Aalto-Helsinki

Description: The Aalto-Helsinki 2016 team started working in the beginning of March. Our brainstorming sessions resulted in more than 50 ideas, of which some were good, some were bad and some were really, really bad. We narrowed the ideas down to the top 5 and then did research to figure out what would be the most promising idea. Ultimately we decided to work with cyanobacteria and the problem they pose every summer in Finland. Cyanobacteria, or blue-green algae, are a problem in Finnish waters especially in the late summer, when they develop big blooms. They produce toxins that can be harmful to people and animals. We decided to concentrate on the most common cyanotoxin found in fresh waters called microcystin-LR (MC), which is a hepatotoxin. We studied MC'™s toxicity mechanisms extensively to figure out the best way to tackle it. The toxicity mechanism in mammalian cells is based on the MC'™s inhibitory effects on protein phosphatase (PP) 1 and 2a. When the PPs are inhibited their target proteins remain phosphorylated which eventually leads to hyperphosphorylation. This results in production of reactive oxygen species that ultimately manifest as oxidative stress. We also found out that the same basic mechanism also happens in yeast cells. So we decided to take advantage of Saccharomyces cerevisiae's oxidative stress response to detect MC. We also want to degrade the toxin. There are a few bacteria that naturally degrade cyanotoxins. We decided to use an enzyme called microcystinase (MlrA), found in some Sphingomonas strains. The degradation leads to a nontoxic product, which is the linear form of the otherwise toxic cyclic heptapeptide. We will study the enzyme kinetics of microcystinase and also the toxicity mechanisms in yeast cells, in order to gain a deeper understanding about the system.We have also worked together with Finland'™s environment center (SYKE). As one of our public outreach projects, we will collaborate with them and work on their Levavahti (Algae Watch) -app. We will try to model a dynamic population model so we could predict how the cyanobacteria blooms will grow and develop, and have this as one of the features in the app.
Collaboration details:
Year: 2016Visit Wiki
E-mail: team@aaltohelsinki.com
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Updated at: 8/31/16