Suppr超能文献

监测肌节网络的成熟:基于超分辨率显微镜的方法。

Monitoring the maturation of the sarcomere network: a super-resolution microscopy-based approach.

机构信息

Department of Cardiac Surgery, Reference and Translation Center for Cardiac Stem Cell Therapy (RTC), Rostock University Medical Center, 18057, Rostock, Germany.

Faculty of Interdisciplinary Research, Department Life, Light and Matter, University Rostock, 18059, Rostock, Germany.

出版信息

Cell Mol Life Sci. 2022 Feb 23;79(3):149. doi: 10.1007/s00018-022-04196-3.

Abstract

The in vitro generation of human cardiomyocytes derived from induced pluripotent stem cells (iPSC) is of great importance for cardiac disease modeling, drug-testing applications and for regenerative medicine. Despite the development of various cultivation strategies, a sufficiently high degree of maturation is still a decisive limiting factor for the successful application of these cardiac cells. The maturation process includes, among others, the proper formation of sarcomere structures, mediating the contraction of cardiomyocytes. To precisely monitor the maturation of the contractile machinery, we have established an imaging-based strategy that allows quantitative evaluation of important parameters, defining the quality of the sarcomere network. iPSC-derived cardiomyocytes were subjected to different culture conditions to improve sarcomere formation, including prolonged cultivation time and micro patterned surfaces. Fluorescent images of α-actinin were acquired using super-resolution microscopy. Subsequently, we determined cell morphology, sarcomere density, filament alignment, z-Disc thickness and sarcomere length of iPSC-derived cardiomyocytes. Cells from adult and neonatal heart tissue served as control. Our image analysis revealed a profound effect on sarcomere content and filament orientation when iPSC-derived cardiomyocytes were cultured on structured, line-shaped surfaces. Similarly, prolonged cultivation time had a beneficial effect on the structural maturation, leading to a more adult-like phenotype. Automatic evaluation of the sarcomere filaments by machine learning validated our data. Moreover, we successfully transferred this approach to skeletal muscle cells, showing an improved sarcomere formation cells over different differentiation periods. Overall, our image-based workflow can be used as a straight-forward tool to quantitatively estimate the structural maturation of contractile cells. As such, it can support the establishment of novel differentiation protocols to enhance sarcomere formation and maturity.

摘要

体外生成源自诱导多能干细胞(iPSC)的人心肌细胞对于心脏疾病建模、药物测试应用和再生医学非常重要。尽管已经开发了各种培养策略,但成熟度仍然是成功应用这些心肌细胞的决定性限制因素。成熟过程包括肌节结构的适当形成,介导心肌细胞的收缩。为了精确监测收缩机制的成熟,我们建立了一种基于成像的策略,允许对定义肌节网络质量的重要参数进行定量评估。将 iPSC 衍生的心肌细胞置于不同的培养条件下,以改善肌节形成,包括延长培养时间和微图案化表面。使用超分辨率显微镜获取肌球蛋白重链的荧光图像。随后,我们确定了 iPSC 衍生的心肌细胞的细胞形态、肌节密度、纤维排列、Z 盘厚度和肌节长度。成年和新生儿心脏组织的细胞作为对照。我们的图像分析表明,当 iPSC 衍生的心肌细胞在结构化的线状表面上培养时,对肌节含量和纤维取向有深远的影响。同样,延长培养时间对结构成熟也有有益的影响,导致更接近成人的表型。通过机器学习对肌节纤维进行自动评估验证了我们的数据。此外,我们成功地将这种方法转移到骨骼肌细胞上,显示出在不同分化阶段,肌节形成细胞得到改善。总的来说,我们基于图像的工作流程可作为一种简单的工具,用于定量估计收缩细胞的结构成熟度。因此,它可以支持建立新的分化方案,以增强肌节形成和成熟。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/39c4/11071788/79448ae4c9ba/18_2022_4196_Fig1_HTML.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验