RESUMEN
BACKGROUND: The objective of this study is to establish Raman signatures from pure cultures of different Candida species using Raman Spectroscopy (RS) and use these signatures for rapid identification of unknown Candida species. METHODS: Pure cultures of five Candida species were evaluated using RS to build a limited signature library. 'Raman Processing' (RP) software was used for Principal Component Analysis (PCA) and Differential Functional Analysis (DFA). RESULTS: Eleven principal components described at least 95% variance in the spectra. Raman signatures from these known Candida species were able to identify the species of unknown Candida cultures with 100% accuracy. CONCLUSION: Raman spectroscopy can improve early identification of Candida species and may facilitate early optimal antifungal therapy.