The incidence of fungal infections, in particular candidiasis and aspergillosis, has considerably increased during the last three decades. This is mainly due to advances in medical treatments and technologies. In high risk patients (e.g. in haematology or intensive care), the prognosis of invasive candidiasis is relatively poor. Therefore, a rapid and correct identification of the infectious agent is important for an efficient and prompt therapy. Most clinical laboratories rely on conventional identification methods that are based on morphological, physiological and nutritional characteristics. However, these have their limitations because they are time-consuming and not always very accurate. Moreover, molecular methods may be required to determine the genetic relationship between the infectious strains, for instance in Candida outbreaks. In addition, the latter methods require time, expensive consumables and highly trained staff to be performed adequately. In this study, we have applied the FTIR spectroscopic approach to different situations encountered in routine mycological diagnosis. We show the potentials of this phenotypic approach, used in parallel with routine identification methods, for the differentiation of 3 frequently encountered Candida species (C. albicans, C. glabrata and C. krusei) by using both suspensions and microcolonies. This approach, developed for an early discrimination, may help in the initial choice of antifungal treatment. Furthermore, we demonstrate the feasibility of the method for intraspecies comparison (typing) of 3 Candida species (C. albicans, C. glabrata and C. parapsilosis), particularly when an outbreak is suspected.
"Despite the fact that conventional/classical tests are largely applied, yet, these tests are faced with several constrains. Time consuming and low discriminative power between closely related species are the major constrains . Currently, genotypic methods are practically preferred than phenotypic methods. "
[Show abstract][Hide abstract] ABSTRACT: Rapid and accurate identification of yeast is increasingly important to stipulate the appropriate therapy thus reducing morbidity and mortality related to yeast infections. Vibrational spectroscopic techniques (infrared (IR) and Raman) could provide potential alternatives to conventional typing methods, because they constitute a rapid, inexpensive and highly specific spectroscopic fingerprint through-which microorganism can be identified. The present study evaluate (FTIR) spectroscopy as a sensitive and effective assay for the identification of the most frequent yeast species isolated from human and animals. One hundred and twenty-eight yeasts isolated from infected human mouths/vaginas, chronic diseased cows, crop mycosis in chicken and soil contaminated with pigeon droppings were phenotypically identified. Using universal primers, ITS1/ITS4, we have amplified ITS1-5.8S-ITS2 rDNA regions for 39 yeast isolates as representative samples. The PCR products were digested with restriction enzyme MspI and examined by PCR-RFLP, which was an efficient technique for identification of Candida spp., Cryptococcus neoformans and Trichosporon asahii. Further, identification of the same 39 isolates were done by FTIR spectroscopy and considered as reference for other strains by comparison of their FTIR spectra. The current study has sharply demonstrated the significant spectral differences between the various examined species of Candida, Cryptococcus, Trichosporon, Rhodotorula and Geotrichum isolated from different sources. Decisively, our research has confirmed that FTIR spectroscopy is a promising diagnostic tool, because of its sensitivity, rapidity, high differentiation capacity and simplicity compared to conventional/molecular techniques.
"Eng., 28(4), 398-409, Dec. 2012 404 diferenciar os três espectros. Esse resultado demonstra que, mesmo nos casos em que os espectros de diferentes micro-organismos apresentem o mesmo aspecto visual, a análise estatística multivariada pode ser potencialmente útil para diferenciar os espectros desses micro-organismos (Essendoubi et al., 2005; Naumann, 2000; Timmins et al., 1998; Tintelnot et al., 2000; Toubas et al., 2007). "
[Show abstract][Hide abstract] ABSTRACT: Films of Candida albicans, Candida dubliniensis and Candida parapsilosis were prepared and the infrared spectra of these films were obtained in the region 4000 to 1000 cm1, with resolution of 4 cm1, in the transmission mode, at 20 ºC. Fifty four spectra were obtained, 18 of each microorganism, with the PerkinElmer Spotlight 400 FT-IR, which has a microscope attached to a FT-IR spectrophotometer. The spectra were analyzed through three methods: (1) mere visual inspection; (2) multivariate statistical analysis; (3) curve-fitting for determining secondary structures of proteins. In the region 1200 to 1000 cm1, the spectral bands show differences that can be seen by a mere visual inspection. On the other hand, the amide I bands, in the region 1710 to 1590 cm1, have the same visual aspect for the three microorganisms. Multivariate statistical analysis was applied to analyze these amide I bands of all the 54 spectra. Principal component analysis (PCA) and techniques of hierarchical cluster analysis (HCA, Hierarchical Clustering Analysis) according to Ward's method were applied using the software MINITAB 15. The results show a clear discrimination of the three microorganisms. The average spectrum of each microorganism was obtained in the amide I band. Each average spectrum was analyzed by curve-fitting for the determination of secondary structures of proteins. The software used was the ORIGIN 7.5 and the results confirm the discrimination obtained through multivariate statistical analysis. This result shows that multivariate statistical analysis can be useful to discriminate infrared spectra of different microorganisms. Furthermore, this work shows that the amide I bands of the infrared spectra of Candida albicans, Candida dubliniensis, and Candida parapsilosis provide a set of data of known group structure that can be useful to test statistical algorithms of cluster analysis.
Revista Brasileira de Engenharia Biomedica 12/2012; 28(4):398-409. DOI:10.4322/rbeb.2012.037
"Fungi, which include filamentous fungi and yeasts, are very important organisms. They are employed in the production of pharmaceuticals, enzymes, organic acids and food, and some of them are associated with several diseases affecting humans and other animals        . The earliest system for fungal species classification relied on morphological characters, mainly those of reproductive structures. "
[Show abstract][Hide abstract] ABSTRACT: Fourier transform infrared is considered a powerful technique for characterizing chemical compositions of complex probes such as microorganisms. It has successfully been applied to fungal identification. In this paper, the current state of identification and characterization of filamentous fungi and yeasts by Fourier transform infrared is reviewed.
Research in Microbiology 03/2010; 161(2):168-75. DOI:10.1016/j.resmic.2009.12.007 · 2.71 Impact Factor
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