School of Biosciences, Cardiff University, Cardiff, Wales, UK.
School of Optometry and Vision Sciences, Cardiff University, Cardiff, Wales, UK.
J Biophotonics. 2021 Jan;14(1):e202000202. doi: 10.1002/jbio.202000202. Epub 2020 Oct 23.
Computational models of cellular structures generally rely on simplifying approximations and assumptions that limit biological accuracy. This study presents a comprehensive image processing pipeline for creating unified three-dimensional (3D) reconstructions of the cell cytoskeletal networks and nuclei. Confocal image stacks of these cellular structures were reconstructed to 3D isosurfaces (Imaris), then tessellations were simplified to reduce the number of elements in initial meshes by applying quadric edge collapse decimation with preserved topology boundaries (MeshLab). Geometries were remeshed to ensure uniformity (Instant Meshes) and the resulting 3D meshes exported (ABAQUS) for downstream application. The protocol has been applied successfully to fibroblast cytoskeletal reorganisation in the scleral connective tissue of the eye, under mechanical load that mimics internal eye pressure. While the method herein is specifically employed to reconstruct immunofluorescent confocal imaging data, it is also more widely applicable to other biological imaging modalities where accurate 3D cell structures are required.
细胞结构的计算模型通常依赖于简化的近似和假设，这些假设限制了生物学的准确性。本研究提出了一种全面的图像处理管道，用于创建细胞细胞骨架网络和核的统一三维（3D）重建。对这些细胞结构的共聚焦图像堆栈进行了 3D 等距曲面重建（Imaris），然后通过应用保留拓扑边界的二次边折叠细化来简化细分，以减少初始网格中的元素数量（MeshLab）。对几何形状进行重新网格化以确保均匀性（Instant Meshes），并将生成的 3D 网格导出（ABAQUS）用于下游应用。该方案已成功应用于模仿眼内压的机械负荷下巩膜结缔组织中纤维母细胞细胞骨架的重组。虽然本文中使用的方法专门用于重建免疫荧光共焦成像数据，但它也更广泛地适用于需要准确 3D 细胞结构的其他生物成像模式。
