Author(s):
Silva, Sónia Carina ; Tobaldini-Valerio, Flávia ; Costa-de-Oliveira, Sofia ; Henriques, Mariana ; Azeredo, Joana ; Ferreira, Eugénio C. ; Lopes, João Almeida ; Sousa, C.
Date: 2016
Persistent ID: http://hdl.handle.net/1822/42696
Origin: RepositóriUM - Universidade do Minho
Project/scholarship:
info:eu-repo/grantAgreement/FCT/5876/147218/PT;
info:eu-repo/grantAgreement/FCT/5876/147337/PT;
info:eu-repo/grantAgreement/FCT/5876-PPCDTI/126270/PT
;
info:eu-repo/grantAgreement/FCT/COMPETE/126270/PT;
Subject(s): Science & Technology
Description
Accurate Candida species identification remains a challenge due to their phenotypic and genotypic similarity. Species belonging to the *psilosis group, are even described as phenotypically indistinguishable. Also, most of the genotypic methods commonly used to discriminate these species are laborious and very expensive. In this work we developed a Fourier-transform infrared spectroscopy with attenuated total reflectance (FTIR-ATR) based method as a reliable alternative for the discrimination between 12 Candida species. The collection comprises 82 clinical isolates obtained from distinct biological products, recovered between 2007 and 2014 in Portugal and Brazil and previously characterised by CHROMagar Candida and PCR-based sequencing techniques. Infrared spectra were analysed with principal component analysis (PCA) and partial least squares discriminant analysis (PLSDA). Results demonstrated that the 12 species could be successfully discriminated by the proposed infrared spectroscopy based method. Noteworthy, the PLSDA model led to the correct identification of 99.6% analysed clinical isolates. This rapid, low cost, and environmental friendly technique proved to be a reliable alternative for the identification of Candida species that share many phenotypic and genotypic characteristics and are often difficult to distinguish.
This work was funded by Fundação para a Ciência e a Tecnologia (FCT) under the strategic projects UID/QUI/50006/2013 and UID/BIO/04469/2013 and COMPETE 2020 (POCI-01-0145-FEDER-006684) and the project RECI/BBB-EBI/0179/2012 (FCOMP-01-0124-FEDER-027462). Sónia Silva was supported by a post-doctoral grant from Fundação para a Ciência e a Tecnologia (SFRH/BPD/111645/2015).
