A method for screening serum for lentivirus packaging

Abstract

The present application belongs to the field of biotechnology and discloses a method for screening serum for lentivirus packaging. SIMCA-P software is used to perform OPLS-DA analysis on the composition and lentivirus yield of different batches of serum to obtain intuitive score graphs and load graphs, thereby establishing a corresponding model to provide support for subsequent serum screening.

Description

Technical Field

[0001] The invention belongs to the field of biotechnology, and in particular relates to a method for screening serum for lentivirus packaging. Background Art

[0002] Bovine serum has many components. In addition to basic amino acids, sugars, lipids and other chemical substances, it also contains many functional active substances, such as plasma proteins, peptides, growth factors, hormones, etc., and there are large differences in serum from different batches and sources. These components often affect the yield and quality stability of the biological product production process, especially the titer of lentivirus packaging. Therefore, the identification and control of serum quality is still an unresolved problem. Summary of the invention

[0003] In order to solve the technical problems mentioned in the background technology, the present invention provides a method for screening serum for lentivirus packaging, and the technical solution is:

[0004] A method for screening serum for lentivirus packaging, which includes establishing a relationship model between serum components and virus yield based on a method for determining serum components and serum lentivirus packaging effects, and screening serum for lentivirus packaging;

[0005] The relationship model is: virus yield = 79.62 + alanine aminotransferase × 0.723 - lactate dehydrogenase × 0.082 + potassium ion × 3.464 + aspartate aminotransferase × 1.075 - triglyceride × 95.637.

[0006] Preferably, the serum is fetal bovine serum.

[0007] Preferably, the method for determining the serum lentivirus packaging effect is a cell transduction method.

[0008] Preferably, the cell transduction method requires that the cells be adapted to the corresponding serum for passage before virus packaging and titer determination.

[0009] Preferably, the adaptation passages need to be more than 3 times.

[0010] Preferably, the virus yield is expressed as a relative titer of virus detection.

[0011] The beneficial effects of the present invention mainly lie in that the present application uses SIMCA-P software to perform OPLS-DA analysis on the composition and lentivirus yield of different batches of serum, obtains intuitive score graphs and loading graphs, and thus establishes corresponding models, providing support for subsequent serum screening.

[0012] The present application can establish a corresponding model based on the serum components, physicochemical properties and efficacy data of some batches. According to the model, the key substances in the serum that affect the virus packaging titer can be identified, which can be used as a screening basis for serum with high virus packaging titer, with higher efficiency and greater throughput.

[0013] Mechanism of action of the present invention: Orthogonal partial least squares discriminant analysis (OPLS-DA) is a supervised discriminant analysis method. The characteristic of this method is that it can remove data changes in the independent variable X that are irrelevant to the classification variable Y, so that the classification information is mainly concentrated on one principal component, and the noise irrelevant to the classification information is effectively filtered out, thereby making the model simple and easy to understand, and improving the analytical ability and effectiveness of the model. It is widely used in metabolomics analysis. By establishing a model between the metabolite expression amount and the grouping relationship, OPLS-DA can better obtain the difference information between groups, and can also predict the grouping of samples. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 The distribution of titer intervals of serum virus packaging in different batches;

[0015] Figure 2 It is the score graph of different batches of serum;

[0016] Figure 3 It is the cross validation result of Example 2;

[0017] Figure 4 Loading diagrams of different batches of serum. DETAILED DESCRIPTION

[0018] The technical solution of the present invention will be further described below in conjunction with specific embodiments. The technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0019] 1. Experimental materials:

[0020] DMEM medium (Gibco, 11965092), T25 square bottle (JiaTe Bio, TCF012025), PEI Max (Selcom, PRIME-P100-100 MG), lentiviral particle packaging reagent (Full-Gene, LT0010), Opti-MEM (Gibco, 31985062), HEK 293T cells (ATCC, CRL-3216), OptiVitro® 293 serum-free virus production medium (Ecosai Bio, HE000-N032), trypsin (Thermo Fisher, 25200114), fetal bovine serum (Ecosai Bio, FSP500) contain multiple batches, the specific batches are shown in Table 1;

[0021] Fetal bovine serum FSD (Ecosai Biotechnology, FSD500), fetal bovine serum (Corning, 35-075-CV), fetal bovine serum (Thermo Fisher, 16000), fetal bovine serum (Situofan, SH30406), fetal bovine serum (Tianhang, 40212-8615), fetal bovine serum (Nova Pharmaceuticals, AB-FBS-1050S), fetal bovine serum (Situofan, SV30208), fetal bovine serum (Situofan, SH30413.03), fetal bovine serum (Xiaopeng, 04-001-1A-USDA), see Table 3 for specific batch tests;

[0022] Unless otherwise specified, other methods and reagents used in this example are conventional methods and reagents in the art.

[0023] 2. Experimental methods:

[0024] A method for screening serum with high virus packaging titer using serum components and physicochemical properties is as follows:

[0025] 1) Determine the lentiviral packaging effect, composition and physicochemical properties of serum;

[0026] 2) Using the original data obtained in step 1, the lentiviral packaging effects were classified, and the OPLS-DA model was established using SIMCA-P software to analyze the correlation analysis of the various components of different batches of serum and the cluster analysis of different batches;

[0027] 3) Determine the levels of triglycerides, alanine aminotransferase, potassium ions, lactate dehydrogenase, and aspartate aminotransferase in serum, and predict the yield of unknown serum according to the formula (yield = 79.62 + alanine aminotransferase × 0.723 - lactate dehydrogenase × 0.082 + potassium ions × 3.464 + aspartate aminotransferase × 1.075 - triglycerides × 95.637), so as to screen serum suitable for virus packaging.

[0028] Preferably, the serum is fetal bovine serum.

[0029] Preferably, the serum lentivirus packaging effect determination requires that the cells be adapted to the corresponding serum before passage.

[0030] Virus packaging and titer determination were performed.

[0031] Preferably, the adaptation passages need to be more than 3 times.

[0032] Preferably, the method for determining the lentiviral titer is a cell transduction method.

[0033] Preferably, the virus yield is expressed as a relative titer of virus detection.

[0034] Example 1. Selection of serum batches for model analysis:

[0035] The method for determining the lentiviral packaging effect of serum in the present invention is as follows:

[0036] a) Adaptation phase: The adherent 293 cells are revived from liquid nitrogen in a medium containing DMEM medium + 10% serum to be tested. The adherent cells are cultured in this medium for adaptation and passage, and the number of passages should be no less than 3 times.

[0037] b) Virus packaging stage, two days in advance, cells were cultured at 10 6 Cell number / T25 culture flask. Before plasmid transfection, it is necessary to confirm that the cell confluence reaches 80-90%, and then use the cells for virus packaging. Taking T25 as an example, the transfection system is a T25 culture flask, the final DNA concentration is 1.5μg / mL, DNA: PEI=1.5:4.5, and the specific operation is as follows: 1. PEI Max: dilute 22.5μg PEIMax with Opti-MEM to 0.25 mL system, incubate at room temperature for 5 minutes, 2. Lentivirus packaging reagent (plasmid containing GFP gene): dilute 7.5μg DNA with Opti-MEM to 0.25mL system, 3. Add PEI Max to DNA to form a PEI / DNA complex, mix well, incubate at room temperature for 10 minutes, then slowly add it to the culture system, and then transfer to the incubator for continued culture. About 6 hours after transfection, remove the original culture medium and replace it with OptiVitro® 293 serum-free virus production medium. 48 hours after transfection, the virus can be harvested and stored at -80℃.

[0038] c) Virus titer detection: One day in advance, adherent 293 cells were digested and counted. 5The cells were inoculated into a 12-well plate at a density of 1.5 cells / well. After one day of culture, 20 μL of the collected virus supernatant sample was inoculated into the 12-well plate. After two days of culture, the cells in the well plate were digested into single cells for flow cytometry detection, and the proportion of green fluorescence-positive cells was recorded. The higher the proportion, the higher the titer of the sample.

[0039] The serum composition and physicochemical properties of the present invention are determined as follows:

[0040] pH and osmotic pressure were measured using a pH meter and an osmotic pressure meter, respectively. Substances such as alanine aminotransferase, alkaline phosphatase, total bilirubin, calcium ions, chloride ions, cholesterol, creatinine, glutamyl transpeptidase, glucose, high-density lipoprotein, low-density lipoprotein, lactate dehydrogenase, phosphorus, potassium, aspartate aminotransferase, sodium, iron, triglycerides, uric acid, albumin, α1-globulin, α2-globulin, β1-globulin, β2-globulin, γ-globulin, and M-globulin were sent to a special testing agency for testing.

[0041] The data analysis method of the present invention is as follows:

[0042] The raw data was saved in an Excel table, with each row representing a batch of serum samples and each column representing a component of the serum. The pre-processed raw data was imported into the SIMCA-P software in the form of Excel, with the sample name in the first column and the component name in the first row as the first name, and the data was standardized using PAR. Since some serum samples had blank values ​​in multiple components or a component was blank in multiple samples, if a serum sample or a component had a blank value of more than 50%, the serum sample or a component needed to be removed and saved as a .USP file. After reopening the .USP original file, the raw data was marked and classified according to the results of high and low virus packaging titers, and the OPLS-DA analysis mode was selected for analysis.

[0043] In order to screen out the components and physicochemical properties of serum that may have a greater impact on the virus titer, serum batches with larger virus packaging titers should be selected for differential analysis. The titer detection was performed according to the method of the specific implementation method, and the virus titer data under the conditions of different batches of serum can be obtained. The results are shown in Table 1, and the frequency histogram is shown in Figure 1 Therefore, 6 batches in the range of 20~30 (12B164, 12B166, 12B169, 12B055, 12B171, 12B167) and 5 batches in the range of 50~60 (i.e., 12B172, 12B251, 12B173, 12J200, 12B194) were selected as samples for the difference study.

[0044] Table 1: Comparison of virus packaging titers of different batches of serum

[0045]

[0046] Example 2: Establishment of a model for the composition and physicochemical properties of serum with different virus packaging titers:

[0047] In order to determine the contribution of serum components and physicochemical properties to virus packaging titer, the components and physicochemical properties of serum batches with high and low virus packaging obtained in Example 1 were tested, and the results are shown in Table 1. The classification model was established using SIMCA, and the components and physicochemical properties of multiple batches of serum were modeled using OPLS-DA using the data in Example 1. The serum was classified according to high and low virus packaging titers. The serum batches with low virus packaging titers (6 batches in the range of 20-30) were named L, and the serum batches with high virus packaging titers (6 batches in the range of 50-60) were named H. Figure 2 As shown, Figure 2 It is a score graph of different batches of serum. The horizontal and vertical axes of the origin (0,0) represent principal components 1 and 2 respectively. The principal component is the new coordinate axis formed after dimensionality reduction of multidimensional data. The variance of principal component 1 is 0.399, indicating that its explanation rate for data variation is 39.9%. The higher the explanation rate, the better. The graph shows that samples with high and low virus packaging titers are clustered obviously. Different batches of serum with high virus packaging titers are distributed on the right side of principal component 2, and different batches of serum with low virus packaging titers are distributed on the left side of principal component 2, indicating that multiple batches of serum may be clustered due to different lentivirus packaging titers.

[0048] Table 2 Composition and physicochemical properties of different batches of serum

[0049]

[0050] The dependent variable fit index R of the initial model 2 Y is 0.987, and the model prediction index Q 2 is 0.937, both of which are over 0.5, indicating that the fitting results of the model are acceptable. To verify the validity of the model, the permutation test is used for iterative analysis. The results are as follows: Figure 3 As shown in Figure 2, after 200 permutation tests, Q 2 The intersection point of the regression line and the vertical axis is less than 0, indicating that the model is not overfitted and the model verification is valid. It is believed that the result can be used for subsequent analysis.

[0051] Figure 4The loading diagram shows the relationship between the composition and physicochemical properties of serum and the virus packaging titer. X is the independent variable, which is the various indicators of serum detection, and the figure shows glucose mmol / L, cholesterol mmol / L, etc. Y is a categorical variable, which is shown in the figure as $M3.DA (L) and $M3.DA (H), which means that the serum can be divided into two categories, L and H, according to the lentiviral packaging effect. L is serum with low virus packaging titer, and H is serum with high virus packaging titer. The closer the variables in the figure, the stronger the correlation between the variables. The serum with virus packaging titer has a strong negative correlation with triglycerides, and the correlation with the measured GFP is -0.952. The average triglyceride content in the serum of the H group is 17% lower than that of the L group. The serum with high virus packaging titer had a strong positive correlation with alanine aminotransferase, potassium ion, lactate dehydrogenase, and aspartate aminotransferase, and the correlation with the measured GFP was 0.85, 0.916, 0.88, and 0.82, respectively. The content of the above substances in the serum of group H was 51%, 28%, 25%, and 53% higher than that of group L. Therefore, in order to screen the serum with high virus titer, it is possible to screen the serum with higher concentrations of alanine aminotransferase, potassium ion, lactate dehydrogenase, aspartate aminotransferase and lower concentrations of triglycerides. By performing multiple regression on alanine aminotransferase, potassium ion, lactate dehydrogenase, aspartate aminotransferase and virus yield, we can obtain: yield = 79.62 + alanine aminotransferase × 0.723 - lactate dehydrogenase × 0.082 + potassium ion × 3.464 + aspartate aminotransferase × 1.075 - triglyceride × 95.637, the significant level of the variance test was 0.011, the multiple correlation coefficient (R) was 0.945, and the determination coefficient (R 2 ) is 0.914, and the corrected coefficient of determination is 0.829, indicating that the model has a good explanatory level. The yield here refers to: relative titer of virus detection (GFP), and the virus packaging titer needs to be determined by the method for determining the lentivirus packaging effect of serum in the present invention.

[0052] Example 3, test serum result verification:

[0053] Serum of different brands and batches was selected to detect its alanine aminotransferase, potassium ion, lactate dehydrogenase, aspartate aminotransferase and triglyceride, and the serum was used for virus packaging at the same time. According to the method in Example 1, the actual virus yield was detected. The calculation formula obtained by Example 2 and the measured physicochemical properties were used to calculate the theoretical virus yield. By comparing the actual virus yield with the theoretical virus yield, the results are shown in Table 3, and the yield prediction success rate reached 95.46%, indicating the rationality of using key substances to measure the virus packaging yield, and also greatly reducing the detection of other irrelevant substances, thereby saving time and improving efficiency. At the same time, this embodiment includes serum of multiple brands, indicating that the method can cope with a variety of scenarios and has certain universality.

[0054] Table 3. Blood collection and chemical properties and yields of different manufacturers

[0055]

[0056] The above-mentioned embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

Claims

1. A method for screening serum for lentivirus packaging, characterized in that: According to the determination method of serum components and serum lentivirus packaging effect, a relationship model between serum components and relative titer of virus detection was established to screen serum for lentivirus packaging; The relationship model is: the value of relative titer of virus detection = 79.62 + the value of alanine aminotransferase in U / L × 0.723 - the value of lactate dehydrogenase in U / L × 0.082 + the value of potassium ion in mmol / L × 3.464 + the value of aspartate aminotransferase in U / L × 1.075 - the value of triglyceride in mmol / L × 95.637; The serum is fetal bovine serum; The method for determining the serum lentivirus packaging effect is as follows: adapting cells to the corresponding serum for passage and then performing virus packaging and titer determination; The number of the adaptive passages is more than 3 times.

Images