Mapping the antigenic diversification of SARS-CoV-2

Large-scale vaccination campaigns have prevented countless SARS-CoV-2 infections, hospitalizations and deaths. However, the emergence of variants that escape from immunity challenges the effectiveness of current vaccines. Given this continuing evolution, an important question is when and how to update SARS-CoV-2 vaccines to antigenically match circulating variants, similar to seasonal influenza viruses where antigenic drift necessitates periodic vaccine updates. Here, we studied SARS-CoV-2 antigenic drift by assessing neutralizing activity against variants-of-concern (VOCs) of a unique set of sera from patients infected with a range of VOCs. Infections with ancestral or Alpha strains induced the broadest immunity, while individuals infected with other VOCs had more strain-specific responses. Omicron was substantially resistant to neutralization by sera elicited by all other variants. Antigenic cartography revealed that all VOCs preceding Omicron belong to one antigenic cluster, while Omicron forms a new antigenic cluster associated with immune escape and likely requiring vaccine updates to ensure vaccine effectiveness.

Full protection against all four SARS-CoV-2 variants of concern (VOC) in hamsters requires revision of spike antigen used for vaccination.

Current licensed COVID-19 vaccines are based on antigen sequences of initial SARS-CoV-2 isolates that emerged in 2019. By mid 2021 these historical virus strains have been completely replaced by new cosmopolitan SARS-CoV-2 lineages. The ongoing pandemic has been further driven by emerging variants of concern (VOC) Alpha, Beta, Gamma and, lately predominant, Delta. These are characterized by an increased transmissibility and possible escape from naturally acquired or vaccine-induced immunity. We here show, using a YF17D-vectored first-generation COVID-19 vaccine (Sanchez-Felipe et al., 2021) and a stringent hamster challenge model (Abdelnabi et al., 2021) that the immunity elicited by a prototypic spike antigen is insufficient to provide optimal protection against the Beta VoC, urging for an antigenic update. We therefore designed an updated second-generation vaccine candidate that carries the sequence of a spike antigen that includes crucial epitopes from multiple VOCs. This vaccine candidate yielded a marked change in target antigen spectrum covered as demonstrated by (i) antigenic cartography and (ii) full protection against infection and virus-induced disease caused by any of the four VOCs (Alpha, Beta, Gamma and Delta) used for challenge. This more universal COVID-19 vaccine candidate also efficiently blocked direct transmission of VOC Delta from vaccinated infected hamsters to non-vaccinated sentinels under prolonged co-housing conditions. In conclusion, our data suggest that current first-generation COVID-19 vaccines need to be adapted to cover emerging sequence diversity of VOC to preserve vaccine efficacy and to contain virus spread at the community level.

Serological Cross-Reactions between Expressed VP2 Proteins from Different Bluetongue Virus Serotypes

Bluetongue (BT) is a severe and economically important disease of ruminants that is widely distributed around the world, caused by the bluetongue virus (BTV). More than 28 different BTV serotypes have been identified in serum neutralisation tests (SNT), which, along with geographic variants (topotypes) within each serotype, reflect differences in BTV outer-capsid protein VP2. VP2 is the primary target for neutralising antibodies, although the basis for cross-reactions and serological variations between and within BTV serotypes is poorly understood. Recombinant BTV VP2 proteins (rVP2) were expressed in Nicotiana benthamiana, based on sequence data for isolates of thirteen BTV serotypes (primarily from Europe), including three ‘novel’ serotypes (BTV-25, -26 and -27) and alternative topotypes of four serotypes. Cross-reactions within and between these viruses were explored using rabbit anti-rVP2 sera and post BTV-infection sheep reference-antisera, in I-ELISA (with rVP2 target antigens) and SNT (with reference strains of BTV-1 to -24, -26 and -27). Strong reactions were generally detected with homologous rVP2 proteins or virus strains/serotypes. The sheep antisera were largely serotype-specific in SNT, but more cross-reactive by ELISA. Rabbit antisera were more cross-reactive in SNT, and showed widespread, high titre cross-reactions against homologous and heterologous rVP2 proteins in ELISA. Results were analysed and visualised by antigenic cartography, showing closer relationships in some, but not all cases, between VP2 topotypes within the same serotype, and between serotypes belonging to the same ‘VP2 nucleotype’.

Identification of novel human derived influenza viruses in pigs with zoonotic potential.

In 2009, a novel swine influenza A virus (IAV) emerged causing a global pandemic that highlighted the role of swine as a reservoir. To date, there is limited information about swine IAV circulating in Latin America. We identified two swine H1N2 and one divergent swine H3N2 viruses that co-circulated in Chilean swine together with the 2009 H1N1 pandemic strain (A(H1N1)pdm09). Phylogenetic analysis revealed several human-to-swine IAV introductions occurring as early as the mid-1980s, and since 2009, several introductions of the A(H1N1)pdm09 strain. Antigenic cartography confirmed that these viruses were antigenically unique and identified drifted variants within the clusters. Human sera from the Chilean general population showed an age-dependent mid to low-level antibody-mediated protection against swine H1N2 and A(H1N1)pdm09-like viruses and poor protection against the swine H3N2 virus, highlighting the zoonotic potential of this strain. Our results underscore the epidemiological importance of studying swine IAV in Latin America for epidemic and pandemic preparedness.

Development of an interactive online tool for genome sequence-based influenza vaccine strain selection

Seasonal influenza viruses in humans infect approximately 5 [percent] to 15 [percent] of the population and cause an estimated half-million deaths worldwide per year. Among the four co-circulating seasonal influenza viruses, subtype H3N2 and H1N1 influenza A viruses have rapid mutations and frequent antigenic drift events, leading to frequent updates of vaccine strains in the seasonal influenza vaccine. Seasonal influenza vaccination is the primary option to prevent and control influenza epidemics, and the selection of an antigenic matched vaccine strain is one of the keys to the success of seasonal influenza vaccination. Thus, it is critical to have robust and rapid antigenic analyses of epidemic strains and estimates of their genetic and antigenic relationship with the vaccine strain in use. In this study, we present vaccineEvol, an interactive and user-friendly web visualization tool that allows researchers to comprehend large sequence datasets into antigenic and genetic analyses. With the integration of the genomic sequences from the public database, the tool enables the users to track and analyze both genetic and antigenic evolutionary dynamics of seasonal influenza viruses. Primarily, our application can quantify both genetic and antigenic distances among seasonal H3N2 influenza A viruses and display genetic and antigenic variants using phylogenetic tree and antigenic cartography, respectively. The users can also interactively analyze genetic and antigenic variants between the phylogenetic tree and antigenic cartography. The application performs machine learning based computations in the backend, which was previously developed in our lab, and efficient construction of trees and maps in the frontend. In summary, in this study, an interactive web server was developed for rapid antigenic and genetic analyses of seasonal influenza viruses and thus facilitate seasonal influenza vaccine strain selection.

Antigenic cartography reveals complexities of genetic determinants that lead to antigenic differences among pandemic GII.4 noroviruses

Noroviruses are the predominant cause of acute gastroenteritis, with a single genotype (GII.4) responsible for the majority of infections. This prevalence is characterized by the periodic emergence of new variants that present substitutions at antigenic sites of the major structural protein (VP1), facilitating escape from herd immunity. Notably, the contribution of intravariant mutations to changes in antigenic properties is unknown. We performed a comprehensive antigenic analysis on a virus-like particle panel representing major chronological GII.4 variants to investigate diversification at the inter- and intravariant level. Immunoassays, neutralization data, and cartography analyses showed antigenic similarities between phylogenetically related variants, with major switches to antigenic properties observed over the evolution of GII.4 variants. Genetic analysis indicated that multiple coevolving amino acid changes—primarily at antigenic sites—are associated with the antigenic diversification of GII.4 variants. These data highlight complexities of the genetic determinants and provide a framework for the antigenic characterization of emerging GII.4 noroviruses.

Re-Invasion of H5N8 High Pathogenicity Avian Influenza Virus Clade 2.3.4.4b in Hokkaido, Japan, 2020

Global dispersion of high pathogenicity avian influenza (HPAI), especially that caused by H5 clade 2.3.4.4, has threatened poultry industries and, potentially, human health. An HPAI virus, A/northern pintail/Hokkaido/M13/2020 (H5N8) (NP/Hok/20) belonging to clade 2.3.4.4b, was isolated from a fecal sample collected at a lake in Hokkaido, Japan where migratory birds rested, October 2020. In the phylogenetic trees of all eight gene segments, NP/Hok/20 fell into in the cluster of European isolates in 2020, but was distinct from the isolates in eastern Asia and Europe during the winter season of 2017–2018. The antigenic cartography indicates that the antigenicity of NP/Hok/20 was almost the same as that of previous isolates of H5 clade 2.3.4.4b, whereas the antigenic distances from NP/Hok/20 to the representative strains in clade 2.3.4.4e and to a strain in 2.3.4 were apparently distant. These data imply that HPAI virus clade 2.3.4.4b should have been delivered by bird migration despite the intercontinental distance, although it was not defined whether NP/Hok/20 was transported from Europe via Siberia where migratory birds nest in the summer season. Given the probability of perpetuation of transmission in the northern territory, periodic updates of intensive surveys on avian influenza at the global level are essential to prepare for future outbreaks of the HPAI virus.

Convolutional Neural Network Based Approach to In Silico Non-Anticipating Prediction of Antigenic Distance for Influenza Virus

Evaluation of the antigenic similarity degree between the strains of the influenza virus is highly important for vaccine production. The conventional method used to measure such a degree is related to performing the immunological assays of hemagglutinin inhibition. Namely, the antigenic distance between two strains is calculated on the basis of HI assays. Usually, such distances are visualized by using some kind of antigenic cartography method. The known drawback of the HI assay is that it is rather time-consuming and expensive. In this paper, we propose a novel approach for antigenic distance approximation based on deep learning in the feature spaces induced by hemagglutinin protein sequences and Convolutional Neural Networks (CNNs). To apply a CNN to compare the protein sequences, we utilize the encoding based on the physical and chemical characteristics of amino acids. By varying (hyper)parameters of the CNN architecture design, we find the most robust network. Further, we provide insight into the relationship between approximated antigenic distance and antigenicity by evaluating the network on the HI assay database for the H1N1 subtype. The results indicate that the best-trained network gives a high-precision approximation for the ground-truth antigenic distances, and can be used as a good exploratory tool in practical tasks.