bhmt Antibody

What is BHMT and why is it a significant research target?

BHMT (betaine-homocysteine S-methyltransferase) is a critical enzyme in the methionine cycle that catalyzes the conversion of betaine and homocysteine into dimethylglycine and methionine, respectively. This enzymatic activity is vital for maintaining proper homocysteine levels in the body . The significance of BHMT as a research target stems from its essential role in homocysteine metabolism and its implications in various pathological conditions including cardiovascular diseases and cancer progression . In particular, recent research has identified BHMT as a potential prognostic biomarker in hepatocellular carcinoma (HCC), where its expression is markedly decreased and linked to adverse clinical outcomes .

What tissue expression patterns should researchers expect when studying BHMT?

Researchers studying BHMT should expect predominant expression in the liver and kidney . According to comprehensive protein databases, BHMT is found exclusively in these tissues, with particularly high expression in hepatic cells . This tissue-specific expression pattern has important implications for experimental design and sample selection. When planning immunohistochemistry or tissue analysis experiments, researchers should use these tissues as positive controls and be cautious about interpreting apparent BHMT signals in other tissues, which may represent non-specific binding or cross-reactivity .

What are the key characteristics of BHMT protein that influence antibody selection?

When selecting antibodies for BHMT detection, researchers should consider these key protein characteristics:

These characteristics should be used to select antibodies that recognize the appropriate epitopes and perform well in the intended experimental applications . For instance, if studying nuclear functions of BHMT, researchers should select antibodies validated for nuclear protein detection.

How should researchers validate BHMT antibody specificity before experimental use?

Rigorous validation of BHMT antibody specificity should follow a multi-step process:

• Molecular weight verification: Perform Western blot analysis to confirm the detection of a band at approximately 45 kDa, which corresponds to the predicted molecular weight of BHMT .

• Positive and negative tissue controls: Test the antibody on liver and kidney samples (positive controls) versus tissues not known to express BHMT (negative controls) .

• Peptide competition assay: Pre-incubate the antibody with the immunizing peptide to confirm that this blocks specific signals.

• siRNA or CRISPR knockdown validation: In cell culture models expressing BHMT, reduce expression through genetic approaches and confirm reduced antibody signal.

• Cross-reactivity assessment: If working across species, validate that the antibody performs as expected in each species of interest. Available antibodies have reported reactivity with human, mouse, and rat BHMT, with predicted reactivity to bovine, horse, dog, and chicken orthologs .

This comprehensive validation approach ensures experimental results reflect true BHMT biology rather than technical artifacts.

Which applications are most suitable for different types of BHMT antibodies?

Different BHMT antibody formats are optimized for specific applications:

When designing experiments, researchers should select antibody formats based on the specific technical requirements of their application. For instance, for co-localization studies using immunofluorescence, conjugated antibodies with distinct fluorophores may be preferred .

What are the optimal experimental conditions for detecting BHMT using immunohistochemistry?

For optimal BHMT detection using immunohistochemistry:

• Tissue preparation: Formalin-fixed, paraffin-embedded (FFPE) liver and kidney tissues show reliable BHMT detection. Fixation time should be optimized (typically 24 hours) to preserve epitopes while maintaining tissue morphology .

• Antigen retrieval: Heat-induced epitope retrieval (HIER) using citrate buffer (pH 6.0) is generally effective. For some antibodies, EDTA buffer (pH 8.0) may yield better results. The optimal retrieval method should be determined empirically for each antibody .

• Blocking and antibody dilution: 5% normal serum (matched to the species of secondary antibody) in PBS with 0.1% Triton X-100 is recommended for blocking. Antibody dilutions should be determined empirically, but typically range from 1:100 to 1:500 for commercial BHMT antibodies .

• Detection system: For chromogenic detection, HRP-conjugated secondary antibodies with DAB substrate provide strong contrast. For fluorescent detection, Alexa Fluor conjugates offer excellent signal-to-noise ratios .

• Controls: Include both technical controls (no primary antibody) and biological controls (BHMT-negative tissues) to confirm signal specificity.

These optimized conditions maximize signal specificity while minimizing background, critical for accurate interpretation of BHMT expression patterns.

How can BHMT antibodies be used to investigate its role in hepatocellular carcinoma?

BHMT antibodies can be strategically employed to investigate its role in hepatocellular carcinoma through several methodological approaches:

• Expression profiling: Immunohistochemical analysis of BHMT in HCC tissue microarrays compared to adjacent normal liver tissue reveals downregulation patterns. Recent studies demonstrate marked decreases in BHMT expression in HCC tissues, correlating with adverse clinical outcomes .

• Prognostic modeling: BHMT protein levels detected by validated antibodies can be incorporated into prognostic models. Research indicates BHMT may serve as an ideal prognostic biomarker for anti-PD-L1 immunotherapy response in HCC patients .

• Immune infiltration correlation: Using multiplexed immunofluorescence with BHMT antibodies alongside immune cell markers can help validate bioinformatic findings suggesting BHMT promotes M1 macrophage infiltration .

• Methionine metabolism pathway analysis: Co-immunoprecipitation using BHMT antibodies can identify protein interaction partners within the methionine metabolism pathway, providing insights into the Hoffman effect (cancer cell dependence on exogenous methionine) in HCC .

• Therapeutic response stratification: BHMT expression detected via antibody-based methods may help stratify HCC patients for response to specific treatment modalities, particularly immunotherapies .

These applications highlight how BHMT antibodies facilitate investigation beyond simple detection, enabling mechanistic insights into HCC pathogenesis and potential therapeutic strategies.

What methodologies can researchers use to study the regulation of BHMT expression by SAM and NF-κB?

To investigate the regulation of BHMT expression by S-adenosylmethionine (SAM) and NF-κB, researchers can implement these methodological approaches:

• Northern blot and real-time RT-PCR analysis: Treat cell lines (e.g., HepG2) with SAM (0.25–5 mM) or MTA (0.25–1 mM) for various time points (up to 18h), then extract RNA and quantify BHMT expression. Normalize expression using appropriate housekeeping genes like HPRT1 or UBC using the 2^(-ΔΔCt) method .

• Promoter activity assays: Transfect cells with BHMT promoter-luciferase constructs (e.g., −347/+33-LUC) to monitor transcriptional activity in response to SAM/MTA treatment. This approach helps identify specific regulatory regions within the promoter .

• Electrophoretic mobility shift assays (EMSA): Use 32P-end labeled DNA fragments containing putative NF-κB binding sites from the BHMT promoter (−142 to −114, −271 to −246, and −310 to −285) to assess nuclear protein binding following SAM/MTA treatment. Perform supershift assays with anti-p50 and anti-p65 antibodies to confirm NF-κB involvement .

• Blocking NF-κB activation: Infect cells with adenoviruses carrying IκBSR (super-repressor) followed by SAM/MTA treatment to determine if the effects are NF-κB-dependent. Measure subsequent changes in BHMT expression by real-time PCR .

• Western blot analysis for nuclear translocation: Assess nuclear translocation of p65 and p50 NF-κB subunits in response to SAM/MTA treatment using subcellular fractionation and Western blotting with specific antibodies .

This multi-faceted approach provides comprehensive insights into the regulatory mechanisms controlling BHMT expression, particularly the repressive effects mediated through SAM-induced NF-κB activation.

How can researchers study BHMT in relation to homocysteine metabolism and cardiovascular disease risk?

To investigate BHMT's role in homocysteine metabolism and cardiovascular disease risk, researchers should implement these methodological approaches:

• Enzymatic activity assays: Measure BHMT activity in tissue samples by quantifying the conversion of betaine and homocysteine to dimethylglycine and methionine. This can be achieved using radioisotope-labeled substrates or HPLC-based methods coupled with antibody-based detection of BHMT protein levels to correlate expression with activity .

• Genetic association studies: Analyze BHMT polymorphisms in cardiovascular disease cohorts, using antibody-based methods to determine if protein expression varies with genotype. Disruptions in BHMT function due to genetic mutations have been linked to hyperhomocysteinemia, a cardiovascular risk factor .

• Dietary intervention studies: Examine how BHMT expression (detected via antibodies) responds to varying dietary intake of methionine and choline, which are known to influence BHMT expression. This approach helps understand nutrient-gene interactions relevant to cardiovascular health .

• Co-expression analyses: Use BHMT antibodies alongside markers of vascular inflammation to investigate correlations between aberrant BHMT expression and vascular pathology in tissue samples.

• BHMT knockout models: Generate BHMT-deficient cell lines or animal models using CRISPR/Cas9, then use BHMT antibodies to confirm knockout efficiency and study the resulting alterations in homocysteine metabolism and cardiovascular parameters.

These methods collectively provide a comprehensive understanding of BHMT's contribution to homocysteine metabolism and its implications for cardiovascular disease risk assessment and intervention.

What strategies should researchers employ when encountering inconsistent Western blot results with BHMT antibodies?

When faced with inconsistent Western blot results using BHMT antibodies, researchers should systematically troubleshoot using these strategies:

• Sample preparation optimization:

  • Ensure complete protein denaturation by adjusting boiling time and SDS concentration

  • Test different lysis buffers as BHMT (45 kDa) extraction efficiency may vary

  • Add protease inhibitors freshly to prevent degradation

  • Quantify protein accurately to ensure equal loading

• Antibody validation and optimization:

  • Titrate antibody concentrations (typically 1:100 to 1:2000 dilutions)

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

  • Test different antibody clones if available (monoclonal antibodies like H-7 may have different epitope recognition than polyclonal options)

  • Verify antibody lot consistency with manufacturer

• Technical considerations:

  • Optimize transfer conditions (time, buffer composition, membrane type)

  • Test both reducing and non-reducing conditions

  • Ensure appropriate blocking (5% non-fat milk or BSA)

  • Consider membrane stripping methods if re-probing

• Controls and verification:

  • Include positive controls (liver or kidney lysates)

  • Run recombinant BHMT protein as reference

  • Use housekeeping proteins appropriate for the tissue being studied

  • Verify results with a second detection method (e.g., ELISA)

By systematically addressing these factors, researchers can establish consistent and reliable Western blot protocols for BHMT detection.

How should researchers interpret conflicting BHMT expression data between different experimental techniques?

When encountering conflicting BHMT expression data between different experimental techniques, researchers should apply this systematic interpretation framework:

• Technique-specific considerations:

  • mRNA vs. protein discrepancies: Remember that Northern blot or RT-PCR measures transcript levels while Western blot/IHC/IF detect protein. Post-transcriptional regulation of BHMT is significant, particularly through SAM and NF-κB pathways . Calculate correlation coefficients between mRNA and protein data to quantify the relationship.

  • IHC vs. Western blot inconsistencies: IHC detects BHMT in its cellular context while Western blot analyzes denatured protein. Epitope accessibility differences can explain disparities. Validate with multiple antibodies recognizing different epitopes .

  • Cell line vs. tissue differences: BHMT expression in cultured cells may differ from in vivo tissues due to microenvironmental factors. Always confirm cell line findings in tissue samples when possible.

• Resolution strategies:

  • Employ multiple antibodies directed against different BHMT epitopes

  • Utilize orthogonal techniques (mass spectrometry) for validation

  • Quantify results using appropriate software and statistical analyses

  • Consider single-cell approaches to address heterogeneity

  • Verify antibody specificity in the specific experimental context

• Data integration approach:

  Technique	Strengths	Limitations	Complementary Methods
  Western blot	Quantitative, size verification	Loses spatial information	IHC, IF
  IHC	Preserves tissue architecture, spatial context	Semi-quantitative	Western blot, RNA-seq
  RT-PCR	Highly sensitive for transcript detection	No protein information	Western blot, proteomics
  ELISA	Quantitative, high-throughput	Limited spatial information	IHC, Western blot

By systematically analyzing and integrating data from multiple techniques, researchers can develop a more complete and accurate understanding of BHMT expression patterns.

What statistical approaches are most appropriate for analyzing BHMT expression in large-scale tissue studies?

For large-scale tissue studies examining BHMT expression, researchers should implement these statistical approaches:

• Preprocessing and normalization:

  • For immunohistochemistry: Use digital pathology quantification with appropriate intensity thresholds for DAB staining, normalizing BHMT staining to tissue area or cell count

  • For Western blot: Normalize BHMT band intensity to validated housekeeping proteins (β-actin, GAPDH) using densitometry software

  • For qPCR: Apply the 2^(-ΔΔCt) method with stable reference genes like HPRT1 or UBC specifically validated for the tissue type

• Appropriate statistical tests:

  • For comparing two groups (e.g., normal vs. tumor): Use paired t-tests for matched samples or Mann-Whitney for non-parametric data

  • For multiple groups: Apply ANOVA with appropriate post-hoc tests (Tukey's, Bonferroni)

  • For correlation with clinical parameters: Utilize Spearman's rank correlation for non-parametric associations

  • For survival analysis: Implement Kaplan-Meier curves with log-rank tests and Cox proportional hazards models incorporating BHMT expression as a continuous or dichotomized variable

• Advanced analytical methods:

  • Multivariate analysis: Principal Component Analysis (PCA) or clustering to identify patterns in BHMT expression across sample types

  • Machine learning: Random forest or support vector machines to build predictive models incorporating BHMT expression for disease outcomes

  • Receiver Operating Characteristic (ROC) curve analysis: To assess BHMT as a biomarker with optimal sensitivity/specificity cutoffs

• Validation and replication:

  • Cross-validation strategies within the dataset

  • Independent validation in separate cohorts

  • Power analysis to ensure adequate sample sizes for detecting biologically meaningful differences

How might BHMT antibodies contribute to understanding the tumor immune microenvironment in HCC?

BHMT antibodies offer significant potential for understanding the tumor immune microenvironment in HCC through these methodological approaches:

• Multiplex immunofluorescence: Combine BHMT antibodies with immune cell markers (CD68, CD163 for macrophages; CD3, CD4, CD8 for T cells) to spatially map the relationship between BHMT expression and immune infiltrates. Recent research suggests BHMT promotes M1 macrophage infiltration in HCC, which can be directly visualized and quantified using this technique .

• Cell sorting and functional studies: Use BHMT antibodies to separate BHMT-high versus BHMT-low HCC cells, then co-culture with immune cells to assess functional impacts on immune activation, cytokine production, and tumor cell killing capacity.

• Secretome analysis: Compare secreted factors from BHMT-expressing versus BHMT-depleted HCC cells to identify potential immune-modulating molecules, followed by validation with specific antibodies and functional assays.

• In vivo modeling: Develop BHMT-overexpressing or BHMT-knockout HCC models, then use antibody-based techniques to characterize changes in tumor-infiltrating lymphocytes, myeloid cells, and response to immunotherapies.

• Clinical correlation studies: Perform retrospective analyses of HCC patient samples using BHMT antibodies alongside immune checkpoint markers (PD-L1, CTLA-4) to evaluate potential correlations with immunotherapy response and survival outcomes .

These approaches collectively could establish BHMT not only as a prognostic biomarker but potentially as a therapeutic target for modulating the immune microenvironment in HCC.

What methodological approaches can researchers use to study post-translational modifications of BHMT?

To investigate post-translational modifications (PTMs) of BHMT, researchers should implement these methodological approaches:

• PTM-specific antibody detection:

  • Develop or source antibodies specific to known BHMT modifications (phosphorylation, acetylation, methylation, ubiquitination)

  • Validate PTM-specific antibodies using in vitro modified recombinant BHMT as positive controls

  • Implement Western blotting with PTM-specific antibodies alongside total BHMT antibodies to determine modification ratios

• Mass spectrometry-based approaches:

  • Immunoprecipitate BHMT using validated antibodies followed by tryptic digestion and LC-MS/MS analysis

  • Utilize neutral loss scanning to detect phosphorylation events

  • Employ Selected Reaction Monitoring (SRM) for targeted quantification of specific modified peptides

  • Compare modification patterns across different physiological and pathological states

• Functional correlation studies:

  • Generate site-directed mutants of potential modification sites (Ser, Thr, Lys residues)

  • Perform enzymatic activity assays to correlate specific modifications with BHMT function

  • Use phosphatase or deacetylase treatments to remove modifications and assess functional consequences

• Regulatory enzyme identification:

  • Conduct co-immunoprecipitation studies with BHMT antibodies to identify interacting kinases, acetyltransferases, or other modifying enzymes

  • Validate interactions through reverse co-IP and proximity ligation assays

  • Perform enzyme inhibitor studies to determine effects on BHMT modification status and activity

These methodological approaches will provide crucial insights into how post-translational modifications regulate BHMT function in normal physiology and disease states, potentially revealing new therapeutic targets.

How can researchers leverage BHMT antibodies to explore the connection between methionine metabolism and epigenetic regulation?

Researchers can employ BHMT antibodies to investigate the interplay between methionine metabolism and epigenetic regulation through these methodological approaches:

• Chromatin immunoprecipitation (ChIP) studies:

  • Perform ChIP-seq using antibodies against histone modifications (H3K4me3, H3K27me3) in cells with manipulated BHMT expression

  • Compare epigenetic landscapes between BHMT-high and BHMT-low conditions to identify differentially regulated genomic regions

  • Validate findings using BHMT antibodies in co-ChIP experiments to determine if BHMT directly associates with chromatin regions

• Metabolite-epigenetic correlation:

  • Use BHMT antibodies to classify samples based on expression levels, then measure:

    • S-adenosylmethionine (SAM) and S-adenosylhomocysteine (SAH) ratios

    • Global DNA and histone methylation levels

    • Activity of epigenetic writers (DNMTs, HMTs)

  • Establish statistical correlations between BHMT expression, methyl donor availability, and epigenetic modifications

• Integrated multi-omics approaches:

  • Combine BHMT immunodetection with:

    • Metabolomics profiling of methionine cycle intermediates

    • RNA-seq for transcriptome analysis

    • Reduced Representation Bisulfite Sequencing (RRBS) for DNA methylation

  • Perform integrative pathway analysis to map relationships between BHMT expression, methionine metabolism, and epigenetic states

• Functional validation studies:

  • Conduct methionine restriction experiments in cells with different BHMT expression levels (detected via antibodies)

  • Measure changes in histone and DNA methylation patterns

  • Assess transcriptional responses of epigenetically regulated genes

  • Evaluate the impact of methyl donor supplementation on reversing epigenetic alterations

These approaches will illuminate how BHMT's role in methionine metabolism contributes to epigenetic regulation, with potential implications for understanding developmental processes, aging, and disease pathogenesis, particularly in cancer where both metabolic and epigenetic dysregulation are hallmarks.