Terpenoid Constituents of Perovskia artemisioides Aerial Parts with Inhibitory Effects on Bacterial Biofilm Growth.
Zahra SadeghiMilena MasulloAntonietta CerulliFilomena NazzaroMahdi Moridi FarimaniSonia PiacentePublished in: Journal of natural products (2020)
Perovskia artemisioides is a perennial and aromatic plant distributed in the Baluchestan region of Iran. In the present work, an n-hexane extract of P. artemisioides aerial parts showed excellent capabilities to both inhibit the formation of biofilms by different Gram-positive and Gram-negative pathogens and block the cell metabolism within microbial biofilms. To correlate the activity of the extract with the biologically active compounds present, first an analytical approach based on LC-HRMS/MSn was carried out. The metabolite profile obtained guided the isolation of 21 compounds, among which two sesquiterpenes (8 and 9) and one diterpene (10) were found to be new. The antimicrobial activity of the isolated compounds was evaluated by determining how they were able not only to reduce the growth of different Gram-positive and Gram-negative human bacteria and phytopathogens but also to inhibit the formation of biofilms by these bacteria and affect the metabolism of microbial cells present within the biofilms. With the aim of correlating the activity exhibited by the extract with the concentration levels of the constituent compounds, a quantitative determination was carried out by an analytical approach based on LC-ESI/QTrap/MS.
Keyphrases
- gram negative
- multidrug resistant
- candida albicans
- oxidative stress
- liquid chromatography
- ms ms
- mass spectrometry
- microbial community
- induced apoptosis
- endothelial cells
- biofilm formation
- pseudomonas aeruginosa
- staphylococcus aureus
- simultaneous determination
- multiple sclerosis
- high resolution
- high resolution mass spectrometry
- single cell
- cell therapy
- signaling pathway
- escherichia coli
- cell proliferation
- mesenchymal stem cells
- tandem mass spectrometry
- molecularly imprinted
- neural network