Strain-delineated composition and spatiotemporal dynamics of cyanobacteria throughout nutrient gradients in a eutrophic, freshwater lake

The composition and dynamics of cyanobacterial communities in freshwater lakes has been studied intensively to explain the timing and intensity of harmful cyanobacterial blooms. Although, there is a knowledge gap in how these communities evolve and move in their lake systems, as well as, how comparable these separate communities are to each other. For this, we have used shotgun metagenomics on shoreline samples around Lake Mendota, a eutrophic, freshwater lake, to obtain cyanobacteria assemblage snapshots. These samples are throughout the typical cyanobacterial growing season and were collected before and after periods of high wind or rain. Additionally, a portion of samples were collected across a nutrient gradient from the Yahara River outlet into Lake Mendota towards the center at the Deep Hole sampling site. In this study we use a combination of meta’omics and time lag analyses to assess how cyanobacteria communities change throughout the season and especially in response to nutrient pulses. Additionally, we use a variety of microdiversity metrics, such as single nucleotide variations, to compare these separated communities’ genomes. These results all can be used to improve our understanding of cyanobacterial bloom compositions across space and time, which can be used to improve bloom forecasting.

Primary Presenter: Krystyn Kibler, University of Wisconsin - Madison (kjkibler@wisc.edu)

Authors:

Katherine McMahon, University of Wisconsin - Madison  (trina.mcmahon@wisc.edu)