Ron Weiss

Associate Professor of Electrical Engineering
Ph.D. 2001, Massachusetts Institute of Technology

My research focuses on programming biological organisms by embedding synthetic biochemical logic circuits into cells, as well as embedding sensors, actuators, and intercellular communication mechanisms. Biological organisms sense their environment, process information, and continuously react to both internal and external stimuli. In my research group, we are exploring mechanisms for harnessing various organisms as computational substrates and micron-scale robots, and extending their behavior by embedding biochemical logic circuitry that precisely controls intra- and inter-cellular processes. This engineering effort of constructing reliable in-vivo logic circuitry with predictable behavior enables a wide range of programmed applications. The application areas include drug and biomaterial manufacturing, programmed therapeutics, embedded intelligence in materials, environmental sensing and effecting, and nanoscale fabrication.

To build the biochemical logic circuits, we use DNA-binding proteins and other small molecules to represent signals, and perform computation by directing synthetic genes to regulate protein expression. As part of the experimental effort, we have built a small library of digital logic inverters that use the genetic processes of transcription and translation (shown in the figure). With these inverters and other computational logic gates, we have constructed and tested several genetic circuits that perform digital computation inside cells. We have also integrated these circuits with intercellular communication mechanisms, in order to engineer coordinated behavior in cell aggregates. To aid in the circuit design effort, we have implemented and are continuously improving BioSPICE, a software tool for predicting the behavior of genetic circuits.

We are now pursuing a variety of interesting and challenging projects that include the prediction of the behavior of complex genetic circuits based on the "device physics" of their components, programming cells to genetically modify their embedded circuits in order to optimize performance and behavior, building signal processing circuits and two-way messaging capabilities into the intercellular communication systems, and extending BioSPICE for structural and cell aggregate predictions.