Distributing tasks via multiple input pathways increase cellular survival in stress
eLife Sciences Publications
© 2017, Granados et al. This article is distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) permitting unrestricted use and redistribution provided that the original author and source are credited.
Improving in one aspect of a task can undermine performance in another, but how such opposing demands play out in single cells and impact on fitness is mostly unknown. Here we study budding yeast in dynamic environments of hyperosmotic stress and show how the corresponding signalling network increases cellular survival both by assigning the requirements of high response speed and high response accuracy to two separate input pathways and by having these pathways interact to converge on Hog1, a p38 MAP kinase. Cells with only the less accurate, reflex-like pathway are fitter in sudden stress, whereas cells with only the slow, more accurate pathway are fitter in fluctuating but increasing stress. Our results demonstrate that cellular signalling is vulnerable to trade-offs in performance, but that these trade-offs can be mitigated by assigning the opposing tasks to different signalling subnetworks. Such division of labour could function broadly within cellular signal transduction.
We thank Michael Elowitz, Robert Endres, Tanniemola Liverpool, FilippoMenolascina, Diego Oyarzun, Lynne Regan, the members of the Swain lab, and particularly Pascal Hersen for critical comments, Pascal Hersen for providing strains, and our funders: the Human Frontier Science Program, the Scottish Universities Life Sciences Alliance, and the UK’s BBSRC (MMC & PSS), the UK’s MRC (MV), the Wellcome Trust (LFM), the UK’s EPSRC (MV via grant EP/N014391/1, AAG, & RT), and Mexico’s CONACyT (AAG & LFM).
This is the author accepted manuscript. The final version is available from eLife Sciences Publications via the DOI in this record.
Vol. 6, article e21415
Place of publication
Except where otherwise noted, this item's license is described as © 2017, Granados et al. This article is distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) permitting unrestricted use and redistribution provided that the original author and source are credited.