Ratiometric GPCR signaling enables directional sensing in yeast.


Accurate detection of extracellular chemical gradients is essential for many cellular behaviors. Gradient sensing is challenging for small cells, which can experience little difference in ligand concentrations on the up-gradient and down-gradient sides of the cell. Nevertheless, the tiny cells of the yeast Saccharomyces cerevisiae reliably decode gradients of extracellular pheromones to find their mates. By imaging the behavior of polarity factors and pheromone receptors, we quantified the accuracy of initial polarization during mating encounters. We found that cells bias the orientation of initial polarity up-gradient, even though they have unevenly distributed receptors. Uneven receptor density means that the gradient of ligand-bound receptors does not accurately reflect the external pheromone gradient. Nevertheless, yeast cells appear to avoid being misled by responding to the fraction of occupied receptors rather than simply the concentration of ligand-bound receptors. Such ratiometric sensing also serves to amplify the gradient of active G protein. However, this process is quite error-prone, and initial errors are corrected during a subsequent indecisive phase in which polarity clusters exhibit erratic mobile behavior.





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Publication Info

Henderson, Nicholas T, Michael Pablo, Debraj Ghose, Manuella R Clark-Cotton, Trevin R Zyla, James Nolen, Timothy C Elston, Daniel J Lew, et al. (2019). Ratiometric GPCR signaling enables directional sensing in yeast. PLoS biology, 17(10). p. e3000484. 10.1371/journal.pbio.3000484 Retrieved from https://hdl.handle.net/10161/24510.

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James H. Nolen

Professor of Mathematics

My research is in the area of probability and partial differential equations, which have been used to model many phenomena in the natural sciences and engineering.  Asymptotic analysis has been a common theme in much of my research.  Current research interests include: stochastic dynamics, interacting particle systems, reaction-diffusion equations, applications to biological models.

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