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.

Nuclear positioning facilitates amoeboid migration along the path of least resistance.

During metazoan development, immune surveillance and cancer dissemination, cells migrate in complex three-dimensional microenvironments1-3. These spaces are crowded by cells and extracellular matrix, generating mazes with differently sized gaps that are typically smaller than the diameter of the migrating cell4,5. Most mesenchymal and epithelial cells and some-but not all-cancer cells actively generate their migratory path using pericellular tissue proteolysis6. By contrast, amoeboid cells such as leukocytes use non-destructive strategies of locomotion7, raising the question how these extremely fast cells navigate through dense tissues. Here we reveal that leukocytes sample their immediate vicinity for large pore sizes, and are thereby able to choose the path of least resistance. This allows them to circumnavigate local obstacles while effectively following global directional cues such as chemotactic gradients. Pore-size discrimination is facilitated by frontward positioning of the nucleus, which enables the cells to use their bulkiest compartment as a mechanical gauge. Once the nucleus and the closely associated microtubule organizing centre pass the largest pore, cytoplasmic protrusions still lingering in smaller pores are retracted. These retractions are coordinated by dynamic microtubules; when microtubules are disrupted, migrating cells lose coherence and frequently fragment into migratory cytoplasmic pieces. As nuclear positioning in front of the microtubule organizing centre is a typical feature of amoeboid migration, our findings link the fundamental organization of cellular polarity to the strategy of locomotion.

Data science in cell imaging.

Cell imaging has entered the 'Big Data' era. New technologies in light microscopy and molecular biology have led to an explosion in high-content, dynamic and multidimensional imaging data. Similar to the 'omics' fields two decades ago, our current ability to process, visualize, integrate and mine this new generation of cell imaging data is becoming a critical bottleneck in advancing cell biology. Computation, traditionally used to quantitatively test specific hypotheses, must now also enable iterative hypothesis generation and testing by deciphering hidden biologically meaningful patterns in complex, dynamic or high-dimensional cell image data. Data science is uniquely positioned to aid in this process. In this Perspective, we survey the rapidly expanding new field of data science in cell imaging. Specifically, we highlight how data science tools are used within current image analysis pipelines, propose a computation-first approach to derive new hypotheses from cell image data, identify challenges and describe the next frontiers where we believe data science will make an impact. We also outline steps to ensure broad access to these powerful tools - democratizing infrastructure availability, developing sensitive, robust and usable tools, and promoting interdisciplinary training to both familiarize biologists with data science and expose data scientists to cell imaging.

Robust and automated detection of subcellular morphological motifs in 3D microscopy images.

Rapid developments in live-cell three-dimensional (3D) microscopy enable imaging of cell morphology and signaling with unprecedented detail. However, tools to systematically measure and visualize the intricate relationships between intracellular signaling, cytoskeletal organization and downstream cell morphological outputs do not exist. Here, we introduce u-shape3D, a computer graphics and machine-learning pipeline to probe molecular mechanisms underlying 3D cell morphogenesis and to test the intriguing possibility that morphogenesis itself affects intracellular signaling. We demonstrate a generic morphological motif detector that automatically finds lamellipodia, filopodia, blebs and other motifs. Combining motif detection with molecular localization, we measure the differential association of PIP2 and KrasV12 with blebs. Both signals associate with bleb edges, as expected for membrane-localized proteins, but only PIP2 is enhanced on blebs. This indicates that subcellular signaling processes are differentially modulated by local morphological motifs. Overall, our computational workflow enables the objective, 3D analysis of the coupling of cell shape and signaling.

Light-sheet microscopy of cleared tissues with isotropic, subcellular resolution.

We present cleared-tissue axially swept light-sheet microscopy (ctASLM), which enables isotropic, subcellular resolution imaging with high optical sectioning capability and a large field of view over a broad range of immersion media. ctASLM can image live, expanded, and both aqueous and non-aqueous chemically cleared tissue preparations. Depending on the optical configuration, ctASLM provides up to 260 nm of axial resolution, a three to tenfold improvement over confocal and other reported cleared-tissue light-sheet microscopes. We imaged millimeter-scale cleared tissues with subcellular three-dimensional resolution, which enabled automated detection of multicellular tissue architectures, individual cells, synaptic spines and rare cell-cell interactions.

Asymmetric nanotopography biases cytoskeletal dynamics and promotes unidirectional cell guidance.

Many biological and physiological processes depend upon directed migration of cells, which is typically mediated by chemical or physical gradients or by signal relay. Here we show that cells can be guided in a single preferred direction based solely on local asymmetries in nano/microtopography on subcellular scales. These asymmetries can be repeated, and thereby provide directional guidance, over arbitrarily large areas. The direction and strength of the guidance is sensitive to the details of the nano/microtopography, suggesting that this phenomenon plays a context-dependent role in vivo. We demonstrate that appropriate asymmetric nano/microtopography can unidirectionally bias internal actin polymerization waves and that cells move with the same preferred direction as these waves. This phenomenon is observed both for the pseudopod-dominated migration of the amoeboid Dictyostelium discoideum and for the lamellipod-driven migration of human neutrophils. The conservation of this mechanism across cell types and the asymmetric shape of many natural scaffolds suggest that actin-wave-based guidance is important in biology and physiology.

Proteolysis-free amoeboid migration of melanoma cells through crowded environments via bleb-driven worrying.

In crowded microenvironments, migrating cells must find or make a path. Amoeboid cells are thought to find a path by deforming their bodies to squeeze through tight spaces. Yet, some amoeboid cells seem to maintain a near-spherical morphology as they move. To examine how they do so, we visualized amoeboid human melanoma cells in dense environments and found that they carve tunnels via bleb-driven degradation of extracellular matrix components without the need for proteolytic degradation. Interactions between adhesions and collagen at the cell front induce a signaling cascade that promotes bleb enlargement via branched actin polymerization. Large blebs abrade collagen, creating feedback between extracellular matrix structure, cell morphology, and polarization that enables both path generation and persistent movement.

Cell shape dynamics: from waves to migration.

We observe and quantify wave-like characteristics of amoeboid migration. Using the amoeba Dictyostelium discoideum, a model system for the study of chemotaxis, we demonstrate that cell shape changes in a wave-like manner. Cells have regions of high boundary curvature that propagate from the leading edge toward the back, usually along alternating sides of the cell. Curvature waves are easily seen in cells that do not adhere to a surface, such as cells that are electrostatically repelled from surfaces or cells that extend over the edge of micro-fabricated cliffs. Without surface contact, curvature waves travel from the leading edge to the back of a cell at -35 µm/min. Non-adherent myosin II null cells do not exhibit these curvature waves. At the leading edge of adherent cells, curvature waves are associated with protrusive activity. Like regions of high curvature, protrusive activity travels along the boundary in a wave-like manner. Upon contact with a surface, the protrusions stop moving relative to the surface, and the boundary shape thus reflects the history of protrusive motion. The wave-like character of protrusions provides a plausible mechanism for the zig-zagging of pseudopods and for the ability of cells both to swim in viscous fluids and to navigate complex three dimensional topography.

Cellular harmonics for the morphology-invariant analysis of molecular organization at the cell surface.

The spatiotemporal organization of membrane-associated molecules is central to the regulation of cellular signals. Powerful new microscopy techniques enable the three-dimensional visualization of localization and activation of these molecules; however, the quantitative interpretation and comparison of molecular organization on the three-dimensional cell surface remains challenging because cells themselves vary greatly in morphology. Here we introduce u-signal3D, a framework to assess the spatial scales of molecular organization at the cell surface in a cell-morphology-invariant manner. We validated the framework by analyzing synthetic signaling patterns painted onto observed cell morphologies, as well as measured distributions of cytoskeletal and signaling molecules. To demonstrate the framework's versatility, we further compared the spatial organization of cell surface signals both within, and between, cell populations, and powered an upstream machine-learning-based analysis of signaling motifs.

Local and global measures of shape dynamics.

The shape and motion of cells can yield significant insights into the internal operation of a cell. We present a simple, yet versatile, framework that provides multiple metrics of cell shape and cell shape dynamics. Analysis of migrating Dictyostelium discoideum cells shows that global and local metrics highlight distinct cellular processes. For example, a global measure of shape shows rhythmic oscillations suggestive of contractions, whereas a local measure of shape shows wave-like dynamics indicative of protrusions. From a local measure of dynamic shape, or boundary motion, we extract the times and locations of protrusions and retractions. We find that protrusions zigzag, while retractions remain roughly stationary along the boundary. We do not observe any temporal relationship between protrusions and retractions. Our analysis framework also provides metrics of the boundary as whole. For example, as the cell speed increases, we find that the cell shape becomes more elongated. We also observe that while extensions and retractions have similar areas, their shapes differ.

Actin-Membrane Release Initiates Cell Protrusions.

Despite the well-established role of actin polymerization as a driving mechanism for cell protrusion, upregulated actin polymerization alone does not initiate protrusions. Using a combination of theoretical modeling and quantitative live-cell imaging experiments, we show that local depletion of actin-membrane links is needed for protrusion initiation. Specifically, we show that the actin-membrane linker ezrin is depleted prior to protrusion onset and that perturbation of ezrin's affinity for actin modulates protrusion frequency and efficiency. We also show how actin-membrane release works in concert with actin polymerization, leading to a comprehensive model for actin-driven shape changes. Actin-membrane release plays a similar role in protrusions driven by intracellular pressure. Thus, our findings suggest that protrusion initiation might be governed by a universal regulatory mechanism, whereas the mechanism of force generation determines the shape and expansion properties of the protrusion.

Machine learning based methodology to identify cell shape phenotypes associated with microenvironmental cues.

Cell morphology has been identified as a potential indicator of stem cell response to biomaterials. However, determination of cell shape phenotype in biomaterials is complicated by heterogeneous cell populations, microenvironment heterogeneity, and multi-parametric definitions of cell morphology. To associate cell morphology with cell-material interactions, we developed a shape phenotyping framework based on support vector machines. A feature selection procedure was implemented to select the most significant combination of cell shape metrics to build classifiers with both accuracy and stability to identify and predict microenvironment-driven morphological differences in heterogeneous cell populations. The analysis was conducted at a multi-cell level, where a "supercell" method used average shape measurements of small groups of single cells to account for heterogeneous populations and microenvironment. A subsampling validation algorithm revealed the range of supercell sizes and sample sizes needed for classifier stability and generalization capability. As an example, the responses of human bone marrow stromal cells (hBMSCs) to fibrous vs flat microenvironments were compared on day 1. Our analysis showed that 57 cells (grouped into supercells of size 4) are the minimum needed for phenotyping. The analysis identified that a combination of minor axis length, solidity, and mean negative curvature were the strongest early shape-based indicator of hBMSCs response to fibrous microenvironment.

Quantitative Multiscale Cell Imaging in Controlled 3D Microenvironments.

The microenvironment determines cell behavior, but the underlying molecular mechanisms are poorly understood because quantitative studies of cell signaling and behavior have been challenging due to insufficient spatial and/or temporal resolution and limitations on microenvironmental control. Here we introduce microenvironmental selective plane illumination microscopy (meSPIM) for imaging and quantification of intracellular signaling and submicrometer cellular structures as well as large-scale cell morphological and environmental features. We demonstrate the utility of this approach by showing that the mechanical properties of the microenvironment regulate the transition of melanoma cells from actin-driven protrusion to blebbing, and we present tools to quantify how cells manipulate individual collagen fibers. We leverage the nearly isotropic resolution of meSPIM to quantify the local concentration of actin and phosphatidylinositol 3-kinase signaling on the surfaces of cells deep within 3D collagen matrices and track the many small membrane protrusions that appear in these more physiologically relevant environments.

Quantifying Modes of 3D Cell Migration.

Although it is widely appreciated that cells migrate in a variety of diverse environments in vivo, we are only now beginning to use experimental workflows that yield images with sufficient spatiotemporal resolution to study the molecular processes governing cell migration in 3D environments. Since cell migration is a dynamic process, it is usually studied via microscopy, but 3D movies of 3D processes are difficult to interpret by visual inspection. In this review, we discuss the technologies required to study the diversity of 3D cell migration modes with a focus on the visualization and computational analysis tools needed to study cell migration quantitatively at a level comparable to the analyses performed today on cells crawling on flat substrates.

Spatiotemporal relationships between the cell shape and the actomyosin cortex of periodically protruding cells.

We investigate the dynamics of cell shape and analyze the actin and myosin distributions of cells exhibiting cortical density traveling waves. These waves propagate by repeated cycles of cortical compression (folding) and dilation (unfolding) that lead to periodic protrusions (oscillations) of the cell boundary. The focus of our detailed analysis is the remarkable periodicity of this phenotype, in which both the overall shape transformation and distribution of actomyosin density are repeated from cycle to cycle even though the characteristics of the shape transformation vary significantly for different regions of the cell. We show, using correlation analysis, that during traveling wave propagation cortical actin and plasma membrane densities are tightly coupled at each point along the cell periphery. We also demonstrate that the major protrusion appears at the wave trailing edge just after the actin cortex density has reached a maximum. Making use of the extraordinary periodicity, we employ latrunculin to demonstrate that sequestering actin monomers can have two distinct effects: low latrunculin concentrations can trigger and enhance traveling waves but higher concentrations of this drug retard the waves. The fundamental mechanism underlying this periodically protruding phenotype, involving folding and unfolding of the cortex-membrane couple, is likely to hold important clues for diverse phenomena including cell division and amoeboid-type migration.

Cellular contact guidance through dynamic sensing of nanotopography.

We investigate the effects of surface nanotopography on the migration and cell shape dynamics of the amoeba Dictyostelium discoideum. Multiple prior studies have implicated the patterning of focal adhesions in contact guidance. However, we observe significant contact guidance of Dictyostelium along surfaces with nanoscale ridges or grooves, even though this organism lacks integrin-based adhesions. Cells that move parallel to nanoridges are faster, more protrusive at their fronts, and more elongated than are cells that move perpendicular to nanoridges. Quantitative studies show that nanoridges spaced 1.5 µm apart exhibit the greatest contact guidance efficiency. Because Dictyostelium cells exhibit oscillatory shape dynamics, we model contact guidance as a process in which stochastic cellular harmonic oscillators couple to the periodicity of the nanoridges. In support of this connection, we find that nanoridges nucleate actin polymerization waves of nanoscale width that propagate parallel to the nanoridges.

Automated image analysis of nuclear shape: what can we learn from a prematurely aged cell?

The premature aging disorder, Hutchinson-Gilford progeria syndrome (HGPS), is caused by mutant lamin A, which affects the nuclear scaffolding. The phenotypic hallmark of HGPS is nuclear blebbing. Interestingly, similar nuclear blebbing has also been observed in aged cells from healthy individuals. Recent work has shown that treatment with rapamycin, an inhibitor of the mTOR pathway, reduced nuclear blebbing in HGPS fibroblasts. However, the extent of blebbing varies considerably within each cell population, which makes manual blind counting challenging and subjective. Here, we show a novel, automated and high throughput nuclear shape analysis that quantitatively measures curvature, area, perimeter, eccentricity and additional metrics of nuclear morphology for large populations of cells. We examined HGPS fibroblast cells treated with rapamycin and RAD001 (an analog to rapamycin). Our analysis shows that treatment with RAD001 and rapamycin reduces nuclear blebbing, consistent with blind counting controls. In addition, we find that rapamycin treatment reduces the area of the nucleus, but leaves the eccentricity unchanged. Our nuclear shape analysis provides an unbiased, multidimensional "fingerprint" for a population of cells, which can be used to quantify treatment efficacy and analyze cellular aging.