SPCC63.06 Antibody

What is SPCC63.06 Antibody and what is its primary research application?

SPCC63.06 antibody refers to antibodies targeting the centrosomal protein 63 (Cep63), which plays critical roles in centrosome duplication and cell cycle regulation. These antibodies are primarily used in applications such as immunoblotting, immunofluorescence, and immunohistochemistry to investigate centrosome biology, cell division defects, and cellular responses to DNA damage. Similar to other well-characterized antibodies like anti-Cep63, they allow researchers to monitor protein expression, localization, and post-translational modifications in various experimental systems . When selecting an appropriate antibody for your experiments, consider the specific epitope recognition, clonality, species reactivity, and validated applications to ensure reliable results.

How should researchers validate SPCC63.06 antibody specificity before experimental use?

Validation of SPCC63.06 antibody specificity requires a multi-faceted approach similar to that used for other research antibodies. Begin with Western blot analysis comparing wild-type samples with Cep63 knockout/knockdown controls to confirm the antibody detects bands of the expected molecular weight exclusively. Perform immunoprecipitation followed by mass spectrometry to verify target enrichment. For immunofluorescence applications, compare staining patterns with other validated Cep63 antibodies and confirm centrosomal localization patterns consistent with Cep63's known subcellular distribution. Peptide competition assays can further confirm specificity by demonstrating signal abrogation when the antibody is pre-incubated with its target peptide. Finally, testing across multiple species and cell types relevant to your research will establish the antibody's specificity boundaries and appropriate experimental contexts .

What are the recommended storage and handling conditions for SPCC63.06 antibody to maintain functionality?

For optimal preservation of SPCC63.06 antibody functionality, store concentrated stock solutions at -20°C or -80°C in small aliquots to prevent repeated freeze-thaw cycles, which can lead to antibody degradation and reduced activity. Working dilutions can typically be stored at 4°C for 1-2 weeks, though specific manufacturer's recommendations should be followed. Most antibodies targeting centrosomal proteins like Cep63 are shipped as buffered aqueous glycerol solutions, which help maintain stability during transport and storage . When handling the antibody, avoid contamination by using sterile technique, minimize exposure to light for fluorophore-conjugated versions, and keep the antibody on ice during experimental setup. Document all freeze-thaw cycles and periodically validate antibody performance with positive controls to ensure continued specificity and sensitivity throughout your research project.

How should I optimize immunostaining protocols when using SPCC63.06 antibody for centrosome visualization?

Optimizing immunostaining with SPCC63.06 antibody for centrosome visualization requires careful attention to several critical parameters. Begin by testing multiple fixation methods, as centrosomal protein epitopes can be sensitive to fixation conditions. Compare 4% paraformaldehyde, methanol, and methanol:acetone fixation to determine which best preserves the epitope while maintaining cellular architecture. For permeabilization, test Triton X-100 (0.1-0.5%) against 0.05% saponin to find the optimal balance between antibody accessibility and centrosome structure preservation.

Antibody concentration is crucial - prepare a dilution series (typically 1:100 to 1:2000) to identify the optimal signal-to-noise ratio. Include positive controls (known centrosomal markers like γ-tubulin) for co-localization studies to confirm proper centrosome labeling. For challenging applications, consider signal amplification techniques such as tyramide signal amplification or the use of biotin-streptavidin systems. Finally, optimize blocking conditions, incubation times (2h at room temperature versus overnight at 4°C), and washing steps to reduce background while maximizing specific signal .

What experimental controls are essential when designing studies with SPCC63.06 antibody?

Rigorous experimental design with SPCC63.06 antibody requires comprehensive controls to ensure valid and reproducible results. Always include:

• Positive controls: Samples known to express Cep63 at detectable levels using established cell lines or tissues.

• Negative controls:

  • Primary antibody omission control to assess secondary antibody specificity

  • Isotype control using non-specific IgG matching the host species and concentration

  • Genetic controls using Cep63 knockout/knockdown cells to confirm specificity

• Technical controls:

  • Loading controls for Western blots (β-actin, GAPDH)

  • Counterstains for immunofluorescence (DAPI for nuclei, γ-tubulin for centrosomes)

• Validation controls:

  • Multiple antibodies against different Cep63 epitopes

  • Recombinant protein expression controls to verify antibody detection capabilities

• Treatment controls:

  • Cell cycle synchronization controls (critical for centrosomal proteins)

  • DNA damage response controls when studying Cep63 functions in genome integrity

These controls help distinguish specific from non-specific signals, validate observed phenotypes, and support the reliability of your findings in centrosome biology research .

How can I troubleshoot weak or nonspecific signals when using SPCC63.06 antibody in Western blotting?

When encountering weak or nonspecific signals with SPCC63.06 antibody in Western blotting, implement this systematic troubleshooting approach:

For weak signals:

• Increase antibody concentration incrementally (e.g., from 1:1000 to 1:500)

• Extend primary antibody incubation time (overnight at 4°C instead of 2h at room temperature)

• Increase protein loading (50-80 μg instead of 10-20 μg)

• Enhance detection sensitivity using amplified ECL substrates or fluorescent secondary antibodies

• Optimize transfer conditions for high molecular weight proteins (reduce transfer time/voltage)

• Check sample preparation method to ensure epitope preservation

For nonspecific signals:

• Increase blocking stringency (5% BSA or 5% milk, or add 0.1% Tween-20)

• Implement more rigorous washing steps (5 × 5 minutes with TBS-T)

• Pre-adsorb antibody with cell lysate from Cep63-knockout cells

• Test alternative membrane types (PVDF vs. nitrocellulose)

• Optimize antibody dilution buffer composition (add 0.1% SDS to reduce hydrophobic interactions)

• Verify sample integrity with fresh lysates and protease inhibitors

When analyzing samples from different species, ensure the antibody's epitope is conserved across those species by performing sequence alignment analysis before experimental design .

How can SPCC63.06 antibody be used in studying centrosome abnormalities in cancer research?

SPCC63.06 antibody offers valuable applications in cancer research through its ability to detect and quantify centrosome abnormalities, which are hallmarks of many cancer types. For comprehensive centrosome analysis in tumor samples, implement a multi-parameter assessment approach:

• Quantitative immunofluorescence analysis: Use SPCC63.06 antibody in conjunction with pericentrin or γ-tubulin antibodies to assess centrosome number, size, and morphology across tumor samples. Calculate the centrosome amplification index (percentage of cells with >2 centrosomes) and correlate with clinical parameters.

• Co-localization studies: Combine with markers of genomic instability (γH2AX) and cell cycle regulators (cyclin E, CDK2) to investigate mechanisms driving centrosome abnormalities.

• High-content screening: Develop automated image analysis workflows to quantify centrosome parameters across large sample cohorts or following drug treatments.

• Live-cell imaging: For dynamic studies, combine with fluorescently-tagged centrosome markers to track centrosome behavior throughout the cell cycle in cancer cell lines.

• Tissue microarray analysis: Apply optimized immunohistochemistry protocols to analyze centrosome abnormalities across diverse tumor types and correlate with patient outcomes.

These applications enable researchers to investigate how centrosome dysregulation contributes to genomic instability, a key factor in cancer progression and response to therapy .

What considerations are important when using SPCC63.06 antibody across different species models?

When applying SPCC63.06 antibody across different species models, researchers must carefully consider epitope conservation and validation requirements. The antibody's target sequence may have varying degrees of homology between species, potentially affecting binding affinity and specificity. Before proceeding with cross-species applications, perform the following:

• Conduct bioinformatic analysis of the target epitope sequence across species of interest, calculating percent identity and noting any amino acid substitutions that might affect antibody recognition.

• Validate the antibody in each new species model through Western blot analysis comparing to a positive control from a validated species.

• For each new species, optimize protocols independently, as fixation conditions, antibody concentrations, and incubation times may require adjustment.

• Consider potential cross-reactivity with related proteins that may have higher homology in certain species, particularly for polyclonal antibodies.

• When interpreting results across species, account for differences in centrosome biology, cell cycle regulation, and protein expression patterns that might influence experimental outcomes.

This methodical approach ensures reliable data generation when extending SPCC63.06 antibody applications to diverse experimental models, from human cell lines to mouse, zebrafish, or other research organisms .

How does epitope specificity influence SPCC63.06 antibody performance in different applications?

Epitope specificity critically determines SPCC63.06 antibody performance across experimental applications through multiple mechanisms. Different regions of the Cep63 protein may be accessible or obscured depending on protein folding, complex formation, or post-translational modifications, creating application-specific constraints:

For structural applications:

• Antibodies targeting surface-exposed epitopes perform better in immunoprecipitation and flow cytometry

• Denaturation-resistant epitopes are preferred for Western blotting

• Conformational epitopes may be essential for detecting native protein interactions

For functional analysis:

• Antibodies recognizing phosphorylation sites can track Cep63 activation during DNA damage response

• Epitopes near protein-protein interaction domains help visualize centrosome assembly dynamics

• C-terminal epitopes may detect specific isoforms with distinct functions

The performance impact of epitope location is quantifiable, as demonstrated in similar antibody development studies. For instance, membrane-distal domain binding can dramatically alter receptor internalization properties compared to membrane-proximal binding, as seen with Siglec-6 antibodies where clones binding to domain 1 displayed markedly different internalization and inhibitory activities .

Understanding these specificity parameters allows researchers to select appropriate antibodies for specific applications, or to employ multiple antibodies recognizing different epitopes for comprehensive protein characterization.

How should researchers quantify and analyze SPCC63.06 antibody staining patterns in fluorescence microscopy?

Quantitative analysis of SPCC63.06 antibody staining patterns requires standardized approaches to ensure reproducibility and statistical validity. Implement this comprehensive workflow:

• Image acquisition standardization:

  • Maintain consistent exposure settings across all experimental conditions

  • Capture Z-stacks (0.2-0.3μm steps) to fully resolve 3D centrosome structures

  • Include technical replicates (minimum 3) and biological replicates (minimum 3)

• Primary quantitative parameters:

  • Signal intensity (integrated density at centrosomes vs. background)

  • Object count (number of Cep63-positive foci per cell)

  • Co-localization coefficients with other centrosomal markers (Pearson's or Mander's)

  • Size measurements (diameter, volume) of Cep63-positive structures

• Advanced analysis approaches:

  • Implement machine learning-based segmentation for complex staining patterns

  • Develop custom ImageJ/FIJI macros for batch processing of large datasets

  • Apply density-based clustering algorithms to distinguish true centrosomal signals

• Statistical analysis:

  • Use non-parametric tests for intensity data (often not normally distributed)

  • Apply multiple comparison corrections for experiments with many conditions

  • Calculate effect sizes (Cohen's d) in addition to p-values

• Visualization standards:

  • Present representative images alongside quantification

  • Include scale bars and indicate image processing methods

  • Use color-blind friendly palettes for multicolor overlays

This methodical approach transforms qualitative observations into quantitative data suitable for rigorous statistical analysis and publication .

What are the common causes of data inconsistency when working with SPCC63.06 antibody and how can they be addressed?

Data inconsistency with SPCC63.06 antibody often stems from multiple technical and biological variables that can be systematically addressed:

To establish protocol robustness, implement "stress testing" by deliberately varying individual parameters within acceptable ranges to determine their impact on experimental outcomes. This approach, similar to that used in Siglec-6 antibody characterization, helps identify critical steps requiring stringent control . Document all procedure details including timing intervals, reagent sources, and equipment settings to facilitate troubleshooting of inconsistent results.

How can researchers differentiate between specific binding and artifacts when interpreting SPCC63.06 antibody results?

Differentiating specific SPCC63.06 antibody binding from artifacts requires a multifaceted validation approach combining controls, alternative methods, and quantitative analysis:

• Implementation of critical controls:

  • Peptide competition assays to confirm signal abrogation with specific blocking peptides

  • Genetic knockdown/knockout validation showing signal reduction proportional to protein depletion

  • Secondary-only controls to identify non-specific secondary antibody binding

  • Pre-immune serum controls (for polyclonal antibodies) to establish baseline background

• Multi-method confirmation:

  • Correlate immunofluorescence results with super-resolution microscopy for precise localization

  • Verify protein-protein interactions detected by co-immunoprecipitation with proximity ligation assays

  • Confirm antibody specificity through mass spectrometry analysis of immunoprecipitated samples

• Signal characteristic analysis:

  • Examine expected localization patterns (centrosomal for Cep63)

  • Verify appropriate molecular weight bands in Western blots

  • Confirm expected cell cycle-dependent changes in signal intensity

  • Analyze signal-to-noise ratios quantitatively across multiple experiments

• Artifact identification guide:

  • Punctate nuclear signals often represent fixation artifacts

  • Membrane accumulation may indicate antibody aggregation

  • Uniform cytoplasmic staining without expected localization suggests specificity issues

  • Signal present in known negative cell types indicates cross-reactivity

How can SPCC63.06 antibody be utilized in studies of DNA damage response pathways?

SPCC63.06 antibody offers powerful applications in DNA damage response (DDR) research due to Cep63's established roles in centrosome regulation following genomic stress. To leverage this antibody effectively in DDR studies:

• Temporal dynamics analysis: Use time-course experiments following DNA damage induction (with agents like etoposide, cisplatin, or ionizing radiation) to track Cep63 localization, post-translational modifications, and protein level changes. This approach can reveal how quickly Cep63 responds to different damage types and through which signaling pathways.

• Post-translational modification profiling: Combine SPCC63.06 with phospho-specific antibodies to monitor Cep63 phosphorylation status following DNA damage, as phosphorylation often regulates protein function during stress responses. This can be quantified through Western blotting with phospho-specific antibodies or mass spectrometry of immunoprecipitated Cep63.

• Protein-protein interaction network mapping: Use SPCC63.06 in immunoprecipitation followed by mass spectrometry to identify damage-specific interaction partners. Compare interactomes between damaged and undamaged conditions to identify DDR-specific associations.

• Functional pathway analysis: Combine with genetic approaches (CRISPR/Cas9, siRNA) targeting specific DDR components to place Cep63 within signaling hierarchies. For example, deplete ATM or ATR kinases to determine their requirement for Cep63 regulation following damage.

• Cell fate correlation: Integrate SPCC63.06 staining with markers of apoptosis, senescence, or cell cycle checkpoints to correlate Cep63 dynamics with cellular outcomes following DNA damage.

This comprehensive approach can uncover previously unknown connections between centrosome regulation and genome maintenance mechanisms .

What methodological approaches are recommended for using SPCC63.06 antibody in co-immunoprecipitation experiments?

For successful co-immunoprecipitation (co-IP) experiments with SPCC63.06 antibody, implement this optimized methodological approach:

• Lysis buffer optimization:

  • Test multiple lysis buffers to preserve protein-protein interactions

  • Start with mild non-ionic detergents (0.5% NP-40 or 1% Triton X-100)

  • Include phosphatase inhibitors (sodium fluoride, sodium orthovanadate) and protease inhibitors

  • Add low concentrations of salt (120-150 mM NaCl) to maintain ionic interactions

• Antibody immobilization strategies:

  • Compare direct antibody coupling to protein A/G beads versus pre-formed antibody-protein complexes

  • For covalent coupling, use cross-linking agents (DSS or BS3) to prevent antibody leaching

  • Determine optimal antibody:bead ratio through titration experiments (typically 2-5 μg antibody per 50 μl bead slurry)

• Binding and washing conditions:

  • Optimize incubation time (2h versus overnight) and temperature (4°C is typically preferred)

  • Implement stringent washing protocol (3-5 washes) with increasing salt concentrations

  • Consider detergent adjustment in wash buffers to reduce background

• Elution techniques:

  • Compare harsh elution (SDS sample buffer) versus native elution (peptide competition)

  • For preserving activity of co-precipitated proteins, use gentle elution methods

• Validation approaches:

  • Perform reverse co-IPs with antibodies against interacting partners

  • Include IgG control and input samples in all Western blot analyses

  • Quantify enrichment through densitometry normalized to input levels

This methodology, similar to approaches used for characterization of antibody binding kinetics in other studies, enables reliable detection of even transient or weak protein-protein interactions involving Cep63 .

How does SPCC63.06 antibody performance compare to site-specific conjugation approaches in advanced imaging applications?

SPCC63.06 antibody performance in advanced imaging applications can be systematically compared to site-specific conjugation approaches, revealing important methodological considerations:

Conventional antibody approach (SPCC63.06):

• Provides excellent specificity through epitope recognition

• Requires indirect immunofluorescence (primary + secondary) for signal amplification

• Limited by antibody penetration in thick specimens

• May cause steric hindrance at crowded cellular structures

• Typically achieves 20-40 nm localization precision in super-resolution applications

Site-specific conjugation alternatives:

• SNAP/HALO-tag fusion proteins:

  • Enable direct covalent labeling with synthetic fluorophores

  • Allow pulse-chase experiments for protein turnover studies

  • Achieve 10-15 nm localization precision in super-resolution microscopy

  • Potential concern: tag size (20 kDa) may interfere with protein function

• Engineered reactive cysteine approaches (similar to ThioMab technology):

  • Generate homogeneous labeling with precise dye-to-protein ratio

  • Reduce background through controlled conjugation chemistry

  • Superior for quantitative fluorescence applications

  • Limitation: requires protein engineering and expression validation

• Unnatural amino acid incorporation:

  • Enables minimal perturbation labeling at defined positions

  • Provides superior signal-to-noise ratio in live-cell applications

  • Achieves maximum specificity without antibody cross-reactivity issues

  • Challenge: complex implementation requiring specialized expression systems

When selecting between these approaches, researchers should consider the specific experimental requirements, including temporal resolution needs, sample type, and whether native protein or overexpression systems will be used. For certain applications requiring single-molecule sensitivity or minimal perturbation, site-specific approaches may outperform conventional antibodies despite their technical complexity .

How might SPCC63.06 antibody be adapted for therapeutic development similar to other targeted antibody therapies?

The potential adaptation of SPCC63.06 antibody for therapeutic applications would follow developmental pathways similar to other successful targeted antibody therapies, with centrosome-targeting specificity as its distinctive advantage:

• Antibody-drug conjugate (ADC) development potential:
  SPCC63.06 could be engineered as an ADC targeting centrosome abnormalities in cancer, following established conjugation principles. The antibody would need modification through one of several conjugation chemistries:

  • Conventional lysine conjugation (similar to gemtuzumab ozogamicin) allowing multi-site payload attachment

  • Cysteine-based conjugation after reduction of interchain disulfide bonds

  • Site-specific conjugation using engineered reactive cysteines for homogeneous drug-antibody ratio (DAR)

  • Enzyme-assisted ligation using formyl glycine-generating enzyme (FGE) or transglutaminase (TG)

  Each approach offers different stability and efficacy profiles that would require optimization for centrosome-directed therapy.

• Target validation requirements:

  • Demonstrate differential expression of Cep63 between normal and cancer cells

  • Establish mechanisms for antibody internalization in target cells

  • Verify tumor accessibility through tissue penetration studies

  • Confirm therapeutic window through normal tissue cross-reactivity studies

• Payload selection considerations:

  • DNA-damaging agents might synergize with centrosome targeting

  • Microtubule inhibitors could enhance mitotic catastrophe in cells with centrosome abnormalities

  • Tubulin binders (auristatins, maytansinoids) remain promising for their potency at low concentrations

• Translational development pathway:

  • Humanization to reduce immunogenicity

  • Fc engineering to enhance effector functions or extend half-life

  • Optimization of drug-antibody ratio for efficacy/safety balance

  • Development of companion diagnostics to identify responsive patient populations

While conceptually promising, this approach would require extensive preclinical validation to establish Cep63 as a viable therapeutic target with sufficient tumor specificity to provide a therapeutic window .

What emerging technologies could enhance the utility of SPCC63.06 antibody in single-cell analysis?

Emerging technologies promise to dramatically enhance SPCC63.06 antibody applications in single-cell analysis through integration with cutting-edge platforms:

• Mass cytometry (CyTOF) integration:

  • Metal-conjugated SPCC63.06 antibodies enable simultaneous detection of 40+ proteins

  • Eliminates autofluorescence and spectral overlap limitations

  • Correlates centrosome abnormalities with complex cellular phenotypes

  • Challenge: requires metal conjugation optimization and signal calibration

• Spatial transcriptomics combination:

  • MERFISH or Visium platforms combined with SPCC63.06 immunofluorescence

  • Correlates centrosomal protein localization with transcriptional states

  • Maps spatial relationship between centrosomes and gene expression domains

  • Implementation: requires multi-round imaging protocols and computational integration

• Live-cell biosensor technologies:

  • SPCC63.06-derived single-chain variable fragments (scFvs) fused to fluorescent reporters

  • Enables real-time tracking of centrosome dynamics without fixation artifacts

  • Potential for optogenetic control of centrosome-associated proteins

  • Development path: requires antibody fragmentation and extensive validation

• Microfluidic single-cell Western blotting:

  • Quantifies Cep63 protein levels in individual cells

  • Correlates with other signaling proteins at single-cell resolution

  • Overcomes averaging effects in heterogeneous populations

  • Technical consideration: requires miniaturized immunoblotting optimization

• Super-resolution expansion microscopy:

  • Physical expansion of specimens improves resolution with standard microscopes

  • Reveals nanoscale organization of centrosome components

  • Compatible with standard SPCC63.06 immunofluorescence protocols

  • Protocol adaptation: optimize anchoring and expansion conditions for centrosomal structures

These technologies transform antibody-based detection from qualitative observation to quantitative, spatially-resolved single-cell analysis with unprecedented detail and dimensionality .

How can computational approaches improve data analysis when working with SPCC63.06 antibody in large-scale microscopy studies?

Advanced computational approaches can significantly enhance data extraction and interpretation from large-scale microscopy studies using SPCC63.06 antibody:

• Deep learning-based image analysis:

  • Convolutional neural networks (CNNs) trained to identify centrosome structures with high accuracy

  • U-Net architectures for precise segmentation of centrosomal structures

  • Transfer learning approaches requiring fewer training images for new experimental contexts

  • Implementation pathway: develop training datasets with expert-annotated centrosome images

• Multi-parametric phenotypic profiling:

  • Extract 200+ morphological features from each cell (centrosome number, size, intensity, texture, etc.)

  • Implement dimensionality reduction techniques (UMAP, t-SNE) to visualize cellular phenotypes

  • Apply clustering algorithms to identify distinct centrosome abnormality patterns

  • Correlation analysis linking centrosome features to cellular outcomes

• Integrative multi-omics analysis frameworks:

  • Combine imaging data with transcriptomics or proteomics using canonical correlation analysis

  • Graph-based data integration linking centrosome phenotypes to molecular signatures

  • Causal inference methods to establish relationships between centrosome changes and cellular responses

  • Software solutions: Develop R/Python packages specifically for centrosome-related datasets

• Automated quality control and artifact detection:

  • Machine learning algorithms to identify technical artifacts in large datasets

  • Automated outlier detection based on multivariate statistical approaches

  • Standardized metrics for immunostaining quality assessment across experiments

  • Implementation: Deploy pretrained models for automated QC in image analysis pipelines

• Cloud-based collaborative analysis platforms:

  • Web-based tools for sharing and analyzing centrosome imaging datasets

  • Standardized analysis workflows ensuring reproducibility across laboratories

  • Version control for analysis parameters and processing steps

  • Development strategy: Adapt existing platforms (CellProfiler, QuPath) with centrosome-specific modules

These computational approaches transform the scale and depth of information extraction from SPCC63.06 antibody experiments, enabling discovery of subtle phenotypes and complex relationships not apparent through conventional analysis methods .