Development and validation of computational models of cellular interaction

In this paper we take the view that computational models of biological systems should satisfy two conditions – they should be able to predict function at a systems biology level, and robust techniques of validation against biological models must be available. A modelling paradigm for developing a predictive computational model of cellular interaction is described, and methods of providing robust validation against biological models are explored, followed by a consideration of software issues

Evolutionary development of tensegrity structures

Contributions from the emerging fields of molecular genetics and evo-devo (evolutionary developmental biology) are greatly benefiting the field of evolutionary computation, initiating a promise of renewal in the traditional methodology. While direct encoding has constituted a dominant paradigm, indirect ways to encode the solutions have been reported, yet little attention has been paid to the benefits of the proposed methods to real problems. In this work, we study the biological properties that emerge by means of using indirect encodings in the context of form-finding problems. A novel indirect encoding model for artificial development has been defined and applied to an engineering structural-design problem, specifically to the discovery of tensegrity structures. This model has been compared with a direct encoding scheme. While the direct encoding performs similarly well to the proposed method, indirect-based results typically outperform the direct-based results in aspects not directly linked to the nature of the problem itself, but to the emergence of properties found in biological organisms, like organicity, generalization capacity, or modularity aspects which are highly valuable in engineering

A Sub-Cellular Viscoelastic Model for Cell Population Mechanics

Understanding the biomechanical properties and the effect of biomechanical force on epithelial cells is key to understanding how epithelial cells form uniquely shaped structures in two or three-dimensional space. Nevertheless, with the limitations and challenges posed by biological experiments at this scale, it becomes advantageous to use mathematical and ‘in silico’ (computational) models as an alternate solution. This paper introduces a single-cell-based model representing the cross section of a typical tissue. Each cell in this model is an individual unit containing several sub-cellular elements, such as the elastic plasma membrane, enclosed viscoelastic elements that play the role of cytoskeleton, and the viscoelastic elements of the cell nucleus. The cell membrane is divided into segments where each segment (or point) incorporates the cell's interaction and communication with other cells and its environment. The model is capable of simulating how cells cooperate and contribute to the overall structure and function of a particular tissue; it mimics many aspects of cellular behavior such as cell growth, division, apoptosis and polarization. The model allows for investigation of the biomechanical properties of cells, cell-cell interactions, effect of environment on cellular clusters, and how individual cells work together and contribute to the structure and function of a particular tissue. To evaluate the current approach in modeling different topologies of growing tissues in distinct biochemical conditions of the surrounding media, we model several key cellular phenomena, namely monolayer cell culture, effects of adhesion intensity, growth of epithelial cell through interaction with extra-cellular matrix (ECM), effects of a gap in the ECM, tensegrity and tissue morphogenesis and formation of hollow epithelial acini. The proposed computational model enables one to isolate the effects of biomechanical properties of individual cells and the communication between cells and their microenvironment while simultaneously allowing for the formation of clusters or sheets of cells that act together as one complex tissue

Designing stem cell niches for differentiation and self-renewal

Mesenchymal stem cells, characterized by their ability to differentiate into skeletal tissues and self-renew, hold great promise for both regenerative medicine and novel therapeutic discovery. However, their regenerative capacity is retained only when in contact with their specialized microenvironment, termed the stem cell niche. Niches provide structural and functional cues that are both biochemical and biophysical, stem cells integrate this complex array of signals with intrinsic regulatory networks to meet physiological demands. Although, some of these regulatory mechanisms remain poorly understood or difficult to harness with traditional culture systems. Biomaterial strategies are being developed that aim to recapitulate stem cell niches, by engineering microenvironments with physiological-like niche properties that aim to elucidate stem cell-regulatory mechanisms, and to harness their regenerative capacity in vitro. In the future, engineered niches will prove important tools for both regenerative medicine and therapeutic discoveries

Integrated biomechanical model of cells embedded in extracellular matrix

Nature encourages diversity in life forms (morphologies). The study of morphogenesis deals with understanding those processes that arise during the embryonic development of an organism. These processes control the organized spatial distribution of cells, which in turn gives rise to the characteristic form for the organism. Morphogenesis is a multi-scale modeling problem that can be studied at the molecular, cellular, and tissue levels. Here, we study the problem of morphogenesis at the cellular level by introducing an integrated biomechanical model of cells embedded in the extracellular matrix. The fundamental aspects of mechanobiology essential for studying morphogenesis at the cellular level are the cytoskeleton, extracellular matrix (ECM), and cell adhesion. Cells are modeled using tensegrity architecture. Our simulations demonstrate cellular events, such as differentiation, migration, and division using an extended tensegrity architecture that supports dynamic polymerization of the micro-filaments of the cell. Thus, our simulations add further support to the cellular tensegrity model. Viscoelastic behavior of extracellular matrix is modeled by extending one-dimensional mechanical models (by Maxwell and by Voigt) to three dimensions using finite element methods. The cell adhesion is modeled as a general Velcro-type model. We integrated the mechanics and dynamics of cell, ECM, and cell adhesion with a geometric model to create an integrated biomechanical model. In addition, the thesis discusses various computational issues, including generating the finite element mesh, mesh refinement, re-meshing, and solution mapping. As is known from a molecular level perspective, the genetic regulatory network of the organism controls this spatial distribution of cells along with some environmental factors modulating the process. The integrated biomechanical model presented here, besides generating interesting morphologies, can serve as a mesoscopic-scale platform upon which future work can correlate with the underlying genetic network

Behavior finding: Morphogenetic Designs Shaped by Function

Evolution has shaped an incredible diversity of multicellular living organisms, whose complex forms are self-made through a robust developmental process. This fundamental combination of biological evolution and development has served as an inspiration for novel engineering design methodologies, with the goal to overcome the scalability problems suffered by classical top-down approaches. Top-down methodologies are based on the manual decomposition of the design into modular, independent subunits. In contrast, recent computational morphogenetic techniques have shown that they were able to automatically generate truly complex innovative designs. Algorithms based on evolutionary computation and artificial development have been proposed to automatically design both the structures, within certain constraints, and the controllers that optimize their function. However, the driving force of biological evolution does not resemble an enumeration of design requirements, but much rather relies on the interaction of organisms within the environment. Similarly, controllers do not evolve nor develop separately, but are woven into the organism’s morphology. In this chapter, we discuss evolutionary morphogenetic algorithms inspired by these important aspects of biological evolution. The proposed methodologies could contribute to the automation of processes that design “organic” structures, whose morphologies and controllers are intended to solve a functional problem. The performance of the algorithms is tested on a class of optimization problems that we call behavior-finding. These challenges are not explicitly based on morphology or controller constraints, but only on the solving abilities and efficacy of the design. Our results show that morphogenetic algorithms are well suited to behavior-finding

Tensegrity and mechanoregulation: from skeleton to cytoskeleton

AbstractObjective: To elucidate how mechanical stresses that are applied to the whole organism are transmitted to individual cells and transduced into a biochemical response.Design: In this article, we describe fundamental design principles that are used to stabilize the musculoskeletal system at many different size scales and show that these design features are embodied in one particular form of architecture that is known as tensegrity.Results: Tensegrity structures are characterized by use of continuous tension and local compression; architecture, prestress (internal stress prior to application of external force), and triangulation play the most critical roles in terms of determining their mechanical stability. In living organisms, use of a hierarchy of tensegrity networks both optimizes structural efficiency and provides a mechanism to mechanically couple the parts with the whole: mechanical stresses applied at the macroscale result in structural rearrangements at the cell and molecular level.Conclusion: Due to use of tensegrity architecture, mechanical stress is concentrated and focused on signal transducing molecules that physically associate with cell surface molecules that anchor cells to extracellular matrix, such as integrins, and with load-bearing elements within the internal cytoskeleton and nucleus. Mechanochemical transduction may then proceed through local stress-dependent changes in molecular mechanics, thermodynamics, and kinetics within the cell. In this manner, the entire cellular response to stress may be orchestrated and tuned by altering the prestress in the cell, just as changing muscular tone can alter mechanical stability and structural coordination throughout the whole musculoskeletal system

A multi-modular tensegrity model of an actin stress fiber

Stress fibers are contractile bundles in the cytoskeleton that stabilize cell structure by exerting traction forces on the extracellular matrix. Individual stress fibers are molecular bundles composed of parallel actin and myosin filaments linked by various actin-binding proteins, which are organized end-on-end in a sarcomere-like pattern within an elongated three-dimensional network. While measurements of single stress fibers in living cells show that they behave like tensed viscoelastic fibers, precisely how this mechanical behavior arises from this complex supramolecular arrangement of protein components remains unclear. Here we show that computationally modeling a stress fiber as a multi-modular tensegrity network can predict several key behaviors of stress fibers measured in living cells, including viscoelastic retraction, fiber splaying after severing, non-uniform contraction, and elliptical strain of a puncture wound within the fiber. The tensegrity model can also explain how they simultaneously experience passive tension and generate active contraction forces; in contrast, a tensed cable net model predicts some, but not all, of these properties. Thus, tensegrity models may provide a useful link between molecular and cellular scale mechanical behaviors and represent a new handle on multi-scale modeling of living materials.Engineering and Applied SciencesOther Research Uni