The Mono-methyl-HIST1H1C (K105) Antibody is a rabbit polyclonal antibody designed to detect mono-methylation at lysine 105 (K105) of the HIST1H1C protein, a member of the histone H1 family. Histone H1 proteins are critical for chromatin compaction and transcriptional regulation, with post-translational modifications like methylation playing roles in epigenetic signaling . This antibody serves as a specialized tool for studying site-specific histone modifications in human cells, particularly in cancer research and chromatin dynamics .
The antibody is validated for use in multiple experimental workflows:
Histone H1 modifications, including methylation, influence chromatin structure and gene expression. While the antibody targets K105 methylation, studies on related residues (e.g., H1.4K85 methylation by WHSC1) demonstrate that such modifications enhance stemness in squamous cell carcinoma of the head and neck (SCCHN) . This suggests K105 methylation may similarly regulate oncogenic pathways or DNA damage responses .
Specificity: Recognizes mono-methylated K105 without cross-reactivity to unmodified H1.2 or other histone variants .
Molecular Weight: Detects HIST1H1C at ~21 kDa (calculated) but may appear at 32–33 kDa due to post-translational modifications .
Species Restriction: Limited to human samples; cross-reactivity with other species untested .
Quantitative Use: Requires optimization for ELISA due to variable epitope accessibility in chromatin .
This antibody could advance studies on histone H1’s role in cancer epigenetics, particularly in SCCHN or other malignancies with dysregulated chromatin modifiers . Combining it with WHSC1 inhibitors may reveal therapeutic synergies targeting histone methylation pathways .
Histone H1 proteins bind to linker DNA between nucleosomes, forming the chromatin fiber. These histones are crucial for condensing nucleosome chains into higher-order structures. Furthermore, they regulate individual gene transcription through chromatin remodeling, nucleosome spacing, and DNA methylation.
The following studies highlight the diverse roles of Histone H1:
Histone H1.2, encoded by the HIST1H1C gene, is a linker histone that binds to linker DNA between nucleosomes, forming the macromolecular structure known as the chromatin fiber. This protein plays essential roles in the condensation of nucleosome chains into higher-order structured fibers. Beyond its structural function, H1.2 acts as a regulator of individual gene transcription through chromatin remodeling, nucleosome spacing, and DNA methylation mechanisms .
The distribution of histone H1 throughout the genome is not uniform. Active and poised gene promoters are characterized by reduced histone H1 levels, while inactive genes and heterochromatin regions are enriched with H1. This differential distribution contributes significantly to gene expression regulation and heterochromatin maintenance . H1.2 is one of at least 11 H1 variants in mammals, with specific variants showing tissue-specific and developmental stage-specific expression patterns.
K105 monomethylation represents a specific post-translational modification of histone H1.2 that likely affects its function in chromatin organization and gene regulation. While direct research on K105 methylation is still emerging, related studies on histone H1 methylation provide valuable insights. For instance, monomethylation of H1.4 at lysine 85 (K85) by the methyltransferase WHSC1 enhances stemness features in cancer cells and promotes transcriptional activation of OCT4 .
By extrapolation, K105 monomethylation of HIST1H1C likely plays regulatory roles in:
Modulating chromatin accessibility at specific genomic loci
Facilitating interactions with transcriptional regulators
Potentially influencing cellular differentiation programs
Contributing to oncogenic or tumor-suppressive mechanisms in various cancer types
The specific lysine position (K105) suggests a unique functional role that may differ from other histone modifications, making it an important target for epigenetic research.
The Mono-methyl-HIST1H1C (K105) antibody serves as a powerful tool for investigating this specific histone modification across multiple experimental platforms:
| Application | Recommended Dilution | Key Benefits | Research Context |
|---|---|---|---|
| ELISA | As specified by manufacturer | Quantitative detection | Measuring modification levels across samples |
| Immunofluorescence (IF) | 1:1-1:10 | Cellular localization | Visualizing nuclear distribution patterns |
| Western Blotting | 1:500 (based on related antibodies) | Protein-level detection | Quantifying modification across conditions |
| ChIP/ChIP-seq | Optimization required | Genome-wide mapping | Identifying genomic targets |
This antibody recognizes the peptide sequence surrounding the mono-methylated K105 site in human HIST1H1C, making it highly specific for this modification . For immunofluorescence applications, the recommended dilution range is 1:1-1:10, indicating the need for relatively concentrated antibody solutions to detect this modification effectively.
While both linker histone H1 and core histone modifications affect chromatin structure and function, several key differences exist:
Structural context: H1 methylation occurs on the linker histone that sits outside the nucleosome core, potentially affecting higher-order chromatin folding rather than direct DNA-histone interactions within the nucleosome.
Functional outcomes: Research on H1.4K85 monomethylation indicates it can promote transcriptional activation and stemness features in cancer cells , suggesting functions that may complement or counterbalance those of core histone modifications.
Regulatory mechanisms: The enzymes responsible for H1 methylation may differ from those modifying core histones. For instance, WHSC1, primarily known for H3K36 di-methylation, also mono-methylates H1.4 at K85 .
Genomic distribution: H1 variants show non-uniform distribution throughout the genome, with depleted levels at active promoters and enriched presence at inactive genes and heterochromatin , creating distinct modification landscapes.
Biological significance: Alterations in histone H1 content can lead to genome-wide replication initiation pattern changes and replication-transcription conflicts , highlighting unique roles compared to core histone modifications.
Multiple complementary techniques can be employed to detect and characterize H1.2 monomethylation:
| Technique | Application | Strengths | Limitations |
|---|---|---|---|
| Immunoblotting | Protein level detection | Quantitative; detects modification in bulk samples | Limited spatial information |
| Immunofluorescence | Cellular localization | Visualizes nuclear distribution | Limited quantification |
| ChIP/ChIP-seq | Genomic mapping | Identifies target genes and regulatory regions | Requires optimization for linker histones |
| Mass Spectrometry | PTM identification | Definitively identifies modifications and their precise locations | Requires specialized equipment |
| In vitro methyltransferase assays | Enzymatic activity | Identifies responsible enzymes | May not reflect in vivo conditions |
For generating robust data, researchers typically combine multiple approaches. For instance, the identification of WHSC1 as a H1 methyltransferase involved initial protein interaction studies using immunoprecipitation followed by mass spectrometry, with subsequent confirmation through in vitro methyltransferase assays and the development of modification-specific antibodies .
Optimizing ChIP protocols for Mono-methyl-HIST1H1C (K105) detection requires careful consideration of linker histone dynamics and modification-specific challenges:
| Parameter | Standard Approach | Optimized Approach for H1.2K105me1 | Rationale |
|---|---|---|---|
| Crosslinking | 1% formaldehyde, 10 min | 1% formaldehyde, 5-8 min | Prevent over-crosslinking that could mask epitopes |
| Sonication | 200-500bp fragments | 150-300bp fragments | Improved resolution for linker histone binding sites |
| Antibody concentration | Standard dilutions | Higher concentration (1:1-1:10) | Ensuring sufficient capture of the specific modification |
| Blocking | Standard blocking | Additional BSA (0.5-1%) | Reducing background signal |
| Controls | IgG control | IgG control + unmodified H1.2 + other H1 variants | Ensuring specificity against related proteins |
| Elution conditions | Standard elution | Optimized for specific antibody | Maximizing recovery of bound material |
For ChIP-seq applications specifically targeting chromatin regions with H1.2K105 monomethylation, researchers should consider:
Increasing sequencing depth to at least 30 million reads to capture potentially sparse signals
Using spike-in controls for normalization
Implementing specialized peak calling algorithms that account for the broader distribution patterns of linker histones
Additionally, designing primers for three different regions of the human HIST1H1C promoter ranging from -2000bp to the transcription start site can help validate ChIP-qPCR results, similar to approaches used in H1C promoter studies .
Distinguishing between histone H1 variants presents several technical and biological challenges:
Antibody cross-reactivity: High sequence homology between H1 variants (particularly H1.2-H1.5) makes generating truly variant-specific antibodies difficult.
Similar biochemical properties: H1 variants have similar molecular weights and charge distributions, complicating separation by standard techniques.
Modification site conservation: Some modification sites may be conserved across variants, making it challenging to attribute a specific function to one variant.
Functional redundancy: Knockout studies have shown that elimination of three H1 subtypes was required to reach 50% of normal H1 levels and cause embryonic lethality in mice, suggesting functional overlap .
Context-dependent functions: The same H1 variant may have different functions depending on cell type, developmental stage, or disease state.
| Challenge | Methodological Solution | Implementation |
|---|---|---|
| Antibody specificity | Epitope mapping and validation | Test against multiple variants; peptide competition assays |
| Variant identification | Mass spectrometry | Use top-down proteomics to analyze intact histones with modifications |
| Genomic distribution | ChIP-seq with variant-specific antibodies | Compare binding profiles across variants |
| Functional redundancy | Combinatorial knockout approaches | Sequential or simultaneous targeting of multiple variants |
| Bioinformatic analysis | Variant-specific motif identification | Computational prediction of variant-specific binding sites |
The combination of these approaches provides a more comprehensive understanding of variant-specific roles in chromatin regulation.
| Experimental Strategy | Methodological Approach | Expected Outcomes |
|---|---|---|
| Genomic profiling | ChIP-seq for K105me1 in cancer vs. normal | Identification of differentially modified regions |
| Transcriptome analysis | RNA-seq integrated with ChIP-seq | Correlation between modification and expression changes |
| Functional studies | CRISPR-engineered K105A/R mutations | Phenotypic consequences of preventing methylation |
| Sphere formation assays | Wild-type vs. K105-mutant cells | Assessment of cancer stemness properties |
| Cancer progression models | K105me1 profiling across stages | Potential prognostic value of the modification |
For robust experimental design, researchers should consider creating cellular models similar to those described for H1.4K85 studies, where wild-type HIST1H1C and a K105A mutant (preventing methylation) are compared for their effects on cancer cell phenotypes . This approach would allow direct assessment of how this specific modification influences cancer-related properties like proliferation, sphere formation capability, and expression of stemness markers.
While the specific methyltransferase responsible for K105 methylation of HIST1H1C has not been definitively identified in the search results, the identification of WHSC1 as the enzyme responsible for H1.4K85 monomethylation provides a valuable research model .
| Approach | Methodology | Analytical Considerations |
|---|---|---|
| Sequence analysis | Compare sequences surrounding K105 and K85 | Identify conserved motifs that might be recognized by the same enzyme |
| Protein interaction studies | Co-immunoprecipitation followed by mass spectrometry | Identify proteins that interact with regions containing K105 |
| In vitro methyltransferase assays | Recombinant enzymes with HIST1H1C substrates | Test WHSC1 and other known histone methyltransferases |
| CRISPR knockout screens | Target known methyltransferases | Assess effects on K105 methylation levels |
| Domain analysis | Examine SET domains of candidate enzymes | Predict substrate specificity based on structure |
WHSC1 (also known as NSD2/MMSET) was previously characterized as an H3K36 di-methyltransferase before its H1.4K85 mono-methylation activity was discovered . This suggests that other known histone methyltransferases may have uncharacterized activities toward linker histones. The discovery approach for K105 methyltransferases should mirror that used for H1.4K85, including immunoprecipitation, mass spectrometry, and in vitro validation.
Based on successful approaches in related histone modification studies, the following experimental design would be optimal:
| Experimental Phase | Methodological Approach | Key Considerations |
|---|---|---|
| Genetic Engineering | CRISPR/Cas9-mediated K105A/R mutations | Generate isogenic cell lines differing only at K105 |
| Rescue Experiments | Re-express wild-type or mutant HIST1H1C | Confirm specificity of observed phenotypes |
| Genomic Profiling | ChIP-seq for modified vs. unmodified | Map genomic distribution of the modification |
| Transcriptome Analysis | RNA-seq of wild-type vs. mutant cells | Identify differentially expressed genes |
| Chromatin Accessibility | ATAC-seq analysis | Determine effects on chromatin structure |
| Cellular Phenotyping | Proliferation, migration, sphere formation | Assess functional consequences |
| Higher-order Structure | Hi-C or similar techniques | Examine 3D genome organization changes |
For detecting subtle phenotypes, researchers should employ:
Time-course experiments to capture dynamic changes
Stress conditions to reveal context-dependent functions
Multiple cell types to assess tissue-specific effects
Developmental models to examine stage-specific roles
This comprehensive approach mirrors successful studies of H1.4K85 methylation, where sphere formation assays revealed higher sphere numbers in cells expressing wild-type H1.4 compared to those with K85A mutations . Similar assays would likely detect functional consequences of HIST1H1C K105 methylation.
Interpreting contradictory results regarding histone H1 methylation across cancer types requires careful consideration of biological and technical factors:
Researchers should consider that different H1 variants may play distinct roles across cancer types. For example, while H1.2 promotes hepatocarcinogenesis , other variants might have different functions in other cancers. Analysis should incorporate:
Multi-dimensional data integration combining:
ChIP-seq for histone modifications
RNA-seq for expression profiles
Mutation data for genetic context
Clinical outcomes for relevance
Computational approaches to identify complex patterns, such as:
Machine learning for pattern recognition
Network analysis for functional connections
Causal inference methods for mechanism identification
This integrated approach can help reconcile apparently contradictory findings by identifying context-specific factors that modulate histone H1 modification functions.
Recent methodological advances have significantly enhanced our ability to study histone H1 variants and their modifications:
| Technology Area | Advanced Technique | Application to H1 Modification Research |
|---|---|---|
| Genomics | CUT&RUN/CUT&Tag | Higher resolution mapping of H1 variant distribution |
| Proteomics | Top-down mass spectrometry | Analysis of intact histones with combinatorial modifications |
| Microscopy | Live-cell super-resolution imaging | Dynamic visualization of H1 variants in chromatin |
| Genetic Engineering | Prime editing/base editing | Precise modification of endogenous H1 genes |
| Structural Biology | Cryo-EM of nucleosome arrays | Visualization of H1-dependent higher-order structures |
| Biophysical Analysis | Single-molecule approaches | Real-time dynamics of H1 binding/dissociation |
For studies specifically focused on H1.2 K105 monomethylation, researchers could apply these advances through:
Developing engineered antibody fragments (Fabs) specific to K105me1 for CUT&RUN experiments, providing higher resolution mapping than traditional ChIP-seq
Employing proximity labeling methods (e.g., APEX2) fused to H1.2 to identify proteins that specifically interact with the methylated form
Utilizing nucleosome reconstitution systems with modified H1.2 to examine structural consequences in vitro
Applying nascent RNA sequencing approaches to correlate modification patterns with transcriptional dynamics
These methodological advances enable more precise interrogation of the functional consequences of specific H1 modifications in diverse biological contexts.