Plant-expressed diagnostic proteins and their use for the identification and differentiation of infected and vaccinated animals with foot-and-mouth disease virus

Abstract

The Foot-and-mouth disease virus (FMDV) affects cloven-hoofed animals and is endemic in most parts of Africa, South America and southern Asia. South Africa is considered a FMDV-free zone but the virus is maintained within the wildlife in the Kruger National Park (KNP), making mitigation of outbreaks a high priority. Diagnostic methods are usually costly due to the high production cost of the reagents used, meaning that regular monitoring and diagnosis of animals around the KNP for FMDV is expensive due to the large amounts of serum continuously being tested. I propose an alternative plant expression platform for the local production of more cost effective diagnostic reagents capable of distinguishing between infected and vaccinated animals (DIVA). I selected the non-structural 3ABC polyprotein of FMDV to express, as it is a suitable candidate as a coating antigen in a competitive enzyme linked immunosorbent assay (C-ELISA) for the detection of neutralizing antibodies in livestock sera. I also chose other variations of the full polyprotein (3AB, 3AB1 and 3B) for expression as they have previously been shown to be effective in FMDV diagnosis. I also selected a second reagent to be expressed: this was the CRAb-FM27 single chain variable fragment (scFv), which binds a 3B epitope on the 3ABC polyprotein and has previously shown to be effective as a competing antibody in a C-ELISA. The 3B antigen and the scFv were successfully expressed and purified from N. benthamiana, which to my knowledge is the first time either has been shown. The plant produced scFv successfully bound the 3B antigen in an I-ELISA. Separately, the plant produced 3B antigen could be used to successfully differentiate FMDV infected and vaccinated guinea pig serum in an I-ELISA. However, testing of these reagents in tandem within a C-ELISA to DIVA sera was inconclusive, and further research is required to optimise C-ELISA conditions

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