Recombinant Arabidopsis thaliana Protein TIFY 4A (TIFY4A)

What is TIFY4A and to which protein family does it belong?

TIFY4A is a member of the TIFY protein family in Arabidopsis thaliana, defined by the presence of a highly conserved TIFY motif (TIF[F/Y]XG) that resides within the larger ZIM domain (Zinc-finger protein expressed in Inflorescence Meristem). The TIFY family in Arabidopsis consists of 18 members divided into two classes based on the presence or absence of a C2C2-GATA domain. TIFY4A belongs to class II that lacks this domain . Within the TIFY family, there are JAZ proteins, PEAPOD proteins, and other members with varying domain structures that determine their specific functions in plant growth and development.

What are the structural domains of TIFY4A and how do they compare to other TIFY family members?

TIFY4A contains the characteristic TIFY/ZIM domain that defines all members of this protein family. Unlike JAZ proteins that possess a Jas domain responsible for jasmonic acid response, or PEAPOD proteins (PPD1 and PPD2) that contain a divergent C-terminal Jas domain and an additional N-terminal PPD-domain, TIFY4A has a specific domain architecture that determines its functional properties . The protein's structure is particularly important for understanding its interactions with other proteins and its role in transcriptional regulation networks in Arabidopsis.

What is the cellular localization of TIFY4A in Arabidopsis cells?

TIFY4A, like other TIFY family proteins that function as transcriptional regulators, is predominantly localized in the nucleus. This localization is consistent with its presumed role in transcriptional regulation. Based on information from related TIFY proteins, we can infer that TIFY4A likely shows nuclear localization where it interacts with transcription factors and other regulatory proteins . Visualization studies using techniques similar to those employed for other TIFY proteins (such as bimolecular fluorescence complementation) would typically show nuclear fluorescence signals when TIFY4A is properly expressed and localized.

What are the recommended expression systems for producing recombinant TIFY4A protein?

For producing recombinant TIFY4A protein, yeast expression systems have proven effective for related Arabidopsis proteins. As demonstrated with BAS1 protein, expression in yeast can yield good purity levels (>90%) and functional protein . For TIFY4A, similar approaches should be considered, with optimization of expression conditions (temperature, induction time, and media composition) to maximize yield. Alternative expression systems include E. coli with appropriate fusion tags (His, GST, or MBP) to enhance solubility, or insect cell systems for proteins requiring eukaryotic post-translational modifications. The choice of expression system should be guided by the intended experimental application and the required protein quality.

How should researchers optimize purification protocols for recombinant TIFY4A?

Purification of recombinant TIFY4A should begin with affinity chromatography using an appropriate tag (such as His-tag) as seen with other Arabidopsis proteins . A typical protocol involves:

• Cell lysis under native conditions using buffer containing 20-50 mM Tris-HCl (pH 7.5-8.0), 100-300 mM NaCl, 10% glycerol, and protease inhibitors

• Affinity chromatography using Ni-NTA or similar resin for His-tagged proteins

• Size exclusion chromatography to remove aggregates and contaminants

• Assessment of purity by SDS-PAGE (using a 15% separating gel with 5% stacking gel as used for similar proteins)

• Verification of identity by Western blot or mass spectrometry

Protein stability should be monitored throughout purification, with optimization of buffer conditions (pH, salt concentration, and additives) to maintain protein integrity and activity.

What methods are most effective for studying TIFY4A protein-protein interactions?

To study TIFY4A protein-protein interactions, several complementary approaches should be considered:

• Yeast two-hybrid (Y2H) assays: Effective for initial screening of potential interacting partners, as demonstrated with other TIFY family members

• Bimolecular fluorescence complementation (BiFC): Particularly useful for confirming interactions in planta, where TIFY4A would be fused to one half of YFP and potential interacting proteins to the other half, allowing visualization of interaction sites within plant cells

• Co-immunoprecipitation (Co-IP): For biochemical confirmation of interactions from plant tissue or heterologous expression systems

• Surface plasmon resonance (SPR) or isothermal titration calorimetry (ITC): For quantitative analysis of binding kinetics and affinity

For BiFC experiments specifically, the protocol established for TIFY8 can be adapted, where interaction signals are predominantly observed in the nucleus and transformation efficiency is controlled using a separate RFP marker .

How does TIFY4A function in Arabidopsis stress response pathways?

TIFY4A likely plays a role in stress response pathways similar to other TIFY family members. Based on knowledge of related proteins, TIFY4A may function by:

• Interacting with transcription factors that regulate stress-responsive genes

• Potentially recruiting co-repressors like TOPLESS through adapter proteins such as NINJA or KIX8/9, as observed with other TIFY proteins

• Modulating responses to environmental stresses through transcriptional regulation

Research approaches to elucidate TIFY4A's specific role should include:

• Transcriptome analysis of TIFY4A overexpression and knockout lines under various stress conditions

• ChIP-seq to identify genomic binding sites of TIFY4A or its interacting transcription factors

• Phenotypic analysis of mutant plants under different stress conditions (drought, salt, pathogen infection)

These approaches would help establish TIFY4A's position in stress signaling networks and its contribution to plant resilience.

What is the relationship between TIFY4A and plant hormone signaling pathways?

TIFY4A may interact with plant hormone signaling pathways, particularly jasmonic acid (JA) signaling, although its exact role differs from JAZ proteins that have a dedicated Jas domain. To investigate TIFY4A's relationship with hormone signaling:

• Analyze TIFY4A expression patterns in response to different hormones (JA, salicylic acid, abscisic acid, auxin)

• Examine phenotypes of TIFY4A mutants when treated with various hormones

• Investigate interaction between TIFY4A and hormone-responsive transcription factors using BiFC or Y2H approaches

• Perform hormone sensitivity assays with TIFY4A overexpression and knockout lines

Unlike JAZ proteins whose stability is affected by JA treatment due to their Jas domain, TIFY4A would likely show different regulatory patterns that need specific investigation to understand its hormone-responsive behavior .

How can live-cell imaging techniques be applied to study TIFY4A dynamics in vivo?

For studying TIFY4A dynamics in vivo, researchers can adapt the live-cell imaging techniques developed for other Arabidopsis proteins. A recommended approach includes:

• Generation of fluorescent protein fusions (GFP or RFP) with TIFY4A under native or constitutive promoters

• Establishing imaging parameters that minimize photobleaching while maintaining temporal resolution (frames every 3-15 minutes depending on the process being studied)

• Using dual-reporter systems similar to the KINGBIRD system (combining different fluorescent markers) to simultaneously track TIFY4A and interacting proteins or cellular structures

• Employing confocal laser scanning microscopy with appropriate filter sets to detect the fluorescent signals

This approach would allow visualization of TIFY4A localization changes in response to developmental cues or environmental stresses, providing insights into its dynamic regulatory functions within living plant cells.

What are common challenges in expressing functional recombinant TIFY4A and how can they be addressed?

Common challenges in expressing functional recombinant TIFY4A include:

• Protein insolubility:

  • Use fusion tags that enhance solubility (MBP, SUMO, or TRX)

  • Optimize expression temperature (typically lower temperatures of 16-20°C)

  • Include solubility enhancers like sorbitol or arginine in culture media

• Protein instability:

  • Include protease inhibitors throughout purification

  • Add stabilizing agents (glycerol, reducing agents) to buffers

  • Test different buffer compositions for optimal stability

  • Consider co-expression with interacting partners

• Low yield:

  • Optimize codon usage for the expression host

  • Test different promoters and expression conditions

  • Consider using a eukaryotic expression system like yeast if E. coli yields are poor

• Improper folding:

  • Co-express with molecular chaperones

  • Include mild detergents or additives that promote proper folding

  • Develop a refolding protocol if the protein must be purified from inclusion bodies

Careful optimization of these parameters will help produce functional recombinant TIFY4A suitable for downstream applications.

How should researchers interpret contradictory results from different assays when studying TIFY4A function?

When facing contradictory results while studying TIFY4A function, researchers should consider:

• Methodological differences:

  • In vitro vs. in vivo approaches may yield different results due to the absence of cellular context in vitro

  • Different detection methods have varying sensitivities and limitations

• Experimental conditions:

  • Protein concentration effects (physiological vs. non-physiological levels)

  • Buffer composition affecting protein behavior

  • Temperature, pH, and salt concentration variations between experiments

• Resolution approach:

  • Use multiple complementary techniques to verify findings

  • For protein interactions, combine Y2H, BiFC, and biochemical approaches as was done for TIFY8

  • When in vitro and in planta results differ (as observed with TIFY8-C4 domain interaction studies), consider that plant-specific factors or modifications may be influencing the interaction

  • Design experiments that bridge the gap between contradictory results (e.g., testing whether additional plant factors are required for an interaction)

• Data interpretation framework:

  • Consider biological context and relevance of each assay

  • Evaluate whether differences reflect true biological complexity rather than experimental artifacts

  • Assess the quality control metrics for each experiment

This systematic approach helps reconcile apparently contradictory findings and develops a more complete understanding of TIFY4A function.

What are the best approaches for validating the specificity of TIFY4A interactions in complex plant systems?

To validate the specificity of TIFY4A interactions in complex plant systems, researchers should implement a multi-layered validation strategy:

• In vivo confirmation techniques:

  • Bimolecular fluorescence complementation (BiFC) with appropriate controls including non-interacting protein pairs

  • Co-immunoprecipitation from plant tissues under native conditions

  • FRET or FLIM-FRET for detecting interactions with spatial resolution

• Specificity controls:

  • Competition assays with unlabeled proteins

  • Domain mapping and mutational analysis to identify critical interaction interfaces

  • Testing related family members to determine interaction specificity within the TIFY family

• Functional validation:

  • Genetic analysis using CRISPR-generated mutants or RNAi lines

  • Phenotypic rescue experiments with wild-type and mutated versions of TIFY4A

  • Transcriptional reporter assays to confirm functional consequences of interactions

• Quantitative approaches:

  • Quantitative mass spectrometry (e.g., SILAC or TMT labeling) to measure interaction stoichiometry

  • Dose-response curves in protein-protein interaction assays

  • Kinetic measurements of association/dissociation rates

The combination of these approaches provides strong evidence for the biological specificity and relevance of TIFY4A interactions, distinguishing genuine interactions from experimental artifacts.

How might TIFY4A be involved in epigenetic regulation of gene expression?

TIFY4A may participate in epigenetic regulation through:

• Recruitment of chromatin-modifying complexes:

  • Similar to how some TIFY proteins recruit TOPLESS co-repressors through adapter proteins like NINJA or KIX8/9

  • Potentially affecting histone modifications at target gene loci

• Interaction with chromatin remodelers:

  • Possible associations with SWI/SNF or other ATP-dependent chromatin remodeling complexes

  • Influence on nucleosome positioning affecting gene accessibility

• Research approaches to investigate epigenetic functions:

  • ChIP-seq for histone modifications at TIFY4A target genes

  • Co-IP followed by mass spectrometry to identify associations with chromatin modifiers

  • ATAC-seq to analyze chromatin accessibility changes in TIFY4A mutants

  • Methylation analysis using bisulfite sequencing in wild-type and mutant plants

These investigations would reveal whether TIFY4A contributes to the establishment or maintenance of epigenetic marks that influence long-term gene expression patterns in Arabidopsis.

What computational approaches are recommended for predicting TIFY4A interactome networks?

For predicting TIFY4A interactome networks, researchers should consider:

• Sequence-based approaches:

  • Homology modeling based on known TIFY protein structures

  • Identification of conserved interaction motifs using multiple sequence alignments

  • Machine learning algorithms trained on known plant protein interaction data

• Structure-based predictions:

  • Molecular docking simulations if structural data is available

  • Protein-protein interaction site prediction using surface patch analysis

  • Molecular dynamics simulations to assess interaction stability

• Network biology approaches:

  • Integration of transcriptome co-expression data

  • Bayesian network modeling using existing interaction datasets

  • Guilt-by-association predictions based on functional annotation

• Validation strategy:

  • Select top candidates from computational predictions for experimental validation

  • Prioritize testing of proteins with related functions in plant stress or development

  • Use Y2H or BiFC to confirm predicted interactions

These computational approaches complement experimental methods and help focus wet-lab validation efforts on the most promising candidate interactors.