Di-methyl-HIST1H3A (K36) Antibody

What is Di-methyl-HIST1H3A (K36) and its significance in epigenetic research?

Di-methyl-HIST1H3A (K36) refers to histone H3.1 protein (coded by the HIST1H3A gene) that has been dimethylated at the lysine 36 position. This specific histone modification plays a crucial role in chromatin structure and gene transcription regulation. Histone H3K36 dimethylation is associated with active gene expression and is involved in multiple cellular processes including DNA repair, alternative splicing, and transcriptional elongation . The significance of this modification lies in its role as part of the "histone code" that regulates DNA accessibility to cellular machinery, thereby controlling transcription, replication, and chromosomal stability .

How does Di-methyl-HIST1H3A (K36) differ from other histone H3 modifications?

Di-methyl-HIST1H3A (K36) is distinct from other histone H3 modifications in several important ways:

• Genomic location: H3K36me2 typically occurs within the gene body of actively transcribed genes, distinguishing it from other modifications like H3K4me3 (promoters) or H3K27me3 (repressed regions) .

• Functional outcomes: Unlike H3K9 methylation which is generally associated with heterochromatin and gene silencing, H3K36 dimethylation is linked to active transcription .

• Degree of methylation: H3K36 can be mono-, di-, or tri-methylated (H3K36me1, H3K36me2, H3K36me3), with each state contributing to distinct chromatin states and having unique reader proteins and biological consequences .

• Enzymatic regulation: Different methyltransferases and demethylases specifically target H3K36, such as the NSD family of methyltransferases that catalyze H3K36 dimethylation .

What are the common applications for Di-methyl-HIST1H3A (K36) antibodies?

Di-methyl-HIST1H3A (K36) antibodies are versatile tools with several key applications in epigenetic research:

These applications enable researchers to study the presence, distribution, and dynamics of H3K36 dimethylation in various biological contexts .

How can I verify the specificity of Di-methyl-HIST1H3A (K36) antibodies in my experimental system?

Verifying antibody specificity is crucial for reliable results in histone modification research. For Di-methyl-HIST1H3A (K36) antibodies, consider these methodological approaches:

• Peptide competition assays: Pre-incubate the antibody with excess immunizing peptide (containing K36me2) before application to your samples. Specific signals should be dramatically reduced or eliminated .

• Methyltransferase knockdown/knockout validation: Deplete known H3K36 methyltransferases (such as NSD family proteins) and confirm reduced signal with the antibody .

• Cross-reactivity testing: Compare signals from your K36me2 antibody with antibodies specific for K36me1 and K36me3, as well as other methyl-lysine modifications (e.g., K9me2) to ensure specificity .

• Positive and negative control samples: Use cell lines with known H3K36me2 status. For instance, HeLa, NIH/3T3, HEK-293T, and C2C12 cells have been validated as positive controls for many H3K36me2 antibodies .

• Multiple antibody validation: Compare results from different vendors' H3K36me2 antibodies to rule out antibody-specific artifacts .

These methods collectively ensure that your observed signals truly represent H3K36 dimethylation rather than cross-reactivity or non-specific binding .

What are the best practices for optimizing ChIP protocols with Di-methyl-HIST1H3A (K36) antibodies?

Optimizing ChIP protocols for H3K36me2 requires attention to several critical factors:

• Crosslinking conditions: For H3K36me2, which occurs in gene bodies, standard formaldehyde crosslinking (1% for 10 minutes) is generally effective, but optimization may be needed based on cell type .

• Sonication parameters: Aim for chromatin fragments of 200-500bp for optimal resolution. Over-sonication can destroy epitopes while under-sonication reduces efficiency .

• Antibody amount: Start with the recommended ratio (1:20 - 1:100 dilution) and titrate as needed . The optimal antibody amount depends on the abundance of H3K36me2 in your samples.

• Washing stringency: For H3K36me2 ChIP, include high-salt washes to reduce background, but avoid overly stringent conditions that may disrupt specific interactions .

• Input controls and normalization: Always process an input sample (pre-immunoprecipitation) alongside your ChIP to normalize for technical biases and starting material differences .

• Positive control loci: Include primers for genes known to be enriched for H3K36me2 (active gene bodies) in qPCR validation, such as housekeeping genes .

• Negative control regions: Include primers for regions expected to lack H3K36me2 (intergenic regions, silent genes) to confirm specificity .

Implementing these practices will help achieve high signal-to-noise ratios in H3K36me2 ChIP experiments .

How does genomic context influence H3K36 methylation patterns and antibody detection efficiency?

Genomic context significantly impacts both the distribution of H3K36 methylation and the efficiency of antibody detection:

• Chromatin state variability: H3K36 methylation status varies with the local chromatin environment. Open, accessible chromatin regions may show different antibody binding efficiency compared to more compact chromatin regions .

• Co-occurring modifications: The presence of other histone modifications can influence antibody accessibility to H3K36me2. For example, regions with high levels of H3K27 acetylation may affect the binding efficiency of H3K36me2 antibodies through steric hindrance or conformational changes .

• Locus-specific effects: Research indicates that depletion of K36me3 has variable, locus-specific effects on the interactions of epigenetic readers, suggesting context-dependent functions of this modification .

• Nucleosome positioning: The positioning of nucleosomes affects the exposure of H3K36me2 epitopes, potentially influencing antibody binding efficiency across different genomic regions .

• Transcriptional status: Actively transcribed regions generally have different patterns of H3K36 methylation compared to silent regions, which can affect antibody detection threshold requirements .

Understanding these contextual influences is crucial for correctly interpreting ChIP-seq or immunofluorescence data that maps H3K36me2 distribution across the genome .

What are the key technical considerations when using Di-methyl-HIST1H3A (K36) antibodies in Western blotting?

Western blotting with Di-methyl-HIST1H3A (K36) antibodies requires attention to several technical aspects for optimal results:

• Sample preparation: Extract histones using specialized acid extraction protocols to efficiently isolate histones from nuclei. Standard protein extraction methods may not effectively capture histone proteins .

• Gel selection: Use high-percentage (15-18%) gels or specialized Triton-Acid-Urea gels to achieve good separation of histone proteins, which have low molecular weights (H3 appears at 15-18 kDa) .

• Transfer conditions: Implement special transfer conditions (lower voltage, longer time) optimized for small proteins to ensure efficient transfer of histones to membranes .

• Blocking optimization: Use BSA-based blocking solutions rather than milk, as milk contains casein which has high phosphate content that may interfere with phospho-specific antibodies that might be used alongside methylation-specific antibodies .

• Dilution optimization: Start with the recommended dilution range (1:1000-1:8000) and adjust based on signal strength and background levels .

• Loading controls: Use total H3 antibodies or housekeeping proteins as loading controls to normalize for variations in histone loading .

• Positive controls: Include lysates from cells known to express H3K36me2, such as HeLa, NIH/3T3, C2C12, or HEK-293T cells .

Addressing these considerations will help achieve clear, specific detection of H3K36me2 in Western blotting applications .

How can researchers effectively troubleshoot non-specific binding or weak signals with Di-methyl-HIST1H3A (K36) antibodies?

Troubleshooting non-specific binding or weak signals requires systematic investigation of multiple parameters:

• Weak signal troubleshooting:

  • Increase antibody concentration (decrease dilution)

  • Extend primary antibody incubation time (overnight at 4°C)

  • Enhance detection system (switch to more sensitive chemiluminescence substrates)

  • Optimize extraction methods to improve histone yield

  • Check for protein degradation during sample preparation

• Non-specific binding troubleshooting:

  • Increase antibody dilution to reduce background

  • Optimize blocking conditions (try different blocking agents or concentrations)

  • Increase washing stringency (more washes, higher salt concentration)

  • Pre-adsorb antibody with non-specific proteins

  • Filter secondary antibody to remove aggregates

  • Confirm antibody lot-to-lot consistency

• Cross-reactivity analysis:

  • Perform peptide competition assays with both specific (K36me2) and non-specific (other methylated lysines) peptides

  • Compare binding patterns with alternative antibodies from different sources

  • Validate signals using genetic approaches (e.g., methyltransferase knockdown)

• Sample-specific issues:

  • Ensure proper sample preparation to expose the epitope

  • Check if target modification is present in your biological system

  • Consider fixation effects on epitope accessibility (for IF/IHC)

Systematic investigation of these factors will help resolve most issues with antibody performance .

What are the recommended storage and handling conditions to maintain Di-methyl-HIST1H3A (K36) antibody efficacy?

Proper storage and handling are essential for maintaining antibody efficacy over time:

Proper adherence to these storage and handling recommendations ensures maximum antibody performance and extends shelf life .

How can Di-methyl-HIST1H3A (K36) antibodies be used to investigate the relationship between histone modifications and disease states?

Di-methyl-HIST1H3A (K36) antibodies serve as valuable tools for investigating connections between this histone modification and various disease states:

• Cancer research applications:

  • Mapping altered H3K36me2 patterns across cancer genomes to identify epigenetic signatures

  • Correlating H3K36me2 levels with oncogene expression or tumor suppressor silencing

  • Investigating NSD methyltransferase dysregulation, which is implicated in multiple cancer types through aberrant H3K36 methylation

• Neurodegenerative disease studies:

  • Examining H3K36me2 changes in models of neurodegeneration

  • Correlating H3K36me2 patterns with altered gene expression in affected tissues

  • Investigating potential epigenetic therapeutic targets

• Developmental disorders research:

  • Analyzing H3K36me2 distribution during normal and abnormal development

  • Studying consequences of mutations in H3K36 methyltransferases or demethylases

  • Correlating developmental gene expression programs with H3K36me2 patterns

• Methodological approaches:

  • ChIP-seq to map genome-wide H3K36me2 changes in disease vs. normal states

  • Immunohistochemistry to visualize altered H3K36me2 in patient samples

  • Western blotting to quantify global H3K36me2 levels in different disease stages

  • Integration with transcriptome data to correlate H3K36me2 changes with gene expression

These applications help elucidate the mechanistic role of H3K36 dimethylation in disease pathogenesis and identify potential epigenetic biomarkers or therapeutic targets .

What are the recent advances in understanding the functional roles of different degrees of H3K36 methylation (mono-, di-, tri-)?

Recent research has revealed distinct functional roles for different degrees of H3K36 methylation:

• H3K36 monomethylation (H3K36me1):

  • Recently identified as a distinct functional state rather than just an intermediate

  • Associated with enhancer regions in some cell types

  • May serve as a precursor mark that primes chromatin for subsequent modifications

  • Regulated by different enzymes than di- and tri-methylation in some contexts

• H3K36 dimethylation (H3K36me2):

  • Enriched across gene bodies of actively transcribed genes

  • Plays a role in regulating alternative splicing by recruiting splicing factors

  • Involved in DNA damage response pathways

  • Mediated primarily by NSD family methyltransferases (NSD1, NSD2, NSD3)

  • Auto-inhibitory state of NSD enzymes is relieved by nucleosome engagement

• H3K36 trimethylation (H3K36me3):

  • Highly enriched at the 3' ends of gene bodies

  • Marks active chromatin and is interpreted by specific epigenetic readers

  • In Drosophila, bound by MSL3 for X-chromosome dosage compensation

  • Interacts with PWWP-domain protein JASPer to recruit JIL1 kinase to active chromatin

  • Shows locus-specific effects when depleted, challenging previous uniform models

• Context-dependent interactions:

  • Recent studies show that the three methylation states contribute to distinct chromatin states

  • The transition between different methylation states is regulated by specific writer and eraser enzymes

  • Reader proteins show different affinities for mono-, di-, and tri-methylated H3K36

  • Genomic context influences the biological outcomes of different methylation states

These discoveries challenge prevailing models and highlight the nuanced roles of different H3K36 methylation states in chromatin regulation .

How can Di-methyl-HIST1H3A (K36) antibodies be integrated into multi-omics approaches to study epigenetic regulation?

Integration of Di-methyl-HIST1H3A (K36) antibodies into multi-omics approaches enables comprehensive analysis of epigenetic regulation:

• ChIP-seq and RNA-seq integration:

  • Map H3K36me2 distribution using ChIP-seq with the antibody

  • Correlate with gene expression data from RNA-seq

  • Analyze how H3K36me2 patterns relate to transcriptional activity

  • Identify genes whose expression correlates strongly with H3K36me2 enrichment

• Epigenome and proteome connections:

  • Use H3K36me2 antibodies in ChIP followed by mass spectrometry (ChIP-MS)

  • Identify proteins that interact with H3K36me2-enriched chromatin regions

  • Characterize reader proteins that specifically recognize H3K36me2

• Multi-mark epigenomic profiling:

  • Perform sequential ChIP (Re-ChIP) with H3K36me2 antibodies and antibodies against other histone marks

  • Identify regions with co-occurrence of multiple modifications

  • Implement CUT&RUN or CUT&Tag methods with H3K36me2 antibodies for higher resolution mapping

  • Combine with ATAC-seq to correlate H3K36me2 with chromatin accessibility

• Single-cell approaches:

  • Adapt H3K36me2 antibodies for single-cell ChIP-seq or CUT&Tag

  • Integrate with single-cell RNA-seq to correlate H3K36me2 and gene expression at single-cell resolution

  • Study cell-to-cell variability in H3K36me2 distribution

• 4D Nucleome integration:

  • Combine H3K36me2 ChIP-seq with Hi-C or other chromosome conformation capture techniques

  • Analyze how H3K36me2 correlates with three-dimensional genome organization

  • Study the role of H3K36me2 in forming topologically associating domains (TADs)

These integrated approaches provide a comprehensive understanding of H3K36me2's role in coordinating various aspects of genome function and regulation .