BHLH104 Antibody

What is BHLH104 and why is it important to develop antibodies against it?

BHLH104 is a basic helix-loop-helix (bHLH) transcription factor belonging to the IVc subgroup of the bHLH family in Arabidopsis thaliana. It functions as a key regulatory component in iron (Fe) homeostasis, positively regulating Fe deficiency responses in plants. Knockout of BHLH104 in Arabidopsis substantially reduces tolerance to Fe deficiency, while overexpression enhances Fe accumulation in soil-grown conditions .

Developing antibodies against BHLH104 is crucial for multiple research applications, including protein localization studies, chromatin immunoprecipitation (ChIP) experiments to identify DNA binding sites, co-immunoprecipitation to study protein-protein interactions, and western blot analysis to quantify protein expression levels. These antibodies enable researchers to track BHLH104's activity and interactions in different experimental conditions, particularly during Fe deficiency responses.

How does BHLH104 function in the iron deficiency response pathway?

BHLH104 plays a pivotal role in the iron deficiency response pathway by directly activating the transcription of Ib subgroup bHLH genes (bHLH38, bHLH39, bHLH100, and bHLH101) . Unlike its downstream targets, BHLH104 expression is not responsive to Fe deficiency, suggesting it functions as a constitutive regulator rather than an inducible factor .

BHLH104 interacts with another IVc subgroup bHLH protein, ILR3 (IAA-LEUCINE RESISTANT3), which also plays an important role in Fe homeostasis. Together, these transcription factors bind directly to the promoters of Ib subgroup bHLH genes and other regulatory genes like PYE . This molecular mechanism forms a regulatory network that coordinates the plant's response to iron availability in the environment.

What are the key experimental techniques that utilize BHLH104 antibodies?

BHLH104 antibodies are essential tools in several experimental techniques used to study this transcription factor:

• Chromatin Immunoprecipitation (ChIP): Used to identify direct DNA binding sites of BHLH104, particularly on promoters of target genes such as bHLH38/39/100/101 .

• Co-Immunoprecipitation (Co-IP): Applied to confirm protein-protein interactions, such as those between BHLH104 and ILR3 or other regulatory proteins .

• Western Blotting: Employed to detect and quantify BHLH104 protein levels under different experimental conditions.

• Immunolocalization: Used to determine the subcellular localization of BHLH104 protein and potential changes in localization during stress responses.

• Protein-DNA Binding Assays: Applied in combination with other techniques like yeast one-hybrid assays to validate direct binding to specific promoter elements.

How can I validate the specificity of a BHLH104 antibody for chromatin immunoprecipitation experiments?

Validating the specificity of BHLH104 antibodies for ChIP experiments requires multiple control measures:

• Use of Genetic Controls: ChIP experiments should include samples from bhlh104 knockout mutants as negative controls. The antibody should show significantly reduced or absent signals in these samples compared to wild-type plants .

• Pre-immune Serum Control: Compare ChIP results using pre-immune serum versus the BHLH104 antibody to ensure that the observed enrichment is antibody-specific.

• Peptide Competition Assay: Pre-incubate the BHLH104 antibody with excess purified peptide used for immunization, which should abolish specific signals if the antibody is genuinely specific.

• Validation of Known Targets: Confirm enrichment of previously identified BHLH104 binding sites, such as promoters of bHLH38/39/100/101 genes, using qPCR after ChIP .

• Western Blot Validation: Perform western blot analysis with the same antibody to confirm it detects a protein of the expected molecular weight that is absent in knockout mutants.

A robust ChIP protocol involving histone modifications in Arabidopsis plants, which can be adapted for BHLH104 ChIP experiments, has been reported .

What are the optimal conditions for using BHLH104 antibodies in protein interaction studies?

For optimal results in protein interaction studies using BHLH104 antibodies:

• Buffer Composition: Use buffers containing 20-50 mM Tris-HCl (pH 7.5), 150 mM NaCl, 0.1-0.5% NP-40 or Triton X-100, 1 mM EDTA, with protease inhibitor cocktail. The specific composition may need optimization based on the interaction partners being studied.

• Cross-linking Considerations: For transient or weak interactions, consider using mild cross-linking agents like formaldehyde (0.1-1%) or DSP (dithiobis(succinimidyl propionate)).

• Antibody Concentration: Titrate the antibody to determine the optimal concentration, typically in the range of 1-5 μg of antibody per mg of total protein.

• Incubation Conditions: For Co-IP, incubate the antibody with protein extract at 4°C for 2-16 hours with gentle rotation.

• Washing Stringency: Optimize washing conditions to remove non-specific interactions while preserving specific ones. This may involve varying salt concentrations and detergent levels.

• Protein Interaction Controls: Include controls for known interaction partners (positive controls) such as ILR3 and non-interacting proteins (negative controls).

The specific protein domains involved in interactions should be considered when designing experiments. For example, the C-terminal regions of BHLH104 (BHLH104-C) are often sufficient for protein interactions, not requiring the canonical bHLH domain .

How can BHLH104 antibodies be used to investigate iron deficiency responses in different plant tissues?

BHLH104 antibodies can be strategically employed to investigate tissue-specific responses to iron deficiency:

• Tissue-Specific Protein Expression Analysis:

  • Extract proteins from different tissues (roots, shoots, leaves, reproductive organs)

  • Perform western blot analysis using BHLH104 antibodies

  • Quantify and compare protein levels across tissues and under different Fe availability conditions

• Chromatin Immunoprecipitation Followed by Sequencing (ChIP-seq):

  • Conduct tissue-specific ChIP-seq to identify genome-wide binding sites of BHLH104

  • Compare binding profiles between different tissues and under varying Fe conditions

  • Identify tissue-specific target genes that may explain differential responses to Fe deficiency

• Immunohistochemistry:

  • Prepare tissue sections from different plant organs

  • Use BHLH104 antibodies for immunolocalization

  • Analyze subcellular localization patterns in different cell types and tissues

• Tissue-Specific Co-Immunoprecipitation:

  • Perform Co-IP using BHLH104 antibodies on protein extracts from different tissues

  • Identify tissue-specific interaction partners through mass spectrometry

  • Compare interaction networks between tissues and under varying Fe conditions

This approach can reveal how BHLH104 functions differently across plant tissues, potentially explaining tissue-specific responses to iron deficiency. Since BHLH104 transcript levels are not affected by Fe deficiency , post-translational modifications or protein-protein interactions likely play key roles in modulating its activity in a tissue-specific manner.

What controls should be included when using BHLH104 antibodies in immunoblotting experiments?

A comprehensive set of controls is essential for reliable immunoblotting with BHLH104 antibodies:

Including these controls helps ensure that observed signals are specific to BHLH104 and facilitates accurate interpretation of experimental results.

How can I optimize ChIP protocols specifically for BHLH104 binding site identification?

Optimizing ChIP protocols for BHLH104 requires careful consideration of several parameters:

• Crosslinking Optimization:

  • Test different formaldehyde concentrations (0.5-3%) and incubation times (5-20 minutes)

  • For plant tissues, vacuum infiltration may improve crosslinking efficiency

  • Consider dual crosslinking with both formaldehyde and protein-specific crosslinkers for enhanced capture of protein-DNA interactions

• Chromatin Fragmentation:

  • Optimize sonication conditions to achieve fragments of 200-500 bp

  • Verify fragmentation efficiency by running samples on agarose gels

  • Consider enzymatic fragmentation alternatives for consistent results

• Antibody Specificity and Quantity:

  • Validate antibody specificity using western blots on wild-type and bhlh104 mutant samples

  • Titrate antibody amounts (2-10 μg per reaction) to determine optimal concentration

  • Consider using epitope-tagged BHLH104 lines and corresponding tag antibodies as alternatives

• Washing Stringency:

  • Modify salt concentrations in wash buffers to balance between reducing background and maintaining specific interactions

  • Test different detergent concentrations to optimize signal-to-noise ratio

• Positive Control Regions:

  • Include primers for known BHLH104 binding sites, such as promoters of bHLH38/39/100/101 genes

  • Design primers for regions not expected to be bound by BHLH104 as negative controls

• Sequential ChIP (Re-ChIP):

  • Consider sequential ChIP to investigate co-occupancy of BHLH104 with interaction partners like ILR3

An efficient ChIP protocol for studying histone modifications in Arabidopsis has been reported and can be adapted for BHLH104 ChIP experiments with appropriate modifications.

What are common pitfalls when using BHLH104 antibodies and how can they be addressed?

Several common challenges arise when working with BHLH104 antibodies:

• Cross-reactivity with Related Proteins:

  • BHLH104 shares sequence similarity with other subgroup IVc bHLH proteins, particularly with bHLH34

  • Solution: Validate antibody specificity using recombinant proteins of related bHLH family members and test on extracts from corresponding knockout mutants

• Low Endogenous Expression Levels:

  • BHLH104 may have relatively low expression levels in some tissues or conditions

  • Solution: Use sensitive detection methods like enhanced chemiluminescence (ECL), increase protein loading, or consider immunoprecipitation prior to immunoblotting

• Post-translational Modifications:

  • Modifications may affect antibody recognition or create multiple band patterns

  • Solution: Use antibodies raised against different epitopes and consider phosphatase treatments to identify modification-dependent signals

• Protein-Protein Interactions Masking Epitopes:

  • BHLH104 forms protein complexes with ILR3 and potentially other proteins , which may mask antibody epitopes

  • Solution: Include protein extraction buffers with ionic detergents or sonication steps to disrupt protein complexes

• Fixation-Induced Epitope Masking in Immunohistochemistry:

  • Excessive fixation may reduce antibody accessibility to epitopes

  • Solution: Optimize fixation conditions and consider antigen retrieval methods

• Inconsistent ChIP Results:

  • Variability in crosslinking efficiency or chromatin accessibility

  • Solution: Standardize plant growth conditions, tissue harvesting, and crosslinking protocols; consider using epitope-tagged BHLH104 lines for more consistent results

• Antibody Batch Variation:

  • Different antibody batches may show varying specificities and sensitivities

  • Solution: Characterize each new batch against previous batches using standard samples

Addressing these challenges requires thorough validation and optimization of protocols for each specific application of BHLH104 antibodies.

How should I analyze ChIP-seq data generated using BHLH104 antibodies?

Analyzing ChIP-seq data for BHLH104 requires a comprehensive bioinformatics approach:

• Quality Control and Preprocessing:

  • Assess sequence quality metrics (base quality scores, GC content)

  • Remove adapter sequences and low-quality reads

  • Align reads to the reference genome using appropriate algorithms (e.g., Bowtie2, BWA)

• Peak Calling:

  • Use peak-calling algorithms appropriate for transcription factors (e.g., MACS2, GEM)

  • Include input DNA control samples to account for background enrichment

  • Consider biological replicates and perform irreproducible discovery rate (IDR) analysis

• Motif Analysis:

  • Perform de novo motif discovery on BHLH104 binding regions (using tools like MEME, HOMER)

  • Compare identified motifs with known E-box elements typically bound by bHLH transcription factors

  • Search for co-occurring motifs that might indicate cooperative binding with other factors

• Genomic Feature Association:

  • Analyze the distribution of binding sites relative to genomic features (promoters, enhancers, gene bodies)

  • Perform gene ontology (GO) enrichment analysis for genes associated with binding sites

  • Focus on iron homeostasis-related genes, particularly the Ib subgroup bHLH genes (bHLH38/39/100/101)

• Comparative Analysis:

  • Compare BHLH104 binding profiles under different conditions (e.g., iron-sufficient vs. iron-deficient)

  • Integrate with ChIP-seq data for interacting partners like ILR3

  • Correlate binding with gene expression data to identify functional binding events

• Visualization and Validation:

  • Create genome browser tracks to visualize binding patterns

  • Validate selected binding sites using ChIP-qPCR

  • Consider the transcriptional outcomes of binding events

For BHLH104, particular attention should be paid to binding sites in promoters of genes involved in iron homeostasis, as these are likely to be functionally significant targets.

How can I integrate BHLH104 protein interaction data with transcriptional regulation data?

Integrating protein interaction and transcriptional regulation data provides a comprehensive view of BHLH104 function:

• Data Collection and Organization:

  • Compile BHLH104 protein interaction data from Y2H, Co-IP, and BiFC experiments

  • Gather transcriptional data from ChIP-seq, RNA-seq, and gene expression analyses

  • Organize data in compatible formats for integration analysis

• Network Construction:

  • Build a protein-protein interaction (PPI) network with BHLH104 and its interactors

  • Construct a gene regulatory network (GRN) based on ChIP-seq binding data and expression correlations

  • Integrate both networks to identify coordinated regulatory modules

• Functional Module Identification:

  • Apply clustering algorithms to identify modules of functionally related genes and proteins

  • Focus on modules enriched for iron homeostasis-related functions

  • Analyze the connectivity between BHLH104, ILR3, and their target genes

• Multi-omics Data Integration:

  • Correlate BHLH104 binding events with expression changes in target genes

  • Assess how protein interactions (e.g., with ILR3) affect binding specificity and transcriptional outcomes

  • Identify condition-specific regulatory mechanisms (e.g., iron deficiency response)

• Visualization Tools:

  • Use network visualization software (e.g., Cytoscape) to represent integrated data

  • Create customized visualization schemes to highlight different data types

  • Generate interactive visualizations for exploring complex relationships

• Validation Experiments:

  • Design validation experiments to test hypotheses generated from integrated analysis

  • Consider genetic approaches (e.g., double mutants of BHLH104 and interaction partners)

  • Perform reporter gene assays to validate predicted regulatory effects

This integrated approach can reveal how BHLH104's protein interactions influence its DNA binding and transcriptional activation capabilities, particularly in the context of iron homeostasis regulation.

What statistical approaches are appropriate for analyzing BHLH104 protein levels across different experimental conditions?

Robust statistical analysis is crucial for interpreting BHLH104 protein quantification data:

• Normalization Methods:

  • Normalize BHLH104 levels to appropriate loading controls (actin, tubulin)

  • Consider total protein normalization methods (e.g., using stain-free technology)

  • For mass spectrometry data, apply appropriate normalization techniques (e.g., NSAF, iBAQ)

• Statistical Tests for Group Comparisons:

  • For normally distributed data: t-test (two groups) or ANOVA with post-hoc tests (multiple groups)

  • For non-normally distributed data: non-parametric alternatives (Mann-Whitney U test, Kruskal-Wallis)

  • For time-course experiments: repeated measures ANOVA or mixed-effects models

• Multiple Testing Correction:

  • Apply appropriate multiple testing corrections (e.g., Bonferroni, Benjamini-Hochberg FDR)

  • Report both raw and adjusted p-values for transparency

• Effect Size Calculation:

  • Calculate and report effect sizes (Cohen's d, fold changes) in addition to p-values

  • Consider biological significance in addition to statistical significance

• Correlation Analyses:

  • Use correlation analyses to relate BHLH104 protein levels with:

    • Expression levels of target genes (bHLH38/39/100/101)

    • Iron content in tissues

    • Phenotypic measurements of iron deficiency responses

• Multivariate Analyses:

  • Consider principal component analysis (PCA) or other dimensionality reduction techniques

  • Apply cluster analysis to identify patterns across multiple experimental conditions

• Statistical Power Considerations:

  • Conduct power analyses to determine appropriate sample sizes

  • Report sample sizes, technical and biological replication information

When analyzing BHLH104 protein levels, it's important to note that while transcript levels are not responsive to iron deficiency , post-translational modifications or protein stability changes might affect protein levels under different conditions.

How can BHLH104 antibodies be used to study the spatial and temporal dynamics of iron deficiency responses?

BHLH104 antibodies enable sophisticated studies of the spatial and temporal aspects of iron deficiency responses:

• Time-Course Immunoblotting:

  • Track BHLH104 protein levels at multiple time points following iron deficiency treatment

  • Correlate protein levels with the expression of downstream genes like bHLH38/39/100/101

  • Compare the dynamics in different tissues (roots vs. shoots)

• Live Cell Imaging with Fluorescent Antibodies:

  • Use fluorescently labeled BHLH104 antibodies for live cell imaging in plant tissues

  • Track protein localization changes in response to iron availability

  • Combine with fluorescent markers for other proteins to observe co-localization dynamics

• Single-Cell Approaches:

  • Apply single-cell proteomics techniques with BHLH104 antibodies

  • Identify cell-type-specific responses to iron deficiency

  • Correlate with single-cell transcriptomics data

• Developmental Stage Analysis:

  • Study BHLH104 abundance and activity across different developmental stages

  • Investigate how the iron deficiency response changes throughout plant development

  • Correlate with expression of interacting partners like ILR3

• Microfluidic Approaches:

  • Combine microfluidic systems with immunofluorescence to study rapid responses

  • Create iron availability gradients and monitor BHLH104 responses in real-time

  • Integrate with other sensors for comprehensive monitoring

• Chromatin Dynamics Studies:

  • Use ChIP-seq with BHLH104 antibodies at different time points after iron deficiency induction

  • Track changes in genomic binding patterns over time

  • Correlate with chromatin accessibility data and histone modification changes

These approaches can reveal how plants coordinate iron deficiency responses across tissues and time, providing insights into the regulatory networks controlling this essential nutrient homeostasis process.

What are the prospects for using BHLH104 antibodies in studying protein degradation mechanisms?

BHLH104 antibodies offer valuable tools for investigating protein degradation mechanisms:

• Protein Stability Assays:

  • Use cycloheximide chase assays with BHLH104 antibodies to measure protein half-life

  • Compare stability under iron-sufficient and iron-deficient conditions

  • Investigate the effects of proteasome inhibitors (e.g., MG132) on BHLH104 levels

• Ubiquitination Studies:

  • Perform immunoprecipitation with BHLH104 antibodies followed by ubiquitin immunoblotting

  • Identify ubiquitination sites using mass spectrometry

  • Investigate the role of specific E3 ligases in targeting BHLH104 for degradation

• Interaction with Degradation Machinery:

  • Examine interactions between BHLH104 and components of the ubiquitin-proteasome system

  • Study the role of BTSL1 and BTSL2, which contain RING E3 ligase domains and interact with bHLH transcription factors

  • Investigate potential competition between FEP3/IMA1 and bHLH factors for BTSL binding

• Protein Modification Impact on Degradation:

  • Investigate how post-translational modifications affect BHLH104 stability

  • Correlate modification status with degradation rates

  • Identify condition-specific degradation patterns

• Spatiotemporal Regulation of Degradation:

  • Use immunofluorescence to track cellular localization during degradation

  • Investigate tissue-specific degradation patterns

  • Study developmental regulation of BHLH104 turnover

Research has shown that BTSL1 and BTSL2 interact with bHLH factors including BHLH104, potentially regulating their stability through ubiquitination and subsequent degradation . The interaction between FEP3/IMA1 and BTSL proteins may inhibit bHLH binding to BTSL1, suggesting a competitive regulatory mechanism .

How might BHLH104 antibodies contribute to understanding cross-talk between iron homeostasis and other nutrient signaling pathways?

BHLH104 antibodies can provide critical insights into the integration of iron homeostasis with other nutrient signaling networks:

• Multi-nutrient Deficiency Studies:

  • Use BHLH104 antibodies to monitor protein levels under combined nutrient stresses

  • Compare responses to iron deficiency alone versus combined deficiencies (Fe+P, Fe+N, Fe+S)

  • Track changes in protein-protein interactions under different nutrient conditions

• Hormone-Nutrient Interactions:

  • Investigate how plant hormones affect BHLH104 protein levels and activity

  • Study protein modifications in response to hormone treatments

  • Examine co-localization with hormone-responsive factors

• Stress Signaling Integration:

  • Monitor BHLH104 responses during abiotic and biotic stresses

  • Investigate potential modifications and interactions specific to stress conditions

  • Study how iron homeostasis adapts to broader stress responses

• Metabolic Pathway Coordination:

  • Use co-immunoprecipitation with BHLH104 antibodies to identify interactors involved in other metabolic pathways

  • Perform ChIP-seq to identify binding to genes outside the canonical iron homeostasis pathway

  • Correlate binding patterns with metabolomic changes

• Developmental Context Integration:

  • Examine how developmental signals influence BHLH104 activity

  • Study tissue-specific responses and modifications

  • Investigate developmental defects in bhlh104 mutants under various nutrient conditions

• Interaction with Other Regulatory Networks:

  • Study the relationship between BHLH104 and other nutrient-responsive transcription factors

  • Investigate potential competition or cooperation for common target genes

  • Examine how BHLH104-containing complexes change under different nutrient conditions

This research direction could reveal how plants integrate multiple nutrient signals to optimize growth and development under varying environmental conditions, with BHLH104 potentially serving as a node in a complex regulatory network.