WO2021227341A1 - 一种基于比色原理检测磷脂酶a2的方法及其应用 - Google Patents

一种基于比色原理检测磷脂酶a2的方法及其应用 Download PDF

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WO2021227341A1
WO2021227341A1 PCT/CN2020/118750 CN2020118750W WO2021227341A1 WO 2021227341 A1 WO2021227341 A1 WO 2021227341A1 CN 2020118750 W CN2020118750 W CN 2020118750W WO 2021227341 A1 WO2021227341 A1 WO 2021227341A1
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solution
phospholipase
color
graphene quantum
reaction
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French (fr)
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李楠
査勇超
牟宗霞
周锐
薛巍
周平
崔鑫
朱桦
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暨南大学
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/75—Systems in which material is subjected to a chemical reaction, the progress or the result of the reaction being investigated
    • G01N21/77—Systems in which material is subjected to a chemical reaction, the progress or the result of the reaction being investigated by observing the effect on a chemical indicator
    • G01N21/78—Systems in which material is subjected to a chemical reaction, the progress or the result of the reaction being investigated by observing the effect on a chemical indicator producing a change of colour
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
    • G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
    • G01N21/33—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using ultraviolet light

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  • the invention belongs to the field of medical detection, and particularly relates to a method for detecting phospholipase A2 based on the colorimetric principle and its application.
  • Phospholipase A2 is one of the members of the phospholipase family widely distributed in the human body. It can specifically act on the sn-2 ester bond of phospholipid molecules and hydrolyze phospholipids to form free fatty acids and lysophospholipids molecules. These products are used in phospholipid renewal and cell information. It plays an important role in physiological processes such as transmission. Therefore, the activity level of phospholipase A2 plays a key role in pathological processes such as information transmission and membrane channel activation during inflammation and tissue damage. For example, studies have shown that phospholipase A2 will be prematurely activated and excessively released when acute pancreatitis occurs, and directly participates in the pathogenesis of acute pancreatitis.
  • phospholipase A2 has become an important detection index in the diagnosis of inflammation-related diseases including acute pancreatitis.
  • Common methods for determining the activity of phospholipase A2 include optical methods, electrochemical methods, immunoassays, and chromatographic-mass spectrometry methods. Although they have been used in practical applications, these methods have disadvantages such as high detection costs, cumbersome steps and long cycles, low specificity, or relying on professional instruments and equipment.
  • Colorimetry colorimetry is a method to determine the content of the component to be tested by comparing or measuring the color depth of the colored substance solution, based on the color reaction that generates the colored compound. The required equipment is simple and easy to operate, and it is a common method widely used in analysis and detection.
  • the detection is aimed at the difficult detection caused by the special terrain of the detection area.
  • Another example is the Chinese patent application “A device, method and smart phone for detecting trace substances” with the publication number CN 109959780 A.
  • the camera of the detection device is used to take photos of the object to be tested, and then the photos are analyzed through the mobile phone APP to find out the content of trace substances in the sample. .
  • these methods all require third-party equipment to assist the smart phone to complete data collection and data reception.
  • smart phones are less involved in biochemical testing. This may be due to the lack of the establishment of a biochemical sensing detection system suitable for mobile terminal devices and the immature development of corresponding mobile phone applications (applications, APP).
  • the primary purpose of the present invention is to overcome the shortcomings and deficiencies of the prior art and provide a method for detecting phospholipase A2 based on the colorimetric principle.
  • Another object of the present invention is to provide the application of the method for detecting phospholipase A2 based on the colorimetric principle.
  • a method for detecting phospholipase A2 based on the colorimetric principle is achieved by any of the following methods:
  • step S2 draw a standard curve according to the absorbance value measured in step S1 and the concentration of the phospholipase A2 aqueous solution;
  • the smart phone-based detection system includes an image acquisition module, an image preprocessing module, a color analysis module, and a detection result display module connected in sequence;
  • the image acquisition module includes a camera, a cuvette, and a black box with the mobile phone, and is used to obtain color images (ie, digital photos) of the standard solution and the solution to be tested;
  • the image preprocessing module is to convert the obtained color images of the standard solution and the solution to be tested into a bitmap format and analyze them with different color models to obtain the average value of the color components of the standard solution and the solution to be tested;
  • the color analysis module draws a relationship curve based on the average value of the color components of the standard solution and the concentration thereof;
  • the result display module is the average value of the color components of the test solution and the drawn relationship curve to obtain the concentration and/or content of the test solution;
  • step S5. Pass the color image obtained in step S4 through the image preprocessing module in the smart phone detection system to obtain the average value of the color components respectively;
  • step S6 According to the color component average value and the concentration of the phospholipase A2 aqueous solution obtained in step S5, the relationship curve is obtained through the color analysis module in the smart phone detection system;
  • the liposomes coated with graphene quantum dots described in steps S1, S3, S4 and S7 are preferably prepared by the following method:
  • the graphene quantum dot solution is added to the liposome film, and the ice bath is ultrasonically dispersed to obtain a mixed solution I; then the mixed solution I is repeatedly squeezed through a polycarbonate membrane to obtain a mixed solution II; The solution II was dialyzed to obtain nano liposomes encapsulating graphene quantum dots.
  • the molar ratio of lecithin to cholesterol in step (1) is 1 to 5:1; preferably 5:1.
  • the amount of chloroform mentioned in step (1) is calculated based on 1ml chloroform per 1.8mmol of cholesterol (or 1ml chloroform per 10.8mmol of lecithin and cholesterol).
  • the ultrasound conditions described in step (1) are: 100W ultrasound for 5-10 minutes; preferably, 100W ultrasound for 5 minutes.
  • the conditions of the rotary steaming described in step (1) are: 40°C rotary steaming for 15-60 minutes; preferably 40°C rotary steaming for 60 minutes.
  • the total mass ratio of the graphene quantum dots to the lecithin and cholesterol in step (2) is 0.02-0.4:30; preferably 0.2:30.
  • the graphene quantum dot solution described in step (2) is an aqueous solution of graphene quantum dots, or a solution obtained by dissolving graphene quantum dots in a phosphate buffer solution; its concentration is 0.01 to 0.2 mg/mL; preferably 0.1 mg/mL mL.
  • the phosphate buffer solution is a mixed solution of disodium hydrogen phosphate and sodium dihydrogen phosphate, and the pH is adjusted to 7.0.
  • the graphene quantum dots described in step (2) are preferably prepared by the following method:
  • the carbon black described in step (i) is preferably carbot vulcan XC-72 carbon black.
  • the concentration of the concentrated nitric acid solution in step (i) is 5-8 mol/L; preferably 6 mol/L.
  • the reflux reaction in step (i) is preferably carried out in an oil bath.
  • the reflux reaction time in step (i) is preferably 24 hours.
  • the filtering described in step (ii) is filtering with a filter paper and a needle filter in sequence.
  • the pore size of the needle filter is 0.22 ⁇ m.
  • step (ii) The conditions for centrifugation in step (ii) are all: 8000 rpm centrifugation for 10 minutes.
  • the pore size of the ultrafiltration centrifuge tube described in step (ii) is 3000 Da.
  • the dialysis described in step (ii) uses a dialysis bag with a molecular weight cut-off of 100 to 500 Da for dialysis.
  • the conditions of the dialysis described in step (ii) are: dialysis with deionized water as the dialysate for 24 hours.
  • the temperature of the extrusion described in step (2) is preferably 40 ⁇ 2°C.
  • step (2) The extrusion described in step (2) is carried out in a liposome extruder.
  • the pore size of the polycarbonate membrane described in step (2) is 200 nm.
  • the number of extrusions described in step (2) is 21 times or more.
  • the dialysis described in step (2) uses a dialysis membrane with a molecular weight cut-off of 8000 Da for dialysis.
  • the dialysis time described in step (2) is 24 hours.
  • the ultrasound conditions described in step (2) are: 100W ultrasound for 40-60 minutes; preferably, 100W ultrasound for 50 minutes.
  • the amount of the phospholipase A2 aqueous solution described in steps S1 and S4 is added at a final concentration of 10 to 200 U/L in the reaction system; preferably, it is added at a final concentration of 10 to 20 U/L in the reaction system. Add 50, 100 and 200U/L.
  • the dosage of the nano liposomes encapsulating graphene quantum dots in steps S1, S3, S4 and S7 is calculated according to the final concentration of 0.029 ⁇ 0.058 mg/ml in the reaction system; The final concentration of the reaction system is 0.054 mg/ml and the calculation is added.
  • TMB 3,3',5,5'-tetramethylbenzidine
  • the H 2 O 2 in steps S1, S3, S4, and S7 is calculated based on the addition of the final concentration in the reaction system of 0.1 to 0.2 mM/L; preferably, the final concentration in the reaction system is Add 0.1mM/L to calculate.
  • the acidic solution described in steps S1, S3, S4 and S7 is an acidic buffer; preferably an acetic acid-sodium acetate buffer; more preferably an acetic acid-sodium acetate buffer with a pH of 3.8.
  • the time for continuing the reaction described in steps S1, S3, S4 and S7 changes according to the color of the solution, that is, it ends when it changes from colorless to blue; preferably 15-30 minutes; more preferably 20 minutes.
  • the wavelength range of the ultraviolet absorption spectrum described in steps S1 and S3 is 500-800 nm, and the wavelength position where the absorbance value is selected is 652 nm.
  • the average value of the color components in step (B) is the average value of each color component in the area divided by each color component of all pixels in the designated area of the color image.
  • the color information extracted in the bitmap format described in step S5 adopts RGB (red, green, blue), HSV (hue, saturation, lightness), HSL (hue, saturation, brightness), and CMYK (cyan-magenta-yellow). -Any one of black); preferably RGB (red, green, and blue) blue component representation; more preferably, RGB (red, green, blue) blue (B) component representation.
  • the detection system for realizing the above method for detecting phospholipase A2, the detection system is a smart phone-based detection system, and includes an image acquisition module, an image preprocessing module, a color analysis module, and a detection result display module connected in sequence;
  • the image acquisition module includes a camera, a cuvette, and a black box with the mobile phone, and is used to obtain color images (ie, digital photos) of the standard solution and the solution to be tested;
  • the image preprocessing module is to convert the obtained color images of the standard solution and the solution to be tested into a bitmap format, and analyze them with different color models to obtain the average value of the color components of the standard solution and the solution to be tested;
  • the color analysis module draws a relationship curve based on the average value of the color components of the standard solution and the concentration thereof;
  • the result display module is the average value of the color components of the test solution and the drawn relationship curve to obtain the concentration and/or content of the test solution.
  • the cuvette is preferably a cuvette filled with sensing reagents.
  • the sensing reagent is 3,3',5,5'-tetramethylbenzidine (TMB), H 2 O 2 and acidic solution.
  • the acidic solution is an acidic buffer; preferably an acetic acid-sodium acetate buffer; more preferably an acetic acid-sodium acetate buffer with a pH of 3.8.
  • the extracted color information in the bitmap format uses RGB (red, green, blue), HSV (hue, saturation, lightness), HSL (hue, saturation, brightness), and CMYK (cyan-magenta-yellow-black). ); preferably, it is represented by the blue component of RGB (red, green, and blue); more preferably, it is represented by the blue (B) component of RGB (red, green, and blue).
  • the average value of the color components is the average value of each color component of all pixels in the color image divided by the number of pixels.
  • the present invention has the following advantages and effects:
  • the analyte phospholipase A2 is directly used as a stimulus to cause the rupture of phospholipid vesicles, which provides new ideas for the design of intelligent bionic microvesicles in response to environmental stimuli and the construction of new intelligent bionic systems.
  • graphene quantum dots Utilizing the nanoenzyme characteristics of graphene quantum dots, that is, it has a unique catalytic activity similar to natural peroxidase, which can replace natural enzymes for color reaction. Compared with the use of natural enzymes, graphene quantum dots have the advantages of low cost, easy mass production, easy storage and not easy to inactivate.
  • the present invention specifically breaks the liposome by phospholipase A2, thereby releasing the graphene quantum dots encapsulated therein. Based on the catalytic activity of graphene quantum dots similar to natural enzymes, it can effectively catalyze the oxidation of the substrate TMB, and the color of the solution changes from colorless to blue. This change is closely related to the activity of phospholipase A2 to establish a visual detection of phospholipase A2. Testing new principles.
  • the present invention uses a smart phone for image acquisition and color analysis, by calculating the pixel value of each component of the standard sample solution in the RGB color space, and then fitting the standard curve for phospholipase A2 detection by the least square method to obtain the phospholipase Correspondence between the linear concentration of A2 and the pixel value of the color component; and then calculate the concentration of phospholipase A2 in the unknown sample solution. So as to realize the sensitive, accurate, convenient and visual detection of phospholipase A2.
  • the present invention is based on the phospholipase A2 detection sensor platform established by the smart phone, using the smart phone's own high-resolution camera, and designing the mobile phone application software to process the color information after the reaction of different concentrations of reagents without additional equipment and Complicated detection can realize rapid detection of reagent concentration.
  • the present invention applies the enzyme-like catalytic properties of graphene quantum dots to the detection of disease markers, and develops a new application of smart phones for disease marker detection in the field of biosensors.
  • the phospholipase A2 color analysis and detection method based on the smart phone established in the present invention can be applied to general biomedical testing, and has great application value and market promotion for medical testing in areas with scarce medical conditions.
  • Fig. 1 is a schematic diagram of a method for detecting phospholipase A2 based on a smart phone of the present invention.
  • Figure 2 is a characterization diagram of graphene quantum dots; among them, A is a scanning electron microscope photo of graphene quantum dots; B is an atomic force microscope photo of graphene quantum dots.
  • Figure 3 shows the emission spectra of graphene quantum dots under different excitation wavelengths and the ultraviolet absorption spectra of different reaction systems; where A is the emission spectra of graphene quantum dots under different excitation wavelengths (the inset is white light and 365nm ultraviolet light irradiation Image of graphene quantum dot solution at time); B is the UV absorption spectra of different reaction systems (in the figure: a is TMB+H 2 O 2 +GQD, b is TMB+H 2 O 2 , c is TMB+GQD, d is H 2 O 2 +GQD; the inset photos are images taken under white light after 20 minutes of reaction in different reaction systems).
  • Figure 4 is a graph showing the comparison of the catalytic activity of graphene quantum dots and natural horseradish peroxidase under different pH conditions.
  • Figure 5 is a graph showing the catalytic activity comparison between graphene quantum dots and natural horseradish peroxidase under different temperature conditions.
  • Figure 6 is a characterization diagram of liposomes; where A is a scanning electron micrograph of liposomes; B is a particle size distribution of liposomes (the inset is an image of liposome solution under white light irradiation).
  • Figure 7 is the result of the color reaction caused by the activity of phospholipase A2; where A is the UV absorption spectrum after the reaction of phospholipase A2 with different active concentrations to rupture the liposome and release graphene quantum dots with TMB and H 2 O 2 ; B is the standard curve of the absorbance of the solution at 652nm with the concentration of phospholipase A2.
  • Fig. 8 is a selective experiment result of phospholipase A2 color detection based on graphene quantum dot liposomes.
  • Figure 9 is a diagram of a color detection system for phospholipase A2 based on a smart phone.
  • Figure 10 is a display interface diagram of different color component models after a smart phone performs color detection and analysis on the same photo.
  • Figure 11 is a graph showing the linear fitting results of the corresponding color models of images of phospholipase A2 with different active concentrations (the active concentrations of phospholipase A2 are 0, 10, 20, 50, 100, 150, 200, 300 U/L, respectively);
  • A is the fitting curve of RGB value with the change of phospholipase A2 activity concentration
  • B is the fitting curve of HSL value with the change of phospholipase A2 activity concentration
  • C is the fitting curve of HSV value with the change of phospholipase A2 activity concentration
  • D It is the fitted curve of the change of CMYK value with phospholipase A2 activity concentration.
  • Figure 12 is the standard curve of the B component in the RGB color model with the change of the phospholipase A2 activity concentration and the mobile phone analysis result display interface diagram of the phospholipase A2 activity concentration in the solution to be tested; where A is the B component in the RGB color model with the phospholipase A2 activity concentration A2 is the standard curve of the activity concentration change; B is the display interface of the mobile phone analysis result of the phospholipase A2 activity concentration in the solution to be tested.
  • the present invention will be further described in detail below in conjunction with examples, but the implementation of the present invention is not limited thereto.
  • the reagents, methods and equipment used in the present invention are conventional reagents, methods and equipment in the technical field.
  • the test methods that do not indicate specific experimental conditions in the following examples are usually in accordance with conventional experimental conditions or in accordance with experimental conditions recommended by the manufacturer.
  • the reagents and raw materials used in the present invention are all commercially available.
  • Example 1 A method for synthesizing graphene quantum dots and its peroxidase-like catalytic activity.
  • the solution 2 was filtered again with a 0.22 ⁇ m syringe filter to obtain a solution 3.
  • the solution 3 was centrifuged at 8000 rpm for 10 minutes, and then the supernatant was pipetted into an ultrafiltration centrifuge tube (with a pore size of 3000 Da) to obtain a solution 4.
  • Centrifuge the solution 4 at 8000 rpm (10 minutes) to basically separate all the clear liquid from the precipitate, and finally put the separated clear liquid into a dialysis bag with a molecular weight cut-off of 100 to 500 Da.
  • the solution is added to the centrifuge tube, and the graphene quantum dots (GQD) are formed after lyophilization.
  • GQD graphene quantum dots
  • the scanning electron microscope photo of the graphene quantum dots is shown in Figure 2A, and the atomic force microscope photo is shown in Figure 2B.
  • the emission spectra of graphene quantum dots at different excitation wavelengths fluorescence spectrophotometer, 405, 425, 445, 465, 485, 505, 525nm
  • images of graphene quantum dot solutions under white light and 365nm ultraviolet light irradiation As shown in Figure 3A.
  • the graphene quantum dots synthesized in 1.1 are added to contain hydrogen peroxide (purchased from Shanghai Macleans Biochemical Technology Co., Ltd., with a purity greater than 99%) and 3,3',5,5'-tetramethylbenzidine (TMB,
  • Graphene quantum dots have a catalytic activity similar to that of natural peroxidase, that is, in an acidic environment and in the presence of hydrogen peroxide, it can effectively catalyze the enzyme reaction substrate 3,3',5,5'-tetramethylbenzidine ( TMB), which causes the oxidation reaction to change from a colorless reactant to a blue product. Therefore, when graphene quantum dots, TMB and hydrogen peroxide are present in the acetic acid buffer solution at pH 3.8, the color of the reaction system will change from colorless to blue.
  • Figure 3B shows the different reaction systems after 20 minutes of reaction.
  • the UV absorption spectra of (the inset photos are images taken under white light after 20 minutes of reaction in different reaction systems). This result proves that graphene quantum dots have excellent natural-like enzyme activity and can replace natural enzymes for color reaction.
  • Graphene quantum dots as nanoenzymes, have similar catalytic activity to natural horseradish peroxidase, that is, they catalyze the reduction of hydrogen peroxide to water and oxygen, and at the same time catalyze the oxidation of its substrate TMB to oxidized TMB.
  • the purpose of this experiment is to compare the catalytic activity of graphene quantum dots and natural horseradish peroxidase under different pH conditions. The specific steps are as follows:
  • the graphene quantum dots synthesized in 1.1 and natural horseradish peroxidase were dissolved in 0.5 ml of different pH (pH 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0) in the buffer solution, the final concentration of the obtained solution containing graphene quantum dots is 20 ⁇ g/ml, and the final concentration of the solution containing natural horseradish peroxidase is 10 Ng/ml;
  • the buffers used are: acetate buffer solution (50mM, pH 2.0-pH 5.0), phosphate buffer solution (50mM, pH 6.0-7.0) and Tris-hydrochloric acid buffer solution (50mM, pH8.0-10.0) ).
  • TMB 3,3',5,5'-tetramethylbenzidine
  • the purpose of this experiment is to compare the catalytic activity of graphene quantum dots and natural horseradish peroxidase under different temperature conditions.
  • the specific steps are as follows: compare the graphene quantum dots synthesized in 1.1 with natural horseradish peroxidase (150u/ mg) were dissolved in 0.5 ml of pH 6 phosphate buffer solution (50 mM), and the final concentrations were respectively 20 ⁇ g/ml and 10 ng/ml. At different temperatures (4, 15, 25, 30, 35, 40, 45 After incubating for 4 hours at 50, 60, 70, 80, 90, 100°C), a final concentration of 0.6mmol/LTMB solution and 1mM hydrogen peroxide solution were added to catalyze the reaction.
  • graphene quantum dots as inorganic nanomaterials, have strong structural stability, and their catalytic activity is basically not changed by environmental temperature changes, and the catalytic activity remains at 95% to 100% under low or high temperature conditions. between. This result shows that compared with natural enzymes, the catalytic activity of graphene quantum dots is less affected by the temperature of the external environment, and can be used under extreme temperature conditions.
  • graphene quantum dots not only have the advantages of lower cost, mass production, and excellent stability than natural enzymes. It is easy to store and use under acid-base or high temperature conditions, and can be a substitute for natural enzymes for a wider range of uses.
  • Example 2 A method for synthesizing liposomes coated with graphene quantum dots
  • Lecithin and cholesterol were mixed at a ratio of 5:1 (molar ratio, 43.2mmol, 30mg), dissolved in 4ml of chloroform, and sonicated (power 100W) for 5 minutes to make the dispersion uniform. Then, the organic solvent was removed by rotary evaporator at 40° C. under reduced pressure for 1 hour, and a transparent film was uniformly formed on the bottom of the flask. At this time, add 2mL 0.1mg/ml graphene quantum dot solution (dissolve the graphene quantum dots prepared in Example 1 in a phosphate buffer solution (pH 7.0)), and ultrasound in an ice bath (power 100W) for 50 minutes to obtain a milky white Turbid liquid.
  • 2mL 0.1mg/ml graphene quantum dot solution dissolve the graphene quantum dots prepared in Example 1 in a phosphate buffer solution (pH 7.0)
  • ultrasound in an ice bath power 100W
  • the obtained liposome solution was dialyzed against a dialysis membrane (with a molecular weight cut-off of less than 8000D), using deionized water as the dialysate, dialyzed for 24 hours to remove the unencapsulated graphene quantum dots, and store the obtained liposome solution At 4°C.
  • Fig. 6A The scanning electron microscope results of the liposomes are shown in Fig. 6A, and the particle size distribution is shown in Fig. 6B (the inset is the image of the liposome solution under white light irradiation). It can be seen from the particle size distribution and scanning electron microscopy results that the liposome vesicles prepared in this example have uniform size and good dispersibility.
  • Example 3 Method for detecting phospholipase A2 using characteristics of liposomes coated with graphene quantum dots
  • the invention provides a method for specifically rupturing liposomes by using phospholipase A2, releasing graphene quantum dots coated therein, and using the peroxidase-like catalytic properties of the phospholipase A2 to perform color development and detection of phospholipase A2.
  • Embodiment 4 Mobile phone-based color analysis and detection system and method
  • the hardware required for detection in the present invention includes a black box (used to block external light sources, self-made, dark box or other options), a cuvette and a smart phone;
  • the smart phone-based detection system in the present invention includes an image acquisition module, an image preprocessing module, a color analysis module, and a detection result display module connected in sequence;
  • the image acquisition module includes a camera, a cuvette and a black box with the mobile phone; the cuvette is filled with sensing reagents; the sample solution is added to the cuvette with the sensing reagents for reaction, and after the reaction is complete Develop the color and place it in the black box, take pictures of the solution in the cell phone's built-in camera and contrast the color dish to obtain the color image (ie digital photo) of the reaction solution; the sample solution includes the standard solution of known concentration and the test solution of unknown concentration Solution: In addition to directly calling the mobile phone camera to take real-time photos, other methods (such as camera, etc.) can also be used to obtain the color image of the reaction solution and store it in the local photo album of the mobile phone, and then perform subsequent operations;
  • the image preprocessing module is to convert the color image of the obtained reaction solution into a bitmap format, and analyze it with different color models; based on the Android system of a smart phone, use the Java tool language to write an application program to convert the image bitmap format
  • the pixel information in is converted into color information, usually expressed in the form of red, green and blue (RGB), and RGB can be converted into other corresponding color models, such as hue saturation lightness (HSV), hue saturation brightness (HSL) and cyan-
  • RGB hue saturation lightness
  • HSL hue saturation brightness
  • CMYK magenta-yellow-black
  • the color components of all pixels in a certain area are calculated, and then divided by the number of pixels as the average value of each component in this area) (form a multi-mode color detection and analysis system); when the mobile phone performs color detection of the reaction solution, After recalling the captured color image, click the RGB, HSV, HSL, CMYK virtual buttons respectively, and the mobile phone software interface will display the color model component parameters of the area ( Figure 10), and the response can be obtained through the image preprocessing module
  • the average value of the color component of the standard solution the pixel value of each component in the RGB, HSV, HSL or CMYK color space
  • the average value of the color component of the solution to be tested the average value of the color component of the solution to be tested;
  • the color analysis module draws a relationship curve based on the average value of the color components of the standard solution and the concentration thereof;
  • the result display module calculates the concentration of the solution to be tested based on the average value of the color components of the solution to be tested and the drawn relationship curve, and can also obtain its content based on the obtained concentration and volume of the solution to be tested; detection;
  • step (2) According to the color image of the reaction solution obtained in step (1), obtain the average value of RGB, HSV, HSL and CMYK color components through the image preprocessing module;
  • the relationship curve is obtained through the color analysis module; here it can be compared with the curve measured by the spectrophotometer , Select a relationship curve with the highest degree of fit as the standard curve for subsequent tests, and it is built into the mobile phone application software; among them, the curve measured by the spectrophotometer is obtained by the following method: prepare at least five concentrations of phospholipase A2 The aqueous solution was then added to the liposomes coated with graphene quantum dots prepared in Example 2 and mixed in a water bath, and then 3,3',5,5'-tetramethylbenzidine (TMB), H 2 O 2 and The acidic solution is reacted.
  • TMB 3,3',5,5'-tetramethylbenzidine
  • the absorbance value is measured with a spectrophotometer, and then a curve is drawn based on the absorbance value and the concentration of the phospholipase A2 aqueous solution; among them, each substance in the reaction system and its concentration are the same as the above step (1) same;
  • the data of the average value of each color component is fitted and compared, and the result is shown in Figure 11.
  • the present invention measures the selection of the B-component fitting curve (Figure 12A) in the RGB data model with the best sensitivity and fit as a built-in test for subsequent tests. standard curve line;

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Abstract

一种基于比色原理检测磷脂酶A2的方法及其应用。可以基于石墨烯量子点具有类天然酶催化活性，在过氧化氢存在的酸性条件下能够有效催化底物TMB氧化，伴随着溶液颜色由无色转化为蓝色。在过氧化氢和TMB共同存在的酸性条件下，根据准样品溶液的吸光值及其浓度关系绘制标准曲线，进而计算得出未知样品溶液中磷脂酶A2的浓度；或在智能手机检测系统的基础上，通过图像采集和颜色分析，通过计算标准样品溶液在RGB颜色模型中B分量颜色平均值，得到磷脂酶A2线性浓度和颜色分量平均值之间的线性关系；进而计算得出未知样品溶液中磷脂酶A2的浓度，从而实现磷脂酶A2的灵敏、准确、便捷和可视化的检测。

Description

一种基于比色原理检测磷脂酶A2的方法及其应用 技术领域
本发明属于医疗检测领域，特别涉及一种基于比色原理检测磷脂酶A2的方法及其应用。
背景技术
磷脂酶A2是广泛分布于人体的磷脂酶家族成员之一，其能够特异性作用于磷脂分子的sn-2酯键，水解磷脂形成游离态的脂肪酸和溶血磷脂分子，这些产物在磷脂更新和细胞信息传递等生理过程中发挥重要作用。因此，磷脂酶A2的活性水平在机体炎症和组织损伤时对于信息传递和膜通道活化等病理过程中起关键性作用。例如，研究表明磷脂酶A2在急性胰腺炎发生时会出现过早激活和过度释放，并直接参与急性胰腺炎的发病过程。磷脂酶A2的检测已成为包括急性胰腺炎在内的炎症相关疾病诊断中一项重要的检测指标。测定磷脂酶A2活性的常用方法包括光学法、电化学法、免疫法和色谱质谱联用方法等。尽管已运用于实际应用中，这些方法依存在检测成本高、步骤繁琐且周期长、特异性低或依赖专业仪器设备等不足。比色法(colorimetry)是通过比较或测量有色物质溶液颜色深度来确定待测组分含量的方法，以生成有色化合物的显色反应为基础。其所需仪器简单，操作简便，是广泛应用于分析检测的常用方法。
此外，随着电子技术的飞速发展，智能手机已经融入人们生活的方方面面，成为人们生活中不可或缺的一部分。随着智能手机硬件及系统的升级，手机的功能越来越强大。目前智能手机已实现对于心率、血压和运动状态等物理参量和生理信号的检测，以及进行污染微量物质的大数据监控管理。譬如，公开号为CN 207262061 U的中国专利申请“一种基于APP的甲烷智能检测系统”将甲烷探测仪与手机通过蓝牙模块进行连接，通过手机APP对探测仪获得的数据进行整理分析，解决在实际检测中针对检测区域特殊地形导致的高难度检测。又如公开号为CN 109959780 A的中国专利申请“一种微量物质检测装置、方法及智能手机”利用检测装置的摄像头对待测物进行拍照，然后通过手机APP对照片分析出样品中微量物质的含量。但这些方法都需要第三方的设备来辅助智能手机完成数据收集、数据接收的工作。此外，智能手机对于生化检测还较少触及。这可能是由于缺少适用于移动终端设备的生化传感检测体系的建立，以及相应的配套手机应用程序(applications,APP)的开发尚不成熟。目前，疾病标志物的检测大部分仍采用中心实验室集中检验，离不开分析仪器设备和专业操作人员，这在即时检验和居家监测领域的应用十分受限。依据智能手机的便携性、普及性和移动终端对于 数据处理和传输的快捷性等优势，尤其是基于其强悍的处理器以及图像获取功能，配合个性化的应用程序开发，在智能手机上实现与生理病理相关的疾病标志物的实时传感检测，具有灵敏快捷、携带方便和使用简便的优点，在健康管理、临床诊疗、疾病监测等方面具有广阔的应用潜力。
将比色检测原理与便携性好普及性高的智能手机移动终端设备相结合，建立快速、便捷和灵敏的磷脂酶检测新方法对于临床诊断和居家监护具有非常重要意义。
发明内容
本发明的首要目的在于克服现有技术的缺点与不足，提供一种基于比色原理检测磷脂酶A2的方法。
本发明的另一目的在于提供所述基于比色原理检测磷脂酶A2的方法的应用。
本发明的目的通过下述技术方案实现：
一种基于比色原理检测磷脂酶A2的方法，为通过如下任一种方法实现：
(A)基于显色法检测磷脂酶A2：
S1、配制至少五个浓度的磷脂酶A2水溶液，然后分别加入包覆石墨烯量子点的脂质体混合后水浴反应，再加入3,3’,5,5’-四甲基联苯胺(TMB)、H 2O 2和酸性溶液继续反应，待反应结束后测量紫外吸收光谱，得到吸光值；
S2、根据步骤S1测量得到的吸光值与磷脂酶A2水溶液的浓度绘制标准曲线；
S3、将待测样品与包覆石墨烯量子点的脂质体混合后水浴反应，然后加入3,3’,5,5’-四甲基联苯胺(TMB)、H 2O 2和酸性溶液继续反应，待反应结束后测量紫外吸收光谱，得待测样品的吸光值；再根据步骤S2绘制的标准曲线获得待测样品中磷脂酶A2的浓度和/或含量；
(B)基于智能手机检测系统检测磷脂酶A2：
所述的基于智能手机检测系统包括依次连接的图像采集模块，图像预处理模块，颜色分析模块和检测结果显示模块；
所述的图像采集模块包括手机自带摄像头、比色皿和黑匣子，用于获取标准溶液和待测溶液的颜色图像(即数码照片)；
所述的图像预处理模块为将获取的标准溶液和待测溶液的颜色图像转换为位图格式，以不同的颜色模型分析，用于获得标准溶液和待测溶液的颜色分量平均值；
所述的颜色分析模块为根据标准溶液的颜色分量平均值及其浓度绘制关系曲线；
所述的结果显示模块为待测溶液的颜色分量平均值和绘制的关系曲线，获得待测溶液的浓度和/或含量；
所述的基于智能手机检测系统检测磷脂酶A2，通过如下步骤实现：
S4、配制至少五个浓度的磷脂酶A2水溶液，然后分别加入包覆石墨烯量子点的脂质体混合后水浴反应，再加入3,3’,5,5’-四甲基联苯胺(TMB)、H 2O 2和酸性溶液继续反应，待反应结束后用智能手机检测系统中的图像采集模块获取反应后的溶液的颜色图像；
S5、将步骤S4中获取颜色图像通过智能手机检测系统中的图像预处理模块，分别获取其颜色分量平均值；
S6、根据步骤S5中获取的颜色分量平均值和磷脂酶A2水溶液的浓度，通过智能手机检测系统中的颜色分析模块获得关系曲线；
S7、将包覆石墨烯量子点的脂质体加入到待测样品中，混合后水浴反应，再加入3,3’,5,5’-四甲基联苯胺(TMB)、H 2O 2和酸性溶液继续反应，待反应结束后通过智能手机检测系统中图像采集模块和图像预处理模块测定待测溶液的颜色分量平均值，然后根据步骤S6中的关系曲线，计算得到待测溶液中磷脂酶A2的浓度和/或含量。
步骤S1、S3、S4和S7中所述的包覆石墨烯量子点的脂质体优选为通过如下方法制备得到：
(1)将卵磷脂与胆固醇加入到氯仿中，超声使其分散均匀，然后旋蒸除去氯仿，得到脂质体薄膜；
(2)将石墨烯量子点溶液加入到脂质体薄膜中，冰浴超声分散均匀，得到混合溶液I；然后将混合溶液I通过聚碳酸酯膜反复挤压，得到混合溶液II；再将混合溶液II进行透析，得到包封石墨烯量子点的纳米脂质体。
步骤(1)中所述的卵磷脂与胆固醇的摩尔比为1～5：1；优选为5：1。
步骤(1)中所述的氯仿的用量为按每1.8mmol胆固醇配比1ml氯仿计算(或每10.8mmol卵磷脂和胆固醇配比1ml氯仿计算)。
步骤(1)中所述的超声的条件为：100W超声5～10min；优选为：100W超声5min。
步骤(1)中所述的旋蒸的条件为：40℃旋蒸15～60分钟；优选为40℃旋蒸60分钟。
步骤(2)中所述的石墨烯量子点与所述卵磷脂和胆固醇的总质量比为0.02～0.4:30；优选为0.2:30。
步骤(2)中所述的石墨烯量子点溶液为石墨烯量子点水溶液，或将石墨烯量子点溶于磷酸缓冲溶液得到的溶液；其浓度为0.01～0.2mg/mL；优选为0.1mg/mL。
所述的磷酸缓冲溶液为磷酸氢二钠和磷酸二氢钠的混合溶液，调节pH为7.0。
步骤(2)中所述的石墨烯量子点优选为通过如下方法制备得到：
(i)将碳黑加入到浓硝酸溶液中，于130℃条件下搅拌回流反应，待反应结束后冷却至室温，吸取上清液，加热除酸至pH为5～7，得到溶液A；
(ii)将溶液A过滤，取滤液；然后将滤液进行离心，取上清液；再将上清液加入到超 滤离心管中，离心，取清液；最后将清液进行透析，待透析结束后，冷冻干燥，得到石墨烯量子点。
步骤(i)中所述的碳黑优选为carbot vulcan XC-72碳黑。
步骤(i)中所述的浓硝酸溶液的浓度5～8mol/L；优选为6mol/L。
步骤(i)中所述的回流反应优选为在油浴下进行回流反应。
步骤(i)中所述的回流反应的时间优选为24小时。
步骤(ii)中所述的过滤为依次用滤纸和针式过滤器进行过滤。
所述的针式过滤器的孔径大小为0.22μm。
步骤(ii)中所述的离心的条件均为：8000rpm离心10分钟。
步骤(ii)中所述的超滤离心管的孔径大小为3000Da。
步骤(ii)中所述的透析为采用截留分子量为100～500Da的透析袋进行透析。
步骤(ii)中所述的透析的条件为：以去离子水为透析液透析24h。
步骤(2)中所述的挤压的温度优选为40±2℃。
步骤(2)中所述的挤压为在脂质体挤出仪中进行。
步骤(2)中所述的聚碳酸酯膜的孔径大小为200nm。
步骤(2)中所述的挤出的次数为21次以上。
步骤(2)中所述的透析为采用截留分子量为8000Da的透析膜进行透析。
步骤(2)中所述的透析的时间为24小时。
步骤(2)中所述的超声的条件为：100W超声40～60min；优选为：100W超声50min。
步骤S1和S4中所述的磷脂酶A2水溶液的用量为按其在所述反应体系的终浓度为10～200U/L添加；优选为按其在所述反应体系的终浓度为10、20、50、100和200U/L添加。
步骤S1、S3、S4和S7中所述的包封石墨烯量子点的纳米脂质体的用量为按其在所述反应体系的终浓度为0.029～0.058mg/ml添加计算；优选为按其在所述反应体系的终浓度为0.054mg/ml添加计算。
步骤S1、S3、S4和S7中所述的水浴反应的条件为：37℃水浴1小时。
步骤S1、S3、S4和S7中所述的3,3’,5,5’-四甲基联苯胺(TMB)为按其在所述反应体系的终浓度为0.5～0.6mmol/L添加计算；优选为按其在所述反应体系的终浓度为0.5mol/L添加计算。
步骤S1、S3、S4和S7中所述的H 2O 2为按其在所述反应体系的终浓度为0.1～0.2mM/L添加计算；优选为按其在所述反应体系的终浓度为0.1mM/L添加计算。
步骤S1、S3、S4和S7中所述的酸性溶液为酸性缓冲液；优选为醋酸-醋酸钠缓冲液；更优选为pH 3.8的醋酸-醋酸钠缓冲液。
步骤S1、S3、S4和S7中所述的继续反应的时间根据应溶液颜色变化，即由无色变成蓝色时终止；优选为15～30分钟；更优选为20分钟。
步骤S1和S3中所述的紫外吸收光谱的波长范围是500～800nm，选取吸光值的波长位置是652nm。
步骤(B)中所述的颜色分量平均值为颜色图像中划定区域内所有像素点各颜色分量除以像素点的个数作为这个区域的各颜色分量的平均值。
步骤S5中所述的位图格式中提取的颜色信息采用RGB(红绿蓝)、HSV(色调、饱和度、明度)、HSL(色调、饱和度、亮度)和CMYK(青-品红-黄-黑)中的任意一种表示；优选采用RGB(红绿蓝)蓝色分量表示；更优选为采用RGB(红绿蓝)中的蓝色(B)分量表示。
所述的基于比色原理检测磷脂酶A2的方法在检测磷脂酶A2(非疾病诊断目的)中的应用。
一种用于实现上述检测磷脂酶A2的方法的检测系统，所述的检测系统为基于智能手机检测系统，包括依次连接的图像采集模块，图像预处理模块，颜色分析模块和检测结果显示模块；
所述的图像采集模块包括手机自带摄像头、比色皿和黑匣子，用于获取标准溶液和待测溶液的颜色图像(即数码照片)；
所述的图像预处理模块为将获取的标准溶液和待测溶液的颜色图像转换为位图格式，以不同的颜色模型进行分析，用于获得标准溶液和待测溶液的颜色分量平均值；
所述的颜色分析模块为根据标准溶液的颜色分量平均值及其浓度绘制关系曲线；
所述的结果显示模块为待测溶液的颜色分量平均值和绘制的关系曲线，获得待测溶液的浓度和/或含量。
所述的比色皿优选为装有传感试剂的比色皿。
所述的传感试剂为3,3’,5,5’-四甲基联苯胺(TMB)、H 2O 2和酸性溶液。
所述的酸性溶液为酸性缓冲液；优选为醋酸-醋酸钠缓冲液；更优选为pH 3.8的醋酸-醋酸钠缓冲液。
所述的位图格式中的提取的颜色信息采用RGB(红绿蓝)、HSV(色调、饱和度、明度)、HSL(色调、饱和度、亮度)和CMYK(青-品红-黄-黑)中的任意一种表示；优选采用RGB(红绿蓝)蓝色分量表示；更优选为采用RGB(红绿蓝)中的蓝色(B)分量表示。
所述的颜色分量平均值为颜色图像中划定区域内所有像素点各颜色分量除以像素点的个数作为这个区域的各颜色分量的平均值。
本发明相对于现有技术具有如下的优点及效果：
(1)利用脂质体的包覆功能，将纳米探针与磷脂囊泡结合，提供生化检测传感的新型信 号放大策略。
(2)将待测物磷脂酶A2直接作为引起磷脂囊泡破裂的刺激因素，为环境刺激响应的智能仿生微囊泡的设计和构建新型智能仿生系统提供新思路。
(3)利用石墨烯量子点的纳米酶特性，即自身具有独特的类似天然过氧化物酶的催化活性，可替代天然酶用于显色反应。相比使用天然酶，石墨烯量子点具有成本低、易大量制造、便于存储且不易失活等优点。
(4)本发明通过磷脂酶A2特异性破解脂质体，从而释放其中包裹的石墨烯量子点。基于石墨烯量子点具有类天然酶催化活性，能够有效催化底物TMB氧化，伴随着溶液颜色由无色转化为蓝色，这一变化与磷脂酶A2的活性密切相关建立可视化检测磷脂酶A2的检测新原理。
(5)本发明利用智能手机进行图像采集和颜色分析，通过计算标准样品溶液在RGB颜色空间中各个分量的像素值，再通过最小二乘法拟合出磷脂酶A2检测的标准曲线，得到磷脂酶A2线性浓度和颜色分量像素值之间的对应关系；进而计算得出未知样品溶液中磷脂酶A2的浓度。从而实现磷脂酶A2的灵敏、准确、便捷和可视化的检测。
(6)本发明基于智能手机建立的磷脂酶A2检测传感平台，利用智能手机自身的高分辨率摄像头，通过设计手机应用软件对不同浓度试剂反应后的颜色信息进行处理，无需额外的设备和复杂的检测，就能实现对试剂浓度的快速检测。
(7)本发明将石墨烯量子点的类酶催化特性应用到疾病标志物的检测中，并开发智能手机在生物传感器领域用于疾病标志物检测的新应用。
(8)本发明所建立的基于智能手机的磷脂酶A2显色分析检测方法可适用于普遍的生物医学检测，对于医疗条件匮乏地区的医学检测具有巨大的应用价值和市场推广性。
附图说明
图1是本发明基于智能手机的磷脂酶A2的检测方法示意图。
图2是石墨烯量子点的表征图；其中，A为石墨烯量子点的扫描电镜照片；B为石墨烯量子点的原子力显微镜照片。
图3是不同激发波长下的石墨烯量子点发射光谱以及不同反应体系的紫外吸收光谱图；其中，A为在不同激发波长下的石墨烯量子点发射光谱图(插图为白光和365nm紫外光照射时石墨烯量子点溶液的图像)；B为不同反应体系的紫外吸收光谱图(图中：a为TMB+H 2O 2+GQD，b为TMB+H 2O 2，c为TMB+GQD，d为H 2O 2+GQD；插图照片为不同反应体系反应20分钟后的白光下拍摄图像)。
图4是石墨烯量子点与天然辣根过氧化物酶在不同pH条件下的催化活性比较图。
图5是石墨烯量子点与天然辣根过氧化物酶在不同温度条件下的催化活性比较图。
图6是脂质体的表征图；其中，A为脂质体的扫描电镜照片；B为脂质体的粒径分布情况(插图为白光照射时脂质体溶液图像)。
图7是磷脂酶A2活性引起的显色反应结果图；其中，A为不同活性浓度的磷脂酶A2使得脂质体破裂释放石墨烯量子点与TMB和H 2O 2反应后的紫外吸收光谱图；B为在652nm处的溶液吸光度随磷脂酶A2活性浓度变化的标准曲线。
图8是基于石墨烯量子点脂质体的磷脂酶A2显色检测的选择性实验结果。
图9是一种基于智能手机的磷脂酶A2的颜色检测系统图。
图10是智能手机对同一照片进行颜色检测分析后以不同颜色分量模型的显示界面图。
图11是不同活性浓度磷脂酶A2的图像的相应颜色模型的线性拟合结果图(磷脂酶A2的活性浓度分别为0，10，20，50，100，150，200，300U/L)；其中，A是RGB数值随磷脂酶A2活性浓度变化的拟合曲线；B是HSL数值随磷脂酶A2活性浓度变化的拟合曲线；C是HSV数值随磷脂酶A2活性浓度变化的拟合曲线；D是CMYK数值随磷脂酶A2活性浓度变化的拟合曲线。
图12是RGB颜色模型中B分量随磷脂酶A2活性浓度变化的标准曲线以及待测溶液中磷脂酶A2活性浓度的手机分析结果显示界面图；其中，A为RGB颜色模型中B分量随磷脂酶A2活性浓度变化的标准曲线；B为待测溶液中磷脂酶A2活性浓度的手机分析结果显示界面。
具体实施方式
下面结合实施例对本发明作进一步详细的描述，但本发明的实施方式不限于此。除非特别说明，本发明采用的试剂、方法和设备为本技术领域常规试剂、方法和设备。下列实施例中未注明具体实验条件的试验方法，通常按照常规实验条件或按照制造厂所建议的实验条件。除非特别说明，本发明所用试剂和原材料均可通过市售获得。
实施例1一种石墨烯量子点合成方法及其类过氧化物酶催化活性。
1.1石墨烯量子点合成
称取0.4g carbot vulcan XC-72碳黑(品牌：麦考林，购于广州普智生物科技有限公司)，加入到100mL 6mol/L的HNO3中，130℃(油浴)条件下搅拌回流反应24小时。然后将反应后的溶液冷却至室温，吸取上清液，加热除酸至pH为5～7，最终溶液体积为50mL，命名为溶液1。将得到的溶液1用滤纸(中速定性滤纸(速率102)，孔径为30～50微米，品牌：Biorad，北京百诺威生物科技有限公司)过滤两次，得到溶液2。再将溶液2用0.22μm的针式过滤器进行再次过滤，得到溶液3。将溶液3在8000rpm下离心10分钟，然后将上 清液吸取到超滤离心管(孔径大小为3000Da)中，得到溶液4。将溶液4在8000rpm下离心(10分钟)，基本将所有清液与沉淀分离，最后将分离得到的清液放入截留分子量为100～500Da的透析袋中，以去离子水为透析液，透析24h。透析结束后，将溶液加到离心管内，冻干处理后即为石墨烯量子点(GQD)。
石墨烯量子点的扫描电镜照片如图2A所示，原子力显微镜照片如图2B所示。石墨烯量子点在不同激发波长(荧光分光光度计，405、425、445、465、485、505、525nm)下的发射光谱，以及在白光和365nm紫外光照射下的石墨烯量子点溶液的图像如图3A所示。
1.2石墨烯量子点的催化活性
将1.1中合成的石墨烯量子点加入到含有过氧化氢(购于上海麦克林生化科技有限公司，纯度大于99％)和3,3’,5,5’-四甲基联苯胺(TMB，购于上海麦克林生化科技有限公司，纯度大于99％)的醋酸缓冲溶液(pH＝4)中，检测石墨烯量子点的催化活性；其中，反应体系中石墨烯量子点的浓度为0.004毫克/毫升，TMB的浓度为0.5mM，H 2O 2的浓度为0.1mM。
石墨烯量子点具有与天然过氧化物酶相似的催化活性，即在酸性环境下且过氧化氢存在条件下有效催化酶反应底物3,3’,5,5’-四甲基联苯胺(TMB)，使其发生氧化反应由无色反应物转变为蓝色产物。因此，当pH3.8的醋酸缓冲溶液中同时存在石墨烯量子点、TMB和过氧化氢时，反应体系的溶液颜色将有无色变为蓝色，图3B显示了不同反应体系反应20分钟后的紫外吸收光谱图(插图照片为不同反应体系反应20分钟后的白光下拍摄图像)。这一结果证明石墨烯量子点具有优异的类天然酶活性，可替代天然酶用于显色反应。
1.3石墨烯量子点的稳定性试验
1.3.1石墨烯量子点与天然辣根过氧化物酶在不同pH条件下的催化活性比较
石墨烯量子点作为纳米酶，自身具有与天然辣根过氧化物酶类似的催化活性，即催化过氧化氢还原生成水和氧气，同时催化其底物TMB氧化生成氧化态的TMB。本实验的目的在于比较石墨烯量子点与天然辣根过氧化物酶在不同pH条件下的催化活性，具体步骤如下：
将1.1中合成的石墨烯量子点和天然辣根过氧化物酶(150u/mg，购于上海麦克林生化科技有限公司)分别溶于0.5毫升不同pH(pH为2.0、3.0、4.0、5.0、6.0、7.0、8.0、9.0、10.0)缓冲溶液中，获得的含有石墨烯量子点的溶液的最终浓度均为20微克/毫升，含有天然辣根过氧化物酶的的溶液的最终浓度均为10纳克/毫升；其中所用缓冲液为：醋酸缓冲溶液(50mM，pH 2.0-pH 5.0)，磷酸缓冲溶液(50mM，pH6.0-7.0)以及Tris-盐酸缓冲溶液(50mM，pH8.0-10.0)。在室温下孵育4个小时后，再分别加入终浓度为0.6mmol/L 3,3’,5,5’-四甲基联苯胺(TMB，购于上海麦克林生化科技有限公司，纯度大于99％)溶液和1mM过氧化氢溶 液进行催化反应。
结果如图4所示：由图4的结果可知，石墨烯量子点与天然过氧化物酶分别在不同pH条件下经过4小时的孵育后，二者针对氧化还原反应的催化活性产生了巨大的差别。仅在适合于大部分生物物质保持其活性的适宜pH条件下如pH6-7时，天然辣根过氧化物酶具有良好的催化功能；当环境的pH在较高或较低数值时，天然辣根过氧化物酶的催化活性将受到严重的破坏，比如溶液的pH2或pH10时，过氧化物酶的催化活性大大降低了约60％。相比之下，纳米材料石墨烯量子点在较广的pH范围内能够维持良好的催化活性，在pH2到pH10这样的pH变化范围内，其催化功能未受明显影响，催化活性一直保持在约90％以上。这一结果说明相比于天然酶，石墨烯量子点在不同pH条件的外界环境下能够有效地维持其催化活性，不易受环境酸碱影响而失去催化活性，具有应用于更广泛检测条件的潜力。
1.3.2石墨烯量子点与天然辣根过氧化物酶在不同温度条件下的催化活性比较
本实验目的在于比较石墨烯量子点与天然辣根过氧化物酶在不同温度条件下的催化活性，具体步骤如下：将1.1中合成的石墨烯量子点和天然辣根过氧化物酶(150u/mg)分别溶于0.5毫升pH6的磷酸缓冲溶液(50mM)中，分别最终浓度分别为20微克/毫升和10纳克/毫升，在不同温度(4、15、25、30、35、40、45、50、60、70、80、90、100℃)下孵育4个小时后，再分别加入终浓度为0.6mmol/LTMB溶液和1mM过氧化氢溶液进行催化反应。
结果如图5所示：由图5的结果可知，石墨烯量子点与天然过氧化物酶分别在不同温度条件下经过4小时的孵育后，二者针对氧化还原反应的催化活性产生了巨大的差别。天然辣根过氧化物酶是生物蛋白质，因此较高的环境温度容易致其失活。其催化活性随着温度高于40℃时发生剧烈的降低，当环境温度为70℃以上时，天然辣根过氧化物酶的催化活性仅存20％到30％。相比之下，石墨烯量子点作为无机纳米材料具有很强的结构稳定性，其催化活性基本不受环境温度的改变而改变，在低温或高温条件下催化活性都保持在95％到100％之间。这一结果说明相比于天然酶，石墨烯量子点的催化活性受外界环境的温度影响较小，能够在温度较为极端的情况下使用。
通过以上环境pH和温度对于石墨烯量子点和天然过氧化物酶催化活性的影响实验，可以证明石墨烯量子点较天然酶不仅具有成本低，可大量制造的优点，而且具有优异的稳定性，便于保存和在酸碱或高温条件下使用，能够成为天然酶的替代物用于更广泛的用途。
实施例2一种包覆石墨烯量子点的脂质体的合成方法
卵磷脂和胆固醇以5：1(摩尔比，共43.2mmol，30mg)的比例混合，溶于4ml氯仿中，超声(功率100W)5分钟使其分散均匀。随后通过旋转蒸发器在40℃下、减压旋蒸1 小时以除去有机溶剂，烧瓶底部均匀的形成一层透明薄膜。此时加入2mL 0.1mg/ml的石墨烯量子点溶液(将实施例1制备石墨烯量子点溶于磷酸缓冲溶液(pH7.0)中)，冰浴超声(功率100W)50分钟，得到乳白色的浑浊液体。将其通过200nm的聚碳酸酯膜(即脂质体挤出仪使用的滤膜孔径为200nm)，反复挤压21次(40℃)。最后将得到的脂质体溶液用透析膜(截留分子量小于8000D)透析，以去离子水为透析液，透析24小时，移除未包封的石墨烯量子点，将获得的脂质体溶液储存在4℃下。
脂质体的扫描电镜结果如图6A所示，粒径分布情况如图6B所示(插图为白光照射时脂质体溶液图像)。从粒径分布和扫描电镜结果可知，本实施例制备的脂质体囊泡尺寸均匀，分散性好。
实施例3利用包覆石墨烯量子点的脂质体的特性检测磷脂酶A2的方法
本发明提供一种利用磷脂酶A2特异性破裂脂质体，释放其中包覆的石墨烯量子点，利用其类过氧化物酶的催化特性进行显色检测磷脂酶A2的方法。
3.1将4uL 13.6mg/mL的脂质体溶液(即实施例2制备的脂质体)用水稀释50倍，取195uL稀释后的脂质体，然后加入5uL不同活性浓度的磷脂酶A2在37℃下反应1h。然后加入785uL缓冲液(醋酸/醋酸钠缓冲液，0.1mol/L，pH＝3.8)，再加入10uL 50mM TMB溶液,然后加入5uL 20mM H 2O 2溶液，反应20分钟后(颜色变化为无色变成蓝色)，测量反应体系紫外吸收光谱；其中，反应体系中磷脂酶A2的终浓度分别为0、2、5、10、20、50、100、150、200、300U/L。
结果如图7所示：溶液在652nm处的吸光度随着磷脂酶A2活性浓度的增加而增加(图7A)；这一变化在磷脂酶A2的活性浓度在10到200U/L之间有良好的线性关系(图7B)。
3.2为验证该方法对于磷脂酶A2的检测具有单一性响应，采用不同类型的磷脂酶进行选择性实验。10uL 50U/L的磷脂酶C(PLC)，磷脂酶D(PLD)(磷脂酶C和磷脂酶D，品牌：源叶生物，均购自广州齐云生物科技有限公司)和磷脂酶A2(PLA2；品牌：源叶，上海源叶生物科技有限公司)溶液，分别与50倍稀释后的脂质体(即实施例2制备的脂质体)溶液200uL混合水浴1小时(37℃)，然后加入785uL缓冲液(醋酸/醋酸钠缓冲液，0.1mol/L，pH＝3.8)、TMB和H 2O 2反应20分钟(体系中H 2O 2和TMB最终浓度分别为0.1mM和0.5mM)，再测紫外吸收光谱。
结果如图8所示：磷脂酶C，磷脂酶D溶液混合水浴后的脂质体溶液，652nm处的紫外吸收峰值并没有明显变化，而与磷脂酶A2溶液混合水浴后的脂质体，652nm处的紫外吸收峰值显著升高，表面该方法对于检测磷脂酶A2具有良好的选择性。
实施例4基于手机的颜色分析检测系统和方法
4.1本发明中的检测所需硬件包括一个黑匣子(用于遮挡外部光源，可自制，暗箱或其他均可)、一个比色皿和一个智能手机；
本发明中的基于智能手机的检测系统包括依次连接的图像采集模块，图像预处理模块，颜色分析模块和检测结果显示模块；
所述的图像采集模块包括手机自带摄像头、比色皿和黑匣子；所述的比色皿装有传感试剂；将样品溶液加入到装有传感试剂的比色皿进行反应，反应完全后显色并置于黑匣子中，通过手机自带摄像头对比色皿中的溶液拍照，获取反应溶液的颜色图像(即数码照片)；所述的样品溶液包括已知浓度的标准溶液和未知浓度的待测溶液；除了直接调用手机摄像头实时拍照外，还可以采用其他方式(如相机等)获取反应溶液的颜色图像并存储于手机本地相册中，再进行后续操作；
所述的图像预处理模块为将获取的反应后的溶液的颜色图像转换为位图格式，以不同的颜色模型分析；基于智能手机的安卓系统，采用Java工具语言编写应用程序将图片位图格式中的像素信息转化为颜色信息，通常以红绿蓝(RGB)形式表示，RGB又可转换成其他对应的颜色模型，如色调饱和度明度(HSV)、色调饱和度亮度(HSL)和青-品红-黄-黑(CMYK)颜色模型，最终提取出对应的各颜色分量平均值(平均值是指兴趣区域所有点的各颜色RGB、HSV、HSL、CMYK平均值，就是所拍摄图像中划定区域内所有像素点各颜色分量都求出来，然后除以像素点的个数作为这个区域的各分量平均值)(形成多模式颜色检测分析系统)；在手机进行反应溶液的颜色检测时，调取拍摄的颜色图像后，分别点击RGB、HSV、HSL、CMYK虚拟按键，手机软件界面就会显示出该区域的各颜色模型分量参数(图10)，即可通过图像预处理模块获得反应后的标准溶液的颜色分量平均值(在RGB、HSV、HSL或CMYK颜色空间中各个分量的像素值)以及待测溶液的颜色分量平均值；
所述的颜色分析模块为根据标准溶液的颜色分量平均值及其浓度绘制关系曲线；
所述的结果显示模块为根据待测溶液的颜色分量平均值和绘制的关系曲线，计算得到待测溶液的浓度，也可以在进一步根据获得的待测溶液的浓度和体积，获得其含量；检测结果显示中调取图片的方式有两种，第一种是直接调用手机摄像头实时拍照，并对拍摄所得照片自动进行兴趣区的划定；第二种是调用手机本地相册中已有的图像手动进行兴趣区的划定；兴趣区图像加载到分析界面后(本实验采用的是第二种方式，分析照片时选用“file”)，计算得出图像的像素信息并进行浓度检测与显示。
4.2本发明中基于手机的颜色分析检测磷脂酶A2的分析方法的原理如图1所示，检测系 统如图9所示，其检测方法具体如下：
(1)配制至少五个浓度的磷脂酶A2水溶液并将其置于比色皿中，然后分别加入实施例2中制备的包覆石墨烯量子点的脂质体混合后水浴，再加入传感试剂3,3’,5,5’-四甲基联苯胺(TMB)、H 2O 2和酸性溶液(pH3.8的醋酸缓冲溶液)进行反应，待反应结束后通过图像采集模块获取反应溶液的颜色图像(即数码照片)；本实施例配制的反应体系中，磷脂酶A2的终浓度为10、20、50、100、150、200、300U/L；TMB的终浓度为0.5mM；H 2O 2的终浓度为0.1mM；包覆石墨烯量子点的脂质的终浓度为0.054mg/ml，所用酸性溶液为pH 3.8、0.1mol/L的醋酸/醋酸钠缓冲液；本实验的全部反应都在比色皿中进行，也具有先在试管、烧杯等容器中反应，等反应结束后再将其转入到比色皿中；
(2)根据步骤(1)中获取的反应溶液的颜色图像，通过图像预处理模块分别获取RGB、HSV、HSL以及CMYK颜色分量平均值；
(3)根据步骤(2)中获取的RGB、HSV、HSL以及CMYK颜色分量平均值与磷脂酶A2水溶液的浓度，通过颜色分析模块获得关系曲线；这里可与分光光度计测得的曲线进行比较，从中选出一个拟合度最高的关系曲线作为后续测试的标准曲线，内置于手机应用软件中；其中，分光光度计测得的曲线为通过如下方法获得：配制至少五个浓度的磷脂酶A2水溶液然后分别加入实施例2中制备的包覆石墨烯量子点的脂质体混合后水浴，再加入3,3’,5,5’-四甲基联苯胺(TMB)、H 2O 2和酸性溶液进行反应，待反应结束后用分光光度计分别测量其吸光值，再根据吸光值与与磷脂酶A2水溶液的浓度绘制曲线；其中，反应体系中各物质及其浓度与上述步骤(1)相同；
对已知不同活度浓度(10、20、50、100、150、200、300U/L)的磷脂酶A2与TMB和H 2O 2反应的显色溶液相对应的RGB、HSV、HSL、CMYK各颜色分量平均值的数据进行拟合比较，结果如图11所示；本发明衡量选取灵敏度和拟合度最好的RGB数据模型中的B分量拟合曲线(图12A)作为后续测试的内置标准曲线；
(4)向待测样品加入实施例2中制备的包覆石墨烯量子点的脂质体混合后水浴，再加入3,3’,5,5’-四甲基联苯胺(TMB)、H 2O 2和酸性溶液进行反应，待反应结束后通过图像采集模块和图像预处理模块测定反应后的待测溶液的颜色分量平均值，然后根据步骤(3)中的关系曲线，计算得到待测溶液中磷脂酶A2的浓度和/或含量；其中，反应体系中TMB、H 2O 2以及所用酸性溶液与上述步骤(1)相同；
未知磷脂酶A2活性浓度的溶液在进行显色后置于暗箱中用手机拍摄溶液图像后，应用软件将根据该图像的颜色分量平均值带入内置标准曲线进行颜色分析检测，手动在手机软件界面点击“浓度(Concentration)”虚拟按键，手机屏幕上将显示所获得的待测磷脂酶A2的活性浓度数值，操作如图12B所示。
上述实施例为本发明较佳的实施方式，但本发明的实施方式并不受上述实施例的限制，其他的任何未背离本发明的精神实质与原理下所作的改变、修饰、替代、组合、简化，均应为等效的置换方式，都包含在本发明的保护范围之内。

Claims (10)

  1. 一种基于比色原理检测磷脂酶A2的方法，其特征在于，为通过如下任一种方法实现：
    (A)基于显色法检测磷脂酶A2：
    S1、配制至少五个浓度的磷脂酶A2水溶液，然后分别加入包覆石墨烯量子点的脂质体混合后水浴反应，再加入3,3’,5,5’-四甲基联苯胺、H 2O 2和酸性溶液继续反应，待反应结束后测量紫外吸收光谱，得到吸光值；
    S2、根据步骤S1测量得到的吸光值与磷脂酶A2水溶液的浓度绘制标准曲线；
    S3、将待测样品与包覆石墨烯量子点的脂质体混合后水浴反应，然后加入3,3’,5,5’-四甲基联苯胺、H 2O 2和酸性溶液继续反应，待反应结束后测量紫外吸收光谱，得待测样品的吸光值；再根据步骤S2绘制的标准曲线获得待测样品中磷脂酶A2的浓度和/或含量；
    (B)基于智能手机检测系统检测磷脂酶A2：
    所述的基于智能手机检测系统包括依次连接的图像采集模块，图像预处理模块，颜色分析模块和检测结果显示模块；
    所述的图像采集模块包括手机自带摄像头、比色皿和黑匣子，用于获取标准溶液和待测溶液的颜色图像；
    所述的图像预处理模块为将获取的标准溶液和待测溶液的颜色图像转换为位图格式，以不同的颜色模型分析，用于获得标准溶液和待测溶液的颜色分量平均值；
    所述的颜色分析模块为根据标准溶液的颜色分量平均值及其浓度绘制关系曲线；
    所述的结果显示模块为待测溶液的颜色分量平均值和绘制的关系曲线，获得待测溶液的浓度和/或含量；
    所述的基于智能手机检测系统检测磷脂酶A2，通过如下步骤实现：
    S4、配制至少五个浓度的磷脂酶A2水溶液，然后分别加入包覆石墨烯量子点的脂质体混合后水浴反应，再加入3,3’,5,5’-四甲基联苯胺、H 2O 2和酸性溶液继续反应，待反应结束后用智能手机检测系统中的图像采集模块获取反应后的溶液的颜色图像；
    S5、将步骤S4中获取颜色图像通过智能手机检测系统中的图像预处理模块，分别获取其颜色分量平均值；
    S6、根据步骤S5中获取的颜色分量平均值和磷脂酶A2水溶液的浓度，通过智能手机检测系统中的颜色分析模块获得关系曲线；
    S7、将包覆石墨烯量子点的脂质体加入到待测样品中，混合后水浴反应，再加入3,3’,5,5’-四甲基联苯胺、H 2O 2和酸性溶液继续反应，待反应结束后通过智能手机检测系统中图像采集模块和图像预处理模块测定待测溶液的颜色分量平均值，然后根据步骤S6中的关系曲线，计 算得到待测溶液中磷脂酶A2的浓度和/或含量。
  2. 根据权利要求1所述的基于比色原理检测磷脂酶A2的方法，其特征在于，步骤S1、S3、S4和S7中所述的包覆石墨烯量子点的脂质体通过如下方法制备得到：
    (1)将卵磷脂与胆固醇加入到氯仿中，超声使其分散均匀，然后旋蒸除去氯仿，得到脂质体薄膜；
    (2)将石墨烯量子点溶液加入到脂质体薄膜中，冰浴超声分散均匀，得到混合溶液I；然后将混合溶液I通过聚碳酸酯膜反复挤压，得到混合溶液II；再将混合溶液II进行透析，得到包封石墨烯量子点的纳米脂质体；
    步骤(1)中所述的卵磷脂与胆固醇的摩尔比为1～5：1；
    步骤(2)中所述的石墨烯量子点与所述卵磷脂和胆固醇的总质量比为0.02～0.4:30；
    步骤(2)中所述的石墨烯量子点溶液为石墨烯量子点水溶液，或将石墨烯量子点溶于磷酸缓冲溶液得到的溶液；
    所述的石墨烯量子点溶液的浓度为0.01～0.2mg/mL。
  3. 根据权利要求2所述的基于比色原理检测磷脂酶A2的方法，其特征在于：
    步骤(2)中所述的石墨烯量子点通过如下方法制备得到：
    (i)将碳黑加入到浓硝酸溶液中，于130℃条件下搅拌回流反应，待反应结束后冷却至室温，吸取上清液，加热除酸至pH为5～7，得到溶液A；
    (ii)将溶液A过滤，取滤液；然后将滤液进行离心，取上清液；再将上清液加入到超滤离心管中，离心，取清液；最后将清液进行透析，待透析结束后，冷冻干燥，得到石墨烯量子点；
    步骤(i)中所述的碳黑为carbot vulcan XC-72碳黑；
    步骤(i)中所述的浓硝酸溶液的浓度5～8mol/L；
    步骤(i)中所述的回流反应为在油浴下进行回流反应；
    步骤(i)中所述的回流反应的时间为24小时；
    步骤(ii)中所述的过滤为依次用滤纸和针式过滤器进行过滤；
    所述的针式过滤器的孔径大小为0.22μm；
    步骤(ii)中所述的离心的条件均为：8000rpm离心10分钟；
    步骤(ii)中所述的超滤离心管的孔径大小为3000Da；
    步骤(ii)中所述的透析为采用截留分子量为100～500Da的透析袋进行透析；
    步骤(ii)中所述的透析的条件为：以去离子水为透析液透析24h。
  4. 根据权利要求2所述的基于比色原理检测磷脂酶A2的方法，其特征在于：
    步骤(1)中所述的超声的条件为：100W超声5～10min；
    步骤(1)中所述的旋蒸的条件为：40℃旋蒸15～60分钟；
    步骤(2)中所述的挤压的温度为40±2℃；
    步骤(2)中所述的挤压为在脂质体挤出仪中进行；
    步骤(2)中所述的聚碳酸酯膜的孔径大小为200nm；
    步骤(2)中所述的挤出的次数为21次以上；
    步骤(2)中所述的透析为采用截留分子量为8000Da的透析膜进行透析；
    步骤(2)中所述的透析的时间为24小时；
    步骤(2)中所述的超声的条件为：100W超声40～60min。
  5. 根据权利要求1所述的基于比色原理检测磷脂酶A2的方法，其特征在于：
    步骤S1和S4中所述的磷脂酶A2水溶液的用量为按其在所述反应体系的终浓度为10～200U/L添加；
    步骤S1、S3、S4和S7中所述的包封石墨烯量子点的纳米脂质体的用量为按其在所述反应体系的终浓度为0.029～0.058mg/ml添加计算；
    步骤S1、S3、S4和S7中所述的3,3’,5,5’-四甲基联苯胺为按其在所述反应体系的终浓度为0.5～0.6mmol/L添加计算；
    步骤S1、S3、S4和S7中所述的H 2O 2为按其在所述反应体系的终浓度为0.1～0.2mM/L添加计算；
    步骤S1、S3、S4和S7中所述的酸性溶液为酸性缓冲液；
    步骤S5中所述的位图格式中提取的颜色信息采用RGB、HSV、HSL和CMYK中的任意一种表示。
  6. 根据权利要求1所述的基于比色原理检测磷脂酶A2的方法，其特征在于：
    步骤S1和S4中所述的磷脂酶A2水溶液的用量为按其在所述反应体系的终浓度为10、20、50、100和200U/L添加；
    步骤S1、S3、S4和S7中所述的包封石墨烯量子点的纳米脂质体的用量为按其在所述反应体系的终浓度为0.054mg/ml添加计算；
    步骤S1、S3、S4和S7中所述的3,3’,5,5’-四甲基联苯胺为按其在所述反应体系的终浓度为0.5mmol/L添加计算；
    步骤S1、S3、S4和S7中所述的H 2O 2为按其在所述反应体系的终浓度为0.1mM/L添加计算；
    步骤S1、S3、S4和S7中所述的酸性溶液为pH 3.8的醋酸-醋酸钠缓冲液；
    步骤S5中所述的位图格式中提取的颜色信息采用采用RGB中的蓝色分量表示。
  7. 根据权利要求1所述的基于比色原理检测磷脂酶A2的方法，其特征在于：
    步骤S1、S3、S4和S7中所述的水浴反应的条件为：37℃水浴1小时；
    步骤S1、S3、S4和S7中所述的继续反应的时间为15～30分钟。
  8. 权利要求1～7任一项所述的基于比色原理检测磷脂酶A2的方法在非疾病诊断目的的检测磷脂酶A2中的应用。
  9. 一种用于实现权利要求1～7任一项所述的检测磷脂酶A2的方法的检测系统，其特征在于：所述的检测系统为基于智能手机检测系统，包括依次连接的图像采集模块，图像预处理模块，颜色分析模块和检测结果显示模块；
    所述的图像采集模块包括手机自带摄像头、比色皿和黑匣子，用于获取标准溶液和待测溶液的颜色图像；
    所述的图像预处理模块为将获取的标准溶液和待测溶液的颜色图像转换为位图格式，以不同的颜色模型进行分析，用于获得标准溶液和待测溶液的颜色分量平均值；
    所述的颜色分析模块为根据标准溶液的颜色分量平均值及其浓度绘制关系曲线；
    所述的结果显示模块为待测溶液的颜色分量平均值和绘制的关系曲线，获得待测溶液的浓度和/或含量。
  10. 根据权利要求9所述的系统，其特征在于：
    所述的位图格式中提取的颜色信息采用RGB、HSV、HSL和CMYK中的任意一种表示。
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