Identifying when past exposure to an infectious disease will protect against newly emerging strains is central to understanding the spread and the severity of epidemics, but the prediction of viral cross-protection remains an important unsolved problem. For foot-and-mouth disease virus (FMDV) research in particular, improved methods for predicting this cross-protection are critical for predicting the severity of outbreaks within endemic settings where multiple serotypes and subtypes commonly co-circulate, as well as for deciding whether appropriate vaccine(s) exist and how much they could mitigate the effects of any outbreak. To identify antigenic relationships and their predictors, we used linear mixed effects models to account for variation in pairwise cross-neutralization titres using only viral sequences and structural data. We identified those substitutions in surface-exposed structural proteins that are correlates of loss of cross-reactivity. These allowed prediction of both the best vaccine match for any single virus and the breadth of coverage of new vaccine candidates from their capsid sequences as effectively as or better than serology. Sub-sequences chosen by the model-building process all contained sites that are known epitopes on other serotypes. Furthermore, for the SAT1 serotype, for which epitopes have never previously been identified, we provide strong evidence – by controlling for phylogenetic structure – for the presence of three epitopes across a panel of viruses and quantify the relative significance of some individual residues in determining cross-neutralization. Identifying and quantifying the importance of sites that predict viral strain cross-reactivity not just for single viruses but across entire serotypes can help in the design of vaccines with better targeting and broader coverage. These techniques can be generalized to any infectious agents where cross-reactivity assays have been carried out. As the parameterization uses pre-existing datasets, this approach quickly and cheaply increases both our understanding of antigenic relationships and our power to control disease.
Foot-and-mouth disease virus (FMDV) outer capsid proteins 1B, 1C and 1D contribute to the virus serotype distribution and antigenic variants that exist within each of the seven serotypes. This study presents phylogenetic, genetic and antigenic analyses of South African Territories (SAT) serotypes prevalent in sub-Saharan Africa. Here, we show that the high levels of genetic diversity in the P1-coding region within the SAT serotypes are reflected in the antigenic properties of these viruses and therefore have implications for the selection of vaccine strains that would provide the best vaccine match against emerging viruses. Interestingly, although SAT1 and SAT2 viruses displayed similar genetic variation within each serotype (32 % variable amino acids), antigenic disparity, as measured by r 1 -values, was less pronounced for SAT1 viruses compared with SAT2 viruses within our dataset, emphasizing the high antigenic variation within the SAT2 serotype. Furthermore, we combined amino acid variation and the r 1 -values with crystallographic structural data and were able to predict areas on the surface of the FMD virion as antigenically relevant. These sites were mostly consistent with antigenic sites previously determined for types A, O and C using mAbs and escape mutant studies. Our methodology offers a quick alternative to determine antigenic relevant sites for FMDV field strains.
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