Rational strategies for enhancing mAb binding to SARS-CoV-2 variants through CDR diversification and antibody-escape prediction.

Since the emergence of SARS-CoV-2, dozens of variants of interest and half a dozen variants of concern (VOCs) have been documented by the World Health Organization. The emergence of these VOCs due to the continuous evolution of the virus is a major concern for COVID-19 therapeutic antibodies and vaccines because they are designed to target prototype/previous strains and lose effectiveness against new VOCs. Therefore, there is a need for time- and cost-effective strategies to estimate the immune escape and redirect therapeutic antibodies against newly emerging variants. Here, we computationally predicted the neutralization escape of the SARS-CoV-2 Delta and Omicron variants against the mutational space of RBD-mAbs interfaces. Leveraging knowledge of the existing RBD-mAb interfaces and mutational space, we fine-tuned and redirected CT-p59 (Regdanvimab) and Etesevimab against the escaped variants through complementarity-determining regions (CDRs) diversification. We identified antibodies against the Omicron lineage BA.1 and BA.2 and Delta variants with comparable or better binding affinities to that of prototype Spike. This suggests that CDRs diversification by hotspot grafting, given an existing insight into the Ag-Abs interface, is an exquisite strategy to redirect antibodies against preselected epitopes and combat the neutralization escape of emerging SARS-CoV-2 variants.

A potential antibody repertoire diversification mechanism through tyrosine sulfation for biotherapeutics engineering and production.

The diversity of three hypervariable loops in antibody heavy chain and light chain, termed the complementarity-determining regions (CDRs), defines antibody's binding affinity and specificity owing to the direct contact between the CDRs and antigens. These CDR regions typically contain tyrosine (Tyr) residues that are known to engage in both nonpolar and pi stacking interaction with antigens through their complementary aromatic ring side chains. Nearly two decades ago, sulfotyrosine residue (sTyr), a negatively charged Tyr formed by Golgi-localized membrane-bound tyrosylprotein sulfotransferases during protein trafficking, were also found in the CDR regions and shown to play an important role in modulating antibody-antigen interaction. This breakthrough finding demonstrated that antibody repertoire could be further diversified through post-translational modifications, in addition to the conventional genetic recombination. This review article summarizes the current advances in the understanding of the Tyr-sulfation modification mechanism and its application in potentiating protein-protein interaction for antibody engineering and production. Challenges and opportunities are also discussed.

Complementarity determining regions in SARS-CoV-2 hybrid immunity.

Pre-vaccination SARS-CoV-2 infection can boost protection elicited by COVID-19 vaccination and post-vaccination breakthrough SARS-CoV-2 infection can boost existing immunity conferred by COVID-19 vaccination. Such 'hybrid immunity' is effective against SARS-CoV-2 variants. In order to understand 'hybrid immunity' at the molecular level we studied the complementarity determining regions (CDR) of anti-RBD (receptor binding domain) antibodies isolated from individuals with 'hybrid immunity' as well as from 'naive' (not SARS-CoV-2 infected) vaccinated individuals. CDR analysis was done by liquid chromatography/mass spectrometry-mass spectrometry. Principal component analysis and partial least square differential analysis showed that COVID-19 vaccinated people share CDR profiles and that pre-vaccination SARS-CoV-2 infection or breakthrough infection further shape the CDR profile, with a CDR profile in hybrid immunity that clustered away from the CDR profile in vaccinated people without infection. Thus, our results show a CDR profile in hybrid immunity that is distinct from the vaccination-induced CDR profile.

General Trends of the Camelidae Antibody VHHs Domain Dynamics.

Conformational flexibility plays an essential role in antibodies' functional and structural stability. They facilitate and determine the strength of antigen-antibody interactions. Camelidae express an interesting subtype of single-chain antibody, named Heavy Chain only Antibody. They have only one N-terminal Variable domain (VHH) per chain, composed of Frameworks (FRs) and Complementarity Determining regions (CDRs) like their VH and VL counterparts in IgG. Even when expressed independently, VHH domains display excellent solubility and (thermo)stability, which helps them to retain their impressive interaction capabilities. Sequence and structural features of VHH domains contributing to these abilities have already been studied compared to classical antibodies. To have the broadest view and understand the changes in dynamics of these macromolecules, large-scale molecular dynamics simulations for a large number of non-redundant VHH structures have been performed for the first time. This analysis reveals the most prevalent movements in these domains. It reveals the four main classes of VHHs dynamics. Diverse local changes were observed in CDRs with various intensities. Similarly, different types of constraints were observed in CDRs, while FRs close to CDRs were sometimes primarily impacted. This study sheds light on the changes in flexibility in different regions of VHH that may impact their in silico design.

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.

Expanding and improving nanobody repertoires using a yeast display method: Targeting SARS-CoV-2.

COVID-19, caused by the coronavirus SARS-CoV-2, represents a serious worldwide health issue, with continually emerging new variants challenging current therapeutics. One promising alternate therapeutic avenue is represented by nanobodies, small single-chain antibodies derived from camelids with numerous advantageous properties and the potential to neutralize the virus. For identification and characterization of a broad spectrum of anti-SARS-CoV-2 Spike nanobodies, we further optimized a yeast display method, leveraging a previously published mass spectrometry-based method, using B-cell complementary DNA from the same immunized animals as a source of VHH sequences. Yeast display captured many of the sequences identified by the previous approach, as well as many additional sequences that proved to encode a large new repertoire of nanobodies with high affinities and neutralization activities against different SARS-CoV-2 variants. We evaluated DNA shuffling applied to the three complementarity-determining regions of antiviral nanobodies. The results suggested a surprising degree of modularity to complementarity-determining region function. Importantly, the yeast display approach applied to nanobody libraries from immunized animals allows parallel interrogation of a vast number of nanobodies. For example, we employed a modified yeast display to carry out massively parallel epitope binning. The current yeast display approach proved comparable in efficiency and specificity to the mass spectrometry-based approach, while requiring none of the infrastructure and expertise required for that approach, making these highly complementary approaches that together appear to comprehensively explore the paratope space. The larger repertoires produced maximize the likelihood of discovering broadly specific reagents and those that powerfully synergize in mixtures.

Optimizing Antibody Affinity and Developability Using a Framework-CDR Shuffling Approach-Application to an Anti-SARS-CoV-2 Antibody.

The computational methods used for engineering antibodies for clinical development have undergone a transformation from three-dimensional structure-guided approaches to artificial-intelligence- and machine-learning-based approaches that leverage the large sequence data space of hundreds of millions of antibodies generated by next-generation sequencing (NGS) studies. Building on the wealth of available sequence data, we implemented a computational shuffling approach to antibody components, using the complementarity-determining region (CDR) and the framework region (FWR) to optimize an antibody for improved affinity and developability. This approach uses a set of rules to suitably combine the CDRs and FWRs derived from naturally occurring antibody sequences to engineer an antibody with high affinity and specificity. To illustrate this approach, we selected a representative SARS-CoV-2-neutralizing antibody, H4, which was identified and isolated previously based on the predominant germlines that were employed in a human host to target the SARS-CoV-2-human ACE2 receptor interaction. Compared to screening vast CDR libraries for affinity enhancements, our approach identified fewer than 100 antibody framework-CDR combinations, from which we screened and selected an antibody (CB79) that showed a reduced dissociation rate and improved affinity against the SARS-CoV-2 spike protein (7-fold) when compared to H4. The improved affinity also translated into improved neutralization (>75-fold improvement) of SARS-CoV-2. Our rapid and robust approach for optimizing antibodies from parts without the need for tedious structure-guided CDR optimization will have broad utility for biotechnological applications.

Landscape of B Cell Receptor Repertoires in COVID-19 Patients Revealed Through CDR3 Sequencing of Immunoglobulin Heavy and Light Chains.

The outbreak and persistence of coronavirus disease 2019 (COVID-19) threaten human health. B cells play a vital role in fighting the infections caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Despite many studies on the immune responses in COVID-19 patients, it is still unclear how B cell receptor (BCR) constituents, including immunoglobulin heavy (IGHs) and light chains (IGLs), respond to SARS-CoV-2 in patients with varying symptoms. In this study, we conducted complementarity-determining region 3 (CDR3) sequencing of BCR IGHs and IGLs from the peripheral blood of COVID-19 patients and healthy donors. The results showed significantly reduced clonal diversity, more expanded clones, and longer CDR3 lengths of IGH and IGL in COVID-19 patients than those in healthy individuals. The IGLs had a much higher percentage of VJ skew usage (47.83% IGLV and 42.86% IGLJ were significantly regulated) than the IGHs (12.09% IGHV and 0% IGHJ) between the healthy individuals and patients, which indicated the importance of BCR light chains. Furthermore, we found a largely expanded IGLV3-25 gene cluster mostly pairing with IGLJ1 and ILGJ2 in COVID-19 patients and a newly identified upregulated IGLJ1 gene and IGLJ2+IGLV13-21 recombination, both of which are potential sources of SARS-CoV-2-targeting antibodies. Our findings on specific immune B-cell signatures associated with COVID-19 have clinical implications for vaccine and biomarker development for disease diagnosis.

Deep learning guided optimization of human antibody against SARS-CoV-2 variants with broad neutralization.

SignificanceSARS-CoV-2 continues to evolve through emerging variants, more frequently observed with higher transmissibility. Despite the wide application of vaccines and antibodies, the selection pressure on the Spike protein may lead to further evolution of variants that include mutations that can evade immune response. To catch up with the virus's evolution, we introduced a deep learning approach to redesign the complementarity-determining regions (CDRs) to target multiple virus variants and obtained an antibody that broadly neutralizes SARS-CoV-2 variants.

Convergent CDR3 homology amongst Spike-specific antibody responses in convalescent COVID-19 subjects receiving the BNT162b2 vaccine.

Convalescent coronavirus disease 2019 (COVID-19) subjects who receive BNT162b2 develop robust antibody responses against SARS-CoV-2. However, our understanding of the clonal B cell response pre- and post-vaccination in such individuals is limited. Here we characterized B cell phenotypes and the BCR repertoire after BNT162b2 immunization in two convalescent COVID-19 subjects. BNT162b2 stimulated many B cell clones that were under-represented during SARS-CoV-2 infection. In addition, the vaccine generated B cell clusters with >65% similarity in CDR3 VH and VL region consensus sequences both within and between subjects. This result suggests that the CDR3 region plays a dominant role adjacent to heavy and light chain V/J pairing in the recognition of the SARS-CoV-2 spike protein. Antigen-specific B cell populations with homology to published SARS-CoV-2 antibody sequences from the CoV-AbDab database were observed in both subjects. These results point towards the development of convergent antibody responses against the virus in different individuals.

Facile isolation of high-affinity nanobodies from synthetic libraries using CDR-swapping mutagenesis.

The generation of high-affinity nanobodies for diverse biomedical applications typically requires immunization or affinity maturation. Here, we report a simple protocol using complementarity-determining region (CDR)-swapping mutagenesis to isolate high-affinity nanobodies from common framework libraries. This approach involves shuffling the CDRs of low-affinity variants during the sorting of yeast-displayed libraries to directly isolate high-affinity nanobodies without the need for lead isolation and optimization. We expect this approach, which we demonstrate for SARS-CoV-2 neutralizing nanobodies, will simplify the generation of high-affinity nanobodies. For complete details on the use and execution of this profile, please refer to Zupancic et al. (2021).

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.

MG1141A as a Highly Potent Monoclonal Neutralizing Antibody Against SARS-CoV-2 Variants.

Since the coronavirus disease outbreak in 2019, several antibody therapeutics have been developed to treat severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. Antibody therapeutics are effective in neutralizing the virus and reducing hospitalization in patients with mild and moderate infections. These therapeutics target the spike protein of SARS-CoV-2; however, emerging mutations in this protein reduce their efficiency. In this study, we developed a universal SARS-CoV-2 neutralizing antibody. We generated a humanized monoclonal antibody, MG1141A, against the receptor-binding domain of the spike protein through traditional mouse immunization. We confirmed that MG1141A could effectively neutralize live viruses, with an EC50 of 92 pM, and that it exhibited effective Fc-mediated functions. Additionally, it retained its neutralizing activity against the alpha (UK), beta (South Africa), and gamma (Brazil) variants of SARS-CoV-2. Taken together, our study contributes to the development of a novel antibody therapeutic approach, which can effectively combat emerging SARS-CoV-2 mutations.

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.

Mechanistic principles of an ultra-long bovine CDR reveal strategies for antibody design.

Antibodies bind antigens via flexible loops called complementarity-determining regions (CDRs). These are usually 6-20 residues long. However, some bovine antibodies have ultra-long CDRs comprising more than 50 residues organized in a stalk and a disulfide-rich knob. The design features of this structural unit and its influence on antibody stability remained enigmatic. Here, we show that the stalk length is critical for the folding and stability of antibodies with an ultra-long CDR and that the disulfide bonds in the knob do not contribute to stability; they are important for organizing the antigen-binding knob structure. The bovine ultra-long CDR can be integrated into human antibody scaffolds. Furthermore, mini-domains from de novo design can be reformatted as ultra-long CDRs to create unique antibody-based proteins neutralizing SARS-CoV-2 and the Alpha variant of concern with high efficiency. Our findings reveal basic design principles of antibody structure and open new avenues for protein engineering.

Characterizing the BCR repertoire during lymphocyte reduction and recovery mediated by cyclophosphamide and granulocyte-macrophage colony-stimulating factor.

Leukopenia is a common manifestation of many diseases, including global outbreak SAS-CoV-2 infection. Granulocyte-macrophage colony-stimulating factor (GM -CSF) has been proved to be effective in promoting lymphocyte regeneration, but adverse immunological effects have also emerged. This study aim to investigate the effect of GM -CSF on BCR heavy chain CDR3 repertoire while promoting lymphocyte regeneration. Cyclophosphamide (CTX) and GM -CSF were used to inhibit and stimulate bone marrow hematopoiesis, respectively. High throughput sequencing was applied to detect the characteristics of BCR CDR3 repertoire in controls, CTX group and GM -CSF group. The white blood cells (WBCs) were quickly reduced (P < 0.05) with lymphocytes decreasing causing by CTX, and the WBCs and lymphocytes returned to the level of controls after GM -CSF treatment. The diversity of BCR heavy chain CDR3 repertoire was also significantly decreased in CTX group. Although there is still a big gap from the controls, the diversity was picked up after GM -CSF treatment. The expression of IGHD01-01, IGHD02-14 and IGHJ04-01 with high-frequency usage regularly and significantly changed in three groups, and many genes with low-frequency usage lost in CTX group and did not reappear in GM -CSF group. Moreover, two shared sequences and accounted for the highest proportion in GM -CSF group have been detected in animal model of chronic lymphocytic leukemia. These results revealed that GM -CSF can partially restore changes in the BCR heavy chain CDR3 repertoire while promoting lymphocyte regeneration, but it may also lead to rearrangement, proliferation and activation of abnormal B cells, which can provide a basis for further study on the adverse immunological effects and mechanism of GM -CSF treatment.

Genetic and structural basis for SARS-CoV-2 variant neutralization by a two-antibody cocktail.

Understanding the molecular basis for immune recognition of SARS-CoV-2 spike glycoprotein antigenic sites will inform the development of improved therapeutics. We determined the structures of two human monoclonal antibodies-AZD8895 and AZD1061-which form the basis of the investigational antibody cocktail AZD7442, in complex with the receptor-binding domain (RBD) of SARS-CoV-2 to define the genetic and structural basis of neutralization. AZD8895 forms an 'aromatic cage' at the heavy/light chain interface using germ line-encoded residues in complementarity-determining regions (CDRs) 2 and 3 of the heavy chain and CDRs 1 and 3 of the light chain. These structural features explain why highly similar antibodies (public clonotypes) have been isolated from multiple individuals. AZD1061 has an unusually long LCDR1; the HCDR3 makes interactions with the opposite face of the RBD from that of AZD8895. Using deep mutational scanning and neutralization escape selection experiments, we comprehensively mapped the crucial binding residues of both antibodies and identified positions of concern with regards to virus escape from antibody-mediated neutralization. Both AZD8895 and AZD1061 have strong neutralizing activity against SARS-CoV-2 and variants of concern with antigenic substitutions in the RBD. We conclude that germ line-encoded antibody features enable recognition of the SARS-CoV-2 spike RBD and demonstrate the utility of the cocktail AZD7442 in neutralizing emerging variant viruses.

Directed evolution of potent neutralizing nanobodies against SARS-CoV-2 using CDR-swapping mutagenesis.

There is widespread interest in facile methods for generating potent neutralizing antibodies, nanobodies, and other affinity proteins against SARS-CoV-2 and related viruses to address current and future pandemics. While isolating antibodies from animals and humans are proven approaches, these methods are limited to the affinities, specificities, and functional activities of antibodies generated by the immune system. Here we report a surprisingly simple directed evolution method for generating nanobodies with high affinities and neutralization activities against SARS-CoV-2. We demonstrate that complementarity-determining region swapping between low-affinity lead nanobodies, which we discovered unintentionally but find is simple to implement systematically, results in matured nanobodies with unusually large increases in affinity. Importantly, the matured nanobodies potently neutralize both SARS-CoV-2 pseudovirus and live virus, and possess drug-like biophysical properties. We expect that our methods will improve in vitro nanobody discovery and accelerate the generation of potent neutralizing nanobodies against diverse coronaviruses.

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.