Recombinant Streptococcus equi subsp. equi Elongation factor G (fusA), partial

What is the function of Elongation Factor G (EF-G) in Streptococcus equi?

Elongation Factor G (EF-G) in Streptococcus equi, like in other bacteria, plays crucial roles in two major steps of protein synthesis: translocation during elongation and ribosome recycling. During elongation, EF-G catalyzes the movement of tRNAs and mRNA through the ribosome after peptide bond formation, coupled with GTP hydrolysis . In the ribosome recycling phase, EF-G works in conjunction with ribosome recycling factor (RRF) to split the 70S ribosome into subunits following translation termination . Multiple rounds of RRF and EF-G action coupled with GTP hydrolysis are necessary for effective ribosome splitting . Disruption of either function can significantly impair bacterial protein synthesis, making EF-G an important target for understanding bacterial physiology and developing antimicrobial strategies.

How does the structure of EF-G relate to its function in bacterial translation?

EF-G possesses a multi-domain structure with functional domains that undergo conformational changes during the translation cycle. The protein contains distinct domains including the GTP-binding domain (domain I) and several other domains (II-V) that facilitate interactions with the ribosome . Critical residues at domain interfaces participate in interdomain communication necessary for proper function . The hydrophobic pocket between domains I, II, and III serves as the binding site for fusidic acid, an antibiotic that inhibits EF-G function .

The conformational dynamics of EF-G are essential for its function, as demonstrated by studies showing that mutations restricting these conformational changes impair translocation and ribosome recycling activities . In S. aureus, mutations at positions F88 and M16 affect protein flexibility and function, suggesting that corresponding residues in S. equi EF-G likely play similar critical roles in maintaining proper conformational dynamics required for translation activities .

What are the key differences between EF-G in Streptococcus equi and other bacterial species?

While the core function of EF-G is conserved across bacterial species, specific sequence variations exist between Streptococcus equi and other bacteria like Staphylococcus aureus or Thermus thermophilus. These differences may affect antibiotic sensitivity, catalytic efficiency, and interaction with species-specific ribosomal components.

For example, the F88L mutation in S. aureus EF-G corresponds to F90L in T. thermophilus, both conferring fusidic acid resistance but with potential differences in the degree of resistance or fitness effects . S. equi likely has its own equivalent position that would confer similar resistance if mutated. The conservation of functional domains across bacterial species suggests similar mechanisms of action, but species-specific variations in non-catalytic regions may influence protein stability, interaction with other translation factors, or regulatory mechanisms that have evolved to suit the particular ecological niche of S. equi as a horse pathogen.

What is the recommended expression system for producing recombinant S. equi EF-G?

For recombinant expression of S. equi subsp. equi EF-G, the Escherichia coli-based expression system using pET vectors is highly recommended based on successful approaches with similar proteins. Using E. coli strain ER2566 with the pTYB4 expression vector has proven effective for other S. equi proteins . This system allows for inducible expression using IPTG (isopropyl-β-d-thiogalactopyranoside) and can be optimized for high yield protein production .

The expression protocol should include:

• PCR amplification of the fusA gene from S. equi subsp. equi chromosomal DNA using specific primers containing appropriate restriction sites (e.g., NcoI and XhoI)

• Digestion of the PCR product and vector with the selected restriction enzymes

• Ligation of the digested PCR product into the expression vector

• Transformation into competent E. coli ER2566 cells

• Selection of transformants on appropriate antibiotic-containing media (e.g., ampicillin 100 μg/ml)

• Sequence verification of the cloned fusA gene

• Large-scale culture and induction with IPTG (typically 0.4-1 mM) at optimal temperature (usually 25-30°C to enhance solubility)

• Cell harvesting and protein purification using affinity chromatography based on the vector's tag system

For partial fusA constructs, careful design of the fragment boundaries based on domain structure analysis is crucial to ensure proper folding and function of the recombinant protein.

What purification strategies are most effective for obtaining active recombinant EF-G protein?

Purification of recombinant S. equi EF-G requires strategies that preserve the protein's native conformation and activity. Based on successful approaches with similar bacterial proteins, a multi-step purification protocol is recommended:

• Affinity Chromatography: Use of the IMPACT-T7 system with a chitin-binding domain fusion allows for single-step purification with on-column cleavage . Alternative affinity tags such as His6 can also be effective.

• Buffer Optimization: Throughout purification, maintain buffers containing:

  • 20-50 mM Tris-HCl or HEPES (pH 7.5-8.0)

  • 100-300 mM NaCl or KCl

  • 5-10% glycerol for stability

  • 1-5 mM DTT or β-mercaptoethanol to prevent oxidation

  • 1-5 mM MgCl₂ (essential for GTPase function)

• Sequential Chromatography: For highest purity, follow affinity chromatography with:

  • Ion exchange chromatography (typically Q-Sepharose)

  • Size exclusion chromatography for final polishing and buffer exchange

• Activity Preservation: Include steps to verify protein activity:

  • GTP binding assay

  • Ribosome-dependent GTPase activity test

  • Translocation efficiency measurements

Purification yield and activity assessment of recombinant S. equi EF-G can be tracked using the following table format:

Note that these values are estimates based on similar bacterial translation factors and actual yields may vary based on specific expression conditions and construct design.

How can one assess the functional activity of recombinant S. equi EF-G in vitro?

Assessing the functional activity of recombinant S. equi EF-G requires multiple complementary approaches that examine different aspects of its dual role in translation elongation and ribosome recycling:

• GTPase Activity Assay:

  • Measure GTP hydrolysis rates using [γ-³²P]GTP in the presence of ribosomes

  • Compare ribosome-dependent and ribosome-independent activities

  • Determine kinetic parameters (K​m and k​cat) for GTP hydrolysis

• Translocation Assays:

  • Pre-translocation complex formation with mRNA and fluorescently labeled tRNAs

  • Monitoring tRNA movement through FRET (Förster resonance energy transfer) changes

  • Quantifying translocation rates using stopped-flow kinetics

  • Measuring the effect of fusidic acid on translocation efficiency

• Ribosome Recycling Assays:

  • Formation of post-termination complexes

  • Measuring subunit dissociation rates in the presence of EF-G and RRF

  • Light scattering techniques to monitor ribosome splitting in real-time

• tRNA Drop-off Assessment:

  • Measuring premature release of tRNAs during elongation

  • Quantifying [³H]tRNA retention on ribosomes in elongation complexes

For comparative analysis, the following table illustrates typical functional parameters for wild-type versus mutant EF-G variants:

These assays collectively provide a comprehensive evaluation of EF-G function and can reveal specific defects associated with mutations or structural alterations.

What structural domains are present in S. equi EF-G and how do they contribute to function?

S. equi Elongation Factor G contains five distinct structural domains (I-V) that work in concert to facilitate its functions in translation. Based on homology with other bacterial EF-G proteins:

• Domain I (G Domain): Contains the GTP-binding and hydrolysis machinery, including the conserved switch I and II regions critical for nucleotide sensing . This domain undergoes significant conformational changes upon GTP binding and hydrolysis.

• Domain II: Forms part of the hydrophobic pocket involved in fusidic acid binding along with domains I and III . It participates in ribosomal interactions and contributes to the power stroke mechanism during translocation.

• Domain III: Creates part of the interdomain pocket and interfaces with domain V during conformational changes that drive translocation .

• Domain IV: The most extended domain that mimics the anticodon arm of tRNA, crucial for maintaining reading frame during translocation by interacting with the decoding center of the small ribosomal subunit.

• Domain V: Interacts with the L11 stalk of the large ribosomal subunit and contributes to factor binding and GTPase activation.

The cooperative action of these domains enables EF-G to coordinate GTP hydrolysis with the mechanical work of translocation and ribosome recycling, making the interdomain communication networks essential for proper translation.

What are the known fusidic acid resistance mutations in EF-G and their effects on protein function?

Fusidic acid (FA) resistance mutations in EF-G have been well-characterized in several bacterial species and provide valuable insights for understanding potential resistance mechanisms in S. equi. From studies in S. aureus and other bacteria, we know that:

• Primary Resistance Mutations:

  • F88L (S. aureus): A primary mutation causing high-level FA resistance but significant fitness cost

  • This corresponds to F90L in Thermus thermophilus, suggesting evolutionary conservation of this resistance mechanism

  • Equivalent positions likely exist in S. equi EF-G

• Compensatory Mutations:

  • M16I/V: Secondary mutations that compensate for fitness loss in F88L mutants while maintaining resistance

  • These mutations restore protein function without reverting drug resistance

• Molecular Mechanism:

  • FA binds to a hydrophobic pocket between domains I, II, and III in the post-translocation state

  • Resistance mutations alter this binding pocket or affect conformational dynamics that prevent FA trapping

  • Most resistance mutations are located at domain interfaces, disrupting the FA binding site

• Functional Consequences:

  • Resistant mutants typically show:

    • Decreased translocation rates

    • Reduced ribosome recycling efficiency

    • Increased tRNA drop-off during elongation

    • Altered GTP hydrolysis kinetics

The following table summarizes the functional effects of different EF-G variants, based on data from S. aureus that would likely parallel effects in S. equi:

Understanding these mutations provides insights into both antibiotic resistance mechanisms and the fundamental structure-function relationships in EF-G that are crucial for bacterial protein synthesis and fitness.

How do conformational dynamics of EF-G affect its function and how can these be investigated?

The conformational dynamics of EF-G are crucial for its proper function in translation, with different conformations required for binding to the ribosome, catalyzing translocation, and facilitating ribosome recycling . Understanding these dynamics requires sophisticated experimental approaches:

• X-ray Crystallography:

  • Captures distinct structural states of EF-G

  • Reveals domain arrangements in different nucleotide-bound states (GTP vs. GDP)

  • Identifies key residues at domain interfaces that mediate conformational changes

  • Limitations: provides static snapshots rather than dynamic information

• Cryo-Electron Microscopy (Cryo-EM):

  • Visualizes EF-G bound to ribosomes in different functional states

  • Captures intermediate conformations during translocation

  • Reveals large-scale conformational changes during the translation cycle

  • Advantage: minimal sample perturbation and visualization in near-native state

• Fluorescence Resonance Energy Transfer (FRET):

  • Real-time monitoring of domain movements during function

  • Requires strategic placement of fluorophore pairs on different domains

  • Measures distances between domains during various steps of translation

  • Provides kinetic information about conformational changes

• Molecular Dynamics Simulations:

  • Computational prediction of conformational flexibility and domain movements

  • Identifies potential communication pathways between distant protein regions

  • Models effects of mutations on protein dynamics

  • Complements experimental approaches with atomistic detail

Research with S. aureus EF-G has demonstrated that mutations like F88L restrict conformational changes necessary for proper function, leading to slower translocation and ribosome recycling . The double mutant F88L/M16I partially restores these conformational dynamics, explaining the fitness compensation observed .

For S. equi EF-G, these approaches would reveal how species-specific variations influence protein dynamics and function. Key investigations would focus on:

• Domain movements during GTP hydrolysis

• Conformational changes upon ribosome binding

• Effect of fusidic acid on trapping specific conformations

• Impact of resistance mutations on protein flexibility and function

These studies would not only advance our understanding of bacterial translation but also inform the development of novel antibiotics targeting EF-G in Streptococcus equi.

How can recombinant S. equi EF-G be used to study strangles pathogenesis?

Recombinant S. equi EF-G can serve as a valuable tool for investigating strangles pathogenesis through several research applications:

• Protein-Specific Antibody Production:

  • Generate antibodies against S. equi EF-G for detection and localization studies

  • Use antibodies to track protein expression levels during infection phases

  • Develop immunohistochemistry protocols to visualize bacterial distribution in tissues

• Bacterial Fitness Assessment:

  • Compare wild-type and mutant EF-G variants in growth competition assays

  • Evaluate how translation efficiency affects bacterial survival in host environments

  • Determine if EF-G variants affect virulence factor expression

• Host-Pathogen Interaction Studies:

  • Investigate potential interactions between bacterial EF-G and host immune components

  • Determine if EF-G contributes to immune evasion through moonlighting functions

  • Assess if antibodies against EF-G provide any protective immunity

• Translational Inhibitor Development:

  • Screen for S. equi-specific EF-G inhibitors that could serve as novel therapeutics

  • Design peptide inhibitors based on structural knowledge of S. equi EF-G

  • Test inhibitor efficacy in infection models

For these applications, the recombinant protein expression systems used for other S. equi proteins can be adapted . The murine model of S. equi infection, which has been used successfully to test protective efficacy of other recombinant proteins , could be employed to assess the role of EF-G in pathogenesis and evaluate potential therapeutic approaches targeting this essential factor.

What are the methodological challenges in comparing wild-type and mutant S. equi EF-G proteins?

Comparing wild-type and mutant S. equi EF-G proteins presents several methodological challenges that researchers must address to obtain reliable and physiologically relevant data:

• Protein Expression and Purification Consistency:

  • Mutations may affect protein folding, stability, or expression levels

  • Challenge: Ensuring equal purity and structural integrity across variants

  • Solution: Use multiple purification steps and validate protein structure via circular dichroism or limited proteolysis

• Functional Assay Design:

  • EF-G functions in multiple translation steps (elongation and recycling)

  • Challenge: Designing assays that distinguish specific functional defects

  • Solution: Develop separate assays for GTPase activity, translocation, and ribosome recycling

• In vitro vs. In vivo Correlation:

  • Biochemical defects may not directly translate to growth phenotypes

  • Challenge: Connecting molecular mechanism to bacterial fitness

  • Solution: Complement biochemical assays with growth competition experiments and in vivo infection models

• Ribosome Source Considerations:

  • EF-G interacts with species-specific ribosomes

  • Challenge: Obtaining sufficient quantities of S. equi ribosomes for assays

  • Solution: Compare activity with both homologous (S. equi) and heterologous (E. coli) ribosomes to assess specificity

• Kinetic vs. Equilibrium Measurements:

  • Mutations often affect rates rather than binding affinities

  • Challenge: Capturing transient states and rate-limiting steps

  • Solution: Employ rapid kinetics approaches (stopped-flow, quench-flow) rather than equilibrium binding assays

A systematic approach to these challenges would include standardized protocols for:

• Protein expression conditions

• Multi-step purification procedures

• Consistent buffer compositions across experiments

• Parallel processing of wild-type and mutant proteins

• Multiple complementary assays to verify findings

These methodological considerations are essential for accurately characterizing the molecular consequences of mutations in S. equi EF-G and their potential impact on bacterial physiology and pathogenesis.

How do experimental conditions affect the function of recombinant S. equi EF-G in translational assays?

The function of recombinant S. equi EF-G in translational assays is significantly influenced by experimental conditions, which must be carefully controlled to obtain reliable and physiologically relevant results:

• Buffer Composition Effects:

  • GTP and Mg²⁺ concentrations: GTPase activity of EF-G requires optimal Mg²⁺:GTP ratios

  • Monovalent ions (K⁺, NH₄⁺): Affect ribosome conformation and factor binding

  • pH: Optimal range 7.4-7.8 for most translational activities

  • Polyamines (spermidine, putrescine): Modulate ribosome-factor interactions

• Temperature Considerations:

  • S. equi grows optimally at 30-37°C

  • Assay temperature affects both reaction rates and conformational dynamics

  • Temperature sensitivity may differ between wild-type and mutant proteins

• Component Ratios and Concentrations:

  • EF-G:ribosome ratios influence measured rates

  • Excess of other translation factors can compensate for EF-G deficiencies

  • Ribosome concentration affects apparent kinetic parameters

• Ribosome Source and Purity:

  • Homologous vs. heterologous ribosomes may interact differently with S. equi EF-G

  • Ribosomal subpopulations (e.g., 70S vs. polyribosomes) have different activities

  • Contaminants in ribosome preparations can affect measured activities

The following table illustrates how varying experimental conditions can affect key parameters of EF-G function:

For comparative studies between wild-type and mutant EF-G variants, maintaining identical conditions is crucial, as mutations may alter the optimal parameters for function. Additionally, time-course experiments rather than endpoint measurements provide more reliable data about the kinetic consequences of mutations, particularly those affecting conformational dynamics like the F88L mutation identified in S. aureus EF-G .

How can structural information about S. equi EF-G inform the design of species-specific translation inhibitors?

Structural information about S. equi EF-G can guide the rational design of species-specific translation inhibitors through several targeted approaches:

• Unique Binding Pocket Identification:

  • Compare crystal structures of S. equi EF-G with those from other bacterial species

  • Identify unique pockets or surface features specific to S. equi EF-G

  • Target these regions for selective inhibitor design

• Structure-Based Drug Design:

  • Utilize the known fusidic acid binding pocket between domains I, II, and III

  • Design modified fusidic acid derivatives with enhanced specificity for S. equi EF-G

  • Focus on interactions with residues that differ between S. equi and other bacteria

• Interdomain Interface Targeting:

  • Exploit knowledge of critical residues at domain interfaces, such as the equivalent of F88 and M16 in S. aureus

  • Design compounds that lock EF-G in specific conformations, preventing necessary structural changes

  • Target the communication pathways between GTP hydrolysis site and functional domains

• Species-Specific Ribosome-EF-G Interaction Inhibition:

  • Identify contact points between S. equi EF-G and S. equi ribosomes

  • Design peptides or small molecules that interfere with these species-specific interactions

  • Focus on disrupting transient interactions that occur during dynamic processes

• Allosteric Inhibitor Development:

  • Target allosteric sites that regulate EF-G conformational dynamics

  • Design inhibitors that bind distant from the active site but influence function

  • Focus on sites that affect domain movements critical for translocation or recycling

The following data table illustrates potential drug discovery parameters for targeting S. equi EF-G:

This structure-based approach could yield inhibitors with high specificity for S. equi, potentially providing targeted therapeutics for strangles with minimal impact on beneficial microbiota.

What techniques can be used to analyze the in vivo dynamics of EF-G in S. equi during infection?

Analyzing the in vivo dynamics of EF-G in S. equi during infection requires sophisticated approaches that can monitor protein expression, localization, and function in the context of host-pathogen interactions:

• Transcriptomic and Proteomic Approaches:

  • RNA-Seq to monitor fusA gene expression levels during different infection stages

  • Ribosome profiling to analyze translation efficiency of EF-G and dependent proteins

  • Proteomics to quantify EF-G abundance relative to other translation factors

  • Post-translational modification analysis to identify regulatory mechanisms

• Fluorescent Protein Tagging and Microscopy:

  • Generate S. equi strains expressing fluorescently tagged EF-G (e.g., mCherry-EF-G fusion)

  • Use fluorescence microscopy to track localization in bacterial cells during infection

  • Employ FRAP (Fluorescence Recovery After Photobleaching) to measure protein mobility

  • Apply super-resolution microscopy to visualize association with ribosomes

• Reporter Systems:

  • Develop translational efficiency reporters dependent on EF-G function

  • Create biosensors that respond to changes in EF-G activity

  • Use dual-luciferase systems to normalize for cell number and metabolic state

• In vivo Crosslinking and Interaction Studies:

  • Apply in vivo crosslinking to capture transient EF-G interactions

  • Perform immunoprecipitation followed by mass spectrometry to identify interaction partners

  • Use proximity labeling methods (BioID, APEX) to map the EF-G interactome during infection

• Animal Models and Tissue Analysis:

  • Employ the mouse model of S. equi infection used in previous studies

  • Perform immunohistochemistry using anti-EF-G antibodies in infected tissues

  • Recover bacteria from infection sites and analyze EF-G expression/mutations

The following experimental design table outlines a comprehensive approach for tracking EF-G dynamics during infection:

These approaches would provide unprecedented insights into how EF-G function contributes to S. equi pathogenesis, potentially revealing new therapeutic targets or mechanisms of bacterial adaptation during infection.

How does S. equi EF-G compare to homologous proteins in related streptococcal species in terms of structure and function?

Comparative analysis of S. equi EF-G with homologous proteins from related streptococcal species reveals important insights into evolutionary conservation, functional specialization, and species-specific adaptations:

The following comparative table illustrates potential differences between S. equi EF-G and related streptococcal species:

Understanding these comparative aspects provides valuable insights for:

• Predicting antibiotic resistance mechanisms across species

• Developing species-selective translation inhibitors

• Understanding host adaptation mechanisms

• Interpreting the evolutionary history of streptococcal translation machinery

Experimental approaches combining structural biology, biochemistry, and comparative genomics would be essential to fully characterize these differences and their functional implications.

What are promising research directions for developing EF-G-targeted therapeutics against S. equi infections?

Several promising research directions exist for developing EF-G-targeted therapeutics against S. equi infections, combining structural insights, novel drug delivery approaches, and mechanism-based inhibitor design:

• Structure-Based Drug Design:

  • Solve high-resolution crystal structures of S. equi EF-G in multiple conformational states

  • Perform virtual screening of compound libraries against identified binding pockets

  • Develop fragment-based approaches targeting unique features of S. equi EF-G

  • Focus on compounds that trap EF-G in non-productive conformations

• Fusidic Acid Derivatives:

  • Synthesize fusidic acid analogs with enhanced specificity for S. equi EF-G

  • Target the hydrophobic pocket between domains I, II, and III

  • Design modifications that remain effective against known resistance mutations

  • Develop combination approaches targeting multiple binding sites simultaneously

• Peptide-Based Inhibitors:

  • Design peptides mimicking ribosomal binding interfaces of EF-G

  • Create stapled peptides that disrupt essential EF-G-ribosome interactions

  • Develop cell-penetrating peptides targeting intracellular EF-G

  • Focus on sequences unique to S. equi for specificity

• Novel Delivery Approaches:

  • Develop nanoparticle formulations for targeted delivery to infection sites

  • Create prodrug approaches for enhanced penetration of the bacterial cell envelope

  • Explore bacteriophage-based delivery systems specific for S. equi

  • Design formulations appropriate for respiratory tract delivery (relevant to strangles)

• Combination Therapeutic Strategies:

  • Identify synergistic combinations targeting multiple translation factors

  • Combine EF-G inhibitors with compounds affecting other steps of bacterial protein synthesis

  • Develop dual-action molecules affecting both EF-G and ribosome function

  • Explore combinations with immune modulators to enhance host response

Research priorities should be ranked according to:

• Likelihood of developing S. equi-specific inhibitors (highest priority)

• Potential to overcome existing resistance mechanisms

• Feasibility of appropriate formulation for respiratory infections

• Potential for minimal impact on commensal flora

These approaches would benefit from collaborations between structural biologists, medicinal chemists, microbiologists, and veterinary scientists to ensure development of clinically relevant therapeutics for strangles.

How might CRISPR-Cas9 technology be applied to study EF-G function in S. equi?

CRISPR-Cas9 technology offers powerful approaches for studying EF-G function in S. equi, enabling precise genetic manipulation to answer fundamental questions about this essential protein:

• Gene Editing Applications:

  • Create point mutations in the native fusA gene to study structure-function relationships

  • Generate S. equi strains carrying known fusidic acid resistance mutations (e.g., F88L equivalent)

  • Introduce compensatory mutations (e.g., M16I equivalent) to study fitness compensation mechanisms

  • Create domain swaps between S. equi and related species to identify species-specific functional regions

• Gene Expression Modulation:

  • Develop CRISPRi systems to create tunable knockdown of EF-G expression

  • Study effects of reduced EF-G levels on growth, virulence, and stress responses

  • Create CRISPR activation (CRISPRa) systems to upregulate EF-G expression

  • Assess consequences of altered EF-G:ribosome ratios on translation fidelity and efficiency

• Protein Tagging Strategies:

  • Introduce fluorescent protein tags at the genomic locus for live-cell imaging

  • Create epitope tags for immunoprecipitation and interaction studies

  • Generate split-protein complementation systems to study EF-G dimerization or interactions

  • Develop biosensor fusions to monitor EF-G conformational states in vivo

• High-Throughput Screening Approaches:

  • Create CRISPR-based libraries of fusA variants for fitness screening

  • Identify novel functional residues through deep mutational scanning

  • Screen for mutations affecting antibiotic susceptibility or virulence

  • Develop reporter systems coupled to EF-G function for compound screening

The implementation of CRISPR-Cas9 technology in S. equi requires optimization of several parameters, as outlined in this methodological table:

CRISPR-based approaches would enable unprecedented insights into EF-G function, potentially revealing:

• Essential vs. non-essential regions of the protein

• Species-specific adaptations in S. equi EF-G

• Novel resistance mechanisms and their fitness consequences

• Regulatory networks controlling translation in response to stress

These studies would significantly advance our understanding of bacterial translation in this important equine pathogen.

What insights might systems biology approaches provide about the role of EF-G in S. equi pathogenesis?

Systems biology approaches can provide comprehensive insights into the role of EF-G in S. equi pathogenesis by integrating multiple layers of biological information:

• Multi-Omics Integration:

  • Combine transcriptomics, proteomics, and metabolomics data to create a holistic view of EF-G's impact

  • Identify correlations between EF-G expression/activity and virulence factor production

  • Map metabolic shifts associated with altered translation efficiency due to EF-G mutations

  • Reveal regulatory networks connecting translation to pathogenesis pathways

• Network Analysis:

  • Construct protein-protein interaction networks centered on EF-G

  • Identify hub proteins connecting translation to virulence mechanisms

  • Map signaling pathways affected by translation stress

  • Reveal indirect effects of EF-G perturbation on cellular physiology

• Genome-Scale Models:

  • Develop constraint-based models of S. equi metabolism incorporating translation costs

  • Simulate effects of altered EF-G function on cellular resource allocation

  • Predict metabolic vulnerabilities in fusA mutants

  • Model growth and virulence factor production under various conditions

• Host-Pathogen Interface Analysis:

  • Integrate bacterial and host transcriptomics during infection

  • Identify host responses specific to S. equi with altered EF-G function

  • Map the temporal dynamics of translation-dependent virulence factor expression

  • Create predictive models of infection outcomes based on translation efficiency

• Comparative Systems Analysis:

  • Compare system-wide effects of EF-G perturbation across different streptococcal species

  • Identify conserved and species-specific responses to translation stress

  • Reveal evolutionary adaptations in translation-virulence coupling

The following data integration scheme illustrates how systems biology approaches can connect EF-G function to pathogenesis:

These systems approaches would provide several key insights:

• Identification of virulence factors most sensitive to translation efficiency

• Discovery of novel regulatory connections between translation and pathogenesis

• Understanding of compensatory mechanisms activated during translation stress

• Prediction of therapeutic targets with maximal impact on pathogenesis

By mapping the complex relationship between EF-G function and the broader pathogenesis network, systems biology approaches could reveal novel intervention points for controlling strangles and related streptococcal infections.