Synthetic path analysis method, system and equipment assisted by organic acid derivatization reagent

Abstract

The invention relates to an organic acid derivatization reagent assisted synthetic route analysis method, system and equipment, and the method comprises the following steps: obtaining a fermentation broth sample of gene editing cells; carrying out chemical derivatization reaction on the intermediate metabolite by using an organic acid derivatization reagent, and converting the intermediate metabolite into a volatile derivative; introducing into a gas chromatograph-mass spectrometer, and separating and detecting the volatile derivative to obtain qualitative and quantitative data of an intermediate metabolite; analyzing metabolic flux distribution in the amino acid synthesis path through a metabolic flux dynamic analysis model; according to the metabolic flux distribution, identifying hidden metabolic nodes and flux limiting nodes in the amino acid synthesis path; and outputting analysis results of hidden metabolic nodes and flux limiting nodes to realize high-sensitivity capture and quantification of metabolic intermediates which are difficult to detect in gene editing cells, so that the aim of systematically analyzing a complete dynamic pathway of an amino acid synthesis network is fulfilled.

Description

Technical Field

[0001] This invention relates to the fields of analytical chemistry and synthetic biology, and in particular to a method, system and equipment for elucidating synthetic pathways assisted by organic acid derivatization reagents. Background Technology

[0002] In the process of microbial fermentation for amino acid production, accurately understanding intracellular metabolic activity is crucial for optimizing production strains. Currently, gas chromatography-mass spectrometry (GC-MS) is commonly used to analyze cellular metabolites, but its effectiveness in detecting certain low-concentration, low-volatility intermediate metabolites (such as aldehydes and ketones) in fermentation broth is limited. These difficult-to-detect intermediates are precisely important links in the amino acid synthesis pathway. Their invisibility prevents a comprehensive understanding of the true operational state of the metabolic network, making it difficult to identify key sites affecting synthesis efficiency and discover potential alternative metabolic pathways. This limitation hinders the clear direction of gene editing and modification, impacting the precise optimization of production strains. Summary of the Invention

[0003] The main objective of this invention is to provide a method, system, and device for analyzing synthetic pathways assisted by organic acid derivatization reagents. By synergistically applying organic acid derivatization reagents with gas chromatography-mass spectrometry, this invention aims to achieve highly sensitive capture and quantification of difficult-to-detect metabolic intermediates in gene-edited cells, thereby completing the systematic analysis of the complete dynamic pathways of their amino acid synthesis network.

[0004] To achieve the above objectives, this invention provides a method for elucidating synthetic pathways assisted by organic acid derivatization reagents, comprising the following steps: A fermentation broth sample of gene-edited cells was obtained, the fermentation broth sample containing intermediate metabolites in the amino acid synthesis process, the intermediate metabolites including aldehyde or ketone precursors; The intermediate metabolite is chemically derivatized using an organic acid derivatizing agent to convert it into a volatile derivative. The derivatized fermentation broth sample was introduced into a gas chromatography-mass spectrometry system to separate and detect the volatile derivatives, thereby obtaining qualitative and quantitative data of the intermediate metabolites. The qualitative and quantitative data were processed using a metabolic flux dynamics analysis model to analyze the metabolic flux distribution in the amino acid synthesis pathway. Based on the metabolic flux distribution, identify hidden metabolic nodes and flux-limiting nodes in the amino acid synthesis pathway; The analysis results of the hidden metabolic nodes and flux-limiting nodes are output to guide gene editing operations to optimize the amino acid synthesis pathway.

[0005] Further, the steps for obtaining fermentation broth samples of gene-edited cells include: The culture medium of gene-edited cells was centrifuged to remove cell debris and solid impurities, and a fermentation broth sample was obtained. Antioxidants and protease inhibitors were added to the fermentation broth sample to inhibit the degradation and enzymatic reactions of the intermediate metabolites.

[0006] Further, the step of chemically derivatizing the intermediate metabolite using an organic acid derivatizing agent to convert the intermediate metabolite into a volatile derivative includes: Carboxylic acid derivatizing reagents are used as organic acid derivatizing reagents to undergo condensation reactions with aldehyde or ketone precursors in the presence of an acidic catalyst; The reaction is carried out under constant temperature and time conditions to completely convert the intermediate metabolite into a volatile derivative.

[0007] Further, the step of introducing the derivatized fermentation broth sample into a gas chromatography-mass spectrometry (GC-MS) instrument to separate and detect the volatile derivatives and obtain qualitative and quantitative data of the intermediate metabolite includes: Volatile derivatives were separated by gas chromatography using a polar chromatographic column with a gradient temperature program. Mass spectrometry detection was performed using electron impact ionization mode, and a stable isotope-labeled analog was used as an internal standard to perform qualitative and quantitative analysis of the volatile derivatives, thereby obtaining qualitative and quantitative data of the intermediate metabolites.

[0008] Furthermore, the step of processing the qualitative and quantitative data using a metabolic flux dynamics analysis model to analyze the metabolic flux distribution in the amino acid synthesis pathway includes: The qualitative and quantitative data are input into a pre-constructed metabolic flow dynamics analysis model based on mass conservation and reaction kinetics; The model was fitted using a numerical optimization algorithm, and the metabolic flux distribution was calculated.

[0009] Further, the step of identifying hidden metabolic nodes and flux-limiting nodes in the amino acid synthesis pathway based on the metabolic flux distribution includes: By analyzing the low-flux regions and abnormal fluctuation points in the metabolic flux distribution, statistical tests are used to identify flux-limiting nodes. A graph-based path mining algorithm is applied to extract non-intuitive connection paths from the metabolic flow dynamic analysis model as hidden metabolic nodes.

[0010] Furthermore, the analysis results of the hidden metabolic nodes and flux-limiting nodes are output to guide the steps of gene editing operations to optimize the amino acid synthesis pathway, including: Based on the identified hidden metabolic nodes and flux-limiting nodes, analytical results are generated that include metabolic pathway topology, flux distribution heatmap, and candidate gene editing targets. The analysis results are integrated with an automated gene editing platform to automatically generate experimental instructions containing specific gene manipulation protocols for implementation path optimization.

[0011] This invention also provides a synthetic pathway analysis system assisted by organic acid derivatization reagents, comprising: The sample acquisition module is used to acquire fermentation broth samples of gene-edited cells; A biochemical reaction module is used to perform a chemical derivatization reaction on the intermediate metabolite using an organic acid derivatization reagent, converting the intermediate metabolite into a volatile derivative. The sample detection module is used to introduce the derivatized fermentation broth sample into a gas chromatography-mass spectrometry instrument to separate and detect the volatile derivatives and obtain qualitative and quantitative data of the intermediate metabolites. The model analysis module is used to process the qualitative and quantitative data through a metabolic flux dynamic analysis model to analyze the metabolic flux distribution in the amino acid synthesis pathway. The path identification module is used to identify hidden metabolic nodes and flux-limiting nodes in the amino acid synthesis pathway based on the metabolic flux distribution. The results output module is used to output the analysis results of the hidden metabolic nodes and flux-limiting nodes, which are used to guide gene editing operations to optimize the amino acid synthesis pathway.

[0012] The present invention also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the above-described organic acid derivatization reagent-assisted synthetic path analysis method.

[0013] The present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the above-described method for resolving synthetic pathways assisted by organic acid derivatization reagents.

[0014] The organic acid derivatization reagent-assisted synthetic pathway analysis method, system, and equipment provided by this invention have the following beneficial effects: This invention improves the detection sensitivity of aldehyde and ketone intermediate metabolites in GC-MS analysis through organic acid derivatization, enabling the accurate determination of these previously difficult-to-detect compounds. Based on the obtained complete metabolite data, combined with a metabolic flux analysis model, two types of key sites in the synthetic pathway can be identified simultaneously: the main nodes limiting overall throughput, and the bypass metabolic nodes easily overlooked in conventional analysis. This dual identification capability provides more comprehensive target information for gene editing. This invention, by interfacing the analysis results with a gene editing platform, directly generates data targeting specific genes, realizing a coherent workflow from metabolic analysis to strain modification, thus improving the efficiency and success rate of strain development. Attached Figure Description

[0015] Figure 1 This is a schematic flowchart of a synthetic pathway analysis method assisted by organic acid derivatization reagents in one embodiment of the present invention; Figure 2 This is a structural block diagram of a synthetic pathway analysis system assisted by organic acid derivatization reagents in one embodiment of the present invention; Figure 3 This is a schematic block diagram of the structure of a computer device according to an embodiment of the present invention.

[0016] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0018] Reference Figure 1 This is a schematic flowchart of a synthetic pathway analysis method assisted by an organic acid derivatization reagent proposed in this invention, including the following steps: S1, Obtain a fermentation broth sample of gene-edited cells, wherein the fermentation broth sample contains intermediate metabolites in the amino acid synthesis process, and the intermediate metabolites include aldehyde or ketone precursors; S2, using an organic acid derivatizing agent to chemically derivatize the intermediate metabolite, converting the intermediate metabolite into a volatile derivative; S3, the derivatized fermentation broth sample is introduced into a gas chromatography-mass spectrometry instrument to separate and detect the volatile derivatives, and to obtain qualitative and quantitative data of the intermediate metabolites; S4, The qualitative and quantitative data are processed by a metabolic flux dynamics analysis model to analyze the metabolic flux distribution in the amino acid synthesis pathway; S5, based on the metabolic flux distribution, identify hidden metabolic nodes and flux-limiting nodes in the amino acid synthesis pathway; S6, output the analysis results of the hidden metabolic nodes and flux-limiting nodes to guide gene editing operations to optimize the amino acid synthesis pathway.

[0019] In one embodiment, for step S1, The steps for obtaining fermentation broth samples of gene-edited cells include: The gene-edited cells were centrifuged to remove cell debris and solid impurities, and fermentation broth samples were obtained. Antioxidants and protease inhibitors were added to the fermentation broth sample to inhibit the degradation of intermediate metabolites and enzymatic reactions.

[0020] In practice, the gene-edited cell culture broth after fermentation is centrifuged. This physical method rapidly separates solid impurities such as cell bodies and insoluble metabolites from the liquid phase containing the target intermediate metabolites, obtaining a clear fermentation broth sample. The optimized selection of centrifugation force and time is based on thoroughly removing cell debris while maximizing the retention of low-abundance metabolites sensitive to shear forces. Centrifugation only completes the initial separation. During subsequent sample processing and storage, intermediate metabolites in the sample (especially chemically reactive aldehyde or ketone precursors) are easily oxidized upon contact with air or transformed by residual enzymes in the sample (such as various dehydrogenases and transaminases), leading to changes in their true concentration and type, and introducing analytical errors. Therefore, this invention immediately adds antioxidants (such as ascorbic acid) and protease inhibitors (such as PMSF or EDTA) to the system after obtaining the clear fermentation broth. Antioxidants effectively scavenge dissolved oxygen and free radicals, blocking oxidation chain reactions; while protease inhibitors broadly inhibit the activity of various hydrolases, terminating the enzymatic reaction process. The synergistic effect of these two additives inhibits the degradation of intermediate metabolites and enzymatic reactions, freezing the metabolic state of the sample at the time of sampling, thereby ensuring the integrity of the sample.

[0021] In one embodiment, for step S2, The step of chemically derivatizing the intermediate metabolite using an organic acid derivatizing agent to convert the intermediate metabolite into a volatile derivative includes: Carboxylic acid derivatizing reagents are used as organic acid derivatizing reagents to undergo condensation reactions with aldehyde or ketone precursors in the presence of an acidic catalyst; The reaction is carried out under constant temperature and time conditions to completely convert the intermediate metabolite into a volatile derivative.

[0022] In this embodiment, an organic acid derivatizing reagent is used to chemically derivatize the intermediate metabolite, thereby addressing the problem that intermediate metabolites such as aldehydes or ketone precursors are difficult to separate and accurately quantify directly using gas chromatography-mass spectrometry (GC-MS) due to their high polarity, low volatility, and poor thermal stability. Specifically, a carboxylic acid derivatizing reagent, such as N,O-bis(trimethylsilyl)trifluoroacetamide or its derivatives, is used as the organic acid derivatizing reagent. The active groups contained in this type of reagent can specifically and efficiently condense with the aldehyde, ketone, and hydroxyl groups in the target metabolite in the presence of an acidic catalyst (such as trimethylchlorosilane). This condensation reaction introduces a hydrophobic trimethylsilyl group, replacing the active hydrogen atom in the metabolite molecule, thereby converting the intermediate metabolite into a chemically stable and significantly more volatile derivative. To ensure the thoroughness and reproducibility of the derivatization reaction and avoid analytical errors caused by incomplete or excessive reactions that generate byproducts, the reaction conditions were precisely controlled. By maintaining constant temperature and time, such as a constant temperature reaction at 70°C for 30 minutes, a uniform and optimal reaction environment was provided for all samples. This controlled environment ensured that the vast majority of target intermediate metabolites in the samples were completely converted into structurally homogeneous volatile derivatives, maximizing derivatization efficiency.

[0023] In one embodiment, for step S3, The steps of introducing the derivatized fermentation broth sample into a gas chromatography-mass spectrometry (GC-MS) instrument to separate and detect the volatile derivatives and obtain qualitative and quantitative data of the intermediate metabolites include: Volatile derivatives were separated by gas chromatography using a polar chromatographic column with a gradient temperature program. Mass spectrometry detection was performed using electron impact ionization mode, and a stable isotope-labeled analog was used as an internal standard to perform qualitative and quantitative analysis of the volatile derivatives, thereby obtaining qualitative and quantitative data of the intermediate metabolites.

[0024] In practice, the powerful separation capabilities of gas chromatography (GC) are utilized, employing polar chromatographic columns (such as DB-WAX stationary phases) to achieve high-resolution separation of multiple volatile derivatives in complex samples. To simultaneously ensure efficient separation and analysis of components with different polarities and boiling points, this embodiment employs a gradient temperature program, where the column oven temperature is gradually increased from a low to a high temperature according to a preset program. This ensures optimal separation of each component on the chromatographic column, avoids co-current peak phenomena, and provides pure component peaks for subsequent mass spectrometry detection. After separation, the components enter the mass spectrometry (MS) detector and are detected using electron impact ionization mode. This mode generates abundant and reproducible characteristic ion fragments, which, by comparison with a standard spectral library, enable precise qualitative analysis of volatile derivatives (i.e., intermediate metabolites before derivatization). Given the complexity of the fermentation broth sample matrix and potential fluctuations in instrument response, this embodiment employs an internal standard method to achieve high-precision quantitative analysis. A known amount of a stable isotope-labeled analogue (e.g., a ^13C or ^2H-labeled metabolite) is added as an internal standard during sample pretreatment. This internal standard exhibits highly consistent behavior with the target analyte during derivatization and detection, but its unique mass-to-charge ratio allows for differentiation by mass spectrometry. By calculating the response ratio of the target analyte to the internal standard, quantitative biases caused by sample pretreatment losses, instrument injection errors, and matrix inhibition effects can be effectively corrected.

[0025] In one embodiment, for step S4, The steps of processing the qualitative and quantitative data using a metabolic flux dynamics analysis model to analyze the metabolic flux distribution in the amino acid synthesis pathway include: The qualitative and quantitative data are input into a pre-constructed metabolic flow dynamics analysis model based on mass conservation and reaction kinetics; The model was fitted using a numerical optimization algorithm, and the metabolic flux distribution was calculated.

[0026] In practical implementation, static qualitative and quantitative data reflecting metabolite concentrations at a specific moment, obtained from GC-MS, are transformed into dynamic information that reveals the direction and rate of carbon flow in the metabolic network, i.e., metabolic flux distribution. Specifically, the qualitative and quantitative data are input into a pre-constructed dynamic analysis model of metabolic flux based on mass conservation and reaction kinetics. The model is pre-constructed based on biochemical knowledge of the target amino acid synthesis pathway, and its framework integrates all known enzymatic reaction steps of the pathway, the stoichiometry of each metabolic node (ensuring that atoms do not appear or disappear out of thin air based on the principle of mass conservation), and basic reaction kinetic characteristics. However, due to the complexity and redundancy of cellular metabolic networks, directly solving for flux distribution is a mathematically underdetermined problem (i.e., the number of equations is less than the number of unknowns). To solve this technical problem, this invention uses numerical optimization algorithms to fit the model, such as parameter estimation based on least squares or evolutionary algorithms: through iterative calculation, a set of most probable metabolic flux values ​​is found, such that the difference between the metabolite concentration predicted by this set of flux values ​​(model output) and the qualitative and quantitative data obtained from actual experimental measurements is minimized. This process essentially uses experimental data as constraints to compress the solution space of the model, thereby calculating a unique metabolic flux distribution that is biochemically reasonable and best matches the experimental data. The distribution chart illustrates the flux magnitude of each branch in the synthetic pathway.

[0027] In one embodiment, for step S5, The step of identifying hidden metabolic nodes and flux-limiting nodes in the amino acid synthesis pathway based on the metabolic flux distribution includes: By analyzing the low-flux regions and abnormal fluctuation points in the metabolic flux distribution, statistical tests are used to identify flux-limiting nodes. A graph-based path mining algorithm is applied to extract non-intuitive connection paths from the metabolic flow dynamic analysis model as hidden metabolic nodes.

[0028] In specific implementation, for step S5, key nodes in the pathway are identified based on the metabolic flux distribution, aiming to mine the engineering information contained in the metabolic flux distribution data, thereby identifying hidden metabolic nodes and flux-limiting nodes in the amino acid synthesis pathway. Specifically, flux-limiting nodes are identified by analyzing low-flux regions and abnormal fluctuation points in the metabolic flux distribution. If the flux of a reaction step is significantly lower than that of upstream and downstream steps, it constitutes a low-flux region, intuitively indicating that this may be a key bottleneck limiting the overall synthesis efficiency; while abnormal fluctuations in the flux of certain nodes in the metabolic network under different experimental conditions may indicate that their regulatory mechanisms are complex or that there are unknown diversions. However, observation alone is insufficient to draw reliable conclusions. This invention uses statistical tests (such as t-tests or analysis of variance) to determine flux-limiting nodes, that is, to determine whether the observed flux differences or fluctuations are statistically significant, thereby eliminating the interference of random errors and screening out the flux-limiting nodes that truly require engineering intervention. For more hidden metabolic nodes, they are usually not reflected in the main flux, but exist in the form of detours or compensatory paths. Traditional analytical methods struggle to uncover non-intuitive connection paths. This invention employs graph-based path mining algorithms (such as shortest path and subgraph enumeration) to extract pathways from the metabolic flux dynamics analysis model. The metabolic network is viewed as a graph composed of nodes (metabolites) and edges (reactions). By traversing all possible paths connecting the starting substrate and the target amino acid, it systematically uncovers bypasses or cycles with weak flow, not of mainstream interest, but potentially activated under specific genetic backgrounds or stress conditions. These pathways are defined as hidden metabolic nodes. By combining quantitative assessment of limiting nodes with systematic discovery of hidden pathways, a comprehensive and high-confidence target list for gene editing, ranging from explicit to implicit, is provided.

[0029] In one embodiment, for step S6, The analysis results of the hidden metabolic nodes and flux-limiting nodes are output to guide the steps of gene editing operations to optimize the amino acid synthesis pathway, including: Based on the identified hidden metabolic nodes and flux-limiting nodes, analytical results are generated that include metabolic pathway topology, flux distribution heatmap, and candidate gene editing targets. The analysis results are integrated with an automated gene editing platform to automatically generate experimental instructions containing specific gene manipulation protocols for implementation path optimization.

[0030] In practical implementation, based on the identified hidden metabolic nodes and throughput-limiting nodes, a comprehensive analytical result is generated, integrating a multi-dimensional visualized diagnostic report, including: a clear metabolic pathway topology diagram, intuitively displaying the entire synthetic network; a throughput distribution heatmap overlaid on the topology diagram, dynamically and visually presenting the throughput calculated in step S5 using color depth; and a clear list of candidate gene editing targets, which directly correspond to the identified metabolic throughput bottlenecks or key node genes of hidden pathways. To achieve high-throughput, standardized pathway optimization, the analytical result is further integrated with an automated gene editing platform. By establishing a standardized data interface, the candidate targets identified in the analytical result and the required operation types (such as knockout, inhibition, or overexpression) are automatically generated into experimental instructions containing specific gene operation protocols that can directly drive the platform. The instructions specify in detail the precise operations required for each target (e.g., the selection of gRNA sequences for CRISPR-Cas9, homologous recombination templates, or inducible promoters) for implementing efficient and precise pathway optimization.

[0031] Reference Figure 2 Here is a structural block diagram of a synthetic pathway analysis system assisted by an organic acid derivatization reagent in one embodiment of the present invention, comprising: The sample acquisition module is used to acquire fermentation broth samples of gene-edited cells; A biochemical reaction module is used to perform a chemical derivatization reaction on the intermediate metabolite using an organic acid derivatization reagent, converting the intermediate metabolite into a volatile derivative. The sample detection module is used to introduce the derivatized fermentation broth sample into a gas chromatography-mass spectrometry instrument to separate and detect the volatile derivatives and obtain qualitative and quantitative data of the intermediate metabolites. The model analysis module is used to process the qualitative and quantitative data through a metabolic flux dynamic analysis model to analyze the metabolic flux distribution in the amino acid synthesis pathway. The path identification module is used to identify hidden metabolic nodes and flux-limiting nodes in the amino acid synthesis pathway based on the metabolic flux distribution. The results output module is used to output the analysis results of the hidden metabolic nodes and flux-limiting nodes, which are used to guide gene editing operations to optimize the amino acid synthesis pathway.

[0032] For the specific implementation of each module in the above device example, please refer to the above method embodiments, which will not be repeated here.

[0033] Reference Figure 3 This invention also provides a computer device, which can be a server, and its internal structure can be as follows: Figure 3As shown, the computer device includes a processor, memory, display screen, input device, network interface, and database connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system, computer programs, and database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database stores the data corresponding to this embodiment. The network interface is used to communicate with external terminals via a network connection. When the computer program is executed by the processor, it implements the above-described method.

[0034] Those skilled in the art will understand that Figure 3 The structures shown are merely block diagrams of some structures related to the present invention and do not constitute a limitation on the computer devices on which the present invention is applied.

[0035] An embodiment of the present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described method. It is understood that the computer-readable storage medium in this embodiment can be a volatile readable storage medium or a non-volatile readable storage medium.

[0036] In summary, this invention obtains fermentation broth samples from gene-edited cells; uses organic acid derivatization reagents to chemically derivatize the intermediate metabolites, converting them into volatile derivatives; introduces the derivatized fermentation broth samples into a gas chromatography-mass spectrometry (GC-MS) instrument to separate and detect the volatile derivatives, obtaining qualitative and quantitative data of the intermediate metabolites; processes the qualitative and quantitative data using a metabolic flux dynamics analysis model to analyze the metabolic flux distribution in the amino acid synthesis pathway; identifies hidden metabolic nodes and flux-limiting nodes in the amino acid synthesis pathway based on the metabolic flux distribution; and outputs the analysis results of the hidden metabolic nodes and flux-limiting nodes to guide gene editing operations in optimizing the amino acid synthesis pathway, thereby achieving highly sensitive capture and quantification of difficult-to-detect metabolic intermediates in gene-edited cells, and thus completing the systematic analysis of the complete dynamic pathway of their amino acid synthesis network.

[0037] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the present invention and embodiments can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual-rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM, etc.

[0038] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, apparatus, article, or method. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, apparatus, article, or method that includes that element.

[0039] The above description is only a preferred embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. An organic acid derivative reagent-assisted synthesis path analysis method characterized by, The method comprises the following steps: obtaining a fermentation broth sample of a gene edited cell, wherein the fermentation broth sample comprises intermediate metabolites in an amino acid synthesis process, and the intermediate metabolites include aldehyde or ketone precursors; performing chemical derivatization reaction on the intermediate metabolites using an organic acid derivatization reagent to convert the intermediate metabolites into volatile derivatives; introducing the derivatized fermentation broth sample into a gas chromatograph-mass spectrometer to separate and detect the volatile derivatives, and obtaining qualitative and quantitative data of the intermediate metabolites; processing the qualitative and quantitative data by a metabolic flux dynamic analysis model to analyze metabolic flux distribution in the amino acid synthesis pathway; identifying hidden metabolic nodes and flux limiting nodes in the amino acid synthesis pathway according to the metabolic flux distribution; outputting the analysis results of the hidden metabolic nodes and flux limiting nodes to guide gene editing operation to optimize the amino acid synthesis pathway.

2. The method according to claim 1, wherein the synthetic pathway analysis method is assisted by an organic acid derivative reagent. The step of obtaining the fermentation broth sample of the gene edited cell comprises: performing centrifugal treatment on the culture broth of the gene edited cell to remove cell debris and solid impurities, and obtaining the fermentation broth sample; adding antioxidants and protease inhibitors to the fermentation broth sample to inhibit degradation and enzymatic reaction of the intermediate metabolites.

3. The method according to claim 1, wherein the synthetic pathway analysis method is assisted by an organic acid derivative reagent. The step of performing chemical derivatization reaction on the intermediate metabolites using an organic acid derivatization reagent to convert the intermediate metabolites into volatile derivatives comprises: using a carboxylic acid derivatization reagent as the organic acid derivatization reagent to perform condensation reaction with the aldehyde or ketone precursors in the presence of an acid catalyst; controlling the reaction temperature and time to be constant to completely convert the intermediate metabolites into volatile derivatives.

4. The method according to claim 1, wherein The step of introducing the derivatized fermentation broth sample into a gas chromatograph-mass spectrometer to separate and detect the volatile derivatives, and obtaining qualitative and quantitative data of the intermediate metabolites comprises: performing gas chromatography separation of the volatile derivatives by using a polar chromatographic column through a gradient temperature program; performing mass spectrometry detection using electron impact ionization mode, and performing qualitative and quantitative analysis of the volatile derivatives by using a stable isotope labeled analog as an internal standard through an internal standard method, to obtain the qualitative and quantitative data of the intermediate metabolites.

5. The method according to claim 1, wherein the synthetic pathway analysis method is assisted by an organic acid derivative reagent. The step of processing the qualitative and quantitative data by a metabolic flux dynamic analysis model to analyze metabolic flux distribution in the amino acid synthesis pathway comprises: inputting the qualitative and quantitative data into a metabolic flux dynamic analysis model based on mass conservation and reaction kinetics which is constructed in advance; performing fitting on the model by using a numerical optimization algorithm to calculate the metabolic flux distribution.

6. The method according to claim 1, wherein The step of identifying hidden metabolic nodes and flux limiting nodes in the amino acid synthesis pathway according to the metabolic flux distribution comprises: determining flux limiting nodes by analyzing low flux regions and abnormal fluctuation points in the metabolic flux distribution using statistical tests; extracting non-intuitive connection paths from the metabolic flux dynamic analysis model as the hidden metabolic nodes by applying a path mining algorithm based on graph theory.

7. The method according to claim 1, wherein the synthetic pathway analysis method is assisted by an organic acid derivative reagent. The output of the analysis results of the hidden metabolic nodes and flux limiting nodes is used to guide the gene editing operation to optimize the steps of the amino acid synthesis path, which includes: Based on the identified hidden metabolic nodes and flux limiting nodes, generate analysis results containing metabolic path topology, flux distribution heatmap and candidate gene editing target points; Integrate the analysis results with the automated gene editing platform to automatically generate experimental instructions containing specific gene operation schemes for implementing path optimization.

8. An organic acid derivative reagent-assisted synthetic pathway analysis system characterized by, It includes: A sample acquisition module is used to acquire a fermentation broth sample of a gene editing cell; A biochemical reaction module is used to perform chemical derivatization reaction on the intermediate metabolites using organic acid derivatization reagents to convert the intermediate metabolites into volatile derivatives; A sample detection module is used to introduce the derivatized fermentation broth sample into a gas chromatograph-mass spectrometer for separation and detection of the volatile derivatives to obtain qualitative and quantitative data of the intermediate metabolites; A model analysis module is used to process the qualitative and quantitative data through a metabolic flow dynamic analysis model to analyze the metabolic flux distribution in the amino acid synthesis path; A path recognition module is used to identify hidden metabolic nodes and flux limiting nodes in the amino acid synthesis path according to the metabolic flux distribution; A result output module is used to output the analysis results of the hidden metabolic nodes and flux limiting nodes for guiding the gene editing operation to optimize the amino acid synthesis path. 9.A computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the computer device is configured to perform the method according to any one of claims 1-8. The processor executes the computer program to realize the steps of the organic acid derivatization reagent assisted synthesis path analysis method in any one of claims 1 to 7.

10. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to realize the steps of the organic acid derivatization reagent assisted synthesis path analysis method in any one of claims 1 to 7.

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