Engineered Bacteria Convert a 3-Bit Binary Code to a 3-Bit Gray Code by Multicellular Artificial-Neural-Network-Type Architecture

Abstract

The neuromorphic computing with genetically engineered cells is still in its infancy and shows great promise to solve various complex computational problems. The success of such computing is dependent on the expansion of its capability to build new and versatile computation functions. The conversion of a binary code to a Gray code is a fundamental concept in digital electronics and computer science. In this work, by using genetically engineered E. coli cells, we created a single-layer artificial neural network (ANN) that works as a 3-bit-binary to Gray code converter. The ANN architecture is built by five engineered E. coli populations in a liquid culture, where a binary input in chemical form is given by adding or not adding (1/0) three chemical inputs, and the converted codes are manifested by the appropriate expression of three fluorescent proteins. The work may have significance in biocomputer technology development, bacterial ANN, and synthetic biology.

Keywords: Artificial Neural Network; Biocomputer; Cellular Device; Code Converter; Synthetic Biology.