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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.

1. Introduction

Over the past few decades, the epidemiology of fungal infections has substantially changed as the proportion of the population at risk has increased [1,2,3,4]. In fact, the prevalence and incidence of nosocomial and healthcare-associated fungal infections, mainly due to Candida spp. and Aspergillus spp., have witnessed an outstanding rise [1,2,3].
Invasive Candida spp. infections affect over 250,000 immunocompromised patients per year worldwide and are responsible for over 50,000 deaths [5,6]. Among healthcare-associated bloodstream infections, candidemia is the fourth most common cause [2,5,7]. The impact of such detrimental opportunistic infections bears dramatic consequences for both patients and the healthcare economy. Indeed, the mortality rate due to Candida infections ranged from 35% to 64% [5,6,8], and hospitalization cost was estimated to be around USD 1.4 billion in 2017 in the USA [9].
By looking at species distribution, Candida albicans remains the most frequently isolated fungal pathogen from blood cultures [10]. Non-albicans Candida species distribution differs greatly from one country to another [11,12]. According to recent reports, Candida glabrata was the second most frequently isolated Candida species from blood cultures in Canada and North America [13,14]. In particular, the prevalence of C. glabrata causing candidemia in the USA increased from 12% in 1992–1993 to 27% in the late 2000s [15]. Clinical surveys from several countries in Southern Europe reported Candida parapsilosis as the second most frequently isolated Candida species from blood cultures and in certain scenarios even the first [8,16,17,18,19]. Correlated to the increase in the prevalence and incidence of non-albicans Candida species among bloodstream infections, researchers have highlighted that drug resistance rates are also increasing over time as they represent the focus of current clinical research efforts [20,21,22,23].
First-line laboratory approach to differentiate Candida species could involve the use of chromogenic media. However, considering that the phenotypic characteristics of different Candida species might be similar, this phenotypic test can only help microbiologists in presumptive species identification, and it is therefore mandatory to confirm the first diagnostic hypothesis with a second molecular approach [24]. To this point, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has been extensively used in routine diagnosis [25]. MALDI-TOF MS can also be performed directly on blood cultures that tested positive for yeast after Gram staining [26], yielding results in a few minutes [27].
A new approach in microbial identification is Fourier transform infrared (FTIR) spectroscopy [28]. This is a spectrum-based technique, first introduced in the 1950s, that, within its wide spectrum of applications, can quantify the absorption of infrared light by molecules present in the microbial cell. The generated IR spectrum provides a specific fingerprint that reflects the cell composition of nucleic acids, proteins, lipids, and carbohydrates [28,29]. Each microorganism has a highly specific infrared absorption chemical signature correlated with genetic information, thus allowing for the identification of the microbial species [30]. The attenuated total reflection (ATR) technique is the most frequently used to investigate the chemical composition of intact microorganisms from a monomicrobial culture grown on solid media [29]. In the ATR method, the IR beam is directed toward an ATR crystal at a defined angle, whereby the total internal reflection occurs within the crystal. Under these conditions, an evanescent wave extends beyond the surface of the ATR crystal only a few microns (0.5–5 mm). The interaction of the evanescent wave with the intact microbial cells previously deposited on the ATR crystal results in the partial attenuation of the total internally reflected IR beam at the wavelengths at which the sample absorbs the IR energy [31]. The attenuated evanescent wave passes back to the IR beam, which exits the opposite end of the crystal to reach the detector in the IR spectrometer. The generated infrared spectrum enables microbial identification. Promising results, using ATR-FTIR spectroscopy, were reported for both bacterial and yeast identification and showed the potential for the discrimination of antibiotic- and antifungal-resistant strains [32,33,34,35].
The aim of the present study was to evaluate the performance of the I-dOne software (Alifax, Polverara (PD)—Italy) for the classification of ATR-FTIR spectra leading to the identification of clinical yeast isolates in comparison with MALDI-TOF MS, the method currently used in our laboratory.
Furthermore, a prototype version of the I-dOne software (Research Use Only, RUO) was used to evaluate the method’s capability to correctly classify the members of the Candida parapsilosis complex at the species level.

2. Materials and Methods

2.1. Study Design and Settings

This is a prospective methodological study conducted from January 2021 to December 2023, at Pisa University Hospital, a tertiary-level care center hosting over 1108 beds and nearly 50,000 admissions per year in 2021. Our clinical epidemiology regarding invasive fungal infections and species distribution has been described elsewhere [18,35]. Isolates were subcultured at 37 °C for 24 h on Sabouraud agar (Biomérieux, Craponne, France). The routine identification of isolated yeast colonies was performed by MALDI-TOF MS (Bruker Corporation, Billerica, MA, USA). In parallel, yeast grown on solid media were spotted onto the ATR crystal for identification by FTIR spectroscopy and interpretation by I-dOne software. All the 284 isolates included in this study were first analyzed with MALDI-TOF and then reassessed with ATR-FTIR using the I-dOne software.

2.2. Yeasts

Yeast isolates were collected at Pisa University Hospital, Mycology Unit, and from the yeast collection of the Department of Biology, University of Pisa, where isolates were kept frozen at −80 °C in brain heart broth with 10% glycerol. For ATR-FTIR spectroscopy, yeast colonies were cultured on solid Tryptic Soy Agar, Sabouraud–gentamycin–chloramphenicol agar, chromID CPSE agar, and Oxoid Chromogenic Candida Agar (Biomérieux) at 37 °C for 24–48 h depending on the species.

2.3. Sample Preparation for ATR-FTIR Spectroscopy

For ATR-FTIR spectroscopy, the spectral acquisition protocol involved background spectrum acquisition prior to the preparation of each sample, in order to compensate for the fluctuation of environmental humidity. Then, a single yeast colony was isolated using a sterile disposable loop and deposited directly onto the ATR crystal sampling surface of the ATR-FTIR spectrometer for the analysis. After sample deposition, a short time was necessary to permit the evaporation of moisture residues from the sample. The sample’s drying was automatically evaluated by the software, and this was necessary to avoid elevated IR absorption by water in the protein region of the infrared spectra. In addition, using the appropriate incorporated sample press, external extra pressure was applied for yeast colonies to ensure good contact between microbial cells and the ATR crystal. After the spectral acquisition, the ATR sampling surface was cleaned with 70% ethanol according to the manufacturer’s instructions in order to remove the organic components of the previously analyzed yeast. The variability in the IR analysis of microorganisms among the yeast spectra belonging to the same species had to be less than the one between the spectra of yeasts from different species. Spectral reproducibility depends mostly on rigorous control of sampling and measurement conditions: the composition of the growth medium and the phase of growth are crucial, as relative peak intensities may be more affected than peak positions, since metabolite production may change over different growth phases according to the available nutrients [36,37]. Spectral acquisition time was approximately 60 s, and the automated spectral processing and the identification of the isolate were completed in another 30 s. The identification process required from 1 to 3 replicates for each sample.

2.4. ATR-FTIR Spectral Acquisition

All spectra ranging between wave numbers 4000 and 400 cm−1 were recorded with an ATR-FTIR spectrometer (Agilent, Santa Clara, CA, USA). The spectral acquisition was reagent-free, and only isopropanol was required as reference spectra and ethanol 70% for the cleaning of the ATR crystal. For data processing, the I-dOne software (version 2.0) was used for the microbiological classification of yeast species. For the subclassification of the Candida parapsilosis complex into each separate species, a custom-developed RUO version of the I-dOne algorithm was used.

2.5. Data Processing

To compare the spectra of the different Candida species, spectra were classified by using a hierarchical classification algorithm, which is capable of classifying the unknown microorganism in progressive subgroups until the final species classification. During this cyclic classification process, all the microbial features (proteins, lipids, carbohydrates, and nucleic acids) are used to distinguish between different groups. The data analysis protocol is fully covered by patent [38]; hence, more in-depth details are not discussed.

3. Results

Identification of Clinical Yeasts by ATR-FTIR Spectroscopy

All 284 isolates were identified at MALDI-TOF analyses, and identification was performed in technical duplicates. The total number of Candida species used in the present study was 284. Of these, 139 (48.9%) were C. albicans, 66 (23.2%) were Candida parapsilosis species complex (47 Candida parapsilosis, 10 Candida metapsilosis, and 9 Candida orthopsilosis); 50 (17.6%) were Candida glabrata, 20 (7%) were Candida tropicalis, and 9 (3.2%) were Candida krusei. The ATR-FTIR spectral reference database initially contained the spectra of isolates belonging to the five most relevant Candida species: C. albicans, C. glabrata, C. parapsilosis species complex, C. tropicalis, and C. krusei. Next, an updated Research Use Only version of the I-dOne software was used to perform spectra analysis on the Candida parapsilosis species complex.
Identification performed by I-dOne software with the ATR-FTIR spectral reference database yielded 284 (100%) out of 284 concordant genus identification results. On a species level, 272 (95.8%) out of the 284 isolates showed concordant identification results with those obtained by MALDI-TOF MS. Identification results by the I-dOne software performed on the ATR-FTIR spectral reference database revealed that 2 (0.7%) out of the 284 yeast isolates were reported as “Candida species”. All these (100%) were identified by MALDI-TOF MS as Candida albicans. In addition, 12 (4.2%) out of 284 isolates were not concordantly identified at the species level by the I-dOne software in comparison to MALDI-TOF (Table 1).
Concordance rates between the I-dOne software and MALDI-ToF MS analysis for the most frequently isolated Candida species were the following: 132 (95%) out of 139 C. albicans, 49 (98%) out of 50 C. glabrata, 47 (100%) out of 47 C. parapsilosis, 9 (100%) out of 9 C. orthopsilosis, 10 (100%) out of 10 C. metapsilosis, 9 (100%) out of 9 C. krusei, and 16 (80%) out of 20 C. tropicalis.
In 12 (4.2%) out of the 284 isolates, species were not concordantly identified between the I-dOne software and MALDI-TOF MS. Non-concordant identification results were the following: five C. albicans were identified as three C. parapsilosis species complex and two C. glabrata; one C. glabrata was identified as C. krusei; and four C. tropicalis were identified as two C. albicans and two C. glabrata. Data regarding not concordantly identified Candida isolates are shown in Table 1.

4. Discussion

The present study settled and then evaluated the diagnostic performance of the I-dOne software (Alifax, Polverara (PD)—Italy) with the ATR-FTIR spectroscopic technique regarding the identification of the most frequent yeast isolates encountered in clinical microbiology, in comparison to MALDI-TOF MS (Bruker Corporation, Billerica, MA, USA), which is the currently used method in our laboratory.
All the analyzed yeast isolates were concordantly identified by MALDI-TOF at the genus level, and 92.2% were identified at the species level. The time required for the analysis of each isolate was 90 s. Twelve isolates were not concordantly identified at the species level. Implementations done in the software upgrade and in the referral spectral library allowed for further species identification and discrimination within the C. parapsilosis species complex. This is a drawback of this molecular diagnostic technique hindering its clinical application up to this point. However, with these promising results, it is reasonable to believe that past issues with species identification within the C. parapsilosis species complex could be overcome as the I-dOne RUO software (Alifax) with the ATR-FTIR spectroscopic technique referral spectral database was able to concordantly identify all C. parapsilosis complex isolates: 100% C. parapsilosis, 100% C. metapsilosis, and 100% C. orthopsilosis.
Our results should, however, be interpreted with caution. The monocentric nature of the study and the research focus limited on the most commonly isolated yeast species in clinical practice available are all study limitations. In addition, it would be of the utmost importance to expand the analysis to Candida auris; therefore, the aim of future studies will be to pursue this goal. Conversely, the prospective nature of the study and the amplitude of the number of isolates analyzed, as well as the software implementation and upgrade delivering new insights on species identification within the C. parapsilosis species complex, are all points of strength.
Surprisingly, despite the relatively low rate of non-concordant species identification (3.9%), when we compared our results with major studies such as those reported by Lam et al. [36], our overall species non-concordant identification rate was higher (3.9% vs. 0%). In previous studies reported by the same authors, the non-concordant identification rate was still lower (0.9%) than the one reported in our study [31]. However, both aforementioned studies used an optimized algorithm, specifically for Sabouraud agar.
Based on the results presented in this study, it can be stated that the I-dOne software (Alifax) with the ATR-FTIR spectroscopic technique referral spectral database could be a reliable alternative to MALDI-TOF MS analysis for the molecular identification of Candida spp. in a clinical laboratory routine workflow. Nevertheless, these results should be further investigated with other studies comparing ATR-FTIR with current clinical reference standards on yeast identification and speciation from other working groups.

5. Conclusions

The I-dOne software with ATR-FTIR was found to be a potential real alternative for routine molecular biology and biochemical analysis for the rapid microbial identification of yeast isolates in a clinical laboratory, as it is fast and easy to perform. Nevertheless, confirmatory studies and investigation regarding diagnostic performance on less frequently isolated yeast species should be the aim of future studies.

Author Contributions

Conceptualization, A.L. and S.B.; methodology, R.F., C.G. and I.F.; software, C.S.; validation, R.F., C.G. and B.T.; formal analysis, R.F.; investigation, R.F.; data curation, I.F.; writing—original draft preparation, I.F.; writing—review and editing, A.L. and A.T.; visualization, I.F.; supervision, A.L. and A.T.; project administration, A.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

This study was notified (Prot. n. 32634) to the local ethical committee, Comitato Etico di Area Vasta Nord-Ovest, University of Pisa, and conducted in full accordance with the principles of the Declaration of Helsinki. Samples were taken as part of the standard patient care and anonymized by the clinical personnel. Research personnel received and used these samples anonymously.

Informed Consent Statement

Patient consent was waived as yeast were collected from waste material after disposal; therefore, patients’ ID and personal info could not be retrieved as only isolates were selected.

Data Availability Statement

All necessary data required to evaluate the conclusions of this study are reported in the tables in the main text.

Acknowledgments

We thank Elena Mitri (Alifax), Stefano Ceschia (Alifax), and Gianpiero Spezzotti (Alifax) for their technical support.

Conflicts of Interest

Iacopo Franconi, Arianna Tavanti, Simona Barnini, Benedetta Tuvo, Chiaramaria Stani, and Antonella Lupetti have no financial or personal relationship with other people or organizations to disclose. Roberta Fais and Cesira Giordano received funding from Alifax to perform I-dOne software validation.

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Table 1. Identification of 284 Candida spp. isolates by I-dOne software with ATR-FTIR spectroscopy.
Table 1. Identification of 284 Candida spp. isolates by I-dOne software with ATR-FTIR spectroscopy.
Candida SpeciesConcordant Results *Non-Concordant Identification at the Species LevelConcordant Identification at the Genus LevelTotal Isolates
N%N%N%N %
Candida albicans13295.0%5 a3.6%21.4%139100.0%
Candida glabrata4998.0%1 b2.0% 0.0%50100.0%
Candida krusei9100.0% 0.0% 0.0%9100.0%
Candida metapsilosis10100.0% 0.0% 0.0%10100.0%
Candida orthopsilosis9100.0% 0.0% 0.0%9100.0%
Candida parapsilosis47100.0% 0.0% 0.0%47100.0%
Candida tropicalis1680.0%4 c20.0% 0.0%20100.0%
Overall27295.8%103.5%20.7%284100.0%
* Using the results from the currently used method (MALDI-TOF) in our laboratory as reference. Species identified as follows: a. 2 C. glabrata; 3 C. parapsilosis complex; b. C. krusei; c. 2 C. albicans; 2 C. glabrata.
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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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