Reprogramming the Human Gut Microbiome Reduces Dietary Energy Harvest

Abstract

The gut microbiome is emerging as a key modulator of host energy balance1. We conducted a quantitative bioenergetics study aimed at understanding microbial and host factors contributing to energy balance. We used a Microbiome Enhancer Diet (MBD) to reprogram the gut microbiome by delivering more dietary substrates to the colon and randomized healthy participants into a within-subject crossover study with a Western Diet (WD) as a comparator. In a metabolic ward where the environment was strictly controlled, we measured energy intake, energy expenditure, and energy output (fecal, urinary, and methane)2. The primary endpoint was the within-participant difference in host metabolizable energy between experimental conditions. The MBD led to an additional 116 ± 56 kcals lost in feces daily and thus, lower metabolizable energy for the host by channeling more energy to the colon and microbes. The MBD drove significant shifts in microbial biomass, community structure, and fermentation, with parallel alterations to the host enteroendocrine system and without altering appetite or energy expenditure. Host metabolizable energy on the MBD had quantitatively significant interindividual variability, which was associated with differences in the composition of the gut microbiota experimentally and colonic transit time and short-chain fatty acid absorption in silico. Our results provide key insights into how a diet designed to optimize the gut microbiome lowers host metabolizable energy in healthy humans.

Extended Data Fig. 1.. Summary of results and study flow.

a, Schematic of overall study design. b, Summary of key microbiome and host factors that are collectively associated with host metabolizable energy in our study. c, CONSORT diagram showing the flow of participants from enrollment through analysis.

Extended Data Fig. 1.. Summary of results and study flow.

a, Schematic of overall study design. b, Summary of key microbiome and host factors that are collectively associated with host metabolizable energy in our study. c, CONSORT diagram showing the flow of participants from enrollment through analysis.

Extended Data Fig. 2.. The experimental paradigm achieved adherence and energy balance.

a, Energy balance (mean of 6 measurement days) estimated from traditional parameters: Energy Balance = Energy Intake (kcals/24h) – Energy Expenditure (kcals/24h). b, Dietary adherence on the WD compared to the MBD over all inpatient days where all 3 meals were consumed on-site, and no changes were made to the feeding for testing. All data reported as mean ± s.e.m. N=17 per diet for both panels. MBD—Microbiome Enhancer Diet; WD—Western Diet.

Extended Data Fig. 3.. Gut microbiome community structure and reprogramming.

a, Fecal weight from 6 days of composited feces averaged to generate daily production. Data reported as mean ± s.e.m. b-c, Alpha-diversity measures of richness and evenness. d, Beta-diversity at the species level assessed with Jaccard Similarity. e, Mean relative abundances and effect sizes of significantly differentially abundant species between diets. The heatmap shows the mean relative abundance of significant species between each diet. The bar graph shows the effect size of the regression coefficient for the comparison of species relative abundance by diet. Species shown in this figure had P < 0.05 and Q < 0.25. f, Q-values for each regression coefficient shown in e, which ranged from 5 × 10⁻¹⁰ to 0.217. The treatment indicates the diet on which the species relative abundance was higher. N=17 per diet for all panels. CAP—Canonical Analysis of Principal Coordinates; MBD—Microbiome Enhancer Diet; RA—relative abundance; WD—Western Diet

Extended Data Fig. 3.. Gut microbiome community structure and reprogramming.

a, Fecal weight from 6 days of composited feces averaged to generate daily production. Data reported as mean ± s.e.m. b-c, Alpha-diversity measures of richness and evenness. d, Beta-diversity at the species level assessed with Jaccard Similarity. e, Mean relative abundances and effect sizes of significantly differentially abundant species between diets. The heatmap shows the mean relative abundance of significant species between each diet. The bar graph shows the effect size of the regression coefficient for the comparison of species relative abundance by diet. Species shown in this figure had P < 0.05 and Q < 0.25. f, Q-values for each regression coefficient shown in e, which ranged from 5 × 10⁻¹⁰ to 0.217. The treatment indicates the diet on which the species relative abundance was higher. N=17 per diet for all panels. CAP—Canonical Analysis of Principal Coordinates; MBD—Microbiome Enhancer Diet; RA—relative abundance; WD—Western Diet

Extended Data Fig. 4.. Host response to dietary intervention.

a, Gastric emptying as evaluated by acetaminophen appearance after a fixed breakfast. b, pH within a 1-hour window of the ileocecal passage. c-g, Visual analog scale data for subjective ratings of fullness, hunger, prospective food consumption, satiety and a composite appetite score. h, Ad libitum energy intake evaluated during lunch and dinner after a fixed breakfast. All data reported as mean ± s.e.m. N=17 per diet for panels a and b; n=16 per diet for panels c-h. MBD—Microbiome Enhancer Diet; WD—Western Diet.

Extended Data Fig. 4.. Host response to dietary intervention.

a, Gastric emptying as evaluated by acetaminophen appearance after a fixed breakfast. b, pH within a 1-hour window of the ileocecal passage. c-g, Visual analog scale data for subjective ratings of fullness, hunger, prospective food consumption, satiety and a composite appetite score. h, Ad libitum energy intake evaluated during lunch and dinner after a fixed breakfast. All data reported as mean ± s.e.m. N=17 per diet for panels a and b; n=16 per diet for panels c-h. MBD—Microbiome Enhancer Diet; WD—Western Diet.

Extended Data Fig. 4.. Host response to dietary intervention.

a, Gastric emptying as evaluated by acetaminophen appearance after a fixed breakfast. b, pH within a 1-hour window of the ileocecal passage. c-g, Visual analog scale data for subjective ratings of fullness, hunger, prospective food consumption, satiety and a composite appetite score. h, Ad libitum energy intake evaluated during lunch and dinner after a fixed breakfast. All data reported as mean ± s.e.m. N=17 per diet for panels a and b; n=16 per diet for panels c-h. MBD—Microbiome Enhancer Diet; WD—Western Diet.

Extended Data Fig. 4.. Host response to dietary intervention.

a, Gastric emptying as evaluated by acetaminophen appearance after a fixed breakfast. b, pH within a 1-hour window of the ileocecal passage. c-g, Visual analog scale data for subjective ratings of fullness, hunger, prospective food consumption, satiety and a composite appetite score. h, Ad libitum energy intake evaluated during lunch and dinner after a fixed breakfast. All data reported as mean ± s.e.m. N=17 per diet for panels a and b; n=16 per diet for panels c-h. MBD—Microbiome Enhancer Diet; WD—Western Diet.

Extended Data Fig. 5. Microbial contributions to host energy balance.

a, The heatmap shows the associations between host ME and mean RA of each species. Each row is a species and each column is an individual participant. The bar graph shows the effect size of the regression coefficient between the independent variable of host metabolizable energy and each species, from compound Poisson regression models (Q < 0.25) b, Q-values for the regression coefficients shown in a, for each species (range 0.023 – 0.198). c, Bland-Altman plot comparing actual metabolizable energy (absorbed COD) measured for each participant with the model prediction with fixed CTT of 48 h for each participant. d, Bland-Altman plot comparing actual metabolizable energy (absorbed COD) measured for each participant with the model prediction with measured CTT for each participant. N=17 per diet for all panels. COD—chemical oxygen demand; ME—metabolizable energy; RA—relative abundance.

Extended Data Fig. 5. Microbial contributions to host energy balance.

a, The heatmap shows the associations between host ME and mean RA of each species. Each row is a species and each column is an individual participant. The bar graph shows the effect size of the regression coefficient between the independent variable of host metabolizable energy and each species, from compound Poisson regression models (Q < 0.25) b, Q-values for the regression coefficients shown in a, for each species (range 0.023 – 0.198). c, Bland-Altman plot comparing actual metabolizable energy (absorbed COD) measured for each participant with the model prediction with fixed CTT of 48 h for each participant. d, Bland-Altman plot comparing actual metabolizable energy (absorbed COD) measured for each participant with the model prediction with measured CTT for each participant. N=17 per diet for all panels. COD—chemical oxygen demand; ME—metabolizable energy; RA—relative abundance.

Fig 1.. The microbiome enhancer diet reduced host energy harvest.

a, Daily energy lost by each participant in feces on the WD vs. MBD in grams COD/day (gCOD/day). b, Host metabolizable energy based on the proportion of fecal COD to dietary intake. c, Calculated host non-metabolizable energy (kcals). All data reported as are mean ± s.e.m. N=17 per diet for all panels. COD—Chemical Oxygen Demand; MBD—Microbiome Enhancer Diet; WD—Western Diet

Fig 2.. Diet reprogrammed the gut microbiome.

a, Fecal bacterial biomass. b, Beta-diversity (Bray-Curtis Dissimilarity). c-d, Fecal and circulating short chain fatty acids. Data are presented as mean ± s.e.m for panels a-d. e, Heatmap shows the mean relative abundance of species whose relative abundance was significantly different by diet; bar plot shows the effect size of the regression coefficient from compound Poisson regression models comparing the relative abundance of each species by diet. Species shown in this figure were significantly different by diet (Q < 0.05), and the diet difference had an effect size ≥ 2. N=17 per diet for panels a-c and e; n=16 per diet for panel d. CAP—Canonical Analysis of Principal Coordinates; MBD—Microbiome Enhancer Diet; SCFA—short-chain fatty acids; WD—Western Diet

Fig 2.. Diet reprogrammed the gut microbiome.

a, Fecal bacterial biomass. b, Beta-diversity (Bray-Curtis Dissimilarity). c-d, Fecal and circulating short chain fatty acids. Data are presented as mean ± s.e.m for panels a-d. e, Heatmap shows the mean relative abundance of species whose relative abundance was significantly different by diet; bar plot shows the effect size of the regression coefficient from compound Poisson regression models comparing the relative abundance of each species by diet. Species shown in this figure were significantly different by diet (Q < 0.05), and the diet difference had an effect size ≥ 2. N=17 per diet for panels a-c and e; n=16 per diet for panel d. CAP—Canonical Analysis of Principal Coordinates; MBD—Microbiome Enhancer Diet; SCFA—short-chain fatty acids; WD—Western Diet

Fig 3.. Host response to diet-induced gut microbiota reprogramming.

a-c, Weight, fat mass and lean mass changes on the WD vs. MBD; n=16 per diet. D, Energy expenditure (sleep metabolic rate extrapolated to 24-hours); n=17 per diet. E-f, Colonic transit time and median colonic pH; n=17 per diet. G-I, An adipose-pancreas-gut appetite-modulating axis shown by leptin, GLP-1, and pancreatic polypeptide iAUC (n=15 per diet). All data reported as mean ± s.e.m. GLP-1—Glucagon-Like Peptide 1; iAUC—Incremental Area Under the Curve; MBD—Microbiome Enhancer Diet; WD—Western Diet

Fig 3.. Host response to diet-induced gut microbiota reprogramming.

a-c, Weight, fat mass and lean mass changes on the WD vs. MBD; n=16 per diet. D, Energy expenditure (sleep metabolic rate extrapolated to 24-hours); n=17 per diet. E-f, Colonic transit time and median colonic pH; n=17 per diet. G-I, An adipose-pancreas-gut appetite-modulating axis shown by leptin, GLP-1, and pancreatic polypeptide iAUC (n=15 per diet). All data reported as mean ± s.e.m. GLP-1—Glucagon-Like Peptide 1; iAUC—Incremental Area Under the Curve; MBD—Microbiome Enhancer Diet; WD—Western Diet

Fig 3.. Host response to diet-induced gut microbiota reprogramming.

a-c, Weight, fat mass and lean mass changes on the WD vs. MBD; n=16 per diet. D, Energy expenditure (sleep metabolic rate extrapolated to 24-hours); n=17 per diet. E-f, Colonic transit time and median colonic pH; n=17 per diet. G-I, An adipose-pancreas-gut appetite-modulating axis shown by leptin, GLP-1, and pancreatic polypeptide iAUC (n=15 per diet). All data reported as mean ± s.e.m. GLP-1—Glucagon-Like Peptide 1; iAUC—Incremental Area Under the Curve; MBD—Microbiome Enhancer Diet; WD—Western Diet

Fig. 4.. The contributions of the gut microbiome to host energy harvest.

a, The heatmap shows the associations between host ME and the mean species RA. Each row is a microbial species and each column is an individual participant. The bar graph shows the effect size of the regression coefficient between the independent variable of host metabolizable energy and each species, from compound Poisson regression models. Figure shows all significant associations with Q < 0.05 and effect size ≤ 2. b, An in silico model comparison of modeled host ME vs. actual ME using the same fixed CTT (48 h) for all participants. c, The same model with each participant’s measured CTT. d, Box plot shows microbial energy harvest through SCFAs as grams COD per day (gCOD/d) for the WD and the MBD. gCOD were calculated as the sum of acetate, propionate, n-butyrate, and iso-butyrate absorbed. Data reported as median with error bars showing minimum and maximum values and box ends showing the 2^nd and 3^rd quartiles. Diamonds are outliers that fall outside 1.5X IQR. e, The percentage of COD absorbed as SCFAs adjusted for total energy intake (in gCOD/day). N=17 per diet for all panels. CCC—concordance correlation coefficient; COD—Chemical Oxygen Demand; CTT—Colonic Transit Time; Host ME—Host Metabolizable Energy; IQR—Interquartile Range; MBD—Microbiome Enhancer Diet; SCFA—short-chain fatty acids; RA—Relative Abundance; WD—Western Diet