The Functional Implications of Bottom Up and Top Down Controls on Marine Bacteria in Arthur Harbor, a Highly Productive Coastal Setting on the West Antarctic Peninsula

Marine bacteria can be broadly classified into two groups based on their ecology; slow growing oligotrophic specialists and fast growing copiotrophs. These ecological strategies are associated with specific taxonomic and functional groups, making it possible to use 16S rRNA gene amplicon and shotgun metagenomic data to qualitatively, and possibly quantitatively, identify the contribution of each strategy to marine biogeochemical cycles. We leveraged a 5-year (2009 to 2014) time series of 16S rRNA gene amplicon data for Arthur Harbor, located near Palmer Station, Antarctica, to identify trends in the abundance of taxa associated with each ecological strategy. Using emergent self-organizing maps, we identified four recurring “modes” in bacterial community structure based on the relative abundance of the ubiquitous SAR11 clade. A different bacterial genus was dominant in each mode; Pelagibacter, Polaribacter, Roseobacter, and Colwellia. To explore the functional implications of these different modes we applied shotgun metagenomics and functional predictions using the newly available tool PAPRICA, in combination with flow cytometry and estimates of bacterial production. Our annotation and assembly of binned contigs corresponding to the dominant genera illuminate the succession of metabolic functions across the 2013-2014 austral summer and inform the timing of autotrophic and mixotrophic (putatively bacterivorous) phytoplankton blooms. Surprisingly, while the abundance of Pelagibacter 16S rRNA gene reads was negatively correlated with the concentration of chlorophyll a, the ratio of Pelagibacter to Polaribacter and Roseobacter was poorly correlated with the ratio of high nucleic acid (HNA) to low nucleic acid (LNA) bacteria as determined by flow cytometry, and the relative size of the HNA population at times contrasted sharply with chlorophyll a. These findings suggest that the physiological state of bacterial cells and top down controls play a strong role in HNA: LNA dynamics.