Determination of mycotoxins in different food commodities by ultra-high-pressure liquid chromatography coupled to triple quadrupole mass spectrometry

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1 RAPID COMMUNICATIONS IN MASS SPECTROMETRY Rapid Commun. Mass Spectrom. 2009; 23: Published online in Wiley InterScience ( Determination of mycotoxins in different food commodities by ultra-high-pressure liquid chromatography coupled to triple quadrupole mass spectrometry Eduardo Beltrán, María Ibáñez, Juan Vicente Sancho and Félix Hernández* Research Institute for Pesticide and Water, University Jaume I, Avda. Sos Baynat, E Castellón, Spain Received 12 February 2009; Revised 7 April 2009; Accepted 7 April 2009 A rapid multianalyte-multiclass method with little sample manipulation has been developed for the simultaneous determination of eleven mycotoxins in different food commodities by using ultrahigh-pressure liquid chromatography coupled to triple quadrupole mass spectrometry (UHPLC/MS/ MS). Toxins were extracted from the samples with acetonitrile/water (80:20, v/v) 0.1% HCOOH and, after a two-fold dilution with water, directly injected into the system. Thanks to the fast highresolution separation of UHPLC, the eleven mycotoxins were separated by gradient elution in only 4 min. The method has been validated in three food matrices (maize kernels, dry pasta (wheat), and eight-multicereal babyfood (wheat, maize, rice, oat, barley, rye, sorghum, millet)) at four different concentration levels. Satisfactory recoveries were obtained (70 110%) and precision (expressed as relative standard deviation) was typically below 15% with very few exceptions. Quantification of samples was carried out with matrix-matched standards calibration. The lowest concentration successfully validated in sample was as low as 0.5 mg/kg for aflatoxins and ochratoxin A in babyfood, and 20 mg/kg for the rest of the selected mycotoxins in all matrices tested. Deoxynivalenol could be only validated at 200 mg/kg, due the poor sensitivity for this mycotoxin analysis. With only two exceptions (HT-2 and deoxynivalenol), the limits of detection (LODs), estimated for a signal-to-noise ratio of 3 from the chromatograms of samples spiked at the lowest level validated, varied between 0.1 and 1 mg/kg in the three food matrices tested. The method was applied to the analysis of different kinds of samples. Positive findings were confirmed by acquiring two transitions (Q quantification, q confirmation) and evaluating the Q/q ratio. Copyright # 2009 John Wiley & Sons, Ltd. *Correspondence to: F. Hernández, Research Institute for Pesticide and Water, University Jaume I, Avda. Sos Baynat, E Castellón, Spain. felix.hernandez@qfa.uji.es Contract/grant sponsor: Laboratory of Public Health, Valencia. Contract/grant sponsor: Generalitat Valenciana (Plataforma de Seguridad Alimentaria; contract/grant number: A-07/08. Mycotoxins are secondary metabolites produced by molds, without biochemical significance in fungal growth and development. 1 Mycotoxins have adverse effects on humans and animals and cause economic losses on crops due to their contamination. 1,2 Although they have existed since ancient times, the term mycotoxins appeared in 1960 when turkey poults died due to the ingestion of peanut contaminated with secondary metabolites from Aspergillus flavus. 1 Mycotoxins are compounds with various chemical structures and, therefore, various biological effects. 3 There are over 300 known compounds that grow under a wide range of climatic conditions on agricultural commodities. 2 Not all secondary metabolites from molds are toxic, so it is necessary to regulate those mycotoxins that can be dangerous for human health. 2,3 Aflatoxins have been classified as carcinogenic to humans, while ochratoxin A and fumonisins are classified as possible carcinogens by the International Agency for Research on Cancer. 4 Due to the serious effects on humans and animals, the European Commission (EC) has established the maximum permitted levels for several mycotoxins. 5,6 The main mycotoxins regulated are: aflatoxins, ochratoxin A, patulin, deoxynivalenol, zearalenone, fumonisins, and HT-2 and T-2 toxin (Table 1). It is therefore necessary to apply sensitive and reliable analytical methods able to reach the regulatory levels established by the EC. Some screening methods have been developed for mycotoxin determination, based on enzyme-linked immunosorbent assays (ELISAs) or immunoaffinity column-based analysis. Normally, they are focused on qualitative aspects, and require the use of liquid chromatography (HPLC) or gas chromatography (GC) for accurate quantification and/or correct confirmation of the compound detected. 3,7,8 In the last few years, HPLC has become the preferred technique for mycotoxins analysis, as it does not require the derivatization step typically applied in GC-based methods. 3 HPLC when coupled to mass spectrometry (MS), or preferably to tandem mass spectrometry (MS/MS), is an Copyright # 2009 John Wiley & Sons, Ltd.

2 1802 E. Beltrán et al. Table 1. Maximum levels for regulated mycotoxins in foodstuffs (intended for direct human consumption) according to EC/1881/2006 Commission Regulation Compound Maximum levels (mg/kg) Foodstuffs (cereals, dried fruit,..) Foods for infants and young children Aflatoxin B Sum aflatoxins (B 1,B 2,G 1 and G 2 ) Aflatoxin M Patulin Ochratoxin A Deoxynivalenol a 200 Zearalenone a 20 Sum fumonisins (B 1 and B 2 ) a 200 Sum toxins (HT-2 and T-2 Toxins) a EC/1126/2007 amending EC/1881/2006. excellent analytical tool within this field due to its already known advantages of high selectivity and sensitivity, substantial reduction of sample treatment, and reliable quantification and confirmation at the low concentrations required. 3,8 12 Nowadays, the trend in mycotoxin analysis is the development of multimycotoxin methods able to cover, in a single run, all mycotoxins considered by European Union (EU) food legislation. 11,12 However, several difficulties are found to reach this objective. First, very different maximum levels are admitted for mycotoxins as a function of their toxicity and type of food (e.g. babyfood has more restricted regulation). Second, the matrix food composition under study is also highly variable, and, finally, mycotoxins present a great diversity in their physicochemical properties. In this way, one of the main problems in multitoxin analysis is the extraction and purification for all analytes, which present great differences in their physicochemical properties. 11 To overcome this obstacle several authors prefer to avoid the purification step, injecting the crude extract. 10,11,13,14 However, injection of crude extracts forces careful consideration of the matrix effects caused by coelution of matrix components. This effect leads to suppression or, more rarely, enhancement of the ionization efficiency of the analyte, affecting the accuracy and precision of the results. 3,10,13 Therefore, to obtain a correct quantification it is necessary to compensate matrix effects. Some approaches are the use of internal standards (isotope-labelled analyte or other compounds with similar properties), matrix-matched standards calibration or the use of standard additions method. 3,15 The best way to compensate matrix effects seems to be the use of isotope-labelled mycotoxins as internal standards, as they normally present the same ionization behaviour as analytes. However, this approach presents an important drawback, the lack of isotope-labelled standards of all mycotoxins that may be included in a multimycotoxin method. 16 Matrix-matched standards calibration, i.e. a blank sample extract spiked with reference standards, is one of the most used approaches to compensate for matrix effects, 3,10,16,17 saving the laborious work of spiking each sample at different levels, as required in the standard additions method. Ultra-high-pressure liquid chromatography (UHPLC) presents the benefits of shorter run times, and narrower chromatographic peaks, which result in increased sensitivity and improved peak resolution. 14,18 Many applications of this recent technique have been reported in different fields such as food safety 14 or environmental analysis, 19,20 and it has also been applied to determination of mycotoxins very recently. 18,21 Ventura et al. 21 developed a UHPLC/MS/MS method for the analysis of aflatoxins and ochratoxin A in beer whereas Ren et al. 18 applied the same technique for the quantification of 17 mycotoxin contaminants in corn feeds and peanut butter. In both cases, a sample purification step was performed by solid-phase extraction (SPE). The aim of this paper is the development of a UHPLC/ MS/MS multianalyte method that allows the determination of eleven relevant EU-regulated mycotoxins in a single analysis in different sample matrices (maize kernels, dry pasta and multicereal babyfood). Until now, this analytical approach has not been applied to the determination of the analytes selected in this work in the three food matrices tested. Due to the wide range of physicochemical properties of the analytes, sample treatment has been minimized, and crude extracts have been directly injected into the LC/MS system, avoiding pre-concentration and purification steps. Matrix effects have been compensated using matrix-matched standards calibration for the correct quantification. After validation of the method in three sample matrices selected, it has been applied to the analysis of 18 samples. Special emphasis has been placed on the confirmation of positive findings. For this purpose, ion intensity ratios between the quantification (Q) and the confirmation transition (q) were calculated and compared to those of reference standards. EXPERIMENTAL Reagents and chemical All mycotoxins standards (>99% purity) were supplied by Sigma Aldrich (Madrid, Spain). Structures of the selected compounds can be found elsewhere. 8,13 HPLC-grade water was obtained from water passed through a MilliQ water purification system (Millipore Ltd., Bedford, MA, USA). HPLC-grade methanol (MeOH), HPLC-grade acetonitrile (ACN), acetic acid (>99.8%) and ammonium acetate (NH 4 Ac) (>99%) were purchased from ScharLab (Barcelona, Spain). Formic acid (HCOOH) (>98%) was obtained from Fluka (Buchs, Switzerland). Individually stock solutions, at around 100 mg/l, were prepared dissolving about 5, 10 or 25 mg of solid reference standard in 15, 100 or 250 ml of ACN, respectively. An intermediate mixed solution (MIX A) containing all aflatoxins at a concentration of 10 mg/l was obtained after mixing individual stock solutions and diluting with ACN. A similar procedure was carried out with OTA, ZEN, DON, HT-2 and T-2 (MIX B) (See Table 2 for abbreviations). The mixture standard solution (around 1 mg/l) was prepared by adding 1 ml of MIX A, 1 ml of MIX B, 1 ml of FB1 standard and 1 ml of FB2 standard (both at 10 mg/l), and diluting to 10 ml with water. Working standard solutions for LC/MS/ MS analysis and for fortification of samples were prepared by dilution of the 1 mg/l mixture solution with water. Stock

3 Table 2. Optimized MS/MS parameters for the eleven mycotoxins selected Determination of mycotoxins in foods by UHPLC/MS/MS 1803 Compound Retention time (min) Ionization mode Precursor ion Cone (V) Product ion Collision energy (ev) Ion ratio (Q/q) Aflatoxin G 2 (AFG2) 2.43 ESIþ [MþH] þ (Q) (q) 30 Aflatoxin G 1 (AFG1) 2.56 ESIþ [MþH] þ (Q) (q) 60 Aflatoxin B 2 (AFB2) 2.68 ESIþ [MþH] þ (Q) (q) 30 Aflatoxin B 1 (AFB1) 2.81 ESIþ [MþH] þ (Q) (q) 35 Deoxynivalenol (DON) 1.46 ESIþ 297.3[MþH] þ (Q) [MþNH 4 ] þ (q) 10 Ochratoxin A (OTA) 3.80 ESIþ [MþH] þ (Q) (q) 70 HT-2 Toxin (HT-2) 3.34 ESIþ [MþNH 4 ] þ (Q) (q) 15 T-2 Toxin (T-2) 3.59 ESIþ [MþNH 4 ] þ (Q) (q) 15 Fumonisin B 2 (FB2) 3.81 ESIþ [MþH] þ (Q) (q) 35 Fumonisin B 1 (FB1) 3.39 ESIþ [MþH] þ (Q) (q) 40 Zearalenone (ZEN) 3.77 ESI [M-H] (Q) (q) 30 Q: transition used for quantification; q: transition used for confirmation. and intermediate standard solutions were stored in a freezer at 208C, whereas working solutions were stored in a fridge. Instrumentation An UPLC TM system (Acquity, Waters, Milford, MA, USA) was interfaced to a triple quadrupole mass spectrometer (TQD, Waters Micromass, Manchester, UK) using an orthogonal Z-spray-electrospray interface. The LC separation was performed using an Acquity UPLC BEH C 18 analytical column (1.7 mm particle size, mm; Waters), at a flow rate of 300 ml/min. Mobile phase was a timeprogrammed gradient using A (H 2 O 0.5 mm NH 4 Ac, 0.1% HCOOH), and B (MeOH 0.5 mm NH 4 Ac, 0.1% HCOOH). The percentage of organic modifier (B) was changed linearly as follows: 0 min, 10%; 4 min, 90%; 4.1 min, 10%; 7 min, 10%. The injection volume was 20 ml. Drying as well as nebulising gas was nitrogen, obtained from a nitrogen generator. The gas flow was set to 1200 L/h. For operation in MS/MS mode, collision gas was argon (99.995%; Praxair, Madrid, Spain) with a pressure of approximately mbar in the collision cell. Experiments were performed by continuous positive/ negative polarity switching (switching time of 0.02 s). Capillary voltages of 3.5 kv (positive ionization mode) and 3.0 kv (negative ionization mode) were applied. The desolvation gas temperature was set to 5008C and the source temperature to 1208C. Temperature column was set to 408C. Dwell times of s/scan were chosen. MassLynx version 4.1 (Waters, Manchester, UK) software was used to process the quantitative data obtained from calibration standards and from samples. Samples Blank samples of maize kernels, dry pasta and eightmulticereal babyfood (wheat, maize, rice, oat, barley, rye, sorghum, millet) used in the validation experiments were purchased from different supermarkets in Castellon. Samples for analysis (at least 1 kg) were provided by the Laboratory of Public Health (Valencia, Spain). Analytical procedure The whole samples were thoroughly triturated using a homogenizer (model K55, Dito Sama, Aubusson, France). After that, 2.5 g triturated samples were accurately weighed (precision 0.1 mg) and transferred to centrifuge tubes (50 ml). Samples were extracted by shaking with 10 ml ACN/water (80:20) 0.1% HCOOH on a mechanical shaker (S.B.S. Instruments S.A, Barcelona, Spain) for 90 min, and then centrifuged at 4000 rpm for 10 min (Consul centrifuge, Orto-Alresa, Madrid, Spain). Afterwards, the supernatant extract was two-fold diluted with HPLC-grade water, taking an aliquot of 5 ml and diluting to 10 ml. After filtration through a 0.22 mm syringe nylon filter (Iso-disc, Supelco), 20 ml were directly injected into the UHPLC/ESI-MS/MS system. Calibration was performed using matrix-matched standards prepared from a two-fold diluted blank extract. Fortification of samples for recovery experiments was performed by delivering 1 ml of 1.25, 5, 50, 500 mg/l mixture standard solution to 2.5 g homogenized blank sample in order to yield fortification levels of 0.5, 2, 20 and 200 mg/kg, respectively. These fortified samples were equilibrated for 1 h prior to extraction. Validation study The validation study was carried out for the eleven selected mycotoxins in three food matrices: maize kernels, dry pasta and eight-multicereal babyfood. Linearity of the method was evaluated taking at least six matrix-matched standard solutions which were analyzed in duplicate in the following ranges: ng/ml for

4 1804 E. Beltrán et al. aflatoxins and ochratoxin, and ng/ml for the rest of compounds. It was considered satisfactory when correlation coefficients were higher than Precision (repeatability, expressed as relative standard deviation (RSD), in %) and recoveries were determined within-day by analyzing fortified blank samples in quintuplicate. This experiment was performed at three levels, 2, 20 and 200 mg/kg for maize kernels and dry pasta, or at four levels (0.5, 2, 20, and 200 mg/kg) in the case of babyfood. Recoveries between % with RSD lower than 20% were considered satisfactory, except for the 0.5 mg/kg level in babyfood, where acceptable recoveries were % according to the legislation. 22 The specificity of the method was evaluated by analyzing a blank procedure, a processed blank sample and a blank sample spiked at the lowest concentration validated. The limit of quantification (LOQ) was estimated for a signal-to-noise (S/N) ratio equal to 10 from selected reaction monitoring (SRM) chromatograms of samples spiked at the lowest concentration validated. The limit of detection (LOD) was estimated, from the same chromatograms, for an S/N ratio of 3. RESULTS AND DISCUSSION This work has been focused on mycotoxins in cereals and babyfood. Our previous experiments led to the conclusion that aflatoxin M1 required a different analytical approach to reach the sensitivity needed in agreement with the EC regulation (maximum level mg/kg in babyfood). In the case of patulin, electrospray ionization (ESI) was not satisfactory, hampering its inclusion in the multianalyte method developed in this article. These two analytes will be investigated in future works. Two product ions were acquired for each compound, avoiding the selection of product ions resulting from nonspecific losses (i.e. H 2 OorNH 3 ). Among them, the most abundant transition was used for quantification (Q) and the second one for confirmation purposes (q). Table 2 shows optimized MS parameters (precursor and product ions, cone voltage and collision energy) and the transitions selected together with their Q/q ratios for mycotoxins investigated in this work. Dwell times around 100 ms did not produce enough data points to define good UHPLC peaks. Thus, a dwell time of 30 ms was selected to obtain adequate peak shape, monitoring 20 SRM transitions in positive ionization mode in a single function and 2 SRM transitions in negative ionization mode. Moreover, the positive-negative switching time selected (only 20 ms) allowed the measurement of all compounds in a single run. LC optimization The wide range of physicochemical properties of mycotoxins, with quite different polarity and acidity characteristics, made it necessary to find a compromise between mobile phase composition (trying to achieve suitable chromatography retention) and MS response for the eleven mycotoxins under study. Better sensitivity was obtained for aflatoxins and DON when 0.5 mm ammonium acetate was added to the mobile phase. Moreover, the addition of small amounts of ammonium acetate avoided the formation of stable sodium adducts, especially in the case of DON, HT-2 and T-2 toxin, and favoured the formation of [MþNH 4 ] þ Optimization of MS/MS conditions Full scan and MS/MS spectra of analytes were obtained from infusion of individual 1 mg/ml methanol/water (50:50) solutions of each compound at a flow rate of 10 ml/min. Experiments were carried out in both positive and negative ionization modes. All selected compounds showed higher signals in positive ionization mode with the exception of ZEN, which showed more satisfactory behaviour in negative ionization mode. Therefore, to acquire the optimum SRM transitions for each analyte, it was necessary to work with positive/negative polarity switching along the chromatographic run. Although most of the ESI positive compounds presented an abundant [MþH] þ ion, it is important to note the formation of ammonium adducts in the group of trichothecenes, especially for trichothecenes A (HT-2 and T-2 toxin). DON presented formation of undesired sodium adducts, which could be minimized with the introduction of small quantities of ammonium acetate (0.5 mm) in the mobile phase. Two different precursor ions, [MþH] þ and [MþNH 4 ] þ, were selected for this compound to obtain the maximum sensitivity. Although some authors studied DON in negative ionization mode, 23,24 in our study the best results were obtained using positive ionization. Figure 1. Effect of the addition of formic acid (HCOOH) to the mobile phase on the response of mycotoxins.

5 Determination of mycotoxins in foods by UHPLC/MS/MS 1805 Figure 2. Effect of ph on the extraction efficiency of mycotoxins from maize kernels spiked at 200 mg/kg. Extraction solvent ACN/water (80:20) precursor ions. However, higher concentrations of this salt (in the range 1 5 mm) produced ionization suppression, so the concentration of ammonium acetate was optimized at 0.5 mm. We also studied the addition of different percentages of HCOOH to the mobile phase in order to increase the sensitivity for fumonisins. 8 The addition of 0.1% HCOOH increased the fumonisins signals five-fold (see FB1 and FB2, Fig. 1) and improved the peak shape. Other compounds, such as aflatoxins, also increased their peak area. On the contrary, OTA and thrichothecene toxins, like DON, HT-2 and T-2, showed a slight decrease in their signals. ZEN was Table 3. Signal suppression/enhancement (SSE) for selected mycotoxins in different food matrices Compound Maize kernels Dry pasta (wheat) SSE (%) Eight-multicereal babyfood Aflatoxin G 2 (AFG2) Aflatoxin G 1 (AFG1) Aflatoxin B 2 (AFB2) Aflatoxin B 1 (AFB1) Deoxynivalenol (DON) Ochratoxin A (OTA) HT-2 Toxin (HT-2) T-2 Toxin (T-2) Fumonisin B 2 (FB2) Fumonisin B 1 (FB1) Zearalenone (ZEN) SSE ¼ (Slope matrix-matched calibration/slope standard calibration in solvent)/100. Table 4. Validation of the UHPLC/MS/MS method for the determination of selected mycotoxins. Mean recoveries (%) and relative standard deviations (%, in brackets) of the overall analytical procedure (n ¼ 5) at the validated levels. Estimated limits of quantification (LOQ) and detection (LOD) Maize kernels Dry pasta (wheat) Eight-multicereal babyfood LOD (mg/kg) LOQ (mg/kg) LOD (mg/kg) 200 mg/kg 20 mg/kg 2 mg/kg 0.5 mg/kg LOQ (mg/kg) LOD (mg/kg) 200 mg/kg 20 mg/kg 2 mg/kg LOQ (mg/kg) 200 mg/kg 20 mg/kg 2 mg/kg Compound Aflatoxin G2 (AFG2) 99 (7) 91 (5) 96 (19) (3) 79 (5) 75 (12) (4) 86 (4) 93 (8) 91 (23) Aflatoxin G 1 (AFG1) 88 (5) 98 (3) 101 (11) (2) 77 (6) 73 (6) (3) 82 (5) 93 (6) 88 (13) Aflatoxin B 2 (AFB2) 101 (5) 89 (12) 120 (21) (3) 76 (6) 73 (10) (5) 81 (4) 96 (9) 63 (24) Aflatoxin B1(AFB1) 94 (5) 96 (8) 108 (23) (3) 69 (7) 76 (11) (7) 67 (11) 76 (14) 61 (27) Deoxynivalenol (DON) 86 (15) n.a. n.a (10) n.a. n.a (13) n.a. n.a. n.a Ochratoxin A (OTA) 70 (9) 75 (13) 81 (12) (3) 64 (5) 64 (18) (7) 76 (13) 104 (13) 102 (14) HT-2 Toxin (HT-2) 96 (11) 102 (11) n.a (7) 84 (9) n.a (8) 85 (9) n.a. n.a T-2 Toxin (T-2) 72 (9) 71 (18) n.a (8) 62 (17) n.a (7) 71 (15) n.a. n.a Fumonisin B2 (FB2) 82 (20) 72 (8) n.a (5) 113 (16) n.a (3) 114 (6) n.a. n.a Fumonisin B 1 (FB1) 90 (12) 58 (4) n.a (3) 101 (10) n.a (6) 104 (5) n.a. n.a Zearalenone (ZEN) 66 (7) 61 (8) n.a (10) 87 (15) n.a (12) 79 (11) n.a. n.a n.a.: not applicable

6 1806 E. Beltrán et al. the only compound that presented a notable suppression under these conditions (around 50%), as the presence of acid in the mobile phase made difficult its ionization in negative mode. Higher HCOOH concentrations were tested, but the results were less satisfactory. Finally, the addition of 0.1% HCOOH to the mobile phase was selected as a compromise for the determination of all mycotoxins. Different mobile phase flow rates were also tested, selecting 0.3 ml/min as a compromise between sensitivity, resolution and analysis time. Higher flow rates did not allow an adequate sensitivity to be reached with the source design of our QqQ instrument. Retention times are shown in Table 2. Selection of extraction solvent The determination of compounds with a wide range of physicochemical properties requires an especial effort to optimize the extraction step. To select an adequate extraction solvent, different mixtures of water/organic solvents at different ratios were tested. The use of the modifier HCOOH at different percentages was also assayed. The best results were obtained when using ACN as organic solvent. The mixture water/acn (50:50) presented low recoveries for the selected analytes, but higher ratios of organic solvent improved the efficiency of extraction. After testing several ratios, the best results corresponded to water/ ACN (20:80), obtaining satisfactory recoveries (>70%) for all compounds with the exception of FB1 and FB2. The use of mixtures of water/methanol led to worse extraction efficiency, especially in the case of aflatoxins. To improve the extraction of fumonisins, we evaluated the addition of acetic acid and formic acid to the extraction solvent. 17,23 After testing different acid percentages in the extraction solvent, the addition of 0.1% HCOOH was selected as a compromise for all analytes. As an illustrative example, when using 0.1% HCOOH the recoveries of FB1 and FB2 in maize increased from 63% and 42% (without HCOOH) to 82% and 80%, respectively (Fig. 2). Matrix effects Reduction of sample treatment in a multitoxin method entails the possibility of analytical problems due to the coelution of matrix components, i.e. matrix effects. Matrix effects can affect the ionization efficiency of the analytes, leading to suppression or enhancement of the signal Figure 3. UHPLC/MS/MS chromatograms for the eleven mycotoxins in (a) maize kernels, (b) dry pasta, and (c) eightmulticereal babyfood, at the lowest level validated (in brackets, expressed in mg/kg).

7 Determination of mycotoxins in foods by UHPLC/MS/MS 1807 depending on the analyte/matrix combination. Obviously, this affects the quantification, unless matrix effects are removed or compensated. In order to evaluate matrix effects, the signal suppressionenhancement (SSE) for each analyte in each matrix was calculated, defined as the percentage of the matrix-matched calibration slope divided by the slope of the standard calibration in solvent. 10,16 SSE ¼ðslope matrix matched calibration= slope standard calibration in solventþ100 For this objective, blank sample extracts were fortified to obtain a matrix-matched standard calibration for every matrix. The matrix-matched curves slopes were compared with that of the calibration standards in solvent. Results are shown in Table 3, where it can be seen that notable signal suppression occurred for aflatoxins, mainly in maize. In general, matrix effects for all analytes were more important in maize in comparison to the other matrices. In dry pasta and babyfood samples, SSE values were within the range %. According to our results the use of matrix-matched standards calibration was required for the correct quantification of analytes, mainly for aflatoxins. Method validation Matrix-matched standards calibration showed good linearity in the studied range ( ng/ml for aflatoxins and OTA, and ng/ml for the rest of compounds) with correlation coefficients 0.99 in all sample matrices. The method was validated for the three food matrices selected in this work (maize, dry pasta and babyfood cereals), by spiking blank samples at different concentration levels in quintuplicate. The objective was to reach a validated level in compliance with the maximum value allowed by the European Commission (Table 1). DON was validated only at 200 mg/kg, whereas HT-2, T-2, FB1 and FB2 were validated at 20 and 200 mg/kg. Aflatoxins and OTA were validated at three levels (2, 20 and 200 mg/kg). An additional fourth level, 0.5 mg/kg, was included for aflatoxins and OTA in baby food, due to the lower levels tolerated in this matrix. As stated before, the 0.1 mg/kg level could not be reached for aflatoxin B 1, requiring higher sensitivity in this particular Figure 4. Application to samples. UHPLC/MS/MS chromatograms corresponding to: (a) blank maize kernels sample spiked at 200 mg/kg, (b) maize kernels sample 1, and (c) maize kernels sample 3. Concentration expressed in mg/kg (in brackets).

8 1808 E. Beltrán et al. case, possibly by pre-concentrating 11 and/or purifying sample extracts. Accuracy and precision were estimated by means of recovery experiments at different spiking levels. The results obtained were satisfactory in the three matrices, with most of recoveries between % and RSDs below 20% (Table 4). The specificity of the method was tested by the analysis of blank samples. No peaks were observed in any of the matrices at the same retention time as target mycotoxins, indicating that there were no matrix compounds that might give a false positive signal in the samples. The lowest level validated for each compound with satisfactory precision and recovery was 20 mg/kg for HT-2, T-2, FB1, FB2 and ZEN in the three food matrices. For aflatoxins and OTA, this value could be lowered down to 2 mg/kg (maize and dry pasta) and to 0.5 mg/kg (babyfood). The poorest sensitivity was for DON that could only be validated at 200 mg/kg as the lowest level. To support these data, Fig. 3 shows illustrative chromatograms for each compound at the lowest concentration validated in the three matrices evaluated. For the first eluting compound (DON), a slightly peak broadening was observed in maize and dry pasta matrices. Estimated LODs and LOQs were calculated for S/N ratios of 3 and 10, respectively, from the SRM chromatograms of samples spiked at the lowest level tested. LODs in the three matrices were found to be between 0.1 and 1 mg/kg, and LOQs ranged between 0.3 and 3.5 mg/kg. The exception was HT-2 (LOD 2 5 mg/kg, LOQ mg/kg) and the less sensitive DON (LOD mg/kg, LOQ mg/kg) (Table 4). Application to samples The validated method was applied to the analysis of several samples provided by the Laboratory of Public Health (Valencia, Spain) and others acquired at local markets. In total, 18 samples were analyzed; five of them corresponded to maize; six samples corresponded to wheat in different kinds of dry pasta; the remaining seven were multicereal babyfood. All the samples analyzed were commercial products. Figure 5. Confirmation of a positive maize kernels sample by the accomplishment of Q/q ratios. LC/ MS/MS chromatograms corresponding to: (a) standard 20 mg/l and (b) sample positive for OTA, FB2, FB1 and ZEN.

9 Only 3 out of 18 samples showed mycotoxin contamination, and the three corresponded to maize kernels. These positive samples showed contamination by fumonisins (FB1 and FB2), thricothecenes (DON, T-2 toxin and HT-2 toxin), OTA and ZEN. As an example, Fig. 4(b) illustrates the positive findings of fumonisins in a maize sample, which contained 528 mg/kg FB1 and 130 mg/kg FB2. The presence of OTA and ZEN was also confirmed, although at lower concentrations. Figure 4(c) shows the presence of DON (814 mg/kg) and HT-2 toxin (34 mg/kg) in another maize sample, as well as the OTA and T-2 at lower concentrations. All positive findings were confirmed by accomplishment of the Q/q ratios (deviations were between the limits established by the European Union), 25,26 as well as by agreement of retention time, with deviations lower than 2.5% in respect to a reference standard. As an example, Fig. 5 shows the confirmation of several mycotoxins in a positive sample. Their ion ratios were calculated (Fig. 5(b)) and compared to those obtained from reference standards (Fig. 5(a)). In all positives, deviations were lower than 15%, which was below the maximum tolerance accepted. 25 Regarding retention times, deviations were lower than 0.6%. CONCLUSIONS A multianalyte UHPLC/MS/MS method has been developed for the fast and reliable screening, quantification and confirmation of eleven mycotoxins in cereals and babyfood. The proposed methodology allows the simultaneous determination of analytes with very different physicochemical properties in a single chromatographic run in less than 5 min. The high selectivity of the triple quadrupole analyzer allows the minimization of sample treatment, facilitating the determination of all analytes without the need to apply a SPE cleanup that might restrict the multiresiduality of the method. In addition, the fast switching of positive-negative ionization mode has allowed the simultaneous determination of positively and negatively ionized compounds, avoiding additional injections into the LC/MS/MS system. The use of matrix-matched standards calibration has led to accurate quantification without the need to use isotopelabelled internal standards. Two SRM transitions have been acquired per compound, allowing in this way a safe identification of the compounds detected in samples. The method has been validated, in three food matrices (maize, dry pasta and multicereal babyfood), obtaining satisfactory accuracy and precision for most of analyte/ matrix combinations, supporting the applicability of the method taking into account the maximum levels of mycotoxins fixed by the EC in foodstuff. Present research is focused on aflatoxin B 1 and its metabolite aflatoxin M 1 in order to reach the sensitivity required for babyfood analysis, accordingly to the very low concentration levels admitted by the EC. Determination of mycotoxins in foods by UHPLC/MS/MS 1809 Acknowledgements The authors are very grateful to the Serveis Centrals d Instrumentació Científica (SCIC) of University Jaume I for using the UPLC-TQD mass spectrometer and to Laboratory of Public Health, Valencia for its financial support and for providing the samples. The authors acknowledge the financial support from the Generalitat Valenciana (Plataforma de Seguridad Alimentaria, Project A-07/08). E.B. is grateful to Universitat Jaume I for his pre-doctoral grant. REFERENCES 1. Bennett JW, Klich M. Clin. Microbiol. Rev. 2003; 16: Hussein HS, Brasel JM. Toxicology 2001; 167: Songsermsakul P, Razzazi-Fazeli E. J. Liq. Chrom. Rel. Technol. 2008; 31: Some Naturally Occurring Substances: Food Items and Constituents, Heterocyclic Aromatic Amines and Mycotoxins, Monographs on the Evaluation of Carcinogenic Risks to Humans, vol. 56, International Agency for Research on Cancer (IARC): Lyon, Commission Regulation 2006/1881/EC European Commission (2006) setting maximum levels for certain contaminants in foodstuffs, Brussels, Commission Regulation 2007/1126/EC European Commission (2007) amending Regulation (EC) No 1881/2006 setting maximum levels for certain contaminants in foodstuffs as regards Fusarium toxins in maize and maize products, Brussels, Sforza S, Dall Asta C, Marchelli R. Mass Spectrom. Rev. 2006; 25: Zöllner P, Mayer-Helm B. J. Chromatogr. A 2006; 1136: Kokkonen M, Jestoi M, Rizzo A. Food Addit. Contam. 2005; 22: Sulyok M, Berthiller F, Krska R, Schuhmacher R. Rapid Commun. Mass Spectrom. 2006; 20: Spanjer MC, Rensen PM, Scholten JM. Food Addit. Contam. 2008; 25: Krska R, Molinelli A. Anal. Bioanal. Chem. 2007; 387: Sulyok M, Krska R, Schuhmacher R. Anal. Bioanal. Chem. 2007; 389: Pozo OJ, Barreda M, Sancho JV, Hernández F, Ll Lliberia J, Cortés MA, Bagó B. Anal. Bioanal. Chem. 2007; 389: Sancho JV, Pozo OJ, López FJ, Hernández F. Rapid Commun. Mass Spectrom. 2002; 16: Sulyok M, Krska R, Schuhmacher R. Food Addit. Contam. 2007; 24: Faberi A, Foglia P, Pastorini E, Samperi R, Laganà A. Rapid Commun. Mass Spectrom. 2005; 19: Ren Y, Zhang Y, Shao S, Cai Z, Feng L, Pan H, Wang Z. J. Chromatogr. A 2007; 1143: Ibáñez M, Sancho JV, Hernández F, McMillan D, Rao R. TrAC Trends Anal. Chem. 2008; 27: Richardson SD. Anal. Chem. 2008; 80: Ventura M, Guillén D, Anaya I, Broto-Puig F, Lliberia JL, Agut M, Comellas L. Rapid Commun. Mass Spectrom. 2006; 20: Commission Regulation 2006/401/EC European Commission (2006), laying down the methods of sampling and analysis for the official control of the levels of mycotoxins in foodstuffs. Brussels, Sørensen LK, Elbæk TH. J. Chromatogr. B 2005; 820: Berthiller F, Schuhmacher R, Buttinger G, Krska R. J. Chromatogr. A 2005; 1062: Commission Decision 2002/657/EC European Commission (2002) Implementing Council Directive 92/23/EC concerning the performance of analytical methods and the interpretation of results, Brussels, Pozo OJ, Sancho JV, Ibáñez M, Hernández F, Niessen WMA. TrAC - Trends Anal. Chem. 2006; 25: 1030.