bk-2016-1241.ch006

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Chapter 6

New (Practical) Strategies in Target, Suspects, and Non-Target LC-MS(/MS) Screening: Bisoprolol and Transformation Products as an Example Thomas Letzel,1 Sylvia Grosse,1 Wolfgang Schulz,2 Thomas Lucke,2 Angela Kolb,3 Manfred Sengl,*,3 and Marion Letzel3 1Chair

of Urban Water Systems Engineering, Technical University of Munich, Am Coulombwall 3, D-85748 Garching, Germany 2Zweckverband Landeswasserversorgung, Laboratory for Operation Control and Research, Am Spitzigen Berg 1, 89129 Langenau, Germany 3Bavarian Environment Agency, Bürgermeister-Ulrich-Str. 160, 86179 Augsburg, Germany *E-mail: [email protected].

Various chemicals of emerging concern (CEC), like pharmaceuticals, their human metabolites and further transformation products (TPs) enter wastewater treatment plants on a daily basis. A mixture of known, expected as well as unknown molecules are discharged into the aquatic environment since only partial elimination takes place for many of these chemicals during physical, biological and chemical treatment processes. In this study, an array of LC-MS methods from three collaborating laboratories was applied to detect and identify the beta blocker bisoprolol and its TPs in different water samples. Starting with theoretical predictions of TPs, an efficient workflow using the combination of suspects and non-target strategies has been developed for the identification of these TPs in a lab-scale wastewater treatment plant and soil columns. A screening workflow including an inter laboratory approach was used for the identification of transformation products in the effluent samples. Subsequently, newly identified compounds were successfully analyzed in effluents of real © 2016 American Chemical Society

Drewes and Letzel; Assessing Transformation Products of Chemicals by Non-Target and Suspect Screening Strategies and ... ACS Symposium Series; American Chemical Society: Washington, DC, 2016.

wastewater treatment plants and river waters. The new TPs were included in target analysis and continuously quantified in sampling campaigns of routine monitoring.


Introduction Various chemicals of emerging concern (CEC), including pharmaceuticals, personal care products, household chemicals, as well as transformation products (TPs) from natural (e.g., wetlands, managed aquifer recharge) and engineered water treatment processes (e.g., activated sludge systems; biofiltration; ozonation; UV/AOP) have been found in the aquatic environment (1–8). CEC often enter wastewater due to their extensive industrial and domestic usage. The total removal of these substances in not achieved during conventional biological wastewater treatment and, hence, a part of the compounds as well as their TPs are present in receiving surface waters (3, 9–11) and groundwater (12–15). As a result of demographic change and an increasing number of new drugs entering the market, the overall consumption of pharmaceuticals is increasing (16). In ageing societies it can be expected that an increasing number of antihypertonic drugs is being used. This is also true for beta blockers. Bisoprolol and Metoprolol for example are belonging to the group of beta blockers, a class of drugs used primarily in cardiovascular diseases. Between 2002 and 2009, for instance, the consumption of bisoprolol increased by more than 140% in Germany, reaching an average of 8 tons per year (16). Concentrations up to 1.4 µg L-1 were reported to occur in wastewater effluents (17). Bisoprolol appears to remove incompletely during wastewater treatment with mean removal efficiencies of 25-40% (18–20). It was rather quickly removed in water-sediment systems, with a 50% decrease in 9-28 days (21). In contrast to many other pharmaceuticals, no data was published for bisoprolol TPs in the aquatic environment so far. In the past, biotransformation of bisoprolol was studied and reported in degradation experiments with the pure substance using eighteen filamentous funghi and six actinomycetes species (22). Therein they described the O-dealkylated metabolite (M4) for eight Cunninghamella strains and for Gliocladium deliquescens. Among all strains tested, only Gliocladiurn deliquescens performed an oxidation of M4 to the corresponding acid (M1), which is also known as the main human metabolite (23). The metabolites named M2 (oxidation of the terminal methyl group) and M3 (ether cleavage followed by oxidation) detected in humans or animals were not observed with microorganisms and funghi (22). All metabolites were formed by a metabolic attack on the 6-methyl-2,5-dioxaheptyl side-chain whereas the isopropylaminopropoxy side-chain remained stable. TPs have known as well as unknown chemical structures, physico-chemical properties, and effects on aquatic organisms. In some cases, they can be even more persistent (24) and toxic (25, 26) than their parent compounds. Until now, the knowledge of TPs occurring in the aquatic environment and their potential effects to organisms has been unsatisfactory (27, 28). A pre-identification approach via suspects screening and hidden target screening using lists or 86 Drewes and Letzel; Assessing Transformation Products of Chemicals by Non-Target and Suspect Screening Strategies and ... ACS Symposium Series; American Chemical Society: Washington, DC, 2016.


databases filled with expected as well as theoretically predicted substances can assist in identifying potentially relevant compounds. These can be “home-made” databases, public compound libraries (like STOFF-IDENT (29) and DAIOS (30)) or comprehensive chemical databases like ChemSpider (31) and Chemicalize (32). In these databases, the chemical formula for the calculation of monoisotopic masses and the isotopic pattern is usually available for compound suggestions along with other physico-chemical properties. Transformation products sometimes are not included in monitoring programs. For this reason, qualitative and quantitative results from environmental samples rarely can be found. In such cases screening techniques like LC-MS/MS become interesting tools, e.g. for the detection and the identification of hidden targets (e.g. sartans and TPs) (33) and classifying them by using the knowledge level (34, 35). The aim of this study was to prove the applicability of an efficient strategy for the suspects and hidden target LC-MS screening of water samples by collaborating laboratories originally using their different workflows. A concept is described for the identification of TPs from the theoretical prediction of the transformation pathways to the final (target) analysis of water from different resources using synthesized reference materials. Bisoprolol serves as an example for studying widely used pharmaceuticals.

Materials and Methods Chemicals and Materials Formic acid (purity >98%), ammonium acetate (purity >98%), and hyper-grade methanol for HPLC-MS analysis were purchased from Merck (Darmstadt, Germany) or Sigma-Aldrich (Seelze, Germany), sodium azide was from Merck (Darmstadt, Germany). HPLC water was prepared from deionized water using a Millipore Milli-Q system (Billerica, MA, USA) or bought from Fluka (Buchs, Switzerland). Acetonitrile HiPerSolv Chromanorm was purchased from BDH (Poole, UK). Bisoprolol fumarate (CAS 104344-23-2) was purchased from Chemos (Regenstauf, Germany). The TPs bisoprolol M1 and bisoprolol M3 were synthesized by aromaLAB AG (Planegg, Germany) (general remark: in this study the names of bisoprolol TPs are used according to Schwartz et al. (22), other bisoprolol TPs are named as BIS_molecular mass, e.g. BIS_295; see also Table 1).

Lab-Scale Wastewater Treatment Plants The biodegradation of bisoprolol (LogD value 0 at pH 7.8, i.e. the pH value in the LWTP) was investigated in continuously operating lab-scale wastewater treatment plants (LWTP); for detailed information, see Letzel et al. (36). Bisoprolol was continuously dosed in the LWTPs for 52 days at concentrations of 10 µg L-1 and 40 µg L-1, respectively. A control plant (without dosing target chemicals) was operated in parallel. Influent and effluent samples were taken 87 Drewes and Letzel; Assessing Transformation Products of Chemicals by Non-Target and Suspect Screening Strategies and ... ACS Symposium Series; American Chemical Society: Washington, DC, 2016.


weekly for the quantification of the parent compound. The effluent sample of day 50 was collected in order to analyze TPs formed during the biological wastewater treatment process using LC-MS system 1 (see below 2.5). All samples were transported and stored at 4°C until analysis. Centrifugation was done in each laboratory before analysis. In order to validate the TPs detected with LC-MS system 1 a second LWTPexperiment was performed with a bisoprolol dose of 1 mg L-1 taking into account the lower sensitivity of LC-MS system 2. The effluent samples of days 28 and 31 were analyzed with LC-MS system 2 (see below 2.5).

Soil Columns Soil column experiments were designed and performed according to DIN 19528. Glass columns (length 30 cm, inner diameter 5.9 cm) were filled with sediments and water from well-characterized aquifers. The soil materials were taken from sites with differing redox conditions (aerobic and anaerobic) to check the influence of oxygen on the elimination of CEC. Aerobic material was used with oxygen rich groundwater (O2 = 9.7 mg L-1) and anaerobic material was treated with anaerobic groundwater (O2 < 0.5 mg L-1) taken from a sampling site nearby. Spiked groundwater (bisoprolol concentrations 50 µg L-1) was recirculated (deviating in that point from DIN 19528 which foresees flow-through experiments) for 50 days at a flow rate of 0.2 mL min-1 in order to simulate a longer duration of bank filtration. Two identical columns were used for each experiment. Two further columns filled with quartz sand represent a control. To one of these reference columns 1 g L-1 sodium azide was added to suppress microbial activity.

Wastewater and Surface Water Samples Grab samples for bisoprolol analysis from four full-scale wastewater treatment plants (WWTP) effluents (WWTP-1: 1,300,000 population equivalents (PE); WWTP-2: 75,000 PE; WWTP-3: 250,000 PE; WWTP-4: 125,000 PE) were taken from April 2014 to December 2014. Grab samples were taken from the rivers Ebrach (a small river of 23 km length, east of Munich, highly influenced by WWTP effluent discharges), Fränkische Rezat (with a remarkable influence of WWTP effluent), Würm, Amper, Main, Isar, Loisach and Danube (south of Regensburg) - all in Bavaria, Southern Germany - between January and December 2014. All samples were stored at 4°C until analysis. Centrifugation was done in each laboratory before analysis.

88 Drewes and Letzel; Assessing Transformation Products of Chemicals by Non-Target and Suspect Screening Strategies and ... ACS Symposium Series; American Chemical Society: Washington, DC, 2016.

Analytical LC-MS Systems


a. RPLC-ESI-QqTOF-MS Analysis (LC-MS System 1) Non-target screening (mainly ‘Hidden Target’ and also ‘Unknown Target’ see Figure in the Appendix) and suspects screening with LC-MS system 1 were carried out for TPs formed during lab-scale wastewater treatment by reversed-phase liquid chromatography (RPLC) coupled to a quadrupole time-of-flight mass spectrometer (QqTOF-MS: TripleTOF 5600, Sciex, Foster City, CA) via electrospray ionization (ESI) in positive and negative ionization mode. For details of the analytical methods see Letzel et al. (33). Unknown Targets were characterized by retention time, empirical formula and MS/MS data. Later was compared with similarity search techniques. This data is not shown in the presented publication due to clearness reasons.

b. RPLC-HILIC-ESI-TOF-MS Analysis (LC-MS System 2) The screening results of LC-MS system 1 (non-target and suspects data) were compared with an analytical LC-MS system 2 containing two Agilent HPLC systems series 1260 Infinity (Waldbronn, Germany). This system was coupled with a time of flight-mass spectrometer equipped using a Jet Stream ESI interface (Agilent Technologies, Santa Clara, CA, USA). The samples were analyzed in extended resolution mode with a mass range (50 -1700 m/z) in full scan mode. Further information regarding the chromatographic details is given in Greco et al. (37) and Rajab et al. (38).

c. RPLC-ESI-QqQ-MS Analysis (LC-MS System 3) Suspects screening and target analysis with LC-MS system 3 were performed with reversed phase liquid chromatography coupled to a triple-quadrupole-like system QTrap 4000 (Sciex, Foster City, CA, USA). External calibration was used for the quantification of bisoprolol and the TPs M1 as well as M3.

d. Combined Use of LC-MS Systems Initially, the effluents of the LWTPs were screened applying two similar analytical systems, i.e. reversed phase liquid chromatography (RPLC) coupled with time-of-flight mass spectrometry (ToF-MS). Both analytical systems used C18-modified silica as stationary phase in RPLC connected with an accurate high resolution mass spectrometer. LC-MS system 1 had the option to perform fragmentation by tandem mass spectrometry (i.e. QqToF-MS) leading to structural molecule information (39) and in addition LC-MS system 2 had the option to retard and separate molecules from an extended polarity range (i.e. using a combination of hydrophilic interaction liquid chromatography (HILIC) 89 Drewes and Letzel; Assessing Transformation Products of Chemicals by Non-Target and Suspect Screening Strategies and ... ACS Symposium Series; American Chemical Society: Washington, DC, 2016.


with RPLC) (37, 38). Each detected molecule was defined by its accurate mass and normalized retention times (see (29)). Typically, molecules were further considered if they showed a comparable chromatographic behavior within both systems and the same empirical formula. The mass spectrometer scanned a mass range of 50-1000 Da (LC-MS system 1) and 50-1700 (LC-MS system 2), respectively, thus the monitoring strategy can be called ‘non-target screening’. With LC-MS system 3 (the triple-quadrupole-like system) analytical measurements were performed in MRM (multiple reaction monitoring) mode resulting in ‘suspects screening’ and ‘target analysis’ (Table 1). This technique includes a sensitive single molecule detection strategy. Currently this setup is the most sensitive detection method for molecules using mass spectrometry. One has to keep in mind that system 1 and 3 have the same ‘collision induced dissociation (CID) cell’ from the same vendor (i.e. a very well comparable fragmentation pattern). Thus the fragmentation values and properties can easily be transferred from system 1 to system 3 and there be used for sensitive MRM measurements.

Theoretical Predictions of Transformation Products The Biodegradation Database Pathway Prediction System of the University of Minnesota (UM-PPS, now exclusively provided from EAWAG as EAWAG-BBD Pathway Prediction System) (40) has been previously used for prediction of TPs in several studies (33, 41–45). In this study, predictions were limited to four levels of transformation. Thus a list of 62 predicted TPs was generated by the program for bisoprolol (UM-PPS-list). The SMILES string (i.e. the output from UM-PPS) of each predicted TP was used for further calculations using EPI SuiteTM v4.10 (46). This tool processes molecular formula and logP values to assess ‘primary degradation’ (Biowin4) and ‘ready biodegradability’ (modeled with Biowin3 and 5). The monoisotopic masses of predicted TPs were calculated with MolE-Molecular Mass Calculator v2.02 (47). Consequently, the predicted transformation products from UM-PPS were used as a hidden target / suspects list to detect possible TPs from LC-MS analysis of LWTP and soil column samples.

Results and Discussion Transformation Products of Bisoprolol Degradation in LWTP First of all, the biodegradation of bisoprolol was investigated in continuously operating lab-scale wastewater treatment plants (LWTP). The elimination efficiency for bisoprolol in LWTP showed an average value of 30% (data not shown, see final report of the project RISK-IDENT) (48) which is consistent with data from literature (18–20). Transformation products present in LWTP effluents were analyzed and identified using various screening techniques in complementary laboratories (or equipment) as recently described in detail (33). 90 Drewes and Letzel; Assessing Transformation Products of Chemicals by Non-Target and Suspect Screening Strategies and ... ACS Symposium Series; American Chemical Society: Washington, DC, 2016.

a. Transformation Products Known by Literature Besides the bisoprolol biotransformation products M1, M2, M3, and M4 reported by Schwartz et al. (22) no additional TPs were described in literature so far.


b. Transformation Products Known by Databases A search for bisoprolol TPs in environmental samples without the knowledge of chemical structures in 2012/13 was not successful using general chemical databases like ChemSpider (31) or Chemicalize (32). Even in specialized compound databases for water-relevant substances like STOFF-IDENT (29) or DAIOS (30), where searchable hints for TPs are included, bisoprolol TPs were not found at that time. In the meantime - using the results of this study - the authors included the relevant bisoprolol TPs into the databases STOFF-IDENT (29) and DAIOS (30) for a broader dissemination. By the way, since 2012 the database STOFF-IDENT (29) is regularly updated by the authors with organic trace compounds and newly identified TPs found in the aqueous environment (also from external information sources) and since 2009 DAIOS (30) is regularly be updated by the authors with newly identified compounds found in the aqueous environment and technical and metabolic degradation products.

c. Expected TPs by Predictions via UM-PPS The number of predicted TPs from the UM-PPS (in 2013) was reduced in this study to the most expected occurring TPs, allowing “very likely”, “likely” and “neutral” transformations, similar to Howard and Muir (49). In total 62 TPs could be predicted for bisoprolol. The already known metabolites M1, M3 and M4 were also predicted by UM-PPS whereas M2, however, was not predicted. Since 2013 the UM-PPS changed into the EAWAG-PPS (40) and this tool is currently be merged into a new tool called EnviPath (50). Latter tool has not been tested in this study, but will be the tool for predictions of microbiological degradation products in the future. No further prediction tools were applied at that time; however new prediction tools will come up in the next years which may be typically be applied in strategies like in this chapter.

d. Analytical Strategy for the Screening of TPs in LWTP Effluent The effluent samples were independently be analyzed in parallel with the LC-MS systems 1 and 2. Thus full scan data files acquired with accurate high resolution mass spectrometers could be obtained. The data was processed with the vendor software Sciex PeakView and Agilent MassHunter Software, respectively, extracting features for accurate mass (thus observing later empirical formula for 91 Drewes and Letzel; Assessing Transformation Products of Chemicals by Non-Target and Suspect Screening Strategies and ... ACS Symposium Series; American Chemical Society: Washington, DC, 2016.


detected compounds). In this study the resulting (ion) masses were compared via extracted ion chromatograms (EIC) with the molecule (ion) masses known from literature and predicted with UM-PPS, i.e. ‘hidden target screening’. The EIC of each TP was defined by a compound mass accuracy within 10 ppm mass tolerance (taking into account the performance of the LC-MS systems used). EICs were evaluated for peak shape and peak intensity (S/N > 3/1). TPs that are exclusively present in the effluent water samples (or significantly higher in the effluent compared to the influent) were used for further investigation. For compounds detected by both laboratories the structures were validated by accurate MS/MS fragmentation in LC-MS system 1 if applicable. Overall four TPs of bisoprolol could be found in LWTP effluents with system 1 (see Table 1) and their structures could be confirmed by MS/MS spectra (see Figure 1). LC-MS system 2 could confirm these compounds by accurate mass. Several observations could be obtained for the dominating ‘M’-labeled TP compounds. M1 and M3 could exclusively be found in the effluent whereas bisoprolol M2 was not detected. The analysis of the original bisoprolol material used for the experiments showed the presence of TP M4 probably stemming from the synthesis. As the concentrations in the spiking solution and the LWTP effluents were comparable, TP M4 was not confirmed as a real elimination product. Bisoprolol TP BIS_295 was only found by LC-MS system 1 including MS/MS spectrum. This was leading to an allocation to category 4a identification with uncertain results (34, 35). Thus no reference material was synthesized at that time. Other features for ‘unknown targets’ could be observed (sometimes incl. also MS/MS data) from system 1. These results are not presented in this chapter.

Transformation Products of Bisoprolol Degradation in Soil Columns Bisoprolol showed a different elimination behavior in real aquifer columns where elimination efficiencies after 42 days were 96.5% under aerobic and 84.2% under anaerobic conditions. In matrix samples and sterile controls bisoprolol was not degraded (Figure 2). The use of real aeorobic and anaerobic aquifer materials and waters ensured that a redox-specific microbiological biocenosis was actively reacting on the test substance and longer adaptation periods were not necessary. Other studies using quartz sand or aerobic sediments as soil samples had to accept an adaptation period of up to 2 years (51, 52). Leachates from one of each column run under aerobic and anaerobic conditions as well as from the sterile control were checked for the formation of TPs after 14 and 42 days. Three out of the four TPs detected in LWTPs (Table 1) were identified and confirmed by MS/MS spectra. The formation of TPs M1 and M3 was higher under anaerobic conditions in comparison to aerobic columns (Figure 3). 92



Table 1. Monitored Bisoprolol TPs in the LWTP Effluent Including Study Name (Like Cited Reference), Category (34, 35), Structure, Detection Comment (a) for LWTP and (b) for Soil Columns) and Source of Information



Figure 1. MS/MS spectra of three dominating signals regarding to Bisoprolol TPs including the expected fragment ions.



Figure 2. Elimination of bisoprolol in soil columns experiments for 42 days.

Figure 3. Formation of TPs of bisoprolol in soil columns under aerobic and anaerobic conditions.

As TPs M1 and M3 were so far only known from degradation studies with funghi (22) both substances were synthesized and could be unambiguously identified by both mass spectrometric systems. Since the signal of TP M4 was already present in the spiking solution in comparable concentrations - most likely as a by-product of bisoprolol - this TP was excluded from further analysis. In the soil column experiments masses of further TPs predicted with UMPPS (like BIS_240 (C12H16O5), BIS_239 (C12H17NO4), BIS_209 (C10H11NO4), and BIS_111 (C6H7O2)) were found using LC-MS system 1. However, these four compounds were not used further on because they were either detected with low intensity (thus no MS/MS spectra were available) or the isotopic signal pattern accuracy was not below 10 ppm. 95 Drewes and Letzel; Assessing Transformation Products of Chemicals by Non-Target and Suspect Screening Strategies and ... ACS Symposium Series; American Chemical Society: Washington, DC, 2016.


Transformation Products of Bisoprolol Degradation Monitored in Real Waters Quantitative analysis was performed for the synthesized bisoprolol TPs M1 and M3 in 8 effluent samples of 4 different WTPs and 16 river samples from 8 rivers in Southern Germany. The limit of quantification (LOQ) for both TPs was 0.025 µg L-1. M1 and M3 were found in most WTP effluents in concentrations of 0.060 – 0.200 µg L-1 and 0.027 – 0.300 µg L-1, respectively. M3 could be detected only once in rivers characterized by high waste water effluent impact (Ebrach, 0.050 µg L-1 and Fränkische Rezat, 0.028 µg L-1) whereas M1 was not found above the LOQ. These results indicate that the TPs M1 and M3 should only be included in river water monitoring programs if LOQs below 0.025 µg L-1 can routinely be achieved. Generalization of the Workflow Strategy and Further Linkages These findings of TPs in samples from laboratory experiments are an important tool within a general strategic workflow for real samples. Figure 1 in Letzel et al. (33) presents an overview of conventional analytical strategies similar to Helbling et al. (44), Letzel (53), Krauss et al. (54) and Hernandez et al. (55) dealing with LC-MS(/MS) techniques for known TPs (target analysis), expected TPs (suspects screening), hidden TPs (non-target screening; via ‘Known Unknowns’) as well as unknown TPs (non-target screening; via ‘Unknown Unknowns’). In comparison to other workflows (also reviewed in Bletsou et al. (56)) the presented workflow is characterized by its comprehensiveness and the linkages between laboratories and screening instruments. The complementary strategies mainly differ in mass spectrometric detection and additional parameters like the availability of reference materials and/or databases. Thus the combined arrangement can be generalized as an overall scheme from prediction through detection to quantification of newly identified targets. Results for TPs from these procedures with different levels of knowledge can be sorted by allocating them to a classification system (33–35). Further tools can be linked in (if needed), like relevant databases (with occurrence data in real environment as the EMPODAT database (57), like exposure (58), like toxicological databases (e.g. human toxicology or ecotoxicology) (59) or like other properties as the usage and tonnage (in STOFF-IDENT).

Conclusions The workflow started with degradation experiments using LWTP and soil columns to identify the significance of potential transformation products. The workflow strategy for analyzing degradation vs. transformation products combines knowledge in the scientific community with a following analytical measurement. Thus literature searches were performed as well as transformation prediction systems like the former UM-PPS software. In a next step complementary (laboratory) LC-MS (/MS) systems were applied for the 96 Drewes and Letzel; Assessing Transformation Products of Chemicals by Non-Target and Suspect Screening Strategies and ... ACS Symposium Series; American Chemical Society: Washington, DC, 2016.


non-target screening strategy. The combination of both (knowledge and analysis) leads to the identification via the ‘hidden target screening’ strategy recently described in Letzel et al. (33). Finally synthesized reference materials evaluate the outcome and bring the compound into the target screening of various monitoring campaigns. This strategy led to new compound identifications of category 1 for Bisoprolol TPs in LWTP and soil columns. The TPs M1 and M3 could be monitored in several treatment plant effluents in ng L-1 scale. It is recommended to study the fate and transport of the TPs M1 and M3 in real subsurface environments such as riverbank filtration systems. The newly identified TPs can be found today in open-source databases like STOFF-IDENT and DAIOS in order to enable analytical chemists to quickly identify these substances by suspects / hidden target screening methods. The flow of the overall scheme from prediction through discovery to quantification of newly identified targets merges effectively the screening activities of cooperating laboratories. Furthermore, this strategy can be extended by the linkage of risk management tools like human toxicological and ecotoxicological databases.

Acknowledgments The authors want to acknowledge A. Bayer, S. Bertsch, F. Rehberger, W. Schüssler and M. Fioretti for their skillful technical assistance. This work was financed by the German Federal Ministry of Education and Research within the RiSKWa program, funding code 02WRS1273.

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