Water-soluble cellulose acetate attenuates glucose intolerance through GLP-1 and PYY signal upregulation

Water-soluble cellulose acetate attenuates glucose intolerance through GLP-1 and PYY signal upregulation | 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 Article Water-soluble cellulose acetate attenuates glucose intolerance through GLP-1 and PYY signal upregulation Kohei Asaeda, Tomohisa Takagi, Eiki Murakami, Hikaru Hashimoto, and 15 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5984591/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 02 Jul, 2025 Read the published version in npj Science of Food → Version 1 posted 15 You are reading this latest preprint version Abstract Water-soluble cellulose acetate (WSCA), derived from natural cellulose and acetate, can be used as a food additive and deliver acetate to the large intestine. In this study, we investigated the effects of dietary WSCA supplementation on impaired glucose metabolism in db/db mice, a model of type 2 diabetes mellitus. db/m and db/db mice were fed either a control diet or a WSCA-supplemented diet for eight weeks. The WSCA-supplemented group exhibited improved glucose intolerance or lipid metabolism without any loss of skeletal muscle mass or grip strength. WSCA supplementation significantly increased acetate concentrations in the cecum, stool, and blood. Furthermore, serum levels of glucagon-like peptide-1 (GLP-1) and peptide YY (PYY) were significantly higher in the WSCA group than in the control group. These findings suggest that WSCA delivers acetate to the colon and prevents diabetes by enhancing GLP-1 and PYY secretion in db/db mice. Biological sciences/Biochemistry Health sciences/Endocrinology/Endocrine system and metabolic diseases Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Diabetes mellitus is a chronic metabolic disease with a globally increasing prevalence every year, making it a major global health issue 1 . In addition to affecting quality of life, diabetes significantly increases the risk of complications and affects patient prognosis 2 . Recent systematic research has shown that short-chain fatty acids (SCFAs) such as butyrate, acetate, and propionate contribute to the improvement of blood glucose levels and dyslipidemia in diabetic mouse models, and their application for diabetes treatment is expected 3 . SCFAs are the primary products of the bacterial fermentation of dietary fiber, performed by gut microbes, that positively impact the host. In particular, acetate, the most abundant SCFA, plays an important role in regulating body weight and insulin sensitivity. Hence, potential therapies to increase gut microbial fermentation and acetate production have been extensively investigated 4 . Cellulose is a naturally occurring polysaccharide and is usually the main component of plant cell walls. Irrespective of species, approximately 50% of solid cell wall components of wood is cellulose. Hence, cellulose is one of the most abundant global organic resources. However, there are limitations to its utilization related to processing because cellulose is insoluble in water and other simple common organic solvents. One approach to addressing this processing issue of cellulose is chemical modification to make it soluble in water or a common solvent. Among such chemical modifications, an approach that has been widely implemented for decades commercially is cellulose acetylation, chemically turning cellulose into cellulose acetate (CA) 5 . Other chemical modifications of cellulose include, for example, methylation, carboxymethylation, and hydroxypropylation, turning cellulose into methyl cellulose (MC), carboxymethyl cellulose (CMC), and hydroxypropyl cellulose (HPC), respectively. MC, CMC, and HPC are water soluble and have been utilized in the food industry to improve food texture. Ordinary CA has been utilized industrially for making materials such as dialysis membranes, water treatment membranes, and film components of polarizers for liquid crystal display, after being processed to the required shape using common organic solvents 5 6 . Ordinary CA has not been utilized in the food industry because it lacks water solubility. Although not yet implemented commercially, water-soluble CA is achieved by controlling the degree of chemical modification (degree of acetylation) within a certain range. For cellulose, the degree of acetylation necessary to make it water soluble is roughly 15–30%, based on the hydroxyl groups available for acetylation, whereas that for ordinary CA is 80–95% 7 . Water-soluble CA with a degree of acetylation of 15–30% is sometimes called WSCA. WSCA, owing to its water solubility, could serve as a food additive. When hydrolyzed, WSCA leads to naturally occurring cellulose and acetate. The degradation of WSCA by enzyme systems (naturally occurring enzyme cocktails) expressed in wood cellulolytic fungus systems is well-studied 8 . These enzyme systems usually include acetyl esterases for naturally occurring acetylated polysaccharides such as xylan; these are also capable of hydrolyzing the acetyl groups in WSCA liberating acetate as a result. WSCA administration was found to increase acetate concentration in human feces and rat cecum contents 9 10 . Therefore, WSCA may act as a prebiotic to modulate host nutritional physiology by increasing the acetate concentration in the intestinal tract of monogastric animals. However, the effects of WSCA on various diseases remain unclear. In this study, we aimed to investigate the effects of WSCA in treating glucose intolerance and body weight control in a mouse model of diabetes mellitus. Results WSCA suppressed weight gain, especially in db/db mice Figure 1 a shows the protocol of the current experiment. The mice on the control diet gained weight, whereas those fed the WSCA diet did not. Significant differences in body weight were observed between the groups, with more pronounced differences in the db/db mice (Fig. 1 b). WSCA intake suppressed a tendency towards obesity (Fig. 1 c). Figure 1 d shows the weekly changes in oral food intake. The amount of food consumed during the acclimatization period was attributed the value of 1.0. (Fig. 1 d). The total amount of food consumed per mouse during the 8-week experiment period is shown in Fig. 1 e. No evident difference in food intake was observed in the db/m group; however, the db/db WSCA group consumed significantly less food than the db/db control group. WSCA normalized blood glucose levels The db/db control group showed a trend toward elevation of blood glucose levels, whereas the db/db WSCA group showed normalization of blood glucose levels (Fig. 2 a). In the glucose tolerance test, the WSCA group showed a lower blood glucose level at 120 min (Fig. 2 b) and lower area under the curves (AUCs) in the oral glucose tolerance test (OGTT) than the control group (Fig. 2 c) in db/m and db/db mice. Insulin levels (Fig. 2 d), fasting insulin levels (Fig. 2 e), and homeostatic model assessment for insulin resistance (HOMA-IR) (Fig. 2 f) were measured simultaneously in the glucose tolerance test. The db/db WSCA group maintained additional insulin secretory capacity and normalized blood glucose levels. In addition, insulin resistance tended to improve in the db/db WSCA group, although the difference was not significant. WSCA improved liver injury and lipid metabolism The biochemistry test results revealed that aspartate aminotransferase (AST), total cholesterol, and glycated albumin levels in the db/db WSCA group were significantly lower than those in the db/db control group (Table 1 ). WSCA improved fatty liver and maintained muscle mass or grip strength The macroscopic appearance and microscopic findings of the liver showed apparent differences in the size and percentage of fat droplets between the db/db control and db/db WSCA groups (Fig. 3 a). Liver weight was significantly lower in the db/db WSCA group than in the db/db control group (Fig. 3 b). NAS score, which indicates the histological severity of fatty liver 11 , was significantly lower in the db/db WSCA group than in the db/db control group (Fig. 3 c). No differences in epididymal or brown fat content were observed (Fig. 3 d and 3 e). While the db/m WSCA and db/db WSCA groups showed reduction in body weight as shown in Fig. 1 b, the plantaris or soleus muscle weight or grip strength did not decrease following WSCA administration (Fig. 3 f, g, and h ). WSCA increased the concentration of acetate in stool, cecum contents, and sera The concentration of acetate significantly increased in the feces, cecum contents, and blood of db/m and db/db mice in the WSCA group compared with that in the control group (Fig. 4 a, d, j). The concentration of propionate significantly increased in the feces of db/m mice in the WSCA group and showed a non-significant but increasing trend in db/db mice in the WSCA group (Fig. 4 b). Regarding the concentration of propionate and butyrate in cecum contents, there was a rising trend in db/m and db/db mice in the WSCA groups (Fig. 4 e, f). Expression of Gpr41 and Gpr43 in the colon did not differ between the db/db control group and the db/db WSCA group The relative mRNA expression of Gpr41 and Gpr43 in the colonic mucosa (normalized to the expression of actin) did not significantly differ between the db/db control and db/db WSCA groups (Fig. 5 a, b). Glucagon-like peptide-1 (GLP-1) and peptide YY (PYY) levels in the sera increased after WSCA administration Serum GLP-1 and PYY levels in db/m and db/db mice in the WSCA group were significantly higher than those in the control group (Fig. 5 c, d). Discussion This is the first study to show that WSCA improves obesity and glucose intolerance in a mouse model of diabetes mellitus. The db/db mice develop diabetes due to overeating caused by their abnormal leptin receptors 12 . WSCA suppressed overeating and normalized body weight in db/db mice. In addition, glucose intolerance, dyslipidemia, and fatty liver observed in db/db mice improved following WSCA intake. The importance of regulating appetite in the treatment of diabetes and obesity caused by overeating has been attracting attention. One of the most researched topics in this context is acetate role – a major SCFA. It has been shown that acetate in the large intestine is absorbed into the bloodstream, crosses the blood-brain barrier, and is directly involved in appetite regulation in the central nervous system, mainly in the hypothalamus 13 . It is also known that acetate in the large intestine promotes the secretion of anorectic hormones such as PYY and GLP-1 from large intestinal L cells and leptin from adipocytes via GPR41 and GPR43 expressed in the intestinal epithelium 14 . It has been well known that GPRs are expressed in various tissues and influence many important metabolic mechanisms that maintain energy homeostasis. In particular, GPR41 and GPR43 can be activated by SCFAs and have been targeted in therapeutic strategies for the treatment of metabolic disorders including 15 16 . As such, it is known that acetate regulates appetite not only via central nervous system but also through gastrointestinal hormones. In the present study, it was found that WSCA increased the concentration of acetate in the intestinal tract and increased serum GLP-1 and PYY. In addition, since an increase in serum acetate concentration was also observed following WSCA intake, it is expected that the central nervous system's appetite control mechanism was also implicated, resulting in the normalization of the amount of food intake in db/db mice. The WSCA examined in this study has the potential to be used as a food additive given its physical properties 8 . Although the involved enzyme systems have not been fully elucidated, the metabolism of WSCA in the digestive systems of ruminants and rodents was investigated. Watabe et al. reported through that WSCA is metabolized by ruminal bacteria cultures in vitro to generate acetate while increasing the proportion of the genus Prevotella in cultures 17 . Genda et al. reported that acetate, succinate, and propionate are increased in the cecum of rats fed with WSCA while increasing the proportion of Bacteroides xylanisolvens belonging to the order Bacteroidales in gut microbiome 10 . Strobel reported that Prevotella ruminicola belonging to the Bacteroidales order is capable of metabolizing succinate to propionate 18 . Taken together, the evidence by Genda and Strobel suggests that WSCA is metabolized to propionate in the gut of rats by bacteria such as those belonging to the order Bacteroidales via a pathway involving cellulose, glucose, phosphoenol pyruvate (PEP), and succinate. In other words, propionate generation from WSCA in the gut of rats suggests that WSCA is subject to enzymatic hydrolysis in the gut to regenerate cellulose. Although we have not analyzed the intestinal bacteria involved in this study, we confirmed the increase in propionate as well as acetate in the feces and cecum contents, and our results were consistent with Genda’s and Strobel’s findings. The results of this study suggest that acetate is mainly involved, but propionate may also be involved. WSCA metabolism was also investigated from human stool cultures. Yamada et al. reported that WSCA is metabolized to acetate and propionate in human stool cultures while increasing Bacteroides uniformis, and that Bacteroides uniformis can grow in pure cultures supplemented with WSCA 9 . It has also been reported that gamma‑aminobutyric acid (GABA) is increased in human stool cultures supplemented with WSCA presumably by the contribution of Bacteroides uniformis 19 . Rodent trials also suggested that WSCA might be beneficial to gut immunity 20 , cholesterolhemia 10 , and moderate bodyweight gain 10 , in line with our findings. In conclusion, WSCA contributes to host health by increasing the concentration of acetate in the large intestine in diabetic mice. Previous systematic search has shown that SCFAs such as butyrate, acetate, and propionate contribute to the improvements in blood glucose levels and dyslipidemia in diabetic mice models; thus, their application for the treatment of diabetes is expected 3 . In the future, it is expected that the safety of WSCA for humans will be verified and its potential application for the prevention and treatment of diabetes will be explored. Methods Animals Seven-week-old male C57BLS/J lar- m+/+Lepr db (heterozygous, db/m) and C57BLKS/J lar- +Lepr db/+Lepr db (homozygous, db/db) mice were obtained from Shimizu Laboratory Supplies (Kyoto, Japan). The mice were maintained at 40–70% relative humidity, 18–24°C, and a 12-h light/dark cycle. They were allowed free access to water and food for 1 week during the acclimation period. Experiments were conducted in accordance with the guidelines of the National Institute of Health for the use of animals in research. The Kyoto Prefectural University of Medicine Animal Care Committee approved all experimental protocols (permission numbers M2023-41). For 8 weeks, the mice were fed either a control diet (control diet; AIN-93G, 361.2 kcal/100 g, fat kcal 7.0% soybean oil, cellulose 5%/w; Oriental Bio Service, Kyoto, Japan) or a modified AIN-93G rodent diet in which 1% cellulose was replaced with WSCA (Table 1 ). The WSCA used in this experiment was provided by Daicel Corporation (Osaka, Japan), and its properties are shown in Supplementary Fig. 1. Oriental Bio Service mixed WSCA with AIN-93G to create a solid rodent food upon our request. Twenty-eight db/m and db/db mice were assigned to four groups: (1) db/m control, (2) db/m WSCA, (3) db/db control, and (4) db/db WSCA. The cages used were 320 mm long, 220 mm wide, and 135 mm high, and 3 − 4 mice were assigned to each cage. The amount of food intake in each group was measured at the same time each week and the food was replaced with fresh food for 9 weeks. At 15 weeks of age, all the mice were sacrificed under isoflurane anesthesia after 16 h of overnight fasting (Fig. 1 a). Analytical procedure for blood glucose level estimation and OGTT Blood was drawn from the tail vein and blood glucose levels were measured using a glucometer (Glutest Mint; Sanwa Kagaku Kenkyusho, Nagoya, Japan) at the same time each week. The OGTT was performed after 16 h of fasting, and 1 g glucose per kilogram of body weight was administered orally by needle feeding at 15 weeks of age. Blood glucose levels were measured before and 30, 60, and 120 min after administration. The AUC in the OGTT was analyzed. Measurement of grip strength The grip strength of 15-week-old mice was measured using a strain gauge (GPM-100; Melquest, Toyama, Japan). Grip strength measurements were taken 10 consecutive times at 1-min intervals over 2 days, and the investigators were blinded to the experimental conditions. Biochemistry Blood samples were taken from fasted mice and serum samples were collected after centrifugation at 900g for 15 min at 17°C. The level of AST and alanine aminotransferase were measured using a standardization support method of the Japanese Society for Clinical Chemistry 21 . The levels of total cholesterol 22 , triglycerides 23 , and non-esterified fatty acids 24 were measured using the enzymatic method of FUJIFILM Wako Pure Chemical Corporation (Osaka, Japan). Low-density lipoprotein cholesterol 25 levels were measured directly by Sekisui Medical (Tokyo, Japan). Glycated albumin level was measured using the enzymatic and BCG methods by Asahi Kasei Pharma (Tokyo, Japan) and FUJIFILM Wako Pure Chemical Corporation (Osaka, Japan). Liver histology The livers of the sacrificed mice were fixed in 10% buffered formaldehyde and embedded in paraffin. Sections were prepared and stained with hematoxylin and eosin (HE). To evaluate fatty liver, microscopic observations were performed at 40× and 200× and evaluated according to the NAS score 26 . Measurement of organ weights The livers, epididymal fat, brown fat, and plantaris and soleus muscles of the mice were removed immediately after they were sacrificed. The weight of each organ per unit of body weight during dissection was evaluated. Measurement of SCFA levels in the feces and cecum contents A portion of the fecal or cecal content was collected, weighed, and suspended in perchloric acid (0.5 mL) to remove the protein. After centrifugation at 10,000 × g for 5 min at 4°C, the resulting supernatant was filtered through a cellulose acetate membrane filter with a pore size of 0.45 µm. Organic acid content was analyzed using ion-exclusion high-performance liquid chromatography. The amounts of organic acid substances per unit weight of feces and cecum were measured 27 . Measurement of SCFA levels in sera Serum contents were immediately added to 5-sulfosalicylic acid, followed by vortexing for 1 min. The samples were centrifuged at 15,000 × g for 15 min and the supernatant was collected. The supernatant was mixed with 2-ethylbutyric acid (internal control), hydrochloric acid, and diethyl ether and vortexed for 1 min. The samples were centrifuged at 3,000 × g for 5 min, and the SCFA-containing ether layers were collected and pooled for gas chromatography-mass spectrometry analysis using a GCMS-QP2010 Ultra instrument (Shimadzu). The VF-WAXms (30 m × 0.25 mm internal diameter × 1 µm; Agilent Technologies) was used for chromatographic separation. Helium (0.92 mL/min) was used as the carrier gas. The mass spectrometer was set to scan mode from m/z 40 − 130 and to the selected ion monitoring mode at m/z 60 (retention time: 9.6) for acetate, m/z 74 (retention time: 10.7) for propionate, and m/z 60 (retention time: 12.5) for n-butyrate. The concentration of SCFAs in each sample was determined using an external standard calibration curve over a specified concentration range 27 . Gene expression analysis in murine colons Total RNA was isolated using the acid guanidinium phenol-chloroform method with TRIzol reagent (Thermo Fisher Scientific USA), according to the manufacturer’s instructions as previously described 28 . The resultant cDNA was used for quantitative reverse transcription polymerase chain reaction (qRT-PCR) using specific primers: GPCR41, 5′-TGGCTTTTCTTTTCCGTCTACCT-3′ and antisense 5′-AAGACCACCAGGGCCATCA-3′; GPCR43, 5′-GATGTGGTACTGCCCGTACGA-3′ and antisense 5′-GACTGCCATGGGAACGAAAA-3′; actin, 5′-TATCCACCTTCCAGCAGATGT-3′ and antisense 5′-AGCTCAGTAACAGTCCGCCTA-3′. PCR was performed using PowerUp SYBR Green PCR master mix and QuantStudio 6 Pro real-time PCR system (Thermo Fisher Scientific). The PCR conditions included 40 cycles at 95°C for 15 s and primer annealing at 60°C for 1 min, with a subsequent melting curve analysis in which the temperature was increased from 60°C to 95°C. Gene expression levels were calculated from the quantitative reverse transcription-PCR data and normalized to actin expression. Measurement of serum GLP-1 and PYY levels Serum samples were collected from the sacrificed mice and processed as described in the “Biochemistry” section. Serum GLP-1 and PYY levels were quantified using a GLP-1 enzyme-linked immunosorbent assay (ELISA) kit (FUJIFILM Wako Pure Chemical Corporation) and a PYY ELISA kit (FUJIFILM Wako Pure Chemical Corporation). Statistical analysis Analysis of variance (ANOVA) was performed to assess the trend of the mean stratified according to normally distributed continuous variables. All analyses were performed using JMP PRO version 14.0.0 (SAS Institute Japan Ltd). Differences were considered statistically significant at p < 0.05. Declarations Data availability statement The datasets analyzed during the current study are available from the corresponding author on reasonable request. Code availability statement There are no computer codes or scripts that should be reported in this report. Competing interest statement All authors declare no financial or non-financial competing interests. Funding This work was supported by a Grant-in-Aid for Scientific Research (KAKENHI) (C) from the Japanese Society for the Promotion of Science (grant number: 24K11092, awarded to Tomohisa Takagi). Author Contribution KA and TT contributed substantially to this study. KA, TT, ME, HH, TY, MK, TS, YH, KI, KU, SS, and YU contributed to the data analysis and interpretation. KA, TT, KM, KU, SS, and YU drafted the manuscript. YN and YI critically revised the manuscript. All authors read and approved the final manuscript. Acknowledgements This work was partially supported by Taiyo Kagaku Co., Ltd. We thank all the members of the Department of Molecular Gastroenterology and Hepatology, Kyoto Prefectural University of Medicine, and Graduate School of Medical Science, Kyoto Prefectural University of Medicine for their help with this study. References Sun, H. et al. IDF Diabetes Atlas: Global, regional and country-level diabetes prevalence estimates for 2021 and projections for 2045. Diabetes Res Clin Pract 183 , 109119 (2022). Chan, J. C. N. et al. The Lancet Commission on diabetes: using data to transform diabetes care and patient lives. Lancet 396 , 2019–2082 (2021). Zheng, J. et al. Effects of short-chain fatty acids on blood glucose and lipid levels in mouse models of diabetes mellitus: A systematic review and network meta-analysis. Pharmacol Res 199 , 107041 (2024). Hernandez, M. A. G., Canfora, E. E., Jocken, J. W. E. & Blaak, E. E. The Short-Chain Fatty Acid Acetate in Body Weight Control and Insulin Sensitivity. Nutrients 11 (2019). Sata, H., Murayama, M. & Shimamoto, S. 5.4 Properties and applications of cellulose triacetate film. Macromolecular Symposia 208 , 323–334 (2004). Shibata, T., Shu, S. & Okura, H. Interaction of Cellulose with Organic Molecules andthe Functionality Derived from it. Journal of The Adhesion Society of Japan 54 , 150–157 (2018). Maim, C. J., Barkey, K. T., Salo, M. & May, D. C. CELLULOSE DERIVATIVES - Far-Hydrolyzed Cellulose Acetates. Industrial & Engineering Chemistry 49 , 79–83 (1957). Puls, J., Altaner, C. & Saake, B. 4.3 Degradation and modification of cellulose acetates by biological systems. Macromolecular Symposia - MACROMOL SYMPOSIA 208 , 239–254 (2004). Yamada, H. et al. Chemical and microbial characterization for fermentation of water-soluble cellulose acetate in human stool cultures. J Sci Food Agric 101 , 2950–2960 (2021). Genda, T. et al. Bacterial Fermentation of Water-Soluble Cellulose Acetate Raises Large-Bowel Acetate and Propionate and Decreases Plasma Cholesterol Concentrations in Rats. J Agric Food Chem 66 , 11909–11916 (2018). Kleiner, D. E. et al. Design and validation of a histological scoring system for nonalcoholic fatty liver disease. Hepatology 41 , 1313–1321 (2005). Chen, H. et al. Evidence that the diabetes gene encodes the leptin receptor: identification of a mutation in the leptin receptor gene in db/db mice. Cell 84 , 491–495 (1996). Frost, G. et al. The short-chain fatty acid acetate reduces appetite via a central homeostatic mechanism. Nat Commun 5 , 3611 (2014). Chambers, E. S., Morrison, D. J. & Frost, G. Control of appetite and energy intake by SCFA: what are the potential underlying mechanisms? Proc Nutr Soc 74 , 328–336 (2015). Hara, T., Kimura, I., Inoue, D., Ichimura, A. & Hirasawa, A. Free fatty acid receptors and their role in regulation of energy metabolism. Rev Physiol Biochem Pharmacol 164 , 77–116 (2013). Kimura, I., Ichimura, A., Ohue-Kitano, R. & Igarashi, M. Free Fatty Acid Receptors in Health and Disease. Physiol Rev 100 , 171–210 (2020). Watabe, Y., Suzuki, Y., Koike, S., Shimamoto, S. & Kobayashi, Y. Cellulose acetate, a new candidate feed supplement for ruminant animals: In vitro evaluations. J Dairy Sci 101 , 10929–10938 (2018). Strobel, H. J. Vitamin B12-dependent propionate production by the ruminal bacterium Prevotella ruminicola 23. Appl Environ Microbiol 58 , 2331–2333 (1992). Yamada, H. et al. In vitro Effects of Cellulose Acetate on Fermentation Profiles, the Microbiome, and Gamma-aminobutyric Acid Production in Human Stool Cultures. Curr Microbiol 80 , 284 (2023). Takeuchi, T. et al. Acetate differentially regulates IgA reactivity to commensal bacteria. Nature 595 , 560–564 (2021). Kotani, K., Maekawa, M. & Kanno, T. [Reestimation of aspartate aminotransferase (AST)/alanine aminotransferase (ALT) ratio based on JSCC consensus method–changes of criteria for a differential diagnosis of hepatic disorders following the alteration from Karmen method to JSCC method]. Nihon Shokakibyo Gakkai Zasshi 91 , 154–161 (1994). Allain, C. C., Poon, L. S., Chan, C. S., Richmond, W. & Fu, P. C. Enzymatic determination of total serum cholesterol. Clin Chem 20 , 470–475 (1974). McGowan, M. W., Artiss, J. D., Strandbergh, D. R. & Zak, B. A peroxidase-coupled method for the colorimetric determination of serum triglycerides. Clin Chem 29 , 538–542 (1983). Christmass, M. A., Mitoulas, L. R., Hartmann, P. E. & Arthur, P. G. A semiautomated enzymatic method for determination of nonesterified fatty acid concentration in milk and plasma. Lipids 33 , 1043–1049 (1998). Friedewald, W. T., Levy, R. I. & Fredrickson, D. S. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem 18 , 499–502 (1972). Kleiner, D. E. et al. Design and validation of a histological scoring system for nonalcoholic fatty liver disease. Hepatology 41 , 1313–1321 (2005). 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). Kajiwara-Kubota, M. et al. Partially hydrolyzed guar gum increased colonic mucus layer in mice via succinate-mediated MUC2 production. NPJ Sci Food 7 , 10 (2023). Tables Table 1. Serum biochemistry results in db/m and db/db mice Table 2. Composition of the test diets (%) Additional Declarations No competing interests reported. Supplementary Files Supplement.docx Cite Share Download PDF Status: Published Journal Publication published 02 Jul, 2025 Read the published version in npj Science of Food → Version 1 posted Editorial decision: Revision requested 06 May, 2025 Reviews received at journal 29 Apr, 2025 Reviews received at journal 28 Apr, 2025 Reviewers agreed at journal 23 Apr, 2025 Reviews received at journal 21 Apr, 2025 Reviewers agreed at journal 21 Apr, 2025 Reviewers agreed at journal 21 Apr, 2025 Reviews received at journal 15 Apr, 2025 Reviewers agreed at journal 12 Apr, 2025 Reviews received at journal 07 Apr, 2025 Reviewers agreed at journal 06 Apr, 2025 Reviewers invited by journal 01 Apr, 2025 Editor assigned by journal 10 Mar, 2025 Submission checks completed at journal 10 Mar, 2025 First submitted to journal 07 Feb, 2025 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. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5984591","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":427975271,"identity":"79edea49-f8d7-4151-8ad5-74a69221a63f","order_by":0,"name":"Kohei Asaeda","email":"","orcid":"","institution":"Kyoto Yamashiro General Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Kohei","middleName":"","lastName":"Asaeda","suffix":""},{"id":427975272,"identity":"630fed35-538a-4c6c-a954-d7524d6d39fd","order_by":1,"name":"Tomohisa Takagi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAklEQVRIiWNgGAWjYFACNgjFzwOmEuDizLg08IC0HAAyJHsYGBtI02JwBk0LTmDPfizx84eKbXLGZw4ff/CBIS3P4AB3AsOPGgZ2c1y28KQdljhw5rax2dm2xMYZDDnFBgd4NzD2HGNgtmzA5bD0BomDbbcTt53nMWzmYahI3HD/7QYG3gYGZoMDOLTwP2/+AdKyuR+mBWTLX3xaJNKOgW3ZwNsD0pID1sKM15Ybz9IszgD9InHmWOLMGQZpxZJALYdljkng9At7f5rxjYqK23L8PckHPnyoSM7jO8C78eGbGptkXCGGBgwgEQN0kkSyAXFakOLSjmgto2AUjIJRMNwBANH4Xf3T7MOxAAAAAElFTkSuQmCC","orcid":"","institution":"Kyoto Prefectural University of Medicine","correspondingAuthor":true,"prefix":"","firstName":"Tomohisa","middleName":"","lastName":"Takagi","suffix":""},{"id":427975273,"identity":"7e743857-8018-410c-938e-f3537cc68162","order_by":2,"name":"Eiki Murakami","email":"","orcid":"","institution":"Kyoto Prefectural University of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Eiki","middleName":"","lastName":"Murakami","suffix":""},{"id":427975274,"identity":"c546d767-466f-4a87-852a-352b44a5aae0","order_by":3,"name":"Hikaru Hashimoto","email":"","orcid":"","institution":"Osaka General Hospital of West Japan Railway Company","correspondingAuthor":false,"prefix":"","firstName":"Hikaru","middleName":"","lastName":"Hashimoto","suffix":""},{"id":427975275,"identity":"ae94555c-db88-4b5e-bedb-8b0b0ecf3f17","order_by":4,"name":"Takeshi Yasuda","email":"","orcid":"","institution":"Akashi City Hospital","correspondingAuthor":false,"prefix":"","firstName":"Takeshi","middleName":"","lastName":"Yasuda","suffix":""},{"id":427975276,"identity":"8682547a-5b73-421a-9a41-729dc64627c1","order_by":5,"name":"Mariko Kubota-Kajiwara","email":"","orcid":"","institution":"Fukuchiyama City Hospital","correspondingAuthor":false,"prefix":"","firstName":"Mariko","middleName":"","lastName":"Kubota-Kajiwara","suffix":""},{"id":427975277,"identity":"dd365962-5e82-44e3-9626-0dfa9bb3de2a","order_by":6,"name":"Takeshi Sugaya","email":"","orcid":"","institution":"Dokkyo Medical University","correspondingAuthor":false,"prefix":"","firstName":"Takeshi","middleName":"","lastName":"Sugaya","suffix":""},{"id":427975278,"identity":"c143df9d-20ab-4763-a46e-74a69af37c77","order_by":7,"name":"Katsura Mizushima","email":"","orcid":"","institution":"Kyoto Prefectural University of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Katsura","middleName":"","lastName":"Mizushima","suffix":""},{"id":427975279,"identity":"15ebed95-05d3-40c2-8569-3ffbf306ce9b","order_by":8,"name":"Yasuki Higashimura","email":"","orcid":"","institution":"Ishikawa Prefectural University","correspondingAuthor":false,"prefix":"","firstName":"Yasuki","middleName":"","lastName":"Higashimura","suffix":""},{"id":427975280,"identity":"400541dc-3013-4bc6-b85d-0c1df63c8559","order_by":9,"name":"Ohue-Kitano Ryuji","email":"","orcid":"","institution":"Kindai University","correspondingAuthor":false,"prefix":"","firstName":"Ohue-Kitano","middleName":"","lastName":"Ryuji","suffix":""},{"id":427975281,"identity":"0da7305d-71d9-4a82-a5ed-9542edfb2060","order_by":10,"name":"Ikuo Kimura","email":"","orcid":"","institution":"Kyoto University","correspondingAuthor":false,"prefix":"","firstName":"Ikuo","middleName":"","lastName":"Kimura","suffix":""},{"id":427975282,"identity":"71784822-273b-4a11-8ad5-cc109bec4bd1","order_by":11,"name":"Ken Inoue","email":"","orcid":"","institution":"Kyoto Prefectural University of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Ken","middleName":"","lastName":"Inoue","suffix":""},{"id":427975283,"identity":"ec491b74-5c43-4414-97d1-1f83d0467736","order_by":12,"name":"Kazuhiko Uchiyama","email":"","orcid":"","institution":"Kyoto Prefectural University of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Kazuhiko","middleName":"","lastName":"Uchiyama","suffix":""},{"id":427975284,"identity":"52b18f02-de52-4b3d-a6ff-d05e07d3dff0","order_by":13,"name":"Shu Shimamoto","email":"","orcid":"","institution":"Daicel Corporation, R\u0026D Headquarters","correspondingAuthor":false,"prefix":"","firstName":"Shu","middleName":"","lastName":"Shimamoto","suffix":""},{"id":427975285,"identity":"6709c3bd-d77c-4a53-8e3c-fad96259114c","order_by":14,"name":"Yuichi Ukawa","email":"","orcid":"","institution":"Daicel Corporation, R\u0026D Headquarters","correspondingAuthor":false,"prefix":"","firstName":"Yuichi","middleName":"","lastName":"Ukawa","suffix":""},{"id":427975286,"identity":"3cbf091a-099d-4b9b-bd5e-4c7deae57a77","order_by":15,"name":"Akiko Kohara","email":"","orcid":"","institution":"Daicel Corporation","correspondingAuthor":false,"prefix":"","firstName":"Akiko","middleName":"","lastName":"Kohara","suffix":""},{"id":427975287,"identity":"1ebc4668-360f-4853-8ff1-9fef3dfb3884","order_by":16,"name":"Masatake Kudoh","email":"","orcid":"","institution":"Daicel Corporation","correspondingAuthor":false,"prefix":"","firstName":"Masatake","middleName":"","lastName":"Kudoh","suffix":""},{"id":427975288,"identity":"d2f1e844-7d6d-4a3f-bc4e-77dd79867f03","order_by":17,"name":"Yuji Naito","email":"","orcid":"","institution":"Kyoto Prefectural University of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Yuji","middleName":"","lastName":"Naito","suffix":""},{"id":427975289,"identity":"4dd2c348-7207-4451-ad03-15de6be8323d","order_by":18,"name":"Yoshito Itoh","email":"","orcid":"","institution":"Kyoto Prefectural University of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Yoshito","middleName":"","lastName":"Itoh","suffix":""}],"badges":[],"createdAt":"2025-02-08 02:38:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5984591/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5984591/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41538-025-00505-9","type":"published","date":"2025-07-02T15:57:05+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":78435532,"identity":"e777093c-8b48-4c02-8dc9-9edf48d6ff68","added_by":"auto","created_at":"2025-03-13 08:03:25","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":318598,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eStudy design and changes in body weight and dietary intake. (a) \u003c/strong\u003eSchema of the research. (\u003cstrong\u003eb)\u003c/strong\u003e Changes in body weight. (\u003cstrong\u003ec)\u003c/strong\u003e Body size appearance at 16 weeks of age. (\u003cstrong\u003ed)\u003c/strong\u003e Changes in oral intake during the observation period. (\u003cstrong\u003ee)\u003c/strong\u003eDaily food intake during the observation period. Error bars represent SEM. *\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, **\u003cem\u003e p\u003c/em\u003e \u0026lt; 0.01, ***\u003cem\u003e p\u003c/em\u003e \u0026lt; 0.001, as determined using one-way analysis of variance (ANOVA).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5984591/v1/f2252d21dc476efefdb399c6.png"},{"id":78435085,"identity":"0c303397-2c5c-4262-b4a1-8ad9e74f5d81","added_by":"auto","created_at":"2025-03-13 07:55:25","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":125167,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eBlood glucose and serum insulin levels. (a)\u003c/strong\u003e Causal blood glucose levels (n = 7). (\u003cstrong\u003eb)\u003c/strong\u003eGlucose tolerance test (blood glucose level). (\u003cstrong\u003ec)\u003c/strong\u003e Area under the curve analysis in the oral glucose tolerance test. (\u003cstrong\u003ed)\u003c/strong\u003e Glucose tolerance test (serum insulinlevel). (\u003cstrong\u003ee)\u003c/strong\u003e Fasting serum insulin levels. (\u003cstrong\u003ef)\u003c/strong\u003eHOMA-IR; (\u003cem\u003efasting blood glucose\u003c/em\u003e) × (\u003cem\u003efasting insulin \u003c/em\u003e)⁄22.5. Error bars represent SEM. * p \u0026lt; 0.05, ** p \u0026lt; 0.01, *** p \u0026lt; 0.001, as determined using one-way ANOVA.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5984591/v1/632bf64250680665e6ba3d62.png"},{"id":78435087,"identity":"576bf543-2db5-4254-8edd-adf138de9023","added_by":"auto","created_at":"2025-03-13 07:55:25","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":516914,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFatty liver, weight of adipose tissue and skeletal muscle, and grip strength of mice. (a)\u003c/strong\u003eRepresentative image of the macroscopic and histological findings in the liver. (\u003cstrong\u003eb) \u003c/strong\u003eRelative liver weight of 16-week-old mice (n = 7). (\u003cstrong\u003ec)\u003c/strong\u003e NAS score in hepatic histological appearance (n = 7). (\u003cstrong\u003ed)\u003c/strong\u003e Relative epididymal fat weight in 16-week-old mice (n = 7). (\u003cstrong\u003ee)\u003c/strong\u003e Relative brown fat weight of 16-week-old mice (n = 7). (\u003cstrong\u003ef)\u003c/strong\u003e Relative plantaris muscle weight of 16-week-old mice (n = 7). (\u003cstrong\u003eg)\u003c/strong\u003e Relative soleus muscle weight of 16-week-old mice (n = 7).\u003cstrong\u003e(h)\u003c/strong\u003e Relative grip strength of 16-week-old mice (n = 7). Error bars represent SEM. *\u003cem\u003e p\u003c/em\u003e \u0026lt; 0.05, **\u003cem\u003e p\u003c/em\u003e \u0026lt; 0.01, ***\u003cem\u003e p\u003c/em\u003e \u0026lt; 0.001, as determined using one-way ANOVA.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5984591/v1/8c43e4cae8d00a94a3376cfa.png"},{"id":78435088,"identity":"c0b85744-c38a-4285-ad0f-ea7a8914c5ba","added_by":"auto","created_at":"2025-03-13 07:55:25","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":68620,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAcetate, propionate, and butyrate concentrations in the cecum, cecum contents, and sera. (a–c)\u003c/strong\u003eAcetate, propionate, and butyrate concentrations in feces. (n = 7). (\u003cstrong\u003ed–f) \u003c/strong\u003eAcetate, propionate, and butyrate concentrations in the cecum. (n = 7). (\u003cstrong\u003eg–i)\u003c/strong\u003e Concentrations of serum acetate, propionate, and butyrate(n = 7). Error bars represent SEM. *\u003cem\u003e p\u003c/em\u003e \u0026lt; 0.05, **\u003cem\u003e p\u003c/em\u003e \u0026lt; 0.01, ***\u003cem\u003e p\u003c/em\u003e \u0026lt; 0.001, as determined using one-way ANOVA.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-5984591/v1/3d9691d5e549f763cdbdc17f.png"},{"id":78435533,"identity":"09c248d5-c5a4-4b02-bc56-40385d935b46","added_by":"auto","created_at":"2025-03-13 08:03:25","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":79129,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eExpression of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eGpr41\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eand \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eGpr43\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e in the colon, and serum GLP-1 and PYY levels. (a–b)\u003c/strong\u003eRelative mRNA expression of \u003cem\u003eGpr41\u003c/em\u003e and \u003cem\u003eGpr43\u003c/em\u003e in the colon normalized to that of \u003cem\u003eGapdh\u003c/em\u003e(n = 7). (\u003cstrong\u003ec–d) \u003c/strong\u003eSerum concentrations of GLP-1 and PYY (n = 7). Error bars represent SEM. *\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, **\u003cem\u003e p\u003c/em\u003e \u0026lt; 0.01, ***\u003cem\u003e p\u003c/em\u003e \u0026lt; 0.001, as determined using one-way ANOVA.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-5984591/v1/bfd96722066bc4668ccfa0f8.png"},{"id":86180708,"identity":"2e33bf0f-42c1-42b9-868a-af453d70f1c7","added_by":"auto","created_at":"2025-07-07 16:22:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2409311,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5984591/v1/2b7b4fe0-440a-4635-9dc6-dd206fede01b.pdf"},{"id":78436911,"identity":"ea4f7e84-6e64-4e97-975f-29918c053519","added_by":"auto","created_at":"2025-03-13 08:11:26","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":244016,"visible":true,"origin":"","legend":"","description":"","filename":"Supplement.docx","url":"https://assets-eu.researchsquare.com/files/rs-5984591/v1/51cbb1d495baa03ae65ce683.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Water-soluble cellulose acetate attenuates glucose intolerance through GLP-1 and PYY signal upregulation","fulltext":[{"header":"Introduction","content":"\u003cp\u003eDiabetes mellitus is a chronic metabolic disease with a globally increasing prevalence every year, making it a major global health issue\u003csup\u003e1\u003c/sup\u003e. In addition to affecting quality of life, diabetes significantly increases the risk of complications and affects patient prognosis\u003csup\u003e2\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eRecent systematic research has shown that short-chain fatty acids (SCFAs) such as butyrate, acetate, and propionate contribute to the improvement of blood glucose levels and dyslipidemia in diabetic mouse models, and their application for diabetes treatment is expected\u003csup\u003e3\u003c/sup\u003e. SCFAs are the primary products of the bacterial fermentation of dietary fiber, performed by gut microbes, that positively impact the host. In particular, acetate, the most abundant SCFA, plays an important role in regulating body weight and insulin sensitivity. Hence, potential therapies to increase gut microbial fermentation and acetate production have been extensively investigated\u003csup\u003e4\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eCellulose is a naturally occurring polysaccharide and is usually the main component of plant cell walls. Irrespective of species, approximately 50% of solid cell wall components of wood is cellulose. Hence, cellulose is one of the most abundant global organic resources. However, there are limitations to its utilization related to processing because cellulose is insoluble in water and other simple common organic solvents. One approach to addressing this processing issue of cellulose is chemical modification to make it soluble in water or a common solvent. Among such chemical modifications, an approach that has been widely implemented for decades commercially is cellulose acetylation, chemically turning cellulose into cellulose acetate (CA)\u003csup\u003e5\u003c/sup\u003e. Other chemical modifications of cellulose include, for example, methylation, carboxymethylation, and hydroxypropylation, turning cellulose into methyl cellulose (MC), carboxymethyl cellulose (CMC), and hydroxypropyl cellulose (HPC), respectively. MC, CMC, and HPC are water soluble and have been utilized in the food industry to improve food texture.\u003c/p\u003e \u003cp\u003eOrdinary CA has been utilized industrially for making materials such as dialysis membranes, water treatment membranes, and film components of polarizers for liquid crystal display, after being processed to the required shape using common organic solvents\u003csup\u003e5 6\u003c/sup\u003e. Ordinary CA has not been utilized in the food industry because it lacks water solubility. Although not yet implemented commercially, water-soluble CA is achieved by controlling the degree of chemical modification (degree of acetylation) within a certain range. For cellulose, the degree of acetylation necessary to make it water soluble is roughly 15\u0026ndash;30%, based on the hydroxyl groups available for acetylation, whereas that for ordinary CA is 80\u0026ndash;95% \u003csup\u003e7\u003c/sup\u003e. Water-soluble CA with a degree of acetylation of 15\u0026ndash;30% is sometimes called WSCA. WSCA, owing to its water solubility, could serve as a food additive. When hydrolyzed, WSCA leads to naturally occurring cellulose and acetate. The degradation of WSCA by enzyme systems (naturally occurring enzyme cocktails) expressed in wood cellulolytic fungus systems is well-studied\u003csup\u003e8\u003c/sup\u003e. These enzyme systems usually include acetyl esterases for naturally occurring acetylated polysaccharides such as xylan; these are also capable of hydrolyzing the acetyl groups in WSCA liberating acetate as a result.\u003c/p\u003e \u003cp\u003eWSCA administration was found to increase acetate concentration in human feces and rat cecum contents\u003csup\u003e9 10\u003c/sup\u003e. Therefore, WSCA may act as a prebiotic to modulate host nutritional physiology by increasing the acetate concentration in the intestinal tract of monogastric animals. However, the effects of WSCA on various diseases remain unclear. In this study, we aimed to investigate the effects of WSCA in treating glucose intolerance and body weight control in a mouse model of diabetes mellitus.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003eWSCA suppressed weight gain, especially in db/db mice\u003c/h2\u003e\n \u003cp\u003eFigure \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ea shows the protocol of the current experiment. The mice on the control diet gained weight, whereas those fed the WSCA diet did not. Significant differences in body weight were observed between the groups, with more pronounced differences in the db/db mice (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eb). WSCA intake suppressed a tendency towards obesity (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ec). Figure \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ed shows the weekly changes in oral food intake. The amount of food consumed during the acclimatization period was attributed the value of 1.0. (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ed). The total amount of food consumed per mouse during the 8-week experiment period is shown in Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ee. No evident difference in food intake was observed in the db/m group; however, the db/db WSCA group consumed significantly less food than the db/db control group.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eWSCA normalized blood glucose levels\u003c/h3\u003e\n\u003cp\u003eThe db/db control group showed a trend toward elevation of blood glucose levels, whereas the db/db WSCA group showed normalization of blood glucose levels (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ea). In the glucose tolerance test, the WSCA group showed a lower blood glucose level at 120 min (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eb) and lower area under the curves (AUCs) in the oral glucose tolerance test (OGTT) than the control group (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ec) in db/m and db/db mice. Insulin levels (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ed), fasting insulin levels (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ee), and homeostatic model assessment for insulin resistance (HOMA-IR) (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ef) were measured simultaneously in the glucose tolerance test. The db/db WSCA group maintained additional insulin secretory capacity and normalized blood glucose levels. In addition, insulin resistance tended to improve in the db/db WSCA group, although the difference was not significant.\u003c/p\u003e\n\u003ch3\u003eWSCA improved liver injury and lipid metabolism\u003c/h3\u003e\n\u003cp\u003eThe biochemistry test results revealed that aspartate aminotransferase (AST), total cholesterol, and glycated albumin levels in the db/db WSCA group were significantly lower than those in the db/db control group (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eWSCA improved fatty liver and maintained muscle mass or grip strength\u003c/h3\u003e\n\u003cp\u003eThe macroscopic appearance and microscopic findings of the liver showed apparent differences in the size and percentage of fat droplets between the db/db control and db/db WSCA groups (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ea). Liver weight was significantly lower in the db/db WSCA group than in the db/db control group (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eb). NAS score, which indicates the histological severity of fatty liver\u003csup\u003e11\u003c/sup\u003e, was significantly lower in the db/db WSCA group than in the db/db control group (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ec). No differences in epididymal or brown fat content were observed (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ed and \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ee). While the db/m WSCA and db/db WSCA groups showed reduction in body weight as shown in Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eb, the plantaris or soleus muscle weight or grip strength did not decrease following WSCA administration (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ef, g, and \u003cstrong\u003eh\u003c/strong\u003e).\u003c/p\u003e\n\u003ch3\u003eWSCA increased the concentration of acetate in stool, cecum contents, and sera\u003c/h3\u003e\n\u003cp\u003eThe concentration of acetate significantly increased in the feces, cecum contents, and blood of db/m and db/db mice in the WSCA group compared with that in the control group (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003ea, d, j). The concentration of propionate significantly increased in the feces of db/m mice in the WSCA group and showed a non-significant but increasing trend in db/db mice in the WSCA group (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eb). Regarding the concentration of propionate and butyrate in cecum contents, there was a rising trend in db/m and db/db mice in the WSCA groups (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003ee, f).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExpression of\u003c/strong\u003e \u003cstrong\u003eGpr41\u003c/strong\u003e \u003cstrong\u003eand\u003c/strong\u003e \u003cstrong\u003eGpr43\u003c/strong\u003e \u003cstrong\u003ein the colon did not differ between the db/db control group and the db/db WSCA group\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe relative mRNA expression of \u003cem\u003eGpr41\u003c/em\u003e and \u003cem\u003eGpr43\u003c/em\u003e in the colonic mucosa (normalized to the expression of actin) did not significantly differ between the db/db control and db/db WSCA groups (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003ea, b).\u003c/p\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003eGlucagon-like peptide-1 (GLP-1) and peptide YY (PYY) levels in the sera increased after WSCA administration\u003c/h2\u003e\n \u003cp\u003eSerum GLP-1 and PYY levels in db/m and db/db mice in the WSCA group were significantly higher than those in the control group (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003ec, d).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis is the first study to show that WSCA improves obesity and glucose intolerance in a mouse model of diabetes mellitus. The db/db mice develop diabetes due to overeating caused by their abnormal leptin receptors\u003csup\u003e12\u003c/sup\u003e. WSCA suppressed overeating and normalized body weight in db/db mice. In addition, glucose intolerance, dyslipidemia, and fatty liver observed in db/db mice improved following WSCA intake. The importance of regulating appetite in the treatment of diabetes and obesity caused by overeating has been attracting attention.\u003c/p\u003e \u003cp\u003eOne of the most researched topics in this context is acetate role \u0026ndash; a major SCFA. It has been shown that acetate in the large intestine is absorbed into the bloodstream, crosses the blood-brain barrier, and is directly involved in appetite regulation in the central nervous system, mainly in the hypothalamus\u003csup\u003e13\u003c/sup\u003e. It is also known that acetate in the large intestine promotes the secretion of anorectic hormones such as PYY and GLP-1 from large intestinal L cells and leptin from adipocytes via GPR41 and GPR43 expressed in the intestinal epithelium\u003csup\u003e14\u003c/sup\u003e. It has been well known that GPRs are expressed in various tissues and influence many important metabolic mechanisms that maintain energy homeostasis. In particular, GPR41 and GPR43 can be activated by SCFAs and have been targeted in therapeutic strategies for the treatment of metabolic disorders including \u003csup\u003e15 16\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAs such, it is known that acetate regulates appetite not only via central nervous system but also through gastrointestinal hormones. In the present study, it was found that WSCA increased the concentration of acetate in the intestinal tract and increased serum GLP-1 and PYY. In addition, since an increase in serum acetate concentration was also observed following WSCA intake, it is expected that the central nervous system's appetite control mechanism was also implicated, resulting in the normalization of the amount of food intake in db/db mice.\u003c/p\u003e \u003cp\u003eThe WSCA examined in this study has the potential to be used as a food additive given its physical properties\u003csup\u003e8\u003c/sup\u003e. Although the involved enzyme systems have not been fully elucidated, the metabolism of WSCA in the digestive systems of ruminants and rodents was investigated. Watabe et al. reported through that WSCA is metabolized by ruminal bacteria cultures in vitro to generate acetate while increasing the proportion of the genus Prevotella in cultures\u003csup\u003e17\u003c/sup\u003e. Genda et al. reported that acetate, succinate, and propionate are increased in the cecum of rats fed with WSCA while increasing the proportion of Bacteroides xylanisolvens belonging to the order Bacteroidales in gut microbiome\u003csup\u003e10\u003c/sup\u003e. Strobel reported that Prevotella ruminicola belonging to the Bacteroidales order is capable of metabolizing succinate to propionate\u003csup\u003e18\u003c/sup\u003e. Taken together, the evidence by Genda and Strobel suggests that WSCA is metabolized to propionate in the gut of rats by bacteria such as those belonging to the order Bacteroidales via a pathway involving cellulose, glucose, phosphoenol pyruvate (PEP), and succinate. In other words, propionate generation from WSCA in the gut of rats suggests that WSCA is subject to enzymatic hydrolysis in the gut to regenerate cellulose. Although we have not analyzed the intestinal bacteria involved in this study, we confirmed the increase in propionate as well as acetate in the feces and cecum contents, and our results were consistent with Genda\u0026rsquo;s and Strobel\u0026rsquo;s findings. The results of this study suggest that acetate is mainly involved, but propionate may also be involved.\u003c/p\u003e \u003cp\u003eWSCA metabolism was also investigated from human stool cultures. Yamada et al. reported that WSCA is metabolized to acetate and propionate in human stool cultures while increasing Bacteroides uniformis, and that Bacteroides uniformis can grow in pure cultures supplemented with WSCA\u003csup\u003e9\u003c/sup\u003e. It has also been reported that gamma‑aminobutyric acid (GABA) is increased in human stool cultures supplemented with WSCA presumably by the contribution of Bacteroides uniformis\u003csup\u003e19\u003c/sup\u003e. Rodent trials also suggested that WSCA might be beneficial to gut immunity\u003csup\u003e20\u003c/sup\u003e, cholesterolhemia\u003csup\u003e10\u003c/sup\u003e, and moderate bodyweight gain\u003csup\u003e10\u003c/sup\u003e, in line with our findings.\u003c/p\u003e \u003cp\u003eIn conclusion, WSCA contributes to host health by increasing the concentration of acetate in the large intestine in diabetic mice. Previous systematic search has shown that SCFAs such as butyrate, acetate, and propionate contribute to the improvements in blood glucose levels and dyslipidemia in diabetic mice models; thus, their application for the treatment of diabetes is expected\u003csup\u003e3\u003c/sup\u003e. In the future, it is expected that the safety of WSCA for humans will be verified and its potential application for the prevention and treatment of diabetes will be explored.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eAnimals\u003c/h2\u003e \u003cp\u003eSeven-week-old male C57BLS/J lar- m+/+Lepr db (heterozygous, db/m) and C57BLKS/J lar- +Lepr db/+Lepr db (homozygous, db/db) mice were obtained from Shimizu Laboratory Supplies (Kyoto, Japan). The mice were maintained at 40\u0026ndash;70% relative humidity, 18\u0026ndash;24\u0026deg;C, and a 12-h light/dark cycle. They were allowed free access to water and food for 1 week during the acclimation period. Experiments were conducted in accordance with the guidelines of the National Institute of Health for the use of animals in research. The Kyoto Prefectural University of Medicine Animal Care Committee approved all experimental protocols (permission numbers M2023-41).\u003c/p\u003e \u003cp\u003eFor 8 weeks, the mice were fed either a control diet (control diet; AIN-93G, 361.2 kcal/100 g, fat kcal 7.0% soybean oil, cellulose 5%/w; Oriental Bio Service, Kyoto, Japan) or a modified AIN-93G rodent diet in which 1% cellulose was replaced with WSCA (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The WSCA used in this experiment was provided by Daicel Corporation (Osaka, Japan), and its properties are shown in Supplementary Fig.\u0026nbsp;1. Oriental Bio Service mixed WSCA with AIN-93G to create a solid rodent food upon our request. Twenty-eight db/m and db/db mice were assigned to four groups: (1) db/m control, (2) db/m WSCA, (3) db/db control, and (4) db/db WSCA. The cages used were 320 mm long, 220 mm wide, and 135 mm high, and 3\u0026thinsp;\u0026minus;\u0026thinsp;4 mice were assigned to each cage. The amount of food intake in each group was measured at the same time each week and the food was replaced with fresh food for 9 weeks. At 15 weeks of age, all the mice were sacrificed under isoflurane anesthesia after 16 h of overnight fasting (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eAnalytical procedure for blood glucose level estimation and OGTT\u003c/h2\u003e \u003cp\u003eBlood was drawn from the tail vein and blood glucose levels were measured using a glucometer (Glutest Mint; Sanwa Kagaku Kenkyusho, Nagoya, Japan) at the same time each week. The OGTT was performed after 16 h of fasting, and 1 g glucose per kilogram of body weight was administered orally by needle feeding at 15 weeks of age. Blood glucose levels were measured before and 30, 60, and 120 min after administration. The AUC in the OGTT was analyzed.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eMeasurement of grip strength\u003c/h2\u003e \u003cp\u003eThe grip strength of 15-week-old mice was measured using a strain gauge (GPM-100; Melquest, Toyama, Japan). Grip strength measurements were taken 10 consecutive times at 1-min intervals over 2 days, and the investigators were blinded to the experimental conditions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eBiochemistry\u003c/h2\u003e \u003cp\u003eBlood samples were taken from fasted mice and serum samples were collected after centrifugation at 900g for 15 min at 17\u0026deg;C. The level of AST and alanine aminotransferase were measured using a standardization support method of the Japanese Society for Clinical Chemistry\u003csup\u003e21\u003c/sup\u003e. The levels of total cholesterol\u003csup\u003e22\u003c/sup\u003e, triglycerides\u003csup\u003e23\u003c/sup\u003e, and non-esterified fatty acids\u003csup\u003e24\u003c/sup\u003e were measured using the enzymatic method of FUJIFILM Wako Pure Chemical Corporation (Osaka, Japan). Low-density lipoprotein cholesterol\u003csup\u003e25\u003c/sup\u003e levels were measured directly by Sekisui Medical (Tokyo, Japan). Glycated albumin level was measured using the enzymatic and BCG methods by Asahi Kasei Pharma (Tokyo, Japan) and FUJIFILM Wako Pure Chemical Corporation (Osaka, Japan).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eLiver histology\u003c/h2\u003e \u003cp\u003eThe livers of the sacrificed mice were fixed in 10% buffered formaldehyde and embedded in paraffin. Sections were prepared and stained with hematoxylin and eosin (HE). To evaluate fatty liver, microscopic observations were performed at 40\u0026times; and 200\u0026times; and evaluated according to the NAS score\u003csup\u003e26\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eMeasurement of organ weights\u003c/h2\u003e \u003cp\u003eThe livers, epididymal fat, brown fat, and plantaris and soleus muscles of the mice were removed immediately after they were sacrificed. The weight of each organ per unit of body weight during dissection was evaluated.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eMeasurement of SCFA levels in the feces and cecum contents\u003c/h2\u003e \u003cp\u003eA portion of the fecal or cecal content was collected, weighed, and suspended in perchloric acid (0.5 mL) to remove the protein. After centrifugation at 10,000 \u0026times; \u003cem\u003eg\u003c/em\u003e for 5 min at 4\u0026deg;C, the resulting supernatant was filtered through a cellulose acetate membrane filter with a pore size of 0.45 \u0026micro;m. Organic acid content was analyzed using ion-exclusion high-performance liquid chromatography. The amounts of organic acid substances per unit weight of feces and cecum were measured\u003csup\u003e27\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eMeasurement of SCFA levels in sera\u003c/h2\u003e \u003cp\u003eSerum contents were immediately added to 5-sulfosalicylic acid, followed by vortexing for 1 min. The samples were centrifuged at 15,000 \u0026times; \u003cem\u003eg\u003c/em\u003e for 15 min and the supernatant was collected. The supernatant was mixed with 2-ethylbutyric acid (internal control), hydrochloric acid, and diethyl ether and vortexed for 1 min. The samples were centrifuged at 3,000 \u0026times; \u003cem\u003eg\u003c/em\u003e for 5 min, and the SCFA-containing ether layers were collected and pooled for gas chromatography-mass spectrometry analysis using a GCMS-QP2010 Ultra instrument (Shimadzu). The VF-WAXms (30 m \u0026times; 0.25 mm internal diameter \u0026times; 1 \u0026micro;m; Agilent Technologies) was used for chromatographic separation. Helium (0.92 mL/min) was used as the carrier gas. The mass spectrometer was set to scan mode from m/z 40\u0026thinsp;\u0026minus;\u0026thinsp;130 and to the selected ion monitoring mode at m/z 60 (retention time: 9.6) for acetate, m/z 74 (retention time: 10.7) for propionate, and m/z 60 (retention time: 12.5) for n-butyrate. The concentration of SCFAs in each sample was determined using an external standard calibration curve over a specified concentration range\u003csup\u003e27\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eGene expression analysis in murine colons\u003c/h2\u003e \u003cp\u003eTotal RNA was isolated using the acid guanidinium phenol-chloroform method with TRIzol reagent (Thermo Fisher Scientific USA), according to the manufacturer\u0026rsquo;s instructions as previously described\u003csup\u003e28\u003c/sup\u003e. The resultant cDNA was used for quantitative reverse transcription polymerase chain reaction (qRT-PCR) using specific primers: GPCR41, 5\u0026prime;-TGGCTTTTCTTTTCCGTCTACCT-3\u0026prime; and antisense 5\u0026prime;-AAGACCACCAGGGCCATCA-3\u0026prime;; GPCR43, 5\u0026prime;-GATGTGGTACTGCCCGTACGA-3\u0026prime; and antisense 5\u0026prime;-GACTGCCATGGGAACGAAAA-3\u0026prime;; actin, 5\u0026prime;-TATCCACCTTCCAGCAGATGT-3\u0026prime; and antisense 5\u0026prime;-AGCTCAGTAACAGTCCGCCTA-3\u0026prime;. PCR was performed using PowerUp SYBR Green PCR master mix and QuantStudio 6 Pro real-time PCR system (Thermo Fisher Scientific). The PCR conditions included 40 cycles at 95\u0026deg;C for 15 s and primer annealing at 60\u0026deg;C for 1 min, with a subsequent melting curve analysis in which the temperature was increased from 60\u0026deg;C to 95\u0026deg;C. Gene expression levels were calculated from the quantitative reverse transcription-PCR data and normalized to actin expression.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eMeasurement of serum GLP-1 and PYY levels\u003c/h2\u003e \u003cp\u003eSerum samples were collected from the sacrificed mice and processed as described in the \u0026ldquo;Biochemistry\u0026rdquo; section. Serum GLP-1 and PYY levels were quantified using a GLP-1 enzyme-linked immunosorbent assay (ELISA) kit (FUJIFILM Wako Pure Chemical Corporation) and a PYY ELISA kit (FUJIFILM Wako Pure Chemical Corporation).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eAnalysis of variance (ANOVA) was performed to assess the trend of the mean stratified according to normally distributed continuous variables. All analyses were performed using JMP PRO version 14.0.0 (SAS Institute Japan Ltd). Differences were considered statistically significant at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":" \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eData availability statement\u003c/h2\u003e \u003cp\u003eThe datasets analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eCode availability statement\u003c/h2\u003e \u003cp\u003eThere are no computer codes or scripts that should be reported in this report.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e\u003cp\u003e \u003ch2\u003eCompeting interest statement\u003c/h2\u003e \u003cp\u003eAll authors declare no financial or non-financial competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis work was supported by a Grant-in-Aid for Scientific Research (KAKENHI) (C) from the Japanese Society for the Promotion of Science (grant number: 24K11092, awarded to Tomohisa Takagi).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eKA and TT contributed substantially to this study. KA, TT, ME, HH, TY, MK, TS, YH, KI, KU, SS, and YU contributed to the data analysis and interpretation. KA, TT, KM, KU, SS, and YU drafted the manuscript. YN and YI critically revised the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eThis work was partially supported by Taiyo Kagaku Co., Ltd. We thank all the members of the Department of Molecular Gastroenterology and Hepatology, Kyoto Prefectural University of Medicine, and Graduate School of Medical Science, Kyoto Prefectural University of Medicine for their help with this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003e Sun, H. et al. IDF Diabetes Atlas: Global, regional and country-level diabetes prevalence estimates for 2021 and projections for 2045. \u003cem\u003eDiabetes Res Clin Pract\u003c/em\u003e \u003cb\u003e183\u003c/b\u003e, 109119 (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Chan, J. C. N. et al. The Lancet Commission on diabetes: using data to transform diabetes care and patient lives. \u003cem\u003eLancet\u003c/em\u003e \u003cb\u003e396\u003c/b\u003e, 2019\u0026ndash;2082 (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Zheng, J. et al. Effects of short-chain fatty acids on blood glucose and lipid levels in mouse models of diabetes mellitus: A systematic review and network meta-analysis. \u003cem\u003ePharmacol Res\u003c/em\u003e \u003cb\u003e199\u003c/b\u003e, 107041 (2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Hernandez, M. A. G., Canfora, E. E., Jocken, J. W. E. \u0026amp; Blaak, E. E. The Short-Chain Fatty Acid Acetate in Body Weight Control and Insulin Sensitivity. \u003cem\u003eNutrients\u003c/em\u003e \u003cb\u003e11\u003c/b\u003e (2019).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Sata, H., Murayama, M. \u0026amp; Shimamoto, S. 5.4 Properties and applications of cellulose triacetate film. \u003cem\u003eMacromolecular Symposia\u003c/em\u003e \u003cb\u003e208\u003c/b\u003e, 323\u0026ndash;334 (2004).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Shibata, T., Shu, S. \u0026amp; Okura, H. Interaction of Cellulose with Organic Molecules andthe Functionality Derived from it. \u003cem\u003eJournal of The Adhesion Society of Japan\u003c/em\u003e \u003cb\u003e54\u003c/b\u003e, 150\u0026ndash;157 (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Maim, C. J., Barkey, K. T., Salo, M. \u0026amp; May, D. C. CELLULOSE DERIVATIVES - Far-Hydrolyzed Cellulose Acetates. \u003cem\u003eIndustrial \u0026amp; Engineering Chemistry\u003c/em\u003e \u003cb\u003e49\u003c/b\u003e, 79\u0026ndash;83 (1957).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Puls, J., Altaner, C. \u0026amp; Saake, B. 4.3 Degradation and modification of cellulose acetates by biological systems. \u003cem\u003eMacromolecular Symposia - MACROMOL SYMPOSIA\u003c/em\u003e \u003cb\u003e208\u003c/b\u003e, 239\u0026ndash;254 (2004).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Yamada, H. et al. Chemical and microbial characterization for fermentation of water-soluble cellulose acetate in human stool cultures. \u003cem\u003eJ Sci Food Agric\u003c/em\u003e \u003cb\u003e101\u003c/b\u003e, 2950\u0026ndash;2960 (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Genda, T. et al. Bacterial Fermentation of Water-Soluble Cellulose Acetate Raises Large-Bowel Acetate and Propionate and Decreases Plasma Cholesterol Concentrations in Rats. \u003cem\u003eJ Agric Food Chem\u003c/em\u003e \u003cb\u003e66\u003c/b\u003e, 11909\u0026ndash;11916 (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Kleiner, D. E. et al. Design and validation of a histological scoring system for nonalcoholic fatty liver disease. \u003cem\u003eHepatology\u003c/em\u003e \u003cb\u003e41\u003c/b\u003e, 1313\u0026ndash;1321 (2005).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Chen, H. et al. Evidence that the diabetes gene encodes the leptin receptor: identification of a mutation in the leptin receptor gene in db/db mice. \u003cem\u003eCell\u003c/em\u003e \u003cb\u003e84\u003c/b\u003e, 491\u0026ndash;495 (1996).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Frost, G. et al. The short-chain fatty acid acetate reduces appetite via a central homeostatic mechanism. \u003cem\u003eNat Commun\u003c/em\u003e \u003cb\u003e5\u003c/b\u003e, 3611 (2014).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Chambers, E. S., Morrison, D. J. \u0026amp; Frost, G. Control of appetite and energy intake by SCFA: what are the potential underlying mechanisms? \u003cem\u003eProc Nutr Soc\u003c/em\u003e \u003cb\u003e74\u003c/b\u003e, 328\u0026ndash;336 (2015).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Hara, T., Kimura, I., Inoue, D., Ichimura, A. \u0026amp; Hirasawa, A. Free fatty acid receptors and their role in regulation of energy metabolism. \u003cem\u003eRev Physiol Biochem Pharmacol\u003c/em\u003e \u003cb\u003e164\u003c/b\u003e, 77\u0026ndash;116 (2013).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Kimura, I., Ichimura, A., Ohue-Kitano, R. \u0026amp; Igarashi, M. Free Fatty Acid Receptors in Health and Disease. \u003cem\u003ePhysiol Rev\u003c/em\u003e \u003cb\u003e100\u003c/b\u003e, 171\u0026ndash;210 (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Watabe, Y., Suzuki, Y., Koike, S., Shimamoto, S. \u0026amp; Kobayashi, Y. Cellulose acetate, a new candidate feed supplement for ruminant animals: In vitro evaluations. \u003cem\u003eJ Dairy Sci\u003c/em\u003e \u003cb\u003e101\u003c/b\u003e, 10929\u0026ndash;10938 (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Strobel, H. J. Vitamin B12-dependent propionate production by the ruminal bacterium Prevotella ruminicola 23. \u003cem\u003eAppl Environ Microbiol\u003c/em\u003e \u003cb\u003e58\u003c/b\u003e, 2331\u0026ndash;2333 (1992).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Yamada, H. et al. In vitro Effects of Cellulose Acetate on Fermentation Profiles, the Microbiome, and Gamma-aminobutyric Acid Production in Human Stool Cultures. \u003cem\u003eCurr Microbiol\u003c/em\u003e \u003cb\u003e80\u003c/b\u003e, 284 (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Takeuchi, T. et al. Acetate differentially regulates IgA reactivity to commensal bacteria. \u003cem\u003eNature\u003c/em\u003e \u003cb\u003e595\u003c/b\u003e, 560\u0026ndash;564 (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Kotani, K., Maekawa, M. \u0026amp; Kanno, T. [Reestimation of aspartate aminotransferase (AST)/alanine aminotransferase (ALT) ratio based on JSCC consensus method\u0026ndash;changes of criteria for a differential diagnosis of hepatic disorders following the alteration from Karmen method to JSCC method]. \u003cem\u003eNihon Shokakibyo Gakkai Zasshi\u003c/em\u003e \u003cb\u003e91\u003c/b\u003e, 154\u0026ndash;161 (1994).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Allain, C. C., Poon, L. S., Chan, C. S., Richmond, W. \u0026amp; Fu, P. C. Enzymatic determination of total serum cholesterol. \u003cem\u003eClin Chem\u003c/em\u003e \u003cb\u003e20\u003c/b\u003e, 470\u0026ndash;475 (1974).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e McGowan, M. W., Artiss, J. D., Strandbergh, D. R. \u0026amp; Zak, B. A peroxidase-coupled method for the colorimetric determination of serum triglycerides. \u003cem\u003eClin Chem\u003c/em\u003e \u003cb\u003e29\u003c/b\u003e, 538\u0026ndash;542 (1983).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Christmass, M. A., Mitoulas, L. R., Hartmann, P. E. \u0026amp; Arthur, P. G. A semiautomated enzymatic method for determination of nonesterified fatty acid concentration in milk and plasma. \u003cem\u003eLipids\u003c/em\u003e \u003cb\u003e33\u003c/b\u003e, 1043\u0026ndash;1049 (1998).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Friedewald, W. T., Levy, R. I. \u0026amp; Fredrickson, D. S. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. \u003cem\u003eClin Chem\u003c/em\u003e \u003cb\u003e18\u003c/b\u003e, 499\u0026ndash;502 (1972).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Kleiner, D. E. et al. Design and validation of a histological scoring system for nonalcoholic fatty liver disease. \u003cem\u003eHepatology\u003c/em\u003e \u003cb\u003e41\u003c/b\u003e, 1313\u0026ndash;1321 (2005).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Miyamoto, J. et al. Ketone body receptor GPR43 regulates lipid metabolism under ketogenic conditions. \u003cem\u003eProc Natl Acad Sci U S A\u003c/em\u003e \u003cb\u003e116\u003c/b\u003e, 23813\u0026ndash;23821 (2019).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Kajiwara-Kubota, M. et al. Partially hydrolyzed guar gum increased colonic mucus layer in mice via succinate-mediated MUC2 production. \u003cem\u003eNPJ Sci Food\u003c/em\u003e \u003cb\u003e7\u003c/b\u003e, 10 (2023).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1. Serum biochemistry results in db/m and db/db mice\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cimg src=\"data:image/png;base64,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\"\u003e\u003cstrong\u003e\u003cbr\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. Composition of the test diets (%)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cimg src=\"data:image/png;base64,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\"\u003e\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"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":"npj-science-of-food","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"npjscifood","sideBox":"Learn more about [npj Science of Food](http://www.nature.com/npjscifood/)","snPcode":"41538","submissionUrl":"https://submission.springernature.com/new-submission/41538/3","title":"npj Science of Food","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-5984591/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5984591/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eWater-soluble cellulose acetate (WSCA), derived from natural cellulose and acetate, can be used as a food additive and deliver acetate to the large intestine. In this study, we investigated the effects of dietary WSCA supplementation on impaired glucose metabolism in db/db mice, a model of type 2 diabetes mellitus. db/m and db/db mice were fed either a control diet or a WSCA-supplemented diet for eight weeks. The WSCA-supplemented group exhibited improved glucose intolerance or lipid metabolism without any loss of skeletal muscle mass or grip strength. WSCA supplementation significantly increased acetate concentrations in the cecum, stool, and blood. Furthermore, serum levels of glucagon-like peptide-1 (GLP-1) and peptide YY (PYY) were significantly higher in the WSCA group than in the control group. These findings suggest that WSCA delivers acetate to the colon and prevents diabetes by enhancing GLP-1 and PYY secretion in db/db mice.\u003c/p\u003e","manuscriptTitle":"Water-soluble cellulose acetate attenuates glucose intolerance through GLP-1 and PYY signal upregulation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-13 07:55:21","doi":"10.21203/rs.3.rs-5984591/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-05-06T16:58:03+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-30T01:09:52+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-28T08:23:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"323531188679186981841706198756631370966","date":"2025-04-23T11:19:15+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-22T01:56:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"112672994652811348187479449238571994498","date":"2025-04-22T01:01:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"335809862269733834008519165759608385633","date":"2025-04-21T08:40:28+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-15T06:46:42+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"150277726135505530765564351112438455698","date":"2025-04-12T04:45:26+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-07T18:08:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"292804118913517652802690191162867765333","date":"2025-04-06T23:30:51+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-01T09:00:06+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-03-10T17:21:44+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-10T09:29:08+00:00","index":"","fulltext":""},{"type":"submitted","content":"npj Science of Food","date":"2025-02-08T02:33:58+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"npj-science-of-food","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"npjscifood","sideBox":"Learn more about [npj Science of Food](http://www.nature.com/npjscifood/)","snPcode":"41538","submissionUrl":"https://submission.springernature.com/new-submission/41538/3","title":"npj Science of Food","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"33fac672-0e54-45b3-a036-6f3a61fc4faf","owner":[],"postedDate":"March 13th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":45599606,"name":"Biological sciences/Biochemistry"},{"id":45599607,"name":"Health sciences/Endocrinology/Endocrine system and metabolic diseases"}],"tags":[],"updatedAt":"2025-07-07T16:19:05+00:00","versionOfRecord":{"articleIdentity":"rs-5984591","link":"https://doi.org/10.1038/s41538-025-00505-9","journal":{"identity":"npj-science-of-food","isVorOnly":false,"title":"npj Science of Food"},"publishedOn":"2025-07-02 15:57:05","publishedOnDateReadable":"July 2nd, 2025"},"versionCreatedAt":"2025-03-13 07:55:21","video":"","vorDoi":"10.1038/s41538-025-00505-9","vorDoiUrl":"https://doi.org/10.1038/s41538-025-00505-9","workflowStages":[]},"version":"v1","identity":"rs-5984591","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5984591","identity":"rs-5984591","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}