Andre Levchenko of the Institute of Cell Engineering and Biomedical Engineering
on being a non-traditional computational biologist:
Why do you consider yourself to be non-traditional?
LEVCHENKO: We create models—the workings of a system expressed in a quantitative language—like other computational biologists. But, unlike professional modelers’, we also have a wet lab. Traditional computational biologists that create theoretical models and may never test their theories. We use our models to generate a hypothesis and then we check our prediction in an experimental system.
When we predict something based on our model, it’s actually more interesting when our experimental results contradicts the model, because it allows us to modify and improve our models to better conceptualize what is really going on. If our models were always correct, it would get boring quickly since it would basically mean that we already know everything about that system.
What biological problems do you study?
LEVCHENKO: We are interested in how cells sense environmental changes and how they adjust their behavior accordingly. We study processes like how cells form tissues during development or how cells misinterpret signals from the environment that cause them make abnormal decisions—to replicate or to move, for example—that can lead to cancer.
We use a variety of organisms across a broad spectrum of complexity for our studies. Some of the projects work with bacterial cells and yeast, others with mammalian neurons and human stem cells. We find a lot of interesting similarities in how different types of cells make decisions.
How do you study cellular decision making?
LEVCHENKO: As our models grow more sophisticated, the experiments become more involved. We learned that we had to control the cell’s environment as precisely as we could to understand how the cells were behaving. To help us with this task, we’ve designed the “lab on a chip”—a plastic chip covered with a glass lid that contains live cells and, features a system of channels and wells that allow us to control the flow of specific chemicals that change the cells behavior. We may choose to treat the cells with growth factors that make the cells divide, chemicals that cause the cells to move or any other number of compounds that cause specific changes in cellular behavior.
We’ve used the “lab on a chip” to see how single nerve cells react when they encounter chemical signals from their environment. The neurons turned and grew toward higher concentrations of certain chemical cues attached to the chip’s surfaces, and toward other molecules free-flowing in solution. When we gave neurons both the surface bound and free-flowing cues, the cells turned randomly, suggesting that the cells do not choose one cue over another.
These “labs on a chip” provide the most realistic environment outside the body where we can test how cells react to different stimuli. Because everyone wants to know how the cells they study really behave, we’ve established a lot of collaborations and shared the chips with many other labs.
Andre Levchenko on how computerized models are like informative video games...only better:
—Interviewed by Vanessa McMains