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Decoding mitochondrial heterogeneity in single muscle fibres by imaging mass cytometry

Lookup NU author(s): Charlotte Warren, Dr David McDonald, Professor David Deehan, Professor Robert Taylor, Dr Andrew Filby, Emeritus Professor Doug Turnbull, Dr Conor Lawless, Dr Amy Vincent

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

© 2020, The Author(s). The study of skeletal muscle continues to support the accurate diagnosis of mitochondrial disease and remains important in delineating molecular disease mechanisms. The heterogeneous expression of oxidative phosphorylation proteins and resulting respiratory deficiency are both characteristic findings in mitochondrial disease, hence the rigorous assessment of these at a single cell level is incredibly powerful. Currently, the number of proteins that can be assessed in individual fibres from a single section by immunohistochemistry is limited but imaging mass cytometry (IMC) enables the quantification of further, discrete proteins in individual cells. We have developed a novel workflow and bespoke analysis for applying IMC in skeletal muscle biopsies from patients with genetically-characterised mitochondrial disease, investigating the distribution of nine mitochondrial proteins in thousands of single muscle fibres. Using a semi-automated analysis pipeline, we demonstrate the accurate quantification of protein levels using IMC, providing an accurate measure of oxidative phosphorylation deficiency for complexes I–V at the single cell level. We demonstrate signatures of oxidative phosphorylation deficiency for common mtDNA variants and nuclear-encoded complex I variants and a compensatory upregulation of unaffected oxidative phosphorylation components. This technique can now be universally applied to evaluate a wide range of skeletal muscle disorders and protein targets.


Publication metadata

Author(s): Warren C, McDonald D, Capaldi R, Deehan D, Taylor RW, Filby A, Turnbull DM, Lawless C, Vincent AE

Publication type: Article

Publication status: Published

Journal: Scientific Reports

Year: 2020

Volume: 10

Issue: 1

Online publication date: 18/09/2020

Acceptance date: 05/08/2020

Date deposited: 19/11/2020

ISSN (electronic): 2045-2322

Publisher: Nature Research

URL: https://doi.org/10.1038/s41598-020-70885-3

DOI: 10.1038/s41598-020-70885-3

PubMed id: 32948797


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