PIK3R1 Recombinant Monoclonal Antibody

What is PIK3R1 and why is it an important research target?

PIK3R1 encodes the p85α regulatory subunit of class IA phosphatidylinositol 3-kinase (PI3K). The canonical human protein consists of 724 amino acid residues with a molecular mass of 83.6 kDa and exists in up to five different isoforms . PIK3R1 binds to activated (phosphorylated) protein-tyrosine kinases through its SH2 domain, serving as an adapter that mediates the association of the p110 catalytic unit to the plasma membrane . PIK3R1 is widely expressed across multiple tissue types and plays crucial roles in immune cell development and function, making it a significant target for understanding immune dysregulation disorders and potential therapeutic interventions .

What are the primary applications for PIK3R1 recombinant monoclonal antibodies in research?

PIK3R1 antibodies serve multiple research applications, with Western blot being the most widely used technique. Other common applications include ELISA, immunofluorescence, flow cytometry, and immunohistochemistry . These antibodies have been extensively used in research, with over 3,800 citations in scientific literature describing their applications . Recombinant monoclonal antibodies provide advantages over conventional polyclonal antibodies, including higher specificity, batch-to-batch consistency, and reduced background signals, making them particularly valuable for detecting specific PIK3R1 isoforms or phosphorylation states.

How do I select the appropriate PIK3R1 antibody clone for my experiments?

When selecting a PIK3R1 recombinant monoclonal antibody, consider the following factors:

• Epitope specificity: Determine whether the antibody recognizes a specific domain, isoform, or phosphorylation site of PIK3R1

• Species reactivity: Confirm cross-reactivity with your experimental species (human, mouse, rat, etc.)

• Application validation: Verify that the antibody has been validated for your intended application (WB, IHC, IF, FC)

• Clone performance: Review published literature citing specific clones (e.g., clone 6G10, VS3-CJ80, or 13E7)

• Antibody format: Consider whether unconjugated or conjugated (HRP, biotin, fluorophores) formats are needed

When studying phosphorylation-dependent functions, antibodies specifically recognizing phospho-PIK3R1 (such as Y467/Y199 or Y607) should be selected for accurate assessment of activation states .

What are the optimal protocols for Western blot detection of PIK3R1?

For Western blot detection of PIK3R1:

• Sample preparation:

  • Use RIPA buffer supplemented with protease and phosphatase inhibitors

  • Load 20-40 μg of total protein per lane

  • Include reducing agent in sample buffer

• Electrophoresis and transfer:

  • Use 8-10% SDS-PAGE gels for optimal resolution around 85 kDa

  • Transfer to PVDF membrane (rather than nitrocellulose) for stronger protein binding

• Antibody incubation:

  • Block with 5% BSA in TBST (not milk, which contains phosphatases)

  • Dilute primary antibody 1:1000-1:2000 in blocking buffer

  • Incubate overnight at 4°C with gentle rocking

  • Wash extensively (5 × 5 minutes) with TBST before secondary antibody

• Detection considerations:

  • Expected molecular weight: ~85 kDa for full-length p85α

  • Include positive controls (e.g., Jurkat or MCF-7 cell lysates)

  • For phospho-specific detection, stimulate cells with appropriate activators (e.g., growth factors)

The key challenge is distinguishing between PIK3R1 isoforms, which may require running higher percentage gels (12-15%) with extended separation times.

How should PIK3R1 antibodies be validated before experimental use?

A comprehensive validation strategy for PIK3R1 antibodies should include:

• Specificity testing:

  • Positive/negative cell lines with known PIK3R1 expression

  • siRNA/shRNA knockdown of PIK3R1 to confirm signal reduction

  • Testing in PIK3R1-mutant cell lines (e.g., cells from APDS2 patients)

  • Peptide competition assays to confirm epitope-specific binding

• Application-specific validation:

  • For IHC/IF: Include isotype controls and antigen retrieval optimization

  • For flow cytometry: Use fluorescence-minus-one (FMO) controls

  • For IP experiments: Compare with non-specific IgG controls

• Cross-reactivity assessment:

  • Test against related proteins (PIK3R2, PIK3R3)

  • Evaluate species cross-reactivity if working with non-human models

• Reproducibility verification:

  • Test across multiple experimental conditions and cell types

  • Compare antibody performance across different lots

This rigorous validation ensures reliable detection of the intended PIK3R1 epitope and minimizes experimental artifacts.

What are the best practices for immunofluorescence staining of PIK3R1?

For optimal immunofluorescence detection of PIK3R1:

• Cell preparation:

  • Culture cells on poly-L-lysine coated coverslips

  • Fix with 4% paraformaldehyde (10 minutes at room temperature)

  • Permeabilize with 0.1% Triton X-100 (5 minutes)

• Antibody staining:

  • Block with 5% normal serum in PBS/0.1% Triton X-100

  • Dilute primary antibody 1:100-1:500 in blocking solution

  • Incubate 2 hours at room temperature or overnight at 4°C

  • Use fluorophore-conjugated secondary antibodies at 1:500-1:1000

• Image acquisition:

  • Expected staining pattern: Primarily cytoplasmic with potential membrane localization upon activation

  • Co-stain with markers for plasma membrane (e.g., wheat germ agglutinin) or other PI3K pathway components

• Controls:

  • Include secondary-only controls

  • Compare staining with multiple PIK3R1 antibodies recognizing different epitopes

  • Include stimulated and unstimulated conditions to observe translocation

Counterstaining with DAPI and phalloidin can provide nuclear and cytoskeletal context to better understand PIK3R1 localization patterns.

How can PIK3R1 recombinant antibodies be used to study immune dysregulation disorders?

PIK3R1 recombinant monoclonal antibodies are valuable tools for studying immune dysregulation disorders, particularly APDS2 (activated PI3Kδ syndrome 2) caused by loss-of-function mutations in PIK3R1 :

• Patient sample analysis:

  • Detect altered expression of PIK3R1 protein in patient-derived lymphocytes

  • Analyze changes in downstream signaling by measuring phosphorylation of AKT, S6, and other effectors

  • Compare PIK3R1 expression between different immune cell subsets (B cells, T cells, etc.)

• Functional assessment:

  • Use antibodies in flow cytometry to correlate PIK3R1 expression with markers of lymphocyte differentiation

  • Apply phospho-specific antibodies to measure baseline and stimulus-induced activation in patient cells

  • Combine with cell sorting to isolate specific populations for further analysis

• Mutation-specific detection:

  • Design antibodies that specifically recognize wild-type but not mutant PIK3R1 (e.g., exon 11 skipping mutants)

  • Use for screening potential patients or monitoring allele-specific expression

• Therapeutic monitoring:

  • Track PIK3R1 and downstream pathway activation in patient samples during targeted therapy

  • Assess normalization of signaling with PI3K inhibitor treatment

These approaches provide mechanistic insights into how PIK3R1 mutations disrupt normal immune function and contribute to lymphoproliferative disorders .

What are the considerations when using PIK3R1 antibodies in conjunction with PI3K pathway inhibitors?

When using PIK3R1 antibodies to evaluate PI3K pathway inhibition:

• Inhibitor-induced conformational changes:

  • Consider how inhibitors may alter epitope accessibility

  • Some inhibitors may stabilize or disrupt PI3K complex formation, affecting antibody recognition

  • Test antibody detection in the presence of the inhibitor in control experiments

• Temporal dynamics:

  • Design time-course experiments to capture both immediate and delayed effects

  • Some inhibitors may initially increase complex formation before disrupting it

  • Use phospho-specific antibodies to monitor kinetics of pathway inactivation

• Isoform selectivity:

  • Determine whether inhibitors differentially affect complexes containing various p110 catalytic subunits

  • Use co-immunoprecipitation with PIK3R1 antibodies to analyze changes in complex composition

• Feedback mechanisms:

  • Monitor compensatory changes in PIK3R1 expression or phosphorylation

  • Assess potential upregulation of alternative regulatory subunits (PIK3R2, PIK3R3)

This approach enables comprehensive assessment of how PI3K pathway inhibitors affect not only downstream signaling but also the composition and conformation of PI3K complexes themselves.

How can phospho-specific PIK3R1 antibodies enhance our understanding of PI3K signaling dynamics?

Phospho-specific PIK3R1 antibodies offer unique insights into PI3K signaling dynamics:

• Regulatory mechanisms:

  • Detect site-specific phosphorylation events (e.g., Y467/Y199, Y607) that modulate p85α function

  • Monitor phosphorylation kinetics in response to various stimuli (growth factors, cytokines, etc.)

  • Assess the impact of specific kinases or phosphatases on PIK3R1 activation state

• Spatial organization:

  • Use immunofluorescence with phospho-specific antibodies to visualize where in the cell PIK3R1 becomes activated

  • Combine with super-resolution microscopy to analyze nanoscale organization of active PI3K complexes

  • Implement proximity ligation assays to detect interaction with specific phosphorylated receptors

• Pathway crosstalk:

  • Investigate how signals from different receptors converge on PIK3R1 phosphorylation

  • Examine the relationship between PIK3R1 phosphorylation and activation of other signaling pathways

• Pathological alterations:

  • Compare phosphorylation patterns between normal and disease states

  • Analyze how mutations in PIK3R1 or interacting proteins affect phosphorylation dynamics

This detailed phosphorylation analysis provides mechanistic insights beyond what can be achieved with antibodies to total PIK3R1 protein.

How can non-specific binding issues with PIK3R1 antibodies be addressed?

Non-specific binding is a common challenge with PIK3R1 antibodies that can be addressed through:

• Blocking optimization:

  • Test different blocking agents (BSA, normal serum, commercial blockers)

  • Increase blocking time (2 hours to overnight)

  • Add 0.1-0.3% Tween-20 to reduce hydrophobic interactions

• Antibody dilution testing:

  • Perform titration experiments to determine optimal concentration

  • Start with manufacturer's recommendation and test 2-3 dilutions above and below

  • Balance signal intensity with background reduction

• Sample preparation refinements:

  • Pre-clear lysates with Protein A/G beads before immunoprecipitation

  • For tissue sections, include avidin/biotin blocking steps if using biotinylated detection systems

  • Use freshly prepared samples to minimize protein degradation and epitope modification

• Alternative antibody selection:

  • Compare recombinant monoclonal antibodies targeting different epitopes

  • Consider using directly conjugated primary antibodies to eliminate secondary antibody cross-reactivity

  • Test antibodies from different manufacturers that may have different production methods

Implementing these strategies can significantly improve signal-to-noise ratio and ensure accurate detection of PIK3R1.

What are the best approaches for distinguishing between PIK3R1 isoforms and related family members?

To differentiate between PIK3R1 isoforms and related family members:

• Isoform-specific detection:

  • Select antibodies raised against regions unique to specific isoforms

  • Use isoform-specific primers for RT-PCR validation alongside antibody detection

  • Run higher percentage gels (12-15%) with extended separation time to resolve similar-sized isoforms

• Family member discrimination:

  • Compare sequence homology between PIK3R1, PIK3R2, and PIK3R3 in the antibody epitope region

  • Validate specificity using cells with knockdown/knockout of individual family members

  • Perform peptide competition assays with peptides corresponding to homologous regions

• Complementary techniques:

  • Combine immunoblotting with mass spectrometry for definitive protein identification

  • Use RNA interference to selectively deplete specific isoforms and confirm antibody specificity

  • Implement gene editing to tag endogenous proteins for unambiguous detection

• Expression pattern analysis:

  • Compare detection patterns with known tissue-specific expression profiles of different isoforms

  • Use cell types with documented differential expression of PIK3R family members

This multi-faceted approach ensures accurate discrimination between highly similar PI3K regulatory subunits.

How should experimental data be interpreted when antibodies detect unexpected PIK3R1 band patterns?

When encountering unexpected band patterns with PIK3R1 antibodies:

• Post-translational modifications:

  • Multiple bands may represent differentially phosphorylated or otherwise modified forms

  • Treat samples with phosphatases or other enzymes to determine if bands collapse to a single species

  • Use phospho-specific antibodies to confirm modification status

• Proteolytic processing:

  • Compare fresh samples with those stored for different periods to assess degradation

  • Include protease inhibitors during sample preparation

  • Analyze band patterns with antibodies targeting different epitopes to map potential cleavage sites

• Alternative splicing:

  • Consider known splice variants (including pathological variants like exon 11 skipping)

  • Correlate protein detection with RT-PCR analysis of splice variants

  • Compare samples from different tissues known to express different isoforms

• Cross-reactivity assessment:

  • Perform immunoprecipitation followed by mass spectrometry to identify proteins in each band

  • Test antibodies in cells with CRISPR-mediated PIK3R1 knockout as negative controls

  • Consider related family members with sequence homology in the antibody epitope region

This systematic approach helps distinguish biologically relevant signals from technical artifacts when interpreting complex band patterns.

How can PIK3R1 recombinant antibodies be employed in studying lymphocyte differentiation?

PIK3R1 recombinant antibodies provide valuable tools for investigating lymphocyte differentiation:

• Developmental stage analysis:

  • Use flow cytometry with PIK3R1 antibodies to track expression levels across B and T cell developmental stages

  • Compare PIK3R1 expression patterns in wild-type versus PIK3R1 mutant lymphocytes

  • Correlate PIK3R1 expression with key developmental markers to identify stage-specific requirements

• Functional assessment:

  • Analyze how PIK3R1 mutations affect B cell follicular development and marginal zone B cell formation

  • Study the impact of PIK3R1 dysfunction on class switching and affinity maturation

  • Investigate T cell differentiation into effector and memory subsets under PIK3R1 deficiency

• Signaling pathway integration:

  • Use phospho-specific antibodies to track activation states during lymphocyte stimulation

  • Perform co-immunoprecipitation to identify stage-specific binding partners

  • Analyze how PIK3R1 interacts with antigen receptor signaling components at various developmental stages

• Comparative analysis:

  • Contrast the effects of PIK3R1 loss-of-function with PIK3CD gain-of-function on lymphocyte development

  • Use antibodies to track differences in protein expression and localization between these conditions

These approaches provide insights into how PIK3R1 contributes to normal lymphocyte development and how its dysfunction leads to immunodeficiency and lymphoproliferation .

What are the considerations for using PIK3R1 antibodies in immunoprecipitation studies?

For successful immunoprecipitation (IP) of PIK3R1:

• Antibody selection:

  • Choose antibodies validated specifically for IP applications

  • Consider epitope location relative to known protein interaction domains

  • Select clones that recognize native (non-denatured) protein conformation

• Lysis conditions:

  • Use mild lysis buffers (e.g., NP-40 or digitonin-based) to preserve protein-protein interactions

  • Include phosphatase inhibitors to maintain phosphorylation-dependent interactions

  • Adjust salt concentration (150-300 mM) to optimize specificity while maintaining interactions

• Experimental controls:

  • Include isotype-matched IgG as negative control

  • Perform reciprocal IP with antibodies against known interaction partners

  • Include input controls (5-10% of lysate used for IP)

• Co-IP applications:

  • Investigate PIK3R1 association with p110 catalytic subunits

  • Study interaction with activated receptor tyrosine kinases

  • Examine recruitment of effector proteins to the PI3K complex

• Analysis methods:

  • Probe immunoblots for both PIK3R1 and interacting proteins

  • Consider mass spectrometry to identify novel binding partners

  • Use proximity ligation assays as complementary in situ interaction detection

These approaches enable detailed analysis of PIK3R1's dynamic interactions under different cellular conditions.

How can PIK3R1 antibodies contribute to understanding disease mechanisms beyond immunodeficiency?

PIK3R1 antibodies facilitate research into diverse pathological conditions:

• Cancer biology:

  • Analyze PIK3R1 expression and phosphorylation status across tumor types

  • Correlate PIK3R1 alterations with cancer progression and treatment response

  • Study how cancer-associated PIK3R1 mutations affect protein interactions and localization

• Metabolic disorders:

  • Investigate PIK3R1 involvement in insulin signaling and glucose homeostasis

  • Examine tissue-specific expression patterns in metabolic disease models

  • Analyze how PIK3R1 participates in adipocyte differentiation and function

• Neurodegenerative diseases:

  • Study PIK3R1 expression in neuronal populations affected by neurodegeneration

  • Assess PIK3R1's role in neuronal survival and autophagy regulation

  • Investigate PIK3R1-dependent signaling in microglia and neuroinflammation

• Developmental biology:

  • Track PIK3R1 expression during embryonic development

  • Analyze tissue-specific functions using conditional knockout models

  • Investigate how PIK3R1 mutations affect organ development and function

These diverse applications highlight PIK3R1's fundamental importance across multiple biological systems and disease contexts beyond its well-characterized roles in immune function.

What statistical approaches are recommended for quantifying PIK3R1 expression across different experimental conditions?

For robust quantification of PIK3R1 expression:

• Western blot analysis:

  • Normalize PIK3R1 band intensity to appropriate loading controls (β-actin, GAPDH, or total protein)

  • Use at least three biological replicates for statistical power

  • Apply densitometry software with background subtraction

  • Consider fold-change relative to control rather than absolute values

• Flow cytometry quantification:

  • Report median fluorescence intensity (MFI) rather than mean

  • Use matched isotype controls for background subtraction

  • Calculate staining index: (MFI sample - MFI control)/standard deviation of control

  • Apply appropriate transformations (e.g., biexponential) for low-expression populations

• Immunohistochemistry scoring:

  • Implement H-score method (intensity × percentage of positive cells)

  • Use digital pathology software for unbiased quantification

  • Analyze multiple fields per sample (minimum 5-10)

• Statistical testing:

  • Apply paired t-tests for before/after comparisons within the same samples

  • Use ANOVA with appropriate post-hoc tests for multiple group comparisons

  • Consider non-parametric alternatives (Mann-Whitney, Kruskal-Wallis) for non-normally distributed data

  • Report effect sizes alongside p-values

These approaches ensure reproducible and statistically sound quantification of PIK3R1 expression changes.

How should conflicting results between different PIK3R1 antibody clones be reconciled?

When facing discrepancies between different PIK3R1 antibody clones:

• Epitope mapping analysis:

  • Determine the specific epitopes recognized by each antibody

  • Consider whether epitopes might be differentially accessible in various experimental conditions

  • Test whether post-translational modifications affect epitope recognition

• Validation hierarchy:

  • Prioritize results from antibodies with more extensive validation

  • Consider genetic approaches (siRNA, CRISPR) to confirm specificity

  • Test antibodies in systems with known PIK3R1 expression patterns

• Methodological considerations:

  • Evaluate whether discrepancies are application-specific (e.g., WB vs. IHC)

  • Assess fixation, antigen retrieval, or other technical variables

  • Test different lots of the same antibody to rule out batch effects

• Reconciliation approach:

  • Use multiple antibodies targeting different epitopes in parallel

  • Implement orthogonal detection methods (mass spectrometry, RNA analysis)

  • Consider whether discrepancies reveal biologically relevant information about protein conformation or interactions

This systematic approach transforms conflicting results into opportunities for deeper understanding of PIK3R1 biology.

What are the best practices for integrating PIK3R1 antibody data with other omics datasets?

For effective integration of antibody-based PIK3R1 data with other omics approaches:

• Multi-omics correlation analysis:

  • Compare protein expression (antibody-based) with mRNA levels (transcriptomics)

  • Correlate PIK3R1 protein levels with phosphoproteomics data for downstream effectors

  • Integrate with metabolomics to connect PI3K signaling to metabolic outcomes

• Temporal alignment considerations:

  • Account for time delays between transcriptional, translational, and post-translational events

  • Design time-course experiments with appropriate sampling for each data type

  • Apply time-series analysis methods to capture dynamic relationships

• Single-cell integration approaches:

  • Combine antibody-based flow cytometry with single-cell RNA-seq

  • Use computational methods like CITE-seq or cellular indexing of transcriptomes and epitopes

  • Apply dimensionality reduction and clustering to identify cell populations with distinct PIK3R1-related phenotypes

• Pathway-level integration:

  • Map antibody-detected PIK3R1 activation to pathway-level changes in transcriptomics data

  • Use knowledge-based approaches (Gene Ontology, pathway enrichment) to interpret integrated datasets

  • Apply network analysis to identify regulatory hubs connected to PIK3R1 function

This integrative approach provides a comprehensive understanding of PIK3R1's role within cellular signaling networks across multiple biological layers.