Insecticidal Activities of Chloramphenicol Derivatives Isolated from a Marine Alga-Derived Endophytic Fungus, Acremonium vitellinum, against the Cotton Bollworm, Helicoverpa armigera (Hübner) (Lepidoptera: Noctuidae).
Dan ChenPeng ZhangTong LiuXiu-Fang WangZhao-Xia LiWei LiFeng-Long WangPublished in: Molecules (Basel, Switzerland) (2018)
A great deal of attention has been focused on the secondary metabolites produced by marine endophytic fungi, which can be better alternatives to chemicals, such as biopesticides, for control of polyphagous pests. On the basis of its novel biocontrol attributes, chemical investigation of a marine alga-derived endophytic fungus, Acremonium vitellinum, resulted in the isolation of three chloramphenicol derivatives (compounds 1⁻3). Their chemical structures were elucidated by detailed analysis of their nuclear magnetic resonance spectra, high-resolution electrospray ionization mass spectrometry, and by comparison with the data available in the literature. In this paper, compound 2 was firstly reported as the natural origin of these fungal secondary metabolites. The insecticidal activities of compounds 1⁻3 against the cotton bollworm, Helicoverpa armigera, were evaluated. The natural compound 2 presented considerable activity against H. armigera, with an LC50 value of 0.56 ± 0.03 mg/mL (compared to matrine with an LC50 value of 0.24 ± 0.01 mg/mL). Transcriptome sequencing was used to evaluate the molecular mechanism of the insecticidal activities. The results presented in this study should be useful for developing compound 2 as a novel, ecofriendly and safe biopesticide.
Keyphrases
- high resolution
- mass spectrometry
- magnetic resonance
- liquid chromatography
- ms ms
- single cell
- simultaneous determination
- systematic review
- tandem mass spectrometry
- gene expression
- genome wide
- working memory
- high performance liquid chromatography
- gas chromatography
- electronic health record
- rna seq
- computed tomography
- capillary electrophoresis
- machine learning
- solid phase extraction
- artificial intelligence