title: Exploring mitochondrial system properties of neurodegenerative diseases through interactome mapping.
abstract: Mitochondria are double membraned, dynamic organelles that are required for a large number of cellular processes, and defects in their function have emerged as causative factors for a growing number of human disorders and are highly associated with cancer, metabolic, and neurodegenerative (ND) diseases. Biochemical and genetic investigations have uncovered small numbers of candidate mitochondrial proteins (MPs) involved in ND disease, but given the diversity of processes affected by MP function and the difficulty of detecting interactions involving these proteins, many more likely remain unknown. However, high-throughput proteomic and genomic approaches developed in genetically tractable model prokaryotes and lower eukaryotes have proven to be effective tools for querying the physical (protein-protein) and functional (gene-gene) relationships between diverse types of proteins, including cytosolic and membrane proteins. In this review, we highlight how experimental and computational approaches developed recently by our group and others can be effectively used towards elucidating the mitochondrial interactome in an unbiased and systematic manner to uncover network-based connections. We discuss how the knowledge from the resulting interaction networks can effectively contribute towards the identification of new mitochondrial disease gene candidates, and thus further clarify the role of mitochondrial biology and the complex etiologies of ND disease.
  
  
  CONCLUSIONS
  Biochemical and genetic investigations have uncovered small numbers of candidate mitochondrial proteins (MPs) involved in neurodegenerative (ND) diseases, but given the diversity of processes affected by MP function and the difficulty of detecting interactions involving these proteins, many more likely remain unknown. Large-scale proteomic and genomic approaches developed in model prokaryotes and lower eukaryotes have proven to be effective tools for querying the physical (protein-protein) and functional (gene-gene) relationships between diverse types of proteins. Extension of this new framework to the mitochondrial sub-system in human will likewise provide a universally informative systems-level view of the physical and functional landscape for exploring the evolutionary principles underlying mitochondrial function. In this review, we highlight how experimental and computational approaches developed recently by our group and others can be effectively used towards elucidating the mitochondrial interactome in an unbiased and systematic manner to uncover network-based connections. We anticipate that the knowledge from these resulting interaction networks can effectively contribute towards the identification of new mitochondrial disease gene candidates, and thus foster a deeper molecular understanding of mitochondrial biology as well as the etiology of mitochondrial diseases. This article is part of a Special Issue: Can Proteomics Fill the Gap Between Genomics and Phenotypes?
authors.affiliation: Department of Biochemistry, Research and Innovation Centre, University of Regina, Regina, Saskatchewan S4S 0A2, Canada.
authors.forename: James
authors.initials: J
authors.lastname: Vlasblom
authors.affiliation: Department of Biochemistry, Research and Innovation Centre, University of Regina, Regina, Saskatchewan S4S 0A2, Canada; Banting and Best Department of Medical Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada; Terrence Donnelly Center for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada.
authors.forename: Ke
authors.initials: K
authors.lastname: Jin
authors.affiliation: Department of Biochemistry, Research and Innovation Centre, University of Regina, Regina, Saskatchewan S4S 0A2, Canada.
authors.forename: Sandy
authors.initials: S
authors.lastname: Kassir
authors.affiliation: Department of Biochemistry, Research and Innovation Centre, University of Regina, Regina, Saskatchewan S4S 0A2, Canada. Electronic address: mohan.babu@uregina.ca.
authors.forename: Mohan
authors.initials: M
authors.lastname: Babu
mesh_terms: D006801:Humans; D008928:Mitochondria / Q000502:physiology*; D024101:Mitochondrial Proteins / Q000502:physiology*; D019636:Neurodegenerative Diseases / Q000503:physiopathology*; D025941:Protein Interaction Mapping / Q000379:methods; D040901:Proteomics / Q000379:methods
chemical_list: D024101:Mitochondrial Proteins
keywords: Epistatic interactions; Mitochondrial diseases; Networks; Neurodegenerative diseases; Protein–protein interactions; RNA interference