869 results about "Metabolic pathway" patented technology

Disclosed is a system for detecting whether the breast cancer is benign or malignant based on multiple modalities, which comprises: an ultrasonomics model configured to extract breast tumor position information and breast tumor morphological features on the basis of an acquired grayscale breast ultrasound image, perform global interactive fusion on the breast tumor position information and breast tumor morphological feature information, and convert a Transformer encoder-based feature output into an output vector of the corresponding classification dimensions by means of a fully connected layer; a metabonomics model configured to obtain a metabolic fingerprint spectrogram and analyze the metabolic fingerprint spectrogram on the basis of a metabolic database and a predetermined significantly differential metabolite to obtain abnormal metabolic pathways, signal transduction pathways, and related biochemical reactions associated with breast cancer malignancy; and a detection module configured to perform joint modeling, based on the breast tumor position information, the breast tumor morphological features, and a peak value of the significantly differential metabolite of the breast cancer malignancy, to output a prediction result about whether the breast cancer is benign or malignant.

The invention relates to the field of gene engineering, and discloses a D-3-phosphoglycerate dehydrogenase mutant, a coding gene thereof and application of the D-3-phosphoglycerate dehydrogenase mutant and the coding gene. Compared with a protein with an amino acid sequence as shown in SEQ ID NO: 1, the mutant comprises mutation at the 131 site and / or the 285 site. The mutant can specifically catalyze a substrate 3-phosphoglycerate to synthesize 3-phosphate-hydroxypyruvic acid, can effectively promote synthesis of L-serine in a metabolic pathway of microorganisms, improves the yield and conversion rate of the L-serine, and reduces the yield of byproducts at the same time.

The invention belongs to the technical field of gene engineering, and particularly relates to application of a ZmDIR11 gene in regulating and controlling salt stress resistance of corn. After salt stress treatment, it is found that the ZmDIR11 gene mutant corn plant growth vigor and material accumulation are significantly lower than those of a wild type B73 material, an oxidative metabolism regulation path, proline accumulation, chlorophyll synthesis, lignan accumulation and a Na < + > / K < + > transport pathway are inhibited, and related metabolic indexes are significantly lower than those of the wild type B73 material. It is shown that the ZmDIR11 gene positively regulates and controls the salt-resistant metabolic pathway of the corn in the corn, and the salt tolerance of the corn is reduced after the ZmDIR11 gene is mutated. The research provides a new gene resource for corn salt-tolerant breeding by utilizing gene engineering.

The invention relates to the technical field of genetic engineering, and particularly discloses a genetic engineering bacterium for producing melanin as well as a construction method and application of the genetic engineering bacterium. According to the application, the yield of the melanin can be effectively increased by modifying a metabolic pathway of the genetically engineered bacterium, and the yield of the melanin reaches 6.2 g / L and 18.5 g / L respectively through shake-flask culture and 5L fermentation tank culture. Compared with the prior art, the yield of melanin produced by the genetically engineered bacterium is improved by 30% at the shake flask fermentation level, the fermentation yield of a fermentation tank is improved by 4.3 times, in addition, expensive tyrosine is changed into glucose as a fermentation precursor substance, the production cost is greatly reduced, and an efficient and feasible solution is provided for large-scale production of melanin.

The invention discloses a mesophilic carotenoid-producing recombinant yarrowia lipolytica strain as well as a construction method and application thereof, the recombinant strain exogenously expresses mesophilic original fatty acid desaturase (FAD3) and isocitrate dehydrogenase (IDH2) mutants from phaffia rhodozyma, and efficient synthesis under the condition of 30 DEG C is realized; secondly, a metabolic pathway of the recombinant strain is optimized based on a metabolic flow push-pull strategy, and isopentenyl pyrophosphate isomerase (IDI), farnesyl pyrophosphate synthase (ERG20), plant alkene dehydrogenase (CarB) and bifunctional plant alkene synthase (CarRP) are overexpressed, so that the flux of a precursor is increased; finally, gene multi-copy of astaxanthin synthase (crtS) and cytochrome P450 reductase (crtR) from phaffia rhodozyma is carried out, and the carotenoid production capacity of yarrowia lipolytica is further improved. The construction method of the mesophilic yarrowia lipolytica is simple, efficient synthesis of carotenoid can be better achieved at the higher temperature, the fermentation cost is greatly reduced, and the industrial production potential is achieved.

The invention discloses construction and application of an L-malic acid producing issatchenkia orientalis strain, and belongs to the technical field of microorganisms and the technical field of microbial fermentation and metabolic engineering. Through a metabolic engineering means, a cytoplasm metabolic pathway of an issatchenkia orientalis strain is transformed, and a pyruvate decarboxylase coding gene, glycerol dehydrogenase and lactic dehydrogenase are knocked out; a pyruvate carboxylase gene derived from aspergillus flavus, a malate dehydrogenase gene derived from corynebacterium glutamicum and phosphoenolpyruvate carboxylase derived from escherichia coli are screened and integrated, so that a cytoplasm rTCA cycle synthesis pathway is enhanced; inserting a dicarboxylic acid external transporter gene from schizosaccharomyces cerevisiae at a neutral site GD21, and knocking out endogenous dicarboxylic acid internal transporter; the L-malic acid yield of the modified yeast strain in the fermentation process is remarkably increased and reaches 140.16 g / L. The engineering strain provided by the invention has good industrial application potential in efficient L-malic acid production.

The invention discloses a gene and a protein for adjusting tobacco polyphenol aroma substances and application of the gene and the protein. The gene is a tobacco NtMYB28 gene, and the CDS sequence of the tobacco NtMYB28 gene is as shown in SEQ ID No. 1. The invention further discloses application of the tobacco NtMYB28 gene in regulating the content of endogenous polyphenol substances in tobacco and regulating and controlling the metabolic pathway of phenylpropane in tobacco. The key gene NtMYB28 capable of simply and effectively adjusting the content of polyphenol substances in tobacco and the metabolic pathway of phenylpropane is found, and the gene can be applied to efficient cultivation of new high-aroma tobacco materials and development and utilization of new high-value functional tobacco germplasm.

The invention discloses a tomato fruit cracking key regulation gene identification method, through the method, 41 key genes for regulating tomato cracking are determined and obtained for the first time, and the genes mainly participate in plant hormone synthesis, cell wall metabolism, wax and cuticle metabolism, absorption and transportation of mineral elements and water, and some transcription factors. Two regulation networks are established and comprise an ethylene-cell wall metabolic pathway and a transcription factor-water channel-mineral element. The research combines high-throughput sequencing and molecular biological techniques, enriches the cracking mechanism of tomato fruits on transcription and translation levels, and thus, has important scientific significance and application prospects.

The invention is applicable to the technical field of bioengineering, and provides a coding gene for enhancing iron deficiency stress tolerance of plants and application. According to the soybean GmMYB14 transcription factor disclosed by the invention, the problem that the growth of soybeans is limited in an iron-deficient environment, particularly calcareous soil and soda saline alkali soil, is solved by excavating and applying the encoding gene (the nucleotide sequence is shown as SEQ ID No.1) of the soybean GmMYB14 transcription factor. Experiments prove that after the gene is over-expressed in arabidopsis thaliana and soybean, the tolerance of plants to iron deficiency stress can be remarkably enhanced. The invention provides a key gene resource for molecular breeding: the GmMYB14 effectively promotes the absorption and utilization of plants on iron by regulating and controlling the metabolic pathway of phenylpropane, not only can improve the planting adaptability of soybeans in low-iron soil, but also can improve the yield and quality of the soybeans, provides powerful technical support for enlarging the planting area of the soybeans in iron-deficient soil regions, and has a wide application prospect. The method is of great significance in relieving insufficient soybean productivity in China and improving the self-sufficiency rate.

The invention relates to the field of bioelectricity data processing, and discloses a tumor cell metabolite distribution three-dimensional reconstruction method and system based on artificial intelligence, and the method comprises the steps: collecting the multi-modal data of tumor cells, recognizing the entity elements of the tumor cells and the corresponding entity relationship from the multi-modal data, and obtaining the entity relationship of the entity elements of the tumor cells; constructing a metabolite knowledge map of the tumor cells; according to the space coordinates of the metabolites and the microenvironment characteristic data of the tumor cells, analyzing a space aggregation mode of the metabolites in the tumor cells; in combination with the spatial distribution mode and the biological metabolic pathway of the metabolites, key features of the metabolites in the tumor cells are extracted, and a metabolite distribution discrimination network of the tumor cells is established; and identifying an abnormal distribution mode of the metabolite in the tumor cells, constructing a metabolite distribution three-dimensional model of the tumor cells, and outputting a metabolite three-dimensional distribution result of the tumor cells. According to the method, the accuracy and comprehensiveness of the three-dimensional distribution result of the tumor cell metabolites can be improved.

The invention relates to the technical field of teasel breeding, and discloses a teasel germplasm resource multi-character collaborative screening breeding method, which comprises the following steps: multi-omics data acquisition: extracting teasel germplasm leaf DNA (deoxyribonucleic acid), and capturing exon regions of disease resistance and metabolism related genes by adopting a targeted sequencing technology to obtain an SNP (single nucleotide polymorphism) marker matrix; the method comprises the following steps: collecting root extracts, detecting medicinal components through ultra-high performance liquid chromatography-mass spectrometry, and constructing a metabolite abundance matrix; measuring phenotype data of plant height, root length, root weight, root rot morbidity and survival rate under drought stress; key site and metabolite correlation analysis: constructing a Bayesian network containing SNP markers, metabolite and phenotypes by using a graph database, and carrying out cross validation through a leave-one-out method. The dipsacus asper germplasm resource multi-character collaborative screening breeding method aims at solving the problem that a traditional breeding method lacks systematic integration analysis of genomes and metabolic pathways in dipsacus asper multi-character collaborative improvement.

The present disclosure provides a recombinant yeast host cell for converting a carbohydrate to ethanol and acetone. The recombinant yeast host cell comprises an engineered metabolic pathway to convert acetyl-CoA to acetone, a downregulated native alcohol dehydrogenase (ADH) gene, and a heterologous alcohol dehydrogenase.

The invention discloses a construction method of a soil microorganism nitrogen metabolism function prediction model, and relates to the technical field of environmental microbiology and agricultural information, and the method comprises the following steps: S1, constructing a spatial-temporal heterogeneity representation engine, and dynamically decoupling a multi-level gradient of a soil environment through an adaptive spatial-temporal mesh generation algorithm; according to the construction method of the soil microorganism nitrogen metabolism function prediction model, the adaptive capacity of the soil microorganism nitrogen metabolism function prediction model in a complex environment is improved, and multi-level environment gradient dynamic analysis from a centimeter-level rhizosphere microdomain to a kilometer-level landscape scale is realized; the problem of cross-scale feature fusion caused by temporal-spatial resolution mismatch of a traditional model is solved, the simplified hypothesis of a traditional statistical model on the synergistic-antagonistic relationship of microbial functional genes is broken through, a dynamic coupling mechanism of a nitrogen metabolism path under environmental disturbance is accurately quantified, and the prediction error is reduced compared with the prior art.

The invention relates to the technical field of collaborative prediction, in particular to a plant polygene stress resistance collaborative prediction method and system based on a federal map neural network. The method comprises the following steps: modeling a multilayer heterogeneous graph according to acquired plant genome data; constructing a dynamic graph neural network model based on time sequence perception; training a dynamic graph neural network model by using the multi-layer heterogeneous graph, and performing distributed privacy calculation on the multi-layer heterogeneous graph by using a federated graph neural network; generalization training is carried out on the small sample scene data based on multi-task learning and a cross-species migration mechanism; and obtaining a gene function prediction result. Through a multi-layer heterogeneous graph fusion technology and a dynamic graph neural network design of time sequence perception, multi-dimensional biological information such as gene regulation, protein interaction, metabolic pathways and stress response can be captured at the same time, and time sequence change characteristics of gene expression in the plant stress response process can be captured at the same time.

The invention discloses application of MUC12 gene in preparation of drugs for reducing rectal cancer liver metastasis, and belongs to the technical field of medical biology. According to the invention, the clear relation between colorectal cancer liver metastasis and fructose metabolism reprogramming is revealed from a molecular mechanism for the first time. The invention provides a brand-new therapeutic target and strategy by determining the brand-new transfer promoting factor MUC12 and the mediated fructose metabolism regulation effect thereof. Different from the traditional therapy only aiming at the strategies of tumor cell proliferation, blood supply and the like, the method disclosed by the invention intervenes aiming at a tumor nutrition metabolic pathway, and can weaken the metabolic adaptation and proliferation capacity of metastatic tumor cells in the liver more specifically. Experimental results show that the functions of targeted inhibition of MUC12 or downstream fructose metabolism key enzymes KHK and ALDOB thereof can significantly reduce the invasion and metastasis ability of tumor cells, and at the same time, normal growth of primary tumors cannot be significantly affected.

The invention provides a Baijiu brewing process simulation method and system, and the method comprises the steps: constructing a metabolic network model of a flavor synthesis path in a Baijiu brewing process, initializing the boundary condition of the metabolic quantity in the metabolic network model, and carrying out the flux balance constraint of the metabolic path of a target flavor substance according to the boundary condition, obtaining the constraint flux of the metabolic pathway of the target flavor substance, and further calculating the metabolic flux distribution of the target flavor substance in the white spirit brewing process; determining a reaction rate constant of each process parameter combination according to the concentration gradient characteristic and the spatial distribution characteristic of the concentration change information of the target flavor substance; and performing metabolism simulation on the brewing reaction of the target flavor substance according to the metabolic flow distribution and each reaction rate constant, outputting the metabolic quantity of the target flavor substance under each process parameter combination, and further screening the brewing process parameters of the target flavor substance. Based on the scheme, multi-parameter metabolism simulation of a flavor substance synthesis path in a white spirit brewing process can be realized.

The embodiment of the invention discloses a sleep peptide and differential metabolite detection method for caenorhabditis elegans, belongs to the technical field of organism metabolism, and aims to research sleep-awakening key metabolite of caenorhabditis elegans and a regulation mechanism of the sleep-awakening key metabolite. According to the sleep peptide for caenorhabditis elegans, the sleep peptide is an F4 monomer as shown in SEQ ID NO: 1. Compared with the prior art, the sleep and awakening process of the caenorhabditis elegans under the intervention of the goat milk-derived sleep peptide is analyzed through a metabonomics technology, the key metabolite for regulating and controlling sleep and awakening is successfully screened out, and a core metabolic pathway related to the key metabolite is disclosed. The application also constructs a metabolite-pathway-target regulation framework, fills the blank of sleep research in the aspect of metabolic regulation, provides a scientific basis for a sleep intervention strategy based on metabolic regulation, and also lays a foundation for developing metabolic markers of sleep states in the future.

The present invention discloses a yeast engineering bacterium containing a (-)-α-bisabolol synthase mutant and its application. By designing (-)-α-bisabolol synthase, the present invention obtains a mutant with high expression level, co-expresses the mutant with ERG20, highly expresses the key rate-limiting enzymes in the metabolic pathway, deletes the promoter to reduce the side reaction pathway, and adopts a multi-copy strategy to improve the metabolic flux in the (-)-α-bisabolol biosynthesis pathway. The shake-flask fermentation yield of the yeast engineering bacterium constructed by the present invention is close to 70 mg / L, which is about 35 times higher than that of the starting strain, and has broad application prospects in the biological fermentation production of (-)-α-bisabolol.

The embodiment of the invention provides a recombinant pichia pastoris strain as well as a construction method and application thereof. The construction method comprises the following steps: by taking a pichia pastoris strain as a host strain, constructing a dual-synthesis path of phenylalanine ammonialyase and tyrosine ammonialyase in the host strain to obtain a first engineering strain; removing chorismic acid feedback inhibition of the first engineering strain based on metabolic engineering to obtain a second engineering strain; optimizing an aromatic amino acid synthesis route of the second engineering strain to obtain a third engineering strain; knocking out a branch metabolic pathway of the third engineering strain to obtain a fourth engineering strain; increasing precursor supply of the fourth engineering strain to obtain a recombinant pichia pastoris strain; according to the construction method provided by the embodiment of the invention, the synthesis path of p-coumaric acid can be systematically optimized, the recombinant pichia pastoris strain for efficiently producing p-coumaric acid by taking methanol as a carbon source is constructed, and compared with a host strain, the recombinant pichia pastoris strain has the advantage that the yield of p-coumaric acid is remarkably increased.

The invention relates to the technical field of microorganism monitoring, and particularly discloses a wetland microorganism activity monitoring method and system.The method comprises the steps that a plurality of first time sequence data sets of different layers and related to different wetland state parameters are obtained; analyzing and acquiring a parameter change mode of each layer according to the first time sequence data set; similarity matching is carried out based on the parameter change mode and a pre-constructed parameter correlation model library, so that microbial metabolism modes of different layers are determined; determining an activity evaluation mode of the microorganisms in the corresponding layer based on a microorganism metabolism mode; generating an activity evaluation result according to the activity evaluation mode and the first time sequence data set; according to the method, the biological action signal and the non-biological process signal are distinguished, the evaluation accuracy is improved, the activity evaluation mode corresponding to the metabolism mode is determined based on the identified metabolism mode, and the difference of evaluating the activity of microorganisms in different metabolism pathways by adopting one index is avoided.

The invention provides a yak healthy feeding optimization method and system based on machine learning. The yak healthy feeding optimization method comprises the steps of obtaining a basic data set; according to the basic data set, performing erucic acid metabolic pathway feature construction to obtain a feature set representing erucic acid mediated lipid metabolic pathway; according to the lipid metabolism path feature set, meat quality improvement effect quantification is carried out, and probability distribution of unsaturated fatty acid deposition efficiency is obtained; according to the probability distribution, feeding amount reverse deduction is carried out, and a high-erucic-acid rapeseed oil intake interval is obtained through calculation; health benefit balance is carried out according to a high-erucic acid rapeseed oil intake interval, and a stable feeding strategy is obtained; biological rationality verification is carried out according to a stable feeding strategy, the continuity of the mapping relation between the feeding amount and the meat quality index is analyzed based on the topological structure of the feature space, and a healthy yak feeding optimization scheme is obtained. The feeding precision, the meat quality improvement effect stability and the yak health guarantee level are improved.

An ultrasound-metabolic synergistic system for diagnosing SLN metastasis of breast cancer. A deep learning model based on grayscale ultrasound is constructed to predict SLN metastasis of breast cancer, and 9 grayscale deep features and 15 grayscale manual features associated with SLN metastasis are obtained. A matrix material based on two-dimensional material MXene / multi-walled carbon nanotubes improves the detection of small metabolic molecules in blood, and metabolomics analysis results show that this has certain potential in detecting SLN metastasis of breast cancer, while revealing metabolic pathways closely associated with metastasis, such as the glucose-alanine cycle and glycolysis, suggesting that alterations in relevant molecular pathways may underlie heterogeneous features in ultrasound radiomics. The combination of ultrasound omics and metabolomics further improves the diagnostic performance for SLN metastasis of breast cancer. Therefore, organic integration of the two serves the diagnosis of SLN metastasis of breast cancer, providing a new strategy and theoretical basis for the accurate diagnosis of SLN metastasis of breast cancer, and possesses practical clinical application values.

The invention discloses escherichia coli recombinant bacteria with high glycolic acid yield and a construction method of the escherichia coli recombinant bacteria, and belongs to the technical field of bioengineering. Lactate dehydrogenase ldhA, phosphate transacetylase pta, acetokinase ackA and pyruvate oxidase poxB are knocked out in escherichia coli, key enzymes isocitrate lyase aceA and glyoxylate reductase ghrA in a glycollic acid synthesis path are over-expressed in a genome level, conversion of carbon flow to glycollic acid is enhanced, and the glycolic acid is converted into glycolic acid. On the basis, malic acid synthase AaceB, malic acid synthase GglcB and glycollic acid oxidase glcDEF are knocked out, a branch metabolic pathway is blocked, an efficient strain which is free of plasmids and resistance genes and does not need to induce glycollic acid production is constructed, the accumulation amount of L-valine fermented in a 5L fermentation tank for 48 hours reaches 51.2 g / L, the yield is 0.6 g / g, and the production intensity is 1.06 g / L / h.

The invention relates to the technical field of plant breeding, and particularly discloses a metabonomics-based alfalfa stress resistance gene analysis function and a breeding method. The core of the method is that screening is carried out by combining a tissue culture technology with metabolic intervention; an alfalfa explant is inoculated into an induction culture medium containing a specific metabolic pathway regulator for metabolic intervention culture; then transferring the obtained callus to a verification culture medium containing the metabolism regulator and an abiotic adversity stress factor at the same time, and carrying out metabolism mark verification and screening; and finally regenerating the screened cell line into a complete plant. According to the method, metabolic pressure is actively applied to the cellular level, and dual verification screening is implemented, so that early-stage, efficient and accurate breeding of the stress-resistant alfalfa material is realized, and the technical problems of long period, low efficiency and insufficient utilization of metabolic information in traditional breeding are solved.

The invention discloses a multi-dimensional efficacy evaluation system for colon cancer targeted drug screening, and relates to the technical field of medical assistance. Comprising a data acquisition module, an inference engine module and an output module. The data acquisition module acquires an organ sample response data set (including apoptosis rate A1, activity decline degree A2 and image structure change score B1) and a patient background data set (including gene mutation discrete variable set G and metabolic pathway continuous variable set M). The inference engine module executes dominant condition rules: generating a negative weight factor alpha according to a gene mutation state and a metabolic activation threshold value; generating a deduction item gamma based on a preset drug-resistant mutation subset; performing weighted calculation on the apoptosis rate and the activity decline degree to generate a basic drug effect score beta, and increasing beta through a critical value; and finally generating a comprehensive response score S. And the output module outputs a drug effect judgment result according to the S, and multi-dimensional accurate evaluation is realized.

Aspects of the disclosure relate to methods and compositions for diagnosing and / or treating subjects having one or more symptoms of Autism Spectrum Disorder (ASD) or subjects at risk of developing ASD. In some embodiments, methods comprise determining and / or modulating levels of chorismate and / or a molecule within a chorismate metabolic pathway in a subject. In some embodiments, methods comprise determining and / or modulating levels of a microbial feature (e.g., a Sarcina bacterium) in a subject. In some embodiments, methods comprise determining and / or modulating levels of proton flux in a gastrointestinal tract in a subject.

The invention discloses a risk assessment method, system and equipment for idiopathic pulmonary arterial hypertension, and belongs to the field of pulmonary arterial hypertension. According to the method, SNP data containing genotypes and effect values, protein marker expression quantity, metabonomics and clinical data are obtained, the SNP effect values are corrected based on linkage imbalance reference information, and PRS is calculated in combination with the genotypes; constructing a protein expression score by utilizing the site effect value and the expression quantity of the pQTL, and fusing the protein expression score with the PRS to form a target PRS; carrying out dimensionality reduction on metabolome data by adopting sparse coding, extracting sparse coefficients of IPAH related metabolic pathways, and converting the sparse coefficients into metabolic pathway scores; converting the clinical indexes into clinical risk scores; based on the clinical parameter distribution target PRS, the metabolic pathway score and the weight coefficient of the clinical risk score, calculating a risk assessment value; and finally, matching the evaluation value with a preset risk threshold value, and outputting a risk evaluation level. And the IPAH risk assessment accuracy of common people is improved.

The invention belongs to the technical field of gene engineering, and discloses recombinant yarrowia lipolytica as well as a construction method and application thereof. The recombinant yarrowia lipolytica PGA1 is obtained by carrying out heterologous expression on an arabidopsis thaliana inositol oxygenase gene and a pseudomonas syringae uronic acid dehydrogenase gene in the yarrowia lipolytica by utilizing a genetic engineering technical means. The recombinant yarrowia lipolytica PGA10 capable of efficiently synthesizing glucaric acid (GA) is finally obtained by further modifying six genes of related metabolic pathways of the recombinant yarrowia lipolytica PGA1. The GA yield of the PGA10 reaches 2233.24 mg / L and is 66.27 times that of PGA1, and the effect is remarkable. The invention not only constructs a GA synthesis method, but also defines the influence of related genes such as opi1 on GA synthesis, and provides reference for the research of heterologous synthesis of GA by microorganisms.

The invention discloses a double-carbon-source mixed fermentation metabolism regulation system for single-cell protein production, and belongs to the technical field of fermentation engineering. The method solves the problems that in the prior art, the independent utilization efficiency of methanol and methane is low, the metabolic pathways of microorganisms to the two carbon sources are different, and high-efficiency single-cell protein production is difficult to realize, and by comprehensively analyzing various data related to historical parameters in the historical parameters, the production efficiency of the single-cell protein is improved. According to the method, key metabolic nodes having significant influence on the yield and quality of the single-cell protein can be accurately identified, and reasonable weights are distributed for the key metabolic nodes, so that the production quality of the single-cell protein in fermentation engineering is optimized, and the realization of a production target is ensured; meanwhile, according to the production target of the actual fermentation engineering, the optimization cost of the key metabolism nodes is evaluated, excessive optimization of high-cost nodes is avoided, the economic benefit of single-cell protein production is improved, the cost budget of the fermentation engineering is reduced, and the flexibility of the fermentation engineering and the scientificity of metabolism regulation decision are enhanced.

The invention provides a teenager disease risk dynamic prediction method and system, and the method comprises the steps: obtaining an electronic health record and subcutaneous metabolite dynamic concentration data of a teenager, and the electronic health record comprises chronic disease related information, a genetic risk value and historical diagnosis data; performing multi-modal fusion on the metabolite concentration data, the genetic risk value and the historical diagnosis data according to a time axis to form a mixed time sequence information set; adaptive optimization is carried out on the mixed time sequence information set, and the collaborative change trend of metabolite fluctuation characteristics and genetic characteristics is identified from the optimized mixed time sequence information set; generating a dynamic graph by adopting a graph neural network based on the collaborative change trend; and tracking an abnormal conduction chain of a metabolic pathway in the dynamic map in real time, and calculating a risk probability matched with the growth stage of the teenagers according to the abnormal conduction chain and chronic disease related information. The dynamic prediction precision and timeliness of the chronic disease risk of teenagers are improved.