Recombinant Pseudomonas syringae pv. syringae N-acetyl-gamma-glutamyl-phosphate reductase (argC)

What is the functional role of N-acetyl-gamma-glutamyl-phosphate reductase (argC) in Pseudomonas syringae?

N-acetyl-gamma-glutamyl-phosphate reductase (AGPR) catalyzes the nicotinamide adenine dinucleotide phosphate (NADPH)-dependent reductive dephosphorylation of N-acetyl-gamma-glutamyl-phosphate to N-acetylglutamate-gamma-semialdehyde. This enzymatic reaction is a critical step in the arginine biosynthetic pathway that is essential for numerous microorganisms and plants, including Pseudomonas syringae . The pathway provides arginine, an amino acid crucial for protein synthesis and cellular functions. In P. syringae, this pathway is particularly important as it contributes to bacterial survival, growth, and potentially to pathogenicity in plant hosts.

What is the structural organization of the N-acetyl-gamma-glutamyl-phosphate reductase enzyme?

The structure of N-acetyl-gamma-glutamyl-phosphate reductase consists of two primary domains: an α/β domain and an α+β domain. The catalytic site is located in the cleft between these domains, where NADP+ binds . Upon cofactor binding, the enzyme undergoes a conformational change, particularly in a loop (Leu88 to His92) that moves more than 5 Å to confine the cofactor's adenine moiety in a hydrophobic pocket . This structural arrangement is essential for proper substrate positioning and catalytic function.

What catalytic residues are critical for argC enzyme function, and how might their modification affect activity?

Based on structural analyses, several key residues play crucial roles in the catalytic mechanism of N-acetyl-gamma-glutamyl-phosphate reductase. His217 and His219 form hydrogen bonds with the substrate, while Arg114 forms an ion pair with the substrate phosphate group . These interactions optimally position the substrate for nucleophilic attack by Cys158 on the substrate γ-carboxyl group. His219 likely functions as a general base to accept a proton from Cys158, with the adjacent ion pair interaction with Glu222's side-chain carboxyl group stabilizing the resulting positive charge on His219 .

For researchers designing site-directed mutagenesis experiments, these residues represent primary targets. Modifications to His217 or His219 would likely disrupt substrate binding, while alterations to Cys158 would directly impact the nucleophilic attack. Changes to Arg114 could affect phosphate group interactions, and modifications to Glu222 might destabilize the catalytic triad. Experimental validation through activity assays comparing wild-type and mutated enzymes would be essential for confirming these predictions.

How can recombineering techniques be optimized for genetic manipulation of argC in Pseudomonas syringae?

Recombineering in P. syringae can be optimized using the RecTE homologous recombination system. For efficient manipulation of argC, consider the following methodology:

• Vector selection: The pUCP24/47 vector system has been successfully used for expressing recombineering proteins in P. syringae .

• Recombination protein expression: For single-stranded DNA oligonucleotide recombination, expressing the P. syringae RecT homolog is sufficient, while efficient double-stranded DNA recombination requires expression of both RecT and RecE homologs .

• DNA substrate design: For argC targeting, design linear DNA fragments with 50-100 bp homology arms flanking the intended modification site. This approach has shown success in making targeted gene disruptions in the P. syringae chromosome .

• Transformation optimization: Electroporation conditions should be optimized specifically for P. syringae pv. syringae (typically 2.5 kV, 25 μF, 200 Ω), and the recombination frequency can be calculated by standardizing the number of resistant transformants to 10^8 viable cells .

• Selection strategy: For argC modifications, consider using antibiotic resistance markers or counterselectable markers like sacB to facilitate the isolation of recombinants .

What approaches can address the challenges of protein solubility when expressing recombinant P. syringae argC in heterologous systems?

When expressing recombinant P. syringae argC in heterologous systems, researchers often encounter solubility issues. These challenges can be addressed through several strategies:

• Optimization of expression conditions: Lowering the induction temperature (16-20°C), reducing IPTG concentration, and extending expression time can improve solubility.

• Solubility tags: Fusion with solubility-enhancing tags such as MBP (maltose-binding protein), SUMO, or TrxA (thioredoxin) can significantly increase soluble expression.

• Co-expression with chaperones: Co-expressing argC with molecular chaperones (GroEL/GroES, DnaK/DnaJ/GrpE) can assist with proper protein folding.

• Domain-based approach: Based on the structural information that argC consists of α/β and α+β domains with NADP+ binding in the cleft between them , expressing individual domains or optimizing constructs to prevent interdomain misfolding may improve solubility.

• Buffer optimization: Screening various buffer conditions during purification, including different pH ranges, salt concentrations, and stabilizing additives such as glycerol or arginine, can enhance protein stability and solubility.

What are the optimal conditions for assaying N-acetyl-gamma-glutamyl-phosphate reductase activity in vitro?

For optimal in vitro assay of N-acetyl-gamma-glutamyl-phosphate reductase activity, consider these methodological parameters:

• Buffer composition: A typical assay buffer would contain 50 mM Tris-HCl (pH 7.5-8.0), 100 mM NaCl, and 5 mM MgCl₂.

• Cofactor requirements: Include 0.2-0.5 mM NADPH as the reducing cofactor, as the enzyme catalyzes an NADPH-dependent reaction .

• Substrate concentration: Optimize N-acetyl-gamma-glutamyl-phosphate concentration between 0.1-1.0 mM for kinetic studies.

• Reaction monitoring: The enzymatic activity can be monitored by:

  • Spectrophotometric measurement of NADPH oxidation at 340 nm

  • HPLC detection of the reaction product N-acetylglutamate-gamma-semialdehyde

  • Coupled enzyme assays that link product formation to a detectable signal

• Controls: Include enzyme-free and substrate-free controls to account for background NADPH oxidation or other non-specific reactions.

• Temperature and pH optimization: Based on the physiological conditions of P. syringae, starting points would be 25-30°C and pH 7.5, but optimization experiments should be conducted to determine the enzyme's pH and temperature optima.

How can researchers effectively analyze the impact of argC mutations on Pseudomonas syringae pathogenicity?

To effectively analyze how argC mutations impact P. syringae pathogenicity, implement this comprehensive methodological approach:

• Generation of defined mutants: Create precise argC mutations using recombineering with the P. syringae RecTE system . This allows for site-directed mutagenesis targeting specific catalytic residues (His217, His219, Cys158, Arg114) or complete gene knockouts.

• In vitro growth characterization: Compare growth rates of wild-type and mutant strains in minimal media with and without arginine supplementation to assess auxotrophy.

• Plant infection assays: Conduct standardized infection assays using:

  • Leaf infiltration with bacterial suspensions

  • Measurement of bacterial growth in planta over 0-7 days

  • Scoring of disease symptoms using established rating scales

  • Comparative analysis across multiple host plants to assess host range effects

• Complementation studies: Perform genetic complementation with:

  • Wild-type argC

  • Site-directed argC mutants

  • Heterologous argC genes from related species

• Transcriptomic analysis: Compare gene expression profiles between wild-type and argC mutants during infection to identify downstream effects on virulence gene expression.

• Metabolomic analysis: Quantify arginine and related metabolites in wild-type and mutant strains to correlate metabolic changes with virulence phenotypes.

What considerations are important when designing experiments to study the evolutionary conservation of argC across Pseudomonas syringae pathovars?

When investigating evolutionary conservation of argC across P. syringae pathovars, consider these methodological aspects:

• Sample selection: Include representative strains from multiple P. syringae pathovars, ensuring coverage of the four major clades identified in phylogenetic analyses . The remarkable degree of congruence observed among housekeeping genes in P. syringae suggests argC likely follows similar evolutionary patterns .

• Sequence analysis approach:

  • PCR amplification and sequencing of argC from diverse strains

  • Alignment and phylogenetic analysis using maximum-likelihood methods

  • Analysis of synonymous vs. non-synonymous substitution rates (dN/dS) to assess selective pressure

• Host association analysis: Apply analysis of molecular variance (AMOVA) to determine whether host association explains genetic variation in argC, similar to analyses showing host association explains only a small proportion of genetic variation in core genome genes .

• Recombination assessment: Apply multiple methods to assess recombination rates:

  • Split decomposition graphs to visualize potential recombination events

  • Calculation of Maynard Smith's I₍A₎ to test for linkage disequilibrium

  • Sliding-window phylogenetic tests to identify potential recombination breakpoints

• Structural mapping of variations: Map sequence variations onto the protein structure to identify whether changes occur in functional regions (catalytic site, cofactor binding) or in less constrained regions.

• Functional conservation testing: Express argC from different pathovars in a common genetic background to test functional complementation and enzyme kinetics.

How should researchers interpret variations in catalytic efficiency of argC enzymes from different Pseudomonas syringae strains?

When analyzing variations in catalytic efficiency among argC enzymes from different P. syringae strains, consider these interpretative frameworks:

• Structure-function relationship analysis: Map amino acid variations to the 3D structure of the enzyme, particularly noting changes near:

  • The catalytic residues (His217, His219, Cys158, Arg114, Glu222)

  • The NADP+ binding cleft between α/β and α+β domains

  • The loop (Leu88 to His92) that undergoes conformational change upon cofactor binding

• Catalytic parameter comparison: Analyze differences in:

  • K​​m values for N-acetyl-gamma-glutamyl-phosphate and NADPH

  • k​cat values representing catalytic turnover rates

  • k​cat/K​m ratios as measures of catalytic efficiency

  • Inhibition profiles and substrate specificity

• Ecological context interpretation: Consider how variations correlate with:

  • Host plant preferences of different pathovars

  • Geographical origin of strains

  • Environmental adaptation factors

• Evolutionary interpretation: Given that P. syringae has a low recombination rate (mutation is approximately four times more likely than recombination to change any nucleotide) , significant variations in argC may reflect long-term adaptive pressures rather than recent horizontal gene transfer.

What statistical approaches are most appropriate for analyzing the relationship between argC variation and strain virulence?

When analyzing relationships between argC variation and strain virulence, implement these statistical approaches:

• Correlation analyses:

  • Pearson or Spearman correlation coefficients to assess relationships between:

    • Enzyme kinetic parameters and quantitative virulence measures

    • Specific amino acid variations and virulence metrics

  • Multiple regression models to account for confounding variables

• Comparative phylogenetic methods:

  • Phylogenetically independent contrasts to control for evolutionary relationships

  • Ancestral state reconstruction to infer the evolutionary history of argC variants

  • Tests for correlated evolution between argC features and virulence traits

• Multivariate approaches:

  • Principal component analysis (PCA) to identify patterns of variation across multiple parameters

  • Cluster analysis to identify groups of strains with similar argC and virulence profiles

  • Partial least squares regression to identify which argC variations best predict virulence

• Machine learning approaches:

  • Random forest algorithms to identify the most important argC features predicting virulence

  • Support vector machines for classification of strains based on argC features

• Statistical power considerations:

  • Given P. syringae's highly clonal nature with limited recombination , larger sample sizes may be needed to detect meaningful associations

  • A priori power analyses should guide sample size determination

How can researchers effectively compare argC function between different recombinant expression systems?

When comparing argC function between different recombinant expression systems, implement this methodological framework:

• Standardization of expression constructs:

  • Use identical coding sequences across expression systems

  • Standardize fusion tags or remove tags enzymatically before comparison

  • Verify complete sequence identity of the expressed protein

• Protein quality assessment:

  • Circular dichroism spectroscopy to compare secondary structure

  • Thermal shift assays to assess protein stability

  • Size exclusion chromatography to confirm monomeric/oligomeric state

  • Activity measurements with defined substrate concentrations

• Comparative enzymatic analysis:

  • Determine kinetic parameters (K​m, k​cat, k​cat/K​m) under identical conditions

  • Analyze pH and temperature optima and stability profiles

  • Assess cofactor specificity (NADPH vs. NADH)

  • Measure inhibition constants for potential inhibitors

• Normalization approaches:

  • Express activity relative to protein concentration determined by multiple methods

  • Consider specific activity (units/mg) for direct comparison

  • Use internal standards across experiments

• Statistical analysis:

  • ANOVA with post-hoc tests to identify significant differences

  • Equivalence testing to determine if different expression systems produce functionally similar enzymes

What are the most promising approaches for developing argC-targeted antimicrobials against Pseudomonas syringae plant infections?

The development of argC-targeted antimicrobials against P. syringae infections could follow these methodological approaches:

• Structure-based inhibitor design:

  • Virtual screening targeting the catalytic site containing His217, His219, and Cys158

  • Fragment-based approaches focused on the substrate binding pocket

  • Transition-state analog design based on the NADPH-dependent reductive dephosphorylation mechanism

• Allosteric inhibitor development:

  • Target the conformational change in the Leu88 to His92 loop that occurs upon NADP+ binding

  • Design compounds that lock the enzyme in an inactive conformation

  • Develop inhibitors that disrupt the ion pair between Arg114 and the substrate phosphate group

• Validation methodology:

  • In vitro enzyme inhibition assays with purified recombinant argC

  • Cell-based assays measuring growth inhibition of P. syringae in minimal media

  • Plant infection models assessing protection efficacy

  • Resistance development monitoring in sequential passage experiments

• Delivery system considerations:

  • Formulation optimization for foliar application

  • Systemic delivery through plant vascular systems

  • Nanoparticle-based targeted delivery

• Selectivity assessment:

  • Comparative inhibition of argC from beneficial microorganisms

  • Effects on plant AGPR homologs

  • Environmental impact studies

How might researchers address the challenges of expressing and purifying sufficient quantities of active recombinant argC for structural studies?

For successful expression and purification of active recombinant argC for structural studies, implement this methodological strategy:

• Expression system optimization:

  • Test multiple expression hosts (E. coli BL21(DE3), Rosetta, Arctic Express)

  • Evaluate codon-optimized synthetic genes

  • Screen expression temperature (16-30°C), inducer concentration, and duration

  • Co-express with molecular chaperones (GroEL/GroES, DnaK/DnaJ/GrpE)

• Construct design considerations:

  • Create multiple constructs with varying N- and C-terminal boundaries

  • Test different solubility-enhancing fusion tags (MBP, SUMO, TrxA)

  • Include TEV or PreScission protease sites for tag removal

  • Design based on structural information about domain organization

• Purification protocol development:

  • Implement multi-step purification (affinity, ion exchange, size exclusion)

  • Screen buffer conditions (pH 6.0-8.5, NaCl 50-500 mM)

  • Include stabilizing additives (5-10% glycerol, 1-5 mM DTT, 0.1-1 mM EDTA)

  • Add NADP+ (0.1-1 mM) to stabilize enzyme conformation

• Activity preservation strategies:

  • Monitor activity throughout purification

  • Identify and minimize proteolytic degradation

  • Optimize storage conditions (-80°C vs. liquid nitrogen)

  • Test cryoprotectants (glycerol, sucrose, trehalose)

• Structural biology preparation:

  • Assess homogeneity by dynamic light scattering

  • Verify secondary structure by circular dichroism

  • Perform thermal shift assays to identify stabilizing conditions

  • Conduct crystallization pre-screens to identify promising conditions

What experimental approaches could best elucidate the regulatory mechanisms controlling argC expression in Pseudomonas syringae under different environmental conditions?

To investigate regulatory mechanisms controlling argC expression in P. syringae under various environmental conditions, implement these methodological approaches:

• Promoter analysis:

  • 5' RACE to map transcription start sites

  • Reporter fusion constructs (GFP, luciferase) to monitor promoter activity

  • Deletion analysis to identify regulatory elements

  • DNA-protein interaction studies (EMSA, DNase footprinting) to identify transcription factor binding sites

• Transcriptional regulation studies:

  • RNA-seq analysis under various conditions (nutrient limitation, plant extract exposure, temperature shifts)

  • qRT-PCR validation of expression changes

  • ChIP-seq to identify transcription factors binding to the argC promoter

  • Construction of transcription factor mutants using recombineering with the P. syringae RecTE system

• Post-transcriptional regulation:

  • Analysis of mRNA stability under different conditions

  • Investigation of potential small RNA regulators

  • Ribosome profiling to assess translation efficiency

• Metabolic regulation:

  • Metabolomic analysis to correlate arginine pathway metabolites with argC expression

  • Enzyme activity assays under different growth conditions

  • Feedback inhibition studies with pathway end products

• In planta expression analysis:

  • Laser capture microdissection coupled with qRT-PCR

  • In planta imaging of reporter strains

  • Comparison of expression in resistant versus susceptible host plants