Mitochondria are tiny organelles found within virtually all of our body's cells. They control a number of important cellular processes, including energy production, fat metabolism, steroid synthesis, and programmed cell death. Recently, multiple studies have shown that inherited or acquired mitochondrial dysfunction can give rise to a host of rare metabolic disorders, as well as many common diseases, including type 2 diabetes mellitus, heart failure, neurodegeneration, and the aging process itself. Mitochondria are complex structures, consisting of an estimated 1500 proteins. The majority of these proteins are encoded in the cell's nucleus, produced in the cytosol, and then imported into the mitochondrion. At present, we only know about 750 of the estimated 1500 mitochondrial proteins. Because mitochondria contribute to so many rare and common human diseases, it's important that we systematically identify all the proteins that constitute this organelle and begin to understand how they function together in health and in disease. Availability of complete mammalian genome sequences, in combination with new protein detection and microscopy technologies, now provide a special opportunity to systematically and comprehensively identify all the protein components of mammalian mitochondria, as well as how they function together. In the current application, we propose to use a multidisciplinary approach that blends protein biochemistry, computational genomics, and imaging, to construct a protein parts list for mammalian mitochondria. This project will provide an important foundation for systematic approaches to mitochondrial function, which will be extremely important in the coming years as we link its activity to common human diseases, such as type 2 diabetes mellitus. Moreover, the protein catalog that we generate will immediately provide a rich source of candidate disease genes for rare mitochondrial disorders. ? ? ?

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
1R01GM077465-01A1
Application #
7196012
Study Section
Genomics, Computational Biology and Technology Study Section (GCAT)
Program Officer
Anderson, Richard A
Project Start
2007-02-01
Project End
2012-01-31
Budget Start
2007-02-01
Budget End
2008-01-31
Support Year
1
Fiscal Year
2007
Total Cost
$470,903
Indirect Cost
Name
Massachusetts Institute of Technology
Department
Type
Organized Research Units
DUNS #
001425594
City
Cambridge
State
MA
Country
United States
Zip Code
02139
Calvo, Sarah E; Julien, Olivier; Clauser, Karl R et al. (2017) Comparative Analysis of Mitochondrial N-Termini from Mouse, Human, and Yeast. Mol Cell Proteomics 16:512-523
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Hung, Victoria; Lam, Stephanie S; Udeshi, Namrata D et al. (2017) Proteomic mapping of cytosol-facing outer mitochondrial and ER membranes in living human cells by proximity biotinylation. Elife 6:
Kamer, Kimberli J; Grabarek, Zenon; Mootha, Vamsi K (2017) High-affinity cooperative Ca2+ binding by MICU1-MICU2 serves as an on-off switch for the uniporter. EMBO Rep 18:1397-1411
Feichtinger, René G; Oláhová, Monika; Kishita, Yoshihito et al. (2017) Biallelic C1QBP Mutations Cause Severe Neonatal-, Childhood-, or Later-Onset Cardiomyopathy Associated with Combined Respiratory-Chain Deficiencies. Am J Hum Genet 101:525-538
Lake, Nicole J; Webb, Bryn D; Stroud, David A et al. (2017) Biallelic Mutations in MRPS34 Lead to Instability of the Small Mitoribosomal Subunit and Leigh Syndrome. Am J Hum Genet 101:239-254
Arroyo, Jason D; Jourdain, Alexis A; Calvo, Sarah E et al. (2016) A Genome-wide CRISPR Death Screen Identifies Genes Essential for Oxidative Phosphorylation. Cell Metab 24:875-885
Calvo, Sarah E; Clauser, Karl R; Mootha, Vamsi K (2016) MitoCarta2.0: an updated inventory of mammalian mitochondrial proteins. Nucleic Acids Res 44:D1251-7
Lam, Stephanie S; Martell, Jeffrey D; Kamer, Kimberli J et al. (2015) Directed evolution of APEX2 for electron microscopy and proximity labeling. Nat Methods 12:51-4
Li, Yang; Calvo, Sarah E; Gutman, Roee et al. (2014) Expansion of biological pathways based on evolutionary inference. Cell 158:213-25

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