Evolutionary dynamics and population genomics of cyanobacterial blooms

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Cyanobacterial blooms occur in lakes worldwide, and almost yearly in many Quebec lakes. The dominant member of the bloom's microbial community is typically the cyanobacterium Microcystis aeruginosa, some strains of which produce toxins harmful to humans and livestock. Blooms can therefore pose a public health threat, and much research has gone into understanding the biology of bloom dynamics and toxin production. We know that blooms are more severe in lakes polluted with nitrogen- and phosphorus-rich fertilizers, but we still lack the ability to control blooms or predict whether they will be toxic. Like many microbes, Microcystis grow rapidly (at least during summer blooms) to large population sizes, generating genetically diverse populations that can respond rapidly to natural selection - meaning that they can evolve in real time, from year to year, or over the course of a summer bloom. The goal of this project is to 'watch' Microcystis evolve over months and years by sequencing genomes from natural populations in Quebec lakes. This will help us answer fundamental questions: Do Microcystis populations follow the same evolutionary trajectory repeatedly, with the same strains (or those with a common set of genes) 'winning' during every summer bloom? If so, this means that blooms are predictable in principle. This research will also identify mutations that provide a selective advantage to Microcystis. If there are particular advantageous mutations or genes that promote bloom formation, the presence or absence of such genes could provide valuable 'biomarkers' of bloom risk. The cellular functions of these genes could potentially be targeted to help prevent blooms. In addition to these practical outcomes for public and environmental health in Canada, this research project will provide a rare glimpse into evolution in real time, adding to our understanding of how microbes adapt to their natural environments. Over the course of this research, 14 highly-qualified personnel will be trained in a multidisciplinary setting, involving computational and laboratory work with collaborators in Canada and internationally.