LimeSeg: a coarse-grained lipid membrane simulation for 3D image segmentation

Phenotypic analysis of complex bioengineered 3D models

With advances in underlying technologies such as complex multicellular systems, synthetic materials, and bioengineering techniques, we can now generate in vitro miniaturized human tissues that recapitulate the organotypic features of normal or diseased tissues. Importantly, these 3D culture models have increasingly provided experimental access to diverse and complex tissues architectures and their morphogenic assembly in vitro. This review presents an analytical toolbox for biological researchers using 3D modeling technologies through which they can find a collation of currently available methods to phenotypically assess their 3D models in their normal state as well as their response to therapeutic or pathological agents.

Nuclear deformability facilitates apical nuclear migration in the developing zebrafish retina

Nuclear positioning is a crucial aspect of cell and developmental biology. One example is the apical movement of nuclei in neuroepithelia before mitosis, which is essential for proper tissue formation. While the cytoskeletal mechanisms that drive nuclei to the apical side have been explored, the influence of nuclear properties on apical nuclear migration is less understood. Nuclear properties, such as deformability, can be linked to lamin A/C expression levels, as shown in various in vitro studies. Interestingly, many nuclei in early development, including neuroepithelial nuclei, express only low levels of lamin A/C. Therefore, we investigated whether increased lamin A expression in the densely packed zebrafish retinal neuroepithelium affects nuclear deformability and, consequently, migration phenomena. We found that overexpressing lamin A in retinal nuclei increases nuclear stiffness, which in turn indeed impairs apical nuclear migration. Interestingly, nuclei that do not overexpress lamin A but are embedded in a stiffer lamin A-overexpressing environment also exhibit impaired apical nuclear migration, indicating that these effects can be cell non-autonomous. Additionally, in the less crowded hindbrain neuroepithelium, only minor effects on apical nuclear migration are observed. Together, this suggests that the material properties of the nucleus influence nuclear movements in a tissue-dependent manner.

Tight junctions control lumen morphology via hydrostatic pressure and junctional tension

Formation of fluid-filled lumina by epithelial tissues is essential for organ development. How cells control the hydraulic and cortical forces to control lumen morphology is not well understood. Here, we quantified the mechanical role of tight junctions in lumen formation using MDCK-II cysts. We found that the paracellular ion barrier formed by claudin receptors is not required for the hydraulic inflation of a lumen. However, the depletion of the zonula occludens scaffold resulted in lumen collapse and folding of apical membranes. Combining quantitative measurements of hydrostatic lumen pressure and junctional tension with modeling enabled us to explain lumen morphologies from the pressure-tension force balance. Tight junctions promote lumen inflation by decreasing cortical tension via the inhibition of myosin. In addition, our results suggest that excess apical area contributes to lumen opening. Overall, we provide a mechanical understanding of how epithelial cells use tight junctions to modulate tissue and lumen shape.

A multicellular developmental program in a close animal relative

All animals develop from a single-celled zygote into a complex multicellular organism through a series of precisely orchestrated processes1,2. Despite the remarkable conservation of early embryogenesis across animals, the evolutionary origins of how and when this process first emerged remain elusive. Here, by combining time-resolved imaging and transcriptomic profiling, we show that single cells of the ichthyosporean Chromosphaera perkinsii-a close relative that diverged from animals about 1 billion years ago3,4-undergo symmetry breaking and develop through cleavage divisions to produce a prolonged multicellular colony with distinct co-existing cell types. Our findings about the autonomous and palintomic developmental program of C. perkinsii hint that such multicellular development either is much older than previously thought or evolved convergently in ichthyosporeans.

The role of Imp and Syp RNA-binding proteins in precise neuronal elimination by apoptosis through the regulation of transcription factors

Neuronal stem cells generate a limited and consistent number of neuronal progenies, each possessing distinct morphologies and functions, which are crucial for optimal brain function. Our study focused on a neuroblast (NB) lineage in Drosophila known as Lin A/15, which generates motoneurons (MNs) and glia. Intriguingly, Lin A/15 NB dedicates 40% of its time to producing immature MNs (iMNs) that are subsequently eliminated through apoptosis. Two RNA-binding proteins, Imp and Syp, play crucial roles in this process. Imp+ MNs survive, while Imp-, Syp+ MNs undergo apoptosis. Genetic experiments show that Imp promotes survival, whereas Syp promotes cell death in iMNs. Late-born MNs, which fail to express a functional code of transcription factors (mTFs) that control their morphological fate, are subject to elimination. Manipulating the expression of Imp and Syp in Lin A/15 NB and progeny leads to a shift of TF code in late-born MNs toward that of early-born MNs, and their survival. Additionally, introducing the TF code of early-born MNs into late-born MNs also promoted their survival. These findings demonstrate that the differential expression of Imp and Syp in iMNs links precise neuronal generation and distinct identities through the regulation of mTFs. Both Imp and Syp are conserved in vertebrates, suggesting that they play a fundamental role in precise neurogenesis across species.

Inverse blebs operate as hydraulic pumps during mouse blastocyst formation

During preimplantation development, mouse embryos form a fluid-filled lumen. Pressurized fluid fractures cell-cell contacts and accumulates into pockets, which coarsen into a single lumen. How the embryo controls intercellular fluid movement during coarsening is unknown. Here we report inverse blebs growing into cells at adhesive contacts. Throughout the embryo we observed hundreds of inverse blebs, each filling with intercellular fluid and retracting within a minute. Inverse blebs grow due to pressure build-up resulting from fluid accumulation and cell-cell adhesion, which locally confines fluid. Inverse blebs retract due to actomyosin contraction, practically pushing fluid within the intercellular space. Importantly, inverse blebs occur infrequently at contacts formed by multiple cells, which effectively serve as fluid sinks. Manipulation of the embryo topology reveals that without sinks inverse blebs pump fluid into one another in futile cycles. We propose that inverse blebs operate as hydraulic pumps to promote luminal coarsening, thereby constituting an instrument used by cells to control fluid movement.

Mechano-osmotic signals control chromatin state and fate transitions in pluripotent stem cells

Acquisition of specific cell shapes and morphologies is a central component of cell fate transitions. Although signaling circuits and gene regulatory networks that regulate pluripotent stem cell differentiation have been intensely studied, how these networks are integrated in space and time with morphological transitions and mechanical deformations to control state transitions remains a fundamental open question. Here, we focus on two distinct models of pluripotency, primed pluripotent stem cells and pre-implantation inner cell mass cells of human embryos to discover that cell fate transitions associate with rapid changes in nuclear shape and volume which collectively alter the nuclear mechanophenotype. Mechanistic studies in human induced pluripotent stem cells further reveal that these phenotypical changes and the associated active fluctuations of the nuclear envelope arise from growth factor signaling-controlled changes in chromatin mechanics and cytoskeletal confinement. These collective mechano-osmotic changes trigger global transcriptional repression and a condensation-prone environment that primes chromatin for a cell fate transition by attenuating repression of differentiation genes. However, while this mechano-osmotic chromatin priming has the potential to accelerate fate transitions and differentiation, sustained biochemical signals are required for robust induction of specific lineages. Our findings uncover a critical mechanochemical feedback mechanism that integrates nuclear mechanics, shape and volume with biochemical signaling and chromatin state to control cell fate transition dynamics.

Emerin deficiency drives MCF7 cells to an invasive phenotype

During metastasis, cancer cells traverse the vasculature by squeezing through very small gaps in the endothelium. Thus, nuclei in metastatic cancer cells must become more malleable to move through these gaps. Our lab showed invasive breast cancer cells have 50% less emerin protein resulting in smaller, misshapen nuclei, and higher metastasis rates than non-cancerous controls. Thus, emerin deficiency was predicted to cause increased nuclear compliance, cell migration, and metastasis. We tested this hypothesis by downregulating emerin in noninvasive MCF7 cells and found emerin knockdown causes smaller, dysmorphic nuclei, resulting in increased impeded cell migration. Emerin reduction in invasive breast cancer cells showed similar results. Supporting the clinical relevance of emerin reduction in cancer progression, our analysis of 192 breast cancer patient samples showed emerin expression inversely correlates with cancer invasiveness. We conclude emerin loss is an important driver of invasive transformation and has utility as a biomarker for tumor progression.

Emerin deficiency drives MCF7 cells to an invasive phenotype

During metastasis, cancer cells traverse the vasculature by squeezing through very small gaps in the endothelium. Thus, nuclei in metastatic cancer cells must become more malleable to move through these gaps. Our lab showed invasive breast cancer cells have 50% less emerin protein resulting in smaller, misshapen nuclei, and higher metastasis rates than non-cancerous controls. Thus, emerin deficiency was predicted to cause increased nuclear compliance, cell migration, and metastasis. We tested this hypothesis by downregulating emerin in noninvasive MCF7 cells and found emerin knockdown causes smaller, dysmorphic nuclei, resulting in increased impeded cell migration. Emerin reduction in invasive breast cancer cells showed similar results. Supporting the clinical relevance of emerin reduction in cancer progression, our analysis of 192 breast cancer patient samples showed emerin expression inversely correlates with cancer invasiveness. We conclude emerin loss is an important driver of invasive transformation and has utility as a biomarker for tumor progression.

Plasma membrane nanodeformations promote actin polymerization through CIP4/CDC42 recruitment and regulate type II IFN signaling

In their environment, cells must cope with mechanical stresses constantly. Among these, nanoscale deformations of plasma membrane induced by substrate nanotopography are now largely accepted as a biophysical stimulus influencing cell behavior and function. However, the mechanotransduction cascades involved and their precise molecular effects on cellular physiology are still poorly understood. Here, using homemade fluorescent nanostructured cell culture surfaces, we explored the role of Bin/Amphiphysin/Rvs (BAR) domain proteins as mechanosensors of plasma membrane geometry. Our data reveal that distinct subsets of BAR proteins bind to plasma membrane deformations in a membrane curvature radius-dependent manner. Furthermore, we show that membrane curvature promotes the formation of dynamic actin structures mediated by the Rho GTPase CDC42, the F-BAR protein CIP4, and the presence of PI(4,5)P2. In addition, these actin-enriched nanodomains can serve as platforms to regulate receptor signaling as they appear to contain interferon-γ receptor (IFNγ-R) and to lead to the partial inhibition of IFNγ-induced JAK/STAT signaling.

Quantifying turgor pressure in budding and fission yeasts based upon osmotic properties

Walled cells, such as plants, fungi, and bacteria cells, possess a high internal hydrostatic pressure, termed turgor pressure, that drives volume growth and contributes to cell shape determination. Rigorous measurement of turgor pressure, however, remains challenging, and reliable quantitative measurements, even in budding yeast are still lacking. Here, we present a simple and robust experimental approach to access turgor pressure in yeasts based upon the determination of isotonic concentration using protoplasts as osmometers. We propose three methods to identify the isotonic condition - three-dimensional cell volume, cytoplasmic fluorophore intensity, and mobility of a cytGEMs nano-rheology probe - that all yield consistent values. Our results provide turgor pressure estimates of 1.0 ± 0.1 MPa for Schizosaccharomyces pombe, 0.49 ± 0.01 MPa for Schizosaccharomyces japonicus, 0.5 ± 0.1 MPa for Saccharomyces cerevisiae W303a and 0.31 ± 0.03 MPa for Saccharomyces cerevisiae BY4741. Large differences in turgor pressure and nano-rheology measurements between the Saccharomyces cerevisiae strains demonstrate how fundamental biophysical parameters can vary even among wild-type strains of the same species. These side-by-side measurements of turgor pressure in multiple yeast species provide critical values for quantitative studies on cellular mechanics and comparative evolution.

CartoCell, a high-content pipeline for 3D image analysis, unveils cell morphology patterns in epithelia

Decades of research have not yet fully explained the mechanisms of epithelial self-organization and 3D packing. Single-cell analysis of large 3D epithelial libraries is crucial for understanding the assembly and function of whole tissues. Combining 3D epithelial imaging with advanced deep-learning segmentation methods is essential for enabling this high-content analysis. We introduce CartoCell, a deep-learning-based pipeline that uses small datasets to generate accurate labels for hundreds of whole 3D epithelial cysts. Our method detects the realistic morphology of epithelial cells and their contacts in the 3D structure of the tissue. CartoCell enables the quantification of geometric and packing features at the cellular level. Our single-cell cartography approach then maps the distribution of these features on 2D plots and 3D surface maps, revealing cell morphology patterns in epithelial cysts. Additionally, we show that CartoCell can be adapted to other types of epithelial tissues.

Synthetic Par polarity induces cytoskeleton asymmetry in unpolarized mammalian cells

Polarized cells rely on a polarized cytoskeleton to function. Yet, how cortical polarity cues induce cytoskeleton polarization remains elusive. Here, we capitalized on recently established designed 2D protein arrays to ectopically engineer cortical polarity of virtually any protein of interest during mitosis in various cell types. This enables direct manipulation of polarity signaling and the identification of the cortical cues sufficient for cytoskeleton polarization. Using this assay, we dissected the logic of the Par complex pathway, a key regulator of cytoskeleton polarity during asymmetric cell division. We show that cortical clustering of any Par complex subunit is sufficient to trigger complex assembly and that the primary kinetic barrier to complex assembly is the relief of Par6 autoinhibition. Further, we found that inducing cortical Par complex polarity induces two hallmarks of asymmetric cell division in unpolarized mammalian cells: spindle orientation, occurring via Par3, and central spindle asymmetry, depending on aPKC activity.

Quantifying turgor pressure in budding and fission yeasts based upon osmotic properties

Walled cells, such as plants, fungi, and bacteria cells, possess a high internal hydrostatic pressure, termed turgor pressure, that drives volume growth and contributes to cell shape determination. Rigorous measurement of turgor pressure, however, remains challenging, and reliable quantitative measurements, even in budding yeast are still lacking. Here, we present a simple and robust experimental approach to access turgor pressure in yeasts based upon the determination of isotonic concentration using protoplasts as osmometers. We propose three methods to identify the isotonic condition - 3D cell volume, cytoplasmic fluorophore intensity, and mobility of a cytGEMs nano-rheology probe - that all yield consistent values. Our results provide turgor pressure estimates of 1.0 ± 0.1 MPa for S. pombe, 0.49 ± 0.01 MPa for S. japonicus, 0.5 ± 0.1 MPa for S. cerevisiae W303a and 0.31 ± 0.03 MPa for S. cerevisiae BY4741. Large differences in turgor pressure and nano-rheology measurements between the S. cerevisiae strains demonstrate how fundamental biophysical parameters can vary even among wildtype strains of the same species. These side-by-side measurements of turgor pressure in multiple yeast species provide critical values for quantitative studies on cellular mechanics and comparative evolution.

From cells to form: A roadmap to study shape emergence in vivo

Organogenesis arises from the collective arrangement of cells into progressively 3D-shaped tissue. The acquisition of a correctly shaped organ is then the result of a complex interplay between molecular cues, responsible for differentiation and patterning, and the mechanical properties of the system, which generate the necessary forces that drive correct shape emergence. Nowadays, technological advances in the fields of microscopy, molecular biology, and computer science are making it possible to see and record such complex interactions in incredible, unforeseen detail within the global context of the developing embryo. A quantitative and interdisciplinary perspective of developmental biology becomes then necessary for a comprehensive understanding of morphogenesis. Here, we provide a roadmap to quantify the events that lead to morphogenesis from imaging to image analysis, quantification, and modeling, focusing on the discrete cellular and tissue shape changes, as well as their mechanical properties.

A simple smiFISH pipeline to quantify mRNA at the single-cell level in 3D

Techniques allowing the precise quantification of mRNA at the cellular level are essential for understanding biological processes. Here, we present a semi-automated smiFISH (single-molecule inexpensive FISH) pipeline enabling quantification of mRNA in a small number of cells (∼40) in fixed whole mount tissue. We describe steps for sample preparation, hybridization, image acquisition, cell segmentation, and mRNA quantification. Although the protocol was developed in Drosophila, it can be optimized for use in other organisms. For complete details on the use and execution of this protocol, please refer to Guan et al.¹.

Active mesh and neural network pipeline for cell aggregate segmentation

Segmenting cells within cellular aggregates in 3D is a growing challenge in cell biology due to improvements in capacity and accuracy of microscopy techniques. Here, we describe a pipeline to segment images of cell aggregates in 3D. The pipeline combines neural network segmentations with active meshes. We apply our segmentation method to cultured mouse mammary gland organoids imaged over 24 h with oblique plane microscopy, a high-throughput light-sheet fluorescence microscopy technique. We show that our method can also be applied to images of mouse embryonic stem cells imaged with a spinning disc microscope. We segment individual cells based on nuclei and cell membrane fluorescent markers, and track cells over time. We describe metrics to quantify the quality of the automated segmentation. Our segmentation pipeline involves a Fiji plugin that implements active mesh deformation and allows a user to create training data, automatically obtain segmentation meshes from original image data or neural network prediction, and manually curate segmentation data to identify and correct mistakes. Our active meshes-based approach facilitates segmentation postprocessing, correction, and integration with neural network prediction.

UNILIPID, a Methodology for Energetically Accurate Prediction of Protein Insertion into Implicit Membranes of Arbitrary Shape

The insertion of proteins into membranes is crucial for understanding their function in many biological processes. In this work, we present UNILIPID, a universal implicit lipid-protein description as a methodology for dealing with implicit membranes. UNILIPID is independent of the scale of representation and can be applied at the level of all atoms, coarse-grained particles down to the level of a single bead per amino acid. We provide example implementations for these scales and demonstrate the versatility of our approach by accurately reflecting the free energy of transfer for each amino acid. In addition to single membranes, we describe the analytical implementation of double membranes and show that UNILIPID is well suited for modeling at multiple scales. We generalize to membranes of arbitrary shape. With UNILIPID, we provide a methodological framework for a simple and general parameterization tuned to reproduce a selected reference hydrophobicity scale. The software we provide along with the methodological description is optimized for specific user features such as real-time response, live visual analysis, and virtual reality experiences.

Ultrastructure of COPII vesicle formation in yeast characterized by correlative light and electron microscopy

Traffic of proteins out of the endoplasmic reticulum (ER) is driven by the COPII coat, a layered protein scaffold that mediates the capture of cargo proteins and the remodeling of the ER membrane into spherical vesicular carriers. Although the components of this machinery have been genetically defined, and the mechanisms of coat assembly extensively explored in vitro, understanding the physical mechanisms of membrane remodeling in cells remains a challenge. Here we use correlative light and electron microscopy (CLEM) to visualize the nanoscale ultrastructure of membrane remodeling at ER exit sites (ERES) in yeast cells. Using various COPII mutants, we have determined the broad contribution that each layer of the coat makes to membrane remodeling. Our data suggest that inner coat components define the radius of curvature, whereas outer coat components facilitate membrane fission. The organization of the coat in conjunction with membrane biophysical properties determines the ultrastructure of vesicles and thus the efficiency of protein transport.

Cellular shape reinforces niche to stem cell signaling in the small intestine

Niche-derived factors regulate tissue stem cells, but apart from the mechanosensory pathways, the effect of niche geometry is not well understood. We used organoids and bioengineered tissue culture platforms to demonstrate that the conical shape of Lgr5+ small intestinal stem cells (ISCs) facilitate their self-renewal and function. Inhibition of non-muscle myosin II (NM II)-driven apical constriction altered ISC shape and reduced niche curvature and stem cell capacity. Niche curvature is decreased in aged mice, suggesting that suboptimal interactions between old ISCs and their niche develop with age. We show that activation of NM IIC or physical restriction to young topology improves in vitro regeneration by old epithelium. We propose that the increase in lateral surface area of ISCs induced by apical constriction promotes interactions between neighboring cells, and the curved topology of the intestinal niche has evolved to maximize signaling between ISCs and neighboring cells.

T cell cytoskeletal forces shape synapse topography for targeted lysis via membrane curvature bias of perforin

Cytotoxic T lymphocytes (CTLs) lyse target cells by delivering lytic granules that contain the pore former perforin to the cytotoxic immunological synapse. Here, we establish that opposing cytoskeletal forces drive lytic granule polarization and simultaneously shape T cell synapse topography to enhance target perforation. At the cell rear, actomyosin contractility drives the anterograde movement of lytic granules toward the nucleus. At the synapse, dynein-derived forces induce negatively curved membrane pockets to which granules are transported around the nucleus. These highly concave degranulation pockets are located directly opposite positively curved bulges on the target cell membrane. We identify a curvature bias in the action of perforin, which preferentially perforates positively curved tumor cell membrane. Together, these findings demonstrate murine and human T cell-mediated cytotoxicity to be a highly tuned mechano-biochemical system, in which the forces that polarize lytic granules locally bend the synaptic membrane to favor the unidirectional perforation of the target cell.

Live imaging of echinoderm embryos to illuminate evo-devo

Echinoderm embryos have been model systems for cell and developmental biology for over 150 years, in good part because of their optical clarity. Discoveries that shaped our understanding of fertilization, cell division and cell differentiation were only possible because of the transparency of sea urchin eggs and embryos, which allowed direct observations of intracellular structures. More recently, live imaging of sea urchin embryos, coupled with fluorescence microscopy, has proven pivotal to uncovering mechanisms of epithelial to mesenchymal transition, cell migration and gastrulation. However, live imaging has mainly been performed on sea urchin embryos, while echinoderms include numerous experimentally tractable species that present interesting variation in key aspects of morphogenesis, including differences in embryo compaction and mechanisms of blastula formation. The study of such variation would allow us not only to understand how tissues are formed in echinoderms, but also to identify which changes in cell shape, cell-matrix and cell-cell contact formation are more likely to result in evolution of new embryonic shapes. Here we argue that adapting live imaging techniques to more echinoderm species will be fundamental to exploit such an evolutionary approach to the study of morphogenesis, as it will allow measuring differences in dynamic cellular behaviors - such as changes in cell shape and cell adhesion - between species. We briefly review existing methods for live imaging of echinoderm embryos and describe in detail how we adapted those methods to allow long-term live imaging of several species, namely the sea urchin Lytechinus pictus and the sea stars Patiria miniata and Patiriella regularis. We outline procedures to successfully label, mount and image early embryos for 10-16 h, from cleavage stages to early blastula. We show that data obtained with these methods allows 3D segmentation and tracking of individual cells over time, the first step to analyze how cell shape and cell contact differ among species. The methods presented here can be easily adopted by most cell and developmental biology laboratories and adapted to successfully image early embryos of additional species, therefore broadening our understanding of the evolution of morphogenesis.

A quantitative biophysical principle to explain the 3D cellular connectivity in curved epithelia

Epithelial cell organization and the mechanical stability of tissues are closely related. In this context, it has been recently shown that packing optimization in bended or folded epithelia is achieved by an energy minimization mechanism that leads to a complex cellular shape: the "scutoid". Here, we focus on the relationship between this shape and the connectivity between cells. We use a combination of computational, experimental, and biophysical approaches to examine how energy drivers affect the three-dimensional (3D) packing of tubular epithelia. We propose an energy-based stochastic model that explains the 3D cellular connectivity. Then, we challenge it by experimentally reducing the cell adhesion. As a result, we observed an increment in the appearance of scutoids that correlated with a decrease in the energy barrier necessary to connect with new cells. We conclude that tubular epithelia satisfy a quantitative biophysical principle that links tissue geometry and energetics with the average cellular connectivity.

Lineage tracing shows that cell size asymmetries predict the dorsoventral axis in the sea star embryo

BACKGROUND

Cell size asymmetries are often linked to cell fate decisions, due to cell volumes and cell fate determinants being unequally partitioned during asymmetric cell divisions. A clear example is found in the sea urchin embryo, where a characteristic and obvious unequal 4th cleavage generates micromeres, which are necessary for mesendoderm cell fate specification. Unlike sea urchin development, sea star development is generally thought to have only equal cleavage. However, subtle cell size asymmetries can be observed in sea star embryos; whether those cell size asymmetries are consistently produced during sea star development and if they are involved in cell fate decisions remains unknown.

RESULTS

Using confocal live imaging of early embryos we quantified cell size asymmetries in 16-cell stage embryos of two sea star species, Patiria miniata and Patiriella regularis. Using photoconversion to perform lineage tracing, we find that the position of the smallest cells of P. miniata embryos is biased toward anterior ventral tissues. However, both blastomere dissociation and mechanical removal of one small cell do not prevent dorsoventral (DV) axis formation, suggesting that embryos compensate for the loss of those cells and that asymmetrical partitioning of maternal determinants is not strictly necessary for DV patterning. Finally, we show that manipulating cell size to introduce artificial cell size asymmetries is not sufficient to direct the positioning of the future DV axis in P. miniata embryos.

CONCLUSIONS

Our results show that although cell size asymmetries are consistently produced during sea star early cleavage and are predictive of the DV axis, they are not necessary to instruct DV axis formation.

Post-transcriptional regulation of transcription factor codes in immature neurons drives neuronal diversity

How the vast array of neuronal diversity is generated remains an unsolved problem. Here, we investigate how 29 morphologically distinct leg motoneurons are generated from a single stem cell in Drosophila. We identify 19 transcription factor (TF) codes expressed in immature motoneurons just before their morphological differentiation. Using genetic manipulations and a computational tool, we demonstrate that the TF codes are progressively established in immature motoneurons according to their birth order. Comparing RNA and protein expression patterns of multiple TFs reveals that post-transcriptional regulation plays an essential role in shaping these TF codes. Two RNA-binding proteins, Imp and Syp, expressed in opposing gradients in immature motoneurons, control the translation of multiple TFs. The varying sensitivity of TF mRNAs to the opposing gradients of Imp and Syp in immature motoneurons decrypts these gradients into distinct TF codes, establishing the connectome between motoneuron axons and their target muscles.

Epithelial cells adapt to curvature induction via transient active osmotic swelling

Generation of tissue curvature is essential to morphogenesis. However, how cells adapt to changing curvature is still unknown because tools to dynamically control curvature in vitro are lacking. Here, we developed self-rolling substrates to study how flat epithelial cell monolayers adapt to a rapid anisotropic change of curvature. We show that the primary response is an active and transient osmotic swelling of cells. This cell volume increase is not observed on inducible wrinkled substrates, where concave and convex regions alternate each other over short distances; and this finding identifies swelling as a collective response to changes of curvature with a persistent sign over large distances. It is triggered by a drop in membrane tension and actin depolymerization, which is perceived by cells as a hypertonic shock. Osmotic swelling restores tension while actin reorganizes, probably to comply with curvature. Thus, epithelia are unique materials that transiently and actively swell while adapting to large curvature induction.

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Rapid inward and outward epithelial rolling triggers cell volume increase

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Epithelial folding induces a mechano-osmotic feedback loop that involvs ion channels

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Cell volume regulation in curved tissues involves actin, membrane tension, and mTORC2

Physical properties of the cytoplasm modulate the rates of microtubule polymerization and depolymerization

The cytoplasm is a crowded, visco-elastic environment whose physical properties change according to physiological or developmental states. How the physical properties of the cytoplasm impact cellular functions in vivo remains poorly understood. Here, we probe the effects of cytoplasmic concentration on microtubules by applying osmotic shifts to fission yeast, moss, and mammalian cells. We show that the rates of both microtubule polymerization and depolymerization scale linearly and inversely with cytoplasmic concentration; an increase in cytoplasmic concentration decreases the rates of microtubule polymerization and depolymerization proportionally, whereas a decrease in cytoplasmic concentration leads to the opposite. Numerous lines of evidence indicate that these effects are due to changes in cytoplasmic viscosity rather than cellular stress responses or macromolecular crowding per se. We reconstituted these effects on microtubules in vitro by tuning viscosity. Our findings indicate that, even in normal conditions, the viscosity of the cytoplasm modulates the reactions that underlie microtubule dynamic behaviors.

Control of nuclear size by osmotic forces in Schizosaccharomyces pombe

The size of the nucleus scales robustly with cell size so that the nuclear-to-cell volume ratio (N/C ratio) is maintained during cell growth in many cell types. The mechanism responsible for this scaling remains mysterious. Previous studies have established that the N/C ratio is not determined by DNA amount but is instead influenced by factors such as nuclear envelope mechanics and nuclear transport. Here, we developed a quantitative model for nuclear size control based upon colloid osmotic pressure and tested key predictions in the fission yeast Schizosaccharomyces pombe. This model posits that the N/C ratio is determined by the numbers of macromolecules in the nucleoplasm and cytoplasm. Osmotic shift experiments showed that the fission yeast nucleus behaves as an ideal osmometer whose volume is primarily dictated by osmotic forces. Inhibition of nuclear export caused accumulation of macromolecules in the nucleoplasm, leading to nuclear swelling. We further demonstrated that the N/C ratio is maintained by a homeostasis mechanism based upon synthesis of macromolecules during growth. These studies demonstrate the functions of colloid osmotic pressure in intracellular organization and size control.

Size scaling in collective cell growth

Size is a fundamental feature of living entities and is intimately tied to their function. Scaling laws, which can be traced to D'Arcy Thompson and Julian Huxley, have emerged as a powerful tool for studying regulation of the growth dynamics of organisms and their constituent parts. Yet, throughout the 20th century, as scaling laws were established for single cells, quantitative studies of the coordinated growth of multicellular structures have lagged, largely owing to technical challenges associated with imaging and image processing. Here, we present a supervised learning approach for quantifying the growth dynamics of germline cysts during oogenesis. Our analysis uncovers growth patterns induced by the groupwise developmental dynamics among connected cells, and differential growth rates of their organelles. We also identify inter-organelle volumetric scaling laws, finding that nurse cell growth is linear over several orders of magnitude. Our approach leverages the ever-increasing quantity and quality of imaging data, and is readily amenable for studies of collective cell growth in other developmental contexts, including early mammalian embryogenesis and germline development.

spheresDT/Mpacts-PiCS: Cell Tracking and Shape Retrieval in Membrane-labeled Embryos

Motivation

Uncovering the cellular and mechanical processes that drive embryo formation requires an accurate read out of cell geometries over time. However, automated extraction of 3D cell shapes from time-lapse microscopy remains challenging, especially when only membranes are labeled.

Results

We present an image analysis framework for automated tracking and three-dimensional cell segmentation in confocal time lapses. A sphere clustering approach allows for local thresholding and application of logical rules to facilitate tracking and unseeded segmentation of variable cell shapes. Next, the segmentation is refined by a discrete element method simulation where cell shapes are constrained by a biomechanical cell shape model. We apply the framework on Caenorhabditis elegans embryos in various stages of early development and analyze the geometry of the 7- and 8-cell stage embryo, looking at volume, contact area and shape over time.

Availability and implementation

The Python code for the algorithm and for measuring performance, along with all data needed to recreate the results is freely available at 10.5281/zenodo.5108416 and 10.5281/zenodo.4540092. The most recent version of the software is maintained at https://bitbucket.org/pgmsembryogenesis/sdt-pics.

Supplementary information

Supplementary data are available at Bioinformatics online.

Scalable robust graph and feature extraction for arbitrary vessel networks in large volumetric datasets

BACKGROUND

Recent advances in 3D imaging technologies provide novel insights to researchers and reveal finer and more detail of examined specimen, especially in the biomedical domain, but also impose huge challenges regarding scalability for automated analysis algorithms due to rapidly increasing dataset sizes. In particular, existing research towards automated vessel network analysis does not always consider memory requirements of proposed algorithms and often generates a large number of spurious branches for structures consisting of many voxels. Additionally, very often these algorithms have further restrictions such as the limitation to tree topologies or relying on the properties of specific image modalities.

RESULTS

We propose a scalable iterative pipeline (in terms of computational cost, required main memory and robustness) that extracts an annotated abstract graph representation from the foreground segmentation of vessel networks of arbitrary topology and vessel shape. The novel iterative refinement process is controlled by a single, dimensionless, a-priori determinable parameter.

CONCLUSIONS

We are able to, for the first time, analyze the topology of volumes of roughly 1 TB on commodity hardware, using the proposed pipeline. We demonstrate improved robustness in terms of surface noise, vessel shape deviation and anisotropic resolution compared to the state of the art. An implementation of the presented pipeline is publicly available in version 5.1 of the volume rendering and processing engine Voreen.

4D analysis of malaria parasite invasion offers insights into erythrocyte membrane remodeling and parasitophorous vacuole formation

Host membrane remodeling is indispensable for viruses, bacteria, and parasites, to subvert the membrane barrier and obtain entry into cells. The malaria parasite Plasmodium spp. induces biophysical and molecular changes to the erythrocyte membrane through the ordered secretion of its apical organelles. To understand this process and address the debate regarding how the parasitophorous vacuole membrane (PVM) is formed, we developed an approach using lattice light-sheet microscopy, which enables the parasite interaction with the host cell membrane to be tracked and characterized during invasion. Our results show that the PVM is predominantly formed from the erythrocyte membrane, which undergoes biophysical changes as it is remodeled across all stages of invasion, from pre-invasion through to PVM sealing. This approach enables a functional interrogation of parasite-derived lipids and proteins in PVM biogenesis and echinocytosis during Plasmodium falciparum invasion and promises to yield mechanistic insights regarding how this is more generally orchestrated by other intracellular pathogens.

Here, Geoghegan, Evelyn et al. provide a lattice light-sheet microscopy based 4D imaging pipeline to quantitatively investigate Plasmodium spp. invasion and show that the nascent parasitophorous vacuole is predominantly formed from host’s erythrocyte membrane and undergoes continuous remodeling throughout invasion.

Volumetric Semantic Instance Segmentation of the Plasma Membrane of HeLa Cells

In this work, an unsupervised volumetric semantic instance segmentation of the plasma membrane of HeLa cells as observed with serial block face scanning electron microscopy is described. The resin background of the images was segmented at different slices of a 3D stack of 518 slices with 8192 × 8192 pixels each. The background was used to create a distance map, which helped identify and rank the cells by their size at each slice. The centroids of the cells detected at different slices were linked to identify them as a single cell that spanned a number of slices. A subset of these cells, i.e., the largest ones and those not close to the edges were selected for further processing. The selected cells were then automatically cropped to smaller regions of interest of 2000 × 2000 × 300 voxels that were treated as cell instances. Then, for each of these volumes, the nucleus was segmented, and the cell was separated from any neighbouring cells through a series of traditional image processing steps that followed the plasma membrane. The segmentation process was repeated for all the regions of interest previously selected. For one cell for which the ground truth was available, the algorithm provided excellent results in Accuracy (AC) and the Jaccard similarity Index (JI): nucleus: JI =0.9665, AC =0.9975, cell including nucleus JI =0.8711, AC =0.9655, cell excluding nucleus JI =0.8094, AC =0.9629. A limitation of the algorithm for the plasma membrane segmentation was the presence of background. In samples with tightly packed cells, this may not be available. When tested for these conditions, the segmentation of the nuclear envelope was still possible. All the code and data were released openly through GitHub, Zenodo and EMPIAR.

Integrity of the short arm of the nuclear pore Y-complex is required for mouse embryonic stem cell growth and differentiation

Many cellular processes, ranging from cell division to differentiation, are controlled by nuclear pore complexes (NPCs). However, studying the contributions of individual NPC subunits to these processes in vertebrates has long been impeded by their complexity and the lack of efficient genetic tools. Here, we use genome editing in mouse embryonic stem cells (mESCs) to characterize the role of NPC structural components, focusing on the short arm of the Y-complex that comprises Nup85, Seh1 and Nup43. We show that Seh1 and Nup43, although dispensable in pluripotent mESCs, are required for their normal cell growth rates, their viability upon differentiation and for the maintenance of proper NPC density. mESCs with an N-terminally truncated Nup85 mutation (in which interaction with Seh1 is greatly impaired) feature a similar reduction of NPC density. However, their proliferation and differentiation are unaltered, indicating that it is the integrity of the Y-complex, rather than the number of NPCs, that is critical to ensure these processes.

Live imaging of microtubule organization, cell expansion, and intercellular space formation in Arabidopsis leaf spongy mesophyll cells

Leaf spongy mesophyll cells form an interconnected network of branched cells and intercellular spaces to maximize the surface area available for light capture and photosynthetic gas exchange. To investigate the morphogenetic events leading to cell separation and branching in Arabidopsis thaliana, we used mesophyll-specific promoters to facilitate imaging of mesophyll cell shape and microtubule (MT) organization over multiple spatiotemporal scales without interference from the overlying epidermal cells. We show that cells enlarge by selective expansion of cell wall regions in contact with intercellular spaces. Cell-cell contacts remain relatively fixed in size, forming the termini of interconnecting branches. Surprisingly, classic schizogeny (de-adhesion of neighboring cells) is relatively infrequent, being related to the local topology of cell junctions during early expansion. Intercellular spaces cue the position of stable MT bundles, which in turn promote efficient dilation of intercellular spaces and cell branching. Our data provide insights into mesophyll morphogenesis and MT organization and lay the groundwork for future investigations.

Cargo crowding contributes to sorting stringency in COPII vesicles

Accurate maintenance of organelle identity in the secretory pathway relies on retention and retrieval of resident proteins. In the endoplasmic reticulum (ER), secretory proteins are packaged into COPII vesicles that largely exclude ER residents and misfolded proteins by mechanisms that remain unresolved. Here we combined biochemistry and genetics with correlative light and electron microscopy (CLEM) to explore how selectivity is achieved. Our data suggest that vesicle occupancy contributes to ER retention: in the absence of abundant cargo, nonspecific bulk flow increases. We demonstrate that ER leakage is influenced by vesicle size and cargo occupancy: overexpressing an inert cargo protein or reducing vesicle size restores sorting stringency. We propose that cargo recruitment into vesicles creates a crowded lumen that drives selectivity. Retention of ER residents thus derives in part from the biophysical process of cargo enrichment into a constrained spherical membrane-bound carrier.

Design of biologically active binary protein 2D materials

Ordered two-dimensional arrays such as S-layers^1,2 and designed analogues^3-5 have intrigued bioengineers^6,7, but with the exception of a single lattice formed with flexible linkers⁸, they are constituted from just one protein component. Materials composed of two components have considerable potential advantages for modulating assembly dynamics and incorporating more complex functionality^9-12. Here we describe a computational method to generate co-assembling binary layers by designing rigid interfaces between pairs of dihedral protein building blocks, and use it to design a p6m lattice. The designed array components are soluble at millimolar concentrations, but when combined at nanomolar concentrations, they rapidly assemble into nearly crystalline micrometre-scale arrays nearly identical to the computational design model in vitro and in cells without the need for a two-dimensional support. Because the material is designed from the ground up, the components can be readily functionalized and their symmetry reconfigured, enabling formation of ligand arrays with distinguishable surfaces, which we demonstrate can drive extensive receptor clustering, downstream protein recruitment and signalling. Using atomic force microscopy on supported bilayers and quantitative microscopy on living cells, we show that arrays assembled on membranes have component stoichiometry and structure similar to arrays formed in vitro, and that our material can therefore impose order onto fundamentally disordered substrates such as cell membranes. In contrast to previously characterized cell surface receptor binding assemblies such as antibodies and nanocages, which are rapidly endocytosed, we find that large arrays assembled at the cell surface suppress endocytosis in a tunable manner, with potential therapeutic relevance for extending receptor engagement and immune evasion. Our work provides a foundation for a synthetic cell biology in which multi-protein macroscale materials are designed to modulate cell responses and reshape synthetic and living systems.

The mitotic protein NuMA plays a spindle-independent role in nuclear formation and mechanics

Eukaryotic cells typically form a single, round nucleus after mitosis, and failures to do so can compromise genomic integrity. How mammalian cells form such a nucleus remains incompletely understood. NuMA is a spindle protein whose disruption results in nuclear fragmentation. What role NuMA plays in nuclear integrity, and whether its perceived role stems from its spindle function, are unclear. Here, we use live imaging to demonstrate that NuMA plays a spindle-independent role in forming a single, round nucleus. NuMA keeps the decondensing chromosome mass compact at mitotic exit and promotes a mechanically robust nucleus. NuMA's C terminus binds DNA in vitro and chromosomes in interphase, while its coiled-coil acts as a central regulatory and structural element: it prevents NuMA from binding chromosomes at mitosis, regulates its nuclear mobility, and is essential for nuclear formation. Thus, NuMA plays a structural role over the cell cycle, building and maintaining the spindle and nucleus, two of the cell's largest structures.

Spatial proteomics defines the content of trafficking vesicles captured by golgin tethers

Intracellular traffic between compartments of the secretory and endocytic pathways is mediated by vesicle-based carriers. The proteomes of carriers destined for many organelles are ill-defined because the vesicular intermediates are transient, low-abundance and difficult to purify. Here, we combine vesicle relocalisation with organelle proteomics and Bayesian analysis to define the content of different endosome-derived vesicles destined for the trans-Golgi network (TGN). The golgin coiled-coil proteins golgin-97 and GCC88, shown previously to capture endosome-derived vesicles at the TGN, were individually relocalised to mitochondria and the content of the subsequently re-routed vesicles was determined by organelle proteomics. Our findings reveal 45 integral and 51 peripheral membrane proteins re-routed by golgin-97, evidence for a distinct class of vesicles shared by golgin-97 and GCC88, and various cargoes specific to individual golgins. These results illustrate a general strategy for analysing intracellular sub-proteomes by combining acute cellular re-wiring with high-resolution spatial proteomics.

Of Cell Shapes and Motion: The Physical Basis of Animal Cell Migration

Motile cells have developed a variety of migration modes relying on diverse traction-force-generation mechanisms. Before the behavior of intracellular components could be easily imaged, cell movements were mostly classified by different types of cellular shape dynamics. Indeed, even though some types of cells move without any significant change in shape, most cell propulsion mechanisms rely on global or local deformations of the cell surface. In this review, focusing mostly on metazoan cells, we discuss how different types of local and global shape changes underlie distinct migration modes. We then discuss mechanical differences between force-generation mechanisms and finish by speculating on how they may have evolved.

Reliable estimation of membrane curvature for cryo-electron tomography

Curvature is a fundamental morphological descriptor of cellular membranes. Cryo-electron tomography (cryo-ET) is particularly well-suited to visualize and analyze membrane morphology in a close-to-native state and molecular resolution. However, current curvature estimation methods cannot be applied directly to membrane segmentations in cryo-ET, as these methods cannot cope with some of the artifacts introduced during image acquisition and membrane segmentation, such as quantization noise and open borders. Here, we developed and implemented a Python package for membrane curvature estimation from tomogram segmentations, which we named PyCurv. From a membrane segmentation, a signed surface (triangle mesh) is first extracted. The triangle mesh is then represented by a graph, which facilitates finding neighboring triangles and the calculation of geodesic distances necessary for local curvature estimation. PyCurv estimates curvature based on tensor voting. Beside curvatures, this algorithm also provides robust estimations of surface normals and principal directions. We tested PyCurv and three well-established methods on benchmark surfaces and biological data. This revealed the superior performance of PyCurv not only for cryo-ET, but also for data generated by other techniques such as light microscopy and magnetic resonance imaging. Altogether, PyCurv is a versatile open-source software to reliably estimate curvature of membranes and other surfaces in a wide variety of applications.

Membrane curvature plays a central role in many cellular processes like cell division, organelle shaping and membrane contact sites. While cryo-electron tomography (cryo-ET) allows the visualization of cellular membranes in 3D at molecular resolution and close-to-native conditions, there is a lack of computational methods to quantify membrane curvature from cryo-ET data. Therefore, we developed a computational procedure for membrane curvature estimation from tomogram segmentations and implemented it in a software package called PyCurv. PyCurv converts a membrane segmentation, i.e. a set of voxels, into a surface, i.e. a mesh of triangles. PyCurv uses the local geometrical information to reliably estimate the local surface orientation, the principal (maximum and minimum) curvatures and their directions. PyCurv outperforms well-established curvature estimation methods, and it can also be applied to data generated by other imaging techniques.

Software tools for 3D nuclei segmentation and quantitative analysis in multicellular aggregates

Today, we are fully immersed into the era of 3D biology. It has been extensively demonstrated that 3D models: (a) better mimic the physiology of human tissues; (b) can effectively replace animal models; (c) often provide more reliable results than 2D ones. Accordingly, anti-cancer drug screenings and toxicology studies based on multicellular 3D biological models, the so-called "-oids" (e.g. spheroids, tumoroids, organoids), are blooming in the literature. However, the complex nature of these systems limit the manual quantitative analyses of single cells' behaviour in the culture. Accordingly, the demand for advanced software tools that are able to perform phenotypic analysis is fundamental. In this work, we describe the freely accessible tools that are currently available for biologists and researchers interested in analysing the effects of drugs/treatments on 3D multicellular -oids at a single-cell resolution level. In addition, using publicly available nuclear stained datasets we quantitatively compare the segmentation performance of 9 specific tools.

Hydraulic fracturing and active coarsening position the lumen of the mouse blastocyst

During mouse pre-implantation development, the formation of the blastocoel, a fluid-filled lumen, breaks the radial symmetry of the blastocyst. The factors that control the formation and positioning of this basolateral lumen remain obscure. We found that accumulation of pressurized fluid fractures cell-cell contacts into hundreds of micrometer-size lumens. These microlumens eventually discharge their volumes into a single dominant lumen, which we model as a process akin to Ostwald ripening, underlying the coarsening of foams. Using chimeric mutant embryos, we tuned the hydraulic fracturing of cell-cell contacts and steered the coarsening of microlumens, allowing us to successfully manipulate the final position of the lumen. We conclude that hydraulic fracturing of cell-cell contacts followed by contractility-directed coarsening of microlumens sets the first axis of symmetry of the mouse embryo.

Nessys: A new set of tools for the automated detection of nuclei within intact tissues and dense 3D cultures

Methods for measuring the properties of individual cells within their native 3D environment will enable a deeper understanding of embryonic development, tissue regeneration, and tumorigenesis. However, current methods for segmenting nuclei in 3D tissues are not designed for situations in which nuclei are densely packed, nonspherical, or heterogeneous in shape, size, or texture, all of which are true of many embryonic and adult tissue types as well as in many cases for cells differentiating in culture. Here, we overcome this bottleneck by devising a novel method based on labelling the nuclear envelope (NE) and automatically distinguishing individual nuclei using a tree-structured ridge-tracing method followed by shape ranking according to a trained classifier. The method is fast and makes it possible to process images that are larger than the computer's memory. We consistently obtain accurate segmentation rates of >90%, even for challenging images such as mid-gestation embryos or 3D cultures. We provide a 3D editor and inspector for the manual curation of the segmentation results as well as a program to assess the accuracy of the segmentation. We have also generated a live reporter of the NE that can be used to track live cells in 3 dimensions over time. We use this to monitor the history of cell interactions and occurrences of neighbour exchange within cultures of pluripotent cells during differentiation. We provide these tools in an open-access user-friendly format.