Multiepitope array as the key for African Swine Fever diagnosis

Abstract

African Swine Fever (ASF) is an acute hemorrhagic fever affecting suids with high mortality and morbidity rate. The causal agent of ASF, the African Swine Fever Virus (ASFV), is an icosahedral virus of 200 nm diameter, composed of an outer envelope layer of host derivation and a linear 170-190 kb long dsDNA molecule. As of today, no efficient therapeutic intervention nor prophylactic measures exist to fight ASFV diffusion, underlining the importance of the early diagnosis and the need for efficient in-field screening of ASF. Recommended guidelines for the diagnosis of ASF are unpracticable in the desirable context of the rapid in-farm screening. In this view, the design of innovative diagnostics based on a panel of multiple ASFV epitopes would amend versatility and the analytical performances of the deliverable, ensuring high quality and accuracy standards worth of implementation in rapid in-field monitoring programs. Pursuing this view, we performed epitope prediction from the major AFSV structural proteins holding the potential to be targeted in innovative rapid diagnostic tests. Selected ASFV structural protein sequences were retrieved from data repositories and their tridimensional structure was computed. Linear and 3D protein structures were subjected to the prediction of the epitope sequences, that are likely to elicit antibody production, by independent bioinformatic tools, providing a list of candidate biomarkers whose batch employment held the potential suitability for the unbiased rapid in-field diagnosis and, in turn, might be implemented in screening programs, crowing the current monitoring and control campaigns that are currently running worldwide.

Keywords: African swine fever virus; Bioinformatics; Immunoinformatics; Multiepitope-based diagnosis.