Multi-Omics Profiling of Phytoplankton Community Metabolism: Linking Meta-Transcriptomics and Metabolomics to Elucidate Phytoplankton Physiology in a Model Coastal System

Elizabeth B Kujawinski1, Krista Longnecker1, Harriet Alexander2, Sonya Dyhrman3, Bethany D. Jenkins4 and Tatiana A Rynearson5, (1)Woods Hole Oceanographic Institution, Woods Hole, MA, United States, (2)MIT-WHOI Joint Program, Woods Hole, MA, United States, (3)Columbia University, Palisades, NY, United States, (4)University of Rhode Island Narragansett Bay, Narragansett, RI, United States, (5)University of Rhode Island, Graduate School of Oceanography, Narragansett, RI, United States
Abstract:
Phytoplankton blooms in coastal areas contribute a large fraction of primary production to the global oceans. Despite their central importance, there are fundamental unknowns in phytoplankton community metabolism, which limit the development of a more complete understanding of the carbon cycle. Within this complex setting, the tools of systems biology hold immense potential for profiling community metabolism and exploring links to the carbon cycle, but have rarely been applied together in this context. Here we focus on phytoplankton community samples collected from a model coastal system over a three-week period. At each sampling point, we combined two assessments of metabolic function: the meta-transcriptome, or the genes that are expressed by all organisms at each sampling point, and the metabolome, or the intracellular molecules produced during the community’s metabolism. These datasets are inherently complementary, with gene expression likely to vary in concert with the concentrations of metabolic intermediates. Indeed, preliminary data show coherence in transcripts and metabolites associated with nutrient stress response and with fixed carbon oxidation. To date, these datasets are rarely integrated across their full complexity but together they provide unequivocal evidence of specific metabolic pathways by individual phytoplankton taxa, allowing a more comprehensive systems view of this dynamic environment. Future application of multi-omic profiling will facilitate a more complete understanding of metabolic reactions at the foundation of the carbon cycle.