Biocomputer Developed Using Living Bacteria Runs Complex Problems Efficiently

An international team of scientists has made a groundbreaking discovery in the field of supercomputing by developing a biocomputer that runs on living bacteria. This innovative technology has been in the making for 20 years and is now set to revolutionize the way we tackle complex problems.

The research, led by McGill University in Montreal, involves collaboration from experts across Canada, Europe, the United Kingdom, and Australia. By combining biology with computer science and engineering, the team has created a biocomputer that uses bacteria to process information. This unique approach could potentially solve problems that standard computers struggle with.

Dan Nicolau, a McGill bioengineering professor and senior author of the research paper, explained that electronic computers are not equipped to handle decision trees, which require complex calculations. He noted that if these types of problems were to be solved using traditional computing methods, it would require an enormous amount of RAM.

The study employed two types of bacteria: Escherichia coli (E. coli) and Vibrio natriegens. E. coli was chosen for its predictable movement through fluid, while V. natriegens was selected for its rapid reproduction rate. By leveraging the unique properties of these microorganisms, the researchers were able to create a biocomputer that can tackle complex problems with minimal resources.

The use of live bacteria instead of digital processing allows the biocomputer to solve big problems at a fraction of the cost and resource requirements compared to regular computers. This breakthrough has significant implications for fields such as science, medicine, and engineering, where complex calculations are often necessary.

The biocomputer's capabilities were put to the test with a math problem known as the Subset Sum Problem, which becomes increasingly difficult as the number of inputs grows. This problem has been shown to be challenging for traditional computers, requiring centuries or even millions of years to solve.

To tackle this problem, the researchers created a physical representation of the graph that branches off into each possible combination of inputs. A tiny structure was built to mirror this graph, with a network of tunnels that reflect the branching paths.

Each fork in the tunnel system represents a decision point, and every route through the tunnels corresponds to a different solution to the problem. By introducing bacteria into these tunnels, the researchers harnessed their rapid reproduction to explore multiple solutions simultaneously.

As the bacteria moved through the tunnels, they effectively created additional processing units, allowing the biocomputer to tackle complex problems in a unique way that differs from traditional digital processing methods.

The researchers employed a sophisticated method to track the movement of bacteria through the network by using automated image analysis.

This allowed them to identify which paths satisfied the problem's constraints, providing crucial information for the biocomputer's operation.

To optimize performance, the team also fine-tuned temperature control within the system, preventing overcrowding and ensuring efficient bacterial travel.

The approach enabled the researchers to effectively harness the power of bacteria as processing units.