PACS2 Antibody, Biotin conjugated

What is PACS2 and what cellular functions would I be investigating with a PACS2 antibody?

PACS2 (phosphofurin acidic cluster sorting protein 2), also known as PACS1L or KIAA0602, is a multifunctional sorting protein with a calculated molecular weight of 98 kDa that typically appears as a 100-130 kDa band on western blots . PACS2 belongs to the phosphofurin acidic cluster sorting protein family that regulates membrane traffic and mediates organ homeostasis .

When investigating PACS2 using antibodies, you would be exploring several key cellular functions:

• Regulation of endoplasmic reticulum (ER)-mitochondria communication

• Maintenance of ER homeostasis

• Control of apoptotic processes

• Ion channel trafficking to distinct subcellular compartments

• Retrograde trafficking from endosomes and from the Golgi

• Regulation of ADAM17 cell-surface availability and subsequent ErbB signaling

Recent functional genome-wide screening identified PACS2 as a critical regulator of ADAM17-mediated shedding . PACS2 interacts with mature ADAM17 in early endocytic compartments, affecting its recycling and stability, thereby sustaining ADAM17 cell-surface activity by preventing its degradation .

How does PACS2 regulate ADAM17 trafficking and ErbB signaling?

PACS2 regulates ADAM17-mediated shedding of ErbB ligands through several specific mechanisms:

• Selective interaction with mature ADAM17: Co-immunoprecipitation experiments revealed that PACS2 primarily interacts with the mature form of ADAM17 in both unstimulated and PMA-stimulated cells .

• Co-localization in early endosomes: Proximity Ligation Assay (PLA) demonstrated that PACS2 and ADAM17 co-localize in early endocytic compartments, with enhanced interaction upon PMA-stimulated ADAM17 internalization .

• Regulation of cell-surface ADAM17 levels: PACS2 knockdown significantly decreases mature ADAM17 at the cell surface without affecting the ADAM17 proenzyme . Cell-surface biotinylation experiments in MDA-MB-231 cells showed reduced cell-surface ADAM17 following PACS2 knockdown .

• Influence on ADAM17 recycling and stability: While PACS2 knockdown does not affect ADAM17 internalization rates, it reduces ADAM17 recycling back to the cell surface and decreases its stability, leading to degradation .

• Specificity for ADAM17: PACS2 selectively regulates ADAM17 without significantly affecting related metalloproteinases like ADAM9, ADAM10, or MT1-MMP .

Through these mechanisms, PACS2 maintains appropriate levels of mature ADAM17 at the cell surface, thereby regulating the shedding of ErbB ligands and subsequent activation of ErbB signaling pathways essential for cellular development, growth, and tumor progression.

What experimental applications are most suitable for biotin-conjugated PACS2 antibodies?

Biotin-conjugated PACS2 antibodies are versatile tools for multiple experimental applications in PACS2 research:

• Western Blotting (WB): For detecting PACS2 expression levels and validating knockdown experiments. Based on recommendations for unconjugated antibodies, starting dilutions of 1:500-1:2000 would be appropriate for biotin-conjugated versions .

• Immunoprecipitation (IP): Particularly valuable for isolating PACS2-interacting protein complexes, such as the PACS2-ADAM17 complex observed in co-immunoprecipitation experiments . The biotin-streptavidin interaction provides a gentle elution option for maintaining complex integrity.

• Immunofluorescence (IF)/Immunocytochemistry (ICC): For studying subcellular localization of PACS2, particularly its co-localization with ADAM17 in early endosomes . Recommended starting dilution range: 1:200-1:800 .

• Proximity Ligation Assay (PLA): This highly sensitive technique has been successfully used to detect PACS2-ADAM17 interactions in situ . Biotin-conjugated antibodies can enhance sensitivity when used with appropriate anti-biotin PLA probes.

• Pull-down assays: For investigating protein-protein interactions under various experimental conditions, such as after stimulation with PMA or physiological stimulants like TNF-α .

What are the typical detection methods for biotin-conjugated PACS2 antibodies?

Biotin-conjugated PACS2 antibodies can be detected using various methods depending on the experimental application:

• Enzyme-linked detection systems:

  • Streptavidin-HRP (horseradish peroxidase) for western blotting and immunohistochemistry

  • Streptavidin-AP (alkaline phosphatase) for applications requiring higher sensitivity or different visualization options

• Fluorescence-based detection:

  • Fluorophore-conjugated streptavidin (e.g., Alexa Fluor 488, 594, 647) for immunofluorescence microscopy

  • Quantum dot-conjugated streptavidin for long-term imaging with minimal photobleaching

• Proximity-based detection systems:

  • Anti-biotin PLA probes for proximity ligation assays to detect protein-protein interactions, as demonstrated for PACS2-ADAM17

  • FRET-based approaches using fluorescent streptavidin as donor/acceptor

• Signal amplification methods:

  • Tyramide signal amplification (TSA) with streptavidin-HRP for detecting low-abundance targets

  • Rolling circle amplification combined with streptavidin detection for single-molecule sensitivity

For optimal results, detection systems should be selected based on experimental requirements for sensitivity, resolution, and compatibility with other reagents in multiplex experiments.

How should I validate the specificity of a biotin-conjugated PACS2 antibody in my experimental system?

Rigorous validation of biotin-conjugated PACS2 antibodies is critical for reliable experimental results. Implement these complementary approaches:

• Genetic knockdown/knockout validation:

  • Perform siRNA knockdown of PACS2 in your experimental cell line. Multiple cell lines have been successfully used for PACS2 knockdown, including MDA-MB-231, HeLa, and MCF-7 cells .

  • If available, use Pacs2-deficient cells (e.g., Pacs2−/− MEFs) as negative controls .

  • Verify reduction in antibody signal by western blot and immunofluorescence in knockdown/knockout samples.

• Molecular weight verification:

  • Confirm that detected bands match the expected molecular weight of PACS2 (observed as 100-130 kDa) .

  • Verify that knockdown reduces intensity of bands at the correct molecular weight.

• Specificity controls:

  • Verify that the antibody does not detect the related protein PACS-1 (PACS-2 siRNA did not knock down PACS-1 in published studies) .

  • Include controls for endogenous biotin by using streptavidin-only detection.

• Rescue experiments:

  • Re-express PACS2 in knockdown or knockout cells and confirm recovery of antibody signal.

  • Such rescue experiments have been successfully performed in Pacs2−/− MEFs .

• Cross-verification with alternative detection methods:

  • Compare antibody results with mRNA expression (RT-qPCR)

  • If available, use multiple antibodies targeting different PACS2 epitopes

A systematic validation approach ensures that experimental observations truly reflect PACS2 biology rather than non-specific antibody binding or technical artifacts.

What controls should I include when using biotin-conjugated PACS2 antibodies for proximity ligation assays (PLA)?

When using biotin-conjugated PACS2 antibodies for proximity ligation assays to study protein interactions (e.g., PACS2-ADAM17), include these essential controls:

• Negative controls for PLA specificity:

  • Single primary antibody controls: Perform PLA with only biotin-conjugated PACS2 antibody or only the interaction partner antibody

  • Knockdown controls: Conduct PLA in cells with PACS2 knockdown and interaction partner knockdown (e.g., ADAM17 knockdown)

  • Non-interacting protein control: Use antibodies against proteins not expected to interact with PACS2

• Positive controls for PLA functionality:

  • Known interacting proteins: Include antibodies against proteins with established interactions

  • PMA treatment control: For PACS2-ADAM17 interactions, PMA treatment enhances the PLA signal

• Biotin-specific controls:

  • Endogenous biotin blocking: Pre-block with unlabeled streptavidin to eliminate signal from endogenous biotinylated proteins

  • Alternative biotin-conjugated antibody: Use biotin-conjugated antibody against unrelated protein to assess non-specific binding

• Subcellular localization controls:

  • Co-staining for organelle markers: Include markers for relevant compartments (e.g., early endosome markers where PACS2-ADAM17 co-localization occurs)

  • Comparison with conventional co-localization: Perform standard dual-immunofluorescence to compare with PLA results

• Quantitative controls:

  • Titration series: Perform PLA with different antibody concentrations to determine optimal signal-to-noise ratio

  • Technical replicates: Include multiple technical replicates to assess assay variability

These controls will help distinguish genuine biological interactions from technical artifacts, ensuring reliable interpretation of PACS2 interaction data.

How can I optimize cell-surface biotinylation protocols to study PACS2's effect on ADAM17 trafficking?

Cell-surface biotinylation is a powerful technique for studying PACS2's regulation of ADAM17 cell-surface availability . To optimize this protocol for investigating PACS2-dependent trafficking:

• Optimized biotinylation conditions:

  • Use membrane-impermeable biotinylation reagent (e.g., Sulfo-NHS-SS-Biotin) at 0.5-1.0 mg/ml in ice-cold PBS

  • Perform labeling at 4°C for 30 minutes to prevent endocytosis during labeling

  • Include free amino acids (glycine) to quench excess biotin reagent

• Trafficking protocol design:

  • For recycling studies: Label surface proteins, allow internalization at 37°C, strip remaining surface biotin, then measure recycled (re-exposed) biotin after various chase periods

  • For degradation studies: Use non-cleavable biotin (e.g., Sulfo-NHS-LC-Biotin) and track total biotinylated protein loss over time

• Comparative analysis in control vs. PACS2-deficient cells:

  • Compare ADAM17 internalization rates (reported to be unaffected by PACS2)

  • Measure ADAM17 recycling rates (reported to be reduced by PACS2 knockdown)

  • Assess ADAM17 degradation (accelerated in PACS2-deficient cells)

• Stimulus-dependent trafficking studies:

  • Compare basal vs. PMA-stimulated conditions (high-dose PMA enhances ADAM17 internalization)

  • Test physiological stimuli like TNF-α that affect ADAM17-dependent shedding

  • Include both high and low PMA doses, as they produce different effects

• Detection and quantification optimization:

  • For western blot analysis: Normalize biotinylated ADAM17 to total ADAM17 and loading controls

  • For microscopy: Use fluorescent streptavidin to visualize biotinylated proteins

  • For selective analysis: Immunoprecipitate ADAM17 before streptavidin detection

This methodological approach will allow precise quantification of how PACS2 affects ADAM17 trafficking dynamics, building on findings that PACS2 regulates ADAM17 cell-surface availability by influencing its recycling and stability .

What methods can I use to study the dynamics of PACS2-ADAM17 interactions in different subcellular compartments?

To investigate the dynamics of PACS2-ADAM17 interactions across various subcellular compartments, employ these complementary methodological approaches:

• Advanced microscopy techniques:

  • Triple-label confocal microscopy: Combine biotin-conjugated PACS2 antibody detection with ADAM17 staining and compartment-specific markers (early endosomes, Golgi, etc.)

  • Live-cell imaging: For dynamic studies, express fluorescently-tagged versions of PACS2 and/or ADAM17

  • Super-resolution microscopy: Techniques like STORM or STED can resolve interactions with nanometer precision

• Biochemical fractionation approaches:

  • Density gradient fractionation: Separate subcellular compartments and analyze distribution of PACS2 and ADAM17

  • Immunoisolation of organelles: Use antibodies against organelle-specific markers to isolate compartments containing PACS2-ADAM17 complexes

  • Protease protection assays: Determine membrane topology of interaction

• Proximity-based interaction mapping:

  • Organelle-specific PLA: Combine PLA with organelle markers to quantify interactions in specific compartments

  • BioID or APEX proximity labeling: Express PACS2 fused to biotin ligase or peroxidase to identify proximity partners in living cells

  • FRET microscopy: For real-time interaction monitoring in specific compartments

• Trafficking dynamics analysis:

  • Pulse-chase with transferrin: Use labeled transferrin to mark early endosomes and track co-trafficking with PACS2 and ADAM17

  • Cargo trapping assays: Use endocytic trafficking inhibitors to trap proteins in specific compartments

  • Photoactivatable fluorescent proteins: Track specific subpopulations through the trafficking pathway

• Stimulus-dependent interaction analysis:

  • Time-resolved PLA: Perform PLA at different time points after stimulation (e.g., PMA treatment enhances PACS2-ADAM17 PLA signal)

  • Synchronized trafficking: Use temperature blocks or reversible inhibitors to synchronize trafficking events

  • Dose-response studies: Compare different PMA concentrations, as low and high doses showed different effects

These methodological approaches will help create a detailed spatiotemporal map of PACS2-ADAM17 interactions throughout the endocytic pathway, expanding our understanding of how PACS2 regulates ADAM17 trafficking and activity.

How can I design experiments to determine the specific domains of PACS2 that mediate interaction with ADAM17?

To identify the specific domains of PACS2 involved in ADAM17 interaction, design a comprehensive experimental strategy combining molecular, biochemical, and cellular approaches:

• Domain mapping through truncation and deletion constructs:

  • Generate a series of PACS2 truncation mutants (N-terminal, C-terminal, and internal domains)

  • Express these constructs in Pacs2−/− MEFs to identify which domains rescue ADAM17-mediated shedding

  • Perform co-immunoprecipitation with ADAM17 to identify minimal interaction domains

  • Conduct PLA using epitope-tagged constructs to confirm interactions in situ

• Site-directed mutagenesis of key residues:

  • Target conserved motifs in PACS2 (acidic clusters, phosphorylation sites)

  • Create point mutations of key residues within identified interaction domains

  • Assess mutant effects on PACS2-ADAM17 binding and ADAM17-mediated shedding

• Chimeric protein approach:

  • Create chimeric proteins between PACS2 and the related PACS1 (which doesn't affect ADAM17)

  • Test chimeras for gain/loss of ADAM17 interaction and functional regulation

  • Map minimal regions sufficient to confer ADAM17-regulatory function

• Peptide competition assays:

  • Synthesize peptides corresponding to potential interaction interfaces

  • Test ability of peptides to disrupt PACS2-ADAM17 interaction in co-immunoprecipitation

  • Validate in cellular assays by introducing cell-permeable peptides

• Structural biology approaches:

  • Perform in silico modeling of potential interaction interfaces

  • If feasible, conduct X-ray crystallography or cryo-EM of interaction domains

  • Use HDX-MS (hydrogen-deuterium exchange mass spectrometry) to identify protected regions during interaction

This multi-faceted approach will provide complementary lines of evidence identifying the specific PACS2 domains that mediate ADAM17 interaction, providing mechanistic insights into how PACS2 regulates ADAM17 trafficking and activity.

What experimental approaches can resolve contradictory findings about PACS2 function across different cell types?

To systematically address contradictory findings regarding PACS2 function across different cell types, implement these rigorous experimental approaches:

• Standardized parallel analysis across multiple cell models:

  • Select diverse cell line panel (epithelial, fibroblast, cancer, normal)

  • Apply identical PACS2 knockdown/knockout methods across all models

  • Use standardized functional readouts (e.g., ADAM17-mediated shedding assays)

  • Include dose-response studies for stimuli (PMA, TNF-α) across all cell types

• Mechanistic analysis of cell-type differences:

  • Profile expression levels of pathway components (ADAM17, substrates, trafficking machinery)

  • Analyze post-translational modifications of PACS2 across cell types

  • Perform quantitative interactome analysis to identify cell-type-specific cofactors

  • Examine subcellular distribution patterns of PACS2 and ADAM17

• Substrate-specific analysis:

  • Compare PACS2 effects on different ADAM17 substrates (HB-EGF, TGF-α) in multiple cell types

  • Normalize for substrate expression levels to eliminate that variable

  • Analyze both basal and stimulated shedding (PMA, TNF-α)

  • Examine substrate-specific trafficking patterns

• Genetic rescue experiments:

  • Reintroduce PACS2 in knockout cells from different tissues

  • Test whether PACS2 from one cell type rescues function in another

  • Create chimeric PACS2 proteins combining domains from different isoforms

  • Include reintroduction at physiological expression levels

• In vivo validation in tissue-specific models:

  • Generate tissue-specific PACS2 knockout models

  • Compare phenotypes across tissues (intestine, skin, etc.)

  • Analyze EGFR activation patterns in different tissues, similar to the pEGFR analysis in intestinal crypts

  • Perform ex vivo culture of primary cells from different tissues

These systematic approaches will help distinguish genuine biological variation in PACS2 function from technical artifacts or concentration-dependent effects, providing a comprehensive understanding of how PACS2 function may be modulated in a context-dependent manner.

How can I design experiments to investigate the physiological significance of PACS2-regulated ADAM17 trafficking in disease models?

To investigate the physiological significance of PACS2-regulated ADAM17 trafficking in disease models, design experiments that connect molecular mechanisms to disease phenotypes:

• Cancer progression models:

  • Experimental design: Compare PACS2 and ADAM17 expression/localization in tumor vs. normal tissues

  • Methodological approach: Use tissue microarrays with biotin-conjugated PACS2 antibodies and ADAM17 staining

  • Functional analysis: Manipulate PACS2 levels in tumor xenograft models and measure effects on growth, invasion, and EGFR activation

  • Mechanistic connection: Correlate PACS2-ADAM17 PLA signals with clinical outcomes and treatment responses

• Inflammatory disease models:

  • Experimental design: Analyze PACS2-dependent ADAM17 regulation in models of inflammatory bowel disease, considering the intestinal phenotype in PACS2-deficient mice

  • Methodological approach: Induce colitis in wild-type vs. Pacs2−/− mice and assess disease severity

  • Endpoint measurements: Evaluate ADAM17-dependent cytokine shedding (TNF-α) and epithelial regeneration (EGFR activation)

  • Therapeutic potential: Test whether stabilizing ADAM17 trafficking can modulate disease progression

• Developmental biology applications:

  • Experimental design: Investigate PACS2-ADAM17-EGFR axis during epithelial development

  • Methodological approach: Use embryonic tissue explants from control vs. Pacs2−/− mice

  • Analysis techniques: Apply live imaging of ADAM17 trafficking during morphogenesis

  • Phenotypic assessment: Evaluate branching morphogenesis and epithelial differentiation

• Precision medicine applications:

  • Experimental design: Screen patient-derived samples for alterations in PACS2-ADAM17 pathway

  • Methodological approach: Develop tissue analysis pipeline combining PLA for PACS2-ADAM17 with phospho-EGFR quantification

  • Clinical correlation: Relate PACS2 function to treatment responses in EGFR-dependent cancers

  • Biomarker development: Assess whether PACS2-ADAM17 PLA signal predicts sensitivity to ADAM17 or EGFR inhibitors

• Therapeutic intervention strategies:

  • Experimental design: Develop approaches to modulate PACS2-ADAM17 interaction

  • Methodological approach: Screen for compounds that enhance or disrupt the interaction using PLA-based high-content screening

  • Validation: Test candidate compounds in disease models where ADAM17-EGFR signaling is implicated

  • Mechanistic assessment: Verify that compounds act through altered ADAM17 trafficking rather than direct enzymatic inhibition

These translational research approaches connect the fundamental PACS2-ADAM17 trafficking mechanisms to disease contexts, potentially identifying new therapeutic strategies for conditions involving dysregulated EGFR signaling.

What methodological approaches can integrate PACS2-ADAM17 trafficking data with systems biology to predict pathway outcomes?

Integrating PACS2-ADAM17 trafficking data with systems biology approaches requires sophisticated methodological strategies to connect molecular mechanisms with pathway-level outcomes:

• Multi-parameter quantitative imaging analysis:

  • Experimental approach: Perform multiplexed imaging combining PACS2-ADAM17 PLA, endosomal markers, and downstream signaling outputs (pEGFR)

  • Analytical method: Apply machine learning algorithms to identify spatial patterns correlating with signaling outcomes

  • Quantitative output: Derive mathematical relationships between PACS2-ADAM17 interaction intensity, subcellular distribution, and EGFR activation

  • Validation strategy: Test predictions by manipulating trafficking at specific compartments

• Integrative proteomics workflow:

  • Experimental design: Combine proximity labeling (BioID/APEX) of PACS2-proximal proteins with phosphoproteomics of downstream pathway components

  • Technical approach: Perform time-resolved analysis after pathway stimulation

  • Computational integration: Develop network models linking trafficking regulators to signaling outcomes

  • Hypothesis testing: Perturb identified nodes and measure effects on ADAM17 trafficking and EGFR signaling

• Computational modeling of trafficking dynamics:

  • Mathematical approach: Develop ordinary differential equation models of ADAM17 trafficking incorporating PACS2-dependent rate constants

  • Parameter determination: Measure trafficking rates in control vs. PACS2-deficient cells

  • Model validation: Test predictions about steady-state distributions and response to perturbations

  • Sensitivity analysis: Identify trafficking steps most critical for pathway output

• Multi-omics data integration:

  • Experimental strategy: Collect transcriptomics, proteomics, and phosphoproteomics data from wild-type vs. Pacs2−/− models

  • Analytical approach: Apply pathway enrichment and causal network analysis

  • Validation method: Test key predictions using targeted perturbations

  • Physiological relevance: Compare with intestinal crypt pEGFR patterns observed in vivo

• Single-cell multi-modal analysis:

  • Technical approach: Combine single-cell imaging of PACS2-ADAM17 with single-cell transcriptomics

  • Analytical method: Correlate cell-to-cell variation in trafficking with gene expression patterns

  • Biological insight: Identify compensatory mechanisms and cell state dependencies

  • Translational application: Define cellular subpopulations with distinct dependency on PACS2-regulated trafficking

These integrative approaches transform descriptive observations of PACS2-ADAM17 trafficking into predictive models of pathway function, enabling rational design of interventions to modulate EGFR signaling in both research and therapeutic contexts.