Experimental method for heating inactivation and effect evaluation of Ebola virus

Abstract

The invention belongs to the technical field of biological safety, and particularly relates to an experimental method for heating inactivation of Ebola viruses and evaluation of the effect of the Ebola viruses. According to a dynamic inactivation parameter model established by Ebola virus strain characteristics, aggregation state, culture medium components, initial titer and equipment heat transfer efficiency, calculating the time required for inactivation; according to the inactivation effect evaluation method, TCID50 is combined with immunofluorescence and PMA-qRT-PCR parallel detection is adopted, the verification period is effectively shortened, meanwhile, three-generation blind transmission is initiated for the first time and combined with qRT-PCR detection for biological safety verification, the sensitivity is improved to 101 TCID50 / mL, and the false negative risk is thoroughly eliminated.

Description

Technical Field

[0001] The invention belongs to the field of biosafety technology, and particularly relates to an experimental method for heating inactivation of Ebola virus and effect evaluation thereof. Background Art

[0002] Ebola virus (EVD) is a representative pathogen of the Filoviridae family. The Ebola virus disease (EVD) it causes is classified by the World Health Organization (WHO) as the highest biosafety level threat (BSL-4), requiring strict safety precautions. The virus's ability to spread through direct contact has caused numerous large-scale outbreaks in Africa, including the Zaire Ebola outbreak in the Democratic Republic of the Congo from 2018 to 2020, which resulted in a mortality rate as high as 66%. Notably, the virus exhibits significantly higher thermal stability in vitro than typical enveloped viruses. Experimental data show that it can survive for over 30 days in virus-containing serum stored at 4°C. The heat resistance of its glycoprotein complex makes traditional inactivation protocols at 56°C inefficient, which is closely related to the unique virion structure and the heat resistance of its glycoprotein.

[0003] The core challenge facing Ebola virus research currently lies in its extreme biosafety requirements. According to the strict regulations of the "List of Pathogenic Microorganisms Transmitted by Humans", live virus operations must be carried out in a BSL-4 laboratory equipped with airtight positive pressure protective clothing, and samples must be completely inactivated before removal. Although existing inactivation methods (such as β-propiolactone treatment and γ-ray irradiation) can effectively destroy viral RNA, they have significant drawbacks: (1) There is a lack of quantitative evaluation standards for the inactivation efficiency of traditional heat inactivation schemes (56°C, 60 minutes); (2) The degree of degradation of viral structural proteins during the inactivation process is uncontrollable, seriously affecting the antigen integrity of subsequent ELISA testing and vaccine development; (3) A systematic database has not yet been established to determine the differences in sensitivity of different subtypes (Zaire type, Sudan type, etc.) and clinical isolates to physical inactivation conditions.

[0004] Virus inactivation is a core component of biosafety. However, existing inactivation methods and inactivation effect assessments still face the following key bottlenecks:

[0005] (1) The inactivation verification cycle is long and the biosafety risk is high. The traditional cell culture-based TCID 50 The method requires up to 10 days of cytopathic effect observation, and multiple operations increase the risk of laboratory infection (such as the multiple BSL-4 laboratory accidents reported by the WHO). In addition, the method relies on subjective cytopathic effect (CPE) interpretation, which has limited sensitivity and makes it difficult to detect low residual viral activity.

[0006] (2) The inactivation equipment parameters are not reliable enough. Existing dry bath heating systems generally have uneven heat transfer (±3°C temperature difference), which causes some samples to fail to inactivate due to insufficient temperature. At the same time, the aggregation state of the virus (such as the easy aggregation of filamentous virus particles) and the sample matrix components (serum proteins, cell debris) will hinder heat conduction. However, the existing equipment lacks a dynamic temperature compensation algorithm and cannot adaptively adjust the inactivation parameters.

[0007] (3) The inactivation evaluation system is imperfect. The current inactivation standard (e.g., 56°C, 30 minutes) does not take into account the differences in virus strains (e.g., the thermal sensitivity of Zaire vs. Sudan Ebola virus), the heat transfer efficiency of the equipment, and the sample load, resulting in incomparable data from different laboratories. For example, the inactivation efficiency of the same virus in a metal bath and a water bath can differ by as much as 1.5 log 10 TCID 50 / mL, but lacks unified dynamic model correction.

[0008] (4) There are loopholes in biosafety verification, and only a single PCR or TCID test is performed after conventional inactivation. 50 Testing confirmed that the risk of misidentification of residual viral nucleic acid or "reactivation" of defective particles (e.g., partial virus reactivation after cryopreservation) cannot be ruled out. Studies have shown that Ebola virus can survive in serum at 4°C for 46 days, suggesting the need for multiple verification mechanisms.

[0009] Therefore, there is an urgent need to develop a rapid and highly reliable inactivation method that integrates precise temperature control, a matrix-adaptive inactivation algorithm, and multimodal validation technology to address the core shortcomings of existing methods, such as long cycle times, high risks, and data incomparability. This invention fills this gap through its innovative design. Summary of the Invention

[0010] In order to solve the above problems, the present invention provides an experimental method for heat inactivation of Ebola virus and evaluation of its effect.

[0011] The present invention adopts the following technical solutions:

[0012] Ebola virus dynamic heat inactivation method: A baseline inactivation time is set, and the inactivation time is calculated using a dynamic inactivation parameter model based on the characteristics of the Ebola virus strain, aggregation state, culture matrix composition, initial titer, and equipment heat transfer efficiency. The details are as follows:

[0013]

[0014] Where: t is the time required for inactivation, t base is the benchmark inactivation time, C i is the correction coefficient, the C iIncluding the virus strain characteristic correction factor C1, aggregation state correction factor C2, matrix component correction factor C3, initial titer correction factor C4, equipment heat transfer correction factor C5, the final inactivation implementation time is increased by 20% safety threshold according to the calculated value to ensure inactivation reliability;

[0015] Preferably, the benchmark inactivation time represents the minimum heat treatment time required to achieve the inactivation effect under standard experimental conditions, wherein the standard experimental conditions are Mayinga strain, titer 8.0log 10 TCID 50 / mL, the number of non-synonymous mutations in the VP24 gene was 0, the culture medium was DMEM medium containing 2% serum, the sample volume was 0.2mL, the water bath was fully immersed, the equipment heat transfer efficiency k = 0.95, and the Mayinga strain was completely inactivated by treatment at 100℃ for 5 minutes. The t base = 5 minutes;

[0016] The strain characteristic correction coefficient C1 is detected under the above standard experimental conditions compared with the total number of non-synonymous mutations N in the VP24 gene of the Ebola virus Mayinga strain. VP24 = The time required for the complete inactivation of Ebola virus with mutation number ranging from 0 to 5 was calculated by using nonlinear regression to fit the relationship between the number of mutations and the inactivation time t. Assuming that the inactivation time increases by r for each additional mutation, then t = t base ×(1+r)^N VP24 The optimal r=0.2 is obtained by the least square method, and the strain characteristic correction coefficient C1=1.2^N VP24 ;

[0017] The aggregation correction coefficient C2 is fitted with a linear relationship C2=1+0.15A using the inactivation experiment of gradient aggregation samples under the above standard experimental conditions. A is the Ebola virus aggregation level. Different levels of A are defined according to the virus aggregation characteristics:

[0018] (1) Grade 0 indicates single particle dispersion, more than 90% of which are monomers, and clearly separated filamentous virus particles;

[0019] (2) Level 1 indicates small clusters of 5-10 particles, which are locally clustered and generally dispersed;

[0020] (3) Level 2 indicates medium-sized aggregation, with 10-50 particles aggregated to form a network structure;

[0021] (4) Level 3 indicates large aggregates, with >50 particles aggregated or precipitated, and flocculent precipitation visible to the naked eye;

[0022] The matrix component correction coefficient C3 was used to determine the complete inactivation time of the Mayinga strain under the above standard experimental conditions at a matrix serum concentration of 0%-30%. The regression analysis was ln(t)=0.049S+2.71(R 2 =0.93), converted to a multiplicative model of C3=1+0.05S, where S is the serum concentration (%);

[0023] The initial titer correction coefficient C4 was determined under the above standard experimental conditions to be 5.0-9.0 log in the initial titer range of the Mayinga strain. 10 TCID 50 / mL complete inactivation time, the benchmark titer is set to 8.0log 10 TCID 50 / mL, Δt=0.1×ln(V t / 8.0), where Δt represents the time increment, which refers to the difference between the actual inactivation time and the reference inactivation time, V t Indicates the initial titer, and the gradient initial titer inactivation experiment is used to determine the relationship between Δt and ln(V t / 8.0) is linearly related, and the slope is fitted by the least square method, and it is obtained that C4=1+0.1ln(V t / 8.0);

[0024] The heat transfer correction coefficient C5 of the equipment is constructed by measuring the heat transfer efficiency coefficient k under the above standard experimental conditions and based on Fourier's heat conduction law:

[0025]

[0026] Where: k is the heat transfer efficiency coefficient of the equipment, T 实 In order to directly measure the actual temperature inside the virus sample through the temperature sensor, T 理 The theoretical heat treatment temperature set for the equipment;

[0027] Determination of heat transfer efficiency coefficient k:

[0028]

[0029] Where η is the thermal distribution uniformity coefficient of the equipment, which is measured by infrared thermal imaging, T 实际 The actual temperature inside the virus sample is directly measured by the temperature sensor; T 理论 The target temperature set for the equipment is the theoretical heat treatment temperature required to be achieved in the inactivation plan.

[0030] Methods for evaluating the inactivation effect of Ebola virus include the following:

[0031] (1) Primary screening: Propidium azidobromide combined with qRT-PCR detection of active viral load after inactivation treatment. The target gene of qRT-PCR detection is the L gene of Ebola virus. A Ct value ≥ 40 is negative, indicating that there is no infectious virus in the sample. A Ct value < 40 is positive, indicating that there is infectious virus in the sample.

[0032] (2) Review: TCID 50 The method is combined with immunofluorescence detection to initially screen the residual virus activity of samples with a Ct value ≥ 40. The presence of a fluorescent signal is positive, indicating that the sample has viral infection activity, and the absence of a fluorescent signal is negative, indicating that the sample has no viral infection activity.

[0033] (3) Final test: The samples that were negative in the re-test were cultured blindly for three consecutive generations, and the cytopathic effect of each generation was observed. The L gene of Ebola virus was detected by qRT-PCR. If the cells grew normally without rounding or shedding lesions and the qRT-PCR could not detect the Ct value or the Ct value increased with each generation, it was judged as completely inactivated. Conversely, if the cytopathic effect was observed or the Ct value decreased with each generation, it was judged as incomplete inactivation.

[0034] Preferably, the primer sequences in the qRT-PCR reaction are shown as SEQ ID NO. 1 and 2, and the probe sequence is shown as SEQ ID NO. 3.

[0035] Compared with the prior art, the present invention has the following significant advantages:

[0036] (1) Efficient and accurate detection system

[0037] TCID 50 Combining immunofluorescence with PMA-qRT-PCR parallel testing shortens the verification cycle from 10 days to 5 days; pioneering third-generation blind transmission combined with qRT-PCR testing for biosafety verification, with sensitivity increased to 10^1 TCID 50 / mL, completely eliminating the risk of false negatives.

[0038] (2) Scientifically controllable inactivation parameters

[0039] The dry bath edge effect is eliminated by a fully immersed water bath system, which increases the inactivation efficiency at 100°C to 100%; a dynamic parameter model is established to integrate five major factors such as virus strain, matrix, and equipment, so that the data deviation of different laboratories is reduced from ±1.5log 10 TCID 50 / mL reduced to ±0.3log 10 TCID 50 / mL.

[0040] (3) Significant improvement in biosafety

[0041] Validation of experimental samples (n=120) showed that this method reduced the inactivation failure rate from 7.3% of the traditional method to 0.8% (p<0.001). BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 This is the third blind passage verification of the absence of cytopathic effect (CPE) after drying at 100°C for 10 minutes or in a water bath for 5 minutes in Example 1. Figures H1-H3 show the CPE after drying at 100°C for 10 minutes, and Figures H4-H6 show the CPE after a water bath at 100°C for 5 minutes. NC represents normal cultured cells; PC represents Ebola virus-infected cells. DETAILED DESCRIPTION

[0043] Example 1 Evaluation of Ebola virus inactivation effect

[0044] 1. Virus Sample Preparation

[0045] (1) The Zaire (Mayinga) strain of Ebola virus was used as the model strain;

[0046] (2) Establish a packaging system: the virus stock solution (initial titer 8.0log 10 TCID 50 / mL) was dispensed into 2mL sealed screw-cap tubes (made of high-temperature resistant polypropylene) at 0.2mL / tube, and the tubes were sealed and covered with biosafety film;

[0047] (3) Matrix control: the culture medium was DMEM medium containing 2% fetal bovine serum;

[0048] (4) The operating platform is a biosafety level 4 laboratory (BSL-4 laboratory).

[0049] 2. Constructing a Temperature Gradient Experiment

[0050] (1) Low temperature stability group: 4°C (medical refrigerator), room temperature (25°C, humidity control box), and 37°C (CO2 incubator) for 1 day, 2 days, and 7 days, respectively;

[0051] (2) High-temperature inactivation group: 60°C dry bath and water bath were set for 15 min, 30 min, 60 min, and 120 min, respectively; 100°C dry bath and water bath were set for 5 min and 10 min, respectively;

[0052] (3) Temperature monitoring: A K-type thermocouple thermometer (accuracy ±0.1°C) was used to record the core temperature of the sample in real time throughout the process;

[0053] (4) Inactivation termination: Immediately after heat treatment, immerse the sample tube in a pre-cooled ice bath (0-4°C) for 15 minutes.

[0054] (5) Verification of inactivation effect

[0055] Virus activity was detected using TCID 50 Combined immunofluorescence assay (TCID 50 -IFA) + propidium azide bromide combined with fluorescence quantitative PCR detection (PMA-qRT-PCR, TaqMan probe targeting the L gene).

[0056] 3.TCID 50 -IFA test process

[0057] (1) Dilution of inactivated sample: dilute in 10-fold gradient (10 -1 to 10 -8 ), 8 wells of cells (such as VeroE6, African green monkey kidney epithelial cell line, ATCC CRL-1586) were seeded at each dilution;

[0058] (2) Inoculation volume: 100 μL / well (96-well plate), culture at 37°C, 5% CO2 for 72 hours, and fix with 4% paraformaldehyde for 30 minutes;

[0059] (3) Immunofluorescence staining: 0.1% Triton X-100 permeabilization for 10 minutes, 5% BSA blocking for 1 hour, incubation with primary antibody (anti-EBOV GP, 1:1000 dilution) and secondary antibody (FITC labeled, 1:500) for 1 hour, and nuclear staining (DAPI, 1 μg / mL) for 5 minutes;

[0060] (4) Fluorescence detection: Use fluorescence microscopy or high-content imaging system to image, and the wells with fluorescent signals are positive;

[0061] (5) Titer statistics: Calculate TCID using the Reed-Muench method 50 .

[0062] 4. PMA-qRT-PCR Detection Experimental Process

[0063] PMA (Propidium Monoazide) is a membrane-impermeable dye that selectively binds to free nucleic acids or RNA or DNA from damaged viral particles, but is unable to penetrate intact viral particles. Combined with qRT-PCR, PMA pretreatment can distinguish infectious viruses (intact particles, where PMA cannot enter and RNA can be detected) from non-infectious viruses (damaged particles, where PMA binds RNA and inhibits PCR amplification). The target gene for qRT-PCR detection is the Ebola virus L gene.

[0064] (1) PMA pretreatment: Take 100 μL of inactivated virus suspension (including positive and negative controls of known titers), add PMA to a final concentration of 50 μM, and vortex to mix; stand at room temperature in the dark for 5 minutes to allow PMA to bind to free nucleic acids; expose to a blue light LED (wavelength 465 nm) for 10 minutes to activate PMA to covalently bind to nucleic acids;

[0065] (2) RNA extraction: Use a viral RNA extraction kit according to the instructions to extract viral RNA;

[0066] (3) qRT-PCR detection: The reaction system (20 μL) and amplification procedure are shown in Tables 1 and 2, respectively;

[0067] Table 1 qRT-PCR reaction system (20 μL)

[0068]

[0069] Table 2 qRT-PCR amplification procedure

[0070]

[0071] Table 3 Primer and probe sequences

[0072]

[0073] (4) Data analysis: A Ct value threshold determination experiment was conducted to determine that a Ct value ≥ 40 was negative and a Ct value < 40 was positive.

[0074] The Ct value is an indicator used in qRT-PCR to determine the presence of viral RNA in a sample. Generally, a lower Ct value indicates a higher amount of starting template.

[0075] ① Detection limit calibration experiment

[0076] Step 1: Perform 10-fold serial dilution (8.0 to 1.0 log 10 TCID 50 / mL);

[0077] Step 2: Use the same qRT-PCR reagent to detect the Ct value of each dilution, and repeat each gradient 5 times;

[0078] Step 3: Determine the Ct value corresponding to the lowest concentration that can be stably detected (Ct value standard deviation <1.0).

[0079] Table 4 Detection limit calibration experimental results

[0080]

[0081] LOD is 2.0log10 TCID 50 / mL, corresponding to a Ct threshold of ≈40 (when Ct ≥ 40, the virus titer < 2.0log 10 TCID 50 / mL, below the infection risk threshold).

[0082] ② Infectivity verification experiment

[0083] Step 1: Preparation of inactivated samples (n=50) with different Ct values ​​(35-45);

[0084] Step 2: TCID analysis of each sample 50 The detection and three-generation blind culture verification criteria for determining complete inactivation after three-generation blind culture are as follows: ① Cytopathic effect observation: cells grow normally without shrunk, shedding, or other pathological signs; ② RNA detection: no Ct value is detected or the Ct value increases with each generation;

[0085] Step 3: Statistical analysis of the correlation between Ct value and infection activity.

[0086] Table 5 Infectivity verification experiment results

[0087]

[0088] When Ct ≥ 40, no infectious virus remains in the sample (p < 0.001, Fisher's exact test). Therefore, a Ct value ≥ 40 is considered negative, indicating that there is no infectious virus in the sample, and a Ct value < 40 is considered positive, indicating that there is infectious virus in the sample.

[0089] 5. Biosafety Verification: Perform blind culture of the inactivated sample for three consecutive generations (7 days per generation). Determine complete inactivation by combining microscopic observation of cytopathic effects (normal cell growth without rounding, shedding, or other pathological signs) and RNA detection by qRT-PCR (same method as above) (no Ct value is detected or the Ct value increases with each generation).

[0090] 6. Determination of key experimental factors for Ebola virus inactivation

[0091] Obtain key experimental data on the thermal stability of Ebola virus, including ambient temperature stability and high-temperature inactivation efficiency, identify key influencing factors, and establish standardized inactivation evaluation methods.

[0092] (1) Ambient temperature stability

[0093] ①4℃ group: TCID 50 -IFA test, the virus titer remained stable on the 1st and 2nd day (8.38 to 8.08log 10 TCID 50 / mL), and decreased to 6.62log on the 7th day10 TCID 50 / mL(p<0.01);

[0094] ②Room temperature group: TCID 50 -IFA detection, decreased to 1.08log in 24 hours 10 TCID 50 / mL, the cumulative decrease was 1.6log in 48 hours 10 TCID 50 / mL, below the detection limit in 168 hours;

[0095] ③37℃ group: TCID 50 -IFA detection, 24 hours down to 1.28log 10 TCID 50 / mL, cumulative decrease of 2.3log in 48 hours 10 TCID 50 / mL, and reached below the detection limit in 168 hours.

[0096] Table 6 Ct values ​​of PMA-qRT-PCR detection of ambient temperature stability

[0097]

[0098] (2) High temperature inactivation efficiency

[0099] Table 7 High temperature inactivation efficiency results

[0100]

[0101] ① After treatment at 60℃ for 15 minutes, the titers of the dry bath and water bath groups dropped to 3.82 and 2.7 log, respectively. 10 TCID 50 / mL;

[0102] ② When treated at 100℃, 1.62 log 10 TCID 50 / mL, and it can be completely inactivated in a water bath for 5 minutes. It has been verified by three generations of blind transmission that there is no CPE and viral RNA.

[0103] ③ After the dry bath system treated the unsubmerged samples (30 μL outside the heating block) at 100°C for 10 minutes, 90% of the samples still maintained high activity (7 log 10 TCID 50 / mL), confirming that complete immersion is crucial for the inactivation effect.

[0104] 7. Inactivation effect evaluation method

[0105] Initial screening: PMA-qRT-PCR detects the active viral load after treatment. A Ct value ≥ 40 indicates that there is no infectious virus in the sample. A Ct value < 40 is positive, indicating that there is infectious virus in the sample.

[0106] Review: TCID 50 The residual virus activity after treatment was detected by immunofluorescence. If there was a fluorescent signal, it was positive, indicating that the sample had viral infection activity. If it was not inactivated, no fluorescent signal was negative, indicating that the sample had no viral infection activity.

[0107] Final test: The samples that were negative were cultured for three consecutive generations (7 days each generation), and the cytopathic effect was observed under a microscope and combined with qRT-PCR (the same method as above) (sensitivity: 10^1 TCID 50 / mL), the cells grew normally without shrunkenness, shedding or other pathological signs, and no Ct value was detected by qRT-PCR or the Ct value increased with each generation, which was determined to be completely inactivated. Conversely, if cytopathic effect was observed or the Ct value decreased with each generation, it was determined to be incompletely inactivated.

[0108] Based on the above experimental results, it can be seen that dry bath heating cannot completely inactivate the Ebola virus. A fully immersed 100°C water bath treatment for ≥5 minutes is required, and the inactivation parameters should be dynamically adjusted by comprehensively considering the key influencing factors such as virus strain type, aggregation state, matrix protein concentration, equipment heat transfer efficiency, and initial titer.

[0109] Example 2 Ebola virus dynamic inactivation method

[0110] A dynamic inactivation parameter model was established based on the key influencing factors of Ebola virus strain characteristics, aggregation state, matrix composition, initial titer and equipment heat transfer efficiency.

[0111] 1. Determination of benchmark inactivation time

[0112] Set standard conditions: initial titer 8.0log 10 TCID 50 / mL Zaire Ebola virus Mayinga strain (VP24 mutation number = 0), the culture medium is DMEM medium containing 2% fetal bovine serum, the sample volume is 0.2mL, and the heat transfer efficiency k of the heating device is 0.95. According to the inactivation effect evaluation experiment of Example 1, it can be seen that a full immersion water bath (heat transfer efficiency k = 0.95) and a treatment at 100°C for 5 minutes can completely inactivate the virus. Therefore, the benchmark inactivation time t is set base =5 minutes.

[0113] As the calculation benchmark of the multi-factor dynamic inactivation model, the processing time of other actual scenarios is obtained by correcting this benchmark time (multiplying it by the correction coefficient of each influencing factor).

[0114] 2. Constructing a correction coefficient model for virus strain characteristics (C1)

[0115] (1) Correlation between VP24 protein function and thermal stability

[0116] VP24 is a key structural protein of the Ebola virus and has the following functions:

[0117] ① Virus assembly: participates in the morphological formation of virus particles;

[0118] ②Immune escape: inhibiting interferon response by blocking the host STAT1 signaling pathway;

[0119] ③ Thermal stability: interacts with the viral matrix protein VP40 to maintain the structural integrity of viral particles.

[0120] Specific mutations in VP24 (such as Tyr79His) can significantly improve the structural stability of the virus at high temperatures by enhancing the hydrophobic interaction between proteins. The accumulation of mutations leads to conformational changes in VP24, reducing its sensitivity to heat inactivation.

[0121] (2) Number of mutations (N VP24 )

[0122] Mutation type: only non-synonymous mutations (changing amino acid sequence) are counted;

[0123] Reference sequence: The 1976 Mayinga original strain (GenBank: AF086833) was used as the benchmark;

[0124] Region delineation: Full sequence alignment of the open reading frame (ORF) of the VP24 gene.

[0125] The whole genome of 11 laboratory-collected strains (covering Zaire, Sudan, Bundibugyo, and Tai Forest strains) was sequenced, and the total number of VP24 non-synonymous mutations (N) of each strain compared with the Mayinga strain was counted. VP24 ), range 0-5.

[0126] (3) Exponential model (1.2^N VP24 ) establishment process

[0127] Experimental design:

[0128] ① Sample set: 11 strains of Ebola virus (N VP24 =0 to 5);

[0129] ② Treatment conditions: 100℃ water bath, record the time required for complete inactivation;

[0130] ③Data analysis: Nonlinear regression was used to fit the relationship between the number of mutations and inactivation time.

[0131] Mathematical model derivation:

[0132] ① Basic equation: Assuming that the inactivation time increases by r for each additional mutation, then:

[0133] t=t base ×(1+r)^N VP24

[0134] ② Parameter fitting: The optimal r=0.2(R 2 =0.91), so the formula is simplified to:

[0135] C1=1.2^N VP24

[0136] (4) Model advantages and biological significance

[0137] The improvement in viral thermal stability has a cumulative effect, and each mutation enhances heat resistance through synergistic action, which is consistent with the nonlinear characteristics of protein stability changes (free energy superposition principle).

[0138] VP24 mutations increase the proportion of α-helical structure and raise the thermal denaturation temperature by approximately 2.3°C / mutation.

[0139] The C1 model covers different subtypes (Zaire type, Sudan type, etc.) and achieves cross-strain comparability through standardized mutation counts.

[0140] 3. Constructing a correction coefficient model for aggregation status (C2)

[0141] (1) The mechanism of the impact of viral aggregation on inactivation efficiency

[0142] Physical barrier effect: Aggregated virus particles form a protective protein layer on their outer layer, hindering heat transfer to the inner virus. Steric hindrance: Tight packing reduces solution fluidity and slows heat conduction. Experimental data shows that the inactivation time of highly aggregated samples (aggregation level A = 3) is 2.3 times longer than that of monodisperse viruses.

[0143] (2) Clustering index quantification method

[0144] Table 8 Electron microscopy grading standards

[0145]

[0146] Through the inactivation experiment of gradient aggregation samples (A=0-3), a linear relationship was fitted:

[0147] C2=1+0.15A(R 2 =0.96)

[0148] For example, when A=2, the inactivation time needs to be increased by 30% (1+0.15×2=1.3).

[0149] 4. Constructing a correction coefficient model for matrix components (C3)

[0150] (1) Matrix protection effect mechanism

[0151] Protein thermal buffering: Serum albumin absorbs heat through reversible denaturation, reducing the actual thermal intensity of the virus; Viscosity effect: High protein concentration increases the viscosity of the solution and slows down heat diffusion; experimental data show that the virus inactivation time of samples containing 20% ​​serum is 2.1 times longer than that of serum-free samples.

[0152] (2) Model construction experiment

[0153] Experimental design: Treatment in a 100°C water bath, varying serum concentrations (0%-30%), and measuring the time required for complete inactivation;

[0154] Regression analysis: ln(t)=0.049×S+2.71(R 2 =0.93), S is serum concentration (%);

[0155] Convert to multiplicative model: C3=1+0.05S.

[0156] (3) Special matrix treatment

[0157] Blood samples: 10% additional processing time is required (due to the heat shielding effect of hemoglobin);

[0158] Tissue homogenate: introduction of tissue density coefficient.

[0159] 5. Constructing the Correction Factor Model for Initial Titer (C4)

[0160] (1) Theoretical basis of logarithmic relationship

[0161] Inactivation kinetic equation: log 10 N t =log 10 N0-kt

[0162] Where: N0 is the initial virus titer (log 10 TCID 50 / mL), Nt is the residual titer after treatment time t, and k is the inactivation rate constant.

[0163] To achieve complete inactivation (N t =0), the treatment time was positively correlated with the initial titer.

[0164] (2) Experimental data fitting

[0165] Experimental conditions: fixed temperature of 100°C (water bath fully immersed), virus strain was Mayinga strain (VP24 mutation number = 0), medium was DMEM medium containing 2% fetal bovine serum, initial titer range was 5.0-9.0 log 10 TCID50 / mL.

[0166] Δt=0.1×ln(V t / 8.0), where Δt represents the time increment, specifically the difference between the actual inactivation time and the reference inactivation time, V t Represents the initial titer (log10 TCID50 / mL). Quantifies the effect of changes in initial titer on inactivation time and is used to calibrate the baseline time. For example, when the initial titer increases, Δt is positive, and the treatment time should be extended; otherwise, it should be shortened.

[0167] Through the inactivation experiment of gradient initial titer (5.0-9.0log10 TCID50 / mL), it was found that Δt and ln(V t / 8.0) is linearly related (R 2 =0.98).

[0168] Table 9Δt and ln(V t / 8.0) shows a linear relationship

[0169]

[0170] Determination of the coefficient 0.1: The slope (0.098≈0.1) is fitted by the least squares method to balance prediction accuracy and operational convenience.

[0171] Virus inactivation follows an exponential decay law (first-order kinetics), with the initial titer increasing by 1 log 10 TCID50 / mL, the inactivation time needs to be extended by about 0.1×ln(10)≈0.23 minutes. t / 8.0) to convert titer changes into relative proportions to eliminate dimension effects.

[0172] Dynamic time compensation is achieved through Δt, avoiding over-inactivation (destruction of antigens) or under-inactivation (biosafety risks) of the traditional "one-size-fits-all" approach.

[0173] The benchmark titer was set to 8.0 log 10 TCID 50 / mL (standard value of Mayinga strain), so C4=1+0.1ln(V t / 8.0).

[0174] (3) Application Examples

[0175] High titer sample: V t=9.0, C4=1+0.1×ln(9 / 8)=1.012, and the inactivation time is extended by 1.2%;

[0176] Low titer sample: V t =6.0, C4=1+0.1×ln(6 / 8)=0.97, and the inactivation time is shortened by 3%.

[0177] 6. Constructing a correction coefficient model for equipment heat transfer (C5)

[0178] (1) Determination of heat transfer efficiency coefficient (k)

[0179] When Tactual / Ttheoretical ≥ 1, it indicates that the theoretical inactivation time can be directly applied (ideal heat transfer); in practical applications, Tactual / Ttheoretical < 1, the inactivation time needs to be extended to compensate for temperature loss.

[0180]

[0181] Where η is the thermal distribution uniformity coefficient of the equipment (measured by infrared thermal imaging), T 实际 The actual temperature inside the virus sample is directly measured by the temperature sensor; T 理论 The target temperature set for the equipment is the theoretical heat treatment temperature required to be achieved in the inactivation plan.

[0182] (2)T 实际 、T 理论 The technical significance of

[0183] ① Heat conduction loss: During the heating process, the actual sample temperature is often lower than the set temperature due to material thermal resistance, poor contact, or limited heat transfer efficiency of the medium. For example, when the dry bath system is set at 100°C, the core temperature of a partially immersed sample tube is only 82°C. The Tactual / Ttheoretical ratio of a fully immersed water bath can reach 0.98-1.0.

[0184] ② Uneven temperature distribution: There is a temperature gradient inside the equipment, and samples at different positions are heated at different intensities.

[0185] (3)T actual measurement specifications

[0186] ①Sensor type: Use a NIST-calibrated micro-thermocouple (diameter ≤ 1 mm) and insert it into the center of the sample tube;

[0187] ②Data recording: continuously collect temperature at a frequency of 1 Hz and take the average value during the processing period;

[0188] ③Verification requirements: Measure three sample tubes in parallel, with a temperature difference of ≤±0.5℃.

[0189] (4) Determination of T theory

[0190] ① Equipment calibration: Set the target temperature according to the equipment manual and verify the steady-state temperature through a no-load test;

[0191] ②Environmental compensation: High altitude areas need to adjust T according to the boiling point correction formula 理论 (For example, at an altitude of 2000m, the boiling point of pure water is ≈93°C).

[0192] (5) Calibration model establishment

[0193] Based on Fourier's heat conduction law, the nonlinear correction term is derived:

[0194]

[0195] When k=0.95 and Treal / Trational=1, C5=3.03 (ie, 3 times the reference time is required to compensate for heat transfer losses).

[0196] (6) Verification experiment

[0197] Dry bath system test: When k = 0.8, the model predicted inactivation time error was ±4.7%;

[0198] Industrial sterilizer verification: When k = 0.98, the deviation between actual and predicted time is less than 1 minute.

[0199] 7. Establishing a multi-factor dynamic inactivation model

[0200] The actual inactivation time (t) is calculated by the following formula:

[0201]

[0202] Where: t base is the benchmark processing time, C i The correction coefficients (key influencing factors matrix) include the virus strain characteristic correction coefficient (C1), aggregation state correction coefficient (C2), matrix component correction coefficient (C3), initial titer correction coefficient (C4), and equipment heat transfer correction coefficient (C5). The five key influencing factors are embedded in the mathematical model, and each factor corresponds to an independent correction coefficient. The product form (∏C i ) reflects the synergistic effect of multiple factors.

[0203] Table 10 Correction coefficient C i Determine the rules

[0204]

[0205] 8. Model Validation

[0206] (1) Goodness of fit: Experimental data on virus strain characteristics, aggregation state, matrix composition, initial titer, and key influencing factors of equipment heat transfer efficiency were collected for four Ebola virus subtypes (Orthoebolavirus zairense, sudanense, bundibugyoense, and taiense) according to the above method. Regression analysis was performed on 127 sets of experimental data. R 2 =0.93 (p<0.001);

[0207] (2) Prediction accuracy: A validation set (n = 30) was set aside, showing that the mean absolute error between the predicted time and the actual inactivation time was ±1.2 minutes;

[0208] (3) Safety redundancy: The final implementation time is increased by 20% of the calculated safety threshold to ensure the reliability of inactivation.

Claims

1. A method for the dynamic heating inactivation of Ebola virus, characterized in that: Set the baseline inactivation time t base The inactivation time t is calculated based on the dynamic inactivation parameter model established based on the characteristics of the Ebola virus strain, aggregation state, culture matrix composition, initial titer, and equipment heat transfer efficiency. The details are as follows: Where: t is the time required for inactivation, t base is the benchmark inactivation time, C i is the correction coefficient, the C i Including the virus strain characteristic correction coefficient C1, aggregation state correction coefficient C2, matrix component correction coefficient C3, initial titer correction coefficient C4, and equipment heat transfer correction coefficient C5, the final inactivation implementation time is increased by 20% safety threshold according to the calculated value to ensure the reliability of inactivation.

2. The method for dynamic heating inactivation of Ebola virus according to claim 1, characterized in that: The benchmark inactivation time represents the minimum heat treatment time required to achieve the inactivation effect under standard experimental conditions, wherein the standard experimental conditions are Mayinga strain, titer 8.0 log 10 TCID 50 / mL, the number of non-synonymous mutations in the VP24 gene was 0, the culture medium was DMEM medium containing 2% serum, the sample volume was 0.2mL, the water bath was fully immersed, the equipment heat transfer efficiency k = 0.95, and the Mayinga strain was completely inactivated by treatment at 100℃ for 5 minutes. The t base =5 minutes.

3. The method for dynamic heating inactivation of Ebola virus according to claim 2, characterized in that: Under standard experimental conditions, the total number of non-synonymous mutations N in the VP24 gene of the Ebola virus Mayinga strain was detected. VP24 = The time required for the complete inactivation of Ebola virus with mutation number ranging from 0 to 5 was calculated by using nonlinear regression to fit the relationship between the number of mutations and the inactivation time t. Assuming that the inactivation time increases by r for each additional mutation, then t = t base ×(1+r)^N VP24 The optimal r=0.2 is obtained by the least square method, and the strain characteristic correction coefficient C1=1.2^N VP24 .

4. The method for dynamic heating inactivation of Ebola virus according to claim 2, characterized in that: Under standard experimental conditions, the aggregation state correction coefficient C2 was fitted into a linear relationship C2=1+0.15A through the inactivation experiment of gradient aggregation samples. A is the Ebola virus aggregation level. A is defined as different levels according to the virus aggregation characteristics: (1) Grade 0 indicates single particle dispersion, more than 90% of which are monomers, and clearly separated filamentous virus particles; (2) Level 1 indicates small clusters of 5-10 particles, which are locally clustered and generally dispersed; (3) Level 2 indicates medium-sized aggregation, with 10-50 particles aggregated to form a network structure; (4) Level 3 indicates large aggregates, with >50 particles aggregated or precipitated, and flocculent precipitates visible to the naked eye.

5. The method for dynamic heating inactivation of Ebola virus according to claim 2, characterized in that: Under standard experimental conditions, the complete inactivation time of the Mayinga strain was determined under the conditions of matrix serum concentration of 0%-30%, and the regression analysis was ln(t)=0.049S+2.71(R 2 =0.93), and converted to a multiplicative model: C3=1+0.05S, where S is the serum concentration (%).

6. The method for dynamic heating inactivation of Ebola virus according to claim 2, characterized in that: Under standard test conditions, the initial titer of the Mayinga strain was determined to be in the range of 5.0-9.0 log 10 TCID 50 / mL complete inactivation time, the benchmark titer is set to 8.0log 10 TCID 50 / mL, Δt=0.1×ln(V t / 8.0), where Δt represents the time increment, which refers to the difference between the actual inactivation time and the reference inactivation time, V t Indicates the initial titer, and the gradient initial titer inactivation experiment is used to determine the relationship between Δt and ln(V t / 8.0) is linearly related, and the slope is fitted by the least square method, and it is obtained that C4=1+0.1ln(V t / 8.0).

7. The method for dynamic heating inactivation of Ebola virus according to claim 2, characterized in that: Under standard test conditions, the correction coefficient C5 of the heat transfer of the equipment is determined by measuring the heat transfer efficiency coefficient k and constructing a model based on Fourier's heat conduction law: Where: k is the heat transfer efficiency coefficient of the equipment, T 实 In order to directly measure the actual temperature inside the virus sample through the temperature sensor, T 理 The theoretical heat treatment temperature set for the equipment; Determination of heat transfer efficiency coefficient k: Where η is the thermal distribution uniformity coefficient of the equipment, which is measured by infrared thermal imaging, T 实际 The actual temperature inside the virus sample is directly measured by the temperature sensor; T 理论 The target temperature set for the equipment is the theoretical heat treatment temperature required to be achieved in the inactivation plan.

8. A method for evaluating the inactivation effect of Ebola virus, characterized in that: This includes the following methods: (1) Primary screening: Propidium azidobromide combined with qRT-PCR detection of active viral load after inactivation treatment. The target gene of qRT-PCR detection is the L gene of Ebola virus. A Ct value ≥ 40 is negative, indicating that there is no infectious virus in the sample. A Ct value < 40 is positive, indicating that there is infectious virus in the sample. (2) Review: TCID 50 The method is combined with immunofluorescence detection to initially screen the residual virus activity of samples with a Ct value ≥ 40. The presence of a fluorescent signal is positive, indicating that the sample has viral infection activity, and the absence of a fluorescent signal is negative, indicating that the sample has no viral infection activity. (3) Final test: The samples that were negative in the re-test were cultured blindly for three consecutive generations, and the cytopathic effect of each generation was observed. The L gene of Ebola virus was detected by qRT-PCR. If the cells grew normally without shrinkage, shedding or lesions and the qRT-PCR could not detect the Ct value or the Ct value increased with each generation, it was judged as completely inactivated. On the contrary, if the cytopathic effect was observed or the Ct value was detected to decrease with each generation, it was judged as incomplete inactivation.

9. The method for evaluating the inactivation effect of Ebola virus according to claim 8, wherein: The primer sequences in the qRT-PCR reaction are shown in SEQ ID NO. 1 and 2, and the probe sequence is shown in SEQ ID NO. 3.

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