Method for improving yield of branched chain aldehyde of lactococcus lactis based on regulation and control of luxS gene and application

Abstract

The invention discloses a method for improving yield of branched chain aldehyde of lactococcus lactis based on regulation and control of a luxS gene and application, and belongs to the field of system biology. Gene function verification and genome scale metabolic network model analysis are creatively combined, the phenotypic effect of the luxS gene is confirmed, and more importantly, the internal action mechanism of the luxS gene is disclosed from the system level, that is, the whole metabolic network flow is influenced by regulating and controlling multiple key enzymes such as transaminase, decarboxylase, dehydrogenase and decarboxylase. The invention reveals that the quorum sensing core gene luxS has a new function of regulating and controlling synthesis of branched chain aldehyde in lactococcus lactis for the first time, and an intercellular communication system is directly linked with production of specific flavor metabolites. The invention provides a brand-new and higher-level regulation target and thought for producing flavor substances by microbial fermentation, and gets rid of the limitation that only metabolic pathway terminal enzyme is singly modified traditionally.

Description

Technical Field

[0001] This invention relates to a method and its application for increasing the yield of branched aldehydes in Lactococcus lactis based on regulating the luxS gene, and belongs to the field of systems biology. Background Technology

[0002] Lactococcus lactis is a Gram-positive bacterium widely found in dairy fermentation environments. It converts sugars into lactic acid through metabolic pathways such as homolactic fermentation. Due to its recognized safety and high acid-producing capacity, it is widely used as a starter strain in the fermentation of cheese, yogurt, and other food industries, and serves as a potential cell factory for producing high-value-added compounds. However, naturally occurring Lactococcus lactis strains have relatively fixed metabolic pathways. 3-Methylbutyraldehyde (with malt and chocolate flavors) and 2-methylbutyraldehyde (with fruit flavors) are important food flavor compounds widely used in the food, beverage, and feed industries. Currently, their production mainly relies on chemical synthesis or plant extraction, but this involves complex processes, high costs, and environmental concerns. The production of natural branched-chain aldehydes through microbial fermentation is a current research hotspot.

[0003] Currently, with the development of metabolic engineering technology, researchers' investigations into the regulatory role of metabolic networks and their metabolic pathways mainly focus on traditional metabolic engineering modification strategies, such as using genetic engineering to locally knock out or overexpress key genes in glycolysis pathways or lactate dehydrogenase. However, due to the complexity of metabolic networks, the modification results often fail to achieve the expected effects. Quorum sensing is a mechanism of intercellular communication in microorganisms. The luxS gene, responsible for synthesizing autoinducer-2 (AI-2), is a key gene in the conserved quorum sensing system in many bacteria. However, how luxS precisely regulates the metabolic network of Lactococcus lactis, especially the degradation pathway of branched-chain amino acids, to affect the production of branched-chain aldehydes, remains unclear.

[0004] To address the aforementioned issues, genome-scale metabolic network models can systematically explore the physiological characteristics of Lactococcus lactis, providing a basis for the efficient design and modification of Lactococcus lactis' ability to produce flavor compounds, as well as for optimizing fermentation conditions and increasing metabolic yield. Summary of the Invention

[0005] To address the shortcomings of the existing technologies, this invention provides a method and application for increasing the yield of branched-chain aldehydes in Lactococcus lactis based on regulating the luxS gene. The aim is to solve the technical problem of the lack of effective means in the existing technologies to enhance the yield of important food flavor compounds such as 3-methylbutyraldehyde and 2-methylbutyraldehyde in Lactococcus lactis strains.

[0006] The first technical solution of this invention is a method for constructing a genome-scale metabolic network model of Lactococcus lactis, comprising the following steps: (1) Perform genome sequencing on Lactococcus lactis and then perform whole-genome sequencing on the sequencing results; (2) Obtain global metabolic response data of Lactococcus lactis, extract key information of metabolic response, and standardize the metabolic response and metabolite names; (3) Using the ipynb platform and the COBRA toolbox, based on the species code and genome annotation results of Lactococcus lactis in the KEGG database, the genome information was automatically retrieved and a preliminary draft model was constructed. (4) Fill in the missing metabolic reactions in the sketch model, delete the duplicate and incorrect metabolic reactions, and refine the model; (5) Validate the model and manually correct it. Use metaGapFill to identify metabolites that cannot be produced or consumed, fill metabolic gaps, and ensure the connectivity and integrity of core metabolic pathways. (6) Refinement of biomass equation: Biomass is measured by experimentally measuring the dry weight of the organism and integrated into the biomass reaction.

[0007] (7) For model simulation and analysis, use the COBRA toolbox to perform flux balance analysis, gene necessity test and growth phenotype array simulation on the model.

[0008] The second technical solution provided by this invention is an analytical method for metabolic pathways affecting branched-chain aldehyde synthesis in Lactococcus lactis. The Lactococcus lactis genome-scale metabolic network model constructed by the method described in the first technical solution is transformed into a computer-recognizable mathematical coefficient matrix. Using the flow balance analysis tools in the COBRA and CarveME toolbox, with the maximization of branched-chain aldehyde synthesis as the objective function, the metabolic flux distribution of other metabolic pathways is calculated to identify key metabolic pathways.

[0009] In some embodiments, the method includes the following steps: S1. To collect global metabolic response data of *Lactococcus lactis*, a coarse model was loaded using COBRApy, branched-chain aldehyde metabolic pathways and metabolites were added, and the upper and lower limits of the model's response flux (-1000~1000 mmol / g / h) were adjusted to ensure reaction quality balance. All metabolites, genes, and reaction formats used were rewritten in SBML format. S2. Perform GapFill on the model. Based on the reaction formula, where l and u are the lower and upper limits of reaction i, z is an indicator variable (zero if no reaction is used, 1 otherwise), c is the user-defined cost associated with using i reactions, is the flux of the objective, and t is the lower limit of the objective. Calculate the minimum number of reactions required. Sv=0 V*≥t l i ≤vi ≤ui v i =0 if z i =0; To set up the growth medium environment for subsequent model validation, MS15 and M17 culture media were set, both of which were set to a model-recognizable ID format. The necessary growth environment medium was selected based on the differences in metabolic flux results. S3. To set constraints for subsequent model validation, gene knockout simulation analysis was used to shut down the uplink and downlink fluxes of the AI2tex (Ai2transport, outer membrane) and AI2tpp (Quorum signal AI-2 exporter) metabolic reactions. S4. Hierarchical metabolic network analysis was performed on the genome-scale metabolic network models of Lactococcus lactis under different genetic engineering operations (luxS gene overexpression, luxS gene knockout). Based on the flux metabolic network analysis, key metabolic nodes were analyzed and changes in branched aldehyde production were predicted. Since 3-methylbutyraldehyde and 2-methylbutyraldehyde are the final flavor compounds of branched aldehydes metabolized by Lactococcus lactis, the maximization of 3-methylbutyraldehyde and 2-methylbutyraldehyde synthesis was taken as the objective function. S5. Correlation analysis was performed on the Lactococcus lactis 408 branched aldehyde network and environmental culture conditions. The conditions for high-yield branched aldehyde production were obtained by using the networkx toolkit.

[0010] The third technical solution provided by this invention is the application of the gene luxS in regulating the branched-chain aldehyde synthesis of Lactococcus lactis. The application is to increase the branched-chain aldehyde synthesis content in Lactococcus lactis by overexpressing the gene luxS, or to reduce the branched-chain aldehyde synthesis content by inhibiting or knocking out the gene luxS in Lactococcus lactis.

[0011] In some embodiments, the branched aldehydes include 3-methylbutyraldehyde and 2-methylbutyraldehyde.

[0012] In some embodiments, the nucleotide sequence of the gene luxS is shown in SEQ ID NO.1.

[0013] The fourth technical solution provided by the present invention is a method for increasing the synthesis of branched aldehydes in Lactococcus lactis, wherein the method is to overexpress the gene luxS in Lactococcus lactis.

[0014] In some embodiments, the branched aldehydes include 3-methylbutyraldehyde and 2-methylbutyraldehyde.

[0015] In some embodiments, the nucleotide sequence of the gene luxS is shown in SEQ ID NO.1.

[0016] The fifth technical solution provided by the present invention is a genetically engineered bacterium, wherein the genetically engineered bacterium uses Lactococcus lactis as the host cell and overexpresses the gene luxS in the host cell.

[0017] In some embodiments, the nucleotide sequence of the gene luxS is shown in SEQ ID NO.1.

[0018] In some embodiments, the lactococcus is lactococcus 408.

[0019] The sixth technical solution provided by this invention is the gene luxS, the nucleotide sequence of which is shown in SEQ ID NO. 1. The seventh technical solution provided by this invention is a recombinant vector carrying the gene luxS described in the sixth technical solution.

[0020] The eighth technical solution provided by the present invention is a recombinant cell containing the gene luxS described in the sixth technical solution or transformed with the recombinant vector described in the seventh technical solution.

[0021] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) This invention reveals for the first time that the quorum sensing core gene luxS has a novel function in regulating branched-chain aldehyde synthesis in Lactococcus lactis, directly linking the intercellular communication system with the production of specific flavor metabolites. This provides a new and higher-level regulatory target and approach for the microbial fermentation production of flavor substances, overcoming the limitations of traditional methods that only modify terminal enzymes of metabolic pathways.

[0022] (2) This invention innovatively combines gene function verification with genome-scale metabolic network model (GEM) analysis, which not only confirms the phenotypic effect of the luxS gene, but more importantly, reveals its intrinsic mechanism of action at the system level: that is, it affects the entire metabolic network flow by regulating multiple key enzymes such as ilvE (transaminase), kivD (decarboxylase), adhE (dehydrogenase), and aldB (decarboxylase). This multi-target, pathway-based regulatory understanding makes the modification strategy of this invention more systematic and scientific, and the effect is more significant. Attached Figure Description

[0023] Figure 1 This is a flowchart illustrating the construction of the Lactococcus lactis 408 genome-scale metabolic network model of the present invention.

[0024] Figure 2 This is a topological diagram of quorum sensing regulation in *Lactococcus lactis* according to the present invention.

[0025] Figure 3 Map showing the expression levels of key genes involved in branched-chain aldehyde metabolism predicted by the model under luxS deletion. Figure 4Figure showing the improvement in branched aldehyde yield through model-guided process optimization. Figure 5 The graph shows the GC-MS determination of branched aldehyde production in Lactococcus lactis 408 according to the present invention.

[0026] Figure 6 Changes in the activity of AI-2 molecules between wild-type and mutant types (24h).

[0027] Figure 7 Growth curves (24h) for wild type and mutant.

[0028] Figure 8 A graph showing the predicted branched aldehyde yield from the model.

[0029] Figure 9 The necessary reactions and necessary (a) MS15 metabolic distribution and (b) M17 metabolic distribution of the model of the present invention under different culture environment conditions are shown.

[0030] Figure 10 The standard curves used in this invention to determine the yield of branched aldehydes are shown in (a) the standard curve of 3-methylbutyraldehyde and (b) the standard curve of 2-methylbutyraldehyde. Detailed Implementation

[0031] refer to Figures 1-10 The preferred embodiments of the present invention will be described below. It should be understood that the embodiments are for better explanation of the present invention and are not intended to limit the present invention.

[0032] Raw materials used in the examples: L. lactis 408 is a type of lactic acid bacteria (Lactococcus lactis), whose biological name is Lactococcus lactis. It was deposited on June 23, 2021, at the China Center for Type Culture Collection (CCTCC), located at Wuhan University Collection Center, Luojia Mountain, Wuchang District, Wuhan, Hubei Province, 430072, China, with accession number CCTCCNO: M 2021742. It is disclosed in patent CN113832075A.

[0033] LuxS original sequence (5'-3'): ATGGCTGAAGTAGAATCTTTTCAATTAGACCACACAAAAGTACTTGCCCCTTATGTCCGCTTAATCGGTAGCGAAACTGGGCCTAAAGGCGATGTTATCACTAATTTTGACGTTCGTTTTGTTCAACCTAATGCGAATGCCATTGGAATGGCCGCTTTACACACTATTGAGCATAGCATGGCTAGTTTAATTCGCGATAGAATTGATGGCATGATTGACTTTTCACCTTTTGGATGTCAA ACTGGTTTCCACATGATTATGTGGGGTGAACATAGTTCAGAAGAAATTGCTAAAGTAATTAAATCTTTCTAGAAGAGCTTGCAAGTGACGAATTTGGTTGGGATAATGTCCCTGGTGTTGCTGAAAAAGAATGCGGAAATTACCGTAATCACTCACTTTTCGGTGCTAAAGAATGGTCTAAGAAAATTCTTTCTGAAGGAATTTCTACTGACCCTTACGAACGTAAAGTAATTTAA (SEQ ID NO.1).

[0034] Example 1: Construction of a genome-scale metabolic network model of Lactococcus lactis like Figure 1 As shown, the specific steps are as follows: Step 1: Genomic DNA was extracted from Lactococcus lactis 408 cells using a kit, a library was constructed, and the samples were sequenced using Illumina short reads. The test data were evaluated using FastQC. Based on the whole genome sequencing results of Lactococcus lactis 408, the genome was functionally annotated using the gene annotation tool Prokka to obtain the annotation results.

[0035] Step 2: Collect metabolic reaction pathways and related information from the KEGG, MetaCyc, and BioCyc databases. Use BiGG data to standardize the names of metabolic reactions and metabolites, and use Python to automatically create a mapping table of KEGG reactions to BiGG reactions and metabolites. Manually add missing metabolites and reactions, compile them into an xlsx file, and use the ipynb platform to read the script and update the final metabolite and reaction information in the model. Set the reversibility of each reaction in the model, specifying that the upper and lower limits of reversible metabolic reactions are both -1000 to 1000 mmol / g / h.

[0036] Step 3: Based on the model, the essential genes and reactions for the growth of *Lactococcus lactis* 408 were predicted. Growth environments under different conditions were manually created and compiled into a .tsv file. The COBRApy script was used to read the file, and gap filling was performed under different environmental conditions (as shown in Tables 1 and 2). This demonstrates that the model can accurately reflect the actual physiological and metabolic state of the bacteria under different culture conditions. Figure 9 As shown, under MS15 conditions, there are 412 essential genes and 340 essential reactions, mainly enriched in amino acid and nucleotide synthesis; under M17 conditions, there are 330 essential genes and 340 essential reactions, concentrated in substrate uptake and lipid metabolism. This is mainly because after GapFill optimization, the model further improved substrate utilization efficiency and reduced the internal synthetic burden.

[0037] Step 4: Gene knockout simulation analysis, manually shutting down the up-bound and low-bound metabolic responses of AI2tex (Ai2 transport, outermembrane) and AI2tpp (Quorum signal AI-2 exporter). Based on metabolic flux analysis, summarize the metabolic bottleneck of Lactococcus lactis 408 branched-chain aldehyde.

[0038] Step 5: Using the scikit-learn machine learning and network analysis toolkit, a hierarchical metabolic network was constructed for the metabolic pathways, metabolites, and refining model. Based on flux-based metabolic network analysis, the branched-chain aldehyde metabolic nodes were identified as kivd (α-keto acid decarboxylase), adhE (aldehyde / alcohol dehydrogenase), aldB (acetolactate decarboxylase), and ilvE (branched-chain amino acid transaminase). The luxS gene acts as an upstream regulator; knocking out the luxS gene can inhibit the expression of these genes, thereby affecting the production of branched-chain aldehydes, such as... Figure 2 and Figure 3 As shown in the figure. The results showed that under the condition of simulated knockout of the luxS gene, the expression levels of kivd (α-keto acid decarboxylase), adhE (aldehyde / alcohol dehydrogenase), aldB (acetolactate decarboxylase), and ilvE (branched-chain amino acid transaminase) all decreased. The inhibitory effect of the luxS gene on the four key branched-chain aldehyde genes, from largest to smallest, was ilvE, aldB, adhE, and kivd.

[0039] Step Six: Correlation analysis was performed using NetworkX on the branched-chain aldehyde metabolic network and environmental culture conditions (pH, leucine, isoleucine, glucose, temperature). The results showed that the maximum yield of branched-chain aldehydes was achieved under the following conditions: glucose 40 g / L, leucine 2.4 g / L, isoleucine 1.4 g / L, pH 7, and culture temperature 30℃. Figure 3 and Figure 4 .

[0040] Table 1 M17 Culture Medium Setup Format

[0041] Table 2 Composition of MS15 culture medium

[0042] Example 2: Strain Construction The specific steps are as follows: Step 1: Knockout of the branched-chain aldehyde metabolism-related gene luxS. Using genomic DNA of L. lactis 408 as a template, the 1000bp gene fragment to the left of luxS was amplified by PCR using primers luxS-HA1-F / R (see Table 3), and the 1000bp gene fragment to the right of luxS was amplified by PCR using primers luxS-HA2-F / R. The pll25 plasmid containing the kanamycin resistance gene was constructed first, and primers sgRNA were used. F / R PCR amplification yielded a 103 bp sgRNA fragment. Three gene fragments were sequentially inserted into the ApaI / XbaI site of plasmid pLL25 to obtain plasmid pLL25-P23-LuxS.

[0043] The gene knockout plasmid pLL25-P23-luxS, which had been constructed, was transformed into L. lactis408 cells via electroporation. The transformed cells were then plated on GM17 plates containing 10 μg / mL Em antibody and incubated statically at 30°C for 24 days. After 36 hours, single colonies were picked, cultured, and their genomes were extracted. Gene knockout mutants were screened by PCR using primers luxS-KO-YZ-F and luxS-KO-YZ-R, and confirmed by sequencing. After n consecutive passages at 30℃ in the absence of antibiotics, pLL25-P23-luxS was lost. Antibiotic resistance analysis and PCR identification were used to finally obtain the luxS gene knockout mutant strain L. lactis 408ΔluxS.

[0044] Step 2: Construction of overexpression of the branched aldehyde-related gene luxS Based on the whole-genome sequencing results of *L. lactis* 408, the luxS gene (gene number SIT-408_orf00267, SEQ ID NO.1) was located in the gene annotation file. Using the gene number, the coding sequence was found in the gene sequence file. The complete fragment of the luxS gene, with a size of 477 bp, was obtained through PCR amplification and gel extraction. Seamless cloning was used to ligate this sequence with the enzyme-digested pIB184 linear vector. The overexpression vector construction flowchart is shown in the figure. Transformation was performed on plates, and positive clones were picked. Colony PCR was performed on pIB184-F / luxS-R using the corresponding specific primers. The target band was approximately 900 bp. Plasmids were extracted from the positive clones with verified bands and sent to Shanghai Shenggao Biotechnology for sequencing. Successfully sequenced plasmids were electroporated into competent *Lactococcus lactis* 408 cells. After multiple passages until plasmid elimination, the recombinant strain 408-OBluxS was constructed.

[0045] Table 3 Primer Information

[0046] Example 3 Determination of strain-related indicators The specific steps are as follows: Step 1: Growth capacity determination of the three bacterial strains. First, *Lactococcus lactis* 408, *Lactococcus lactis* 408 overexpression luxS, and *Lactococcus lactis* 408ΔluxS were multiplied twice overnight in M17 broth at 30℃. During the culture process, the bacterial density of the samples was measured every two hours at a wavelength of 600nm (e.g., ...). Figure 7 By measuring the growth curves of three bacterial strains, it was found that the luxS gene can affect the growth ability of Lactococcus lactis.

[0047] Step 2: Determination of branched-chain aldehydes L. lactis 408, recombinant strain 408-OBluxS, and L. lactis 408ΔluxS by gas chromatography-mass spectrometry. Stable early-stage cells were obtained by overnight incubation at 30°C in M17 medium, followed by centrifugation at 8000×g for 10 min at 4°C. The obtained cells were washed twice with 50 mM β-glycerophosphate sodium buffer (pH 7.5). The cells were added to amino acid medium (see Table 4). The cell density at 600 nm was measured, with a cell-free mixture used as a control, to achieve a final cell density of 20 at 600 nm. Growth was terminated by rapid freezing of the vials in liquid nitrogen after 24 h of incubation at 30°C. Before flavor analysis, the vials were stored at -80°C. The temperature was then increased to 240°C at 10°C / min and finally isothermed for 10 min. The MS parameters used for analysis were as follows: transfer line temperature, 250 °C; ion source, electron impact mode; electron energy, 70 eV; ion trap temperature, 230 °C; and full scan mode (35–450 m / z). Volatile compounds were identified using the NIST 2.0 mass spectrometry library or chromatographic methods published in the literature. 3-Methylbutyraldehyde and 2-methylbutyraldehyde were quantified by comparison with standard curves. Standard curves were established using 3-methylbutyraldehyde standard solutions at concentrations of 50, 100, 250, 500, and 750 μmol / L and 2-methylbutyraldehyde at concentrations of 20, 30, 40, 50, and 100 μmol / L (e.g., [missing information]). Figure 10 (As shown). Among the 3-methylbutyraldehyde production, the highest yield was observed in strain 408-OBluxS, an overexpression strain of strain 408, at 64.592 μg / mL. The yield of 2-methylbutyraldehyde showed a similar trend. The luxS mutant strain remained the lowest yield strain at 15.243 μg / mL (as shown in Table 4 and...). Figure 5 (As shown). The maximum error rate of 21.37% is mainly because the actual measured values ​​are very low; even if the absolute error is small, the calculated error rate will be very large. Based on the above experimental results, it can be demonstrated that the luxS gene can affect the yield of branched aldehydes from Lactococcus lactis 408.

[0048] Table 4 Comparison of branched aldehyde yield and model-predicted yield, and error rate

[0049] Table 5 Amino Acid Culture Medium Formulation

[0050] Step 3: AI-2 signal molecule determination. The AI-2 bioluminescence experiment used *V. harvestyi* BB170 as an indicator bacterium (provided by Haibo Biotechnology Co., Ltd.). *L. lactis* 408, recombinant strain 408-OBluxS, and *L. lactis* 408ΔluxS were cultured in M17 medium until the logarithmic growth phase. A 1% inoculum was then added to fresh M17 medium and cultured for 12 hours. Every 2 hours, the bacterial culture was collected and divided into two portions. One portion was used to determine the OD600 value, and the other portion was centrifuged at 6000 rpm for 20 minutes. The supernatant was filtered through a sterile 0.22 μm filter for later use. *V. harvestyi* BB170 was inoculated into AB medium and cultured at 30°C with shaking (OD600 0.7-1.2). Then, it was diluted 1:5000 with fresh AB medium, shaken to mix, and the diluted solution was mixed with the sample to be tested. The sample was then cultured in the dark for 4 hours as the test sample. Bioluminescence values ​​were measured using a multimode microplate reader, and relative light units were used as the measurement value for AI-2 activity. Sterile supernatant of strain BB170 served as a positive control, AB medium as a negative control, and M17 medium as a medium control.

[0051] The results are as follows Figure 6 As shown in the figure, the specific results are shown in Table 6.

[0052] Table 6. Relative fluorescence intensity (RLU) of Lactococcus lactis 408 and its mutant strains over 24 hours.

[0053] Depend on Figure 6 Table 6 shows that within 2-24 hours, the relative fluorescence intensity of the Lactococcus lactis 408 luxS overexpressing strain AI-2 was higher than that of Lactococcus lactis 408 and higher than that of Lactococcus lactis 408 ΔluxS, indicating that the luxS gene can affect the production of signaling molecules in Lactococcus lactis 408 AI-2.

[0054] The present invention has been disclosed above with reference to preferred embodiments, but it is not intended to limit the present invention. Anyone skilled in the art can make various modifications and alterations without departing from the spirit and scope of the present invention. Therefore, the scope of protection of the present invention should be defined by the claims.

Claims

1. A method for constructing a genome-scale metabolic network model of Lactococcus lactis, characterized in that, Includes the following steps: (1) Perform genome sequencing on Lactococcus lactis and then perform whole-genome sequencing on the sequencing results; (2) Obtain global metabolic response data of Lactococcus lactis, extract key information of metabolic response, and standardize the metabolic response and metabolite names; (3) Using the ipynb platform and the COBRA toolbox, based on the species code and genome annotation results of Lactococcus lactis in the KEGG database, the genome information was automatically retrieved and a preliminary draft model was constructed. (4) Fill in the missing metabolic reactions in the sketch model, delete the duplicate and incorrect metabolic reactions, and refine the model; (5) Validate the model and manually correct it. Use metaGapFill to identify metabolites that cannot be produced or consumed, fill metabolic gaps, and ensure the connectivity and integrity of core metabolic pathways. (6) Refinement of biomass equation: Biomass is measured by experimentally measuring the dry weight of the organism and integrated into the biomass reaction. (7) For model simulation and analysis, use the COBRA toolbox to perform flux balance analysis, gene necessity test and growth phenotype array simulation on the model.

2. An analytical method for analyzing metabolic pathways affecting branched-chain aldehyde synthesis in Lactococcus lactis, characterized in that, The Lactococcus lactis genome-scale metabolic network model constructed by the method described in claim 1 is transformed into a computer-recognizable mathematical coefficient matrix. Using the flow balance analysis tools in the COBRA and CarveME toolbox, with the maximization of branched aldehyde synthesis as the objective function, the metabolic flux distribution of other metabolic pathways is calculated, and key metabolic pathways are identified.

3. The application of the gene luxS in regulating the synthesis of branched aldehydes in Lactococcus lactis, characterized in that, The application involves increasing the content of branched-chain aldehyde synthesis by overexpressing the gene luxS in Lactococcus lactis, or reducing the content of branched-chain aldehyde synthesis by inhibiting or knocking out the gene luxS in Lactococcus lactis, the nucleotide sequence of which is shown in SEQ ID NO.

1.

4. The application according to claim 3, characterized in that, The branched aldehydes include 3-methylbutanal and 2-methylbutanal.

5. A method for increasing the synthesis of branched-chain aldehydes by Lactococcus lactis, characterized in that, The method involves overexpressing the gene luxS in Lactococcus lactis, the nucleotide sequence of which is shown in SEQ ID NO.

1.

6. The method according to claim 5, characterized in that, The branched aldehydes include 3-methylbutanal and 2-methylbutanal.

7. A genetically engineered bacterium, characterized in that, The genetically engineered bacteria use Lactococcus lactis as the host cell and overexpress the gene luxS in the host cell. The nucleotide sequence of the gene luxS is shown in SEQ ID NO.

1.

8. Gene luxS, characterized in that, The nucleotide sequence of the gene luxS is shown in SEQ ID NO.

1.

9. A recombinant vector carrying the gene luxS as described in claim 8.

10. Recombinant cells containing the gene luxS of claim 8 or transformed with the recombinant vector of claim 9.

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