SCFD2 Antibody

What cell types show positive SCFD2 expression for antibody validation studies?

SCFD2 antibody (such as 13375-1-AP) has been validated across multiple cell lines, providing researchers with reliable positive controls for experimental design. Positive Western blot detection has been confirmed in COLO 320, HepG2, Jurkat, and K-562 cells, while immunoprecipitation has been successfully performed in COLO 320 cells . For tissue-based detection, human colon cancer tissue and normal human colon tissue have demonstrated positive immunohistochemical staining. When establishing validation protocols, researchers should consider including at least one of these cell types as a positive control to ensure antibody performance before proceeding with experimental samples.

What applications can SCFD2 antibody be used for in research protocols?

SCFD2 antibody has been validated for multiple research applications with specific optimization parameters for each technique:

Each application requires specific optimization to achieve optimal signal-to-noise ratios. The antibody shows cross-reactivity with human, mouse, and rat samples, making it suitable for comparative studies across these species .

What buffer systems are optimal for SCFD2 antibody detection in IHC applications?

For optimal antigen retrieval when using SCFD2 antibody in immunohistochemistry applications, TE buffer at pH 9.0 is the recommended primary buffer system . This alkaline pH helps expose epitopes by breaking protein cross-links formed during fixation. If this buffer system proves suboptimal for specific tissue samples, citrate buffer at pH 6.0 can be used as an alternative retrieval method. The optimal buffer system may vary depending on tissue type, fixation method, and fixation duration. Researchers should conduct preliminary optimization experiments comparing both buffer systems on control tissues to determine which provides the best signal-to-noise ratio for their specific experimental samples.

What is the molecular weight profile of SCFD2 for accurate Western blot analysis?

When conducting Western blot analysis using SCFD2 antibody, researchers should expect to observe a protein band between 70-75 kDa, which corresponds to the SCFD2 protein . The calculated molecular weight based on amino acid sequence is 75 kDa (684 amino acids), but the observed molecular weight may vary slightly due to post-translational modifications or tissue-specific expression patterns. When analyzing Western blot results, researchers should be aware that slight variations in apparent molecular weight may occur depending on the gel percentage, running conditions, and sample preparation methods. Any significant deviation from the expected 70-75 kDa range may indicate potential specificity issues or sample degradation.

What are the optimal storage conditions for maintaining SCFD2 antibody activity?

To maintain SCFD2 antibody efficacy and prevent activity loss, proper storage conditions are essential. The antibody should be stored at -20°C in its supplied buffer (PBS with 0.02% sodium azide and 50% glycerol, pH 7.3) . Under these conditions, the antibody remains stable for one year after shipment. Importantly, aliquoting is not necessary for -20°C storage of this particular antibody formulation, which simplifies laboratory management. For smaller size formats (20 μl), the antibody contains 0.1% BSA as a stabilizing agent. Researchers should avoid repeated freeze-thaw cycles and minimize exposure to light, particularly for fluorophore-conjugated versions, to preserve binding activity and specificity.

How can researchers validate SCFD2 antibody specificity for confidence in experimental results?

Validating SCFD2 antibody specificity requires a multi-faceted approach beyond simple positive controls. For definitive validation, researchers should implement:

• Knockdown/knockout validation: Generate SCFD2 knockdown (siRNA/shRNA) or knockout (CRISPR-Cas9) cell lines from positive control cells like COLO 320 or HepG2. Compare antibody signals between wild-type and knockdown/knockout samples - a significant reduction in signal intensity confirms specificity.

• Peptide competition assay: Pre-incubate the SCFD2 antibody with excess immunizing peptide (SCFD2 fusion protein Ag4197) before application to samples. Specific binding will be competitively inhibited, causing signal reduction.

• Cross-reactivity testing: Test antibody performance across species if cross-species experiments are planned. While the antibody shows reactivity with human, mouse, and rat samples , sequence alignment analysis should be performed to identify potential epitope conservation in other species.

• Molecular weight confirmation: Verify that detected bands correspond to the expected 70-75 kDa range . Multiple bands may indicate degradation products, alternatively spliced isoforms, or non-specific binding.

• Multi-antibody validation: When possible, compare results using alternative antibodies targeting different SCFD2 epitopes to confirm consistent expression patterns.

This comprehensive validation approach provides robust evidence of antibody specificity before proceeding with critical experiments.

What strategies can resolve inconsistent SCFD2 antibody staining in tissue microarrays?

When encountering variable SCFD2 antibody staining across tissue microarray samples, several methodological strategies can improve consistency:

• Optimize antigen retrieval parameters: For SCFD2 antibody, systematically test both recommended buffer systems (TE buffer pH 9.0 and citrate buffer pH 6.0) with varied retrieval times (10-30 minutes) and temperatures (95-121°C).

• Implement dual antigen retrieval protocol: Apply a sequential retrieval process using both buffer systems in succession (typically acidic followed by alkaline) to maximize epitope exposure while minimizing tissue damage.

• Standardize fixation protocols: Excessive fixation can mask epitopes. If possible, standardize fixation times for prospective samples or extend antigen retrieval for archival samples with unknown fixation parameters.

• Titrate antibody concentration: Perform a dilution series specific to each tissue type, expanding beyond the recommended 1:50-1:500 range to identify optimal signal-to-noise ratios for each tissue context.

• Implement signal amplification: Consider tyramide signal amplification or polymer-based detection systems to enhance weak signals while maintaining specificity.

• Control slide position effects: Place control tissues in multiple positions within each staining batch to identify and correct for position-dependent staining variability.

By systematically implementing these optimization strategies, researchers can achieve more consistent SCFD2 staining across heterogeneous tissue samples.

How do sample preparation methods affect SCFD2 epitope preservation for immunodetection?

Sample preparation significantly impacts SCFD2 epitope preservation and subsequent antibody detection efficacy. Key considerations include:

By optimizing these parameters for specific experimental contexts, researchers can significantly improve SCFD2 antibody detection sensitivity and reproducibility.

What approaches can distinguish between specific and non-specific SCFD2 antibody binding in complex samples?

Distinguishing specific from non-specific SCFD2 antibody binding requires systematic technical approaches:

• Tiered blocking strategy: Implement a sequential blocking protocol using both protein blocks (5% BSA or 5% non-fat milk) and serum blocks (matched to secondary antibody species) to minimize non-specific interactions. For tissues with high background, add 0.1-0.3% Triton X-100 to blocking buffer to reduce hydrophobic interactions.

• Secondary antibody-only controls: Include controls omitting primary SCFD2 antibody but including all other reagents to identify secondary antibody-mediated background.

• Isotype controls: Use rabbit IgG at equivalent concentration to SCFD2 antibody (which is rabbit polyclonal) to distinguish between specific binding and Fc receptor interactions.

• Competitive inhibition: Pre-incubate SCFD2 antibody with excess immunizing peptide before application. Specific signals should diminish while non-specific binding persists.

• Cross-adsorption protocol: For tissues with persistent non-specific binding, pre-adsorb the SCFD2 antibody against tissue homogenates from negative control samples to remove cross-reactive antibodies.

• Signal thresholding: Implement quantitative image analysis using signal intensity thresholds based on negative control tissues to distinguish specific from background signals.

• Multi-spectral imaging: For challenging samples, employ spectral unmixing to separate specific SCFD2 antibody signal from tissue autofluorescence.

These methodological approaches provide a comprehensive strategy for confidently identifying genuine SCFD2 expression patterns against background noise.

How can advanced microscopy techniques enhance SCFD2 localization studies?

Advanced microscopy techniques can significantly improve the resolution and specificity of SCFD2 localization studies beyond standard immunofluorescence approaches:

• Super-resolution microscopy: Techniques like Structured Illumination Microscopy (SIM), Stimulated Emission Depletion (STED), or Single-Molecule Localization Microscopy (SMLM) can resolve SCFD2 distribution with 20-100 nm resolution, revealing subcellular organization patterns undetectable with conventional microscopy.

• Proximity ligation assay (PLA): For studying SCFD2 interactions with suspected binding partners, PLA provides single-molecule sensitivity for detecting protein-protein interactions within 40 nm proximity, generating fluorescent spots only when proteins are closely associated.

• Correlative Light and Electron Microscopy (CLEM): Combine immunofluorescence detection of SCFD2 with subsequent electron microscopy imaging of the same sample to correlate protein localization with ultrastructural features.

• Live-cell imaging strategies: For dynamic studies, consider fusion of fluorescent proteins to SCFD2 using CRISPR knock-in approaches rather than antibody-based detection, allowing real-time tracking of protein movement.

• Expansion microscopy: Physically expand samples using polymer networks to achieve effective resolution enhancement, particularly useful for densely packed cellular structures where conventional resolution limitations obscure co-localization patterns.

• Light-sheet microscopy: For three-dimensional analysis of SCFD2 distribution in thick tissue sections or organoids, light-sheet approaches provide superior optical sectioning with reduced photobleaching.

When implementing these advanced techniques, researchers should optimize fixation and antibody concentration specifically for each method, as optimal parameters often differ from standard protocols.

What critical controls should be included in SCFD2 antibody experimental workflows?

Robust experimental design for SCFD2 antibody applications requires comprehensive controls tailored to each technique:

For Western Blot:

• Positive control samples: Include lysates from validated positive cell lines (COLO 320, HepG2, Jurkat, or K-562 cells) .

• Loading controls: Probe for housekeeping proteins (β-actin, GAPDH) to normalize SCFD2 expression.

• Molecular weight markers: Verify the observed 70-75 kDa band matches the expected SCFD2 molecular weight .

• Antibody validation control: Include samples from SCFD2 knockdown/knockout models when available.

• Non-specific binding control: Perform secondary-only incubation on duplicate membrane sections.

For Immunohistochemistry:

• Positive tissue controls: Include human colon cancer or normal colon tissue sections in each staining batch.

• Negative tissue controls: Include tissues known to lack SCFD2 expression.

• Technical negative controls: Omit primary antibody while maintaining all other staining steps.

• Absorption controls: Pre-incubate antibody with immunizing peptide to confirm staining specificity.

• Isotype controls: Apply matched concentration of non-specific rabbit IgG to parallel sections.

For Immunoprecipitation:

• Input control: Analyze a fraction of pre-IP lysate to confirm target protein presence.

• IgG control: Perform parallel IP with non-specific rabbit IgG.

• Reciprocal IP: When studying protein interactions, confirm findings by IP of suspected interaction partners.

• Lysate titration: Confirm linearity of IP efficiency using varying amounts of input protein (1.0-3.0 mg recommended) .

Incorporating these systematic controls enables confident interpretation of experimental results and facilitates troubleshooting when unexpected outcomes occur.

How should researchers design multiplexing experiments incorporating SCFD2 antibody?

Designing successful multiplexing experiments with SCFD2 antibody requires careful consideration of several technical parameters:

• Antibody compatibility assessment: Since SCFD2 antibody (13375-1-AP) is a rabbit polyclonal , pair it with antibodies from different host species (mouse, goat, rat) to avoid cross-reactivity between secondary detection systems.

• Sequential multiplexing protocol: For multi-epitope detection on the same sample:

  • Begin with the lowest abundance target (which may be SCFD2 depending on your tissue context)

  • Use tyramide signal amplification (TSA) for signal development

  • Perform complete antibody stripping between rounds (validated by no-primary control)

  • Proceed to subsequent targets in order of increasing abundance

• Spectral separation optimization: When using fluorescent detection:

  • Select fluorophores with minimal spectral overlap (≥30 nm between emission peaks)

  • Include single-stain controls for spectral unmixing calibration

  • Consider long Stokes-shift fluorophores to maximize multiplexing capacity

• Cross-platform validation: Confirm co-expression patterns using complementary techniques:

  • Validate IHC multiplexing results with sequential single-stain sections

  • Cross-validate spatial co-expression with fractionation studies for biochemical confirmation

• Quantitative panel design: For quantitative multiplexing applications:

  • Include at least one reference marker stable across experimental conditions

  • Design acquisition parameters to capture full dynamic range of each target

  • Implement batch correction algorithms for multi-slide experiments

By implementing these design principles, researchers can generate reliable multiplexed data sets that accurately reflect the relationship between SCFD2 and other proteins of interest.

What quantification methods best measure SCFD2 expression levels across different applications?

Accurate quantification of SCFD2 expression requires application-specific methodological approaches:

For Western Blot Quantification:

• Densitometric analysis: Measure integrated density of the 70-75 kDa SCFD2 band using software like ImageJ, normalizing to loading controls.

• Standard curve method: Include a dilution series of positive control lysate (e.g., COLO 320 cells) to establish a linear detection range.

• Total protein normalization: Use technologies like Stain-Free gels or REVERT total protein stains rather than single housekeeping proteins for more reliable normalization.

• Replication requirements: Perform minimum of three biological replicates with technical duplicates, reporting results as mean ± standard deviation.

For IHC Quantification:

• H-score implementation: Calculate H-score (0-300) by multiplying staining intensity (0-3) by percentage of positive cells (0-100%) for semi-quantitative analysis.

• Digital pathology approaches: Use calibrated whole-slide scanning and automated image analysis with algorithms that:

  • Precisely segment nuclear, cytoplasmic, and membrane compartments

  • Classify staining intensity based on optical density measurements

  • Report both percentage positivity and staining intensity metrics

• Multiplex normalization: When performing multiplexed analysis, normalize SCFD2 signals to invariant epitopes to control for section-to-section variability.

For Flow Cytometry Applications:

• Median fluorescence intensity (MFI): Report SCFD2 expression as MFI with subtracted isotype control values.

• Molecules of Equivalent Soluble Fluorochrome (MESF): Convert arbitrary fluorescence units to absolute values using calibration beads.

• Quantitative flow cytometry: Establish standard curves using beads with known antibody binding capacity (ABC) to determine actual antibody binding sites per cell.

These quantification strategies provide rigorous metrics for comparing SCFD2 expression across experimental conditions and between different cellular contexts.

What approaches can resolve contradictory SCFD2 expression data between different detection methods?

When faced with discrepancies in SCFD2 expression patterns between different detection methods, researchers should implement a systematic resolution strategy:

• Epitope accessibility assessment: Different methodologies expose epitopes differently. The SCFD2 antibody (13375-1-AP) targets a specific fusion protein region that may be differentially accessible in native versus denatured states. Compare native-state methods (IP, IHC) with denaturing methods (Western blot) to identify potential conformational epitope issues.

• Isoform-specific detection analysis: Perform RT-PCR to identify potential SCFD2 splice variants in your experimental system. Compare PCR results with Western blot banding patterns to determine if discrepancies result from detection of different isoforms.

• Post-translational modification mapping: Treat samples with phosphatases, glycosidases, or deubiquitinating enzymes before analysis to determine if modifications affect epitope recognition across different methods.

• Cross-validation with orthogonal technologies:

  • Compare antibody-based detection with MS/MS peptide identification

  • Validate protein expression with transcript-level measurements (qRT-PCR, RNA-seq)

  • Use CRISPR-Cas9 tagged endogenous SCFD2 for direct visualization

• Sample preparation harmonization: Standardize key parameters across techniques:

  • Use identical fixation protocols when comparing IHC to IF

  • Prepare parallel samples from the same biological replicates

  • Process all comparative samples simultaneously to minimize batch effects

• Antibody performance metrics: Calculate detection sensitivity and dynamic range for each method to determine which technique provides most reliable quantification for your specific experimental context.

By systematically investigating these technical factors, researchers can reconcile contradictory data and determine which methodological approach provides the most accurate representation of SCFD2 biology in their experimental system.

How should researchers interpret variations in SCFD2 molecular weight observed in Western blots?

When interpreting variations in SCFD2 molecular weight on Western blots, researchers should consider several biological and technical factors:

• Expected molecular weight range: The established molecular weight for SCFD2 is 70-75 kDa, with a calculated weight of 75 kDa (684 amino acids) . Bands within this range likely represent the canonical protein form.

• Post-translational modification analysis: Shifts above the expected molecular weight may indicate:

  • Glycosylation: Treat parallel samples with glycosidases to confirm

  • Ubiquitination: Compare reducing vs. non-reducing conditions

  • Phosphorylation: Test with lambda phosphatase treatment

  • SUMOylation: Particularly for nuclear protein fractions

• Proteolytic processing interpretation: Bands below 70 kDa may represent:

  • Degradation products: Compare fresh vs. stored samples

  • Physiological cleavage: Correlate with biological stimuli

  • Extraction artifacts: Test multiple lysis buffer compositions

• Technical variables assessment:

  • Gel percentage effects: Higher percentage gels may improve resolution around the target molecular weight

  • Buffer system impacts: Tris-glycine vs. Tris-tricine systems resolve different MW ranges optimally

  • Sample preparation influences: Heat denaturation duration can affect apparent MW

• Tissue/cell-specific pattern analysis: Create a reference database of SCFD2 banding patterns across different tissues and cell lines, noting consistent variations that may represent tissue-specific isoforms or modifications.

By systematically analyzing these variables, researchers can determine whether observed molecular weight variations represent biologically relevant SCFD2 forms or technical artifacts requiring methodological refinement.

What bioinformatic approaches can predict potential SCFD2 antibody cross-reactivity?

Predicting potential cross-reactivity of SCFD2 antibody requires multi-layered bioinformatic analysis:

• Epitope prediction and alignment: Since the SCFD2 antibody was generated against a fusion protein (Ag4197) , researchers should:

  • Obtain the immunizing peptide sequence from the manufacturer

  • Perform BLAST searches against the proteome of experimental species

  • Identify proteins with >70% sequence identity in the epitope region

  • Pay particular attention to other SEC1 family proteins

• Structural homology modeling:

  • Generate 3D structural models of SCFD2 and potential cross-reactive proteins

  • Perform structural alignment to identify surface-exposed regions with similar conformational epitopes

  • Calculate electrostatic surface potential to identify functionally similar patches that might cross-react

• Domain conservation analysis:

  • SCFD2 contains SEC1-like domains shared with other trafficking proteins

  • Map domain boundaries using resources like Pfam and InterPro

  • Quantify sequence conservation within these domains across protein families

• Antibody binding site prediction tools:

  • Implement epitope prediction algorithms (BepiPred, DiscoTope)

  • Calculate surface accessibility of predicted epitopes

  • Cross-reference with known post-translational modification sites that might affect recognition

• Machine learning-based cross-reactivity prediction:

  • Apply deep learning approaches similar to those used in antibody design

  • Train models on known cross-reactivity datasets

  • Generate probabilistic cross-reactivity scores for candidate proteins

How can advanced data analysis enhance SCFD2 antibody staining interpretation in tissue samples?

Advanced computational approaches can significantly improve the accuracy and biological relevance of SCFD2 staining pattern interpretation:

• Machine learning-based tissue segmentation:

  • Train neural networks to identify tissue compartments and cell types

  • Analyze SCFD2 expression patterns within specific anatomical contexts

  • Correlate expression with tissue architecture and pathological features

• Spatial statistics implementation:

  • Apply Ripley's K-function or Getis-Ord Gi* analysis to identify significant clustering

  • Quantify co-localization using Pearson's correlation coefficient or Manders' overlap coefficient

  • Implement nearest neighbor analysis to characterize spatial relationships with other markers

• Single-cell phenotyping integration:

  • Combine SCFD2 staining with multiplexed panels for comprehensive cellular phenotyping

  • Apply dimensionality reduction techniques (tSNE, UMAP) to identify cell populations

  • Correlate SCFD2 expression with specific cellular states or differentiation stages

• Cross-platform data integration:

  • Correlate tissue-level SCFD2 expression with transcriptomic data

  • Integrate proteomic measurements with spatial expression patterns

  • Link antibody-based findings with genetic associations from population studies

• Digital pathology standardization:

  • Implement color deconvolution algorithms to separate stains in brightfield IHC

  • Apply batch correction techniques to enable cross-study comparisons

  • Establish standardized reporting metrics for SCFD2 expression levels

These advanced analytical approaches transform descriptive observations into quantitative, reproducible metrics that facilitate deeper biological insights and enable statistically robust comparisons across experimental conditions.