BHLHE40 Antibody

What is BHLHE40 and what are its primary biological functions?

BHLHE40, also known as BHLHB2, DEC1, SHARP2, or STRA13, is a basic helix-loop-helix transcription factor that regulates multiple biological processes. It functions as a key regulator of:

• Immunity during infection and inflammatory conditions

• T cell cytokine production, particularly restraining IL-10 while promoting GM-CSF expression

• Germinal center reactions in B cells

• T follicular helper (TFH) cell proliferation

• Cancer progression, particularly in pancreatic ductal adenocarcinoma through epithelial-mesenchymal transition (EMT) and stemness-related pathways

The protein has a molecular weight of approximately 46-50 kDa as observed in Western blot analyses .

How does BHLHE40 contribute to immune regulation in different disease models?

BHLHE40 exhibits context-dependent functions across different immune-related conditions:

In autoimmunity:

• BHLHE40-deficient mice (Bhlhe40−/−) are protected from experimental autoimmune encephalomyelitis (EAE), the primary animal model for multiple sclerosis

• This protection occurs because Bhlhe40−/− CD4+ T cells are non-pathogenic and produce increased IL-10, a cytokine that restrains T helper cell effector functions

• IL-10 receptor blockade renders Bhlhe40−/− mice susceptible to EAE, confirming the mechanism

In infection models:

• Cd4-Cre+Bhlhe40fl/fl mice are highly susceptible to Toxoplasma gondii and Mycobacterium tuberculosis infections

• BHLHE40 is required for proper T helper 1 (TH1) responses and balancing IFN-γ and IL-10 production, which is crucial for protective immunity against these pathogens

In germinal center reactions:

• BHLHE40 limits the generation of the earliest germinal center B cells but doesn't affect early memory B cells or plasmablasts

• It restricts T follicular helper cell numbers by restraining their proliferation

• Bhlhe40−/− mice develop B cell lymphoma with age, characterized by accumulation of monoclonal GC B-like cells and polyclonal TFH cells in various tissues

Experimental Applications and Methodologies

For optimal IHC detection of BHLHE40 in tissue sections:

• Antigen retrieval: Use TE buffer pH 9.0 as the preferred method. Alternatively, citrate buffer pH 6.0 may be used but may yield different results

• Antibody dilution: Start with a dilution range of 1:50-1:500, with optimization required for each specific tissue type

• Tissue-specific considerations:

  • Human endometrial cancer tissue: May show nuclear localization pattern

  • Human pancreatic cancer tissue: Shows increased expression correlating with T stage, lymph node metastasis, and AJCC stage

  • Mouse stomach tissue: Validated for detection with standard protocols

• Control validation: Always include:

  • Positive controls (tissues known to express BHLHE40)

  • Negative controls (omission of primary antibody)

  • When possible, validation using BHLHE40 knockout or knockdown tissues/cells

• Signal detection and quantification: Use appropriate image analysis software to quantify nuclear staining intensity, as BHLHE40 is a transcription factor primarily localized to the nucleus.

What are the common issues in Western blot detection of BHLHE40 and how can they be resolved?

Common issues and their solutions for Western blot detection of BHLHE40:

• Multiple bands or unexpected molecular weight:

  • BHLHE40 has an expected molecular weight of 46-50 kDa

  • If observing multiple bands, consider:

    • Post-translational modifications

    • Potential degradation products

    • Non-specific binding

  Solution: Use fresh lysates with protease inhibitors, optimize blocking conditions (try 5% BSA instead of milk), and validate with positive control lysates from cells known to express BHLHE40 (e.g., HeLa, MDA-MB-231)

• Weak or no signal:

  • BHLHE40 expression can be heterogeneous and context-dependent

  Solution: Verify BHLHE40 expression in your system using RT-PCR before Western blot, enrich nuclear fractions (as BHLHE40 is a transcription factor), and optimize primary antibody concentration (try 1:1000 for initial testing)

• High background:

  Solution: Increase washing time/steps, optimize blocking (5% BSA in TBST for 1-2 hours), and try a more dilute primary antibody solution with overnight incubation at 4°C

• Specific cell line considerations:

  • SGC-7901 cells are confirmed to express detectable levels of BHLHE40

  • BXPC3 pancreatic cancer cells have relatively low endogenous BHLHE40 expression (useful for overexpression studies)

How can researchers effectively design knockout/knockdown validation experiments for BHLHE40 antibodies?

A robust validation strategy for BHLHE40 antibodies should include:

• CRISPR/Cas9 knockout:

  • Design guide RNAs targeting early exons of BHLHE40

  • Validate knockout by genomic PCR, mRNA analysis (RT-PCR), and protein analysis

  • Compare Western blot signals between wild-type and knockout cells using the antibody to be validated

• shRNA/siRNA knockdown:

  • For transient validation, use siRNA targeting different regions of BHLHE40 mRNA

  • For stable knockdown, use lentiviral-based shRNA systems

  • Verify knockdown efficiency by RT-PCR (>70% reduction in mRNA is recommended)

  • Compare Western blot signals between control and knockdown samples

• Overexpression validation:

  • Utilize the BXPC3 pancreatic cancer cell line, which has low endogenous BHLHE40 expression

  • Transfect with BHLHE40 expression vectors (e.g., using pCDH plasmid containing the CDS sequence of human BHLHE40)

  • Confirm increased signal in Western blot, which should appear at 46-50 kDa

• Cross-validation with multiple antibodies:

  • Test at least two antibodies targeting different epitopes of BHLHE40

  • Compare staining patterns in the same samples across different applications (WB, IHC, IF)

How can researchers effectively use BHLHE40 antibodies to study the role of this factor in autoimmune disease models?

To investigate BHLHE40 in autoimmune disease models:

• Experimental autoimmune encephalomyelitis (EAE) studies:

  • Track BHLHE40 expression in different immune cell populations during disease progression using flow cytometry

  • Protocol: Isolate cells from lymphoid organs and CNS of EAE mice at different disease stages, perform surface staining for cell markers, followed by intracellular staining for BHLHE40

  • Compare BHLHE40 expression between wild-type and genetically modified mice

  • Correlate BHLHE40 expression with cytokine production, particularly GM-CSF and IL-10

• T cell transfer studies:

  • Purify CD4+ T cells from wild-type and Bhlhe40−/− mice

  • Label cells with tracking dyes (e.g., CFSE)

  • Transfer into recipient mice followed by immunization

  • Analyze proliferation, cytokine production, and pathogenicity

• ChIP-seq analysis:

  • Use validated BHLHE40 antibodies for chromatin immunoprecipitation followed by sequencing

  • Identify direct target genes regulated by BHLHE40 in different immune cell populations

  • Correlate binding sites with genes involved in autoimmune pathology

  • Compare binding profiles between resting and activated cells

• Co-immunoprecipitation studies:

  • Identify BHLHE40 protein interaction partners in different immune cell types

  • Analyze how these interactions change during autoimmune disease progression

  • Link interaction changes to functional outcomes in disease models

What approaches should researchers use to investigate BHLHE40's role in cancer progression, particularly in pancreatic ductal adenocarcinoma?

Based on recent findings on BHLHE40 in pancreatic cancer , researchers should:

• Expression analysis in patient samples:

  • Perform IHC staining of BHLHE40 in PDAC patient tissues

  • Correlate expression with clinicopathological features including T stage, lymph node metastasis, and AJCC stage

  • Develop a scoring system based on staining intensity and percentage of positive cells

  • Analyze association with patient survival and treatment response

• Functional studies in cancer cell lines:

  • Compare BHLHE40 expression across multiple pancreatic cancer cell lines

  • Use BXPC3 cells for overexpression studies as they have low endogenous BHLHE40 expression

  • Assess effects on:

    • EMT-related markers (Snail, Slug, Vimentin, ZEB1)

    • Stemness markers (SOX9, Oct4, CD133)

    • Migration and invasion assays

    • Sphere formation capacity

• Tumor-immune interaction studies:

  • Co-culture BHLHE40-overexpressing cancer cells with CD8+ T cells

  • Measure T cell apoptosis, IFNγ production, and PD-1 expression

  • Analyze changes in T cell receptor signaling and effector functions

  • Assess cancer cell resistance to T cell-mediated killing

• In vivo tumor models:

  • Establish orthotopic pancreatic tumors using control and BHLHE40-manipulated cancer cells

  • Monitor tumor growth, metastasis, and immune infiltration

  • Analyze changes in the tumor microenvironment, focusing on:

    • Cancer-associated fibroblasts (CAFs)

    • T cell infiltration and function

    • Tumor cell stemness

How should researchers interpret conflicting BHLHE40 expression data across different experimental systems?

When faced with conflicting BHLHE40 expression data:

• Consider contextual expression patterns:

  • BHLHE40 expression is highly context-dependent and can vary between:

    • Cell types (heterogeneous expression in CD4+ T cells )

    • Activation states (transient induction in light zone B cells )

    • Disease models (differential expression between autoimmunity and infection )

    • Cancer vs. normal tissues (elevated in PDAC with correlation to advanced stage )

• Analyze subcellular localization:

  • BHLHE40 is primarily nuclear as a transcription factor

  • Confirm proper nuclear extraction protocols were used for Western blot

  • In IHC/IF, evaluate nuclear vs. cytoplasmic staining patterns

  • Consider post-translational modifications that might affect localization or antibody recognition

• Reconcile data through comprehensive analysis:

  • Integrate data from multiple techniques (WB, IHC, RT-PCR, RNA-seq)

  • When possible, perform single-cell analysis to account for cellular heterogeneity

  • Consider temporal dynamics by analyzing multiple time points

  • Control for experimental variables (antibody lot, protocol differences, sample preparation)

• Validate with genetic approaches:

  • Use reporter systems (e.g., Bhlhe40-GFP bacterial artificial chromosome reporter mice )

  • Complement antibody detection with mRNA analysis

  • Perform rescue experiments in knockout/knockdown systems

What statistical approaches are most appropriate for analyzing BHLHE40 expression in correlation with clinical outcomes in cancer studies?

For robust statistical analysis of BHLHE40 in cancer studies:

• Expression quantification methods:

  • For IHC: Use H-score (combining intensity and percentage of positive cells)

  • For gene expression: Use normalized expression values (FPKM, TPM, or similar)

  • Establish clear thresholds for "high" vs. "low" expression based on:

    • Median split

    • Optimal cutoff determined by ROC curve analysis

    • Expression quartiles

• Survival analysis approaches:

  • Kaplan-Meier curves with log-rank test for comparing high vs. low BHLHE40 expression groups

  • Cox proportional hazards models to calculate hazard ratios (HR)

  • Include relevant clinical covariates (stage, grade, age, treatment)

  • Report with appropriate statistics (HR 1.83, p = 0.005 was observed in PDAC patients )

• Correlation with clinicopathological features:

  • Chi-square or Fisher's exact test for categorical variables

  • t-test or Mann-Whitney for continuous variables

  • Adjust for multiple testing using Bonferroni or FDR correction

  • Present data in clear tables with proper statistical annotation

• Advanced multivariate models:

  • Develop prognostic risk models combining BHLHE40 with other markers (e.g., ITGA2, ITGA3, and ADAM9 as reported in PDAC )

  • Validate models in independent cohorts

  • Assess model performance through ROC curve analysis (AUC values: 1-year AUC 0.626, 3-year AUC 0.647, and 5-year AUC 0.766 were reported in PDAC )

  • Consider machine learning approaches for complex integration with other molecular markers

How can researchers utilize BHLHE40 antibodies to investigate the role of this transcription factor in tumor immunology?

Given BHLHE40's dual roles in tumor cells and immune cells, researchers should:

• Single-cell analysis of tumor microenvironment:

  • Perform single-cell RNA-seq of tumor tissues

  • Map BHLHE40 expression across all cell populations

  • Validate expression patterns using multicolor flow cytometry with BHLHE40 antibodies

  • Focus on T cell subsets, particularly TH1-like tumor-infiltrating CD4+ T cells which show high BHLHE40 expression

• Checkpoint blockade response studies:

  • Analyze BHLHE40 expression in responders vs. non-responders to immune checkpoint inhibitors

  • BHLHE40 is highly expressed by TH1-like tumor-infiltrating CD4+ T cells in microsatellite-unstable, checkpoint blockade-sensitive tumors

  • Design combination therapies targeting BHLHE40-regulated pathways alongside checkpoint inhibitors

• Co-culture systems:

  • Establish co-cultures of tumor cells with different immune cell populations

  • Manipulate BHLHE40 expression in either compartment

  • Analyze bidirectional interactions and signaling

  • Assess changes in:

    • T cell activation and effector functions

    • Cancer cell resistance mechanisms

    • Cytokine production and responsiveness

• Spatial transcriptomics and multiplex imaging:

  • Map BHLHE40 expression spatially within tumors

  • Correlate with markers of immune activation/suppression

  • Analyze proximity relationships between BHLHE40+ tumor cells and specific immune populations

  • Develop multiplexed antibody panels including BHLHE40 alongside immune markers

What are the methodological considerations for investigating BHLHE40 in the germinal center reaction and B cell lymphoma development?

Based on findings that Bhlhe40-deficient mice develop B cell lymphoma with age :

• Temporal analysis of germinal center development:

  • Track BHLHE40 expression during different stages of the germinal center reaction

  • Use flow cytometry with BHLHE40 antibodies to analyze expression in:

    • CCR6+ activated B cells (show high BHLHE40 expression on day 4 post-immunization)

    • Early GC B cells (show BHLHE40 downregulation)

    • Dark zone vs. light zone GC B cells

    • Memory B cells and plasmablasts

• Lineage tracing experiments:

  • Utilize Bhlhe40-reporter mice to track cell fate decisions

  • Sort BHLHE40+ and BHLHE40- B cell populations at early timepoints post-immunization

  • Perform adoptive transfer to track differentiation trajectories

  • Compare T-dependent vs. T-independent immune responses (BHLHE40 specifically regulates T-dependent responses)

• B cell lymphoma model characterization:

  • Monitor aging Bhlhe40−/− mice for lymphoma development

  • Characterize lymphoma cells via immunophenotyping, including BHLHE40 expression

  • Perform clonality analysis (monoclonal GC B-like cells were observed)

  • Analyze genetic alterations and gene expression profiles of lymphoma cells

• Mechanistic studies of lymphomagenesis:

  • Investigate BHLHE40's role in regulating:

    • DNA damage responses in GC B cells

    • Apoptosis regulation during negative selection

    • Interaction with known lymphoma oncogenes/tumor suppressors

    • Cell cycle control mechanisms