PIK3AP1 Antibody, HRP conjugated

What is PIK3AP1 and why is it important in cell signaling research?

PIK3AP1, also known as B-cell adapter for phosphoinositide 3-kinase (BCAP), is a signaling adapter protein that contributes significantly to B-cell development by linking B-cell receptor (BCR) signaling to the phosphoinositide 3-kinase (PI3K)-Akt signaling pathway. It provides a docking site for the PI3K subunit PIK3R1, complementing the role of BCR coreceptor CD19 in coupling BCR and PI3K activation. Beyond B cells, PIK3AP1 links Toll-like receptor (TLR) signaling to PI3K activation—a process that prevents excessive inflammatory cytokine production—and participates in PI3K activation in natural killer cells. PIK3AP1 may also promote survival of mature B-cells through REL activation .

What are the technical specifications of commercially available PIK3AP1 Antibody, HRP conjugated?

The commercially available PIK3AP1 Antibody, HRP conjugated (e.g., product A68968-100) is a polyclonal antibody derived from rabbit hosts with IgG isotype specificity. The antibody is generated using recombinant Human Phosphoinositide 3-kinase adapter protein 1 protein (293-404AA) as the immunogen. It specifically targets human PIK3AP1 and is purified using Protein G methods. The product is supplied in a buffer containing 0.03% Proclin 300, 50% Glycerol, and 0.01M PBS at pH 7.4, with a standard volume of 100 μl .

What is the correct storage protocol for maintaining antibody activity?

For optimal maintenance of antibody activity, PIK3AP1 Antibody, HRP conjugated should be shipped at 4°C. Upon receipt, store the antibody at -20°C for short-term usage or -80°C for long-term storage. It is crucial to avoid repeated freeze-thaw cycles as this can significantly compromise antibody functionality. For research applications requiring frequent usage, consider preparing small aliquots to minimize freeze-thaw cycles .

How should ELISA protocols be optimized when using PIK3AP1 Antibody, HRP conjugated?

For optimal ELISA protocols using PIK3AP1 Antibody, HRP conjugated:

• Coating: Use purified PIK3AP1 protein or cell lysates containing PIK3AP1 to coat plates at 1-10 μg/ml in carbonate buffer (pH 9.6) overnight at 4°C.

• Blocking: Block with 3-5% BSA or non-fat milk in PBS-T (PBS with 0.05% Tween-20) for 1-2 hours at room temperature.

• Antibody dilution: Start with a 1:1000 dilution of the PIK3AP1 Antibody, HRP conjugated and perform titration experiments (1:500, 1:1000, 1:2000, 1:5000) to determine optimal signal-to-noise ratio.

• Detection: Use TMB (3,3',5,5'-Tetramethylbenzidine) substrate for HRP detection, with reaction timing typically between 5-30 minutes depending on signal development.

• Standard curve: Include a standard curve using recombinant PIK3AP1 protein ranging from 0.1-1000 ng/ml to ensure quantitative accuracy.

This approach should be further optimized for each specific experimental system to obtain reliable results .

How can cross-reactivity be assessed and minimized when using PIK3AP1 antibodies?

To assess and minimize cross-reactivity with PIK3AP1 antibodies:

• Assessment methods:

  • Perform Western blot analysis with recombinant proteins from related family members

  • Use cell lines with PIK3AP1 knockout/knockdown as negative controls

  • Compare staining patterns across multiple antibody clones targeting different epitopes

• Minimization strategies:

  • Pre-absorb the antibody with recombinant proteins of closely related family members

  • Optimize antibody concentration to minimize non-specific binding

  • Include appropriate blocking agents (5% BSA or non-fat milk)

  • Include 0.1-0.5% Triton X-100 in wash buffers to reduce hydrophobic interactions

  • Increase wash stringency by adding up to 500mM NaCl to wash buffers

Cross-reactivity assessment is particularly important when studying the PI3K pathway due to structural similarities between adaptor proteins .

What are the recommended approaches for validating PIK3AP1 Antibody, HRP conjugated in different experimental systems?

Comprehensive validation of PIK3AP1 Antibody, HRP conjugated should include:

For tissue-specific research, validation should be conducted in the specific tissue/cell types of interest, as PIK3AP1 expression varies across hematopoietic cell populations .

How can PIK3AP1 Antibody, HRP conjugated be utilized to investigate the PI3K/AKT signaling pathway in cancer research?

PIK3AP1 Antibody, HRP conjugated can be strategically employed in cancer research to:

• Quantify PIK3AP1 expression levels: Use ELISA to measure PIK3AP1 protein expression across cancer cell lines, patient samples, and normal controls to establish correlation with cancer progression.

• Monitor PIK3AP1-PI3K interaction dynamics: Develop sandwich ELISA assays using PIK3AP1 Antibody, HRP conjugated to detect PIK3AP1-PI3K complexes in response to various stimuli or treatments.

• Study miRNA regulation: Investigate how miRNAs like miR-1246 regulate PIK3AP1 expression and downstream PI3K/AKT signaling in cancer models. Recent research has demonstrated that miR-1246 affects the PI3K/AKT signaling pathway by targeting PIK3AP1, thereby inhibiting the development of thyroid cancer .

• Evaluate treatment responses: Use the antibody to monitor PIK3AP1 expression changes following treatment with PI3K/AKT pathway inhibitors to evaluate efficacy and resistance mechanisms.

• Investigate feedback loops: Explore the recently described miR-567-PIK3AP1-PI3K/AKT-c-Myc feedback loop that regulates tumor growth and chemoresistance in gastric cancer .

These approaches can provide significant insights into the role of PIK3AP1 in cancer development and potential therapeutic strategies targeting the PI3K/AKT pathway.

What are the critical considerations for experimental design when studying PIK3AP1 in B-cell signaling pathways?

When designing experiments to study PIK3AP1 in B-cell signaling:

• Proper controls selection: Include both PIK3AP1 knockout models and CD19 knockout models to distinguish BCAP-dependent from CD19-dependent PI3K activation. Research has shown that BCAP (PIK3AP1) has a complementary role to the BCR coreceptor CD19 in coupling BCR and PI3K activation .

• Time-course considerations: Design experiments with appropriate time points (0, 5, 15, 30, 60, 120 minutes) after BCR stimulation to capture the dynamic recruitment of PIK3AP1 to signaling complexes.

• Stimulus selection: Compare different stimuli (anti-IgM, anti-CD40, IL-4, LPS) to activate distinct pathways that may differentially involve PIK3AP1.

• Cell population heterogeneity: Sort B-cell subpopulations (transitional, follicular, marginal zone) before analysis, as PIK3AP1 function may vary across developmental stages.

• Model system selection: Consider both cell lines and primary cells, as studies have shown that BCAP KO B cells do not have defects in differentiating into activated B cells, antibody-secreting cells, or in secreting antibodies in certain contexts .

• Phosphorylation status analysis: Include phospho-specific readouts for PI3K pathway components to connect PIK3AP1 activity to downstream signaling events.

These considerations will help generate more robust and interpretable data when investigating the role of PIK3AP1 in B-cell biology.

How can optimal experimental design be implemented to accurately determine PIK3AP1 signaling kinetics?

To accurately determine PIK3AP1 signaling kinetics, implement these optimal experimental design principles:

• Time-resolved measurements: Collect data at logarithmically spaced time points (e.g., 0, 1, 3, 10, 30, 100, 300 minutes) to capture both rapid early events and slower later processes.

• Perturbation strategies: Use reversible PI3K inhibitors at various concentrations and apply mathematical modeling to extract rate constants from inhibitor response curves. This approach has proven powerful in minimizing the number of experiments needed to infer biological parameters from cell signaling assays .

• Single-cell analysis: Employ flow cytometry or microscopy-based approaches to account for cell-to-cell variability in PIK3AP1 signaling dynamics.

• Parameter estimation: Utilize computational methods for parameter estimation, as studies have shown that intuitive measurement protocols often fail to generate data that restrict the range of possible parameter values .

• Iterative design: Implement iterative cycles of experimentation and computational modeling to progressively refine experimental conditions, as this strategy has been shown to dramatically reduce parameter uncertainty (with mean variance of estimates dropping more than sixty-fold in some studies) .

• Multiplexed measurements: Simultaneously measure multiple components of the pathway (PIK3AP1, PI3K, AKT) to constrain model parameters and improve parameter estimation accuracy.

This methodologically rigorous approach ensures more accurate determination of signaling kinetics compared to traditional, intuitive experimental designs.

How should researchers address inconsistent results when using PIK3AP1 Antibody, HRP conjugated in ELISA applications?

When encountering inconsistent ELISA results with PIK3AP1 Antibody, HRP conjugated:

• Antibody stability assessment:

  • Verify storage conditions (-20°C short-term, -80°C long-term)

  • Check for visible precipitates in antibody solution

  • Prepare fresh working dilutions for each experiment

• Protocol optimization:

  • Titrate antibody concentration more precisely (1:1000, 1:2000, 1:5000, 1:10000)

  • Optimize blocking buffer composition (compare BSA vs. casein vs. non-fat milk)

  • Adjust incubation times and temperatures for antigen-antibody binding

• Sample preparation standardization:

  • Ensure consistent cell lysis methods

  • Quantify total protein concentration in all samples

  • Standardize sample dilutions across experiments

• Detection system verification:

  • Check HRP activity using control substrates

  • Evaluate TMB substrate freshness and storage conditions

  • Consider alternative detection methods if inconsistency persists

• Positive and negative controls:

  • Include recombinant PIK3AP1 protein as positive control

  • Use samples from PIK3AP1 knockout models as negative controls

What strategies can help differentiate between true PIK3AP1 signals and background in complex biological samples?

To differentiate true PIK3AP1 signals from background in complex samples:

• Validation with multiple detection methods:

  • Confirm ELISA results with Western blot or immunoprecipitation

  • Use non-HRP conjugated PIK3AP1 antibodies targeting different epitopes

  • Apply mass spectrometry to verify protein identity in immunoprecipitates

• Sample pre-treatment optimization:

  • Deplete abundant proteins that may cause non-specific binding

  • Perform differential centrifugation to enrich membrane fractions where signaling complexes reside

  • Use phosphatase inhibitors to preserve phosphorylation-dependent interactions

• Advanced control strategies:

  • Include isotype-matched irrelevant antibodies as negative controls

  • Prepare serial dilutions of samples to verify signal linearity

  • Use competitive binding with free PIK3AP1 peptide to confirm signal specificity

• Data normalization approaches:

  • Normalize to housekeeping proteins

  • Apply background subtraction algorithms

  • Use ratio metrics comparing signal to pre-immune serum background

How can researchers interpret PIK3AP1 expression data in the context of PI3K pathway activity?

To properly interpret PIK3AP1 expression data in relation to PI3K pathway activity:

• Correlation with pathway activation markers:

  • Always measure phosphorylation status of key downstream effectors (p-AKT, p-S6K, p-4EBP1)

  • Calculate correlation coefficients between PIK3AP1 levels and phosphorylation of pathway components

  • Consider the ratio of PIK3AP1 to total PI3K as a metric of potential pathway engagement

• Context-dependent interpretation:

  • In B cells: Interpret PIK3AP1 function in the context of BCR signaling and CD19 co-receptor activity

  • In other immune cells: Consider TLR signaling context and inflammatory responses

  • In cancer cells: Evaluate in relation to miRNA regulation (e.g., miR-1246, miR-567) and feedback loops

• Temporal dynamics consideration:

  • Determine whether changes in PIK3AP1 expression precede or follow PI3K pathway activation

  • Establish temporal relationship between PIK3AP1 recruitment and PI3K activation

  • Consider the kinetics of PI3K pathway activation in comparison to PIK3AP1 expression changes

• Integrated data analysis:

  • Apply pathway analysis tools to position PIK3AP1 data within the broader signaling network

  • Use computational modeling to predict how PIK3AP1 expression changes might affect pathway output

  • Consider feedback and feedforward loops that may complicate linear interpretation of expression data

What emerging technologies might enhance the utility of PIK3AP1 antibodies in multiparametric analyses?

Several emerging technologies could significantly enhance PIK3AP1 antibody utility:

• Mass cytometry (CyTOF) integration:

  • Metal-conjugated PIK3AP1 antibodies can be incorporated into CyTOF panels

  • Enables simultaneous measurement of PIK3AP1 with 40+ cellular markers

  • Allows correlation of PIK3AP1 expression with cell type, activation state, and other signaling molecules

• Proximity ligation assays (PLA):

  • Can detect PIK3AP1 interactions with binding partners (PI3K, BCR components)

  • Provides spatial resolution of interaction events within cells

  • Enables quantification of interaction frequency in single cells

• CRISPR-based screening with antibody readouts:

  • Combine genome-wide CRISPR screens with PIK3AP1 antibody detection

  • Identify novel regulators of PIK3AP1 expression and function

  • Map genetic dependencies of PIK3AP1 signaling pathways

• Single-cell proteomics:

  • Apply PIK3AP1 antibodies in emerging single-cell proteomic platforms

  • Correlate PIK3AP1 expression with other proteins at single-cell resolution

  • Identify rare cell populations with unique PIK3AP1 signaling characteristics

How might computational modeling improve our understanding of PIK3AP1's role in signaling networks?

Computational modeling can advance understanding of PIK3AP1 signaling through:

• Network topology mapping:

  • Integrate PIK3AP1 antibody-derived data into signaling network models

  • Identify critical nodes and feedback mechanisms in PIK3AP1-mediated signaling

  • Predict system-level responses to perturbations of PIK3AP1 expression or function

• Parameter estimation for kinetic models:

  • Apply optimal experimental design principles to derive precise rate constants for PIK3AP1-related reactions

  • Build ordinary differential equation (ODE) models of PIK3AP1 signaling dynamics

  • Use these models to predict cellular responses under various conditions

• Machine learning approaches:

  • Train models on PIK3AP1 expression data across various cell types and conditions

  • Identify patterns and relationships not apparent in conventional analyses

  • Predict cellular outcomes based on PIK3AP1 expression patterns

• Multi-scale modeling:

  • Link molecular-level PIK3AP1 signaling models to cellular and tissue-level phenotypes

  • Predict how changes in PIK3AP1 function affect higher-order biological processes

  • Guide experimental design for testing model predictions

What are the potential applications of PIK3AP1 antibodies in therapeutic development and biomarker discovery?

PIK3AP1 antibodies could contribute to therapeutics and biomarkers through:

• Cancer biomarker development:

  • Use PIK3AP1 antibodies to assess expression in tumor biopsies

  • Correlate expression with patient outcomes and treatment responses

  • Develop companion diagnostics for PI3K pathway-targeted therapies

  • Investigate the potential of PIK3AP1 as a biomarker in thyroid cancer, where miR-1246 regulates PI3K/AKT signaling by targeting PIK3AP1

• Immunotherapy research:

  • Investigate PIK3AP1's role in immune checkpoint inhibitor responses

  • Target PIK3AP1-dependent pathways to enhance anti-tumor immunity

  • Modulate B-cell and natural killer cell functions through PIK3AP1-targeted approaches

• Drug discovery:

  • Screen for compounds that modulate PIK3AP1-PI3K interactions

  • Develop assays to identify inhibitors of PIK3AP1-dependent signaling

  • Explore the potential of targeting the miR-567-PIK3AP1-PI3K/AKT-c-Myc feedback loop in gastric cancer

• Personalized medicine approaches:

  • Stratify patients based on PIK3AP1 expression or mutation status

  • Tailor treatment strategies based on PIK3AP1-dependent pathway activation

  • Monitor treatment efficacy using PIK3AP1 as a response marker