1 research outputs found
Interaction Metabolomics to Discover Synergists in Natural Product Mixtures
Mass spectrometry metabolomics has become increasingly
popular
as an integral aspect of studies to identify active compounds from
natural product mixtures. Classical metabolomics data analysis approaches
do not consider the possibility that interactions (such as synergy)
could occur between mixture components. With this study, we developed
“interaction metabolomics” to overcome this limitation.
The innovation of interaction metabolomics is the inclusion of compound
interaction terms (CITs), which are calculated as the product of the
intensities of each pair of features (detected ions) in the data matrix.
Herein, we tested the utility of interaction metabolomics by spiking
known concentrations of an antimicrobial compound (berberine) and
a synergist (piperine) into a set of inactive matrices. We measured
the antimicrobial activity for each of the resulting mixtures against Staphylococcus aureus and analyzed the mixtures with liquid
chromatography coupled to high-resolution mass spectrometry. When
the data set was processed without CITs (classical metabolomics),
statistical analysis yielded a pattern of false positives. However,
interaction metabolomics correctly identified berberine and piperine
as the compounds responsible for the synergistic activity. To further
validate the interaction metabolomics approach, we prepared mixtures
from extracts of goldenseal (Hydrastis canadensis) and habañero pepper (Capsicum chinense)
and correctly correlated synergistic activity of these mixtures to
the combined action of berberine and several capsaicinoids. Our results
demonstrate the utility of a conceptually new approach for identifying
synergists in mixtures that may be useful for applications in natural
products research and other research areas that require comprehensive
mixture analysis