The multivariate statistical selection of fungal strains isolated from Neoteredo reynei, with the high hydrolytic potential to deconstruct cellulose.

Clicks: 248
ID: 1915
2019
The aim of this study was to select isolated filamentous fungi, naturally occurring in the digestive tract of Neoteredo reynei, with high potential to hydrolyze cellulolytic biomass. The selection of the fungi strains, which produce cellulases, was performed by adding carboxymethylcellulose (CMC), microcrystalline cellulose (MCC) or glucose in the media containing peptone and yeast-extract. In this case, the glucose was used as a reference standard for the growth of the mycelia. The abilities of the fungal strains, to hydrolyze cellulose, on the solid media (MCC or CMC), were evaluated. Two methods were used: the congo-red and the speed of mycelial growth. The measurements of the diameters were performed at 24 h intervals, and the speed of the mycelial growth was calculated after 72 h of cultivation. The molecular and morphological identification of the fungi were applied to the isolated strains. Statistical analysis, including ANOVA and Tukey test, and multivariate analysis were applied as tools to select the strains. Twelve strains were isolated and the results of the identification were 2 strains of Hypocrea lutea, 2 strains of Trichoderma reesei, 2 strains of Aspergillus niger; 2 genera of Aspergillus sp., 2 genera of Trichoderma sp., 1 genus of Fusarium sp. and 1 genus of Gliocadium sp. The discrimination analysis methods such as HCA (Hierarchical Cluster Analysis) and PCA (Principal Component Analysis) indicated three strains with the highest potential to hydrolyze cellulose. In this study, the selection strategy was successful, resulting in the classification of strains from the genera Trichoderma and Hypocrea. This is the first time that this kind of studying was applied to select the potential of the cellulolytic fungal strains, isolated from N. reynei, using the methods of the growth of the mycelial diameter and the statistical discrimination.
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Authors Ferreira, Nelson Rosa;de Moura Sarquis, Maria Inez;Gobira, Rubens Menezes;da Silva Souza, Márcia Gleice;Santos, Alberdan Silva;
Journal food research international (ottawa, ont)
Year 2019
DOI S0963-9969(19)30244-3
URL
Keywords Keywords not found

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