A bicinchoninic acid (BCA) protein quantitative kit (PC0020), and a hepatic TG assay kit (BC0625), fenofibrate (IF0040-500 mg, purity ≥ 99%), and phosphate buffered saline (PBS) powder were bought from Beijing Solarbio Science & Technology Co., Ltd. (Beijing, China). Assay kits for hepatic cholesterol and free fatty acid (FFA) were the products of Shanghai Lengton Bioscience Co., Ltd. (Shanghai, China). Assay kits for plasma total cholesterol (TC), high density lipoprotein (HDL) cholesterol (HDL-C), and TG were bought from Biosino Bio-technology and Science Incorporation (Beijing, China). Pellets of complete protease inhibitor were the product of Roche (Schweiz, Germany). Deionized water was obtained from a Milli-Q gradient system (Bedford, MA). The remaining reagents used in this study were of the analytical grade.

Several previous studies suggest that the TG-lowering drug fenofibrate has inconsistent effects on obesity due to differences in intervention time and fenofibrate dosage. As patients with obesity need a long-term intervention, it is important to clarify whether long-term fenofibrate treatment benefits obesity using the well-acknowledged ob/ob mouse model. In this study, ob/ob mice were fed with a typical Western diet (as described later) for more than 3 months. Considering the potential side effects and the long-term intervention (22), the dosage of fenofibrate was determined as 20 mg/kg/d rather than 100 or 300 mg/kg/d that are used in short-term interventions (19, 20). At the end of this experiment, the plasma lipid profiles, body weight, liver weight, and epididymal fat weight were used to evaluate the effect of fenofibrate on lipid deposition in combination with other analysis methods. To investigate the underlying mechanisms, real-time quantitative polymerase chain reaction (RT-qPCR) and Western Blotting experiments were used for determining the expression of lipid metabolism-related genes and proteins, respectively. As accumulating evidence have demonstrated that gut microbiota may modulate obesity (10, 23), the effect of fenofibrate on gut microbiota in ob/ob mice was also analyzed in the present study.

This study was approved by the laboratory animals′ ethical committee of Shandong First Medical University (W202204150222). Ob/ob mice (male, 42–56 days old) were bought from Beijing HFK Bioscience Co., Ltd. (Beijing, China; License number: SCXK 2019-0008). High-fat chow was the product of Research Diets Inc. (Product #D12492, New Brunswick, NJ, USA). This chow was composed of casein (30 mesh, 200 g), L-cystine (3 g), maltodextrin 10 (125 g), sucrose (68.8 g), cellulose (BW200, 50 g), soybean oil (25 g), lard (245 g, containing 0.72 mg/g of cholesterol on average), mineral mix (S10026, 10 g), dicalcium phosphate (13 g), calcium carbonate (5.5 g), potassium citrate∙1 H₂O (16.5), vitamin mix V10001 (10 g), choline bitartrate (2 g), and FD & C blue dye #1 (0.05 g). In this chow diet, protein, carbohydrate, and fat provide 20, 20, and 60% of the total calorie, respectively. After 7 days′ adaptive feeding, mice were randomly divided into two groups (eight mice in each group): the vehicle group (Vehicle, water by gavage) and the fenofibrate group (Fenofibrate, 20 mg/kg/d by gavage). Of note, fenofibrate is insoluble in water. Sodium carboxy methyl cellulose solution is generally used for preparation of suspension liquid when drugs are water-insoluble. However, carboxy methyl cellulose may affect the body weight and lipid profiles of the treated animals at the concentration of 2% (24). To eliminate the potential interference of the solvent medium, fenofibrate was made into suspension liquid (prepared every 2 days) via vortex with water before gavage. The average food intake and body weight were recorded weekly.

After 13-weeks intervention, the mice were anesthetized with 0.5% pentobarbital sodium by intraperitoneal injection (0.3 mL per mouse) after 12 h fasting. Blood was collected from the orbital sinus using heparinized capillary tubes under anesthesia. To remove the residual blood, the animals were perfused with ~10 mL of sterilized PBS through left ventricle before tissue sampling (25). To prevent potential contamination, the ileum and colon contents containing gut microbiota were carefully sampled in a horizontal flow clean bench. These ileum and colon contents were immediately frozen in liquid nitrogen and mailed to the Applied Protein Technology company with the protection of dry ice (Shanghai, China). Liver and epididymal fat were weighted, cut into pieces, and kept at −80°C before use. Liver or epididymal fat index was calculated according to the following formula: organ index = [(organ weight × 100%) ÷ body weight].

Freshly sampled blood was centrifugated at 3,000 × g for 15 min at 4°C to obtain plasma. The levels of TC, TG, and HDL-C in the plasma were determined by the corresponding assay kits according to the manufacturers′ instructions. The absorbance of the samples was recorded on a Tecan Infinite 200 type multifunctional microplate reader (Molecular Devices, Lagerhausstrasse, Austria). Non-HDL-C was calculated by TC minus HDL-C. Additionally, 100 μL of mixed plasma in each group was separated by a Superose^TM 6 10/300 gel chromatography column that was linked to an ÄKTA fast protein liquid chromatography (FPLC) system. The column was eluted with mobile phase (0.9% NaCl) at a flow rate of 0.3 mL/min. The eluent was collected with an automatic collector with 0.5 mL in each fraction. In this study, 28 fractions were collected and the TC and TG levels in the very low-density lipoprotein (VLDL) and LDL fractions were determined by the commercially available assay kits.

Approximately 100 mg of liver was homogenized in 9-fold (w/v) freshly prepared PBS using a tissue grinder. The supernatant obtained after centrifugation at 1,100 × g for 10 min at 4°C was diluted at different ratio using PBS and then used to determine the concentration of TC, TG, and FFA according to the manufacturers' instructions. The protein content in each sample was determined by the BCA assay kit.

The H & E experiment was carried out according to a previous publication (26). Liver samples were fixed in 4.0% paraformaldehyde at 4°C for 24 h and then embedded in paraffin. Approximately 5 micro-thick sections were cut with a sliding microtome (Leica, Germany). The slices were deparaffinized with xylene and gradient ethanol solutions, and then rinsed in distilled water for a few seconds. The nuclei were stained with heamatoxylin for 60 s, rinsed in distilled water, differentiated with acid alcohol (0.3%) for a few seconds, and then rinsed in distilled water for a few seconds. In the following, the slices were stained with 0.5% eosin for 60 s, dehydrated, cleared and mounted. The stained slices were visualized using an Olympus IX51 type microscope (Tokyo, Japan), and the images were recorded with a JVC 3-CCD camera at a magnification time of 200 × . In this study, the lipid droplets with a diameter > 10 μm were used for calculation of the average lipid droplet size. Furthermore, the number of the lipid droplets with a diameter > 20 μm was counted within a randomly chosen area of 20,000 μm² in each slice for calculation of the average lipid droplet number.

Total ribonucleic acid (RNA) was isolated from the liver tissue using TRIzol reagent (CW0580s, Beijing, China) according to the manufacturer's instruction. The concentration and purity of total RNAs were measured by a nanodrop ultraviolet spectrophotometer. The total RNAs were considered to be pure if the ratio of A260/A80 > 1.90. A HiFiScript complementary deoxyribonucleic acid (cDNA) synthesis kit (CW2569M, Beijing, China) was used to prepare cDNA using 1.0 μg of total RNA that obtained from each sample. RT-qPCR was carried out in an ABI QuantStudio 3 PCR system (Thermo Fisher, USA) using an UltraSYBR mixture (low ROX) (CW2601, Beijing, China). This method was used to detect the expression of lipid metabolism-related genes including sterol regulatory element binding protein (SREBP)-1c, PPARγ, PPARα, carnitine palmitoyltransferase (CPT)-1α, CPT-2, ACOX-1, stearoyl Coenzyme A desaturase-1 (SCD-1), and fatty acid synthase (FAS) as listed in Table 1. The specific primers were synthesized by QingDao Ribo Xingke Biotechnology Co., Ltd. (Qingdao, China). The program was set as following: initial denaturation at 95°C for 10 min followed by 40 cycles of 95°C (denaturation temperature) for 10 s, 60°C (annealing temperature) for 30 s, and 72°C (elongating temperature) for 32 s. The relative expression of target gene was calculated by the method of 2^−DDCt based on the housekeeping gene glyceraldehyde-3-phosphate dehydrogenase (GAPDH).

Total proteins of the mice liver were extracted using radioimmunoprecipitation assay buffer containing complete protease inhibitor. Equal amounts of protein (~40 μg) were subjected to sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and then transferred onto polyvinylidene fluoride membranes (Millipore, ROPB61783, USA) by electroblotting (27). The membranes were first blotted with 5% of defatted milk power for 2 h at room temperature. Then, the membranes were blotted with the corresponding primary and secondary antibodies listed as follows: a mouse monoclonal antibody against SREBP-1c (2A4) (SANTA CRUZ, USA, sc-13551, 1:500), a rabbit polyclonal antibody against PPARγ (Proteintech, USA, 16643-1-AP, 1:1000), a mouse monoclonal antibody against PPARα (Abcam, USA, ab97609, 1:800), a mouse monoclonal antibody against β-actin (Abcam, USA, ab8226, 1:1000), a rabbit polyclonal antibody against LDLR (Abcam, USA, ab30532, 1:200), and secondary antibodies including a goat anti-rabbit IgG H&L (HRP) (Abcam, USA, ab6721, 1:3000) and a goat anti-mouse IgG H&L (HRP) (Abcam, USA, ab205719, 1:5000). After blotting, immunoblots were revealed by enhanced chemiluminescence solution from Millipore (WBKLS0500, USA). The images were recorded on a Clinx ChemiScope 6000 pro system (Shanghai, China). The expression of the target proteins was normalized by housekeeping protein β-actin.

As for the plasma, each 10 μL plasma sample was added with 90 μL of PBS and 20 μL 5 × loading buffer. The mixture was mixed well and heated at 80°C for 10 min. Approximately 5 (for Apo A-I) or 10 μL (for Apo B) plasma medium was subjected to 12.5% (for Apo A-I) or 6% (Apo B) SDS-PAGE. Finally, the membranes were botted with the corresponding primary and secondary antibodies listed as follows: a rabbit polyclonal antibody against albumin (Proteintech, 16475-1-AP, Wuhan, China, 1:10,000), a mouse monoclonal antibody against Apo A-I (Proteintech, 66206-1-Ig, Wuhan, China, 1:1000), and a rabbit polyclonal antibody against Apo B (Proteintech, 20578-1-AP, Wuhan, China, 1:800). The expression of the target proteins was normalized by albumin.

Total genomic deoxyribonucleic acid (DNA) was extracted from the fecal samples using CTAB/SDS method. The concentration and purity of DNA were determined by 1.0% agarose gel electrophoresis. The concentration of DNA was adjusted to 1.0 μg/mL using sterile water. The V3-V4 region of the 16S rRNA genes were amplified using the 341F-806R primers. PCR products were purified with an AxyPrepDNA gel extraction kit (AXYGEN). Sequencing library was generated using a NEB Next^® Ultra^TM DNA library Prep Kit for Illumina (NEB, USA) following the manufacturer's instructions. Finally, the library was sequenced on an Illumina Miseq/HiSeq2500 platform and 250/300 bp paired-end reads were generated. The paired-end reads were assigned to each sample based on the unique barcodes. Sequence analysis was carried out by the UPARSE software package using the UPARSE-OTU and UPARSE-OTUref algorithms.

All the bioassay results were expressed as mean ± standard deviation (SD) for at least three independent experiments. Statistical analysis was performed by Student-t-test, and the differences were considered to be significant at a p < 0.05.

In this study, one ob/ob mouse in the vehicle group was removed from the final statistical analysis due to a great body weight loss induced by an unknown reason (Supplementary Data 1). As shown in Figure 1A, the beginning body weight of the mice in the vehicle and fenofibrate group had no significant difference. The high-fat diet induced ~40% body weight gain in mice. However, the final body weight of the mice in the vehicle and fenofibrate group showed no significant difference. Furthermore, fenofibrate intervention had no obvious influence on the food intake of the mice (Figure 1B). In the plasma, fenofibrate treatment dramatically decreased the TG level by ~21.0% compared to that of vehicle group (Figure 1C, p < 0.05). However, fenofibrate intervention had no significant effect on the levels of TC, HDL-C, and non-HDL-C (Figures 1D–F). The results of ÄKTA FPLC demonstrated that fenofibrate lowered the levels of TG in both VLDL and LDL fractions (Figure 1G) compared with the vehicle group, which were consistent with the reduced plasma TG level in the fenofibrate group. In this study, fenofibrate decreased the cholesterol level in the LDL fractions and increased the cholesterol level in the VLDL fractions (Figure 1H). This result was consistent with the non-significant difference of the plasma TC and non-HDL-C between vehicle and fenofibrate groups (Figures 1D,F). Additionally, fenofibrate showed no effect on the expression of Apo A-I (Figure 3A) and Apo B48 proteins (Figure 3B). However, fenofibrate intervention significantly reduced the expression of Apo B100 by ~107.5% (Figure 3B, p < 0.05).

As shown in Figure 2A, fenofibrate intervention obviously increased the liver index by ~31.7% compared to the vehicle group (p < 0.05). Of note, fenofibrate intervention significantly increased the lipid accumulation in the liver (Figure 2C). In this study, the lipid droplet with a diameter > 10 μm was analyzed for comparation of the lipid droplet size, and the results demonstrated that fenofibrate increased the lipid droplet size by 71.2% compared to the vehicle group (Figure 2B, p < 0.01). Furthermore, the average number of the lipid droplet with a diameter > 20 μm per 20,000 μm² in fenofibrate group was ~3.3-fold of that in the vehicle group (Figure 2D, p < 0.01). In line with these findings, fenofibrate intervention increased TG content from 42.0 ± 11.3 μg/g protein to 63.9 ± 10.8 μg/g protein in the liver (Figure 2E, p < 0.05). However, the content of TC and FFA in the liver had no significant difference between the vehicle group and fenofibrate group (Figures 2F,G).

LDLR plays a key role in clearance of LDL and VLDL particles from the circulation (10). In the present study, fenofibrate significantly increased the expression of LDLR protein by ~3.7-fold compared to the vehicle group (Figure 3C, p < 0.01). As a PPARα agonist, fenofibrate intervention significantly increased the expression of PPARα protein by 46.3% compared with the vehicle group (Figure 3D, p < 0.05). Of note, fenofibrate treatment dramatically increased the expression of PPARγ protein by ~2.1-fold in the liver of the ob/ob mice compared to the vehicle group (Figure 3E, p < 0.01). Furthermore, fenofibrate enhanced the expression of the precursor and cleaved SREBP-1c by ~88.5% (p < 0.05) and 97.3% (p < 0.01), respectively (Figure 3F).

Compared with the vehicle group, fenofibrate had no significant effects on the gene expression of PPARα, ACOX-1, CPT-1α, and CPT-2 (Figures 4A–D). However, fenofibrate significantly increased the gene expression of PPARγ by ~31% and elevated the gene expression of SREBP-1c by ~83% (Figures 4E,F, p < 0.05). Furthermore, fenofibrate dramatically enhanced the gene expression of SCD-1 and FAS by 1.8- and 2.2-fold, respectively (Figures 4G,H, p < 0.05).

In this study, fenofibrate treatment significantly elevated the fat index by 44.6% compared to the vehicle group (Figure 5A, p < 0.01). In the white adipose tissue, fenofibrate intervention significantly increased the expression of PPARα protein by 4.18-fold compared with the vehicle group (Figure 5B, p < 0.05). Of note, fenofibrate treatment dramatically enhanced the expression of PPARγ and SREBP-1c proteins by 7.45- and 4.71-fold, respectively (p < 0.01, Figures 5C,D).

Gut microbiota is correlated with TC and TG metabolism (10, 23, 28). The rank-abundance curves (Figure 6A) and the species accumulation curves (Figure 6B) demonstrated that species richness of the gut microbiota was great enough in this study. Of note, a lower number of OTU was observed in fenofibrate intervention group compared to that of vehicle group (Figure 6C). The α-diversity (Figure 6D) and β-diversity analysis (Figure 6E) suggested that the species in the fenofibrate group have a greater dispersion and a lower value of median number. The principal co-ordinates analysis (PCoA) showed that the microbiota species have a mild difference between fenofibrate and vehicle group (Figure 6F). The top 10 microbiota species in different classification levels including phylum, class, order, family, genus, and species, were shown in Figure 7. Of note, fenofibrate intervention elevated the average relative abundance of p_Firmicutes (0.584 ± 0.145 vs. 0.457 ± 0.076) and reduced the p_Bacteroidetes (0.085 ± 0.095 vs. 0.144 ± 0.156) and p_Actinobacteria (0.015 ± 0.019 vs. 0.035 ± 0.067) at the phylum level; it increased the average relative abundance of c_Clostridia (0.544 ± 0.146 vs. 0.384 ± 0.082, p < 0.05) and decreased c_Bacteroidia (0.085 ± 0.095 vs. 0.144 ± 0.156) and c_Erysipelotrichia (0.037 ± 0.039 vs. 0.067 ± 0.008) at the class level; fenofibrate elevated the average relative abundance of o_Clostridiales (0.544 ± 0.146 vs. 0.384 ± 0.082, p < 0.05) and reduced o_Bacteroidales (0.085 ± 0.095 vs. 0.144 ± 0.156) and o_Erysipelotrichales (8.456 E-4 ± 2.182 E-4 vs. 4.852 E-4 ± 2.375 E-4, p < 0.05) at the order level; it increased the relative abundance of f_Lachnospiraceae (0.408 ± 0.150 vs. 0.271 ± 0.067) and f_Ruminococcaceae (0.122 ± 0.031 vs. 0.102 ± 0.047) at the family level. Furthermore, fenofibrate enhanced the abundance of g_Lachnospiraceae.NK4A136.group (0.068 ± 0.062 vs. 0.016 ± 0.009) and g_[Eubacterium] brachy group (6.08 E-4 ± 3.299 E-4 vs. 2.228 E-4 ± 1.337 E-4, p < 0.05) at the genus level and reduced the relative abundance of s_uncultured.bacterium (0.422 ± 0.132 vs. 0.553 ± 0.058, p < 0.05), s_Lactobacillus crispatus (5.719 E-6 ± 1.014 E-5 vs. 8.124 E-5 ± 6.429 E-5, p < 0.01)and s_Lachnospiraceae.bacterium.28.4 (0.034 ± 0.052 vs. 0.057 ± 0.048) at the species level (Figure 7 and Supplementary Data 2).

However, the Anosim analysis demonstrated that the R value was less than zero (R = −0.017) and the P-value was >0.05 (P = 0.532), suggesting the species difference within groups was greater than that between groups (Figure 8A). This may be explained by the great dispersion of the microbiota species in the fenofibrate group (Figure 6D). According to the Linear Discriminant Analysis (LDA) Effect Size (LEfSe) analysis, fenofibrate intervention showed a depletion of Rickettsiales and Micrococcacles at the order level, and displayed a depletion of Anaplasmataceae and Micrococcaceae at the family level. Furthermore, fenofibrate depleted the abundance of Gordonibacter, Allobaculum, Wolbachia, and Pseudarthrobacter at the genus level (Figures 8B,C). Further analysis demonstrated that the k_Bacteria.p_Actinobacteria.c_Actinobacteira.o_Micrococcales, k_Bacteria.p_Actinobacteria.c_Coriobacteriia.o_Coriobacteriales, k_Bacteria.p_Firmicutes.c_Erysipelotrichia.o_Erysipelotrichales. f_Erysipelotrichaceae.g_Allobaculum, and k_Bacteria.p_Proteobacteria.c _Alphaproteobacteria.o_Richettsiales could be assigned as biomarkers. For instance, fenofibrate significantly decreased the abundance of k_Bacteria.p_Actinobacteria.c_Actinobacteira.o_Micrococcales (Figure 8D) and especially the Micrococcaceae at the family level (Figure 8E).