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

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.

Differentiation and identification of filamentous fungi by high-throughput FTIR spectroscopic analysis of mycelia.

Routine identification of fungi based on phenotypic and genotypic methods can be fastidious and time-consuming. In this context, there is a constant need for new approaches allowing the rapid identification of molds. Fourier-transform infrared (FTIR) spectroscopy appears as such an indicated method. The objective of this work was to evaluate the potential of FTIR spectroscopy for an early differentiation and identification of filamentous fungi. One hundred and thirty-one strains identified using DNA sequencing, were analyzed using FTIR spectroscopy of the mycelia obtained after a reduced culture time of 48 h compared to current conventional methods. Partial least square discriminant analysis was used as a chemometric method to analyze the spectral data and for identification of the fungal strains from the phylum to the species level. Calibration models were constructed using 106 strains pertaining to 14 different genera and 32 species and were used to identify 25 fungal strains in a blind manner. Identification levels of 98.97% and 98.77% achieved were correctly assigned to the genus and species levels respectively. FTIR spectroscopy with its high discriminating power and rapidity therefore shows strong promise for routine fungal identification. Upgrading of our database is ongoing to test the technique's robustness.

Study of jojoba oil aging by FTIR.

As the jojoba oil was used in cosmetic, pharmaceutical, dietetic food, animal feeding, lubrication, polishing and bio-diesel fields, it was important to study its aging at high temperature by oxidative process. In this work a FT-MIR methodology was developed for monitoring accelerate oxidative degradation of jojoba oils. Principal component analysis (PCA) was used to differentiate various samples according to their origin and obtaining process, and to differentiate oxidative conditions applied on oils. Two spectroscopic indices were calculated to report simply the oxidation phenomenon. Results were confirmed and deepened by multivariate curve resolution-alternative least square method (MCR-ALS). It allowed identifying chemical species produced or degraded during the thermal treatment according to a SIMPLISMA pretreatment.