Model Of Morphogenesis Research Articles

Timing of resting zone parathyroid hormone-related protein expression affects maintenance of the growth plate during secondary ossification: a computational study.

Secondary ossification and maintenance of the growth plate are crucial aspects of long bone formation. Parathyroid hormone-related protein (PTHrP) has been implicated as a key factor in maintaining the growth plate, and studies suggest that PTHrP expression in the resting zone is closely related with formation of the secondary ossification center (SOC). However, details of the relationship between resting zone PTHrP expression and preservation of the growth plate remain unclear. In this study, we aim to investigate the role of resting zone PTHrP expression on maintenance of the growth plate using a computational method. We extend an existing continuum-based particle model of tissue morphogenesis to include PTHrP and Indian hedgehog (Ihh) signaling, allowing the model to capture biochemical and mechanical regulation of individual cell activities. Our model indicates that the timing of resting zone PTHrP expression-specifically the rate of increase in production at the onset of SOC formation-is potentially a crucial mechanism for maintenance of the growth plate.

D’Arcy Thompson and Synthetic Biology—Then and Now

AbstractThough often presented as a recent scientific endeavor, synthetic biology began in the 19th century and was a particularly active field in the years preceding the publication of D’Arcy Thompson’s On Growth and Form. Much synthetic biology of the era was devoted to the construction of nonliving chemical systems that would undergo morphogenesis or dynamic behaviors which had been observed in living organisms. The point was to show that “life-like” structure and behavior could be generated by physicochemical laws and required no vitalist element. D’Arcy Thompson’s careful analysis of physicochemical morphogenetic mechanisms as possible explanations of organic form links closely to this way of thinking. In the modern era, when we can genetically engineer cells to undergo specific behaviors, and program cells to undergo simple morphogenetic behaviors of the kind that Thompson and others felt might underly natural morphogenesis, it is possible to test whether they will in fact produce a predictable multicellular shape. This addresses essentially the same questions about the morphogenetic role of physicochemical forces, such as surface tension, but does so “the other way round”: physicochemical mechanisms are not being used as models for morphogenesis by natural cells but rather as a means to engineer cells to make designed forms.

Classical sorting algorithms as a model of morphogenesis: Self-sorting arrays reveal unexpected competencies in a minimal model of basal intelligence

The Diverse Intelligence research seeks to understand commonalities in behavioral competencies across a wide range of implementations. Especially interesting are simple systems that provide unexpected examples of memory, decision-making, or problem-solving in substrates that at first glance do not appear to be complex enough to implement such capabilities. We seek to develop tools to determine minimal requirements for such capabilities, and to learn to recognize and predict basal forms of intelligence in unconventional substrates. Here, we apply novel analyses to the behavior of classical sorting algorithms—short pieces of code studied for many decades. To study these sorting algorithms as a model of biological morphogenesis and its competencies, we break two formerly ubiquitous assumptions: top-down control (instead, each element within an array of numbers can exert minimal agency and implement sorting policies from the bottom up), and fully reliable hardware (instead, allowing elements to be “damaged” and fail to execute the algorithm). We quantitatively characterize sorting activity as traversal of a problem space, showing that arrays of autonomous elements sort themselves more reliably and robustly than traditional implementations in the presence of errors. Moreover, we find the ability to temporarily reduce progress in order to navigate around a defect, and unexpected clustering behavior among elements in chimeric arrays consisting of two different algorithms. The discovery of emergent problem-solving capacities in simple, familiar algorithms contributes a new perspective showing how basal forms of intelligence can emerge in simple systems without being explicitly encoded in their underlying mechanics.

A novel type of malformed floral organs mutant in barley was conferred by loss-of-function mutations of the MADS-box gene HvAGL6.

The advanced model of floral morphogenesis is based largely on data from Arabidopsis (Arabidopsis thaliana) and rice (Oryza sativa), but this process is less well understood in the Triticeae. Here, we investigated a sterile barley (Hordeum vulgare) mutant with malformed floral organs (designated mfo1), of which the paleae, lodicules, and stamens in each floret were all converted into lemma-like organs, and the ovary was abnormally shaped. Combining bulked-segregant analysis, whole-genome resequencing, and TILLING approaches, the mfo1 mutant was attributed to loss-of-function mutations in the MADS-box transcription factor gene HvAGL6, a key regulator in the ABCDE floral morphogenesis model. Through transcriptomic analysis between young inflorescences of wild-type and mfo1 plants, 380 genes were identified as differentially expressed, most of which function in DNA binding, protein dimerization, cell differentiation, or meristem determinacy. Regulatory pathway enrichment showed HvAGL6 associates with transcriptional abundance of many MADS-box genes, including the B-class gene HvMADS4. Mutants with deficiency in HvMADS4 exhibited the conversion of stamens into supernumerary pistils, producing multiple ovaries resembling the completely sterile multiple ovaries 3.h (mov3.h) mutant. These findings demonstrate that the regulatory model of floral morphogenesis is conserved across plant species and provides insights into the interactions between HvAGL6 and other MADS-box regulators.

Stress sharing as cognitive glue for collective intelligences: A computational model of stress as a coordinator for morphogenesis

Individual cells have numerous competencies in physiological and metabolic spaces. However, multicellular collectives can reliably navigate anatomical morphospace towards much larger, reliable endpoints. Understanding the robustness and control properties of this process is critical for evolutionary developmental biology, bioengineering, and regenerative medicine. One mechanism that has been proposed for enabling individual cells to coordinate toward specific morphological outcomes is the sharing of stress (where stress is a physiological parameter that reflects the current amount of error in the context of a homeostatic loop). Here, we construct and analyze a multiscale agent-based model of morphogenesis in which we quantitatively examine the impact of stress sharing on the ability to reach target morphology. We found that stress sharing improves the morphogenetic efficiency of multicellular collectives; populations with stress sharing reached anatomical targets faster. Moreover, stress sharing influenced the future fate of distant cells in the multi-cellular collective, enhancing cells’ movement and their radius of influence, consistent with the hypothesis that stress sharing works to increase cohesiveness of collectives. During development, anatomical goal states could not be inferred from observation of stress states, revealing the limitations of knowledge of goals by an extern observer outside the system itself. Taken together, our analyses support an important role for stress sharing in natural and engineered systems that seek robust large-scale behaviors to emerge from the activity of their competent components.

Evaluating predictions of the patterning cascade model of crown morphogenesis in the human lower mixed and permanent dentition

Evaluating predictions of the patterning cascade model of crown morphogenesis in the human lower mixed and permanent dentition

Evolutionary Implications of Self-Assembling Cybernetic Materials with Collective Problem-Solving Intelligence at Multiple Scales.

In recent years, the scientific community has increasingly recognized the complex multi-scale competency architecture (MCA) of biology, comprising nested layers of active homeostatic agents, each forming the self-orchestrated substrate for the layer above, and, in turn, relying on the structural and functional plasticity of the layer(s) below. The question of how natural selection could give rise to this MCA has been the focus of intense research. Here, we instead investigate the effects of such decision-making competencies of MCA agential components on the process of evolution itself, using in silico neuroevolution experiments of simulated, minimal developmental biology. We specifically model the process of morphogenesis with neural cellular automata (NCAs) and utilize an evolutionary algorithm to optimize the corresponding model parameters with the objective of collectively self-assembling a two-dimensional spatial target pattern (reliable morphogenesis). Furthermore, we systematically vary the accuracy with which the uni-cellular agents of an NCA can regulate their cell states (simulating stochastic processes and noise during development). This allows us to continuously scale the agents' competency levels from a direct encoding scheme (no competency) to an MCA (with perfect reliability in cell decision executions). We demonstrate that an evolutionary process proceeds much more rapidly when evolving the functional parameters of an MCA compared to evolving the target pattern directly. Moreover, the evolved MCAs generalize well toward system parameter changes and even modified objective functions of the evolutionary process. Thus, the adaptive problem-solving competencies of the agential parts in our NCA-based in silico morphogenesis model strongly affect the evolutionary process, suggesting significant functional implications of the near-ubiquitous competency seen in living matter.

Mechanochemical modeling of morphogenesis in cell polarization for budding yeast

Cell polarization is a multiphysics problem resulting from coupling protein pathways and cell morphological evolution. The most common example is asexual reproduction in budding yeast through Cdc42 and septin signals. However, how the interaction between the Cdc42-septin systems and the mechanical deformation of the cell surface is not well understood. To explore the interaction, we build a three-dimensional mechanochemical coupling framework to investigate the Cdc42-septin systems and elucidate how morphogenesis at the cell scale enhances the robustness of cell polarization in budding yeast. We utilize the viscous active shell model to describe the moving boundary of the cell surface, and the mechanochemical coupling is achieved through the introduction of cell surface mean curvature and active contraction-growth effects. With a normal effect of septin, numerical results demonstrate the budding processes with different transition shapes of budding profiles. On the other hand, the mechanochemical coupling problem with a weak effect of septin drives the emergence of wrinkles on the cell surface. We also apply linear perturbation analysis of the cell surface deformation to show how cell shape evolution is subjected to active contraction-growth effects. Our results show that a 3D coupled mechanochemical model can reproduce the budding morphology in yeast. Such a model provides a more comprehensive portrait of cell polarity and can be used to characterize both wild-type and mutant phenotypes such as septin mutants.

Biomechanical Model of Morphogenesis of Spiral Phyllotaxis Patterns and its Computer’s Visualization

Biomechanical Model of Morphogenesis of Spiral Phyllotaxis Patterns and its Computer’s Visualization

Mathematical modeling of early processes of morphogenesis of epithelial tissues

Studying morphogenetic processes through traditional methods, such as observa-tion and experimentation, can be highly complex and laborious. Utilizing mathematical modeling methods makes it possible to analyze big data and uncover patterns that may be unnoticed when employing traditional approaches. In this study, a vertex mathemati-cal model of squamous epithelial tissue morphogenesis is proposed. The elementary unit of the system is the cell, which can dynamically change its shape and size. We in-troduce a new potential that accounts not only for the elasticity of cell perimeters and areas but also for the elasticity of their internal angles. Additionally, we introduce an inte-gral equation of chemical signaling, which allows for the consideration of chemo-mechanical cell-cell interactions. In addition to the above, the model incorporates im-portant processes of real epithelia, such as cell proliferation and intercalation. Based on the simulation results, a diagram of the system's principal states was constructed as a function of control parameters. A parameter range is identified within which the cellular system adopts the most energetically favorable and stable configurations. Furthermore, two processes occur in the early stages of morphogenesis, namely morula formation and blastula formation. This paper provides a detailed physical and mathematical description of these processes. The obtained results can be utilized in developing methods for influ-encing morphogenetic processes in medical applications.

Pattern formation in dense populations studied by inference of nonlinear diffusion‐reaction mechanisms

SummaryReaction‐diffusion systems have been proposed as a model for pattern formation and morphogenesis. The Fickian diffusion typically employed in these constructions model the Brownian motion of particles. The biological and chemical elements that form the basis of this process, like cells and proteins, occupy finite mass and volume and interact during migration. We propose a Reaction‐Diffusion system with Maxwell‐Stefan formulation to construct the diffusive flux. This formulation relies on inter‐species force balance and provides a more realistic model for interacting elements. We also present a variational system inference‐based technique to extract these models from spatiotemporal data for these processes. We show that the inferred models can capture the characteristics of local Turing instability that instigates the pattern formation process. Moreover, the equilibrium solutions of the inferred models form similar patterns to the observed data.

Morphoelastic models discriminate between different mechanisms of left-right asymmetric stomach morphogenesis

The mechanisms by which the vertebrate stomach undergoes its evolutionarily conserved leftward bending remain incompletely understood. Although the left and right sides of the organ are known to possess different gene expression patterns and undergo distinct morphogenetic events, the physical mechanisms by which these differences generate morphological asymmetry remain unclear. Here, we develop a continuum model of asymmetric stomach morphogenesis. Using a morphoelastic framework, we investigate the morphogenetic implications of a variety of hypothetical, tissue-level growth differences between the left and right sides of a simplified tubular organ. Simulations reveal that, of the various differential growth mechanisms tested, only one category is consistent with the leftward stomach curvature observed in wild-type embryos: equal left and right volumetric growth rates, coupled with transversely isotropic tissue thinning on the left side. Simulating this mechanism in a defined region of the model over a longer period of growth leads to mature stomach-like curvatures.

On the robustness of discontinuous patterns in degenerate reaction–diffusion systems with perturbed hysteresis

In this paper, we study the dynamics of a morphogenesis model which reproduces the formation of discontinuous patterns observed in numerous biological or ecological systems. This model is determined by a degenerate reaction–diffusion system with hysteresis in the non-diffusive equation. We focus on the robustness of discontinuous patterns under the action of a perturbation of the hysteresis process. We analyze the bifurcations of homogeneous stationary solutions to this nonlinear model and prove that the trivial solution is the only one to resist to a perturbation of strong intensity. We then prove an original result on the structural transformation of discontinuous patterns, which are seen to react by acquiring a supplementary discontinuity jump under the effect of a perturbation of small intensity. We interpret the supplementary jump for ecological systems as the possible emergence of an invasive ecosystem. Numerical simulations and animations are finally provided to guide intuition on the complex morphogenesis process of this dynamical system.

Deciphering the roles of subcellular distribution and interactions involving the MEF2 binding region, the ankyrin repeat binding motif and the catalytic site of HDAC4 in Drosophila neuronal morphogenesis

BackgroundDysregulation of nucleocytoplasmic shuttling of histone deacetylase 4 (HDAC4) is associated with several neurodevelopmental and neurodegenerative disorders. Consequently, understanding the roles of nuclear and cytoplasmic HDAC4 along with the mechanisms that regulate nuclear entry and exit is an area of concerted effort. Efficient nuclear entry is dependent on binding of the transcription factor MEF2, as mutations in the MEF2 binding region result in cytoplasmic accumulation of HDAC4. It is well established that nuclear exit and cytoplasmic retention are dependent on 14–3-3-binding, and mutations that affect binding are widely used to induce nuclear accumulation of HDAC4. While regulation of HDAC4 shuttling is clearly important, there is a gap in understanding of how the nuclear and cytoplasmic distribution of HDAC4 impacts its function. Furthermore, it is unclear whether other features of the protein including the catalytic site, the MEF2-binding region and/or the ankyrin repeat binding motif influence the distribution and/or activity of HDAC4 in neurons. Since HDAC4 functions are conserved in Drosophila, and increased nuclear accumulation of HDAC4 also results in impaired neurodevelopment, we used Drosophila as a genetic model for investigation of HDAC4 function.ResultsHere we have generated a series of mutants for functional dissection of HDAC4 via in-depth examination of the resulting subcellular distribution and nuclear aggregation, and correlate these with developmental phenotypes resulting from their expression in well-established models of neuronal morphogenesis of the Drosophila mushroom body and eye. We found that in the mushroom body, forced sequestration of HDAC4 in the nucleus or the cytoplasm resulted in defects in axon morphogenesis. The actions of HDAC4 that resulted in impaired development were dependent on the MEF2 binding region, modulated by the ankyrin repeat binding motif, and largely independent of an intact catalytic site. In contrast, disruption to eye development was largely independent of MEF2 binding but mutation of the catalytic site significantly reduced the phenotype, indicating that HDAC4 acts in a neuronal-subtype-specific manner.ConclusionsWe found that the impairments to mushroom body and eye development resulting from nuclear accumulation of HDAC4 were exacerbated by mutation of the ankyrin repeat binding motif, whereas there was a differing requirement for the MEF2 binding site and an intact catalytic site. It will be of importance to determine the binding partners of HDAC4 in nuclear aggregates and in the cytoplasm of these tissues to further understand its mechanisms of action.

Modelling of morphogenesis to support the design of fungal-based engineered living materials

Abstract To realize the potential of materials comprising living organisms, bioengineers require a holistic understanding of the reciprocal relationship between environmental conditions and the biochemical and biophysical processes that influence development and behaviour. Mathematical modelling has a critical part to play in managing the complexity of biological dynamical systems and attaining higher degrees of control over their trajectories and endpoints. To support the development of mycelium-based engineered living materials, this paper reviews the literature of growth models for filamentous fungi with emphasis on the connection between morphogenesis and metabolism.

Soliton approximation in continuum models of leader-follower behavior.

Complex biological processes involve collective behavior of entities (bacteria, cells, animals) over many length and time scales and can be described by discrete models that track individuals or by continuum models involving densities and fields. We consider hybrid stochastic agent-based models of branching morphogenesis and angiogenesis (new blood vessel creation from preexisting vasculature), which treat cells as individuals that are guided by underlying continuous chemical and/or mechanical fields. In these descriptions, leader (tip) cells emerge from existing branches and follower (stalk) cells build the new sprout in their wake. Vessel branching and fusion (anastomosis) occur as a result of tip and stalk cell dynamics. Coarse graining these hybrid models in appropriate limits produces continuum partial differential equations(PDEs) for endothelial cell densities that are more analytically tractable. While these models differ in nonlinearity, they produce similar equationsat leading order when chemotaxis is dominant. We analyze this leading order system in a simple quasi-one-dimensional geometry and show that the numerical solution of the leading order PDE is well described by a soliton wave that evolves from vessel to source. This wave is an attractor for intermediate times until it arrives at the hypoxic region releasing the growth factor. The mathematical techniques used here thus identify common features of discrete and continuum approaches and provide insight into general biological mechanisms governing their collective dynamics.

PLURIPOTENCY AND PERSPECTIVES OF CELL TECHNOLOGIES

Biology of pluripotency is a modern field of biological science, and at the same time a tool for modeling human morphogenesis in vitro. Pluripotency is the property of cells to self-renew and differentiate into all types of cells of an adult organism, which appears in early embryogenesis in mammals. Pluripotent stem cells (PSCs) have limitless potential in regenerative and translational medicine, which open up perspectives for solving multiple diseases, including hereditary ones. This review describes the characteristics and uniqueness of PSCs, modeling of early human morphogenesis in vitro in blastocyst-like structures and gastruloids, modeling of organogenesis in organoids. Next, we considered the use of PSCs in regenerative medicine with their risks of capability to oncogenicity and immunogenicity in implication of a cell replacement therapy. However, therapeutic approaches using PSCs are still in their infancy and need to be deeply scrutinized.

The roles of GpsB and DivIVA in Staphylococcus aureus growth and division.

The spheroid bacterium Staphylococcus aureus is often used as a model of morphogenesis due to its apparently simple cell cycle. S. aureus has many cell division proteins that are conserved across bacteria alluding to common functions. However, despite intensive study, we still do not know the roles of many of these components. Here, we have examined the functions of the paralogues DivIVA and GpsB in the S. aureus cell cycle. Cells lacking gpsB display a more spherical phenotype than the wild-type cells, which is associated with a decrease in peripheral cell wall peptidoglycan synthesis. This correlates with increased localization of penicillin-binding proteins at the developing septum, notably PBPs 2 and 3. Our results highlight the role of GpsB as an apparent regulator of cell morphogenesis in S. aureus.

Magnetic Nanofibrous Hydrogels for Dynamic Control of Stem Cell Differentiation.

The extracellular matrix in tissue consists of complex heterogeneous soft materials with hierarchical structure and dynamic mechanical properties dictating cell and tissue level function. In many natural matrices, there are nanofibrous structures that serve to guide cell activity and dictate the form and function of tissue. Synthetic hydrogels with integrated nanofibers can mimic the structural properties of native tissue; however, model systems with dynamic mechanical properties remain elusive. Here we demonstrate modular nanofibrous hydrogels that can be reversibly stiffened in response to applied magnetic fields. Iron oxide nanoparticles were incorporated into gelatin nanofibers through electrospinning, followed by chemical stabilization and fragmentation. These magnetoactive nanofibers can be mixed with virtually any hydrogel material and reversibly stiffen the matrix at a low fiber content (≤3%). In contrast to previous work, where a large quantity of magnetic material disallowed cell encapsulation, the low nanofiber content allows matrix stiffening with cells in 3D. Using adipose derived stem cells, we show how nanofibrous matrices are beneficial for both osteogenesis and adipogenesis, where stiffening the hydrogel with applied magnetic fields enhances osteogenesis while discouraging adipogenesis. Skeletal myoblast progenitors were used as a model of tissue morphogenesis with matrix stiffening augmenting myogenesis and multinucleated myotube formation. The ability to reversibly stiffen fibrous hydrogels through magnetic stimulation provides a useful tool for studying nanotopography and dynamic mechanics in cell culture, with a scope for stimuli responsive materials for tissue engineering.

Closing the loop on morphogenesis: a mathematical model of morphogenesis by closed-loop reaction-diffusion.

Morphogenesis, the establishment and repair of emergent complex anatomy by groups of cells, is a fascinating and biomedically-relevant problem. One of its most fascinating aspects is that a developing embryo can reliably recover from disturbances, such as splitting into twins. While this reliability implies some type of goal-seeking error minimization over a morphogenic field, there are many gaps with respect to detailed, constructive models of such a process. A common way to achieve reliability is negative feedback, which requires characterizing the existing body shape to create an error signal-but measuring properties of a shape may not be simple. We show how cells communicating in a wave-like pattern could analyze properties of the current body shape. We then describe a closed-loop negative-feedback system for creating reaction-diffusion (RD) patterns with high reliability. Specifically, we use a wave to count the number of peaks in a RD pattern, letting us use a negative-feedback controller to create a pattern with N repetitions, where N can be altered over a wide range. Furthermore, the individual repetitions of the RD pattern can be easily stretched or shrunk under genetic control to create, e.g., some morphological features larger than others. This work contributes to the exciting effort of understanding design principles of morphological computation, which can be used to understand evolved developmental mechanisms, manipulate them in regenerative-medicine settings, or engineer novel synthetic morphology constructs with desired robust behavior.