Enterobacterales plasmid sharing amongst human bloodstream infections, livestock, wastewater, and waterway niches in Oxfordshire, UK

  1. William Matlock  Is a corresponding author
  2. Samuel Lipworth
  3. Kevin K Chau
  4. Manal AbuOun
  5. Leanne Barker
  6. James Kavanagh
  7. Monique Andersson
  8. Sarah Oakley
  9. Marcus Morgan
  10. Derrick W Crook
  11. Daniel S Read
  12. Muna Anjum
  13. Liam P Shaw
  14. Nicole Stoesser  Is a corresponding author
  15. REHAB Consortium
  1. University of Oxford, United Kingdom
  2. Animal and Plant Health Agency, United Kingdom
  3. Oxford University Hospitals NHS Trust, United Kingdom
  4. Centre for Ecology and Hydrology, United Kingdom

Abstract

Plasmids enable the dissemination of antimicrobial resistance (AMR) in common Enterobacterales pathogens, representing a major public health challenge. However, the extent of plasmid sharing and evolution between Enterobacterales causing human infections and other niches remains unclear, including the emergence of resistance plasmids. Dense, unselected sampling is highly relevant to developing our understanding of plasmid epidemiology and designing appropriate interventions to limit the emergence and dissemination of plasmid-associated AMR. We established a geographically and temporally restricted collection of human bloodstream infection (BSI)-associated, livestock-associated (cattle, pig, poultry, and sheep faeces, farm soils) and wastewater treatment work (WwTW)-associated (influent, effluent, waterways upstream/downstream of effluent outlets) Enterobacterales. Isolates were collected between 2008-2020 from sites <60km apart in Oxfordshire, UK. Pangenome analysis of plasmid clusters revealed shared 'backbones', with phylogenies suggesting an intertwined ecology where well-conserved plasmid backbones carry diverse accessory functions, including AMR genes. Many plasmid 'backbones' were seen across species and niches, raising the possibility that plasmid movement between these followed by rapid accessory gene change could be relatively common. Overall, the signature of identical plasmid sharing is likely to be a highly transient one, implying that plasmid movement might be occurring at greater rates than previously estimated, raising a challenge for future genomic One Health studies.

Data availability

Accessions for existing BSI and REHAB reads and assemblies can be found in Lipworth et al., 2021 (BioProject PRJNA604975) and Shaw et al., 2021 (BioProject PRJNA605147) respectively. Analysis scripts can be found in the GitHub repository https://github.com/wtmatlock/oxfordshire-overlap.

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

Article and author information

Author details

  1. William Matlock

    Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
    For correspondence
    william.matlock@ndm.ox.ac.uk
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5608-0423
  2. Samuel Lipworth

    Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  3. Kevin K Chau

    Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  4. Manal AbuOun

    Animal and Plant Health Agency, Addlestone, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  5. Leanne Barker

    Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  6. James Kavanagh

    Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  7. Monique Andersson

    Clinical infection, Oxford University Hospitals NHS Trust, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  8. Sarah Oakley

    Clinical infection, Oxford University Hospitals NHS Trust, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  9. Marcus Morgan

    Clinical infection, Oxford University Hospitals NHS Trust, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  10. Derrick W Crook

    Nuffield Department of Medicine, 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:" 0000-0002-0590-2850
  11. Daniel S Read

    Centre for Ecology and Hydrology, Wallingford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  12. Muna Anjum

    Animal and Plant Health Agency, Addlestone, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  13. Liam P Shaw

    Department of Biology, University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  14. Nicole Stoesser

    Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
    For correspondence
    nicole.stoesser@ndm.ox.ac.uk
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4508-7969
  15. REHAB Consortium

Funding

Medical Research Foundation (MRF-145-0004-TPG-AVISO)

  • William Matlock

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

Reviewing Editor

  1. Marc J Bonten, University Medical Center Utrecht, Netherlands

Version history

  1. Preprint posted: May 6, 2022 (view preprint)
  2. Received: December 1, 2022
  3. Accepted: March 22, 2023
  4. Accepted Manuscript published: March 24, 2023 (version 1)
  5. Version of Record published: December 7, 2023 (version 2)

Copyright

© 2023, Matlock 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

  • 1,270
    views
  • 248
    downloads
  • 4
    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. William Matlock
  2. Samuel Lipworth
  3. Kevin K Chau
  4. Manal AbuOun
  5. Leanne Barker
  6. James Kavanagh
  7. Monique Andersson
  8. Sarah Oakley
  9. Marcus Morgan
  10. Derrick W Crook
  11. Daniel S Read
  12. Muna Anjum
  13. Liam P Shaw
  14. Nicole Stoesser
  15. REHAB Consortium
(2023)
Enterobacterales plasmid sharing amongst human bloodstream infections, livestock, wastewater, and waterway niches in Oxfordshire, UK
eLife 12:e85302.
https://doi.org/10.7554/eLife.85302

Share this article

https://doi.org/10.7554/eLife.85302

Further reading

    1. Genetics and Genomics
    2. Neuroscience
    Bohan Zhu, Richard I Ainsworth ... Javier González-Maeso
    Research Article

    Genome-wide association studies have revealed >270 loci associated with schizophrenia risk, yet these genetic factors do not seem to be sufficient to fully explain the molecular determinants behind this psychiatric condition. Epigenetic marks such as post-translational histone modifications remain largely plastic during development and adulthood, allowing a dynamic impact of environmental factors, including antipsychotic medications, on access to genes and regulatory elements. However, few studies so far have profiled cell-specific genome-wide histone modifications in postmortem brain samples from schizophrenia subjects, or the effect of antipsychotic treatment on such epigenetic marks. Here, we conducted ChIP-seq analyses focusing on histone marks indicative of active enhancers (H3K27ac) and active promoters (H3K4me3), alongside RNA-seq, using frontal cortex samples from antipsychotic-free (AF) and antipsychotic-treated (AT) individuals with schizophrenia, as well as individually matched controls (n=58). Schizophrenia subjects exhibited thousands of neuronal and non-neuronal epigenetic differences at regions that included several susceptibility genetic loci, such as NRG1, DISC1, and DRD3. By analyzing the AF and AT cohorts separately, we identified schizophrenia-associated alterations in specific transcription factors, their regulatees, and epigenomic and transcriptomic features that were reversed by antipsychotic treatment; as well as those that represented a consequence of antipsychotic medication rather than a hallmark of schizophrenia in postmortem human brain samples. Notably, we also found that the effect of age on epigenomic landscapes was more pronounced in frontal cortex of AT-schizophrenics, as compared to AF-schizophrenics and controls. Together, these data provide important evidence of epigenetic alterations in the frontal cortex of individuals with schizophrenia, and remark for the first time on the impact of age and antipsychotic treatment on chromatin organization.

    1. Computational and Systems Biology
    2. Genetics and Genomics
    Weichen Song, Yongyong Shi, Guan Ning Lin
    Tools and Resources

    We propose a new framework for human genetic association studies: at each locus, a deep learning model (in this study, Sei) is used to calculate the functional genomic activity score for two haplotypes per individual. This score, defined as the Haplotype Function Score (HFS), replaces the original genotype in association studies. Applying the HFS framework to 14 complex traits in the UK Biobank, we identified 3619 independent HFS–trait associations with a significance of p < 5 × 10−8. Fine-mapping revealed 2699 causal associations, corresponding to a median increase of 63 causal findings per trait compared with single-nucleotide polymorphism (SNP)-based analysis. HFS-based enrichment analysis uncovered 727 pathway–trait associations and 153 tissue–trait associations with strong biological interpretability, including ‘circadian pathway-chronotype’ and ‘arachidonic acid-intelligence’. Lastly, we applied least absolute shrinkage and selection operator (LASSO) regression to integrate HFS prediction score with SNP-based polygenic risk scores, which showed an improvement of 16.1–39.8% in cross-ancestry polygenic prediction. We concluded that HFS is a promising strategy for understanding the genetic basis of human complex traits.