In vitro reconstruction of branched tubular structures from lung epithelial cells in high cell concentration gradient environment

Instability mechanisms of repelling peak solutions in a multi-variable activator-inhibitor system

We study the linear stability properties of spatially localized single- and multi-peak states generated in a subcritical Turing bifurcation in the Meinhardt model of branching. In one spatial dimension, these states are organized in a foliated snaking structure owing to peak-peak repulsion but are shown to be all linearly unstable, with the number of unstable modes increasing with the number of peaks present. Despite this, in two spatial dimensions, direct numerical simulations reveal the presence of stable single- and multi-spot states whose properties depend on the repulsion from nearby spots as well as the shape of the domain and the boundary conditions imposed thereon. Front propagation is shown to trigger the growth of new spots while destabilizing others. The results indicate that multi-variable models may support new types of behavior that are absent from typical two-variable models.

Deep-learning on-chip light-sheet microscopy enabling video-rate volumetric imaging of dynamic biological specimens

Volumetric imaging of dynamic signals in a large, moving, and light-scattering specimen is extremely challenging, owing to the requirement on high spatiotemporal resolution and difficulty in obtaining high-contrast signals. Here we report that through combining a microfluidic chip-enabled digital scanning light-sheet illumination strategy with deep-learning based image restoration, we can realize isotropic 3D imaging of a whole crawling Drosophila larva on an ordinary inverted microscope at a single-cell resolution and a high volumetric imaging rate up to 20 Hz. Enabled with high performances even unmet by current standard light-sheet fluorescence microscopes, we in toto record the neural activities during the forward and backward crawling of a 1st instar larva, and successfully correlate the calcium spiking of motor neurons with the locomotion patterns.

A review of regulated self-organizing approaches for tissue regeneration

Tissue and organ regeneration is the dynamic process by which a population of cells rearranges into a specific form with specific functions. Traditional tissue regeneration utilizes tissue grafting, cell implantation, and structured scaffolds to achieve clinical efficacy. However, tissue grafting methods face a shortage of donor tissue, while cell implantation may involve leakage of the implanted cells without a supportive 3D matrix. Cell migration, proliferation, and differentiation in structured scaffolds may disorganize and frustrate the artificially pre-designed structures, and sometimes involve immunogenic reactions. To overcome this limitation, the self-organizing properties and innate regenerative capability of tissue/organism formation in the absence of guidance by structured scaffolds has been investigated. This review emphasizes the growing subfield of the regulated self-organizing approach for neotissue formation and describes advances in the subfield using diverse, cutting-edge, inter-disciplinarity technologies. We cohesively summarize the directed self-organization of cells in the micro-engineered cell-ECM system and 3D/4D cell printing. Mathematical modeling of cellular self-organization is also discussed for providing rational guidance to intractable problems in tissue regeneration. It is envisioned that future self-organization approaches integrating biomathematics, micro-nano engineering, and gene circuits developed from synthetic biology will continue to work in concert with self-organizing morphogenesis to enhance rational control during self-organizing in tissue and organ regeneration.

Reaction-Diffusion Model-Based Research on Formation Mechanism of Neuron Dendritic Spine Patterns

The pattern abnormalities of dendritic spine, tiny protrusions on neuron dendrites, have been found related to multiple nervous system diseases, such as Parkinson's disease and schizophrenia. The determination of the factors affecting spine patterns is of vital importance to explore the pathogenesis of these diseases, and further, search the treatment method for them. Although the study of dendritic spines is a hot topic in neuroscience in recent years, there is still a lack of systematic study on the formation mechanism of its pattern. This paper provided a reinterpretation of reaction-diffusion model to simulate the formation process of dendritic spine, and further, study the factors affecting spine patterns. First, all four classic shapes of spines, mushroom-type, stubby-type, thin-type, and branched-type were reproduced using the model. We found that the consumption rate of substrates by the cytoskeleton is a key factor to regulate spine shape. Moreover, we found that the density of spines can be regulated by the amount of an exogenous activator and inhibitor, which is in accordance with the anatomical results found in hippocampal CA1 in SD rats with glioma. Further, we analyzed the inner mechanism of the above model parameters regulating the dendritic spine pattern through Turing instability analysis and drew a conclusion that an exogenous inhibitor and activator changes Turing wavelength through which to regulate spine densities. Finally, we discussed the deep regulation mechanisms of several reported regulators of dendritic spine shape and densities based on our simulation results. Our work might evoke attention to the mathematic model-based pathogenesis research for neuron diseases which are related to the dendritic spine pattern abnormalities and spark inspiration in the treatment research for these diseases.

The nonlinear initiation of side-branching by activator-inhibitor-substrate (Turing) morphogenesis

An understanding of the underlying mechanism of side-branching is paramount in controlling and/or therapeutically treating mammalian organs, such as lungs, kidneys, and glands. Motivated by an activator-inhibitor-substrate approach that is conjectured to dominate the initiation of side-branching in a pulmonary vascular pattern, I demonstrate a distinct transverse front instability in which new fingers grow out of an oscillatory breakup dynamics at the front line without any typical length scale. These two features are attributed to unstable peak solutions in 1D that subcritically emanate from Turing bifurcation and that exhibit repulsive interactions. The results are based on a bifurcation analysis and numerical simulations and provide a potential strategy toward also developing a framework of side-branching for other biological systems, such as plant roots and cellular protrusions.

High repeatability from 3D experimental platform for quantitative analysis of cellular branch pattern formations

Three-dimensional (3D) cell and tissue cultures more closely mimic biological environments than two-dimensional (2D) cultures and are therefore highly desirable in culture experiments. However, 3D cultures often fail to yield repeatable experimental results because of variation in the initial culture conditions, such as cell density and distribution in the extracellular matrix, and therefore reducing such variation is a paramount concern. Here, we present a 3D culture platform that demonstrates highly repeatable experimental results, obtained by controlling the initial cell cluster shape in the gel cube culture device. A micro-mould with the desired shape was fabricated by photolithography or machining, creating a 3D pocket in the extracellular matrix contained in the device. Highly concentrated human bronchial epithelial cells were then injected in the pocket so that the cell cluster shape matched the fabricated mould shape. Subsequently, the cubic device supplied multi-directional scanning, enabling high-resolution capture of the whole tissue structure with only a low-magnification lens. The proposed device significantly improved the repeatability of the developed branch pattern, and multi-directional scanning enabled quantitative analysis of the developed branch pattern formations. A mathematical simulation was also conducted to reveal the mechanisms of branch pattern formation. The proposed platform offers the potential to accelerate any research field that conducts 3D culture experiments, including tissue regeneration and drug development.

Endothelial cell regulation of salivary gland epithelial patterning

Perfusion-independent regulation of epithelial pattern formation by the vasculature during organ development and regeneration is of considerable interest for application in restoring organ function. During murine submandibular salivary gland development, the vasculature co-develops with the epithelium during branching morphogenesis; however, it is not known whether the vasculature has instructive effects on the epithelium. Using pharmacological inhibitors and siRNA knockdown in embryonic organ explants, we determined that VEGFR2-dependent signaling is required for salivary gland epithelial patterning. To test directly for a requirement for endothelial cells in instructive epithelial patterning, we developed a novel ex vivo cell fractionation/reconstitution assay. Immuno-depletion of CD31⁺ endothelial cells in this assay confirmed a requirement for endothelial cells in epithelial patterning of the gland. Depletion of endothelial cells or inhibition of VEGFR2 signaling in organ explants caused an aberrant increase in cells expressing the ductal proteins K19 and K7, with a reduction in Kit⁺ progenitor cells in the endbuds of reconstituted glands. Addition of exogenous endothelial cells to reconstituted glands restored epithelial patterning, as did supplementation with the endothelial cell-regulated mesenchymal factors IGFBP2 and IGFBP3. Our results demonstrate that endothelial cells promote expansion of Kit⁺ progenitor cells and suppress premature ductal differentiation in early developing embryonic submandibular salivary gland buds.

In Vitro Experimental Model for the Long-Term Analysis of Cellular Dynamics During Bronchial Tree Development from Lung Epithelial Cells

Lung branching morphogenesis has been studied for decades, but the underlying developmental mechanisms are still not fully understood. Cellular movements dynamically change during the branching process, but it is difficult to observe long-term cellular dynamics by in vivo or tissue culture experiments. Therefore, developing an in vitro experimental model of bronchial tree would provide an essential tool for developmental biology, pathology, and systems biology. In this study, we succeeded in reconstructing a bronchial tree in vitro by using primary human bronchial epithelial cells. A high concentration gradient of bronchial epithelial cells was required for branching initiation, whereas homogeneously distributed endothelial cells induced the formation of successive branches. Subsequently, the branches grew in size to the order of millimeter. The developed model contains only two types of cells and it facilitates the analysis of lung branching morphogenesis. By taking advantage of our experimental model, we carried out long-term time-lapse observations, which revealed self-assembly, collective migration with leader cells, rotational motion, and spiral motion of epithelial cells in each developmental event. Mathematical simulation was also carried out to analyze the self-assembly process and it revealed simple rules that govern cellular dynamics. Our experimental model has provided many new insights into lung development and it has the potential to accelerate the study of developmental mechanisms, pattern formation, left–right asymmetry, and disease pathogenesis of the human lung.

Turing mechanism underlying a branching model for lung morphogenesis

The mammalian lung develops through branching morphogenesis. Two primary forms of branching, which occur in order, in the lung have been identified: tip bifurcation and side branching. However, the mechanisms of lung branching morphogenesis remain to be explored. In our previous study, a biological mechanism was presented for lung branching pattern formation through a branching model. Here, we provide a mathematical mechanism underlying the branching patterns. By decoupling the branching model, we demonstrated the existence of Turing instability. We performed Turing instability analysis to reveal the mathematical mechanism of the branching patterns. Our simulation results show that the Turing patterns underlying the branching patterns are spot patterns that exhibit high local morphogen concentration. The high local morphogen concentration induces the growth of branching. Furthermore, we found that the sparse spot patterns underlie the tip bifurcation patterns, while the dense spot patterns underlies the side branching patterns. The dispersion relation analysis shows that the Turing wavelength affects the branching structure. As the wavelength decreases, the spot patterns change from sparse to dense, the rate of tip bifurcation decreases and side branching eventually occurs instead. In the process of transformation, there may exists hybrid branching that mixes tip bifurcation and side branching. Since experimental studies have reported that branching mode switching from side branching to tip bifurcation in the lung is under genetic control, our simulation results suggest that genes control the switch of the branching mode by regulating the Turing wavelength. Our results provide a novel insight into and understanding of the formation of branching patterns in the lung and other biological systems.

Directing three-dimensional multicellular morphogenesis by self-organization of vascular mesenchymal cells in hyaluronic acid hydrogels

BACKGROUND

Physical scaffolds are useful for supporting cells to form three-dimensional (3D) tissue. However, it is non-trivial to develop a scheme that can robustly guide cells to self-organize into a tissue with the desired 3D spatial structures. To achieve this goal, the rational regulation of cellular self-organization in 3D extracellular matrix (ECM) such as hydrogel is needed.

RESULTS

In this study, we integrated the Turing reaction-diffusion mechanism with the self-organization process of cells and produced multicellular 3D structures with the desired configurations in a rational manner. By optimizing the components of the hydrogel and applying exogenous morphogens, a variety of multicellular 3D architectures composed of multipotent vascular mesenchymal cells (VMCs) were formed inside hyaluronic acid (HA) hydrogels. These 3D architectures could mimic the features of trabecular bones and multicellular nodules. Based on the Turing reaction-diffusion instability of morphogens and cells, a theoretical model was proposed to predict the variations observed in 3D multicellular structures in response to exogenous factors. It enabled the feasibility to obtain diverse types of 3D multicellular structures by addition of Noggin and/or BMP2.

CONCLUSIONS

The morphological consistency between the simulation prediction and experimental results probably revealed a Turing-type mechanism underlying the 3D self-organization of VMCs in HA hydrogels. Our study has provided new ways to create a variety of self-organized 3D multicellular architectures for regenerating biomaterial and tissues in a Turing mechanism-based approach.

An in vitro-in silico interface platform for spatiotemporal analysis of pattern formation in collective epithelial cells

A multicellular organization is a complex resulting from the coordinated migration of cells to form a specific pattern. The directionality of migration is governed by the mechanical and molecular dynamics of factors secreted from the cells. The mechanism underlying pattern formation is too complex to unveil by culture experiments alone. A mathematical model could provide a powerful tool for elucidating the mechanism of pattern formation by computing the molecular dynamics, which are difficult to visualize by culture experiments. However, there tends to be a gap between mathematical models and experimental research due to incongruity between the idealized conditions of the model and the experimental results. This paper presents an in vitro-in silico interface platform for elucidating the logic of multicellular pattern formation. Two-dimensional collective cell pattern formation was developed using normal human bronchial epithelial cells. Then, geometrical control of collective cells followed by feedback iteration was used to bridge the gap between the mathematical model and in vitro experiments. The mechanisms underlying the pattern formation of bronchial epithelial cells were evaluated using a reaction-diffusion model. The results indicated that differences in the diffusion rates of the activator and inhibitor determine the direction of collective cell migration to form a specific pattern.

Tissue in Cube: In Vitro 3D Culturing Platform with Hybrid Gel Cubes for Multidirectional Observations

An in vitro 3D culturing platform enabling multidirectional observations of 3D biosamples is presented. The 3D structure of biosamples can be recognized without fluorescence. The cubic platform employs two types of hydrogels that are compatible with conventional culture dishes or well plates, facilitating growth in culture, ease of handling, and viewing at multiple angles.

High-throughput mathematical analysis identifies Turing networks for patterning with equally diffusing signals

The Turing reaction-diffusion model explains how identical cells can self-organize to form spatial patterns. It has been suggested that extracellular signaling molecules with different diffusion coefficients underlie this model, but the contribution of cell-autonomous signaling components is largely unknown. We developed an automated mathematical analysis to derive a catalog of realistic Turing networks. This analysis reveals that in the presence of cell-autonomous factors, networks can form a pattern with equally diffusing signals and even for any combination of diffusion coefficients. We provide a software (available at http://www.RDNets.com) to explore these networks and to constrain topologies with qualitative and quantitative experimental data. We use the software to examine the self-organizing networks that control embryonic axis specification and digit patterning. Finally, we demonstrate how existing synthetic circuits can be extended with additional feedbacks to form Turing reaction-diffusion systems. Our study offers a new theoretical framework to understand multicellular pattern formation and enables the wide-spread use of mathematical biology to engineer synthetic patterning systems.