Whole-genome sequencing and machine learning analysis of staphylococcus aureus from multiple heterogeneous sources in china reveals common genetic traits of antimicrobial resistance

Wei Wang, Michelle Baker, Yue Hu, Jin Xu, Dajin Yang, Alexandre Maciel-Guerra, Ning Xue, Hui Li, Shaofei Yan, Menghan Li, Yao Bai, Yinping Dong, Zixin Peng, Jinjing Ma, Fengqin Li, Tania Dottorini

Research output: Journal PublicationArticlepeer-review

15 Citations (Scopus)

Abstract

Staphylococcus aureus is a worldwide leading cause of numerous diseases ranging from food-poisoning to lethal infections. Methicillin-resistant S. aureus (MRSA) has been found capable of acquiring resistance to most antimicrobials. MRSA is ubiquitous and diverse even in terms of antimicrobial resistance (AMR) profiles, posing a challenge for treatment. Here, we present a comprehensive study of S. aureus in China, addressing epidemiology, phylogenetic reconstruction, genomic characterization, and identification of AMR profiles. The study analyzes 673 S. aureus isolates from food as well as from hospitalized and healthy individuals. The isolates have been collected over a 9-year period, between 2010 and 2018, from 27 provinces across China. By whole-genome sequencing, Bayesian divergence analysis, and supervised machine learning, we reconstructed the phylogeny of the isolates and compared them to references from other countries. We identified 72 sequence types (STs), of which, 29 were novel. We found 81 MRSA lineages by multilocus sequence type (MLST), spa, staphylococcal cassette chromosome mec element (SCCmec), and Panton-Valentine leukocidin (PVL) typing. In addition, novel variants of SCCmec type IV hosting extra metal and antimicrobial resistance genes, as well as a new SCCmec type, were found. New Bayesian dating of the split times of major clades showed that ST9, ST59, and ST239 in China and European countries fell in different branches, whereas this pattern was not observed for the ST398 clone. On the contrary, the clonal transmission of ST398 was more intermixed in regard to geographic origin. Finally, we identified genetic determinants of resistance to 10 antimicrobials, discriminating drug-resistant bacteria from susceptible strains in the cohort. Our results reveal the emergence of Chinese MRSA lineages enriched of AMR determinants that share similar genetic traits of antimicrobial resistance across human and food, hinting at a complex scenario of evolving transmission routes.

Original languageEnglish
Article numbere01185-20
JournalmSystems
Volume6
Issue number3
DOIs
Publication statusPublished - Jun 2021

Keywords

  • Antimicrobial resistance
  • Bayesian divergence analysis
  • Foodborne pathogen
  • Methicillin-resistant Staphylococcus aureus (MRSA)
  • Staphylococcus aureus
  • Supervised machine learning
  • Whole-genome sequencing

ASJC Scopus subject areas

  • Genetics
  • Ecology, Evolution, Behavior and Systematics
  • Molecular Biology
  • Physiology
  • Biochemistry
  • Computer Science Applications
  • Microbiology
  • Modelling and Simulation

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