Method for efficiently expressing recombinant protein by using engineering algal strain

Abstract

The invention provides a method for efficiently expressing a recombinant protein by using an engineering algal strain, and belongs to the technical field of bioinformatics and biosynthesis, the method for efficiently expressing the recombinant protein by using the engineering algal strain comprises the following steps: firstly, screening a high-quality algal strain through an expression efficiency vector, and pre-culturing under an optimized culture condition; induction parameters are accurately calculated through an induction optimization equation set, and the optimal induction effect is achieved. Then obtaining target protein through the steps of centrifugation, ultrasonication and the like, and purifying by using protein purification resin and gel filtration chromatography. The whole process is monitored through a protein expression matrix and an expression anomaly vector, and the product quality stability is ensured. According to the method, accurate control and quality guarantee of the engineering algal strain recombinant protein expression process are realized, and the technical problems of unstable yield and quality of the algal strain expression recombinant protein in the prior art are solved.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of bioinformatics, and specifically relates to a method for efficiently expressing recombinant proteins by using an engineered algal strain. BACKGROUND

[0002] Recombinant proteins are important research objects in the field of modern biological medicine, and are widely used in disease diagnosis, treatment and basic research. Traditional recombinant protein expression systems mainly include Escherichia coli, yeast and mammalian cells, etc., but these expression systems have limitations in protein yield, post-translational modification and cost. In recent years, microalgae expression system has gradually become a new choice for recombinant protein production due to its rapid growth, low cultivation cost and ability to perform eukaryotic post-translational modification. Microalgae expression system is particularly suitable for producing complex proteins such as membrane proteins, antibodies and bioactive factors, and has shown broad application prospects in the fields of medicine, agriculture and industry.

[0003] However, the microalgae expression system still faces many technical problems in practical application. First, the expression efficiency of the engineered algal strain is affected by multiple factors, including light intensity, temperature, nutritional conditions, etc. These factors have complex interactions, making it difficult to accurately control the expression process. Second, the parameter optimization during the induction expression stage mainly relies on experience judgment, lacking scientific quantitative indicators and optimization methods, resulting in large differences in expression levels between different batches. In addition, the existing expression process lacks a systematic quality monitoring system, which cannot timely discover and correct abnormal situations in the expression process, affecting the consistency of product quality.

[0004] Especially in the batch production process, due to the lack of effective parameter optimization and process control methods, the expression efficiency of the engineered algal strain and the quality of the recombinant protein often show significant fluctuations. This instability seriously restricts the industrial application of the microalgae expression system, and becomes a core technical problem to be solved in this field. That is, there is a technical problem of instability in the yield and quality of recombinant proteins expressed by algal strains in the prior art. SUMMARY

[0005] Therefore, the present application provides a method for efficiently expressing recombinant proteins by using an engineered algal strain, which can solve the technical problem of instability in the yield and quality of recombinant proteins expressed by algal strains in the prior art.

[0006] The application is implemented in the following manner: the application provides a method for efficiently expressing recombinant proteins by using engineered algae strains, which comprises the following steps: screening engineered algae strains and constructing an expression efficiency vector; pre-culturing the screened engineered algae strains; determining the density of the engineered algae strains and recording the growth curve; adding an inducing agent, calculating the induction parameters by an induction optimization equation set, and controlling the induction process; collecting the culture and centrifuging to obtain algae body precipitate; resuspending the algae body precipitate in a lysis buffer and performing ultrasonic crushing; obtaining supernatant by centrifugal separation, adding a protein purification resin for incubation; performing elution by using an elution buffer containing imidazole, collecting the recombinant proteins, and constructing a protein expression matrix; purifying the recombinant proteins by using gel filtration chromatography; determining the concentration, purity and biological activity of the purified recombinant proteins, and constructing an expression anomaly vector; when any component of the expression anomaly vector exceeds a preset threshold value, modifying the parameters of the induction optimization equation set according to the expression anomaly vector.

[0007] In the step of screening the engineered algae strains and constructing the expression efficiency vector, the algae strains with a growth rate of 1.5 to 2.5 times per 24 hours, a chlorophyll content of 3 to 8 mg per ml, and a photosynthetic efficiency greater than 15% are selected, and the expression efficiency vector is a three-dimensional row vector, and the vector elements are the growth rate, the chlorophyll content and the photosynthetic efficiency of the engineered algae strains.

[0008] In the step of pre-culturing, the screened engineered algae strains are inoculated into a culture medium containing a nitrogen source at a concentration of 10 to 15 mmol / L and a phosphorus source at a concentration of 1 to 2 mmol / L.

[0009] In the step of determining the density of the engineered algae strains and recording the growth curve, the algae strains are cultured for 48 to 72 hours under the conditions of an illumination intensity of 2000 to 3000 lux and a temperature of 25 to 28℃.

[0010] In the step of calculating the induction parameters by the induction optimization equation set and controlling the induction process, the concentration of the inducing agent is controlled to be 0.5 to 1.0 mmol / L, and the induction time is controlled to be 24 to 36 hours.

[0011] In the step of collecting the culture and centrifuging, the rotation speed is controlled to be 4000 to 5000 rpm, and the centrifugation time is controlled to be 10 to 15 minutes.

[0012] In the step of ultrasonic crushing, the ultrasonic crushing is performed for 3 to 5 minutes, the intermittent time is controlled to be 3 to 5 seconds, and the power is controlled to be 300 to 400 W.

[0013] In the step of adding the protein purification resin for incubation, the volume ratio of the protein purification resin to the supernatant is controlled to be 1:10 to 1:20, and the incubation is performed at a temperature of 4 to 8℃ for 2 to 4 hours.

[0014] The step of elution by using the elution buffer containing imidazole is specifically using the elution buffer containing imidazole with a concentration gradient of 50 to 300 millimoles per liter.

[0015] The step of purifying the recombinant protein by using gel filtration chromatography is specifically using a flow rate of 0.5 to 1.0 milliliter per minute.

[0016] The protein expression matrix is an m-row n-column matrix, wherein m is the number of batches of expression of the recombinant protein, and n is the number of parameters of expression of the recombinant protein, and the parameters of expression of the recombinant protein include yield, purity and biological activity of the recombinant protein.

[0017] Each component of the expression abnormality vector represents the deviation degree of the recombinant protein in the three quality indicators of concentration, purity and biological activity, and the preset threshold is the mean value of each component of the expression abnormality vector plus or minus twice the standard deviation.

[0018] Compared with the prior art, the method for efficiently expressing the recombinant protein by using the engineering algae strain is provided, and the method for expressing the recombinant protein by the engineering algae strain based on multi-dimensional matrix analysis and equation optimization is provided. The method realizes all-around monitoring of the expression process by constructing an expression efficiency vector, a protein expression matrix and an expression abnormality vector. The expression efficiency vector is used for evaluating the growth state of the engineering algae strain, the protein expression matrix records the expression parameters of different batches, and the expression abnormality vector can timely find the process deviation. Meanwhile, by introducing the induced optimization equation set, a quantitative optimization model of the induction parameters is established, so that the expression process is more controllable.

[0019] The method of the present application overcomes the limitations of relying on experience in the prior art. By establishing cell density induction equations, inducer concentration equations and induction time equations, the accurate calculation of key process parameters is realized. These equations comprehensively consider multiple factors such as the growth state of the engineering algae strain, the characteristics of the target protein and the culture conditions, ensuring the optimization of the induction process. In addition, the establishment of the multi-dimensional matrix analysis system provides an objective evaluation standard for the expression process, so that process abnormalities can be timely discovered and corrected.

[0020] By systematically integrating multiple optimization links, the present application successfully solves the stability problem of the engineering algae strain expressing the recombinant protein. The parameter optimization based on the mathematical model ensures the accurate control of the process, and the multi-dimensional matrix analysis system ensures the stability of the product quality. This method not only improves the expression efficiency of the recombinant protein, but more importantly, significantly improves the consistency between batches, laying a foundation for the industrial application of the microalgae expression system. In summary, the present application solves the technical problems of unstable yield and quality of the algae strain expressing the recombinant protein in the prior art. BRIEF DESCRIPTION OF DRAWINGS

[0021] Figure 1 is a flow chart of the method for efficiently expressing recombinant protein by using the engineered algal strain.

[0022] Figure 2 is a comparison chart of growth indicators of the engineered algal strain in Example 2.

[0023] Figure 3 is a curve chart of the medium nutrient concentration in Example 2.

[0024] Figure 4 is a growth curve chart of the engineered algal strain in Example 2.

[0025] Figure 5 is an analysis chart of the CD3 protein purification process in Example 2.

[0026] Figure 6 is a comparison chart of the Perforin protein expression optimization effect in Example 3. DETAILED DESCRIPTION

[0027] In order to make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application.

[0028] As shown in Figure 1 is a flow chart of a method for efficiently expressing recombinant protein by using the engineered algal strain provided by the present application, and the method comprises the following steps:

[0029] S01, screening the engineered algal strain and constructing the expression efficiency vector, selecting the algal strain with a growth rate of 1.5 to 2.5 times per 24 hours, a chlorophyll content of 3 to 8 milligrams per milliliter, and a photosynthetic efficiency greater than 15%;

[0030] S02, inoculating the screened engineered algal strain into a culture medium containing a nitrogen source concentration of 10 to 15 millimoles per liter and a phosphorus source concentration of 1 to 2 millimoles per liter for pre-culture;

[0031] S03, culturing under the conditions of an illumination intensity of 2000 to 3000 lux and a temperature of 25 to 28℃ for 48 to 72 hours, determining the density of the engineered algal strain and recording the growth curve of the engineered algal strain;

[0032] S04, adding an inducer to the culture system, calculating the induction parameters by an induction optimization equation set, and controlling the inducer concentration at 0.5 to 1.0 millimoles per liter and the induction time at 24 to 36 hours according to the induction parameters;

[0033] S05, collecting the culture and centrifuging at a speed of 4000 to 5000 revolutions per minute for 10 to 15 minutes to obtain algal body precipitate;

[0034] S06, resuspending the algal body in a lysis buffer, ultrasonic crushing for 3 to 5 minutes, intermittent time of 3 to 5 seconds, power of 300 to 400 watts;

[0035] S07, obtaining supernatant by centrifugal separation, adding protein purification resin, the volume ratio of the protein purification resin to the supernatant being 1 to 10 to 1 to 20, incubating at 4 to 8°C for 2 to 4 hours;

[0036] S08, eluting by using an elution buffer containing imidazole with a concentration gradient of 50 to 300 millimoles per liter, collecting the recombinant protein, and constructing a protein expression matrix;

[0037] S09, purifying the recombinant protein by gel filtration chromatography, flow rate being 0.5 to 1.0 milliliter per minute;

[0038] S10, determining the concentration, purity and biological activity of the purified recombinant protein, constructing an expression abnormal vector, and modifying the parameters of the induction optimization equation group in S04 according to the expression abnormal vector when any component of the expression abnormal vector exceeds a preset threshold;

[0039] The recombinant protein is any one of CD45, CD3, CD4, CD8, CD16, CD56, CD19, CD55, CD59, CD25, CD127, PD-1, CD28, CD64, CD11b, CD35, Perfori; the applicable algae include one or more of Chlamydomonas reinhardtii, Chlorella sp., Dunaliella salina, Prorocentrum minimum, Alexandrium sp., Platymonas sp., Scenedesmus sp., Euglena sp., Porphyridium sp., and Nephroselmis sp., preferably Chlamydomonas reinhardtii. The above-mentioned algal cell strains have established stable ribosome entry site sequences, chloroplast targeting sequences and endoplasmic reticulum localization sequences through long-term laboratory domestication and genetic modification, and can realize high-efficiency expression of the above-mentioned human cell surface marker antibodies.

[0040] The expression efficiency vector is a three-dimensional row vector, and the vector elements are the growth rate of the engineering algae strain, the chlorophyll content and the photosynthetic efficiency, respectively.

[0041] The protein expression matrix is an m-row n-column matrix, wherein m is the number of recombinant protein expression batches, n is the number of recombinant protein expression parameters, and the recombinant protein expression parameters include recombinant protein yield, recombinant protein purity, and recombinant protein activity;

[0042] Each component of the expression abnormality vector represents the deviation degree of the recombinant protein in concentration, purity, and biological activity. If any component exceeds the preset threshold, it indicates that the batch production is abnormal, and the production parameters need to be adjusted to guide the optimization of the expression process parameters of the next batch of recombinant protein;

[0043] The preset threshold is the mean value of each component of the expression abnormality vector plus or minus twice the standard deviation.

[0044] After such modification, the S10 step forms a closed-loop process control system with the entire patent scheme, embodying the technical advancement of the present application.

[0045] The induction optimization equation set includes a cell density induction equation, an inducer concentration equation, and an induction time equation;

[0046] The cell density induction equation is used to calculate the induction start time point, and the input parameters include the growth curve slope of the engineering algae strain, the chlorophyll content, and the engineering algae strain density, and the output parameter is the induction start time point in the induction parameter;

[0047] The inducer concentration equation is used to calculate the optimal concentration of the inducer, and the input parameters include the molecular weight of the recombinant protein, the photosynthetic efficiency, and the engineering algae strain density, and the output parameter is the inducer concentration in the induction parameter;

[0048] The induction time equation is used to calculate the induction termination time point, and the input parameters include the recombinant protein concentration, the engineering algae strain density, and the medium nutrient concentration, and the output parameter is the induction duration in the induction parameter.

[0049] The specific embodiments of the above steps are described in detail below. The specific embodiment of step S01 is for the screening of engineering algae strains and the construction of expression efficiency vectors. First, single cell sorting of engineering algae strains is performed using flow cytometry, and the sorted single cells are cultured in a medium containing a nitrogen source concentration of 12 millimoles per liter and a phosphorus source concentration of 1.5 millimoles per liter. The culture is carried out under the conditions of light intensity 2500 lux and temperature 26°C, and the cell density is measured every 24 hours to calculate the growth rate. Algae strains with a growth rate of 1.5 to 2.5 times per 24 hours are selected. The chlorophyll content is measured using a spectrophotometer. After centrifugation to collect the algae strains, 90% acetone solution is added for chlorophyll extraction. The absorbance values at 663 nanometers and 645 nanometers are measured, and the contents of chlorophyll a and chlorophyll b are calculated according to the chlorophyll content calculation formula. Algae strains with a total chlorophyll content of 3 to 8 milligrams per milliliter are selected. The photosynthetic efficiency is measured using a pulse-modulated chlorophyll fluorescence instrument. The maximum photochemical efficiency of the algae strains is measured after 20 minutes of dark adaptation, and algae strains with a photosynthetic efficiency greater than 15% are selected. The expression efficiency vectors are constructed based on the growth rate, chlorophyll content, and photosynthetic efficiency obtained by screening. Principal component analysis is used to reduce the dimensionality of the expression efficiency vectors, and algae strains with a first principal component contribution rate greater than 85% are selected as candidate engineering algae strains. The purpose of this step is to obtain engineering algae strains with excellent expression performance through multi-index screening, laying a foundation for the subsequent efficient expression of recombinant proteins. The reference value for growth rate is 2 times per 24 hours, the reference value for chlorophyll content is 5 milligrams per milliliter, and the reference value for photosynthetic efficiency is 20%.

[0050] The specific embodiment of step S02 is the pre-culture of the screened engineering algae strains. First, the medium is prepared. The nitrogen and phosphorus source stock solutions are added to sterile water in the calculated proportions, the pH value is adjusted to 7.2, and 121°C high-pressure sterilization is performed for 20 minutes. The engineering algae strains are inoculated into the sterilized medium using sterile operation, with an inoculation density of 1×10 6 cells per milliliter. Pre-culture is carried out under the conditions of light intensity 2500 lux, temperature 26°C, and light-dark cycle of 16 hours light and 8 hours dark. The nitrogen and phosphorus source concentrations in the medium are measured every 12 hours. The nitrogen concentration is measured by spectrophotometry, and the phosphorus concentration is measured by molybdenum blue colorimetry. Based on the measurement results, the nitrogen and phosphorus sources are supplemented in time to maintain the nitrogen concentration at 10 to 15 millimoles per liter and the phosphorus concentration at 1 to 2 millimoles per liter. The purpose of this step is to obtain engineering algae strains in good growth state through pre-culture, preparing for the subsequent induction expression. The reference value for nitrogen concentration is 12 millimoles per liter, and the reference value for phosphorus concentration is 1.5 millimoles per liter.

[0051] The specific implementation of step S03 is to culture the engineered algal strain and record the growth curve. The engineered algal strain is cultured for 48 to 72 hours under light intensity of 2000 to 3000 lux and temperature of 25 to 28°C, and the density of the engineered algal strain is measured every 6 hours by using a hemocytometer. The measured density data is converted into natural logarithm, and the growth curve is fitted by using the least squares method to calculate the slope of the growth curve. The growth curve is predicted by using a recurrent neural network to predict the trend of cell density change in the next 24 hours. At the same time, the cell morphology is observed by using an optical microscope, and parameters such as cell size and movement state are recorded. The cell cycle is analyzed by using a flow cytometer, and the proportions of G1, S and G2 / M phase cells are calculated. The purpose of this step is to monitor the growth state of the engineered algal strain to provide a basis for determining the optimal induction time point. The reference value of the density of the engineered algal strain is 5×10 6

[0052] The specific implementation of step S04 is to calculate the induction parameters by induction optimization equation system and perform induction. First, the induction start time point is calculated according to the cell density induction equation, which uses a fuzzy neural network algorithm to take the slope of the growth curve of the engineered algal strain, the chlorophyll content and the density of the engineered algal strain as input variables, and calculates the optimal induction start time point by the trained neural network. Then, the optimal concentration of the inducer is calculated according to the inducer concentration equation, which uses a genetic algorithm optimization to take the molecular weight of the recombinant protein, the photosynthetic efficiency and the density of the engineered algal strain as parameters of the fitness function, and calculates the optimal inducer concentration by iterative optimization. Finally, the induction duration is calculated according to the induction time equation, which uses a support vector regression algorithm to take the concentration of the recombinant protein, the density of the engineered algal strain and the nutrient concentration of the culture medium as feature vectors, and predicts the optimal induction duration by the trained model. The induction process is controlled according to the calculated induction parameters, and the inducer concentration is controlled at 0.5 to 1.0 millimole per liter, and the induction time is controlled at 24 to 36 hours. The purpose of this step is to improve the expression efficiency of the recombinant protein by optimizing the induction parameters. The reference value of the inducer concentration is 0.8 millimole per liter, and the reference value of the induction time is 30 hours.

[0053] ​The specific implementation of step S05 is to collect the culture and perform centrifugation. The culture is collected using a continuous flow centrifuge at a speed of 4000 to 5000 revolutions per minute for 10 to 15 minutes. A temperature sensor is used to monitor the temperature of the centrifuge cavity in real time during centrifugation to ensure that the temperature is maintained at about 4°C. After centrifugation, the algal body precipitate is collected using sterile operation, and the supernatant is collected for medium component analysis. The conductivity of the supernatant is measured using a conductivity meter, and the pH value of the supernatant is measured using a pH meter. The metabolic state during the culture process is evaluated based on the measurement results. The algal body precipitate is weighed and recorded, and the biomass yield is calculated. The purpose of this step is to obtain the target algal body by centrifugal separation, preparing for subsequent lysis and purification. The reference value of the speed is 4500 revolutions per minute, the reference value of the centrifugation time is 12 minutes, and the reference value of the biomass yield is 2 grams of dry weight per liter.

[0054] The specific implementation of step S06 is to perform ultrasonic disruption of the algal body. First, prepare the lysis buffer, which contains 50 millimoles per liter of phosphate buffer, 150 millimoles per liter of sodium chloride, 1 millimole per liter of EDTA, 1 millimole per liter of PMSF, and 10% glycerol, with a pH value adjusted to 7.4. The algal body precipitate is resuspended at a ratio of 10 milliliters of lysis buffer per gram of wet weight, and mixed thoroughly using a vortex shaker. The resuspended solution is transferred to an ultrasonic disruptor equipped with an ice bath, and set to an ultrasonic power of 300 to 400 watts. The disruption is performed using an intermittent ultrasonic mode, with each ultrasonic treatment lasting 3 to 5 seconds and the intermittent time being 3 to 5 seconds, for a total disruption time of 3 to 5 minutes. A temperature sensor is used to monitor the sample temperature in real time during ultrasonic treatment to ensure that the temperature does not exceed 10°C. After ultrasonic treatment, the disruption effect is observed using an optical microscope, and the disruption rate is calculated. The purpose of this step is to release the intracellular recombinant protein under mild disruption conditions, while avoiding protein degradation. The reference value of the ultrasonic power is 350 watts, the reference value of the disruption time is 4 minutes, and the reference value of the disruption rate is 95%.

[0055] The specific implementation of step S07 is to purify the recombinant protein by affinity chromatography. First, centrifuge the broken sample at 10000 rpm for 15 minutes at 4°C, and collect the supernatant. Determine the total protein concentration in the supernatant by the Bradford method, and preliminarily detect the expression amount of the target protein by immunoblotting. According to the detection result, calculate the amount of protein purification resin, and control the volume ratio of protein purification resin to supernatant between 1 to 10 and 1 to 20. Add the equilibrated protein purification resin to the supernatant, and gently stir at 4 to 8°C for 2 to 4 hours. Adjust the stirring speed using the adaptive fuzzy control algorithm, and adjust the stirring parameters in real time according to the sample temperature and mixing uniformity. After incubation, transfer the mixture to a chromatography column, and control the flow rate at 1 ml / min using a peristaltic pump. The purpose of this step is to preliminarily enrich the target protein through specific binding. The reference value of the amount of resin is 5% of the volume of the supernatant, and the reference value of the incubation time is 3 hours.

[0056] The specific implementation of step S08 is gradient elution. Elution is performed using an increasing concentration gradient of imidazole solution, with the imidazole concentration gradually increasing from 50 mmol / L to 300 mmol / L, with a total of 6 concentration gradient points. Collect 5 column volumes of eluate at each gradient point, and monitor the absorbance at 280 nm online using a UV spectrophotometer. Perform SDS polyacrylamide gel electrophoresis analysis on the collected eluate, and perform gray scale scanning of the electrophoresis results using a gel imaging system to calculate the relative content of each component. According to the electrophoresis analysis results, combine the elution components with higher target protein content, and construct a protein expression matrix. Use multivariate statistical analysis methods to analyze the expression matrix, and calculate the correlation between each expression parameter. The purpose of this step is to obtain high-purity target protein through gradient elution, and to quantitatively evaluate the expression process. The reference values of the imidazole concentration gradient are 50, 100, 150, 200, 250, and 300 mmol / L.

[0057] The specific implementation of step S09 is to perform gel filtration chromatography. First, the protein sample obtained in step S08 is concentrated by centrifugation of an ultrafiltration centrifuge tube at 4°C and 4000 revolutions per minute, and the sample volume is concentrated to 1 / 10 of the original volume. The concentrated sample is filtered through a 0.22 micron filter to remove insoluble impurities that may be present. Gel filtration chromatography is performed using a high-performance liquid chromatography system, a gel filtration column with a suitable molecular weight fractionation range is selected, and the mobile phase is phosphate buffer with a flow rate controlled at 0.5 to 1.0 milliliters per minute. The sample is injected using an automatic sampler, and the absorbance values at multiple wavelengths are detected simultaneously by a diode array detector. The chromatogram is analyzed using chromatography workstation software to calculate the retention time, peak area, and theoretical plate number of each peak. The molecular weight of the target protein is calculated based on the calibration curve of the standard proteins. The purpose of this step is to further improve the purity of the protein by molecular sieving effect, and to obtain a protein sample with good monodispersity. The reference value of the flow rate is 0.8 milliliters per minute, and the reference value of the theoretical plate number is 8000.

[0058] The specific implementation of step S10 is to evaluate the quality of the purified recombinant protein. The protein concentration is determined by the Bradford method, and bovine serum albumin is used as a standard to prepare a standard curve. The protein purity is determined by SDS polyacrylamide gel electrophoresis and high-performance liquid chromatography, and the purity value is calculated by gel scanning and peak area integration. The biological activity of the protein is evaluated by enzyme-linked immunosorbent assay and cell function test, and the activity recovery rate is calculated. The measured concentration, purity and activity data are arranged according to batch, and a protein expression matrix is constructed. The standard deviation of each column of data in the expression matrix is calculated to construct an expression abnormality vector. The expression abnormality vector is analyzed using principal component analysis to identify key factors affecting expression quality. Hierarchical clustering analysis is used to classify the expression data of different batches to evaluate the stability of the process. The purpose of this step is to ensure the availability of the recombinant protein through comprehensive quality evaluation, and to provide a basis for process optimization. The reference value of the protein concentration is 1 milligram per milliliter, the reference value of the purity is 95%, and the reference value of the activity recovery rate is 80%.

[0059] The formulas or equations related to the present application are described in detail as follows.

[0060] 1. The construction of the expression efficiency vector is shown as follows:

[0061] E = [α, β, γ];

[0062] In the formula, α is the growth rate of the engineered algal strain; β is the chlorophyll content; γ is the photosynthetic efficiency; and E is the expression efficiency vector.

[0063] Wherein, the parameter acquisition method is:

[0064] α is calculated by measuring the cell density every 24 hours: where N t is the cell density at time t, N0 is the initial cell density, and t is the culture time;

[0065] β is determined by spectrophotometer: β = 20.2D 645 + 8.02D 663 , where D 645 is the absorbance at 645 nm, and D 663 is the absorbance at 663 nm;

[0066] γ is determined by chlorophyll fluorometer: where F m is the maximum fluorescence value, and F0 is the initial fluorescence value.

[0067] 2. The cell density induction equation is expressed as follows:

[0068]

[0069] where T i is the induction starting time point; α is the growth curve slope; β is the chlorophyll content; N is the engineered algal strain density; β0 is the reference chlorophyll content, which is 5 mg / mL; N0 is the reference cell density, which is 1 x 10 6 per mL; k1, k2, k3, and k4 are weight coefficients; ε1 is the error term, which is in the range of 0.1-0.3; the logarithmic term reflects the nonlinear effect of the growth rate, the exponential term embodies the saturation effect of the chlorophyll content, and the square root term represents the decreasing effect of the cell density.

[0070] The construction process of the cell density induction equation is as follows:

[0071] First, a basic data matrix is established

[0072] where t i is the optimal induction time point; α i is the growth curve slope; β i is the chlorophyll content; N i is the engineered algal strain density; and n is the number of historical data sets.

[0073] The construction process includes the following steps:

[0074] Step 1: The importance of each parameter is determined by principal component analysis to obtain a contribution degree vector W = [ω1, ω2, ω3], where ω i represents the contribution degree of the i-th parameter.

[0075] Step 2: A nonlinear regression method is used to fit different function forms for each parameter, respectively:

[0076] f1(a) = k1ln(a) reflects the logarithmic effect of growth rate;

[0077] f2(b) = k2exp(b / b0) reflects the saturation effect of chlorophyll;

[0078] reflects the diminishing effect of cell density;

[0079] Step 3: Introduce interaction terms reflects the coupling between parameters;

[0080] Step 4: Optimize coefficients by least squares method to obtain the final equation.

[0081] 3, the concentration of inducer equation is shown as follows:

[0082]

[0083] In the formula, C i is the inducer concentration; M is the molecular weight of recombinant protein; γ is the photosynthetic efficiency; N is the density of engineering algae; N0 is the reference cell density, taking the value of 1 × 10 6 6 per milliliter; p1, p2, p3, p4 are weight coefficients; ε2 is the error term, ranging from 0.05 to 0.15; the square root term reflects the nonlinear relationship between molecular weight and inducer demand, the square term embodies the enhancement effect of photosynthetic efficiency, and the logarithmic term represents the slow-changing effect of cell density.

[0084] Wherein, the construction process of the inducer concentration equation is:

[0085] First, the response surface design matrix is established

[0086] In the formula, C i is the optimal inducer concentration; M i is the molecular weight of recombinant protein; γ i is the photosynthetic efficiency; N i is the density of engineering algae; m is the number of experimental groups.

[0087] The construction steps include:

[0088] Step 1: Use partial least squares method to analyze the influence degree of each factor on the inducer concentration;

[0089] Step 2: According to the molecular weight and inducer binding kinetics, introduce M 0.5 term;

[0090] Step 3: Based on the relationship between photosynthetic efficiency and energy supply, introduce γ 2 term;

[0091] Step 4: ln(N / N0) term was introduced to consider the saturation effect of cell density;

[0092] Step 5: interaction term was introduced to reflect the balance between protein synthesis and cell density.

[0093] 4. Induction time equation is expressed as follows:

[0094]

[0095] where D i is induction duration; P is recombinant protein concentration; N is engineered algal strain density; S is medium nutrient concentration; P0 is reference protein concentration, taking value of 0.1 mg / ml; N c is critical cell density, taking value of 5 x 10 6 6 / ml; S0 is reference nutrient concentration, taking value of 10 mmol / L; q1, q2, q3, q4 are weight coefficients; ε3 is error term, ranging from 0.2 to 0.4; logarithmic term reflects the gradual process of protein accumulation, exponential decay term embodies the inhibitory effect of cell density, and square root term represents the efficiency change of nutrient utilization.

[0096] The construction process of induction time equation is as follows:

[0097] Establish time series matrix

[0098] where D i is optimal induction time; P i is protein concentration; N i is cell density; S i is nutrient concentration; k is observation point number.

[0099] The construction steps include:

[0100] Step 1: dynamic characteristics of each parameter are determined through time series analysis;

[0101] Step 2: ln(P / P0) term is introduced based on protein accumulation law;

[0102] Step 3: exp(-N / N c ) term is introduced to consider the inhibitory effect of cell density;

[0103] Step 4: term is introduced according to nutrient utilization efficiency;

[0104] Step 5: interaction term is added to reflect the relationship between protein synthesis and cell metabolism.

[0105] ​All the benchmark values and critical values are obtained by statistical analysis of experimental data: β0: determined by measuring the average chlorophyll content of multiple batches of normally growing algae strains; N0: determined according to the inoculation density and cell growth characteristics; P0: determined based on the detection limit of recombinant protein expression; N c : determined by cell growth inhibition experiment; S0: determined according to medium formula optimization experiment.

[0106] 5. The protein expression matrix is represented as follows:

[0107]

[0108] In the formula, Y ij represents the jth expression parameter of the ith batch, j = 1, 2, 3 corresponding to yield, purity, and activity, respectively.

[0109] 6. The expression abnormality vector is represented as follows:

[0110] V = [σ1, σ2, σ3];

[0111] In the formula, is the average value of the jth column.

[0112] 7. The contribution rate calculation in principal component analysis is represented as follows:

[0113]

[0114] In the formula, R i is the contribution rate of the ith principal component; λ i is the ith eigenvalue; when R1> 85%, the algae strain is selected as a candidate engineering algae strain.

[0115] 8. The growth curve fitting equation is represented as follows:

[0116] lnN(t) = kt + b + ε4;

[0117] In the formula, N(t) is the cell density at time t; k is the growth curve slope; b is the intercept; ε4is the error term, ranging from 0.05 to 0.15.

[0118] 9. The recurrent neural network prediction equation is represented as follows:

[0119] N t+1 = f(W h h t +W x N t +b h )+ε5;

[0120] In the formula, N t+1 is the predicted cell density at the next time; h t is the hidden state; Wh x h

[0121] 10、Breakage rate is calculated as follows:

[0122]

[0123] wherein η is the breakage rate; N b is the number of broken cells; N t is the total number of cells; the breakage rate threshold is 95%.

[0124] 11、Purity of elution peak is calculated as follows:

[0125]

[0126] wherein P is the protein purity; A t is the peak area of target protein; A s is the total peak area; the purity threshold is 95%.

[0127] 12、Activity recovery rate is calculated as follows:

[0128]

[0129] wherein R is the activity recovery rate; U p is the activity after purification; U0 is the activity before purification; the activity recovery rate threshold is 80%.

[0130] 13、Abnormal expression vector threshold is calculated as follows:

[0131] Δ = [0.2, 0.1, 0.15];

[0132] wherein the three components of the vector correspond to the standard deviation thresholds of yield, purity and activity respectively, and when any component exceeds the corresponding threshold, the parameters of the induction optimization equation set need to be corrected.

[0133] Specifically, the principle of the present application is that the core principle of the present application is to establish a complete optimization and monitoring system for the expression process of an engineering algal strain. First, theoretically, the expression efficiency of a recombinant protein is closely related to the physiological state of an engineering algal strain. The introduction of an expression efficiency vector realizes accurate evaluation of the physiological state of an engineering algal strain by monitoring three key indicators, i.e., growth rate, chlorophyll content and photosynthetic efficiency. These indicators can reflect the growth vigor, photosynthetic efficiency and metabolic capacity of the algal strain, and provide a scientific basis for determining the optimal induction timing.

[0134] ​​​The design of induction optimization equations is based on the growth kinetics and protein synthesis mechanism of the engineering algal strain. The cell density induction equation considers the growth cycle characteristics of the engineering algal strain, and determines the physiological state of the cells in the most suitable induction by analyzing the slope of the growth curve and the change in chlorophyll content. The inducer concentration equation is based on the molecular characteristics of the target protein and the metabolic capacity of the algal strain to calculate the optimal induction intensity. The induction time equation ensures that the induction is terminated when the protein accumulation reaches a maximum while the cell viability has not yet decreased by monitoring the protein expression level and the medium nutrient status.

[0135] The introduction of the protein expression matrix and the expression abnormality vector establishes a data-driven quality control system. The protein expression matrix records the expression data of multiple batches, and the relationship between the process parameters and the expression effect is revealed through statistical analysis. The expression abnormality vector realizes early warning of abnormal situations by calculating the deviation of key parameters. This data-based monitoring method ensures the controllability of the process and the stability of the product quality.

[0136] A specific embodiment 1 of the present application is provided below, and the specific implementation of each step in embodiment 1 is described in detail as follows.

[0137] The specific implementation of step S01 is the screening of the engineering algal strain and the construction of the expression efficiency vector. First, flow cytometry is used to sort single cells of the engineering algal strain, and the sorted single cells are cultured in a medium containing a nitrogen source concentration of 12 millimoles per liter and a phosphorus source concentration of 1.5 millimoles per liter. The culture is carried out under the conditions of light intensity 2500 lux and temperature 26°C, and the cell density is measured every 24 hours. The evaluation is carried out according to the expression efficiency vector E = [α, β, γ]. The growth rate α is calculated by measuring the cell density: N t is the cell density at time t, N0 is the initial cell density, and t is the culture time. Algal strains with a growth rate of 1.5 to 2.5 times per 24 hours are selected. The chlorophyll content β is measured by a spectrophotometer: β = 20.2D 645 + 8.02D 663 , D 645 is the absorbance at 645 nanometers, and D 663 is the absorbance at 663 nanometers. Algal strains with a total chlorophyll content of 3 to 8 milligrams per milliliter are selected. The photosynthetic efficiency γ is measured by a chlorophyll fluorometer: F m is the maximum fluorescence value, and F0 is the initial fluorescence value. Algal strains with a photosynthetic efficiency greater than 15% are selected. Principal component analysis is used to reduce the dimension of the expression efficiency vector, and the principal component contribution rate is calculated: R i is the contribution rate of the i-th principal component, and λ iFor the ith characteristic value, select the first principal component contribution rate greater than 85% of the algae strain as the candidate engineering algae strain. The reference value of the growth rate is 2 times per 24 hours, the reference value of the chlorophyll content is 5 mg per ml, and the reference value of the photosynthetic efficiency is 20%. This step obtains an engineering algae strain with excellent expression performance through multi-index screening, laying a foundation for efficient expression of recombinant proteins in the subsequent step.

[0138] The specific implementation of step S02 is to pre-culture the screened engineering algae strain. First, prepare the culture medium, add the nitrogen source and phosphorus source stock solution to sterile water according to the calculated proportion, adjust the pH value to 7.2, and autoclave at 121°C for 20 minutes. Sterile operation is used to inoculate the engineering algae strain into the sterilized culture medium, and the inoculation density is 1×10 6 cells per ml. Pre-culture under the conditions of light intensity 2500 lux, temperature 26°C, and light-dark cycle of 16 hours light and 8 hours dark. Sample every 12 hours to determine the concentration of nitrogen source and phosphorus source in the culture medium, determine the nitrogen source concentration by spectrophotometry, determine the phosphorus source concentration by molybdenum blue colorimetry, and supplement the nitrogen source and phosphorus source in time according to the determination results to maintain the nitrogen source concentration at 10 to 15 mmol / L and the phosphorus source concentration at 1 to 2 mmol / L. The nutrient concentration matrix is represented as: where N t and P t are the nitrogen source and phosphorus source concentrations at time t. This step obtains engineering algae strains with good growth status through pre-culture, preparing for subsequent induction expression. The reference value of the nitrogen source concentration is 12 mmol / L, and the reference value of the phosphorus source concentration is 1.5 mmol / L.

[0139] The specific implementation of step S03 is to culture the engineering algae strain and record the growth curve. Culture under the conditions of light intensity 2000 to 3000 lux and temperature 25 to 28°C for 48 to 72 hours, and determine the engineering algae strain density every 6 hours by using a hemocytometer. Fit according to the growth curve fitting equation lnN(t) = kt + b + ε4, where N(t) is the cell density at time t, k is the growth curve slope, b is the intercept, and ε4 is the error term with a range of 0.05 to 0.15. Use the recurrent neural network prediction equation N t+1 = f(W h h t +W x N t +b h )+ε5 to predict the cell density trend in the next 24 hours, where N t+1 is the predicted cell density at the next time, h t is the hidden state, W h and W x are weight matrices, and b his the bias term, f is the activation function, ε5is the error term and ranges from 0.1 to 0.2. Meanwhile, the cell morphology is observed by optical microscope, and the parameters such as cell size and movement state are recorded. The cell cycle is analyzed by flow cytometry, and the proportions of G1, S and G2 / M phase cells are calculated. The cell cycle distribution matrix is established wherein G i1 , S i1 , and M i1 represent the proportions of G1, S and G2 / M phase cells at the i th time point, respectively. This step provides the basis for determining the optimal induction time point by monitoring the growth state of the engineered algal strain. The reference value of the engineered algal strain density is 5 x 10 6 cells per milliliter, the reference value of the growth curve slope is 0.15, and the reference value of the proportion of G1 phase cells is 60%.

[0140] The specific implementation of step S04 is to calculate the induction parameters and perform induction by induction optimization equations. First, the basic data matrix is constructed wherein t i is the optimal induction time point, a i is the growth curve slope, β i is the chlorophyll content, N i is the engineered algal strain density, and n is the number of historical data sets. The induction start time point is calculated according to the cell density induction equation wherein β0is the reference chlorophyll content with a value of 5 milligrams per milliliter, N0is the reference cell density with a value of 1 x 10 6 cells per milliliter, k1, k2, k3, and k4 are weight coefficients, and ε1is the error term ranging from 0.1 to 0.3. Then, the optimal induction agent concentration is calculated according to the induction agent concentration equation wherein M is the molecular weight of the recombinant protein, γ is the photosynthetic efficiency, p1, p2, p3, and p4 are weight coefficients, and ε2is the error term ranging from 0.05 to 0.15. Finally, the induction duration is calculated according to the induction time equation wherein P is the recombinant protein concentration, S is the medium nutrient concentration, P0is the reference protein concentration with a value of 0.1 milligram per milliliter, N c is the critical cell density with a value of 5 x 10 6 cells per milliliter, S0is the reference nutrient concentration with a value of 10 millimoles per liter, q1, q2, q3, and q4 are weight coefficients, and ε3is the error term ranging from 0.2 to 0.4. The induction process is controlled according to the calculated induction parameters, the induction agent concentration is controlled at 0.5 to 1.0 millimoles per liter, and the induction time is controlled at 24 to 36 hours. This step improves the expression efficiency of the recombinant protein by optimizing the induction parameters. The reference value of the induction agent concentration is 0.8 millimoles per liter, and the reference value of the induction time is 30 hours.

[0141] The specific implementation of step S05 is to collect the culture and centrifuge. The culture is collected by a continuous flow centrifuge at a speed of 4000 to 5000 revolutions per minute for 10 to 15 minutes. A temperature sensor is used to monitor the temperature of the centrifuge cavity in real time during centrifugation to ensure that the temperature is maintained at about 4°C. After centrifugation, the algal body precipitate is collected by sterile operation, and the supernatant is collected for medium component analysis. The conductivity of the supernatant is measured by a conductivity meter, and the pH value of the supernatant is measured by a pH meter. The metabolic state during the culture is evaluated according to the measurement results. The algal body precipitate is weighed and recorded, and the biomass yield is calculated wherein M d is the dry weight mass, V is the culture volume, and t is the culture time. This step separates the target algal body by centrifugation, preparing for subsequent lysis and purification. The reference value of the speed is 4500 revolutions per minute, the reference value of the centrifugation time is 12 minutes, and the reference value of the biomass yield is 2 grams of dry weight per liter.

[0142] The specific implementation of step S06 is to perform ultrasonic disruption on the algal body. First, prepare the lysis buffer, which contains 50 millimoles per liter of phosphate buffer, 150 millimoles per liter of sodium chloride, 1 millimole per liter of EDTA, 1 millimole per liter of PMSF, and 10% glycerol, with a pH value adjusted to 7.4. The algal body precipitate is resuspended at a ratio of 10 milliliters of lysis buffer per gram of wet weight, and mixed well by a vortex shaker. The disruption rate is calculated using the formula wherein η is the disruption rate, N b is the number of disrupted cells, and N t is the total number of cells. The resuspended solution is transferred to an ultrasonic disruptor equipped with an ice bath, and the ultrasonic power is set to 300 to 400 watts. The disruption is performed in an intermittent ultrasonic mode, with each ultrasonic treatment lasting 3 to 5 seconds and the intermittent time being 3 to 5 seconds. The total disruption time is 3 to 5 minutes. A temperature sensor is used to monitor the sample temperature in real time during ultrasonic treatment to ensure that the temperature does not exceed 10°C. A disruption parameter matrix is established wherein P i is the ultrasonic power, t i is the disruption time, and T i is the sample temperature. After ultrasonic treatment, the disruption effect is observed by an optical microscope, and the disruption rate is calculated by image analysis software. This step releases the intracellular recombinant protein by mild disruption conditions while avoiding protein degradation. The reference value of the ultrasonic power is 350 watts, the reference value of the disruption time is 4 minutes, and the reference value of the disruption rate is 95%.

[0143] The specific embodiment of step S07 is to purify the recombinant protein by affinity chromatography. First, centrifuge the broken sample at 10000 rpm for 15 minutes at 4°C, and collect the supernatant. Determine the total protein concentration in the supernatant by the Bradford method, and preliminarily detect the expression amount of the target protein by immunoblotting. The protein concentration standard curve equation is A=kC+b, where A is the absorbance value at 595 nm, C is the protein concentration, k is the slope, and b is the intercept. Calculate the amount of protein purification resin according to the test results, and control the volume ratio of protein purification resin to supernatant to be between 1:10 and 1:20. Add the equilibrated protein purification resin to the supernatant, and gently stir at 4-8°C for 2-4 hours. Adjust the stirring speed using the adaptive fuzzy control algorithm, and the stirring speed control equation is where v is the stirring speed, v0 is the initial speed, ΔT is the temperature deviation, k p and k d are the proportional and differential coefficients, respectively. Establish the stirring parameter matrix where v i is the stirring speed, T i is the temperature, and H i is the mixing uniformity. After incubation, transfer the mixture to a chromatography column, and control the flow rate to be 1 ml / min using a peristaltic pump. This step achieves preliminary enrichment of the target protein through specific binding. The reference value of the resin amount is 5% of the supernatant volume, and the reference value of the incubation time is 3 hours.

[0144] The specific embodiment of step S08 is gradient elution. Elution is performed using an increasing concentration gradient of imidazole solution, with the imidazole concentration gradually increasing from 50 mmol / L to 300 mmol / L, with a total of 6 concentration gradient points. The elution peak purity calculation formula is where P is the protein purity, A t is the target protein peak area, and A s is the total peak area. Collect 5 column volumes of eluate at each gradient point, and monitor the absorbance value at 280 nm online using a UV spectrophotometer. Establish the elution curve data matrix where C i is the imidazole concentration, A i is the absorbance value, and V i is the elution volume. Analyze the collected eluate by SDS polyacrylamide gel electrophoresis, perform gray scale scanning of the electrophoresis results using a gel imaging system, and calculate the relative content of each component. According to the electrophoresis analysis results, combine the elution components with higher target protein content, and construct the protein expression matrix where Y ijrepresents the jth expression parameter of the ith batch, j = 1, 2, 3 respectively corresponding to yield, purity, activity. The expression matrix is analyzed by using multivariate statistical analysis method, and the correlation between each expression parameter is calculated. This step obtains high-purity target protein by gradient elution, and quantitatively evaluates the expression process. The reference value of imidazole concentration gradient is 50, 100, 150, 200, 250, 300 millimoles per liter.

[0145] The specific implementation of step S09 is to perform gel filtration chromatography. First, the protein sample obtained in step S08 is concentrated, and the sample volume is concentrated to 1 / 10 of the original volume by centrifugation of an ultrafiltration centrifuge tube at 4°C and 4000 revolutions per minute. The concentrated sample is filtered through a 0.22 micron filter membrane to remove insoluble impurities that may be present. Gel filtration chromatography is performed using a high-performance liquid chromatography system, a gel filtration column with a suitable molecular weight fractionation range is selected, and the mobile phase is phosphate buffer with a flow rate controlled at 0.5 to 1.0 milliliters per minute. The chromatographic parameter matrix is established where t i is the retention time, A i is the peak area, and N i is the theoretical plate number. The sample is injected by an automatic sampler, and the absorbance values at multiple wavelengths are detected simultaneously by a diode array detector. The chromatogram is analyzed by using chromatography workstation software to calculate the retention time, peak area, and theoretical plate number of each peak. The molecular weight of the target protein is calculated according to the calibration curve of the standard protein logM = k x t R +b, where M is the molecular weight, t R is the relative retention time, k is the slope, and b is the intercept. This step further improves the purity of the protein by the molecular sieve effect, and obtains a protein sample with good monodispersity. The reference value of the flow rate is 0.8 milliliters per minute, and the reference value of the theoretical plate number is 8000.

[0146] The specific implementation of step S10 is to evaluate the quality of the purified recombinant protein. The protein concentration is determined by the Bradford method, and bovine serum albumin is used as a standard to prepare a standard curve. SDS polyacrylamide gel electrophoresis and high-performance liquid chromatography are used to determine the purity of the protein. Enzyme-linked immunosorbent assay and cell function test are used to evaluate the biological activity of the protein, and the activity recovery rate calculation formula is where R is the activity recovery rate, U p is the activity after purification, and U0 is the activity before purification. The measured concentration, purity, and activity data are arranged according to the batch, and a protein expression matrix is constructed. The standard deviation of each column of data in the expression matrix is calculated, and an expression anomaly vector V = [σ1, σ2, σ3] is constructed, where The average value of the jth column is set. Set the expression abnormal vector threshold value Δ = [0.2, 0.1, 0.15], when any component exceeds the corresponding threshold value, the parameters of the induced optimization equation set need to be corrected. The principal component analysis method is used to analyze the expression abnormal vector, and the key factors affecting the expression quality are identified. The hierarchical clustering analysis method is used to classify the expression data of different batches, and the stability of the process is evaluated. This step ensures the availability of the recombinant protein through comprehensive quality evaluation, and provides the basis for process optimization. The reference value of the protein concentration is 1 milligram per milliliter, the reference value of the purity is 95%, and the reference value of the activity recovery rate is 80%.

[0147] In order to better understand and implement the present application, two specific application scenarios of the present application are provided below: Example 2, high-efficiency expression of CD3 protein: A certain biological pharmaceutical research team uses the method of the present application to express CD3 protein. First, the engineering algae strains are screened, and flow cytometry is used to sort 10 engineering algae strains, and various growth indicators are measured, as shown in Table 1:

[0148] Table 1 Growth indicators of engineering algae strains

[0149] Strain No. Growth rate (times / 24h) Chlorophyll content (mg / mL) Photosynthetic efficiency (%) YS01 1.8 4.2 16.8 YS02 2.1 5.5 19.2 YS03 1.6 3.8 15.4 YS04 2.3 6.1 21.5 YS05 1.9 4.8 17.6 YS06 1.7 4.1 16.2 YS07 2.2 5.8 20.3 YS08 1.5 3.5 14.8 YS09 2.0 5.2 18.5 YS10 1.8 4.5 17.1

[0150] Figure 2 Comparison chart of engineering algae strain growth indicators: This chart shows the comparison of three key growth indicators (growth rate, chlorophyll content and photosynthetic efficiency) of 10 engineering algae strains. Using a grouped column chart, the advantages of YS04 and YS07 in each indicator are clearly shown. According to the determination results, the expression efficiency vector E = [α, β, γ] is constructed, and after principal component analysis, YS04 and YS07 are selected for subsequent experiments. The selected engineering algae strains are inoculated in the pre-culture medium, and the concentration changes of nitrogen and phosphorus sources in the medium are monitored every 12 hours, as shown in Table 2:

[0151] Table 2 Monitoring table of medium nutrient concentration

[0152] Time (h) Nitrogen source concentration (mM) Phosphorus source concentration (mM) 0 12.0 1.5 12 10.8 1.3 24 9.5 1.1 36 11.2 1.4 48 10.1 1.2

[0153] Figure 3 Nutrient concentration change curve of culture medium: This chart uses a double-Y-axis curve to show the dynamic changes of nitrogen and phosphorus source concentrations during the culture process. The blue curve represents the nitrogen concentration, and the red curve represents the phosphorus concentration. The consumption and replenishment process of nutrients can be observed intuitively. After pre-culturing for 48 hours, the engineering algae strains are transferred to the induction culture system, and the cell density is measured every 6 hours using the hemocytometer method, and the growth curve data are recorded, as shown in Table 3:

[0154] Table 3 Growth curve data table of engineering algae strains

[0155] Time (h) YS04 density (x 10 6 / mL)] 6 ​​ 0 1.0 1.0 6 1.4 1.3 12 2.1 1.9 18 3.2 2.8 24 4.8 4.2 30 6.5 5.7 36 8.2 7.1

[0156] Figure 4 Growth curve of engineering algae strains: The figure shows the growth curves of YS04 and YS07 strains during the induction culture process, and contains the fitting curve. From the curve, it can be clearly seen that the growth rate of YS04 is slightly higher than that of YS07. According to the growth curve data, the least square method is used to fit the growth curve equation: lnN(t) = 0.156t + 13.82 + 0.08. At the same time, cell cycle analysis was carried out, and the results showed that the proportion of G1 phase cells was 62.5%, which met the requirements of the induction conditions. According to the cell density induction equation, the optimal induction starting time was calculated to be after 24 hours of culture, and according to the inducer concentration equation, the optimal inducer concentration was calculated to be 0.8 millimoles per liter. The key parameters during the induction process are shown in Table 4:

[0157] Table 4 Key parameters for CD3 protein induction expression

[0158] Parameter item Value Standard deviation Induction start time (h) 24 0.15 Inducer concentration (mM) 0.8 0.06 Induction duration (h) 30 0.25 Culture temperature (℃) 26 0.12 Illumination intensity (lux) 2500 50

[0159] After the induction was completed, the algae were collected and the samples were treated by ultrasonic disruption. The disruption parameters and effects are shown in Table 5:

[0160] Table 5 Algae disruption parameters and effects table

[0161] Crushing parameters Value range Optimal value Ultrasonic power (W) 300-400 350 Ultrasonic time (min) 3-5 4 Intermittent time (s) 3-5 4 Sample temperature (℃) 4-10 6 Crushing rate (%) 90-98 96

[0162] After obtaining the lysate supernatant, affinity chromatography purification was carried out, and 6 concentration gradient points were used for elution. The protein purity analysis results during the elution process are shown in Table 6:

[0163] Table 6 Eluate protein purity analysis table

[0164] Imidazole concentration (mM) Target protein content (%) Impurity protein content (%) 50 15.2 84.8 100 45.6 54.4 150 78.3 21.7 200 92.5 7.5 250 96.8 3.2 300 97.2 2.8

[0165] Figure 5 CD3 protein purification process analysis: The figure uses an area chart to show the content changes of target protein and impurities under different imidazole concentrations. By gradually filling the color area, the trend of protein component change during the purification process is intuitively displayed. The elution components with a purity greater than 95% were further purified by gel filtration chromatography, and the quality evaluation results of the final product are shown in Table 7:

[0166] Table 7 CD3 protein final product quality evaluation table

[0167] Quality index Detection result Quality control standard Protein concentration (mg / mL) 1.2 ≥1.0 Protein purity (%) 98.5 ≥95.0 Activity recovery rate (%) 85.6 ≥80.0 Endotoxin (EU / mg) 0.08 ≤0.1 Aggregate content (%) 1.2 ≤2.0

[0168] Traditional CD3 protein expression method mainly adopts mammalian cell expression system, which has problems of high culture cost, long expression period and low yield. By using traditional method, the expression amount of CD3 protein is usually 0.1-0.3 mg / ml, the purity is difficult to reach more than 95%, and the activity recovery rate is generally between 60-70%. The present application adopts the expression system of the engineering algae strain, controls the expression process through the optimized induction parameter equation group, so that the expression amount of CD3 protein is increased to 1.2 mg / ml, the purity is reached to 98.5%, and the activity recovery rate is increased to 85.6%. At the same time, the culture period of the present application is shortened to 3-4 days, which significantly reduces the production cost.

[0169] Example 3, high efficient expression of perforin protein: an immunology institute uses the method of the present application to express perforin protein. After preliminary screening, the engineering algae strain with growth rate of 2.2 times per 24 hours, chlorophyll content of 5.9 mg / ml and photosynthetic efficiency of 20.8% is selected for experiment. The nutrient consumption in the pre-culture process is shown in Table 8:

[0170] Table 8: Nutrient monitoring table of perforin expression pre-culture stage

[0171] Culture time (h) Nitrogen source consumption rate (%) Phosphorus source consumption rate (%) 12 15.2 12.8 24 28.6 25.4 36 42.3 38.7 48 55.8 51.2

[0172] The optimal induction parameters calculated according to the induction optimization equation group are shown in Table 9:

[0173] Table 9: Perforin expression induction optimization parameter table

[0174] Optimized parameters Calculated value Actual value Deviation rate (%) Induction start time (h) 28.5 28.0 1.75 Inducer concentration (mM) 0.85 0.80 5.88 Induction duration (h) 32.5 32.0 1.54

[0175] The final product quality evaluation results of the perforin protein obtained by the optimized expression process are shown in Table 10:

[0176] Table 10: Perforin protein product quality evaluation table

[0177] Quality index Detection value Reference range Protein concentration (mg / mL) 0.95 ≥0.8 Protein purity (%) 96.8 ≥95.0 Activity recovery rate (%) 82.5 ≥80.0 Monomer content (%) 97.2 ≥95.0

[0178] Figure 6Comparison of expression optimization effect of Perforin protein: the figure uses grouped column chart to compare the differences of traditional method and optimization method in various quality indexes, including expression amount, purity, activity recovery rate and monomer content. The traditional Perforin protein expression method mainly depends on insect cell expression system, and has problems such as low expression amount, great purification difficulty, unstable activity and the like. By using the traditional method, the expression amount of Perforin protein is generally 0.3-0.5 mg per ml, the purity is between 90-93%, and the activity recovery rate is less than 70%. By using the engineering algal strain expression system combined with the optimized induction strategy, the expression amount of Perforin protein is increased to 0.95 mg per ml, the purity is increased to 96.8%, and the activity recovery rate is increased to 82.5%, which significantly improves the yield and quality of the protein.

[0179] It should be noted that the variables involved in the present application are explained in detail as shown in Table 11.

[0180] Table 11: Variable Explanation Table

[0181]

[0182] The above description is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto, and any person skilled in the art can easily think of changes or replacements within the technical range disclosed by the present application, which should be covered within the protection scope of the present application.

Claims

1. A method for efficiently expressing recombinant proteins by using an engineered algal strain, characterized in that, The method comprises the following steps: Screening of engineering algae and construction of expression efficiency vector; pre-culturing of screened engineering algae; determination of engineering algae density and recording of growth curve; addition of inducer, calculation of induction parameters by induction optimization equation set, and control of induction process; collection of culture and centrifugation to obtain algal body precipitate; resuspension of algal body precipitate in lysis buffer and ultrasonic crushing; Supernatant is obtained by centrifugal separation, and protein purification resin is added for incubation; elution is performed by using elution buffer containing imidazole, and the recombinant protein is collected, and a protein expression matrix is constructed; the recombinant protein is purified by gel filtration chromatography; the concentration, purity and biological activity of the purified recombinant protein are determined, and an expression abnormality vector is constructed; when any component of the expression abnormality vector exceeds a preset threshold value, the parameters of the induction optimization equation set are modified according to the expression abnormality vector.

2. The method of claim 1, wherein, The step of screening of engineering algae and construction of expression efficiency vector is specifically selecting algae strains with a growth rate of 1.5 to 2.5 times per 24 hours, a chlorophyll content of 3 to 8 mg per ml, and a photosynthetic efficiency greater than 15%, and the expression efficiency vector is a three-dimensional row vector, and the vector elements are the growth rate, the chlorophyll content and the photosynthetic efficiency of the engineering algae.

3. The method of claim 2, wherein, The step of pre-culturing is specifically inoculating the screened engineering algae into a culture medium containing a nitrogen source concentration of 10 to 15 mmol / L and a phosphorus source concentration of 1 to 2 mmol / L.

4. The method of claim 3, wherein, The step of determining the engineering algae density and recording the growth curve is specifically culturing for 48 to 72 hours under the conditions of an illumination intensity of 2000 to 3000 lux and a temperature of 25 to 28℃.

5. The method of claim 4, wherein, The step of calculating the induction parameters by the induction optimization equation set and controlling the induction process is specifically controlling the inducer concentration to be 0.5 to 1.0 mmol / L and the induction time to be 24 to 36 hours.

6. The method of claim 5, wherein, The step of collecting the culture and centrifuging is specifically rotating at a speed of 4000 to 5000 rpm for 10 to 15 minutes.

7. The method of claim 6, wherein, The step of ultrasonic crushing is specifically crushing for 3 to 5 minutes, with an intermittent time of 3 to 5 seconds and a power of 300 to 400 W.

8. The method of claim 7, wherein, The step of adding the protein purification resin for incubation is specifically incubating the protein purification resin and the supernatant at a volume ratio of 1:10 to 1:20 at 4 to 8℃ for 2 to 4 hours.

9. The method of claim 8, wherein, The step of elution by using the elution buffer containing imidazole is specifically using the elution buffer containing imidazole with a concentration gradient of 50 to 300 mmol / L.

10. The method of claim 9, wherein, The step of purifying the recombinant protein by gel filtration chromatography is specifically at a flow rate of 0.5 to 1.0 ml / min.

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