Synthetic biological circuits for continuous signal processing

Abstract

Natural organisms evolved gene networks that measure continuous environmental information and adjust gene expression to maximize fitness. Engineered cells will need to be capable of similar signal processing and computation in order to operate efficaciously in complex environments, like the human body. In this thesis I describe the development of synthetic biological circuits that enable such capabilities. In the first chapter, analog gene networks are engineered to measure the concentration of molecules and to perform mathematical operations such as addition and division. Building on this work, analog gene networks are next engineered to compensate for input-sensor circuit crosstalk. Finally, in the third chapter, analog-to-digital converters are introduced to convert signals from analog gene circuits into discrete regimes of gene expression. This mixed-signal approach merges the benefits of analog signal processing and of digital signal integration to enable robust continuous signal processing. I posit that the computational architecture demonstrated herein will enable novel applications for the field of synthetic biology.