ABSTRACT
Establishing the host range for novel viruses remains a challenge. Here, we address the challenge of identifying non-human animal coronaviruses that may infect humans by creating an artificial neural network model that learns from the binding of the spike protein of alpha and beta coronaviruses to their host receptor. The proposed method produces a human-Binding Potential (h-BiP) score that distinguishes, with high accuracy, the binding potential among human coronaviruses. Two viruses, previously unknown to bind human receptors, were identified: Bat coronavirus BtCoV/133/2005 (a MERS related virus) and Rhinolophus affinis coronavirus isolate LYRa3 a SARS related virus. We further analyze the binding properties of these viruses using molecular dynamics. To test whether this model can be used for surveillance of novel coronaviruses, we re-trained the model on a set that excludes SARS-COV-2 viral sequences. The results predict the binding of SARS-CoV-2 with a human receptor, indicating that machine learning methods are an excellent tool for the prediction of host expansion events.
Subject(s)
InfectionsABSTRACT
COVID-19 vaccines are playing a vital role in controlling the COVID-19 pandemic. As SARS-CoV-2 variants encoding mutations in the surface glycoprotein, Spike, continue to emerge, there is increased need to identify immunogens and vaccination regimens that provide the broadest and most durable immune responses. We compared the magnitude and breadth of the neutralizing antibody response, as well as levels of Spike-reactive memory B cells, in individuals receiving a second dose of BNT126b2 at a short (3-4 week) or extended interval (8-12 weeks) and following a third vaccination approximately 6-8 months later. We show that whilst an extended interval between the first two vaccinations can greatly increase the breadth of the immune response and generate a higher proportion of Spike reactive memory B cells, a third vaccination leads to similar levels between the two groups. Furthermore, we show that the third vaccine dose enhances neutralization activity against omicron lineage members BA.1, BA.2 and BA.4/BA.5 and this is further increased following breakthrough infection during the UK omicron wave. These findings are relevant for vaccination strategies in populations where COVID-19 vaccine coverage remains low.
Subject(s)
Breakthrough Pain , COVID-19ABSTRACT
As SARS-CoV-2 variants continue to emerge globally, a major challenge for COVID-19 vaccination is the generation of a durable antibody response with cross-neutralizing activity against both current and newly emerging viral variants. Cross-neutralizing activity against major variants of concern (B.1.1.7, P.1 and B.1.351) has been observed following vaccination, albeit at a reduced potency, but whether vaccines based on the Spike glycoprotein of these viral variants will produce a superior cross-neutralizing antibody response has not been fully investigated. Here, we used sera from individuals infected in wave 1 in the UK to study the long-term cross-neutralization up to 10 months post onset of symptoms (POS), as well as sera from individuals infected with the B.1.1.7 variant to compare cross-neutralizing activity profiles. We show that neutralizing antibodies with cross-neutralizing activity can be detected from wave 1 up to 10 months POS. Although neutralization of B.1.1.7 and B.1.351 is lower, the difference in neutralization potency decreases at later timepoints suggesting continued antibody maturation and improved tolerance to Spike mutations. Interestingly, we found that B.1.1.7 infection also generates a cross-neutralizing antibody response, which, although still less potent against B.1.351, can neutralize parental wave 1 virus to a similar degree as B.1.1.7. These findings have implications for the optimization of vaccines that protect against newly emerging viral variants.