Literature DB >> 25481069

Implementation of an FTIR spectral library of 486 filamentous fungi strains for rapid identification of molds.

A Lecellier1, V Gaydou1, J Mounier2, A Hermet2, L Castrec2, G Barbier2, W Ablain3, M Manfait1, D Toubas4, G D Sockalingum5.   

Abstract

Filamentous fungi may cause food and feed spoilage and produce harmful metabolites to human and animal health such as mycotoxins. Identification of fungi using conventional phenotypic methods is time-consuming and molecular methods are still quite expensive and require specific laboratory skills. In the last two decades, it has been shown that Fourier transform infrared (FTIR) spectroscopy was an efficient tool for microorganism identification. The aims of this study were to use a simple protocol for the identification of filamentous fungi using FTIR spectroscopy coupled with a partial least squares discriminant analysis (PLS-DA), to implement a procedure to validate the obtained results, and to assess the transferability of the method and database. FTIR spectra of 486 strains (43 genera and 140 species) were recorded. An IR spectral database built with 288 strains was used to identify 105 different strains. It was found that 99.17% and 92.3% of spectra derived from these strains were correctly assigned at the genus and species levels, respectively. The establishment of a score and a threshold permitted to validate 80.79% of the results obtained. A standardization function (SF) was also implemented and tested on FTIR data from another instrument on a different site and permitted to increase the percentage of well predicted spectra for this set from 72.15% to 89.13%. This study confirms the good performance of high throughput FTIR spectroscopy for fungal identification using a spectral library of molds of industrial relevance.
Copyright © 2014 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  FTIR spectroscopy; Filamentous fungi; Food industry; Identification; PLS-DA; Standardization function

Mesh:

Year:  2014        PMID: 25481069     DOI: 10.1016/j.fm.2014.01.002

Source DB:  PubMed          Journal:  Food Microbiol        ISSN: 0740-0020            Impact factor:   5.516


  6 in total

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Authors:  Lisa M T Lam; Philippe J Dufresne; Jean Longtin; Jacqueline Sedman; Ashraf A Ismail
Journal:  J Clin Microbiol       Date:  2019-04-26       Impact factor: 5.948

2.  Multicenter Evaluation of Attenuated Total Reflectance Fourier Transform Infrared (ATR-FTIR) Spectroscopy-Based Method for Rapid Identification of Clinically Relevant Yeasts.

Authors:  Lisa M T Lam; Ashraf A Ismail; Simon Lévesque; Simon F Dufresne; Mathew P Cheng; Émilie Vallières; Me-Linh Luong; Jacqueline Sedman; Philippe J Dufresne
Journal:  J Clin Microbiol       Date:  2021-10-20       Impact factor: 11.677

3.  Evidence of preserved collagen in an Early Jurassic sauropodomorph dinosaur revealed by synchrotron FTIR microspectroscopy.

Authors:  Yao-Chang Lee; Cheng-Cheng Chiang; Pei-Yu Huang; Chao-Yu Chung; Timothy D Huang; Chun-Chieh Wang; Ching-Iue Chen; Rong-Seng Chang; Cheng-Hao Liao; Robert R Reisz
Journal:  Nat Commun       Date:  2017-01-31       Impact factor: 14.919

4.  High-throughput screening of Mucoromycota fungi for production of low- and high-value lipids.

Authors:  Gergely Kosa; Boris Zimmermann; Achim Kohler; Dag Ekeberg; Nils Kristian Afseth; Jerome Mounier; Volha Shapaval
Journal:  Biotechnol Biofuels       Date:  2018-03-14       Impact factor: 6.040

5.  Microcultivation and FTIR spectroscopy-based screening revealed a nutrient-induced co-production of high-value metabolites in oleaginous Mucoromycota fungi.

Authors:  Simona Dzurendova; Boris Zimmermann; Achim Kohler; Valeria Tafintseva; Ondrej Slany; Milan Certik; Volha Shapaval
Journal:  PLoS One       Date:  2020-06-22       Impact factor: 3.240

6.  Potential of Near Infrared Spectroscopy as a Rapid Method to Discriminate OTA and Non-OTA-Producing Mould Species in a Dry-Cured Ham Model System.

Authors:  Eva Cebrián; Félix Núñez; Mar Rodríguez; Silvia Grassi; Alberto González-Mohino
Journal:  Toxins (Basel)       Date:  2021-09-03       Impact factor: 4.546

  6 in total

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