Proteases as Biological Bits for Programmable Medicine

Engineered biocircuits that interface with living systems as plug-and-play constructs may enable new applications for programmable therapies and diagnostics. We create biological bits (bbits) using proteases - a family of pleiotropic, promiscuous enzymes - to construct the biological equivalent of Boolean logic gates, comparators and analog-to-digital converters. We use these modules to write a cell-free bioprogram that can combine with bacteria-infected blood, quantify infection burden, and then calculate and unlock a selective drug dose. Inspired by probabilistic computing, we leverage multi- and common-target protease promiscuity as the biological analog of superposition to program three probabilistic bbits that solve all implementations of the two-bit oracle problem, Learning Parity with Noise. Treating a network of dysregulated proteases in a living animal as an oracle, we use this algorithm to resolve the probability distribution of coagulation proteases in vivo, allowing diagnosis of pulmonary embolism with high sensitivity and specificity (AUROC = 0.92) in a mouse model of thrombosis. Our results demonstrate that protease activity can be programmed in cell-free systems to carry out classical and probabilistic algorithms for programmable medicine.