Learning the cell cycle with a game: Virtual experiments in cell biology

Cell Cycle Learn (CCL) is a learning game designed for undergraduate students in Biology to learn common knowledge about the cell-division cycle along with practical skills related with setting up an experiment and the scientific method in general. In CCL, learners are guided through the process of formulating hypotheses, conducting virtual experiments and analysing the results in order to validate or invalidate the hypotheses. The game has been designed in the University of Toulouse and introduced last year as part of the curriculum of a cellular biology class. This paper presents early results of an evaluation of the game enabled by questionnaires filled by the participants and game data collected during the training sessions. The results demonstrate with examples that both types of data can be used to assess the game's utility

A Synthesis of the Cell2Organ Developmental Model

Over the past twenty years, many techniques have appeared to simulate artificial creatures at different scales: starting with the simulation of their behaviour at the beginning of the 90s, researchers have continued by modifying the robots’ morphologies to adapt them to their environment. More recently, developmental mechanisms of living beings have inspired artificial embryogenesis to generate smaller creatures composed of tens to thousands of cells. However, we observe that no traversal model, able to simulate creatures at these different scales, exists. Starting from a unique cell, our project’s goal is to develop a complete creature, which contains different organs and high-level functionalities. Thus, we propose a developmental model based on three layers of simulation. The first one consists in a chemical environment where cells can divide and manipulate substrates and chemical reactions. The aim is to develop a metabolism adapted to the environment. Often forgotten in classical models, this is crucial in all living systems. It allows every organism to perform actions in its environment with accumulated energy. Our developmental model also includes a physic layer that allows the creatures to produce global motion in a Newtonian world. Cells can here modify their shape to modify the shape of the organism. A hydrodynamic layer simulates substrate flows in the environment so that the cells can modify the whole environment. Finally, we propose a new method to get rid of the molecular morphogens by the mean of a L-System driven morphogenesis

A Synthesis of the Cell2Organ Developmental Model

Over the past twenty years, many techniques have appeared to simulate artificial creatures at different scales: starting with the simulation of their behaviour at the beginning of the 90s, researchers have continued by modifying the robots’ morphologies to adapt them to their environment. More recently, developmental mechanisms of living beings have inspired artificial embryogenesis to generate smaller creatures composed of tens to thousands of cells. However, we observe that no traversal model, able to simulate creatures at these different scales, exists. Starting from a unique cell, our project’s goal is to develop a complete creature, which contains different organs and high-level functionalities. Thus, we propose a developmental model based on three layers of simulation. The first one consists in a chemical environment where cells can divide and manipulate substrates and chemical reactions. The aim is to develop a metabolism adapted to the environment. Often forgotten in classical models, this is crucial in all living systems. It allows every organism to perform actions in its environment with accumulated energy. Our developmental model also includes a physic layer that allows the creatures to produce global motion in a Newtonian world. Cells can here modify their shape to modify the shape of the organism. A hydrodynamic layer simulates substrate flows in the environment so that the cells can modify the whole environment. Finally, we propose a new method to get rid of the molecular morphogens by the mean of a L-System driven morphogenesis

An introduction to the Bio-Logic of Artificial Creatures

The purpose of this volume is to present current work of the Intelligent Computer Graphics community, a community growing up year after year. This volume is a kind of continuation of the previously published Springer volume "Artificial Intelligence Techniques for Computer Graphics." Nowadays, intelligent techniques are more and more used in Computer Graphics in order, not only to optimise the processing time, but also to find more accurate solutions for a lot of Computer Graphics problems, than with traditional methods. This volume contains both invited and selected extended papers from the last 3IA Conference (3IA’2009), which has been held in Athens (Greece) in May 2009. The Computer Graphics areas approached in this volume are behavioural modelling, declarative modelling, intelligent modelling and rendering, data visualisation, scene understanding, realistic rendering, and more

Optimization of synchronization experiments using a checkpoint-oriented cell cycle simulator

National audienceCell cycle synchronization at a specific stage is often an essential requirement to investigate biological events and mechanisms using the large panel of molecular and cellular biology technologies. Optimization of the synchronization parameters is most of the time neglected, which could result in experimental time wasting or even in erroneous conclusions. Here we report the development of a cell cycle checkpoint-oriented simulator, based on agent-based modeling (ABM), that reproduces the dynamic behavior of a proliferating cell population and its response to checkpoint activation

Developmental Design of Synthetic Bacterial Architectures by Morphogenetic Engineering

International audienceSynthetic biology is an emerging scientific field that promotes the standardized manufacturing of biological components without natural equivalents. Its goal is to create artificial living systems that can meet various needs in health care or energy domains. While most works are focused on the individual bacterium as a chemical reactor, our project, SynBioTIC, addresses a novel and more complex challenge: shape engineering; that is, the redesign of natural morphogenesis toward a new kind of developmental 3D printing. Potential applications include organ growth, natural computing in biocircuits, or future vegetal houses. To create in silico multicellular organisms that exhibit specific shapes, we construe their development as an iterative process combining fundamental collective phenomena such as homeostasis, patterning, segmentation, and limb growth. Our numerical experiments rely on the existing Escherichia coli simulator Gro, a physicochemical computation platform offering reaction-diffusion and collision dynamics solvers. The synthetic bioware of our model executes a set of rules, or genome, in each cell. Cells can differentiate into several predefined types associated with specific actions (divide, emit signal, detect signal, die). Transitions between types are triggered by conditions involving internal and external sensors that detect various protein levels inside and around the cell. Indirect communication between bacteria is relayed by morphogen diffusion and the mechanical constraints of 2D packing. Starting from a single bacterium, the overall architecture emerges in a purely endogenous fashion through a series of developmental stages, inlcuding proliferation, differentiation, morphogen diffusion, and synchronization. The genome can be parametrized to control the growth and features of appendages individually. As exemplified by the L and T shapes that we obtain, certain precursor cells can be inhibited while others can create limbs of varying size (divergence of the homology). Such morphogenetic phenotypes open the way to more complex shapes made of a recursive array of core bodies and limbs and, most importantly, to an evolutionary developmental exploration of unplanned functional forms

Spatial Computing in Synthetic Bioware: Creating Bacterial Architectures

International audienceSynthetic biology is an emerging scientific field that promotes the standardized manufacturing of biological components without natural equivalents. Its goal is to create artificial living systems that can meet various needs in health care, nanotechnology and energy. Most works are currently focused on the individual bacterium as a chemical reactor. Our project, SynBioTIC, addresses a novel and more complex challenge: shape engineering, i.e. the redesign of natural morphogenesis toward a new kind of " developmental 3D printing ". Potential applications include organ growth, natural computing in biocircuits, or future vegetal houses. Using realistic agent-based simulations of bacterial mats, we experiment with mechanisms allowing cell assemblies to collectively self-repair and develop complex structures. To create multicellular organisms that exhibit specific shapes (a completely original task) we construe their development iteratively by combining basic processes such as homeostasis, segmentation, and controlled proliferation in silico. We use the E. coli simulator Gro 1 , a physico-chemical computation platform offering reaction-diffusion and collision dynamics solvers. The synthetic " bioware " of our model executes a set of rules, or " genome " , in each cell. Cells can differentiate into several predefined types associated with specific actions (divide, tumble, emit signal, die, etc.). Transitions between types are triggered by conditions involving internal and external sensors that detect various protein levels inside and around the cell. There is no direct molecular signaling between two neighboring bacteria, only indirect communication via morphogen diffusion and the mechanical constraints of 2D packing. In any case, the overall architecture emerges in a purely endogenous fashion. For now, cell behaviors are set by rules hand-coded in the Gro script language. Starting from a single bacterium, our artificial creatures execute a series of developmental stages. First, isotropic proliferation produces a roughly circular population characterized by homeostatic activity (black and white cores in Fig. 1a,b). This is based on leader cells emitting a morphogen, while other cells continually divide and die at the periphery where the morphogen concentra-1 Jang, Oishi, Egbert & Klavins (2012) ACS Syn Biol, 1:365–74. (a) (b) (c) Figure 1: Example of simulated organisms. (a,b) T and L shapes. Each limb of the organism stems from differentiated precursor cells. Starting from a four-pointed star, this makes it possible to introduce a " divergence of homology " through different parameter values in each limb, whether unequal lengths or complete silencing. (c) Three-pointed star shape. Here, limb growth is undifferentiated and the organism exhibits radial symmetry. tion drops. Then, the central region of the disc differentiates from the crown. Each cell also contains an oscillatory mechanism acting like a internal clock. In the crown, these oscillators are synchronized, i.e. characterized by a uniform phase. At this stage, a new wave of morphogen is triggered by a randomly activated cell on the crown, and rapidly propagates (suppressing any competitor wave). The encounter between the wave front and the current state of the oscillator determines whether each cell differentiates, and into what type. The period of oscillations controls the number of segments that can appear. Finally, precursor cells emerge at the periphery of these segments and stimulate new local proliferation , which eventually triggers limb growth in a way similar to the apical meristem of plant shoots (Fig. 1c). Applying this mechanism to two segments and two precursors , North and South, then on the equator that they form (areas of equal morphogen concentration), the system gives rise to a second pair, East and West, i.e. four differentiated seeds in total. This makes it possible to control the growth and features of single appendages. The L and T shapes of Fig. 1 exemplify this " divergence of homology " : some precursors are inhibited while others create limbs of varying size. Such morphogenetic phenotypes allow us to envision more complex shapes made of an array of cores and limbs, by iterating the above processes. Most importantly, they open the door to an evolutionary (" evo-devo ") exploration