Recombinant Chlamydophila caviae Histidine--tRNA ligase (hisS)

What is Chlamydophila caviae Histidine--tRNA ligase (hisS) and what is its biological function?

Chlamydophila caviae Histidine--tRNA ligase (hisS) is an essential aminoacyl-tRNA synthetase that catalyzes the attachment of histidine to its cognate tRNA molecule (tRNA^His). This charged tRNA is critical for protein synthesis, specifically for incorporating histidine amino acids into growing polypeptide chains during translation. In Chlamydophila caviae, which causes inclusion conjunctivitis (GPIC) and genital tract infections in guinea pigs, hisS plays a vital role in maintaining proper protein synthesis .

The enzyme belongs to the class II aminoacyl-tRNA synthetase family and functions by a two-step reaction mechanism:

• Activation of histidine with ATP to form histidyl-AMP

• Transfer of the activated histidine to the appropriate tRNA molecule

This aminoacylation process is fundamental to the organism's ability to synthesize proteins required for its developmental cycle, particularly during transformation from elementary body (EB) to reticulate body (RB) forms within host cells.

How is the hisS gene conserved across different Chlamydiaceae species?

The hisS gene demonstrates significant conservation across Chlamydiaceae species, reflecting its essential role in protein synthesis. Comparative genomic analyses reveal that hisS is part of the core genome shared among Chlamydophila caviae, Chlamydophila abortus, and Chlamydophila pneumoniae, with sequence identity typically exceeding 85% . This conservation extends to key catalytic and structural domains essential for aminoacylation function.

A significant difference is observed in metabolic gene complements between species. For instance, Cp. abortus contains biotin biosynthetic genes (bioBFDA) that are absent from Cp. caviae . Such genomic differences may reflect niche-specific adaptations that complement the core functions maintained by conserved genes like hisS.

How does inhibition of hisS affect Chlamydophila cellular processes?

Inhibition of hisS activity produces cascading effects throughout Chlamydophila cellular processes:

First, reduced aminoacylation function directly impairs protein synthesis. Studies with histidinol, a competitive inhibitor of histidyl-tRNA synthetase, demonstrate that inhibition can decrease protein synthesis by 20-30% . This effect can be measured using puromycin analogs like OP-puromycin, which are incorporated into nascent polypeptides and can be detected by fluorescent probes .

Beyond immediate translation effects, hisS inhibition triggers cellular stress responses. Research demonstrates that decreased aminoacylation leads to accumulation of uncharged tRNAs, which activates the integrated stress response pathway through phosphorylation of eIF2α . Cells transfected with mutant HARS (histidyl-tRNA synthetase) show 2-2.5 fold increases in phosphorylated eIF2α compared to controls .

Additionally, sustained hisS inhibition impacts developmental processes. In other systems where aminoacyl-tRNA synthetase function was compromised, significant impairment of differentiation processes was observed. For example, inhibition with 1-2 mM histidinol significantly decreased neurite outgrowth in PC12 cells . Similar developmental disruptions would likely occur in the Chlamydophila lifecycle, potentially interfering with the EB to RB transition essential for productive infection.

What experimental approaches allow accurate measurement of recombinant hisS activity?

Multiple complementary methods can be employed to measure the aminoacylation activity of recombinant Chlamydophila caviae hisS:

Aminoacylation Assay with Detection of Charged tRNA:
This direct method measures the formation of histidyl-tRNA using either radioactive or non-radioactive detection methods:

• Reaction mixture: Purified hisS enzyme, histidine (radiolabeled or unlabeled), ATP, Mg²⁺, and tRNA^His

• Detection options: Acid-precipitation of charged tRNA followed by scintillation counting (radioactive method) or northern blotting with specific probes (non-radioactive method)

• Advantages: Directly measures the complete reaction

• Limitations: May require specialized equipment or radioactive materials depending on detection method

Pyrophosphate Detection Assay:
This continuous spectrophotometric assay couples the release of pyrophosphate to a colorimetric reaction:

• Reaction components: hisS, histidine, ATP, tRNA, coupled enzyme system (pyrophosphatase plus downstream enzymes that link to NAD(P)H oxidation)

• Measurement: Decrease in absorbance at 340 nm corresponding to NAD(P)H consumption

• Advantages: Real-time monitoring, non-radioactive, amenable to high-throughput formats

• Limitations: Potential interference from coupling enzymes or assay components

ATP Consumption Assay:
This approach monitors the consumption of ATP during the aminoacylation reaction:

• Method: Coupling ATP hydrolysis to luciferase reaction or other ATP-detection systems

• Measurement: Decrease in luminescence or other ATP-dependent signal

• Advantages: High sensitivity, adaptable to plate reader formats

• Limitations: Does not directly confirm charging of tRNA

When determining kinetic parameters, standard conditions typically include:

• Temperature: 37°C

• pH: 7.5-8.0

• ATP: 2-5 mM

• Mg²⁺: 5-10 mM

• Variable histidine: 1-100 μM (for Km determination)

• Variable tRNA^His: 0.1-10 μM (for Km determination)

How can metabolomic approaches be applied to study hisS function in Chlamydophila caviae?

Metabolomic approaches offer powerful tools for understanding the systemic effects of hisS function in Chlamydophila caviae:

Hybrid Dynamic/Static (HDS) Modeling Framework:
The HDS method combines kinetic representation with metabolic flux analysis (MFA) to model metabolic systems with limited experimental parameters . This approach is particularly valuable for studying hisS in the context of Chlamydophila metabolism:

• Implementation strategy: The aminoacylation reaction catalyzed by hisS can be included in the dynamic module, while connected metabolic pathways can be represented in the static module

• Advantage: Requires significantly fewer kinetic parameters while maintaining model accuracy

• Data requirement: Enzyme reaction rates can be estimated from metabolite concentration time series data

This approach can discriminate enzymes into static and dynamic modules based on their behavior in response to perturbations . For hisS research, this would allow modeling its interactions with broader metabolic networks with minimal parameter requirements.

Experimental Design for Metabolomic Studies:
A systematic approach should include:

• Baseline metabolite profiling of wild-type C. caviae under standard growth conditions

• Perturbation studies using sub-lethal concentrations of histidinol (0.5-1 mM)

• Time-series sampling post-inhibition to capture dynamic metabolic responses

• Detection of key metabolites including:

  • Amino acids (particularly histidine)

  • Nucleotides involved in aminoacylation (ATP, AMP)

  • tRNA species (charged and uncharged)

  • Stress response metabolites

Data Analysis and Integration:
The application of appropriate statistical methods is critical:

• Principal Component Analysis (PCA) to identify major variation sources

• Pathway enrichment analysis to identify significantly affected metabolic processes

• Integration with the HDS modeling approach to distinguish dynamic and static elements of the metabolic response

• Correlation analysis between metabolite changes and phenotypic outcomes

What methods can be used to evaluate the impact of site-directed mutations on hisS function?

Evaluating how site-directed mutations affect Chlamydophila caviae hisS function requires a multi-faceted approach combining structural analysis, biochemical characterization, and cellular studies:

Structural Impact Assessment:

Biochemical Characterization:
A comprehensive enzyme kinetics analysis should examine:

• Catalytic efficiency: Determine changes in kcat and Km for all substrates (histidine, ATP, tRNA^His)

• Thermal stability: Measure enzyme melting temperatures via differential scanning fluorimetry

• Oligomerization state: Assess whether mutations affect dimerization using size exclusion chromatography

• Substrate specificity: Test activity with non-cognate amino acids and tRNAs to detect specificity alterations

• Inhibitor sensitivity: Compare sensitivity to histidinol or other inhibitors between wild-type and mutant enzymes

Cellular Function Evaluation:
When possible, assess mutant hisS function in cellular contexts:

• Complementation studies: Test whether mutant hisS can rescue growth in conditional knockout strains

• Protein synthesis measurement: Using methods like OP-puromycin incorporation to quantify translation rates

• Stress response activation: Measuring phosphorylation of eIF2α as an indicator of integrated stress response

• Growth kinetics: Comparing growth rates and developmental cycle progression

Systematic Mutation Strategy:
Design a comprehensive mutation panel targeting:

• Catalytic residues: Directly involved in histidine activation or transfer

• tRNA binding interface: Responsible for tRNA^His recognition

• Dimerization interface: Critical for maintaining quaternary structure

• Species-specific residues: Unique to C. caviae compared to other Chlamydiaceae

For each mutation, correlate structure-based predictions with experimental outcomes to build a comprehensive structure-function map of C. caviae hisS.

How do you resolve discrepancies between in vitro enzyme activity and cellular phenotypes?

Discrepancies between in vitro hisS activity measurements and observed cellular phenotypes require systematic analysis to resolve:

Common Discrepancy Patterns:

• Magnitude discrepancies: In vitro enzyme assays often show higher specific activity than estimated in vivo rates

• Inhibitor potency differences: Compounds like histidinol may show different IC50 values between systems

• Mutant impact variations: Mutations that severely compromise enzyme activity in vitro sometimes produce milder cellular phenotypes

Resolution Approach:

First, evaluate methodological differences that might explain discrepancies:

• Reaction conditions: Buffer composition, pH, temperature, and ionic strength differences

• Substrate concentrations: Cellular ATP, histidine, and tRNA^His concentrations may differ significantly from in vitro conditions

• Presence of regulatory factors: Cellular environments contain potential regulators absent from purified systems

Second, consider biological compensation mechanisms:

• Protein turnover rates: Differences in enzyme stability between test tube and cellular environment

• Adaptive responses: Stress response activation may partially compensate for reduced function

• Pathway redundancy: Alternative metabolic routes may bypass some effects of reduced hisS activity

Third, develop bridging experiments:

• Cell extract studies: Using cell-free extracts as an intermediate between purified enzyme and whole-cell systems

• Reconstituted systems: Gradually increasing complexity by adding cellular components to purified hisS

• Dose-response relationships: Establishing mathematical relationships between in vitro parameters and cellular outcomes

Case Example Application:
Studies with histidinol inhibition provide a useful model. While histidinol at 1-2 mM reduces protein synthesis by 20-30% in cellular systems , in vitro IC50 values might be in the μM range. This discrepancy can be systematically addressed by:

• Measuring intracellular histidinol concentrations to determine actual exposure

• Assessing histidinol metabolism or efflux that might reduce effective concentration

• Evaluating compensatory upregulation of translation factors

• Testing whether stress response activation partially offsets inhibition effects

What statistical approaches are most appropriate for analyzing hisS enzyme kinetics data?

Rigorous statistical analysis is crucial for accurately determining kinetic parameters of Chlamydophila caviae hisS:

Model Selection and Fitting:
For basic kinetic analysis, direct non-linear regression using appropriate enzyme kinetic models is strongly preferred over linearization methods:

• Michaelis-Menten equation: v = Vmax[S]/(Km + [S])

  • Standard model for single-substrate reactions or when other substrates are at saturating concentrations

  • Parameters: Vmax (maximum velocity) and Km (Michaelis constant)

• Bi-substrate models: For analyzing ATP and histidine binding

  • Random sequential: v = Vmax[A][B]/(KiaKb + Ka[B] + Kb[A] + [A][B])

  • Ordered sequential: v = Vmax[A][B]/(KiaKb + Ka[B] + [A][B])

  • Ping-pong: v = Vmax[A][B]/(Ka[B] + Kb[A] + [A][B])

• Inhibition models: For analyzing histidinol inhibition

  • Competitive: v = Vmax[S]/(Km(1+[I]/Ki) + [S])

  • Non-competitive: v = Vmax[S]/((Km + [S])(1+[I]/Ki))

  • Mixed: v = Vmax[S]/((Km(1+[I]/αKi) + S))

Experimental Design Considerations:

• Replication strategy: Minimum of 3-5 technical replicates and 2-3 biological replicates

• Concentration range: Should span from 0.2×Km to 5×Km for accurate parameter estimation

• Data points distribution: More points near the Km value

• Controls: Include enzyme-free and substrate-free controls in each experiment

Advanced Statistical Approaches:

• Global fitting: Simultaneously analyzing multiple datasets with shared parameters

• Bayesian methods: Incorporating prior knowledge about expected parameter values

• Bootstrap analysis: Generating confidence intervals by resampling experimental data

Reporting Standards:
For rigorous hisS kinetic analysis, report:

• Best-fit parameter values with 95% confidence intervals

• Goodness-of-fit statistics (R², sum of squares)

• Residual plots to demonstrate lack of systematic deviations

• Complete experimental conditions (temperature, pH, buffer composition)

This comprehensive approach ensures that kinetic parameters are accurately determined and can be meaningfully compared across studies.

How can computational models help predict the impact of hisS mutations on Chlamydophila caviae metabolism?

Computational modeling provides powerful tools for predicting how hisS mutations affect Chlamydophila caviae metabolism:

Structural Modeling and Mutation Impact Prediction:
Starting with protein structure analysis:

• Homology modeling: Creating a 3D model of C. caviae hisS based on related structures

• Molecular dynamics simulations: Assessing how mutations affect protein dynamics

• Binding site analysis: Predicting changes in substrate affinity and catalytic efficiency

Metabolic Network Integration:
The Hybrid Dynamic/Static (HDS) method described in search result is particularly valuable:

• Integration of hisS into the dynamic module: Modeling the aminoacylation reaction with detailed kinetics

• Connection to the static module: Linking to protein synthesis and amino acid metabolism

• Perturbation analysis: Simulating the effects of reduced hisS activity or altered kinetic parameters

The HDS method provides a significant advantage by requiring fewer experimental parameters than fully kinetic models while maintaining the ability to predict dynamic system behavior . This approach distinguishes enzymes into static and dynamic modules based on their metabolic behavior, allowing focused experimental characterization of only the most critical kinetic parameters .

Specific Applications to Mutation Analysis:
Mutations in hisS can be classified and analyzed:

• Catalytic site mutations: Directly affect aminoacylation chemistry

• tRNA binding site mutations: Alter substrate recognition

• Structural mutations: Affect protein stability or dimerization

For each mutation class, the modeling can predict:

By integrating these predictions with experimental validation, researchers can develop comprehensive models of how specific mutations affect both enzyme function and broader metabolic consequences in Chlamydophila caviae.

How can recombinant hisS be used to study Chlamydophila caviae pathogenesis and host-pathogen interactions?

Recombinant Chlamydophila caviae hisS offers several innovative approaches for investigating pathogenesis and host-pathogen interactions:

Tracking Protein Synthesis During Infection:

• Tagged hisS constructs: Creating fluorescently labeled or epitope-tagged hisS variants

• In situ activity assays: Developing methods to measure aminoacylation activity within infected cells

• Application: Monitoring translational activity during different stages of the developmental cycle

This approach can provide insights into:

• Temporal changes in protein synthesis during host cell invasion

• Metabolic adaptations in response to changing microenvironments

• Responses to host defense mechanisms

Investigating Entry Mechanisms:
Chlamydophila caviae entry into host cells involves specific molecular events including:

• GM1-containing microdomain clustering

• Accumulation of tyrosine-phosphorylated proteins

• Actin polymerization controlled by Cdc42 and Rac GTPases

Recombinant hisS tools can be used to investigate whether aminoacylation activity influences these entry processes through:

• Correlation studies between hisS activity and invasion efficiency

• Examining effects of histidinol treatment on bacterial entry processes

• Investigating potential non-canonical functions of hisS during host cell interaction

Stress Response and Persistence Studies:
Aminoacyl-tRNA synthetase inhibition triggers stress responses , which may relate to chlamydial persistence:

• Stress pathway activation: Measure eIF2α phosphorylation during infection with and without hisS inhibition

• Persistence induction: Determine whether sub-inhibitory histidinol treatment induces aberrant RB forms

• Host response modulation: Examine how hisS inhibition affects host inflammatory responses

The connection between hisS inhibition, protein synthesis reduction (20-30%), and stress response activation provides a foundation for understanding how translational stress influences the chlamydial developmental cycle and host-pathogen interaction.

What is the potential of targeting hisS for antimicrobial development against Chlamydiaceae?

Histidyl-tRNA synthetase represents a promising antimicrobial target with several advantages and challenges:

Target Validation Evidence:
Several lines of evidence support hisS as a viable antimicrobial target:

• Essentiality: As an aminoacyl-tRNA synthetase, hisS is critical for protein synthesis

• Inhibition effects: Studies with histidinol demonstrate that inhibiting histidyl-tRNA synthetase reduces protein synthesis by 20-30% and triggers stress responses

• Metabolic importance: Disruption of aminoacylation affects multiple cellular processes beyond translation

Inhibitor Development Strategies:
Several approaches can be employed to develop selective hisS inhibitors:

• Substrate analogs: Compounds structurally similar to histidine or ATP

• Transition state mimics: Molecules that mimic the aminoacylation reaction intermediate

• Allosteric inhibitors: Compounds binding to non-catalytic sites

• Dimerization inhibitors: Molecules that disrupt the functional dimeric structure

Selectivity Considerations:
Critical for developing safe antimicrobials is achieving selectivity for bacterial over human histidyl-tRNA synthetase:

• Structural differences: Exploiting unique features of bacterial hisS

• Species-specific pockets: Targeting binding sites unique to Chlamydiaceae

• Cellular uptake: Designing compounds selectively transported into bacterial cells

Development Challenges:
Several factors complicate hisS-targeted drug development:

• Intracellular location of Chlamydiaceae requiring compound penetration of host cell and inclusion membrane

• Potential for resistance development through target mutation

• Need for compounds that maintain activity in the unique microenvironment of chlamydial inclusions

Despite these challenges, the demonstrated impact of histidinol on protein synthesis and stress pathway activation suggests that even partial inhibition of hisS can have significant biological effects, making it a promising target for therapeutic development.

How can the hybrid dynamic/static (HDS) modeling approach enhance research on hisS and other metabolic enzymes?

The Hybrid Dynamic/Static (HDS) modeling approach offers significant advantages for studying hisS within the broader context of Chlamydophila metabolism:

Fundamental Principles of the HDS Method:
The HDS method divides a metabolic system into dynamic and static modules:

• Dynamic module: Reactions represented by differential equations with detailed kinetics

• Static module: Reactions analyzed using metabolic flux analysis (MFA) without requiring kinetic information

This approach dramatically reduces the experimental effort required for model construction while maintaining the ability to simulate system dynamics .

Application to hisS Research:
For studying hisS in Chlamydophila caviae:

• Parameter Reduction: By including only hisS and closely related reactions in the dynamic module, the number of required kinetic parameters is minimized

• System-Level Analysis: The static module can encompass broader metabolic networks connected to aminoacylation

• Perturbation Studies: Effects of hisS inhibition or mutation can be simulated throughout the metabolic network

• Enzyme Classification: The method can distinguish enzymes into static and dynamic modules based on metabolite concentration data

Implementation Methodology:
The practical implementation involves:

• Construction of a stoichiometric model of C. caviae metabolism

• Estimation of enzyme reaction rates from metabolite concentration time series data

• Discrimination of dynamic and static enzymes using computational optimization

• Integration of kinetic parameters for hisS and other dynamic module enzymes

• Simulation of system behavior under various conditions

Advantages for Broader Metabolic Research:
Beyond hisS studies, the HDS approach offers several benefits:

• Scalability: Can be applied to larger metabolic systems with numerous enzymes

• Tolerance to noise: The method performs well even with noisy metabolite data

• Adaptability: Can be applied to strictly regulated metabolic systems like central carbon metabolism

• Reduced experimental burden: Requires experimental determination of far fewer kinetic parameters

This modeling approach is particularly valuable for intracellular pathogens like Chlamydophila caviae, where experimental measurement of comprehensive kinetic parameters is challenging.