NR2F1 Antibody

What is NR2F1 and why is it significant in research?

NR2F1 (nuclear receptor subfamily 2 group F member 1), also known as COUP-TFI, is a transcription factor belonging to the steroid/thyroid hormone receptor superfamily. It plays critical roles in regulating spatiotemporal gene expression during development and in adulthood. NR2F1 has significant research importance because its aberrant expression causes Bosch-Boonstra-Schaaf Optic Atrophy Syndrome, a rare neurodevelopmental disorder. Additionally, altered NR2F1 expression is frequently observed in various cancers, where it serves as both a prognostic marker and potential therapeutic target .

What are the common alternative names for NR2F1?

When researching NR2F1 antibodies, it's important to be aware of its alternative nomenclature. NR2F1 may also be referenced as:

• COUP-TFI (Chicken Ovalbumin Upstream Promoter Transcription Factor I)

• SVP44

• BBOAS

• BBSOAS

• COUPTF1

• COUP transcription factor 1

This knowledge is crucial when conducting literature searches or ordering antibodies, as suppliers may use different nomenclature.

How should researchers select the appropriate anti-NR2F1 antibody for their specific application?

Selecting the appropriate anti-NR2F1 antibody requires careful consideration of several factors:

• Application compatibility: Different antibodies perform optimally in specific applications. For example, based on systematic comparison studies, some antibodies work better for Western blot, while others are more suitable for immunofluorescence or flow cytometry .

• Target region specificity: Consider which region of NR2F1 the antibody targets. Different antibodies recognize distinct regions of the protein, which can affect their specificity and sensitivity .

• Species cross-reactivity: Verify that the antibody recognizes NR2F1 in your species of interest. Some antibodies show cross-reactivity with multiple species (human, mouse, rat), while others are species-specific .

• Validation data: Review published literature and manufacturer data on antibody validation, particularly studies using knockout controls .

• Signal-to-noise ratio: Consider antibodies with higher signal-to-noise ratios for clearer detection, especially in techniques like immunofluorescence .

What controls should be used when validating an anti-NR2F1 antibody?

Proper controls are essential for validating anti-NR2F1 antibodies:

• Positive controls: Use cell lines or tissues known to express NR2F1 at detectable levels. For instance, certain neural crest-derived cells express NR2F1 and can serve as positive controls .

• Negative controls:

  • CRISPR/Cas9-engineered NR2F1 knockout cells

  • Wild-type vs. Nr2f1-null mice tissues

  • Cells that do not express NR2F1 (e.g., some hiPSC lines)

• Technical controls:

  • Primary antibody-only control

  • Secondary antibody-only control

  • Unstained samples to assess autofluorescence (particularly important for nucleolar analyses)

• Concentration gradients: Test different antibody concentrations to determine optimal working dilutions that minimize background while maintaining specific signal .

How can researchers discriminate between specific and non-specific signals when using NR2F1 antibodies?

Discriminating between specific and non-specific signals requires systematic verification:

• Compare multiple antibodies: Use different antibodies targeting distinct epitopes of NR2F1. Consistent localization patterns across multiple antibodies suggest specific binding .

• Knockout validation: Compare staining patterns in wild-type and NR2F1 knockout samples. Signals that persist in knockout samples indicate non-specific binding .

• Blocking peptide competition: Pre-incubate the antibody with the immunizing peptide to block specific binding sites. Signals that remain after this treatment suggest non-specific binding .

• Quantify signal-to-noise ratios: Calculate mean fluorescence intensities (MFI) in positive samples versus background in negative controls .

• Cross-validate with other techniques: Confirm protein expression using orthogonal methods such as RT-PCR, RNA-seq, or proteomics approaches .

What is the true subcellular localization of NR2F1 and how has this been misinterpreted in research?

NR2F1's true subcellular localization is primarily within the nucleoplasm, consistent with its function as a transcription factor that binds to thousands of targets including genes and their enhancers .

This misinterpretation highlights the importance of using properly validated antibodies and appropriate controls. The artificial nucleolar staining pattern may depend on:

• NR2F1 expression levels

• Fixation methods

• Tissue type

• Specific antibody used

Which anti-NR2F1 antibody produces the controversial nucleolar staining pattern and why is this significant?

The mouse monoclonal antibody clone H8132 (referenced as Ab3 in comparative studies) produces the controversial nucleolar staining pattern . This antibody has been widely used in multiple studies that reported nucleolar localization of NR2F1 in tumor cells, prostate cancer cells, and breast cancer cells .

The significance of this finding is substantial for several reasons:

What are the optimal fixation and staining protocols for detecting NR2F1 by immunofluorescence?

Optimal protocols for NR2F1 immunofluorescence detection should consider the following:

• Fixation method: Different fixation methods can affect antibody accessibility to epitopes. For NR2F1, paraformaldehyde (PFA) fixation (typically 4%) is commonly used, but the duration and temperature of fixation should be optimized for your specific cell type or tissue .

• Antibody concentration: Titrate antibody concentrations to determine the optimal working dilution. For example, when using the H8132 clone, researchers found that 1.0 μg/ml provided balanced detection of both diffuse nuclear signal and nuclear aggregates, while higher concentrations (2 μg/ml) resulted in additional cytoplasmic staining and lower concentrations (0.4 μg/ml) primarily detected aggregates .

• Permeabilization: Ensure adequate permeabilization to allow antibody access to nuclear proteins. Common reagents include Triton X-100 or methanol, but the optimal concentration and duration should be determined empirically.

• Blocking: Use appropriate blocking solutions (typically 1-5% BSA or normal serum) to reduce non-specific binding.

• Secondary antibody selection: Choose secondary antibodies with minimal cross-reactivity to other species' immunoglobulins.

• Counterstaining: Include DAPI or other nuclear stains to visualize nuclei and assess nuclear morphology .

How do different anti-NR2F1 antibodies perform in various experimental applications?

Based on comparative analysis of seven commonly used anti-NR2F1 antibodies (labeled Ab1-Ab7 in the research), performance varies significantly across applications:

Immunofluorescence (IF) Performance:

• All seven antibodies could detect overexpressed NR2F1 in the nucleus, but with different intensities.

• Some antibodies (Ab5, 6, and 7) could detect NR2F1 in IF despite not being recommended for this application by manufacturers .

• Signal-to-noise ratios varied considerably between antibodies.

Western Blot (WB) Performance:

• Different antibodies showed varying specificities and sensitivities.

• Some antibodies detected additional bands besides the expected 46.2 kDa NR2F1 band.

Flow Cytometry (FC) Performance:

• Not all antibodies are suitable for flow cytometry applications.

Specificity Across Species:

• While many antibodies react with human NR2F1, cross-reactivity with mouse and rat orthologs varies between antibodies .

For comprehensive selection, researchers should consider published comparative analyses and manufacturer's validation data, and when possible, conduct their own validation for their specific experimental conditions.

How can researchers accurately quantify NR2F1 expression levels in heterogeneous cell populations?

Accurate quantification of NR2F1 in heterogeneous populations requires a multi-faceted approach:

• Flow cytometry with validated antibodies:

  • Use antibodies specifically validated for flow cytometry

  • Include appropriate isotype controls and fluorescence-minus-one (FMO) controls

  • Consider fixation and permeabilization protocols optimized for nuclear proteins

• Single-cell analysis approaches:

  • Single-cell RNA-seq (scRNA-seq) can reveal NR2F1 expression heterogeneity

  • Studies have shown that NR2F1 is expressed in only 68% of human neural crest cells (hNCC), highlighting the importance of single-cell resolution

  • Consider co-expression analysis with known NR2F1 interactors

• Imaging-based quantification:

  • Use high-content imaging systems with validated antibodies

  • Implement appropriate image analysis algorithms to quantify nuclear signal intensity

  • Establish clear thresholds for positive vs. negative cells based on controls

  • Consider mean fluorescence intensity (MFI) measurements rather than simple positive/negative classification

• Multi-parameter approaches:

  • Combine antibodies against NR2F1 with markers of cell states or lineages

  • Consider co-staining with cell cycle markers to account for expression variations during cell cycle progression

What are the challenges in studying NR2F1 interactions with nucleolar proteins and how can they be addressed?

Studying potential NR2F1 interactions with nucleolar proteins presents several challenges:

How can researchers investigate the functional significance of NR2F1 in cancer dormancy and metastasis?

Investigating NR2F1's role in cancer dormancy and metastasis requires sophisticated approaches:

• NR2F1 manipulation strategies:

  • Use CRISPR-Cas9 knockout systems to eliminate NR2F1 expression

  • Employ inducible expression systems to control NR2F1 levels temporally

  • Utilize NR2F1-specific agonists, such as the recently identified compound that activates dormancy programs in malignant cells

• Model systems:

  • 3D culture systems including patient-derived organoids

  • Patient-derived xenograft (PDX) models

  • Genetically engineered mouse models with conditional NR2F1 expression

  • Metastasis models that recapitulate dormancy and reactivation phases

• Experimental approaches:

  • RNA sequencing to identify transcriptional changes associated with NR2F1 activation, including inhibition of cell cycle progression, mTOR signaling suppression, and metastasis inhibition

  • Neoadjuvant and adjuvant treatment paradigms with NR2F1 agonists to assess effects on disseminated tumor cells (DTCs) and macrometastatic growth

  • Long-term studies to evaluate durability of dormancy programming after cessation of treatment

  • Combination approaches with standard therapies to assess potential synergistic effects

• Biomarker development:

  • Develop reliable detection methods for NR2F1 in clinical specimens

  • Establish correlations between NR2F1 expression/activation and patient outcomes

  • Identify downstream effectors that could serve as surrogate markers for NR2F1 activity

How can researchers address inconsistent staining patterns observed with anti-NR2F1 antibodies?

Inconsistent staining patterns can be addressed through systematic troubleshooting:

• Antibody validation:

  • Verify antibody specificity using positive and negative controls

  • Consider using alternative antibodies targeting different epitopes of NR2F1

  • Check for potential cross-reactivity with related proteins (e.g., NR2F2)

• Protocol optimization:

  • Systematically vary fixation methods, durations, and temperatures

  • Test different permeabilization reagents and conditions

  • Optimize blocking solutions to reduce background staining

  • Titrate antibody concentrations to determine optimal working dilutions

• Sample-specific considerations:

  • Be aware that staining patterns may vary depending on cell type and NR2F1 expression levels

  • Consider tissue-specific processing requirements

  • Account for potential autofluorescence, particularly in nucleoli

• Technical controls:

  • Include primary antibody-only and secondary antibody-only controls

  • Use unstained samples to assess autofluorescence

  • Consider using fluorescence-minus-one (FMO) controls in multicolor experiments

• Quantitative assessment:

  • Calculate signal-to-noise ratios under different conditions

  • Measure mean fluorescence intensities to objectively compare staining patterns

  • Use image analysis software to quantify nuclear vs. nucleolar vs. cytoplasmic distribution

What are the potential causes of false positive nucleolar staining with anti-NR2F1 antibodies?

Several factors can contribute to false positive nucleolar staining:

• Antibody-specific factors:

  • Certain antibodies, particularly the mouse monoclonal antibody clone H8132, are prone to producing nucleolar-like staining patterns that are not specific to NR2F1

  • Cross-reactivity with nucleolar proteins, possibly due to epitope similarity

  • Non-specific binding of mouse IgG to nucleolar components

• Technical factors:

  • Overfixation can lead to epitope masking and non-specific binding

  • Inadequate blocking can result in high background, particularly in nucleoli

  • Excessive antibody concentration may increase non-specific binding

• Biological factors:

  • Nucleoli are dense structures that can trap antibodies

  • RNA-rich nucleolar environment may non-specifically bind certain antibodies

  • Phase separation properties of nucleoli may concentrate hydrophobic antibodies

• Cell-specific factors:

  • Certain cell types may show more pronounced nucleolar staining artifacts

  • Expression levels of NR2F1 may influence the appearance of nucleolar staining

  • Cell cycle stage can affect nucleolar morphology and apparent staining patterns

To distinguish true from false nucleolar staining, researchers should use multiple antibodies, include appropriate controls (especially knockout controls), and cross-validate with other techniques not dependent on immunostaining.

How might new antibody technologies improve the specificity and sensitivity of NR2F1 detection?

Emerging antibody technologies offer promising avenues for enhanced NR2F1 detection:

• Recombinant antibody development:

  • Single-chain variable fragments (scFvs) or single-domain antibodies with improved specificity

  • Engineered antibodies with optimized binding affinities for NR2F1 epitopes

  • Humanized versions of existing monoclonal antibodies for reduced background

• Nanobody technology:

  • Camelid-derived single-domain antibodies (nanobodies) that offer smaller size for improved tissue penetration

  • Nanobodies engineered for specific recognition of distinct NR2F1 conformational states

• Aptamer alternatives:

  • DNA or RNA aptamers selected for high-affinity binding to NR2F1

  • Peptide aptamers designed to recognize specific NR2F1 epitopes with high specificity

• Proximity-based detection systems:

  • Split fluorescent protein systems for visualizing NR2F1 interactions

  • FRET-based biosensors to detect NR2F1 conformational changes or binding events

  • Proximity ligation assays (PLA) for improved sensitivity and specificity

• Multiplexed detection approaches:

  • Mass cytometry (CyTOF) with metal-conjugated antibodies for highly multiplexed analysis

  • Multiplex immunofluorescence with spectral unmixing for simultaneous detection of NR2F1 and interaction partners

  • Spatial transcriptomics combined with protein detection for correlating NR2F1 protein localization with gene expression patterns

What are the implications of the recent findings on nucleolar NR2F1 staining for past research and future studies?

The discovery that nucleolar NR2F1 staining is an artifact has significant implications: