Frontiers in Microbiology (Nov 2020)

NGS-Based S. aureus Typing and Outbreak Analysis in Clinical Microbiology Laboratories: Lessons Learned From a Swiss-Wide Proficiency Test

  • David Dylus,
  • David Dylus,
  • David Dylus,
  • Trestan Pillonel,
  • Onya Opota,
  • Daniel Wüthrich,
  • Daniel Wüthrich,
  • Helena M. B. Seth-Smith,
  • Helena M. B. Seth-Smith,
  • Adrian Egli,
  • Adrian Egli,
  • Stefano Leo,
  • Vladimir Lazarevic,
  • Jacques Schrenzel,
  • Sacha Laurent,
  • Claire Bertelli,
  • Dominique S. Blanc,
  • Stefan Neuenschwander,
  • Alban Ramette,
  • Laurent Falquet,
  • Laurent Falquet,
  • Frank Imkamp,
  • Peter M. Keller,
  • Andre Kahles,
  • Andre Kahles,
  • Simone Oberhaensli,
  • Simone Oberhaensli,
  • Valérie Barbié,
  • Christophe Dessimoz,
  • Christophe Dessimoz,
  • Christophe Dessimoz,
  • Christophe Dessimoz,
  • Christophe Dessimoz,
  • Gilbert Greub,
  • Aitana Lebrand

DOI
https://doi.org/10.3389/fmicb.2020.591093
Journal volume & issue
Vol. 11

Abstract

Read online

Whole genome sequencing (WGS) enables high resolution typing of bacteria up to the single nucleotide polymorphism (SNP) level. WGS is used in clinical microbiology laboratories for infection control, molecular surveillance and outbreak analyses. Given the large palette of WGS reagents and bioinformatics tools, the Swiss clinical bacteriology community decided to conduct a ring trial (RT) to foster harmonization of NGS-based bacterial typing. The RT aimed at assessing methicillin-susceptible Staphylococcus aureus strain relatedness from WGS and epidemiological data. The RT was designed to disentangle the variability arising from differences in sample preparation, SNP calling and phylogenetic methods. Nine laboratories participated. The resulting phylogenetic tree and cluster identification were highly reproducible across the laboratories. Cluster interpretation was, however, more laboratory dependent, suggesting that an increased sharing of expertise across laboratories would contribute to further harmonization of practices. More detailed bioinformatic analyses unveiled that while similar clusters were found across laboratories, these were actually based on different sets of SNPs, differentially retained after sample preparation and SNP calling procedures. Despite this, the observed number of SNP differences between pairs of strains, an important criterion to determine strain relatedness given epidemiological information, was similar across pipelines for closely related strains when restricting SNP calls to a common core genome defined by S. aureus cgMLST schema. The lessons learned from this pilot study will serve the implementation of larger-scale RT, as a mean to have regular external quality assessments for laboratories performing WGS analyses in a clinical setting.

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