Recombinant Pseudomonas syringae pv. tomato 7-cyano-7-deazaguanine synthase (queC)

What is 7-cyano-7-deazaguanine synthase (queC) and what reaction does it catalyze?

7-Cyano-7-deazaguanine synthase (EC 6.3.4.20), also known as preQ0 synthase or queC gene product, is an enzyme that catalyzes a critical nitrile-forming reaction in the biosynthetic pathway of deazapurines . Specifically, it catalyzes the following chemical reaction:

7-carboxy-7-carbaguanine + NH₃ + ATP → 7-cyano-7-carbaguanine + ADP + phosphate + H₂O

This enzyme binds Zn²⁺ as a cofactor and is classified as a ligase that forms carbon-nitrogen bonds . In biochemical terms, it functions as a 7-carboxy-7-carbaguanine:ammonia ligase (ADP-forming) . The enzyme from Geobacillus kaustophilus has been extensively characterized and shows high thermostability with an optimal pH of 9.5 and an apparent temperature optimum at 60°C .

How does Pseudomonas syringae pv. tomato enter and infect host plants?

Pseudomonas syringae pv. tomato infection involves a sophisticated entry process driven by chemotaxis toward plant-derived compounds that help the bacteria locate plant openings . Research has demonstrated that perception of gamma-aminobutyric acid (GABA) and L-Proline (L-Pro), two abundant components in the tomato apoplast, through the PsPto-PscC chemoreceptor drives bacterial entry into the tomato apoplast .

The specific mechanism works as follows:

• Recognition of GABA and L-Pro by the PsPto-PscC chemoreceptor causes chemoattraction toward these amino acids

• This chemotactic response facilitates bacterial movement toward plant openings

• The chemoreceptor also participates in regulating GABA catabolism

• Mutation of the PsPto-PscC chemoreceptor reduces chemotactic response, impairs entry, and diminishes virulence

Interestingly, GABA and L-Pro levels significantly increase in tomato plants upon pathogen infection and are involved in regulating plant defense responses. This represents an example of how bacteria have evolved to respond to plant signals produced during host-pathogen interactions to ensure efficient infection .

What phylogenetic relationships exist between different Pseudomonas syringae pv. tomato strains?

Multilocus sequence typing (MLST) analysis has revealed distinct phylogenetic relationships between different Pseudomonas syringae pv. tomato strains. Two main clusters have been identified :

The typical P. syringae pv. tomato strains form a distinct phylogenetic clade separate from PtoDC3000. They have all been isolated from tomato, show higher virulence on tomato than PtoDC3000, and do not cause disease on either A. thaliana or cauliflower .

PtoDC3000 belongs to a mixed phylogenetic group containing almost identical P. syringae pv. maculicola and P. syringae pv. tomato isolates from cultivated Brassicaceae and wild Solanaceae species . This unusual phylogenetic positioning makes PtoDC3000 an atypical tomato isolate, despite being widely used as a model organism.

What are the optimized methodologies for expressing and purifying recombinant 7-cyano-7-deazaguanine synthase from Pseudomonas syringae pv. tomato?

Based on successful heterologous expression of 7-cyano-7-deazaguanine synthase from other prokaryotes like G. kaustophilus , an effective methodology for expressing and purifying this enzyme from Pseudomonas syringae pv. tomato would include:

Optimized Expression Protocol:

• Vector Selection: Use pET-based expression vectors with T7 promoter systems for high-level expression in E. coli BL21(DE3) or similar strains

• Codon Optimization: Adjust codons to match E. coli preference while maintaining the Pseudomonas syringae pv. tomato queC sequence integrity

• Expression Conditions: Based on the thermostability of the enzyme from G. kaustophilus, induction at 30°C with 0.5 mM IPTG for 4-6 hours can yield functional protein

• Buffer Optimization: Include Zn²⁺ in buffers (typically 1-5 μM) to ensure proper cofactor binding

Purification Strategy:

• Initial Capture: Immobilized metal affinity chromatography (IMAC) using a His-tag

• Secondary Purification: Size exclusion chromatography to remove aggregates

• Buffer Composition: 50 mM Tris-HCl, pH 7.5-8.0, 150 mM NaCl, 1-5 μM ZnCl₂, 5% glycerol

Activity Assessment:
Activity can be measured using an HPLC-MS based assay to detect the formation of 7-cyano-7-deazaguanine from 7-carboxy-7-deazaguanine in the presence of ATP and ammonia . ³¹P NMR spectroscopy can be employed to monitor ATP conversion to ADP during the reaction .

How does recombination contribute to the evolution of Pseudomonas syringae pv. tomato and its pathogenicity factors?

Recombination plays a critical role in the evolution of Pseudomonas syringae pv. tomato, particularly in developing and diversifying its pathogenicity mechanisms. Analysis of multilocus sequence typing (MLST) data reveals several important insights :

• Recombination Frequency: Population genetic tests indicate that recombination contributed more than mutation to the variation between isolates

• Recombination Breakpoints: Several recombination breakpoints were detected within sequenced gene fragments

• Type III Secreted Effectors: Recombination may play an important role in the reassortment of Type III Secreted (T3S) effectors between strains

This is exemplified by analysis of the locus coding for the type III secreted effector AvrPto1, which showed evidence of recombination-driven evolution . The data suggest that recombination serves as a mechanism for:

• Horizontal transfer of virulence genes between different strains

• Creation of novel combinations of effector proteins

• Adaptation to new host plants or environmental conditions

• Generation of diversity that may help evade host resistance mechanisms

This recombination-driven evolution helps explain the phylogenetic relationship between PtoDC3000 and its close relatives, despite detected recombination between them . Understanding these recombination patterns is crucial for predicting the emergence of new pathogen variants and developing durable disease resistance strategies.

What experimental considerations are critical when studying the biochemical properties and kinetics of 7-cyano-7-deazaguanine synthase?

When investigating the biochemical properties and kinetics of 7-cyano-7-deazaguanine synthase, several experimental considerations are critical for obtaining accurate and reproducible results:

Enzyme Stability and Storage:

• Maintain purified enzyme at -80°C in buffer containing 10-20% glycerol

• Consider the thermostability profile (temperature optimum approximately 60°C for the G. kaustophilus enzyme)

• Account for pH dependency with optimal activity at pH 9.5

Reaction Conditions for Kinetic Studies:

• Ensure strict substrate specificity control, as the enzyme shows high specificity for the natural substrate 7-carboxy-7-deazaguanine

• Include metal cofactor (Zn²⁺) at appropriate concentrations

• Control ATP concentration as a critical parameter affecting reaction rate

• Monitor AMP and pyrophosphate as co-products of preQ₀ formation

Analytical Methods:

• HPLC-MS based assays provide accurate quantification of substrate consumption and product formation

• ³¹P NMR spectroscopy enables real-time monitoring of ATP conversion to ADP

• Fluorescence-based thermal-shift assays can assess protein stability under various conditions

Data Analysis Considerations:

• Apply appropriate enzyme kinetics models (Michaelis-Menten, allosteric models)

• Account for potential product inhibition

• Consider cooperative binding effects if multiple substrates are involved

• Validate results using multiple analytical methods to minimize technique-specific artifacts

How can quasi-experimental design approaches be applied to study Pseudomonas syringae pv. tomato host interactions?

Quasi-experimental design approaches offer valuable methodologies for studying Pseudomonas syringae pv. tomato host interactions when random assignment is not feasible due to ethical or practical constraints . These approaches are particularly relevant for field studies or when working with genetically diverse plant populations.

Applicable Quasi-Experimental Designs:

• Nonequivalent Groups Design:

  • Compare infection outcomes between different plant cultivars or ecotypes with varying levels of resistance

  • Control for confounding variables by selecting groups as similar as possible in relevant characteristics

  • Example: Comparing PtoDC3000 infection progression in different tomato cultivars versus Arabidopsis thaliana ecotypes

• Regression Discontinuity Design:

  • Utilize natural thresholds in plant populations (such as expression levels of defense genes)

  • Examine bacterial proliferation rates on either side of the threshold

  • Example: Studying infection outcomes in plants with expression levels of defense genes above or below a certain threshold

• Natural Experiments:

  • Leverage naturally occurring events that affect bacterial pathogenicity

  • Example: Studying how environmental factors like temperature shifts affect the PsPto-PscC chemoreceptor's ability to detect GABA and L-Pro

Implementation Considerations:

• Carefully document all potential confounding variables

• Use statistical methods like propensity score matching to account for non-random assignment

• Include appropriate controls to strengthen causal inferences

• Combine with genomic or transcriptomic approaches to identify molecular mechanisms

What role does 7-cyano-7-deazaguanine synthase play in the metabolic pathways and virulence of Pseudomonas syringae pv. tomato?

While direct evidence from the search results is limited, integration of information from multiple sources suggests that 7-cyano-7-deazaguanine synthase (queC) plays important roles in Pseudomonas syringae pv. tomato metabolism and potentially virulence:

Biosynthetic Pathway Involvement:

• QueC catalyzes a critical step in the biosynthesis of queuosine, a modified nucleoside found in certain tRNAs

• This reaction converts 7-carboxy-7-deazaguanine to 7-cyano-7-deazaguanine (preQ₀) using ATP and ammonia

• The pathway continues to produce queuosine, which affects translational fidelity and efficiency

Potential Contributions to Virulence:

• Translational Control: Modified tRNAs containing queuosine may regulate the translation of specific virulence factors

• Stress Adaptation: Queuosine modification may enhance bacterial survival under stress conditions encountered during plant infection

• Metabolic Versatility: The enzyme may contribute to metabolic flexibility needed during different infection phases

Research Approaches to Investigate Virulence Connections:

• Generate queC knockout mutants in Pseudomonas syringae pv. tomato and assess:

  • Growth characteristics in various media

  • Ability to cause disease in different host plants

  • Expression of type III secretion system components

• Utilize comparative genomics to:

  • Examine queC conservation across Pseudomonas strains with different virulence profiles

  • Identify potential horizontal gene transfer events involving queC

  • Correlate queC sequence variations with host range differences

How can researchers use large-language models and AI tools to enhance their studies of Pseudomonas syringae pv. tomato enzymes?

Researchers studying Pseudomonas syringae pv. tomato enzymes like 7-cyano-7-deazaguanine synthase can leverage large language models (LLMs) and AI tools to enhance various aspects of their research process:

Literature Analysis and Knowledge Integration:

• Deploy AI tools to systematically analyze the vast corpus of research on Pseudomonas syringae pv. tomato across multiple databases

• Use specialized AI search engines designed for academic papers to find answers to specific research questions

• Integrate knowledge from diverse sources to generate novel hypotheses about enzyme function and regulation

Experimental Design Optimization:

• Apply AI models to identify optimal parameters for recombinant protein expression

• Design quasi-experimental approaches that account for potential confounding variables

• Optimize data collection strategies for complex experiments

Data Analysis and Visualization:

• Utilize AI tools for analyzing tabular data from enzyme kinetics experiments

• Improve understanding of structured data through advanced prompting methods

• Generate comprehensive visualizations of metabolic pathways involving queC

Limitations and Considerations:

For tabular data analysis specifically, researchers should consider the TabPFN model approach, which uses synthetic data based on causal models to train foundational models that can make accurate predictions even with small datasets (less than 10,000 rows) .