Recombinant Pasteurella multocida Uncharacterized Protein PM1123 (PM1123) is a protein derived from the bacterium Pasteurella multocida, a pathogen responsible for various diseases in animals, including porcine atrophic rhinitis and swine plague . The protein PM1123 is expressed in Escherichia coli and is available as a recombinant full-length protein with a His tag for purification purposes .
Source: The protein is expressed in Escherichia coli.
Tag: It is fused with an N-terminal His tag to facilitate purification.
Length: The protein is full-length, consisting of 123 amino acids.
Form: It is provided as a lyophilized powder.
Purity: Greater than 90% as determined by SDS-PAGE.
Storage: Recommended storage at -20°C or -80°C to maintain stability .
Recombinant proteins like PM1123 can be used in various biomedical applications, including:
Vaccine Development: Understanding the immunogenic properties of proteins from Pasteurella multocida can aid in developing more effective vaccines against diseases caused by this bacterium.
Diagnostic Tools: Recombinant proteins can serve as antigens in diagnostic assays to detect antibodies against Pasteurella multocida.
Basic Research: Studying the functions and interactions of uncharacterized proteins like PM1123 can provide insights into bacterial pathogenesis and host-pathogen interactions.
| Characteristics | Description |
|---|---|
| Species | Pasteurella multocida |
| Source | Escherichia coli |
| Tag | His tag |
| Protein Length | Full Length (1-123 amino acids) |
| Form | Lyophilized powder |
| Purity | >90% by SDS-PAGE |
| Storage Buffer | Tris/PBS-based buffer, 6% Trehalose, pH 8.0 |
| Reconstitution | Deionized sterile water to 0.1-1.0 mg/mL |
KEGG: pmu:PM1123
STRING: 272843.PM1123
PM1123 is an uncharacterized protein from Pasteurella multocida strain Pm70, a Gram-negative, nonmotile coccobacillus . This bacterium is commonly found in the upper respiratory tract of domestic animals and can cause various diseases including fowl cholera in poultry, atrophic rhinitis in pigs, and bovine hemorrhagic septicemia in cattle . The protein is identified by the UniProt ID Q9CLT6 and is classified as "uncharacterized," meaning its precise biological function remains undetermined .
For recombinant expression, several systems have been demonstrated effective:
| Expression System | Advantages | Considerations |
|---|---|---|
| E. coli | High yield, cost-effective, rapid growth | May form inclusion bodies, potential endotoxin contamination |
| Yeast | Post-translational modifications, secretion capability | Longer production time, complex media requirements |
| Baculovirus | Enhanced folding, higher eukaryotic modifications | Technical complexity, higher cost |
| Mammalian Cell | Best for complex proteins, native-like modifications | Highest cost, longest production time |
The protein has been successfully expressed in E. coli with an N-terminal His-tag, which facilitates purification using immobilized metal affinity chromatography (IMAC) . For optimal results, researchers should consider:
Using BL21(DE3) or similar expression strains
Optimizing induction conditions (temperature, IPTG concentration)
Employing a two-step purification protocol (IMAC followed by size exclusion chromatography)
As an uncharacterized protein, several bioinformatic approaches should be employed to generate functional hypotheses:
Homology-based approaches: Perform BLAST, HHpred, and HMMER searches against characterized protein databases, including distantly related sequences .
Domain and motif analysis: Scan for conserved domains using Pfam, PROSITE, and InterPro to identify functional motifs.
Structural prediction and comparison: Use AlphaFold2, I-TASSER, or SWISS-MODEL to generate structural models, followed by structural alignment with characterized proteins using DALI or TM-align.
Genomic context analysis: Examine neighboring genes in the P. multocida genome, as functionally related genes are often co-located or co-expressed.
Protein-protein interaction prediction: Use tools like STRING or PSICQUIC to predict potential interaction partners that might suggest function.
The COMBREX project approach demonstrates that existing experimental information can provide functional insights for more than half of all uncharacterized proteins through sequence and domain-composition similarity analyses .
While the specific role of PM1123 in pathogenicity remains unknown, several methodological approaches can elucidate its potential involvement:
Gene knockout studies: Generate PM1123 deletion mutants and assess virulence in appropriate animal models.
Transcriptomic analysis: Compare PM1123 expression levels under various conditions (e.g., infection vs. laboratory culture) using RNA-Seq.
Localization studies: Determine cellular localization using fluorescent protein fusions or immunogold electron microscopy.
Host interaction assays: Investigate if recombinant PM1123 interacts with host proteins or affects host cell processes such as cytokine production, phagocytosis, or apoptosis.
Immunological studies: Assess whether PM1123 elicits protective immunity in animal models, which would support its role in pathogenesis and potential as a vaccine candidate .
Given that P. multocida causes various diseases across multiple host species, PM1123 may have host-specific functions that should be investigated in relevant experimental systems .
To elucidate the cellular function of PM1123, a multi-faceted experimental approach is recommended:
Subcellular localization: Fractionate bacterial cells to determine if PM1123 is cytoplasmic, membrane-associated, or secreted.
Protein-protein interaction studies:
Pull-down assays with His-tagged PM1123
Bacterial two-hybrid systems
Cross-linking followed by mass spectrometry
Co-immunoprecipitation with anti-PM1123 antibodies
Phenotypic characterization of mutants:
Analyze growth curves in various media
Assess biofilm formation capability
Measure resistance to environmental stresses
Evaluate membrane integrity and permeability
Metabolomic profiling: Compare metabolite profiles between wild-type and PM1123 knockout strains to identify affected pathways.
Structural determination: X-ray crystallography or NMR spectroscopy may reveal structural homology to proteins of known function.
Validation of predicted functions requires a systematic approach:
Start with in silico predictions: Generate specific hypotheses about PM1123 function using computational methods described in section 2.1.
Design targeted biochemical assays:
If predicted to be an enzyme, design activity assays with potential substrates
If predicted to bind specific molecules, perform binding assays (e.g., SPR, ITC)
If predicted to have structural roles, assess effects on membrane integrity or cell morphology
Include proper controls:
Positive controls: proteins with known activities similar to those predicted
Negative controls: mutated versions of PM1123 with altered predicted active sites
Expression controls: ensure consistent protein levels across experiments
Follow with in vivo validation:
Generate complemented mutants to confirm phenotype rescue
Use conditional expression systems to study essential functions
Employ CRISPR interference for partial knockdown if complete deletion is lethal
Confirm specificity:
Test related proteins from other bacterial species
Create point mutations in predicted functional domains
Structural characterization requires careful planning:
Protein preparation optimization:
Test multiple constructs with different boundaries and tags
Screen buffer conditions (pH, salt, additives) for stability
Assess protein homogeneity by dynamic light scattering
Crystallization strategy:
Begin with commercial screening kits
Optimize promising conditions systematically
Consider surface entropy reduction mutations for challenging proteins
NMR considerations:
Produce isotopically labeled protein (15N, 13C)
Perform preliminary 1D experiments to assess feasibility
Consider TROSY techniques if molecular weight exceeds 20 kDa
Computational approaches:
Generate models using AlphaFold2 to guide experimental design
Validate experimental structures against computational predictions
Identify potential functional sites through conservation mapping
Data analysis workflow:
Establish protocols for data processing and refinement
Plan for validation using tools like MolProbity
Design follow-up experiments to test structure-based hypotheses
Contradictory results are common when studying uncharacterized proteins. A systematic integration approach includes:
Construct a data matrix:
List all experiments performed and their results
Identify conflicts and consistencies
Weigh evidence based on experimental rigor and reproducibility
Consider contextual factors:
Examine experimental conditions (pH, temperature, media composition)
Assess protein constructs used (full-length vs. truncated, tag position)
Consider strain-specific differences in Pasteurella multocida
Apply Bayesian reasoning:
Start with prior probabilities based on computational predictions
Update with experimental evidence, accounting for technique reliability
Calculate posterior probabilities for competing functional hypotheses
Design discriminatory experiments:
Identify experiments that can specifically distinguish between competing hypotheses
Prioritize orthogonal techniques (e.g., if structural studies and binding assays conflict, try genetic approaches)
Collaborate with specialists:
Consult with experts in particular techniques for alternative interpretations
Consider reproducibility in different laboratories
Comparative genomics offers powerful tools for functional prediction:
Phylogenetic profiling:
Map presence/absence of PM1123 homologs across bacterial species
Correlate with ecological niches or pathogenicity patterns
Identify co-evolving gene families
Synteny analysis:
Examine conservation of genomic context across related species
Identify operonic structures that suggest functional relationships
Look for horizontally transferred genomic islands
Evolutionary rate analysis:
Calculate selective pressure (dN/dS ratios) to identify conserved functional regions
Perform codon-based Z-tests for selection
Identify lineage-specific accelerated evolution
Structural comparison across homologs:
Align predicted or determined structures from multiple species
Identify conserved pockets or interfaces
Map conservation onto structural models
Pan-genome analysis:
Determine if PM1123 belongs to core or accessory genome of Pasteurella
Correlate gene presence with phenotypic traits across strains
As an uncharacterized protein, PM1123's potential as a therapeutic target requires systematic evaluation:
Immunogenicity assessment:
Test recombinant PM1123 for antibody production in animal models
Evaluate T-cell responses to PM1123 epitopes
Compare protection levels against different P. multocida strains
Conservation analysis:
Determine sequence conservation across pathogenic strains
Identify strain-specific variations that might affect vaccine efficacy
Map epitopes onto structural models to predict accessibility
Target validation studies:
Confirm whether antibodies against PM1123 neutralize bacterial function
Determine if passive immunization provides protection
Assess if PM1123 is essential for virulence or survival in vivo
Formulation optimization:
Test different adjuvants for enhanced immunogenicity
Evaluate delivery systems for optimal immune response
Consider combination with other P. multocida antigens
Cross-protection potential:
Assess protection against heterologous strains
Evaluate efficacy across different host species
Determine duration of protective immunity
Given that P. multocida causes significant economic losses in livestock industries and occasional human infections, developing effective vaccines has substantial value .