Mass spectrometry flow-based multi-dimensional detection of epigenetic and metabolic single cells

Abstract

This invention discloses a single-cell multidimensional detection composition and application for epigenetics and metabolism based on mass cytometry. The invention provides an antibody composition for single-cell multidimensional mass cytometry, comprising: A1) an antibody group for labeling cell surface proteins, A2) an antibody group for labeling intracellular proteins, and A3) an antibody group for labeling mixed-sample tags, including a CD45 antibody. The antibody composition of this invention innovatively constructs a 44-channel detection system including 20 surface marker antibodies, 18 intracellular marker antibodies, and 6 CD45 barcode antibodies. It can analyze, at single-cell resolution, the complete biological chain of how epigenetic modifications of innate immune cells, under external stimulation, crosstalk with intracellular kinase phosphorylation signals, thereby altering cellular metabolic state (Arginase-1) and ultimately affecting the release of effector factors (such as IL-6, IFN-γ, etc.).

Description

Technical Field

[0001] This invention belongs to the field of biological detection and immunology technology, and relates to a single-cell multidimensional detection composition for epigenetics and metabolism based on mass cytometry and its application. Background Technology

[0002] The innate immune system, as the body's first line of defense against invading pathogens, plays an irreplaceable and crucial role in sensing danger signals, reshaping the tissue microenvironment, and initiating subsequent adaptive immune responses. In recent years, with the rapid development of immune checkpoint inhibitors, personalized tumor vaccines, and novel adjuvant vaccines, accurately analyzing the heterogeneity and functional activation status of innate immune cells (such as classical / non-classical monocytes, myeloid / plasma-like dendritic cells, and natural killer cells) at the single-cell level has become a key step in the pharmacodynamic evaluation of innovative drugs and the immune monitoring of clinical trials.

[0003] Currently, flow cytometry is the most widely used mainstream detection technology in this field. However, in actual industrial applications targeting large-scale clinical cohorts or multi-center vaccine subjects, existing technologies still have the following significant defects and shortcomings: (i) The fragmentation of detection dimensions and low throughput limit the discovery of functional biomarkers: Existing commercial flow cytometry detection solutions usually focus on cell surface lineage typing or detect a limited number of intracellular functional molecules. The activation of innate immune cells is a highly dynamic and complex process regulated by multiple signaling nodes; a simple surface phenotype or the production of a single cytokine cannot truly reflect the final functional efficacy of the cell. In the preclinical and clinical evaluation of drugs or vaccines, there is an urgent need for detection tools capable of integrating and analyzing the following key functional modules: epigenetic remodeling events that determine cell differentiation and memory formation (such as m6A modification of RNA and histone H3K27ac acetylation levels); upstream kinase cascades mediating signal transduction and transcriptional activation (such as phosphorylation levels of STAT1 / STAT3 and downstream ribosomal protein S6 in the mTOR pathway); indicators reflecting the immunosuppressive state of the microenvironment and metabolic reprogramming (such as the expression level of arginase-1); and core cycle markers (Ki-67) indicating cell proliferation and survival potential. Current technologies cannot achieve spatial physical co-capture and signal amplification of the above-mentioned cross-dimensional (nuclear, cytoplasmic, and cell membrane) targets in the same reaction system and at the same single-cell resolution, leading to the loss of a large amount of information on key functional subpopulations that determine differences in drug response. (II) Significant batch effects lead to incomparability of data across experiments and centers, severely hindering translational medicine evaluation: When conducting batch testing of dozens to hundreds of clinical samples required for drug registration applications, traditional flow cytometry and open-well plate detection methods are easily affected by differences in operating techniques, antibody batch differences, and daily instrument fluctuations, which can easily introduce severe batch effects. To ensure data availability, existing technologies often rely on complex backend R language or Python algorithms for batch correction. However, this purely "mathematical correction" is essentially a post-hoc remedy, which may not only overfit real biological differences but also fail to meet the high requirements for detection precision, intermediate precision, and batch-to-batch consistency in clinical testing or drug development. (III) Complex and unstandardized operating procedures make it difficult to achieve high-throughput automation: Current multicolor schemes relying on flow cytometry are complex and require highly experienced operators, and intracellular staining involves tedious steps such as fixation and membrane perforation, and multiple centrifugation and washing. These steps increase sample processing variability and operational errors, and may affect the detection stability of some intracellular functional molecules, which is not conducive to the standardization of existing manual operation processes into automated clinical testing products that comply with GMP / GLP standards in the industrial sector.

[0004] Therefore, there is an urgent need in this field to develop a multi-parameter mass spectrometry flow cytometry detection product that can reduce batch calibration requirements, has the ability to perform physical mixing and standardization of multiple samples, and can achieve joint detection of multiple intracellular and extracellular functional indicators, so as to effectively support the clinical evaluation of the immune effects of modern innovative drugs and vaccines. Summary of the Invention

[0005] To address the limitations of existing flow cytometry assays in monitoring innate immune cell function, such as limited detection dimensions, insufficient compatibility for combined detection of multiple intracellular targets, and batch-to-batch variations introduced by multi-sample batch processing, this invention provides a metal isotope-labeled antibody composition based on a mass spectrometry flow cytometry platform, and a standardized method for combined detection of multiple parameters in single cells using this composition.

[0006] To address the aforementioned technical problems, a first aspect of the present invention provides an antibody composition for single-cell multidimensional mass cytometry, the antibody composition comprising: A1) A group of antibodies used to label cell surface proteins, including CD8 antibody, CD4 antibody, CD3 antibody, IgD antibody, CD1c antibody, CD183 antibody, CD86 antibody, CD57 antibody, CD192 antibody, CD14 antibody, CD56 antibody, TCR-γδ antibody, CD38 antibody, CD27 antibody, CD123 antibody, CD45RA antibody, HLA-DR antibody, CD11c antibody, CD19 antibody, and CD16 antibody; A2) A group of antibodies for labeling intracellular proteins, including IFN-α antibody, CXCL9 antibody, H3K27ac antibody, IL-1β antibody, pS6 antibody, TNF-α antibody, IL-4 antibody, Ki-67 antibody, CXCL10 antibody, Arginase-1 antibody, IL-6 antibody, MCP-1 antibody, CD69 antibody, m6A antibody, Granzyme B antibody, IFN-γ antibody, pSTAT1 antibody, and pSTAT3 antibody; A3) Antibody group used to label mixed samples, which includes CD45 antibody.

[0007] In the antibody composition described above, each antibody is labeled with a different metal isotope.

[0008] In the antibody composition described above, the metal isotope is any one of the following: 141Pr, 150Nd, 112Cd, 142Nd, 143Nd, 145Nd, 156Gd, 161Dy, 171Yb, 173Yb, 209Bi, 115In, 147Sm, 152Sm, 158Gd, 159Tb, 160Gd, 155Gd, 170Er, 174Yb 169Tm, 162Dy, 165Ho, 172Yb, 176Yb, 144Nd, 148Nd, 151Eu, 153Eu, 154Sm, 167Er, 168Er, 175Lu, 146Nd, 149Sm, 163Dy, 164Dy, 166Er, 106Cd, 110Cd, 111Cd, 113Cd, 114Cd and 116Cd.

[0009] In the antibody composition described above, each isotope-labeled antibody is written as antibody-metal isotope, where the part before the hyphen is the antibody and the part after the hyphen is the labeled metal isotope. For example, CD3-141Pr indicates that the antibody CD3 is labeled with the metal isotope 141Pr.

[0010] In the antibody composition described above, the antibody group shown in A1) includes CD3-141Pr, CD57-150Nd, CD8-112Cd, IgD-142Nd, CD1c-143Nd, CD183-145Nd, CD56-156Gd, CD123-161Dy, HLA-DR-171Yb, CD11c-173Yb, CD16-209Bi, CD4-115In, CD86-147Sm, CD192-152Sm, TCR-γδ-158Gd, CD38-159Tb, CD27-160Gd, CD14-155Gd, CD45RA-170Er, and CD19-174Yb; The antibody group shown in A2) includes Granzyme B-169Tm, Ki-67-162Dy, IL-6-165Ho, IFN-γ-172Yb, pSTAT3-176Yb, IFN-α-144Nd, H3K27ac-148Nd, pS6-151Eu, TNF-α-153Eu, IL-4-154Sm, CD69-167Er, m6A-168Er, pSTAT1-175Lu, CXCL9-146Nd, IL-1β-149Sm, CXCL10-163Dy, Arginase-1-164Dy, and MCP-1-166Er; The antibody group shown in A3) includes: CD45-106Cd, CD45-110Cd, CD45-111Cd, CD45-113Cd, CD45-114Cd and CD45-116Cd.

[0011] Secondly, the present invention provides the application of the antibody composition of the first aspect in the preparation of single-cell multidimensional mass spectrometry flow cytometry detection products.

[0012] Thirdly, the present invention provides a single-cell multidimensional mass cytometry detection product, which includes the antibody composition of the first aspect.

[0013] In some implementations, the product is a chip or a reagent kit.

[0014] Fourthly, the present invention provides a method for single-cell multidimensional mass cytometry detection, the method being for non-disease diagnosis and treatment purposes, comprising the following steps: B1) Incubate N single-cell samples to be tested with protein transport inhibitors to obtain N pretreated single cells, where N is a natural number greater than or equal to 1 and less than or equal to 20. B2) The N pretreated single cells were labeled with CD45 antibodies labeled with different metal isotopes using multiple barcodes to obtain N pretreated single cells with multiple barcodes; the N pretreated single cells with multiple barcodes were then combined to obtain a mixed sample pool, and the mixed sample pool was washed using a laminar flow washing device to obtain barcode-stained cell samples. The multiple barcode labeling is achieved by labeling each pretreated single cell with any three antibodies from the antibody group shown in A3 in the first aspect. The three metal isotope-labeled CD45 antibodies labeled in each pretreated single cell sample are different from each other, resulting in N pretreated single cells with multiple barcode labeling. B3) The barcode-stained cell samples were sequentially stained with live and dead cells and then with FcR-blocking staining to obtain the processed cells; B4) The treated cells are stained with the antibody group shown in A1) of the first aspect to obtain surface antibody-stained cells; B5) Fix and perforate the surface antibody-stained cells to obtain fixed and perforated cells; B6) The fixed and perforated cells were stained with the antibody group shown in A2) of the first aspect to obtain intracellular antibody-stained cells; B7) The cells stained with the intracellular antibody were then stained with DNA intercalating agent and then analyzed by mass spectrometry flow cytometry to obtain single-cell multidimensional data.

[0015] In some embodiments, a portion of the cells is stained with AO / PI before incubation with the protein transport inhibitor to determine cell concentration and viability.

[0016] In some embodiments, the N single-cell samples to be tested are peripheral blood mononuclear cell samples to be tested.

[0017] In an embodiment of the present invention, the N single-cell samples to be tested can be 748 single-cell samples to be tested.

[0018] In some embodiments, the single-cell multidimensional data includes at least one of the following: 1) fine subpopulation annotation results, and 2) multidimensional target expression abundance data. The detailed subset annotation results include single-cell typing and frequency data of classical immune cell subsets such as B cells, CD4+ T cells, CD8+ T cells, monocytes, dendritic cells, NK cells, and γδ T cells, and / or single-cell typing and frequency data of 69 detailed immune cell subsets (e.g., HLA-DR+ plasmacytoid dendritic cells, IL-6+ classical monocytes, central memory CD4+ T cells, effector memory CD4+ T cells, Ki-67+ CD16- CD56++ NK cells, CD38+ effector CD4+ T cells, etc.).

[0019] The multidimensional target expression abundance data includes the expression levels or dynamic changes of epigenetic modifications (m6A, H3K27ac), kinase phosphorylation signals (pSTAT1, pSTAT3), cellular metabolic state (Arginase-1), proliferative activity (Ki-67), or effector cytokines (IL-6, IFN-γ, CXCL10, etc.) of various fine immune cell subsets at the single-cell level.

[0020] In the method described above, the protein transport inhibitors are Brefeldin A and Monensin.

[0021] In some embodiments, the protein transport inhibitor is incubated for 2 hours.

[0022] In some embodiments, the mixed sample pool is washed using a laminar flow washing device under the following conditions: flow rate: 10 μL; volume: 80 μL; cycles: 25.

[0023] In the method described above, the dye used for staining the dead and live cells is cisplatin.

[0024] In the method described above, the DNA intercalating agent is an Ir-DNA intercalating agent.

[0025] This invention innovatively constructs a mass spectrometry flow cytometry antibody composition consisting of up to 44 metal isotope-labeled antibodies. It not only includes a first antibody group targeting classic surface typing such as CD14, CD16, CD11c, and CD123, but also, more importantly, introduces a combined intracellular and epigenetic antibody group: including Ki-67 for assessing proliferation, pSTAT1 and pSTAT3 for assessing interferon and inflammatory signal reception, pS6 for assessing translational and metabolic activity, Arginase-1 for assessing myeloid-suppressive function, IFN-α / CXCL9 for assessing effector output, and m6A and H3K27ac for revealing deep regulatory mechanisms. Combined with six anti-CD45 barcode antibodies labeled with 106Cd, 110Cd, 111Cd, 113Cd, 114Cd, and 116Cd, this composition achieves "three out of six" multiplex labeling pooling of 20 independent samples.

[0026] The beneficial effects of the present invention are that the antibody composition of the present invention and its application have the following advantages: Deep integration of multiple omics dimensions: For the first time at single-cell resolution, this study reveals the complete biological chain of how epigenetic modifications of innate immune cells, under external stimulation, interfere with intracellular kinase phosphorylation signals, thereby altering cellular metabolic state (Arginase-1) and ultimately affecting the release of effector factors (such as IL-6, IFN-γ, etc.).

[0027] High throughput and zero batch effect: By pooling 20 independent samples into a single sample pool for staining and instrumentation, not only can antibody reagents and instrument time be significantly saved, but batch effects caused by experimental operations and instrument fluctuations can also be significantly reduced.

[0028] Data consistency and standardization closed loop: By introducing laminar wash technology for non-mechanical damage washing and combining it with customized high-dimensional data cleaning algorithms, extremely high data repeatability is guaranteed. Attached Figure Description

[0029] Figure 1 Seven metal channels (140Ce, 142Nd, 151Eu, 153Eu, 165Ho, 175Lu, 176Yb) were selected as internal references for microsphere standardization.

[0030] Figure 2 The image shows the result of signal drift correction for microsphere standardization.

[0031] Figure 3 This is a deconvolution scatter plot of 20 independent samples encoded using a "choose three out of six" combination based on six CD45 codes (106Cd to 116Cd).

[0032] Figure 4 The image shows the demixing verification results of the Single Cell Debarcoding software, demonstrating the cell purity and demixing efficiency of 20 independent samples.

[0033] Figure 5 The UMAP dimensionality reduction plot is colored according to the experimental pool, showing that the cells in different pools are uniformly mixed and distributed without obvious batch effect clustering.

[0034] Figure 6 A panoramic view of the distribution of peripheral blood innate immune cell subsets (UMAP dimensionality reduction).

[0035] Figure 7 Heatmaps of six classic immune cell subset markers.

[0036] Figure 8 This is a schematic diagram of a hierarchical clustering strategy.

[0037] Figure 9 UMAP distribution map of 69 fine subsets of immune cells.

[0038] Figure 10 An overview of the phenotypic characteristics of 69 fine subgroups.

[0039] Figure 11 This is a dynamic graph showing the significant increase in the frequency of monocytes and dendritic cells and the decrease in the frequency of T cells on day 1 after vaccination.

[0040] Figure 12 A line graph showing the upregulation of expression of functional molecules (IFN-γ, Ki-67, CXCL10, pSTAT1) in innate immune cell populations was used to capture early activation signals of vaccines.

[0041] Figure 13 The frequency of the breakthrough infection group was compared with that of the non-breakthrough infection group at the coarse cell subset level (no significant difference).

[0042] Figure 14 This represents the fine cellular subpopulation characteristics of the breakthrough infection group.

[0043] Figure 15 Heatmap of cellular expression heterogeneity of epigenetic probes (H3K27ac and m6A) in the breakthrough infection group and the non-breakthrough infection group.

[0044] Figure 16 This study aimed to analyze the differential expression of H3K27ac in "IL-6+ classical monocytes" and specific subtypes of NK cells (Ki-67+CD16-CD56++) and m6A in specific subtypes of CD4+ T cells (CD38+ effector type) between the infected and uninfected groups.

[0045] Figure 17 Box plot showing differential expression of H3K27ac and m6A in specific cell subpopulations in breakthrough infection and non-breakthrough infection populations.

[0046] Figure 18 This study presents a Spearman correlation network topology diagram of specific fine immune cell subsets and serum cytokines and neutralizing antibodies, revealing the linkage mechanism between epigenetic modifications (m6A / H3K27ac), kinase signaling (pSTAT3), metabolic enzymes (Arginase-1), and effector factors (IL-6, IFN-γ). Detailed Implementation

[0047] The present invention will now be described in further detail with reference to specific embodiments. The given embodiments are merely illustrative of the invention and not intended to limit its scope. The embodiments provided below can serve as a guide for further improvements by those skilled in the art and do not constitute a limitation on the invention in any way.

[0048] Unless otherwise specified, the experimental methods used in the following examples are conventional methods, performed according to the techniques or conditions described in the literature in this field or according to the product instructions. Unless otherwise specified, the materials and reagents used in the following examples are commercially available.

[0049] Unless otherwise specified, the quantitative experiments in the following examples are all repeated three times, and the results are averaged.

[0050] Terms and Abbreviations CyTOF: Mass Flow Cytometry; R10 Medium: R10 culture medium, formulated as RPMI-1640 (Thermo Fisher, catalog number C11875500BT) + 10% FBS (Thermo Fisher, catalog number C11875500BT) + 1% Pen-strepsolution (Vivacell, catalog number C3420-0100). CSB: Cell Staining Buffer, formula (excluding Ca) 2+ / Mg 2+ PBS (Sangon Biotech Shanghai Co., Ltd., catalog number E607009) + 2% FBS; BFA: Brefeldin A (Sigma-Aldrich, catalog number B5936-200UL). Monensin: Protein Transport Inhibitor (Waters Corporation, Product No. 554724); Cisplatin: Cell viability staining solution labeled with 195 Pt (Hangzhou Pukang Medical Technology Co., Ltd., catalog number P03536-0000). FCR-blocking: Used to block FCR-related staining without interfering with antibody-mediated specific staining (Biolegend, catalog number 422302). Ir-DNA: Nucleic acid intercalating agent containing iridium (Hangzhou Pukang Medical Technology Co., Ltd., catalog number P03534-0000).

[0051] Example 1: Antibody combination and titration required for high-parameter mass spectrometry flow cytometry detection 1. Single-cell multidimensional mass cytometry detection of antibody compositions In the initial design phase of the research and development, a detailed technical survey and evaluation of currently available commercial CyTOF detection antibody compositions was conducted. The survey revealed that existing commercial antibody compositions have significant technical bottlenecks: they cannot simultaneously detect intracellular metabolic enzymes (such as Arginase-1), kinases (pSTAT1 / 3), and extremely fragile epigenetic modification molecules (m6A, H3K27ac).

[0052] To overcome the challenge of simultaneous detection of multidimensional targets, we first explored and compared various conditions for the immobilization and permeation system (focusing on comparing the performance of methanol-immobilized and permeation systems and Foxp3-immobilized and permeation systems under different stimulation conditions). Preliminary experimental results confirmed that different permeation conditions significantly affected the signal retention of specific markers. Conventional systems did indeed lead to the loss of some surface antigen epitopes or severe attenuation of epigenetic / kinase signals, failing to achieve a balance between phenotype and epigenetic characteristics.

[0053] Furthermore, in mass cytometry, if metal isotope channels are randomly superimposed, the instrument will generate inherent signal spillover and impurity interference between adjacent mass number (M±1) and isotope oxide (M+16) channels, which can easily lead to the masking of low-abundance targets and the generation of false positives.

[0054] To this end, after long-term antibody titration, channel arrangement optimization, and signal-to-noise ratio (SNR) testing, combined with the optimal conditions of the membrane permeation system, dozens of isotope conjugation schemes were compared and screened. Ultimately, the precise pairing combinations of 44 specific antibodies and isotopes of this invention were determined. This scheme scientifically allocates highly expressed surface antigens to metal channels with low background interference, while avoiding the oxide interference channels of the main high-abundance proteins in the same system for the extremely difficult-to-detect m6A (designated 168Er channel) and H3K27ac (designated 148Nd channel).

[0055] After screening, the antibody composition for single-cell multidimensional mass spectrometry flow cytometry detection was determined to contain the following 44 isotope-labeled antibodies (isotope-labeled antibodies are written in the format of antibody-metal isotope, indicating that the antibody is labeled with a metal isotope): Surface protein antibodies: CD3-141Pr antibody, CD57-150Nd antibody, CD8-112Cd antibody, IgD-142Nd antibody, CD1c-143Nd antibody, CD183-145Nd antibody, CD56-156Gd antibody, CD123-161Dy antibody, HLA-DR-171Yb antibody, CD11c-173Yb antibody, CD16-209Bi antibody, CD4-115In antibody, CD86-147Sm antibody, CD192-152Sm antibody, TCR-γδ-158Gd antibody, CD38-159Tb antibody, CD27-160Gd antibody, CD14-155Gd antibody, CD45RA-170Er antibody, and CD19-174Yb antibody.

[0056] Intracellular protein antibodies: Granzyme B-169Tm antibody, Ki-67-162Dy antibody, IL-6-165Ho antibody, IFN-γ-172Yb antibody, pSTAT3-176Yb antibody, IFN-α-144Nd antibody, H3K27ac-148Nd antibody, pS6-151Eu antibody, TNF-α-153Eu antibody, IL-4-154Sm antibody, CD69-167Er antibody, m6A-168Er antibody, pSTAT1-175Lu antibody, CXCL9-146Nd antibody, IL-1β-149Sm antibody, CXCL10-163Dy antibody, Arginase-1-164Dy antibody, and MCP-1-166Er antibody.

[0057] Six CD45 metal-tagged antibodies in the mixed sample: Six anti-human CD45 antibodies labeled with 106Cd, 110Cd, 111Cd, 113Cd, 114Cd and 116Cd: CD45-106Cd antibody, CD45-110Cd antibody, CD45-111Cd antibody, CD45-113Cd antibody, CD45-114Cd antibody and CD45-116Cd antibody.

[0058] The antibodies used in this study were commercially available antibodies, as detailed in Table 1. After purchasing the naked antibodies, we used the Maxpar MCP9 and Maxpar X8 metal antibody tagging kits from StandardBioTools to metal label the naked antibodies, obtaining antibodies labeled with different isotopes at a concentration of 0.5 mg / ml. (The antibody preservation reagent for the Maxpar MCP9 metal antibody tagging kit was CANDOR's HRP-Protector, catalog number 222500; the antibody preservation reagent for the Maxpar X8 metal antibody tagging kit was Antibody Stabilizer (CANDOR, catalog number 131500) and ProClin300 (Sigma-Aldrich, catalog number 48912-U).

[0059] Table 1 is a list of antibodies.

[0060] 2. Single-cell multidimensional mass cytometry detection of antibody composition titration Before large-scale sample staining, the six CD45 metal tag antibodies, surface antibodies and intracellular antibodies used for sample mixing were rigorously titrated to determine the optimal working concentration, ensure the highest signal-to-noise ratio and eliminate interchannel leakage interference.

[0061] 1) Cell preparation All antibody titrations were performed using PBMCs (peripheral blood mononuclear cells) isolated and frozen from leukocytes of healthy individuals.

[0062] 2) Mixed sample labeled CD45 antibody titration For six anti-human CD45 antibodies labeled 106Cd, 110Cd, 111Cd, 113Cd, 114Cd, and 116Cd, a series of concentration gradients were set for staining titration. The starting concentration was set to 1 µl, and a total of four gradient concentrations and one blank tube were set to ensure that the signal intensity of each tag was uniform and there was no cross-contamination during the "three out of six" multiplex labeling separation.

[0063] 3) Surface protein antibody titration The initial concentration of the surface antibody titration was set to 2 µl, and a total of 5 gradient concentrations and one blank tube were set.

[0064] 4) Intracellular protein antibody titration The initial concentration of intracellular antibodies (including signaling molecules and epigenetic markers) was set at 4 µl, and five gradient concentrations and one blank control tube were also set up. 5) Data analysis and concentration determination After the titration samples were collected by MSFLO mass cytometry (Hangzhou PTK Medical Technology Co., Ltd.), quality control operations such as cell debris removal, double cell adhesion, and dead cell removal were performed using FlowJo software, and the samples were then uniformly merged and compared. The gradient concentration with the best discrimination between positive and negative groups and the lowest background signal was selected as the final titer concentration, and the "mixed sample label", "surface antibody mixture" and "intracellular antibody mixture" were prepared according to this concentration for subsequent formal experiments.

[0065] Mixed labeling: CD45-106Cd antibody, CD45-110Cd antibody, CD45-111Cd antibody, CD45-113Cd antibody, CD45-114Cd antibody and CD45-116Cd antibody were specifically added to Cell Staining Buffer (CSB solution). 1 µl of each metal isotope-labeled antibody was added to 99 µl of CSB solution, with a concentration of 5 µg / mL.

[0066] Surface protein antibody mixture: Dissolve the surface protein antibodies in Cell Staining Buffer according to Table 2, and the volume of each antibody added and its concentration in a 100ul staining system are shown in Table 2.

[0067] Table 2 shows the preparation of surface protein antibody mixtures.

[0068] Intracellular protein antibody mixture: The intracellular protein antibodies shown in Table 3 were dissolved in the Permeabilization buffer of the Invitrogen Transcription FacTor Staining Buffer Set (catalog number 00-5523) kit, and the volume of each antibody added and its concentration in a 100ul staining system are shown in Table 3.

[0069] Table 3 shows the preparation of intracellular protein antibody mixtures.

[0070] Example 2: Establishment of a single-cell multidimensional mass cytometry detection method for innate immunity Objective: To standardize the entire process of single-sample innate immune mass spectrometry flow cytometry detection of 20 individuals, including cell resuscitation, metal antibody staining, on-machine collection and routine maintenance, to ensure data consistency, reproducibility and meet the needs of drug development and large-scale clinical cohort studies.

[0071] Based on time-of-flight mass cytometry (CyTOF), this technology enables the simultaneous detection of 44 immune biomarkers using metal-tagged antibody labeling. It is suitable for: multidimensional mapping analysis of innate immune cells, dynamic monitoring of drug targets (such as the pSTAT3 / pS6 signaling pathway), and large-scale clinical cohort studies (20 samples / batch).

[0072] 1. Pre-treatment of cells (single cells from 20 samples per experiment) 1) Twenty single-cell cryovials were rapidly shaken in a 37°C water bath to thaw the frozen cells until the solids inside were about the size of soybeans. The cells were then removed from the water bath and slowly added dropwise to 15mL centrifuge tubes. The cryovials were rinsed twice with 1mL of R10 Medium and then added to the centrifuge tubes. Finally, R10 Medium was added to a final volume of 6mL.

[0073] 2) Centrifuge 500g at room temperature for 5 minutes and discard the supernatant.

[0074] 3) Resuspend the cells in 1 mL of R10 Medium, then add more R10 Medium to 6 mL. Place the 15 mL centrifuge tube containing the cells in a 37°C, 5% CO2 cell culture incubator for 1 hour (the cap should be loosened appropriately to ensure gas supply to the cells).

[0075] 4) Remove the cells from the incubator, tighten the cap, invert the centrifuge tube to mix, take a small sample of 10µl, mix with an equal volume of AO / PI staining solution, and use a cell counter to determine the concentration and viability of live cells.

[0076] 5) In addition to the small sample taken for AO / PI detection as described above, centrifuge the remaining cells at 500 g for 5 minutes at room temperature and discard the supernatant. Adjust the cell concentration to approximately 0.682 × 10⁻⁶ cells using R10 Medium. 7 220 µl of cell suspension per well was seeded into 96-well plates, with 2 wells per sample (1.5 million cells / well). 200 µl of PBS was added to the perimeter of each well to prevent culture medium evaporation.

[0077] 6) Prepare the blocking agent according to Table 4 (the purpose is to block the secretion of cytokines by the sample), and seed it into 96-well plates at 5.9 µl / well. Incubate in a CO2 incubator for 2 hours to obtain 20 pretreated single-cell samples.

[0078] Table 4 shows the formulation of the blocking agents.

[0079] 2. Staining process 1) Prepare a laminar flow washing machine 2) Collect cells a. After incubation, collect 20 pretreated single-cell samples from the culture plate. Wash each well twice with 200µl R10Medium. Collect the cells from each sample into 15mL centrifuge tubes, for a total of 20 tubes. Add 2mL Cell Staining Buffer to each tube and centrifuge at 500g for 5 minutes at room temperature. Discard the supernatant. b. Resuspend the cells in 2 mL of Cell Staining Buffer, centrifuge at 500 g for 5 minutes at room temperature, discard the supernatant, and clean the cells. c. Resuspend the cells with 90ul Cell Staining Buffer, bringing the total cell suspension in the tube to 100ul.

[0080] 3) Mixed sample label staining and sample pooling a. According to Table 5, prepare the mixed label for each sample in an eight-tube strip, add 1 μL of each mixed label, and add 3 μL of mixed labels to each sample. Add the prepared mixed label (3 μL in total) to the corresponding cell sample, mix well by pipetting, and then spread it into a 96-well laminar flow washing plate, 2 wells per sample, 50 μL per well. Place the plate in a laminar flow washing machine and let it settle and incubate for 45 minutes. Table 5 shows the preparation of mixed sample labels.

[0081] b. After staining incubation, the mixed sample pool is washed using a laminar flow washing device under the following conditions: flow rate 10 μL, volume 80 μL, and 25 cycles. c. After washing, combine all cells from 20 samples into a 15mL centrifuge tube. Wash each well twice with 50µl Cell Staining Buffer and collect the cells into a 15mL centrifuge tube. Add Cell Staining Buffer to a final volume of 6mL, mix well by pipetting, divide into 3 equal tubes, each containing 2mL of cell suspension, centrifuge at 500g at room temperature for 5 minutes, and discard the supernatant. d. Use 2 mL of PBS (without Ca2+)2+ / Mg 2+ Resuspend the cells, centrifuge at 500 g for 5 minutes at room temperature, and discard the supernatant; 4) Cisplatin staining a. Prepare cisplatin staining solution according to Table 6. Add 1 mL of cisplatin staining solution prepared in Table 6 to each tube, resuspend and mix the cell pellet, and let it react at room temperature for 5 minutes. Table 6 shows the cisplatin staining solutions.

[0082] b. Add 2 mL of Cell Staining Buffer to the centrifuge tube to stop the reaction. Centrifuge at 500 g for 5 minutes at room temperature and discard the supernatant. c. Add 2 mL of Cell Staining Buffer to resuspend the cells, centrifuge at 500 g at room temperature for 5 minutes, discard the supernatant, and clean the cells. 5) FcR-blocking staining Resuspend cells in 85 μL Cell Staining Buffer, add 5 μL FcR-blocking, for a total staining system of 100 μL. Mix well by pipetting and incubate at room temperature for 10 minutes. There is no need to remove the blocking solution after incubation.

[0083] 6) Surface antibody staining a. Add 100 μL of the surface protein antibody mixture prepared in Table 2 to each tube, mix the sample by pipetting (be careful to avoid generating air bubbles), and incubate at room temperature for 30 minutes; b. After the sample staining incubation is complete, add 2 mL of Cell Staining Buffer to each sample tube, centrifuge at 500 g at room temperature for 5 minutes, and discard the supernatant; wash twice in total. 7) Fix the ruptured membrane a. Prepare Fixation / Permeabilization (Invitrogen Transcription FacTor Staining Buffer Set, catalog number 00-5523) according to Tables 7 and 8 of the kit instructions. Mix the cells in the residual supernatant by pipetting, add 1 mL of Fixation / Permeabilization buffer as shown in Table 7 to each tube, and incubate at room temperature for 30 minutes in the dark. Table 7 shows the Fixation / Permeabilization buffer.

[0084] Table 8 shows the Permeabilization buffer.

[0085] b. Add 2 mL of the Permeabilization buffer shown in Table 8 to the sample, centrifuge at 800 g for 5 minutes at room temperature, and discard the supernatant; c. Resuspend the cells in 2 mL of Permeabilization buffer, centrifuge at 800 g at room temperature for 5 minutes, discard the supernatant, and clean the cells. 8) Intracellular antibody staining a. Add two portions of 100 μL intracellular protein antibody as shown in Table 3 to each tube, resuspend the cells in a total of 200 μL antibody mixture, and incubate at room temperature for 30 minutes. b. After incubation, add 2 mL of Cell Staining Buffer to the sample, centrifuge at 800 g for 5 minutes at room temperature, and discard the supernatant; wash twice in total. 9) Ir-DNA staining a. Prepare the Ir-DNA staining solution according to Table 9, dilute it with the fixation and membrane-breaking agent (Ir staining special, Hangzhou Pukang Medical Technology Co., Ltd., product number P03535-0000), add 1 mL of the Ir-DNA staining solution shown in Table 9 to each sample, and immediately pipette to mix well; b. Incubate at room temperature for 1 hour or at 4°C overnight (4°C can be stored for 48 hours) until just before processing. Use CSB to wash away the Ir-DNA staining solution to obtain stained cells. Table 9 shows the Ir-DNA staining solution.

[0086] 3. On-machine testing Before analysis, the stained cells were resuspended in a solution containing 7-channel calibration microspheres (140Ce, 142Nd, 151Eu, 153Eu, 165Ho, 175Lu, 176Yb) (Hangzhou Pukang Medical Technology Co., Ltd., catalog number P03533-0000) for signal drift correction and standardization during subsequent data reading. The stained cells were analyzed using MSFLO mass cytometry (Hangzhou Pukang Medical Technology Co., Ltd.). Based on the ion count of each metal channel in each cell, the expression level of the corresponding antibody-binding protein was obtained, yielding single-cell multidimensional immunophenotypic data. This data includes single-cell typing and frequency data of classical and refined immune cell subsets, as well as epigenetic modifications, kinase phosphorylation signals, cell metabolic state, proliferative activity, and expression abundance data of effector cytokines within each subset. This allows for comprehensive detection of cell typing, proliferative state, interferon and inflammatory signal reception status, translational and metabolic activity, myeloid suppression function, effector output, and deep regulatory mechanisms.

[0087] Example 3: Application of innate immunity single-cell multidimensional mass cytometry in the characterization of immune response and breakthrough infection in a large vaccine cohort. To verify the technical effectiveness of the 44-color antibody composition and high-throughput barcoding detection method of the present invention in real large-scale clinical samples, this embodiment uses the composition to analyze 748 samples from a prospective COVID-19 mRNA vaccine cohort (peripheral blood mononuclear cell samples collected at two time points: before and the first day after vaccination from 374 individuals who received the COVID-19 mRNA vaccine in Kunming, Yunnan in 2023, and simultaneously followed up to observe breakthrough infection records in this cohort within 180 days after vaccination (Yunnan University Affiliated Hospital Medical Ethics Committee Review No.: 2023113, ClinicalTrials.gov NCT05907044).

[0088] I. Innate Immunity Single-Cell Multidimensional Mass Cycling Detection The 748 single-cell samples were tested according to the method in Example 2, with 20 samples per test. Samples with fewer than 20 samples were also considered as one test. A total of 38 tests were conducted.

[0089] II. Data Acquisition, Microsphere Standardization and Automatic Unmixing The expression levels of the corresponding antibody-binding proteins were obtained using an MSFLO mass cytometry system (Hangzhou Spectrum Medical Technology Co., Ltd.).

[0090] 1) The expression levels of the corresponding antibody-binding proteins were normalized and deconvolved using MATLAB-based software.

[0091] a. Signal drift correction: Using the "Bead Normalization" software module, the expression of 7 metal channels (140Ce, 142Nd, 151Eu, 153Eu, 165Ho, 175Lu, 176Yb) corresponding to custom microspheres (Beads) was selected as internal parameters. Figure 1 This effectively corrected for short-term and long-term signal fluctuations during mass spectrometry detection, ensuring high comparability of data from a large batch of 748 samples. Figure 2 This effectively eliminated instrument signal fluctuations in 748 samples, ensuring data comparability.

[0092] b. High-throughput automated single-cell unmixing: The composition utilizes CD45 antibodies labeled with six cadmium (Cd) isotopes (106Cd to 116Cd), and mixing is achieved through a "three-out-of-six" combination encoding. The FCS file of the mixed samples was extracted using "Single Cell Debarcoding" software. By setting a reasonable unmixing threshold (Minimum separation cutoff) and combining it with Mahalanobis distance to remove cell debris or incorrectly assigned cells, the mixed data was successfully deconvolved into 748 clean single-sample FCS files (containing the protein expression levels of all single cells within each sample). Figure 3 , Figure 4 ),like Figure 3 and Figure 4 As shown, the scatter plot boundaries between different coding combinations are clear, the barcode signals of each sample have extremely high separation, and there is no significant cross-interference between channels. Simultaneously, the use of Mahalanobis distance effectively eliminates two-cell and non-specifically bound cell debris. This fully demonstrates that the 'six-to-three' isotope coding strategy employed in this invention achieves 20-fold high-throughput mixed sample processing while ensuring extremely high single-cell resolution accuracy and data recovery quality.

[0093] Figure 3 A demixing threshold was selected for one sample in the mixed sample, where 111000 represents samples containing 106Cd-CD45, 110Cd-CD45, and 111Cd-CD45, but not containing 113Cd-CD45, 114Cd-CD45, and 116Cd-CD45. Cell debris was removed by Mahalanobis distance, and the mixed sample was successfully demixed into pure single subject data.

[0094] Figure 4 The number 111000 indicates that it contains 106Cd-CD45, 110Cd-CD45, and 111Cd-CD45, but does not contain 113Cd-CD45, 114Cd-CD45, or 116Cd-CD45.

[0095] 2) High-resolution single-cell dimensionality reduction clustering and fine subpopulation annotation The 748 individual sample FCS files were merged and demixed using the Pytometry toolkit in Python 3.12.5 (converted to AnnData format), and 5000 cells / samples were downsampled and standardized using the inverse hyperbolic sine function (arcsinh, cofactor=5).

[0096] a. Classical Immune Cell Subpopulation Identification: After data quality control (removal of dead and adherent cells), 3.39 million cells were extracted and batch-corrected using Harmony-Py. Based on PCA features, the 15 nearest neighbors were calculated and a nearest neighbor graph was constructed. Clustering was performed using the Leiden algorithm, and dimensionality reduction was achieved using UMAP. This successfully identified six classical immune cell subpopulations: B cells, CD4+ T cells, CD8+ T cells, monocytes and dendritic cells, NK cells, and γδ T cells. Figure 5 , Figure 6 , Figure 7 ). Figure 6 After Harmony batch correction, the six classic immune cell subsets (B cells, CD4+ T cells, CD8+ T cells, monocytes and dendritic cells, NK cells, and γδ T cells) were clearly separated.

[0097] b. Functional biomarker-driven fine-grained subpopulation analysis: To reveal the heterogeneity within immune cells, using a Python 3.12.5 environment, and combining open-source packages such as pytometry, anndata, and scanpy with machine learning libraries (such as scikit-learn and scipy), cell subsets were extracted from each of the aforementioned major subpopulations. The nearest neighbor graph was reconstructed using the functional and phenotypic biomarkers in the antibody ensemble of this invention, and the Leiden algorithm was applied for fine-grained partitioning. Figure 8 This hierarchical clustering ultimately identified 69 fine subsets of immune cells, and preliminary visualization was performed using packages such as matplotlib and seaborn, comprehensively reflecting the complex heterogeneity of the innate immune network in real clinical samples. Figure 9 , Figure 10 ).

[0098] 3) Statistical mining and biological mechanism analysis of multidimensional data Feature matrices and single-cell expression abundance data of the 69 fine subsets of immune cells were extracted for biological feature mining. During the data reshaping and statistical testing phase, open-source toolkits such as dplyr, data.table, tidyr, and broom in the R language environment were used for data cleaning and model validation. Simultaneously, open-source visualization and analysis modules such as ggplot2, ggpubr, patchwork, Rmisc, and FME were used to graphically render multidimensional spatial features, target expression differences, and correlation networks. Through this systematic high-dimensional data mining, the dynamic immune landscape and deep mechanisms of breakthrough infection in the vaccinated population were successfully elucidated, validating the application value of this composition.

[0099] a. Early dynamic activation capture of innate immunity: Data shows that on day 1 after vaccination, the frequency of monocytes and dendritic cells (DCs) increased significantly, while the frequency of T cells decreased. Figure 11 Simultaneously, the functional molecules (IFN-γ, Ki-67, CXCL10, pSTAT1) in the composition of this invention showed significantly increased expression in the innate immune cell population, perfectly capturing the rapid activation and proliferation response of the innate immune system to vaccines. Figure 12 ).

[0100] b. Immune subset characteristics of breakthrough infection: Compared with the non-breakthrough infection population, there was no significant difference in the breakthrough infection population at the crude subset level. Figure 13 However, further analysis of this composition revealed a significant reduction in HLA-DR+ pDCs and IL-6+ classical monocytes, while central memory and effector memory CD4 T cells increased on day 1 post-inoculation. Figure 14 HLA-DR+ plasmacytoid dendritic cells and IL-6+ classical monocytes were significantly reduced, while central memory and effector memory CD4+ T cells increased on day 1 post-inoculation.

[0101] c. Validation of core advantages (analysis of the linkage between epigenetics and functional metabolism): The core epigenetic probes (H3K27ac and m6A) of the composition of this invention show significant expression heterogeneity in different immune subsets. Figure 15 Analysis revealed that H3K27ac expression in both IL-6+ classical monocytes and specific NK cell subtypes (Ki-67+ CD16- CD56++) in the infected group was significantly lower than that in the uninfected group before and after inoculation; simultaneously, m6A expression in CD38+ effector CD4 T cells in the infected group was also significantly inhibited after inoculation. Figure 16 , Figure 17 Furthermore, through Spearman correlation analysis, a synergistic association between specific fine immune subsets and serum cytokines and neutralizing antibodies was successfully established. Figure 18 ).

[0102] The above results fully demonstrate that the mass spectrometry flow cytometry detection composition provided by this invention can sensitively and reliably indicate the correlation between epigenetic markers and the risk of breakthrough infection at the single-cell level, providing clues for further mechanism research.

[0103] The present invention has been described in detail above. For those skilled in the art, the invention can be practiced in a wide range of ways with equivalent parameters, concentrations, and conditions without departing from its spirit and scope, and without requiring unnecessary experiments. Although specific embodiments have been given, it should be understood that further modifications can be made to the invention. In summary, according to the principles of the invention, this application is intended to include any changes, uses, or improvements to the invention, including changes made using conventional techniques known in the art that depart from the scope disclosed herein. Some of the essential features can be applied within the scope of the following appended claims.

Claims

1. An antibody composition for single-cell multidimensional mass cytometry, characterized in that: The antibody composition comprises: A1) A group of antibodies used to label cell surface proteins, including CD8 antibody, CD4 antibody, CD3 antibody, IgD antibody, CD1c antibody, CD183 antibody, CD86 antibody, CD57 antibody, CD192 antibody, CD14 antibody, CD56 antibody, TCR-γδ antibody, CD38 antibody, CD27 antibody, CD123 antibody, CD45RA antibody, HLA-DR antibody, CD11c antibody, CD19 antibody, and CD16 antibody; A2) A group of antibodies for labeling intracellular proteins, including IFN-α antibody, CXCL9 antibody, H3K27ac antibody, IL-1β antibody, pS6 antibody, TNF-α antibody, IL-4 antibody, Ki-67 antibody, CXCL10 antibody, Arginase-1 antibody, IL-6 antibody, MCP-1 antibody, CD69 antibody, m6A antibody, Granzyme B antibody, IFN-γ antibody, pSTAT1 antibody, and pSTAT3 antibody; A3) Antibody group used to label mixed samples, which includes CD45 antibody.

2. The antibody composition according to claim 1, characterized in that: Each antibody is labeled with a different metal isotope.

3. The antibody composition according to claim 2, characterized in that: The metal isotope is any one of the following: 141Pr, 150Nd, 112Cd, 142Nd, 143Nd, 145Nd, 156Gd, 161Dy, 171Yb, 173Yb, 209Bi, 115In, 147Sm, 152Sm, 158Gd, 159Tb, 160Gd, 155Gd, 170Er, 174Yb, 169Tm 162Dy, 165Ho, 172Yb, 176Yb, 144Nd, 148Nd, 151Eu, 153Eu, 154Sm, 167Er, 168Er, 175Lu, 146Nd, 149Sm, 163Dy, 164Dy, 166Er, 106Cd, 110Cd, 111Cd, 113Cd, 114Cd and 116Cd.

4. The antibody composition according to any one of claims 1-3, characterized in that: The antibody group shown in A1) includes CD3-141Pr, CD57-150Nd, CD8-112Cd, IgD-142Nd, CD1c-143Nd, CD183-145Nd, CD56-156Gd, CD123-161Dy, HLA-DR-171Yb, CD11c-173Yb, CD16-209Bi, CD4-115In, CD86-147Sm, CD192-152Sm, TCR-γδ-158Gd, CD38-159Tb, CD27-160Gd, CD14-155Gd, CD45RA-170Er, and CD19-174Yb; The antibody group shown in A2) includes Granzyme B-169Tm, Ki-67-162Dy, IL-6-165Ho, IFN-γ-172Yb, pSTAT3-176Yb, IFN-α-144Nd, H3K27ac-148Nd, pS6-151Eu, TNF-α-153Eu, IL-4-154Sm, CD69-167Er, m6A-168Er, pSTAT1-175Lu, CXCL9-146Nd, IL-1β-149Sm, CXCL10-163Dy, Arginase-1-164Dy, and MCP-1-166Er; The antibody group shown in A3) includes: CD45-106Cd, CD45-110Cd, CD45-111Cd, CD45-113Cd, CD45-114Cd and CD45-116Cd.

5. The use of the antibody composition of any one of claims 1-4 in the preparation of single-cell multidimensional mass cytometry detection products.

6. A single-cell multidimensional mass cytometry detection product comprising the antibody composition of any one of claims 1-4.

7. A method for single-cell multidimensional mass cytometry detection in a single instance, wherein the method is for non-disease diagnosis and treatment purposes, comprising the following steps: B1) Incubate N single-cell samples to be tested with protein transport inhibitors to obtain N pretreated single cells, where N is a natural number greater than or equal to 1 and less than or equal to 20. B2) The N pretreated single cells were subjected to multiple barcode labeling using CD45 antibodies labeled with different metal isotopes to obtain N pretreated single cells with multiple barcode labeling. The N pretreated single cells with multiple barcode labels are then combined to obtain a mixed sample pool. The mixed sample pool is then washed using a laminar flow washing device to obtain barcode-stained cell samples. The multiple barcode labeling is performed by labeling each pretreated single cell with any three antibodies from the antibody group shown in claim 4 (A3). The three metal isotope-labeled CD45 antibodies labeled in each pretreated single cell sample are different from each other, resulting in N pretreated single cells with multiple barcode labeling. B3) The barcode-stained cell samples were sequentially stained with live and dead cells and then with FcR-blocking staining to obtain the processed cells; B4) Stain the treated cells with the antibody group shown in A1) of any one of claims 1-4 to obtain surface antibody-stained cells; B5) Fix and perforate the surface antibody-stained cells to obtain fixed and perforated cells; B6) The fixed and perforated cells are stained with the antibody group shown in A2) of any one of claims 1-4 to obtain intracellular antibody-stained cells; B7) The cells stained with the intracellular antibody were then stained with DNA intercalating agent and then analyzed by mass spectrometry flow cytometry to obtain single-cell multidimensional data.

8. The method according to claim 7, characterized in that: The protein transport inhibitors are Brefeldin A and Monensin.

9. The method according to claim 7 or 8, characterized in that: The dye used to stain the dead and live cells is cisplatin.

10. The method according to any one of claims 7-9, characterized in that: The DNA intercalating agent is an Ir-DNA intercalating agent.

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