KIR2DL3 Antibody

What is KIR2DL3 and what is its biological significance?

KIR2DL3 (Killer cell Immunoglobulin-like Receptor, Two Domains, Long cytoplasmic tail, 3), also known as CD158b, is an inhibitory receptor expressed by a subset of natural killer (NK) cells. It is a 341 amino acid, ~58 kDa single-pass type-1 transmembrane glycoprotein containing two Ig-like C2-type domains . Functionally, KIR2DL3 serves as a receptor specific for HLA Class I molecules, particularly HLA-Cw3 and related HLA-C alleles. This receptor is crucial for immune regulation as it inhibits NK cell cytotoxicity upon recognition of specific MHC class I molecules on target cells .

The biological significance of KIR2DL3 lies in its role in the "missing self" recognition mechanism. When KIR2DL3 engages with its HLA-C ligands, it generates inhibitory signals through its immunoreceptor tyrosine-based inhibitory motif (ITIM), preventing NK cell-mediated killing of healthy cells. Importantly, genetic studies have associated KIR2DL3 with protection against certain cancers and viral infections when paired with specific HLA haplotypes .

How do I select the appropriate KIR2DL3 antibody for my specific research application?

Selection of an appropriate KIR2DL3 antibody requires consideration of multiple factors:

Application compatibility: Different antibodies perform optimally in specific applications. For example:

• For flow cytometry: Clone GL183 and D8L3D antibodies are well-validated

• For Western blotting: Polyclonal antibodies targeting amino acids 22-342 have demonstrated efficacy

• For immunohistochemistry: Select antibodies specifically validated for IHC applications

Epitope recognition: Consider which domain of KIR2DL3 you need to target. Some antibodies recognize the extracellular domain (e.g., those targeting amino acids 22-245), while others may target different regions .

Cross-reactivity concerns: Due to high sequence homology between KIR family members, carefully review specificity data. Many antibodies cross-react with KIR2DL2 and sometimes KIR2DS2 due to their structural similarities .

Clone selection: If studying specific allelic variants, note that certain KIR2DL3 alleles (KIR2DL3005 and KIR2DL3015) do not react with some antibody clones such as ECM41 .

Creating a decision matrix based on your specific experimental needs will facilitate selecting the most appropriate antibody for your research questions.

What are the most validated methods for detecting KIR2DL3 expression?

Flow cytometry represents the gold standard for detecting KIR2DL3 expression, particularly on primary NK cells. The D8L3D rabbit monoclonal antibody has been extensively validated for flow cytometry of live cells at a 1:100 dilution . When using flow cytometry, researchers should:

• Include appropriate isotype controls

• Consider dual staining with NK cell markers (CD56, CD16)

• Implement compensation when using multiple fluorophores

• Consider fixation effects on epitope accessibility

Additional validated detection methods include:

For optimal results, validation using positive controls (NK cell lines with confirmed KIR2DL3 expression) and negative controls (cell lines lacking KIR2DL3) is essential .

How can I distinguish between KIR2DL3 and other highly homologous KIR family members?

Distinguishing between KIR2DL3 and other KIR family members represents a significant challenge due to high sequence homology, particularly with KIR2DL2 and KIR2DS2. Recommended approaches include:

Combined antibody panels: Use antibody combinations that allow for differential staining patterns. For example, antibody panels that include clone GL183 (which recognizes KIR2DL3, KIR2DL2, and KIR2DS2) in combination with other specific antibodies can help distinguish between these receptors through exclusion gating strategies .

Genetic confirmation: Complement antibody-based detection with KIR genotyping of your samples. This approach provides definitive information about which KIR genes are present, allowing for more accurate interpretation of antibody staining patterns .

Novel antibody combinations: Recent research has identified antibody combinations that can identify NK cells with relatively high expression of KIR2DS2, which helps differentiate them from cells expressing KIR2DL3. This approach is valuable for functional studies examining NK cell activation in response to specific ligands .

Functional assays: Utilize inhibition assays with cells expressing specific HLA-C ligands to distinguish between inhibitory KIR2DL3 and activating KIR2DS2 based on functional outcomes rather than just expression .

What are the technical challenges in studying KIR2DL3 allelic variants?

Studying KIR2DL3 allelic variants presents several technical challenges:

Antibody epitope recognition differences: Research has identified KIR2DL3 alleles (KIR2DL3005 and KIR2DL3015) that do not react with the anti-KIR2DL3-specific ECM41 antibody while still being recognized by antibodies that react with KIR2DL2/L3/S2. Additionally, KIR2DL3*005 is unexpectedly stained by anti-KIR2DL1/S1-specific antibodies (EB6B and 11PB6) .

Critical amino acid residues: Site-directed mutagenesis studies have demonstrated that specific amino acids are critical for antibody binding. Glutamine at position 35 is required for ECM41 staining, while glutamic acid 35 and arginine 50 are relevant for staining with EB6B or 11PB6 antibodies .

To address these challenges:

• Implement combined genotypic and phenotypic approaches

• Use multiple antibody clones recognizing different epitopes

• Consider functional assays that examine ligand specificity

• For critical experiments, sequence the KIR2DL3 alleles present in your samples

Despite allelic recognition differences, functional analysis indicates that the specificity of KIR2DL3*005 for HLA-C molecules does not differ from other KIR2DL2/L3 alleles .

How do I optimize flow cytometry protocols for KIR2DL3 detection?

Optimizing flow cytometry for KIR2DL3 detection requires attention to several parameters:

Antibody titration: Determine the optimal concentration for each antibody clone. For example, D8L3D rabbit mAb has been validated at a 1:100 dilution for flow cytometry of live cells .

Buffer composition: Test different staining buffers containing various concentrations of bovine serum albumin (BSA) or fetal bovine serum (FBS) to reduce non-specific binding.

Blocking strategy: Include Fc receptor blocking reagents to minimize non-specific binding, particularly important when working with primary NK cells and other immune cells.

Multicolor panel design: When designing multicolor panels:

• Assign brightest fluorophores to KIR2DL3 antibodies if the expected expression is low

• Avoid fluorophore combinations with significant spectral overlap

• Include appropriate compensation controls

Sample preparation considerations:

• Fresh vs. frozen samples: Fresh samples typically provide better staining results

• Fixation impact: If fixation is necessary, validate that your antibody's epitope recognition is preserved

• Cell concentration: Maintain consistent cell concentrations between samples (typically 1 million cells per 100 μl)

Gating strategy recommendations:

• Gate on lymphocytes based on FSC/SSC

• Exclude doublets and dead cells

• Identify NK cells (CD3-CD56+)

• Analyze KIR2DL3 expression on the NK cell population

How can I design experiments to evaluate KIR2DL3-mediated NK cell licensing?

NK cell licensing (also called education) refers to the process by which inhibitory receptors like KIR2DL3 confer functional competence to NK cells upon interaction with self-MHC molecules. To evaluate KIR2DL3-mediated licensing, consider these experimental approaches:

Degranulation assay design:

• Isolate NK cells from donors with known KIR and HLA genotypes

• Phenotype the NK cells using anti-KIR antibodies to identify KIR2DL3+ subsets

• Challenge NK cells with class I MHC-deficient target cells (e.g., K562)

• Measure degranulation (CD107a expression) in KIR2DL3+ vs. KIR2DL3- NK cell subsets from the same donor

• Compare donors with and without the cognate HLA-C group 1 ligands

Research indicates that KIR2DL3 and KIR2DL1 have similar capacity to license NK cells, suggesting that inhibitory signal strength and the amount of available HLA-C ligands do not directly correlate with licensing efficiency .

Cytokine production assay:
Measure IFN-γ production in response to stimulation with cytokines (IL-12/IL-15/IL-18) or target cells, comparing KIR2DL3+ NK cells from individuals with and without HLA-C group 1 alleles.

Receptor calibration analysis:
Quantify KIR2DL3 expression levels using antibody binding capacity beads to correlate receptor density with functional responses, as receptor expression levels may impact licensing efficiency.

When comparing licensing through different inhibitory receptors (e.g., KIR2DL3 vs. KIR2DL1), use multiparameter flow cytometry to analyze NK cell subsets expressing single receptors to avoid the confounding effects of multiple inhibitory receptors .

What approaches can distinguish between KIR2DL3 and KIR2DS2 in functional studies?

Distinguishing between the inhibitory KIR2DL3 and the activating KIR2DS2 in functional studies is crucial yet challenging due to their high sequence homology. Advanced approaches include:

Novel antibody combinations: Recent research has identified antibody combinations that allow identification of NK cells with relatively high expression of KIR2DS2. This approach permits examination of primary human NK cell activation in response to KIR2DS2-specific ligands .

Single KIR receptor expression systems:

• Transfect cell lines (such as NKL) with individual KIR receptors

• Confirm expression using flow cytometry with multiple antibody clones

• Test functional responses against target cells expressing known ligands

• Compare responses between cells expressing different KIR receptors

Receptor mutagenesis approaches:
Introduce specific mutations at key positions in KIR2DL3 and KIR2DS2 to distinguish their functional effects. Site-directed mutagenesis has shown that amino acid positions 35 and 50 are particularly important for antibody binding and potentially for functional differences .

Biochemical signaling analysis:
Evaluate differential signaling by examining:

• Phosphorylation of inhibitory motifs (ITIMs) in KIR2DL3

• Recruitment of SHP-1/2 phosphatases (characteristic of inhibitory signaling)

• Association with DAP12 (characteristic of activating KIR2DS2 signaling)

These approaches require careful controls and validation but provide more definitive functional separation between these highly similar receptors.

How can I evaluate the impact of KIR2DL3 polymorphisms on antibody binding and function?

Evaluating the impact of KIR2DL3 polymorphisms requires systematic approaches:

Allele-specific antibody reactivity mapping:

• Sequence KIR2DL3 alleles in your study population

• Test binding of different antibody clones to cells expressing known KIR2DL3 alleles

• Create a binding profile matrix correlating alleles with antibody reactivity patterns

Research has shown that certain KIR2DL3 alleles (KIR2DL3005 and KIR2DL3015) do not react with the anti-KIR2DL3-specific ECM41 antibody. Site-directed mutagenesis demonstrated that glutamine at position 35 is critical for ECM41 binding .

Ligand binding assays with allelic variants:

• Express different KIR2DL3 alleles in reporter cell lines

• Test binding to HLA-C tetramers or cell lines expressing different HLA-C allotypes

• Measure functional outcomes (e.g., inhibition of cytotoxicity)

Functional analysis has revealed that despite antibody reactivity differences, the specificity of KIR2DL3*005 for HLA-C molecules does not differ from other KIR2DL2/L3 alleles .

Structure-function correlation:
Using site-directed mutagenesis, create point mutations at polymorphic positions and assess:

• Antibody binding (flow cytometry)

• Ligand binding (tetramer binding assays)

• Functional outcomes (inhibitory capacity in cytotoxicity assays)

Research has demonstrated that glutamic acid at position 35 and arginine at position 50 are relevant for staining with EB6B or 11PB6 antibodies , providing insight into critical residues affecting antibody recognition.