“To understand cellular life at this mesoscale is not to reduce the system down to every infinitesimally small interaction, but rather to see how all the pieces fit together.”
Sivaraj (Shiv) Sivaramakrishnan, new faculty in Genetics, Cell Biology, and Development, began his career as a mechanical engineer studying the fluid dynamics of liquid steel. Now, he investigates protein interactions both in and outside of living cells.
This surprising career switch arose entirely through serendipity. Days before he was to start a job in computational mechanics, Shiv received a call. His company needed to immediately fill a job studying biological fluid flow through medical devices. He accepted, shifting his focus from steel to cells, while maintaining an engineer’s angle on complex systems.
From an engineering perspective, it is tempting to try reduce biological complexity down to a collection of components that function in discrete, predictable ways—much like pistons in a car or switches in a computer. Yet biology utilizes an entirely different sort of organization than human-designed machines.
Biological systems don’t have exact blueprints—rather, intricate cellular functions appear to emerge out of densely packed clusters of molecules. To the human eye, these systems seem chaotic, yet somehow, they manage to satisfy all of the high order functions necessary for life, including transport, communication and infrastructure. “To understand cellular life at this mesoscale is not to reduce the system down to every infinitesimally small interaction, but rather to see how all the pieces fit together,” says Shiv.
Shiv’s lab attempts to understand cellular life at the mesoscale by bridging the gap between our structural understanding of proteins and their emergent cellular functions. One way he approaches the problem is by constructing bits and pieces of cytoskeleton completely outside of cells. He uses nanotechnology to construct synthetic subcellular scaffolds, and then examines how various proteins interact with these extracellular “jungle gyms.”
Living cells, however, are vastly more complex than any model humans can build, making it necessary to also examine protein behavior in vivo. In particular, Shiv hopes to tease apart the mixed messages being passed around in cellular signaling pathways.
For example, when a ligand binds to a cell-surface receptor, that single interaction can often trigger multiple distinct signaling cascades. “What we are fundamentally missing in the signal processing sense is how the information is actually being sorted out,” says Shiv.
In order to address this problem, Shiv uses genetic linkers to add a physical connection between any two proteins in a signaling cascade. He can then control the frequency of interaction between those two proteins, enabling him to directly examine how that particular interaction contributes to cellular response.
Shiv’s innovative approaches remain deeply inspired by his background in mechanical engineering. “Even the most sophisticated machine or computer doesn't come close to a single cell,” says Sivaramakrishnan, who feels lucky to have stumbled into the biological sciences. “For me, biology is the ultimate engineer's dream.”
— Colleen Smith