Cell-free prototyping and rapid optimization of paper-based biological sensors

Cell-free systems enable the use of biological mechanisms without the need to maintain cell efficacy and thus enable the creation of low burden and fieldable detection platforms for nucleic acids, small molecules, and toxins. However, designing and optimizing portable cell-free biological sensors for clinical and environmental applications is challenging due to the complexity of the system and lack of high-throughput workflows. Here we describe a method to accelerate the in vitro prototyping and optimization of paper-based cell-free sensors using high-throughput acoustic liquid handling in a 384-well format. This methodology allows for lyophilized cell-free tickets with varying formulations of energy sources, cryoprotectants, and cofactors to be prepared and measured in mass to assess biosensor performance. We show how this system coupled to machine learning accelerates design–build–test cycles and improves performance in β-galactosidase based biosensors.