NFIA Antibody

What is NFIA and what is its significance in research?

NFIA (Nuclear Factor I/A) is a member of the NFI family of transcription factors, which in vertebrates consists of four members: NFI-A, NFI-B, NFI-C, and NFI-X. NFIA functions as a cellular transcription factor and plays critical roles in various biological processes. The protein has a calculated molecular weight of approximately 55 kDa, though it is typically observed at 60-70 kDa in western blots, likely due to post-translational modifications .

NFIA has emerged as an important research target due to its involvement in:

• Transcriptional regulation of brown fat development and function

• Development of retinal AII amacrine cells

• Glioblastoma progression through a feed-forward loop with NFκB

• Cerebellar development, often studied alongside other NFI family members

What applications are NFIA antibodies compatible with?

NFIA antibodies have been validated for multiple applications in research settings:

It is recommended to titrate each antibody in your specific experimental system to obtain optimal results, as sensitivity can be sample-dependent .

What species reactivity has been confirmed for NFIA antibodies?

Most commercially available NFIA antibodies show reactivity with:

• Human samples

• Mouse samples

• Rat samples

Some antibodies have also been tested for reactivity with dog samples . When selecting an NFIA antibody, it's important to verify the specific reactivity profile for your species of interest, as this can vary between products .

How can I validate the specificity of an NFIA antibody for my particular experiment?

Validating antibody specificity is crucial for reliable results. Based on published methodologies, consider these approaches:

• Positive control testing: Use cell lines known to express NFIA, such as A431 cells, HeLa cells, Jurkat cells, or L02 cells for Western blot validation. For tissue controls, mouse liver tissue, brain tissue, or human prostate/gliomas tissue samples have been confirmed positive .

• Knockout/knockdown validation: Compare staining between wild-type samples and those with NFIA knocked down or knocked out. Several studies have used shRNA against NFIA (shNFIA) compared to control shRNA (shCont) to validate specificity .

• Epitope blocking: Pre-incubate the antibody with the immunizing peptide before application to your sample. Specific binding should be significantly reduced.

• Cross-application validation: Test the antibody in multiple applications (e.g., if using for IHC, also validate by Western blot) to confirm target molecular weight and specificity.

• Motif analysis verification: For ChIP experiments, verify that the binding sites identified by NFIA antibodies are enriched with NFI motifs, consistent with direct DNA binding .

What are the optimal conditions for NFIA antibody use in immunohistochemistry of neural tissues?

The optimal conditions for NFIA immunohistochemistry in neural tissues, based on published protocols:

• Fixation: Perfusion with PBS followed by 4% paraformaldehyde, with post-fixation for 48-72 hours has been successfully used for cerebellar tissue .

• Antigen retrieval: Heat-mediated antigen retrieval in 10 mM sodium citrate solution (pH 6.0) at 95°C for 15 minutes is recommended for optimal staining . Some protocols alternatively suggest antigen retrieval with TE buffer pH 9.0 .

• Sectioning: Both paraffin-embedded and vibratome sections (50 μm) have been successfully used .

• Blocking: Use a solution containing 2% serum and 0.2% Triton X-100 in PBS for 2 hours .

• Antibody dilutions: For neural tissues, dilutions between 1:50 and 1:500 have been reported, with 1:400 showing good results in cerebellar tissue .

• Co-staining markers: For retinal tissue, markers such as ChAT and GFAP can be co-labeled with NFIA . For cerebellar tissue, S100β, PAX6, and Ki67 have been successfully co-stained with NFIA .

• Signal detection: Secondary antibody incubation for approximately 2 hours at room temperature, followed by DAPI counterstaining .

How does NFIA co-localize and interact with other transcription factors in functional studies?

NFIA has been shown to interact with several transcription factors, most notably with PPARγ in brown adipose tissue development. Key findings regarding these interactions include:

• NFIA and PPARγ co-localization: ChIP-seq analysis revealed that NFIA and PPARγ co-localize at brown-fat-specific enhancers. The binding of NFIA precedes and facilitates the binding of PPARγ, leading to increased chromatin accessibility and active transcription .

• Binding patterns: Genome-wide binding analysis showed that the majority of NFI binding sites are located distal to genes, similar to PPARγ. Motif analysis confirmed that NFI binding sites in brown adipocytes are strongly enriched with NFI motifs .

• Sequential binding mechanism: NFIA binding precedes PPARγ binding, suggesting a pioneer factor-like activity where NFIA helps establish accessible chromatin regions for subsequent binding of PPARγ .

• Functional consequences: Introduction of NFIA into myoblasts resulted in brown adipocyte differentiation, with induction of brown-fat-specific genes including Cidea and Ppargc1a, as well as the thermogenic gene Ucp1 .

• NFIA-NFκB feed-forward loop: In glioblastoma research, a feed-forward loop between NFIA and NFκB has been identified, where these transcription factors promote each other's expression and cooperatively regulate downstream targets .

What are the key considerations for optimizing NFIA antibody dilutions across different experimental approaches?

Optimizing antibody dilutions is essential for achieving specific signal while minimizing background. Based on published protocols:

• Western blot optimization:

  • Recommended dilution range: 1:500-1:1000

  • Start with manufacturer's recommended dilution and adjust based on signal intensity

  • Include positive controls (e.g., A431 cells, HeLa cells) to benchmark signal strength

  • Consider gradual titration series (e.g., 1:250, 1:500, 1:1000, 1:2000) to determine optimal signal-to-noise ratio

• Immunohistochemistry optimization:

  • Recommended dilution range: 1:50-1:500

  • Tissue-specific optimization may be necessary (e.g., brain tissue vs. adipose tissue)

  • Antigen retrieval methods significantly impact optimal dilution (TE buffer pH 9.0 or citrate buffer pH 6.0)

  • For neural tissues, 1:400 dilution has been effectively used with appropriate blocking

• Immunoprecipitation considerations:

  • Recommended amount: 0.5-4.0 μg antibody for 1.0-3.0 mg of total protein lysate

  • Optimization should focus on antibody-to-protein ratio rather than simple dilution

  • Pre-clearing samples can improve specificity when optimizing IP conditions

• ChIP optimization:

  • Start with antibody amounts used in published protocols (typically 2-5 μg per reaction)

  • Validate with known NFIA target regions (e.g., enhancers of Pparg, Cidea, and Ucp1)

  • Sonication conditions should be optimized separately from antibody dilution

It is strongly recommended to titrate each reagent in your specific testing system, as optimal conditions can vary based on tissue type, fixation method, and detection system .

How can I troubleshoot inconsistent results when using NFIA antibodies?

When encountering inconsistent results with NFIA antibodies, consider these troubleshooting strategies:

• Antibody storage issues:

  • Verify proper storage conditions: -20°C, avoiding repeated freeze-thaw cycles

  • Some NFIA antibodies are supplied in PBS with 0.02% sodium azide and 50% glycerol (pH 7.3)

  • For lyophilized antibodies, proper reconstitution is critical (e.g., adding 50 μL distilled water to reach 1 mg/mL)

• Sample preparation concerns:

  • NFIA is primarily nuclear, so extraction methods should effectively isolate nuclear proteins

  • For tissue samples, fixation time can significantly impact epitope accessibility

  • For brain tissue, heat-mediated antigen retrieval in sodium citrate solution (pH 6.0) at 95°C for 15 min is crucial

• Detection issues:

  • The observed molecular weight of NFIA (60-70 kDa) differs from the calculated weight (55 kDa)

  • Verify secondary antibody compatibility with host species (typically rabbit for NFIA antibodies)

  • For fluorescent detection, check for autofluorescence in your tissue type

• Specificity concerns:

  • Some NFIA antibodies may cross-react with other NFI family members

  • Confirm antibody specificity using controls such as NFIA-knockout tissues or NFIA-knockdown cells

  • Consider using multiple antibodies targeting different epitopes to validate results

• Application-specific troubleshooting:

  • For ChIP assays, verify enrichment at known NFIA binding sites like enhancers of Pparg and Ucp1

  • For IHC, test multiple antigen retrieval methods as some NFIA antibodies work better with TE buffer (pH 9.0) while others prefer citrate buffer (pH 6.0)

What methodological approaches are needed when studying NFIA's role in transcriptional regulation?

Investigating NFIA's transcriptional regulatory functions requires several sophisticated methodological approaches:

• Chromatin immunoprecipitation coupled with sequencing (ChIP-seq):

  • This approach has successfully identified 12,486 and 12,748 NFI binding sites on day 0 and day 6 of differentiation, respectively

  • Motif analysis of binding sites typically shows strong enrichment of NFI motifs, confirming direct DNA binding

  • For NFIA-specific binding, some researchers have used FLAG-tagged NFIA with M2 antibody in transfected cells

• Assay for Transposase-Accessible Chromatin with sequencing (ATAC-seq):

  • ATAC-seq combined with NFIA ChIP-seq has revealed that NFIA binding increases chromatin accessibility

  • This technique helps determine whether NFIA acts as a pioneer factor in opening chromatin

• Integration with other transcription factor binding data:

  • Co-ChIP with other factors like PPARγ, C/EBPα, C/EBPβ, and EBF2 has revealed cooperative binding

  • H3K27 acetylation (H3K27Ac) ChIP-seq can identify active enhancers bound by NFIA

• Functional validation through gain/loss-of-function studies:

  • Lentiviral vectors expressing HA-tagged NFIA cDNA for overexpression studies

  • shRNA specific to human NFIA (shNFIA) for knockdown studies

  • NFIA knockout mice for in vivo validation of transcriptional targets

• Reporter assays:

  • Promoter-reporter constructs, such as the NFκB p65 (-507 to 67) and NFIA (-1400 to -450) promoter plasmids ligated into pGL3-basic vector

  • Site-directed mutagenesis of binding sites to confirm direct regulation

  • Co-transfection experiments to test cooperative activation with other factors

• RNA-seq following NFIA manipulation:

  • Hierarchical clustering of genes quantified by RNA-seq has shown global changes in gene expression caused by NFIA introduction

  • This approach helps identify direct and indirect targets of NFIA

These methodological approaches, when combined, provide a comprehensive understanding of NFIA's role in transcriptional regulation across different biological contexts.

How do polyclonal and monoclonal NFIA antibodies compare for different research applications?

When selecting between polyclonal and monoclonal NFIA antibodies, consider these application-specific differences:

Most validated NFIA antibodies in the search results are polyclonal, particularly rabbit polyclonal antibodies that have been extensively validated in Western blot, immunohistochemistry, and ChIP applications .

What are the critical parameters for using NFIA antibodies in co-immunoprecipitation studies?

When performing co-immunoprecipitation (co-IP) with NFIA antibodies to study protein-protein interactions, several critical parameters should be considered:

• Antibody selection:

  • Choose antibodies validated specifically for IP applications

  • For co-IP studies of NFIA with other transcription factors, antibodies recognizing native protein conformation are preferred

  • Some studies have successfully used anti-NFIA rabbit polyclonal antibodies (e.g., from Active Motif)

• Protein extraction conditions:

  • Use gentle lysis buffers that preserve protein-protein interactions

  • Nuclear extraction is typically necessary as NFIA is predominantly nuclear

  • Avoid harsh detergents that may disrupt weak or transient interactions

• Antibody-to-lysate ratio:

  • Recommended ratio: 0.5-4.0 μg antibody for 1.0-3.0 mg of total protein lysate

  • Optimization of this ratio is critical for specific pull-down while minimizing background

• Pre-clearing strategy:

  • Pre-clear lysates with appropriate control IgG and beads to reduce non-specific binding

  • Match the pre-clearing IgG species to the IP antibody species (typically rabbit for NFIA)

• Positive controls:

  • Include known NFIA interaction partners as positive controls

  • For studies of NFIA-PPARγ interactions, co-IP can be validated against ChIP-seq data showing co-localization

  • For NFIA-NFκB interactions, NFκB p65 has been successfully co-immunoprecipitated with NFIA

• Detection strategies:

  • For tagged NFIA, studies have successfully used HA-tagged NFIA constructs

  • When detecting multiple proteins, optimize stripping and re-probing protocols or use duplicate blots

• Validation approaches:

  • Perform reciprocal co-IPs when possible (i.e., immunoprecipitate with anti-NFIA and detect interaction partner, then reverse)

  • Compare results between native complexes and overexpressed proteins

  • Validate functional relevance of interactions through reporter assays or functional studies

What recent advancements in antibody technology are relevant to NFIA research?

Recent technological advancements relevant to NFIA antibody research include:

• Deep learning approaches for antibody design:

  • IgDesign, a deep learning method for antibody complementarity-determining region (CDR) design, has demonstrated success in designing antibody binders for therapeutic antigens

  • Such approaches could potentially be applied to develop more specific NFIA antibodies with improved binding characteristics

• Antibody validation initiatives:

  • Projects like the Human Protein Atlas have contributed to better validation of antibodies, including NFIA antibodies

  • Standardized validation protocols help ensure antibody specificity across applications

• Recombinant antibody technology:

  • Recombinant NFIA antibodies offer improved batch-to-batch consistency compared to traditional polyclonal antibodies

  • These technologies allow for engineering specific binding properties and reduced background

• Application-specific antibody development:

  • Custom antibodies designed specifically for applications like ChIP-seq or super-resolution microscopy

  • These specialized antibodies can improve signal-to-noise ratios in challenging applications

• Conjugated antibodies for multiplexing:

  • Direct fluorophore-conjugated NFIA antibodies enable multiplexed imaging with other nuclear factors

  • This is particularly valuable when studying co-localization of NFIA with other transcription factors like PPARγ or NFκB

• Single-cell applications:

  • Antibodies optimized for single-cell protein analysis techniques

  • These can help resolve heterogeneity in NFIA expression across cell populations

These technological advancements continue to expand the toolkit available for researchers studying NFIA, potentially enabling more precise and comprehensive analyses of its functions in various biological contexts.