Identification of emerging contaminants in the environment by LC/Q-TOF MS using suspect andnon-target screening workflows combined with commercial and open-source MS/MS libraries

Sascha Lege1, J.D. Berset2, Thomas Glauner3, Nicola Cimino4 and C. Zwiener1

1 Environmental Analytical Chemistry, Eberhard-Karls-University Tuebingen, Germany; 2 Water and Soil Protection Laboratory, Bern, Switzerland;3 Agilent Technologies Sales & Services GmbH, Waldbronn, Germany; 2 Agilent Technologies Italia S.p.A., Roma, Italy (nicola_cimino@agilent.com)

Environmental regulations focus on monitoring a limited number of well-known compounds whichrepresent only a small fraction of the anthropogenic chemicals found in the environment. In addition tothese priority compounds there are transformation and degradation products formed during wastewatertreatment or in the environment which are typically not monitored and often not even known. To obtaincomprehensive data on the chemical water quality, targeted analytical methods are complemented byuntargeted acquisition methods using high resolution LC/MS. Statistical software programs as well asaccurate mass compound databases and libraries for contaminants, known and theoretically predictedtransformation products are essential. In this work we show the use of commercial and open-sourcelibraries along with fragment prediction enabled by a new library conversion tool.

• HR Q-TOF LC/MS screening with an Agilent Q-TOF and the MassHunter Water Screening PCDL allowsthe identification of contaminants with high confidence.

• The MassHunter to MassBank converter allows the import and export of accurate mass MS/MSspectra in the NORMAN MassBank format. This was efficiently used to complement the PCDLcontent.

• Contaminant screening in WWTP effluents reveals information about the catchment area and theefficiency of the treatment process.

• This was confirmed by statistical data analysis using the Agilent Mass Profiler Professional statisticalsoftware program.

Introduction Conclusions

ExperimentalEffluents of wastewater treatment plants, receiving water from agricultural and urban areas, werecollected as 14-day composite samples. Separation was done using an Agilent 1290 Infinity UHPLCsystem coupled to an Agilent 6550 iFunnel Q-TOF LC/MS instrument. Acquisition was performed withpositive and negative ionization with All Ions MS/MS fragmentation. Data was evaluated using the Find-by-Formula data mining tool for target and suspect screening. For non-target screening data was minedusing the Find-by-Molecular Feature algorithm and further treated using the Mass Profiler Professional(MPP) statistical software. Identification of significant features was performed using the new AgilentWater Screening PCDL (G6882CA) combined with information downloaded from NORMAN MassBank.Open source library spectra were made available for the MassHunter data analysis software by acustom-made library conversion tool.

Figure 1: Schematic overview of the Target, Suspect and Non-Target workflow using the WaterScreening PCDL and open source libraries for compound identification.

Target screening for pesticides and PPCPsA subset PCDL with 390 entries was created from the Water Screening PCDL including all compounds forwhich reference standards were available. From the 390 targeted compounds, 315 were detected inpositive mode, and 75 were detected in negative mode. With a direct injection of 100 μL of water into theUHPLC Q-TOF MS system, more than 60% of the compounds could be quantified at or below 10 ng/L,another 35% of the compounds were detected between 10 and 100 ng/L. For most targeted compounds,one or more specifi c fragment ions could be used as qualifier ions, and generally mass accuracy of themolecular ions and fragments was better than 5 ppm.

MassHunter to MassBank converter

The MassHunter to MassBank converter was developed to simplify the upload of spectral data tocommunity-driven, open source data bases and libraries to enable spectral exchange and in generalcollaboration in the environmental space. At the same time the converter tool allows the integration ofaccurate mass MS/MS spectra from public repositories and predicted fragments or literature spectrainto a user derived PCDL. The PCDL is a central part of all data evaluation workflows to aid compoundidentification.

Results and Discussion

Figure 3: EIC chromatograms of molecular ion and fragments, MS peak spectra and calibration curvesfor ibuprofen (negative mode) and quinoxyfen (positive mode).

Figure 4: Overlay of precursor and fragment ion traces for valsartan in an effluent sample (A),coelution plot (B) and compound identification results including the co-elution score (C).

Based on the identifcation rules (figure 4), fourteen additional pharmaceuticals and metabolites wereidentified in the effluent samples. In addition the UV filter phenylbenzimidazole sulfonic acid, nine furtherpesticides, 2 perfluorinated compounds and several organophosphates were found. For the metamizolmetabolites N-fomyl-4-aminoantipyrin and N-Acetyl-4-aminoantipyrin or the sulfamethoxazole metaboliteN4-acetylsulfamethoxazole no accurate mass MS/MS spectra were available in the Water ScreeningPCDL and spectra were downloaded from NORMAN MassBank and converted into the PCDL format.Presence of the compounds in the effluent samples was successfully confirmed using the same All IonsMS/MS workflow and the same identification rules.

Figure 5: All Ions MS/MS identification results for N4-acetylsulfamethoxazole (A), N-acetyl-4-aminoantipyrin, and N-formyl-4-aminoantipyrin in the effluent samples based on accuratemass MS/MS spectra downloaded from NORMAN MassBank.

The chemical inventory of the WWTPs differed based on the catchment area as well as the seasonal useof pesticides and pharmaceuticals. This was also confirmed using the non-targeted feature findingalgorithm and multivariate statistics comparing the different WWTPs over the sampling period in theMass Profiler Professional software (figure 6). Significant features in the sample groups were identifiedby database searches using both, commercial and open-source libraries, sometimes resulting incomplementary identifications. Hierarchical clustering and similarity searches allowed the detection offurther compounds of emerging concern.

Figure 6: Normalized EIC chromatograms of the antiepileptic drug carbamazepine (A) and the pesticideazoxystrobin (B) over the course of the sampling period in the effluents of treatment plant AI(left) and PCA of water contaminants in the 4 treatment plants over all time points (C).

Accurate Mass Full Spectrum or All Ions MS/MS Acq.(LC/Q-TOF)

Profiling(MPP Statistical data evaluation)

Target and Broad Suspect Screen(Targeted Data Analysis)

Spectral verification(All Ions workflow

and/or library matching)

Molecular Ion Hypothesis(Molecular formula generation)

MS/MS Acquisition(Identification)

Water screening PCDL & External spectra(Norman MassBank)

Figure 2: Screenshot of the MassHunter to MassBank converter enabling the export of usercontributed spectra to NORMAN MassBank and the import of spectra into the MassHunterPCDL format.

Import into PCDL

Export to NORMAN MassBank

Negative All Ions MS/MS

Positive All Ions MS/MS

Suspect and Non-target screening – “What else is in my sample?”In a Broad Suspect screening data was re-analyzed looking for all remaining compounds included in theWater Screening PCDL. The availability of accurate mass MS/MS information is key for the identificationof potential candidates, and is either used in the All Ions MS/MS workflow for the extraction andalignment of EICs of the molecular ion and characteristic fragments, or for the library matching of anacquired accurate mass MS/MS spectrum against the reference spectra in the PCDL.

Identification based on:

Mass deviation < 5 ppm for precursorand fragments

Perfect co-elution (co-elution score > 90) Consistent ion ratios

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