ATL72 Antibody

What is ATL72 and why is it important in plant research?

ATL72 refers to a protein in Arabidopsis thaliana, a widely used model organism in plant biology. As with many ATL family proteins, it likely functions as an E3 ubiquitin ligase involved in protein degradation pathways and cellular regulation mechanisms. Understanding ATL72's function can provide insights into plant development, stress responses, and cellular signaling pathways. The antibody against ATL72 allows researchers to detect, quantify, and study the expression patterns of this protein across different experimental conditions .

What are the key specifications of the commercially available ATL72 antibody?

The ATL72 antibody is available as a polyclonal antibody raised in rabbits against recombinant Arabidopsis thaliana ATL72 protein. It is typically supplied in liquid form with a storage buffer containing 50% glycerol, 0.01M PBS (pH 7.4), and 0.03% Proclin 300 as a preservative. The antibody is purified using antigen affinity methods and is classified as an IgG isotype. It is specifically designed to react with Arabidopsis thaliana and has been validated for ELISA and Western Blot applications . The antibody should be stored at -20°C or -80°C to maintain its stability and functionality.

How does ATL72 antibody compare to other plant protein antibodies in terms of specificity?

While specific comparative data for ATL72 antibody versus other plant protein antibodies is limited in the provided research, general antibody principles apply. Polyclonal antibodies like the ATL72 antibody typically recognize multiple epitopes on the target protein, which can provide robust detection signals but might introduce potential cross-reactivity with structurally similar proteins. For optimal specificity, researchers should validate the antibody in their specific experimental system before proceeding with full-scale experiments. This validation is particularly important for plant protein antibodies where evolutionary conservation of protein domains may lead to cross-reactivity with related proteins .

What is the optimal protocol for using ATL72 antibody in Western Blot applications?

For Western Blot applications using ATL72 antibody, researchers should follow this general methodology with appropriate optimizations:

• Sample preparation: Extract total protein from Arabidopsis tissues using standard extraction buffers containing protease inhibitors.

• Protein separation: Separate proteins using SDS-PAGE (10-12% gel recommended for mid-sized proteins).

• Transfer: Transfer proteins to a PVDF or nitrocellulose membrane (0.45 μm pore size).

• Blocking: Block the membrane with 5% non-fat milk or BSA in TBST for 1 hour at room temperature.

• Primary antibody incubation: Dilute ATL72 antibody (starting dilution 1:1000, optimize as needed) in blocking buffer and incubate overnight at 4°C.

• Washing: Wash the membrane 3-5 times with TBST, 5 minutes each.

• Secondary antibody: Incubate with an appropriate anti-rabbit secondary antibody (conjugated to HRP or fluorescent tag) for 1 hour at room temperature .

• Detection: Develop using chemiluminescence or fluorescence detection methods appropriate for your secondary antibody.

Researchers should optimize antibody concentration, incubation times, and detection methods based on their specific experimental setup.

How should researchers prepare samples for optimal ATL72 detection in plant tissues?

For optimal detection of ATL72 in plant tissues, sample preparation is crucial:

• Harvest fresh plant tissue and immediately flash-freeze in liquid nitrogen to prevent protein degradation.

• Grind tissue to a fine powder in liquid nitrogen using a mortar and pestle.

• Extract proteins using a buffer containing: 50 mM Tris-HCl (pH 7.5), 150 mM NaCl, 1% Triton X-100, 0.5% sodium deoxycholate, and freshly added protease inhibitor cocktail.

• For membrane-associated proteins like ATL72 (as many E3 ligases are membrane-associated), consider using specialized extraction buffers with appropriate detergents.

• Clarify the extract by centrifugation (14,000 × g for 15 minutes at 4°C).

• Quantify protein concentration using Bradford or BCA assay to ensure equal loading.

• Add Laemmli buffer and heat samples at 95°C for 5 minutes before loading onto gels .

This method preserves protein integrity while maximizing extraction efficiency for membrane-associated proteins like ATL72.

What controls should be included when using ATL72 antibody in experimental procedures?

Including appropriate controls is essential for reliable results with ATL72 antibody:

• Positive control: Include a sample known to express ATL72, such as specific Arabidopsis tissues where the protein is highly expressed.

• Negative control: Use tissue from ATL72 knockout/knockdown plants if available.

• Loading control: Probe for housekeeping proteins (e.g., Actin, GAPDH, or Tubulin) to ensure equal loading across samples.

• Primary antibody control: Omit the primary antibody in one lane/sample to identify non-specific binding of the secondary antibody.

• Peptide competition assay: Pre-incubate the antibody with excess purified ATL72 peptide to demonstrate specificity.

• Cross-reactivity control: If studying related species, include samples from distantly related plants to assess potential cross-reactivity .

These controls help validate antibody specificity and ensure experimental rigor when working with ATL72 antibody.

What validation methods should researchers employ to confirm ATL72 antibody specificity?

To validate ATL72 antibody specificity, researchers should employ multiple complementary approaches:

• Western blot analysis: Confirm a single band of expected molecular weight (or explained additional bands).

• Genetic knockout/knockdown validation: Compare wild-type and ATL72-deficient plant samples to confirm absence/reduction of signal.

• Mass spectrometry validation: Immunoprecipitate with ATL72 antibody and confirm protein identity via mass spectrometry.

• Immunofluorescence with competing peptide: Perform parallel immunostaining with and without pre-incubation with antigenic peptide.

• Orthogonal detection methods: Compare results from different detection methods (e.g., qPCR for mRNA levels vs. protein detection).

• Cross-reactivity testing: Test antibody against related ATL family proteins or heterologously expressed ATL72 protein .

These validation steps provide complementary evidence for antibody specificity and should be reported in research publications.

What are common issues encountered with ATL72 antibody and how can they be resolved?

Common issues with ATL72 antibody may include:

• Weak or no signal:

  • Increase antibody concentration

  • Extend incubation time

  • Optimize extraction buffer to better solubilize the protein

  • Use more sensitive detection methods

• Multiple bands/high background:

  • Increase blocking stringency (5% BSA instead of milk)

  • Reduce primary antibody concentration

  • Increase washing duration and frequency

  • Add 0.1-0.5% Tween-20 to antibody dilution buffer

  • Filter antibody solution before use

• Inconsistent results:

  • Standardize protein extraction procedure

  • Prepare fresh working solutions

  • Control for plant growth conditions and developmental stage

  • Carefully track antibody freeze-thaw cycles

  • Aliquot antibody to avoid repeated freeze-thaw cycles

These troubleshooting approaches address most common issues encountered with polyclonal antibodies like ATL72 antibody.

How should researchers assess batch-to-batch variability when using ATL72 antibody?

Batch-to-batch variability is a common concern with polyclonal antibodies. Researchers should:

• Maintain reference samples: Keep aliquots of previously validated plant samples to test new antibody batches.

• Perform parallel testing: Run samples with both old and new antibody batches side by side.

• Quantitative comparison: Use densitometry to compare signal intensities between batches.

• Documentation: Record lot numbers, dilutions, and performance characteristics of each batch.

• Standardized validation: Apply the same validation procedures to each new batch.

• Supplier communication: Request validation data from suppliers when purchasing new batches.

• Internal controls: Include consistent positive and negative controls with each experiment .

These practices help maintain experimental consistency despite potential batch-to-batch variations in antibody performance.

How can ATL72 antibody be used in co-immunoprecipitation studies to identify interaction partners?

For co-immunoprecipitation (Co-IP) studies with ATL72 antibody:

• Sample preparation:

  • Extract proteins under native conditions using gentle lysis buffers (50 mM Tris-HCl pH 7.5, 150 mM NaCl, 0.5% NP-40, protease inhibitors)

  • Maintain sample at 4°C throughout to preserve protein interactions

• Pre-clearing:

  • Incubate lysate with Protein A/G beads to remove proteins that bind non-specifically

• Immunoprecipitation:

  • Incubate pre-cleared lysate with ATL72 antibody (2-5 μg per mg of total protein)

  • Add Protein A/G beads and incubate overnight at 4°C with gentle rotation

  • Wash beads 4-5 times with wash buffer containing reduced detergent

• Analysis:

  • Elute bound proteins by boiling in SDS sample buffer

  • Analyze by SDS-PAGE followed by western blotting or mass spectrometry

  • Use IgG control to identify non-specific binding

• Confirmation:

  • Validate interactions using reciprocal Co-IP with antibodies against identified partners

  • Consider complementary approaches like yeast two-hybrid or BiFC to validate interactions

This approach can identify proteins that interact with ATL72, providing insights into its functional networks and regulatory mechanisms.

What considerations are necessary for developing an ATL72 antibody-based immunohistochemistry protocol?

For immunohistochemistry (IHC) with ATL72 antibody in plant tissues:

• Tissue preparation:

  • Fix plant tissues in 4% paraformaldehyde in PBS

  • Embed in paraffin or prepare frozen sections (8-10 μm thickness)

  • For paraffin sections, perform antigen retrieval using citrate buffer (pH 6.0)

• Permeabilization:

  • Treat sections with 0.1% Triton X-100 to allow antibody penetration

  • For cell wall digestion, consider treating with cell wall degrading enzymes

• Blocking:

  • Block with 3-5% BSA or normal serum from the species of secondary antibody

• Antibody incubation:

  • Dilute ATL72 antibody (starting at 1:100, optimize as needed)

  • Incubate overnight at 4°C in a humid chamber

  • Include negative controls (no primary antibody, pre-immune serum)

• Detection:

  • Use fluorescent or enzyme-conjugated secondary antibodies appropriate for rabbit IgG

  • For co-localization studies, use secondary antibodies with distinct fluorophores

  • Consider antifade mounting media to reduce photobleaching

• Validation:

  • Compare results with ATL72 expression patterns determined by other methods

  • Include wild-type and ATL72 mutant tissues for comparison

These considerations help develop robust IHC protocols for visualizing ATL72 distribution in plant tissues.

How can researchers adapt ATL72 antibody for high-throughput screening of Arabidopsis mutant lines?

For high-throughput screening of Arabidopsis mutant lines using ATL72 antibody:

• Sample preparation automation:

  • Use multi-well plate formats for protein extraction

  • Implement robotic systems for protein quantification and normalization

  • Consider protein extraction protocols compatible with 96-well formats

• Assay miniaturization:

  • Develop dot blot or ELISA-based methods for ATL72 detection

  • Optimize antibody concentrations for microwell formats

  • Use automated liquid handling systems for washing and reagent addition

• Detection methods:

  • Implement fluorescence-based detection for higher sensitivity

  • Consider multiplexed detection of ATL72 alongside control proteins

  • Use image analysis software for quantitative assessment

• Validation strategy:

  • Include standard samples on each plate for cross-plate normalization

  • Implement statistical methods for hit identification (Z-score, etc.)

  • Confirm hits with secondary assays like western blotting

• Data management:

  • Develop databases to link phenotypic and molecular data

  • Implement quality control metrics to identify failed assays

  • Use statistical methods to identify mutants with significant alterations in ATL72 levels

This approach enables efficient screening of large mutant collections to identify genes affecting ATL72 expression or stability.

How should researchers interpret western blot banding patterns when using ATL72 antibody?

When interpreting western blot results with ATL72 antibody:

• Band size analysis:

  • The primary band should correspond to the predicted molecular weight of ATL72

  • Higher molecular weight bands may indicate post-translational modifications (e.g., ubiquitination, SUMOylation)

  • Lower molecular weight bands might represent degradation products or alternative splice variants

• Pattern interpretation:

  • Consistent appearance of multiple bands may indicate family members with epitope similarity

  • Treatment-dependent band shifts may indicate post-translational modifications

  • Tissue-specific banding patterns may reflect differential processing

• Quantitative analysis:

  • Normalize ATL72 signal to loading controls for quantitative comparisons

  • Use densitometry software for accurate quantification

  • Apply appropriate statistical tests when comparing conditions

• Validation approaches:

  • Compare observed patterns with published literature

  • Confirm unexpected bands with alternative methods (MS, immunoprecipitation)

  • Use genetic approaches (knockout/overexpression) to validate band identity

These interpretative guidelines help researchers extract meaningful biological insights from ATL72 antibody western blot results.

What statistical approaches are recommended for analyzing quantitative data generated using ATL72 antibody?

For statistical analysis of quantitative data from ATL72 antibody experiments:

• Normalization strategies:

  • Normalize ATL72 signal to housekeeping proteins (Actin, GAPDH, Tubulin)

  • Consider total protein normalization using stain-free gels or Ponceau staining

  • Express results as fold-change relative to control samples

• Statistical tests:

  • For two-group comparisons: Student's t-test (parametric) or Mann-Whitney U test (non-parametric)

  • For multiple groups: ANOVA with appropriate post-hoc tests (Tukey, Dunnett, etc.)

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

• Technical considerations:

  • Include at least three biological replicates per condition

  • Test for normality before selecting parametric/non-parametric tests

  • Consider power analysis to determine appropriate sample sizes

• Visualization methods:

  • Present data as mean ± standard deviation or standard error

  • Use box plots or violin plots to show data distribution

  • Include individual data points for greater transparency

• Addressing variability:

  • Report coefficients of variation for technical replicates

  • Identify and handle outliers according to pre-established criteria

  • Consider hierarchical statistical models for complex experimental designs

These statistical approaches ensure robust analysis of ATL72 antibody-generated data while maintaining experimental rigor.

How can researchers correlate ATL72 protein expression data with plant phenotypes or stress responses?

To correlate ATL72 protein expression with plant phenotypes or stress responses:

• Experimental design:

  • Collect both phenotypic data and samples for protein analysis in parallel

  • Use time-course experiments to capture dynamic responses

  • Include multiple stress intensities to establish dose-response relationships

• Correlation approaches:

  • Calculate Pearson's or Spearman's correlation coefficients between ATL72 levels and phenotypic measurements

  • Use regression analysis to model relationships between protein levels and phenotypic parameters

  • Consider multivariate analyses when multiple phenotypes are measured

• Advanced methods:

  • Apply principal component analysis to reduce dimensionality of complex datasets

  • Use clustering methods to identify patterns in protein expression and phenotypic responses

  • Consider machine learning approaches for complex, non-linear relationships

• Causality testing:

  • Complement correlation studies with genetic approaches (ATL72 overexpression/knockdown)

  • Use pharmacological approaches to manipulate ATL72 function if available

  • Consider time-resolved studies to establish temporal precedence

• Validation strategies:

  • Test correlations across different experimental conditions or genetic backgrounds

  • Compare with published data on related ATL family proteins

  • Validate findings using independent experimental approaches

These approaches help establish meaningful connections between ATL72 protein levels and plant phenotypes, contributing to our understanding of ATL72's biological function.