Codon optimization underpins generalist parasitism in fungi

  1. Thomas Badet
  2. Remi Peyraud
  3. Malick Mbengue
  4. Olivier Navaud
  5. Mark Derbyshire
  6. Richard P Oliver
  7. Adelin Barbacci
  8. Sylvain Raffaele  Is a corresponding author
  1. Université de Toulouse, INRA, CNRS, France
  2. Curtin University, Australia

Abstract

The range of hosts that parasites can infect is a key determinant of the emergence and spread of disease. Yet the impact of host range variation on the evolution of parasite genomes remains unknown. Here, we show that codon optimization underlies genome adaptation in broad host range parasite. We found that the longer proteins encoded by broad host range fungi likely increase natural selection on codon optimization in these species. Accordingly, codon optimization correlates with host range across the fungal kingdom. At the species level, biased patterns of synonymous substitutions underpin increased codon optimization in a generalist but not a specialist fungal pathogen. Virulence genes were consistently enriched in highly codon-optimized genes of generalist but not specialist species. We conclude that codon optimization is related to the capacity of parasites to colonize multiple hosts. Our results link genome evolution and translational regulation to the long term persistence of generalist parasitism.

Data availability

The following data sets were generated
    1. Mbengue M
    2. Navaud O
    3. Raffaele S
    (2016) Sclerotinia sclerotiorum isolates genome sequence
    Publicly available at the NCBI BioProject (accession no: PRJNA342788).
The following previously published data sets were used

Article and author information

Author details

  1. Thomas Badet

    Laboratoire des Interactions Plantes-Microorganismes, Université de Toulouse, INRA, CNRS, Castanet-Tolosan, France
    Competing interests
    The authors declare that no competing interests exist.
  2. Remi Peyraud

    Laboratoire des Interactions Plantes-Microorganismes, Université de Toulouse, INRA, CNRS, Castanet Tolosan, France
    Competing interests
    The authors declare that no competing interests exist.
  3. Malick Mbengue

    Laboratoire des Interactions Plantes-Microorganismes, Université de Toulouse, INRA, CNRS, Castanet-Tolosan, France
    Competing interests
    The authors declare that no competing interests exist.
  4. Olivier Navaud

    Laboratoire des Interactions Plantes-Microorganismes, Université de Toulouse, INRA, CNRS, Castanet-Tolosan, France
    Competing interests
    The authors declare that no competing interests exist.
  5. Mark Derbyshire

    Centre for Crop and Disease Management, Department of Environment and Agriculture, Curtin University, Perth, Australia
    Competing interests
    The authors declare that no competing interests exist.
  6. Richard P Oliver

    Centre for Crop and Disease Management, Department of Environment and Agriculture, Curtin University, Perth, Australia
    Competing interests
    The authors declare that no competing interests exist.
  7. Adelin Barbacci

    Laboratoire des Interactions Plantes-Microorganismes, Université de Toulouse, INRA, CNRS, Castanet-Tolosan, France
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3156-272X
  8. Sylvain Raffaele

    Laboratoire des Interactions Plantes-Microorganismes, Université de Toulouse, INRA, CNRS, Castanet-Tolosan, France
    For correspondence
    sylvain.raffaele@toulouse.inra.fr
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2442-9632

Funding

European Research Council (ERC-StG 336808)

  • Thomas Badet
  • Remi Peyraud
  • Malick Mbengue
  • Olivier Navaud
  • Sylvain Raffaele

Labex TULIP (ANR-10-LABX-41; ANR-11-IDEX-0002-02)

  • Thomas Badet
  • Remi Peyraud
  • Malick Mbengue
  • Olivier Navaud
  • Adelin Barbacci
  • Sylvain Raffaele

Australian grains research and development corporation

  • Mark Derbyshire
  • Richard P Oliver

Curtin University of Technology

  • Mark Derbyshire
  • Richard P Oliver

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

Copyright

© 2017, Badet 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

  • 3,401
    views
  • 679
    downloads
  • 38
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

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. Thomas Badet
  2. Remi Peyraud
  3. Malick Mbengue
  4. Olivier Navaud
  5. Mark Derbyshire
  6. Richard P Oliver
  7. Adelin Barbacci
  8. Sylvain Raffaele
(2017)
Codon optimization underpins generalist parasitism in fungi
eLife 6:e22472.
https://doi.org/10.7554/eLife.22472

Share this article

https://doi.org/10.7554/eLife.22472

Further reading

    1. Genetics and Genomics
    2. Microbiology and Infectious Disease
    Dániel Molnár, Éva Viola Surányi ... Judit Toth
    Research Article

    The sustained success of Mycobacterium tuberculosis as a pathogen arises from its ability to persist within macrophages for extended periods and its limited responsiveness to antibiotics. Furthermore, the high incidence of resistance to the few available antituberculosis drugs is a significant concern, especially since the driving forces of the emergence of drug resistance are not clear. Drug-resistant strains of Mycobacterium tuberculosis can emerge through de novo mutations, however, mycobacterial mutation rates are low. To unravel the effects of antibiotic pressure on genome stability, we determined the genetic variability, phenotypic tolerance, DNA repair system activation, and dNTP pool upon treatment with current antibiotics using Mycobacterium smegmatis. Whole-genome sequencing revealed no significant increase in mutation rates after prolonged exposure to first-line antibiotics. However, the phenotypic fluctuation assay indicated rapid adaptation to antibiotics mediated by non-genetic factors. The upregulation of DNA repair genes, measured using qPCR, suggests that genomic integrity may be maintained through the activation of specific DNA repair pathways. Our results, indicating that antibiotic exposure does not result in de novo adaptive mutagenesis under laboratory conditions, do not lend support to the model suggesting antibiotic resistance development through drug pressure-induced microevolution.

    1. Computational and Systems Biology
    2. Genetics and Genomics
    Sanjarbek Hudaiberdiev, Ivan Ovcharenko
    Research Article

    Enhancers and promoters are classically considered to be bound by a small set of transcription factors (TFs) in a sequence-specific manner. This assumption has come under increasing skepticism as the datasets of ChIP-seq assays of TFs have expanded. In particular, high-occupancy target (HOT) loci attract hundreds of TFs with often no detectable correlation between ChIP-seq peaks and DNA-binding motif presence. Here, we used a set of 1003 TF ChIP-seq datasets (HepG2, K562, H1) to analyze the patterns of ChIP-seq peak co-occurrence in combination with functional genomics datasets. We identified 43,891 HOT loci forming at the promoter (53%) and enhancer (47%) regions. HOT promoters regulate housekeeping genes, whereas HOT enhancers are involved in tissue-specific process regulation. HOT loci form the foundation of human super-enhancers and evolve under strong negative selection, with some of these loci being located in ultraconserved regions. Sequence-based classification analysis of HOT loci suggested that their formation is driven by the sequence features, and the density of mapped ChIP-seq peaks across TF-bound loci correlates with sequence features and the expression level of flanking genes. Based on the affinities to bind to promoters and enhancers we detected five distinct clusters of TFs that form the core of the HOT loci. We report an abundance of HOT loci in the human genome and a commitment of 51% of all TF ChIP-seq binding events to HOT locus formation thus challenging the classical model of enhancer activity and propose a model of HOT locus formation based on the existence of large transcriptional condensates.