Recombinant Arabidopsis thaliana RING-H2 finger protein ATL58 (ATL58)

What is ATL58 and how is it classified within plant proteins?

ATL58 (At1g33480) is a member of the Arabidopsis Tóxicos en Levadura (ATL) family, a group of plant-specific RING-type ubiquitin ligases characterized by RING-H2 finger domains. The Arabidopsis genome contains 91 ATL isoforms, with ATL58 being annotated as a RING-type E3 ubiquitin transferase . Common features of ATL family proteins include one or two N-terminal transmembrane-like hydrophobic regions, a conserved GLD motif, a RING-H2 type zinc finger domain, and a diverse C-terminal region likely involved in substrate recognition .

How does ATL58 relate to other members of the ATL family functionally?

While the specific function of ATL58 has not been extensively characterized, other members of the ATL family have established roles in plant stress responses and metabolic regulation. For example:

• ATL15 functions in sugar-responsive plant growth in Arabidopsis

• ATL8 is involved in sugar starvation stress responses and may interact with Starch Synthase 4

• ATL2 plays a role in plant immune responses against pathogens like Alternaria brassicicola

Based on sequence homology and the conserved E3 ubiquitin ligase domain, ATL58 likely functions in protein ubiquitination pathways related to environmental stress responses or metabolic regulation .

What expression systems are optimal for producing recombinant ATL58 protein?

E. coli is the most commonly used expression system for recombinant ATL58 production. The full-length protein (1-261aa) can be successfully expressed with an N-terminal His-tag in E. coli systems . When designing expression constructs, researchers should consider:

• Using BL21(DE3) or similar strains optimized for protein expression

• Including appropriate protease cleavage sites if tag removal is desired

• Temperature optimization (typically lower temperatures of 18-25°C improve folding)

• Induction conditions (IPTG concentration and timing)

The hydrophobic N-terminal region may affect solubility, so expression strategies that address membrane protein challenges might be beneficial .

What purification methods yield the highest purity of recombinant ATL58?

Purification of His-tagged ATL58 typically follows these steps:

• Affinity chromatography using Ni-NTA or similar matrix

• Buffer exchange to remove imidazole

• Size exclusion chromatography for higher purity

The commercial recombinant ATL58 protein demonstrates greater than 90% purity as determined by SDS-PAGE . For optimal results:

• Include protease inhibitors during cell lysis

• Use reducing agents (DTT or β-mercaptoethanol) to maintain cysteine residues in the RING domain

• Consider detergent addition (0.1-0.5% mild non-ionic detergents like Triton X-100) if solubility issues occur due to the transmembrane-like domain

Researchers should confirm protein identity by western blot and/or mass spectrometry .

What storage conditions maintain ATL58 stability and activity?

Based on manufacturer recommendations for recombinant ATL58:

• Store lyophilized protein at -20°C/-80°C upon receipt

• After reconstitution, store at -20°C/-80°C with glycerol addition (recommended final concentration of 50%)

• Aliquot to avoid repeated freeze-thaw cycles

• Working aliquots can be stored at 4°C for up to one week

• Reconstitute in deionized sterile water to a concentration of 0.1-1.0 mg/mL

• Storage buffer typically contains Tris/PBS-based buffer with 6% trehalose at pH 8.0

Repeated freezing and thawing significantly reduces protein activity and should be avoided .

How can the ubiquitin ligase activity of ATL58 be assessed in vitro?

To evaluate the E3 ubiquitin ligase activity of ATL58, researchers typically employ an in vitro ubiquitination assay system containing:

• Purified recombinant ATL58 protein

• Ubiquitin (often fluorescently labeled or tagged)

• E1 ubiquitin-activating enzyme

• E2 ubiquitin-conjugating enzyme

• ATP regeneration system

• Reaction buffer (typically containing Tris-HCl, MgCl₂, DTT)

The reaction products are analyzed by SDS-PAGE followed by western blotting or fluorescence detection. Controls should include reactions lacking ATP or using a mutated version of ATL58 with substituted key cysteine residues in the RING domain (similar to the ATL2 C138A mutant described in reference ). This approach has successfully demonstrated ubiquitin ligase activity for other ATL family members, including ATL8 and ATL15 .

What approaches can determine ATL58 subcellular localization?

Based on studies of other ATL family proteins, the following approaches are recommended:

• Fluorescent protein fusion analysis:

  • Generate C-terminal or N-terminal GFP fusions of ATL58

  • Express in plant cells (protoplasts, N. benthamiana leaves via Agrobacterium-mediated transformation)

  • Visualize using confocal microscopy

  • Co-localize with established markers (e.g., AtPIP2A-mCherry for plasma membrane)

• Cell fractionation and western blotting:

  • Express tagged ATL58 in plant tissues

  • Perform cellular fractionation to separate membrane and soluble fractions

  • Analyze protein distribution by western blotting

  • Include controls for each cellular compartment

Given the N-terminal transmembrane-like domain, ATL58 is predicted to localize to membranes, similar to other ATL family members that show plasma membrane and/or endomembrane localization .

How can potential protein interaction partners of ATL58 be identified?

Several complementary approaches can be used to identify ATL58 interaction partners:

• Yeast two-hybrid screening:

  • Use ATL58 fragments (avoiding transmembrane domains) as bait

  • Screen against Arabidopsis cDNA libraries

  • Validate interactions with directed Y2H assays

• Co-immunoprecipitation followed by mass spectrometry:

  • Express tagged ATL58 (FLAG, HA, or GFP) in Arabidopsis

  • Perform immunoprecipitation using antibodies against the tag

  • Identify co-precipitating proteins by mass spectrometry

  • Similar approaches identified Starch Synthase 4 as an interactor with ATL8

• Bimolecular fluorescence complementation (BiFC):

  • Fuse ATL58 and candidate interactors with complementary fragments of fluorescent proteins

  • Co-express in plant cells

  • Visualize reconstituted fluorescence as evidence of interaction

Studies of other ATL family members suggest potential interaction partners may include metabolic enzymes or proteins involved in stress response pathways .

What considerations are important when designing knockout or overexpression studies for ATL58?

When designing genetic studies of ATL58 function:

For knockout studies:

• Obtain T-DNA insertion lines for At1g33480 (ATL58) from repositories like ABRC

• Verify homozygous T-DNA insertions by PCR using gene-specific primers and T-DNA border primers

• Confirm absence of ATL58 transcript using RT-PCR and RT-qPCR

• Include multiple independent knockout lines to control for insertion position effects

• Consider generating CRISPR/Cas9 knockout lines as an alternative approach

For overexpression studies:

• Place the ATL58 coding sequence under control of a constitutive promoter (e.g., CaMV35S)

• Include an epitope tag for protein detection (HA, FLAG, GFP)

• Select multiple independent transgenic lines with varying expression levels

• Verify transgene expression by RT-qPCR and protein level by western blot

• Consider inducible expression systems to study potential deleterious effects

Important controls:

• Generate catalytically inactive versions (e.g., mutations in the RING domain)

• Include wild-type plants grown under identical conditions

• Compare phenotypes across multiple generations and growth conditions

How should experiments be designed to study ATL58 responses to environmental stimuli?

Based on studies of related ATL family proteins and their responses to environmental stimuli:

• Sugar response experiments:

  • Grow seedlings on sugar-free medium for 8-10 days

  • Transfer to media containing various sugars (sucrose, glucose) at different concentrations

  • Monitor ATL58 expression at multiple time points (1h, 3h, 6h, 24h) using RT-qPCR

  • Include sugar analogs (non-metabolizable) to distinguish metabolic from signaling effects

  • Compare wild-type and atl58 mutant responses to sugar treatments

• Sugar starvation experiments:

  • Grow plants under normal conditions, then subject to extended darkness

  • Monitor ATL58 expression during the dark period (4h, 8h, 24h, 48h)

  • Analyze metabolite changes (starch, soluble sugars) in wild-type vs. atl58 mutants

  • This approach revealed ATL8 as a sugar starvation response gene

• Stress response assays:

  • Subject plants to various abiotic stresses (drought, salt, cold, heat)

  • Monitor ATL58 expression changes

  • Compare stress tolerance between wild-type and ATL58 transgenic lines

  • Analyze potential stress-response markers and metabolites

The experimental design should incorporate appropriate biological and technical replicates with controls for developmental stage and environmental conditions .

What statistical approaches are most appropriate for analyzing ATL58 functional data?

When analyzing data from ATL58 experiments, consider these statistical approaches:

• For expression analysis:

  • Normalize qPCR data using multiple reference genes (e.g., ACTIN, UBQ10)

  • Apply the ΔΔCt method for relative quantification

  • Use ANOVA followed by post-hoc tests (Tukey's HSD) for multiple comparisons

  • Consider log transformation for data that doesn't meet normality assumptions

• For phenotypic analysis:

  • Use paired t-tests when comparing the same plants before and after treatment

  • For comparing multiple genotypes and treatments, use two-way ANOVA with appropriate post-hoc tests

  • Include power analysis to ensure adequate sample sizes (n≥15 for most plant growth parameters)

  • Control for random effects when designing experiments with multiple batches or growth chambers

• For molecular interaction studies:

  • Apply appropriate statistical tests for co-localization analysis

  • For protein-protein interaction quantification, use multiple biological replicates and appropriate controls

  • Consider Bayesian approaches for complex datasets with multiple variables

When comparing technical versus biological replicates, prioritize biological replicates to account for natural variation, following the principle: "Block what you can, randomize what you cannot" (George Box, 1978) .

How can the substrate specificity of ATL58 be determined in the context of the ubiquitin-proteasome system?

Determining E3 ligase substrate specificity requires multiple complementary approaches:

• Protein microarray screening:

  • Purify active recombinant ATL58 protein

  • Screen against protein microarrays containing Arabidopsis proteins

  • Perform in vitro ubiquitination assays on candidate substrates

  • Validate with pull-down assays and mass spectrometry

• Differential proteomics:

  • Compare protein abundance and ubiquitination profiles between wild-type and atl58 mutants

  • Use ubiquitin remnant profiling (K-ε-GG antibodies) to enrich ubiquitinated peptides

  • Identify proteins with altered abundance or ubiquitination status by mass spectrometry

  • Focus on proteins that accumulate in atl58 mutants under specific conditions

• Proximity-dependent labeling:

  • Fuse ATL58 to promiscuous biotin ligases (BioID or TurboID)

  • Express fusion proteins in Arabidopsis

  • Identify biotinylated proteins by streptavidin pull-down and mass spectrometry

  • Compare results with control conditions and catalytically inactive mutants

This multi-faceted approach can identify potential substrates, which should then be validated through in vitro and in vivo ubiquitination assays .

How does ATL58 function in the context of broader signaling networks in response to environmental changes?

To position ATL58 within signaling networks:

• Transcriptome analysis:

  • Perform RNA-seq comparing wild-type and atl58 mutants under normal and stress conditions

  • Identify differentially expressed genes and enriched pathways

  • Apply gene set enrichment analysis against GO terms or custom gene sets

  • Meta-analysis approaches similar to those used for hypoxia-responsive genes could reveal ATL58's role in stress responses

• Genetic interaction studies:

  • Generate double mutants between atl58 and mutants in related pathways

  • Analyze epistatic relationships and phenotypic enhancement/suppression

  • Focus on sugar signaling components based on the role of related ATL proteins

• Phosphoproteomics and hormone analysis:

  • Compare signaling pathway activation between genotypes

  • Monitor changes in stress-related hormones (ABA, ethylene, jasmonate)

  • Integrate data into existing models of stress response networks

A systems biology approach integrating these datasets would position ATL58 within the broader context of plant stress response networks .

How do genetic variations in ATL58 contribute to natural variation in Arabidopsis ecotypes?

To explore natural variation in ATL58 function:

• Sequence analysis across ecotypes:

  • Analyze ATL58 sequence polymorphisms across the 1001 Arabidopsis genomes

  • Identify non-synonymous substitutions, particularly in functional domains

  • Associate sequence variants with geographic distribution and environmental factors

• Expression variation studies:

  • Compare ATL58 expression levels and patterns across diverse accessions

  • Relate expression differences to environmental adaptations

  • Identify potential cis-regulatory variants affecting expression

• Functional complementation:

  • Transform atl58 mutants with variants from different ecotypes

  • Compare complementation efficiency across various stress conditions

  • Identify functional consequences of natural variation

• Association studies:

  • Perform GWAS on stress tolerance traits across Arabidopsis accessions

  • Identify potential ATL58 associations with phenotypic variation

  • Validate through targeted genetic studies

This approach could reveal how ATL58 contributes to local adaptation in Arabidopsis, similar to studies of genetic variability in root system architecture .

What is the evolutionary significance of ATL58 in plant adaptation to environmental stresses?

To investigate the evolutionary significance of ATL58:

• Comparative genomics:

  • Identify ATL58 orthologs across plant species, from mosses to angiosperms

  • Compare sequence conservation, especially in functional domains

  • Analyze selection patterns (Ka/Ks ratios) to identify regions under purifying or positive selection

• Cross-species functional studies:

  • Express ATL58 orthologs from diverse species in Arabidopsis atl58 mutants

  • Test complementation of stress response phenotypes

  • Identify conserved and divergent functions

• Environmental adaptation analysis:

  • Compare ATL58 sequence and expression patterns in plants from contrasting environments

  • Correlate variations with specific environmental challenges

  • Design field experiments similar to the "synchronized-genetic-perturbation-field-experiment" approach used to study UVR8

This evolutionary perspective would provide insights into how ATL58 might have contributed to plant adaptation to diverse environmental conditions throughout evolutionary history.

What are the optimal conditions for analyzing the membrane association of ATL58?

ATL58 contains an N-terminal transmembrane-like domain suggesting membrane localization. To analyze this association:

• Microsomal fractionation protocol:

  • Homogenize plant tissue in extraction buffer (50 mM HEPES pH 7.5, 250 mM sucrose, 5% glycerol, 1 mM EDTA, protease inhibitors)

  • Filter through miracloth and centrifuge at 8,000 × g for 10 min to remove debris

  • Ultracentrifuge supernatant at 100,000 × g for 1 hour to separate microsomal (pellet) and soluble (supernatant) fractions

  • Resuspend microsomal pellet in extraction buffer + 1% detergent

  • Analyze fractions by SDS-PAGE and western blotting with anti-ATL58 antibodies

  • Include controls for membrane (e.g., H+-ATPase) and soluble (e.g., cytosolic GAPDH) proteins

• Membrane integration analysis:

  • Treat microsomes with:
    a) High salt (1M NaCl) to release peripherally associated proteins
    b) Alkaline conditions (0.1M Na2CO3, pH 11) to release non-integral proteins
    c) Detergents (1% Triton X-100) to solubilize integral membrane proteins

  • Analyze ATL58 distribution after each treatment by western blotting

  • Compare with known integral, peripheral, and soluble protein controls

This approach has successfully characterized the membrane association of other ATL family proteins .

How can synthetic biology approaches be used to engineer ATL58 with modified substrate specificity?

To engineer ATL58 with modified substrate specificity:

• Domain swapping:

  • Create chimeric proteins by swapping the C-terminal substrate recognition domain between ATL58 and other ATL family members

  • Express in atl58 mutant background

  • Assess phenotypic complementation and substrate ubiquitination

• Structure-guided mutagenesis:

  • Model the ATL58 structure using AlphaFold or similar tools

  • Identify residues likely involved in substrate recognition

  • Create libraries of point mutations in these regions

  • Screen for altered substrate specificity or novel functions

• Directed evolution:

  • Create random mutation libraries of the ATL58 substrate-binding domain

  • Develop a selection system in yeast or bacteria for desired functions

  • Perform iterative rounds of selection and amplification

  • Characterize improved variants in planta

These approaches could generate ATL58 variants with novel functions for both basic research and potential biotechnological applications.

What methodological approaches can resolve discrepancies in ATL58 functional data across different experimental systems?

Researchers often encounter discrepancies when studying proteins across different experimental systems. To resolve such issues with ATL58:

• Standardized expression systems comparison:

  • Express identical ATL58 constructs in multiple systems (E. coli, yeast, insect cells, plant cells)

  • Compare protein activity, stability, and post-translational modifications

  • Identify system-specific factors affecting function

• Controlled environmental conditions:

  • Design experiments with carefully matched growth conditions across labs

  • Include identical positive and negative controls

  • Use standardized protocols for protein purification and activity assays

• Multi-laboratory validation:

  • Implement ring trials where identical experiments are performed in different laboratories

  • Use statistical approaches to identify sources of variation

  • Develop robust protocols that produce consistent results across settings

• Data integration approaches:

  • Apply meta-analysis techniques similar to those used in the RNA-Seq studies of hypoxia responses

  • Identify consistent patterns across datasets despite methodological variations

  • Focus on high-confidence results validated across multiple systems