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

K Yoneya,T Miki,M Kagami,HP Grossart,S Van den Wyngaert

doi:10.3354/ame01966

Abstract

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 algaStaurastrumsp., the diatomsUlnariasp. andFragilaria crotonensis, and chytrid fungi. The number of attached fungi per host cell showed a non-random clumped parasite distribution onUlnariasp. andF. crotonensis, but a random Poisson distribution onStaurastrumsp. 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 forUlnariasp. andF. crotonensiswell, 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 ofStaurastrumsp. 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.

Highlights

Interactions between phytoplankton and fungal parasites such as chytrids are key processes in aquaticPublisher: Inter-Research · www.int-res.comAquat Microb Ecol 87: 1–15, 2021 plankton to zooplankton via zooplankton grazing on chytrid zoospores, the so-called ‘mycoloop’ (Kagami et al 2007, 2011, 2014)
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
We found that the infections in the Ulnaria system with the C4 strain and those in the Fragilaria system deviated from a Poisson distribution and had a clumped distribution, whereas the Staurastrum system’s distribution was not distinguishable from Poisson

Summary

Introduction

Interactions between phytoplankton and fungal parasites such as chytrids are key processes in aquaticPublisher: Inter-Research · www.int-res.comAquat Microb Ecol 87: 1–15, 2021 plankton to zooplankton via zooplankton grazing on chytrid zoospores, the so-called ‘mycoloop’ (Kagami et al 2007, 2011, 2014). Most studies do not focus on individuallevel heterogeneity in the interactions between host cells and parasitic chytrids (except Bruning 1991b, Van den Wyngaert et al 2014), but focus on population-averaged parameters only (e.g. the prevalence of infection, transmission, and of zooplankton grazing rates on chytrid zoospores). This is based on an implicit assumption that the encounter between host cells and chytrid zoospores occurs at random and that the dynamics of host−parasite interactions can be reasonably understood with the population-averaged parameters. Contrary to phytoplankton− chytrid interactions, human epidemiology and general parasitology consider the non-random interactions between the host and infective agents and nonrandom individual-level heterogeneity in hosts as major determinants of the spread and persistence of infectious diseases (Paull et al 2012)

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