Evaluating solvent extraction systems using metabolomics approaches

Abstract

Metabolic fingerprinting was performed on a set of botanical extracts to compare the extraction efficiency of different solvents to inform the construction of phytochemical libraries. We compared the extraction efficiency, examining both yield and chemical diversity, of eight single-solvent extractions prepared in parallel and using solvent–solvent partitioning. Three-dimensional data were reduced into features, which were used as unbiased metrics to identify solvents that would produce botanical extracts with the greatest chemical diversity. Chemical diversity and extract yield did not necessarily increase together. For each species and tissue, the total number of observable chemical features closely approached maximum values when three different single-solvent extractions were performed in parallel. The dynamic range of detectable compounds in plant extracts was increased significantly by performing solvent partitioning. Overall, maximum chemical diversity in a plant extract was most efficiently approached if solvent partitioning was performed on an extract made with 70% ethanol. We have shown that using metabolic fingerprinting is useful for assessing compound diversity in complex plant extracts.