Characterization of SARS-CoV-2 humoral immune response in a subject with unique sampling: A case report.

BACKGROUND: The development of vaccine candidates for COVID-19, and the administration of booster vaccines, has meant a significant reduction in COVID-19 related deaths world-wide and the easing of global restrictions. However, new variants of SARS-CoV-2 have emerged with less susceptibility to vaccine induced immunity leading to breakthrough infections among vaccinated people. It is generally acknowledged that immunoglobulins play the major role in immune-protection, primarily through binding to the SARS-COV-2 receptor binding domain (RBD) and thereby inhibiting viral binding to the ACE2 receptor. However, there are limited investigations of anti-RBD isotypes (IgM, IgG, IgA) and IgG subclasses (IgG1-4) over the course of vaccination and breakthrough infection. METHOD: In this study, SARS-CoV-2 humoral immunity is examined in a single subject with unique longitudinal sampling. Over a two year period, the subject received three doses of vaccine, had two active breakthrough infections and 22 blood samples collected. Serological testing included anti-nucleocapsid total antibodies, anti-RBD total antibodies, IgG, IgA, IgM and IgG subclasses, neutralization and ACE2 inhibition against the wildtype (WT), Delta and Omicron variants. RESULTS: Vaccination and breakthrough infections induced IgG, specifically IgG1 and IgG4 as well as IgM and IgA. IgG1 and IgG4 responses were cross reactive and associated with broad inhibition. CONCLUSION: The findings here provide novel insights into humoral immune response characteristics associated with SARS-CoV-2 breakthrough infections.

Automated optimisation of solubility and conformational stability of antibodies and proteins.

Biologics, such as antibodies and enzymes, are crucial in research, biotechnology, diagnostics, and therapeutics. Often, biologics with suitable functionality are discovered, but their development is impeded by developability issues. Stability and solubility are key biophysical traits underpinning developability potential, as they determine aggregation, correlate with production yield and poly-specificity, and are essential to access parenteral and oral delivery. While advances for the optimisation of individual traits have been made, the co-optimization of multiple traits remains highly problematic and time-consuming, as mutations that improve one property often negatively impact others. In this work, we introduce a fully automated computational strategy for the simultaneous optimisation of conformational stability and solubility, which we experimentally validate on six antibodies, including two approved therapeutics. Our results on 42 designs demonstrate that the computational procedure is highly effective at improving developability potential, while not affecting antigen-binding. We make the method available as a webserver at www-cohsoftware.ch.cam.ac.uk.