“From an engineer’s perspective, molecular systems in living organisms fascinated me; each cell has thousands of living machines with many intricate, inter-dependent parts all working together. I began to wonder how all these machines work and, even more important, why they stop working correctly in Alzheimer’s disease or schizophrenia.”
At Cornell, Daniel has been studying neurotransmitter symporters—molecular pumps that import neurotransmitters into cells for recycling after they are released for signaling. He also studies the mechanism of protein synthesis catalyzed by the ribosome, a giant molecular machine with almost 60 parts, with an eye towards designing better ribosome-targeting antibiotics. In both projects, Daniel uses single-molecule fluorescence imaging to watch the motions of these machines in real time to better understand how they work. To make this work, he developed a set of software tools to interpret the large, complex datasets from these experiments and also improved the imaging technique for much higher throughput than previously possible.
“I came to Cornell wanting to understand how these living machines work, but I did not know what techniques were best suited to achieve this goal. The Tri-I CBM program gave me the flexibility to learn new techniques like single-molecule imaging as well as computational methods like molecular dynamics simulations. Working with the faculty at Cornell and in collaboration with faculty at Columbia has made this possible.”