Evidence of increased Cathepsin B/L and decreased TMPRSS2 usage for cell entry by the SARS-CoV-2 Omicron variant

The SARS-CoV-2 Omicron variant harbours mutations in its spike protein, which may affect its cell entry, tropism, and response to interventions. To elucidate these effects, we developed a mathematical model of SARS-CoV-2 entry into cells and applied it to analyse recent in vitro data. SARS-CoV-2 enters cells using host proteases, either Cathepsin B/L or TMPRSS2. We estimated >4-fold increase and >3-fold decrease in entry efficiency using Cathepsin B/L and TMPRSS2, respectively, of the Omicron variant relative to the original or other strains in a cell type-dependent manner. Our model predicted that Cathepsin B/L inhibitors would be more and TMPRSS2 inhibitors less efficacious against the Omicron than the original strain. Furthermore, the two inhibitor classes would exhibit synergy, although the drug concentrations maximizing synergy would have to be tailored to the Omicron variant. These findings provide insights into the cell entry mechanisms of the Omicron variant and have implications for interventions.

Low dose prime and delayed boost can improve COVID-19 vaccine efficacies by increasing B cell selection stringency in germinal centres

The efficacy of COVID-19 vaccines appears to depend in complex ways on the vaccine dosage and the interval between the prime and boost doses. Unexpectedly, lower dose prime and longer prime-boost intervals have yielded higher efficacies in clinical trials. To elucidate the origins of these effects, we developed a stochastic simulation model of the germinal centre (GC) reaction and predicted the antibody responses elicited by different vaccination protocols. The simulations predicted that a lower dose prime could increase the selection stringency in GCs due to reduced antigen availability, resulting in the selection of GC B cells with higher affinities for the target antigen. The boost could relax this selection stringency and allow the expansion of the higher affinity GC B cells selected, improving the overall response. With a longer dosing interval, the decay in the antigen with time following the prime could further increase the selection stringency, amplifying this effect. The effect remained in our simulations even when new GCs following the boost had to be seeded by memory B cells formed following the prime. These predictions offer a plausible explanation of the observed paradoxical effects of dosage and dosing interval on vaccine efficacy. Tuning the selection stringency in the GCs using prime-boost dosages and dosing intervals as handles may help improve vaccine efficacies.

Mechanistic Insights into the Effects of Key Mutations on SARS-CoV-2 RBD-ACE2 Binding

Some recent SARS-CoV-2 variants appear to have increased transmissibility than the original strain. An underlying mechanism could be the improved ability of the variants to bind receptors on target cells and infect them. In this study, we provide atomic-level insight into the binding of the receptor binding domain (RBD) of the wild-type SARS-CoV-2 spike protein and its single (N501Y), double (E484Q, L452R) and triple (N501Y, E484Q, L452R) mutated variants to the human ACE2 receptor. Using extensive all-atom molecular dynamics simulations and advanced free energy calculations, we estimate the associated binding affinities and binding hotspots. We observe significant secondary structural changes in the RBD of the mutants, which lead to different binding affinities. We find higher binding affinities of the double (E484Q, L452R) and triple (N501Y, E484Q, L452R) mutated variants than the wild type and the N501Y variant, which could contribute to the higher transmissibility of recent variants containing these mutations.

The relative strength and timing of innate immune and CD8 T-cell responses underlie the heterogeneous outcomes of SARS-CoV-2 infection

SARS-CoV-2 infection results in highly heterogeneous outcomes, from cure without symptoms to acute respiratory distress and death. While immunological correlates of disease severity have been identified, how they act together to determine the outcomes is unknown. Here, using a new mathematical model of within-host SARS-CoV-2 infection, we analyze diverse clinical datasets and predict that a subtle interplay between innate and CD8 T-cell responses underlies disease heterogeneity. Our model considers essential features of these immune arms and immunopathology from cytokines and effector cells. Model predictions provided excellent fits to patient data and, by varying the strength and timing of the immune arms, quantitatively recapitulated viral load changes in mild, moderate, and severe disease, and death. Additionally, they explained several confounding observations, including viral recrudescence after symptom loss, prolonged viral positivity before cure, and mortality despite declining viral loads. Together, a robust conceptual understanding of COVID-19 outcomes emerges, bearing implications for interventions. TeaserModeling explains how a subtle interplay between innate immune and CD8 T-cell responses determines the severity of COVID-19.

Modelling the population-level protection conferred by COVID-19 vaccination

Although severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines work predominantly by eliciting neutralizing antibodies (NAbs), how the protection they confer depends on the NAb response to vaccination is unclear. Here, we collated and analysed in vitro dose-response curves of >70 NAbs and constructed a landscape defining the spectrum of neutralization efficiencies of NAbs elicited. We mimicked responses of individuals by sampling NAb subsets of known sizes from the landscape and found that they recapitulated responses of convalescent patients. Combining individual responses with a mathematical model of within-host SARS-CoV-2 infection post-vaccination, we predicted how the population-level protection conferred would increase with the NAb response to vaccination. Our predictions captured the outcomes of vaccination trials. Our formalism may help optimize vaccination protocols, given limited vaccine availability. One sentence summaryViremic control by the spectrum of neutralizing antibodies elicited by vaccination determines COVID-19 vaccine efficacies.

The quantitative landscape of the neutralizing antibody response to SARS-CoV-2

Neutralizing antibodies (NAbs) appear promising interventions against SARS-CoV-2 infection. Over 100 NAbs have been identified so far and several are in clinical trials. Yet, which NAbs would be the most potent remains unclear. Here, we analysed reported in vitro dose-response curves (DRCs) of >70 NAbs and estimated corresponding 50% inhibitory concentrations, slope parameters, and instantaneous inhibitory potentials (IIPs), presenting a comprehensive quantitative landscape of NAb responses to SARS-CoV-2. NAbs with high IIPs are likely to be potent. To assess the applicability of the landscape in vivo, we analysed available DRCs of NAbs from individual patients and found that the responses closely resembled the landscape. Further, we created virtual patient plasma samples by randomly sampling NAbs from the landscape and found that they recapitulated plasma dilution assays from convalescent patients. The landscape thus offers a facile tool for benchmarking NAbs and would aid the development of NAb-based therapies for SARS-CoV-2 infection.