3D immuno-confocal image reconstruction of fibroblast cytoskeleton and nucleus architecture

Abstract

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.