A macrophage polarization detection method based on metasurface plasmonic resonance and application thereof

Abstract

The application provides a macrophage polarization detection method based on metasurface plasmonic resonance and application, and relates to the technical field of biological detection. The detection method comprises the following steps: preparing a MetaSPR biosensor; adding the macrophages to be detected to the MetaSPR biosensor, so that the macrophages are in contact with antibodies; using the metasurface plasmonic resonance technology to detect the resonance signal generated by the combination of the antibodies and the surface markers of the macrophages in real time; and judging the polarization state of the macrophages according to the resonance signal. The detection method based on the MetaSPR technology can establish a macrophage polarization evaluation platform in one step, without labels, with high throughput and rapidness. The MetaSPR macrophage polarization platform does not need labels, and can complete single-step detection by directly placing the cells on the MetaSPR biosensor. The MetaSPR macrophage polarization platform can simultaneously perform classification analysis on 96 uncharacterized macrophage samples within 15 minutes.

Description

Technical Field

[0001] This invention relates to the field of biodetection technology, and in particular to a method and application for detecting macrophage polarization based on metasurface plasmon resonance. Background Technology

[0002] Macrophages are diverse innate immune cells that play a crucial role in regulating immune responses and tissue repair. As highly plastic cells, macrophages can differentiate into two main phenotypes based on different stimuli: the pro-inflammatory M1 subtype and the anti-inflammatory M2 subtype. These differentiated macrophages are involved in the development and progression of various diseases and influence disease course in different ways.

[0003] With the development of biosensing technology, surface plasmon resonance (SPR) has attracted widespread attention as a label-free, real-time, and highly sensitive detection technique. Traditional SPR techniques require coupling prisms to excite photons, which is limited by complex optical equipment and suffers from insufficient sensitivity and spatial resolution. In contrast, metasurface plasmon resonance (MetaSPR) achieves direct light-plasma coupling through a periodic array of nanostructures, eliminating the need for traditional prism configurations. This technology has been widely applied in affinity analysis, biomarker detection, and cell proliferation and cytotoxicity research. However, its application in immunology still requires further exploration.

[0004] Therefore, this invention is proposed. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention provides a method and application for macrophage polarization detection based on metasurface plasmon resonance (MAP). This detection method based on MetaSPR technology enables a one-step, label-free, high-throughput, and rapid establishment of a macrophage polarization assessment platform. This MetaSPR macrophage polarization platform requires no markers; cells are simply placed directly on the MetaSPR biosensor to complete a single-step detection. It can simultaneously classify and analyze 96 uncharacterized macrophage samples within just 15 minutes.

[0006] In order to achieve the objective of this invention, the following technical solution is adopted: This invention provides a method for detecting macrophage polarization based on metasurface plasmon resonance, comprising the following steps: S1. Fabrication of MetaSPR biosensors; S2. Add the macrophages to be tested onto the MetaSPR biosensor to bring the macrophages into contact with the antibody; S3. Real-time detection of resonance signals generated by the binding of antibodies to macrophage surface markers using metasurface plasmon resonance technology; S4. Determine the polarization state of macrophages based on resonance signals.

[0007] Furthermore, S1 specifically includes: S101, Prepare a 96-well MetaSPR plate; S102. Immobilize antibodies on the surface of a 96-well MetaSPR plate.

[0008] Furthermore, S101 specifically includes: forming a nanocup array pattern on a silicon substrate by laser interference lithography and ion etching, coating a UV-curable adhesive onto the patterned mold, covering it with a PET film, and peeling the PET film off the mold after UV curing to obtain a PET film with a nanocup structure. Subsequently, titanium and gold layers were deposited sequentially on the surface of the PET film to form the MetaSPR chip; The MetaSPR chip is cut and fixed onto a standard 96-hole board to obtain a 96-hole MetaSPR board.

[0009] Furthermore, S102 specifically includes: adding a protein A solution into the chip wells to allow protein A to adsorb onto the chip surface; then adding an antibody solution into the chip wells to allow the antibody to be directionally immobilized on the chip surface through the specific binding of protein A to the Fc region of the antibody; After antibody fixation, casein-containing buffer is added to the chip wells for incubation to block the remaining active sites.

[0010] Furthermore, in S102, adding the antibody solution to the chip wells specifically includes: immobilizing anti-CD80 antibody, anti-CD86 antibody, anti-CD206 antibody, and anti-CD163 in different chip wells.

[0011] Furthermore, the antibodies are: anti-CD80 antibody, anti-CD86 antibody, anti-CD206 antibody, and anti-CD163 antibody.

[0012] Furthermore, the polarization states include M0, M1, or M2.

[0013] Furthermore, the macrophage surface markers include: M1 macrophage markers and / or M2 macrophage markers; Among them, the M1 macrophage markers are selected from any one or more of CD80 or CD86; M2 macrophage markers are selected from any one or more of CD206 or CD163.

[0014] Furthermore, the macrophages to be tested are in the state of a live cell suspension, and the sample volume of the macrophages to be tested is 80,000 to 100,000 live cells / mL.

[0015] This invention also provides a MetaSPR biosensor based on a metasurface plasmon resonance method for detecting macrophage polarization, the MetaSPR biosensor comprising: The substrate layer is a PET film with a periodic nanocup array structure; A metal layer is deposited on the surface of the nanocup array structure; Protein A layer, wherein the protein A layer is adsorbed onto the surface of the metal layer; An antibody layer, wherein the antibody layer is directionally immobilized on a protein A layer by the specific binding of protein A to the Fc region of the antibody, wherein the antibody is selected from one or more of anti-CD80 antibody, anti-CD86 antibody, anti-CD206 antibody and anti-CD163 antibody; The amino acid sequence of the protein A layer is shown in SEQ ID NO.1.

[0016] SEQ ID NO.1 AQGTVDAKFDKEQQNAFYEILHLPNLTEEQRNAFIQSLKDDPSQSANLLAEAKKLNDAQAPKVDAKFDKEQQNAFYEILHLPNLTEEQRNAFIQSLKDDPSQSANLLAEAKKLNDAQA PKVDAKFDKEQQNAFYEILHLPNLTEEQRNAFIQSLKDDPSQSANLLAEAKKLNDAQAPKVDAKFDKEQQNAFYEILHLPNLTEEQRNAFIQSLKDDPSQSANLLAEAKKLNDAQAPKC Furthermore, the metal layer comprises a gold layer and a titanium layer, wherein the titanium layer is in direct contact with the substrate layer; the thickness of the gold layer is 80nm~100nm, and the thickness of the titanium layer is 5nm~10nm.

[0017] The present invention also provides a macrophage polarization assessment device, including the above-mentioned MetaSPR biosensor and a detection instrument for detecting metasurface plasmon resonance signals.

[0018] This invention also provides the application of the above-mentioned macrophage polarization detection method based on metasurface plasmon resonance, or MetaSPR biosensor, or macrophage polarization assessment device in drug screening, immunomodulator evaluation, or probiotic screening.

[0019] The present invention has the following technical effects: This detection method offers a rapid, label-free, and high-throughput real-time detection approach. This one-step detection can quickly classify macrophage polarization states (M0, M1, M2) and assess their relative polarization levels within just 15 minutes, effectively overcoming the limitations of existing polarization detection methods. The platform integrates multiple surface biomarkers and has the ability to process large numbers of samples simultaneously, making it an ideal tool for large-scale immunological research and drug development.

[0020] The accuracy and specificity of this detection method based on MetaSPR have been validated through high consistency with flow cytometry. It can also assess unknown macrophage samples and measure their polarization levels relative to standard induction conditions, providing a robust, rapid and reliable tool for studying macrophage polarization, which is helpful for mechanism research, immunotherapy evaluation and preclinical drug development. Attached Figure Description

[0021] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0022] Figure 1 The results of MetaSPR chip performance characterization and antibody immobilization strategy optimization are as follows: a) shows the preparation process of the 96-well MetaSPR plate; b) shows the absorption spectrum of 0%-18% sucrose solutions; c) shows the differential spectrum of 0%-18% sucrose solutions after baseline correction; and d) shows the difference in optical density (OD) between the corresponding sucrose solutions at two wavelengths. 605 –OD 585 e represents the dual-wavelength optical density value (OD). 605 -OD 585The intensity varies with refractive index (RI), and the data are expressed as mean ± standard deviation, with n = 3 independent samples; f is a schematic diagram of two preparation methods for functionalizing MetaSPR biosensors with two antibodies; g is the dynamic monitoring curve of anti-CD86 antibody immobilization on the MetaSPR chip; h is the corresponding response value of anti-CD86 antibody immobilization on the MetaSPR chip; i is the dynamic monitoring curve of anti-CD80 antibody immobilization on the MetaSPR chip; j is the corresponding response value of anti-CD80 antibody immobilization on the MetaSPR chip; k is the dynamic monitoring result of anti-CD206 antibody immobilization on the MetaSPR chip; l is the corresponding relative response value of anti-CD206 antibody immobilization on the MetaSPR chip; m is the dynamic monitoring curve of anti-CD163 antibody immobilization on the MetaSPR chip; n is the corresponding relative response value of anti-CD163 antibody immobilization on the MetaSPR chip. Figure 2 The MetaSPR biosensor was used to assess the affinity of macrophage-related CD markers. Figure a shows a schematic diagram of affinity detection for CD86, CD80, CD206, and CD163; figure b shows the kinetic curve of the interaction between CD86 and anti-CD86 antibody; figure c shows the kinetic curve of the interaction between CD80 and anti-CD80 antibody; figure d shows the kinetic curve of the interaction between CD206 and anti-CD206 antibody; figure e shows the kinetic curve of the interaction between CD163 and anti-CD163 antibody; figure f shows the relative response difference corresponding to the interaction between different concentrations of CD86 and anti-CD86 antibody; and figure g shows the interaction between different concentrations of CD86 and anti-CD86 antibody. The relative response differences between CD80 and anti-CD80 antibody; h represents the relative response differences between CD206 and anti-CD206 antibody at different concentrations; i represents the relative response differences between CD163 and anti-CD163 antibody at different concentrations; j represents the fitted curves of the interaction between CD86 and anti-CD86 antibody at different concentrations; k represents the fitted curve of the interaction between CD80 and anti-CD80 antibody; l represents the fitted curve of the interaction between CD206 and anti-CD206 antibody; m represents the fitted curve of the interaction between CD163 and anti-CD163 antibody. Data are expressed as mean ± standard deviation, and n = 3 independent samples. Figure 3The image shows the polarization of M1 macrophages in cells measured using the MetaSPR biosensor. Figure a shows a schematic diagram of M1 macrophage induction and detection using the MetaSPR biosensor; figure b shows representative images of each group before and 24 hours after inducing agent treatment (scale bar: 100 μm); figure c shows a schematic diagram for selecting the optimal number of test cells; figure d shows the dynamic monitoring results of M1 and M0 macrophages with different cell numbers; figure e shows the relative response values ​​of M1 and M0 macrophages with different cell numbers in the kinetic data; figure f shows the dynamic monitoring of M1 and M0 macrophages using the MetaSPR biosensor with anti-CD86 antibody; figure g shows the signal response values ​​of M1 and M0 macrophages monitored using the anti-CD86 MetaSPR biosensor; figure h shows the dynamic monitoring of M1 and M0 macrophages using the anti-CD86 MetaSPR biosensor; figure i shows the signal response values ​​of M1 and M0 macrophages monitored ... i shows the signal response values ​​of M1 and M0 macrophages monitored using the anti-CD86 MetaSPR biosensor; figure j shows the signal response values ​​of M1 and M0 macrophages monitored using the anti-CD86 MetaSPR biosensor; figure j shows the signal response values ​​of M1 and M0 macrophages monitored using the anti-CD86 MetaSPR biosensor; figure j Signal response values ​​of the MetaSPR biosensor for dynamic monitoring of M1 and M0 macrophages; j is a schematic diagram of the induction, inhibition, and detection of M1 macrophages using the MetaSPR biosensor; k is the dynamic monitoring of M1 macrophages using the anti-CD86 MetaSPR biosensor under induction and inhibition conditions; l is the dynamic monitoring of M1 macrophages using the anti-CD80 MetaSPR biosensor under induction and inhibition conditions; data are expressed as mean ± SD, n = 3 independent samples, p ≥ standard error; *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001 (Tukey HSD post-hoc test was performed after one-way ANOVA); Figure 4The image shows the polarization of M2 macrophages in cells measured using the MetaSPR biosensor. Figure a shows a schematic diagram of M2 macrophage induction and detection using MetaSPR technology; figure b shows representative images of each group before and 48 hours after induction treatment (scale bar: 100 μm); figure c shows dynamic monitoring of M2 and M0 macrophages using the anti-CD206 MetaSPR biosensor; figure d shows the signal response values ​​of M1 and M0 macrophages monitored using the anti-CD206 MetaSPR biosensor; figure e shows the dynamic monitoring of M2 and M0 macrophages using the anti-CD163 MetaSPR biosensor; figure f shows the signal response values ​​of M2 and M0 macrophages monitored using the anti-CD163 MetaSPR biosensor; figure g shows a schematic diagram of M2 macrophage induction, inhibition, and detection using the MetaSPR biosensor; figure h shows the dynamic monitoring of M2 macrophages under induction and inhibition conditions using the anti-CD206 MetaSPR biosensor; figure i shows the signal response values ​​of M2 macrophages under induction and inhibition conditions using the anti-CD163 MetaSPR biosensor. The MetaSPR biosensor dynamically monitors M2 macrophages under induced inhibition conditions; Figure 5This paper presents a comprehensive analysis of macrophage polarization using the MetaSPR biosensor, showcasing different polarization levels. Figure a illustrates the detection principle of the MetaSPR biosensor using CD80 and CD86 markers to detect M0 and M2 macrophages, and CD206 and CD163 markers to detect M0 and M1 macrophages. Figure b shows the dynamic monitoring of M1 and M0 macrophages using the anti-CD206 MetaSPR biosensor. Figure c shows the signal response values ​​of M1 and M0 macrophages using the anti-CD206 MetaSPR biosensor. Figure d shows the dynamic monitoring of M1 and M0 macrophages using the anti-CD163 MetaSPR biosensor. Figure e shows the signal response values ​​of M1 and M0 macrophages using the anti-CD163 MetaSPR biosensor. Figure f shows the dynamic monitoring of M2 and M0 macrophages using the anti-CD86 MetaSPR biosensor. Figure g shows the signal response values ​​of M2 and M0 macrophages using the anti-CD86 MetaSPR biosensor. Figure h shows the signal response values ​​of M2 and M0 macrophages using the anti-CD80 MetaSPR biosensor. MetaSPR biosensor dynamically monitored M2 and M0 macrophages; i represents the signal response values ​​of M2 and M0 macrophages dynamically monitored using the anti-CD80 MetaSPR biosensor, with data expressed as mean ± standard deviation, n=3 independent samples; j is a schematic diagram of clustering M1 macrophages based on CD86 and CD80 expression levels; k is a heatmap of CD86 and CD80 MetaSPR signals in each treatment group; l is a schematic diagram of clustering M1 macrophages based on CD206 and CD163 expression levels; m is a heatmap of CD206 and CD163 MetaSPR signals in each treatment group; n=5 independent samples, ns indicates p≥0.05; *p<0.05; **p<0.01; ***p<0.001; ****p<0.0001 (Tukey HSD post-hoc test was used after one-way ANOVA); Figure 6 The following is an assessment of macrophage polarization induced by norcantharidin (NCTD): a) Representative flow cytometry analysis results of M1 macrophages polarized at different concentrations of NCTD; b) Analysis of four macrophage subsets classified according to CD80 and CD86 expression; c) Schematic diagram of macrophage polarization status assessed by MetaSPR technology at different concentrations of NCTD; d) Dynamic monitoring of CD86 markers after macrophage treatment with different concentrations of NCTD using an anti-CD86 MetaSPR biosensor; e) Signal response values ​​of CD86 markers after macrophage treatment with different concentrations of NCTD using an anti-CD86 MetaSPR biosensor; f) Correlation fitting curve (R²) between CD86 signal values ​​measured by the MetaSPR platform and the proportion of CD86-positive cells detected by flow cytometry. 2=0.9749); g represents the dynamic monitoring of CD80 markers after macrophages were treated with different concentrations of NCTD using the anti-CD80 MetaSPR biosensor; h represents the signal response value of CD80 markers after macrophages were treated with different concentrations of NCTD using the anti-CD80 MetaSPR biosensor; i represents the correlation fitting curve between the CD80 signal value measured by the MetaSPR platform and the proportion of CD80-positive cells detected by flow cytometry (R = 0.9749). 2 =0.8975); j represents the dynamic monitoring of CD206 markers in macrophages treated with different concentrations of NCTD using an anti-CD206 MetaSPR biosensor; k represents the signal response value of CD206 markers in macrophages treated with different concentrations of NCTD using an anti-CD206 MetaSPR biosensor; l represents the dynamic monitoring of CD163 markers in macrophages treated with different concentrations of NCTD using an anti-CD163 MetaSPR biosensor; m represents the signal response value of CD163 markers in macrophages treated with different concentrations of NCTD using an anti-CD163 MetaSPR biosensor; data are expressed as mean ± standard deviation, n = 3 independent samples; Figure 7 : A high-throughput fully automated probiotic strain screening scheme based on MetaSPR technology, where a is a schematic diagram of the overall MetaSPR detection platform used for probiotic screening. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below. Obviously, the described embodiments are only a part of the embodiments of this invention, and not all of them. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0024] The following is a detailed explanation using specific embodiments: The materials used in the examples were sourced from: mouse CD86 protein (catalog number HY-P7638), CD206 protein (catalog number HY-P702528), CD163 protein (catalog number HY-P700669), CD86 antibody (catalog number HY-P86649), CD80 antibody (catalog number HY-P990127), IL-4 protein (catalog number HY-P70644), IL-13 protein (catalog number HY-P70460), and IFN-γ. Protein (catalog number HY-P7071), dexamethasone (catalog number HY-14648), and trametinib (catalog number HY-10999) were all purchased from MedchemExpress; mouse CD80 protein (catalog number 50446-M08H) was purchased from SinoBiological; CD206 antibody (catalog number 18704-1-AP) and CD163 antibody (catalog number 83285-4-RR) were purchased from Proteintech; APC anti-mouse... CD80 antibody (catalog number 104713) and FITC anti-mouse CD86 antibody (catalog number 159219) were purchased from BioLegend; Nocontalidin (catalog number BD6420) was purchased from bidepharm; LPS (catalog number L2880) was purchased from Sigma-Aldrich; ovalbumin (catalog number S7951) was purchased from Sigma-Aldrich; aluminum hydroxide adjuvant (catalog number A850335) was purchased from Macklin; mouse IgE ELISA kit (catalog number SEA545Mu) was purchased from Cloud-Clone Corp; mouse IL-5 ELISA kit (catalog number EK205HS) was purchased from MultiSciences; histamine ELISA kit (catalog number E-EL-0032) was purchased from Elabscience.

[0025] Example 1: Fabrication of MetaSPR Biosensor First, a cone-shaped nanocup array structure was fabricated on a silicon substrate using laser interferometry combined with ion etching. Then, a UV-curable adhesive was coated onto the patterned mold surface, and a PET film was applied. (The last sentence appears to be incomplete and possibly refers to a specific process involving 105 mW / cm².) 2 After the adhesive is cured by intense ultraviolet irradiation, the PET film with the formed nanocup structure is removed. Next, a 9 nm thick titanium layer and a 90 nm thick gold layer are deposited sequentially to form the MetaSPR chip. After metal layer deposition, the chip is cut to standard detection plate size and securely fixed onto a conventional 96-well plate to obtain the MetaSPR biochip.

[0026] The MetaSPR chip was washed with 50% ethanol, followed by washing with deionized water and drying with nitrogen. Next, 2 μL of protein A solution (MES buffer, pH 5.0) was added to the center of each well and incubated overnight at 4°C. Then, 50 μL of PBS solution containing 0.5% casein was added to each well and incubated at 37°C for 20 minutes to block all residual active sites. Subsequently, CD80, CD86, CD206, or CD163 antibodies were diluted to a concentration of 20 μg / mL in PBST (PBS + 0.05 wt% Tween-20) buffer. 2 μL of the antibody solution was added to the center of each well and incubated overnight at 4°C. Finally, the chip was sealed with a membrane and stored at 4°C until analysis, yielding the MetaSPR biosensor.

[0027] Experimental Example 1: Characteristic Analysis of MetaSPR Biosensors To evaluate the sensitivity of the unmodified antibody-based MetaSPR chip, the absorption spectra of sucrose solutions at different concentrations were measured using a 96-well MetaSPR plate covering a refractive index (RI) range of 1.3330 to 1.3594. This 96-well MetaSPR plate was fabricated by integrating the MetaSPR chip with a standard microplate. Figure 1 (a) As sucrose concentration and refractive index increase, the wavelength of the corresponding absorption peak gradually redshifts ( Figure 1 (b) Meanwhile, the optical density (OD) at 585 nm 585 The optical density (OD) at 605 nm decreased, while the optical density at 605 nm decreased. 605 ) rise ( Figure 1 (c) A difference spectrum can be obtained by subtracting the absorption spectrum of the aqueous solution from the absorption spectrum of the sucrose solution. For example... Figure 1 As shown in d and 1e, the difference in optical density (OD) between 605 nm and 585 nm in the refractive index range of 1.3330 to 1.3594. 605 –OD 585 R is strongly linearly correlated with refractive index. 2 The value reached 0.9995. These results indicate that the MetaSPR chip possesses excellent detection sensitivity.

[0028] Experimental Example 2: Optimization of Antibody Immobilization Method Preparation of the control group: The MetaSPR chip was washed with 75% ethanol, followed by washing with deionized water and drying with nitrogen. Then, 50 μL of mercapto-polyethylene glycol carboxyl solution (HS-EG-COOH solution) was added to each well, and the reaction was carried out at 4°C for 14 hours. After the reaction, each well was thoroughly washed with ultrapure water. To activate surface activity, EDC solution (76.68 mg / mL, MES buffer, pH 5.0) and NHS solution (11.5 mg / mL, MES buffer, pH 5.0) were added. After activation, the chip was carefully washed and dried. Subsequently, CD80, CD86, CD206, or CD163 antibodies were diluted to 20 μg / mL in MES buffer (pH 5.0), and 2 μL of the antibody solution was added to the center of each well, and the mixture was incubated overnight at 4°C to allow covalent binding to the surface. Next, 50 μL of PBS solution containing 0.5 wt% casein was added to each well, and the mixture was incubated at 37°C for 20 minutes to block the remaining active sites. Finally, the chip was covered with a sealing membrane and stored at 4°C for later testing.

[0029] The efficiency of antibody immobilization on the MetaSPR chip directly determines the intensity and stability of the detection signal.

[0030] To differentiate different polarization states of macrophages, four membrane proteins were selected as detection targets. CD80 and CD86 were chosen as surface markers for M1 macrophages: these two proteins can bind to CD28 or cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) receptors on the surface of T cells, providing co-stimulatory signals to promote T cell activation and proliferation. For M2 macrophages, CD206 and CD163 were selected. CD206 is a mannose receptor with multiple glycan-binding domains, mediating glycan-ligand-mediated endocytosis; while CD163 is a macrophage scavenger receptor, playing a key role in clearing the haptoglobin-hemoglobin (HpHb) complex and regulating inflammatory responses. Therefore, anti-CD80, anti-CD86, anti-CD206, and anti-CD163 antibodies were immobilized on a MetaSPR chip to construct a biosensor for identifying macrophage phenotypes (MetaSPR biosensor).

[0031] like Figure 1As shown in g–n, compared to the control group, the protein A-modified chip exhibited a stronger immobilization signal for all four antibodies. This improvement is likely attributed to the unique Fc-specific interaction between protein A and IgG, which results in a more ordered and uniform antibody layer on the chip surface, thereby increasing the effective surface density and enhancing the MetaSPR response. In contrast, the covalent carboxyl coupling used in the control group relied on the reaction between amino groups distributed on the antibody surface, which may lead to randomization of antibody orientation and potentially steric hindrance to the antigen-binding region. Therefore, all four MetaSPR biosensors were prepared using a protein A-mediated immobilization method.

[0032] Experiment Example 3: Affinity analysis of macrophage-related CD markers using MetaSPRMP (MetaSPR macrophage polarization platform is defined as MetaSPRMP). Affinity reflects the strength of the intermolecular interaction in a reversible binding reaction. To evaluate the detection capability of the MetaSPR biosensor, its binding affinity to commercially available recombinant mouse CD protein was first characterized. Recombinant mouse CD80 was diluted with HBS-ET buffer to 0, 0.15625, 0.3125, 0.625, 1.25, and 2.5 μg / mL; CD86, CD206, and CD163 were diluted using the same dilution gradient as CD80, and then added to the corresponding antibody-functionalized wells of the MetaSPRMP platform for assay. Figure 2 (a) in the middle.

[0033] Signal changes on the MetaSPRMP platform were recorded in real time to continuously monitor the binding kinetics between each antibody and its target protein. Binding and dissociation processes were monitored for 10 and 20 minutes, respectively. Figure 2 As shown in the figure, with the increase of target protein concentration, all four biosensors exhibited a rapidly rising MetaSPRMP platform signal during the binding phase; the signal attenuation was minimal during the dissociation phase, indicating that they have rapid binding and highly stable binding characteristics.

[0034] Kinetic parameters were obtained by fitting real-time binding curves using a Langmuir model with a 1:1 binding stoichiometry. The equilibrium dissociation constant (KD) was determined individually for each antibody-protein combination. Specifically, the KD values ​​for CD86, CD80, CD206, and CD163 were 129 pM, 96.3 pM, 73.5 pM, and 266 pM, respectively, indicating a strong and stable interaction between the antibody and antigen. The equilibrium MetaSPR response values ​​were extracted from the real-time binding curves and used for quantitative analysis. Figure 2As shown in fi, at the end of the binding phase, the endpoint RU value increases with increasing protein concentration, and the results for each antibody-protein combination are consistent and reproducible. Based on these equilibrium response data, a standard curve was plotted within the test concentration range using a four-parameter logistic regression (4PL) model. Figure 2 jm in (R). Goodness of fit (R) 2 The values ​​were: CD86 0.9952, CD80 0.9950, CD206 0.9943, and CD163 0.9923, indicating a robust and predictable relationship between the MetaSPRMP biosensor response value and the analyte concentration.

[0035] In summary, these affinity analysis results confirm the analytical performance of the MetaSPRMP platform at the protein level and provide a foundation for subsequent assessment of macrophage polarization using live cells.

[0036] Experimental Example 4: LPS and IFN-γ-induced M1 polarization of RAW264.7 macrophages RAW264.7 macrophages were treated with lipopolysaccharide (LPS) and interferon-γ (IFN-γ) under a series of experimental conditions to induce M1 polarization. Cells cultured alone in medium served as the M0 control group (G1 group received complete medium with LPS and IFN-γ concentrations of 0), while groups G2 through G6 received increasing concentrations of LPS (25–200 ng / mL) and IFN-γ (5–40 ng / mL), respectively. Figure 3 As shown in 'a'.

[0037] G2: 25 ng / mL LPS+ 5 ng / mL IFN-γ; G3: 50 ng / mL LPS+ 10 ng / mL IFN-γ; G4: 100 ng / mL LPS+ 20 ng / mL IFN-γ; G5: 150 ng / mL LPS+ 30 ng / mL IFN-γ; G6: 200 ng / mL LPS + 40 ng / mL IFN-γ.

[0038] like Figure 3As shown in b, prior to polarization induction, RAW264.7 cells predominantly exhibited a round morphology, characteristic of the resting M0 phenotype. After 24 hours of incubation in fresh medium (G1 group), all cells maintained this round morphology, indicating that the M0 state was maintained. In contrast, cells treated with LPS and IFN-γ showed significant morphological changes associated with M1 polarization, including irregular cell shape and the formation of multiple short, branched filopodia. Among the treatment groups, only a few cells in the G2 group (25 ng / mL LPS + 5 ng / mL IFN-γ) exhibited M1-like morphology, while the proportion of polarized cells was significantly higher in the G3 to G6 groups. However, no significant differences were found between the G3 and G6 groups based solely on morphological observation, highlighting the need for more sensitive assessment methods.

[0039] Experiment Example 5: Cell Number Optimization Based on MetaSPRMP Platform Detection Method In this experiment, groups G1-G6 are consistent with those in Experiment 4.

[0040] To determine the appropriate cell number required for the MetaSPRMP platform assay, G1 phase (primarily M0 phase) and G3 phase (induced by M1 phase) cells were selected as representative populations. After treatment, cells were suspended in culture medium at densities of 9000, 45000, 90000, 135000, and 180000 cells per milliliter, respectively. 50 μL of the sample was loaded per well for the G1 and G3 phase cells to be detected by the anti-CD86 MetaSPRMP biosensor, and real-time binding reaction data were recorded for up to 900 seconds. Figure 3 (c in the text)

[0041] Insufficient cell number leads to limited antibody-antigen binding between cell surface markers and surface-fixed antibodies, resulting in a weak MetaSPR signal; conversely, excessive cell density can restrict the effective utilization of available binding sites, thus hindering further signal enhancement. To assess the signal differences associated with M1 polarization, the response values ​​of the endpoint MetaSPRMP platform in the G1 group were subtracted from those in the G3 group (ΔRU = RUG3). RUG1). The ΔRU value remained positive across all cell counts tested, indicating that the CD86-related binding strength in M1-polarized macrophages was higher than that in predominantly M0-type macrophages. This is consistent with the characteristic of CD86 as a representative marker of M1. Figure 3 d in Figure 3 (e in the text).

[0042] Notably, the ΔRU value significantly increased at 2250 cells per well and peaked at 4500 cells per well, a value significantly higher than that at 2250 cells. Conversely, when the cell count was further increased to 6750 or 9000 cells per well, the ΔRU value decreased, indicating that excessive cell load adversely affects effective signal contrast. Therefore, 4500 cells per well was ultimately determined to be the optimal cell density for subsequent measurements on the MetaSPRMP platform.

[0043] Experimental Example 6: MetaSPRMP Plateau Analysis of M1 Polarization State under Different Induction Conditions In this experiment, groups G1-G6 are consistent with those in Experiment 4.

[0044] Using optimized cell numbers, macrophages in the G1–G6 groups were analyzed using the MetaSPRMP platform, which is functionalized with anti-CD86 and anti-CD80, respectively, to evaluate the expression of M1-related surface markers under different induction conditions.

[0045] In CD86 detection, all groups treated with LPS / IFN-γ showed significantly higher CD86-related signal intensities than the G1 group, which was predominantly M0 type, consistent with morphological observations. Figure 3 The G6 group (200 ng / mL LPS + 40 ng / mL IFN-γ) showed the second lowest response level among the induction groups, significantly lower than the G3, G4, and G5 groups, indicating that overstimulation did not further enhance CD86 expression, but rather weakened the effective M1-related signal. The CD86 response in the G2 group was at an intermediate level, significantly lower than the G3 group but comparable to the G4 and G5 groups.

[0046] A similar response pattern was observed in CD80 detection: group G3 again showed the strongest MetaSPR signal, while group G1 showed the lowest response intensity; group G6 remained the second lowest, with CD80 signal intensity comparable to group G1, but significantly lower than groups G3-G5. In contrast, group G2 showed a moderate enhancement in CD80-related response compared to groups G1 and G6, but still significantly lower than groups G3-G5. Figure 3 hi in the middle.

[0047] Overall, the CD86 and CD80 detection results consistently categorized the tested conditions into different response groups: groups G3-G5 showed strong M1-related signals; group G2 showed moderate M1 polarization; group G6, despite strong stimulation, exhibited a low M1-related response; and group G1 served as a negative control. This clear stratification provided a solid foundation for subsequent cluster analysis.

[0048] Experimental Example 7: Characterization of the inhibitory effect of MetaSPRMP on M1 polarization Based on the above analysis, group G3 (50 ng / mL LPS + 10 ng / mL IFN-γ) exhibited the strongest and most consistent M1-related MetaSPR response, and was therefore selected as the representative M1 induction condition for further characterization of the MetaSPRMP platform. To further evaluate the ability of the MetaSPRMP platform to distinguish macrophage M1 polarization status under regulated conditions, an M1 polarization inhibition model was constructed using dexamethasone (DEX). Figure 3 (j) As a classic glucocorticoid, DEX has been shown to inhibit nuclear factor κB (NF-κB)-related pro-inflammatory activity and reduce the expression of M1-related markers.

[0049] like Figure 3 As shown in k and 3l, compared with the G3 group, the MetaSPR signals associated with CD80 and CD86 were significantly reduced in macrophages treated with DEX. These results demonstrate that the MetaSPRMP platform can effectively distinguish M1 polarization states under both induction and pharmacological inhibition conditions, exhibiting good sensitivity and discriminative ability.

[0050] Experimental Example 8: Characterization Analysis of M2 Polarization Induction and Inhibition on the MetaSPRMP Platform Building upon the successful detection of M1 macrophage polarization using the MetaSPRMP platform, this study further investigated the platform's ability to characterize and inhibit M2 polarization. RAW264.7 macrophages were co-incubated with different concentrations of IL-4 and IL-13 to induce M2 polarization. Six groups were established: a control group (T1) and five stimulation groups treated with increasing concentrations of IL-4 and IL-13 (5 / 5, 10 / 10, 20 / 20, 30 / 30, and 40 / 40 ng / mL), designated T2 to T6. Figure 4 (a) in the middle.

[0051] Similar to the M1 polarization study, morphological observation was first performed using an optical microscope. Figure 4 (b) Before induction, macrophages in all groups exhibited a typical round morphology, consistent with the M0 phenotype; while the M2 group tended to show a slender spindle-shaped morphology. After 48 hours of induction with culture medium or interleukin, cells in the T1 group remained round, indicating that they maintained the M0 state; cells in the T2 and T3 groups mainly retained a round morphology, with only a few cells showing a slender spindle-shaped structure, suggesting limited M2 polarization; while more significant morphological changes were observed in the T4 to T6 groups: a larger proportion of cells exhibited the typical spindle-shaped morphology associated with M2 macrophages.

[0052] After completing morphological observation, the expression of M2 macrophage-related markers under different induction conditions was evaluated using the MetaSPRMP platform, which was functionalized with anti-CD206 and anti-CD163 antibodies. Figure 4 (cf). In CD206 detection, group T6 showed the strongest MetaSPR signal intensity, significantly higher than all other groups; groups T4 and T5 were next, with signal intensities significantly higher than groups T1 and T2; group T3 showed a moderate enhancement compared to group T2, and was also significantly higher than the control group T1, indicating that within the tested cytokine concentration range, CD206-related signal intensity increased in a dose-dependent manner. CD163 detection results showed a similar trend: group T6 again produced the strongest MetaSPR signal, significantly better than groups T5 and T4; furthermore, the CD163 signal intensities of groups T4 to T6 were significantly higher than those of groups T1 to T3, clearly demonstrating the significant difference between strong and weak induction conditions.

[0053] In summary, the combined MetaSPRMP platform response results of CD206 and CD163 indicate that different M2 polarization levels exist under different induction conditions: group T6 corresponds to a high M2 polarization state, while groups T4 and T5 show a moderate degree of M2 polarization; in contrast, groups T2 and T3 show relatively low M2-related responses, while group T1 remains a non-polarized M0 control group.

[0054] Based on the MetaSPRMP platform response results for CD206 and CD163, the T6 condition (40 ng / mL IL-4 + 40 ng / mL IL-13) – which produced the strongest M2-related signal – was selected for subsequent inhibition analysis. To investigate whether the MetaSPRMP platform could detect regulatory changes in M2 polarization, trametinib was added to the experiment to inhibit the induction process. Trametinib is a selective MEK inhibitor, and previous studies have reported that it can inhibit M2 macrophage polarization through multiple signaling pathways. Therefore, in the presence of 10 nM trametinib, macrophages were treated with 40 ng / mL IL-4 + 40 ng / mL IL-13 to construct an M2 polarization inhibition model. Figure 4 (g in the example). Figure 4 h in Figure 4 As shown in i, macrophages treated with IL-4 and IL-13 alone (T6 group) exhibited strong CD206 and CD163 MetaSPR responses; in contrast, the addition of trametinib significantly reduced both CD206 and CD163 signals compared to the T6 group. This weakened MetaSPR response further demonstrates that the MetaSPRMP platform can sensitively monitor changes in macrophage M2 polarization under pharmacological regulation.

[0055] In summary, the MetaSPRMP platform successfully achieved precise characterization of M2 macrophage polarization induced by different concentrations of IL-4 and IL-13. Within the tested range, the MetaSPR signal intensity of CD206 and CD163 increased with increasing cytokine concentration, clearly distinguishing low, medium, and high M2 polarization levels. Furthermore, compared to the T6 group, macrophages treated with trametinib showed significantly reduced MetaSPR signals of CD206 and CD163, reflecting a decrease in M2 polarization levels under inhibitory conditions, and demonstrating the MetaSPRMP platform's ability to detect such regulatory changes. These results confirm that the MetaSPRMP platform can effectively characterize M2 polarization and detect its dynamic changes under different experimental conditions.

[0056] Experiment Example 9: Cross-detection of macrophage polarization using the MetaSPRMP platform To further evaluate the ability of the MetaSPRMP platform to distinguish between the M1 and M2 polarization states, a cross-detection experiment was conducted. Figure 5 (a) Macrophages in the M1-induced group (G1–G6) were detected using CD206 and CD163 MetaSPR biosensors, while CD80 and CD86 sensors were used in the M2-induced group (T1–T6). Figure 6 b– Figure 6 As shown in e, the intensity of CD206 and CD163 MetaSPR signals produced by M1-induced macrophages (G2–G6) was extremely low, lower than that of the control group (G1); similarly, the intensity of CD80 and CD86 signals produced by M2-induced macrophages (T2–T6) was comparable to or lower than that of the T1 control group. Figure 5 f– Figure 5 (i in the text).

[0057] These results demonstrate that the MetaSPRMP platform can specifically detect macrophage polarization status, with extremely low cross-reactivity between the M1 and M2 markers. The consistently low signal intensity in the cross-detection experiments further highlights the platform's specificity and reliability in analyzing macrophage polarization characteristics.

[0058] Experiment Example 10: Cluster Analysis of Macrophage Polarization State Based on MetaSPRMP Platform To systematically classify macrophage polarization levels and provide a framework for assessing unknown samples, two-dimensional scatter plots were constructed using response data from the MetaSPRMP platform. For M1 polarization types, CD80 and CD86 signals were plotted on the x and y axes, respectively. Data sources included the M0 control group (G1 / T1), LPS / IFN-γ treatment groups (G2–G6), and IL-4 / IL-13 treatment groups (T2–T6). By combining the distribution of these data points with previously observed statistically significant differences in RU values, four polarization categories were defined: high polarization, intermediate polarization, low polarization, and negative polarization. Figure 5 (j) High M1 polarization includes samples treated with 50 ng / mL LPS + 10 ng / mL IFN-γ, 100 ng / mL LPS + 20 ng / mL IFN-γ, and 150 ng / mL LPS + 30 ng / mL IFN-γ; moderate M1 polarization corresponds to 25 ng / mL LPS + 5 ng / mL IFN-γ; low M1 polarization includes samples treated with 200 ng / mL LPS + 40 ng / mL IFN-γ; the negative category includes the M0 control group and all IL-4 / IL-13 treated samples. Corresponding heatmaps are generated to visualize the CD80 and CD86 signal intensities of each sample, visually presenting the biomarker expression levels under different experimental conditions. Figure 5 k in the middle.

[0059] M2 polarization was analyzed using a similar method, with CD206 and CD163 signals used as the x and y axes, respectively. The classification was based on the distribution of samples in the graph and the statistically significant differences in previously observed RU values. Figure 5 Cells treated with 40 ng / mL IL-4 + 40 ng / mL IL-13 showed high M2 polarization; moderate M2 polarization corresponded to cells treated with 30 ng / mL IL-4 + 30 ng / mL IL-13; low M2 polarization included cells treated with 20 ng / mL IL-4 + 20 ng / mL IL-13, and some cells treated with 10 ng / mL IL-4 + 10 ng / mL IL-13; the negative category encompassed M0 cells, the remaining cell subpopulation treated with 10 ng / mL IL-4 + 10 ng / mL IL-13, and all LPS / IFN-γ treated samples. Heatmaps of CD206 and CD163 signals were also generated to support visual comparisons of M2 marker intensities across all samples. Figure 5 (m in the middle).

[0060] This clustering strategy demonstrates that the MetaSPRMP platform can effectively classify macrophages into M0, M1, and M2 states, and further distinguish their polarization levels (high, medium, or low). By clearly presenting biomarker expression and integrating significance indicators based on RU values, this method establishes an analytical framework for rapidly evaluating unknown samples, simultaneously inferring their polarization state and approximate correspondence with standard induction concentrations.

[0061] Experimental Example 11: Verifying the MetaSPRMP Platform Using NCTD-Induced M1 Polarization To further validate the applicability of the MetaSPRMP platform for assessing unknown samples, researchers treated RAW264.7 macrophages with norcantharidin (NCTD) at different concentrations of 0, 5, 10, and 20 μM—a concentration previously reported to induce M1 polarization in a concentration-dependent manner. Flow cytometry (a standard method for assessing macrophage polarization) was used to detect the induction of M1 polarization using APC anti-mouse CD80 antibody and FITC anti-mouse CD86 antibody.

[0062] like Figure 6 a in Figure 6 As shown in b, in the M0 control group cells, the CD80-CD86- population accounted for 73.8±2.21%, while the CD80+CD86+ population accounted for only 4.17±0.66%. With increasing NCTD concentration, the proportion of the CD80-CD86- population gradually decreased (64±5.79% at 5 μM; 32.83±0.96% at 10 μM; and 27.6±1.99% at 20 μM), while the CD80+CD86+ population correspondingly increased (reaching 9.87±1.31% at 5 μM, 20.57±1.46% at 10 μM, and 30.13±2.76% at 20 μM). Based on the overall distribution of CD80 and CD86 expression and the observed population concentration-dependent changes, four polarization levels can be defined: negative (M0 state, culture medium treatment control), low polarization (5 μM NCTD), moderate polarization (10 μM NCTD), and high polarization (20 μM NCTD). These levels reflect the gradual increase in M1 polarization.

[0063] Subsequently, the same unlabeled cell population was directly applied to the MetaSPRMP platform to simultaneously detect CD80, CD86, CD206, and CD163 signals. Figure 6(c) The results showed that the response value of the MetaSPRMP platform to CD86 was 1.38 ± 0.29 in the M0 group; 6.67 ± 0.98 in the 5 μM NCTD treatment group; 15.29 ± 0.74 in the 10 μM NCTD treatment group; and 17.71 ± 1.42 in the 20 μM NCTD treatment group. Figure 6 Similarly, at the corresponding concentrations, the CD80 response in group M0 increased from 2.15±0.27 to 2.93±0.19, 10 μM NCTD increased to 4.01±0.29, and 20 μM NCTD increased to 8.19±1.10 (de in the text). Figure 6 (gh). The RU value of the signal from the MetaSPRMP platform was compared with the total CD80 measured by flow cytometry. + or CD86 + Comparative analysis of cell population numbers (including double-positive and single-positive cells) revealed a strong linear correlation between the two: CD86 R 2 The value is 0.9750, CD80's R 2 The value is 0.9023 ( Figure 6 f in Figure 6 (i in the text).

[0064] In contrast, the responses of CD206 and CD163 remained consistently low across all NCTD concentrations. Specifically, the RU values ​​for CD206 were as follows: M0 phase: 4.06 ± 0.83; 5 μM: 3.84 ± 0.69; 10 μM: 3.59 ± 0.74; 20 μM: 1.71 ± 0.44 (… Figure 6 The RU values ​​for CD163 were also: M0: 4.65 ± 0.79; 5 μM: 3.88 ± 0.28; 10 μM: 4.42 ± 0.26; 20 μM: 4.00 ± 0.37 (jk); CD163 RU values ​​... Figure 6 These results further confirm the absence of M2 polarization in the NCTD-treated samples, indicating that the treatment selectively promotes M1 polarization without inducing significant M2 marker expression.

[0065] Notably, when the integrated CD80 / CD86 / CD206 / CD163 MetaSPRMP platform data was mapped to the pre-established M1 / M2 classification MetaSPRMP platform, the polarization status of all NCTD-treated samples was completely consistent with the flow cytometry results: M0 cells were classified as negative; cells treated with 5, 10, and 20 μM NCTD corresponded to low, medium, and high M1 categories, respectively; and all NCTD-treated samples were classified as M2 negative, which further validates the specificity of the MetaSPRMP platform in distinguishing between M1 and M2 states.

[0066] These findings demonstrate that the MetaSPRMP platform can accurately and rapidly determine the polarization state and level of macrophages in unknown samples in a single 15-minute assay. By integrating multiple surface biomarkers and employing a well-established polarization classification framework, this platform provides a reliable tool for high-throughput drug screening, assessing macrophage responses to different compounds and directly inferring corresponding standard induction levels and polarization states.

[0067] Experiment Example 12: High-throughput screening of probiotics using the MetaSPRMP platform to regulate M1 polarization Based on the comprehensive validation of the MetaSPRMP platform described above, it has been confirmed that the platform can detect the expression of macrophage surface markers in a high-throughput, rapid, and sensitive manner. Building on this, further research using the MetaSPRMP platform will be conducted to evaluate whether probiotics play a role in the early inflammatory stage of allergic rhinitis (AR) by regulating M1 macrophage polarization.

[0068] Allergic rhinitis (AR) is one of the most common chronic diseases worldwide. Macrophage polarization plays a crucial role in the pathogenesis of AR, with the M1 and M2 phenotypes exerting different functional roles at different stages of inflammation. M1 macrophages are abundant in the early inflammatory stage of AR and participate in the inflammatory response; during AR, inflammatory factors such as IL-23, IL-12, and IFN-α can induce macrophage differentiation into the M1 phenotype. The M1 phenotype has a pro-inflammatory effect and further exacerbates the inflammatory response, potentially leading to tissue damage; conversely, the M2 phenotype is mainly active in the late stage of AR, possessing both anti-inflammatory effects and the potential to exacerbate AR.

[0069] Given the central role of M1 macrophages in the early inflammatory response, targeting and modulating their polarization state may be an effective strategy for controlling the initial inflammatory response in allergic rhinitis (AR). Probiotics have been considered a potential therapeutic approach for alleviating allergy symptoms and modulating immune and inflammatory responses in allergic diseases, including AR. However, their mechanisms of action are not fully elucidated, particularly regarding their impact on macrophage polarization. Therefore, a systematic and efficient method is urgently needed to screen probiotics capable of modulating macrophage polarization. Based on this, the MetaSPRMP platform was used for high-throughput screening of candidate probiotics to assess their potential for inhibiting M1 polarization. The top four selected probiotics were further validated in vivo in an AR model. This method also allowed for a deeper exploration of the underlying mechanisms behind the anti-inflammatory effects of probiotics.

[0070] As shown in Table 1, a total of 44 probiotic strains were included in the screening candidate list. These strains mainly belong to the lactic acid bacteria genus, including Lactobacillus (Lactobacillus). L. rhamnosus, L. plantarum, L. fermentum, L. sakei, L. pentosus, L. curvatus and L. brevis Bifidobacterium spp. B. longum and B. breve ) and other lactic acid bacteria, such as Lactobacillus, Lactobacillus mesenteriae, and Enterococcus faecalis. The M1 cell induction protocol was established based on the above standard method, using 50 ng / mL LPS + 10 ng / mL IFN-γ. After co-culturing the diluted probiotic preparations of 44 probiotics with LPS and IFN-γ for 24 hours, cells were collected, and the expression levels of CD80, CD86, CD206, and CD163 were detected using the MetaSPRMP platform. Figure 7 (a) in the middle.

[0071] Table 1: List of 44 candidate probiotic strains for screening A total of 44 probiotic strains were used, along with an M1 control group, an M0 control group, and a blank control per well, forming 46 experimental groups. These groups were assigned to two 96-well MetaSPRMP plates for automated analysis. The entire automated process took only 30 minutes, enabling rapid and high-throughput preliminary assessment of the effect of each probiotic on M1 polarization inhibition. Each experimental group had three replicates, and the results were presented as a heatmap. Significant heterogeneity was observed among the different probiotic strains, with significant differences in their ability to regulate M1 polarization, providing a basis for subsequent candidate strain screening. The MetaSPRMP platform detection results of CD86, CD80, CD206, and CD163 induced by the 44 probiotics were further analyzed and sorted in descending order. The CD86 RU values ​​induced by each probiotic were distributed between the M1 and M0 control groups: the top five were as follows: E. faecalis116, L. plantarum 31, L. plantarum 445, L. brevis 121 and L. brevis 132; the last five are as follows: L. plantarum 2, L. fermentum 1, LGG, L. plantarum 1 and BL21. CD80 also shows a similar trend: the top five are respectively E. faecalis 116, L. plantarum 820, L. plantarum 445, L. plantarum 31 and L. lactis 48; the last five are L. plantarum 2, L. plantarum 1, L. fermentum 1, LGG and LRa05. CD206 and CD163 in all strains showed similar RU levels to M0 and M1.

[0072] In addition, the RU values ​​of each group of CD86 and CD80 are mapped to... Figure 5 The diagram shown in Figure j illustrates clustering. The results show: L. plantarum 31, L. plantarum 445, L. plantarum 820, L. plantarum 1365, L. curvatus 990, L. curvatus 996, L. mesenteroides 291, E. faecalis 116, L. lactis 48 , L. lactis 89 and L. brevis All 121 strains were classified as having high M1 levels, indicating that the metabiotics derived from these strains only showed limited inhibitory effects on M1 polarization; L. plantarum 6, L. plantarum 90, L. plantarum 428, L. curvatus 1437, L. curvatus 1505, L. curvatus 1535, L. sakei 780, L. sakei 1 389, L.sakei 1391, L. mesenteroides 726, L. mesenteroides 1111, L. pentosus 1388, E. faecalis 186, E. faecalis 446, E. faecalis 447, L. lactis 91, L. lactis 832, L. lactis 847, L. lactis 921, L. lactis 933, L. lactis 959 and L. brevis 308 corresponds to the M1 level, suggesting it has a moderate inhibitory effect on M1 polarization; BBr60, LRa05, L. plantarum 290, L. plantarum 292, and L. brevis 66 exhibits a low M1 level, indicating a stronger inhibitory effect on M1 polarization; it is worth noting that M0, BL21, LGG, L. plantarum 1, L. plantarum 2 and L. fermentum All 1 values ​​were classified as "negative" M1, indicating a strong inhibitory effect on M1 polarization. Further mapping of the RU values ​​of CD206 and CD163 to... Figure 6 In the schematic clustering of l, all 46 groups were located in the "negative" region, which corresponds to the M0 cell and different M1 cell level intervals defined by MetaSPRMP. Ultimately, LGG, L. plantarum 1, L. plantarum 2, and L. fermentum 1 was identified as one of the four strains with the strongest inhibitory effect on M1 polarization.

[0073] Overall, by using the MetaSPRMP platform to perform fully automated screening of 44 probiotic strains within 30 minutes, LGG can be quickly identified. L. plantarum 1 , L. plantarum 2 and L. fermentum 1. These four strains exhibited the strongest inhibitory effect on M1 polarization. Therefore, they were selected for further in vivo evaluation.

[0074] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the technical solutions of the embodiments of the present invention.

Claims

1. A method for detecting macrophage polarization based on metasurface plasmon resonance, characterized in that, Includes the following steps: S1. Fabrication of MetaSPR biosensors; S2. Add the macrophages to be tested onto the MetaSPR biosensor to bring the macrophages into contact with the antibody; S3. Real-time detection of resonance signals generated by the binding of antibodies to macrophage surface markers using metasurface plasmon resonance technology; S4. Determine the polarization state of macrophages based on resonance signals.

2. The macrophage polarization detection method based on metasurface plasmon resonance according to claim 1, characterized in that, S1 specifically includes: S101, Prepare a 96-well MetaSPR plate; S102. Immobilize antibodies on the surface of a 96-well MetaSPR plate.

3. The macrophage polarization detection method based on metasurface plasmon resonance according to claim 2, characterized in that, The antibodies are: anti-CD80 antibody, anti-CD86 antibody, anti-CD206 antibody, and anti-CD163 antibody.

4. The macrophage polarization detection method based on metasurface plasmon resonance according to claim 1, characterized in that, The macrophage surface markers include: M1 macrophage markers and / or M2 macrophage markers; Among them, the M1 macrophage markers are selected from any one or more of CD80 or CD86; M2 macrophage markers are selected from any one or more of CD206 or CD163.

5. The macrophage polarization detection method based on metasurface plasmon resonance according to claim 1, characterized in that, The macrophages to be tested are in the state of a live cell suspension, and the sample volume of the macrophages to be tested is 80,000 to 100,000 live cells / mL.

6. A MetaSPR biosensor applied to the macrophage polarization detection method based on metasurface plasmon resonance as described in any one of claims 1 to 5, characterized in that, The MetaSPR biosensor includes: The substrate layer is a PET film with a periodic nanocup array structure; A metal layer is deposited on the surface of the nanocup array structure; Protein A layer, wherein the protein A layer is adsorbed onto the surface of the metal layer; An antibody layer, wherein the antibody layer is directionally immobilized on a protein A layer by the specific binding of protein A to the Fc region of the antibody, wherein the antibody is selected from one or more of anti-CD80 antibody, anti-CD86 antibody, anti-CD206 antibody and anti-CD163 antibody; The amino acid sequence of the protein A layer is shown in SEQ ID NO.

1.

7. The MetaSPR biosensor according to claim 6, characterized in that, The metal layer comprises a gold layer and a titanium layer, wherein the titanium layer is in direct contact with the substrate layer; the thickness of the gold layer is 80nm~100nm, and the thickness of the titanium layer is 5nm~10nm.

8. A macrophage polarization assessment device, characterized in that, This includes the MetaSPR biosensor as described in any one of claims 6 to 7, and a detection instrument for detecting metasurface plasmon resonance signals.

9. The application of a macrophage polarization detection method based on metasurface plasmon resonance as described in any one of claims 1 to 5, or the MetaSPR biosensor as described in any one of claims 6 to 7, or the macrophage polarization assessment device as described in claim 8, in drug screening, immunomodulator evaluation, or probiotic screening.

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