Plant cell provenance data processing method, system and equipment

Abstract

The invention discloses a plant cell provenance data processing method, system and device, and relates to the technical field of bioinformation.The method comprises the steps that growth data of plant cell provenance are collected and stored; wherein the plant cell provenance comprises at least one of a plant cell chassis synthesis engineering provenance and a plant cell chassis synthesis engineering positive provenance; according to the growth data, automatically screening an optimal plant cell chassis synthesis engineered provenance and / or an optimal plant cell chassis synthesis engineered positive provenance, and obtaining and storing an engineered female parent provenance and / or an engineered positive female parent provenance; the method solves the problems of low screening efficiency, high cost and difficulty in guaranteeing the quality of plant cell provenances in the process of artificially screening the plant cell provenances with high target product synthesis capacity in the plant cell suspension culture technology.

Description

Technical Field

[0001] The present application relates to the field of bioinformatics, and in particular to a method, system, and device for processing plant cell provenance data. Background Art

[0002] Against the backdrop of the rapid development of synthetic biology technology, since plant cells or tissues have unique natural biosynthetic capabilities, environmentally friendly characteristics, and renewable advantages, the industrial research on biotransformation (synthesis of their own natural substances or exogenous substances) using plant cell suspension culture is increasing. In the industrial research on plant cell suspension culture technology, plant cell provenance for synthesizing their own natural substances or exogenous substances through plant cell suspension culture is first obtained by artificial construction or modification, and then the plant cell provenance is industrialized and amplified. However, during the industrial amplification process, the plant cell provenance may experience degradation or instability in the ability to synthesize the target product, resulting in a loss of cultivation cost for industrial amplification. Therefore, it is necessary to regularly screen the plant cell provenance to eliminate plant cell provenances that are prone to degradation or instability in the ability to synthesize their own natural substances or exogenous substances during the industrial amplification process.

[0003] However, currently, plant cell provenances with high ability to synthesize their own natural substances or exogenous substances are mainly screened artificially. However, artificial screening requires a large amount of manual observation, testing, and evaluation of individuals, which is extremely tedious and time-consuming, resulting in low screening efficiency. Secondly, if the screening is unsuccessful, repeated experiments are required, which increases costs and prolongs the screening cycle, resulting in high screening costs. In addition, since artificial screening relies heavily on experience and limited knowledge, it can only be selected through certain obvious characteristics or known parts, which is relatively blind and random, making it easy to omit or ignore plant cell provenances with potential excellence, and the quality of the screened plant cell provenances is difficult to guarantee. Summary of the Invention

[0004] The purpose of this application is to provide a plant cell provenance data processing method, system and equipment to solve the problems of low screening efficiency, high cost and difficulty in ensuring the quality of plant cell provenance in plant cell suspension culture technology, which are caused by artificial screening of plant cell provenances with high target product synthesis ability.

[0005] To achieve the above objectives, this application provides the following solutions:

[0006] In a first aspect, the present application provides a method for processing plant cell provenance data, comprising:

[0007] Collecting and storing growth data of plant cell provenances; wherein the plant cell provenances include at least one of plant cell chassis synthetic engineered provenances and plant cell chassis synthetic engineered positive provenances;

[0008] According to the growth data, the best plant cell chassis synthetic engineered provenance and / or the best plant cell chassis synthetic engineered positive provenance are automatically screened, and the engineered maternal provenance and / or the engineered positive maternal provenance are obtained and stored.

[0009] Optionally, the automatic screening of the best plant cell chassis synthetic engineered provenance based on growth data specifically includes:

[0010] The fresh weight to dry weight ratio R(t) of the plant cell chassis synthetic engineered provenance at a preset volume and culture time t was calculated according to formula (1):

[0011]

[0012] Wherein, Dw(t) is the dry weight of the plant cell chassis synthetic engineered provenance at the time of culture t, and Fw(t) is the fresh weight of the plant cell chassis synthetic engineered provenance at the time of culture t;

[0013] The fresh weight proliferation rate Kf and dry weight proliferation rate Kd of the plant cell chassis synthetic engineered provenance at culture time t were calculated according to formulas (2) and (3):

[0014]

[0015] Among them, F W0 is the initial fresh weight of the plant cell chassis synthetic engineered provenance, D W0 is the initial dry weight of the synthetically engineered provenance of the plant cell chassis;

[0016] The fresh weight to dry weight proliferation ratio δ of the plant cell chassis synthetic engineered provenance was calculated according to formula (4):

[0017]

[0018] Screening plant cell chassis synthetic engineering provenance in the rapid growth and division phase to obtain the first best plant cell chassis synthetic engineering provenance:

[0019] If the plant cell chassis synthetic engineered provenance meets the first condition, the second condition, the third condition or the fourth condition, the plant cell chassis synthetic engineered provenance is in a rapid growth and division phase, and the first optimal plant cell chassis synthetic engineered provenance is screened; wherein:

[0020] The first condition includes:

[0021] R(t) is less than Fw(t);

[0022] The second condition includes:

[0023] Kd is less than Kf;

[0024] The third condition includes:

[0025] R(t) is greater than a preset first threshold and not greater than a preset second threshold;

[0026] The fourth condition includes:

[0027] δ is greater than a preset fourth threshold.

[0028] Optionally, the automatic screening of the best plant cell chassis synthetic engineered provenance based on growth data further includes:

[0029] Based on the growth data of the plant cell chassis synthetic engineered provenance, the maximum fresh weight yield prediction model is used to predict the maximum fresh weight yield of the first best plant cell chassis synthetic engineered provenance;

[0030] Based on the growth data of the plant cell chassis synthetic engineered provenance, the ideal fresh weight prediction model is used to predict the ideal fresh weight of the first best plant cell chassis synthetic engineered provenance;

[0031] The first best plant cell chassis synthetic engineered provenance with the largest maximum fresh weight yield or ideal fresh weight is selected to obtain the second best plant cell chassis synthetic engineered provenance.

[0032] Optionally, the automatic screening of the best plant cell chassis synthetic engineered positive provenance based on growth data specifically includes:

[0033] According to at least one of the first method, the second method, and the third method, selecting a plant cell chassis synthesis engineered positive provenance with an optimal first combination of influencing factors; wherein the combination of influencing factors includes at least two of the chassis expression host type, primers, vectors, and engineered bacterial strains;

[0034] The first method includes:

[0035] The transfection success probability prediction model is constructed to predict and output the transfection success probability of different first plant cell chassis synthetic engineered positive provenances; wherein different first plant cell chassis synthetic engineered positive provenances are synthesized by using different combinations of the influencing factors;

[0036] Selecting the first plant cell chassis synthetic engineering positive provenance with the highest probability of successful transfection, and obtaining the plant cell chassis synthetic engineering positive provenance with the best combination of first influencing factors;

[0037] The second method includes:

[0038] Through the constructed transfection efficiency comprehensive score prediction model of engineered positive provenance, the comprehensive scores of transfection efficiency of engineered positive provenance synthesized in different first plant cell chassis are predicted and output;

[0039] Select the first plant cell chassis synthetic engineering positive provenance with the largest comprehensive score of transfection efficiency, and obtain the plant cell chassis synthetic engineering positive provenance with the best combination of first influencing factors;

[0040] The third method includes:

[0041] The second plant cell chassis synthetic engineered positive provenance with the largest comprehensive score of transfection efficiency is selected to obtain the plant cell chassis synthetic engineered positive provenance with the best combination of first influencing factors; wherein, the second plant cell chassis synthetic engineered positive provenance is synthesized by using a target influencing factor combination, and the target influencing factor combination refers to the influencing factor combination used to synthesize the first plant cell chassis synthetic engineered positive provenance with a probability of transfection success greater than a preset fifth threshold.

[0042] Optionally, the transfection efficiency comprehensive score prediction model is:

[0043]

[0044] Among them, G is the comprehensive score of positive transfection efficiency, F w is the fresh weight of the plant cell chassis synthetic engineered positive provenance, D w is the dry weight of the plant cell chassis synthetic engineered positive provenance, p exp is the target product content of the plant cell chassis synthesis engineered positive provenance, F w,max is the maximum fresh weight of the plant cell chassis synthetic engineered positive provenance, D w,max is the maximum dry weight of the plant cell chassis synthetic engineered positive provenance, P exp,max is the maximum target product content of the plant cell chassis synthetic engineered positive provenance, α, β, and γ are weight coefficients, and α+β+γ=1.

[0045] Optionally, the automatic screening of the best plant cell chassis synthetic engineered positive provenance based on growth data further includes:

[0046] Based on the growth data of the plant cell chassis synthetic engineering positive provenance, the maximum fresh weight yield prediction model is used to predict the maximum fresh weight yield of the plant cell chassis synthetic engineering positive provenance with the best combination of the first influencing factors;

[0047] Based on the growth data of the plant cell chassis synthetic engineered positive provenance, the ideal fresh weight prediction model is used to predict the ideal fresh weight of the plant cell chassis synthetic engineered positive provenance with the best combination of the first influencing factors;

[0048] The plant cell chassis synthetic engineering positive provenance with the best combination of the first influencing factors for maximum fresh weight yield or ideal fresh weight is selected to obtain the plant cell chassis synthetic engineering positive provenance with the best combination of the second influencing factors.

[0049] Optionally, the maximum fresh weight yield prediction model is:

[0050] X max =a·V+b; (7)

[0051] Among them, X max is the maximum fresh weight yield when the culture volume V is enlarged, a is the slope constant, and b is the intercept constant.

[0052] Optionally, the ideal fresh weight prediction model is:

[0053] F ideal =F w0 ·e k·t ; (8)

[0054] Among them, F ideal is the predicted ideal fresh weight after t days of cultivation, and k is the growth rate constant.

[0055] In a second aspect, the present application provides a plant cell provenance data processing system, comprising:

[0056] A collection module, for collecting and storing growth data of plant cell provenances; wherein the plant cell provenances include at least one of plant cell chassis synthetic engineered provenances and plant cell chassis synthetic engineered positive provenances;

[0057] The first screening module is used to automatically screen the best plant cell chassis synthesis engineered provenance based on growth data, and obtain and store the engineered female provenance;

[0058] The second screening module is used to automatically screen the best plant cell chassis for synthesizing engineered positive provenance based on growth data, and obtain and store engineered positive female provenance.

[0059] In a third aspect, the present application provides a computer device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of any of the above-described plant cell provenance data processing methods.

[0060] According to the specific embodiments provided in this application, this application discloses the following technical effects:

[0061] The present application provides a plant cell base provenance data processing method, system and device, which collects and stores the growth data of plant cell provenance (including at least one of plant cell chassis synthetic engineered provenance and plant cell chassis synthetic engineered positive provenance), can trace the plant cell chassis synthetic engineered provenance and / or plant cell chassis synthetic engineered positive provenance according to the stored growth data, realize the unified growth data management of plant cell chassis synthetic engineered provenance and / or plant cell chassis synthetic engineered positive provenance, and improve management efficiency; automatically screen the best plant cell chassis synthetic engineered provenance and / or the best plant cell chassis synthetic engineered positive provenance according to the data, obtain and store the engineered provenance. The invention relates to an engineered maternal source and / or an engineered positive maternal source, and realizes rapid and automatic screening of engineered maternal source and / or engineered positive maternal source, with high screening efficiency. Manual screening based on experience, acquired knowledge and experimental data is not required, and costs are effectively reduced. The problems of low screening efficiency and high cost in plant cell suspension culture technology that exist in manual screening of plant cell sources with high target product synthesis capacity are solved. The invention also adopts a unified screening standard, avoids the blindness and randomness of manual screening, and the problem that plant cell sources with potential excellence are easily missed or ignored, thereby improving the quality of the screened engineered maternal source and / or engineered positive maternal source, and solving the problem that the quality of manually screened plant cell sources is difficult to ensure. In addition, non-optimal plant cell chassis synthetic engineered provenances and / or plant cell chassis synthetic engineered positive provenances can be accurately eliminated through screening, avoiding the continued use of non-optimal plant cell chassis synthetic engineered provenances and / or plant cell chassis synthetic engineered positive provenances for amplification operations, reducing the amplification operation costs of plant cell chassis synthetic engineered provenances, and to a certain extent avoiding the phenomenon of degradation or instability of the synthetic ability of the target product in the plant cell provenance during the industrial amplification process, thereby reducing the problem of cultivation cost losses in industrial amplification. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0063] Figure 1 This is a diagram of an application environment of a method for processing plant cell provenance data in one embodiment of the present application;

[0064] Figure 2 A schematic flow chart of a method for processing plant cell provenance data provided in one embodiment of the present application;

[0065] Figure 3 A schematic diagram of the functional modules of a plant cell provenance data processing system provided in one embodiment of the present application;

[0066] Figure 4 A schematic diagram of the structure of a computer device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0067] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0068] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0069] The plant cell provenance data processing method provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be set up separately, or it can be integrated on the server 104, or it can be placed on the cloud or other servers. The terminal 102 can send the growth data of the plant cell provenance to the server 104. After the server 104 receives the growth data of the plant cell provenance, it automatically screens the best plant cell chassis synthetic engineered provenance and / or the best plant cell chassis synthetic engineered positive provenance based on the growth data, obtains and stores the engineered maternal provenance and / or the engineered positive maternal provenance. The server 104 can feed back the obtained engineered maternal provenance to the terminal 102. In addition, in some embodiments, the plant cell provenance data processing method can also be implemented separately by the server 104 or the terminal 102, such as the terminal 102 can directly process the growth data of the plant cell provenance, or the server 104 can obtain the growth data of the plant cell provenance from the data storage system for processing.

[0070] The terminal 102 may be, but is not limited to, various desktop computers, laptop computers, smart phones, and tablet computers. The server 104 may be implemented as an independent server or a server cluster consisting of multiple servers, or may be a cloud server.

[0071] In an exemplary embodiment, Figure 2As shown, a method for processing plant cell provenance data is provided. The method is executed by a computer device, specifically a computer device such as a terminal or a server, or a terminal and a server. In the embodiment of the present application, the method is applied to Figure 1 The server 104 in the example is used as an example to illustrate the process, including the following steps 201 to 202.

[0072] Step 201 , collecting and storing growth data of plant cell provenances; wherein the plant cell provenances include at least one of plant cell chassis synthetic engineered provenances and plant cell chassis synthetic engineered positive provenances.

[0073] In the embodiments of the present application, the plant cell chassis synthetic engineered provenance refers to the cells or tissues with reproductive capacity of the collected plant explants, which are plant cells, plant tissues or plant organoids with proliferation capacity and can be used for industrial production through plant tissue culture and directed construction. Directed construction refers to dedifferentiation treatment or directed differentiation treatment, which guides cells to develop in a predetermined direction. It can be used for industrial production, and refers to the plant cells, plant tissues or plant organoids formed that can be used for large-scale production and synthesis of their own natural substances or exogenous substances. Plant tissue is an aggregate composed of plant cells with similar morphology and the same function. Plant organoids refer to three-dimensional structures similar to plant organs formed under in vitro conditions using plant cell or tissue culture technology. Compared with traditional two-dimensional cell culture, plant organoids are closer to the in vivo environment and can better simulate the functional and structural characteristics of real organs. For example, organoids such as roots and buds can be generated from explants such as stem segments and leaves through plant tissue culture technology. Plant explants refer to the target parts of living plants (such as roots, stems, leaves, flowers, and fruits).

[0074] Plant cell chassis synthetic engineered positive provenance refers to an engineered positive provenance obtained by infecting a chassis expression host with an engineered bacterium that has introduced a target gene sequence. Engineered positive provenance refers to plant cells, plant tissues, or plant organoids that can express the target gene sequence, have the ability to proliferate, and synthesize target products (such as pharmaceutical raw materials, artificial proteins, industrial enzyme preparations, etc.), and can be used for industrial production. The target gene sequence is the gene sequence that enables the synthetic plant cell chassis synthetic engineered positive provenance to synthesize the target product. Chassis expression hosts include engineered maternal provenance.

[0075] Growth data for plant cell chassis synthetic engineered provenance includes information about the exogenous maternal plant, the specific part of the exogenous maternal plant collected (e.g., roots, stems, leaves, flowers, fruits), cell type, cell generation number, initial fresh and dry weight of the cells, fresh and dry weight of the cells at culture time t, an image of the plant cell chassis synthetic engineered provenance, and the name of the person responsible for collection. Exogenous maternal plant information includes the Chinese and Latin species name of the exogenous maternal plant, its origin, the types of active products produced, and the amount of active products produced. Cell type refers to the part of the exogenous maternal plant from which the plant cell chassis synthetic engineered provenance was obtained, or the growth stage of the plant cell engineered provenance. Cell generation number refers to the number of passages. This refers to the process by which cells or tissues are separated from their source explant, dedifferentiated, or directed differentiated, and then separated from one culture vessel and cultured in two or more new vessels for further culture. Initial fresh and dry weights refer to the fresh and dry weights of the cells or tissues at the time they are placed in the culture medium of the new vessel. The fresh weight and dry weight of cells at culture time t refer to the fresh weight and dry weight of cells at any culture time t in a certain volume.

[0076] Growth data for positive provenances synthesized from plant cell chassis include information about the exogenous maternal plant, the specific part of the exogenous maternal plant collected (e.g., roots, stems, leaves, flowers, fruits), cell type, cell generation number, initial fresh and dry weight of the cells, fresh and dry weight of the cells at the incubation time t, an image of the synthetic provenance, the name of the person responsible for collection, and information about the chassis expression host and engineered bacteria used to synthesize the positive provenance. Engineered bacteria information includes primers, vectors, and engineered bacteria strains. Primers, vectors, and engineered bacteria must be compatible with the chassis expression host (e.g., primer restriction sites match vector ligation sites, vectors match resistance tags, and plants must use the specific promoter CaMV35S and T-DNA border sequences). The target gene sequence (target gene fragment) is introduced into the vector using synthetic primers, and the vector containing the introduced target gene sequence is then transferred into the host bacteria to produce the engineered bacteria.

[0077] Primer information includes the length of the primer sequence, the GC content (the ratio of the two bases guanine (G) and cytosine (C)), the Tm value (the temperature at which half of the DNA double helix unwinds into a single strand under specific conditions), specificity, and secondary structure. Vector information includes the vector name, vector sequence, key sites of the vector (such as the site where the specific gene fragment is located, enzyme cleavage sites, and other functional site markers), the type and characteristics of the vector promoter, the type and function of the vector tag (such as fluorescent tags, affinity tags, etc.), the enzyme cleavage sites of the vector (listing the enzyme cleavage sites and recognition sequences of commonly used restriction endonucleases separately), the physical size of the vector (measured in the number of bases or expressed by other physical indicators), and pictures reflecting the structure and function of the vector. Information on engineered bacteria includes the recombinant technology methods and steps used to construct the engineered bacteria, labeling information for the engineered bacteria (such as fluorescent tags), the host bacteria species used and their specific source information, expression conditions for the engineered bacteria (such as the conditions for inducing expression and temperature control), the specific methods and steps for culturing the engineered bacteria, background information on the source of the engineered bacteria (such as independent research and development or external acquisition), a detailed description of the external appearance of the engineered bacteria (such as colony morphology, color, size, and other characteristics), the activation steps for the engineered bacteria (including the required time and culture conditions), and images of the engineered bacteria. Labeling information for the engineered bacteria is used to identify the specific characteristics of the engineered bacteria, facilitating the verification and purification (specific adsorption) of the engineered bacteria for plant cell chassis synthesis, as well as the tracking and location of the engineered bacteria.

[0078] Step 202 : Automatically screen the best plant cell chassis synthetic engineered provenance based on the growth data of the plant cell chassis synthetic engineered provenance, and obtain and store the engineered maternal provenance and / or engineered positive maternal provenance.

[0079] The engineered maternal provenance and / or engineered positive maternal provenance of the embodiments of the present application can be used as plant cell provenance for plant cell (or tissue) suspension culture production.

[0080] Implement the above-mentioned steps 201 to 202, by collecting and storing the growth data of plant cell provenance (including at least one of plant cell chassis synthetic engineered provenance and plant cell chassis synthetic engineered positive provenance), it is possible to trace the plant cell chassis synthetic engineered provenance and / or the plant cell chassis synthetic engineered positive provenance according to the stored growth data, thereby realizing unified growth data management of the plant cell chassis synthetic engineered provenance and / or the plant cell chassis synthetic engineered positive provenance, and improving management efficiency; by automatically screening the best plant cell chassis synthetic engineered provenance and / or the best plant cell chassis synthetic engineered positive provenance according to the data, obtaining and storing the engineered maternal provenance and The invention relates to a method for screening engineered maternal sources and / or engineered positive maternal sources, which realizes rapid and automatic screening of engineered maternal sources and / or engineered positive maternal sources with high screening efficiency. It does not require manual screening based on experience, acquired knowledge and experimental data, effectively reduces costs, and solves the problems of low screening efficiency and high cost in plant cell suspension culture technology that exist in manual screening of plant cell sources with high target product synthesis ability. The invention also adopts a unified screening standard, which avoids the blindness and randomness of manual screening, and the problem that plant cell sources with potential excellence are easily missed or ignored, thereby improving the quality of the screened engineered maternal sources and / or engineered positive maternal sources, and solving the problem that the quality of manually screened plant cell sources is difficult to ensure. In addition, non-optimal plant cell chassis synthetic engineered provenances and / or plant cell chassis synthetic engineered positive provenances can be accurately eliminated through screening, avoiding the continued use of non-optimal plant cell chassis synthetic engineered provenances and / or plant cell chassis synthetic engineered positive provenances for amplification operations, reducing the amplification operation costs of plant cell chassis synthetic engineered provenances, and to a certain extent avoiding the phenomenon of degradation or instability of the synthetic ability of the target product in the plant cell provenance during the industrial amplification process, thereby reducing the problem of cultivation cost losses in industrial amplification.

[0081] In another exemplary embodiment of the present application, the growth data collected in the above step 201 also includes the culture data and code identification ID of the plant cell chassis synthetic engineered provenance and / or the plant cell chassis synthetic engineered positive provenance.

[0082] In the embodiment of the present application, cultivation data covers cell T0 generation ID, the culture medium used for cell culture, culture form (such as solid state, liquid culture, expression symbol G / Y), culture volume (L), culture conditions (such as light duration, light intensity, temperature, the nutrient composition required for cultivation, etc.), the starting date (year, month, day) of each generation culture cycle, incubation time t, and the operator name of the operator who performs the cultivation work, etc. Cell T0 generation ID is the T0 generation ID set for plant cell chassis synthetic engineering provenance and / or plant cell chassis synthetic engineering positive provenance, and T0 refers to the first generation cell. Gathering cultivation data is convenient for understanding cultivation information when needed. Code ID is the unique identification ID set artificially for plant cell chassis synthetic engineering provenance. The code ID of plant cell chassis synthetic engineering positive provenance is the unique identification ID set artificially for plant cell chassis synthetic engineering positive provenance. The embodiments of the present application effectively achieve the traceability of the provenance of plant cell chassis synthetic engineered provenance and / or plant cell chassis synthetic engineered positive provenance, comprehensively manage the plant explant information, and effectively manage the provenance throughout its life cycle.

[0083] In another exemplary embodiment of the present application, in the above step 202, the optimal plant cell chassis synthetic engineered provenance is automatically screened based on the growth data, specifically including the following steps 301 to 304.

[0084] in:

[0085] Step 301, calculate the fresh weight to dry weight ratio R(t) of the plant cell chassis synthetic engineered provenance cultured in a fixed volume for a time period of t according to formula (1):

[0086]

[0087] Wherein, Dw(t) is the dry weight of the plant cell chassis synthetic engineered provenance at culture time t, and Fw(t) is the fresh weight of the plant cell chassis synthetic engineered provenance at culture time t.

[0088] Step 302: Calculate the fresh weight proliferation rate Kf and dry weight proliferation rate Kd of the plant cell chassis synthetic engineered provenance at a culture time of t according to formulas (2) and (3):

[0089]

[0090] Among them, F W0 is the initial fresh weight of the plant cell chassis synthetic engineered provenance, D W0 is the initial dry weight of the synthetically engineered provenance of the plant cell chassis.

[0091] Step 303, calculate the fresh weight to dry weight proliferation ratio δ of the plant cell chassis synthetic engineered provenance according to formula (4):

[0092]

[0093] Step 304: Screen plant cell chassis synthetic engineered provenances in a rapid growth and division phase based on at least one of R(t) and δ to obtain a first optimal plant cell chassis synthetic engineered provenance:

[0094] If the plant cell chassis synthetic engineered provenance meets the first condition, the second condition, the third condition or the fourth condition, the plant cell chassis synthetic engineered provenance is in a rapid growth and division phase, and the first optimal plant cell chassis synthetic engineered provenance is screened, wherein:

[0095] The first condition includes:

[0096] R(t) is less than Fw(t);

[0097] The second condition includes:

[0098] Kd is less than Kf;

[0099] The third condition includes:

[0100] R(t) is greater than a preset first threshold and not greater than a preset second threshold;

[0101] The fourth condition includes:

[0102] δ is greater than a preset fourth threshold.

[0103] In the embodiment of the present application, the first optimal plant cell chassis synthetic engineered provenance is the engineered maternal provenance, which can be used as the plant cell provenance for plant cell (or tissue) suspension culture production. The order of steps 302 to 303 and step 301 is not specifically limited and can be set according to actual needs. Steps 302 to 303 can be performed while step 301 is being performed. Steps 301 can be performed first, and then steps 302 to 303 can be performed. Steps 302 to 303 can also be performed first, and then step 301 can be performed.

[0104] The growth stage of a plant cell chassis synthetically engineered provenance can be inferred by changes in R(t). If R(t) is not less than Fw(t) or if the values of R(t) and Fw(t) are equal, the plant cell chassis synthetically engineered provenance is in the mature growth stage. If R(t) is less than Fw(t), the plant cell chassis synthetically engineered provenance is in the rapid growth and division stage.

[0105] If R(t) is greater than 1 and not greater than the first threshold value, the plant cell chassis synthetic engineered provenance is in the early stage of growth and division. If R(t) is greater than the first threshold value and not greater than the second threshold value, the plant cell chassis synthetic engineered provenance is in the rapid growth and division stage. If R(t) is greater than the second threshold value, the plant cell chassis synthetic engineered provenance is in the mature growth stage. The embodiment of the present application does not specifically limit the first threshold value and the second threshold value, which can be set according to actual needs. For example, setting the first threshold value to 15 and the second threshold value to 30, the accurate division of the growth stage of the plant cell chassis synthetic engineered provenance can be achieved.

[0106] The growth stage of a plant cell chassis synthetically engineered provenance can also be inferred by changes in its Kd and Kf. If Kd is greater than Kf, the plant cell chassis synthetically engineered provenance is in the early stages of growth and division. If Kd is equal to Kf, the plant cell chassis synthetically engineered provenance is in the mature growth stage. If Kd is less than Kf, the plant cell chassis synthetically engineered provenance is in the rapid growth and division stage.

[0107] The growth stage of the plant cell chassis synthetic engineered provenance can also be inferred by the change of δ of the plant cell chassis synthetic engineered provenance. The larger δ is, the faster the growth and division is. If δ is greater than 0 and not greater than the third threshold value, the plant cell chassis synthetic engineered provenance is in the mature growth stage. If δ is greater than the third threshold value and not greater than the fourth threshold value, the plant cell chassis synthetic engineered provenance is in the early growth and division stage. If δ is greater than the fourth threshold value, the plant cell chassis synthetic engineered provenance is in the rapid growth and division stage. The embodiment of the present application does not specifically limit the third threshold value and the fourth threshold value, which can be set according to actual needs. For example, setting the third threshold value to 3 and the fourth threshold value to 8, the accurate division of the growth stage of the plant cell chassis synthetic engineered provenance can be achieved.

[0108] The initial stage of growth and division refers to the period when the engineered plant cell chassis is first transferred into a fixed-volume culture environment, during which cells or tissues experience rapid water exchange. As cells lose water, they shrink and accumulate dry matter, marking the beginning of growth and division. The rapid growth and division phase refers to the period when plant cell edges display dense fibrosis and small vacuoles form within the cells. During this phase, cells grow vigorously and divide rapidly. During the mature stage, cells divide slowly and contain more cellular material. The greater the cellular material, the more mature the cell.

[0109] In another exemplary embodiment of the present application, in the above step 202, the optimal plant cell chassis synthetic engineered seed source is automatically screened based on the growth data, and the following steps 401 to 403 are also included.

[0110] in:

[0111] Step 401 : using a maximum fresh weight yield prediction model to predict the maximum fresh weight yield of the first optimal plant cell chassis synthetic engineered provenance.

[0112] Step 402 : Use an ideal fresh weight prediction model to predict the ideal fresh weight of the first optimal plant cell chassis synthetic engineered provenance.

[0113] Step 403 , selecting the first best plant cell chassis synthetic engineered provenance with the largest maximum fresh weight yield or the largest ideal fresh weight, to obtain the second best plant cell chassis synthetic engineered provenance.

[0114] In the embodiment of the present application, the second best plant cell chassis synthetic engineered provenance is the engineered maternal provenance, which can be used as the plant cell provenance for plant cell (or tissue) suspension culture production. The order of step 402 and step 401 is not specifically limited and can be set according to actual needs. Step 402 can be performed at the same time as step 401, step 401 can be performed first, then step 402, or step 402 can be performed first, then step 401.

[0115] In another exemplary embodiment of the present application, the above-mentioned plant cell provenance data processing method further includes:

[0116] Before step 202, the growth data of the plant cell provenance is pre-processed.

[0117] In the embodiments of the present application, there is no specific limitation on pre-processing, and it can be set according to actual needs. For example, pre-processing includes outlier processing, and outlier processing may include removing outliers or replacing outliers. For example, pre-processing includes filling missing values. For another example, pre-processing includes normalization processing. By pre-processing the growth data, the availability of the growth data can be ensured, and the accuracy of screening the best plant cell chassis synthetic engineered provenance and the best plant cell chassis synthetic engineered positive provenance can be improved.

[0118] In another exemplary embodiment of the present application, in the above step 202, selecting the best plant cell chassis for synthesizing engineered positive provenance based on growth data specifically includes:

[0119] According to at least one of the first method, the second method or the third method, a plant cell chassis synthesis engineered positive provenance with the best combination of first influencing factors is selected; wherein the combination of influencing factors includes at least two of the chassis expression host type, primers, vectors and engineered bacterial strains.

[0120] The plant cell chassis synthetic engineered positive provenance with the best combination of the first influencing factors in the embodiment of the present application can be used as the plant cell provenance for plant cell (or tissue) suspension culture production.

[0121] The first method includes the following steps a1 to a2, wherein:

[0122] Step a1: predict and output the transfection success probability of different first plant cell chassis synthetic engineered positive provenances through the constructed transfection success probability prediction model.

[0123] In the embodiment of the present application, different first plant cell chassis are synthesized into engineered positive provenances by using different combinations of influencing factors, and the chassis expression host type, primer, vector type and engineered bacterial strain of different combinations of influencing factors are different.

[0124] Step a2: selecting the first plant cell chassis synthetic engineering positive provenance with the highest probability of successful transfection, and obtaining the plant cell chassis synthetic engineering positive provenance with the best combination of first influencing factors.

[0125] The second method includes the following steps b1 to b2, wherein:

[0126] Step b1, predicting and outputting the comprehensive transfection efficiency scores of engineered positive provenances synthesized by different first plant cell chassis through the constructed comprehensive transfection efficiency score prediction model of engineered positive provenances.

[0127] Step b2: selecting the first plant cell chassis synthetic engineering positive provenance with the largest comprehensive score of transfection efficiency, and obtaining the plant cell chassis synthetic engineering positive provenance with the best combination of first influencing factors.

[0128] The third method includes:

[0129] Step c1, selecting the second plant cell chassis synthetic engineered positive provenance with the largest comprehensive score for transfection efficiency, and obtaining the plant cell chassis synthetic engineered positive provenance with the best combination of first influencing factors; wherein the second plant cell chassis synthetic engineered positive provenance is synthesized by using a target influencing factor combination, and the target influencing factor combination refers to the influencing factor combination used to synthesize the first plant cell chassis synthetic engineered positive provenance with a probability of successful transfection greater than a preset fifth threshold.

[0130] In the embodiment of the present application, while ensuring the success probability of synthesizing the engineered positive provenance of the plant cell chassis, the transfection efficiency is ensured and the trial-and-error cost is reduced. The fifth threshold is not specifically limited and can be set according to actual needs.

[0131] By selecting the plant cell chassis synthetic engineering positive provenance with the best combination of first influencing factors from all plant cell chassis synthetic engineering positive provenances, the optimization treatment for the plant cell chassis synthetic engineering positive provenance is achieved.

[0132] The method of the present application can be used to regularly optimize the plant cell chassis synthetic engineered provenance and plant cell chassis synthetic engineered positive provenance used for industrial amplification to avoid the phenomenon that the plant cell provenance's ability to synthesize its own natural substances or exogenous substances degenerates or becomes unstable during the industrial amplification process.

[0133] In another exemplary embodiment of the present application, the transfection success probability prediction model is:

[0134]

[0135] Where P is the probability of successful positive transfection; X1~X n is the independent variable, indicating the factors affecting the success of transfection, and n is the total number of factors affecting the success of transfection; β0~β n is the regression coefficient, which indicates the influencing factors X1~X n The degree of influence on the probability of successful positive transfection P.

[0136] In the present embodiment, the factors affecting the success of transfection include but are not limited to primers, vector types, engineering bacterial strains, chassis expression host types, etc. The factors affecting the success of transfection are parameterized to obtain independent variables X1~X n The parameterization process is not specifically limited and can be set according to actual needs. For example, categorical variables such as primers, vector types, engineered bacterial strains, and chassis expression host types are encoded, and numerical variables are standardized. By parameterizing the factors affecting the success of transfection in each sample, X1~X n , and record the positive transfection success rate (the proportion of positive cells after transfection) of each sample as the label of the sample. n As input, the label of each sample is used to supervise the model training, and after the training is completed, a transfection success probability prediction model is obtained.

[0137] In another exemplary embodiment of the present application, the comprehensive score prediction model for transfection efficiency is:

[0138]

[0139] Among them, G is the comprehensive score of positive transfection efficiency, F w is the fresh weight of the plant cell chassis synthetic engineered positive provenance, D w is the dry weight of the plant cell chassis synthetic engineered positive provenance, p exp is the target product content of the plant cell chassis synthesis engineered positive provenance, F w,max is the maximum fresh weight of the plant cell chassis synthetic engineered positive provenance, D w,maxis the maximum dry weight of the plant cell chassis synthetic engineered positive provenance, P exp,max is the maximum target product content of the plant cell chassis synthetic engineered positive provenance, α, β, and γ are weight coefficients, and α + β + γ = 1. α measures the impact of the fresh weight of the plant cell chassis synthetic engineered provenance on transfection efficiency, β reflects the dry weight biomass retention of the engineered provenance, and γ quantifies the priority of target product yield.

[0140] In another exemplary embodiment of the present application, the above-mentioned plant cell chassis synthesis data processing method further includes:

[0141] Before collecting primer information, design and select primers.

[0142] In the present embodiment, primer design tools and primer selection tools can be directly linked to design and select primers. When designing primers, codon preferences are screened according to the chassis expression host, and specific matching is achieved in combination with the target gene sequence (designing primers or probes that can accurately match the specific target gene sequence), avoiding primer binding to non-target regions in the genome of the chassis expression host.

[0143] In another exemplary embodiment of the present application, in the above step 202, the optimal plant cell chassis for synthesizing engineered positive provenance is selected based on growth data, and the following steps 501 to 503 are also included.

[0144] in:

[0145] Step 501 : Based on the growth data of the plant cell chassis synthetic engineered positive provenance, a maximum fresh weight yield prediction model is used to predict the maximum fresh weight yield of the plant cell chassis synthetic engineered positive provenance with the best combination of first influencing factors.

[0146] Step 502 : Based on the growth data of the plant cell chassis synthetically engineered positive provenance, an ideal fresh weight prediction model is used to predict the ideal fresh weight of the plant cell chassis synthetically engineered positive provenance with the best combination of first influencing factors.

[0147] Step 503 , selecting the plant cell chassis synthetic engineered positive provenance with the best combination of the first influencing factors for maximum fresh weight yield or ideal fresh weight, and obtaining the plant cell chassis synthetic engineered positive provenance with the best combination of the second influencing factors.

[0148] In the embodiment of the present application, the plant cell chassis synthetic engineered positive provenance with the best combination of the second influencing factors is the engineered positive maternal provenance, which can be used as the plant cell provenance for plant cell (or tissue) suspension culture production. The order of step 502 and step 501 is not specifically limited and can be set according to actual needs. Step 502 can be performed while step 501 is being performed, step 501 can be performed first, then step 502, or step 502 can be performed first, then step 501.

[0149] In another exemplary embodiment of the present application, the maximum fresh weight yield prediction model is:

[0150] X max =a·V+b; (7)

[0151] Among them, X max is the maximum fresh weight yield of the plant cell provenance under the amplification of the culture volume V; a is the slope constant, which refers to the predicted fresh weight increment when the culture volume V increases by 1 unit; b is the intercept constant, which refers to the initial fresh weight of the plant cell chassis synthetic engineered provenance when the culture volume V is zero.

[0152] In the embodiment of the present application, the above-mentioned linear maximum fresh weight yield prediction model can accurately and quickly predict the maximum fresh weight yield of plant cell chassis synthetic engineered provenance and / or engineered positive provenance under culture volume V magnification.

[0153] In another exemplary embodiment of the present application, the above-mentioned ideal fresh weight prediction model is:

[0154] F ideal =F w0 ·e k·t ; (8)

[0155] Among them, F ideal is the predicted ideal fresh weight after t days of cultivation, and k is the growth rate constant.

[0156] In the embodiment of the present application, the ideal fresh weight prediction model described above can accurately and quickly predict the ideal fresh weight of the plant cell chassis synthetic engineered provenance and / or engineered positive provenance after t days of culture.

[0157] In another exemplary embodiment of the present application, the above-mentioned method for processing plant cell provenance data further includes the following steps 601 to 602. In which:

[0158] Step 601, calculating the fresh weight proliferation rate and / or dry weight proliferation rate of the engineered maternal provenance and / or the engineered positive maternal provenance after t days of culture.

[0159] Step 602: Select an engineered maternal provenance and / or an engineered positive maternal provenance whose fresh weight proliferation rate after t days of culture meets the fresh weight proliferation rate requirement and / or whose dry weight proliferation rate after t days of culture meets the dry weight proliferation rate requirement, to obtain the best engineered maternal provenance and / or the best engineered positive maternal provenance.

[0160] In the embodiments of the present application, the fresh weight proliferation rate and / or dry weight proliferation rate after culturing for t days are used to screen the engineered maternal provenance and / or engineered positive maternal provenance whose fresh weight proliferation rate after culturing for t days meets the fresh weight proliferation rate requirement after culturing for t days and / or whose dry weight proliferation rate after culturing for t days meets the dry weight proliferation rate requirement after culturing for t days. The obtained optimal engineered maternal provenance and / or optimal engineered positive maternal provenance can be used for large-scale production.

[0161] The fresh weight proliferation rate of the engineered maternal provenance and / or engineered positive maternal provenance after culturing for t days is calculated according to formula (9):

[0162]

[0163] Among them, T r f is the fresh weight proliferation rate of the engineered maternal provenance or engineered positive maternal provenance after t days of culture, F pf (t) is the fresh weight of the engineered maternal provenance or engineered positive maternal provenance after t days of culture, F pf0 It is the initial fresh weight of the engineered female parent or engineered positive female parent.

[0164] The dry weight proliferation rate of the engineered maternal provenance and / or engineered positive maternal provenance after culturing for t days is calculated according to formula (10):

[0165]

[0166] Among them, T r d is the dry weight proliferation rate of the engineered maternal provenance or engineered positive maternal provenance after t days of culture, F pd (t) is the dry weight of the engineered maternal or engineered positive maternal provenance after t days of culture, F pd0 is the initial dry weight of the engineered female parent or engineered positive female parent.

[0167] Based on the same inventive concept, embodiments of the present application also provide a plant cell provenance data processing system for implementing the aforementioned plant cell provenance data processing method. The solution provided by this system is similar to the solution described in the aforementioned method. Therefore, the specific limitations of the one or more plant cell chassis synthesis data processing system embodiments provided below can be found in the aforementioned limitations of the engineered provenance data processing method and will not be further elaborated here.

[0168] In an exemplary embodiment, Figure 3 As shown, a plant cell provenance data processing system 70 is provided, comprising:

[0169] The first collection module 701 is used to collect growth data of plant cell provenances; wherein the plant cell provenances include at least one of plant cell chassis synthetic engineered provenances and plant cell chassis synthetic engineered positive provenances;

[0170] The first screening module 702 is used to automatically screen the best plant cell chassis synthesis engineered provenance based on growth data to obtain engineered female parent provenance;

[0171] The second screening module 703 is used to automatically screen the best plant cell chassis synthesis engineered positive provenance based on the growth data, and obtain and store the engineered positive female provenance.

[0172] In the embodiments of the present application, the relevant introductions to the plant cell chassis synthetic engineered provenance and its growth data, and the plant cell chassis synthetic engineered positive provenance and its growth data are described in detail in the above method embodiments, which will not be repeated here.

[0173] In another exemplary embodiment of the present application, the first screening module 702 is further configured to:

[0174] The fresh weight to dry weight ratio R(t) of the plant cell chassis synthetic engineered provenance cultured in a fixed volume for a time period of t was calculated according to formula (1);

[0175] According to formulas (2) and (3), the fresh weight proliferation rate Kf and dry weight proliferation rate Kd of the plant cell chassis synthetic engineered provenance at culture time t were calculated;

[0176] The fresh weight to dry weight proliferation ratio δ of the plant cell chassis synthetic engineered provenance was calculated according to formula (4);

[0177] According to at least one of R(t) and δ, plant cell chassis synthetic engineered provenance in a rapid growth and division phase is screened to obtain a first optimal plant cell chassis synthetic engineered provenance:

[0178] If the plant cell chassis synthetic engineered provenance meets the first condition, the second condition, the third condition or the fourth condition, the plant cell chassis synthetic engineered provenance is in a rapid growth and division phase, and the first optimal plant cell chassis synthetic engineered provenance is screened, wherein:

[0179] The first condition includes:

[0180] R(t) is less than Fw(t);

[0181] The second condition includes:

[0182] Kd is less than Kf;

[0183] The third condition includes:

[0184] R(t) is greater than a preset first threshold and not greater than a preset second threshold;

[0185] The fourth condition includes:

[0186] δ is greater than a preset fourth threshold.

[0187] In the embodiments of the present application, the relevant introductions of formulas (1) to (4) are detailed in the records of the above-mentioned method embodiments and will not be repeated here. The growth stage of the plant cell chassis synthetic engineering provenance can be inferred by the change of R(t). If R(t) is not less than Fw(t), the chassis synthetic engineering provenance is in the early stage of growth and division. If R(t) and Fw(t) are equal, the plant cell chassis synthetic engineering provenance is in the mature growth stage. If R(t) is less than Fw(t), the plant cell chassis synthetic engineering provenance is in the rapid growth and division stage.

[0188] If R(t) is greater than 1 and not greater than the first threshold value, the plant cell chassis synthetic engineered provenance is in the early stage of growth and division. If R(t) is greater than the first threshold value and not greater than the second threshold value, the plant cell chassis synthetic engineered provenance is in the rapid growth and division stage. If R(t) is greater than the second threshold value, the plant cell chassis synthetic engineered provenance is in the mature growth stage. The embodiment of the present application does not specifically limit the first threshold value and the second threshold value, which can be set according to actual needs. For example, setting the first threshold value to 15 and the second threshold value to 30, the accurate division of the growth stage of the plant cell chassis synthetic engineered provenance can be achieved.

[0189] The growth stage of a plant cell chassis synthetically engineered provenance can also be inferred by changes in its Kd and Kf. If Kd is greater than Kf, the plant cell chassis synthetically engineered provenance is in the early stages of growth and division. If Kd is equal to Kf, the plant cell chassis synthetically engineered provenance is in the mature growth stage. If Kd is less than Kf, the plant cell chassis synthetically engineered provenance is in the rapid growth and division stage.

[0190] The growth stage of the plant cell chassis synthetic engineered provenance can also be inferred by the change of δ of the plant cell chassis synthetic engineered provenance. The larger δ is, the faster the growth and division is. If δ is greater than 0 and not greater than the third threshold value, the plant cell chassis synthetic engineered provenance is in the mature growth stage. If δ is greater than the third threshold value and not greater than the fourth threshold value, the plant cell chassis synthetic engineered provenance is in the early growth and division stage. If δ is greater than the fourth threshold value, the plant cell chassis synthetic engineered provenance is in the rapid growth and division stage. The embodiment of the present application does not specifically limit the third threshold value and the fourth threshold value, which can be set according to actual needs. For example, setting the third threshold value to 3 and the fourth threshold value to 8, the accurate division of the growth stage of the plant cell chassis synthetic engineered provenance can be achieved.

[0191] In another exemplary embodiment of the present application, the first screening module 702 is further configured to:

[0192] The maximum fresh weight yield prediction model was used to predict the maximum fresh weight yield of the first best plant cell chassis synthetic engineered provenance;

[0193] The ideal fresh weight prediction model was used to predict the ideal fresh weight of the first best plant cell chassis synthetic engineered provenance;

[0194] The first best plant cell chassis synthetic engineered provenance with the largest maximum fresh weight yield or the largest ideal fresh weight is selected to obtain the second best plant cell chassis synthetic engineered provenance.

[0195] In the embodiments of the present application, the relevant introductions of the maximum fresh weight yield prediction model and the ideal fresh weight prediction model are detailed in the description of the above method embodiments and will not be repeated here.

[0196] In another exemplary embodiment of the present application, the second screening module 703 is further configured to:

[0197] According to at least one of the first method, the second method or the third method, a plant cell chassis synthesis engineered positive provenance with the best combination of first influencing factors is selected; wherein the combination of influencing factors includes at least two of the chassis expression host type, primers, vectors and engineered bacterial strains.

[0198] In the embodiments of the present application, the relevant introductions to the first method, the second method and the third method are detailed in the description of the above method embodiments and will not be repeated here.

[0199] In another exemplary embodiment of the present application, the second screening module 703 is further configured to:

[0200] Based on the growth data of the plant cell chassis synthetic engineering positive provenance, the maximum fresh weight yield prediction model is used to predict the maximum fresh weight yield of the plant cell chassis synthetic engineering positive provenance with the best combination of the first influencing factors;

[0201] Based on the growth data of the plant cell chassis synthetic engineered positive provenance, the ideal fresh weight prediction model is used to predict the ideal fresh weight of the plant cell chassis synthetic engineered positive provenance with the best combination of the first influencing factors;

[0202] The plant cell chassis synthetic engineering positive provenance with the best combination of the first influencing factors for maximum fresh weight yield or ideal fresh weight is selected to obtain the plant cell chassis synthetic engineering positive provenance with the best combination of the second influencing factors.

[0203] In another exemplary embodiment of the present application, the plant cell provenance data processing system 70 further includes:

[0204] The preprocessing module is used to preprocess the growth data of the plant cell chassis synthetic engineered provenance and / or the plant cell chassis synthetic engineered positive provenance.

[0205] In the embodiments of the present application, the relevant introduction to the preprocessing is detailed in the description of the above method embodiments and will not be repeated here.

[0206] In another exemplary embodiment of the present application, the plant cell provenance data processing system 70 further includes:

[0207] The primer design module is used to design and select primers before collecting primer information.

[0208] In the present embodiment, primer design tools and primer selection tools can be directly linked to design and select primers. When designing primers, codon preferences are screened according to the chassis expression host, and specific matching is achieved in combination with the target gene sequence (designing primers or probes that can accurately match the specific target gene sequence), avoiding primer binding to non-target regions in the genome of the chassis expression host.

[0209] In another exemplary embodiment of the present application, the plant cell provenance data processing system 70 further includes:

[0210] The third screening module is used to calculate the fresh weight proliferation rate and / or dry weight proliferation rate of the engineered maternal provenance and / or the engineered positive maternal provenance after t days of culture;

[0211] Select engineered maternal provenance and / or engineered positive maternal provenance whose fresh weight proliferation rate after culturing for t days meets the fresh weight proliferation rate requirement and / or whose dry weight proliferation rate after culturing for t days meets the dry weight proliferation rate requirement to obtain the best engineered maternal provenance and / or the best engineered positive maternal provenance.

[0212] In the embodiments of the present application, the relevant introduction to the calculation method of the fresh weight proliferation rate and dry weight proliferation rate of the engineered maternal seed source and / or the engineered positive maternal seed source after t days of culture is detailed in the description of the above method embodiments and will not be repeated here.

[0213] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Figure 4 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O) and a communication interface. The processor, the memory and the input / output interface are connected via a system bus, and the communication interface is connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a method for processing plant cell chassis synthesis data is implemented.

[0214] Those skilled in the art will understand that Figure 4 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0215] In an exemplary embodiment, a computer device is further provided, including a memory and a processor. The memory stores a computer program, and the processor implements the steps in the above method embodiments when executing the computer program.

[0216] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0217] In an exemplary embodiment, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0218] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0219] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory may include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0220] The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processors involved in the various embodiments provided herein may include, but are not limited to, general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic units, data processing logic units based on quantum computing, and the like.

[0221] The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0222] This document uses specific examples to illustrate the principles and implementation methods of this application. The description of the above examples is only intended to help understand the method and core concept of this application. At the same time, for those skilled in the art, based on the concept of this application, there may be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A method for processing plant cell provenance data, characterized in that: The plant cell provenance data processing method comprises: Collecting and storing growth data of plant cell provenances; wherein the plant cell provenances include at least one of plant cell chassis synthetic engineered provenances and plant cell chassis synthetic engineered positive provenances; According to the growth data, the best plant cell chassis synthetic engineered provenance and / or the best plant cell chassis synthetic engineered positive provenance are automatically screened, and the engineered maternal provenance and / or the engineered positive maternal provenance are obtained and stored.

2. The method for processing plant cell provenance data according to claim 1, wherein: The automatic screening of the best plant cell chassis synthetic engineered provenance based on growth data specifically includes: The fresh weight to dry weight ratio R(t) of the plant cell chassis synthetic engineered provenance at a preset volume and culture time t was calculated according to formula (1): Wherein, Dw(t) is the dry weight of the plant cell chassis synthetic engineered provenance at the time of culture t, and Fw(t) is the fresh weight of the plant cell chassis synthetic engineered provenance at the time of culture t; The fresh weight proliferation rate Kf and dry weight proliferation rate Kd of the plant cell chassis synthetic engineered provenance at culture time t were calculated according to formulas (2) and (3): Among them, F W0 is the initial fresh weight of the plant cell chassis synthetic engineered provenance, D W0 is the initial dry weight of the synthetically engineered provenance of the plant cell chassis; The fresh weight to dry weight proliferation ratio δ of the plant cell chassis synthetic engineered provenance was calculated according to formula (4): Screening plant cell chassis synthetic engineering provenance in the rapid growth and division phase to obtain the first best plant cell chassis synthetic engineering provenance: If the plant cell chassis synthetic engineered provenance meets the first condition, the second condition, the third condition or the fourth condition, the plant cell chassis synthetic engineered provenance is in a rapid growth and division phase, and the first optimal plant cell chassis synthetic engineered provenance is screened; wherein: The first condition includes: R(t) is less than Fw(t); The second condition includes: Kd is less than Kf; The third condition includes: R(t) is greater than a preset first threshold and not greater than a preset second threshold; The fourth condition includes: δ is greater than a preset fourth threshold.

3. The method for processing plant cell provenance data according to claim 2, wherein: The method of automatically screening the best plant cell chassis synthetic engineered provenance based on growth data also includes: Based on the growth data of the plant cell chassis synthetic engineered provenance, the maximum fresh weight yield prediction model is used to predict the maximum fresh weight yield of the first best plant cell chassis synthetic engineered provenance; Based on the growth data of the plant cell chassis synthetic engineered provenance, the ideal fresh weight prediction model is used to predict the ideal fresh weight of the first best plant cell chassis synthetic engineered provenance; The first best plant cell chassis synthetic engineered provenance with the largest maximum fresh weight yield or ideal fresh weight is selected to obtain the second best plant cell chassis synthetic engineered provenance.

4. The method for processing plant cell provenance data according to claim 1, wherein: The automatic screening of the best plant cell chassis synthetic engineered positive provenance based on growth data specifically includes: According to at least one of the first method, the second method, and the third method, selecting a plant cell chassis synthesis engineered positive provenance with an optimal first combination of influencing factors; wherein the combination of influencing factors includes at least two of the chassis expression host type, primers, vectors, and engineered bacterial strains; The first method includes: The transfection success probability prediction model is constructed to predict and output the transfection success probability of different first plant cell chassis synthetic engineered positive provenances; wherein different first plant cell chassis synthetic engineered positive provenances are synthesized by using different combinations of the influencing factors; Selecting the first plant cell chassis synthetic engineering positive provenance with the highest probability of successful transfection, and obtaining the plant cell chassis synthetic engineering positive provenance with the best combination of first influencing factors; The second method includes: Through the constructed transfection efficiency comprehensive score prediction model of engineered positive provenance, the comprehensive scores of transfection efficiency of engineered positive provenance synthesized in different first plant cell chassis are predicted and output; Select the first plant cell chassis synthetic engineering positive provenance with the largest comprehensive score of transfection efficiency, and obtain the plant cell chassis synthetic engineering positive provenance with the best combination of first influencing factors; The third method includes: The second plant cell chassis synthetic engineered positive provenance with the largest comprehensive score of transfection efficiency is selected to obtain the plant cell chassis synthetic engineered positive provenance with the best combination of first influencing factors; wherein, the second plant cell chassis synthetic engineered positive provenance is synthesized by using a target influencing factor combination, and the target influencing factor combination refers to the influencing factor combination used to synthesize the first plant cell chassis synthetic engineered positive provenance with a probability of transfection success greater than a preset fifth threshold.

5. The method for processing plant cell provenance data according to claim 4, characterized in that: The comprehensive score prediction model for transfection efficiency is: Among them, G is the comprehensive score of positive transfection efficiency, F w is the fresh weight of the plant cell chassis synthetic engineered positive provenance, D w is the dry weight of the plant cell chassis synthetic engineered positive provenance, p exp is the target product content of the plant cell chassis synthesis engineered positive provenance, F w,max is the maximum fresh weight of the plant cell chassis synthetic engineered positive provenance, D w,max is the maximum dry weight of the plant cell chassis synthetic engineered positive provenance, P exp,max is the maximum target product content of the plant cell chassis synthetic engineered positive provenance, α, β, and γ are weight coefficients, and α+β+γ=1.

6. The method for processing plant cell provenance data according to claim 4, characterized in that: The method of automatically screening the best plant cell chassis synthetic engineered positive provenance based on growth data also includes: Based on the growth data of the plant cell chassis synthetic engineering positive provenance, the maximum fresh weight yield prediction model is used to predict the maximum fresh weight yield of the plant cell chassis synthetic engineering positive provenance with the best combination of the first influencing factors; Based on the growth data of the plant cell chassis synthetic engineered positive provenance, the ideal fresh weight prediction model is used to predict the ideal fresh weight of the plant cell chassis synthetic engineered positive provenance with the best combination of the first influencing factors; The plant cell chassis synthetic engineering positive provenance with the best combination of the first influencing factors for maximum fresh weight yield or ideal fresh weight is selected to obtain the plant cell chassis synthetic engineering positive provenance with the best combination of the second influencing factors.

7. The method for processing plant cell provenance data according to claim 3 or 6, characterized in that: The maximum fresh weight yield prediction model is: X max =a·V+b; (7) Among them, X max is the maximum fresh weight yield when the culture volume V is enlarged, a is the slope constant, and b is the intercept constant.

8. The method for processing plant cell provenance data according to claim 3 or 6, characterized in that: The ideal fresh weight prediction model is: F ideal =F w0 ·e k·t ; (8) Among them, F ideal is the predicted ideal fresh weight after t days of cultivation, and k is the growth rate constant.

9. A plant cell provenance data processing system, characterized in that: The plant cell provenance data processing system comprises: A collection module, for collecting and storing growth data of plant cell provenances; wherein the plant cell provenances include at least one of plant cell chassis synthetic engineered provenances and plant cell chassis synthetic engineered positive provenances; The first screening module is used to automatically screen the best plant cell chassis synthesis engineered provenance based on growth data, and obtain and store the engineered female provenance; The second screening module is used to automatically screen the best plant cell chassis for synthesizing engineered positive provenance based on growth data, and obtain and store engineered positive female provenance.

10. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the plant cell provenance data processing method according to any one of claims 1 to 8.

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