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Gene regulatory networks (GRNs) form naturally predefined and optimised computational units envisioned to act as biohardware able to solve hard computational problems efficiently. This interplay of GRNs via signalling pathways allows the consideration as well as implementation of interconnection-free and fault tolerant programmable computing agents. It has been quantitatively shown in an in vivo study that a reporter gene encoding the green fluorescent protein (gfp) can be switched between high and low expression states, thus mimicking a NAND gate and a RS flip-flop. This was accomplished by incorporating the N-acyl homoserine lactone (AHL) sensing lux operon from Vibrio fischeri along with a toggle switch in Escherichia coli. gfp expression was quantified using flow cytometry. The computational capacity of this approach is extendable by coupling several logic gates and flip-flops. We demonstrate its feasibility by designing a finite automaton capable of solving a knapsack problem instance.

BIOSIGNAL-BASED COMPUTING BY AHL INDUCED SYNTHETIC GENE REGULATORY NETWORKS - From an in vivo Flip-Flop Implementation to Programmable Computing Agents