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Researchers Simulate Movement of Single-Celled Organisms



Image: TU Wien

A research team at TU Wien (Vienna) has successfully simulated the process of single-celled organisms moving in a desired direction despite not having a brain or nervous system. Prior to the new developments, researchers were not sure how the small organisms were capable of such a process. 

The team calculated the physical interaction between a simple model organism and its environment, with the latter being a liquid with a non-uniform chemical composition containing unevenly distributed food sources. 

The research was published in the journal PNAS

The Simulated Organism

The researchers equipped the simulated organism with the ability to process data about its food and environnement. By relying on a machine learning algorithm, the information processing could be modified and optimized in evolutionary steps. This meant that the researchers developed a computer organism capable of moving and searching for food similar to real-life organisms. 

Andreas Zöttl led the research project at the Institute of Theoretical Physics at TU Wien. 

“At first glance, it is surprising that such a simple model can solve such a difficult task,” Zöttl says. “Bacteria can use receptors to determine in which direction, for example, the oxygen or nutrient concentration is increasing, and this information then triggers a movement into the desired direction. This is called chemotaxis.” 

While multicellular organisms have an interconnection of nerve cells, single-celled organisms have no nerve cells. Because of this, they can only go through simple processing steps within the cell.

To be able to explain this, you need a realistic, physical model for the movement of these unicellular organisms,” says Zöttl. “We have chosen the simplest possible model that physically allows independent movement in a fluid in the first place. Our single-celled organism consists of three masses connected by simplified muscles. The question now arises: can these muscles be coordinated in such a way that the entire organism moves in the desired direction? And above all: can this process be realised in a simple way, or does it require complicated control?”

Implementing the Computer Model

Benedikt Hartl was the one who implemented the model on the computer. 

“Even if the unicellular organism does not have a network of nerve cells — the logical steps that link its ‘sensory impressions' with its movement can be described mathematically in a similar way to a neuronal network,” says Hartl.

Single-celled organisms have logical connections between different elements of the cell, and movement takes place when chemical signals are triggered. 

Maximilian Hübl completed several of the calculations in the research.

“These elements and the way they influence each other were simulated on the computer and adjusted with a genetic algorithm: Generation after generation, the movement strategy of the virtual unicellular organisms was changed slightly,” reports Hübl.

When the unicellular organisms succeeded in directing their movement to the desired chemicals, they were allowed to “reproduce,” while those that didn’t “died out.” After going through many generations, a type of evolution took place and a control network emerged. This network enabled a virtual unicellular organism to convert chemical perceptions into targeted movement, and it does so simply and with basic circuitry. 

“You shouldn't think of it as a highly developed animal that consciously perceives something and then runs towards it,” says Zöttl. “It's more like a random wobbling movement. But one that ultimately leads in the right direction on average. And that's exactly what you observe with single-celled organisms in nature.”

Alex McFarland is a tech writer who covers the latest developments in artificial intelligence. He has worked with AI startups and publications across the globe.