Deep mining of early antibody response in COVID-19 patients yields potent neutralisers and reveals high level of convergence.
Thursday March 18, 2021
9am PT/12pm ET
Speaker: Dr. John McCafferty, IONTAS
In this webinar, Dr. John McCafferty presents results from the deep-mining of the antibody repertoires of hospitalized COVID-19 patients using a combination of phage display technology and B cell receptor repertoire sequencing to isolate neutralizing antibodies and gain insights into the early antibody response. This comprehensive discovery approach yielded potent neutralizing antibodies with distinct mechanisms of action. In particular, a novel non-ACE2 receptor blocking antibody that is not expected to be affected by any of the major viral variants reported was identified. Potent neutralizing antibodies with near germline sequences within both the IgG and IgM pools at early stages of infection were also found. The study results highlight a highly convergent antibody response with the same sequences occurring both within this patient group and within the responses described in previously published anti-SARS-CoV-2 antibody studies.
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Steps in data processing and analysis of adaptive immune receptor repertoires: best practices, pitfalls, and future directions.
Tuesday April 6, 2021
8am PT/11pm ET/5pm CET
Speaker: Prof. Victor Greiff, University of Oslo
High-throughput sequencing has enabled the capture of adaptive immune receptor repertoire (AIRR) data at unprecedented depth and precision. This webinar will give an in-depth walk-through of best practices to conceive, analyze and perform AIRR studies for answering fundamental immunological questions as well as discovering novel immunodiagnostic biomarkers and design (therapeutic) immune receptors. Specifically, Dr. Greiff will address current approaches to perform AIRR-compliant AIRR data processing encompassing bulk and single-cell approaches and experimental and bioinformatics quality control. Furthermore, he will summarize the computational methods that have been recently developed to deconstruct the high-dimensional complexity of immune receptor repertoires, e.g., 1) diversity-, 2) phylogenetic-, 3) networks- and 4) machine learning-based methods that have been applied to dissect and understand the diversity, architecture, evolution and antigen specificity of immune repertoires. Finally, Dr. Greiff will discuss experimental and computational methods in light of their underlying assumptions, limitations and pitfalls and highlight promising avenues of future research in basic and applied AIRR systems immunology.
