Fine-Tuning of Energy Levels Regulates SUC2 via a SNF1-Dependent Feedback Loop
Artikel i vetenskaplig tidskrift, 2020

Nutrient sensing pathways are playing an important role in cellular response to different energy levels. In budding yeast, Saccharomyces cerevisiae, the sucrose non-fermenting protein kinase complex SNF1 is a master regulator of energy homeostasis. It is affected by multiple inputs, among which energy levels is the most prominent. Cells which are exposed to a switch in carbon source availability display a change in the gene expression machinery. It has been shown that the magnitude of the change varies from cell to cell. In a glucose rich environment Snf1/Mig1 pathway represses the expression of its downstream target, such as SUC2. However, upon glucose depletion SNF1 is activated which leads to an increase in SUC2 expression. Our single cell experiments indicate that upon starvation, gene expression pattern of SUC2 shows rapid increase followed by a decrease to initial state with high cell-to-cell variability. The mechanism behind this behavior is currently unknown. In this work we study the long-term behavior of the Snf1/Mig1 pathway upon glucose starvation with a microfluidics and non-linear mixed effect modeling approach. We show a negative feedback mechanism, involving Snf1 and Reg1, which reduces SUC2 expression after the initial strong activation. Snf1 kinase activity plays a key role in this feedback mechanism. Our systems biology approach proposes a negative feedback mechanism that works through the SNF1 complex and is controlled by energy levels. We further show that Reg1 likely is involved in the negative feedback mechanism.


nutrient signaling



dynamic modeling




Sebastian Persson

Göteborgs universitet

Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik

Niek Welkenhuysen

Göteborgs universitet

Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik

Sviatlana Shashkova

Göteborgs universitet

Marija Cvijovic

Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik

Göteborgs universitet

Frontiers in Physiology

1664042x (eISSN)

Vol. 11 954



Cell- och molekylärbiologi




Mer information

Senast uppdaterat