What is the relationship between bacteria and neural networks?

Researchers at the Technion have developed a synthetic biological system for pattern recognition based on bacterial communities according to the design rules of artificial neural networks

Researchers at the Faculty of Biomedical Engineering at the Technion have developed a computational biological system that identifies chemical patterns using populations of living bacteria that communicate with each other. the development published yesterday in the journal Kind Communication Led Dr. Ramez Daniel and the postdoctoral student Dr. Li Shiming.

During evolution, multi-cellular biological systems developed that are capable of performing complex operations, including various computational processes such as monitoring, signal processing and decision-making. In the immune system of mammals, for example, an invasion of bacteria and viruses activates a series of actions in different cells and thus puts the body on the defensive against the invaders. These mechanisms are based on the action of a large population of cells and communication between these cells.

Natural biological systems such as the brain develop over millions of years from prolonged evolutionary adaptation, and they fulfill complex tasks through inter-cellular coordination; Most of thebiological systems the synthetics, on the other hand, are intelligently designed and built by engineers, with the intention that they will fulfill specific tasks defined based on computational principles. In recent decades, there has been a boom in the development of electronic systems that perform complex operations with impressive success. These are layered neural networks - artificial systems which draw inspiration from biology (the human brain) and perform various operations including pattern recognition.

In the current study, the researchers did the opposite: creating a biological system that draws inspiration from those neuronal networks. The article by the Technion researchers b- Kind CommunicationDescribes a pattern recognition technology based on bacterial colony computation. The bacteria in the system built at the Technion are E. coli bacteria that were fixed in 'wells' on a solid standard. The introduction of chemical information (input) on one side of the device triggers a biochemical chain reaction between the bacteria, leading to the production of optical information (output) on the other side of the device.

According to Dr. Daniel, "What is so beautiful here is that there is joint work here, or in the professional language collective analog. The idea is that the bacterial community consists of simple and limited details, but its joint activity - a biological mechanism known as quorum sensing - allows it to perform complex computational operations. This is how the brain works and this is how artificial neuron networks work: in intercellular interaction; Our innovation is that we were able to demonstrate an artificial biological system that provides impressive performance based on the same concept. Thus, in fact, togetherness is strength."

The main author of the article is the postdoctoral student Dr. Shiming Lee, who came to the Technion after a PhD in neuroscience at Ohio University. "When I heard about Ramez's lab, I realized that it was an opportunity to put a 'twist' on artificial biological systems that perform calculations. This is how I arrived at the Technion three years ago, and the road since then has been difficult and challenging - very complex experiments and many failures. We did experiments with different materials, we tested their effect on the bacteria, we built a feedback loop to improve the system, we built an algorithm that would allow us to draw conclusions about the input from the output, and in the end we succeeded, which is very exciting."

According to Dr. Daniel, "We have successfully demonstrated here a biological model based on the structure of neuronal networks. We demonstrated this model in a specific task - identifying chemical patterns - but it can be the basis for a wide range of applications such as monitoring toxins in water and food, medical diagnosis (e.g. identifying cancer cells), tissue restoration and the development of biological computers. It is fascinating to see how the field of synthetic biology, one of whose goals is the design of biological systems inspired by engineering, receives another direction here - a design that comes from neuronal systems.

The researchers thank Prof. Nathaniel Korin for his assistance in the research.

for an article in the scientific journal Nature Communications. click here

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