This study was approved by the institutional review board at Sheba Medical Center, and informed written consent was obtained from all participating subjects.
1. DNA isolation and quantification
<ol>
	<li>Digestion and cell lysis of intestinal biopsies
	<ol>
		<li>Retrieve intestinal biopsies, either freshly collected or those stored at -20 &#176;C or -80 &#176;C. If using frozen biopsies, thaw on ice.</li>
		<li>Add 600 &#181;L of nuclei lysis solution to a sterile 1.7 mL micro-centrifuge tube, chilled on ice.</li>
		<li>Place biopsy into a microcentrifuge tube with lysis solution and incubate at 65 &#176;C for 15-30 min.</li>
		<li>Add 17.5 &#181;L of 20 mg/mL proteinase K and incubate overnight at 55 &#176;C, with gentle shaking.</li>
		<li>Allow sample to cool to room temperature for 5 min before proceeding to step 1.3.</li>
	</ol>
	</li>
	<li>Cell lysis of whole blood
	<ol>
		<li>Obtain 3 mL of whole blood in EDTA-, heparin-, or citrate-containing tube.</li>
		<li>Gently rock tube until thoroughly mixed, and transfer blood to a sterile 15 mL centrifuge tube containing 9 mL of cell lysis solution. Invert several times during a 10 min incubation period at room temperature.</li>
		<li>Centrifuge at 2,000 x g for 10 min at room temperature, and then discard as much supernatant as possible without disturbing the visible white pellet. Approximately 50&#8211;100 &#956;L of residual liquid will remain.</li>
		<li>Vortex tube vigorously for 15 s until completely resuspended. Add 3 mL of nuclei lysis solution and pipet several times. The solution should become viscous.</li>
	</ol>
	</li>
	<li>Protein precipitation
	<ol>
		<li>Add 200 &#181;L of protein precipitation buffer to the tissue, or 1 mL to the blood. Vortex vigorously for 20 s and incubate on ice for 5 min. Small protein clumps may be visible after vortexing.</li>
		<li>Centrifuge at 16,000 x g for 4 min. A tight pellet containing precipitated proteins should form.</li>
		<li>Carefully transfer supernatant, without disturbing the pellet, to a new 1.7 mL tube. 
		NOTE: If pellet is not tight, consider another centrifuge at 16,000 x g for 4 min.</li>
	</ol>
	</li>
	<li>DNA precipitation and rehydration
	<ol>
		<li>Add 1 mL of 2-propanol to tube containing the supernatant, and gently mix by inverting. DNA should become visible as white floating substance.</li>
		<li>Centrifuge at 16,000 x g for 1 min. Remove the supernatant completely using a pipette.</li>
		<li>Add 1 mL of freshly prepared 70% ethanol, and invert tube several times. Centrifuge at 16,000 x g for 1 min at room temperature. Discard supernatant carefully.</li>
		<li>Repeat step 1.4.3.</li>
		<li>Place open tube inverted on clean absorbent paper for 10-15 min. Re-invert tube and confirm complete hydration. If needed, leave to air-dry for additional 10-15 min. 
		NOTE: It is crucial for pellet to dry completely.</li>
		<li>Add 50 &#181;L of ultra-pure water (UPW). If needed, DNA can be diluted more after quantification.</li>
		<li>Incubate for 1 h on heat block at 65 &#176;C, for DNA rehydration.</li>
	</ol>
	</li>
	<li>DNA quantification 
	NOTE: DNA was quantified using a fluorometer and designated reagents, as specified in table of materials.
	<ol>
		<li>Bring standards to room temperature and prepare the kit, including 0.5 mL designated tubes.</li>
		<li>Prepare buffer and dye mix in a 15 mL tube, according to number of samples. Add 200 &#181;L of buffer and 1 &#181;L of dye per sample. Include 2 samples for standards. It is recommended to calculate an additional sample in order to avoid that the buffer will not be sufficient.
		<ol>
			<li>For the 2 standards, place 190 &#181;L of the above-prepared mix in 0.5 mL tube. Add 10 &#181;L of the standard.</li>
			<li>For each sample, place 199 &#181;L of the above-prepared mix in 0.5 mL tube. Add 1 &#181;L of the DNA.</li>
		</ol>
		</li>
		<li>Read the samples. The result indicates DNA concentration of the sample.</li>
		<li>If samples are over the limit, dilute the DNA 1:10 with UPW, and repeat read.</li>
	</ol>
	</li>
</ol>
2. Library preparation
NOTE: The current protocol utilizes a multiplex, PCR-based assay kit compatible with NGS sequencers. The kit contains 24 different indices each targeting conserved regions within the V&#946; and the J&#946; regions. This enables a one-step PCR reaction and pooling of different samples. See table of materials for details.
<ol>
	<li>Prepare DNA samples. Obtain 150 ng of DNA and add UPW for a total of 5 &#181;L. 
	NOTE: It is possible to use less than 150 ng of DNA for library preparation, with minimum concentration of 10 ng/&#181;L.</li>
	<li>Place pipettes and tips in hood with UV light for 15 min to break down residual DNA. Meanwhile, allow different index tubes (for library preparation) and DNA polymerase to thaw on ice.</li>
	<li>In a biological hood, add 45 &#181;L from the different index tubes into PCR tubes. To follow, add 0.2 &#181;L of the DNA polymerase and the 5 &#181;L of DNA prepared in step 2.1 into PCR tubes.</li>
	<li>Run PCR reaction using a pre-set program, according to the manufacturer&#39;s instructions.</li>
</ol>
3. Amplicon purification and quantification
<ol>
	<li>Use magnetic beads for removal of excess primers, nucleotides, and enzymes.
	<ol>
		<li>Warm the beads at least 30 min to room temperature. Prepare enough fresh 80% ethanol for 400 &#181;L per sample.</li>
		<li>Add 50 &#181;L (IGH) or 35 &#181;L (TCR&#946;) of the beads to each PCR tube and mix by pipetting 10 times. Incubate 10 min at room temperature.</li>
		<li>Place the mixed sample on the magnetic stand for 5 min.</li>
		<li>Aspirate 95 &#181;L (IGH) or 80 &#181;L (TCR&#946;) of the clear liquid and discard. Aspirate remaining liquid using a 10 &#181;L tip.</li>
		<li>Add 200 &#181;L of 80% ethanol to each sample. Incubate 30 s. Aspirate 195 &#181;L of ethanol and discard. Aspirate remaining liquid using 10 &#181;L tip.</li>
		<li>Repeat step 3.1.5. Open the caps of the tubes and let air dry for 5 min.</li>
		<li>Immediately after the 5 min, remove from magnetic stand and add 25 &#181;L of elution buffer (10 mM Tris-HCl, pH 8.0). Mix by pipetting until homogeneous. Incubate at room temperature for 2 min.</li>
		<li>Place the tubes on the magnetic stand for 5 min. Transfer 22 &#181;L to a new PCR tube. Measure the DNA concentration (step 1.5).</li>
	</ol>
	</li>
	<li>Amplicon quantification 
	NOTE: The current protocol uses an automated electrophoresis machine for quality control of DNA concentration, size, and integrity. See table of materials for details.
	<ol>
		<li>Place reagents and screentape at room temperature for at least 30 min.</li>
		<li>In a new 1.7 mL micro-centrifuge tube, make a 1 ng/&#181;L dilution of the DNA samples quantified in step 3.1.8 with UPW for a total volume of at least 3 &#181;L.</li>
		<li>Vortex diluted DNA before use. Place 2 &#181;L of buffer, together with 2 &#181;L of the diluted DNA in the pre-labeled specialized PCR strips (provided in the kit) and place the caps. Place on shaker for 1 min, followed by spin down of PCR strips. 
		NOTE: Due to the viscosity of buffer, ensure excess buffer is removed from the tip before transfer to the sample tubes.</li>
		<li>Place in the machine, the screentape and PCR strips without the caps. Open the lid of tip box inside the machine. Assign the position with appropriate labels. Start the machine. 
		NOTE: The output histogram should be a single peak at the desired size of the amplicons (Figure 1A). In samples of poor quality, additional peaks will be observed (Figure 1B), indicating poor bead clean-up or formation of primer dimers.</li>
	</ol>
	</li>
</ol>
4. Next-generation sequencing
<ol>
	<li>Quantification and pooling of library
	<ol>
		<li>Calculate final DNA concentration in nM, using DNA value from step 3.1.8, and the size in base pairs (bp) of the product&#8217;s peak, obtained from electrophoresis machine results (see Figure 1).</li>
		<li>For each sample, calculate DNA volume to take for a final concentration of 4 nM, in a final volume of 10-20 &#181;L elution buffer.</li>
		<li>Prepare a new dilution mix for each sample and take 2 &#181;L from it to a new pool mix. 
		NOTE: For samples that have less than 4 nM, add the maximum amount of sample possible.</li>
	</ol>
	</li>
	<li>NGS run of library 
	NOTE: The current protocol uses a bench-top sequencer platform. See table of materials for details.
	<ol>
		<li>Prepare a fresh solution of 0.2 N NaOH. Add 10 &#181;L of 0.2 N NaOH to the diluted library prepared in step 4.1.3. Add 5% PhiX to tube and vortex briefly. Spin down the tube to ensure all the solution has settled to the bottom of the tube.</li>
		<li>Incubate for 5 min at room temperature to denature the double stranded DNA. Add 980 &#956;L of pre-chilled buffer from the kit to the tube containing DNA and vortex briefly.</li>
		<li>Place the diluted library on ice, and prepare the library as follows. For a mix of 17 pM, add 425 &#181;L of DNA from step 4.2.2 and 575 &#181;L of buffer. Invert library several times and spin down. Load 600 &#181;L of the final library onto the designated cartridge, and place samples in the machine.</li>
		<li>Start the run following the software instructions.</li>
	</ol>
	</li>
</ol>
5. Sequencing analysis
<ol>
	<li>Download sequencing metrics from sequencer, and verify that sequencing data is within the following ranges (specific for the kit used in the current protocol). Samples not meeting these criteria are subject to repeat run: 
	Cluster Density (Density (K/mm2)): 945K &#8211; 1800K 
	Percent of reads passing filter (Clusters PF (%)): &#62;90% 
	Quality scores (%&#62;=Q30): &#62;85% 
	PhiX alignment (Aligned %): 1.5% - 10% 
	PhiX Error Rate (%): &#60;1.0%</li>
</ol>

<ol>
	<li>Bassing, C. H., Swat, W., Alt, F. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+mechanism+and+regulation+of+chromosomal+V(D)J+recombination.">The mechanism and regulation of chromosomal V(D)J recombination.</a> Cell. 109, 45-55 (2002).</li><li>Roth, D. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=V(D)J+Recombination:+Mechanism,+Errors,+and+Fidelity.">V(D)J Recombination: Mechanism, Errors, and Fidelity.</a> Microbiology Spectrum. 2 (6), (2014).</li><li>Heather, J. M., Ismail, M., Oakes, T., Chain, B. <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+sequencing+of+the+T-cell+receptor+repertoire:+pitfalls+and+opportunities.">High-throughput sequencing of the T-cell receptor repertoire: pitfalls and opportunities.</a> Brief Bioinformatics. 19 (4), 554-565 (2018).</li><li>Pabst, O., Hazanov, H., Mehr, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Old+questions,+new+tools:+does+next-generation+sequencing+hold+the+key+to+unraveling+intestinal+B-cell+responses.">Old questions, new tools: does next-generation sequencing hold the key to unraveling intestinal B-cell responses.</a> Mucosal Immunology. 8 (1), 29-37 (2015).</li><li>Bashford-Rogers, R. J. M., Smith, K. G. C., Thomas, D. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Antibody+repertoire+analysis+in+polygenic+autoimmune+diseases.">Antibody repertoire analysis in polygenic autoimmune diseases.</a> Immunology. 155 (1), 3-17 (2018).</li><li>Lee, Y. N., 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=Characterization+of+T+and+B+cell+repertoire+diversity+in+patients+with+RAG+deficiency.">Characterization of T and B cell repertoire diversity in patients with RAG deficiency.</a> Science Immunology. 1 (6), (2016).</li><li>Werner, L., 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=Alterations+in+T+and+B+Cell+Receptor+Repertoires+Patterns+in+Patients+With+IL10+Signaling+Defects+and+History+of+Infantile-Onset+IBD.">Alterations in T and B Cell Receptor Repertoires Patterns in Patients With IL10 Signaling Defects and History of Infantile-Onset IBD.</a> Frontiers Immunology. 11, 109 (2020).</li><li>Zhang, 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=Immune+receptor+repertoires+in+pediatric+and+adult+acute+myeloid+leukemia.">Immune receptor repertoires in pediatric and adult acute myeloid leukemia.</a> Genome Medicine. 11 (1), 73 (2019).</li><li>Chapman, C. G., 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=Characterization+of+T-cell+Receptor+Repertoire+in+Inflamed+Tissues+of+Patients+with+Crohn's+Disease+Through+Deep+Sequencing.">Characterization of T-cell Receptor Repertoire in Inflamed Tissues of Patients with Crohn's Disease Through Deep Sequencing.</a> Inflammatory Bowel Diseases. 22 (6), 1275-1285 (2016).</li><li>Werner, L., 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=Altered+T+cell+receptor+beta+repertoire+patterns+in+pediatric+ulcerative+colitis.">Altered T cell receptor beta repertoire patterns in pediatric ulcerative colitis.</a> Clinical and Experimental Immunology. 196 (1), 1-11 (2019).</li><li>Bashford-Rogers, R. J. M., 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=Analysis+of+the+B+cell+receptor+repertoire+in+six+immune-mediated+diseases.">Analysis of the B cell receptor repertoire in six immune-mediated diseases.</a> Nature. 574 (7776), 122-126 (2019).</li><li>Wu, 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=Expanded+TCRbeta+CDR3+clonotypes+distinguish+Crohn's+disease+and+ulcerative+colitis+patients.">Expanded TCRbeta CDR3 clonotypes distinguish Crohn's disease and ulcerative colitis patients.</a> Mucosal Immunology. 11 (5), 1487-1495 (2018).</li><li>Rosati, 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=Identification+of+disease-associated+traits+and+clonotypes+in+the+T-cell+receptor+repertoire+of+monozygotic+twins+affected+by+inflammatory+bowel+diseases.">Identification of disease-associated traits and clonotypes in the T-cell receptor repertoire of monozygotic twins affected by inflammatory bowel diseases.</a> Journam of Crohn's and Colitis. , (2019).</li><li>Allez, M., 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=T+cell+clonal+expansions+in+ileal+Crohn's+disease+are+associated+with+smoking+behaviour+and+postoperative+recurrence.">T cell clonal expansions in ileal Crohn's disease are associated with smoking behaviour and postoperative recurrence.</a> Gut. 68 (11), 1961-1970 (2019).</li><li>Li, 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=IMGT/HighV+QUEST+paradigm+for+T+cell+receptor+IMGT+clonotype+diversity+and+next+generation+repertoire+immunoprofiling.">IMGT/HighV QUEST paradigm for T cell receptor IMGT clonotype diversity and next generation repertoire immunoprofiling.</a> Nature Communications. 4, 2333 (2013).</li><li>H, I. 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=Strategies+for+B-cell+receptor+repertoire+analysis+in+primary+immunodeficiencies:+from+severe+combined+immunodeficiency+to+common+variable+immunodeficiency.">Strategies for B-cell receptor repertoire analysis in primary immunodeficiencies: from severe combined immunodeficiency to common variable immunodeficiency.</a> Frontiers Immunology. 6, 157 (2015).</li><li>Ghraichy, M., Galson, J. D., Kelly, D. F., Truck, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=B-cell+receptor+repertoire+sequencing+in+patients+with+primary+immunodeficiency:+a+review.">B-cell receptor repertoire sequencing in patients with primary immunodeficiency: a review.</a> Immunology. 153 (2), 145-160 (2018).</li><li>Zhuang, Y., 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=Application+of+immune+repertoire+sequencing+in+cancer+immunotherapy.">Application of immune repertoire sequencing in cancer immunotherapy.</a> International Immunopharmacology. 74, 105688 (2019).</li><li>Liu, X., 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=T+cell+receptor+beta+repertoires+as+novel+diagnostic+markers+for+systemic+lupus+erythematosus+and+rheumatoid+arthritis.">T cell receptor beta repertoires as novel diagnostic markers for systemic lupus erythematosus and rheumatoid arthritis.</a> Annual Rheumatic Diseases. 78 (8), 1070-1078 (2019).</li><li>Wong, G. K., Heather, J. M., Barmettler, S., Cobbold, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Immune+dysregulation+in+immunodeficiency+disorders:+The+role+of+T-cell+receptor+sequencing.">Immune dysregulation in immunodeficiency disorders: The role of T-cell receptor sequencing.</a> Journal of Autoimmunity. 80, 1-9 (2017).</li><li>Delhalle, S., Bode, S. F. N., Balling, R., Ollert, M., He, F. Q. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+roadmap+towards+personalized+immunology.">A roadmap towards personalized immunology.</a> NPJ System Biology and Applications. 4, 9 (2018).</li><li>Laubli, 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=The+T+cell+repertoire+in+tumors+overlaps+with+pulmonary+inflammatory+lesions+in+patients+treated+with+checkpoint+inhibitors.">The T cell repertoire in tumors overlaps with pulmonary inflammatory lesions in patients treated with checkpoint inhibitors.</a> Oncoimmunology. 7 (2), 1386962 (2018).</li><li>Hogan, S. 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=Peripheral+Blood+TCR+Repertoire+Profiling+May+Facilitate+Patient+Stratification+for+Immunotherapy+against+Melanoma.">Peripheral Blood TCR Repertoire Profiling May Facilitate Patient Stratification for Immunotherapy against Melanoma.</a> Cancer Immunology Research. 7 (1), 77-85 (2019).</li><li>Aversa, I., Malanga, D., Fiume, G., Palmieri, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Molecular+T-Cell+Repertoire+Analysis+as+Source+of+Prognostic+and+Predictive+Biomarkers+for+Checkpoint+Blockade+Immunotherapy.">Molecular T-Cell Repertoire Analysis as Source of Prognostic and Predictive Biomarkers for Checkpoint Blockade Immunotherapy.</a> International Journal of Molecular Sciences. 21 (7), (2020).</li><li>Hirsch, 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=Precision+and+prognostic+value+of+clone-specific+minimal+residual+disease+in+acute+myeloid+leukemia.">Precision and prognostic value of clone-specific minimal residual disease in acute myeloid leukemia.</a> Haematologica. 102 (7), 1227-1237 (2017).</li><li>De Simone, M., Rossetti, G., Pagani, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Single+Cell+T+Cell+Receptor+Sequencing:+Techniques+and+Future+Challenges.">Single Cell T Cell Receptor Sequencing: Techniques and Future Challenges.</a> Frontiers Immunology. 9, 1638 (2018).</li><li>Zemmour, D., 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=Single-cell+gene+expression+reveals+a+landscape+of+regulatory+T+cell+phenotypes+shaped+by+the+TCR.">Single-cell gene expression reveals a landscape of regulatory T cell phenotypes shaped by the TCR.</a> Nature Immunology. 19 (3), 291-301 (2018).</li><li>Zheng, C., 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=Landscape+of+Infiltrating+T+Cells+in+Liver+Cancer+Revealed+by+Single-Cell+Sequencing.">Landscape of Infiltrating T Cells in Liver Cancer Revealed by Single-Cell Sequencing.</a> Cell. 169 (7), 1342-1356 (2017).</li></ol>

All authors have nothing to disclose.

Changes in abundance and function of B and T lymphocytes are often encountered in different malignancies18, chronic inflammatory disorders (e.g., ulcerative colitis and rheumatoid arthritis)10,19, and in various immunodeficiencies17,20. The current method utilizes NGS to facilitate an in-depth view of TCR and BCR repertoires, enabling detection of subtle changes in T and B cell clo...

The adaptive immune system, comprised of T and B lymphocytes, utilizes immunological memory to recognize a previously encountered antigen and initiate a rapid response. Lymphocytes are generated in the bone marrow and mature in the thymus (T cells) or bone marrow (B cells). Both the T cell receptor (TCR) and B cell receptor (BCR) display unique configurations that allow recognition of specific antigens. In homeostasis, T and B cells constantly circulate and survey the trillions of different peptides presented on antigen-presenting cells. TCR or BCR ligation of a specific antigen with high affinity, together with appropriate co-stimulation, leads to cell activation, resulting in cytokine secretion, clonal expansion and generation of antibodies, in the case of B cells.
The enormous array of the different T or B cells is collectively termed immune repertoire, enabling recognition of countless of different epitopes. In order to generate such a vast repertoire, a complex process of random assembly of different gene segments takes place, creating nearly endless combinations of receptors that can bind unique antigens1. This process, called V(D)J recombination, includes rearrangements of different variable (V), diversity (D) and joining (J) genes, accompanied by random deletions and insertions of nucleotides in the junctions2.
The architecture of the adaptive immune system has interested scientists in different fields for many decades. In the past, Sanger sequencing, complementary determining region 3 (CDR3) spectratyping, and flow cytometry were used to characterize the immune repertoire, but provided low resolution. In the last decade, advances in next-generation sequencing (NGS) methods enabled in-depth insight into the characteristics and composition of an individual&#8217;s TCR and BCR repertoires3,4. These high-throughput systems (HTS) sequence and process millions of rearranged TCR or BCR products simultaneously and permit a high-resolution analysis of specific T and B cells at the nucleotide or amino acid level. NGS provides a new strategy to study the immune repertoire in both health and disease. Studies utilizing HTS demonstrated altered TCR and BCR repertoires in autoimmune diseases5, primary immunodeficiencies6,7, and malignancies, such as in acute myeloid leukemia8. Using NGS, we and others have shown oligoclonal expansion of specific T and B cell clones, in patients with inflammatory bowel disease (IBD), including ulcerative colitis and Crohn&#8217;s disease9,10,11,12,13,14. Overall, studies from different fields suggest changes in the repertoire have a crucial role in the pathogenesis of immune-mediated disorders.
The current protocol describes a method for isolation of DNA from intestinal biopsies and blood, generation of TCR&#946; and IGH PCR libraries for NGS, and performance of sequencing run. We also provide basic steps in immune repertoire data analysis. This protocol can be applied for the generation of TCR&#945;, TCR&#947;, and IGL libraries as well. The method is also compatible with other organs (e.g., lymph nodes, tumors, synovial fluid, fat tissue, etc.) as long as tissue-specific digestion protocols are used.

<table><tbody><tr><td>2-propanol</td><td>Sigma</td><td>I9516-500ML</td><td></td></tr><tr><td>1.7 mL micro-centrifuge tubes</td><td>Axygen</td><td>8187631104051</td><td></td></tr><tr><td>15 mL centrifuge tubes</td><td>Greiner</td><td>188261</td><td></td></tr><tr><td>Absolute ethanol</td><td>Merck</td><td>1.08543.0250</td><td></td></tr><tr><td>Amplitaq Gold</td><td>Thermo Fisher</td><td>N8080241</td><td></td></tr><tr><td>AMPure XP Beads</td><td>Beckman Coulter</td><td>A63881</td><td></td></tr><tr><td>Heat block</td><td>Bioer</td><td>Not applicable</td><td></td></tr><tr><td>High Sensitivity D1000 Sample Buffer</td><td>Agilent</td><td>5067-5603</td><td>For Tapestation</td></tr><tr><td>High Sensitivity D1000 ScreenTape</td><td>Agilent</td><td>5067-5584</td><td>For Tapestation. Tubes sold seperately</td></tr><tr><td>Lymphotrack Assay kit</td><td>Invivoscribe</td><td>TRB: 70-91210039 IGH: 70-92250019</td><td>Each includes 24 indexes</td></tr><tr><td>MiSeq Reagent Kit v2 (500 cycle)</td><td>Illumina</td><td>MS-102-2003</td><td>Includes standard flow cell type and all reagents required</td></tr><tr><td>MiSeq Sequencer</td><td>Illumina</td><td>SY-410-1003</td><td></td></tr><tr><td>PCR strips</td><td>4titude</td><td>4ti-0792</td><td></td></tr><tr><td>Proteinase K</td><td>Invitrogen</td><td>EO0491</td><td></td></tr><tr><td>Qubit 4 Fluorometer</td><td>Thermo Fisher</td><td>Q33226</td><td></td></tr><tr><td>Qubit dsDNA HS Assay Kit</td><td>Thermo Fisher</td><td>Q32854</td><td>Includes buffer, dye, standards, and specialized tubes</td></tr><tr><td>Shaker</td><td>Biosan</td><td>Not applicable</td><td></td></tr><tr><td>Tapestation 2100 Bioanalyzer</td><td>Agilent</td><td>G2940CA</td><td></td></tr><tr><td>ultra pure water</td><td>Bio-lab</td><td>7501</td><td></td></tr><tr><td>Wizard DNA isolation kit</td><td>Promega</td><td>A1120</td><td>Includes cell lysis solution, nuclei lysis solution, and protein precipitation buffer</td></tr></tbody></table>

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.

Herein, we describe a method for DNA isolation from intestinal tissue and blood, preparation of libraries for NGS, and basic steps of a sequencing run for immune repertoire sequencing. The run will generate fastq files, which can be further converted to fasta files for use in the international ImMunoGeneTics (IMGT)/HighV-QUEST platform. This HTS performs and manages many analyses of tens of thousands of rearranged TCR&#946; and IGH sequences, at the nucleotide level15. IMGT/HighV-QUEST enables ana...

Watch this Scientific Journal Video about T and B Cell Receptor Immune Repertoire Analysis using Next-generation Sequencing at JoVE.com

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

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 ...

t-b-cell-receptor-immune-repertoire-analysis-using-next-generation

Research

Education

JoVE Core

JoVE Journal

Anatomy and Physiology

Immunology and Infection

Unit 1

The Lymphatic and Immune System

SCIENTISTS IN ACTION

8.1K 조회수.  Sheba Medical Center. The current protocol describes a method for DNA isolation from blood samples and intestinal biopsies, generation of TCRβ and IGH PCR libraries for next-generation sequencing, performance of a NGS run and basic data analysis.

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

Flow-sorting and Exome Sequencing of the Reed-Sternberg Cells of Classical Hodgkin Lymphoma

The Hodgkin Reed-Sternberg cells of classical Hodgkin lymphoma are sparsely distributed within a background of inflammatory lymphocytes and typically comprise less than 1% of the tumor mass. Material derived from bulk tumor contains tumor content at a concentration insufficient for characterization. Therefore, fluorescence activated cell sorting using eight antibodies, as well as side- and forward-scatter, is described here as a method of rapidly separating and concentrating with high purity thousands of HRS cells from the tumor for subsequent study. At the same time, because standard protocols for exome sequencing typically require 100-1,000 ng of input DNA, which is often too high, even with flow sorting, we also provide an optimized, low-input library construction protocol capable of producing high-quality data from as little as 10 ng of input DNA. This combination is capable of producing next-generation libraries suitable for hybridization capture of whole-exome baits or more focused targeted panels, as desired. Exome sequencing of the HRS cells, when compared against healthy intratumor T or B cells, can identify somatic alterations, including mutations, insertions and deletions, and copy number alterations. These findings elucidate the molecular biology of HRS cells and may reveal avenues for targeted drug treatments.

Here, we describe a combined flow cytometric cell sorting and low-input, next-generation library construction protocol designed to produce high-quality, whole-exome data from the Hodgkin Reed-Sternberg (HRS) cells of classical Hodgkin lymphoma (CHL).

고전적인 Hodgkin 림프종의 Reed-Sternberg 세포의 흐름 정렬 및 Exome 시퀀싱

The Hodgkin Reed-Sternberg cells of classical Hodgkin lymphoma are sparsely distributed within a background of inflammatory lymphocytes and typically ...

연구

유전학

Reusable Single Cell for Iterative Epigenomic Analyses

Current single-cell epigenome analyses are designed for single use. The cell is discarded after a single use, preventing analysis of multiple epigenetic marks in a single cell and requiring data from other cells to distinguish signal from experimental background noise in a single cell. This paper describes a method to reuse the same single cell for iterative epigenomic analyses. 
In this experimental method, cellular proteins are first anchored to a polyacrylamide polymer instead of crosslinking them to protein and DNA, alleviating structural bias. This critical step allows repeated experiments with the same single cell. Next, a random primer with a scaffold sequence for proximity ligation is annealed to the genomic DNA, and the genomic sequence is added to the primer by extension using a DNA polymerase. Subsequently, an antibody against an epigenetic marker and control IgG, each labeled with different DNA probes, are bound to the respective targets in the same single cell. 
Proximity ligation is induced between the random primer and the antibody by adding a connector DNA with complementary sequences to the scaffold sequence of the random primer and the antibody-DNA probe. This approach integrates antibody information and nearby genome sequences in a single DNA product of proximity ligation. By enabling repeated experiments with the same single cell, this method allows an increase in data density from a rare cell and statistical analysis using only IgG and antibody data from the same cell. The reusable single cells prepared by this method can be stored for at least a few months and reused later to broaden epigenetic characterization and increase data density. This method provides flexibility to researchers and their projects.

The present protocol describes a single-cell method for iterative epigenomic analyses using a reusable single cell. The reusable single cell allows analyses of multiple epigenetic marks in the same single cell and statistical validation of the results.

반복적인 후성유전체학 분석을 위한 재사용 가능한 단일 세포

Current single-cell epigenome analyses are designed for single use. The cell is discarded after a single use, preventing analysis of multiple epigenetic ...

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.

생성<em&gt; 드 노보</em&gt; 중심 Hemichain의 레트로 바이러스 형질 도입에 의해 항원 특이 적 인간 T 세포 수용체

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

면역학 및 감염병학

Genome-wide Analysis of HDAC Inhibitor-mediated Modulation of microRNAs and mRNAs in B Cells Induced to Undergo Class-switch DNA Recombination and Plasma Cell Differentiation

Antibody responses are accomplished through several critical B cell-intrinsic processes, including somatic hypermutation (SHM), class-switch DNA recombination (CSR), and plasma cell differentiation. In recent years, epigenetic modifications or factors, such as histone deacetylation and microRNAs (miRNAs), have been shown to interact with B-cell genetic programs to shape antibody responses, while the dysfunction of epigenetic factors has been found to lead to autoantibody responses. Analyzing genome-wide miRNA and mRNA expression in B cells in response to epigenetic modulators is important for understanding the epigenetic regulation of B-cell function and antibody response. Here, we demonstrate a protocol for inducing B cells to undergo CSR and plasma cell differentiation, treating these B cells with histone deacetylase (HDAC) inhibitors (HDIs), and analyzing mRNA and microRNA expression. In this protocol, we directly analyze complementary DNA (cDNA) sequences using next-generation mRNA sequencing (mRNA-seq) and miRNA-seq technologies, mapping of the sequencing reads to the genome, and quantitative reverse transcription (qRT)-PCR. With these approaches, we have defined that, in B cells induced to undergo CSR and plasma cell differentiation, HDI, an epigenetic regulator, selectively modulates miRNA and mRNA expression and alters CSR and plasma cell differentiation.

Epigenetic factors can interact with genetic programs to modulate gene expression and regulate B cell function. By combining in vitro B-cell stimulation, qRT-PCR, and high-throughput microRNA-sequence and mRNA-sequence approaches, we can analyze the epigenetic modulation of miRNA and gene expression in B cells.

MicroRNAs 받 클래스 스위치 DNA 재조합 및 플라즈마 세포 차별화에 B 세포 유도에서 mRNAs의 게놈 넓은 분석의 HDAC 억제제 중재 변조

Antibody responses are accomplished through several critical B cell-intrinsic processes, including somatic hypermutation (SHM), class-switch DNA ...

Streamlined Single Cell TCR Isolation and Generation of Retroviral Vectors for In Vitro and In Vivo Expression of Human TCRs

Although, several methods for sequencing of paired T cell receptor (TCR) alpha and beta chains from single T cells have been developed, none so far have been conducive to downstream in vivo functional analysis of TCR heterodimers. We have developed an improved protocol based on a two-step multiplex-nested PCR, which results in a PCR product that spans entire variable regions of a human TCR alpha and beta chains. By identifying unique restriction sites and incorporating them into the PCR primers, we have made the PCR product compatible with direct sub-cloning into the template retroviral vector. The resulting retroviral construct encodes a chimeric human/mouse TCR with a mouse intracellular domain, which is functional in mouse cells or in in vivo mouse models. Overall, the protocol described here combines human single cell paired TCR alpha and beta chain identification with streamlined generation of retroviral vectors readily adaptable for in vitro and in vivo TCR expression. The video and the accompanying material are designed to give a highly detailed description of the single cell PCR, so that the critical steps can be followed and potential pitfalls avoided. Additionally, we provide a detailed description of the cloning steps necessary to generate the expression vector. Once mastered, the whole procedure from single cell sorting to TCR expression could be performed in a short two-week period.

Streamlined Single Cell TCR Isolation and Generation of Retroviral Vectors for In Vitro and In Vivo Expression of Human TCRs

The current protocol combines single cell paired human TCR alpha and beta chain sequencing with streamlined generation of retroviral vectors compatible with in vitro and in vivo TCR expression.

단일 셀 TCR 고립과 Retroviral 벡터 생체 외에서 의 생성과 Vivo에서 표현의 인간의 TCRs 간소화

Although, several methods for sequencing of paired T cell receptor (TCR) alpha and beta chains from single T cells have been developed, none so far have ...

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.

VDJ-SEQ : B 세포 림프종의 클론 진화 패턴을 나타 내기 위해 재 배열 면역 글로불린 무거운 체인 유전자의 깊은 시퀀싱 분석

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

의학

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.

마우스와 차세대 시퀀싱에 의해 인간의 항 체 레파토리의 식별

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.

농축 된 인간 기억 B 세포 집단에서 원하는 특이성을 가진 항체의 선택 및 회복을위한 단세포 스크리닝 방법

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

Predictive Immune Modeling of Solid Tumors

Immunotherapies show promise in the treatment of oncology patients, but complex heterogeneity of the tumor microenvironment makes predicting treatment response challenging. The ability to resolve the relative populations of immune cells present in and around the tumor tissue has been shown to be clinically-relevant to understanding response, but is limited by traditional techniques such as flow cytometry and immunohistochemistry (IHC), due the large amount of tissue required, lack of accurate cell type markers, and many technical and logistical hurdles. One assay (e.g., the ImmunoPrism Immune Profiling Assay) overcomes these challenges by accommodating both small amounts of RNA and highly degraded RNA, common features of RNA extracted from clinically archived solid tumor tissue. The assay is accessed via a reagent kit and cloud-based informatics that provides an end-to-end quantitative, high-throughput immuno-profiling solution for Illumina sequencing platforms. Researchers start with as few as two sections of formalin-fixed paraffin-embedded (FFPE) tissue or 20-40 ng of total RNA (depending on sample quality), and the protocol generates an immune profile report quantifying eight immune cell types and ten immune escape genes, capturing a complete view of the tumor microenvironment. No additional bioinformatic analysis is required to make use of the resulting data. With the appropriate sample cohorts, the protocol may also be used to identify statistically significant biomarkers within a patient population of interest.

The use of an RNA-based approach to determine quantitative immune profiles of solid tumor tissues and leverage clinical cohorts for immune-oncology biomarker discovery is described through a molecular and informatics protocols.

고형 종양의 예측 면역 모델링

Immunotherapies show promise in the treatment of oncology patients, but complex heterogeneity of the tumor microenvironment makes predicting treatment ...

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 ...