- Tytuł:
- Bioinformatic insight into Portulaca oleracea L. (Purslane) of Bulgarian and Greek origin
- Autorzy:
-
Balabanova, V.
Hristov, I.
Zheleva-Dimitrova, D.
Sugareva, P.
Lozanov, V.
Gevrenova, R. - Powiązania:
- https://bibliotekanauki.pl/articles/2117810.pdf
- Data publikacji:
- 2020
- Wydawca:
- Polska Akademia Nauk. Czasopisma i Monografie PAN
- Tematy:
-
Portulaca oleracea
LC–HRAMS
secondary metabolites
descriptive analysis
multivariate statistics - Opis:
- Portulaca oleracea L. (Portulacaceae) is used as functional food and its nutritional and therapeutic properties are related to the high levels of organic and fatty acids, polyphenols, polysaccharides and cyclo-dopa amides. This study presents a strategy based on liquid chromatography – high resolution accurate mass spectrometry method (LC – HRAMS) and bioinformatic methods to analyze 33 purslane accessions originating from 11 floristic regions in Bulgaria together with 5 accessions of Greek provenance. Extracts were obtained by microwave extraction. Based on the LC-MS metabolic “fingerprints” of assayed samples, a purslane metabolic database was developed. LC-MS data were proceeded with Software application Compound Discover 2.0 (Thermo Fischer Sci., USA). Principal Component Analysis (PCA) combined with both descriptive and differential analyses were used to find marker metabolites to distinguish different geographical regions. The differential analysis of the Bulgarian and Greek samples allowed the identification of 50 marker metabolites. Based on accurate masses, retention times, fragmentation patterns in MS/MS, comparison with commercial standards and literature data, these secondary metabolites were identified after detailed analysis of Volcano-plots. For the first time, 29 compounds are reported. The identified compounds were used to perform a study of the biosynthetic pathways of purslane secondary metabolites using Kyoto Encyclopedia of Genes and Genomes (KEGG) software platform. The statistical treatments identified marker compounds that can be used to distinguish the origin of accession set. Combining LC-MS data with multivariate statistical analysis was shown to be effective in studying the purslane metabolites, allowing for integration of chemistry with geographic origin.
- Źródło:
-
Acta Biologica Cracoviensia. Series Botanica; 2020, 62, 1; 7-21
0001-5296 - Pojawia się w:
- Acta Biologica Cracoviensia. Series Botanica
- Dostawca treści:
- Biblioteka Nauki
Artykuł