Stereotypic antibody clonotypes exist in healthy individuals and may provide protective immunity against viral infections by neutralization. We observed that 13 out of 17 patients with COVID-19 had stereotypic variable heavy chain (V_H) antibody clonotypes directed against the receptor-binding domain (RBD) of SARS-CoV-2 spike protein. These antibody clonotypes were comprised of immunoglobulin heavy variable (IGHV)3-53 or IGHV3-66 and immunoglobulin heavy joining (IGHJ)6 genes. These clonotypes included IgM, IgG₃, IgG₁, IgA₁, IgG₂, and IgA₂ subtypes and had minimal somatic mutations, which suggested swift class switching after SARS-CoV-2 infection. The different immunoglobulin heavy variable chains were paired with diverse light chains resulting in binding to the RBD of SARS-CoV-2 spike protein. Human antibodies specific for the RBD can neutralize SARS-CoV-2 by inhibiting entry into host cells. We observed that one of these stereotypic neutralizing antibodies could inhibit viral replication in vitro using a clinical isolate of SARS-CoV-2. We also found that these V_H clonotypes existed in six out of 10 healthy individuals, with IgM isotypes predominating. These findings suggest that stereotypic clonotypes can develop de novo from naïve B cells and not from memory B cells established from prior exposure to similar viruses. The expeditious and stereotypic expansion of these clonotypes may have occurred in patients infected with SARS-CoV-2 because they were already present.

Neutralizing antibodies that recognize the SARS-CoV-2 spike glycoprotein are the principal host defense against viral invasion. Variants of SARS-CoV-2 bear mutations that allow escape from neutralization by many human antibodies, especially those in widely distributed (“public”) classes. Identifying antibodies that neutralize these variants of concern and determining their prevalence are important goals for understanding immune protection. To determine the Delta and Omicron BA.1 variant specificity of B cell repertoires established by an initial Wuhan strain infection, we measured neutralization potencies of 73 antibodies from an unbiased survey of the early memory B cell response. Antibodies recognizing each of three previously defined epitopic regions on the spike receptor binding domain (RBD) varied in neutralization potency and variant-escape resistance. The ACE2 binding surface (“RBD-2”) harbored the binding sites of neutralizing antibodies with the highest potency but with the greatest sensitivity to viral escape; two other epitopic regions on the RBD (“RBD-1” and “RBD-3”) bound antibodies of more modest potency but greater breadth. The structures of several Fab:spike complexes that neutralized all five variants of concern tested, including one Fab each from the RBD-1, -2, and -3 clusters, illustrated the determinants of broad neutralization and showed that B cell repertoires can have specificities that avoid immune escape driven by public antibodies. The structure of the RBD-2 binding, broad neutralizer shows why it retains neutralizing activity for Omicron BA.1, unlike most others in the same public class. Our results correlate with real-world data on vaccine efficacy, which indicate mitigation of disease caused by Omicron BA.1.

In antibody discovery, in-depth analysis of an antibody library and high-throughput retrieval of clones in the library are crucial to identifying and exploiting rare clones with different properties. However, existing methods have technical limitations, such as low process throughput from the laborious cloning process and waste of the phenotypic screening capacity from unnecessary repetitive tests on the dominant clones. To overcome the limitations, we developed a new high-throughput platform for the identification and retrieval of clones in the library, TrueRepertoire™. This new platform provides highly accurate sequences of the clones with linkage information between heavy and light chains of the antibody fragment. Additionally, the physical DNA of clones can be retrieved in high throughput based on the sequence information. We validated the high accuracy of the sequences and demonstrated that there is no platform-specific bias. Moreover, the applicability of TrueRepertoire™ was demonstrated by a phage-displayed single-chain variable fragment library targeting human hepatocyte growth factor protein.

C-Met is a promising target in cancer therapy for its intrinsic oncogenic properties. However, there are currently no c-Met-specific inhibitors available in the clinic. Antibodies blocking the interaction with its only known ligand, hepatocyte growth factor, and/or inducing receptor internalization have been clinically tested. To explore other therapeutic antibody mechanisms like Fc-mediated effector function, bispecific T cell engagement, and chimeric antigen T cell receptors, a diverse panel of antibodies is essential. We prepared a chicken immune scFv library, performed four rounds of bio-panning, obtained 641 clones using a high-throughput clonal retrieval system (TrueRepertoire^TM, TR), and found 149 antigen-reactive scFv clones. We also prepared phagemid DNA before the start of bio-panning (round 0) and, after each round of bio-panning (round 1–4), performed next-generation sequencing of these five sets of phagemid DNA, and identified 860,207 HCDR3 clonotypes and 443,292 LCDR3 clonotypes along with their clonal abundance data. We then established a TR data set consisting of antigen reactivity for scFv clones found in TR analysis and the clonal abundance of their HCDR3 and LCDR3 clonotypes in five sets of phagemid DNA. Using the TR data set, a random forest machine learning algorithm was trained to predict the binding properties of in silico HCDR3 and LCDR3 clonotypes. Subsequently, we synthesized 40 HCDR3 and 40 LCDR3 clonotypes predicted to be antigen reactive (AR) and constructed a phage-displayed scFv library called the AR library. In parallel, we also prepared an antigen non-reactive (NR) library using 10 HCDR3 and 10 LCDR3 clonotypes predicted to be NR. After a single round of bio-panning, we screened 96 randomly-selected phage clones from the AR library and found out 14 AR scFv clones consisting of 5 HCDR3 and 11 LCDR3 AR clonotypes. We also screened 96 randomly-selected phage clones from the NR library, but did not identify any AR clones. In summary, machine learning algorithms can provide a method for identifying AR antibodies, which allows for the characterization of diverse antibody libraries inaccessible by traditional methods.

The immune escape of Omicron variants significantly subsides by the third dose of an mRNA vaccine. However, it is unclear how Omicron variant-neutralizing antibodies develop under repeated vaccination. We analyze blood samples from 41 BNT162b2 vaccinees following the course of three injections and analyze their B-cell receptor (BCR) repertoires at six time points in total. The concomitant reactivity to both ancestral and Omicron receptor-binding domain (RBD) is achieved by a limited number of BCR clonotypes depending on the accumulation of somatic hypermutation (SHM) after the third dose. Our findings suggest that SHM accumulation in the BCR space to broaden its specificity for unseen antigens is a counterprotective mechanism against virus variant immune escape.

Lee A, et al. Immune Netw. 2021 Oct;21(5):e34. https://doi.org/10.4110/in.2021.21.e34