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PBPRA2383 is a protein belonging to the UPF0434 family found in Photobacterium profundum strain SS9, a deep-sea gram-negative bacterium adapted to high-pressure environments. This protein is part of a group of proteins with unknown function (UPF) that are subjects of ongoing research to determine their biological roles. The recombinant form is typically produced in expression systems like E. coli for research purposes, similar to other recombinant proteins from the same organism .
Recombinant PBPRA2383 stability depends on multiple factors including buffer composition, temperature, and protein formulation. For lyophilized preparations, 12-month stability can be expected when stored at -20°C/-80°C. Liquid formulations typically maintain stability for approximately 6 months at -20°C/-80°C. For working solutions, storage at 4°C is recommended for up to one week, with repeated freezing and thawing strongly discouraged as it can lead to protein denaturation and loss of activity .
Research-grade recombinant PBPRA2383 typically has a purity of >85% as determined by SDS-PAGE analysis. For studies requiring higher purity, especially those involving structural biology or sensitive functional assays, researchers should verify if higher purity preparations (>95%) are available or implement additional purification steps using chromatographic techniques .
The optimal expression system for PBPRA2383 is typically E. coli, similar to other recombinant proteins from P. profundum. When designing experiments, researchers should consider the following expression system comparison:
| Expression System | Advantages | Disadvantages | Recommended for PBPRA2383 |
|---|---|---|---|
| E. coli | High yield, cost-effective, rapid expression | Limited post-translational modifications | Primary choice for basic studies |
| Insect cells | Better folding, some PTMs | Higher cost, longer production time | Complex functional studies |
| Mammalian cells | Full range of PTMs, native-like folding | Highest cost, complex protocols, lower yields | Not typically necessary unless specific PTMs required |
E. coli remains the standard choice for PBPRA2383 expression, particularly BL21(DE3) strains with pET vector systems, as they provide good yields of soluble protein under optimized induction conditions .
When designing experiments to investigate PBPRA2383's potential role in pressure adaptation, a randomized block design is recommended to account for variables that might influence results. The experimental design should include:
Control groups (wild-type P. profundum strains and knockout strains)
Variable pressure conditions (atmospheric to deep-sea pressures)
Multiple biological replicates (minimum n=3)
Response variables should include growth rates, gene expression profiles, and protein activity measurements. The use of factorial experimental design allows researchers to examine interactions between pressure and other environmental factors (temperature, salinity) that might influence PBPRA2383 function .
For optimal reconstitution of lyophilized PBPRA2383:
Briefly centrifuge the vial before opening to collect all material at the bottom
Reconstitute using deionized sterile water to a concentration of 0.1-1.0 mg/mL
Add glycerol to a final concentration of 5-50% (with 50% being optimal for long-term storage)
Prepare small working aliquots to avoid repeated freeze-thaw cycles
Validate protein activity after reconstitution using appropriate functional assays
This protocol minimizes protein aggregation and maintains functional integrity for downstream applications .
Investigating structure-function relationships of PBPRA2383 requires a multi-faceted approach:
Computational methods:
Homology modeling using related UPF family proteins as templates
Molecular dynamics simulations under different pressure conditions
Binding site prediction and virtual screening for potential ligands
Experimental validation:
Site-directed mutagenesis of predicted functional residues
Circular dichroism spectroscopy to assess secondary structure changes under varying conditions
X-ray crystallography or cryo-EM for definitive structural determination
The combination of these approaches allows researchers to generate hypotheses about PBPRA2383 function based on structural features and test these hypotheses experimentally, particularly focusing on pressure-responsive structural elements .
For studying PBPRA2383 interactions with other proteins, researchers should implement a complementary set of methodologies:
| Technique | Resolution | Advantages | Limitations | Data Output |
|---|---|---|---|---|
| Pull-down assays | Low | Simple, identifies direct binding partners | Non-specific binding, requires antibodies | Qualitative |
| Co-immunoprecipitation | Medium | Works with endogenous proteins | Requires specific antibodies | Semi-quantitative |
| Surface Plasmon Resonance | High | Real-time kinetics, no labels needed | Requires purified proteins | Quantitative binding constants |
| Proximity Labeling (BioID) | Medium | Identifies transient interactions | Requires genetic modification | Network identification |
| Crosslinking Mass Spectrometry | High | Identifies interaction interfaces | Complex data analysis | Structural interaction data |
A tiered approach beginning with pull-down assays followed by validation using higher resolution techniques provides the most comprehensive understanding of PBPRA2383's interaction network .
While specific functional data for PBPRA2383 is limited, comparisons with other UPF proteins from extremophiles suggest potential roles in stress response. Functional comparison should assess:
Sequence conservation patterns across pressure-adapted microorganisms
Expression profiles under stress conditions (pressure, temperature, oxidative stress)
Phenotypic effects of gene knockout/overexpression
Structural adaptations that correlate with environmental niche
These comparative analyses may reveal whether PBPRA2383 represents a unique adaptation to deep-sea environments or shares common mechanisms with other extremophile stress-response proteins .
Researchers frequently encounter challenges when expressing PBPRA2383 and similar proteins from deep-sea organisms. The most common issues and solutions include:
| Challenge | Possible Causes | Solutions |
|---|---|---|
| Low solubility | Improper folding, hydrophobic regions | Lower induction temperature (16-20°C), use solubility tags (SUMO, MBP), optimize buffer composition |
| Poor expression yield | Codon bias, toxic to host | Use codon-optimized sequence, use tightly regulated expression systems, try different E. coli strains |
| Aggregation after purification | Buffer incompatibility, concentration too high | Screen buffer conditions (pH, salt concentration), add stabilizing agents (glycerol, arginine) |
| Loss of activity | Improper folding, missing cofactors | Include cofactors in purification buffers, validate with functional assays |
Systematic optimization of expression conditions through factorial experimental design can identify optimal parameters for soluble expression .
When faced with contradictory data regarding PBPRA2383 function, researchers should:
Evaluate methodological differences between studies (expression systems, tags, buffer conditions)
Assess the sensitivity and specificity of assays used to measure protein function
Consider environmental variables that might influence protein behavior (pressure, temperature, pH)
Use statistical approaches like meta-analysis to integrate findings across multiple studies
Design definitive experiments that directly address contradictions with appropriate controls
In publications, researchers should present both supporting and contradicting evidence, avoiding confirmation bias. Analysis of variance (ANOVA) can help determine if observed differences are statistically significant or within expected experimental variation .
For analyzing pressure-dependent effects on PBPRA2383 activity, the following statistical approaches are recommended:
Multiple regression analysis: To model relationships between pressure (independent variable) and various measurements of PBPRA2383 activity (dependent variables)
Two-way ANOVA: To assess the effects of pressure and other factors (temperature, pH, salt concentration) as well as their interactions
Repeated measures design: For tracking changes in PBPRA2383 activity across a pressure gradient using the same protein preparation
Goodness of fit analysis: Using the coefficient of determination (r²) to assess how well pressure-response models explain observed activity variations
For proper interpretation, researchers should report both statistical significance (p-values) and effect sizes to provide a complete picture of pressure effects on PBPRA2383 activity .
For comprehensive analysis of potential post-translational modifications (PTMs) in PBPRA2383, the following mass spectrometry approaches are most valuable:
Bottom-up proteomics: Enzymatic digestion followed by LC-MS/MS to identify specific modified residues
Top-down proteomics: Analysis of intact protein to determine the stoichiometry of modifications
Middle-down approach: Limited proteolysis to generate large peptides that maintain the context of modifications
While PTMs in bacterially expressed recombinant proteins are typically limited, native PBPRA2383 from P. profundum may contain modifications relevant to function. Particular attention should be paid to potential phosphorylation sites that might be involved in signaling pathways responsive to pressure changes .
To investigate potential enzymatic activity of PBPRA2383, researchers should design a systematic screening approach:
Sequence-based prediction: Analyze the protein sequence for known catalytic motifs or structural similarities to characterized enzymes
Activity screening: Test the protein against a panel of potential substrates from major enzyme classes (hydrolases, transferases, oxidoreductases)
Cofactor supplementation: Perform activity assays in the presence of common cofactors (metals, NAD(P)H, ATP)
Pressure-dependent analysis: Compare activity under atmospheric versus high-pressure conditions
Data should be collected using multiple detection methods (spectrophotometric, fluorometric, and chromatographic) to maximize the chances of detecting subtle enzymatic activities. Control experiments must include heat-denatured protein and buffer-only conditions .
PBPRA2383 offers valuable opportunities for comparative studies of pressure adaptation across various marine organisms. A comprehensive research program might include:
Phylogenetic analysis of PBPRA2383 homologs across pressure-adapted and non-adapted species
Heterologous expression of PBPRA2383 in pressure-sensitive organisms to assess if it confers pressure resistance
Structural comparison of PBPRA2383 with homologs from different depth zones to identify pressure-adaptive features
Transcriptomic and proteomic profiling to position PBPRA2383 within pressure-responsive pathways
Such studies would contribute to understanding fundamental mechanisms of adaptation to extreme environments and potentially identify molecular features that enable protein function under high pressure conditions .
To determine the in vivo function of PBPRA2383, researchers should implement a multi-faceted experimental design incorporating:
| Approach | Methodology | Expected Outcomes | Limitations |
|---|---|---|---|
| Gene knockout | CRISPR-Cas or homologous recombination | Phenotypic changes indicating function | Possible redundancy masking effects |
| Conditional expression | Inducible promoter systems | Temporal correlation of expression with function | Technical challenges in P. profundum |
| Localization studies | Fluorescent protein fusion or immunolocalization | Subcellular location suggesting functional role | Tagging may affect function |
| Interactome mapping | Affinity purification-mass spectrometry | Identification of interaction partners | Complex data interpretation |
| Complementation studies | Expression in knockout strains | Restoration of function confirming causality | May require optimization for expression |
A randomized block design should be employed when testing phenotypes under different pressure conditions to control for batch-to-batch variation. Quantitative measurements (growth rates, gene expression, metabolite levels) should be analyzed using appropriate statistical methods to determine significance .