key: cord-0959101-tb8k979g
authors: Schultheiß, Christoph; Paschold, Lisa; Simnica, Donjete; Mohme, Malte; Willscher, Edith; von Wenserski, Lisa; Scholz, Rebekka; Wieters, Imke; Dahlke, Christine; Tolosa, Eva; Sedding, Daniel G.; Ciesek, Sandra; Addo, Marylyn; Binder, Mascha
title: Next Generation Sequencing of T and B cell receptor repertoires from COVID-19 patients showed signatures associated with severity of disease
date: 2020-06-30
journal: Immunity
DOI: 10.1016/j.immuni.2020.06.024
sha: 7cf5227987acfc03e547d7309a7aa0879ee520b9
doc_id: 959101
cord_uid: tb8k979g

Summary We profiled adaptive immunity in COVID-19 patients with active infection or after recovery and created a repository of currently >14 million B and T cell receptor (BCR, TCR) sequences from blood of these patients. The B cell response showed converging IGHV3-driven BCR clusters closely associated with SARS-CoV-2 antibodies. Clonality and skewing of TCR repertoires was associated with interferon type I and III responses, early CD4+ and CD8+ T cell activation and counterregulation by the coreceptors BTLA, Tim-3, PD-1, TIGIT and CD73. Tfh, Th17-like and nonconventional (but not classical anti-viral) Th1 cell polarizations were induced. SARS-CoV-2-specific T cell responses were driven by TCR clusters shared between patients with a characteristic trajectory of clonotypes and traceability over the disease course. Our data provide fundamental insight into adaptive immunity to SARS-CoV-2 with the actively updated repository providing a resource for the scientific community urgently needed to inform therapeutic concepts and vaccine development.

We are currently facing a pandemic of COVID-19 which is forcing us to live with the causative zoonotic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) at least development.

To close this gap, we performed a comprehensive immunological analysis to decode the 93 adaptive immune response directed against the virus using next-generation 94 immunosequencing flanked by antibody diagnostics, cytokine profiling and flow cytometry in 95 a cohort of hospitalized patients with active COVID-19 disease and a cohort that had 96 recovered from COVID-19 without medical intervention. The herein generated data 97 represents the basis for an actively updated repository (https://gateway-98 covid19.ireceptor.org/home; study: IR-Binder-000001) opened for public scientific use that be hospitalized and 12 out of 20 patients were critically ill with need for mechanical 117 ventilation or extracorporeal membrane oxygenation (ECMO). As reference, we used an age-Characteristics of patient cohorts 1 and 2 are shown in Table S1 and disease courses in Figure 1 . HLA typing results of the cohort are shown in Table S2 . lymphocyte counts were normal or even increased in the majority of patients (Figure 2A-2E ).

The CD4 + /CD8 + T cell ratio was shifted towards CD4 + T cells ( Figure 2F ) and regulatory T 7 We reasoned that the previously reported cytokine storm in COVID-19 may be responsible 148 for some of the blood count abnormalities of these patients (Mehta et al., 2020). Indeed, IL-6 149 and IL-10, both involved in class switch recombination but also in T cell exhaustion, were 150 significantly increased in plasma of patients with active COVID-19 in line with previous data 151 (Chen et al., 2020; Diao et al., 2020) , while the recovered patients showed normal 152 concentrations ( Figure 3A) . Also, surprisingly, plasma concentrations of BAFF were 153 exclusively increased in active COVID-19 patients and exhibited a very unusual positive 154 correlation with B cell counts, while APRIL was only elevated in plasma of recovered patients 155 ( Figure 3A and S1). The antiviral cytokine pattern was compatible with an interferon type I 156 and type III response, the latter persisting at increased levels during the recovery phase in 

Th17 and nonconventional Th1 cell responses in 164 Based on the impact of SARS-CoV-2 on T cell numbers, the CD4 + /CD8 + ratio as well as 165 secretory immune checkpoint molecules, we aimed to explore the functional state of T cells 166 in COVID-19 by multiparametric flow cytometry. For this analysis, we used subjects with 167 active disease at the date of sample collection with samples acquired between two weeks 168 and one month from symptom onset. We found six patients matching these selection criteria, 169 five from cohort 2 and one from cohort 1&2 with a median number of 23 days after symptom 170 onset. Unsupervised cluster analysis clearly revealed two differentially abundant clusters in 171 the T cell compartment of COVID-19 patients ( Figure 4A ). As annotation of the markers 172 indicates, both clusters contained cells expressing co-inhibitory receptors, namely BTLA (B-expression of co-inhibitory receptors in each lymphocyte subpopulation confirmed that BTLA was strongly upregulated on both CD4 + and CD8 + T cells compared to controls ( Figure 4B for the CD8 + subset, PD-1 upregulation was more pronounced on the CD4 + subset, together with a strong downregulation of the metabolically active ecto-5'-nucleotidase CD73, which is 181 also involved in the modulation of innate immune activation during viral immune response suggesting that SARS-CoV-2 substantially affects adaptive immunity, immune cell 201 architecture and function. We hypothesized that -by in-depth sequence analyzes of B and T 202 cell repertoires in our two informative cohorts -we may reveal the nature of protective versus detrimental B and T cell responses. This may be used as a prognostic biomarker in patients 204 and is critically needed to develop monoclonal antibodies to SARS-CoV-2, but also to 205 determine the optimal T cell engagement strategy for vaccine development. For this purpose,

we created a COVID-19 BCR and TCR sequence repository in response to the COVID-19 207 pandemic that is continuously fed with new annotated sequence data (details on data 208 deposition illustrated in Figure S4 ; https://gateway-covid19.ireceptor.org/home; study: IR-

Binder-000001). At the time of submission, the repository contains sequences from a total of 210 37 patients, including 69 time points and overall >6.2 million BCR and >8.3 million TCR 211 sequences which were retrieved from this repository for the analyzes presented here.

Sequencing details and depths of BCR and TCR repertoires are shown in Table S3 .

Convergence of B cell responses towards IGHV3 containing rearrangements without 214 significant somatic hypermutation in 215 Global IGH metrics showed slightly more diverse and richer repertoires in COVID-19 216 patients, an effect that was more pronounced in the recovered cases of cohort 1 ( Figure 5A ).

Overall, only very slight increases in IGH somatic hypermutation as proxy for germinal center 218 reactions were discernable in repertoires from COVID-19 patients as compared to healthy 219 donors ( Figure 5B ). We found noteworthy, that there was a rather broad range of somatic 220 hypermutation across individuals. To study a potential clinical significance associated with 221 this, we compared the rate of somatically mutated BCRs per patient in critically ill individuals 222 who had required mechanical ventilation or extracorporeal membrane oxygenation (ECMO) 223 with those of hospitalized individuals who did not require any ventilation support in the course 224 of their disease. This analysis showed that high somatic hypermutation (corresponding to a 225 low percentage of naïve B cells) was a pattern associated with a more severe clinical picture 226 ( Figure 5B) . Notably, BCRs with high somatic hypermutation did not display evidence for 227 clonal expansion as compared to BCRs without. Table S4 ). These 13 BCR repertoires were aligned with 5 BCR repertoires from individuals 242 who did not develop rVZV-EBOV specific antibodies at day 28 after vaccination. As negative 243 control, we used 13 and 6 randomly chosen BCR repertoires from healthy donors which were Table S5 . Notably, we also detected five distinct B cell clonotypes in 8 different patients Table S6. at recovery (day 27) enabled us to dissect T cell dynamics during viral clearance. We needed. This, on the one hand, will facilitate better prognostication in patients with risk 312 factors and improve monitoring of immunity to SARS-CoV-2 in recovered individuals. On the importantly -to determine the optimal T cell engagement strategies for vaccines.

In the work presented here, we provide a comprehensive immunological profile of two 317 cohorts of patients: Cohort 1 comprising individuals recovered after mild to moderate COVID- 

The most salient part of our study, however, is the examination of >14 million TCR and BCR 368 sequences from blood of COVID-19 patients and especially their clustering enabling us to contribution of specific receptor configurations to adaptive immunity in infection, 372 autoimmunity or cancer. Sophisticated bioinformatic pipelines may allow to reduce the 373 complexity of the large datasets resulting from such trials to effectively discover reactive 374 clusters of TCR as well as target specific BCR-antibody sequences.

Here, we aimed at clustering T cells relevant for immunity against SARS-CoV-2. We Table S1 506 and S2.

Overview of COVID-19 disease course, intervention and sample collection of patients 508 infected with SARS-Cov-2 in cohort 1 (recovered) and 2 (active). pt, patient. 

Further, presumably virus-specific TCR and BCR (or neutralizing antibody sequences) were 699 bioinformatically deduced by comparing immune repertoires of COVID-19 patients with 700 corresponding control groups (healthy donors and an Ebola vaccination cohort; Table S4 ). Days after first symptoms Mean trajectory of clonotypes

Ecto-5'-nucleotidase CD73 modulates the 743 innate immune response to influenza infection but is not required for development of 744 influenza-induced acute lung injury

The Signaling Role of CD40

Functional heterogeneity of 750 human memory CD4+ T cell clones primed by pathogens or vaccines

MiXCR: software for comprehensive adaptive immunity 753 profiling

IMGT/V-QUEST: the highly customized 755 and integrated system for IG and TR standardized V-J and V-D-J sequence analysis

Standardized next-generation sequencing 759 of immunoglobulin and T-cell receptor gene recombinations for MRD marker identification in 760 acute lymphoblastic leukaemia; a EuroClonality-NGS validation study

Clinical and immunological features of severe and moderate 764 coronavirus disease 2019

Reduction and Functional Exhaustion of T Cells in Patients With Coronavirus 767 Disease

Predicting the 769 spectrum of TCR repertoire sharing with a data-driven model of recombination

Inhibitory 772 Receptors Beyond T Cell Exhaustion

SPADEVizR: an R package for visualization, analysis and integration of SPADE 775 results

Narrowing of human influenza A 777 virus-specific T cell receptor alpha and beta repertoires with increasing age

23-35. in peripheral blood may predict severe progression in COVID-19 patients

Elevated exhaustion levels and reduced functional diversity of T cells 912 in peripheral blood may predict severe progression in COVID-19 patients

A pneumonia outbreak associated with a new coronavirus of 916 probable bat origin

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Anti-SARS-CoV-2-positive Anti-rVSV-ZEBOV-negative Anti-rVSV-ZEBOV-positive

We thank the following investigators and advisors for contributing