1. MOLECULAR NETWORKING-BASED DEREPLICATION OF AMBUIC ACID DERIVATIVES FROM THE MARINE FUNGUS PESTALOTIOPSIS SP. 4A11
- Author
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Márcio Luis Andrade e Silva, Sabrina Ketrin Targanski, Patrícia Mendonça Pauletti, Ana Helena Januário, Marcos Antônio Soares, Luis Claudio Kellner Filho, Aline O. dos Santos, Rhenner Ávila Assis, Gustavo Muniz Dias, Hector H. F. Koolen, Wilson Roberto Cunha, Célio F. F. Angolini, Kátia Aparecida de Siqueira, Felipe M. A. da Silva, and Lívia Soman de Medeiros
- Subjects
Pestalotiopsis sp ,Ambuic acid ,biology ,Stereochemistry ,Chemistry ,Molecular networking ,ambuic acid ,Ascidiaceae ,Didemnum perlucidum ,molecular networking ,Fungus ,biology.organism_classification - Abstract
Ambuic acid (AA) is a highly-modified cyclohexenone and known as a promising inhibitor of quorum sensing in methicillinresistant Staphylococcus aureus, and is thus a candidate as an antivirulence drug. This molecule is mainly produced by the species of Pestalotiopsis and, since its discovery twenty years ago, only a restricted amount of AA-derivatives have been described. Despite being a promising subject, methods for the analysis of modified AA-analogues via mass spectrometry remain unexplored. In order to adress this question, the marine fungus Pestalotiopsis sp. 4A11 associated with the ascidian Didemnum perlucidum was grown in a solid rice medium and its crude extract was chemically studied. From this extract, AA and 10-hydroxy ambuic acid (10-HAA) were isolated and identified using NMR spectroscopy with the aim of obtaining model compounds for the MS analysis. These served as reference compounds (seeds) to guide the dereplication of other AA-analogues via LC-MS/MS-based molecular networking. Based on the manual interpretation of the fragmentation pathways of the seeds and related compounds observed in the networks, six AA-derivatives were dereplicated in the extract. Furthermore, three analogues with unprecedented chemical formulas were proposed as putative unprecedented AA-derivatives. The fragmentation annotation proposed represents a fast and feasible method for characterizing AA-derivatives.
- Published
- 2022