1. Signaling network alterations in mitochondrial disease Xiaoyan Robert Bao Mootha lab Massachusetts General Hospital

2. Most common inborn error of metabolism (~1/5000 live births) Genetic heterogeneity (~75 known nuclear disease-causing genes; maternally inherited mtDNA syndromes) Clinical heterogeneity: epilepsy, stroke-like episodes, vision loss, hearing loss, GI dismotility, lactic acidosis, hepatopathy Diagnosis remains difficult, and no effective treatments exist myopathy subacute neurodegeneration Mitochondrial diseases

3. Described in 1993 in Saguenay Lac-Saint-Jean (SLSJ) Incidence ~ 1/2063 live births (1979-1990) Carrier rate ~ 1/23 in SLSJ Morin et al Am J Hum Genet 1993 An example of such a disease: Leigh Syndrome French Canadian Variant Clinical Features Brainstem gliosis, necrosis Mild developmental delay Ataxia Reye-like syndrome Facial dysmorphism Mortality due to acidotic crises Death between 6 mos and 12 yrs of age Biochemical Features Cytochrome c oxidase deficiency

4. RNA 1,600,000 mRNA measures DNA 2,000,000 nucleotides Protein 85,000 peptides LRPPRC Combining genomic information to discover the disease gene Lee et al Am J Hum Genet 2001 Mootha et al PNAS 2003 H2NH2NCOOH Exon 9Exon 35

5. Physiological measurements 1. O 2 Consumption 2. Acid production 1. qRT-PCR 2. Western Blot Confirmation of knockdown Disease specific assay 1.Western Blot for respiratory chain proteins shRNA “Disease” cells Can we model disease in a dish? Gohil et al J Biol Chem 2010

6. Systematically defining pathways that are altered Gohil et al J Biol Chem 2010

7. SCO1SCO2SLC25A4PUS1 LRPPRC TK2 POLG PEO1 TAZ SURF1 COX10 BCS1L COX15 DGUOK FXN ETHE1 V. Gohil, unpublished RNAi against other OXPHOS disease genes

8. Shaham et al PNAS 2010 Chemical perturbation of OXPHOS function Metabolic profiling of cell culture media

9. We have constructed different types of cellular models of mitochondrial disease: RNAi, dominant negative, chemical In initial studies, we see robust transcriptional and metabolite changes in response to these genetic or chemical lesions. We hypothesize that some of these transcriptional/metabolic changes are mediated by kinase signaling events Such signaling events may contribute to disease pathogenesis. We look forward to working with the LINCS centers to identify kinase signaling events that drive these changes, using mass spectrometry (Broad) and imaging based (HMS) methods Potential collaborations with LINCS centers

10. Acknowledgments Vamsi Mootha Casey Belcher-Timme Vishal Gohil Olga Goldberger Roland Nilsson Oded Shaham Nancy Slate Katherine Sims David E. Root Biao Luo Clary Clish Arvind Ramanathan Amanda Souza NIH/NIDDK R01DK081457