Surface-guided computing to analyze subcellular morphology and membrane-associated signals in 3D

Abstract

Signal transduction and cell function are governed by the spatiotemporal organization of membrane-associated molecules. Despite significant advances in visualizing molecular distributions by 3D light microscopy, cell biologists still have limited quantitative understanding of the processes implicated in the regulation of molecular signals at the whole cell scale. In particular, complex and transient cell surface morphologies challenge the complete sampling of cell geometry, membrane-associated molecular concentration and activity and the computing of meaningful parameters such as the cofluctuation between morphology and signals. Here, we introduce u-Unwrap3D, a framework to remap arbitrarily complex 3D cell surfaces and membrane-associated signals into equivalent lower dimensional representations. The mappings are bidirectional, allowing the application of image processing operations in the data representation best suited for the task and to subsequently present the results in any of the other representations, including the original 3D cell surface. Leveraging this surface-guided computing paradigm, we track segmented surface motifs in 2D to quantify the recruitment of Septin polymers by blebbing events; we quantify actin enrichment in peripheral ruffles; and we measure the speed of ruffle movement along topographically complex cell surfaces. Thus, u-Unwrap3D provides access to spatiotemporal analyses of cell biological parameters on unconstrained 3D surface geometries and signals.

Geometric changes in the nucleoids of Deinococcus radiodurans reveal involvement of new proteins in recovery from ionizing radiation

“…This phenotype appears similar to blebbing behavior, typically seen in mammalian cells under apoptosis, stem-cell differentiation, and other “cell-fate” determination states [52]. While quantitative determination of blebbing for the purpose of tracking signaling pathway activation has occurred in mammalian cells [53–55], this method of spatiotemporal organization analysis has not yet been utilized in bacteria. These results warrant further exploration as they may provide insight into potential signaling pathways in Deinococcus under IR stress.…”

“…While quantitative determination of blebbing for the purpose of tracking signaling pathway activation has occurred in mammalian cells [53][54][55], this method of spatiotemporal organization analysis has not yet been utilized in bacteria. These results warrant further exploration as they may provide insight into potential signaling pathways in Deinococcus under IR stress.…”

A general algorithm for consensus 3D cell segmentation from 2D segmented stacks

“…Surface meshes in Fig. 5 were extracted using u-Unwrap3D 15 and visualized using MeshLab 130 . Rotating surface mesh movies were created using ChimeraX 131 .…”

“…length, area, and volume) and molecular expression (e.g. mean marker expression 12 , subcellular patterns 13 ) to perform comparative analyses or in downstream processing such as surface unwrapping 14,15 .…”

“…length, area, and volume) and molecular expression (e.g. mean marker expression 12 , subcellular patterns 13 ) to perform comparative analyses or in downstream processing such as surface unwrapping 14,15 .Segmentation is easy when cells are isolated, well-contrasted and uniformly illuminated, and amenable to binary intensity thresholding and connected component analysis 16 . However, this is rare.…”