Comparative analysis of barley dietary fiber fermented with and without Lactiplantibacillus plantarum dy-1 in promoting gut health and regulating hepatic energy metabolism in high-fat diet-induced obese mice

Abstract

A previous study has revealed that Lactiplantibacillus plantarum (Lp. plantarum) dy-1 fermentation changed the structural properties and in vitro fecal fermentation characteristics of barley dietary fiber. However, the health-promoting effects of fermented dietary fiber in vivo remained unclear. This study was aimed at comparing the ameliorative effects of barley dietary fiber fermented with or without Lp. plantarum dy-1 on lipid metabolism, gut microbiota composition and hepatic energy metabolism. After a twelve-week intervention, fermented barley dietary fiber (FBDF) reduced the body weight and fat accumulation in liver and epididymal white adipose tissue, improved HFD-induced hyperlipidemia and glucose intolerance, and increased short chain fatty acid (SCFA) levels, exhibiting effects that were better than those of raw barley dietary fiber (RBDF). FBDF supplementation improved the gut microbiota composition, specifically enhancing the abundance of probiotic and SCFA-producing bacteria, such as Akkermansia and Muribaculaceae, while RBDF exhibited regulatory effects on harmful bacteria (Escherichia–Shigella and Desulfovibrionaceae). Additionally, FBDF up-regulated the expression of genes related to energy metabolic processes, such as aerobic respiration and oxidative phosphorylation, inhibited the genes related to lipid biosynthetic metabolism, and improved the activities of hepatic energy metabolism-related enzymes, demonstrating effects that were better than those of RBDF. Therefore, this study indicated the potential of using FBDFs as healthy food resources to prevent obesity or as prebiotics to improve gut microbiota.

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1. Introduction

Obesity has become more common in recent years due to unhealthy dietary patterns and sedentary lifestyle and continues to be a challenge to public health worldwide. Obesity is mainly characterized by the disorders of glucose and lipid metabolism and may lead to a series of diseases, including hyperlipidemia, atherosclerosis, coronary heart disease, non-alcoholic fatty liver and type 2 diabetes.^1,2 Although anti-obesity drugs, such as orlistat and sibutramine, can alleviate the symptoms, they may cause adverse effects on the visceral organs.³ Therefore, considerable attention has been focused on the prevention of obesity through dietary interventions.

Dietary fiber (DF) is a carbohydrate polymer that cannot be digested by human digestive enzymes. DF has benefits of reducing fat absorption, improving glucose and lipid metabolism and preventing obesity.^4–6 Wang et al. found that insoluble DF from okara effectively alleviated high-fat diet-induced obese symptoms, such as hyperlipidemia, glucose intolerance and insulin resistance.⁷ As DFs can reach the colon and be fermented by the gut microbiota to produce short chain fatty acids (SCFAs), they can also regulate gut microbiota and improve intestinal health.^8,9 Consequently, DF is regarded as an important dietary supplement for obesity prevention.

Barley (Hordeum vulgare L.) is the fourth major cereal crop that is grown worldwide. The beneficial effects of barley, such as anti-obesitic, anti-diabetic, hypolipidemic and anti-inflammatory activities, have been previously demonstrated.¹⁰ The whole barley grain contains starch, protein, dietary fiber, minerals and other bioactive phytochemicals.¹¹ While only less than 10% of barley is used for human consumption, the remainder is primarily utilized for animal feed and malting purposes. The dietary fiber content in barley accounts for approximately 11%–34%, including β-glucan, arabinoxylan and cellulose.¹² Nevertheless, due to the complex structure and unappealing taste of DFs, the utilization rate of barley DFs remain relatively low.

Cereal fermentation has shown potential in improving physiological activities.¹³ It is reported that fermentation can also release bioactive compounds (such as bound phenolics) and change the structure of cereal DF.¹⁴ Our previous studies found that Lactiplantibacillus plantarum (Lp. plantarum) dy-1 fermented barley extract alleviated obesity caused by high-fat diet in rats, and mainly by activating AMPK/PGC1α axis regulated signaling pathways.^15,16Lp. plantarum dy-1 fermented barley also changed the structure of β-glucan, enhanced in vitro physiological activities, and altered the effects on the lipid metabolism in Caenorhabditis elegans.¹⁷ Meanwhile, Lp. plantarum dy-1 fermentation changed the microstructure and monosaccharide components of barley DF, remarkably enhanced the liberation of bound phenolics, and enhanced the functional properties and in vitro fecal fermentation characteristics, indicating the promotion potential of fermented barley DF against obesity.¹⁸ However, the underlying mechanisms by which the barley dietary fiber fermented by Lp. plantarum dy-1 exert the potential anti-obesity effects are yet to be established.

Therefore, the objective of this study was to construct an obese mice model induced with high-fat diet (HFD), and systematically investigate the intervention effects of barley dietary fiber before and after fermentation on the lipid metabolism, gut microbiota composition and genes linked to lipid metabolism of the liver. This investigation could provide a foundation for the utilization of fermented barley dietary fiber as a dietary supplement for obesity prevention.

2. Materials and methods

2.1 Materials and reagents

Barley bran was provided by Ruimu Biotechnology Co., Ltd (Yancheng, China). Lp. plantarum dy-1 was separated in our laboratory, and preserved in the database of the Chinese Common Microbe Bacterial Preservation Administration Center (CGMCC No. 6016). All other chemical reagents in this study were purchased from Sinopharm Chemical Reagent Co. Ltd (Shanghai, China) and were of analytical grade.

2.2 Preparation of RBDF and FBDF

The preparations of raw barley dietary fiber (RBDF) and Lp. plantarum dy-1 fermented barley dietary fiber (FBDF) were performed according to the previously described procedure.¹⁸ The dietary fiber, moisture, protein, ash, and total phenolics contents of RBDF and FBDF are presented in Table S1.† The main composition of FBDF was dietary fiber (86.91%), and the total free phenolics content was increased after fermentation (increased by 6.74 times).

2.3 Animal experimental design

The animal experiment was conducted in accordance with the Principles of Laboratory Animal Care (NIH publication no. 8023, revised 1978), and approved by the Jiangsu University Experimental Animal Ethical Management and Use Committee (Permission No.: UJS-IACUC-2022091303). All intragastric work was carried out gently and decisively during the experiment.

Male C57BL/6 mice at 5–6 weeks old were purchased from Changzhou Cavens Experimental Animal Co., Ltd (Changzhou, China, SCXK (SU) 2021-0013). The mice were caged individually in LARC at a temperature of 22 ± 2 °C and a relative humidity of 40%–60%, and artificially illuminated on an approximate 12 hours-light/dark cycle. The air exchange was about 18 times per h. All the mice were provided with food and filtered tap water ad libitum. A 7-day adaptation period was provided before the study began.

Mice were randomly separated into two groups: the normal-diet (ND) group and the HFD group. The ND group was fed with a basic diet, and the HFD group were fed with a high-fat diet (formula shown in Table S2†) for 12 weeks. After feeding the mice with these diets for 12 weeks, the mice were confirmed as the obese model when their body weight exceeded 20% of the normal mice.

This study included four experimental groups: the normal diet (ND) group, the HFD group, and two dietary fiber intervention groups (RBDF and FBDF) (10 mice per group). During the twelve-week treatment, the HFD group were still fed with the high-fat diet and the ND group were fed with the basic diet. The RBDF and FBDF groups were fed with a high-fat diet supplemented with 10% RBDF or 10% FBDF, respectively, and the formula is shown in Table S3.†

The body weight of the mice was monitored weekly, and the body length was measured in the final week of the study to calculate the Lee's index. The oral glucose tolerance test (OGTT) was measured as previously described on the last day of the animal experiment.¹⁹ The stool samples were also collected and stored at −80 °C. After the experiment, all mice were subjected to a 12 hour fasting period. Subsequently, euthanasia was performed using cervical dislocation. Blood samples, adipose tissue, liver and colon were collected and kept for further analysis.

2.4 Blood biochemical assays

The serum triglyceride (TG), total cholesterol (TC), high density lipoprotein cholesterol (HDL), and low density lipoprotein cholesterol (LDL) were determined using a Beckman Coulter AU480 Automatic Biochemical Analyzer (Beckman Coulter Inc., Pasadena, USA). The insulin levels were determined using Mouse INS (insulin) ELISA kit (Elabscience Co. Ltd, Wuhan, China). The homeostatic index of insulin resistance (HOMA-IR) was assessed as follows: HOMA-IR = fasting blood glucose × fasting serum insulin/22.5.

2.5 Histopathology evaluation

The liver, adipose tissue and colon samples were fixed in 4% paraformaldehyde for further processing. The tissues were embedded in paraffin and cut into 4 μm sections. After that, the tissue paraffin sections were stained with hematoxylin and eosin (H&E). Subsequently, the stained sections were examined and imaged using a Leica DM6000 B Microscope (Leica Co. Ltd, Shanghai, China).

2.6 Hepatic glycogen, TG and TC contents determination

0.1 g liver was homogenized with a high-throughput tissue grinder²⁰ and centrifuged at 8000 rpm for 15 min at 4 °C, and the supernatant was stored at −80 °C. Hepatic glycogen, TG and TC contents were determined using commercially available kits (Nanjing Jiancheng Bio CO., Nanjing, China).

2.7 Short-chain fatty acid (SCFA) determination

Following our established procedure, SCFAs were analyzed using gas chromatography (Shimadzu GC-2010 Plus, Shimadzu Co. Ltd, Kyoto, Japan). Fecal samples were weighed and homogenized in water. After centrifugation, the supernatant was determined using a gas chromatograph equipped with DB-FFAP column (30 m × 0.25 mm × 0.25 μm). The chromatographic conditions were identical to those used in the previous study.¹⁸

2.8 16S rRNA amplicon sequencing

The mouse feces total genomic DNA was extracted using an OMEGA Soil DNA Kit (Omega Bio-Tek, Norcross, GA, USA). PCR amplification of the 16S rRNA gene V3–V4 region was performed using the forward primer (341F): 5′-CCTACGGGNGGCWGCAG-3′ and the reverse primer (805R): 5′-GACTACHVGGGTATCTAATCC-3′. The PCR components were as follows: 12.5 μL of Phusion Hot start flex 2× Master Mix, 2.5 μL of each forward and reverse primer, 50 ng of DNA template, and add ddH₂O to 25 μL. Thermal cycling: initial denaturation (98 °C, 30 s), 35 cycles (98 °C, 10 s of denaturation, 54 °C, 30 s of annealing, 72 °C, 45 s of extension, and a final extension of 72 °C for 10 min). PCR amplicons were purified by AMPure XT beads (Beckman Coulter Genomics, Danvers, MA, USA), and then the amplicons were quantified and sequenced with the Illumina NovaSeq 6000 platform (Kapa Biosciences, Woburn, MA, USA). Microbiome bioinformatics was provided by Shanghai Biotree Biotechnology Co., Ltd (Shanghai, China).

2.9 Transcriptome sequencing of the liver

Ground livers were used for total RNA extraction by using Trizol reagent (Thermo Fisher Scientific Inc., Waltham, MA, USA), following the manufacturer's procedure. The extracted RNA was assessed for quality and purity using Bioanalyzer 2100 and RNA 6000 Nano LabChip Kit (Agilent, CA, USA). After the total RNA was extracted, 5 μg of RNA was used for two rounds of purification using Dynabeads Oligo (dT) (Thermo Fisher, Waltham, CA, USA). Following purification, the RNA was fragmented, reverse-transcribed and amplified to construct the cDNA library. After library preparation, sequencing was performed on an Illumina Novaseq 6000, following the vendor's recommended protocol (Illumina, San Diego, CA, USA). The resulting data underwent quality control, read mapping, and expression analysis before further differential analysis.

2.10 Quantitative real-time PCR (RT-PCR) validation

The total RNA of the liver tissue was extracted using TRIzol, following the manufacturer's protocol (Takara Bio Co., Beijing, China). Then, the RNA was converted into cDNA and used for relative quantitative RT-PCR, as described in our earlier study.²¹ Primer sequences are listed in Table S4.† The comparative threshold cycle (Ct) method was used to analyze the results, and the results were expressed as the fold change of gene expression (2^−ΔΔCt).

2.11 Determination of hepatic energy metabolism-related metabolites and enzymes

The liver tissue was homogenized and centrifuged as previously described. The hepatic ATP content, NADH oxidase (NOX) activity, succinate dehydrogenase (SDH) activity, and ATPase activity were determined using commercially available kits (Nanjing Jiancheng Bio Co., Nanjing, China). The hepatic acetyl-CoA (ACA) content was determined using the Acetyl-CoA ELISA kit (Nanjing Boyan Biotechnology Co. Ltd, Nanjing, China). The NAD⁺/NADH content was determined using commercially available kits (Beyotime Biotechnology Inc., Shanghai, China).

2.12 Statistical analysis

All statistical analysis was accomplished using SPSS Statistics software version 26.0 (SPSS, Chicago, IL, USA). One-way analysis of variance (ANOVA) was used to test for differences between the means. Different lowercase letters indicate significant differences (p < 0.05). The data are expressed as the mean ± standard deviation (SD).

3. Results and discussion

3.1 FBDF changed the body weight, tissue weight and Lee's index

The changes of body weight are shown in Fig. 1A. In week 0, the body weights of the HFD group, RBDF group and FBDF group were all significantly higher than that of the ND group (p < 0.05). After RBDF and FBDF intervention for 12 weeks, the body weights of the mice were significantly decreased, especially the FBDF treatment. As shown in Table 1, the final body weight and Lee's index of the HFD group were markedly elevated compared with that of the ND group. Notably, the final body weight and Lee's index of the RBDF and FBDF groups were significantly reduced in comparison with the HFD group. The epididymal white adipose tissue (WAT) weight and liver weight were also higher than those of the ND group. RBDF and FBDF intervention reversed the changes that arose from HFD, and the epididymal WAT weight and liver weight were reduced. In addition, there was no difference in the food intake among the three groups HFD, RBDF and FBDF. Meanwhile, in the ND group, the food intake was higher than those of others (p < 0.05). Overall, these results indicated that the groups supplemented with RBDF and FBDF considerably inhibited HFD-induced weight gain, while FBDF exhibited better improvement.

Fig. 1 Effects of FBDF and RBDF on obesity indicators in mice. (A) Body weight changes during dietary intervention, (B) fasting blood glucose levels, (C) serum insulin levels, (D) area under the blood glucose change curve, (E) changes in blood glucose levels after oral administration of glucose, (F) HOMA-IR, (G) serum TG, (H) serum TC, (I) serum LDL, (J) serum HDL, (K) liver TG; (L) liver TC, (M) liver glycogen. The homeostasis model assessment of insulin resistance (HOMA-IR) was calculated as follows: fasting insulin (ng mL⁻¹) × fasting glucose (mmol L⁻¹)/22.5. Different letters above the bars indicate significant differences (p < 0.05).

Table 1 Body weight and tissue weight for mice in each group at the end of the experiment

Parameter	ND	HFD	RBDF	FBDF
Values are expressed as mean ± SD. Values in the same line with different letters were considered significantly different (P < 0.05). Lee's index as [body weight (g)^1/3 × 1000/body length (cm)]. WAT: white adipose tissue.
Body weight (g)	27.73 ± 0.70^c	43.27 ± 3.69^a	35.36 ± 2.68^b	33.56 ± 1.83^b
Body length (snout-anus) (cm)	8.00 ± 0.13^b	8.53 ± 0.28^a	8.39 ± 0.15^a	8.31 ± 0.29^a
Lee's index	378.42 ± 7.72^b	411.83 ± 18.11^a	391.10 ± 12.05^b	388.44 ± 12.48^b
Epididymal WAT (%)	1.59 ± 0.64^c	5.91 ± 0.67^a	3.39 ± 1.76^b	3.38 ± 1.13^b
Liver weight (g)	0.90 ± 0.05^c	1.28 ± 0.18^a	1.24 ± 0.22^ab	1.11 ± 0.14^b
Liver index (%)	3.26 ± 0.18^ab	2.94 ± 0.22^b	3.55 ± 0.71^a	3.32 ± 0.37^ab
Food intake (g per day per rat)	2.95 ± 0.23^a	2.63 ± 0.20^b	2.78 ± 0.29^ab	2.50 ± 0.24^b

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High fat diet feeding causes the body weight to increase, resulting in the accumulation of fat in the liver and other organs.²² Our results were in accordance with these observations. FBDF and RBDF intervention could significantly reduce the body weight, epididymal WAT weight and liver weight caused by the high fat diet without affecting the food intake of mice, and the effects of FBDF were better. Zheng et al. found that highland barley dietary fiber significantly reduced body weight and ameliorated tissue damage in HFD-fed mice, indicating the role of barley dietary fiber as a dietary supplement for the interventions of obesity,²³ which was consistent with our study. In addition, our previous study revealed that Lp. plantarum dy-1 fermentation changed the structure of FBDF and promoted the release of bound phenolics,¹⁸ thereby improving the functional properties. Herein, FBDF fermented by Lp. plantarum dy-1 enhanced the effects of anti-obesity, largely due to the facilitated release of bound phenolics by Lp. plantarum dy-1.

3.2 FBDF changed the glucose homeostasis and serum lipid levels

The impacts of FBDF and RBDF treatment on impaired glucose homeostasis are shown in Fig. 1B–F. The contents of serum fasting blood glucose and fasting insulin, as well as the OGTT and HOMA-IR, were determined. The fasting blood glucose level, fasting insulin level, OGTT_AUC value and HOMA-IR index in the HFD group were significantly higher than those of the ND group (p < 0.05), confirming the impaired glucose and insulin tolerance in HFD-induced rats. The RBDF and FBDF groups exhibited significant reductions in fasting blood glucose level compared to the HFD group. The treatment with RBDF and FBDF reduced the fasting insulin levels and OGTT_AUC values, although there were no significant differences compared with the HFD group. The FBDF intervention was observed to improve the insulin sensitivity as the HOMA-IR index showed. Notably, the reduction effects of FBDF intervention on the fasting blood glucose level and HOMA-IR value were more obvious than those of the RBDF treatment.

Fig. 1G–J illustrates the levels of TG, TC, LDL and HDL in the serum. Compared with the NC group, mice in the HFD group had significantly higher serum TG, TC, LDL and HDL levels (p < 0.05). After FBDF intervention, the TG level of mice was significantly reduced (p < 0.05), while the TC, LDL and HDL levels showed no statistical differences (p > 0.05). The RBDF treatment also can decrease the serum TG level, but with no significant difference when compared with the HFD group. The results indicated that FBDF had the better effects on lowering serum lipid levels.

Glucose and lipid metabolism disorder is a typical complication of metabolic syndrome such as obesity.²⁴ The results show that FBDF reversed HFD-induced glucose intolerance and lipid accumulation in the serum, and the effects were better than those of RBDF. Previous studies have shown that the intake of dietary fiber can alleviate hyperglycemia and hyperlipidemic symptoms. Okara insoluble dietary fiber was shown to alleviate HFD-induced hyperlipidemia, glucose intolerance and insulin resistance,⁷ which was consistent with our study. Additionally, we found that fermentation enhanced the hypoglycemic and hypolipidemic effects of barley dietary fiber. This result was consistent with the findings of Zhang et al., which showed that Lp. plantarum dy-1 fermentation significantly improved the lipid metabolism regulating effects of barley in high-fat diet-induced obese rats.²⁵ Meanwhile, Lp. plantarum dy-1 fermentation changed the microstructure and monosaccharide components, and improved the water-holding capacity and oil retaining capacity of FBDF,¹⁸ thereby reducing dietary lipid absorption into the small intestine, facilitating the maintenance of serum lipid levels.¹⁹ Thus, the FBDF showed better efficacy in alleviating hyperlipidemia, which was attributed to the improved physicochemical properties of dietary fiber.

3.3 FBDF changed the lipid accumulation in liver and adipose tissue

Liver is a crucial organ in the maintenance of metabolism, and HFD is one of the major causes of fatty liver disease.²⁶ H&E staining images of liver tissue sections are shown in Fig. 2A. The livers of mice in the HFD group revealed an increased number of lipid droplets created by liver steatosis, and seemed to be a fatty liver phenotype. While RBDF and FBDF treatment dramatically alleviated the hepatic steatosis, especially the FBDF group, the lipid deposition and fat vacuolation in the liver were reduced. Furthermore, liver TG levels in the RBDF and FBDF groups were considerably lower compared with those in the HFD group (p < 0.05) (Fig. 1K). Compared with the HFD group, the liver TC levels and liver glycogen content of the RBDF and FBDF groups showed no significant difference (p > 0.05) (Fig. 1L–M). Interestingly, FBDF treatment inhibited liver lipid accumulation more effectively in the HFD fed mice. Overall, FBDF supplementation effectively reversed the fat accumulation in the liver induced by HFD, and the result was in agreement with the report of Ni et al.²⁷ This could be because the adsorption and viscosity of FBDF was beneficial in hindering the absorption of dietary fat, resulting in reduced fat accumulation in the liver.

Fig. 2 H&E staining sections of the (A) liver, (B) abdominal white adipose tissue, and (C) brown adipose tissue (×200).

The abdominal white adipose tissue sections and brown adipose tissue sections were also stained with H&E. As shown in Fig. 2B, the size of the abdominal white adipocytes in the HFD group increased compared with that of the ND group. RBDF and FBDF intervention can alleviate HFD-induced adipocyte hypertrophy. Meanwhile, the adipocyte structure and size in the FBDF group were similar with that of the NC group. In addition, the intervention of BDF, particularly FBDF, can alleviate the vacuolation and size of brown adipocytes (Fig. 2C). The results showed that FBDF could markedly improve white adipocyte hypertrophy and brown adipocyte vacuolation caused by HFD. The results were consistent with a previous study, which showed that okara insoluble dietary fiber treatment markedly improved white adipose tissue hypertrophy caused by HFD.⁷ Previous studies have shown that brown adipose tissue is a potential treatment for obesity due to the thermogenic activity capacity and energy expenditure.²⁸ Xiao et al. found that fermented barley extracts remarkable decreased the cell size of brown adipose tissues, and promoted the adipose tissue browning via activating the uncoupling protein 1 (UCP-1)-dependent pathway to suppress the obesity.²⁰ FBDF showed the capacity of reducing the fat vacuolation of brown adipocytes, indicating that fermented dietary fiber can activate brown adipose tissue thermogenesis and increase energy expenditure to alleviate obesity caused by HFD.

3.4 Effects of Lp. plantarum dy-1 fermentation on SCFAs concentration

SCFAs are the main metabolites produced by gut microbiota during the fermentation of DF, and play an important role in the maintenance of health.²⁹ As shown in Fig. 3A–G, the concentrations of acetate, propionate, butyrate, isobutyrate, valerate, isovalerate and total SCFAs in fecal samples were measured. Compared with the ND group, the contents of propionate and total SCFAs were markedly reduced in the HFD group (p < 0.05). Treatment with RBDF and FBDF increases the contents of SCFAs in fecal samples. In particular, the contents of propionate and total SCFAs were significantly higher than those of the HFD group (p < 0.05), suggesting their potential prebiotic effects. Moreover, the FBDF group exhibited higher total SCFAs, acetate, propionate and isobutyrate than the RBDF group, which indicated that FBDF had the better function of increasing the SCFAs levels.

Fig. 3 Effects of RBDF and FBDF on the short-chain fatty acids levels in mice: (A) acetate, (B) propionate, (C) butyrate, (D) isobutyrate, (E) valerate, (F) isovalerate, and (G) total SCFAs. Different letters above the bars indicate significant differences (p < 0.05).

Previous studies have shown that SCFAs play a critical role in gut health, and influence the metabolism of tissue or organs (such as liver and adipose tissue).²⁵ SCFAs can inhibit the synthesis of cholesterol, and then improve the cholesterol metabolism in the body.³⁰ SCFAs can also activate G protein-coupled receptor 43 (GPR43) and reduce lipid accumulation in white adipose tissue.³¹ SCFAs, such as butyrate, provide energy to the intestinal epithelium, and reduce bacterial translocation and intestinal inflammation.³² The results showed that the contents of individual SCFAs and total SCFAs were improved in the FBDF and RBDF groups. Furthermore, the FBDF group had the better elevation, on account of the fermentation changing the structure and fermentation characteristics of dietary fiber. Therefore, we speculate that Lp. plantarum dy-1 fermentation may improve the gut probiotic effects and reduce the obesity-related phenotype by increasing the production of SCFAs in HFD-induced obese mice.

3.5 FBDF regulated the profile of gut microbiota

Fig. S1† shows the results of α-diversity and β-diversity analysis. The Chao1 and observed species indexes represent the bacterial abundance, and the Shannon and Simpson indexes represent the bacterial diversity. Compared with the ND group, the observed species and Chao1 indexes were significantly reduced by 25.27% and 25.88% (p < 0.05), respectively, which were alleviated by the intervention of BDF (Fig. S1A and B†). Meanwhile, the FBDF group exhibited higher observed species and Chao1 indexes than the RBDF group, suggesting that Lp. plantarum dy-1 fermentation can regulate the effects of BDF on gut microbiota abundance. The Shannon and Simpson indexes showed no statistical differences (p > 0.05). For β-diversity, principal coordinates analysis (PCoA) demonstrated a notable separation among the ND, HFD, RBDF and FBDF groups (Fig. S1E†), demonstrating that RBDF and FBDF treatment influenced the gut microbiota composition.

The overall structure of the gut microbiota was examined at the phylum and genus levels (Fig. 4). As shown in Fig. 4A, the gut microbiota was mainly composed of Firmicutes, Bacteroidota, Desulfobacterota, Proteobacteria and Actinobacteriota at the phylum levels. The HFD group exhibited a higher abundance of Firmicutes and a lower abundance of Bacteroidota (Fig. 4B and C). Moreover, the Firmicutes/Bacteroidota ratio was also higher when compared with the ND group (Fig. 4D). However, there were no statistical differences (p > 0.05). Interestingly, FBDF treatment decreased the relative abundance of Firmicutes and increased the relative abundance of Bacteroidota. Furthermore, the Firmicutes/Bacteroidota ratio was significantly lower than that of the HFD group (p < 0.05). Finally, the effects of RBDF on the relative abundance of gut microbiota at the phylum levels were different from those of FBDF.

Fig. 4 Effects of RBDF and FBDF on the structure of the gut microbiota in mice. (A) Relative abundances of the gut microbiota at the phylum level. (B and C) Relative abundances of Firmicutes and Bacteroidota. (D) Firmicutes/Bacteroidota ratio. (E) Heatmap of the top 30 taxa at the genus level. (F–M) Relative abundances of Muribaculaceae, Clostridiales, Desulfovibrionaceae, Enterorhabdus, Bacteroides, Escherichia–Shigella, Akkermansia and Lachnoclostridium. Different letters above the bars indicate significant differences (p < 0.05).

The heatmap of the top 30 genera in the abundance of each group are shown in Fig. 4E. In comparison with the ND group, the abundances of Lactobacillus, Dubosiella, Muribaculaceae, Muribaculum and Mucispirillum were decreased, and the abundances of Desulfovibrionaceae, Robinsoniella, Ileibacterium, Colidextribacter, Clostridiales and Escherichia–Shigella were increased in the HFD group. We found that the FBDF groups enhanced the relative abundance of Muribaculaceae, Enterorhabdus, Bacteroides, Akkermansia and Lachnoclostridium (p < 0.05), while the relative abundance of Escherichia–Shigella, Desulfovibrionaceae and Clostridiales were decreased (Fig. 4F–M). Furthermore, we discovered that RBDF can significantly decrease the relative abundance of Escherichia–Shigella and Desulfovibrionaceae (p < 0.05). However, it exhibited no regulatory effects on Muribaculaceae, Lachnoclostridium or Akkermansia (p > 0.05).

Gut microbiota has been identified as an important factor involved in the development of obesity.^33,34 Previous studies showed that HFD caused an increase in the relative abundance of Firmicutes and a decrease in Bacteroidota.³⁵ Our results were in agreement with these findings. Moreover, HFD elevated the ratio of Firmicutes/Bacteroidota of the gut microbiota.³⁶ While FBDF and RBDF revealed diverse impacts on the abundance of these bacteria at the phyla level, FBDF treatment decreased the relative abundance of Firmicutes and increased Bacteroidota, and decreased the Firmicutes/Bacteroidota ratio. This suggests that FBDF may be more effective than RBDF in improving the gut microbiota composition at the phylum level, potentially contributing to their anti-obesity effects.

Muribaculaceae produces SCFAs via endogenous (such as mucin glycans) and exogenous polysaccharides (such as dietary fibers), and exhibits a cross-feeding relationship with probiotics, such as Bifidobacterium and Lactobacillus.³⁷ The increased abundance of Muribaculaceae showed alleviating effects on obesity and type 2 diabetes. Thus, Muribaculaceae is a potential probiotic bacterial family.³⁸ After mice were HFD fed, the abundance of Muribaculaceae was decreased. Meanwhile, FBDF intervention reversed the decrease of Muribaculaceae. These results were consistent with those found by Zhang et al.,¹⁹ suggesting that the alleviated obesity-related symptoms from FBDF treatment are associated with increased Muribaculaceae abundance. Akkermansia is a next-generation probiotic, which functions mainly by maintaining the integrity of the intestinal barrier and improving metabolic pathways.³⁹Akkermansia also showed the effects of ameliorating obesity induced by diet, and the FBDF group demonstrated that a higher abundance of Akkermansia could be beneficial to improve obesity. Bacteroides are known as a group of polysaccharide-degrading bacteria and the principal products are SCFAs.⁴⁰Lachnoclostridium possesses the ability to produce SCFAs, especially butyrate, through which microbiota influence the host physiology.⁴¹ Notably, the FBDF group revealed an enriched abundance of Bacteroides and Lachnoclostridium. This aligns with our previous findings of in vitro fecal fermentation and the SCFAs levels. Furthermore, the relative abundance of Desulfovibrionaceae was positively correlated with obesity-induced inflammation.⁴² FBDF and RBDF treatment decreased the abundance of Desulfovibrionaceae, demonstrating the beneficial anti-obesity effects. FBDF supplementation improved the gut microbiota composition, and especially enhanced the abundance of probiotic and SCFA-producing bacteria, such as Akkermansia, Muribaculaceae and Bacteroides. Meanwhile, RBDF exhibited regulatory effects on harmful bacteria Escherichia–Shigella and Desulfovibrionaceae. The reasons might be due to the better physicochemical properties and fermentation characteristics of FBDF, which were beneficial to the growth of probiotic and SCFA-producing bacteria.

3.6 FBDF regulated the hepatic gene expression profile

To determine the effects of RBDF and FBDF treatment on the liver, the hepatic gene expression was analyzed by RNA sequencing. The RBDF group exhibited 98 upregulation genes and 208 downregulation genes compared to the HFD group, and the FBDF group showed 125 upregulation genes and 612 downregulation genes compared with the HFD group (Fig. 5A, C). Simultaneously, 223 regulated genes were identified between the FBDF and RBDF groups. A total of 12 differentially expressed genes (DEG) were randomly selected for RT-PCR verification, as shown in Fig. 5B and Fig. S2.† The relative expressions of the genes were consistent with the transcriptome results, indicating that the RNA sequencing results were highly reliable.

Fig. 5 Effects of RBDF and FBDF on the hepatic transcriptome. (A) Numbers of differentially expressed genes (DEG) between the different groups. (B) Sequencing results of partial DEG in FBDF vs. RBDF. (C) Heatmap showing the DEG expression levels. (D–F) The enriched GO biological processes of DEG on the hepatic transcriptome. Different letters above the bars indicate significant differences (p < 0.05).

Gene set enrichment analysis (GSEA) can effectively improve the shortcomings of traditional enrichment analysis, and more comprehensively explain the regulatory role of a certain functional unit. Based on the GSEA analysis principle, GO analysis was conducted on the DEG. Fig. 5 displays the 15 functions related to metabolism. Compared with the HFD group, the expression levels of genes related to mitochondrial respiratory chain complex I, negative regulation of lipid storage, NADH dehydrogenase activity, aerobic respiration, energy reserve metabolic processes and mitochondrial ribosome biological processes in the liver of the RBDF group were significantly up-regulated (Fig. 5D). The expression levels of genes related to fatty acid biosynthesis, lipid biosynthesis, lipid droplet, steroid biosynthesis and cholesterol biosynthesis were significantly down-regulated. Additionally, FBDF and RBDF exhibited similar regulatory effects. The FBDF interventions particularly affected the expression levels of genes related to the energy reserve metabolism, cytochrome c oxidase, mitochondrial proton transporting ATP synthetase complex, and mitochondrial respiratory chain complex I (Fig. 5E). In addition, the FBDF group showed a better change in the genes associated with the expression levels of the activity of NADH dehydrogenase, mitochondrial respiratory chain complex I, lipoprotein metabolism, fatty acid biosynthesis, adipocyte differentiation, unsaturated fatty acid biosynthesis and negative regulation of insulin secretion (Fig. 5F), suggesting that FBDF has better effects in regulating the energy metabolism and lipid metabolism.

Pathway analysis showed that the RBDF and FBDF treatment can up-regulate the expression levels of genes related to energy metabolism, such as aerobic respiration and oxidative phosphorylation, and significantly inhibit the genes related to lipid biosynthetic metabolism. Mitochondrial respiratory chain complex I is the largest membrane-bound enzyme of the mitochondrial oxidative phosphorylation system in the cell.⁴³ NADH dehydrogenase is also a kind of membrane-bound enzyme that is responsible for NADH oxidation in the terminal of electron transport systems, transferring electrons from NADH to ubiquinone in the mitochondria.⁴⁴ Cytochrome c oxidase is the key enzyme of aerobic respiration, as the terminal electron acceptor of the respiratory chain in the mitochondrion.⁴⁵ Mitochondrial proton transporting ATP synthetase complex can convert the energy of oxidation–reduction reactions of the electron transport chain to synthesize ATP.⁴⁶ In our study, the expressions of mitochondrial respiratory chain complex I, NADH dehydrogenase, cytochrome c oxidase and mitochondrial proton transporting ATP synthetase complex were up-regulated by FBDF treatment. This suggests that FBDF intervention is beneficial to hepatic aerobic respiration and oxidative phosphorylation. Our previous study also found that barley extracts fermented by Lp. plantarum dy-1 enhanced the dehydrogenase activity in the mitochondria and the adipose tissue thermogenesis in obese rats.²⁰ Yeast β-glucan supplementation reversed hepatic mitochondrial dysfunction and improved oxidative phosphorylation in obese type 2 diabetic mice.⁴⁷ Thus, we postulated that the efficacy of FBDF in alleviating oxidative phosphorylation was attributed to the abundant β-glucan and other polysaccharides in barley dietary fiber. Furthermore, Lp. plantarum dy-1 fermentation was beneficial in enhancing the effects of FBDF, which were better than those of RBDF.

3.7 Effects of Lp. plantarum dy-1 fermentation on hepatic energy metabolism-related metabolites and enzymes

Based on the hepatic RNA sequencing, the genes related to energy metabolism were up-regulated after RBDF and FBDF treatment. Thus, we speculated that RBDF and FBDF might alleviate obesity-related symptoms via improving hepatic oxidative phosphorylation. The NAD⁺/NADH ratio, and contents of ACA and ATP are important hepatic energy metabolism-related metabolites for evaluating the level of mitochondrial energy metabolism. Based on the transcriptome results, the NAD⁺/NADH ratio, contents of ACA and ATP in the liver were determined to evaluate the effects of FBDF on regulating the intermediate metabolites of hepatic energy metabolism. As shown in Fig. 6A–C, compared with the ND group, the NAD⁺/NADH ratio, ACA content and ATP content in the HFD group were decreased by 25.73%, 13.42% and 17.86%, respectively. After intervention with FBDF, the ACA content, NAD⁺/NADH ratio and ATP content were significantly increased by 29.14%, 14.93% and 47.91%, respectively. Conversely, there was no significant difference in hepatic energy metabolism-related metabolites in the RBDF group.

Fig. 6 Levels of hepatic energy metabolism-related metabolites and enzymes. (A) Contents of ACA. (B) Contents of ATP. (C) Contents of NAD⁺/NADH. (D) Enzyme activity of SDH. (E) Enzyme activity of NOX. (F) Enzyme activity of ATPase. Different letters above the bars indicate significant differences (p < 0.05).

SDH and NOX are key enzymes in the tricarboxylic acid cycle (TCA) and oxidative phosphorylation.⁴⁸ The activities of SDH, NOX and ATPase were determined to evaluate the effects of FBDF on hepatic energy metabolism-related enzymes. As shown in Fig. 6D–F, compared with the ND group, the NOX activity in the HFD group was significantly decreased (p < 0.05). The FBDF treatment increased the activities of SDH, NOX and ATPase by 44.33%, 32.51% and 27.11%, respectively (p < 0.05). Compared with the HFD group, the activities of SDH, NOX and ATPase in the RBDF group were increased by 9.10%, 11.70% and 12.55%, respectively, but the differences were not significant.

SDH, as the key enzyme in the TCA and respiratory electron transfer chain, reveals the activity of the mitochondria oxidative phosphorylation.⁴⁹ NOX can catalyze the oxidation of NADH through the oxidative phosphorylation pathway to produce electrons.⁵⁰ Impairment of oxidative phosphorylation can lead to a decrease in cellular ATPase synthesis and activity, leading to a decrease in energy metabolism.⁵¹ This study demonstrated that RBDF and FBDF treatment can improve the activities of SDH, NOX and ATPase, and the effects of FBDF were better than those of RBDF. Thus, the results suggested that FBDF may enhance the oxidative phosphorylation in liver mitochondria by improving the activities of hepatic energy metabolism-related enzymes, which is consistent with the hepatic RNA sequencing results.

4. Conclusion

In conclusion, Lp. plantarum dy-1 fermented dietary fiber showed higher bioactivities on alleviating obesity-symptoms in HFD-induced obese mice, as represented by reducing the body weight and fat accumulation in liver and epididymal WAT, improving HFD-induced hyperlipidemia and glucose intolerance, and increasing the SCFA levels of feces. Both FBDF and RBDF supplementation improved the gut microbiota composition. FBDF especially enhanced the abundance of probiotic and SCFA-producing bacteria, while RBDF exhibited no regulatory effects on beneficial bacteria. Additionally, FBDF up-regulated the expression of genes related to energy metabolism, and improved the activities of hepatic energy metabolism-related enzymes. Therefore, these findings indicated the potential of FBDF for improvement of obesity symptoms and utilization as a health food resource.

Data availability

The authors confirm that the data supporting the findings of this study are available within the article.

Conflicts of interest

There are no conflicts of interest to declare.

Acknowledgements

This research was partially funded by the National Natural Science Foundation of China (32072200, 32472305), Jiangsu Provincial Key Research and Development Program (BE2022353), Zhenjiang Innovation Capacity Construction Plan – Construction of Discipline Key Laboratories (SS2024005), and the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD).

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Footnote

† Electronic supplementary information (ESI) available. See DOI: https://doi.org/10.1039/d4fo04776a

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