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Brief Report

Rapid Identification of Clinically Relevant Candida spp. by I-dOne Software Using Attenuated Total Reflectance Fourier Transform Infrared (ATR-FTIR) Spectroscopy

by
Iacopo Franconi
1,†,
Roberta Fais
1,†,‡,
Cesira Giordano
2,
Benedetta Tuvo
1,
Chiaramaria Stani
3,
Arianna Tavanti
4,
Simona Barnini
2 and
Antonella Lupetti
1,*
1
Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Via San Zeno 37-39, 56127 Pisa, Italy
2
SD Microbiology Bacteriology, Azienda Ospedaliero-Universitaria Pisana, 56126 Pisa, Italy
3
Elettra Sincrotrone Trieste S.C.p.A., 34149 Trieste, Italy
4
Department of Biology, University of Pisa, 56127 Pisa, Italy
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
‡
Current address: UOC Chemical-Clinical Analyses Laboratory, Ospedale San Luca, USL North-West Tuscany, 55100 Lucca, Italy.
J. Fungi 2025, 11(1), 40; https://doi.org/10.3390/jof11010040
Submission received: 5 December 2024 / Revised: 31 December 2024 / Accepted: 3 January 2025 / Published: 7 January 2025
(This article belongs to the Special Issue Diagnosis of Invasive Fungal Diseases, 2nd Edition)
Versions Notes

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.
Keywords: ATR-FTIR spectroscopy; Candida spp.; I-dOne software; Candida spp. identification ATR-FTIR spectroscopy; Candida spp.; I-dOne software; Candida spp. identification

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MDPI and ACS Style

Franconi, I.; Fais, R.; Giordano, C.; Tuvo, B.; Stani, C.; Tavanti, A.; Barnini, S.; Lupetti, A. Rapid Identification of Clinically Relevant Candida spp. by I-dOne Software Using Attenuated Total Reflectance Fourier Transform Infrared (ATR-FTIR) Spectroscopy. J. Fungi 2025, 11, 40. https://doi.org/10.3390/jof11010040

AMA Style

Franconi I, Fais R, Giordano C, Tuvo B, Stani C, Tavanti A, Barnini S, Lupetti A. Rapid Identification of Clinically Relevant Candida spp. by I-dOne Software Using Attenuated Total Reflectance Fourier Transform Infrared (ATR-FTIR) Spectroscopy. Journal of Fungi. 2025; 11(1):40. https://doi.org/10.3390/jof11010040

Chicago/Turabian Style

Franconi, Iacopo, Roberta Fais, Cesira Giordano, Benedetta Tuvo, Chiaramaria Stani, Arianna Tavanti, Simona Barnini, and Antonella Lupetti. 2025. "Rapid Identification of Clinically Relevant Candida spp. by I-dOne Software Using Attenuated Total Reflectance Fourier Transform Infrared (ATR-FTIR) Spectroscopy" Journal of Fungi 11, no. 1: 40. https://doi.org/10.3390/jof11010040

APA Style

Franconi, I., Fais, R., Giordano, C., Tuvo, B., Stani, C., Tavanti, A., Barnini, S., & Lupetti, A. (2025). Rapid Identification of Clinically Relevant Candida spp. by I-dOne Software Using Attenuated Total Reflectance Fourier Transform Infrared (ATR-FTIR) Spectroscopy. Journal of Fungi, 11(1), 40. https://doi.org/10.3390/jof11010040

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