gut microbiota during early infancy may represent a promising avenue for reducing health risks associated with maternal obesity. Further research will be needed to determine which strategies are most effective, when they should be implemented, and how they can be integrated into routine maternal and child healthcare.
Taken together, the findings underline the importance of addressing obesity before and during pregnancy, while also highlighting the potential of microbiome-focused approaches to support healthier outcomes for future generations.
CCH insight:
Evidence for the role of the gut microbiome in obesity and metabolic health continues to grow. This study is ground-breaking in demonstrating that maternal obesity influences the new-born child’s microbiome, potentially priming the child for health challenges later in life right from their first few weeks of life. On the positive side, this offers the potential to identify babies at risk of metabolic diseases from a very early stage of life, and also the opportunity for early interventions though diet, pre- and probiotics.
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