Exploring Systems Properties of Mitochondrial Networks in Neurodegenerative Disease

Sandy Kassir1, Vishaldeep Sidhu1, Ke Jin1,2, James Vlasblom1, Sadhna Phanse2, Zhaolei Zhang2, Mohan Babu1

1. Department of Biochemistry, Research and Innovation Centre, University of Regina, SK, Canada; 2. Terrence Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, ON, Canada

Proteomic approaches such as affinity purification in combination with mass spectrometry (AP-MS) and yeast two-hybrid have been proven successful in the isolation of native soluble or membrane protein-protein interactions and complexes in model organisms, including the yeast Saccharomyces cerevisiae and the eubacterium Escherichia coli. In this talk, I will discuss how the AP-MS purification strategy, in particular, can be a powerful tool for generating interactome maps for disease-causing mitochondrial proteins (MPs). MPs are involved in many cellular processes, as a result of their propensity to interact with each other and with other extra-compartmental proteins, and hence defects in their function have emerged as causative factors for diverse human disorders, particularly neurodegenerative (ND) diseases like Parkinson’s, Alzheimer’s and Huntington’s. To date, biochemical and genetic investigations have uncovered only a small number of MPs involved in ND diseases. Given the diversity of processes affected by mitochondrial function, and because it is difficult to pinpoint the role of mitochondrial dysfunction in human diseases, many more remain unknown. We are addressing this deficit by focusing on over 600 putative disease-causing MPs, of which we have affinity purified roughly 80 lentiviral tagged proteins in the mammalian model human embryonic kidney (HEK293) cell line. Interactors of the purified proteins were then identified with a high performance Orbitrap Elite mass spectrometer. Our assay captured both previously known interacting proteins, as well as several new associations that have not been reported previously. The data we have generated so far provides new insight into the complex etiologies of ND disease, and opens avenues for identifying new therapeutic drug targets that could ameliorate many diseases all together.