Dataset Information

Effect of Monocerin, a Fungal Secondary Metabolite, on Endothelial Cells.

ABSTRACT: This study reports the isolation and identification of the endophytic fungus Exserohilum rostratum through molecular and morphological analysis using optical and transmission electron microscopy (TEM), as well as the procurement of its secondary metabolite monocerin, an isocoumarin derivative. Considering the previously observed biological activities of monocerin, this study was performed on human umbilical vein endothelial cells (HUVECs) that are widely used as an in vitro model for several different purposes. Important parameters, such as cell viability, senescence-associated β-galactosidase, cellular proliferation by using 5(6)-carboxyfluorescein diacetate N-succinimidyl ester (CFSE), apoptosis analysis with annexin, cellular morphology through scanning electron microscopy (SEM), and laser confocal analysis were evaluated after exposing the cells to monocerin. After 24 h of exposure to monocerin at 1.25 mM, there was more than 80% of cell viability and a low percentage of cells in the early and late apoptosis and necrosis. Monocerin increased cell proliferation and did not induce cell senescence. Morphological analysis showed cellular integrity. The study demonstrates aspects of the mechanism of action of monocerin on endothelial cell proliferation, suggesting the possibility of its pharmaceutical application, such as in regenerative medicine.

SUBMITTER: Gomes TC

PROVIDER: S-EPMC10222415 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature

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Effect of Monocerin, a Fungal Secondary Metabolite, on Endothelial Cells.

Gomes Tainah Colombo TC Conrado Rafael R Oliveira Rodrigo Cardoso de RC Selari Priscila Jane Romano Gonçalves PJRG Melo Itamar Soares de IS Araújo Welington Luiz WL Maria Durvanei Augusto DA De Souza Ana Olívia AO

Toxins 20230518 5

This study reports the isolation and identification of the endophytic fungus <i>Exserohilum rostratum</i> through molecular and morphological analysis using optical and transmission electron microscopy (TEM), as well as the procurement of its secondary metabolite monocerin, an isocoumarin derivative. Considering the previously observed biological activities of monocerin, this study was performed on human umbilical vein endothelial cells (HUVECs) that are widely used as an in vitro model for seve ...[more]

PMID: 37235378

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Project description:Fungal secondary metabolites (SMs) contribute to the diversity of fungal ecological communities, niches, and lifestyles. Many fungal SMs have one or more medically and industrially important activities (e.g., antifungal, antibacterial, and antitumor). The genes necessary for fungal SM biosynthesis are typically located right next to each other in the genome and are known as biosynthetic gene clusters (BGCs). However, whether fungal SM bioactivity can be predicted from specific attributes of genes in BGCs remains an open question. We adapted machine learning models that predicted SM bioactivity from bacterial BGC data with accuracies as high as 80% to fungal BGC data. We trained our models to predict the antibacterial, antifungal, and cytotoxic/antitumor bioactivity of fungal SMs on two data sets: (i) fungal BGCs (data set comprised of 314 BGCs) and (ii) fungal (314 BGCs) and bacterial BGCs (1,003 BGCs). We found that models trained on fungal BGCs had balanced accuracies between 51% and 68%, whereas training on bacterial and fungal BGCs had balanced accuracies between 56% and 68%. The low prediction accuracy of fungal SM bioactivities likely stems from the small size of the data set; this lack of data, coupled with our finding that including bacterial BGC data in the training data did not substantially change accuracies currently limits the application of machine learning approaches to fungal SM studies. With >15,000 characterized fungal SMs, millions of putative BGCs in fungal genomes, and increased demand for novel drugs, efforts that systematically link fungal SM bioactivity to BGCs are urgently needed.IMPORTANCEFungi are key sources of natural products and iconic drugs, including penicillin and statins. DNA sequencing has revealed that there are likely millions of biosynthetic pathways in fungal genomes, but the chemical structures and bioactivities of >99% of natural products produced by these pathways remain unknown. We used artificial intelligence to predict the bioactivities of diverse fungal biosynthetic pathways. We found that the accuracies of our predictions were generally low, between 51% and 68%, likely because the natural products and bioactivities of only very few fungal pathways are known. With >15,000 characterized fungal natural products, millions of putative biosynthetic pathways present in fungal genomes, and increased demand for novel drugs, our study suggests that there is an urgent need for efforts that systematically identify fungal biosynthetic pathways, their natural products, and their bioactivities.

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Dataset Information

Effect of Monocerin, a Fungal Secondary Metabolite, on Endothelial Cells.

Publications

Effect of Monocerin, a Fungal Secondary Metabolite, on Endothelial Cells.

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