GB3 Antibody refers to monoclonal or polyclonal antibodies specific to globotriaosylceramide (Gb3), a neutral glycosphingolipid expressed on cell membranes. Key characteristics include:
GB3 Antibody binds to distinct epitopes of Gb3, enabling its use in diagnostic and research contexts:
Antigen Recognition:
Molecular Weight (MW):
GB3 Antibody serves as a diagnostic and prognostic tool in specific diseases:
Mechanism: Anti-Gb3 antibodies mark autoimmune myocardial inflammation in FDCM, potentially guiding therapy .
Burkitt Lymphoma: GB3 (CD77) is a tumor-associated antigen, with antibodies aiding in diagnosis via flow cytometry .
Synthesis: Gb3 is synthesized by A4GALT (α4-galactosyltransferase), with polyclonal A4GALT antibodies used to study enzymatic activity .
| Type | Host/Clone | Purification | Applications |
|---|---|---|---|
| Monoclonal | Lewis Rat (IgM, 38.13) | Protein-A affinity chromatography | Flow cytometry, IHC |
| Polyclonal (A4GALT) | Rabbit | Antigen affinity purification | Western blot, ELISA |
ELISA: In-house assays (e.g., FSL-Gb3-coated plates) measure circulating anti-Gb3 levels, with a cut-off of P/N > 2.56 for myocarditis detection .
Immunohistochemistry: Identifies Gb3 in tissue biopsies, aiding in FDCM diagnosis .
| Application | Method | Purpose |
|---|---|---|
| Flow Cytometry | PE/FITC-conjugated anti-GB3 | Detecting Gb3 on cell surfaces |
| Immunohistochemistry | Frozen section staining | Diagnosing FDCM or Burkitt lymphoma |
| ELISA | Anti-Gb3 IgM detection | Monitoring autoimmune FDCM |
| Metric | Value | Patient Group |
|---|---|---|
| Sensitivity | 87.5% | FDCM + myocarditis |
| Specificity | 81.1% | FDCM without myocarditis |
| AUC (ROC Curve) | Not reported |
Here’s a structured collection of FAQs for researchers working with GBF3 antibodies, based on academic research scenarios and synthesized from peer-reviewed sources:
Method: Perform Western blotting using protein extracts from Arabidopsis thaliana (wild-type vs. GBF3 knockout mutants). Include recombinant GBF3 protein as a positive control.
Critical step: Pre-absorb the antibody with excess recombinant GBF3 to confirm signal loss .
Data interpretation: A single band at ~70 kDa (predicted molecular weight) confirms specificity .
Protocol:
Case study: A 2024 analysis of antibody classification errors used confusion matrices and similarity graphs to identify antibody pairs frequently misclassified due to shared epitopes .
Strategy:
Model: Memory B cell language models (mBLMs) trained on antibody sequences can predict specificity by identifying key residues (e.g., CDR3 motifs) .
Findings:
| Fixation Method | Nuclear Signal Retention | Background Noise |
|---|---|---|
| Formalin | High | Moderate |
| Methanol | Reduced | Low |
Solution: Combine laser capture microdissection with qRT-PCR for cell-type-specific analysis .
Data normalization: Use housekeeping genes validated for plant tissues (e.g., ACTIN2 in Arabidopsis) .
Troubleshooting workflow: