Recombinant Pseudomonas putida Dephospho-CoA kinase (coaE)
Description
Enzymatic Function and Role in CoA Biosynthesis
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GTP dependency: The Thermococcus kodakarensis DPCK (TK1697) preferentially uses GTP over ATP, with kinetic parameters for GTP and for dephospho-CoA .
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Structural divergence: Archaeal DPCKs (arCOG04076 family) lack homology to bacterial/eukaryotic DPCKs but share distant relations with thiamine pyrophosphokinases .
Key Kinetic Parameters
Comparative kinetics of DPCK homologs reveal species-specific adaptations:
| Organism | Substrate | |||
|---|---|---|---|---|
| T. kodakarensis (TK1697) | Dephospho-CoA | 0.14 ± 0.02 | 5.57 | 40.4 |
| GTP | 0.26 ± 0.06 | 6.68 | 25.7 | |
| E. histolytica | Dephospho-CoA | 0.11 | 1.48 | 13.5 |
| ATP | 0.020 | 1.41 | 70.5 |
Data sourced from kinetic assays comparing archaeal and eukaryotic DPCK activity .
Metabolic Engineering in P. putida
While CoaE is not explicitly studied in P. putida, the organism’s metabolic plasticity and recombinant capabilities are well-documented:
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Host versatility: P. putida is engineered for heterologous pathways (e.g., prodigiosin , rhamnolipids ) using tools like Tn5 transposons and SEVA vectors .
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Carbon flux optimization: Studies on xylose utilization highlight P. putida’s ability to rewire central metabolism via adaptive laboratory evolution .
Implications for CoA Pathway Engineering
CoA is critical for acyl-group transfer reactions, and its biosynthesis in P. putida could be enhanced via:
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Heterologous expression: Introducing GTP-dependent archaeal DPCKs (e.g., TK1697) to bypass ATP competition in CoA synthesis .
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Genomic integration: Leveraging rrn operons as high-expression sites for pathway genes .
Research Gaps and Future Directions
Product Specs
Target Background
Q&A
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What experimental designs are most effective for studying the enzymatic activity of Recombinant Pseudomonas putida Dephospho-CoA kinase (coaE)?
To investigate the enzymatic activity of Recombinant Pseudomonas putida Dephospho-CoA kinase, a well-structured experimental design should include:
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Control and Experimental Groups: Establish control groups with wild-type strains and experimental groups with recombinant strains expressing coaE. This allows for comparative analysis of enzymatic activity.
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Assay Conditions: Optimize assay conditions such as pH, temperature, and substrate concentrations to determine their effects on enzyme kinetics. Standardized conditions should be maintained across all experiments to ensure reproducibility.
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Kinetic Analysis: Employ Michaelis-Menten kinetics to assess enzyme activity, measuring reaction rates at varying substrate concentrations. Data should be analyzed using nonlinear regression to derive kinetic parameters such as and .
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Data Validation: Use multiple replicates and statistical analysis (e.g., ANOVA) to validate results and assess the significance of differences observed between recombinant and control strains .
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How can data contradictions in the characterization of coaE activity be analyzed?
Data contradictions in the characterization of Dephospho-CoA kinase activity can be addressed through:
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What are the implications of genetic modifications on the metabolic pathways in Recombinant Pseudomonas putida?
Genetic modifications in Recombinant Pseudomonas putida can significantly impact metabolic pathways by:
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What methodologies are employed for the heterologous expression of coaE in Pseudomonas putida?
Heterologous expression of coaE in Pseudomonas putida involves several methodologies:
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Vector Systems: Utilize plasmid vectors that contain strong promoters compatible with Pseudomonas putida's transcriptional machinery. The choice of vector can significantly influence expression levels.
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Transformation Techniques: Employ electroporation or heat shock methods for introducing plasmids into Pseudomonas putida cells. Optimizing conditions such as voltage and incubation times is critical for successful transformation.
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Screening for Expression: Use reporter genes (e.g., green fluorescent protein) alongside coaE to facilitate screening for successful transformants. This allows rapid identification of colonies expressing the gene of interest.
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Expression Optimization: Conduct experiments to optimize expression conditions, including induction timing, temperature, and media composition, which can enhance protein yield and functionality .
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How does the metabolic engineering of Pseudomonas putida facilitate biotechnological applications?
Metabolic engineering of Pseudomonas putida enhances its utility in biotechnology by:
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Substrate Flexibility: Engineering strains to utilize diverse substrates (e.g., lignocellulosic biomass) increases their applicability in bioprocesses aimed at sustainable production.
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Product Yield Improvement: Modifying metabolic pathways can lead to higher yields of desired products, such as biofuels or biochemicals, making processes more economically viable.
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Synthetic Biology Approaches: Implementing synthetic biology techniques allows for the design of novel biosynthetic pathways that can produce compounds not naturally synthesized by Pseudomonas putida.
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Adaptive Evolution Strategies: Utilizing adaptive laboratory evolution techniques enables the development of strains with improved performance under industrial conditions, further enhancing their biotechnological potential .
