Metabolite for MAFLD based on multi-omics conjoint analysis and application of metabolite

Abstract

The invention belongs to the technical field of biological pharmacy, and provides metabolite for MAFLD based on multi-omics conjoint analysis and application of the metabolite, the metabolite comprises metabolite of Bacteroides uniformi bacteria for preparing medicine for treating MAFLD, the metabolite of the Bacteroides uniformi bacteria is hexadecanedioic acid, and the application refers to application of HDA in preparing medicine for treating and / or relieving MAFLD. The invention verifies that XBP1 as a key target molecule for HDA intervention has a regulation effect on lipid metabolism disorder and ferroptosis in the MAFLD course; in addition, the relieving effect of HDA on in-vivo MAFLD in mice is verified, a theoretical basis and practical guidance are provided for developing novel MAFLD treatment drugs, and important clinical significance is achieved.

Description

Technical Field

[0001] The present invention belongs to the technical field of biological detection, and particularly relates to metabolites for MAFLD based on multi-omics joint analysis and their applications. Background Art

[0002] To diagnose metabolic associated fatty liver disease (MAFLD), two core conditions need to be met: one is that the liver fat accumulation of the patient reaches or exceeds the threshold of 5%, and the other is that there is at least one manifestation of metabolic abnormality, which may manifest as obesity, type 2 diabetes or other metabolic disorder states. Research shows that the pathological changes of the liver tissue in MAFLD patients are usually more severe than those in non-alcoholic fatty liver disease (NAFLD) patients, and the clinical prognosis is poor. The clinical manifestations of MAFLD are diverse and complex. As the disease progresses, patients may develop serious complications such as hepatitis, liver fibrosis and even cirrhosis. It is usually accompanied by other metabolic diseases such as diabetes and hypertension. It is also associated with a variety of additional clinical manifestations, including obesity, insulin resistance (IR) and chronic kidney disease, etc. In clinical practice, the diagnosis of MAFLD often relies on the combination of imaging examinations and biochemical indicators. Ultrasonography is the most commonly used preliminary screening tool, while liver biopsy is regarded as the gold standard for diagnosis, although non-invasive detection methods are gradually being recognized. And currently, there is not only a lack of effective drug treatments for MAFLD, but also a lack of effective biomarkers to monitor the treatment effect and disease progression. Therefore, early identification and classification of MAFLD are crucial for formulating effective treatment plans.

[0003] With the continuous deepening of the research on the interaction between the gut microbiota composition and the pathogenesis of MAFLD, researchers are gradually discovering potential new therapeutic targets, and these discoveries are expected to bring breakthrough progress to improving the long-term management effect and patient prognosis of MAFLD. In recent years, major breakthroughs in omics methods have provided opportunities to discover MAFLD biomarkers in different biological specimens by leveraging technological advancements. These advancements help identify and stratify the risks of MAFLD patients. Research shows that metabolomics can identify biomarkers related to MAFLD by analyzing changes in plasma and liver metabolites, thereby providing a basis for early diagnosis and treatment. Therefore, through metabolomic analysis, researchers can better understand the gender differences in MAFLD and its role in disease progression, which provides a new perspective for personalized treatment.

[0004] The present invention aims to explore the gut microbial characteristics of patients with MAFLD and their relationship with metabolic disorders through multi-omics analysis. By collecting fecal and plasma samples from patients with MAFLD and healthy controls (HC), fecal metagenomic sequencing and plasma metabolomics analysis were respectively performed. And through a mouse model of MAFLD induced by a high-fat diet, the effects of key metabolites of Bacteroides uniformis on liver injury, steatosis and inflammatory response were evaluated. It provides a theoretical basis and practical guidance for the development of new therapeutic drugs for MAFLD. Summary of the Invention

[0005] The object of the present invention is to provide metabolites for MAFLD based on multi-omics combined analysis and their applications; to determine biomarkers for MAFLD diagnosis and / or risk prediction through fecal metagenomic sequencing and plasma metabolomics analysis; to determine the key metabolites of Bacteroides uniformis in alleviating MAFLD through a mouse model of MAFLD induced by a high-fat diet, and then verify the pathway of the key metabolites in alleviating MAFLD by using the induced in vitro MAFLD model and in vivo mouse experiments; to provide a theoretical basis and practical guidance for the development of new diagnostic methods and therapeutic drugs for MAFLD.

[0006] In order to achieve the above object, the technical solution of the present invention is as follows:

[0007] The present invention provides metabolites for MAFLD based on multi-omics combined analysis, and the metabolites include metabolites of Bacteroides uniformis for preparing drugs for treating MAFLD, and the metabolites of Bacteroides uniformis are hexadecanedioic acid (HDA).

[0008] Preferably, the metabolites further include any one or more of indolepyruvic acid, pyrrolidine, β-alanine, β-hydroxylated derivative of phenylalanine, anonaine, γ-glutamyl isoleucine, lysine protease (P-18:1(9Z)), phenobarbital, daidzein, lysine protease (20:0 / 0:0) for use as MAFLD diagnostic biomarkers.

[0009] The present invention also provides the application of the above metabolites in the preparation of drugs for treating and / or alleviating MAFLD.

[0010] Preferably, the metabolite is hexadecanedioic acid, which alleviates MAFLD symptoms by downregulating the XBP1-Hrd1 pathway and simultaneously activating the Nrf2 / SLC7A11 / GPX4 signaling axis to inhibit ferroptosis.

[0011] Preferably, the dosage of the hexadecanedioic acid is 40-80 μg / mL.

[0012] The present invention also provides an application of the metabolite as a biomarker in the preparation of a detection kit for MAFLD diagnosis and / or risk prediction.

[0013] The present invention also provides an application of the product of the metabolite as a biomarker in the preparation of a product for MAFLD diagnosis and / or risk prediction.

[0014] The present invention also provides an application of the metabolite as a biomarker in screening drugs for treating and / or alleviating MAFLD.

[0015] Preferably, the metabolite as a biomarker is derived from plasma.

[0016] The present invention also provides an application of a biomarker in the preparation of a detection kit for MAFLD diagnosis and / or risk prediction, and the biomarker is any one or more of the metabolites as biomarkers described above.

[0017] Preferably, the biomarker is the combination of all of the metabolites as biomarkers described above.

[0018] Preferably, the biomarker further includes any one or more of bacteria s__Bacteroides_uniformis, s__Dialister_invisus, s__Phocaeicola_dorei, s__Collinsella_aerofaciens, s__Dorea_longicatena, and s__Clostridium_sp_AM22_11AC.

[0019] Preferably, the biomarker further includes the combination of bacteria s__Bacteroides_uniformis, s__Dialister_invisus, s__Phocaeicola_dorei, s__Collinsella_aerofaciens, s__Dorea_longicatena, and s__Clostridium_sp_AM22_11AC.

[0020] Advantages of the present invention:

[0021] 1. Currently, MAFLD mainly relies on the intervention of patients' lifestyles and dietary control, and there is still a lack of effective drug treatment. Through an in vivo MAFLD model, the present invention has determined that the key metabolite capable of inhibiting ferroptosis and alleviating MAFLD symptoms by downregulating the XBP1-Hrd1 pathway and simultaneously activating the Nrf2 / SLC7A11 / GPX4 signaling axis is HDA. Using a mixture of palmitic acid / oleic acid (PA / OA) to induce an MAFLD model of the human hepatocellular carcinoma cell line HepG2 and an MAFLD mouse model as research models, the regulatory effects of HDA on lipid metabolism disorders and ferroptosis during the MAFLD process in vivo and in vitro are further verified, providing a theoretical basis and practical guidance for the development of new MAFLD treatment drugs, and having important clinical significance.

[0022] 2. Through the sequencing of the human fecal metagenome, the present invention identifies potential biomarkers in the microorganisms of MAFLD patients. By performing non-targeted metabolomics on the plasma of MALFD patients and the control group, the potential biomarkers and related metabolic pathways in the plasma of MAFLD patients are identified, providing a scientific basis for the pathogenesis and early screening of MAFLD. Brief Description of the Drawings

[0023] Figure 1 It is a LEfSe analysis diagram of the differential flora in the feces of MAFLD patients and HC ((a) is a bar chart of the LDA value distribution, (b) is an evolutionary cladogram);

[0024] Figure 2 It is a HMDB classification annotation and differential expression volcano diagram of plasma metabolites in MAFLD patients and the HC group ((a) is the HMDB classification annotation of plasma metabolites, (b) is the differential expression volcano diagram of plasma metabolites);

[0025] Figure 3 It is a MAFLD diagnosis model diagram ((a) is a MAFLD diagnosis model based on combined plasma metabolites, (b) is a MAFLD diagnosis model based on flora, (c) is a MAFLD diagnosis model based on flora + combined plasma metabolites);

[0026] Figure 4 It is the Bu bacterium alleviating liver lipid deposition in the MAFLD mouse model (oil red O staining and light microscopy examination);

[0027] Figure 5 It is the common differential metabolites of the Bu bacterium playing a relieving role in MAFLD mice;

[0028] Figure 6 It is HDA alleviating lipid deposition in the HepG2 cells of the in vitro MAFLD model (results of light microscopy examination after oil red O staining of each group of cells)

[0029] Figure 7 Observation by transmission electron microscopy of the effect of HDA on mitochondrial ferroptosis in the MAFLD model of HepG2 cells in vitro (the electron microscope model is JEM1400, the accelerating voltage is 80 kV, and 5000k and 10000k represent the magnification of the electron microscope images);

[0030] Figure 8 Effect of HDA on the mRNA expression levels of XBP1, Nrf2, Hrd1, SLC7A11, and GPX4 in the MAFLD model of HepG2 cells in vitro (compared with the Con group, ***P < 0.001, ****P < 0.0001; compared with the Mod group, ##P < 0.01, P < 0.001, #P < 0.0001; compared with the Mod + Erastin group, &P < 0.05, &&P < 0.01, &&&&P < 0.0001);

[0031] Figure 9 Western Blot band diagram and quantitative analysis of the gray value of the protein expression level of XBP1, Nrf2, Hrd1, SLC7A11, and GPX4 in the MAFLD model of HepG2 cells in vitro by HDA;

[0032] Figure 10 Relief of liver lipid deposition in the MAFLD mouse model by Bu live bacteria, Bu bacterial supernatant, and exogenous HDA (Oil Red O staining and light microscopy examination);

[0033] Figure 11 Observation by transmission electron microscopy of the effect of HDA on mitochondrial ferroptosis in hepatocytes of MAFLD mice (the electron microscope model is JEM1400, the accelerating voltage is 80 kV, and 5000k and 10000k represent the magnification of the electron microscope images);

[0034] Figure 12 Effect of HDA on the mRNA expression levels of XBP1, Nrf2, Hrd1, SLC7A11, and GPX4 in MAFLD mice in vitro (compared with the NC group, ***P < 0.001, ****P < 0.0001; compared with the PBS group, ##P < 0.01, P < 0.001);

[0035] Figure 13 Western Blot band diagram and quantitative analysis of the gray value of the protein expression level of XBP1, Nrf2, Hrd1, SLC7A11, and GPX4 in MAFLD mice by HDA. Specific Embodiments

[0036] Unless otherwise specified, the experimental methods used in the following examples are all conventional methods.

[0037] Materials, reagents, etc. used in the following examples can be obtained from commercial sources without special instructions.

[0038] In order to make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below with reference to specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0039] Example 1 Analysis of the Gut Bacterial Metagenomics of MAFLD Patients

[0040] 1 Subjects and Methods

[0041] 1.1 Subjects

[0042] A total of 120 healthy control subjects (HC) and 120 patients with metabolic associated fatty liver disease (MAFLD) were recruited.

[0043] 1.2 Gut Bacterial Shotgun Metagenomic Sequencing

[0044] Sequencing and bioinformatics analysis were completed relying on Shanghai Bioeasy Biomedical Technology Co., Ltd. The specific contents are as follows:

[0045] [[ID=2�]]Fecal samples were collected. Novogene Bioinformatics Technology Co., Ltd. (Beijing, China) used the SDS method to extract fecal DNA, and finally paired-end sequencing of all samples was performed through the Illumina platform.

[0046] The MetaPhlAn analysis platform was used to identify and analyze the species of metagenomic samples. The LEfSe software was used to determine the features most likely to explain the differences between groups and visually display them in the form of a cladogram.

[0047] 2 Analysis Results of Gut Microbiota in the MAFLD Group and the HC Group

[0048] Differential microbiota analysis was performed using the LEfSe algorithm (linear discriminant analysis effect size). With an LDA value of 2 as the screening threshold, the key microbiota that could distinguish different groups at each taxonomic level were determined (see Figure 1(a)-(b)). Analysis found that Bacteroidetes was significantly enriched in the healthy control group (LDA = 4.479), which was the most prominent characteristic phylum differentiating from the MAFLD group. Compared with the MAFLD group, the genus with significant enrichment and key differentiating classification in the HC group was g__Bacteroides (LDA = 4.094). Compared with HC, the obvious genera in the MAFLD group were g__Lachnospiraceae_unclassified (LDA = 3.903), g__Collinsella (LDA = 3.566), g__Dorea (LDA = 3.274), and g__Veillonella (LDA = 2.806). Compared with the MAFLD group, the obvious species in the HC group were s__Bacteroides_uniformis (LDA = 3.818), s__Dialister_invisus (LDA = 3.263), and s__Phocaeicola_dorei (LDA = 3.023). Compared with HC, the obvious species in the MAFLD group were s__Collinsella_aerofaciens (LDA = 3.536), s__Dorea_longicatena (LDA = 3.115), and s__Clostridium_sp_AM22_11AC (LDA = 2.954).

[0049] Example 2 Plasma Untargeted Metabolomics of MAFLD Patients

[0050] 1 Experimental Method

[0051] Relying on Shanghai Biointeresting Biomedical Technology Co., Ltd., the detection and bioinformatics analysis of plasma untargeted metabolism of the research objects in Example 1 were completed as follows:

[0052] Transfer 100 μL of plasma sample to an EP tube, then add methanol extraction solution, mix well and let stand, and then centrifuge for 15 minutes; collect the supernatant and place it in a sample vial for testing. Chromatographic separation was carried out using the Vanquish ultra-high performance liquid chromatography system of Thermo Fisher Scientific, equipped with an ACQUITY UPLC HSS T3 column (2.1 mm × 100 mm, 1.8 μm) of Waters, and finally chromatographic and mass spectrometric analyses were completed.

[0053] The open-source software ProteoWizard was used to convert the raw data into the mzXML format. Subsequently, data processing procedures such as peak identification, extraction, alignment, and integration were performed using an R language package (based on the XCMS core). The metabolite identification was completed by matching with a self-built MS / MS library of BiotreeDB (V2.1), and the matching algorithm score threshold (Cutoff value) was set to 0.3. The metabolite identification was completed.

[0054] Metabolomics data analysis: After preprocessing the raw data, principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were used to evaluate the differences between groups and the similarity within groups. The student's t-test was applied to calculate the significance of metabolite differences between two groups, and at the same time, the fold change of their expression was analyzed for double screening.

[0055] 2 Experimental results

[0056] The identified differential metabolites were classified by the HMDB compound classification system (Superclass level). The analysis showed that these differential molecules mainly belonged to two categories: lipids and lipid-like compounds, and organic acids and their derivatives (see Figure 2 (a)). The top 10 differential metabolites (VIP values are all greater than 3.46) were shown according to the VIP value size (see Figure 2 (b)). Six differential metabolites were upregulated, namely: Indolepyruvate (VIP = 4.3683, P = 4.97E-13), Pyrrolidine (VIP = 4.1661, P = 2.27E-09), β-Alanine (VIP = 3.7988, P = 0.00000000187), DL-Dopa (β-hydroxylated derivative of phenylalanine) (VIP = 6.89E-10, P = 3.22E-07), Reticuline (VIP = 3.5883, P = 0.00002807), gamma-Glutamylisoleucine (VIP = 3.4643, P = 0.00000005559); four differential metabolites were downregulated, namely LysoPC(P-18:1(9Z)) (VIP = 3.8085, P = 1.62E-10), Phenobarbital (VIP = 3.6712, P = 1.63E-07), Daidzein (VIP = 3.5585, P = 1.29E-09), LysoPC(20:0 / 0:0) (VIP = 3.4780, P = 1.07E-09).

[0057] Example 3 Verification of the Diagnostic Efficacy of Gut Microbiota and Metabolomics Analysis for MAFLD

[0058] The receiver operating characteristic (ROC) was performed using the R package "pROC" to analyze the differential microorganisms screened in Example 1 and the differential plasma metabolites screened in Example 2, draw the ROC curve, and evaluate the diagnostic efficacy of gut microbiota and metabolomics for MAFLD.

[0059] The metabolites with the highest AUC values for individual metabolites were Indolepyruvate (0.78), Daidzein (0.74), and LysoPC(P-181(9Z)) (0.74) (see Table 1). The AUC value of the combined metabolite MAFLD diagnostic model (0.91) was larger than that of the microorganism (0.8). The multi-omics data (gut microbiota + metabolites) had better predictive value than the single-omics data, and the AUC value reached 0.93 (see Figure 3 )

[0060] The results showed that individual metabolites such as Indolepyruvate, Daidzein, and LysoPC(P-181(9Z)) could be used to diagnose MAFLD. The combined prediction model of metabolites and the combination of metabolites and microorganisms had high accuracy in diagnosing MAFLD. Among them, the accuracy of the combined metabolites prediction was better than that of gut microbiota, and the multi-omics data (combined metabolites + gut microbiota) had higher predictive value than the single-omics data. That is to say, plasma metabolomics and gut microbiota could both become biomarkers for the diagnosis of MAFLD.

[0061] Table 1 Results of the Diagnostic Model for Individual Metabolites

[0062] Metabolite Name AUC Specificity Sensitivity Indolylpyruvic Acid 0.7751 0.7417 0.7250 Pyrrolidine 0.7300 0.6291 0.7042 β-Alanine 0.7208 0.5500 0.8167 β-Hydroxylated Derivative of Phenylalanine 0.7328 0.7167 0.6833 γ-Glutamylisoleucine 0.7113 0.5917 0.7583 LysoPC(P-18:1(9Z)) 0.7384 0.5896 0.7854 Phenobarbital 0.6827 0.7583 0.5500 Daidzein 0.7383 0.8542 0.5875 LysoPC(20:0 / 0:0) 0.7151 0.7458 0.6458

[0063] Example 4 Construction of an In Vivo Model to Analyze the Metabolites of B. uniformis in MAFLD Mice

[0064] 1 Experimental Materials

[0065] Experimental strain: Bacteroides uniformis (Bu) BNCC139204 was purchased from Beijing NaChuangLian Biotechnology Co., Ltd.

[0066] Experimental animals: Healthy male C57BL / 6J mice were purchased from Beijing SPF Biotechnology Co., Ltd. The maintenance feed for mice and the Western diet feed D12492 (60% high fat) were purchased from Beijing Botai Hongda Biotechnology Co., Ltd.

[0067] 2 Experimental Methods

[0068] Twenty-four C57BL / 6J mice were raised under standard laboratory conditions: 25 ± 1 °C, relative humidity of 55 ± 5%, 12 h light and 12 h dark alternating, and the mice had free access to water. After one week of adaptive feeding, an antibiotic mixture (vancomycin, 100 mg / kg; neomycin sulfate, metronidazole, and ampicillin, 200 mg / kg) was given, dissolved in 200 μl and gavaged to the mice every morning for 7 consecutive days. The fecal smear test and 16S rRNA further confirmed the formation of germ-free mice (ABX mice). The 24 mice were evenly divided into 3 groups, namely NC, high-fat diet HFD, and Bu group. Among them, the mice in the NC group were fed with normal feed for 12 weeks, 3 times a week, and the mice in the other two groups were fed with high-fat feed D12492 (60% high fat) for 12 weeks, 3 times a week. The Bu group was gavaged once every other day, which was carried out simultaneously with the fatty liver modeling, and the cycle was also 12 weeks. The gavage substance was PBS with about 2×10 8 cfu of Bu bacteria, and the other groups were gavaged with about 200 μL of PBS to the mice.

[0069] H&E and oil red staining were used to analyze the pathological changes of liver tissue, and methods such as real-time quantitative PCR and immunoblotting were used to detect the expression levels of liver-related genes (XBP1, Hrd1, Nrf2, SLC7A11, and GPX4). Metabolomics studies were carried out on mouse feces, plasma, liver tissue, and Bu bacteria supernatant by GC-MS, and the method was partially the same as that in Example 2.

[0070] 3 Results

[0071] The oil red and HE staining of the liver in the Bu intervention group mice was improved compared with the HFD group (see Figure 4 ). By intersecting the metabolites in the in vitro Bu culture supernatant, the plasma metabolites reversed after Bu intervention, the fecal metabolites, the liver metabolites, and the differential metabolites in the plasma of MAFLD patients, it was found that hexadecanedioic acid (HDA) was the only beneficial metabolite intersection that met the trend (see Figure 5 ), that is to say, the common differential metabolite for Bu bacteria to play a relieving role in MAFLD mice was HDA. Searching the KEGG database for the annotated genes of the Bacteroides uniformis species, it was found that there was a fabZ gene, which catalyzed the dehydration of 3-hydroxyacyl-ACP (the precursor of HDA) to generate 2,3-enoyl-ACP, which was one of the necessary steps for HDA synthesis.

[0072] Example 5 Application of DHA in vitro models and mice

[0073] 1 Materials and Methods

[0074] 1.1 Materials

[0075] Experimental cell line: Human HepG2 was purchased from Wuhan Saibakang (Shanghai) Biotechnology Co., Ltd. (product number: iCell-h092 (STR identification)).

[0076] HDA working solution: Weigh 1 mg of HDA and dissolve it in 100 μl of ethanol to prepare a 1 mg / ml solution, and dilute it with water / culture medium.

[0077] OA / PA fatty liver modeling working solution:

[0078] OA: Stock solution concentration 12 mM → working concentration 0.5 mM, diluted 24 times; PA: Stock solution concentration 6 mM → working concentration 0.25 mM, diluted 24 times; 24 parts of the total volume = 1 part of OA + 1 part of PA + 22 parts of complete culture medium. Taking 1 ml as an example, add 1 / 24 = 0.0417 ml of OA, add 1.2 / 24 = 0.0417 ml of PA, and the rest is culture medium.

[0079] 1.2 Methods

[0080] Using the human hepatocellular carcinoma cell line HepG2 as a research model, an in vitro MAFLD model was induced and constructed using a palmitic acid / oleic acid (PA / OA) mixture. Lipid deposition was observed by Oil Red O staining, and methods such as PCR, immunoblot analysis, and electron microscopy observation were combined to confirm the improvement effect of HDA on the in vitro MAFLD model.

[0081] (1) Cell experiments

[0082] 1) Damage with 1 mM PA / OA fatty acid modeling solution for 24 h. The administration concentrations of HDA were 32 μg / mL, 16 μg / mL, 8 μg / mL, 4 μg / mL, 2 μg / mL, 1 μg / mL, and 320 μg / mL, 160 μg / mL, 80 μg / mL, 40 μg / mL, 20 μg / mL, 10 μg / mL respectively. After acting on HepG2 cells for 24 h, CCK8 was used to detect cell viability. Experimental groups: ① Blank group (Con): HepG2 cells; ② Model group (Mod): HepG2 cells + 1 mM PA / OA fatty acid modeling solution for 24 h of damage; ③ Experimental groups: Mod + 20 μg / mL HDA, Mod + 40 μg / mL HDA, Mod + 60 μg / mL HDA, and Mod + 80 μg / mL HDA.

[0083] (2) Obtain the final experimental grouping according to the results of step (1): ① Blank group (Con): HepG2 cells; ② Model group (Mod): HepG2 cells + fatty acid modeling solution of 1 mM PA / OA for 24 hours of injury; ③ Low-dose HDA group (Mod + HDA-L): HepG2 cells + 40 μg / mL HDA + pre-administered fatty acid modeling solution of 1 mM PA / OA for 24 hours of injury; ④ High-dose HDA group (Mod + HDA-H): HepG2 cells + 80 μg / mL HDA + pre-administered fatty acid modeling solution of 1 mM PA / OA for 24 hours of injury; ⑤ Ferroptosis induction group (Mod + Erastin): HepG2 cells + fatty acid modeling solution of 1 mM PA / OA for 24 hours of injury + 10 μmol / L Erastin; ⑥ Ferroptosis induction group + low-dose HDA group (Mod + Erastin + HDA-L): HepG2 cells + fatty acid modeling solution of 1 mM PA / OA for 24 hours of injury + 10 μmol / L Erastin + 40 μg / mL HDA; ⑦ Ferroptosis induction group + high-dose HDA group (Mod + Erastin + HDA-H): HepG2 cells + fatty acid modeling solution of 1 mM PPA / OA for 24 hours of injury + 10 μmol / L Erastin + 80 μg / mL HDA.

[0084] (2) Animal experiments

[0085] Fifty-three C57BL / 6J mice, with the same feeding conditions as before. After one week of adaptive feeding, the mice were given an antibiotic mixture to form germ-free mice (ABX mice), with the same protocol as before. The 53 mice were divided into 9 groups, namely NC control group (n = 9), HFD high-fat diet group (n = 8), PBS buffer group (n = 5), Bu live bacteria group (n = 6), inact Bu inactivated bacteria (n = 5), Bu_SN bacterial supernatant group (n = 5), CBA sterile medium (n = 5), HDA-L low-dose exogenous HDA group (n = 5), HDA-H high-dose exogenous HDA group (n = 5). Among them, the mice in the NC group were fed with normal feed for 12 weeks, and the mice in the remaining groups were fed with high-fat feed D12492 (60% high fat) for 12 weeks. Gavage was performed once every other day, simultaneously with the fatty liver modeling, and the cycle was also 12 weeks. The mice in groups 1 and 3 were given 200 μL of buffer PBS by gavage, and the Bu, inact Bu, Bu_SN, CBA, HDA-L, and HDA-H groups were respectively gavaged with 0.2 ml of Bu bacteria containing 2×10 8 CFU, inactivated Bu bacteria containing 2×10 8 CFU, Bu bacterial supernatant, Columbia Blood Agar without Bu bacteria (CBA), 8 mg low-dose HDA, and 16 mg high-dose HDA.

[0086] Electron microscopy was used to observe the signs of mitochondrial ferroptosis, H&E staining was used for pathological analysis of the pathological changes of colon tissues, and real-time quantitative PCR and Western blotting were used to detect the expression levels of liver-related genes (XBP1, Hrd1, Nrf2, SLC7A11, and GPX4).

[0087] 2 Results

[0088] 2.1 HDA can alleviate lipid deposition and hepatocyte injury in the HepG2 cell MAFLD model in vitro

[0089] As Figure 6 shown, compared with the model group, when the HDA concentration was 80 μg / mL and 40 μg / mL, the lipid deposition and hepatocyte injury in HepG2 cells were the lowest. Therefore, 80 μg / mL and 40 μg / mL HDA were selected for subsequent mechanism research.

[0090] 2.2 Effects of HDA on oxidative stress and ferroptosis in the HepG2 cell MAFLD model

[0091] Compared with the Control group, the signs of mitochondrial ferroptosis were up-regulated in the Mod group and the Mod+Erastin group, and were reversed in the HDA administration group, with the most obvious effect at 80 μg / mL HDA, showing a dose-effect relationship (see Figure 7 ).

[0092] 2.3 HDA delays the HepG2 cell MAFLD model in vitro by down-regulating ferroptosis through XBP1-Hrd1-Nrf2 / SLC7A11 / GPX4

[0093] Compared with the Control group, the mRNA and protein expression levels of XBP1 / Hrd1 were significantly increased, and the gene and protein expression levels of Nrf2 / SLC7A11 / GPX4 were decreased in the Mod group and the Mod+Erastin group, and were reversed after HDA administration intervention, with the most obvious effect at 80 μg / mL HDA, showing a dose-effect relationship (see Figures 8 - 9 ).

[0094] 2.4 Effects of live bacteria Bu, inactivated bacteria inact Bu, bacterial supernatant Bu_SN, sterile culture medium CBA, and exogenous HDA on liver function and blood lipids in MAFLD mice

[0095] Except for the Inact Bu and CBA groups, the lipid deposition in the liver of mice in the Bu, Bu_SN, and HDA intervention groups detected by oil red and HE staining was lower than that in the PBS group (see Figure 10 ).

[0096] 2.5 Metabolite HDA down-regulates the signs of mitochondrial ferroptosis in hepatocytes of MAFLD mice

[0097] Compared with the NC group, liver cells in the PBS group showed mitochondrial abnormalities, such as increased membrane density, ruptured outer membrane, reduced or disappeared cristae, but did not show the characteristics of apoptosis such as chromatin condensation, nor the characteristics of cell necrosis such as cytoplasmic and organelle swelling and plasma membrane rupture, nor the double-membrane vesicle characteristics of autophagy. After HDA intervention, the situation improved (see Figure 11 ).

[0098] 2.6 The metabolite HDA delays the progression of MAFLD in mice by downregulating ferroptosis through activating XBP1-Hrd1-Nrf2-SLC7A11-GPX4

[0099] Compared with the NC group, PCR and WB found that XBP1 and Hrd1 were upregulated, and Nrf2-SLC7A11-GPX4 was downregulated in the HFD group. After HDA intervention, the above indicators were reversed (see Figures 12 - 13 ).

[0100] In summary, the in vitro MAFLD model induced and constructed by the present invention can confirm that HDA delays the progression of MAFLD by downregulating ferroptosis through the common mechanism of XBP1 / Hrd1 / Nrf2 / SLC7A11 / GPX4. And in vivo mouse experiments can confirm that HDA delays the progression of MAFLD by downregulating ferroptosis through the common mechanism of XBP1 / Hrd1 / Nrf2 / SLC7A11 / GPX4.

[0101] The above-described embodiments only represent the preferred embodiments of the present invention. The description is relatively specific and detailed, but it should not be construed as a limitation to the scope of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several modifications and improvements can still be made, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the appended claims.

Claims

1. Metabolites for MAFLD based on multi-omics joint analysis, characterized in that, The metabolite includes the metabolite of Bacteroides uniformis for preparing a drug for treating MAFLD, and the metabolite of Bacteroides uniformis is hexadecanedioic acid.

2. The metabolite according to claim 1, wherein The metabolite also includes one or more of indolepyruvic acid, pyrrolidine, β-alanine, β-hydroxylated derivative of phenylalanine, anonaine, γ-glutamyl isoleucine, lysine protease (P-18:1(9Z)), phenobarbital, daidzein, lysine protease (20:0 / 0:0) for use as a diagnostic biomarker for MAFLD.

3. Use of the metabolite according to claim 1 in the preparation of a drug for treating and / or alleviating MAFLD.

4. The application according to claim 3, characterized in that, The metabolite is hexadecanedioic acid, which alleviates MAFLD symptoms by downregulating the XBP1-Hrd1 pathway and simultaneously activating the Nrf2 / SLC7A11 / GPX4 signaling axis to inhibit ferroptosis.

5. The application according to claim 4, wherein The dosage of the hexadecanedioic acid is 40-80 μg / mL.

6. Use of the metabolite as a biomarker according to claim 2 in the preparation of a detection kit for diagnosing and / or predicting the risk of MAFLD.

7. Use of the metabolite as a biomarker according to claim 2 in the screening of a drug for treating and / or alleviating MAFLD.

8. Use of a product for detecting the metabolite as a biomarker according to claim 2 in the preparation of a diagnostic and / or risk prediction article for MAFLD.

9. The application according to any one of claims 6 to 8, characterized in that, The metabolite used as a biomarker is derived from plasma.

10. Use of a biomarker in the preparation of a detection kit for the diagnosis and / or risk prediction of MAFLD, characterized in that, The biomarker is any one or more of the metabolites for use as a diagnostic biomarker for MAFLD in claim 2.

11. The application according to claim 10, wherein The biomarker is the combination of all the metabolites for use as a diagnostic biomarker for MAFLD in claim 2.

12. The application according to claim 10 or 11, characterized in that, The biomarker also includes any one or more of bacteria s__Bacteroides_uniformis, s__Dialister_invisus, s__Phocaeicola_dorei, s__Collinsella_aerofaciens, s__Dorea_longicatena and s__Clostridium_sp_AM22_11AC.

13. The application according to claim 10 or 11, characterized in that, The biomarker also includes the combination of bacteria s__Bacteroides_uniformis, s__Dialister_invisus, s__Phocaeicola_dorei, s__Collinsella_aerofaciens, s__Dorea_longicatena and s__Clostridium_sp_AM22_11AC.

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