Project: Characterizing plankton parasite-host metabolites and the response of heterotrophic bacteria

Nearly half of annual primary production in the ocean is released by phytoplankton as labile metabolites, making up a large portion of dissolved organic carbon (DOC) that can fuel microbial food webs and mediate cell signaling and species interactions. Phytoplankton mortality is a major source of labile DOC, and yet, the contribution of different sources of mortality to carbon cycling remains unclear. This is especially true for parasitism. In recent genomics surveys, parasitic protists have been found to be widespread in the ocean and well-connected to potential phytoplankton hosts via network analysis. The family Amoebophyridae (Syndiniales) are one of the ubiquitous and phylogenetically diverse groups of protist parasites, known to infect a range of hosts and drive shifts in microbial diversity and bloom phenology. Though not well quantified, these parasites are thought to have a similar impact on carbon cycling as viruses, with rapid host infection (2-3 d) and a rerouting of particulate carbon to labile DOC. In this project, we performed culture-based experiments and used untargeted metabolomics to profile labile DOC released over an infection cycle. Phytoplankton cultures included two strains of Amoebophyra sp. that infect the same dinoflagellate host (Scrippsiella acuminata), allowing us to explore new insights into strain-level infection dynamics. Separate incubation experiments were also conducted to expose parasite-derived filtrate (collected fresh from cultures after host lysis) to natural bacterial communities. Samples were collected for metabarcoding and metatranscriptomics at discrete time points to characterize changes in bacterial community assembly and gene expression in the presence of labile DOC. This work aims to provide new perspectives on plankton parasitism and its role in biogeochemical cycling, which can inform future research directions in microbial parasite-host systems and lead to more accurate food web and ecosystem models in a changing ocean environment.