ccdc153 Antibody

What is CCDC153 and why is it of interest to researchers?

CCDC153 (Coiled-coil domain containing 153) is a protein whose properties are still being elucidated in ongoing research. Current evidence suggests it functions as a neuronal subtype marker (PMID: 28166221) and is also known as Dynein regulatory complex protein 12 (DRC12) . The protein has a calculated molecular weight of 24 kDa, though it often appears as a dimer at 45-48 kDa in Western blot analyses .

CCDC153 is of interest to researchers studying:

• Neuronal subtypes and classification

• Dynein regulatory complex components

• Coiled-coil domain-containing proteins and their structural functions

The gene is conserved across species with orthologs in humans (UniProt ID: Q494R4), mice (P0C7Q1), and rats (Q5FVL4), making it suitable for comparative studies .

What are the key differences between polyclonal and monoclonal antibodies against CCDC153?

When selecting between these antibodies, researchers should consider the specific experimental requirements, including sensitivity needs and the importance of epitope specificity.

What are the optimal conditions for using CCDC153 antibody in Western blot applications?

For optimal Western blot results with CCDC153 antibody:

Sample Preparation:

• Include positive controls such as COLO 320 cells, HepG2 cells, or human brain tissue where CCDC153 is expressed

• Prepare total protein extracts using standard lysis buffers (RIPA or NP-40)

• Load 20-30 μg of total protein per lane

Protocol Optimization:

• Dilution range: Use 1:500-1:2000 for most polyclonal antibodies

• Expected band: Look for the 45-48 kDa band (dimer) rather than the calculated 24 kDa monomer

• Blocking: 5% non-fat milk or BSA in TBST (1 hour at room temperature)

• Primary antibody incubation: Overnight at 4°C with gentle rocking

• Secondary antibody: Anti-rabbit HRP (1:5000-1:10000) for 1 hour at room temperature

Troubleshooting:

• If bands are weak, increase antibody concentration or extend incubation time

• If high background occurs, increase washing steps or dilute antibody further

• For multiple bands, consider using a more specific monoclonal antibody or additional blocking steps

The observed molecular weight (45-48 kDa) being larger than the calculated weight (24 kDa) is a characteristic feature of CCDC153 detection and represents dimerization rather than non-specific binding .

How should researchers optimize immunohistochemistry protocols for CCDC153 detection in tissue samples?

Tissue Preparation and Antigen Retrieval:

• Fix tissues in 10% neutral buffered formalin and embed in paraffin

• Cut sections at 4-6 μm thickness

• For antigen retrieval, use TE buffer pH 9.0 (primary recommendation) or alternatively citrate buffer pH 6.0

• Heat-induced epitope retrieval: 95-98°C for 15-20 minutes followed by 20 minutes cooling

Staining Protocol:

• Antibody dilution: 1:20-1:200 for polyclonal antibodies

• Primary antibody incubation: 1 hour at room temperature or overnight at 4°C

• Detection system: HRP/DAB or fluorescence-based systems are suitable

• Counterstain: Hematoxylin for brightfield or DAPI for fluorescence

Positive Controls:

• Human prostate hyperplasia tissue has shown consistent positive results

• Include positive controls in each experiment to validate staining patterns

Expected Results:

• CCDC153 immunoreactivity patterns will depend on tissue type

• Compare staining patterns with publicly available data from Human Protein Atlas for reference

For challenging tissues, titration of antibody concentration and optimization of antigen retrieval time may be necessary to balance signal intensity with background staining.

How can researchers address the discrepancy between predicted and observed molecular weight of CCDC153 in experimental data?

The discrepancy between CCDC153's calculated molecular weight (24 kDa) and its observed molecular weight (45-48 kDa) on Western blots represents a significant consideration in experimental design . Several approaches can help researchers address this:

Analytical Approaches:

• Denaturing conditions analysis: Compare reducing vs. non-reducing conditions to determine if disulfide bonds contribute to dimerization

• Cross-linking studies: Utilize protein cross-linking agents to stabilize potential complexes before SDS-PAGE

• Mass spectrometry validation: Confirm protein identity through peptide mass fingerprinting of the 45-48 kDa band

• 2D gel electrophoresis: Separate based on both isoelectric point and molecular weight to identify potential post-translational modifications

Experimental Validation:

• Run protein samples alongside recombinant CCDC153 expressing only the monomeric form

• Include both positive controls (COLO 320 or HepG2 cells) and negative controls

• Consider size-exclusion chromatography before Western blotting to separate monomeric and dimeric forms

The research literature suggests that CCDC153 frequently appears as a dimer on Western blots , indicating that this observation is a characteristic feature rather than an experimental artifact. This dimerization may have functional significance in its role within the dynein regulatory complex.

What experimental approaches should be used to investigate CCDC153's suggested role as a neuronal subtype marker?

Based on the limited characterization of CCDC153 and its potential role as a neuronal subtype marker (PMID: 28166221) , the following experimental approaches are recommended:

Neuronal Subtype Profiling:

• Perform immunohistochemistry on brain sections from different regions to map CCDC153 expression patterns

• Combine with established neuronal subtype markers (NeuN, calbindin, parvalbumin, etc.) in co-localization studies

• Analyze differential expression across development stages to identify temporal patterns

Functional Characterization:

• Use RNAi or CRISPR-Cas9 to knock down/out CCDC153 in neuronal cultures and assess phenotypic changes

• Perform electrophysiological recordings of CCDC153-positive neurons to determine functional properties

• Investigate protein-protein interactions within the dynein regulatory complex to understand mechanistic roles

Transcriptomic Analysis:

• Conduct single-cell RNA sequencing of CCDC153-positive versus negative neuronal populations

• Create a correlation matrix of CCDC153 expression with known neuronal subtype markers

• Develop a transcriptomic signature for CCDC153-positive cells

Validation in Disease Models:

• Examine CCDC153 expression in neurodevelopmental and neurodegenerative disease models

• Assess whether CCDC153 patterns are altered in pathological states

This multi-modal approach will help establish whether CCDC153 is merely correlated with specific neuronal subtypes or plays a causative role in neuronal differentiation or function.

How do different immunogen designs for CCDC153 antibodies affect epitope recognition and experimental outcomes?

Different manufacturers use various immunogen designs for CCDC153 antibodies, which significantly impacts epitope recognition and experimental results:

Impact on Experimental Outcomes:

• N-terminal targeting antibodies may fail to detect processed forms lacking this region

• C-terminal antibodies provide more consistent detection when protein processing occurs

• Fusion protein immunogens typically yield antibodies with broader application range but require more extensive validation

When inconsistent results occur between antibodies targeting different regions, researchers should:

• Compare staining patterns using multiple antibodies targeting different epitopes

• Validate using recombinant expression systems with tagged CCDC153

• Consider the biological context (tissue type, processing events) when interpreting discrepancies

What are the most effective troubleshooting strategies for non-specific binding or weak signal when using CCDC153 antibodies?

Common Issues and Solutions Matrix:

Advanced Troubleshooting for CCDC153-Specific Issues:

• If the expected 45-48 kDa band is absent but smaller fragments appear, consider potential proteolytic degradation during sample preparation

• For neuronal tissues showing variable staining, compare fixation methods (4% PFA vs. 10% NBF) to optimize epitope preservation

• When signals differ between monoclonal and polyclonal antibodies, verify epitope accessibility in your specific sample preparation

Validation Controls:

• Use COLO 320 cells, HepG2 cells, or human brain tissue as positive controls

• Consider peptide blocking experiments to confirm antibody specificity

• Implement siRNA knockdown validation in cell lines expressing CCDC153

How might researchers leverage CCDC153 antibodies to explore the protein's potential role in the dynein regulatory complex?

Given CCDC153's identification as Dynein regulatory complex protein 12 (DRC12) , researchers can employ several strategies to investigate its function:

Co-immunoprecipitation Studies:

• Use CCDC153 antibodies to pull down associated proteins in the dynein regulatory complex

• Analyze interacting partners through mass spectrometry

• Confirm interactions through reverse co-IP experiments with antibodies against known dynein complex components

Structural Biology Approaches:

• Employ super-resolution microscopy with CCDC153 antibodies to localize the protein within ciliary/flagellar structures

• Use proximity ligation assays to validate protein-protein interactions in situ

• Combine with transmission electron microscopy for ultrastructural localization

Functional Analysis in Model Systems:

• Create CCDC153 knockdown/knockout models in ciliated cells

• Assess ciliary motility and structure using high-speed videomicroscopy

• Examine dynein arm assembly using CCDC153 antibodies as diagnostic tools

Disease Model Applications:

• Investigate CCDC153 expression and localization in primary ciliary dyskinesia samples

• Screen for CCDC153 mutations in patients with unexplained ciliopathies

• Develop diagnostic approaches using CCDC153 antibodies for ciliary dysfunction

This multi-faceted approach will help position CCDC153 within the broader context of dynein regulatory complex biology and potentially reveal new therapeutic targets for ciliopathies.

What methodological considerations should researchers address when designing single-cell analyses of CCDC153 expression in heterogeneous tissues?

When investigating CCDC153 at the single-cell level in heterogeneous tissues, researchers should consider these methodological approaches:

Sample Preparation Optimization:

• For fixed tissues: Test multiple fixation protocols to preserve both epitope accessibility and cellular morphology

• For dissociated cells: Use gentle enzymatic dissociation methods to maintain CCDC153 epitope integrity

• Consider nuclear isolation protocols for combined DNA/protein analyses

Single-Cell Analysis Techniques:

• Flow Cytometry/FACS:

  • Use fluorophore-conjugated CCDC153 antibodies for cell sorting

  • Combine with neuronal subtype markers for multi-parameter analysis

  • Validate antibody performance in dissociated cells before full experiments

• Single-Cell Imaging:

  • Implement multiplexed immunofluorescence with sequential antibody labeling

  • Consider clearing techniques (CLARITY, iDISCO) for thick tissue sections

  • Use computational analysis to quantify co-localization patterns

• Integrated Multi-Omics:

  • Combine CCDC153 protein detection with single-cell RNA sequencing

  • Implement CITE-seq or similar approaches for simultaneous protein/RNA detection

  • Correlate CCDC153 protein levels with transcriptome profiles

Validation Strategies:

• Include known positive cell types (based on brain regions where CCDC153 is expressed)

• Perform RNA-protein correlation studies to validate antibody specificity

• Use multiple antibodies targeting different CCDC153 epitopes as cross-validation

These methodological considerations will enable researchers to accurately map CCDC153 expression at single-cell resolution, potentially revealing new insights into its neuronal subtype marker role and dynein regulatory functions.

How should researchers address the variability in reported molecular weights for CCDC153 across different experimental systems?

The observed inconsistency between CCDC153's calculated molecular weight (24 kDa) and various reported weights (predominantly 45-48 kDa) requires systematic analytical approaches :

Analytical Framework for Molecular Weight Discrepancies:

• Systematic Documentation:

  • Record experimental conditions: gel percentage, running buffer, reducing agents, sample preparation method

  • Document antibody clone/lot number and epitope region targeted

  • Compare observed weights with published literature using standardized reporting

• Biochemical Characterization:

  • Perform protein deglycosylation assays to identify potential glycosylation contributions

  • Use phosphatase treatment to assess impact of phosphorylation on migration

  • Employ chemical crosslinking to stabilize potential oligomeric states

• Expression System Comparisons:

  • Generate tagged recombinant CCDC153 in bacterial, insect, and mammalian systems

  • Compare migration patterns across expression systems to identify post-translational contributions

  • Include domain deletion constructs to map regions contributing to mobility shifts

Interpreting Common Patterns:

• The consistent observation of 45-48 kDa bands suggests stable dimerization rather than random aggregation

• Differences between predicted and observed weights may indicate biological relevance rather than technical artifacts

• Cross-validation with mass spectrometry is essential to confirm protein identity

This systematic approach allows researchers to distinguish between technical variability and biologically meaningful molecular weight differences, improving data interpretation and experimental reproducibility.

What are the best practices for validating CCDC153 antibody specificity in neurobiological research applications?

Validating antibody specificity is critical for neurobiological research where false positives/negatives can lead to significant misinterpretation. For CCDC153 antibodies, implement this comprehensive validation framework:

Multi-level Validation Strategy:

Neurobiological-Specific Considerations:

• Test antibodies on brain tissue sections from multiple species to assess cross-reactivity

• Validate in both fixed tissue and cell culture models to assess fixation effects

• Include developmental timepoints to capture potential expression dynamics

• Compare against Allen Brain Atlas or other neuroanatomical resources for expression patterns

Documentation and Reporting:

• Document all validation experiments with appropriate controls

• Report antibody catalog numbers, lot numbers, and dilutions

• Include representative images of both positive and negative controls

• Make validation data available through repositories or supplementary materials

Implementing these validation practices will strengthen the reliability of CCDC153 research in neurobiology and facilitate reproducibility across laboratories.

How can researchers effectively use CCDC153 antibodies in multiplexed immunofluorescence protocols?

Multiplexed immunofluorescence with CCDC153 antibodies requires careful optimization to maintain specificity while enabling co-detection with other markers:

Protocol Design Considerations:

• Antibody Panel Selection:

  • Consider host species compatibility (CCDC153 antibodies are available in rabbit and mouse hosts)

  • Select fluorophores with minimal spectral overlap

  • Plan panel based on subcellular localization patterns to facilitate image analysis

• Sequential Staining Approaches:

  • For same-species antibodies, implement tyramide signal amplification (TSA) with heat/chemical stripping between rounds

  • Consider zenon labeling or directly conjugated primary antibodies to avoid cross-reactivity

  • Test order effects (which antibody is applied first) as this may impact epitope accessibility

• Optimization Parameters:

  Parameter	Recommendation	Rationale
  Antibody dilution	Start with higher dilution (1:100)	Reduces background in multiplexed settings
  Blocking	10% normal serum from host of secondary antibodies	Prevents non-specific binding
  Washing	Extended PBS-T washes (4× 10 minutes)	Reduces background in multi-antibody protocols
  Counterstains	DAPI for nuclei, WGA for membranes	Provides cellular context for localization
  Controls	Single-stain controls for each fluorophore	Enables spectral unmixing if needed

• Compatible Application Examples:

  • CCDC153 + neuronal markers (NeuN, MAP2) in brain tissue sections

  • CCDC153 + ciliary markers (acetylated tubulin, ARL13B) in ciliated cells

  • CCDC153 + organelle markers to determine subcellular localization

Image Acquisition and Analysis:

• Use spectral imaging systems for highly multiplexed panels

• Implement linear unmixing algorithms to resolve spectral overlap

• Consider imaging one fluorophore at a time with sequential scanning to minimize bleed-through

• Use appropriate controls for automated segmentation and quantification

These approaches enable effective multiplexed detection of CCDC153 alongside other proteins of interest while maintaining signal specificity and quantitative reliability.

What considerations should researchers address when developing quantitative assays for CCDC153 expression levels?

Developing quantitative assays for CCDC153 requires addressing several technical considerations to ensure accuracy and reproducibility:

Quantitative Western Blot Development:

• Establish linear dynamic range by titrating protein amounts (5-50 μg)

• Include recombinant CCDC153 standard curve for absolute quantification

• Normalize to appropriate housekeeping proteins (β-actin, GAPDH) consistently expressed across samples

• Use fluorescent secondary antibodies rather than chemiluminescence for wider linear range

• Account for the dimer form (45-48 kDa) as the predominant species

ELISA and Immunoassay Development:

• Test both sandwich and competitive formats to determine optimal sensitivity

• Evaluate antibody pairs targeting different epitopes for sandwich ELISA

• Establish standard curves using recombinant CCDC153

• Determine minimal detectable concentration and working range

• Validate assay precision with intra- and inter-assay CV determination

Image-Based Quantification:

• Standardize image acquisition parameters (exposure time, gain, binning)

• Use automated analysis pipelines to reduce investigator bias

• Implement intensity calibration using fluorescent standards

• Consider z-stack acquisition to capture total cellular expression

• Normalize to cell number or area for comparative analyses

Critical Validation Steps:

• Spike-and-recovery experiments to assess matrix effects

• Dilutional linearity testing to confirm quantitative accuracy

• Cross-validation with orthogonal methods (e.g., mass spectrometry)

• Analysis of biological replicates to establish normal variation ranges