TPD52L1 Antibody

What is TPD52L1 and why is it a target for antibody research?

TPD52L1 (Tumor protein D52-like 1), also known as hD53, encodes a member of the tumor protein D52 (TPD52) family. The protein contains a coiled-coil domain and may form homo- or hetero-dimers with TPD52 family members . It's involved in cell proliferation and calcium signaling, and interacts with mitogen-activated protein kinase kinase kinase 5 (MAP3K5/ASK1), positively regulating MAP3K5-induced apoptosis . Research interest in TPD52L1 has grown due to its roles in cancer biology and DNA damage response pathways .

What are the common applications for TPD52L1 antibodies?

TPD52L1 antibodies are used in multiple experimental techniques:

How should TPD52L1 antibodies be stored for optimal performance?

Most TPD52L1 antibodies should be stored at -20°C . Long-term storage requires aliquoting to avoid repeated freeze-thaw cycles that can compromise antibody performance . Many formulations contain glycerol (typically 50%) and sodium azide (0.02%) as preservatives . Some antibody formulations may contain BSA (bovine serum albumin) as a stabilizer . According to manufacturer recommendations, properly stored antibodies typically remain stable for one year after shipment .

How can I validate the specificity of a TPD52L1 antibody for my experimental system?

A multi-faceted approach to validating TPD52L1 antibody specificity includes:

• Western blot verification: Confirm molecular weight corresponds to expected size (calculated MW: 22 kDa; observed MW: 25 kDa)

• siRNA knockdown controls: Use TPD52L1-specific siRNAs to reduce target expression and confirm antibody specificity

• Isoform recognition: Determine which isoforms your antibody detects. Some antibodies specifically recognize isoforms 1, 3, and 4 (NP_003278.1, NP_001003396.1, and NP_001003397.1)

• Cross-reactivity assessment: Test antibody with both human and mouse samples if working across species

• Immunogen sequence verification: Compare the immunogen sequence with your protein of interest to ensure epitope conservation

Enhanced validation methods include orthogonal RNA sequencing validation, which confirms antibody specificity by correlating protein detection with transcript levels .

What are the recommended protocols for immunoprecipitating TPD52L1 and its binding partners?

For successful co-immunoprecipitation of TPD52L1 and interacting proteins:

• Lysate preparation: Use 1.0-3.0 mg of total protein lysate with 0.5-4.0 μg of TPD52L1 antibody

• Buffer composition: For TPD52L1-ATM interactions, standard IP buffers have been successful in detecting endogenous complexes

• Detection method: Following IP with TPD52L1 antibody, Western blot analysis can identify binding partners such as ATM

• Controls: Include non-specific immunoglobulin as a negative control to evaluate non-specific binding

• Reciprocal IP: Confirm interactions by performing reverse IP (e.g., IP with ATM antibody and detection of TPD52L1)

Research has demonstrated successful co-immunoprecipitation of endogenous TPD52L1 with ATM from SK-BR-3 cell lysates, confirming their direct interaction in cultured cells .

What conditions are optimal for immunohistochemical detection of TPD52L1 in tissue samples?

For optimal IHC detection of TPD52L1:

• Antigen retrieval: Use TE buffer pH 9.0 (primary recommendation) or citrate buffer pH 6.0 as an alternative

• Antibody dilution: Use between 1:50-1:500 dilution depending on the specific antibody and tissue type

• Incubation conditions: For some protocols, overnight incubation at room temperature has proven effective

• Detection system: Standard avidin-biotin systems with DAB chromogen work well for visualizing TPD52L1

• Positive control tissues: Human prostate cancer tissue has been validated as a positive control

Note that sample-dependent optimization may be necessary, and researchers should check validation data galleries from manufacturers for tissue-specific protocols .

How does TPD52L1 function as a negative regulator of ATM protein levels in DNA damage response?

TPD52L1 has been identified as a negative regulator of ATM protein levels in the DNA damage response pathway. Key findings include:

• Protein level regulation: Increased TPD52L1 expression in breast cancer cells and TPD52L1-expressing BALB/c 3T3 cells compromised ATM-mediated cellular responses to DNA double-strand breaks (DSBs)

• Post-transcriptional mechanism: TPD52L1 expression reduced steady-state ATM protein levels by approximately 50% without affecting ATM transcript levels, indicating post-transcriptional regulation

• Direct interaction: GST pull-down and co-immunoprecipitation assays confirmed direct interactions between TPD52L1 and ATM

• Interaction domains: The binding interaction involves TPD52L1 residues 111-131 and ATM residues 1-245 and 772-1102

• Functional consequences: TPD52L1-expressing cells showed significantly increased radiation sensitivity in clonogenic assays due to compromised ATM-mediated DNA repair signaling

This regulatory mechanism has significant implications for understanding radiosensitivity in cancer cells with altered TPD52L1 expression .

What experimental approaches can be used to study TPD52L1's role in cell proliferation and cancer biology?

Multiple experimental approaches can be employed to investigate TPD52L1's functions in cell proliferation and cancer:

• Expression modulation studies:

  • Overexpression: Transfection with HA-TPD52L1 in cell lines like SK-BR-3 and MDA-MB-231

  • Knockdown: siRNA-mediated silencing (using validated sequences like Si-D52-1 and Si-D52-2)

• Radiation sensitivity assays:

  • Clonogenic survival assays following γ-ray irradiation to assess cell survival fractions

  • γH2AX foci quantification to measure DNA damage repair efficiency

• Signaling pathway analysis:

  • Western blot analysis of phospho-ATM, phospho-CHK2, and phospho-p53 levels following irradiation

  • Time-course experiments (e.g., 15 minutes post-irradiation) to capture early signaling events

• Protein-protein interaction studies:

  • Co-immunoprecipitation with endogenous proteins

  • GST pull-down assays using recombinant protein fragments

  • Truncation mutant analysis to map interaction domains

• Tissue expression profiling:

  • IHC analysis of TPD52L1 expression in cancer tissues compared to normal tissues

What are the known interactions between TPD52L1 and 14-3-3 proteins, and how can these be experimentally investigated?

The interaction between TPD52L1 and 14-3-3 proteins represents an important regulatory mechanism:

• Alternative splicing regulation: Alternative splicing of TPD52L1 has been identified as a mechanism for regulating 14-3-3 binding

• Experimental investigation approaches:

  • Co-immunoprecipitation assays to detect endogenous protein complexes

  • GST pull-down assays using recombinant proteins

  • Yeast two-hybrid screening to identify interaction domains

  • Site-directed mutagenesis of potential 14-3-3 binding motifs

  • Immunofluorescence co-localization studies

• Functional significance:

  • 14-3-3 proteins often regulate subcellular localization, protein stability, and activity

  • The interaction may influence TPD52L1's roles in cell proliferation and apoptosis regulation

Research by Boutros et al. (2003) established the fundamental understanding of these interactions, demonstrating how alternative splicing provides a mechanism for regulating the binding between TPD52L1 and 14-3-3 proteins .

How can I address weak or non-specific signals when using TPD52L1 antibodies in Western blot applications?

To improve Western blot results with TPD52L1 antibodies:

Researchers should also consider that TPD52L1 may undergo post-translational modifications that affect protein migration during electrophoresis, potentially explaining the difference between calculated (22 kDa) and observed (25 kDa) molecular weights .

What are the key considerations when selecting between different TPD52L1 antibody clones for specific applications?

When selecting a TPD52L1 antibody for your research:

• Immunogen considerations:

  • N-terminal immunogens: Antibodies raised against sequences like "MEAQAQGLLETEPLQGTDEDAVASADFSSMLSEEEKEELKAELVQLEDEITTLRQVLSAKERHLVEI"

  • Mid-region immunogens: Antibodies against sequences like "SPTFKSFEERVETTVTSLKTKVGGTNPNGGSFEEVLSSTAHASAQSLAGGSRRTKEEELQC"

  • C-terminal peptides: Antibodies against "C-EPLQGTDEDAVASAD"

• Isoform recognition:

  • Some antibodies specifically recognize isoforms 1, 3, and 4

  • Consider which isoforms are expressed in your experimental system

• Host species considerations:

  • Rabbit polyclonal antibodies: Often used for multiple applications

  • Mouse monoclonal antibodies: Clone d1D5 is validated for ELISA, IHC, and FACS

  • Goat polyclonal antibodies: Available for ELISA and Western blot applications

• Application-specific performance:

  • For IF/ICC: Select antibodies validated in cell lines similar to your experimental system

  • For IHC: Choose antibodies validated with appropriate antigen retrieval methods

  • For co-IP experiments: Select antibodies demonstrated to work in IP applications

How can experimental conditions be optimized when studying TPD52L1's interaction with ATM in the context of DNA damage response?

To optimize experiments investigating TPD52L1-ATM interactions in DNA damage response:

• Radiation dosage optimization:

  • 6 Gy γ-ray irradiation has been successfully used in TPD52L1-ATM interaction studies

  • Perform dose-response experiments to determine optimal radiation levels for your cell model

• Timing considerations:

  • Early signaling events (phospho-ATM, phospho-CHK2, phospho-p53) can be detected 15 minutes post-irradiation

  • Time-course experiments (0, 15, 30, 60 min) may reveal dynamic interaction patterns

• Cell line selection:

  • SK-BR-3 and MCF-7 cells have been validated for TPD52L1-ATM interaction studies

  • BALB/c 3T3 cells with stable TPD52L1 expression provide good models for mechanistic studies

• Experimental readouts:

  • γH2AX foci quantification: Measure through immunofluorescence microscopy

  • Clonogenic survival assays: Assess functional consequences of altered TPD52L1-ATM interactions

  • Western blot analysis: Monitor ATM, CHK2, and p53 phosphorylation status

• Controls for specificity:

  • TPD52L1 siRNA knockdown: Si-D52-1 and Si-D52-2 sequences have been validated

  • Non-targeting control siRNAs: Essential for comparing knockdown effects

  • Vector control cells: Critical when using stable expression systems

These optimization strategies ensure robust and reproducible results when investigating the regulatory role of TPD52L1 in ATM-mediated DNA damage response pathways.

What are promising approaches for investigating TPD52L1's potential as a therapeutic target in cancer?

Emerging approaches for exploring TPD52L1 as a cancer therapeutic target include:

• Radiation sensitization strategies:

  • Modulating TPD52L1 expression could potentially enhance radiation therapy effectiveness in cancer cells

  • Development of small molecule inhibitors of TPD52L1-ATM interaction may sensitize resistant tumors

• Biomarker development:

  • Evaluation of TPD52L1 expression levels across cancer types using tissue microarrays and IHC

  • Correlation of expression with patient outcomes and treatment responses

  • Exploration of TPD52L1 as a predictive biomarker for radiation therapy response

• Therapeutic antibody approaches:

  • Development of antibody-drug conjugates targeting TPD52L1-expressing cancer cells

  • Investigation of TPD52L1 accessibility on the cell surface in various tumor types

• Protein-protein interaction disruption:

  • High-throughput screening for small molecules that disrupt TPD52L1 interactions with ATM

  • Structure-based drug design targeting the mapped interaction domains (TPD52L1 residues 111-131)

• Combination therapy strategies:

  • Investigating synergistic effects between TPD52L1 modulation and DNA damage-inducing chemotherapeutics

  • Exploring the impact of TPD52L1 inhibition on PARP inhibitor sensitivity

How might advanced imaging techniques enhance our understanding of TPD52L1 localization and dynamics during DNA damage response?

Advanced imaging approaches for studying TPD52L1 dynamics include:

• Live-cell imaging techniques:

  • FRAP (Fluorescence Recovery After Photobleaching) to study TPD52L1 mobility

  • FRET (Förster Resonance Energy Transfer) to examine real-time interactions with ATM and other partners

  • Optogenetic tools to modulate TPD52L1 activity with spatiotemporal precision

• Super-resolution microscopy:

  • STORM/PALM imaging to visualize TPD52L1 nanoscale organization in nuclear repair foci

  • SIM (Structured Illumination Microscopy) to track TPD52L1 recruitment to DNA damage sites

• Correlative light and electron microscopy (CLEM):

  • Combining fluorescence microscopy with EM to study TPD52L1 localization at ultrastructural levels

  • ImmunoEM to visualize TPD52L1 in the context of chromatin and nuclear architecture

• Multiplexed imaging:

  • Multiplexed immunofluorescence to simultaneously track TPD52L1, ATM, γH2AX, and other DDR proteins

  • Mass cytometry imaging to analyze dozens of proteins in the TPD52L1 interaction network

• 4D imaging approaches:

  • Time-lapse confocal microscopy to track TPD52L1 dynamics throughout the DNA damage response

  • Light sheet microscopy for extended imaging with minimal phototoxicity

Current immunofluorescence protocols using TPD52L1 antibodies at 1:20-1:200 dilutions in cell lines like MCF-7 and U2OS provide a foundation for these advanced imaging approaches.

What computational approaches might help predict new functional roles and interaction partners for TPD52L1?

Computational methods to explore TPD52L1 function include:

• Structural biology approaches:

  • Homology modeling of TPD52L1 based on related protein structures

  • Molecular dynamics simulations to understand TPD52L1 conformational dynamics

  • Protein-protein docking to predict interaction interfaces with ATM and other partners

  • Analysis of the coiled-coil domain and its role in protein-protein interactions

• Network biology analysis:

  • Protein-protein interaction network expansion using databases and text mining

  • Pathway enrichment analysis to place TPD52L1 in cellular signaling contexts

  • Functional module identification to discover coordinated activities

• Multi-omics data integration:

  • Correlation of TPD52L1 expression with transcriptomic, proteomic, and phosphoproteomic data

  • Identification of co-expressed gene modules across cancer datasets

  • Analysis of synthetic lethal interactions to identify potential therapeutic vulnerabilities

• Machine learning applications:

  • Prediction of post-translational modification sites on TPD52L1

  • Classification of cancer types based on TPD52L1 expression patterns

  • Deep learning approaches to predict protein functions from sequence data

• Functional site prediction tools:

  • ELM (Eukaryotic Linear Motif) has been successfully used to identify functional sites in TPD52L1

  • Similar approaches can predict additional binding motifs, localization signals, and regulatory elements