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三维角蛋白网络的定量绘图。

Quantitative mapping of keratin networks in 3D.

机构信息

Institute of Molecular and Cellular Anatomy, RWTH Aachen University, Aachen, Germany.

Interdisciplinary Centre for Clinical Research, RWTH Aachen University, Aachen, Germany.

出版信息

Elife. 2022 Feb 18;11:e75894. doi: 10.7554/eLife.75894.

Abstract

Mechanobiology requires precise quantitative information on processes taking place in specific 3D microenvironments. Connecting the abundance of microscopical, molecular, biochemical, and cell mechanical data with defined topologies has turned out to be extremely difficult. Establishing such structural and functional 3D maps needed for biophysical modeling is a particular challenge for the cytoskeleton, which consists of long and interwoven filamentous polymers coordinating subcellular processes and interactions of cells with their environment. To date, useful tools are available for the segmentation and modeling of actin filaments and microtubules but comprehensive tools for the mapping of intermediate filament organization are still lacking. In this work, we describe a workflow to model and examine the complete 3D arrangement of the keratin intermediate filament cytoskeleton in canine, murine, and human epithelial cells both, in vitro and in vivo. Numerical models are derived from confocal airyscan high-resolution 3D imaging of fluorescence-tagged keratin filaments. They are interrogated and annotated at different length scales using different modes of visualization including immersive virtual reality. In this way, information is provided on network organization at the subcellular level including mesh arrangement, density and isotropic configuration as well as details on filament morphology such as bundling, curvature, and orientation. We show that the comparison of these parameters helps to identify, in quantitative terms, similarities and differences of keratin network organization in epithelial cell types defining subcellular domains, notably basal, apical, lateral, and perinuclear systems. The described approach and the presented data are pivotal for generating mechanobiological models that can be experimentally tested.

摘要

机械生物学需要关于特定 3D 微环境中发生的过程的精确定量信息。将显微镜、分子、生化和细胞力学数据的丰富性与定义的拓扑结构联系起来已被证明是极其困难的。建立用于生物物理建模的这种结构和功能 3D 图谱对于细胞骨架来说是一个特殊的挑战,细胞骨架由长而交织的丝状聚合物组成,协调着细胞内过程和细胞与环境的相互作用。迄今为止,已有有用的工具可用于肌动蛋白丝和微管的分割和建模,但用于中间丝组织映射的综合工具仍然缺乏。在这项工作中,我们描述了一种工作流程,用于模拟和检查犬、鼠和人上皮细胞中角蛋白中间丝细胞骨架的完整 3D 排列,包括体外和体内。数值模型是从荧光标记的角蛋白丝的共聚焦空气扫描高分辨率 3D 成像中得出的。它们在不同的长度尺度上使用不同的可视化模式进行询问和注释,包括沉浸式虚拟现实。通过这种方式,可以提供关于亚细胞水平上的网络组织的信息,包括网格排列、密度和各向同性配置以及关于丝形态的细节,如捆绑、曲率和取向。我们表明,这些参数的比较有助于以定量方式识别上皮细胞类型中角蛋白网络组织的相似性和差异性,这些上皮细胞类型定义了亚细胞区域,特别是基底、顶、侧和核周系统。所描述的方法和呈现的数据对于生成可以通过实验测试的机械生物学模型是至关重要的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0bd9/8979588/6cf38559d422/elife-75894-fig1.jpg

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