ATL13 Antibody

What cellular processes does ATL3 participate in, and why is studying it important?

ATL3 functions primarily as an ER-localized transmembrane protein involved in endoplasmic reticulum membrane dynamics. Recent research has demonstrated that ATL3, along with ATL2, contributes significantly to autophagosome formation by recruiting and stabilizing the ULK1 complex at autophagosome formation sites on the ER . ATL3 also participates in ER-isolation membrane (IM) contact formation during autophagosome expansion . Additionally, ATL3 has been implicated as a putative receptor promoting degradation of tubular ER through interaction with ATG8 family autophagy proteins . Studying ATL3 is particularly important for understanding fundamental cellular processes like autophagy regulation, ER morphology maintenance, and the pathophysiology of neurodegenerative diseases associated with ER dysfunction.

What experimental models are suitable for ATL3 antibody applications?

Based on validated reactivity, ATL3 antibodies have been successfully employed in human, mouse, and rat experimental models . Specifically, the antibody has shown positive detection in various cell lines including HEK-293T, HEK-293, HeLa, HepG2, SMMC-7721, Jurkat, and NIH/3T3 cells, as well as in mouse and rat liver tissues . For tissue-based experiments, successful immunohistochemistry has been reported in human stomach cancer tissue, suggesting its utility in clinical samples as well . When designing experiments with new cell lines or tissues not listed in validation data, preliminary testing with appropriate positive controls is strongly recommended.

What are the recommended starting dilutions for different experimental applications?

For Western Blot applications, the recommended dilution range is 1:2000-1:12000, indicating high sensitivity that allows for conservative use of the antibody . For Immunoprecipitation, use 0.5-4.0 μg of antibody for 1.0-3.0 mg of total protein lysate . Immunohistochemistry applications should start with dilutions between 1:50-1:500, while Immunofluorescence/ICC applications similarly work well in the 1:50-1:500 range . It is crucial to note that these are starting recommendations, and optimization for your specific experimental system is essential for obtaining reliable results.

How can I optimize ATL3 antibody performance in ULK1 complex co-localization studies?

Co-localization studies examining ATL3's interaction with the ULK1 complex require careful experimental design. Research has shown that ATL2/3 depletion affects ULK1 and ATG101 recruitment to FIP200-ATG13-specified autophagosome formation sites . When designing co-localization experiments:

• Use dual immunofluorescence staining with ATL3 antibody (dilution 1:50-1:500) alongside antibodies against ULK1 complex components (FIP200, ULK1, ATG13, and ATG101) .

• Include starvation conditions (such as EBSS medium) to induce autophagy, as this enhances the visualization of autophagosome formation sites.

• Incorporate appropriate controls, including ATL3 knockout or knockdown cells, to validate specificity.

• Consider using super-resolution microscopy techniques for more precise co-localization assessment, as conventional confocal microscopy may not resolve the fine details of ER structures.

• Analyze the percentage of ATL3-positive structures that co-localize with ULK1 complex components before and after autophagy induction to quantitatively assess recruitment dynamics.

What methodological approaches can resolve contradictory results when studying ATL3's role in autophagy?

Contradictory results in ATL3 autophagy studies often arise from differences in experimental conditions or cell types. To address these contradictions:

• Compare autophagy markers comprehensively: Assess multiple markers beyond LC3 conversion, including p62 degradation and autophagosome formation by EM analysis, as demonstrated in studies of ATL2/3 DKO cells .

• Implement rescue experiments: Reintroduce ATL3 expression in knockout models to confirm phenotype reversal, which helps establish causality rather than correlation .

• Utilize pharmacological modulators: Apply autophagy inducers (rapamycin) and inhibitors (bafilomycin A1) to distinguish between defects in autophagosome formation versus degradation .

• Examine autophagy flux: Rather than static measurements, implement flux assays that track the dynamic progression of autophagy under basal and induced conditions.

• Control for ER morphology changes: Since ATL3 affects ER structure, independently assess whether observed autophagy defects are direct or secondary to altered ER morphology .

How should I interpret differences in ATL3 antibody binding patterns between different subcellular fractions?

Interpreting subcellular fraction differences requires understanding ATL3's structural organization:

• Consider protein topology: ATL3 is a transmembrane protein with distinct domains (a cytosolic GTPase domain, a middle domain, and transmembrane segments) . Antibodies targeting different epitopes may yield varying results in subcellular fractions.

• Validate with fractionation controls: Always include markers for different subcellular compartments (e.g., calnexin for ER, GAPDH for cytosol).

• Account for detergent effects: The choice of detergent in lysis buffers can significantly affect transmembrane protein solubilization and epitope accessibility.

• Compare native versus denatured conditions: Some epitopes may only be accessible in denatured conditions (Western blotting) but not in native conditions (IP).

• Consider post-translational modifications: ATL3 function may be regulated by modifications that alter antibody recognition in different cellular compartments.

What controls are essential when using ATL3 antibody in knockout/knockdown validation studies?

For rigorous knockout/knockdown validation:

• Include positive control samples: Always run wild-type or parental cell line samples alongside your KO/KD samples.

• Implement loading controls: Use housekeeping proteins of similar molecular weight ranges but distinct from your target.

• Consider multiple detection methods: Validate ATL3 depletion using both Western blotting (1:2000-1:12000 dilution) and immunofluorescence (1:50-1:500 dilution) .

• Assess functional outcomes: Beyond protein depletion, examine functional consequences such as altered LC3-II/LC3-I ratios or p62 accumulation .

• Validate with multiple antibody clones: If available, use antibodies targeting different epitopes to confirm complete protein elimination.

• Include rescue experiments: Reintroduce ATL3 expression to restore normal phenotype, confirming specificity of observed effects.

• Sequence verification: Confirm genomic alterations in CRISPR-generated knockouts through sequencing.

What are the methodological considerations for studying ATL3's interactions with the ULK1 complex components?

When investigating ATL3-ULK1 complex interactions:

• Optimize immunoprecipitation conditions: Use 0.5-4.0 μg antibody for 1.0-3.0 mg total protein lysate with gentle lysis conditions to preserve protein complexes .

• Consider crosslinking approaches: For transient interactions, implement chemical crosslinking before cell lysis.

• Perform reciprocal co-immunoprecipitations: Pull down with ATL3 antibody and probe for ULK1 complex components, then reverse the approach.

• Include appropriate negative controls: Use IgG controls and samples from ATL3 knockout cells to establish specificity.

• Assess interaction dynamics: Compare interactions under basal, starvation-induced, and rapamycin-treated conditions to understand regulatory mechanisms .

• Consider proximity labeling methods: For weak or transient interactions, techniques like BioID or APEX2 may provide additional insights.

• Address subcellular context: Fractionate cells to enrich for ER membranes where these interactions occur physiologically.

How can I differentiate between ATL3's direct role in autophagy versus indirect effects through ER morphology changes?

Distinguishing direct versus indirect effects requires:

• Generate separation-of-function mutants: Identify and use ATL3 mutants that maintain ER structure but lose autophagy-related functions.

• Implement acute protein depletion: Use techniques like auxin-inducible degron systems for rapid ATL3 depletion before significant ER morphology changes occur.

• Conduct temporal analyses: Monitor the sequence of events following ATL3 depletion to determine whether autophagy defects precede or follow ER structural changes.

• Utilize domain-specific constructs: Express individual domains of ATL3 to identify which specifically interact with autophagy machinery.

• Perform domain-swapping experiments: Replace ATL3 domains with those from other atlastins to identify autophagy-specific regions.

• Compare with other ER morphology modulators: Contrast ATL3 depletion effects with other manipulations that alter ER structure through different mechanisms.

• Assess direct binding: Use purified proteins in binding assays to establish direct interactions between ATL3 and autophagy components.

How should researchers interpret varied ATL3 expression patterns across different tissue types?

Interpreting tissue-specific expression patterns requires:

• Normalize to appropriate controls: Different tissues have varying protein expression levels and may require tissue-specific loading controls.

• Consider alternative splicing: ATL3 may have tissue-specific isoforms that affect antibody recognition or function.

• Account for cell-type heterogeneity: In complex tissues, ATL3 may be expressed in specific cell populations, diluting the signal in whole-tissue lysates.

• Compare multiple detection methods: Validate expression patterns using immunohistochemistry (recommended dilution 1:50-1:500) in addition to Western blotting .

• Reference tissue expression databases: Cross-reference findings with publicly available transcriptomic and proteomic databases.

• Examine functional context: Assess whether expression differences correlate with tissue-specific autophagy rates or ER morphology variations.

• Consider developmental stage: ATL3 expression may vary during development or aging, necessitating age-matched samples.

What approaches help resolve discrepancies between protein levels detected by Western blot versus immunofluorescence?

To address technique-dependent discrepancies:

• Optimize fixation methods: Test multiple fixation protocols as they can dramatically affect epitope accessibility in immunofluorescence.

• Validate antibody specificity in both applications: Confirm specificity using knockout controls in both Western blotting and immunofluorescence.

• Consider protein localization: Concentrated proteins in specific compartments may appear prominent in immunofluorescence despite modest total levels.

• Assess detergent effects: Different detergents in immunofluorescence protocols may affect membrane protein detection.

• Implement quantitative immunofluorescence: Use calibration standards to quantify fluorescence signals for comparison with Western blot densitometry.

• Account for sample preparation differences: Denaturation in Western blotting versus native conditions in immunofluorescence can affect epitope accessibility.

• Control for autofluorescence: Tissue autofluorescence can confound immunofluorescence results, particularly in certain cell types or after certain treatments.

How can researchers accurately interpret ATL3 knockout phenotypes in the context of compensatory mechanisms?

For accurate interpretation of knockout phenotypes:

• Assess related protein expression: Measure levels of other atlastin family members (particularly ATL1 and ATL2) that might compensate for ATL3 loss .

• Implement acute depletion approaches: Compare phenotypes from acute depletion (siRNA) versus stable knockout to identify compensatory adaptations.

• Analyze temporal dynamics: Examine phenotypes at various time points after ATL3 depletion to capture evolving compensatory responses.

• Consider genetic background effects: The same knockout may produce different phenotypes in different cell lines due to varied compensatory capacities.

• Implement double or triple knockouts: Research has shown that ATL2/3 double knockout produces more dramatic phenotypes than single knockouts, suggesting functional redundancy .

• Perform transcriptomic and proteomic profiling: Identify upregulated genes/proteins that might compensate for ATL3 loss.

• Validate in multiple models: Compare knockout effects across different cell types and organisms to distinguish universal versus context-specific responses.

What methodological approaches can elucidate ATL3's role in forming ER-isolation membrane contact sites during autophagosome formation?

To investigate ATL3's role in ER-isolation membrane contacts:

• Implement correlative light-electron microscopy (CLEM): Combine fluorescence microscopy of tagged ATL3 with EM to visualize its localization at ER-isolation membrane contact sites.

• Utilize proximity labeling techniques: Apply BioID or APEX2 fused to ATL3 to identify proteins in close proximity at contact sites.

• Perform time-lapse imaging: Use live-cell imaging with fluorescently tagged ATL3 and autophagy markers to track dynamic interactions during autophagosome formation.

• Apply super-resolution microscopy: Techniques like STORM or PALM can resolve the precise localization of ATL3 at contact sites beyond the diffraction limit.

• Implement in vitro reconstitution: Reconstitute membrane contact sites using purified components to establish minimum requirements for ATL3-mediated tethering.

• Utilize split-fluorescent protein approaches: Apply techniques like split-GFP to visualize ATL3-mediated contact sites in living cells.

• Perform domain mapping experiments: Identify which ATL3 domains are essential for contact site formation using truncation or point mutation constructs.

How can researchers design experiments to distinguish between ATL3's roles in general autophagy versus selective ERphagy?

To differentiate between general autophagy and ERphagy roles:

• Monitor selective cargo degradation: Compare degradation rates of ER proteins versus non-ER autophagy substrates in ATL3-depleted cells.

• Assess ATL3 interaction with selective autophagy receptors: Analyze ATL3 binding to known ERphagy receptors versus core autophagy machinery .

• Utilize ER stress inducers: Apply agents like tunicamycin to specifically induce ERphagy and assess ATL3 involvement under these conditions.

• Implement cargo-specific autophagy assays: Use specialized reporters for different autophagy pathways to determine which are most affected by ATL3 manipulation.

• Perform structure-function analyses: Identify ATL3 domains specifically required for ERphagy versus general autophagy through mutational approaches.

• Analyze ATL3 dynamics during different autophagy types: Compare ATL3 recruitment patterns during starvation-induced autophagy versus ER stress-induced ERphagy.

• Consider double knockout approaches: Compare ATL3 knockout with dual ATL3/known ERphagy receptor knockouts to identify epistatic relationships.

What experimental strategies can reveal the mechanistic differences between ATL2 and ATL3 in autophagy regulation?

To distinguish ATL2 versus ATL3 functions:

• Perform individual versus combined knockouts: Compare phenotypes of ATL2 KO, ATL3 KO, and ATL2/3 DKO cells to identify unique and redundant functions .

• Conduct cross-complementation experiments: Test whether ATL2 expression can rescue ATL3 KO phenotypes and vice versa.

• Analyze binding partner differences: Compare interactomes of ATL2 and ATL3 to identify unique interaction partners that might explain functional differences.

• Examine tissue-specific expression patterns: Analyze whether differential expression across tissues correlates with functional specialization.

• Perform domain-swapping experiments: Create chimeric proteins containing domains from both ATL2 and ATL3 to map function-specific regions.

• Investigate post-translational modification differences: Determine whether ATL2 and ATL3 are differently regulated by phosphorylation, ubiquitination, or other modifications.

• Assess subcellular localization patterns: Examine whether ATL2 and ATL3 localize to different ER subdomains, potentially explaining functional divergence.