The Circuitry of Yeast
For centuries, yeast has helped scientists understand how cells work. Now, two inventive teams have applied an engineering approach coupled with computer modeling to reveal new details about key biological pathways by which yeast cells regulate themselves in a changing environment, as reported in the January 25, 2008 issue of Science and the August 28, 2008 issue of Nature.
“What’s interesting to me was looking at this biological system from an information-processing perspective,” says Jerome Mettetal, PhD, a physicist at the Massachusetts Institute of Technology and lead author of the Science paper. “By applying temporally varying inputs, you can find out a lot about the system that you wouldn’t be able to see otherwise.”
Traditionally, biologists measure how cells respond by adding or taking something away in a steady-state context. But in real cells, inputs from the environment vary constantly. To understand the mechanisms by which cells respond to changes, the two teams created microfluidic arrays that confine yeast cells in a chamber and feed them in regular cycles, controlled by software. Based on the output, each team generated a model of the inner workings of the cells.
Mettetal’s team added bursts of salt to the microfluidic array in order to tease out how yeast responds to changes in osmotic pressure—the salt level in the surrounding medium. They then built a model based on the response generated by the yeast. When they compared their model to known cell responses to osmotic changes, they discovered new roles for three different negative feedback loops—the processes by which a biological system reestablishes equilibrium.
The research team on the Nature paper applied a similar engineering approach to better understand how yeast cells respond to fluctuations in nutrient levels. If yeast is deprived of its favorite sugar (glucose), it will consume an alternative and less nutritious sugar (galactose). The researchers created a sinusoidal input by alternately feeding and starving yeast of glucose on different time scales while galactose was constantly present in the environment. The cells responded to long-term changes in glucose, but not to faster fluctuations.
The researchers then made a model based on the well-known metabolism of galactose. But the experimental yeast was responding much faster to the glucose fluctuations than the model predicted. “This suggested something was crucially missing from the model,” says co-author Jeff Hasty, PhD, associate professor of bioengineering at the University of California, San Diego. Studying live yeast provided the answer: The messenger RNA necessary for the galactose metabolic pathway was degraded when glucose was present. “The most exciting thing is that without the model, none of this would have happened,” said Hasty.
“The broader contribution of each of these pieces will be to point to the value of using periodic input signals as a means to tease out the structure and function of the underlying system,” says James Collins, PhD, professor of biomedical engineering at Boston University. “I am already beginning to think about how these might be interesting tools to use to look at other systems, bacteria in particular.”