WDR83 Antibody, HRP conjugated

What is WDR83 and why is it important for research?

WDR83 (WD repeat domain-containing protein 83) is a protein that acts as a MAPK organizer and plays a significant role in cellular signaling pathways. The importance of WDR83 lies in its ability to selectively facilitate the activation of ERK signaling in an agonist-specific manner, which is crucial for multiple cellular processes . WDR83 has been found to be upregulated in gastric cancer tissues compared to normal tissues, suggesting its potential role in cancer development and progression . Additionally, WDR83 exhibits a unique bidirectional regulatory relationship with its natural antisense transcript DHPS, making it an interesting subject for studying gene expression regulation mechanisms . Research on WDR83 provides insights into signal transduction pathways that are frequently dysregulated in human diseases, particularly cancer.

What applications are WDR83 antibodies commonly used for?

WDR83 antibodies are primarily used for detecting endogenous levels of total WDR83 protein across various research applications. The most common applications include:

• Immunohistochemistry (IHC): WDR83 antibodies can effectively detect the protein in paraffin-embedded human tissue samples including thyroid cancer and colon cancer tissues .

• Western blotting: For quantitative analysis of WDR83 protein expression in cell lysates and tissue samples, particularly in studies examining signaling pathway activation .

• Investigating ERK signaling pathways: WDR83 antibodies are valuable tools for studying the role of WDR83 in facilitating agonist-specific ERK activation .

• Cancer research: Given WDR83's elevated expression in gastric cancer, antibodies against this protein are useful for oncology research to understand its contribution to cancer development .

How does HRP conjugation affect the performance of WDR83 antibodies?

HRP (Horseradish Peroxidase) conjugation provides significant advantages for WDR83 antibodies in certain research applications:

• Direct detection system: HRP-conjugated antibodies eliminate the need for secondary antibodies, streamlining experimental protocols and reducing potential cross-reactivity issues.

• Enhanced sensitivity: The enzymatic amplification provided by HRP can significantly increase detection sensitivity compared to unconjugated antibodies, which is particularly valuable when studying proteins with low expression levels.

• Compatibility with multiple substrates: HRP-conjugated antibodies can be used with various substrates (DAB, TMB, luminol) allowing flexibility in detection methods (colorimetric, chemiluminescent).

• Stability considerations: While HRP conjugation enhances detection capabilities, it may slightly reduce antibody stability compared to unconjugated versions. Proper storage at -20°C and avoiding repeated freeze-thaw cycles is essential for maintaining optimal activity.

• Application optimization: When transitioning from unconjugated to HRP-conjugated WDR83 antibodies, dilution optimization is necessary as the working concentration typically differs due to the enhanced sensitivity of the conjugated version.

What controls should be included when using WDR83 antibodies?

For rigorous research using WDR83 antibodies, the following controls are essential:

• Positive controls:

  • Human thyroid or colon cancer tissue sections for IHC applications, as these have been validated for WDR83 antibody detection

  • Cell lines known to express WDR83 (such as MGC803 gastric cancer cells)

• Negative controls:

  • Isotype control: Rabbit IgG at the same concentration as the WDR83 antibody

  • Secondary antibody only (for unconjugated primary antibodies)

  • Tissue or cells with WDR83 knockdown via siRNA treatment

• Specificity controls:

  • Pre-absorption with immunizing peptide

  • Western blot showing a single band at the expected molecular weight

  • Parallel experiments with alternative WDR83 antibodies recognizing different epitopes

• Technical controls:

  • Antibody titration to determine optimal working concentration

  • Inclusion of housekeeping protein detection (such as β-actin) for normalization

Implementing these controls ensures reliable and reproducible results while eliminating potential artifacts or non-specific staining.

How can I optimize WDR83 antibody protocols for detecting low-abundance WDR83 in different cell compartments?

Optimizing protocols for low-abundance WDR83 detection requires compartment-specific approaches:

Nuclear Detection:

• Signal amplification: Implement tyramide signal amplification (TSA) with HRP-conjugated WDR83 antibodies, which can increase sensitivity up to 100-fold.

• Extended incubation: Increase primary antibody incubation to overnight at 4°C with gentle agitation to improve epitope binding.

• Nuclear extraction: Perform subcellular fractionation to concentrate nuclear proteins before analysis.

• Antigen retrieval optimization: For IHC/ICC, test multiple antigen retrieval methods (heat-induced epitope retrieval at various pH values, enzymatic retrieval) to maximize epitope accessibility.

Cytoplasmic Detection:

• Permeabilization optimization: Test different permeabilization agents (0.1-0.5% Triton X-100, 0.05-0.25% saponin) and durations to preserve cytoplasmic structure while allowing antibody access.

• Fixation method adjustment: Compare paraformaldehyde, methanol, and acetone fixation to determine which best preserves WDR83 epitopes in the cytoplasm.

• Detergent selection: Use milder detergents in wash buffers to prevent loss of cytoplasmic proteins.

Quantitative Comparison Table for Detection Methods:

Based on subcellular localization analysis, WDR83 transcripts are expressed in both cytoplasm and nucleus , suggesting that optimization for both compartments may be necessary depending on your research question.

How can I effectively use WDR83 antibodies to study its interaction with ERK signaling pathways?

To effectively study WDR83's role in ERK signaling using HRP-conjugated antibodies:

• Stimulation experiments:

  • Conduct time-course experiments with pathway agonists like PMA (5 nM) following serum starvation

  • Monitor both WDR83 expression and ERK1/2 phosphorylation status

  • Compare results between normal and WDR83 knockdown conditions

• Co-immunoprecipitation strategy:

  • Use pull-down assays with anti-WDR83 antibodies to identify interaction partners

  • Confirm interactions with reverse co-IP using antibodies against suspected partners

  • Analyze complexes under different stimulation conditions to capture dynamic interactions

• Pathway inhibition analysis:

  • Employ specific MEK inhibitors (U0126, PD98059) alongside WDR83 detection

  • Compare pathway component changes with or without WDR83 knockdown

  • Create a comprehensive pathway map by integrating results from multiple inhibitors

• Proximity-based detection:

  • Implement proximity ligation assays (PLA) to visualize and quantify WDR83-ERK interactions in situ

  • Compare interaction frequency under different cellular conditions

Experimental Protocol for WDR83-ERK Signaling Study:

• Transfect cells with WDR83 siRNA or control siRNA (50-100 nM)

• After 48 hours, serum-starve cells for 12 hours

• Stimulate with PMA (5 nM) for various time points (0, 5, 15, 30, 60 minutes)

• Harvest cells and prepare lysates with phosphatase inhibitors

• Perform western blotting with anti-phospho-ERK1/2 and total ERK1/2 antibodies

• In parallel, detect WDR83 expression using HRP-conjugated WDR83 antibody

• Quantify band intensities and calculate phospho-ERK/total ERK ratios

This methodological approach follows established protocols that have demonstrated WDR83's role in facilitating agonist-specific ERK activation in gastric cancer cells .

What strategies can resolve conflicting WDR83 antibody data in cancer tissue analysis?

When facing conflicting WDR83 antibody results in cancer tissue analysis, implement these systematic troubleshooting strategies:

• Epitope mapping verification:

  • Compare the epitope recognition sites of different antibodies

  • Test for potential post-translational modifications that might mask epitopes

  • Consider using antibodies targeting different regions of WDR83

• Expression level reconciliation:

  • Implement absolute quantification methods (using recombinant protein standards)

  • Normalize data using multiple housekeeping proteins selected based on tissue-specific stability

  • Perform parallel RNA-level analysis (qPCR, RNA-seq) to correlate with protein findings

• Tissue heterogeneity assessment:

  • Employ laser capture microdissection to analyze specific cell populations

  • Use single-cell approaches when possible to resolve cell-type specific expression

  • Implement spatial transcriptomics alongside IHC to correlate location with expression

• Technical validation matrix:

• Decision tree for resolving conflicts:

  • If antibodies target different epitopes and show different results: Consider isoform-specific or post-translationally modified forms of WDR83

  • If technique-dependent differences emerge: Prioritize results from methods with most stringent controls

  • If tissue-dependent variations exist: Consider microenvironment effects on WDR83 expression or modification

The strong correlation between WDR83 and DHPS expression in gastric cancer tissues (r=0.7107, P<0.0001) provides a reference point against which to evaluate conflicting data.

How can I design experiments to study the bidirectional regulatory relationship between WDR83 and DHPS using antibodies?

To investigate the WDR83-DHPS bidirectional regulation using antibodies:

• Knockdown-rescue experimental design:

  • Perform siRNA knockdown of WDR83 and measure DHPS levels using appropriate antibodies

  • Conduct the reverse experiment with DHPS knockdown and measure WDR83 levels

  • Rescue experiments by introducing expression constructs containing:

    • Full-length WDR83/DHPS transcripts

    • Coding sequence only (CDS)

    • 3'UTR only constructs

• RNA-protein complex detection:

  • Implement RNA immunoprecipitation (RIP) with WDR83 antibodies to capture associated DHPS transcripts

  • Perform RNA protection assays to identify double-stranded RNA regions between WDR83 and DHPS

  • Use RNA-binding protein immunoprecipitation followed by sequencing (RIP-seq) to identify all interactions

• Blocking experiments:

  • Use 2'-O-methyl oligoribonucleotides to inhibit RNA-RNA interactions

  • Measure resulting changes in both WDR83 and DHPS levels

  • Implement luciferase reporter assays with 3'UTR constructs to quantify interaction effects

Comprehensive Experimental Protocol:

• Transfect cells with siRNAs targeting non-overlapping regions of WDR83 or DHPS

• After 48-72 hours, harvest cells and split samples for:

  • Protein analysis: Western blotting with WDR83 and DHPS antibodies

  • RNA analysis: qRT-PCR for transcripts

  • Functional analysis: Cell viability, migration, or signaling assays

• In parallel experiments, transfect cells with expression constructs:

  • Full-length transcripts

  • CDS-only constructs

  • 3'UTR-only constructs

• Measure effects on both proteins using specific antibodies

• Perform luciferase reporter assays with constructs containing the overlapping 3'UTR regions

These approaches build on published strategies that have successfully demonstrated the bidirectional regulation between WDR83 and DHPS through their overlapping 3'UTRs .

What are the critical factors affecting WDR83 antibody, HRP conjugated performance in different applications?

Several critical factors can impact the performance of HRP-conjugated WDR83 antibodies:

• Conjugation ratio optimization:

  • The HRP:antibody ratio significantly affects performance

  • Over-conjugation can reduce antibody affinity and specificity

  • Under-conjugation results in reduced signal strength

  • Optimal molar ratios typically range from 2:1 to 4:1 (HRP:antibody)

• Buffer composition considerations:

  • Avoid sodium azide in working solutions as it inhibits HRP activity

  • Optimize pH between 7.0-7.5 for maximum HRP stability and activity

  • Include stabilizing proteins (0.1-1% BSA) to prevent non-specific binding

  • Consider adding 0.01-0.05% detergent to reduce background in membrane applications

• Application-specific factors:

• Substrate selection guidance:

  • For high sensitivity: Use enhanced chemiluminescent (ECL) substrates

  • For quantitative analysis: Consider chromogenic substrates with lower kinetics

  • For spatial resolution in tissue: DAB provides excellent localization with minimal diffusion

• Storage and stability:

  • Store concentrated antibody at -20°C in single-use aliquots

  • Include stabilizing proteins (1-5% BSA) and cryoprotectants (25-50% glycerol)

  • Avoid repeated freeze-thaw cycles (limit to <5)

  • Working dilutions should be prepared fresh and used within 24 hours

Methodical optimization of these factors will maximize the performance of HRP-conjugated WDR83 antibodies across different experimental applications.

How can I validate the specificity of WDR83 antibodies for research applications?

Comprehensive validation of WDR83 antibody specificity requires a multi-dimensional approach:

• Genetic validation strategies:

  • siRNA/shRNA knockdown: Confirm signal reduction with WDR83-specific siRNAs compared to scrambled controls

  • CRISPR-Cas9 knockout: Generate complete WDR83 knockout cell lines as definitive negative controls

  • Overexpression: Demonstrate signal increase with WDR83 expression constructs

• Biochemical validation approaches:

  • Western blot profile analysis: Confirm single band at expected molecular weight

  • Peptide competition assay: Pre-incubate antibody with immunizing peptide to block specific binding

  • Immunoprecipitation-mass spectrometry: Confirm identity of captured proteins

• Cross-platform validation:

  • Compare results across multiple detection methods (IHC, IF, WB, ELISA)

  • Ensure consistent detection patterns between techniques

  • Validate with orthogonal methods (e.g., mRNA detection via ISH or qPCR)

• Tissue panel validation:

  • Test antibody on multiple tissue types with known WDR83 expression patterns

  • Include both positive tissues (thyroid, colon) and negative controls

  • Confirm expected subcellular localization patterns

Validation Decision Matrix:

Implementing this validation framework ensures that research findings with WDR83 antibodies are reproducible and biologically relevant.

What are the best practices for multiplexing WDR83 antibody with other signaling pathway markers?

Optimizing multiplex detection of WDR83 alongside other signaling pathway markers requires careful consideration of several factors:

• Antibody panel design principles:

  • Primary antibody host species diversification: Select WDR83 and companion antibodies from different host species (rabbit, mouse, goat)

  • Fluorophore selection for IF/Flow: Choose spectrally distinct fluorophores with minimal overlap

  • For brightfield IHC: Implement sequential detection with different chromogens (DAB, AEC, Fast Red)

• Validated marker combinations:

• Sequential multiplexing protocol optimization:

  • Order of detection: Begin with lowest abundance target (often WDR83)

  • Complete antibody stripping between rounds: Validate using secondary-only controls

  • Cross-reactivity prevention: Block between detection rounds with species-specific fragments

• Signal separation strategies:

  • Spectral unmixing for fluorescent detection

  • Sequential chromogenic development with intermediate imaging

  • Cyclic immunofluorescence with antibody stripping

• Data normalization approach:

  • Include universal housekeeping markers across all multiplex panels

  • Implement tissue/cell segmentation for spatial context

  • Use multi-parameter analysis to identify co-expression patterns

Based on research showing WDR83's role in ERK signaling , particularly valuable multiplex combinations include WDR83 with phospho-ERK1/2, total ERK1/2, and upstream activators to comprehensively map pathway dynamics.

How can I effectively use WDR83 antibodies to investigate its role in cancer development and progression?

To effectively investigate WDR83's role in cancer using antibodies:

• Comprehensive tissue profiling strategy:

  • Analyze WDR83 expression across cancer progression stages using tissue microarrays

  • Compare expression in matched tumor/normal pairs from the same patient

  • Correlate expression with clinical outcomes (survival, recurrence, treatment response)

• Functional investigation approaches:

  • Modulate WDR83 levels (knockdown/overexpression) and assess:

    • Proliferation and apoptosis rates

    • Migration and invasion capabilities

    • Anchorage-independent growth

    • Response to therapeutic agents

  • Monitor downstream ERK pathway activation after WDR83 manipulation

• Mechanism exploration methods:

  • Investigate WDR83-DHPS regulatory axis in different cancer types

  • Explore RNA-based regulatory mechanisms using RNA protection assays

  • Identify protein-protein interactions in cancer-specific contexts

• Translational research applications:

  • Assess WDR83 as a potential biomarker for specific cancer subtypes

  • Evaluate its utility in predicting treatment response

  • Investigate WDR83-targeting approaches as potential therapeutic strategies

Experimental Workflow for Cancer Studies:

• Patient sample characterization:

  • IHC analysis of WDR83 in tumor tissues with clinicopathological correlation

  • Quantitative scoring using digital pathology algorithms

  • Statistical analysis of associations with disease features

• Functional validation in cell models:

  • Select appropriate cancer cell lines based on baseline WDR83 expression

  • Perform knockdown/overexpression experiments

  • Measure proliferation, migration, invasion, and drug sensitivity

• Mechanistic investigations:

  • Analyze ERK pathway activation using phospho-specific antibodies

  • Examine WDR83-DHPS regulatory interactions

  • Investigate downstream transcriptional effects

Research has demonstrated that WDR83 expression is significantly increased in gastric cancer samples compared to normal tissues (P=0.0198) , providing a foundation for investigating its role in other cancer types using similar methodological approaches.

How can new developments in antibody technology enhance WDR83 research?

Emerging antibody technologies offer significant opportunities to advance WDR83 research:

• Single-domain antibodies (nanobodies):

  • Advantages for WDR83 research:

    • Superior tissue penetration for whole-mount applications

    • Access to sterically hindered epitopes in protein complexes

    • Improved stability for challenging experimental conditions

  • Application: Developing WDR83-specific nanobodies could enable super-resolution imaging of WDR83-ERK complexes in intact cells

• Recombinant antibody fragments:

  • Benefits for WDR83 detection:

    • Consistent lot-to-lot reproducibility

    • Customizable binding domains

    • Reduced background from Fc-mediated interactions

  • Implementation: Engineer Fab or scFv fragments targeting WDR83-specific epitopes for improved signal-to-noise ratio in complex samples

• Site-specific conjugation technologies:

  • Advantages over traditional HRP conjugation:

    • Controlled HRP:antibody ratio

    • Preserved antigen-binding regions

    • Enhanced sensitivity and reduced background

  • Protocol: Employ enzymatic conjugation (transpeptidase) or click chemistry for optimized HRP-antibody linkage

• Proximity-based detection systems:

  • Applications with WDR83:

    • Visualize WDR83-DHPS RNA duplex formation in situ

    • Map protein interaction networks in different cellular compartments

    • Quantify dynamic changes in complex formation after stimulation

  • Methodologies: Proximity ligation assay (PLA), FRET-based systems, or BioID approaches

Implementation Strategy Table:

These advanced antibody technologies can significantly enhance sensitivity, specificity, and spatial resolution in WDR83 research, particularly for investigating its role in ERK signaling and cancer development.

What are the key considerations for using WDR83 antibodies in high-throughput or automated research platforms?

Optimizing WDR83 antibodies for high-throughput and automated platforms requires specific adaptations:

• Assay miniaturization strategies:

  • Determine minimum antibody concentration maintaining signal-to-noise ratio (typically 0.5-2 μg/ml for HRP-conjugated antibodies)

  • Optimize incubation times and temperatures for reduced protocol duration

  • Establish robust positive/negative controls suitable for Z-factor calculations

  • Validate performance consistency across 96, 384, and 1536-well formats

• Automation-specific protocol modifications:

  • Adjust reagent viscosity and surface tension for reliable automated dispensing

  • Incorporate dead volumes appropriate for liquid handling systems

  • Implement mixing parameters that prevent well-to-well contamination

  • Determine storage stability of working dilutions at room temperature and 4°C

• Data acquisition and analysis optimization:

  • Establish dynamic range specific to WDR83 detection in high-throughput format

  • Develop normalization algorithms accounting for plate position effects

  • Implement quality control metrics for automated result validation

  • Create decision trees for automated outlier identification and handling

• Cross-platform validation requirements:

• Recommended workflow for platform transition:

  • Begin with manual protocol optimization on a small scale

  • Transition to semi-automated workflow with manual quality checks

  • Implement full automation with comprehensive validation

  • Continuous monitoring with periodic manual verification

Implementing these considerations will facilitate reliable, reproducible WDR83 detection in high-throughput screening applications, particularly for drug discovery efforts targeting ERK pathway modulation or cancer therapeutics.

How can I integrate WDR83 antibody-based detection with emerging -omics technologies?

Integrating WDR83 antibody detection with modern -omics approaches creates powerful multi-dimensional analyses:

• Antibody-based proteomics integration:

  • Mass spectrometry-immunohistochemistry correlation:

    • Validate WDR83 antibody specificity with MS-identified peptides

    • Use antibody-based enrichment prior to MS analysis

    • Correlate MS-quantified abundance with antibody signal intensity

  • Reverse phase protein array (RPPA) implementation:

    • Include WDR83 in pathway-focused protein arrays

    • Validate antibody specificity and dynamic range for RPPA application

    • Correlate with tissue microarray data for cross-platform validation

• Transcriptomics integration strategies:

  • Single-cell approaches:

    • Combine RNA-seq with antibody detection in single cells

    • Correlate WDR83 protein levels with DHPS transcript levels at single-cell resolution

    • Investigate cell-type specific expression patterns

  • Spatial transcriptomics:

    • Overlay WDR83 antibody staining with spatial RNA mapping

    • Investigate regional variation in WDR83-DHPS co-expression

    • Correlate with ERK pathway activation markers

• Epigenomics correlation approaches:

  • ChIP-seq integration:

    • Compare WDR83 protein levels with chromatin states at regulated genes

    • Investigate E2F1 binding sites in WDR83-expressing cells

  • Methylation analysis:

    • Correlate WDR83 expression with methylation status of its promoter

    • Investigate epigenetic mechanisms in WDR83-DHPS co-regulation

Multi-omics Integration Workflow:

• Sample preparation with preservation for multiple analyses:

  • Cryopreservation protocols compatible with protein and RNA integrity

  • Sectioning strategies for adjacent analysis of the same sample

  • Fixation optimization for epitope preservation and nucleic acid quality

• Data integration pipeline:

  • Computational alignment of spatial datasets

  • Normalization strategies across platforms

  • Machine learning approaches for pattern recognition

• Validation strategy:

  • Orthogonal confirmation of key findings

  • Single-cell validation of bulk observations

  • Functional testing of computationally predicted relationships

This multi-dimensional approach builds on established correlations between WDR83 and DHPS expression (r=0.7107, P<0.0001) to explore the broader regulatory networks and functional implications in normal and disease states.

What future directions in WDR83 research could benefit from improved antibody technologies?

Several emerging research directions for WDR83 would benefit from advanced antibody technologies:

• Therapeutic targeting of WDR83-dependent signaling:

  • Development of therapeutic antibodies targeting WDR83 functional domains

  • Creation of antibody-drug conjugates for cancer-specific delivery

  • Design of intrabodies to modulate WDR83 function in specific cellular compartments

  • Potential applications in cancers with ERK pathway dysregulation

• Structural biology and protein-protein interaction mapping:

  • Development of conformation-specific antibodies to capture distinct WDR83 states

  • Implementation of intracellular proximity labeling using engineered antibody fragments

  • High-resolution mapping of the WDR83 interactome in different cellular contexts

  • Correlation of structural states with functional outcomes

• Dynamic cellular processes monitoring:

  • Real-time tracking of WDR83 localization using antibody-based biosensors

  • Monitoring ERK pathway activation kinetics with multiplexed antibody arrays

  • Investigation of WDR83-DHPS RNA duplex formation dynamics

  • Correlation with cellular phenotypes in development and disease

• Clinical biomarker development:

  • Standardization of WDR83 detection for diagnostic applications

  • Correlation of WDR83 expression patterns with treatment responses

  • Development of companion diagnostics for targeted therapies

  • Monitoring treatment efficacy through quantitative WDR83 analysis

Research Opportunity Assessment:

Given WDR83's role in ERK signaling and its upregulation in cancer tissues , these research directions could significantly advance our understanding of cancer biology and lead to novel therapeutic approaches.