Niche-specific genome degradation and convergent evolution shaping Staphylococcus aureus adaptation during severe infections

Abstract

During severe infections, Staphylococcus aureus moves from its colonising sites to blood and tissues, and is exposed to new selective pressures, thus potentially driving adaptive evolution. Previous studies have shown the key role of the agr locus in S. aureus pathoadaptation, however a more comprehensive characterisation of genetic signatures of bacterial adaptation may enable prediction of clinical outcomes and reveal new targets for treatment and prevention of these infections. Here, we measured adaptation using within-host evolution analysis of 2,590 S. aureus genomes from 396 independent episodes of infection. By capturing a comprehensive repertoire of single-nucleotide and structural genome variations, we found evidence of a distinctive evolutionary pattern within the infecting populations compared to colonising bacteria. These invasive strains had up to 20-fold enrichments for genome degradation signatures and displayed significantly convergent mutations in a distinctive set of genes, linked to antibiotic response and pathogenesis. In addition to agr-mediated adaptation we identified non-canonical, genome-wide significant loci including sucA-sucB and stp1. The prevalence of adaptive changes increased with infection extent, emphasising the clinical significance of these signatures. These findings provide a high-resolution picture of the molecular changes when S. aureus transitions from colonisation to severe infection and may inform correlation of infection outcomes with adaptation signatures.

Data availability

All data generated or analysed during this study are included in the manuscript and supporting file 1-6.The code to call, filter and annotated within-host variants and to perform the enrichment analysis is available on github at https://github.com/stefanogg/staph_adaptation_paper

The following data sets were generated
The following previously published data sets were used

Article and author information

Author details

  1. Stefano G Giulieri

    Department of Microbiology and Immunology, University of Melbourne, Parkville, Australia
    Competing interests
    The authors declare that no competing interests exist.
  2. Romain Guérillot

    Department of Microbiology and Immunology, University of Melbourne, Melbourne, Australia
    Competing interests
    The authors declare that no competing interests exist.
  3. Sebastian Duchene

    Department of Microbiology and Immunology, University of Melbourne, Melbourne, Australia
    Competing interests
    The authors declare that no competing interests exist.
  4. Abderrahman Hachani

    Department of Microbiology and Immunology, University of Melbourne, Melbourne, Australia
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8032-2154
  5. Diane Daniel

    Department of Microbiology and Immunology, University of Melbourne, Melbourne, Australia
    Competing interests
    The authors declare that no competing interests exist.
  6. Torsten Seemann

    Microbiological Diagnostic Unit, University of Melbourne, Melbourne, Australia
    Competing interests
    The authors declare that no competing interests exist.
  7. Joshua S Davis

    Department of Infectious Diseases, John Hunter Hospital, Newcastle, Australia
    Competing interests
    The authors declare that no competing interests exist.
  8. Steven YC Tong

    Victorian Infectious Diseases Service, University of Melbourne, Melbourne, Australia
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1368-8356
  9. Bernadette C Young

    University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6071-6770
  10. Daniel J Wilson

    University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0940-3311
  11. Timothy P Stinear

    Department of Microbiology and Immunology, University of Melbourne, Melbourne, Australia
    Competing interests
    The authors declare that no competing interests exist.
  12. Benjamin P Howden

    Department of Microbiology and Immunology, University of Melbourne, Melbourne, Australia
    For correspondence
    bhowden@unimelb.edu.au
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0237-1473

Funding

National Health and Medical Research Council

  • Timothy P Stinear

National Health and Medical Research Council

  • Benjamin P Howden

The University of Melbourne

  • Stefano G Giulieri

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

Ethics

Human subjects: Ethics approval was obtained at each partecipating site to the CAMERA2 trial and written informed onsent was obtained from each participant or surrogate decision maker.

Copyright

© 2022, Giulieri 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

  • 2,871
    views
  • 605
    downloads
  • 30
    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. Stefano G Giulieri
  2. Romain Guérillot
  3. Sebastian Duchene
  4. Abderrahman Hachani
  5. Diane Daniel
  6. Torsten Seemann
  7. Joshua S Davis
  8. Steven YC Tong
  9. Bernadette C Young
  10. Daniel J Wilson
  11. Timothy P Stinear
  12. Benjamin P Howden
(2022)
Niche-specific genome degradation and convergent evolution shaping Staphylococcus aureus adaptation during severe infections
eLife 11:e77195.
https://doi.org/10.7554/eLife.77195

Share this article

https://doi.org/10.7554/eLife.77195

Further reading

    1. Computational and Systems Biology
    2. Genetics and Genomics
    Eric V Strobl, Eric Gamazon
    Research Article

    Root causal gene expression levels – or root causal genes for short – correspond to the initial changes to gene expression that generate patient symptoms as a downstream effect. Identifying root causal genes is critical towards developing treatments that modify disease near its onset, but no existing algorithms attempt to identify root causal genes from data. RNA-sequencing (RNA-seq) data introduces challenges such as measurement error, high dimensionality and non-linearity that compromise accurate estimation of root causal effects even with state-of-the-art approaches. We therefore instead leverage Perturb-seq, or high-throughput perturbations with single-cell RNA-seq readout, to learn the causal order between the genes. We then transfer the causal order to bulk RNA-seq and identify root causal genes specific to a given patient for the first time using a novel statistic. Experiments demonstrate large improvements in performance. Applications to macular degeneration and multiple sclerosis also reveal root causal genes that lie on known pathogenic pathways, delineate patient subgroups and implicate a newly defined omnigenic root causal model.

    1. Chromosomes and Gene Expression
    2. Genetics and Genomics
    Steven Henikoff, David L Levens
    Insight

    A new method for mapping torsion provides insights into the ways that the genome responds to the torsion generated by RNA polymerase II.