Protein misfolding and aggregation are associated with an increasing number of human disorders, such as Alzheimer’s disease and Parkinson’s disease. Additionally, the formation of insoluble deposits during recombinant protein production impedes the commercialization of several peptide drugs. Recent computational studies highlight the existence of a selective pressure to escape from protein aggregation; exerted both on protein sequence and gene expression levels. However, direct experimental evidence demonstrating how natural selection shapes protein sequence and concentration in living cells is still missing. The objective of the here presented project is to exploit a simple cellular model to test how protein aggregation is selected in a biological context. For this, we would study the cell fitness of different yeast cell strains expressing proteins with different aggregation propensity and in growth competition. We have generated a system where each strain is marked with a fluorescent reporter that informs about protein expression, localisation and formation of intracellular deposits. Simultaneously, a specific DNA tag informs about the proportion of each strain in the culture at each time point. By this we will evaluate how protein aggregation influences cell fitness, thus deriving evolutionary principles underlying intracellular regulation of protein deposition.
Field of science
- /natural sciences/biological sciences/biochemistry/biomolecules/proteins/protein folding
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