Abstract Title

Trait variation in resource competition traits among Microcystis strains in presence and absence of their microbiomes

Start Date

26-5-2022 9:15 AM

End Date

26-5-2022 9:30 AM

Abstract

Freshwater harmful algal blooms are often dominated by Microcystis, a phylogenetically cohesive group of cyanobacteria marked by extensive genetic and physiological diversity. We have previously shown that this genetic diversity and the presence of a microbiome of heterotrophic bacteria influences competitive interactions with eukaryotic phytoplankton. In this study, we sought to explain these observations by characterizing Monod equation parameters for resource usage (maximum growth rate μmax , half saturation value for growth Ks) as a function of N (25-30,000 μg/L) and P (1-3,000 μg/L) levels for 4 different strains (NIES-843, PCC 9701, PCC 7806, PCC 7806 ΔmcyB) in presence and absence of a microbiome derived from Microcystis isolated from Lake Erie. Results indicated significant differences in maximum growth rates and half saturation values among isolates, and variable effects of the microbiome depending on the Microcystis strain, either increasing, decreasing, or not affecting growth rates and/or the half saturation values. As these parameters are commonly used in predictive models for harmful algal blooms, our data suggest that models can be improved by incorporating genotype dependencies of growth kinetic parameters. Additionally, our data highlights the importance of the microbiome in altering Microcystis-intrinsic traits and thus bloom dynamics.

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May 26th, 9:15 AM May 26th, 9:30 AM

Trait variation in resource competition traits among Microcystis strains in presence and absence of their microbiomes

Freshwater harmful algal blooms are often dominated by Microcystis, a phylogenetically cohesive group of cyanobacteria marked by extensive genetic and physiological diversity. We have previously shown that this genetic diversity and the presence of a microbiome of heterotrophic bacteria influences competitive interactions with eukaryotic phytoplankton. In this study, we sought to explain these observations by characterizing Monod equation parameters for resource usage (maximum growth rate μmax , half saturation value for growth Ks) as a function of N (25-30,000 μg/L) and P (1-3,000 μg/L) levels for 4 different strains (NIES-843, PCC 9701, PCC 7806, PCC 7806 ΔmcyB) in presence and absence of a microbiome derived from Microcystis isolated from Lake Erie. Results indicated significant differences in maximum growth rates and half saturation values among isolates, and variable effects of the microbiome depending on the Microcystis strain, either increasing, decreasing, or not affecting growth rates and/or the half saturation values. As these parameters are commonly used in predictive models for harmful algal blooms, our data suggest that models can be improved by incorporating genotype dependencies of growth kinetic parameters. Additionally, our data highlights the importance of the microbiome in altering Microcystis-intrinsic traits and thus bloom dynamics.