AUR3 Antibody

What is AUR3 Antibody and what cellular structures does it target?

AUR3 Antibody is a monoclonal antibody developed against human Aurora-A serine/threonine kinase. This antibody binds specifically to centrosomes and spindle poles in human cells, making it valuable for studying cell division processes. When properly validated, the antibody should detect a single protein band at approximately 46 kDa on SDS-PAGE Western blots . Aurora kinase antibodies are critical for investigating cell cycle regulation, particularly mitotic events involving centrosome duplication and spindle formation.

What criteria should researchers use when selecting an AUR3 Antibody?

When selecting an AUR3 Antibody, researchers should evaluate its validation data across multiple applications. Effective antibodies should: (1) recognize the target protein in Western blots at the correct molecular weight, (2) show specific localization to centrosomes and spindle poles in immunofluorescence, (3) successfully immunoprecipitate the kinase, and (4) ideally cross-react with orthologs from model organisms if comparative studies are planned . Additionally, researchers should consider whether the antibody affects kinase activity, as some antibodies may inhibit function while others (like the 35C1 described in literature) allow measurement of kinase activity after immunoprecipitation .

How can researchers validate AUR3 Antibody specificity?

A robust validation protocol for AUR3 Antibody should include:

The most definitive validation involves using genetic knockout models where Aurora-A is absent, confirming that the antibody signal disappears in these samples . Organizations like YCharOS are working to characterize antibodies using knockout cell lines, providing independent validation data that researchers should consult when available .

What is the optimal protocol for AUR3 Antibody in immunofluorescence applications?

For optimal immunofluorescence using AUR3 Antibody:

• Culture cells on appropriate coverslips or chamber slides

• Fix cells using 4% paraformaldehyde (10 minutes at room temperature) or ice-cold methanol (5 minutes)

• Permeabilize with 0.1% Triton X-100 (if using paraformaldehyde fixation)

• Block with 5% normal serum in PBS for 1 hour

• Incubate with optimally titrated AUR3 Antibody (typically 1:100 to 1:500 dilution) overnight at 4°C

• Wash three times with PBS

• Apply fluorophore-conjugated secondary antibody at appropriate dilution

• Counterstain DNA with DAPI

• Mount and image using confocal microscopy

When selecting secondary antibodies and fluorophores, consider the expression level of Aurora-A (which varies through the cell cycle) and match with appropriately bright fluorophores for clear visualization of centrosomes . For co-staining experiments, avoid fluorophores with high spectral overlap when detecting markers that might co-localize with Aurora-A .

How should AUR3 Antibody be optimized for Western blotting?

For Western blotting, researchers should:

• Harvest cells during mitosis when Aurora-A expression peaks

• Use phosphatase inhibitors in lysis buffers to preserve phosphorylation states

• Titrate the antibody to determine optimal concentration (typically 1:1000 to 1:5000)

• Include positive controls (recombinant Aurora-A) and negative controls (Aurora-A depleted samples)

• Consider using gradient gels (4-12%) for optimal separation

• Block membranes with 5% BSA rather than milk (which contains phosphatases)

• Incubate with primary antibody overnight at 4°C

• Use enhanced chemiluminescence detection systems for highest sensitivity

To prevent non-specific binding, centrifuge the antibody at 10,000 RPM for 3 minutes prior to dilution, particularly important if using conjugated antibodies that can form aggregates .

What controls are essential when using AUR3 Antibody?

Every experiment with AUR3 Antibody should include:

The absence of these controls significantly increases the risk of misinterpreting experimental results, especially when studying a spatially and temporally regulated protein like Aurora-A .

How can AUR3 Antibody be incorporated into multi-parameter flow cytometry panels?

When incorporating AUR3 Antibody into flow cytometry panels:

For panels with more than 8 markers, consider using spectral flow cytometry platforms like Cytek Aurora, which provides better resolution for discriminating between similar fluorophores .

What are the key considerations for phospho-Aurora kinase detection?

Detecting phosphorylated Aurora kinase requires special considerations:

• Use specialized fixation buffers designed for phosphoprotein preservation

• Ensure rapid sample processing to prevent phosphatase activity

• Keep samples cold (4°C) during all processing steps

• Use phosphatase inhibitors in all buffers

• Select antibodies specifically validated for phospho-epitope detection

• Include positive controls treated with phosphatase inhibitors

• Include negative controls treated with phosphatases or Aurora kinase inhibitors

• Consider using dual staining with total Aurora-A and phospho-specific antibodies to normalize for expression variations

Phosphorylation states are particularly sensitive to experimental conditions, making standardized protocols essential for reproducible results across experiments .

How can AUR3 Antibody be used for immunoprecipitation followed by kinase activity assays?

For immunoprecipitation (IP) followed by kinase activity assays:

• Confirm the antibody does not inhibit kinase activity (as verified for 35C1 clone)

• Prepare cell lysates in non-denaturing buffers containing protease and phosphatase inhibitors

• Pre-clear lysates with protein A/G beads to reduce non-specific binding

• Incubate cleared lysates with optimized amount of AUR3 Antibody (typically 1-5 μg)

• Capture antibody-antigen complexes with protein A/G beads

• Wash extensively to remove contaminants while preserving kinase activity

• Split the immunoprecipitate for parallel analysis:

  • Western blot to confirm Aurora-A pull-down

  • Kinase assay using appropriate substrates (e.g., histone H3)

• Quantify phosphorylation by autoradiography or phospho-specific antibodies

The 35C1 monoclonal antibody described in the literature specifically maintains Aurora-A kinase activity after immunoprecipitation, making it suitable for measuring in vivo kinase activity .

How can machine learning approaches improve experiments using AUR3 Antibody?

Machine learning (ML) approaches can enhance AUR3 Antibody experiments in several ways:

• Predicting antibody-antigen binding affinities using library-on-library approaches

• Optimizing experimental design through active learning strategies, which can reduce the number of required experiments by up to 35%

• Improving out-of-distribution prediction for novel Aurora kinase variants or related proteins

• Analyzing complex binding patterns in high-dimensional data from flow cytometry or imaging experiments

• Developing more specific antibodies by analyzing epitope characteristics that confer specificity

The Absolut! simulation framework, for example, has been used to evaluate active learning strategies for antibody-antigen binding prediction, potentially accelerating experimental workflows . By implementing these computational approaches, researchers can design more efficient experimental protocols and reduce the resources needed for comprehensive analyses.

What are common pitfalls in data interpretation when using AUR3 Antibody?

Researchers should be aware of these common pitfalls:

To avoid these issues, researchers should validate findings with multiple detection methods and include appropriate genetic controls (siRNA knockdown or CRISPR knockout) . Additionally, understanding the normal cell cycle-dependent expression pattern of Aurora-A is crucial for correct interpretation.

How can researchers address weak or absent signals when using AUR3 Antibody?

When troubleshooting weak or absent signals:

For flow cytometry applications specifically, fluorochrome aggregation can reduce signal quality. Centrifuge antibody solutions at high speed (10,000 RPM for 3 minutes) before use to remove aggregates, and use specialized staining buffers for antibodies conjugated to polymer dyes like Brilliant Violet .

How should researchers evaluate batch-to-batch consistency of AUR3 Antibody?

To ensure batch-to-batch consistency:

• Maintain a reference stock of a validated antibody lot

• Test each new batch side-by-side with the reference in your specific application

• Compare staining patterns, signal intensity, and background levels

• Document lot numbers and performance metrics for all experiments

• Consider developing a standardized quantitative assay for antibody validation

• Store validation data in a centralized database for reference

• Participate in community efforts like YCharOS to share antibody validation data

Antibody reproducibility has been identified as a major challenge in biomedical research, with many antibodies failing to recognize their intended targets or recognizing additional molecules . Careful validation of each batch is therefore essential for research integrity.

How is cryoEM being used for antibody discovery and characterization?

Cryo-electron microscopy (cryoEM) is revolutionizing antibody research through:

• Structure-based antibody discovery approaches that can identify functional antibody sequences

• Detailed epitope mapping at near-atomic resolution

• Conformational analysis of antibody-antigen complexes

• Evaluation of binding modes and interaction surfaces

• Optimization of antibody properties based on structural insights

These approaches can potentially improve Aurora kinase antibodies by enabling rational design of reagents with enhanced specificity and reduced cross-reactivity with related family members. CryoEM can also help characterize the structural basis for antibodies that either inhibit or preserve Aurora kinase activity .

What open science initiatives are improving antibody reliability for research?

Several initiatives are addressing antibody reliability challenges:

• YCharOS works with antibody manufacturers and knockout cell line producers to independently validate antibodies, identifying high-performing renewable antibodies for many targets

• The "Only Good Antibodies" initiative brings together researchers and partner organizations to promote best practices in antibody selection and validation

• Open data sharing platforms for antibody characterization results

• Community-driven validation efforts to identify reliable reagents

• Development of standardized validation protocols across research communities

These initiatives aim to address technical, policy, behavioral, and data sharing challenges in antibody research. By participating in these collaborative efforts, researchers can contribute to improved research reproducibility and integrity in the field .