Systematic survey of human SARS-CoV-2 monoclonal antibodies
Scientists have been studying the immune reaction to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and immunization since the start of the coronavirus disease 2019 (COVID-19) pandemic. Understanding public reactions to specific antigens is crucial for determining the molecular characteristics of recurring antibodies within the broad antibody repertoire. It is also critical for the development of effective pandemic vaccinations.
In a new study, published on the bioRxiv* preprint server, scientists have mined information from several research publications and patents to create a dataset of approximately 8000 human antibodies to the SARS-CoV-2 spike from more than 200 donors.
Scientists have extracted material from multiple academic publications and patents to construct a dataset of over 8000 human antibodies to the SARS-CoV-2 spike from more than 200 donors, according to a new study published on the bioRxiv preprint server.
The most important findings
As previously stated, scientists gathered 8048 antibodies from 215 donors, for a total of 8048 antibodies. It was discovered that 99.4 percent of the human antibodies interacted with SARS-CoV-2, with the remaining antibodies reacting with SARS-CoV or seasonal coronaviruses. The data was obtained from 88 scientific publications and 13 patents that described antibodies to SARS-CoV-2.
In a study of 7997 antibodies against SARS-CoV-2, 7923 antibodies bound to the spike (S) protein, 49 antibodies bound to the nucleocapsid (N) protein, and 25 antibodies bound to the ORF8 protein. Furthermore, epitope information was available for the majority of the SARS-CoV-2 S antibodies tested in this study. Researchers also gathered information on other characteristics (where available), such as germline gene utilization, sequence, structure, bait for isolation, and so on, to supplement their findings.
Scientists were able to examine patterns of germline gene utilization in antibodies that targeted distinct domains on the S protein, such as the RBD, NTD, and S2, thanks to the large amount of data. It was discovered that the nature of the public antibody response differed among domains. The current study successfully demonstrated the diversity of sequence properties that might be used to generate a public antibody response to a single antigen in a controlled setting.
Scientists have pointed out that a public antibody response may not always entail a specific set of IGHV/IGK(L)V genes, as previously thought. This is especially evident when either the IGHV or the IGK(L)V genes express residues that only contribute minimally to the paratope’s composition. The highly conserved stem region of influenza hemagglutinin has a paratope that is totally assigned to the IGHV1-69 heavy chain, indicating that the heavy chain is the IGHV1-69.
An in-depth structural investigation may be required for confirmation, but the IGHV3-30/IGHD1-26 antibodies to S2 detected in the current study could indicate an equivalent IGK(L)V-independent public antibody response to the same antigen. The forms of antibody responses to SARS-CoV-2 S protein that the general public has are numerous. In this case, it is possible that utilizing the customary rigorous definition of public clonotype to examine public antibody reactions will not be sufficient.
According to research, the antibody response of the general public to distinct antigens can differ significantly in terms of sequence characteristics. For example, IGHV6-1 and IGHD3-9 are markers of the general public’s antibody response to the Influenza virus, whereas IGHV3-23 is frequently used to detect antibodies to the Dengue and Zika viruses, among other viruses. These germline genes, on the other hand, are only seldom utilized in the antibody response to SARS-CoV-2.
The amino acid sequence of an antibody determines the structure of the antibody, which in turn impacts the binding capacity of the antibody. As a result, the sequence of an antibody can theoretically be used to determine the antigen specificity of the antibody. It is demonstrated in the current study that a deep learning model can be trained to distinguish between SARS-CoV-2 S antibodies and influenza HA antibodies, with the primary sequence information serving as the basis for the distinction.
Technological innovations and next steps
As a result of technical developments, the pace at which antibodies are discovered and characterized has been greatly expedited. As a result of the development of a single-cell high-throughput screen employing the Berkeley Lights Beacon optofluidics device and advancements in paired B-cell receptor sequencing, this has been a significant step forward. When large volumes of sequence information on antibodies to different antigens are accumulated, the researchers believe that they will be able to create a generic sequence-based model that will reliably predict the antigen specificity of any antibody.
Conclusions
SARS-CoV-2 antibodies have yielded a wealth of new and helpful insights as a result of the large amount of publicly available material. In the case of other infections, however, such information has not been easily available. One of the reasons for the widespread availability of SARS-CoV-2 antibodies is because the epidemic has been so severe that it has prompted scientists from a wide range of disciplines and from all over the world to focus their efforts on SARS-CoV-2. Our collective knowledge has advanced at an unparalleled rate and scope as a result of this collaborative effort by many distinct research groups working in tandem.
As more antibodies are identified and defined, scientists anticipate that their understanding of the molecular characteristics of the antibody response to SARS-CoV-2 will improve. This will aid in the addressing of some of the fundamental concerns about antigenicity and immunogenicity that have been posed over time. Also gained insight into how the human immune repertoire has developed to respond to certain viral infections that have coexisted with humans for several hundred years will be possible as a result of this research.
NOTE:
bioRxiv provides preliminary scientific papers that have not been peer-reviewed and should not be regarded as definitive, should not be used to influence clinical practice or health-related behavior, and should not be treated as authoritative information.
