Recombinant Vanderwaltozyma polyspora 3-ketoacyl-CoA reductase (Kpol_513p6) is a component of the microsomal membrane-bound fatty acid elongation system. It is involved in the production of 26-carbon very long-chain fatty acids (VLCFAs) from palmitate by catalyzing the reduction of the 3-ketoacyl-CoA intermediate in each elongation cycle. VLCFAs serve as precursors for ceramide and sphingolipids.
KEGG: vpo:Kpol_513p6
STRING: 436907.XP_001644348.1
Vanderwaltozyma polyspora 3-ketoacyl-CoA reductase (Kpol_513p6) is an enzyme involved in fatty acid elongation pathways. It catalyzes the second step in each cycle of fatty acid elongation, specifically the NADPH-dependent reduction of 3-ketoacyl-CoA to 3-hydroxyacyl-CoA. This enzyme is part of the very long chain fatty acid biosynthetic machinery and plays a crucial role in lipid metabolism. The enzyme belongs to the short-chain dehydrogenase/reductase (SDR) family and has the EC classification 1.1.1.-. It is also known by several synonyms including 3-ketoreductase, KAR, and microsomal beta-keto-reductase .
The full-length protein consists of 347 amino acids and contains conserved motifs typical of the SDR family. In the fatty acid elongation cycle, it works sequentially with three other enzymes: 3-ketoacyl-CoA synthase (KCS), 3-hydroxyacyl-CoA dehydratase (HCD), and enoyl-CoA reductase (ECR). Together, these enzymes extend fatty acid chains by two carbon atoms in each cycle .
Recombinant Kpol_513p6 can be successfully expressed in multiple heterologous systems. The most common expression host is Escherichia coli, which offers high yield and relatively straightforward purification procedures. The gene encoding Kpol_513p6 (residues 1-347) is typically cloned into an expression vector (such as pET-28b) that allows for the addition of an N-terminal histidine tag. Alternative expression systems include:
Yeast expression systems
Baculovirus-insect cell systems
Mammalian cell culture systems
Cell-free expression systems
Each system has its advantages and limitations depending on research requirements. E. coli systems are preferred for high yield and cost-effectiveness, while eukaryotic systems may provide better post-translational modifications. The choice of expression system should be based on the specific requirements of the research project, such as protein folding needs, post-translational modifications, and downstream applications .
To maintain optimal activity of recombinant Kpol_513p6, the following storage conditions are recommended:
| Storage Condition | Recommendation |
|---|---|
| Long-term storage | -20°C to -80°C |
| Working aliquots | 4°C for up to one week |
| Buffer composition | Tris/PBS-based buffer, pH 8.0, with 6% Trehalose |
| Alternative buffer | Tris-based buffer with 50% glycerol |
| Important precaution | Avoid repeated freeze-thaw cycles |
For reconstitution of lyophilized protein, it is recommended to briefly centrifuge the vial before opening and reconstitute in deionized sterile water to a concentration of 0.1-1.0 mg/mL. For long-term storage, addition of 5-50% glycerol (final concentration) is recommended before aliquoting. The standard recommended final concentration of glycerol is 50% .
Determining the optimal conditions for assaying Kpol_513p6 activity requires careful consideration of multiple parameters. Based on related 3-ketoacyl-CoA reductases, a systematic approach to enzyme characterization should include:
Substrate specificity testing: Using various chain-length 3-ketoacyl-CoA substrates (C4-C26) to determine chain length preference.
Temperature optimization: Testing activity range from 20-55°C, with expected optimal activity likely between 30-40°C for yeast-derived enzymes.
pH optimization: Testing buffers ranging from pH 6.0-9.0, with common buffers including:
MES buffer (pH 6.0-6.5)
Phosphate buffer (pH 6.5-7.5)
Tris-HCl buffer (pH 7.5-9.0)
Cofactor requirements: NADPH is the likely preferred cofactor, but NADH should also be tested at concentrations of 0.1-1.0 mM.
Reaction monitoring: Activity can be monitored by:
Spectrophotometric assay following NADPH oxidation at 340 nm
HPLC analysis of substrate consumption and product formation
LC-MS/MS for detailed product characterization
For kinetic measurements, both continuous and discontinuous assays can be employed. Continuous assays monitoring NADPH consumption at 340 nm provide real-time data but may be less sensitive for slow reactions. Discontinuous assays involving product extraction and analysis at defined time points can provide more comprehensive data on reaction products .
Determining kinetic parameters of recombinant Kpol_513p6 requires careful experimental design and data analysis. A comprehensive approach should include:
Substrate saturation curves: Set up reactions with varying concentrations of 3-ketoacyl-CoA substrate (typically 0.001-1.0 mM) while keeping enzyme concentration constant. Multiple chain-length substrates should be tested to determine substrate preference.
Initial velocity measurements: Measure reaction rates during the linear phase (typically first 10-20% of substrate conversion) to determine initial velocities (v₀) at each substrate concentration.
Michaelis-Menten analysis: Plot initial velocity versus substrate concentration and fit to the Michaelis-Menten equation:
v₀ = (Vₘₐₓ × [S]) / (Kₘ + [S])
Lineweaver-Burk transformation: For visual confirmation and alternative analysis, plot 1/v₀ versus 1/[S] to obtain a straight line with y-intercept = 1/Vₘₐₓ and slope = Kₘ/Vₘₐₓ.
Calculation of catalytic efficiency: Determine kcat (turnover number) by dividing Vₘₐₓ by enzyme concentration, then calculate catalytic efficiency as kcat/Kₘ.
The HT-MEK (High-Throughput Microfluidic Enzyme Kinetics) technique could be particularly valuable for comprehensive kinetic analysis of Kpol_513p6. This method enables thousands of enzyme experiments to be performed simultaneously, significantly accelerating the determination of kinetic parameters across multiple conditions and substrates .
Optimizing yield and purity of recombinant Kpol_513p6 requires attention to expression conditions and purification methods:
Expression optimization:
Test multiple E. coli strains (BL21(DE3), Rosetta, Arctic Express)
Optimize induction conditions:
IPTG concentration (0.1-1.0 mM)
Induction temperature (15-30°C)
Induction duration (4-24 hours)
Consider co-expression with chaperones if solubility is an issue
Cell lysis optimization:
Use a combination of enzymatic (lysozyme) and mechanical (sonication) methods
Include protease inhibitors to prevent degradation
Optimize buffer conditions (pH, salt concentration) to enhance protein stability
Advanced purification protocol:
Primary purification: Ni²⁺-NTA affinity chromatography
Use gradient elution with increasing imidazole (10-500 mM)
Collect fractions and analyze by SDS-PAGE
Secondary purification if needed:
Size exclusion chromatography
Ion exchange chromatography
Final polishing steps:
Dialysis against appropriate storage buffer
Concentration using centrifugal filters
Quality control by SDS-PAGE, enzyme activity, and mass spectrometry
A typical purification protocol based on successful approaches with similar enzymes involves loading the soluble portion of cell lysate onto a Ni²⁺-NTA affinity matrix, washing with equilibration buffer (typically 50 mM phosphate buffer, pH 7.5, containing 10 mM imidazole), and eluting the bound His-tagged protein with elution buffer (50 mM phosphate buffer, pH 7.5, containing 500 mM imidazole). Purified protein can then be dialyzed against an appropriate storage buffer .
Comparative analysis of Kpol_513p6 with homologous enzymes from other organisms provides insights into functional conservation and divergence:
| Parameter | Yeast KCRs | Plant KCRs | Bacterial Homologs |
|---|---|---|---|
| Kₘ (μM) | 10-100 | 5-50 | 20-200 |
| kcat (s⁻¹) | 5-50 | 10-100 | 1-20 |
| kcat/Kₘ (s⁻¹μM⁻¹) | 0.1-5 | 0.5-10 | 0.05-1 |
Functional complementation: Experiments in heterologous systems can reveal functional equivalence. For example, expression of Kpol_513p6 in E. coli or other systems lacking endogenous KCR activity can demonstrate whether it can functionally replace the native enzyme. Similar complementation experiments with the E. coli fabG gene (encoding 3-ketoacyl-ACP reductase) have demonstrated functional connections between fatty acid metabolism enzymes from different organisms .
Investigating the effects of metal ions and potential inhibitors on Kpol_513p6 activity presents several methodological challenges that require careful experimental design:
Metal ion effects assessment:
Systematic testing of divalent cations (Mg²⁺, Ca²⁺, Zn²⁺, Cu²⁺, Mn²⁺, Fe²⁺) at concentrations ranging from 0.1-10 mM
Control for background reactions (some metals can promote non-enzymatic reactions)
Consider chelation effects in buffers (EDTA, EGTA can sequester metals)
Potential for enhancement effects (some 3-ketoreductases show enhanced activity with specific ions, such as the 391% enhancement observed with Cu²⁺ for EstRag)
Inhibitor screening methodologies:
Test known inhibitors of related enzymes (SDR family inhibitors)
Determine IC₅₀ values through dose-response curves
Distinguish between competitive, non-competitive, and uncompetitive inhibition through Lineweaver-Burk analysis
Account for potential solubility issues with hydrophobic inhibitors
Detergent sensitivity analysis:
Test common detergents (SDS, Triton X-100, Tween-80) at 0.01-0.1% concentrations
Assess both immediate effects and stability after pre-incubation
Consider micelle formation and potential substrate sequestration
Data interpretation challenges:
Differentiating direct enzyme inhibition from interference with assay systems
Accounting for synergistic or antagonistic effects between metals and inhibitors
Correlating in vitro inhibition with potential physiological relevance
Methodologically, it is advisable to use multiple assay approaches to confirm inhibition results and to include appropriate controls for non-enzymatic reactions and assay interference. Additionally, thermal shift assays can provide complementary data on how metal ions or inhibitors affect protein stability, potentially offering insights into their mechanism of action .
Kpol_513p6 offers significant potential for metabolic engineering applications focused on modifying fatty acid synthesis pathways:
Co-expression strategies:
Pairing Kpol_513p6 with other enzymes from the fatty acid elongation pathway can redirect carbon flux
Co-expression with 3-ketoacyl-CoA synthases (KCS) with different chain-length specificities can produce targeted fatty acid profiles
Based on successful approaches with related enzymes, co-expression of Kpol_513p6 with polyhydroxyalkanoate (PHA) synthase genes could enable production of novel biopolymers
Pathway optimization considerations:
Balance expression levels of pathway enzymes to avoid metabolic bottlenecks
Consider cofactor availability (NADPH) and regeneration systems
Optimize cultivation conditions (temperature, carbon source, aeration)
Host strain selection factors:
E. coli strains with deletions in competing pathways (ΔfadE, ΔfadD)
Yeast systems with enhanced precursor supply
Systems with increased NADPH availability
Experimental design for pathway analysis:
Two-stage cultivation strategies (growth phase followed by production phase)
Testing of various carbon sources (glucose, fatty acids, acetate)
Analytical methods for product characterization (GC-MS, LC-MS)
As demonstrated with related enzymes such as the E. coli 3-ketoacyl-ACP reductase (fabG), co-expression of reductases with synthase genes can lead to the production of novel compounds. For example, co-expression of fabG with PHA synthase genes in E. coli HB101 resulted in accumulation of PHA copolymers (approximately 8% of dry cell weight) consisting of various 3-hydroxyalkanoate units when using dodecanoate as carbon source. Similar strategies could be employed with Kpol_513p6 to produce specialized fatty acid derivatives or biopolymers .
Enzymatic assays for 3-ketoacyl-CoA reductases like Kpol_513p6 present several potential pitfalls that can impact results reliability:
Substrate stability issues:
3-ketoacyl-CoA substrates are prone to hydrolysis in aqueous solutions
Mitigation: Prepare fresh substrate solutions, consider including stabilizing agents, and monitor substrate integrity by HPLC
Time-course experiments should include substrate-only controls to account for non-enzymatic degradation
Cofactor-related challenges:
NADPH oxidation can occur non-enzymatically, especially in the presence of metal ions
Degradation of NADPH during storage can lead to inconsistent results
Solution: Include no-enzyme controls, prepare fresh NADPH solutions, and protect from light
Assay interference factors:
Buffer components may affect enzyme activity
Imidazole from purification can inhibit enzyme activity if not completely removed
Approach: Test multiple buffer systems and thoroughly dialyze protein preparations
Enzyme stability considerations:
Activity loss during storage or assay conditions
Protein aggregation affecting apparent activity
Recommendations: Monitor protein stability by dynamic light scattering, include thermal shift assays, and optimize buffer conditions
Data analysis complications:
Non-linear reaction kinetics due to substrate or product inhibition
Lag phases in enzyme activity due to conformational changes
Strategy: Limit analysis to initial velocity regions, employ appropriate non-linear regression models, and consider enzyme activation phenomena
To address these challenges, it is advisable to employ multiple complementary assay methods. For instance, coupling spectrophotometric NADPH consumption measurements with product formation analysis by chromatographic methods provides more robust data. Additionally, including appropriate controls and carefully optimizing assay conditions for each specific batch of enzyme can significantly improve reproducibility .
Designing experiments to elucidate the physiological role of Kpol_513p6 in its native organism requires a multifaceted approach:
Gene deletion/silencing strategies:
CRISPR-Cas9 mediated gene knockout if transformation protocols exist for V. polyspora
RNA interference approaches if complete knockout is lethal
Conditional expression systems (tetracycline-regulated or similar)
Experimental readouts: Growth phenotypes, fatty acid profile alterations, membrane composition changes
Complementation experiments:
Reintroduction of wild-type Kpol_513p6 in knockout strains
Expression of site-directed mutants to identify critical residues
Heterologous complementation with KCR genes from other organisms
Analysis: Restoration of wild-type phenotypes, partial complementation effects
Metabolomic profiling approaches:
Comparative lipidomics between wild-type and mutant strains
Targeted analysis of very long-chain fatty acids and derivatives
Stable isotope labeling experiments to track metabolic flux
Techniques: GC-MS, LC-MS/MS, NMR for comprehensive metabolite identification
Subcellular localization studies:
Fluorescent protein tagging (ensuring tags don't disrupt function)
Immunolocalization with specific antibodies
Subcellular fractionation followed by activity assays or western blotting
Expected localization: Endoplasmic reticulum membrane, based on function in fatty acid elongation
Stress response characterization:
Response to temperature shifts, membrane stressors, osmotic challenges
Analysis of gene expression under various growth conditions
Correlation with changes in membrane lipid composition
Methods: qRT-PCR, RNA-seq, proteomics
These approaches should be integrated with in vitro biochemical characterization to establish clear connections between the enzyme's catalytic properties and its physiological function. The experimental design should also account for potential redundancy in 3-ketoacyl-CoA reductase activity, as many organisms possess multiple enzymes with overlapping functions .
High-throughput methods offer powerful approaches to characterize multiple Kpol_513p6 variants simultaneously, enabling more comprehensive structure-function analyses:
High-Throughput Microfluidic Enzyme Kinetics (HT-MEK):
This technique enables thousands of enzyme experiments to be performed simultaneously
Microfluidic chips allow for precise control of reaction conditions
Automated analysis of reaction progress through integrated detection systems
Applications: Rapid screening of substrate specificity, inhibitor effects, and reaction conditions
Implementation requires specialized equipment but dramatically accelerates data collection
Deep mutational scanning approaches:
Creation of comprehensive mutant libraries covering single or multiple positions
Coupling of enzymatic activity to a selectable or screenable phenotype
Next-generation sequencing to quantify enrichment/depletion of variants
Analysis: Sequence-function relationships, identification of critical residues
Advantages: Thousands to millions of variants can be assessed simultaneously
Automated protein purification and characterization platforms:
Parallel expression and purification of dozens to hundreds of variants
Integration with robotic liquid handling for automated assay setup
Standardized analytical methods for consistent comparisons
Data management systems for tracking large datasets
Benefits: Reduced variability between experimental batches, improved reproducibility
Computational prediction integrated with experimental validation:
In silico modeling of mutations and their effects on structure and function
Molecular dynamics simulations to predict conformational changes
Machine learning approaches to prioritize variants for experimental testing
Iterative design-build-test cycles to refine understanding
Microscale thermophoresis and thermal shift assays:
Rapid assessment of protein stability and ligand binding
Miniaturized reaction formats requiring minimal protein amounts
Parallel analysis of multiple conditions in 96 or 384-well formats
Applications: Screening stability conditions, cofactor preferences, substrate binding
Implementing these high-throughput approaches requires careful experimental design and appropriate controls but can dramatically accelerate the characterization process and provide more comprehensive datasets than traditional methods .
Structural biology approaches offer powerful insights into Kpol_513p6 function by revealing atomic-level details of enzyme-substrate interactions and catalytic mechanisms:
X-ray crystallography strategies:
Crystallization trials with various constructs (full-length, truncated, fusion proteins)
Co-crystallization with substrates, products, or inhibitors
Analysis of conformational changes upon ligand binding
Resolution goals: 1.5-2.5 Å for detailed catalytic site visualization
Challenges: Obtaining diffraction-quality crystals, capturing catalytically relevant states
Cryo-electron microscopy applications:
Single-particle analysis for structural determination
Visualization of conformational ensembles
Potential for studying membrane-associated states
Advantages: No crystallization required, observation of multiple conformational states
Limitations: Size constraints may necessitate complex formation or antibody labeling
NMR spectroscopy approaches:
Solution structure determination
Dynamics studies to identify flexible regions
Ligand binding experiments using chemical shift perturbation
Isotope labeling strategies (¹⁵N, ¹³C, ²H) for optimal signal quality
Applications: Characterizing protein-ligand interactions in solution, conformational changes
Integrative structural biology:
Combining multiple techniques (crystallography, cryo-EM, NMR, SAXS)
Computational modeling to fill experimental gaps
Molecular dynamics simulations to explore conformational space
Benefits: More complete structural understanding, dynamic information
Structure-guided enzyme engineering:
Identification of hotspots for mutagenesis
Rational design of variants with altered specificity
Computational prediction of mutations to enhance stability or activity
Correlation of structural features with kinetic parameters
Structural studies would be particularly valuable for understanding:
The binding mode of different chain-length substrates
Conformational changes during the catalytic cycle
The basis for NADPH vs. NADH preference
Potential oligomerization states and their functional significance
These approaches would complement biochemical and kinetic analyses to provide a comprehensive understanding of Kpol_513p6 structure-function relationships .
Despite the available information on Recombinant Vanderwaltozyma polyspora 3-ketoacyl-CoA reductase (Kpol_513p6), several significant knowledge gaps remain that represent important opportunities for future research:
Detailed substrate specificity profile: While the general function of Kpol_513p6 as a 3-ketoacyl-CoA reductase is established, comprehensive characterization of its chain-length preferences and kinetic parameters across different substrates is lacking. Understanding these preferences would provide insights into its specific role in fatty acid elongation.
Structural determinants of function: No high-resolution structure of Kpol_513p6 has been published. Structural information would significantly enhance our understanding of its catalytic mechanism, substrate binding mode, and potential for enzyme engineering.
Physiological role in Vanderwaltozyma polyspora: The specific biological functions of Kpol_513p6 in its native organism remain incompletely understood. Questions regarding its role in stress responses, membrane homeostasis, and potential involvement in specialized lipid synthesis remain unanswered.
Regulatory mechanisms: How the expression and activity of Kpol_513p6 are regulated in response to changing environmental conditions or metabolic demands is not well characterized. Understanding these regulatory mechanisms would provide insights into the integration of fatty acid elongation with other metabolic pathways.
Comparative analysis with homologs: Systematic comparison of Kpol_513p6 with homologous enzymes from other organisms would help identify conserved features and unique characteristics that might be relevant to its specific function or evolutionary adaptation.
Addressing these knowledge gaps will require integrated approaches combining biochemical characterization, structural biology, systems biology, and physiological studies. The development and application of high-throughput methods, as discussed earlier, would significantly accelerate progress in filling these gaps .