At5g42223 Antibody

What is the At5g42223 gene and what role does it play in Arabidopsis thaliana?

At5g42223 is a gene found in the model plant organism Arabidopsis thaliana, which is part of the autophagy-related gene family. While specific information about this particular gene is limited in the current literature, research on related autophagy genes such as ATG5 and ATG7 indicates that these genes are involved in catabolic pathways capable of degrading cellular components ranging from individual molecules to organelles. The autophagy process helps cells cope with various stresses by removing superfluous or hazardous material. Transcriptional upregulation of autophagy-related genes like ATG5 and ATG7 has been shown to positively affect important agronomic traits including biomass, seed yield, pathogen tolerance, and oxidative stress resistance . When investigating At5g42223, researchers should consider its potential role within the broader context of plant autophagy mechanisms and stress responses.

How do I validate the specificity of an At5g42223 antibody?

Validating antibody specificity is crucial for ensuring reliable experimental results. For At5g42223 antibodies, employ multiple complementary approaches:

• Western blot analysis: Use wild-type and knockout/knockdown plant lines to confirm antibody specificity. The antibody should detect a band of the expected molecular weight in wild-type samples that is absent or significantly reduced in knockout lines.

• Immunoprecipitation followed by mass spectrometry: This technique can verify that the antibody is pulling down the intended target. Similar to approaches used in interactome studies of ATG5, affinity purification coupled with LC-MS/MS can confirm specificity while potentially revealing interaction partners .

• Immunofluorescence microscopy: Compare localization patterns in wild-type versus knockout plants. Specific antibodies will show distinct subcellular localization patterns that disappear in knockout lines.

• Peptide competition assay: Pre-incubate the antibody with purified At5g42223 protein or peptide before application to samples. If specific, the signal should be blocked or significantly reduced.

• Cross-reactivity testing: Test the antibody against closely related proteins to ensure it does not recognize similar epitopes in other proteins.

These validation steps are essential to avoid experimental artifacts and data misinterpretation that could lead to contradictory results in the literature.

How should I design experiments to study At5g42223 function in plant stress responses?

When designing experiments to investigate At5g42223 function in stress responses, implement a robust experimental design that accounts for biological variability and controls for confounding factors:

• Variable identification and control: Clearly define independent variables (e.g., stress treatments, genetic backgrounds) and dependent variables (e.g., protein expression levels, phenotypic responses). Control for extraneous variables such as growth conditions, plant age, and circadian rhythms .

• Treatment design: Apply systematic manipulation of stress conditions (e.g., drought, salt, pathogen exposure) with appropriate controls. Include both short-term and long-term stress applications to distinguish between immediate responses and adaptive mechanisms.

• Null and alternative hypothesis formulation: Clearly state testable hypotheses. For example, H0: "At5g42223 expression does not change under oxidative stress" versus H1: "At5g42223 expression increases under oxidative stress" .

• Sample size determination: Ensure sufficient biological and technical replicates to achieve statistical power. Consider preliminary experiments to estimate effect size and variability.

• Time-course analysis: Include multiple time points to capture the dynamic nature of stress responses and avoid missing transient effects.

• Multiple stress conditions: Test various stressors to determine if At5g42223 functions in general stress responses or is specific to particular stresses, similar to studies done with ATG5 and ATG7 that showed specific effects on pathogen tolerance and oxidative stress resistance .

• Genetic complementation: Include rescue experiments with native At5g42223 to confirm phenotypes observed in knockout/knockdown lines.

This comprehensive approach will provide robust evidence for the functional role of At5g42223 in plant stress responses.

What are the key considerations when designing co-immunoprecipitation experiments with At5g42223 antibodies?

When designing co-immunoprecipitation (co-IP) experiments with At5g42223 antibodies to identify protein interaction partners, consider the following methodological aspects:

• Antibody quality and specificity: Ensure the antibody has been validated for IP applications. Confirm specificity through western blot analysis comparing wild-type and knockout plants.

• Crosslinking optimization: Determine whether crosslinking is necessary to capture transient interactions. If used, optimize crosslinker concentration and exposure time to prevent artifactual associations while preserving genuine interactions.

• Lysis buffer composition: The buffer should effectively solubilize membrane-associated proteins while maintaining protein-protein interactions. Test different detergent types and concentrations to optimize extraction efficiency while preserving interactions.

• Control samples: Include appropriate negative controls such as:

  • IgG control from the same species as the primary antibody

  • Lysate from At5g42223 knockout plants processed identically

  • Beads-only controls to identify non-specific binding

• Washing stringency: Optimize wash buffer composition and washing steps to remove non-specific interactions while retaining true interaction partners.

• Elution conditions: Select appropriate elution methods based on antibody binding characteristics and downstream applications.

• Confirmation methodology: Validate identified interactions through reciprocal co-IPs, yeast two-hybrid assays, or bimolecular fluorescence complementation.

• Mass spectrometry analysis: Similar to approaches used for ATG5 interactome studies , employ affinity purification coupled with LC-MS/MS to identify interaction partners comprehensively. Consider both wild-type and autophagy-inactive mutant versions to distinguish autophagy-dependent and independent interactions.

This methodological approach will provide reliable identification of At5g42223 protein interaction networks, potentially revealing both expected autophagy-related partners and novel interactions suggesting additional cellular functions.

How do I reconcile contradictory findings about At5g42223 function in the literature?

Navigating contradictory findings in antibody research requires systematic analysis of experimental context. When faced with seemingly conflicting results regarding At5g42223 function, consider the following analytical framework:

• Context-dependent analysis: Examine the five major categories of contextual characteristics that can explain apparent contradictions in biomedical literature :

  • Internal to the experimental system (e.g., cell type, tissue specificity, developmental stage)

  • External factors (e.g., growth conditions, stress treatments)

  • Endogenous/exogenous variables (e.g., protein modifications, interaction partners)

  • Known controversies in the field

  • Incomplete reporting of experimental context

• Species-specific effects: Determine if contradictions arise from differences in model systems or species used. Even within Arabidopsis, different ecotypes may show variable responses.

• Temporal context: Assess whether conflicting results stem from observations at different time points or developmental stages.

• Methodological differences: Analyze variations in experimental approaches, including:

  • Antibody sources and validation methods

  • Protein extraction protocols

  • Detection techniques

  • Data normalization procedures

• Statistical robustness: Evaluate the statistical power and appropriate application of statistical methods in conflicting studies.

• Publication bias: Consider whether negative results might be underrepresented in the literature.

• Systematic literature review: Create a structured comparison table of contradictory findings, explicitly noting all variables that might explain differences:

This systematic approach to literature analysis can transform apparent contradictions into deeper insights about context-dependent functions of At5g42223, similar to how contradictions regarding p53 expression have been resolved by identifying context-specific regulation .

What statistical approaches are most appropriate for analyzing quantitative data from At5g42223 antibody experiments?

Selecting appropriate statistical methods for antibody-based research requires careful consideration of experimental design and data characteristics:

• Exploratory data analysis:

  • Begin with descriptive statistics and visualization to assess data distribution

  • Check for normality using Shapiro-Wilk or Kolmogorov-Smirnov tests

  • Identify potential outliers and determine whether they represent biological variation or technical artifacts

• Statistical test selection:

  • For comparing two groups: t-test (parametric) or Mann-Whitney U test (non-parametric)

  • For multiple group comparisons: ANOVA followed by post-hoc tests (Tukey, Bonferroni) for parametric data or Kruskal-Wallis with post-hoc tests for non-parametric data

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

  • For correlation analysis: Pearson (linear) or Spearman (rank-based) correlation coefficients

• Multiple testing correction:

  • Apply Benjamini-Hochberg procedure to control false discovery rate in large-scale analyses

  • Consider family-wise error rate control (Bonferroni) for smaller, targeted experiments

• Sample size considerations:

  • Perform power analysis to determine adequate sample size

  • Report effect sizes alongside p-values to indicate biological significance

• Regression models for complex relationships:

  • Linear regression for continuous predictors

  • Logistic regression for binary outcomes

  • Multiple regression for controlling confounding variables

• Advanced methods for interactome data:

  • Network analysis tools to visualize and quantify protein interaction networks

  • Enrichment analysis to identify overrepresented functional categories

  • Similar to approaches used in ATG5 interactome studies , employ statistical methods that can identify significant protein-protein interactions while controlling for non-specific binding

How can I study post-translational modifications of At5g42223 protein?

Investigating post-translational modifications (PTMs) of At5g42223 requires specialized approaches that preserve modification states while enabling their detection and quantification:

• Sample preparation optimization:

  • Include phosphatase inhibitors (e.g., sodium fluoride, sodium orthovanadate) for phosphorylation studies

  • Add deacetylase inhibitors (e.g., trichostatin A, nicotinamide) when studying acetylation

  • Use protease inhibitor cocktails to prevent degradation

  • Consider rapid tissue freezing in liquid nitrogen to preserve labile PTMs

• Enrichment strategies:

  • For phosphorylation: Immobilized metal affinity chromatography (IMAC) or titanium dioxide (TiO2) enrichment

  • For ubiquitination: Tandem ubiquitin binding entities (TUBEs) or specific anti-ubiquitin antibodies

  • For acetylation: Anti-acetyllysine antibodies or acetylated protein enrichment kits

• Mass spectrometry approaches:

  • Similar to studies with ATG5 complex components , employ LC-MS/MS after affinity purification to identify PTMs

  • Use both data-dependent acquisition (DDA) and parallel reaction monitoring (PRM) for comprehensive PTM mapping

  • Apply collision-induced dissociation (CID) and electron transfer dissociation (ETD) fragmentation methods to improve PTM site localization

• Site-specific antibodies:

  • Develop or obtain antibodies that specifically recognize modified forms of At5g42223

  • Validate specificity using synthetic peptides with and without the modification

  • Compare signals in wild-type samples versus PTM site mutants

• Functional validation:

  • Generate site-specific mutants (e.g., phosphomimetic or phosphonull) to assess functional consequences

  • Perform phenotypic assays to determine effects of mutations on protein function

  • Assess interaction partner changes using co-IP experiments

• Quantitative dynamics:

  • Implement SILAC or TMT labeling to quantify changes in modification levels under different conditions

  • Perform time-course experiments to capture dynamic changes in response to stimuli

This comprehensive approach will provide insights into how PTMs regulate At5g42223 function, potentially revealing regulatory mechanisms similar to those observed for other autophagy proteins like ATG5, where phosphorylation and acetylation have been implicated in functional regulation .

What approaches can I use to study the nuclear localization and potential non-autophagy functions of At5g42223?

Investigating potential non-canonical functions of At5g42223, particularly in the nucleus, requires specialized techniques to distinguish these functions from classical autophagy roles:

• Subcellular fractionation and localization:

  • Implement differential centrifugation to isolate nuclear, cytoplasmic, and membrane fractions

  • Confirm fractionation purity using compartment-specific markers (e.g., histone H3 for nucleus, tubulin for cytosol)

  • Perform western blotting on fractions to detect At5g42223 in nuclear compartments

  • Use immunofluorescence microscopy with co-staining for nuclear markers to visualize localization

• Nuclear function analysis:

  • Similar to studies with ATG5 and ATG12 , examine potential interactions with nuclear proteins

  • Perform chromatin immunoprecipitation (ChIP) to assess potential DNA binding

  • Investigate interactions with transcription factors or chromatin remodeling complexes

  • Analyze transcriptome changes in knockout/knockdown lines to identify regulated genes

• Domain mapping and mutational analysis:

  • Generate domain deletion mutants to identify regions required for nuclear localization

  • Create nuclear localization signal (NLS) or nuclear export signal (NES) mutants

  • Develop constructs expressing only specific domains to determine their independent functions

• Interactome analysis:

  • Perform nuclear-specific interactome studies using proximity labeling techniques like BioID or TurboID

  • Compare interactome data from autophagy-deficient mutants versus wild-type to distinguish autophagy-dependent and independent interactions

  • Validate key interactions through reciprocal co-IPs and functional assays

• Temporal regulation:

  • Investigate cell cycle-dependent localization changes

  • Study localization dynamics under different stress conditions

  • Perform time-lapse imaging with fluorescently tagged proteins

• Functional consequences:

  • Develop nucleus-restricted or cytoplasm-restricted versions of the protein

  • Assess phenotypic consequences of altered localization

  • Measure impact on gene expression, DNA damage responses, and other nuclear processes

This approach will help determine whether At5g42223, like ATG5 and other autophagy proteins, has functions beyond canonical autophagy pathways , potentially revealing novel roles in nuclear processes such as transcriptional regulation or chromatin organization.

What are the optimal fixation and permeabilization conditions for immunofluorescence studies with At5g42223 antibodies?

Optimizing fixation and permeabilization for immunofluorescence with At5g42223 antibodies requires balancing epitope preservation with cellular access:

• Fixation method selection:

  • Paraformaldehyde (PFA) fixation (3-4%): Preserves protein structure while maintaining cellular architecture

  • Methanol fixation: May better expose some epitopes but can disrupt membrane structures

  • Glyoxal fixation: Consider as an alternative that may preserve certain epitopes better than PFA

  • Compare multiple fixation methods side-by-side to determine optimal epitope preservation for your specific antibody

• Fixation optimization:

  • Duration: Test different fixation times (10-30 minutes for PFA)

  • Temperature: Compare room temperature versus 4°C fixation

  • Buffer composition: PBS versus specialized fixation buffers

  • pH: Optimize pH based on the specific antibody requirements

• Permeabilization strategies:

  • Detergent selection: Compare Triton X-100 (0.1-0.5%), Tween-20 (0.05-0.2%), and saponin (0.1-0.5%)

  • Duration: Test different permeabilization times (5-30 minutes)

  • Sequential approach: Consider separate versus combined fixation/permeabilization steps

• Antigen retrieval:

  • Heat-induced epitope retrieval: Test buffer composition (citrate, EDTA) and heating methods

  • Enzymatic retrieval: Consider protease-based methods if heat retrieval is ineffective

  • pH variation: Compare acidic versus basic retrieval buffers

• Blocking optimization:

  • Blocking agent: Test BSA, normal serum, commercial blocking solutions

  • Duration: Optimize blocking time (30 minutes to overnight)

  • Temperature: Compare room temperature versus 4°C blocking

• Systematic optimization workflow:

  • Begin with manufacturer's recommended protocol if available

  • Test each variable independently while keeping others constant

  • Perform sequential optimization of the most critical parameters

  • Document all optimization steps and quantify signal-to-noise ratios

• Validation controls:

  • Include knockout/knockdown samples as negative controls

  • Use known localization patterns of related proteins (like ATG5) as reference points

  • Perform peptide competition assays to confirm specificity

This methodical approach to fixation and permeabilization optimization will maximize the specificity and sensitivity of At5g42223 detection in immunofluorescence applications.

How can I optimize western blot protocols for detecting low-abundance At5g42223 protein in plant tissues?

Detecting low-abundance proteins like At5g42223 in plant tissues requires specialized western blot optimization:

• Sample preparation enhancement:

  • Implement tissue-specific extraction buffers optimized for Arabidopsis

  • Add protease inhibitor cocktails to prevent degradation

  • Consider protein concentration methods (TCA precipitation, acetone precipitation)

  • Optimize sample-to-buffer ratios to maximize protein concentration

  • Remove interfering compounds using specialized plant protein extraction kits

• Protein loading optimization:

  • Increase protein loading (50-100 µg) while monitoring for lane distortion

  • Use gradient gels to improve resolution of closely migrating species

  • Optimize gel percentage based on At5g42223's molecular weight

  • Consider longer running times at lower voltage for better resolution

• Transfer optimization:

  • Test different membrane types (PVDF, nitrocellulose) and pore sizes

  • Optimize transfer conditions (wet transfer vs. semi-dry)

  • Consider longer transfer times at lower voltage

  • Use transfer enhancers for high molecular weight proteins

  • Monitor transfer efficiency with reversible staining (Ponceau S)

• Signal enhancement strategies:

  • Employ enhanced chemiluminescence (ECL) substrates designed for high sensitivity

  • Consider amplification systems like tyramide signal amplification

  • Use high-affinity primary antibodies and optimize concentration

  • Test different secondary antibody systems (conventional vs. polymer-based)

  • Optimize antibody incubation conditions (time, temperature, buffer composition)

• Background reduction:

  • Increase blocking stringency (time, blocker concentration)

  • Test different blocking agents (milk, BSA, commercial blockers)

  • Add detergents (Tween-20, Triton X-100) to wash buffers

  • Increase washing frequency and duration

  • Pre-absorb antibodies with plant extracts from knockout lines

• Detection optimization:

  • Use digital imaging systems with high sensitivity settings

  • Implement longer exposure times while monitoring background

  • Consider fluorescent secondary antibodies for quantitative analysis

  • Use cumulative exposure approaches for very low signals

• Enrichment approaches:

  • Consider immunoprecipitation before western blotting

  • Use subcellular fractionation to concentrate the protein from relevant compartments

This systematic optimization approach will maximize the likelihood of detecting low-abundance At5g42223 protein while maintaining specificity and quantitative accuracy.

What are the most common pitfalls in At5g42223 antibody-based experiments and how can I avoid them?

Anticipating and preventing common pitfalls in antibody-based experiments is crucial for reliable results:

• Non-specific binding:

  • Problem: Secondary bands or diffuse signal in western blots

  • Solution: Validate antibody specificity using knockout controls, increase blocking stringency, optimize antibody concentration, consider alternative antibodies targeting different epitopes

• Variable reproducibility:

  • Problem: Inconsistent results between experiments

  • Solution: Standardize protocols with detailed SOPs, use consistent protein extraction methods, implement positive controls in each experiment, consider using loading normalization for quantitative comparisons

• Epitope masking:

  • Problem: Reduced or absent signal due to protein modifications or interactions

  • Solution: Test multiple antibodies targeting different epitopes, optimize sample preparation to preserve native protein state, consider denaturing conditions for western blots

• Cross-reactivity with related proteins:

  • Problem: False positive signals from proteins with similar epitopes

  • Solution: Perform peptide competition assays, validate with knockout/knockdown controls, use immunoprecipitation followed by mass spectrometry to confirm identity of detected proteins

• Batch-to-batch antibody variation:

  • Problem: Different results with new antibody lots

  • Solution: Request lot-specific validation data from suppliers, maintain reference samples for comparison, validate each new lot against previous standards

• Inappropriate controls:

  • Problem: Inability to interpret results due to inadequate controls

  • Solution: Always include positive and negative controls, use isotype controls for immunoprecipitation, include loading controls for western blots, implement knockout/knockdown lines as specificity controls

• Tissue-specific expression variations:

  • Problem: Inconsistent detection across different plant tissues

  • Solution: Optimize extraction protocols for each tissue type, adjust protein loading based on expected expression levels, consider enrichment steps for tissues with low expression

• Post-translational modification interference:

  • Problem: Antibody recognition affected by protein modifications

  • Solution: Use phosphatase treatment before western blotting if phosphorylation affects recognition, employ antibodies specific to modified forms if studying PTMs, consider multiple antibodies targeting different regions

This comprehensive troubleshooting guide addresses the most common experimental challenges encountered when working with plant antibodies, particularly for potentially low-abundance proteins like At5g42223.

How can I determine if apparent contradictions in At5g42223 localization studies are due to technical artifacts or biological variability?

Resolving localization discrepancies requires systematic investigation of both technical and biological factors:

• Technical artifact assessment:

  • Compare fixation and permeabilization methods across studies

  • Evaluate antibody specificity through appropriate controls

  • Assess microscopy settings (exposure, gain, threshold) for potential bias

  • Review image processing methods for artificial enhancement or suppression

• Antibody validation framework:

  • Test multiple antibodies targeting different epitopes

  • Perform peptide competition assays to confirm specificity

  • Use fluorescent protein fusions as independent validation

  • Compare immunofluorescence with subcellular fractionation results

• Context-dependent localization analysis:

  • Similar to approaches used to resolve contradictions in biomedical literature , systematically evaluate:

    • Cell/tissue type differences

    • Developmental stage variations

    • Stress condition effects

    • Circadian or diurnal timing

• Quantitative evaluation:

  • Implement quantitative image analysis rather than relying on representative images

  • Score localization patterns across multiple cells and biological replicates

  • Report localization as distributions rather than binary classifications

  • Use statistical approaches to determine significance of localization changes

• Dynamic localization investigation:

  • Perform time-course experiments to capture transient localization changes

  • Use live-cell imaging with fluorescent protein fusions to monitor real-time dynamics

  • Implement photo-convertible or photo-activatable tags to track protein movement

• Controlled variation studies:

  • Systematically alter conditions to determine factors affecting localization

  • Test effects of specific stressors, hormones, or developmental cues

  • Examine shuttle mechanism by inhibiting nuclear import/export

• Biological replication framework:

  • Use multiple plant lines and ecotypes

  • Test localization across different growth conditions

  • Implement biological and technical replicates with appropriate statistical analysis

This systematic approach will help distinguish genuine biological variability in At5g42223 localization from technical artifacts, similar to how apparent contradictions regarding protein expression in different contexts have been resolved in previous studies .

What emerging techniques might advance our understanding of At5g42223 function beyond current methodological limitations?

Several cutting-edge approaches show promise for overcoming current limitations in studying At5g42223:

• Advanced imaging technologies:

  • Super-resolution microscopy (PALM, STORM, SIM) to visualize protein localization beyond the diffraction limit

  • Lattice light-sheet microscopy for long-term live imaging with minimal phototoxicity

  • Correlative light and electron microscopy (CLEM) to connect protein localization with ultrastructural context

  • Expansion microscopy to physically enlarge samples for improved resolution

• Proximity labeling innovations:

  • TurboID and miniTurbo for rapid biotin labeling of proximal proteins

  • Split-TurboID for detecting protein-protein interactions in specific compartments

  • Organelle-targeted proximity labeling to map subcellular interactomes

  • Temporal control of proximity labeling to capture dynamic interactions

• CRISPR-based approaches:

  • CRISPR activation/inhibition for precise manipulation of At5g42223 expression

  • Base editing for introducing specific mutations without double-strand breaks

  • Prime editing for precise genetic modifications

  • CRISPR-mediated tagging at endogenous loci for physiological expression levels

• Single-cell technologies:

  • Single-cell proteomics to examine cell-type-specific expression

  • Single-cell transcriptomics to identify genes co-regulated with At5g42223

  • Spatial transcriptomics to map expression patterns across tissues

  • Single-molecule imaging to track individual protein molecules

• Structural biology advances:

  • Cryo-electron microscopy for high-resolution protein structure determination

  • AlphaFold2 and other AI prediction tools for structural modeling

  • Hydrogen-deuterium exchange mass spectrometry to map protein dynamics and interactions

  • Integrative structural biology combining multiple data types

• Systems biology approaches:

  • Multi-omics integration to connect At5g42223 function to broader cellular networks

  • Network analysis to predict functional relationships based on correlation patterns

  • Machine learning applications for predicting protein function and interactions

  • Mathematical modeling of autophagy dynamics incorporating At5g42223

These emerging techniques promise to advance our understanding of At5g42223 beyond current limitations, potentially revealing unexpected functions similar to those discovered for ATG5, which has been found to have roles beyond canonical autophagy, including potential nuclear functions and interactions with proteins involved in diverse cellular processes .

How can researchers design experiments to distinguish between autophagy-dependent and autophagy-independent functions of At5g42223?

Distinguishing between canonical autophagy roles and potential alternative functions of At5g42223 requires targeted experimental design:

• Mutational strategy implementation:

  • Similar to approaches used with ATG5 , generate autophagy-inactive mutations that maintain protein-protein interactions

  • Create domain-specific mutants to disrupt particular functions while preserving others

  • Develop separation-of-function mutants through targeted mutagenesis of key residues

• Complementation experimental design:

  • Compare phenotypic rescue with wild-type versus autophagy-inactive mutants

  • Implement domain-specific complementation to map function to protein regions

  • Use tissue-specific or inducible expression to temporally and spatially control complementation

• Comparative interactome analysis:

  • Compare protein interaction networks between wild-type and autophagy-deficient mutants

  • Identify interactors that associate regardless of autophagy functionality

  • Validate key differential interactors through targeted biochemical approaches

• Subcellular compartment-specific studies:

  • Implement compartment-targeted versions of At5g42223

  • Assess function when restricted to specific cellular locations

  • Compare phenotypes with autophagy mutants affected at different steps

• Temporal dissection approaches:

  • Use rapid inducible degradation systems (AID, dTAG) to distinguish immediate versus long-term effects

  • Implement time-course studies to separate primary from secondary consequences

  • Develop systems for acute versus chronic protein depletion

• Genetic interaction network mapping:

  • Perform epistasis analysis with canonical autophagy genes

  • Screen for genetic interactions with non-autophagy pathways

  • Implement quantitative genetic interaction mapping to identify pathway connections

• Systematic comparison table:

  • Create a structured comparison of phenotypes between autophagy-deficient mutants:

This experimental framework will enable researchers to systematically dissect the functions of At5g42223, determining which phenotypes depend on its role in canonical autophagy versus potential alternative functions, similar to how ATG5 has been shown to have autophagy-independent roles in various cellular processes .