GATL3 Antibody
Description
GATL3 Antibody Overview
The GATL3 antibody (e.g., Sigma-Aldrich SAB1301599) is a rabbit-derived polyclonal IgG antibody raised against the N-terminal region of human GATSL3. It is validated for use in Western blot (1:250–1:500 dilution) and immunohistochemistry (1:50–1:100 dilution) . Key features include:
Biological Role of GATL3
GATL3 belongs to the galacturonosyltransferase-like family, which is implicated in pectin biosynthesis in plants. In Arabidopsis thaliana, GATL3 (gene AT3G15750) shows a fold change of 0.489 in expression under experimental conditions, suggesting regulatory roles in cell-wall modification . While its mammalian function is less characterized, homology suggests potential involvement in glycosylation pathways.
Applications in Research
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Plant Studies: GATL3 antibodies may aid in analyzing pectin-related pathways in plant models (e.g., Arabidopsis) .
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Mammalian Systems: Preliminary data link GATSL3 to glycan synthesis, though functional studies are scarce .
Gene Expression Profile (Arabidopsis)
Technical Considerations
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Validation: Limited peer-reviewed studies directly using GATL3 antibodies exist. Most data derive from vendor-provided technical validations .
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Cross-Reactivity: No cross-reactivity with GATA-3 (a transcription factor in cancer biology) has been reported, despite nomenclature similarities .
Future Directions
Further studies are needed to:
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Elucidate GATL3’s role in mammalian glycosylation.
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Explore its utility in plant biotechnology for modifying cell-wall properties.
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Validate antibody performance in high-throughput omics workflows.
Product Specs
Constituents: 50% Glycerol, 0.01M Phosphate Buffered Saline (PBS), pH 7.4
Target Background
Q&A
FAQs for GATA3 Antibody Research (Academic Focus)
What is the role of GATA3 in epithelial cell differentiation, and how can its antibody be used to study this process?
GATA3 regulates luminal epithelial differentiation in organs like the mammary gland and urinary bladder. Researchers use GATA3 antibodies in immunohistochemistry (IHC) to map protein localization in tissue sections. For example:
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Methodology: Optimize IHC protocols using FFPE tissues with antigen retrieval (e.g., heat-induced retrieval with Citrate buffer pH 6.0) and validate nuclear staining patterns in breast carcinoma controls .
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Key finding: Strong nuclear GATA3 expression correlates with luminal subtypes in breast cancer (ER+/AR+ tumors) .
How reliable is GATA3 as a diagnostic marker for urothelial carcinoma compared to other tumor types?
GATA3 is highly sensitive for urothelial carcinoma but varies by tumor grade and subtype. A tissue microarray study of 13,093 tumors revealed:
| Tumor Type | GATA3 Positivity Rate | Strong Staining (%) |
|---|---|---|
| Breast Carcinoma | 19.6% | 15% |
| Urothelial Carcinoma | 53% | 18% |
| Basal Cell Carcinoma | 97.1% | 38.2% |
Interpretation: Use GATA3 in panels with FOXA1 or HER2 to distinguish urothelial from prostate adenocarcinoma .
What experimental controls are critical when validating GATA3 antibody specificity?
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Positive controls: Breast cancer tissues (expected nuclear staining) .
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Negative controls: Melanoma or squamous cell carcinoma of the skin (typically GATA3-negative) .
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Technical validation: Compare Western blot results (55 kDa band for full-length GATA3) with IHC to confirm antibody specificity .
How do contradictory findings about GATA3 expression in extramammary Paget disease (EMPD) impact diagnostic workflows?
A study of 72 EMPD cases showed:
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GATA3 sensitivity: 100% in intraepithelial disease vs. 65% for GCDFP15 .
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Pitfall: Weak GATA3 staining in normal epidermal cells (spinous layer) may mimic tumor cells.
Resolution: Combine GATA3 with GCDFP15 and assess nuclear size/architecture to avoid false positives .
What molecular mechanisms explain GATA3’s dual role as a tumor suppressor and oncogene in different cancers?
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Pro-tumorigenic: In breast cancer, GATA3 promotes luminal differentiation and correlates with taxane resistance .
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Anti-tumorigenic: Loss of GATA3 in T-cell lymphomas disrupts immune regulation, enabling tumor progression .
Experimental design: Use siRNA knockdown in cell lines (e.g., MCF-7) followed by RNA-seq to identify downstream targets like FOXA1 .
How can researchers optimize GATA3 antibody multiplex assays for single-cell RNA sequencing (scRNA-seq) validation?
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Tissue dissociation: Preserve epitopes with gentle enzymatic digestion (e.g., collagenase IV).
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Antibody validation: Pre-test clones (e.g., EP368) on FFPE sections to confirm nuclear localization .
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Data integration: Cross-reference scRNA-seq clusters (e.g., GATA3+ luminal cells) with IHC results from matched samples .
What statistical approaches resolve discrepancies in GATA3 expression data across public datasets?
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Meta-analysis: Harmonize data from TCGA (breast cancer) and GEO (EMPD) using R/Bioconductor.
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Adjustments: Normalize for batch effects and tumor purity. For example, GATA3’s association with neutrophilia in systemic sclerosis highlights context-dependent expression .
