  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.
