New computer code for the mechanics of tissues and cells in three dimensions
Biological materials are made up of individual components, including tiny motors that convert fuel into movement. This creates patterns of movement and the material structures itself through constant energy consumption. Such permanently moving materials are referred to as "active matter". The mechanics of cells and tissues can be described by the theory of active matter, a scientific concept to understand the shape and movement of living materials. The theory of active matter consists of many sophisticated mathematical equations. Scientists at the Max Planck Institute of Molecular Cell Biology and Genetics (MPI-CBG) in Dresden, the Centre for Systems Biology Dresden (CSBD) and TU Dresden have now developed an algorithm and implemented it in an open-source supercomputer code that can solve the equations of active matter theory in realistic scenarios for the first time. These results bring us a big step closer to solving the age-old puzzle of how cells and tissues get their shape and the design of artificial biological machines.
Biological processes and patterns are often very complex. Physical theories provide a precise and quantitative framework to understand them. The theory of active matter provides a framework to understand and describe the behaviour of active matter - materials consisting of individual components that can convert a chemical fuel ("food") into mechanical forces. Several researchers from Dresden were significantly involved in the development of this theory, including Frank Jülicher, Director at the Max Planck Institute for the Physics of Complex Systems and Stephan Grill, Director at the MPI-CBG. With these physical principles, the dynamics of active living matter can be described and predicted using mathematical equations. However, these equations are complex and difficult to solve. Scientists therefore need the power of supercomputers to understand and analyse living materials. There are various ways to predict the behaviour of active matter. Some focus on the tiny individual particles, others study active matter at the molecular level, and still others study active liquids on a large scale. These studies help scientists to understand how active matter behaves at different length scales in space and over time.
Solving complex mathematical equations
Researchers from the working group of Ivo Sbalzarini, TU Dresden professor at the Centre for Systems Biology Dresden (CSBD), research group leader at the Max Planck Institute of Molecular Cell Biology and the Max Planck Institute of Molecular Biology;for Molecular Cell Biology and Genetics (MPI-CBG) and Dean of the Faculty of Computer Science at TU Dresden, have now developed a computer algorithm that solves the mathematical equations of active matter. Their work was published in the journal "Physics of Fluids" and highlighted on the front page. The team describes an algorithm that can solve the complex equations of active matter in three dimensions and in complex shaped geometries. „Our algorithm works for different geometries in three dimensions and over time“, says Abhinav Singh, one of the first authors of the study and a mathematician by training. He continues: "Even when the data points are not uniformly distributed, our algorithm uses a novel numerical approach that works seamlessly for complex biologically realistic scenarios to solve the equations of the theory with high accuracy. Using our approach, we can finally understand the long-term behaviour of active materials in both moving and stationary scenarios and predict their dynamics. In addition, the theory and simulations could be used to programme biological materials or to develop molecular machines on the nanoscale that perform useful work.The other first author, Philipp Suhrcke, a graduate of the TU Dresden's Computational Modelling and Simulation Master's programme, adds: "Thanks to our work, scientists can now predict, for example, the shape of a tissue or when a biological material will become unstable or dysregulated. This is important in order to better understand the mechanisms of growth and disease.
A powerful code for everyone
The research team implemented the algorithm using the open source library OpenFPM. This makes it freely available to others. OpenFPM was developed by the Sbalzarini Group to make scientific computing accessible to all. The researchers first developed a new computer language in OpenFPM that makes it possible to write supercomputer codes more easily and much faster. This means you don't have to start from scratch every time you want to write code, effectively reducing development times in scientific research from months or years to days or weeks. This brings enormous increases in productivity. Due to the large computational effort required to study three-dimensional active materials, the new code is scalable on multiprocessor supercomputers thanks to the use of OpenFPM. Although the code is designed for powerful supercomputers, it can also be used on normal workstations to study two-dimensional materials.
The lead scientist of the study, Ivo Sbalzarini, summarises: „Ten years of our research have gone into developing this code to improve the productivity of computer-based science. This is now all combined in one tool to understand the three-dimensional behaviour of living materials. Open-source, scalable and capable of handling complex scenarios, our code opens up new possibilities for exploring active materials. We could finally understand how cells and tissues maintain their shape and thus answer the fundamental question of morphogenesis, which has fascinated scientists for centuries. The code could also help us to design artificial biological machines with a minimal number of components.“
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The computer code for this study is available in the 3Dactive-hydrodynamics Github directory at: https://github.com/mosaic-group/3Dactive-hydrodynamics
The open source library OpenFPM is available at:
https://github.com/mosaic-group/openfpm_pdata
Publications on the computer language used and the OpenFPM software library:
https://doi.org/10.1016/j.cpc.2019.03.007
https://doi.org/10.1140/epje/s10189-021-00121-x
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