Functional antibodies exhibit light chain coherence.

The vertebrate adaptive immune system modifies the genome of individual B cells to encode antibodies that bind particular antigens¹. In most mammals, antibodies are composed of heavy and light chains that are generated sequentially by recombination of V, D (for heavy chains), J and C gene segments. Each chain contains three complementarity-determining regions (CDR1-CDR3), which contribute to antigen specificity. Certain heavy and light chains are preferred for particular antigens^2-22. Here we consider pairs of B cells that share the same heavy chain V gene and CDRH3 amino acid sequence and were isolated from different donors, also known as public clonotypes^23,24. We show that for naive antibodies (those not yet adapted to antigens), the probability that they use the same light chain V gene is around 10%, whereas for memory (functional) antibodies, it is around 80%, even if only one cell per clonotype is used. This property of functional antibodies is a phenomenon that we call light chain coherence. We also observe this phenomenon when similar heavy chains recur within a donor. Thus, although naive antibodies seem to recur by chance, the recurrence of functional antibodies reveals surprising constraint and determinism in the processes of V(D)J recombination and immune selection. For most functional antibodies, the heavy chain determines the light chain.

Analysis of TCR Repertoire by High-Throughput Sequencing Indicates the Feature of T Cell Immune Response after SARS-CoV-2 Infection.

Coronavirus disease 2019 (COVID-19) is a global infectious disease caused by the SARS-CoV-2 coronavirus. T cells play an essential role in the body's fighting against the virus invasion, and the T cell receptor (TCR) is crucial in T cell-mediated virus recognition and clearance. However, little has been known about the features of T cell response in convalescent COVID-19 patients. In this study, using 5'RACE technology and PacBio sequencing, we analyzed the TCR repertoire of COVID-19 patients after recovery for 2 weeks and 6 months compared with the healthy donors. The TCR clustering and CDR3 annotation were exploited to discover groups of patient-specific TCR clonotypes with potential SARS-CoV-2 antigen specificities. We first identified CD4+ and CD8+ T cell clones with certain clonal expansion after infection, and then observed the preferential recombination usage of V(D) J gene segments in CD4+ and CD8+ T cells of COVID-19 patients with different convalescent stages. More important, the TRBV6-5-TRBD2-TRBJ2-7 combination with high frequency was shared between CD4+ T and CD8+ T cells of different COVID-19 patients. Finally, we found the dominant characteristic motifs of the CDR3 sequence between recovered COVID-19 and healthy control. Our study provides novel insights on TCR in COVID-19 with different convalescent phases, contributing to our understanding of the immune response induced by SARS-CoV-2.

TCR meta-clonotypes for biomarker discovery with tcrdist3 enabled identification of public, HLA-restricted clusters of SARS-CoV-2 TCRs.

T-cell receptors (TCRs) encode clinically valuable information that reflects prior antigen exposure and potential future response. However, despite advances in deep repertoire sequencing, enormous TCR diversity complicates the use of TCR clonotypes as clinical biomarkers. We propose a new framework that leverages experimentally inferred antigen-associated TCRs to form meta-clonotypes - groups of biochemically similar TCRs - that can be used to robustly quantify functionally similar TCRs in bulk repertoires across individuals. We apply the framework to TCR data from COVID-19 patients, generating 1831 public TCR meta-clonotypes from the SARS-CoV-2 antigen-associated TCRs that have strong evidence of restriction to patients with a specific human leukocyte antigen (HLA) genotype. Applied to independent cohorts, meta-clonotypes targeting these specific epitopes were more frequently detected in bulk repertoires compared to exact amino acid matches, and 59.7% (1093/1831) were more abundant among COVID-19 patients that expressed the putative restricting HLA allele (false discovery rate [FDR]<0.01), demonstrating the potential utility of meta-clonotypes as antigen-specific features for biomarker development. To enable further applications, we developed an open-source software package, tcrdist3, that implements this framework and facilitates flexible workflows for distance-based TCR repertoire analysis.

An Alternative Binding Mode of IGHV3-53 Antibodies to the SARS-CoV-2 Receptor Binding Domain.

IGHV3-53-encoded neutralizing antibodies are commonly elicited during SARS-CoV-2 infection and target the receptor-binding domain (RBD) of the spike (S) protein. Such IGHV3-53 antibodies generally have a short CDR H3 because of structural constraints in binding the RBD (mode A). However, a small subset of IGHV3-53 antibodies to the RBD contain a longer CDR H3. Crystal structures of two IGHV3-53 neutralizing antibodies here demonstrate that a longer CDR H3 can be accommodated in a different binding mode (mode B). These two classes of IGHV3-53 antibodies both target the ACE2 receptor binding site, but with very different angles of approach and molecular interactions. Overall, these findings emphasize the versatility of IGHV3-53 in this common antibody response to SARS-CoV-2, where conserved IGHV3-53 germline-encoded features can be combined with very different CDR H3 lengths and light chains for SARS-CoV-2 RBD recognition and virus neutralization.

GIANA allows computationally-efficient TCR clustering and multi-disease repertoire classification by isometric transformation.

Similarity in T-cell receptor (TCR) sequences implies shared antigen specificity between receptors, and could be used to discover novel therapeutic targets. However, existing methods that cluster T-cell receptor sequences by similarity are computationally inefficient, making them impractical to use on the ever-expanding datasets of the immune repertoire. Here, we developed GIANA (Geometric Isometry-based TCR AligNment Algorithm) a computationally efficient tool for this task that provides the same level of clustering specificity as TCRdist at 600 times its speed, and without sacrificing accuracy. GIANA also allows the rapid query of large reference cohorts within minutes. Using GIANA to cluster large-scale TCR datasets provides candidate disease-specific receptors, and provides a new solution to repertoire classification. Querying unseen TCR-seq samples against an existing reference differentiates samples from patients across various cohorts associated with cancer, infectious and autoimmune disease. Our results demonstrate how GIANA could be used as the basis for a TCR-based non-invasive multi-disease diagnostic platform.

Sequence signatures of two public antibody clonotypes that bind SARS-CoV-2 receptor binding domain.

Since the COVID-19 pandemic onset, the antibody response to SARS-CoV-2 has been extensively characterized. Antibodies to the receptor binding domain (RBD) on the spike protein are frequently encoded by IGHV3-53/3-66 with a short complementarity-determining region (CDR) H3. Germline-encoded sequence motifs in heavy chain CDRs H1 and H2 have a major function, but whether any common motifs are present in CDR H3, which is often critical for binding specificity, is not clear. Here, we identify two public clonotypes of IGHV3-53/3-66 RBD antibodies with a 9-residue CDR H3 that pair with different light chains. Distinct sequence motifs on CDR H3 are present in the two public clonotypes that seem to be related to differential light chain pairing. Additionally, we show that Y58F is a common somatic hypermutation that results in increased binding affinity of IGHV3-53/3-66 RBD antibodies with a short CDR H3. These results advance understanding of the antibody response to SARS-CoV-2.

TRB sequences targeting ORF1a/b are associated with disease severity in hospitalized COVID-19 patients.

The potential protective or pathogenic role of the adaptive immune response to SARS-CoV-2 infection has been vigorously debated. While COVID-19 patients consistently generate a T lymphocyte response to SARS-CoV-2 antigens, evidence of significant immune dysregulation in these patients continues to accumulate. In this study, next generation sequencing of the T cell receptor beta chain (TRB) repertoire was conducted in hospitalized COVID-19 patients to determine if immunogenetic differences of the TRB repertoire contribute to disease course severity. Clustering of highly similar TRB CDR3 amino acid sequences across COVID-19 patients yielded 781 shared TRB sequences. The TRB sequences were then filtered for known associations with common diseases such as EBV and CMV. The remaining sequences were cross-referenced to a publicly accessible dataset that mapped COVID-19 specific TCRs to the SARS-CoV-2 genome. We identified 158 SARS-CoV-2 specific TRB sequences belonging to 134 clusters in our COVID-19 patients. Next, we investigated 113 SARS-CoV-2 specific clusters binding only one peptide target in relation to disease course. Distinct skewing of SARS-CoV-2 specific TRB sequences toward the nonstructural proteins (NSPs) encoded within ORF1a/b of the SARS-CoV-2 genome was observed in clusters associated with critical disease course when compared to COVID-19 clusters associated with a severe disease course. These data imply that T-lymphocyte reactivity towards peptides from NSPs of SARS-CoV-2 may not constitute an effective adaptive immune response and thus may negatively affect disease severity.

HLA class I-associated expansion of TRBV11-2 T cells in multisystem inflammatory syndrome in children.

Multisystem inflammatory syndrome in children (MIS-C), a hyperinflammatory syndrome associated with SARS-CoV-2 infection, shares clinical features with toxic shock syndrome, which is triggered by bacterial superantigens. Superantigen specificity for different Vß chains results in Vß skewing, whereby T cells with specific Vß chains and diverse antigen specificity are overrepresented in the T cell receptor (TCR) repertoire. Here, we characterized the TCR repertoire of MIS-C patients and found a profound expansion of TCRß variable gene 11-2 (TRBV11-2), with up to 24% of clonal T cell space occupied by TRBV11-2 T cells, which correlated with MIS-C severity and serum cytokine levels. Analysis of TRBJ gene usage and complementarity-determining region 3 (CDR3) length distribution of MIS-C expanded TRBV11-2 clones revealed extensive junctional diversity. Patients with TRBV11-2 expansion shared HLA class I alleles A02, B35, and C04, indicating what we believe is a novel mechanism for CDR3-independent T cell expansion. In silico modeling indicated that polyacidic residues in the Vß chain encoded by TRBV11-2 (Vß21.3) strongly interact with the superantigen-like motif of SARS-CoV-2 spike glycoprotein, suggesting that unprocessed SARS-CoV-2 spike may directly mediate TRBV11-2 expansion. Overall, our data indicate that a CDR3-independent interaction between SARS-CoV-2 spike and TCR leads to T cell expansion and possibly activation, which may account for the clinical presentation of MIS-C.

Structural basis of a shared antibody response to SARS-CoV-2.

Molecular understanding of neutralizing antibody responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) could accelerate vaccine design and drug discovery. We analyzed 294 anti-SARS-CoV-2 antibodies and found that immunoglobulin G heavy-chain variable region 3-53 (IGHV3-53) is the most frequently used IGHV gene for targeting the receptor-binding domain (RBD) of the spike protein. Co-crystal structures of two IGHV3-53-neutralizing antibodies with RBD, with or without Fab CR3022, at 2.33- to 3.20-angstrom resolution revealed that the germline-encoded residues dominate recognition of the angiotensin I converting enzyme 2 (ACE2)-binding site. This binding mode limits the IGHV3-53 antibodies to short complementarity-determining region H3 loops but accommodates light-chain diversity. These IGHV3-53 antibodies show minimal affinity maturation and high potency, which is promising for vaccine design. Knowledge of these structural motifs and binding mode should facilitate the design of antigens that elicit this type of neutralizing response.