Poster Presentation 24th Annual Lorne Proteomics Symposium 2019

Using quantitative proteomics to resolve genomic diagnosis of mitochondrial disease (#119)

Daniella H Hock 1 , Alison Compton 2 3 , Joanna Sacharz 1 , Boris Reljic 1 , David R Thorburn 2 3 4 , David A Stroud 1
  1. Department of Biochemistry and Molecular Biology, University of Melbourne, Bio21 Molecular Science and Biotechnology Institute, Parkville, VIC, Australia
  2. Murdoch Children’s Research Institute, Royal Children’s Hospital, Melbourne, VIC, Australia
  3. Department of Paediatrics, University of Melbourne, Parkville, VIC, Australia
  4. Victorian Clinical Genetic Services, Royal Children’s Hospital, Parkville, VIC, Australia

Mitochondrial diseases are the most common type of inherited metabolic disorders affecting approximately 1 in 5000 live births. These disorders can manifest at any stage of life and compromise energy production via oxidative phosphorylation (OXPHOS) via myriad mechanisms. The current diagnosis for mitochondrial disease relies on target exome sequencing of genes encoding known mitochondrial proteins combined with clinical notes and basic biochemical measurements such as respiratory chain enzyme activity. Due to its complex genetics and phenotypic heterogeneity, over 40% of patients with suspected mitochondrial diseases remain undiagnosed. Quantitative proteomics is an untargeted approach that allows not only discovery of the disease gene but also can provide insights into the molecular function of the mutation within the patient cellular proteome.In this study, primary fibroblasts from two patients with suspected mitochondrial disease were subjected to quantitative proteomics using Tandem Mass Tag (TMT) labels. Patient 1 (P1) had no likely pathogenic variants detected after Whole Exome Sequencing (WES) or mitochondrial DNA sequencing, and no clear enzymatic defect detected in fibroblasts. Quantitative proteomics results suggest decreased abundance of proteins belonging to the large subunit of the mitoribosome compared to multiple control fibroblasts. Re-analysis of sequencing data identified two novel variants in mitoribosome genes that were targeted for follow-up studies. Patient 2 (P2) has two missense variants identified as possible causative mutations: MT-ATP6 p.Leu49Pro (81% heteroplasmy in blood) and a heterozygous ATAD3A p.Thr228Met. Proteomics results demonstrate unchanged levels of ATAD3A protein across samples while MT-ATP6 is among the least abundant mitochondrial proteins in P2, together with other Complex V subunits. This suggests co-dependency between the proteins for a fully functional complex. Further investigations using Blue Native PAGE (BN-PAGE) shows strong defect in mitochondrial Complex V assembly, confirming the MT-ATP6 p.Leu49Pro missense variant as P2 diagnosis. Hence, our study demonstrates the utility of quantitative proteomics to complement the diagnosis of mitochondrial diseases.