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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 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. Tissue shape changes in the posterior endoderm of the early Drosophila embryo are driven by actomyosin contractions emerging from a transcriptional induction followed by a mechanically-driven propagation of RhoI–myosin II activation.

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.

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.

Key cellular functions and developmental processes rely on cascades of GTPases. GTPases of the Rab family provide a molecular ID code to the generation, maintenance and transport of intracellular compartments. Here, we addressed the molecular design principles of endocytosis by focusing on the conversion of early endosomes into late endosomes, which entails replacement of Rab5 by Rab7. We modelled this process as a cascade of functional modules of interacting Rab GTPases. We demonstrate that intermodule interactions share similarities with the toggle switch described for the cell cycle. However, Rab5‐to‐Rab7 conversion is rather based on a newly characterized ‘cut‐out switch’ analogous to an electrical safety‐breaker. Both designs require cooperativity of auto‐activation loops when coupled to a large pool of cytoplasmic proteins. Live cell imaging and endosome tracking provide experimental support to the cut‐out switch in cargo progression and conversion of endosome identity along the degradative pathway. We propose that, by reconciling module performance with progression of activity, the cut‐out switch design could underlie the integration of modules in regulatory cascades from a broad range of biological processes. Synopsis The transition from early to late endosomes is regulated by the loss of the small GTPase Rab5 and the concomitant acquisition of Rab7 in a mechanism termed Rab conversion (Rink et al , 2005 ). The behaviour of the two master GTPases creates a paradox: on the one hand, early endosomes are required to maintain Rab5 and increase Rab5's activity as they (1) receive incoming cargo from the plasma membrane, (2) grow in size through homotypic early endosome fusion and (3) package cargo destined for degradation while sorting recycling cargo to the cell surface. On the other hand, when cargo has sufficiently accumulated in fewer and larger endosomes and the surface density of Rab5 reaches its peak, Rab5 needs to be switched off and substituted by Rab7 to irreversibly commit cargo for degradation. To resolve this paradox, we considered these two master GTPases as modules and applied a combination of theoretical and experimental approaches to unravel the yet unknown design principles of the switch system. Here, we identified two design principles that can explain the maintenance and dynamic transition between successive Rab domains or Rab modules, each requiring only a single inhibitory interaction (Figure 2 ): (1) Toggle switch. Rab5 displays cooperative auto‐activation and suppresses Rab7. (2) Cut‐out switch. Rab5 activates Rab7; Rab7 displays cooperative auto‐activation and suppresses Rab5. According to model 1, Rab5 auto‐activates and controls the level of Rab7 by a negative feedback loop. To perform such a task, it is necessary for Rab5 to maintain its level above a threshold; therefore, by decreasing the level of Rab5, Rab5 will be replaced by Rab7. According to model 2, Rab5 activates Rab7 until Rab7 reaches a threshold upon which it inactivates Rab5 through a negative feedback loop and hence Rab5 activity needs to increase for Rab7 activity to pass its threshold. So far, model 2 is best supported by the experimental data (Figure 3 and Table I ). Therefore, we propose that Rab conversion is operated by a cut‐out switch analogous to an electrical safety‐breaker (Morecoft and Hehre, 1933 ; Oliver, 1990 ) controlled by Rab7. To our knowledge, this is the first example of a cut‐out switch used in a biological system. We propose that the design principle shown here is not limited to Rab conversion but may underlie other modules posing a similar paradox. This proposal is supported by a series of experimental evidences for the necessary components of predicted cut‐out switches in other modules centred on Rab as well as other GTPases in intracellular transport. In conclusion, the description of the Rab5–Rab7 system as small functional units, or modules, represented by individual Rab domains (Miaczynska and Zerial, 2002 ) gives the possibility to further develop a more comprehensive model of the entire endocytic pathway, taking into account the recycling branch as well as further molecular components of the endocytic machinery, for example, coats and SNARE proteins (Heinrich and Rapoport, 2005 ). It is conceivable that the cut‐out switch described here could be a design principle shared by other regulatory cascades from a broad range of biological processes.

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.

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. Lecuit and colleagues use live imaging and laser ablation approaches to show that germ-band extension of the Drosophila embryo is associated with new junction growth, which is dependent on both tissue-level and local forces.

Endocytosis is a complex process fulfilling many cellular and developmental functions. Understanding how it is regulated and integrated with other cellular processes requires a comprehensive analysis of its molecular constituents and general design principles. Here, we developed a new strategy to phenotypically profile the human genome with respect to transferrin (TF) and epidermal growth factor (EGF) endocytosis by combining RNA interference, automated high-resolution confocal microscopy, quantitative multiparametric image analysis and high-performance computing. We identified several novel components of endocytic trafficking, including genes implicated in human diseases. We found that signalling pathways such as Wnt, integrin/cell adhesion, transforming growth factor (TGF)-β and Notch regulate the endocytic system, and identified new genes involved in cargo sorting to a subset of signalling endosomes. A systems analysis by Bayesian networks further showed that the number, size, concentration of cargo and intracellular position of endosomes are not determined randomly but are subject to specific regulation, thus uncovering novel properties of the endocytic system. Systems analysis of endocytosis Endocytosis, the process that cells use to internalize proteins and other molecules by engulfment in the cell membrane, is central to many cellular and development functions. By combining genome-wide RNAi screening, automated high-resolution confocal microscopy and quantitative multi-parametric image analysis, Collinet et al . obtain an accurate profile of the activity of human genes in endocytosis. Several novel components of endocytosis and endosome trafficking are revealed, and systems analysis indicates that the number, size and concentration of cargo within endosomes are not determined randomly but are subject to specific regulation within the cell. A new strategy is presented to accurately profile the activity of human genes in endocytosis by combining genome-wide RNAi, automated high-resolution confocal microscopy and quantitative multi-parametric image analysis. Several novel components of endocytosis and endosome trafficking were uncovered; a systems analysis further revealed that the cell regulates the number, size and concentration of cargo within endosomes.

Tissue morphogenesis emerges from coordinated cell shape changes driven by actomyosin contractions. Patterns of gene expression regionalize cell behaviours by controlling actomyosin contractility. We report two modes of control over Rho1 and MyosinII activation in the Drosophila endoderm. First, Rho1/MyoII are induced in a spatially restricted primordium via localized transcription of the GPCR 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 blocked 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. Thus endoderm morphogenesis emerges from local transcriptional initiation and a mechanically driven cycle of cell deformation.

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.