Three-dimensional Tissue Engineered Skeletal Muscle Modelling Facioscapulohumeral Muscular Dystrophy
Brain a journal of neurology(2024)
摘要
Facioscapulohumeral muscular dystrophy (FSHD) is caused by sporadic misexpression of the transcription factor double homeobox 4 (DUX4) in skeletal muscles. So far, monolayer cultures and animal models have been used to study the FSHD disease mechanism and for FSHD therapy development, but these models do not fully recapitulate the disease and there is a lack of knowledge on how DUX4 misexpression leads to skeletal muscle dysfunction. To overcome these barriers, we have developed a three-dimensional tissue engineered skeletal muscle (3D-TESM) model by generating genetically matched myogenic progenitors (MPs) from human induced pluripotent stem cells of three mosaic FSHD patients. 3D-TESMs derived from genetically affected MPs recapitulate pathological features including DUX4 and DUX4 target gene expression, smaller myofiber diameters, and reduced absolute forces upon electrical stimulation. RNA sequencing data illustrates increased expression of DUX4 target genes in 3D-TESMs compared to two-dimensional (2D) myotubes, and cellular differentiation was improved by 3D culture conditions. Treatment of 3D-TESMs with three different small molecules identified in drug development screens in 2D muscle cultures showed no improvements, and sometimes even declines, in contractile force and sarcomere organization. These results suggest that these compounds either have a detrimental effect on the formation of 3D-TESMs, an effect that might have been overlooked or was challenging to detect in 2D cultures and in vivo models, and/or that further development of the 3D-TESM model is needed. In conclusion, we have developed a 3D skeletal muscle model for FSHD that can be employed for preclinical research focusing on DUX4 expression and downstream pathways of FSHD in relation to contractile properties. In the future, we expect that this model can also be used for preclinical drug screening.
更多查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
数据免责声明
页面数据均来自互联网公开来源、合作出版商和通过AI技术自动分析结果,我们不对页面数据的有效性、准确性、正确性、可靠性、完整性和及时性做出任何承诺和保证。若有疑问,可以通过电子邮件方式联系我们:report@aminer.cn