Recombinant Arabidopsis thaliana Transcription factor bHLH53 (BHLH53)

What is the basic structure of the bHLH53 transcription factor?

bHLH53 belongs to the basic/helix-loop-helix (bHLH) superfamily of transcription factors, characterized by a conserved bHLH signature domain of approximately 60 amino acids with two functionally distinct regions. The basic region at the N-terminal end of the domain comprises roughly 15 amino acids with a high number of basic residues and is responsible for DNA binding. The HLH region at the C-terminal end functions as a dimerization domain and consists mainly of hydrophobic residues that form two amphipathic α-helices separated by a loop region of variable sequence and length . The bHLH53 protein in Arabidopsis thaliana has the UniProt accession number Q84RD0 .

What DNA sequence motifs does bHLH53 recognize?

Like other bHLH proteins, bHLH53 is predicted to recognize the core DNA sequence motif known as the E-box (5′-CANNTG-3′). One of the most common variants of the E-box is the palindromic G-box (5′-CACGTG-3′). Specific conserved amino acids within the basic region provide recognition of the core consensus site, while other residues dictate specificity for particular types of E-boxes. Additionally, nucleotides flanking the hexanucleotide core play a role in binding specificity .

How does bHLH53 fit into the larger bHLH family in Arabidopsis?

bHLH53 is one of 147 bHLH proteins identified in the Arabidopsis genome, making this one of the largest transcription factor families in this plant species. These proteins can be classified into 21 subfamilies based on phylogenetic analysis of the bHLH domain sequences. This classification is supported by multiple criteria, including chromosomal distribution, conservation of exon/intron structural patterns, and predicted DNA binding activities .

What antibodies are available for studying bHLH53 protein?

Researchers can access polyclonal antibodies specific to Arabidopsis thaliana bHLH53, such as the one with product code CSB-PA771157XA01DOA. This antibody is raised in rabbit using recombinant Arabidopsis thaliana bHLH53 protein as the immunogen. It has been validated for applications including ELISA and Western Blot (WB). The antibody is supplied in liquid form with a storage buffer containing 50% glycerol, 0.01M PBS (pH 7.4), and 0.03% Proclin 300 as a preservative. For optimal results, store at -20°C or -80°C and avoid repeated freeze-thaw cycles .

What methods can be used to study bHLH53 DNA binding specificity?

To investigate DNA binding specificity of bHLH53, researchers can employ several complementary approaches:

• Yeast One-Hybrid Assays: To determine if bHLH53 can bind to specific DNA sequences.

• Electrophoretic Mobility Shift Assay (EMSA): To validate direct DNA binding and characterize affinity for various E-box variants.

• Chromatin Immunoprecipitation (ChIP): To identify genomic regions bound by bHLH53 in vivo.

• DNA Affinity Purification Sequencing (DAP-seq): For genome-wide profiling of binding sites.

Similar to studies performed on other bHLH proteins like PIF3 and PIF4, these methods can determine whether bHLH53 has specificity for the G-box or other E-box variants .

How can I express and purify recombinant bHLH53 protein?

A methodological approach for recombinant bHLH53 expression and purification typically involves:

• Cloning: Amplify the full-length bHLH53 coding sequence from Arabidopsis cDNA using gene-specific primers with appropriate restriction sites.

• Vector Construction: Clone the sequence into an expression vector (such as pET or pGEX) for bacterial expression systems.

• Expression: Transform into an E. coli expression strain (BL21 or Rosetta) and induce protein expression with IPTG.

• Purification: Use affinity chromatography (His-tag or GST-tag) followed by size exclusion chromatography.

• Validation: Confirm protein identity using mass spectrometry and assess activity through DNA binding assays.

For structural studies, it may be preferable to express only the bHLH domain (approximately 60 amino acids) rather than the full-length protein, particularly if the full protein exhibits poor solubility.

Does bHLH53 form homodimers or heterodimers?

While specific dimerization data for bHLH53 is not directly stated in the provided search results, based on the general properties of bHLH transcription factors, bHLH53 likely has the capacity to form both homodimers and heterodimers. Research on related family members such as PIF3 and PIF4 has demonstrated that these proteins can form both homodimers and heterodimers, and that both configurations can bind specifically to the G-box DNA sequence motif . Experimental verification of bHLH53's dimerization preferences would require techniques such as yeast two-hybrid assays, co-immunoprecipitation, or bimolecular fluorescence complementation (BiFC).

What techniques can be used to study bHLH53 protein-protein interactions?

To investigate potential interaction partners of bHLH53, researchers can employ multiple complementary approaches:

• Yeast Two-Hybrid (Y2H): A high-throughput screening tool to identify potential interaction partners.

• Co-Immunoprecipitation (Co-IP): To confirm interactions in planta using the bHLH53-specific antibody .

• Bimolecular Fluorescence Complementation (BiFC): For visualizing interactions in living cells.

• FRET/FLIM: To study the dynamics and strength of protein interactions.

• Protein Pull-Down Assays: Using recombinant bHLH53 to identify interacting proteins from plant extracts.

The choice of method depends on the specific research question, with Y2H providing broader screening capability and techniques like Co-IP or BiFC offering higher confidence validation in the native cellular environment.

What genes are regulated by bHLH53 in Arabidopsis?

While the specific gene targets of bHLH53 are not explicitly detailed in the provided search results, research approaches to identify these targets would include:

• ChIP-seq Analysis: This technique has been extensively used in Arabidopsis to identify binding sites for numerous transcription factors. For bHLH53, ChIP-seq would reveal genome-wide binding locations .

• RNA-seq of bHLH53 Mutants or Overexpressors: To identify differentially expressed genes dependent on bHLH53 function.

• Integration with Open Chromatin Data: Combining bHLH53 binding data with ATAC-seq or DNase-seq data to identify accessible chromatin regions where bHLH53 may function.

Research in Arabidopsis has shown that bHLH transcription factors often participate in extensive transcriptional networks. The ChIP-Hub platform has documented over 52.3 million high-confidence peaks from experiments for open chromatin, annotated TFs, and histone modifications in plants, with Arabidopsis having approximately 3,500 individual experiments generated .

How does bHLH53 function within transcriptional networks?

bHLH53 likely functions within larger transcriptional networks, as demonstrated for other bHLH proteins in Arabidopsis. Integrative analysis of TF-bound genomic regions in Arabidopsis has revealed potential TF co-associations by regulating similar sets of target genes . Based on patterns observed with other bHLH proteins, bHLH53 may participate in one of the three dominant co-associated TF modules identified in Arabidopsis:

• Module M1: Consisting of regulators from TF families of bZIP, bHLH, and MYB

• Module M2: Containing various regulators for histone regulation

• Module M3: Including MADS TFs responsible for flower development

The specific module association of bHLH53 would need to be determined experimentally through ChIP-seq and network analysis approaches .

How can CRISPR-Cas9 be used to study bHLH53 function?

For functional characterization of bHLH53 using CRISPR-Cas9 genome editing, researchers can implement the following methodological approach:

• Guide RNA Design: Design multiple sgRNAs targeting conserved regions within the bHLH domain or other functional domains of bHLH53.

• Vector Construction: Clone the sgRNAs into a plant CRISPR-Cas9 expression vector.

• Plant Transformation: Transform Arabidopsis using the floral dip method.

• Mutant Screening: Screen transformants for mutations using targeted sequencing.

• Phenotypic Analysis: Characterize mutants for developmental, physiological, and molecular phenotypes.

• Transcriptome Analysis: Perform RNA-seq to identify genes affected by bHLH53 mutation.

• Complementation Studies: Validate specificity by complementing with the wild-type bHLH53 gene.

This approach can generate complete knockout lines or targeted mutations that specifically affect DNA binding or dimerization capabilities while maintaining protein expression.

What is known about the evolutionary conservation of bHLH53 across plant species?

While the search results don't specifically address the evolutionary conservation of bHLH53, a comprehensive approach to studying its evolutionary history would include:

• Comparative Genomics: Identify bHLH53 orthologs in other plant species through sequence similarity searches.

• Phylogenetic Analysis: Construct phylogenetic trees to determine the evolutionary relationships among bHLH53 and related proteins across species.

• Domain Conservation Analysis: Compare conservation of the bHLH domain and other functional regions.

• Synteny Analysis: Examine conservation of genomic context around the bHLH53 locus.

The bHLH family in Arabidopsis has been classified into 21 subfamilies based on phylogenetic analysis . Determining which subfamily contains bHLH53 would provide insights into its potential functional conservation across species.

Why might recombinant bHLH53 show poor solubility, and how can this be addressed?

Transcription factors, including bHLH proteins, often present solubility challenges when expressed as recombinant proteins. Common solutions include:

• Expression Optimization:

  • Reduce induction temperature (16-20°C)

  • Use lower IPTG concentrations (0.1-0.5 mM)

  • Test different E. coli strains (Rosetta, Arctic Express)

• Construct Modification:

  • Express only the bHLH domain rather than full-length protein

  • Create fusion proteins with solubility-enhancing tags (MBP, SUMO)

  • Perform bioinformatic analysis to identify and remove aggregation-prone regions

• Buffer Optimization:

  • Include low concentrations of non-ionic detergents (0.05-0.1% Triton X-100)

  • Add stabilizing agents (5-10% glycerol, 100-500 mM NaCl)

  • Test different pH conditions (pH 6.5-8.5)

• Co-expression Strategies:

  • Co-express with known interaction partners

  • Co-express with chaperones (GroEL/GroES, DnaK/DnaJ)

A systematic approach testing these variables can significantly improve the yield of soluble, functional bHLH53 protein.

What are the common pitfalls in ChIP-seq experiments for bHLH transcription factors?

When performing ChIP-seq for bHLH transcription factors like bHLH53, researchers should be aware of these common challenges and solutions:

• Antibody Specificity:

  • Challenge: Cross-reactivity with other bHLH family members due to conserved domains

  • Solution: Validate antibody specificity using knockout lines and peptide competition assays

• Fixation Conditions:

  • Challenge: Over-fixation can mask epitopes while under-fixation leads to poor DNA recovery

  • Solution: Optimize formaldehyde concentration (1-1.5%) and fixation time (10-20 minutes)

• Chromatin Fragmentation:

  • Challenge: Inconsistent sonication can lead to biased genomic coverage

  • Solution: Standardize sonication protocols and verify fragment size distribution (200-500 bp)

• Low Signal-to-Noise Ratio:

  • Challenge: bHLH factors may have weak or transient binding

  • Solution: Increase cell input, optimize wash conditions, and use spike-in controls

• Data Analysis Considerations:

  • Challenge: Identifying true binding sites versus background

  • Solution: Use appropriate peak calling parameters (IDR < 0.05 is recommended) and biological replicates

Consensus Motif Amino Acid Frequencies in bHLH Domain

The table below compares the frequency of conserved amino acids in the bHLH domain between the general bHLH consensus and Arabidopsis bHLH proteins:

This data highlights the conservation and divergence patterns in Arabidopsis bHLH proteins compared to the general bHLH consensus .

Predicted DNA Binding Specificity of bHLH Subgroups

Based on the amino acid composition at key positions in the basic region, different bHLH proteins can be predicted to have different DNA binding specificities:

Without specific information about bHLH53's basic region composition, its exact DNA binding specificity group would need to be determined experimentally or through sequence analysis .

How might single-cell technologies advance our understanding of bHLH53 function?

Single-cell approaches offer promising new avenues for studying bHLH53 function with increased resolution:

• Single-Cell RNA-seq (scRNA-seq):

  • Can reveal cell type-specific expression patterns of bHLH53

  • May identify cell populations where bHLH53 has the most significant regulatory impact

  • Could detect subtle transcriptional responses missed in bulk tissue analysis

• Single-Cell ATAC-seq (scATAC-seq):

  • Would map chromatin accessibility changes in response to bHLH53 activity at single-cell resolution

  • Could identify cell type-specific regulatory elements targeted by bHLH53

• CUT&Tag at Single-Cell Level:

  • Would profile bHLH53 binding sites in individual cells

  • Could reveal heterogeneity in binding patterns across cell populations

• Live-Cell Imaging:

  • Using fluorescently tagged bHLH53 to track dynamics in real-time

  • Could reveal temporal aspects of bHLH53 nuclear localization and chromatin association

These technologies would complement the extensive bulk ChIP-seq data already available for Arabidopsis transcription factors .

What computational approaches can improve prediction of bHLH53 target genes?

Advanced computational methods to predict bHLH53 target genes include:

• Integrative Analysis Frameworks:

  • Combine ChIP-seq, ATAC-seq, and transcriptome data

  • Integrate with existing platforms like ChIP-Hub, which has documented extensive TF binding data in Arabidopsis

  • Weight predictions based on multiple evidence types

• Machine Learning Approaches:

  • Train models on known bHLH binding sites to predict new targets

  • Use convolutional neural networks to identify complex sequence patterns

  • Implement ensemble methods that combine multiple prediction algorithms

• Network Inference Methods:

  • Build gene regulatory networks incorporating bHLH53

  • Analyze co-expression patterns across various conditions

  • Identify network motifs involving bHLH53 and other transcription factors

• Comparative Genomics:

  • Leverage conservation of binding sites across related species

  • Identify evolutionarily conserved regulatory modules

Integration of these computational approaches with experimental validation would provide the most comprehensive understanding of bHLH53's regulatory targets.