Gentamicin C1a high-yield biological manufacturing method based on metabolic network modeling and reverse metabolic engineering modification

Abstract

The invention belongs to the field of microbial engineering, and provides a gentamicin C1a high-yield biological manufacturing method based on metabolic network modeling and reverse metabolic engineering renovation, which comprises the following steps: S1, constructing a genome scale metabolic model of a target production strain, predicting and screening a first target gene in positive correlation with gentamicin biosynthesis by using the model; s2, performing whole genome sequencing on the gentamicin high-yield mutant strain, and identifying a second target gene related to the high-yield character through comparative genomics analysis; s3, combining the first target gene predicted in the step S1 and the second target gene identified in the step S2, and constructing to obtain a recombinant engineering strain; s4, carrying out fermentation culture on the recombinant engineering strain, and supplementing materials in the fermentation process; by remarkably improving the production efficiency and strain performance of gentamicin C1a, important technical support and theoretical basis are provided for green biological manufacturing of antibiotics.

Description

Technical Field

[0001] This invention belongs to the field of microbial engineering, specifically a method for producing high-yield gentamicin C1a based on metabolic network modeling and reverse metabolic engineering. Background Technology

[0002] Gentamicin, an important aminoglycoside antibiotic, is widely used clinically to treat various bacterial infections. Gentamicin C1a is one of its key active components, exhibiting significant antibacterial activity, especially against drug-resistant Gram-negative bacteria. Currently, gentamicin production mainly relies on microbial fermentation, particularly using *Micromonospora echinospora* as the production strain. However, traditional production methods suffer from low yield, high cost, and inefficient process control, making it difficult to meet the growing market demand and economic requirements.

[0003] Regarding the aforementioned technologies, although the development of metabolic engineering and synthetic biology has provided powerful tools for the construction of microbial cell factories, the inventors believe that the following shortcomings exist in the development of high-yield gentamicin strains: Existing technologies mostly rely on random mutagenesis and screening, or single-gene manipulation of known pathways, which are inefficient and highly indiscriminate, and cannot systematically identify and coordinate key metabolic bottlenecks and regulatory nodes affecting product synthesis. The molecular mechanisms behind the high-yield traits of high-yield strains obtained through traditional mutagenesis are often unclear. The biosynthesis of gentamicin involves complex metabolic networks and multi-level regulation. Overexpression of genes involved in the biosynthetic pathway often fails to fully release the production potential due to limitations such as precursor supply, energy balance, reducing power matching, or transcriptional regulation. A multi-target synergistic modification strategy is needed. After gentamicin C1a accumulates to a certain concentration in the fermentation broth, it inhibits the growth and metabolism of the cells themselves, limiting further increases in yield.

[0004] To address the problems raised in the background art, those skilled in the art have proposed a method for manufacturing high-yield gentamicin C1a biopharmaceuticals based on metabolic network modeling and reverse metabolic engineering. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention provides a method for producing high-yield gentamicin C1a based on metabolic network modeling and reverse metabolic engineering. This method solves the problems of existing technologies that rely heavily on random mutagenesis and screening, or single-gene manipulation of known pathways, which are inefficient and highly indiscriminate. These methods fail to systematically identify and coordinate key metabolic bottlenecks and regulatory nodes affecting product synthesis. Furthermore, the molecular mechanisms behind the high-yield traits of high-yield strains obtained through traditional mutagenesis are often unclear. Due to limitations such as precursor supply, energy balance, reducing power matching, or transcriptional regulation, the production potential cannot be fully released, requiring a multi-target synergistic modification strategy. Additionally, the accumulation of gentamicin C1a in the fermentation broth to a certain concentration inhibits the growth and metabolism of the cells, limiting further yield increases.

[0006] A method for manufacturing high-yield gentamicin C1a biopharmaceuticals based on metabolic network modeling and reverse metabolic engineering includes the following steps: S1: Construct a genome-scale metabolic model of the target production strain and use the model to predict and screen the first target genes positively correlated with gentamicin biosynthesis; S2: Whole-genome sequencing was performed on the high-yield gentamicin mutant strain, and comparative genomics analysis was used to identify the second target gene associated with the high-yield trait. S3: Combine the first target gene predicted in step S1 and the second target gene identified in step S2, and co-express them in the target production strain to construct a recombinant engineered strain. S4: The recombinant engineered strain is fermented and cultured, and feed is added during the fermentation process, and adsorption resin is added to remove the product in the fermentation broth in situ.

[0007] Preferably, the target production strain in step S1 is Micromonospora echinococcosis, and the genome-scale metabolic model is the iFX1172 model, which contains 2022 metabolic reactions, 1641 metabolites and 1172 genes.

[0008] Preferably, the first target gene in step S1 is at least one selected from the genC gene encoding 2-deoxy-acyl-inosyl synthase and the metK gene encoding S-adenosylmethionine synthase.

[0009] Preferably, the second target gene in step S2 is the BldD gene, which encodes a global transcriptional regulatory factor.

[0010] Preferably, the combination in step S3 is co-expression of the genC gene, the metK gene, and the BldD gene.

[0011] Preferably, in step S4, the feeding strategy includes adding a carbon source and a nitrogen source, wherein the carbon source contains sucrose and the nitrogen source contains corn steep liquor.

[0012] Preferably, in step S4, the adsorption resin is a microporous resin 001×8, and the product is gentamicin C1a.

[0013] Preferably, the strain is Micromonospora echinococcosis, whose genome integrates and co-expresses exogenous genC, metK and BldD genes.

[0014] A recombinant engineered strain constructed by the method of any one of claims 1-8, wherein the strain is Micromonospora echinococcosis, and its genome integrates and co-expresses exogenous genC gene, metK gene and BldD gene.

[0015] Preferably, the recombinant engineered strain is used in the production of gentamicin C1a.

[0016] Compared with the prior art, the present invention has the following beneficial effects: 1. This invention establishes the first high-quality genome-scale metabolic model iFX1172 for Micromonospora echinospora. The model covers 2022 reactions, 1641 metabolites and 1172 genes, and has high phenotypic prediction consistency and metabolic network coverage. It provides systematic theoretical tools and database support for the metabolic research and engineering modification of this species.

[0017] 2. This invention uses metabolic model prediction and genome analysis of high-yield mutants to screen gene targets that significantly promote gentamicin synthesis, and identifies and verifies key metabolic engineering targets.

[0018] 3. By combining the expression of the above three target genes, the present invention achieves a gentamicin C1a yield of 226.4 mg / L, which is 40.1% higher than the starting strain KL01. Further combining carbon and nitrogen source optimization and resin adsorption process, the gentamicin C1a titer is finally increased to 894.1 mg / L, which is about 4.5 times higher than the original strain, thus achieving a significant increase in the yield of gentamicin C1a single component.

[0019] 4. Through metabolic flux analysis and targeted metabolomics, this invention demonstrates that engineered strains significantly improve precursor supply and energy metabolism efficiency by enhancing TCA cycle activity, improving ATP supply, and balancing redox states, providing an intrinsic driving force for the efficient synthesis of gentamicin and elucidating the metabolic mechanism behind high yield.

[0020] 5. This invention effectively alleviates the product inhibition effect and prolongs the metabolic activity of the cells by screening the optimal combination of carbon and nitrogen sources and combining it with in-situ adsorption technology of microporous resin, thereby further improving production stability and final yield, and developing a process optimization strategy suitable for industrial fermentation.

[0021] 6. This invention, through a systematic research strategy integrating computational models, genomics, metabolic engineering, and process control, is not only applicable to the optimization of gentamicin production, but also provides a referable methodological system for the efficient biomanufacturing of secondary metabolites from other actinomycetes.

[0022] In summary, this invention significantly improves the production efficiency and strain performance of gentamicin C1a, providing important technical support and theoretical basis for the green biomanufacturing of antibiotics. Attached Figure Description

[0023] Figure 1 GEM construction of Micromonas ATCC15837 for this invention and whole genome analysis of Micromonas 49-92S-GM03 mutant strain (A) Schematic diagram of iFX1172 modification and development pipeline (B) Response distribution by metabolic subsystem (C) Memorandum score (D) Predicted and measured growth rate (E) Predicted and measured specific production rate of gentamicin (F) Using Circos (v 0.69-8) Visualization of the complete genome sequence of Micromonospora 49-92S-GM03 (G) K-mer analysis of sequencing data (H) Homology of nucleic acid level between strain 49-92S-GM03 and Streptomyces azureina A3 (2) (H) Homology of nucleic acid level between strain 49-92S-GM03 and Streptomyces azureina A3 (2) (I) Consistency of nucleic acid level between strain 49-92S-GM03 and Micromonospora ATCC15837 (J) Homology of nucleic acid level between strain 49-92S-GM03 and Streptomyces azureina A3 (K) Homology of protein level between strain 49-92S-GM03 and Micromonospora ATCC15837; Figure 2 The target prediction and metabolic engineering analysis of this invention includes: (A) Target prediction of gentamicin overproduction using modified forced target throughput (FSEOF); ​​(B) Pathway classification of 24 predicted targets across 6 different pathways; (C) Selected targets for combinatorial modification in the construction of a gentamicin cell factory; (D) Engineering of *Micromonospora echinococcus* 49-92S; (E) Gentamicin potency of a stepwise engineered *Micromonospora echinococcus* 49-92S strain; and (F) Cell growth of a stepwise engineered *Micromonospora echinococcus* 49-92S strain. Figure 3Physiological characteristics analysis of *Micromonospora echinococcus* fermentation for the present invention: (A) Engineering modification of *Micromonospora echinococcus* 49-92S; (B) Gentamicin titer of progressively engineered *Micromonospora echinococcus* 49-92S strain; (C) Cell growth of progressively engineered *Micromonospora echinococcus* 49-92S strain; (D) Engineering modification of *Micromonospora echinococcus* 49-92S; (E) Gentamicin titer of progressively engineered *Micromonospora echinococcus* 49-92S strain; (F) Cell growth of progressively engineered *Micromonospora echinococcus* 49-92S strain; (G) Oxygen uptake rate and carbon dioxide emission rate; (H) Total sugar and ammonium ion concentration; (I) PMV and gentamicin titer; (J) Dissolved oxygen and pH value. Figure 4 Metabolic characteristics analysis of strains 49-92S-KL01 and 49-92S-KL02 of the present invention in a 5L bioreactor: (A) Fermentation results of strain 49-92S-KL01; (B) Fermentation results of strain 49-92S-KL02; (C) Overview of intracellular metabolite concentration trends of strains 49-92S-KL01 and 49-92S-KL02. Figure 5 The fermentation optimization analysis diagram for the overproduction of gentamicin in this invention includes: (A) the effect of different carbon sources on gentamicin C1a titer; (B) the effect of different nitrogen sources on gentamicin C1a titer; (C) the effect of combined carbon and nitrogen sources on gentamicin C1a titer; (D) the effect of extracellular gentamicin C1a concentration on yield; (E) the total sugar and ammonium ion concentrations of strains 49-92S and Mech12 in a 5L bioreactor; and (F) the results of PMV and gentamicin C1a titer detection for strains 49-92S and Mech12 in a 5L bioreactor. Figure 6 Principal component analysis (PCA) and correlation analysis of intracellular metabolites of Micromonospora echinosporia 49-92S-KL01 and 49-92S-KL02 at different time periods for the present invention: (A) 24 hours; (B) 48 hours; (C) 72 hours; (D) 96 hours; (E) 120 hours; (F) correlation heatmap analysis. Figure 7 Analysis of intracellular reducing cofactor levels of Micromonospora echinococcosis KL01 and KL02 for the present invention: (A) Intracellular ATP / ADP ratio (B) Intracellular NADH / NAD+ ratio. Detailed Implementation

[0024] The embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples. The following examples are for illustrative purposes only and should not be construed as limiting the scope of the invention.

[0025] Example 1: As shown in the attached document Figure 1 To be continued Figure 7 As shown: This invention provides a method for manufacturing high-yield gentamicin C1a biopharmaceuticals based on metabolic network modeling and reverse metabolic engineering, comprising the following steps: S1: Constructing a genome-scale metabolic model and predicting the first target gene. Using *Micromonospora echinospora* ATCC15837 as the target strain, the RAVEN toolbox (v2.7.8) was used. The high-quality consensus model Sco-GEM for *Streptomyces cerevisiae* was used as a template. Model reconstruction was performed based on protein homology, combined with manual refinement. The first genome-scale metabolic model (GEM) for *Micromonospora echinospora* was finally constructed, named iFX1172. This model contains 2022 metabolic reactions, 1641 metabolites, and 1172 genes, achieving a total score of 71% on the MEMOTE assessment, demonstrating high-quality predictive ability. Using the iFX1172 model, flux balance analysis was performed in the COBRA toolbox using a forced target flux scan method. Simulations were performed with glucose as the carbon source, gradually limiting the theoretical maximum biomass from 25% to 85% to maximize gentamicin synthesis flux, thereby identifying 24 reactions strongly positively correlated with gentamicin production rates, such as... Figure 2 As shown in Figures A and B. Based on the model annotation, two key genes were identified as the first target genes: genC (encoding 2-deoxy-acyl-inosyl synthase, which is involved in the first step of gentamicin biosynthesis) and metK (encoding S-adenosylmethionine synthase, which provides the cofactor required for methylation modification). S2: Whole-genome sequencing and reverse engineering were used to identify the second target gene. Whole-genome sequencing was performed on the high-genome-producing gentamicin mutant strain *M. echinospora* 49-92S-GM03, obtained through ARTP mutagenesis. Comparative genomics analysis compared the mutant's genome sequence with the original strain or the ATCC15837 reference genome, identifying 381 gene mutations, including 4 SNPs, 365 deletions, and 12 insertions. Functional annotation and phenotypic association analysis of these mutant genes were performed to screen for beneficial mutations associated with high yield. Reverse engineering validation revealed that integrating the BldD gene (encoding a global transcription regulator) at a specific mutation site significantly increased gentamicin production. After introducing the BldD gene carrying this mutation into the starting strain 49-92S, the constructed Mech04 strain achieved a gentamicin yield of 664.8 mg / L, a 29.3% increase compared to the control. Figure 3 As shown in section B. Therefore, the BldD gene was identified as the second target gene.

[0026] The production performance of the original 49-92S strain was further improved by ARTP random mutagenesis based on computer vision and deep learning platform. The results showed that the high-yielding mutant M. echinospora 49-92S-GM03 produced approximately 998 mg / L gentamicin, which was about 72.7% higher than the parent strain. The whole genome of 49-92S-GM03 was sequenced using DNBSEQ 2000 and Nanopore platforms, and single-base correction was performed using GATK (v1.6-13). The complete genome of the Micromonospora echinospora mutant 49-92S-GM03 consists of a single circular chromosome with a length of 7,819,078 bp and an average GC content of 72.46%, with an accuracy of 99.93%. Figure 1 (As shown in F). K-mer analysis (k = 15 here) was used to assess the sequence integrity and completeness of the genome assembly. Figure 1 (The G portion). It is estimated that the entire genome size is approximately 7.74 M, close to the actual genome size obtained. Furthermore, Figure 1 Section H shows the nucleic acid collinearity plot of strains 49-92S-GM03 and S. coelicolor A3.2. The results show that the Map Length accounts for only 0.201% of the Refs Length, indicating very few collinear regions and a large amount of structural variation between the two strains (Table S3). Specifically, between 2,000,000 bp and 2,500,000 bp in the genome of 49-92S-GM03, compared with S. coelicolor A3.2, 49-92S-GM03 has an additional insertion sequence of approximately 500,000 bp. This insertion sequence contains several genes related to secondary metabolite synthesis, such as polyketide synthase genes and non-ribosomal peptide synthase genes, which may give GM03 a unique function in the synthesis of secondary metabolites. In addition, there are several inverted regions in the GM03 genome. For example, at genomic positions between 4,000,000 bp and 4,500,000 bp, the gene sequence of GM03 is completely reversed compared to that of S. coelicolor A3.2. These inverted regions contain several genes related to cell wall synthesis, such as peptidoglycan synthase and lipopolysaccharide synthase genes. The inversions may affect the expression regulation of these genes, thereby altering the cell wall structure and function of GM03. Figure 1Figure 1 shows the nucleic acid linearity plots of GM03 and *M. echinospora* ATCC15837. The results show that the Map Length accounts for 80.886% of the Refs Length, indicating a large number of collinear regions between the two strains, but also some significant structural variations. Specifically, the GM03 genome contains multiple insertion and deletion regions. For example, between 5,000,000 bp and 5,500,000 bp in the GM03 genome, compared to *M. echinospora* ATCC15837, GM03 has an additional insertion sequence of approximately 500,000 bp. This insertion sequence contains several genes related to nitrogen metabolism, such as nitrate reductase and nitrite reductase genes, which may give GM03 a stronger ability in nitrogen metabolism. In addition, the GM03 genome also contains several inverted regions. For example, at genomic positions between 6,000,000 bp and 6,500,000 bp, the gene sequence of GM03 is completely reversed compared to that of M. echinospora ATCC15837. These inverted regions contain several genes related to energy metabolism, such as cytochrome oxidase and ATP synthase genes, and the inversions may affect the expression regulation of these genes, thereby altering the energy metabolism efficiency of GM03.

[0027] The genome of *M. echinospora* 49-92S-GM03 was annotated using various bioinformatics tools, identifying 3988 protein-coding genes. The final annotated dataset included 7324 protein-coding genes from RAST and 6783 from Prokka. Furthermore, 79 tRNA genes, 9 rRNA genes, and 59 sRNA genes were identified in the genome. Fourteen CRISPR sequences and 1431 tandem repeat sequences were predicted to be present in the genome. Genes in the entire *M. echinospora* 49-92S-GM03 genome were then classified using WEGO 2.0 based on secondary terms from the three ontologies of gene ontology (cellular components, molecular functions, and biological processes). It was found that most genes are involved in catalytic activity and metabolic processes, rather than other functions. Figure 4 Part A). The classification of KEGG pathways in protein-coding genes is shown in (see Part A). Figure 4Part B of the subsystem contains 3988 coding sequences, with 371 and 327 sequences assigned to the "carbohydrate metabolism" and "amino acid metabolism" categories, respectively, ranking first and second in subsystem distribution. The "cofactor and vitamin metabolism" category also accounts for a significant proportion with 254 coding sequences, which may be closely related to its enhanced energy metabolism capacity. Furthermore, the biosynthetic potential for secondary metabolite production was analyzed using "antiSMASH v5.1.2". Specifically, antiSMASH predicted a gene cluster with 96.08% sequence identity to the previously reported gentamicin synthesis gene cluster of M. echinospora ATCC15835 (GenBank accession number: KY971520) (MacNeil et al., 1992). This gene cluster, located between 2726320 bp and 2768160 bp, contains 32 open reading frames and has the same gene arrangement as the gentamicin synthesis gene cluster of M. echinospora ATCC15835. Furthermore, this gene cluster shares 99.99% sequence identity with the gentamicin synthesis gene cluster of the reported gentamicin B industrial strain M. echinospora CCTCC M 2018898. Beneficial genes involved in gentamicin biosynthesis were characterized and optimized. The metK gene was overexpressed in strain 49-92S to form strain Mech02. Finally, glutamine synthase glnA was selected for overexpression to form strain Mech03, as the gentamicin biosynthesis process requires multiple aminotransferase steps. Results showed that the growth of strain Mech01 was not significantly different from the initial strain, but its fermentation titer was increased by approximately 23.9% compared to the initial strain. Figure 2 (Part E). Furthermore, overexpression of the metK gene in strain Mech02 significantly improved the growth of *Micromonospora echinococcus*. The PMV of strain Mech02 was 19.5% higher than that of the original strain. Figure 2 (Part F). The Mech02 strain increased the gentamicin titer by 12.8%, but significantly improved the gentamicin yield to 6.0 mg / L / h, which was approximately 66.7% higher than that of the 49-92S strain. Figure 5 Compared to the starting strain, strain Mech03 showed only a 7.2% increase in gentamicin production while maintaining a similar growth rate. Figure 2 (Part F of the middle section).

[0028] Furthermore, to investigate the potential mechanism of efficient gentamicin synthesis in the 49-92S-GM03 mutant strain, whole-genome sequencing of the gentamicin-producing strain was performed. The results showed that 381 mutations were identified in the 49-92S-GM03 mutant strain, including 4 single nucleotide polymorphisms (SNPs), 365 deletions, and 12 insertions. Through functional annotation and bioinformatics analysis, these mutated genes were classified into functional categories such as metabolism-related, regulatory-related, and membrane transport-related, with some mutations concentrated in secondary metabolic pathways and directly related to gentamicin synthesis. Subsequently, five mutated genes (BldD, msmX, rhaB, serA, and entF) obtained from the above functional categories were integrated into the parental strain 49-92S to identify beneficial mutated genes that contribute to improving gentamicin biosynthesis in *Micromonospora echinococcosis* strains. Figure 3 (Part A). Compared with the control strain 49-92S, the BldD mutant (Mech04 strain) and the msmX mutant (Mech06 strain) reverse-engineered strains increased gentamicin production by 29.3% and 16.7%, respectively. Figure 3 Part B). In particular, the Mech04 strain carrying the global regulatory factor BldD mutant produced the highest gentamicin yield, reaching 664.8 mg / L. Furthermore, the BldD mutant did not alter the cell morphology and prevent spore production as it does in *Streptomyces roseosus*. The Mech04 strain still exhibited clumping during fermentation and had relatively well-developed hyphae, while the parental strain was more dispersed, showing thin and short hyphae (…). Figure 6 However, strain Mech06 exhibited premature cell autolysis and degradation during the later stages of fermentation. Compared to the starting strain, the final wet weight of strain Mech06 was reduced by 7.6% ( Figure 3 (Part C). Furthermore, reverse engineering of the rhaB mutant (Mech05 strain) and the entF mutant (Mech08 strain) showed that the gentamicin potency was similar to or slightly higher than the control 49-92S strain. However, the gentamicin potency of the Mech07 strain carrying the serA mutant decreased by 6.5% (from 514.2 mg / L to 480.9 mg / L). These results indicate that multiple mutants obtained from GEM models and strain mutagenesis reverse engineering are beneficial for gentamicin production, providing new and valuable targets for further improving cell production potential. Combined expression of identified dominant genes (genC, metK, and BldD, respectively) in the 49-92S strain was used to further increase gentamicin yield. Four engineered strains were designed and constructed using different target combinations. Figure 3(Part D). All engineered strains showed higher gentamicin yields than the original strains. The Mech09 strain, co-expressing genC and metK, achieved a titer of 696.5 mg / L, an increase of approximately 35.5% compared to the original strain. Figure 3 (Part E). Compared with the initial strain, PMV increased significantly by 63.0%, which may be related to the optimization of its growth conditions or metabolic pathways. Figure 3 (Part F). The Mech10 recombinant strain, co-expressing the metK and BldD genes, had a biomass similar to the control strain 49-92S. Compared to the starting strain, the Mech10 strain achieved a potency of 621.3 mg / L, an increase of approximately 20.8%. For the Mech11 strain, co-expressing the genC and BldD genes, its fermentation potency increased by approximately 24.7% compared to the initial strain 49-92S, reaching 641.1 mg / L. Figure 3 (Part E). The Mech12 strain, formed by co-expressing the three genes, showed the best gentamicin production titer at 782.8 mg / L, approximately 52.2% higher than 49-92S. Its growth was also significantly improved, increasing by 39.8% compared to the starting strain. Figure 3 (Part F). Furthermore, the productivity of the combined expressed metabolically engineered strains was significantly improved ( Figure 6 Among them, Mech12 had the highest productivity, reaching 6.5 mg / L / h, followed by Mech09 and Mech10. These findings highlight the efficacy of tailored gene modifications in enhancing gentamicin biosynthesis and underscore the different effects of various combination strategies.

[0029] Feed-batch fermentation of strain Mech12 with glucose as the primary carbon source was conducted to further investigate its gentamicin production performance in a 5L bioreactor. During the exponential growth phase, the metabolic parameters of both strains showed a linear correlation with biomass accumulation. As carbon and nitrogen sources decreased to limiting levels, growth tended to plateau or decline, consistent with the transition from primary to secondary metabolism. Supplementation with a carbon source could temporarily increase OUR and CER, but at this point, fermentation entered a slow growth phase primarily focused on cell maintenance, a potentially stringent response of empty tRNA on ribosomes. Figure 3 (Part G). Furthermore, the total sugar content in the Mech12 strain culture remained low throughout the fermentation process, reflecting its high metabolic efficiency. Figure 3(H section). Compared to the parental strain, the lag phase of strain Mech12 was significantly shorter, beginning to consume substrate and accumulate product after 20 h, while the parental strain did not begin until 60 h. At the end of fermentation, the gentamicin titer of strain Mech12 reached 956.3 mg / L, an increase of 47.1% compared to the 650.0 mg / L of the parental strain. Figure 3 (Part I). These results all indicate that the recombinant strain after combined expression has stronger metabolic capacity and product levels. Furthermore, the Mech12 strain also exhibited excellent growth performance, with a maximum biomass concentration of 39.5%, which is 30.8% higher than the parent strain (30.2%). This growth advantage is consistent with stronger metabolic activity, allowing for more efficient utilization of substrates in the synthesis of biomass and products. Compared with the 49-92S strain, the DO change in the later stages of fermentation of the Mech12 strain showed a gradual decreasing trend, which is due to the higher viscosity and limited oxygen supply in the later stages of fermentation. Figure 3 (Part J in the original text). Therefore, further improvements in gentamicin production could potentially be achieved through fed-batch processing and semi-continuous fermentation. These findings highlight the enhanced metabolic capacity and productivity of Mech12, providing insights into its remarkable potential for gentamicin biosynthesis.

[0030] S3: Recombinant engineered strains were constructed using combinatorial genetic engineering. The starting strain was *M. echinospora* KL01, an engineered strain producing gentamicin C1a, obtained by knocking out the genK and genL genes from strain 49-92S, as shown in Table 1. Expression cassettes containing the genC, metK, and BldD genes were constructed using the *Streptomyces*-*Escherichia coli* shuttle integration vector pIB139. The target gene fragments were amplified by PCR and ligated into the pIB139 vector, which had been double-digested with NdeI and XbaI, to construct recombinant plasmids. Through conjugation transfer, using *E. coli* ET12567 (pUZ8002) as the donor, the expression cassettes containing the genC, metK, and BldD genes were integrated into the ΦC31 attB site on the chromosome of strain KL01. After antibiotic selection and PCR verification, the recombinant engineered strain was obtained and named *M. echinospora* KL02 (see Table 1). To further analyze the differences in intracellular metabolism caused by combined overexpression targets, the intracellular metabolite profiles of strains KL01 and KL02 at different time points during fermentation were examined. Figure 4 (Part C). In PCA analysis, spots in the same group of samples have the same color, and the tightness of the clustering of spots in the same group reflects the parallelism between samples and the reliability of the data. Figure 6Furthermore, correlation heatmap analysis revealed that the correlation coefficients between samples within a group were all above 0.95, while the correlation coefficients between samples between groups ranged from 0.5 to 0.8. Figure 6 These data demonstrate that the samples used in the experiment exhibit a high degree of repeatability and consistency, providing a reliable basis for subsequent analysis.

[0031] For the EMP pathway, when the strain is modified, the carbon flux rate changes accordingly, and the EMP pathway responds rapidly to stress, resulting in significant differences in the concentration of metabolites along this pathway. The results showed that, compared to the control group, the concentrations of upstream EMP metabolites G6P and F6P in the KL02 strain increased from 24 to 72 h, then rapidly decreased in the later stages, while the mid-to-downstream metabolite 3PG accumulated after 72 h. This trend is consistent with the phenomenon that the KL02 strain exhibits strong glucose metabolism in the early stages of fermentation, followed by a slower consumption rate in the later stages. Furthermore, the concentrations of metabolites S7P and R5P in the PPP pathway of the KL02 strain increased significantly from 24 to 72 h, indicating that glucose metabolism at this stage shifts to the pentose phosphate pathway to provide precursors for cell growth. The gradual decrease in intracellular metabolite concentrations in the later stages of fermentation suggests that the intracellular metabolic pathway is gradually migrating to the gentamicin synthesis pathway. Compared with the control strain, the concentrations of succinyl-CoA and acetyl-CoA metabolites in the TCA cycle of strain KL02 increased to varying degrees from 24 to 96 h of fermentation, which is beneficial to the accumulation of precursor substances in gentamicin synthesis. Metabolic flux analysis was performed to compare the rapid gentamicin C1a synthesis stages of strains KL01 and KL02 (Table 2). The results showed that simultaneous overexpression of genC, metK, and BldD genes in strain KL01 significantly increased the flux of the gentamicin C1a biosynthetic pathway, which is consistent with the goals of metabolic engineering. In addition to affecting secondary metabolic pathways, overexpression of the three gene loci also caused other changes in intracellular metabolism in strain KL02 (…). Figure 4 Part D of the middle section).

[0032] Table 2. Specific rates and carbon recovery of Micromonospora echinococcosis 49-92S-KL01 and 49-92S-KL02 during fermentation 96–120 h.

[0033] Although the rate of conversion from G6P to F6P increased from 0.93 mmol / gDCW / h to 1.16 mmol / gDCW / h, the relative carbon flux of the EMP pathway decreased. Therefore, strain KL02 significantly improved substrate utilization. For the TCA cycle, strain KL02 also showed increased metabolic flux, consistent with increased levels of intracellular metabolites in later stages. The TCA cycle primarily accumulates reducing coenzymes such as NADH, which can be further converted into energy sources like ATP through oxidative phosphorylation to maintain cell growth and metabolism. Furthermore, ATP is required for gentamicin C1a synthesis; therefore, the increased TCA cycle may contribute to providing sufficient energy for gentamicin biosynthesis. Notably, the metabolic flux of the anastomosis pathway decreased significantly. Since this pathway consumes one ATP molecule, the reduced flux helps conserve ATP. In addition, we analyzed the intracellular reducing power of strains KL01 and KL02. The results suggest that greater gentamicin C1a production may, to some extent, be accompanied by higher NADH / NAD+ and ATP / ADP ratios. The ATP / ADP ratio of strain KL02 was significantly higher than that of strain KL01. Figure 7 This result indicates that the availability of reducing cofactors is a key variable in enhancing gentamicin C1a production. Therefore, by combining overexpression of the genC, metK, and BldD genes, the KL02 strain can effectively improve substrate redistribution and energy supply during product synthesis. S4: Optimize fermentation process and in-situ product removal. KL02 strain was fed-batch fermented in a 5L fermenter. The basic fermentation medium composition (g / L) was: soluble starch 35, feather peptone 13, corn flour 25, soybean meal 31, etc. Feeding strategy optimization: During fermentation, carbon and nitrogen sources were added according to substrate consumption. Through experimental screening, such as... Figure 5 As shown, the optimal feeding scheme was determined to be: adding sucrose as a carbon source and adding corn steep liquor as a nitrogen source. This combination effectively promoted gentamicin C1a synthesis, resulting in a significant increase in yield. In-situ product inhibition was relieved: when fermentation proceeded to approximately 60-72 hours, the concentration of gentamicin C1a in the fermentation broth accumulated to approximately 150 mg / L. This concentration was confirmed to begin significantly inhibiting yield, as shown in the figure. Figure 5 As shown in section D, microporous adsorption resin 001×8 is aseptically added to the fermenter. The addition of the resin can adsorb gentamicin C1a in situ in the fermentation broth, reduce product feedback inhibition, and maintain the metabolic activity of the cells.

[0034] To further increase the yield of gentamicin C1a, the effects of using different carbon and nitrogen sources for feeding were first investigated to obtain the optimal gentamicin yield. Figure 5Regarding carbon sources, several commonly used carbon sources, including glucose, sucrose, and maltose, were tested. The results showed that when glucose was used as a supplemental carbon source, the recombinant strain KL02 did not exhibit a significant potency increase compared to the control group in the later stages of fermentation. Figure 5 (Part A). When starch and sucrose were used as carbon sources, the gentamicin C1a yield of the recombinant strain was further increased. Specifically, the final titer obtained in the batch using sucrose was 332.2 mg / L, an increase of 48.8% compared to the control group. Figure 5 (Part A). This indicates that sucrose may be a more suitable carbon source for recombinant strains, helping them maintain a stable metabolic state during fermentation, thereby promoting the synthesis of gentamicin C1a. Furthermore, the addition of sodium citrate also improved the potency of gentamicin C1a. Regarding nitrogen sources, the effects of different nitrogen sources, such as ammonium salts, soybean meal, and yeast extract, on the yield of gentamicin C1a were investigated (…). Figure 5 (Part B). While ammonium salts, when used as a nitrogen source, can be rapidly absorbed and utilized by the strain, they easily lead to a rapid decrease in the pH of the fermentation broth, which is detrimental to the stable accumulation of gentamicin C1a. In contrast, when peptone is used as a nitrogen source, the pH change in the fermentation broth is more moderate, and the yield of gentamicin C1a is 289.8 mg / L, an increase of 29.8% compared to the control group. When corn steep liquor is selected as the supplemental culture medium, the gentamicin C1a titer reaches its highest level of 324.2 mg / L, an increase of 45.3% compared to the control group. Amino acids and other organic substances in corn steep liquor can serve as precursors for gentamicin biosynthesis, directly participating in the synthesis of secondary metabolites. This direct supplementation of substances can reduce the competitive utilization of carbon and nitrogen sources by the bacteria, allowing them to focus on the generation of the target product. Furthermore, different optimal combinations of carbon and nitrogen sources have a significant impact on the yield of gentamicin C1a. Among them, the combination of peptone and corn steep liquor can increase the yield from 220.1 mg / L in the control group to 283.3 mg / L, showing its effective promoting effect. In the selection of carbon sources, both starch and sucrose showed a synergistic effect when combined with corn steep liquor, further increasing yield. In particular, the combination of sucrose and corn steep liquor achieved the highest value, reaching 369.9 mg / L. Figure 5 (Part C). This indicates that the rich nutrients in corn steep liquor, when matched with a carbon source, can significantly promote the accumulation of the target product. In conclusion, combining corn steep liquor with a suitable carbon source configuration is one of the key strategies for increasing gentamicin C1a yield.

[0035] Table 1 Summary of strains and plasmids used in this invention

[0036] Table 1 lists the bacterial strains used and designed in this study, along with their culture methods. *Escherichia coli* DH5α (containing apramycin resistance) was used as the host for plasmid assembly, replication, and preservation. *Escherichia coli* ET12567 (pUZ8002) was used for inoculation transfer. All *E. coli* strains were cultured in LB medium (10 g tryptone, 10 g sodium chloride, and 5 g yeast extract per liter) at 37 °C. Appropriate antibiotics were added to the LB medium for plasmid maintenance and selection. Gentamicin-producing strains (*Micromonas echinococcosis* 49-92S) and gentamicin-producing C1a recombinant strains (*Micromonas echinococcosis* 49-92S-KL01) were used in this study. Bacterial suspensions were inoculated from glycerol tubes onto slant agar and cultured at 35.5 °C for 8–10 days. The slant culture medium (g / L) consisted of 10 g of soluble starch, 0.02 g of asparagine, 1 g of calcium carbonate, 0.5 g of magnesium sulfate heptahydrate, 0.3 g of dipotassium hydrogen phosphate trihydrate, 0.5 g of sodium chloride, 1 g of potassium nitrate, 15 g of agar powder, and 18 g of wheat bran. The slant was then transferred to a 500 mL shake flask containing 60 mL of fermentation medium and incubated at 220 rpm and 35.5 °C for 48 hours. The seed culture medium (g / L) consisted of 15 g of soluble starch, 1 g of glucose, 20 g of corn flour, 15 g of soybean meal, 3 g of feather peptone, 0.5 g of potassium nitrate, and 4 g of calcium carbonate. The seed culture was inoculated into a 5 L fermenter at a 12% inoculum. The fermentation medium (g / L) consisted of 35 g of soluble starch, 13 g of feather peptone, 25 g of corn flour, 31 g of soybean meal, 0.7 g of ammonium sulfate, 0.6 g of potassium nitrate, 7 g of calcium carbonate, 0.03 g of cobalt chloride, and 5 g of glucose. The stirring speed was automatically adjusted using the DO-stat strategy based on the incubation time (initial speed 150 rpm). Aeration was set to 1 vvm. The pressure was set to 0.05 MPa, and the dissolved oxygen concentration was maintained above 40%. 5M NaOH was automatically added via a PID-controlled peristaltic pump to maintain the pH above 7.2.

[0037] Using the complete method described above, the recombinant engineered strain KL02, under the optimized fermentation process, achieved a final gentamicin C1a titer of 894.1 mg / L, which was 4.5 times higher than that of the original strain KL01.

[0038] Example 2: A specific recombinant engineered strain product obtained by a method for manufacturing high-yield gentamicin C1a based on metabolic network modeling and reverse metabolic engineering.

[0039] Strain name: Micromonospora echinospora KL02.

[0040] Parental background: This strain was modified from Micromonospora echinospora KL01. The KL01 strain is a derivative strain of industrial strain 49-92S with the genK and genL genes knocked out through genetic engineering, and is used to produce gentamicin C1a (as shown in Table 1).

[0041] Genotypic characteristics: A foreign expression cassette containing the genC, metK, and BldD genes was integrated into the genome of strain KL01 through genetic engineering. These genes are co-expressed and driven by strong constitutive promoters (such as PermE). The integration site is the attB site of Streptomyces phage ΦC31.

[0042] Product Forms and Preservation: This strain can be prepared into glycerol cryovials (-80°C) or vacuum freeze-dried powder for long-term preservation and as a starting seed for the production of gentamicin C1a.

[0043] Product performance: The KL02 strain can stably produce gentamicin C1a in a 5L fermenter using an optimized fed-batch fermentation process (sucrose and corn steep liquor added, and in-situ adsorption using resin 001×8), with a final potency of 894.1 mg / L.

[0044] The combined results of metabolomics and metabolic flux analysis indicate that significant changes in key metabolic pathways in strain KL02 laid the foundation for the efficient synthesis of gentamicin C1a. However, the dynamic performance of different metabolic pathways also revealed potential bottlenecks in the efficiency of carbon and nitrogen source utilization during production. First, metabolomics data showed that strain KL02 exhibited increased concentrations of upstream metabolites (such as G6P and F6P) in the EMP pathway during the early stages of fermentation, while downstream metabolites (such as 3PG) accumulated in the later stages. This suggests that carbon flow exhibits a significant time dependence at different stages and may limit the efficient utilization of carbon sources. Second, the changing trends in metabolite concentrations in the PP pathway indicate that this pathway plays an important role in the regulation of precursor synthesis and cell growth. However, the decrease in these metabolites in the later stages of fermentation may lead to insufficient precursor supply, thereby affecting further synthesis of gentamicin. Furthermore, the increase in TCA cycle metabolites (such as succinyl-CoA and acetyl-CoA) and the improvement in metabolic flux suggest that this cycle makes a significant contribution to the provision of reducing power (NADH) and energy (ATP). However, the significant decrease in metabolic flux in the replenishment pathway and the reduction in ATP consumption suggest that optimizing carbon source supply to maintain TCA cycle activity and further enhance ATP production may be a key strategy for enhancing gentamicin synthesis. Analysis of reducing power and energy status (NADH / NAD+ and ATP / ADP ratios) showed that strain KL02 exhibited stronger energy supply capacity and higher availability of reducing cofactors. These characteristics are consistent with the metabolic properties of other reported high-producing antibiotic strains. Furthermore, previous studies have shown that the addition of sodium citrate significantly downregulates the levels of key enzymes in glycolysis and the TCA cycle, including a reduction in phosphofructokinase and pyruvate kinase, leading to a redistribution of glucose metabolic flux to gentamicin secondary metabolism. This invention observed similar phenomena; the dynamic changes in metabolite concentrations in the EMP pathway of strain KL02 (such as a significant decrease in G6P and F6P) and the increase in TCA cycle metabolic flux further indicate that these metabolic pathways play an important role in precursor supply and energy metabolism regulation. In summary, the results indicate that the high-yielding strain achieved higher reducing power (NADH / NAD+) and energy levels (ATP / ADP) by optimizing carbon flow and increasing flux in key pathways, providing a crucial driving force for the efficient synthesis of gentamicin. This observation also corroborates the central role of energy metabolism regulation in optimizing secondary metabolite production.

[0045] Example 3: Based on Example 1, the specific application method of recombinant engineered strain M. echinospora KL02 in the industrial production of gentamicin C1a includes the following steps: 1. Seed Culture: KL02 strain was retrieved from a glycerol storage tube and streaked onto an agar slant containing apramycin (25 μg / mL) and nalidixic acid (25 μg / mL). The culture was incubated at 35.5°C for 8-10 days for activation. Spores or mycelia were then picked and inoculated into seed culture medium, and cultured with shaking at 35.5°C and 220 rpm for 48 hours to obtain the seed culture.

[0046] 2. Fermentation Production: Transfer the seed culture at an inoculum rate of 10-12% to a bioreactor with a capacity of 5L or more containing fermentation medium. Control the fermentation conditions as follows: temperature 35.5°C, aeration rate 1 vvm, pH ≥ 7.2 maintained by automatic addition of 5M NaOH, and dissolved oxygen (DO) concentration maintained above 40%.

[0047] 3. Process Control and Optimization: Feeding: In the mid-to-late stages of fermentation, a feed solution is started. The feed solution consists of concentrated sucrose solution and corn steep liquor, and the flow rate is controlled based on the residual sugar and ammonium nitrogen concentrations. In-situ Adsorption: When online monitoring or offline detection shows that the gentamicin C1a concentration in the fermentation broth reaches 100-150 mg / L, microporous adsorption resin 001×8 is aseptically added to the reactor (the amount added is approximately 2-5% of the fermentation broth volume) to continuously remove the product.

[0048] Product Harvesting: After fermentation (approximately 120-144 hours), the bacterial cells and resin are separated by filtration or centrifugation. High-purity gentamicin C1a can be recovered from the resin through a desorption step. The fermentation supernatant can also be further purified through ion exchange, chromatography, and other steps.

[0049] Analytical methods: Total sugar and reducing sugar were determined using the DNS method. Biomass was determined by the centrifugation volumetric method. Ammonium nitrogen was determined by spectrophotometry. The concentration of gentamicin C1a was analyzed by high-performance liquid chromatography (HPLC) using a Waters Luna® C18 column. The mobile phase was 5.0 g / L sodium heptanesulfonate solution, with formic acid and methanol accounting for 5% and 70%, respectively. Isocratic elution was performed at a flow rate of 1.0 mL / min, and the column temperature was 30 °C. The UV detector wavelength was 330 nm, and the injection volume was 20 mL. In summary, the fermentation broth was acidified to 1.8–2.0 and stirred with a magnetic stirrer for 30 min at room temperature. Then, it was centrifuged at 4000 rpm for 20 min at room temperature, and the supernatant was derivatized with OPA reagent and filtered through a 0.22 μm filter for subsequent measurements. Intracellular ATP, NADH, NADH / NAD+, and ATP / ADP concentrations were analyzed using the kit (BioVision) according to its instructions.

[0050] Application results: By using the KL02 strain and the above process, efficient and stable production of gentamicin C1a can be achieved. The final fermentation titer is significantly higher than that of traditional production strains. For example, the titer can reach 894.1 mg / L in fed-batch fermentation, providing an efficient cell factory and process solution for large-scale industrial production. To further evaluate the potential production performance of the optimized process, fed-batch fermentation of strain KL02 was performed in a 5 L bioreactor. As a control, the yields of strain KL02 were 226.4 mg / L and 1.6 mg / L / h, respectively. Figure 4 Part B). The optimized process yielded a gentamicin C1a titer of 417.4 mg / L and a production rate of 2.9 g / L / h. Figure 5 (Part E). Compared with the control group, the gentamicin C1a titer in the optimized group increased by 84.4%, indicating that rational metabolic network reprogramming provides a powerful driving force for tapping the cellular potential of gentamicin biosynthesis. As fermentation progresses, a certain level of gentamicin accumulation is thought to inhibit the growth of *Micromonas echinococcosis* strains. To investigate the effect of extracellular gentamicin C1a levels on cell fermentation, a gentamicin C1a addition experiment was subsequently conducted. The results showed that in the designed six concentration gradients of 50 mg / L, 100 mg / L, 150 mg / L, 200 mg / L, 250 mg / L, and 300 mg / L, when the gentamicin C1a concentration was above 150 mg / L, the yield of gentamicin C1a in the shake flask began to decrease significantly by 63.4% (…). Figure 5 (Part D). Therefore, high concentrations of gentamicin C1a inhibit the synthetic ability of the strain, and the inhibitory effect increases with increasing gentamicin C1a concentration. Previous studies have investigated strategies for in-situ product removal using various adsorption resins to improve fermentation product yield. For example, in-situ product removal based on D152 resin was successfully used to increase the ε-poly-L-lysine yield of Streptomyces GIM8. In-situ adsorption using Amberlite XAD16 resin alleviated the inhibitory effect of high concentrations of (R)-(-)-mellein formation on cell growth. Here, in-situ adsorption using microporous resin was used to alleviate the inhibition of KL02 by gentamicin C1a. Adsorption resin 001x8 was added to the fermentation medium, and the results showed that in the later stages of fermentation, the addition of microporous resin significantly increased the rate of glucose consumption by KL02, and by the end of fermentation, the glucose in the medium was almost depleted. Figure 5(See section E in Figure 5). Furthermore, the biomass of strain KL02 significantly increased after the addition of adsorption resin 001x8. The optimal batch yield of gentamicin C1a reached 894.1 mg / L, a 2.9-fold increase compared to the control group (226.4 mg / L) and a 1.1-fold increase compared to the fed-batch optimization group (417.4 mg / L) (section F in Figure 5). These results indicate that the significant changes in key metabolic pathways in strain KL02 laid the foundation for the efficient synthesis of gentamicin C1a.

[0051] Example 4: Based on Example 1, using Micromonospora echinococcosis 49-92S as the starting strain, the following recombinant strains were constructed using the same genetic engineering method as in Example 1 (integration expression based on the pIB139 vector): Mech09 strain: co-expressing genC and metK genes; Mech10 strain: co-expressing metK and BldD genes; Mech11 strain: co-expressing genC and BldD genes.

[0052] The engineered strain described above and the empty vector control strain (CK-) were cultured under the same shake-flask fermentation conditions (culture medium and conditions as in Example 1). Gentamicin titer and cell volume (PMV) were determined after 120 hours of fermentation (see [link to example 1]). Figure 3 Parts E and F).

[0053] Mech09 strain (genC+metK): Gentamicin titer reached 696.5 mg / L, which is about 35.5% higher than the original strain (514.2 mg / L).

[0054] Mech10 strain (metK+BldD): Gentamicin titer was 621.3 mg / L, an increase of approximately 20.8%.

[0055] Mech11 strain (genC+BldD): Gentamicin titer was 641.1 mg / L, an increase of approximately 24.7%.

[0056] Conclusion: Overexpression of any two of the genC, metK, and BldD genes significantly increased gentamicin yield. This demonstrates the flexibility and scalability of the target gene combinations defined in the claims. Overexpression of genC and metK, as the first target genes (whether alone or in combination with BldD), has a clear and positive technical effect on yield improvement, providing multiple feasible solutions for constructing engineered strains with different needs.

[0057] Example 5: Based on Example 1, the specific construction method, quality assessment, and use as a standalone tool of the genome-scale metabolic model iFX1172.

[0058] The genome annotation file of *Micromonospora echinococcosis* ATCC15837 (GenBank: GCA_002266845.1) and the protein FASTA sequence were used as inputs. The high-quality consensus metabolic model *Sco-GEM* of *Streptomyces cerevisiae* was used as a template. The *getModelFromHomology* function in the RAVEN toolbox was used for a bidirectional protein homology search via BLASTp, with parameters set as follows: maximum E-value 10^-50, minimum alignment length 90 residues, and minimum identity 40%. An initial draft model was generated, containing 1290 reactions, 1370 metabolites, and 1377 genes. Reactions were added from the template using the *fillGaps* function to ensure the synthesis of all biomass precursors. The gentamicin biosynthetic pathway, involving 10 genes and 13 associated enzymatic reactions, was manually added. Gibbs free energy (threshold -30 kJ / mol) was calculated using eQuilibrator or referenced from the MetaCyc database to determine reaction reversibility and avoid invalid cycles. The elemental balance and stoichiometry of all reactions were checked and corrected. Following these steps, the final model iFX1172 was obtained, containing 1172 genes, 1641 metabolites, and 2022 metabolic reactions. The model is released in SBML L3V1 FBCv2 format. The development and management of iFX1172 are reproducibly tracked and can be freely obtained from https: / / github.com / FengxuSysbio / Mech-GEM. This model is versioned; the analysis in this invention uses version 1.0.1. This model is released in SBML L3V1 FBCv2 format.

[0059] Evaluation using the MEMOTE test suite showed that iFX1172 achieved an overall score of 71%, with 100% stoichiometry and 79% mass balance. The model accurately predicted the growth capacity of the strain on different carbon and nitrogen sources, and the predictions showed good agreement with literature and experimental data. This iFX1172 model can be used not only for target prediction but also independently for: Phenotypic simulation: Predicting the growth and metabolic capacity of M. echinospora under various nutritional conditions.

[0060] Essential gene analysis: Using single-gene knockout simulation, 194 essential genes are predicted to guide non-knockout regions in genetic engineering.

[0061] Metabolic flux analysis reveals key metabolic features in gentamicin synthesis, such as enhanced TCA cycle, improved ATP supply, and redox balance.

[0062] The specific embodiments described herein are merely illustrative of the spirit of the invention. Those skilled in the art to which this invention pertains may make various modifications or additions to the described specific embodiments or use similar methods to substitute them, without departing from the spirit of the invention or exceeding the scope defined by the appended claims.

Claims

1. A method for manufacturing high-yield gentamicin C1a biopharmaceuticals based on metabolic network modeling and reverse metabolic engineering, characterized in that, Includes the following steps: S1: Construct a genome-scale metabolic model of the target production strain and use the model to predict and screen the first target genes positively correlated with gentamicin biosynthesis; S2: Whole-genome sequencing was performed on the high-yield gentamicin mutant strain, and comparative genomics analysis was used to identify the second target gene associated with the high-yield trait. S3: Combine the first target gene predicted in step S1 and the second target gene identified in step S2, and co-express them in the target production strain to construct a recombinant engineered strain. S4: The recombinant engineered strain is fermented and cultured, and feed is added during the fermentation process, and adsorption resin is added to remove the product in the fermentation broth in situ.

2. The method for manufacturing high-yield gentamicin C1a biopharmaceuticals based on metabolic network modeling and reverse metabolic engineering according to claim 1, characterized in that: The target production strain in step S1 is Micromonospora echinococcosis, and the genome-scale metabolic model is the iFX1172 model, which contains 2022 metabolic reactions, 1641 metabolites and 1172 genes.

3. The method for manufacturing high-yield gentamicin C1a biopharmaceuticals based on metabolic network modeling and reverse metabolic engineering according to claim 1 or 2, characterized in that: The first target gene in step S1 is at least one selected from the genC gene encoding 2-deoxy-acyl-inositose synthase and the metK gene encoding S-adenosylmethionine synthase.

4. The method for manufacturing high-yield gentamicin C1a biopharmaceuticals based on metabolic network modeling and reverse metabolic engineering according to claim 1, characterized in that: The second target gene in step S2 is the BldD gene, which encodes a global transcriptional regulatory factor.

5. The method for manufacturing high-yield gentamicin C1a biopharmaceuticals based on metabolic network modeling and reverse metabolic engineering according to claim 4, characterized in that: The combination in step S3 is the co-expression of the genC gene, the metK gene, and the BldD gene.

6. The method for manufacturing high-yield gentamicin C1a biopharmaceuticals based on metabolic network modeling and reverse metabolic engineering according to claim 1, characterized in that: In step S4, the feeding strategy includes adding a carbon source and a nitrogen source. The carbon source comprises sucrose, and the nitrogen source comprises corn steep liquor.

7. The method for manufacturing high-yield gentamicin C1a biopharmaceuticals based on metabolic network modeling and reverse metabolic engineering according to claim 6, characterized in that, In step S4, the adsorption resin is microporous resin 001×8, and the product is gentamicin C1a.

8. A recombinant engineered bacterial strain constructed by the method according to any one of claims 1-7, characterized in that, The strain is Micromonospora echinococcosis, and its genome integrates and co-expresses exogenous genC, metK, and BldD genes.

9. The recombinant engineered strain according to claim 8, characterized in that, The strain is Micromonosporaechinospora KL02.

10. The use of the recombinant engineered strain according to claim 9 in the production of gentamicin C1a.

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