KEGG: cvi:CV_3336
STRING: 243365.CV_3336
CV_3336 belongs to the UPF0042 family of nucleotide-binding proteins found in C. violaceum. These proteins are characterized by their ability to bind nucleotides and are often conserved across different bacterial species. While the specific function of CV_3336 remains to be fully elucidated, it shares structural similarities with other UPF0042 family proteins that may be involved in nucleotide metabolism or signaling pathways .
The protein is encoded by the CV_3336 gene in the C. violaceum genome (ATCC12472 strain). Like other members of this protein family, it likely contains conserved motifs for nucleotide binding, which may be critical for its biological function within the bacterial cell.
For context, C. violaceum contains well-studied regulatory proteins such as VioS, which functions as a repressor of violacein biosynthesis without influencing the CviI/R quorum sensing system . The CviI/R system positively regulates multiple phenotypes including violacein production, protease activity, and chitinolytic activity . Understanding how CV_3336 might interact with these or other regulatory systems would be a valuable research direction.
To predict the function of CV_3336, researchers should implement a multi-faceted bioinformatic approach:
Sequence homology analysis: Compare the CV_3336 sequence against characterized proteins using BLAST, searching both general (nr) and specialized (Swiss-Prot) databases.
Domain prediction: Identify conserved domains using tools like InterPro, SMART, or CDD to reveal functional modules.
Structural prediction: Generate 3D models using AlphaFold2 or similar tools, then compare against known structures using tools like Dali server.
Genomic context analysis: Examine neighboring genes that might be functionally related or form an operon with CV_3336.
Phylogenetic analysis: Construct a phylogenetic tree of homologous proteins to identify evolutionary relationships.
A sample workflow for functional prediction might include:
| Analysis Step | Tools | Expected Outcome | Time Requirement |
|---|---|---|---|
| Sequence homology | BLAST, HHpred | List of homologous proteins with e-values | 1-2 hours |
| Domain prediction | InterPro, SMART | Identified domains and motifs | 1 hour |
| Structure prediction | AlphaFold2, I-TASSER | 3D model with confidence scores | 4-24 hours |
| Genomic context | PATRIC, IMG/M | Gene neighborhood map | 2-3 hours |
| Phylogenetic analysis | MEGA, MrBayes | Evolutionary tree with bootstrap values | 4-8 hours |
The optimal expression system for CV_3336 requires careful consideration of several factors:
For prokaryotic expression, E. coli BL21(DE3) remains a primary choice due to its well-established protocols and high yield potential. When working with CV_3336, consider the following expression parameters:
Vector selection: pET vectors with T7 promoter systems offer strong, inducible expression. For improved solubility, consider fusion tags such as MBP, SUMO, or TrxA.
Induction conditions: Test multiple induction parameters following this experimental design:
| Parameter | Test Conditions | Rationale |
|---|---|---|
| Temperature | 16°C, 25°C, 37°C | Lower temperatures (16-25°C) often improve protein folding |
| IPTG concentration | 0.1 mM, 0.5 mM, 1.0 mM | Optimal concentration balances expression and toxicity |
| Induction OD₆₀₀ | 0.4-0.6, 0.6-0.8, 0.8-1.0 | Cell density affects expression efficiency |
| Induction time | 4h, 8h, 16h (overnight) | Duration impacts yield and potential degradation |
Codon optimization: As C. violaceum has different codon usage than E. coli, codon optimization of the CV_3336 gene sequence for E. coli expression may significantly improve yields.
For proteins that prove difficult to express in E. coli, consider alternative systems such as Bacillus subtilis (for secreted expression) or eukaryotic systems like P. pastoris (for proteins requiring complex folding or post-translational modifications).
To characterize the nucleotide-binding properties of CV_3336, researchers should employ multiple complementary techniques:
Thermal shift assays (TSA): Measure protein stability changes upon nucleotide binding using a real-time PCR machine. Screen various nucleotides (ATP, GTP, CTP, UTP) at different concentrations (0.1-5 mM) to identify potential ligands.
Isothermal titration calorimetry (ITC): Quantify binding thermodynamics. A typical experiment would titrate nucleotides (0.5-1 mM) into purified CV_3336 (50-100 μM) to determine KD, ΔH, and stoichiometry.
Surface plasmon resonance (SPR): For kinetic binding parameters (kon and koff), immobilize CV_3336 on a sensor chip and flow various nucleotides at different concentrations.
Fluorescence-based assays: If CV_3336 contains tryptophan residues near the predicted binding site, intrinsic fluorescence quenching upon nucleotide binding provides a direct readout of binding.
Example data interpretation table:
| Nucleotide | ΔTm (°C) from TSA | KD (μM) from ITC | kon (M⁻¹s⁻¹) from SPR | koff (s⁻¹) from SPR |
|---|---|---|---|---|
| ATP | +7.5 ± 0.5 | 25 ± 3 | 1.5 × 10⁵ | 3.8 × 10⁻³ |
| GTP | +4.2 ± 0.3 | 78 ± 6 | 8.2 × 10⁴ | 6.4 × 10⁻³ |
| CTP | +1.1 ± 0.4 | 320 ± 24 | 5.5 × 10⁴ | 1.8 × 10⁻² |
| UTP | +0.8 ± 0.5 | 480 ± 35 | 3.2 × 10⁴ | 1.5 × 10⁻² |
Note: This is example data for illustrative purposes. Actual binding parameters would need to be experimentally determined.
To elucidate the function of CV_3336 in C. violaceum, researchers should implement a multi-faceted experimental strategy:
Gene knockout/knockdown studies: Generate CV_3336 deletion mutants using CRISPR-Cas9 or homologous recombination. Compare phenotypes with wild-type C. violaceum across multiple growth conditions and stress responses.
Transcriptomic analysis: Perform RNA-Seq comparing wild-type and CV_3336 mutant strains to identify differentially expressed genes, potentially revealing pathways associated with CV_3336 function.
Protein-protein interaction studies: Implement pull-down assays or bacterial two-hybrid screening to identify interaction partners of CV_3336.
Metabolomic profiling: Compare metabolite profiles between wild-type and mutant strains using LC-MS/MS to detect metabolic changes resulting from CV_3336 deletion.
Complementation studies: Reintroduce wild-type CV_3336 and mutated versions (targeting predicted functional domains) to confirm phenotype restoration and identify critical residues.
Given C. violaceum's established quorum sensing system, special attention should be paid to potential interactions between CV_3336 and the CviI/R system, which regulates multiple phenotypes including violacein production, protease activity, and chitinolytic activity .
Based on our understanding of C. violaceum's regulatory systems, several potential experimental designs could reveal CV_3336's role in bacterial regulatory networks:
Regulatory network examination: Investigate potential interactions between CV_3336 and known regulatory elements such as VioS (repressor of violacein biosynthesis) and the CviI/R quorum sensing system .
Reporter fusion assays: Construct transcriptional fusions between promoters of interest (e.g., vioA, cviI, cviR) and reporter genes (gfp, lacZ) in both wild-type and CV_3336 mutant backgrounds to quantify regulatory effects.
Chromatin immunoprecipitation (ChIP) analysis: If CV_3336 potentially functions as a DNA-binding protein, perform ChIP-seq to identify genomic binding sites.
in vitro transcription assays: Reconstitute transcription machinery with purified RNA polymerase, potential promoter regions, and CV_3336 to directly test regulatory effects.
For experimental design, a multi-condition approach might reveal context-dependent functions:
| Condition | Wild-type | ΔCV_3336 | ΔCV_3336 complemented | Measurements |
|---|---|---|---|---|
| Standard LB (30°C) | Baseline | Compare to WT | Should restore WT | Growth rate, violacein, protease activity |
| Nutrient limitation | Stress response | Compare to WT | Should restore WT | Stress response genes, metabolic shifts |
| With exogenous AHLs | QS activation | Compare to WT | Should restore WT | QS-regulated phenotypes |
| High cell density | Natural QS induction | Compare to WT | Should restore WT | Transcriptome analysis |
This approach would provide comprehensive insights into how CV_3336 functions across different physiological states of C. violaceum.
Structure-function analysis of CV_3336 should incorporate both computational and experimental approaches:
Structural modeling: Generate a 3D model using AlphaFold2 or similar tools, focusing on the UPF0042 domain architecture and potential nucleotide-binding sites.
Site-directed mutagenesis: Based on structural predictions, create point mutations in conserved residues, particularly those predicted to be involved in nucleotide binding. Express these mutants and assess their:
Ability to bind nucleotides (using methods described in section 2.3)
Capacity to complement phenotypes in CV_3336 knockout strains
Structural integrity through circular dichroism and thermal stability assessments
X-ray crystallography or Cryo-EM: For definitive structural characterization, determine the high-resolution structure of CV_3336, ideally in both apo and nucleotide-bound states.
Molecular dynamics simulations: Once structural data is available, simulate protein dynamics to understand conformational changes upon nucleotide binding and identify potential allosteric sites.
A systematic mutagenesis approach might include:
| Residue | Predicted role | Mutation | Expected effect |
|---|---|---|---|
| K45 | Nucleotide binding | K45A | Decreased nucleotide affinity |
| D78 | Coordination of metal ion | D78A | Disrupted metal binding |
| R103 | Phosphate interaction | R103A | Reduced nucleotide specificity |
| E124 | Catalytic activity | E124Q | Preserved binding, lost catalysis |
| G137 | Conformational flexibility | G137P | Restricted conformational change |
Note: These are hypothetical residues based on typical nucleotide-binding proteins. Actual critical residues would be determined through structural analysis.
Although C. violaceum is generally non-pathogenic, it can cause severe infections in humans, particularly in immunodeficient individuals . Investigating CV_3336's potential role in pathogenicity requires specialized approaches:
Infection models: Compare virulence of wild-type and CV_3336 mutant strains using appropriate infection models such as:
Virulence factor expression: Analyze the expression of known virulence factors in the presence and absence of CV_3336:
Type III secretion system components, particularly Chromobacterium outer protein C (CopC), which has been shown to inactivate caspases and dysregulate programmed cell death in epithelial cells
Hemolysins and other cytotoxins
Antibiotic resistance determinants (C. violaceum is intrinsically resistant to penicillin, colistin, and most cephalosporins )
Host-pathogen interaction studies: Investigate how CV_3336 might influence:
Example experimental progression table:
| Research Phase | Techniques | Key Questions | Controls |
|---|---|---|---|
| Initial screening | Growth curves in stress conditions | Does CV_3336 affect survival under host-like stress? | Wild-type, complemented mutant |
| In vitro virulence | Epithelial cell invasion assays | Is cell invasion affected by CV_3336 deletion? | Non-invasive bacterial strain |
| Model organism studies | C. elegans survival assays | Does CV_3336 affect pathogenicity in vivo? | Non-virulent bacterial strain |
| Advanced model | Murine infection model | Is systemic infection progression altered? | Attenuated C. violaceum strain |
For comprehensive structural characterization of CV_3336, researchers should consider a multi-technique approach:
X-ray crystallography: The gold standard for high-resolution protein structures. Critical steps include:
Screening diverse crystallization conditions (typically 500-1000 initial conditions)
Testing both apo and nucleotide-bound forms
Optimizing crystals for diffraction beyond 2.5 Å resolution
Considering selenomethionine labeling for phase determination
Cryo-electron microscopy (Cryo-EM): Particularly valuable if CV_3336 forms larger complexes or resists crystallization:
Sample preparation optimization (protein concentration, buffer conditions)
Screening for uniform particle distribution
High-resolution data collection and processing
Nuclear Magnetic Resonance (NMR): For studying dynamic regions and ligand binding:
¹⁵N/¹³C labeling for backbone and side-chain assignments
Titration experiments with potential nucleotide ligands
Relaxation measurements to identify flexible regions
Small-angle X-ray scattering (SAXS): For low-resolution envelope determination and studying conformational changes:
Concentration series to detect aggregation
Comparison between apo and nucleotide-bound states
Decision matrix for selecting structural techniques:
| Technique | Resolution | Sample requirements | Equipment access | Time investment | Best for |
|---|---|---|---|---|---|
| X-ray crystallography | 1-3 Å | 5-10 mg, crystals | Synchrotron | 3-12 months | Atomic details, ligand binding |
| Cryo-EM | 2.5-4 Å | 0.1-0.5 mg | Cryo-EM facility | 2-6 months | Large complexes, flexible proteins |
| NMR | Atomic (limited size) | 5-15 mg, ¹⁵N/¹³C labeled | NMR spectrometer | 2-6 months | Dynamics, weak interactions |
| SAXS | 10-30 Å | 1-2 mg | SAXS beamline | 1-2 months | Conformational changes, flexibility |
As a UPF0042 nucleotide-binding protein, CV_3336 may play a role in C. violaceum's nucleotide metabolism. A comprehensive investigation should include:
Nucleotide hydrolysis assays: Test whether CV_3336 possesses ATPase, GTPase, or other nucleotide hydrolysis activities:
Malachite green assay for phosphate release
HPLC analysis of reaction products
Coupled enzyme assays for real-time monitoring
Metabolic flux analysis: Compare nucleotide metabolism in wild-type and CV_3336 mutant strains:
Label C. violaceum cultures with ¹³C-glucose or ¹⁵N-labeled precursors
Analyze metabolite labeling patterns by LC-MS/MS
Quantify differences in nucleotide synthesis and degradation rates
Transcriptional response: Analyze how nucleotide pool imbalances affect CV_3336 expression:
Treat cells with nucleotide synthesis inhibitors (e.g., trimethoprim, azaserine)
Monitor CV_3336 expression using qRT-PCR or reporter constructs
Compare with known nucleotide metabolism genes
Protein interaction network: Identify proteins that interact with CV_3336:
Co-immunoprecipitation followed by mass spectrometry
Bacterial two-hybrid screening
Proximity labeling approaches (e.g., BioID)
Example nucleotide hydrolysis assay findings (hypothetical):
| Nucleotide | Activity (nmol Pi/min/mg) | Km (μM) | kcat (min⁻¹) | kcat/Km (M⁻¹min⁻¹) |
|---|---|---|---|---|
| ATP | 245 ± 18 | 75 ± 8 | 12.3 ± 0.9 | 1.6 × 10⁵ |
| GTP | 183 ± 22 | 120 ± 15 | 9.2 ± 1.1 | 7.6 × 10⁴ |
| CTP | 42 ± 7 | 350 ± 36 | 2.1 ± 0.3 | 6.0 × 10³ |
| UTP | 28 ± 5 | 410 ± 42 | 1.4 ± 0.2 | 3.4 × 10³ |
Generating and validating specific antibodies against CV_3336 requires a systematic approach:
Antibody generation strategy:
Design immunogenic peptides from unique regions of CV_3336
Express full-length protein for immunization
Consider both polyclonal (higher sensitivity) and monoclonal (higher specificity) approaches
Validation experiments:
Western blot analysis comparing wild-type and ΔCV_3336 strains
Preabsorption controls with purified CV_3336 protein
Immunoprecipitation followed by mass spectrometry verification
Immunofluorescence microscopy comparing signal in wild-type vs. mutant
Cross-reactivity assessment:
Test against closely related bacterial species
Check reactivity with purified homologous proteins
Perform epitope mapping to confirm antibody binding sites
Comprehensive antibody validation should include:
| Validation approach | Expected result (specific antibody) | Potential issues | Controls |
|---|---|---|---|
| Western blot | Single band at expected MW in WT, absent in ΔCV_3336 | Non-specific bands | Preimmune serum, blocking with antigen |
| Immunoprecipitation | Enrichment of CV_3336 confirmed by MS | Co-precipitation of interactors | IgG control, ΔCV_3336 strain |
| Immunofluorescence | Specific localization pattern in WT, absent in ΔCV_3336 | Background staining | Secondary antibody only, preimmune serum |
| ELISA | High signal with CV_3336, low with related proteins | Cross-reactivity | Titration curve, competitive inhibition |
A rigorous validation approach will ensure experimental results with these antibodies are reliable and reproducible.