Generation of a proteomic database to reveal interactomes of human neural diseases associated-proteins
Leclere, Flavien Eric
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The rising rates of neurodegenerative and neurodevelopmental disorders have led to much discovery on their genetic abnormalities and clinical manifestations. However, the link between the genomics and phenotypes of these diseases has yet to be elucidated. Through proteomics, identification of protein complexes will be useful in defining the molecular mechanisms of these disorders at both the protein and systems levels. With the use of a stats database, the novel proteomic approach of CompPASS can be used to produce high confidence interaction networks for proteins encoded by disease-associated genes. Due to the cell-specificity of these protein complexes, a new stats database using physiologically relevant cells is needed to study neural disorders. In this study, we were able to express, immunoprecipate, and analyze by MS 50 different baits by using the SH-SY5Y neuroblastoma cell line. The new SH-SY5Y stats table was analyzed and found to correctly decipher background and high-confidence interacting proteins. Additionally, we provide validation for our approach as the analysis resulted in the identification of HCIPs that were not found by using the existing 293T cell stats database. The newly created SH-SY5Y stats table will help link the genetic abnormalities underlying neural disorders to their phenotypes. We hope this platform will eventually result in treatments to improve the quality of life of individuals suffering from these pathologies.
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