Acetyl-Histone H3.1 (K4) Recombinant Monoclonal Antibody

What is the biological significance of H3K4 acetylation?

H3K4 acetylation occurs on histone H3, a core component of nucleosomes that wrap and compact DNA into chromatin. As a post-translational modification, H3K4 acetylation contributes to the "histone code" that regulates DNA accessibility for cellular machineries involved in transcription, DNA repair, and replication .

Research has revealed significant cross-talk between H3K4 acetylation and H3K4 trimethylation (H3K4me3), with H3K4me3 being a well-established hallmark of transcription initiation . Notably, all K4-trimethylated histone H3 in human, mouse, and Drosophila cells undergoes dynamic acetylation mediated by the same lysine acetyltransferase, p300/CBP . This dynamic acetylation plays an essential role in the activation of immediate-early genes through facilitating RNA polymerase II association .

Genome-wide analyses have demonstrated that H3K4 acetylation, similar to H3K4me3, is enriched at the 5' ends of active genes along with other histone H3 acetylation marks . This positioning at transcription start sites further supports its role in gene activation.

How do I validate the specificity of an Acetyl-Histone H3.1 (K4) antibody?

Validation of antibody specificity is critical for reliable experimental outcomes. For Acetyl-Histone H3.1 (K4) antibodies, several complementary approaches should be employed:

• Dot blot analysis: Test the antibody against a panel of modified and unmodified histone peptides. A specific antibody should:

  • Show strong reactivity with H3K4ac peptides

  • Show minimal cross-reactivity with other modifications (e.g., H3K4me, H3K4 formyl, H3K4 crotonyl)

  • Show minimal binding to unmodified H3 peptides

• Western blot validation:

  • Compare samples from cells treated with and without histone deacetylase (HDAC) inhibitors

  • The H3K4ac signal should increase after HDAC inhibitor treatment

  • Use appropriate loading controls (total H3)

• ChIP validation:

  • Perform ChIP-qPCR targeting genes known to be enriched for active histone marks (e.g., GAPDH, EIF4A2) as positive controls

  • Include regions known to lack the modification (e.g., HBB promoter in non-erythroid cells, Sat2 satellite repeats) as negative controls

  • Compare enrichment patterns with other active marks like H3K4me3

• ChIP-seq validation:

  • Examine genome-wide distribution for expected enrichment patterns

  • The antibody should show enrichment at transcription start sites of active genes

  • The pattern should correlate with other active histone marks

A properly validated antibody should consistently demonstrate specificity across multiple validation methods.

What applications are Acetyl-Histone H3.1 (K4) antibodies best suited for?

Acetyl-Histone H3.1 (K4) antibodies have been validated for several important research applications:

• Chromatin Immunoprecipitation (ChIP):

  • For mapping genomic distribution of H3K4ac

  • Typically requires 1-10 μg antibody per experiment with 4-10 million cells

  • Used to identify specific genomic loci enriched for this modification

• ChIP-sequencing (ChIP-seq):

  • For genome-wide profiling of H3K4ac distribution

  • Illumina sequencing platforms with 30 million or more reads provide sufficient depth

  • Analysis reveals global patterns at transcription start sites and regulatory regions

• Western blotting:

  • For detecting global levels of H3K4ac in cell or tissue lysates

  • Typically used at 1/1000-1/10000 dilution

  • Can resolve acetylated from non-acetylated forms using acid-urea gels

• Dot blot analysis:

  • For testing antibody specificity

  • Can detect as little as 0.2 pmol of the target peptide

  • Useful for comparing specificity against multiple histone modifications

• Immunocytochemistry/Immunofluorescence (ICC/IF):

  • For visualizing nuclear localization of H3K4ac

  • Provides spatial information within individual nuclei

  • Can be combined with other antibodies for colocalization studies

Each application requires specific optimization of antibody concentration, incubation conditions, and appropriate controls to achieve reliable results.

How should ChIP experiments with Acetyl-Histone H3.1 (K4) antibodies be optimized?

Optimizing ChIP experiments with Acetyl-Histone H3.1 (K4) antibodies requires careful consideration of several parameters:

• Antibody amount: Titrate the antibody to determine optimal concentration. Based on published protocols, 1-10 μg per ChIP experiment is typically effective. For example, ChIP assays have been successfully performed using 1, 2, 5, and 10 μg of antibody against H3K4ac per experiment .

• Chromatin preparation:

  • Use fresh cross-linked chromatin (1% formaldehyde for 10 minutes)

  • Sonicate to generate fragments of 200-500 bp

  • Use 4-10 million cells per experiment (e.g., HeLa cells)

• Essential controls:

  • Use non-specific IgG (1 μg/IP) as a negative IP control

  • Include primers for positive control regions (e.g., GAPDH and EIF4A2 promoters) in qPCR analysis

  • Include primers for negative control regions (e.g., HBB promoter, Sat2 satellite repeat)

• Data analysis:

  • Express results as percent of input (the relative amount of immunoprecipitated DNA compared to input DNA after qPCR analysis)

  • For ChIP-seq, align reads to the reference genome using appropriate algorithms (e.g., BWA)

  • Examine peak distribution along the genome, particularly at transcription start sites

• Technical considerations:

  • Pre-clear chromatin with protein A/G beads to reduce background

  • Use optimized wash buffers with appropriate salt concentrations

  • Consider that H3K4ac is dynamically regulated and may have rapid turnover

Successful ChIP experiments should show enrichment at active gene promoters compared to negative control regions and negative control IP samples.

How do experimental conditions affect H3K4 acetylation levels?

H3K4 acetylation is dynamically regulated and sensitive to various experimental conditions:

• HDAC inhibition: Treatment with HDAC inhibitors (e.g., Trichostatin A) causes rapid accumulation of acetylated histones, including H3K4ac, due to blocked deacetylation .

• HAT inhibition: The p300/CBP inhibitor C646 blocks dynamic acetylation of H3K4me3, disrupting RNA polymerase II association and activation of immediate-early genes .

• Cell cycle effects: Histone modifications can vary throughout the cell cycle, potentially affecting H3K4ac levels. Cell synchronization may be necessary for certain experiments.

• Metabolic state: Acetylation requires acetyl-CoA as a substrate, so cellular metabolic changes can affect acetylation levels. Nutrient availability and metabolic inhibitors may alter global H3K4ac.

• Gene activation: Induction of immediate-early genes is associated with dynamic changes in H3K4 acetylation. Serum stimulation after starvation can be used to study these dynamics .

• Cross-talk with other modifications: H3K14 acetylation has been shown to protect H3K4me3 from demethylation, suggesting that manipulating one histone modification can affect others .

When designing experiments to study H3K4ac, these factors should be controlled or accounted for to ensure reproducible and interpretable results.

What methods can be used to quantify changes in H3K4 acetylation?

Several complementary methods can be employed to quantify changes in H3K4 acetylation:

• Western blot analysis:

  • Use acid-urea (AU) gels to separate histones based on charge, resolving acetylated from non-acetylated forms

  • Normalize H3K4ac signal to total H3 to account for loading differences

  • Use dilution series of standards for semi-quantitative analysis

  • Particularly useful for assessing global changes

• ChIP-qPCR:

  • Calculate percent of input for specific genomic regions

  • Compare enrichment at regions of interest versus control regions

  • Provides locus-specific quantification

  • Example data shows recovery of 0.2-1.5% of input at active promoters (GAPDH, EIF4A2) compared to <0.05% at inactive regions (HBB, Sat2)

• ChIP-seq:

  • Generate genome-wide enrichment profiles

  • Calculate normalized read density at regions of interest

  • Create metagene profiles to visualize average distribution patterns

  • Identify differentially enriched regions between conditions

  • Allow visualization of enrichment patterns along chromosomes

• Dot blot quantification:

  • Use dilution series of modified peptides as standards

  • Apply equal amounts of histone extract from different conditions

  • Quantify signal intensity with image analysis software

  • Useful for comparing relative levels between conditions

Each method has advantages and limitations regarding sensitivity, specificity, and throughput. Combining multiple approaches provides more robust quantification and interpretation of H3K4ac changes.

How does H3K4 acetylation interact with H3K4 methylation?

The relationship between H3K4 acetylation and methylation reveals complex regulatory mechanisms:

• Co-occurrence and cross-talk:

  • All K4-trimethylated histone H3 in human, mouse, and Drosophila cells undergoes rapid, continuous turnover of acetylation

  • This suggests that H3K4me3 and H3K4ac can co-exist on the same histone tail or exist in dynamic equilibrium

• Enzymatic regulation:

  • Dynamic acetylation of H3K4me3 is specifically mediated by p300/CBP in both mouse and fly cells

  • Inhibition of p300/CBP using the small molecule inhibitor C646 blocks dynamic acetylation of H3K4me3 globally

• Impact on gene expression:

  • The dynamic acetylation of H3K4me3 plays an essential role in the activation of immediate-early genes

  • Inhibition of this process disrupts RNA polymerase II association with inducible gene promoters

• Protection mechanisms:

  • In yeast, H3K14 acetylation protects H3K4me3 from demethylation by Jhd2

  • Loss of histone H3-specific acetyltransferases (HATs) results in genome-wide depletion of H3K4me3

  • This depletion is not due to transcription defects but to increased demethylase activity on hypoacetylated histones

• Evolutionary conservation:

  • The mechanism of rapid dynamic acetylation of all H3K4me3 is precisely conserved across human, mouse, and Drosophila

  • This high degree of conservation suggests fundamental importance in chromatin biology

These findings indicate that H3K4 acetylation and methylation operate together in an intricate regulatory network controlling gene expression, with acetylation potentially serving as a mechanism to preserve or regulate methylation states.

What techniques can reveal the dynamics of H3K4 acetylation turnover?

Investigating the dynamic nature of H3K4 acetylation requires specialized techniques:

• HDAC inhibitor time courses:

  • Treat cells with HDAC inhibitors (e.g., TSA) for various durations

  • Measure H3K4ac accumulation over time by Western blot or ChIP

  • Calculate turnover rates based on accumulation kinetics

  • This approach has revealed that H3K4me3 is subject to rapid, continuous turnover of acetylation

• HAT inhibitor studies:

  • Use p300/CBP inhibitors like C646 to block acetylation

  • Monitor the rate of acetylation loss at specific genomic regions

  • Compare effects on different genes or regulatory elements

  • This approach has shown that p300/CBP mediates dynamic acetylation of H3K4me3

• Pulse-chase experiments:

  • Label cellular acetyl-CoA pools with isotope-labeled acetate

  • Chase with non-labeled acetate

  • Track labeled acetyl groups on histones using mass spectrometry

  • Calculate half-life of acetyl marks on specific residues

• Time-resolved ChIP:

  • Perform ChIP at multiple time points after stimulus

  • Measure changes in H3K4ac at target genes

  • Correlate with transcriptional changes

  • This can reveal kinetics of acetylation changes during gene activation

• Sequential ChIP (Re-ChIP):

  • First ChIP with anti-H3K4me3 antibody

  • Second ChIP on the eluted material with anti-H3K4ac antibody

  • This identifies genomic regions where both modifications co-occur

  • Can reveal temporal relationships between modifications during gene activation

These methods can provide valuable insights into the highly dynamic nature of H3K4 acetylation and its role in transcriptional regulation.

How does H3K4 acetylation contribute to transcriptional regulation?

H3K4 acetylation plays multifaceted roles in transcriptional regulation:

• Promoter activation:

  • H3K4ac is enriched at the 5' ends of active genes

  • Dynamic acetylation of H3K4me3 is essential for RNA polymerase II association at promoters

  • Inhibition of p300/CBP disrupts this association and blocks gene activation

• Immediate-early gene regulation:

  • H3K4 acetylation dynamics are particularly important for immediate-early gene activation

  • These genes require rapid transcriptional responses, and H3K4ac provides a mechanism for quick regulation

  • This suggests a role in stimulus-responsive gene expression

• Interplay with histone methylation:

  • H3K4ac may protect H3K4me3 from demethylation

  • Loss of histone H3 acetylation results in genome-wide depletion of H3K4me3

  • This creates a regulatory circuit where acetylation helps maintain methylation states that promote transcription

• HAT involvement:

  • p300/CBP specifically mediates dynamic acetylation of H3K4me3

  • In yeast, Ada2 and Sas3 play redundant roles in maintaining H3K4me3 levels

  • This suggests specificity in the enzymes that regulate H3K4 acetylation

• Evolutionary conservation:

  • The mechanism of H3K4 acetylation regulation is conserved from Drosophila to humans

  • This high degree of conservation underscores its fundamental importance in transcriptional control

The data collectively indicate that H3K4 acetylation serves as both a direct regulator of transcription through affecting chromatin structure and RNA polymerase II recruitment, and as an indirect regulator by protecting other activating modifications like H3K4me3.

How do I troubleshoot weak or inconsistent signals in ChIP experiments?

When encountering challenges with Acetyl-Histone H3.1 (K4) ChIP experiments, consider these troubleshooting strategies:

• For weak signals:

  • Increase antibody amount (titrate from 1-10 μg per ChIP)

  • Optimize chromatin fragmentation (200-500 bp fragments are ideal)

  • Increase cell number (use 4-10 million cells per ChIP experiment)

  • Reduce wash stringency (lower salt concentration in wash buffers)

  • Consider that H3K4ac might be dynamically regulated with rapid turnover

  • Try adding HDAC inhibitors to cell culture prior to harvest

• For high background:

  • Pre-clear chromatin with protein A/G beads

  • Increase washing stringency (higher salt concentration in wash buffers)

  • Use more blocking protein (BSA or non-fat dry milk) in IP buffer

  • Include additional negative control regions in qPCR analysis (HBB promoter, Sat2)

  • Compare with a non-specific IgG control IP (use 1 μg/IP)

• For inconsistent results between replicates:

  • Standardize cross-linking conditions (1% formaldehyde for 10 minutes)

  • Ensure consistent antibody-to-chromatin ratios

  • Check sonication efficiency across samples

  • Use internal normalization controls

  • Consider the biological variability in acetylation levels

• For unexpected distribution patterns:

  • Verify antibody specificity using dot blot analysis

  • Check enrichment at known positive control regions (GAPDH, EIF4A2 promoters)

  • Compare with published ChIP-seq profiles

  • Consider cell type-specific differences in H3K4ac distribution

A properly optimized ChIP protocol should yield enrichment at active gene promoters compared to negative control regions, with recovery values typically ranging from 0.2-1.5% of input for active regions versus <0.05% for inactive regions .

How should ChIP-seq data for H3K4ac be analyzed and interpreted?

ChIP-seq data analysis for H3K4ac requires several analytical steps and interpretative frameworks:

• Primary data processing:

  • Align reads to the reference genome using appropriate algorithms (e.g., BWA)

  • Perform quality control to assess library complexity and enrichment

  • Call peaks to identify significantly enriched regions

  • Generate normalized coverage tracks for visualization

• Distribution pattern analysis:

  • Examine peak distribution along chromosomes

  • Focus on distribution around transcription start sites (TSS)

  • Create metagene profiles to visualize average patterns

  • Expected pattern: enrichment at the 5' ends of active genes

• Comparative analysis:

  • Compare H3K4ac with H3K4me3 distribution (they should substantially overlap)

  • Compare with other active histone marks (H3K27ac, H3K9ac)

  • Correlate with transcription levels (RNA-seq data)

  • Check for co-occurrence with p300/CBP binding sites

• Functional interpretation:

  • Perform gene ontology analysis of H3K4ac-marked genes

  • Identify enriched transcription factor binding motifs in H3K4ac peaks

  • Consider the relationship with immediate-early gene activation

  • Examine changes in response to experimental conditions

• Visualization examples:

  • Peak distribution along complete chromosome sequences

  • Zoomed views of specific gene regions (e.g., GAPDH, EIF4A2)

  • Heatmaps showing H3K4ac enrichment across multiple genes

  • Browser tracks showing the relationship with gene structure and other histone marks

Properly analyzed ChIP-seq data should reveal that H3K4ac is primarily enriched at active gene promoters and correlates well with transcriptional activity and the presence of other active histone marks.

What controls are essential for validating experimental findings related to H3K4 acetylation?

Robust validation of H3K4 acetylation findings requires multiple types of controls:

• Antibody specificity controls:

  • Dot blot analysis testing cross-reactivity with:

    • H3K4ac peptide (positive control)

    • Unmodified H3 peptide (negative control)

    • Other H3K4 modifications (H3K4me, H3K4 formyl, H3K4 crotonyl)

    • Other acetylated lysines on H3

  • Using multiple antibodies (polyclonal and monoclonal) targeting the same modification

• ChIP-qPCR controls:

  • Positive control regions known to be enriched for active marks:

    • GAPDH promoter

    • EIF4A2 promoter

  • Negative control regions:

    • HBB promoter (in non-erythroid cells)

    • Sat2 satellite repeat

  • IgG control IP to establish background levels

• Genetic and chemical validation:

  • HAT inhibitor treatments (e.g., C646 for p300/CBP)

  • HDAC inhibitor treatments as positive controls for acetylation

  • Manipulation of enzymes involved in H3K4 acetylation (p300/CBP) or deacetylation

  • Histone mutants where possible (H3K4R or H3K4Q)

• Cross-validation with other techniques:

  • Western blot to confirm global changes

  • Immunofluorescence to visualize nuclear distribution

  • Mass spectrometry for absolute quantification

  • RNA-seq to correlate with transcriptional outcomes

• Biological replicates:

  • Multiple independent experiments

  • Different cell lines or tissues where appropriate

  • Different time points to capture dynamics

These controls collectively ensure that observations about H3K4 acetylation are specific, reproducible, and biologically meaningful, rather than artifacts of the experimental system or antibody properties.

How might single-cell epigenomic approaches advance our understanding of H3K4 acetylation?

Single-cell approaches represent the frontier for understanding H3K4 acetylation heterogeneity:

• Single-cell ChIP-seq adaptations:

  • Current technical challenges in sensitivity and throughput

  • Modified protocols to improve antibody efficiency with limited material

  • Computational methods to address technical noise

  • Potential to reveal cell-to-cell variation in H3K4ac patterns

• CUT&Tag and CUT&RUN single-cell approaches:

  • Higher sensitivity than traditional ChIP for limited material

  • More direct approach with fewer washing steps

  • Potential for multiplexing with other histone modifications

  • Could reveal correlation between H3K4ac and other marks at single-cell resolution

• Integrated multi-omics approaches:

  • Combining H3K4ac profiling with RNA-seq in the same cells

  • Correlating with chromatin accessibility (ATAC-seq)

  • Establishing causal relationships between H3K4ac dynamics and gene expression heterogeneity

  • Understanding cell-to-cell variability in immediate-early gene responses

• Spatial epigenomics:

  • In situ approaches to visualize H3K4ac in tissue contexts

  • Correlating with cell positioning and microenvironment

  • Tracking H3K4ac dynamics during tissue development

  • Understanding the role of H3K4ac in maintaining tissue-specific gene expression programs

These emerging approaches will likely reveal how H3K4 acetylation heterogeneity contributes to cell fate decisions, developmental processes, and disease progression at unprecedented resolution.

What is the potential role of H3K4 acetylation in disease contexts?

H3K4 acetylation has emerging implications in various disease contexts:

• Cancer:

  • Altered H3K4ac patterns may contribute to oncogene activation

  • Mutations in p300/CBP (mediators of H3K4ac) are found in multiple cancer types

  • Dynamic H3K4 acetylation may be involved in cancer cell response to environmental changes

  • Potential therapeutic target through modulation of acetylation/deacetylation balance

• Neurodegenerative diseases:

  • H3K4ac dynamics may be disrupted in conditions like Alzheimer's disease

  • The role of H3K4ac in immediate-early gene activation suggests potential importance in neuronal plasticity and memory formation

  • HDAC inhibitors show neuroprotective effects in multiple models, potentially through restoring acetylation patterns

  • Metabolic disruptions in neurodegenerative diseases may affect acetyl-CoA availability for histone acetylation

• Inflammatory disorders:

  • H3K4ac likely plays a role in the rapid activation of inflammatory genes

  • The involvement of H3K4ac in immediate-early gene response suggests importance in cytokine production

  • Targeting the dynamic acetylation of H3K4me3 could provide new anti-inflammatory approaches

  • Differential H3K4ac patterns may contribute to chronic inflammatory states

• Therapeutic implications:

  • p300/CBP inhibitors like C646 could provide targeted approaches to modulate H3K4ac

  • Understanding the interplay between H3K4 acetylation and methylation could inform combination therapies

  • Biomarkers based on H3K4ac patterns might help stratify patients for epigenetic therapies

  • Metabolic interventions affecting acetyl-CoA pools could indirectly modulate H3K4ac levels

Future research in these areas may establish H3K4 acetylation as both a biomarker and therapeutic target in multiple disease contexts.

How can new technologies enhance detection and functional analysis of H3K4 acetylation?

Emerging technologies promise to revolutionize H3K4 acetylation research:

• Advanced genomic approaches:

  • CUT&RUN and CUT&Tag for higher resolution and lower background

  • Long-read sequencing to link H3K4ac with distant regulatory elements

  • Targeted epigenome editing (using CRISPR-dCas9 fused to acetyltransferases or deacetylases) to establish causality

  • Single-molecule real-time techniques to observe dynamic changes

• Proteomics innovations:

  • Enhanced mass spectrometry for absolute quantification of H3K4ac

  • Targeted proteomics to quantify combinatorial histone modifications

  • Identification of proteins specifically binding to H3K4ac versus H3K4me3

  • Proximity labeling to identify the complete interactome of H3K4ac-containing chromatin

• Imaging technologies:

  • Super-resolution microscopy to visualize H3K4ac distribution in the nucleus

  • Live-cell imaging using engineered reader domains to track H3K4ac dynamics

  • Multiplexed imaging to simultaneously monitor multiple histone modifications

  • Correlative light and electron microscopy to link H3K4ac with chromatin ultrastructure

• Computational approaches:

  • Machine learning to predict H3K4ac sites from DNA sequence and other epigenetic features

  • Integrative multi-omics analysis to understand the relationship between H3K4ac and other cellular processes

  • Modeling approaches to simulate dynamic acetylation/deacetylation cycling

  • Network analysis to position H3K4ac within broader epigenetic regulatory networks

These technological advances will likely provide deeper insights into the mechanistic roles of H3K4 acetylation in chromatin dynamics and gene regulation, with implications for both basic science and clinical applications.