During development cell deformations are spatially organized, however, how cellular mechanics is spatially controlled is unclear. Spatial control of cell identity often determines local cellular mechanics in a two-tiered mechanism. Theoretical studies also proposed that molecular gradients, so called “mechanogens”, spatially control mechanics. We report evidence of a similar mechanism required for Drosophila gastrulation. We show that the GPCR ligand Fog, expressed in the posterior endoderm, diffuses and acts in a concentration-dependent manner to activate actomyosin contractility at a distance during a wave of tissue invagination. While Fog is uniformly distributed in the extracellular space, it forms a surface-bound gradient that recruits Myosin-II via receptor oligomerization. This activity gradient self-renews as the wave propagates and is shaped by both receptor endocytosis and modulation of GPCR signalling by integrins upon adhesion to the vitelline membrane. This exemplifies how chemical, mechanical and geometrical cues underly the emergence of a self-organized mechanogen activity gradient. During morphogenesis patterned contractility drives tissue shape changes. Here they show that GPCR signaling and integrin activation give rise to a dynamically translocating gradient of contractility required for a self-organized wave of tissue invagination.

During development cell deformations are spatially organized, however, how cellular mechanics is spatially controlled is unclear. Spatial control of cell identity often determines local cellular mechanics in a two-tiered mechanism ( [1][1] ). Theoretical studies also proposed that molecular gradients, so called “mechanogens”, spatially control mechanics ( [2][2], [3][3] ). We report evidence of such a “mechanogen” required for Drosophila gastrulation. We show that the GPCR ligand Fog, expressed in the posterior endoderm ( [4][4]–[6][5] ), diffuses and acts in a concentration-dependent manner to activate actomyosin contractility at a distance during a wave of tissue invagination. While Fog is uniformly distributed in the extracellular space, it forms a surface-bound gradient that activates Myosin-II via receptor oligomerization. This activity gradient self-renews as the wave propagates and is shaped by both receptor endocytosis and a feedback mechanism involving adhesion to the vitelline membrane by integrins. This exemplifies how chemical, mechanical and geometrical cues underly the emergence of a self-organized mechanogen activity gradient. ### Competing Interest Statement The authors have declared no competing interest. [1]: #ref-1 [2]: #ref-2 [3]: #ref-3 [4]: #ref-4 [5]: #ref-6

During morphogenesis, mechanical forces induce large-scale deformations; yet, how forces emerge from cellular contractility and adhesion is unclear. In Drosophila embryos, a tissue-scale wave of actomyosin contractility coupled with adhesion to the surrounding vitelline membrane drives polarized tissue invagination. We show that this process emerges subcellularly from the mechanical coupling between myosin II activation and sequential adhesion/de-adhesion to the vitelline membrane. At the wavefront, integrin clusters anchor the actin cortex to the vitelline membrane and promote activation of myosin II, which in turn enhances adhesion in a positive feedback. Following cell detachment, cortex contraction and advective flow amplify myosin II. Prolonged contact with the vitelline membrane prolongs the integrin-myosin II feedback, increases integrin adhesion, and thus slows down cell detachment and wave propagation. The angle of cell detachment depends on adhesion strength and sets the tensile forces required for detachment. Thus, we document how the interplay between subcellular mechanochemical feedback and geometry drives tissue morphogenesis.

How the shape of embryos and organs emerges during development is a fundamental question that has fascinated scientists for centuries. Tissue dynamics arise from a small set of cell behaviours, including shape changes, cell contact remodelling, cell migration, cell division and cell extrusion. These behaviours require control over cell mechanics, namely active stresses associated with protrusive, contractile and adhesive forces, and hydrostatic pressure, as well as material properties of cells that dictate how cells respond to active stresses. In this Review, we address how cell mechanics and the associated cell behaviours are robustly organized in space and time during tissue morphogenesis. We first outline how not only gene expression and the resulting biochemical cues, but also mechanics and geometry act as sources of morphogenetic information to ultimately define the time and length scales of the cell behaviours driving morphogenesis. Next, we present two idealized modes of how this information flows — how it is read out and translated into a biological effect — during morphogenesis. The first, akin to a programme, follows deterministic rules and is hierarchical. The second follows the principles of self-organization, which rests on statistical rules characterizing the system’s composition and configuration, local interactions and feedback. We discuss the contribution of these two modes to the mechanisms of four very general classes of tissue deformation, namely tissue folding and invagination, tissue flow and extension, tissue hollowing and, finally, tissue branching. Overall, we suggest a conceptual framework for understanding morphogenetic information that encapsulates genetics and biochemistry as well as mechanics and geometry as information modules, and the interplay of deterministic and self-organized mechanisms of their deployment, thereby diverging considerably from the traditional notion that shape is fully encoded and determined by genes. Tissue morphogenesis is instructed by the interplay of biochemical cues, mechanics and tissue geometry. Conceptually, these instructions can be deployed either deterministically, functioning as a pre-patterned programme for shape changes, or stochastically, whereby the shape emerges in a self-organized fashion. This Review discusses recent insights into how pre-patterned and stochastic tissue shaping are integrated during development.

Tissue morphogenesis emerges from coordinated cell shape changes driven by actomyosin contractions. Patterns of gene expression regionalize and polarize cell behaviours by controlling actomyosin contractility. Yet how mechanical feedbacks affect tissue morphogenesis is unclear. We report two modes of control over Rho1 and MyosinII activation in the Drosophila endoderm. First, Rho1/MyoII are induced in a primordium via localized transcription of the GPCR ligand Fog. Second, a tissue-scale wave of Rho1/MyoII activation and cell invagination progresses anteriorly. The wave does not require sustained gene transcription, and is not governed by regulated Fog delivery. Instead, MyoII inhibition blocked acute Rho1 activation and propagation, revealing a mechanical feedback driven by MyoII. Last, we identify a cycle of 3D cell deformations whereby MyoII activation and invagination in each row of cells drives adhesion to the vitelline membrane, apical spreading, MyoII activation and invagination in the next row. Thus endoderm morphogenesis emerges from local transcriptional initiation and a mechanically driven wave of cell deformation.

Morphogenesis relies on the active generation of forces, and the transmission of these forces to surrounding cells and tissues. Hence measuring forces directly in developing embryos is an essential task to study the mechanics of development. Among the experimental techniques that have emerged to measure forces in epithelial tissues, force inference is particularly appealing. Indeed it only requires a snapshot of the tissue, as it relies on the topology and geometry of cell contacts, assuming that forces are balanced at each vertex. However, establishing force inference as a reliable technique requires thorough validation in multiple conditions. Here we performed systematic comparisons of force inference with laser ablation experiments in four epithelial tissues from two animals, the fruit fly and the quail. We show that force inference accurately predicts single junction tension, tension patterns in stereotyped groups of cells, and tissue-scale stress patterns, in wild type and mutant conditions. We emphasize its ability to capture the distribution of forces at different scales from a single image, which gives it a critical advantage over perturbative techniques such as laser ablation. Overall, our results demonstrate that force inference is a reliable and efficient method to quantify the mechanical state of epithelia during morphogenesis, especially at larger scales when inferred tensions and pressures are binned into a coarse-grained stress tensor.

Tissue morphogenesis arises from coordinated changes in cell shape driven by actomyosin contractions. Patterns of gene expression regionalize cell behaviours by controlling actomyosin contractility. Here we report two modes of control over Rho1 and myosin II (MyoII) activation in the Drosophila endoderm. First, Rho1-MyoII are induced in a spatially restricted primordium via localized transcription of the G-protein-coupled receptor ligand Fog. Second, a tissue-scale wave of Rho1-MyoII activation and cell invagination progresses anteriorly away from the primordium. The wave does not require sustained gene transcription, and is not governed by regulated Fog delivery. Instead, MyoII inhibition blocks Rho1 activation and propagation, revealing a mechanical feedback driven by MyoII. We find that MyoII activation and invagination in each row of cells drives adhesion to the vitelline membrane mediated by integrins, apical spreading, MyoII activation and invagination in the next row. Endoderm morphogenesis thus emerges from local transcriptional initiation and a mechanically driven cycle of cell deformation.

Morphogenesis relies on the active generation of forces, and the transmission of these forces to surrounding cells and tissues. Hence measuring forces directly in developing embryos is an essential task to study the mechanics of development. Among the experimental techniques that have emerged to measure forces in epithelial tissues, force inference is particularly appealing. Indeed it only requires a snapshot of the tissue, as it relies on the topology and geometry of cell contacts, assuming that forces are balanced at each vertex. However, establishing force inference as a reliable technique requires thorough validation in multiple conditions. Here we performed systematic comparisons of force inference with laser ablation experiments in three distinct Drosophila epithelia. We show that force inference accurately predicts single junction tensions, tension patterns in stereotyped groups of cells, and tissue-scale stress patterns, in wild type and mutant conditions. We emphasize its ability to capture the distribution of forces at different scales from a single image, which gives it a critical advantage over perturbative techniques such as laser ablation. Our results demonstrate that force inference is a reliable and efficient method to quantify the mechanics of epithelial tissues during morphogenesis.

AbstractTissue morphogenesis emerges from coordinated cell shape changes driven by actomyosin contraction1, 2. Spatial patterns of gene expression regionalize and polarize cell behaviours, such as apical constriction in the ventral mesoderm and cell intercalation in the lateral ectoderm ofDrosophila3. Thus, tissue dynamics is largely governed genetically. Actomyosin contractile networks drive cell and tissue-level shape changes and can respond to mechanical stimuli4–9. However how genetic information and mechanical control drive tissue-level morphogenesis is not well understood.Here we report two phases and modalities of Rho1 and non-muscle MyosinII (MyoII) activation in theDrosophilaposterior endoderm. First, Rho1/MyoII are induced apically in a spatially restricted primordium region via localized transcription of the GPCR ligand Fog. Second, a tissue-scale travelling wave of Rho1/MyoII activation and cell invagination progresses anteriorly across the dorsal epithelium at a constant speed of 1 cell every 3 minutes. Remarkably, the MyoII wave does not require sustained gene transcription, and is also insensitive to perturbations in the level and pattern of Fog expression. Thus, whilefogtranscription initiates Rho1/MyoII activation in the primordium, Fog delivery does not govern wave dynamics. Instead, perturbing the mechanical environment of the endoderm impaired MyoII wave dynamics. MyoII inhibition blocked acute Rho1 activation and propagation, suggesting that MyoII contractility provides both local feedback amplification and spatial coupling necessary for wave progression. Finally, we identify a cycle of 3D cell deformations that link MyoII activation and invagination in one row of cells to vitelline membrane attachment, apical spreading, MyoII activation and invagination in the next row, to drive anterior progression of the invagination wave. Thus endoderm morphogenesis emerges from local transcriptional initiation and a mechanically driven travelling cycle of cell contraction and deformation.

Morphogenesis of an epithelial tissue emerges from the behavior of its constituent cells, including changes in shape, rearrangements, and divisions. In many instances the directionality of these cellular events is controlled by the polarized distribution of specific molecular components. In recent years, our understanding of morphogenesis and polarity highly benefited from advances in genetics, microscopy, and image analysis. They now make it possible to measure cellular dynamics and polarity with unprecedented precision for entire tissues throughout their development. Here we review recent approaches to visualize and measure cell polarity and tissue morphogenesis. The chapter is organized like an experiment. We first discuss the choice of cell and polarity reporters and describe the use of mosaics to reveal hidden cell polarities or local morphogenetic events. Then, we outline application-specific advantages and disadvantages of different microscopy techniques and image projection algorithms. Next, we present methods to extract cell outlines to measure cell polarity and detect cellular events underlying morphogenesis. Finally, we bridge scales by presenting approaches to quantify the specific contribution of each cellular event to global tissue deformation. Taken together, we provide an in-depth description of available tools and theoretical concepts to quantitatively study cell polarity and tissue morphogenesis over multiple scales.

Tissue morphogenesis relies on the production of active cellular forces. Understanding how such forces are mechanically converted into cell shape changes is essential to our understanding of morphogenesis. Here we use Myosin II pulsatile activity during Drosophila embryogenesis to study how transient forces generate irreversible cell shape changes. Analyzing the dynamics of junction shortening and elongation resulting from Myosin II pulses, we find that long pulses yield less reversible deformations, typically a signature of dissipative mechanics. This is consistent with a simple viscoelastic description, which we use to model individual shortening and elongation events. The model predicts that dissipation typically occurs on the minute timescale, a timescale commensurate with that of force generation by Myosin II pulses. We test this estimate by applying time-controlled forces on junctions with optical tweezers. Our results argue that active junctional deformation is stabilized by dissipation. Hence, tissue morphogenesis requires coordination between force generation and dissipation.

Convergence-extension is a widespread morphogenetic process driven by polarized cell intercalation. In the Drosophila germ band, epithelial intercalation comprises loss of junctions between anterior-posterior neighbours followed by growth of new junctions between dorsal-ventral neighbours. Much is known about how active stresses drive polarized junction shrinkage. However, it is unclear how tissue convergence-extension emerges from local junction remodelling and what the specific role, if any, of junction growth is. Here we report that tissue convergence and extension correlate mostly with new junction growth. Simulations and in vivo mechanical perturbations reveal that junction growth is due to local polarized stresses driven by medial actomyosin contractions. Moreover, we find that tissue-scale pulling forces at the boundary with the invaginating posterior midgut actively participate in tissue extension by orienting junction growth. Thus, tissue extension is akin to a polarized fluid flow that requires parallel and concerted local and tissue-scale forces to drive junction growth and cell-cell displacement.

Functional genomics screens using multi-parametric assays are powerful approaches for identifying genes involved in particular cellular processes. However, they suffer from problems like noise, and often provide little insight into molecular mechanisms. A bottleneck for addressing these issues is the lack of computational methods for the systematic integration of multi-parametric phenotypic datasets with molecular interactions. Here, we present Integrative Multi Profile Analysis of Cellular Traits (IMPACT). The main goal of IMPACT is to identify the most consistent phenotypic profile among interacting genes. This approach utilizes two types of external information: sets of related genes (IMPACT-sets) and network information (IMPACT-modules). Based on the notion that interacting genes are more likely to be involved in similar functions than non-interacting genes, this data is used as a prior to inform the filtering of phenotypic profiles that are similar among interacting genes. IMPACT-sets selects the most frequent profile among a set of related genes. IMPACT-modules identifies sub-networks containing genes with similar phenotype profiles. The statistical significance of these selections is subsequently quantified via permutations of the data. IMPACT (1) handles multiple profiles per gene, (2) rescues genes with weak phenotypes and (3) accounts for multiple biases e.g. caused by the network topology. Application to a genome-wide RNAi screen on endocytosis showed that IMPACT improved the recovery of known endocytosis-related genes, decreased off-target effects, and detected consistent phenotypes. Those findings were confirmed by rescreening 468 genes. Additionally we validated an unexpected influence of the IGF-receptor on EGF-endocytosis. IMPACT facilitates the selection of high-quality phenotypic profiles using different types of independent information, thereby supporting the molecular interpretation of functional screens.

Nature 464, 243–249 (2010); doi:10.1038/nature08779 Readers alerted us to a technical mistake (a shift of one row) made during the compilation of Supplementary Table 4, resulting in the assignment of 455 gene symbols to the wrong gene IDs. For the affected genes, the cluster group, the number of positive small interfering and endoribonuclease-prepared RNAs (si/esiRNAs) per gene and the Phenoscore values were assigned to the wrong gene symbol (although they were all assigned to the correct gene ID).

Adherens junctions display dual properties of robustness and plasticity. In multicellular organisms, they support both strong cell-cell adhesion and rapid cell-cell contact remodeling during development and wound healing. The core components of adherens junctions are clusters of cadherin molecules, which mediate cell-cell adhesion through homophilic interactions in trans. Interactions of cadherins with the actin cytoskeleton are essential for providing both stability and plasticity to adherens junctions. Cadherins regulate the turnover of actin by regulating its polymerization and anchor tensile actomyosin networks at the cell cortex. In turn, actin regulates cadherin turnover by regulating its endocytosis and actomyosin networks exert forces driving remodeling of cell-cell contacts. The interplay between adherens junctions and contractile actomyosin networks has striking outcomes during epithelial morphogenesis. Their integrated dynamics result in different morphogenetic patterns shaping tissues and organs.

BACKGROUND:Endocytosis allows the import and distribution of cargo into a series of endosomes with distinct morphological and biochemical characteristics. Our current understanding of endocytic cargo trafficking is based on the kinetics of net cargo transport between endosomal compartments without considering individual endosomes. However, endosomes form a dynamic network of membranes undergoing fusion and fission, thereby continuously exchanging and redistributing cargo. The macroscopic kinetic properties, i.e., the properties of the endosomal network as a whole, result from the collective behaviors of many individual endosomes, a problem so far largely unaddressed. RESULTS:Here, we developed a general theoretical framework to describe the dynamics of cargo distributions in the endosomal network. We combined the theory with quantitative experiments to study how the macroscopic kinetic properties of the endosomal network emerge from microscopic processes at the level of individual endosomes. We compared our theory predictions to experimental data in which dynamic distributions of endocytosed low-density lipoprotein (LDL) were quantified. CONCLUSIONS:Our theory can quantitatively describe the observed cargo distributions as a function of time. Remarkably, the theory allows determining microscopic kinetic parameters such as the fusion rate between endosomes from still images of cargo distributions at different times of internalization. We show that this method is robust and sensitive because cargo distributions result from an average over many stochastic events in many cells. Our results provide theoretical and experimental support to the "funnel model" of endosome progression and suggest that the conversion of early to late endosomes is the major mode of LDL trafficking.

Modeling of the epileptic encephalopathies, severe disorders of infancy characterized by both seizures refractory to treatment and cognitive impairment, has seen progress over the recent years. Initial animal models focusing on inducing repetitive seizures in immature animals used to be the closest model to these devastating disorders; the generation of these models and recent discoveries from them are initially discussed. Recent advances in genetics have allowed for the development of animal models based on genetic defects found in human cases of the encephalopathies. While models of Dravet syndrome and Generalized Epilepsy with Febrile Seizures plus (GEFS+) are discussed in an alternate chapter, the pathologic characteristics of other genetic models will be discussed, especially in relation to how they match the human disorders. Unfortunately, many of these epileptic encephalopathies remain poorly modeled, and limitations causing this lack of quality are also discussed.