Recombinant Haemophilus somnus ATP synthase subunit c (atpE)

What is the structure and function of H. somnus ATP synthase subunit c (atpE)?

Haemophilus somnus ATP synthase subunit c (atpE) is an 84-amino acid protein component of the F0 sector of ATP synthase. The full-length protein (1-84aa) has the amino acid sequence: MENIITATIFGSVILLAVAALATAIGFSLLGGKFLESSARQPELAASLQTKMFIVAGLLDAISMIAVGIALLFIFANPFIGLLN . Functionally, it serves as a critical component of the ATP synthase complex, participating in the generation of ATP through proton translocation across the bacterial membrane.

To study the structure-function relationship, researchers typically employ protein structure prediction tools combined with site-directed mutagenesis of conserved residues to evaluate their impact on ATP synthesis activity. Circular dichroism spectroscopy and X-ray crystallography are recommended methodologies for structural analysis, while enzymatic activity assays provide functional insights .

How is recombinant H. somnus atpE protein typically expressed and purified?

Recombinant H. somnus ATP synthase subunit c (atpE) is commonly expressed using E. coli expression systems with an N-terminal histidine tag to facilitate purification . The standard methodology includes:

• Transformation of the atpE gene construct into an appropriate E. coli strain

• Induction of protein expression using IPTG in LB or specialized media

• Cell lysis through sonication or pressure-based methods

• Immobilized metal affinity chromatography (IMAC) for His-tagged protein purification

• Size exclusion chromatography for further purification if needed

• Lyophilization for stable storage

The purified protein typically appears as a single band of approximately 10 kDa on SDS-PAGE with purity >90% . For optimal stability, the protein should be reconstituted in deionized sterile water to a concentration of 0.1-1.0 mg/mL with 5-50% glycerol as a cryoprotectant before storage at -20°C/-80°C .

What role does atpE play in bacterial pathogenesis of Haemophilus somnus?

Haemophilus somnus (now classified as Histophilus somni) is a Gram-negative opportunistic pathogen associated with multisystemic diseases in bovines . While atpE itself has not been directly identified as a primary virulence factor, it functions within the context of energy metabolism that supports pathogenesis.

To investigate its potential role in pathogenesis, researchers should employ the following methodological approaches:

• Comparative transcriptomics between virulent and avirulent strains to assess differential expression of atpE

• Construction of atpE knockout mutants followed by virulence assays in appropriate model systems

• Evaluation of atpE expression under host-mimicking conditions (oxygen limitation, nutrient restriction)

• Assessment of antibody responses to atpE in infected animals to determine immunogenicity

The relationship between ATP synthesis efficiency and virulence can be assessed by measuring intracellular ATP levels during infection processes using luciferase-based assays .

How can researchers properly store and reconstitute recombinant H. somnus atpE protein?

For optimal research outcomes, proper storage and reconstitution of recombinant H. somnus atpE protein is critical. The recommended protocol includes:

For reconstitution:

• Briefly centrifuge the vial before opening to bring contents to the bottom

• Reconstitute in deionized sterile water to 0.1-1.0 mg/mL

• Add glycerol to a final concentration of 5-50% (50% is recommended for optimal stability)

• Aliquot to minimize freeze-thaw cycles

• Verify protein integrity post-reconstitution via SDS-PAGE if experimental outcomes are inconsistent

How can contradictory data on atpE structure-function relationships be resolved through experimental design?

When encountering conflicting data regarding the structure-function relationships of H. somnus atpE, researchers should implement a systematic contradiction analysis approach:

• Perform critical comparative analysis of experimental methodologies across studies, examining differences in:

  • Protein preparation methods (expression systems, purification protocols)

  • Buffer compositions and pH conditions

  • Analytical techniques used for structural determination

  • Activity assay conditions (temperature, substrate concentrations)

• Design validation experiments incorporating:

  • Multiple orthogonal structural analysis techniques (CD spectroscopy, NMR, X-ray crystallography)

  • Site-directed mutagenesis targeting specific residues with conflicting reports

  • Functional assays under standardized conditions with appropriate controls

  • In silico molecular dynamics simulations to reconcile structural discrepancies

• Implement quantitative meta-analytical techniques to identify experimental variables that may account for observed discrepancies.

This methodological framework enables researchers to systematically address contradictions and establish reproducible structure-function relationships for H. somnus atpE.

What strategies can effectively integrate genomic and proteomic data for comprehensive atpE analysis across Haemophilus species?

Effective integration of genomic and proteomic data for comprehensive atpE analysis requires a structured cross-disciplinary approach:

• Data Collection and Standardization:

  • Collect genomic sequences of atpE genes across multiple Haemophilus species and strains

  • Standardize proteomic datasets using consistent sample preparation protocols

  • Develop a unified data management plan specifying formats and metadata standards following FAIR principles

• Comparative Analysis Methodology:

  • Perform phylogenetic analysis of atpE sequences to establish evolutionary relationships

  • Apply multiple sequence alignment to identify conserved domains and species-specific variations

  • Use homology modeling to predict structural implications of sequence variations

  • Correlate proteomic expression data with genomic features

• Integration Platforms:

  • Implement knowledge graph approaches to map relationships between genomic variants and protein properties

  • Utilize machine learning algorithms to identify patterns across datasets

  • Develop visualization tools that simultaneously represent genomic and proteomic data

• Validation Methods:

  • Design targeted experiments to test predictions derived from integrated analyses

  • Use CRISPR-based genome editing to validate the functional significance of identified genomic features

  • Apply protein engineering to confirm structure-function predictions

This integrated approach facilitates the development of comprehensive models of atpE diversity and function across Haemophilus species.

How can atpE be utilized as a molecular diagnostic target for bacterial identification and what are the optimal primer design considerations?

The utilization of atpE as a molecular diagnostic target for bacterial identification requires careful consideration of primer design and optimization:

• Primer Design Methodology:

  • Target regions of atpE with sufficient species-specificity to distinguish from closely related bacteria

  • Optimal primer characteristics include:

    • Length between 18-24 nucleotides

    • G or C nucleotide at the 3' end to promote binding stability

    • Melting temperature around 54-60°C

    • GC content of 40-60%

    • Absence of secondary structures and primer-dimer formation potential

• Optimization Strategies:

  • Perform gradient PCR to determine optimal annealing temperatures

  • Evaluate different DNA extraction methods to maximize yield and purity

  • Test varying magnesium concentrations to optimize enzyme activity

  • Validate specificity against closely related bacterial species

• Clinical Application Considerations:

  • For diagnostic applications in clinical samples, primers with more than 24 bases demonstrated higher detection rates

  • Evaluate primers against clinical samples rather than laboratory strains only

  • Consider multiplex PCR approaches targeting atpE alongside other genetic markers for increased specificity

The validation results from a study using atpE primers designed with Thermo Fisher Scientific Oligo Primer design tools showed 100% detection rate against positive control bacterial DNA of Mycobacterium tuberculosis H37Rv, with 61.54% sensitivity and 100% specificity when applied to clinical samples .

What are the challenges and solutions for structural characterization of membrane-associated atpE protein?

Structural characterization of membrane-associated proteins like H. somnus atpE presents unique challenges requiring specialized approaches:

• Challenges:

  • Hydrophobic nature compromises solubility in aqueous buffers

  • Tendency to aggregate during purification

  • Conformational dynamics influenced by lipid environment

  • Difficulty in obtaining sufficient quantities for structural studies

• Methodological Solutions:

  • Detergent Screening:

    • Systematic evaluation of different detergent classes (non-ionic, zwitterionic)

    • Optimization of detergent concentration and protein-to-detergent ratios

    • Use of mild detergents like DDM or digitonin for initial solubilization

  • Membrane Mimetics:

    • Incorporation into nanodiscs with defined lipid composition

    • Reconstitution in liposomes for functional studies

    • Use of amphipols for stabilization in detergent-free environment

  • Advanced Structural Techniques:

    • Solid-state NMR for structure determination in native-like environments

    • Cryo-electron microscopy for visualization of protein complexes

    • X-ray crystallography with lipidic cubic phase for crystallization

• Quality Assessment Methods:

  • Circular dichroism to verify secondary structure integrity in different environments

  • Size-exclusion chromatography coupled with multi-angle light scattering (SEC-MALS) to assess oligomeric state

  • Thermal stability assays to optimize buffer conditions

Implementing these specialized approaches enables researchers to overcome the inherent challenges in structural characterization of membrane proteins like atpE.

What are the optimal conditions for functional assays of recombinant H. somnus atpE?

Designing robust functional assays for recombinant H. somnus atpE requires careful optimization of experimental conditions:

• Reconstitution in Proteoliposomes:

  • Prepare liposomes using E. coli polar lipid extract (70%) and phosphatidylcholine (30%)

  • Incorporate purified atpE at protein-to-lipid ratios between 1:50 and 1:200 (w/w)

  • Perform reconstitution through detergent removal using Bio-Beads or dialysis

  • Verify incorporation efficiency through sucrose gradient centrifugation

• Proton Translocation Assays:

  • Use pH-sensitive fluorescent dyes (e.g., ACMA or pyranine) to monitor proton movement

  • Establish a proton gradient using valinomycin-induced K⁺ diffusion

  • Measure fluorescence changes at excitation/emission wavelengths appropriate for the selected dye

  • Include appropriate controls with known proton channel inhibitors

• ATP Synthesis Measurements:

  • Reconstruct functional ATP synthase complex with purified subunits including atpE

  • Establish a proton motive force across the membrane

  • Quantify ATP production using luciferin/luciferase assays

  • Determine kinetic parameters under varying substrate concentrations and pH conditions

• Critical Parameters and Troubleshooting:

  • Temperature sensitivity: Perform assays at physiologically relevant temperatures (35-37°C)

  • Buffer composition: Optimize ionic strength and divalent cation concentrations

  • Protein orientation: Ensure correct orientation of atpE in the membrane

  • Signal-to-noise ratio: Adjust protein concentration and instrument sensitivity

These methodological guidelines provide a framework for rigorous functional characterization of recombinant H. somnus atpE.

How can researchers effectively design experiments to study atpE interactions with other ATP synthase subunits?

Investigating protein-protein interactions between atpE and other ATP synthase subunits requires a multifaceted experimental approach:

• In vitro Interaction Assays:

  • Co-immunoprecipitation using antibodies against atpE or interacting partners

  • Pull-down assays utilizing the His-tag on recombinant atpE

  • Surface plasmon resonance (SPR) to determine binding kinetics and affinities

  • Isothermal titration calorimetry (ITC) for thermodynamic characterization

• Crosslinking Strategies:

  • Chemical crosslinking with agents of varying spacer arm lengths

  • Photo-crosslinking for capturing transient interactions

  • Mass spectrometry analysis of crosslinked products to identify interaction interfaces

  • Distance constraints derived from crosslinking for structural modeling

• Fluorescence-based Approaches:

  • Förster resonance energy transfer (FRET) between fluorescently labeled subunits

  • Fluorescence correlation spectroscopy (FCS) to study interaction dynamics

  • Single-molecule fluorescence to observe conformational changes during interaction

• Genetic Approaches:

  • Bacterial two-hybrid screening to identify potential interaction partners

  • Suppressor mutation analysis to identify compensatory mutations

  • Site-directed mutagenesis targeting predicted interaction interfaces

• Computational Methods:

  • Molecular docking simulations to predict binding modes

  • Molecular dynamics simulations to assess stability of predicted complexes

  • Coevolution analysis to identify co-varying residues indicative of interaction

This comprehensive experimental design allows researchers to characterize the interaction network of H. somnus atpE within the ATP synthase complex, providing insights into assembly and function.

What methodologies can be employed to study the impact of mutations on atpE function and stability?

A systematic approach to studying the impact of mutations on atpE function and stability includes:

• Rational Mutation Selection:

  • Evolutionary conservation analysis across species to identify functionally important residues

  • Structural modeling to predict residues involved in protein-protein interactions or catalysis

  • Literature-based selection of residues previously implicated in function

  • Random mutagenesis approaches for unbiased screening

• Generation of Mutant Variants:

  • Site-directed mutagenesis using PCR-based techniques

  • Golden Gate assembly for multiple mutation introduction

  • CRISPR-Cas9 genome editing for chromosomal mutations in native context

  • Verification of mutations by DNA sequencing

• Stability Analysis:

  • Thermal shift assays to determine melting temperatures

  • Circular dichroism spectroscopy to assess secondary structure changes

  • Limited proteolysis to identify conformational changes

  • Aggregation propensity measurements using light scattering techniques

• Functional Characterization:

  • Proton translocation assays in reconstituted systems

  • ATP synthesis/hydrolysis measurements

  • Growth complementation in atpE-deficient strains

  • Ion binding studies using isothermal titration calorimetry or fluorescence spectroscopy

• Structure-Function Correlation:

  • Structural determination of key mutants using X-ray crystallography or cryo-EM

  • Molecular dynamics simulations to assess dynamic behavior changes

  • Hydrogen-deuterium exchange mass spectrometry to probe conformational dynamics

This comprehensive methodology enables researchers to establish causal relationships between specific amino acid residues and atpE function or stability, providing insights into the molecular mechanisms of ATP synthase operation.

How should researchers approach the analysis of conflicting data on atpE function across different bacterial species?

When confronted with conflicting data on atpE function across different bacterial species, researchers should implement a structured analytical framework:

• Systematic Literature Review:

  • Conduct a comprehensive search across multiple databases

  • Apply inclusion/exclusion criteria to ensure data quality

  • Extract methodological details that might explain discrepancies

  • Categorize findings based on experimental approaches and bacterial species

• Meta-analysis Approach:

  • Apply statistical methods to quantify the degree of heterogeneity in results

  • Perform sensitivity analyses to identify potential sources of variation

  • Use forest plots to visualize effect sizes across studies

  • Identify moderator variables that may explain inconsistent findings

• Comparative Sequence-Function Analysis:

  • Align atpE sequences from species with conflicting functional data

  • Identify sequence divergences that correlate with functional differences

  • Apply machine learning algorithms to detect patterns in sequence-function relationships

  • Generate testable hypotheses based on sequence-function correlations

• Experimental Validation Strategy:

  • Design experiments that directly address identified discrepancies

  • Use standardized protocols across different bacterial species

  • Perform head-to-head comparisons under identical conditions

  • Consider species-specific factors (growth conditions, membrane composition)

This systematic approach enables researchers to transcend mere recognition of conflicts and develop a coherent understanding of atpE function that accounts for species-specific variations.

What statistical approaches are most appropriate for analyzing atpE sequence conservation and variation?

Robust statistical analysis of atpE sequence conservation and variation requires a multi-layered approach:

• Conservation Analysis:

  • Calculate position-specific conservation scores using information theory-based methods

  • Apply evolutionary trace methods to map conservation patterns onto structural models

  • Identify differentially conserved regions between taxonomic groups

  • Statistical significance testing of conservation differences using permutation tests

• Coevolution Analysis:

  • Calculate mutual information between all pairs of positions to identify co-evolving residues

  • Apply direct coupling analysis to distinguish direct from indirect correlations

  • Conduct statistical coupling analysis to identify sectors of functionally linked residues

  • Validate predicted coevolving networks through mutation studies

• Selection Pressure Analysis:

  • Calculate dN/dS ratios to identify sites under positive or purifying selection

  • Apply likelihood ratio tests to assess statistical significance of selection

  • Implement branch-site models to detect episodic selection in specific lineages

  • Bayesian approaches to estimate posterior probabilities of selection

• Population Genetics Parameters:

  • Calculate nucleotide diversity (π) and Watterson's theta (θ)

  • Perform neutrality tests (Tajima's D, Fu and Li's F) to detect demographic events or selection

  • Apply McDonald-Kreitman test to compare polymorphism and divergence

  • Implement coalescent simulations to test evolutionary hypotheses

These statistical approaches provide a comprehensive framework for characterizing evolutionary patterns in atpE sequences, revealing functional constraints and adaptive changes across bacterial species.

What are the future research directions for Haemophilus somnus atpE studies?

The exploration of Haemophilus somnus atpE presents several promising research directions:

• Structural Biology Frontiers:

  • High-resolution structure determination of the complete H. somnus ATP synthase complex

  • Investigation of species-specific structural features that might relate to pathogenesis

  • Conformational dynamics studies during the catalytic cycle using advanced biophysical techniques

  • Structure-based drug design targeting unique features of H. somnus atpE

• Functional Genomics Approaches:

  • Comparative transcriptomic analysis of atpE expression under different growth conditions

  • Identification of regulatory networks controlling atpE expression

  • Genome-wide interaction screens to identify genetic modifiers of atpE function

  • Single-cell analysis to investigate heterogeneity in atpE expression during infection

• Host-Pathogen Interaction Studies:

  • Investigation of atpE as a potential immunogenic target

  • Analysis of host immune responses to atpE during infection

  • Evaluation of atpE contribution to bacterial survival in host environments

  • Development of atpE-based diagnostic tools for Haemophilus infection

• Therapeutic Applications:

  • Exploration of atpE as a novel antibiotic target

  • Development of inhibitors specific to H. somnus atpE

  • Investigation of atpE-based vaccine strategies

  • Exploitation of atpE for strain-specific detection in clinical samples

These future directions will expand our understanding of H. somnus atpE beyond its basic biochemical function, potentially leading to new diagnostic and therapeutic approaches for Haemophilus infections.

How can integrated -omics approaches enhance our understanding of atpE in bacterial physiology and pathogenesis?

Integrated -omics approaches offer powerful strategies to comprehensively understand atpE's role in bacterial physiology and pathogenesis:

• Multi-omics Data Collection:

  • Genomics: Whole-genome sequencing to identify atpE variants and genomic context

  • Transcriptomics: RNA-seq to profile expression patterns under diverse conditions

  • Proteomics: Mass spectrometry-based quantification of protein levels and post-translational modifications

  • Metabolomics: Analysis of metabolic profiles to assess the impact of atpE on energy metabolism

  • Interactomics: Protein-protein interaction mapping to define the atpE interactome

• Integration Methodologies:

  • Network biology approaches to construct integrated molecular networks

  • Bayesian integration methods to identify causal relationships between different data types

  • Machine learning algorithms to detect patterns across multi-omics datasets

  • Systems biology modeling to predict emergent properties from integrated data

• Experimental Validation Framework:

  • Hypothesis generation based on integrated data analysis

  • Targeted experiments to validate predictions from multi-omics integration

  • Iterative refinement of models based on experimental outcomes

  • Development of predictive models for bacterial behavior under different conditions

• Applications to Pathogenesis Research:

  • Identification of condition-specific atpE regulation during infection processes

  • Characterization of atpE contribution to metabolic adaptation in host environments

  • Discovery of potential interactions between atpE and host factors

  • Assessment of atpE as a biomarker for virulence potential or antibiotic resistance