Zibo Chen, Jackie Yen Tan, Yi Wen, Shengniao Niu, Sek-Man Wong

Mixed virus infections in plants are common in nature and their interactions affecting host plants would depend mainly on plant species, virus strains, the order of infection and initial amount of inoculum. Hence, the prediction of outcome of virus competition in plants is not easy. In this study, we applied evolutionary game theory to model the interactions between Hibiscus latent Singapore virus (HLSV) and Tobacco mosaic virus (TMV) in Nicotiana benthamiana under co-infection in a plant host. The accumulation of viral RNA was quantified using qPCR at 1, 2 and 8 days post infection (dpi), and two different methods were employed to predict the dominating virus. TMV was predicted to dominate the game in the long run and this prediction was confirmed by both qRT-PCR at 8 dpi and the death of co-infected plants after 15 dpi. In addition, we validated our model by using data reported in the literature. Ten out of fourteen reported co-infection outcomes agreed with our predictions. Explanations were given for the four interactions that did not agree with our model. Hence, it serves as a valuable tool in making long term predictions using short term data obtained in virus co-infections.