batf Antibody

What is BATF and why is it significant in immunological research?

BATF (basic leucine zipper transcription factor, ATF-like) is a critical AP-1 family transcription factor that controls the differentiation of lineage-specific cells in the immune system. It mediates the differentiation of T-helper 17 cells (Th17), follicular T-helper cells (TfH), CD8(+) dendritic cells, and plays a crucial role in class-switch recombination (CSR) in B-cells . BATF functions through heterodimer formation with JUNB, recognizing and binding the DNA sequence 5'-TGA[CG]TCA-3' . This heterodimer also complexes with IRF4 or IRF8 in immune cells to recognize immune-specific regulatory elements (AICE sequences) .

BATF's significance stems from its central role in coordinating multiple aspects of adaptive immunity. Studies with BATF-deficient mice (BatfΔZ/ΔZ) have demonstrated impaired Th17 development, decreased CD4+ T cell numbers, defective T-dependent humoral responses, and resistance to experimental autoimmune encephalomyelitis (EAE) . These characteristics make BATF a crucial target for studying autoimmunity, inflammation, and the molecular basis of adaptive immune responses.

What types of BATF antibodies are available for research applications?

Researchers have several options for BATF antibodies, varying in clonality, host species, and applications:

The polyclonal antibody (13507-1-AP) is purified using antigen affinity methods and recognizes the full BATF protein . The monoclonal antibody (D7C5) offers high specificity and is suitable for detecting endogenous BATF levels in various applications . Selection between these antibodies should be based on the specific experimental requirements, target species, and application techniques.

What are the recommended dilutions and protocols for different applications?

Optimal dilutions and protocols vary by application. Based on validated research protocols:

It is recommended to titrate these antibodies in each specific experimental system to obtain optimal results, as performance can be sample-dependent .

How should I design experiments to study BATF's role in Th17 cell differentiation?

When investigating BATF's role in Th17 differentiation, implement the following methodological approach:

• Isolation and culture: Isolate naive CD4+ T cells (CD4+CD62L+CD44low) from spleen and lymph nodes using magnetic separation or FACS.

• Th17 polarization: Culture cells with plate-bound anti-CD3ε (2-5 μg/ml) and soluble anti-CD28 under Th17-polarizing conditions (TGF-β, IL-6, anti-IFN-γ, anti-IL-4).

• BATF detection timeline: Analyze BATF expression at multiple timepoints (6, 12, 24, 48, 72 hours) to capture dynamic regulation during differentiation.

• Functional validation: Quantify Th17-associated genes by qPCR (IL-17, IL-21, IL-23R) to correlate with BATF expression levels .

• Experimental controls: Include parallel cultures of Th1 and Th2 cells as comparative controls, and if available, cells from BATF-deficient mice (BatfΔZ/ΔZ) as negative controls .

For RNA-level analysis, qPCR assessing IL-17, IL-21, and IL-23R expression serves as functional validation of Th17 differentiation and correlates with BATF activity . Flow cytometry with intracellular staining for IL-17 and BATF can establish a direct relationship between BATF expression and the Th17 phenotype at the single-cell level.

What approaches should I use to investigate BATF in B cell class-switch recombination?

To study BATF's role in B cell class-switch recombination (CSR), implement this research strategy:

• B cell isolation: Purify naive B cells from spleen using CD43-negative selection (for untouched B cells) or CD19-positive selection.

• In vitro stimulation: Culture B cells with appropriate stimuli:

  • T-dependent stimulation: Anti-CD40 + IL-4 (for IgG1/IgE)

  • T-independent stimulation: LPS or TNP-LPS (validated in BATF studies)

• Time course analysis: Monitor BATF expression over 24-96 hours during CSR progression.

• CSR assessment:

  • Surface marker analysis: Flow cytometry for IgG1, IgG2c expression

  • Molecular analysis: RT-PCR for activation-induced cytidine deaminase (AID), germline transcripts, and circular DNA

  • Functional analysis: ELISA for secreted immunoglobulins

• Comparative controls: Include parallel cultures from wild-type and, if available, BatfΔZ/ΔZ mice. Research has shown BatfΔZ/ΔZ B cells proliferate in response to LPS but fail to undergo productive CSR, providing critical control data .

Notably, in vivo validation using the TNP-LPS T-independent antigen system demonstrated that while wild-type mice mount IgG1 responses, BatfΔZ/ΔZ mice show impaired responses despite some evidenced B cell activation . This approach distinguishes between BATF's effects on B cell activation versus productive class switching.

How can I validate BATF antibody specificity for my experiments?

Validating BATF antibody specificity is critical for experimental rigor. Implement the following comprehensive validation strategy:

• Genetic validation:

  • Use tissues/cells from BATF knockout models (BatfΔZ/ΔZ) as negative controls

  • Compare with heterozygous (Batf+/ΔZ) and wild-type (Batf+/+) samples to assess dose-dependence

• Expression system validation:

  • Test antibody against recombinant BATF protein

  • Use cells transfected with tagged BATF constructs as positive controls

• Molecular weight verification:

  • Confirm detection at the expected molecular weight (14-15 kDa)

  • Be aware that post-translational modifications may cause slight shifts

• Cross-reactivity assessment:

  • Test against other BATF family members (BATF2, BATF3) to ensure specificity

  • Evaluate performance across different species if cross-species work is planned

• Application-specific validation:

  • For immunofluorescence: Include peptide competition assays

  • For flow cytometry: Compare with isotype controls and FMO (fluorescence minus one)

  • For Western blotting: Include recombinant protein ladders and size controls

Immunoblotting experiments with splenocyte extracts from BatfΔZ/ΔZ mice have confirmed absence of BATF protein, validating both the knockout model and antibody specificity . This genetic validation approach represents the gold standard for antibody specificity determination.

Why might I observe different BATF expression patterns between T cell subsets, and how should I interpret these differences?

Differential BATF expression across T cell subsets reflects its subset-specific regulatory roles. When analyzing such differences, consider:

• Subset-specific functions: BATF has demonstrated distinct roles in Th17, Th2, and Tfh cells, with minimal impact on Th1 cells . These functional differences are reflected in expression patterns.

• Quantitative assessment: When comparing subsets, implement qPCR analysis for BATF alongside subset-defining transcription factors:

  • Th17: RORγt, IL-17, IL-21, IL-23R

  • Th1: T-bet

  • Th2: GATA3, IL-4

  • Treg: Foxp3

• Dynamic regulation: BATF expression changes during differentiation and activation. Studies have shown significant upregulation during Th17 polarization, while expression remains lower in fully differentiated Th1 cells .

• Interpreting apparent discrepancies: When observing differences between protein and mRNA levels, consider:

  • Post-transcriptional regulation

  • Protein stability differences

  • Technical variations in detection sensitivity

Published research has demonstrated that BatfΔZ/ΔZ splenocytes show normal levels of IFN-γ (Th1 cytokine), reduced levels of IL-4 (Th2 cytokine), and severely diminished IL-17 (Th17 cytokine), confirming subset-specific dependencies on BATF . Flow cytometry analysis further validated these patterns, showing dramatic reduction in IL-17+ cells in BatfΔZ/ΔZ mice without significant changes in Th1 cells .

What methodological approaches can be used to study BATF-JUNB-IRF4 complex formation?

The BATF-JUNB-IRF4/IRF8 complex is crucial for recognizing immune-specific regulatory elements. To study this complex, implement these methodological approaches:

• Co-immunoprecipitation (Co-IP):

  • Immunoprecipitate with anti-BATF antibody (D7C5 recommended at 1:100 dilution)

  • Immunoblot for JUNB, IRF4, or IRF8

  • Reverse IP with anti-JUNB or anti-IRF4 antibodies to confirm interaction

• Proximity ligation assay (PLA):

  • Visualize protein-protein interactions in situ

  • Use antibodies against BATF and JUNB/IRF4 from different host species

  • Detect fluorescent signals only when proteins are in close proximity

• DNA-binding assays:

  • Electrophoretic mobility shift assay (EMSA) with labeled AICE sequence (5'-TGAnTCA/GAAA-3')

  • Perform supershift using anti-BATF, anti-JUNB, and anti-IRF4 antibodies

  • Include competition with unlabeled consensus and mutant probes

• Chromatin immunoprecipitation (ChIP):

  • Perform sequential ChIP (ChIP-reChIP) to identify genomic regions bound by both BATF and JUNB/IRF4

  • Analyze with qPCR for known target genes or ChIP-seq for genome-wide binding patterns

Research has established that BATF functions through heterodimer formation with JUNB, recognizing the DNA sequence 5'-TGA[CG]TCA-3', and this heterodimer complexes with IRF4/IRF8 to recognize the AICE sequence (5'-TGAnTCA/GAAA-3') . These assays will help elucidate the molecular mechanisms underlying this complex formation and its target gene regulation.

How can I investigate the role of BATF in autoimmune disease models?

To investigate BATF's role in autoimmune pathology, implement the following experimental approaches:

• Experimental autoimmune encephalomyelitis (EAE) model:

  • BATF knockout mice (BatfΔZ/ΔZ) show resistance to EAE, consistent with Th17 cells' role in this model

  • Compare disease progression between wild-type and BATF-deficient mice

  • Analyze CNS-infiltrating T cells for IL-17 and other inflammatory markers

• Cellular analysis in autoimmune contexts:

  • Isolate cells from peripheral lymphoid tissues and inflammatory sites

  • Perform flow cytometry analysis of Th17 cells (CD4+IL-17+) and Tfh cells (CD4+CXCR5+PD-1+)

  • Quantify BATF expression in disease-relevant cell populations

• Therapeutic targeting approach:

  • Design experiments using BATF inhibition strategies (e.g., small molecules, blocking peptides)

  • Assess impact on disease progression in established autoimmune models

  • Compare with standard of care treatments

• Translational correlation studies:

  • Analyze BATF expression in samples from human autoimmune disease patients

  • Correlate expression with disease severity and activity markers

  • Establish relevance of mouse model findings to human disease

The resistance of BATF knockout mice to EAE provides strong evidence for BATF's role in autoimmune inflammation . This model serves as an excellent system to dissect the molecular mechanisms by which BATF contributes to autoimmunity, potentially identifying new therapeutic targets.

Why might I observe discrepancies in BATF antibody performance between applications, and how should I troubleshoot these issues?

When encountering discrepancies in BATF antibody performance across applications, consider these methodological troubleshooting strategies:

• Application-specific epitope accessibility:

  • Western blotting: Denatured proteins expose all epitopes

  • Flow cytometry/IF: Conformation-dependent epitopes may be variably accessible

  • IP: Native protein folding may mask certain epitopes

  Solution: Try multiple antibodies recognizing different epitopes. The polyclonal 13507-1-AP recognizes multiple epitopes while the monoclonal D7C5 targets a specific epitope .

• Fixation and preparation effects:

  • Cross-linking fixatives (paraformaldehyde) can mask epitopes

  • Methanol fixation denatures proteins, potentially destroying conformational epitopes

  • Permeabilization methods affect antibody accessibility

  Solution: Optimize fixation/permeabilization protocols for each application. For flow cytometry with D7C5, specific permeabilization protocols are recommended (1:400-1:1600 dilution) .

• Expression level variations:

  • Low endogenous expression may require signal amplification

  • Cell type-specific expression patterns affect detection sensitivity

  • Activation status dramatically affects BATF expression levels

  Solution: Implement positive controls with known BATF expression (e.g., activated T cells). The D7C5 antibody has been validated for detecting endogenous levels of BATF .

• Species-specific performance differences:

  • Antibody reactivity may vary between human, mouse, and rat samples

  • Amino acid sequence variations affect epitope recognition

  Solution: Confirm species reactivity for your specific application. The 13507-1-AP antibody has validated reactivity with human, mouse, and rat samples .

Methodical optimization and validation across multiple experimental conditions will help resolve discrepancies and ensure reliable results across different applications.

How can BATF expression analysis be incorporated into studies of human immune disorders?

BATF expression analysis can provide valuable insights into human immune disorders through these methodological approaches:

• Clinical sample analysis:

  • Isolate PBMCs from patients with autoimmune diseases or immunodeficiencies

  • Perform flow cytometry to measure BATF in specific lymphocyte subsets

  • Compare expression between patients and healthy controls, correlating with disease activity

• Functional ex vivo studies:

  • Stimulate patient-derived T cells under Th17-polarizing conditions

  • Measure BATF induction and correlation with IL-17 production

  • Compare polarization efficiency between patient and control samples

• Single-cell analysis approach:

  • Implement single-cell RNA-seq to correlate BATF with disease-associated gene modules

  • Use mass cytometry (CyTOF) with BATF antibody to identify patient-specific immune cell phenotypes

  • Correlate BATF expression patterns with clinical parameters

• Genetic association studies:

  • Analyze BATF polymorphisms in patient cohorts

  • Correlate genetic variants with expression levels and disease outcomes

  • Implement functional studies of disease-associated variants

Given BATF's critical role in multiple immune cell lineages, including Th17, Th2, and B cells, analyzing its expression and function in human samples may reveal dysregulated pathways contributing to autoimmunity, immunodeficiency, or aberrant immune responses . The resistance of BATF-deficient mice to experimental autoimmune encephalomyelitis suggests potential relevance to multiple sclerosis and other T cell-mediated autoimmune conditions .

What new research directions are emerging for BATF in cancer immunology?

Emerging research directions exploring BATF in cancer immunology include:

• Tumor-infiltrating lymphocyte (TIL) analysis:

  • Characterize BATF expression in TILs versus peripheral blood lymphocytes

  • Correlate BATF levels with T cell exhaustion markers (PD-1, CTLA-4, LAG-3)

  • Evaluate whether BATF expression predicts immunotherapy response

• Therapeutic manipulation approaches:

  • Develop strategies to modulate BATF for enhancing anti-tumor immunity

  • Investigate effects of BATF modulation on CAR-T cell functionality

  • Explore combination approaches targeting BATF pathways with checkpoint inhibitors

• Tumor microenvironment interactions:

  • Study how tumor-derived factors affect BATF expression in immune cells

  • Analyze BATF's role in tumor-associated B cell responses and tertiary lymphoid structures

  • Investigate BATF-dependent cytokine networks within the tumor microenvironment

• Predictive biomarker development:

  • Evaluate BATF as a potential biomarker for immunotherapy response

  • Develop immunohistochemical protocols for BATF detection in clinical samples

  • Correlate BATF expression patterns with patient outcomes

While direct evidence linking BATF to cancer immunology is still emerging, its fundamental roles in coordinating multiple aspects of the lymphocyte communication network required for robust immune responses suggest it may significantly impact anti-tumor immunity. The methodological approaches outlined provide a framework for investigating these potential connections.

What are the optimal storage conditions for BATF antibodies, and how can I maximize their shelf life?

For optimal storage and maximum shelf life of BATF antibodies, follow these evidence-based recommendations:

• Temperature conditions:

  • Store BATF antibodies at -20°C according to manufacturer specifications

  • 13507-1-AP and D7C5 antibodies are stable for one year after shipment when stored at -20°C

  • Avoid repeated freeze-thaw cycles which can degrade antibody quality

• Buffer composition:

  • BATF antibodies are typically supplied in PBS with 0.02% sodium azide and 50% glycerol at pH 7.3

  • This formulation enhances stability during storage

  • For the 13507-1-AP antibody, 20µl sizes contain 0.1% BSA as an additional stabilizer

• Aliquoting recommendations:

  • For 13507-1-AP, aliquoting is unnecessary for -20°C storage

  • For other antibody formulations, consider creating single-use aliquots to prevent contamination and repetitive freeze-thaw cycles

• Working solution handling:

  • For diluted working solutions, prepare fresh and use within 24 hours

  • Store working dilutions at 4°C during experimental procedures

  • Return stock solutions to -20°C promptly after use

• Stability testing:

  • Periodically validate antibody performance with positive controls

  • Consider including a standardized positive sample with each experiment to monitor antibody performance over time

Following these storage recommendations will help maintain antibody specificity and sensitivity for consistent experimental results over the product's lifespan.

What controls should I include when analyzing BATF expression by flow cytometry?

When analyzing BATF expression by flow cytometry, implement these essential controls:

• Antibody specificity controls:

  • Isotype control: Include matched isotype (Rabbit IgG for D7C5) at the same concentration to assess non-specific binding

  • Blocking peptide competition: Pre-incubate antibody with immunizing peptide to verify specificity

  • Genetic control: If available, include BATF-deficient cells (e.g., from BatfΔZ/ΔZ mice)

• Staining controls:

  • Fluorescence Minus One (FMO): Include all antibodies except anti-BATF to set negative gating boundaries

  • Single-color controls: For compensation when using multiple fluorochromes

  • Unstained cells: To determine autofluorescence levels

• Biological controls:

  • Positive expression control: Include cell types known to express BATF (activated T cells)

  • Negative expression control: Include cell types with minimal BATF expression (naive/resting cells)

  • Activation gradient: Compare cells at different activation states to confirm expected expression patterns

• Technical validation controls:

  • Titration control: Determine optimal antibody concentration (recommended 1:400-1:1600 for D7C5)

  • Fixation/permeabilization control: Optimize protocol, as BATF requires effective nuclear access

  • Instrument settings control: Include standardized beads to ensure consistent instrument performance

For flow cytometry with BATF antibody D7C5, use fixed and permeabilized cells following validated protocols, as this antibody is specifically validated for detecting endogenous levels of BATF protein . Appropriate controls ensure reliable interpretation of BATF expression patterns across different cell populations and experimental conditions.