Protein molecular weight distribution detection method and detection system based on gel filtration technology and application thereof

Abstract

The invention discloses a protein molecular weight distribution detection method based on a gel filtration technology, and the method comprises the following steps: building a protein molecular weight detection technology platform based on the gel filtration technology, and detecting the characteristic peaks or characteristic sections and light absorption values of milk and dairy product proteins under a specific wavelength in real time; and designing and proposing an evaluation measure sigma / sigma 0, a section ratio and applicable conditions and ranges for calculating the molecular weight distribution of the protein, and detecting and analyzing the molecular weight distribution of the protein. The molecular weight distribution measure is designed to describe the concentration distribution and change of proteins with different molecular weights, so that the protein coagulation / degradation degree of the milk and the dairy products is evaluated, the quality of the milk and the dairy products is identified, and the dairy products and non-dairy products are distinguished. Establishment of the method is helpful for flexibly and conveniently evaluating and monitoring the quality of milk and dairy products in a plurality of application scenes such as storage and shelf life tracking.

Description

Technical Field

[0001] This invention belongs to the field of detection method technology, and relates to a protein molecular weight distribution detection method, detection system and its application based on gel filtration technology. Background Technology

[0002] Methods for protein acquisition and detection:

[0003] Protein is an extremely important high-molecular-weight organic compound in living organisms. It is a major component of human tissues and organs and a vital part of maintaining human life activities. Protein deficiency can lead to adverse health effects such as weakened immunity, decreased metabolism, and anemia. Humans primarily obtain protein through food, including meat, fish, eggs, and milk and dairy products. Among these, milk and dairy products have become a highly efficient source of high-quality protein in modern diets.

[0004] Milk and dairy products contain almost all the essential nutrients that promote human growth and development and maintain health, including proteins, fats, carbohydrates, minerals and vitamins. Among them, milk protein is the main nutrient, and high-quality complete milk protein has an amino acid composition similar to that of human milk. Its content is an important indicator for the current quality assessment of milk and dairy products.

[0005] Raw milk is an unstable complex system. In actual production, farms or factories typically use heat treatment and refrigeration to extend the shelf life of raw materials. Although heat treatment processes such as pasteurization, ultra-pasteurization, and ultra-high temperature sterilization effectively extend the shelf life of milk and dairy products (Yi Shengnan, Zhang Shuwen, Lu Jing 2020), quality defects such as gelation and bitterness caused by protein degradation and aggregation still affect its quality and shelf life (Wang Hui, Sun Qi, Liu Lu 2013). The main reasons for these phenomena include: First, raw milk, as a mixture, is an unstable system that continuously undergoes separation of the fat layer and protein layer, and aggregation of protein molecules, which heat treatment can accelerate (Li Linqiang, Tian Wanqiang, Zan Linsen 2011). Second, residual enzyme activity from raw milk and heat-resistant proteases produced by contaminating microorganisms continuously degrade milk proteins, affecting the quality of milk and dairy products. In addition, heat treatment processes can cause other effects besides protein molecule aggregation. For example, high temperatures can accelerate the production of furosine and cause Maillard reactions between proteins and reducing sugars in milk (Yi Shengnan, Lu Jing, Pang Xiaoyang 2021). In summary, multiple factors lead to quality defects in milk and dairy products during actual production, such as coagulation, whey separation, and bitterness, which seriously affect the quality and shelf life of milk and dairy products.

[0006] For the detection of protein content and types in milk and dairy products, the main current detection method in my country is the national standard "Determination of Protein in Food" (GB 5009.5). The Kjeldahl method and spectrophotometry in this standard can only determine total nitrogen content, have insufficient resolution, and are complex, time-consuming, and labor-intensive. In recent years, electrophoresis and enzyme-linked immunosorbent assay (ELISA) techniques have been gradually applied to the detection of protein types in milk and dairy products. Several industry standards now exist, such as "Determination of β-lactoglobulin in Milk and Dairy Products—Polyacrylamide Gel Electrophoresis" (NY / T 1663-2008) and "Determination of Bovine Immunoglobulin G in Exported Dairy Products—Enzyme-Linked Immunosorbent Assay" (SN / T 3132-2012). Based on this, researchers have employed a variety of equipment and physical, chemical, and biological detection methods to detect residual microorganisms, heat-resistant proteases, and related physicochemical indicators in milk and dairy products. These methods include: laser particle size analyzer, scanning electron microscope, HPLC-tandem mass spectrometry (Chen Xinxin, Lu Jing, Liu Lu 2018), SDS-PAGE and Native-PAGE gel electrophoresis, enzyme-antibody double-labeled colloidal gold technology (Li, Zhou et al. 2014), flow cytometry, infrared spectroscopy (Lv Yuan, Yin Yuanming, Tang Jiani 2009), and electronic eye, electronic nose, and electronic tongue (Song Huimin, Lu Jing, Lv Jiaping 2016).

[0007] While the above techniques can detect the content and composition of milk and dairy products to varying degrees, they still have significant limitations. For example, laser particle size analyzers track changes in the size and distribution of casein micelles, but are not suitable for detecting casein particles smaller than 0.22 μm and free monomeric whey proteins; HPLC-tandem mass spectrometry requires enzymatic digestion of large milk protein molecules or peptides into smaller molecules before detection, offering high precision but hindering the capture of global information on protein components; SDS-PAGE gel electrophoresis can visualize the distribution of different protein bands in milk and dairy products through staining, enabling qualitative and semi-quantitative analysis of proteins, but it cannot perform precise calculations and is only suitable as an auxiliary detection method; ELISA readers are mainly used to detect the content of specific biologically active enzymes (such as plasmin); flow cytometry is used to detect microorganisms in milk and dairy products. Furthermore, the equipment used in these techniques (especially HPLC-tandem mass spectrometry and flow cytometry) is relatively expensive, and they require highly skilled personnel and testing facilities, making them unsuitable for rapid detection in the actual production environment of the food manufacturing industry.

[0008] If a detection technology can achieve a balance between professionalism, accuracy, accessibility, and ease of operation, and analyze key signals or components directly related to quality in macromolecular colloidal solutions of milk and dairy products, and develop methods to track and detect changes in the molecular weight of proteins in milk and dairy products in real time, and develop a detection technology that can be easily and conveniently implemented in application scenarios in the food manufacturing industry, then it can be better applied to the quality assessment of milk and dairy products.

[0009] The principle and applicability of gel filtration technology:

[0010] Gel filtration (GF), also known as size exclusion gel chromatography, gel chromatography, and molecular sieve chromatography, originated in the 1960s. Its basic principle is to separate different components based on the varying degrees of inhibition caused by different gels due to their different molecular sizes (L. Nelson 2017). Specifically, the selected gel is a porous, non-surface-charged material that does not interact with the sample being analyzed. Based on this characteristic, a porous gel is used as a carrier (stationary phase) to separate substances according to their molecular weight. When protein molecules of different molecular weights pass through the carrier, protein molecules with a particle size larger than the carrier pore size flow directly out through the carrier gaps, while protein molecules with a particle size smaller than the carrier pore size enter the carrier particles. That is, the larger the protein molecular weight, the shorter the residence time within the carrier particles, and vice versa. This allows for the separation of components in a mixture according to their molecular weight. The separation range of a gel filtration carrier is determined by the pore size of the carrier.

[0011] As a chromatography technique, gel filtration is commonly used for the separation and purification of molecules in various fields, such as the preparation of pancreatic lipase inhibitory peptides derived from *Porphyra yezoensis* (patent number: CN202211041254.9) (Sun Lechang, Leng Meng, Cao Minjie 2022), and a method for the preparation and separation of metalloproteinases (patent number: CN202211112596.5) (Li Rongfeng, Li Pengcheng, Yu Huahua 2022). Gel filtration can also be applied to the detection and evaluation of changes in protein molecular weight. A 2016 report described a method for establishing a fingerprint of raw milk elution peaks on a specific gel column by measuring the peak position, peak height, and peak area of ​​all elution peaks in the gel filtration system. Principal component analysis (PCA) and other algorithms were then used to determine the presence of other impurities in the sample and to evaluate the quality of the milk (Gao.P 2016). It is worth noting that this analytical method relies on the global information of the elution peaks of raw milk, and the adopted PCA dimensionality reduction technique is based on feature extraction rather than feature selection. In other words, it cannot identify key components directly related to quality, resulting in poor interpretability. Furthermore, this analytical method does not focus on key information of markers directly related to milk quality and fails to fully utilize the ability of gel filtration technology to characterize system components. Summary of the Invention

[0012] To address the shortcomings of existing technologies, the present invention aims to provide a protein molecular weight distribution detection method based on gel filtration technology. By designing a molecular weight distribution measure, the method characterizes the concentration distribution and changes of proteins with different molecular weights, thereby assessing the degree of protein aggregation / degradation in milk and dairy products, identifying the quality of milk and dairy products, and distinguishing between dairy and non-dairy products.

[0013] This invention establishes a robust method for detecting protein molecular weight distribution based on gel filtration technology. Using this method, the molecular weight distribution of milk and dairy product proteins is calculated by real-time detection of characteristic peaks or regions and their absorbance values ​​at specific wavelengths. This allows for the assessment of the impact of conditions such as natural storage, heating, protease degradation, and psychrophilic bacterial infection on the quality of milk and dairy products. This invention facilitates flexible and convenient assessment and monitoring of milk and dairy product quality, as well as the differentiation between milk and non-dairy products, across multiple application scenarios including production, transportation, storage, and shelf life.

[0014] This invention selects gel filtration technology to analyze protein characteristic peaks or regions and their absorbance values, and further proposes a method for detecting protein molecular weight distribution based on gel filtration technology. The method specifically includes the following steps:

[0015] (1) A protein molecular weight detection technology platform was built based on gel filtration technology to detect the characteristic peaks or characteristic segments of milk and dairy product proteins at specific wavelengths and their absorbance values ​​in real time.

[0016] (2) Design and propose evaluation measures Σ / Σ0, segment proportion and applicable conditions and range for calculating the molecular weight distribution of proteins, and conduct detection and analysis of the molecular weight distribution of proteins.

[0017] The method described in this invention can be used for quality analysis of milk and / or dairy products.

[0018] In step (1) of this invention, the protein molecular weight detection technology platform built based on gel filtration technology includes the following:

[0019] (1.1) Select a carrier and determine the performance of the pre-packed column (referring to a self-packed gel column), including: column volume, number of plates, asymmetry factor and drop height, etc. The judgment of whether it is qualified or not is based on the carrier's instruction manual. For commercial columns, refer to their instruction manuals.

[0020] The carrier refers to a molecular sieve carrier with a fractionation range of 1kDa to 100kDa, 5kDa to 250kDa, and 10kDa to 1500kDa, respectively; preferably, the fractionation range of the carrier is 10kDa to 1500kDa.

[0021] The column volume is approximately 20–40 mL for rapid detection of intact proteins, preferably 30 mL; the column volume for separating single protein molecules is recommended to be greater than 70 mL, preferably 70–120 mL.

[0022] The number of trays, asymmetry factor, and tray drop height shall be determined according to the method specified in the instruction manual of the carrier used.

[0023] (1.2) Select the sample detection method, including sample processing method, mobile phase and flow rate;

[0024] The mobile phase used in the non-denaturing detection method is 50 mM Tris-HCl and 0.15 M NaCl, while the mobile phase used in the denaturing detection method is 0.5% SDS and 50 mM Tris-HCl.

[0025] The flow rate of the mobile phase is 0.5 to 1.5 mL / min; preferably, it is 1 mL / min.

[0026] The specific steps for selecting the sample detection method are as follows:

[0027] (1.2.1) Sample defatting: Centrifuge the sample at 10,000 to 15,000 rpm for 10 min at 4℃ to 8℃ to remove the upper lipid layer, and transfer the intermediate phase or all samples except the lipid layer to a new centrifuge tube.

[0028] (1.2.2) Process the defatted samples using non-denaturing or denaturing detection methods as needed;

[0029] (1.2.2.1) Non-denaturing detection method for whole milk protein: take defatted and homogenized milk and dairy products and dilute them 50 to 60 times. After dilution, filter them with a 0.22 μm or 0.45 μm microporous membrane. The higher the protein content of the sample, the higher the dilution factor.

[0030] (1.2.2.2) Non-denaturing detection method for milk protein single molecules and their polymers: Take defatted and homogenized milk and dairy products, add acid to adjust the pH to 4.6 for isoelectric point precipitation, centrifuge at 4℃~8℃ and 10000~15000rpm for 10min, and transfer the supernatant and precipitate to new centrifuge tubes and label them as acid supernatant or acid precipitate, thus completing the non-denaturing treatment.

[0031] (1.2.2.3) Method for detecting denaturation of single milk protein molecules: Take defatted and homogenized milk and dairy products, add acid to adjust the pH to 4.6 for isoelectric point precipitation, centrifuge at 4℃~8℃ and 10000~15000rpm for 10min, and transfer the supernatant and precipitate to new centrifuge tubes, labeled as acid supernatant or acid precipitate. Take the required volume and add 2% SDS and 2mM DTT to the final concentration, and make up the remaining volume with ddH2O. Incubate in a water bath at 60℃ for 30min to complete the denaturation treatment.

[0032] (1.2.3) Concentration calibration before gel filtration is divided into the same dilution factor or the same protein content;

[0033] (1.2.3.1) At the same dilution factor, the sample to be tested was centrifuged at 4℃~8℃ and 10000~15000rpm for 10min, and the intermediate phase was taken, diluted to the same factor and filtered through a 0.22μm or 0.45μm microporous membrane.

[0034] (1.2.3.2) For samples with the same protein content, after centrifugation at 4℃~8℃ and 10000~15000rpm for 10min, the intermediate phase was filtered through a 0.22μm or 0.45μm microporous membrane, the concentration of the filtered portion was determined, and the samples were uniformly diluted to the same concentration.

[0035] (1.2.4) Perform gel filtration, and select gel columns of different volumes as needed (preferably S300 gel columns);

[0036] (1.2.4.1) Non-denaturing method: Take 0.5% to 4% of the gel column volume of sample and pass it through the gel column. Use 50mM Tris-HCl and 0.15M NaCl as the mobile phase and the flow rate as 0.5 to 1.5 mL / min (preferably 1 mL / min). The sample volume passing through the column must exceed the volume of the gel column used. Compare and analyze the column peak chromatogram and the raw data. The raw data is obtained from the gel filtration system used and read and exported in real time.

[0037] (1.2.4.2) Denaturation method: Take 0.5% to 4% of the gel column volume of sample and pass it through the gel column. Use 0.5% SDS and 50mM Tris-HCl as the mobile phase and the flow rate is 0.5 to 1.5 mL / min (preferably 1 mL / min). The sample volume passing through the column must exceed the volume of the gel column used. Compare and analyze the column peak chromatogram and the original data.

[0038] The present invention further includes a pretreatment step before step (1.2.1): the milk and dairy product samples are processed according to their physical form. First, for liquid or gel samples, they are homogenized by stirring, shaking, or ultrasonication. Second, for solid samples, the protein content is accurately weighed, dissolved, and homogenized according to the percentage of protein, so that the protein content is greater than or equal to 2.8 g / 100 mL.

[0039] (1.3) Fit the formula for calculating the molecular weight of proteins in gel columns using protein standards:

[0040] The linear relationship between the protein molecular weight coefficient and the elution peak position is as follows: V = -klgM + b or lgM = -kV + b, where V represents the elution peak position (also called retention volume or elution volume) corresponding to the absorbance value, in mL, and M represents the relative molecular weight of the protein standard.

[0041] Each time a column is packed, the molecular weight calculation formula needs to be refitted using protein standards.

[0042] In one specific embodiment, the formula for calculating the molecular weight coefficient of the fitted gel column is: y = -4.2666x + 37.285, R 2 =0.9733

[0043] y represents the position of the elution peak of the unknown protein (V), and x represents the logarithm of the calculated relative molecular weight (lgM).

[0044] In step (2) of this invention, the evaluation measure Σ / Σ0=ΣM×mAU / ΣmAU

[0045] Wherein, “M” refers to the molecular weight of the protein, that is, M in the above formula V=-klogM+b, which can be calculated by the standard molecular weight formula and the position of the elution peak;

[0046] “mAU” refers to the absorbance value, which is read and exported in real time by the gel filtration system used;

[0047] “ΣmAU” is the sum of the absorbance values ​​at all points within a specified range, abbreviated as Σ0; where the starting position of the specified range is not less than the first elution peak of the protein, and the ending position is not greater than the elution position of the small molecule polypeptide or amino acid calculated by the molecular weight calculation formula.

[0048] “M×mAU” is the product of the molecular weight of the protein and its absorbance value within the specified range;

[0049] “ΣM×mAU” is the sum of M×mAU of the corresponding protein within the specified range, and is abbreviated as Σ.

[0050] In step (2) of the present invention, the percentage of the evaluation measurement segment is the percentage of the Σ0 of the feature segment to the Σ0 of the specified range;

[0051] The characteristic region refers to the interval from the start to the end of an elution peak, and / or the range of peaks of a protein or polypeptide from the start to the end of elution, calculated according to the protein molecular weight formula. In particular, the characteristic region is included within a specified range.

[0052] In one specific embodiment, step (1) of the present invention, which relies on gel filtration technology to build a protein molecular weight detection technology platform, mainly includes the following:

[0053] (1.1) Select a carrier and determine the performance of the pre-packed column (referring to a self-packed gel column), including: column volume, number of plates, asymmetry factor and drop height, etc. The judgment of whether it is qualified or not is based on the carrier's instruction manual. For commercial columns, refer to their instruction manuals.

[0054] The fractionation range of the carrier is 10 kDa to 1500 kDa.

[0055] The column volume is approximately 20–40 mL for the gel column used for rapid detection of intact proteins, preferably 30 mL; the column volume for the gel column used to separate single protein molecules is recommended to be more than 70 mL, preferably 70–120 mL.

[0056] The column efficiency, including the number of trays, asymmetry factor, and tray drop height, shall be based on the specifications of the carrier used.

[0057] The commercial columns are finished gel columns produced and verified by the manufacturer, requiring no additional carrier filling. The manufacturer provides basic information about the gel columns, including carrier, column height, column volume, number of plates, asymmetry factor, and plate drop height. The commercial columns also undergo relevant performance testing to verify the accuracy of the data provided by the manufacturer.

[0058] The gel filtration platform used in this invention can be domestically produced or imported.

[0059] (1.2) Select the sample detection method, including sample processing method, mobile phase and flow rate;

[0060] Taking milk as an example, the sample detection method includes two schemes. One scheme is a non-denaturing detection method to obtain the characteristic peaks or characteristic regions of whole milk protein or milk protein single molecules and their polymers in the natural state of the sample. The other scheme is a denaturing detection method to obtain the characteristic peaks or characteristic regions of milk protein single molecules. The pretreatment and sample defatting steps are the same for both schemes: (1.2.1) Pretreatment steps: The samples are processed according to their physical form. First, for liquid or gel samples, homogenization is carried out by stirring, shaking, or ultrasound. Second, for solid samples, the protein content is accurately weighed, dissolved, and homogenized according to its percentage, so that the protein content is greater than or equal to 2.8 g / 100 mL. (1.2.2) Sample defatting: After the pretreatment is completed, the sample is centrifuged at 4℃~8℃ and 10000~15000 rpm for 10 min to remove the upper lipid layer. The intermediate phase or all samples except the lipid layer are then aspirated into a new centrifuge tube as needed. (1.2.3) Process the defatted samples as needed using non-denaturing or denaturing detection methods: (1.2.3.1) For the non-denaturing detection method of whole milk protein, taking a sample with a protein content of approximately 3.0 g / 100 mL as an example, take defatted and homogenized milk and dairy products and dilute them 50 to 60 times. After dilution, filter the sample through a 0.22 μm or 0.45 μm microporous membrane. The higher the protein content of the sample, the higher the dilution factor should be. (1.2.3.2) For the non-denaturing detection method of milk protein single molecules and their polymers, take defatted and homogenized milk and dairy products, add acid to adjust the pH to 4.6, and perform isoelectric point precipitation at 4℃~8℃ and 10000~15000 rpm. Centrifuge at high speed for 10 min, and transfer the supernatant and precipitate to new centrifuge tubes, labeled as acid supernatant or acid precipitate, to complete the non-denaturing treatment; (1.2.3.3) Denaturation detection method for single milk protein molecules: Take defatted and homogenized milk and dairy products, add acid to adjust the pH to 4.6 for isoelectric point precipitation, centrifuge at high speed of 10 min at 10000-15000 rpm at 4℃~8℃, and transfer the supernatant and precipitate to new centrifuge tubes, labeled as acid supernatant or acid precipitate. Take the required volume and add SDS and DTT to a final concentration of 2% and 2 mM, and make up the remaining volume with ddH2O. Incubate in a water bath at 60℃ for 30 min to complete the denaturation treatment.(1.2.4) Concentration calibration before gel filtration is divided into the same dilution factor or the same protein content: (1.2.4.1) For the same dilution factor, the sample to be tested is centrifuged at 4℃~8℃ and 10000~15000rpm for 10min, and the intermediate phase is taken, diluted to the same factor, and filtered through a 0.22μm or 0.45μm microporous membrane; (1.2.4.2) For the same protein content, the sample to be tested is centrifuged at 4℃~8℃ and 10000~15000rpm for 10min, and the intermediate phase is filtered through a 0.22μm or 0.45μm microporous membrane, the concentration of the filtered portion is calibrated, and then uniformly diluted to the same concentration; (1.2.5) Gel filtration is performed, and different volumes of gel columns (preferably S300 gel columns) are selected as needed: (1.2.5.1) Non-denaturing method, 0.5%~4% of the sample volume of the gel column is passed through the gel column, and 50mM (1.2.5.2) Denaturation method: Take 0.5% to 4% of the gel column volume of sample and pass it through the gel column. Use 0.5% SDS and 50mM Tris-HCl as the mobile phase and the flow rate is 0.5% to 1.5mL / min (preferably 1mL / min). The sample volume passing through the column must exceed the volume of the gel column. Compare and analyze the column peak chromatogram and the original data.

[0061] (1.3) Fit the formula for calculating the molecular weight of proteins in gel columns using protein standards:

[0062] In gel filtration systems, for a specific length of gel column with a defined carrier, there is a one-to-one mapping between protein molecular weight and elution peak position. Therefore, the mapping between the molecular weight of a protein standard and its elution peak position can be fitted based on the measured elution peak positions of protein standards with different molecular weights.

[0063] This invention uses protein molecular weight standards. Each protein molecular weight is processed according to step (1.2), and the absorbance value at an A280nm wavelength is measured. The protein is accurately quantified and diluted to the same concentration, such as 2mg / mL. 500μL is taken for gel column testing to ensure that the injection volume of protein molecular weight standards for each gel column is not less than 100μg. The relationship between the elution peak position (V) and the protein molecular weight (M) is recorded and calculated.

[0064] The relationship between the protein molecular weight coefficient and the elution peak position is as follows: V = -klgM + b or lgM = -kV + b, where V represents the elution peak position corresponding to the absorbance value in mL, and M represents the relative molecular weight of the protein standard. Taking the non-denaturing method of protein standard processed by the non-denaturing method through an S300 column (23 mL column volume) as an example (see Table 1), according to the experimental data in Table 1, the fitting formula for the protein molecular weight coefficient is: y = -4.2666x + 37.285, R 2 =0.9733 (see Figure 16 Therefore, based on the elution peak position (V, i.e., y) of the unknown protein, the logarithm of the relative molecular weight (lgM, i.e., x) can be calculated, and from the formula, M = 10. (37.285 -y) / 0.4.2666 It is worth noting that the elution peak position of the standard will change with the volume of the gel column used. That is, each time the column is packed, the molecular weight calculation formula needs to be refitted with the protein standard, and the protein standard used to fit the formula must be processed in the same way as the sample to be tested.

[0065] Table 1. Protein molecular weight standards passed through an S300 column (23 mL column volume).

[0066] Protein molecular weight standards Molecular weight (kDa) lg(M) Elution peak position V (mL) Ferritin (horse spleen) 440 5.643 13.38 Aldolase (rabbit muscle) 158 5.199 15.27 β-galactosidase 116 5.064 15.226 Phosphatase B 97.2 4.988 16.193 BSA 66.4 4.822 16.61 Egg white protein 44.3 4.646 17.135 trypsin inhibitors 20.1 4.303 19.279

[0067] In one specific embodiment, in step (2) of the present invention, based on the principle of gel filtration, protein samples are eluted from the gel column in descending order of molecular weight. During the elution process, the gel filtration system measures, collects, and records the unit volume and absorbance value of the eluted protein molecules at a specific wavelength (generally A280nm wavelength) in real time, and plots a peak diagram of the unit volume and absorbance value. The product of the unit volume and the absorbance value represents the amount of protein in that unit volume. The sum of the protein amounts in all unit volumes of the sample is the total protein amount. The peak diagram clearly depicts the distribution relationship between the absorbance values ​​of proteins of different molecular weights and their unit volume. When the sample changes, the peak diagram also changes accordingly. Therefore, reasonable indicators reflecting the molecular weight distribution of proteins can be designed to quantitatively assess changes in the components of the protein complex system.

[0068] Based on this, the present invention proposes an assessment measure Σ / Σ0 and a segment proportion analysis method specifically for analyzing the overall situation of proteins.

[0069] Evaluation metric: Σ / Σ0

[0070] To comprehensively characterize the overall distribution of proteins of different molecular weights, this invention first introduces and defines the following measures:

[0071] "ΣM×mAU / ΣmAU" is the ratio of the sum of M×mAU of proteins within a specified range to the sum of absorbance values ​​at each point, abbreviated as Σ / Σ0. This value reflects the overall molecular weight level and molecular weight distribution of proteins in the sample. The smaller the value, the higher the degree of molecular weight variation and the higher the degree of protein particle decomposition.

[0072] Here, "M" refers to the molecular weight of the protein, which is the M in the above formula V=-klogM+b, and can be calculated by the standard molecular weight formula and the position of the elution peak.

[0073] “mAU” refers to the absorbance value, which is read and exported in real time by the gel filtration system used;

[0074] "ΣmAU" is the sum of absorbance values ​​at all points within a specified range, abbreviated as Σ0. The specified range begins at a position no less than the first elution peak of the protein and ends at a position no greater than the elution position of the small molecule peptide or amino acid calculated using the molecular weight formula. See the example calculation below. Figure 33 ;

[0075] “M×mAU” is the product of the molecular weight of the protein and the absorbance value within the specified range; where the starting position of the specified range is not less than the first elution peak of the protein and the ending position is not greater than the elution position of the small molecule polypeptide or amino acid calculated by the molecular weight calculation formula.

[0076] “ΣM×mAU” represents the sum of M×mAU values ​​for the corresponding proteins within a specified range, abbreviated as Σ. The specified range begins at a position no less than the first elution peak of the protein and ends at a position no greater than the elution position of the small polypeptide or amino acid calculated using the molecular weight formula. See the example calculation below. Figure 33 .

[0077] Assessment Measure: Segment Proportion

[0078] In this invention, the detection wavelength is 280 nm. Taking the non-denaturing column chromatography detection of whole milk protein in fresh milk on an S300 column (23 mL column volume) as an example, the elution peak range is 9 mL to 22 mL, with three characteristic segments: Segment 1 is the direct elution peak of molecular particles larger than the gel pore size, with a peak position range of 9 mL to 13.6 mL; Segment 2 is mainly the elution peak of casein particles, with a peak position range of 13.6 to 17.4 mL; Segment 3 is mainly the elution peak of whey protein and lactoglobulin, with a peak position range of 17.4 to 22 mL. (See [link to relevant documentation]). Figure 34The percentage of ΣmAU in each characteristic region of a sample relative to the total ΣmAU within the protein absorption peak range is used to determine the proportion of protein in that characteristic region within the total protein. The ratio of ΣmAU in each characteristic region to the total ΣmAU varies with the molecular weight of milk proteins. Therefore, milk quality can be assessed by detecting changes in the proportion of each region, a process known as region analysis.

[0079] The present invention also proposes the application of the method in the quality testing of milk and / or dairy products, and in the identification of dairy products and non-dairy products.

[0080] Based on the above methods, the present invention also proposes a detection system, comprising: a memory and a processor; the memory stores a computer program, and when the computer program is executed by the processor, the method described in the present invention is implemented.

[0081] While the resolution of the gel filtration technology mentioned in this invention is not as high as that of HPLC, it allows for the observation of the overall molecular weight distribution of the analyzed sample when used for the detection of protein complex systems. Compared with other methods such as ion exchange, gel filtration requires less sample concentration and uses smaller volumes. Compared with existing methods for detecting / evaluating milk and dairy products, the gel filtration technology used in this invention is safe, simple, and highly sensitive, capable of detecting microgram-level target protein molecules from trace volumes (tens to hundreds of microliters) of sample at high resolution, and detecting changes in protein molecular weight in real time based on the elution peak position. The gel filtration technology features a one-to-one correspondence between molecular weight and migration time, and is simple and safe to operate, achieving a good balance between detection accuracy and technical accessibility. Therefore, using gel filtration technology to detect changes in the molecular weight of proteins in milk and dairy products, and subsequently evaluating the quality of milk and dairy products, is a reliable and feasible technical route.

[0082] The beneficial effects of this invention include: the establishment of the method of this invention helps to flexibly and conveniently carry out the evaluation and monitoring of the quality of milk and dairy products in multiple application scenarios such as storage and shelf-life tracking. Attached Figure Description

[0083] Figure 1 This is a simplified flowchart of the experimental procedure for detecting milk proteins based on gel filtration technology.

[0084] Figure 2 The peak chromatogram of a short column packed with S200 support was determined using 1% acetone.

[0085] Figure 3 The peak chromatogram of a short column packed with S300 support was determined using 1% acetone.

[0086] Figure 4 The peak chromatogram of CL-4B carrier packed with short column was determined using 1% acetone.

[0087] Figure 5 S100 column efficiency peak diagram - 1% acetone.

[0088] Figure 6 S200 column efficiency peak diagram - 1% acetone.

[0089] Figure 7 S300 column efficiency peak diagram - 1% acetone.

[0090] Figure 8 The elution peak position of κ-casein standard on an S100 long column.

[0091] Figure 9 The elution peak position of κ-casein standard on an S200 long column.

[0092] Figure 10 The position of the elution peak of κ-casein standard on an S300 long column.

[0093] Figure 11 The peak diagram for detecting casein acid precipitation on an S100 long column.

[0094] Figure 12 The peak diagram for detecting casein acid precipitation using an S200 long column.

[0095] Figure 13 The peak diagram for detecting casein acid precipitation using an S300 long column.

[0096] Figure 14 The peak height of BSA standards with concentrations of 1 μg to 10 μg eluted through an S300 short column.

[0097] Figure 15 This is a linear relationship curve between the total amount of BSA standard loaded onto the column and the peak height of the elution peak.

[0098] Figure 16 This invention demonstrates the linear relationship between the molecular weight coefficient of proteins and the position of elution peaks in the S300 gel column.

[0099] Figure 17 Peak diagram of three segments for raw milk diluted 50 times.

[0100] Figure 18 The column graph shows the peaks of freshly ground soybean milk diluted 50 times.

[0101] Figure 19 The column graph shows the peaks of Vitasoy diluted 50 times.

[0102] Figure 20 The column chart shows the peaks after diluting coconut milk 15 times.

[0103] Figure 21 A peak graph of commercially available Russian infant formula.

[0104] Figure 22This is a peak graph of milk powder used by Want Want Group.

[0105] Figure 23 Acid supernatant peak chromatograms of normal / abnormal samples of raw milk, UHT milk and Want Want milk were obtained using an S300 long column (84 mL).

[0106] Figure 24 Acid precipitation peak diagrams for normal / abnormal samples of raw milk, UHT milk and Want Want milk were obtained using an S300 long column (84 mL).

[0107] Figure 25 The relationship between Σ0 and time when raw milk is placed at 4℃.

[0108] Figure 26 The results for milk self-coagulation at 4℃ (Σ0) and time data before (left) and after (right) correction; Section 1: blue diamond icon, Section 2: brown square icon, Section 3: gray triangle icon.

[0109] Figure 27 The results of the three-stage heating of raw milk for 30 minutes were compared.

[0110] Figure 28 Comparison of peaks for proteinase K degradation at 37℃ for 1 hour at 5 μg / mL (left) and 5 ng / mL (right).

[0111] Figure 29 The growth curves of Listeria monocytogenes cultured at 4℃, 20℃, 30℃ and 37℃ are shown for this invention.

[0112] Figure 30 Acid washing and peak removal chromatograms of normal / abnormal samples from March to June were obtained using an S300 long column (81 mL).

[0113] Figure 31 The percentage of acid supernatant from three batches of normal and abnormal samples in segments 1 and 2 from March to June.

[0114] Figure 32 A peak diagram of acid precipitation elution in normal / abnormal samples from March to June was obtained using an S300 long column (81 mL).

[0115] Figure 33 This is an example of Σ / Σ0 calculation in this invention.

[0116] Figure 34 This is a diagram of the three segments of the protein sample of this invention. Detailed Implementation

[0117] The present invention will be further described in detail below with reference to the specific embodiments and accompanying drawings. Except for the contents specifically mentioned below, the processes, conditions, and experimental methods for implementing the present invention are all common knowledge and general knowledge in the art, and the present invention does not have any particular limitations.

[0118] This invention utilizes data collected and recorded from self-packed S300 gel columns to optimize mobile phase and sample processing methods, design evaluation measures, and assess and test changes in protein molecular weight in samples such as milk under different factors and application scenarios. First, this invention verifies that the fractional elution method can clearly distinguish between dairy and non-dairy products, comparing the elution peaks of non-dairy, dairy, and reconstituted milk on a short S300 column using raw milk elution peaks as a control. Second, it verifies the changes in protein molecular weight during the self-coagulation process of raw milk proteins at 4°C, and extends the simulation to include the effects of heating, proteinase K simulating exogenous heat-resistant proteases, and Listeria monocytogenes simulating psychrophilic bacteria on milk proteins. Finally, it supplements the analysis with real spoiled samples as controls to examine the changes in the molecular weight of milk proteins and their polymers behind the milk phase transition.

[0119] The main components of milk protein are casein and whey protein. Casein accounts for 80%–82% of the protein, with a molecular weight of 57–375 kDa. There are four main types: α-casein, β-casein, β-whey protein, and β-whey protein. s1 -Casein, α s2 Casein, β-casein, and κ-casein have molecular weights of 23614 Da, 25230 Da, 23983 Da, and 19023 Da, respectively. Whey protein content is 18%–20%, mainly consisting of β-lactoglobulin, α-lactalbumin, and serum albumin, with molecular weights of 18277 Da, 14175 Da, and 66276 Da, respectively. In milk, casein binds to some whey proteins through hydrophobic interactions, hydrogen bonds, and ionic bonds to form larger aggregates of micelles. It also binds to soluble calcium ions to form calcium caseinate-calcium phosphate complex particles, with diameters up to 800 nm. Casein has an isoelectric point of 4.6. Utilizing the principle of lowest solubility at the isoelectric point, adjusting the pH of milk to 4.6 causes casein to precipitate, leaving whey protein in the supernatant. In gel filtration, proteins flow out in order of molecular weight, with larger casein complex particles flowing out first, followed by smaller whey protein particles, thus allowing for differentiation and identification.

[0120] Example 1: Establishment of a method for detecting protein molecular weight distribution based on gel filtration technology

[0121] 1. Experimental operation procedures adopted in this invention

[0122] This invention uses milk and dairy products as test samples, with absorbance at A280nm as the unit of concentration calibration, and a gel filtration platform as the detection platform. Pure 25 designed a simplified experimental procedure diagram for detecting milk proteins based on molecular weight changes, see [link to diagram]. Figure 1 .

[0123] 1.1 Sample Packaging and Visual Inspection

[0124] 1.1.1 Sample Packaging

[0125] Milk and dairy products are processed and packaged in a clean bench or biosafety cabinet.

[0126] Liquid dairy products: According to experimental requirements, dispense the liquid milk into sterile centrifuge tubes of 2mL, 15mL or 50mL, label the dispensing time and volume, and freeze at -20℃ or -80℃.

[0127] Thick dairy products: Weigh a certain amount of thick dairy products (e.g., 10g, 20g or 50g) according to experimental requirements, dispense them into sterile centrifuge tubes of equal volume (15mL or 50mL), mark the dispensing time and weight, and freeze at -20℃ or -80℃.

[0128] Powdered dairy products: Weigh a certain amount of powder (e.g., 10g, 20g or 50g) according to experimental requirements, dispense it into sterile sealed bags, mark the dispensing time and weight, and freeze at -20℃ or -80℃.

[0129] 1.1.2 Sensory observation

[0130] Normal liquid emulsion: Dispense 5-10 mL of liquid emulsion into a 15 mL colorless transparent centrifuge tube, invert and mix well. The liquid emulsion should be homogeneous, have good fluidity, no stratification, and no obvious flocculent or particulate sediment on the tube wall.

[0131] Abnormal liquid milk: Various factors during production or storage (bacterial contamination, thermostable enzyme degradation, abnormal raw milk, etc.) cause the liquid milk to exhibit an abnormal state such as colloidal particles (precipitation) or stratification under its natural state. It is clearly stratified when centrifuged at high speed. Its sensory characteristics include, but are not limited to: when dispensed into transparent centrifuge tubes, different degrees of flocculated particles may appear on the tube walls when the tubes are slightly inverted; water-emulsion stratification occurs when centrifuged at high speed, with a relatively clear aqueous phase on top and milk protein precipitation on the bottom.

[0132] 1.2 Sample Preparation

[0133] 1.2.1 Sampling

[0134] 1.2.1.1 Liquid dairy products

[0135] In a clean bench, after homogenizing the sample, use a pipette to take the required volume, such as 1 mL of liquid emulsion into a 1.5 mL centrifuge tube, and keep it on ice for later use.

[0136] 1.2.1.2 Dissolving and preparing viscous colloidal dairy products or solid milk powder

[0137] Based on the protein content in the ingredient lists of viscous dairy products and solid milk powder, calculate the mass of viscous dairy products and solid milk powder needed to prepare 100mL of liquid milk, so that the protein content in the dissolved solid milk powder is between 2.8g and 3.5g / 100g.

[0138] In a clean bench, weigh the required viscous dairy product or solid milk powder into a beaker using an electronic balance, add sufficient ultrapure water, and dissolve it by magnetic stirring at 65°C with a stirring frequency of 500 rpm until it is completely dissolved and there are no particulate or flocculent precipitates. Finally, bring the volume up to 100 mL.

[0139] The dissolved liquid emulsion can be aliquoted into centrifuge tubes of 2mL, 15mL or 50mL and stored at -20℃ or -80℃.

[0140] In a clean bench, homogenize the prepared sample again, and use a pipette to take the required volume, such as 1 mL of liquid, into a 1.5 mL centrifuge tube, and keep it on ice for later use.

[0141] 1.2.2 Sample degreasing

[0142] 1.2.2.1 Normal liquid dairy products

[0143] High-speed centrifugation: Centrifuge the prepared sample on ice at high speed (4℃, 10000rpm for 10min). At this time, the liquid milk is mainly divided into two layers. The upper layer is milk fat, which is colloidal (fresh milk), blocky (UHT milk), or has a thin milk fat layer (skim milk or other types of modified milk); the lower layer is milk protein, which is generally milky white (there may be a small amount of solid insoluble matter at the bottom).

[0144] Collecting milk protein: Remove the top layer of milk fat and use a 1 mL pipette to transfer the middle layer of milk protein into a new 1.5 mL centrifuge tube; (Note: Avoid inserting the pipette into the bottom of the test tube to aspirate solid insoluble matter).

[0145] 1.2.2.2 Abnormal liquid dairy products

[0146] High-speed centrifugation: The prepared sample was centrifuged at high speed (4℃, 10000 rpm for 10 min) on ice. At this time, the liquid milk mainly consists of three layers: the upper layer is milk fat, which is colloidal (fresh milk), blocky (UHT milk), or has a thin milk fat layer (skim milk or other types of modified milk); the middle layer may be milk protein or a relatively clear solution; the bottom layer consists of a large amount of milk protein precipitate and insoluble solids.

[0147] Collect the milk protein precipitate: Remove the top layer of milk fat and use a pipette to transfer all the middle and bottom layers of milk protein precipitate into a new 1.5 mL centrifuge tube (Note: Mix the undissolved milk protein precipitate at the bottom with a pipette before transferring).

[0148] 1.2.3 Preparation of defatted whole milk protein samples or single-molecule separation of milk proteins after acid precipitation

[0149] 1.2.3.1 Preparation of defatted normal whole milk protein samples or single-molecule separation of milk proteins after acid precipitation

[0150] Preparation of defatted normal whole milk protein sample: Homogenize the defatted sample again and take the required volume for the experiment.

[0151] After acid precipitation of normal defatted samples, single-molecule separation of milk proteins is performed: The normal defatted samples are homogenized again and thoroughly mixed. Then, the required volume (usually about 1.6 mL in a 2 mL centrifuge tube) of sample is added to concentrated hydrochloric acid (4.8 μL of concentrated hydrochloric acid is added to 1 mL of sample) for thorough isoelectric point precipitation (referred to as acid precipitation). The samples are centrifuged at 4℃ and 12000 rpm for 10 min. The supernatant and precipitate are then transferred to new centrifuge tubes (the precipitate is mixed with the same volume of 50 mM Tris-HCl and 0.15 M NaCl until no obvious large particles are visible). These are labeled as acid supernatant or acid precipitate and are kept for later use.

[0152] During this process, some fat may remain that was not completely removed during defatting. These should be removed as much as possible to avoid affecting subsequent operations.

[0153] 1.2.3.2 Preparation of abnormally defatted whole milk protein samples or single-molecule separation of milk proteins after acid precipitation

[0154] Preparation of abnormal defatted whole milk protein samples: Homogenize the abnormal defatted sample again, and after thorough mixing, take an appropriate amount of sample into a centrifuge tube (generally use a 2mL centrifuge tube, take about 1.6mL), and centrifuge at 4℃ and 12000rpm for 10min. If obvious stratification occurs, transfer the upper layer to a new centrifuge tube for later use. Add the same volume of 50mM Tris-HCl and 0.15M NaCl solution to the remaining lower layer and mix until no obvious large particles are visible. Label this as the aqueous phase (upper layer) or the emulsion phase (lower layer) for later use. If no obvious stratification occurs after high-speed centrifugation, use the entire sample for later use.

[0155] Single-molecule separation of milk protein after abnormal defatting acid precipitation: The abnormal defatting sample is homogenized again and thoroughly mixed. A certain amount of sample (generally about 1.6 mL in a 2 mL centrifuge tube) is taken and concentrated hydrochloric acid is added (4.8 μL of concentrated hydrochloric acid is added to 1 mL of sample) to carry out sufficient isoelectric point precipitation (referred to as acid precipitation). Centrifuge at 4℃ and 12000 rpm for 10 min. Transfer the supernatant to a new centrifuge tube and label it as acid supernatant. The precipitate at the bottom of the original centrifuge tube is mixed with the same volume of 50 mM Tris-HCl and 0.15 M NaCl solution until there are no obvious large particles. This is labeled as acid precipitate and used for later use.

[0156] (Note: There may be some fat that was not completely removed during the defatting process. Please remove it as much as possible to avoid affecting subsequent operations.)

[0157] 1.2.4 Sample non-denaturation / denaturation treatment and concentration calibration

[0158] 1.2.4.1 Sample non-denaturing treatment and concentration calibration

[0159] Non-denaturing processing: After completing steps 1, 2, and 3 above, the non-denaturing processing is complete;

[0160] After non-denaturing treatment, dilute to the same dilution factor: Since the test sample may still contain fat or insoluble matter that may clog the filter membrane, it is recommended to take the intermediate phase for dilution after high-speed centrifugation. Dilute the test sample to the same dilution factor, take the required volume for filtration (0.22μm or 0.45μm filter membrane), and then proceed with subsequent detection.

[0161] Non-denaturing treatment followed by dilution to the same protein content: Since the sample may still contain fat or insoluble matter that could affect concentration determination and clog the filter membrane, it is recommended to centrifuge at high speed and then take the intermediate phase for concentration calibration. Filter the required volume of intermediate phase (using a 0.22 μm or 0.45 μm filter membrane), and then take a certain volume of the filtered portion to determine the A280 value (note that the optimal A280 value is between 0.2 and 0.8; dilution can be performed as needed). Convert and record this value as the A280 value of the filtered original sample solution (unit: A280 / mL). Use the filtered A280 value as the standard to adjust to the same protein content.

[0162] 1.2.4.2 Sample denaturation method and concentration calibration

[0163] Denaturation treatment: After completing 1.2.3, take the required volume of the sample to be tested, add SDS to a final concentration of 2% and DTT to 2mM, make up the remaining volume with ddH2O, and incubate in a 60℃ water bath for 30min to complete the denaturation treatment.

[0164] After denaturation treatment, dilute to the same dilution factor: Since the test sample may still contain fat or insoluble matter that may clog the filter membrane, it is recommended to take the intermediate phase after high-speed centrifugation for dilution. Dilute the test sample to the same dilution factor, take the required volume for filtration (0.22μm or 0.45μm filter membrane), and then proceed with subsequent detection.

[0165] After denaturation treatment, dilute to the same protein content: Since the test sample may still contain fat or insoluble matter that may affect concentration calibration and clog the filter membrane, it is recommended to take the intermediate phase after high-speed centrifugation for concentration calibration before and after filtration. Filter the required volume of intermediate phase (using a 0.22μm or 0.45μm filter membrane), and then take a certain volume of the filtered portion to determine the A280 value (note that the optimal A280 value is between 0.2 and 0.8; dilution can be performed as needed). Convert and record the A280 value of the original test sample solution after filtration (unit: A280 / mL). Use the filtered A280 value as the standard to adjust to the same protein content.

[0166] 1.3 Sample loading detection based on gel filtration system

[0167] 1.3.1 Non-denaturing column chromatography test

[0168] Adjust the sample to the same dilution factor or the same protein content (e.g., 5A280 / mL), take 500 μL and pass it through an S300 column (the column volume depends on the detection requirements), use 50 mM Tris-HCl and 0.15 M NaCl as the mobile phase, and a flow rate of 1 mL / min to obtain the column peak chromatogram and raw data for subsequent analysis.

[0169] 1.3.2 Denaturation Method for Column Detection

[0170] Adjust the sample to the same dilution factor or the same protein content (e.g., 5A280 / mL), take 500 μL and pass it through an S300 long column with 0.5% SDS and 50 mM Tris-HCl as the mobile phase at a flow rate of 1 mL / min. Obtain the column peak chromatogram and raw data for subsequent analysis.

[0171] 1.4 Analysis of Sample Test Results

[0172] 1.4.1 Plotting and Analysis of Raw Data

[0173] The raw data of the sample to be tested were exported from the platform's supporting software. The raw data of the samples under the same processing conditions were plotted, with the elution volume (mL) as the x-axis and the A280 absorbance (mAU) as the y-axis, to compare and analyze the differences in peak shape, elution peak and absorbance between the samples.

[0174] 1.4.2 Σ / Σ0 analysis or segment proportion analysis

[0175] See “Step (2) of the present invention” above for details.

[0176] 2. Selection of gel filtration carrier and determination of sample dilution factor and protein content for passing through the gel column.

[0177] 2.1 Determining gel filtration column efficiency and identifying gel column carriers

[0178] GE After the pure 25 gel filtration platform was installed and set up in the laboratory, a relatively universal detection method was established through the exploration and adjustment of various technical parameters. This method mainly includes: selection of gel filtration carrier; detection of gel filtration column efficiency, including plate number, asymmetry factor (As), and plate drop height (h); detection of purity of protein molecular weight standards in gel columns and fitting of protein molecular weight calculation formula (M).

[0179] Research indicates that casein complex particles in milk proteins have a relatively large molecular weight, requiring gel filtration carriers with a wide separation range. Several suitable carriers are available, including the Superdex, Sephacryl, and Superose series. Based on our laboratory's existing Sepharose CL-4B carrier (fractionation range: 60–20000 kDa), Sephacryl S200 carrier (fractionation range: 5–250 kDa), and S300 carrier (fractionation range: 10–1500 kDa), these three carriers were packed into GE X16 / 20 short columns (16 mm inner diameter, 20 cm height). Following the carrier instructions, the number of plates, asymmetry factor, and column volume were determined using 1% acetone. Column efficiency data and peak diagrams are shown in Table 2 and [Table data would be inserted here]. Figures 2-4 The CL-4B peak shape was poor, so this gel column was discarded.

[0180] Table 2 Column efficiency parameters after loading with three different carriers.

[0181] carrier Number of trays / meter Asymmetry factor (As) Column volume / mL S200 5728.23 1.45 21.4 S300 8641.91 1.35 23.1 CL-4B 1560 2.12 20

[0182] Research and analysis indicate that κ-casein (κ-CN) and para-κ-casein (para-κ-CN) in milk and dairy products can be used to characterize the quality of raw milk. The relative molecular weights of target molecules such as κ-casein, its hydrolysis product para-κ-casein, and further hydrolysis products mainly range from 4 kDa to 19 kDa. Specifically, the relative molecular weight of κ-casein is 19023 Da, and that of para-κ-casein is 12316 Da (calculated based on the amino acid sequence of the primary structure of κ-casein in the Modern Dairy Industry Handbook). The molecular weight difference between κ-casein and para-κ-casein is approximately 7 kDa, suggesting that a longer gel column is needed for their separation. Therefore, this invention utilizes long columns packed with materials of different fractionation ranges to explore feasible methods for separating κ-casein and para-κ-casein. Sephacryl carrier series S100, S200 and S300 gel columns, which are more suitable for separating mixtures with small molecular weight differences, were packed with three different packing materials (Lishui Technology, specification GCC X15 / 600, unit mm).

[0183] Subsequently, using ultrapure water as the mobile phase and 1% acetone as the sample, at a flow rate of 1 mL / min and a wavelength of 280 nm, the column volume and column efficiency parameters were determined. The column efficiency parameters are shown in Table 3, and the peak chromatograms are shown in [Table 3]. Figures 5-7 According to the packing instructions, the median particle size (d50v) of these three packing materials is 50 μm. The evaluation indicators for gel column packing efficiency are the theoretical plate height (HETP, in cm) and the asymmetry factor (As), where As ranges from 0.8 to 1.8, with values ​​closer to 1 being better. Column performance is commonly compared using the concept of the reduced plate height (h, HETP / d50v) (reduced plate refers to lowering the structural elevation of a floor or roof slab, an architectural term); h < 3 indicates excellent column performance. Table 3 shows that the column volume of the three long columns is approximately 80 mL, the asymmetry factor is within the acceptable range, and the h value is less than 3, indicating good column efficiency, suitable for subsequent experiments.

[0184] Table 3. Fractionation range and column efficiency parameters of S100, S200 and S300 gel columns

[0185]

[0186]

[0187] To select a more suitable long column for the detection of κ-casein and its hydrolysis product, by-κ-casein, and further hydrolysis products in milk and dairy products, the elution range of protein standards, the elution peak position of κ-casein, and the elution peak of casein acid-precipitated samples were compared among three long columns. Experimental data showed that the S300 long column outperformed the S100 and S200 long columns and was suitable for the detection of target molecules in milk and dairy products. Details are as follows:

[0188] Based on the formula for calculating the protein molecular weight of S100, S200, and S300 long columns using protein standards, the effective elution range is defined as the distance from the breakout peak to the elution peak of the insulin standard (5733.49 Da). The optimal elution range for the filter columns is determined by the principle that a larger effective elution range results in better separation performance for samples of different molecular weights. Specifically, the effective elution range for the S100 long column is 33 mL to 46 mL (13 mL total), for the S200 long column it is 31 mL to 50 mL (17 mL total), and for the S300 long column it is 42 mL to 69 mL (27 mL total). The elution range of the S300 long column is larger than that of the S100 and S200 long columns.

[0189] Based on the formula for calculating the molecular weight of proteins, the theoretical elution peak positions of κ-casein standard (19023 Da) on S100, S200, and S300 long columns were 39.37 mL, 40.52 mL, and 59.38 mL, respectively. Experimental data showed that after denaturation treatment, the elution peak positions of κ-casein standard on S100, S200, and S300 long columns were 37.80 mL, 38.58 mL, and 59.21 mL, respectively. The experimental values ​​showed high consistency with the theoretical values ​​(see...). Figures 8-10 The calculation results show that the elution peak position of the κ-casein standard in the S100 long column differs from the breakout peak at 33 mL by 4.8 mL; in the S200 long column, the difference is 7.58 mL; and in the S300 long column, the difference is 17.38 mL. The distance between the elution peak and the breakout peak of the κ-casein standard in the S300 long column is greater than that in the S100 and S200 long columns.

[0190] Comparison of casein acid precipitation elution peaks after denaturation treatment with S100, S200, and S300 long columns (see...) Figures 11-13 Among them, the S100 and S200 long columns showed obvious tailing at the elution peak position at 40 mL, but failed to form an elution peak for κ-casein. The elution peak range of κ-casein in the S300 long column (50-60 mL) can form two independent elution peaks that do not interfere with each other with the breakthrough peak (35-45 mL).

[0191] In summary, based on the comparison of the effective elution range, the elution peak position of κ-casein standards, and the interval between the elution peak and the breakthrough peak of casein acid precipitation samples, the S300 long column outperforms the S100 and S200 columns and is more suitable for the detection and analysis of κ-casein and its further hydrolysis products in milk.

[0192] 2.2 Determine the dilution factor and protein content of the sample before passing it through the gel column.

[0193] 2.2.1 Samples of the same dilution factor passed through a gel column

[0194] Multiple standards for milk and dairy products require that the protein content of milk be greater than or equal to 2.8 g / 100 mL. When 500 μL of the stock solution is loaded onto a column, the theoretical protein mass in the sample should be greater than or equal to 14 mg. Milk treated with high-speed centrifugation was serially diluted 10-fold using the intermediate phase. UV spectrophotometer scans from 200 to 700 nm showed a maximum absorbance at 280 nm. The 10-fold dilution was too turbid to measure absorbance; at 100-fold dilution, the A280 absorbance was 2.014 (see Table 4). Since different protein components are separated after passing through the gel column, the elution volume increases, resulting in a lower signal value. However, the absorbance at 100-fold dilution was low; therefore, a 50-fold dilution was chosen before column chromatography to measure the A280 nm absorbance (see Table 4). The signal value was measured to be around 25-30 mAU, which is in line with expectations. It is recommended that when the protein content is greater than or equal to 2.8 g / 100 mL, the absorbance should be measured at A280 wavelength after at least 50-fold dilution.

[0195] Table 4. Results of A280 absorbance scans of milk protein at gradient dilutions.

[0196] Dilution <![CDATA[10 -4 ]]> <![CDATA[10 -3 ]]> <![CDATA[10 -2 ]]> <![CDATA[10 -1 ]]> A280nm reading (spectral scan) 0.007 0.182 2.014 turbid

[0197] 2.2.2 Determine the minimum detection threshold for gel filtration and the relationship between total volume loaded onto the column and elution peak height.

[0198] To clarify the lower limit of detection for gel filtration assays, this invention uses bovine serum albumin (BSA) as a protein standard and detects BSA standards of different concentrations using an S300 short column. Figure 14 As shown, when the total amount of BSA loaded onto the column was 1 μg and 2.5 μg, no obvious elution peak was observed; when the total amount loaded was 5 μg, a slightly raised elution peak was visible; and when the total amount loaded was 10 μg, an obvious elution peak was observed. Therefore, when detecting samples with the same protein content by column chromatography, the content should not be less than 5 μg.

[0199] The total amount of BSA standard loaded onto the column was set to range from 5 μg to 500 μg. The absorbance values ​​of the elution peak of the BSA standard were statistically analyzed, and the results are shown in Table 5. Figure 15 As shown, with the total amount of BSA loaded onto the column as the abscissa and the absorbance of its elution peak as the ordinate, a linear curve is fitted to the total amount loaded onto the column and the absorbance of the elution peak. The absorbance of the elution peak of the BSA standard is linearly related to the total amount loaded onto the column.

[0200] Table 5. Peak heights of BSA standards at concentrations of 5 μg to 5000 μg eluted through an S300 short column.

[0201] BSA (μg) Mean position mL Average peak height mAU 5 16.09 0.09 10 16.16 0.26 25 15.99 0.88 50 16.11 1.70 100 16.22 3.37 250 16.44 8.63 500 16.43 17.42

[0202] 3. Fitting the formula for calculating the molecular weight of proteins using gel column chromatography

[0203] Gel filter column carriers are porous gels with a specific pore size range. Proteins of different molecular weights in solution elute at different rates and have different elution peak positions in the gel filter column. For the same carrier, the column volume changes each time the gel column is packed, and the elution peak position of the same protein changes accordingly. To analyze data obtained from gel columns of different volumes, protein standards of different molecular weights need to be passed through gel columns of different volumes, the specific elution peak position of the protein standard needs to be determined, and a formula relating the elution peak to the molecular weight of the protein standard needs to be fitted.

[0204] Multiple protein molecular weight standards were selected, and each protein molecular weight was processed according to the experimental operation procedure adopted in this invention (1). The absorbance value at an A280nm wavelength was measured, and the protein was accurately quantified and diluted to the same concentration, such as 2 mg / mL. 500 μL of the protein molecular weight standard was passed through a gel column for testing, ensuring that the injection volume of the protein molecular weight standard for each gel column was not less than 100 μg. The relationship between the elution peak position (V) and the protein molecular weight (M) was recorded and calculated. The linear relationship between the protein molecular weight coefficient and the elution peak position is as follows: V = -klgM + b or lgM = -kV + b, where V represents the elution peak position corresponding to the absorbance value in mL, and M represents the relative molecular weight of the protein standard. Taking the non-denaturing method of passing the protein standard through an S300 column (23 mL column volume) as an example (see Table 6), according to the experimental data in Table 6, the fitting formula for the protein molecular weight coefficient is: y = -4.2666x + 37.285, R 2 =0.9733 (see Figure 16 Therefore, based on the elution peak position (V, i.e., y) of the unknown protein, the logarithm of the relative molecular weight (lgM, i.e., x) can be calculated, and from the formula, M = 10. (37.285-y) / 0.4.2666 .

[0205] It is worth noting that the elution peak position of the standard will change with the volume of the gel column used. That is, each time the column is packed, the molecular weight calculation formula needs to be refitted with the protein standard, and the protein standard used to fit the formula must be processed in the same way as the sample to be tested.

[0206] Table 6. Relative molecular weights and elution peak positions of protein molecular weight standards

[0207] Protein molecular weight standards Molecular weight (kDa) lg(M) Elution peak position V (mL) Ferritin (horse spleen) 440 5.643 13.38 Aldolase (rabbit muscle) 158 5.199 15.27 β-galactosidase 116 5.064 15.226 Phosphatase B 97.2 4.988 16.193 BSA 66.4 4.822 16.61 Egg white protein 44.3 4.646 17.135 trypsin inhibitors 20.1 4.303 19.279

[0208] Example 2: Gel filtration technology can be used to identify dairy products or non-dairy protein products produced under different conditions.

[0209] To further verify the application of gel filtration technology in the detection of real samples, this invention used the elution peak of raw milk as a control and compared the elution peaks of non-dairy products, dairy products, and reconstituted milk on an S300 column. The analysis results show that gel filtration technology can clearly distinguish dairy products or non-dairy products produced under different conditions.

[0210] 1. Elution peaks of whole milk proteins from milk and dairy products or non-dairy products on an S300 short column (23 mL column volume).

[0211] The non-dairy products used in the experiment were freshly ground soybean milk, and the dairy products were Vitasoy containing soybeans and milk powder and coconut milk containing sodium caseinate. The milk powder used for reconstituted milk were Want Want Group milk powder and commercially available Russian milk powder.

[0212] For testing dairy and non-dairy products, the product is first diluted with ultrapure water according to the protein content stated in the product instructions, and then its elution peak chromatogram and characteristic region distribution are detected using an S300 short column (see...). Figures 17-22 (See Table 7); The mobile phase for detection was 50 mM Tris-HCl, 0.15 M NaCl, pH 7.8; the flow rate was 1 mL / min.

[0213] Figure 17 The elution peak chromatogram of raw milk, used as a control, is divided into three characteristic segments. For example... Figure 18 , 19 As shown, the elution peak diagrams of freshly ground soybean milk (50-fold dilution) and Vitasoy (50-fold dilution) mainly show the breakout peak in segment one, without segments two and three. Freshly ground soybean milk exhibits a slight peak in the 14–24 mL range. Figure 18 Vitasoy has an elution peak for small molecules at 21 mL (see...). Figure 19 ).like Figure 20 As shown, the elution peak diagram of coconut milk (15-fold dilution) shows a single elution peak and a second elution peak, but no third elution peak. The elution peak diagram of commercially available Russian reconstituted milk powder (10.42g of milk powder dissolved in 100mL of ultrapure water and then diluted 10-fold) shows a single elution peak, with no obvious second or third elution peaks (see...). Figure 21 The elution peak diagram of Want Want milk powder reconstituted milk powder shows three distinct characteristic segments. Figure 22 The peak patterns of commercially available Russian reconstituted milk powder, fresh milk, and Want Want reconstituted milk powder showed significant differences, with the peak shape of Want Want reconstituted milk powder being closest to that of fresh milk.

[0214] like Figures 17-22 As shown in Table 7, by comparing the elution peak diagrams of dairy and non-dairy products under different production conditions, it can be seen that milk proteins exhibit unique elution peaks in the gel filtration system. Therefore, distinguishing milk proteins from non-dairy proteins by the elution peaks of the gel filtration system is a feasible technical approach.

[0215] Table 7. Elution Peak Characteristics of Dairy and Non-Dairy Products

[0216] sample Section 1 Section Two Section 3 Raw milk (control) √ √ √ Freshly ground soybean milk √ × × Vitasoy √ × × Coconut milk √ √ × Commercially available Russian infant formula √ × × Want Want Milk Powder √ √ √

[0217] (Note: √ indicates that the section exists, × indicates that the section does not exist)

[0218] 2. Elution peaks of milk protein monomers from milk and dairy products on an S300 long column (84 mL column volume).

[0219] Meanwhile, the acid supernatant and acid precipitation elution peak chromatograms of commercially available fresh milk (Bright Dairy), UHT milk (New Hope), and normal / abnormal samples of Want Want milk were compared. The acid supernatant and acid precipitation elution peak chromatograms are shown below. Figure 23 and Figure 24 .

[0220] like Figure 23 As shown in the elution peak diagram of acid supernatant from different samples on an S300 long column (84 mL), raw milk exhibits two distinct elution peaks in the 60–75 mL range (peaks at 63.6 / 66.57 mL) (calculated using the protein molecular weight formula y = -18.878x + 147.4, R...). 2 =0.9885, the molecular weight in this range is close to that of lactalbumin; UHT has 1 peak (peak at 66.29 mL); Want Want Milk is UHT milk, and neither normal nor abnormal samples showed obvious elution peaks in this range. Analysis suggests that the elution peak range of 60-75 mL during acid washing can distinguish between raw milk and UHT milk. Within the 75-84 mL range, the elution peak positions of different samples showed significant differences. UHT milk had no obvious elution peak, the elution peak of raw milk was 77.57 mL (molecular weight approximately 5.01 kDa), the elution peak of abnormal Want Want Milk samples was 79.6 mL (molecular weight approximately 3.91 kDa), and the elution peak of normal Want Want Milk samples was 83.09 mL (molecular weight approximately 2.55 kDa). Analysis suggests that the elution peak range of 75-84 mL during acid washing can not only distinguish between raw milk and UHT milk, but also identify whether the molecular weight of dairy protein has changed.

[0221] like Figure 24As shown, in the elution peak chromatogram of different samples on an S300 long column (84 mL), within the range of 45–65 mL, raw milk showed one elution peak (peak tip 54.57 mL, molecular weight approximately 82.67 kDa), and UHT showed one (peak tip 56.04 mL, molecular weight approximately 69.1 kDa). The elution peaks of acid precipitation in both normal and abnormal Want Want milk samples were not obvious. Analysis suggests that the 45–65 mL elution peak range can distinguish between raw milk and UHT milk. Within the 75–84 mL elution peak range, neither raw milk nor UHT milk showed obvious elution peaks, while both normal and abnormal Want Want milk samples showed obvious elution peaks, but it was impossible to determine whether the molecular weight of the dairy protein had changed.

[0222] In summary, the elution peaks of gel columns with different column lengths can distinguish between milk proteins and non-milk proteins, dairy products produced under different conditions, and whether the molecular weight of proteins in dairy products has changed.

[0223] Example 3 analyzes the feasibility of coagulation filtration section analysis based on the impact of various conditions on the quality of milk and dairy products.

[0224] 1. Gel filtration assay to detect the autocoagulation of proteins in raw milk stored at 4°C.

[0225] At 4℃, enzyme activity is very low, and the effect of protease on milk protein can be ignored. This example uses raw milk stored at 4℃ as the subject to investigate the changes in the molecular weight of milk protein during storage at 4℃. The experimental setup included storage times of 2 hours, 1 day, 2 days, 3 days, and 4 days. For gel filtration assays, two parallel samples were taken from each storage time point, and the average result was calculated. The relationship between Σ0 (i.e., ΣmAU) and the number of days of storage was determined. The results show that the Σ0 of milk protein at different storage time points at 4℃ exhibits a decreasing trend (results are shown in Figure 1). Figure 25 This means that the total amount of protein in raw milk detected by gel column chromatography decreases with increasing storage time.

[0226] Fresh milk was stored at 4°C. The relationship between Σ0 and time was analyzed. A decrease in Σ0 indicates that some large aggregated particles were lost during sample pretreatment. Correction is needed when calculating the percentage of segments. The lost portion is attributed to segment 1 (correction results are shown in Table 8). Figure 26 In section 1, the concentration continuously increases; while in sections 2 and 3, the concentration continuously decreases. These represent the percentage of protein in the solution. As time progresses, protein molecules continuously aggregate and coagulate into large particles, which are removed during pretreatment by centrifugation or filtration through a 0.22μm microporous membrane.

[0227] Table 8. Data on the relationship between Σ0, segment percentage, and time of milk self-coagulation at 4℃ (before and after correction)

[0228]

[0229] 2. Evaluate the effect of heating on the coagulation of milk proteins.

[0230] The denaturation degree of different protein components varies with heat treatment temperatures. Therefore, heat treatment temperature is one of the key factors affecting the quality of milk protein. Due to limitations in laboratory conditions, raw milk could not be obtained; therefore, fresh milk was used as a sample (fresh milk undergoes pasteurization, resulting in minimal component changes, and can be initially treated as raw milk; the distribution range of characteristic regions is shown in [reference needed]). Figure 17 This study investigated the changes in milk protein after heating in a water bath at different temperatures for 30 minutes. The water bath temperature gradient was 60℃ to 90℃, with a heating interval of 5℃. Heated samples were immediately cooled in an ice bath and then passed through an S300 gel column. By comparing three characteristic regions, the proportion of the third region decreased when the heating temperature was 75℃ or higher. The Σ / Σ0 ratio of samples with different heating treatments was calculated. The results showed that heating promotes milk protein coagulation (see Table 9). Figure 27 .

[0231] The results show that the protein in the third region coagulates and enlarges upon heating, first migrating to the second region, and then to the first region. After treatment at different temperatures, the Σ0 percentage in the third region decreased from 32.95% to 16.00%; the Σ0 percentage in the second region increased due to the influx of protein from the third region, then decreased as it gradually migrated to the first region, with little overall change; the Σ0 percentage in the first region increased from 43.48% to 59.55%.

[0232] Table 9. Percentage of raw milk segments after heating at different temperatures

[0233]

[0234] (Note: NTC refers to samples that have not undergone heat treatment)

[0235] 3. Using proteinase K to simulate exogenous proteases to assess the degradation of milk proteins by proteases.

[0236] The heat-stable proteases in milk are mainly endogenous and exogenous. Endogenous heat-stable proteases primarily refer to plasmin, a natural protease transported from the blood to the mammary glands and secreted into milk (Wang Hui, Lü Jiaping, Chi Yujie, 2009); exogenous heat-stable proteases are proteases produced by various bacterial activities. This invention uses proteinase K as a reference to preliminarily study the effects of storage time and enzyme concentration on milk proteins.

[0237] Proteinase K was purchased from Shanghai Sangon Biotech Co., Ltd. The instruction manual only provided the quantity, without a formula for calculating enzyme activity, making it impossible to accurately convert this into an effect on milk protein. In this example, the final concentrations of proteinase K added to raw milk were 5 μg / mL and 5 ng / mL, respectively, and the mixtures were incubated at 37°C for 1 hour to detect the degradation of milk protein. Figure 28 As shown, after 5 μg / mL proteinase K degraded milk protein at 37℃ for 1 hour, the signal value in the first segment was approximately 2 mAU (see...). Figure 28 (Left figure) The signal value of proteinase K at 37℃ for 1 hour, below 5 ng / mL, degrades raw milk protein to a protein level of 32 mAU (see left figure). Figure 28 (See right figure). The experiment on the degradation of milk protein by proteinase K demonstrates that gel filtration technology can detect the changes in the enzymatic hydrolysis of milk proteins by different concentrations of proteinase.

[0238] 4. Use Listeria elastraceae as a psychrophilic mimic to assess the degradation of milk protein by psychrophilic bacteria and establish a method for the determination of psychrophilic bacteria.

[0239] Psychrophilic bacteria contamination is a significant factor affecting milk quality. Raw milk requires refrigeration during production and transportation, but some psychrophilic bacteria can continue to grow and proliferate under low-temperature conditions. The heat-resistant extracellular proteases they produce retain some activity even after ultra-high temperature (UHT) sterilization, causing UHT milk to deteriorate during long-term storage and ultimately shortening its shelf life. Studies have shown that the number of psychrophilic bacteria in raw milk is greater than 1 × 10⁻⁶. 4 and 5×10 4 At CFU / mL, protease activity and hydrolytic capacity will increase (Vithanage, Dissanayake et al. 2017). Sterilization at 140℃ for 5 seconds resulted in 29% residual protease. Proteases produced before the killing of psychrophilic bacteria can digest casein, leading to bitterness and curdling, significantly impacting the mouthfeel and texture of UHT milk (Li Xiaojian, Lü Yang, Guo Huiyuan 2014). When the number of psychrophilic bacteria in the raw milk reaches 10... 5 At CFU / mL, it has a significant effect on the bitterness of UHT milk, 10 3 and 10 4 CFU / mL has no significant effect on the bitterness of UHT milk (Jiang Yiming & Han Jianchun, 2015).

[0240] Based on this, using Listeria monocytogenes, an existing bacterium in the laboratory, as a reference bacterium, we simulated the infection of raw milk by psychrophilic bacteria to explore the degradation of raw milk proteins by psychrophilic bacteria. The specific experimental procedures are as follows:

[0241] Following our proprietary SOP, we rejuvenated the bacterial strain, picked single colonies, and incubated them in nutrient broth at different temperatures for specific times. Afterward, we measured the OD value (600 nm). We plotted a growth curve with OD value on the ordinate and incubation time (h). See [link to SOP]. Figure 29 The growth curve from 4℃ culture showed that one division took approximately 11.84 hours, with the rapid growth phase occurring from 48 to 72 hours post-inoculation, followed by a saturation phase after 72 hours.

[0242] 0.9 mL of pasteurized milk was infected with 0.1 mL of Listeria monocytogenes dilution and incubated at 4°C. Samples were taken after 2 h and 60 h to test the sensitivity of Listeria monocytogenes to degrade milk proteins. The theoretical colony counts were 300 and 1000 (approximately 3000 was obtained by plate counting). Because the 0.1 mL bacterial solution diluted the milk, polymers in the milk dissolved, increasing the total protein content. Although the protein content was slightly higher at 60 h than at 2 h, the increase in 1000 CFU / mL with increasing bacterial count was less than that of the control NTC. Furthermore, the Σ / Σ0 ratio of 1000 copies showed a negative value. Finally, the sensitivity of 1000 CFU / mL for determining Listeria monocytogenes using gel filtration analysis was verified. The experimental results are as follows:

[0243] Considering the preservation of pasteurized milk in the cold chain, the experimental conditions should use actual temperature and extended time. First, this invention tested the growth curves of Listeria monocytogenes at 4 / 20 / 30 / 37℃, with the fastest growth observed at 30℃ (see...). Figure 29 The growth curve shows that it takes about 11.84 hours for it to divide once at 4℃. The rapid growth period is from 48 to 72 hours after inoculation, and it enters the saturation stage after 72 hours.

[0244] Samples were prepared by contaminating pasteurized milk with 0.9 mL of milk and 0.1 mL of diluted Listeria monocytogenes for 2 h and 67 h. The theoretical input of Listeria monocytogenes colony-forming units (CFU / mL) was 10, respectively. 3 10 4 10 5 and 10 6 (Plate count: 4.2 × 10⁻⁶) 3 3.09×10 4 2.82×10 5 3.1×10 6 The effect of 1,000 on milk protein was determined.

[0245] The sensitivity of Listeria monocytogenes in degrading milk proteins was further tested by placing samples with colony units of 300 and 1000 (actual bacterial count approximately 3000) for 60 hours. Due to the dilution of milk with 0.1 mL of physiological saline, polymers in the milk dissolved, increasing the total protein content. Although the levels at 60 hours were slightly higher than at 2 hours, the increase in 1000 CFU / mL was less than that of the control NTC (see Table 10), and the ratio of 1000 to Σ / Σ0 was negative (see Table 10). Finally, the sensitivity of 1000 CFU / mL for determining Listeria monocytogenes using gel filtration analysis was verified.

[0246] Table 10. Analysis data of Σ0 and Σ / Σ0 of Listeria monocytogenes with different colony counts after 60 h of growth.

[0247] Σ0 2h 60h 60h-2h Increase ratio NTC 28775.41 30172.81 1397.4 0.0486 300 29810.38 32992.3 3181.92 0.1067 1000 30817.38 31779.92 962.54 0.0312

[0248] Σ / Σ0 2h 60h 60h-2h Reduce ratio NTC 846.232 853.889 7.657 0.0090 300 906.462 947.89 41.428 0.0457 1000 919.657 898.457 -21.2 -0.0231

[0249] Compared with other methods for detecting psychrophilic bacteria, the sensitivity of gel filtration for detecting Listeria is close to that of methods such as flowing blood cell method, direct fluorescence filtration method, aminopeptidase method, and bioluminescence method, but is similar to or slightly lower than that of RQ-PCR (230-3000 CFU / mL).

[0250] This experiment used Listeria monocytogenes as a reference bacterium to simulate the changes in milk protein molecules degraded by psychrophilic bacteria. This will inevitably differ from the actual situation of psychrophilic bacteria in raw milk. Therefore, more refined experimental design and implementation are needed based on actual conditions to more accurately assess the impact of psychrophilic bacteria on milk quality and determine the sensitivity of the corresponding detection system.

[0251] The above experiments analyzed in detail the changes in milk quality under various conditions, demonstrating the role of the coagulation filtration technology proposed in this invention in the analysis of milk protein quality, and establishing quantitative indicators for the analysis of changes in milk quality.

[0252] Example 4: Comparison of the percentage of Σ / Σ0 and different processed UHT milk segments in the market.

[0253] The protein distribution of several domestic raw milk samples and whole, skimmed, and partially skimmed UHT milk samples (from different production dates) was analyzed using gel filtration technology. Differences in the protein Σ / Σ0 ratio and protein segments were compared under different treatments and sterilization processes. According to gel filtration analysis, Σ / Σ0 represents the molecular weight distribution of proteins; a higher value indicates a higher concentration of large-molecule proteins in the solution, and vice versa. Σ0 represents the total protein content in the solution; a high Σ0 indicates a high protein content, while a low Σ0 indicates a low protein concentration, possibly due to aggregated protein molecules being too large to be detected during gel filtration. The segment proportion results were generally consistent with Σ / Σ0; a larger Σ / Σ0 indicates a higher proportion of segment 1, while a smaller Σ / Σ0 indicates a higher proportion of segments 3 and 2 (see Table 11). Based on this, the quality of various dairy products can be evaluated.

[0254] Table 11 Statistical Results of Raw Milk and UHT Milk

[0255]

[0256] (Note: The capital letters in the brand name are the abbreviation of the milk brand.)

[0257] Example 5: Comparison of the percentage of abnormal and normal samples

[0258] During the experiment of this invention, a batch of products that were found to have deteriorated during the sales process were obtained. Using normal samples as a control, acid supernatants and acid precipitates from batches of normal / abnormal samples from March to June were prepared and analyzed on an S300 long column (81 mL column volume). The formula for calculating the molecular weight of the protein is: y = -18.67x + 143.81, R... 2 Elution peak chromatogram of 0.9894.

[0259] like Figure 30 As shown, in the elution peak diagrams of the acid supernatant of normal / abnormal samples on an S300 long column (81 mL column volume), there is a breakout peak near 32 mL, which may be due to incomplete separation of casein micelles. There are differential elution peaks in the 70 mL to 80 mL range. The acid elution peak of the abnormal sample is at 77 mL (molecular weight 3.79 kDa), while the acid elution peak of the normal sample is at 80 mL (molecular weight 2.62 kDa).

[0260] Based on the segment proportion method, the proportion of characteristic segments in the latest elution peak within the 75–81 mL range (81 mL column volume for S300 column) of the acid supernatant of four groups of normal / abnormal Want Want samples was analyzed, along with the significance of the differences. Using the 75–81 mL range as the specified range, 75–78 mL was designated as characteristic segment 1, and 78–81 mL as characteristic segment 2. The proportions of characteristic segments 1 and 2 in the acid supernatant of normal / abnormal samples from March to June were calculated within the specified range (segment proportion results are shown in Table 12). The calculations showed that the difference in the proportions of characteristic segments 1 and 2 in the acid supernatant of normal samples from March to June was lower than that in the abnormal samples (see Table 12). Figure 31 A t-test (paired two-sample analysis of the mean) was performed on the proportions of normal and abnormal samples in segment 1. The results showed a significant difference, as shown in Table 12.

[0261] Table 12. Proportion of normal and abnormal acid supernatant segments 1 and 2 in total segments from March to June.

[0262]

[0263] like Figure 32 As shown, in the elution peak diagram of acid precipitation of normal / abnormal samples on an S300 long column (81 mL), there is a breakthrough peak near 32 mL, which is casein micelles; from March to June, the peak height of the breakthrough peak (30-40 mL) of the four groups of normal / abnormal samples is higher than that of the elution peak (50-60 mL); the elution peak in the 80-95 mL range has two inconsistent peaks, and no region for distinguishing normal / abnormal samples was found.

[0264] In summary, when analyzing acid supernatant samples using non-denaturing detection methods, within the latest elution peak range of an S300 long column (81 mL), the difference in the proportion of normal sample segment 1 and segment 2 is lower than that of abnormal sample, and the difference in the proportion of normal and abnormal samples in segment 1 is extremely significant. This demonstrates the role of the coagulation filtration technology proposed in this invention in the analysis of milk protein quality.

[0265] References

[0266] Gao.P(2016)."Establishment and application of milk fingerprint by gelfiltration chromatography." JDairySci 99(12):9493-9501.

[0267] L. Nelson, D. (2017). Lehninger Principles of Biochemistry Freeman and Company.

[0268] Li,YS,Y.Zhou and XYMeng(2014)."Enzyme-antibody dual labeled goldnanoparticles probe for ultrasensitive detection of kappa-casein in bovinemilk samples." Biosens Bioelectron 61:241-244.

[0269] Vithanage, NR, M. Dissanayake, G. Bolge, EAPalombo, TRYeager and N. Datta (2017). "Microbiological quality of raw milk attributable to prolonged refrigeration conditions." J Dairy Res 84(1):92-101.

[0270] Chen, X.X., Lu, J., Liu, L. (2018). "Determination of 12 Oligosaccharides in Breast Milk by Ultra-High Performance Liquid Chromatography-Mass Spectrometry." Food Product Science 39(04).

[0271] Jiang, Yiming; Han, Jianchun (2015). "A Study on the Negative Impact of Psychrophilic Bacteria on UHT Milk Quality." China's dairy industry 43(8).

[0272] Li, Linqiang; Tian, ​​Wanqiang; Zan, Linsen (2011). "Changes in physicochemical properties of ultra-high temperature sterilized milk during shelf life and the effect of ultrafiltration on its quality stability." Journal of Northwest A&F University (Natural Science Edition) 39(5).

[0273] Li Rongfeng, Li Pengcheng, Yu Huahua (2022). A metalloproteinase and its isolation method. CHINA.

[0274] Li Xiaojian, Lü Yang, Guo Huiyuan (2014). "Study on the Influence of Psychrophilic Bacteria on UHT Milk Quality". China's dairy industry 43(8).

[0275] Lü Yuan, Yin Yuanming, Tang Jiani (2009). "Research progress on rapid detection methods for psychrophilic bacteria in raw milk." Food Science 30(03).

[0276] Song, Huimin; Lu, Jing; Lü, Jiaping (2016). "Evaluation of Milk Heating Degree and Flavor Changes Based on Electronic Nose and Electronic Tongue." China's dairy industry 44(2).

[0277] Sun, Lechang; Leng, Meng; Cao, Minjie (2022). "A pancreatic lipase inhibitory peptide derived from *Porphyra yezoensis*, its preparation method, and its application."

[0278] Wang Hui, Lü Jiaping, and Chi Yujie (2009). "Study on the thermal denaturation kinetics of plasmin in milk with different somatic cell numbers." Food Science 30(19).

[0279] Wang Hui, Sun Qi, Liu Lu (2013). "Establishment and Validation of a UHT Milk Shelf Life Prediction Model." Chinese Agricultural Science 46(3):586-594.

[0280] Yi Shengnan, Lu Jing, and Pang Xiaoyang (2021). "Effects of heat treatment on the degree of Maillard reaction and volatile components in milk." Food Science 42(14): 9-15. Yi Shengnan, Zhang Shuwen, Lu Jing (2020). "Effects of different storage temperatures on the physicochemical properties and flavor of ultra-pasteurized milk during shelf life." Food Industry Technology 41(21).

[0281] The scope of protection of this invention is not limited to the above embodiments. Any variations and advantages that can be conceived by those skilled in the art without departing from the spirit and scope of this invention are included in this invention and are protected by the appended claims.

Claims

1. A method for detecting protein molecular weight distribution based on gel filtration technology, characterized in that, Includes the following steps: Step (1) Build a protein molecular weight detection technology platform based on gel filtration technology to detect the characteristic peaks or characteristic regions of milk and dairy product proteins at specific wavelengths and their absorbance values ​​in real time. Step (1) includes the following sub-steps: (1.1) Select the carrier and determine the performance of the pre-packed column, including: column volume, number of trays, asymmetry factor and drop height; (1.2) Select the sample detection method, including sample processing method, mobile phase and flow rate; (1.3) Fitting the formula for calculating the molecular weight of proteins in gel columns; Step (2) Design and propose an evaluation measure Σ / Σ0, segment proportion and its applicable conditions and range for calculating the molecular weight distribution of proteins, and conduct detection and analysis on the molecular weight distribution of proteins.

2. The method as described in claim 1, characterized in that, In step (1.1), The carrier refers to a molecular sieve carrier with a fractionation range of 1kDa to 100kDa, 5kDa to 250kDa, and 10kDa to 1500kDa; and / or, the column volume is 20 to 40 mL for rapid detection of intact proteins and more than 70 mL for separating single protein molecules. And / or, In step (1.2), The mobile phase used in the non-denaturing detection method is 50 mM Tris-HCl and 0.15 M NaCl, while the mobile phase used in the denaturing detection method is 0.5% SDS and 50 mM Tris-HCl. And / or, The flow rate of the mobile phase is 0.5–1.5 mL / min.

3. The method as described in claim 1, characterized in that, In step (1.2), the sample selection and detection method includes the following: (1.2.1) Sample defatting: Centrifuge the sample at 4℃~8℃ and 10000~15000rpm for 10min to remove the upper lipid layer, and transfer the intermediate phase or all samples except the lipid layer to a new centrifuge tube. (1.2.2) Process the defatted samples using non-denaturing or denaturing detection methods as needed; (1.2.3) Concentration calibration before gel filtration is divided into the same dilution factor or the same protein content; (1.2.4) Perform gel filtration, and select gel columns of different volumes as needed.

4. The method as described in claim 3, characterized in that, Step (1.2.2) involves processing the defatted sample using either non-denaturing or denaturing detection methods as needed, specifically including the following steps: (1.2.2.1) Non-denaturing detection method for whole milk protein: take defatted and homogenized milk and dairy products and dilute them 50 to 60 times. After dilution, filter them through a 0.22 μm or 0.45 μm microporous membrane. (1.2.2.2) Non-denaturing detection method for milk protein single molecules and their polymers: Take defatted and homogenized milk and dairy products, add acid to adjust the pH to 4.6 for isoelectric point precipitation, centrifuge at 4℃~8℃, 10000~15000rpm for 10min, and transfer the supernatant and precipitate to new centrifuge tubes, labeled as acid supernatant or acid precipitate, to complete the non-denaturing treatment; (1.2.2.3) Method for detecting denaturation of single milk protein molecules: Take defatted and homogenized milk and dairy products, add acid to adjust the pH to 4.6 for isoelectric point precipitation, centrifuge at 4℃~8℃ and 10000~15000rpm for 10min, and transfer the supernatant and precipitate to new centrifuge tubes, labeled as acid supernatant or acid precipitate. Take the required volume of acid supernatant and / or acid precipitate and add 2% SDS and 2mM DTT to the final concentration. Make up the remaining volume with ddH2O and incubate in a water bath at 60℃ for 30min to complete the denaturation treatment.

5. The method as described in claim 3, characterized in that, The concentration calibration before gel filtration (1.2.3) is divided into the same dilution factor or the same protein content, and specifically includes the following steps: (1.2.3.1) At the same dilution factor, the sample to be tested was centrifuged at 4℃~8℃ and 10000~15000rpm for 10min, and the intermediate phase was taken, diluted to the same factor and filtered through a 0.22μm or 0.45μm microporous membrane. (1.2.3.2) For samples with the same protein content, after centrifugation at 4℃~8℃ and 10000~15000rpm for 10min, the intermediate phase was filtered through a 0.22μm or 0.45μm microporous membrane, the concentration of the filtered portion was determined, and the samples were uniformly diluted to the same concentration. And / or, The step (1.2.4) involves gel filtration, where different column volumes of gel columns are selected as needed. Specifically, this includes the following steps: (1.2.4.1) Non-denaturing method: Take 0.5% to 4% of the gel column volume of sample and pass it through the gel column. Use 50mM Tris-HCl and 0.15M NaCl as the mobile phase and the flow rate is 0.5 to 1.5 mL / min. The sample elution volume should exceed the gel column volume. Analyze the column peak chromatogram and raw data. (1.2.4.2) Denaturation method: Take 0.5% to 4% of the gel column volume of sample and pass it through the gel column. Use 0.5% SDS and 50 mM Tris-HCl as the mobile phase and the flow rate is 0.5 to 1.5 mL / min. The sample elution volume should exceed the gel column volume. Analyze the column peak chromatogram and raw data.

6. The method as described in claim 1, characterized in that, In step (1.3), the linear relationship between protein molecular weight and elution peak position is as follows: V = -klgM + b or lgM = -kV + b, where V represents the elution peak position corresponding to the absorbance value in mL, and M represents the relative molecular weight of the protein standard. And / or, Each time a column is packed, the protein standard is used to perform column chromatography detection and molecular weight calculation formula fitting again.

7. The method as described in claim 1, characterized in that, In step (2), Σ / Σ0=ΣM×mAU / ΣmAU; Wherein, "M" refers to the protein molecular weight, which is calculated using the standard molecular weight formula and the position of the elution peak; "mAU" refers to the absorbance value, which is read and exported in real time by the gel filtration system used; "ΣmAU" is the sum of the absorbance values ​​at all points within a specified range, and is abbreviated as Σ0; "M×mAU" is the product of the molecular weight and absorbance of the protein within the specified range; "ΣM×mAU" is the sum of M×mAU of the corresponding protein within the specified range, abbreviated as Σ; The specified range begins at a position no less than the first elution peak of the protein and ends at a position no greater than the elution position of the small molecule peptide or amino acid calculated using the molecular weight formula.

8. The method as described in claim 1, characterized in that, In step (2), the segment ratio is the percentage of the Σ0 of the feature segment as described in claim 7 to the Σ0 of the specified range as described in claim 7; The characteristic region refers to the interval from the start to the end of an elution peak, and / or the range of peaks of a protein or polypeptide from the start to the end of elution, calculated according to the protein molecular weight formula. In particular, the characteristic region is included within a specified range.

9. The application of the method according to any one of claims 1 to 8 in the quality testing of milk and / or dairy products, and the identification of dairy products from non-dairy products.

10. A detection system, characterized in that, include: Memory and processor; The memory stores a computer program that, when executed by the processor, implements the method as described in any one of claims 1 to 8.

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