Host: Rabbit (polyclonal)
Conjugation: HRP enzyme for signal amplification
Target Epitope: Variable by product (e.g., C-terminal peptides, recombinant proteins)
Reactivity: Human, Mouse, Rat (commonly validated)
Applications: WB, ELISA, IHC-P, Immunofluorescence
Colon Cancer: SLC5A1 is overexpressed in colon cancer tissues and promotes proliferation, migration, and invasion. HRP-conjugated antibodies were used to validate SLC5A1 downregulation by Hesperidin, a flavonoid inhibiting EGFR phosphorylation .
Pancreatic Cancer: SLC5A1 knockdown via shRNA reduced glucose uptake and suppressed tumor growth in vitro and in vivo. HRP-based detection confirmed SLC5A1-EGFR interaction, critical for AMPK/mTOR signaling .
Western Blot: Antibodies like PA2244 (Boster Bio) show distinct bands at 73 kDa in human HepG2 and mouse kidney lysates .
Immunohistochemistry: Novus Biologicals’ NBP2-20338 demonstrated membranous localization in lung fibrosis tissues .
Specificity: Cross-reactivity tests show no off-target binding in Human, Mouse, and Rat .
Sensitivity: Detection limits as low as 0.1 μg/ml in WB (e.g., Bioss bs-1128R-HRP) .
Lot Consistency: Purification via Protein A/G ensures >95% purity .
Species Restrictions: Untested in feline tissues; cross-reactivity predictions vary .
Storage: Requires -20°C storage with avoidance of freeze-thaw cycles .
Background Noise: Optimal blocking (e.g., 5% non-fat milk) minimizes non-specific signals .
HRP-conjugated SLC5A1 antibodies are optimized for several applications with specific dilution recommendations:
Western Blot: 1:300-5000 dilution
ELISA: 1:500-1000 dilution
These ranges provide starting points for optimization. The specific antibody concentration varies by lot and manufacturer, so validation in your specific experimental system is recommended.
Most commercially available SLC5A1 antibodies with HRP conjugation have been validated for:
Cross-reactivity with other species may exist based on sequence homology but requires experimental validation .
For maximum stability and preservation of activity:
Store at -20°C for long-term storage
Aliquot to avoid repeated freeze-thaw cycles
For short-term storage (≤1 month after reconstitution), 2-8°C is acceptable
Avoid exposure to light to preserve HRP activity
Some formulations contain glycerol (40-50%) and preservatives like Proclin-300 (0.03%) or sodium azide (0.02-0.05%)
Proper storage is critical as HRP activity can diminish with improper handling.
For IHC-P applications, optimal antigen retrieval significantly affects staining quality:
Heat-Induced Epitope Retrieval (HIER) at pH 6.0 using citrate buffer is generally recommended
Some antibodies perform better with Tris-EDTA buffer (pH 8.0)
For human lung fibrosis tissue, Trilogy™ (EDTA-based, pH 8.0) buffer with 15 minutes retrieval has shown good results
Temperature and duration optimization is critical: typically 95-100°C for 10-20 minutes
A comparison of different retrieval methods should be conducted during validation to determine optimal conditions for your specific tissue type.
A comprehensive validation requires several controls:
Positive tissue controls: Human duodenum shows high SLC5A1 expression and serves as an excellent positive control
Negative tissue controls: Human cerebral cortex generally shows minimal SLC5A1 expression
Absorption controls: Pre-incubation of antibody with immunizing peptide
Secondary antibody controls: Omission of primary antibody
Cross-validation: Compare results with another validated SLC5A1 antibody
Knockout/knockdown validation: Using CRISPR or siRNA SLC5A1-depleted samples as described in pancreatic cancer studies
Correlating protein detection with RNA-seq data for SLC5A1 expression in the same tissues provides additional validation evidence .
Research has demonstrated SLC5A1's oncogenic role in pancreatic cancer, which can be investigated using SLC5A1 antibodies:
Expression analysis: Compare SLC5A1 levels between pancreatic cancer tissue and adjacent non-cancerous tissue using IHC-P or Western blotting
Functional studies: Assess glucose uptake in SLC5A1-knockdown pancreatic cancer cells using fluorescent glucose analogs (2-NBDG)
Signaling pathway analysis: Investigate AMPK/mTOR pathway activation following SLC5A1 inhibition
Protein-protein interactions: Examine SLC5A1 association with EGFR using co-immunoprecipitation followed by Western blot
Research findings show SLC5A1 knockdown reduces cellular glucose uptake, activates AMPK, and suppresses mTOR signaling, leading to reduced pancreatic cancer cell growth .
When investigating SLC5A1-EGFR interactions, consider these methodological adaptations:
Lysis buffer optimization: Use buffers containing 1% Triton X-100 or NP-40 that preserve membrane protein interactions
Cross-linking (optional): Mild formaldehyde cross-linking (0.5-1%) may help stabilize transient interactions
Antibody selection: Use non-conjugated SLC5A1 antibodies for immunoprecipitation
Detection strategy:
Immunoprecipitate with anti-SLC5A1 and detect EGFR by Western blot
Reverse approach: immunoprecipitate with anti-EGFR and detect SLC5A1
Controls: Include IgG control immunoprecipitation and input sample controls
Validation: Confirm interactions by reciprocal co-immunoprecipitation or proximity ligation assay
Research has established a correlation between SLC5A1 and EGFR expression in pancreatic cancer patients (P=0.0035), with direct protein interaction confirmed by co-immunoprecipitation .
Non-specific background can compromise data interpretation. Common causes and solutions include:
The observed molecular weight of SLC5A1 should be approximately 73 kDa, though post-translational modifications may alter the apparent molecular weight .
When encountering unexpected expression patterns:
Compare with literature data: SLC5A1 is highly expressed in intestinal epithelium (duodenum) but lower in cerebral cortex
Verify antibody specificity: Use multiple antibodies targeting different epitopes (e.g., NBP2-38748 and NBP2-33629 for orthogonal validation)
Consider post-translational modifications: These can affect antibody recognition
Evaluate RNA expression: Compare protein expression with RNA-seq data for the same tissues
Assess experimental conditions: Sub-optimal conditions may lead to false negative results
Consider biological variables: Expression can vary with disease state, physiological conditions, or genetic background
SLC5A1 mutations cause congenital glucose-galactose malabsorption, a rare autosomal recessive disorder. Antibody-based approaches can help investigate these variants:
Expression analysis: Compare expression levels of wild-type vs. mutant SLC5A1 in patient samples
Localization studies: Examine subcellular localization changes in mutant proteins using IHC or ICC
Functional validation: After site-directed mutagenesis introduction of specific variants, detect protein expression levels by Western blot
Trafficking studies: Determine if mutations affect membrane localization using cell-surface biotinylation followed by antibody detection
Structure-function correlations: Map epitope recognition to help understand structural impacts of mutations
Research on Turkish patients has identified several SLC5A1 mutations through molecular studies that can be further characterized using antibody-based methods .
When investigating SLC5A1's role in cancer metabolism:
Physiological glucose conditions: Compare antibody-detected SLC5A1 expression under varying glucose concentrations (0.5mM, 5mM, 25mM, 50mM)
Metabolic stress conditions: Assess SLC5A1 expression under hypoxia, nutrient deprivation, or pharmacological AMPK activation
Multi-parameter analysis: Combine SLC5A1 detection with markers of cellular metabolism (HIF-1α, GLUT1) or signaling pathways (p-AMPK, p-mTOR)
In vivo tumor models: Use SLC5A1 antibodies for IHC analysis of xenograft tumors before and after glucose transport inhibition
Patient sample stratification: Correlate SLC5A1 expression with clinical outcomes and metabolic parameters
Research has demonstrated that SLC5A1 knockdown reduces glucose uptake in pancreatic cancer cells, triggers AMPK activation, and suppresses mTOR signaling, ultimately inhibiting cancer cell growth .
To ensure data consistency across different antibody lots:
Lot-to-lot validation: Compare new lots against previous lots using:
Western blot of reference samples
Comparative IHC/ICC on standard positive controls
Titration curves to ensure similar sensitivity
Reference standard inclusion: Include a consistent positive control sample in each experiment
Quantitative calibration: Use standard curves with known quantities of recombinant SLC5A1
Documentation: Maintain detailed records of lot numbers, dilutions, and experimental conditions
Signal normalization: Normalize signal intensity to housekeeping proteins or total protein staining
Manufacturers typically perform lot-to-lot testing, but researcher validation is essential for critical applications.
For comprehensive antibody reporting in publications:
Complete antibody information:
Validation evidence:
Positive and negative controls used
Knockout/knockdown validation
Cross-reactivity testing
Experimental conditions:
Exact dilutions used
Incubation times and temperatures
Blocking reagents
Antigen retrieval methods
Detection systems:
Enhanced chemiluminescence (ECL) details
Image acquisition parameters
Quantification methods:
Software used
Normalization approach
Following these documentation standards improves reproducibility and facilitates accurate interpretation by the research community.