Formyl-HIST1H1E (K62) Antibody is validated for:
Western Blotting: Detects formylated HIST1H1E in lysates (e.g., Jurkat cells) .
Immunocytochemistry: Visualizes subcellular localization of formylated histones in fixed cells .
Immunofluorescence: Enables spatial mapping of formylation patterns in chromatin .
| Application | Positive Control | Dilution | Source |
|---|---|---|---|
| WB | Jurkat cell lysate | 1:500–1:2000 | |
| IHC | Mouse colon tissue | 1:50–1:200 | |
| ICC/IF | Fixed human/mouse cells | 1:50–1:200 |
K62 Formylation: Specifically disrupts histone-DNA interactions, potentially modulating chromatin accessibility .
Disease Links: Mutations in HIST1H1E are associated with neurodevelopmental disorders, though formylation’s role remains unexplored .
Formyl-HIST1H1E (K62) is part of a broader family of formylated histone antibodies targeting distinct lysine residues:
Key suppliers and product codes:
Neurodevelopmental Disorders: HIST1H1E mutations (e.g., frameshifts in the C-terminal tail) are linked to Rahman syndrome and autism, though formylation’s role remains unstudied .
Epigenetic Regulation: Formylation may compete with other PTMs (e.g., acetylation) at K62, modulating chromatin dynamics .
Specificity: Cross-reactivity with non-formylated HIST1H1E or other histones must be validated .
Reproducibility: Limited data on lot-to-lot consistency across suppliers.
Scarcity: Fewer formylation-specific antibodies exist compared to acetylation or methylation targets .
Mechanistic Studies: Investigate how K62 formylation impacts chromatin structure and transcription.
Disease Models: Explore formylation’s role in HIST1H1E-associated neurodevelopmental disorders.
Technological Advancements: Develop high-throughput assays (e.g., ChIP-seq) for formylated histones.
Formyl-HIST1H1E (K62) antibodies are valuable tools for:
Chromatin immunoprecipitation (ChIP) experiments to identify genomic binding sites of formylated HIST1H1E
Immunofluorescence imaging to visualize nuclear distribution patterns
Western blotting to quantify formylation levels across different cell types and conditions
Investigating epigenetic modifications in neurodevelopmental disorders, particularly in Rahman syndrome models
Examining temporal dynamics of histone modifications during cellular differentiation and stress response
Frameshift mutations in HIST1H1E, particularly those affecting the C-terminal domain, have been associated with Rahman syndrome, characterized by intellectual disability and distinctive facial features . These mutations may potentially alter post-translational modification patterns, including formylation at K62. Researchers investigating the molecular pathogenesis of HIST1H1E-related disorders should consider how these mutations might affect formylation status, potentially disrupting chromatin organization and gene expression patterns during neurodevelopment.
For optimal results with Formyl-HIST1H1E (K62) antibody applications:
Immunohistochemistry/Immunofluorescence Preparation:
Use freshly prepared 4% paraformaldehyde for tissue fixation (15-20 minutes)
Perform antigen retrieval using citrate buffer (pH 6.0) at 95-100°C for 15-20 minutes
Include a permeabilization step with 0.2% Triton X-100 for 10 minutes
Block with 3-5% BSA or normal serum for at least 1 hour
Incubate with primary antibody at optimal dilution (typically 1:100-1:500) at 4°C overnight
Western Blot Sample Preparation:
Extract histones using specialized acid extraction protocols to efficiently recover histone proteins
Include deacetylase and demethylase inhibitors (e.g., sodium butyrate, nicotinamide) in lysis buffers
Maintain samples at 4°C throughout processing to prevent degradation of post-translational modifications
Antibody validation is critical for ensuring experimental reliability. Recommended approaches include:
Peptide Competition Assays: Pre-incubate antibody with formylated and non-formylated HIST1H1E peptides containing the K62 residue
Knockout/Knockdown Controls: Compare signals in wild-type versus HIST1H1E-depleted samples
Modification-Specific Controls: Compare signals after treatment with deformylase enzymes
Cross-Reactivity Testing: Evaluate potential binding to other formylated histones, particularly other H1 variants
Mass Spectrometry Validation: Confirm formylation at K62 in immunoprecipitated samples
For optimal ChIP results with Formyl-HIST1H1E (K62) antibodies:
Crosslinking: Use 1% formaldehyde for 10 minutes at room temperature
Sonication: Optimize conditions to generate chromatin fragments of 200-500 bp
Immunoprecipitation:
Use 2-5 μg antibody per chromatin sample (derived from ~1-2 × 10^6 cells)
Include appropriate controls (IgG, input DNA, non-formylated HIST1H1E)
Incubate overnight at 4°C with gentle rotation
Washing: Perform stringent washing steps to reduce background (at least 5 washes)
Elution and Reversal: Elute immunocomplexes and reverse crosslinks at 65°C for 4-6 hours
DNA Purification: Use silica column-based methods for optimal DNA recovery
Analysis: Perform qPCR or next-generation sequencing to analyze enriched genomic regions
Distinguishing formylation from other lysine modifications (acetylation, methylation) requires specialized approaches:
Mass Spectrometry Analysis:
Use high-resolution MS/MS to identify the precise mass shift associated with formylation (+28 Da)
Implement targeted approaches focusing on K62-containing peptides
Apply multiple fragmentation techniques (CID, ETD, HCD) for comprehensive analysis
Combinatorial Antibody Approaches:
Use antibodies specific for different modifications at K62 in parallel experiments
Perform sequential immunoprecipitation to identify co-occurrence of modifications
Enzymatic Treatment Controls:
Studying formylation in patient samples presents several technical challenges:
Limited Sample Availability: Rahman syndrome is rare, with only about 52 documented patients exhibiting HIST1H1E variants
Variant-Specific Effects: Different frameshift mutations may differentially impact post-translational modification patterns
Tissue-Specific Considerations:
Neural tissues are challenging to access in living patients
Peripheral blood may not reflect neural epigenetic patterns
Patient-derived iPSCs may be required for neuronal differentiation models
Detection Sensitivity:
Formylation levels may be low and technically challenging to detect
Background signal may complicate interpretation in heterozygous mutation carriers
Methodological Solutions:
To establish correlations between formylation, chromatin accessibility, and gene expression, researchers should implement multi-omic approaches:
Integrated Analysis Pipeline:
Perform ChIP-seq with Formyl-HIST1H1E (K62) antibodies
Couple with ATAC-seq to measure chromatin accessibility
Integrate RNA-seq data to correlate with gene expression patterns
Include Hi-C or other chromosome conformation capture techniques
Bioinformatic Analysis Strategies:
Identify genomic regions enriched for formylated HIST1H1E
Compare with accessibility peaks from ATAC-seq
Correlate with differentially expressed genes
Apply machine learning approaches to identify predictive patterns
Temporal Analysis:
Rahman syndrome, caused by frameshift mutations in HIST1H1E, presents with intellectual disability, distinctive facial features, and other neurodevelopmental abnormalities . The relationship between K62 formylation and disease pathogenesis may involve:
Altered Chromatin Compaction: Formylation may influence histone-DNA binding affinity, potentially disrupting normal chromatin architecture
Dysregulated Gene Expression: Changes in chromatin structure could lead to aberrant gene expression patterns during critical neurodevelopmental windows
Developmental Consequences: The 23 frameshift variants identified in 52 patients all result in almost identical shorter proteins with a shared divergent C-terminal tail , which may alter the pattern or recognition of post-translational modifications like formylation
Cellular Senescence Effects: Some HIST1H1E mutations accelerate cellular senescence and cause premature aging phenotypes , which might be linked to changes in formylation patterns
Several model systems offer complementary advantages for studying Formyl-HIST1H1E (K62) in neurodevelopmental contexts:
iPSC-derived neuronal cultures from patient samples
CRISPR-engineered cell lines with specific HIST1H1E mutations
Neural organoids that recapitulate aspects of brain development
Mouse models with equivalent mutations in the murine Hist1h1e gene
Conditional knockout/knockin models for temporal and tissue-specific studies
Include developmental time-course analyses
Examine multiple neural cell types (neurons, glia, neural progenitors)
Compare heterozygous versus homozygous mutations to assess dose-dependent effects
Distinguishing specific effects of altered formylation from other mutation consequences requires sophisticated experimental approaches:
Site-Specific Mutation Analysis:
Generate K62R mutants (preventing formylation) without affecting other protein functions
Compare with disease-causing frameshift mutations
Assess differential effects on chromatin structure and gene expression
Enzymatic Modulation Experiments:
Manipulate formylation enzymes while maintaining HIST1H1E sequence
Use small molecule inhibitors or activators of formylation pathways
Compare phenotypic outcomes with mutation models
Modification-Specific Protein Interactions:
Emerging technologies with potential to advance Formyl-HIST1H1E (K62) research include:
Advanced Antibody Technologies:
Single-domain antibodies with improved specificity
Recombinant antibody fragments with enhanced epitope recognition
Modification-specific nanobodies for live-cell imaging
Novel Microscopy Approaches:
Super-resolution microscopy to visualize chromatin organization
Live-cell imaging of formylation dynamics
Correlative light and electron microscopy for ultrastructural context
Mass Spectrometry Innovations:
Integration of multiple omics technologies offers comprehensive insights into formylation biology:
Complementary Technologies:
ChIP-seq: Genomic localization of formylated HIST1H1E
ATAC-seq: Chromatin accessibility correlations
CUT&RUN/CUT&Tag: Higher resolution mapping of histone modifications
Hi-C/Micro-C: 3D chromatin architecture analysis
RNA-seq: Transcriptional consequences
Proteomics: Interaction partners and co-occurring modifications
Integrated Analysis Frameworks:
Computational methods to correlate data across platforms
Machine learning approaches to identify predictive patterns
Network analysis to map regulatory relationships
Single-Cell Multi-Omics: