Fungal Secondary Metabolism and in silico Analyses: the Role of Bioinformatics in the Prediction of Biosynthetic Gene Clusters
DOI:
https://doi.org/10.22481/exon.v14i1.20528Keywords:
biosynthetic gene clusters, secondary metabolism, filamentous fungi, AntiSMASH, bioinformaticsAbstract
Secondary metabolism provides non-essential products for organisms. Besides playing an important role in ecological relationships, they may have an appealing biotechnological potential. Among the most studied microorganisms are fungi, which are known to synthesize a plethora of secondary metabolites. In order to produce these compounds, the activity of biosynthetic gene clusters (BGCs) is often necessary. The recent advance of DNA sequencing technologies has rendered the use of genomic data more accessible. Therefore, the use of in silico methodologies allows the inference of natural compound production. In this study we exemplify the prediction of secondary metabolism BGCs from the genome of the fungus Penicillium echinulatum, making use of the antiSMASH tool. The most abundant families of secondary metabolites found for P. echinulatum included synthetic clusters of terpenes, non-ribosomal peptides (NRPs) and clusters similar to NRPs. In addition, the approach allowed for the identification of 26 BGCs for P. echinulatum, from which clavaric acid, naphthopyrone, nidulanin A, oxaleimide C, and phyllostictine A are highlighted. In this sense, it is possible to observe that bioinformatics tools are fundamental in the identification of organisms that produce compounds of interest, since they optimize processes and reduce costs.
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