ATMIN Antibody

What is ATMIN and why is it significant in research?

ATMIN (ATM/ATR-substrate Chk2-interacting Zn2+-finger protein) is a crucial scaffold protein in the DNA damage response pathway. It plays a vital role in the Rad51 focus formation pathway, which is essential for repairing DNA lesions. ATMIN's significance stems from its ability to form Rad51-containing foci in response to DNA methylating agents and persistent single-stranded DNA gaps, which is vital for maintaining genomic stability. The protein facilitates DNA damage repair and prevents apoptosis induced by excessive DNA damage, making it an important target for research in cancer biology, cellular stress responses, and DNA repair mechanisms .

What species reactivity can I expect from commercial ATMIN antibodies?

Most commercially available ATMIN antibodies demonstrate cross-reactivity across multiple mammalian species. For instance, the mouse monoclonal ATMIN Antibody (B-1) detects ATMIN in mouse, rat, and human samples . Similarly, rabbit polyclonal antibodies against ATMIN typically show reactivity with human, mouse, and rat specimens . Always check the specific product documentation for validated species reactivity before designing experiments involving non-standard model organisms.

What are the common applications for ATMIN antibodies in research?

ATMIN antibodies are validated for multiple research applications including:

• Western blotting (WB): For protein expression quantification

• Immunoprecipitation (IP): For protein-protein interaction studies

• Immunofluorescence (IF): For subcellular localization

• Enzyme-linked immunosorbent assay (ELISA): For quantitative analysis

• Immunocytochemistry (ICC): For cellular detection

The choice of application depends on your specific research question. For example, immunofluorescence is particularly useful for studying ATMIN's role in Rad51 focus formation after DNA damage, while immunoprecipitation helps investigate ATMIN's interaction with other proteins in the DNA damage response pathway .

How can ATMIN antibodies be utilized in studying DNA damage response pathways?

ATMIN antibodies serve as invaluable tools for investigating DNA damage response (DDR) mechanisms. For detailed pathway analysis, researchers can employ ATMIN antibodies in chromatin immunoprecipitation (ChIP) assays to detect ATMIN binding to specific DNA regions during stress response. The antibodies can also be used in co-immunoprecipitation experiments to identify novel protein interactions within the ATM/ATR signaling cascade.

For advanced investigations, consider using ATMIN antibodies in conjunction with phospho-specific antibodies against ATM/ATR substrates to create a comprehensive map of temporal DDR activation. This approach allows for the delineation of ATMIN's scaffolding function in the context of different types of DNA damage (e.g., double-strand breaks versus replication stress). When designing such experiments, it's crucial to verify the specificity of the antibody for recognizing ATMIN's different functional domains, particularly the N-terminal nucleic acid binding domain, nuclear localization signal, and C-terminal SQ/TQ cluster domain .

What methodological considerations should be made when using ATMIN antibodies for quantitative protein analysis?

For quantitative protein analysis using ATMIN antibodies, several methodological considerations are critical:

• Antibody selection: Choose between monoclonal (higher specificity) and polyclonal (potentially higher sensitivity) antibodies based on your experimental needs. Monoclonal antibodies like ATMIN Antibody (B-1) offer consistent lot-to-lot reproducibility .

• Normalization strategy: ATMIN expression can vary significantly across cell types and under different stress conditions. Implement appropriate loading controls and consider using absolute quantification methods (e.g., recombinant protein standards) for more accurate comparisons.

• Post-translational modification awareness: ATMIN undergoes phosphorylation in response to DNA damage, which may affect antibody binding. If studying stress responses, consider using phospho-specific antibodies alongside total ATMIN antibodies.

• Statistical validation: Implement molecular amplification fingerprinting (MAF) techniques for more accurate quantification. Studies show that MAF error correction significantly improves the reliability of quantitative analysis, with uncorrected data showing poor prediction capabilities (R² = 0.69) compared to MAF-corrected data (R² = 0.94) .

How can ATMIN antibodies contribute to antibody library development research?

ATMIN antibodies can serve as model systems in antibody library development research. Recent advances in antibody library creation, such as the Immunoglobulin Language Model (IgLM), use deep learning to generate high-quality antibody libraries trained on billions of real antibody sequences . When incorporating ATMIN antibodies into such research:

• Training data contribution: Characterized ATMIN antibodies with validated specificity can serve as valuable training sequences for deep learning models like IgLM.

• Specificity profile benchmarking: Use well-characterized ATMIN antibodies as benchmarks when validating custom specificity profiles created through computational approaches. This is especially relevant when assessing whether computationally designed antibodies can discriminate between closely related epitopes .

• Experimental validation: ATMIN antibodies can serve as controls in phage display experiments for selection of antibody libraries, particularly when validating computational models that disentangle different binding modes .

What are the optimal conditions for using ATMIN antibodies in Western blotting?

For optimal Western blotting results with ATMIN antibodies, follow these methodological guidelines:

When troubleshooting, consider that ATMIN may undergo post-translational modifications that alter its migration pattern. Additionally, for phosphorylated ATMIN detection, use phospho-specific antibodies and BSA for blocking instead of milk .

What controls should be implemented when using ATMIN antibodies in immunofluorescence studies?

Implementing proper controls is critical for reliable immunofluorescence studies with ATMIN antibodies:

• Positive controls: Include cell lines known to express ATMIN, particularly those under genotoxic stress conditions that induce Rad51 foci formation.

• Negative controls:

  • Primary antibody omission control

  • Secondary antibody-only control

  • Isotype control using non-specific IgG from the same species

  • ATMIN-depleted cells (siRNA or CRISPR knockout) where possible

• Specificity controls:

  • Peptide competition assay using the immunizing peptide

  • Dual staining with an alternative ATMIN antibody recognizing a different epitope

• Technical controls:

  • Include DAPI nuclear staining to confirm nuclear localization

  • Co-stain with Rad51 antibodies to verify functional ATMIN-dependent foci formation

For advanced studies, consider inducing DNA damage (e.g., with methylating agents) to demonstrate the expected relocalization of ATMIN to Rad51-containing foci, which serves as both a functional control and biological validation .

How can I validate the specificity of an ATMIN antibody for my research applications?

Validating antibody specificity is crucial for reliable research outcomes. For ATMIN antibodies, implement these validation strategies:

• Genetic validation:

  • Use CRISPR/Cas9 or siRNA knockdown of ATMIN

  • Compare signal in wildtype versus knockout/knockdown samples

  • Expected result: significant reduction or elimination of signal in depleted samples

• Expression validation:

  • Overexpress tagged ATMIN (e.g., FLAG-ATMIN) in cells

  • Perform dual labeling with anti-ATMIN and anti-tag antibodies

  • Expected result: co-localization of signals

• Analytical validation:

  • Perform Western blot analysis to confirm a single band at the expected molecular weight (approximately 110-120 kDa)

  • Conduct immunoprecipitation followed by mass spectrometry to confirm target identity

  • Verify preservation of signal following appropriate antigen retrieval protocols

• Domain-specific verification:

  • Design domain deletion constructs (e.g., removing the N-terminal nucleic acid binding domain)

  • Test whether the antibody recognizes the domain it was raised against

  • This is particularly important given ATMIN's multiple functional domains

How can ATMIN antibodies be incorporated into studies of DNA damage-induced apoptosis?

ATMIN antibodies offer valuable insights into DNA damage-induced apoptosis pathways through several methodological approaches:

• Temporal analysis: Use ATMIN antibodies in time-course studies following DNA damage induction to track ATMIN redistribution and correlate it with apoptotic markers. This approach reveals the critical time window when ATMIN's scaffolding function transitions from promoting DNA repair to initiating apoptotic signaling.

• Co-localization studies: Employ dual immunofluorescence with ATMIN antibodies and markers for:

  • Early apoptosis (phosphatidylserine exposure via Annexin V)

  • Mid-stage apoptosis (activated caspases)

  • Late apoptosis (DNA fragmentation via TUNEL assay)

• Functional rescue experiments: In ATMIN-deficient cells showing increased susceptibility to DNA damage-induced apoptosis, reintroduce wildtype or mutant ATMIN constructs and use ATMIN antibodies to confirm expression and localization. This approach can identify which domains of ATMIN are essential for anti-apoptotic functions.

• Pathway dissection: Use ATMIN antibodies in combination with inhibitors of ATM/ATR kinases to determine how ATMIN's functions in apoptosis regulation depend on these upstream kinases .

What are the considerations for using ATMIN antibodies in computational antibody design research?

When incorporating ATMIN antibodies in computational antibody design research, consider these methodological approaches:

• Sequence-structure relationship analysis: Include validated ATMIN antibody sequences in training datasets for deep learning models like Immunoglobulin Language Model (IgLM). This can help train models to predict antibody structures with high accuracy, particularly for antibodies targeting nuclear proteins .

• Epitope mapping for binding mode analysis: Use experimental data from ATMIN antibodies to validate computational models that predict different binding modes. This is especially valuable when the models need to distinguish between chemically similar ligands, as demonstrated in recent research combining phage display and computational analysis .

• Integration with RFdiffusion networks: Consider incorporating ATMIN antibody structural data when fine-tuning RFdiffusion networks for de novo antibody design. Recent research has shown that combining computational protein design using fine-tuned RFdiffusion networks with yeast display screening enables the generation of antibodies that bind specific epitopes with atomic-level precision .

• Molecular amplification fingerprinting (MAF) application: Apply MAF techniques when analyzing sequencing data from ATMIN antibody libraries to improve accuracy. Studies show that MAF error correction significantly enhances the ability to distinguish between different immune statuses and improves predictive models (increasing the area under ROC curve from 0.69 to 0.94) .

How can ATMIN antibodies contribute to understanding the relationship between DNA damage response and cancer development?

ATMIN antibodies provide essential tools for investigating the complex relationship between DNA damage response (DDR) and cancer development:

• Biomarker validation: Use ATMIN antibodies in tissue microarray analysis of cancer specimens to evaluate whether ATMIN expression or localization correlates with:

  • Cancer stage and grade

  • Treatment response

  • Patient prognosis

• DDR pathway integrity assessment: Employ ATMIN antibodies to evaluate the integrity of the ATM-dependent DNA damage response in tumor samples:

  • Reduced ATMIN-positive foci may indicate DDR deficiencies

  • Altered ATMIN expression patterns could suggest adaptations that promote cancer cell survival

• Therapeutic response prediction: Monitor ATMIN dynamics using immunofluorescence or immunohistochemistry before and after treatment with:

  • DNA-damaging agents (radiotherapy, platinum compounds)

  • PARP inhibitors

  • ATM/ATR pathway inhibitors

• Mechanistic studies: Use ATMIN antibodies in ChIP-seq experiments to identify genomic regions where ATMIN acts as a transcription factor, potentially regulating genes involved in both DDR and cancer progression.

• Synthetic lethality exploration: In cancer cells with specific DDR defects, use ATMIN antibodies to monitor changes in ATMIN-dependent pathways following treatment with agents targeting complementary DDR pathways .

How might ATMIN antibodies be utilized in next-generation antibody library development technologies?

ATMIN antibodies can play a significant role in advancing next-generation antibody library technologies through several innovative approaches:

• Integration with deep learning models: ATMIN antibodies can serve as valuable training data for deep learning models like IgLM, which has been trained on half a billion real human antibody sequences. As models evolve, the structural and binding characteristics of well-characterized ATMIN antibodies can help refine prediction algorithms for antibody-antigen interactions .

• Custom specificity profile development: The methodologies used to characterize ATMIN antibody specificity can inform the development of computational approaches for designing antibodies with customized specificity profiles. This is particularly relevant for creating antibodies that distinguish between closely related epitopes, as demonstrated in recent research combining phage display experiments with biophysics-informed modeling .

• Cross-species application: Since ATMIN antibodies typically demonstrate reactivity across multiple species (human, mouse, rat), they provide valuable data for developing computational models that can generate antibodies for different species. This advantage has been highlighted in systems like IgLM, which can generate antibodies for mice, primates, and humans due to its training on diverse species datasets .

• Rapid response applications: The methodologies developed for computational antibody design using IgLM and similar technologies could dramatically accelerate the production of specific antibodies during disease outbreaks, similar to how antibody libraries provided researchers with blueprints for synthesizing molecules used in COVID-19 vaccines .

What role might ATMIN antibodies play in advancing atomically accurate antibody design?

ATMIN antibodies can contribute to the emerging field of atomically accurate antibody design in several ways:

• Structural template refinement: The structural characteristics of ATMIN antibodies, particularly their complementarity-determining regions (CDRs), can serve as templates for refining computational methods like RFdiffusion networks. These networks have demonstrated the ability to design antibodies that bind user-specified epitopes with atomic-level precision .

• Validation methodologies: The experimental approaches used to validate ATMIN antibodies can inform the development of validation protocols for de novo designed antibodies. This includes cryo-EM structural data confirmation of proper Ig fold and binding poses, which has been critical in confirming the accuracy of computational antibody designs .

• Affinity maturation strategies: The knowledge gained from studying natural ATMIN antibody binding can inform affinity maturation strategies for computationally designed antibodies. Recent research has shown that affinity maturation using OrthoRep can produce single-digit nanomolar binders that maintain intended epitope selectivity .

• Combinatorial design approaches: Insights from ATMIN antibody structure-function relationships can guide the development of combination approaches that merge computationally designed heavy and light chain CDRs to create binders with specific properties. This methodology has been successfully applied to create binders to complex targets with atomic-level precision in both structure and epitope targeting .