PPP1CA Antibody, Biotin conjugated

What is PPP1CA and why is it an important research target?

PPP1CA (Protein Phosphatase 1, Catalytic Subunit, alpha Isoform) is one of the three catalytic subunits of protein phosphatase 1. This protein is highly conserved in eukaryotic cells and plays crucial roles in dephosphorylating various cellular substrates. PPP1CA participates in the regulation of multiple cellular processes including cell division, glycogen metabolism, muscle contractility, protein synthesis, and apoptosis . Research on PPP1CA is significant due to its involvement in fundamental cellular functions and its association with over 200 regulatory proteins to form highly specific holoenzymes which dephosphorylate hundreds of biological targets .

The catalytic subunit of PPP1CA is a particularly important research target as it forms the core of various protein phosphatase complexes that have distinct functions depending on their regulatory subunits. Understanding how these complexes function is essential for elucidating cell signaling pathways and developing potential therapeutic interventions for diseases involving dysregulated phosphorylation.

What are the key specifications of the PPP1CA Antibody, Biotin conjugated?

The biotin-conjugated PPP1CA antibody has the following specifications:

These specifications are crucial for experimental planning and ensure appropriate application of the antibody in research settings.

How does the biotin conjugation enhance antibody utility in research applications?

The biotin conjugation significantly enhances the utility of PPP1CA antibody in several ways:

• Increased detection sensitivity: The biotin-streptavidin system is one of the strongest non-covalent biological interactions (Kd ≈ 10^-15 M), enabling highly sensitive detection of target proteins even at low expression levels.

• Versatile detection methods: The biotin tag allows for multiple detection strategies using streptavidin conjugated to various reporter molecules (HRP, fluorophores, gold particles), providing flexibility across different experimental platforms .

• Amplification capability: The tetravalent nature of streptavidin means that multiple reporter molecules can bind to a single biotin-conjugated antibody, creating signal amplification for enhanced detection.

• Compatibility with proximity labeling techniques: As evidenced in search results, biotin-based proximity labeling methods like PhotoPPI can be valuable for studying protein-protein interactions involving PPP1CA .

• Reduced background interference: The biotin-streptavidin system often results in lower non-specific binding compared to other detection methods, leading to improved signal-to-noise ratios in experimental readouts.

These enhancements make biotin-conjugated antibodies particularly valuable in studies requiring high sensitivity and specificity, such as investigating low-abundance protein interactions or complex formation involving PPP1CA.

What experimental conditions should be optimized when using PPP1CA Antibody, Biotin conjugated in ELISA?

When optimizing ELISA experiments with biotin-conjugated PPP1CA antibody, researchers should consider the following parameters:

Systematic optimization of these parameters will ensure reliable and reproducible results when using the biotin-conjugated PPP1CA antibody for ELISA applications.

What storage and handling practices maximize the shelf-life of PPP1CA Antibody, Biotin conjugated?

To maximize shelf-life and maintain functionality of biotin-conjugated PPP1CA antibody, follow these research-validated practices:

• Storage temperature: Store at -20°C to -80°C for long-term preservation of antibody activity . Avoid storing at 4°C for extended periods as this can lead to gradual loss of activity.

• Aliquoting strategy: Upon receipt, divide the antibody into small single-use aliquots (10-20 μl) to minimize freeze-thaw cycles. Each freeze-thaw cycle can reduce antibody activity by approximately 10-15% .

• Light protection: Store in amber tubes or wrapped in aluminum foil to protect the biotin conjugate from light exposure, which can degrade the biotin molecule and reduce detection sensitivity .

• Buffer conditions: The antibody is typically provided in a buffer containing 50% glycerol, which prevents freezing at -20°C and maintains protein stability. If dilution is necessary, use buffers containing stabilizing proteins (0.1-1% BSA) and appropriate preservatives .

• Contamination prevention: Use sterile technique when handling antibodies to prevent microbial contamination, which can degrade the antibody and introduce experimental artifacts.

• Transport conditions: If the antibody must be transported between facilities, use dry ice for shipping and monitor temperature to ensure it remains frozen throughout transport.

• Documentation: Maintain detailed records of antibody lot number, receipt date, aliquoting dates, and freeze-thaw cycles to track potential sources of variability in experimental results.

When properly stored and handled, biotin-conjugated antibodies typically maintain activity for 12-18 months, though actual shelf-life may vary based on specific storage conditions and frequency of use.

How can PPP1CA Antibody, Biotin conjugated be employed in proximity labeling studies to identify protein interactions?

Proximity labeling with biotin-conjugated PPP1CA antibody can be implemented through the following methodological approach:

• Experimental design principles: Leverage the biotin conjugate as both a detection tag and a proximity marker by incorporating it into systems like PhotoPPI or adapting methods similar to K-BIPS . This requires careful planning of positive and negative controls to distinguish specific interactions from background labeling.

• Cell preparation protocol:

  • Culture cells expressing PPP1CA or transfect with tagged PPP1CA constructs

  • If using the PhotoPPI approach, introduce the photosensitive proximity probe (PP1)

  • Create appropriate control conditions (e.g., knockdown PPP1CA, use competitor peptides, or employ non-relevant control antibodies)

• Crosslinking and labeling methodology:

  • Optimize antibody concentration and incubation conditions (typically 1-10 μg/ml antibody for 1-4 hours at 4°C or room temperature)

  • If using photoreactive approaches, determine optimal UV exposure parameters (wavelength, duration, intensity)

  • For enzymatic biotinylation methods, optimize enzyme concentration and biotin-substrate availability

• Sample processing procedure:

  • Lyse cells under conditions that preserve protein-protein interactions (e.g., RIPA buffer with protease inhibitors)

  • Enrich biotinylated proteins using streptavidin beads with optimized binding and washing conditions

  • Elute bound proteins using appropriate methods (e.g., biotin competition, reducing agents, or on-bead digestion)

• Analysis and validation protocol:

  • Identify enriched proteins by mass spectrometry using both qualitative and quantitative approaches

  • Implement appropriate statistics to distinguish specific interactions from background

  • Validate key interactions through orthogonal methods (co-immunoprecipitation, FRET, etc.)

This approach can reveal both stable and transient interactions involving PPP1CA, providing insights into its function within different cellular contexts and protein complexes .

How can PPP1CA Antibody, Biotin conjugated be used to study the PP1-Gadd34 complex in unfolded protein response (UPR)?

The biotin-conjugated PPP1CA antibody offers sophisticated approaches to investigate the PP1-Gadd34 complex in UPR through the following methodological framework:

• Experimental system design: Implement a cellular model of UPR using established inducers such as tunicamycin (Tm), which disrupts N-linked glycosylation, or thapsigargin, which depletes ER calcium stores . This should include time-course experiments to capture the dynamic assembly and function of the PP1-Gadd34 complex.

• Analytical approach for complex formation:

  • Use the biotin-conjugated antibody to immunoprecipitate PPP1CA under native conditions

  • Analyze co-precipitated proteins by western blotting for Gadd34 and other potential regulatory subunits

  • Quantify complex formation kinetics relative to UPR induction

  • Compare results across different UPR inducers to distinguish pathway-specific effects

• Substrate identification protocol:

  • Adapt the K-BIPS (Kinase-catalyzed Biotinylation to Identify Phosphatase Substrates) method described in the research literature

  • Combine with selective inhibition of the PP1-Gadd34 interaction using compounds like guanabenz (Gb)

  • Analyze phosphorylation changes in known substrates (e.g., eIF2α) and potential novel substrates

  • Validate findings using phosphatase assays with recombinant PP1-Gadd34 complex

• Spatial-temporal dynamics assessment:

  • Use the biotin-conjugated antibody with streptavidin-fluorophore conjugates for immunofluorescence studies

  • Track localization changes of PPP1CA during UPR progression

  • Implement live-cell imaging if possible to monitor real-time dynamics

  • Correlate PPP1CA localization with UPR markers and cellular outcomes

• Functional impact evaluation:

  • Manipulate PPP1CA levels or activity (knockdown, overexpression, inhibition)

  • Assess effects on UPR signaling branches (PERK, IRE1, ATF6)

  • Measure impact on cell survival, protein synthesis, and chaperone expression

  • Correlate findings with physiological or pathological UPR conditions

This comprehensive approach would significantly expand our understanding of PP1-Gadd34 beyond its canonical role in eIF2α dephosphorylation, potentially revealing novel functions in UPR regulation and protein homeostasis .

What methodological approaches can resolve the challenge of distinguishing PPP1CA from other PP1 catalytic subunit isoforms (PPP1CB, PPP1CC) in research studies?

Distinguishing between highly homologous PP1 catalytic subunit isoforms presents a significant challenge that can be addressed through these methodological approaches:

• Epitope-specific antibody selection:

  • The biotin-conjugated PPP1CA antibody targeting amino acids 192-330 should be evaluated for potential cross-reactivity with PPP1CB and PPP1CC

  • Compare sequence alignments of the three isoforms in the target region to identify unique epitopes

  • Consider using antibodies targeting post-translational modifications specific to PPP1CA

  • Validate specificity using recombinant proteins of all three isoforms in controlled experiments

• Genetic manipulation strategies:

  • Implement isoform-specific knockdown using validated siRNAs or shRNAs

  • Create CRISPR/Cas9 knockout cell lines for each isoform

  • Introduce epitope-tagged versions of each isoform for specific detection

  • Use rescue experiments with isoform-specific constructs to confirm functional specificity

• Regulatory subunit-based discrimination:

  • Exploit differential binding of regulatory subunits to specific PP1 isoforms

  • Use co-immunoprecipitation with regulatory subunits known to preferentially bind PPP1CA

  • Analyze isoform-specific protein complexes using BioID or proximity labeling approaches

  • Map isoform-specific interactomes to infer functional differences

• Subcellular localization analysis:

  • Determine if PPP1CA has distinct localization patterns compared to other isoforms

  • Use super-resolution microscopy with isoform-specific antibodies or tags

  • Perform subcellular fractionation followed by isoform-specific detection

  • Correlate localization patterns with known functions of each isoform

• Substrate specificity profiling:

  • Develop in vitro assays using recombinant isoforms and substrate arrays

  • Implement K-BIPS methodology with isoform-specific manipulations

  • Perform phosphoproteomic analysis after isoform-specific depletion

  • Identify and validate isoform-specific substrates

These approaches, often used in combination, provide a comprehensive strategy for dissecting the specific roles of PPP1CA versus other PP1 isoforms in complex biological processes while minimizing cross-reactivity issues and ensuring experimental rigor.

How can researchers adapt the K-BIPS method using PPP1CA Antibody, Biotin conjugated to identify novel substrates?

Adapting the K-BIPS (Kinase-catalyzed Biotinylation to Identify Phosphatase Substrates) method with biotin-conjugated PPP1CA antibody involves a sophisticated experimental approach:

• Methodological principle adaptation:
  The K-BIPS method described in the research literature uses kinase-catalyzed biotinylation to identify proteins that become hyperphosphorylated when specific phosphatases are inhibited. The biotin-conjugated PPP1CA antibody can be incorporated into this workflow through the following modifications:

• Experimental setup and controls:

  • Design paired experiments with PPP1CA inhibition or knockdown versus controls

  • Include conditions that distinguish between direct substrates and secondary effects

  • Implement selective inhibition using PPP1CA-specific regulatory protein disruptors

  • Create appropriate negative controls using non-relevant antibodies or inactive PPP1CA mutants

• Modified K-BIPS protocol implementation:

  • Treat cells with phosphatase inhibitors or PPP1CA-specific disruptors (e.g., compounds targeting PP1-regulatory subunit interactions)

  • Apply ATP-biotin for kinase-catalyzed biotinylation of hyperphosphorylated substrates

  • Use the biotin-conjugated PPP1CA antibody to identify proteins that both interact with PPP1CA and become hyperphosphorylated upon its inhibition

  • Compare enrichment patterns between different conditions to identify potential direct substrates

• Advanced quantitative proteomics integration:

  • Implement SILAC, TMT, or label-free quantification for robust statistical analysis

  • Apply stringent filtering criteria based on enrichment ratios and statistical significance

  • Cluster potential substrates based on functional categories and phosphorylation motifs

  • Cross-reference with known phosphoproteomic datasets for validation

• Bioinformatic analysis and substrate validation:

  • Analyze enriched proteins for common phosphorylation motifs and functional categories

  • Perform sequence analysis to identify PP1 consensus dephosphorylation sites

  • Validate top candidates using in vitro dephosphorylation assays with recombinant PPP1CA

  • Confirm physiological relevance through targeted mutations of phosphorylation sites

• Context-specific substrate profiling:

  • Apply the method across different cellular conditions (e.g., cell cycle phases, stress responses)

  • Compare substrate profiles between different PP1 holoenzymes by manipulating regulatory subunits

  • Investigate substrate dynamics in response to specific signaling pathways

This adapted approach leverages the specificity of the biotin-conjugated PPP1CA antibody while incorporating the powerful substrate identification capability of the K-BIPS method to reveal the complex substrate network of PPP1CA in various cellular contexts .

How should researchers interpret variations in PPP1CA detection patterns across different experimental conditions?

Variations in PPP1CA detection patterns require systematic interpretation through these analytical frameworks:

• Expression level variations analysis:

  • Quantify relative expression levels across different cell types, tissues, or experimental conditions

  • Normalize to appropriate housekeeping controls based on experimental context

  • Consider using multiple normalization strategies to confirm trends

  • Interpret changes in the context of known regulators of PPP1CA expression

• Post-translational modification assessment:

  • Evaluate whether detection variations correlate with known phosphorylation states of PPP1CA (e.g., phosphorylation at Thr320)

  • Consider how these modifications might affect antibody binding or protein function

  • Implement phosphatase treatments of samples to determine if modifications affect detection

  • Use phospho-specific antibodies in parallel to correlate modifications with function

• Complex formation interpretation:

  • Analyze whether variations reflect differential association with regulatory subunits

  • Consider how complex formation might mask or expose the epitope recognized by the antibody

  • Compare native versus denaturing conditions to assess complex stability

  • Investigate correlations between PPP1CA detection and the presence of known interacting partners

• Localization pattern evaluation:

  • Assess whether detection variations reflect changes in subcellular localization

  • Correlate localization patterns with known functions in different cellular compartments

  • Consider how localization changes may affect accessibility to the antibody

  • Implement fractionation studies to confirm compartment-specific detection patterns

• Technical variables consideration:

  • Evaluate the impact of sample preparation methods on epitope preservation

  • Assess lot-to-lot variations in antibody performance

  • Consider fixation effects for immunohistochemistry or immunofluorescence applications

  • Implement appropriate positive and negative controls across experiments

• Biological context integration:

  • Interpret variations in relation to cellular processes (cell cycle, differentiation, stress responses)

  • Consider pathway activation states that might affect PPP1CA function or detection

  • Correlate changes with known functional outcomes of PPP1CA activity

  • Place observations within the broader context of phosphatase biology

This multifaceted analytical approach enables researchers to distinguish biologically meaningful variations from technical artifacts and extract maximum information from experimental observations involving PPP1CA.

What are the critical parameters for validating protein-protein interactions identified through PPP1CA antibody-based proximity labeling?

Validating protein-protein interactions identified through PPP1CA antibody-based proximity labeling requires rigorous application of these critical parameters:

• Statistical stringency criteria:

  • Implement appropriate statistical models for distinguishing specific interactions from background

  • Establish significance thresholds based on false discovery rate control (typically FDR < 0.05)

  • Apply fold-enrichment cutoffs appropriate to the experimental system (often ≥1.5-2 fold)

  • Consider both abundance and consistency across replicates in ranking potential interactors

• Control experiment design:

  • Include multiple negative controls (non-relevant antibodies, competing peptides, PPP1CA-depleted samples)

  • Implement "bait-free" controls to identify proteins prone to non-specific labeling

  • Use competition experiments with unlabeled antibody to confirm specificity

  • Consider reversed labeling approaches (e.g., SILAC label swap) to control for technical bias

• Orthogonal validation methods:

  • Confirm key interactions using co-immunoprecipitation with non-conjugated antibodies

  • Implement reciprocal pull-downs using antibodies against the identified interactors

  • Utilize techniques like FRET, BiFC, or PLA to validate interactions in intact cells

  • Consider in vitro binding assays with recombinant proteins for direct interaction confirmation

• Functional relevance assessment:

  • Determine if interacting proteins share functional pathways with PPP1CA

  • Assess co-localization in relevant cellular compartments

  • Evaluate whether interactions change under conditions where PPP1CA function is altered

  • Test the functional impact of disrupting specific interactions

• Structural and motif analysis:

  • Search for known PP1-binding motifs (RVxF, SILK, MyPhoNE) in identified interactors

  • Perform domain mapping to identify specific interaction regions

  • Consider structural modeling to assess the plausibility of direct interactions

  • Test the effect of mutations in potential binding motifs on interaction strength

• Literature and database integration:

  • Cross-reference with published PPP1CA interactomes and substrate databases

  • Compare with interactions identified for other PP1 isoforms and regulatory subunits

  • Consider evolutionary conservation of interactions across species

  • Place new interactions in the context of known PPP1CA functions and regulatory networks

By systematically addressing these parameters, researchers can distinguish biologically meaningful interactions from experimental artifacts and develop a high-confidence interactome for PPP1CA that advances understanding of its diverse cellular functions .

How can researchers troubleshoot inconsistent results when using PPP1CA Antibody, Biotin conjugated in different experimental contexts?

When encountering inconsistent results with biotin-conjugated PPP1CA antibody, implement this systematic troubleshooting framework:

• Antibody quality assessment:

  • Verify antibody integrity through simple dot blot or ELISA against recombinant PPP1CA

  • Check for potential degradation by running the antibody on a non-reducing SDS-PAGE

  • Assess biotin conjugation efficiency using streptavidin-HRP detection

  • Consider testing multiple lots if available to identify lot-specific issues

  • Implement positive controls using well-characterized samples known to contain PPP1CA

• Epitope accessibility evaluation:

  • Determine if experimental conditions might affect accessibility of the epitope (AA 192-330)

  • Test different sample preparation methods (various lysis buffers, fixation protocols)

  • Consider native versus denaturing conditions based on experimental goals

  • Evaluate whether post-translational modifications might affect epitope recognition

  • Test whether regulatory subunit binding could mask the epitope in certain contexts

• Protocol optimization strategies:

  • Systematically vary antibody concentration across a wide range (1:100 to 1:10,000)

  • Modify incubation conditions (time, temperature, buffer composition)

  • Optimize blocking conditions to reduce background while preserving specific signal

  • Adjust washing stringency based on signal-to-noise considerations

  • Consider the impact of detergents and salt concentration on antibody-antigen interactions

• Cross-reactivity investigation:

  • Assess potential cross-reactivity with other PP1 isoforms through controlled experiments

  • Implement knockdown/knockout validation to confirm signal specificity

  • Test in systems with varying expression levels of related phosphatases

  • Consider species-specific variations that might affect antibody performance

• Context-dependent variable analysis:

  • Evaluate how cellular context (cell type, growth conditions, stress) affects PPP1CA expression or modification

  • Consider cell cycle stage, which can affect PPP1CA localization and complex formation

  • Assess the impact of phosphatase inhibitors or activators that might be present in your system

  • Determine whether other proteins in your experimental system might compete for antibody binding

• Technical troubleshooting checklist:

  • Verify reagent quality, including streptavidin conjugates for detection

  • Check equipment calibration and performance (plate readers, imaging systems)

  • Ensure consistent sample handling across experiments

  • Implement fresh reagent preparation for critical components

  • Consider temperature sensitivity of certain reactions involving the antibody

By systematically addressing these parameters, researchers can identify the sources of inconsistency and develop robust protocols for using biotin-conjugated PPP1CA antibody across different experimental contexts .

How can PPP1CA Antibody, Biotin conjugated be utilized in studying the role of PPP1CA in DNA damage response and non-homologous end joining?

Recent research reveals PPP1CA plays a critical role in DNA damage response, particularly in non-homologous end joining (NHEJ). The biotin-conjugated antibody can be employed through these methodological approaches:

• DNA damage induction and PPP1CA recruitment analysis:

  • Induce DNA double-strand breaks using ionizing radiation, radiomimetic drugs, or site-specific nucleases

  • Use the biotin-conjugated antibody with streptavidin-fluorophore detection to track PPP1CA recruitment to damage sites

  • Implement live-cell imaging with complementary markers of DNA damage response

  • Quantify recruitment kinetics and correlation with damage resolution

• DNA-PK complex interaction studies:

  • Investigate the interaction between PPP1CA and DNA-PKcs using proximity labeling approaches

  • Assess how PPP1CA affects DNA-PKcs phosphorylation at key regulatory sites (Ser-2056 and Thr-2609)

  • Determine the impact of PNUTS (Phosphatase 1 Nuclear Targeting Subunit) on PPP1CA function in this context

  • Map interaction domains between PPP1CA and components of the DNA-PK complex

• Functional impact assessment:

  • Measure NHEJ efficiency after PPP1CA manipulation using reporter assays

  • Assess DNA-PK kinase activity in the presence or absence of functional PPP1CA

  • Determine how PPP1CA affects DNA end processing and ligation

  • Evaluate cell survival and genomic stability after DNA damage in PPP1CA-depleted cells

• Regulatory mechanism dissection:

  • Investigate how regulatory subunits like PNUTS modulate PPP1CA function in DNA repair

  • Assess post-translational modifications of PPP1CA during DNA damage response

  • Determine whether PPP1CA substrate specificity changes in response to DNA damage

  • Map the phosphatase-kinase networks that regulate NHEJ progression

• Therapeutic implications exploration:

  • Investigate whether PPP1CA inhibition sensitizes cells to DNA-damaging agents

  • Assess potential synthetic lethality between PPP1CA inhibition and defects in other repair pathways

  • Explore combination approaches targeting both kinase and phosphatase activities in DNA repair

  • Evaluate PPP1CA as a potential biomarker for DNA repair proficiency

This comprehensive approach leverages the specificity and sensitivity of the biotin-conjugated PPP1CA antibody to elucidate its multifaceted roles in maintaining genomic integrity through regulation of DNA damage response pathways .

What methodological approaches can resolve spatiotemporal dynamics of PPP1CA in live cells?

Resolving the spatiotemporal dynamics of PPP1CA in live cells requires sophisticated methodological approaches that can be enhanced using biotin-conjugated PPP1CA antibody:

• Intrabody-based live imaging strategy:

  • Develop cell-permeable nanobody derivatives of the PPP1CA antibody

  • Conjugate with biotin to allow streptavidin-fluorophore labeling for live imaging

  • Optimize concentration and incubation conditions to achieve specific labeling with minimal perturbation

  • Implement pulse-chase labeling to track distinct populations of PPP1CA over time

• Split-reporter complementation system:

  • Design constructs fusing PPP1CA with one half of a split fluorescent protein

  • Fuse known or suspected interaction partners with the complementary half

  • Use biotin-streptavidin as an orthogonal labeling approach to confirm interactions

  • Measure spatial and temporal dynamics of complex formation in response to cellular stimuli

• FRET/FLIM analysis protocol:

  • Develop FRET pairs using the biotin-conjugated antibody with streptavidin-fluorophore as donor/acceptor

  • Tag suspected interaction partners with complementary fluorophores

  • Measure energy transfer efficiency to determine interaction distances

  • Implement FLIM to distinguish between bound and unbound populations of PPP1CA

• Optogenetic control integration:

  • Combine light-controlled protein interaction modules with PPP1CA

  • Use the biotin-conjugated antibody to track redistribution after optogenetic stimulation

  • Measure functional consequences of induced relocalization

  • Correlate spatial positioning with phosphatase activity using phospho-specific reporters

• Super-resolution microscopy application:

  • Employ PALM/STORM techniques using the biotin-streptavidin system for single-molecule localization

  • Implement structured illumination microscopy (SIM) for enhanced spatial resolution

  • Use lattice light-sheet microscopy for improved temporal resolution with reduced phototoxicity

  • Apply correlative light and electron microscopy to place PPP1CA within ultrastructural context

• Microfluidic and optogenetic integration:

  • Develop microfluidic systems for precise temporal control of stimuli

  • Combine with photocleavable linkers to activate or inactivate PPP1CA at specific locations

  • Integrate biosensor technology to correlate PPP1CA dynamics with substrate dephosphorylation

  • Implement computational modeling to predict spatiotemporal dynamics from experimental data

These approaches, particularly when used in combination, provide unprecedented insight into how PPP1CA localization, mobility, and interaction dynamics contribute to its diverse cellular functions across different cellular compartments and in response to various stimuli.

How can multi-omics approaches incorporate PPP1CA Antibody, Biotin conjugated to discover novel regulatory networks?

Integrating biotin-conjugated PPP1CA antibody into multi-omics frameworks enables comprehensive mapping of PPP1CA-associated regulatory networks through these sophisticated methodological approaches:

• Integrated proteomics-phosphoproteomics workflow:

  • Use the biotin-conjugated antibody for PPP1CA immunoprecipitation under native conditions

  • Perform parallel phosphoproteomic analysis after PPP1CA modulation (inhibition, knockdown)

  • Implement quantitative proteomics (SILAC, TMT) to identify differential regulation

  • Integrate datasets to distinguish direct substrates from secondary effects using computational models

  • Correlate changes in protein abundance with phosphorylation status to identify regulatory hubs

• ChIP-seq adaptation for phosphatase studies:

  • Modify chromatin immunoprecipitation protocols using the biotin-conjugated PPP1CA antibody

  • Map PPP1CA association with chromatin in different cellular contexts

  • Correlate with histone phosphorylation status and gene expression data

  • Identify transcriptional regulatory networks influenced by PPP1CA activity

  • Integrate with chromatin accessibility (ATAC-seq) and 3D chromatin organization (Hi-C) data

• Translatomics integration:

  • Assess how PPP1CA affects translation through ribosome profiling after manipulation

  • Focus on known roles in protein synthesis regulation, particularly during UPR

  • Correlate with phosphorylation status of translation factors (e.g., eIF2α)

  • Develop models of translational regulation networks controlled by PPP1CA

• Metabolomics correlation analysis:

  • Perform metabolomic profiling after PPP1CA modulation

  • Focus on pathways known to be regulated by phosphorylation (glycolysis, TCA cycle)

  • Correlate metabolic changes with alterations in enzyme phosphorylation status

  • Identify metabolic network nodes sensitive to PPP1CA activity

• Single-cell multi-omics approach:

  • Implement single-cell proteomics with PPP1CA activity measurements

  • Correlate with single-cell transcriptomics to identify cell state-specific functions

  • Map heterogeneity in PPP1CA-regulated networks across cell populations

  • Identify regulatory principles that emerge at the single-cell level

• Computational network integration:

  • Develop mathematical models incorporating enzyme kinetics, phosphorylation/dephosphorylation rates

  • Integrate multi-dimensional datasets using machine learning approaches

  • Identify emergent properties of PPP1CA-regulated networks

  • Generate testable hypotheses regarding context-specific functions

• Temporal multi-omics design:

  • Implement time-course experiments after PPP1CA activation or inhibition

  • Track cascade effects across multiple regulatory layers

  • Identify feedback and feedforward loops within the network

  • Develop dynamic models of PPP1CA-regulated processes

This comprehensive multi-omics strategy leverages the specificity of the biotin-conjugated PPP1CA antibody to map the extensive regulatory networks influenced by this phosphatase, providing unprecedented insight into its diverse cellular functions .