Fitness effects of altering gene expression noise in Saccharomyces cerevisiae

Abstract

Gene expression noise is an evolvable property of biological systems that describes differences in expression among genetically identical cells in the same environment. Prior work has shown that expression noise is heritable and can be shaped by selection, but the impact of variation in expression noise on organismal fitness has proven difficult to measure. Here, we quantify the fitness effects of altering expression noise for the TDH3 gene in Saccharomyces cerevisiae. We show that increases in expression noise can be deleterious or beneficial depending on the difference between the average expression level of a genotype and the expression level maximizing fitness. We also show that a simple model relating single-cell expression levels to population growth produces patterns consistent with our empirical data. We use this model to explore a broad range of average expression levels and expression noise, providing additional insight into the fitness effects of variation in expression noise.

Data availability

Flow data (FCS files) used to quantify fluorescence levels produced by the 43 TDH3 promoter alleles are available in the FlowRepository (flowrepository.org) under experiment ID FR-FCM-ZY8Y.Raw bright field and fluorescence images, as well as bright field images where cell division events were annotated, are available on Zenodo (https://zenodo.org) with DOI 10.5281/zenodo.1327545All other data are provided as source data and/or supplementary files with the manuscript.

Article and author information

Author details

  1. Fabien Duveau

    Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, United States
    Competing interests
    No competing interests declared.
  2. Andrea Hodgins-Davis

    Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, United States
    Competing interests
    No competing interests declared.
  3. Brian PH Metzger

    Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, United States
    Competing interests
    No competing interests declared.
  4. Bing Yang

    Department of Molecular, Cellular and Developmental Biology, University of Michigan, Ann Arbor, United States
    Competing interests
    No competing interests declared.
  5. Stephen Tryban

    Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, United States
    Competing interests
    No competing interests declared.
  6. Elizabeth A Walker

    Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, United States
    Competing interests
    No competing interests declared.
  7. Tricia Lybrook

    Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, United States
    Competing interests
    No competing interests declared.
  8. Patricia J Wittkopp

    Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, United States
    For correspondence
    wittkopp@umich.edu
    Competing interests
    Patricia J Wittkopp, Senior editor, eLife.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7619-0048

Funding

National Institutes of Health (R01GM108826)

  • Patricia J Wittkopp

European Molecular Biology Organization (EMBO ALTF 1114-2012)

  • Brian PH Metzger

National Science Foundation (CB-1021398)

  • Patricia J Wittkopp

National Institutes of Health (1F32GM115198)

  • Andrea Hodgins-Davis

National Institutes of Health (R35GM118073)

  • Patricia J Wittkopp

National Institutes of Health (T32 HG000040)

  • Brian PH Metzger

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

Reviewing Editor

  1. Naama Barkai, Weizmann Institute of Science, Israel

Publication history

  1. Received: April 5, 2018
  2. Accepted: August 17, 2018
  3. Accepted Manuscript published: August 20, 2018 (version 1)
  4. Version of Record published: September 11, 2018 (version 2)

Copyright

© 2018, Duveau 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.

Metrics

  • 4,555
    Page views
  • 648
    Downloads
  • 28
    Citations

Article citation count generated by polling the highest count across the following sources: Crossref, Scopus, PubMed Central.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Fabien Duveau
  2. Andrea Hodgins-Davis
  3. Brian PH Metzger
  4. Bing Yang
  5. Stephen Tryban
  6. Elizabeth A Walker
  7. Tricia Lybrook
  8. Patricia J Wittkopp
(2018)
Fitness effects of altering gene expression noise in Saccharomyces cerevisiae
eLife 7:e37272.
https://doi.org/10.7554/eLife.37272

Further reading

    1. Computational and Systems Biology
    2. Evolutionary Biology
    Mihaly Badonyi, Joseph A Marsh
    Research Article Updated

    Assembly pathways of protein complexes should be precise and efficient to minimise misfolding and unwanted interactions with other proteins in the cell. One way to achieve this efficiency is by seeding assembly pathways during translation via the cotranslational assembly of subunits. While recent evidence suggests that such cotranslational assembly is widespread, little is known about the properties of protein complexes associated with the phenomenon. Here, using a combination of proteome-specific protein complex structures and publicly available ribosome profiling data, we show that cotranslational assembly is particularly common between subunits that form large intermolecular interfaces. To test whether large interfaces have evolved to promote cotranslational assembly, as opposed to cotranslational assembly being a non-adaptive consequence of large interfaces, we compared the sizes of first and last translated interfaces of heteromeric subunits in bacterial, yeast, and human complexes. When considering all together, we observe the N-terminal interface to be larger than the C-terminal interface 54% of the time, increasing to 64% when we exclude subunits with only small interfaces, which are unlikely to cotranslationally assemble. This strongly suggests that large interfaces have evolved as a means to maximise the chance of successful cotranslational subunit binding.

    1. Evolutionary Biology
    2. Microbiology and Infectious Disease
    Pramod K Jangir et al.
    Research Article

    Bacterial pathogens show high levels of chromosomal genetic diversity, but the influence of this diversity on the evolution of antibiotic resistance by plasmid acquisition remains unclear. Here, we address this problem in the context of colistin, a ‘last line of defence’ antibiotic. Using experimental evolution, we show that a plasmid carrying the MCR-1 colistin resistance gene dramatically increases the ability of Escherichia coli to evolve high-level colistin resistance by acquiring mutations in lpxC, an essential chromosomal gene involved in lipopolysaccharide biosynthesis. Crucially, lpxC mutations increase colistin resistance in the presence of the MCR-1 gene, but decrease the resistance of wild-type cells, revealing positive sign epistasis for antibiotic resistance between the chromosomal mutations and a mobile resistance gene. Analysis of public genomic datasets shows that lpxC polymorphisms are common in pathogenic E. coli, including those carrying MCR-1, highlighting the clinical relevance of this interaction. Importantly, lpxC diversity is high in pathogenic E. coli from regions with no history of MCR-1 acquisition, suggesting that pre-existing lpxC polymorphisms potentiated the evolution of high-level colistin resistance by MCR-1 acquisition. More broadly, these findings highlight the importance of standing genetic variation and plasmid/chromosomal interactions in the evolutionary dynamics of antibiotic resistance.