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

COVID-19 exhibits extensive patient-to-patient heterogeneity. To link immune response variation to disease severity and outcome over time, we longitudinally assessed circulating proteins as well as 188 surface protein markers, transcriptome, and T cell receptor sequence simultaneously in single peripheral immune cells from COVID-19 patients. Conditional-independence network analysis revealed primary correlates of disease severity, including gene expression signatures of apoptosis in plasmacytoid dendritic cells and attenuated inflammation but increased fatty acid metabolism in CD56dimCD16hi NK cells linked positively to circulating interleukin (IL)-15. CD8+ T cell activation was apparent without signs of exhaustion. Although cellular inflammation was depressed in severe patients early after hospitalization, it became elevated by days 17-23 post symptom onset, suggestive of a late wave of inflammatory responses. Furthermore, circulating protein trajectories at this time were divergent between and predictive of recovery versus fatal outcomes. Our findings stress the importance of timing in the analysis, clinical monitoring, and therapeutic intervention of COVID-19.

Adaptive immune responses to SARS-CoV-2 persist in the pharyngeal lymphoid tissue of children.

Most studies of adaptive immunity to SARS-CoV-2 infection focus on peripheral blood, which may not fully reflect immune responses at the site of infection. Using samples from 110 children undergoing tonsillectomy and adenoidectomy during the COVID-19 pandemic, we identified 24 samples with evidence of previous SARS-CoV-2 infection, including neutralizing antibodies in serum and SARS-CoV-2-specific germinal center and memory B cells in the tonsils and adenoids. Single-cell B cell receptor (BCR) sequencing indicated virus-specific BCRs were class-switched and somatically hypermutated, with overlapping clones in the two tissues. Expanded T cell clonotypes were found in tonsils, adenoids and blood post-COVID-19, some with CDR3 sequences identical to previously reported SARS-CoV-2-reactive T cell receptors (TCRs). Pharyngeal tissues from COVID-19-convalescent children showed persistent expansion of germinal center and antiviral lymphocyte populations associated with interferon (IFN)-γ-type responses, particularly in the adenoids, and viral RNA in both tissues. Our results provide evidence for persistent tissue-specific immunity to SARS-CoV-2 in the upper respiratory tract of children after infection.

Resident Macrophages Cloak Tissue Microlesions to Prevent Neutrophil-Driven Inflammatory Damage.

Neutrophils are attracted to and generate dense swarms at sites of cell damage in diverse tissues, often extending the local disruption of organ architecture produced by the initial insult. Whether the inflammatory damage resulting from such neutrophil accumulation is an inescapable consequence of parenchymal cell death has not been explored. Using a combination of dynamic intravital imaging and confocal multiplex microscopy, we report here that tissue-resident macrophages rapidly sense the death of individual cells and extend membrane processes that sequester the damage, a process that prevents initiation of the feedforward chemoattractant signaling cascade that results in neutrophil swarms. Through this "cloaking" mechanism, the resident macrophages prevent neutrophil-mediated inflammatory damage, maintaining tissue homeostasis in the face of local cell injury that occurs on a regular basis in many organs because of mechanical and other stresses. VIDEO ABSTRACT.

Intravenous nanoparticle vaccination generates stem-like TCF1+ neoantigen-specific CD8+ T cells.

Personalized cancer vaccines are a promising approach for inducing T cell immunity to tumor neoantigens. Using a self-assembling nanoparticle vaccine that links neoantigen peptides to a Toll-like receptor 7/8 agonist (SNP-7/8a), we show how the route and dose alter the magnitude and quality of neoantigen-specific CD8+ T cells. Intravenous vaccination (SNP-IV) induced a higher proportion of TCF1+PD-1+CD8+ T cells as compared to subcutaneous immunization (SNP-SC). Single-cell RNA sequencing showed that SNP-IV induced stem-like genes (Tcf7, Slamf6, Xcl1) whereas SNP-SC enriched for effector genes (Gzmb, Klrg1, Cx3cr1). Stem-like cells generated by SNP-IV proliferated and differentiated into effector cells upon checkpoint blockade, leading to superior antitumor response as compared to SNP-SC in a therapeutic model. The duration of antigen presentation by dendritic cells controlled the magnitude and quality of CD8+ T cells. These data demonstrate how to optimize antitumor immunity by modulating vaccine parameters for specific generation of effector or stem-like CD8+ T cells.

Integrating population and single-cell variations in vaccine responses identifies a naturally adjuvanted human immune setpoint.

Multimodal single-cell profiling methods can capture immune cell variations unfolding over time at the molecular, cellular, and population levels. Transforming these data into biological insights remains challenging. Here, we introduce a framework to integrate variations at the human population and single-cell levels in vaccination responses. Comparing responses following AS03-adjuvanted versus unadjuvanted influenza vaccines with CITE-seq revealed AS03-specific early (day 1) response phenotypes, including a B cell signature of elevated germinal center competition. A correlated network of cell-type-specific transcriptional states defined the baseline immune status associated with high antibody responders to the unadjuvanted vaccine. Certain innate subsets in the network appeared "naturally adjuvanted," with transcriptional states resembling those induced uniquely by AS03-adjuvanted vaccination. Consistently, CD14+ monocytes from high responders at baseline had elevated phospho-signaling responses to lipopolysaccharide stimulation. Our findings link baseline immune setpoints to early vaccine responses, with positive implications for adjuvant development and immune response engineering.

Differential Expression of the Transcription Factor GATA3 Specifies Lineage and Functions of Innate Lymphoid Cells.

Lymphoid tissue inducer (LTi) cells are regarded as a subset of innate lymphoid cells (ILCs). However, these cells are not derived from the ILC common progenitor, which generates other ILC subsets and is defined by the expression of the transcription factor PLZF. Here, we examined transcription factor(s) determining the fate of LTi progenitors versus non-LTi ILC progenitors. Conditional deletion of Gata3 resulted in the loss of PLZF+ non-LTi progenitors but not the LTi progenitors that expressed the transcription factor RORγt. Consistently, PLZF+ non-LTi progenitors expressed high amounts of GATA3, whereas GATA3 expression was low in RORγt+ LTi progenitors. The generation of both progenitors required the transcriptional regulator Id2, which defines the common helper-like innate lymphoid progenitor (ChILP), but not cytokine signaling. Nevertheless, low GATA3 expression was necessary for the generation of functionally mature LTi cells. Thus, differential expression of GATA3 determines the fates and functions of distinct ILC progenitors.

Influenza vaccination reveals sex dimorphic imprints of prior mild COVID-19.

Acute viral infections can have durable functional impacts on the immune system long after recovery, but how they affect homeostatic immune states and responses to future perturbations remain poorly understood1-4. Here we use systems immunology approaches, including longitudinal multimodal single-cell analysis (surface proteins, transcriptome and V(D)J sequences) to comparatively assess baseline immune statuses and responses to influenza vaccination in 33 healthy individuals after recovery from mild, non-hospitalized COVID-19 (mean, 151 days after diagnosis) and 40 age- and sex-matched control individuals who had never had COVID-19. At the baseline and independent of time after COVID-19, recoverees had elevated T cell activation signatures and lower expression of innate immune genes including Toll-like receptors in monocytes. Male individuals who had recovered from COVID-19 had coordinately higher innate, influenza-specific plasmablast, and antibody responses after vaccination compared with healthy male individuals and female individuals who had recovered from COVID-19, in part because male recoverees had monocytes with higher IL-15 responses early after vaccination coupled with elevated prevaccination frequencies of 'virtual memory'-like CD8+ T cells poised to produce more IFNγ after IL-15 stimulation. Moreover, the expression of the repressed innate immune genes in monocytes increased by day 1 to day 28 after vaccination in recoverees, therefore moving towards the prevaccination baseline of the healthy control individuals. By contrast, these genes decreased on day 1 and returned to the baseline by day 28 in the control individuals. Our study reveals sex-dimorphic effects of previous mild COVID-19 and suggests that viral infections in humans can establish new immunological set-points that affect future immune responses in an antigen-agnostic manner.

Innate and adaptive lymphocytes sequentially shape the gut microbiota and lipid metabolism.

The mammalian gut is colonized by numerous microorganisms collectively termed the microbiota, which have a mutually beneficial relationship with their host. Normally, the gut microbiota matures during ontogeny to a state of balanced commensalism marked by the absence of adverse inflammation. Subsets of innate lymphoid cells (ILCs) and conventional T cells are considered to have redundant functions in containment and clearance of microbial pathogens, but how these two major lymphoid-cell populations each contribute to shaping the mature commensal microbiome and help to maintain tissue homeostasis has not been determined. Here we identify, using advanced multiplex quantitative imaging methods, an extensive and persistent phosphorylated-STAT3 signature in group 3 ILCs and intestinal epithelial cells that is induced by interleukin (IL)-23 and IL-22 in mice that lack CD4+ T cells. By contrast, in immune-competent mice, phosphorylated-STAT3 activation is induced only transiently by microbial colonization at weaning. This early signature is extinguished as CD4+ T cell immunity develops in response to the expanding commensal burden. Physiologically, the persistent IL-22 production from group 3 ILCs that occurs in the absence of adaptive CD4+ T-cell activity results in impaired host lipid metabolism by decreasing lipid transporter expression in the small bowel. These findings provide new insights into how innate and adaptive lymphocytes operate sequentially and in distinct ways during normal development to establish steady-state commensalism and tissue metabolic homeostasis.

Transcriptional Response of Respiratory Epithelium to Nontuberculous Mycobacteria.

The incidence of pulmonary nontuberculous mycobacteria (NTM) disease is increasing, but host responses in respiratory epithelium infected with NTM are not fully understood. In this work, we aimed to identify infection-relevant gene expression signatures of NTM infection of the respiratory epithelium. We infected air-liquid interface (ALI) primary respiratory epithelial cell cultures with Mycobacterium avium subsp. avium (MAC) or Mycobacterium abscessus subsp. abscessus (MAB). We used cells from four different donors to obtain generalizable data. Differentiated respiratory epithelial cells at the ALI were infected with MAC or MAB at a multiplicity of infection of 100:1 or 1,000:1, and RNA sequencing was performed at Days 1 and 3 after infection. In response to infection, we found down-regulation of ciliary genes but upregulation of genes associated with cytokines/chemokines, such as IL-32, and cholesterol biosynthesis. Inflammatory response genes tended to be more upregulated by MAB than by MAC infection. Primary respiratory epithelial cell infection with NTM at the ALI identified ciliary function, cholesterol biosynthesis, and cytokine/chemokine production as major host responses to infection. Some of these pathways may be amenable to therapeutic manipulation.

Robust Inference of Cell-to-Cell Expression Variations from Single- and K-Cell Profiling.

Quantifying heterogeneity in gene expression among single cells can reveal information inaccessible to cell-population averaged measurements. However, the expression level of many genes in single cells fall below the detection limit of even the most sensitive technologies currently available. One proposed approach to overcome this challenge is to measure random pools of k cells (e.g., 10) to increase sensitivity, followed by computational "deconvolution" of cellular heterogeneity parameters (CHPs), such as the biological variance of single-cell expression levels. Existing approaches infer CHPs using either single-cell or k-cell data alone, and typically within a single population of cells. However, integrating both single- and k-cell data may reap additional benefits, and quantifying differences in CHPs across cell populations or conditions could reveal novel biological information. Here we present a Bayesian approach that can utilize single-cell, k-cell, or both simultaneously to infer CHPs within a single condition or their differences across two conditions. Using simulated as well as experimentally generated single- and k-cell data, we found situations where each data type would offer advantages, but using both together can improve precision and better reconcile CHP information contained in single- and k-cell data. We illustrate the utility of our approach by applying it to jointly generated single- and k-cell data to reveal CHP differences in several key inflammatory genes between resting and inflammatory cytokine-activated human macrophages, delineating differences in the distribution of 'ON' versus 'OFF' cells and in continuous variation of expression level among cells. Our approach thus offers a practical and robust framework to assess and compare cellular heterogeneity within and across biological conditions using modern multiplexed technologies.

Recent progress using systems biology approaches to better understand molecular mechanisms of immunity.

The immune system is composed of multiple dynamic molecular and cellular networks, the complexity of which has been revealed by decades of exacting reductionist research. However, understanding of the immune system sufficient to anticipate its response to novel perturbations requires a more integrative or systems approach to immunology. While methods for unbiased high-throughput data acquisition and computational integration of the resulting datasets are still relatively new, they have begun to substantially enhance our understanding of immunological phenomena. Such approaches have expanded our view of interconnected signaling and transcriptional networks and have highlighted the function of non-linear processes such as spatial regulation and feedback loops. In addition, advances in single cell measurement technology have demonstrated potential sources and functions of response heterogeneity in system behavior. The success of the studies reviewed here often depended upon integration of one or more systems biology approaches with more traditional methods. We hope these examples will inspire a broader range of immunologists to probe questions in a quantitative and integrated manner, advancing collective efforts to understand the immune "system".

Protective role of G-CSF in dextran sulfate sodium-induced acute colitis through generating gut-homing macrophages.

Granulocyte colony-stimulating factor (G-CSF) is a pleiotropic cytokine best known for its role in promoting the generation and function of neutrophils. G-CSF is also found to be involved in macrophage generation and immune regulation; however, its in vivo role in immune homeostasis is largely unknown. Here, we examined the role of G-CSF in dextran sulfate sodium (DSS)-induced acute colitis using G-CSF receptor-deficient (G-CSFR(-/-)) mice. Mice were administered with 1.5% DSS in drinking water for 5days, and the severity of colitis was measured for the next 5days. GCSFR(-/-) mice were more susceptible to DSS-induced colitis than G-CSFR(+/+) or G-CSFR(-/+) mice. G-CSFR(-/-) mice harbored less F4/80(+) macrophages, but a similar number of neutrophils, in the intestine. In vitro, bone marrow-derived macrophages prepared in the presence of both G-CSF and macrophage colony-stimulating factor (M-CSF) (G-BMDM) expressed higher levels of regulatory macrophage markers such as programmed death ligand 2 (PDL2), CD71 and CD206, but not in arginase I, transforming growth factor (TGF)-ß, Ym1 (chitinase-like 3) and FIZZ1 (found in inflammatory zone 1), and lower levels of inducible nitric oxide synthase (iNOS), CD80 and CD86 than bone marrow-derived macrophages prepared in the presence of M-CSF alone (BMDM), in response to interleukin (IL)-4/IL-13 and lipopolysaccharide (LPS)/interferon (IFN)-γ, respectively. Adoptive transfer of G-BMDM, but not BMDM, protected G-CSFR(-/-) mice from DSS-induced colitis, and suppressed expression of tumor necrosis factor (TNF)-α, IL-1ß and iNOS in the intestine. These results suggest that G-CSF plays an important role in preventing colitis, likely through populating immune regulatory macrophages in the intestine.

Teplizumab induces persistent changes in the antigen-specific repertoire in individuals at-risk for type 1 diabetes.

BACKGROUND: Teplizumab, a FcR non-binding anti-CD3 mAb, is approved to delay progression of type 1 diabetes (T1D) at-risk patients. Previous investigations described the immediate effects of the 14-day treatment, but longer-term effects of the drug remain unknown. METHODS: With an extended analysis of study participants, we found that 36% were undiagnosed or remained clinical diabetes free after 5 years suggesting operational tolerance. Using single cell RNA-seq, we compared the phenotypes, transcriptome, and repertoire of peripheral blood CD8+ T cells including autoreactive T cells from study participants before and after teplizumab and features of responders and non-responders. RESULTS: At 3 months, there were transcriptional signatures of cell activation in CD4+ and CD8+ T cells including signaling that was reversed at 18 months. At that time, there was reduced expression of genes in T cell receptor and activation pathways in clinical responders. In CD8+ T cells, we found increased expression of genes associated with exhaustion and immune regulation with teplizumab treatment. These transcriptional features were further confirmed in an independent cohort. Pseudotime analysis showed differentiation of CD8+ exhausted and memory cells with teplizumab treatment. IL7R expression was reduced and patients with lower expression of CD127 had longer diabetes free intervals. In addition, the frequency of autoantigen reactive CD8+ T cells, that expanded in the placebo group over 18 months, did not increase in the teplizumab group. CONCLUSION: These findings indicate that teplizumab promotes operational tolerance in T1D, involving activation followed by exhaustion and regulation and prevents expansion of autoreactive T cells. CLINICALTRIALS: gov: NCT01030861. FUNDING: NIDDK/NIH, Juvenile Diabetes Research Foundation.

A unified metric of human immune health.

Immunological health has been challenging to characterize but could be defined as the absence of immune pathology. While shared features of some immune diseases and the concept of immunologic resilience based on age-independent adaptation to antigenic stimulation have been developed, general metrics of immune health and its utility for assessing clinically healthy individuals remain ill defined. Here we integrated transcriptomics, serum protein, peripheral immune cell frequency and clinical data from 228 patients with 22 monogenic conditions impacting key immunological pathways together with 42 age- and sex-matched healthy controls. Despite the high penetrance of monogenic lesions, differences between individuals in diverse immune parameters tended to dominate over those attributable to disease conditions or medication use. Unsupervised or supervised machine learning independently identified a score that distinguished healthy participants from patients with monogenic diseases, thus suggesting a quantitative immune health metric (IHM). In ten independent datasets, the IHM discriminated healthy from polygenic autoimmune and inflammatory disease states, marked aging in clinically healthy individuals, tracked disease activities and treatment responses in both immunological and nonimmunological diseases, and predicted age-dependent antibody responses to immunizations with different vaccines. This discriminatory power goes beyond that of the classical inflammatory biomarkers C-reactive protein and interleukin-6. Thus, deviations from health in diverse conditions, including aging, have shared systemic immune consequences, and we provide a web platform for calculating the IHM for other datasets, which could empower precision medicine.

Human transcriptional signature of protection after Plasmodium falciparum immunization and infectious challenge via mosquito bites.

The identification of immune correlates of protection against infectious pathogens will accelerate the design and optimization of recombinant and subunit vaccines. Systematic analyses such as immunoprofiling including serological, cellular, and molecular assessments supported by computational tools are key to not only identify correlates of protection but also biomarkers of disease susceptibility. The current study expands our previous cellular and serological profiling of vaccine-induced responses to a whole parasite malaria vaccine. The irradiated sporozoite model was chosen as it is considered the most effective vaccine against malaria. In contrast to whole blood transcriptomics analysis, we stimulated peripheral blood mononuclear cells (PBMC) with sporozoites and enriched for antigen-specific cells prior to conducting transcriptomics analysis. By focusing on transcriptional events triggered by antigen-specific stimulation, we were able to uncover quantitative and qualitative differences between protected and non-protected individuals to controlled human malaria infections and identified differentially expressed genes associated with sporozoite-specific responses. Further analyses including pathway and gene set enrichment analysis revealed that vaccination with irradiated sporozoites induced a transcriptomic profile associated with Th1-responses, Interferon-signaling, antigen-presentation, and inflammation. Analyzing longitudinal time points not only post-vaccination but also post-controlled human malaria infection further revealed that the transcriptomic profile of protected vs non-protected individuals was not static but continued to diverge over time. The results lay the foundation for comparing protective immune signatures induced by various vaccine platforms to uncover immune correlates of protection that are common across platforms.

Multiscale integration of human and single-cell variations reveals unadjuvanted vaccine high responders are naturally adjuvanted.

Advances in multimodal single cell analysis can empower high-resolution dissection of human vaccination responses. The resulting data capture multiple layers of biological variations, including molecular and cellular states, vaccine formulations, inter- and intra-subject differences, and responses unfolding over time. Transforming such data into biological insight remains a major challenge. Here we present a systematic framework applied to multimodal single cell data obtained before and after influenza vaccination without adjuvants or pandemic H5N1 vaccination with the AS03 adjuvant. Our approach pinpoints responses shared across or unique to specific cell types and identifies adjuvant specific signatures, including pro-survival transcriptional states in B lymphocytes that emerged one day after vaccination. We also reveal that high antibody responders to the unadjuvanted vaccine have a distinct baseline involving a rewired network of cell type specific transcriptional states. Remarkably, the status of certain innate immune cells in this network in high responders of the unadjuvanted vaccine appear "naturally adjuvanted": they resemble phenotypes induced early in the same cells only by vaccination with AS03. Furthermore, these cell subsets have elevated frequency in the blood at baseline and increased cell-intrinsic phospho-signaling responses after LPS stimulation ex vivo in high compared to low responders. Our findings identify how variation in the status of multiple immune cell types at baseline may drive robust differences in innate and adaptive responses to vaccination and thus open new avenues for vaccine development and immune response engineering in humans.

Tracking B cell responses to the SARS-CoV-2 mRNA-1273 vaccine.

Protective immunity following vaccination is sustained by long-lived antibody-secreting cells and resting memory B cells (MBCs). Responses to two-dose SARS-CoV-2 mRNA-1273 vaccination are evaluated longitudinally by multimodal single-cell analysis in three infection-naïve individuals. Integrated surface protein, transcriptomics, and B cell receptor (BCR) repertoire analysis of sorted plasmablasts and spike+ (S-2P+) and S-2P- B cells reveal clonal expansion and accumulating mutations among S-2P+ cells. These cells are enriched in a cluster of immunoglobulin G-expressing MBCs and evolve along a bifurcated trajectory rooted in CXCR3+ MBCs. One branch leads to CD11c+ atypical MBCs while the other develops from CD71+ activated precursors to resting MBCs, the dominant population at month 6. Among 12 evolving S-2P+ clones, several are populated with plasmablasts at early timepoints as well as CD71+ activated and resting MBCs at later timepoints, and display intra- and/or inter-cohort BCR convergence. These relationships suggest a coordinated and predictable evolution of SARS-CoV-2 vaccine-generated MBCs.

Multiomics integration of 22 immune-mediated monogenic diseases reveals an emergent axis of human immune health.

Monogenic diseases are often studied in isolation due to their rarity. Here we utilize multiomics to assess 22 monogenic immune-mediated conditions with age- and sex-matched healthy controls. Despite clearly detectable disease-specific and "pan-disease" signatures, individuals possess stable personal immune states over time. Temporally stable differences among subjects tend to dominate over differences attributable to disease conditions or medication use. Unsupervised principal variation analysis of personal immune states and machine learning classification distinguishing between healthy controls and patients converge to a metric of immune health (IHM). The IHM discriminates healthy from multiple polygenic autoimmune and inflammatory disease states in independent cohorts, marks healthy aging, and is a pre-vaccination predictor of antibody responses to influenza vaccination in the elderly. We identified easy-to-measure circulating protein biomarker surrogates of the IHM that capture immune health variations beyond age. Our work provides a conceptual framework and biomarkers for defining and measuring human immune health.

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

Multimodal single-cell profiling methods that measure protein expression with oligo-conjugated antibodies hold promise for comprehensive dissection of cellular heterogeneity, yet the resulting protein counts have substantial technical noise that can mask biological variations. Here we integrate experiments and computational analyses to reveal two major noise sources and develop a method called "dsb" (denoised and scaled by background) to normalize and denoise droplet-based protein expression data. We discover that protein-specific noise originates from unbound antibodies encapsulated during droplet generation; this noise can thus be accurately estimated and corrected by utilizing protein levels in empty droplets. We also find that isotype control antibodies and the background protein population average in each cell exhibit significant correlations across single cells, we thus use their shared variance to correct for cell-to-cell technical noise in each cell. We validate these findings by analyzing the performance of dsb in eight independent datasets spanning multiple technologies, including CITE-seq, ASAP-seq, and TEA-seq. Compared to existing normalization methods, our approach improves downstream analyses by better unmasking biologically meaningful cell populations. Our method is available as an open-source R package that interfaces easily with existing single cell software platforms such as Seurat, Bioconductor, and Scanpy and can be accessed at "dsb [ https://cran.r-project.org/package=dsb ]".

Robust, persistent adaptive immune responses to SARS-CoV-2 in the oropharyngeal lymphoid tissue of children.

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.