Bioguided isolation to discriminate antimicrobial compounds from volatile oils is a time- and money-consuming process. Considering the limitations of the classical methods, it would be a great improvement to use chemometric techniques to identify putative biomarkers from volatile oils. For this purpose, antimicrobial assays of volatile oils extracted from different plant species were carried out against Streptococcus mutans. Eight volatile oils that showed different antimicrobial effects (inactive, weakly active, moderately active and very active) were selected in this work. The volatile oils’ composition was determined by GC-MS-based metabolomic analysis. Orthogonal projection to latent structures discriminant analysis and decision tree were carried out to access the metabolites that were highly correlated with a good antimicrobial activity. Initially, the GC-MS metabolomic data were pretreated by different methods such as centering, autoscaling, Pareto scaling, level scaling and power transformation. The level scaling was selected by orthogonal projection to latent structures discriminant analysis as the best pre-treatment according to the validation results. Based on this data, decision tree was also carried out using the same pretreatment. Both techniques (orthogonal projection to latent structures discriminant analysis and decision tree) pointed palmitic acid as a discriminant biomarker for the antimicrobial activity of the volatile oils against S. mutans. Additionally, orthogonal projection to latent structures discriminant analysis and decision tree predicted as “very active” the antimicrobial activity of volatile oils, which did not belong to the training group. This predicted result is in agreement with our experimental result (MIC = 31.25 εg ml−1). The present study can contribute to the development of useful strategies to help identifying antimicrobial constituents of complex oils.
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F.A.S., I.P.S. and F.B.C. contributed in collecting plant samples and their identifications. I.P.S. extracted the VOs and performed the metabolite identification and antimicrobial assays. F.A.S. performed the pretreatments of the GC-MS data and the chemometric analysis. F.A.S. and I.P.S. drafted the manuscript. F.A.S. and I.P.S. contributed equally in this work. N.A.J.C.F. and F.B.C. designed the experiments, supervised the laboratory works and contributed to critical reading of the manuscript. All the authors have read the final manuscript and approved the submission.
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dos Santos, F.A., Sousa, I.P., Furtado, N.A.J.C. et al. Combined OPLS-DA and decision tree as a strategy to identify antimicrobial biomarkers of volatile oils analyzed by gas chromatography-mass spectrometry. Rev. Bras. Farmacogn. 28, 647–653 (2018). https://doi.org/10.1016/j.bjp.2018.08.006
- Antimicrobial activity
- Decision tree
- Volatile oils
- Gas chromatography-mass spectrometry
- Orthogonal projection to latent structures
- discriminant analysis