Determining Mycotoxins in Baby Foods and Animal ... - ACS Publications

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Determining Mycotoxins in Baby Foods and Animal Feeds Using Stable Isotope Dilution and Liquid Chromatography Tandem Mass Spectrometry Kai Zhang,* Jon W. Wong, Alexander J. Krynitsky, and Mary W. Trucksess Office of Regulatory Science, Center for Food Safety and Applied Nutrition, U.S. Food and Drug Administration, HFS-706, 5100 Paint Branch Parkway, College Park, Maryland 20740, United States ABSTRACT: We developed a stable isotope dilution assay with liquid chromatography tandem mass spectrometry (LC−MS/ MS) to determine multiple mycotoxins in baby foods and animal feeds. Samples were fortified with [13C]-uniformly labeled mycotoxins as internal standards ([13C]-IS) and prepared by solvent extraction (50% acetonitrile in water) and filtration, followed by LC−MS/MS analysis. Mycotoxins in each sample were quantitated with the corresponding [13C]-IS. In general, recoveries of aflatoxins (2−100 ng/g), deoxynivalenol, fumonisins (50−2000 ng/g), ochratoxin A (20−1000 ng/kg), T-2 toxin, and zearalenone (40−2000 ng/g) in tested matrices (grain/rice/oatmeal-based formula, animal feed, dry cat/dog food) ranged from 70 to 120% with relative standard deviations (RSDs) 0.99, including aflatoxins B1, B2, G1, and G2 (0.05−25 ng/mL); deoxynivalenol and fumonisins B1, B2, and B3 (5.0−500 ng/mL); ochratoxin A (1.0−250 ng/mL); and T-2 toxin and zearalenone (2.5−250 ng/mL). A slope

ratio of a pair of matrix-matched and solvent calibration curves was used to suggest ionization suppression. It is worth noting that only indepth statistical analysis could determine whether two slopes are different. LC−MS/MS Conditions. All sample analyses were performed on a Shimadzu Prominence/20 series (Columbia, MD) liquid chromatograph coupled with an Applied Biosystems (Forest City, CA) 6500 quadrupole linear ion trap (QTrap) mass spectrometer equipped with an electrospray ionization (ESI) interface source. LC separation was achieved using a Phenomenex Kinetex XB-C18 LC column (100 mm × 2.1 mm i.d., 2.6 μm) and a 10 × 2.1 mm guard cartridge (Torrance, CA). The LC mobile phases consist of 10 mM ammonium formate/ 0.1% formic acid/water (A) and 10 mM ammonium formate/0.1% formic acid/methanol (B). Gradient elution at 0.3 mL/min flow rate started at 5% B, was ramped to 40% B in 2 min via linear gradient mode and then to 100% B by 9 min via exponential gradient mode (pump B curves 3 to 6), was held for 2.5 min, and was changed to 5% B at 12 min. Total run time was 15 min including 3 min of column conditioning time. Injection volume was 10 μL, and the column temperature was 40 °C. Ionization source dependent parameters were set as follows: curtain gas (CUR), 30 psi; ion spray voltage, 4,500 V for the positive mode and −4,500 V for the negative mode; nitrogen collision gas (CAD), medium; source temperature (TEM), 500 °C; ion source gases 1 and 2 (GS1 and GS2), each at 60 psi. Resolutions at Q1 and Q3 were set to unit. Two MRM transitions of each [13C]-labeled or native mycotoxin were determined in a previous study34,35 or generated using direct infusion. All native mycotoxins and [13C]-IS were monitored in polarity switching ionization mode. Switching time was 20 ms, scan time was 0.2 s, and the scheduled MRM window was set to 30 s. Zearalenone and [13C]-zearalenone were analyzed in the negative mode, and the other mycotoxins and [13C]-IS were analyzed in the positive mode. Nitrogen gas (99% purity) was used in the ESI source and the collision cell. The identification of target mycotoxins was based on two specific MRM transitions. Retention time, values of DP, CE, and CXP, and the two selected MRM transitions are listed in Table 1.

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RESULTS AND DISCUSSION MS/MS Optimization. One of the limitations associated with MS/MS analysis is that it is difficult to predict whether a selected MRM transition will be free from coextracted/eluted matrix interferences from food or feed samples. The molecular ions ([M + H]+ or [M − H]−) for all target myxotoxins and [13C]-mycotoxins in full-scan MS experiments were determined using positive or negative ionization mode. For each analyte, the two most intense fragments (MRM transitions) were generated and selected using MRM compound optimization tuning. Because these transitions were determined using solvent-only standards, it is possible that MRM transitions may be suppressed due to matrix interferences compromising the sensitivity and specificity needed to identify and quantitate 8938

dx.doi.org/10.1021/jf503943r | J. Agric. Food Chem. 2014, 62, 8935−8943

2 2 2 2 50 50 50 50 20 40 40

aflatoxin B1 aflatoxin B2 aflatoxin G1 aflatoxin G2 deoxynivalenol fumonisin B1 fumonisin B2 fumonisin B3 ochratoxin A T-2 toxin zearalenone

104(2) 101(2) 105(5) 104(10) 120(8) 92(13) 87(10) 95(9) 96(3) 99(19) 108(10)

grain based 103(2) 100(4) 106(1) 106(6) 84(25) 101(22) 70(9) 76(21) 97(4) 114(17) 108(4)

rice based 101(2) 99(3) 107(3) 104(5) 110(4) 102(9) 81(8) 111(2) 97(5) 85(18) 101(7)

oatmeal based 103(2) 100(3) 106(3) 104(6) 105(19) 98(15) 79(12) 94(19) 96(4) 100(28) 106(7)

av 10 10 10 10 200 200 200 200 100 200 200

fortification (ng/g) 100(2) 97(2) 102(3) 99(3) 106(4) 75(9) 82(10) 78(9) 102(4) 80(5) 101(2)

grain based 97(2) 96(2) 101(3) 100(4) 96(10) 106(13) 76(12) 74(8) 100(5) 91(13) 102(4)

rice based 97(2) 94(4) 101(1) 93(3) 94(8) 82(9) 74(4) 71(13) 104(5) 84(7) 102(3)

oatmeal based 98(2) 96(3) 101(2) 97(4) 99(9) 88(19) 77(10) 75(10) 102(5) 85(10) 102(3)

ave 50 50 50 50 1000 1000 1000 1000 500 1000 1000


grain based 98(1) 97(1) 104(1) 96(5) 106(8) 116(6) 95(5) 76(10) 103(3) 83(17) 98(2)

rice based 97(3) 97(1) 101(1) 96(5) 110(12) 100(7) 91(15) 97(16) 105(2) 80(8) 100(4)

oatmeal based

97(2) 97(2) 102(2) 97(4) 110(10) 103(14) 103(14) 85(17) 102(3) 85(14) 99(2)

av

8939

113(1) 106(3) 102(2) 74(9) 112(5) 105(9) 106(4) 102(3) 81(4) 113(10) 110(5)

4 4 4 4 100 100 100 100 40 80 80

aflatoxin B1 aflatoxin B2 aflatoxin G1 aflatoxin G2 deoxynivalenol fumonisin B1 fumonisin B2 fumonisin B3 ochratoxin A T-2 toxin zearalenone

99(4) 101(2) 95(3) 101(12) 90(6) 74(11) 83(5) 101(27) 108(3) 87(12) 75(9)

cat food 101(3) 98(5) 96(4) 93(6) 71(4) 86(23) 100(8) 77(19) 117(4) 84(11) 72(5)

dog food 104(7) 102(5) 98(5) 89(16) 91(20) 88(20) 96(12) 95(21) 102(16) 96(17) 86(22)

av 20 20 20 20 400 400 400 400 200 400 400


animal feed 101(1) 102(1) 99(3) 115(9) 101(4) 93(11) 94(9) 100(12) 98(3) 102(7) 103(4)

cat food

100(5) 102(5) 99(6) 101(3) 89(7) 111(5) 106(2) 96(15) 100(3) 110(16) 97(10)

dog food

102(3) 102(3) 100(4) 97(19) 102(13) 93(18) 95(11) 94(12) 98(4) 100(15) 98(7)

av

100 100 100 100 2000 2000 2000 2000 1000 2000 2000

fortification (ng/g)

106(4) 103(3) 103(1) 71(9) 90(10) 101(4) 104(6) 106(5) 99(2) 83(14) 96(2)

animal feed

103(2) 100(2) 97(5) 108(4) 105(5) 105(16) 91(8) 85(4) 100(4) 120(6) 111(7)

cat food

103(3) 100(2) 100(2) 104(8) 102(9) 117(7) 97(15) 98(21) 104(1) 119(10) 105(4)

dog food

104(3) 101(3) 100(4) 94(20) 99(10) 108(11) 97(11) 96(15) 101(3) 107(19) 104(8)

av

Each recovery reported as mean (RSD)%. In each matrix, recovery was calculated as the mean value of 4 replicates. Average (av) recovery at each fortification concentration was reported as the mean of the 12 replicates.

a

animal feed


mycotoxin

Table 4. Recoveries (%) in Dry Cat/Dog Food and Animal Feeda

Each recovery reported as mean (RSD)%. In each matrix, recovery was calculated as the mean value of 4 replicates. Average (av) recovery at each fortification concentration was reported as the mean of the 12 replicates.

a


mycotoxin

Table 3. Recoveries (%) in Grain/Rice/Oatmeal-Based Baby Foodsa

Journal of Agricultural and Food Chemistry Article


Journal of Agricultural and Food Chemistry

Article

Figure 1. Using a different MRM transition for aflatoxin G1 to avoid interference in animal feed samples. A: Undetected transition (328.8 → 115.1) due to interference. B: Detected transition (328.8 → 200.0).

Figure 2. Using negative ionization to achieve better S/N for zearalenone (100 ng/g) in animal feed samples. A: Extracted ion chromatogram in positive ionization mode. B: Extracted ion chromatogram in negative ionization mode.

mycotoxins. This is especially true in complex matrices prepared without using extensive sample cleanup. In the course of developing the method, some MRM transitions such as 319.2 m/z → 128.0 m/z of zearalenone and 328.8 m/z → 115.1 m/z of aflatoxin G1 became difficult to monitor in some animal feed samples, though they worked well in solvent or baby food matrices. Because of this, the method was modified to use different MRM transitions (328.8 m/z → 200.0 m/z) for aflatoxin G1 and using negative ionization mode to monitor zearalenone. This modification allowed the two mycotoxins to be unambiguously identified in animal feed samples. Figure 1 shows that the new transition (328.8 m/z → 200.0 m/z) of aflatoxin G1 can be clearly detected in the same animal feed samples. Under positive ionization mode, the absolute signal intensity of zearalenone is higher than that under negative ionization mode, but the sensitivity (single-to-noise ratio) was offset by the corresponding high background noise caused by coeluted matrix components. The second transition was barely

detected. Switching to negative ionization mode produced a much cleaner background, and even though the absolute signal intensity of zearalenone decreased, the resulting signal-to-noise became sufficient for identification and quantitation (Figure 2). Matrix Effects. For this study slope ratios between matrixmatched calibration curves and solvent calibration curves were used to graphically suggest matrix effects in the test samples. If the suppression or enhancement is marginal, the ratio (matrixmatched/solvent-only standard) would equal or be very close to 1.00; if there is severe suppression/enhancement, the ratio would deviate from one. Specifically, using [13C]-IS, the ratios of the 11 mycotoxins in the six tested matrices center toward 1.00, ranging from 0.86 (aflatoxin G2 in animal feed extract) to 1.09 (ochratoxin A in grain-based baby food extract) as illustrated in Figure 3. As previously discussed, [13C]-IS and the unlabeled mycotoxins undergo the same ionization conditions, and therefore the coeluted matrix components have the same impact on a target mycotoxin and its [13C]-IS during ionization. 8940



Article

Figure 3. Slope ratios of matrix-matched and solvent calibration curves used to suggest matrix effects in baby food and animal feed matrices.

calibration standards at realistic low concentrations to estimate the instrument LODs/LOQs. This way we would be able to find out the instrument performance in terms of the sensitivity in the presence of matrix components without overestimating or underestimating the sensitivity of the 11 target mycotoxins. Generally, LODs and LOQs are estimated using signal-to-noise (S/N) ratio (e.g., LOD = 3 × S/N and LOQ = 10 × S/N), but in extracted ion chromatograms, there is little or no background noise, making it difficult to accurately assess the sensitivity of target mycotoxins. Based on a well-established EPA protocol,36 the LOQs of the 11 mycotoxins were determined by measuring the standard deviations of repeat injections of matrix-matched calibration standards at low concentrations. The LOQs were statistically estimated using a predefined confidence interval (e.g., 99%). Estimated LOQs ranged from 0.02 ng/g (aflatoxin B1 in rice-based baby food) to 8.3 ng/g (deoxynivalenol in animal feed) (Table 2). The major interferences in cereal-based baby food and animal feed matrices could be fat, proteins, and fibers. Complete separation of target mycotoxins with low concentrations from these matrix components would require extraction, solvent exchange, defatting, and extensive cleanup procedures. The diversity of physicochemical properties of the 11 target mycotoxins further complicates the selection of extraction and cleanup procedures.13,14,37 Because quantitation was achieved based on the relative response between fortified [13C]-IS and mycotoxins, only a simple dilution and filtration was used to prepare our samples. As long as a fortified [13C]-IS and its native counterpart reached equilibration in extraction solvent and sample, the accuracy and precision would be maintained.28 Recoveries at three fortification concentrations in the six selected matrices are listed in Tables 3 and 4. The majority of the recoveries are in the range of 70−120% with RSDs less than 20%. Obviously, using [13C]-IS enabled us to achieve the confidence in quantitative analysis via a simple sample preparation. It is worth noting that at the lowest fortification concentration, 4 ng/g, aflatoxin G2’s recoveries in all pet food and feed matrices are just around 70%, which is much lower than those of the other three aflatoxins. It is speculated that the ion suppression caused the signal intensity of aflatoxin G2 to approach the detection limit, leading to the

Therefore, if a calibration curve is established using relative responses of the mycotoxin and [ 13 C]-IS, the matrix suppression would be corrected. True matrix suppression or enhancement on the calibration curves can only be demonstrated by statistically evaluating the difference between the slopes and using the standard error of the slopes. However, here we have calculated a slope ratio to graphically suggest matrix effects in the different test samples (Figure 3). For example, without using [13C]-aflatoxin B1, the average slope ratio of aflatoxin B1 in the six matrices is 0.81 with a RSD of 18%; while using [13C]-aflatoxin B1, the average ratio is 1.01 with a RSD of 2%. The same pattern is clearly observed for the other mycotoxins. These results emphasize the unpredictable and complex nature of matrix suppressions that would affect quantitation in the course of LC−MS/MS analysis, although it is well-known that matrix suppressions are determined by various factors such as physicochemical properties of target matrices and mycotoxin, sample preparation procedures, LC separation conditions, and MS ionization. There are no universal sample cleanup procedures, LC separation programs, or ionization sources that can eliminate/separate coeluted matrix interferences for these target mycotoxins. A common practice is to use matrix-matched calibration standards. It would be a heavy burden for researchers to find blank matrices and prepare matrix-matched calibration standards when analyzing multiple mycotoxins in a wide range of matrices, which has been the bottleneck for routine mycotoxin analysis that compromises sample throughput and increases labor cost per sample. Obviously, the use of [13C]-IS eliminated the need for matrix-matched calibration standards for quantitation in this study, achieving satisfactory accuracy and precision in an efficient manner. If such a practice could be adopted for routine mycotoxin analysis, the corresponding sample throughput would be improved with ensured data quality. Matrix-Dependent LOQs and Recovery Studies. It is important to determine the LODs/LOQs in an objective manner by factoring in the impact of matrix interferences and background noise. Whether the stable isotope dilution approach can be successfully applied for mycotoxin analysis is determined by the detectability of the native mycotoxins and their [13C]-IS. Therefore, we chose to use the matrix-matched 8941



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Table 5. Detected Mycotoxins in Animal Feed Samples (Av ± SDa, ng/g) mycotoxin aflatoxin B1 aflatoxin B2 aflatoxin G1 aflatoxin G2 deoxynivalenol fumonisin B1 fumonisin B2 fumonisin B3 ochratoxin A T-2 toxin zearalenone a

cattle feed

cat food

cotton seed meal

fish feed

hog feed

poultry feed

sheep feed

Determining Mycotoxins in Baby Foods and Animal ... - ACS Publications

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