Abstract
Staphylococcus aureus remains an important human pathogen responsible for a high burden of disease in healthcare and community settings. The emergence of multidrug-resistant strains is of increasing concern world-wide. The identification of S. aureus is currently based upon phenotypic and genotypic methods. Here, an alternative approach involving mass spectral analysis of surface-associated proteins of intact bacterial cells by matrix-assisted laser desorption/ionisation time of flight mass spectrometry (MALDI-TOF-MS) was investigated using 95 isolates obtained directly from a clinical laboratory at The Royal London Hospital and 39 isolates from the Staphylococcal Reference Unit, Health Protection Agency, London. Results obtained indicate that clinical isolates share many common mass ions with-type/reference strains which allowed their correct identification when searched against a comprehensive database that has been in the process of development for several years. The existing database contains more than 5000 profiles of various bacterial pathogens, but comprises mainly type or reference strains. The MicrobeLynx software successfully identified all isolates to the correct genus and all but four to the correct species. These were misidentified in the first instance due to contamination or low mass ion intensity but once the cultures were purified and re-analysed they were confirmed as S. aureus by both MALDI-TOF-MS and 16S rRNA sequence analysis. The high percentage of correct identifications coupled with the high speed and the minimal sample preparation required, indicate that MALDI-TOF-MS has the potential to perform high throughput identification of clinical isolates of S. aureus despite the inherent diversity of this species. The method is, however, only reproducible if variable parameters such as sample preparation, media, growth condition, etc. are standardised.
| Original language | English |
|---|---|
| Pages (from-to) | 507-513 |
| Number of pages | 7 |
| Journal | Infection, Genetics and Evolution |
| Volume | 9 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - Jul 2009 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- 16S rRNA
- Intact cell MALDI
- MALDI-TOF-MS
- Microbial identification
- Staphylococcus aureus
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