The Granulysin (GNLY) antibody is a specific immunoglobulin designed to detect and study the Granulysin protein, a member of the saposin-like protein (SAPLIP) family. GNLY is expressed by cytotoxic T lymphocytes (CTLs) and natural killer (NK) cells, functioning as an antimicrobial agent, tumor cell lytic factor, and alarmin that activates immune responses . The antibody enables researchers to analyze GNLY expression, localization, and functional roles in immune processes, infection, and cancer .
GNLY antibodies are utilized across multiple experimental techniques:
Multiple antibody formats are available, each optimized for specific experimental needs:
Immune Activation: GNLY activates antigen-presenting cells (APCs) via TLR4, promoting adaptive immune responses . Antibodies confirmed this by blocking GNLY-mediated DC activation .
Tumor Rejection: Transgenic mice expressing human GNLY exhibited enhanced tumor rejection, validated using GNLY-specific antibodies .
Infection and Autoimmunity: Elevated GNLY levels correlate with immune defense against Mycobacterium tuberculosis and tissue damage in Stevens-Johnson syndrome .
Applications : immunohistochemistry (IHC)
Sample type: tissues
Review: immunohistochemistry (IHC) was performed, sugesting that the expression of four key genes (CERCAM, EMP1, GNLY, PTPRR) in two patients from Gulou-Cohort2 (Scale bars=100 μm).
Antibody selection requires validation across three domains: specificity, sensitivity, and reproducibility. For GNLY (Granulysin), a cytotoxic granule protein expressed in NK cells and T lymphocytes:
Specificity: Use Western blot (WB) with lysates from GNLY-knockout (KO) cell lines (e.g., CRISPR-edited Jurkat cells) to confirm absence of cross-reactive bands .
Sensitivity: Optimize antigen retrieval conditions (e.g., citrate buffer pH 6.0 vs. EDTA pH 9.0) for formalin-fixed paraffin-embedded (FFPE) tissues .
Reproducibility: Compare staining patterns across independent cohorts using antibodies from distinct clonal lineages (e.g., polyclonal ab204594 vs. monoclonal ab223326) .
Non-specific binding often arises from epitope similarity to paralogs (e.g., granulysin vs. granulysin-like proteins). Mitigation strategies:
Pre-absorption assay: Incubate antibody with recombinant GNLY (1:5 molar ratio, 1 hr at 4°C) to block specific binding .
Cross-reactivity screening: Test antibody against HEK293T cells transiently expressing granulysin-like proteins (e.g., GNLYL1, GNLYL2) .
Multiplex validation: Combine with RNAscope® for GNLY mRNA co-localization in tissue sections .
GNLY mediates antimicrobial activity via membrane disruption. Key assays:
Intracellular Listeria killing: Co-culture dNK cells with Listeria-infected JEG-3 trophoblasts; quantify bacterial CFUs after 24 hrs (blocking controls: anti-GNLY IgG vs. isotype) .
TLR4 dependency: Use TLR4-KO dendritic cells to validate GNLY-induced APC activation (e.g., IL-12p70 ELISA) .
Discrepancies arise from model systems and antibody validation gaps:
Perform single-cell RNA-seq on tumor-infiltrating lymphocytes to distinguish GNLY expression in cytotoxic vs. exhausted T cells.
Use Fab-based antibodies (e.g., recombinant GNLY-Fab) to avoid Fc-mediated false positives in flow cytometry .
GNLY shares structural motifs with lupus-associated autoantigens (e.g., Ro52). Advanced approaches:
Epitope mapping: Phage display libraries to identify antibody-binding linear vs. conformational epitopes .
Competitive ELISA: Pre-incubate serum with GNLY-derived peptides (15-mer overlapping) to block pathogenic autoantibodies .
Cryo-EM structural validation: Resolve antibody-GNLY complexes at <4Å resolution to confirm binding specificity .
Decidual NK (dNK) cells transfer GNLY via nanotubes to kill intracellular Listeria without host cell apoptosis . Protocol:
Dual-chamber Transwells: Separate dNK (upper) and Listeria-infected JEG-3 trophoblasts (lower; MOI 10:1).
GNLY inhibition: Add 10 µg/mL anti-GNLY blocking antibody (e.g., ab223326) to upper chamber.
Quantification: At 24 hrs, lyse trophoblasts and plate serial dilutions on BHI agar.
Brefeldin A (Golgi disruptor) to block secretory GNLY.
Recent advances integrate AI-driven models:
RFdiffusion fine-tuning: Generates de novo antibody paratopes targeting GNLY epitopes (RMSD <2.0Å vs. crystal structures) .
Molecular dynamics (MD) simulations: Simulate GNLY-antibody binding under endosomal pH (5.5) to predict off-target dissociation .
| Parameter | RFdiffusion Output | Traditional Hybridoma |
|---|---|---|
| Affinity (KD) | 1.2 nM ± 0.3 | 8.5 nM ± 2.1 |
| Developability index | 82% (optimal) | 64% (high aggregation risk) |
| Epitope coverage | Discontinuous (aa 45-89) | Linear (aa 12-27) |
Activation alters GNLY’s conformational states, impacting antibody accessibility:
Fixation conditions: Compare 4% PFA (surface GNLY) vs. methanol permeabilization (intracellular pools) .
Activation markers: Co-stain with CD69 (early activation) and PD-1 (exhaustion) in chronic infection models .
Signal-to-noise optimization: Titrate antibodies using GNLY-overexpressing vs. KO Jurkat cells (Figure 1).
GNLY forms oligomers in cytotoxic granules; avoid over-fixation to prevent epitope masking .
Use tandem dye conjugates (e.g., PE-Cy7) to minimize spectral overlap with granzyme B .
Multiplexed validation: Combine orthogonal techniques (e.g., IHC, scRNA-seq, functional assays) for antibody verification .
Open data sharing: Deposit characterization data in repositories like Antibody Registry (RRID:AB_204594).
Ethical reporting: Disclose antibody lot numbers and validation workflows in publications to enhance reproducibility .