Recombinant Arabidopsis thaliana RING-H2 finger protein ATL81 (ATL81)

How is recombinant ATL81 protein typically expressed and purified for research purposes?

The expression and purification of recombinant ATL81 typically follows these methodological steps:

• Expression system selection: E. coli is commonly used for expression of recombinant ATL81 with an N-terminal His tag .

• Construct design: The coding sequence for mature ATL81 (amino acids 20-332) is cloned into an appropriate expression vector with an N-terminal His tag for purification .

• Expression conditions: Based on protocols for similar proteins:

  • Induction with IPTG at optimal temperature (typically 16-25°C)

  • Extended expression time (6-16 hours) to maximize yield while minimizing inclusion body formation

• Purification strategy:

  • Immobilized metal affinity chromatography (IMAC) using the His tag

  • Buffer optimization to maintain zinc finger integrity, typically including:

    • Tris/PBS-based buffer, pH 8.0

    • Addition of zinc (critical for maintaining RING-H2 domain structure)

    • 6% Trehalose as a stabilizing agent

• Storage conditions:

  • Lyophilization or storage in buffer with 50% glycerol

  • Aliquoting to avoid repeated freeze-thaw cycles

  • Storage at -20°C/-80°C for long-term preservation

Important methodological consideration: Unlike some other recombinant proteins, ATL81 and related RING-H2 proteins should be purified under native conditions rather than denaturing and refolding processes, as proper folding is critical for zinc finger integrity and function .

How does ATL81 relate to other members of the ATL family in Arabidopsis thaliana?

ATL81 is one member of a large family of RING-H2 proteins in Arabidopsis thaliana. Research has revealed important relationships within this family:

• Evolutionary relationship: The ATL family represents a group of plant-specific E3 ubiquitin ligases that have undergone significant expansion in plants. In Arabidopsis, approximately 80 ATL genes have been identified, while in rice (Oryza sativa), about 121 ATL genes have been found .

• Domain conservation: All ATL family members share three critical features:

  • A canonical RING-H2 domain with conserved spacing between zinc-coordinating residues

  • Transmembrane helices toward the amino-terminus

  • A conserved GLD motif between the transmembrane helices and the RING-H2 domain

• Structural diversity: Despite conserved domains, ATLs show high variability in size (ranging from 124 to 993 amino acid residues) and in the regions outside the conserved domains, particularly at the carboxy-terminus following the RING-H2 domain .

• Functional implications: The ATL family in Arabidopsis has been implicated in various cellular processes, with some members showing early response to elicitor treatments, suggesting roles in plant defense responses .

What experimental designs are most effective for studying ATL81 function in vivo and in vitro?

Effective experimental design for ATL81 research requires careful consideration of several factors:

In vitro experiments:

• Protein interaction studies:

  • Fluorescence anisotropy (FA): This technique has been successfully used to study RNA-TZF interactions in related proteins and can be adapted to study ATL81 interactions with potential substrates or partners .

  • Electrophoretic mobility shift assays (EMSAs): Useful for examining binding activities and determining dissociation constants (Kd) for protein-substrate interactions .

• Enzymatic activity assays:

  • In vitro ubiquitination assays: To measure E3 ligase activity, requiring recombinant E1, E2, ubiquitin, ATP, and potential substrates.

  • Controls: Include negative controls (lacking ATP or with mutated critical residues in the RING-H2 domain) to validate specificity.

In vivo experiments:

• Expression studies:

  • Randomized block design: This approach is preferred over completely randomized design when studying ATL81 expression under various conditions .

  • Design matrix for a randomized block experiment:

  Treatment	Block 1 (Age Group 1)	Block 2 (Age Group 2)	Block 3 (Age Group 3)
  Control	Random assignment	Random assignment	Random assignment
  Stress 1	Random assignment	Random assignment	Random assignment
  Stress 2	Random assignment	Random assignment	Random assignment

• Functional characterization:

  • Plant transformation: For overexpression or knockdown studies.

  • Phenotypic analysis: Systematically evaluate multiple parameters under controlled conditions.

  • Statistical considerations: Include adequate biological and technical replicates (minimum n=3) for robust statistical analysis .

• Interaction studies:

  • Co-immunoprecipitation: Using anti-ATL81 antibodies to pull down protein complexes.

  • Yeast two-hybrid screening: To identify potential interacting partners.

  • BiFC (Bimolecular Fluorescence Complementation): To visualize protein interactions in planta.

When designing ATL81 experiments, researchers should consider:

• Control for confounding variables

• Use factorial designs when studying multiple variables (e.g., treatment and cell line)

• Determine appropriate sample size based on expected effect size and desired statistical power

How can researchers evaluate the importance of zinc finger integrity for ATL81 function?

Evaluating zinc finger integrity in ATL81 requires multiple complementary approaches:

• Site-directed mutagenesis strategy:

  • Critical residues to target: The conserved cysteines and histidines within the RING-H2 domain that coordinate zinc binding .

  • Recommended mutations: Replace cysteines with serines or alanines and histidines with alanines or leucines.

  • Control mutations: Include mutations in non-conserved residues outside the zinc-binding sites.

• Structural analysis approaches:

  • Circular dichroism (CD): To assess changes in secondary structure upon mutation or zinc removal.

  • Zinc binding assays: Using zinc-specific fluorescent probes or isothermal titration calorimetry.

  • Limited proteolysis: To compare structural stability between wild-type and mutant proteins.

• Functional assays:

  • In vitro ubiquitination assays: Compare activity between wild-type and mutant proteins.

  • Binding assays with potential substrates: Use fluorescence anisotropy or EMSAs to measure affinities .

  • Cellular localization studies: Determine if mutations affect proper localization.

Based on studies with related proteins, the integrity of the zinc finger domain is likely critical for ATL81 function. For instance, mutations of conserved cysteine residues within related RR-TZF motifs have been shown to diminish interactions, suggesting that zinc finger integrity is important for binding .

What are the optimal conditions for expressing and purifying active recombinant ATL81 protein?

Optimizing expression and purification of active ATL81 requires careful attention to several factors:

• Expression optimization:

  • E. coli strain selection: BL21(DE3) or Rosetta strains are often preferred for RING domain proteins.

  • Temperature: Lower temperatures (16-18°C) often improve solubility of RING finger proteins.

  • Induction conditions: Lower IPTG concentrations (0.1-0.5 mM) and longer induction times.

  • Media supplementation: Adding 50-100 μM ZnCl₂ to the growth media can improve proper folding of the RING-H2 domain.

• Solubility enhancement strategies:

  • Fusion partners: GST tags have been shown to produce soluble recombinant RING-H2 proteins in bacteria .

  • Comparison of purification results with different tags:

  Tag Type	Solubility	Purity	Activity	Comments
  His-tag	Variable	High	Variable	May require refolding
  GST-tag	Higher	Good	Better	Shown to maintain proper folding
  MBP-tag	Highest	Good	Good	Large tag may interfere with some assays

• Critical purification considerations:

  • Native conditions: Purify under native conditions rather than denaturing conditions to maintain proper folding .

  • Buffer composition: Include zinc (10-50 μM ZnCl₂) in all buffers to maintain zinc finger integrity.

  • Reducing agents: Include DTT or β-mercaptoethanol to prevent oxidation of cysteines.

  • pH optimization: Typically pH 7.5-8.0 works best for RING-H2 proteins.

  • Storage buffer: Tris/PBS-based buffer with 6% Trehalose at pH 8.0, with addition of 50% glycerol for freezing .

• Quality control:

  • Western blot analysis: Using anti-ATL81 antibodies to confirm identity .

  • Activity assays: Verify ubiquitin ligase activity with in vitro assays.

  • Zinc content analysis: ICP-MS to confirm proper zinc incorporation.

How does ATL81 fit into the evolutionary context of plant RING-H2 proteins?

The evolutionary context of ATL81 within plant RING-H2 proteins reveals important insights about functional specialization:

• Evolutionary distribution:

  • ATL family members are plant-specific and have been identified in all plant species examined.

  • The canonical RING-H2 domain with specific spacing between zinc-coordinating residues is highly conserved across plant species .

• Gene family expansion:

  • Significant expansion of the ATL family is observed in plants compared to other eukaryotes.

  • In analyses of 24 plant genomes, most (in 17 of 24 genomes) contain a high percentage (≥85%) of proteins with the canonical ATL architecture (RING-H2 domain + transmembrane helix), suggesting strong evolutionary selection for this domain arrangement .

• Structural adaptations:

  • The RING-H2 domain represents a subtle variation of the canonical RING domain, present in less than 10% of RING fingers described in eukaryotes .

  • The conservation of RING-H2 in several plant gene families, but not in other eukaryotes, suggests specialization for plant-specific functions .

• Phylogenetic analysis insights:

  • ATL81 belongs to a specific clade within the larger ATL family.

  • Phylogenetic trees constructed from complete gene sequences, concatenated motifs, and the 42 amino acid segment encompassing the RING-H2 domain all provide consistent phylogenies .

  • Some ATL clades show patterns of species-specific expansion, suggesting adaptation to specific environmental challenges.

• Domain diversity:

  • Apart from the conserved domains (RING-H2, GLD motif, transmembrane helices), ATLs show high sequence diversity.

  • The region showing most size variability is at the carboxy-terminus following the RING-H2 domain, which may be absent in some members or display extensions of several hundred residues .

The specialization of the RING-H2 domain in plants suggests that ATL81 and related proteins may have evolved to fulfill plant-specific functions, possibly related to unique aspects of plant physiology or defense responses.

What experimental approaches can be used to study ATL81's role in the ubiquitin-proteasome system?

Studying ATL81's role in the ubiquitin-proteasome system (UPS) requires a multi-faceted experimental approach:

By combining these approaches, researchers can establish:

• The specific role of ATL81 in the UPS

• Its substrate specificity

• The biological processes regulated by ATL81-mediated ubiquitination

• The conditions under which ATL81 is activated

What are the best approaches for designing experiments to study ATL81 function in different plant tissues?

Designing robust experiments to study ATL81 function across plant tissues requires careful planning:

• Experimental design optimization:

  • Good-Toulmin like estimator via Thompson sampling (GT-TS): This computational method is valuable for iterative experimental design when studying proteins across multiple tissues, allowing estimation of how many cells are required from each tissue to maximize discovery .

  • Randomized block design: More effective than completely randomized design when studying expression across different plant tissues or under various treatments .

• Tissue-specific expression analysis:

  • mRNA analysis: RT-qPCR or RNA-seq to quantify tissue-specific expression patterns.

  • Protein analysis: Western blotting or tissue-specific proteomics.

  • Promoter analysis: Using ATL81 promoter fused to reporter genes (GUS, GFP).

  Example data table format for tissue-specific expression:

  Tissue Type	Relative ATL81 Expression (RT-qPCR)	Protein Level (Western Blot)	Developmental Stage
  Root	(data)	(data)	Seedling
  Stem	(data)	(data)	Mature
  Leaf	(data)	(data)	Mature
  Flower	(data)	(data)	Stage 12
  Silique	(data)	(data)	Stage 1

• Functional characterization strategies:

  • Tissue-specific knockdown/knockout: Using tissue-specific promoters or inducible systems.

  • Tissue-specific overexpression: Using tissue-specific promoters.

  • Complementation experiments: Expressing ATL81 in specific tissues of knockout plants.

• Response to environmental stimuli:

  • Sequential decision-making strategies: For systematic experiment prioritization when studying ATL81 response to multiple stimuli .

  • Early response gene analysis: Based on related ATL family members, consider testing if ATL81 functions as an early response gene to various stimuli .

• Statistical considerations:

  • Sample size determination: Based on expected effect size and desired statistical power .

  • Control for confounding variables: Particularly important when studying multiple tissues or conditions .

  • Data analysis approaches: Analysis of variance (ANOVA) for comparing multiple tissues or conditions .

How can researchers effectively analyze and interpret data from ATL81 protein interaction studies?

Effective analysis and interpretation of ATL81 protein interaction data requires rigorous approaches:

• Fluorescence anisotropy (FA) data analysis:

  • Binding curve fitting: Use non-linear regression to fit binding curves and determine dissociation constants (Kd).

  • Example equation: FA = FAmin + [(FAmax - FAmin) × (([P] / (Kd + [P]))]

  • Comparison with controls: Include positive controls (known interactions) and negative controls (non-binding proteins).

  • Statistical validation: Report confidence intervals for Kd values.

• Electrophoretic mobility shift assay (EMSA) analysis:

  • Quantification: Use densitometry to quantify band shifts.

  • Competition experiments: Include unlabeled competitors to confirm specificity.

  • Mutational analysis: Compare binding of wild-type and mutant proteins.

• Co-immunoprecipitation (Co-IP) data interpretation:

  • Validation criteria: Reproducibility across multiple biological replicates.

  • Controls: Include IgG controls, input controls, and reciprocal Co-IPs.

  • Quantification: Normalize Co-IP signal to input and IP efficiency.

• Mass spectrometry data analysis for interaction partners:

  • Filtering criteria: Minimum peptide count, confidence scores, and enrichment over controls.

  • Statistical approach: Use appropriate statistical tests to determine significant enrichment.

  • Network analysis: Place identified interactions in biological context.

  • Example data presentation format:

  Protein	Peptides	Score	Fold Enrichment	p-value	Known Function
  Protein X	12	87.5	8.3	0.003	Transcription factor
  Protein Y	8	62.1	5.7	0.008	E2 enzyme
  Protein Z	15	91.2	7.2	0.001	Stress response

• Yeast two-hybrid (Y2H) data interpretation:

  • Validation in planta: Confirm Y2H interactions using in planta methods.

  • Domain mapping: Use truncated proteins to map interaction domains.

  • Functional relevance: Assess biological significance through phenotypic analysis.

• Integration of multiple interaction datasets:

  • Consensus approach: Prioritize interactions detected by multiple methods.

  • Biological context: Interpret interactions in the context of known biological processes.

  • Pathway enrichment analysis: Determine if interacting proteins are enriched in specific pathways.

• Validation of interactions:

  • Genetic approaches: Phenotypic analysis of double mutants.

  • Subcellular co-localization: Microscopy to confirm protein co-localization.

  • Functional assays: Determine if interacting proteins affect ATL81 activity.

What are the most effective methods to analyze ATL81 gene expression data across different experimental conditions?

Analyzing ATL81 gene expression data requires careful methodology and appropriate statistical approaches:

• RT-qPCR data analysis:

  • Reference gene selection: Use multiple reference genes (minimum 3) that are stable under the experimental conditions.

  • Normalization method: Use geometric averaging of multiple reference genes (e.g., geNorm or NormFinder algorithms).

  • Relative quantification: Use the 2^(-ΔΔCt) method with proper validation of primer efficiencies.

  • Statistical analysis: Apply appropriate statistical tests based on experimental design:

    • t-test for comparing two conditions

    • ANOVA for multiple conditions

    • Mixed models for complex designs

• RNA-seq data analysis pipeline:

  • Quality control: Filter low-quality reads and adapters (FastQC, Trimmomatic).

  • Alignment: Map to Arabidopsis reference genome (STAR or HISAT2).

  • Quantification: Count reads per gene (featureCounts, HTSeq).

  • Normalization: Normalize for sequencing depth and gene length (FPKM, TPM, or using DESeq2/edgeR).

  • Differential expression analysis: Use DESeq2, edgeR, or limma-voom with appropriate statistical models.

  • Visualization: MA plots, volcano plots, and heatmaps.

• Time-course expression analysis:

  • Specialized tools: Use time-course specific packages (e.g., maSigPro, ImpulseDE2).

  • Pattern identification: Cluster genes with similar expression patterns.

  • Early response characterization: For studying ATL81 as a potential early response gene .

• Meta-analysis across multiple experiments:

  • Effect size calculation: Use standardized mean differences or log-fold changes.

  • Heterogeneity assessment: Evaluate consistency across experiments (I² statistic).

  • Random-effects models: Account for between-study variability.

• Integration with other data types:

  • Proteomics correlation: Compare transcript and protein level changes.

  • Chromatin accessibility: Integrate with ATAC-seq or DNase-seq data.

  • Transcription factor binding: Correlate with ChIP-seq data for relevant transcription factors.

• Functional interpretation:

  • Gene Ontology enrichment: Identify biological processes correlated with ATL81 expression.

  • Gene set enrichment analysis (GSEA): Detect subtle but coordinated changes in predefined gene sets.

  • Co-expression network analysis: Identify genes with similar expression patterns (WGCNA).

• Visualization best practices:

  • Error representation: Always include measures of variability (standard error or confidence intervals).

  • Sample size reporting: Clearly state biological and technical replicate numbers.

  • Example expression data visualization:

  Treatment	Time Point (h)	ATL81 Relative Expression	Standard Error	p-value
  Control	0	1.00	0.05	-
  Control	1	1.12	0.08	0.240
  Elicitor	0	1.03	0.07	0.680
  Elicitor	1	3.75	0.21	<0.001

How does ATL81 compare structurally and functionally to other ATL family members in Arabidopsis thaliana?

ATL81 shares key features with other ATL family members while possessing unique characteristics:

Understanding these similarities and differences provides crucial context for ATL81 research and may guide hypotheses about its specific functions in plant biology.

How do experimental approaches for studying ATL81 differ from those used for other protein families?

Studying ATL81 requires specialized experimental approaches that differ from those used for other protein families:

• Specific considerations for membrane-associated E3 ligases:

  • Protein expression challenges: The presence of transmembrane domains in ATL81 creates specific challenges for recombinant expression.

  • Solubilization strategies: Require careful optimization of detergents or membrane mimetics.

  • Functional assays: Must account for potential membrane association in activity assays.

• Structural biology approaches:

  • Crystallization challenges: Membrane-associated RING-H2 proteins like ATL81 are difficult to crystallize.

  • Alternative strategies: NMR spectroscopy of isolated domains or cryo-EM for larger complexes.

  • Computational modeling: May be more heavily relied upon compared to soluble proteins.

• Maintaining zinc finger integrity:

  • Buffer requirements: All buffers must contain zinc and reducing agents.

  • Purification conditions: Native conditions are essential as denaturation/refolding can compromise zinc finger structure .

  • Activity preservation: Additional care needed to maintain proper folding compared to non-zinc finger proteins.

• Substrate identification methods:

  • Proximity-dependent labeling: BioID or TurboID fusions to identify proteins in proximity to ATL81.

  • Ubiquitination site mapping: Specialized proteomics to identify ubiquitinated proteins dependent on ATL81.

  • E2 enzyme profiling: Testing multiple E2 enzymes to identify functional pairs with ATL81.

• In vivo studies:

  • Subcellular localization: Requires membrane markers for co-localization studies.

  • Protein-protein interactions: Membrane yeast two-hybrid systems may be required instead of conventional Y2H.

  • Functional redundancy: Higher potential for genetic redundancy among ATL family members may necessitate multiple gene knockouts.

• Comparative methodological approaches:

  Methodology	Adaptation for ATL81	Challenges	Solutions
  Protein expression	GST or MBP fusion	Transmembrane domains	Use only mature protein (aa 20-332)
  Interaction studies	Membrane Y2H or split-ubiquitin	Membrane association	Include appropriate controls
  Ubiquitination assays	In vitro reconstitution	E2 enzyme selection	Test panel of E2 enzymes
  Localization studies	Fluorescent protein fusion	Interference with function	C- and N-terminal tags
  Functional analysis	Gene editing	Redundancy	Multiple gene targeting

This specialized methodology ensures that experiments accurately capture the unique properties of ATL81 as a membrane-associated RING-H2 E3 ligase.

What are common problems encountered when working with recombinant ATL81 and how can they be resolved?

Researchers frequently encounter specific challenges when working with ATL81 and other RING-H2 proteins. Here are evidence-based solutions:

• Low protein expression levels:

  • Problem: ATL81 often expresses poorly in bacterial systems.

  • Solutions:

    • Optimize codon usage for E. coli

    • Use specialized E. coli strains (Rosetta, Arctic Express)

    • Lower induction temperature (16-18°C)

    • Test different fusion tags (GST has shown success with related proteins)

    • Supplement growth media with 50-100 μM ZnCl₂

• Protein insolubility:

  • Problem: Transmembrane domains can cause aggregation.

  • Solutions:

    • Express only the mature protein (amino acids 20-332)

    • Use solubility-enhancing tags (GST, MBP)

    • Add mild detergents (0.1% Triton X-100 or NP-40)

    • Optimize lysis buffer composition

    • Consider inclusion body isolation and refolding as a last resort

• Loss of zinc finger integrity:

  • Problem: Improper folding of the RING-H2 domain.

  • Solutions:

    • Purify under native conditions (avoid denaturing protocols)

    • Include zinc (10-50 μM ZnCl₂) in all buffers

    • Add reducing agents (1-5 mM DTT or β-mercaptoethanol)

    • Include stabilizing agents (6% Trehalose)

    • Avoid EDTA in all buffers

• Inactive recombinant protein:

  • Problem: Purified protein lacks expected E3 ligase activity.

  • Solutions:

    • Verify zinc incorporation using zinc-specific assays

    • Test multiple E2 enzymes as partners

    • Ensure proper buffer conditions (pH 7.5-8.0, zinc, reducing agents)

    • Add protease inhibitors to prevent degradation

    • Test protein immediately after purification

• Protein instability during storage:

  • Problem: Activity loss during storage.

  • Solutions:

    • Store in small aliquots to avoid freeze-thaw cycles

    • Add 50% glycerol for -20°C/-80°C storage

    • Use lyophilization for long-term storage

    • Test activity after storage to establish stability timeline

• Troubleshooting decision tree:

  Symptom	First Check	If Negative	If Still Problematic
  Low yield	Expression level	Solubility	Alternative expression system
  No activity	Zinc presence	E2 enzyme compatibility	Protein integrity by SDS-PAGE
  Aggregation	Buffer conditions	Remove transmembrane region	Detergent screening
  Degradation	Protease inhibitors	Expression temperature	Purification speed
  Poor binding	Assay conditions	Protein concentration	Alternative binding assays

How can researchers overcome challenges in studying ATL81 function in Arabidopsis thaliana?

Studying ATL81 function in Arabidopsis presents specific challenges that can be addressed with these methodological approaches:

• Genetic redundancy issues:

  • Challenge: Functional overlap with other ATL family members may mask phenotypes.

  • Solutions:

    • Create higher-order mutants targeting multiple related ATLs

    • Use inducible RNAi or artificial microRNAs targeting conserved regions

    • Employ CRISPR-Cas9 multiplex targeting

    • Use dominant-negative approaches (e.g., expressing RING-H2 mutant versions)

• Phenotypic analysis limitations:

  • Challenge: Subtle phenotypes may be difficult to detect.

  • Solutions:

    • Implement high-throughput phenotyping platforms

    • Test multiple growth conditions, particularly stress conditions

    • Use more sensitive assays (transcriptomics, metabolomics)

    • Design randomized block experiments to control for environmental variation

    • Increase statistical power through proper experimental design

• Protein detection difficulties:

  • Challenge: Low abundance of native ATL81 protein.

  • Solutions:

    • Generate high-affinity antibodies against unique regions

    • Use epitope tagging (HA, FLAG, GFP) with native promoter

    • Employ targeted proteomics approaches (SRM/MRM)

    • Use immunoprecipitation to enrich before detection

• Substrate identification challenges:

  • Challenge: Transient nature of E3-substrate interactions.

  • Solutions:

    • Use proteasome inhibitors to stabilize ubiquitinated proteins

    • Employ proximity labeling methods (BioID, TurboID)

    • Create "substrate traps" by mutating the RING-H2 domain

    • Perform comparative proteomics between wild-type and atl81 mutants

• Experimental design considerations:

  • Challenge: Complex biological variation in plants.

  • Solutions:

    • Implement randomized block designs rather than completely randomized designs

    • Control for developmental stage and time of day

    • Ensure adequate biological replication (minimum n=3, preferably n≥5)

    • Use proper statistical methods for data analysis

• Decision framework for experimental approach selection:

  Research Objective	Recommended Primary Approach	Alternative Approach	Validation Method
  Gene function	T-DNA insertion lines	CRISPR-Cas9 knockout	Complementation
  Protein localization	Native promoter fusion	Transient expression	Fractionation
  Interaction partners	Co-IP/MS	Membrane Y2H	BiFC in planta
  Ubiquitination targets	Quantitative proteomics	Candidate approach	In vitro confirmation
  Transcriptional effects	RNA-seq	RT-qPCR array	Promoter analysis

By implementing these solutions, researchers can overcome the inherent challenges of studying ATL81 and generate more robust and reproducible data.