Optimization of a Differential Ion Mobility SpectrometryâTandem Mass

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Optimization of a differential ion mobility spectrometry–tandem mass spectrometry method for high-throughput analysis of nicotine and related compounds: Application to electronic cigarette refill liquids Jorge Regueiro, Anupam Giri, and Thomas Wenzl Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.6b01241 • Publication Date (Web): 13 May 2016 Downloaded from http://pubs.acs.org on May 15, 2016

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Analytical Chemistry

Optimization of a differential ion mobility spectrometry–tandem mass spectrometry method for high-throughput analysis of nicotine and related compounds: Application to electronic cigarette refill liquids

Jorge Regueiro, Anupam Giri, Thomas Wenzl*

European Commission, Directorate General Joint Research Centre, Institute for Reference Materials and Measurements, Retieseweg 111, B-2440 Geel, Belgium

*Corresponding author. Tel.: +32 14 571320 E-mail address: [email protected] (T. Wenzl)

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ABSTRACT Fast market penetration of electronic cigarettes is leading to an exponentially growing number of electronic refill liquids with different nicotine contents and an endless list of flavors. Therefore, rapid and simple methods allowing a fast screening of these products are necessary to detect harmful substances which can negatively impact health of consumers. In this regard, the present work explores the capabilities of differential ion mobility spectrometry coupled to tandem mass spectrometry for high-throughput analysis of nicotine and eleven related compounds in commercial refill liquids for electronic cigarettes. The influence of main factors affecting the ion mobility separation, such as modifier types and concentration, separation voltage, and temperature, was systematically investigated. Despite small molecular weight differences among the studied compounds, a good separation was achieved in the ion mobility cell under the optimized conditions, which involved the use of ethanol as polar gas-phase chemical modifier. Indeed, differential ion mobility was able to resolve (resolution >4) nicotine from its structural isomer anabasine without the use of any chromatographic separation. The quantitative performance of the proposed method was then evaluated, showing satisfactory precision (RSD ≤16%) and recoveries ranging from 85 to 100% for nicotine, and from 84 to 126% for the rest of the target analytes. Several commercial electronic cigarette refill liquids were analyzed to demonstrate the applicability of the method. In some cases, significant differences were found between labeled and measured levels of nicotine. Anatabine, cotinine, myosmine and nornicotine were also found in some of the analyzed samples.

Keywords: alkaloids, differential ion mobility spectrometry; field-asymmetric ion mobility spectrometry; tobacco; e-liquid; e-cigarette

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INTRODUCTION Electronic (e)-cigarettes are battery-powered devices that simulate tobacco cigarettes by converting liquid into an inhalable aerosol. The liquid (e-liquid) can be contained in a disposable cartridge or in a tank within the e-cigarettes device that can be refilled by the users 1. e-cigarettes are becoming increasingly popular in recent years as "healthier" alternatives to traditional tobacco cigarettes 2, as smoking cessation aids, and as a way to circumvent certain smoke-free laws 3. The rapid market penetration of e-cigarettes has led to an exponentially growing number of refill solutions containing different amounts of nicotine (NIC), typically in range from 0 mg/mL to 24 mg/mL. E-liquids are available in a huge variety of flavours that most often fall in five main categories: tobacco flavours (similar to cigarettes), fruit flavours (cherry, apple, etc.), menthol flavours, sweet flavours (candy, vanilla, chocolate, etc.) and beverages (coffee, black tea, wine, etc.). Due to the lack of standardization in the manufacture and quality control of e-cigarettes refill liquids, significant differences between the NIC content measured and declared on the labels have been recently reported 4,5. Nicotine in e-liquids is extracted from tobacco and this process may also extract other minor tobacco alkaloids, such as nornicotine (NNIC), anatabine (ATB), anabasine (ABS) and myosmine (MYO), and cause the formation of degradation products such β-nicotyrine, cotinine (COT) and nicotine-N-oxide 6. Oxidative degradation of nicotine can also occur during the manufacturing processes of e-liquids, and therefore, high amounts of nicotine-related compounds can indicate an inadequate handling and storage 1. In some cases, tobacco absolute extracts (also called natural tobacco extracts) are used as additives in tobacco-flavoured liquids to better simulate the tobacco flavour, which can result in higher amounts of nicotine-related impurities 7. For the determination of NIC and related compounds, liquid chromatography coupled to tandem mass spectrometry (LC–MS/MS) has been commonly employed in recent years, especially for biological matrices, such as urine, plasma and saliva 8-11, although some authors have also used LC‒ MS/MS for their analysis in e-cigarettes 7,12,13. 2 ACS Paragon Plus Environment


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An ongoing trend in analytical chemistry is the development of high-throughput mass spectrometry (MS)-based methods for simple and rapid determination of targeted chemicals in complex mixtures. As a result, the development of fast pre-separation techniques prior to MS is crucial, especially when analyzing low molecular weight compounds, where the probability of appearance of isobaric and isomeric interferences can be high

14

. In this regard, ion mobility spectrometry (IMS) has

emerged over the last decade as a viable alternative to chromatographic techniques in their hyphenation with MS. IMS separates ionized molecules based on their mobilities in the gas phase, typically at atmospheric pressure, in the presence of an electric field

15,16

. Under these conditions,

the mobility of an ion depends on its size, charge and shape, and therefore, IMS can be particularly useful to resolve isobaric and isomeric compounds in complex samples

17-19

. Ion mobility

separations can be accomplished at the millisecond timescale which makes the technique very attractive for high-throughput applications when interfaced to MS. In conventional ion mobility, ions move through a drift tube under a constant coaxial electric field of low strength in the presence of an inert buffer gas, typically at atmospheric pressure. During this process, ions are subjected to a number of collisions with the buffer gas that depend on the collision cross section of a given ion as well as on the nature of the buffer gas 15. Thus, the time required for ions to pass the ion mobility cell (i.e., drift time) will be different depending on the shape, size, and charge of the ions. Differential ion mobility spectrometry (DMS), also known as planar field-asymmetric ion mobility spectrometry (p-FAIMS), takes advantage of electric field-dependent ion mobility behavior under high electric field conditions. A number of studies have shown the utility of DMS coupled to MS in different applications, most of which have been recently reviewed by Schneider et al.

20

. The

filtering action of DMS can add sufficient selectivity to allow samples to be either infused directly or flow injected without a LC separation in order to increase sample throughput instance, Hall et al.

22

18,21-27

. For

successfully applied a DMS–MS/MS approach for the separation and

quantification of common metabolites of drugs of abuse in urine samples. Very recently, Da Costa 3 ACS Paragon Plus Environment

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et al.

28

developed a method for direct analysis of oil additives by FAIMS-MS combined with

electrospray ionization (ESI) and desorption electrospray ionization (DESI). DMS has also been used after LC as an orthogonal separation technique to achieve highly selective multidimensional separations 29-31. In an effort to further evaluate the analytical capabilities of this technique, an ESI-DMS–MS/MS method was developed and validated in the present work for rapid separation and quantification of NIC and eleven related compounds in e-cigarettes refill liquids.

EXPERIMENTAL SECTION Chemical and Reagents (+)-Anabasine hydrochloride (1.000 ± 0.005 mg/mL in methanol), (–)-cotinine (1.000 ± 0.005 mg/mL in methanol), cytisine (≥99%), 4,4′-dipyridyl (98%), 4-(methylnitrosamino)-1-(3pyridyl)-1-butanol (1.000 ± 0.005 mg/mL in methanol), myosmine (≥98%), (–)-nicotine (1.00 ± 0.05 mg/mL in methanol), N-nitrosoanabasine (≥99%), N-nitrosoanatabine (≥97%), (±)-Nnitrosonornicotine (1.000 ± 0.005 mg/mL in methanol) and (±)-nornicotine (1.000 ± 0.005 mg/mL in methanol) were purchased from Sigma-Aldrich (Diegem, Belgium). (R,S)-Anatabine (≥95%) was obtained from Cayman Chemical (Ann Arbor, MI, USA). The isotope-labeled standard (±)nicotine-D4 (100 µg/mL in acetonitrile) was also purchased from Sigma-Aldrich. Exact masses and chemical structures of the analyzed compounds are shown in Table 1. Individual stock solutions of each analyte (ca. 100 µg/mL) and a mixture of them were prepared in methanol and then stored in amber glass vials at −20 ºC. Working standard solutions were made by appropriate dilution in methanol/water/formic acid (80:19.9:0.1, v/v/v). Methanol (MeOH, LC–MS grade), absolute ethanol (EtOH, HPLC grade), 2-propanol (2-PrOH, HPLC grade), acetone (HPLC grade), acetonitrile (ACN, LC–MS grade) and ethyl acetate (AcOEt, HPLC grade) were purchased from VWR International (Leuven, Belgium). 2-butanol (2-BuOH, HPLC grade) and formic acid (FA, 98–100%) were obtained from Sigma-Aldrich. Ultrapure water 4 ACS Paragon Plus Environment


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was produced using a Milli-Q Gradient water purification system from Merck Millipore (Bedford, MA, USA). Regenerated cellulose membrane syringe filters (13 mm, 0.20 µm) were purchased from Grace (Lokeren, Belgium).

Sample collection and preparation Twelve e-cigarette refill liquids declaring on their labels nicotine concentrations from 0 to 18 mg/mL were purchased via internet shops from different vendors in the EU between February and April 2015. Approximately 10 mg of each sample were accurately weighed into a 100 mL volumetric flask and filled up to the mark with methanol/water/formic acid (80:19.9:0.1, v/v/v). An aliquot of each sample dilution was passed through a 0.20 µm regenerated cellulose syringe filter and stored in amber glass vials at −20 °C until analysis. For method validation, a pooled sample was prepared from five nicotine-free e-liquid samples, previously analyzed in order to guarantee the absence of NIC.

Differential Mobility Spectrometry–Mass Spectrometry (DMS–MS) DMS separation was performed in a SelexION differential ion mobility device from AB SCIEX (Darmstadt, Germany), which features a planar DMS cell with dimensions 1 × 10 × 30 mm for gap height, width and length, respectively. The DMS cell was coupled to a hybrid quadrupole linear ion trap mass spectrometer QTRAP 6500 (AB SCIEX) equipped with a IonDrive Turbo V ion source. The cell was mounted in the atmospheric pressure region between the curtain and the orifice plates of the mass spectrometer, using the vacuum drag (2.8 L/min) to provide the transport gas flow through the cell. Nitrogen (boil-off) was used as transport gas. Optimized DMS conditions were as follows: cell temperature, 110 °C; SV, 3950 V; DMS resolution enhancement, off; and DMS offset, 40 V. Ethanol was used as chemical modifier at 2% (v/v) in the transport gas, which corresponded to 260 µL/min to the curtain gas. For optimization of the DMS separation, the CoV was scanned from −60 V to +20 V in 0.3 V steps; at each increment of CoV, MS or MS/MS spectra were 5 ACS Paragon Plus Environment

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recorded and the obtained data were plotted in the form of ionograms (MS signal intensity versus CoV). For quantitative analysis, a characteristic CoV value ensuring optimal separation was selected for each target analyte ion. CoV values at the peak apex were determined after Gaussian smoothing (smoothing width, 0.5 points). The mass spectrometer was operated in the positive ESI mode under the following specific conditions: ion spray voltage, 4000 V; source temperature, 300 °C; curtain gas, 20 psi; ion source gas 1, 40 psi; ion source gas 2, 30 psi; declustering potential, 50 V and collision gas, medium. Nitrogen (boil-off) was employed as curtain and collision gas, whereas air (zero grade) was used as ion source gas 1 and 2. Quantitative experiments were performed in multiple reaction monitoring (MRM) mode using optimized MS/MS ion transitions. The dwell time was 10 ms and the pause between mass ranges was 20 ms. Additionally, full scan (m/z 100–300) experiments were carried out during the method development. An ultra-high performance liquid chromatography system Nexera X2 (Shimadzu Benelux, 'sHertogenbosch, The Netherlands) comprising two LC-30AD pumps, a DGU-20A degasser, an autosampler SIL-30AC and a column oven CTO-30A was used for flow injection analysis (FIA). Although chromatographic separation was not carried out, a C18 guard column (4 mm × 2 mm) from Phenomenex (Utrecht, The Netherlands) was installed to avoid any potential entrance of sample

particles

into

the

MS

system.

An

isocratic

mobile

phase

consisting

of

methanol/water/formic acid (80:19.9:0.1, v/v/v) was used at a flow rate of 250 µL/min, and the injection volume was 5 µL. For infusion experiments, a flow of 5 µL/min of a standard mixture solution (ca. 200 ng/mL) was delivered by the MS built-in syringe pump and combined with the LC flow via T-piece union. Instrument control and data acquisition were performed with Analyst software (v. 1.6, AB SCIEX). PeakView software (v. 2.1, AB SCIEX) was used for data processing, whereas MultiQuant software (v. 3.0, AB SCIEX) was used for processing of quantitative MRM data.



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RESULTS AND DISCUSSION Optimization of DMS separation Accounting for the inherent basicity of most of the studied compounds (pKa 4.8–10.2), the positive ESI mode was selected for their ionization in the present work. In all cases, the full scan spectra exhibited the corresponding protonated molecules [M+H]+ as base peaks. Optimization of the ESIMS/MS parameters was first carried out by infusion of individual standard solutions. Two MS/MS ion transitions were monitored for each compound; the most intense transition was used for quantification, while the other one was employed for identification (Table 2). During sample analyses, confirmation was accomplished by comparing the quantifier-to-qualifier transition ratios in samples to those of the calibration standards within the maximum permitted tolerances in accordance with Commission Decision 2002/657/EC 32, which was just used as a guide. DMS separation of the protonated molecules was next evaluated, aiming at achieving satisfactory gas-phase separation of the analytes in a short run time, without compromising detection sensitivity. The experimental conditions were systematically optimized by investigating the influence of main parameters affecting the separation process. Calculation of peak capacity was used to objectively assess the DMS separation performance. The peak capacity (PC) can be defined as the maximum number of peaks that can be separated within a given CoV range, as shown in Eq. 1 20, PC =

(CoV − CoV ) (1) FWHM

where the numerator provides the total spread of the peaks in the CoV space and the denominator represents the average width of peaks at half height. Eq. 1 shows that the PC can be improved by either increasing the spread of the peaks (CoVmax − CoVmin) or narrowing the peak width in the CoV space. In addition, the resolution (Rs) between NIC and ABS was as well considered for the optimization of the separation process. These two compounds are not only structural isomers, having therefore the same exact mass, but they also yield similar MS/MS spectra with many common product ions. Thus, although in lower abundance, the major MS/MS ion transitions of 7 ACS Paragon Plus Environment

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ABS are also present in the MS/MS spectrum of NIC, which may result in an overestimation of ABS in the presence of a large amount of NIC. Therefore, good resolution of these compounds is crucial to ensure a proper quantitation. Though the cell temperature, the transport gas type and the asymmetric RF waveform applied between the two electrodes (i.e., the SV) are known to play major roles in the DMS separation, the addition of an organic solvent into the transport gas has been recently reported to highly improve the separation power of the DMS

33-36

. Therefore, seven polar organic solvents (methanol, ethanol,

2-propanol, 2-butanol, acetonitrile, acetone and ethyl acetate) were first evaluated as chemical modifiers for the DMS separation of nicotine and related compounds. For this purpose, each modifier was added into the transport gas at 1.5% (v/v) and the CoV was scanned over the range of −60 to +20 V, while keeping constant the DMS cell temperature at 150 °C and the SV at 3600 V. As can be seen in Fig. 1A, in the absence of chemical modifiers the compounds are barely separated with CoV values spanning from −3.0 to +4.5 V (PC= 4). This indicates that the twelve analytes experience a relatively similar differential mobility within a narrow 7.5 V compensation voltage window. Conversely, the addition of polar modifiers into the transport gas caused, in general terms, an improvement in the separation of the target analytes (Fig. 1B–H). All component peaks were shifted towards more negative CoV values and spread over a wider range in the ionograms, resulting in an increased peak capacity. The observed separation enhancement can be explained by the dynamic clustering/declustering model, where neutral modifier molecules form clusters with analyte ions during the low field portion of the asymmetric RF waveform and decluster during the high electric field period 33,34. This process increases the collision cross section of the ion-molecule complexes as compared to the unclustered ions, increasing the overall differential mobility of the analyte ions and, in this way, improving their separation 14. Among the modifiers examined, ethanol provided the best separation in terms of peak capacity (PC= 17) followed by methanol (PC= 16), both providing at least a 3-fold improvement as compared to the separation without modifier (Fig. 1B–C). On the other hand, ethyl acetate showed the greatest total spread in the CoV space (25.6 V), 8 ACS Paragon Plus Environment


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but without resulting in a more efficient separation (PC= 10) due to the parallel increase in the peak widths (Fig. 1H). A similar trend was observed for acetonitrile and acetone, which yielded peak capacity values of 12 and 11, respectively (Fig. 1F–G). In addition, when the separation was carried out using ethyl acetate, acetonitrile or acetone as modifiers, peaks were rather noisy and in many cases split, which highly contributed to peak broadening. This might be the result of heterogeneous gas-phase cluster populations formed under these conditions. Therefore, the analyte ions might be spread out into a number of different cluster states, producing a broader distribution of ion mobilities 20. Although the addition of modifier into the transport gas enhanced peak capacity, a loss of absolute MS response was observed for all compounds compared to nitrogen alone. Methanol and ethanol produced a minimum loss in signal intensity, whereas the use of higher alcohols, 2-propanol and 2butanol, led to an important decrease. Low responses were also obtained with the rest of the tested modifiers. This effect is likely due to the proton transfer reactions occurring between the ions and the neutral modifier molecules, as it has been previously reported for other analytes during DMS separations 18,21. These data highlight the different ion-molecule chemistries that can occur with the addition of various organic modifiers, resulting in substantial differences in terms of signal intensity, CoV spread, peak widths and, even relative order of the target analytes in the ionograms. Finally, ethanol was selected as modifier for the DMS separation of nicotine and related compounds, as a good compromise between efficiency and detection sensitivity. It is known that the temperature of the transport gas is inversely proportional to the gas density thereby affecting the number of collisions of the ions with the transport gas. It also impacts the chemical interactions that occur, shifting clustering equilibrium in one direction or the other

20,37

.

Therefore, the effect of temperature on the DMS separation was evaluated at 110 ºC, 150 ºC and 190 ºC, while keeping the SV at 3600 V. Although the peak capacity at 150 ºC was slightly higher, it was observed that the separation in terms of peak distribution over the CoV span was better at 110 9 ACS Paragon Plus Environment

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ºC, yielding less overlapped peaks (Fig. 2). In addition, the resolution between the two isomeric compounds NIC and ABS was higher at the lowest temperature (Rs= 3.1), so 110 ºC was finally used for further experiments. It is noteworthy that not only the peak capacity but also the separation order of the analytes was altered by the temperature. Thus, while some compounds shifted to less negative CoV, others stayed fairly constant or even shifted to more negative values (Table S1, Supplementary Information). This fact highlights the possibility of altering the selectivity of the DMS separation just by changing the cell temperature. Fig. S1 (Supplementary Information) illustrates the change in the order of the peaks in the CoV space at the studied temperatures. The influence of the ethanol concentration on the separation efficiency was next investigated at 1%, 1.5% and 2% (v/v) in the transport gas. The use of higher percentages of modifier normally increases the risk for ion losses due to proton transfer reactions in the DMS cell. Among the tested concentrations, it was observed that higher amounts of modifier resulted in an improvement in peak shape and symmetry, and further increased the resolution between the NIC and ABS (Fig. S2, Supplementary Information). Therefore, 2% (v/v) was finally selected as modifier concentration. Under these conditions, the effect of the electric field strength was evaluated at SV ranging from 3000 to 4000 V (Fig. S3, Supplementary Information). As expected, better separation was obtained at higher SV, with peaks spanning within a 26.9 V window at the highest SV. Eventually, a SV of 3950 V was selected as the optimal value accounting for both peak capacity and sensitivity. Fig. 3A shows the MRM ionograms for the DMS separation of nicotine and related compounds under the optimized conditions. As can be observed, the analytes were spread from −20.4 V for NNAL to −46.2 V for MYO, showing a peak capacity slightly higher than 16, a satisfactory peak distribution and a resolution between the two isomeric compounds NIC and ABS above 4. The 2D contour plot of ion intensity as a function of CoV and m/z (full scan acquisition) illustrates the multidimensional nature of the data produced by DMS–MS (Fig. 3B).



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Quantitative analysis by DMS–MS/MS Once the optimal conditions for the DMS separation had been established, a quantitative method based on DMS–MS/MS was developed and its analytical performance evaluated. Samples were directly analyzed by DMS–MS/MS without any chromatographic separation, which allowed for a total analysis time below 1 min. This highly increases the overall analysis throughput for quantification, compared to conventional LC– or GC–MS assays, which generally require much longer analysis times 1,38,39. For this purpose, each MRM transition was assigned the characteristic CoV value of the corresponding analyte ion (Table 2). The variation in the specific CoV values was first assessed by calculating the relative standard deviation (RSD) from five DMS separations on the same day (within-day variability) and from analyses carried out over a 1-month period (between-day variability). In all cases the variation in the CoV values was below 1.5% (Table S2, Supplementary Information), allowing a very precise DMS filtration of the ions of interest prior to MS/MS analysis. The linearity of the method was tested using standard solutions at eight concentration levels evenly distributed in the approximate range of 9–900 ng/mL for all compounds except NIC, which was studied from 16.5 to 1649 ng/mL (Table S3, Supplementary Information). Calibration curves were constructed using the ratios of the peak area of the compounds to the peak area of the isotopelabeled internal standard. Determination coefficients (R2) >0.990 were obtained for all compounds using weighed (1/x) linear calibration curves. The lack-of-fit (LOF) test was applied to statistically decide whether the selected linear model was adequate to describe the experimental data. The test compares the variability of the proposed model residuals to the variability between observations at replicate values of the independent variable. Results of the LOF test for the calibration range considered, at a confidence level of 95 % are also shown in Table S3. Since p-values were greater than 0.05 for all compounds, the linear regression models appear to adequately fit the data.


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Although the proposed DMS–MS/MS method allows for a very fast analysis, it should be noted that the separation occurs after the ionization process, and therefore, matrix effects (ion suppression/signal enhancement in the source) may occur in case of co-elution of matrix constituents with the target analytes. In order to evaluate the matrix effects, an extract of a pooled eliquid sample was spiked at three concentration levels (0.3, 3 and 6 mg/mL; low, medium, and high, respectively) and the responses (Rse) were compared with those obtained for standard solutions (Rstd) at the same concentration levels. The percent matrix effect (%ME) was then calculated as (Rse/Rstd-1) × 100, where a negative result indicates ionization suppression and a positive result indicates signal enhancement 40. Despite the potential complexity of e-liquids and the lack of a preionization separation of the analytes, %ME was found not to be significant for any of the analytes, ranging from -8% for MYO to 7% for NATB (Table 3). This result can be easily understood if considering the enormous dilution factor applied during the sample preparation (ca. 10,000-fold). For applications involving more complex matrices, such as biological samples, or where lower limits of detection are required, the use of DMS–MS/MS may result in significant matrix effects. Due to the lack of certified reference materials (CRM), the trueness of the DMS–MS/MS method was assessed by recovery experiments using a pooled e-liquid sample spiked with all the target analytes at three concentration levels (0.3, 3 and 6 mg/mL; low, medium, and high, respectively). Recoveries were calculated by dividing the difference between the measured concentrations for spiked and non-spiked samples by the added concentrations. In all cases, recoveries were considered satisfactory, with values in the range of 84–126% (Table 3). For NIC, recovery varied from 85% at the lowest level to 100% at the intermediate concentration level. The precision of the method was evaluated both at repeatability and intermediate precision conditions from an e-liquid sample spiked with all the target analytes at three concentration levels (0.3, 3 and 6 mg/mL; low, medium, and high, respectively). Three subsamples of each concentration level were analyzed under repeatability conditions (same operator, same laboratory and same equipment) on five days. Homogeneity of variances was checked by Cochran test and 12 ACS Paragon Plus Environment


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2

then analysis of variance (ANOVA) was applied to estimate within-days variance ( σ within ) and 2 between-days variance ( σ between ). Repeatability was expressed as the percent relative standard

2 deviation (%RSDr) calculated by dividing the root square of σ within by the overall mean of the

determinations. Intermediate precision (%RSDIP) calculated by dividing the root square of the total 2

2 variance ( σ within + σ between ) by the overall mean of the determinations (Table 3). Both, repeatability

and intermediate precision were satisfactory, showing RSDs values ≤9 % and ≤15 %, respectively. The lower limit of quantification (LLOQ) of the method was defined as the lowest concentration of the calibration range (8–16 ng/mL, Table S3) with a required repeatability ≤20%. To verify that the assay was capable of complying with this requirement at the lowest concentration level, RSD values were calculated from 5 replicate injections at the LLOQ. RSD values were in all cases below 10% at this concentration level. It should be remarked that the sensitivity obtained with the proposed method is enough for a fast screening of e-cigarettes refill liquids, since most of the target analytes must be present at mg/mL levels to exert a physiological effect on the human body 41. Finally, a total of twelve e-cigarettes refill liquids purchased from different vendors in EU were analyzed by the proposed method in order to demonstrate its applicability (Table S4). NIC concentrations up to 12.76 mg/mL were measured in the analyzed samples. Among the studied nicotine related compounds, only ATB, COT, MYO and NNIC were detected in any of the samples, at concentrations in the µg/mL level. Measured concentrations of NIC were then compared with values declared by manufactures on their packages (Table S4). In some cases, significant differences were found between labeled and measured levels of NIC. For instance, L3 and L12 contained NIC concentrations significantly lower than declared, whereas L1, labeled as containing no NIC, presented NIC at 12.76 mg/mL. These findings indicate that information about NIC levels on product packages may be inaccurate, which highlights the importance of proper analytical tools to guaranty the quality of the products available on the market.


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CONCLUSIONS A DMS–MS/MS-based approach is proposed as a high-throughput analysis platform for the separation and quantification of NIC and eleven related compounds in refill liquids of e-cigarettes. Different modifiers have been assessed to improve the peak capacity and the separation power of DMS, and results indicate that different selectivity is provided as a function of the nature of the modifier. Among the tested modifiers, ethanol (2%) provided the best compromise between separation, peak shape and sensitivity. The positive impact of chemical modifiers was consistent with the recent literature in DMS. Cell temperature and SV were also found to present a significant effect in the DMS separation. Under optimal conditions, a good separation was achieved without any previous chromatographic separation, showing a peak capacity higher than 16 and a resolution between the two isomeric compounds, NIC and ABS, above 4. The proposed method allows for a whole run in less than 1 min without the need for re-equilibration, which highly increases the sample throughput as compared to conventional LC– or GC–MS methods. The suitability of the DMS–MS/MS approach for quantitative analyses was evaluated in terms of linearity, precision and recovery. Satisfactory intermediate precision (RSD ≤15%) and recoveries ranging from 85 to 100% for NIC, and from 84 to 126% for the rest of the target analytes were obtained. In order to demonstrate the applicability of the proposed method, several commercial e-cigarette refill liquids were analyzed, showing, in general, significant differences between the measured levels of NIC and the amounts indicated by manufacturers. The current work represents the first DMS separation of nicotine related compounds and shows the potential of DMS–MS/MS for the fast analysis of these compounds in e-cigarettes. Future work could involve the investigation of the feasibility of this technique for applications requiring highthroughput, such as clinical and forensic analysis.



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Page 16 of 26

ASSOCIATED CONTENT Supporting Information Table S1, effect of temperature on CoV and FWHM. Table S2, reproducibility of CoV under optimal conditions. Table S3, linearity evaluation of the proposed method. Table S4, analysis of several commercial e-cigarettes liquids. Figure S1, influence of temperature on the selectivity. Figure S2, influence of the percentage of ethanol on the separation of the target analytes. Figure S3, effect of the SV on the DMS separation of the target analytes.


Page 17 of 26

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REFERENCES (1) Famele, M.; Ferranti, C.; Abenavoli, C.; Palleschi, L.; Mancinelli, R.; Draisci, R. Nicotine Tob. Res. 2014, ntu197. (2) McNeill, A.; Brose, L.; Calder, R.; Hitchman, S.; Hajek, P.; McRobbie, H. Public Health England 2015. (3) Grana, R.; Benowitz, N.; Glantz, S. A. Circulation 2014, 129, 1972-1986. (4) Davis, B.; Dang, M.; Kim, J.; Talbot, P. Nicotine Tob. Res. 2014, ntu080. (5) Cheng, T. Tob. Control 2014, 23, ii11-ii17. (6) Etter, J. F.; Zäther, E.; Svensson, S. Addiction 2013, 108, 1671-1679. (7) Farsalinos, K. E.; Gillman, I.; Melvin, M. S.; Paolantonio, A. R.; Gardow, W. J.; Humphries, K. E.; Brown, S. E.; Poulas, K.; Voudris, V. Int. J. Environ. Res. Public. Health 2015, 12, 3439-3452. (8) Piller, M.; Gilch, G.; Scherer, G.; Scherer, M. J. Chromatogr. B 2014, 951, 7-15. (9) Xu, X.; Iba, M. M.; Weisel, C. P. Clin. Chem. 2004, 50, 2323-2330. (10) McGuffey, J. E.; Wei, B.; Bernert, J. T.; Morrow, J. C.; Xia, B.; Wang, L.; Blount, B. C. PLoS One 2014, 9, e101816. (11) Kataoka, H.; Inoue, R.; Yagi, K.; Saito, K. J. Pharm. Biomed. Anal. 2009, 49, 108-114. (12) Kim, H.-J.; Shin, H.-S. J. Chromatogr. A 2013, 1291, 48-55. (13) Kubica, P.; Kot-Wasik, A.; Wasik, A.; Namieśnik, J. J. Chromatogr. A 2013, 1289, 13-18. (14) Schneider, B. B.; Covey, T. R.; Nazarov, E. G. International Journal for Ion Mobility Spectrometry 2013, 16, 207-216. (15) Kanu, A. B.; Dwivedi, P.; Tam, M.; Matz, L.; Hill, H. H. J. Mass Spectrom. 2008, 43, 1-22. (16) Borsdorf, H.; Eiceman, G. A. Appl. Spectrosc. Rev. 2006, 41, 323-375. (17) Parson, W. B.; Schneider, B. B.; Kertesz, V.; Corr, J. J.; Covey, T. R.; Van Berkel, G. J. Rapid Commun. Mass Spectrom. 2011, 25, 3382-3386. (18) Porta, T.; Varesio, E.; Hopfgartner, G. r. Anal. Chem. 2013, 85, 11771-11779. (19) Li, H.; Giles, K.; Bendiak, B.; Kaplan, K.; Siems, W. F.; Hill Jr, H. H. Anal. Chem. 2012, 84, 3231-3239. (20) Schneider, B. B.; Nazarov, E. G.; Londry, F.; Vouros, P.; Covey, T. R. Mass Spectrom. Rev. 2015. (21) Bylda, C.; Thiele, R.; Kobold, U.; Bujotzek, A.; Volmer, D. A. Anal. Chem. 2015, 87, 2121-2128. (22) Hall, A. B.; Coy, S. L.; Nazarov, E. G.; Vouros, P. J. Forensic Sci. 2012, 57, 750-756. (23) Noestheden, M. R.; Headley, J. V.; Peru, K. M.; Barrow, M. P.; Burton, L. L.; Sakuma, T.; Winkler, P.; Campbell, J. L. Environ. Sci. Technol. 2014, 48, 10264-10272. (24) Smith, R. W.; Cox, L. B.; Yudin, A.; Reynolds, J. C.; Powell, M.; Creaser, C. S. Analytical Methods 2015, 7, 34-39. (25) Shvartsburg, A. A.; Smith, R. D. Anal. Chem. 2012, 84, 7297-7300. (26) Kafle, A.; Klaene, J.; Hall, A. B.; Glick, J.; Coy, S. L.; Vouros, P. Rapid Commun. Mass Spectrom. 2013, 27, 1473-1480. (27) Pang, N.; Yan, C. Int. J. Mass Spectrom. 2014, 362, 48-55. (28) Da Costa, C.; Turner, M.; Reynolds, J. C.; Whitmarsh, S.; Lynch, T.; Creaser, C. S. Anal. Chem. 2016, 88, 2453-2458. (29) Beach, D. G.; Melanson, J. E.; Purves, R. W. Anal. Bioanal. Chem. 2015, 407, 2473-2484. (30) Ray, J. A.; Kushnir, M. M.; Yost, R. A.; Rockwood, A. L.; Meikle, A. W. Clin. Chim. Acta 2015, 438, 330336. (31) Varesio, E.; Le Blanc, J. Y.; Hopfgartner, G. Anal. Bioanal. Chem. 2012, 402, 2555-2564. (32) EC. OJ 2002, L 221, 8–36. (33) Eiceman, G.; Krylov, E.; Krylova, N.; Nazarov, E.; Miller, R. Anal. Chem. 2004, 76, 4937-4944. (34) Schneider, B. B.; Covey, T. R.; Coy, S. L.; Krylov, E. V.; Nazarov, E. G. Anal. Chem. 2010, 82, 1867-1880. (35) Levin, D. S.; Vouros, P.; Miller, R. A.; Nazarov, E. G.; Morris, J. C. Anal. Chem. 2006, 78, 96-106. (36) Rorrer, L. C.; Yost, R. A. Int. J. Mass Spectrom. 2011, 300, 173-181. (37) Schneider, B. B.; Covey, T. R.; Coy, S. L.; Krylov, E. V.; Nazarov, E. G. Int. J. Mass Spectrom. 2010, 298, 45-54. 16 ACS Paragon Plus Environment


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(38) Trehy, M. L.; Ye, W.; Hadwiger, M. E.; Moore, T. W.; Allgire, J. F.; Woodruff, J. T.; Ahadi, S. S.; Black, J. C.; Westenberger, B. J. J. Liq. Chromatogr. Relat. Technol. 2011, 34, 1442-1458. (39) Smyth, T. J.; Ramachandran, V.; McGuigan, A.; Hopps, J.; Smyth, W. F. Rapid Commun. Mass Spectrom. 2007, 21, 557-566. (40) Chambers, E.; Wagrowski-Diehl, D. M.; Lu, Z.; Mazzeo, J. R. J. Chromatogr. B 2007, 852, 22-34. (41) Benowitz, N. L.; Hukkanen, J.; Jacob, P. Handb. Exp. Pharmacol. 2009, 29-60.


Page 19 of 26

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Table 1. Exact masses and chemical structures of the target analytes

Compound

Exact mass (u)

Compound

Exact mass (u)

Myosmine (MYO)

146.08

Cotinine (COT)

176.09

Nornicotine (NNIC)

148.10

N-Nitrosonornicotine (NNN)

177.09

4,4'-Dipyridyl (DIPY)

156.07

N-Nitrosoanatabine (NATB)

189.09

Anatabine (ATB)

160.10

Cytisine (CYS)

190.11

Anabasine (ABS)

162.12

N-Nitrosoanabasine NABS

191.11

162.12

4(Methylnitrosamino)1-(3-pyridyl)-1butanol (NNAL)

209.12

Nicotine (NIC)

Structure

Structure



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 20 of 26

Table 2. Specific MRM conditions and compensation voltage values for the determination of nicotine and related compounds

Compound MYO

NNIC

DIPY

ATB

ABS

NIC

NIC-D4* COT

NNN

NATB

CYS

NABS NNAL

Q1/Q3 (m/z)

EP (V)

CE (eV)

CXP (V)

5

35

5

5

30

12

149.1/80.0

a

10

28

10

149.1/132.1

10

20

18

157.1/130.1a

5

35

12

157.1/77.0

5

40

10

161.1/144.0a

12

20

15

161.1/80.0

12

40

10

12

20

12

12

25

5

12

22

15

163.1/106.1

12

20

5

167.1/136.1a

12

25

15

167.1/84.0

12

30

5

177.1/80.0a

12

32

10

177.1/98.0

12

30

12

12

15

15

12

28

12

10

15

12

190.1/79.1

10

40

10

191.1/147.9a

12

20

18

191.1/133.0

12

40

15

192.1/162.1a

10

15

12

192.1/133.1

10

30

12

a

10

32

10

147.1/105.0

a

147.1/129.9

163.1/146.0

a

163.1/94.1 163.1/132.1

178.1/148.1

a

a

178.1/120.1 190.1/160.1

210.1/93.0

a

T1/T2 ± tol.b

CoV (V)

2.2 ± 0.3

-46.2

1.8 ± 0.2

-40.6

1.2 ± 0.1

-38.2

3.1 ± 0.5

-43.3

0.9 ± 0.1

-46.0

2.2 ± 0.3

-36.0

1.8 ± 0.2

-36.5

3.1 ± 0.5

-34.0

1.7 ± 0.2

-30.2

1.4 ± 0.1

-29.0

4.5 ± 0.7

-25.6

2.2 ± 0.3

-27.5

1.6 ± 0.2 -20.4 210.1/149.0 10 20 12 *Isotope-labeled standard a Quantifier transition; EP= entrance potential; CE= collision energy; CXP= collision exit potential; CoV= compensation voltage b Quantifier-to-qualifier transition ratios and tolerances for positive identification


Page 21 of 26

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48


Table 3. Matrix effects, recovery, repeatability and intermediate precision of the proposed method.

Compound

%ME

Recovery (%)

RSDr (%)

RSDIP (%)

Medium 2

High -3

Low

Medium

High

Low

Medium

High

Low

Medium

High

MYO

Low -8

84

90

86

8

5

4

9

6

7

NNIC

-3

6

4

117

111

114

6

3

7

12

7

7

DIPY

6

-4

-3

126

117

115

8

4

4

15

9

8

ATB

4

-7

-6

125

114

109

6

3

4

11

6

7

ABS

5

3

-4

112

116

111

6

4

2

13

7

5

NIC

-7

5

-5

85

100

98

4

3

4

10

6

6

COT

2

-4

3

124

118

115

8

3

2

12

6

7

NNN

-4

6

-3

125

119

114

7

4

3

10

8

5

NATB

-5

7

5

126

116

113

7

3

3

9

6

8

CYS

-1

-6

-4

125

126

120

2

4

4

7

7

8

NABS

6

-3

-5

115

107

104

9

3

5

9

5

6

NNAL

3

1

6

111

119

114

6

3

2

12

4

4

20

ACS Paragon Plus Environment


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Page 22 of 26

Figure 1. DMS ionograms showing the effect of different organic modifiers on the separation of the target analytes. Conditions: separation voltage, 3600 V; cell temperature, 150 °C; modifier concentration, 1.5% (v/v).

Figure 2. DMS ionograms showing the effect of the ion mobility cell temperature on the separation of the target analytes and the resolution between the isomeric compounds NIC and ABS. Conditions: separation voltage, 3600 V; modifier, 1.5% (v/v) EtOH.

Figure 3. DMS separation of NIC and related compounds under optimized conditions: (a) MRM ionograms (b) 2D contour plot of ion intensity as a function of CoV and m/z (full scan acquisition). Conditions: separation voltage, 3950 V; modifier, 2% (v/v) EtOH; cell temperature, 110 °C.


Page 23 of 26

Figure 1

(a)

No m odiffier

1.4e6

8.0e5 Intensity (cts.)

Intensity (cts.)

(b)

MeOH

9.0e5

1.2e6 1.0e6 8.0e5 6.0e5 4.0e5

7.0e5 6.0e5 5.0e5 4.0e5 3.0e5 2.0e5

2.0e5

1.0e5

0.0

0.0

-60

-50

-30

-20 -10 CoV (V)

0

10

20

-60

1.8e5

6.0e5

1.6e5 1.4e5

5.0e5 4.0e5 3.0e5

0

10

20

(d)

1.2e5 1.0e5 8.0e4

2.0e4

0.0

0.0

-60

-50

-40

-30

-20 -10 CoV (V)

0

10

20

-60

(e)

2-BuOH

-50

-40

-30

-20 -10 CoV (V)

0

4.0e5 3.6e5

10

20

(f)

4.4e5

Intensity (cts.)

Intensity (cts.)

-20 -10 CoV (V)

4.0e4

1.0e5

ACN

3.2e5 2.8e5 2.4e5 2.0e5 1.6e5 1.2e5 8.0e4 4.0e4 0.0

-60

-50

-40

-30

-20 -10 CoV (V)

0

2.8e5

10

-60

20

(g)

Acetone

4.0e5 3.6e5 Intensity (cts.)

2.0e5 1.6e5 1.2e5

-50

-40

-30

-20 -10 CoV (V)

0

10

20

(h)

AcOEt

3.2e5 2.8e5 2.4e5 2.0e5 1.6e5 1.2e5

8.0e4

8.0e4

4.0e4

4.0e4 0.0

0.0

-60

-30

6.0e4

2.0e5

2.4e5

-40

2-PrOH

2.0e5

7.0e5

2.2e5 2.0e5 1.8e5 1.6e5 1.4e5 1.2e5 1.0e5 8.0e4 6.0e4 4.0e4 2.0e4 0.0

-50

2.2e5

(c) Intensity (cts.)

Intensity (cts.)

-40

EtOH

8.0e5

Intensity (cts.)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


-50

-40

MYO NNIC DIPY

-30

-20 -10 CoV (V)

0

ATB ABS NIC

10

20

-60

-50

-40

-30

COT NNN NATB

-20 -10 CoV (V)

0

10

20

CYS NABS NNAL



Figure 2

5.2e5

4.4e5

1.2e5

4.0e5

110 °C



(a)

NIC

1.4e5

4.8e5

3.2e5 2.8e5 2.4e5 2.0e5 1.6e5

8.0e4 6.0e4

ABS

4.0e4

1.2e5 8.0e4

2.0e4

4.0e4 0.0

0.0

-55

-45

-35

-25 -15 CoV (V)

-5

5

15

-55

-45

-35

1.4e5 7.0e5

150 °C

-5

5

15

(b)

NIC



-25 -15 CoV (V)

1.2e5

6.0e5

4.0e5 3.0e5

ABS

8.0e4 6.0e4 4.0e4

2.0e5

2.0e4

1.0e5 0.0

0.0

-55

-45

-35

-25 -15 CoV (V)

-5

5

15

-55

-45

-35

-25 -15 CoV (V)

-5

5

15

(c)

1.0e6

NIC

2.4e5

9.0e5 8.0e5

2.0e5

190 °C Intensity (cts.)


1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 24 of 26

6.0e5 5.0e5 4.0e5 3.0e5

1.6e5

1.2e5

8.0e4

ABS

2.0e5 4.0e4

1.0e5 0.0

0.0

-55

-45

-35

MYO NNIC DIPY

-25 -15 CoV (V)

-5

5

ATB ABS NIC

15

-55

-45

-35

COT NNN NATB

-25 -15 CoV (V)

-5

5

15

CYS NABS NNAL


Page 25 of 26

COT

Figure 3

(a)

5.5e5

NABS

5.0e5 4.5e5

ABS

1.5e5 1.0e5

MY O

2.0e5

NNAL

2.5e5

NNIC DIPY NIC

ATB

NNN

3.0e5

CY S

3.5e5

m/z

NATB

4.0e5

Intensity (cts.)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


5.0e4 0.0 -54

-50

-46

-42

-38

-34

-30

-26

-22

-18

-14

-10

245 240 235 230 225 220 215 210 205 200 195 190 185 180 175 170 165 160 155 150 145 140 135 130 125

(b)

NNAL NABS CY S

NATB NNN

COT

ABS

NIC ATB

DIPY NNIC

MY O

-54

-54

-52

-50

-50

-48

-46

-46

-44

-42

-42

CoV (V)

-40

-38

-38

-36

-34

-34

-32

-30

-30

-28

-26

-26

-24

-22

-22

-20

-18

-18

-16

-14

-14

-12

-10

-10

CoV (V)



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 26 of 26

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