SLC39A1 Antibody Pair

What is SLC39A1 and why is it important in research?

SLC39A1, also known as ZIP1 (Zinc-Iron-regulated transporter-like Protein 1), is a member of the zinc-iron permease family localized to the cell membrane. It functions as a zinc uptake transporter, mediating the influx of Zn²⁺ into cells from extracellular space . SLC39A1 plays a pivotal role in maintaining zinc balance within cells and is involved in various physiological processes including immune function, growth, and development . It may function as a major endogenous zinc uptake transporter in many cells throughout the body and is responsible for the rapid uptake and accumulation of physiologically effective zinc in prostate cells . The importance of SLC39A1 in research stems from its dysregulation being linked to various diseases, including cancer, diabetes, and neurodegenerative disorders, highlighting its potential as a therapeutic target .

How do I select the appropriate SLC39A1 antibody for my experimental needs?

When selecting an SLC39A1 antibody, consider these methodological factors:

• Experimental application: Determine which applications you need the antibody for (Western blot, IHC, IF, ELISA, etc.) and verify the antibody is validated for those specific applications. For example, some antibodies like ab105416 are suitable for WB, IHC-P, and ICC/IF , while others may be optimized for ELISA only .

• Species reactivity: Confirm the antibody reacts with your species of interest. Many SLC39A1 antibodies react with human samples, but cross-reactivity with mouse or rat samples varies between products .

• Validation data: Review the available validation data for each antibody. Look for antibodies with multiple validations (denoted by numbers in parentheses in catalogs) and published citations .

• Antibody type: Consider whether a polyclonal or monoclonal antibody better suits your needs. Polyclonal antibodies like PACO33876 may provide higher sensitivity but potentially lower specificity .

• Immunogen information: Review the immunogen used to generate the antibody. For instance, PACO33876 was generated using recombinant Human Zinc transporter ZIP1 protein (amino acids 126-179) , which may affect epitope recognition.

What are the recommended storage conditions for SLC39A1 antibodies?

For optimal performance and longevity of SLC39A1 antibodies, follow these methodological storage guidelines:

• Temperature: Most SLC39A1 antibodies should be stored at -20°C for long-term storage .

• Buffer composition: Many commercially available antibodies are provided in specific buffer formulations designed to maintain stability. For example, PACO33876 is supplied in a storage buffer containing 0.03% Proclin 300, 50% Glycerol, and 0.01M PBS at pH 7.4 .

• Aliquoting: To prevent repeated freeze-thaw cycles, divide the antibody into small aliquots before freezing, especially for frequent use.

• Working dilutions: Diluted working solutions can typically be stored at 4°C for up to one week, but specific recommendations may vary by manufacturer.

• Avoid contamination: Use sterile techniques when handling antibodies to prevent microbial contamination.

Following proper storage conditions will help maintain antibody specificity and sensitivity, ensuring reliable experimental results in SLC39A1 detection assays.

How can SLC39A1 expression be effectively analyzed in cancer tissues?

Analysis of SLC39A1 expression in cancer tissues requires a multi-faceted methodological approach:

For comprehensive analysis, integrate results from multiple detection methods and correlate with clinical data to understand the biological significance of SLC39A1 alterations in specific cancer types.

What are the methodological considerations for investigating SLC39A1's role in immune cell infiltration?

Investigating SLC39A1's role in immune cell infiltration requires sophisticated methodological approaches:

• Single-sample Gene Set Enrichment Analysis (ssGSEA): This computational approach can evaluate the correlation between SLC39A1 expression and immune cell populations. Research in hepatocellular carcinoma has utilized this method to demonstrate that SLC39A1 overexpression is associated with increased infiltration of Th2 cells and reduced infiltration of cytotoxic cells .

• Immunohistochemical Multi-staining: Perform multiplex IHC to simultaneously visualize SLC39A1 expression and immune cell markers in tissue sections. This approach allows for spatial correlation between SLC39A1 expression patterns and specific immune cell populations.

• Flow Cytometry Analysis: When working with fresh tissues or in vitro models, flow cytometry can quantify immune cell populations in relation to SLC39A1 expression levels. Consider using SLC39A1 antibodies conjugated with fluorochromes or implementing sequential staining protocols.

• In vitro Co-culture Systems: Establish co-culture systems with SLC39A1-modulated cancer cells and immune cells to directly investigate functional interactions. Monitor changes in immune cell activation, cytokine production, and cytotoxic activity.

• Cytokine Profiling: Measure cytokine production in relation to SLC39A1 expression to understand how this zinc transporter influences the tumor immune microenvironment.

When designing these experiments, it's crucial to incorporate appropriate controls and validate findings across multiple experimental systems. Integration of these approaches provides a comprehensive understanding of how SLC39A1 impacts immune infiltration in the tumor microenvironment, which has important implications for immunotherapy research.

How do I integrate transcriptomic, proteomic, and metabolomic approaches to understand SLC39A1 function?

Integrating multi-omics approaches to understand SLC39A1 function requires careful experimental design and comprehensive data analysis:

• Experimental Design for Multi-omics Integration:

  • Use consistent cellular/tissue models across all platforms

  • Include SLC39A1 overexpression and knockdown conditions alongside appropriate controls

  • Process samples in parallel for different omics analyses to minimize batch effects

• Transcriptomic Analysis:

  • Perform RNA-seq or microarray analysis on SLC39A1-modulated cells

  • Identify differentially expressed genes and enriched pathways

  • Focus on zinc-responsive transcription factors and downstream targets

• Proteomic Analysis:

  • Implement mass spectrometry-based proteomics to identify altered protein expression and post-translational modifications

  • Consider phosphoproteomics to capture signaling pathway changes

  • Verify key findings with orthogonal methods like Western blotting

• Metabolomic Analysis:

  • Use untargeted and targeted metabolomics to capture both global metabolic shifts and specific metabolite changes

  • Pay particular attention to metabolic pathways known to be affected by zinc availability

• Integrated Data Analysis:

  • Employ pathway enrichment analysis across all omics datasets

  • Identify concordant and discordant patterns between transcripts, proteins, and metabolites

  • Use network analysis to identify key nodes connecting different molecular layers

The power of this approach has been demonstrated in renal cell carcinoma research, where SLC39A1 transfection was shown to significantly alter several metabolic pathways at transcriptional, protein, and metabolic levels. These included purine and pyrimidine metabolism, amino acid and derivatives metabolism, lactose metabolism, and free fatty acid metabolism . Additionally, SLC39A1 overexpression promoted ferroptosis and triggered significant crosstalk in PI3K-AKT signaling, cAMP signaling, and peroxisome proliferators-activated receptor (PPAR) signaling pathways .

What are the common challenges in detecting SLC39A1 using Western blot and how can they be overcome?

Western blot detection of SLC39A1 presents several challenges that can be addressed with these methodological solutions:

• Background Issues:

  • Challenge: High background can mask specific SLC39A1 bands, especially with polyclonal antibodies.

  • Solution: Optimize blocking conditions (try 5% BSA instead of milk for zinc-binding proteins), increase washing time and volume, and use freshly prepared buffers. Consider titrating primary antibody concentration; for instance, ab105416 has been used at both 1 μg/mL and 2 μg/mL concentrations for mouse kidney tissue lysate .

• Multiple Bands:

  • Challenge: Detecting multiple bands instead of the predicted 34 kDa SLC39A1 band.

  • Solution: Validate specificity using positive and negative controls, including SLC39A1 knockdown/knockout samples. Consider that post-translational modifications may affect protein migration. Always compare with the expected band size (34 kDa for SLC39A1) .

• Low Signal Intensity:

  • Challenge: Weak detection of endogenous SLC39A1.

  • Solution: Increase protein loading (15-30 μg per lane), optimize primary antibody incubation (overnight at 4°C), and use enhanced chemiluminescence (ECL) substrates with appropriate sensitivity. The validated protocol used 15 μg of mouse kidney tissue lysate with ab105416 antibody .

• Tissue-Specific Expression Variation:

  • Challenge: Variable SLC39A1 expression across different tissues and cell lines.

  • Solution: Select appropriate positive controls based on literature. Kidney tissue is a reliable positive control for SLC39A1 detection . Consider longer exposure times for tissues with lower expression levels.

• Protein Degradation:

  • Challenge: Loss of SLC39A1 signal due to protein degradation.

  • Solution: Use fresh samples whenever possible, include protease inhibitors in lysis buffers, maintain samples at cold temperatures during processing, and avoid repeated freeze-thaw cycles.

By systematically addressing these challenges, researchers can achieve reliable and specific detection of SLC39A1 in Western blot applications, enabling accurate quantification of this important zinc transporter in various experimental conditions.

How do I optimize immunostaining protocols for SLC39A1 detection in different tissue types?

Optimizing immunostaining protocols for SLC39A1 requires tissue-specific adjustments and methodological considerations:

• Antigen Retrieval Optimization:

  • Liver Tissue: For hepatocellular carcinoma samples, heat-induced epitope retrieval using citrate buffer (pH 6.0) has proven effective for SLC39A1 detection .

  • Kidney Tissue: For renal cell carcinoma specimens, EDTA buffer (pH 9.0) may provide superior unmasking of SLC39A1 epitopes .

  • Other Tissues: Systematically compare different antigen retrieval methods (heat vs. enzymatic, different pH buffers) to determine optimal conditions for your specific tissue.

• Primary Antibody Concentration and Incubation:

  • Start with manufacturer's recommended dilutions (varies by antibody).

  • For tissues with expected low expression (like early-stage HCC), longer incubation times (overnight at 4°C) with more concentrated antibody solution may improve detection .

  • For tissues with high expression, titrate antibody concentration to prevent oversaturation and background.

• Signal Amplification Strategies:

  • For weakly expressed SLC39A1, employ tyramide signal amplification (TSA) systems.

  • Consider using polymer-based detection systems which offer higher sensitivity than traditional avidin-biotin methods.

  • For multiplex staining, sequential TSA approach allows co-localization studies with other markers.

• Tissue-Specific Background Reduction:

  • High-Lipid Tissues: Extended permeabilization with 0.3% Triton X-100 improves antibody penetration.

  • Tissues with High Endogenous Peroxidase: Double quenching steps (3% H₂O₂, 10-15 minutes each) may be necessary.

  • Tissues with Endogenous Biotin: Consider biotin-free detection systems or additional blocking steps.

• Counterstaining Considerations:

  • For subcellular localization studies, nuclear counterstains like DAPI or Hoechst provide context.

  • For quantitative analysis of membrane-localized SLC39A1, moderate hematoxylin counterstaining prevents signal masking.

Always include both positive controls (tissues known to express SLC39A1, such as kidney) and negative controls (primary antibody omission, isotype controls) to validate staining specificity. Systematic optimization of these parameters will enable reliable SLC39A1 detection across diverse tissue types.

What strategies can resolve conflicting data regarding SLC39A1 expression in cancer studies?

Resolving conflicting data on SLC39A1 expression in cancer requires systematic methodological approaches:

• Reconciling Opposite Expression Patterns:

  • Methodological Approach: When faced with studies showing both overexpression and decreased expression of SLC39A1 in hepatocellular carcinoma, implement the following strategy:

    • Compare cancer staging between studies (early vs. advanced HCC)

    • Analyze cancer subtypes and etiologies (viral vs. non-viral, fibrotic background)

    • Evaluate detection methods (antibody clones, detection systems)

    • Assess scoring systems and quantification approaches

• Cell Type-Specific Expression Analysis:

  • Methodological Approach: Use single-cell technologies or laser capture microdissection to isolate specific cell populations from heterogeneous tumors.

  • This approach can reveal that apparent contradictions may reflect different cell types within the tumor microenvironment expressing SLC39A1 at varying levels.

• Functional Validation Experiments:

  • Methodological Approach: Implement both overexpression and knockdown/knockout models to assess functional outcomes.

  • For example, SLC39A1 knockdown has been shown to repress proliferation, invasion, and migration abilities of HCC cells , while transfection with SLC39A1 in renal cancer cells impaired tumor metabolism .

• Integrating Multi-omics Data:

  • Methodological Approach: Analyze SLC39A1 at genomic, transcriptomic, proteomic, and metabolomic levels within the same samples.

  • This approach can identify post-transcriptional regulation mechanisms explaining discrepancies between mRNA and protein levels.

• Context-Dependent Expression Analysis:

  • Methodological Approach: Systematically evaluate SLC39A1 expression in relation to:

    • Zinc availability in tumor microenvironment

    • Hypoxic vs. normoxic regions

    • Proliferative vs. invasive tumor fronts

    • Response to treatment (pre/post-therapy samples)

By implementing these methodological approaches, researchers can better understand the complex and potentially context-dependent role of SLC39A1 in cancer biology, leading to more accurate interpretation of seemingly conflicting data.