Sucrose-preferring gut microbes prevent host obesity by producing exopolysaccharides

Sucrose-preferring gut microbes prevent host obesity by producing exopolysaccharides | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Biological Sciences - Article Sucrose-preferring gut microbes prevent host obesity by producing exopolysaccharides Ikuo Kimura, Hidenori Shimizu, Junki Miyamoto, Keiko Hisa, Ryuji Ohue-Kitano, and 31 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3889905/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 29 Jan, 2025 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Abstract Commensal bacteria affect host health by producing various metabolites from dietary carbohydrates via bacterial glycometabolism; however, the underlying mechanism of action remains unclear. Here, we identified Streptococcus salivarius as a unique anti-obesity commensal bacterium. We found that S. salivarius may prevent host obesity caused by excess sucrose intake via the exopolysaccharide (EPS)-short-chain fatty acid (SCFA)-carbohydrate metabolic axis. Healthy human donor-derived S. salivarius produced high EPS levels from sucrose but not from other sugars. S. salivarius abundance was significantly decreased in human donors with obesity, and the EPS-SCFA bacterial carbohydrate metabolic process was attenuated. Our findings reveal an important mechanism by which host–commensal interactions in glycometabolism affect energy regulation, suggesting an approach for preventing lifestyle-related diseases via prebiotics and probiotics by targeting bacteria and EPS metabolites. Biological sciences/Microbiology Biological sciences/Physiology Health sciences/Diseases/Metabolic disorders Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Although diet is the most important factor for daily nutrient acquisition, dysregulation of energy homeostasis due to excessive dietary intake, particularly high fat and sugar intake, leads to obesity 1 , 2 . Sucrose (table sugar), glucose (dextrose), and fructose (fruit sugar) are simple saccharides. Of the sugars consumed daily 3 , 4 , sucrose and glucose are the most common. As sucrose intake increases in Western countries, sucrose-rich diets may be associated with rising health problems, such as obesity and diabetes. Although bacteria also utilize these sugars as an energy source, their metabolic pathway differs from that of humans 5 , 6 . After glycolysis, anaerobic bacteria convert pyruvate to lactate and other organic acids such as short-chain fatty acids (SCFAs; acetate, propionate, and butyrate). Gut microbes produce these end products through sugar metabolism in environments where oxygen is limited 5 , 6 . They produce SCFAs from fermentable fibres, which are indigestible polysaccharides that are not absorbed by the small intestine because host enzymes cannot digest them 7 , 8 . The SCFAs act as energy sources for the host and as signalling factors via host G protein-coupled receptors GPR41 and GPR43, improving the host homeostasis by acting on the endocrine systems 9 – 11 . GPR41 influences host metabolic functions, enhances sympathetic activity, and promotes gut hormone secretion 11 – 13 , while GPR43 suppresses fat accumulation and promotes gut hormone secretion 11 , 12 , 14 . Sugars are anabolized into polysaccharides during glycometabolism. Storage polysaccharides such as glycogen and starch are carbohydrates used to store and provide energy. In animals, glycogen is primarily stored in the liver and muscles 3 , resulting in sudden increases in energy requirements. Additionally, starch, found in grains, potatoes, and legumes, is the main form of sugar stored in plants 5 . They serve as energy sources and are broken down into glucose during digestion. Bacteria also produce different types of storage polysaccharides, such as levans and dextrans 15 – 17 , depending on the type of bacteria and environmental conditions. We have recently reported that prebiotics associated with the exopolysaccharide (EPS) produced by Leuconostoc mesenteroides provide substantial metabolic benefits to the host 18 , 19 . This polysaccharide is indigestible because its glycosidic linkages cannot be cleaved by host amylase. Furthermore, fermented foods, such as pickles, kimchi, and sauerkraut, are produced by the fermentative action of L. mesenteroides , lactic acid bacteria 20 , 21 . These findings suggest that some gut microbes may produce indigestible polysaccharides from sugars and contribute to host metabolic benefits. Therefore, in this study, we sought high-EPS-producing gut microbes in humans and investigated the relationship between host sugar intake and the prebiotic effects of gut microbe-produced EPS, as well as the molecular mechanism underlying the effect of microbial metabolites on host health. Results Isolation of EPS-producing human commensal bacteria S. salivarius We first screened EPS-producing bacteria using bacterial ropy colonies as an indicator 22 in human faeces (472 donors) (Extended Data Fig. 1 ). These samples were cultured on de Man, Rogosa, and Sharpe (MRS) agar with different sugar sources (Fig. 1 a). Bacterial ropy colonies (47 donors) were then observed in the culture of human faeces with sucrose alone, excluding other sugar sources. However, such colonies were absent in the culture of mouse faeces with sucrose (Fig. 1 a). The bacterial colonies were identified as Weissella cibaria (19 donors), L. mesenteroides (14 donors), Streptococcus salivarius (six donors), Weissella confuse (five donors), and Leuconostoc lactis (three donors) (Fig. 1 b). Among them, only S. salivarius is a human commensal bacterium, while the others are lactic acid bacteria commonly found in fermented foods 23 , 24 . Furthermore, we investigated the relationship between the presence of bacteria in human faeces and the body mass index (BMI) of donors (Fig. 1 c). Remarkably, only S. salivarius was sufficiently detected in all donors, and its occupancy showed an inverse correlation with obesity (BMI ≥ 30). Therefore, we focused on S. salivarius . The isolated S. salivarius (a gram-positive, spherical, facultative anaerobe) produced EPS on MRS agar with sucrose (Extended Data Fig. 2 a). S. salivarius -produced EPS (SsEPS) was purified by ethanol precipitation/dialysis and analysed using 1 H NMR spectroscopy. The purified SsEPS consisted of levan (fructan, with linear structures of fructose linked by β-2,6-glycosidic bonds) and dextran (α-glucan, with main-chain glucose monomers linked by α-1,6-glycosidic bonds and branched by α-1,3-glycosidic side chains) (Fig. 1 d and Extended Data Fig. 2 b–i). In MRS broth containing 15% sucrose, S. salivarius produced large amounts of EPS (13 mg/mL). However, when the MRS medium contained 15% glucose, 15% fructose, or 7.5% glucose + 7.5% fructose, EPS production failed despite bacterial proliferation (Fig. 1 e). Upon RNA sequencing, KEGG orthology (KO) analysis showed that the EPS synthesis pathway was enriched in sucrose-supplemented S. salivarius culture (Fig. 1 f and Extended Data Fig. 3 a). Furthermore, 14 putative glycosyltransferase-encoding genes were extracted by comparing their mRNA expression between sucrose- and glucose-supplemented cultures (Fig. 1 g). The mRNA expression of the five putative glycosyltransferase genes significantly increased along with the SsEPS yield in the medium containing 15% sucrose, but not in the medium containing glucose (Extended Data Fig. 3 b). Additionally, levansucrase and glycosyltransferase, RS02300 and RS07295, were highly expressed after sucrose supplementation. Therefore, SsEPS may be synthesized by the putative levansucrase and glycosyltransferase, RS02300 and RS07295, respectively. Thus, the human commensal bacterium S. salivarius produces large amounts of EPS in the form of levans and dextrans. We investigated the gut microbial composition between lean and donors with obesity (Extended Data Fig. 4 a). Besides the occupancy of S. salivarius , the levels of SCFAs and EPS in the faeces of lean donors were significantly higher than those in donors with obesity (Fig. 1 h). The shotgun metagenomic sequencing data showed that obesity was associated with the carbohydrate metabolic pathway. Correlation analysis revealed a strong correlation between EPS hydrolase, glycolysis, and SCFA production (Extended Data Fig. 4 b). Moreover, glycolytic pathway analysis showed that obesity attenuated EPS and glycolysis pathways (Fig. 1 i). Therefore, human obesity is associated with a decrease in S. salivarius and attenuation of EPS and SCFAs synthesis cascades. Improvement of host metabolic functions by SsEPS Subsequently, we investigated the bacteria associated with SCFA production from SsEPS using in vitro gut microbe monoculture screening 25 . Among the 47 gut microbial strains tested, Bacteroides species, B. ovatus and B. thetaiotaomicron , and Bacteroidales S24-7 group members, Muribaculum intestinale , Paramuribaculum intestinale , and Duncaniella muris , efficiently produced SCFAs after 0.3% SsEPS addition. In contrast, other gut microbes did not produce SCFAs (Fig. 2 a). To determine whether SsEPS is an indigestible polysaccharide, we examined intestinal SCFA levels after SsEPS intake. The levels of faecal and plasma SCFAs (acetate, propionate, and butyrate) were significantly higher in mice fed a high-fat diet (HFD) supplemented with SsEPS than in those fed an HFD supplemented with cellulose (Fig. 2 b). Thus, in the host intestine, consumption of SsEPS promotes the production of SCFAs by gut microbes. We investigated the SsEPS effects on host energy homeostasis in HFD-induced obese mice. Four-week-old mice were fed an HFD supplemented with either SsEPS or cellulose as non-fermented fibre for 12 weeks. The body weight of the mice fed with SsEPS was markedly lower than that of control mice fed with cellulose during growth (Fig. 2 c). Furthermore, the fat mass of the white adipose tissue (WAT) of SsEPS-fed mice was significantly lower than that of the control mice at 16 weeks of age (Fig. 2 c). Blood glucose, plasma triglyceride (TGs), non-esterified fatty acid (NEFAs), and total cholesterol levels in SsEPS-fed mice were significantly lower than those in the cellulose-fed control mice (Fig. 2 d and Extended Data Fig. 5a). HFD-induced insulin resistance and impaired glucose tolerance, as assessed by insulin tolerance test (ITT) and glucose tolerance test (GTT), respectively, were significantly attenuated in SsEPS-fed mice compared to those in the cellulose-fed control mice (Extended Data Fig. 5b). Additionally, plasma insulin levels were significantly lower and plasma GLP-1 levels were significantly higher in SsEPS-fed mice than in cellulose-fed control mice (Fig. 2 e and Extended Data Fig. 5c). Moreover, the resulting food intake was significantly lower in SsEPS-fed mice than in cellulose-fed control mice (Extended Data Fig. 5d). However, these SsEPS-induced effects, such as the suppression of body and fat weight gain (Fig. 2 c), reduced hyperglycemia and hyperlipidemia (Fig. 2 d and Extended Data Fig. 5a), increased plasma GLP-1 levels (Fig. 2 e), and improved insulin sensitivity (Extended Data Fig. 5b), were sufficiently attenuated in Gpr41Gpr43 double-deficient mice. Dietary fibre-derived gut microbial SCFAs promote gut hormone secretion, such as GLP-1, through GPR41 and GPR43, thereby maintaining energy homeostasis and glucose metabolism 11 . Therefore, continuous SsEPS intake improves energy homeostasis. Additionally, we examined the effects of SsEPS-derived gut microbial SCFAs on glucose homeostasis in the host using GTT. Administration of SsEPS significantly attenuated the increase in blood glucose levels after glucose administration compared to that in control mice; this effect was abolished in Gpr41Gpr43 double-deficient mice (Fig. 2 f). Moreover, the plasma levels of insulin and incretin GLP-1 were higher in SsEPS-administered mice than in control mice after glucose administration. These effects were abolished in Gpr41Gpr43 double-deficient mice (Fig. 2 f and Extended Data Fig. 5e). Furthermore, under germ-free (GF) conditions, the SsEPS-induced inhibition of blood glucose elevation and the SsEPS-induced increase in plasma insulin and GLP-1 levels were abolished (Fig. 2 g and Extended Data Fig. 5e). Therefore, SsEPS supplementation improves glucose homeostasis in the host by producing gut microbial SCFAs. Change of host gut microbiota by SsEPS Continuous SsEPS intake markedly increased SCFA levels in the faeces and plasma (Fig. 2 b). Given the pivotal role SCFAs play in the beneficial effects of SsEPS on the host, we investigated the changes in the gut microbial composition mediated by SsEPS and identified the gut microbes related to SCFAs production. 16S rRNA amplicon sequencing showed that SsEPS supplementation altered the relative abundances of the major phyla in the gut microbiota (Fig. 3 a). Notably, the abundances of Bacteroidota and Verrucomicrobiota were significantly increased, while that of Firmicutes was significantly decreased in SsEPS-fed mice (Fig. 3 a). The effect of SsEPS on the gut microbiome was confirmed by the hierarchical clustering of individual families (Fig. 3 b). These changes in the gut microbiota after SsEPS intake were associated with the abundance of several families of gut microbes (Fig. 3 b). Subsequently, a correlation analysis between the gut microbes and SCFAs by comparing these gut microbes at the genus level (Fig. 3 c) showed high correlation coefficients for Bacteroidales S24-7, including Muribaculum , Paramuribaculum , Duncaniella , and Bacteroides (Fig. 3 d). In addition, the abundance of five species which efficiently produced SCFAs during in vitro gut microbe monoculture (Fig. 2 a) significantly increased after SsEPS supplementation (Fig. 3 e). As shown by the shotgun metagenomic sequencing data, SsEPS uptake was associated with the carbohydrate metabolic pathway according to GO enrichment analysis (Extended Data Fig. 6). Furthermore, glycolytic pathway analysis showed that SsEPS intake increased levan and glucan degradation, and SCFAs synthesis (Fig. 3 f). Thus, SsEPS intake contributes to the production of SCFAs via the polysaccharide catabolic cascade of members of the Bacteroidales S24-7 group and the genus Bacteroides . Amelioration of sucrose-induced metabolic dysfunction by S. salivarius S. salivarius and SsEPS were detected in human faeces but not in mouse faeces (Fig. 1 a). While Bacteroides and Bacteroidales S24-7 groups are SCFA producers by SsEPS intake in mice, the Bacteroidales S24-7 group is not dominant in humans 26 . Therefore, we performed a co-transfer experiment for these species ( B. ovatus and B. thetaiotaomicron ) and confirmed their intestinal colonisation (Extended Data Fig. 7a–c). We found that faecal EPS levels were sufficiently higher in S. salivarius -colonised and S. salivarius - and Bacteroides -co-colonised mice but not in Bacteroides -colonised mice after drinking 20% sucrose than in GF mice (Fig. 4 a and Extended Data Fig. 7d). Faecal acetate and propionate levels were markedly higher only in S. salivarius and Bacteroides -co-colonised mice. Conversely, butyrate levels were similar between these groups (Fig. 4 b). Butyrate production by SsEPS intake (Fig. 2 b) was not reflected in the gnotobiotic experiments, possibly because of the interaction of other gut microbes besides Bacteroides . Thus, S. salivarius produces EPS, and Bacteroides produces SCFAs from SsEPS in the gut. Two weeks after colonisation, glucose clearance, as assessed using intraperitoneal GTT (ipGTT) in S. salivarius - and Bacteroides -co-colonised mice, notably improved between these groups (Fig. 4 c). Plasma insulin and GLP-1 levels after glucose administration were higher in S. salivarius and Bacteroides -co-colonised mice than in S. salivarius or Bacteroides -colonised mice. However, it has been reported that plasma GLP-1 levels are very high in GF mice (Fig. 4 d) 27 , 28 . Moreover, we examined the effects of S. salivarius and Bacteroides co-colonisation on host energy homeostasis in a sucrose-induced obese mouse model. The body weight of S. salivarius and Bacteroides -co-colonised mice was markedly lower than those of GF or other colonised mice during growth (Fig. 4 e). Additionally, the WAT fat mass was notably lower in S. salivarius and Bacteroides -co-colonised mice than in the other groups at 16 weeks of age (Fig. 4 e). The blood glucose, plasma triglyceride, and NEFAs levels of S. salivarius and Bacteroides -co-colonised mice were significantly lower than those of GF mice (Fig. 4 f and Extended Data Fig. 7e). Furthermore, plasma GLP-1 levels were significantly higher in S. salivarius and Bacteroides -co-colonised mice than in either S. salivarius - or Bacteroides -colonised mice (Fig. 4 g). Conversely, in the glucose- or fructose-induced obese mouse models, S. salivarius -colonised mice did not show an increase in faecal EPS levels (Extended Data Fig. 7f). Therefore, S. salivarius and Bacteroides -co-colonisation improved the metabolic state of the host upon sucrose intake. Finally, we investigated the effects of S. salivarius on host energy homeostasis using a mouse model of human flora. In this experiment, 7-week-old mice colonised with S. salivarius -dominant [Ss (+)] or S. salivarius -non-dominant human gut microbiota [Ss (-)] were fed an HFD supplemented with sugars (sucrose, glucose, or fructose) for 9 weeks (Extended Data Fig. 8a–c). In faecal microbiota transplantation (FMT) experiments, faecal SCFAs and EPS levels of [Ss (+)]-colonised mice with sucrose supplementation were significantly higher than those of [Ss (-)]-colonised mice with sucrose supplementation, and also higher than those of mice with glucose or fructose supplementation (Extended Data Fig. 9a, b). The number of S. salivarius was also sufficiently increased in [Ss (+)]-colonised mice with sucrose supplementation than in [Ss (-)]-colonised mice with sucrose, glucose, or fructose supplementation (Extended Data Fig. 9c). The body weight of [Ss (+)]-colonised mice supplemented with sucrose was markedly lower than that of [Ss (-)]-colonised mice supplemented with sucrose during growth, whereas it was similar between [Ss (+)]- and [Ss (-)]-colonised mice supplemented with glucose or fructose (Fig. 4 h). Additionally, WAT fat mass was significantly lower in [Ss (+)]-colonised mice with sucrose supplementation than in [Ss (-)]-colonised mice with sucrose supplementation, but not in those with glucose or fructose supplementation, at 16 weeks of age (Fig. 4 h). The blood glucose levels of [Ss (+)] sucrose-supplemented colonised mice were significantly lower than those of [Ss (-)] sucrose-supplemented mice, but not glucose- or fructose-supplemented colonised mice (Fig. 4 i). Furthermore, plasma GLP-1 levels were significantly higher in [Ss (+)]-colonised mice supplemented with sucrose than in [Ss (-)]-colonised mice supplemented with sucrose (Fig. 4 j). Thus, S. salivarius -dominant human gut microbiota efficiently ameliorated sucrose-induced metabolic dysfunction. Discussion Commensal bacteria affect host energy homeostasis by producing various metabolites from host carbohydrate intake via glycometabolism. However, its exact mechanism of action remains unclear. In this study, we found that gut microbes prevent host obesity through excess dietary sucrose intake via the exopolysaccharide (EPS)–SCFA–carbohydrate metabolism axis and identified S. salivarius as a unique anti-obesity commensal bacterium. In the first screening, we identified only commensal S. salivarius as a high-EPS-producing bacterium in human donors because all other high-EPS-producing bacteria were bacteria living in fermented foods. Additionally, while other human gut microbes may produce different EPS, S. salivarius , being the dominant bacterium in the gut microbiota, can produce large amounts of EPS from sucrose, suggesting that host sucrose intake affects the production of SCFAs, depending on SsEPS. In contrast, EPS has diverse polysaccharide structures, monosaccharide components, main-chain lengths, and branching 22 , 29 . Although our study demonstrated that SsEPS was metabolised to SCFAs by gut microbes, thereby affecting host metabolic conditions, it is possible that EPS itself directly affects host physiological functions or that SCFAs affect the host in a receptor-independent manner, such as through de novo metabolic function via SCFA transporters and histone deacetylase inhibition 30 , 31 . Moreover, differences in S. salivarius strains may affect the EPS structure and production. Further studies on S. salivarius are required to clarify the relationship between homeostasis in humans and gut microbial EPS production. Moreover, we need to clarify the physiological significance of the relationship between the host and gut regarding the observation that S. salivarius synthesizes EPS only from sucrose and not from glucose or fructose. As a facultatively anaerobic lactic acid bacterium, S. salivarius preferentially inhabits the small intestine, contrary to most other gut microbes that inhabit the colon. This preference is because sucrose, a disaccharide composed of glucose and fructose, is digested by host sucrase into its constituent monosaccharides, which are absorbed in the small intestine. Therefore, S. salivarius competes with the host sucrose in the small intestine and inhibits the absorption of monosaccharides by the host. Furthermore, SsEPS, an indigestible polysaccharide produced from sucrose by S. salivarius , is not digested by the host enzyme; Bacteroides utilizes it to produce SCFAs in the gut. The produced SCFAs contribute to the metabolic health of the host (graphic abstract). Therefore, S. salivarius and EPS may partly contribute to metabolic improvement and high SCFA production by α-glucosidase inhibitors 32 , 33 . In the present study, we demonstrated that commensal bacteria selectively confer obesity tolerance to their hosts through bacterial glycoanabolism. Indigestible polysaccharides play a critical role in regulating the host gut environment and homeostasis by modulating gut microbiota 5 , 7 , 10 . These findings suggest a fundamental mechanism underlying the interplay among diet, host, and commensal bacteria for energy homeostasis via host and commensal glycometabolism through gut microbial EPS production. Additionally, they contribute to the development of breakthrough anti-obesity drugs for high sugar intake in present dietary lifestyles by using probiotics of S. salivarius and thus prompting the proliferation of S. salivarius in the intestine or functional foods and dietary supplements by tailoring the prebiotic use of EPS as dietary fibre for the prevention of lifestyle diseases. Declarations Acknowledgments This works was supported by research grants from the AMED (JP17gm1010007 and JP23gm1510011), JSPS KAKENHI (JP21H04862 to I.K., JP22K17771 to J.M., and 21K19813 to S.N.), JST-OPERA (JPMJOP1833), JST-MOONSHOOT (JPMJMS2023 to I.K. and S.N.), and Noster Inc (to I.K.). Author contributions H.S. performed the experiments and wrote the paper; J.M. performed the experiments and wrote the paper; K.H. performed the experiments and interpreted the data; R.O.K. performed the experiments and interpreted the data; H.T. performed the experiments and interpreted the data; M.Y. performed the experiments; A.N. performed the experiments; D.S. performed the experiments and interpreted the data; Y.M. performed the experiments; K.W. performed the experiments; S.N. performed the experiments; S.T. performed the experiments; T.I. performed the experiments; Y.N. performed the experiments; N.Y. performed the experiments; C.M. performed the experiments and interpreted the data; T.K. performed the experiments; I.H. performed the experiments; A.M. performed the experiments and interpreted the data; R.A. performed the experiments and interpreted the data; S.K. performed the experiments; M.U. performed the experiments; T.M. performed the experiments and interpreted the data; S.I. performed the experiments and interpreted the data; J.I. performed the experiments and interpreted data; N.S.A. performed the experiments and interpreted the data; H.T. performed the experiments and interpreted the data; H.M. performed the experiments and interpreted the data; S.N. performed the experiments and interpreted the data; T.Y. performed the experiments and interpreted the data; A.T. performed the experiments and interpreted the data; K.Y. performed the experiments and interpreted the data; H.O. performed the experiments and interpreted the data; T.K. performed the experiments and interpreted the data; H.I. performed the experiments and interpreted the data; I.K. supervised the project, interpreted the data, and wrote the paper; I.K. had primary responsibility for the final content. All authors read and approved the final version of the manuscript. Competing interests H.S, K.H, and D.S. are employees of Noster Inc. Otherwise the authors have no competing interests. Data availability The 16S rRNA sequencing data have been deposited into the DNA Data Bank of Japan (DDBJ) under accession Nos. DRA017528, DRA017529, and DRA017628. The shotgun metagenomic sequencing date are available under accession Nos. DRA017626 and DRA017627. RNA sequencing data are accessible via accession Nos. DRA017530 and E-GEAD-664. Source data for Figs 1–4, Extended Data Figs 1–9, 16S rRNA sequencing, shotgun metagenomic sequencing, and RNA sequencing data have been deposited into the Dryad repository (doi:10.5061/dryad.n8pk0p33b). All data generated or analysed during this study that are not included in this published article or its Supplementary Information files are available from the corresponding authors upon reasonable request. References Kahn, S. E., Hull, R. L. & Utzschneider, K. M. 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Bacterial exopolysaccharides from extreme marine habitats: production, characterization and biological activities. Mar Drugs. 8 (2010). https://doi.org/10.3390/md8061779 Furusawa, Y. et al. Commensal microbe-derived butyrate induces the differentiation of colonic regulatory T cells. Nature 504 , 446–450 (2013). https://doi.org/10.1038/nature12721 Salazar, N. et al. Functional Effects of EPS-Producing. Front Microbiol 10 , 1809 (2019). https://doi.org/10.3389/fmicb.2019.01809 Smith, B. J. et al. Changes in the gut microbiome and fermentation products concurrent with enhanced longevity in acarbose-treated mice. BMC Microbiol 19 , 130 (2019). https://doi.org/10.1186/s12866-019-1494-7 Zhang, X. et al. Effects of acarbose on the gut microbiota of prediabetic patients: a randomized, double-blind, controlled crossover trial. Diabetes Ther. 8 , 293–307 (2017). https://doi.org/10.1007/s13300-017-0226-y Bushnell, B., Rood, J. & Singer, E. BBMerge - Accurate paired shotgun read merging via overlap. PLoS One 12 , e0185056 (2017). https://doi.org/10.1371/journal.pone.0185056 Blanco-Míguez, A. et al. Extending and improving metagenomic taxonomic profiling with uncharacterized species using MetaPhlAn 4. Nat. Biotechnol. 41 , 1633–1644 (2023). https://doi.org/10.1038/s41587-023-01688-w Beghini, F. et al. Integrating taxonomic, functional, and strain-level profiling of diverse microbial communities with bioBakery 3. Elife 10 (2021). https://doi.org/10.7554/eLife.65088 Mallick, H. et al. Multivariable association discovery in population-scale meta-omics studies. PLoS Comput Biol 17 , e1009442 (2021). https://doi.org/10.1371/journal.pcbi.1009442 Miyamoto, J. et al. Ketone body receptor GPR43 regulates lipid metabolism under ketogenic conditions. Proc. Natl. Acad. Sci. U. S. A. 116 , 23813–23821 (2019). https://doi.org/10.1073/pnas.1912573116 Nishida, A., Miyamoto, J., Shimizu, H. & Kimura, I. Gut microbial short-chain fatty acids-mediated olfactory receptor 78 stimulation promotes anorexigenic gut hormone peptide YY secretion in mice. Biochem. Biophys. Res. Commun. 557 , 48–54 (2021). https://doi.org/10.1016/j.bbrc.2021.03.167 Methods Human faecal samples collection Study participants were recruited between 2017 and 2022 from Kyoto University (permit number: R2875-4), Keio University (permit number: 20210021), Kobe University (permit number: B210124), Kyoto Medical Center (permit number: 20–074), Tokyo University of Agriculture and Technology (permit number: 210704-2846) and Fukujuji Hospital (permit number: 21016). The volunteers were Japanese individuals aged 20–80 years. The exclusion criteria were as follows: Participants with a BMI below 18.5 or above 60 kg m − 2 ; those who regularly took medication with proton pump inhibitors; those with diabetes and hyperlipidemia; those who used antibiotics within 2 weeks; and those who consumed probiotic supplements, including milk, yogurt, and fermented food before sample collection. All the participants involved in this study provided written informed consent. Faecal samples were collected using a stool collection tube and stored at − 80°C until preparation and analysis. Faecal samples cultured condition Human and mouse faecal samples were cultured on MRS agar (Difco Laboratories Inc., Detroit, MI, USA) or MRS agar containing 15% fructose, galactose, glucose, lactose, maltose, and sucrose at 30°C for 48 h under anaerobic conditions. EPS product colonies were picked and underwent 16S ribosomal RNA (rRNA) gene amplification using the primers 27F (5′-AGAGTTTGATCCTGGCTCAG-3′) and 1492R (5′-GGTTACCTTGTTACGACTT-3′). The PCR products were purified using an UltraClean PCR Clean-Up Kit (MO BIO Laboratories, San Diego, CA, USA), and directly sequenced using a Big Dye Terminator Cycle Sequencing Kit ver. 3.1 (Applied Biosystems, Foster City, CA, USA) and an ABI 3730xl DNA analyzer system (Applied Biosystems). The isolated strains shared more than 98% similarity in their 16S rRNA gene sequences. Bacterial culture The cultivation of S. salivarius in MRS medium containing 15% sucrose, 15% glucose, 15% fructose, and 7.5% glucose + 7.5% fructose was monitored for 24 h. The dominant gut bacteria were selected using a human gut microbial gene catalog 25 obtained from the Japan Collection of Microorganisms (JCM). Bacteria were recovered according to the manufacturer’s instructions as previously described 18 . Intestinal bacteria were collected in nutrient broth (Difco Laboratories Inc.) containing 10% glycerol and stored at − 80°C. Characterisation of S. salivarius-produced EPS S. salivarius was cultured on MRS agar alone at 37°C or MRS agar containing 15% sucrose at 30°C for 48 h under anaerobic conditions and imaged using scanning electron microscopy (SEM; JSM-7500F; HUSRI, Aichi, Japan). SsEPS were collected from the agar plate and purified using ethanol precipitation, as previously described 18 or dialysis membranes with a molecular cutoff of 3,500 Da (Snake Skin dialysis tubing, Thermo Fisher Scientific, Waltham, MA, USA). The precipitated SsEPS was dried over calcium chloride for 24–48 h. To determine its monosaccharide composition, SsEPS was extracted as described previously 18 , with certain modifications. Briefly, SsEPS was hydrolysed by addition of trifluoroacetic acid (0.5 M) and incubated at 120°C for 0.5–2 h. After incubation, the supernatant was filtered through a 0.45 µm filter. The monosaccharide composition was analysed by ligand exchange chromatography using an 8.0 × 300 mm SUGAR SC1011 column (Shodex, Tokyo, Japan). Detection was performed using a RID-20A (Shimadzu, Kyoto, Japan), with D-glucose and D-fructose (Nacalai Tesque, Kyoto, Japan) as standards. The average molecular weight of SsEPS was determined by size exclusion chromatography using an 8.0 × 300 mm OHpak SB-800 HQ series column (Shodex). Standards for purchased pullulans (Shodex) and dextrans (Sigma-Aldrich, St. Louis, MO, USA) with average molecular weights of 1,600,000–5,900 and 1,500,000–2,800,000 Da, respectively, were established using calibration curves. Structure of S. salivarius-produced EPS The structure of the SsEPS was confirmed using 1 H and 13 C NMR spectroscopy. SsEPS was dissolved in 750 µL of D 2 O containing 0.1% 3-(trimethylsilyl) propionic-2,2,3,3- d 4 acid sodium salt (TMSP). After allowing the solution to stand for 12 h, the 1 H NMR spectrum was recorded using a JEOL ECA-500 spectrometer with a frequency of 500 MHz at 25°C. Chemical shifts are reported in δ (ppm) relative to TMSP as the chemical shift internal standard. 13 C NMR spectra were recorded on a JEOL ECA-500 spectrometer with a frequency of 125 MHz at 25°C and are reported relative to TMSP signal as the chemical shift internal standard. The infrared (IR) spectra were recorded using a JASCO FT/IR-4100 spectrometer. S. salivarius -produced levan: IR (neat cm − 1 ): 3415 (OH); 1 H NMR (500 MHz, D 2 O): δ 4.20 (d, J = 8.0 Hz, 1H), 4.14–4.08 (m, 1H), 3.98–3.87 (m, 2H), 3.78 (d, J = 12.0 Hz, 1H), 3.69 (d, J = 12.0 Hz, 1H), 3.59–3.55 (m, 1H); 13 C{ 1 H} NMR (125 MHz, D 2 O): δ 107.1, 83.2, 79.2, 78.1, 66.2, 62.8. S. salivarius -produced glucan: IR (neat cm − 1 ): 3375 (OH); 1 H NMR (500 MHz, D 2 O): δ 4.99 (d, J = 2.9 Hz, 1H), 4.04–3.92 (m, 2H), 3.80–3.70 (m, 2H), 3.59 (dd, J = 9.7, 2.9 Hz, 1H); 13 C{ 1 H} NMR (125 MHz, D 2 O): δ 100.5, 76.2, 74.3, 73.0, 72.4, 68.4. RNA isolation and quantitative reverse transcriptase (qRT)-PCR S. salivarius was cultured in MRS medium containing 15% sucrose or 15% glucose at 30°C for 10 h under anaerobic conditions. Total RNA was extracted using the NucleoSpin RNA kit (Takara Bio, Shiga, Japan) and reverse-transcribed into cDNA using Moloney murine leukemia virus reverse transcriptase (Thermo Fisher Scientific). SYBR Premix Ex Taq II (Takara Bio) and StepOnePlus real-time PCR system (Applied Biosystems) were used for qRT-PCR analysis, as previously described 18 . SsEPS-synthesised enzyme primer sequences are listed in Extended Data Table 1. RNA-sequencing data analysis Sequencing libraries were constructed using the NEBNext rRNA Depletion Kit (Bacteria) (New England Biolabs, Inc., MA, USA) and the TruSeq Stranded mRNA Library Prep Kit (Illumina, CA, USA) according to the manufacturer's protocols. The sequencing libraries were sequenced on an Illumina HiSeq 2500 platform with 100 bp paired-end reads. On average, 1.2 million read pairs per sample were sequenced across eight samples (4 glucose samples and 4 sucrose samples). RNA-Seq data were analysed using the CLC Genomics Workbench (Qiagen Bioinformatics, Venlo, Netherlands) to identify differentially expressed genes. To obtain clean reads, low-quality reads were removed by trimming, whereas high-quality reads were aligned to the S. salivarius NCTC 7366 genome retrieved from the NCBI database. The parameters were set as follows: minimum length fraction = 0.8 and minimum similarity fraction = 0.8. Expression values were established as transcripts per million reads (TPM). The KEGG Pathway enrichment analysis was performed from the GhostKOALA result of expressed genes. The enriched pathway for the experiment was identified from the Welch's t-test result with false discovery rate correction (q < 0.01) using the R software environment. A gene set enrichment analysis was performed using the Kyoto Encyclopedia of Genes and Genomes database (KEGG) ( http://www.genome.jp/kegg/ ). Shotgun metagenomic sequencing data analysis DNA was quantitated using Qubit fluorometric quantitation (Thermo Fisher Scientific) and qualified by DNA size profiling on a fragment analyzer (Agilent, Santa Clara, CA, USA). High molecular weight DNA (> 10 kbp; 3 µg) was used to build the library. DNA shearing into fragments of approximately 150 bp was performed using an ultrasonicator (Covaris, Woburn, MA, USA), and the DNA fragment library was constructed using the Ion Plus Fragment Library and Ion Xpress Barcode Adapters kits (Thermo Fisher). Purified and amplified DNA fragment libraries were sequenced using DNBSEQ-G400 (MGI Tech) with a minimum of 20 million high-quality reads of 150 bp (on average) generated per library. The paired-end sequences were merged by BBmaps (v38.84-0) 34 . They underwent preprocessing by Kneaddata (v0.12.0) to remove the host genome based on the human (hg37 dec_v0.1) and mouse (C57BL_6NJ) genome databases. The Whole genome sequence based axonomy profile was generated by MetaPhlAn (v4.0.4) 35 . Microbial gene families and metabolic pathways were assessed using HUMAnN3 (v3.8) 36 based on the UniRef90 EC filtered database (uniref90_201901). MaAsLin2 was used to identify significant pathway from HUMAnN3 outputs 37 . All computational scripts are available on GitHub [ https://github.com/petadimensionlab/EPS ]. SCFAs measurement SCFA levels in human faeces, murine faeces, and murine plasma were measured following a previously described modified protocol 38 . Ether layers containing SCFAs were collected and pooled for gas chromatography-mass spectrometry (GC-MS) using a GCMS-QP2010 Ultra GC mass spectrometer (Shimadzu). The SCFA concentration was evaluated over a specified concentration range. EPS measurement. The faecal contents (300 mg) were immediately mixed with five volumes of sterile distilled water containing 2% 5-sulfosalicylic acid and vortexed. The mixture was then centrifuged, and the supernatant containing the EPS was collected. Two volumes of hexane were added to the supernatant, which was then vortexed for 5 min. After centrifugation of the samples at 10,000 × g for 15 min, the water layers containing EPS were collected and subjected to HPLC analysis using an RID-20A (Shimadzu) and an 8.0 × 300 mm OHpak SB-800 HQ series column (Shodex). Animal Study C57BL/6J, Gpr41Gpr43 double-deficient, and ICR mice were housed under a 12-h light-dark cycle and fed normal chow (CE-2; CLEA, Tokyo, Japan). GF-ICR mice were housed in vinyl isolators under a 12-h light–dark cycle and fed normal chow (CL-2, 50kGy irradiated; CLEA). Gpr41Gpr43 double-deficient mice were generated as described previously 12 . All experimental procedures involving mice were performed according to the protocols approved by the Committee on the Ethics of Animal Experiments of the Kyoto University Animal Experimentation Committee (Lif-K21020) and Tokyo University of Agriculture and Technology (permit number: R05-47 and R05-48). Four-week-old C57BL/6J and Gpr41Gpr43 double-deficient mice were fed a modified D12492 diet (60% kcal fat; Research Diets, New Brunswick, NJ, USA) for 12 weeks in high fat diet (HFD) studies. The composition of the modified diet is shown in Extended Data Table 2. After fasting 24 h, 7-week-old C57BL/6J, Gpr41Gpr43 double-deficient, conventional ICR, and GF-ICR healthy male mice were fed 0.2 g AIN-93G, containing 50% cellulose or 50% SsEPS. After 1 h, glucose (2 g/kg body weight) was intraperitoneally administered to each mouse. Blood glucose levels in the tail vein were measured using a OneTouch UltraVue glucometer (LifeScan, Milpitas, CA, USA) and an LFS Quick Sensor (LifeScan) before and at 15, 30, 60, 90, and 120 min after injection. Plasma samples were collected from the inferior vena cava at 15 min after glucose administration for insulin and GLP-1 measurement 18 , 39 . For the gnotobiotic experiments, 5-week-old GF-ICR mice were fed an AIN-93G diet (50kGy irradiated; Research Diets) for 4 weeks. After 2 weeks, each bacterial strain (1 × 10 8 CFU/mouse) was administered via oral gavage three times per week. Sterilised water containing 20% sucrose with or without 0.5% acarbose as an α-glucosidase inhibitor (Tokyo Chemical Industries, Japan), glucose, and fructose were administered for 2 weeks (fig. S7A and S7G). For long-term treatment, 7-week-old GF-ICR mice were fed an AIN-93G diet, D12492 diet (Research Diets), or modified D12492 diet (50kGy irradiated) for 9 weeks. Each bacterial strain (1 × 10 8 CFU/mouse) was administered via oral gavage three times a week at 7 and 11 weeks old. The composition of the modified D12492 diet is shown in Extended Data Table 3. Faecal transplantation in animal experiment The faecal samples from two women, Ss (+) (aged 43 with a BMI of 30.0 kg m − 2 ) and Ss (-) (aged 45 with a BMI of 40.5 kg m − 2 ) were suspended in equal volumes of nutrient broth (Difco Laboratories Inc.) containing 10% glycerol and stored at − 80℃ until use. The thawed frozen samples were cultured anaerobically at 37℃ for 24 hours in GAM medium (Nissui, Tokyo, Japan), filtered through a membrane paper, and orally inoculated into germ-free mice (approximately 250 µl per mouse). Faecal culture solutions were administered once weekly until 16 weeks of age. Biochemical analyses Blood glucose levels were measured using a OneTouch UltraVue glucometer (LifeScan) and an LFS Quick Sensor (LifeScan). The levels of plasma non-esterified fatty acids (LabAssayTM NEFA; Wako Pure Chemical Co. Ltd., Osaka, Japan), triglycerides (LabAssayTM Triglyceride; Wako Pure Chemical Co. Ltd.), total cholesterol (LabAssayTM Cholesterol; Wako Pure Chemical Co. Ltd.), insulin (Mouse Insulin enzyme-linked immunosorbent assay [ELISA]; Shibayagi, Gunma, Japan), and active glucagon like peptide-1 (GLP-1) (GLP-1 [Active] ELISA; Merck Millipore, Billerica, MA, USA) were measured according to the manufacturer’s instructions. To prevent degradation of active GLP-1, plasma samples were treated with a dipeptidyl peptidase IV inhibitor (Merck Millipore). DNA extraction and gut microbial composition DNA was extracted from faecal samples using the FastDNA SPIN kit for feces (MP Biomedicals, Irvine, CA, USA) as described previously 18 . Partial 16S rRNA gene sequences were amplified by targeting the hypervariable regions v4 using the primers 515F; 5′-TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGGTGYCAGCMGCCGCGGTAA-3′ and 806R; 5′-GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGGGACTACHVGGGTWTCTAAT-3′. Amplicons generated from each sample were purified using AMPure XP Beads (Beckman Coulter, Brea, CA, USA), and appended with Nextera XT index kit (Illumina, San Diego, CA, USA). Amplicons were sequenced using a MiSeq sequencer (Illumina) and MiSeq Reagent kit (version 3.0; 600 cycles). The 16S rRNA sequence data were then processed using the quantitative insights into the microbial ecology 2 (QIIME 2) pipeline, and analysed using the MiSeq Reporter software with the SILVA database (Illumina). Diversity was analysed using QIIME script core_diversity_analyses.py. Permutational multivariate analysis of variance (QIIME script compare_categories.py) was used to assess the statistical significance of sample groupings. For quantitative PCR, SYBR Premix Ex Taq II (Takara Bio) and StepOnePlus real-time PCR system (Applied Biosystems) were used. The bacterial primer sequences are listed in Extended Data Tables 4 and 5. Statistical analysis The mean ± standard error of the mean is presented for all values. We assessed the normality of the data using the Shapiro–Wilk test (normal distribution was defined at p ≥ 0.05). To determine the statistical significance between two groups with normal distribution, we used Student's t-test. For groups with non-normal distribution, the Mann–Whitney U test was used for comparison. One-way analysis of variance (ANOVA) was used to compare data from multiple groups (three or more). For normally distributed sample sets, Dunnett’s post-hoc test was used, whereas the Kruskal–Wallis test paired with Dunn’s post-hoc test was used for non-normally distributed sample sets. Statistical significance was set at p < 0.05. Additionally, The Benjamini–Hochberg procedure was used to estimate the false discovery rates (Q-values) of the 16S rRNA gene sequencing data. This study analysed the correlations between microbiota and gut environmental factors. To calculate correlations, we used Spearman's rank correlation coefficients for bacterial genus abundance, including Muribaculum , Paramuribaculum , Duncaniella , Bacteroides , Akkermansia , Faecalitalea , Desulfovibrio , Streptococcus , Blautia , and Ruminococcus and faecal SCFAs, such as acetate, propionate, and n-butyrate. We selected only correlations with an absolute value above 0.6 and a Q-value below 0.05. Outliers were evaluated using the Smirnov–Grubbs test. Additional Declarations Yes there is potential Competing Interest. H.S, K.H, and D.S. are employees of Noster Inc. Otherwise the authors have no competing interests. Supplementary Files ExtendedDataFiguresandTables.pdf GraphicalAbstract.jpg Cite Share Download PDF Status: Published Journal Publication published 29 Jan, 2025 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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University","correspondingAuthor":false,"prefix":"","firstName":"Akari","middleName":"","lastName":"Matsuki","suffix":""},{"id":272031062,"identity":"d0dcc7a8-534b-4fdd-adb2-567064e9dd1c","order_by":20,"name":"Ryo Akashi","email":"","orcid":"https://orcid.org/0009-0001-7366-9376","institution":"Hokkaido University","correspondingAuthor":false,"prefix":"","firstName":"Ryo","middleName":"","lastName":"Akashi","suffix":""},{"id":272031063,"identity":"c07336de-0d29-4360-be38-e3146c2e6dee","order_by":21,"name":"Seiichi Kitahama","email":"","orcid":"","institution":"Chibune General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Seiichi","middleName":"","lastName":"Kitahama","suffix":""},{"id":272031064,"identity":"c4285eb4-6933-4691-bf37-d5c1675c65f5","order_by":22,"name":"Masako Ueyama","email":"","orcid":"","institution":"Fukujuji Hospital","correspondingAuthor":false,"prefix":"","firstName":"Masako","middleName":"","lastName":"Ueyama","suffix":""},{"id":272031065,"identity":"8e3706ed-a313-434d-936a-18d1ef996641","order_by":23,"name":"Takumi Murakami","email":"","orcid":"","institution":"National Institute of Genetics","correspondingAuthor":false,"prefix":"","firstName":"Takumi","middleName":"","lastName":"Murakami","suffix":""},{"id":272031066,"identity":"e6ea2351-9693-4905-97bd-937fb08de049","order_by":24,"name":"Shinsuke Inuki","email":"","orcid":"","institution":"Kyoto University","correspondingAuthor":false,"prefix":"","firstName":"Shinsuke","middleName":"","lastName":"Inuki","suffix":""},{"id":272031067,"identity":"b16d7b21-ec5e-4798-9319-ad007a121079","order_by":25,"name":"Junichiro Irie","email":"","orcid":"https://orcid.org/0000-0003-2662-4121","institution":"Keio University","correspondingAuthor":false,"prefix":"","firstName":"Junichiro","middleName":"","lastName":"Irie","suffix":""},{"id":272031068,"identity":"83878124-5436-428e-98e8-5a703461abd7","order_by":26,"name":"Noriko Satoh-Asahara","email":"","orcid":"","institution":"National Hospital Organization Kyoto Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Noriko","middleName":"","lastName":"Satoh-Asahara","suffix":""},{"id":272031069,"identity":"b787e9de-414b-4b59-aac9-10f5b3c8e5f0","order_by":27,"name":"Hirokazu Toju","email":"","orcid":"https://orcid.org/0000-0002-3362-3285","institution":"Kyoto University","correspondingAuthor":false,"prefix":"","firstName":"Hirokazu","middleName":"","lastName":"Toju","suffix":""},{"id":272031070,"identity":"f3fde8c6-bdbb-4013-ad1a-7431e844534f","order_by":28,"name":"Hiroshi Mori","email":"","orcid":"https://orcid.org/0000-0003-0806-7704","institution":"National Institute of Genetics","correspondingAuthor":false,"prefix":"","firstName":"Hiroshi","middleName":"","lastName":"Mori","suffix":""},{"id":272031071,"identity":"a15278d4-3ace-4437-b067-7426fe3181ea","order_by":29,"name":"Shinji Nakaoka","email":"","orcid":"","institution":"Hokkaido University","correspondingAuthor":false,"prefix":"","firstName":"Shinji","middleName":"","lastName":"Nakaoka","suffix":""},{"id":272031072,"identity":"e6c93dd1-9773-49a9-8611-29869d6e8428","order_by":30,"name":"Tomoya Yamashita","email":"","orcid":"https://orcid.org/0000-0003-0267-3842","institution":"Kobe University Graduate School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Tomoya","middleName":"","lastName":"Yamashita","suffix":""},{"id":272031073,"identity":"43a6ba52-e7e5-44d4-866c-a2cc1008fe70","order_by":31,"name":"Atsushi Toyoda","email":"","orcid":"https://orcid.org/0000-0002-0728-7548","institution":"National Institute of Genetics","correspondingAuthor":false,"prefix":"","firstName":"Atsushi","middleName":"","lastName":"Toyoda","suffix":""},{"id":272031074,"identity":"926932dc-ce59-4860-ba91-653977ba418e","order_by":32,"name":"Kenji Yamamoto","email":"","orcid":"","institution":"Wakayama University","correspondingAuthor":false,"prefix":"","firstName":"Kenji","middleName":"","lastName":"Yamamoto","suffix":""},{"id":272031075,"identity":"ee6cb898-adb2-4227-94df-0d2ae7e76f66","order_by":33,"name":"Hiroaki Ohno","email":"","orcid":"https://orcid.org/0000-0002-3246-4809","institution":"Kyoto University","correspondingAuthor":false,"prefix":"","firstName":"Hiroaki","middleName":"","lastName":"Ohno","suffix":""},{"id":272031076,"identity":"d090467b-a5e5-459f-8798-9a902dc535b2","order_by":34,"name":"Takane Katayama","email":"","orcid":"","institution":"Kyoto University","correspondingAuthor":false,"prefix":"","firstName":"Takane","middleName":"","lastName":"Katayama","suffix":""},{"id":272031077,"identity":"fd77016b-8862-4f2b-96f7-afef20698ba8","order_by":35,"name":"Hiroshi Itoh","email":"","orcid":"https://orcid.org/0000-0003-2514-4919","institution":"Keio University","correspondingAuthor":false,"prefix":"","firstName":"Hiroshi","middleName":"","lastName":"Itoh","suffix":""}],"badges":[],"createdAt":"2024-01-23 04:56:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3889905/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3889905/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41467-025-56470-0","type":"published","date":"2025-01-29T05:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":51213932,"identity":"97709b15-bf3e-450d-b6e8-37574d389d0e","added_by":"auto","created_at":"2024-02-16 06:32:21","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":3901075,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIsolation and characterisation of EPS-producing human commensal bacteria \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eS. salivarius\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e. \u003c/strong\u003e(a)\u003cstrong\u003e \u003c/strong\u003eEPS high-producing bacteria using bacterial ropy colonies as an indicator in human and mouse faeces cultured in MRS medium containing 15% fructose, galactose, glucose, lactose, maltose, and sucrose. Red arrowheads indicate EPS production. (b) Types of EPS-producing bacteria isolated from 47 human faeces. (c) Correlation between EPS high-producing bacterial occupancy in human faeces and donor body mass index (BMI). (d) Structural characterisation was performed using proton nuclear magnetic resonance (\u003csup\u003e1\u003c/sup\u003eH NMR) spectroscopy. (e) Growth curves of EPS biosynthesis and optical density at 600 nm (OD\u003csub\u003e600\u003c/sub\u003e) (n = 3 per group). (f, g) The KEGG pathway enrichment analysis on EPS synthesis pathway and expression of putative levansucrase and glucosyltransferase mRNAs in MRS medium containing sucrose or glucose during bacterial culture for 10 h were measured by RNA-seq (n = 4 per group). (h) Spearman’s rank correlation between faecal levels of total short-chain fatty acids (SCFAs) such as acetate, propionate, and butyrate, exopolysaccharides (EPS) and donor body mass index (BMI) in human faeces (n = 180). (i) Polysaccharide synthesis, polysaccharide decomposition, glycolytic pathway and SCFAs synthesis were compared between lean and donors with obesity in shotgun metagenomic sequencing analysis (n = 26 per group). ***\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001, **\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01, *\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05 (Mann–Whitney U test). Results are presented as the mean ± standard error of the mean (SE).\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3889905/v1/30fac9dd89d9388838676ff0.jpg"},{"id":51213931,"identity":"39b02288-c60e-421c-9f73-ae4958ce4dd5","added_by":"auto","created_at":"2024-02-16 06:32:18","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":2871423,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMetabolic improvement effect of SsEPS intake in high-fat diet (HFD)-induced obesity. \u003c/strong\u003e(a) Bacterial SCFA levels in the culture supernatants of each gut bacterium (n = 6 per group). **\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01 compared with control (Mann–Whitney U test). (b–e) C57BL/6J and \u003cem\u003eGpr41Gpr43\u003c/em\u003e double-deficient mice were fed an HFD supplemented with 10% cellulose or SsEPS for 12 weeks. (b) Faecal (left) and plasma (right) SCFA levels were measured using GC-MS (n = 9–10 per group). (c) Changes in body and tissue weight (n = 9–10 per group). Epi, epididymal; peri, perirenal; sub, subcutaneous; WAT, white adipose tissue. (d, e) Blood glucose, plasma non-esterified fatty acid (NEFAs), and plasma GLP-1 levels were measured at the end of the experimental period (n = 9–10 per group). NS, not significant. (f, g) Following 24 h of fasting, the mice were fed 0.2 g AIN-93G, containing 50% cellulose or 50% SsEPS, and an intraperitoneal glucose tolerance test was performed 1 h after feeding. Wild-type (n = 10 per group), \u003cem\u003eGpr41Gpr43\u003c/em\u003e double-deficient (n = 7–8 per group), ICR (n = 8–9 per group), and GF-ICR (n = 8 per group) mice were used. **\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01, *\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05 (Mann–Whitney U test). Plasma insulin levels were measured 15 min after intraperitoneal glucose administration. Wild-type (n = 8–9 per group), \u003cem\u003eGpr41Gpr43\u003c/em\u003e double-deficient (n = 7–8 per group), ICR (n = 8 per group), and GF-ICR (n = 8 per group) mice were used. **\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01 (Dunn’s post-hoc test). NS, not significant. Results are presented as means ± standard error of the mean (SE).\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3889905/v1/758ae7a796106d7e0d67a48e.jpg"},{"id":51214191,"identity":"5ed0b5c5-200c-4327-bdcc-f6020594e873","added_by":"auto","created_at":"2024-02-16 06:40:22","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":3476752,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIdentification of gut bacterial SCFAs production pathway by SsEPS intake. \u003c/strong\u003e(a–c) Gut microbial composition was evaluated to determine the principal coordinate analysis and relative abundance at the phylum level (a), heatmap of the bacterial domain at the family level (b), and genus level (c) (n = 10 per group). **\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01, *\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05 (Mann–Whitney U test). (d) Spearman’s rank correlation between the levels of the main contributing bacterial genera and faecal short-chain fatty acids (SCFAs) in high-fat diet (HFD)-fed mice supplemented with cellulose versus HFD-fed mice supplemented with SsEPS. (e) SsEPS-utilizing \u003cem\u003eBacteroides\u003c/em\u003e and \u003cem\u003eBacteroidales\u003c/em\u003e S24-7 group species were detected by qPCR (n = 10 per group). **\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01 (Mann–Whitney U test). (f) EPS degradation, SCFAs synthesis, and glycolysis pathways were compared between cellulose- and SsEPS-fed mice in shotgun metagenomic sequencing analysis (n = 5 per group). Results are presented as means ± standard error of the mean (SE).\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3889905/v1/f8efff23015033bed0fe5a66.jpg"},{"id":51213934,"identity":"b0318d61-90ad-415d-bd2b-51d8b74160e4","added_by":"auto","created_at":"2024-02-16 06:32:22","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":2377831,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eImprovement of sucrose-induced metabolic function by \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eS. salivarius\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e. \u003c/strong\u003e(a, b) Germ-free (GF) and colonised mice (Ss, \u003cem\u003eS. salivarius\u003c/em\u003e; Bo+Bt, \u003cem\u003eB. ovatus \u003c/em\u003eand \u003cem\u003eB. thetaiotaomicron\u003c/em\u003e; and Ss+Bo+Bt, \u003cem\u003eS. salivarius\u003c/em\u003e, \u003cem\u003eB. ovatus\u003c/em\u003e, and \u003cem\u003eB. thetaiotaomicron\u003c/em\u003e) were generated and drank sterilised water containing 20% sucrose, after which faecal EPS (a) and SCFAs (b) were measured by HPLC and GC/MS (n = 9–10 per group). (c) After colonisation, an intraperitoneal glucose tolerance test was performed (n = 7–10 per group). **\u003cem\u003eP\u003c/em\u003e\u0026lt; 0.01, compared with GF mice (Dunn’s post-hoc test). (d) Plasma insulin (left) and GLP-1 (right) levels were measured 15 min after intraperitoneal glucose administration (n = 7–10 per group). **\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01, *\u003cem\u003eP\u003c/em\u003e\u0026lt; 0.05 (Dunn’s post-hoc test). (e–g) After colonisation, the mice were given water containing 20% sucrose for 8 weeks. (e) Experimental scheme for the gnotobiotic analysis and changes in body and tissue weights. **\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01, *\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, compared with GF mice (Dunn’s post-hoc test). Blood glucose (f) and plasma GLP-1 (g) levels were measured at the end of the experimental period (n = 7–10 per group). **\u003cem\u003eP\u003c/em\u003e\u0026lt; 0.01, *\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05 (Dunn’s post-hoc test). (h–j) \u003cem\u003eS. salivarius\u003c/em\u003e-dominant [Ss (+)] or -nondominant human gut microbiota [Ss (-)] mice were generated from human donors to GF mice and fed a HFD supplemented with sugars (sucrose, glucose, or fructose). (h) Experimental scheme for faecal microbiota transplantation experiment and changes in body and tissue weight. (i, j) Blood glucose (i) and plasma GLP-1 (j) levels were measured at the end of the experimental period (n = 5–7 per group). **\u003cem\u003eP\u003c/em\u003e\u0026lt; 0.01, *\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, compared with Ss (-) mice (Mann–Whitney U test, per group). Results are presented as means ± standard error of the mean (SE).\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3889905/v1/703f82e79f3f498ae0c93bab.jpg"},{"id":75076963,"identity":"75aa71a4-579f-424c-8891-cd86791cbd25","added_by":"auto","created_at":"2025-01-30 08:07:33","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":13929182,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3889905/v1/de2009be-39e1-464f-93dd-fb857c58f9ac.pdf"},{"id":51213933,"identity":"6de1c9d6-51d6-4f8b-859e-e14c70643117","added_by":"auto","created_at":"2024-02-16 06:32:21","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1677437,"visible":true,"origin":"","legend":"","description":"","filename":"ExtendedDataFiguresandTables.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3889905/v1/2d7994918c6408f4fec28d62.pdf"},{"id":51213937,"identity":"197314f6-7454-408a-9937-8af42e3b9387","added_by":"auto","created_at":"2024-02-16 06:32:22","extension":"jpg","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":1398166,"visible":true,"origin":"","legend":"","description":"","filename":"GraphicalAbstract.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3889905/v1/5d088360d8249cc635a28289.jpg"}],"financialInterests":"\u003cb\u003eYes\u003c/b\u003e there is potential Competing Interest.\nH.S, K.H, and D.S. are employees of Noster Inc. Otherwise the authors have no competing interests.","formattedTitle":"Sucrose-preferring gut microbes prevent host obesity by producing exopolysaccharides","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAlthough diet is the most important factor for daily nutrient acquisition, dysregulation of energy homeostasis due to excessive dietary intake, particularly high fat and sugar intake, leads to obesity\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Sucrose (table sugar), glucose (dextrose), and fructose (fruit sugar) are simple saccharides. Of the sugars consumed daily\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e, sucrose and glucose are the most common. As sucrose intake increases in Western countries, sucrose-rich diets may be associated with rising health problems, such as obesity and diabetes.\u003c/p\u003e \u003cp\u003eAlthough bacteria also utilize these sugars as an energy source, their metabolic pathway differs from that of humans\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. After glycolysis, anaerobic bacteria convert pyruvate to lactate and other organic acids such as short-chain fatty acids (SCFAs; acetate, propionate, and butyrate). Gut microbes produce these end products through sugar metabolism in environments where oxygen is limited\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. They produce SCFAs from fermentable fibres, which are indigestible polysaccharides that are not absorbed by the small intestine because host enzymes cannot digest them\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. The SCFAs act as energy sources for the host and as signalling factors via host G protein-coupled receptors GPR41 and GPR43, improving the host homeostasis by acting on the endocrine systems\u003csup\u003e\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. GPR41 influences host metabolic functions, enhances sympathetic activity, and promotes gut hormone secretion\u003csup\u003e\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e, while GPR43 suppresses fat accumulation and promotes gut hormone secretion\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eSugars are anabolized into polysaccharides during glycometabolism. Storage polysaccharides such as glycogen and starch are carbohydrates used to store and provide energy. In animals, glycogen is primarily stored in the liver and muscles\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e, resulting in sudden increases in energy requirements. Additionally, starch, found in grains, potatoes, and legumes, is the main form of sugar stored in plants\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. They serve as energy sources and are broken down into glucose during digestion. Bacteria also produce different types of storage polysaccharides, such as levans and dextrans\u003csup\u003e\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e, depending on the type of bacteria and environmental conditions. We have recently reported that prebiotics associated with the exopolysaccharide (EPS) produced by \u003cem\u003eLeuconostoc mesenteroides\u003c/em\u003e provide substantial metabolic benefits to the host\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. This polysaccharide is indigestible because its glycosidic linkages cannot be cleaved by host amylase. Furthermore, fermented foods, such as pickles, kimchi, and sauerkraut, are produced by the fermentative action of \u003cem\u003eL. mesenteroides\u003c/em\u003e, lactic acid bacteria\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThese findings suggest that some gut microbes may produce indigestible polysaccharides from sugars and contribute to host metabolic benefits. Therefore, in this study, we sought high-EPS-producing gut microbes in humans and investigated the relationship between host sugar intake and the prebiotic effects of gut microbe-produced EPS, as well as the molecular mechanism underlying the effect of microbial metabolites on host health.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eIsolation of EPS-producing human commensal bacteria\u003c/strong\u003e \u003cstrong\u003eS. salivarius\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe first screened EPS-producing bacteria using bacterial ropy colonies as an indicator\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e in human faeces (472 donors) (Extended Data Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). These samples were cultured on de Man, Rogosa, and Sharpe (MRS) agar with different sugar sources (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ea). Bacterial ropy colonies (47 donors) were then observed in the culture of human faeces with sucrose alone, excluding other sugar sources. However, such colonies were absent in the culture of mouse faeces with sucrose (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ea). The bacterial colonies were identified as \u003cem\u003eWeissella cibaria\u003c/em\u003e (19 donors), \u003cem\u003eL. mesenteroides\u003c/em\u003e (14 donors), \u003cem\u003eStreptococcus salivarius\u003c/em\u003e (six donors), \u003cem\u003eWeissella confuse\u003c/em\u003e (five donors), and \u003cem\u003eLeuconostoc lactis\u003c/em\u003e (three donors) (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eb). Among them, only \u003cem\u003eS. salivarius\u003c/em\u003e is a human commensal bacterium, while the others are lactic acid bacteria commonly found in fermented foods\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. Furthermore, we investigated the relationship between the presence of bacteria in human faeces and the body mass index (BMI) of donors (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ec). Remarkably, only \u003cem\u003eS. salivarius\u003c/em\u003e was sufficiently detected in all donors, and its occupancy showed an inverse correlation with obesity (BMI\u0026thinsp;\u0026ge;\u0026thinsp;30). Therefore, we focused on \u003cem\u003eS. salivarius\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003eThe isolated \u003cem\u003eS. salivarius\u003c/em\u003e (a gram-positive, spherical, facultative anaerobe) produced EPS on MRS agar with sucrose (Extended Data Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ea). \u003cem\u003eS. salivarius\u003c/em\u003e-produced EPS (SsEPS) was purified by ethanol precipitation/dialysis and analysed using \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003eH NMR spectroscopy. The purified SsEPS consisted of levan (fructan, with linear structures of fructose linked by \u0026beta;-2,6-glycosidic bonds) and dextran (\u0026alpha;-glucan, with main-chain glucose monomers linked by \u0026alpha;-1,6-glycosidic bonds and branched by \u0026alpha;-1,3-glycosidic side chains) (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ed and Extended Data Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eb\u0026ndash;i). In MRS broth containing 15% sucrose, \u003cem\u003eS. salivarius\u003c/em\u003e produced large amounts of EPS (13 mg/mL). However, when the MRS medium contained 15% glucose, 15% fructose, or 7.5% glucose\u0026thinsp;+\u0026thinsp;7.5% fructose, EPS production failed despite bacterial proliferation (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ee). Upon RNA sequencing, KEGG orthology (KO) analysis showed that the EPS synthesis pathway was enriched in sucrose-supplemented \u003cem\u003eS. salivarius\u003c/em\u003e culture (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ef and Extended Data Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ea). Furthermore, 14 putative glycosyltransferase-encoding genes were extracted by comparing their mRNA expression between sucrose- and glucose-supplemented cultures (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eg). The mRNA expression of the five putative glycosyltransferase genes significantly increased along with the SsEPS yield in the medium containing 15% sucrose, but not in the medium containing glucose (Extended Data Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eb). Additionally, levansucrase and glycosyltransferase, RS02300 and RS07295, were highly expressed after sucrose supplementation. Therefore, SsEPS may be synthesized by the putative levansucrase and glycosyltransferase, RS02300 and RS07295, respectively. Thus, the human commensal bacterium \u003cem\u003eS. salivarius\u003c/em\u003e produces large amounts of EPS in the form of levans and dextrans.\u003c/p\u003e\n\u003cp\u003eWe investigated the gut microbial composition between lean and donors with obesity (Extended Data Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003ea). Besides the occupancy of \u003cem\u003eS. salivarius\u003c/em\u003e, the levels of SCFAs and EPS in the faeces of lean donors were significantly higher than those in donors with obesity (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eh). The shotgun metagenomic sequencing data showed that obesity was associated with the carbohydrate metabolic pathway. Correlation analysis revealed a strong correlation between EPS hydrolase, glycolysis, and SCFA production (Extended Data Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eb). Moreover, glycolytic pathway analysis showed that obesity attenuated EPS and glycolysis pathways (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ei). Therefore, human obesity is associated with a decrease in \u003cem\u003eS. salivarius\u003c/em\u003e and attenuation of EPS and SCFAs synthesis cascades.\u003c/p\u003e\n\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n\u003ch2\u003eImprovement of host metabolic functions by SsEPS\u003c/h2\u003e\n\u003cp\u003eSubsequently, we investigated the bacteria associated with SCFA production from SsEPS using in vitro gut microbe monoculture screening\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. Among the 47 gut microbial strains tested, \u003cem\u003eBacteroides\u003c/em\u003e species, \u003cem\u003eB. ovatus\u003c/em\u003e and \u003cem\u003eB. thetaiotaomicron\u003c/em\u003e, and \u003cem\u003eBacteroidales\u003c/em\u003e S24-7 group members, \u003cem\u003eMuribaculum intestinale\u003c/em\u003e, \u003cem\u003eParamuribaculum intestinale\u003c/em\u003e, and \u003cem\u003eDuncaniella muris\u003c/em\u003e, efficiently produced SCFAs after 0.3% SsEPS addition. In contrast, other gut microbes did not produce SCFAs (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ea). To determine whether SsEPS is an indigestible polysaccharide, we examined intestinal SCFA levels after SsEPS intake. The levels of faecal and plasma SCFAs (acetate, propionate, and butyrate) were significantly higher in mice fed a high-fat diet (HFD) supplemented with SsEPS than in those fed an HFD supplemented with cellulose (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eb). Thus, in the host intestine, consumption of SsEPS promotes the production of SCFAs by gut microbes.\u003c/p\u003e\n\u003cp\u003eWe investigated the SsEPS effects on host energy homeostasis in HFD-induced obese mice. Four-week-old mice were fed an HFD supplemented with either SsEPS or cellulose as non-fermented fibre for 12 weeks. The body weight of the mice fed with SsEPS was markedly lower than that of control mice fed with cellulose during growth (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ec). Furthermore, the fat mass of the white adipose tissue (WAT) of SsEPS-fed mice was significantly lower than that of the control mice at 16 weeks of age (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ec). Blood glucose, plasma triglyceride (TGs), non-esterified fatty acid (NEFAs), and total cholesterol levels in SsEPS-fed mice were significantly lower than those in the cellulose-fed control mice (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ed and Extended Data Fig.\u0026nbsp;5a). HFD-induced insulin resistance and impaired glucose tolerance, as assessed by insulin tolerance test (ITT) and glucose tolerance test (GTT), respectively, were significantly attenuated in SsEPS-fed mice compared to those in the cellulose-fed control mice (Extended Data Fig.\u0026nbsp;5b). Additionally, plasma insulin levels were significantly lower and plasma GLP-1 levels were significantly higher in SsEPS-fed mice than in cellulose-fed control mice (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ee and Extended Data Fig.\u0026nbsp;5c). Moreover, the resulting food intake was significantly lower in SsEPS-fed mice than in cellulose-fed control mice (Extended Data Fig.\u0026nbsp;5d). However, these SsEPS-induced effects, such as the suppression of body and fat weight gain (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ec), reduced hyperglycemia and hyperlipidemia (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ed and Extended Data Fig.\u0026nbsp;5a), increased plasma GLP-1 levels (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ee), and improved insulin sensitivity (Extended Data Fig.\u0026nbsp;5b), were sufficiently attenuated in \u003cem\u003eGpr41Gpr43\u003c/em\u003e double-deficient mice. Dietary fibre-derived gut microbial SCFAs promote gut hormone secretion, such as GLP-1, through GPR41 and GPR43, thereby maintaining energy homeostasis and glucose metabolism\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Therefore, continuous SsEPS intake improves energy homeostasis.\u003c/p\u003e\n\u003cp\u003eAdditionally, we examined the effects of SsEPS-derived gut microbial SCFAs on glucose homeostasis in the host using GTT. Administration of SsEPS significantly attenuated the increase in blood glucose levels after glucose administration compared to that in control mice; this effect was abolished in \u003cem\u003eGpr41Gpr43\u003c/em\u003e double-deficient mice (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ef). Moreover, the plasma levels of insulin and incretin GLP-1 were higher in SsEPS-administered mice than in control mice after glucose administration. These effects were abolished in \u003cem\u003eGpr41Gpr43\u003c/em\u003e double-deficient mice (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ef and Extended Data Fig.\u0026nbsp;5e). Furthermore, under germ-free (GF) conditions, the SsEPS-induced inhibition of blood glucose elevation and the SsEPS-induced increase in plasma insulin and GLP-1 levels were abolished (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eg and Extended Data Fig.\u0026nbsp;5e). Therefore, SsEPS supplementation improves glucose homeostasis in the host by producing gut microbial SCFAs.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n\u003ch2\u003eChange of host gut microbiota by SsEPS\u003c/h2\u003e\n\u003cp\u003eContinuous SsEPS intake markedly increased SCFA levels in the faeces and plasma (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eb). Given the pivotal role SCFAs play in the beneficial effects of SsEPS on the host, we investigated the changes in the gut microbial composition mediated by SsEPS and identified the gut microbes related to SCFAs production. 16S rRNA amplicon sequencing showed that SsEPS supplementation altered the relative abundances of the major phyla in the gut microbiota (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ea). Notably, the abundances of Bacteroidota and Verrucomicrobiota were significantly increased, while that of Firmicutes was significantly decreased in SsEPS-fed mice (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ea). The effect of SsEPS on the gut microbiome was confirmed by the hierarchical clustering of individual families (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eb). These changes in the gut microbiota after SsEPS intake were associated with the abundance of several families of gut microbes (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eb). Subsequently, a correlation analysis between the gut microbes and SCFAs by comparing these gut microbes at the genus level (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ec) showed high correlation coefficients for \u003cem\u003eBacteroidales\u003c/em\u003e S24-7, including \u003cem\u003eMuribaculum\u003c/em\u003e, \u003cem\u003eParamuribaculum\u003c/em\u003e, \u003cem\u003eDuncaniella\u003c/em\u003e, and \u003cem\u003eBacteroides\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ed). In addition, the abundance of five species which efficiently produced SCFAs during in vitro gut microbe monoculture (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ea) significantly increased after SsEPS supplementation (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ee). As shown by the shotgun metagenomic sequencing data, SsEPS uptake was associated with the carbohydrate metabolic pathway according to GO enrichment analysis (Extended Data Fig.\u0026nbsp;6). Furthermore, glycolytic pathway analysis showed that SsEPS intake increased levan and glucan degradation, and SCFAs synthesis (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ef). Thus, SsEPS intake contributes to the production of SCFAs via the polysaccharide catabolic cascade of members of the \u003cem\u003eBacteroidales\u003c/em\u003e S24-7 group and the genus \u003cem\u003eBacteroides\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAmelioration of sucrose-induced metabolic dysfunction by\u003c/strong\u003e \u003cstrong\u003eS. salivarius\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eS. salivarius\u003c/em\u003e and SsEPS were detected in human faeces but not in mouse faeces (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ea). While \u003cem\u003eBacteroides\u003c/em\u003e and \u003cem\u003eBacteroidales\u003c/em\u003e S24-7 groups are SCFA producers by SsEPS intake in mice, the \u003cem\u003eBacteroidales\u003c/em\u003e S24-7 group is not dominant in humans\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. Therefore, we performed a co-transfer experiment for these species (\u003cem\u003eB. ovatus\u003c/em\u003e and \u003cem\u003eB. thetaiotaomicron\u003c/em\u003e) and confirmed their intestinal colonisation (Extended Data Fig.\u0026nbsp;7a\u0026ndash;c). We found that faecal EPS levels were sufficiently higher in \u003cem\u003eS. salivarius\u003c/em\u003e-colonised and \u003cem\u003eS. salivarius\u003c/em\u003e- and \u003cem\u003eBacteroides\u003c/em\u003e-co-colonised mice but not in \u003cem\u003eBacteroides\u003c/em\u003e-colonised mice after drinking 20% sucrose than in GF mice (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003ea and Extended Data Fig.\u0026nbsp;7d). Faecal acetate and propionate levels were markedly higher only in \u003cem\u003eS. salivarius\u003c/em\u003e and \u003cem\u003eBacteroides\u003c/em\u003e-co-colonised mice. Conversely, butyrate levels were similar between these groups (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eb). Butyrate production by SsEPS intake (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eb) was not reflected in the gnotobiotic experiments, possibly because of the interaction of other gut microbes besides \u003cem\u003eBacteroides\u003c/em\u003e. Thus, \u003cem\u003eS. salivarius\u003c/em\u003e produces EPS, and \u003cem\u003eBacteroides\u003c/em\u003e produces SCFAs from SsEPS in the gut.\u003c/p\u003e\n\u003cp\u003eTwo weeks after colonisation, glucose clearance, as assessed using intraperitoneal GTT (ipGTT) in \u003cem\u003eS. salivarius\u003c/em\u003e- and \u003cem\u003eBacteroides\u003c/em\u003e-co-colonised mice, notably improved between these groups (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003ec). Plasma insulin and GLP-1 levels after glucose administration were higher in \u003cem\u003eS. salivarius\u003c/em\u003e and \u003cem\u003eBacteroides\u003c/em\u003e-co-colonised mice than in \u003cem\u003eS. salivarius\u003c/em\u003e or \u003cem\u003eBacteroides\u003c/em\u003e-colonised mice. However, it has been reported that plasma GLP-1 levels are very high in GF mice (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003ed)\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Moreover, we examined the effects of \u003cem\u003eS. salivarius\u003c/em\u003e and \u003cem\u003eBacteroides\u003c/em\u003e co-colonisation on host energy homeostasis in a sucrose-induced obese mouse model. The body weight of \u003cem\u003eS. salivarius\u003c/em\u003e and \u003cem\u003eBacteroides\u003c/em\u003e-co-colonised mice was markedly lower than those of GF or other colonised mice during growth (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003ee). Additionally, the WAT fat mass was notably lower in \u003cem\u003eS. salivarius\u003c/em\u003e and \u003cem\u003eBacteroides\u003c/em\u003e-co-colonised mice than in the other groups at 16 weeks of age (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003ee). The blood glucose, plasma triglyceride, and NEFAs levels of \u003cem\u003eS. salivarius\u003c/em\u003e and \u003cem\u003eBacteroides\u003c/em\u003e-co-colonised mice were significantly lower than those of GF mice (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003ef and Extended Data Fig.\u0026nbsp;7e). Furthermore, plasma GLP-1 levels were significantly higher in \u003cem\u003eS. salivarius\u003c/em\u003e and \u003cem\u003eBacteroides\u003c/em\u003e-co-colonised mice than in either \u003cem\u003eS. salivarius\u003c/em\u003e- or \u003cem\u003eBacteroides\u003c/em\u003e-colonised mice (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eg). Conversely, in the glucose- or fructose-induced obese mouse models, \u003cem\u003eS. salivarius\u003c/em\u003e-colonised mice did not show an increase in faecal EPS levels (Extended Data Fig.\u0026nbsp;7f). Therefore, \u003cem\u003eS. salivarius\u003c/em\u003e and \u003cem\u003eBacteroides\u003c/em\u003e-co-colonisation improved the metabolic state of the host upon sucrose intake.\u003c/p\u003e\n\u003cp\u003eFinally, we investigated the effects of \u003cem\u003eS. salivarius\u003c/em\u003e on host energy homeostasis using a mouse model of human flora. In this experiment, 7-week-old mice colonised with \u003cem\u003eS. salivarius\u003c/em\u003e-dominant [Ss (+)] or \u003cem\u003eS. salivarius\u003c/em\u003e-non-dominant human gut microbiota [Ss (-)] were fed an HFD supplemented with sugars (sucrose, glucose, or fructose) for 9 weeks (Extended Data Fig.\u0026nbsp;8a\u0026ndash;c). In faecal microbiota transplantation (FMT) experiments, faecal SCFAs and EPS levels of [Ss (+)]-colonised mice with sucrose supplementation were significantly higher than those of [Ss (-)]-colonised mice with sucrose supplementation, and also higher than those of mice with glucose or fructose supplementation (Extended Data Fig.\u0026nbsp;9a, b). The number of \u003cem\u003eS. salivarius\u003c/em\u003e was also sufficiently increased in [Ss (+)]-colonised mice with sucrose supplementation than in [Ss (-)]-colonised mice with sucrose, glucose, or fructose supplementation (Extended Data Fig.\u0026nbsp;9c). The body weight of [Ss (+)]-colonised mice supplemented with sucrose was markedly lower than that of [Ss (-)]-colonised mice supplemented with sucrose during growth, whereas it was similar between [Ss (+)]- and [Ss (-)]-colonised mice supplemented with glucose or fructose (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eh). Additionally, WAT fat mass was significantly lower in [Ss (+)]-colonised mice with sucrose supplementation than in [Ss (-)]-colonised mice with sucrose supplementation, but not in those with glucose or fructose supplementation, at 16 weeks of age (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eh). The blood glucose levels of [Ss (+)] sucrose-supplemented colonised mice were significantly lower than those of [Ss (-)] sucrose-supplemented mice, but not glucose- or fructose-supplemented colonised mice (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003ei). Furthermore, plasma GLP-1 levels were significantly higher in [Ss (+)]-colonised mice supplemented with sucrose than in [Ss (-)]-colonised mice supplemented with sucrose (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003ej). Thus, \u003cem\u003eS. salivarius\u003c/em\u003e-dominant human gut microbiota efficiently ameliorated sucrose-induced metabolic dysfunction.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eCommensal bacteria affect host energy homeostasis by producing various metabolites from host carbohydrate intake via glycometabolism. However, its exact mechanism of action remains unclear. In this study, we found that gut microbes prevent host obesity through excess dietary sucrose intake via the exopolysaccharide (EPS)\u0026ndash;SCFA\u0026ndash;carbohydrate metabolism axis and identified \u003cem\u003eS. salivarius\u003c/em\u003e as a unique anti-obesity commensal bacterium.\u003c/p\u003e \u003cp\u003eIn the first screening, we identified only commensal \u003cem\u003eS. salivarius\u003c/em\u003e as a high-EPS-producing bacterium in human donors because all other high-EPS-producing bacteria were bacteria living in fermented foods. Additionally, while other human gut microbes may produce different EPS, \u003cem\u003eS. salivarius\u003c/em\u003e, being the dominant bacterium in the gut microbiota, can produce large amounts of EPS from sucrose, suggesting that host sucrose intake affects the production of SCFAs, depending on SsEPS. In contrast, EPS has diverse polysaccharide structures, monosaccharide components, main-chain lengths, and branching\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Although our study demonstrated that SsEPS was metabolised to SCFAs by gut microbes, thereby affecting host metabolic conditions, it is possible that EPS itself directly affects host physiological functions or that SCFAs affect the host in a receptor-independent manner, such as through de novo metabolic function via SCFA transporters and histone deacetylase inhibition\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. Moreover, differences in \u003cem\u003eS. salivarius\u003c/em\u003e strains may affect the EPS structure and production. Further studies on \u003cem\u003eS. salivarius\u003c/em\u003e are required to clarify the relationship between homeostasis in humans and gut microbial EPS production. Moreover, we need to clarify the physiological significance of the relationship between the host and gut regarding the observation that \u003cem\u003eS. salivarius\u003c/em\u003e synthesizes EPS only from sucrose and not from glucose or fructose.\u003c/p\u003e \u003cp\u003eAs a facultatively anaerobic lactic acid bacterium, \u003cem\u003eS. salivarius\u003c/em\u003e preferentially inhabits the small intestine, contrary to most other gut microbes that inhabit the colon. This preference is because sucrose, a disaccharide composed of glucose and fructose, is digested by host sucrase into its constituent monosaccharides, which are absorbed in the small intestine. Therefore, \u003cem\u003eS. salivarius\u003c/em\u003e competes with the host sucrose in the small intestine and inhibits the absorption of monosaccharides by the host. Furthermore, SsEPS, an indigestible polysaccharide produced from sucrose by \u003cem\u003eS. salivarius\u003c/em\u003e, is not digested by the host enzyme; \u003cem\u003eBacteroides\u003c/em\u003e utilizes it to produce SCFAs in the gut. The produced SCFAs contribute to the metabolic health of the host (graphic abstract). Therefore, \u003cem\u003eS. salivarius\u003c/em\u003e and EPS may partly contribute to metabolic improvement and high SCFA production by α-glucosidase inhibitors\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn the present study, we demonstrated that commensal bacteria selectively confer obesity tolerance to their hosts through bacterial glycoanabolism. Indigestible polysaccharides play a critical role in regulating the host gut environment and homeostasis by modulating gut microbiota\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. These findings suggest a fundamental mechanism underlying the interplay among diet, host, and commensal bacteria for energy homeostasis via host and commensal glycometabolism through gut microbial EPS production. Additionally, they contribute to the development of breakthrough anti-obesity drugs for high sugar intake in present dietary lifestyles by using probiotics of \u003cem\u003eS. salivarius\u003c/em\u003e and thus prompting the proliferation of \u003cem\u003eS. salivarius\u003c/em\u003e in the intestine or functional foods and dietary supplements by tailoring the prebiotic use of EPS as dietary fibre for the prevention of lifestyle diseases.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis works was supported by research grants from the AMED (JP17gm1010007 and JP23gm1510011), JSPS KAKENHI (JP21H04862 to I.K., JP22K17771 to J.M., and 21K19813 to S.N.), JST-OPERA (JPMJOP1833), JST-MOONSHOOT (JPMJMS2023 to I.K. and S.N.), and Noster Inc (to I.K.).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eH.S. performed the experiments and wrote the paper; J.M. performed the experiments and wrote the paper; K.H. performed the experiments and interpreted the data; R.O.K. performed the experiments and interpreted the data; H.T. performed the experiments and interpreted the data; M.Y. performed the experiments; A.N. performed the experiments; D.S. performed the experiments and interpreted the data; Y.M. performed the experiments; K.W. performed the experiments; S.N. performed the experiments; S.T. performed the experiments; T.I. performed the experiments; Y.N. performed the experiments; N.Y. performed the experiments; C.M. performed the experiments and interpreted the data; T.K. performed the experiments; I.H. performed the experiments; A.M. performed the experiments and interpreted the data; R.A. performed the experiments and interpreted the data; S.K. performed the experiments; M.U. performed the experiments; T.M. performed the experiments and interpreted the data; S.I. performed the experiments and interpreted the data; J.I. performed the experiments and interpreted data; N.S.A. performed the experiments and interpreted the data; H.T. performed the experiments and interpreted the data; H.M. performed the experiments and interpreted the data; S.N. performed the experiments and interpreted the data; T.Y. performed the experiments and interpreted the data; A.T. performed the experiments and interpreted the data; K.Y. performed the experiments and interpreted the data; H.O. performed the experiments and interpreted the data; T.K. performed the experiments and interpreted the data; H.I. performed the experiments and interpreted the data; I.K. supervised the project, interpreted the data, and wrote the paper; I.K. had primary responsibility for the final content. All authors read and approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eH.S, K.H, and D.S. are employees of Noster Inc. Otherwise the authors have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe 16S rRNA sequencing data have been deposited into the DNA Data Bank of Japan (DDBJ) under accession Nos. DRA017528, DRA017529, and DRA017628. The shotgun metagenomic sequencing date are available under accession Nos. DRA017626 and DRA017627. RNA sequencing data are accessible via accession Nos. DRA017530 and E-GEAD-664. Source data for Figs 1\u0026ndash;4, Extended Data Figs 1\u0026ndash;9, 16S rRNA sequencing, shotgun metagenomic sequencing, and RNA sequencing data have been deposited into the Dryad repository (doi:10.5061/dryad.n8pk0p33b). All data generated or analysed during this study that are not included in this published article or its Supplementary Information files are available from the corresponding authors upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eKahn, S. E., Hull, R. L. \u0026amp; Utzschneider, K. M. Mechanisms linking obesity to insulin resistance and type 2 diabetes. \u003cem\u003eNature\u003c/em\u003e \u003cstrong\u003e444\u003c/strong\u003e, 840\u0026ndash;846 (2006). https://doi.org/10.1038/nature05482\u003c/li\u003e\n\u003cli\u003eZimmet, P., Alberti, K. G. \u0026amp; Shaw, J. Global and societal implications of the diabetes epidemic. \u003cem\u003eNature\u003c/em\u003e \u003cstrong\u003e414\u003c/strong\u003e, 782\u0026ndash;787 (2001). https://doi.org/10.1038/414782a\u003c/li\u003e\n\u003cli\u003eCori, C. F. Mammalian carbohydrate metabolism. \u003cem\u003ePhysiol. 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Commun.\u003c/em\u003e \u003cstrong\u003e557\u003c/strong\u003e, 48\u0026ndash;54 (2021). https://doi.org/10.1016/j.bbrc.2021.03.167\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eHuman faecal samples collection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStudy participants were recruited between 2017 and 2022 from Kyoto University (permit number: R2875-4), Keio University (permit number: 20210021), Kobe University (permit number: B210124), Kyoto Medical Center (permit number: 20\u0026ndash;074), Tokyo University of Agriculture and Technology (permit number: 210704-2846) and Fukujuji Hospital (permit number: 21016). The volunteers were Japanese individuals aged 20\u0026ndash;80 years. The exclusion criteria were as follows: Participants with a BMI below 18.5 or above 60 kg m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e; those who regularly took medication with proton pump inhibitors; those with diabetes and hyperlipidemia; those who used antibiotics within 2 weeks; and those who consumed probiotic supplements, including milk, yogurt, and fermented food before sample collection. All the participants involved in this study provided written informed consent. Faecal samples were collected using a stool collection tube and stored at \u0026minus;\u0026thinsp;80\u0026deg;C until preparation and analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFaecal samples cultured condition\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHuman and mouse faecal samples were cultured on MRS agar (Difco Laboratories Inc., Detroit, MI, USA) or MRS agar containing 15% fructose, galactose, glucose, lactose, maltose, and sucrose at 30\u0026deg;C for 48 h under anaerobic conditions. EPS product colonies were picked and underwent 16S ribosomal RNA (rRNA) gene amplification using the primers 27F (5\u0026prime;-AGAGTTTGATCCTGGCTCAG-3\u0026prime;) and 1492R (5\u0026prime;-GGTTACCTTGTTACGACTT-3\u0026prime;). The PCR products were purified using an UltraClean PCR Clean-Up Kit (MO BIO Laboratories, San Diego, CA, USA), and directly sequenced using a Big Dye Terminator Cycle Sequencing Kit ver. 3.1 (Applied Biosystems, Foster City, CA, USA) and an ABI 3730xl DNA analyzer system (Applied Biosystems). The isolated strains shared more than 98% similarity in their 16S rRNA gene sequences.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBacterial culture\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe cultivation of \u003cem\u003eS. salivarius\u003c/em\u003e in MRS medium containing 15% sucrose, 15% glucose, 15% fructose, and 7.5% glucose\u0026thinsp;+\u0026thinsp;7.5% fructose was monitored for 24 h. The dominant gut bacteria were selected using a human gut microbial gene catalog\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e obtained from the Japan Collection of Microorganisms (JCM). Bacteria were recovered according to the manufacturer\u0026rsquo;s instructions as previously described\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Intestinal bacteria were collected in nutrient broth (Difco Laboratories Inc.) containing 10% glycerol and stored at \u0026minus;\u0026thinsp;80\u0026deg;C.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCharacterisation of S. salivarius-produced EPS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eS. salivarius\u003c/em\u003e was cultured on MRS agar alone at 37\u0026deg;C or MRS agar containing 15% sucrose at 30\u0026deg;C for 48 h under anaerobic conditions and imaged using scanning electron microscopy (SEM; JSM-7500F; HUSRI, Aichi, Japan). SsEPS were collected from the agar plate and purified using ethanol precipitation, as previously described\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e or dialysis membranes with a molecular cutoff of 3,500 Da (Snake Skin dialysis tubing, Thermo Fisher Scientific, Waltham, MA, USA). The precipitated SsEPS was dried over calcium chloride for 24\u0026ndash;48 h. To determine its monosaccharide composition, SsEPS was extracted as described previously\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e, with certain modifications. Briefly, SsEPS was hydrolysed by addition of trifluoroacetic acid (0.5 M) and incubated at 120\u0026deg;C for 0.5\u0026ndash;2 h. After incubation, the supernatant was filtered through a 0.45 \u0026micro;m filter. The monosaccharide composition was analysed by ligand exchange chromatography using an 8.0 \u0026times; 300 mm SUGAR SC1011 column (Shodex, Tokyo, Japan). Detection was performed using a RID-20A (Shimadzu, Kyoto, Japan), with D-glucose and D-fructose (Nacalai Tesque, Kyoto, Japan) as standards. The average molecular weight of SsEPS was determined by size exclusion chromatography using an 8.0 \u0026times; 300 mm OHpak SB-800 HQ series column (Shodex). Standards for purchased pullulans (Shodex) and dextrans (Sigma-Aldrich, St. Louis, MO, USA) with average molecular weights of 1,600,000\u0026ndash;5,900 and 1,500,000\u0026ndash;2,800,000 Da, respectively, were established using calibration curves.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStructure of S. salivarius-produced EPS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe structure of the SsEPS was confirmed using \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003eH and \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003eC NMR spectroscopy. SsEPS was dissolved in 750 \u0026micro;L of D\u003csub\u003e2\u003c/sub\u003eO containing 0.1% 3-(trimethylsilyl) propionic-2,2,3,3-\u003cem\u003ed\u003c/em\u003e\u003csub\u003e4\u003c/sub\u003e acid sodium salt (TMSP). After allowing the solution to stand for 12 h, the \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003eH NMR spectrum was recorded using a JEOL ECA-500 spectrometer with a frequency of 500 MHz at 25\u0026deg;C. Chemical shifts are reported in \u003cem\u003e\u0026delta;\u003c/em\u003e (ppm) relative to TMSP as the chemical shift internal standard. \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003eC NMR spectra were recorded on a JEOL ECA-500 spectrometer with a frequency of 125 MHz at 25\u0026deg;C and are reported relative to TMSP signal as the chemical shift internal standard. The infrared (IR) spectra were recorded using a JASCO FT/IR-4100 spectrometer.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eS. salivarius\u003c/em\u003e-produced levan: IR (neat cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e): 3415 (OH); \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003eH NMR (500 MHz, D\u003csub\u003e2\u003c/sub\u003eO): \u003cem\u003e\u0026delta;\u003c/em\u003e 4.20 (d, \u003cem\u003eJ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;8.0 Hz, 1H), 4.14\u0026ndash;4.08 (m, 1H), 3.98\u0026ndash;3.87 (m, 2H), 3.78 (d, \u003cem\u003eJ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;12.0 Hz, 1H), 3.69 (d, \u003cem\u003eJ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;12.0 Hz, 1H), 3.59\u0026ndash;3.55 (m, 1H); \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003eC{\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003eH} NMR (125 MHz, D\u003csub\u003e2\u003c/sub\u003eO): \u003cem\u003e\u0026delta;\u003c/em\u003e 107.1, 83.2, 79.2, 78.1, 66.2, 62.8.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eS. salivarius\u003c/em\u003e-produced glucan: IR (neat cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e): 3375 (OH); \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003eH NMR (500 MHz, D\u003csub\u003e2\u003c/sub\u003eO): \u003cem\u003e\u0026delta;\u003c/em\u003e 4.99 (d, \u003cem\u003eJ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.9 Hz, 1H), 4.04\u0026ndash;3.92 (m, 2H), 3.80\u0026ndash;3.70 (m, 2H), 3.59 (dd, \u003cem\u003eJ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;9.7, 2.9 Hz, 1H); \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003eC{\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003eH} NMR (125 MHz, D\u003csub\u003e2\u003c/sub\u003eO): \u003cem\u003e\u0026delta;\u003c/em\u003e 100.5, 76.2, 74.3, 73.0, 72.4, 68.4.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRNA isolation and quantitative reverse transcriptase (qRT)-PCR\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eS. salivarius\u003c/em\u003e was cultured in MRS medium containing 15% sucrose or 15% glucose at 30\u0026deg;C for 10 h under anaerobic conditions. Total RNA was extracted using the NucleoSpin RNA kit (Takara Bio, Shiga, Japan) and reverse-transcribed into cDNA using Moloney murine leukemia virus reverse transcriptase (Thermo Fisher Scientific). SYBR Premix Ex Taq II (Takara Bio) and StepOnePlus real-time PCR system (Applied Biosystems) were used for qRT-PCR analysis, as previously described\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. SsEPS-synthesised enzyme primer sequences are listed in Extended Data Table\u0026nbsp;1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRNA-sequencing data analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSequencing libraries were constructed using the NEBNext rRNA Depletion Kit (Bacteria) (New England Biolabs, Inc., MA, USA) and the TruSeq Stranded mRNA Library Prep Kit (Illumina, CA, USA) according to the manufacturer's protocols. The sequencing libraries were sequenced on an Illumina HiSeq 2500 platform with 100 bp paired-end reads. On average, 1.2\u0026nbsp;million read pairs per sample were sequenced across eight samples (4 glucose samples and 4 sucrose samples). RNA-Seq data were analysed using the CLC Genomics Workbench (Qiagen Bioinformatics, Venlo, Netherlands) to identify differentially expressed genes. To obtain clean reads, low-quality reads were removed by trimming, whereas high-quality reads were aligned to the \u003cem\u003eS. salivarius\u003c/em\u003e NCTC 7366 genome retrieved from the NCBI database. The parameters were set as follows: minimum length fraction\u0026thinsp;=\u0026thinsp;0.8 and minimum similarity fraction\u0026thinsp;=\u0026thinsp;0.8. Expression values were established as transcripts per million reads (TPM). The KEGG Pathway enrichment analysis was performed from the GhostKOALA result of expressed genes. The enriched pathway for the experiment was identified from the Welch's t-test result with false discovery rate correction (q\u0026thinsp;\u0026lt;\u0026thinsp;0.01) using the R software environment. A gene set enrichment analysis was performed using the Kyoto Encyclopedia of Genes and Genomes database (KEGG) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.genome.jp/kegg/\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eShotgun metagenomic sequencing data analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDNA was quantitated using Qubit fluorometric quantitation (Thermo Fisher Scientific) and qualified by DNA size profiling on a fragment analyzer (Agilent, Santa Clara, CA, USA). High molecular weight DNA (\u0026gt;\u0026thinsp;10 kbp; 3 \u0026micro;g) was used to build the library. DNA shearing into fragments of approximately 150 bp was performed using an ultrasonicator (Covaris, Woburn, MA, USA), and the DNA fragment library was constructed using the Ion Plus Fragment Library and Ion Xpress Barcode Adapters kits (Thermo Fisher). Purified and amplified DNA fragment libraries were sequenced using DNBSEQ-G400 (MGI Tech) with a minimum of 20\u0026nbsp;million high-quality reads of 150 bp (on average) generated per library. The paired-end sequences were merged by BBmaps (v38.84-0)\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. They underwent preprocessing by Kneaddata (v0.12.0) to remove the host genome based on the human (hg37 dec_v0.1) and mouse (C57BL_6NJ) genome databases. The Whole genome sequence based axonomy profile was generated by MetaPhlAn (v4.0.4)\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. Microbial gene families and metabolic pathways were assessed using HUMAnN3 (v3.8)\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e based on the UniRef90 EC filtered database (uniref90_201901). MaAsLin2 was used to identify significant pathway from HUMAnN3 outputs\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. All computational scripts are available on GitHub [\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/petadimensionlab/EPS\u003c/span\u003e\u003c/span\u003e].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSCFAs measurement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSCFA levels in human faeces, murine faeces, and murine plasma were measured following a previously described modified protocol\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. Ether layers containing SCFAs were collected and pooled for gas chromatography-mass spectrometry (GC-MS) using a GCMS-QP2010 Ultra GC mass spectrometer (Shimadzu). The SCFA concentration was evaluated over a specified concentration range.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEPS measurement.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe faecal contents (300 mg) were immediately mixed with five volumes of sterile distilled water containing 2% 5-sulfosalicylic acid and vortexed. The mixture was then centrifuged, and the supernatant containing the EPS was collected. Two volumes of hexane were added to the supernatant, which was then vortexed for 5 min. After centrifugation of the samples at 10,000 \u0026times; g for 15 min, the water layers containing EPS were collected and subjected to HPLC analysis using an RID-20A (Shimadzu) and an 8.0 \u0026times; 300 mm OHpak SB-800 HQ series column (Shodex).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnimal Study\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eC57BL/6J, \u003cem\u003eGpr41Gpr43\u003c/em\u003e double-deficient, and ICR mice were housed under a 12-h light-dark cycle and fed normal chow (CE-2; CLEA, Tokyo, Japan). GF-ICR mice were housed in vinyl isolators under a 12-h light\u0026ndash;dark cycle and fed normal chow (CL-2, 50kGy irradiated; CLEA). \u003cem\u003eGpr41Gpr43\u003c/em\u003e double-deficient mice were generated as described previously\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. All experimental procedures involving mice were performed according to the protocols approved by the Committee on the Ethics of Animal Experiments of the Kyoto University Animal Experimentation Committee (Lif-K21020) and Tokyo University of Agriculture and Technology (permit number: R05-47 and R05-48).\u003c/p\u003e\n\u003cp\u003eFour-week-old C57BL/6J and \u003cem\u003eGpr41Gpr43\u003c/em\u003e double-deficient mice were fed a modified D12492 diet (60% kcal fat; Research Diets, New Brunswick, NJ, USA) for 12 weeks in high fat diet (HFD) studies. The composition of the modified diet is shown in Extended Data Table\u0026nbsp;2.\u003c/p\u003e\n\u003cp\u003eAfter fasting 24 h, 7-week-old C57BL/6J, \u003cem\u003eGpr41Gpr43\u003c/em\u003e double-deficient, conventional ICR, and GF-ICR healthy male mice were fed 0.2 g AIN-93G, containing 50% cellulose or 50% SsEPS. After 1 h, glucose (2 g/kg body weight) was intraperitoneally administered to each mouse. Blood glucose levels in the tail vein were measured using a OneTouch UltraVue glucometer (LifeScan, Milpitas, CA, USA) and an LFS Quick Sensor (LifeScan) before and at 15, 30, 60, 90, and 120 min after injection. Plasma samples were collected from the inferior vena cava at 15 min after glucose administration for insulin and GLP-1 measurement\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eFor the gnotobiotic experiments, 5-week-old GF-ICR mice were fed an AIN-93G diet (50kGy irradiated; Research Diets) for 4 weeks. After 2 weeks, each bacterial strain (1 \u0026times; 10\u003csup\u003e8\u003c/sup\u003e CFU/mouse) was administered via oral gavage three times per week. Sterilised water containing 20% sucrose with or without 0.5% acarbose as an \u0026alpha;-glucosidase inhibitor (Tokyo Chemical Industries, Japan), glucose, and fructose were administered for 2 weeks (fig. S7A and S7G). For long-term treatment, 7-week-old GF-ICR mice were fed an AIN-93G diet, D12492 diet (Research Diets), or modified D12492 diet (50kGy irradiated) for 9 weeks. Each bacterial strain (1 \u0026times; 10\u003csup\u003e8\u003c/sup\u003e CFU/mouse) was administered via oral gavage three times a week at 7 and 11 weeks old. The composition of the modified D12492 diet is shown in Extended Data Table\u0026nbsp;3.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFaecal transplantation in animal experiment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe faecal samples from two women, Ss (+) (aged 43 with a BMI of 30.0 kg m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e) and Ss (-) (aged 45 with a BMI of 40.5 kg m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e) were suspended in equal volumes of nutrient broth (Difco Laboratories Inc.) containing 10% glycerol and stored at \u0026minus;\u0026thinsp;80℃ until use. The thawed frozen samples were cultured anaerobically at 37℃ for 24 hours in GAM medium (Nissui, Tokyo, Japan), filtered through a membrane paper, and orally inoculated into germ-free mice (approximately 250 \u0026micro;l per mouse). Faecal culture solutions were administered once weekly until 16 weeks of age.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBiochemical analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBlood glucose levels were measured using a OneTouch UltraVue glucometer (LifeScan) and an LFS Quick Sensor (LifeScan). The levels of plasma non-esterified fatty acids (LabAssayTM NEFA; Wako Pure Chemical Co. Ltd., Osaka, Japan), triglycerides (LabAssayTM Triglyceride; Wako Pure Chemical Co. Ltd.), total cholesterol (LabAssayTM Cholesterol; Wako Pure Chemical Co. Ltd.), insulin (Mouse Insulin enzyme-linked immunosorbent assay [ELISA]; Shibayagi, Gunma, Japan), and active glucagon like peptide-1 (GLP-1) (GLP-1 [Active] ELISA; Merck Millipore, Billerica, MA, USA) were measured according to the manufacturer\u0026rsquo;s instructions. To prevent degradation of active GLP-1, plasma samples were treated with a dipeptidyl peptidase IV inhibitor (Merck Millipore).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDNA extraction and gut microbial composition\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDNA was extracted from faecal samples using the FastDNA SPIN kit for feces (MP Biomedicals, Irvine, CA, USA) as described previously\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Partial 16S rRNA gene sequences were amplified by targeting the hypervariable regions v4 using the primers 515F; 5\u0026prime;-TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGGTGYCAGCMGCCGCGGTAA-3\u0026prime; and 806R; 5\u0026prime;-GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGGGACTACHVGGGTWTCTAAT-3\u0026prime;. Amplicons generated from each sample were purified using AMPure XP Beads (Beckman Coulter, Brea, CA, USA), and appended with Nextera XT index kit (Illumina, San Diego, CA, USA). Amplicons were sequenced using a MiSeq sequencer (Illumina) and MiSeq Reagent kit (version 3.0; 600 cycles). The 16S rRNA sequence data were then processed using the quantitative insights into the microbial ecology 2 (QIIME 2) pipeline, and analysed using the MiSeq Reporter software with the SILVA database (Illumina). Diversity was analysed using QIIME script core_diversity_analyses.py. Permutational multivariate analysis of variance (QIIME script compare_categories.py) was used to assess the statistical significance of sample groupings. For quantitative PCR, SYBR Premix Ex Taq II (Takara Bio) and StepOnePlus real-time PCR system (Applied Biosystems) were used. The bacterial primer sequences are listed in Extended Data Tables\u0026nbsp;4 and 5.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard error of the mean is presented for all values. We assessed the normality of the data using the Shapiro\u0026ndash;Wilk test (normal distribution was defined at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026ge;\u0026thinsp;0.05). To determine the statistical significance between two groups with normal distribution, we used Student's t-test. For groups with non-normal distribution, the Mann\u0026ndash;Whitney U test was used for comparison. One-way analysis of variance (ANOVA) was used to compare data from multiple groups (three or more). For normally distributed sample sets, Dunnett\u0026rsquo;s post-hoc test was used, whereas the Kruskal\u0026ndash;Wallis test paired with Dunn\u0026rsquo;s post-hoc test was used for non-normally distributed sample sets. Statistical significance was set at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Additionally, The Benjamini\u0026ndash;Hochberg procedure was used to estimate the false discovery rates (Q-values) of the 16S rRNA gene sequencing data. This study analysed the correlations between microbiota and gut environmental factors. To calculate correlations, we used Spearman's rank correlation coefficients for bacterial genus abundance, including \u003cem\u003eMuribaculum\u003c/em\u003e, \u003cem\u003eParamuribaculum\u003c/em\u003e, \u003cem\u003eDuncaniella\u003c/em\u003e, \u003cem\u003eBacteroides\u003c/em\u003e, \u003cem\u003eAkkermansia\u003c/em\u003e, \u003cem\u003eFaecalitalea\u003c/em\u003e, \u003cem\u003eDesulfovibrio\u003c/em\u003e, \u003cem\u003eStreptococcus\u003c/em\u003e, \u003cem\u003eBlautia\u003c/em\u003e, and \u003cem\u003eRuminococcus\u003c/em\u003e and faecal SCFAs, such as acetate, propionate, and n-butyrate. We selected only correlations with an absolute value above 0.6 and a Q-value below 0.05. Outliers were evaluated using the Smirnov\u0026ndash;Grubbs test.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-3889905/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3889905/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCommensal bacteria affect host health by producing various metabolites from dietary carbohydrates via bacterial glycometabolism; however, the underlying mechanism of action remains unclear. Here, we identified \u003cem\u003eStreptococcus salivarius\u003c/em\u003e as a unique anti-obesity commensal bacterium. We found that \u003cem\u003eS. salivarius\u003c/em\u003e may prevent host obesity caused by excess sucrose intake via the exopolysaccharide (EPS)-short-chain fatty acid (SCFA)-carbohydrate metabolic axis. Healthy human donor-derived \u003cem\u003eS. salivarius\u003c/em\u003e produced high EPS levels from sucrose but not from other sugars. \u003cem\u003eS. salivarius\u003c/em\u003e abundance was significantly decreased in human donors with obesity, and the EPS-SCFA bacterial carbohydrate metabolic process was attenuated. Our findings reveal an important mechanism by which host\u0026ndash;commensal interactions in glycometabolism affect energy regulation, suggesting an approach for preventing lifestyle-related diseases via prebiotics and probiotics by targeting bacteria and EPS metabolites.\u003c/p\u003e","manuscriptTitle":"Sucrose-preferring gut microbes prevent host obesity by producing exopolysaccharides","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-16 06:32:09","doi":"10.21203/rs.3.rs-3889905/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nature-communications","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"NCOMMS","sideBox":"Learn more about [Nature Communications](http://www.nature.com/ncomms/)","snPcode":"","submissionUrl":"https://mts-ncomms.nature.com/","title":"Nature Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Communications","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"ebf0d914-03fa-49f7-a1b5-c685c489eb37","owner":[],"postedDate":"February 16th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":28687081,"name":"Biological sciences/Microbiology"},{"id":28687082,"name":"Biological sciences/Physiology"},{"id":28687083,"name":"Health sciences/Diseases/Metabolic disorders"}],"tags":[],"updatedAt":"2025-01-30T08:07:24+00:00","versionOfRecord":{"articleIdentity":"rs-3889905","link":"https://doi.org/10.1038/s41467-025-56470-0","journal":{"identity":"nature-communications","isVorOnly":false,"title":"Nature Communications"},"publishedOn":"2025-01-29 05:00:00","publishedOnDateReadable":"January 29th, 2025"},"versionCreatedAt":"2024-02-16 06:32:09","video":"","vorDoi":"10.1038/s41467-025-56470-0","vorDoiUrl":"https://doi.org/10.1038/s41467-025-56470-0","workflowStages":[]},"version":"v1","identity":"rs-3889905","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3889905","identity":"rs-3889905","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}