TY - JOUR
T1 - Towards eco-metabolomics
T2 - NADES-guided extraction enables semi-quantitative metabolomics for Melissa officinalis
AU - Spaggiari, Chiara
AU - Hiemstra, Isa Sara Aimee
AU - Kazbar, Antoinette
AU - Costantino, Gabriele
AU - Righetti, Laura
PY - 2025/2
Y1 - 2025/2
N2 - In recent years, there has been a growing emphasis on the development of green extraction techniques that minimize environmental impact while maximizing yield of the extracted compounds. To this aim, in this study we investigated the potential of green solvents for extracting bioactive compounds from Melissa officinalis (MO) leaves. Specifically, we focus on the application of 20 Natural Deep Eutectic Solvents (NADES) with a relative polarity ranging from 0.34 to 1.29. Their extraction affinity against a set of 11 plant metabolites was predicted using COSMO-RS software and experimentally validated using quantitative LC[sbnd]HRMS analysis. Subsequently, the same extracts were subjected to non-target metabolomics to uncover the NADES selectivity towards the wide spectrum of MO leaf metabolites. Data preprocessing and feature alignment were performed using MZmine, and aligned features were annotated using SIRIUS+CSI:FingerID. Overall, 249 and 195, metabolites were annotated in positive and negative ionization ion mode, respectively. Additionally, to have a more accurate view of the different NADES extraction capacity, we adopted a semi-quantitative approach that enables the prediction of concentration for all the annotated metabolites (N = 444). The results highlighted the selectivity of some NADES in extracting very diverse biochemical classes, providing valuable insights into the composition and concentration of bioactive compounds. Interestingly, thymol-menthol NADES demonstrated the ability to efficiently extract a broad range of bioactive compounds, yielding a metabolome comparable to that obtained with conventional ethanolic. Overall, the entire workflow facilitated the green extraction and annotation of known bioactive molecules that had never been described in MO.
AB - In recent years, there has been a growing emphasis on the development of green extraction techniques that minimize environmental impact while maximizing yield of the extracted compounds. To this aim, in this study we investigated the potential of green solvents for extracting bioactive compounds from Melissa officinalis (MO) leaves. Specifically, we focus on the application of 20 Natural Deep Eutectic Solvents (NADES) with a relative polarity ranging from 0.34 to 1.29. Their extraction affinity against a set of 11 plant metabolites was predicted using COSMO-RS software and experimentally validated using quantitative LC[sbnd]HRMS analysis. Subsequently, the same extracts were subjected to non-target metabolomics to uncover the NADES selectivity towards the wide spectrum of MO leaf metabolites. Data preprocessing and feature alignment were performed using MZmine, and aligned features were annotated using SIRIUS+CSI:FingerID. Overall, 249 and 195, metabolites were annotated in positive and negative ionization ion mode, respectively. Additionally, to have a more accurate view of the different NADES extraction capacity, we adopted a semi-quantitative approach that enables the prediction of concentration for all the annotated metabolites (N = 444). The results highlighted the selectivity of some NADES in extracting very diverse biochemical classes, providing valuable insights into the composition and concentration of bioactive compounds. Interestingly, thymol-menthol NADES demonstrated the ability to efficiently extract a broad range of bioactive compounds, yielding a metabolome comparable to that obtained with conventional ethanolic. Overall, the entire workflow facilitated the green extraction and annotation of known bioactive molecules that had never been described in MO.
KW - Green extraction
KW - Melissa officinalis
KW - Metabolomics
KW - NADES
KW - Non-targeted semi quantification
U2 - 10.1016/j.sampre.2025.100154
DO - 10.1016/j.sampre.2025.100154
M3 - Article
AN - SCOPUS:85217689286
SN - 2772-5820
VL - 13
JO - Advances in Sample Preparation
JF - Advances in Sample Preparation
M1 - 100154
ER -