A E. coli biocomputer solves a maze by sharing work

E. coli grows in our intestines, sometimes with unfortunate consequences, and facilitates scientific advances — in DNA, biofuels, and the Pfizer covid vaccine, to name a few. Now this multi-talented bacterium has a new trick: it can solve a classic computational maze problem using distributed computing by dividing the necessary calculations between different genetically engineered cell types.

This beautiful feat is the merit of synthetic biology, which aims to adapt biological circuits in the same way as electronic circuits and to program cells as easily as computers.

Labyrinth experimentThis is part of what some researchers see as a promising direction in the field: instead of designing a single cell type to do all the work, they design multiple cell types, each with different functions, to carry out the work. Working together, these engineering microbes may be able to “compute” and solve problems in the wild like multicellular networks.

So far, for better or worse, taking full advantage of the design power of biology has eluded and frustrated synthetic biologists. “Nature can do this (think in a brain), but guk I still don’t know how to design it using biology at that enormous level of complexity, ”says Pamela Silver, a synthetic biologist at Harvard.

With research E. coli as a maze repairer, directed by biophysicist Sangram Bagh at the Saha Institute for Nuclear Physics in Kolkata, it is a simple and fun toy problem. But it also serves as proof of the principle of computation distributed among cells, demonstrating how more complex and practical computational problems can be solved in a similar way. If this approach works on a larger scale, from pharmacy, agriculture, and space travel, it can unlock apps.

“As we move to solve more complex problems with biological engineering systems, the expansion of the load will be an important ability to implement this expansion,” says David McMillen, a bioengineer at the University of Toronto.

How to build a maze of bacteria

Getting it E. coli it involved some ingenuity in solving the problem of the labyrinth. The bacteria did not walk through the well-cut palace maze. Rather, the bacteria examined various labyrinth configurations. Configuration: One maze for each test tube, each maze created by a different chemical crop.

The chemical recipes were taken from a 2 × 2 network indicating the maze problem. The upper left square of the grid is the beginning of the maze, and the lower right square is the destination. Each square in the network can be open or blocked, giving you 16 possible mazes.

Bagh and his colleagues mathematically translated this problem into a truth board 1s eta 0s, showing all possible maze configurations. These configurations were then mapped to 16 different chemical combinations. The presence or absence of each chemical corresponds to whether a particular square in the maze is open or blocked.

The team designed several sets E. coli these chemicals were detected and analyzed with different genetic circuits. Together, the mixed bacterial population functions as a distributed computer; each set of cells performs a part of the computation, processing the chemical information and solving the maze.

When the experiment was launched, the researchers put it first E. coli In 16 test tubes, he added a chemical-identical maze each time, and let the bacteria grow. After 48 hours, if E. coli he did not detect a clear path through the labyrinth — that is, if the necessary chemicals were not present — then the system remained dark. If there was a correct chemical combination, the corresponding circuits were “turned on” and the bacteria together indicated fluorescent proteins, yellow, red, blue, or pink, to indicate solutions. “If there’s a path, a solution, the bacteria shine,” Bagh says.

What Bagh was particularly excited about was the 16 labyrinths that rotated through E. coli he provided physical proof that only three were fixable. “Calculating this with a mathematical equation is not easy,” Bagh says. “With this experiment, you can see it very easily.”

High goals

Bagh envisions a biological computer that assists in cryptography or steganography (the art and science of hiding information) that uses mazes. encrypted and hide data, respectively. But the implications extend beyond these applications to the broader intentions of synthetic biology.

the idea of synthetic biology It dates back to the 1960s, but the field was created in 2000 specifically with the creation of synthetic biological circuits (specifically, Switch and one oscillator) which made it increasingly possible to program cells to produce the desired compounds or to react intelligently in their environment.