Critical Point in Self-Organized Tissue Growth

Dynamic readout of the Hh gradient in the Drosophila wing disc reveals pattern-specific tradeoffs between robustness and precision

Understanding the principles underlying the design of robust, yet flexible patterning systems is a key problem in developmental biology. In the Drosophila wing, Hedgehog (Hh) signaling determines patterning outputs using dynamical properties of the Hh gradient. In particular, the pattern of collier (col) is established by the steady-state Hh gradient, whereas the pattern of decapentaplegic (dpp), is established by a transient gradient of Hh known as the Hh overshoot. Here, we use mathematical modeling to suggest that this dynamical interpretation of the Hh gradient results in specific robustness and precision properties. For instance, the location of the anterior border of col, which is subject to self-enhanced ligand degradation is more robustly specified than that of dpp to changes in morphogen dosage, and we provide experimental evidence of this prediction. However, the anterior border of dpp expression pattern, which is established by the overshoot gradient is much more precise to what would be expected by the steady-state gradient. Therefore, the dynamical interpretation of Hh signaling offers tradeoffs between robustness and precision to establish tunable patterning properties in a target-specific manner.

Morphogens in the evolution of size, shape and patterning

Much of the striking diversity of life on Earth has arisen from variations in the way that the same molecules and networks operate during development to shape and pattern tissues and organs into different morphologies. However, we still understand very little about the potential for diversification exhibited by different, highly conserved mechanisms during evolution, or, conversely, the constraints that they place on evolution. With the aim of steering the field in new directions, we focus on morphogen-mediated patterning and growth as a case study to demonstrate how conserved developmental mechanisms can adapt during evolution to drive morphological diversification and optimise functionality, and to illustrate how evolution algorithms and computational tools can be used alongside experiments to provide insights into how these conserved mechanisms can evolve. We first introduce key conserved properties of morphogen-driven patterning mechanisms, before summarising comparative studies that exemplify how changes in the spatiotemporal expression and signalling levels of morphogens impact the diversification of organ size, shape and patterning in nature. Finally, we detail how theoretical frameworks can be used in conjunction with experiments to probe the role of morphogen-driven patterning mechanisms in evolution. We conclude that morphogen-mediated patterning is an excellent model system and offers a generally applicable framework to investigate the evolution of developmental mechanisms.

The Unreasonable Effectiveness of Reaction Diffusion in Vertebrate Skin Color Patterning

In 1952, Alan Turing published the reaction-diffusion (RD) mathematical framework, laying the foundations of morphogenesis as a self-organized process emerging from physicochemical first principles. Regrettably, this approach has been widely doubted in the field of developmental biology. First, we summarize Turing's line of thoughts to alleviate the misconception that RD is an artificial mathematical construct. Second, we discuss why phenomenological RD models are particularly effective for understanding skin color patterning at the meso/macroscopic scales, without the need to parameterize the profusion of variables at lower scales. More specifically, we discuss how RD models (a) recapitulate the diversity of actual skin patterns, (b) capture the underlying dynamics of cellular interactions, (c) interact with tissue size and shape, (d) can lead to ordered sequential patterning, (e) generate cellular automaton dynamics in lizards and snakes, (f) predict actual patterns beyond their statistical features, and (g) are robust to model variations. Third, we discuss the utility of linear stability analysis and perform numerical simulations to demonstrate how deterministic RD emerges from the underlying chaotic microscopic agents.

Stability of Pattern Formation in Systems with Dynamic Source Regions

We explain the principles of gene expression pattern stabilization in systems of interacting, diffusible morphogens, with dynamically established source regions. Using a reaction-diffusion model with a step-function production term, we identify the phase transition between low-precision indeterminate patterning and the phase in which a traveling, well-defined contact zone between two domains is formed. Our model analytically explains single- and two-gene domain dynamics and provides pattern stability conditions for all possible two-gene regulatory network motifs.

Coupling cell proliferation rates to the duration of recruitment controls final size of the Drosophila wing

Organ growth driven by cell proliferation is an exponential process. As a result, even small variations in proliferation rates, when integrated over a relatively long developmental time, will lead to large differences in size. How organs robustly control their final size despite perturbations in cell proliferation rates throughout development is a long-standing question in biology. Using a mathematical model, we show that in the developing wing of the fruit fly, Drosophila melanogaster, variations in proliferation rates of wing-committed cells are inversely proportional to the duration of cell recruitment, a differentiation process in which a population of undifferentiated cells adopt the wing fate by expressing the selector gene, vestigial. A time-course experiment shows that vestigial-expressing cells increase exponentially while recruitment takes place, but slows down when recruitable cells start to vanish, suggesting that undifferentiated cells may be driving proliferation of wing-committed cells. When this observation is incorporated in our model, we show that the duration of cell recruitment robustly determines a final wing size even when cell proliferation rates of wing-committed cells are perturbed. Finally, we show that this control mechanism fails when perturbations in proliferation rates affect both wing-committed and recruitable cells, providing an experimentally testable hypothesis of our model.

Forward and feedback control mechanisms of developmental tissue growth

The size and proportions of animals are tightly controlled during development. How this is achieved remains poorly understood. The control of organ size entails coupling of cellular growth and cell division on one hand, and the measure of organ size on the other. In this review we focus on three layers of growth control consisting of genetic patterning, notably chemical gradients, mechanics and energetics which are complemented by a systemic control unit that modulates growth in response to the nutritional conditions and coordinates growth between different organs so as to maintain proportions. Growth factors, often present as concentration dependent chemical gradients, are positive inducers of cellular growth that may be considered as deterministic cues, hence acting as organ-intrinsic controllers of growth. However, the exponential growth dynamics in many developing tissues necessitate more stringent growth control in the form of negative feedbacks. Feedbacks endow biological systems with the capacity to quickly respond to perturbations and to correct the growth trajectory to avoid overgrowth. We propose to integrate chemical, mechanical and energetic control over cellular growth in a framework that emphasizes the self-organizing properties of organ-autonomous growth control in conjunction with systemic organ non-autonomous feedback on growth.

Roadmap for the multiscale coupling of biochemical and mechanical signals during development

The way in which interactions between mechanics and biochemistry lead to the emergence of complex cell and tissue organization is an old question that has recently attracted renewed interest from biologists, physicists, mathematicians and computer scientists. Rapid advances in optical physics, microscopy and computational image analysis have greatly enhanced our ability to observe and quantify spatiotemporal patterns of signalling, force generation, deformation, and flow in living cells and tissues. Powerful new tools for genetic, biophysical and optogenetic manipulation are allowing us to perturb the underlying machinery that generates these patterns in increasingly sophisticated ways. Rapid advances in theory and computing have made it possible to construct predictive models that describe how cell and tissue organization and dynamics emerge from the local coupling of biochemistry and mechanics. Together, these advances have opened up a wealth of new opportunities to explore how mechanochemical patterning shapes organismal development. In this roadmap, we present a series of forward-looking case studies on mechanochemical patterning in development, written by scientists working at the interface between the physical and biological sciences, and covering a wide range of spatial and temporal scales, organisms, and modes of development. Together, these contributions highlight the many ways in which the dynamic coupling of mechanics and biochemistry shapes biological dynamics: from mechanoenzymes that sense force to tune their activity and motor output, to collectives of cells in tissues that flow and redistribute biochemical signals during development.

Global constraints within the developmental program of the Drosophila wing

Organismal development is a complex process, involving a vast number of molecular constituents interacting on multiple spatio-temporal scales in the formation of intricate body structures. Despite this complexity, development is remarkably reproducible and displays tolerance to both genetic and environmental perturbations. This robustness implies the existence of hidden simplicities in developmental programs. Here, using the Drosophila wing as a model system, we develop a new quantitative strategy that enables a robust description of biologically salient phenotypic variation. Analyzing natural phenotypic variation across a highly outbred population and variation generated by weak perturbations in genetic and environmental conditions, we observe a highly constrained set of wing phenotypes. Remarkably, the phenotypic variants can be described by a single integrated mode that corresponds to a non-intuitive combination of structural variations across the wing. This work demonstrates the presence of constraints that funnel environmental inputs and genetic variation into phenotypes stretched along a single axis in morphological space. Our results provide quantitative insights into the nature of robustness in complex forms while yet accommodating the potential for evolutionary variations. Methodologically, we introduce a general strategy for finding such invariances in other developmental contexts.

Engineering Stem Cell Self-organization to Build Better Organoids

Organoids form through self-organization processes in which initially homogeneous populations of stem cells spontaneously break symmetry and undergo in-vivo-like pattern formation and morphogenesis, though the processes controlling this are poorly characterized. While these in vitro self-organized tissues far exceed the microscopic and functional complexity obtained by current tissue engineering technologies, they are non-physiological in shape and size and have limited function and lifespan. Here, we discuss how engineering efforts for guiding stem-cell-based development at multiple stages can form the basis for the assembly of highly complex and rationally designed self-organizing multicellular systems with increased robustness and physiological relevance.

Shaping Organs: Shared Structural Principles Across Kingdoms

Development encapsulates the morphogenesis of an organism from a single fertilized cell to a functional adult. A critical part of development is the specification of organ forms. Beyond the molecular control of morphogenesis, shape in essence entails structural constraints and thus mechanics. Revisiting recent results in biophysics and development, and comparing animal and plant model systems, we derive key overarching principles behind the formation of organs across kingdoms. In particular, we highlight how growing organs are active rather than passive systems and how such behavior plays a role in shaping the organ. We discuss the importance of considering different scales in understanding how organs form. Such an integrative view of organ development generates new questions while calling for more cross-fertilization between scientific fields and model system communities.

Regulation of size and scale in vertebrate spinal cord development

All vertebrates have a spinal cord with dimensions and shape specific to their species. Yet how species‐specific organ size and shape are achieved is a fundamental unresolved question in biology. The formation and sculpting of organs begins during embryonic development. As it develops, the spinal cord extends in anterior–posterior direction in synchrony with the overall growth of the body. The dorsoventral (DV) and apicobasal lengths of the spinal cord neuroepithelium also change, while at the same time a characteristic pattern of neural progenitor subtypes along the DV axis is established and elaborated. At the basis of these changes in tissue size and shape are biophysical determinants, such as the change in cell number, cell size and shape, and anisotropic tissue growth. These processes are controlled by global tissue‐scale regulators, such as morphogen signaling gradients as well as mechanical forces. Current challenges in the field are to uncover how these tissue‐scale regulatory mechanisms are translated to the cellular and molecular level, and how regulation of distinct cellular processes gives rise to an overall defined size. Addressing these questions will help not only to achieve a better understanding of how size is controlled, but also of how tissue size is coordinated with the specification of pattern.

This article is categorized under:

Establishment of Spatial and Temporal Patterns > Regulation of Size, Proportion, and Timing

Signaling Pathways > Global Signaling Mechanisms

Nervous System Development > Vertebrates: General Principles

BMP Signaling Gradient Scaling in the Zebrafish Pectoral Fin

Secreted growth factors can act as morphogens that form spatial concentration gradients in developing organs, thereby controlling growth and patterning. For some morphogens, adaptation of the gradients to tissue size allows morphological patterns to remain proportioned as the organs grow. In the zebrafish pectoral fin, we found that BMP signaling forms a two-dimensional gradient. The length of the gradient scales with tissue length and its amplitude increases with fin size according to a power-law. Gradient scaling and amplitude power-laws are signatures of growth control by time derivatives of morphogenetic signaling: cell division correlates with the fold change over time of the cellular signaling levels. We show that Smoc1 regulates BMP gradient scaling and growth in the fin. Smoc1 scales the gradient by means of a feedback loop: Smoc1 is a BMP agonist and BMP signaling represses Smoc1 expression. Our work uncovers a layer of morphogen regulation during vertebrate appendage development.

The role of topology and mechanics in uniaxially growing cell networks

In biological systems, the growth of cells, tissues and organs is influenced by mechanical cues. Locally, cell growth leads to a mechanically heterogeneous environment as cells pull and push their neighbours in a cell network. Despite this local heterogeneity, at the tissue level, the cell network is remarkably robust, as it is not easily perturbed by changes in the mechanical environment or the network connectivity. Through a network model, we relate global tissue structure (i.e. the cell network topology) and local growth mechanisms (growth laws) to the overall tissue response. Within this framework, we investigate the two main mechanical growth laws that have been proposed: stress-driven or strain-driven growth. We show that in order to create a robust and stable tissue environment, networks with predominantly series connections are naturally driven by stress-driven growth, whereas networks with predominantly parallel connections are associated with strain-driven growth.

Positional information and tissue scaling during development and regeneration

In order to contribute to the appropriate tissues during development, cells need to know their position within the embryo. This positional information is conveyed by gradients of signaling molecules, termed morphogens, that are produced in specific regions of the embryo and induce concentration-dependent responses in target tissues. Positional information is remarkably robust, and embryos often develop with the correct proportions even if large parts of the embryo are removed. In this Review, we discuss classical embryological experiments and modern quantitative analyses that have led to mechanistic insights into how morphogen gradients adapt, scale and properly pattern differently sized domains. We analyze these experimental findings in the context of mathematical models and synthesize general principles that apply to multiple systems across species and developmental stages.

Model systems for regeneration: planarians

Planarians are a group of flatworms. Some planarian species have remarkable regenerative abilities, which involve abundant pluripotent adult stem cells. This makes these worms a powerful model system for understanding the molecular and evolutionary underpinnings of regeneration. By providing a succinct overview of planarian taxonomy, anatomy, available tools and the molecular orchestration of regeneration, this Primer aims to showcase both the unique assets and the questions that can be addressed with this model system.

Universality of biochemical feedback and its application to immune cells

We map a class of well-mixed stochastic models of biochemical feedback in steady state to the mean-field Ising model near the critical point. The mapping provides an effective temperature, magnetic field, order parameter, and heat capacity that can be extracted from biological data without fitting or knowledge of the underlying molecular details. We demonstrate this procedure on fluorescence data from mouse T cells, which reveals distinctions between how the cells respond to different drugs. We also show that the heat capacity allows inference of the absolute molecule number from fluorescence intensity. We explain this result in terms of the underlying fluctuations, and we demonstrate the generality of our work.

Theory of mechanochemical patterning in biphasic biological tissues

The formation of self-organized patterns is key to the morphogenesis of multicellular organisms, although a comprehensive theory of biological pattern formation is still lacking. Here, we propose a minimal model combining tissue mechanics with morphogen turnover and transport to explore routes to patterning. Our active description couples morphogen reaction and diffusion, which impact cell differentiation and tissue mechanics, to a two-phase poroelastic rheology, where one tissue phase consists of a poroelastic cell network and the other one of a permeating extracellular fluid, which provides a feedback by actively transporting morphogens. While this model encompasses previous theories approximating tissues to inert monophasic media, such as Turing's reaction-diffusion model, it overcomes some of their key limitations permitting pattern formation via any two-species biochemical kinetics due to mechanically induced cross-diffusion flows. Moreover, we describe a qualitatively different advection-driven Keller-Segel instability which allows for the formation of patterns with a single morphogen and whose fundamental mode pattern robustly scales with tissue size. We discuss the potential relevance of these findings for tissue morphogenesis.