Self-organized BMP signaling dynamics underlie the development and evolution of digit segmentation patterns in birds and mammals.

Repeating patterns of synovial joints are a highly conserved feature of articulated digits, with variations in joint number and location resulting in diverse digit morphologies and limb functions across the tetrapod clade. During the development of the amniote limb, joints form iteratively within the growing digit ray, as a population of distal progenitors alternately specifies joint and phalanx cell fates to segment the digit into distinct elements. While numerous molecular pathways have been implicated in this fate choice, it remains unclear how they give rise to a repeating pattern. Here, using single-cell RNA sequencing and spatial gene expression profiling, we investigate the transcriptional dynamics of interphalangeal joint specification in vivo. Combined with mathematical modeling, we predict that interactions within the BMP signaling pathway-between the ligand GDF5, the inhibitor NOGGIN, and the intracellular effector pSMAD-result in a self-organizing Turing system that forms periodic joint patterns. Our model is able to recapitulate the spatiotemporal gene expression dynamics observed in vivo, as well as phenocopy digit malformations caused by BMP pathway perturbations. By contrasting in silico simulations with in vivo morphometrics of two morphologically distinct digits, we show how changes in signaling parameters and growth dynamics can result in variations in the size and number of phalanges. Together, our results reveal a self-organizing mechanism that underpins amniote digit segmentation and its evolvability and, more broadly, illustrate how Turing systems based on a single molecular pathway may generate complex repetitive patterns in a wide variety of organisms.

Secreted inhibitors drive the loss of regeneration competence in Xenopus limbs.

Absence of a specialized wound epidermis is hypothesized to block limb regeneration in higher vertebrates. However, the factors preventing its formation in regeneration-incompetent animals are poorly understood. To characterize the endogenous molecular and cellular regulators of specialized wound epidermis formation in Xenopus laevis tadpoles, and the loss of their regeneration competency during development, we used single-cell transcriptomics and ex vivo regenerating limb cultures. Transcriptomic analysis revealed that the specialized wound epidermis is not a novel cell state, but a re-deployment of the apical-ectodermal-ridge (AER) programme underlying limb development. Enrichment of secreted inhibitory factors, including Noggin, a morphogen expressed in developing cartilage/bone progenitor cells, are identified as key inhibitors of AER cell formation in regeneration-incompetent tadpoles. These factors can be overridden by Fgf10, which operates upstream of Noggin and blocks chondrogenesis. These results indicate that manipulation of the extracellular environment and/or chondrogenesis may provide a strategy to restore regeneration potential in higher vertebrates.

A dot-stripe Turing model of joint patterning in the tetrapod limb.

Iterative joints are a hallmark of the tetrapod limb, and their positioning is a key step during limb development. Although the molecular regulation of joint formation is well studied, it remains unclear what controls the location, number and orientation (i.e. the pattern) of joints within each digit. Here, we propose the dot-stripe mechanism for joint patterning, comprising two coupled Turing systems inspired by published gene expression patterns. Our model can explain normal joint morphology in wild-type limbs, hyperphalangy in cetacean flippers, mutant phenotypes with misoriented joints and suggests a reinterpretation of the polydactylous Ichthyosaur fins as a polygonal joint lattice. By formulating a generic dot-stripe model, describing joint patterns rather than molecular joint markers, we demonstrate that the insights from the model should apply regardless of the biological specifics of the underlying mechanism, thus providing a unifying framework to interrogate joint patterning in the tetrapod limb.

The myeloid lineage is required for the emergence of a regeneration-permissive environment following Xenopus tail amputation.

Regeneration-competent vertebrates are considered to suppress inflammation faster than non-regenerating ones. Hence, understanding the cellular mechanisms affected by immune cells and inflammation can help develop strategies to promote tissue repair and regeneration. Here, we took advantage of naturally occurring tail regeneration-competent and -incompetent developmental stages of Xenopus tadpoles. We first establish the essential role of the myeloid lineage for tail regeneration in the regeneration-competent tadpoles. We then reveal that upon tail amputation there is a myeloid lineage-dependent change in amputation-induced apoptosis levels, which in turn promotes tissue remodelling, and ultimately leads to the relocalization of the regeneration-organizing cells responsible for progenitor proliferation. These cellular mechanisms failed to be executed in regeneration-incompetent tadpoles. We demonstrate that regeneration incompetency is characterized by inflammatory myeloid cells whereas regeneration competency is associated with reparative myeloid cells. Moreover, treatment of regeneration-incompetent tadpoles with immune-suppressing drugs restores myeloid lineage-controlled cellular mechanisms. Collectively, our work reveals the effects of differential activation of the myeloid lineage on the creation of a regeneration-permissive environment and could be further exploited to devise strategies for regenerative medicine purposes.

Adapting machine-learning algorithms to design gene circuits.

BACKGROUND: Gene circuits are important in many aspects of biology, and perform a wide variety of different functions. For example, some circuits oscillate (e.g. the cell cycle), some are bistable (e.g. as cells differentiate), some respond sharply to environmental signals (e.g. ultrasensitivity), and some pattern multicellular tissues (e.g. Turing's model). Often, one starts from a given circuit, and using simulations, asks what functions it can perform. Here we want to do the opposite: starting from a prescribed function, can we find a circuit that executes this function? Whilst simple in principle, this task is challenging from a computational perspective, since gene circuit models are complex systems with many parameters. In this work, we adapted machine-learning algorithms to significantly accelerate gene circuit discovery. RESULTS: We use gradient-descent optimization algorithms from machine learning to rapidly screen and design gene circuits. With this approach, we found that we could rapidly design circuits capable of executing a range of different functions, including those that: (1) recapitulate important in vivo phenomena, such as oscillators, and (2) perform complex tasks for synthetic biology, such as counting noisy biological events. CONCLUSIONS: Our computational pipeline will facilitate the systematic study of natural circuits in a range of contexts, and allow the automatic design of circuits for synthetic biology. Our method can be readily applied to biological networks of any type and size, and is provided as an open-source and easy-to-use python module, GeneNet.

A single-cell molecular map of mouse gastrulation and early organogenesis.

Across the animal kingdom, gastrulation represents a key developmental event during which embryonic pluripotent cells diversify into lineage-specific precursors that will generate the adult organism. Here we report the transcriptional profiles of 116,312 single cells from mouse embryos collected at nine sequential time points ranging from 6.5 to 8.5 days post-fertilization. We construct a molecular map of cellular differentiation from pluripotency towards all major embryonic lineages, and explore the complex events involved in the convergence of visceral and primitive streak-derived endoderm. Furthermore, we use single-cell profiling to show that Tal1-/- chimeric embryos display defects in early mesoderm diversification, and we thus demonstrate how combining temporal and transcriptional information can illuminate gene function. Together, this comprehensive delineation of mammalian cell differentiation trajectories in vivo represents a baseline for understanding the effects of gene mutations during development, as well as a roadmap for the optimization of in vitro differentiation protocols for regenerative medicine.

Identity and novelty in the avian syrinx.

In its most basic conception, a novelty is simply something new. However, when many previously proposed evolutionary novelties have been illuminated by genetic, developmental, and fossil data, they have refined and narrowed our concept of biological "newness." For example, they show that these novelties can occur at one or multiple levels of biological organization. Here, we review the identity of structures in the avian vocal organ, the syrinx, and bring together developmental data on airway patterning, structural data from across tetrapods, and mathematical modeling to assess what is novel. In contrast with laryngeal cartilages that support vocal folds in other vertebrates, we find no evidence that individual cartilage rings anchoring vocal folds in the syrinx have homology with any specific elements in outgroups. Further, unlike all other vertebrate vocal organs, the syrinx is not derived from a known valve precursor, and its origin involves a transition from an evolutionary "spandrel" in the respiratory tract, the site where the trachea meets the bronchi, to a target for novel selective regimes. We find that the syrinx falls into an unusual category of novel structures: those having significant functional overlap with the structures they replace. The syrinx, along with other evolutionary novelties in sensory and signaling modalities, may more commonly involve structural changes that contribute to or modify an existing function rather than those that enable new functions.

Size-reduced embryos reveal a gradient scaling-based mechanism for zebrafish somite formation.

Little is known about how the sizes of animal tissues are controlled. A prominent example is somite size, which varies widely both within an individual and across species. Despite intense study of the segmentation clock governing the timing of somite generation, how it relates to somite size is poorly understood. Here, we examine somite scaling and find that somite size at specification scales with the length of the presomitic mesoderm (PSM) despite considerable variation in PSM length across developmental stages and in surgically size-reduced embryos. Measurement of clock period, axis elongation speed and clock gene expression patterns demonstrate that existing models fail to explain scaling. We posit a 'clock and scaled gradient' model, in which somite boundaries are set by a dynamically scaling signaling gradient across the PSM. Our model not only explains existing data, but also makes a unique prediction that we confirm experimentally - the formation of periodic 'echoes' in somite size following perturbation of the size of one somite. Our findings demonstrate that gradient scaling plays a central role in both progression and size control of somitogenesis.

Feedback between tissue packing and neurogenesis in the zebrafish neural tube.

Balancing the rate of differentiation and proliferation in developing tissues is essential to produce organs of robust size and composition. Although many molecular regulators have been established, how these connect to physical and geometrical aspects of tissue architecture is poorly understood. Here, using high-resolution timelapse imaging, we find that changes to cell geometry associated with dense tissue packing play a significant role in regulating differentiation rate in the zebrafish neural tube. Specifically, progenitors that are displaced away from the apical surface due to crowding, tend to differentiate in a Notch-dependent manner. Using simulations we show that interplay between progenitor density, cell shape and changes in differentiation rate could naturally result in negative-feedback control on progenitor cell number. Given these results, we suggest a model whereby differentiation rate is regulated by density dependent effects on cell geometry to: (1) correct variability in cell number; and (2) balance the rates of proliferation and differentiation over development to 'fill' the available space.

Observing the cell in its native state: Imaging subcellular dynamics in multicellular organisms.

True physiological imaging of subcellular dynamics requires studying cells within their parent organisms, where all the environmental cues that drive gene expression, and hence the phenotypes that we actually observe, are present. A complete understanding also requires volumetric imaging of the cell and its surroundings at high spatiotemporal resolution, without inducing undue stress on either. We combined lattice light-sheet microscopy with adaptive optics to achieve, across large multicellular volumes, noninvasive aberration-free imaging of subcellular processes, including endocytosis, organelle remodeling during mitosis, and the migration of axons, immune cells, and metastatic cancer cells in vivo. The technology reveals the phenotypic diversity within cells across different organisms and developmental stages and may offer insights into how cells harness their intrinsic variability to adapt to different physiological environments.

On the Formation of Digits and Joints during Limb Development.

Critical steps in forming the vertebrate limb include the positioning of digits and the positioning of joints within each digit. Recent studies have proposed that the iterative series of digits is established by a Turing-like mechanism generating stripes of chondrogenic domains. However, re-examination of available data suggest that digits are actually patterned as evenly spaced spots, not stripes, which then elongate into rod-shaped digit rays by incorporating new cells at their tips. Moreover, extension of the digit rays and the patterning of the joints occur simultaneously at the distal tip, implying that an integrated model is required to fully understand these processes.

Mathematically guided approaches to distinguish models of periodic patterning.

How periodic patterns are generated is an open question. A number of mechanisms have been proposed--most famously, Turing's reaction-diffusion model. However, many theoretical and experimental studies focus on the Turing mechanism while ignoring other possible mechanisms. Here, we use a general model of periodic patterning to show that different types of mechanism (molecular, cellular, mechanical) can generate qualitatively similar final patterns. Observation of final patterns is therefore not sufficient to favour one mechanism over others. However, we propose that a mathematical approach can help to guide the design of experiments that can distinguish between different mechanisms, and illustrate the potential value of this approach with specific biological examples.

Orientation of Turing-like Patterns by Morphogen Gradients and Tissue Anisotropies.

Patterning of periodic stripes during development requires mechanisms to control both stripe spacing and orientation. A number of models can explain how stripe spacing is controlled, including molecular mechanisms, such as Turing's reaction-diffusion model, as well as cell-based and mechanical mechanisms. However, how stripe orientation is controlled in each of these cases is poorly understood. Here, we model stripe orientation using a simple, yet generic model of periodic patterning, with the aim of finding qualitative features of stripe orientation that are mechanism-independent. Our model predicts three qualitatively distinct classes of orientation mechanism: gradients in production rates, gradients in model parameters, and anisotropies (e.g. in diffusion or growth). We provide evidence that the results from our minimal model may also apply to more specific and complex models, revealing features of stripe orientation that may be common to a variety of biological systems.

Interplay of cell shape and division orientation promotes robust morphogenesis of developing epithelia.

Epithelial cells acquire functionally important shapes (e.g., squamous, cuboidal, columnar) during development. Here, we combine theory, quantitative imaging, and perturbations to analyze how tissue geometry, cell divisions, and mechanics interact to shape the presumptive enveloping layer (pre-EVL) on the zebrafish embryonic surface. We find that, under geometrical constraints, pre-EVL flattening is regulated by surface cell number changes following differentially oriented cell divisions. The division pattern is, in turn, determined by the cell shape distribution, which forms under geometrical constraints by cell-cell mechanical coupling. An integrated mathematical model of this shape-division feedback loop recapitulates empirical observations. Surprisingly, the model predicts that cell shape is robust to changes of tissue surface area, cell volume, and cell number, which we confirm in vivo. Further simulations and perturbations suggest the parameter linking cell shape and division orientation contributes to epithelial diversity. Together, our work identifies an evolvable design logic that enables robust cell-level regulation of tissue-level development.