Attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy is a spectrum-based technique that quantifies the absorption of infrared light by molecules present in the microbial cell. The aim of the present study was to evaluate the performance of the ATR-FTIR spectroscopic technique via I-dOne software (Version 2.0) compared with the MALDI-TOF MS in identifying Candida spp. Each infrared spectrum was compared with spectra stored in the software database. The updated version of the I-dOne software was used to analyze ATR-FTIR spectra. All Candida isolates 284/284 (100%) were classified correctly according to the genus. Overall species identification yielded 272/284 (95.8%) concordant identification results with MALDI-TOF MS. Additionally, all 79 isolates belonging to the Candida parapsilosis species complex were identified correctly to the species level with the updated version of the I-dOne software. Only 12 (4.2%) isolates were misidentified at the species level. The present study highlights the potential diagnostic performance of the I-dOne software with ATR-FTIR spectroscopic technique referral spectral database as a real alternative for routine identification of the most frequently isolated Candida spp.
Rapid Identification of Clinically Relevant Candida spp. by I-dOne Software Using Attenuated Total Reflectance Fourier Transform Infrared (ATR-FTIR) Spectroscopy
Franconi, Iacopo;Fais, Roberta;Giordano, Cesira;Tuvo, Benedetta;Tavanti, Arianna;Barnini, Simona;Lupetti, Antonella
2025-01-01
Abstract
Attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy is a spectrum-based technique that quantifies the absorption of infrared light by molecules present in the microbial cell. The aim of the present study was to evaluate the performance of the ATR-FTIR spectroscopic technique via I-dOne software (Version 2.0) compared with the MALDI-TOF MS in identifying Candida spp. Each infrared spectrum was compared with spectra stored in the software database. The updated version of the I-dOne software was used to analyze ATR-FTIR spectra. All Candida isolates 284/284 (100%) were classified correctly according to the genus. Overall species identification yielded 272/284 (95.8%) concordant identification results with MALDI-TOF MS. Additionally, all 79 isolates belonging to the Candida parapsilosis species complex were identified correctly to the species level with the updated version of the I-dOne software. Only 12 (4.2%) isolates were misidentified at the species level. The present study highlights the potential diagnostic performance of the I-dOne software with ATR-FTIR spectroscopic technique referral spectral database as a real alternative for routine identification of the most frequently isolated Candida spp.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
