Fermented Momordica charantia L. juice modulates hyperglycemia, lipid profile, and gut microbiota in type 2 diabetic rats

Food Research International 121 (2019) 367–378

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Fermented Momordica charantia L. juice modulates hyperglycemia, lipid profile, and gut microbiota in type 2 diabetic rats

T

He Gao, Jia-Jia Wen, Jie-Lun Hu, Qi-Xing Nie, Hai-Hong Chen, Tao Xiong, Shao-Ping Nie, ⁎ Ming-Yong Xie State Key Laboratory of Food Science and Technology, China-Canada Joint Lab of Food Science and Technology (Nanchang), Nanchang University, Nanchang 330047, China

A R T I C LE I N FO

A B S T R A C T

Keywords: Momordica charantia Lactobacillus plantarum Type 2 diabetes Gut microbiota Lipidomics

The effect of Lactobacillus plantarum-fermentation on the anti-diabetic functionality of Momordica charantia was examined using a high-fat-diet and low-dose streptozocin-induced type 2 diabetic rat model. Fermented Momordica charantia juice (FMCJ) administration mitigated the hyperglycemia, hyperinsulinemia, hyperlipidemia, and oxidative stress in diabetic rats more favorably than the non-fermented counterpart. Treatments with FMCJ improved ergosterols and lysomonomethyl-phosphatidylethanolamines metabolisms more effectively. Supplement of FMCJ regulated the composition of the gut microbiota, such as increased the abundance of Bacteroides caecigallinarum, Oscillibacter ruminantium, Bacteroides thetaiotaomicron, Prevotella loescheii, Prevotella oralis, and Prevotella melaninogenica, in diabetic rats compared with untreated diabetic rats. Moreover, FMCJtreated diabetic rats exhibited higher concentrations of acetic acid, propionic acid, butyric acid, total short-chain fatty acids and lower pH values in colonic contents than that in non-fermented juice-treated rats. These results demonstrated that Lactobacillus plantarum-fermentation enhanced the anti-diabetic property of MC juice by favoring the regulation of gut microbiota and the production of SCFAs.

1. Introduction It was estimated by the International Diabetes Federation that 425 million people suffered from diabetes worldwide in 2017 and 12% of the global health expenditure (about $727 billion) was spent on diabetes (http://www.diabetesatlas.org/). Type 2 diabetes (T2D) is characterized by high levels of blood glucose, relative insulin deficiency, and insulin resistance in target organs (Chatterjee, Khunti, & Davies, 2017). Furthermore, T2D increase the risk of complications, such as diabetic kidney disease, cardiovascular autonomic neuropathy, arterial stiffness, and hypertension, resulting in disease deterioration and even death (Dabelea et al., 2017). However, anti-diabetic drugs often cause adverse effects, such as abdominal discomfort, nausea, and diarrhea (Tahrani, Barnett, & Bailey, 2016). To this end, it is necessary to treat T2D with an alternative, such as medicinal plants, with none or less

side-effect (Governa et al., 2018). Momordica charantia (MC) has been used for the treatment of T2D in Asia, Africa, and South America for thousands of years. A recent study demonstrated that MC juice (MCJ) exhibited hypoglycemic, hypolipidemic, and antioxidant effects in STZ-induced rats (Mahmoud, El Ashry, El Maraghy, & Fahmy, 2017). Moreover, MC supplements for 3-month mitigated hyperglycemia and improved insulin secretion in individuals with T2D (Cortez-Navarrete, Martinez-Abundis, Perez-Rubio, GonzalezOrtiz, & Mendez-Del Villar, 2018). On the other hand, since they play roles in the host metabolism, gut microbiota and its metabolites have received increasing attention on the treatment of T2D (Hartstra, Nieuwdorp, & Herrema, 2016). Recently, MC has been reported to regulate the composition of particular gut microbiota without affecting the normal population diversity in diabetic rats (Zhu, Bai, Zhang, Xiao, & Dong, 2016).

Abbreviation: T2D, type 2 diabetes; STZ, streptozotocin; LAB, Lactic acid bacteria; FMCJ, fermented Momordica charantia juice; NFMCJ, non-fermented Momordica charantia juice; HFD, high-fat diet HFD; DM, diabetes mellitus; MC, Momordica charantia; MCJ, Momordica charantia juice; C, control; FBG, fasting blood glucose; GSP, glycated serum protein; HOMA-IR, Homeostasis model assessment of insulin resistance; QUICKI, Quantitative insulin sensitivity check index; T., trends; TC, total cholesterol; TG, triacylglycerols; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; SOD, superoxide dismutase; CAT, catalase; MDA, malondialdehyde; SCFA, short-chain fatty acid; PLS-DA, partial least-square-discrimination analysis; VIP, variable importance in the projection; LPF, Lactobacillus plantarum-fermentation; S, Richness; H, Shannon-Wiener index; Hmax, Maximum Shannon-Wiener index; E, Evenness ⁎ Corresponding author. E-mail address: [email protected] (M.-Y. Xie). https://doi.org/10.1016/j.foodres.2019.03.055 Received 11 November 2018; Received in revised form 15 March 2019; Accepted 25 March 2019 Available online 26 March 2019 0963-9969/ © 2019 Elsevier Ltd. All rights reserved.

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considered as an animal model for type 2 diabetes (Srinivasan, Viswanad, Asrat, Kaul, & Ramarao, 2005). Simultaneously, those fed the basal diet were injected with an equivalent volume of saline. Levels of FBG in rats were measured after 1-week injection. Rats were considered to be type 2 diabetic rats when the level of FBG exceeded 16.7 mmol/L. A total of 30 type 2 diabetic rats were randomly divided into three groups (n = 10): diabetes (D), D plus FMCJ (D + FMCJ), D plus NFMCJ (D + NFMCJ). Additionally, normal chow-fed rats were set as the control group (C). All oral administrations were conducted with 10 mL/kg of BW over the 4-week period. Body weight was daily measured, and food intake and water consumption were weekly determined. At the end of the treatment, rats were fasted for 12 h and then executed. Blood samples were collected and centrifuged at 1000 × g for 10 min to obtain the serum for the following analysis. Moreover, the colonic contents of rats were quickly removed and stored at −80 °C before analysis. All animals used in this experiment were approved by the institutional animal care and use committee, Nanchang University [SYXK (Gan) 2015-0001]. Additionally, these rats were cared for in accordance with the Guidelines for the Care and Use of Laboratory Animals published by the U.S. National Institutes of Health (NIH Publication 85–23, 1996).

These anti-diabetic effects of MC were attributable to its bioactive compounds, such as saponins, polyphenol, and polysaccharides (Han et al., 2018; Zhang, Chen, & Bai, 2018). Cucurbitane-type triterpenoids derived from MC alleviated T2D by improving insulin sensitivity and glucose metabolism (Han et al., 2018). As another major component, MC polysaccharides ameliorated hyperglycemia, regulated serum insulin level, and protected pancreatic islets in STZ-induced diabetic mice (Zhang et al., 2018). Nonetheless, the function of these substances depends on their structures and contents, which are susceptible to alteration by food processes (Ktenioudaki, Alvarez-Jubete, & Gallagher, 2015). Fermentation has captured growing attention as a bioconversion tool to enhance the functionality of food products, not merely a food preservation method (Septembre-Malaterre, Remize, & Poucheret, 2017). Currently, lactic acid bacteria (LAB) species were widely applied to prepare functional fruit and vegetable juices by hydrolyzing phenolic compounds, generating metabolites, and degrading anti-nutritional molecular (Kwaw et al., 2018; Septembre-Malaterre et al., 2017). For instance, LAB fermentation has been shown to increase the total phenolic and flavonoid contents, as well as remodel the phenolic profile, and hence boost the antioxidant capacity in mulberry juice (Filannino, Di Cagno, & Gobbetti, 2018). Fermented MCJ with Lactobacillus plantarum (L. plantarum) degraded momordicosides to release aglycones and other metabolites, and therefore boosted the inhibition of α-glucosidase activity (Mazlan, Annuar, & Sharifuddin, 2015). However, an animal experiment was needed to be carried out for fully understanding the effect of L. plantarum-fermentation (LPF) on the anti-diabetic property of MC in vivo. In addition, L. plantarum NCU116 isolated from pickled vegetables was found to heighten the anti-diabetic effect of carrot in streptozocin (STZ)-induced diabetic rats (Li et al., 2014). Consequently, the aim of this study was to investigate the anti-diabetic property of L. plantarumfermented MCJ on the high-fat diet and low-dose STZ induced T2D rats.

2.3. Measurements of FBG, oral glucose tolerance test (OGTT), serum glycated serum protein (GSP) and insulin

2. Material and chemicals

Levels of FBG and OGTT were analyzed by Accu-Chek Performa (Roche Diagnostics, Mannheim, Germany). All groups were oral administrated glucose (aqueous solution, 2 g/kg of BW). After that, the blood glucose levels of rats were measured at 0, 30, 60, 90, 120, and 180 min. Concentrations of serum GSP and insulin were evaluated by the ELISA kits purchased from Nanjing Jiancheng Bioengineering Institute (Nanjing, Jiangsu, China). Homeostasis model assessment of insulin resistance (HOMA-IR) and Quantitative insulin sensitivity check index (QUICKI) were determined (Katz et al., 2000; Matthews et al., 1985).

2.1. Juice preparation

2.4. Analysis of serum lipids

Fresh unripe MC was obtained from a local supermarket (Nanchang, China). The fruit was washed and cut. The non-edible part was removed. The rest was crushed into juice without adding water. The resulting juice was initially sterilized at 102 °C for 20 min with 1 Atm. Subsequently, the sterilized juice was inoculated with L. plantarum NCU116 strain powder (0.01%, w/w) and then fermented at 37 °C for 48 h to prepare the fermented M. charantia juice (FMCJ). The non-fermented counterpart (NFMCJ) was prepared as control under the same conditions without inoculation and fermentation. The fermented juice was sterilized at 102 °C for 20 min with 1 Atm. The MCJ was kept at −20 °C.

Total cholesterol (TC), triacylglycerols (TG), high-density lipoprotein cholesterol (HDLeC), and low-density lipoprotein cholesterol (LDLC) were examined by an Automatic biochemical analyzer (Mindray BS380, Shengzheng, China).

2.2. Experimental animals

2.6. Lipidomics

Forty male Wistar rats (160–200 g) were purchased from Beijing Vital River Laboratory Animal Technology Co., Ltd. (China). Other rats were purchased at the same time for another experiment (Gao et al., 2018). Thus, the results of normal and model groups were consistent with the previous literature. Rats were housed under the condition (25 ± 2 °C, 50 ± 5% relative humidity, and 12/12 h day-night cycle). After 1 week acclimation, 10 rats were selected and fed a standard pellet diet, and the rest was fed a high-fat diet (HFD, comprising 66.5% of standard pellet diet, 20% of sucrose, 10% of lard, 2.5% of cholesterol, and 1% of sodium cholate) (Gao et al., 2018). After 8-week dietary manipulation, rats fasted 12 h. Subsequently, the HFD-fed rats were injected with STZ (30 mg/kg of body weight, BW) by the tail vein injection to establish type 2 diabetic rats model (Gao et al., 2018). The combination of HFD-fed and low-dose STZ treated rats was be

Lipids were extracted using a modified Sarafian method (Sarafian et al., 2014). To extract lipids in the serum, the distilled water (975 μL) was added to dilute sample (25 μL) and stand in the ice bath for 10 min, and subsequently the methanol (2.0 μL) and dichloromethane (0.9 μL) were added to the diluted serum sample. The mixture was vortexed to obtain a monophase. The monophase was added to water (1 μL) and dichloromethane (0.9 μL) to get an emulsion, and the protein was separated from the two liquid phases by centrifugation at 1200 rpm for 10 min. The lower dichloromethane phase was transferred by pipetting and put into a fresh Eppendorf tube. The dichloromethane phase was evaporated under a stream of nitrogen, dried lipid extracts were reconstituted in 1 mL methanol/dichloromethane (1:1, v/v) containing 5 mM ammonium acetate for lipidomics analysis. The liquid chromatographic separation was performed with the

2.5. Evaluation of serum oxidative stress Activities of superoxide dismutase (SOD) and catalase (CAT), and levels of malondialdehyde (MDA) were measured by the commercial kits purchased from Nanjing Jiancheng Bioengineering Institute (Nanjing, Jiangsu, China).

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3.2. FBG, OGTT, GSP, and insulin

Shimadzu Nexera X2 UHPLC system (Kyoto, Japan), with the Shimpack GIST C18 column (2.1 mm × 75 mm, 2 μm) at 30 °C. The flow rate was set at 0.35 mL/min and the injection volume was set at 3.5 μL. For both positive and negative mode, mobile phases included a mixture containing distilled water, MeOH, ACN (3:1:1) with 5 mM ammonium (A) and a mixture of isopropanol modified with 5 mM ammonium. The gradient program condition was set as follows: 0.5 min, 20% of B; 1.5 min, 40% of B; 3 min, 60% of B; 13 min, 98% of B; 13.1 min, 20% of B; 17 min, 20% of B. The mass system was carried out by the AB SCIEX Triple TOF 5600 in both positive and negative models. In positive model, the collision energy, declustering potential, and ion spray voltage were set at 35, 80, and 5500 V. In negative model, collision energy, declustering potential, and ion spray voltage were set at −35, −80, and − 5500 V. The other parameters were set as follows: collision energy spread, 15 V; mass range, 50–1000 m/z; curtain gas, 35 psi; gas 1 and gas2, 50 psi; drying temperature, 500 °C.

Untreated diabetic rats maintained notably higher FBG, serum insulin, HOMA-IR, and QUICKI levels compared with the normal rats (p < .01) (Fig. 1). FMCJ and NFMCJ intakes significantly decreased these levels in T2D rats compared with untreated diabetic rats. Meanwhile, the treatments of FMCJ and NFMCJ decreased the blood glucose level in diabetic rats at 30, 60, 90, 120, and 180 min, compared with the untreated diabetic rats (two-way ANOVA, p < .001). Moreover, D + FMCJ group exhibited lower levels of FBG and serum insulin than that in D + NFMCJ group. However, no significant difference was observed in GSP between untreated and treated diabetic groups (Fig. 1D). 3.3. Serum lipids Levels of TC, TG, and LDL-C in D group were notably higher than that in C group (p < .01), while the HDL-C was significantly declined (p < .01) (Fig. 1H). However, FMCJ and NFJMCJ displayed strong effects on decreasing TC, TG, and LDL-C than those in D group (p < .01), whereas the HDL-C was markedly elevated (p < .01). More importantly, D + FMCJ group exhibited lower TC, TG, and LDL-C levels, as well as a higher HDL-C than those of D + NFMCJ group.

2.7. DGGE analysis The DNA extracted from colonic contents by DNA Stool Mini Kit (QIAamp DNA Stool Mini Kit, QIAGEN, Shanghai, China) and used as template DNAs in PCR. The amplification of V3 regions of bacterial 16S rDNA, DGGE analysis, and bands identification was performed as described previously (Nie et al., 2019).

3.4. Oxidative stress The enhanced oxidative stress of T2D rats was mitigated by the administrations of FMCJ and NFMCJ (Table 1). Furthermore, FMCJ reduced oxidative stresses more favorably than NFMCJ in T2D rats.

2.8. Measurements of colonic SCFAs and pH

3.5. Lipidomics analysis

Colonic SCFAs and pH values were determined as our previous report (Gao et al., 2018).

3.5.1. Potential biomarker associated with T2D The score plots of the PLS-DA model presented a clear separation between C and D groups (Fig. 2A and B). The positive model (R2 = 0.859, Q2 = 0.701) and negative (B, R2 = 0.859, Q2 = 0.785) demonstrated that the PLS-DA model was reliable. A total of 114 metabolites were detected in different groups (Supplementary Table S2 and S3). Meanwhile, 11 lipids met the criteria with (p < .05, FDR < 0.05, and VIP > 1) (Table 2).

2.9. Statistical analysis The data were analyzed by SPSS 17.0 software (SPSS, Inc., Chicago, IL). One-way analysis of variance (ANOVA) and Student's t-test were used to determine the significance of the difference between groups. The level of significance was set up at p < .05. For the data of blood glucose levels during the OGTT, treatments by time interactions were determined using a two-way ANOVA. The LC-MS/MS data were analyzed using PeakView and LipidView software (AB SCIEX). Based on the MS and MS/MS data, the lipid was identified by searching in the HMDB (http://www.hmdb.ca), Lipidmaps (http://www.lipidmaps.org), and METLIN (http://metlin.scripps.edu). The output data matrix from LipidView was exploited to perform the multivariate analysis by MetaboAnalyst 4.0 (http://www.metaboanalyst.ca.). Partial leastsquare-discrimination analysis (PLS-DA), heatmap analysis, hierarchical clustering analysis, and the variable importance in the projection (VIP) was performed by MetaboAnalyst 4.0. Potential metabolite markers changed among experimental groups were selected according to VIP > 1 from the PLS-DA model and Student's t-test (p value < .05). Correlation analysis was performed by R software.

3.5.2. FMCJ and NFMCJ treatments improved lipids metabolism PLS-DA model exhibited an evident separation among C, D, D + FMCJ, and D + NFMCJ groups in both positive (R2 = 0.901 and Q2 = 0.667) and negative (R2 = 0.812 and Q2 = 0.616) model (Fig. 2C and D), indicating FMCJ and NFMCJ could affect the lipidomic profile of the serum in T2D rats. Bigger differences were observed between D and D + NFMCJ groups than those between D and D + FMCJ groups. Fig. 2C and D reflected the alteration of lipids, including significantly changed and unchanged metabolites. For understanding the notably influenced lipids, the further analysis was needed to carry out. As shown in Supplementary Table S4, 22 and 21 metabolites were significantly affected by administrations of FMCJ and NFMCJ in T2D rats, respectively. 11 lipids were remarkably influenced in T2D rats by FMCJ and NFMCJ treatments which were performed in the heatmap (Fig. 2E). Hierarchical clustering analysis of the sample and the lipid were also shown in the heatmap. A relatively lower similarity was observed in lipid patterns between D and the rest groups. D + FMCJ group was clustered with C group more closely than D + NFMCJ group. Focus on the amelioration of the 11 considerably disturbed lipids in T2D rats by intakes of FMCJ and NFMCJ, 7 metabolites were matched (p < .05, FDR < 0.05, and VIP > 1) (Table 2). Administrations of FMCJ and NFJMCJ reversed the decreased Cer32:0;2, DAG32:0, and LPI20:0 in diabetic rats (p < .01). More importantly, FMCJ treatments significantly attenuated the decrement of LMMPE18:0 and Erg18:3 in T2D rats, while no remarkable difference was observed between D + NFMCJ and D groups. Moreover, supplementation of NFMCJ could

3. Results 3.1. BW, food intake, and water consumption Supplements of FMCJ and NFMCJ significantly alleviated the loss of BW in T2D rats compared with untreated diabetic rats (p < .01) (Fig. 1A). Meanwhile, treatments with FMCJ and NFMCJ remarkably ameliorated the increment of food and water intakes in T2D rats (Supplementary Table S1). Furthermore, a higher value of BW and a lower level of water consumption were observed in D + FMCJ group compared with D + NFMCJ group. 369

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Fig. 1. Effects of FMCJ and NFMCJ on body weight, FBG, OGTT, GSP, insulin, HOMA-IR, QUICKI, and lipids in diabetic rats. FBG, fasting blood glucose; OGTT, oral glucose tolerance test; GSP, glycated serum protein; HOMA-IR, Homeostasis model assessment of insulin resistance; QUICKI, Quantitative insulin sensitivity check index; TC, total cholesterol; TG, triacylglycerols; LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol; C, control group; D, diabetes group; D + FMCJ, diabetes mellitus plus fermented M. charantia juice group; D + NFMCJ, diabetes mellitus plus non-fermented M. charantia juice group. Different letters indicate significantly different (p < .05).

with FMCJ-treated group was lower than that of the non-fermentedtreated group (8.7:3.5:1.0). Meanwhile, a higher proportion of butyrate was presented in D + FMCJ group than D + NFMCJ group. Treatments of FMCJ and NFMCJ in diabetic rats had lower values of pH than that of D group (p < .01) (Fig. 4B). D + FMCJ group reached a lower degree of colonic pH, which was associated with more concentration of colonic SCFAs, compared with D + NFMCJ group.

improve the cholesteryl ester (16CE:0) and LPE22:1 in T2D rats, while no significant difference was recorded between D + FMCJ and D groups. On the other hand, increased levels of fatty acids (FFA18:2), methy ethanolamines (ME18:1), and lysophosphatidylinositol phosphates (LPIP18:01 and 18:1) were reduced by FMCJ and NFMCJ treatments, although no significant difference was found. 3.6. DGGE analysis

3.8. Correlation analysis Treatments with FMCJ and NFMCJ significantly heightened the richness in diabetic rats compared with D group (p < .01) (Fig. 3A). Higher levels of Shannon-Wiener index were showed in D + FMCJ and D + NFMCJ groups compared with D group (p < .01). Simultaneously, D + FMCJ and D + NFMCJ groups displayed significant increments of the maximum Shannon-Wiener index compared with D group (p < .01). For the evenness, no significant difference was recorded among the four groups. A relatively low similarity was observed between D and the rest groups (Fig. 3B). D + FMCJ and D + NFMCJ groups were clustered with C group. These results suggested that MCJ and LPF treatments might be considered as major factors, affecting the intestinal microbiota of T2D rats. Meanwhile, the relationship between DGGE patterns and environmental factors were analyzed by redundancy analysis (RDA) (Fig. 3C–E). Diabetes mellitus (DM), MCJ, and LPF were considered as environmental factors. A total of 31 bands were found on the RDA and significantly correlated with DM, MCJ and LPF. Fig. 3 shows 15, 10, and 7 bands had a positive correlation, whereas 9, 14, and 5 bands had a negative correlation with DM, MCJ and LPF, respectively. Bacteroides caecigallinarum, Prevotella loescheii, and Prevotella oralis were positively associated with MCJ and LPF (Table 3). Meanwhile, Oscillibacter ruminantium, Bacteroides thetaiotaomicron, and Prevotella melaninogenica exhibited positive relationships with LPF. Prevotella copri showed a positive correlation with MCJ.

The results of correlation analysis based on the colon microbiota, SCFAs, and lipids were shown in Fig. 5. Clearly, butyrate was positively correlated with Prevotella loescheii and Prevotella copri (r > 0.77) (Fig. 5A). Propionate and valerate were negatively correlated with Prevotella copri (r < −0.83). Acetate and total SCFA were negatively correlated with Clostridium bolteae and Alistipes obesi (r < −0.80), while were positively correlated with and Helicobacter pylori (r > 0.58). Furthermore, acetate, butyrate, and total SCFA showed negative correlations with LPE22:1 and ME 18:1 (r < −0.53) (Fig. 5B). On the other hand, Prevotella loescheii and Prevotella copri were positively correlated with FFA18:2 (r > 0.74), whereas were negatively correlated with Cer32:0;2, DAG32:0, and LMMPE18:0 (r < −0.54) (Fig. 5C). Prevotella loescheii presented positive correlation with LPI20:0 (r > 0.77), while negative correlations with LPE22:1 and LPIP18:1 (r < −0.80). Clostridium bolteae and Alistipes obesi showed positive correlations with ME18:1(r = 1), whereas negative correlation with Erg18:3, LPI20:0, and LPIP18:0 (r < −0.77). Simultaneously, Helicobacter pylori was positively correlated with Erg18:3, FFA18:2, LPI20:0, and LPIP18:0 (r ≥ 0.77), while negatively correlated with LPE22:1 and ME18:1 (r < −0.77). 4. Discussion T2D is characterized by increased FBG, hyperinsulinemia, and insulin resistance (Hu, Nie, & Xie, 2018). MC has been reported to present hypoglycemic and hypoinsulinemic activities (Cortez-Navarrete et al., 2018; Mahmoud et al., 2017; Zhu et al., 2016). In the present study, the hypoglycemic effect of FMCJ and NFMCJ in T2D rats was in agreement with the previous literature (Cortez-Navarrete et al., 2018; Mahmoud et al., 2017; Zhu et al., 2016). Moreover, D + FMCJ group exhibited more favorably regulatory effects on FBG and serum insulin than those in D + NFMCJ group, which was attributable to fermentation exerted favorably impacts on food matrix (Septembre-Malaterre et al., 2017). The transformation of MC by LPF could be beneficial for ameliorating T2D, via reducing total carbohydrate content and improving inhibition of α-glucosidase in vitro (Mazlan et al., 2015). Fermented carrot juice exhibited hypoglycemic and hypoinsulinemic functionalities in T2D rats (Li et al., 2014). Collectively, LPF could enhance the regulatory effect of MC on the hyperglycemia and hyperinsulinemia of T2D rats.

3.7. Colonic SCFAs and pH D group presented the lowest contents of SCFAs in colonic contents among four groups (Fig. 4A). Concentrations of acetic acid and total SCFAs in FMCJ-treated group were significantly higher than that of D group (p < .01). Treatment with FMCJ markedly increased the concentrations of propionic and butyric acids by 2.8% and 60.6%, respectively, in diabetic rats compared with D group (p < .05), while no significant difference was observed between D + NFMCJ and D groups. Moreover, FMCJ-administrated group presented more concentration of colonic SCFAs than that of the non-fermented-treated group in diabetic rats. On the other hand, the ratio of acetate:propionate:butyrate (5.4:2.1:1.0) was the lowest with normal rats among the different groups, while that of the untreated diabetic rats was highest (11.6:4.9:1.0). The ratio of acetate:propionate:butyrate (8.1:3.1:1.0) Table 1 Effect of FMCJ and NFMCJ on oxidative stress in diabetic rats. Parameters

C

D

D + FMCJ

D + NFMCJ

SOD (U/mL) CAT (U/mL) MDA (μmol/L)

262.0 ± 51.1c 199.3 ± 22.3c 4.0 ± 1.7a

101.4 ± 11.1a 59.5 ± 30.7a 7.2 ± 1.8b

238.8 ± 65.9b 129.0 ± 15.6b 2.7 ± 0.9a

176.2 ± 47.5b 130.7 ± 36.4b 3.6 ± 0.8a

SOD, superoxide dismutase; CAT, catalase; MDA, malondialdehyde; C, control group; D, diabetes group; D + FMCJ, diabetes mellitus plus fermented M. charantia juice group; D + NFMCJ, diabetes mellitus plus non-fermented M. charantia juice group. Different letters indicated significantly different (p < .05). 371

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Fig. 2. Lipidomics: PLS-DA score plots between C and D groups in the positive (A, R2 = 0.859, Q2 = 0.701) and negative (B, R2 = 0.859, Q2 = 0.785) model; PLS-DA score plots of the C, D, D + FMCJ, and D + NFMCJ groups in positive (C, R2 = 0.901, Q2 = 0.667) and negative (D, R2 = 0.812, Q2 = 0.616) model; heatmap of normalized lipids concentrations in serum samples (E, columns represent the samples and rows represent the lipids). C, control group; D, diabetes group; D + FMCJ, diabetes mellitus plus fermented M. charantia juice group; D + NFMCJ, diabetes mellitus plus non-fermented M. charantia juice group; Cer, Ceramides; CE, Cholesteryl ester; DAG, Diacylglycerols; Erg, Ergosterols; FFA, Fatty acids; LMMPE, Lysomonomethyl-PE; LPE, Lysophosphatidylethanolamine; LPI, Lysophosphatidylinositol; LPIP, Lysophosphatidylinositol phosphates; ME, Methyl Ethanolamines..

facilitate to investigate the global alteration of lipid profiles in diabetic rats and the underlying mechanism of treatment of T2D (Markgraf, AlHasani, & Lehr, 2016). FMCJ treatment might exert more impacts on the lipid profile of T2D rats than the non-fermented counterpart. Ceramides exerted impacts on T2D and its associated complications by the complex mechanism, such as affecting the insulin signal transduction, sphingolipid biosynthesis, β-cell apoptosis, and insulin gene expression (Galadari, Rahman, Pallichankandy, Galadari, & Thayyullathil, 2013). As a glycerolipid, diacylglycerols played roles in cellular lipid metabolism, membrane bilayers, TG synthesis, and served as message molecules (Markgraf et al., 2016). Lysophosphatidylinositol showed a close relation with T2D patient, which was associated with the LPI/GPR55 system (Moreno-Navarrete et al., 2012). Ergosterols have been demonstrated to mitigate T2D in mice by regulating the PI3K/Akt pathway and PKC pathway to trigger the glucose transporter 4 translocation and expression (Xiong et al., 2018). Lysomonomethyl-Phosphatidylethanolamines, belonging to glycerophospholipids, were considered as the discriminating marker between patients with Myeloproliferative Neoplasms and normal individuals in the lipidomic profile of blood plasma (de Oliveira, Da Silva, Turco, Júnior, & Maria de Lourdes, 2015). The disorder of CE was associated with diabetic dyslipidemia (Mooradian, 2009). As a major class of phospholipids, glycerophospholipids were closely linked with the membrane structure and function, which was affected by T2D (Weijers, 2012). Raised plasma FFA exerted impacts on contributing to insulin resistance and βcell dysfunction, whereas the decrement of increased plasma FFA should benefit the treatment of T2D (Boden & Shulman, 2002). lysophosphatidylinositol phosphates have been reported to generate by the phosphorylation of LPI and exist in the plasma membrane fraction (Wheeler & Boss, 1989). Gut microbiota could affect the host lipid metabolism by producing SCFAs to stimulate GPR41 and GPR43 (Ghazalpour, Cespedes, Bennett, & Allayee, 2016). Administration of FMCJ and NFMCJ could improve the composition of gut microbiota in diabetic rats, and hence produce SCFAs, leading to the improvement of lipidomic profiles. Taken together, these results implied that FMCJ and NFMCJ could improve lipid metabolism by modulating the trend of lipids including sterol lipids, sphingolipids, glycerolipids, and

HFD-fed and STZ-induced diabetic rats presented a significant increase in TC, TG, and LDL-C, which was in agreement with the literature (Gao et al., 2018;Li et al., 2014; Srinivasan et al., 2005). These results were possibly due to the abnormalities in lipid metabolism (Li et al., 2014; Srinivasan et al., 2005). The increment of TG in HFD-fed and STZ-induced diabetic rats was probably caused by elevated absorption and production of TG in the formation of chylomicrons after consuming HFD which was rich in fat (Srinivasan, Patole, Kaul, & Ramarao, 2004). The increase in TC was possibly due to increased absorption of TC after HFD treatment through the small intestine in HFD-fed and STZ-induced diabetic rats (Colca et al., 1991). Furthermore, higher levels of TC and TG might contribute to cardiovascular complications (Srinivasan et al., 2005). Consequently, the modulation of serum lipids is essential to reduce the risk of complications and disease progression in diabetic individuals (Chatterjee et al., 2017). Treatments of FMCJ had a more effectively hypolipidemic effect on T2D rats than those of NFMCJ. This finding was probably associated with more colonic butyric acid presented in D + FMCJ group than that in D + NFMCJ group (Li et al., 2014). Taken together, FMCJ exerted more favorably impacts on regulating serum lipids in T2D rats than the counterpart. In HFD-fed and STZ-induced diabetic rats, decreased activities of SOD and CAT led to the increase in free radicals (Li et al., 2014). Moreover, MDA formed by lipid peroxidation was intensified in diabetic rats (Paun & Danska, 2016). In the current study, FMCJ reduced oxidative stresses more effectively in T2D rats than NFMCJ, which was in agreement with the previous literature (Li et al., 2014). This was possibly due to fermentation hydrolyzed momordicosides to produced aglycones and other polyphenols in MC, leading to improving its bioactive properties (Mazlan et al., 2015). T2D is a complex glucose and lipid metabolic disorders. As a major group of organic molecules, lipids exhibited plenty of bioactivities such as energy storage, cell signaling, and cellular structural support. According to the results of serum lipids, FMCJ could notably attenuate the elevated serum TC and TG in T2D rats (p < .01). Meanwhile, intakes of FMCJ and NFMCJ could regulate the gut microbiota and its metabolites in diabetic rats. However, the underlying mechanism remained to be elucidated. As a branch of metabolomics, lipidomics could

Table 2 Metabolites influenced by FMCJ and NFMCJ treatments in diabetic rats (n = 8). Metabolites

Cer 32:0;2 16 CE:0 DAG 32:0 Erg 18:3 FFA 18:2 LMMPE 18:0 LPE 22:1 LPI 20:0 LPIP 18:0 LPIP 18:1 ME 18:1

D/C

D + FMCJ/D

D + NFMCJ/D

T.

FC

p.value

FDR

VIP

T.

FC

p.value

FDR

VIP

T.

FC

p.value

FDR

VIP

↓ ↓ ↓ ↓ ↑ ↓ ↑ ↓ ↑ ↑ ↑

0.15 0.08 0.16 0.38 1.72 0.16 1.58 0.29 1.46 1.54 1.80

.001 .005 .000 .002 .004 .001 .000 .000 .000 .000 .000

0.008 0.029 0.006 0.014 0.025 0.008 0.004 0.004 0.000 0.000 0.002

2.33 1.91 2.36 1.59 1.14 2.28 1.02 1.89 1.02 1.07 1.19

↑ ↑ ↑ ↑ ↓ ↑ ↓ ↑ ↓ ↓ ↓

6.89 6.14 6.73 2.03 0.80 6.26 0.69 2.82 0.77 0.76 0.62

.000 .217 .000 .007 .076 .008 .003 .001 .000 .000 .001

0.000 0.318 0.000 0.029 0.137 0.029 0.020 0.005 0.002 0.004 0.008

2.36 0.71 2.33 1.17 0.51 1.72 0.75 1.52 0.69 0.69 0.88

↑ ↑ ↑ ↑ ↓ ↓ ↓ ↑ ↓ ↓ ↓

7.88 30.60 8.33 1.58 0.56 0.19 0.51 2.31 0.70 0.71 0.61

.000 .003 .004 .283 .010 .195 .037 .029 .000 .002 .004

0.003 0.013 0.016 0.413 0.032 0.331 0.101 0.081 0.003 0.009 0.016

2.04 1.79 1.80 0.54 0.91 0.62 1.25 1.08 0.73 0.69 0.81

FC, fold change; T., trends; ↑ and ↓, up and down regulate; C, control group; D, diabetes group; D + FMCJ, diabetes mellitus plus fermented M. charantia juice group; D + NFMCJ, diabetes mellitus plus non-fermented M. charantia juice group; Cer, Ceramides; CE, Cholesteryl ester; DAG, Diacylglycerols; Erg, Ergosterols; FFA, Fatty acids; LMMPE, Lysomonomethyl-PE; LPE, Lysophosphatidylethanolamine; LPI, Lysophosphatidylinositol; LPIP, Lysophosphatidylinositol phosphates; ME, Methyl Ethanolamines. 373

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Fig. 3. Effects of FMCJ and NFMCJ on colon microbiota in diabetic rats. Diversity indices (A) calculated from the DGGE banding profiles, DGGE of bacterial 16S rDNA amplifications in V3 region and UPGMA cluster analysis (B), RDA for DM (C), MCJ (D), LPF (E). The circle means Van Dobben circles. The red circle indicates the positive correlation circle and the blue one means the negative correlation circle. S, Richness; H, Shannon-Wiener index; Hmax, Maximum Shannon-Wiener index; E, Evenness; DM, diabetes mellitus; MCJ, Momordica charantia juice; LFP, Lactobacillus plantarum fermentation; C, control group; D, diabetes group; D + FMCJ, diabetes mellitus plus fermented M. charantia juice group; D + NFMCJ, diabetes mellitus plus non-fermented M. charantia juice group. Different letters indicate significantly different (p < .05). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

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Fig. 3. (continued) Table 3 Band identification for searching the bacterial identity in DGGE. Band

Closest relative

Identity

Accession no.

DM

MCJ

LPF

r3 r4 r8 r9 r12 r14 r15 r21 r41 r44

Bacteroides caecigallinarum Clostridium bolteae Oscillibacter ruminantium Alistipes obesi Bacteroides thetaiotaomicron Helicobacter pylori Prevotella loescheii Prevotella oralis Prevotella melaninogenica Prevotella copri

95% 90% 85% 93% 88% 93% 97% 97% 89% 88%

NR_145844.1 NR_113410.1 NR_118156.1 NR_133025.1 NR_074277.1 NR_044761.1 NR_113109.1 NR_042841.1 NR_102895.1 NR_113411.1

− + − + − + − − −

+ −

+ − + − + − + + +

− − + + +

+ indicates positive correlation, − indicates negative correlation. DM, diabetes mellitus; MCJ, Momordica charantia juice; LPF, Lactobacillus plantarum fermentation. Fig. 4. SCFAs (A) and pH (B) of colonic contents in diabetic rats. C, control group; D, diabetes group; D + FMCJ, diabetes mellitus plus fermented M. charantia juice group; D + NFMCJ, diabetes mellitus plus non-fermented M. charantia juice group. Different letters indicate significantly different (p < .05).

glycerophospholipids. Furthermore, the fermented sample could significantly ameliorate the metabolic disorder of Ergs and LMMPE in T2D rats than that of the non-fermented counterpart. Soluble fermentable fibers, phenolics, and phytochemicals were candidate prebiotics, selectively utilized by the gut microbiota to improve the host health (Gibson et al., 2017). LAB fermentation remodeled the profile and type of bioactive compounds in fruits and vegetables to enhance the prebiotic effect (Septembre-Malaterre et al., 2017). Bacteroides caecigallinarum could produce acetate and succinate as the major end products (Saputra et al., 2015). Butyric acid was a major metabolic end product from glucose, ribose, and xylose in Oscillibacter ruminantium (Lee et al., 2012). As a dominant member of the normal human distal intestinal and colonic microbiota, Bacteroides thetaiotaomicron was able to acquire and hydrolyze dietary polysaccharides and manipulate host gene expression for maintaining a mutually advantageous partnership (Xu et al., 2003). Prevotella exerted an impact on high-fiber dietary-induced improvement in glucose metabolism in individuals (Kovatcheva-Datchary et al., 2015). Propionic, butyric, acetic, and isovaleric acids were the major end products of Prevotella loescheii (Kurita-Ochiai, Fukushima, & Ochiai, 1995). Furthermore, Prevotella oralis and Prevotella melaninogenica were able to produce acetic and succinic acids (main metabolite), and small amounts of isobutyric and isovaleric acids (L. Holdeman, Moore, Churn, & Johnson, 1982; Holdeman & Johnson, 1982). Collectively, LPF could enhance the effect of MC on the regulation of gut microbiota in T2D rats. SCFAs are principal end products of dietary fiber fermentation by intestinal microorganisms and considered as important signaling molecules and energy sources for the host (Gibson et al., 2017). Reduction of SCFAs has been positively associated with T2D (Koh, De Vadder, Kovatcheva-Datchary, & Backhed, 2016). In the present study,

D + FMCJ group had more concentration of colonic SCFAs than that of the non-fermented-treated group, which was in agreement with the previous report by Li et al. (2014). The lower ratio of acetate:propionate:butyrate and the higher proportion of butyrate was in D + FMCJ group than those of D + NFMCJ group, suggesting that FMCJ had more beneficial effects than the non-fermented counterpart for the human health (Fernando et al., 2010). As an SCFA receptor, G protein-coupled receptor (GPR) 43 could be activated by acetate in white adipose tissue to modulate the energy uptake and improve glucose and lipid metabolism (Kimura et al., 2013). Additionally, GPR41 was activated by propionate to increase insulin sensitivity, maintain energy and glucose homeostasis (De Vadder et al., 2014). Butyrate, a major energy source for the colonic epithelium, induced intestinal gluconeogenesis to improve glucose and energy homeostasis (De Vadder et al., 2014). D + FMCJ group had more concentrations of SCFAs, especially for acetic and butyric acids, than those in D + NFMCJ group. This might be a factor which FMCJ had more effectively anti-diabetic property than NFMCJ. Moreover, these results indirectly reflected the improvement of the gut microbiota in diabetic rats by supplementation of FMCJ. Treatments of FMCJ and NFMCJ could reduce the colonic pH, which was associated with more concentration of colonic SCFAs. D + FMCJ group had a lower level of colonic pH than that of D + NFMCJ group. Furthermore, a lower level of pH in the colonic lumen was beneficial for gut health via inhibiting the growth of pathogenic microorganisms.

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Fig. 5. Correlation analysis between colon microbiota and SCFAs (A), SCFAs and lipids (B), colon microbiota and lipids (C). Cer, Ceramides; CE, Cholesteryl ester; DAG, Diacylglycerols; Erg, Ergosterols; FFA, Fatty acids; LMMPE, Lysomonomethyl-PE; LPE, Lysophosphatidylethanolamine; LPI, Lysophosphatidylinositol; LPIP, Lysophosphatidylinositol phosphates; ME, Methyl Ethanolamines.

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Collectively, FMCJ might exert more favorable impacts on T2D than non-fermented juice.

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5. Conclusions In conclusion, the fermented MCJ with L. plantarum NCU116 exhibited more potently anti-diabetic effects than non-fermented one. Administration of FMCJ exerted more beneficial impacts on the management of body weight, water intake, FBG, insulin, lipids and oxidative stress in diabetic rats compared with NFMCJ. Intakes of FMCJ could improve the lipidomic profile of the serum in diabetic rats, by modulating the ergosterols and lysomonomethyl-PE metabolisms. Furthermore, FMCJ remodeled the gut microbiota of diabetic rats by increased the abundance of Bacteroides caecigallinarum, Oscillibacter ruminantium, Bacteroides thetaiotaomicron, Prevotella loescheii, Prevotella oralis and Prevotella melaninogenica. Meanwhile, FMCJ supplement favored the increased colonic SCFAs and the reduction of pH value in T2D rats more effectively than NFMCJ. Overall, these results indicated that the FMCJ ameliorated type 2 diabetes more effectively than non-fermented one, which was possibly associated with the effects on gut microbiota and its metabolites. Acknowledgments This research was funded by the National Key Research and Development Program of China (2017YFD0400705-2), Collaborative Project in Agriculture and Food Field between China and Canada (2017ZJGH0102001), Outstanding Science and Technology Innovation Team Project in Jiangxi Province (20165BCB19001), Jiangxi Provincial Major Program of Research and Development Foundation (Agriculture field, 20165ABC28004), and Research Project of State Key Laboratory of Food Science and Technology (SKLF-ZZA-201611). Conflicts of interest The authors declare no competing financial interest. Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.foodres.2019.03.055. References Boden, G., & Shulman, G. I. (2002). Free fatty acids in obesity and type 2 diabetes: Defining their role in the development of insulin resistance and beta-cell dysfunction. European Journal of Clinical Investigation, 32(Suppl. 3), 14–23. Chatterjee, S., Khunti, K., & Davies, M. J. (2017). Type 2 diabetes. Lancet, 389(10085), 2239–2251. Colca, J. R., Dailey, C. F., Palazuk, B. J., Hillman, R. M., Dinh, D. M., Melchior, G. W., & Spilman, C. H. (1991). Pioglitazone hydrochloride inhibits cholesterol absorption and lowers plasma cholesterol concentrations in cholesterol-fed rats. Diabetes, 40(12), 1669–1674. Cortez-Navarrete, M., Martinez-Abundis, E., Perez-Rubio, K. G., Gonzalez-Ortiz, M., & Mendez-Del Villar, M. (2018). Momordica charantia administration improves insulin secretion in type 2 diabetes mellitus. Journal of Medicinal Food, 21(7), 672–677. Dabelea, D., Stafford, J. M., Mayer-Davis, E. J., D'Agostino, R., Jr., Dolan, L., Imperatore, G., ... Pihoker, C. (2017). Association of type 1 diabetes vs type 2 diabetes diagnosed during childhood and adolescence with complications during teenage years and young adulthood. Jama, 317(8), 825–835. De Vadder, F., Kovatcheva-Datchary, P., Goncalves, D., Vinera, J., Zitoun, C., Duchampt, A., ... Mithieux, G. (2014). Microbiota-generated metabolites promote metabolic benefits via gut-brain neural circuits. Cell, 156(1–2), 84–96. Fernando, W. M. A. D. B., Brennan, C. S., Flint, S., Ranaweera, K. K. D. S., Bamunuarachchi, A., & Morton, H. R. (2010). Enhancement of short chain fatty acid formation by pure cultures of probiotics on rice fibre. International Journal of Food Science and Technology, 45(4), 690–696. Filannino, P., Di Cagno, R., & Gobbetti, M. (2018). Metabolic and functional paths of lactic acid bacteria in plant foods: Get out of the labyrinth. Current Opinion in Biotechnology, 49, 64–72. Galadari, S., Rahman, A., Pallichankandy, S., Galadari, A., & Thayyullathil, F. (2013). Role of ceramide in diabetes mellitus: Evidence and mechanisms. Lipids in Health and

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