Name: qkat: quantitative semi-automated typing of killer-cell immunoglobulin-like receptor genes
Uploaded: 2019-03-06T13:00:00.000+00:00
Duration: 7 min 58 s
Description: Watch this Scientific Journal Video about qKAT: Quantitative Semi-automated Typing of Killer-cell Immunoglobulin-like Receptor Genes at JoVE.com

The project received funding from the Medical Research Council (MRC), the European Research Council (ERC) under the European Union&#39;s Horizon 2020 research and innovation programme (grant agreement No. 695551) and the National Institute of Health (NIH) Cambridge Biomedical Research Centre and NIH Research Blood and Transplant Research Unit (NIHR BTRU) in Organ Donation and Transplantation at the University of Cambridge and in partnership with NHS Blood and Transplant (NHSBT). The views expressed are those of the authors and not necessarily those of the NHS, the NIHR, the Department of Health, or the NHSBT.

1. Preparation and Plating out of DNA
<ol>
	<li>Accurately quantify the gDNA concentration using a spectrophotometric or fluorometric instrument.</li>
	<li>Dilute DNA to 4 ng/&#181;L on a 96-well deep-well plate. Include at least one control gDNA sample with a known copy number and one non-template control.</li>
	<li>Centrifuge the 96-well plates at 450 x g for 2 min.</li>
	<li>Using a liquid handling instrument, dispense each sample in quadruplicate onto 384-well qPCR plates so that every well has 10 ng of DNA (2.5 &#181;L/well). Prepare at least ten 384-well plates, one for each qKAT reaction.</li>
	<li>If gDNA is being dispensed from more than one 96-well plate, perform a full-volume wash with 2% bleach and ultrapure water to clean the needles of the liquid handling system between each 96-well plate of gDNA samples.</li>
	<li>Air-dry the DNA by incubating the 384-well plates in a clean area at room temperature for at least 24 h.</li>
</ol>
2. Preparation of the Primers and Probes
NOTE: qKAT consists of ten multiplex reactions. Each reaction includes three primer pairs and three fluorescence-labeled probes that specifically amplify two KIR genes and one reference gene. The probes that were published in Jiang et al.27 were modified so that the oligonucleotides are now labeled with ATTO dyes since they offer improved photostability and long signal lifetimes. Pre-aliquoted primer combinations are commercially available (see Table of Materials).
<ol>
	<li>Prepare primer combinations for each reaction as per the dilutions given in Table 1.</li>
	<li>Prepare probe combinations for each reaction as per Table 1. Test each individual probe prior to making the combination.</li>
</ol>
3. Preparation of the Master Mix
NOTE&#160;The volumes mentioned below are for performing one qKAT reaction on a set of 10x 384-well plates.
<ol>
	<li>Ensure that the gDNA samples plated on the 384-well plates are completely dry. Conduct all steps on ice and keep the reagents covered from exposure to light as much as possible since the fluorescence-labeled probes are photo- and thermo-sensitive.</li>
	<li>Defrost the qPCR buffer, primer, and probe aliquots at 4 &#176;C.</li>
	<li>On ice, prepare a master mix for 10x 384-well plates by adding 18.86 mL of ultrapure water, 20 mL of qPCR buffer, 1,000 &#181;L of preprepared primer combination, and 180 &#181;L of preprepared probe combination (Table 2).</li>
	<li>Distribute the master mix evenly across a 96-deep well plate using a multi-channel pipette, pipetting 415 &#181;L into each well. Keep this plate in an ice box covered from light.</li>
	<li>Using a liquid handling instrument, dispense 9.5 &#181;L of the master mix into each well of the 384-well plate with dried gDNA. Seal the plate with a foil and immediately place it at 4 &#176;C. Repeat this process for the remaining plates, ensuring that the needles of the liquid handling system are washed with water between each plate.</li>
	<li>Centrifuge the 384-well plates at 450 x g for 3 min and incubate them at 4 &#176;C overnight or between 6 - 12 h to resuspend the DNA and to dissipate any air bubbles.</li>
</ol>
4. qPCR Assay
<ol>
	<li>Following the overnight incubation, centrifuge at 450 x g for 3 min to dissipate any remaining air bubbles.</li>
	<li>For purposes of automation, connect the qPCR machine (e.g., LightCycler 480) to a microplate handler (see Table of Materials). Program the microplate handler to place the plates into the qPCR machine from a cooled storage dock that is protected from light. 
	NOTE&#160;The assays should, in theory, work on other qPCR machines with compatible optic settings.</li>
	<li>Use the following cycling conditions: 95 &#176;C for 5 min followed by 40 cycles of 95 &#176;C for 15 s and 66 &#176;C for 50 s, with data collection at 66 &#176;C.</li>
	<li>Once the run is complete, have the robot collect the plate from the qPCR machine and place it in the discard dock.</li>
</ol>
5. Post-run Analysis
<ol>
	<li>After amplification, calculate the quantification cycle (Cq) values using either the second derivative maximum method or the Fit Points method with the software of the qPCR machine (see Table of Materials), following the steps below.</li>
	<li>Open the qPCR software and, in the Navigator tab, open the saved reaction experiment file for one plate.</li>
	<li>For the analysis using the second derivative maximum method, select the Analysis tab, and create a new analysis using Abs Quant/Second Derivative Max method.
	<ol>
		<li>In the Create new analysis window, select analysis type: Abs Quant/Second Derivative Max method, subset: All Samples, program: Amplification, name: Rx-DFO (where x is the reaction number).</li>
		<li>Select Filter Comb and choose VIC/HEX/Yellow555 (533-580). This ensures that the data collected for STAT6 is selected.</li>
		<li>Select Colour Compensation for VIC/HEX/Yellow555(533-580). Click Calculate. Repeat this for Fam (465-510) and Cy5/Cy5.5(618-660). Click Save file.</li>
	</ol>
	</li>
	<li>For the analysis using the Fit Points method, select Abs Quant/Fit Points in the Analysis tab.
	<ol>
		<li>In the Create new analysis window, select analysis type: Abs Quant/Fit Points method, subset: All Samples, program: Amplification, name: RxF-DFO (where x is the reaction number).</li>
		<li>Select the correct filters and color compensations for STAT6 and each of the KIR genes (Fam/Cy5). In the Noiseband tab, set the noise band to exclude the background noise.</li>
		<li>In the Analysis tab, set the fit points to 3 and select Show fit points. Click Calculate. Click Save file.</li>
	</ol>
	</li>
</ol>
6. Export of the Results
<ol>
	<li>In the qPCR software, open the Navigator tab. Select Results Batch Export.</li>
	<li>Open the folder in which the experiment files are saved and transfer the files into the right-hand side section of the window. Click Next. Select the name and the location of the export file.</li>
	<li>Select Analysis type Abs Quant/Second Derivative Max method or Abs Quant/Fit Points. Click Next. Check that the name of the file, the export folder, and the analysis type are correct and click Next to start the export process.</li>
	<li>Wait until the Export Status is Ok. The screen will automatically move to the next step. Check that all selected files have been exported successfully so that the number of files failed = 0. Click Done.</li>
	<li>Use scripts split_file.pl and roche2sds.pl to split the exported plates into individual reactions for each plate. 
	NOTE&#160;The scripts are provided on request/GitHub.</li>
</ol>
7. Copy Number Calculations
<ol>
	<li>Open the copy number analysis software (e.g., CopyCaller). Select Import real-time PCR results file and load text files created by roche2sds.pl.</li>
	<li>Select Analyze and conduct the analysis by either selecting calibrator sample with known copy number or by selecting most frequent copy number. See Table 5 for the most frequent copy number of KIR genes typically observed in European-origin&#160;populations.</li>
</ol>
8. Data-quality Checks
<ol>
	<li>Use R script KIR_CNVdata_analysis_for_Excel_ver020215.R to combine copy number data from all the plates into a spreadsheet. 
	NOTE&#160;The scripts are provided on request/GitHub.</li>
	<li>Recheck the raw data on the copy number analysis software for samples that do not conform to the known linkage disequilibrium (LD) for KIR genes (Table 6).</li>
</ol>

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J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Co-evolution+of+human+leukocyte+antigen+(HLA)+class+I+ligands+with+killer-cell+immunoglobulin-like+receptors+(KIR)+in+a+genetically+diverse+population+of+sub-Saharan+Africans.">Co-evolution of human leukocyte antigen (HLA) class I ligands with killer-cell immunoglobulin-like receptors (KIR) in a genetically diverse population of sub-Saharan Africans.</a> PLoS Genetics. 9, e1003938 (2013).</li><li>Nakimuli, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Killer+cell+immunoglobulin-like+receptor+(KIR)+genes+and+their+HLA-C+ligands+in+a+Ugandan+population.">Killer cell immunoglobulin-like receptor (KIR) genes and their HLA-C ligands in a Ugandan population.</a> Immunogenetics. 65, 765-775 (2013).</li><li>Bontadini, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Distribution+of+killer+cell+immunoglobin-like+receptors+genes+in+the+Italian+Caucasian+population.">Distribution of killer cell immunoglobin-like receptors genes in the Italian Caucasian population.</a> Journal of Translational Medicine. 4, 1-9 (2006).</li><li>Graef, T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=KIR2DS4+is+a+product+of+gene+conversion+with+KIR3DL2+that+introduced+specificity+for+HLA-A*11+while+diminishing+avidity+for+HLA-C.">KIR2DS4 is a product of gene conversion with KIR3DL2 that introduced specificity for HLA-A*11 while diminishing avidity for HLA-C.</a> The Journal of Experimental Medicine. 206, 2557-2572 (2009).</li><li>B&#233;ziat, V., Hilton, H. G., Norman, P. J., Traherne, J. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Deciphering+the+killer-cell+immunoglobulin-like+receptor+system+at+super-resolution+for+natural+killer+and+T-cell+biology.">Deciphering the killer-cell immunoglobulin-like receptor system at super-resolution for natural killer and T-cell biology.</a> Immunology. 150, 248-264 (2017).</li><li>Blokhuis, J. H., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=KIR2DS5+allotypes+that+recognize+the+C2+epitope+of+HLA-C+are+common+among+Africans+and+absent+from+Europeans.">KIR2DS5 allotypes that recognize the C2 epitope of HLA-C are common among Africans and absent from Europeans.</a> Immunity, Inflammation and Disease. 5, 461-468 (2017).</li><li>Martin, M. P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Epistatic+interaction+between+KIR3DS1+and+HLA-B+delays+the+progression+to+AIDS.">Epistatic interaction between KIR3DS1 and HLA-B delays the progression to AIDS.</a> Nature Genetics. 31, 429-434 (2002).</li><li>Khakoo, S. I., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=HLA+and+NK+cell+inhibitory+receptor+genes+in+resolving+hepatitis+C+virus+infection.">HLA and NK cell inhibitory receptor genes in resolving hepatitis C virus infection.</a> Science. 305, 872-874 (2004).</li><li>van Bergen, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=KIR-ligand+mismatches+are+associated+with+reduced+long-term+graft+survival+in+HLA-compatible+kidney+transplantation.">KIR-ligand mismatches are associated with reduced long-term graft survival in HLA-compatible kidney transplantation.</a> American Journal of Transplantation. 11, 1959-1964 (2011).</li><li>Hiby, S. E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Association+of+maternal+killer+-+cell+immunoglobulin-like+receptors+and+parental+HLA+-+C+genotypes+with+recurrent+miscarriage.">Association of maternal killer - cell immunoglobulin-like receptors and parental HLA - C genotypes with recurrent miscarriage.</a> Human Reproduction. 23, 972-976 (2008).</li><li>Nakimuli, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+KIR+B+centromeric+region+present+in+Africans+but+not+Europeans+protects+pregnant+women+from+pre-eclampsia.">A KIR B centromeric region present in Africans but not Europeans protects pregnant women from pre-eclampsia.</a> Proceedings of the National Academy of Sciences. 112, 845-850 (2015).</li><li>van Bergen, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=HLA+reduces+killer+cell+Ig-like+receptor+expression+level+and+frequency+in+a+humanized+mouse+model.">HLA reduces killer cell Ig-like receptor expression level and frequency in a humanized mouse model.</a> The Journal of Immunology. 190, 2880-2885 (2013).</li><li>Bachanova, V., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Donor+KIR+B+Genotype+Improves+Progression-Free+Survival+of+Non-Hodgkin+Lymphoma+Patients+Receiving+Unrelated+Donor+Transplantation.">Donor KIR B Genotype Improves Progression-Free Survival of Non-Hodgkin Lymphoma Patients Receiving Unrelated Donor Transplantation.</a> Biology of Blood and Marrow Transplantation. 22, 1602-1607 (2016).</li><li>Cooley, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Donor+selection+for+natural+killer+cell+receptor+genes+leads+to+superior+survival+after+unrelated+transplantation+for+acute+myelogenous+leukemia.">Donor selection for natural killer cell receptor genes leads to superior survival after unrelated transplantation for acute myelogenous leukemia.</a> Blood. 116, 2411-2419 (2010).</li><li>Barani, S., Khademi, B., Ashouri, E., Ghaderi, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=KIR2DS1,+2DS5,+3DS1+and+KIR2DL5+are+associated+with+the+risk+of+head+and+neck+squamous+cell+carcinoma+in+Iranians.">KIR2DS1, 2DS5, 3DS1 and KIR2DL5 are associated with the risk of head and neck squamous cell carcinoma in Iranians.</a> Human Immunology. 79, 218-223 (2018).</li><li>Vilches, C., Casta&#241;o, J., G&#243;mez-Lozano, N., Estefan&#237;a, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Facilitation+of+KIR+genotyping+by+a+PCR-SSP+method+that+amplifies+short+DNA+fragments.">Facilitation of KIR genotyping by a PCR-SSP method that amplifies short DNA fragments.</a> Tissue Antigens. 70, 415-422 (2007).</li><li>Ashouri, E., Ghaderi, A., Reed, E. F., Rajalingam, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+novel+duplex+SSP-PCR+typing+method+for+KIR+gene+profiling.">A novel duplex SSP-PCR typing method for KIR gene profiling.</a> Tissue Antigens. 74, 62-67 (2009).</li><li>Martin, M. P., Carrington, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=KIR+locus+polymorphisms:+genotyping+and+disease+association+analysis.">KIR locus polymorphisms: genotyping and disease association analysis.</a> Methods in Molecular Biology. , 49-64 (2008).</li><li>Crum, K. A., Logue, S. E., Curran, M. D., Middleton, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Development+of+a+PCR-SSOP+approach+capable+of+defining+the+natural+killer+cell+inhibitory+receptor+(KIR)+gene+sequence+repertoires.">Development of a PCR-SSOP approach capable of defining the natural killer cell inhibitory receptor (KIR) gene sequence repertoires.</a> Tissue Antigens. 56, 313-326 (2000).</li><li>Houtchens, K. A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High-throughput+killer+cell+immunoglobulin-like+receptor+genotyping+by+MALDI-TOF+mass+spectrometry+with+discovery+of+novel+alleles.">High-throughput killer cell immunoglobulin-like receptor genotyping by MALDI-TOF mass spectrometry with discovery of novel alleles.</a> Immunogenetics. 59, 525-537 (2007).</li><li>Livak, K. J., Schmittgen, T. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Analysis+of+relative+gene+expression+data+using+real-time+quantitative+PCR+and+the+2-&#916;&#916;CT+method.">Analysis of relative gene expression data using real-time quantitative PCR and the 2-&#916;&#916;CT method.</a> Methods. 25, 402-408 (2001).</li><li>Traherne, J. A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=KIR+haplotypes+are+associated+with+late-onset+type+1+diabetes+in+European-American+families.">KIR haplotypes are associated with late-onset type 1 diabetes in European-American families.</a> Genes and Immunity. 17, 8-12 (2016).</li><li>Hydes, T. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+interaction+of+genetic+determinants+in+the+outcome+of+HCV+infection:+Evidence+for+discrete+immunological+pathways.">The interaction of genetic determinants in the outcome of HCV infection: Evidence for discrete immunological pathways.</a> Tissue Antigens. 86, 267-275 (2015).</li><li>Dunphy, S. E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=2DL1,+2DL2+and+2DL3+all+contribute+to+KIR+phenotype+variability+on+human+NK+cells.">2DL1, 2DL2 and 2DL3 all contribute to KIR phenotype variability on human NK cells.</a> Genes and Immunity. 16, 301-310 (2015).</li><li>Jiang, W., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=qKAT:+A+high-throughput+qPCR+method+for+KIR+gene+copy+number+and+haplotype+determination.">qKAT: A high-throughput qPCR method for KIR gene copy number and haplotype determination.</a> Genome Medicine. 8, 1-11 (2016).</li></ol>

The authors have nothing to disclose.

We described a novel semi-automated high-throughput method, called qKAT, which facilitates copy number typing of KIR genes. The method is an improvement over conventional methods like SSP-PCR, which are low-throughput and can only indicate the presence or absence of these highly polymorphic genes.
The accuracy of the copy number data obtained is dependent on multiple factors, including the quality and concentration-uniformity of the gDNA samples and the quality of the reagents. The quality and accuracy of the gDNA samples across a plate are extremely important since variations in concentration across the plate can result in errors in the calculation of the copy number. Since the assays were validated using European-origin sample sets, data from cohorts from other parts of the world require more thorough checks. This is to ensure that instances of allele dropout or non-specific primer/probe binding are not misinterpreted as copy number variation.
While the assays were designed and optimized to run as high-throughput, they can be modified to run fewer samples. The confidence metric in the copy number analysis software is affected when analyzing fewer samples, but this can be improved if control genomic DNA samples with a known KIR gene copy number are included on the plate and additional sample replicates are included.
For laboratories without liquid/plate-handling robots, master mix can be dispensed using multi-channel pipettes and plates can be manually loaded into the qPCR instrument.
The main aim behind the development of qKAT was to create a simple, high-throughput, high-resolution, and cost-effective method to genotype KIRs for disease association studies. This was successfully achieved since qKAT has been employed in investigating the role of KIR in several large disease association studies, including a range of infectious diseases, autoimmune conditions, and pregnancy disorders4,24,25,26.

In humans, the killer immunoglobulin-like receptor(KIR) locus is mapped on the long arm of chromosome 19 within the leukocyte receptor complex (LRC). This locus is around 150 kb in length and includes 15 KIR genes arranged head-to-tail. The KIR loci that are currently known are KIR2DL1, KIR2DL2/KIR2DL3, KIR2DL4, KIR2DL5A, KIR2DL5B, KIR2DS1-5, KIR3DL1/KIR3DS1, KIR3DL2-3, and two pseudogenes, KIR2DP1 and KIR3DP1. The KIR genes encode for two-dimensional (2D) and three-dimensional (3D) immunoglobulin-like domain receptors with short (S; activating) or long (L; inhibitory) cytoplasmic tails, which are expressed by natural killer (NK) cells and subsets of T cells. Copy number variation&#160;exhibited within the KIR locus forms diverse haplotypes with variable gene content1. Non-allelic homologous recombination (NAHR), facilitated by a close head-to-tail gene arrangement and high-sequence homology, is the mechanism proposed to be responsible for the haplotypic variability. Over 100 different haplotypes have been reported in populations worldwide1,2,3,4. All these haplotypes could be divided into two major groups: A and B haplotypes. The A haplotype contains 7 KIR genes: KIR3DL3, KIR2DL1, KIR2DL3, KIR2DL4, KIR3DL1, and KIR3DL2, which are inhibitory KIR genes, and the activating KIR gene KIR2DS4. However, up to 70% of European-origin individuals who are homozygous for KIR haplotype A exclusively carry a non-functional &#34;deletion&#34; form of KIR2DS45,6. All other KIR gene combinations form group B haplotypes, including at least one of the specific KIR genes KIR2DS1, KIR2DS2, KIR2DS3, KIR2DS5, KIR3DS1, KIR2DL2, and KIR2DL5, and typically include two or more activating KIR genes.
HLA Class I molecules have been identified as the ligands for certain inhibitory receptors (KIR2DL1, KIR2DL2, KIR2DL3, and KIR3DL1), activating receptors (KIR2DS1, KIR2DS2, KIR2DS4, KIR2DS5, and KIR3DS1), and for KIR2DL4, which is a unique KIR that contains a long cytoplasmic tails like other inhibitory KIR receptors but also has a positively charged residue near the extracellular domain which is a common feature of other activating KIR receptors. The combination of variants within the KIR genes and the HLA genes influences receptor ligand interaction that shapes potential NK cell responsiveness at the individual level7,8. Evidence from genetic association studies has indicated that KIR plays a role in viral resistance (e.g., human immunodeficiency virus [HIV]9 and hepatitis C virus [HCV]10), the success of transplantation11, the risk of pregnancy disorders and reproductive success12,13, the protection against relapse after allogeneic hematopoietic stem cell transplantation (HSCT)14,15,16, and the risk of cancers17.
The combination of high-sequence homology and allelic and haplotypic diversity presents challenges in the task of accurately genotyping KIR genes. Conventional methods to type KIR genes include sequence-specific primer (SSP) polymerase chain reaction (PCR)18,19,20, sequence-specific oligonucleotide probe (SSOP) PCR21, and matrix assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS)22. The drawbacks of these techniques are that they only provide partial insight into the genotype of an individual whilst also being laborious to perform. Recently next-generation sequencing (NGS) has been applied to type the KIR locus specifically. While this method is very powerful, it can be expensive to run, and it is time-consuming to conduct in-depth analysis and data checks.
qKAT is a high-throughput quantitative PCR method. While conventional methods are laborious and time-consuming, this method makes it possible to run nearly 1,000 genomic DNA (gDNA) samples in five days and gives the KIR genotype, as well as the gene copy number. qKAT consists of ten multiplex reactions, each of which targets two KIR loci and one reference gene of a fixed copy number in the genome (STAT6) used for the relative quantification of the KIR gene copy number23. This assay has been successfully used in studies involving large population panels and disease cohorts on infectious diseases such as HCV, autoimmune conditions like type 1 diabetes, and pregnancy disorders such as preeclampsia, as well as providing a genetic underpinning to studies aimed at understanding the NK cell function1,4,24,25,26.

<table><tbody><tr><td>&lt;strong&gt;REAGENTS&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>Oligonucleotides</td><td>Sigma</td><td>Custom order</td><td>SEQUENCES: Listed in Table 4</td></tr><tr><td>Probes labelled with ATTO dyes</td><td>Sigma</td><td>Custom order</td><td>SEQUENCES: Listed in Table 3</td></tr><tr><td>SensiFAST Probe No-ROX Kit</td><td>Bioline</td><td>BIO-86020</td><td>&amp;minus;</td></tr><tr><td>MilliQ water</td><td>&amp;minus;</td><td>&amp;minus;</td><td>&amp;minus;</td></tr><tr><td>&lt;strong&gt;Name&lt;/strong&gt;</td><td>&lt;strong&gt;Company&lt;/strong&gt;</td><td>&lt;strong&gt;Catalog Number&lt;/strong&gt;</td><td>&lt;strong&gt;Comments&lt;/strong&gt;</td></tr><tr><td>&lt;strong&gt;EQUIPMENT&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>Centrifuge with a swinging bucket rotor</td><td>Eppendorf(or equivalent)</td><td>Eppendorf 5810R or equivalent system</td><td></td></tr><tr><td>NanoDrop</td><td>Thermo Scientific</td><td>ND-2000</td><td></td></tr><tr><td>&lt;strong&gt;OR&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>QuBit Fluorometer</td><td>Life Technologies</td><td>Q33216</td><td></td></tr><tr><td>Matrix Hydra</td><td>Thermo Scientific</td><td>109611</td><td></td></tr><tr><td>LightCycler 480 II Instrument 384-well</td><td>Roche</td><td>05015243001</td><td></td></tr><tr><td>Twister II Microplate Handler with M&amp;eacute;Cour Thermal Plate Stacker (M&amp;eacute;Cour)</td><td>Caliper Life Sciences</td><td>204135</td><td></td></tr><tr><td>Vortex mixer</td><td>Biosan</td><td>BS-010201-AAA</td><td></td></tr><tr><td>Single-channel pipettes (volume range: 0.5&amp;ndash;10 &amp;micro;L, 2&amp;ndash;20 &amp;micro;L, 20&amp;ndash;200 &amp;micro;L, 200&amp;ndash;1,000 &amp;micro;L; 1-10 mL)</td><td>Gilson(or equivalent)</td><td>F144801, F123600, F123615, F123602, F161201</td><td></td></tr><tr><td>RNase- and DNase-free pipette tips filtered (10 &amp;micro;L, 20 &amp;micro;L, 200 &amp;micro;L, 1,000 &amp;micro;L, 10 mL)</td><td>Starlab (or equivalent)</td><td>S1111-3810, S1120-1810, S1120-8810, S1111-6810, I1054-0001</td><td></td></tr><tr><td>StarTub PS Reagent Reservoir, 55 mL</td><td>STARLAB</td><td>E2310-1010</td><td></td></tr><tr><td>50 mL Centrifuge Tube</td><td>STARLAB</td><td>E1450-0200</td><td></td></tr><tr><td>96-well deep well plate</td><td>Fisher Scientific</td><td>12194162</td><td></td></tr><tr><td>LC480 384 Multi-well plates</td><td>Roche</td><td>04729749001</td><td></td></tr><tr><td>LightCycler 480 Sealing Foil</td><td>Roche</td><td>04729757001</td><td></td></tr><tr><td>&lt;strong&gt;Name&lt;/strong&gt;</td><td>&lt;strong&gt;Company&lt;/strong&gt;</td><td>&lt;strong&gt;Catalog Number&lt;/strong&gt;</td><td>&lt;strong&gt;Comments&lt;/strong&gt;</td></tr><tr><td>&lt;strong&gt;SOFTWARE&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>Roche LightCycler 480 Software v1.5</td><td></td><td></td><td></td></tr><tr><td>Applied Biosystems CopyCaller Software v2.1</td><td></td><td></td><td>https://www.thermofisher.com/uk/en/home/technical-resources/software-downloads/copycaller-software.html</td></tr><tr><td>KIR haplotype identifier</td><td></td><td></td><td>http://www.bioinformatics.cimr.cam.ac.uk/haplotypes/</td></tr></tbody></table>

qkat: quantitative semi-automated typing of killer-cell immunoglobulin-like receptor genes

Killer cell immunoglobulin-like receptors (KIRs) are a set of inhibitory and activating immune receptors, on natural killer (NK) and T cells, encoded by a polymorphic cluster of genes on chromosome 19. Their best-characterized ligands are the human leukocyte antigen (HLA) molecules that are encoded within the major histocompatibility complex (MHC) locus on chromosome 6. There is substantial evidence that they play a significant role in immunity, reproduction, and transplantation, making it crucial to have techniques that can accurately genotype them. However, high-sequence homology, as well as allelic and copy number variation, make it difficult to design methods that can accurately and efficiently genotype all KIR genes. Traditional methods are usually limited in the resolution of data obtained, throughput, cost-effectiveness, and the time taken for setting up and running the experiments. We describe a method called quantitative KIR semi-automated typing (qKAT), which is a high-throughput multiplex real-time polymerase chain reaction method that can determine the gene copy numbers for all genes in the KIR locus. qKAT is a simple high-throughput method that can provide high-resolution KIR copy number data, which can be further used to infer the variations in the structurally polymorphic haplotypes that encompass them. This copy number and haplotype data can be beneficial for studies on large-scale disease associations, population genetics, as well as investigations on expression and functional interactions between KIR and HLA.

Watch this Scientific Journal Video about qKAT: Quantitative Semi-automated Typing of Killer-cell Immunoglobulin-like Receptor Genes at JoVE.com

qKAT: Quantitative Semi-automated Typing of Killer-cell Immunoglobulin-like Receptor Genes

Quantitative killer cell immunoglobulin-like receptor (KIR) semi-automated typing (qKAT) is a simple, high-throughput, and cost-effective method to copy number type KIR genes for their application in population and disease association studies.

Killer cell immunoglobulin-like receptors (KIRs) are a set of inhibitory and activating immune receptors, on natural killer (NK) and T cells, encoded by a ...

qkat-quantitative-semi-automated-typing-killer-cell-immunoglobulin

Nanyang Technological University

Research

JoVE Journal

Genetics

8.6K Views.  University of Cambridge. Deze methode kan antwoord geven op belangrijke vragen over NK celreceptorgenetica zoals haplotypediversiteit en hoe dit zich verhoudt tot ziekte. Visuele demonstratie van deze methode zal helpen om het protocol in uw laboratorium in te stellen, inclusief het automatiseringsproces en data-analyse. De belangrijkste voordelen van deze techniek zijn dat qKAT, in tegenstelling tot conventionele methoden, staat voor kwantitatieve KIR geautomatiseerde typen, een hoge doorvoer is en het genexemplaarn...

Video: qKAT: Quantitative Semi-automated Typing of Killer-cell Immunoglobulin-like Receptor Genes

Immunoglobulin Gene Sequence Analysis In Chronic Lymphocytic Leukemia: From Patient Material To Sequence Interpretation

During B cell maturation, the complex process of immunoglobulin (IG) gene V(D)J recombination coupled with somatic hypermutation (SHM) gives rise to a unique DNA sequence within each individual B cell. Since B cell malignancies result from the clonal expansion of a single cell, IG genes represent a unique molecular signature common to all the malignant cells within an individual patient; thus, IG gene rearrangements can be used as clonal markers. In addition to serving as an important clonal identifier, the IG gene sequence can act as a &#39;molecular timeline&#39; since it is associated with specific developmental stages and hence reflects the history of the B cell involved in the neoplastic transformation. Moreover, for certain malignancies, in particular chronic lymphocytic leukemia (CLL), the IG gene sequence holds prognostic and potentially predictive capabilities. That said, extrapolating meaningful conclusions from IG gene sequence analysis would be impossible if robust methods and tools were not available to aid in their analysis. This article, drawing on the vast experience of the European Research Initiative on CLL (ERIC), details the technical aspects and essential requirements necessary to ensure reliable and reproducible IG gene sequence analysis in CLL, a test that is now recommended for all CLL patients prior to treatment. More specifically, the various analytical stages are described ranging from the identification of the clonotypic IG gene rearrangement and the determination of the nucleotide sequence to the accurate clinical interpretation of the IG gene sequence data.

Herein, we present a protocol that details the technical aspects and essential requirements to ensure robust IG gene sequence analysis in patients with chronic lymphocytic leukemia (CLL), based on the accumulated experience of the European Research initiative on CLL (ERIC).

During B cell maturation, the complex process of immunoglobulin (IG) gene V(D)J recombination coupled with somatic hypermutation (SHM) gives rise to a ...

Cancer Research

Simultaneous Quantification of T-Cell Receptor Excision Circles (TRECs) and K-Deleting Recombination Excision Circles (KRECs) by Real-time PCR

T-cell receptor excision circles (TRECs) and K-deleting recombination excision circles (KRECs) are circularized DNA elements formed during recombination process that creates T- and B-cell receptors. Because TRECs and KRECs are unable to replicate, they are diluted after each cell division, and therefore persist in the cell. Their quantity in peripheral blood can be considered as an estimation of thymic and bone marrow output. By combining well established and commonly used TREC assay with a modified version of KREC assay, we have developed a duplex quantitative real-time PCR that allows quantification of both newly-produced T and B lymphocytes in a single assay. The number of TRECs and KRECs are obtained using a standard curve prepared by serially diluting TREC and KREC signal joints cloned in a bacterial plasmid, together with a fragment of T-cell receptor alpha constant gene that serves as reference gene. Results are reported as number of TRECs and KRECs/106 cells or per ml of blood. The quantification of these DNA fragments have been proven useful for monitoring immune reconstitution following bone marrow transplantation in both children and adults, for improved characterization of immune deficiencies, or for better understanding of certain immunomodulating drug activity.

Simultaneous Quantification of T-Cell Receptor Excision Circles TRECs and K-Deleting Recombination Excision Circles KRECs by Real-time PCR

Here, we describe a method for simultaneous quantification of T-cell receptor excision circles (TRECs) and K-deleting recombination excision circles (KRECs). The TREC/KREC assay can be used as marker of thymic and bone marrow output.

T-cell receptor excision circles (TRECs) and K-deleting recombination excision circles (KRECs) are circularized DNA elements formed during recombination ...

Immunology and Infection

Generation of Recombinant Human IgG Monoclonal Antibodies from Immortalized Sorted B Cells

Finding new methods for generating human monoclonal antibodies is an active research field that is important for both basic and applied sciences, including the development of immunotherapeutics. However, the techniques to identify and produce such antibodies tend to be arduous and sometimes the heavy and light chain pair of the antibodies are dissociated. Here, we describe a relatively simple, straightforward protocol to produce human recombinant monoclonal antibodies from human peripheral blood mononuclear cells using immortalization with Epstein-Barr Virus (EBV) and Toll-like receptor 9 activation. With an adequate staining, B cells producing antibodies can be isolated for subsequent immortalization and clonal expansion. The antibody transcripts produced by the immortalized B cell clones can be amplified by PCR, sequenced as corresponding heavy and light chain pairs and cloned into immunoglobulin expression vectors. The antibodies obtained with this technique can be powerful tools to study relevant human immune responses, including autoimmunity, and create the basis for new therapeutics.

Synthesis of human monoclonal antibodies is the first step in studies aimed at unraveling the pathophysiological mechanisms of auto-antibody-mediated immune responses. We have developed a protocol to generate recombinant human immunoglobulin G (IgG) monoclonal antibodies from blood sorted B cells, including B-cell isolation, antibody cloning and in vitro synthesis.

Finding new methods for generating human monoclonal antibodies is an active research field that is important for both basic and applied sciences, ...

Generating De Novo Antigen-specific Human T Cell Receptors by Retroviral Transduction of Centric Hemichain

T cell receptors (TCRs) are used clinically to direct the specificity of T cells to target tumors as a promising modality of immunotherapy. Therefore, cloning TCRs specific for various tumor-associated antigens has been the goal of many studies. To elicit an effective T cell response, the TCR must recognize the target antigen with optimal affinity. However, cloning such TCRs has been a challenge and many available TCRs possess sub-optimal affinity for the cognate antigen. In this protocol, we describe a method of cloning de novo high affinity antigen-specific TCRs using existing TCRs by exploiting hemichain centricity. It is known that for some TCRs, each TCR&#945; or TCR&#946; hemichain do not contribute equally to antigen recognition, and the dominant hemichain is referred to as the centric hemichain. We have shown that by pairing the centric hemichain with counter-chains differing from the original counter-chain, we are able to maintain the antigen specificity, while modulating its interaction strength for the cognate antigen. Thus, the therapeutic potential of a given TCR can be improved by optimizing the pairing between the centric and counter hemichains.

Generating De Novo Antigen-specific Human T Cell Receptors by Retroviral Transduction of Centric Hemichain

Herein we describe a novel method to generate antigen-specific T cell receptors (TCRs) by pairing the TCR&#945; or TCR&#946; of an existing TCR, possessing the antigen-specificity of interest, with complementary hemichain of the peripheral T cell receptor repertoire. The de novo generated TCRs retain antigen-specificity with varying affinity.

T cell receptors (TCRs) are used clinically to direct the specificity of T cells to target tumors as a promising modality of immunotherapy. Therefore, ...

VDJ-Seq: Deep Sequencing Analysis of Rearranged Immunoglobulin Heavy Chain Gene to Reveal Clonal Evolution Patterns of B Cell Lymphoma

Understanding tumor clonality is critical to understanding the mechanisms involved in tumorigenesis and disease progression. In addition, understanding the clonal composition changes that occur within a tumor in response to certain micro-environment or treatments may lead to the design of more sophisticated and effective approaches to eradicate tumor cells. However, tracking tumor clonal sub-populations has been challenging due to the lack of distinguishable markers. To address this problem, a VDJ-seq protocol was created to trace the clonal evolution patterns of diffuse large B cell lymphoma (DLBCL) relapse by exploiting VDJ recombination and somatic hypermutation (SHM), two unique features of B cell lymphomas.
In this protocol, Next-Generation sequencing (NGS) libraries with indexing potential were constructed from amplified rearranged immunoglobulin heavy chain (IgH) VDJ region from pairs of primary diagnosis and relapse DLBCL samples. On average more than half million VDJ sequences per sample were obtained after sequencing, which contain both VDJ rearrangement and SHM information. In addition, customized bioinformatics pipelines were developed to fully utilize sequence information for the characterization of IgH-VDJ repertoire within these samples. Furthermore, the pipeline allows the reconstruction and comparison of the clonal architecture of individual tumors, which enables the examination of the clonal heterogeneity within the diagnosis tumors and deduction of clonal evolution patterns between diagnosis and relapse tumor pairs. When applying this analysis to several diagnosis-relapse pairs, we uncovered key evidence that multiple distinctive tumor evolutionary patterns could lead to DLBCL relapse. Additionally, this approach can be expanded into other clinical aspects, such as identification of minimal residual disease, monitoring relapse progress and treatment response, and investigation of immune repertoires in non-lymphoma contexts.

This protocol describes an approach to interrogate the recombined immunoglobulin heavy chain VDJ regions of lymphomas by deep-sequencing and retrieve VDJ rearrangement and somatic hypermutation status to delineate clonal architecture of individual tumor. Comparing clonal architecture between paired diagnosis and relapse samples reveals lymphoma relapse clonal evolution modes.

Understanding tumor clonality is critical to understanding the mechanisms involved in tumorigenesis and disease progression. In addition, understanding ...

Medicine

Generation of Discriminative Human Monoclonal Antibodies from Rare Antigen-specific B Cells Circulating in Blood

Monoclonal antibodies (mAbs) are powerful tools useful for both fundamental research and in biomedicine. Their high specificity is indispensable when the antibody needs to distinguish between highly related structures (e.g., a normal protein and a mutated version thereof). The current way of generating such discriminative mAbs involves extensive screening of multiple Ab-producing B cells, which is both costly and time consuming. We propose here a rapid and cost-effective method for the generation of discriminative, fully human mAbs starting from human blood circulating B lymphocytes. The originality of this strategy is due to the selection of specific antigen binding B cells combined with the counter-selection of all other cells, using readily available Peripheral Blood Mononuclear Cells (PBMC). Once specific B cells are isolated, cDNA (complementary deoxyribonucleic acid) sequences coding for the corresponding mAb are obtained using single cell Reverse Transcription-Polymerase Chain Reaction (RT-PCR) technology and subsequently expressed in human cells. Within as little as 1 month, it is possible to produce milligrams of highly discriminative human mAbs directed against virtually any desired antigen naturally detected by the B cell repertoire.

We describe a method for the production of human antibodies specific for an antigen of interest, starting from rare B cells circulating in human blood. Generation of these natural antibodies is efficient and rapid, and the antibodies obtained can discriminate between highly related antigens.

Monoclonal antibodies (mAbs) are powerful tools useful for both fundamental research and in biomedicine. Their high specificity is indispensable when the ...

Identification of Mouse and Human Antibody Repertoires by Next-Generation Sequencing

The immense adaptability of antigen recognition by antibodies is the basis of the acquired immune system. Despite our understanding of the molecular mechanisms underlying the production of the vast repertoire of antibodies by the acquired immune systems, it has not yet been possible to arrive at a global view of a complete antibody repertoire. In particular, B cell repertoires have been regarded as a black box because of their astronomical number of antibody clones. However, next-generation sequencing technologies are enabling breakthroughs to increase our understanding of the B cell repertoire. In this report, we describe a simple and efficient method to visualize and analyze whole individual mouse and human antibody repertoires. From the immune organs, representatively from spleen in mice and peripheral blood mononuclear cells in humans, total RNA was prepared, reverse transcribed, and amplified using the 5&#39;-RACE method. Using a universal forward primer and antisense primers for the antibody class-specific constant domains, antibody mRNAs were uniformly amplified in proportions reflecting their frequencies in the antibody populations. The amplicons were sequenced by next-generation sequencing (NGS), yielding more than 105 antibody sequences per immunological sample. We describe the protocols for antibody sequence analyses including V(D)J-gene-segment annotation, a bird&#39;s-eye view of the antibody repertoire, and our computational methods.

Here, we describe protocols for the analysis and visualization of the structure and constitution of whole antibody repertoires. This involves the acquisition of vast sequences of antibody RNA using next-generation sequencing.

The immense adaptability of antigen recognition by antibodies is the basis of the acquired immune system. Despite our understanding of the molecular ...

Single-cell Screening Method for the Selection and Recovery of Antibodies with Desired Specificities from Enriched Human Memory B Cell Populations

The human antibody repertoire represents a largely untapped source of potential therapeutic antibodies and useful biomarkers. While current computational methods, such as next generation sequencing (NGS), yield enormous sets of data on the antibody repertoire at the sequence level, functional data is required to identify which sequences are relevant for a particular antigen or set of antigens. Here, we describe a method to identify and recover individual antigen-specific antibodies from peripheral blood mononuclear cells (PBMCs) from a human blood donor. This method utilizes an initial enrichment of mature B cells and requires a combination of phenotypic cell markers and fluorescently-labeled protein to isolate IgG memory B cells via flow cytometry. The heavy and light chain variable regions are then cloned and re-screened. Although limited to the memory B cell compartment, this method takes advantage of flow cytometry to interrogate millions of B cells and returns paired heavy and light chain sequences from a single cell in a format ready for expression and confirmation of specificity. Antibodies recovered with this method can be considered for therapeutic potential, but can also link specificity and function with bioinformatic approaches to assess the B cell repertoire within individuals.

The BSelex method to identify and recover individual antigen-specific antibodies from human peripheral blood mononuclear cells combines flow cytometry with single cell PCR and cloning.

The human antibody repertoire represents a largely untapped source of potential therapeutic antibodies and useful biomarkers. While current computational ...

T and B Cell Receptor Immune Repertoire Analysis using Next-generation Sequencing

Immunological memory, the hallmark of adaptive immunity, is orchestrated by T and B lymphocytes. In circulation and different organs, there are billions of unique T and B cell clones, and each one can bind a specific antigen, leading to proliferation, differentiation and/or cytokine secretion. The vast heterogeneity in T and B cells is generated by random recombination of different genetic segments. Next-generation sequencing (NGS) technologies, developed in the last decade, enable an unprecedented in-depth view of the T and B cell receptor immune repertoire. Studies in various inflammatory conditions, immunodeficiencies, infections and malignancies demonstrated marked changes in clonality, gene usage, and biophysical properties of immune repertoire, providing important insights about the role of adaptive immune responses in different disorders.
Here, we provide a detailed protocol for NGS of immune repertoire of T and B cells from blood and tissue. We present a pipeline starting from DNA isolation through library preparation, sequencing on NGS sequencer and ending with basic analyses. This method enables exploration of specific T and B cells at the nucleotide or amino-acid level, and thus can identify dynamic changes in lymphocyte populations and diversity parameters in different diseases. This technique is slowly entering clinical practice and has the potential for identification of novel biomarkers, risk stratification and precision medicine.

The current protocol describes a method for DNA isolation from blood samples and intestinal biopsies, generation of TCR&#946; and IGH PCR libraries for next-generation sequencing, performance of a NGS run and basic data analysis.

Immunological memory, the hallmark of adaptive immunity, is orchestrated by T and B lymphocytes. In circulation and different organs, there are billions ...

Profiling of the Human Natural Killer Cell Receptor-Ligand Repertoire

Natural killer (NK) cells are among the first responders to viral infections. The ability of NK cells to rapidly recognize and kill virally infected cells is regulated by their expression of germline-encoded inhibitory and activating receptors. The engagement of these receptors by their cognate ligands on target cells determines whether the intercellular interaction will result in NK cell killing. This protocol details the design and optimization of two complementary mass cytometry (CyTOF) panels. One panel was designed to phenotype NK cells based on receptor expression. The other panel was designed to interrogate expression of known ligands for NK cell receptors on several immune cell subsets. Together, these two panels allow for the profiling of the human NK cell receptor-ligand repertoire. Furthermore, this protocol also details the process by which we stain samples for CyTOF. This process has been optimized for improved reproducibility and standardization. An advantage of CyTOF is its ability to measure over 40 markers in each panel, with minimal signal overlap, allowing researchers to capture the breadth of the NK cell receptor-ligand repertoire. Palladium barcoding also reduces inter-sample variation, as well as consumption of reagents, making it easier to stain samples with each panel in parallel. Limitations of this protocol include the relatively low throughput of CyTOF and the inability to recover cells after analysis. These panels were designed for the analysis of clinical samples from patients suffering from acute and chronic viral infections, including dengue virus, human immunodeficiency virus (HIV), and influenza. However, they can be utilized in any setting to investigate the human NK cell receptor-ligand repertoire. Importantly, these methods can be applied broadly to the design and execution of future CyTOF panels.

Here we design two complementary mass cytometry (CyTOF) panels and optimize a CyTOF staining protocol with the aim of profiling the natural killer cell receptor and ligand repertoire in the setting of viral infections.

Natural killer (NK) cells are among the first responders to viral infections. The ability of NK cells to rapidly recognize and kill virally infected cells ...

qKAT: Quantitative Semi-automated Typing of Killer-cell Immunoglobulin-like Receptor Genes

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