SP 4

Validation in cellular models

The aim of this project is to perform a systematic functional validation of predictive genetic models of Parkinson disease (PD)-related pathway and network dysregulations in patient-derived cellular models. The main readout criteria are different aspects of mitochondrial defects to identify a subgroup of PD-patients with mitochondrial dysfunction as (part of the) cause for the development of disease.

Automated cell culture with devices for high-throughput analysis. The image shows an automated lab which allows for fully automated cell culture and high-throughput/High-Content cellular screens at our project partner at the University of Tübingen (www.dzne.de/standorte/tuebingen/forschergruppen/jain.html).

Targeted (low throughput) validation of mitochondrial function (e.g. mitochondrial membrane potential, morphology, and integrity of the mitochondrial genome) will be the first stage validation performed in fibroblasts and neurons derived from patient’s induced pluripotent stem cells (iPSC). Analyses will be performed on materials from patients with PD-linked PINK1 and Parkin mutations as a reference, and, importantly, on material from those sporadic patients identified as to exhibit deregulated mitochondrial pathways and therefore represent the postulated mitochondrial phenotype of PD.
The second stage validation will extend these studies by using high-throughput cellular screening approaches in combination with multiparametric or high-content cellular readouts. We will use morphological (e.g. neurite outgrowth, mitochondrial function, morphology) as well as genomic phenotypes (e.g. genome wide RNA expression). To model the predicted effects of multiple risk factors involved in PD, we will perform multiple perturbations simultaneously using knock down and over-expression on patient-derived or isogenic iPSCs.
The third stage validation will cover a proteomic analysis. Protein interaction network data will be generated by quantitative analysis of mitochondria isolated from a limited set of patient-derived iPSC lines. From there, a strong focus on the prediction of highly connected functionally related protein clusters shall allow the selection of proteins with an increased likelihood to contribute to a specific phenotype.
The goal is to validate the identified “master regulators” and dissect the disease specific network, which enable us to provide a tool in form of high-throughput cellular assays for identifying potential drug targets.

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