In a recent study out of the Molecular Sciences Institute, researchers led by Richard Yu have found that cell signaling systems can be described in a quantitative way, just like electrical circuits. In work recently published in Nature, Yu used genetic reporters — mostly fluorescently tagged proteins — to find that the mitogen-activated -protein kinase Fus3 provides negative feedback to the S. cerevisiae pheromone response pathway. It does that by adjusting the dose-response alignment to match receptor-ligand binding to downstream output.
The yeast pheromone response pathway is a model circuit that takes external pheromone and tranduces the signal inside the cell to activate a cascade of signaling proteins in the cytoplasm, eventually leading to expression of pheromone-responsive genes in the nucleus. Yeast make use of this sensing circuit to quantitatively measure the amount of pheromone coming from potential mating partners to determine which one to grow toward and mate with.
The work was done under the auspices of the Alpha Project, and its goal is to gain a quantitative understanding of eukaryotic regulatory networks like the yeast pheromone pathway in response to perturbations. Yu says the team started out building reporter molecules for important members of the pathway, "basically going from the membrane down into the nucleus," but decided to fine-tune the approach when it was taking too long.
True to systems biology form, Yu and his colleagues started out by watching the system and trying to build a digital model against which they could test real-time perturbations. "Roger [Brent] calls this the 'epistemological hack' — basically we've defined understanding as having this predictive model," Yu says. In the course of their observations, they noted that the downstream output looks "exactly like the binding of pheromone by the receptor," Yu says, "a linear relationship between receptor occupancy and downstream activity." With his background in physics, it didn't take much effort to notice how similar it was to a voltage circuit from his electrical engineering classes. What he also saw was that this dose-response alignment was set up quickly. "Our basic hypothesis was, whatever is happening to set that up is probably happening in the first 15 minutes, so let's look at what's happening in the first 15 minutes," he says.
They found that inhibition of the Fus3 kinase led to disruption of the dose-response alignment, naming Fus3 as a central player in the negative feedback loop that adjusts dose-response alignment. In other words, Fus3, which acts downstream of the membrane-bound G-protein coupled receptor — Sst2 and Ste5 — mediates the dose response of the cell. When it's inhibited, the alignment is off. Yu also found parts of the pathway that they hadn't characterized yet. "We found one area in Sst2, this regulator of G-protein signaling … we saw that actually Sst2 helps bind Ste5 to the membrane," Yu says.
Another interesting finding was that the dose-response alignment feedback loop actually improves the transmission of information. First, Yu says, it reduces the amount of noise amplification from upstream steps. In other words, a small change in dose effects a large change downstream, "so any sort of fluctuation will be magnified downstream." Secondly, "if you get [dose-response alignment] with negative feedback, you can preserve a little bit more of the output dynamic range," he adds. "Basically, you can get the input and the output to line up, but the absolute value, the actual amount of change that you can get at downstream, gets much smaller as the dose responses align."
For future studies, Yu would like to look more closely at what else Fus3 might be phosphorylating. In the meantime, he's just happy to have helped lay the foundation for more quantitative systems measurements. "Biologists early on, they'd say, 'We want to learn about the information handling characteristics of [a] pathway.' Well, what does that mean?" Instead of just a buzzword, information in biological systems can finally take on real meaning, as a "very grounded, quantitative way of measuring one aspect, one fundamental function of [a] system," Yu says.