Boets, E. et al. (2017) Systemic availability and metabolism of colonicderived short-chain fatty acids in healthy subjects: a stable isotope study. Journal of Physiology, 595(2), pp. 541-555. (doi:10.1113/JP272613) This is the author's final accepted version.There may be differences between this version and the published version. You are advised to consult the publisher's version if you wish to cite from it.http://eprints.gla.ac.uk/128777/ Key Point Summary SCFAs are bacterial metabolites produced during colonic fermentation of undigested carbohydrates, such as dietary fibre and prebiotics, and could mediate the interaction between diet, the microbiota and the host. We quantified the fraction of colonic administered SCFA that could be recovered in the systemic circulation, the fraction that was excreted via breath and urine and the fraction that was used as a precursor for glucose, cholesterol and fatty acids. This information is essential to understand the molecular mechanisms by which SCFA beneficially affect physiological functions such as glucose and lipid metabolism and immune function. AbstractThe short-chain fatty acids (SCFAs), acetate, propionate and butyrate are bacterial metabolites that mediate the interaction between diet, the microbiota and the host. In this study, the systemic availability of SCFAs and their incorporation into biologically relevant molecules was quantified. Known amounts of 13 C-labelled acetate, propionate and butyrate were introduced in the colon of 12 healthy subjects using colon delivery capsules and plasma levels of 13 C-SCFAs and of 13 C-glucose, 13 C-cholesterol and 13 C-fatty acids were measured.The butyrate producing capacity of the intestinal microbiota was quantified as well. Systemic availability of colonic-administered acetate, propionate and butyrate was 36%, 9% and 2%, respectively. Conversion of acetate into butyrate (24%) was the most prevalent interconversion by the colonic microbiota and was not related to the butyrate-producing capacity in the faecal samples. Less than 1% of administered acetate was incorporated into cholesterol and <15% in fatty acids. On average, 6% of colonic propionate was incorporated into glucose. The SCFAs were mainly excreted via the lungs after oxidation to 13 CO 2 whereas less than 0.05% of the SCFAs were excreted into urine. These results will allow future evaluation and quantification of SCFAs production from 13 C-labelled fibres in the human colon by measuring 13 C-labelled SCFA concentrations in blood.

Short chain fatty acids (SCFA), including acetate, propionate, and butyrate, are produced during bacterial fermentation of undigested carbohydrates in the human colon. In this study, we applied a stable-isotope dilution method to quantify the in vivo colonic production of SCFA in healthy humans after consumption of inulin. Twelve healthy subjects performed a test day during which a primed continuous intravenous infusion with [1-13C]acetate, [1-13C]propionate and [1-13C]butyrate (12, 1.2 and 0.6 μmol·kg−1·min−1, respectively) was applied. They consumed 15 g of inulin with a standard breakfast. Breath and blood samples were collected at regular times during the day over a 12 h period. The endogenous rate of appearance of acetate, propionate, and butyrate was 13.3 ± 4.8, 0.27 ± 0.09, and 0.28 ± 0.12 μmol·kg−1·min−1, respectively. Colonic inulin fermentation was estimated to be 137 ± 75 mmol acetate, 11 ± 9 mmol propionate, and 20 ± 17 mmol butyrate over 12 h, assuming that 40%, 10%, and 5% of colonic derived acetate, propionate, and butyrate enter the systemic circulation. In conclusion, inulin is mainly fermented into acetate and, to lesser extents, into butyrate and propionate. Stable isotope technology allows quantifying the production of the three main SCFA in vivo and proved to be a practical tool to investigate the extent and pattern of SCFA production.

Consumption of wheat bran (WB) has been associated with improved gastrointestinal health and a reduced risk for colorectal cancer, cardiovascular diseases and metabolic disorders.These benefits are likely mediated by a combination of mechanisms, including colonic fermentation of the WB fibre, faecal bulking and the prevention of oxidative damage due to its antioxidant capacities. The relative importance of those mechanisms is not known and may differ for each health effect. WB has been modified by reducing particle size, heat treatment or modifying tissue composition to improve its technological properties and facilitate bread making processes. However, the impact of those modifications on human health has not been fully elucidated. Some modifications reinforce whereas others attenuate the health effects of coarse WB. This review summarises available WB modifications, the mechanisms by which WB induces health benefits, the impact of WB modifications thereon and the available evidence for these effects from in vitro and in vivo studies.

Wheat bran (WB) is a constituent of whole grain products with beneficial effects for human health. Within the human colon, such insoluble particles may be colonized by specific microbial teams which can stimulate cross-feeding, leading to a more efficient carbohydrate fermentation and an increased butyrate production. We investigated the extent to which WB fractions with different properties affect the fermentation of other carbohydrates in the colon. Ten healthy subjects performed four test days, during which they consumed a standard breakfast supplemented with 10 g 13C-inulin. A total of 20 g of a WB fraction (unmodified WB, wheat bran with a reduced particle size (WB RPS), or de-starched pericarp-enriched wheat bran (PE WB)) was also added to the breakfast, except for one test day, which served as a control. Blood samples were collected at regular time points for 14 h, in order to measure 13C-labeled short-chain fatty acid (SCFA; acetate, propionate and butyrate) concentrations. Fermentation of 13C-inulin resulted in increased plasma SCFA for about 8 h, suggesting that a sustained increase in plasma SCFA can be achieved by administering a moderate dose of carbohydrates, three times per day. However, the addition of a single dose of a WB fraction did not further increase the 13C-SCFA concentrations in plasma, nor did it stimulate cross-feeding (Wilcoxon signed ranks test).

Background Digital food registration via online platforms that are coupled to large food databases obviates the need for manual processing of dietary data. The reliability of such platforms depends on the quality of the associated food database. Objective In this study, we validate the database of MyFitnessPal versus the Belgian food composition database, Nubel. Methods After carefully given instructions, 50 participants used MyFitnessPal to each complete a 4-day dietary record 2 times (T1 and T2), with 1 month in between T1 and T2. Nutrient intake values were calculated either manually, using the food composition database Nubel, or automatically, using the database coupled to MyFitnessPal. First, nutrient values from T1 were used as a training set to develop an algorithm that defined upper limit values for energy intake, carbohydrates, fat, protein, fiber, sugar, cholesterol, and sodium. These limits were applied to the MyFitnessPal dataset extracted at T2 to remove extremely high and likely erroneous values. Original and cleaned T2 values were correlated with the Nubel calculated values. Bias was estimated using Bland-Altman plots. Finally, we simulated the impact of using MyFitnessPal for nutrient analysis instead of Nubel on the power of a study design that correlates nutrient intake to a chosen outcome variable. Results Per food portion, the following upper limits were defined: 1500 kilocalories for total energy intake, 95 grams (g) for carbohydrates, 92 g for fat, 52 g for protein, 22 g for fiber, 70 g for sugar, 600 mg for cholesterol, and 3600 mg for sodium. Cleaning the dataset extracted at T2 resulted in a 2.8% rejection. Cleaned MyFitnessPal values demonstrated strong correlations with Nubel for energy intake (r=0.96), carbohydrates (r=0.90), fat (r=0.90), protein (r=0.90), fiber (r=0.80), and sugar (r=0.79), but weak correlations for cholesterol (ρ=0.51) and sodium (ρ=0.53); all P values were ≤.001. No bias was found between both methods, except for a fixed bias for fiber and a proportional bias for cholesterol. A 5-10% power loss should be taken into account when correlating energy intake and macronutrients obtained with MyFitnessPal to an outcome variable, compared to Nubel. Conclusions Dietary analysis with MyFitnessPal is accurate and efficient for total energy intake, macronutrients, sugar, and fiber, but not for cholesterol and sodium.