Objective：
Dietary supplements are widely used in functional foods for its health benefits. However, the efficacy of the combination of red yeast rice, phytosterol ester and lycopene (RPL) in the regulation of glucose and lipid metabolism disorders and obesity hasn’t yet been studied. The aim of this study was to investigate whether supplement of RPL attenuates these metabolism disorders in mice, and whether gut microbiota plays a key role in this process.
Methods：
High-fat/high-cholesterol (HFHC) or normal chow (NC) diet was fed to C57BL/6 male mice for 12 weeks. Simultaneously, treatment with RPL at gradient dose (RPL1, RPL2, and RPL3 representing low, medium and high dose combination of RPL, respectively) or simvastatin (as a positive control) was applied by daily gavage. The mice were assessed by body weight and epididymal fat weight. The glucose and lipid metabolism in mice were evaluated by oral glucose tolerance test and serum lipid levels. 16S rDNA sequencing was performed to characterize the fecal microbial diversity and community composition. Correlations between differential fecal bacteria and phenotypic indexes of mice were also analyzed.
Results：
12-week-HFHC diet caused obesity, impaired glucose tolerance and elevated serum lipid levels. Compared to simvastatin, supplements of RPL1 and RPL2 not only significantly alleviated impaired glucose tolerance and hyperlipidemia, but also attenuated obesity induced by HFHC diet. However, supplement of RPL3 only showed mild decrease in epididymal fat weight, inferior to the effect of RPL1 and RPL2.
16S rDNA sequencing revealed that RPL1 and RPL2 treatments improved intestinal microbiota dysbiosis caused by HFHC diet in mice, as evidenced by an increase in the abundance of known beneficial bacteria and a decrease in the percentage of abundance of known obesity-related bacteria. Consistent with phenotypic results, KEGG analyses showed that both RPL1 and RPL2 groups restored many metabolic pathways upregulated by HFHC feeding, while group RPL3 didn’t exert this effect.
Moreover, differential fecal bacteria derived from RPL1 and RPL2 groups showed significant correlations with phenotypic indexes of mice, which may suggest a connection between altered fecal microbiota and the effect of RPL1 and RPL2 supplements on glucose and lipid metabolism in obese mice.
Conclusions：
Our data suggested that RPL1 and RPL2 groups attenuated obesity, glucose and lipid metabolism disorders induced by HFHC feeding in mice, superior to RPL3 and SMV groups. Supplement of RPL may attenuate glucose and lipid metabolism disorders by regulating structure and function of intestinal microbiota in mice, which may be an important mechanism for RPL to regulate metabolism and needs further research.

Fig.1 (A) Mice were maintained on either a normal control diet (NC) or a high fat high cholesterol diet (HFHC) and exposed to daily simvastatin or RPL gavage for 12 weeks, n = 12 per group. (B) Representative images of mice at the end of experiment. (C)Weekly energy intake per mouse. (D)Changes of bodyweight during the experiment. (E) Representative images of epididymal fat pad and related images of H&E-staining. Scale-bar, 50μm. (F) Weight of epididymal fat. (G) Pathological injury score of epididymal adipose tissue. (H) Fasting blood glucose of mice. (I) Oral glucose tolerance test (OGTT) of mice after 14-16h fasting. (J) Area under curve of OGTT. (K) Serum LDL-C level. (L) Serum T-CHO level. (M)Ratio of LDL-C to T-CHO. Error bars, s. e. m.

Fig.2 (A) α-diversity analysis by Chao1 of all groups. (B) β-diversity analysis by PCoA based on euclidean distance.<b> (</b>C-F) Relative abundance of Blautia (C), Lachnoclostridium (D), Coriobacteriaceae_UCG-002 (E). Error bars, s. e. m. (G) Predicted functions of fecal microbiota based on KEGG by Kruskal-Wallis. (H) Correlation analysis for differentiated genus and phenotypic data. Spearman corrections were employed.

Fig.2 (A) α-diversity analysis by Chao1 of all groups. (B) β-diversity analysis by PCoA based on euclidean distance. (C-F) Relative abundance of Blautia (C), Lachnoclostridium (D), Coriobacteriaceae_UCG-002 (E). Error bars, s. e. m. (G) Predicted functions of fecal microbiota based on KEGG by Kruskal-Wallis. (H) Correlation analysis for differentiated genus and phenotypic data. Spearman corrections were employed.

xin huang

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