Ganoderma lucidum fermented green tea as well as preparation method and application thereof

Abstract

The invention discloses ganoderma lucidum fermented green tea as well as a preparation method and application thereof. The preparation method comprises the following steps: step 1, preparing tea suspension liquid; 2, cooling the tea suspension to room temperature, and inoculating ganoderma lucidum mycelia; and step 3, culturing the tea suspension inoculated with the ganoderma lucidum mycelia in a shaking table incubator at 28 DEG C and 180 rpm for 12 days, then centrifuging to take supernate, and freeze-drying the supernate to obtain the ganoderma lucidum fermented green tea. According to the invention, the weight of mice, the sizes of liver lipid droplets and epididymal fat cells are obviously reduced, the abundance of lipid-lowering bacteria (such as Lactococcus and Lacnospirals) is also increased, and the levels of triglyceride (TG), diacylglycerol (DG), monoacylglycerol (MG) and free fatty acid (FFA) are reduced; the mRNA expression of AMPK, UCP1, PGC1 alpha and PPAR gamma in the back fat is up-regulated, the heat production effect is enhanced through the AMPK-PGC1 alpha pathway, and the abundance of lipid-lowering bacteria is increased, so that the fat accumulation is reduced.

Description

Technical Field

[0001] The present invention relates to the field of biomedicine, and in particular to ganoderma lucidum fermented green tea and a preparation method and application thereof. Background Art

[0002] Obesity is a global health epidemic that affects millions of people of all ages and socioeconomic backgrounds. Its growing prevalence has attracted widespread attention because it is closely associated with metabolic disorders such as type 2 diabetes, cardiovascular disease, and non-alcoholic fatty liver disease. A high-fat diet is an important factor in the obesity epidemic. HFD intake disrupts glucose and lipid metabolism, impairs the function of metabolic organs such as the liver, pancreas, and adipose tissue, leads to hyperglycemia, dyslipidemia, and insulin resistance, and further exacerbates obesity and related health problems.

[0003] Studies have shown that drinking tea (including green tea and fermented tea) can alleviate the adverse health effects of HFD by reducing body weight, reducing liver fat and serum cholesterol, and improving insulin sensitivity and fasting blood glucose levels. In HFD-fed mice, green tea reduced body weight, fat accumulation, and hepatic steatosis by activating the AMPK pathway and downregulating lipid biosynthesis and inflammation-related proteins. Junshan Yinzhen tea extract (white tea) may prevent obesity by regulating intestinal flora, improving intestinal barrier integrity, reducing endotoxemia, and alleviating HFD-induced chronic inflammation. Similarly, Fuzhuan tea extract (black tea) showed anti-obesity effects in HFD-fed mice by reprogramming intestinal flora. Fuzhuan tea increased caffeine levels and altered the serum metabolome, especially the caffeine metabolic pathway, thereby reducing fat deposition. These findings suggest that tea drinking may offset the effects of HFD by improving metabolism, reducing inflammation, and regulating intestinal flora.

[0004] Ganoderma lucidum is a globally renowned edible and medicinal macrofungus known for its bioactive compounds and diverse pharmacological actions, including antioxidant, antidiabetic, anti-inflammatory, immunomodulatory, antitumor, and neuroprotective effects. Limited research has been conducted on the physiological effects of fermented Ganoderma lucidum tea, especially fermented Ganoderma lucidum green tea (TFG). Summary of the invention

[0005] The technical problem to be solved by the present invention is to provide a ganoderma lucidum fermented green tea and a preparation method and application thereof in view of the deficiencies in the prior art.

[0006] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0007] A method for preparing ganoderma lucidum fermented green tea comprises the following steps:

[0008] Step 1: Grind green tea into tea powder, then mix the tea powder with distilled water and sterilize at high temperature to obtain a tea suspension;

[0009] Step 2: After the tea suspension is cooled to room temperature, inoculate the mycelium of Ganoderma lucidum;

[0010] Step 3: The tea suspension inoculated with the mycelium of Ganoderma lucidum is cultured in a shaking incubator at 28° C. and 180 rpm for 12 days, and then the supernatant is obtained by centrifugation. The supernatant is freeze-dried to obtain the Ganoderma lucidum fermented green tea.

[0011] For further improvement, the mass ratio of tea powder to distilled water is 20:400.

[0012] A ganoderma lucidum fermented green tea, the preparation method of the ganoderma lucidum fermented green tea is as described in claim 1 or 2, and the theabrownin content in the supernatant is 14.70 mg / 100 mL.

[0013] A further improvement is that the Ganoderma lucidum fermented green tea contains dihydrodehydroconiferyl alcohol, α-linolenic acid, dibutyl phthalate, butyl isobutyl phthalate, lauryl diethanolamine, dihydro-5-undecyl-2(3H)-furanone and N-acetyl-L-tryptophan; the contents of dihydrodehydroconiferyl alcohol, α-linolenic acid, dibutyl phthalate, butyl isobutyl phthalate, lauryl diethanolamine, dihydro-5-undecyl-2(3H)-furanone and N-acetyl-L-tryptophan are as follows:

[0014] Compound TFG, ng / g Dihydrodehydrodisinopyrol 94649.32 α-linolenic acid 10618415 Dibutyl phthalate 8831400 Isobutyl butyl phthalate 8982875 Lauryl diethanolamine 13116380 Dihydro-5-undecyl-2(3H)-furanone 2470915 N-Acetyl-L-Tryptophan 2388009

[0015] An application of fermented green tea, the preparation method of the Ganoderma lucidum fermented green tea is as described in claim 1 or 2, and the Ganoderma lucidum fermented green tea is used as an anti-obesity drug.

[0016] In a further improvement, the ganoderma-fermented green tea is used as a drug for increasing the abundance of lipid-lowering bacteria, including Lactococcus and Lachnospirales.

[0017] As a further improvement, the Ganoderma lucidum fermented green tea is used as a drug for reducing the abundance of Bacteroidetes microorganisms in the intestine and increasing the abundance of Firmicutes microorganisms in the intestine.

[0018] In a further improvement, the Ganoderma lucidum fermented green tea is used as a drug for increasing the mRNA expression of AMPK, UCP1, PGC1α and PPARγ in back fat.

[0019] In a further improvement, the ganoderma-fermented green tea is used as a medicament for lowering the levels of triglycerides, diglycerides, monoglycerides and free fatty acids.

[0020] Compared with the existing methods, the present invention has the following advantages:

[0021] 1. The present invention significantly reduces the body weight, liver lipid droplets and epididymal adipocyte size of mice, increases the abundance of lipid-lowering bacteria (such as Lactococcus and Lachnospirales), reduces the levels of triglycerides (TG), diglycerols (DG), monoglycerols (MG) and free fatty acids (FFA); upregulates the mRNA expression of AMPK, UCP1, PGC1α and PPARγ in back fat, enhances thermogenesis through the AMPK-PGC1α pathway, and increases the abundance of lipid-lowering bacteria, thereby reducing fat accumulation.

[0022] 2. Compared with existing green tea, it has a higher content of theabrownin. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 .In vitro lipid-lowering activity of TFG.

[0024] Figure 2 .Donut plot of TFG components.

[0025] Figure 3 .Intersection diagram of “hyperlipidemia and lipid metabolism” and TFG targets.

[0026] Figure 4 .The GO database was used to analyze the potential target map of TFG for intervention of lipid metabolism.

[0027] Figure 5a . Effects of TFG on (a) body weight, liver and epididymal fat index (n=6).

[0028] Figure 5b . Graph of serum TG, TC, LDL-C and HDL-C levels (n=6).

[0029] Figure 5c .The average area of ​​single adipocytes in epididymal adipose tissue and the percentage of Oil Red O staining area of ​​liver lipid droplets (n=3). Different letters above the bars indicate statistically significant differences (P<0.05).

[0030] Figure 6 .Histogram of relative abundance of mouse fecal microbiota at the phylum level.

[0031] Figure 7 .PCoA analysis of β diversity among different groups.

[0032] Figure 8a .LEfSe analysis revealed the abundance patterns of specific microorganisms among the g__Lactococcus groups.

[0033] Figure 8b.LEfSe analysis revealed the abundance profile of specific microorganisms among the s__Lactococcus_lactis groups.

[0034] Figure 8c .LEfSe analysis revealed the abundance patterns of specific microorganisms among the s__Muribaculum_intestinale groups.

[0035] Figure 8d .LEfSe analysis revealed abundance patterns of specific microorganisms among o_Lachnospirales groups.

[0036] Fig. 9 .Tax4Fun analysis based on KEGG database predicts microbial functions.

[0037] Fig.10 OPLS-DA analysis of mouse fecal metabolomics: left side includes ND group; right side excludes ND group.

[0038] Fig.11 .Volcano plot of differential metabolites in mice: HFD vs. ND on the left; TFG1 vs. HFD in the middle; TFG2 vs. HFD on the right.

[0039] Fig.12 .The effect of TFG on the levels of TG, DG, MG and FFA in feces.

[0040] Fig.13 OPLS-DA analysis results of mouse liver transcripts: the left figure includes the ND group; the right figure excludes the ND group.

[0041] Fig.14 .Distribution of differentially expressed genes in the differential comparison combinations.

[0042] Fig.15 .Correlation analysis of differentially expressed genes, metabolites and microorganisms.

[0043] Fig.16 .Relative mRNA expression levels of thermogenic markers (AMPK, UCP1, PGC1α, PRDM16, and PPARγ) in dorsal adipose tissue.

[0044] Fig.17 .Target interaction map in the STRING database.

[0045] Fig.18 .Sankey dot pathway enrichment map.

[0046] Fig.19 .TFG active ingredient-target-pathway network diagram for intervention of lipid metabolism.

[0047] Fig. 20.Active ingredient-target network diagram.

[0048] Fig.21 .H&E stained sections of epididymal fat and Oil Red O stained sections of liver lipid droplets. DETAILED DESCRIPTION

[0049] 1. Materials and Methods

[0050] 1.1 Preparation of TFG (Ganoderma lucidum fermented green tea):

[0051] The Ganoderma lucidum strain was identified and provided by Dr. Wang Xiaoguo from Guangxi Academy of Agricultural Sciences. To prepare the inoculum, the stored mycelia were activated on potato dextrose agar medium at 28°C for one week. Green tea was purchased from Chen Yifan Company (Qingdao, China), ground into powder using a grinder (DC-100, Dingzang Company, Jinhua, China), and passed through a 100-mesh sieve. 20 g of tea powder was mixed with 400 ml of distilled water in a 1-liter conical flask. The tea suspension was sterilized at 121°C for 20 minutes and inoculated with Ganoderma lucidum mycelia after cooling (Ganoderma lucidum mycelia on a 0.3 cm*0.3 cm slope were dug with an inoculation shovel for inoculation). The culture was carried out in a shaking incubator (ZWYR-D2401, Zhicheng Company, Shanghai, China) at 28°C and 180 rpm for 12 days. The supernatant was obtained by centrifugation at 4500 rpm and 4°C. The supernatant was freeze-dried to collect TFG and stored at 4°C. The same ratio (1:20, w:v) and treatment method were used to prepare freeze-dried powder (NFT) of non-fermented green tea and stored at 4°C for subsequent experiments. After drying 100 ml of the supernatant, about 5 g of Ganoderma lucidum fermented tea was obtained.

[0052] 1.2 Animal experiments and sample collection

[0053] Animal experiments were performed in accordance with the Guide for the Care and Use of Laboratory Animals of Hunan Agricultural University (NO.2024115-01). 70 healthy male C57BL / 6J mice (initial weight: 18.90±0.81 g, six weeks old) were purchased from Hunan Slake Jingda Laboratory Animal Co., Ltd. (License No.: SCXK-2024-0009, Changsha, China). Mice were housed in an environment with a temperature of 20-22°C, humidity of 40%-60%, and a 12 / 12 h light-dark cycle, with free access to food and water. Normal diet (ND, 3.62 kcal / g, 12% of energy from fat) and high-fat diet (HFD, 4.98 kcal / g, 60% of energy from fat) were purchased from Shuyu Biotechnology (Shanghai) Co., Ltd. (Shanghai, China). All mice underwent a one-week adaptation period before the experiment.

[0054] 70 mice were randomly divided into 7 groups (n=10) for a 4-week experiment: (1) ND group: mice were fed with a normal diet; (2) HFD group: mice were fed with a high-fat diet; (3) HFD positive control group (PC-HFD): mice were fed with HFD and supplemented with orlistat (20 mg / kg / day, Hunan Mingrui Pharmaceutical Co., Ltd.); (4) Unfermented tea (NFT) 1 group: mice were fed with HFD and supplemented with NFT (200 mg / kg / day); (5) NFT2 group: mice were fed with HFD and supplemented with NFT (400 mg / kg / day); (6) TFG1 group: mice were fed with HFD and supplemented with TFG (200 mg / kg / day); (7) TFG2 group: mice were fed with HFD and supplemented with TFG (400 mg / kg / day). The doses of 200 mg / kg / day and 400 mg / kg / day are equivalent to approximately 3.5 g and 7 g of tea intake per day for a 60 kg adult, respectively.

[0055] Mice in the ND and HFD groups were given 1 ml of distilled water by gavage every day, while mice in the PC, NFT1, NFT2, TFG1, and TFG2 groups were given corresponding doses of orlistat, NFT, or TFG by gavage every day. All mice were weighed once a week during weeks 0-4. At the end of the experiment, mice were euthanized using sodium pentobarbital (50 mg / kg body weight, intraperitoneal injection). Body weight (after fasting for 12 hours), liver weight, and epididymal fat weight were recorded. Blood, feces, liver, and adipose tissue samples were collected for further analysis. The liver index calculation formula is: liver index (%) = liver weight / body weight × 100%; the epididymal fat index calculation formula is: epididymal fat index (%) = epididymal fat weight / body weight × 100%.

[0056] 1.3 Biochemical analysis and histological examination

[0057] Serum was obtained by centrifugation at 2500 × g for 15 min (4°C). Total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) levels in serum were measured using commercial test kits (Hunan Yonghe Sunshine Technology Co., Ltd., Changsha, China). All biochemical analyses were performed on a biochemical automatic analyzer (7180, Hitachi High-Technologies Corporation, Tokyo, Japan).

[0058] Epididymal fat and liver tissues were fixed in 4% paraformaldehyde for 24 hours. Subsequently, the tissues were dehydrated, paraffin-embedded and sectioned. Epididymal fat tissue sections were stained with hematoxylin and eosin (H&E). Liver tissue sections were stained with Oil Red O. Images of all sections were taken using an upright optical microscope (ECLIPSE E100, Nikon, Tokyo, Japan). Image acquisition and analysis were performed using an imaging system (NIKON DS-U3, Nikon, Tokyo, Japan).

[0059] 1.4 Liver transcriptome analysis

[0060] Total RNA was extracted using a commercial RNA extraction kit (Trizol, Sangon Biotech, Shanghai, China). Then, total RNA was evaluated and quantified using a Qubit fluorometer and a Qsep400 high-throughput bio-fragment analyzer. mRNA libraries were constructed by polyA selection, fragmentation, cDNA synthesis, and adapter ligation. The libraries were amplified, purified, and quantified before sequencing on the BGI platform. Data analysis started with quality control using fastp to filter raw reads. Clean reads were aligned to the reference genome using HISAT. Gene expression levels were quantified using featureCounts and normalized to FPKM values. Differential expression analysis was performed using DESeq2, and P values ​​were corrected by Benjamini & Hochberg. Significantly differentially expressed genes were identified based on the corrected P values ​​and log2 fold change thresholds. Functional enrichment analysis was performed using hypergeometric tests for KEGG pathway and GO term analysis.

[0061] 1.5 Non-targeted metabolome analysis of fecal samples

[0062] The stool samples stored at -80°C were thawed on ice. 400 μL of methanol-water (7:3, v / v) solution and internal standard were added to 20 mg of sample and vortexed for 3 minutes. The samples were sonicated in an ice bath for 10 minutes and then vortexed for 1 minute. Subsequently, the samples were placed at -20°C for 30 minutes. After centrifugation at 13000g for 10 minutes (4°C), the supernatant was centrifuged again at 13000g for 3 minutes (4°C). 200 μL of supernatant was taken for LC-MS analysis.

[0063] LC-MS analysis was performed in positive ion mode using a Waters ACQUITY Premier HSS T3 column (1.8 μm, 2.1 x 100 mm). Mobile phase A: 0.1% formic acid in water; B: 0.1% formic acid in acetonitrile. Gradient: 5%-20% B (2 minutes), 60% B (3 minutes), 99% B (1 minute, hold for 1.5 minutes), back to 5% B (0.1 minute, hold for 2.4 minutes). Column temperature: 40°C; Flow rate: 0.4 mL / min; Injection volume: 4 μL. The same gradient was used in negative ion mode. MS analysis used electrospray ionization, and full scan MS and data-dependent MSn scans were performed in both modes (m / z 75–1000, resolution 35000, ion spray voltage 3.5 / 3.2 kV [±], sheath gas 30, auxiliary gas 5, ion transfer tube 320 °C, vaporizer 300 °C, collision energy 30 / 40 / 50 V, signal threshold 1*e6 cps, top 10, exclude 3 s).

[0064] 1.6 Analysis of short-chain fatty acids in feces

[0065] Quantification of short-chain fatty acids (SCFAs) in feces using GC-MS. In brief, 20 mg of sample was mixed with 1 mL of 0.5% (v / v) phosphoric acid in a 2 mL EP tube. The mixture was ground and vortexed for 10 minutes and then sonicated for 5 minutes. Centrifuged at 12000 rpm for 10 minutes (4°C). 100 μL of supernatant was mixed with 500 μL of MTBE (containing internal standard), vortexed for 3 minutes, sonicated for 5 minutes, and centrifuged again at 12000 rpm for 10 minutes (4°C). GC-MS / MS analysis was performed using an Agilent 7890B gas chromatograph coupled to a 7000D mass spectrometer using a DB-FFAP column (30 m × 0.25 mm inner diameter × 0.25 μm film thickness, J&W Scientific, USA). Helium was used as the carrier gas at a flow rate of 1.2 mL / min. 1 μL injection, split mode (split ratio 5:1). The column temperature was maintained at 50 °C for 1 min, then increased at 18 °C / min to 220 °C and maintained for 5 min. All samples were analyzed in multiple reaction monitoring mode with injector and transfer line temperatures of 250 °C and 230 °C, respectively.

[0066] 1.7 Fecal DNA extraction and 16S rRNA amplicon sequencing

[0067] Genomic DNA was extracted from stool samples using the CTAB method and evaluated on a 1% agarose gel. High-quality DNA samples were used to amplify the V3-V4 region of the 16S rRNA gene using barcoded primers (forward: 5′-CCTAYGGGRBGCASCAG-3′, reverse: 5′-GGACTACNNGGGTATCTAAT-3′). DNA PCR-Free Sample Preparation Kit (Illumina) was used to prepare sequencing libraries. 2.0 Fluorometer and Agilent Bioanalyzer 2100 evaluation. Sequencing was performed on the Illumina NovaSeq platform, generating 250 bp paired-end reads. Reads were matched to samples using barcodes, and barcode and primer sequences were trimmed. Raw tags were quality filtered using fastp to obtain high-quality clean tags. Sequencing data were analyzed using QIIME (v1.9.1). Reads with exact barcode matches were identified as valid sequences, and low-quality sequences were removed. Paired-end reads were merged using FLASH (v1.2.7). High-quality sequences were clustered into OTUs using UPARSE (v7.0.1001) at 97% sequence identity. Amplicon sequence variants (ASVs) were analyzed using Deblur. OTU abundance data were normalized to match the sample with the fewest sequences.

[0068] 1.8 Real-time quantitative PCR analysis

[0069] Total RNA was extracted from dorsal adipose tissue using TRIzol reagent. Subsequently, double-stranded cDNA was synthesized from RNA using a high-capacity cDNA reverse transcription kit (Thermo Fisher, Waltham, MA, USA). Real-time quantitative PCR was then performed using the synthesized cDNA as a template. PCR amplification used SYBR green mix (Sangon Biotechnology, Shanghai, China). The primer sequences of the target genes are shown in Table 1. Data were normalized using β-actin as an internal reference and analyzed using the 2^-ΔΔCT^ method.

[0070] Table 1. Primers used in real-time quantitative PCR

[0071]

[0072] AMPK, AMP-activated protein kinase; UCP1, uncoupling protein 1; PGC1α, peroxisome proliferator-activated receptor γ coactivator 1α; PRDM16, PR domain-containing 16; PPARγ, peroxisome proliferator-activated receptor γ.

[0073] 2. Results and Discussion

[0074] 2.1 Chemical components and lipid-lowering activity of TFG supernatant

[0075] As shown in Table 2, compared with NFT, the total flavonoids, tea polyphenols, catechins, soluble sugars, and caffeine in TFG decreased by 87.10%, 66.99%, 77.06%, 41.67%, and 22.48%, respectively. In addition, free amino acids and theabrownin increased by 1.56 and 9.21 times, respectively. The binding ability of TFG to bile salts (sodium glycinate and sodium taurocholate) was significantly increased, indicating that TFG has a stronger lipid-lowering activity ( Figure 1 ).

[0076] Table 2. Main chemical components of TFG (measured based on the supernatant after fermentation)

[0077]

[0078] NFT, non-fermented tea; TFG, Ganoderma lucidum fermented green tea.

[0079] UPLC-MS / MS and GC-MS / MS analysis

[0080] A total of 2772 metabolites were identified from TFG and NFT tea samples using UPLC-MS / MS and GC-MS platforms (Table S1: Comprehensive metabolite list). These metabolites included amino acids and their derivatives (12.52%), flavonoids (11.76%), phenolic acids (10.71%), terpenoids (9.96%), heterocyclic compounds (6.1%), esters (5.63%), alkaloids (4.87%), and various other metabolites ( Figure 2 ).

[0081] 2.2 Active ingredient target analysis

[0082] The collected compounds were analyzed using TCMSP and Swiss ADME platforms. These databases initially screened out 111 compounds with potential bioactivity. Among them, 14 compounds had an oral bioavailability (OB) ≥ 30% and a drug similarity (DL) ≥ 0.10. In addition, 64 compounds met the gastrointestinal absorption and drug similarity criteria. These results are summarized in Table S2 (Active ingredients and activity prediction of TFG). Ultimately, 78 TFG components were classified as “active ingredients”. The targets of these 78 compounds were identified using the “Related Targets” function in the TCMSP database. The Uniprot database (www.uniprot.org / ) was used to convert protein names to gene names, and targets without corresponding gene names were deleted. Ultimately, we obtained gene targets associated with the active ingredients of TFG, and a total of 746 unique targets were screened.

[0083] 2.3 Analysis of the interaction between active ingredients and lipid metabolism targets

[0084] Targets related to “hyperlipidemia and lipid metabolism” were retrieved from GeneCards, OMIM, and DisGeNET databases, and a total of 1743 targets were screened. The three datasets were imported into the R package (version 3.5.1), and 212 common targets were obtained. A Venn diagram of TFG-lipid metabolism was generated ( Figure 3We identified the intersections between lipid metabolism-related targets and the targets of TFG active ingredients, which were considered as potential targets of TFG acting on lipid metabolism.

[0085] 2.4 TFG screening of key components and targets of lipid metabolism

[0086] The 212 TFG-lipid metabolism targets were uploaded to the STRING database (https: / / string-db.org / ), set as human species, and a protein interaction network containing 2801 edges was obtained ( Fig.17 ). Protein-protein interaction (PPI) analysis was then performed on the targets, and the results were imported into Cytoscape 3.10.1 for further analysis and visualization. The PPI network was analyzed using the “Network Analyzer” plug-in, and key targets were screened out based on the degree values.

[0087] Enrichment analysis of core genes

[0088] Potential targets were enriched using the DAVID database (https: / / david.ncifcrf.gov / ). Functional enrichment analysis of 47 core targets was performed using the Gene Ontology (GO) database (http: / / geneontology.org / ), revealing 593 biological processes (BPs), 69 cellular components (CCs), and 163 molecular functions (MFs). BP, CC, and MF entries were sorted in descending order according to their enrichment scores (-log10 P), as shown in Table 1. Figure 4 As shown. The Kyoto Encyclopedia of Genes and Genomes (KEGG) database (www.genome.jp / ) was used to perform enrichment analysis on signal pathways, and a total of 179 enriched signal pathways were obtained. The top 20 enriched signal pathways were displayed in the form of a Sankey dot pathway enrichment diagram ( Fig.18 ). On the left is a Sankey diagram showing the number of genes and their distribution in each pathway; on the right is a bubble chart, where the size of the bubble indicates the number of genes and the color represents the P value. A free online platform (https: / / www.bioinformatics.com.cn / ) was used to visualize the results.

[0089] like Figure 4 and Fig.18As shown, the main biological processes include positive regulation of RNA polymerase II-mediated transcription, positive regulation of gene expression, phosphorylation, positive regulation of DNA-templated transcription, protein phosphorylation, positive regulation of cell population proliferation, G-protein coupled receptor signaling pathway, and lipid metabolic process. The main cell components include cytoplasm, plasma membrane, nucleus, and intracellular membrane-bound organelles. The main molecular functions include protein binding, metal ion binding, ATP binding, enzyme binding, protein serine / threonine kinase activity, kinase activity, and signal receptor binding. The key pathways involve lipid and atherosclerosis, metabolic pathways, insulin resistance, insulin signaling pathway, PI3K-Akt signaling pathway, FoxO signaling pathway, AGE-RAGE signaling pathway in diabetic complications, and non-alcoholic fatty liver disease.

[0090] 2.4 Active ingredient-target-pathway map analysis

[0091] According to the results of KEGG pathway enrichment analysis, a network diagram of active ingredient-target-pathway was constructed using Cytoscape (3.10.1) Fig.19 ). Circular nodes represent key components, and parallelogram nodes represent key targets and signaling pathways. The network diagram contains 909 nodes and 2,507 edges. The darker the node color of the active ingredient, the stronger the correlation between the active ingredient and the intersection targets. Analysis of the entire network identified dihydrodehydrodiconiferyl alcohol, α-linolenic acid, dibutyl phthalate, butyl isobutyl phthalate, lauryldiethanolamine, dihydro-5-undecyl-2(3H)-furanone, and N-acetyl-L-tryptophan as key components, indicating that they may significantly affect lipid metabolism. Figure S4 mainly shows the detailed relationship between TFG active ingredients and their target genes. Studies have shown that TFG acts on multiple targets through multiple components, thereby affecting multiple signaling pathways.

[0092] Through enrichment analysis of the DAVID database, the key target genes of TFG, including PRKAA2, MAPK14, PRKAB1, MTOR, LIPE, ADRB3, CNR1, PPARG, SLC25A20, PRKACA, HRAS, MGLL, and FGFR1, were significantly enriched in the thermogenesis signaling pathway. In addition, other core target genes were significantly enriched in pathways related to thermogenesis, such as the AMPK signaling pathway, MAPK signaling pathway, mTOR signaling pathway, and adipocyte lipolysis regulation. Therefore, understanding the potential link between TFG and thermogenesis may provide valuable insights into its mechanism of action in lipid metabolism and obesity management.

[0093] 2.5 Effects of TFG on mouse body weight, serum lipid levels, and histological changes

[0094] As Figure 5aAs shown, the final body weight and weight gain of the TFG group mice were significantly lower than those of the high-fat diet (HFD) group (P<0.05). There were no significant differences in the final body weight and weight gain of the TFG group mice compared with the positive control group (PC) and the NFT group. There were no significant differences in the liver and epididymal fat indices among the mice in different groups. The levels of total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) in the serum of the TFG group mice were not significantly different from those of the HFD group and the PC-HFD group ( Figure 5b ).

[0095] H&E staining showed that the adipocyte area in the epididymal tissue sections of the HFD group mice was significantly larger than that of the normal diet (ND) group. In contrast, the adipocyte areas of the PC-HFD, NFT, and TFG groups were significantly reduced. Oil Red O staining stained fat red, and the larger the stained area, the higher the fat content. Comparing the liver lipid droplets and epididymal adipocyte areas, both the TFG and NFT groups significantly reduced the lipid droplets and adipocyte areas of the mice ( Figure 5c , Fig.21 ). The reduction in the liver lipid droplet area indicates that liver lipid metabolism may be improved, while the smaller adipocytes in the epididymal adipose tissue may reflect a decrease in fat mass.

[0096] 2.6 TFG treatment reveals changes in gut bacterial composition through 16S rRNA analysis

[0097] As Figure 6 shown, compared with the ND group, the HFD group reduced Bacteroidetes and increased Firmicutes, resulting in an elevated Firmicutes to Bacteroidetes ratio (F / B). In contrast, TFG treatment increased Bacteroidetes and reduced Firmicutes, decreasing the F / B ratio compared with the HFD group. The F / B ratio of the PC-HFD group was the highest, indicating that orlistat was more effective than HFD alone in reducing Bacteroidetes and increasing Firmicutes.

[0098] TFG decreased the F / B ratio, which was consistent with previous studies.

[0099] Principal coordinate analysis (PCoA) of the β-diversity of fecal microbiota showed overlap among the groups ( Figure 7 ), indicating similar microbial community structures. Therefore, TFG, NFT, or orlistat did not significantly alter the gut microbiota composition. The study of specific microbial taxa revealed the subtle effects of TFG on gut health and metabolism. In the ND, HFD, and PC-HFD groups, g__Lactococcus and s__Lactococcus_lactis were not detected, but TFG significantly increased their abundances ( Figure 8a-8dTFG also significantly increased the levels of s__Muribaculum_intestinale. Notably, TFG had the highest fecal abundance of o_Lachnospirales among all groups.

[0100] Lactococcus chungangensis CAU 28 alleviates diet-induced obesity in mice by reducing weight gain and lipid accumulation. It inhibits the formation of TG and the proliferation of lipogenic transcription factors such as FASN and PPARγ, while regulating serum adipokine levels by increasing adiponectin and decreasing leptin. Lactococcus G423 improves growth and lipid metabolism in broiler chickens by regulating the gut microbiota, significantly reducing abdominal fat percentage and serum TG, TC, and LDL levels. Lactococcus lactis strains, such as CRL1434, modulate the gut microbiota and metabolic parameters in HFD-induced obese mice, reducing body and adipose tissue weight, glucose, cholesterol, TG, and inflammatory cytokines, while increasing anti-inflammatory cytokines such as IL-10. Administration of Lactococcus lactis subsp.cremoris in mice fed a Western diet reduces weight gain, liver fat and inflammation, and improves glucose tolerance.

[0101] Muribaculumintestinale, a member of the Muribaculaceae family, is known to degrade complex carbohydrates, contributing to nutrient absorption and intestinal health. Lachnospiraceae produces SCFAs such as butyrate, which mediate anti-inflammatory and insulin resistance protection, enhance intestinal barrier function, and alleviate HFD-induced insulin resistance.

[0102] The NK4A136 group in Lachnospiraceae was associated with reversing HFD-induced dysbiosis and weight gain. These microorganisms helped reduce fat accumulation, improve lipid profiles, regulate adipokine levels, and enhance nutrient absorption, suggesting that TFG may exert its lipid-lowering effects by promoting the proliferation of these bacteria.

[0103] 2.7 Prediction of microbial functions using Tax4Fun

[0104] Tax4Fun predicts microbial community functions by integrating species annotations in the SILVA database and the KEGG prokaryotic classification. It uses the 16S copy number in the NCBI genome annotation to normalize the OTU abundance table. Fig. 9 As shown, Tax4Fun was used to predict the enrichment of microbial communities in thermogenesis and related pathways based on KEGG data. Compared with the HFD group, the TFG group significantly increased the relative abundance of the PPAR signaling pathway.

[0105] 2.8TFG reduces metabolites enriched in thermogenesis pathway through metabolomics analysis

[0106] To elucidate the mechanism by which TFG exerts its lipid-lowering effect through the thermogenic pathway, we performed non-targeted metabolomics analysis of fecal samples. The principal component scores were analyzed using the orthogonal partial least squares discriminant analysis (OPLS-DA) model, and significant differences were found between the groups ( Fig.10 ), indicating that TFG treatment significantly altered the metabolic profile.

[0107] Based on VIP (variable importance projection) > 1 and P < 0.05, differential metabolites were identified in the comparisons of HFD vs. ND, TFG1 vs. HFD, and TFG2 vs. HFD groups. We detected 4904, 4905, and 4904 differential spectra in these three comparisons, respectively, of which 1240, 696, and 584 showed significant changes. The volcano plots show these differential metabolites ( Fig.11 a, b and c).

[0108] Fig.12 It was shown that among the differential metabolites related to thermogenesis pathway, the TFG group significantly reduced the levels of 3 triglycerides (TG), 6 diglycerides (DG), 1 monoglyceride (MG), and 4 free fatty acids (FFA) in feces. Previous studies have shown that bioactive compounds in tea reduce TG, DG, and MG levels by inhibiting digestive enzymes and activating the AMPK pathway. Oolong tea, which is rich in γ-aminobutyric acid, significantly reduces TG levels by promoting thermogenesis, lipid metabolism, and fatty acid oxidation, while inhibiting lipogenesis. Tea polyphenols inhibit lipid and protein absorption and activate AMPK in liver, muscle, and adipose tissue, reducing gluconeogenesis and fatty acid synthesis, thereby reducing TG, DG, and MG levels. Catechins and other polyphenols in tea also inhibit digestive enzymes, resulting in reduced lipid absorption, thereby reducing TG, DG, and MG levels. In summary, tea drinking has been shown to regulate adipocyte function and enhance energy expenditure by regulating thermogenic-related proteins and signaling pathways, thereby reducing lipid levels. This study revealed key differential metabolites in the thermogenic pathway, indicating the significant impact of TFG.

[0109] Tea reduces fecal FFA levels in association with its anti-inflammatory properties and enhanced fatty acid oxidation. Previous studies have found that tea compounds reduce inflammation associated with obesity and metabolic disorders, improve lipid metabolism, and reduce FFA levels. White tea and oolong tea upregulate enzymes such as CPT-1, which enhance fatty acid oxidation. Pu'er tea increases gene expression for fatty acid uptake and β-oxidation, further reducing FFA levels. Tea polyphenols activate the AMPK pathway, promote fatty acid oxidation, and inhibit lipid biosynthesis, thereby reducing FFA levels.

[0110] As shown in Table 3, the TFG supplementation group significantly reduced the fecal acetate content compared with the other five groups (P < 0.05). Tomioka et al. (2023) also pointed out that the acetate concentration decreased after drinking black tea. We infer that TFG changed the intestinal flora composition, which is a key factor in SCFA production, resulting in a decrease in acetate levels.

[0111] Table 3. Effects of TFG on short-chain fatty acid levels in mouse feces

[0112]

[0113]

[0114] ND, normal diet group; HFD, high-fat diet group; PC-HFD, 20 mg / kg / day orlistat group; NFT1, 200 mg / kg / day NFT group; NFT2, 400 mg / kg / day NFT group; TFG1, 200 mg / kg / day TFG group; TFG2, 400 mg / kg / day TFG group.

[0115] 2.9TFG alters the liver transcriptome and regulates genes related to thermogenesis pathways

[0116] To investigate the intergroup differences in mouse liver transcripts, OPLS-DA was used to analyze differentially expressed genes. The greater the separation between groups, the more significant the difference. Fig.13 The results showed that the NFT2, PC-HFD, TFG1, and TFG2 groups were significantly different from the ND and HFD groups. Of note, the differences between the HFD and TFG groups were greater than those between the NFT and PC-HFD groups ( Fig.13 ). This showed that the hepatic gene expression in the HFD intervention group (NFT2, PC-HFD, TFG1, TFG2) was significantly different compared with the HFD and ND groups (P<0.05). In addition, the differences in hepatic gene expression in TFG-treated mice were more significant than those in NFT- and orlistat-treated mice. These findings suggest that TFG significantly regulates hepatic transcripts in mice fed a high-fat diet.

[0117] Fig.14 The distribution of differentially expressed genes (upregulated and downregulated) in each comparison group is shown. Between the ND and HFD groups, 684 genes showed significant expression changes, of which 244 were upregulated and 440 were downregulated, indicating that the high-fat diet significantly altered gene expression in the mouse liver. The number of differentially expressed genes in the NFT and TFG groups increased significantly with increasing tea concentration. Notably, TFG induced greater changes in liver gene expression than NFT. These findings suggest that TFG more effectively promotes changes in liver gene expression in mice fed a high-fat diet.

[0118] In this study, we found that TFG differentially regulated key genes in thermogenesis pathway, such as Dpf3, Atp5k, and ND3. Compared with the HFD group, the expression of Dpf3 was decreased in the TFG1 and TFG2 groups (P<0.05), while the expression of Atp5k and ND3 was upregulated in the TFG2 group (P<0.05). Other differentially expressed genes were also enriched in pathways related to thermogenesis, including the MAPK signaling pathway. Gadd45a and Tgfb3 were upregulated and Il1a was downregulated in the TFG1 group (P<0.05), while Gadd45a was upregulated and Hspa1a and Il1a were downregulated in the TFG2 group (P<0.05). Grin3b was downregulated in the cAMP signaling pathway in both the TFG1 and TFG2 groups (P<0.05).

[0119] Dpf3 interacts with the SWI / SNF complex, which regulates energy metabolism genes, suggesting that it may be involved in thermogenesis. Atp5k is a subunit of mitochondrial ATP synthase, and ND3 is essential for oxidative phosphorylation and ATP synthesis, processes that are closely related to thermogenesis. These results suggest that TFG regulates thermogenesis by regulating the expression of key genes, which may affect mitochondrial function and energy metabolism.

[0120] Integrative analysis of liver transcriptome, fecal metabolome, and 16S rRNA

[0121] Using Spearman correlation, we performed cluster heat map analysis of differentially expressed genes, metabolites related to thermogenesis pathways, and differential microorganisms between groups.

[0122] like Fig.15 As shown in the figure, Muribaculumintestinale was significantly positively correlated with Atp5k and Gadd45a, and significantly negatively correlated with Grin3b. Atp5k gene was significantly positively correlated with Muribaculumintestinale, Lactococcus and Lactococcus lactis. Dpf3 gene was significantly positively correlated with DG(90659302), DG(10:0 / 12:0 / 0:0), DG

[0123] (18:3(9Z,12Z,15Z) / 16:1(9Z) / 0:0), DG(90659302), TG(14:0 / 14:1(9Z) / 15:0), DG(9543716), TG(21:0 / 8:0 / 8:0) and TG(18:0 / 18:3(6Z,9Z,12Z) / 16:1(9Z)) were significantly positively correlated.

[0124] 2.10 RT-PCR analysis of genes related to thermogenesis pathway

[0125] Although transcriptome and metabolome analyses did not show significant enrichment of thermogenic pathways, decreased fecal TG, MG, DG, and FFA levels were observed. Significant changes in thermogenic genes and pathways in the liver suggest that TFG may indirectly activate thermogenesis by altering fatty acid oxidation and insulin sensitivity. Since thermogenesis mainly occurs in BAT, we performed RT-PCR analysis of thermogenic genes in dorsal adipose tissue of mice to further investigate the regulatory mechanism of TFG on fat metabolism. PRDM16 and PGC1α, which are essential for the formation of brown adipocytes, were also detected.

[0126] like Fig.16 As shown, the TFG2 group significantly increased the gene expression of AMPK, UCP1, PGC1α, and PPARγ compared with the HFD group, showing a dose-dependent relationship. Previous studies have shown that tea regulates fat metabolism through thermogenic pathways, including upregulation of UCP1 and activation of the PPARγ / FGF21 / AMPK / UCP1 pathway, thereby increasing energy expenditure and reducing fat accumulation. Yellow tea stimulates thermogenesis through heterogeneous browning of adipose tissue, involving upregulation of UCP1 and PGC1α. Green tea polysaccharides promote adipose thermogenesis by regulating intestinal flora and increasing the expression of UCP1 and PGC1α.

[0127] The AMPK-PGC1α pathway acts as a metabolic sensor to regulate the browning and thermogenesis of adipocytes. Dark tea enhances BAT activity and induces WAT browning through the AMPK-PGC1α pathway, reducing fat accumulation. We propose that theabrownins in TFG also contribute to the lipid-lowering effect. Theabrownins enhance thermogenesis by activating the AMPK-PGC1α pathway and increase the expression of UCP1 in BAT and WAT, which is consistent with our findings. Therefore, it is inferred that TFG mainly enhances thermogenesis through the AMPK-PGC1α pathway, thereby reducing fat accumulation in mice.

[0128] Conclusion

[0129] In the present invention, we used an integrated approach combining UPLC--MS / MS, GC--MS / MS and network pharmacology to quantify and predict the key bioactive compounds with lipid-lowering effects in TFG. The lipid-reducing effect of TFG was subsequently verified using a HFD mouse model. Specifically, the administration of TFG resulted in a reduction in final body weight and weight gain. Histological examination further demonstrated that TFG reduced the size of liver lipid droplets and epididymal adipocytes. In addition, TFG significantly increased the abundance of several lipid-lowering bacteria in feces. Metabolomics and transcriptomics analysis of fecal and liver samples showed that TFG significantly reduced the levels of TG, DG, MG and FFA enriched in the thermogenic pathway. Key genes such as Dpf3, Atp5k and ND3 were differentially regulated. RT-PCR analysis confirmed that TFG significantly upregulated the expression of AMPK, UCP1, PGC1α and PPARγ in back fat. Based on these findings, we inferred that TFG enhances thermogenesis through the AMPK-PGC1α pathway, thereby reducing fat accumulation in mice.

[0130] The preferred embodiments of the present invention disclosed above are only used to help illustrate the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific implementation methods described. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A method for preparing ganoderma lucidum fermented green tea, characterized in that: The steps include: Step 1: Grind green tea into tea powder, then mix the tea powder with distilled water and sterilize at high temperature to obtain a tea suspension; Step 2: After the tea suspension is cooled to room temperature, inoculate the mycelium of Ganoderma lucidum; Step 3: The tea suspension inoculated with the mycelium of Ganoderma lucidum is cultured in a shaking incubator at 28° C. and 180 rpm for 12 days, and then the supernatant is obtained by centrifugation. The supernatant is freeze-dried to obtain the Ganoderma lucidum fermented green tea.

2. The method for preparing Ganoderma lucidum fermented green tea according to claim 1, characterized in that: The mass ratio of tea powder to distilled water is 20:

400.

3. A Ganoderma lucidum fermented green tea, characterized in that: The method for preparing Ganoderma lucidum fermented green tea is as described in claim 1 or 2, and the theabrownin content in the supernatant is 14.70 mg / 100 mL.

4. The Ganoderma lucidum fermented green tea according to claim 1, characterized in that: The ganoderma lucidum fermented green tea contains dihydrodehydroconiferyl alcohol, α-linolenic acid, dibutyl phthalate, butyl isobutyl phthalate, lauryl diethanolamine, dihydro-5-undecyl-2(3H)-furanone and N-acetyl-L-tryptophan; the contents of dihydrodehydroconiferyl alcohol, α-linolenic acid, dibutyl phthalate, butyl isobutyl phthalate, lauryl diethanolamine, dihydro-5-undecyl-2(3H)-furanone and N-acetyl-L-tryptophan are as follows: 。 5. An application of fermented green tea, characterized in that: The preparation method of the Ganoderma lucidum fermented green tea is as described in claim 1 or 2, and the Ganoderma lucidum fermented green tea is used as an anti-obesity drug.

6. The use of fermented green tea according to claim 5, characterized in that: The ganoderma-fermented green tea is used as a drug for increasing the abundance of lipid-lowering bacteria including Lactococcus and Lachnospirales.

7. The use of fermented green tea according to claim 5, characterized in that: The ganoderma-fermented green tea is used as a medicine for reducing the abundance of Bacteroidetes microorganisms in the intestine and increasing the abundance of Firmicutes microorganisms in the intestine.

8. The use of fermented green tea according to claim 5, characterized in that: The ganoderma-fermented green tea is used as a drug for increasing the mRNA expressions of AMPK, UCP1, PGC1α and PPARγ in back fat.

9. The use of fermented green tea according to claim 5, characterized in that: The ganoderma-fermented green tea is used as a medicine for lowering the levels of triglycerides, diacylglycerols, monoacylglycerols and free fatty acids.

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