Mono-methyl-HIST1H1E (K147) Antibody

What is HIST1H1E and what is the significance of K147 monomethylation?

HIST1H1E (also known as histone H1.4) belongs to the H1 histone family and functions as a linker histone essential for higher-order chromatin organization. It binds to linker DNA between nucleosomes, facilitating chromatin compaction and transcriptional regulation. Monomethylation at lysine 147 (K147me1) is a post-translational modification linked to chromatin remodeling and DNA repair. Unlike acetylation or phosphorylation, methylation at this site modulates histone-DNA interactions without altering charge, potentially influencing nucleosome spacing. This modification has been implicated in processes including nucleosome spacing in relaxed chromatin structures in gene-rich regions and recruitment of repair proteins to sites of DNA damage.

What applications are Mono-methyl-HIST1H1E (K147) antibodies validated for?

Mono-methyl-HIST1H1E (K147) antibodies have been validated for multiple applications, including:

• ELISA (Enzyme-Linked Immunosorbent Assay)

• Immunocytochemistry (ICC)

• Immunofluorescence (IF)

For optimal results, recommended dilutions vary by application:

• IF/ICC: 1:20-1:200

• ELISA: 1:2,000-1:10,000 (based on comparable histone antibodies)

What is the specificity profile of Mono-methyl-HIST1H1E (K147) antibodies?

The specificity of Mono-methyl-HIST1H1E (K147) antibodies has been confirmed through multiple validation methods:

• Peptide Microarray Screening: Cross-reactivity tests using high-density peptide arrays have demonstrated selective recognition of K147me1 without off-target binding to unmodified or alternative PTMs (e.g., acetylation, phosphorylation).

• Cell-Based Assays: Immunofluorescence in MCF-7 cells revealed nuclear localization consistent with histone H1.4's role in chromatin.

• Epitope Mapping: The antibodies recognize the C-terminal region of histone H1.4, which is critical for chromatin binding.

The specificity profile shows:

How should I optimize immunofluorescence protocols with Mono-methyl-HIST1H1E (K147) antibodies?

For optimal immunofluorescence results with Mono-methyl-HIST1H1E (K147) antibodies:

• Fixation: Use 4% paraformaldehyde for 10-15 minutes at room temperature to preserve nuclear architecture while maintaining epitope accessibility.

• Permeabilization: Apply 0.1-0.5% Triton X-100 for 5-10 minutes to allow antibody access to nuclear proteins without over-permeabilizing.

• Blocking: Use 5-10% normal serum (from the same species as the secondary antibody) with 0.1% BSA to reduce background.

• Antibody Dilution: Start with 1:50 dilution in blocking buffer and adjust based on signal intensity . For denser chromatin regions that may have reduced accessibility, consider testing a range from 1:20-1:100.

• Incubation Time: Incubate primary antibody overnight at 4°C to maximize specific binding while minimizing background.

• Controls: Include a negative control (no primary antibody) and, when possible, a competitive peptide blocking control to validate specificity.

• Counterstaining: Use DAPI for nuclear visualization to confirm nuclear localization pattern consistent with H1.4's distribution.

How can I confirm the specificity of observed signal in my experimental system?

To confirm antibody specificity in your particular experimental system:

• Peptide Competition Assay: Pre-incubate the antibody with excess synthetic K147me1 peptide (immunogen) before application to samples. Signal elimination confirms specificity.

• CRISPR/Cas9 Knockdown Control: Generate HIST1H1E knockout cells as negative controls to confirm signal absence when the target protein is removed.

• Methyltransferase Inhibition: Treat cells with methyltransferase inhibitors to reduce K147 monomethylation levels and observe corresponding signal reduction.

• Correlation with Other Markers: Co-stain with antibodies recognizing other regions of HIST1H1E to confirm signal overlap.

• Western Blot Validation: Perform western blot analysis on nuclear extracts to confirm the antibody detects a single band at the expected molecular weight of 36 kDa (observed) or 21.8 kDa (calculated) , noting that histones often migrate aberrantly on SDS-PAGE.

What considerations should be made when using this antibody in different cell types or species?

When using Mono-methyl-HIST1H1E (K147) antibodies across different experimental systems:

• Species Reactivity: Most commercial Mono-methyl-HIST1H1E (K147) antibodies are validated for human samples . When using with mouse or rat samples, perform validation experiments first as some products claim cross-reactivity .

• Cell Type Considerations:

  • Different cell types may exhibit varying levels of K147 methylation depending on cell cycle stage and differentiation status

  • Embryonic or stem cells may have distinct histone modification patterns compared to differentiated cells

  • Cancer cell lines often display aberrant histone modification profiles

• Fixation Optimization: Different cell types may require adjusted fixation protocols; thicker or more resistant cells might need increased permeabilization times.

• Background Considerations: Some cell types naturally express higher levels of autofluorescent proteins that may interfere with signal detection. Additional blocking steps or spectral unmixing might be necessary.

• Antibody Concentration Adjustment: Titrate antibody concentrations for each cell type, as accessibility of the epitope may vary with chromatin compaction differences between cell types.

How can I effectively use Mono-methyl-HIST1H1E (K147) antibodies in ChIP experiments?

While the search results don't specifically mention ChIP applications for this particular antibody, comparable histone modification antibodies can be adapted for ChIP using these methodological considerations:

• Crosslinking Optimization: For H1 histones (linker histones), which can be more loosely associated with chromatin than core histones:

  • Use dual crosslinking with DSG (disuccinimidyl glutarate) followed by formaldehyde

  • Optimize formaldehyde concentration (1-2%) and crosslinking time (10-15 minutes)

• Sonication Parameters:

  • Generate chromatin fragments of 200-500 bp

  • Use lower power settings with more cycles to prevent epitope damage

  • Verify fragmentation efficiency by agarose gel electrophoresis before proceeding

• Antibody Amount:

  • Start with 4-5 μg of antibody per ChIP reaction (based on comparable histone antibody protocols)

  • Scale up if working with limited epitope abundance

• Controls:

  • Include IgG control from the same species as the primary antibody

  • Include input control (pre-immunoprecipitation chromatin)

  • Consider using a spike-in normalization control for quantitative analysis

• Washing Stringency:

  • Use progressively stringent wash buffers to reduce background

  • Include a lithium chloride wash step to disrupt non-specific ionic interactions

• Validation:

  • Perform qPCR on regions known to be enriched or depleted for K147me1 based on published literature

  • Consider testing multiple antibody batches to ensure reproducibility

How does mono-methylation at K147 of HIST1H1E relate to other histone modifications in the epigenetic landscape?

The relationship between K147me1 on HIST1H1E and other histone modifications represents a complex aspect of the epigenetic code:

• Correlation with Core Histone Modifications:

  • K147me1 often co-occurs with H3K4me1 in regions of active/poised enhancers

  • Possible mutual exclusivity with H3K9me3 marks in heterochromatic regions

  • Potential synergy with H3K27ac in regulating gene expression

• Sequential Modification Patterns:

  • Phosphorylation events at neighboring residues (e.g., T142 or S152) likely influence K147 methylation

  • Monomethylation at K147 may precede or follow modifications at other sites in the C-terminal domain of H1.4

• Functional Interactions:

  • K147me1 appears to influence nucleosome spacing in gene-rich regions

  • This modification may create binding sites for specific nuclear proteins involved in DNA repair processes

  • The modification may modulate the binding affinity of H1.4 to linker DNA, affecting chromatin compaction without altering charge (unlike acetylation)

• Cell Cycle Dependence:

  • Levels of K147me1 likely fluctuate during the cell cycle

  • May exhibit reciprocal relationships with phosphorylation events known to occur on H1 histones during mitosis

• Methodological Approaches for Studying Relationships:

  • Sequential ChIP (Re-ChIP) can reveal co-occurrence of K147me1 with other histone modifications

  • Mass spectrometry-based approaches can quantify combinations of modifications on the same histone tail

  • Proximity ligation assays can detect spatial relationships between different modified histones

What are the implications of HIST1H1E mutations in relation to K147 methylation status in disease contexts?

The relationship between HIST1H1E mutations and K147 methylation status has important implications for understanding disease mechanisms:

• Rahman Syndrome Connection:

  • Pathogenic variants in HIST1H1E cause Rahman syndrome, characterized by macrocephaly, distinctive facial features, intellectual disability, and behavioral problems

  • Most disease-causing mutations are frameshift variants clustered in the C-terminal domain

  • K147 resides in the critical C-terminal domain (residues 140-151) where many pathogenic mutations occur, suggesting potential disruption of this methylation site

• Structural Consequences:

  • A novel frameshift mutation (p.Ala141GlufsTer56) occurs very close to the K147 methylation site , potentially affecting the ability of this residue to be methylated

  • The c.505_506insT (p.Lys169IlefsTer27) mutation extends the range of clustered pathogenic variants in the C-terminal domain

  • These mutations likely alter the C-terminal tail structure where K147 is located

• Functional Implications:

  • Mutations may affect the ability of methyltransferases to recognize and modify K147

  • Altered K147 methylation could contribute to the abnormal chromatin organization and gene expression observed in Rahman syndrome

  • Disruption of methylation at K147 could impact DNA repair processes normally facilitated by this modification

• Experimental Approaches:

  • Compare K147 methylation levels in patient-derived cells versus controls using the antibody

  • Assess correlations between specific mutations and K147 methylation status

  • Engineer mutations in cell models to directly test effects on K147 methylation

• Therapeutic Considerations:

  • Understanding how mutations affect K147 methylation could potentially inform therapeutic strategies

  • Compounds that target enzymes regulating K147 methylation might be explored for therapeutic development

What are common issues when working with Mono-methyl-HIST1H1E (K147) antibodies and how can they be resolved?

When working with Mono-methyl-HIST1H1E (K147) antibodies, researchers may encounter several technical challenges:

• High Background Signal:

  • Cause: Insufficient blocking, excessive antibody concentration, or non-specific binding

  • Solution: Increase blocking time/concentration, optimize antibody dilution (start with 1:50 for IF/ICC and adjust) , add 0.1% Tween-20 to wash buffers, increase wash duration and frequency

• Weak or No Signal:

  • Cause: Insufficient epitope exposure, over-fixation, antibody degradation, low target abundance

  • Solution: Optimize antigen retrieval (try heat-mediated retrieval at pH 6.0 or 9.0), reduce fixation time, use fresh antibody aliquots, increase antibody concentration or incubation time

• Inconsistent Results Between Experiments:

  • Cause: Variations in cell culture conditions affecting K147 methylation levels, antibody batch differences

  • Solution: Standardize cell culture conditions, use internal controls, maintain detailed records of antibody lots used, consider pooling data from multiple experimental runs

• Aberrant Molecular Weight in Western Blots:

  • Cause: Histone proteins often migrate atypically on SDS-PAGE

  • Solution: Note that while the calculated molecular weight is 21.8 kDa, observed molecular weight is approximately 36 kDa ; use appropriate positive controls

• Storage and Handling Issues:

  • Cause: Repeated freeze-thaw cycles, improper storage

  • Solution: Aliquot antibody upon receipt to avoid freeze-thaw cycles, store at -20°C for long-term or 4°C for up to one month, avoid exposure to light with fluorescently-labeled secondary antibodies

How can I distinguish between mono-, di-, and tri-methylation signals at K147?

Distinguishing between different methylation states at K147 requires careful consideration of antibody specificity and experimental design:

• Antibody Selection:

  • Use antibodies specifically validated for mono-methylation at K147

  • Check cross-reactivity profiles against di- and tri-methylated variants in antibody documentation

  • Refer to the specificity table showing high specificity for K147me1 with negligible signal for unmodified K147 and no cross-reactivity with other modifications

• Validation Methods:

  • Peptide competition assays using specifically mono-, di-, or tri-methylated K147 peptides

  • Western blot analysis of samples enriched for different methylation states

  • Mass spectrometry validation of immunoprecipitated material

• Control Experiments:

  • Use methyltransferase inhibitors that preferentially affect specific methylation states

  • Compare with samples where known methyltransferases for mono-, di-, or tri-methylation are knocked down

  • Include positive controls where available for each methylation state

• Analytical Approaches:

  • Sequential immunoprecipitation to deplete one methylation state before probing for another

  • Correlation analysis with other histone marks known to associate with specific methylation states

  • Quantitative analysis of signal intensities under standardized conditions

• Technical Considerations:

  • Different methylation states may require adjusted antigen retrieval methods

  • Signal-to-noise ratios may vary between different methylation state-specific antibodies

  • Consider the biological distribution of each methylation state when interpreting results

What considerations should be made when integrating Mono-methyl-HIST1H1E (K147) antibody data with other epigenetic profiling techniques?

Integrating data from Mono-methyl-HIST1H1E (K147) antibody experiments with other epigenetic techniques requires careful analytical approaches:

What is the current understanding of K147 monomethylation in chromatin organization?

Recent research has expanded our understanding of K147 monomethylation in chromatin organization:

• Nucleosome Spacing: K147me1 correlates with relaxed chromatin structures in gene-rich regions, suggesting a role in maintaining optimal spacing between nucleosomes. This modification may create a more accessible chromatin environment without completely disrupting the higher-order structure.

• Chromatin Compaction Regulation: Unlike charge-altering modifications (acetylation/phosphorylation), methylation at K147 modulates histone-DNA interactions through more subtle mechanisms, potentially affecting the binding kinetics rather than electrostatic properties.

• Interaction with Chromatin Remodelers: Emerging evidence suggests K147me1 may serve as a recognition site for specific chromatin remodeling complexes, facilitating targeted chromatin reorganization.

• Cell-Type Specific Patterns: Different cell types exhibit distinct patterns of K147me1 distribution, likely reflecting their specific gene expression programs and chromatin architecture requirements.

• Cell Cycle Dynamics: Levels of K147me1 appear to fluctuate during the cell cycle, potentially playing a role in the dramatic chromatin reorganization that occurs during mitosis and subsequent chromatin reassembly.

How does K147 methylation status correlate with gene expression patterns?

The relationship between K147 methylation and gene expression represents an emerging area of research:

• Enhancer Activity: K147me1 appears to correlate with enhancer activity, particularly in gene-rich regions where it may facilitate the formation of long-range chromatin interactions necessary for enhancer-promoter communication.

• Transcriptional Regulation: While not directly binding to DNA like transcription factors, K147me1 influences chromatin accessibility, affecting the ability of transcriptional machinery to access target genes.

• Context-Dependent Effects: The same K147me1 mark may have different effects on gene expression depending on:

  • Genomic context (promoter vs. gene body vs. intergenic)

  • Presence of other histone modifications

  • Cell type and developmental stage

  • Environmental conditions and cellular stress

• Relationship to DNA Methylation: Emerging data suggests interplay between K147 methylation and DNA methylation patterns, with potential reciprocal regulation affecting gene silencing.

• Developmental Programming: Studies indicate that K147me1 patterns established during development may contribute to cell fate decisions and lineage-specific gene expression programs.

What is the relationship between HIST1H1E mutations, K147 methylation, and Rahman syndrome?

Recent research has begun to elucidate connections between HIST1H1E mutations, K147 methylation, and Rahman syndrome pathogenesis:

• Mutation Clustering: Pathogenic HIST1H1E variants are remarkably clustered in a 99-bp region of the C-terminal domain, with a recently reported novel variant (c.505_506insT; p.Lys169IlefsTer27) extending this cluster by 42-bp downstream . This clustering suggests the functional importance of this region, which includes the K147 residue.

• Frameshift Consequences: The reported frameshift mutation (c.416_419dupAGAA, p.Ala141GlufsTer56) occurs extremely close to the K147 methylation site , potentially affecting methylation at this residue and its downstream functional effects.

• Shared C-Terminal Sequences: Despite different mutation positions, the resulting mutant proteins often share the same altered C-terminal sequences. For example, all 20 previously reported C-terminal domain pathogenic variants share the same last 38 amino acids .

• Phenotypic Heterogeneity: Different HIST1H1E mutations can lead to varying clinical presentations, even among patients with mutations affecting similar regions. This suggests complex relationships between specific mutations, resulting modifications (including K147 methylation), and phenotypic outcomes .

• Emerging Research Directions: Current investigations focus on:

  • How specific mutations affect K147 methylation status

  • Whether altered K147 methylation contributes to the neurodevelopmental features of Rahman syndrome

  • Potential therapeutic approaches targeting the epigenetic consequences of HIST1H1E mutations

How does using Mono-methyl-HIST1H1E (K147) antibodies compare with studying other histone H1 modifications?

When comparing studies of K147 monomethylation with other H1 modifications:

• Technical Differences:

  • K147me1 antibodies target a specific modification in the C-terminal domain, while antibodies to phosphorylated H1 (common in mitosis) often target the N-terminal domain

  • Extraction protocols may need optimization depending on modification type, as some modifications affect histone solubility

  • Signal intensity and distribution patterns vary significantly between different H1 modifications

• Biological Context:

  Modification	Typical Function	Genomic Distribution	Technique Considerations
  K147me1	Chromatin remodeling, DNA repair	Gene-rich, relaxed chromatin	Requires high antibody specificity
  T17 phosphorylation	Cell cycle regulation	Heterochromatin during mitosis	Often requires synchronized cells
  K63me1	Transcriptional regulation	Active gene regions	Different epitope accessibility
  Various acetylation sites	Chromatin decompaction	Transcriptionally active regions	May require milder fixation

• Modification Interdependence:

  • Some H1 modifications are mutually exclusive while others are cooperative

  • Sequential modification patterns may exist where one modification influences the occurrence of another

  • Consider the possibility of modification crosstalk when designing experiments

• Evolutionary Conservation:

  • K147 methylation appears in multiple species, suggesting functional importance

  • Other H1 modifications show variable conservation across species, requiring careful consideration when extrapolating between model systems

• Methodological Adaptation:

  • K147me1 detection may require specific buffer conditions to preserve the modification

  • Different modifications may have different stability during experimental procedures

  • Consider combined approaches to study multiple modifications simultaneously

What advantages and limitations does immunological detection of K147 methylation have compared to mass spectrometry-based approaches?

Understanding the trade-offs between antibody-based and mass spectrometry approaches for studying K147 methylation:

• Sensitivity Comparison:

  • Antibody-Based Methods: Offer high sensitivity for detecting specific modifications in small samples

  • Mass Spectrometry: Requires larger sample amounts but provides absolute quantification

• Specificity Considerations:

  • Antibody-Based Methods: Subject to potential cross-reactivity issues, though validation data shows high specificity for K147me1

  • Mass Spectrometry: Provides unambiguous identification of modifications with exact mass determination

• Throughput and Scalability:

  • Antibody-Based Methods: Higher throughput for screening multiple samples

  • Mass Spectrometry: Lower throughput but can simultaneously detect multiple modifications on the same protein

• Spatial Information:

  • Antibody-Based Methods: Preserve spatial information through IF/ICC techniques

  • Mass Spectrometry: Typically sacrifices spatial information but excels at detecting co-occurring modifications

• Quantification Approaches:

  • Antibody-Based Methods:

    • Semi-quantitative unless carefully calibrated

    • Signal intensity can be affected by epitope accessibility

    • Relative quantification between samples is more reliable than absolute measurements

  • Mass Spectrometry:

    • Provides absolute quantification when using isotope-labeled standards

    • Can determine stoichiometry of modifications

    • Less affected by structural context that might limit antibody access

• Novel Modification Discovery:

  • Antibody-Based Methods: Limited to detecting known modifications for which antibodies exist

  • Mass Spectrometry: Can discover novel or unexpected modifications

How do research findings on K147 methylation compare across different model systems and human studies?

Comparative analysis of K147 methylation research across different experimental systems reveals important considerations:

What emerging techniques might enhance the study of K147 methylation?

Several cutting-edge methodologies show promise for advancing K147 methylation research:

• Single-Cell Epigenomics:

  • Single-cell ChIP-seq adaptations could reveal cell-to-cell variability in K147me1 distribution

  • Integration with single-cell transcriptomics would link K147me1 patterns to gene expression at unprecedented resolution

  • Emerging microfluidic approaches may enable processing of limited clinical samples

• Live-Cell Imaging:

  • Methylation-specific nanobodies could enable real-time visualization of K147me1 dynamics

  • FRET-based sensors might detect changes in K147 methylation status during cellular processes

  • Correlative light and electron microscopy could connect K147me1 patterns to ultrastructural features

• Spatial Epigenomics:

  • Combining K147me1 antibody detection with spatial transcriptomics to maintain tissue context

  • Multiplex immunofluorescence techniques to simultaneously visualize multiple histone modifications

  • Imaging mass cytometry to preserve spatial relationships while quantifying modification levels

• Targeted Epigenome Editing:

  • CRISPR-dCas9 fused to methyltransferases or demethylases to manipulate K147 methylation at specific loci

  • Optogenetic control of K147 methylation writers/erasers to study temporal dynamics

  • Site-specific introduction of modified histones to study functional consequences

• Computational Approaches:

  • Machine learning algorithms to predict K147me1 distribution based on DNA sequence and other epigenetic features

  • Network analysis to place K147me1 in broader epigenetic regulatory networks

  • Molecular dynamics simulations to understand how K147 methylation affects chromatin fiber structure

What are the most significant unanswered questions regarding K147 methylation in HIST1H1E?

Despite progress in understanding K147 methylation, several critical questions remain:

• Enzymatic Regulation:

  • Which methyltransferases and demethylases specifically act on K147?

  • How is the activity of these enzymes regulated in different cellular contexts?

  • Do HIST1H1E mutations affect enzyme recruitment or activity?

• Reader Proteins:

  • What specific proteins recognize and bind to K147me1?

  • How does this recognition translate into functional outcomes?

  • Are there tissue-specific readers with specialized functions?

• Functional Significance:

  • What is the direct impact of K147 methylation on chromatin structure at the molecular level?

  • How does this modification influence transcription factor binding and enhancer function?

  • What role does K147me1 play in cellular differentiation and development?

• Disease Relevance:

  • How do alterations in K147 methylation contribute to the pathogenesis of Rahman syndrome?

  • Are there connections to other neurodevelopmental disorders or cancer?

  • Could targeting K147 methylation have therapeutic potential?

• Environmental Influence:

  • How do environmental factors affect K147 methylation patterns?

  • Is K147 methylation responsive to cellular stress or metabolic changes?

  • Could K147me1 serve as a biomarker for environmental exposures?

How might understanding K147 methylation contribute to therapeutic approaches for HIST1H1E-related disorders?

The potential therapeutic implications of K147 methylation research are significant:

• Diagnostic Applications:

  • K147me1 levels might serve as biomarkers for disease progression or treatment response

  • Altered patterns could potentially distinguish between different HIST1H1E mutation types

  • Integration with other epigenetic markers could improve diagnostic accuracy

• Drug Development Targets:

  • Enzymes regulating K147 methylation represent potential therapeutic targets

  • Small molecules that mimic or block interactions with K147me1 readers could modulate downstream effects

  • Compounds that stabilize or disrupt specific chromatin conformations related to K147me1 might normalize gene expression

• Personalized Medicine Approaches:

  • K147 methylation profiles might predict individual responses to epigenetic therapies

  • Mutation-specific effects on K147 methylation could inform tailored treatment strategies

  • Combinatorial approaches targeting multiple epigenetic modifications might address complex phenotypes

• Gene Therapy Considerations:

  • Understanding how K147 methylation affects chromatin packaging could inform gene therapy vector design

  • CRISPR-based approaches might target both the genetic mutation and resulting epigenetic dysregulation

  • Modification-specific epigenome editing could potentially normalize K147me1 patterns

• Developmental Timing:

  • Knowledge of when K147 methylation patterns are established during development

  • Potential critical windows for therapeutic intervention

  • Reversibility assessment of established epigenetic alterations