Blebs promote cell survival by assembling oncogenic signalling hubs.

Most human cells require anchorage for survival. Cell-substrate adhesion activates diverse signalling pathways, without which cells undergo anoikis-a form of programmed cell death1. Acquisition of anoikis resistance is a pivotal step in cancer disease progression, as metastasizing cells often lose firm attachment to surrounding tissue2,3. In these poorly attached states, cells adopt rounded morphologies and form small hemispherical plasma membrane protrusions called blebs4-11. Bleb function has been thoroughly investigated in the context of amoeboid migration, but it has been examined far less in other scenarios12. Here we show by three-dimensional imaging and manipulation of cell morphological states that blebbing triggers the formation of plasma membrane-proximal signalling hubs that confer anoikis resistance. Specifically, in melanoma cells, blebbing generates plasma membrane contours that recruit curvature-sensing septin proteins as scaffolds for constitutively active mutant NRAS and effectors. These signalling hubs activate ERK and PI3K-well-established promoters of pro-survival pathways. Inhibition of blebs or septins has little effect on the survival of well-adhered cells, but in detached cells it causes NRAS mislocalization, reduced MAPK and PI3K activity, and ultimately, death. This unveils a morphological requirement for mutant NRAS to operate as an effective oncoprotein. Furthermore, whereas some BRAF-mutated melanoma cells do not rely on this survival pathway in a basal state, inhibition of BRAF and MEK strongly sensitizes them to both bleb and septin inhibition. Moreover, fibroblasts engineered to sustain blebbing acquire the same anoikis resistance as cancer cells even without harbouring oncogenic mutations. Thus, blebs are potent signalling organelles capable of integrating myriad cellular information flows into concerted cellular responses, in this case granting robust anoikis resistance.

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

Cell segmentation is the fundamental task. Only by segmenting, can we define the quantitative spatial unit for collecting measurements to draw biological conclusions. Deep learning has revolutionized 2D cell segmentation, enabling generalized solutions across cell types and imaging modalities. This has been driven by the ease of scaling up image acquisition, annotation and computation. However 3D cell segmentation, which requires dense annotation of 2D slices still poses significant challenges. Labelling every cell in every 2D slice is prohibitive. Moreover it is ambiguous, necessitating cross-referencing with other orthoviews. Lastly, there is limited ability to unambiguously record and visualize 1000's of annotated cells. Here we develop a theory and toolbox, u-Segment3D for 2D-to-3D segmentation, compatible with any 2D segmentation method. Given optimal 2D segmentations, u-Segment3D generates the optimal 3D segmentation without data training, as demonstrated on 11 real life datasets, >70,000 cells, spanning single cells, cell aggregates and tissue.

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

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.

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

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.

Increasing the field-of-view in oblique plane microscopy via optical tiling.

Fast volumetric imaging of large fluorescent samples with high-resolution is required for many biological applications. Oblique plane microscopy (OPM) provides high spatiotemporal resolution, but the field of view is typically limited by its optical train and the pixel number of the camera. Mechanically scanning the sample or decreasing the overall magnification of the imaging system can partially address this challenge, albeit by reducing the volumetric imaging speed or spatial resolution, respectively. Here, we introduce a novel dual-axis scan unit for OPM that facilitates rapid and high-resolution volumetric imaging throughout a volume of 800 × 500 × 200 microns. This enables us to perform volumetric imaging of cell monolayers, spheroids and zebrafish embryos with subcellular resolution. Furthermore, we combined this microscope with a multi-perspective projection imaging technique that increases the volumetric interrogation rate to more than 10 Hz. This allows us to rapidly probe a large field of view in a dimensionality reduced format, identify features of interest, and volumetrically image these regions with high spatiotemporal resolution.

The mitotic exit network regulates the spatiotemporal activity of Cdc42 to maintain cell size.

During G1 in budding yeast, the Cdc42 GTPase establishes a polar front, along which actin is recruited to direct secretion for bud formation. Cdc42 localizes at the bud cortex and then redistributes between mother and daughter in anaphase. The molecular mechanisms that terminate Cdc42 bud-localized activity during mitosis are poorly understood. We demonstrate that the activity of the Cdc14 phosphatase, released through the mitotic exit network, is required for Cdc42 redistribution between mother and bud. Induced Cdc14 nucleolar release results in premature Cdc42 redistribution between mother and bud. Inhibition of Cdc14 causes persistence of Cdc42 bud localization, which perturbs normal cell size and spindle positioning. Bem3, a Cdc42 GAP, binds Cdc14 and is dephosphorylated at late anaphase in a Cdc14-dependent manner. We propose that Cdc14 dephosphorylates and activates Bem3 to allow Cdc42 inactivation and redistribution. Our results uncover a mechanism through which Cdc14 regulates the spatiotemporal activity of Cdc42 to maintain normal cell size at cytokinesis.

Prolonged cyclin-dependent kinase inhibition results in septin perturbations during return to growth and mitosis.

We investigated how Saccharomyces cerevisiae coordinate polarization, budding, and anaphase during a unique developmental program called return to growth (RTG) in which cells in meiosis return to mitosis upon nutrient shift. Cells reentering mitosis from prophase I deviate from the normal cell cycle by budding in G2 instead of G1. We found that cells do not maintain the bipolar budding pattern, a characteristic of diploid cells. Furthermore, strict temporal regulation of M-phase cyclin-dependent kinase (CDK; M-CDK) is important for polarity establishment and morphogenesis. Cells with premature M-CDK activity caused by loss of checkpoint kinase Swe1 failed to polarize and underwent anaphase without budding. Mutants with increased Swe1-dependent M-CDK inhibition showed additional or more penetrant phenotypes in RTG than mitosis, including elongated buds, multiple buds, spindle mispositioning, and septin perturbation. Surprisingly, the enhanced and additional phenotypes were not exclusive to RTG but also occurred with prolonged Swe1-dependent CDK inhibition in mitosis. Our analysis reveals that prolonged activation of the Swe1-dependent checkpoint can be detrimental instead of beneficial.