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Isolation and Characterization of Antifungal Metabolites from the Melia azedarach-Associated Fungus Diaporthe eucalyptorum.

Yu-Qi GaoShuang-Tian DuJian XiaoDa-Cheng WangWen-Bo HanQiang ZhangJin-Ming Gao
Published in: Journal of agricultural and food chemistry (2020)
Two biosynthetically related new metabolites, eucalyptacid A (1) and eucalactam B (2), along with six known compounds (3-8), eugenitol (3), cytosporone C (4), 4-hydroxyphenethyl alcohol (5), 1-(4-hydroxyphenyl)ethane-1,2-diol (6), N-(2-hydroxy-2-phenylethyl)acetamide (7), and phomopene (8), were isolated from the solid rice cultures of the endophytic fungus Diaporthe eucalyptorum KY-9 that had been isolated from Melia azedarach. Also, two further new derivatives (2a, 2b) were prepared from 2. The structures were elucidated by exhaustive analysis of NMR and ESIMS data and chemical methods such as Marfey's protocol. Compound 1 was identified as a rare polyketide fatty acid, (8E)-3,5,11-trihydroxy-2,10,12-trimethyltetradecenoic acid, and 2 was determined to be the first cyclic depsipeptide containing the same fatty acid unit as 1 and a Gly-Gly-Thr tripeptide chain. Its N-terminal end is N-acylated by an 11-hydroxy fatty acid with a branch alkyl chain of 14:1. The 11-hydroxyl group connects to the carboxylic group of the C-terminal amino acid to form a 22-membered lactone ring. A hypothetical biosynthetic pathway for the new polyketides is proposed. The isolated compounds were assayed for their inhibition against four plant pathogenic fungi, Alternaria solani, Botrytis cinerea, Fusarium solani, and Gibberella saubinettii. Compounds 1, 4, 6, and 7 exhibited antifungal activities against Alternaria solani, with minimal inhibitory concentration (MIC) values from 6.25 to 50 μM. Thus, strain KY-9 represents an untapped source for the development of biological control agents to prevent the infection of pathogenic fungus A. solani.
Keyphrases
  • fatty acid
  • candida albicans
  • ms ms
  • amino acid
  • high resolution
  • randomized controlled trial
  • magnetic resonance
  • electronic health record
  • ionic liquid
  • big data
  • machine learning
  • solid state
  • drug induced