NR1H2 Antibody

What is NR1H2 and why is it an important research target?

NR1H2 (Nuclear Receptor Subfamily 1, Group H, Member 2), also known as Liver X Receptor beta (LXR-β), belongs to the nuclear receptor superfamily. It functions as a key regulator of macrophage activity, controlling transcriptional programs involved in lipid homeostasis and inflammation. NR1H2 preferentially binds to double-stranded oligonucleotide direct repeats with the consensus half-site sequence 5'-AGGTCA-3' and 4-nucleotide spacing (DR-4) . It plays a critical role in regulating cholesterol uptake through MYLIP-dependent ubiquitination of LDLR, VLDLR, and LRP8 . These physiological functions make NR1H2 a significant target in research related to metabolic disorders, inflammation, and lipid regulation.

Which applications are most commonly validated for NR1H2 antibodies?

Based on comprehensive antibody validation studies, NR1H2 antibodies have been successfully employed in multiple experimental applications:

For optimal results, researchers should select antibodies specifically validated for their intended application, as reactivity and optimal dilution can vary significantly between techniques .

What dilution ranges are recommended for Western blot applications with NR1H2 antibodies?

Western blot (WB) protocol optimization is critical for detecting NR1H2. Based on multiple manufacturer specifications, the following dilution ranges are recommended:

It is strongly recommended to perform preliminary titration experiments with your specific sample types, as optimal dilutions may vary depending on sample source, protein expression levels, and detection methods . The observed molecular weight for NR1H2 in Western blot applications is consistently reported at approximately 51 kDa .

How do epitope selection and antibody clonality affect NR1H2 detection across different experimental contexts?

Epitope specificity significantly impacts experimental outcomes when investigating NR1H2. The available antibody products target distinct regions of the protein:

Monoclonal antibodies offer higher specificity but potentially lower sensitivity, making them ideal for applications requiring precise target recognition. Polyclonal antibodies typically provide stronger signals by recognizing multiple epitopes but may exhibit higher background in some applications .

For cross-species studies, researchers should note that sequence homology varies by region. Antibodies targeting highly conserved domains show greater cross-reactivity (human/mouse/rat/pig) , while those targeting variable regions may be species-specific.

What are the optimal tissue fixation and antigen retrieval methods for immunohistochemical detection of NR1H2?

Immunohistochemical detection of NR1H2 requires careful consideration of tissue preparation methodology:

Based on systematic studies across multiple tissue types (n=1267 images analyzed), successful IHC protocols for NR1H2 typically employ:

• Fixation: 10% neutral buffered formalin fixation for 24-48 hours yields optimal results

• Sectioning: 4-5μm sections mounted on positively charged slides

• Antigen Retrieval: Heat-induced epitope retrieval (HIER) in citrate buffer (pH 6.0) for 20 minutes

• Blocking: 3-5% normal serum (species-dependent on secondary antibody)

• Primary Antibody Incubation: Dilution ranges of 1:20-1:50 for optimal staining

• Detection System: HRP-polymer based detection systems yield superior results compared to biotin-based methods

The Human Protein Atlas project has comprehensively validated NR1H2 antibodies across 44 normal human tissues and 20 common cancer types, providing a robust reference for expected staining patterns .

How should researchers address potential cross-reactivity concerns when using NR1H2 antibodies?

Cross-reactivity validation is essential for meaningful NR1H2 research. Multiple approaches should be employed:

• Knockout/Knockdown Controls: The definitive validation control utilizes samples from NR1H2 knockout/knockdown models. Published literature includes at least 4 studies using this gold-standard approach .

• Peptide Competition Assays: Pre-incubation with immunizing peptide should abolish specific staining. Some manufacturers offer blocking peptides specifically designed for their NR1H2 antibodies .

• Cross-Species Reactivity Analysis: Predicted reactivity based on epitope conservation:

  • Human: 100% (reference sequence)

  • Dog: 90% homology

  • Guinea Pig: 86% homology

  • Rat: 86% homology

  • Horse: 79% homology

• Multiple Antibody Comparison: Using antibodies targeting different epitopes can confirm specificity. The Human Protein Atlas employed this strategy across their tissue microarray validation studies .

When publishing results, researchers should document which validation approaches were employed, as these significantly impact the interpretation of experimental outcomes.

What is the normal tissue distribution pattern of NR1H2 and how should this influence experimental design?

Understanding NR1H2's tissue-specific expression pattern is crucial for experimental design and interpretation:

The comprehensive Human Protein Atlas evaluation analyzed NR1H2 expression across 44 normal tissues, 11 brain regions, and 25 disease tissues, establishing baseline expression patterns for comparative studies . When designing experiments targeting specific tissues, researchers should select antibodies validated in their tissue of interest, as detection efficiency can vary by tissue type.

What methodological considerations are important for studying NR1H2 in disease models?

When investigating NR1H2 in pathological contexts, several methodological considerations are critical:

• Disease-Specific Expression Changes: The Human Protein Atlas has documented NR1H2 expression changes in multiple disease states, including:

  • Alzheimer's disease (brain tissue)

  • Atherosclerosis (arterial tissue)

  • Carcinomas (lung, breast, colon, ovary, pancreas, prostate)

  • Inflammatory conditions (Crohn's disease, rheumatoid arthritis)

• Control Selection: Appropriate control tissues must be matched for:

  • Age and sex of donor

  • Anatomical region (particularly critical for brain studies)

  • Fixation methodology and duration

  • Processing method

• Quantification Approaches: For comparing disease vs. normal tissues:

  • Use digital image analysis with standardized exposure settings

  • Employ multiple antibodies targeting different epitopes

  • Include isotype controls to assess background staining

  • Consider multiplexed approaches to evaluate co-localization with disease markers

• Statistical Analysis: When comparing expression levels between disease models and controls, apply appropriate statistical tests based on sample distribution and experimental design.

What are the technical challenges in ChIP applications with NR1H2 antibodies and how can they be addressed?

Chromatin Immunoprecipitation (ChIP) with NR1H2 antibodies presents specific technical challenges:

• Cross-linking Optimization: As a nuclear receptor that binds DNA, NR1H2 requires careful cross-linking optimization:

  • Standard formaldehyde cross-linking (1% for 10 minutes) may be insufficient

  • Consider dual cross-linking approaches (DSG followed by formaldehyde)

  • Evaluate cross-linking efficiency through sonication testing

• Antibody Selection: Only specific NR1H2 antibodies are validated for ChIP applications:

  • Look for antibodies specifically tested in ChIP/ChIP-seq applications

  • Consider antibodies targeting the DNA-binding domain for direct binding studies

  • Polyclonal antibodies targeting internal regions have shown success in published ChIP applications

• Control Strategies:

  • Input controls are essential for normalization

  • IgG controls (matched to host species) assess non-specific binding

  • Known NR1H2 binding sites can serve as positive controls

  • Regions without predicted binding sites serve as negative controls

• Data Analysis Considerations:

  • NR1H2 binds preferentially to DR-4 motifs (direct repeats with consensus half-site sequence 5'-AGGTCA-3')

  • Peak calling algorithms should be optimized for transcription factor binding patterns

  • Integration with transcriptomic data enhances functional interpretation

How can multiplexed immunofluorescence approaches be optimized for studying NR1H2 interactions with other proteins?

Multiplexed immunofluorescence offers powerful insights into NR1H2's protein-protein interactions and cellular context:

• Antibody Compatibility Planning:

  • Select NR1H2 antibodies from different host species than interaction partner antibodies

  • If using same-species antibodies, employ sequential staining with intermediate blocking steps

  • Test for cross-reactivity between secondary antibodies

• Epitope Retrieval Harmonization:

  • Identify compatible antigen retrieval conditions for all target proteins

  • Consider tyramide signal amplification for low-abundance targets

  • Validate multiplex protocol against single-stain controls

• Spectral Considerations:

  • Select fluorophores with minimal spectral overlap

  • Include single-stain controls for spectral unmixing

  • Consider autofluorescence quenching (especially important in liver tissue)

• Analysis Approaches:

  • Employ cell-by-cell colocalization analysis

  • Consider proximity ligation assays for direct interaction studies

  • Quantify subcellular distribution patterns using digital image analysis

What experimental approaches can address contradictory findings in NR1H2 research?

Research discrepancies in NR1H2 studies often stem from methodological differences. Systematic approach to resolving contradictions includes:

• Antibody Characterization Discrepancies: Different antibodies may yield contradictory results due to:

  • Epitope differences (N-terminal vs. internal vs. C-terminal)

  • Clonality differences (monoclonal vs. polyclonal)

  • Cross-reactivity with related proteins (particularly NR1H3/LXRα)

  Resolution Strategy: Employ multiple antibodies targeting different epitopes, including at least one validated through knockout/knockdown studies .

• Species Differences: NR1H2 function may vary between species:

  • Human NR1H2: 461 amino acids

  • Mouse/Rat: Sequence divergence in regulatory domains

  • Other species: Variable conservation

  Resolution Strategy: Confirm antibody reactivity in your species of interest through validated controls.

• Isoform Detection: Alternative splicing may generate multiple NR1H2 isoforms:

  • Standard Western blot protocols may not resolve all isoforms

  • Isoform distribution may vary by tissue type

  Resolution Strategy: Use high-resolution gel systems (gradient gels) and antibodies targeting conserved regions.

• Context-Dependent Regulation: NR1H2 function is modulated by:

  • Ligand binding state

  • Post-translational modifications

  • Cofactor availability

  Resolution Strategy: Characterize experimental conditions thoroughly, including cell type, treatment conditions, and timepoints.

What are the best practices for quantifying NR1H2 expression levels across different experimental platforms?

Quantitative assessment of NR1H2 requires platform-specific considerations:

• Western Blot Quantification:

  • Use housekeeping controls appropriate to your experimental context

  • Consider total protein normalization (Ponceau S, REVERT staining)

  • Ensure signal is within linear range of detection

  • Report relative expression with appropriate statistical analysis

• Immunohistochemistry Quantification:

  • Standardize staining conditions across all samples

  • Use digital image analysis for objective quantification

  • Report both staining intensity and percentage of positive cells

  • Consider established scoring systems (H-score, Allred score)

• qPCR for mRNA Expression:

  • Validate primer specificity through melt curve analysis and sequencing

  • Use multiple reference genes for normalization

  • Consider absolute quantification with standard curves

  • Report fold-changes with appropriate statistical analysis

• Cross-Platform Validation:

  • Correlate protein levels (Western blot) with mRNA expression (qPCR)

  • Validate spatial distribution with immunohistochemistry

  • Consider functional assays to correlate expression with activity

These methodological approaches ensure robust, reproducible quantification across experimental platforms.