KIR2DS5 Antibody

What is KIR2DS5 and why is it significant in immunological research?

KIR2DS5 is an activating killer immunoglobulin-like receptor expressed on natural killer (NK) cells. It belongs to the KIR family of receptors that regulate NK cell cytotoxicity through recognition of altered MHC-I expression on infected or transformed cells. KIR2DS5 is particularly significant because it has been associated with improved clinical outcomes in various diseases, including COVID-19, where KIR2DS5-positive patients demonstrated significantly shorter recovery times compared to KIR2DS5-negative patients (mean 21.6 ± 2.8 days vs. 44.6 ± 2.2 days) . The receptor triggers both NK cell cytotoxicity and interferon γ (IFN-γ) release, potentially explaining its protective effects in viral infections . This makes it a valuable target for immunological research focused on host defense mechanisms and potential therapeutic approaches.

What are the known allelic variations of KIR2DS5?

KIR2DS5 is polymorphic, with several identified alleles that differ in their expression levels and glycosylation patterns. The most frequently observed allele is KIR2DS5002, but researchers have identified multiple variants (KIR2DS5002 through KIR2DS5009) . These allelic products show consistent variation in expression levels when transfected into cell lines, with KIR2DS5003 exhibiting the highest level of expression, while KIR2DS5002 and KIR2DS5009 show the lowest . The intermediate expression levels are seen with KIR2DS5004 through KIR2DS5008 . These differences in expression are consistent across different cell lines and detection methods, indicating intrinsic properties of the polypeptide sequences rather than cell type-specific effects.

How does KIR2DS5 positivity influence clinical outcomes in disease states?

Research has demonstrated that KIR2DS5 positivity correlates with improved clinical outcomes in several conditions. In COVID-19 specifically:

• KIR2DS5-positive patients with severe ARDS showed significantly shorter time to recovery compared to KIR2DS5-negative patients (21.6 ± 2.8 days vs. 44.6 ± 2.2 days)

• By day 28 after admission, 60% of KIR2DS5-positive patients had recovered compared to only 9% of KIR2DS5-negative patients

• In patients with moderate COVID-19, KIR2DS5 positivity was associated with freedom from transfer to ICU (0% vs 22%, p-value = 0.04)

• KIR2DS5-positive patients required less oxygen supplementation than KIR2DS5-negative patients (22% vs. 46%), though this did not reach statistical significance (p-value = 0.08)

Beyond COVID-19, KIR2DS5 has shown protective effects in acute rejection of kidney grafts, malaria, HIV infection, and hepatitis C-induced hepatocellular carcinoma . The enhanced activation of NK cells through KIR2DS5 may explain these observations, as NK cell exhaustion has been associated with poorer outcomes in various infectious diseases.

What antibodies are available for KIR2DS5 detection and how specific are they?

Several antibodies have been developed for KIR2DS5 detection in research applications:

• F6075: A rabbit polyclonal antisera raised against the peptide HEGFRRKPSLLA, corresponding to amino acids 1-12 of KIR2DS5

• 5E11A6: A mouse monoclonal antibody produced by immunizing BALB/c mice with a KIR2DS5*002-Fc fusion protein isolated from a baculovirus system

Both antibodies have been tested for specificity using flow cytometry with a panel of NKL cell lines expressing single KIR allotypes (KIR2DS1, 2DS2, 2DS4, 2DS5, 2DL1, 2DL2, 2DL3, 2DL5A, and 3DL1) . This comprehensive validation ensures minimal cross-reactivity with other KIR family members, making these antibodies suitable for selective detection of KIR2DS5 in research applications.

How can researchers validate KIR2DS5 antibody specificity in their experimental systems?

To validate KIR2DS5 antibody specificity in experimental systems, researchers should:

• Use cell line panels: Test antibodies against a panel of cell lines expressing different KIR family members, similar to the validation approach used for F6075 and 5E11A6

• Include appropriate controls:

  • Positive control: Cells transfected with KIR2DS5 (preferably tagged constructs like V5 or HA tags for verification)

  • Negative control: Cells transfected with empty vector or other KIR family members

• Perform cross-validation with multiple detection methods:

  • Flow cytometry for surface expression

  • Western blotting for protein size and expression levels

  • Immunoprecipitation followed by mass spectrometry for definitive identification

• Use isotype-matched controls for monoclonal antibodies to rule out non-specific binding (e.g., mouse IgG1 kappa for 5E11A6)

This systematic validation approach ensures that observed signals are specific to KIR2DS5 and not due to cross-reactivity with structurally similar KIR family members.

What are the optimal methods for detecting KIR2DS5 expression in primary human NK cells?

For detecting KIR2DS5 expression in primary human NK cells, researchers should consider a multi-method approach:

• Flow Cytometry:

  • Use KIR2DS5-specific antibodies (F6075 or 5E11A6)

  • Include appropriate isotype controls

  • Co-stain with NK cell markers (CD56, CD16) and other KIR receptors to characterize receptor co-expression patterns

  • Analyze both percentage of positive cells and mean fluorescence intensity (MFI)

• RT-PCR for detecting KIR2DS5 mRNA:

  • Design primers specific to KIR2DS5, avoiding regions with high homology to other KIR family members

  • Consider including sequence verification of amplicons due to high sequence similarity between KIR genes

• Single-cell RNA sequencing:

  • Provides comprehensive expression profiles and can identify KIR2DS5+ subpopulations

  • Enables correlation of KIR2DS5 expression with other NK cell receptors and functional states

For all methods, comparison with KIR genotyped reference samples is recommended to establish reliable detection thresholds and account for allelic variation in expression levels.

How can researchers distinguish between different KIR2DS5 alleles in experimental settings?

Distinguishing between KIR2DS5 alleles requires specialized approaches due to their high sequence similarity:

• DNA-based methods:

  • Sequence-specific primer PCR (SSP-PCR) with primers designed to target polymorphic regions

  • Next-generation sequencing of the KIR locus for comprehensive allele determination

  • Restriction fragment length polymorphism (RFLP) analysis based on differential cutting sites

• Protein-based methods:

  • Western blotting can reveal differences in glycosylation patterns and molecular weights between allelic products

  • Flow cytometry with allele-specific antibodies, though these may not be available for all alleles

  • Mass spectrometry for precise identification of sequence variations

• Expression pattern analysis:

  • Different alleles show characteristic expression levels when transfected into cell lines

  • KIR2DS5003 exhibits higher expression than KIR2DS5002 and KIR2DS5*009

  • These differences can be quantified by comparing the ratio of extracellular to intracellular expression

For the most accurate results, researchers should combine DNA-based genotyping with protein expression analysis to confirm the presence and functionality of specific alleles.

What experimental protocols are recommended for studying the functional consequences of KIR2DS5 activation?

To study the functional consequences of KIR2DS5 activation, consider these methodological approaches:

• NK cell cytotoxicity assays:

  • Use antibody-dependent cross-linking of KIR2DS5 with F6075 or 5E11A6 antibodies

  • Measure target cell killing using chromium release or flow cytometry-based assays

  • Compare KIR2DS5+ and KIR2DS5- NK cell populations from the same donor

• Cytokine production assessment:

  • Measure IFN-γ secretion following KIR2DS5 engagement using ELISA or cytometric bead array

  • Analyze production of other cytokines (TNF-α, GM-CSF) to characterize the response profile

  • Use intracellular cytokine staining to identify producing cells in heterogeneous populations

• Signaling pathway analysis:

  • Western blotting for phosphorylation of downstream signaling molecules

  • Live cell imaging with fluorescent reporters to visualize calcium flux or other rapid signaling events

  • RNA-seq to characterize transcriptional responses to KIR2DS5 activation

• Stable cell line models:

  • Generate NK cell lines (e.g., KHYG1) stably expressing KIR2DS5 through transduction and cell sorting

  • Create reporter cell lines where KIR2DS5 activation triggers measurable outputs (luciferase, GFP)

  • Compare functional responses between different KIR2DS5 alleles to identify functional variations

These approaches can systematically characterize the signaling and functional consequences of KIR2DS5 engagement in various experimental contexts.

How can researchers overcome challenges in detecting low-expression KIR2DS5 alleles?

Detection of low-expression KIR2DS5 alleles like KIR2DS5002 and KIR2DS5009 presents technical challenges that can be addressed through several strategies:

• Signal amplification techniques:

  • Use biotin-streptavidin systems to amplify antibody signals

  • Employ tyramide signal amplification for immunohistochemistry and flow cytometry

  • Consider fluorescent nanoparticle-conjugated antibodies for enhanced sensitivity

• Optimized staining protocols:

  • Increase antibody concentration (titrate to determine optimal concentration)

  • Extend incubation times to allow for complete binding

  • Reduce background with careful blocking and washing steps

• Enrichment approaches:

  • Magnetic or flow-based cell sorting to enrich for KIR2DS5+ populations

  • Use RNA-binding protein immunoprecipitation to concentrate KIR2DS5 mRNA for detection

  • Culture cells with cytokines (IL-2, IL-15) that may upregulate KIR expression

• Alternative detection methods:

  • Digital PCR for sensitive detection of KIR2DS5 transcripts

  • Proximity ligation assay for protein detection with single-molecule sensitivity

  • Mass cytometry (CyTOF) for high-dimensional analysis with enhanced signal-to-noise ratio

Combining these approaches can significantly improve detection of low-abundance KIR2DS5 allelic products in various experimental systems.

What are the critical factors affecting glycosylation patterns of KIR2DS5 and how can they be analyzed?

KIR2DS5 shows variable glycosylation patterns that affect protein detection and potentially function. Critical factors and analysis methods include:

• Key determinants of glycosylation:

  • Polymorphic residues at positions 123 and 157 significantly alter glycosylation patterns and surface expression levels

  • N-linked glycosylation motifs can be predicted using tools like NetNGlyc 1.0

  • Cell type-specific glycosylation machinery may influence the final pattern

• Analysis methods:

  • Western blotting reveals characteristic double bands representing differently glycosylated isoforms

  • PNGase F digestion to remove N-linked glycans and compare deglycosylated protein sizes

  • Lectin binding assays to characterize specific glycan structures

• Methodological considerations:

  • Use gradient gels (4-15% polyacrylamide) for optimal resolution of glycoforms

  • Include both reducing and non-reducing conditions to assess the impact of disulfide bonding

  • Compare glycosylation patterns between primary cells and cell lines for consistency

• Functional implications:

  • Monitor the ratio between mature (fully glycosylated) and immature forms across different alleles

  • Correlate glycosylation patterns with surface expression levels and functional activity

  • Use site-directed mutagenesis to modify potential glycosylation sites and assess functional consequences

Understanding these glycosylation patterns is crucial for accurate detection and functional characterization of KIR2DS5 variants.

How can computational approaches be used to predict KIR2DS5 binding partners and functional properties?

Computational approaches offer powerful tools for predicting KIR2DS5 interactions and functions:

• Homology modeling:

  • KIR2DS5 structure can be modeled based on related KIRs with known crystal structures (e.g., KIR2DS2)

  • Molecular dynamics simulations and energy minimization can refine these models

  • Quality assessment tools like Procheck verify model reliability

• Molecular docking:

  • Predict potential binding partners by docking KIR2DS5 models with MHC-I molecules and other candidates

  • Calculate binding energies to rank likely interaction partners

  • Simulate the effects of allelic variations on binding properties

• Sequence-based predictions:

  • Machine learning algorithms trained on known KIR-ligand pairs

  • Conservation analysis across species to identify functionally important residues

  • Coevolution analysis to detect correlated mutations suggesting interaction interfaces

• Systems biology approaches:

  • Network analysis integrating expression data, protein interactions, and clinical correlations

  • Prediction of signaling pathways activated by different KIR2DS5 alleles

  • Population-level modeling of KIR2DS5 distribution and disease associations

These computational approaches can generate testable hypotheses about KIR2DS5 function and guide experimental designs for binding partner identification.

What are the implications of KIR2DS5 polymorphisms for personalized medicine approaches in infectious and autoimmune diseases?

KIR2DS5 polymorphisms have significant implications for personalized medicine:

• Disease risk stratification:

  • KIR2DS5 positivity predicts improved outcomes in COVID-19 patients

  • KIR2DS5-positive patients with severe COVID-19 show 60% recovery by day 28 vs. only 9% in KIR2DS5-negative patients

  • Similar protective associations have been observed in kidney transplantation, malaria, HIV, and hepatitis C

• Treatment response prediction:

  • KIR2DS5 status could potentially predict response to immunotherapies that depend on NK cell function

  • Patient stratification based on KIR genotype might optimize treatment selection

  • Monitoring KIR2DS5+ NK cell populations during treatment could serve as a biomarker for response

• Therapeutic targeting opportunities:

  • Development of agonistic antibodies to stimulate KIR2DS5 signaling in KIR2DS5-positive individuals

  • Allele-specific approaches might be needed due to expression level differences

  • Combined therapies targeting multiple NK receptors based on individual KIR profiles

• Clinical implementation considerations:

  • KIR genotyping assays would need standardization for clinical use

  • Interpretation guidelines accounting for ethnic variations in KIR distribution

  • Integration with other genetic and clinical markers for improved predictive power

This emerging field connects basic KIR2DS5 biology with potential clinical applications, offering new pathways for personalized immunotherapy approaches.

How does KIR2DS5 interact with other NK cell receptors to modulate immune responses?

KIR2DS5 functions within a complex network of activating and inhibitory receptors on NK cells:

• Receptor co-expression patterns:

  • KIR2DS5 expression varies among NK cell subsets and may correlate with specific functional states

  • Co-expression with inhibitory KIRs may create balanced regulation of NK cell activation

  • NK cell education may be influenced by the specific combination of KIRs expressed

• Signal integration mechanisms:

  • KIR2DS5 triggers NK cell cytotoxicity and IFN-γ release through activating pathways

  • The balance between activating signals (from KIR2DS5) and inhibitory signals determines the activation threshold

  • Synergistic or antagonistic interactions with other receptors (NKG2D, NCRs) shape the final response

• Methodological approaches to study receptor interactions:

  • Multi-parameter flow cytometry to correlate receptor expression with functional readouts

  • CRISPR-based genetic modification to create NK cells with defined receptor combinations

  • Single-cell analysis to identify receptor expression patterns associated with enhanced function

• Temporal dynamics:

  • Sequential engagement of different receptors may influence the activation pathway

  • Receptor clustering and synapse formation patterns include KIR2DS5 in conjunction with other molecules

  • Receptor expression changes during NK cell activation may alter the contribution of KIR2DS5 over time

Understanding these complex interactions is essential for accurately predicting how KIR2DS5 variants influence immune responses in different contexts.

How should researchers normalize and quantify KIR2DS5 expression data across different experimental platforms?

Standardizing KIR2DS5 expression data across different platforms requires careful normalization approaches:

• Flow cytometry data normalization:

  • Calculate the ratio of extracellular to intracellular expression to control for total protein production

  • Use standardized mean fluorescence intensity (MFI) compared to isotype controls

  • Include standardized reference samples across experiments for inter-experimental calibration

• Western blot quantification:

  • Normalize band intensity to loading controls (β-actin, GAPDH)

  • Calculate the ratio between mature and immature glycoforms for each sample

  • Use internal reference standards for cross-gel comparisons

• RT-PCR and transcriptomic data:

  • Select appropriate reference genes with stable expression across conditions

  • Use absolute quantification with standard curves when possible

  • Apply batch correction methods for large-scale datasets

• Cross-platform integration:

  • Develop conversion factors between different measurement methods

  • Use rank-based metrics rather than absolute values when combining diverse data types

  • Apply statistical methods that account for platform-specific technical variability

This standardized approach enables reliable comparison of KIR2DS5 expression data from different studies and experimental systems.

What statistical approaches are most appropriate for analyzing the relationship between KIR2DS5 genotype and clinical outcomes?

When analyzing KIR2DS5 genotype-outcome relationships, these statistical approaches are recommended:

• Primary analysis methods:

  • Kaplan-Meier survival analysis for time-to-event outcomes (e.g., time to recovery)

  • Log-rank test to compare outcomes between KIR2DS5-positive and negative groups

  • Chi-square or Fisher's exact test for categorical outcomes (e.g., ICU transfer rates)

• Multivariate approaches:

  • Cox proportional hazards models to adjust for confounding factors

  • Logistic regression for binary outcomes with adjustment for demographics and comorbidities

  • Propensity score matching to balance KIR2DS5+ and KIR2DS5- groups

• Sample size considerations:

  • Power calculations based on expected effect sizes (e.g., 60% vs. 9% recovery by day 28)

  • Adjustment for multiple testing when examining multiple KIR genes or outcomes

  • Consideration of allele frequencies in the study population

• Validation strategies:

  • Split discovery/validation cohorts as demonstrated in COVID-19 studies

  • External validation in independent patient populations

  • Cross-validation techniques for smaller datasets

These statistical approaches help establish robust associations between KIR2DS5 genotype and clinical outcomes while accounting for potential confounding factors.