Mono-methyl-HIST1H1C (K45) Antibody

What is HIST1H1C and what biological functions does it serve?

HIST1H1C (also known as H1.2, H1F2, or Histone H1c) is a member of the linker histone H1 family that binds to linker DNA between nucleosomes, forming the macromolecular structure known as the chromatin fiber. Functionally, HIST1H1C is necessary for the condensation of nucleosome chains into higher-order structured fibers, influencing nucleosome positioning and spacing. Beyond structural roles, it acts as a regulator of individual gene transcription through chromatin remodeling, nucleosome spacing, and DNA methylation mechanisms . The protein contains 213 amino acid residues, is localized to the nucleus and chromosomes, and features various post-translational modifications, particularly phosphorylation .

How does mono-methylation at K45 position differ functionally from methylation at other lysine residues in HIST1H1C?

Mono-methylation at K45 in HIST1H1C represents a specific post-translational modification that likely affects chromatin structure and gene regulation differently than modifications at other positions. While research specifically on K45 methylation is still developing, comparative studies with other methylation sites provide context. For instance, WHSC1-mediated mono-methylation of histone H1.4 at K85 has been shown to induce transcriptional activation of genes like OCT4, promoting stemness features in squamous cell carcinoma . Methylation at different lysine residues creates distinct binding surfaces for effector proteins, producing varied downstream effects on chromatin accessibility and transcriptional activity. The position of K45 within the histone may influence its interaction with DNA and other nuclear proteins, potentially affecting both local and global chromatin architecture.

What are the known methyltransferases responsible for HIST1H1C K45 mono-methylation?

While the search results don't specifically identify the methyltransferase for K45 mono-methylation of HIST1H1C, they provide important contextual information. WHSC1 (Wolf-Hirschhorn syndrome candidate 1) has been identified as a protein lysine methyltransferase that mono-methylates histone H1.4 at K85 . This finding suggests that members of the SET domain-containing methyltransferase family may be candidates for K45 methylation of HIST1H1C. Research methodologies to identify the responsible methyltransferase would typically include in vitro methyltransferase assays using recombinant histones and candidate enzymes, followed by mass spectrometry verification, similar to how WHSC1 was identified for H1.4K85 methylation .

What are the optimal experimental conditions for detecting mono-methyl-HIST1H1C (K45) in different cell types?

For optimal detection of mono-methyl-HIST1H1C (K45), researchers should consider:

• Sample preparation: Nuclear extraction protocols are essential for concentrating nuclear proteins. The Nuclear Extraction kit (Active Motif) has been successfully used in similar histone modification studies . For cell lysis, CelLytic M reagent with complete protease inhibitor cocktail effectively preserves post-translational modifications .

• Application-specific dilutions:

  Application	Recommended Dilution	Incubation Conditions
  Western Blot	1:100-1:1000	Overnight at 4°C
  Immunocytochemistry	1:20-1:200	1-2 hours at room temperature
  Immunofluorescence	1:10-1:100	1-2 hours at room temperature
  ELISA	As per kit instructions	As per kit instructions

• Cell type considerations: When working with cancer cell lines like SCCHN cells (SCC-35, PE/CA-PJ15, FaDu), culture in appropriate media supplemented with 10% fetal bovine serum, 1% penicillin/streptomycin, and 2 nM L-glutamine at 37°C with 5% CO2 . For non-cancer cells, maintenance conditions should be modified accordingly based on specific cell requirements.

How can I validate the specificity of a mono-methyl-HIST1H1C (K45) antibody?

Validating the specificity of a mono-methyl-HIST1H1C (K45) antibody requires multiple complementary approaches:

• Peptide competition assay: Pre-incubate the antibody with increasing concentrations of the synthetic mono-methyl-K45 peptide before immunoblotting. Signal reduction confirms specificity.

• Knockout/knockdown controls: Use CRISPR/Cas9 to knockout HIST1H1C or siRNA to knockdown expression (similar to the WHSC1 siRNA approach described in the search results ). The methylation signal should decrease in these conditions.

• Methyltransferase inhibition/deletion: Inhibit or deplete the methyltransferase responsible for K45 methylation and confirm signal reduction.

• Cross-reactivity testing: Test the antibody against unmethylated HIST1H1C peptides and peptides methylated at other positions to ensure no cross-reactivity.

• Mass spectrometry validation: Use mass spectrometry to confirm the presence and site-specificity of the modification in immunoprecipitated samples.

• Dot blot titration: Apply decreasing amounts of modified and unmodified peptides to membrane and probe with the antibody to determine sensitivity and specificity thresholds.

What are the recommended protocols for using mono-methyl-HIST1H1C (K45) antibody in chromatin immunoprecipitation (ChIP) experiments?

While specific ChIP protocols for mono-methyl-HIST1H1C (K45) antibody aren't detailed in the search results, a comprehensive protocol can be developed based on similar histone modification ChIP experiments:

• Crosslinking: Fix cells with 1% formaldehyde for 10 minutes at room temperature, then quench with 125mM glycine.

• Chromatin preparation:

  • Lyse cells in SDS lysis buffer

  • Sonicate to fragment chromatin to 200-500bp fragments

  • Verify fragmentation by gel electrophoresis

• Immunoprecipitation:

  • Pre-clear chromatin with protein A/G beads

  • Incubate chromatin with 2-5μg mono-methyl-HIST1H1C (K45) antibody overnight at 4°C

  • Add protein A/G beads and incubate for 2-4 hours

  • Wash sequentially with low salt, high salt, LiCl, and TE buffers

• DNA recovery:

  • Reverse crosslinks with proteinase K treatment at 65°C

  • Purify DNA using phenol-chloroform extraction or commercial kits

  • Quantify DNA by qPCR or prepare for sequencing

• Controls:

  • Input chromatin (non-immunoprecipitated)

  • IgG control (non-specific antibody)

  • Positive control regions (known to be enriched for mono-methyl-HIST1H1C)

• Data analysis: Calculate fold enrichment or percent input for target genomic regions.

How does mono-methylation of HIST1H1C compare to other histone H1 variants in terms of genomic distribution and function?

Mono-methylation of histone H1 variants shows distinct genomic distribution patterns that correlate with different functional outcomes:

• Genomic distribution comparison:

  • HIST1H1C (H1.2) mono-methylation likely associates with specific genomic regions related to its particular functions

  • In comparison, WHSC1-mediated H1.4K85 mono-methylation has been shown to associate with promoter regions of stemness-related genes like OCT4

• Functional implications:

  • While H1 is traditionally associated with transcriptional repression through chromatin compaction, mono-methylation can create binding sites for specific effector proteins

  • H1.4K85 mono-methylation is associated with transcriptional activation and stemness features in SCCHN cells

  • Different H1 variants show tissue-specific expression patterns and varied roles in development and differentiation

• Experimental determination approaches:

  • ChIP-seq using variant-specific antibodies to map genomic localization

  • Sequential ChIP (re-ChIP) to determine co-occurrence with other histone modifications

  • Integration with transcriptomic data to correlate with gene expression

A comprehensive understanding requires mapping mono-methylation patterns across different H1 variants using variant-specific antibodies combined with genomic sequencing approaches.

What is the relationship between HIST1H1C mono-methylation and cancer progression?

The relationship between HIST1H1C mono-methylation and cancer progression can be inferred from parallel studies of histone H1 modifications in cancer:

• Evidence from comparable H1 modifications:

  • WHSC1-mediated mono-methylation of H1.4K85 has been shown to induce stem-cell like features in squamous cell carcinoma of the head and neck (SCCHN)

  • This modification was found to promote expression of stemness factors like OCT4

  • The presence of cancer stem-like cells is associated with therapeutic resistance and poor outcomes

• Mechanistic considerations:

  • Mono-methylation of HIST1H1C likely alters chromatin accessibility at specific genomic regions

  • These changes may affect expression of genes involved in proliferation, differentiation, or therapy resistance

  • The modification may create binding sites for specific reader proteins that mediate downstream effects

• Therapeutic implications:

  • The enzymes responsible for H1 methylation, such as WHSC1, represent potential therapeutic targets

  • Development of WHSC1 inhibitors is mentioned as a potential therapeutic approach for SCCHN

  • Targeting histone modifications may offer approaches to overcome therapy resistance

How can mono-methyl-HIST1H1C (K45) antibody be used to study chromatin dynamics during cellular differentiation?

The mono-methyl-HIST1H1C (K45) antibody provides a powerful tool for investigating chromatin reorganization during differentiation:

• Time-course analysis:

  • Track changes in K45 mono-methylation levels during differentiation using Western blotting

  • Correlate these changes with expression of differentiation markers

  • Combine with ChIP-seq at different time points to map genomic redistribution

• Cell population heterogeneity assessment:

  • Use immunofluorescence with mono-methyl-HIST1H1C (K45) antibody (1:10-1:100 dilution) to quantify modification levels in single cells

  • Combine with markers of differentiation status to characterize heterogeneous populations

  • Employ flow cytometry for high-throughput analysis of cellular subpopulations

• Functional studies:

  • Compare differentiation potential in cells with normal versus altered K45 methylation

  • Use CRISPR/Cas9 to generate K45 mutants (K45A or K45R) to prevent methylation

  • Assess changes in sphere formation capacity as an indicator of stemness, similar to assays used in SCCHN studies

• Mechanistic investigations:

  • Identify proteins interacting with mono-methylated K45 using techniques like immunoprecipitation followed by mass spectrometry

  • Use similar approaches to those that identified H1 as a WHSC1-interacting protein

  • Determine how these interactions change during differentiation

What are common artifacts or false positives when using mono-methyl-HIST1H1C (K45) antibody, and how can they be mitigated?

When working with mono-methyl-HIST1H1C (K45) antibody, researchers may encounter several artifacts:

• Cross-reactivity with other methylated histones:

  • Problem: The antibody may detect similar methylation sites on other histone proteins

  • Solution: Always validate specificity using peptide competition assays and include appropriate controls like methylation site mutants

• Degradation of histone modifications:

  • Problem: Methylation marks can be lost during sample preparation

  • Solution: Always include protease inhibitors, phosphatase inhibitors, and deacetylase inhibitors in lysis buffers; maintain samples at cold temperatures; process samples quickly

• Batch-to-batch antibody variability:

  • Problem: Different lots may show varying specificity and sensitivity

  • Solution: Validate each new lot against a standard sample; maintain a reference sample for quality control

• False negatives due to epitope masking:

  • Problem: Protein-protein interactions may block antibody access to the modification

  • Solution: Optimize extraction and denaturation conditions; try different fixation methods for immunofluorescence

• Background in immunostaining:

  • Problem: High background can obscure specific signals

  • Solution: Optimize blocking conditions; try different blocking agents (BSA, normal serum); increase washing steps; use recommended dilutions (1:20-1:200 for ICC, 1:10-1:100 for IF)

How can I quantitatively assess the level of HIST1H1C K45 mono-methylation across different experimental conditions?

Quantitative assessment of HIST1H1C K45 mono-methylation requires standardized approaches:

• Western blot quantification:

  • Use a dilution series of recombinant modified histone as a standard curve

  • Normalize signals to total HIST1H1C levels using a modification-insensitive antibody

  • Employ fluorescent secondary antibodies for wider linear detection range

  • Recommended dilution range: 1:100-1:1000

• ELISA-based quantification:

  • Develop sandwich ELISA using mono-methyl-HIST1H1C (K45) antibody for capture

  • Include calibration curves with synthetic modified peptides

  • This approach allows higher throughput compared to Western blotting

• Mass spectrometry-based quantification:

  • Employ targeted MS approaches (MRM/PRM) for absolute quantification

  • Use synthetic isotope-labeled peptides as internal standards

  • This provides the most accurate measurement of modification stoichiometry

• ImageJ analysis for immunofluorescence:

  • Calculate mean fluorescence intensity in nuclei

  • Correct for background and normalize to DAPI signal

  • Use recommended antibody dilutions (1:10-1:100)

• Data representation:

  Method	Normalization Approach	Units	Dynamic Range
  Western Blot	Total HIST1H1C	Relative units	~10-fold
  ELISA	Standard curve	ng/mL	~100-fold
  Mass Spec	Internal standard	fmol/μg protein	~1000-fold
  IF microscopy	Nuclear area	Mean fluorescence	~20-fold

What controls should be included in experiments using the mono-methyl-HIST1H1C (K45) antibody?

A robust experimental design with appropriate controls is essential:

• Positive controls:

  • Cell lines known to express high levels of mono-methyl-HIST1H1C (K45)

  • Recombinant mono-methylated HIST1H1C protein or synthetic peptide

  • Samples overexpressing the relevant methyltransferase

• Negative controls:

  • HIST1H1C knockout/knockdown cells (using siRNA approaches similar to those described for WHSC1)

  • K45A or K45R mutant HIST1H1C (similar to the H1.4K85A mutant approach)

  • Methyltransferase inhibitor-treated cells

  • Secondary antibody-only control (for immunostaining)

• Validation controls:

  • Peptide competition assay to confirm specificity

  • Independent detection method (e.g., mass spectrometry)

  • Alternative antibody recognizing the same modification

• Loading and normalization controls:

  • Total HIST1H1C levels (using modification-insensitive antibody)

  • Other nuclear proteins (e.g., histone H3) for nuclear extraction quality

  • GAPDH or β-actin for total protein loading

• Biological context controls:

  • Treatment conditions known to affect histone methylation

  • Time course to capture dynamic changes

  • Multiple cell types to assess tissue-specific patterns

How should changes in HIST1H1C K45 mono-methylation be interpreted in the context of gene expression changes?

Interpretation of HIST1H1C K45 mono-methylation in relation to gene expression requires integrated analysis:

• Correlation analysis approach:

  • Combine ChIP-seq data for mono-methyl-HIST1H1C (K45) with RNA-seq

  • Calculate Pearson/Spearman correlation between modification enrichment and transcript levels

  • Perform gene set enrichment analysis to identify affected pathways

• Contextual interpretation:

  • While H1 histones are traditionally associated with repressive chromatin, mono-methylation may have distinct effects

  • Compare with known effects of other H1 modifications, such as WHSC1-mediated H1.4K85 mono-methylation, which activates OCT4 expression and promotes stemness in SCCHN cells

  • Consider cell type specificity—effects may differ between cancer and normal cells

• Mechanistic insights:

  • Identify potential "reader" proteins that recognize the modification

  • Determine if the modification affects H1 binding to chromatin using FRAP (Fluorescence Recovery After Photobleaching)

  • Assess changes in chromatin accessibility at K45 mono-methylation sites using ATAC-seq

• Temporal dynamics:

  • Track both modification and expression changes over time

  • Establish whether modification changes precede, coincide with, or follow expression changes

  • This helps establish cause-effect relationships

What bioinformatic approaches are most effective for analyzing ChIP-seq data generated using mono-methyl-HIST1H1C (K45) antibody?

Effective bioinformatic analysis of mono-methyl-HIST1H1C (K45) ChIP-seq requires specialized approaches:

• Data preprocessing and quality control:

  • Filter low-quality reads (PHRED < 20)

  • Remove PCR duplicates

  • Check for ChIP enrichment using normalized strand cross-correlation (NSC) and relative strand cross-correlation (RSC)

• Peak calling strategies:

  • For broadly distributed modifications, use broad peak callers (SICER, MACS2 with broad flag)

  • For sharper peaks, standard peak callers (MACS2) are appropriate

  • Include input chromatin or IgG controls for background correction

• Integrative analysis:

  • Correlate with other histone modifications

  • Integrate with gene expression data (RNA-seq)

  • Compare with chromatin accessibility data (ATAC-seq, DNase-seq)

  • Analyze co-occurrence with transcription factor binding sites

• Genomic distribution analysis:

  • Characterize enrichment relative to genomic features (promoters, enhancers, gene bodies)

  • Compare with distributions of other H1 modifications, such as H1.4K85 mono-methylation, which has been found at promoters of stemness genes

  • Create aggregation plots around transcription start sites and other features

• Motif enrichment analysis:

  • Identify DNA sequence motifs enriched in regions with K45 mono-methylation

  • Predict transcription factors that might co-occur with the modification

How can mono-methyl-HIST1H1C (K45) patterns be integrated into broader epigenomic profiling studies?

Integration of mono-methyl-HIST1H1C (K45) data into comprehensive epigenomic studies:

• Multi-omic integration frameworks:

  • Use tools like ChromHMM or EpiSig to define chromatin states based on combinations of modifications

  • Apply dimensionality reduction techniques (PCA, t-SNE, UMAP) to visualize relationships between different epigenetic marks

  • Employ machine learning approaches to predict functional outcomes from modification patterns

• Cross-modification analysis:

  • Correlate mono-methyl-HIST1H1C (K45) with core histone modifications (H3K4me3, H3K27me3, H3K27ac)

  • Compare with other H1 modifications like H1.4K85 mono-methylation, which is associated with stemness in cancer

  • Identify synergistic or antagonistic relationships between modifications

• 3D genome organization integration:

  • Correlate modification patterns with chromatin interaction data (Hi-C, ChIA-PET)

  • Determine whether modified regions interact with each other in 3D space

  • Assess relationships to topologically associated domains (TADs) and chromatin loops

• Disease-specific considerations:

  • Compare modification patterns between normal and disease states

  • In cancer studies, correlate with mutations in epigenetic modifiers

  • Connect to patient outcomes for potential biomarker development, similar to how WHSC1 overexpression has been associated with poor differentiation in SCCHN

• Data visualization and sharing:

  • Develop browser tracks for genome browsers (UCSC, IGV)

  • Deposit data in repositories (GEO, ArrayExpress) with comprehensive metadata

  • Create integrative visualizations showing relationships between different epigenetic marks