Barley β-glucan consumption improves glucose tolerance by increasing intestinal succinate concentrations

The gut microbiota ferments undigested dietary components, shaping metabolite profiles that influence host physiology. Diet composition rapidly modulates the microbiome and is associated with health and disease, including obesity and type 2 diabetes. Dietary fiber, particularly soluble fibers such as β-glucans, pectin, and fructans, is a key driver of microbiome and metabolite changes. Barley is rich in β-glucan and is consumed in several Asian countries; it is known to lower blood glucose and cholesterol, potentially via viscosity-mediated delayed nutrient absorption and by altering gut microbiota. Prior human and animal studies report barley-associated increases in taxa such as Bifidobacterium, Blautia, Agathobacter, and metabolites, and improvements in glucose tolerance associated with Prevotella abundance. Succinate, a microbiota-derived intermediate in the propionate pathway, has been implicated as a substrate for intestinal gluconeogenesis that improves glycemic control. Given heterogeneous findings and limited concurrent microbiome-metabolome profiling, this study tests the hypothesis that barley β-glucan increases succinate and succinate-producing bacteria, thereby improving glucose metabolism, and seeks to determine whether these effects are β-glucan-specific using β-glucan-free barley flour as control.

- Diet and microbiota: Microbiota composition responds to dietary patterns and diversity, with links to cardiometabolic health and disease. - Fiber effects: Soluble fibers (β-glucan, fructans) are fermented by gut microbes, inducing specific compositional and metabolic shifts. - Barley studies: Cross-sectional data in Japanese cohorts showed positive correlations between barley intake and fecal Bifidobacterium and butyrate. A randomized controlled trial found barley increased Blautia, Agathobacter, and some metabolites. Improvements in glucose tolerance after barley-rich bread were associated with higher Prevotella; microbiota transfer from responders improved glucose metabolism in mice. - Succinate and metabolism: Fiber-rich diets can increase succinate and succinate-producers, enhancing intestinal gluconeogenesis and improving glycemic control and energy balance in mice. Prevotella species and several Bacteroidetes and Ruminococcaceae taxa can produce succinate. Succinate may act as a signaling molecule affecting host metabolism.

Design: Two mouse studies assessing effects of barley β-glucan on gut microbiota, metabolites (including succinate), and glucose tolerance. Intervention flours: β-glucan-free barley flour (BGL; hulless barley "Shikoku-Hadaka 84") vs β-glucan-rich barley flour (BF; hulless barley "Beau fiber"). BF contained 9.8% β-glucan; BGL contained none. Total dietary fiber, protein, and lipids were measured by AOAC methods with comparable protein and lipid between flours; total dietary fiber differed by 8.5 g due to β-glucan. Study 1 (microbiome/metabolome with diet fat variation): - Animals: Eight-week-old male C57BL/6J mice (n=4 groups, 10/group). Housing: 12 h light/dark, 22±1°C, 50±5% humidity; 7-day acclimation. - Diets: 8 weeks of either normal AIN-93G-based diet or middle-fat diet (25% energy from lard fat), each containing equal amounts of BGL or BF, yielding four groups: normal+BGL, normal+BF, middle-fat+BGL, middle-fat+BF. Diets adjusted with milk casein and cellulose to equalize protein and total dietary fiber across groups. - Measurements: Body weight, food intake, food efficiency; organ weights (liver, visceral fat); cecal content weight. Cecal contents collected for microbiome and metabolome analyses. - Microbiome: DNA from cecal contents; 16S rRNA V1–V2 amplified (primers 27F-mod/338R), sequenced on Illumina MiSeq. QIIME2 with DADA2 for denoising; taxonomy via SILVA132 naive Bayes classifier. Alpha diversity (Chao1, Shannon); beta diversity (Bray–Curtis), PCoA. LEfSe for LDA effect sizes. Volcano plots for differential taxa. - Metabolome: Cecal metabolites extracted; CE-TOFMS (Agilent) in positive/negative modes; internal standards (methionine sulfone, D-camphol-10-sulfonic acid). Annotation and quantification via MasterHands; PCA/PCoA in SIMCA. Concentrations below detection set to zero. Targeted GC/MS for succinate validation. Random forest models to classify BGL vs BF using metabolites alone and combined with genus-level taxa; variable importance via caret varImp. - Statistics: Two-way ANOVA with fat (normal vs middle-fat) and barley flour (BGL vs BF) as factors; or nonparametric tests if non-normal. Volcano plots p<0.05 and fold-change cutoffs (>1.5 or <0.67). Study 2 (role of succinate uptake): - Animals: slc13a2 knockout (Slc13a2−/−) mice and wild-type (Slc13a2+/+) controls; 7-day acclimation. Genotyping by PCR with specified primers. - Diets: 8 weeks middle-fat diet (25% energy fat) with BGL or BF: groups Slc13a2+/+ BGL (n=10), Slc13a2+/+ BF (n=10), Slc13a2−/− BGL (n=10), Slc13a2−/− BF (n=10). Two Slc13a2−/− mice in BF group with growth defects were excluded. - Outcomes: Cecal microbiota (16S as above), cecal short-chain fatty acids (SCFAs) and organic acids by GC-MS (crotonic acid internal standard), and oral glucose tolerance test (OGTT; 20% glucose at 1.5 g/kg; blood glucose at 0, 15, 30, 60, 120 min with enzymatic assay). Organ and cecal content weights collected at termination. - Statistics: Two-way ANOVA with genotype and barley flour as factors; repeated-measures ANOVA for OGTT (time and barley flour). Beta diversity via Bray–Curtis PCoA; volcano plots for differential taxa. Significance at 5%.

- β-glucan dominates over dietary fat in shaping gut microbiota and metabolites (Study 1): PCoA of cecal microbiota and metabolome separated samples by barley flour type (BF vs BGL) independent of fat content, indicating a strong β-glucan effect. - Taxa increased with BF: Relative abundances of Bacteroides, Ruminococcus 1, and Parasutterella significantly increased with BF compared to BGL; LEfSe identified Bacteroides and Parasutterella as characteristic of BF. - Metabolites increased with BF: Succinate and glucose-6-phosphate (G6P) were significantly elevated in BF vs BGL. Random forest classification identified succinate, azelate, and glutarate as important discriminators of BF vs BGL; adding microbiota data highlighted succinate, Bacteroides, and Parasutterella as key variables. - Succinate pathway activation: Malate, fumarate, and succinate were consistently higher in BF groups. GC/MS quantification confirmed increased succinate. Succinate correlated positively with Bacteroides and Parasutterella, and negatively with certain Clostridiales/Ruminococcaceae genera, supporting activation of succinate-producing pathways by BF. - Genotype vs diet effects (Study 2): In Slc13a2+/+ and Slc13a2−/− mice, weighted PCoA showed major microbiota differences driven by BF vs BGL rather than genotype; Parasutterella and Muribaculaceae increased with BF in both genotypes. - Organic acids/SCFAs in Slc13a2 models: In Slc13a2+/+ mice, BF increased cecal acetate and succinate. In Slc13a2−/− mice, succinate hyperaccumulated under both BGL and BF due to impaired uptake, with relative decreases in SCFAs (acetate, propionate, butyrate). - Glucose tolerance: In Slc13a2+/+ mice, BF significantly reduced blood glucose during OGTT at 30, 60, and 120 minutes and lowered iAUC versus BGL, indicating improved glucose tolerance attributable to β-glucan. This glucose-lowering effect was attenuated in Slc13a2−/− mice, implicating succinate uptake in mediating β-glucan’s metabolic benefits. - Additional phenotypes: BF reduced visceral fat weight compared with BGL irrespective of diet fat content; cecal content weight increased with BF; middle-fat BF reduced body weight, food intake, and food efficiency ratio versus BGL.

The study tested whether barley β-glucan specifically modulates the gut microbiota and metabolome to increase succinate and improve glucose metabolism. Across two dietary fat levels, β-glucan robustly restructured the cecal microbiota and metabolome, increasing Bacteroides and Parasutterella—taxa capable of fermenting glycans and producing succinate—and elevating intermediates in the succinate pathway. Correlations between these taxa and succinate, and random forest feature importance, support a mechanistic link between β-glucan fermentation and succinate production. In vivo relevance was probed using Slc13a2-deficient mice that lack a key dicarboxylate transporter for succinate uptake. While β-glucan similarly shifted microbiota composition in both genotypes, only wild-type mice exhibited improved glucose tolerance after BF intake; this effect was attenuated in Slc13a2−/− mice, which showed succinate accumulation and reduced SCFAs. These findings align with prior reports that microbiota-derived succinate serves as a substrate for intestinal gluconeogenesis, enhancing glycemic control. The lack of an increase in propionate despite elevated succinate suggests potential bottlenecks, such as vitamin B12-dependent steps (methylmalonyl-CoA mutase) or community composition favoring succinate accumulation. Overall, the data indicate that β-glucan-induced succinate production and host succinate handling are integral to the glucose-lowering effects of barley β-glucan.

Barley β-glucan intake selectively increases succinate-producing bacteria (notably Bacteroides and Parasutterella) and elevates succinate and upstream pathway intermediates in the gut. In wild-type mice, these changes coincide with improved glucose tolerance, whereas Slc13a2 deficiency, which impairs succinate uptake, attenuates the glucose-lowering effect, implicating succinate as a mediator of β-glucan’s metabolic benefits. The work identifies succinate and succinate-producing microbes as β-glucan-associated signatures and supports a succinate–intestinal gluconeogenesis mechanism for improved glycemic control. Future research should: (i) directly test whether β-glucan fermentation by specific taxa increases succinate via in vitro fermentation models; (ii) assess vitamin B12 availability and its impact on succinate-to-propionate conversion during barley intake; (iii) define succinate concentration ranges that optimize metabolic benefits without adverse effects; and (iv) evaluate translational relevance in human trials with integrated metabologenomic profiling.

- Causality between specific taxa (e.g., Bacteroides, Parasutterella) and succinate production was inferred from correlations; direct mechanistic proof (e.g., in vitro fermentation, gnotobiotic models) is lacking. - Potential constraints on succinate-to-propionate conversion (e.g., vitamin B12 availability) were not measured. - Succinate accumulation can influence inflammation and diarrhea; although overt diarrhea was not observed and body weight increased, comprehensive assessment of inflammatory markers was not reported. - Mouse model findings may not directly generalize to humans; only two barley varieties were tested, and food form/matrix effects may differ in practice. - In Study 2, two Slc13a2−/− mice in the BF group were excluded due to growth defects, which could affect group comparisons; sample sizes after exclusion were not detailed per group.