pat-4 Antibody

What is PAT-4 antibody and what does it target?

PAT-4 antibody [PAT-4/9/H10] is a highly specific mouse monoclonal antibody that targets PAT4 (SLC36A4), a member of the proton-assisted amino-acid transporter (PAT) or solute-linked carrier 36 (SLC36) family. This antibody specifically recognizes an antigenic amino acid sequence within the N-terminus of PAT4 (REELDMDVMRPLINE-C). PAT4 functions as a positive regulator of growth and mTORC1 signaling and has been identified as upregulated in aggressive forms of colorectal cancer, suggesting its potential as a biomarker .

What applications is PAT-4 antibody validated for?

The PAT-4 antibody has been validated for immunohistochemistry (IHC) and Western blot (WB) applications as indicated in its technical specifications . These techniques enable researchers to visualize PAT4 distribution in tissue sections and quantify expression levels in cell lysates. For optimal results in each application, researchers should follow specific protocols that account for the antibody's characteristics and the nature of the target protein.

What is the molecular weight of PAT4 detected by this antibody?

The molecular weight of PAT4 (SLC36A4) recognized by the PAT-4 antibody is approximately 60 kDa . This information is critical for Western blot analysis, as it allows researchers to identify the correct band representing PAT4 and distinguish it from non-specific binding. When performing Western blots, always include appropriate molecular weight markers to accurately identify the target protein band.

How was PAT-4 antibody generated and what is its isotype?

PAT-4 antibody was created by immunizing mice with a keyhole limpet haemocyanin-conjugated, cysteine-coupled peptide based on an antigenic amino acid sequence within the N-terminus of PAT4 (REELDMDVMRPLINE-C) . The antibody is of the IgG2a kappa subclass and was developed using the P3/NS1/1-Ag4.1 myeloma cell line. The recommended growing conditions for hybridoma maintenance are RPMI medium supplemented with 10% FCS plus HAT essential .

What is the significance of PAT4 in cellular biology and disease?

PAT4 (SLC36A4) plays a significant role in cellular metabolism as a proton-assisted amino acid transporter. Research has identified PAT4 as a positive regulator of growth and mTORC1 signaling . The mTORC1 pathway integrates inputs from nutrients, growth factors, and energy status to regulate cell growth, protein synthesis, and metabolism. PAT4's upregulation in aggressive forms of colorectal cancer suggests its involvement in cancer progression, potentially through enhanced amino acid sensing and mTORC1 activation in cancer cells .

How does PAT4 contribute to mTORC1 signaling pathways?

PAT4 contributes to mTORC1 signaling as a positive regulator through its function as an amino acid transporter. The mTORC1 pathway integrates nutrient availability signals, including amino acids, to regulate cellular growth and metabolism. Studies initially in Drosophila identified members of the PAT/SLC36 family as growth regulators, with effects later confirmed to be conserved in human PAT proteins including PAT4 .

Current research suggests that PAT4 may transport specific amino acids that serve as signals for mTORC1 activation. The heightened expression of PAT4 in aggressive cancers indicates that enhanced amino acid transport through this protein might support increased mTORC1 activity, contributing to the accelerated growth and altered metabolism characteristic of cancer cells. Experimental approaches using PAT-4 antibody can help elucidate the mechanistic connections between PAT4 transport activity and mTORC1 signaling components.

How can PAT-4 antibody be used to investigate colorectal cancer biomarkers?

Given that PAT4 is upregulated in aggressive forms of colorectal cancer, PAT-4 antibody serves as a valuable tool for investigating its potential as a biomarker . Researchers can design studies using tissue microarrays from colorectal cancer patients at different disease stages to correlate PAT4 expression with clinical outcomes.

A comprehensive experimental approach would include:

Results from these approaches could establish whether PAT4 expression levels have prognostic value, predictive power for treatment response, or utility in patient stratification for targeted therapies.

What controls should be included when using PAT-4 antibody in cancer research?

When designing experiments with PAT-4 antibody for cancer research, rigorous controls are essential to ensure reliable and interpretable results. The following controls should be included:

• Positive tissue control: 786-O human renal cancer cells are recommended as a positive control for PAT-4 antibody . These cells express PAT4 and can validate antibody performance.

• Negative controls:

  • Isotype control: Use a non-specific mouse IgG2a kappa antibody to identify non-specific binding

  • Technical negative control: Omit primary antibody while keeping all other steps identical

  • Biological negative control: Include tissues or cells known to have minimal PAT4 expression

• Specificity controls:

  • Peptide competition: Pre-incubate PAT-4 antibody with the immunizing peptide sequence (REELDMDVMRPLINE-C) to demonstrate binding specificity

  • siRNA knockdown: Compare PAT4 staining in wild-type versus PAT4-knockdown samples

• Validation controls:

  • Orthogonal detection methods: Confirm PAT4 expression using alternative techniques like RT-qPCR or RNA-seq

  • Multiple antibody approach: If available, use antibodies targeting different PAT4 epitopes

Including these controls provides the necessary framework for confident interpretation of PAT-4 antibody results in cancer research contexts.

How can PAT-4 antibody be used in multiplexed immunoassays?

Multiplexed immunoassays using PAT-4 antibody can provide valuable insights into the relationship between PAT4 and other proteins in signaling networks. When designing multiplexed experiments, consider the following approaches:

• Sequential multiplexed IHC/IF:

  • Use PAT-4 antibody (mouse IgG2a) alongside antibodies from different host species (rabbit, goat)

  • Employ directly conjugated primary antibodies with different fluorophores

  • Consider sequential staining with stripping between rounds for antibodies from the same species

• Technical considerations:

  • Test for cross-reactivity between secondary antibodies

  • Optimize signal-to-noise ratio for each primary antibody independently first

  • Account for potential spectral overlap in fluorescence channels

• Recommended protein combinations:

  • PAT4 with mTORC1 pathway components (mTOR, Raptor, S6K)

  • PAT4 with other amino acid transporters (PAT1, LAT1)

  • PAT4 with cancer progression markers in colorectal tissue

When multiplexing with multiple rabbit antibodies, careful protocol design is required, potentially involving serial antibody labeling and stripping strategies or using directly labeled primary antibodies .

How does PAT4 differ functionally from other SLC36 family members?

While all SLC36 family members function as proton-assisted amino acid transporters, PAT4 (SLC36A4) exhibits distinct characteristics compared to other family members like PAT1 (SLC36A1). Both PAT1 and PAT4 are ubiquitously expressed in human tissues and function as positive regulators of growth and mTORC1 signaling, but they appear to have specialized roles .

Key differences may include:

• Substrate specificity and transport kinetics

• Subcellular localization patterns

• Tissue-specific expression profiles

• Regulatory mechanisms controlling transporter activity

• Pathological contexts in which they play significant roles

PAT4's particular upregulation in aggressive colorectal cancers suggests a unique role in certain pathological contexts that may not be shared by other family members . Comparative studies using antibodies against different PAT family members can help delineate their distinct functions and contributions to normal physiology and disease states.

What are the recommended sample preparation protocols for PAT-4 antibody in IHC?

For optimal PAT-4 antibody performance in immunohistochemistry, careful sample preparation is crucial. The following protocol is recommended:

• Tissue collection and fixation:

  • Fix tissues in 10% neutral-buffered formalin for 24-48 hours

  • Maintain consistent fixation times across experimental samples

  • Process and embed in paraffin following standard histology protocols

• Sectioning:

  • Cut sections at 4-5 μm thickness

  • Mount on positively charged slides

  • Air dry overnight or at 37°C for 1 hour

• Antigen retrieval:

  • Deparaffinize and rehydrate sections

  • Perform heat-induced epitope retrieval using citrate buffer (pH 6.0) or EDTA buffer (pH 9.0)

  • Optimize retrieval conditions (time, temperature, buffer) for your specific tissue type

• Blocking steps:

  • Block endogenous peroxidase with 3% H₂O₂ in methanol (10 minutes)

  • Block non-specific binding with 5-10% normal serum in PBS with 1% BSA (30-60 minutes)

• Antibody incubation:

  • Incubate with appropriately diluted PAT-4 antibody (starting at 1:200 dilution)

  • Optimize incubation conditions (time, temperature, diluent)

• Detection and visualization:

  • Use appropriate detection system based on experimental requirements

  • Counterstain, dehydrate, and mount using standard procedures

This protocol should be optimized for specific tissue types and research questions.

What dilution ranges should be tested for PAT-4 antibody in different applications?

Determining the optimal dilution of PAT-4 antibody is critical for achieving specific signal with minimal background. The following table summarizes recommended dilution ranges for different applications:

For each new experimental system or antibody lot, perform a dilution series to identify the concentration providing optimal signal-to-noise ratio. The dilution yielding the strongest specific signal with minimal background should be selected. Document optimization results for future reference.

What are the optimal Western blot conditions for detecting PAT4 with this antibody?

For optimal detection of PAT4 (~60 kDa) using Western blot, the following protocol is recommended:

• Sample preparation:

  • Lyse cells in RIPA buffer containing protease inhibitors

  • Include phosphatase inhibitors if phosphorylation status is relevant

  • Determine protein concentration using Bradford or BCA assay

• Gel electrophoresis:

  • Load 20-50 μg total protein per lane

  • Use 10% or 4-12% gradient SDS-PAGE gels

  • Include 786-O human renal cancer cell lysate as positive control

• Transfer:

  • Transfer to PVDF membrane at 100V for 1 hour or 30V overnight at 4°C

  • Verify transfer efficiency with reversible protein stain

• Blocking:

  • Block with 5% non-fat dry milk in TBST for 1 hour at room temperature

  • For phospho-specific studies, consider 5% BSA instead of milk

• Antibody incubation:

  • Dilute PAT-4 antibody 1:1000 in blocking buffer

  • Incubate overnight at 4°C with gentle agitation

  • Wash thoroughly with TBST (3 × 10 minutes)

• Detection:

  • Incubate with HRP-conjugated anti-mouse secondary antibody (1:5000)

  • Wash thoroughly with TBST (3 × 10 minutes)

  • Develop using ECL substrate and image

• Controls and validation:

  • Include molecular weight markers

  • Run parallel blots for loading controls (e.g., β-actin, GAPDH)

  • Consider peptide competition control for specificity verification

This protocol should be optimized for specific cell types and experimental conditions.

How can researchers distinguish between specific and non-specific staining with PAT-4 antibody?

Distinguishing specific PAT-4 antibody staining from non-specific background is crucial for accurate data interpretation. Implement the following strategies:

• Pattern analysis:

  • Specific PAT4 staining should show a pattern consistent with its known subcellular localization

  • Membrane-associated staining is expected for a transporter protein like PAT4

  • Diffuse or ubiquitous staining may indicate non-specific binding

• Control comparisons:

  • Compare staining patterns between positive controls (786-O cells) and negative controls

  • Include technical controls (primary antibody omission, isotype controls)

  • Use peptide competition to confirm signal specificity

• Signal validation:

  • Test multiple antibody concentrations to identify optimal signal-to-noise ratio

  • Compare staining across different detection systems

  • Evaluate staining in tissues with known PAT4 expression profiles

• Orthogonal verification:

  • Correlate protein detection with mRNA expression

  • Use genetic manipulation (siRNA knockdown) to confirm specificity

  • If available, employ alternative antibodies targeting different PAT4 epitopes

• Technical optimization:

  • Adjust blocking conditions to minimize background

  • Optimize washing steps (duration, buffer composition)

  • Consider alternative fixation or antigen retrieval methods

Systematic implementation of these approaches will help ensure that observed signals truly represent PAT4 distribution rather than artifacts or non-specific interactions.

What troubleshooting strategies are most effective for PAT-4 antibody experiments?

When encountering challenges with PAT-4 antibody experiments, systematic troubleshooting approaches can help identify and resolve issues:

For recurring issues, consider reaching out to the antibody manufacturer for technical support and consult recent literature for optimized protocols specific to PAT4 detection in your experimental system.

How should researchers quantify PAT4 expression in immunohistochemical samples?

Accurate quantification of PAT4 expression in immunohistochemical samples requires standardized approaches:

• Scoring systems:

  • H-score: Calculate by multiplying staining intensity (0-3) by percentage of positive cells (0-100), yielding scores from 0-300

  • Allred score: Combine proportion score (0-5) and intensity score (0-3) for a total score of 0-8

  • Quick score: Similar to H-score but with simplified categories

• Digital image analysis:

  • Use calibrated image analysis software for unbiased quantification

  • Define regions of interest (ROI) consistently across samples

  • Measure parameters including staining intensity, percentage positive area, and staining pattern

• Controls and normalization:

  • Include reference standards in each staining batch

  • Normalize data to account for batch-to-batch variations

  • Use internal controls within each tissue section when possible

• Statistical considerations:

  • Determine appropriate sample size through power analysis

  • Establish scoring thresholds based on control samples

  • Consider inter-observer and intra-observer variability

• Reporting standards:

  • Clearly document quantification methods in publications

  • Include representative images of different staining intensities

  • Report both raw and normalized/processed data

Consistent application of these approaches enables reliable comparisons across samples and studies, enhancing the reproducibility and clinical relevance of PAT4 expression analysis.

What approaches can be used to correlate PAT4 expression with mTORC1 signaling activity?

To investigate the relationship between PAT4 expression and mTORC1 signaling activity, researchers can employ several complementary approaches:

• Co-localization studies:

  • Perform dual immunofluorescence with PAT-4 antibody and antibodies against mTORC1 components (mTOR, Raptor)

  • Analyze co-localization using confocal microscopy and quantitative co-localization metrics

  • Examine subcellular distribution patterns under different nutrient conditions

• Functional correlation:

  • Manipulate PAT4 expression (overexpression, knockdown) and measure changes in:

    • Phosphorylation of mTORC1 substrates (S6K, 4E-BP1) by Western blot

    • mTORC1 localization to lysosomes by immunofluorescence

    • Cell size and protein synthesis rates as functional readouts

• Pharmacological approaches:

  • Compare PAT4 inhibition/knockdown with direct mTORC1 inhibitors (rapamycin, torin)

  • Assess responses to amino acid availability under PAT4 manipulation

  • Evaluate differential effects on downstream mTORC1 targets

• Clinical sample analysis:

  • Quantify PAT4 expression and phospho-S6K/4E-BP1 levels in patient samples

  • Perform correlation analysis between PAT4 levels and mTORC1 activity markers

  • Stratify patients based on PAT4/mTORC1 status and analyze clinical outcomes

• Systems biology approaches:

  • Integrate PAT4 expression data with phosphoproteomics of mTORC1 pathway components

  • Model PAT4-mTORC1 relationships across different tissue/cell types

  • Identify feedback mechanisms and regulatory networks

These approaches collectively provide a comprehensive assessment of how PAT4 contributes to mTORC1 signaling regulation in both normal and pathological contexts.

How should conflicting results between PAT4 protein and mRNA expression be interpreted?

Discrepancies between PAT4 protein levels detected with PAT-4 antibody and mRNA expression measurements are not uncommon and require careful interpretation:

• Biological explanations:

  • Post-transcriptional regulation: microRNAs or RNA-binding proteins may regulate PAT4 mRNA translation

  • Protein stability: PAT4 protein half-life may differ substantially from mRNA half-life

  • Translational efficiency: Factors affecting ribosome recruitment to PAT4 mRNA

  • Post-translational modifications: Changes affecting antibody epitope recognition

• Technical considerations:

  • Sensitivity differences between protein and RNA detection methods

  • Antibody specificity issues (cross-reactivity with related proteins)

  • Sample preparation differences affecting protein vs. RNA preservation

  • Primer design limitations for mRNA detection

• Verification approaches:

  • Use alternative detection methods for both protein and mRNA

  • Perform time-course studies to identify temporal relationships

  • Examine multiple epitopes if alternative antibodies are available

  • Include positive controls with known protein/mRNA ratios

• Reconciliation strategies:

  • Consider subcellular fractionation to identify protein localization changes

  • Investigate potential translational regulation mechanisms

  • Examine PAT4 regulation in different cellular contexts

When faced with discrepancies, avoid dismissing either result. Instead, consider these differences as potential insights into PAT4 regulation that warrant further investigation.

What are the best practices for comparing PAT4 expression across different tumor samples?

For reliable comparison of PAT4 expression across tumor samples using PAT-4 antibody, implement these best practices:

• Standardized sample handling:

  • Maintain consistent collection protocols

  • Standardize fixation time and conditions

  • Process and store samples uniformly

  • Document ischemia time and fixation parameters

• Batch controls and normalization:

  • Include control samples in each staining batch

  • Use tissue microarrays when possible to minimize batch effects

  • Include internal reference standards for normalization

  • Process all comparative samples simultaneously

• Quantification methods:

  • Employ consistent scoring/quantification approaches

  • Use digital image analysis for objective assessment

  • Analyze multiple fields per sample (minimum 3-5)

  • Blind observers to sample identity during scoring

• Data analysis considerations:

  • Account for tumor heterogeneity in sampling strategy

  • Normalize for tissue composition (tumor percentage)

  • Consider cell-specific analysis rather than whole-sample average

  • Use appropriate statistical methods for non-normally distributed data

• Reporting and validation:

  • Document antibody lot, dilution, and staining protocol details

  • Include representative images across expression ranges

  • Validate key findings with orthogonal techniques

  • Consider multi-institutional validation for clinical applications

Following these practices enhances the reliability and reproducibility of comparative PAT4 expression studies, particularly in clinical research contexts.

How can researchers integrate PAT4 expression data with other cancer biomarkers?

Integrating PAT4 expression data with other cancer biomarkers provides a more comprehensive understanding of disease mechanisms and potential therapeutic strategies:

• Multiparameter analysis approaches:

  • Multiplexed immunohistochemistry/immunofluorescence

  • Sequential staining protocols for tissue sections

  • Digital spatial profiling technologies

  • Multi-omics integration (proteomics, transcriptomics, metabolomics)

• Statistical integration methods:

  • Correlation analysis between PAT4 and other markers

  • Hierarchical clustering to identify patient subgroups

  • Principal component analysis for dimension reduction

  • Machine learning approaches for pattern recognition

• Pathway-focused integration:

  • Combine PAT4 with other mTORC1 pathway components

  • Analyze alongside metabolic markers (other transporters, metabolic enzymes)

  • Integrate with proliferation and survival markers

  • Correlate with drug resistance indicators

• Clinical data integration:

  • Relate PAT4 expression patterns to treatment responses

  • Analyze survival outcomes based on combined marker profiles

  • Develop predictive models incorporating multiple markers

  • Validate in independent patient cohorts

• Visualization strategies:

  • Heat maps for multiple marker comparisons

  • Network diagrams showing marker relationships

  • Forest plots for prognostic/predictive value comparisons

  • Interactive dashboards for exploratory data analysis

This integrated approach can reveal new insights into the role of PAT4 in cancer biology and identify opportunities for precision medicine strategies targeting PAT4-dependent pathways in specific patient subgroups.

How might PAT-4 antibody be used in high-throughput screening applications?

PAT-4 antibody offers significant potential for high-throughput screening applications to identify modulators of PAT4 expression or function:

• Cell-based screening platforms:

  • Develop automated immunofluorescence protocols for PAT4 detection

  • Create cell lines with fluorescent reporters linked to PAT4 promoter

  • Establish high-content imaging workflows to assess PAT4 subcellular distribution

• Compound screening applications:

  • Screen for small molecules that modulate PAT4 expression

  • Identify compounds that affect PAT4 trafficking or stability

  • Discover drugs that selectively target PAT4-overexpressing cancer cells

• Functional screening approaches:

  • Combine PAT-4 antibody detection with metabolic measurements

  • Integrate with amino acid uptake assays to correlate transport with expression

  • Assess effects on downstream mTORC1 signaling in parallel

• Technical considerations:

  • Optimize PAT-4 antibody protocols for microplate formats

  • Develop quantitative readouts amenable to statistical analysis

  • Implement automated image analysis pipelines for consistent scoring

• Validation strategies:

  • Confirm hits with orthogonal assays

  • Validate effects in multiple cell types

  • Establish dose-response relationships for promising compounds

Such screening approaches could identify novel therapeutic strategies for cancers where PAT4 overexpression contributes to disease progression, particularly aggressive colorectal cancers mentioned in the antibody literature .

What emerging technologies might enhance PAT4 detection and functional analysis?

Several emerging technologies hold promise for advancing PAT4 detection and functional analysis beyond traditional antibody-based methods:

• Advanced imaging technologies:

  • Super-resolution microscopy for precise subcellular localization

  • Label-free imaging techniques for live cell PAT4 monitoring

  • Correlative light and electron microscopy for ultrastructural context

• Single-cell analysis platforms:

  • Mass cytometry (CyTOF) for high-parameter single-cell profiling

  • Single-cell proteomics for PAT4 expression heterogeneity assessment

  • Digital spatial profiling for in situ single-cell analysis

• Protein interaction mapping:

  • Proximity labeling techniques (BioID, APEX) to identify PAT4 interaction partners

  • Protein complementation assays for dynamic interaction monitoring

  • Native mass spectrometry for intact complex analysis

• Functional assessment technologies:

  • Microfluidic systems for real-time amino acid transport measurement

  • CRISPR-based genetic screens for PAT4 pathway components

  • Metabolic flux analysis to assess PAT4's impact on cellular metabolism

• In vivo monitoring approaches:

  • Antibody-based imaging probes for non-invasive PAT4 detection

  • Patient-derived organoids for personalized PAT4 functional assessment

  • Circulating tumor cell analysis for PAT4 expression in metastatic disease

Integration of these technologies with traditional antibody-based methods will provide more comprehensive insights into PAT4 biology and its potential as a therapeutic target.