Single-cell study links metabolism with nutrient signaling and reveals sources of variability
Artikel i vetenskaplig tidskrift, 2017

Background: The yeast AMPK/SNF1 pathway is best known for its role in glucose de/repression. When glucose becomes limited, the Snf1 kinase is activated and phosphorylates the transcriptional repressor Mig1, which is then exported from the nucleus. The exact mechanism how the Snf1-Mig1 pathway is regulated is not entirely elucidated. Results: Glucose uptake through the low affinity transporter Hxt1 results in nuclear accumulation of Mig1 in response to all glucose concentrations upshift, however with increasing glucose concentration the nuclear localization of Mig1 is more intense. Strains expressing Hxt7 display a constant response to all glucose concentration upshifts. We show that differences in amount of hexose transporter molecules in the cell could cause cell-to-cell variability in the Mig1-Snf1 system. We further apply mathematical modelling to our data, both general deterministic and a nonlinear mixed effect model. Our model suggests a presently unrecognized regulatory step of the Snf1-Mig1 pathway at the level of Mig1 dephosphorylation. Model predictions point to parameters involved in the transport of Mig1 in and out of the nucleus as a majorsource of cell to cell variability. Conclusions: With this modelling approach we have been able to suggest steps that contribute to the cell-to-cell variability. Our data indicate a close link between the glucose uptake rate, which determines the glycolytic rate, and the activity of the Snf1/Mig1 system. This study hence establishes a close relation between metabolism and signalling.

Dynamical modelling

Microfluidics systems

Non-linear mixed effect modelling

Glucose uptake


Niek Welkenhuysen

Göteborgs universitet

Johannes Borgqvist

Chalmers, Matematiska vetenskaper

Göteborgs universitet

M. Backman

Göteborgs universitet

Loubna Bendrioua

Göteborgs universitet

Mattias Goksör

Göteborgs universitet

Caroline B. Adiels

Göteborgs universitet

Marija Cvijovic

Chalmers, Matematiska vetenskaper

Göteborgs universitet

Stefan Hohmann

Chalmers, Biologi och bioteknik

BMC Systems Biology

1752-0509 (eISSN)

Vol. 11 1 Article Number: 59- 59





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