Quantum resonance fluorescence immunoassay medical detection method

Abstract

The invention relates to the technical field of fluorescence immunoassay, and discloses a quantum resonance fluorescence immunoassay medical detection method, which comprises the following steps: 1, carrying out fixation and permeation treatment on cells, respectively incubating the cells by using labeled different quantum dot-antibody compounds, specifically binding antibodies with corresponding target proteins in the cells, and detecting the target proteins in the cells; a labeled cell sample is obtained; 2, under a confocal microscope, laser with a specific wavelength is adopted to excite the marked cell sample, and fluorescence lifetime image data of different quantum dot emission wavelengths are collected; according to the method, the fluorescence lifetime image data of different quantum dot emission wavelengths are acquired through the confocal microscope, the position and content information of different target proteins can be clearly distinguished, simultaneous analysis and accurate positioning of multiple target proteins are realized, and an efficient means is provided for multi-protein research in a complex biological system.

Description

Technical Field

[0001] The invention relates to the technical field of fluorescent immunoassay, in particular to a quantum resonance fluorescent immunoassay medical detection method. Background Art

[0002] In the field of medical testing, fluorescent immunoassay technology is a commonly used detection method. Traditional fluorescent immunoassay methods are mainly based on labeling antibodies with organic fluorescent dyes, and the content of the target protein is determined by detecting the fluorescence intensity. For example, commonly used fluoresceins (such as FITC, TRITC, etc.) are widely used in immune labeling. During the operation, antibodies labeled with fluorescent dyes are incubated with cells or tissue samples to allow the antibodies to specifically bind to the target protein, and then the fluorescent signal is observed using equipment such as a fluorescence microscope.

[0003] However, traditional fluorescent immunoassay technology has some limitations. On the one hand, the fluorescence spectrum of organic fluorescent dyes is narrow and prone to fluorescence quenching, which makes it difficult to select suitable fluorescent dyes for distinguishing labels when detecting multiple target proteins, and the detection sensitivity is subject to certain limitations. On the other hand, detection based solely on fluorescence intensity is easily interfered by factors such as impurities in the sample, photobleaching, and fluctuations in the intensity of the excitation light, resulting in poor accuracy and stability of the test results.

[0004] The technical solution closest to the proposal of this application is the immunoassay method based on traditional fluorescent labeling. Its implementation process usually includes the following steps: First, select a suitable organic fluorescent dye to label the target protein antibody. The labeling process mainly covalently connects the fluorescent dye to the antibody through a chemical reaction. Then, the cell or tissue sample is processed, such as fixation and permeabilization, so that the antibody can enter the cell and bind to the target protein. After that, use equipment such as a fluorescence microscope or flow cytometer to excite the sample with light of a specific wavelength and detect the fluorescence intensity to analyze the expression of the target protein.

[0005] Therefore, we propose a quantum resonance fluorescence immunoassay medical detection method. Summary of the invention

[0006] The present invention mainly solves the technical problems existing in the above-mentioned prior art and provides a quantum resonance fluorescence immunoassay medical detection method.

[0007] In order to achieve the above-mentioned purpose, the present invention adopts the following technical scheme: quantum resonance fluorescence immunoassay medical detection method, using quantum dots with different emission wavelengths to respectively label different target protein antibodies, using a confocal microscope as the detection device, and operating according to the following steps:

[0008] Step 1: After the cells are fixed and permeabilized, they are incubated with different labeled quantum dot-antibody complexes to allow the antibodies to specifically bind to the corresponding target proteins in the cells, thereby obtaining labeled cell samples;

[0009] Step 2: Under a confocal microscope, use a laser of a specific wavelength to excite the labeled cell sample and collect fluorescence lifetime image data of different quantum dot emission wavelengths;

[0010] Step 3: Based on the fluorescence lifetime image data, the protein concentration-fluorescence lifetime standard curve is obtained through the fluorescence lifetime analysis algorithm, and the protein concentration-fluorescence lifetime standard curve is fitted to obtain the calculation formula for the content of different target proteins in the cell;

[0011] Step 4: For cell samples with unknown protein expression levels, repeat steps 1 and 2 above, and substitute the final fluorescence lifetime data into the content calculation formula obtained in step 3 above to obtain the content and location information of each target protein in the cell.

[0012] Preferably, the cells are fixed using paraformaldehyde solution, the fixation time is 15-30 minutes, and the fixation temperature is 4°C.

[0013] Preferably, the cells are permeabilized using TritonX-100 solution, the permeabilization time is 5-15 minutes, and the concentration of TritonX-100 solution is 0.1%-0.5%.

[0014] Preferably, the particle size of the quantum dots is in the range of 2-10 nm, and the surface of the quantum dots is modified with carboxyl or amino groups to enhance the ability to bind to antibodies.

[0015] Preferably, in the labeled quantum dot-antibody complex, the molar ratio of quantum dots to antibodies is 1:1-1:5.

[0016] Preferably, in the confocal microscope detection in step 2, the wavelength of the laser is 405nm-633nm, and the scanning resolution is 512×512 pixels to 1024×1024 pixels.

[0017] Preferably, the fluorescence lifetime analysis algorithm adopts an exponential decay fitting algorithm or a convolution inversion algorithm.

[0018] Preferably, the standard curve is prepared by reacting a recombinant target protein of known concentration with a quantum dot-antibody complex, measuring its fluorescence lifetime data and drawing a standard curve, and the concentration range of the standard curve is 0.1 ng / mL-10 μg / mL.

[0019] Beneficial Effects

[0020] The present invention provides a quantum resonance fluorescence immunoassay medical detection method. It has the following beneficial effects:

[0021] (1) This quantum resonance fluorescence immunoassay medical detection method uses quantum dots with different emission wavelengths to label different target protein antibodies, and can detect multiple target proteins in the same cell sample. After cell fixation and permeabilization, different quantum dot-antibody complexes specifically bind to the corresponding target proteins. Fluorescence lifetime image data of different quantum dot emission wavelengths are collected through confocal microscopy, which can clearly distinguish the location and content information of different target proteins, realize simultaneous analysis and precise positioning of multiple target proteins, and provide an efficient means for multi-protein research in complex biological systems.

[0022] (2) The quantum resonance fluorescence immunoassay medical detection method, quantum dots have unique optical properties, and their fluorescence intensity is high and stable. Under the conditions of suitable particle size range (2-10nm) and surface modification (carboxyl or amino modification), after binding with antibodies, laser excitation can produce a strong fluorescence signal. As in the embodiment, when the cell sample labeled with quantum dots is excited by 405nm laser, the target protein detection shows high sensitivity, and low-concentration protein can be effectively detected. Compared with traditional immunoassay technology, lower content of target protein can be detected, which improves the lower limit of detection sensitivity.

[0023] (3) This quantum resonance fluorescence immunoassay medical detection method uses an exponential decay fitting algorithm or a convolution inversion algorithm to calculate the target protein content based on the fluorescence lifetime image data. Unlike traditional detection methods that rely only on fluorescence intensity, the fluorescence lifetime is not affected by factors such as the concentration of fluorescent substances, photobleaching, and fluctuations in the intensity of excitation light, and can provide more stable and accurate detection results. For example, in complex biological samples, even if there is background fluorescence interference or changes in sample conditions, the target protein information can still be accurately obtained by analyzing the fluorescence lifetime, thereby improving the accuracy and reliability of the detection.

[0024] (4) In this quantum resonance fluorescence immunoassay medical detection method, the surface of quantum dots is modified with carboxyl or amino groups to enhance the binding ability with antibodies, and the molar ratio of quantum dots to antibodies in the quantum dot-antibody complex (1:1-1:5) is studied and optimized. Appropriate modification and molar ratio can avoid quantum dot aggregation, reduce the risk of nonspecific binding, and ensure the accuracy and stability of detection. For example, carboxyl-modified quantum dots bind to antibodies through electrostatic attraction under physiological pH conditions, and different molar ratios show different characteristics in terms of fluorescence signal intensity, detection sensitivity, binding efficiency, etc., providing flexible optimization options for actual detection.

[0025] (5) This quantum resonance fluorescence immunoassay medical detection method can select different wavelengths of laser (405nm-633nm) and scanning resolution (512×512 pixels to 1024×1024 pixels) according to the characteristics of the sample in the confocal microscope detection. For example, when detecting high-grade gliomas, the 633nm laser is less affected by the blood layer and can effectively meet the needs of special sample detection, thereby improving the applicability and flexibility of the detection method and playing a role in a variety of biomedical detection scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the implementation of the present invention or the technical solution in the prior art, the following is a brief introduction to the drawings required for the implementation or the prior art description. Obviously, the drawings described below are only exemplary, and for ordinary technicians in this field, other implementation drawings can be derived from the provided drawings without creative work.

[0027] Figure 1 For the present invention. DETAILED DESCRIPTION

[0028] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0029] A quantum resonance fluorescence immunoassay medical detection method, in which different target protein antibodies are respectively labeled with quantum dots of different emission wavelengths, and a confocal microscope is used as the detection device, and the following steps are performed:

[0030] Step 1: After the cells are fixed and permeabilized, they are incubated with different labeled quantum dot-antibody complexes to allow the antibodies to specifically bind to the corresponding target proteins in the cells, thereby obtaining labeled cell samples;

[0031] Step 2: Under a confocal microscope, use a laser of a specific wavelength to excite the labeled cell sample and collect fluorescence lifetime image data of different quantum dot emission wavelengths;

[0032] Step 3: Based on the fluorescence lifetime image data, the protein concentration-fluorescence lifetime standard curve is obtained through the fluorescence lifetime analysis algorithm, and the protein concentration-fluorescence lifetime standard curve is fitted to obtain the calculation formula for the content of different target proteins in the cell;

[0033] Step 4: For cell samples with unknown protein expression levels, repeat steps 1 and 2 above, and substitute the final fluorescence lifetime data into the content calculation formula obtained in step 3 above to obtain the content and location information of each target protein in the cell.

[0034] Embodiment 1:

[0035] The cells are fixed using paraformaldehyde solution for 15-30 minutes at a temperature of 4°C.

[0036] The cells are then permeabilized using a TritonX-100 solution for 5-15 minutes at a concentration of 0.1%-0.5%.

[0037] The antibodies are labeled with quantum dots of different particle size ranges, and then the cells are incubated with antibody complexes of different labeled quantum dots, so that the antibodies specifically bind to the corresponding target proteins in the cells, thereby obtaining labeled cell samples;

[0038] The quantum dots labeled with antibodies that specifically bind to the target protein have different particle sizes, so that they produce different colors after being excited, which is convenient for multi-color observation. The particle size range of the optional quantum dots is preferably 2-10nm.

[0039] To enhance the binding ability of quantum dots to antibodies, the surface of quantum dots is modified with carboxyl groups. Specifically, the quantum dot precursor is mixed with thioglycolic acid in an appropriate solvent and reaction conditions. The thiol (-SH) will coordinate with the atoms on the surface of the quantum dots, thereby connecting the carboxyl group (-COOH) to the surface of the quantum dots.

[0040] Under physiological pH conditions, antibody molecules usually have certain positive charge areas. The carboxyl group will dissociate in aqueous solution to form negatively charged carboxylate ions (-COO-). Electrostatic attraction will occur between the carboxyl group on the surface of quantum dots and the positively charged area on the surface of antibody molecules, thereby promoting the proximity and binding of quantum dots and antibodies.

[0041] The steps of quantum dot carboxyl modification process are as follows:

[0042] 1. Prepare quantum dot precursor solution: Dissolve the quantum dot precursor in toluene and ensure it is evenly dispersed.

[0043] 2. Adding a carboxyl-containing modification reagent: Add thioglycolic acid to the quantum dot precursor solution at a molar ratio of 1:5 between quantum dots and thioglycolic acid.

[0044] 3. Control the reaction conditions: Under the protection of inert gas nitrogen, heat the reaction system to 80°C-120°C and react for 6 hours-12 hours.

[0045] 4. Post-treatment: After the reaction is completed, unreacted reagents and impurities are removed by washing or the like to obtain carboxyl-modified quantum dots.

[0046] In the labeled quantum dot-antibody complex, the molar ratio of quantum dots to antibodies is 1:1.

[0047] Using a confocal microscope, a laser with a wavelength of 405nm was used to excite the labeled cell samples, and the scanning resolution was set to 512×512 pixels to 1024×1024 pixels to collect fluorescence lifetime image data at different quantum dot emission wavelengths. When the 405nm laser excites the quantum dots, the quantum dots can produce fluorescence. It can provide higher sensitivity when detecting large tumors.

[0048] Fluorescence lifetime refers to the average time it takes for a fluorescent molecule to return from an excited state to a ground state. Fluorescence lifetime image data is the presentation of lifetime information about the fluorescence emitted by different quantum dots (corresponding to different target proteins) collected under a confocal microscope. It reflects the changes in the fluorescence characteristics of different locations and different target proteins over time.

[0049] Based on the fluorescence lifetime image data, a protein concentration-fluorescence lifetime standard curve is obtained by a fluorescence lifetime analysis algorithm. The standard curve uses the known concentration of the target protein as the horizontal axis and the fluorescence lifetime data processed by the fluorescence lifetime analysis algorithm as the vertical axis. The concentration range of the standard curve is preferably 0.1 ng / mL-10 μg / mL.

[0050] Then, the protein concentration-fluorescence lifetime standard curve was fitted to obtain the calculation formula for the content of different target proteins in the cells.

[0051] In this embodiment, the fluorescence lifetime analysis algorithm adopts an exponential decay fitting algorithm. In the fluorescence process, the decay of the fluorescence intensity of many fluorescent substances over time follows an exponential law. For a given fluorescence emission system, the change of its fluorescence intensity I(t) over time t can be expressed by the following formula:

[0052]

[0053] Where I0 is the initial fluorescence intensity, and τ is the fluorescence lifetime we want to determine. The exponential decay fitting algorithm is based on a large number of data points of fluorescence intensity changing over time. Through fitting methods such as the least squares method, we find the exponential decay function curve that best fits these data points, thereby determining the value of the fluorescence lifetime.

[0054] Use a confocal microscope to collect data on the change of fluorescence intensity over time to obtain a series of discrete data points. Then, substitute these data into the above exponential decay formula, and continuously adjust the parameters and to minimize the sum of square errors between the fitting curve and the actual data points. The final value is the fluorescence lifetime of the fluorescent substance in the current system.

[0055] After completing all the above operations, take a cell sample with unknown protein expression level, repeat steps 1 and 2 above, and substitute the final fluorescence lifetime data into the content calculation formula obtained in step 3 above to obtain the content and location information of each target protein in the cell.

[0056] Embodiment 2:

[0057] The cells are fixed using paraformaldehyde solution for 15-30 minutes at a temperature of 4°C.

[0058] The cells are then permeabilized using a TritonX-100 solution for 5-15 minutes at a concentration of 0.1%-0.5%.

[0059] The antibodies are labeled with quantum dots of different particle size ranges, and then the cells are incubated with antibody complexes of different labeled quantum dots, so that the antibodies specifically bind to the corresponding target proteins in the cells, thereby obtaining labeled cell samples;

[0060] The quantum dots labeled with antibodies that specifically bind to the target protein have different particle sizes, so that they produce different colors after being excited, which is convenient for multi-color observation. The particle size range of the optional quantum dots is preferably 2-10nm.

[0061] In order to enhance the binding ability of quantum dots to antibodies, the surface of quantum dots is modified with amino groups. Specifically, an amino-containing precursor is introduced during the preparation of quantum dots. Aminosilane compounds are used as one of the precursors, and the amino group is directly connected to the surface of quantum dots under high-temperature pyrolysis reaction conditions. Taking CdSe quantum dots as an example, 3-aminopropyltriethoxysilane (APTES) is added during its synthesis process, and the reaction is carried out at a temperature of 200°C-300°C for several hours to tens of hours. APTES will decompose and connect the amino group to the surface of the quantum dots. Under physiological pH conditions, antibody molecules usually have a certain negative charge area. The amino group will be protonated in an aqueous solution to form a positively charged ammonium ion (-NH3 + ). The amino groups on the surface of the quantum dots and the negatively charged areas on the surface of the antibody molecules generate electrostatic attraction, which brings the quantum dots and antibodies closer to each other, thereby increasing the chance of the two combining.

[0062] In the labeled quantum dot-antibody complex, the molar ratio of quantum dots to antibodies is 1:1.

[0063] A confocal microscope was used to excite and label the cell samples with a laser at a wavelength of 405 nm. The scanning resolution was set to 512×512 pixels to 1024×1024 pixels to collect fluorescence lifetime image data at different quantum dot emission wavelengths.

[0064] Fluorescence lifetime refers to the average time it takes for a fluorescent molecule to return from an excited state to a ground state. Fluorescence lifetime image data is the presentation of lifetime information about the fluorescence emitted by different quantum dots (corresponding to different target proteins) collected under a confocal microscope. It reflects the changes in the fluorescence characteristics of different locations and different target proteins over time.

[0065] Based on the fluorescence lifetime image data, a protein concentration-fluorescence lifetime standard curve is obtained by a fluorescence lifetime analysis algorithm. The standard curve uses the known concentration of the target protein as the horizontal axis and the fluorescence lifetime data processed by the fluorescence lifetime analysis algorithm as the vertical axis. The concentration range of the standard curve is preferably 0.1 ng / mL-10 μg / mL.

[0066] Then, the protein concentration-fluorescence lifetime standard curve was fitted to obtain the calculation formula for the content of different target proteins in the cells.

[0067] In this embodiment, the fluorescence lifetime analysis algorithm adopts an exponential decay fitting algorithm.

[0068] Finally, take a cell sample with unknown protein expression level, repeat steps 1 and 2 above, substitute the final fluorescence lifetime data into the content calculation formula obtained in step 3 above to obtain the content and location information of each target protein in the cell.

[0069] In this embodiment, the difference from the first embodiment is that the quantum dots are modified with amino groups. In the biological environment, the carboxyl-modified and amino-modified quantum dots have different stability and biocompatibility. Due to their negative charge properties, the carboxyl-modified quantum dots have good dispersibility and stability and will interact with some cations in the body. The amino-modified quantum dots may show different characteristics in terms of binding affinity with certain biological molecules and cellular uptake, and they are selected according to the specific application scenario.

[0070] Embodiment three:

[0071] The cells are fixed using paraformaldehyde solution for 15-30 minutes at a temperature of 4°C.

[0072] The cells are then permeabilized using a TritonX-100 solution for 5-15 minutes at a concentration of 0.1%-0.5%.

[0073] The antibodies are labeled with quantum dots of different particle size ranges, and then the cells are incubated with antibody complexes of different labeled quantum dots, so that the antibodies specifically bind to the corresponding target proteins in the cells, thereby obtaining labeled cell samples;

[0074] The quantum dots labeled with antibodies that specifically bind to the target protein have different particle sizes, so that they produce different colors after being excited, which is convenient for multi-color observation. The particle size range of the optional quantum dots is preferably 2-10nm.

[0075] To enhance the binding ability of quantum dots to antibodies, the surface of quantum dots is modified with carboxyl groups. Specifically, the quantum dot precursor is mixed with thioglycolic acid in an appropriate solvent and reaction conditions. The thiol (-SH) will coordinate with the atoms on the surface of the quantum dots, thereby connecting the carboxyl group (-COOH) to the surface of the quantum dots.

[0076] Under physiological pH conditions, antibody molecules usually have certain positive charge areas. The carboxyl group will dissociate in aqueous solution to form negatively charged carboxylate ions (-COO-). Electrostatic attraction will occur between the carboxyl group on the surface of quantum dots and the positively charged area on the surface of antibody molecules, thereby promoting the proximity and binding of quantum dots and antibodies.

[0077] The steps of quantum dot carboxyl modification process are as follows:

[0078] 1. Prepare quantum dot precursor solution: Dissolve the quantum dot precursor in toluene and ensure it is evenly dispersed.

[0079] 2. Adding a carboxyl-containing modification reagent: Add thioglycolic acid to the quantum dot precursor solution at a molar ratio of 1:5 between quantum dots and thioglycolic acid.

[0080] 3. Control the reaction conditions: Under the protection of inert gas nitrogen, heat the reaction system to 80°C-120°C and react for 6 hours-12 hours.

[0081] 4. Post-treatment: After the reaction is completed, unreacted reagents and impurities are removed by washing or the like to obtain carboxyl-modified quantum dots.

[0082] In the labeled quantum dot-antibody complex, the molar ratio of quantum dots to antibodies is 1:5.

[0083] A confocal microscope was used to excite and label the cell samples with a laser at a wavelength of 405 nm. The scanning resolution was set to 512×512 pixels to 1024×1024 pixels to collect fluorescence lifetime image data at different quantum dot emission wavelengths.

[0084] Fluorescence lifetime refers to the average time it takes for a fluorescent molecule to return from an excited state to a ground state. Fluorescence lifetime image data is the presentation of lifetime information about the fluorescence emitted by different quantum dots (corresponding to different target proteins) collected under a confocal microscope. It reflects the changes in the fluorescence characteristics of different locations and different target proteins over time.

[0085] Based on the fluorescence lifetime image data, a protein concentration-fluorescence lifetime standard curve is obtained by a fluorescence lifetime analysis algorithm. The standard curve uses the known concentration of the target protein as the horizontal axis and the fluorescence lifetime data processed by the fluorescence lifetime analysis algorithm as the vertical axis. The concentration range of the standard curve is preferably 0.1 ng / mL-10 μg / mL.

[0086] Then, the protein concentration-fluorescence lifetime standard curve was fitted to obtain the calculation formula for the content of different target proteins in the cells.

[0087] In this embodiment, the fluorescence lifetime analysis algorithm adopts an exponential decay fitting algorithm.

[0088] Take a cell sample with unknown protein expression level, repeat steps 1 and 2 above, substitute the final fluorescence lifetime data into the content calculation formula obtained in step 3 above to obtain the content and location information of each target protein in the cell.

[0089] In this embodiment, the difference from the first embodiment is that different molar ratios of quantum dots to antibodies will produce significantly different effects. At a low molar ratio of less than 1:1, the fluorescence signal intensity is weak, the detection sensitivity is low, the risk of nonspecific binding increases, and the detection cost increases due to antibody waste; while at a high molar ratio of 1:5, although the fluorescence signal intensity is enhanced and the detection sensitivity is improved, problems such as quantum dot aggregation and increased steric hindrance are prone to occur, affecting the binding efficiency and detection accuracy. Therefore, in practical applications, it is necessary to carefully select the appropriate molar ratio to balance various factors according to specific detection requirements and conditions to ensure that the detection results are accurate and reliable.

[0090] Embodiment 4:

[0091] The cells are fixed using paraformaldehyde solution for 15-30 minutes at a temperature of 4°C.

[0092] The cells are then permeabilized using a TritonX-100 solution for 5-15 minutes at a concentration of 0.1%-0.5%.

[0093] The antibodies are labeled with quantum dots of different particle size ranges, and then the cells are incubated with antibody complexes of different labeled quantum dots, so that the antibodies specifically bind to the corresponding target proteins in the cells, thereby obtaining labeled cell samples;

[0094] The quantum dots labeled with antibodies that specifically bind to the target protein have different particle sizes, so that they produce different colors after being excited, which is convenient for multi-color observation. The particle size range of the optional quantum dots is preferably 2-10nm.

[0095] To enhance the binding ability of quantum dots to antibodies, the surface of quantum dots is modified with carboxyl groups. Specifically, the quantum dot precursor is mixed with thioglycolic acid in an appropriate solvent and reaction conditions. The thiol (-SH) will coordinate with the atoms on the surface of the quantum dots, thereby connecting the carboxyl group (-COOH) to the surface of the quantum dots.

[0096] Under physiological pH conditions, antibody molecules usually have certain positive charge areas. The carboxyl group will dissociate in aqueous solution to form negatively charged carboxylate ions (-COO-). Electrostatic attraction will occur between the carboxyl group on the surface of quantum dots and the positively charged area on the surface of antibody molecules, thereby promoting the proximity and binding of quantum dots and antibodies.

[0097] The steps of quantum dot carboxyl modification process are as follows:

[0098] 1. Prepare quantum dot precursor solution: Dissolve the quantum dot precursor in toluene and ensure it is evenly dispersed.

[0099] 2. Adding a carboxyl-containing modification reagent: Add thioglycolic acid to the quantum dot precursor solution at a molar ratio of 1:5 between quantum dots and thioglycolic acid.

[0100] 3. Control the reaction conditions: Under the protection of inert gas nitrogen, heat the reaction system to 80°C-120°C and react for 6 hours-12 hours.

[0101] 4. Post-treatment: After the reaction is completed, unreacted reagents and impurities are removed by washing or the like to obtain carboxyl-modified quantum dots.

[0102] In the labeled quantum dot-antibody complex, the molar ratio of quantum dots to antibodies is 1:1.

[0103] Fluorescence lifetime refers to the average time it takes for a fluorescent molecule to return from an excited state to a ground state. Fluorescence lifetime image data is the presentation of lifetime information about the fluorescence emitted by different quantum dots (corresponding to different target proteins) collected under a confocal microscope. It reflects the changes in the fluorescence characteristics of different locations and different target proteins over time.

[0104] Using a confocal microscope, a laser with a wavelength of 633nm was used to excite and label the cell samples. The scanning resolution was set to 512×512 pixels to 1024×1024 pixels, and fluorescence lifetime image data of different quantum dot emission wavelengths were collected. Although the sensitivity provided by the 633nm laser is relatively low when exciting protoporphyrin IX, it has an advantage when facing the situation where the blood layer blocks the fluorescence. For example, when detecting high-grade gliomas, the 633nm laser is a better choice because it is less affected by the blood layer.

[0105] Based on the fluorescence lifetime image data, a protein concentration-fluorescence lifetime standard curve is obtained by a fluorescence lifetime analysis algorithm. The standard curve uses the known concentration of the target protein as the horizontal axis and the fluorescence lifetime data processed by the fluorescence lifetime analysis algorithm as the vertical axis. The concentration range of the standard curve is preferably 0.1 ng / mL-10 μg / mL.

[0106] Then, the protein concentration-fluorescence lifetime standard curve was fitted to obtain the calculation formula for the content of different target proteins in the cells.

[0107] In this embodiment, the fluorescence lifetime analysis algorithm adopts an exponential decay fitting algorithm. In the fluorescence process, the decay of the fluorescence intensity of many fluorescent substances over time follows an exponential law. For a given fluorescence emission system, the change of its fluorescence intensity I(t) over time t can be expressed by the following formula:

[0108]

[0109] Where I0 is the initial fluorescence intensity, and τ is the fluorescence lifetime we want to determine. The exponential decay fitting algorithm is based on a large number of data points of fluorescence intensity changing over time. Through fitting methods such as the least squares method, we find the exponential decay function curve that best fits these data points, thereby determining the value of the fluorescence lifetime.

[0110] Use a confocal microscope to collect data on the change of fluorescence intensity over time to obtain a series of discrete data points. Then, substitute these data into the above exponential decay formula, and continuously adjust the parameters and to minimize the sum of square errors between the fitting curve and the actual data points. The final value is the fluorescence lifetime of the fluorescent substance in the current system.

[0111] Finally, take a cell sample with unknown protein expression level, repeat steps 1 and 2 above, substitute the final fluorescence lifetime data into the content calculation formula obtained in step 3 above to obtain the content and location information of each target protein in the cell.

[0112] In this embodiment, the difference from the first embodiment is that a laser with a wavelength of 633 nm is used to excite the cell sample. Although the sensitivity provided by the laser with a wavelength of 633 nm is relatively low, it has an advantage when the blood layer blocks the fluorescence. When detecting high-grade glioma samples, the 633 nm laser is a better choice because it is less affected by the blood layer.

[0113] Embodiment five:

[0114] The cells are fixed using paraformaldehyde solution for 15-30 minutes at a temperature of 4°C.

[0115] The cells are then permeabilized using a TritonX-100 solution for 5-15 minutes at a concentration of 0.1%-0.5%.

[0116] The antibodies are labeled with quantum dots of different particle size ranges, and then the cells are incubated with antibody complexes of different labeled quantum dots, so that the antibodies specifically bind to the corresponding target proteins in the cells, thereby obtaining labeled cell samples;

[0117] The quantum dots labeled with antibodies that specifically bind to the target protein have different particle sizes, so that they produce different colors after being excited, which is convenient for multi-color observation. The particle size range of the optional quantum dots is preferably 2-10nm.

[0118] To enhance the binding ability of quantum dots to antibodies, the surface of quantum dots is modified with carboxyl groups. Specifically, the quantum dot precursor is mixed with thioglycolic acid in an appropriate solvent and reaction conditions. The thiol (-SH) will coordinate with the atoms on the surface of the quantum dots, thereby connecting the carboxyl group (-COOH) to the surface of the quantum dots.

[0119] Under physiological pH conditions, antibody molecules usually have certain positive charge areas. The carboxyl group will dissociate in aqueous solution to form negatively charged carboxylate ions (-COO-). Electrostatic attraction will occur between the carboxyl group on the surface of quantum dots and the positively charged area on the surface of antibody molecules, thereby promoting the proximity and binding of quantum dots and antibodies.

[0120] The steps of quantum dot carboxyl modification process are as follows:

[0121] 1. Prepare quantum dot precursor solution: Dissolve the quantum dot precursor in toluene and ensure it is evenly dispersed.

[0122] 2. Adding a carboxyl-containing modification reagent: Add thioglycolic acid to the quantum dot precursor solution at a molar ratio of 1:5 between quantum dots and thioglycolic acid.

[0123] 3. Control the reaction conditions: Under the protection of inert gas nitrogen, heat the reaction system to 80°C-120°C and react for 6 hours-12 hours.

[0124] 4. Post-treatment: After the reaction is completed, unreacted reagents and impurities are removed by washing or the like to obtain carboxyl-modified quantum dots.

[0125] In the labeled quantum dot-antibody complex, the molar ratio of quantum dots to antibodies is 1:1.

[0126] A confocal microscope was used to excite and label the cell samples with a laser at a wavelength of 405 nm. The scanning resolution was set to 512×512 pixels to 1024×1024 pixels to collect fluorescence lifetime image data at different quantum dot emission wavelengths.

[0127] Fluorescence lifetime refers to the average time it takes for a fluorescent molecule to return from an excited state to a ground state. Fluorescence lifetime image data is the presentation of lifetime information about the fluorescence emitted by different quantum dots (corresponding to different target proteins) collected under a confocal microscope. It reflects the changes in the fluorescence characteristics of different locations and different target proteins over time.

[0128] Based on the fluorescence lifetime image data, a protein concentration-fluorescence lifetime standard curve is obtained by a fluorescence lifetime analysis algorithm. The standard curve uses the known concentration of the target protein as the horizontal axis and the fluorescence lifetime data processed by the fluorescence lifetime analysis algorithm as the vertical axis. The concentration range of the standard curve is preferably 0.1 ng / mL-10 μg / mL.

[0129] Then, the protein concentration-fluorescence lifetime standard curve was fitted to obtain the calculation formula for the content of different target proteins in the cells.

[0130] In this embodiment, the fluorescence lifetime analysis algorithm adopts a convolution inversion algorithm. In the fluorescence detection system, due to the influence of factors such as the instrument response function, the measured fluorescence decay curve is not an ideal exponential decay form, but the result of convolution with the instrument response function. The convolution inversion algorithm is to restore the real fluorescence decay process from the measured fluorescence decay curve containing the instrument response information, and then determine the fluorescence lifetime. It is based on the mathematical convolution theorem and is achieved by performing a deconvolution operation on the measured data and the known instrument response function.

[0131] When applying, the instrument response function h(t) must be accurately determined first, which can be obtained by measuring a standard sample with an extremely short fluorescence lifetime. Then, the fluorescence decay curve g(t) of the actual sample is measured. According to the convolution theorem,

[0132]

[0133] Where I(α) is the true fluorescence decay function (including fluorescence lifetime information). h(t-α) indicates that the instrument response function has been shifted in time. α is the integral variable, and t-α represents a delay or advance in time relative to t on the time axis. It reflects the relationship between the influence of the instrument response on the true fluorescence decay function I(α) at ​​different time points and time. For example, if t is a specific detection time point, it describes the response of the instrument to the fluorescence signal at different times before or after this time point. This response will change with the change of , thereby affecting the final measurement result g(t).

[0134] The above convolution equation is solved by a deconvolution algorithm, such as an iterative method, a Fourier transform method, etc., to obtain I(α), and then the fluorescence lifetime is determined from I(α). Usually, the part that conforms to the exponential decay law is found and its time constant is calculated as the fluorescence lifetime.

[0135] Finally, take a cell sample with unknown protein expression level, repeat steps 1 and 2 above, substitute the final fluorescence lifetime data into the content calculation formula obtained in step 3 above to obtain the content and location information of each target protein in the cell.

[0136] In this embodiment, the difference from the first embodiment is that the fluorescence lifetime analysis algorithm adopts the convolution inversion algorithm. These two algorithms have their own advantages and disadvantages when processing fluorescence lifetime image data. The exponential decay fitting algorithm is relatively simple and direct, and the calculation speed is fast, but the accuracy may be slightly lower for data with complex fluorescence decay processes or large instrument effects. The convolution inversion algorithm can take into account factors such as instrument response and restore the fluorescence decay process more accurately, but the calculation process is relatively complex and requires high computing resources and data quality.

[0137] The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited by the above embodiments, and the above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, and these changes and improvements all fall within the scope of the present invention to be protected.

[0138] The protection scope of the present invention is defined by the following claims and their equivalents.

Claims

1. Quantum resonance fluorescence immunoassay medical detection method, characterized in that: Different target protein antibodies were labeled with quantum dots of different emission wavelengths, and a confocal microscope was used as the detection device. The following steps were followed: Step 1: After the cells are fixed and permeabilized, they are incubated with different labeled quantum dot-antibody complexes to allow the antibodies to specifically bind to the corresponding target proteins in the cells, thereby obtaining labeled cell samples; Step 2: Under a confocal microscope, use a laser of a specific wavelength to excite the labeled cell sample and collect fluorescence lifetime image data of different quantum dot emission wavelengths; Step 3: Based on the fluorescence lifetime image data, the protein concentration-fluorescence lifetime standard curve is obtained through the fluorescence lifetime analysis algorithm, and the protein concentration-fluorescence lifetime standard curve is fitted to obtain the calculation formula for the content of different target proteins in the cell; Step 4: For cell samples with unknown protein expression levels, repeat steps 1 and 2 above, and substitute the final fluorescence lifetime data into the content calculation formula obtained in step 3 above to obtain the content and location information of each target protein in the cell.

2. The quantum resonance fluorescence immunoassay medical detection method according to claim 1, characterized in that: The cells are fixed with paraformaldehyde solution for 15-30 minutes at a temperature of 4°C.

3. The quantum resonance fluorescence immunoassay medical detection method according to claim 1, characterized in that: The cell permeabilization treatment uses TritonX-100 solution, the permeabilization time is 5-15 minutes, and the concentration of TritonX-100 solution is 0.1%-0.5%.

4. The quantum resonance fluorescence immunoassay medical detection method according to claim 1, characterized in that: The particle size of the quantum dots ranges from 2 to 10 nm, and the surface of the quantum dots is modified with carboxyl or amino groups to enhance the ability to bind to antibodies.

5. The quantum resonance fluorescence immunoassay medical detection method according to claim 1, characterized in that: In the labeled quantum dot-antibody complex, the molar ratio of quantum dots to antibodies is 1:1-1:

5.

6. The quantum resonance fluorescence immunoassay medical detection method according to claim 1, characterized in that: In the confocal microscope detection in step 2, the wavelength of the laser is 405nm-633nm, and the scanning resolution is 512×512 pixels to 1024×1024 pixels.

7. The quantum resonance fluorescence immunoassay medical detection method according to claim 1, characterized in that: The fluorescence lifetime analysis algorithm adopts an exponential decay fitting algorithm or a convolution inversion algorithm.

8. The quantum resonance fluorescence immunoassay medical detection method according to claim 1, characterized in that: The preparation of the standard curve uses a known concentration of recombinant target protein to react with the quantum dot-antibody complex, measures its fluorescence lifetime data and draws a standard curve, and the concentration range of the standard curve is 0.1 ng / mL-10 μg / mL.

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