Method for extracting binary coagulation immune signals

Abstract

The application relates to the technical field of biomedical engineering, and particularly discloses a method for extracting binary condensate immune signals, which comprises the following steps: screening disease-related high-expression genes by using a disease model, a normal model and a drug treatment model; screening important protein molecules based on the high-expression genes by using a nucleic acid-protein affinity analysis method; constructing a fusion carrier based on cytoskeleton proteins, important protein molecules and green fluorescent protein tracing; and identifying risk genes and possible downstream proteins associated with condensates by spatial omics imaging based on the fusion carrier of the disease model, the normal model and the drug treatment model, and quantifying the condensation process of the condensates. The application reduces the influence of problems such as condensate state destruction and spatial distribution information loss, and accurately realizes in-situ spatial omics imaging and analysis of an immune microenvironment evolution process of a complex disease.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of biomedical engineering, and particularly relates to a method for extracting immune signals of binary condensates. BACKGROUND

[0002] In the evolution process of complex diseases, nucleic acids and proteins in important immune cells can play immune regulation functions through the formation of binary condensates, and the observation and analysis thereof are of great significance for understanding the common pathological basis of autoimmune diseases. For example, a long-chain terminal repeat sequence is an endogenous nucleic acid sequence in the genome, which is usually in a silent state under physiological conditions; but under pathological conditions, its transcription and translation products, such as RNA and polypeptides, can form immune complexes or binary condensates with protein molecules and participate in immune responses. Most of the current researches focus on the assembly and regulation of condensates with known components. However, the immune signal pathways downstream of the condensates are very complex and difficult to measure. In view of this problem, the commonly used methods are only simple nucleic acid molecule sequencing and protein spectrum analysis. The physical solidification and nucleic acid and protein purification processes of such methods can cause problems such as destruction of the condensate state and loss of spatial distribution information. Therefore, the understanding of how the condensates play immune regulation roles is limited, and it is difficult to achieve the goal of in-situ spatial omics imaging and analysis of immune microenvironments in the evolution process of complex diseases. SUMMARY

[0003] Based on this, the present application provides a method for extracting immune signals of binary condensates, which is suitable for discovering important transposons in autoimmune diseases and promoting the conversion process of candidate drugs.

[0004] According to a first aspect of the present application, a method for extracting immune signals of binary condensates is provided, comprising:

[0005] Screening disease-related highly expressed genes by using disease models, normal models and drug treatment models;

[0006] Screening important protein molecules based on the highly expressed genes by using nucleic acid-protein affinity analysis methods;

[0007] Constructing a fusion vector based on cytoskeletal proteins, the important protein molecules and green fluorescent protein tracing;

[0008] Identifying risk genes and possible downstream proteins associated with condensates by spatial omics imaging based on the fusion vectors of the disease models, the normal models and the drug treatment models, and quantifying the condensation process of the condensates.

[0009] According to an embodiment of the present application, the screening of disease-related highly expressed genes by using disease models, normal models and drug treatment models comprises:

[0010] The peripheral immune tissues or peripheral blood of the disease model and the normal model are made into a disease model cell suspension and a normal model cell suspension;

[0011] The cells in the disease model cell suspension and the normal model cell suspension are lysed by using a nucleic acid extraction reagent, and the solution is subjected to organic phase separation, and after standing, centrifuged.

[0012] The nucleic acids in the disease model cells and the normal model cells are separated and extracted for sequencing to obtain disease model expressed genes and disease model protein information and normal model expressed genes and normal model protein information;

[0013] By comparing the disease model expressed genes and the normal model expressed genes, high expression genes are screened out.

[0014] According to the embodiment of the application, the fusion carrier based on the disease model, the normal model and the drug treatment model identifies the risk genes associated with the condensate and the possible downstream proteins through spatial omics imaging, and quantifies the condensation process of the condensate, including:

[0015] The detection and analysis of the condensate are realized by using fluorescence imaging, fluorescence bleaching recovery experiment and the like;

[0016] The important peripheral immune tissues of the disease model and the drug treatment model are made into samples;

[0017] The immune-related RNA nucleic acid molecules are captured and recognized by using the fusion protein;

[0018] Spatial omics imaging is performed by using a confocal microscope, and fluorescence positioning, quantification and differential analysis are performed.

[0019] According to the embodiment of the application, the nucleic acids in the disease model cells and the normal model cells are separated and extracted for sequencing to obtain disease model expressed genes and disease model protein information and normal model expressed genes and normal model protein information, including:

[0020] The nucleic acid extraction reagent is added to the disease model cell suspension and / or the normal model cell suspension at a ratio of 1 milliliter of the nucleic acid extraction reagent corresponding to every five million cells, and mixed evenly;

[0021] Chloroform is added to the disease model cell suspension and / or the normal model cell suspension, and mixed evenly, wherein the volume ratio of the nucleic acid extraction reagent to the chloroform is 10:1-10:3, to obtain a disease model lysis solution and / or a normal model lysis solution;

[0022] After standing and centrifugation, the disease model lysate and / or the normal model lysate are subjected to organic phase separation to obtain a water phase containing RNA, an organic phase containing DNA, and an intermediate phase containing proteins and other impurities.

[0023] According to an embodiment of the present application, the separation extracts nucleic acids in the disease model cells and the normal model cells for sequencing to obtain disease model expressed genes and disease model protein information and normal model expressed genes and normal model protein information, which further comprises:

[0024] Isopropyl alcohol is added to the water phase, wherein the volume ratio of the nucleic acid extraction reagent to the isopropyl alcohol is 5:2-5:3, and after incubation at 4°C, centrifugation is performed to precipitate the RNA in the water phase;

[0025] An equal volume of anhydrous ethanol is added to the organic phase and mixed, and the DNA is precipitated by centrifugation;

[0026] A 10% ethanol solution containing 0.1 mol of sodium citrate is added to the DNA, the precipitate is resuspended, and after incubation, centrifugation, and drying and washing, a DNA precipitate is obtained.

[0027] According to an embodiment of the present application, the screening of highly expressed genes by comparing the disease model expressed genes and the normal model expressed genes comprises:

[0028] The separated DNA precipitate and RNA precipitate are subjected to high-throughput sequencing analysis to obtain analysis results of the disease model and / or the normal model;

[0029] By comparing the analysis results of the disease model with the analysis results of the normal model, the differentially expressed genes are functionally annotated to screen highly expressed immune-related genes.

[0030] According to an embodiment of the present application, it further comprises:

[0031] The highly expressed genes include one or more of Camk4, Ddx4, Fas, Nox2, and Nlrp6.

[0032] According to an embodiment of the present application, the construction of a fusion vector based on cytoskeletal proteins, important protein molecules, and green fluorescent protein tracing comprises:

[0033] The cytoskeletal protein includes a cytoskeletal protein TPPP fragment in SEQ ID No. 1;

[0034] The highly expressed gene CAMK4 includes a nucleic acid sequence in SEQ ID No. 2;

[0035] The high-expression gene DDX4 comprises the nucleic acid sequence in SEQ ID No. 3.

[0036] The high-expression gene FAS comprises the nucleic acid sequence in SEQ ID No. 4.

[0037] The high-expression gene NLRP6 comprises the nucleic acid sequence in SEQ ID No. 5.

[0038] The important protein molecule comprises the CAMK4 protein sequence in SEQ ID No. 6.

[0039] The important protein molecule comprises the DDX4 protein sequence in SEQ ID No. 7.

[0040] The important protein molecule comprises the FAS protein sequence in SEQ ID No. 8.

[0041] The important protein molecule comprises the NLRP6 protein sequence in SEQ ID No. 9.

[0042] According to an embodiment of the present application, the fusion protein is used to capture and identify immune-related RNA nucleic acid molecules, comprising:

[0043] After transcription of the fusion vector, a vector RNA nucleic acid molecule is obtained;

[0044] The vector RNA nucleic acid molecule is injected into the mouse body by means of lipid nanoparticle delivery, comprising:

[0045] The vector RNA nucleic acid molecule is dissolved in a sodium citrate buffer solution with a concentration of 5-10 millimoles per liter;

[0046] The vector RNA nucleic acid molecule is mixed with the lipid nanoparticle, and the mixture of the vector RNA nucleic acid molecule and the lipid nanoparticle is injected into the mouse body intravenously,

[0047] The weight ratio of the total lipid in the lipid nanoparticle to the vector RNA nucleic acid molecule ranges from 20:1 to 50:1.

[0048] According to an embodiment of the present application, the drug treatment model is a result model after four weeks of drug treatment of the disease model.

[0049] From the above technical solutions, it can be seen that the method for extracting binary coagulation immune signals provided by the present application has the following beneficial effects:

[0050] Compared with the conventional method, the application reduces the influence of problems such as agglomerate state destruction, spatial distribution information loss, and accurately realizes in-situ spatial omics imaging and analysis of immune microenvironment evolution process of complex diseases; the application can comprehensively analyze the agglomeration process of binary agglomerates, and draw a regional map of nucleic acid-protein interaction; the application realizes in-situ precise screening of immune-related genes by using the properties of agglomerates and spatial omics imaging technology; the application is suitable for discovering important transposons and functions in autoimmune diseases, and promoting the transformation of related candidate drugs. BRIEF DESCRIPTION OF DRAWINGS

[0051] Figure 1 It is a system framework schematic diagram of the embodiment of the application.

[0052] Figure 2 It is a gene expression analysis process schematic diagram of the embodiment of the application.

[0053] Figure 3 It is an important protein molecule screening schematic diagram of the embodiment of the application.

[0054] Figure 4 It is an agglomerate detection and change monitoring schematic diagram of the embodiment of the application, wherein step a is an agglomerate detection process schematic diagram, and step b is a lipid nanoparticle delivery imaging process schematic diagram. DETAILED DESCRIPTION

[0055] In order to make the purpose, technical scheme and advantages of the application more clear and obvious, the following combines specific embodiments, and refers to the drawings, and makes further detailed description to the application.

[0056] According to a first aspect of the application, a binary agglomerate immune signal extraction method is provided, comprising:

[0057] Using disease models, normal models and drug treatment models, disease-related highly expressed genes are screened out;

[0058] Using nucleic acid-protein affinity analysis method, based on highly expressed genes, important protein molecules are screened out;

[0059] A fusion vector based on cytoskeletal proteins, important protein molecules and green fluorescent protein tracking is constructed;

[0060] Based on the fusion vector of the disease model, the normal model and the drug treatment model, the risk genes and possible downstream proteins associated with the agglomerates are identified by spatial omics imaging, and the agglomeration process of the agglomerates is quantified.

[0061] As Figure 1As shown, the application uses important peripheral immune tissues or peripheral blood of disease models and normal models to extract nucleic acid molecules and proteins by organic phase separation method, and performs nucleic acid sequencing analysis. The high expression immune related gene and protein information is preliminarily screened out to construct an immune gene library.

[0062] The application uses the third generation tool of AlphaFold and the nucleic acid-protein affinity analysis method to screen out a protein molecule with the molecular structure characteristics of low complexity domain, shortest amino acid sequence and strongest nucleic acid molecule affinity. A green fluorescent protein fusion expression vector is constructed, and the expression is realized by using lipid nanoparticles to deliver it, and the formation and change of the condensate are detected and analyzed.

[0063] Based on the screening results, the application uses fluorescence probes and antibodies for in situ spatial omics imaging in important immune cells by comparing disease models and drug treatment models. The fusion protein is used to capture nucleic acid molecules and observe the signals in the condensate and the adjacent area to identify important nucleic acid and protein molecules that play an immune regulation function. At the same time, the fluorescence microscopy imaging results are quantified and subjected to difference analysis. The condensate is associated with the immune response, so as to accurately and effectively extract the binary condensate immune signal in situ, and promote the conversion of candidate drugs.

[0064] According to the embodiment of the application, the cytoskeletal protein is fused with an important protein molecule fragment, and the cytoskeletal protein has the core function of the cytoskeletal protein TPPP, is stably expressed in cells and has a large capture area. Figure 4 a, and has the IDR sequence of the important protein molecule fragment to drive the formation of the condensate, thereby capturing the nucleic acid molecules.

[0065] According to the embodiment of the application, as shown in Figure 2 The disease related high expression genes are screened out by using disease models, normal models and drug treatment models, including:

[0066] The peripheral immune tissues or peripheral blood of the disease model and the normal model are prepared into a disease model cell suspension and a normal model cell suspension;

[0067] The cells in the disease model cell suspension and the normal model cell suspension are lysed by using a nucleic acid extraction reagent, and the solution is subjected to organic phase separation. After standing, centrifugation is performed to obtain disease model cells and normal model cells.

[0068] The nucleic acids in the disease model cells and the normal model cells are separated and extracted for sequencing to obtain disease model expression genes and disease model protein information and normal model expression genes and normal model protein information.

[0069] By comparing the disease model expression genes and the normal model expression genes, high expression genes are screened out.

[0070] According to the embodiment of the present application, the peripheral immune tissues or peripheral blood of the disease model and the normal model are made into a disease model cell suspension and a normal model cell suspension, specifically including: taking fresh spleen tissues of a lupus erythematosus disease mouse and a normal mouse respectively, grinding, filtering through a 70-micron cell screen, and then making cell suspensions, and placing on ice. The peripheral blood is lysed by a red blood cell lysis solution, centrifuged, and the supernatant is discarded, and then resuspended in pre-cooled phosphate buffer.

[0071] According to the embodiment of the present application, the nucleic acids in the disease model cells and the normal model cells are separated and extracted for sequencing to obtain disease model expressed gene and disease model protein information and normal model expressed gene and normal model protein information, including:

[0072] The nucleic acid extraction reagent is added to the disease model cell suspension and / or the normal model cell suspension at a ratio of 1 milliliter of nucleic acid extraction reagent corresponding to every five million cells, and mixed evenly;

[0073] Chloroform is added to the disease model cell suspension and / or the normal model cell suspension, and mixed evenly, wherein the volume ratio of the nucleic acid extraction reagent to the chloroform is 10:1-10:3, to obtain a disease model lysis solution and / or a normal model lysis solution;

[0074] After standing and centrifugation, the disease model lysis solution and / or the normal model lysis solution undergoes organic phase separation, to obtain a water phase containing RNA, an organic phase containing DNA, and an intermediate phase containing proteins and other impurities.

[0075] According to the embodiment of the present application, the nucleic acid extraction reagent can be a TRIzol RNA extraction reagent, ThermoFisher Scientific.

[0076] According to the embodiment of the present application, the main components of the nucleic acid extraction reagent are phenol, guanidine isothiocyanate, and sodium dodecyl sulfate, etc.

[0077] According to the embodiment of the present application, the nucleic acids in the disease model cells and the normal model cells are separated and extracted for sequencing to obtain disease model expressed gene and disease model protein information and normal model expressed gene and normal model protein information, further including:

[0078] Isopropyl alcohol is added to the water phase, wherein the volume ratio of the nucleic acid extraction reagent to the isopropyl alcohol is 5:2-5:3, and after incubation at 4°C, the RNA in the water phase is precipitated by centrifugation;

[0079] An equal volume of anhydrous ethanol is added to the organic phase and mixed evenly, and the DNA is precipitated by centrifugation;

[0080] A 10% ethanol solution containing 0.1 mole of sodium citrate is added to the DNA, the precipitate is resuspended, and after incubation, centrifugation, and drying and washing, a DNA precipitate is obtained.

[0081] According to the embodiment of the present application, the nucleic acid in the disease model cell and the normal model cell is separated and extracted for sequencing to obtain the disease model expression gene and disease model protein information and the normal model expression gene and normal model protein information, specifically comprising: adding 1 milliliter of nucleic acid extraction reagent to the suspension according to the proportion of 1:5 million cells, and aspirating and mixing. After standing for 5 minutes, 0.2 milliliters of chloroform is added according to the proportion of 1 milliliter of reagent, and mixed. After standing for 3 minutes, the lysate is centrifuged at 12000xg at 4°C for 15 minutes to separate the organic phase.

[0082] The upper aqueous phase is transferred to a new test tube, and isopropanol is added according to the proportion of 0.5 milliliters of nucleic acid extraction reagent per 1 milliliter. After incubation at 4°C for 10 minutes, centrifugation is performed at 12000xg for 10 minutes to precipitate the RNA. The supernatant is discarded, and the precipitate is resuspended with 75% ethanol according to the proportion of 1:1. After centrifugation at 7500xg for 5 minutes, the supernatant is discarded, and the precipitate is dried for 5-10 minutes. Finally, the precipitate is redissolved with 50 microliters of RNAase-free water.

[0083] The organic phase is separated and mixed with an equal volume of anhydrous ethanol, and the DNA is precipitated by centrifugation at 2000xg for 5 minutes. The precipitate is resuspended with a 10% ethanol solution containing 0.1 mole of sodium citrate according to the proportion of 1:1. After incubation for 30 minutes, the supernatant is discarded after centrifugation at 2000xg at 4°C for 5 minutes, and the precipitate is air-dried for 5-10 minutes. The DNA is washed twice with 8 millimoles per liter of sodium hydroxide solution.

[0084] According to the embodiment of the present application, by comparing the disease model expression gene and the normal model expression gene, the high expression gene is screened out, including:

[0085] The separated DNA precipitate and RNA precipitate are subjected to high-throughput sequencing analysis to obtain the analysis results of the disease model and / or the normal model;

[0086] By comparing the analysis results of the disease model with the analysis results of the normal model, the differentially expressed genes are functionally annotated, and the high expression immune-related genes are screened out.

[0087] According to the embodiment of the present application, it further includes:

[0088] The high expression gene includes one or more of Camk4, Ddx4, Fas, Nox2, and Nlrp6.

[0089] According to the embodiment of the present application, as shown in Figure 3 The nucleic acid-protein affinity analysis method is used to screen out important protein molecules based on the high expression gene, specifically comprising:

[0090] Based on the screened high expression genes, the amino acid sequence of the protein product molecule is obtained. The AlphaFold third generation tool and nucleic acid-protein affinity analysis method are used to evaluate the properties of the protein molecule. The specific screening criteria are whether it has a low complexity domain, the length of the amino acid sequence, and the nucleic acid molecule affinity and other structural characteristics.

[0091] The low complexity domain of the relevant protein molecule is calculated by the model, and the important protein sequence is screened by the tool, which has the following characteristics: having a low complexity domain, the length of the amino acid sequence is 20, and the nucleic acid molecule affinity is strong. The screened amino acid fragment is referred to as TARGET, as shown in Figure 3 The protein database is searched for proteins containing the same sequence to further screen possible immune-related proteins.

[0092] According to an embodiment of the present application, a fusion vector based on cytoskeletal proteins, important protein molecules and green fluorescent protein tracing is constructed, including:

[0093] The cytoskeletal protein includes the cytoskeletal protein TPPP fragment in SEQ ID No. 1;

[0094] The high expression gene CAMK4 includes the nucleic acid sequence in SEQ ID No. 2;

[0095] The high expression gene DDX4 includes the nucleic acid sequence in SEQ ID No. 3;

[0096] The high expression gene FAS includes the nucleic acid sequence in SEQ ID No. 4;

[0097] The high expression gene NLRP6 includes the nucleic acid sequence in SEQ ID No. 5;

[0098] The important protein molecule includes the CAMK4 protein sequence in SEQ ID No. 6;

[0099] The important protein molecule includes the DDX4 protein sequence in SEQ ID No. 7;

[0100] The important protein molecule includes the FAS protein sequence in SEQ ID No. 8;

[0101] The important protein molecule includes the NLRP6 protein sequence in SEQ ID No. 9.

[0102] According to an embodiment of the present application, a fusion vector based on cytoskeletal proteins, important protein molecules and green fluorescent protein tracing is constructed, including:

[0103] As Figure 4As shown in step a, green fluorescent protein is used for fluorescence tracing, and the cytoskeleton protein fragment (aa. 45-166) removes the disordered sequence at both ends and retains its core function. The fusion carrier protein serves as a tool for capturing target RNA nucleic acid molecules after being expressed on the body surface.

[0104] According to the screened sequence fragments, primers are designed, and the corresponding gene fragments are amplified by PCR. Then, the amplified gene fragments and the vector are digested by using restriction endonucleases for enzyme digestion treatment, and the digested gene fragments are connected with the vector by using T4 DNA ligase. The constructed plasmid is mixed in proportion using Lipofectamine reagent (Thermo Fisher Scientific) and then transfected into cells for amplification on the culture medium.

[0105] According to an embodiment of the present application, based on the fusion carrier of the disease model, the normal model and the drug treatment model, the risk genes and possible downstream proteins associated with the condensate are identified by spatial omics imaging, and the condensation process of the condensate is quantified, including:

[0106] The detection and analysis of the condensate are realized by using fluorescence imaging, fluorescence bleaching recovery experiment and the like;

[0107] The important peripheral immune tissues of the disease model and the drug treatment model are made into samples;

[0108] The immune-related RNA nucleic acid molecules are captured and identified by using the fusion protein;

[0109] Spatial omics imaging is performed by using a confocal microscope, and fluorescence positioning, quantification and differential analysis are performed.

[0110] According to an embodiment of the present application, the detection and analysis of the condensate are realized by using fluorescence imaging, fluorescence bleaching recovery experiment and the like, including:

[0111] After transfection for 48 hours, observation is performed under a spinning disk confocal microscope with a 63-fold oil immersion objective lens. The condensate detection index is specifically: whether green fluorescence forms a condensate of sufficient size in the cell is observed under a microscope; secondly, the fluorescence intensity is counted and compared with the untransfected group to analyze whether there is a significant difference; the cell is treated with a small molecule reagent such as 1, 6-hexanediol which can dissolve the condensate droplet, and the morphological change of the condensate is observed; and a fluorescence bleaching recovery experiment is performed. Specifically, a 5*5 square micrometer size area is bleached by using a 488 nanometer wavelength laser, and the fluorescence intensity is recorded once every 5 seconds after bleaching, for a total of 5 minutes. The recovery of the fluorescence intensity is recorded and normalized. Whether the fluorescence intensity of the condensate recovers over time is continuously observed, and the recovery time is measured to quantify the droplet dynamics. The condensation process of the condensate is analyzed from multiple aspects.

[0112] The coagulation ability of the coagulation component screened is verified through the step. Meanwhile, the immune-related gene library and the coagulation process of the coagulation component are quantified.

[0113] According to an embodiment of the present application, the transfection reagent is Lipofectamine 3000 (Thermo Fisher Scientific), and the transfection process includes the following steps:

[0114] The cells are inoculated into a 24-well plate at 5-10 x 10^4 cells per well. Incubate overnight in a cell incubator at 37°C, 5% CO2.

[0115] In a sterile microcentrifuge tube A, dissolve 1-3 μg of plasmid DNA in 100 μL of Opti-MEM I Reduced Serum Medium, and mix gently. In another sterile microcentrifuge tube B, add 20 μL of Lipofectamine 3000 to 100 μL of Opti-MEM I Reduced Serum Medium, and mix gently. Incubate at room temperature for 5 minutes.

[0116] Add the diluted DNA solution in tube A to the diluted Lipofectamine 3000 solution in tube B, and mix gently. Incubate at room temperature for 15-20 minutes to form the DNA-Lipofectamine complex.

[0117] Wash three times with 1 mL of PBS, then aspirate the PBS. Add 100 μL of the DNA-Lipofectamine complex to each well, and gently shake the 24-well plate to distribute the complex evenly. Place the 24-well plate in the incubator and incubate for 4-6 hours.

[0118] After 4-6 hours, gently aspirate the medium containing the DNA-Lipofectamine complex. Add 1 mL of fresh cell culture medium containing 10% FBS and 1% penicillin-streptomycin to each well. Continue to incubate for 24-48 hours.

[0119] According to an embodiment of the present application, the drug treatment model is a disease model drug treatment result model after four weeks of treatment.

[0120] According to an embodiment of the present application, the autoimmune disease animal model is a systemic lupus erythematosus mouse, and the treatment model mouse is treated for 4 weeks by administering the candidate drug mycophenolate (MCE). The important peripheral immune tissue is the spleen, and the slice thickness is 50 microns.

[0121] According to an embodiment of the present application, the fusion protein is used to capture and recognize immune-related RNA nucleic acid molecules, including:

[0122] transcription of the fusion vector to obtain a vector RNA nucleic acid molecule;

[0123] The vector RNA nucleic acid molecule is injected into the mouse intravenously by means of lipid nanoparticle delivery, including:

[0124] The vector RNA nucleic acid molecule is dissolved in a sodium citrate buffer with a concentration of 5-10 millimoles per liter;

[0125] The vector RNA nucleic acid molecule is mixed with the lipid nanoparticle, and the mixture of the vector RNA nucleic acid molecule and the lipid nanoparticle is injected into the mouse intravenously,

[0126] The weight ratio of the total lipid in the lipid nanoparticle to the vector RNA nucleic acid molecule is in the range of 20:1-50:1.

[0127] According to the embodiments of the present application, as Figure 4 The RNA nucleic acid molecule after transcription of the fusion vector described above is injected into the mouse intravenously by means of lipid nanoparticle delivery, such as Figure 4 The tissue sample is taken 4 hours after injection.

[0128] The RNA delivery step is as follows: the molar mass of the sequence is calculated to determine the required molecular weight, the RNA is dissolved in a sodium citrate buffer with a concentration of 5-10 millimoles per liter. The RNA is mixed with the lipid nanoparticle, the weight ratio of the total lipid to the mRNA is 40:1, and the initial amount of RNA injected into each mouse is 2.5 micrograms (based on the body weight ratio of 0.1 microgram / gram). Each mouse is injected intravenously with 50 microliters of the mixture of the lipid and the RNA. According to the requirements, the gradient concentration is set, and the indicators of the agglomerate formation are further quantitatively analyzed.

[0129] The composition of the agglomerate and the adjacent space is confirmed by fluorescence co-localization. The presence of the screened highly expressed genes or proteins in the agglomerate space is observed to detect the immune correlation. At the same time, the agglomerate components are specifically extracted and analyzed to identify new RNA nucleic acid molecules with immune regulation function.

[0130] The RNA nucleic acid sequence captured by the cytoskeleton protein is identified by the method of immunocrosslinking co-immunoprecipitation and sequencing. The cell suspension is placed on ice, and the protein-nucleic acid complex is crosslinked by irradiation with ultraviolet light of 365 nanometer wavelength for 30 seconds. Subsequently, the complex is extracted according to the conventional method of immunocrosslinking co-immunoprecipitation, and sequencing is performed after purification to extract the nucleic acid molecule information.

[0131] According to the embodiments of the present application, the spatial omics imaging is performed by confocal microscopy, and the fluorescence localization, quantification and differential analysis are performed, specifically:

[0132] After four weeks of drug treatment, the therapeutic effect of the drug is confirmed by methods such as enzyme-linked immunosorbent assay detection of serum. Under a spinning disk confocal microscope, the sample section is observed with a 100x oil immersion objective to observe the distribution of the condensate in the cell.

[0133] The immune cell types are labeled using antibodies. Specifically, the cell labeling antibody is CD68-PE, and the specifically labeled immune cells are macrophages. The identified nucleic acid sequences are specifically labeled using a fluorescent probe.

[0134] Important immune cells are identified through the FITC channel, and the average fluorescence intensity, droplet number, and fluorescence area of the condensate in macrophages and other cells are calculated, and the molecular weight of each component in the condensate is quantified.

[0135] The imaging and analysis steps are as follows: when taking pictures, sample along the Z axis at 1 micrometer intervals, record the longitudinal full length of the tissue for 50 micrometers, and obtain 50 consecutive fluorescence image files with spatial information for each tissue sample.

[0136] Image processing scripts written in Python are used to identify and quantify the fluorescence points in each channel and calculate their area, number, and average fluorescence intensity; statistical difference analysis is performed on the above detection indicators and the control group. The data is subjected to non-parametric t-test using statistical software to obtain more information. The comparison is between the disease model and the drug treatment model, between macrophages and other tissue cells, and between intracellular and extracellular.

[0137] By integrating the difference information and the analysis results, new nucleic acid molecules and protein molecules with immune regulation function are found after visualization, and imaging and analysis of immune microenvironment in situ spatial omics are systematically realized.

[0138] The above specific embodiments further illustrate the purpose, technical solutions, and beneficial effects of the present application. It should be understood that the above description is only a specific embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.

Claims

1. A method for extracting immune signals from binary agglomerates, characterized in that, include: Disease-related high-expression genes were screened using disease models, normal models, and drug treatment models. Important protein molecules were screened based on the highly expressed genes using nucleic acid-protein affinity analysis. A fusion vector based on cytoskeletal proteins, the aforementioned important protein molecules, and green fluorescent protein tracking was constructed; Based on the fusion vector of the disease model, normal model and drug treatment model, risk genes and downstream proteins associated with aggregates are identified by spatial omics imaging, and the aggregation process of aggregates is quantified. The screening of disease-related highly expressed genes using disease models, normal models, and drug treatment models includes: The peripheral immune tissues or peripheral blood of the disease model and the normal model were used to prepare disease model cell suspensions and normal model cell suspensions; The cells in the disease model cell suspension and the normal model cell suspension were lysed using a nucleic acid extraction reagent, and the solutions were separated into organic phases. After standing, the solutions were centrifuged to obtain the disease model cells and the normal model cells. Nucleic acids were isolated and extracted from the disease model cells and the normal model cells and sequenced to obtain information on genes and proteins expressed in the disease model and proteins expressed in the normal model. By comparing the genes expressed in the disease model with those expressed in the normal model, highly expressed genes are screened out.

2. The method for extracting immune signals from binary agglomerates according to claim 1, characterized in that, The fusion vector based on disease models, normal models, and drug treatment models identifies risk genes and potential downstream proteins associated with agglomerates through spatial omics imaging, and quantifies the agglomerate aggregation process, including: Fluorescence imaging and fluorescence bleaching recovery assay techniques were used to detect and analyze condensates. Samples were prepared from key peripheral immune tissues in disease models and drug treatment models. The fusion protein was used to capture and recognize immune-related RNA nucleic acid molecules. Spatial omics imaging was performed using confocal microscopy to conduct fluorescence localization, quantification, and differential analysis.

3. The method for extracting immune signals from binary agglomerates according to claim 1, characterized in that, The process involves separating and extracting nucleic acids from the disease model cells and the normal model cells, and sequencing them to obtain information on genes and proteins expressed in the disease model and those expressed in the normal model, including: Add the nucleic acid extraction reagent to the disease model cell suspension and / or normal model cell suspension at a ratio of 1 ml of nucleic acid extraction reagent per 5 million cells, and mix well; Chloroform was added to the disease model cell suspension and / or normal model cell suspension, and the mixture was stirred. The volume ratio of the nucleic acid extraction reagent to the chloroform was 10:1-10:3 to obtain the disease model lysis buffer and / or normal model lysis buffer. After standing and centrifugation, the lysate from the disease model and / or the lysate from the normal model undergo organic phase separation to obtain an aqueous phase containing RNA, an organic phase containing DNA, and an intermediate phase containing proteins and impurities.

4. The method for extracting immune signals from binary agglomerates according to claim 1, characterized in that, The step of separating and extracting nucleic acids from the disease model cells and the normal model cells for sequencing to obtain information on disease model expressed genes and proteins, as well as information on normal model expressed genes and proteins, further includes: Isopropanol is added to the aqueous phase, wherein the volume ratio of the nucleic acid extraction reagent to the isopropanol is 5:2-5:

3. After incubation at 4°C, the RNA in the aqueous phase is precipitated by centrifugation. Add an equal volume of anhydrous ethanol to the organic phase, mix well, and centrifuge to precipitate the DNA; Add a 10% ethanol solution containing 0.1 moles of sodium citrate to the DNA, resuspend the precipitate, incubate, centrifuge, dry and wash to obtain the DNA precipitate.

5. The method for extracting immune signals from binary agglomerates according to claim 1, characterized in that, The process of screening for highly expressed genes by comparing the genes expressed in the disease model and the genes expressed in the normal model includes: The separated DNA and RNA precipitates were subjected to high-throughput sequencing analysis to obtain the analysis results of the disease model and / or normal model. By comparing the analysis results of the disease model with those of the normal model, the differentially expressed genes are functionally annotated, thereby screening out highly expressed immune-related genes.

6. The method for extracting immune signals from binary agglomerates according to claim 1, characterized in that, Also includes: The highly expressed genes include one or more of Camk4, Ddx4, Fas, Nox2, and Nlrp6.

7. The method for extracting immune signals from binary agglomerates according to claim 6, characterized in that, The constructed fusion vector based on cytoskeletal proteins, the aforementioned important protein molecules, and green fluorescent protein tracking includes: The cytoskeletal protein includes the cytoskeletal protein TPPP fragment in SEQ ID No. 1; The highly expressed gene CAMK4 includes the nucleic acid sequence in SEQ ID No. 2; The highly expressed gene DDX4 includes the nucleic acid sequence in SEQ ID No. 3; The highly expressed gene FAS includes the nucleic acid sequence in SEQ ID No. 4; The highly expressed gene NLRP6 includes the nucleic acid sequence in SEQ ID No. 5; The important protein molecule includes the CAMK4 protein sequence in SEQ ID No. 6; The important protein molecule includes the DDX4 protein sequence in SEQ ID No. 7; The important protein molecule includes the FAS protein sequence in SEQ ID No. 8; The important protein molecule includes the NLRP6 protein sequence in SEQ ID No.

9.

8. The method for extracting immune signals from binary agglomerates according to claim 4, characterized in that, The method of using fusion proteins to capture and recognize immune-related RNA nucleic acid molecules includes: The fusion vector was transcribed to obtain vector RNA nucleic acid molecules. The carrier RNA nucleic acid molecule was intravenously injected into mice via lipid nanoparticle delivery, including: The vector RNA nucleic acid molecule was dissolved in sodium citrate buffer at a concentration of 5-10 mmol / L; The carrier RNA nucleic acid molecule was mixed with the lipid nanoparticles, and the mixture was intravenously injected into mice. The weight ratio of total lipids in the lipid nanoparticles to the carrier RNA nucleic acid molecules ranges from 20:1 to 50:

1.

9. The method for extracting immune signals from binary agglomerates according to claim 6, characterized in that, The drug treatment model is the result model of the disease model after four weeks of drug treatment.

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