Multi-omics identifies large mitoribosomal subunit instability caused by pathogenic MRPL39 variants as a cause of pediatric onset mitochondrial disease

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

  • Sumudu S.C. Amarasekera
  • Daniella H. Hock
  • Nicole J. Lake
  • Sarah E. Calvo
  • Sabine W. Grønborg
  • Emma I. Krzesinski
  • David J. Amor
  • Michael C. Fahey
  • Cas Simons
  • Flemming Wibrand
  • Vamsi K. Mootha
  • Monkol Lek
  • Sebastian Lunke
  • Zornitza Stark
  • Østergaard, Elsebet
  • John Christodoulou
  • David R. Thorburn
  • David A. Stroud
  • Alison G. Compton
MRPL39 encodes one of 52 proteins comprising the large subunit of the mitochondrial ribosome (mitoribosome). In conjunction with 30 proteins in the small subunit, the mitoribosome synthesizes the 13 subunits of the mitochondrial oxidative phosphorylation (OXPHOS) system encoded by mitochondrial Deoxyribonucleic acid (DNA). We used multi-omics and gene matching to identify three unrelated individuals with biallelic variants in MRPL39 presenting with multisystem diseases with severity ranging from lethal, infantile-onset (Leigh syndrome spectrum) to milder with survival into adulthood. Clinical exome sequencing of known disease genes failed to diagnose these patients; however quantitative proteomics identified a specific decrease in the abundance of large but not small mitoribosomal subunits in fibroblasts from the two patients with severe phenotype. Re-analysis of exome sequencing led to the identification of candidate single heterozygous variants in mitoribosomal genes MRPL39 (both patients) and MRPL15. Genome sequencing identified a shared deep intronic MRPL39 variant predicted to generate a cryptic exon, with transcriptomics and targeted studies providing further functional evidence for causation. The patient with the milder disease was homozygous for a missense variant identified through trio exome sequencing. Our study highlights the utility of quantitative proteomics in detecting protein signatures and in characterizing gene-disease associations in exome-unsolved patients. We describe Relative Complex Abundance analysis of proteomics data, a sensitive method that can identify defects in OXPHOS disorders to a similar or greater sensitivity to the traditional enzymology. Relative Complex Abundance has potential utility for functional validation or prioritization in many hundreds of inherited rare diseases where protein complex assembly is disrupted.
OriginalsprogEngelsk
TidsskriftHuman Molecular Genetics
Vol/bind32
Udgave nummer15
Sider (fra-til)2441-2454
Antal sider14
ISSN0964-6906
DOI
StatusUdgivet - 2023

Bibliografisk note

Funding Information:
This research was supported by grants and fellowships from the Australian National Health and Medical Research Council (1140851, 1164479, 1159456, 1155244, 2009732 plus 111353 to the Australian Genomics Health Alliance), plus grants from the US Department of Defense Congressionally Directed Medical Research Programs PR170396, the Australian Mito Foundation, the Vincent Chiodo Charitable Trust and the Victorian Government’s Operational Infrastructure Support Program. The Chair in Genomic Medicine awarded to JC is generously supported by The Royal Children’s Hospital Foundation. We acknowledge the Bio21 Mass Spectrometry and Proteomics Facility (MMSPF) for the provision of instrumentation, training, and technical support. The Yale Center for Mendelian Genomics (NIH M#UM1HG006504-05) is funded by the National Human Genome Research Institute and the National Heart, Lung, and Blood Institute. The GSP Coordinating Center (U24 HG008956) contributed to cross-program scientific initiatives and provided logistical and general study coordination. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. DHH is supported by a Melbourne International Research Scholarship and the Mito Foundation PhD Top-up Scholarship. VKM is an Investigator at the Howard Hughes Medical Institute.

Publisher Copyright:
© 2023 The Author(s). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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