ATM Monoclonal Antibody

What is the subcellular localization of ATM protein in neuronal tissues?

ATM protein demonstrates predominant cytoplasmic localization in specific neuronal cells. Studies using anti-ATM monoclonal antibodies show that in mouse cerebellum, ATM is exclusively expressed in the cytoplasm of Purkinje cells (PCs) in the cerebellar cortex. Similar cytoplasmic ATM immunoreactivity has been observed in a subset of neurons in dorsal root ganglia. This localization pattern in mouse cerebellum resembles that reported in human adult cerebellum . When conducting immunohistochemical studies, it is essential to include appropriate negative controls, such as ATM-knockout tissues (Atm−/−), to validate antibody specificity.

Which tissue types express ATM protein at detectable levels?

ATM expression has been documented across various tissues through antibody-based detection methods. According to validation studies, ATM is expressed in:

• Brain tissue (corpus callosum and cerebellum)

• Fibroblasts

• Cervix carcinoma

• Embryonic kidney

• Liver

• Erythroleukemia cells

When designing experiments to detect ATM in these tissues, researchers should consider tissue-specific optimization of antibody concentrations and incubation conditions.

How should ATM monoclonal antibodies be stored to maintain optimal activity?

For long-term storage, ATM monoclonal antibodies should be maintained at -20°C for up to one year. For short-term storage and frequent use, store at 4°C for up to one month. It is crucial to avoid repeated freeze-thaw cycles as these can significantly degrade antibody performance . When working with these antibodies, proper handling includes maintaining a cold chain during experiments and avoiding contamination.

How do I validate the specificity of an ATM monoclonal antibody for my research?

Validating antibody specificity requires multiple complementary approaches:

• Western blotting validation: Load protein extracts from both wild-type and ATM-knockout (Atm−/−) tissues on 7.5% low crosslinking acrylamide gels (121:1 acrylamide:bisacrylamide). The absence of signal in knockout tissues confirms specificity .

• Immunoprecipitation assays: Perform pull-down experiments followed by mass spectrometry to confirm target enrichment.

• Multi-application testing: Validate across different applications (WB, IHC, ICC, IF, Flow Cytometry) to ensure consistent specificity .

• Cross-reactivity testing: If working with non-human samples, test the antibody against multiple species to determine cross-reactivity boundaries.

What pharmacokinetic/pharmacodynamic models are relevant when studying therapeutic ATM monoclonal antibodies?

For therapeutic applications of ATM monoclonal antibodies (such as ATM-027 in multiple sclerosis studies), a two-compartment pharmacokinetic model is most appropriate. Key parameters to consider include:

• Total volume of distribution: approximately 5.9 liters

• Terminal half-life: approximately 22.3 days in typical patients

• EC50 for receptor expression: 138-148 μg/L using inhibitory sigmoidal Emax-models

• Target cell reduction: treatment with ATM-027 decreases target T cell numbers to approximately 25.7-28.9% of baseline values

When designing dosing regimens, these parameters enable prediction of antibody concentrations and biological effects over time.

How do ATM monoclonal antibodies perform across different experimental systems?

Performance varies significantly across experimental platforms:

These parameters should be optimized for each specific experimental setup and cell/tissue type .

What is the recommended protocol for ATM detection in fibroblast samples?

For detecting ATM in fibroblast samples, the following optimized protocol is recommended:

• For Western Blotting:

  • Lyse fibroblasts in RIPA buffer supplemented with protease inhibitors

  • Load 30-50 μg protein per lane on 7.5% low crosslinking acrylamide gels (121:1 acrylamide:bisacrylamide)

  • Transfer to PVDF membrane at 100V for 2 hours

  • Block with 5% non-fat milk for 1 hour at room temperature

  • Incubate with anti-ATM antibody (1:500 dilution) overnight at 4°C

  • Wash and incubate with HRP-conjugated secondary antibody

  • Detect using chemiluminescent protocol

• For Immunocytochemistry:

  • Fix fibroblasts with 4% paraformaldehyde for 15 minutes

  • Permeabilize with 0.1% Triton X-100 for 10 minutes

  • Block with 1% BSA in PBS for 30 minutes

  • Incubate with anti-ATM antibody (1:100 dilution) for 2 hours at room temperature

  • Follow with fluorophore-conjugated secondary antibody incubation

  • Counterstain nuclei with DAPI before mounting

How should I analyze ATM expression in neuronal tissues by immunohistochemistry?

For neuronal tissue analysis:

• Tissue preparation:

  • Fix tissues in 4% paraformaldehyde

  • Create paraffin-embedded or frozen sections (10-12 μm thickness)

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

• Staining procedure:

  • Block endogenous peroxidase with 0.3% H₂O₂

  • Apply protein block (5% normal serum)

  • Incubate with anti-ATM antibody overnight at 4°C

  • Use appropriate detection system (e.g., avidin-biotin complex)

  • Develop with DAB and counterstain with hematoxylin

• Analysis focus:

  • Examine Purkinje cell layer in cerebellum for cytoplasmic staining

  • Compare with ATM-knockout tissues as negative controls

  • Assess subcellular localization (primarily cytoplasmic in neurons)

What are the best methods for quantifying ATM receptor expression on cell surfaces?

For quantitative analysis of cell surface ATM:

• Flow cytometry approach:

  • Prepare single-cell suspensions

  • Block Fc receptors with appropriate blocking solution

  • Stain with anti-ATM antibody (1:50-1:100 dilution)

  • Apply fluorophore-conjugated secondary antibody

  • Analyze using standard flow cytometry protocols

  • Quantify using mean fluorescence intensity (MFI)

• Modeling receptor expression:

  • Apply inhibitory sigmoidal Emax-model for continuous receptor expression data

  • For categorical data, use proportional odds model

  • Determine EC50 values for correlation between models

  • Calculate percentage change from baseline after antibody treatment

How can I resolve inconsistent staining patterns when using ATM monoclonal antibodies?

Inconsistent staining may result from several factors:

• Antibody specificity issues:

  • Validate antibody using ATM-knockout tissues or cells

  • Confirm expression patterns align with known tissue distribution

  • Test multiple antibody lots for consistency

• Technical considerations:

  • Optimize antigen retrieval methods for fixed tissues

  • Adjust antibody concentration and incubation times

  • Ensure proper blocking to reduce non-specific binding

  • Control temperature during all incubation steps

• Sample preparation factors:

  • Standardize fixation protocols and times

  • Minimize time between tissue collection and fixation

  • Use freshly prepared buffers and reagents

What controls should be included when studying ATM expression in disease models?

A comprehensive control strategy includes:

• Genetic controls:

  • ATM-knockout (Atm−/−) tissues/cells as negative controls

  • Tissues with known high expression (e.g., cerebellum) as positive controls

• Antibody controls:

  • Isotype control antibodies to assess non-specific binding

  • Secondary antibody-only controls to evaluate background

  • Peptide competition assays to confirm binding specificity

• Disease-specific controls:

  • Age-matched normal tissues for comparison to disease samples

  • Treatment-naive samples when evaluating therapy effects

  • Time-course controls to account for disease progression

How do I interpret contradictory results between different detection methods for ATM?

When facing contradictory results between methods:

• Methodological considerations:

  • Western blotting detects denatured proteins; conformation-specific antibodies may not work

  • IHC/ICC preserves spatial information but may have accessibility limitations

  • Flow cytometry only detects surface or permeabilized cellular epitopes

• Resolution approaches:

  • Use multiple antibodies targeting different epitopes of ATM

  • Employ complementary techniques (e.g., mRNA analysis, reporter assays)

  • Consider post-translational modifications that might affect epitope recognition

  • Evaluate subcellular fractionation to resolve localization discrepancies

• Data integration:

  • Weigh results based on technique sensitivity and specificity

  • Consider biological context when interpreting conflicting data

  • Document experimental conditions thoroughly for reproducibility assessment

How can ATM monoclonal antibodies be applied in neurodegenerative disease research?

ATM's unique cytoplasmic localization in neurons makes it valuable for neurodegenerative research:

• Cerebellar ataxia studies:

  • Monitor Purkinje cell ATM expression and localization changes

  • Correlate ATM levels with disease progression

  • Investigate ATM's role in neuronal survival pathways

• DNA damage response in neurons:

  • Evaluate nuclear versus cytoplasmic ATM distribution in response to oxidative stress

  • Assess post-translational modifications of ATM in neurodegenerative conditions

  • Monitor ATM activation status using phospho-specific antibodies

• Therapeutic targeting:

  • Use ATM antibodies to identify neurons susceptible to degeneration

  • Develop screening platforms for compounds that modulate ATM activity

  • Track treatment efficacy through changes in ATM expression or localization

What considerations are important when developing pharmacodynamic biomarkers based on ATM detection?

When developing ATM-based biomarkers:

• Assay development:

  • Select antibodies with high specificity and sensitivity

  • Establish standardized protocols with defined cut-off values

  • Validate across multiple sample types and disease states

• Clinical correlation:

  • Correlate ATM expression/activity with clinical outcomes

  • Determine temporal relationships between ATM changes and disease progression

  • Establish minimally important differences for intervention studies

• Monitoring parameters:

  • For therapeutic antibodies like ATM-027, monitor target cell reduction (expect 25.7-28.9% of baseline)

  • Track receptor expression using established EC50 values (138-148 μg/L)

  • Consider terminal half-life (approximately 22.3 days) when designing sampling schedules

How do recent findings on ATM's cytoplasmic functions impact antibody selection and experimental design?

The discovery of ATM's cytoplasmic localization has important implications:

• Epitope selection:

  • Choose antibodies recognizing epitopes accessible in both nuclear and cytoplasmic environments

  • Consider antibodies specific to different ATM conformational states

  • Select clones validated for the appropriate subcellular compartment

• Functional studies:

  • Design experiments that differentiate between ATM's DNA damage response and cytoplasmic signaling roles

  • Include cytoplasmic signaling partners in interaction studies

  • Develop assays specific to cytoplasmic ATM activation states

• Disease relevance:

  • Investigate neuronal-specific functions separately from general cellular functions

  • Consider tissue-specific processing or modifications that might affect antibody recognition

  • Incorporate cell type-specific analyses, particularly focusing on Purkinje cells and dorsal root ganglia neurons