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New models describing biological tissues can enable people to better understand biological processes



Life order

Two types of particles (red and green) interact with each other. Although particles of the same type will inevitably attract or repel each other, particles of different types may not interact with each other. Here, green particles chase red particles. On a large scale, the highly compressed bands of green particles chase the bands of red particles. This creates sequences and moves in the system.Image credit: MPIDS/Novak, Saha, Agudu Canalejo, Goldstein

At first glance, a pack of wolves has nothing to do with vinegar and oil. But a team led by Ramin Golestanian, director of the Max Planck Institute for Dynamics and Self-organization, developed a model that establishes a link between the movement of predators and prey and the isolation of vinegar and oil. They extended a theoretical framework, which until now is only valid for inanimate things. In addition to predators and prey, other biological systems can now be described, such as enzymes or self-organizing cells.


At first glance, order is not always obvious. If you run with a pack of wolves hunting deer, the sports will appear chaotic. However, if the prey is viewed from a bird̵

7;s-eye view and a long period of time passes, the animal’s movement patterns will become obvious. In physics, this behavior is considered orderly. But how does this order appear? Ramin Golestanian’s Department of Life Material Physics is dedicated to solving this problem and has studied the physical rules that control the movement of life or activity systems. The goal of Golestanian is to reveal the universal characteristics of active creatures. This includes not only larger organisms, such as predators and prey, but also bacteria, enzymes and motor proteins, and artificial systems such as micro-robots. Golestanian explained: “When we describe a group of such active systems over a long distance and a long time, the specific details of the system lose importance. Their overall distribution in the space eventually becomes the decisive feature.”

From inanimate to living system

His team in Göttingen recently made a breakthrough in describing living matter. To achieve this goal, Suropriya Saha, Jaime Agudo-Canalejo, and Ramin Golestanian started with a well-known description of the behavior of inanimate matter and expanded it. The main point is to consider the fundamental difference between life and inanimate matter. Contrary to inanimate passive matter, animate active matter can move on its own. Physicists use the Cahn-Hilliard equation to describe how inanimate mixtures (such as oil and water emulsions) separate.

The features developed in the 1950s are considered the standard model of phase separation. It is based on the principle of reciprocity: tit for tat. Therefore, oil repels water in the same way as water repels oil. However, this is not always the case for biological or active systems. The predator hunts down the prey, and the prey tries to escape the predator. It has only recently been shown that even in the movement of the smallest systems (such as enzymes), there is no irreversible (ie active) behavior. Therefore, enzymes can be concentrated exclusively in a single cell area, which is necessary for many biological processes. After this discovery, researchers in Göttingen studied the massive accumulation behavior of different enzymes. Will they mix together or form groups? Will there be new and unexpected features? To answer these questions, the research team began to work.

Sudden wave

The first task is to modify the Cahn-Hilliard equation to include irreversible interactions. Because this equation describes a non-living system, the reciprocity of passive interaction is deeply embedded in its structure. Therefore, every process it describes ends in thermodynamic equilibrium. In other words, all participants eventually enter a rest state. However, life span occurs outside of thermodynamic equilibrium. This is because life systems are not static, but use energy to achieve a certain purpose (such as their own reproduction). Suropriya Saha and her colleagues consider this behavior by extending the Cahn-Hilliard equation with parameters that characterize non-reciprocal activities. In this way, they can now describe any process different from the passive process.

Saha and her colleagues used computer simulations to study the effects of introducing modifications. Saha said: “It is surprising that even the smallest reciprocity can cause fundamental deviations from the behavior of passive systems.” For example, researchers have observed the formation of traveling waves in a mixture of two different types of particles. . In this phenomenon, the band of one component catches up with the band of the other component, resulting in a pattern of moving stripes. In addition, complex crystal lattices can be formed in particle mixtures, in which small clusters of one component chase groups of another component. Researchers hope to contribute to the scientific progress of physics and biology through their work. For example, the new model can describe and predict the behavior of different cells, bacteria or enzymes. Golestanian said: “We have used this model to teach an old dog new tricks.” “Our research shows that physics helps our understanding of biology, and the challenge of studying biological matter is physics. The basic research has opened up new ways.”


Mathematician improves the model of the relationship between predator and prey in the wild


More information:
Suropriya Saha et al. Scalar active mixture: irreversible Cahn-Hilliard model, Physical Review X (2020). DOI: 10.1103 / PhysRevX.10.041009

Courtesy of the Max Planck Institute

Citation: New models describing biological tissues can better understand biological processes (October 30, 2020), which can be downloaded from https://phys.org/news/2020-10-biologic from October 30, 2020. html search

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