E. coli thrives in our guts, sometimes to an unfortunate effect, and facilitates scientific breakthroughs, in DNA, biofuels, and Pfizer’s covid vaccine, to name just a few. Now this multi-talented bacterium has a new trick: It can solve a classic computational maze problem using distributed computing, dividing the necessary calculations between different types of genetically modified cells.
This genius feat is a credit to synthetic biology, which aims to assemble biological circuits much like electronic circuits and program cells as easily as computers.
The maze experimentThis is part of what some researchers consider 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 do the job. Working together, these engineered microbes might be able to “compute” and solve problems more like multicellular networks in nature.
Until now, for better or for worse, the full harnessing of the design power of biology has eluded and frustrated synthetic biologists. “Nature you can do this (think brain), but us I still don’t know how to design at that overwhelming level of complexity using biology, ”says Pamela Silver, a Harvard synthetic biologist.
The study with E. coli As maze solvers, led 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 a proof of principle for distributed inter-cell computing, demonstrating how more complex and practical computational problems could be solved in a similar way. If this approach works on a larger scale, it could unlock applications related to everything from pharmaceuticals to agriculture to space travel.
“As we move toward solving more complex problems with engineered biological systems, distributing load in this way will be an important ability to establish,” says David McMillen, a bioengineer at the University of Toronto.
How to build a bacteria maze
Get E. coli Solving the maze problem required some ingenuity. Bacteria did not roam a palatial maze of well-trimmed hedges. Rather, the bacteria analyzed various maze configurations. The setup: one maze per test tube, with each maze generated by a different chemical mixture.
The chemical recipes were extracted from a 2 × 2 grid representing 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 on the grid can be an open or blocked path, resulting in 16 possible mazes.
Bagh and his colleagues mathematically translated this problem into a truth table composed of 1sand 0s, showing all possible maze configurations. They then mapped those configurations into 16 different mixtures of four chemicals. The presence or absence of each chemical corresponds to whether a particular square is open or blocked in the maze.
The team designed several sets of E. coli with different genetic circuits that detected and analyzed those chemicals. Together, the mixed population of bacteria functions as a distributed computer; Each of the different sets of cells performs part of the calculation, processes the chemical information, and solves the maze.
When running the experiment, the researchers first put the E. coli in 16 test tubes, I added a different chemical maze mix to each and let the bacteria grow. After 48 hours, if the E. coli it did not detect a clear path through the maze, that is, if the required chemicals were absent, then the system remained dark. If the correct chemical combination was present, the corresponding circuits are “turned on” and the bacteria collectively express fluorescent proteins, in yellow, red, blue or pink, to indicate solutions. “If there is a way, a solution, the bacteria shine,” says Bagh.
What Bagh found particularly exciting was that in traversing the 16 mazes, the E. coli provided physical proof that only three were solvable. “Calculating this with a mathematical equation is not easy,” says Bagh. “With this experiment, you can visualize it very simply.”
Bagh envisions such a biological computer that aids in cryptography or steganography (the art and science of hiding information), which use mazes to code and cover up data, respectively. But the implications extend beyond those applications to the higher ambitions of synthetic biology.
The idea of Synthetic biology dates from the 1960s, but the field emerged specifically in 2000 with the creation of synthetic biological circuits (specifically, a toggle switch and a oscillator) that made it increasingly possible to program cells to produce desired compounds or react intelligently within their environments.