Unbiased Metabolomics of Volatile Secondary Metabolites in Essential Oils Originated from Myrtaceae Species

Abstract

In this study, an untargeted metabolomic approach was applied to analyze volatile secondary metabolites in five different essential oils (i.e., anise myrtle oil, honey myrtle oil, lemon myrtle oil, lemon-scented tea tree oil, and peppermint gum oil) from the Myrtaceae family, originating from the Australian bush plants. A total of 503 volatile secondary metabolites were tentatively identified across the five oils using static headspace two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC-TOFMS). Both principal component analysis and partial least squares discriminant analysis generated using the identified metabolites revealed a clear discrimination into five clusters of oils. Nevertheless, only 24 of 503 identified metabolites significantly differentiated the five essential oils and these metabolites were identified as biomarkers based on their variable importance in the projection score. In terms of cluster analysis, the essential oils were clustered into five different groups using hierarchical cluster analysis. However, K-mean clustering showed that lemon myrtle oil and lemon-scented tea tree oil were clustered together due to their very close chemical composition compared to the other studied essential oils. Additionally, metabolite set enrichment analysis revealed that ketones represented the primary class in all essential oils, followed by aryl-aldehydes. In summary, despite belonging to the same Myrtaceae family, these oils can be well discriminated based on their respective species.