Modeling single-cell phenotypes links yeast stress acclimation to transcriptional repression and pre-stress cellular states

  1. Andrew C Bergen
  2. Rachel A Kocik
  3. James Hose
  4. Megan N McClean
  5. Audrey P Gasch  Is a corresponding author
  1. University of Wisconsin-Madison, United States

Abstract

Stress defense and cell growth are inversely related in bulk culture analyses; however, these studies miss substantial cell-to-cell heterogeneity, thus obscuring true phenotypic relationships. Here, we devised a microfluidics system to characterize multiple phenotypes in single yeast cells over time before, during, and after salt stress. The system measured cell and colony size, growth rate, and cell-cycle phase along with nuclear trans-localization of two transcription factors: stress-activated Msn2 that regulates defense genes and Dot6 that represses ribosome biogenesis genes during an active stress response. By tracking cells dynamically, we discovered unexpected discordance between Msn2 and Dot6 behavior that revealed subpopulations of cells with distinct growth properties. Surprisingly, post-stress growth recovery was positively corelated with activation of the Dot6 repressor. In contrast, cells lacking Dot6 displayed slower growth acclimation, even though they grow normally in the absence of stress. We show that wild-type cells with a larger Dot6 response display faster production of Msn2-regulated Ctt1 protein, separable from the contribution of Msn2. These results are consistent with the model that transcriptional repression during acute stress in yeast provides a protective response, likely by redirecting translational capacity to induced transcripts.

Data availability

All data generated and analyzed during this study are included in the manuscript and supporting files. Code used to analyze image files and generate data for cellular phenotypes is included in Source Code Files. Supplementary Data Files containing cells and associated phenotypic information are included. Source Data Files have been provided for Figure 4, and Figure 4 - supplement 1.

Article and author information

Author details

  1. Andrew C Bergen

    Center for Genomic Science Innovation, University of Wisconsin-Madison, Madison, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1295-7718
  2. Rachel A Kocik

    Center for Genomic Science Innovation, University of Wisconsin-Madison, Madison, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2422-4538
  3. James Hose

    Center for Genomic Science Innovation, University of Wisconsin-Madison, Madison, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Megan N McClean

    Center for Genomic Science Innovation, University of Wisconsin-Madison, Madison, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Audrey P Gasch

    Center for Genomic Science Innovation, University of Wisconsin-Madison, Madison, United States
    For correspondence
    agasch@wisc.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8182-257X

Funding

National Science Foundation (1715324)

  • Audrey P Gasch

Burroughs Wellcome Fund (1R35GM128873)

  • Megan N McClean

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

© 2022, Bergen et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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https://doi.org/10.7554/eLife.82017

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