Programming Human Chaperone Systems Against Neurodegenerative Disease

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Cellular stress causes protein misfolding and aggregation, which is combatted by protein chaperone enzymes (disaggregases). In neurons, protein misfolding and aggregation can lead to neurodegenerative diseases including amyotrophic lateral sclerosis (ALS), Alzheimer's disease, frontotemporal dementia, Parkinson's disease, Huntington's disease, and spinocerebellar ataxias. The lack of viable therapeutic options reflects the dearth of our understanding regarding the cellular processes that go awry in these diseases. Since protein quality control is required for all living organisms, simple model systems such as yeast are powerful tools to study the analogous human process in a rapid and cost-efficient way. This project will leverage high-throughput genetic engineering in yeast to study and engineer human disaggregase systems to combat toxic protein aggregates that underlie Parkinson’s disease and ALS. First, I will test the hypothesis that unique combinations of human hsp110, hsp70, and hsp40 chaperones can impart disaggregase substrate specificity in a cell. I will create and test plasmid libraries for all possible triplet combinations of the known hsp110/70/40 genes in yeast models of Parkinson’s and ALS. Second, I will use eMAGE, a technique that I invented during my PhD, to engineer the previously characterized human disaggregase machinery comprised of hsp110 (Apg-2), hsp70 (Hsc70) and hsp40 (Hdj1). Lastly, I will validate the findings from yeast in human neuronal cell models of Parkinson’s disease and ALS. The experimental pipeline outlined in this proposal leverages the scale and power of yeast genetics to identify Hsp110/70/40 mutants and gene combinations that exhibit rescue of toxicity, which are then experimentally validated in a bona fide human neuron. This project will greatly enhance the current understanding of human disaggregase mechanisms by exhaustively screening the combinatorial space of three-gene chaperone interactions and it will likely identify new mechanisms for candidate therapeutics of Parkinson’s disease and ALS.