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| Author(s): |
Karen Dayane de Oliveira Bandeira
Total Authors: 1
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| Document type: | Master's Dissertation |
| Press: | Ribeirão Preto. |
| Institution: | Universidade de São Paulo (USP). Faculdade de Ciências Farmacêuticas de Ribeirão Preto (PCARP/BC) |
| Defense date: | 2017-03-31 |
| Examining board members: |
Leonardo Gobbo Neto;
Emerson Ricardo Pansarin;
Jonas Augusto Rizzato Paschoal
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| Advisor: | Leonardo Gobbo Neto |
| Abstract | |
The Orchidaceae family is the largest family among monocotyledons and represents one of the largest families of flowering plants with an estimated 30,000 species. The taxonomic complexity of one of the genera within this family, the Catasetum, has aroused much interest from growers and researchers in Orchidaceae, especially due to the new taxa being discovered in the genus. Aiming to improve the classification of species of the genus, a tool to be used is the analysis of the chemical constituents of the metabolism of these plants, where it is evidenced the need for studies using analytical methodologies more sensitive, fast and effective, such as the metabolomics analysis. Obtaining the metabolic fingerprint is the detailed obtaining of the metabolites of the organism under certain condition, producing a chromatogram that is characteristic of that plant, like a fingerprint. Through this, it is possible to determine metabolic differences in samples, through statistical tools. For the refinement of the data, it is necessary to use specific softwares that extract the useful information from analyzes data. The information generated can be used with different applications. A total of 51 samples were analyzed by GC-MS and UHPLC-MS (ESI-Orbitrap), 42 different species of the genus Catasetum and some duplicates. Metabolic \"fingerprints\" were processed in the MetAlignTM and MSClust softwares, and the generated matrices were analyzed by Principal Component Analysis (PCA), hierarchical cluster analysis (HCA) and partial least squares orthogonal discriminant analysis (OPLS-DA). The methods used for analysis by both GC-MS and UHPLC-MS resulted in satisfactory data for metabolomics analysis, generating 57 volatile substances identified from the flower fragrance, being neryl acetate, sabinene, ?-myrcene, ?-pinene and ?-pinene the most frequent. The results of the metabolic analyzes showed proximity to the phylogeny, mainly in more specific levels. The groups generated by the analyzes, in general, were coherent regarding the metabolic similarity between the species that compose them, suggesting the possibility of the use of metabolic fingerprints as a good tool for chemotaxonomic analysis (AU) | |
| FAPESP's process: | 14/20436-0 - Metabolomics as a tool for chemotaxonomic analysis of the genus Catasetum (Orchidaceae) |
| Grantee: | Karen Dayane de Oliveira Bandeira |
| Support Opportunities: | Scholarships in Brazil - Master |