C1orf127 antibodies are primarily polyclonal and designed for research applications such as Western Blot (WB), Immunohistochemistry (IHC), and Immunoprecipitation (IP). Key features include:
All antibodies target human C1orf127, with no validated cross-reactivity to mouse/rat homologs.
Immunogen sequences vary, focusing on C-terminal or N-terminal regions.
PA5-46338 (Thermo Fisher) and HPA027654 (Sigma-Aldrich) are affinity-purified for specificity.
C1orf127 antibodies are employed to study protein expression and localization.
Cancer Tissues: The Human Protein Atlas ( ) reports C1orf127 expression in colorectal, breast, prostate, and lung cancers, though reliability scores remain "uncertain" due to limited validation.
Normal Tissues: Highest expression observed in testes and brain (olfactory bulb, hippocampus) ( ).
Extracellular Matrix: Suggested localization based on signal peptide prediction ( ).
Molecular Chaperones: Interacts with CCT3 and CCT6B, implying potential roles in protein folding ( ).
Western Blot: Detects ~65–89 kDa bands, consistent with predicted molecular weights ( ).
Immunohistochemistry: Prestige Antibody (HPA027654) shows punctate staining in brain regions (e.g., hippocampus) and basal ganglia ( ).
While C1orf127’s role in cancer is unclear, preliminary data suggest:
Survival Correlation: High expression linked to uncertain prognosis in cancers like colorectal and breast, but statistical significance (p < 0.001) is unconfirmed ( ).
Expression Patterns: Variable staining across tumor types, with no consistent overexpression observed ( ).
Functional Unknowns: C1orf127’s biological role remains elusive, limiting antibody utility to descriptive studies.
Validation Gaps: Most antibodies lack rigorous validation for IP or functional assays (e.g., only PA5-55672 tested in IHC).
Research Priorities:
Functional Studies: Investigate interactions with CCT3/CCT6B.
Cancer Mechanisms: Explore links to DNA repair or replication pathways.
C1orf127 (Chromosome 1 Open Reading Frame 127) is an uncharacterized human protein with emerging importance in various biological processes. As a protein with potential roles in gene expression regulation, cell signaling, and protein interactions, it represents a valuable target for research investigations in molecular biology, genomics, and cell biology. The development of specific antibodies against C1orf127 allows researchers to explore its expression patterns, subcellular localization, and potential interactions in different experimental contexts .
The available C1orf127 antibodies primarily include polyclonal antibodies raised in rabbits. These antibodies target different regions of the C1orf127 protein and come in various forms:
| Antibody Type | Conjugation | Applications | Target Region | Source |
|---|---|---|---|---|
| Polyclonal (PACO39942) | Non-conjugated | ELISA, IHC | 401-648AA | Rabbit |
| Polyclonal | FITC | Not specified | 401-648AA | Rabbit |
Additionally, C1orf127 recombinant protein antigens are available, which can be used for antibody competition assays and as controls in experimental validation .
C1orf127 antibodies have been validated for several research applications:
Immunohistochemistry (IHC): With recommended dilutions of 1:20-1:200, successfully tested on human adrenal gland tissue and pancreatic cancer tissue
Antibody Competition: Used to confirm specificity of other antibodies targeting C1orf127
Proper antibody validation is crucial for generating reliable and reproducible results. A comprehensive validation approach for C1orf127 antibodies should follow these methodological steps:
Cell line selection: Identify cell lines with high C1orf127 expression using proteomics databases such as PaxDB
Knockout controls: Generate CRISPR/Cas9 knockout cell lines for C1orf127 to serve as negative controls
Immunoblot validation: Compare antibody reactivity between parental and knockout cell lines using western blotting
Expression profiling: Use validated antibodies to identify cell lines with the highest endogenous expression of C1orf127
Application-specific validation: Test the antibody in your specific application (IHC, IF, IP, etc.) using appropriate positive and negative controls
This systematic approach ensures that the antibody specifically recognizes C1orf127 and minimizes the risk of false positives or misleading results.
Proper storage and handling of C1orf127 antibodies are essential for maintaining their performance and longevity:
Storage temperature: Store at -20°C or -80°C for long-term preservation
Freeze-thaw cycles: Minimize repeated freezing and thawing as this can degrade antibody quality and performance
Working aliquots: Consider preparing small working aliquots to avoid repeated freeze-thaw cycles of the entire stock
Buffer conditions: Most C1orf127 antibodies are supplied in a buffer containing 50% glycerol, 0.01M PBS at pH 7.4, with 0.03% Proclin 300 as a preservative
Handling precautions: Avoid contamination by using sterile pipette tips and tubes when handling the antibody
Optimizing IHC protocols for C1orf127 detection requires careful attention to several parameters:
Antibody dilution: Start with the recommended range (1:20-1:200) and perform a dilution series to determine optimal concentration for your specific tissue
Antigen retrieval: Test different antigen retrieval methods (heat-induced epitope retrieval with citrate buffer pH 6.0 or EDTA buffer pH 9.0) to maximize signal specificity
Detection system: Compare direct and indirect detection systems; for fluorescent detection, non-conjugated antibodies require secondary antibodies while FITC-conjugated antibodies can be visualized directly
Blocking conditions: Optimize blocking conditions (5-10% normal serum from the species of the secondary antibody) to minimize background staining
Tissue-specific considerations: For human adrenal gland and pancreatic tissues, where C1orf127 detection has been validated, consider tissue-specific fixation and processing requirements
Investigating protein-protein interactions for an uncharacterized protein like C1orf127 requires thoughtful experimental design:
Co-immunoprecipitation (Co-IP): Use validated C1orf127 antibodies to precipitate the protein along with its binding partners from cell lysates, followed by mass spectrometry identification
Proximity ligation assay (PLA): Detect and visualize potential interactions between C1orf127 and suspected binding partners in situ
Pull-down assays: Utilize the available C1orf127 recombinant protein (with His6-ABP tag) as bait to identify interacting proteins
Yeast two-hybrid screening: Employ this technique as a complementary approach to identify potential binding partners
FRET/BRET analysis: For suspected interactions, use these techniques to confirm proximity and interaction in living cells
Ensuring antibody specificity is crucial for meaningful results. Common specificity issues and their solutions include:
Cross-reactivity: Test the antibody against CRISPR/Cas9 knockout cells to confirm specificity for C1orf127
Batch-to-batch variation: Use recombinant C1orf127 protein as a positive control to normalize between experiments and antibody batches
Non-specific binding: Optimize blocking conditions and washing steps; consider using antibody diluents containing blocking agents
Epitope masking: Test different sample preparation methods (denaturation conditions for western blot, fixation protocols for IHC/IF) to ensure epitope accessibility
Background signal: Include appropriate isotype controls (rabbit IgG for polyclonal antibodies) to distinguish specific from non-specific signals
Determining the optimal antibody concentration is essential for balancing signal strength and specificity:
Titration experiments: Perform a systematic dilution series covering the recommended range (e.g., 1:20-1:200 for IHC, 1:2000-1:10000 for ELISA)
Signal-to-noise optimization: Calculate signal-to-noise ratios for each dilution to determine the concentration that maximizes specific signal while minimizing background
Positive controls: Include samples known to express C1orf127 at varying levels to assess detection sensitivity
Negative controls: Include C1orf127-negative samples or blocking peptide competitions to confirm specificity at each concentration
Reproducibility testing: Once an optimal concentration is identified, perform replicate experiments to ensure consistency
Investigating expression patterns of uncharacterized proteins like C1orf127 requires a multi-faceted approach:
Tissue microarray (TMA) analysis: Use validated C1orf127 antibodies for IHC on TMAs containing diverse human tissues to establish an expression atlas
Single-cell analysis: Combine C1orf127 antibodies with cell type-specific markers for flow cytometry or imaging-based single-cell analysis
Quantitative immunoblotting: Systematically analyze C1orf127 protein levels across cell lines and primary cells representing different tissues
Correlation with transcriptomic data: Compare protein expression data with publicly available RNA-seq datasets to identify potential discrepancies between mRNA and protein levels
Subcellular localization mapping: Use immunofluorescence with organelle markers to determine the subcellular distribution of C1orf127 in different cell types
Antibodies can be powerful tools for functional studies through targeted perturbation:
Neutralization experiments: Test whether C1orf127 antibodies can block protein function when added to living cells or in vitro systems
Intracellular antibody delivery: Explore microinjection or protein transfection methods to deliver antibodies intracellularly to disrupt C1orf127 function
Knockdown validation: Use antibodies to validate the efficiency of siRNA or CRISPR-based knockdown/knockout approaches targeting C1orf127
Inducible expression systems: Combine antibody detection with inducible expression systems to study temporal aspects of C1orf127 function
Post-translational modification analysis: Use modification-specific antibodies (if available) or general C1orf127 antibodies in combination with enzymatic treatments to investigate regulatory modifications
Digital image analysis: Use specialized software to quantify staining intensity, subcellular localization, and co-localization with other markers
Scoring systems: Develop standardized scoring systems based on staining intensity and percentage of positive cells for IHC analysis
Normalization strategies: Implement appropriate normalization to control for technical variations between specimens and batches
Statistical validation: Apply appropriate statistical tests to determine significance of observed differences in C1orf127 expression
Machine learning approaches: For large datasets, consider machine learning algorithms to identify patterns in C1orf127 expression across samples
When different methods yield conflicting results for C1orf127 detection:
Method-specific limitations: Recognize that each detection method (western blot, IHC, IF, ELISA) has inherent limitations and may detect different forms of the protein
Epitope accessibility: Consider whether sample preparation methods affect epitope accessibility differently across techniques
Antibody validation: Revisit antibody validation data to ensure specificity in each application context
Complementary approaches: Use orthogonal methods (e.g., mass spectrometry) to resolve discrepancies
Biological variability: Consider whether discrepancies reflect genuine biological variability rather than technical artifacts
Several cutting-edge technologies hold promise for advancing C1orf127 research:
CRISPR-based tagging: Endogenous tagging of C1orf127 using CRISPR/Cas9 to visualize and purify the native protein without antibodies
Proximity labeling: Techniques like BioID or APEX2 fusion to C1orf127 to identify proximal proteins in living cells
Single-molecule imaging: Super-resolution microscopy combined with site-specific labeling to track C1orf127 dynamics
Nanobodies development: Engineering of smaller antibody fragments for improved tissue penetration and reduced immunogenicity
Computational prediction: Integration of structural prediction and interaction network analysis to guide hypothesis-driven research
Researchers can play a crucial role in advancing the field through:
Rigorous validation reporting: Publish detailed antibody validation data following the guidelines for antibody characterization
Resource sharing: Contribute validated protocols and positive/negative control samples to repositories
Collaborative validation: Participate in multi-laboratory validation studies to assess reproducibility
Feedback to suppliers: Provide detailed feedback to antibody suppliers regarding performance in specific applications
Open science practices: Share raw data from antibody testing to help build community consensus on reliable reagents