Quantitative analysis of total mycotoxins in metabolic extracts of four strains of Bipolaris sorokiniana (Helminthosporium sativum)

Metabolomic approaches for the determination of metabolites from pathogenic microorganisms: A review

Metabolomics is a high precision analytical approach to obtaining detailed information of varieties of metabolites produced in biological systems, including foods. This study reviews the use of metabolomic approaches such as liquid chromatography mass spectrometry (LCMS), gas chromatography mass spectrometry (GC-MS), matrix assisted laser desorption /ionization tandem time of flight mass spectrometry (MALDI-TOF-MS) and nuclear magnetic resonance (NMR) for investigating the presence of foodborne pathogens and their metabolites. Pathogenic fungi and their notable metabolites (mycotoxins) have been studied more extensively using metabolomics as compared to bacteria, necessitating further studies in this regard. Nevertheless, such identified fungal and bacteria metabolites could be used as biomarkers for a more rapid detection of these pathogens in food. Other important compounds detected through metabolomics could also be correlated to functionality of these pathogenic strains, determined by the composition of the foods in which they exist, thereby providing insights into their metabolism. Considering the prevalence of these food pathogens, metabolomics still has potentials in the determination of food-borne pathogenic microorganisms especially for the determination of pathogenic bacteria toxins and is expected to generate research interests for further studies and applications.

Advancements in IR spectroscopic approaches for the determination of fungal derived contaminations in food crops

Infrared spectroscopy is a rapid, nondestructive analytical technique that can be applied to the authentication and characterization of food samples in high throughput. In particular, near infrared spectroscopy is commonly utilized in the food quality control industry to monitor the physical attributes of numerous cereal grains for protein, carbohydrate, and lipid content. IR-based methods require little sample preparation, labor, or technical competence if multivariate data mining techniques are implemented; however, they do require extensive calibration. Economically important crops are infected by fungi that can severely reduce crop yields and quality and, in addition, produce mycotoxins. Owing to the health risks associated with mycotoxins in the food chain, regulatory limits have been set by both national and international institutions for specific mycotoxins and mycotoxin classes. This article discusses the progress and potential of IR-based methods as an alternative to existing chemical methods for the determination of fungal contamination in crops, as well as emerging spectroscopic methods.

Potential of Fourier transform infrared spectroscopy (FT-IR) to differentiate environmental Aspergillus fungi species A. niger, A. ochraceus, and A. westerdijkiae using two different methodologies

We assessed the ability of Fourier transform infrared spectroscopy (FT-IR) to differentiate three important and morphologically similar Aspergillus species: A. ochraceus and A. westerdijkiae, and A. niger. Fungi were processed by two methods, powdered mycelia and conidiospore-saline solution, and then recorded in a spectrometer. Second derivatives with nine points of smoothing were applied as spectra data pretreatment. Partial least squares regression was used for the species comparison models and a prediction test was used to evaluate the models. The powdered-mycelia methodology correctly identified 100% of the prediction test set to discriminate A. niger from A. ochraceus and A. westerdijkiae; in addition, it had a 86.6% success rate in discriminating A. ochraceus and A. westerdijkiae. This is the first time a study assessed the ability of FT-IR to differentiate A. niger, A. ochraceus, and A. westerdijkiae, and we believe this technique is very promising for classifying and distinguish fungi isolates.

Rapid strain classification and taxa delimitation within the edible mushroom genus Pleurotus through the use of diffuse reflectance infrared Fourier transform (DRIFT) spectroscopy

Fourier transform infrared (FT-IR) spectroscopy has been successfully applied for the identification of bacteria and yeasts, but only to a limited extent for discriminating specific groups of filamentous fungi. In the frame of this study, 73 strains - from different associated hosts/substrates and geographic regions - representing 16 taxa of the edible mushroom genus Pleurotus (Basidiomycota, Agaricales) were examined through the use of diffuse reflectance infrared Fourier transform (DRIFT) spectroscopy. A binary matrix, elaborated on the basis of presence/absence of specific absorbance peaks combined with cluster analysis, demonstrated that the spectral region 1800-600 cm(-1) permitted clear delimitation of individual strains into Pleurotus species. In addition, closely related species (e.g., Pleurotus ostreatus and Pleurotus pulmonarius) or taxa of the subgenus Coremiopleurotus demonstrated high similarity in their absorbance patterns, whereas genetically distinct entities such as Pleurotus dryinus, Pleurotus djamor, and Pleurotus eryngii provided spectra with noteworthy differences. When specific regions (1800-1700, 1360-1285, 1125-1068, and 950-650 cm(-1)) were evaluated in respect to the absorbance values demonstrated by individual strains, it was evidenced that this methodology could be eventually exploited for the identification of unknown Pleurotus specimens with a stepwise process and with the aid of a dichotomous key developed for this purpose. Moreover, it was shown that the nature of original fungal material examined (mycelium, basidiomata, and basidiospores) had an effect on the outcome of such analyses, and so did the use of different mycelium growth substrates. In conclusion, application of FT-IR spectroscopy provided a fast, reliable, and cost-efficient solution for the classification of pure cultures from closely related mushroom species.