University of Sussex
Browse
Prediction_of_Staphylococcus_aureus_Antimicrobial_Resistance.pdf (225.49 kB)

Prediction of Staphylococcus aureus antimicrobial resistance by whole-genome sequencing.

Download (225.49 kB)
journal contribution
posted on 2023-06-08, 18:17 authored by N C Gordon, J R Price, K Cole, R Everitt, M Morgan, J Finney, A M Kearns, B Pichon, B Young, D J Wilson, Martin LlewelynMartin Llewelyn, J Paul, T E A Peto, D W Crook, A S Walker, T Golubchik
Whole-genome sequencing (WGS) could potentially provide a single platform for extracting all the information required to predict an organism's phenotype. However, its ability to provide accurate predictions has not yet been demonstrated in large independent studies of specific organisms. In this study, we aimed to develop a genotypic prediction method for antimicrobial susceptibilities. The whole genomes of 501 unrelated Staphylococcus aureus isolates were sequenced, and the assembled genomes were interrogated using BLASTn for a panel of known resistance determinants (chromosomal mutations and genes carried on plasmids). Results were compared with phenotypic susceptibility testing for 12 commonly used antimicrobial agents (penicillin, methicillin, erythromycin, clindamycin, tetracycline, ciprofloxacin, vancomycin, trimethoprim, gentamicin, fusidic acid, rifampin, and mupirocin) performed by the routine clinical laboratory. We investigated discrepancies by repeat susceptibility testing and manual inspection of the sequences and used this information to optimize the resistance determinant panel and BLASTn algorithm. We then tested performance of the optimized tool in an independent validation set of 491 unrelated isolates, with phenotypic results obtained in duplicate by automated broth dilution (BD Phoenix) and disc diffusion. In the validation set, the overall sensitivity and specificity of the genomic prediction method were 0.97 (95% confidence interval [95% CI], 0.95 to 0.98) and 0.99 (95% CI, 0.99 to 1), respectively, compared to standard susceptibility testing methods. The very major error rate was 0.5%, and the major error rate was 0.7%. WGS was as sensitive and specific as routine antimicrobial susceptibility testing methods. WGS is a promising alternative to culture methods for resistance prediction in S. aureus and ultimately other major bacterial pathogens.

History

Publication status

  • Published

File Version

  • Published version

Journal

Journal of Clinical Microbiology

ISSN

0095-1137/02

Publisher

American Society for Microbiology

Issue

4

Volume

52

Page range

1182-1191

Department affiliated with

  • Global Health and Infection Publications

Full text available

  • Yes

Peer reviewed?

  • Yes

Legacy Posted Date

2014-09-15

First Open Access (FOA) Date

2015-02-24

First Compliant Deposit (FCD) Date

2015-02-24

Usage metrics

    University of Sussex (Publications)

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC