Impact of Cyanidin-3-Glucoside on Gut Microbiota and Relationship with Metabolism and Inflammation in High Fat-High Sucrose Diet-Induced Insulin Resistant Mice

Fei Huang, Ruozhi Zhao, Min Xia, Garry X Shen, Fei Huang, Ruozhi Zhao, Min Xia, Garry X Shen

Abstract

The present study assessed the effects of freeze-dried cyanidin-3-glucoside (C3G), an anthocyanin enriched in dark-red berries, compared to Saskatoon berry powder (SBp) on metabolism, inflammatory markers and gut microbiota in high fat-high sucrose (HFHS) diet-induced insulin-resistant mice. Male C57 BL/6J mice received control, HFHS, HFHS + SBp (8.0 g/kg/day) or HFHS + C3G (7.2 mg/kg/day, equivalent C3G in SBp) diet for 11 weeks. The HFHS diet significantly increased plasma levels of glucose, cholesterol, triglycerides, insulin resistance and inflammatory markers. The HFHS + SBp diet increased the Bacteroidetes/Firmicutes (B/F) ratio and relative abundance of Muriculaceae family bacteria in mouse feces detected using 16S rRNA gene sequencing. The HFHS + SBp or HFHS + C3G diet attenuated glucose, lipids, insulin resistance and inflammatory markers, and increased the B/F ratio and Muriculaceae relative abundance compared to the HFHS diet alone. The relative abundances of Muriculaceae negatively correlated with body weight, glucose, lipids, insulin resistance and inflammatory mediators. Functional predication analysis suggested that the HFHS diet upregulated gut bacteria genes involved in inflammation, and downregulated bacteria involved in metabolism. C3G and SBp partially neutralized HFHS diet-induced alterations of gut bacteria. The results suggest that C3G is a potential prebiotic, mitigating HFHS diet-induced disorders in metabolism, inflammation and gut dysbiosis, and that C3G contributes to the metabolic beneficial effects of SBp.

Keywords: Saskatoon berry; cyanidin-3-glucoside; gut microbiota; high fat-high sucrose diet-induced insulin-resistant mice; inflammation.

Conflict of interest statement

The authors declare that they0 have no competing interests.

Figures

Figure 1
Figure 1
Effects of Cyanidin-3-glucoside (C3G) supplemented in a high fat-high sucrose (HFHS) diet on the body weight and food intake of mice. Male C57 BL/J6 mice (6 weeks of age) were randomized into 4 groups and received the following diets for 11 weeks: control (CTL) group: control diet, HFHS group: HFHS diet, Saskatoon berry powder (SBp) group: SBp (8.0 g/kg/day) supplemented in the HFHS diet, C3G group: C3G (7.2 mg/kg/day) supplemented in the HFHS diet. Body weights and food intake were measured every two weeks up to 10 weeks. (A) Body weights, (B) daily food intake. The values are expressed as mean ± standard deviation (SD) g (n = 8/group). *, **: p < 0.05 or 0.01 HFHS versus CTL group, +, ++: p < 0.05 or 0.01 SBp versus CTL group, ^^: p < 0.01 C3G versus CTL group.
Figure 2
Figure 2
Levels of glucose, cholesterol and triglycerides in plasma of mice fed with HFHS diets supplemented with or without C3G. The dietary regimen was the same as described in the legend of Figure 1. Fasting plasma glucose, cholesterol and triglycerides were measured biochemically using assay kits. Values are expressed as mean ± SD mg/dL (n = 8/group). **: p < 0.01 versus the control (CTL) group; +, ++: p < 0.05 or 0.01 versus the HFHS group.
Figure 3
Figure 3
Effects of HFHS diets supplemented with C3G on insulin and insulin resistance in mice. The experimental regimen was described in the legend of Figure 1. The levels of fasting plasma insulin (ng/mL) were measured at indicated time points (A). Homeostatic model assessment of insulin resistance (HOMA-IR) was calculated according to the levels of glucose and insulin in the same plasma samples (B). Values are expressed as mean ± SD (n = 8/group). **: p < 0.01 versus the control (CTL) group; ++: p < 0.05 or 0.01 versus the HFHS group.
Figure 4
Figure 4
Levels of inflammatory regulators in plasma of mice receiving the HFHS diet supplemented with C3G. The experimental regimen was described in the legend of Figure 1. The levels of monocyte chemotactic protein-1 (MCP-1) and plasminogen activator inhibitor-1 (PAI-1) were analyzed in plasma collected before tissue harvesting using enzyme-linked immunosorbent assay (ELISA) kits for mouse MCP-1 (A) or PAI-1 (B). Values are expressed as mean ± SD ng/mL (n = 8/group). **: p < 0.01 versus the control (CTL) group; ++: p < 0.05 or 0.01 versus the HFHS group.
Figure 5
Figure 5
Effect of the HFHS diet supplemented with C3G on β-diversity of gut microbiota in mice. The experimental regimen was described in the legend of Figure 1. Principle component analysis (PCA) was based on Bray–Curtis dissimilarities between all sample sets (weighted by taxon abundance).
Figure 6
Figure 6
Effects of HFHS diet supplemented with or without the relative abundance of Bacteroidetes and Firmicutes and their ratios. The experimental regimen was described in the legend of Figure 1. (A) Relative abundance (%) of Bacteroidetes in gut microbial composition. (B) Relative abundance (%) of Firmicutes in gut microbial composition. (C) Ratio of Bacteroidetes over Firmicutes (B/F) in gut microbiota. (D) Ratio of Firmicutes over Bacteroidetes (F/B) in gut microbiota. Values are expressed as mean ± SD (%) (n = 8/group). *, **: p < 0.05 or 0.01 versus the control (CTL) group; +, ++: p < 0.05 or 0.01 versus the HFHS group.
Figure 7
Figure 7
Effect of four HFHS (H) diets supplemented with C3G on the relative abundance of gut family bacteria. The experimental regimen was described in the legend of Figure 1. (A) Statistical differences among mice with different diets (analysis of variance (ANOVA) and post-hoc Tukey test), (B) correlation heatmap of relative abundance of gut microbiota on family level with physiological and biochemical parameters, (C) extended error bar plot (STAMP tool) showing difference in mean relative abundance between the SBp (S) group and HFHS group, (D) mean proportion and difference in mean proportion of family bacteria (STAMP tool) between the C3G group and the HFHS group (mean ± SD). ∗: p < 0.05 in overall ANOVA result, ●: p < 0.05 in the HFHS (H) group versus the control (CTL) group (H/CTL), ■: p < 0.05 in the SBp (S) group versus the CTL group (S/CTL), ▲: p < 0.05 in the C3G group versus the CTL group (C3G/CTL), ○: p < 0.05 in the S group versus the H group (S/H), □: p < 0.05 in the C3G group versus the H group (C3G/H), △: p < 0.05 in the C3G group versus the S group (C3G/S). *, **, ***: p < 0.05 or 0.01 or 0.001 in positive (blue) or negative (red) correlations between the abundance of each gut family bacteria and physiological or biochemical variables.
Figure 8
Figure 8
Effects of HFHS diets supplemented with and without C3G on metagenome functional activity in gut microbiota based on the Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt). The experimental regimen was the same as described in legend of Figure 1. Differences in relative abundance (%) in each selected pathway among various dietary groups are in the form of a bar plot. Values are expressed as mean value (n = 8/group). **: p < 0.01, showing ANOVA results among the four groups.

References

    1. Henning R.J. Type-2 diabetes mellitus and cardiovascular disease. Future Cardiol. 2018;14:491–509. doi: 10.2217/fca-2018-0045.
    1. Skyler J.S., Bakris G.L., Bonifacio E., Darsow T., Eckel R.H., Groop L., Groop P.-H., Handelsman Y., Insel R.A., Mathieu C. Differentiation of diabetes by pathophysiology, natural history, and prognosis. Diabetes. 2017;66:241–255. doi: 10.2337/db16-0806.
    1. Bradley B.H.R. Dietary fat and risk for type 2 diabetes: A review of recent research. Cur. Nutr. Rep. 2018;7:214–226. doi: 10.1007/s13668-018-0244-z.
    1. Kopp W. How western diet and lifestyle drive the pandemic of obesity and civilization diseases. Diab. Met. Syn. Obes. Targets Ther. 2019;12:2221. doi: 10.2147/DMSO.S216791.
    1. Sonnenburg J.L., Bäckhed F. Diet–microbiota interactions as moderators of human metabolism. Nature. 2016;535:56–64. doi: 10.1038/nature18846.
    1. Wen L., Duffy A. Factors influencing the gut microbiota, inflammation, and type 2 diabetes. J. Nutr. 2017;147:1468S–1475S. doi: 10.3945/jn.116.240754.
    1. Mazza G. Compositional and functional properties of saskatoon berry and blueberry. Int. J. Fruit. Sci. 2005;5:101–120. doi: 10.1300/J492v05n03_10.
    1. Mazza G. Anthocyanins and Other Phenolic Compounds of Saskatoon Berries Amelanchier alnifolia Nutt. J. Food Sci. 1986;51:1260–1264. doi: 10.1111/j.1365-2621.1986.tb13100.x.
    1. Gould K., Smreciu A., Wood S. Amelanchier Alnifolia: Saskatoon, Service Berry, June Berry, Shadbush, Shadblow, Indian Pear, May Cherry. [(accessed on 13 August 2020)]; Available online: .
    1. Hosseinian F.S., Beta T. Saskatoon and wild blueberries have higher anthocyanin contents than other Manitoba berries. J. Agric. Food Chem. 2007;55:10832–10838. doi: 10.1021/jf072529m.
    1. Zhao R., Le K., Li W., Ren S., Moghadasian M.H., Beta T., Shen G.X. Effects of Saskatoon berry powder on monocyte adhesion to vascular wall of leptin receptor-deficient diabetic mice. J. Nutr. Biochem. 2014;25:851–857. doi: 10.1016/j.jnutbio.2014.03.016.
    1. De Souza D.R., Willems J.L., Low N.H. Phenolic composition and antioxidant activities of saskatoon berry fruit and pomace. Food Chem. 2019;290:168–177. doi: 10.1016/j.foodchem.2019.03.077.
    1. Lachowicz S., Oszmiański J., Seliga Ł., Pluta S. Phytochemical composition and antioxidant capacity of seven saskatoon berry (Amelanchier alnifolia Nutt.) Genotypes Grown in Poland. Molecules. 2017;22:853. doi: 10.3390/molecules22050853.
    1. Zhao R., Xie X., Le K., Li W., Moghadasian M.H., Beta T., Shen G.X. Endoplasmic reticulum stress in diabetic mouse or glycated LDL-treated endothelial cells: Protective effect of Saskatoon berry powder and cyanidin glycans. J. Nutr. Biochem. 2015;26:1248–1253. doi: 10.1016/j.jnutbio.2015.05.015.
    1. Zhao R., Khafipour E., Sepehri S., Huang F., Beta T., Shen G.X. Impact of Saskatoon berry powder on insulin resistance and relationship with intestinal microbiota in high fat–high sucrose diet-induced obese mice. J. Nutr. Biochem. 2019;69:130–138. doi: 10.1016/j.jnutbio.2019.03.023.
    1. Miranda C.L., Johnson L.A., De Montgolfier O., Elias V.D., Ullrich L.S., Hay J.J., Paraiso I.L., Choi J., Reed R.L., Revel J.S. Non-estrogenic xanthohumol derivatives mitigate insulin resistance and cognitive impairment in high-fat diet-induced obese mice. Sci. Rep. 2018;8:1–17. doi: 10.1038/s41598-017-18992-6.
    1. Walters W., Hyde E.R., Berg-Lyons D., Ackermann G., Humphrey G., Parada A., Gilbert J.A., Jansson J.K., Caporaso J.G., Fuhrman J.A. Improved bacterial 16S rRNA gene (V4 and V4–5) and fungal internal transcribed spacer marker gene primers for microbial community surveys. Msystems. 2016;1:e00009–e00015. doi: 10.1128/mSystems.00009-15.
    1. Bolyen E., Rideout J.R., Dillon M.R., Bokulich N.A., Abnet C.C., Al-Ghalith G.A., Alexander H., Alm E.J., Arumugam M., Asnicar F. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat. Biotech. 2019;37:852–857. doi: 10.1038/s41587-019-0209-9.
    1. Langille M.G., Zaneveld J., Caporaso J.G., McDonald D., Knights D., Reyes J.A., Clemente J.C., Burkepile D.E., Thurber R.L.V., Knight R. Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences. Nat. Biotech. 2013;31:814. doi: 10.1038/nbt.2676.
    1. Yamashita Y., Wang L., Nanba F., Ito C., Toda T., Ashida H. Procyanidin promotes translocation of glucose transporter 4 in muscle of mice through activation of insulin and AMPK signaling pathways. PLoS ONE. 2016;11:e0161704. doi: 10.1371/journal.pone.0161704.
    1. Luna-Vital D.A., de Mejia E.G. Anthocyanins from purple corn activate free fatty acid-receptor 1 and glucokinase enhancing in vitro insulin secretion and hepatic glucose uptake. PLoS ONE. 2018;13:e0200449. doi: 10.1371/journal.pone.0200449.
    1. Du C., Shi Y., Ren Y., Wu H., Yao F., Wei J., Wu M., Hou Y., Duan H. Anthocyanins inhibit high-glucose-induced cholesterol accumulation and inflammation by activating LXRα pathway in HK-2 cells. Drug Des. Dev. Ther. 2015;9:5099.
    1. Sun C.-D., Zhang B., Zhang J.-K., Xu C.-J., Wu Y.-L., Li X., Chen K.-S. Cyanidin-3-glucoside-rich extract from Chinese bayberry fruit protects pancreatic β cells and ameliorates hyperglycemia in streptozotocin-induced diabetic mice. J. Med. Food. 2012;15:288–298. doi: 10.1089/jmf.2011.1806.
    1. Xie X., Zhao R., Shen G.X. Influence of delphinidin-3-glucoside on oxidized low-density lipoprotein-induced oxidative stress and apoptosis in cultured endothelial cells. J. Agric. Food Chem. 2012;60:1850–1856. doi: 10.1021/jf204461z.
    1. Chen G., Wang G., Zhu C., Jiang X., Sun J., Tian L., Bai W. Effects of cyanidin-3-O-glucoside on 3-chloro-1, 2-propanediol induced intestinal microbiota dysbiosis in rats. Food Chem. Toxicol. 2019;133:110767. doi: 10.1016/j.fct.2019.110767.
    1. Pradipta I., Kong D., Tan J.B.L. Natural organic antioxidants from green tea form a protective layer to inhibit corrosion of steel reinforcing bars embedded in mortar. Constr. Build. Mater. 2019;221:351–362. doi: 10.1016/j.conbuildmat.2019.06.006.
    1. Chen Y., Li Q., Zhao T., Zhang Z., Mao G., Feng W., Wu X., Yang L. Biotransformation and metabolism of three mulberry anthocyanin monomers by rat gut microflora. Food Chem. 2017;237:887–894. doi: 10.1016/j.foodchem.2017.06.054.
    1. Lagkouvardos I., Lesker T.R., Hitch T.C.A., Gálvez E.J.C., Smit N., Neuhaus K., Wang J., Baines J.F., Abt B., Stecher B., et al. Sequence and cultivation study of Muribaculaceae reveals novel species, host preference, and functional potential of this yet undescribed family. Microbiome. 2019;7:28. doi: 10.1186/s40168-019-0637-2.
    1. Volk J.K., Nyström E.E., van der Post S., Abad B.M., Schroeder B.O., Johansson Å., Svensson F., Jäverfelt S., Johansson M.E., Hansson G.C. The Nlrp6 inflammasome is not required for baseline colonic inner mucus layer formation or function. J. Exp. Med. 2019;216:2602–2618. doi: 10.1084/jem.20190679.
    1. Smith B.J., Miller R.A., Ericsson A.C., Harrison D.C., Strong R., Schmidt T.M. Changes in the gut microbiome and fermentation products concurrent with enhanced longevity in acarbose-treated mice. BMC Microbiol. 2019;19:130. doi: 10.1186/s12866-019-1494-7.
    1. Zhao L., Zhang F., Ding X., Wu G., Lam Y.Y., Wang X., Fu H., Xue X., Lu C., Ma J., et al. Gut bacteria selectively promoted by dietary fibers alleviate type 2 diabetes. Science. 2018;359:1151–1156. doi: 10.1126/science.aao5774.
    1. Zhang L., Xie C., Nichols R.G., Chan S.H., Jiang C., Hao R., Smith P.B., Cai J., Simons M.N., Hatzakis E. Farnesoid X receptor signaling shapes the gut microbiota and controls hepatic lipid metabolism. MSystems. 2016;1:e00016–e00070. doi: 10.1128/mSystems.00070-16.
    1. Petersen C., Wankhade U.D., Bharat D., Wong K., Mueller J.E., Chintapalli S.V., Piccolo B.D., Jalili T., Jia Z., Symons J.D. Dietary supplementation with strawberry induces marked changes in the composition and functional potential of the gut microbiome in diabetic mice. J. Nutr. Biochem. 2019;66:63–69. doi: 10.1016/j.jnutbio.2019.01.004.

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