Recombinant Desulfovibrio vulgaris Chaperone protein htpG (htpG), partial

What is the primary function of HtpG in Desulfovibrio vulgaris?

HtpG (high temperature protein G) in D. vulgaris functions as a molecular chaperone involved in protein folding and quality control. Similar to homologs in other bacterial species, D. vulgaris HtpG likely assists in proper folding of nascent polypeptides and refolding of denatured proteins. Based on studies of HtpG in other bacteria, it serves as a metal-dependent ATPase with chaperonin activity that contributes to maintaining proteostasis, particularly under stress conditions . The protein likely helps D. vulgaris adapt to environmental stresses by preventing protein aggregation and facilitating proper protein folding.

What experimental systems are appropriate for studying recombinant D. vulgaris HtpG function?

To study recombinant D. vulgaris HtpG function, researchers can employ:

• In vitro protein refolding assays: Using denatured model substrates like firefly luciferase to assess chaperone activity, as demonstrated with mHtpG. Thermal denaturation can render luciferase soluble but inactive, and recovery of activity can be measured upon incubation with purified recombinant HtpG .

• ATPase activity assays: Testing metal dependency of ATPase function using various metal ions and chelating agents.

• Bacterial two-hybrid systems: For investigating protein-protein interactions between HtpG and potential cochaperones or client proteins, similar to methods used to study E. coli HtpG interactions with DnaA .

• Mutant strain analysis: Creating and characterizing ΔhtpG mutants to assess physiological roles and compensatory mechanisms, as has been done with M. tuberculosis .

How does D. vulgaris HtpG potentially interact with the DnaK-DnaJ-GrpE (KJE) chaperone system?

Research on M. tuberculosis HtpG demonstrates that mHtpG works cooperatively with the KJE chaperone system, primarily through direct interaction with the cochaperone DnaJ2 . For D. vulgaris HtpG, researchers should investigate:

• Direct protein-protein interactions: Using co-immunoprecipitation, bacterial two-hybrid systems, or surface plasmon resonance to detect and characterize interactions between D. vulgaris HtpG and components of the KJE system, particularly DnaJ homologs.

• Functional cooperation: Employing in vitro protein refolding assays with combinations of purified D. vulgaris HtpG and KJE components at varying concentrations. For example, with mHtpG, researchers observed that addition of mHtpG stimulates luciferase folding by KJE in a progressive manner, with approximately 100% increase in refolding when mHtpG is present with the KJE system containing 20 μM DnaK .

• Quantitative proteomics analysis: Investigating expression changes in KJE components and other chaperones in ΔhtpG D. vulgaris mutants to identify potential compensatory mechanisms, similar to the iTRAQ-based approach used with M. tuberculosis that revealed increased expression of DnaJ1, DnaJ2, ClpX, and ClpC1 in the absence of HtpG .

What is the metal dependency profile of D. vulgaris HtpG's ATPase activity, and how does this compare to HtpG from other bacterial species?

D. vulgaris HtpG likely exhibits metal-dependent ATPase activity similar to mHtpG. To characterize this:

• Metal specificity assays: Test ATPase activity with various metal ions (Mg²⁺, Mn²⁺, Ca²⁺, Zn²⁺) at different concentrations to determine optimal cofactors.

• Inhibition studies: Use metal chelators like EDTA to confirm metal dependency and identify critical concentration thresholds.

• Site-directed mutagenesis: Target predicted metal-binding residues in D. vulgaris HtpG to confirm their role in metal coordination and ATPase function.

• Comparative analysis: Direct comparison with HtpG from M. tuberculosis, E. coli, and other species to elucidate evolutionary adaptations in metal utilization. This is particularly relevant given D. vulgaris' role as a sulfate-reducing bacterium with specialized metal homeostasis mechanisms .

How does the absence of HtpG affect the global proteome of D. vulgaris, particularly under stress conditions?

Based on studies with M. tuberculosis, deletion of htpG leads to significant alterations in protein expression profiles . For D. vulgaris, researchers should:

• Quantitative proteomics approaches: Implement iTRAQ or TMT-based quantitative proteomics to compare wild-type and ΔhtpG D. vulgaris strains under various stress conditions (heat, oxidative stress, nutrient limitation). In M. tuberculosis, 1,172 proteins were identified across biological replicates, with 76 proteins downregulated and 127 upregulated in the ΔhtpG strain .

• Functional categorization: Classify differentially expressed proteins into functional categories (metabolism, cell wall processes, information pathways, etc.) to identify biological processes most affected by HtpG absence.

• Temporal proteome dynamics: Examine proteome changes at different time points after stress exposure to understand the kinetics of compensatory responses.

• Targeted validation: Confirm key proteomics findings with Western blotting for selected proteins, particularly other chaperones and proteases that may be upregulated as compensatory mechanisms.

What are the optimal conditions for expressing and purifying recombinant D. vulgaris HtpG?

For efficient expression and purification of recombinant D. vulgaris HtpG:

• Expression systems:

  • E. coli BL21(DE3) with pET-based vectors is generally suitable for recombinant HtpG expression

  • Consider codon optimization for D. vulgaris sequences

  • Testing multiple fusion tags (His6, GST, MBP) to identify optimal solubility and activity

• Expression conditions:

  • IPTG concentration: 0.1-1.0 mM

  • Induction temperature: 16-30°C (lower temperatures often improve solubility)

  • Induction duration: 4-18 hours

  • Media supplementation with metal ions (Mg²⁺, Mn²⁺) that support proper folding

• Purification strategy:

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

  • Ion exchange chromatography as a secondary purification step

  • Size exclusion chromatography to ensure proper oligomeric state (typically dimeric)

  • Buffer optimization to maintain stability and activity (typically 20-50 mM Tris-HCl, pH 7.5-8.0, 100-300 mM NaCl, 5-10% glycerol, 1-5 mM DTT)

How should researchers design knockout and complementation experiments for D. vulgaris htpG?

Based on approaches used with M. tuberculosis , researchers should:

• Knockout construction:

  • Consider specialized transduction approaches similar to those used for M. tuberculosis

  • Design primers to amplify ~800 bp flanking regions of D. vulgaris htpG

  • Clone these regions into a suitable vector flanking an antibiotic resistance marker

  • Confirm deletion by PCR, Southern blotting, and Western blotting

• Complementation strategy:

  • Clone the full-length htpG gene with its native promoter into an integrative or replicative vector

  • Include epitope tags if needed for detection while ensuring they don't interfere with function

  • Confirm expression in the complemented strain via Western blotting

• Phenotypic characterization:

  • Compare growth rates of wild-type, ΔhtpG, and complemented strains under standard and stress conditions

  • Assess protein aggregation levels using aggregation-sensitive reporter systems

  • Measure survival rates following exposure to various stressors

• Controls and validation:

  • Include vector-only controls for complementation

  • Verify that phenotypic changes in the knockout are specifically due to htpG deletion by successful restoration in the complemented strain

How should researchers interpret contradictory findings between in vitro and in vivo studies of D. vulgaris HtpG function?

When faced with contradictory results between in vitro and in vivo experiments:

• Contextual factors assessment:

  • Evaluate differences in experimental conditions (pH, salt concentration, presence of cofactors)

  • Consider the complexity of the cellular environment versus purified systems

  • Assess potential redundancy with other chaperone systems that may mask effects in vivo

• Methodological reconciliation approaches:

  • Implement in vivo crosslinking to capture transient interactions

  • Develop cell-free extracts that better mimic the cellular environment while allowing biochemical manipulation

  • Use proximity labeling approaches to identify the in vivo interactome of HtpG

• Integration framework:

  • Develop models that incorporate both in vitro biochemical activities and in vivo physiological contexts

  • Consider that in vitro studies may reveal mechanistic potential that is regulated or modulated in vivo

As noted with M. tuberculosis HtpG, while certain functions occur in vitro without other proteins, involvement of cochaperones in vivo cannot be ruled out and requires further investigation .

What statistical approaches are most appropriate for analyzing quantitative data from D. vulgaris HtpG functional assays?

For robust statistical analysis of HtpG functional data:

• For enzymatic activity assays (ATPase activity, protein refolding):

  • Employ Michaelis-Menten kinetics analysis to determine Km and Vmax

  • Use nonlinear regression models for dose-response relationships

  • Apply multiple comparisons correction (Bonferroni or FDR) when testing multiple conditions

• For proteomics data:

  • Implement stringent fold-change thresholds (e.g., ≤0.55-fold for downregulation, ≥1.83-fold for upregulation) with appropriate P-value cutoffs (P ≤ 0.05) as used in M. tuberculosis studies

  • Apply normalization techniques appropriate for the specific proteomics platform

  • Consider both statistical significance and biological relevance when interpreting results

• For growth and stress response data:

  • Use repeated measures ANOVA for time-course experiments

  • Apply survival analysis methods (Kaplan-Meier, Cox proportional hazards) for stress resistance studies

  • Include adequate biological and technical replicates (minimum n=3 for each)

How does D. vulgaris HtpG function compare to HtpG in pathogenic bacteria like M. tuberculosis?

Comparative analysis should focus on:

• Structural comparisons:

  • Sequence alignment and phylogenetic analysis of HtpG across species

  • Structural modeling to identify conserved and divergent regions

  • Analysis of metal-binding sites and their conservation

• Functional conservation:

  • Compare ATPase activities and metal dependencies

  • Assess interaction profiles with KJE system components

  • Evaluate substrate specificity differences

• Physiological impact:

  • Compare growth defects in ΔhtpG mutants under various stress conditions

  • Analyze differential expression patterns in response to htpG deletion

  • Assess differences in stress response mechanisms

M. tuberculosis HtpG exhibits metal-dependent ATPase activity and associates with the KJE system through DnaJ2 . Deletion of htpG in M. tuberculosis leads to compensatory upregulation of DnaJ1, DnaJ2, ClpX, and ClpC1 . These findings provide a valuable framework for investigating whether similar mechanisms exist in D. vulgaris.

What is the evolutionary significance of HtpG conservation among sulfate-reducing bacteria like D. vulgaris?

Evolutionary analysis should consider:

• Phylogenetic distribution:

  • Construct comprehensive phylogenetic trees of HtpG across diverse bacterial species

  • Analyze conservation patterns in relation to metabolic capabilities (particularly sulfate reduction)

  • Assess correlation between environmental niche and HtpG sequence features

• Adaptive significance:

  • Investigate whether specific features of D. vulgaris HtpG relate to adaptation to sulfate-reducing lifestyle

  • Analyze conservation of metal-binding residues in relation to metal availability in typical D. vulgaris habitats

  • Examine selective pressure (dN/dS ratios) on htpG genes across sulfate-reducing bacteria

• Functional implications:

  • Consider whether HtpG in sulfate-reducing bacteria has evolved specialized functions related to protection of sulfur metabolism enzymes

  • Explore potential roles in managing oxidative stress associated with sulfate reduction

What are the promising approaches for investigating D. vulgaris HtpG's role in microbial community interactions?

Future research should explore:

• Microbiome context:

  • Examine D. vulgaris HtpG expression in polymicrobial communities versus pure culture

  • Investigate whether HtpG influences D. vulgaris interactions with other microbes

  • Assess the impact of D. vulgaris ΔhtpG mutants on community composition in relevant environments

• Host-microbe interactions:

  • Study the role of HtpG in D. vulgaris interactions with host cells, particularly in contexts like ulcerative colitis where Desulfovibrio has been implicated

  • Investigate whether HtpG influences the immunostimulatory properties of D. vulgaris

  • Examine potential connections between HtpG and flagellin expression, considering the importance of D. vulgaris flagellin in interactions with host LRRC19 receptors

• Environmental adaptation:

  • Explore HtpG's role in D. vulgaris adaptation to changing environmental conditions, particularly in microbiomes

  • Investigate stress response coordination between D. vulgaris and other community members

How might CRISPR-Cas9 gene editing approaches enhance research on D. vulgaris HtpG?

CRISPR-Cas9 technology offers several advantages for D. vulgaris HtpG research:

• Precise genetic manipulation:

  • Creation of point mutations in metal-binding residues or interaction domains

  • Introduction of domain swaps between HtpG of different species

  • Generation of truncated variants to assess domain-specific functions

• Regulatory studies:

  • Engineering of inducible or repressible htpG expression systems

  • Creation of reporter fusions to monitor htpG expression under various conditions

  • Modification of promoter elements to investigate transcriptional regulation

• High-throughput approaches:

  • CRISPR interference (CRISPRi) screens to identify genetic interactions with htpG

  • CRISPR activation (CRISPRa) to enhance htpG expression under specific conditions

  • CRISPR-based imaging to track HtpG localization in living cells

• Methodological considerations:

  • Optimization of Cas9 delivery methods for D. vulgaris

  • Design of appropriate guide RNAs with minimal off-target effects

  • Development of selection strategies for successful transformants