LAUSR

This work presented an application of genetic distributed computing, where an abstract computational problem was mapped on a complex truth table and solved using simple genetic circuits distributed among various cell populations. Maze generating and solving are challenging problems in mathematics and computing. Here, we mapped all the input-output matrices of a 2 × 2 mathematical maze on a 4-input-4-output truth table. The logic values of four chemical inputs determined the 16 different 2 × 2 maze problems on a chemical space. We created six multi-input synthetic genetic AND gates, which distributed among six cell populations and organized in a single layer. Those cell populations in a mixed culture worked as a computational solver, which solved the chemically generated maze problems by expressing or not expressing four different fluorescent proteins. The three available "solutions" were visualized by glowing bacteria, and for the 13 "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 may have significance in cellular computation and synthetic biology.