NFYC Antibody

What is NFYC and why is it important in transcriptional regulation?

NFYC (Nuclear Transcription Factor Y, subunit gamma) is a component of the sequence-specific heterotrimeric transcription factor (NF-Y) that recognizes CCAAT motifs in promoter regions of target genes. NFYC forms a tight dimer with the B subunit, which is required for subunit A association. The resulting trimer binds DNA with high specificity and affinity .

The significance of NFYC lies in its dual role as both an activator and repressor of transcription, depending on its interacting cofactors. NF-Y regulates numerous tissue-specific genes, including those involved in the major histocompatibility complex (MHC) class II pathway and albumin gene expression, despite these genes having non-overlapping expression patterns .

How do monoclonal and polyclonal NFYC antibodies differ in research applications?

Methodologically, researchers should select antibodies based on experimental requirements. Monoclonal antibodies (such as PCRP-NFYC-1A11) offer superior specificity for detecting particular regions of NFYC and provide consistent results across experiments . In contrast, polyclonal antibodies (like those from Abcam or Proteintech) recognize multiple epitopes, increasing detection sensitivity but potentially introducing more variability .

For detecting conformational changes or post-translational modifications, polyclonal antibodies are often advantageous, while monoclonals are preferred for distinguishing between closely related proteins or isoforms.

What are the optimal protocols for Western blot detection of NFYC?

For successful Western blot detection of NFYC:

• Sample Preparation:

  • Use fresh cell lysates from relevant cell lines (HeLa, K-562) that express NFYC

  • Include protease inhibitors to prevent degradation

• Protocol Optimization:

  • Dilution Range: 1:500-1:2000 for polyclonal antibodies (Proteintech)

  • Alternate Range: 0.2-2μg/mL (1:250-1:2500) for other commercial antibodies

• Detection Parameters:

  • Expected Molecular Weight: 48-50 kDa

  • Positive Controls: Recombinant NFYC protein, HeLa cell lysate

• Troubleshooting Strategy:

  • For weak signals, decrease antibody dilution and increase exposure time

  • For high background, increase blocking time and washing steps

  • For non-specific bands, pre-adsorb antibody with non-relevant proteins

The methodological success depends on antibody validation with appropriate controls. When optimizing, verify that the antibody detects the expected molecular weight band (approximately 50.3 kDa for full-length NFYC) .

How should researchers optimize NFYC immunohistochemistry protocols for different tissue types?

Optimizing IHC protocols for NFYC detection requires tissue-specific adjustments:

• Fixation and Antigen Retrieval:

  • Formalin-fixed, paraffin-embedded tissues typically require citrate buffer-based antigen retrieval to enhance staining

  • Heat-induced epitope retrieval (HIER) is generally more effective than protease-based methods for nuclear transcription factors

• Antibody Selection and Dilution:

  • For human tissues: Start with 1:25-1:100 dilution (5-20μg/mL)

  • Validated in human breast carcinoma and mouse renal cell carcinoma

• Detection Systems:

  • DAB (3,3'-diaminobenzidine) staining provides good visualization of nuclear NFYC

  • Signal amplification methods may be necessary for tissues with low expression

• Controls and Validation:

  • Include positive control tissues with known NFYC expression

  • Use antibody-specific negative controls and isotype controls

Methodologically, researchers should perform titration experiments to determine the optimal antibody concentration for each tissue type, as NFYC expression levels vary across tissues. Antibodies targeting different epitopes may also perform differently depending on tissue fixation method and processing .

How can researchers validate NFYC antibody specificity to avoid misleading results?

A comprehensive validation approach includes:

• Multiple Antibody Verification:

  • Use antibodies targeting different epitopes of NFYC (N-terminal, C-terminal, AA 259-308)

  • Compare results from both monoclonal and polyclonal antibodies

• Genetic Controls:

  • NFYC knockdown/knockout validation

  • Overexpression studies with tagged NFYC constructs

• Peptide Competition Assays:

  • Pre-incubate antibody with immunizing peptide to confirm specificity

  • Should eliminate or significantly reduce specific signal

• Cross-Reactivity Assessment:

  • Test against other NF-Y family members (NFYA, NFYB)

  • Verify species cross-reactivity claims with appropriate controls

• Functional Validation:

  • Conduct transcriptional reporter assays to confirm antibody detection correlates with functional activity

  • Test inhibition of DNA binding or transcriptional activity as demonstrated with NF-Y antibodies in MHC class II gene regulation

The gold standard approach combines multiple validation methods, particularly important when studying transcription factors with potential isoforms or family members with high sequence homology.

What are the most common issues with NFYC antibodies in immunofluorescence applications and how can they be addressed?

For optimal results with immunofluorescence:

• Use paraformaldehyde fixation (typically 4%) with Triton X-100 permeabilization for nuclear transcription factors

• Begin with recommended dilutions (e.g., 4μg/ml for ab220748)

• Include nuclear counterstains (DAPI) to confirm nuclear localization

• Consider dual-staining with other nuclear markers to validate localization patterns

When troubleshooting, methodically change one variable at a time while maintaining all others constant to identify the source of the issue.

How can NFYC antibodies be utilized to study protein-protein interactions within the transcriptional machinery?

NFYC antibodies can be powerful tools for investigating protein-protein interactions through several advanced methodologies:

• Co-Immunoprecipitation (Co-IP) Approaches:

  • Use NFYC antibodies to pull down the protein complex

  • Identify interaction partners through mass spectrometry

  • Verify known interactions with NFYA and NFYB subunits as positive controls

  • Can reveal how NFYC interacts with cofactors that determine its activator or repressor function

• Chromatin Immunoprecipitation (ChIP) Applications:

  • Map NFYC binding sites genome-wide using ChIP-seq

  • Combine with sequential ChIP to determine co-occupancy with other transcription factors

  • Investigate dynamic binding during cellular differentiation or stress responses

• Proximity Ligation Assays (PLA):

  • Visualize and quantify protein interactions in situ

  • Particularly useful for transient interactions within the transcriptional machinery

  • Can be combined with other cellular markers to study interaction in specific cellular contexts

• Functional Blocking Studies:

  • Use antibodies to block specific protein-protein interactions as demonstrated with NF-Y antibodies that inhibit transcription by blocking reinitiation but not pre-formed complexes

  • Can reveal temporal aspects of complex assembly

These approaches allow researchers to move beyond simple detection to understand the dynamic roles of NFYC in transcriptional regulation across different cellular contexts.

What are the considerations for using NFYC antibodies in studying disease-associated transcriptional dysregulation?

When investigating NFYC's role in disease contexts:

• Tissue-Specific Expression Patterns:

  • NFYC has been implicated in various diseases, including cancer, where altered expression has been observed

  • Antibody selection should consider tissue-specific epitope accessibility and expression level

  • Validation in relevant disease models is essential (e.g., gliomas where NFYC was found to be significantly increased)

• Integration with Genomic Data:

  • Correlate antibody-based protein detection with genomic alterations

  • Consider how variants like the NFKB1 insertion-deletion (rs28362491) that affect expression might influence antibody detection

• Post-Translational Modifications:

  • Disease states may alter PTMs affecting antibody recognition

  • Consider antibodies specific to modified forms when relevant

• Therapeutic Development Considerations:

  • NFYC monoclonal antibodies could be used to assess potential target accessibility

  • Study potential cross-reactivity with other transcription factors to predict off-target effects

  • Evaluate effects of antibody binding on transcription factor activity in disease models

• Longitudinal Studies:

  • Use antibodies to track changes in NFYC expression during disease progression

  • Consider epitope stability in stored samples for retrospective analyses

The methodological approach should integrate antibody-based detection with functional assays to establish causality between NFYC alterations and disease phenotypes.

How should researchers interpret conflicting results from different NFYC antibodies?

When faced with contradictory results from different NFYC antibodies:

• Epitope Mapping Analysis:

  • Compare the epitope targets of each antibody (N-terminal, C-terminal, specific amino acid regions)

  • Some antibodies target amino acids 1-263, others 259-308, 100-300, or 400+ regions

  • Different epitopes may be differentially accessible depending on protein conformation or complex formation

• Isoform Consideration:

  • NFYC has multiple transcript variants encoding different isoforms

  • Verify which isoforms each antibody detects based on the epitope location

  • Cross-reference with mRNA expression data for expected isoforms in your experimental system

• Methodological Validation:

  • Test antibodies using multiple techniques (e.g., if WB and IHC give different results)

  • Consider fixation and sample preparation effects on epitope availability

  • Implement orthogonal approaches (RNA interference, overexpression) to validate findings

• Quantitative Comparison:

  • Develop standardized quantification methods for each antibody

  • Establish detection thresholds and dynamic ranges

  • Use recombinant NFYC protein standards to calibrate sensitivity

• Resolution Strategy:

  • Report all findings with detailed methodological context

  • Consider the possibility that both results are correct but reflecting different aspects of NFYC biology

  • Design decisive experiments that can distinguish between alternative interpretations

The methodological approach should emphasize transparency in reporting antibody details and experimental conditions to facilitate interpretation of seemingly conflicting results.

What statistical approaches are most appropriate for analyzing NFYC expression data from antibody-based methods?

For robust statistical analysis of NFYC antibody data:

• Normalization Procedures:

  • For Western blots: Normalize NFYC signals to appropriate loading controls (GAPDH, β-actin, total protein)

  • For IHC/IF: Use appropriate internal controls and normalize staining intensity

  • Consider the linearity range of detection methods when quantifying

• Statistical Testing Selection:

  • For comparing two groups: t-test (parametric) or Mann-Whitney (non-parametric)

  • For multiple groups: ANOVA with appropriate post-hoc tests

  • For correlations with clinical outcomes: Kaplan-Meier survival analysis with log-rank tests

• Technical Replication Requirements:

  • Minimum of 3 technical replicates for Western blots

  • For IHC/IF: Multiple fields per sample (typically 5-10 fields)

  • Consider biological replicates more important than technical replicates

• Power Analysis for Sample Size:

  • Calculate required sample size based on expected effect size and variability

  • For IHC studies in clinical samples, power calculations should account for heterogeneity

• Advanced Analytical Approaches:

  • For high-dimensional data: Consider multivariate analyses, principal component analysis

  • For clinical correlations: Multivariate Cox regression to adjust for confounding factors

  • For single-cell analyses: Appropriate clustering and trajectory inference methods

The methodological rigor in statistical analysis should match the complexity of the biological question being addressed and account for the specific limitations of antibody-based detection methods.

How are NFYC antibodies being utilized in studying autoimmune responses and infection-related chronic conditions?

Recent research has begun exploring connections between transcription factors like NFYC and autoimmune phenomena:

• Autoantibody Profiling:

  • NFYC antibodies are being used as tools to understand how transcription factors may become targets of autoantibodies in certain conditions

  • Researchers are investigating whether molecular mimicry between pathogens and transcription factors might contribute to autoimmunity

• Post-Infection Syndrome Studies:

  • Following observations in COVID-19 patients who developed neuropsychiatric symptoms, researchers are investigating transcription factor dysregulation

  • NFYC antibodies help assess whether altered NFYC function may contribute to post-infection syndromes

• Methodological Innovations:

  • PhIP-Seq (Phage Immunoprecipitation Sequencing) combined with anti-NFYC antibodies is being used to understand cross-reactivity between antibodies against pathogens and human proteins

  • This approach helps identify potential autoimmune targets in post-infection syndromes

• Therapeutic Implications:

  • Understanding the role of NFYC in immune regulation may inform treatment approaches

  • Some studies are investigating IVIG (intravenous immunoglobulin) therapy in patients with suspected autoimmune mechanisms underlying chronic symptoms

The methodological approach involves careful validation of both commercial antibodies against NFYC and potential autoantibodies targeting NFYC or related transcription factors in patient samples.

What considerations should researchers take into account when applying NFYC antibodies in multi-omics research approaches?

Integrating NFYC antibody data into multi-omics frameworks requires:

• Cross-Platform Data Integration:

  • Correlate antibody-based protein measurements with transcriptomic data on NFYC expression

  • Consider how post-transcriptional regulation might explain discrepancies between mRNA and protein levels

  • Integrate with epigenomic data on chromatin accessibility at NFYC binding sites

• Single-Cell Applications:

  • Adapt NFYC antibodies for single-cell protein analysis techniques

  • Combine with single-cell RNA-seq to correlate NFYC protein levels with target gene expression

  • Consider spatial aspects of NFYC function using imaging mass cytometry or similar approaches

• Network Analysis Considerations:

  • Use NFYC antibody data to validate predicted transcriptional networks

  • Infer NFYC activity from downstream target expression patterns

  • Integrate with protein-protein interaction data to build comprehensive regulatory networks

• Temporal Dynamics:

  • Design time-course experiments with NFYC antibodies to capture dynamic changes

  • Correlate with temporal transcriptome and epigenome data

  • Consider using multiple antibodies targeting different epitopes to capture different functional states

• Computational Challenges:

  • Develop normalization methods that allow integration of antibody-based data with other omics data types

  • Account for different dynamic ranges and noise characteristics between platforms

  • Implement appropriate visualization tools for integrated analysis