News Article | April 17, 2017
From the clown fish to leopards, skin colour patterns in animals arise from microscopic interactions among coloured cells that obey equations discovered by the mathematician Alan Turing. Today, researchers at the University of Geneva (UNIGE), Switzerland, and SIB Swiss Institute of Bioinformatics report in the journal Nature that a southwestern European lizard slowly acquires its intricate adult skin colour by changing the colour of individual skin scales using an esoteric computational system invented in 1948 by another mathematician: John von Neumann. The Swiss team shows that the 3D geometry of the lizard's skin scales causes the Turing mechanism to transform into the von Neumann computing system, allowing biology-driven research to link, for the first time, the work of these two mathematical giants. A multidisciplinary team of biologists, physicists and computer scientists lead by Michel Milinkovitch, professor at the Department of Genetics and Evolution of the UNIGE Faculty of Science, Switzerland and Group Leader at the SIB Swiss Institute of Bioinformatics, realised that the brown juvenile ocellated lizard (Timon lepidus) gradually transforms its skin colour as it ages to reach an intricate adult labyrinthine pattern where each scale is either green or black. This observation is at odd with the mechanism, discovered in 1952 by the mathematician Alan Turing, that involves microscopic interactions among coloured cells. To understand why the pattern is forming at the level of scales, rather than at the level of biological cells, two PhD students, Liana Manukyan and Sophie Montandon, followed individual lizards during 4 years of their development from hatchlings crawling out of the egg to fully mature animals. For multiple time points, they reconstructed the geometry and colour of the network of scales by using a very high resolution robotic system developed previously in the Milinkovitch laboratory. The researchers were then surprised to see the brown juvenile scales change to green or black, then continue flipping colour (between green and black) during the life of the animal. This very strange observation prompted Milinkovitch to suggest that the skin scale network forms a so-called 'cellular automaton'. This esoteric computing system was invented in 1948 by the mathematician John von Neumann. Cellular automata are lattices of elements in which each element changes its state (here, its colour, green or black) depending on the states of neighbouring elements. The elements are called cells but are not meant to represent biological cells; in the case of the lizards, they correspond to individual skin scales. These abstract automata were extensively used to model natural phenomena, but the UNIGE team discovered what seems to be the first case of a genuine 2D automaton appearing in a living organism. Analyses of the four years of colour change allowed the Swiss researchers to confirm Milinkovitch's hypothesis: the scales were indeed flipping colour depending of the colours of their neighbour scales. Computer simulations implementing the discovered mathematical rule generated colour patterns that could not be distinguished from the patterns of real lizards. How could the interactions among pigment cells, described by Turing equations, generate a von Neumann automaton exactly superposed to the skin scales? The skin of a lizard is not flat: it is very thin between scales and much thicker at the center of them. Given that Turing's mechanism involves movements of cells, or the diffusion of signals produced by cells, Milinkovitch understood that this variation of skin thickness could impact on the Turing's mechanism. The researchers then performed computer simulations including skin thickness and saw a cellular automaton behaviour emerge, demonstrating that a Cellular Automaton as a computational system is not just an abstract concept developed by John von Neumann, but also corresponds to a natural process generated by biological evolution. However, the automaton behaviour was imperfect as the mathematics behind Turing's mechanism and von Neumann automaton are very different. Milinkovitch called in the mathematician Stanislav Smirnov, Professor at the UNIGE, who was awarded the Fields Medal in 2010. Before long, Smirnov derived a so-called discretisation of Turing's equations that would constitute a formal link with von Neumann's automaton. Anamarija Fofonjka, a third PhD student in Milinkovitch's team implemented Smirnov new equations in computer simulations, obtaining a system that had become un-differentiable from a von Neumann automaton. The highly multidisciplinary team of researchers had closed the loop in this amazing journey, from biology to physics to mathematics ... and back to biology.
Buil A.,Swiss Institute of Bioinformatics |
Buil A.,University of Oslo |
Buil A.,King's College London
Nature genetics | Year: 2015
Understanding the genetic architecture of gene expression is an intermediate step in understanding the genetic architecture of complex diseases. RNA sequencing technologies have improved the quantification of gene expression and allow measurement of allele-specific expression (ASE). ASE is hypothesized to result from the direct effect of cis regulatory variants, but a proper estimation of the causes of ASE has not been performed thus far. In this study, we take advantage of a sample of twins to measure the relative contributions of genetic and environmental effects to ASE, and we find substantial effects from gene × gene (G×G) and gene × environment (G×E) interactions. We propose a model where ASE requires genetic variability in cis, a difference in the sequence of both alleles, but where the magnitude of the ASE effect depends on trans genetic and environmental factors that interact with the cis genetic variants.
Agency: European Commission | Branch: FP7 | Program: CPCSA | Phase: ICT-2013.9.9 | Award Amount: 72.73M | Year: 2013
Understanding the human brain is one of the greatest challenges facing 21st century science. If we can rise to the challenge, we can gain profound insights into what makes us human, develop new treatments for brain diseases and build revolutionary new computing technologies. Today, for the first time, modern ICT has brought these goals within sight. The goal of the Human Brain Project, part of the FET Flagship Programme, is to translate this vision into reality, using ICT as a catalyst for a global collaborative effort to understand the human brain and its diseases and ultimately to emulate its computational capabilities. The Human Brain Project will last ten years and will consist of a ramp-up phase (from month 1 to month 36) and subsequent operational phases.\nThis Grant Agreement covers the ramp-up phase. During this phase the strategic goals of the project will be to design, develop and deploy the first versions of six ICT platforms dedicated to Neuroinformatics, Brain Simulation, High Performance Computing, Medical Informatics, Neuromorphic Computing and Neurorobotics, and create a user community of research groups from within and outside the HBP, set up a European Institute for Theoretical Neuroscience, complete a set of pilot projects providing a first demonstration of the scientific value of the platforms and the Institute, develop the scientific and technological capabilities required by future versions of the platforms, implement a policy of Responsible Innovation, and a programme of transdisciplinary education, and develop a framework for collaboration that links the partners under strong scientific leadership and professional project management, providing a coherent European approach and ensuring effective alignment of regional, national and European research and programmes. The project work plan is organized in the form of thirteen subprojects, each dedicated to a specific area of activity.\nA significant part of the budget will be used for competitive calls to complement the collective skills of the Consortium with additional expertise.
Agency: European Commission | Branch: FP7 | Program: CP | Phase: ICT-2009.5.3 | Award Amount: 17.89M | Year: 2011
Medicine is undergoing a revolution that is transforming the nature of healthcare from reactive to preventive. The changes are catalyzed by a new systems approach to disease which focuses on integrated diagnosis, treatment and prevention of disease in individuals. This will replace our current mode of medicine over the coming years with a personalized predictive treatment . While the goal is clear, the path is fraught with challenges.P-medicine brings together international leaders in their fields to create an infrastructure that will facilitate this translation from current practice to personalized medicine. In achieving this objective p-medicine has formulated a coherent, integrated workplan for the design, development, integration and validation of technologically challenging areas of today.Our emphasis is on formulating an open, modular framework of tools and services, so that p-medicine can be adopted gradually, including efficient secure sharing and handling of large personalized data sets, enabling demanding Virtual Physiological Human (VPH) multiscale simulations (in silico oncology), building standards-compliant tools and models for VPH research, drawing on the VPH Toolkit and providing tools for large-scale, privacy-preserving data and literature mining, a key component of VPH research. We will ensure that privacy, non-discrimination, and access policies are aligned to maximize protection of and benefit to patients. The p-medicine tools and technologies will be validated within the concrete setting of advanced clinical research. Pilot cancer trials have been selected based on clear research objectives, emphasising the need to integrate multilevel datasets, in the domains of Wilms tumour, breast cancer and leukaemia. To sustain a self-supporting infrastructure realistic use cases will be built that will demonstrate tangible results for clinicians.The project is clinically driven and promotes the principle of open source and open standards.
Agency: European Commission | Branch: FP7 | Program: CP-FP | Phase: HEALTH.2013.2.4.2-1 | Award Amount: 8.33M | Year: 2014
Asymptomatic vascular damage accumulates for years before patients are identified and subjected to therapeutic measures. The limited knowledge on early vascular disease pathophysiology is reflected in the lack of therapeutic options. SysVasc aims to overcome this limitation by mounting a comprehensive systems medicine approach to elucidate pathological mechanisms, which will yield molecular targets for therapeutic intervention. The consortium is based on established multidisciplinary European research networks, including specialists in pre-clinical and clinical research, omics technologies, and systems biology from research intensive SMEs and academia; partners synergistically provide access to an extensive number of selected population-based cohorts and associated datasets, cutting edge modeling and simulation methods, and established cardiovascular disease (CVD) animal models and patient cohorts. The coordinated application of these tools and know-how will identify pathophysiological mechanisms and key molecules responsible for onset and progression of CVD and validate their potential to serve as molecular targets for therapeutic intervention. To this end, the consortium will also use unique resources to evaluate molecular homology between the available model systems and human disease, which will yield reliable essential preclinical research tools to explore proof of concepts for therapeutic intervention studies and ultimately translate relevant results into novel therapeutic approaches. Collectively, SysVasc will identify and validate novel biology-driven key molecular targets for CVD treatment. Major scientific, societal and economic impact is expected including, but not limited to, providing a valuable resource to further CVD research, and enhance competitiveness of participating SMEs and European health industry in general by translating knowledge into innovative services in therapeutic target and drug research.
Agency: European Commission | Branch: FP7 | Program: CP-FP | Phase: HEALTH.2012.2.2.2-1 | Award Amount: 8.22M | Year: 2013
In spite of valuable approaches applied to get a broad understanding of genetic, epidemiologic and molecular and system-level biological principles of human aging, cognitive decline remains as one of the greatest health challenges of the old age, with nearly 50% of adults over 85 afflicted of Alzheimers disease. Furthermore, drug development has not performed as expected in clinical trials, at least in part because of an insufficient mechanistic understanding at the systemic level in human. AgedBrainSYSBIO is a timely and straightforward project based on the integration of available transcriptomics, proteomics and metabolomics data, addition of relevant novel sets of data, their modeling and experimental testing in both human, mouse and drosophila. The concept is to identify subsets of pathways with two unique druggable hallmarks: (i) the validation of interactions occurring locally in subregions of neurons and (ii) a human and/or primate accelerated evolutionary signature, using six interacting approaches: (1) the identification of interacting protein networks from recent Late-Onset Alzheimer Disease- Genome Wide Association Studies (LOAD-GWAS) data, (2) the experimental validation of interconnected networks working in subregion of a neuron (such as dendrites and dendritic spines), (3) the inclusion of these experimentally validated networks in larger networks obtained from available databases to extend possible protein interactions, (4) the identification of human and/or primate positive selection either in coding or in regulatory gene sequences,(5) the manipulation of these human and/or primate accelerated evolutionary interacting proteins in human neurons derived from induced Pluripotent Stem Cells (iPSCs) and modeling prediction challenged in drosophila and novel mouse transgenic models. This work will finally allow (6) the validation of new druggable targets and markers as a proof-of-concept towards the prevention and cure of aging cognitive defects.
Agency: European Commission | Branch: FP7 | Program: MC-ITN | Phase: FP7-PEOPLE-2012-ITN | Award Amount: 4.10M | Year: 2013
This ITN is built around the biological question of O-glycosylation in gastric cancer for training in systems glycobiology. For meeting the needs of the research goal and for training for future systems glycobiology operations, cross disciplinary international institutes have been identified with top level state-of-the-art glycobioanalytical, glycotechnological and glycobioinformatics platforms. These platforms will be utilized and adopted to address the biology. The researchers will be exposed to academia and industry working together to develop resources of common use for addressing complex biological questions. This has been shown in the area of proteomics, to be a successful way for developing bioinformatics, databases, software, bioanalysis, reagents and biomolecule synthesis/production. These resources are now in use throughout the life science environment in academia, biotech and biopharma. However, there is no individual institute to our knowledge that can prepare new systems glycobiologists for the full impact of the environment they will operate in. This ITN is addressing this deficiency in training, in order to contribute to make Europe a competitive environment for the new generation of multidisciplinary research for complex glycobiological questions. The training to address the systems glycobiology in gastric cancer will provide the researchers with biological and technological workshops and courses in project management and business operations together with bidirectional secondments between academia-industry. Two dedicated training partners have been identified in order to provide efficient on-site training and self studies promoted by E-learning. In the research process we will identify and transfer technologies and biological outcomes for commercialization. A significant part of the training will also be to provide researchers with techniques peripheral to the ones available on their home base.