Synthetic Metabolic Computation in a Bioluminescent Whole-cell Sensing System

In natural biological systems, signal processing and decision making is an integrative framework that includes regulation of gene expression and metabolic pathways. Metabolic engineering for computation has been rarely demonstrated in the framework of synthetic biology. However, given that there is often unwanted crosstalk amongst synthetic genetic devices, a lack of orthogonal genetic devices and cellular resource limitations, it may be challenging to scale biological systems based only on gene networks to the level needed for complex computations in living cells. To overcome this challenge we integrate genetic and metabolic circuits of bacterial bioluminescent reaction (the luxABCDE cassette) to create an artificial framework that performs complex computation in living cells with fewer components and resources. First, we redesigned it by splitting the five genes in different combinations to execute sophisticated analog computational functions (e.g. find the minimum between two analog signals), logic gates (e.g. AND and XOR) and a comparator with programmable activation thresholds acting as an analog-to-digital converter. Second, we integrated the constructed synthetic gene circuits based luxABCDE cassette with environmental stress to improve the specificity of the detection error of bacterial biosensors.