Linking light-dependent life history traits with population dynamics for Prochlorococcus and cyanophage

David Jean Robert Demory1, Riyue Liu2, Yue Chen3, Fangxin Zhao3, Ashley Coenen4, Qinglu Zeng5 and Joshua S Weitz6, (1)Georgia Institute of Technology, School of Biological Sciences, Atlanta, GA, United States, (2)The Hong Kong University of Science and Technology, Division of Life Science, Hong Kong, (3)The Hong Kong University of Science and Technology, Department of Ocean Science, Hong Kong, (4)Georgia Institute of Technology, School of Physics, United States, (5)The Hong Kong University of Science and Technology, Division of Life Science and Department of Ocean Science, Hong Kong, (6)University of Maryland, United States
Abstract:
Prochlorococcus grow in diurnal rhythms driven by diel cycles. Their ecology depends on light, nutrients, and top-down mortality processes including lysis by viruses. Cyanophage, viruses that infect cyanobacteria, are also impacted by light. For example, extracellular viability and intracell infection kinetics of some cyanophage vary between light and dark conditions. Nonetheless, it remains unclear if light-dependent viral life history traits scale-up to influence population-level dynamics. In this study we examined the impact of diel-forcing on both cellular- and population-scale dynamics in two Prochlorococcus-phage systems. To do so, we developed a light-driven population model including both cellular growth and viral infection dynamics. We then tested the model against measurements of experimental infection dynamics with diel forcing to examine the extent to which population level changes in both viral and host abundances could be explained by light-dependent life history traits. Model-data integration reveals that light-dependent adsorption can improve fits to population dynamics for some virus-host pairs. However, light-dependent variation alone does not fully explain realized host and virus population dynamics. Instead, we show evidence of a previously unrecognized lysis saturation at relatively high virus to cell ratios. Altogether, our study represents a quantitative approach to integrate mechanistic models to reconcile Prochlorococcus-virus dynamics spanning cellular to population scales.