Chemical diversity and species differentiation in Brazilian Vanilla: insights from LC-HRMS/MS metabolomics

dc.creatorLima, Gesiane da Silva
dc.creatorBevilaqua, Giovanni Bonatti
dc.creatorMachado, Hugo Gontijo
dc.creatorAlves, Rosa de Belém das Neves
dc.creatorBianchetti , Luciano de Bem
dc.creatorMaciel, Lanaia Itala Louzeiro
dc.creatorAcioli, Bianca Micaela Macario Gonçalves
dc.creatorLima, Nerilson Marques
dc.creatorVieira, Roberto Fontes
dc.creatorVaz, Boniek Gontijo
dc.date.accessioned2026-09-18T11:34:53Z
dc.date.available2026-09-18T11:34:53Z
dc.date.issued2026
dc.description.abstractIntroduction Vanilla species represent a taxonomically complex and economically important group of orchids, yet species discrimination and chemotaxonomic characterization remain challenging due to high intrageneric metabolic variability and limited molecular insights. Objectives We aimed to apply an untargeted metabolomic approach to characterize the metabolic signatures of three Brazilian Vanilla species (V. pompona, V. phaeantha, and V. calyculata) and to evaluate the relative contributions of species identity and biome origin to metabolic diversification. Methods The leaf metabolome of 102 Vanilla were profiled using high-resolution LC-HRMS/MS. Multivariate analyses including PCA and PLS-DA served to explore variance structures and build discriminant models. Discriminant features were selected using integrated criteria (VIP scores and volcano-plot significance). Annotation leveraged GNPS molecular networking and in silico databases to classify key metabolite classes. Results Unsupervised PCA revealed pronounced intraspecific metabolic heterogeneity, preventing spontaneous grouping by species or biome. Supervised PLS-DA models, however, provided robust species classification (Q² = 0.74–0.90), while biome-based models lacked predictive power, indicating limited environmental influence on leaf metabolomes. Consensus selection between models identified 17 core biomarkers, including phenolic acids, cinnamic acid derivatives, C-glycosylated flavonoids, lipids, terpenoids, and N-containing compounds, with ferulic acid (a key precursor of vanillin) emerging as a prominent discriminating metabolite. Conclusions Untargeted LC-HRMS metabolomics coupled with chemometric modelling delineates species-specific metabolic fingerprints within Vanilla, offering a generalizable strategy for chemotaxonomy and species authentication. The conserved metabolic features also spotlight biologically meaningful pathways for biodiversity assessment and valorization of native Vanilla resources.
dc.identifier.citationLIMA, Gesiane S. et al. Chemical diversity and species differentiation in Brazilian Vanilla: insights from LC-HRMS/MS metabolomics. Metabolomics, New York, v. 22, n. 2, e48, 2026. DOI: 10.1007/s11306-026-02422-8. Disponível em: https://link.springer.com/article/10.1007/s11306-026-02422-8. Acesso em: 15 set. 2026.
dc.identifier.doi10.1007/s11306-026-02422-8
dc.identifier.issn1573-3882
dc.identifier.issne- 1573-3890
dc.identifier.urihttps://repositorio.bc.ufg.br//handle/ri/31633
dc.language.isoeng
dc.publisher.countryEstados unidos
dc.publisher.departmentInstituto de Química - IQ (RMG)
dc.rightsAcesso Aberto
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectVanilla
dc.subjectMetabolsomics
dc.subjectLC-HRMS/MS
dc.subjectVanilla pompona Schiede
dc.subjectVanilla phaeantha Rchb.f
dc.subjectVanilla calyculata Schltr
dc.subject.ODS15 - Vida terrestre
dc.subject.ODS9 - Industria, inovação e infraestrutura
dc.titleChemical diversity and species differentiation in Brazilian Vanilla: insights from LC-HRMS/MS metabolomics
dc.typeArtigo

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