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Comparison and optimization of two MALDI-TOF MS platforms for the identification of medically relevant yeast species

  • M. A. Pence
  • E. McElvania TeKippe
  • M. A. Wallace
  • C.-A. D. BurnhamEmail author
Article

Abstract

The rapid identification of yeast is essential for the optimization of antifungal therapy. The objective of our study was to evaluate two matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) platforms, the bioMérieux VITEK MS (IVD Knowledgebase v.2.0) and Bruker Biotyper (software version 3.1), for the rapid identification of medically relevant yeast. One hundred and seventeen isolates, representing six genera and 18 species, were analyzed using multiple direct smear methods to optimize identification. Sequence analysis was the gold standard for comparison. Isolates were analyzed with VITEK MS using the direct smear method +/− a 25 % formic acid on-plate extraction. For Biotyper, isolates were analyzed using direct smear without formic acid, and with 25 % and 100 % formic acid on-plate extractions. When all methods were included, VITEK MS correctly identified 113 (96.6 %) isolates after 24 h with one misidentification, and Biotyper correctly identified 77 (65.8 %) isolates using a threshold of ≥2.0 with no misidentifications. Using a revised threshold of ≥1.7, Biotyper correctly identified 103 (88.0 %) isolates, with 3 (2.6 %) misidentifications. For both platforms, the number of identifications was significantly increased using a formic acid overlay (VITEK MS, p < 0.01; Biotyper, p < 0.001), and reducing the Biotyper threshold from ≥2.0 to ≥1.7 significantly increased the rate of identification (p < 0.001). The data in this study demonstrate that the direct smear method with on-plate formic acid extraction can be used for yeast identification on both MS platforms, and more isolates are identified using the VITEK MS system (p < 0.01).

Keywords

Yeast Isolate Clinical Microbiology Laboratory Direct Smear Yeast Identification Formic Acid Extraction 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

The authors thank the Barnes-Jewish Hospital microbiology laboratory for their assistance with this project.

Conflict of interest

E.M.T. and M.A.P. are recipients of the bioMérieux Scholarship in Clinical Microbiology, and the supplies for the work in this study was supported in part by these scholarships. C.-A.D.B. has received research support from bioMérieux.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • M. A. Pence
    • 1
  • E. McElvania TeKippe
    • 1
  • M. A. Wallace
    • 1
  • C.-A. D. Burnham
    • 1
    Email author
  1. 1.Department of Pathology and Immunology, Division of Laboratory and Genomic MedicineWashington University School of MedicineSt. LouisUSA

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