setdb2 Antibody

What is SETDB2 and why is it important in epigenetic research?

SETDB2 (SET domain bifurcated 2) is a histone methyltransferase that specifically trimethylates lysine 9 on histone 3 (H3K9me3). This epigenetic modification maintains chromatin in a conformation where promoters become inaccessible to transcription factors, effectively silencing gene transcription . SETDB2 plays critical roles in regulating inflammatory responses, macrophage phenotype transitions, and has been implicated in cancer pathogenesis, making it a significant target for epigenetic research .

What are the key considerations when selecting a SETDB2 antibody for research applications?

When selecting a SETDB2 antibody, researchers should consider:

• Antibody specificity (validated against SETDB2 knockout/knockdown controls)

• Species reactivity (human, mouse, rat, etc.)

• Recognized epitope (N-terminal, C-terminal, or specific domains)

• Application compatibility (WB, IF, ChIP, etc.)

• Clonality (monoclonal for specific epitopes vs. polyclonal for broader detection)

• Validation data availability (published literature citations, manufacturer data)

Most commercial SETDB2 antibodies have a predicted molecular weight of 82 kDa but observe at approximately 101 kDa on Western blots .

How is SETDB2 protein structurally and functionally different from other histone methyltransferases?

SETDB2 belongs to the Class V-like SAM-binding methyltransferase protein superfamily and contains the SET domain characteristic of histone methyltransferases. Unlike some other methyltransferases, SETDB2 specifically targets H3K9 for trimethylation and has a bifurcated SET domain structure. It requires both the active site and flanking cysteine residues for its catalytic activity . SETDB2 is particularly involved in regulation of inflammatory gene expression through recruitment of H3K9me3 enrichment at the promoter regions of NF-κB-dependent genes .

Applications and Experimental Protocols

For optimal SETDB2 detection by Western blot:

• Sample preparation: Use RIPA buffer with protease inhibitors; nuclear fractionation may improve detection

• Protein loading: Load 20-50 μg of total protein per lane

• Gel percentage: Use 8-10% SDS-PAGE gels for better resolution of the ~101 kDa band

• Transfer conditions: Semi-dry or wet transfer with methanol-containing buffer

• Blocking: 5% non-fat milk or BSA in TBST (1 hour at room temperature)

• Primary antibody incubation: 1:200-1:1000 dilution in blocking buffer (overnight at 4°C)

• Detection: HRP-conjugated secondary antibody with ECL detection system

Remember that SETDB2 has an observed molecular weight of approximately 101 kDa despite a calculated weight of 82 kDa .

What are the best practices for ChIP assays using SETDB2 antibodies?

For successful SETDB2 ChIP assays:

• Crosslinking: 1% formaldehyde for 10-15 minutes at room temperature

• Sonication: Optimize to achieve 200-500 bp DNA fragments

• Antibody selection: Use ChIP-validated SETDB2 antibodies or perform validation if not available

• Immunoprecipitation: 2-5 μg antibody per ChIP reaction with overnight incubation

• Include controls:

  • Positive control: IgG ChIP

  • Negative control: Non-specific genomic region

  • Technical validation: Input chromatin

• qPCR analysis: Design primers for NF-κB binding sites on inflammatory gene promoters

Studies have successfully used this approach to demonstrate SETDB2 enrichment at NF-κB binding sites of inflammatory gene promoters (e.g., IL-1β, TNFα, IL-6) .

How can I verify SETDB2 antibody specificity in my experimental system?

To verify SETDB2 antibody specificity:

• Genetic validation:

  • Use SETDB2 knockout/knockdown cells (e.g., CRISPR-Cas9, siRNA)

  • The signal should be reduced/absent in these samples

• Epitope competition:

  • Pre-incubate antibody with the immunizing peptide

  • This should block specific binding

• Multiple antibody approach:

  • Use different antibodies recognizing distinct epitopes of SETDB2

  • Similar patterns would support specificity

• Molecular weight verification:

  • SETDB2 should appear at approximately 101 kDa in Western blots

• Subcellular localization:

  • SETDB2 is predominately nuclear in most cell types

Research by Melvin et al. used Setdb2^f/f^Lyz2Cre+ mice to confirm antibody specificity in ChIP experiments .

What are important controls when studying SETDB2-mediated H3K9 trimethylation using ChIP assays?

When studying SETDB2-mediated H3K9 trimethylation:

• Essential controls:

  • IgG control to establish background signal

  • Input chromatin (typically 1-5% of starting material)

  • H3K9me3 ChIP to confirm successful enrichment

  • SETDB2 ChIP to demonstrate direct protein binding

• Experimental validations:

  • Compare H3K9me3 levels at target promoters in SETDB2 knockdown/knockout cells

  • Include non-target regions where SETDB2 is not expected to bind

  • Sequential ChIP (SETDB2 followed by H3K9me3) to directly link SETDB2 binding with methylation

• Functional validation:

  • RNA expression analysis of genes associated with SETDB2-bound promoters

  • Reporter assays with wild-type vs. mutated binding sites

Studies have demonstrated decreased H3K9me3 at inflammatory gene promoters following coronavirus infection, corresponding to decreased SETDB2 expression .

How should I design experiments to study SETDB2 interactions with transcription factors like NF-κB and STAT3?

To study SETDB2 interactions with transcription factors:

• Co-immunoprecipitation approaches:

  • Immunoprecipitate SETDB2 and probe for NF-κB (RELA) or STAT3

  • Reverse IP to confirm interaction

  • Include appropriate controls (IgG, lysate input)

• Proximity ligation assays:

  • Visualize protein-protein interactions in situ

  • Requires antibodies from different species

• GST-pulldown assays:

  • Use recombinant GST-SETDB2 to pull down interacting partners

  • Gallagher's lab demonstrated that SETDB2 interacts with both RELA and STAT3 using this approach

• ChIP-reChIP:

  • First ChIP with SETDB2 antibody

  • Second ChIP with NF-κB or STAT3 antibodies

  • Identifies genomic regions bound by both proteins

• Functional validation:

  • Test effects of STAT3 inhibitors or NF-κB pathway modulators on SETDB2 function

  • Use STAT3 or RELA knockout/knockdown models

Research has shown STAT3 inhibits SETDB2 interaction with RELA, affecting inflammatory gene expression .

How do I interpret discrepancies between SETDB2 mRNA and protein levels in my experiments?

When facing discrepancies between SETDB2 mRNA and protein levels:

• Consider post-transcriptional regulation:

  • miRNA regulation of SETDB2 mRNA

  • mRNA stability differences

  • Alternative splicing (up to 3 different isoforms reported)

• Check protein stability and turnover:

  • SETDB2 may undergo post-translational modifications affecting stability

  • Use proteasome inhibitors to test degradation rates

• Tissue/cell-specific regulation:

  • SETDB2 regulation varies across tissues and disease states

  • In LUAD, SETDB2 expression is decreased at both mRNA and protein levels

• Experimental timing:

  • Temporal dynamics may differ between mRNA and protein regulation

  • Include multiple time points in your analysis

• Assay sensitivity:

  • Different detection methods have varying sensitivities

  • Western blot may detect only abundant protein variants

Research in macrophages following coronavirus infection showed coordinated changes in both SETDB2 mRNA and protein levels .

What are common issues encountered with SETDB2 antibodies and how can I troubleshoot them?

Common issues with SETDB2 antibodies and troubleshooting approaches:

• Weak or no signal in Western blots:

  • Increase antibody concentration or protein loading

  • Optimize incubation times and temperatures

  • Try nuclear extraction (SETDB2 is nuclear protein)

  • Test different blocking reagents (milk vs. BSA)

• Multiple bands or non-specific binding:

  • Increase washing stringency

  • Adjust antibody dilution

  • Validate with SETDB2 knockdown/knockout controls

  • Try different antibody clones or vendors

• High background:

  • Increase blocking time/concentration

  • Decrease primary antibody concentration

  • Use more stringent washing conditions

  • Try different detection systems

• Batch-to-batch variability:

  • Request lot-specific validation data from manufacturers

  • Perform in-house validation with each new lot

  • Consider using monoclonal antibodies for greater consistency

• Species cross-reactivity issues:

  • Verify species reactivity claims

  • Test antibodies raised against conserved epitopes for cross-species studies

How should I interpret changes in SETDB2 expression and function in disease models like cancer or inflammation?

When interpreting SETDB2 changes in disease models:

• In cancer contexts:

  • SETDB2 downregulation is observed in lung adenocarcinoma and correlates with worse prognosis

  • Consider both expression levels and functional activity

  • Correlate with clinical parameters (staging, metastasis, survival)

  • Assess relationship with other known oncogenic pathways

• In inflammatory conditions:

  • SETDB2 regulates macrophage phenotype transitions (inflammatory to reparative)

  • SETDB2 expression is regulated by IFNβ via JAK/STAT1 pathways

  • Reduced SETDB2 in diabetic macrophages correlates with persistent inflammation

  • STAT3 inhibits SETDB2 interaction with NF-κB (RELA)

• Context-specific considerations:

  • Cell type specificity (epithelial vs. immune cells)

  • Temporal dynamics during disease progression

  • Upstream regulatory changes

  • Downstream gene expression effects

Research has shown that SETDB2 suppression promotes inflammatory cytokine expression by preventing H3K9me3 deposition at NF-κB-dependent promoters .

How can SETDB2 antibodies be used to investigate the epigenetic regulation of inflammatory pathways in disease models?

Advanced applications for studying SETDB2 in inflammatory regulation:

• Genome-wide mapping approaches:

  • ChIP-seq to identify all SETDB2 binding sites

  • CUT&RUN for higher resolution profiling with less material

  • Integration with H3K9me3 ChIP-seq to correlate binding with function

  • Correlation with RNA-seq to link epigenetic changes to transcriptional output

• Inflammatory disease models:

  • Tissue-specific SETDB2 knockout models (e.g., Setdb2^f/f^Lyz2Cre for myeloid-specific deletion)

  • Single-cell approaches to examine heterogeneity in SETDB2 function

  • Ex vivo stimulation of patient-derived cells

• Therapeutic intervention assessment:

  • Examine SETDB2 changes following anti-inflammatory treatments

  • Develop compounds that modulate SETDB2 activity or interactions

• Multi-omics integration:

  • Combine ChIP-seq, ATAC-seq, and RNA-seq data

  • Research has shown SETDB2 suppresses inflammatory gene programs by inhibiting chromatin accessibility at NF-κB-dependent gene promoters

• Time-course studies:

  • Track SETDB2 dynamics during inflammation resolution

  • Correlate with macrophage phenotype transitions

What are the latest methodologies for studying SETDB2 protein interactions using specialized antibody-based techniques?

Cutting-edge approaches for SETDB2 protein interaction studies:

• Proximity-dependent labeling:

  • BioID or TurboID fusion with SETDB2

  • APEX2-based proximity labeling

  • Identifies the complete SETDB2 interactome without need for stable interactions

• Advanced proteomic approaches:

  • Quantitative IP-MS following SETDB2 immunoprecipitation

  • RIME (Rapid Immunoprecipitation Mass spectrometry of Endogenous proteins)

  • Cross-linking mass spectrometry (XL-MS) to capture transient interactions

• High-resolution microscopy:

  • Super-resolution imaging with SETDB2 antibodies

  • FRET/FLIM to detect protein-protein interactions in live cells

  • Single-molecule tracking to study SETDB2 dynamics

• Chromatin-focused methods:

  • HiChIP to identify long-range interactions mediated by SETDB2

  • CUT&Tag for improved chromatin profiling

  • Cleavage Under Targets and Release Using Nuclease (CUT&RUN)

• Validation approaches:

  • Protein complementation assays

  • Split luciferase assays

  • CRISPR-based tagging of endogenous proteins

Research has identified STAT3 and NF-κB (RELA) as key SETDB2 interacting partners with interaction scores of 0.40 and 0.50, respectively, in human wound macrophages .

How can I design experiments to investigate the role of SETDB2 in the context of other histone modifications and chromatin remodeling complexes?

For investigating SETDB2 in broader epigenetic contexts:

• Sequential ChIP approaches:

  • First ChIP for SETDB2 followed by second ChIP for other histone marks

  • Identify genomic regions with co-occurrence of modifications

  • Compare with single ChIP datasets to identify unique regions

• Integrative genomics:

  • Combine SETDB2 ChIP-seq with datasets for other histone marks (H3K4me3, H3K27ac, etc.)

  • Integrate with chromatin accessibility data (ATAC-seq, DNase-seq)

  • Correlate with expression data (RNA-seq)

• Protein complex purification:

  • Mass spectrometry following SETDB2 immunoprecipitation

  • Size exclusion chromatography to identify SETDB2-containing complexes

  • Density gradient separation of nuclear extracts

• Functional dependency tests:

  • Knockdown of potential complex components

  • Assess effects on SETDB2 binding and H3K9me3 deposition

  • Use targeted degradation approaches (PROTAC, dTAG)

• High-resolution imaging:

  • Co-localization studies of SETDB2 with other epigenetic regulators

  • Live-cell imaging to study dynamics of complex formation

  • 3D chromatin organization studies

Research has shown that SETDB2-mediated H3K9me3 marks prevent chromatin accessibility at inflammatory gene promoters, affecting their expression during macrophage phenotype transitions .

How can SETDB2 antibodies be used to study its role in lung adenocarcinoma progression and patient prognosis?

SETDB2 antibodies can be applied to lung adenocarcinoma research in multiple ways:

• Prognostic biomarker development:

  • Immunohistochemistry (IHC) on patient tissue microarrays

  • Correlation with clinical outcomes and survival

  • Research has shown decreased SETDB2 expression in LUAD correlates with worse prognosis

• Tissue analysis approaches:

  • Compare SETDB2 levels between tumor/normal tissues

  • Correlate with pathological stage and nodal metastatic status

  • IHC staining has demonstrated significantly lower SETDB2 in high-grade LUAD compared to low-grade or normal lung tissues

• Mechanistic studies:

  • ChIP-seq to identify SETDB2 target genes in LUAD

  • Research has shown SETDB2 suppresses NRF2 transcription by recruiting H3K9me3 at the NRF2 promoter region

  • Investigate SETDB2 regulation of oxidative stress pathways

• Functional validation:

  • SETDB2 restoration in LUAD cell lines

  • Assessment of tumor growth, migration, and stemness phenotypes

  • Correlation with NRF2 pathway activation

• Therapeutic implications:

  • Screen for compounds that restore SETDB2 expression/function

  • Target downstream pathways activated by SETDB2 loss

Research has demonstrated that SETDB2 inhibition promotes cell growth, migration ability, and stemness maintenance in LUAD models .

What methodological approaches should I use to investigate SETDB2's role in regulating macrophage phenotype transitions in wound healing and tissue repair?

For studying SETDB2's role in macrophage phenotype regulation:

• Genetic models:

  • Use Setdb2^f/f^Lyz2Cre mice for myeloid-specific SETDB2 deletion

  • Compare inflammatory to reparative phenotype transitions

  • Analyze wound healing dynamics in vivo

• Cell isolation and analysis:

  • FACS-isolate macrophage populations from wounds

  • Compare CD11b+Ly6C^hi^ (inflammatory) vs. CD11b+Ly6C^lo^ (reparative) populations

  • Analyze SETDB2 expression and function in each subset

• Multi-omics approaches:

  • RNA-seq and ATAC-seq of wound macrophages

  • Research has demonstrated SETDB2 suppresses inflammatory gene program by inhibiting chromatin accessibility at NF-κB-dependent gene promoters

  • ChIP-seq for H3K9me3 at inflammatory gene promoters

• Cytokine profiling:

  • Measure inflammatory cytokine expression (IL-1β, TNF, IL-6)

  • Correlate with SETDB2 expression levels

  • Compare normal vs. diabetic wound macrophages

• Pathway analysis:

  • Investigate IFNβ/JAK/STAT1 pathway in SETDB2 regulation

  • Examine STAT3/SETDB2/NF-κB axis interactions

  • The STAT3/SETDB2 axis has been shown to modulate macrophage phenotype during tissue repair