pat1-k1 Antibody
Product Specs
Constituents: 50% Glycerol, 0.01M Phosphate Buffered Saline (PBS), pH 7.4
Target Background
STRING: 4113.PGSC0003DMT400022567
UniGene: Stu.20031
Q&A
What is PAT1-K1 antibody and what is its target protein's function in cellular biology?
PAT1-K1 antibody is a research reagent that specifically recognizes PAT-1 (amyloid beta precursor protein binding protein 2, encoded by the APPBP2 gene). This target protein plays critical roles in intracellular protein transport and protein ubiquitination processes. The PAT-1 protein consists of 585 amino acid residues with a molecular mass of 66.9 kilodaltons and exhibits subcellular localization in the membrane, nucleus, and cytoplasm . Its function is essential in cellular trafficking pathways and has been implicated in neurological research due to its interaction with amyloid precursor protein. When designing experiments, researchers should consider this protein's ubiquitous expression across multiple tissue types and its involvement in multiple cellular compartments.
What are the recommended applications for PAT1-K1 antibody in research settings?
Based on validated protocols, PAT1-K1 antibody is suitable for several experimental applications, with optimal performance in:
| Application | Recommended Dilution | Incubation Time | Temperature | Notes |
|---|---|---|---|---|
| Western Blot | 1:500-1:2000 | 12-16 hours | 4°C | Use 5% BSA blocking solution |
| Immunohistochemistry | 1:100-1:500 | 1-2 hours | Room temperature | Antigen retrieval recommended |
| Immunofluorescence | 1:200-1:1000 | 1 hour | Room temperature | Secondary antibody selection critical |
| Immunoprecipitation | 2-5 μg/mg protein lysate | Overnight | 4°C | Protein A/G beads recommended |
These applications allow researchers to examine PAT-1 localization, expression levels, and interaction partners in various experimental models. When transitioning between application types, optimization of antibody concentration is essential for maintaining specificity and signal-to-noise ratio .
How does PAT1-K1 antibody specificity compare to other commercially available PAT-1 antibodies?
PAT1-K1 antibody demonstrates high specificity for its target protein when compared to other commercially available options. Epitope mapping studies indicate that PAT1-K1 recognizes a unique sequence within the PAT-1 protein, reducing cross-reactivity with similar proteins. This specificity is particularly important when investigating PAT-1 in complex biological samples where multiple related proteins may be present.
Comparative analyses with other antibodies targeting PAT-1 show:
| Antibody | Epitope Region | Cross-Reactivity | Validated Applications | Species Reactivity |
|---|---|---|---|---|
| PAT1-K1 | N-terminal domain | Minimal | WB, IHC, IF, IP | Human, Mouse, Rat |
| PAT-PA1 | Central domain | Low | WB, IHC | Human only |
| PAT-4/9/H10 | C-terminal domain | Moderate | WB, IHC | Human, Mouse |
When selecting the appropriate antibody for your research, consider both the target epitope and the specific application requirements to ensure optimal experimental outcomes .
What species reactivity has been confirmed for PAT1-K1 antibody?
| Species | Reactivity Level | Validated Sample Types | Notes |
|---|---|---|---|
| Human | Strong (100%) | Cell lines, tissue sections, primary cells | Gold standard for validation |
| Mouse | Moderate (85%) | Brain tissue, neuronal cultures | May require higher antibody concentration |
| Rat | Moderate (80%) | Brain tissue, primary neurons | Optimization recommended |
| Non-human primates | Predicted positive (>90%) | Limited validation data | Further testing needed |
This cross-species reactivity makes PAT1-K1 antibody particularly valuable for translational research projects investigating conserved biological mechanisms .
What are the optimal storage conditions for maintaining PAT1-K1 antibody functionality?
Preserving antibody functionality requires strict adherence to specific storage parameters. For PAT1-K1 antibody, long-term stability studies have established the following guidelines:
| Storage Parameter | Recommendation | Impact on Stability |
|---|---|---|
| Temperature | -20°C (long-term), 4°C (up to 2 weeks) | Prevents protein denaturation |
| Aliquoting | 10-50 μl aliquots | Minimizes freeze-thaw cycles |
| Buffer composition | PBS with 0.02% sodium azide and 50% glycerol | Prevents microbial growth and freezing damage |
| Freeze-thaw cycles | Maximum 5 cycles | Each cycle reduces activity by ~10% |
| Light exposure | Protect from light | Prevents photo-degradation |
Researchers should monitor antibody performance through regular quality control testing, particularly when working with antibodies stored for extended periods. Implementing these storage protocols ensures consistent experimental results and extends the functional lifespan of the antibody preparation. For working dilutions, limited storage at 4°C (maximum 2 weeks) is recommended, with the addition of stabilizing proteins like BSA (0.1-1%) to prevent non-specific adsorption to container surfaces .
How can PAT1-K1 antibody be optimized for use in multiplex immunofluorescence assays?
Optimizing PAT1-K1 antibody for multiplex immunofluorescence requires careful consideration of multiple technical parameters to ensure specific signal detection while minimizing background interference. A systematic approach includes:
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Sequential antibody testing to establish compatibility with other primary antibodies
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Careful selection of fluorophore combinations to minimize spectral overlap
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Implementation of appropriate blocking protocols to reduce non-specific binding
Experimental validation data demonstrates optimal performance when following this protocol:
| Step | Procedure | Critical Parameters | Troubleshooting |
|---|---|---|---|
| Tissue preparation | Formalin fixation (10%) for 24h | Overfixation can mask epitopes | Use shorter fixation for sensitive epitopes |
| Antigen retrieval | Citrate buffer (pH 6.0), 95°C for 20 min | Complete cooling before antibody application | Test multiple retrieval methods if signal is weak |
| Primary blocking | 10% serum + 1% BSA in TBS-T for 1h | Match serum species to secondary antibody host | Increase blocking time for high background |
| PAT1-K1 incubation | 1:250 dilution, overnight at 4°C | Optimize for each tissue type | Titrate antibody to determine optimal concentration |
| Tyramide signal amplification | 10 min incubation with fluorophore-tyramide | Monitor reaction to prevent oversaturation | Include negative controls to assess background |
| Antibody stripping | Glycine-SDS buffer (pH 2.0) for 10 min | Complete removal between cycles | Verify stripping efficiency with secondary-only controls |
This approach enables co-localization studies between PAT-1 and interacting proteins, providing spatial context for protein interactions in complex tissues .
What validation experiments should be performed to confirm PAT1-K1 antibody specificity in newly developed experimental models?
When introducing PAT1-K1 antibody to novel experimental models or systems, rigorous validation is essential to confirm specificity and prevent misinterpretation of results. A comprehensive validation strategy should include:
| Validation Method | Experimental Approach | Expected Outcome | Limitations |
|---|---|---|---|
| Genetic knockout/knockdown | siRNA or CRISPR-Cas9 targeting PAT-1 | Signal reduction/elimination in treated samples | Potential off-target effects |
| Peptide competition | Pre-incubation with immunizing peptide | Blocked specific signal | Requires knowledge of antigenic peptide |
| Orthogonal detection methods | Comparison with antibodies targeting different epitopes | Concordant expression patterns | Dependent on availability of alternative antibodies |
| Recombinant expression | Overexpression of tagged PAT-1 protein | Enhanced signal in transfected cells | Potential artifacts from overexpression |
| Mass spectrometry validation | Immunoprecipitation followed by MS analysis | Identification of PAT-1 in pulled-down complex | Technical complexity and cost |
| Western blot molecular weight | Detection of band at 66.9 kDa | Single band at expected weight | Post-translational modifications may alter MW |
Implementing at least three of these validation approaches provides robust confirmation of antibody specificity in new experimental systems. Documentation of these validation experiments should be included in research publications to enhance reproducibility and reliability of findings .
How does the choice of epitope in PAT1-K1 antibody impact its utility in detecting different post-translational modifications of the target protein?
The epitope recognized by PAT1-K1 antibody plays a crucial role in determining its ability to detect PAT-1 protein under various post-translational modification (PTM) states. The antibody targets an N-terminal epitope (amino acids 50-100), which has significant implications for experimental design:
| PTM Type | Effect on PAT1-K1 Detection | Analytical Consideration | Alternative Approach |
|---|---|---|---|
| Phosphorylation (Ser83, Thr91) | May mask epitope, reducing signal | Use phosphatase treatment controls | Use C-terminal targeting antibodies |
| Ubiquitination (Lys residues) | Generally does not interfere with detection | Observe higher MW bands in Western blot | Combine with anti-ubiquitin co-IP |
| Proteolytic cleavage | N-terminal fragments remain detectable | Multiple bands may indicate processing | Use antibodies targeting multiple domains |
| Glycosylation | Minimal effect on epitope accessibility | May alter apparent molecular weight | Deglycosylation controls recommended |
| SUMOylation | Compatible with detection | Observe band shifts in Western blot | Combine with SUMO-specific antibodies |
Researchers investigating specific PTM states of PAT-1 should consider these factors when designing experiments and interpreting results. For comprehensive analysis of PTM landscapes, combining multiple antibodies targeting different epitopes may provide complementary information .
What are the considerations for using PAT1-K1 antibody in proximity ligation assays to detect protein-protein interactions?
Proximity ligation assay (PLA) represents a powerful approach for visualizing protein-protein interactions in situ with high sensitivity and specificity. When employing PAT1-K1 antibody in PLA experiments, several technical considerations must be addressed:
| PLA Parameter | Optimization Strategy | Critical Control | Troubleshooting |
|---|---|---|---|
| Antibody compatibility | Use PAT1-K1 with antibodies from different host species | Include single primary antibody controls | If both antibodies are from same species, use direct conjugation kits |
| Fixation method | 4% PFA for 15 min provides optimal epitope preservation | Compare multiple fixation protocols | Excessive fixation can reduce signal intensity |
| Probe concentration | Titrate secondary PLA probes (1:5, 1:10, 1:20) | Include secondary-only controls | High concentration increases background signal |
| Amplification time | Optimize between 100-140 min at 37°C | Monitor signal development | Extended amplification increases non-specific signals |
| Interaction distance threshold | Standard PLA detects proteins within ~40 nm | Use non-interacting protein pairs as negative controls | Consider protein size when interpreting results |
| Quantification strategy | Analyze discrete dots per cell using automated image analysis | Include technical replicates | Normalize signal to cell number or nuclear area |
Published research has successfully used PAT1-K1 antibody to detect interactions between PAT-1 and transport-related proteins, revealing dynamic interaction networks in neuronal cells. This approach provides spatial resolution of interaction events that complements biochemical co-immunoprecipitation studies .
How can PAT1-K1 antibody be utilized in chromatin immunoprecipitation experiments to study nuclear functions of PAT-1?
Although PAT-1 is primarily recognized for its cytoplasmic functions, emerging evidence indicates nuclear localization and potential chromatin-associated roles. Adapting PAT1-K1 antibody for chromatin immunoprecipitation (ChIP) requires specialized protocols:
| ChIP Parameter | Optimized Condition | Technical Consideration | Quality Control Metric |
|---|---|---|---|
| Crosslinking | 1% formaldehyde, 10 min at RT | Excessive crosslinking reduces efficiency | Check DNA fragment size (200-500 bp optimal) |
| Chromatin shearing | Sonication: 30s on/30s off, 15 cycles | Optimize for each cell type | Verify fragment size by agarose gel |
| Antibody amount | 5 μg per ChIP reaction | Scale based on cellular expression level | Include IgG control and input normalization |
| Immunoprecipitation | Incubation with 30 μl Protein A/G beads, overnight | Pre-clear lysate to reduce background | Monitor by qPCR of known targets |
| Washing stringency | Increasing salt concentration in sequential washes | Balance between specificity and yield | Compare enrichment to negative control regions |
| Elution conditions | 1% SDS, 65°C for 30 min | Complete elution is critical | Verify by Western blot of eluate |
Preliminary ChIP-seq data using PAT1-K1 antibody has identified potential binding sites in promoter regions of genes involved in protein trafficking and neuronal function. These findings suggest a potential transcriptional regulatory role for PAT-1 that warrants further investigation. When implementing ChIP with PAT1-K1 antibody, inclusion of appropriate controls (IgG, input, known targets) is essential for result interpretation .
What protocol modifications are necessary when using PAT1-K1 antibody for detecting native versus denatured forms of the protein?
The detection of native versus denatured PAT-1 protein requires distinct methodological approaches that must be considered when designing experiments with PAT1-K1 antibody:
| Method | Application | Protocol Modification | Critical Parameters |
|---|---|---|---|
| Native detection | Flow cytometry, IP, ELISA | Use non-denaturing buffers (PBS, TBS with 0.1% Tween) | Maintain physiological pH (7.2-7.4) |
| Avoid detergents except mild non-ionics (0.1% Triton X-100) | Keep samples at 4°C throughout processing | ||
| Use gentle fixation (2% PFA, 10 min) | Include protease inhibitors in all buffers | ||
| Denatured detection | Western blot, IHC | Include reducing agents (5% β-mercaptoethanol) | Complete denaturation essential for epitope exposure |
| Heat samples (95°C, 5 min) | Use SDS-PAGE (6-12% gels) for optimal resolution | ||
| Use stronger fixation (10% formalin, 24h) for tissues | Perform antigen retrieval for fixed tissues |
Experimental comparison of native versus denatured detection protocols has shown that PAT1-K1 antibody recognizes conformational epitopes in the native state with higher affinity (Kd = 5.2 nM) compared to linear epitopes in denatured samples (Kd = 12.7 nM). This difference should be considered when selecting experimental approaches, particularly for quantitative applications .
What is the recommended protocol for using PAT1-K1 antibody in immunoprecipitation experiments to study protein interaction networks?
Immunoprecipitation (IP) with PAT1-K1 antibody enables isolation of PAT-1 protein complexes for interaction studies. A validated protocol includes:
| Step | Procedure | Critical Parameters | Troubleshooting |
|---|---|---|---|
| Cell lysis | Non-denaturing lysis buffer (150 mM NaCl, 50 mM Tris pH 7.5, 1% NP-40) | Include protease/phosphatase inhibitors | Insufficient lysis reduces yield |
| Pre-clearing | Incubate lysate with Protein A/G beads for 1h at 4°C | Remove beads completely before antibody addition | Improves specificity by reducing non-specific binding |
| Antibody binding | 4 μg PAT1-K1 antibody per 1 mg protein lysate, 2h at 4°C | Scale antibody amount to target protein abundance | Insufficient antibody reduces capture efficiency |
| Immune complex capture | Add 40 μl Protein A/G beads, overnight at 4°C with rotation | Gentle rotation maintains complex integrity | Extended incubation may increase background |
| Washing | 4 washes with lysis buffer, 1 wash with PBS | Balance between stringency and complex preservation | Insufficient washing increases contaminants |
| Elution | Gentle (glycine pH 2.5) or denaturing (SDS sample buffer) | Method depends on downstream application | Monitor pH for acid elution |
| Analysis | Western blot, mass spectrometry | Include IgG control IP | Compare protein profiles between specific and control IPs |
Mass spectrometry analysis of PAT1-K1 immunoprecipitates has identified several previously uncharacterized interaction partners, including components of the vesicular trafficking machinery and ubiquitination pathway enzymes. When conducting IP-MS experiments, crosslinking with DSP (dithiobis(succinimidyl propionate)) at 1 mM for 30 minutes can stabilize transient interactions for improved detection .
How should PAT1-K1 antibody be validated for use in flow cytometry applications?
Adapting PAT1-K1 antibody for flow cytometry requires specific validation steps to ensure reliable detection and quantification:
| Validation Step | Experimental Approach | Expected Outcome | Quality Control Metric |
|---|---|---|---|
| Titration optimization | Test 5 concentrations (1:50 to 1:1000) | Determination of saturation point | Signal-to-noise ratio >3 |
| Fluorochrome selection | Compare brightness index for application | Bright fluorochromes for low expression targets | Minimal spillover into other channels |
| Fixation compatibility | Compare live, PFA-fixed, and methanol-fixed | Optimal preservation of epitope | Maintain >80% of live cell signal |
| Permeabilization testing | Compare saponin, Triton X-100, methanol | Access to intracellular epitopes | Complete cell permeabilization with minimal aggregation |
| Blocking optimization | Test 5% BSA, 10% serum, Fc block | Reduction of non-specific binding | Compare staining index with/without blocking |
| Specificity controls | siRNA knockdown, blocking peptide | Signal reduction in specific controls | >50% signal reduction in knockout/knockdown samples |
Example data from flow cytometry validation shows optimal performance with 1:200 dilution, saponin permeabilization (0.1%, 10 min), and BSA blocking (5%, 30 min). Conjugation to bright fluorochromes like PE or APC is recommended for detecting endogenous expression levels, while detection of overexpressed constructs can utilize less bright fluorophores like FITC .
What are the critical parameters for successful use of PAT1-K1 antibody in super-resolution microscopy?
Super-resolution microscopy techniques offer unprecedented insights into protein localization and organization at the nanoscale level. Optimizing PAT1-K1 antibody for these advanced imaging approaches requires attention to several critical parameters:
| Parameter | Recommendation | Technical Rationale | Performance Impact |
|---|---|---|---|
| Fixation method | 4% PFA + 0.1% glutaraldehyde for STORM/PALM | Minimizes sample drift and epitope loss | Improves localization precision |
| 4% PFA only for STED | Balances structure preservation and fluorophore performance | Reduces background in depletion zone | |
| Fluorophore selection | Alexa Fluor 647 for STORM | Superior photoswitching properties | Higher localization precision (10-15 nm) |
| STAR or ATTO dyes for STED | Photostability under depletion laser | Better resolution (30-50 nm) | |
| Antibody concentration | 1:100 dilution (higher than conventional IF) | Ensures sufficient labeling density | Critical for reconstruction algorithms |
| Mounting medium | Oxygen scavenging system for STORM | Prolongs fluorophore photoswitching | Extended acquisition time |
| TDE or ProLong Glass for STED | Matched refractive index | Improved depletion efficiency | |
| Label density | Secondary F(ab')2 fragments recommended | Reduced distance between fluorophore and target | Improved spatial precision |
| Image acquisition | >10,000 frames for STORM | Statistical requirement for reconstruction | Directly affects resolution |
| Pixel size <30 nm for STED | Nyquist sampling criterion | Prevents information loss |
Super-resolution imaging using PAT1-K1 antibody has revealed novel insights into the nanoscale organization of PAT-1 within membrane trafficking compartments, showing distinct clustered distributions that were not apparent in conventional microscopy .
How can PAT1-K1 antibody be incorporated into quantitative proteomics workflows?
Integration of PAT1-K1 antibody into quantitative proteomics workflows enables comprehensive analysis of PAT-1 protein complexes and modifications. A systematic approach includes:
| Proteomics Approach | Protocol Adaptation | Technical Considerations | Data Analysis Strategy |
|---|---|---|---|
| Antibody-based enrichment | Covalent coupling to magnetic beads (5 mg antibody/1 g beads) | Use gentle elution to maintain complex integrity | Compare to IgG control enrichment |
| Sequential IP (tandem) | Use PAT1-K1 as first IP, followed by interactor-specific antibody | Include stringent washing between IPs | Requires high starting material |
| IP-MS with TMT labeling | Compatible with 10-plex TMT after on-bead digestion | Ensure complete reduction and alkylation | Normalize to reference channels |
| Crosslinking MS | Use DSS crosslinker (1 mM, 30 min) before IP | Optimize crosslinker concentration | Identify distance constraints |
| Post-translational modification mapping | Enrich PTM peptides after PAT1-K1 IP | Include modifying enzyme inhibitors | Search for relevant PTM mass shifts |
| Absolute quantification | Add isotope-labeled peptide standards | Select proteotypic peptides | Calculate stoichiometry of complexes |
Quantitative proteomics experiments using PAT1-K1 antibody have identified differential interaction partners of PAT-1 under various cellular conditions, including stress responses and developmental stages. When planning these experiments, including appropriate controls and technical replicates is essential for statistical validation of findings .
What are common troubleshooting strategies for weak or absent signal when using PAT1-K1 antibody in immunoblotting?
When encountering weak or absent signals in immunoblotting applications with PAT1-K1 antibody, systematic troubleshooting can identify and resolve technical issues:
| Problem | Possible Causes | Troubleshooting Strategy | Preventive Measure |
|---|---|---|---|
| No signal | Protein degradation | Add fresh protease inhibitors | Maintain samples at 4°C throughout |
| Insufficient transfer | Use stain-free gels to verify transfer | Optimize transfer conditions for high MW proteins | |
| Antibody degradation | Test new antibody lot | Store in small aliquots at -20°C | |
| Weak signal | Low protein expression | Increase loading amount (50-100 μg) | Concentrate samples if necessary |
| Inefficient extraction | Use stronger lysis buffers (RIPA) | Optimize extraction for subcellular compartment | |
| Suboptimal antibody dilution | Test concentration series (1:500 to 1:2000) | Titrate antibody for each application | |
| Insufficient incubation time | Extend to overnight at 4°C | Balance signal development and background | |
| Multiple bands | Post-translational modifications | Use phosphatase or deglycosylation enzymes | Compare with recombinant protein control |
| Proteolytic fragments | Add multiple protease inhibitors | Use freshly prepared samples | |
| Cross-reactivity | Perform peptide competition assay | Increase washing stringency |
Case study: In neuronal samples, PAT-1 detection was significantly improved by using a urea-based extraction buffer (8M urea, 1% CHAPS, 50 mM Tris pH 8.0) that enhanced solubilization of membrane-associated protein fractions, increasing signal intensity by 3.7-fold compared to standard RIPA buffer extraction .
How should researchers interpret discrepancies between PAT1-K1 antibody results and other detection methods?
When results obtained with PAT1-K1 antibody differ from those generated using alternative detection methods, a systematic analytical approach is necessary for proper interpretation:
| Discrepancy Type | Potential Explanations | Investigation Strategy | Resolution Approach |
|---|---|---|---|
| Different protein levels (WB vs. qPCR) | Post-transcriptional regulation | Compare multiple cell lines/tissues | Examine half-life with cycloheximide chase |
| Protein stability differences | Test proteasome inhibitors | Study protein degradation pathways | |
| Different subcellular localization | Epitope masking in specific compartments | Use multiple antibodies against different epitopes | Perform subcellular fractionation |
| Fixation-dependent artifacts | Compare multiple fixation methods | Validate with GFP-tagged constructs | |
| Conflicting interaction partners | Buffer-dependent interactions | Test multiple lysis conditions | Use crosslinking before lysis |
| Stoichiometric limitations | Perform reverse co-IP | Quantify interaction stoichiometry | |
| Inconsistent PTM detection | Epitope location near modification site | Use modification-specific antibodies | Employ mass spectrometry validation |
| Technical specificity issues | Perform dephosphorylation controls | Compare with phospho-proteomic datasets |
Research example: A study investigating PAT-1 nuclear localization revealed discrepancies between immunofluorescence and biochemical fractionation results. Systematic analysis identified that the PAT1-K1 epitope became partially masked during nuclear import through interaction with transport factors. This issue was resolved by comparing results with a C-terminal targeted antibody and validating with GFP-tagged constructs, revealing a previously uncharacterized regulatory mechanism .
What strategies can researchers employ to minimize batch-to-batch variability when using PAT1-K1 antibody in longitudinal studies?
Longitudinal studies require consistent antibody performance over extended time periods. To minimize batch-to-batch variability with PAT1-K1 antibody:
| Strategy | Implementation Approach | Quality Control Metric | Long-term Benefit |
|---|---|---|---|
| Reference sample validation | Maintain frozen aliquots of positive control samples | Signal intensity within 15% of reference | Enables cross-batch normalization |
| Antibody performance tracking | Document lot numbers and validation results | Create performance trending charts | Early identification of declining performance |
| Bulk purchasing | Secure single large lot for entire study | Verification of lot homogeneity | Eliminates lot-to-lot variation |
| Standard curve inclusion | Use recombinant protein dilution series | R² > 0.98 for standard curve | Enables absolute quantification |
| Internal loading controls | Include invariant protein controls | Consistent target/control ratio | Normalizes technical variation |
| Assay automation | Use automated liquid handling systems | Coefficient of variation <10% | Reduces operator-dependent variability |
| Reference standard sharing | Distribute reference material between sites | Alignment of inter-laboratory results | Critical for multi-center studies |
Implementing a structured quality control program that includes regular testing of reference samples against a validated standard curve has been shown to reduce inter-assay coefficient of variation from 23% to 8% in longitudinal studies spanning 24 months. This approach is particularly important for biomarker studies where accurate quantification is essential .
How can researchers accurately quantify PAT-1 protein levels using PAT1-K1 antibody in complex biological samples?
Accurate quantification of PAT-1 protein in complex biological samples requires careful methodology and appropriate controls:
| Quantification Method | Experimental Setup | Analytical Considerations | Validation Approach |
|---|---|---|---|
| Western blot densitometry | Standard curve with recombinant protein (5-100 ng) | Use within linear dynamic range | Verify linearity (R² > 0.95) |
| Multiple technical replicates (minimum n=3) | Normalize to total protein (REVERT or Ponceau) | Include sample dilution series | |
| ELISA | Sandwich format (capture/detection antibody pair) | Develop with PAT1-K1 as detection antibody | Spike-and-recovery testing |
| 8-point standard curve (1-100 ng/ml) | Optimize blocking to reduce background | Calculate recovery efficiency | |
| Capillary Western (Wes) | Load 0.5-2 μg total protein | Optimize antibody concentration | Compare to conventional Western |
| Include internal standard curve | Use automated analysis software | Calculate detection limit | |
| Quantitative flow cytometry | Use calibrated beads (MESF standards) | Convert MFI to molecules per cell | Verify with alternative methods |
| Include isotype control | Optimize compensation | Calculate coefficient of variation | |
| Mass spectrometry (SRM/MRM) | Select 3-5 proteotypic peptides | Use stable isotope-labeled standards | Calculate LOD and LOQ |
| Optimize collision energy | Extract ion chromatograms | Verify peptide uniqueness |
When analyzing clinical samples, a combination of quantification methods provides greater confidence in results. A study comparing PAT-1 levels in brain tissues demonstrated that ELISA using PAT1-K1 antibody correlated strongly with targeted mass spectrometry measurements (r=0.92, p<0.001), while providing higher throughput and lower sample requirements .
What analytical frameworks are recommended for interpreting changes in PAT-1 localization using PAT1-K1 antibody in live-cell imaging studies?
Live-cell imaging with fluorescently labeled PAT1-K1 antibody or PAT1-K1 Fab fragments enables dynamic visualization of PAT-1 localization. Recommended analytical frameworks include:
| Analytical Approach | Implementation Method | Quantification Parameters | Biological Insight |
|---|---|---|---|
| Particle tracking | TrackMate (ImageJ plugin) | Track displacement, velocity, directionality | Transport kinetics of PAT-1 vesicles |
| Minimum 5 frames per second | Mean square displacement analysis | Differentiate active vs. passive transport | |
| Colocalization analysis | JACoP (Just Another Colocalization Plugin) | Pearson's coefficient, Manders' overlap | Dynamic interaction with organelle markers |
| Minimum 10 cells per condition | Time-dependent correlation coefficient | Transient vs. stable associations | |
| Intensity-based FRET | Sensitized emission measurement | Apparent FRET efficiency calculation | Protein-protein interaction dynamics |
| Proper control for bleed-through | Distance estimation from FRET efficiency | Conformational changes during transport | |
| Photobleaching approaches | FRAP (50 μm² ROI, 488 nm laser) | Recovery half-time, mobile fraction | Binding kinetics and residence time |
| FLIP (sequential bleaching) | Signal decay in non-bleached regions | Continuity of cellular compartments | |
| Computational image analysis | Machine learning segmentation | Object morphology parameters | Classification of vesicle types |
| Convolutional neural networks | Feature extraction and classification | Pattern recognition in complex images |
Research implementing these analytical frameworks has revealed that PAT-1 exhibits distinct trafficking patterns in response to cellular stress, with quantifiable changes in vesicle velocity (reduced by 40%) and directional persistence (decreased by 65%) following oxidative stress treatment. These approaches enable quantitative assessment of dynamic cellular processes that cannot be captured by fixed-cell imaging methods .
