Screening for metabolites of venlafaxine and citalopram in edible plants

Pharmaceuticals as pollutants have garnered increased scientific interest over recent years. Their continuous release results in a pseudo persistence, which can lead to a constant exposure of organisms to active pharmaceutical ingredients (APIs). APIs are commonly found in wastewater. Most wastewater treatment plants (WWTPs) are not equipped to sufficiently remove APIs from their effluent streams. Sewage sludge used as fertilizer presents another route of contamination. This thesis focuses on the uptake and metabolization of antidepressant medication (ADM) by edible plants. Citalopram and venlafaxine were chosen as two common antidepressants. Cress, peas, and maize were grown hydroponically in deliberately contaminated tap water solutions. The plants were separated into different parts, homogenized, and extracted with a 2:1 solution of hydrochloric acid (0.1 M) and acetonitrile (ACN). The samples were separated with reversed phase high performance liquid chromatography (RP HPLC) using a water/methanol gradient. The detector of choice was a quadrupole time of flight (QToF) instrument equipped with a drift tube (DT) for ion mobility (IM) measurements and collision cell for MS/MS. The detector was operated as MS, MS/MS, IM MS, and IM MS/MS. The main focus of this thesis is the untargeted screening for potential API metabolites using a statistical analysis of IM MS data, comparing extracts of treated and untreated plants; and subsequently validating the identity of these metabolite candidates using targeted MS/MS and IM MS/MS. A set of targeted screening methods were also performed in MS mode, by searching the generated HPLC MS data using a m/z database of hypothetical phase I and phase II metabolites of venlafaxine and citalopram. In addition to metabolite screening, this thesis includes a quasi quantitative uptake study, monitoring the uptake of both APIs in cress. By measuring the API concentrations in the water of the hydroponic growth kits the total API amount that has been taken up was estimated. submitted by David Schmiedjell BSc Masterarbeit Universität Linz 2022