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Using computer simulation models to investigate the most promising microRNAs to improve muscle regeneration during ageing

MicroRNAs (miRNAs) regulate gene expression through interactions with target sites within mRNAs, leading to enhanced degradation of the mRNA or inhibition of translation. Skeletal muscle expresses many different miRNAs with important roles in adulthood myogenesis (regeneration) and myofibre hypertro...

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Autores principales: Proctor, Carole J., Goljanek-Whysall, Katarzyna
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5614911/
https://www.ncbi.nlm.nih.gov/pubmed/28951568
http://dx.doi.org/10.1038/s41598-017-12538-6
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author Proctor, Carole J.
Goljanek-Whysall, Katarzyna
author_facet Proctor, Carole J.
Goljanek-Whysall, Katarzyna
author_sort Proctor, Carole J.
collection PubMed
description MicroRNAs (miRNAs) regulate gene expression through interactions with target sites within mRNAs, leading to enhanced degradation of the mRNA or inhibition of translation. Skeletal muscle expresses many different miRNAs with important roles in adulthood myogenesis (regeneration) and myofibre hypertrophy and atrophy, processes associated with muscle ageing. However, the large number of miRNAs and their targets mean that a complex network of pathways exists, making it difficult to predict the effect of selected miRNAs on age-related muscle wasting. Computational modelling has the potential to aid this process as it is possible to combine models of individual miRNA:target interactions to form an integrated network. As yet, no models of these interactions in muscle exist. We created the first model of miRNA:target interactions in myogenesis based on experimental evidence of individual miRNAs which were next validated and used to make testable predictions. Our model confirms that miRNAs regulate key interactions during myogenesis and can act by promoting the switch between quiescent/proliferating/differentiating myoblasts and by maintaining the differentiation process. We propose that a threshold level of miR-1 acts in the initial switch to differentiation, with miR-181 keeping the switch on and miR-378 maintaining the differentiation and miR-143 inhibiting myogenesis.
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spelling pubmed-56149112017-10-11 Using computer simulation models to investigate the most promising microRNAs to improve muscle regeneration during ageing Proctor, Carole J. Goljanek-Whysall, Katarzyna Sci Rep Article MicroRNAs (miRNAs) regulate gene expression through interactions with target sites within mRNAs, leading to enhanced degradation of the mRNA or inhibition of translation. Skeletal muscle expresses many different miRNAs with important roles in adulthood myogenesis (regeneration) and myofibre hypertrophy and atrophy, processes associated with muscle ageing. However, the large number of miRNAs and their targets mean that a complex network of pathways exists, making it difficult to predict the effect of selected miRNAs on age-related muscle wasting. Computational modelling has the potential to aid this process as it is possible to combine models of individual miRNA:target interactions to form an integrated network. As yet, no models of these interactions in muscle exist. We created the first model of miRNA:target interactions in myogenesis based on experimental evidence of individual miRNAs which were next validated and used to make testable predictions. Our model confirms that miRNAs regulate key interactions during myogenesis and can act by promoting the switch between quiescent/proliferating/differentiating myoblasts and by maintaining the differentiation process. We propose that a threshold level of miR-1 acts in the initial switch to differentiation, with miR-181 keeping the switch on and miR-378 maintaining the differentiation and miR-143 inhibiting myogenesis. Nature Publishing Group UK 2017-09-26 /pmc/articles/PMC5614911/ /pubmed/28951568 http://dx.doi.org/10.1038/s41598-017-12538-6 Text en © The Author(s) 2017 https://creativecommons.org/licenses/by/4.0/ Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Proctor, Carole J.
Goljanek-Whysall, Katarzyna
Using computer simulation models to investigate the most promising microRNAs to improve muscle regeneration during ageing
title Using computer simulation models to investigate the most promising microRNAs to improve muscle regeneration during ageing
title_full Using computer simulation models to investigate the most promising microRNAs to improve muscle regeneration during ageing
title_fullStr Using computer simulation models to investigate the most promising microRNAs to improve muscle regeneration during ageing
title_full_unstemmed Using computer simulation models to investigate the most promising microRNAs to improve muscle regeneration during ageing
title_short Using computer simulation models to investigate the most promising microRNAs to improve muscle regeneration during ageing
title_sort using computer simulation models to investigate the most promising micrornas to improve muscle regeneration during ageing
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5614911/
https://www.ncbi.nlm.nih.gov/pubmed/28951568
http://dx.doi.org/10.1038/s41598-017-12538-6
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