Objective/Rationale:
Mutations in the Leucine-rich Repeat Kinase 2 gene (LRRK2) are the single most common cause for inherited Parkinson's disease (PD). LRRK2 is a large protein consisting of several domains with different functions. Beside enzymatically active domains, able to modify other proteins, it contains others allowing protein-protein interactions. Therefore the project aims at understanding how LRRK2 interacts with other proteins in the cell, how these interactions differ between normal and mutated versions of the gene, and how these differences impact the development and progression of PD.
Project Description:
For this purpose, LRRK2-associated protein complexes will be systematically isolated from cell culture and tissues by affinity-based purification methods and subsequently analyzed by high end mass spectrometry. To represent the endogenous situation as close as possible, patient-derived induced human pluripotent stem cells (hiPSC) differentiated into neurons will be used. This model allows the study of LRRK2 within the context of an individual patient-derived protein repertoire. Following the idea of “guilt-by-association” the identified LRRK2 interacting proteins will be assigned to cellular functions by bioinformatic meta-analysis. This information will be finally used to better understand the physiological role of LRRK2 as well as pathophysiological changes caused by PD-associated LRRK2 mutations.
Relevance to Diagnosis/Treatment of Parkinson’s Disease:
By deciphering LRRK2 protein interaction networks we aim at getting better mechanistic insights into its function on a molecular level. The rationale behind this approach is to use these protein interaction networks to identify LRRK2-depentent cellular pathways and to understand how they are affected in Parkinson’s disease. The successful identification of cellular pathways which are affected by LRRK2 mutations could finally be used to consider rational therapeutic strategies for the treatment of LRRK2-associated PD.
Anticipated Outcome:
By creating high confidence knowledge on both normal LRRK2 interactions as well as deviations occurring as a consequence of LRRK2 mutations, we hope to identify cellular pathways of LRRK2 action and PD-associated changes. The data will be made available to the scientific community though public databases (IntAct, offered by the EBI, Hinxton, UK) and shall serve as a basis for future functional studies.
Progress Report
To understand the physiological as well as pathophysiological function of the protein LRRK2, this project systematically analyzes its associated protein networks established by direct and indirect protein interactions (protein complexes). The team has established several cellular model systems allowing the isolation of the LRRK2-associated protein complexes by co-purification approaches, which are subsequently identified by mass spectrometry. Among them are engineered neuronal cell lines (SH-SY5Y) that permit the inducible expression of normal or pathogenic LRRK2 variants. In addition, the team performed pull-down assays for the co-purification and mass spectrometric identification of associated proteins with recombinant LRRK2 from model brain tissue. By this approach the team demonstrated that LRRK2 interacts with proteins associated with neuronal vesicles. To understand the function of LRRK2 complexes in the pathophysiological context, induced pluripotent stem cells (hiPSC) have been generated from patient skin fibroblasts, which can be differentiated into neuronal cell types. These cells are currently being used to isolate protein complexes associated with pathogenic forms of LRRK2 in a cellular context close to the human disease.
Based on the data generated as part of the project as well as data from literature, the team has established a highly detailed reference LRRK2 interactome, embedded in a wider context of Parkinson’s related interactions. Currently the network contains data from 156 manually full-text curated publications, covering 2,654 protein-protein interaction evidences. The data set is publically available via IntAct: www.ebi.ac.uk/intact/query/annot:"dataset:parkinsons".
June 2014