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Diagnostic microbiology and infectious disease
Jul, 2020;97 (3): 115060.

Staphylococcus aureus whole genome sequence-based susceptibility and resistance prediction using a clinically amenable workflow.

Scott A Cunningham, Patricio R Jeraldo, Audrey N Schuetz, Angela A Heitman, Robin Patel
Author Information
  1. Scott A Cunningham: Division of Clinical Microbiology, Mayo Clinic, Rochester, MN.
  2. Patricio R Jeraldo: Department of Surgery and Center for Individualized Medicine Microbiome Program, Mayo Clinic, Rochester, MN.
  3. Audrey N Schuetz: Division of Clinical Microbiology, Mayo Clinic, Rochester, MN; Division of Infectious Diseases, Department of Medicine, Mayo Clinic, Rochester, MN.
  4. Angela A Heitman: Division of Clinical Microbiology, Mayo Clinic, Rochester, MN.
  5. Robin Patel: Division of Clinical Microbiology, Mayo Clinic, Rochester, MN; Division of Infectious Diseases, Department of Medicine, Mayo Clinic, Rochester, MN. Electronic address: patel.robin@mayo.edu.
PMID: 32417617 DOI: 10.1016/j.diagmicrobio.2020.115060

Abstract

We used graphical user interface-based automated analytical tools from Next Gen Diagnostics (Mountain View, CA) and 1928 Diagnostics (Gothenburg, Sweden) to analyze whole genome sequence (WGS) data from 102 unique blood culture isolates of Staphylococcus aureus to predict antimicrobial susceptibly, with results compared to those of phenotypic susceptibility testing. Of 916 isolate/antibiotic combinations analyzed using the Next Gen Diagnostics tool, there were 9 discrepancies between WGS predictions and phenotypic susceptibility/resistance, including 8 for clindamycin and 1 for minocycline. Of 612 isolate/antibiotic combinations analyzed using the 1928 Diagnostics tool, there were 13 discrepancies between WGS predictions and phenotypic susceptibility/resistance, including 9 for clindamycin, 3 for trimethoprim-sulfamethoxazole, and 1 for rifampin. Trimethoprim-sulfamethoxazole was not assessed by Next Gen Diagnostics, and minocycline was not assessed by 1928 Diagnostics. There was complete concordance between phenotypic susceptibility/resistance and genotypic prediction of susceptibility/resistance using both analytical platforms for oxacillin, vancomycin, and mupirocin, as well as by the Next Gen Diagnostics analytical tool for levofloxacin (the 1928 Diagnostics tool did not assess levofloxacin). These results suggest that, from a performance standpoint, with some caveats, automatic bioinformatics tools may be acceptable to predict susceptibility and resistance to a panel of antibiotics for S. aureus.

Keywords

Antibiotics Genome Sequencing Staphylococcus aureus

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Grants

  1. R01 AR056647/NIAMS NIH HHS
  2. UM1 AI104681/NIAID NIH HHS

MeSH Term

Anti-Bacterial Agents
Bacterial Proteins
Drug Resistance, Bacterial
Genome, Bacterial
Genotype
Humans
Microbial Sensitivity Tests
Software
Staphylococcal Infections
Staphylococcus aureus
Whole Genome Sequencing
Workflow

Chemicals

Anti-Bacterial Agents
Bacterial Proteins
Journal Article
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