An in silico FSHD muscle fibre for modelling DUX4 dynamics and predicting the impact of therapy

Matthew V. Cowley, Johanna Pruller, Massimo Ganassi, Peter S. Zammit, Christopher R.S. Banerji

Research output: Contribution to journalArticlepeer-review

2 Citations (SciVal)

Abstract

Facioscapulohumeral muscular dystrophy (FSHD) is an incurable myopathy linked to over‐expression of the myotoxic transcription factor DUX4. Targeting DUX4 is the leading therapeutic approach, however it is only detectable in 0.1‐3.8% of FSHD myonuclei. How rare DUX4 drives FSHD and the optimal anti‐DUX4 strategy is unclear. We combine stochastic gene expression with compartment models of cell states, building a simulation of DUX4 expression and consequences in FSHD muscle fibres. Investigating iDUX4 myoblasts, scRNAseq and snRNAseq of FSHD muscle we estimate parameters including DUX4 mRNA degradation, transcription and translation rates and DUX4 target gene activation rates. Our model accurately recreates the distribution of DUX4 and target gene positive cells seen in scRNAseq of FSHD myocytes. Importantly we show DUX4 drives significant cell death despite expression in only 0.8% of live cells. Comparing scRNAseq of unfused FSHD myocytes to snRNAseq of fused FSHD myonuclei, we find evidence of DUX4 protein syncytial diffusion and estimate its rate via genetic algorithms. We package our model into freely available tools, to rapidly investigate consequences of anti‐DUX4 therapy.

Original languageEnglish
Article numbere88345
Number of pages27
JournaleLife
Volume12
Early online date15 May 2023
DOIs
Publication statusPublished - 22 Jun 2023

Bibliographical note

Funding Information:
CSRB was supported by the Turing‐Roche Partnership. MVC was supported by the EPSRC Centre for Doctoral Training in Sustainable Chemical Technologies (EP/L016354/1) and Friends of FSH research (Project: An in‐silico approach to understanding DUX4 expression). JP was supported by Muscular Dystrophy UK (19GRO‐PG12‐0493) and currently by the FSHD Society (FSHD‐Winter2021‐ 4491649104). MG was supported by the Medical Research Council (MR/S002472/1) and now by SOLVE FSHD. The Zammit lab was also generously supported by Association Française contre les Myopathies.

Data availability:
All data generated or analysed during this study are publicly available or included in the manuscript, all code employed is published as part of our shiny app at 3 public domain URLs listed in the manuscript, and available at GitHub: https://github.com/MVCowley/in-silico-FSHD-muscle-fiber-tools, copy archived at Cowley, 2023.

Publisher Copyright:
© 2023, eLife Sciences Publications Ltd. All rights reserved.

ASJC Scopus subject areas

  • General Neuroscience
  • General Biochemistry,Genetics and Molecular Biology
  • General Immunology and Microbiology

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