Anti-Acetylcholinesterase and Synergistic Antifungal Activities of Selected Salvia Species: Correlation with Metabolic Profiles

Abstract

Salvia species are known for their anti-fungal and anti-acetylcholinesterase (AChE) activity. Metabolomics is defined as a comprehensive quantitative and qualitative analysis of large-scale of metabolites. In this study, besides determining anti-acetylcholinesterase and synergistic antifungal activities of selected Salvia species (S. cryptantha Montbret & Aucher ex Benth., S. tchihatcheffii (Fisch. & C. A. Mey.) Boiss., S. officinalis L., S. virgata Jacq.), the metabolite profiles were clarified and correlation analyzes between the activity results and profiles were carried out. Aerial parts of all plant materials were extracted by methanol to determine the metabolic profile by using GC-MS (Gas Chromatography-Mass Spectrometry) and LC-QTOF-MS (Liquid Chromatography Quadrupole Time of Flight Mass Spectrometry). Also, Ellman's spectrophotometric method for anti-acetylcholinesterase activity and the checkerboard method for synergistic antifungal activity between extracts and fluconazole were performed. 295 known and 1408 unknown metabolites were detected by using GC-MS while 346 known and 69008 unknown metabolites were by using LC-QTOF-MS. S. cryptantha, S. tchihatcheffii, S. officinalis, and S. virgata demonstrated inhibitory activities on AChE with the ratio of 32.72%, 5.9%, 43.96%, and 12.1% respectively at the concentration of 200 µg/mL. A synergism was found for all Salvia sp. against Candida tropicalis ATCC 750 strain (FICI values of ≤0.5). In addition, primary and secondary metabolites, which are highly correlated with both activities, were determined. All Salvia species exhibited synergic activity with fluconazole while having weak AChE inhibitory activity. Combining natural products with synthetic drugs is important in order to increase efficacy. At the same time, herbal products must be used carefully at the point of herb-drug interactions. Further studies are needed to investigate active metabolites according to correlation results.