The WSB2 antibody (Catalog No. 12124-2-AP) is a rabbit-derived IgG immunoglobulin targeting the WSB2 protein, which plays roles in gonadal development, IL-21 receptor regulation, and cancer progression . Validated for Western blot (WB), immunofluorescence (IF/ICC), immunoprecipitation (IP), and ELISA, this antibody is widely used to investigate WSB2’s molecular functions .
The antibody has been tested across multiple platforms:
The antibody’s specificity is confirmed via knockout (KO) validation and cross-reactivity studies . For instance, it detects WSB2 in colorectal cancer tissues, supporting its role as a differentiation biomarker . Broader antibody validation frameworks, such as KO cell line testing (as highlighted in independent studies) , further reinforce its reliability.
Ubiquitination Pathways: WSB2 facilitates substrate recognition in E3 ubiquitin ligase complexes, enabling proteasomal degradation of target proteins .
IL-21 Signaling: Modulates IL-21 receptor expression and downstream signal transduction .
Cancer Research: Elevated WSB2 levels correlate with differentiation states in colorectal cancer, suggesting diagnostic potential .
WSB2’s involvement in disease pathways highlights therapeutic opportunities:
Oncology: Potential biomarker for tumor differentiation status .
Immunology: Role in IL-21 signaling implicates WSB2 in autoimmune and inflammatory diseases .
Further studies are needed to:
KEGG: spo:SPCC1442.07c
STRING: 4896.SPCC1442.07c.1
The wss2 Antibody is a polyclonal antibody raised against the wss2 protein from Schizosaccharomyces pombe (fission yeast), specifically strain 972/ATCC 24843. It is generated using recombinant wss2 protein as the immunogen and is produced in rabbits. This antibody is primarily intended for research applications focusing on fission yeast systems and is not approved for diagnostic or therapeutic purposes .
The wss2 Antibody has been validated for specific laboratory techniques including Enzyme-Linked Immunosorbent Assay (ELISA) and Western Blotting (WB). These applications enable researchers to detect and quantify the presence of wss2 protein in experimental samples. The antibody has undergone affinity purification to enhance its specificity for the target protein, making it suitable for sensitive detection methods in research settings .
For optimal preservation of antibody activity, wss2 Antibody should be stored at either -20°C or -80°C upon receipt. The product is supplied in a storage buffer containing 50% glycerol, 0.01M PBS (pH 7.4), and 0.03% Proclin 300 as a preservative. It is critical to avoid repeated freeze-thaw cycles as these can compromise antibody performance. Aliquoting the antibody upon first thaw is recommended for laboratories that will not use the entire volume in a single experiment .
For comprehensive validation of wss2 Antibody specificity in fission yeast experiments, researchers should implement a multi-tiered approach:
Positive controls: Use purified recombinant wss2 protein at known concentrations
Negative controls: Include samples from wss2 knockout strains
Competitive inhibition: Pre-incubate antibody with purified antigen before application
Cross-reactivity assessment: Test against closely related proteins
This methodological framework parallels validation approaches used for other specific antibodies in research, such as those targeting SARS-CoV-2 spike proteins, where multiple validation methods ensure antibody performance reliability .
While specific dilution recommendations must be empirically determined for each experimental setup, researchers should consider these starting parameters:
| Application | Suggested Initial Dilution Range | Optimization Considerations |
|---|---|---|
| Western Blot | 1:1000 - 1:5000 | Protein expression level, detection method sensitivity |
| ELISA | 1:5000 - 1:20000 | Direct vs. indirect format, blocking conditions |
A titration series should be performed for each new experimental system, with particular attention to signal-to-noise ratio. This approach ensures optimal antibody performance while conserving reagent. The methodology parallels optimization strategies used with neutralizing antibodies in other research contexts .
To discriminate between specific wss2 protein binding and non-specific background, researchers should implement these methodological controls:
Pre-immune serum comparison: Compare signals obtained with wss2 Antibody to those with pre-immune serum from the same animal
Blocking peptide competition: Pre-incubate the antibody with excess immunizing peptide
Signal comparison between wild-type and knockout samples: Analyze differential signals
Secondary antibody-only controls: Assess background from detection system
This approach mirrors verification methods used in antibody-based research where distinguishing specific binding is crucial for accurate data interpretation, similar to strategies employed in studies of neutralizing antibodies against pathogens .
When investigating wss2 protein interactions in S. pombe, researchers should consider:
Physiological relevance: Design experiments under conditions where wss2 is naturally expressed
Crosslinking strategy: Use reversible crosslinkers for transient interactions
Antibody orientation: Consider using the wss2 Antibody for both immunoprecipitation and detection in separate experiments
Blocking strategy: Optimize blocking conditions to minimize non-specific interactions
Sequential immunoprecipitation: For complex interaction networks, use sequential IP approaches
This experimental framework builds on methodologies used in antibody-based interaction studies, where careful consideration of experimental design ensures detection of genuine protein-protein interactions .
When facing contradictory results between experimental platforms (e.g., discrepancies between ELISA and Western blot data), researchers should:
Evaluate protein conformation effects: Assess whether denaturation affects epitope accessibility
Consider post-translational modifications: Determine if modifications impact antibody recognition
Implement orthogonal validation: Use alternative detection methods like mass spectrometry
Examine buffer compatibility: Test if buffer components interfere with antibody-antigen interaction
Assess epitope masking: Determine if protein interactions obscure the epitope in certain contexts
This systematic troubleshooting approach parallels strategies used when resolving discrepancies in antibody-based experiments, as demonstrated in studies of antibody responses to viral proteins .
When confronting false negative results in wss2 detection experiments, consider these methodological solutions:
Epitope masking: Use different extraction or denaturation conditions to expose hidden epitopes
Protein degradation: Add appropriate protease inhibitors to all buffers
Low expression levels: Implement signal amplification methods or concentrate samples
Interfering compounds: Purify samples further or modify buffer composition
Antibody degradation: Verify antibody integrity via SDS-PAGE analysis
This troubleshooting framework is based on established protocols for resolving detection issues in antibody-based experiments, reflecting approaches used in studies of antibody functionality in various research contexts .
For optimizing wss2 Antibody performance in difficult samples, researchers should consider:
Sample preparation modifications:
For membrane-rich samples: Test different detergent combinations
For complex lysates: Implement fractionation strategies
For fixed samples: Optimize antigen retrieval methods
Signal enhancement approaches:
Tyramide signal amplification for immunohistochemistry
Enhanced chemiluminescence optimization for Western blots
Amplification systems for ELISA
These optimization strategies reflect approaches used in antibody-based detection systems where sample complexity presents challenges for specific antigen detection .
Advanced computational approaches can significantly improve understanding of wss2 Antibody specificity:
Epitope mapping prediction: Use algorithms to identify potential binding sites on the wss2 protein
Binding mode analysis: Apply biophysics-informed models to differentiate between specific and non-specific interactions
Cross-reactivity assessment: Employ sequence homology and structural similarity analyses to predict potential cross-reactive proteins
This computational framework draws from recent advances in antibody specificity modeling, where machine learning approaches have been used to design antibodies with custom specificity profiles. These methods can identify distinct binding modes associated with specific ligands, enabling more refined prediction of antibody-antigen interactions .
For enhancing wss2 Antibody specificity in complex experimental systems, consider:
Affinity purification: Perform additional antigen-specific purification
Counter-selection strategies: Deplete cross-reactive antibodies using related antigens
Competitive blocking: Add excess non-target proteins that might cross-react
Custom specificity engineering: Apply computational approaches to identify variants with enhanced specificity profiles
These approaches parallel methodologies described in advanced antibody research, where biophysics-informed models are trained on experimentally selected antibodies to predict and generate specific variants beyond those observed in initial experiments .
For integrating wss2 Antibody-based approaches with complementary techniques:
Multi-omics integration:
Combine antibody-based protein detection with transcriptomics to correlate wss2 protein levels with gene expression
Integrate with mass spectrometry for validation and identification of post-translational modifications
Combine with chromatin immunoprecipitation techniques if studying chromatin-associated functions
Functional validation approaches:
Complement antibody detection with CRISPR-based gene editing
Correlate antibody-detected localization with live-cell imaging of tagged proteins
Emerging technologies that could enhance wss2 Antibody utility include:
Single-domain antibody derivatives: Development of smaller antibody fragments with enhanced tissue penetration
Engineered specificity profiles: Application of machine learning approaches to design antibodies with custom binding characteristics
Multiplexed detection systems: Integration with microfluidic or spatial profiling technologies
Nanobody development: Creation of camelid-derived single-domain antibodies against wss2 for specialized applications
These potential developments align with cutting-edge approaches in antibody engineering, where computational methods combined with high-throughput experimental techniques are enabling the design of antibodies with precisely tailored specificity properties .