Non-random patterns of chytrid infections on phytoplankton host cells: mathematical and chemical ecology approaches

Host−parasite interactions between phytoplankton and fungi (chytrids) are key processes in aquatic ecosystems. However, individual-level heterogeneity in these interactions remains unexplored, although its importance in predicting the spread of diseases has been demonstrated in epidemiology. In this study, we experimentally tested whether individual-level heterogeneity could be a good indicator of phytoplankton−chytrid interactions, using a freshwater green alga Staurastrum sp., the diatoms Ulnaria sp. and Fragilaria crotonensis, and chytrid fungi. The number of attached fungi per host cell showed a non-random clumped parasite distribution on Ulnaria sp. and F. crotonensis, but a random Poisson distribution on Staurastrum sp. To explore the potential mechanisms of these patterns, we developed a mathematical model describing sequential encounters between chytrid zoospores and host cells. The statistical fits of the model explained the parasite distributions for Ulnaria sp. and F. crotonensis well, indicating that the clumped parasite distributions may result from an infection rate, increasing with the number of infections that already occurred on each host cell. Simultaneous analysis of volatile organic compounds (VOCs) from uninfected and infected host populations revealed that, among 13 VOCs detected, 6 components characterized the differences in VOC compositions between species and infection status. In particular, the level of beta-ionone, potentially acting against fungal activities, was significantly reduced in the presence of chytrid infection of Staurastrum sp. These VOCs are targets for future studies, which potentially act as chemical signals influencing chytrid zoospores’ behaviors. The combination of mathematical and chemical analyses represents a promising approach to better understand the individual-level processes of phytoplankton−chytrid interactions.