Workflow for the identification of biotransformation products of amine-containing psychotropic drugs in the aquatic environment

Pharmaceuticals are continuously discarded Pharmaceuticals are continuously discarded into the aquatic system through wastewater treatment plants (WWTPs). The microbial degradation of these organic micropollutants and formation of transformation products (TPs) under aerobic conditions is the fundamental process for their elimination. It is of paramount importance to understand the microbial metabolic pathways so as to obtain knowledge of how fast micropollutants degraded and to assess the exposure to their potential TPs as they can be more polar and consequently environmentally persistent. In this study, batch reactors seeded with activated sludge from the WWTP of Athens were set up to assess biotic, abiotic and sorption losses of selective psychotropic drugs, containing amine moieties. Biodegradation and transformation products were identified using liquid chromatography quadrupole-time-offlight mass spectrometry (LC-QToF-MS). A workflow for target, suspect and non-target screening was developed. Data treatment was performed by using metabolite tools accompanying Bruker’s maxis impact ESI-QToF-MS and the structure elucidation of the candidate transformation products was based on accurate mass and isotopic pattern measurements by HRMS and tentative interpretation of MS/MS spectra. Finally four biotransformation products were identified for both lidocaine and ephedrine. Despite the structure similarities, different degradation constants were calculated for each compound

Targeted determination of more than 1500 micropollutants & transformation products in wastewater samples by liquid chromatography quadrupole-time-of-flight mass spectrometry with an accurate-mass database

High resolution mass spectrometry has dramatically improved the possibilities of the environmental analysis. The present study describes the development of an analytical method, based on liquid chromatography quadrupole-time-of-flight mass spectrometry (LC–QToF-MS) for the target determination of more than 1500 contaminants of emerging concern (CECs) and transformation products (TPs) including, among others, pharmaceuticals, illicit drugs, personal care products, pesticides, industrial chemicals, and sweeteners in wastewater. Analytes were extracted from wastewater samples by mixed mode solid-phase extraction, and data were acquired through broad-band Collision Induced Dissociation (bbCID) mode, providing MS and MS/MS spectra, simultaneously, in both positive and negative ionization mode (two separate runs). The in-house mass spectral database was built by injection of standard solution of the analytes and it includes information of the retention time, parent ions and adducts, as well as fragment ions. The raw data were analyzed with Bruker Target Analysis 1.3 software. Retention time, accurate mass of the precursor ion and adducts, isotopic pattern, in combination with absence of the peak in the procedural blank were the parameters used for confirmation of the target compounds. Experimental fragment ions were also considered, along with the ion ratio, intensity and isotopic pattern. Furthermore, semi-quantitation of these contaminants was possible. The method herein presented, in addition of providing accurate information about the presence of a large number of relevant substances, has the advantage that the data generated can be further processed for suspect and non-target screening, expanding the information on the samples. An important advantage of this method is that retrospective investigation of the data is available to look for the presence of additional CECs and their TPs, which were not considered at the time of the analysi

PEAKTRAMS: An automated computational approach for the simultaneous detection of features in reverse phase and hilic hrms screening

Comparison of chromatograms obtained in reserved phase (RP) liquid chromatography and hydrophilic interaction liquid chromatography (HILIC) can provide valuable information for the identification and confirmation of suspect and non-target compounds. The plausibility of the obtained chromatographic retention times (RTs) in both modes as well as the ψomparison of the MS/MS spectra are strong points to be considered. This work presents the development of a novel automatic approach for the identification of common peaks between RP and HILIC chromatograms. The core of the program is written in R-project while a simple and user friendly graphical user interface (GUI) was built in JAVA. The first step consists of the introduction of the target chromatograms of the same sample (one obtained by RP and one by HILIC) plus the corresponding blank chromatograms. Blank subtraction was performed first using an algorithm to find in each scan the common m/z features (with a given mass accuracy). This algorithm also considers the RTs (a tolerance interval is applied), so the subtraction takes place even with slight drifts in the RTs between target and blank chromatograms. After blank subtraction, two different lists are obtained with the detected peaks in both RP and HILIC modes. Subsequently, m/z values are compared and matches are listed. The developed workflow was validated with solvent standards and with spiked wastewater samples with a mixture of compounds with a wide range of physicochemical properties. Successful results were obtained for 26 out of the 27 evaluated substances, allowing the recording of the corresponding RTs in both RP and HILIC mode

Non-target approach for the determination of novel micropollutants in wastewater using liquid chromatography quadrupole-time of flight mass spectrometry (LC-QTOF-MS)

Wastewaters contain a very large list of micropollutants and transformation products of environmental concern. All these (mostly) synthetic organic chemicals enter the wastewater treatment plants (WWTP) with influents and due to incomplete or zero removal are released in the aquatic environment. Thus, the study of the fate of the emerging pollutants and their transformation products in WWTPs is of paramount environmental importance and can also provide valuable information related to consumption trends. Target screening procedures are limited to a small fraction of these substances, due to the inability to obtain standards for all that substances and the ignorance of the existence of many of them. Recent advances in high resolution mass spectrometry (HRMS) have opened up new windows of opportunity in the field of complex samples analysis. Suspect screening, with suspected substances based on prior information but with no reference standard, is a powerful tool which allows a large increment in the number of compounds to be evaluated. However, in most cases many of the peaks showing greater intensity not correspond to substances included in the target and suspect screening lists. These substances are potentially relevant, due to their high concentration, and their identification is environmentally important. Nevertheless, full identification of unknown compounds is often difficult and there is no guarantee of a successful outcome. The aim of the present work is the development and application of a workflow for the tentative identification of relevant unknown substances (not detected in the previously applied target and suspect methods) using liquid chromatography quadrupole-time-of-flight mass spectrometry (LC–QToF-MS)

Targeted and non-targeted liquid chromatography-mass spectrometric workflows for identification of transformation products of emerging pollutants in the aquatic environment

Identification of transformation products (TPs) of emerging pollutants is challenging, due to the vast number of compounds, mostly unknown, the complexity of the matrices and their often low concentrations, requiring highly selective, highly sensitive techniques.Wecompile background information on biotic and abiotic formation of TPs and analytical developments over the past five years. We present a database of biotic or abiotic TPs compiled fromthose identified in recent years.We discuss mass spectrometric (MS) techniques and workflows for target, suspect and non-target screening of TPs with emphasis on liquid chromatography coupled to MS (LC-MS). Both low- and high-resolution (HR) mass analyzers have been applied, but HR-MS is the technique of choice, due to its high confirmatory capabilities, derived fromthe high resolving power and the mass accuracy in MS and MS/MS modes, and the sophisticated software developed

Identification of unknowns in real wastewater through the application of a LC-QTOF-MS based workflow

Wastewater contains a high number of organic micropollutants and transformation products of environmental concern. Recent approaches, combining methodologies based on target and suspect screening (for suspected substances based on prior information but with no reference standard) are important for the comprehensive characterization of environmental samples. Nevertheless, samples still contain many chromatographic peaks which do not correspond to substances included in target and suspect screening lists. These substances may be potentially relevant (e.g. due to their concentration or potential effects) and thus the identification of selected non-targets is important. However, full identification of unknown compounds is often difficult and there is no guarantee of a successful outcome. The aim of this work is to show some specific examples on the identification of unknown compounds in real wastewater (collected from the WWTP of Athens). Identifications were conducted using a developed integrated workflow based on LC–QToF-MS to detect formerly unknown organic contaminants in wastewater

Biotransformation of citalopram: Insights from identification of transformation products by LC-QToF-MS

Biodegradation is considered to be the key process for the elimination of the majority of pharmaceuticals in the environment. During wastewater treatment or once they are disposed in the aquatic environment, pharmaceuticals may transformed to new, structurally-related compounds which are called transformation products (TPs). Since most of these compounds are unknowns, their identification is essential not only to provide a comprehensive risk assessment on micropollutants in the environment, but also to design improved removal technologies for (pseudo)persistent trace contaminants. In this study, batch reactors seeded with activated sludge from the WWTP of Athens were set up to assess biotic, abiotic and sorption losses of a SSRI drug, citalopram. TPs were identified by reversed-phase liquid chromatography quadrupole-time-of-flight mass spectrometry (RPLC-QToF-MS). Hydrophilic interaction liquid chromatography (HILIC) was also used as a complementary, orthogonal, technique for the identified TPs, instead of NMR. A workflow for suspect and non-target screening was developed. A suspect list of possible TPs was compiled by literature and in silico prediction tools (EAWAG-BBD Pathway Prediction System and Bruker’s Metabolite Predict). Structure elucidation of TPs was based on accurate mass and isotopic pattern measurements and interpretation of MS/MS spectra by the observed fragmentation pattern and library-spectrum match. In total, thirteen TPs were identified. Four out of them were fully identified and confirmed by reference standards (desmethylcitalopram, citalopram amide, citalopram carboxylic acid and 3-oxo-citalopram). A probable structure based on diagnostic evidence and tentative candidates were proposed for the additional five and four TPs, respectively. Finally, a transformation pathway based on the identified compounds was presented

Degradation and by-products identification of benzothiazoles and benzotriazoles during chlorination by LC-HR-MS/MS

Nowadays, chlorination is the most prevalent disinfection method applied for water treatment in Europe. Chlorine can be supplied as sodium hypochlorite (NaOCl) which reacts in water to produce the disinfectants hypochlorous acid (HOCl) and hypochlorite ion (OCl-), otherwise known as free chlorine. Although the primary purpose of chlorination is the elimination of micropollutants via oxidation, several investigations have shown that chlorine reacts with micropollutants leading in the production of undesired by-products. 1,3-benzothiazoles (BTHs) and 1,2,3-benzotriazoles (BTRs) are classified as high production volume emerging environmental pollutants due to their broad industrial and domestic application, and even though recently several analytical methods have been applied for their determination , there is still a lack of research for their by-products’ identification. Initially, the degradation of three BTHs (BTH, 2-OH-BTH and 2-amino-BTH) and four BTRs (1-H-BTRi, TTRi, XTRi and 1-OH-BTRi) during chlorination was investigated by UHPLC-MS/MS (QqQ). Although chlorination appeared to be an insufficient degradation process for BTH and 1-H-BTRi, all their examined substituted derivatives seem to be significantly degraded when the molar ratio of sodium hypochlorite and the target analytes was between 5000:1 – 1000:1. Then, LC high resolution MS/MS (q-TOFMS) was used to investigate the formation of by-products in the chlorinated samples. Two suspect by-products of 2-amino-BTH and one of XTRi were tentatively identified based on their probable structure, mass accuracy, retention time and fragmentation and isotopic pattern. An interesting observation was the formation of 1-H-BTRi as a degradation product of 1-OH-BTRi during chlorination. Moreover, post-acquisition non-target treatment of the MS data revealed several unknown by-products of the tested analytes

Extended suspect and non-target strategies to characterize emerging polar organic contaminants in raw wastewater with LC-HRMS/MS

An integrated workflow based on liquid chromatography coupled to a quadrupole-time-of-flight mass spectrometer (LC-QTOF-MS) was developed and applied to detect and identify suspect and unknown contaminants in Greek wastewater. Tentative identifications were initially based on mass accuracy, isotopic pattern, plausibility of the chromatographic retention time and MS/MS spectral interpretation (comparison with spectral libraries, in silico fragmentation). Moreover, new specific strategies for the identification of metabolites were applied to obtain extra confidence including the comparison of diurnal and/or weekly concentration trends of the metabolite and parent compounds and the complementary use of HILIC. Thirteen of 284 predicted and literature metabolites of selected pharmaceuticals and nicotine were tentatively identified in influent samples from Athens and seven were finally confirmed with reference standards. Thirty four nontarget compounds were tentatively identified, four were also confirmed. The sulfonated surfactant diglycol ether sulfate was identified along with others in the homologous series (SO4C2H4(OC2H4)xOH), which have not been previously reported in wastewater. As many surfactants were originally found as nontargets, these compounds were studied in detail through retrospective analysi

QSRR models to support suspect high resolution mass spectrometric screening of emerging contaminants in environmental samples

Over the last decade, the application of liquid chromatography - high resolution mass spectroscopy (LC-HRMS) has been growing extensively due its ability to identify a wide range of suspect and unknown compounds in environmental samples. However, certain information such as mass accuracy and isotopic pattern of the precursor ion, MS/MS spectra evaluation and retention time plausibility are needed to reach a certain identification confidence. In this context, a comprehensive workflow based on computational tools was developed to understand the retention time behavior of a large number of compounds belonging to emerging contaminants. An extensive dataset was built, containing information for the retention time of 528 and 298 compounds for positive and negative electrospray ionization mode, respectively, to expand the applicability domain of the developed models. Then, the dataset was split into training and test employing k-nearest neighborhood clustering technique so as to build and validate the models’ internal and external prediction ability. The best subset of molecular descriptors was selected using genetic algorithms which is based on the evolutionary computations, and could result in representative selection of descriptors. Multiple Linear Regression, Artificial Neural Networks and Support Vector Machines were used to correlate the selected descriptors with the experimental retention times. Several validation techniques were used, including Golbraikh-Tropsha acceptable model criteria's, Euclidean based applicability domain, r2m, concordance correlation coefficient values, to measure the accuracy and precision of the models. The best linear and non-linear models for each dataset were derived and used to predict the retention time of suspect compounds in a wide-scope survey as the evaluation data set. Overall, the proposed workflow was fast, reliable, and less time consuming which can be employed for identification purposes in environmental sample