Mechanistic Image-Based Modelling: Concepts and Applications.

Advancements in imaging techniques have led to a rapid growth of available imaging data. Interpretation of the imaging data and extraction of biologically, physiologically and/or medically relevant information, however, remains challenging. In contrast, mechanistic computational modelling provides a means to formalise and dissect mechanisms governing the behaviour of complex systems. However, its application often is limited due to the lack of relevant data for model building and validation. Exploitation of the imaging data to build, parameterise and validate computational models gives rise to an image-based modelling approach. In this chapter, we introduce the basics of the mechanistic image-based modelling approach and review its application in developmental biology and biomedical research as well as for medical device development and drug discovery and development. Implementation of image-based modelling in pharmaceutical industry holds promise to further advance model-informed drug discovery and development and aids substantially in our understanding of drug pharmacokinetic, pharmacodynamic and ultimately de-risk drug development.

Cell number in mesenchymal stem cell aggregates dictates cell stiffness and chondrogenesis.

BACKGROUND: Although mesenchymal stem/stromal cell (MSC) chondrogenic differentiation has been thoroughly investigated, the rudiments for enhancing chondrogenesis have remained largely dependent on external cues. Focus to date has been on extrinsic variables such as soluble signals, culture conditions (bioreactors), and mechanical stimulation. However, the role of intrinsic mechanisms of MSC programming-based mechanobiology remains to be explored. Since aggregation of MSCs, a prerequisite for chondrogenesis, generates tension within the cell agglomerate, we inquired if the initial number of cells forming the aggregate (aggregate cell number (ACN)) can impact chondrogenesis. METHODS: Aggregates of varying ACN were formed using well-established centrifugation approach. Progression of chondrogenic differentiation in the aggregates was assessed over 3 weeks in presence and absence of transforming growth factor-beta 1 (TGF-ß1). Mechanical properties of the cells were characterized using high-throughput real-time deformability cytometry (RT-DC), and gene expression was analyzed using Affymetrix gene array. Expression of molecular markers linked to chondrogenesis was assessed using western blot and immunofluorescence. RESULTS: Reducing ACN from 500 k to 70 k lead to activation and acceleration of the chondrogenic differentiation, independent of soluble chondro-inductive factors, which involves changes to ß-catenin-dependent TCF/LEF transcriptional activity and expression of anti-apoptotic protein survivin. RT-DC analysis revealed that stiffness and size of cells within aggregates are modulated by ACN. A direct correlation between progression of chondrogenesis and emergence of stiffer cell phenotype was found. Affymetrix gene array analysis revealed a downregulation of genes associated with lipid synthesis and regulation, which could account for observed changes in cell stiffness. Immunofluorescence and western blot analysis revealed that increasing ACN upregulates the expression of lipid raft protein caveolin-1, a ß-catenin binding partner, and downregulates the expression of N-cadherin. As a demonstration of the relevance of these findings in MSC-based strategies for skeletal repair, it is shown that implanting aggregates within collagenous matrix not only decreases the necessity for high cell numbers but also leads to marked improvement in the quality of the deposited tissue. CONCLUSIONS: This study presents a simple and donor-independent strategy to enhance the efficiency of MSC chondrogenic differentiation and identifies changes in cell mechanics coincident with MSC chondrogenesis with potential translational applications.

Generation of 3D Soluble Signal Gradients in Cell-Laden Hydrogels Using Passive Diffusion.

Soluble signal gradients play an important role in organ patterning, cell migration, and differentiation. Currently, signal gradients in 2D cell culture are realized using microfluidics and here cells are exposed to high and nonphysiological shear stress. Tissue morphogenesis (organogenesis) however occurs in 3D and therefore there is a need for simple and practical systems to impose gradients to cells dispersed in 3D matrix. Herein, a 3D gradient generator based on passive diffusion elements that recapitulates interstitial flow and is capable of imposing predictable gradients over long length scales (6 mm) lasting up to 48 h to cells dispersed in a hydrogel environment is reported. Using recombinant human WNT3A (rhWNT3A), the spatiotemporal activation of the canonical WNT pathway in human epithelial kidney cells and human mesenchymal stems cells expressing a green fluorescence protein reporter on a transcription factor/lymphoid enhancer-binding factor (TCF/LEF) promoter is demonstrated. By refining computation models based on experimental findings, the diffusion coefficient of rhWNT3A in presence of human cells in 3D is determined. Furthermore, the formation of rhBMP4 gradients is visualized using immunohistochemistry by staining for phospho-SMAD1/5, the downstream targets of the bone morphogenetic protein (BMP) pathway. The simplicity of the gradient generator is expected to spur its adoption in studying developmental biology paradigms in vitro.

LBIBCell: a cell-based simulation environment for morphogenetic problems.

MOTIVATION: The simulation of morphogenetic problems requires the simultaneous and coupled simulation of signalling and tissue dynamics. A cellular resolution of the tissue domain is important to adequately describe the impact of cell-based events, such as cell division, cell-cell interactions and spatially restricted signalling events. A tightly coupled cell-based mechano-regulatory simulation tool is therefore required. RESULTS: We developed an open-source software framework for morphogenetic problems. The environment offers core functionalities for the tissue and signalling models. In addition, the software offers great flexibility to add custom extensions and biologically motivated processes. Cells are represented as highly resolved, massless elastic polygons; the viscous properties of the tissue are modelled by a Newtonian fluid. The Immersed Boundary method is used to model the interaction between the viscous and elastic properties of the cells, thus extending on the IBCell model. The fluid and signalling processes are solved using the Lattice Boltzmann method. As application examples we simulate signalling-dependent tissue dynamics. AVAILABILITY AND IMPLEMENTATION: The documentation and source code are available on http://tanakas.bitbucket.org/lbibcell/index.html

Simulating tissue morphogenesis and signaling.

During embryonic development tissue morphogenesis and signaling are tightly coupled. It is therefore important to simulate both tissue morphogenesis and signaling simultaneously in in silico models of developmental processes. The resolution of the processes depends on the questions of interest. As part of this chapter we introduce different descriptions of tissue morphogenesi s. In the simplest approximation tissue is a continuous domain and tissue expansion is described according to a predefined function of time (and possibly space). In a slightly more advanced version the expansion speed and direction of the tissue may depend on a signaling variable that evolves on the domain. Both versions will be referred to as "prescribed growth." Alternatively tissue can be regarded as incompressible fluid and can be described with Navier-Stokes equations. Local cell expansion, proliferation, and death are then incorporated by a source term. In other applications the cell boundaries may be important and cell-based models must be introduced. Finally, cells may move within the tissue, a process best described by agent-based models.

Inter-dependent tissue growth and Turing patterning in a model for long bone development.

The development of long bones requires a sophisticated spatial organization of cellular signalling, proliferation, and differentiation programs. How such spatial organization emerges on the growing long bone domain is still unresolved. Based on the reported biochemical interactions we developed a regulatory model for the core signalling factors IHH, PTCH1, and PTHrP and included two cell types, proliferating/resting chondrocytes and (pre-)hypertrophic chondrocytes. We show that the reported IHH-PTCH1 interaction gives rise to a Schnakenberg-type Turing kinetics, and that inclusion of PTHrP is important to achieve robust patterning when coupling patterning and tissue dynamics. The model reproduces relevant spatiotemporal gene expression patterns, as well as a number of relevant mutant phenotypes. In summary, we propose that a ligand-receptor based Turing mechanism may control the emergence of patterns during long bone development, with PTHrP as an important mediator to confer patterning robustness when the sensitive Turing system is coupled to the dynamics of a growing and differentiating tissue. We have previously shown that ligand-receptor based Turing mechanisms can also result from BMP-receptor, SHH-receptor, and GDNF-receptor interactions, and that these reproduce the wildtype and mutant patterns during digit formation in limbs and branching morphogenesis in lung and kidneys. Receptor-ligand interactions may thus constitute a general mechanism to generate Turing patterns in nature.