Engineered Bacteria Computationally Solve Chemically Generated 2X2 Maze Problems

TL;DR

This study demonstrates how engineered bacteria with genetic logic circuits can computationally solve simple 2x2 maze problems by processing chemical inputs and visualizing solutions through fluorescence.

Contribution

The paper introduces a novel biological approach to maze solving using engineered bacteria that process chemical inputs and produce visual outputs, advancing biocomputation methods.

Findings

Engineered bacteria successfully solved all 2x2 maze problems.

Bacteria visualized solutions via fluorescent protein expression.

System distinguished between solvable and unsolvable maze cases.

Abstract

Maze generating and solving are challenging problems in mathematics and computing. Here we generated simple 2X2 maze problems applying four chemicals and created a set of engineered bacteria, which in a mixed population worked as a computational solver for any such problem. The input-output matrices of a mathematical maze were mapped through a truth table, where the logic values of four chemical inputs determined the sixteen different 2X2 maze problems on a chemical space. Our engineered bacteria, which consisted of six different genetic logic circuits and distributed among six cell populations processed the chemical information and solved the problems by expressing or not expressing four different fluorescent proteins. The three available solutions were visualized by glowing bacteria and for the thirteen no solution cases no bacteria glowed. Thus, our system not only solved the maze problems but also showed the number of solvable and unsolvable problems. This work presented a new and abstract cellular computational way towards maze problems and may have significance in biocomputation and synthetic biology.