Nontargeted acquisition with targeted and suspect screening of pharmaceutical drugs and their metabolites in wastewater

Simultaneous quantitation and screening by the SCIEX X500R QTOF system and SCIEX OS software

Marta Massano^1,2 , Alberto Salomone^1,2 and Holly Lee^3
1University of Turin, Italy; ²Centro Regionale Antidoping, Italy; ³SCIEX, Canada

Abstract

A solid phase extraction method using low sample volumes of 30 mL was developed on the SCIEX X500R QTOF system to semi-quantitate 105 pharmaceutical drugs in wastewater. Using the X500R QTOF system, the MS/MS spectra collected from SWATH DIA were retrospectively analyzed in Molecule Profiler to search for drug metabolites that were not targeted in the initial drug screening. The Molecule Profiler module was able to find the same metabolites discovered by the conventional suspect screening workflow in the Analytics module, but without requiring advanced knowledge of the analyte details for targeted screening.

Introduction

This technical note describes the identification of pharmaceutical drugs and their metabolites in wastewater using nontargeted acquisition coupled with suspect screening. A solid-phase extraction (SPE) LC-MS/MS method was developed for the semi-quantitative screening of 105 pharmaceutical drugs. The X500R QTOF system was used to collect MS/MS data by SWATH data-independent acquisition (DIA). These data were used to identify targeted drug compounds and retrospectively detect previously untargeted metabolites from a combined approach of spectral library matching and diagnostic fragment confirmation. Molecule Profiler software provided a complementary workflow for metabolite identification by matching common fragments against those from in silico fragmentation.

Wastewater monitoring has been increasingly adopted to assess community drug exposure due to its low costs, non-invasive sample collection and comprehensive analytical coverage.¹ In contrast, drug epidemiological data derived from self-reported surveys and toxicological reports can be expensive and be biased from the lack of or skewed responses from the sampled populations. SWATH DIA produces high-resolution MS/MS spectra that are composites of all analytes present in the sample and can be retrospectively mined.

Here, an end-to-end workflow using the X500R QTOF system and integrated modules within the SCIEX OS software provided high-resolution MS and MS/MS data for targeted and nontargeted screening of drugs and their metabolites in wastewater environments. Figure 1 shows the identification of carbamazepine and its metabolites based on complementary approaches of MS/MS library matching and in silico fragment confirmation in the Molecule Profiler software module of SCIEX OS software.

Key features of SWATH DIA on the X500R QTOF system coupled with targeted and nontargeted screening with SCIEX OS software
 

• SWATH DIA acquisition on the X500R QTOF system provided comprehensive MS/MS coverage for both targeted and nontargeted screening of all compounds
  
  
• Integration of the Analytics module and Molecule Profiler software within SCIEX OS software enabled a seamless transition between spectral library matching and in silico fragmentation predictions for compound identification in a single software platform
  
  
• A SPE LC-MS/MS workflow enabled the simultaneous semiquantitation and identification of 105 pharmaceutical drugs in small volumes of wastewater samples

Experimental methods

Chemicals and samples: The target analyte list included 105 pharmaceutical drugs and 3 surrogate internal standards. Individual neat standards were mixed to prepare stock solutions in methanol from which calibration standards (5–1000 ng/L) were prepared in MilliQ water for semi-quantitation. Influent wastewater samples were collected as 24-hour composites from 4 sites in the northwestern region of Italy. Upon collection, a 1 L aliquot of composite wastewater was transferred to refrigerated glass bottles and stored at -20°C until analysis.

Sample preparation: A 100 mL sample of wastewater was centrifuged at 4000 rpm for 5 minutes and vacuum-filtered through a 0.22 µm filter. A 30 mL aliquot of filtered wastewater was spiked with the surrogate internal standards and extracted using an Oasis HLB SPE cartridge (200 mg, 6 cm³ , Waters, Milford, MA). Each cartridge was preconditioned with 5 mL of methanol and 5 mL of MilliQ water before loading the sample, then was vacuum dried and eluted with 10 mL of methanol. Upon evaporation to dryness, the residue was reconstituted with 50 µL of methanol for LC-MS/MS analysis. Spiked MilliQ water was prepared in the same manner for semi-quantitative assessment of limits of detection (LOD) and extraction recoveries.

Chromatography: LC separation was performed on a SCIEX ExionLC AC system using a Phenomenex Kinetex C18 column (100 x 2.1 mm, 1.7 µm, P/N: 00D-4475-AN). A flow rate of 0.5 mL/min, an injection volume of 5 µL and a column temperature of 45°C were used. The LC conditions used are shown in Table 1.

Mass spectrometry: Analysis was performed using the X500R QTOF system in both positive and negative electrospray ionization mode. Table 2 shows the method parameters used for the mass spectrometer. The SWATH DIA method consisted of 16 variable windows covering a mass range of m/z 130–520.

Data processing: Data were acquired and processed using SCIEX OS software, versions 2.2 and 3.1. A custom library of previously acquired MS/MS spectra was used for library searching. The Molecule Profiler software was used to screen for drug metabolites. Figure 2 shows the overall workflow.

Targeted analysis of drugs in wastewater

In contrast to the 100–250 mL samples typically used in SPE methods for wastewater analysis, only 30 mL was extracted here, which reduced solvent consumption and the matrix load. The SPE LC-MS/MS method achieved recoveries of ≥70% for 60% of the 105 targeted drugs and 50–70% for most of the remaining analytes based on comparisons of pre- and post-extracted aqueous spikes. Based on aqueous spikes exhibiting signal-to-noise (S/N) ratios ≥3 above the background, the instrumental LODs were estimated to be ≤5 ng/L for 72% of the analytes and 5–15 ng/L for the remainder, consistent with the typical concentration ranges of drugs observed in wastewater. As such, the developed SPE LC-MS/MS method provided acceptable performance based on fit-for-purpose criteria for the semiquantitation of a large panel of targeted analytes in wastewater influents (Table 3). Table 3 shows the average concentration range for a subset of the 105 targeted drugs detected in wastewater whereby compound identification in each sample was confirmed by retention time (RT) matches against authentic standards, mass error of <5 ppm for the exact precursor and fragment m/z peaks, and spectral MS/MS matching against a custom library of previously acquired MS/MS spectra using reference standards. The traffic light system in the SCIEX OS software expedites data review by enabling the user to filter and display only the results passing predefined confidence thresholds for identification, such as mass error and matches in RT, isotope ratio pattern and MS/MS spectra against a library, as shown by some example positive hits in Figure 3.

In addition to confirming positive detection of the parent drugs, monitoring their metabolites has become increasingly prevalent, since specific metabolites have demonstrated toxicity comparable to their parent drugs.

Suspect screening for previously untargeted metabolites using SCIEX OS software

Non-targeted acquisition by SWATH DIA enabled retrospective analysis of TOF MS/MS to screen for previously untargeted compounds, such as the metabolites of positive drug hits in wastewater. Due to its well-documented metabolic pathways, ^2-4 carbamazepine (CBZ) was used as the model parent drug to screen for metabolites that were not initially targeted. The molecular formula and exact precursor masses of 8 known CBZ metabolites were determined a priori from the literature to generate a suspect screening list in the processing method (Figure 3). The RT mode was selected for these suspect compounds with unknown RTs to “Find top peak” to identify the most intense peak eluting at a specific RT within the extracted ion chromatogram (XIC). Three metabolites, 10,11-dihydro-10-hydroxycarbamazepine (10-OH-CBZ), 10,11-dihydro-10,11- dihydroxycarbamazepine (DiOH-CBZ) and carbamazepine 10,11- epoxide (EP-CBZ) were identified based on mass error (<5 ppm), isotope ratio and spectral matching against a custom library (Figure 3). Although DiOH-CBZ was not present in the custom library, its predominant fragments of [C₁₃H₁₀N]⁺, [C₁₄H₁₂NO]⁺ and [C₁₅H₁₀NO₂]⁺ were present with good mass error (<5 ppm), which is consistent with MS/MS spectra reported in published databases.⁵ In addition, Formula Finder predicted several candidate formulas based on the MS and MS/MS spectra, one of which matched the structure of DiOH-CBZ found in the ChemSpider database (Figure 4) .

A limitation of this workflow is that it required a priori knowledge of the molecular formula and/or exact precursor mass m/z of the compounds to be targeted for suspect screening. This demands an exhaustive search in the literature to produce a comprehensive list of suspect metabolites, which can be time-consuming and labor-intensive. As such, some of the wastewater samples were reinterrogated using the Molecule Profiler module to corroborate these findings here and screen for additional metabolites that may have been missed from suspect screening. 

Detection of additional CBZ metabolites using Molecule Profiler software

The Molecule Profiler software in SCIEX OS software provided an orthogonal workflow for detecting metabolites by searching for precursor compounds that also share characteristic fragments from the parent CBZ structure such as m/z 194.0941, 192.0795 and 179.0725. These fragments are commonly observed in the MS/MS spectra of CBZ metabolites in the published literature.^1-4 As shown in Figure 5, the software used in silico biotransformation pathways to predict a list of expected cleavage metabolites, such as DiOH-CBZ, which could not be previously confirmed by MS/MS library matching due to its absence in the reference spectral library. Table 4 shows a list of metabolites identified based on good mass error (<5 ppm) and comparison between in silico fragmentation of the predicted candidate structure and the MS/MS spectra. In addition to the same metabolites found by the Analytics module, Molecule Profiler software tentatively identified additional metabolites such as C₁₄H₁₃NO₃ and C₁₅H₁₂N₂O₂ that were not previously targeted.

For example, a monohydroxycarbamazepine structure was predicted for the candidate compound C₁₅H₁₂N₂O₂, observed at m/z 253.0979 at a RT of 3.31 minutes. This peak was separate from its other structural isomers, EP-CBZ and oxcarbazepine (OX-CBZ), which elute at 2.98 and 3.98 minutes, respectively. All 3 isomers lose the carboxamide group (CONH3) to produce the fragment pairs at m/z 210.091 and 208.076. EP-CBZ and OXCBZ have been reported to produce additional major fragments at m/z 236.071 and 180.081, which were not observed in the experimental MS/MS spectrum here.^2,4 The lack of a reference MS/MS spectrum for library confirmation precluded further confirmation of the exact positional isomer of the monohydroxycarbamazepine. 

Overall, the Molecule Profiler software identified similar metabolites found by suspect screening in the Analytics module of SCIEX OS software and tentatively identified others, all without a priori knowledge of the analyte details. Both modules provide complementary approaches such as MS/MS library matching and in silico-based fragmentation pattern prediction to aid in the discovery of known and novel metabolites. The integration of Molecule Profiler software with SCIEX OS software enables the user to seamlessly transport their metabolite findings to the Analytics module for further library confirmation and updates of their spectral library with any novel metabolites identified, as shown in Figure 2.

Conclusion
 

• SWATH DIA of MS/MS spectra enables retrospective mining of previously acquired data for drug metabolites that were not targeted during the initial pharmaceutical drug screen
  
  
• Accuracies of ≥70% and LODs of ≤5 ng/L for the majority of the targeted drugs were achieved based on solvent spikes and were deemed adequate for the semi-quantitative screening of 105 pharmaceutical drugs in wastewater using SPE LCMS/MS
  
  
• Molecule Profiler software provided an automated workflow for metabolite identification without a priori knowledge of the analyte details for processing
  
  
• Integration of Molecule Profiler software with SCIEX OS software enabled a streamlined workflow for transferring metabolite findings to be orthogonally confirmed by interrogation of the MS/MS spectra using diagnostic fragment ions and library searching in the Analytics module of SCIEX OS software

References
 

1. Massano, M.; Salomone, A.; Gerace, E.; Alladio, E.; Vincenti, M.; Minella, M. (2023) Wastewater surveillance of 105 pharmaceutical drugs and metabolites by means of ultra-high-performance liquid-chromatography-tandem high resolution mass spectrometry. J. Chrom. A. 1693, 463896.
   
   
2. Miao, X-S.; Metcalfe, C.D. (2003) Determination of carbamazepine and its metabolites in aqueous samples using liquid chromatography-electrospray tandem mass spectrometry. Anal. Chem. 75, 3731-3738.
   
   
3. Breton, H.; Cociglio, M.; Bressolle, F.; Peyriere, H.; Blayac, J.P.; Hillaire-Buys, D. (2005) Liquid chromatographyelectrospray mass spectrometry determination of carbamazepine, oxcarbamazepine and eight of their metabolites in human plasma. J. Chrom. B. 828, 80-90.
   
   
4. Bahlmann, A.; Brack, W.; Schneider, R.J.; Krauss, M. (2014) Carbamazepine and its metabolites in wastewater: Analytical pitfalls and occurrence in Germany and Portugal. Wat. Res. 57, 104-114.
   
   
5. National Center for Biotechnology Information (2023). PubChem Compound Summary for CID 83852, Dihydroxycarbazepine. Retrieved April 18, 2023 from https://pubchem.ncbi.nlm.nih.gov/compound/Dihydroxycarba zepine.