key: cord-0942696-7li1gfeb
authors: Manthiram, Kalpana; Xu, Qin; Milanez-Almeida, Pedro; Martins, Andrew; Radtke, Andrea; Hoehn, Kenneth; Chen, Jinguo; Liu, Can; Tang, Juanjie; Grubbs, Gabrielle; Stein, Sydney; Ramelli, Sabrina; Kabat, Juraj; Behzadpour, Hengameh; Karkanitsa, Maria; Spathies, Jacquelyn; Kalish, Heather; Kardava, Lela; Kirby, Martha; Cheung, Foo; Preite, Silvia; Duncker, Patrick; Romero, Nahir; Preciado, Diego; Gitman, Lyuba; Koroleva, Galina; Smith, Grace; Shaffer, Arthur; McBain, Ian; Pittaluga, Stefania; Germain, Ronald; Apps, Richard; Sadtler, Kaitlyn; Moir, Susan; Chertow, Daniel; Kleinstein, Steven; Khurana, Surender; Tsang, John; Mudd, Pamela; Schwartzberg, Pamela
title: Robust, persistent adaptive immune responses to SARS-CoV-2 in the oropharyngeal lymphoid tissue of children
date: 2022-03-23
journal: Res Sq
DOI: 10.21203/rs.3.rs-1276578/v1
sha: 9e2728a998a46e0b3b5c0bf1b9ce743d6cb50ed0
doc_id: 942696
cord_uid: 7li1gfeb

SARS-CoV-2 infection triggers adaptive immune responses from both T and B cells. However, most studies focus on peripheral blood, which may not fully reflect immune responses in lymphoid tissues at the site of infection. To evaluate both local and systemic adaptive immune responses to SARS-CoV-2, we collected peripheral blood, tonsils, and adenoids from 110 children undergoing tonsillectomy/adenoidectomy during the COVID-19 pandemic and found 24 with evidence of prior SARS-CoV-2 infection, including detectable neutralizing antibodies against multiple viral variants. We identified SARS-CoV-2-specific germinal center (GC) and memory B cells; single cell BCR sequencing showed that these virus-specific B cells were class-switched and somatically hypermutated, with overlapping clones in the adenoids and tonsils. Oropharyngeal tissues from COVID-19-convalescent children showed persistent expansion of GC and anti-viral lymphocyte populations associated with an IFN-γ-type response, with particularly prominent changes in the adenoids, as well as evidence of persistent viral RNA in both tonsil and adenoid tissues of many participants. Our results show robust, tissue-specific adaptive immune responses to SARS-CoV-2 in the upper respiratory tract of children weeks to months after acute infection, providing evidence of persistent localized immunity to this respiratory virus.

in GC and anti-viral memory responses following In nearly all seropositive participants, we detected S1 + RBD + B cells in PBMCs and both 109 pharyngeal tissues (Fig. 1e) , with the exception of two donors (CNMC 91 and 104) who 110 had almost no S1 + RBD + binding B cells in the peripheral blood (Extended Data Fig. 1a) . 111

These two donors also had the lowest serum neutralizing antibody titers to WA-1 among 112 our cohort. Surprisingly, one participant (CNMC 32) had high serum neutralization titers 113 but very low percentages of S1 + RBD + B cells, particularly in the oropharyngeal tissues, 114 highlighting heterogeneity in responses to SARS-CoV-2. 115 116 Evaluation of B cell populations by high-dimensional flow cytometry revealed that the 117 majority of S1 + RBD + B cells were CD27 + immunoglobulin (Ig) class-switched memory B 118 cells (IgD -CD38 -CD27 + ) ( Fig. 1f -g, Extended Data Fig. 1b, Supplementary Fig. 1-2) , 119 indicating a robust memory B cell response was generated and maintained in the upper 120 respiratory tract as long as 10 months into the convalescent period (Extended Data Fig.  121 1c). These S1 + RBD + memory B cells were primarily IgG + , with lower percentages of IgA + 122 cells compared to total CD27 + memory B cells in the tissue, perhaps reflecting the 123 inflammatory milieu during infection (Extended Data Fig. 1d ). Of note, the percentage of 124 S1 + RBD + cells we found among CD27 + switched memory B cells in the oropharyngeal 125 tissue was comparable to that recently reported in lung and lung-draining lymph nodes 126 from convalescent autopsy donors (Fig. 1f, Extended Data Fig. 1e ) 13 . 127

The predominance of Ig class-switched CD27 + memory B cells among S1 + RBD + B cells 129 suggested that they originated from GC reactions, although the timing of class switching 130 remains controversial 15 . Because the tonsils and adenoids are secondary lymphoid tissues 131 and sites of robust GC formation, we could directly examine the involvement of GCs. Flow 132 cytometric analysis revealed a substantial portion of GC B cells among the S1 + RBD + B 133 cells in both tissues (Fig. 1g) . Paired analyses of tonsils and adenoids from the same donor 134 revealed that the adenoids had higher frequencies of S1 + RBD + cells among both total and 135 GC B cells compared to tonsils, perhaps reflecting higher viral exposure due to their 136 location in the nasopharynx (Extended Data Fig. 1f-g) . Frequencies of S1 + RBD + B cells in negative (DN, IgD -CD27 -CD38 -CD19 + ) B cells 16, 17 . We also saw an expansion of DN B 150 cells among S1 + RBD + B cells in both adenoids and tonsils (Fig. 1g) . However, most of 151 these S1 + RBD + DN B cells exhibited characteristics of DN1 (CD21 + CD11c -) cells, which 152 are derived from GCs (Fig. 1i) . Only a small portion were DN2 (CD21 -CD11c + ) cells, which 153 originate from extrafollicular B cell activation and were reported to expand in acute severe 154 COVID-19 16 . Our findings, therefore, suggest that robust humoral responses to CoV-2 associated with intact GC reactions and B cell memory are present in the upper 156 respiratory tract mucosal lymphoid tissue. 157

158

To investigate B cell responses in greater detail, we sorted S1-binding (S1 + ) and non-160 binding (S1 -) B cells from tonsils, adenoids, and PBMCs from two subjects with a history 161 of COVID-19, as well as one uninfected control (Supplementary Fig. 3a-b) . Over 1860 S1 + 162 B cells and 25000 S1 -B cells were captured and characterized by CITE-seq (Cellular 163

Indexing of Transcriptomes and Epitopes by Sequencing), which simultaneously measured cytometric analysis, the majority of S1 + B cells in the tonsils and adenoids were in cluster 172 2, which represented CD27 + memory B cells (Fig. 2c -e). Adenoids and tonsils had a smaller 173 but clear portion of S1 + cells that were in cluster 4, which had a GC B cell gene expression 174 signature and surface protein profile ( Fig. 2b -e, Extended Data Fig. 2a-b) . In contrast, S1 + 175 cells in the blood were primarily in cluster 9 ( Fig. 2a-c, e) , which was also a CD27 + IgD -176 population (Fig. 2e , lower heatmap) but had different surface marker and gene expression 177 profiles compared to CD27 + IgDmemory B cells in the lymphoid tissues (Fig. 2e, upper  178 heatmap; Extended Data Fig. 2a ). S1 + cells from both the peripheral blood and tissues also 179 clustered separately when cells were clustered by transcript expression alone (Extended 180 Data Fig. 3) . Furthermore, S1 + memory B cells in cluster 2 had higher expression of CXCR3 181 and HOPX, genes known to be induced by T-bet in T cells 19 , than their S1counterparts, 182

suggesting that they may have developed in a more IFN-g rich environment 183

(Supplementary Table 5 compared to S1 -B cells, indicative of antigen-driven clonal expansion (Fig. 3c) . The high 192 mutation frequency in S1 + B cells is consistent with prior work showing that subjects with 193 mild COVID-19 had higher frequencies of hypermutated memory B cells compared to those 194 with severe COVID-19 22 and suggests that these SARS-CoV-2-specific clones underwent 195 somatic hypermutation in GCs. 196 197 Intriguingly, we also observed that a portion of S1 + B cell clones (a total of 83 cells from 29 198 clones: 20 clones from donor 89 and 9 from donor 71) were present in both the tonsils and 199 adenoids (Fig. 3d) . The shared S1 + clones were nearly all isotype-switched cells (Extended 200 Data Fig. 2f ) and, like the total S1 + B cell population, were comprised primarily of cells from 201 cluster 2 (CD27 + memory B cells) (Fig. 2e) . However, a small number of cells from shared 202 clones in the tonsil of one donor were GC B cells (cluster 4) ( Fig. 2e ; Supplementary Table  203 6). The distribution of these shared clones across adenoid and tonsil within some clonal 204 lineage trees suggested that B cell clones migrated between these oropharyngeal lymphoid 205 tissues and raised the possibility that class switching can occur before, during, or after 206 SHM (Fig. 3e) . Thus, multimodal single cell analysis of the SARS-CoV-2-specific B cells 207 both supports their emergence from GCs and suggests sharing and potential migration of 208 clonally expanded B cells between oropharyngeal lymphoid tissues. 209 210

To determine whether prior SARS-CoV-2 infection can broadly alter the immune landscape 212 of mucosal tissues beyond acute infection, we compared the immune cell profiles of tonsils, 213 adenoids, and peripheral blood from individuals with a history of COVID-19 to those 214 without, using both unsupervised analyses and manual gating of high-dimensional flow 215 cytometry data (samples included in each analysis are listed in Supplementary Table 2) . 216

To probe cell populations in greater detail, CD19 + B, CD4 + T, and CD8 + T lymphocytes 217 were first gated and then analyzed separately. Adenoids and tonsils were evaluated 218 together, whereas PBMCs were examined on their own, to account for and increase 219 sensitivity for detecting distinct populations in tissues and peripheral blood. 220

In the unsupervised analysis of B cell phenotypes, we compared those with prior COVID-222 19 to control subjects while controlling for age and sex. This analysis highlighted 14 223 clusters and revealed more pronounced changes in the adenoids post-COVID-19 ( Fig. 4a-224 b, Extended Data Fig. 4) . Clusters 3 and 10 were significantly increased in the adenoids of 225 participants with a history of COVID-19 (Fig. 4b) ; these clusters represented IgG + and IgM + 226 GC B cells, respectively. In addition, cluster 14, which clustered with naïve B cells, was 227 decreased in both adenoids and tonsils of COVID-19 convalescent subjects ( Fig. 4a-b) . In 228 the peripheral blood, a CD127 + IgD + B cell cluster was also decreased following COVID-19 229 Post-COVID-19, we observed that the adenoids had lower percentages of CD4 + T cells 236 (Extended Data Fig. 5a ). Unsupervised clustering further underscored differences in 237 COVID-19-convalescent samples ( Fig. 5a -b, Extended Data Fig. 6a -b) that included a 238 reduction in cluster 9, which represents naïve CD4 + T cells (CD45RA + CCR7 + ), in both 239 tonsils and adenoids from COVID-19 convalescent subjects ( Fig. 5a-b) . Traditional gating 240 confirmed decreased percentages of naïve CD4 + T cells in lymphoid tissue (Fig. 5c) . 241 242 Conversely, cluster 3, which represents a CD57 + PD-1 hi subset, was significantly enriched 243 after COVID-19 in both the adenoids and tonsils ( Fig. 5a-b) ; manual gating confirmed an 244 expanded CD57 + PD-1 hi CD4 + T cell population in the tissues (Fig. 5d ). CD57 has been 245 described as a marker of T cell senescence but is also found on a population of tonsillar 246 GC-Tfh cells 23-25 , a subset of CD4 + T helper cells that provide contact-mediated signals to 247 antigen-stimulated B cells for GC formation and maintenance. Compared to the total CD4 + 248 T cell population in the tissues, the CD57 + PD-1 hi CD4 + T cell population exhibited higher 249 expression of CXCR5 and CD69, indicative of a Tfh phenotype and characteristic of tissue-250 resident memory T (TRM) cells, respectively 6 ( Fig. 5e) . Imaging studies revealed that 251 CD57 + PD-1 hi CD4 + T cells were located within the GC (Fig. 5f ). Moreover, their frequency Fig. 5j-k) . Similar to the characteristics we found in adenoid CD4 + T cells, 288 regulatory T cells (CD25 + CD127 -) in the adenoids were also more activated after COVID-289 19, with a higher percentage of HLA-DR + CD38 + and CXCR3 + CCR6cells, again 290 suggesting the adenoids may have been primed by a stronger immune response to SARS-291

CoV-2 than the tonsils (Extended Data Fig. 5l-m) . Thus, we find an expansion of 292 percentages of Tfh as well as Tfr cells in the tonsils and adenoids that extends into 293 convalescence, providing further evidence for prolonged GC responses to SARS-CoV-2 in 294 the upper respiratory tract of children. 295 296

Because lymphocyte populations in the peripheral blood differ from the tonsil and adenoid, 298 we evaluated PBMCs separately; unsupervised grouping of high-dimensional flow 299 cytometry data revealed two clusters (cluster 5 and cluster 11) that were increased 300 following COVID-19 ( Fig. 6a- Supplementary Fig. 7a -b); both contained circulating Tfh 301 (cTfh)-like cells (CD45RA -CXCR5 + PD-1 + ) that expressed CD38, a marker of recently 302 activated T cells 28 ; cluster 11 was CXCR3 + while cluster 5 was not. Although we did not 303 find increased percentages of total cTfh cells by manual gating, we found that cTfh cells 304 were skewed to a CXCR3 + CCR6phenotype in the COVID-19-experienced group (Fig. 6c) ; 305 these cells produced IFN-g upon stimulation with PMA and ionomycin (Extended Data Fig.  306 7a). Analogous to prior reports, we also observed an increased frequency of stem cell-like 307 Fig. 7b) , 308 perhaps reflecting long-lived memory T cells following recovery from COVID-19 in 309

To identify SARS-CoV-2 antigen-specific CD4 + T cells, we stimulated tonsil, adenoid, and 312 peripheral blood mononuclear cells with spike (S), membrane (M), and nucleocapsid (N) 313 peptide pools and assessed the activation-induced markers (AIM) CD40L, OX40, and 4-314

1BB on T cells. Although we were not able to precisely identify and phenotype the SARS-315

CoV-2-specific T cells in the adenoids and tonsils due to the highly activated status of T 316 cells at baseline without stimulation in these tissues (Extended Data Fig. 7c- 

CoV-2-reactive CD4 + T cells were identified in the peripheral blood with the greatest 318 responses to the S peptide pool (Fig. 6d-e) . By concatenating all the peptide-activated 319

CD4 + T cells, we found that the SARS-CoV-2-responsive CD4 + T cells in the peripheral 320 blood were primarily memory cells that were enriched for CXCR3 + cTfh cells (CD45RA -321 

To further evaluate anti-viral responses, we examined CD8 + T cell in the tonsils and 328 adenoids. With unsupervised clustering, we found that cluster 1, which represented naïve 329 CD8 + T cells, decreased following COVID-19 in the adenoids ( Fig. 7a -b, Extended Data 330 CD8 + T cells (HLA-DR + CD38 + CXCR3 + CCR7 -CD45RA -); cluster 2 expressed higher CD38, 336 while cluster 3 expressed more CD57. Manual gating demonstrated that CD57 + PD-1 + CD8 + 337 T cells were significantly higher in adenoids and tonsils (Fig. 7c) , while activated HLA-338 DR + CD38 + CD8 + T cells trended higher in tonsils of the COVID-19-convalescent group 339 (Extended Data Fig. 9d ). As in CD4 + T cells, the COVID-19-convalescent adenoids also 340 had significantly more CXCR3 + CCR6 -CD8 + T cells (Tc1 skewed) (Extended Data Fig. 9e ). 341

Furthermore, CD8 + T cells in the adenoid produced more IFN-g than those in the tonsils 342 upon PMA/ionomycin stimulation, again indicating the ability of the adenoids to create a 343 more IFN-g rich environment during the anti-viral response (Extended Data Fig. 9f) . 344 345 CD8 + T cells expressing the senescence marker CD57 and inhibitory surface protein PD-346 1 are expanded in the peripheral blood of adults with moderate and severe COVID-19; 347 however, the function of these cells and whether they represent a non-functional 348 "exhausted" population is not clear 30,31 . We found that CD57 + PD-1 + CD8 + T cells in the 349 adenoids and tonsils had robust pro-inflammatory cytokine and cytotoxic factor production 350 following PMA and ionomycin stimulation (Extended Data Fig. 9g-h) . Table 7) . SARS-CoV-2 was detected in 7 out of 9 FFPE 386 adenoid blocks and 15 out of 22 FFPE tonsil blocks from COVID-19-convalescent 387

individuals, but not in any control tissue samples. In several samples, participants' previous 388 positive PCR from a nasal swab was over 100 days prior to surgery, including one which 389 was 303 days before surgery. Moreover, the copies of viral RNA significantly correlated 390 with the percentage of S1 + RBD + cells among GC B cells in the tonsil (Fig. 8b) . Although CoV-2 test to surgery (n = 10). 678 e. Frequency of S1 + RBD + cells among total CD19 + B cells from PBMC, adenoid, and 679 tonsil from COVID vs. CON (PBMC COVID n = 18, CON n = 33; adenoid COVID n = 16, 680 CON n = 27; and tonsil COVID n = 16, CON n = 30). 681 f. Representative flow cytometry plots demonstrating the percentage of SARS-CoV-2-682 specific (S1 + RBD + ) cells among CD27 + IgDswitched memory B cells in PBMC, adenoid, 683 and tonsil following COVID-19. Gating strategy shown in Supplementary Fig 1-2 . a. Sub-isotype frequencies among S1 + and S1 -B cells from PBMC, adenoid, and tonsil of 718 one COVID-19 convalescent donor (CNMC 89). Labels show the raw number of cells with 719 a given sub-isotype and are only included for sub-isotypes that make up at least 10% of a 720 given category. 721 b. Somatic hypermutation (SHM) frequency among S1 + and S1 -B cells from PBMC, CD4 + T cells were included in the SPICE analysis (see Supplementary Fig. 6) . 

This study was approved by the Institutional Review Board (IRB) at Children's National 865

Hospital (IRB protocol number 00009806). Written informed consent was obtained from 866 parent/guardians of all enrolled participants, and assent was obtained from minor 867 participants over 7 years of age. 868

We recruited 110 children who underwent tonsillectomy and/or adenoidectomy at 870

Children's National Hospital (CNH) in Washington, DC, USA. All children scheduled to 871 undergo tonsillectomy at CNH were eligible. The first 102 participants were recruited from 872 late September 2020 to early February 2021 without screening for prior COVID-19. An 873 additional 2 participants were subsequently recruited with known history of COVID-19, plus 874 6 additional subjects (one of whom turned out to be positive by serology) were recruited in 875

May and June 2021. Because not all tissues or blood were available from each subject, we 876 collected a total of 106 blood samples, 100 adenoids, and 108 tonsils from 110 participants 877 (Supplementary Table 2 ). No statistical methods were used to predetermine sample size. 878

All participants had negative RT-PCR testing from a nasopharyngeal swab for SARS-CoV-879 2 within 72 hours of the surgery. Demographic information and clinical data were collected 880 through parental questionnaires and chart review and inputted and managed in REDCap, 881 and biologic samples were acquired in the operating room by a separate clinical team at 882

Eleven participants had previous confirmed SARS-CoV-2 infection with RT-PCR or antigen 884 testing from nasopharyngeal swabs. Another thirteen COVID-19-exposed participants 885 were identified through serum antibody testing and/or identification of B cells that recognize 886 the spike protein of SARS-CoV-2 by flow cytometry (described below). One participant 887 (CNMC 43) had SARS-CoV-2 detected by RT-PCR from the nasopharynx 20 days prior to 888 surgery but had negative serology and no SARS-CoV-2 specific B cells in the tissue or 889 blood. We excluded this subject from our subsequent analysis. 890

Controls for flow cytometric analyses were selected among subjects with no serologic or 892 cellular evidence of prior COVID-19. The primary indication for tonsillectomy in all 24 893 participants with prior COVID-19 was adenotonsillar hypertrophy leading to sleep 894 disordered breathing (SDB) or obstructive sleep apnea (OSA) (Supplementary Table 1 and 895

3) except one participant who had eustachian tube dysfunction. Patients with SDB and 896 OSA both have breathing difficulties during sleep (primarily snoring); however, patients 897 with OSA had polysomnography documenting an apnea-hypopnea index greater than 1, 898 while those with SDB did not undergo polysomnography testing and were diagnosed by 899 clinical history alone. None of the 24 participants with COVID-19 had frequent recurrent 900 tonsillitis (more than 6 episodes in a year) or other medical problems that directly affect the 901 immune system aside from atopic disease, nor did they take immunomodulating 902 medications aside from nasal/inhaled steroid or loratadine within 2 weeks of surgery. Table 2 . 915

Blood samples were obtained just prior to the surgical procedure in the operating room in 917 serum separator tubes (BD) for serum collection and sodium heparin tubes (BD) for 918 peripheral blood mononuclear cells (PBMCs) extraction from an intravenous line placed for 919 anesthesia. Once received in the laboratory on the day of collection, serum separator tubes 920 were spun at 1200g for 10 min, and serum was aliquoted and stored at -80°C. PBMCs 921 were isolated the day after collection by density gradient centrifugation (Lymphocyte 922 Separation Medium, MP Biomedicals) at 1500rpm for 30 min at room temperature with no 923 brake and washed with PBS. If red blood cell contamination was present, cells were lysed 924 with ACK buffer. 925

Tonsil and adenoid tissues were stored in RPMI media with 5% FBS (VWR), gentamicin 926 50mg/mL (Gibco), and 1X antibiotic/antimycotic solution (Gibco) on ice immediately after 927 collection. Tissues were processed the day after collection. A 3-5mm portion of tonsil and 928 adenoid tissue was cut and fixed in 5mL of 10% buffered formalin (Avantik) for 24-48 h. 929

The fixed tissue was then incubated in 70% ethanol until it was paraffin-embedded. The 930 remainder of the tissue was mechanically disrupted and filtered through a 100μm cell 931 strainer to create a single cell suspension, lysed with ACK buffer (Gibco), and washed with 932 PBS three times. Freshly isolated PBMCs and tonsil and adenoid cells were surface 933 stained and analyzed with flow cytometry as described below on the day of processing. 934

The remaining cells were stored in liquid nitrogen in the presence of FBS (VWR) with 10% 935

After thawing frozen serum to room temperature, IgG and IgM antibodies against the spike 938 (S) protein and receptor-binding domain (RBD) of the S protein of SARS-CoV-2 were 939 analyzed using ELISA as previously described 38,58 . Positivity thresholds were based on Briefly, human codon-optimized cDNA encoding SARS-CoV-2 S glycoprotein of the WA-1, 949 B. 1.429, B.1.1.7, P.1, B.1.351, B.1.526, B.1.617.2, and B.1.1 .529 strains were synthesized 950 by GenScript and cloned into eukaryotic cell expression vector pcDNA 3.1 between 951 the BamHI and XhoI sites. Pseudovirions were produced by co-transfection Lenti-X 293T 952 cells with psPAX2(gag/pol), pTrip-luc lentiviral vector and pcDNA 3.1 SARS-CoV-2-spike-953 deltaC19, using Lipofectamine 3000. The supernatants were harvested at 48h post 954 transfection and filtered through 0.45µm membranes and titrated using 293T-ACE2-955

For the neutralization assay, 50 µL of SARS-CoV-2 S pseudovirions were pre-incubated 957

with an equal volume of medium containing serum at varying dilutions at room temperature 958 (RT) for 1 h, then virus-antibody mixtures were added to 293T-ACE2-TMPRSS2 cells in a 959 96-well plate. The input virus with all SARS-CoV-2 strains used in the current study were 960 the same (2x10 5 Relative light units/50 µL/well). After a 3 h incubation, the inoculum was 961 replaced with fresh medium. Cells were lysed 24 h later, and luciferase activity was 962 measured using luciferin. Controls included cells only, virus without any antibody and 963 positive sera. The cut-off value or the limit of detection for the neutralization assay is 1:10. 964

Data are shown in Supplementary Table 4 . 965

5 million cells per sample of PBMC, adenoid, or tonsil were resuspended in PBS with 2% 968 FBS and 2 mM EDTA (FACS buffer). Biotinylated S1 and RBD probes (BioLegend) were 969 crosslinked with fluorochrome-conjugated streptavidin in a molar ratio of 4:1. 970

Fluorochrome-conjugated streptavidin was split into 5 aliquots and conjugated to 971 biotinylated S1 and RBD probes by mixing for 20 min/aliquot at 4°C. Cells were first stained 972 with the viability dye, Zombie NIR (1:800 dilution, BioLegend), for 15 min at RT, washed 973 twice and then incubated with True-Stain Monocyte Blocker (BioLegend) for 5 min. An 974 antibody cocktail containing the rest of the surface antibodies, the fluorochrome-975 conjugated S1 and RBD probes, and Brilliant Stain Buffer Plus (BD) were then added 976 directly to the cells and incubated for 30 min at RT in the dark (200uL staining volume). 977

Cells were washed three times and fixed in 1% paraformaldehyde for 20 min at RT before 978 washing again and collecting on a spectral flow cytometer (Aurora, Cytek). Antibodies used 979 in this assay are shown in Supplementary Table 8 . 

CoV-2 N1 or N2 genes, they needed to average the manufacturer's limit of 1244 detection of ≥ 0.1 copies per µl and two positive droplets per well

Please see above for a detailed description of statistical analysis of results from 1247 unsupervised analysis as well as where to find reproducible scripts

Statistical analyses were 1251 performed using SPSS (IBM, version 28.0.0.0). Differences between groups were 1252 compared using the Mann-Whitney U test for independent values and Wilcoxon signed 1253 ranks test for paired values. Correlations were assessed using the Spearman rank 1254 correlation. All statistical tests were two-sided

Standardization of ELISA protocols for serosurveys of the SARS-1257

CoV-2 pandemic using clinical and at-home blood sampling

Neutralisation of 1260 circulating SARS-CoV-2 delta and omicron variants by convalescent plasma and 1261 SARS-CoV-2 hyperimmune intravenous human immunoglobulins for treatment of 1262 COVID-19

Antibody signature induced by SARS-CoV-2 spike protein 1265 immunogens in rabbits

Antibody affinity maturation and plasma IgA associate with clinical 1268 outcome in hospitalized COVID-19 patients

OMIP-069: Forty-Color Full Spectrum 1271 Flow Cytometry Panel for Deep Immunophenotyping of Major Cell Subsets in 1272 Human Peripheral Blood

Time-resolved systems immunology reveals a late juncture linked to 1275 fatal COVID-19

Broad immune activation underlies shared set point signatures 1278 for vaccine responsiveness in healthy individuals and disease activity in patients 1279 with lupus

Integrated analysis of multimodal single-cell data

Normalizing and denoising protein 1283 expression data from droplet-based single cell profiling. bioRxiv

Complex heatmaps reveal patterns and 1286 correlations in multidimensional genomic data

Elegant Graphics for Data Analysis. 1 edn

comprehensive 1291 database for human and mouse immunoglobulin and T cell receptor genes

IgBLAST: an immunoglobulin variable 1294 domain sequence analysis tool

Change-O: a toolkit for analyzing large-scale B cell 1297 immunoglobulin repertoire sequencing data

A spectral clustering-based method for identifying 1300 clones from high-throughput B cell repertoire sequencing data

Hierarchical Clustering Can Identify B Cell Clones with High 1303 Confidence in Ig Repertoire Sequencing Data

Models of somatic hypermutation targeting and substitution based 1306 on synonymous mutations from high-throughput immunoglobulin sequencing data

Phylogenetic analysis of migration, 1309 differentiation, and class switching in B cells. bioRxiv

Repertoire-wide phylogenetic models of B cell molecular 1314 evolution reveal evolutionary signatures of aging and vaccination

Likelihood models for detecting positively selected amino 1318 acid sites and applications to the HIV-1 envelope gene

ggtree: an r package for 1321 visualization and annotation of phylogenetic trees with their covariates and other 1322 associated data

IBEX: an iterative immunolabeling and chemical bleaching 1325 method for high-content imaging of diverse tissues

IBEX: A versatile multiplex optical imaging approach for deep 1328 phenotyping and spatial analysis of cells in complex tissues

Lymph-node resident CD8α+ dendritic cells capture antigens 1332 from migratory malaria sporozoites and induce CD8+ T cell responses

Histo-1335 cytometry: a method for highly multiplex quantitative tissue imaging analysis 1336 applied to dendritic cell subset microanatomy in lymph nodes

Spatial distribution and function of T follicular regulatory cells in 1339 human lymph nodes

Hyperactivated PI3Kδ promotes self and commensal reactivity at 1342 the expense of optimal humoral immunity

Data Availability: As sequencing data were collected from children, who are considered 1346 a vulnerable population, raw CITE-seq data are available upon request to corresponding 1347 authors. All other data are provided with the article or upon request from the 1348 corresponding authors

Code Availability: The R scripts used in this paper are

Acknowledgements: We thank the patients and their families for their generous 1354 participation

Julie Reilley and Neha Bansal for their technical assistance

RTB) of NIAID for 1356 figure illustrations; the Division of Otolaryngology at Children's National Hospital for 1357 helping with participant recruitment; the National Cancer Institute Sequencing Facility for 1358 sequencing support

The antibody response 1364 study was supported by FDA's Perinatal Health Center of Excellence (PHCE) project 1365 grant #GCBER005 to S.K. The work of

Author contributions

developed patient recruitment materials and/or recruited 1373 participants

All authors contributed to the final review and editing of the paper

Competing interests: S. Preite and A.S. are currently employees of AstraZeneca and may 1379 own stock or stock options. S.H.K. receives consulting fees from Peraton. K.B.H. receives 1380 consulting fees from Prellis Biologics

Extended Figure Data 1. Characterization of neutralization titers and S1 + RBD + B cells 1387 a. Correlation among frequencies of S1 + RBD + cell among B cells in peripheral blood

The color of data points indicates neutralizing titers (PsVNA50) to 1389

Frequency of CD27 + switched memory (SM) B cells among total B cells and among 1392

Frequency of S1 + RBD + cells among CD27 + SM B cells in adenoid and tonsil according 1395 to time from presumed active infection (positive PCR/antigen test from nasopharyngeal 1396 swab) to surgery

Proportion of each isotype among S1 + RBD + SM B cells and total SM B cells in PBMC

tonsil following COVID-19. The percentage of IgA + cells was significantly 1399 lower among S1 + RBD + SM B cells compared to total SM B cells in the tissue

Percentage of S1 + RBD + cells among CD27 + SM B cells from PBMC, adenoid, and tonsil 1402 following COVID-19 (COVID) vs. controls (CON)

Percentage of S1 + RBD + cells among total B cells (f) and GC B cells (g) from 14 1404 pairs of adenoid and tonsil COVID samples vs

Summary of correlations among neutralizing titers (PsVNA50) against several SARS-1406

CoV-2 variants and frequencies of S1 + RBD + cells among B cells in peripheral blood, 1407 adenoids, and tonsils

Mean number of GCs per total scanned tissue area (i) and mean GC area

GC area in section/total number of GCs in section) (j) from adenoid and tonsil in COVID 1410 vs. CON samples

Significance calculated 1415 with Mann-Whitney U test for unpaired values or Wilcoxon signed ranks test for paired 1416 values from the same donor. Correlation analysis performed with Spearman's rank 1417 correlation

Extended Data Figure 2

Extended Data Figure 2. CITE-seq analysis of SARS-CoV-2 antigen-specific B cells 1421

Heatmap of unsupervised clustering by CITE-seq antibody expression of S1 + and S1 -B 1422 cells from tonsil, adenoid, and PBMCs from three donors (2 COVID-19 convalescent and 1423 1 control) yielding 15 clusters. Most S1 + B cells are in cluster 2 which is IgD -and CD27 + , 1424 indicative of a memory B cell phenotype

Heatmap showing expression of signature gene sets for germinal center (GC) B cells

memory B cells, and plasma cells/plasmablasts (PC/PB) among all B cells (S1 + and S1 -) 1427 from tonsil, adenoid, and PBMC 1428 organized by cluster

Heatmap showing differentially expressed (DE) genes in S1 + vs. S1 -B cells from tonsil 1430 and adenoid from cluster 2 (which are CD27 + memory B cells, shown in Fig

Extended Data Fig. 2a). DE gene list is in Supplementary Table 5

Sub-isotype frequencies among S1 + and S1 -B cells from adenoid, tonsil and PBMC of 1433 two COVID-19 convalescent donors (CNMC 71 and 89) and one control

Labels show the raw number of cells with a given sub-isotype and are only shown for sub-1435 isotypes that make up at least 10% of a given category

Somatic hypermutation (SHM) frequency among S1 + and S1 -B cells of all isotypes from 1437

PBMC, adenoid, and tonsil of each donor. Mutation frequency calculated in V gene

Significance calculated with the Mann Whitney U test

Sub-isotype frequencies among S1 + B cells from clones shared between tonsil and 1440 adenoid vs. unshared clones. Labels show the raw number of cells with a given sub-isotype 1441 and are only included for sub-isotypes that make up at least 10% of a given category

Extended Data Figure 3. Gene-based clustering of CITE-seq of S1 + and S1 -B cells 1448

Unsupervised clustering based on gene expression of sorted S1 + and S1 -B cells from 1449 tonsil, adenoid, and PBMCs from three donors (2 COVID-19 convalescent and 1 control

Top defining genes for each cluster are noted. Top bar shows the 1451 corresponding cluster based on CITE-seq surface protein expression

Data Fig. 2a-b); middle bar indicates which cells are S1 + , and lower bar indicates tissue of 1453 origin

Extended Data Figure 4

Extended Data Figure 4. UMAP of unsupervised clustering of B cells from tonsil and 1458 adenoid 1459 a. Uniform manifold approximation and projection (UMAP) of unsupervised clustering of 1460 surface markers from flow cytometric analysis of CD19 + B cells from adenoid and tonsil

Heatmaps of marker/antibody expression overlayed on UMAP

Extended Data Figure

Extended Data Figure 5. Phenotyping of expanded CD4 + T cell populations in tissue 1467

Significance calculated using Mann-Whitney U test to 1500 compare two groups and Spearman's rank test for correlations

Extended Data Figure 6

Extended Data Figure 6. UMAP of unsupervised clustering of CD4 + T cells from tonsil 1505 and adenoid

Uniform manifold approximation and projection (UMAP) of unsupervised clustering of 1507 surface markers from flow cytometric analysis of CD4 + T cells from adenoid and tonsil

Heatmaps of marker/antibody expression overlayed on UMAP

Flow cytometry plots showing frequency of HLA-DR + CD38 + and ICOS + CXCR5 + cells 1528 from concatenated antigen-specific CD4 + T cells from PBMC following SARS

peptide stimulation compared to total CD4 + T cells. AIM + CD4 + T cells were concatenated 1530 from all three peptide pool stimulations of PBMCs from all 6 donors

Supplementary Table 9

Extended Data Figure 8

Extended Data Figure 8. UMAP of unsupervised clustering of CD8 + T cells from tonsil 1537 and adenoid

Uniform manifold approximation and projection (UMAP) of unsupervised clustering of 1539 surface markers from flow cytometric analysis of CD8 + T cells from adenoid and tonsil

Heatmaps of marker/antibody expression overlayed on UMAP

Phenotyping of CD8 + T cells from tonsil and adenoid 1547 1548 a. Quantification of the effect of prior SARS-CoV-2 infection on CD8 + T cell clusters in tonsil 1549 estimated with a linear model controlling for age and sex

Frequencies of naïve (TN, CD45RA + CCR7 + ) and effector memory (TEM

CCR7 -) CD8 + T cells in adenoid (b) and tonsil (c) of COVID-19-convalescent samples 1553 (COVID) vs. controls (CON)

Frequency of HLA-DR + CD38 + (d) and CXCR3 + CCR6 -(e) cells among CD8 + T cells 1555 in adenoid and tonsil from COVID vs. CON

Comparison of IFN-g production by CD8 + T cells in adenoid versus tonsil following PMA 1557 and ionomycin stimulation (n = 26 which includes 13 COVID and 13 CON of each tissue)

Intracellular cytokine and cytotoxic factor production by different CD8 + T cell 1559 subsets gated by CD57 and PD-1 from adenoid (g, n = 13) and tonsil (h

COVID-19-convalescent donors. Mean expression of each cytokine is plotted in the 1561 heatmap

Representative flow cytometry plots showing the expression of CD69, CD103

and CXCR5 levels on HLA-DR + CD38 + CD8 + T cells in tonsil. Phenotypes are similar in 1564 adenoid

Gating strategy shown in Supplementary Fig. 5. Samples analyzed in panels a-e are listed 1566 in Supplementary Table 2 (COVID adenoid n = 17, CON adenoid n = 42, COVID tonsil n = 1567 18, CON tonsil n = 46), and in panel f-h are in Supplementary Table 9

Significance calculated using Mann-Whitney U test

1e-3 quantiles were excluded. Single cells in each sample were first clustered using k-1013 means (k = 500, referred to as metacells), followed by merging cluster centroids from 1014 different samples with the same staining (i.e., tonsil/adenoids vs PBMC) for meta clustering 1015 and dimensionality reduction. Specifically, 500 centroids from each sample (metacells) 1016 were merged followed by another run of k-means meta-clustering (again k = 500), which 1017 were finally used in Leiden clustering and to learn a t-UMAP model to project the metacells 1018 (i.e., single cell-level k-means centroids; shown in plots). Seurat (4.0.3), uwot (0.1.10), and 1019 leiden (0.3.9) were used in shared nearest neighbors graph building, t-UMAP projection, 1020 and meta-clustering, respectively, with default settings. Leiden meta-clusters were mapped 1021 back to the single cell level and the ranked frequency of single cells in each Leiden meta-1022 cluster in each sample was modeled linearly as a function of age, sex, and history of 1023 COVID-19 (COVID status) (as in lm(rank(frequency) ~ age + sex + status). Prior to 1024 statistical modeling, PCA of frequencies was used to detect and exclude outlier samples. 1025 were further diluted by incremental addition of a 1:1 volume of media up to 8 mL, then 1036 centrifuged at 1600 rpm for 5 min. Cells were then resuspended in 300 μL of media, 1037 incubated at RT for 5 min, washed with media without DNase I, and filtered through a 1038 100µm strainer before spinning down for culture and resuspending in staining buffer (PBS 1039 + 1% BSA). Cells were then incubated with Fc blocker (Human TruStain FcX, BioLegend), 1040 stained with TotalSeq-C human hashtag antibodies (BioLegend) to uniquely label the 1041 sample origin (by tissue and donor), and washed with PBS + 0.04% BSA. Adenoids and 1042 tonsils from the 3 donors (6 samples in total) were pooled together and PBMCs from 3 1043were pooled together separately. The number of cells to pool from each tissue and donor 1044 was calculated with the aim of pooling a similar number of S1 + positive B cells from each 1045 sample. Pooled cells were first incubated with Fc blocker at 4°C for 10 min followed by 1046 CITE-seq and sorting antibody cocktails in the following order at 4°C: TotalSeq anti-CXCR3 1047 antibody for 10 min, TotalSeq chemokine cocktail (anti-CCR7, CCR6, CXCR5 antibodies) 1048 for 10 min, and the rest of CITE-seq antibodies and fluorescence-labeled sorting antibodies 1049 and viability dye (Aqua) for 30 min (Supplementary Table 8 ). Cells were then washed with 1050 PBS+0.04% BSA and resuspended in PBS+2% FBS. S1 + and S1 -B cells were sorted from 1051 each pool on a BD FACS Aria Fusion sorter for tonsil/adenoid pool and FACS Aria Illu Sorted S1 + and S1 -B cells were mixed with the reverse transcription mix and partitioned 1059 into single cell Gel-Bead in Emulsion (GEM) using 10x 5' Chromium Single Cell Immune the pooled samples using manual cutoffs on the hashtag antibody staining. We removed 1076 cells with less than 100 detected genes, greater than 30% mitochondrial reads, or mRNA 1077 counts greater than 25,000. To exclude cells with extremely high surface antibody counts, 1078we also removed the top 0.05% of cells in the surface antibody total count distribution. Cell 1079 clustering was performed by applying the FindNeighbors() function from Seurat on a 1080 distance matrix generated from the dsb-transformed surface protein data, followed by 1081Louvain clustering on the resulting SNN graph using Seurat's FindClusters() algorithm, with 1082 a resolution parameter of 1. Expression of selected genes were visualized using the 1083ComplexHeatmap package 67 , and the percentage of cells per cluster for the S1 + and S1 -1084 cells was plotted using ggplot2 68 . For the comparison of differentially expressed genes 1085 between the S1 + and S1 -B cells, we first downsampled the fastq files from the S1 + 1086 sequencing library to more closely match the reads-per-cell obtained in the S1sequencing 1087 libraries using seqtk v1.3. Differential expression was then compared using the MAST 1088 algorithm with "Donor" as a latent variable, as implemented in the Seurat FindMarkers 1089 function. For RNA-based clustering S1 + and S1 -B cells, we first downsampled the fastq 1090 files from the S1 + sequencing library to more closely match the reads-per-cell obtained in 1091 the S1sequencing libraries using seqtk v1.3. Cells were then clustered using the top 15 1092PCs derived from the 2000 most variable genes, selected by Seurat's 1093FindVariableFeatures function using the "vst" method. Clustering was performed using the 1094 included, which led to the exclusion of all S1 + cells from CNMC 99 (control with no history 1127 of COVID-19) and S1 + PBMCs from CNMC 89 (COVID-19 convalescent). Clonal overlap 1128 among tissues can be used as a measure of immunological connectivity. Clonal overlap 1129 was calculated using the Jaccard index, which for each pair of tissues is the number of 1130 unique clones found in both tissues (intersect) divided by the total number of unique clones 1131 among the two tissues (union). Clones were labelled as "S1 + " if they contained at least one 1132 S1 + sorted B cell. To infer lineage trees, we estimated tree topologies, branch lengths, and Hoechst (Biotium) and sections were mounted using Fluoromount G (Southern Biotech). 1157

Images were acquired using an inverted Leica TCS SP8 X confocal microscope equipped 1159 Buffer Plus (BD) was then added directly to the cells and incubated for 30 min at RT in the 1211 dark (total staining volume 180uL). Stained cells were washed three times and fixed in 1% 1212 paraformaldehyde for 20 min at RT before collecting on the Aurora spectral cytometer 1213 (Cytek). Antibodies and reagents used in this assay are listed in Supplementary Table 8 . 1214

Frozen cells were thawed as described in "Processing for CITE-seq." 2 million PBMC, 1216 adenoid, or tonsil cells from each sample were resuspended in 200 µL of complete RPMI 1217 medium containing 10% FBS (VWR), 2 mM glutamine, 0.055 mM beta-mercaptoethanol, 1218 1% penicillin/streptomycin, 1 mM sodium pyruvate, 10 mM HEPES, and 1% non-essential 1219 amino acids. Cells were stimulated with PMA (50ng/ml, Sigma) and ionomycin (1000ng/ml, 1220Sigma) for 2.5 h in the presence of anti-CD107a (BioLegend), GolgiSTOP (monensin, BD), 1221and GolgiPlug (BFA, BD). After stimulation, surface markers were stained as described 1222 above in the AIM assay. Surface-stained cells were washed and fixed with Cytofix Fixation 1223 Buffer (BD) at RT for 20 min and washed with permeabilization buffer (eBioscience) twice. 1224Then, the intracellular cytokine antibody mix was added for 30 min at RT (staining volume 1225 50uL). Stained cells were collected on the Aurora spectral cytometer (Cytek). Antibodies 1226 used in this assay are listed in Supplementary Table 8 . 1227

RNA was extracted from scrolls cut from FFPE tonsil and adenoid tissues using the using Mann-Whitney U test. Gating strategy in Supplementary Fig. 7 .