Li Jiawei, Yang Yiming, Yi Ziqi, Zhu Yu, Yang Haowei, Chen Baiming, Lobie Peter E, Ma Shaohua
Tsinghua Shenzhen International Graduate School (SIGS), Tsinghua University, Shenzhen 518055, China.
Key Laboratory of Industrial Biocatalysis, Ministry of Education, Tsinghua University, Beijing 100084, China.
Research (Wash D C). 2025 May 15;8:0699. doi: 10.34133/research.0699. eCollection 2025.
Achieving high maturity and functionality in in vitro skeletal muscle models is essential for advancing our understanding of muscle biology, disease mechanisms, and drug discovery. However, current models struggle to fully recapitulate key features such as sarcomere structure, muscle fiber composition, and contractile function while also ensuring consistency and rapid production. Adult stem cells residing in muscle tissue are known for their powerful regenerative potential, yet tissue-derived skeletal muscle organoids have not been established. In this study, we introduce droplet-engineered skeletal muscle organoids derived from primary tissue using cascade-tubing microfluidics. These droplet-engineered organoids (DEOs) exhibit high maturity, including well-developed striated sarcomeres, spontaneous and stimulated contractions, and recapitulation of parental muscle fiber types. Notably, DEOs are produced in just 8 d without the need for primary cell culture-substantially accelerating the 50- to 60-d process required by classical organoid models. Additionally, the cascade-tubing microfluidics platform enables high-throughput production of hundreds of uniform DEO replicates from a small tissue sample, providing a scalable and reproducible solution for skeletal muscle research and drug screening.
在体外骨骼肌模型中实现高成熟度和功能对于推进我们对肌肉生物学、疾病机制和药物发现的理解至关重要。然而,当前的模型难以完全重现关键特征,如肌节结构、肌纤维组成和收缩功能,同时还要确保一致性和快速生产。存在于肌肉组织中的成体干细胞以其强大的再生潜力而闻名,但源自组织的骨骼肌类器官尚未建立。在本研究中,我们介绍了使用级联微流控技术从原代组织中衍生出的液滴工程化骨骼肌类器官。这些液滴工程化类器官(DEO)表现出高成熟度,包括发育良好的横纹肌节、自发和刺激收缩,以及对亲代肌纤维类型的重现。值得注意的是,DEO只需8天即可产生,无需原代细胞培养,这大大加快了经典类器官模型所需的50至60天的过程。此外,级联微流控平台能够从小组织样本高通量生产数百个均匀的DEO复制品,为骨骼肌研究和药物筛选提供了可扩展且可重复的解决方案。