E. E. coli develops inside us, sometimes with unfortunate effects, and it contributes to scientific advances – DNA, biofuels and Pfizer’s covid vaccine, to name a few. Now this versatile bacterium has a new strategy: it can solve a classic computational maze problem using distributed computing – dividing the necessary calculations into different types of genetically engineered cells.
This neat feat is an achievement for artificial biology, whose goal is to create biological circuits, such as electronic circuits, and to program cells as easily as computers.
The labyrinth test is part of what some researchers consider a promising aspect of the case: instead of having a single type of cell engineer to do all the work, they design multiple types of cells to accomplish the task, each with a different function. Working in concert, these engineers may be able to “count” germs like wild wild multicellular networks and solve problems.
So far, for better or worse, artificial biologists who have fully utilized the design power of biology have avoided and become frustrated. “Nature It can (think of a brain), but We I still don’t know how to design that irresistible level of complexity using biology, “said Pamela Silver, a synthetic biologist at Harvard.
Study with E. coli A simple and fun toy problem, as a maze solver led by biophysicist Sangram Bug of the Saha Institute of Nuclear Physics in Kolkata. But it also serves as evidence of the principle of computing distributed across cells, demonstrating how more complex and practical computational problems can be solved in the same way. If this method works on a larger scale, it can unlock applications related to everything from pharmaceuticals to agriculture to space travel.
“As we move toward solving more complex problems with engineered biological systems, load shedding is becoming an important force,” said David Macmillan, a bioengineer at the University of Toronto.
How to create a bacterial maze
Getting E. coli There are some tricks involved in solving the maze problem. The bacteria did not roam the well-trimmed hedgehog maze. Rather, the bacteria have analyzed different labyrinth configurations. Setup: One labyrinth per test tube, each labyrinth produced by a different chemical combination.
The chemical recipes were abstracted from a 2 × 2 grid representing a maze problem. The square at the top left of the grid is the beginning of the maze, and the square at the bottom right is the destination. Each square in the grid can be either an open path or a block, resulting in 16 possible mazes.
Tiger and his colleagues have mathematically translated this problem into a true table 1s and 0s, showing all possible maze configurations. They then mapped those configurations to 16 different combinations of four chemicals. The presence or absence of each chemical corresponds to whether a particular square in the maze is open or closed.
The team has multiple sets of engineers E. coli With the help of various genetic circuits that identify and analyze those chemicals. Together, the mixed population of bacteria acts as a distributed computer; Different sets of cells perform part of each calculation, processing chemical information and solving maze.
Researchers were the first to run the experiment E. coli In 16 test tubes, a different chemical-puzzle combination is added to each, allowing the bacteria to grow. 48 hours later, if E. coli No clear path could be identified through the labyrinth অর্থাৎ that is, if the necessary chemicals were missing তাহলে the system would remain dark. When the right chemical combination is present, the corresponding circuits are “turned on” and the bacteria collectively release fluorescent proteins, yellow, red, blue or pink, to indicate solutions. “If there’s a way, a solution, the bacteria glow,” says Tiger.
What made the tiger feel particularly exciting was the churning through all 16 puzzles. E. coli Only three provide physical evidence that was solvable. “It’s not easy to calculate with a mathematical equation,” said Tiger. “Through this experiment, you can imagine it very easily.”
Tiger has envisioned a biological computer that assists in cryptography or steganography (the art and science of hiding information), which uses magic to encrypt and encrypt data, respectively. But the effects extend beyond those applications to the ambitions of synthetic biology.
The concept of synthetic biology dates back to the 1960s, but in 2000 the field emerged with the creation of synthetic biological circuits (specifically, a toggle switch and an oscillator) that made it increasingly possible for cells to produce the desired compounds or react intelligently. Their environment.