ERR2 Antibody

What is ERR2/NR3B2 and why is it important in research?

ERR2, also known as Estrogen-related receptor beta or NR3B2, belongs to the orphan nuclear receptor family. It is expressed in multiple tissues including liver, brain, uterus, vagina, and cervix, and plays a significant role in early placental development . ERR2 is part of a family that includes ERR-alpha (ERR1, ESRL1; NR3B1) and ERR-gamma (ESRRG; NR3B3) . Its study is important because nuclear receptors function as ligand-regulated transcription factors that control numerous physiological processes. Understanding ERR2 expression and function contributes to knowledge of developmental biology, metabolism regulation, and potential therapeutic targets in disease states.

What experimental applications are ERR2 antibodies suitable for?

ERR2 antibodies have been validated for multiple experimental techniques:

Researchers should note that each application requires specific optimization protocols, and the antibody performance may vary depending on sample preparation methods .

How can I distinguish between different ERR family members in my experiments?

The ERR family (ERR-alpha/NR3B1, ERR-beta/NR3B2, and ERR-gamma/NR3B3) shares structural similarities but has distinct tissue expression patterns and functions. To distinguish between them:

• Select antibodies raised against unique epitopes specific to ERR2/NR3B2

• Verify specificity using positive and negative controls (tissues known to express or lack ERR2)

• Perform parallel staining with isoform-specific antibodies

• Consider using Western blot to confirm the molecular weight of the detected protein (ERR2 has a distinct molecular weight from ERR-alpha and ERR-gamma)

• For gene expression studies, design PCR primers or probes that target non-homologous regions

In cases where cross-reactivity is a concern, validation using genetic knockdown or knockout systems provides the most definitive confirmation of specificity .

What is the optimal protocol for immunofluorescence detection of ERR2 in neuronal cells?

Based on successful detection protocols for ERR2 in motoneurons , the following methodology is recommended:

• Fixation: 4% paraformaldehyde in PBS for 15-20 minutes at room temperature

• Permeabilization: 0.2% Triton X-100 in PBS for 10 minutes

• Blocking: 5% normal serum (species depends on secondary antibody) with 1% BSA in PBS for 1 hour

• Primary antibody: Anti-ERR2/NR3B2 at optimized dilution (typically 1:100 to 1:500) overnight at 4°C

• Washing: 3 × 5 minutes in PBS

• Secondary antibody: Fluorophore-conjugated secondary antibody (e.g., Alexa Fluor) at 1:500 for 1 hour at room temperature

• Counterstaining: DAPI (1:1000) for nuclear visualization

• Mounting: Anti-fade mounting medium

For dual labeling with cellular markers (as demonstrated in the motoneuron studies), ensure secondary antibodies have non-overlapping emission spectra. When studying neuronal subtypes, correlation with functional properties (such as firing patterns) may require combined electrophysiological recording and immunostaining approaches .

How should I optimize Western blot protocols for ERR2 detection?

For optimal Western blot detection of ERR2:

• Sample preparation:

  • Extract proteins using RIPA buffer supplemented with protease inhibitors

  • Include phosphatase inhibitors if studying phosphorylation states

  • Heat samples at 95°C for 5 minutes in reducing sample buffer

• Gel electrophoresis:

  • Use 10% SDS-PAGE for optimal resolution of ERR2 (approximately 45-55 kDa)

  • Load 20-50 μg of total protein per lane

• Transfer:

  • Semi-dry or wet transfer to PVDF membrane (preferred over nitrocellulose for nuclear proteins)

  • Transfer at 100V for 1 hour or 30V overnight at 4°C

• Blocking:

  • 5% non-fat dry milk in TBST for 1 hour at room temperature

  • For phospho-specific detection, use 5% BSA instead of milk

• Antibody incubation:

  • Primary antibody: Anti-ERR2 at 1:1000 dilution in blocking buffer, overnight at 4°C

  • Secondary antibody: HRP-conjugated at 1:5000-1:10000 for 1 hour at room temperature

• Detection:

  • Enhanced chemiluminescence (ECL) substrate

  • Expose to X-ray film or use digital imaging systems

Include positive controls (tissues known to express ERR2, such as liver or brain extracts) and negative controls (tissues with minimal expression) to validate specificity .

How can ERR2 antibodies be used to investigate chromatin binding and transcriptional regulation?

ERR2, as a nuclear receptor, functions as a transcription factor. To investigate its chromatin binding and regulatory functions:

• Chromatin Immunoprecipitation (ChIP):

  • Cross-link cells with 1% formaldehyde for 10 minutes

  • Lyse cells and sonicate chromatin to 200-500 bp fragments

  • Immunoprecipitate with ERR2 antibody (typically 2-5 μg per reaction)

  • Reverse cross-links and purify DNA

  • Analyze by qPCR or sequencing (ChIP-seq)

• ChIP-seq analysis:

  • Focus on identification of ERR2 binding motifs

  • Compare binding sites with known estrogen response elements (EREs)

  • Integrate with transcriptome data to correlate binding with gene expression

• Re-ChIP (sequential ChIP):

  • For investigating co-localization with other transcription factors like Oct4

  • Studies have shown ERR2 interacts with Oct4 to regulate Nanog gene expression

• Methodological considerations:

  • Use highly specific antibodies validated for ChIP applications

  • Include appropriate controls (IgG, input DNA)

  • Consider cell-type specific binding patterns

This approach has been successfully employed to demonstrate how ERR2 interacts with pluripotency factors to regulate stem cell gene expression networks .

What is the relationship between ERR2 expression and cellular firing patterns in neurons?

Research has revealed an interesting correlation between ERR2 expression and neuronal firing patterns, particularly in motoneurons:

• Expression pattern findings:

  • Immediate firing motoneurons consistently express ERR2 in their nuclei

  • Delayed firing motoneurons are ERR2-negative

  • This creates a clear molecular marker for functionally distinct neuronal subtypes

• Experimental methodology:

  • Combined patch-clamp electrophysiology with post-recording immunostaining

  • Neurobiotin filling during recording allows precise identification of recorded neurons

  • Immunofluorescence detection of ERR2 (red) in neurobiotin-filled motoneurons (green)

  • Correlation of ERR2 expression with electrophysiological parameters (AHP relaxation time constants and rheobase)

• Quantitative analysis:

  • Plot of AHP relaxation time constants against rheobases for labeled motoneurons

  • Statistical analysis of the correlation between ERR2 expression and firing properties

This research demonstrates how ERR2 antibodies can be used to identify molecular markers that correlate with functional neuronal properties, potentially identifying new neuronal subtypes and regulatory mechanisms governing excitability .

How do I investigate potential interactions between ERR2 and other nuclear receptors or transcription factors?

To investigate protein-protein interactions involving ERR2:

• Co-immunoprecipitation (Co-IP):

  • Prepare nuclear extracts from cells of interest

  • Immunoprecipitate with anti-ERR2 antibody

  • Analyze precipitates by Western blot for potential interacting partners

  • Reverse Co-IP (immunoprecipitate with antibodies against suspected partners)

• Proximity Ligation Assay (PLA):

  • In situ technique to visualize protein-protein interactions

  • Requires antibodies from different species for ERR2 and interacting partner

  • Provides spatial information about where interactions occur within cells

• Bimolecular Fluorescence Complementation (BiFC):

  • Genetic approach requiring fusion proteins

  • Can be used to confirm interactions identified by Co-IP or PLA

• Mass spectrometry analysis:

  • Immunoprecipitate ERR2 complexes

  • Identify binding partners through mass spectrometry

  • Validate findings through targeted approaches

Published research has demonstrated ERR2 interactions with pluripotency factors like Oct4, providing a framework for investigating other potential protein partners .

What are common pitfalls when working with ERR2 antibodies and how can I address them?

Researchers frequently encounter these challenges when working with ERR2 antibodies:

For nuclear proteins like ERR2, adequate permeabilization is particularly important. Triton X-100 (0.2-0.5%) or methanol treatment can improve nuclear access. Additionally, antigen retrieval methods (heat-induced or enzymatic) may be necessary for formalin-fixed tissues .

How can I validate the specificity of my ERR2 antibody?

Comprehensive validation of ERR2 antibody specificity requires multiple approaches:

• Positive and negative controls:

  • Use tissues/cells known to express ERR2 (liver, brain) as positive controls

  • Use tissues with minimal expression as negative controls

  • Include species-matched IgG controls for immunostaining applications

• Molecular weight verification:

  • Confirm detection of a band at the expected molecular weight on Western blots

  • Check for absence of non-specific bands

• Genetic approaches:

  • siRNA or shRNA knockdown of ERR2

  • CRISPR/Cas9 knockout of ERR2

  • Overexpression of tagged ERR2 protein

• Multiple antibody approach:

  • Use antibodies targeting different epitopes of ERR2

  • Consistent results with different antibodies strengthen confidence in specificity

• Peptide competition:

  • Pre-incubate antibody with immunizing peptide

  • Should eliminate specific signal in Western blot or immunostaining

Documentation of these validation steps should be included in research publications to support the reliability of findings .

How can ERR2 antibodies be applied in single-cell analysis techniques?

Single-cell analysis techniques represent emerging approaches for studying ERR2 expression and function:

• Single-cell immunostaining:

  • Flow cytometry using ERR2 antibodies (requires permeabilization protocols optimized for nuclear proteins)

  • Mass cytometry (CyTOF) for multi-parameter analysis including ERR2

  • Imaging flow cytometry to correlate ERR2 expression with morphological features

• Single-cell Western blot:

  • Microfluidic platforms for protein analysis at single-cell resolution

  • Requires highly specific antibodies and optimized detection systems

• Immuno-FISH:

  • Combined detection of ERR2 protein and target gene expression

  • Particularly useful for studying transcriptional regulation in heterogeneous populations

• Spatial transcriptomics integration:

  • Correlation of protein expression (by immunostaining) with transcriptomic data

  • Allows for detailed mapping of ERR2 activity in complex tissues

These approaches enable researchers to address questions about cellular heterogeneity in ERR2 expression and function that are not accessible through bulk analysis methods .

What role does ERR2 play in cancer biology and how can antibodies help investigate this?

ERR2 has emerging roles in cancer biology that can be investigated using antibody-based approaches:

• Expression analysis in cancer tissues:

  • Immunohistochemistry to evaluate ERR2 expression in tumor vs. normal tissues

  • Correlation with clinical parameters and patient outcomes

  • Published research has shown ERR2 involvement in cervical cancer proliferation through inhibition of TGF-β signaling

• Functional studies:

  • Combined knockdown/knockout with immunostaining to validate effects

  • Investigation of downstream pathways regulated by ERR2

• Therapeutic target assessment:

  • Evaluation of compounds like DY131 that target ERR2

  • Studies have demonstrated antimitotic activity of DY131 in breast cancer through effects on ERR2 splice variants

• Methodological approaches:

  • Tissue microarrays for high-throughput screening of ERR2 expression

  • Multiplex immunofluorescence to study co-expression with other cancer markers

  • ChIP-seq to identify cancer-specific ERR2 binding sites

Through these approaches, researchers can build a comprehensive understanding of ERR2's role in cancer development, progression, and potential therapeutic targeting .

How might computational approaches enhance ERR2 antibody applications in research?

Computational approaches are increasingly important for maximizing the research potential of ERR2 antibodies:

• Epitope prediction and antibody design:

  • In silico analysis to identify unique epitopes specific to ERR2 versus other ERR family members

  • Machine learning approaches to predict antibody binding characteristics

  • These approaches can be modeled after the computational antibody design strategies demonstrated in recent nanobody research

• Automated image analysis:

  • Machine learning algorithms for quantification of immunostaining patterns

  • Deep learning for classification of ERR2 expression in different cell types

  • Particularly useful for large-scale tissue analysis

• Integrated multi-omics analysis:

  • Correlation of antibody-based protein detection with transcriptomic and epigenomic data

  • Systems biology approaches to position ERR2 within regulatory networks

• Virtual screening for ERR2 modulators:

  • Computational prediction of compounds that may affect ERR2 function

  • Follow-up validation using antibody-based detection of effects on ERR2 expression or localization

These computational approaches can significantly enhance traditional antibody applications by improving specificity, streamlining analysis, and generating new hypotheses about ERR2 function .

What are best practices for reproducibility when using ERR2 antibodies across different research labs?

Ensuring reproducibility with ERR2 antibodies requires attention to several key factors:

• Antibody selection and reporting:

  • Document complete antibody information (manufacturer, catalog number, lot number, RRID)

  • Report validation methods employed

  • Consider using antibodies cited in multiple peer-reviewed publications

• Protocol standardization:

  • Develop and share detailed protocols specifying critical parameters

  • Document all buffer compositions, incubation times, and temperatures

  • Report optimization steps undertaken

• Controls implementation:

  • Include appropriate positive and negative controls in all experiments

  • Use consistent control samples across experiments

  • Consider developing stable cell lines with defined ERR2 expression levels as reference standards

• Quantification methods:

  • Clearly describe image acquisition parameters

  • Detail analysis methods and software used

  • Make raw data available when possible through repositories

• Collaborative validation:

  • Consider multi-laboratory validation for critical findings

  • Participate in antibody validation initiatives

These practices align with broader reproducibility initiatives in biological research and help ensure that findings related to ERR2 can be reliably replicated across different research environments .