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Oct 25, 2016 - ABSTRACT: Ion mobility spectrometry allows for the measurement of the collision cross section (CCS), which provides information about t...
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Ion mobility-derived collision cross section as an additional identification point for multi-residue screening of pesticides in fish feed Jorge Regueiro, Noelia Negreira, and Marc H.G. Berntssen Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.6b03381 • Publication Date (Web): 25 Oct 2016 Downloaded from http://pubs.acs.org on October 27, 2016

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Ion mobility-derived collision cross section as an additional identification point for multi-residue screening of pesticides in fish feed

Jorge Regueiro*, Noelia Negreira, Marc H.G. Berntssen

National Institute of Nutrition and Seafood Research (NIFES), PO Box 2029 Nordnes, N-5817 Bergen, Norway

*Corresponding author. Tel.: +47 99487709; fax: +47 55905299. E-mail address: [email protected]; [email protected] URL: http://www.nifes.no

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ABSTRACT Ion mobility spectrometry allows for the measurement of the collision cross section (CCS), which provides information about the shape of an ionic molecule in the gas phase. While the hyphenation of travelling-wave ion mobility spectrometry (TWIMS) with high-resolution quadrupole time-offlight mass spectrometry (QTOFMS) has been mainly used for structural elucidation purposes, its potential for fast screening of small molecules in complex samples has not yet been thoroughly evaluated. The current work explores the capabilities of ultra-high performance liquid chromatography (UHPLC) coupled to a new design TWIMS-QTOFMS for the screening and identification of a large set of pesticides in complex salmon feed matrices. A database containing TWIMS-derived CCS values for more than two hundred pesticides is hereby presented. CCS measurements showed high intra- and inter-day repeatability (RSD 1000 registered pesticides worldwide 3), but also because of the high complexity of these matrices, which generally account for above 30% fat 33. It is therefore necessary to explore new analytical strategies that allow a higher degree of confidence in the identification process to guarantee that novel fish feeds are free from pesticides and do not pose a risk to farmed fish, and ultimately to consumers. In the present work, we investigate the capabilities of ultra-high performance liquid chromatography (UHPLC) coupled to a novel design TWIMS-QTOFMS instrument (Vion IMS QTOF) for the screening of pesticides in salmon feeds. The use of TWIMS in combination with QTOFMS was demonstrated to provide an extra-dimension, resulting in increased peak capacity and selectivity, which is especially beneficial when screening for a large number of pesticides in a complex matrix such as salmon feed. A database including retention times, accurate masses, fragment ions and CCS values for over two hundred common pesticides and one synergist was 4 ACS Paragon Plus Environment

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generated. The potential of CCS as an additional identification point for pesticides was discussed. Finally, several salmon feed samples were analyzed in order to demonstrate the applicability of the proposed approach.

EXPERIMENTAL SECTION Chemicals, reagents and materials The analytical standards used in this study were purchased either individually or as multicomponent certified reference materials from various suppliers, including Dr. Ehrenstorfer GmbH (Augsburg, Germany), Sigma-Aldrich (Steinheim, Germany) and SPEX CertiPrep (Metuchen, NJ, USA). A mixture of them was prepared in acetonitrile at ca. 10 µg/mL and stored in amber glass vials at −25 ºC. Working standard solutions were made by appropriate dilution in acetonitrile or in 0.1% formic acid in water (v/v). Leucine-enkephalin, used as lock mass standard, and the instrument calibration solution (CCS Major Mix) were purchased from Waters (Manchester, UK). HPLC grade acetonitrile was obtained from Sigma-Aldrich and used for sample extraction. LCMS grade methanol and acetonitrile were purchased from Merck (Darmstadt, Germany). Ultrapure water (18.2 MΩ cm) was produced using a Milli-Q Gradient water purification system from Merck. LCMS grade ammonium acetate and acetic acid were obtained from VWR International (Oslo, Norway), and formic acid (98−100%) was purchased from Merck. Marvin software was used for drawing and characterizing chemical structures (v. 16.5.2.0, ChemAxon, Budapest, Hungary).

Sample collection and preparation Commercially available Atlantic salmon feed samples were obtained from the Norwegian National surveillance program conducted by NIFES on behalf of the Norwegian Food Safety Authorities and are representative samples from different manufacturers in Norway and the UK. Although the specific feed compositions were unknown, general current commercial salmon feeds consist of 5 ACS Paragon Plus Environment

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different proportions of marine ingredients (fishmeal, fish oil, fish protein concentrate, etc.) and plant ingredients (soybeans, sunflower meal, soy protein concentrate, rapeseed oil, etc.). The fat and protein contents of the analyzed samples ranged from 25% to 40% and from 32% to 40%, respectively. Feed samples were homogenized at 2,000 RPM using a stainless steel blender GRINDOMIX GM 300 from Retsch (Haan, Germany) and then stored in polypropylene containers at −25 ºC until further processing. On the day of the analysis, the samples were thawed at room temperature (20±2 °C) and 2.5 g were accurately weighed into a 15 mL polypropylene centrifuge tube. Then, 5 mL of acetonitrile/water/formic acid (75:24:1, v/v/v) were added and the sample was shaken for 1 h at 2,500 RPM in a multi-tube vortexer BenchMixer XL (Benchmark Scientific, NJ, USA). The tube was centrifuged at 3,000 RCF (Eppendorf 5810R, Eppendorf, Hamburg, Germany) for 5 min and the supernatant was then collected and stored at −25 ºC for 3 h in order to precipitate lipids and other macromolecules. A 0.5 mL aliquot was transferred into a 2 mL polypropylene microcentrifuge tube and diluted with 0.5 mL of 0.1% formic acid in water (v/v), yielding a cloudy suspension. After vortex shaking for 20 s, the tube was centrifuged at 18,000 RCF (Eppendorf 5427R, Eppendorf) for 5 min at 10 ºC and the clear supernatant was passed through 0.20 µm regenerated cellulose syringe filter into an autosampler vial.

UHPLC-TWIMS-QTOFMS analysis UHPLC was performed on ACQUITY UPLC I-Class system from Waters, consisting of a binary pump, a vacuum degasser, an autosampler and a column oven. Chromatographic separation of pesticides was carried out on a column ACQUITY UPLC BEH C18 (100 × 2.1 mm, 1.7 µm) also from Waters, maintained at 45 ºC. Water and methanol, both containing ammonium acetate (10 mM, pH 5.0), were used as mobile phases A and B, respectively. The following linear gradient was used: 0 min, 2% B; 0.25 min, 2% B; 12.25 min, 99% B; 13.00 min, 99% B; 13.01 min, 2% B, and 17.00 min, 2% B. The flow rate was set to 0.45 mL/min and the injection volume was 5 µL. 6 ACS Paragon Plus Environment

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The UHPLC system was coupled to the recently released hybrid mass spectrometer Vion IMS QTOF from Waters. The LockSpray ion source was operated in positive electrospray ionization (ESI) mode under the following specific conditions: capillary voltage, 0.45 kV; reference capillary voltage, 3.00 kV; cone voltage, 10 V; source offset, 80 V; source temperature, 110 °C; desolvation gas temperature, 450 °C; desolvation gas flow, 900 L/h, and cone gas flow, 40 L/h. Nitrogen (>99.5%) was employed as desolvation and cone gas. For the TWIMS separation, the following settings were applied: trap bias, 40 V; stopper height, 40 V; gate height, 40 V; trap wave velocity, 100 m/s; trap pulse height A, 20 V; trap pulse height B, 5 V, IMS wave velocity, 250 m/s; IMS wave height, 45 V; gate release, 2 ms, and nitrogen (>99.5%) as trap and IMS buffer gas at 1.6 L/min and 25 mL/min, respectively. CCS calibration was performed regularly using a mixture of calibrants (Table S-1, Supporting Information) prepared in acetonitrile/water/formic acid (50:49.9:0.1, v/v/v). The Vion IMS QTOF constitutes the thirdgeneration of the hybrid TWIMS-MS system, where the TWIMS cell is placed for the first time between the StepWave ion guide and the quadrupole (Fig. S-1, Supporting Information). By locating the TWIMS cell before the high vacuum region, it is possible to apply a higher nitrogen pressure (~3.3 mbar) in the separation cell, without the need of a previous helium-filled chamber like in the second-generation TWIMS-MS system (Synapt G2) 34. Data were acquired in high-definition (HD)MSE mode in the range m/z 50−1000 at 0.2 s/scan. Thus, two independent scans with different collision energies (CE) were alternatively acquired during the run: a low-energy scan (CE 4 V), to monitor the protonated molecules and other potential adducts, and a high-energy scan (CE ramp 8−45 V), to fragment the ions travelling through the collision cell. Argon (≥99.999%) was used as collision-induced dissociation (CID) gas. The TOF analyzer was operated in the sensitivity mode, providing an average resolving power (m/∆m) in the scanned m/z range of approximately 40,000 full width at half maximum (FWHM). Calibration of the TOF analyzer was carried out regularly by infusion (10 µL/min) of the corresponding calibration solution according to the manufacturer’s guidelines. For lock mass correction, a 100 ng/mL standard 7 ACS Paragon Plus Environment

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solution of leucine-enkephalin in acetonitrile/water/formic acid (50:49.9:0.1, v/v/v) was continuously infused (5 µL/min) through the reference probe and scanned every 30 s. Dual point correction upon leucine-enkephalin CID fragmentation at 25 V was conducted using the product ions at m/z 397.1870 (C21H25N4O4+) and m/z 120.0808 (C8H10N+). According to instrument specifications, mass measurement accuracy better than 1 ppm root mean square (RMS), based on 10 consecutive repeat measurements of the [M+Na]+ ion of raffinose (m/z 527.1588), should be achieved under these conditions. Data acquisition and processing were performed with UNIFI software (v. 1.8, Waters).

RESULTS AND DISCUSSION For the analysis of pesticides in the EU, the guidance document SANTE/11945/2015 sets criteria for the identification of pesticides by chromatography coupled to MS, which are based on retention time tolerances and different spectrometric requirements (diagnostic ions, ion ratios, mass accuracy, etc.) depending on the MS system used 35. Given the large number (>1000) of registered pesticides, as well as the potentially unlimited number of interferences from complex matrices such as salmon feed, more stringent requirements are being applied to reduce the rate of false-positive detections. In this regard, it was assessed whether the hyphenation of TWIMS with QTOFMS would provide a higher degree of confidence in the identification workflow. To evaluate the suitability of this approach, a total of 223 pesticides belonging to different chemical families and one pesticide synergist were considered (Table S-2, Supporting Information). Different standard mixture solutions were prepared at 100 ng/mL in 0.1% formic acid in water (v/v) and analyzed by UHPLCTWIMS-QTOFMS. The novel geometry of the TWIMS-QTOFMS system used in the current work, allows applying higher wave amplitudes (hence electric fields), which results in higher IMS resolving power (CCS/∆CCS) than the first-generation TWIMS-MS system (Synapt HDMS), without producing significant ion fragmentation during the separation process. Still some fragmentation can be expected for some labile pesticides during the different stages of the ESI8 ACS Paragon Plus Environment

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TWIMS-QTOFMS analysis. If dissociation occurs before the TWIMS cell, fragments would present shorter drift times than the precursor ion as they have greater mobilities. Instead, when dissociation occurs after the TWIMS cell, the drift time of the fragment ions would match that of the precursor ion. If the precursor ion dissociates during the TWIMS separation, then the resulting fragment ions would have drift times between these two extremes. For instance, Fig. 1 illustrates the extracted ion mobiligrams obtained for protonated hexazinone (m/z 253.1659) and one of its major fragments observed during the low-energy scan (m/z 171.0877). As it is shown, two peaks were obtained for this fragment ion at drift times of 3.50 ms and 4.79 ms, respectively. The one at earliest drift time would correspond to a fragment formed before the TWIMS cell, either in the ESI source (in-source fragment) or in the trap region. The last one corresponds to a fragment formed after the TWIMS separation due to, for example, the low collision energy (4 V) applied to ensure a proper ion transmission through the argon-filled collision cell. When such a situation exists, the UNIFI software automatically selects the fragment ion matching the drift time of the precursor ion to guarantee a proper assignment of the fragment ions during the screening workflow.

Ion mobility-derived CCS values for pesticides While the majority of applications of TWIMS have utilized the ion mobility as a separation technique, few efforts have been made so far on developing TWIMS-derived CCS databases to facilitate the use of ion mobility measurements for identification and characterization purposes 24-26. Out of the 224 compounds analyzed in the present work, 184 were characterized by the corresponding protonated molecules, whereas sodium and ammonium adducts were selected when the [M+H]+ ions were either absent or present in very low abundance. Some pesticides (bendiocarb, carbaryl, diethofencarb, methiocarb and promecarb) were entirely fragmented before the TWIMS cell (in-source fragmentation), so the corresponding fragments were used instead. The type of adduct, molecular formula, retention time, exact mass, main fragment ions and average measured CCS values (n=20) for all the studied pesticides are displayed in Table S-2 (Supporting 9 ACS Paragon Plus Environment

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Information). As shown, the CCS values ranged from 122.4 Å2 for the promecarb in-source fragment ion to 308.7 Å2 for doramectin. To study the correlation existing between m/z and CCS, the experimentally determined CCS values were plotted as a function of m/z, and the corresponding coefficient of determination (R2) was calculated (Fig. 2). The CCS values of the ions were found to strongly correlate (R2= 0.9341) with their corresponding m/z values. In TWIMS, the smaller ions are carried by the travelling wave, exiting the cell earlier, whereas the bigger ions ‘roll over’ the wave, thus taking longer to move through the gas-filled mobility cell. This explains the high correlation that is generally observed between m/z and CCS for small molecules presenting certain structural rigidity

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although this correlation is very high, relying on m/z alone to predict CCS is insufficient as many ions have the same m/z but a different 3D structure. While drifting, compact ions undergo fewer collisions with the buffer gas than more extended ions, and therefore traverse the TWIMS cell faster. This principle can allow for the separation of species with identical mass but different structure, as shown in Fig. 3. As can be observed, ipconazole and tebufenpyrad have the same molecular formula, but their corresponding [M+H]+ ions present different drift times in TWIMS. As clearly shown using a surface model, ipconazole has a more compact structure than tebufenpyrad, so it experiences fewer collisions, which results in a smaller CCS value. When plotting the measured CCS values for all the pesticides against their chromatographic retention times (Fig. S-2, Supporting Information), very poor correlation was observed (R2= 0.4092) and, in most cases, different CCS values were obtained for co-eluting compounds. These results indicate that TWIMS provides an additional separation dimension that increases peak capacity and selectivity. However, in order to be able to use CCS as an additional identification point for the analysis of pesticides, it is necessary to demonstrate the precision of the CCS measurements. Thus, the intraday precision was evaluated from the analysis of five replicates of a standard mixture solution (100 ng/mL) on the same day, whereas the inter-day precision was assessed from analyses performed over five days, with three replicates per day. For intra-day measurements, the relative standard 10 ACS Paragon Plus Environment

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deviation (RSD) of the CCS values was ≤0.3% for 177 pesticides, between 0.3% and 0.5% for 38 pesticides, and between 0.5% and 0.7% for only 9 compounds. Excellent inter-day precision was also observed (Fig. 4), with RSD values below 1% for all the pesticides, and most of them ranging from 0.3% to 0.5%. Similar results in terms of CCS precision were obtained by Paglia et al.

24,25

,

who proposed CCS as a robust additional measurement for the identification of metabolites and lipids in metabolomics studies. Contrasting DTIMS, the exact ion drift mechanisms in TWIMS are not yet fully understood. As a result, TWIMS CCS values cannot be directly derived from the measured drift times of the analytes as it is done in DTIMS. Thus, in order to estimate CCS values using TWIMS, it is necessary to determine a calibration relationship between ions with known CCS values obtained on DTIMS instrumentation and the drift times measured in TWIMS. Although this calibration approach has now been established for several years, there is still some uncertainty as to how the choice of calibrant ions influences the accuracy of CCS values calculated from TWIMS drift times29,37,38. Several studies have shown that using calibrant ions with similar physical properties as the analytes may result in significantly smaller errors in calibrated CCS values29,37,39. In the present work, calibration of the TWIMS measurements was performed automatically during the regular instrument setup using a mixture of small molecules, poly-DL-alanine oligomers (n=7-16) and perfluoroalkylphosphazines (Table S-1, Supporting Information). In order to assess the accuracy of the CCS values estimated with these calibrants, they were compared to the DTIMS CCS values in nitrogen for pesticides available in the literature40,41. As can be observed in Table 1, the TWIMSderived CCS values for these pesticides matched the literature DTIMS CCS values within ±2.3% error, and 14 out of 20 compounds matched within ±1.0% error. Therefore, the calibration approach used in the present work seems to provide accurate CCS measurements for pesticides. Indeed, our results show the power of TWIMS in separating and distinguishing pesticides, which could therefore provide an additional tool for their identification in screening studies. Goscinny et al.

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pesticides in fruits and vegetables. However, drift times are instrument/conditions dependent, so the use of CCS values constitutes a more robust approach that can be used across multiple platforms and conditions. To the best of our knowledge, this paper provides for the first time a TWIMSderived CCS database for pesticides.

Screening of pesticides in fish feed by UHPLC-TWIMS-QTOFMS Once the database including retention times, exact ion masses, fragment ions and CCS values had been established (Table S-2, Supporting Information), the suitability of UHPLC-TWIMSQTOFMS for the qualitative screening of pesticides in complex matrices such as fish feed was evaluated. Eight different fish feed samples were first analyzed to guarantee the absence of the studied pesticides, spiked with a mixture of 223 pesticides and one synergist (0.100 mg/kg), and then analyzed in duplicate following the method described in the Experimental Section. As the main aim of these experiments was to assess the robustness of CCS as an additional identification point for the analysis of pesticides in complex matrices, recovery and precision of the method were not considered in the current work.

Fig. S-3 (Supporting Information) displays the total ion

chromatogram (TIC) for a typical salmon feed sample, which shows the complexity of this matrix. The CCS difference (∆CCS) between the database CCS and the measured CCS in the spiked samples was below 1% for 84% of the analyzed pesticides and below 1.8% for all the rest (Fig. S-4, Supporting Information). These results indicate that the measured CCS values are not influenced by the sample matrix, even in very complex samples like fish feed, which can account for up to 40% fat. Therefore, a ±2% tolerance for ∆CCS seems to be a conservative criterion to be applied during the screening of pesticides. These findings are in line with previous results from Beucher and coworkers

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, who found high inter-matrix reproducibility for experimentally determined TWIMS

CCS values of growth promotors. These results also demonstrate the applicability of the reported CCS database for identification purposes.

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Furthermore, ion mobility data can be used as tool to effectively reduce spectral complexity observed in complex samples, simplifying the identification process of the pesticides. For instance, in many screening methods is common to use the DIA acquisition modes such as MSE or All-ionfragmentation, which alternate between low and high collision energy scans. At low collision energy, the accurate mass measurements of precursor ions are obtained, whereas at the high collision energy, the product ions for all precursors are obtained. The low- and high-energy spectra are then deconvoluted based on the retention time. However, in complex samples multiple compounds often have indistinguishable retention times. Consequently, the high collision energy scans may contain product ions corresponding to multiple precursor ions at a given retention time, complicating the identification process. To overcome this problem, TWIMS allows the drift time separation of many co-eluting precursor ions. As the TWIMS separation occurs before the CID fragmentation, precursor and product ions present the same drift time. Thus, low- and high-energy spectra are both retention time- and drift time-aligned to filter out fragments that do not match the precursor’s drift time. Fig. 5 shows the low- and high-energy spectra obtained for azoxystrobin with and without drift time filtering in one of the spiked fish feed samples. As can be observed, the drift time alignment resulted in much cleaner spectra at both collision energy conditions, which highly simplifies the identification process. Finally, ten real commercial and representative salmon feed samples were analyzed in order to demonstrate the applicability of the proposed UPLC-TWIMS-QTOF approach for screening of pesticides. An important issue to consider during the development of screening methods is the falsepositive rate, which should be kept as low as possible in order to avoid unnecessary follow-up actions for identification and confirmation. The use of isotopic pattern match and fragmentation information have been shown to be effective ways of reducing false-positive detections 4. However, the detectability is generally reduced due to the lower abundance of the isotopes and/or the product ions. This can be particularly critical for those pesticides that are only detected as sodium adducts, due to their poor/null fragmentation. Therefore, the application of CCS filtering (∆CCS ≤ 2%) in 13 ACS Paragon Plus Environment

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addition to mass accuracy and retention time, can be helpful to increase the selectivity and decrease the false-positive rate. For instance, several feed samples displayed a peak at m/z 315.067 that produced a detection hit for malaoxon using tolerances of ±5 ppm and ±0.1 min (Fig. S-5, Supporting Information). Due to the low abundance of the protonated molecule, no fragments information was obtained during the high-energy scan, so its positive identification would require an additional analysis using, for example, a higher concentration factor. However, based on CCS measurement this hit could be identified as a false positive (CCSexp= 171.2 Å2, CCSdatabase= 164.3 Å2) eliminating the need for further investigations on the identity of the unknown compound. As shown in Table 2, several pesticides in our database could be positively identified by following the identification criteria established by the EU guidance document SANTE/11945/2015

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, i.e.

retention time tolerance ≤0.1 min, mass accuracy for the detected adduct ≤5 ppm and at least one detected fragment ion. In addition, a ±2% tolerance for the ∆CCS was applied in order to provide a higher degree of confidence in the identification process and to decrease the likelihood of falsepositive results. Among them, ethoxyquin was the most frequently detected compound, being present in eight out of ten fish feed samples. Ethoxyquin is a fungicide applied as a postharvest treatment to fruit entering cold storage as a scald preventive agent, but it is also authorized in the EU as a synthetic antioxidant in animal feed. Earlier studies have also reported the overall presence of this compound in fish feed samples 43,44 as well as its transfer from feed to fish 44,45. Another compound showing a high detection frequency was the organophosphate insecticide pirimiphos-methyl, which was identified in six of the analyzed samples. Pirimiphos-methyl is known to be one of most frequently detected pesticides in crops

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, and it has been previously

reported in fish feed samples and farmed fish tissues 43,44. Tebuconazole, a triazole fungicide widely used in cereals, was also identified in five out of ten samples. Although its presence in cereals and dry animal feed has been earlier documented

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, this is the first time that tebuconazole is

identified in fish feed. Piperonyl butoxide, a synergist used in many pesticides formulations, was 14 ACS Paragon Plus Environment

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also found in three of the analyzed samples. To our knowledge, this compound is also reported for the first time in fish feed samples.

CONCLUSIONS In the current study, UHPLC coupled to a novel generation TWIMS-QTOFMS instrument was applied for fast screening and identification of more than 220 pesticides in fish feed. The use of TWIMS-derived CCS values was proven for the first time as an additional identification point to be included in the pesticides screening workflow, thus increasing the confidence in the pesticide assignment. This paper provides for the first time a TWIMS-derived CCS database for a large set of pesticides. Unlike TWIMS drift times, which are instrument/conditions dependent, CCS values can be used across multiple platforms and conditions for identification purposes. The CCS measurements showed high intra- and inter-day precision (RSD