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An in silico FSHD muscle fiber for modeling DUX4 dynamics and predicting the impact of therapy
Facioscapulohumeral muscular dystrophy (FSHD) is an incurable myopathy linked to the 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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10287159/ https://www.ncbi.nlm.nih.gov/pubmed/37184373 http://dx.doi.org/10.7554/eLife.88345 |
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author | Cowley, Matthew V Pruller, Johanna Ganassi, Massimo Zammit, Peter S Banerji, Christopher RS |
author_facet | Cowley, Matthew V Pruller, Johanna Ganassi, Massimo Zammit, Peter S Banerji, Christopher RS |
author_sort | Cowley, Matthew V |
collection | PubMed |
description | Facioscapulohumeral muscular dystrophy (FSHD) is an incurable myopathy linked to the 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 are unclear. We combine stochastic gene expression with compartment models of cell states, building a simulation of DUX4 expression and consequences in FSHD muscle fibers. 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 targets 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 the consequences of anti-DUX4 therapy. |
format | Online Article Text |
id | pubmed-10287159 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-102871592023-06-23 An in silico FSHD muscle fiber for modeling DUX4 dynamics and predicting the impact of therapy Cowley, Matthew V Pruller, Johanna Ganassi, Massimo Zammit, Peter S Banerji, Christopher RS eLife Cell Biology Facioscapulohumeral muscular dystrophy (FSHD) is an incurable myopathy linked to the 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 are unclear. We combine stochastic gene expression with compartment models of cell states, building a simulation of DUX4 expression and consequences in FSHD muscle fibers. 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 targets 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 the consequences of anti-DUX4 therapy. eLife Sciences Publications, Ltd 2023-05-15 /pmc/articles/PMC10287159/ /pubmed/37184373 http://dx.doi.org/10.7554/eLife.88345 Text en © 2023, Cowley, Pruller et al https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Cell Biology Cowley, Matthew V Pruller, Johanna Ganassi, Massimo Zammit, Peter S Banerji, Christopher RS An in silico FSHD muscle fiber for modeling DUX4 dynamics and predicting the impact of therapy |
title | An in silico FSHD muscle fiber for modeling DUX4 dynamics and predicting the impact of therapy |
title_full | An in silico FSHD muscle fiber for modeling DUX4 dynamics and predicting the impact of therapy |
title_fullStr | An in silico FSHD muscle fiber for modeling DUX4 dynamics and predicting the impact of therapy |
title_full_unstemmed | An in silico FSHD muscle fiber for modeling DUX4 dynamics and predicting the impact of therapy |
title_short | An in silico FSHD muscle fiber for modeling DUX4 dynamics and predicting the impact of therapy |
title_sort | in silico fshd muscle fiber for modeling dux4 dynamics and predicting the impact of therapy |
topic | Cell Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10287159/ https://www.ncbi.nlm.nih.gov/pubmed/37184373 http://dx.doi.org/10.7554/eLife.88345 |
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