Rapid identification of Candida species by confocal Raman microspectroscopy
Candida species are important nosocomial pathogens associated with high mortality rates. Rapid detection and identification of Candida species can guide a clinician at an early stage to prescribe antifungal drugs or to adjust empirical therapy when resistant species are isolated. Confocal Raman microspectroscopy is highly suitable for the rapid identification of Candida species, since Raman spectra can be directly obtained from microcolonies on a solid culture medium after only 6 h of culturing. In this study, we have used a set of 42 Candida strains comprising five species that are frequently encountered in clinical microbiology to test the feasibility of the technique for the rapid identification of Candida species. The procedure was started either from a culture on Sabouraud medium or from a positive vial of an automated blood culture system. Prior to Raman measurements, strains were subcultured on Sabouraud medium for 6 h to form microcolonies. Using multivariate statistical analyses, a high prediction accuracy (97 to 100%) was obtained with the Raman method. Identification with Raman microspectroscopy may therefore be significantly faster than identification with commercial identification systems that allow various species to be identified and that often require 24 to 48 h before a reliable identification is obtained. We conclude that confocal Raman microspectroscopy offers a rapid, accurate, and easy-to-use alternative for the identification of clinically relevant Candida species.
|Keywords||*Bacterial Typing Techniques, Algorithms, Candida/*classification/*growth & development, Candidiasis/microbiology, Culture Media, Humans, Microscopy, Confocal, Research Support, Non-U.S. Gov't, Spectrum Analysis, Raman|
Maquelin, K., Choo-Smith, L.P., Endtz, H.P., Bruining, H.A., & Puppels, G.J.. (2002). Rapid identification of Candida species by confocal Raman microspectroscopy. Journal of Clinical Microbiology. Retrieved from http://hdl.handle.net/1765/9833