Symptom observation underestimates co-infections: insight from viral and bacterial diseases in rice fields in Burkina Faso
Symptom observation underestimates co-infections: insight from viral and bacterial diseases in rice fields in Burkina Faso
Billard, E.; Bangratz, M.; Kassankogno, A. I.; Saengram, P.; Guigma, A. K.; Cotto, O.; Thebaud, G.; Wonni, I.; Sereme, D.; Poulicard, N.; Cunnac, S.; Hutin, M.; Hebrard, E.; Tollenaere, C.
AbstractCo-occurrence of multiple diseases and co-infection of individual plants by various pathogens have potential epidemiological and evolutionary implications. Based on previous information on the co-occurrence of the rice yellow mottle disease (caused by the rice yellow mottle virus, RYMV) and bacterial leaf streak (BLS, due to Xanthomonas oryzae pv. oryzicola, Xoc) in Burkina Faso, and experimental evidence of interactions between the pathogens causing these two diseases, we aimed to monitor the two pathogens more intensively in farmers rice fields. To this purpose, we selected fields showing both types of symptoms to maximize the chance of observing co-infections at the plant scale. We performed observations and sampling in two sites over two consecutive years. Over a global dataset of 1666 samples, 1341 were symptomatic. Although the sampling design aimed to observe co-infections, only 37 of these samples (2.8%) were annotated as presenting both yellow mottle and BLS symptoms. The samples were then subjected to a newly designed molecular detection test that specifically amplifies both the virus (RYMV) and the bacteria (Xo). This revealed that 166 samples, i.e. 12.4% of symptomatic samples, were co-infected by RYMV and Xo, hence showing that symptom observation in the field greatly underestimates co-infection levels. Combining these data with a previously published dataset, we estimated that up to 1-4% of all plants in disease hotspots are simultaneously infected by the two pathogens. Further research on multiple infections would benefit from longitudinal surveys over the crop growing season rather than such a cross-sectional study.