Quantification of SARS-CoV-2 neutralizing antibody by wild-type plaque reduction neutralization, microneutralization and pseudotyped virus neutralization assays.

Virus neutralization assays measure neutralizing antibodies in serum and plasma, and the plaque reduction neutralization test (PRNT) is considered the gold standard for measuring levels of these antibodies for many viral diseases. We have developed procedures for the standard PRNT, microneutralization assay (MNA) and pseudotyped virus neutralization assay (PNA) for severe acute respiratory syndrome coronavirus 2. The MNA offers advantages over the PRNT by reducing assay time, allowing increased throughput and reducing operator workload while remaining dependent upon the use of wild-type virus. This ensures that all severe acute respiratory syndrome coronavirus 2 antigens are present, but Biosafety Level 3 facilities are required. In addition to the advantages of MNA, PNA can be performed with lower biocontainment (Biosafety Level 2 facilities) and allows for further increases in throughput. For each new vaccine, it is critical to ensure good correlation of the neutralizing activity measured using PNA against the PRNT or MNA. These assays have been used in the development and licensure of the ChAdOx1 nCoV-19 (AstraZeneca; Oxford University) and Ad26.COV2.S (Janssen) coronavirus disease 2019 vaccines and are critical for demonstrating bioequivalence of future vaccines.

Severity of heterosubtypic influenza virus infection in ferrets is reduced by live attenuated influenza vaccine.

Live attenuated influenza vaccine (LAIV) is widely used to protect humans from seasonal influenza infection, particularly in children. In contrast to inactivated vaccines, the LAIV can induce both mucosal and cellular immune responses. Here we show that a single dose of monovalent H1N1pdm09-specific LAIV in the ferret model is fully protective against a subsequent wild-type H1N1pdm09 challenge, and furthermore reduces the severity of disease following challenge with a different influenza A subtype (H3N2). The reduced severity comprised reductions in weight loss and fever, as well as more rapid clearance of virus, compared to non-vaccinated H3N2-challenged ferrets. No H3N2-neutralizing antibodies were detected in vaccinated ferret sera. Rather, heterosubtypic protection correlated with interferon-gamma+ (IFN-γ+) T-cell responses measured in peripheral blood and in lung lymphocytes. The IFN-γ+ cells were cross-reactive to H3N2 virus even when obtained from vaccinated animals that had never been exposed to H3N2 virus. We believe this study provides compelling evidence that the LAIV can provide a significant reduction in infection and symptoms when challenged with heterosubtypic influenza strains not included in the LAIV, highlighting the importance of cross-reactive T-cells in the design of a universal influenza vaccine.

A rigid body framework for multicellular modeling.

Off-lattice models are a well-established approach in multicellular modeling, where cells are represented as points that are free to move in space. The representation of cells as point objects is useful in a wide range of settings, particularly when large populations are involved; however, a purely point-based representation is not naturally equipped to deal with objects that have length, such as cell boundaries or external membranes. Here we introduce an off-lattice modeling framework that exploits rigid body mechanics to represent objects using a collection of conjoined one-dimensional edges in a viscosity-dominated system. This framework can be used to represent cells as free moving polygons, to allow epithelial layers to smoothly interact with themselves, to model rod-shaped cells such as bacteria and to robustly represent membranes. We demonstrate that this approach offers solutions to the problems that limit the scope of current off-lattice multicellular models.

Heterosubtypic cross-protection correlates with cross-reactive interferon-gamma-secreting lymphocytes in the ferret model of influenza.

An effective universal vaccine for influenza will likely need to induce virus-specific T-cells, which are the major mediator of heterosubtypic cross-protection between different subtypes of influenza A virus. In this study we characterise the cell-mediated immune response in ferrets during heterosubtypic protection induced by low-dose H1N1 virus infection against an H3N2 virus challenge, given 4 weeks later. Although the ferrets were not protected against the infection by H3N2 virus, the duration of virus shedding was shortened, and clinical disease was markedly reduced. No cross-reactive neutralizing antibodies were detected, but cross-reactive interferon-gamma-secreting T cells were detected in the circulation prior to H3N2 challenge. These T-cells peaked at 11 days post-H1N1 infection, and were strongly induced in blood and in lung following H3N2 infection. The rapid induction of interferon-gamma-secreting cells in ferrets previously infected with H1N1 virus, but not in naïve ferrets, suggests induction of memory T-cells. These results are in accord with the observations that pre-existing cross-reactive T-cells correlate with protection in humans and have implications for outbreak modelling and universal vaccine design.

On the statistical analysis of the GS-NS0 cell proteome: imputation, clustering and variability testing.

We have undertaken two-dimensional gel electrophoresis proteomic profiling on a series of cell lines with different recombinant antibody production rates. Due to the nature of gel-based experiments not all protein spots are detected across all samples in an experiment, and hence datasets are invariably incomplete. New approaches are therefore required for the analysis of such graduated datasets. We approached this problem in two ways. Firstly, we applied a missing value imputation technique to calculate missing data points. Secondly, we combined a singular value decomposition based hierarchical clustering with the expression variability test to identify protein spots whose expression correlates with increased antibody production. The results have shown that while imputation of missing data was a useful method to improve the statistical analysis of such data sets, this was of limited use in differentiating between the samples investigated, and highlighted a small number of candidate proteins for further investigation.