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.

Prolonged Cell Cycle Arrest in Response to DNA damage in Yeast Requires the Maintenance of DNA Damage Signaling and the Spindle Assembly Checkpoint.

Cells evoke the DNA damage checkpoint (DDC) to inhibit mitosis in the presence of DNA double-strand breaks (DSBs) to allow more time for DNA repair. In budding yeast, a single irreparable DSB is sufficient to activate the DDC and induce cell cycle arrest prior to anaphase for about 12 to 15 hours, after which cells "adapt" to the damage by extinguishing the DDC and resuming the cell cycle. While activation of the DNA damage-dependent cell cycle arrest is well-understood, how it is maintained remains unclear. To address this, we conditionally depleted key DDC proteins after the DDC was fully activated and monitored changes in the maintenance of cell cycle arrest. Degradation of Ddc2ATRIP, Rad9, Rad24, or Rad53CHK2 results in premature resumption of the cell cycle, indicating that these DDC factors are required both to establish and to maintain the arrest. Dun1 is required for establishment, but not maintenance of arrest, whereas Chk1 is required for prolonged maintenance but not for initial establishment of the mitotic arrest. When the cells are challenged with 2 persistent DSBs, they remain permanently arrested. This permanent arrest is initially dependent on the continuous presence of Ddc2 and Rad53; however, after 15 hours both proteins become dispensable. Instead, the continued mitotic arrest is sustained by spindle-assembly checkpoint (SAC) proteins Mad1, Mad2, and Bub2 but not by Bub2's binding partner Bfa1. These data suggest that prolonged cell cycle arrest in response to 2 DSBs is achieved by a handoff from the DDC to specific components of the SAC. Furthermore, the establishment and maintenance of DNA damage-induced cell cycle arrest requires overlapping but different sets of factors.

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.

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.

Human ZBP1 induces cell death-independent inflammatory signaling via RIPK3 and RIPK1.

ZBP1 is an interferon-induced cytosolic nucleic acid sensor that facilitates antiviral responses via RIPK3. Although ZBP1-mediated programmed cell death is widely described, whether and how it promotes inflammatory signaling is unclear. Here, we report a ZBP1-induced inflammatory signaling pathway mediated by K63- and M1-linked ubiquitin chains, which depends on RIPK1 and RIPK3 as scaffolds independently of cell death. In human HT29 cells, ZBP1 associated with RIPK1 and RIPK3 as well as ubiquitin ligases cIAP1 and LUBAC. ZBP1-induced K63- and M1-linked ubiquitination of RIPK1 and ZBP1 to promote TAK1- and IKK-mediated inflammatory signaling and cytokine production. Inhibition of caspase activity suppressed ZBP1-induced cell death but enhanced cytokine production in a RIPK1- and RIPK3 kinase activity-dependent manner. Lastly, we provide evidence that ZBP1 signaling contributes to SARS-CoV-2-induced cytokine production. Taken together, we describe a ZBP1-RIPK3-RIPK1-mediated inflammatory signaling pathway relayed by the scaffolding role of RIPKs and regulated by caspases, which may induce inflammation when ZBP1 is activated below the threshold needed to trigger a cell death response.

Centriole distal-end proteins CP110 and Cep97 influence centriole cartwheel growth at the proximal end.

Centrioles are composed of a central cartwheel tethered to nine-fold symmetric microtubule (MT) blades. The centriole cartwheel and MTs are thought to grow from opposite ends of these organelles, so it is unclear how they coordinate their assembly. We previously showed that in Drosophila embryos an oscillation of Polo-like kinase 4 (Plk4) helps to initiate and time the growth of the cartwheel at the proximal end. Here, in the same model, we show that CP110 and Cep97 form a complex close to the distal-end of the centriole MTs whose levels rise and fall as the new centriole MTs grow, in a manner that appears to be entrained by the core cyclin-dependent kinase (Cdk)-Cyclin oscillator that drives the nuclear divisions in these embryos. These CP110 and Cep97 dynamics, however, do not appear to time the period of centriole MT growth directly. Instead, we find that changing the levels of CP110 and Cep97 appears to alter the Plk4 oscillation and the growth of the cartwheel at the proximal end. These findings reveal an unexpected potential crosstalk between factors normally concentrated at opposite ends of the growing centrioles, which might help to coordinate centriole growth. This article has an associated First Person interview with the first authors of the paper.

Centrioles generate a local pulse of Polo/PLK1 activity to initiate mitotic centrosome assembly.

Mitotic centrosomes are formed when centrioles start to recruit large amounts of pericentriolar material (PCM) around themselves in preparation for mitosis. This centrosome "maturation" requires the centrioles and also Polo/PLK1 protein kinase. The PCM comprises several hundred proteins and, in Drosophila, Polo cooperates with the conserved centrosome proteins Spd-2/CEP192 and Cnn/CDK5RAP2 to assemble a PCM scaffold around the mother centriole that then recruits other PCM client proteins. We show here that in Drosophila syncytial blastoderm embryos, centrosomal Polo levels rise and fall during the assembly process-peaking, and then starting to decline, even as levels of the PCM scaffold continue to rise and plateau. Experiments and mathematical modelling indicate that a centriolar pulse of Polo activity, potentially generated by the interaction between Polo and its centriole receptor Ana1 (CEP295 in humans), could explain these unexpected scaffold assembly dynamics. We propose that centrioles generate a local pulse of Polo activity prior to mitotic entry to initiate centrosome maturation, explaining why centrioles and Polo/PLK1 are normally essential for this process.

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.

An Autonomous Oscillation Times and Executes Centriole Biogenesis.

The accurate timing and execution of organelle biogenesis is crucial for cell physiology. Centriole biogenesis is regulated by Polo-like kinase 4 (Plk4) and initiates in S-phase when a daughter centriole grows from the side of a pre-existing mother. Here, we show that a Plk4 oscillation at the base of the growing centriole initiates and times centriole biogenesis to ensure that centrioles grow at the right time and to the right size. The Plk4 oscillation is normally entrained to the cell-cycle oscillator but can run autonomously of it-potentially explaining why centrioles can duplicate independently of cell-cycle progression. Mathematical modeling indicates that the Plk4 oscillation can be generated by a time-delayed negative feedback loop in which Plk4 inactivates the interaction with its centriolar receptor through multiple rounds of phosphorylation. We hypothesize that similar organelle-specific oscillations could regulate the timing and execution of organelle biogenesis more generally.

Visualization of T Cell Migration in the Spleen Reveals a Network of Perivascular Pathways that Guide Entry into T Zones.

Lymphocyte homeostasis and immune surveillance require that T and B cells continuously recirculate between secondary lymphoid organs. Here, we used intravital microscopy to define lymphocyte trafficking routes within the spleen, an environment of open blood circulation and shear forces unlike other lymphoid organs. Upon release from arterioles into the red pulp sinuses, T cells latched onto perivascular stromal cells in a manner that was independent of the chemokine receptor CCR7 but sensitive to Gi protein-coupled receptor inhibitors. This latching sheltered T cells from blood flow and enabled unidirectional migration to the bridging channels and then to T zones, entry into which required CCR7. Inflammatory responses modified the chemotactic cues along the perivascular homing paths, leading to rapid block of entry. Our findings reveal a role for vascular structures in lymphocyte recirculation through the spleen, indicating the existence of separate entry and exit routes and that of a checkpoint located at the gate to the T zone.

Motion sensing superpixels (MOSES) is a systematic computational framework to quantify and discover cellular motion phenotypes.

Correct cell/cell interactions and motion dynamics are fundamental in tissue homeostasis, and defects in these cellular processes cause diseases. Therefore, there is strong interest in identifying factors, including drug candidates that affect cell/cell interactions and motion dynamics. However, existing quantitative tools for systematically interrogating complex motion phenotypes in timelapse datasets are limited. We present Motion Sensing Superpixels (MOSES), a computational framework that measures and characterises biological motion with a unique superpixel 'mesh' formulation. Using published datasets, MOSES demonstrates single-cell tracking capability and more advanced population quantification than Particle Image Velocimetry approaches. From > 190 co-culture videos, MOSES motion-mapped the interactions between human esophageal squamous epithelial and columnar cells mimicking the esophageal squamous-columnar junction, a site where Barrett's esophagus and esophageal adenocarcinoma often arise clinically. MOSES is a powerful tool that will facilitate unbiased, systematic analysis of cellular dynamics from high-content time-lapse imaging screens with little prior knowledge and few assumptions.

Characterization of Biological Motion Using Motion Sensing Superpixels.

Precise spatiotemporal regulation is the foundation for the healthy development and maintenance of living organisms. All cells must correctly execute their function in the right place at the right time. Cellular motion is thus an important dynamic readout of signaling in key disease-relevant molecular pathways. However despite the rapid advancement of imaging technology, a comprehensive quantitative description of motion imaged under different imaging modalities at all spatiotemporal scales; molecular, cellular and tissue-level is still lacking. Generally, cells move either 'individually' or 'collectively' as a group with nearby cells. Current computational tools specifically focus on one or the other regime, limiting their general applicability. To address this, we recently developed and reported a new computational framework, Motion Sensing Superpixels (MOSES). Incorporating the individual advantages of single cell trackers for individual cell and particle image velocimetry (PIV) for collective cell motion analyses, MOSES enables 'mesoscale' analysis of both single-cell and collective motion over arbitrarily long times. At the same time, MOSES readily complements existing single-cell tracking workflows with additional characterization of global motion patterns and interaction analysis between cells and also operates directly on PIV extracted motion fields to yield rich motion trajectories analogous for single-cell tracks suitable for high-throughput motion phenotyping. This protocol provides a step-by-step practical guide for those interested in applying MOSES to their own datasets. The protocol highlights the salient features of a MOSES analysis and demonstrates the ease-of-use and wide applicability of MOSES to biological imaging through demo experimental analyses with ready-to-use code snippets of four datasets from different microscope modalities; phase-contrast, fluorescent, lightsheet and intra-vital microscopy. In addition we discuss critical points of consideration in the analysis.

Cell autonomous role of iASPP deficiency in causing cardiocutaneous disorders.

Desmosome components are frequently mutated in cardiac and cutaneous disorders in animals and humans and enhanced inflammation is a common feature of these diseases. Previous studies showed that inhibitor of Apoptosis Stimulating p53 Protein (iASPP) regulates desmosome integrity at cell-cell junctions and transcription in the nucleus, and its deficiency causes cardiocutaneous disorder in mice, cattle, and humans. As iASPP is a ubiquitously expressed shuttling protein with multiple functions, a key question is whether the observed cardiocutaneous phenotypes are caused by loss of a cell autonomous role of iASPP in cardiomyocytes and keratinocytes specifically or by a loss of iASPP in other cell types such as immune cells. To address this, we developed cardiomyocyte-specific and keratinocyte-specific iASPP-deficient mouse models and show that the cell-type specific loss of iASPP in cardiomyocytes or keratinocytes is sufficient to induce cardiac or cutaneous disorders, respectively. Additionally, keratinocyte-specific iASPP-deficient mice have delayed eyelid development and wound healing. In keratinocytes, junctional iASPP is critical for stabilizing desmosomes and iASPP deficiency results in increased and disorganized cell migration, as well as impaired cell adhesion, consistent with delayed wound healing. The identification of a cell autonomous role of iASPP deficiency in causing cardiocutaneous syndrome, impaired eyelid development and wound healing suggests that variants in the iASPP gene also may contribute to polygenic heart and skin diseases.