Comprehensive metabolomics unveil the discriminatory metabolites of some Mediterranean Sea marine algae in relation to their cytotoxic activities.
Sci Rep
; 12(1): 8094, 2022 05 16.
Article
em En
| MEDLINE
| ID: mdl-35577889
Marine algae have served as a treasure trove of structurally variable and biologically active metabolites. The present study emphasizes on UPLC-MS metabolites fingerprinting for the first systematic broad scale metabolites characterization of three different phyla of marine seaweeds; Ulva fasciata, Pterocladia capillacea and Sargassum hornschuchii along with Spirulina platensis harvested from the Mediterranean Sea. A total of 85 metabolites belonging to various classes including mostly fatty acids and their derivatives, terpenoids, amino acids and dipeptides with considerable amounts of polyphenolic compounds. OPLS-DA model offered a better overview of phylum-based discrimination rapidly uncovering the compositional heterogeneity in metabolite profiles of algae extracts. An OPLS model was constructed using the cytotoxic activities against PC3 and MDA-MB-231 tumor cells to succinctly screen cytotoxic discriminatory metabolites among the tested algae species. The coefficient plot revealed that unsaturated fatty acids as stearidonic acid and linolenic acid, terpenoids namely as rosmanol, campestanol, dipeptides primarily glutamylglycine, glycyltyrosine along with polyphenolic compounds being abundantly present in S. platensis and U. fasciata samples with relatively marked cytotoxic potential might be the significant contributors synergistically meditating their anti-proliferative activity against PC3 and MDA-MB-231 tumor cells. Such results serve as baseline for understanding the chemistry of these species and performing strict correlation between metabolite and activity where a lack of information in this regard is observed.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Espectrometria de Massas em Tandem
/
Antineoplásicos
Tipo de estudo:
Prognostic_studies
Idioma:
En
Revista:
Sci Rep
Ano de publicação:
2022
Tipo de documento:
Article