CD81 Antibody, HRP conjugated

What is CD81 and why is it an important research target?

CD81, also known as TAPA-1 (Target of Anti-proliferative Antibody 1) and Tetraspanin-28, is a widely expressed 25-26 kDa palmitoylated component of plasma membrane lipid rafts. It contains four transmembrane segments, two extracellular loops (30 and 90 amino acids), and three short cytoplasmic regions. CD81 is a multifunctional protein that interacts with various membrane proteins including CD151, TfR2, LDL R, PCSK9, Glypican 3, and complexes of CD19-CD21 .

Its importance as a research target stems from its critical roles in:

• Organization of plasma membrane microdomains

• Facilitation of B and T cell activation pathways

• Functioning as an integrin-binding adhesion molecule

• Serving as a receptor for hepatitis C virus E2 glycoprotein

• Altered expression during viral infections (HCV and HIV-1)

• Development of CD4+CD8+ DP thymocytes

• Supporting B cell receptor signaling

These diverse functions make CD81 relevant to immunology, virology, and cell biology research areas .

What are the standard applications for CD81 antibody detection?

CD81 antibodies are versatile research tools applicable across multiple experimental platforms:

CD81 antibodies have been validated in various cell lines including Jurkat, Ramos, Daudi, HEK-293, HCT 116, and THP-1 cells . The experimental conditions should be optimized for each specific application and sample type to achieve optimal results.

What is the difference between using a direct HRP-conjugated CD81 antibody versus a two-step detection system?

Both approaches have distinct advantages depending on experimental needs:

Direct HRP-conjugated CD81 antibody:

• Provides single-step detection, reducing protocol time and potential washing losses

• Eliminates cross-reactivity concerns from secondary antibodies

• Offers cleaner background in complex samples

• Typically requires higher primary antibody concentration

• May have lower signal amplification potential

Two-step system (Primary CD81 antibody + HRP-conjugated secondary):

• Allows for signal amplification as multiple secondary antibodies can bind each primary antibody

• More economical when using the same primary antibody across different detection methods

• Provides flexibility to change detection systems

• Demonstrated effectiveness in various cell lines as shown in Western blot analyses of Jurkat and Ramos human cell lines

For maximum sensitivity in challenging samples, the two-step system is often preferred, while direct conjugates offer advantages in multiplexing applications or when reducing protocol time is critical.

How do I determine the optimal concentration of CD81 antibody for my experiment?

Determining the optimal concentration requires systematic titration:

• Initial range finding: Start with manufacturer's recommended dilution range (e.g., 1:1000-1:6000 for WB or 1:500-1:2000 for IHC)

• Serial dilution test: Prepare 3-5 dilutions across this range

• Control inclusion: Include both positive controls (known CD81-expressing cells like Jurkat or Ramos) and negative controls

• Signal-to-noise evaluation: Select the dilution providing maximum specific signal with minimal background

• Sample-specific optimization: Adjust based on your specific sample type, as detection efficiency may vary between cell lines

• Instrument calibration: For fluorescence-based methods, perform detector adjustment using appropriate control samples

Remember that optimal dilution is highly dependent on sample type, protein expression level, and detection system sensitivity . For Western blot detection, validated dilutions range from 1:10000 for transfected cell samples to 1:1000 for endogenous protein levels .

How can CD81 antibodies be used to study exosome biology?

CD81 serves as a key exosomal marker due to its enrichment in these extracellular vesicles:

• Exosome characterization: CD81 antibodies enable identification and quantification of exosome populations through Western blot, ELISA, or flow cytometry

• Isolation validation: Verification of successful exosome isolation by detecting CD81 using immunoblotting

• Density gradient analysis: CD81 detection across gradient fractions defines exosome-containing fractions

• Exosome standards analysis: Research demonstrates CD81 detection in exosome standards from various cell lines (HT-29, LNCaP) using CD81 antibodies

• Co-localization studies: Combined with other exosomal markers (CD9, CD63) to confirm vesicle identity

• Functional studies: Using CD81 antibodies to potentially block exosome uptake or alter biogenesis

The detection of CD81 in exosome standards has been demonstrated using the Simple Western system, with bands observed at approximately 29 kDa, slightly higher than in whole cell lysates, likely due to post-translational modifications specific to exosomal CD81 .

How does CD81 expression relate to viral pathogenesis, and how can antibodies help study this?

CD81 plays critical roles in multiple viral infection mechanisms:

• Hepatitis C virus (HCV) interactions:

  • CD81 functions as a receptor for HCV E2 glycoprotein

  • Antibodies can block viral binding to investigate entry mechanisms

  • Expression mapping across liver sections reveals infection susceptibility patterns

• HIV-1 research applications:

  • CD81 expression on lymphocytes is altered during HIV-1 infection

  • Antibodies enable tracking of expression changes during disease progression

  • Co-immunoprecipitation with CD81 antibodies identifies virus-host protein complexes

• Immunomodulatory effects:

  • CD81-E2 interaction inhibits NK cell cytolytic activity

  • Provides co-stimulatory signals to T cells

  • Inhibits maturation of plasmacytoid dendritic cells

  • These effects can be studied using blocking CD81 antibodies

• Methodological approaches:

  • Flow cytometry to quantify CD81 expression changes on different immune cell populations

  • Immunohistochemistry to map expression in tissues during infection

  • Co-localization studies to visualize viral-host protein interactions

Understanding these interactions provides potential therapeutic targets and insights into viral pathogenesis mechanisms .

What controls should be included when using CD81 antibodies in immunological research?

Comprehensive control strategies ensure reliable and interpretable results:

• Positive cellular controls:

  • Jurkat human acute T cell leukemia cell line

  • Ramos human Burkitt's lymphoma cell line

  • Both demonstrate consistent and detectable CD81 expression

• Negative controls:

  • Isotype controls matching the CD81 antibody's host species and isotype

  • For flow cytometry: isotype control antibodies (e.g., IC0041P when using FAB4615P)

  • Non-expressing cell lines or CD81 knockdown/knockout samples

• Expression validation controls:

  • Transfected versus non-transfected 293T cells to confirm antibody specificity

  • Western blot detection shows clear difference between transfected (+) and non-transfected (-) samples

• Technical controls:

  • Secondary antibody only controls to assess non-specific binding

  • Blocking peptide competition to confirm epitope specificity

  • Multiple detection methods to cross-validate findings

• Sample preparation controls:

  • Comparison of reducing versus non-reducing conditions (CD81 detection is typically performed under reducing conditions)

  • Different buffer systems to optimize extraction of membrane proteins

These controls should be systematically incorporated into experimental design to ensure antibody specificity and result reliability .

Why might CD81 appear at different molecular weights in Western blot analysis?

CD81 can present at various molecular weights due to several biological and technical factors:

• Documented weight variations:

  • Calculated molecular weight: 26 kDa

  • Observed weights in different systems:

    • 22 kDa in standard Western blot

    • 26 kDa in Jurkat and Ramos cell lysates

    • 27 kDa in SK-Mel-28 melanoma cell lysates

    • 29 kDa in exosome preparations

• Biological explanations:

  • Post-translational modifications (glycosylation, palmitoylation)

  • Tissue/cell-specific processing

  • Formation of protein complexes resistant to denaturation

  • Incomplete reduction of disulfide bonds

  • Protein degradation or proteolytic processing

• Technical considerations:

  • Different gel systems and running buffers

  • Variation in sample preparation methods

  • Differences in molecular weight standards

  • Resolution limitations in specific PAGE systems

To address inconsistencies, researchers should:

• Use multiple antibodies targeting different epitopes

• Compare reducing and non-reducing conditions

• Include positive control samples of known molecular weight

• Consider performing mass spectrometry validation

• Document specific experimental conditions when reporting results

What are the optimal sample preparation methods for detecting CD81 in different applications?

Sample preparation must be tailored to CD81's membrane protein characteristics:

For Western Blot:

• Cell lysis in buffer containing 1% NP-40 or Triton X-100 with protease inhibitors

• Processing typically under reducing conditions using Western Blot Buffer Group 1

• Protein loading of 30 μg per lane is effective for endogenous detection

• SDS-PAGE separation using 12% gels provides optimal resolution

• Heat samples at 95°C for 5 minutes to ensure complete denaturation

For Flow Cytometry:

• Use freshly isolated cells whenever possible

• For blood lymphocytes, standard isolation protocols using density gradients are effective

• Maintain cells at 4°C during antibody incubation to prevent internalization

• Fix with 1-2% paraformaldehyde if analysis must be delayed

• Follow specific protocols for staining membrane-associated proteins

For Immunohistochemistry:

• Formalin-fixed, paraffin-embedded tissues require antigen retrieval

• Optimal retrieval uses TE buffer pH 9.0

• Alternative method: citrate buffer pH 6.0

• Block endogenous peroxidase activity if using HRP detection systems

• Human tonsillitis tissue serves as an effective positive control

For Immunofluorescence:

• Paraformaldehyde fixation (4%) preserves membrane protein structure

• Mild permeabilization (0.1% Triton X-100) maintains membrane integrity

• Extended blocking (1-2 hours) reduces non-specific binding

• Dilution ranges of 1:600-1:2400 have been validated for CD81 detection

How can I optimize CD81 detection when working with challenging sample types?

When standard protocols yield suboptimal results, consider these advanced approaches:

• For tissues with high autofluorescence:

  • Use Sudan Black B (0.1-0.3%) treatment to quench autofluorescence

  • Consider HRP-based detection with tyramide signal amplification

  • Employ spectral unmixing on confocal microscope systems

  • Use lower dilutions of primary antibody (1:500) to improve signal-to-noise ratio

• For limited samples (biopsies, rare cell populations):

  • Implement signal amplification systems (ABC method, polymer detection)

  • Consider using Simple Western system which has been validated for CD81 detection

  • Increase antibody incubation time (overnight at 4°C)

  • Use signal enhancers specific for membrane proteins

• For exosome preparations:

  • Validate isolation purity using multiple markers (CD81, CD9, CD63)

  • Load higher protein concentrations (0.5 mg/ml) as used for exosome standards

  • Compare with cellular lysates to confirm proper size detection (29 kDa vs 26 kDa)

  • Consider non-reducing conditions if signal is weak

• For multiplexing with other markers:

  • Carefully select antibodies raised in different host species

  • Perform sequential rather than simultaneous staining for challenging combinations

  • Use directly conjugated antibodies to avoid cross-reactivity

  • Validate each antibody individually before combining

These approaches should be systematically tested with appropriate controls to determine optimal conditions for each specific sample type .

How should I interpret CD81 expression patterns across different cell types?

CD81 expression varies significantly across cell lineages, requiring careful comparative analysis:

• Lymphoid cells:

  • Consistent expression on B lymphocytes

  • Variable expression on T cell subsets

  • Demonstrated detection in Jurkat (T cell), Ramos and Daudi (B cell) lines

  • Often used as a pan-lymphocyte marker in flow cytometry

• Non-hematopoietic cells:

  • Detected in epithelial cells (HCT 116 colorectal cells)

  • Present in HEK-293 (embryonic kidney) cells

  • Expression in SK-Mel-28 malignant melanoma cells

  • Often co-localized with other tetraspanins in epithelial tissues

• Interpretation framework:

  • Compare relative expression levels using quantitative methods

  • Consider CD81's role in membrane organization when analyzing distribution patterns

  • Evaluate co-expression with functional partners (CD19, integrins)

  • Assess changes in expression under different stimulation conditions

• Physiological relevance:

  • Higher expression typically correlates with active membrane remodeling

  • Changes in expression may indicate altered cell activation states

  • Tissue-specific patterns reflect functional specialization

  • Expression on exosomes indicates active vesicular trafficking

When analyzing data, consider both the absolute expression level and the pattern of subcellular distribution, as both provide important functional information about cell state and activity .

What are the key considerations when analyzing CD81 in the context of disease models?

Disease-related CD81 analysis requires contextual interpretation:

• Viral infections:

  • In HCV research, monitor CD81 accessibility on cell surface

  • For HIV studies, track CD81 expression changes on specific lymphocyte subsets

  • Correlate CD81 levels with viral load and disease progression

  • Assess CD81 interaction with viral proteins using co-immunoprecipitation

• Cancer models:

  • Compare CD81 expression between malignant and normal tissues

  • Evaluate correlation with invasiveness and metastatic potential

  • Consider CD81's role in exosome biology and intercellular communication

  • SK-Mel-28 melanoma cells provide a model system for studying CD81 in cancer

• Immune disorders:

  • Analyze CD81 expression on regulatory T cells and myeloid-derived suppressor cells

  • CD81 supports immunosuppressive functions in these populations

  • Evaluate impact on B cell receptor signaling in autoimmune conditions

  • Human tonsillitis tissue serves as an inflammatory model for CD81 expression

• Data interpretation frameworks:

  • Compare against appropriate disease-free controls

  • Consider dynamics of expression throughout disease progression

  • Integrate CD81 data with other disease markers for comprehensive analysis

  • Validate findings across multiple experimental approaches

• Functional correlations:

  • Assess how CD81 expression changes correlate with cellular function

  • Consider CD81's partners (CD19-CD21 complex, integrins) in functional assessments

  • Evaluate impacts on cell migration, activation, and signaling

  • Determine whether CD81 serves as a contributor to or consequence of pathology

This multifaceted approach provides deeper insights into CD81's role in disease mechanisms rather than simply documenting expression changes .

How can I quantitatively analyze CD81 expression data from different experimental platforms?

Proper quantification approaches vary by methodology:

• Western blot quantification:

  • Normalize CD81 signal to loading controls (β-actin, GAPDH)

  • Use densitometry software with background subtraction

  • Perform replicate analyses (n≥3) for statistical validation

  • Present data as relative expression compared to control samples

  • Account for the different observed molecular weights (22-29 kDa)

• Flow cytometry analysis:

  • Report mean fluorescence intensity (MFI) rather than percent positive

  • Calculate ratio of sample MFI to isotype control MFI

  • Use consistent gating strategies across experimental conditions

  • Consider fluorescence minus one (FMO) controls for multicolor panels

  • Human peripheral blood lymphocytes provide reliable positive controls

• Immunohistochemistry quantification:

  • Use digital image analysis for objective quantification

  • Score based on staining intensity and percent positive cells

  • Implement tissue microarray approaches for high-throughput analysis

  • Include standardized positive control tissues (e.g., human tonsillitis)

• Cross-platform data integration:

  • Standardize expression to percent of control across platforms

  • Apply appropriate statistical tests based on data distribution

  • Create normalized expression indices when combining multiple metrics

  • Use visualization tools that highlight patterns across experimental approaches

• Statistical considerations:

  • Account for technical and biological replicates separately

  • Apply appropriate transformations for non-normally distributed data

  • Consider non-parametric methods for small sample sizes

  • Report effect sizes alongside p-values for meaningful interpretation

These quantitative approaches enable rigorous comparison of CD81 expression data across experimental conditions, providing more reliable and reproducible results .

What are the advantages and limitations of using CD81 antibodies for exosome characterization compared to other markers?

CD81 offers specific benefits and challenges as an exosomal marker:

Advantages:

• Consistent enrichment in exosomes across diverse cell types

• Well-characterized antibodies with validated specificity

• Detectable in exosome standards from multiple cell lines (HT-29, LNCaP)

• Membrane orientation preserved in exosomes, maintaining antibody accessibility

• Established detection protocols across multiple platforms

Limitations:

• Not exclusive to exosomes - also present on parent cells

• Expression levels vary by cell type, affecting detection sensitivity

• Post-translational modifications may differ between cellular and exosomal CD81

• Standard curve calibration challenging due to different molecular weights observed (29 kDa in exosomes vs. 26 kDa in cells)

• Requires complementary markers (CD9, CD63) for definitive exosome identification

Methodological implications:

• Combine CD81 with other markers for comprehensive exosome characterization

• Consider differences in molecular weight when comparing cell lysates to exosome samples

• Validate antibody performance specifically in exosome preparations

• Use particles of known size (calibration beads) alongside immunological detection

• Implement appropriate sample preparation methods optimized for vesicular preparations

How can I design multiplexed immunoassays that include CD81 detection?

Creating effective multiplexed assays requires strategic planning:

• Antibody selection considerations:

  • Choose CD81 antibodies from different host species than other targets

  • Verify non-overlapping emission spectra for fluorescent conjugates

  • Test for cross-reactivity between all components of the multiplex panel

  • Consider directly conjugated primary antibodies to eliminate secondary antibody issues

• Panel design strategies:

  • For flow cytometry:

    • Include CD81-PE (phycoerythrin) conjugates which are well-validated

    • Allocate brightest fluorophores to lowest expressed targets

    • Design panels that examine tetraspanin web components simultaneously

  • For imaging:

    • Ensure spectrally distinct fluorophores for co-localization studies

    • Consider sequential staining protocols for challenging combinations

    • Include nuclear counterstains for accurate cellular localization

• Technical optimization:

  • Titrate each antibody individually before combining

  • Include comprehensive controls (FMO, isotype, single-stained)

  • Validate specificity using transfected versus non-transfected cells

  • Adjust instrument settings to accommodate all fluorophores

• Analysis considerations:

  • Implement compensation matrices for spectral overlap

  • Use standardized analysis templates across experiments

  • Consider dimensionality reduction techniques for complex datasets

  • Quantify co-localization using established algorithms and metrics

This structured approach enables reliable simultaneous detection of CD81 alongside other markers, providing more comprehensive biological insights .

What experimental approaches can validate the specificity of CD81 antibody detection in my research system?

Comprehensive validation ensures reliable research outcomes:

• Genetic validation:

  • Compare wild-type to CD81 knockout/knockdown samples

  • Use transfection systems (as demonstrated with 293T cells)

  • Employ CRISPR-Cas9 editing to create isogenic control lines

  • Quantify detection signal correlation with known expression levels

• Biochemical validation:

  • Perform peptide competition assays with immunizing antigen

  • Use multiple antibodies targeting different CD81 epitopes

  • Compare native versus denatured sample detection

  • Confirm size by mass spectrometry after immunoprecipitation

• Cross-platform verification:

  • Correlate Western blot findings with flow cytometry results

  • Compare protein detection with mRNA expression data

  • Use immunoprecipitation followed by mass spectrometry

  • Implement orthogonal detection methods (ELISA, proteomics)

• Specificity controls:

  • Test antibody reactivity on multiple species (human, mouse, rat)

  • Examine cross-reactivity with related tetraspanins (CD9, CD63)

  • Evaluate detection in tissues with known expression patterns

  • Include isotype controls matched to antibody class and host species

• Documentation requirements:

  • Record all validation experiments in detail

  • Include positive and negative control data in publications

  • Specify exact antibody clone, catalog number, and dilution

  • Report the observed molecular weight in your specific system

This systematic validation approach increases confidence in research findings and improves reproducibility across different laboratories and experimental systems .