Immune regulation metabolite screening by immune system humanized mouse intestinal flora disturbance model

Abstract

The invention relates to a method for screening and identifying metabolites and florae with a human immune regulation effect, which comprises the following steps: (1) establishing immune system humanized mice with multiple intestinal types, and analyzing the change of the florae, the metabolites and the immune system through intestinal flora sequencing, serum metabolome sequencing, flow cytometry and transcriptome sequencing; (2) determining the correlation and sequence between flora related metabolites and the change of the immune system through bioinformatics analysis; and (3) confirming the regulation and control relationship between the candidate metabolites and the immune subgroups in the step (2) through biological experiments. By means of the screening method, the chemical small molecule metabolites for regulating and controlling the human immune cells in the normal physiological state can be screened on a large scale, and the chemical small molecule metabolites can be developed into immunotherapy drugs or used as cell therapy drug culture system components. The screened propionic acid can promote cytotoxicity of T cells and CAR-T and secretion of related cytokines in the aspect of function regulation of the T cells, and the metabolite 2-hydroxybutyric acid is highly positively correlated with the Treg cells and can promote generation and functions of the Treg cells.

Description

Technical Field

[0001] This invention belongs to the field of biomedical technology, specifically, it relates to the screening of immune-regulating metabolites using a humanized mouse gut microbiota disruption model of the immune system, and the application of the screened immune-regulating metabolites. Background Technology

[0002] Existing technologies have revealed a close correlation between gut microbiota dysbiosis and the development of various immune imbalances, such as autoimmune diseases, tumors, and metabolic syndrome. For example, by exploring gut microbiota and its metabolites, probiotics and natural products that can be used to treat Treg cell deficiency immunodeficiency diseases have been identified. 16S rDNA sequencing technology was used to detect the gut microbiota in mice with Treg cell deficiency-mediated autoimmune diseases; metabolomics techniques were used to detect changes in the metabolomic profile of the gut microbiota in these mice; and molecular biology and gene knockout mice were used to study the molecular mechanisms of action of probiotics and metabolites. Results showed that severe gut microbiota dysbiosis occurred in mice with Treg cell deficiency-mediated immunodeficiency diseases. Based on changes in gut microbiota and metabolomic profiles, *Lactobacillus reuteri* and its metabolite inosine were used to treat Treg cell deficiency mice. *L. reuteri* and inosine inhibited Treg cell deficiency-induced autoimmune diseases by activating the adenosine receptor A2AR. In conclusion, the gut microbiota contains a large number of microorganisms and many unique metabolites, which can serve as an important source of novel natural medicines for the discovery of new probiotics and active natural products for the treatment of autoimmune diseases, tumors, and other diseases.

[0003] However, current technologies do not utilize humanized mouse models of the immune system—that is, mouse models with human immune systems—to study changes in the relationship between gut microbiota and metabolites and immune regulation under normal physiological conditions. Furthermore, the immune systems of mice differ significantly from those of humans, and normal human immune responses cannot be replicated in mice, thus hindering the study of the relationship between metabolites and normal human immune changes.

[0004] Furthermore, the differences in gut microbiota imbalance among mouse models of gut microbiota imbalance are generally insufficient to provide enough sample abundance, which increases the difficulty of identifying the correlation between metabolites and immune regulation under normal physiological conditions.

[0005] Therefore, existing technologies urgently need to simulate the effects of metabolites on the human immune function under real human conditions, while increasing sample variability, in order to more accurately understand the immunomodulatory effects of metabolites on the human body. Summary of the Invention

[0006] To address the shortcomings of existing technologies, this application provides a method for screening and identifying metabolites and microbiota with immunomodulatory effects. The method includes the following steps: (1) establishing humanized mice with various intestinal types and analyzing changes in intestinal microbiota, metabolites, and the immune system using intestinal microbiota, serum metabolites, and immune system detection methods; (2) determining the correlation and ranking between different bacterial species, serum metabolites, and human immune subpopulations through bioinformatics analysis; and (3) confirming the regulatory relationship between candidate metabolites and human immune subpopulations in step (2) through biological experiments.

[0007] In some embodiments of this application, the humanized immune system mice in step (1) include one or more of PBMC humanized mice, HSC humanized mice, and Hu-BLT model humanized mice. In some embodiments of this application, the humanized immune system mice in step (1) can be one or more; by using multiple humanized immune system mice for screening, they can complement each other and increase the chance of successfully screening metabolites with immunomodulatory effects.

[0008] As some embodiments of this application, the humanized immune system mouse in step (1) is an HSC humanized mouse; the HSC humanized mouse is an immunodeficient mouse transplanted with human hematopoietic stem cells and reconstructed with human immune cells.

[0009] To investigate the regulation of human immune cells by gut microbiota metabolites, this application constructed humanized mouse models with different intestinal types and studied the changes in metabolites and the immune system using targeted metabolic sequencing and flow cytometry, respectively. This invention, by using humanized mouse models of the immune system with human cells or tissues, leverages their ability to mimic human immune dynamics to screen for metabolites with immunomodulatory effects. Humanized mouse models of the immune system serve as a bridge between basic research and clinical translation and have already been widely applied in fields such as oncology and infectious diseases.

[0010] As one of the main immune killer cells, T cells play an important role in maintaining immune balance and tumor killing through the regulation of their function.

[0011] Common humanized mouse models of the immune system are based on immunodeficient mice, in which mature human peripheral blood mononuclear cells (PBMCs), human hematopoietic stem cells (HSCs), or fetal thymus and fetal liver are transplanted and simultaneously inoculated with human bone marrow hematopoietic stem cells to reconstitute the human immune system in immunodeficient mice.

[0012] As some embodiments of this application, the serum metabolome in step (1) includes targeted metabolome or non-targeted metabolome, and the immune system detection method includes flow cytometry, single-cell sequencing, and mass spectrometry.

[0013] As some embodiments of this application, the gut microbiota-differentiated immune system humanized mice described in step (1) are one or more.

[0014] As some embodiments of this application, the gut microbiota-differentiated immune system humanized mice described in step (1) are multiple, and these gut microbiota-differentiated immune system humanized mice have multiple intestinal types.

[0015] Enteric typing, or gut microbiota typing, is a classification system based on the dominant genera of gut microbiota combined with the functional biases of the entire gut microbiota. Different enteric types possess different microbial structures and functional genes. It can serve as an effective method for differentiating human gut microbiota.

[0016] As some embodiments of this application, the intestinal type includes multiple types such as gnotobiotics, humanized flora, single-bacterial colonization, sterile, dysbiosis, and pathological intestinal type.

[0017] As some embodiments of this application, the intestinal type includes two, three, four, five, or six of the following: gnotobiotics, humanized flora, single-bacterial colonization, sterile, dysbiosis, and pathological intestinal type.

[0018] As some embodiments of this application, the humanized mice with differential gut microbiota immune systems described in step (1) are multiple, and these humanized mice with differential gut microbiota immune systems have two, three, four, five, six, seven, eight, nine, ten or more intestinal types, gnotobiotics, humanized microbiota, single bacterial colonization or sterility.

[0019] As some embodiments of this application, the intestinal type includes the intestinal type of HIS mice raised in a specific pathogen-free environment (SPF), the intestinal type of HIS mice receiving long-term, full-life-cycle antibiotic combination therapy (ABA), the intestinal type of HIS mice with dysbiosis (DYS) induced by periodic antibiotic use, and the intestinal type of HIS mice transferred to a low-barrier clean-level mouse facility (CLT).

[0020] As part of some embodiments of this application, step (1) uses SPF immune system humanized mice as a control.

[0021] As some embodiments of this application, the metabolites are selected from gut microbiota-related metabolites or metabolites of the body affected by changes in gut microbiota.

[0022] As some embodiments of this application, the immunodeficient mice include one or more of nude mice, NOD scid mice, RAG1KO mice, RAG2KO mice, Il2rgKO mice, and severely immunodeficient mice.

[0023] As some embodiments of this application, the severely immunodeficient mouse is a mouse containing at least one of T cell deficiency, B cell deficiency, and NK cell deficiency.

[0024] As some embodiments of this application, the severely immunodeficient mice are one or more of NOG mice, NSG mice, NCG mice, NPG mice, NKG mice, BRG mice, and their derivative strains.

[0025] As some embodiments of this application, the severely immunodeficient mice are selected from NBSGW mice, NSGW41 mice, NOG-EXL mice, NCG-M mice, NCG-FLT3-KO mice, NCG-X-TSLP mice, NCG-hIL6 mice, NCG-X-hIL15 mice, NKG mice, NKG-hIL15 mice, NKG-hIL6 mice, NCG-X mice, NCG-MHC-dKO mice, BALB / cRag2-null IL-2Rγc-null mice, and NOD.Cg-Prkdc. scid Il2rg tm1Wjl / SzJ Mice, NOD-Prkdc em26Cd52 Il2rg em26Cd22 / Nju Mice, NPG mice, NPG-B2M mice, BRGSF mice, BRGS mice, BRGST mice, and one or more of their derivative strains.

[0026] As some embodiments of this application, the gut microbiota detection method includes one or more of 16S rRNA sequencing, whole genome sequencing, and metagenomic sequencing.

[0027] Metagenomic sequencing focuses on the entire microbial community in a specific habitat. Using high-throughput sequencing technology, it eliminates the need for microbial isolation and culture, overcoming the technical limitations of traditional microbial isolation and culture research. Instead, it extracts total DNA from environmental microorganisms for study, obtaining the sum of environmental microbial genome information to investigate community structure, species classification, systematic evolution, gene function, and metabolic pathways of environmental microorganisms. Metagenomic sequencing technology promotes the development and utilization of microbial resources and accelerates in-depth research in the field of microbial ecology.

[0028] As some embodiments of this application, the changes in the immune system in step (2) include one or more of the following: changes in T cell function, changes in B cell function, changes in natural killer cells, changes in hematopoietic stem cells, changes in neutrophils, changes in basophils, changes in eosinophils, changes in monocytes, and changes in macrophages.

[0029] As some embodiments of this application, the human immune subsets in step (2) include CMP (common myeloid progenitor cells), GMP (granulocyte-macrophage progenitor cells), MEP (megakaryocytic erythroid progenitor cells), HSC (hematopoietic stem cells), LMPP (lympho-myeloid-primed progenitors), MPP (multipotent progenitors), and IgA. + B cells, IgG + B cells, IgM + B cells, immature B cells, plasmablasts, transitional B cells, FOXP3 + T cells, IL-2 + T cells, IL-4 + T cells, IL-13 + T cells, IL-17A + T cells, IL-21 + T cells, IL-22 + T cells, IFN-γ + T cells, TNF-α + One or more of the following are found in T cells.

[0030] As some embodiments of this application, the biological experiment described in step (3) includes one or more of cell experiments, animal experiments, and clinical experiments.

[0031] As some embodiments of this application, the cell experiments include treating immune cell subsets with the candidate metabolites and detecting changes in the immune cell subsets, including changes in the number, function, phenotype, and interactions between immune cells.

[0032] As some embodiments of this application, the animal experiments include treating humanized experimental animals with the candidate metabolites and detecting changes in the immune cell subsets, physiological, biochemical, and health status of the experimental animals.

[0033] As some embodiments of this application, the clinical trial includes administering the candidate metabolite to a patient and detecting changes in the patient's immune cell subsets, physiological, biochemical, and health status.

[0034] As some embodiments of this application, the cell experiments include treating T cells or CAR-T cells with propionic acid and detecting changes in IFN-γ secretion from T cells or CAR-T cells.

[0035] As some embodiments of this application, the animal experiments include treating humanized mice with propionic acid and detecting the IFN-γ levels in the peripheral blood and spleen of the humanized mice.

[0036] As some embodiments of this application, the animal experiments include treating tumor mice with propionic acid and CAR-T cells, and detecting the tumor volume and weight of the tumor mice.

[0037] As some embodiments of this application, the cell experiments include treating T cells with 2-hydroxybutyric acid and detecting changes in the number of Treg cells.

[0038] As some embodiments of this application, the cell experiments include treating T cells with gamma-linolenic acid and detecting changes in the number of Treg cells.

[0039] As some embodiments of this application, the animal experiments include treating mice treated with a high dose of IL-2 with 2-hydroxybutyric acid and detecting the reduction of cytotoxicity and changes in the number of Treg cells induced by the high dose of IL-2.

[0040] As some embodiments of this application, the correlation analysis in step (2) includes statistical analysis or artificial intelligence algorithm analysis.

[0041] As some embodiments of this application, the statistical analysis includes one or more of Pearson correlation analysis, Spearman correlation analysis, Kendall Tau correlation analysis, and Point-Biserial correlation analysis.

[0042] As some embodiments of this application, the correlation analysis is Pearson correlation analysis and Spearman correlation analysis.

[0043] As some embodiments of this application, the artificial intelligence algorithm analysis includes one of linear regression, logistic regression, decision tree, Naive Bayes, support vector machine (SVM), ensemble learning, K-nearest neighbor algorithm, K-means algorithm, neural network, and deep reinforcement learning (DQN).

[0044] As some embodiments of this application, the metabolite in step (2) is selected from subericacid, phenylpyruvic acid, octanoic acid, caproic acid, azelaic acid, malonic acid, phenyllactic acid, D-xylose, deoxycholic acid, mandelic acid, deoxycholic acid, 3-hydroxyphenylacetic acid, L-aspartic acid, D-xylulose, L-tyrosine, methylsuccinic acid, glutaric acid, D-glucose, L-α-aminobutyric acid, and indoleacetic acid. The following are listed: dimethylglycine, aminocaproic acid, tauroursodeoxycholic acid, taurocholic acid, taurochenodeoxycholic acid, propionic acid (PA), taurohyodeoxycholic acid, L-histidine, taurodeoxycholic acid, propionylcarnitine, 3-indolepropionic acid, butyric acid, 4-hydroxyphenylpyruvic acid, sarcosine, 3-hydroxyisovaleric acid, citramalic acid, and 2-hydroxybutyric acid.2-HB), nicotinic acid, D-fructose, oxoglutaric acid, β-deoxycholic acid, eicosapentaenoic acid (EPA), 8-11-14-eicosatrienoic acid, docosapentaenoic acid (22n-6), linoleic acid, β-alanine, 2-hydroxy-2-methylbutyric acid, γ-linolenic acid, cis- and trans-cinnamic acid, carnitine, and glyceric acid.

[0045] As some embodiments of this application, the metabolites in step (2) that are positively correlated with the proportion of T cells secreting IFN-γ include propionic acid, taurohyodeoxycholic acid, tauroursodeoxycholic acid, taurocholic acid, taurochenodeoxycholic acid, histidine, indolepropionic acid, chenodeoxycholic acid, gluconolactone, and one or more of their derivatives.

[0046] As some embodiments of this application, metabolites that are negatively correlated with the proportion of T cells secreting IFN-γ include one or more of myristoleic acid, methylglutaric acid, ketoglutaric acid, nicotinic acid, and their derivatives.

[0047] As some embodiments of this application, with Foxp3 + Metabolites positively correlated with Treg cell changes include one or more of 2-hydroxybutyric acid, butyric acid, citramalic acid, 3-hydroxyisovaleric acid, 4-hydroxyphenylpyruvic acid, taurochenodeoxycholic acid, and their derivatives.

[0048] As some embodiments of this application, with Foxp3 + Metabolites negatively correlated with Treg cell changes include one or more of β-alanine, 2-hydroxy-2-methylbutyric acid, γ-linolenic acid, and their derivatives.

[0049] In some embodiments of this application, metabolites positively correlated with the proportion of T cells secreting IFN-γ include propionic acid and its derivatives. In some embodiments of this application, metabolites negatively correlated with the proportion of T cells secreting IFN-γ include nicotinic acid and its derivatives.

[0050] As some embodiments of this application, with Foxp3 + Metabolites positively correlated with changes in Treg cells include 2-hydroxybutyric acid and its derivatives.

[0051] As some embodiments of this application, with Foxp3 + Metabolites negatively correlated with changes in Treg cells include gamma-linolenic acid and its derivatives.

[0052] As some embodiments of this application, propionic acid is positively correlated with one or more of the following: enhancing the secretion capacity of IFN-γ and TNF-α of T cells, enhancing the secretion capacity of IFN-γ and TNF-α of CAR-T cells, and increasing the tumor-killing ability of CAR-T cells.

[0053] Spearman correlation analysis revealed a high correlation between IFN-γ secreted T cells and IFN-γ secretion. Further in vitro and in vivo experiments validated that the microbial metabolite propionic acid can promote T cell cytotoxicity and the secretion of related cytokines, enhance the secretion of IFN-γ and TNF-α by T cells, and promote the tumor-killing ability of CAR-T cells.

[0054] As some embodiments of this application, 2-hydroxybutyric acid is positively correlated with the production and function of human Treg cells, as well as with one or more of the following: inhibition of T cell expansion, toxic side effects, slowing of weight loss, and increasing the proportion of Treg cells induced by high doses of IL2.

[0055] As some embodiments of this application, gamma-linolenic acid is associated with inhibiting the production of human Treg cells.

[0056] Pearson correlation analysis revealed a strong positive correlation between 2-hydroxybutyrate (2-hydroxybutyrate) and Treg cells. The metabolite 2-hydroxybutyrate promoted Treg cell production and function, and inhibited T cell expansion and toxic side effects induced by high-dose IL2 injection in humanized mice. The functions of these small molecule metabolites on T cells have never been reported before.

[0057] As some embodiments of this application, the immune-regulating effect is an immune-regulating effect under normal physiological conditions in the human body.

[0058] In this article, the immune regulation under normal physiological conditions refers to the immune regulation under non-autoimmune disease conditions.

[0059] This application also provides the use of propionic acid and its derivatives in the preparation of immunomodulatory products, wherein the immunomodulation includes one or more of the following: enhancing the secretion capacity of human T cells of IFN-γ and TNF-α, enhancing the secretion capacity of human CAR-T cells of IFN-γ and TNF-α, and promoting the tumor-killing ability of human CAR-T cells.

[0060] As some embodiments of this application, the immunomodulatory product is a drug that modulates the immune system under normal physiological conditions. In this context, normal physiological conditions refer to a state of non-immune disease.

[0061] As some embodiments of this application, the product includes one or more of the following: pharmaceuticals, health products, and food.

[0062] As some embodiments of this application, the drug includes biological products containing or producing propionic acid and its derivatives.

[0063] As some embodiments of this application, the biological product includes a culture medium for culturing cell therapy drugs.

[0064] As some embodiments of this application, the biological product that produces propionic acid and its derivatives includes microbial agents. As some embodiments of this application, the microbial agents include probiotics, engineered bacteria, oncolytic bacteria, prebiotics that promote the production of propionic acid and its derivatives by intestinal flora, and symbiotics composed of probiotics and prebiotics that promote the production of propionic acid and its derivatives by probiotics.

[0065] This application also provides the use of 2-hydroxybutyric acid and its derivatives in the preparation of immunomodulatory products, wherein the immunomodulation includes one or more of the following: promoting the production of Treg cells, inhibiting T cell expansion induced by high doses of IL2, toxic side effects, slowing down weight loss, and increasing the proportion of Treg cells.

[0066] As some embodiments of this application, the immunomodulatory product is an immunomodulatory product under normal physiological conditions in the human body.

[0067] As some embodiments of this application, the product includes one or more of the following: pharmaceuticals, health products, and food.

[0068] As some embodiments of this application, the drug includes biological products containing 2-hydroxybutyric acid and its derivatives.

[0069] As some embodiments of this application, the biological product includes a culture medium for culturing cell therapy drugs.

[0070] As some embodiments of this application, the biological product that produces 2-hydroxybutyric acid and its derivatives includes microbial agents. As some embodiments of this application, the microbial agents include probiotics, engineered bacteria, oncolytic bacteria, prebiotics that promote the production of 2-hydroxybutyric acid and its derivatives by intestinal flora, and symbiotics composed of probiotics and prebiotics that promote the production of 2-hydroxybutyric acid and its derivatives by probiotics.

[0071] As described above, the immune system humanized mouse gut microbiota disruption model of the present invention, used for screening immune-regulating metabolites, has the following beneficial effects:

[0072] This invention enables large-scale screening of gut microbiota metabolites using a humanized mouse gut microbiota disruption model of the immune system, targeted metabolomics, and flow cytometry.

[0073] The method of this invention simulates the characteristics of human immune dynamics and can screen out metabolites with immune-regulating effects under normal human physiological conditions.

[0074] This invention is the first to discover that treatment of human T cells with propionic acid enhances the secretion of IFN-γ and TNF-α, and that CAR-T cells treated with propionic acid also exhibit enhanced IFN-γ and TNF-α secretion in the later stages, along with improved tumor-killing effects. Furthermore, treatment of human T cells with 2-hydroxybutyric acid increases the production of Treg cells, enhances related immunosuppressive functions, and slows down the T cell proliferation, toxic side effects, and weight loss caused by high-dose IL2. This invention expands the role of small molecules in the regulation of immune cells. Attached Figure Description

[0075] Figure 1 Propionic acid treatment was shown to promote IFN-γ secretion;

[0076] Figure 2 This study demonstrated that injecting propionic acid into humanized mice with the immune system promoted the secretion of IFN-γ by T cells;

[0077] Figure 3This study showed that propionic acid treatment of CAR-T cells promoted their IFN-γ secretion;

[0078] Figure 4 This study demonstrated that propionic acid treatment of CAR-T cells promoted their tumor-killing effect.

[0079] Figure 5 The study showed that propionic acid treatment of CAR-T cells inhibited tumor growth and weight.

[0080] Figure 6 This study showed that propionic acid treatment of CAR-T cells promoted their tumor-killing activity, and that IFN-γ and TNF-α secretion occurred in TILS.

[0081] Figure 7 This study demonstrated that propionic acid treatment of T cells promotes their differentiation into Th1 cell-related pathways;

[0082] Figure 8 The study demonstrated that in vitro treatment with 2-HB (2-hydroxybutyric acid) promoted the production of Treg cells;

[0083] Figure 9 This study demonstrates how injecting 2-hydroxybutyric acid into immune system-humanized mice can alleviate the cytotoxicity induced by high doses of IL-2.

[0084] Figure 10 The study demonstrated that injecting 2-hydroxybutyric acid into immune system-humanized mice alleviated the cytotoxicity induced by high doses of IL-2 and increased the proportion of Treg cells.

[0085] Figure 11 This study demonstrates that 2-hydroxybutyrate treatment of T cells promotes transcriptional profile changes associated with their Treg cells;

[0086] Figure 12 A heatmap showing the correlation between metabolites screened using the method for screening metabolites with immunomodulatory effects in Examples 1-2 of this application and the regulation of the immune system is shown.

[0087] Figure 13 A heatmap showing the correlation between microorganisms and metabolites screened by the method for screening metabolites with immunomodulatory effects described in Examples 1-2 of this application is shown.

[0088] Figure 14 The diagram illustrates the design flowchart for starting with humanized mice with different immune systems, then establishing humanized mouse models with three different bacterial communities, studying and confirming the link between metabolites and the immune system, and applying the research results. Detailed Implementation

[0089] To make the technical means, creative features, achieved objectives, and effects of this invention readily understandable, the technical solutions in the embodiments of this invention will be clearly and completely described below in conjunction with the embodiments of this invention. Obviously, the described embodiments are merely some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0090] [Experimental Materials]

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[0095] Unless otherwise specified, the experimental methods used in the following examples are conventional methods. Unless otherwise specified, the materials and reagents used in the following examples are commercially available.

[0096] Example 1

[0097] Construction of humanized mice with differentially expressed immune systems from three gut microbiota

[0098] To establish a gut microbiota clearance (antibiotic-induced gut microbiota clearance, hereinafter referred to as ABX) HIS mouse model, parental NCG mice were fed drinking water containing an antibiotic cocktail consisting of 1 g / L ampicillin (A100339, Sangon Biotech), 1 g / L metronidazole (A600633, Sangon Biotech), 1 g / L neomycin (A610366, Sangon Biotech), and 0.5 g / L vancomycin (A600983, Sangon Biotech). Mice had free access to water. Offspring of these mice were used to create HIS mice, which were fed antibiotics for life during the experiment, with the antibiotics changed twice weekly.

[0099] To simulate gut microbiota dysbiosis induced by short-term antibiotic use, SPF-fed humanized immune system mice were administered an antibiotic mixture twice daily for one week via gavage, followed by a two-week interval, and then a second week of administration. This model was then used in experiments. The antibiotic mixture consisted of ampicillin (100 mg / kg), vancomycin (50 mg / kg), neomycin (100 mg / kg), and metronidazole (100 mg / kg). Control group SPF mice were administered water via gavage only.

[0100] Under normal conditions, SPF-fed humanized immune system mice are transferred to a clean-level animal facility (CLEAN LEVEL, CL) for 4 weeks to establish a natural microbiome exposure model, which is referred to as the clean-level transfer (CLT) model.

[0101] The three humanized mouse models of immune system with different microbial communities described above represent different degrees of microbial imbalance. By using multiple mouse models with different degrees of microbial imbalance, the distribution of different bacterial species in the microbial community was changed, the abundance of microbial community and metabolites in the test samples was increased, and changes in microbial community, metabolism, and immunity were induced for correlation analysis.

[0102] The corresponding control SPF mice were all housed in an SPF facility.

[0103] Example 2:

[0104] Three types of HIS mice provided a rich sample resource for correlation analysis among gut bacteria, microbial metabolites, and immune cell types, with SPF mice serving as a control. Correlation analysis between immune subsets and gut bacteria and related metabolites was the primary method used in this study to identify human immune-regulating bacteria and metabolites. Notably, the correlation between immune subsets and metabolites was more extensive and stronger than the correlation between immune subsets and the microbiome. This observation supports the view that the regulation of the host immune system by the microbiome primarily occurs through metabolic effects.

[0105] Starting with humanized mice with different immune systems, we then established humanized mouse models of the immune system with three distinct bacterial flora. We investigated and confirmed the link between metabolites and the immune system. The design flowchart for applications based on these findings can be found in [link to flowchart]. Figure 14 .

[0106] The correlation matrix between bacteria and immune response revealed associations among 25 bacterial genera and 21 immune phenotypes.

[0107] The applicant conducted an analysis to identify the correlation between potential immunomodulatory microorganisms, immune cells, and metabolites. The analysis showed that the metabolite-immune matrix, composed of 51 metabolites, was positively or negatively correlated with 21 different immune cell phenotypes.

[0108] The proportion of T cells secreting IFN-γ was positively correlated with several metabolites, including propionic acid, taurohyodeoxycholic acid, tauroursodeoxycholic acid, taurocholic acid, taurochenodeoxycholic acid, histidine, indolepropionic acid, chenodeoxycholic acid, and gluconolactone, and negatively correlated with myristoleic acid, methylglutaric acid, ketoglutaric acid, and niacin. Furthermore, 2-HB was closely related to the levels of Treg cells and IL-2+ T cells (see [link to relevant documentation]). Figure 1 A and Figure 8 A).

[0109] With Foxp3 + Metabolites associated with Treg cell changes include 2-hydroxybutyric acid, butyric acid, citramalicacid, 3-hydroxyisovaleric acid, 4-hydroxyphenylpyruvic acid, taurochenodeoxycholic acid, β-alanine, 2-hydroxy-2-methylbutyric acid, and γ-linolenic acid.

[0110] The three humanized immune system mice had dysbiosis ranging from severe to moderate to mild. The samples used for screening were complementary, increasing the abundance of samples containing metabolites that regulate immune responses.

[0111] The heatmap showing the correlation between metabolites and immune system regulation identified using the above animal models and methods is shown below. Figure 12 The correlation heatmap of the screened microorganisms and metabolites is shown below. Figure 13 .

[0112] Example 3:

[0113] To further validate the results in Example 2, Spearman correlation analysis was performed on the correlation between metabolites and T cells. The results are shown in […]. Figure 1 It can be seen that T cells secreting IFN-γ show the strongest positive correlation with PA and the strongest negative correlation with niacin.

[0114] T cells were cultured with different concentrations of metabolites for 3 days, and the cell supernatant was collected, stored at -80℃, and cytokines were detected (see [link to data]). Figure 2 A). IFN-γ concentration was determined using the Human IFN-γ ELISA MAX™ (Biolegend, USA, Cat: 430104) according to the manufacturer's instructions. Flow cytometry further analyzed IFN-γ levels after PA treatment, revealing that treatment with 2 mM propionic acid promoted T cell IFN-γ secretion. Figure 2 B).

[0115] For short-term PA treatment in SPF HIS mice, PA (60 mg / kg) was administered intravenously (IV) daily for one week. For GF-HIS mice, PA (200 mM) was administered via drinking water for one month, with water changed every three days. IFN-γ levels in peripheral blood and spleen were measured. Results are shown below. Figure 3 It is evident that short-term PA treatment promotes IFN-γ secretion from T cells. Further analysis of CAR-T cells treated with PA followed by co-culture with corresponding HEP-12 tumor cells revealed that PA treatment further promoted IFN-γ secretion from CAR-T cells. Figure 4 AC).

[0116] To further verify the tumor-suppressing effect of CAR-T cells after PA treatment in vivo, the applicant first subcutaneously injected 3 million HEP-12 tumor cells into 6-8 week old NCG mice. When the tumor size reached 300 mm... 3 At approximately 8:00 PM, mice were randomly divided into three groups. The three groups received intratumoral injections of 1 million CAR-T cells, simulated CAR-T cells, and PA-treated CAR-T cells in 25 μl PBS, respectively. Tumor growth rate was monitored daily, and mice were sacrificed 8 days after CAR-T cell injection for indicator analysis. Figures 5-6 It is evident that PA treatment stimulates CAR-T cells to secrete IFN-γ. Figure 6 ), and reduces tumor volume and weight ( Figure 5 B-C), namely, propionic acid treatment of CAR-T cells promotes their tumor-killing effect, and the secretion of IFN-γ and TNF-α by CAR-T cells in TILS. Transcriptome analysis of PA-treated T cells was performed to reveal its mechanism of action. Figure 7 .

[0117] Example 4

[0118] The correlation between metabolites and Treg cells was analyzed, and the positive and negative correlations obtained from screening were validated in vitro. The proportion of Treg cells after culturing T cells with different concentrations of metabolites for 3 days was detected by flow cytometry. Figure 8).from Figure 8 As can be seen from A to B and C to D, with increasing 2-hydroxybutyric acid (2-hydroxybutyric acid) concentration, the number of human Treg cells increases, or 2-hydroxybutyric acid promotes the production of human Treg cells. From... Figure 8 As can be seen in A~B and E~F, treatment with γ-linolenic acid (γ-linolenic acid) inhibits the production of Treg cells.

[0119] The HDIL2 mouse model was generated using the previously described hydrodynamic injection method. In summary, the human IL-2 cDNA clone in the vector pckv-6-xl4 (Origene) was purified using the GoldHiEndoFree plasmid Maxi Kit (Cat ID: CW2014M, CoWin Biosciences). Subsequently, HIS mice were weighed and injected with 50 μg of IL-2 plasmid using a 27-gauge needle. For 2-HB treatment, HIS mice were given a daily dose of 100 mg / kg 2-HB starting two days prior to the hydrodynamic injection (procedure details are provided). Figure 9 A) Mice were continuously injected with 2-HB for one week, while the control group received only PBS injections. Mouse body weight was monitored daily, and flow cytometry was performed at the experimental endpoint. Transcriptome sequencing was used to analyze CD4 T cells treated with 2-HB in vitro for 3 days to elucidate its mechanism of action.

[0120] 2-HB treatment results are shown in Figure 9 B. It is evident that injection of 2-hydroxybutyric acid (GHB) into humanized mice with a weakened immune system alleviated the cytotoxicity induced by high-dose IL-2, resulting in reduced weight loss in the mice. Simultaneously, injection of GHB into humanized mice with a weakened immune system alleviated the cytotoxicity induced by high-dose IL-2 and increased the proportion of Treg cells. Figure 10 (A~C). Furthermore, 2-hydroxybutyric acid treatment of T cells promotes changes in their Treg cell-related transcriptional profiles (…). Figure 11 ).

[0121] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the methods and techniques disclosed above without departing from the scope of the present invention to create equivalent embodiments. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A method for screening and identifying metabolites and microbiota with human immune-regulating effects, characterized in that, The method includes the following steps: (1) Establish humanized mice with various intestinal types and analyze the changes in gut microbiota, metabolites and immune system through intestinal microbiota, serum metabolites and immune system detection methods; (2) The correlation and ranking of different bacterial species, serum metabolites and human immune subsets were determined by bioinformatics analysis; And (3) confirm the regulatory relationship between candidate metabolites and immune cell subsets in step (2) through biological experiments.

2. The method according to claim 1, characterized in that, The humanized mice for the immune system in step (1) include one or more of the following: PBMC humanized mice, HSC humanized mice, and Hu-BLT model humanized mice; Preferably, the humanized immune system mouse is an HSC humanized mouse; the HSC humanized mouse is an immunodeficient mouse that has been transplanted with artificial hematopoietic stem cells and reconstructed with human immune cells; Alternatively, the serum metabolome mentioned in step (1) may include a targeted metabolome or a non-targeted metabolome, and the immune system detection method may include flow cytometry, single-cell sequencing, or mass flow cytometry. Alternatively, the gut microbiota-differentiated immune system humanized mice described in step (1) may be one or more; Alternatively, the humanized mice with differential gut microbiota in step (1) may be multiple, and these humanized mice with differential gut microbiota may have multiple intestinal types, including gnotobiotics, humanized microbiota, single bacterial colonization, sterile, dysbiosis, and pathological intestinal types. Alternatively, in step (1), SPF immune system humanized mice can be used as a control. Alternatively, the metabolome can be selected from gut microbiota-related metabolites or metabolites of the body affected by changes in gut microbiota; Preferably, the immunodeficient mice include one or more of nude mice, NOD scid mice, RAG1 KO mice, RAG2 KO mice, Il2rg KO mice, and severely immunodeficient mice; Preferably, the severely immunodeficient mouse is a mouse containing at least one of T cell deficiency, B cell deficiency, and NK cell deficiency; Preferably, the severely immunodeficient mice are one or more of NOG mice, NSG mice, NCG mice, NPG mice, NKG mice, BRG mice, and their derivative strains; More preferably, the severely immunodeficient mice are selected from NBSGW mice, NSGW41 mice, NOG-EXL mice, NCG-M mice, NCG-FLT3-KO mice, NCG-X-TSLP mice, NCG-hIL6 mice, NCG-X-hIL15 mice, NKG mice, NKG-hIL15 mice, NKG-hIL6 mice, NCG-X mice, NCG-MHC-dKO mice, BALB / c Rag2-null IL-2Rγc-null mice, and NOD.Cg-Prkdc mice. scid Il2rg tm1Wjl / SzJ Mice, NOD-Prkdc em26Cd52 Il2rg em26Cd22 / Nju One or more of the following: mice, NPG mice, NPG-B2M mice, BRGSF mice, BRGS mice, BRGST mice, and their derivative strains; The intestinal types include those of HIS mice raised in a pathogen-free environment, those of HIS mice treated with long-term, full-life-cycle antibiotic combination therapy, those of HIS mice with dysbiosis caused by periodic antibiotic use, and those of HIS mice transferred to a low-barrier, clean-level mouse facility. Preferably, the gut microbiota method includes one or more of 16S rRNA detection, whole genome sequencing, and metagenomic sequencing.

3. The method according to claim 1, characterized in that, The changes in immune cell subsets in step (2) include one or more of the following: changes in T cells, B cells, natural killer cells, hematopoietic stem cells, neutrophils, basophils, eosinophils, monocytes, and macrophages. Alternatively, the biological experiments described in step (3) may include one or more of the following: cell experiments, animal experiments, and clinical experiments; Preferably, the human immune subsets in step (2) include CMP, GMP, MEP, HSC, LMPP, MPP, and IgA. + B cells, IgG + B cells, IgM + B cells, immature B cells, plasmablasts, transitional B cells, FOXP3 + T cells, IL-2 + T cells, IL-4 + T cells, IL-13 + T cells, IL-17A + T cells, IL-21 + T cells, IL-22 + T cells, IFN-γ + T cells, TNF-α + One or more of the following in T cells; Preferably, the cell experiment includes treating immune cell subsets with the candidate metabolites and detecting changes in the immune cell subsets; more preferably, the changes in the immune cell subsets include changes in the number, function, phenotype of immune cells and changes in the interactions between immune cells. Preferably, the animal experiment includes treating humanized experimental animals with the candidate metabolites and detecting changes in the immune cell subsets, physiological, biochemical, and health status of the experimental animals; Preferably, the clinical trial includes administering the candidate metabolite to a patient and detecting changes in the patient's immune cell subsets, physiological, biochemical, and health status. More preferably, the cell experiment includes treating T cells or CAR-T cells with propionic acid and detecting changes in IFN-γ secretion by T cells or CAR-T cells; More preferably, the animal experiment includes treating humanized mice with propionic acid and detecting the IFN-γ levels in the peripheral blood and spleen of the humanized mice; More preferably, the animal experiment includes treating tumor mice with propionic acid and CAR-T cells, and detecting the tumor volume and weight of the tumor mice; More preferably, the cell experiment includes treating T cells with 2-hydroxybutyric acid and detecting changes in the number of Treg cells; More preferably, the cell experiment includes treating T cells with γ-linolenic acid and detecting changes in the number of Treg cells; More preferably, the animal experiments include treating mice treated with high doses of IL-2 with 2-hydroxybutyric acid and detecting the reduction of cytotoxicity and changes in the number of Treg cells induced by high doses of IL-2.

4. The method according to claim 1, characterized in that, The correlation analysis in step (2) includes statistical analysis or artificial intelligence algorithm analysis; Preferably, the statistical analysis includes one or more of Pearson correlation analysis, Spearman correlation analysis, Kendall Tau correlation analysis, and Point-Biserial correlation analysis; Preferably, the correlation analysis is Pearson correlation analysis and Spearman correlation analysis; Preferably, the artificial intelligence algorithm analysis includes one of linear regression, logistic regression, decision tree, Naive Bayes, support vector machine, ensemble learning, K-nearest neighbor algorithm, K-means algorithm, neural network, and deep reinforcement learning.

5. The method according to claim 1, characterized in that, The metabolites in step (2) are selected from succinic acid, phenylpyruvic acid, caprylic acid, hexanoic acid, azelaic acid, malonic acid, phenyllactic acid, D-xylose, deoxycholic acid, mandelic acid, deoxycholic acid, 3-p-hydroxyphenylacetic acid, L-aspartic acid, D-xylulose, L-tyrosine, methylsuccinic acid, glutaric acid, glucose, L-α-aminobutyric acid, indoleacetic acid, dimethylglycine, aminocaproic acid, tauroursodeoxycholic acid, taurochlicic acid, taurochideoxycholic acid, propionic acid, taurine and deoxycholic acid. Bile acid conjugates, L-histidine, taurideoxycholic acid, propionylcarnitine, 3-indolepropionic acid, butyric acid, 4-hydroxyphenylpyruvic acid, sarcosine, 3-hydroxyisovaleric acid, citrate, 2-hydroxybutyric acid, nicotinic acid, D-fructose, ketoglutarate, β-deoxycholic acid, eicosapentaenoic acid, 8-11-14-eicosatrienoic acid, eicosapentaenoic acid, linoleic acid, β-alanine, 2-hydroxy-2-methylbutyric acid, γ-linoleic acid, cis- and trans-cinnamic acid, carnitine, glyceric acid.

6. The method according to claim 1, characterized in that, The metabolites in step (2) that are positively correlated with the proportion of T cells secreting IFN-γ include propionic acid, tauroursodeoxycholic acid, tauroursodeoxycholic acid, taurourcholic acid, taurourchenodeoxycholic acid, histidine, indolepropionic acid, chenodeoxycholic acid, gluconolactone, and one or more of their derivatives. Metabolites that are negatively correlated with the proportion of T cells that secrete IFN-γ include one or more of myristone acid, methylglutaric acid, ketoglutaric acid, nicotinic acid, and their derivatives; With Foxp3 + Metabolites positively correlated with Treg cell changes include one or more of 2-hydroxybutyric acid, butyric acid, citrate, β-hydroxyisovaleric acid, 4-hydroxyphenylpyruvic acid, taurine chenodeoxycholic acid, and their derivatives. With Foxp3 + Metabolites negatively correlated with Treg cell changes include one or more of β-alanine, 2-hydroxy-2-methylbutyric acid, γ-linolenic acid, and their derivatives; Preferably, the metabolites that are positively correlated with the proportion of T cells that secrete IFN-γ include propionic acid and its derivatives, and the metabolites that are negatively correlated with the proportion of T cells that secrete IFN-γ include nicotinic acid and its derivatives. Preferably, with Foxp3 + Metabolites positively correlated with changes in Treg cells include 2-hydroxybutyric acid and its derivatives; Preferably, with Foxp3 + Metabolites negatively correlated with changes in Treg cells include gamma-linolenic acid and its derivatives.

7. The method according to claim 6, characterized in that, Propionic acid is positively correlated with one or more of the following: enhancing the secretion of IFN-γ and TNF-α by T cells, enhancing the secretion of IFN-γ and TNF-α by CAR-T cells, and increasing the tumor-killing ability of CAR-T cells.

8. The method according to claim 6, characterized in that, 2-Hydroxybutyric acid (2-HHB) is positively correlated with the production and function of human Treg cells, as well as with one or more of the following: inhibition of high-dose IL2-induced T cell proliferation, toxic side effects, slowed weight loss, and increased Treg cell proportion. Alternatively, gamma-linolenic acid may be associated with inhibiting the production of human Treg cells.

9. The application of propionic acid and its derivatives in the preparation of immunomodulatory products, characterized in that, The immune regulation includes one or more of the following: enhancing the secretion capacity of human T cells of IFN-γ and TNF-α, enhancing the secretion capacity of human CAR-T cells of IFN-γ and TNF-α, and promoting the tumor-killing ability of human CAR-T cells. Preferably, the product includes one or more of the following: pharmaceuticals, health products, and food. Preferably, the drug comprises a biological product containing or producing propionic acid and its derivatives; More preferably, the biological product includes a culture medium for culturing cell therapy drugs; More preferably, the biological product that produces propionic acid and its derivatives includes a microbial agent; more preferably, the microbial agent includes probiotics, engineered bacteria, oncolytic bacteria, prebiotics that promote the production of propionic acid and its derivatives by intestinal flora, and symbiotics composed of probiotics and prebiotics that promote the production of propionic acid and its derivatives by probiotics. The application of 10,2-hydroxybutyric acid and its derivatives in the preparation of immunomodulatory products, characterized in that, The immune regulation includes one or more of the following: promoting the production of Treg cells, inhibiting T cell expansion induced by high dose IL2, toxic side effects, slowing down weight loss, and increasing the proportion of Treg cells; Preferably, the product includes one or more of the following: pharmaceuticals, health products, and food. Preferably, the drug comprises a biological product containing 2-hydroxybutyric acid and its derivatives; More preferably, the biological product includes a culture medium for culturing cell therapy drugs; More preferably, the biological product that produces 2-hydroxybutyric acid and its derivatives includes a microbial agent; more preferably, the microbial agent includes probiotics, engineered bacteria, oncolytic bacteria, prebiotics that promote the production of 2-hydroxybutyric acid and its derivatives by intestinal flora, and symbiotics composed of probiotics and prebiotics that promote the production of 2-hydroxybutyric acid and its derivatives by probiotics.

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