Biological reagent production optimization method and system based on microbial metabolism characteristics

Abstract

The invention relates to the technical field of microbial metabolism, in particular to a biological reagent production optimization method and system based on microbial metabolism characteristics. The method comprises the following steps: acquiring a biological reagent to produce a microbial strain, and determining the component proportion of a microbial culture medium and optimal microbial culture conditions; carrying out microorganism culture metabolism recording and metabolic flow path analysis on the biological reagent production microorganism strain, and simultaneously carrying out metabolic characteristic analysis to obtain metabolic quantitative characteristics of the biological reagent production microorganism; carrying out metabolic bottleneck node identification analysis on the metabolic flow path of the biological reagent production microorganisms to obtain metabolic bottleneck nodes of the biological reagent production microorganisms; and carrying out microbial production optimization on the corresponding biological reagent production microbial culture metabolism process, and carrying out production post-treatment and purification separation to obtain a biological reagent production optimization product. The production efficiency of the biological reagent can be remarkably improved, so that the stability and the consistency of the biological reagent product are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of microbial metabolism, and in particular to a method and system for optimizing the production of biological reagents based on microbial metabolism characteristics. Background Art

[0002] In the production process of biological reagents, the metabolic characteristics of microorganisms directly affect the yield, purity and production cost of the products. Therefore, optimizing the microbial metabolic process and improving the production efficiency of biological reagents have become an important research topic in the biopharmaceutical and biotechnology industries. In recent years, with the development of systems biology and metabolic engineering, optimization methods based on microbial metabolic characteristics have gradually attracted attention. Through comprehensive analysis of microbial genomes, transcriptomes, metabolomes and other information, researchers can have a deeper understanding of the metabolic pathways and physiological characteristics of microorganisms, so as to optimize them in a targeted manner. However, most of the existing metabolic optimization methods rely on a single "gene editing" or "metabolic pathway regulation". These methods usually require complex experiments and a lot of computational work, and cannot comprehensively and accurately consider the metabolic pathways of microorganisms, resulting in the inability to accurately determine the metabolic bottlenecks in the metabolic pathways. Summary of the invention

[0003] Based on this, it is necessary for the present invention to provide a method and system for optimizing the production of biological reagents based on microbial metabolic characteristics to solve at least one of the above technical problems.

[0004] To achieve the above object, a method for optimizing the production of biological reagents based on microbial metabolic characteristics comprises the following steps:

[0005] Step S1: obtaining a biological reagent production microbial strain, and determining a microbial culture medium composition ratio and a microbial optimal culture condition according to the biological reagent production microbial strain; performing a microbial culture metabolism record on the biological reagent production microbial strain based on the microbial culture medium composition ratio and the microbial optimal culture condition, and generating a biological reagent production microbial culture metabolism process;

[0006] Step S2: performing metabolic flow pathway analysis on the metabolic process of the biological reagent production microorganism culture to generate the metabolic flow pathway of the biological reagent production microorganism; performing metabolic characteristic analysis on the metabolic process of the biological reagent production microorganism culture based on the metabolic flow pathway of the biological reagent production microorganism to obtain the quantitative metabolic characteristics of the biological reagent production microorganism;

[0007] Step S3: Based on the quantitative characteristics of the biological reagent production microbial metabolism, the metabolic bottleneck node identification analysis is performed on the metabolic flow pathway of the biological reagent production microbial to obtain the metabolic bottleneck node of the biological reagent production microbial; based on the metabolic bottleneck node of the biological reagent production microbial, the corresponding biological reagent production microbial cultivation metabolic process is optimized to generate the biological reagent production microbial metabolism optimization process;

[0008] Step S4: performing post-production processing and purification separation on the biological reagent microbial production metabolism optimization process to obtain the biological reagent production optimization product.

[0009] Further, step S1 includes the following steps:

[0010] Step S11: obtaining a biological reagent production microbial strain, wherein the biological reagent production microbial strain includes yeast, bacteria or fungi suitable for biological reagent production;

[0011] Step S12: performing genome analysis and biochemical property analysis on the biological reagent production microbial strain to obtain the biological reagent microbial strain genome analysis data and the biological reagent microbial strain chemical property data; performing nutritional metabolic demand analysis on the corresponding biological reagent production microbial strain based on the biological reagent microbial strain genome analysis data and the biological reagent microbial strain chemical property data to obtain the nutritional metabolic demand of the biological reagent microbial strain;

[0012] Step S13: performing a culture medium composition ratio analysis on the corresponding biological reagent production microbial strain based on the nutritional metabolic requirements of the biological reagent microbial strain to generate a microbial culture medium composition ratio;

[0013] Step S14: performing strain culture experiment on the corresponding biological reagent production microbial strain according to the composition ratio of the microbial culture medium to generate a biological reagent microbial strain culture experiment table; further screening and determining the optimal culture conditions of the microorganism according to the biological reagent microbial strain culture experiment table;

[0014] Step S15: Based on the composition ratio of the microbial culture medium and the optimal culture conditions of the microorganisms, the microbial culture metabolism record of the biological reagent production microbial strain is performed to generate the biological reagent production microbial culture metabolism process.

[0015] Furthermore, the composition ratio of the microbial culture medium in step S13 is specifically 20 g / L of glucose, 5 g / L of sucrose, 3 g / L of ammonium nitrate, 2 g / L of amide, 0.002 g / L of biotin, 2 g / L of phosphorus, 1 g / L of sulfur and 0.1 g / L of sodium.

[0016] Furthermore, the optimal culture conditions for the microorganisms in step S14 are specifically a temperature of 35° C., a pH value of 7.0, a dissolved oxygen concentration of 30%, an enzyme concentration of 5%, a culture time of 48 hours, and a stirring speed of 220 rpm.

[0017] Further, step S2 includes the following steps:

[0018] Step S21: using an isotope labeling experiment to perform metabolic flow directional tracking of corresponding metabolites in the metabolic process of biological reagent production microorganisms, so as to generate a metabolic flow trajectory diagram of biological reagent production microorganisms;

[0019] Step S22: performing metabolic flow pathway analysis on each metabolic reaction in the metabolic flow trajectory diagram of the biological reagent production microorganism to generate a metabolic flow pathway of the biological reagent production microorganism;

[0020] Step S23: using metabolic flux analysis technology to quantitatively analyze the metabolic pathway flow of the biological reagent production microorganism metabolic flow pathway to obtain the biological reagent production metabolic flux corresponding to the microbial metabolic flow pathway; based on the biological reagent production metabolic flux corresponding to the microbial metabolic flow pathway, performing enzyme reaction activity evaluation and analysis on the biological reagent production microbial cultivation metabolic process to obtain the biological reagent production microbial metabolic enzyme reaction activity;

[0021] Step S24: obtaining the corresponding microbial carbon dioxide production and microbial oxygen consumption through the metabolic flow pathway of the biological reagent production microorganism, and quantitatively calculating the gas exchange rate of the biological reagent production microorganism culture metabolic process based on the microbial carbon dioxide production and microbial oxygen consumption, so as to obtain the gas exchange rate of the biological reagent production microorganism;

[0022] Step S25: taking the metabolic enzyme reaction activity of the biological reagent producing microorganism and the gas exchange rate of the biological reagent producing microorganism as the metabolic quantitative characteristics to obtain the metabolic quantitative characteristics of the biological reagent producing microorganism.

[0023] Further, step S3 includes the following steps:

[0024] Step S31: performing a statistical analysis of the enzyme reaction rate and reaction flux of the corresponding biological reagent production microbial metabolic flow pathway based on the metabolic enzyme reaction activity of the biological reagent production microorganism, so as to obtain the enzyme reaction rate and enzyme reaction flux corresponding to the microbial metabolic flow pathway;

[0025] Step S32: Based on the gas exchange rate of the biological reagent production microorganism, the enzyme reaction rate corresponding to the microbial metabolic flow pathway, and the enzyme reaction flux, a microbial metabolic bottleneck calculation formula is used to perform a metabolic bottleneck quantitative calculation on each time node in the biological reagent production microbial metabolic flow pathway to obtain a microbial metabolic bottleneck score corresponding to each time node;

[0026] Step S33: performing metabolic bottleneck node identification analysis on the corresponding time nodes in the biological reagent production microbial metabolic flow pathway based on the microbial metabolic bottleneck score corresponding to each time node, so as to obtain the biological reagent production microbial metabolic bottleneck node;

[0027] Step S34: Based on the biological reagent production microbial metabolism bottleneck node, the corresponding biological reagent production microbial cultivation metabolism process is optimized to generate a biological reagent production microbial metabolism optimization process.

[0028] Furthermore, the microbial metabolism bottleneck calculation formula in step S32 is specifically:

[0029]

[0030] Where B(t) is the microbial metabolic bottleneck score corresponding to time node t, n is the number of enzymes involved in the reaction in the metabolic pathway, and v i (t) is the enzyme reaction rate corresponding to enzyme i at time node t, K i (t) is the catalytic coefficient of enzyme i at time node t, is the Michaelis constant corresponding to enzyme i at time node t, L i (t) is the enzyme reaction flux corresponding to enzyme i at time node t, m is the number of substrates affecting the enzyme reaction in the metabolic pathway, S j (t) is the concentration of the jth reaction substrate at time node t, is the saturation constant corresponding to the jth reaction substrate at time node t, E a is the gas exchange rate of the biological reagent production microorganism, R is the gas constant, T(t) is the temperature corresponding to the time node t, T 0 is the reaction reference temperature, and η is the correction coefficient of the microbial metabolic bottleneck score.

[0031] Further, step S34 includes the following steps:

[0032] Step S341: performing microbial production strategy analysis on the corresponding microbial culture metabolic process of the bioreagent production based on the bioreagent production microbial metabolism bottleneck node to generate a bioreagent microbial enzyme gene knock-in optimization strategy or a bioreagent microbial inhibition byproduct formation optimization strategy;

[0033] Step S342: According to the biological reagent microbial enzyme gene knock-in optimization strategy or the biological reagent microbial inhibition of byproduct formation optimization strategy, the corresponding biological reagent production microbial cultivation metabolic process is optimized to generate a biological reagent microbial production metabolic optimization process.

[0034] Further, step S4 includes the following steps:

[0035] Step S41: predicting the product generation of the biological reagent microbial production metabolism optimization process to obtain the peak of biological reagent microbial production product generation; analyzing the production harvesting timing of the corresponding biological reagent microbial production metabolism optimization process based on the peak of biological reagent microbial production product generation to obtain the biological reagent microbial production harvesting timing;

[0036] Step S42: performing concentration gradient distribution analysis on the corresponding production metabolites in the biological reagent microbial production metabolism optimization process based on the biological reagent microbial production harvesting timing to obtain the concentration gradient distribution of the biological reagent microbial metabolites;

[0037] Step S43: performing phased stratified extraction and post-processing on the corresponding production metabolism fermentation liquid in the biological reagent microbial production metabolism optimization process based on the concentration gradient distribution of the biological reagent microbial metabolites, so as to obtain preliminary concentrated metabolites of the biological reagent corresponding to each production metabolism stage;

[0038] Step S44: using molecular sieve and ultrafiltration membrane technology to perform molecular weight separation on the preliminary concentrated metabolites of the biological reagent corresponding to each production metabolic stage, so as to screen and separate high molecular weight target products and low molecular weight by-products through the molecular size of the molecular sieve and the pore size of the ultrafiltration membrane to generate the biological reagent production separation target product;

[0039] Step S45: removing non-specific impurities and purifying the target product of biological reagent production and separation to obtain the optimized product of biological reagent production.

[0040] Furthermore, the present invention also provides a biological reagent production optimization system based on microbial metabolic characteristics, which is used to execute the biological reagent production optimization method based on microbial metabolic characteristics as described above. The biological reagent production optimization system based on microbial metabolic characteristics comprises:

[0041] The biological reagent microbial culture metabolism recording module is used to obtain the biological reagent production microbial strains, and determine the microbial culture medium composition ratio and the microbial optimal culture conditions according to the biological reagent production microbial strains; based on the microbial culture medium composition ratio and the microbial optimal culture conditions, the microbial culture metabolism record of the biological reagent production microbial strains is performed, thereby generating the biological reagent production microbial culture metabolism process;

[0042] The microbial culture metabolism quantitative characteristic analysis module is used to analyze the metabolic flow pathways of the biological reagent production microbial culture metabolism process to generate the biological reagent production microbial metabolic flow pathways; based on the biological reagent production microbial metabolic flow pathways, the metabolic characteristic analysis of the biological reagent production microbial culture metabolism process is performed to obtain the biological reagent production microbial metabolic quantitative characteristics;

[0043] The biological reagent microbial production optimization module is used to identify and analyze the metabolic bottleneck nodes of the biological reagent production microbial metabolic flow pathway based on the quantitative characteristics of the biological reagent production microbial metabolism, so as to obtain the biological reagent production microbial metabolic bottleneck node; based on the biological reagent production microbial metabolic bottleneck node, the corresponding biological reagent production microbial cultivation metabolic process is optimized for microbial production, thereby generating a biological reagent microbial production metabolic optimization process;

[0044] The microbial production metabolism purification and separation module is used for post-production processing and purification and separation of the biological reagent microbial production metabolism optimization process to obtain the biological reagent production optimization product.

[0045] Beneficial effects of the present invention:

[0046] 1. The method for optimizing the production of biological reagents based on the metabolic characteristics of microorganisms proposed in the present invention, compared with the prior art, has the beneficial effect of laying the foundation for subsequent cultivation and product production by selecting microbial strains (such as yeast, bacteria or fungi) suitable for the production of biological reagents. The selection of microorganisms should be based on their ability to efficiently express the target biological reagents, for example, by screening those strains that can efficiently produce target molecules or have a higher metabolic rate under specific environmental conditions, thereby providing potential for optimizing production. By determining the composition ratio of the microbial culture medium according to the biological reagent production microbial strain, the purpose of this stage is to optimize the composition of the culture medium to meet the growth and metabolic needs of the microorganisms, thereby realizing an efficient target biological reagent production fermentation process. Different microorganisms have different nutritional requirements. Therefore, by analyzing the genome data and metabolic characteristics of the strain, the optimal ratio of the carbon source, nitrogen source, minerals, vitamins and other components required by the strain can be accurately determined, and its growth conditions under different environments can be tested to screen out the best culture conditions. At this stage, by adjusting factors such as temperature, pH value, dissolved oxygen level, and culture time, the most suitable growth environment conditions for the target strain are found to improve production efficiency. At the same time, by recording the microbial culture metabolism of the biological reagent production microbial strain based on the composition ratio of the microbial culture medium and the optimal culture conditions of the microorganism, the key data such as the product generation process, the consumed nutrients, and the cell growth curve can be recorded in detail. These data help to fully understand the metabolic pathways of the microorganisms and their dynamic changes during the culture process, and provide a basis for further process optimization. Through in-depth analysis of the culture metabolic process, potential metabolic bottlenecks can be discovered and targeted adjustments can be made to improve the production efficiency and quality of biological reagents. Secondly, by analyzing the metabolic flow pathways of the biological reagent production microbial culture metabolic process, the process of each metabolic reaction can be analyzed to identify the key metabolic pathways of the biological reagent production microorganism. Through this analysis, it can be revealed which metabolic pathways play a leading role in the synthesis of biological reagents and which reaction steps may be bottlenecks. The metabolic flow pathways of microorganisms can be comprehensively and accurately considered, providing a theoretical basis for optimizing microbial metabolism, and can also help discover potential metabolic bottlenecks in subsequent processes. By conducting metabolic characteristic analysis on the metabolic process of biological reagent production microorganism cultivation based on the metabolic flow pathways of biological reagent production microorganisms, a comprehensive metabolic quantitative model can be constructed by comprehensively considering the metabolic enzyme reaction activity and gas exchange rate of the microorganisms. This model can reflect the metabolic state of microorganisms at different production stages and provide guidance for microbial metabolic regulation. The metabolic enzyme reaction activity provides direct data on the intracellular enzyme catalytic rate, while the gas exchange rate reflects the intensity of the overall metabolic activity. By combining these two characteristics, we can have a deep understanding of the relationship between microbial energy metabolism, material synthesis and consumption, and provide multi-dimensional data support for microbial engineering transformation and production process optimization.Then, the metabolic bottleneck nodes of the metabolic pathways of the biological reagent production microorganisms are identified and analyzed based on the quantitative characteristics of the biological reagent production microorganism metabolism. The main function of this step is to identify the bottleneck nodes in the metabolic process. By calculating the microbial metabolic bottleneck score at each time node, we can accurately understand the limiting factors in the metabolic process and their impact on the overall production efficiency at different production stages, and further identify the time nodes that need to be improved in the metabolic network, so that potential bottleneck problems in the production process can be discovered and solved, ensuring the smooth progress of the production process and the maximization of the biological reagent output. By optimizing the microbial production of the corresponding biological reagent production microbial cultivation metabolic process based on the biological reagent production microbial metabolic bottleneck node, different strategies can be adopted, such as gene editing, enzyme engineering, and culture condition optimization, to improve the performance of microorganisms at the metabolic bottleneck node. This process helps to eliminate the limiting factors in production, thereby improving the yield and production efficiency. For example, by modifying the metabolic pathway to improve the activity of key enzymes, or by adjusting the environmental conditions, microorganisms can be more efficient in metabolic reactions at the bottleneck node, which can maximize the metabolic potential of microorganisms and improve the overall efficiency and sustainability of the production process. Finally, by performing post-production processing and purification separation on the metabolic optimization process of microbial production of biological reagents, in the process of biological reagent production, the microbial culture medium usually contains a large amount of cell debris, unreacted substrates, metabolic intermediates and by-products. In order to obtain high-purity biological reagents, appropriate post-processing technology must be used for separation and purification, which can effectively remove impurities, improve the purity and yield of the final product, and separate the target product in a shorter time, thereby improving the production efficiency of the target biological reagent.

[0047] 2. The biological reagent production optimization system based on microbial metabolic characteristics proposed in the present invention is generally composed of a biological reagent microbial culture metabolism recording module, a microbial culture metabolism quantitative characteristic analysis module, a biological reagent microbial production optimization module and a microbial production metabolism purification and separation module. It can realize any biological reagent production optimization method based on microbial metabolic characteristics described in the present invention, and is used to combine the operations between computer programs running on each module to realize the biological reagent production optimization method based on microbial metabolic characteristics. The internal structures of the system cooperate with each other, which can greatly reduce duplication of work and manpower investment, and can quickly and effectively provide a more accurate and efficient biological reagent production optimization process based on microbial metabolic characteristics, thereby simplifying the operation process of the biological reagent production optimization system based on microbial metabolic characteristics. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments thereof made with reference to the following drawings:

[0049] Figure 1 The schematic diagram of the process flow of the method for optimizing the production of biological reagents based on the metabolic characteristics of microorganisms of the present invention;

[0050] Figure 2 for Figure 1 Detailed step flow diagram of step S1;

[0051] Figure 3 It is a schematic diagram of the composition ratio of the microbial culture medium of the present invention;

[0052] Figure 4 It is a partial experimental schematic diagram of the biological reagent microbial strain cultivation experiment table of the present invention. DETAILED DESCRIPTION

[0053] The technical method of the present invention is described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by technicians in this field without creative work are within the scope of protection of the present invention.

[0054] In addition, the accompanying drawings are only schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor methods and / or microcontroller methods.

[0055] It should be understood that, although the terms "first", "second", etc. may be used herein to describe various units, these units should not be limited by these terms. These terms are used only to distinguish one unit from another unit. For example, without departing from the scope of the exemplary embodiments, the first unit may be referred to as the second unit, and similarly the second unit may be referred to as the first unit. The term "and / or" used herein includes any and all combinations of one or more of the listed associated items.

[0056] To achieve this, please refer to Figures 1 to 4 The present invention provides a method for optimizing the production of biological reagents based on microbial metabolic characteristics, the method comprising the following steps:

[0057] Step S1: obtaining a biological reagent production microbial strain, and determining a microbial culture medium composition ratio and a microbial optimal culture condition according to the biological reagent production microbial strain; performing a microbial culture metabolism record on the biological reagent production microbial strain based on the microbial culture medium composition ratio and the microbial optimal culture condition, and generating a biological reagent production microbial culture metabolism process;

[0058] Step S2: performing metabolic flow pathway analysis on the metabolic process of the biological reagent production microorganism culture to generate the metabolic flow pathway of the biological reagent production microorganism; performing metabolic characteristic analysis on the metabolic process of the biological reagent production microorganism culture based on the metabolic flow pathway of the biological reagent production microorganism to obtain the quantitative metabolic characteristics of the biological reagent production microorganism;

[0059] Step S3: Based on the quantitative characteristics of the biological reagent production microbial metabolism, the metabolic bottleneck node identification analysis is performed on the metabolic flow pathway of the biological reagent production microbial to obtain the metabolic bottleneck node of the biological reagent production microbial; based on the metabolic bottleneck node of the biological reagent production microbial, the corresponding biological reagent production microbial cultivation metabolic process is optimized to generate the biological reagent production microbial metabolism optimization process;

[0060] Step S4: performing post-production processing and purification separation on the biological reagent microbial production metabolism optimization process to obtain the biological reagent production optimization product.

[0061] In the embodiment of the present invention, please refer to Figure 1 FIG. 1 is a schematic diagram of the steps of the method for optimizing the production of biological reagents based on the metabolic characteristics of microorganisms of the present invention. In this example, the method for optimizing the production of biological reagents based on the metabolic characteristics of microorganisms includes the following steps:

[0062] Step S1: obtaining a biological reagent production microbial strain, and determining a microbial culture medium composition ratio and a microbial optimal culture condition according to the biological reagent production microbial strain; performing a microbial culture metabolism record on the biological reagent production microbial strain based on the microbial culture medium composition ratio and the microbial optimal culture condition, and generating a biological reagent production microbial culture metabolism process;

[0063] In an embodiment of the present invention, suitable strains are screened from the microbial strains required for the production process of biological reagents, mainly including yeast, bacteria or fungi suitable for the production of biological reagents. These microorganisms need to have efficient metabolic ability, good growth rate, stable genome and the ability to produce target biological reagents, thereby obtaining biological reagent production microbial strains. The genome of the microbial strain is comprehensively analyzed by using high-throughput sequencing technology. First, high-quality genomic DNA is extracted from the selected microbial strain to obtain the complete genome sequence of the microorganism. Then, the genome sequence is annotated using genome analysis software (such as BLAST, GeneMarkS, etc.), and functional genes related to the production of biological reagents (such as enzymes, metabolic pathways, etc.) are identified. The biochemical property analysis includes determining the metabolites, enzyme activity, pH value, temperature adaptability, etc. of the microorganism, and obtaining qualitative and quantitative data of metabolites by liquid chromatography (HPLC), gas chromatography (GC) and other technologies, and constructing the metabolic network of the microorganism by using metabolic modeling tools (such as COPASI, OptFlux, iMOSFET, etc.), and performing nutritional metabolic demand analysis. These tools help determine the nutrients required by the microorganism in the production process by analyzing the metabolic pathways, enzyme activities and key metabolite production pathways of the microorganism. Such as carbon source, nitrogen source, vitamins, inorganic salts, etc., identify the metabolic bottlenecks of microorganisms under different culture conditions, and then deduce their optimal nutritional requirements. Based on the nutritional metabolic requirements obtained by previous analysis, the composition ratio of microbial culture medium is analyzed to calculate the optimal culture medium composition ratio according to the nutritional requirements of microorganisms by using optimization algorithms (such as response surface method, simulated annealing algorithm, genetic algorithm, etc.), and determine the most suitable carbon source (glucose, sucrose), nitrogen source (amino acid, amide), biotin, other essential elements and their concentrations for the production of biological reagents to ensure that the culture medium not only meets the growth needs of microorganisms, but also generates a culture medium composition ratio that is highly adaptable, economical and conducive to the production of target biological reagents, such as glucose 20g / L, sucrose 5g / L, ammonium nitrate 3g / L, amide 2g / L, biotin 0.002g / L, phosphorus 2g / L, sulfur 1g / L and sodium 0.1g / L, thereby generating a microbial culture medium composition ratio (such as Figure 3At the same time, by designing and conducting a culture experiment of a microbial strain according to the previously determined culture medium composition ratio, firstly, according to the selected microbial culture medium formula, the culture medium required for the experiment is configured, and its temperature, pH value, dissolved oxygen concentration, enzyme concentration, culture time and stirring speed and other conditions are strictly controlled, so as to generate a culture experiment table, and by evaluating the growth of microorganisms and the generation of target products under different culture conditions according to the previously generated culture experiment table, the best culture conditions for microorganisms that are most conducive to the production of biological reagents are screened out, specifically, the temperature is 35°C, the pH value is 7.0, the dissolved oxygen concentration is 30%, the enzyme concentration is 5%, the culture time is 48 hours and the stirring speed is 220rpm. Then, by combining the previously determined culture medium composition ratio and optimal culture conditions, the culture metabolic process of the microorganisms is systematically recorded. First, through high-frequency data acquisition, the growth curve of the microorganisms, changes in metabolites, dissolved oxygen levels, pH changes and other data during the culture process are recorded in real time. By using a bioreactor (such as Biostat, Applikon, etc.) equipped with an automated control system to monitor various parameters of the culture process, the recorded data can be processed in real time through a data analysis platform (such as MATLAB, R software, etc.) to analyze the metabolic trends of the microorganisms and their relationship with the culture conditions, and finally record the culture metabolic process of the microorganisms used to produce biological reagents.

[0064] Step S2: performing metabolic flow pathway analysis on the metabolic process of the biological reagent production microorganism culture to generate the metabolic flow pathway of the biological reagent production microorganism; performing metabolic characteristic analysis on the metabolic process of the biological reagent production microorganism culture based on the metabolic flow pathway of the biological reagent production microorganism to obtain the quantitative metabolic characteristics of the biological reagent production microorganism;

[0065] In an embodiment of the present invention, an isotope labeling experiment is used to track the metabolic flow in the metabolic process of biological reagent production microorganisms. First, a labeled isotope (such as 13C or 15N) is added to the microbial culture medium. The marker enters the cell through the metabolic pathway of the microorganism. As the metabolic reaction proceeds, the isotope-labeled molecules will be absorbed by different metabolites. The flow direction and conversion path of the marker are detected and identified, and a corresponding metabolic flow trajectory diagram of the microorganism is generated. Based on the previously obtained metabolic flow trajectory diagram, the conversion path of each metabolic reaction is analyzed. A metabolic flow pathway model of a biological reagent production microorganism is constructed by using metabolic network analysis software (such as Cytoscape or Pathway Studio) combined with metabolic flow data. The model shows the flow direction and interaction of each major metabolic reaction of the microorganism in the biological reagent production process, and also connects the nodes and edges in the metabolic pathway diagram to generate a systematic metabolic flow pathway, thereby generating a metabolic flow pathway of the biological reagent production microorganism. At the same time, the metabolic flux analysis (MFA) technology is used to quantitatively analyze the flow of the metabolic pathways of biological reagent production microorganisms. This analysis usually uses steady-state isotope labeling data as input, and solves the reaction rates of each metabolic pathway through linear programming or nonlinear least squares method to solve the metabolic flux of each metabolic reaction. The enzyme reaction activity in the metabolic process of biological reagent production microorganisms is evaluated by combining the metabolic flux obtained by previous quantitative analysis. The reaction rate of a specific enzyme under different culture conditions is measured, and the parameters are estimated using enzyme kinetic methods (such as the Michaelis-Menten model). Enzyme activity analysis methods such as spectrophotometry, fluorescence or electrochemical analysis can be selected to quantitatively measure the catalytic efficiency of key enzymes in a specific reaction process, thereby deducing the key enzyme reaction activity that affects the flow of metabolic pathways. The gas exchange characteristics of microorganisms are analyzed according to the previously determined metabolic pathways of biological reagent production microorganisms, mainly including carbon dioxide production and oxygen consumption. The gas exchange rate of microorganisms is quantified by combining metabolic pathway data, and the gas exchange rate of microorganisms under different culture conditions is calculated, that is, the ratio of the difference between carbon dioxide production and oxygen consumption to time. Then, the enzyme reaction activity and gas exchange rate obtained by quantification are used as metabolic quantitative characteristics for comprehensive analysis. In this process, multivariate regression analysis methods or principal component analysis (PCA) can be used to integrate these two quantitative characteristics into the metabolic quantitative characteristics of biological reagent production microorganisms. This quantitative characteristic can accurately reflect the energy metabolism and material metabolism in the microbial metabolic process, provide an important basis for production optimization, and finally obtain the metabolic quantitative characteristics of biological reagent production microorganisms.

[0066] Step S3: Based on the quantitative characteristics of the biological reagent production microbial metabolism, the metabolic bottleneck node identification analysis is performed on the metabolic flow pathway of the biological reagent production microbial to obtain the metabolic bottleneck node of the biological reagent production microbial; based on the metabolic bottleneck node of the biological reagent production microbial, the corresponding biological reagent production microbial cultivation metabolic process is optimized to generate the biological reagent production microbial metabolism optimization process;

[0067] In the embodiment of the present invention, the enzyme reaction rate and reaction flux of the corresponding biological reagent production microorganism metabolic flow pathway are statistically analyzed by combining the enzyme reaction activity obtained in the previous analysis. First, the metabolic enzyme activity in the biological reagent production microorganism is determined by high performance liquid chromatography (HPLC) and other analytical techniques, and the activity level of each metabolic enzyme is further analyzed by enzyme-linked immunosorbent assay (ELISA). The concentration data of metabolites within a certain time interval are collected and combined with the metabolic pathway information. The metabolic flux analysis (Flux Balance The FBA model is used to mathematically model the microbial metabolic flow pathway and calculate the rate of each metabolic reaction. The model is based on the actual quantitative data of the genome and metabolites, combined with the biological reaction rate equation, and further obtains the enzyme reaction rate and flux data. The number of enzymes involved in the reaction in the metabolic pathway, the enzyme reaction rate, the enzyme reaction flux, the gas exchange rate and related parameters are combined to form a suitable bottleneck calculation formula to perform a quantitative calculation of the metabolic bottleneck at each time node in the metabolic flow pathway of the biological reagent production microorganism, so as to quantitatively calculate the bottleneck score value of each time node. At the same time, the corresponding time nodes in the metabolic flow pathway of the biological reagent production microorganism are analyzed by combining the bottleneck score value corresponding to each time node. The bottleneck identification method based on the dynamic optimization algorithm is used to gradually analyze the change of the bottleneck value of each time node on the time axis, that is, by setting a bottleneck score threshold, the time nodes with bottleneck scores higher than the threshold are identified as potential metabolic bottleneck nodes, and the time nodes with bottleneck scores lower than or equal to the threshold are not bottleneck nodes, so as to identify the metabolic bottleneck nodes of the biological reagent production microorganism. Then, by combining the previously identified biological reagent production microbial metabolic bottleneck nodes, the corresponding biological reagent production microbial cultivation metabolic process is optimized for microbial production. In this step, the identified metabolic bottleneck nodes are first analyzed in detail, and optimization methods such as simulated annealing algorithm and genetic algorithm are used. Combined with the metabolic flow analysis model, targeted optimization plans are proposed. The goal of the optimization process is to increase metabolic flux, reduce the load of bottleneck reactions, and optimize the expression level or catalytic efficiency of certain key enzymes in production to achieve maximum production of products. Through microbial engineering technologies, such as gene editing and metabolic regulation, the metabolic flow of microorganisms is gradually adjusted to reduce the impact of bottleneck reactions, thereby improving the production efficiency of biological reagents, making the microbial metabolic flow more balanced, and finally optimizing the generation of biological reagent microbial production metabolic optimization process.

[0068] Step S4: performing post-production processing and purification separation on the biological reagent microbial production metabolism optimization process to obtain the biological reagent production optimization product.

[0069] In an embodiment of the present invention, a predictive analysis of product generation is performed on the metabolic optimization process of the production of biological reagent microorganisms that has been previously optimized, so as to predict the generation of metabolites under different conditions by using a metabolic network, and to obtain metabolic pathway information of biological reagent microorganisms through the accumulation and analysis of experimental data, and to establish a metabolic flux analysis (MFA) model, which can accurately reflect the synthesis, decomposition, flow and other information of each metabolite, and to use metabolic flux analysis technology (MFA) and genomics data to predict metabolic flux, determine the rate of metabolite generation under different culture conditions, and predict the peak time of product generation, that is, the moment when the metabolite reaches the maximum concentration, combined with mathematical modeling methods, such as dynamic system simulation and inverse The response rate analysis is performed, and the optimal harvesting time is obtained by comparing the concentrations of metabolites at different time points, that is, the target product is harvested when the concentration reaches the expected peak. The previously determined optimal harvesting time is combined with the statistical analysis of the concentration gradient distribution of the corresponding production metabolites in the metabolic optimization process of the biological reagent microbial production to determine the product concentration and distribution characteristics at different stages. In the specific operation, the harvested fermentation broth samples are first separated and concentrated, and the concentration distribution changes of metabolites at different stages are measured using analytical tools such as high performance liquid chromatography (HPLC). Then, the corresponding production metabolic fermentation broth in the metabolic optimization process of the biological reagent microbial production is staged by combining the concentration distribution changes of metabolites obtained in the previous analysis. The process of stratified extraction is to first stratify the fermentation broth according to different stages (such as early fermentation, mid-culture, and mature stage). Through liquid-liquid extraction technology, different metabolites are separated into different phases through solvent distribution coefficients, thereby achieving preliminary separation and concentration of metabolites. The preliminary concentrated metabolites corresponding to each production metabolic stage are further purified and separated by using molecular sieves and ultrafiltration membrane technology. First, molecular sieves (such as silica gel, polymer molecular sieves, etc.) are used for molecular screening. The high molecular weight target product and low molecular weight by-products are separated by using the difference in pore size of the molecular sieve. The flow rate and sample loading amount are controlled to ensure that the target product can fully pass through the pores of the molecular sieve, while the low molecular weight by-products are retained. In the molecular sieve layer, an ultrafiltration membrane (such as polyamide or polyethersulfone membrane) is then used for further filtration treatment. According to the difference in the size of the membrane pore size, the target product is finely separated. The ultrafiltration membrane can effectively retain large molecular substances, and low molecular weight impurities and by-products are allowed to pass through, thereby maximizing the purity of the target product. The high molecular weight target product and low molecular weight by-products are separated by physical separation technology, and impurities are effectively removed at the same time. Then, the previously separated biological reagent target product is further treated to remove non-specific impurities and purify. Common impurities include proteins, nucleic acids, salts and small molecular pollutants. The methods used include gel filtration, ion exchange chromatography, etc., and by using ion exchange chromatography technology,Select a specific resin suitable for the target product, separate the product and impurities based on the charge difference, then use gel filtration chromatography technology to separate the target product based on its molecular size, remove low molecular weight non-specific impurities, and further purify the target product using reverse phase high performance liquid chromatography (HPLC). Through the combination of these methods, ensure that the target product is thoroughly purified, remove all non-specific impurities, and ensure the high quality and purity of the final biological reagent, and finally obtain the optimized product for biological reagent production.

[0070] Further, step S1 includes the following steps:

[0071] Step S11: obtaining a biological reagent production microbial strain, wherein the biological reagent production microbial strain includes yeast, bacteria or fungi suitable for biological reagent production;

[0072] Step S12: performing genome analysis and biochemical property analysis on the biological reagent production microbial strain to obtain the biological reagent microbial strain genome analysis data and the biological reagent microbial strain chemical property data; performing nutritional metabolic demand analysis on the corresponding biological reagent production microbial strain based on the biological reagent microbial strain genome analysis data and the biological reagent microbial strain chemical property data to obtain the nutritional metabolic demand of the biological reagent microbial strain;

[0073] Step S13: performing a culture medium composition ratio analysis on the corresponding biological reagent production microbial strain based on the nutritional metabolic requirements of the biological reagent microbial strain to generate a microbial culture medium composition ratio;

[0074] Step S14: performing strain culture experiment on the corresponding biological reagent production microbial strain according to the composition ratio of the microbial culture medium to generate a biological reagent microbial strain culture experiment table; further screening and determining the optimal culture conditions of the microorganism according to the biological reagent microbial strain culture experiment table;

[0075] Step S15: Based on the composition ratio of the microbial culture medium and the optimal culture conditions of the microorganisms, the microbial culture metabolism record of the biological reagent production microbial strain is performed to generate the biological reagent production microbial culture metabolism process.

[0076] As an embodiment of the present invention, refer to Figure 2 As shown, Figure 1 Detailed step flow diagram of step S1 in FIG. 1 , in this embodiment, step S1 includes the following steps:

[0077] Step S11: obtaining a biological reagent production microbial strain, wherein the biological reagent production microbial strain includes yeast, bacteria or fungi suitable for biological reagent production;

[0078] In an embodiment of the present invention, suitable strains are screened out from the microbial strains required for the biological reagent production process, mainly including yeast, bacteria or fungi suitable for the production of biological reagents. These microorganisms must have efficient metabolic capacity, good growth rate, stable genome and the ability to produce target biological reagents. The strains can be obtained through literature retrieval, strain library query, and laboratory screening. The selected microorganisms must undergo preliminary culture and evaluation to ensure their good performance in the fermentation process, and the strains are confirmed by using molecular biology tools such as PCR technology, 16S rRNA gene sequencing, or ITS regional analysis to ensure the accuracy and purity of the strains, determine the microbial strains suitable for the production of biological reagents, and finally obtain the microbial strains for the production of biological reagents.

[0079] Step S12: performing genome analysis and biochemical property analysis on the biological reagent production microbial strain to obtain the biological reagent microbial strain genome analysis data and the biological reagent microbial strain chemical property data; performing nutritional metabolic demand analysis on the corresponding biological reagent production microbial strain based on the biological reagent microbial strain genome analysis data and the biological reagent microbial strain chemical property data to obtain the nutritional metabolic demand of the biological reagent microbial strain;

[0080] In an embodiment of the present invention, the genome of the microbial strain is comprehensively analyzed by using high-throughput sequencing technology. First, high-quality genomic DNA is extracted from the selected microbial strain, and whole genome sequencing is performed using a platform such as Illumina NovaSeq to obtain a complete genome sequence of the microorganism. Then, the genome sequence is annotated using genome analysis software (such as BLAST, GeneMarkS, etc.) to identify functional genes related to the production of biological reagents (such as enzymes, metabolic pathways, etc.). The biochemical property analysis includes determining the metabolites, enzyme activity, pH value, temperature adaptability, etc. of the microorganism, and obtaining qualitative and quantitative data of metabolites through liquid chromatography (HPLC), gas chromatography (GC) and other technologies. Through these analyses, detailed genomic characteristics and chemical property data of the microbial strain are obtained, thereby obtaining biological reagent microbial strain genome analysis data and biological reagent microbial strain chemical property data. At the same time, based on the previously obtained genome analysis data and biochemical characteristic data, metabolic modeling tools (such as COPASI, OptFlux, iMOSFET, etc.) are used to construct the metabolic network of microorganisms and conduct nutritional metabolic demand analysis. These tools help determine the nutrients required for the production process by analyzing the metabolic pathways, enzyme activities and production pathways of key metabolites of microorganisms, such as carbon sources, nitrogen sources, vitamins, inorganic salts, etc. Through mathematical modeling and simulation, the metabolic bottlenecks of microorganisms under different culture conditions are identified, and then the optimal nutritional requirement configuration is calculated, and finally the nutritional metabolic requirements of biological reagent microbial strains are obtained.

[0081] Step S13: performing a culture medium composition ratio analysis on the corresponding biological reagent production microbial strain based on the nutritional metabolic requirements of the biological reagent microbial strain to generate a microbial culture medium composition ratio;

[0082] In an embodiment of the present invention, an analysis of the composition ratio of the microbial culture medium is carried out based on the nutritional metabolic demand data obtained by the previous analysis, so as to calculate the optimal proportion of the culture medium components according to the nutritional needs of the microorganisms by using an optimization algorithm (such as a response surface method, a simulated annealing algorithm, a genetic algorithm, etc.). During the analysis process, it is necessary to consider the differences in the demand for culture medium components of the microorganisms under different environmental conditions, and determine the carbon source (glucose, sucrose), nitrogen source (amino acid, amide), biotin, other essential elements and their concentrations that are most suitable for the production of biological reagents, so as to ensure that the culture medium not only meets the growth requirements of the microorganisms, but also has a low production cost, and generates a culture medium composition ratio that is highly adaptable, highly economical and conducive to the production of the target biological reagent, such as glucose 20g / L, sucrose 5g / L, ammonium nitrate 3g / L, amide 2g / L, biotin 0.002g / L, phosphorus 2g / L, sulfur 1g / L and sodium 0.1g / L, and finally generate a microbial culture medium composition ratio (such as Figure 3shown).

[0083] Step S14: performing strain culture experiment on the corresponding biological reagent production microbial strain according to the composition ratio of the microbial culture medium to generate a biological reagent microbial strain culture experiment table; further screening and determining the optimal culture conditions of the microorganism according to the biological reagent microbial strain culture experiment table;

[0084] In an embodiment of the present invention, a culture experiment of a microbial strain is designed and carried out according to the previously determined culture medium composition ratio. First, the culture medium required for the experiment is prepared according to the selected microbial culture medium formula, and its temperature, pH value, dissolved oxygen concentration, enzyme concentration, culture time, stirring speed and other conditions are strictly controlled. Then, the biological reagent production microbial strain is inoculated to the preset culture conditions, and a fermenter or shake flask is used for culture, and periodic sampling and analysis are performed. During the culture process, important parameters such as the initial concentration, the end concentration, and the dissolved oxygen level of the metabolites need to be monitored in real time to ensure the integrity of the experimental data, thereby generating a biological reagent microbial strain culture experiment table (such as Figure 4 At the same time, the growth of microorganisms and the generation of target products under different culture conditions were evaluated according to the previously generated biological reagent microbial strain culture experimental table, so as to screen out the culture conditions that are most conducive to the production of biological reagents, and finally the optimal culture conditions for microorganisms were obtained, which were specifically 35°C, pH 7.0, 30% dissolved oxygen concentration, 5% enzyme concentration, 48 hours culture time and 220 rpm stirring speed.

[0085] Step S15: Based on the composition ratio of the microbial culture medium and the optimal culture conditions of the microorganisms, the microbial culture metabolism record of the biological reagent production microbial strain is performed to generate the biological reagent production microbial culture metabolism process.

[0086] In an embodiment of the present invention, by combining the previously determined culture medium composition ratio and the optimal culture conditions, the culture metabolic process of the microorganism is systematically recorded. First, through high-frequency data acquisition, the growth curve of the microorganism, the change of metabolites, the dissolved oxygen level, the pH change and other data during the culture process are recorded in real time, and the various parameters of the culture process are monitored by using a bioreactor (such as Biostat, Applikon, etc.) equipped with an automated control system. The recorded data can be processed in real time through a data analysis platform (such as MATLAB, R software, etc.) to analyze the metabolic trend of the microorganism and its relationship with the culture conditions, and determine the metabolic state of the microorganism at different stages, nutrient consumption and product synthesis. These metabolic process data not only help to further optimize the biological reagent production process, but also provide effective guidance for large-scale production, and finally record the metabolic process of the biological reagent production microorganism culture.

[0087] Further, step S2 includes the following steps:

[0088] Step S21: using an isotope labeling experiment to perform metabolic flow directional tracking of corresponding metabolites in the metabolic process of biological reagent production microorganisms, so as to generate a metabolic flow trajectory diagram of biological reagent production microorganisms;

[0089] In an embodiment of the present invention, an isotope labeling experiment is used to track the metabolic flow in the metabolic process of biological reagent production microorganisms. First, a labeled isotope (such as 13C or 15N) is added to the microbial culture medium. The marker enters the cell through the metabolic pathway of the microorganism. As the metabolic reaction proceeds, the isotope-labeled molecules will be absorbed by different metabolites. In the process of directional tracking of metabolic flow, the flow direction and conversion path of the marker are detected and identified by mass spectrometry (MS) or nuclear magnetic resonance (NMR) technology, and a corresponding metabolic flow trajectory diagram of the microorganism is generated. This diagram can clearly reflect the generation and conversion process of different products in the metabolic pathway, and finally a metabolic flow trajectory diagram of the biological reagent production microorganism is generated.

[0090] Step S22: performing metabolic flow pathway analysis on each metabolic reaction in the metabolic flow trajectory diagram of the biological reagent production microorganism to generate a metabolic flow pathway of the biological reagent production microorganism;

[0091] In an embodiment of the present invention, based on the previously obtained metabolic flow trajectory diagram, the conversion path of each metabolic reaction is analyzed, and a metabolic network analysis software (such as Cytoscape or Pathway Studio) is used to combine the metabolic flux data to construct a metabolic flow pathway model of a biological reagent production microorganism. The model shows the flow direction and interaction of each major metabolic reaction of the microorganism in the biological reagent production process. During the analysis process, it is necessary to estimate the rate constant, substrate and product concentration of each reaction, and connect them through the nodes and edges in the metabolic pathway diagram to generate a systematic metabolic flow pathway, ensure that all reactions are appropriately included, and finally generate a metabolic flow pathway of the biological reagent production microorganism.

[0092] Step S23: using metabolic flux analysis technology to quantitatively analyze the metabolic pathway flow of the biological reagent production microorganism metabolic flow pathway to obtain the biological reagent production metabolic flux corresponding to the microbial metabolic flow pathway; based on the biological reagent production metabolic flux corresponding to the microbial metabolic flow pathway, performing enzyme reaction activity evaluation and analysis on the biological reagent production microbial cultivation metabolic process to obtain the biological reagent production microbial metabolic enzyme reaction activity;

[0093] In an embodiment of the present invention, the metabolic pathway of the biological reagent production microorganism is quantitatively analyzed by using metabolic flux analysis (MFA) technology. The analysis usually uses steady-state isotope labeling data as input, and the reaction rate of each metabolic pathway is solved by linear programming or nonlinear least squares method. In specific operation, by establishing a mathematical model containing all relevant metabolic reactions, the flux of each metabolic reaction is solved by using isotope labeling experimental data. These flux values ​​will provide a basis for the optimal metabolic flux of biological reagent production, thereby obtaining the biological reagent production metabolic flux corresponding to the microbial metabolic flux pathway. At the same time, the enzyme reaction activity in the biological reagent production microbial metabolism process is evaluated by combining the biological reagent production metabolic flux obtained by previous quantitative analysis, so as to measure the reaction rate of a specific enzyme under different culture conditions, and use enzyme kinetics methods (such as Michaelis-Menten model) to estimate parameters, and can choose to use enzyme activity analysis methods, such as spectrophotometry, fluorescence or electrochemical analysis, to quantitatively measure the catalytic efficiency of key enzymes in a specific reaction process, thereby deriving the key enzyme reaction activity that affects the metabolic pathway flow, and finally obtaining the biological reagent production microbial metabolic enzyme reaction activity.

[0094] Step S24: obtaining the corresponding microbial carbon dioxide production and microbial oxygen consumption through the metabolic flow pathway of the biological reagent production microorganism, and quantitatively calculating the gas exchange rate of the biological reagent production microorganism culture metabolic process based on the microbial carbon dioxide production and microbial oxygen consumption, so as to obtain the gas exchange rate of the biological reagent production microorganism;

[0095] In an embodiment of the present invention, the gas exchange characteristics of the microorganisms are analyzed according to the previously determined metabolic pathways of the biological reagent production microorganisms, mainly including carbon dioxide production and oxygen consumption, and the carbon dioxide concentration and oxygen consumption rate produced by the microorganisms are measured in real time during the culture process, thereby obtaining the carbon dioxide production of the microorganisms and the oxygen consumption of the microorganisms. At the same time, by combining the metabolic pathway data, the gas exchange rate of the microorganisms is quantified, and the gas exchange rate of the microorganisms under different culture conditions is calculated, that is, the ratio of the difference between carbon dioxide production and oxygen consumption to time, and finally the gas exchange rate of the biological reagent production microorganisms is obtained.

[0096] Step S25: taking the metabolic enzyme reaction activity of the biological reagent producing microorganism and the gas exchange rate of the biological reagent producing microorganism as the metabolic quantitative characteristics to obtain the metabolic quantitative characteristics of the biological reagent producing microorganism.

[0097] In an embodiment of the present invention, a comprehensive analysis is performed by taking the previously quantified metabolic enzyme reaction activity of the biological reagent production microorganism and the gas exchange rate of the biological reagent production microorganism as metabolic quantitative characteristics. In this process, a multivariate regression analysis method or principal component analysis (PCA) can be used to integrate these two quantitative characteristics into the metabolic quantitative characteristics of the biological reagent production microorganism. The quantitative characteristics can accurately reflect the energy metabolism and material metabolism in the microbial metabolic process, provide an important basis for production optimization, and finally obtain the metabolic quantitative characteristics of the biological reagent production microorganism.

[0098] Further, step S3 includes the following steps:

[0099] Step S31: performing a statistical analysis of the enzyme reaction rate and reaction flux of the corresponding biological reagent production microbial metabolic flow pathway based on the metabolic enzyme reaction activity of the biological reagent production microorganism, so as to obtain the enzyme reaction rate and enzyme reaction flux corresponding to the microbial metabolic flow pathway;

[0100] In an embodiment of the present invention, the enzyme reaction rate and reaction flux of the corresponding biological reagent production microorganism metabolic flow pathway are statistically analyzed by combining the metabolic enzyme reaction activity of the biological reagent production microorganism obtained in the previous analysis. First, the metabolic enzyme activity in the biological reagent production microorganism is determined by analytical techniques such as high performance liquid chromatography (HPLC), and the activity level of each metabolic enzyme is further analyzed by enzyme-linked immunosorbent assay (ELISA). By collecting metabolite concentration data within a certain time interval and combining metabolic pathway information, a metabolic flux analysis (Flux Balance Analysis, FBA) model is used to mathematically model the microbial metabolic flow pathway, and the rate of each metabolic reaction is calculated. The model is based on the actual quantitative data of the genome and metabolites, combined with the biological reaction rate equation, and further derives the enzyme reaction rate and flux data, ensuring the accurate calculation of the enzyme reaction rate, and finally obtaining the enzyme reaction rate and enzyme reaction flux corresponding to the microbial metabolic flow pathway.

[0101] Step S32: Based on the gas exchange rate of the biological reagent production microorganism, the enzyme reaction rate corresponding to the microbial metabolic flow pathway, and the enzyme reaction flux, a microbial metabolic bottleneck calculation formula is used to perform a metabolic bottleneck quantitative calculation on each time node in the biological reagent production microbial metabolic flow pathway to obtain a microbial metabolic bottleneck score corresponding to each time node;

[0102] In an embodiment of the present invention, a suitable microbial metabolic bottleneck calculation formula is formed by combining the number of enzymes participating in the reaction in the metabolic pathway, the enzyme reaction rate, the catalytic coefficient, the Michaelis constant, the enzyme reaction flux, the number of substrates affecting the enzyme reaction in the metabolic pathway, the reaction substrate concentration, the saturation constant, the gas exchange rate of the biological reagent production microorganism, the gas constant, the temperature, the reaction reference temperature and related parameters to perform a quantitative calculation of the metabolic bottleneck at each time node in the biological reagent production microbial metabolic flow pathway, so as to quantitatively calculate the bottleneck value of each time node, and finally obtain the microbial metabolic bottleneck score value corresponding to each time node.

[0103] Step S33: performing metabolic bottleneck node identification analysis on the corresponding time nodes in the biological reagent production microbial metabolic flow pathway based on the microbial metabolic bottleneck score corresponding to each time node, so as to obtain the biological reagent production microbial metabolic bottleneck node;

[0104] In an embodiment of the present invention, metabolic bottleneck node identification and analysis is performed on the corresponding time nodes in the metabolic flow path of the biological reagent production microorganism by combining the microbial metabolic bottleneck score corresponding to each time node, and a bottleneck identification method based on a dynamic optimization algorithm is adopted to gradually analyze the change of the bottleneck value of each time node on the time axis, that is, by setting a bottleneck score threshold, the time nodes with bottleneck score values ​​higher than the threshold are identified as potential metabolic bottleneck nodes, and the time nodes lower than or equal to the threshold are not bottleneck nodes. The method identifies the metabolic bottleneck nodes by comparing the score values ​​of different time nodes, and further adjusts the threshold parameters in combination with the actual feedback data of microbial metabolism to ensure the accuracy of the bottleneck nodes, and finally identifies the metabolic bottleneck nodes of the biological reagent production microorganisms.

[0105] Step S34: Based on the biological reagent production microbial metabolism bottleneck node, the corresponding biological reagent production microbial cultivation metabolism process is optimized to generate a biological reagent production microbial metabolism optimization process.

[0106] In an embodiment of the present invention, microbial production optimization is performed on the corresponding biological reagent production microbial culture metabolic process by combining the previously identified biological reagent production microbial metabolic bottleneck node. In this step, the identified metabolic bottleneck node is first analyzed in detail, and optimization methods such as simulated annealing algorithm and genetic algorithm are used. Combined with the metabolic flow analysis model, a targeted optimization plan is proposed. The goal of the optimization process is to increase metabolic flux, reduce the load of bottleneck reactions, and optimize the expression level or catalytic efficiency of certain key enzymes in production to achieve maximum production of products. Through microbial engineering technologies, such as gene editing and metabolic regulation, the metabolic flow of microorganisms is gradually adjusted to reduce the impact of bottleneck reactions, thereby improving the production efficiency of biological reagents, making the microbial metabolic flow more balanced, and finally optimizing the generation of biological reagent microbial production metabolic optimization process.

[0107] Furthermore, the microbial metabolism bottleneck calculation formula in step S32 is specifically:

[0108]

[0109] Where B(t) is the microbial metabolic bottleneck score corresponding to time node t, n is the number of enzymes involved in the reaction in the metabolic pathway, and v i (t) is the enzyme reaction rate corresponding to enzyme i at time node t, K i (t) is the catalytic coefficient of enzyme i at time node t, is the Michaelis constant corresponding to enzyme i at time node t, L i (t) is the enzyme reaction flux corresponding to enzyme i at time node t, m is the number of substrates affecting the enzyme reaction in the metabolic pathway, S j (t) is the concentration of the jth reaction substrate at time node t, K sj (t) is the saturation constant corresponding to the jth reaction substrate at time node t, E a is the gas exchange rate of the biological reagent production microorganism, R is the gas constant, T(t) is the temperature corresponding to the time node t, T 0 is the reaction reference temperature, and η is the correction coefficient of the microbial metabolic bottleneck score.

[0110] The present invention obtains a microbial metabolic bottleneck calculation formula by using a specific mathematical model and verifying it, which is used to quantitatively calculate the metabolic bottleneck at each time node in the metabolic flow pathway of the biological reagent production microorganism. The microbial metabolic bottleneck calculation formula can accurately quantify the metabolic bottleneck score of each time node by comprehensively considering variables such as metabolic reaction rate, enzyme activity, substrate concentration, temperature, etc. at different time nodes. This makes the evaluation of metabolic bottlenecks more detailed, and can identify the rate-limiting steps within a specific time period, providing data support for subsequent optimization. This formula not only takes into account the enzyme reaction rate and enzyme flux, but also multiple biological parameters such as the enzyme catalytic coefficient, Michaelis constant, substrate concentration, saturation constant, etc. This multi-factor consideration makes the metabolic bottleneck evaluation more comprehensive and can more accurately reflect the actual biological metabolic state. Secondly, the gas-temperature factor in the formula It can dynamically consider the effects of gas exchange rate and reaction temperature on enzyme activity and metabolic processes. By adjusting the sensitivity to changes in temperature and gas exchange, it can better predict changes in enzyme reaction rates under different ambient temperatures and gas exchanges. The inhibitory effect of substrate concentration on enzyme reaction is taken into account. The concentration of substrate in the metabolic pathway affects the activity and reaction rate of the enzyme. Therefore, by incorporating this inhibitory effect, it is possible to more accurately identify whether there is a potential bottleneck at high substrate concentration. In addition, by introducing the correction coefficient, the calculation formula can be more flexibly adjusted to adapt to different experimental conditions and environmental factors. The correction coefficient can be adjusted according to the experimental results to adapt to different microbial metabolic environments, thereby improving the applicability and accuracy of the formula. By analyzing the metabolic bottleneck score value at each time node, the most critical bottleneck node in the production process can be identified, and then precise metabolic optimization can be performed, which helps to make targeted adjustments in the production process, such as adjusting parameters such as substrate concentration, enzyme concentration, and temperature to improve the production efficiency of biological reagents. By effectively identifying and optimizing metabolic bottlenecks, unnecessary energy waste and substrate waste can be reduced, thereby improving the overall efficiency of the production process. In summary, the formula fully considers the microbial metabolic bottleneck score value B(t) corresponding to the time node t, the number of enzymes involved in the reaction in the metabolic pathway n, and the enzyme reaction rate v corresponding to enzyme i at the time node t. i (t), the catalytic coefficient K corresponding to enzyme i at time node t i (t), the Michaelis constant corresponding to enzyme i at time node t The enzyme reaction flux L corresponding to enzyme i at time node t i (t), the number of substrates affecting the enzyme reaction in the metabolic pathway m, the concentration S corresponding to the jth reaction substrate at time node t j (t), the saturation constant corresponding to the jth reaction substrate at time node t Gas exchange rate E of microorganisms producing biological reagents a , gas constant R, temperature T(t) corresponding to time node t, reaction base temperature T 0 , the correction coefficient η of the microbial metabolic bottleneck score value, constitutes a functional relationship based on the correlation between the microbial metabolic bottleneck score value B(t) corresponding to the time node t and the above parameters This formula can realize the quantitative calculation process of the metabolic bottleneck at each time node in the metabolic flow pathway of microorganisms in the production of biological reagents. At the same time, the introduction of the correction coefficient η of the microbial metabolic bottleneck score value can be adjusted according to the errors occurring in the calculation process, thereby improving the accuracy and applicability of the microbial metabolic bottleneck calculation formula.

[0111] Further, step S34 includes the following steps:

[0112] Step S341: performing microbial production strategy analysis on the corresponding microbial culture metabolic process of the bioreagent production based on the bioreagent production microbial metabolism bottleneck node to generate a bioreagent microbial enzyme gene knock-in optimization strategy or a bioreagent microbial inhibition byproduct formation optimization strategy;

[0113] In an embodiment of the present invention, a production strategy is formulated for the biological reagent production microorganism culture metabolic process at the corresponding time point by combining the previously identified bottleneck node of biological reagent production microorganism metabolism, so as to introduce the optimized enzyme gene into the microbial genome by gene knock-in technology, or inhibit the generation of by-products by gene editing technology, and other optimization strategies, for example, using the CRISPR / Cas9 system to knock in or knock out the relevant enzyme gene to enhance the flow of the target metabolic pathway and reduce the generation of unwanted by-products. This process also needs to be combined with gene expression regulation technology, such as using a promoter to control the expression of the target enzyme to ensure that the biological reagent production microorganism after gene knock-in can continue to exert the optimization effect during the culture process. The culture conditions such as the nitrogen source and carbon source of the microorganism can also be adjusted by metabolic engineering means to further reduce the possibility of by-product generation, ensure that the metabolic network develops in the optimized direction of the target product, and finally generate a biological reagent microorganism enzyme gene knock-in optimization strategy or a biological reagent microorganism inhibition of by-product formation optimization strategy.

[0114] Step S342: According to the biological reagent microbial enzyme gene knock-in optimization strategy or the biological reagent microbial inhibition of byproduct formation optimization strategy, the corresponding biological reagent production microbial cultivation metabolic process is optimized to generate a biological reagent microbial production metabolic optimization process.

[0115] In an embodiment of the present invention, based on the previously formulated optimization strategy, the corresponding biological reagent production microbial culture metabolic process is systematically adjusted by metabolic engineering means, so as to optimize the metabolic network and improve the metabolic efficiency of the production microorganism by using metabolic flux analysis (MFA) combined with experimental data. Specifically, the synthesis of the target product can be further enhanced by optimizing the culture medium composition and adjusting the culture conditions (such as temperature, pH, dissolved oxygen content, etc.). In terms of gene knock-in, metabolic pathway modification technology can be used to overexpress or knock-in important metabolic enzymes to reduce dependence on by-products, and the activity of specific enzymes can be further controlled by small molecule regulators (e.g., metabolic regulators, specific inhibitors, etc.). For example, gene expression regulation and feedback inhibition using a systems biology platform can ensure the balance of microbial metabolism, reduce energy waste and improve the production efficiency of the target product. Through modeling and simulation of metabolic networks, metabolic flow changes can be monitored in real time and corresponding regulation and adjustment can be made to achieve efficient production of biological reagents, and ultimately optimize the generation of biological reagent microbial production metabolic optimization process.

[0116] Further, step S4 includes the following steps:

[0117] Step S41: predicting the product generation of the biological reagent microbial production metabolism optimization process to obtain the peak of biological reagent microbial production product generation; analyzing the production harvesting timing of the corresponding biological reagent microbial production metabolism optimization process based on the peak of biological reagent microbial production product generation to obtain the biological reagent microbial production harvesting timing;

[0118] In an embodiment of the present invention, a predictive analysis of product generation is performed on the metabolic optimization process of the production of biological reagent microorganisms that has been previously optimized for production, so as to predict the generation of metabolites under different conditions by using a metabolic network, and to obtain metabolic pathway information of the biological reagent microorganisms through the accumulation and analysis of experimental data, and to establish a metabolic flux analysis (MFA) model, which can accurately reflect the synthesis, decomposition, flow and other information of each metabolite, and to use metabolic flux analysis technology (MFA) and genomics data to predict metabolic flux, determine the rate of metabolite generation under different culture conditions, and optimize the microbial growth environment by adjusting temperature, pH, dissolved oxygen and other conditions, so as to predict the peak time of product generation, that is, the moment when the metabolites reach the maximum concentration, which will be used as a reference point for subsequent production and harvesting timing analysis to ensure the maximum production of microbial products, thereby obtaining the peak of product generation in the production of biological reagent microorganisms. At the same time, the optimal harvesting time is further analyzed based on the product generation peak obtained from the previous analysis and the time distribution curve of the metabolite concentration. In this step, the concentration changes of the target product and by-product in the fermentation broth are tracked in real time by the online monitoring system, combined with mathematical modeling methods, such as dynamic system simulation and reaction rate analysis, and by comparing the concentrations of metabolites at different time points. The optimal harvesting time is obtained, that is, when the concentration of the target product reaches the expected peak, the harvesting is carried out. At this time, the harvesting can maximize the yield of the target product, avoid the accumulation of by-products and waste of resources, and finally obtain the harvesting time of the biological reagent microbial production.

[0119] Step S42: performing concentration gradient distribution analysis on the corresponding production metabolites in the biological reagent microbial production metabolism optimization process based on the biological reagent microbial production harvesting timing to obtain the concentration gradient distribution of the biological reagent microbial metabolites;

[0120] In an embodiment of the present invention, by combining the previously determined biological reagent microbial production and harvesting timing, the corresponding production metabolites in the biological reagent microbial production metabolism optimization process are statistically analyzed to determine the product concentration and distribution characteristics at different stages. In specific operations, the harvested fermentation broth samples are first separated and concentrated, and the concentration changes of metabolites at different stages are measured using analytical tools such as high performance liquid chromatography (HPLC). The concentration of metabolites at different sampling points is analyzed multiple times to obtain a specific distribution map of the concentration gradient. The analysis results of the concentration gradient distribution will help determine the key metabolites that need to be separated, and ultimately obtain the concentration gradient distribution of the biological reagent microbial metabolites.

[0121] Step S43: performing phased stratified extraction and post-processing on the corresponding production metabolism fermentation liquid in the biological reagent microbial production metabolism optimization process based on the concentration gradient distribution of the biological reagent microbial metabolites, so as to obtain preliminary concentrated metabolites of the biological reagent corresponding to each production metabolism stage;

[0122] In an embodiment of the present invention, the corresponding production metabolism fermentation broth in the biological reagent microbial production metabolism optimization process is subjected to staged stratified extraction by combining the concentration gradient distribution of the biological reagent microbial metabolites obtained by previous analysis. In this process, the fermentation broth is first stratified according to different stages (such as early fermentation, mid-culture, and mature stage). Through liquid-liquid extraction technology, different metabolites are separated into different phases by solvent distribution coefficients, thereby achieving preliminary separation and concentration of metabolites. In specific operations, a suitable organic solvent is selected to mix with the aqueous phase so that the target metabolites preferentially enter the organic phase, while the by-products remain in the aqueous phase. According to the product characteristics of each stage, different solvent combinations are selected for multiple extractions, thereby efficiently separating the metabolites of different stages. The main purpose of this stage is to preliminarily separate the target product and the by-product, and finally obtain the preliminary concentrated metabolites of the biological reagent corresponding to each production metabolism stage.

[0123] Step S44: using molecular sieve and ultrafiltration membrane technology to perform molecular weight separation on the preliminary concentrated metabolites of the biological reagent corresponding to each production metabolic stage, so as to screen and separate high molecular weight target products and low molecular weight by-products through the molecular size of the molecular sieve and the pore size of the ultrafiltration membrane to generate the biological reagent production separation target product;

[0124] In an embodiment of the present invention, molecular sieves and ultrafiltration membrane technology are used to further purify and separate the preliminary concentrated metabolites of biological reagents corresponding to each production metabolic stage. First, molecular sieves (such as silica gel, polymer molecular sieves, etc.) are used for molecular screening. The high molecular weight target product and the low molecular weight by-product are separated by using the difference in pore size of the molecular sieve, and the flow rate and sample loading amount are controlled to ensure that the target product can fully pass through the pores of the molecular sieve, while the low molecular weight by-product is retained in the molecular sieve layer. Then, an ultrafiltration membrane (such as a polyamide or polyethersulfone membrane) is used for further filtration treatment. According to the difference in the size of the membrane pore size, the target product is finely separated. The ultrafiltration membrane can effectively retain macromolecular substances, and what passes through are low molecular weight impurities and by-products. The purity of the target product is maximized by using a combination of multi-stage molecular sieves and ultrafiltration membranes, so as to separate the high molecular weight target product and the low molecular weight by-product by physical separation technology, effectively remove impurities, and achieve a high purity target biological reagent product, and finally generate a biological reagent production separation target product.

[0125] Step S45: removing non-specific impurities and purifying the target product of biological reagent production and separation to obtain the optimized product of biological reagent production.

[0126] In an embodiment of the present invention, the previously separated biological reagent production and separation target product is further subjected to non-specific impurities removal and purification treatment. Common impurities include proteins, nucleic acids, salts and small molecule pollutants. The methods used include gel filtration, ion exchange chromatography, etc., so as to select a specific resin suitable for the target product by using ion exchange chromatography technology, and separate the product and impurities according to the charge difference. Then, gel filtration chromatography technology is used to separate the target product by molecular size to remove low molecular weight non-specific impurities, and reverse phase high performance liquid chromatography (HPLC) is used to further purify the target product. Through the combination of these methods, it is ensured that the target product is thoroughly purified, all non-specific impurities are removed, and the high quality and high purity of the final biological reagent are guaranteed, so as to finally obtain an optimized product for biological reagent production.

[0127] Furthermore, the present invention also provides a biological reagent production optimization system based on microbial metabolic characteristics, which is used to execute the biological reagent production optimization method based on microbial metabolic characteristics as described above. The biological reagent production optimization system based on microbial metabolic characteristics comprises:

[0128] The biological reagent microbial culture metabolism recording module is used to obtain the biological reagent production microbial strains, and determine the microbial culture medium composition ratio and the microbial optimal culture conditions according to the biological reagent production microbial strains; based on the microbial culture medium composition ratio and the microbial optimal culture conditions, the microbial culture metabolism record of the biological reagent production microbial strains is performed, thereby generating the biological reagent production microbial culture metabolism process;

[0129] The microbial culture metabolism quantitative characteristic analysis module is used to analyze the metabolic flow pathways of the biological reagent production microbial culture metabolism process to generate the biological reagent production microbial metabolic flow pathways; based on the biological reagent production microbial metabolic flow pathways, the metabolic characteristic analysis of the biological reagent production microbial culture metabolism process is performed to obtain the biological reagent production microbial metabolic quantitative characteristics;

[0130] The biological reagent microbial production optimization module is used to identify and analyze the metabolic bottleneck nodes of the biological reagent production microbial metabolic flow pathway based on the quantitative characteristics of the biological reagent production microbial metabolism, so as to obtain the biological reagent production microbial metabolic bottleneck node; based on the biological reagent production microbial metabolic bottleneck node, the corresponding biological reagent production microbial cultivation metabolic process is optimized for microbial production, thereby generating a biological reagent microbial production metabolic optimization process;

[0131] The microbial production metabolism purification and separation module is used for post-production processing and purification and separation of the biological reagent microbial production metabolism optimization process to obtain the biological reagent production optimization product.

[0132] Therefore, the embodiments should be regarded as illustrative and non-restrictive from all points, and the scope of the present invention is limited by the appended claims rather than the above description, and it is therefore intended that all changes falling within the meaning and range of equivalent elements of the application documents are included in the present invention.

[0133] The above description is only a specific embodiment of the present invention, so that those skilled in the art can understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but should conform to the widest scope consistent with the principles and novel features invented herein.

Claims

1. A method for optimizing the production of biological reagents based on microbial metabolic characteristics, characterized in that: The following steps are involved: Step S1: obtaining a biological reagent production microbial strain, and determining a microbial culture medium composition ratio and a microbial optimal culture condition according to the biological reagent production microbial strain; performing a microbial culture metabolism record on the biological reagent production microbial strain based on the microbial culture medium composition ratio and the microbial optimal culture condition, and generating a biological reagent production microbial culture metabolism process; Step S2: performing metabolic flow pathway analysis on the metabolic process of the biological reagent production microorganism culture to generate the metabolic flow pathway of the biological reagent production microorganism; performing metabolic characteristic analysis on the metabolic process of the biological reagent production microorganism culture based on the metabolic flow pathway of the biological reagent production microorganism to obtain the quantitative metabolic characteristics of the biological reagent production microorganism; Step S3: Based on the quantitative characteristics of the biological reagent production microbial metabolism, the metabolic bottleneck node identification analysis is performed on the metabolic flow pathway of the biological reagent production microbial to obtain the metabolic bottleneck node of the biological reagent production microbial; based on the metabolic bottleneck node of the biological reagent production microbial, the corresponding biological reagent production microbial cultivation metabolic process is optimized to generate the biological reagent production microbial metabolism optimization process; Step S4: performing post-production processing and purification separation on the biological reagent microbial production metabolism optimization process to obtain the biological reagent production optimization product.

2. The method for optimizing the production of biological reagents based on microbial metabolic characteristics according to claim 1, characterized in that: Step S1 includes the following steps: Step S11: obtaining a biological reagent production microbial strain, wherein the biological reagent production microbial strain includes yeast, bacteria or fungi suitable for biological reagent production; Step S12: performing genome analysis and biochemical property analysis on the biological reagent production microbial strain to obtain the biological reagent microbial strain genome analysis data and the biological reagent microbial strain chemical property data; performing nutritional metabolic demand analysis on the corresponding biological reagent production microbial strain based on the biological reagent microbial strain genome analysis data and the biological reagent microbial strain chemical property data to obtain the nutritional metabolic demand of the biological reagent microbial strain; Step S13: performing a culture medium composition ratio analysis on the corresponding biological reagent production microbial strain based on the nutritional metabolic requirements of the biological reagent microbial strain to generate a microbial culture medium composition ratio; Step S14: performing strain culture experiment on the corresponding biological reagent production microbial strain according to the composition ratio of the microbial culture medium to generate a biological reagent microbial strain culture experiment table; further screening and determining the optimal culture conditions of the microorganism according to the biological reagent microbial strain culture experiment table; Step S15: Based on the composition ratio of the microbial culture medium and the optimal culture conditions of the microorganisms, the microbial culture metabolism record of the biological reagent production microbial strain is performed to generate the biological reagent production microbial culture metabolism process.

3. The method for optimizing the production of biological reagents based on microbial metabolic characteristics according to claim 2, characterized in that: The composition ratio of the microbial culture medium in step S13 is specifically 20 g / L of glucose, 5 g / L of sucrose, 3 g / L of ammonium nitrate, 2 g / L of amide, 0.002 g / L of biotin, 2 g / L of phosphorus, 1 g / L of sulfur and 0.1 g / L of sodium.

4. The method for optimizing the production of biological reagents based on microbial metabolic characteristics according to claim 2, characterized in that: The optimal culture conditions for the microorganisms in step S14 are specifically a temperature of 35° C., a pH value of 7.0, a dissolved oxygen concentration of 30%, an enzyme concentration of 5%, a culture time of 48 hours, and a stirring speed of 220 rpm.

5. The method for optimizing the production of biological reagents based on microbial metabolic characteristics according to claim 1, characterized in that: Step S2 includes the following steps: Step S21: using an isotope labeling experiment to perform metabolic flow directional tracking of corresponding metabolites in the metabolic process of biological reagent production microorganisms, so as to generate a metabolic flow trajectory diagram of biological reagent production microorganisms; Step S22: performing metabolic flow pathway analysis on each metabolic reaction in the metabolic flow trajectory diagram of the biological reagent production microorganism to generate a metabolic flow pathway of the biological reagent production microorganism; Step S23: using metabolic flux analysis technology to quantitatively analyze the metabolic pathway flow of the biological reagent production microorganism metabolic flow pathway to obtain the biological reagent production metabolic flux corresponding to the microbial metabolic flow pathway; based on the biological reagent production metabolic flux corresponding to the microbial metabolic flow pathway, performing enzyme reaction activity evaluation and analysis on the biological reagent production microbial cultivation metabolic process to obtain the biological reagent production microbial metabolic enzyme reaction activity; Step S24: obtaining the corresponding microbial carbon dioxide production and microbial oxygen consumption through the metabolic flow pathway of the biological reagent production microorganism, and quantitatively calculating the gas exchange rate of the biological reagent production microorganism culture metabolic process based on the microbial carbon dioxide production and microbial oxygen consumption, so as to obtain the gas exchange rate of the biological reagent production microorganism; Step S25: taking the metabolic enzyme reaction activity of the biological reagent producing microorganism and the gas exchange rate of the biological reagent producing microorganism as the metabolic quantitative characteristics to obtain the metabolic quantitative characteristics of the biological reagent producing microorganism.

6. The method for optimizing the production of biological reagents based on microbial metabolic characteristics according to claim 5, characterized in that: Step S3 includes the following steps: Step S31: performing a statistical analysis of the enzyme reaction rate and reaction flux of the corresponding biological reagent production microbial metabolic flow pathway based on the metabolic enzyme reaction activity of the biological reagent production microorganism, so as to obtain the enzyme reaction rate and enzyme reaction flux corresponding to the microbial metabolic flow pathway; Step S32: Based on the gas exchange rate of the biological reagent production microorganism, the enzyme reaction rate corresponding to the microbial metabolic flow pathway, and the enzyme reaction flux, a microbial metabolic bottleneck calculation formula is used to perform a metabolic bottleneck quantitative calculation on each time node in the biological reagent production microbial metabolic flow pathway to obtain a microbial metabolic bottleneck score corresponding to each time node; Step S33: performing metabolic bottleneck node identification analysis on the corresponding time nodes in the biological reagent production microbial metabolic flow pathway based on the microbial metabolic bottleneck score corresponding to each time node, so as to obtain the biological reagent production microbial metabolic bottleneck node; Step S34: Based on the biological reagent production microbial metabolism bottleneck node, the corresponding biological reagent production microbial cultivation metabolism process is optimized to generate a biological reagent production microbial metabolism optimization process.

7. The method for optimizing the production of biological reagents based on microbial metabolic characteristics according to claim 6, characterized in that: The microbial metabolism bottleneck calculation formula in step S32 is specifically: Where B(t) is the microbial metabolic bottleneck score corresponding to time node t, n is the number of enzymes involved in the reaction in the metabolic pathway, and v i (t) is the enzyme reaction rate corresponding to enzyme i at time node t, K i (t) is the catalytic coefficient of enzyme i at time node t, is the Michaelis constant corresponding to enzyme i at time node t, L i (t) is the enzyme reaction flux corresponding to enzyme i at time node t, m is the number of substrates affecting the enzyme reaction in the metabolic pathway, S j (t) is the concentration of the jth reaction substrate at time node t, is the saturation constant corresponding to the jth reaction substrate at time node t, E a is the gas exchange rate of the bioreagent production microorganism, R is the gas constant, T(t) is the temperature corresponding to the time node t, T0 is the reaction reference temperature, and η is the correction coefficient of the microbial metabolic bottleneck score.

8. The method for optimizing the production of biological reagents based on microbial metabolic characteristics according to claim 6, characterized in that: Step S34 includes the following steps: Step S341: performing microbial production strategy analysis on the corresponding microbial culture metabolic process of the bioreagent production based on the bioreagent production microbial metabolism bottleneck node to generate a bioreagent microbial enzyme gene knock-in optimization strategy or a bioreagent microbial inhibition byproduct formation optimization strategy; Step S342: According to the biological reagent microbial enzyme gene knock-in optimization strategy or the biological reagent microbial inhibition of byproduct formation optimization strategy, the corresponding biological reagent production microbial cultivation metabolic process is optimized to generate a biological reagent microbial production metabolic optimization process.

9. The method for optimizing the production of biological reagents based on microbial metabolic characteristics according to claim 1, characterized in that: Step S4 includes the following steps: Step S41: predicting the product generation of the biological reagent microbial production metabolism optimization process to obtain the peak of biological reagent microbial production product generation; analyzing the production harvesting timing of the corresponding biological reagent microbial production metabolism optimization process based on the peak of biological reagent microbial production product generation to obtain the biological reagent microbial production harvesting timing; Step S42: performing concentration gradient distribution analysis on the corresponding production metabolites in the biological reagent microbial production metabolism optimization process based on the biological reagent microbial production harvesting timing to obtain the concentration gradient distribution of the biological reagent microbial metabolites; Step S43: performing phased stratified extraction and post-processing on the corresponding production metabolism fermentation liquid in the biological reagent microbial production metabolism optimization process based on the concentration gradient distribution of the biological reagent microbial metabolites, so as to obtain preliminary concentrated metabolites of the biological reagent corresponding to each production metabolism stage; Step S44: using molecular sieve and ultrafiltration membrane technology to perform molecular weight separation on the preliminary concentrated metabolites of the biological reagent corresponding to each production metabolic stage, so as to screen and separate high molecular weight target products and low molecular weight by-products through the molecular size of the molecular sieve and the pore size of the ultrafiltration membrane to generate the biological reagent production separation target product; Step S45: removing non-specific impurities and purifying the target product of biological reagent production and separation to obtain the optimized product of biological reagent production.

10. A biological reagent production optimization system based on microbial metabolic characteristics, characterized in that: For executing the method for optimizing the production of biological reagents based on the metabolic characteristics of microorganisms as claimed in claim 1, the biological reagent production optimization system based on the metabolic characteristics of microorganisms comprises: The biological reagent microbial culture metabolism recording module is used to obtain the biological reagent production microbial strains, and determine the microbial culture medium composition ratio and the microbial optimal culture conditions according to the biological reagent production microbial strains; based on the microbial culture medium composition ratio and the microbial optimal culture conditions, the microbial culture metabolism record of the biological reagent production microbial strains is performed, thereby generating the biological reagent production microbial culture metabolism process; The microbial culture metabolism quantitative characteristic analysis module is used to analyze the metabolic flow pathways of the biological reagent production microbial culture metabolism process to generate the biological reagent production microbial metabolic flow pathways; based on the biological reagent production microbial metabolic flow pathways, the metabolic characteristic analysis of the biological reagent production microbial culture metabolism process is performed to obtain the biological reagent production microbial metabolic quantitative characteristics; The biological reagent microbial production optimization module is used to identify and analyze the metabolic bottleneck nodes of the biological reagent production microbial metabolic flow pathway based on the quantitative characteristics of the biological reagent production microbial metabolism, so as to obtain the biological reagent production microbial metabolic bottleneck node; based on the biological reagent production microbial metabolic bottleneck node, the corresponding biological reagent production microbial cultivation metabolic process is optimized for microbial production, thereby generating a biological reagent microbial production metabolic optimization process; The microbial production metabolism purification and separation module is used for post-production processing and purification and separation of the biological reagent microbial production metabolism optimization process to obtain the biological reagent production optimization product.

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