SLC1A3 Antibody

What is SLC1A3 and why is it important in research?

SLC1A3 (Solute Carrier Family 1 Member 3) encodes the excitatory amino acid transporter 1 (EAAT1), a glial high-affinity glutamate transporter primarily expressed in astrocytes. This protein plays a crucial role in glutamate homeostasis by removing excess glutamate from the synaptic cleft, preventing excitotoxicity. SLC1A3 is considered a documented astrocyte marker, making its detection valuable in neuroscience research . Recent studies have also identified SLC1A3 as a potential prognostic biomarker in hepatocellular carcinoma (HCC), suggesting its role extends beyond glutamate transport to immune modulation and cancer progression . The protein has a molecular weight of approximately 59.6 kilodaltons and is conserved across multiple species including humans, mice, and rats.

What are the common applications for SLC1A3 antibodies?

SLC1A3 antibodies are utilized across multiple experimental applications, with varying degrees of optimization depending on the specific antibody variant. The most common applications include:

These applications enable researchers to visualize SLC1A3 expression patterns in tissues, assess protein levels in experimental conditions, and determine subcellular localization . The selection of the appropriate application depends on the specific research question and available sample types.

How do I choose between different SLC1A3 antibody variants?

When selecting an SLC1A3 antibody, researchers should consider the specific domain being targeted, species reactivity, and validated applications. Various antibodies target different epitopes of the SLC1A3 protein:

• Cytoplasmic domain antibodies - target amino acids in intracellular regions

• C-terminal antibodies - recognize sequences at the C-terminus (e.g., AA 519-537)

• N-terminal antibodies - bind to sequences at the N-terminus (e.g., AA 14-42)

• Extracellular loop antibodies - target exposed regions (e.g., 2nd extracellular loop, AA 188-200)

Species reactivity is another critical factor, as some antibodies are optimized for human samples while others work across human, mouse, and rat tissues. Most commercial SLC1A3 antibodies are polyclonal and raised in rabbits, though some monoclonal options exist for applications requiring higher specificity . Review the validation data for your specific application before selection, as performance can vary significantly between applications even for the same antibody.

How can SLC1A3 antibodies be utilized to study its role in immune cell infiltration?

Recent studies have identified significant correlations between SLC1A3 expression and immune cell infiltration patterns in hepatocellular carcinoma. To investigate these relationships, researchers can employ a multi-faceted approach combining antibody-based techniques with bioinformatics analysis:

• Tissue microarray (TMA) immunohistochemistry using validated SLC1A3 antibodies to quantify expression levels across patient cohorts

• Multiplex immunofluorescence to simultaneously visualize SLC1A3 and immune cell markers

• Correlation of protein expression data with transcriptomic profiles

Analysis of the LIHC dataset revealed that SLC1A3 expression positively correlates with infiltration of T cells CD4 memory activated, while negatively correlating with anti-tumor immune cells such as activated NK cells and monocytes . This finding suggests SLC1A3 may play a role in immune evasion mechanisms in HCC. To validate these relationships experimentally, researchers can use SLC1A3 antibodies in combination with immune cell markers in multiplex immunostaining protocols, followed by quantitative image analysis.

What are the challenges in SLC1A3 antibody specificity and how can they be addressed?

Ensuring antibody specificity remains a significant challenge in SLC1A3 research due to sequence homology with other glutamate transporters and potential cross-reactivity. Several approaches can mitigate these issues:

• Validation through knockout/knockdown controls: Using tissues or cells with SLC1A3 knockdown (via siRNA approaches) as negative controls. Specific siRNA sequences for SLC1A3 knockdown include: 5′-CGACAGTGAAACCAAGATGTA-3′ and 5′-CCGACCATACAGAATGAGCTA-3′ .

• Epitope mapping: Selecting antibodies targeting unique regions of SLC1A3 that have minimal homology with related proteins.

• Cross-validation with multiple antibodies: Using antibodies recognizing different epitopes (N-terminal vs. C-terminal) to confirm consistent staining patterns.

• Enhanced validation approaches: Utilizing orthogonal methods such as RNAseq correlation data to verify antibody specificity .

• Species-specific considerations: When working across species, select antibodies recognizing conserved epitopes or species-specific variants.

The immunogen sequence information provided with commercial antibodies can help determine potential cross-reactivity. For example, one antibody uses the immunogen sequence "NGEEPKMGGRMERFQQGVRKRTLLAKKKVQNITKEDVK" , while another targets "MKKPYQLIAQDNETEKPID" at the C-terminus .

How can SLC1A3 antibodies be employed in studying its regulation of the EMT process in cancer?

SLC1A3 has been implicated in regulating the epithelial-mesenchymal transition (EMT) process in hepatocellular carcinoma, contributing to poor prognosis . Investigating this regulatory role requires sophisticated experimental designs:

• Protein-protein interaction studies: Co-immunoprecipitation using SLC1A3 antibodies followed by mass spectrometry to identify binding partners involved in EMT signaling.

• Subcellular localization changes: Immunofluorescence with SLC1A3 antibodies to track localization changes during EMT induction.

• Correlation with EMT markers: Dual immunohistochemistry or western blot analysis to assess relationships between SLC1A3 and classical EMT markers (E-cadherin, vimentin, Snail, etc.).

• Functional validation: Combine SLC1A3 knockdown/overexpression with antibody-based detection of EMT markers to establish causality.

• Patient sample analysis: Retrospective studies using tissue microarrays stained for SLC1A3 and EMT markers to evaluate clinical correlations.

For western blot analysis, researchers should use RIPA buffer with protease inhibitors for protein extraction, followed by SDS-PAGE separation and transfer to PVDF membranes. Chemiluminescence detection methods provide sensitive visualization of protein bands . Quantitative image analysis software can then be used to correlate SLC1A3 expression levels with EMT marker expression across experimental conditions or patient samples.

What protocols are recommended for immunohistochemistry using SLC1A3 antibodies?

For optimal immunohistochemistry results with SLC1A3 antibodies, the following protocol is recommended:

Paraffin-embedded sections (IHC-P):

• Deparaffinization and rehydration:

  • Xylene: 2 × 5 minutes

  • 100% ethanol: 2 × 3 minutes

  • 95%, 80%, 70% ethanol: 3 minutes each

  • Distilled water: 5 minutes

• Antigen retrieval:

  • Heat-induced epitope retrieval in citrate buffer (pH 6.0) for 20 minutes

  • Cool to room temperature for 20 minutes

• Peroxidase blocking:

  • 3% hydrogen peroxide in methanol for 15 minutes

  • PBS wash: 3 × 5 minutes

• Blocking:

  • 5% normal goat serum in PBS with 0.1% Triton X-100 for 1 hour

• Primary antibody incubation:

  • Dilute SLC1A3 antibody 1:200-1:500 in blocking solution

  • Incubate overnight at 4°C in a humidified chamber

• Secondary antibody and detection:

  • PBS wash: 3 × 5 minutes

  • HRP-conjugated secondary antibody: 1 hour at room temperature

  • PBS wash: 3 × 5 minutes

  • DAB development: 2-10 minutes (monitor under microscope)

  • Counterstain with hematoxylin, dehydrate, and mount

For immunofluorescence applications, replace steps 3-6 with fluorophore-conjugated secondary antibodies and DAPI counterstaining. Proper controls should include primary antibody omission and, ideally, tissue from SLC1A3 knockout models or siRNA-treated samples .

How can I optimize western blot protocols for SLC1A3 detection?

Western blot analysis for SLC1A3 requires careful optimization due to the protein's membrane-associated nature and potential post-translational modifications. The following protocol enhances detection sensitivity:

• Sample preparation:

  • Use RIPA buffer supplemented with protease inhibitors

  • Include phosphatase inhibitors if phosphorylation status is relevant

  • Homogenize tissues thoroughly on ice

  • Sonicate briefly (3 × 10 seconds) to shear DNA

  • Centrifuge at 12,000g for 15 minutes at 4°C

  • Collect supernatant and determine protein concentration

• Gel electrophoresis:

  • Use 8-10% SDS-PAGE gels (SLC1A3 is approximately 60 kDa)

  • Load 20-40 μg protein per lane

  • Include positive control (brain tissue lysate)

  • Run at 100V until dye front reaches bottom

• Transfer:

  • Use PVDF membrane (better for hydrophobic proteins)

  • Transfer at 100V for 60-90 minutes in cold transfer buffer

  • Verify transfer using Ponceau S staining

• Blocking and antibody incubation:

  • Block with 5% non-fat milk or BSA in TBST for 1 hour

  • Incubate with SLC1A3 antibody (1:500-1:2000) overnight at 4°C

  • Wash 3 × 10 minutes with TBST

  • Incubate with HRP-conjugated secondary antibody for 1 hour

  • Wash 3 × 10 minutes with TBST

• Detection:

  • Use enhanced chemiluminescence substrate

  • Expose to X-ray film or image using a digital imager

  • Expected band size: 59-65 kDa (depending on glycosylation)

Key optimization steps include preventing protein degradation during sample preparation, adjusting antibody concentration based on signal-to-noise ratio, and using longer blocking times for highly sensitive antibodies .

What considerations are important when using SLC1A3 antibodies for quantitative analyses?

Quantitative analysis using SLC1A3 antibodies requires rigorous controls and standardization:

• Establishing linearity ranges:

  • For western blots: Create standard curves using increasing amounts of protein

  • For IHC/IF: Titrate antibody concentrations to determine optimal signal-to-noise ratio

• Normalization strategies:

  • Western blot: Normalize to appropriate loading controls (β-actin, GAPDH, or membrane protein controls like Na+/K+ ATPase)

  • IHC/IF: Use internal controls (unaffected regions of the same tissue) for relative quantification

• Technical replicates:

  • Perform at least three technical replicates per experiment

  • Include biological replicates (different samples from the same experimental group)

• Image acquisition standardization:

  • For fluorescence: Establish fixed exposure settings based on brightest sample

  • For IHC: Standardize staining batch, development time, and imaging parameters

• Quantification methods:

  • For IHC: H-score method (staining intensity × percentage of positive cells)

  • For IF: Mean fluorescence intensity or integrated density measurements

  • For WB: Densitometry with background subtraction

• Statistical analysis:

  • Use appropriate statistical tests based on data distribution

  • Report variability measures (standard deviation or standard error)

  • Define significance thresholds prior to analysis

When comparing SLC1A3 expression across experimental conditions, consider using multiple antibodies targeting different epitopes to validate findings, particularly for novel or contentious observations .

How does SLC1A3 expression correlate with immune cell infiltration in cancer?

Recent studies using CIBERSORT immune infiltration analysis have revealed significant correlations between SLC1A3 expression and immune cell populations in hepatocellular carcinoma:

These findings suggest that SLC1A3 may influence the tumor immune microenvironment, potentially contributing to immune evasion mechanisms. The positive correlation with activated memory CD4+ T cells coupled with negative correlations with anti-tumor immune cells (NK cells, monocytes) indicates that SLC1A3 could play a role in creating an immunosuppressive environment favorable for tumor growth .

To investigate these correlations experimentally, researchers can:

• Use flow cytometry with SLC1A3 antibodies to assess expression on specific immune cell populations

• Perform immunohistochemical analysis on consecutive tissue sections for SLC1A3 and immune cell markers

• Conduct in vitro co-culture experiments to determine the functional impact of SLC1A3 expression on immune cell activity

These approaches provide complementary data to computational analyses and help establish causative relationships between SLC1A3 expression and immune cell behavior.

What techniques can be used to study SLC1A3's role in modulating T cell responses?

Given the correlation between SLC1A3 expression and T cell infiltration patterns, several experimental approaches can elucidate its mechanistic role:

• Co-culture systems:

  • Establish co-cultures of SLC1A3-expressing cells (wild-type or overexpressing) with isolated T cells

  • Measure T cell activation markers (CD69, CD25) and cytokine production (IL-2, IFN-γ)

  • Use SLC1A3 antibodies for blocking experiments to determine functional relevance

• Glutamate metabolism analysis:

  • Assess extracellular glutamate levels in the presence/absence of SLC1A3 inhibition

  • Measure T cell metabolic profiles using Seahorse analysis when exposed to different glutamate conditions

  • Correlate with immunophenotyping using SLC1A3 and T cell marker antibodies

• In vivo models:

  • Generate conditional SLC1A3 knockout models in specific cell types

  • Analyze tumor infiltrating lymphocytes using flow cytometry and immunohistochemistry

  • Perform adoptive transfer experiments with labeled T cells to track migration and activation status

• Multi-parameter imaging:

  • Use multiplex immunofluorescence with SLC1A3 antibodies and T cell markers

  • Perform spatial analysis to determine proximity relationships between SLC1A3+ cells and T cell subsets

  • Quantify co-localization patterns across tissue microenvironments

These approaches can help determine whether SLC1A3's impact on T cells is mediated through glutamate concentration modulation, direct cell-cell interactions, or indirect effects via other soluble factors or metabolites .