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111 protocols using ImmunoSEQ Assay

Samples were sequenced using the immunoSEQ assay (Adaptive Biotechnologies) utilizing the deep-level resolution to identify and quantitate the TCR β chain (TRB). In brief, the somatically rearranged TRB was amplified from 159.36–1,200 ng genomic DNA using a two-step, amplification bias-controlled multiplex PCR approach, and libraries were sequenced with raw Illumina sequence reads demultiplexed and processed as described previously.59 (link), 60 (link) Clonality was calculated according to the equation provided by Adaptive Technologies and their immunoSEQ software: 1 − (entropy) / log2(# of productive unique reads).
Additional data from peripheral blood samples used for TCR productive clonality comparisons were taken from the immuneACCESS open access database (Adaptive Biotechnologies). Henderson et al.42 (link) isolated, by FACS, CD4+CD25+CD127low Tregs from the peripheral blood (PB) of three young donors, whose ages ranged from 9.2–16.1 years. In the second study included, Emerson et al.61 (link) FACS-isolated CD4+CD45RA+CD62L+ (naive) and CD4+CD45RACD45RO+ (memory) T cells from 17 APB samples. Each study also used the immunoSEQ assay (Adaptive Biotechnologies) for TRB sequencing.
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To confirm the clonality screening results obtained via flow cytometry, TCRB deep sequencing was performed from 65 patients, accompanied by sequencing of 20 healthy controls (whose samples also underwent immunogene panel sequencing). Genomic DNA was used in all cases. Sequencing and data analysis were conducted as previously described with ImmunoSEQ assay by Adaptive Biotechnologies Corp43 (link)44 (link). Only productive TCR sequences were included in all analyses in this report.
Clonality was calculated according to the formula:

where pi is the proportional abundance of the rearrangement i, and N is the total number of rearrangements. The numerator of the equation is Shannon’s entropy. TCR repertoire overlap between two samples was calculated with the following formula:

in which ai is the template count of clone i in sample A, bi the template count of clone i in sample B, A the total number of templates in sample A, and B the total number of templates in sample B.
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Immunosequencing of the CDR3 regions of human TCRβ chains was performed using the ImmunoSEQ Assay (Adaptive Biotechnologies, Seattle, WA), as previously described70 (link)–72 . In brief, extracted genomic DNA was amplified in a bias-controlled multiplex PCR, with (i) a first PCR step consisting in forward and reverse amplification primers specific for every V and J gene segment, to allow the amplification of the hypervariable CDR3 region, and (ii) a second PCR adding a proprietary barcode sequence and Illumina adapter sequences. CDR3 libraries were sequenced on an Illumina MiSeq system according to the manufacturer’s instructions. ImmunoSeq Analizer 3.0 suite was used for sample export and preliminary statistics and quality control steps while R Bioconductor73 environment and Immunarch R74 suite were used for all the downstream analyses as previously described (Supplementary Data 8)21 (link).
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KIR+CD8+ T cells were sorted from PBMCs of nine healthy subjects, and DNA was extracted using QIAamp DNA Micro Kit (Qiagen). Sequencing of the CDR3 regions of human TCRβ chains was performed using the immunoSEQ Assay by Adaptive Biotechnologies.
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High-throughput sequencing of TCRs of cell line A01 was performed using the ImmunoSEQ assay (Adaptive Biotechnologies, Seattle, WA) with TCR-β and/or TCR-α/δ assays for each sample using a multiplex PCR approach following by Illumina high-throughput sequencing (Robins et al., 2010 (link); Carlson et al., 2013 (link)). The TCRs of C56SL37 and C58SL37 were sequenced by a single cell approach (Wang et al., 2012).
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6

Quantitative Analysis of SARS-CoV-2 Specific T Cell Responses

Immunosequencing of the CDR3 regions of human TCRβ chains was performed on blood genomic DNA using the immunoSEQ Assay (Adaptive Biotechnologies), which includes bias-controlled multiplex PCR, high-throughput sequencing, and identification and quantitation of absolute abundance of unique TCRβ CDR3 regions, and quantitation of the corresponding T cell fractions by template count normalization7 (link). Attribution of TCR sequences to SARS-CoV-2 spike or other non-spike SARS-CoV-2 protein specificities were assigned as described by Alter et al. and Sinder et al. 8 (link), 9 (link). The breadth summary metric was calculated as the number of unique annotated rearrangements among total number of unique productive rearrangements in the individual sample’s dataset. The depth metric was calculated by combining two elements; (a) the raw frequency of each rearrangement in the total repertoire in the individual sample’s dataset, and an estimate of clonal generations of the lineage represented by each rearrangement. The resultant depth metric estimates the relative number of clonal expansion generations across the TCRs, normalized by the total number of TCRs sequenced in the sample. Hence, the metric can range from negative to positive values9 (link).
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Mice (n = 3 per group) were immunized with TLR7–alum- or TLR7-NP-adjuvanted recombinant HA (H1 HA PR8) as described above. GC B cells were sorted from draining lymph nodes of immunized mice 14 days post-immunization and DNA was extracted using a QIAmp DNA Micro Kit (Qiagen). Sequencing of mouse IgH chains was performed using the immunoSEQ Assay (Adaptive Biotechnologies). The diversity index iChao1 is calculated using the Adaptive Biotechnologies Immuoseq Analyzer software. iChao1 is a non-parametric estimator of the lower bound of the total number of unique templates within an individual’s repertoire. The lower bound is the minimum number of unique templates predicted to be within an individual’s repertoire, with a 95% confidence interval58 (link)–60 .
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DNA from frozen PBMC was extracted using the DNA mini kit from Qiagen following manufacturer's instruction. For tumor samples slides from paraffin-embedded tumor or pieces of the fresh-frozen samples were incubated for 30 min at 65 °C in the extraction solution (0,2 M saccharose, 100 mM Tris, 100 mM NaCl, 50 mM EDTA, 0,5% SDS) and then cooled to 37 °C before treatment with RNase and proteinase K for 18 h at 37 °C. DNA was then purified using phenol-chloroform and chloroform extraction followed by NaCl ethanol precipitation. Five μg DNA/sample were used for TCR sequencing by Adaptive Biotechnologies using the immunoSEQ assay as previously described [45 (link)].
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Genomic DNA was extracted from pretreatment and on treatment peripheral blood samples and the CDR3 regions of TCRβ chains was sequenced using the immunoSEQ Assay (Adaptive Biotechnologies, Seattle, WA) [22 ]. T-cell fraction and Simpson Clonality were calculated as previously described.[23 ] TCR clonality graph was made in Graphpad Prism version 7.
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For TCRα sequencing, purified genomic DNA was sequenced by Adaptive Biotechnologies using the ImmunoSEQ assay (http://www.immunoseq.com) as described (34 (link)). PBMCs were subjected to deep-resolution sequencing (identified TCRs with a frequency of 1 in 2 × 105 to 1 × 106), and gut tissue samples were subjected to survey resolution (1 in 60,000), we reasoned that survey-level sequencing was sufficient for identification of expanded TCRs in the gut, but a greater in-depth might be required identify those TCRs if they were less expanded in the blood (31 (link)). Data were analyzed using the ImmunoSEQ analyser tools. Productive rearrangements (in-frame without stop codons) and TCR gene segment assignment were done as part of the ImmunoSEQ assay. The list of final clones generated by ImmunoSEQ was analyzed using VDJ tools (version 1.2.1) (35 (link)). Throughout our analysis, we applied the following filters: frame = in and reads >1. The filter applied for TCR analysis of unconventional T-cells is summarized in Figure 5B. In most of our analyses we stated TCR frequencies as a fraction of 1. MAIT Match server (http://www.cbs.dtu.dk/services/MAIT_Match/) was used to identify additional TCRs with MAIT-like features (36 (link)). TCR-α repertoire normalized data has been supplied in Supplementary Tables 24.
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