SETDB1 (UniProt: Q15047), also known as ESET or KMT1E, is a histone H3K9 methyltransferase involved in transcriptional repression and heterochromatin formation. Antibodies targeting SETDB1 are essential for investigating its roles in immune regulation, cancer biology, and viral latency .
Applications:
| Application | Dilution Range | Validated Reactivity |
|---|---|---|
| Western Blot | 1:20,000–1:100,000 | Human, Mouse, Rat |
| IHC | 1:500–1:2,000 | Human colon, mouse/rat liver |
| IF/ICC | 1:400–1:1,600 | A431 cells |
Molecular Weight: 170–180 kDa (observed) vs. 143 kDa (calculated), reflecting post-translational modifications .
Epitope: Derived from a recombinant SETDB1 fusion protein (Ag21644).
Specificity: Human SETDB1 (cross-reacts with rat).
Host/Isotype: Mouse IgG1.
B Cell Maturation: SETDB1 antibodies validated knockout models show arrested pro-B cell development due to ERV derepression (e.g., MLV upregulation) .
T Cell Regulation: SETDB1 ablation in CD4+ T cells promotes Th1 differentiation via ERV-mediated enhancer activation .
Mechanism: SETDB1 antibodies (e.g., 66293-1-Ig) confirmed SETDB1’s role in silencing endogenous retroviruses (ERVs) like MMTV and MLV through H3K9me3 deposition :
| ERV Type | Fold Upregulation (SETDB1 KO) | Chromosomal Loci |
|---|---|---|
| MuLV | Up to 877× | Chr8, Chr1, Chr11 |
| MMTV | 10.5–30.6× | Chr12, Chr6, Chr4 |
Microarray Analysis: SETDB1 depletion in pro-B cells upregulated immune response genes (GO:0006955, P = 5.42×10⁻²²) :
| Gene | Function | Fold Change |
|---|---|---|
| Il4i1 | B cell activation | ↑3.2× |
| Cd38 | Immune signaling | ↑4.5× |
| H2-Aa | Antigen presentation | ↑6.1× |
Viral Reactivation: SETDB1 knockout reactivated silenced MSCV-LTR retroviruses in 40% of cells within 3 days .
SETDB1 antibodies have revealed its dual role:
STRING: 7955.ENSDARP00000082796
UniGene: Dr.106645
This comprehensive compilation addresses frequently asked questions about SETDB1 antibodies for scientific research, drawing from multiple peer-reviewed sources with current data through 2025. SETDB1, a histone H3 lysine 9-specific methyltransferase, has emerged as a crucial epigenetic regulator with significant implications in cancer biology and immune system modulation. This document details methodological approaches to antibody selection, validation protocols, and interpretation frameworks for experimental results spanning various research applications from basic Western blotting to complex ChIP-sequencing and functional studies.
SETDB1 (SET domain bifurcated histone lysine methyltransferase 1) is a critical enzyme that specifically trimethylates 'Lys-9' of histone H3. This epigenetic modification represents a specific tag for transcriptional repression by recruiting HP1 proteins to methylated histones. SETDB1 primarily functions in euchromatin regions, playing a central role in silencing euchromatic genes . Its activity is coordinated with DNA methylation, making it essential for studying gene regulation mechanisms and epigenetic reprogramming. Recent research has demonstrated SETDB1's significance in cancer progression, particularly melanoma, where its amplification accelerates tumor formation . Additionally, SETDB1 has critical functions in immune cell development and regulation, including B cell maturation and T cell activity .
Based on current commercial antibodies available (as of 2025), SETDB1 antibodies have been validated for multiple applications:
| Application | Validated Antibody Examples | Typical Dilution Ranges |
|---|---|---|
| Western Blotting (WB) | Mouse mAb 5H6D4, Rabbit pAb N2C1 | 1:500-1:100,000 |
| Immunohistochemistry (IHC) | Mouse mAb 5H6D4, Rabbit pAb | 1:500-1:2000 |
| Immunofluorescence (IF/ICC) | Mouse mAb 5H6A12, Rabbit pAb | 1:400-1:1600 |
| Chromatin Immunoprecipitation (ChIP) | Rabbit pAb, Mouse mAb | Assay dependent |
| Immunoprecipitation (IP) | Rabbit pAb | 1:100-1:500 |
| Flow Cytometry | Mouse mAb 5H6A12 | Assay dependent |
These applications allow researchers to study SETDB1 expression, localization, interactions, and DNA binding sites .
Selection should be based on:
Target species compatibility: Commercial antibodies show reactivity with human, mouse, and rat SETDB1, but cross-reactivity varies between products. For example, many antibodies were raised against human SETDB1 but cross-react with mouse and rat due to sequence conservation .
Application specificity: Some antibodies perform better in specific applications. For example, clone 5H6D4 is optimized for Western blot with dilutions up to 1:100,000, while others may be more suitable for ChIP or immunofluorescence .
Epitope consideration: Antibodies targeting different regions of SETDB1 may yield different results. Some target the N-terminus (AA 1-397), others the C-terminus (AA 1193-1225) . This is important as SETDB1 forms complexes with other proteins, and epitope accessibility may vary.
Validation data: Prior validation in your specific experimental system is crucial. Review published studies that used the antibody in similar contexts and examine manufacturer validation data showing expected molecular weight detection (170-180 kDa for SETDB1) .
A thorough validation process should include:
Positive and negative controls: Use cell lines known to express SETDB1 (HeLa, HEK293, MCF-7) as positive controls and SETDB1 knockdown/knockout cells as negative controls .
Expected molecular weight confirmation: SETDB1 has a calculated molecular weight of 143 kDa but typically appears at 170-180 kDa in SDS-PAGE due to post-translational modifications .
Multiple detection methods: Validate using orthogonal approaches (e.g., if using the antibody for immunofluorescence, confirm expression with Western blot).
Peptide competition assay: Pre-incubation of the antibody with its immunogen peptide should abolish specific binding.
Cross-reactivity assessment: Test against related proteins to ensure specificity, particularly other SET domain-containing proteins.
Reproducibility testing: Ensure results are consistent across multiple experiments and batches of antibodies .
Based on validated protocols:
Sample preparation: HeLa, HEK293, or similar cell/tissue lysates should be prepared in RIPA or similar buffer with protease inhibitors.
Gel percentage: Use 5-8% SDS-PAGE gels due to SETDB1's high molecular weight (170-180 kDa) .
Transfer conditions: Transfer at lower voltage for longer periods (e.g., 30V overnight) to ensure complete transfer of high molecular weight proteins.
Blocking: 5% non-fat milk or BSA in TBST for 1 hour at room temperature.
Primary antibody incubation: Dilute according to manufacturer's recommendation (typically 1:1000-1:3000 for most antibodies, though some like 5H6D4 can be used at much higher dilutions of 1:20,000-1:100,000) .
Detection system: HRP-conjugated secondary antibodies with enhanced chemiluminescence provide good sensitivity for SETDB1 detection .
Expected outcome: A distinct band at approximately 170-180 kDa, with potential secondary bands depending on the cell type and antibody specificity .
Chromatin immunoprecipitation with SETDB1 antibodies requires:
Crosslinking optimization: Standard 1% formaldehyde for 10 minutes at room temperature works for most applications, but optimization may be needed for specific targets.
Chromatin fragmentation: Sonication should be optimized to generate fragments of 200-500 bp.
Antibody amount: Typically 4-5 μg of SETDB1 antibody per ChIP reaction .
Controls: Include IgG control from the same species as the SETDB1 antibody, and positive control antibodies targeting histones.
Validation by qPCR: Analyze enrichment at known SETDB1 target sites like ERVs or HOX genes .
Data analysis: SETDB1 ChIP-Seq data shows target genes are significantly enriched in downregulated but not upregulated genes, indicating its primary role in gene repression .
Successful ChIP experiments with SETDB1 antibodies have been demonstrated using commercial antibodies with HeLa chromatin extracts and SETDB1-bound regions like P53P2 .
Advanced methodological approaches include:
Tissue microarray analysis: SETDB1 antibodies have been used in melanoma tissue microarrays showing overexpression in 70% of malignant melanomas compared to 5% of normal melanocytes . This technique allows high-throughput analysis of SETDB1 expression across multiple patient samples.
Xenograft model monitoring: SETDB1 antibodies can quantify expression in zebrafish melanoma models to correlate expression with tumor aggressiveness .
Mechanistic studies: Using SETDB1 antibodies in ChIP-seq followed by RNA-seq in SETDB1-overexpressing versus normal cells reveals target genes and pathways affected, particularly HOX genes that are dysregulated by SETDB1 overexpression .
Co-immunoprecipitation: SETDB1 antibodies can identify interaction partners in cancer cells, revealing its association with transcriptional repressor complexes that silence tumor suppressor genes .
Epigenetic profiling: Combining SETDB1 ChIP-seq with H3K9me3 ChIP-seq and DNA methylation analysis can provide comprehensive understanding of SETDB1's role in establishing repressive chromatin states in cancer cells .
Based on recent immune research:
Conditional knockout models: SETDB1 antibodies can verify knockout efficiency in specific immune cell populations where SETDB1 has been deleted using Cre-lox systems .
Flow cytometry: SETDB1 antibodies suitable for flow cytometry can quantify expression levels in different immune cell populations and correlate with cell maturation stages .
CRISPR screening validation: SETDB1 antibodies can validate knockout efficiency in CRISPR screens identifying SETDB1 as an immune modulator .
Cytokine profiling: Correlating SETDB1 levels (via Western blot/immunohistochemistry) with cytokine expression profiles can reveal its role in regulating immune responses .
ERV expression analysis: SETDB1 ChIP followed by qPCR for specific ERVs can determine how SETDB1 regulates endogenous retroviruses in immune cells, particularly in B cell development where SETDB1 deletion leads to ERV upregulation and disrupted B cell maturation .
Advanced approaches include:
Sequential ChIP (Re-ChIP): Using SETDB1 antibodies in combination with antibodies against other epigenetic regulators (KAP1/TRIM28, SUV39H1, G9a, GLP) to identify genomic regions where these proteins co-localize .
Proximity ligation assay (PLA): This technique can visualize protein-protein interactions between SETDB1 and its binding partners in situ, as reported in scientific literature .
Co-immunoprecipitation followed by mass spectrometry: SETDB1 antibodies can pull down protein complexes for identification of novel interacting partners .
FRET/BRET analyses: When combined with fluorescent protein tagging, SETDB1 antibodies can be used to validate protein interactions identified through resonance energy transfer techniques.
Biochemical fractionation: SETDB1 antibodies can track the protein through different cellular fractions, particularly in studies of its association with promyelocytic leukemia-nuclear bodies (PML-NBs) .
Multiple bands may occur due to:
Post-translational modifications: SETDB1 undergoes extensive modifications, causing shifts in molecular weight. The calculated molecular weight is 143 kDa, but the observed weight is typically 170-180 kDa .
Alternative splice variants: SETDB1 has multiple isoforms that may be detected by antibodies recognizing common epitopes.
Degradation products: Proteolytic cleavage during sample preparation can result in lower-molecular-weight fragments.
Cross-reactivity: Some antibodies may cross-react with related SET domain-containing proteins.
Non-specific binding: Insufficient blocking or high antibody concentration can lead to background bands.
To address these issues:
Use fresh samples with protease inhibitors
Try different antibodies targeting different epitopes
Include positive controls (cell lines known to express SETDB1)
Optimize blocking conditions and antibody dilutions
Consider using SETDB1 knockout/knockdown samples as negative controls
When facing contradictory results:
Epitope accessibility: Different antibodies target different regions of SETDB1. Some epitopes may be masked in certain protein complexes or conformational states.
Specificity variation: Antibodies may have different cross-reactivities with related proteins or SETDB1 isoforms.
Application optimization: Each antibody may require different optimization for specific applications. For example, antibody 5H6D4 is optimized for Western blot while others may perform better in IHC .
Validation approach: Use orthogonal methods to confirm results:
Genetic approaches (siRNA, CRISPR knockout)
Multiple antibodies targeting different epitopes
Complementary techniques (e.g., RNA expression, reporter assays)
Context dependency: SETDB1 function varies between cell types and conditions. For example, its complex formation differs between cancer and immune cells .
Researchers face several methodological challenges:
Transient interactions: SETDB1 forms dynamic complexes with proteins like KAP1/TRIM28, requiring specialized techniques like crosslinking or proximity labeling to capture .
Context-dependent associations: SETDB1 forms different complexes in different cellular contexts. For example, it associates with the HUSH complex, KRAB-ZFP, and KAP1/TRIM28 in context-dependent manners .
Antibody interference: Antibodies may disrupt protein complexes during immunoprecipitation. Using multiple antibodies targeting different epitopes can help verify interactions.
Complex size limitations: Large complexes may be difficult to isolate intact. Gradient fractionation followed by immunoblotting can help characterize complex composition.
Specificity verification: Functional validation through reconstitution experiments using purified components is essential to confirm direct interactions versus indirect associations .
Emerging research approaches include:
Biomarker development: SETDB1 antibodies can help identify patient subgroups with SETDB1 overexpression, who might benefit from targeted therapies. Immunohistochemistry analysis has shown 70% of malignant melanomas overexpress SETDB1 .
Drug screening validation: SETDB1 antibodies can assess the efficacy of compounds targeting SETDB1 enzymatic activity or protein-protein interactions.
Mechanism elucidation: Combining SETDB1 ChIP-seq with H3K9me3 profiling can reveal how SETDB1 inhibitors affect the epigenetic landscape in cancer cells.
In vivo imaging: Developing imaging applications with labeled SETDB1 antibodies could monitor therapy response in animal models.
Therapeutic window assessment: Comparing SETDB1 expression patterns between cancer and normal tissues can help determine potential off-target effects of SETDB1-targeting therapies .
Advanced immunology research approaches:
Single-cell analysis: Combining SETDB1 antibody staining with single-cell RNA-seq can reveal heterogeneity in SETDB1 expression and its correlation with immune evasion gene signatures.
Spatial transcriptomics: Correlating SETDB1 expression with immune cell infiltration patterns in tumor sections can provide insights into local immune regulation.
Ex vivo tumor models: SETDB1 antibodies can monitor expression in patient-derived organoids or explants treated with immunotherapeutics.
Functional immune assays: Correlating SETDB1 levels with T cell killing efficacy, antigen presentation, and cytokine profiles can elucidate its role in immune escape.
Conditional expression systems: Inducible SETDB1 expression/deletion in tumor models allows temporal analysis of immune response dynamics using SETDB1 antibodies to confirm manipulation .
This emerging research area requires:
ChIP-seq optimization: SETDB1 antibodies must be carefully validated for ChIP-seq to map binding sites at ERV loci with high specificity.
Integration with RNA-seq: Correlating SETDB1 binding with ERV expression requires integrated genomic approaches.
Genetic complementation: Using SETDB1 knockout cells reconstituted with wild-type or mutant SETDB1 allows functional domain mapping, with antibodies verifying expression levels.
Functional immunology: CRISPR screens have identified SETDB1 as critical for immune clearance of melanoma through ERV derepression, requiring antibody validation of knockout efficiency .
Cross-species comparison: SETDB1 antibodies with cross-reactivity to multiple species can help compare ERV regulation mechanisms across evolutionary contexts .