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人类骨骼肌细胞的细胞形态特征作为成肌能力的预测指标:精准细胞治疗的新范式。

Cell shape characteristics of human skeletal muscle cells as a predictor of myogenic competency: A new paradigm towards precision cell therapy.

作者信息

Desprez Charlotte, Danovi Davide, Knowles Charles H, Day Richard M

机构信息

Centre for Precision Healthcare, UCL Division of Medicine, University College London, London, UK.

Department of Digestive Physiology, Rouen University Hospital, Rouen, France.

出版信息

J Tissue Eng. 2023 Mar 16;14:20417314221139794. doi: 10.1177/20417314221139794. eCollection 2023 Jan-Dec.

Abstract

Skeletal muscle-derived cells (SMDC) hold tremendous potential for replenishing dysfunctional muscle lost due to disease or trauma. Current therapeutic usage of SMDC relies on harvesting autologous cells from muscle biopsies that are subsequently expanded in vitro before re-implantation into the patient. Heterogeneity can arise from multiple factors including quality of the starting biopsy, age and comorbidity affecting the processed SMDC. Quality attributes intended for clinical use often focus on minimum levels of myogenic cell marker expression. Such approaches do not evaluate the likelihood of SMDC to differentiate and form myofibres when implanted in vivo, which ultimately determines the likelihood of muscle regeneration. Predicting the therapeutic potency of SMDC in vitro prior to implantation is key to developing successful therapeutics in regenerative medicine and reducing implementation costs. Here, we report on the development of a novel SMDC profiling tool to examine populations of cells in vitro derived from different donors. We developed an image-based pipeline to quantify morphological features and extracted cell shape descriptors. We investigated whether these could predict heterogeneity in the formation of myotubes and correlate with the myogenic fusion index. Several of the early cell shape characteristics were found to negatively correlate with the fusion index. These included total area occupied by cells, area shape, bounding box area, compactness, equivalent diameter, minimum ferret diameter, minor axis length and perimeter of SMDC at 24 h after initiating culture. The information extracted with our approach indicates live cell imaging can detect a range of cell phenotypes based on cell-shape alone and preserving cell integrity could be used to predict propensity to form myotubes in vitro and functional tissue in vivo.

摘要

骨骼肌衍生细胞(SMDC)在补充因疾病或创伤而丧失功能的肌肉方面具有巨大潜力。目前SMDC的治疗用途依赖于从肌肉活检中采集自体细胞,随后在体外进行扩增,然后再植入患者体内。异质性可能由多种因素引起,包括起始活检的质量、影响处理后的SMDC的年龄和合并症。临床使用的质量属性通常侧重于肌源性细胞标志物表达的最低水平。这些方法没有评估SMDC在体内植入时分化并形成肌纤维的可能性,而这最终决定了肌肉再生的可能性。在植入前体外预测SMDC的治疗效力是再生医学中开发成功疗法并降低实施成本的关键。在此,我们报告了一种新型SMDC分析工具的开发,用于体外检测来自不同供体的细胞群体。我们开发了一种基于图像的流程来量化形态特征并提取细胞形状描述符。我们研究了这些是否可以预测肌管形成中的异质性并与肌源性融合指数相关。发现几个早期细胞形状特征与融合指数呈负相关。这些包括培养开始后24小时时细胞占据的总面积、面积形状、边界框面积、紧凑度、等效直径、最小雪貂直径、短轴长度和SMDC的周长。我们的方法提取的信息表明,活细胞成像仅基于细胞形状就可以检测一系列细胞表型,并且保持细胞完整性可用于预测体外形成肌管和体内功能组织的倾向。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d65/10026113/ad0cbd5c39fc/10.1177_20417314221139794-fig1.jpg

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