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Quantitative assessment of moniliformin in cereals via alternative precipitation pathways, aided by LC-LIT-MS and LC-Q-TOF-MS
Food Chemistry 174 (2015) 372–379
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Food Chemistry journal homepage: www.elsevier.com/locate/foodchem
Analytical Methods
Quantitative assessment of moniliformin in cereals via alternative precipitation pathways, aided by LC-LIT-MS and LC-Q-TOF-MS Chee Wei Lim a,⇑, Kit Yee Lai a, Jie Fang Yeo a, Siew Hoon Tai b, Sheot Harn Chan a a b
Food Safety Laboratory, Applied Sciences Group, Health Sciences Authority, 11 Outram Road, Singapore 169078, Singapore AB SCIEX (Distribution), 10 Biopolis Road, #03-06, Chromos, Singapore 138670, Singapore
a r t i c l e
i n f o
Article history: Received 12 June 2014 Received in revised form 25 September 2014 Accepted 11 November 2014 Available online 15 November 2014 Keywords: Moniliformin Cereals Diagnostic PHREE purification Mass spectrometry
a b s t r a c t The availability of a simple chemical precipitation workflow aided by targeted and untargeted mass spectrometry would provide an accurate diagnostic platform for the direct determination of moniliformin in cereals for food safety control. In-house method validation was performed at six concentration levels of 8, 40, 80, 200, 400, and 600 ng g1 in cereal flours of wheat, corn, rye, oats and barley. Spiking experiments were made at three concentration levels of 20, 40 and 100 ng g1. Protein precipitation and ‘‘PHREE’’ column cleanup strategy provided recoveries of 81–108% for all cereals matrices using external calibrants. ‘‘PHREE’’ purification provided significant (p < 0.05) ion signal enhancement reduction advantage for all matrices except corn flour. Moniliformin underwent significant (p < 0.05) degradation over 2 weeks when prepared in acidified water. A simple, low-cost and fit-for-purpose procedure for the identification and quantitation of moniliformin in cereals becomes available to support prospective regulatory function. Ó 2014 Elsevier Ltd. All rights reserved.
1. Introduction Moniliformin is a mycotoxin produced by several Fusarium species on cereals crops and has been widely reported to be present in localised pockets across three continents including Europe, North America and Pacific Rim (Chelkowski, 1989; Chelkowski, Zajkowli, Zawadzki, & Perkowski, 1987; Lamprecht, Marasas, Thiel, Schneider, & Knox-Davis, 1986; Lew, Chelkowski, Pronczuk, & Edinger, 1996; Scott, Abbas, Mirocha, Lawrence, & Weber, 1987; Thalman, Matzenauer, & Gruber-Schley, 1985; Thiel, Meyer, & Marasas, 1982). Although moniliformin is reported to inflict toxicological effects on several avian species such as cockerels and ducklings (Scarpino, Blandino, Negre, Reyneri, & Vanara, 2013; Von Bargen, Lohrey, Cramer, & Humpf, 2012), the European Food Safety Authority (EFSA) is currently working on a scientific opinion on the risk of moniliformin for public health (EFSA, 2010). As a small and highly polar molecule, moniliformin exists as a water-soluble sodium or potassium salt in nature (Steyn, Thiel, & Van Shalkwyk, 1978). Several analytical methods were reported previously for moniliformin identification and quantitation. They include the application of hyphenated liquid chromatograph coupled to different detectors such as ultraviolet (UV), diode array ⇑ Corresponding author. Tel.: +65 6213 0756; fax: +65 6213 0749. E-mail addresses: [email protected], [email protected] (C.W. Lim). http://dx.doi.org/10.1016/j.foodchem.2014.11.069 0308-8146/Ó 2014 Elsevier Ltd. All rights reserved.
detector (DAD), electrospray ionisation (ESI) and atmospheric pressure chemical ionisation (APCI) mass spectrometry (Jin, Han, Cai, Wu, & Ren, 2010; Munimbazi & Bullerman, 1998; Scarpino et al., 2013; Sewram, Nieuwoudt, Marasas, Sheperd, & Ritieni, 1999; Sørensen, Nielsen, & Trange, 2007). Common to these analytical methods, an independent HRMS confirmation tool was not applied to address analyte specificity needs. The absence of a confirmation technique with high analyte specificity could create identification challenges to analysts because in real samples, interference due to co-elution can occur. To improve method sensitivity and specificity, a high resolution mass spectrometry (HRMS) aided by carbon labelled isotopic dilution strategy was reported recently (Von Bargen et al., 2012). The application of HRMS as the go-to analytical tool of choice for moniliformin detection reflects the demand for high quality data needed to support health policy formulation. For this reason, we developed a novel cereals purification workflow aided by HRMS without the need to apply isotopic dilution. A modified protein precipitation-mediated pathway that bears on cereals composition was introduced for the first time, aided by the application of a protein exclusion purification column known as ‘‘PHREE’’ (a brand from Phenomenex, Torrance, CA). The application of strong anion exchanger (SAX) columns (Munimbazi & Bullerman, 1998; Sørensen et al., 2007; Von Bargen et al., 2012), as well as non-polar C18-columns (Shepherd & Gilbert, 1986) for moniliformin detection were reported previously. For Jin et al.
C.W. Lim et al. / Food Chemistry 174 (2015) 372–379
(2010) and Scarpino et al. (2013), respectively, home-make SPE columns and commercially available MycoSepÒ 240 moniliformin clean-up column were used for moniliformin detection. Common to these publications, no statistical data treatment (at 95% confidence interval) was reported to quantify the benefits of applying SPE purifications for moniliformin detection. In our study, we applied paired t-test to quantify the benefits of applying ‘‘PHREE’’ purification at 95% confidence interval. So, for the first time, method accuracy, precision, selectivity, sensitivity, repeatability and moniliformin stability in individual major cereal flours of maize, oats, wheat, barley and rye were examined. Measurement uncertainty was used to quantify the benefits of applying ‘‘PHREE’’ purification. Method robustness was assessed using 52 real cereals flours. For the purpose of performing confirmation, a Q-TOF instrument was used. This way, a clear scoring system for the accurate determination of moniliformin in cereals can be achieved to support regulatory function. 2. Materials and methods 2.1. Instrumentation In this paper, we selected two independent techniques for the accurate identification and quantitation of moniliformin in cereals. For experiments involving method validation, we selected multiple-reaction-monitoring transition (MRM-transition) quantitation strategy as our primary analytical method of choice. An Agilent model 1290 infinity LC (Palo Alto, CA, USA) coupled to a Qtrap 5500 MS instrument (AB SCIEX, Foster City, CA, USA) mass spectrometer was applied. The LC system comprised of four solvent reservoirs, a built-in degasser, two binary pumps and a refrigerated auto-sampler. In order to extend the servicing life of the LC column, as well as to minimise potential contamination to the MS instrument, an inline filter (0.3 lm, Agilent Technologies, Palo Alto, CA, USA) was used. Briefly, moniliformin was separated using a Gemini column (a brand from Phenomenex, C6-Phenyl, 3 lm, 50 2 mm Torrence, CA, USA) with a flow rate of 0.4 mL min1. The LC column was maintained at room temperature for all experiments. Mobile phases A and B consisted of methanol and ultrapure water respectively, each containing 0.1% acetic acid. Gradient elution was applied as follows: 100% B hold 2 min, 100–0 in 0.5 min and hold 1.5 min, 0–100% in 0.5 min and hold 1.5 min. The separated analyte was then ionised using electrospray ionisation and detected by tandem mass spectrometry. Electrospray ionisation was performed in negative ionisation mode under MRM-transition condition because moniliformin produced a single salient product ion identified as mass-to-charge ratio (m/z) 41 (Jestoi, Rokka, Rizzo, & Peltonen, 2003; Von Bargen et al., 2012) when infusion was performed by using a 100 ng mL1 standard solution made in mobile phase B. Electrospray voltage was set to 5.5 kV. Source temperature and nitrogen gas flows (GS1 and GS2) were set to 500 °C and 45 psi, respectively. Collision cell energy was optimised as 23 eV. Dwell time and scan rate were set to 200 ms and 1000 da s1, respectively, for the entire duration of the experiment. For experiments involving suspect sample confirmation, we employed the 5600+ Q-TOF (AB SCIEX, Foster City, CA, USA). MS conditions related to ion spray voltage floating (in kV), temperature (in °C) and nitrogen gas flow (GS1 and GS2) were reproduced from QTRAP 5500 settings for MRM-transition experiments, with the exception of collision cell energy (CE = 35 eV). The HRMS method file comprised of two experiments in a single period. The first and second experiments in the MS method file were programmed to perform full scan IDA (mass range from 80–65) and MS/MS (mass range from 40–650) data acquisition, respectively.
373
Accumulation times for IDA and MS/MS experiments were 150 and 200 ms, respectively. HRMS scan resolution power was approximately 20,000 fwhm based on m/z 609.28066 (C33H40N2O9, reserpine). By applying this HRMS method programming strategy, for example, an MS/MS scan will be triggered when an m/z value of 96.99 (for moniliformin, [MH]) was detected during the full scan mode. 2.2. Materials and reagents Moniliformin of 99.0% purity was purchased from Sigma– Aldrich and received in neat form. Methanol and acetic acid were of HPLC grade from Labscan. Acetic acid was prepared as 0.1% acetic acid in ultrapure water, purified by passing through a Purelab Option-Q water purification system (a brand from Elga, UK). Methanol was used to prepare moniliformin standard stock solution. From this stock solution, fresh calibrants of moniliformin were prepared by dilution using ultrapure water (containing 0.1% acetic acid) at six concentration levels of 1, 5, 10, 25, 50, and 75 ng mL1, as required. Moniliformin standard was used as-received without further purification. Unused standards were discarded immediately. Cereal flours of wheat, rye, barley, oat and corn were purchased from a local confectionary and tested for the presence of moniliformin before use. A single batch of cereal flours was used to perform method development and validation. For method robustness assessment, random retail sampling was performed for a total of 52 cereal flours comprised of a random mixture of wheat, rye, barley, oat and corn. For all cereals samples, homogenisation was performed by blending prior to use. Sample extraction solvent was prepared as 80% acetonitrile in mobile phase B. 2.3. Sample preparation and extraction Extraction was performed by applying a modified workflow published previously for trichothecenes in grains analysis (Lim, Tai, Lee, & Chan, 2011). For the purpose of performing method validation and unknown sample assessment, 5-g (w) sample weight was taken. Briefly, 20 mL (v1) of extraction solvent was added to an aliquot cereal flour sample and shaken for 30 min. The mixture was centrifuged at 8000 rpm (3226g) for 6 min at room temperature. An aliquot of the supernatant was diluted using an equal volume (v2) of mobile phase B. Next, the diluted supernatant was shaked vigorously and 1 mL (v3) purified using a commercially available ‘‘PHREE’’ column (a brand from Phenomenex, Torrence, CA, USA). No ‘‘PHREE’’ column conditioning required before use. 5 lL of the final purified supernatant was injected into the LCMSMS/Q-TOF for analysis. This way, a solute to solvent ratio of 1:8 can be achieved. The ‘‘PHREE’’ columns were originally designed to remove proteins and phospholipids from plasma samples. In this study, we evaluated the feasibility of applying ‘‘PHREE’’ purification as a solution to address ion signal enhancement for moniliformin detection in cereals using MS. 2.4. Evaluation of signal enhancement/suppression effect and detection limit Matrix effect assessment provides information related to ion signal enhancement/suppression due to co-extractants over a practical concentration range. For this reason, spiking experiments were made at six concentration levels of 1, 5, 10, 25, 50, and 75 ng mL1 (S). By performing post-extraction spiking experiments, it is possible to identify and distinguish interference due to co-extractants from effects due to recovery. Spiking concentration levels (C, in ng g1) were determined as:
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C ¼ ðS=wÞ ðv 1 þ v 2Þ v 3;
ð1Þ
By applying the formula in Eq. (1), the six spiking concentration levels of 8, 40, 80, 200, 400, and 600 ng g1 (n = 3) can be made in individual cereal extract. Ion signal enhancement/suppression (M) was assessed as:
ð2Þ
Linearity was assessed using a residual plot and statistical test for goodness-of-fit. LOD and LOQ were calculated as (2.33 standard deviation)/Gradient of slope and LOD + (1.64 standard deviation)/Gradient of slope, respectively (European Commission, 2006). 2.5. Recovery, intra-day and inter-day repeatability studies A 5-g aliquot of individual cereal flour was spiked with moniliformin at three concentration levels of 5, 10 and 25 ng mL1 (40, 80 and 200 ng g1) and extracted using protocols described under ‘‘sample preparation and extraction’’. Recovery (R) performance was assessed and expressed as:
Abundance (counts)
M ¼ ðArea of matrix-matched standard =Area of matrix-free standardÞ 100;
Polar modified C18
C6-Phenyl
R ¼ ðMean concentration; n ¼ 6intraday;interday =Spiked concentrationÞ 100;
ð3Þ
3. Results and discussion 3.1. Analytical approach The intention of this study was to develop an analytical workflow fit-for-purpose for the direct detection of moniliformin in cereals. To fulfil this objective, we divided our experiments into three phases, namely analyte retention, sample purification and confirmation MS technique selection. Analyte separation represents a fundamental stage for any analytical method development, with the exception of model driven quantitative small molecules analysis (Lim & Chan, 2013; Lim, Tai, & Chan, 2012). For a polar small molecule such as moniliformin, analyte separation is important because interference originating from coextractants present in complex sample matrices implies challenges to accurate quantitative analysis. For this reason, we evaluated two potential LC column candidates of similar dimensions, represented by Gemini C6 Phenyl column (Phenomenex, Torrence, CA, USA) and Synergi polar C18 column (Phenomenex, Torrence, CA, USA). Analyte retention was applied as assessment criterion. Owing to differences in LC column stationary phase between the two candidates examined, chromatographic separation conditions such as flow rate and elution time were individually optimised. Fig. 1 summarises the chromatographic performance of applying Gemini C6 Phenyl column as the LC column of choice over Synergi Polar C18 column. Our observation that Gemini C6 Phenyl column offers superior performance for moniliformin retention is consistent with report published previously (Von Bargen et al., 2012). Within the framework of analytical chemistry, it is established that analyte separation can be achieved via two strategies. They include physical separation using classical method such as LC column to perform chromatographic separation, as well as using the enhanced analyte specificity offered by triple-stage mass spectrometry (Khiu, Lim, Lee, Yap, & Chan, 2014; Lim & Chan, 2013; Ting, Rad, Gygi, & Hass, 2012). In this work, however, moniliformin produced a single salient daughter ion fragment of m/z 41. Due to its inherently small ion fragment (m/z smaller than 50), triple-stage mass spectrometry becomes an unsuitable candidate for moniliformin assessment. Moreover,
Time (min) Fig. 1. Ion chromatograms comparing retention times of moniliformin using C6Phenyl column and polar modified C18 column.
the linear-ion-trap is designed to measure ion fragments greater than or equal to m/z 50. The adaptation of Gemini C6 Phenyl column as the LC column of choice implies user confidence in moniliformin identification via its retention time can be achieved. With challenges related to analyte retention addressed, we examined the next phase of our experiment involving sample purification. Here, we applied a modified workflow published previously for trichothecene assessment (Lim et al., 2012). Instead of using pure acetonitrile as the extraction solvent of choice, 20% ultra-pure water acidified using acetic acid was added. The motivation for using an 80:20 acetonitrile/water composition is consistent with the analytical strategy applied for the recovery of multi-mycotoxins from maize and grains published previously (Sulyok, Berthiller, Krska, & Schuhmacher, 2006). The presence of 0.1% acetic acid to the extraction solvent implies some soluble flour and gluten protein would be co-extracted as well (Kurowska & Bushuk, 1988). The presence of solubilised protein or gluten in the sample extract would present technical challenges when MS is applied as the analytical tool of choice. Therefore we can expect to observe some ion signal variation effects since solubilised compounds such as protein or gluten originating from cereals can interfere with the electrospray ionisation processes, such as via mechanisms published previously (Trufelli et al., 2011). For these reasons, a simple and easy sample purification procedure is required, such as the sample purification strategy reported by Scarpino et al. (2013) using MycoSepÒ 240 moniliformin cleanup
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column. Two experiments were made to investigate the dominant physical phenomena when sample extraction was performed by using extraction solvent alone and when 1:1 dilution using mobile phase B was applied. For the first experiment involving direct extraction, a solute to solvent ratio of 1:4 was applied; performing 1:1 dilution would produce a solute to solvent ratio of 1:8. In the former experiment, no apparent precipitate was observed for all cereal flours of wheat, corn, rye, oats and barley. When 1:1 dilution was performed, white/pale yellow precipitate was observed for all cereal extracts except corn. Although the analytical approach for precipitation applied in our study is reversed in comparison to conventional protein precipitation involving the application of 80% or greater fractions of acetonitrile content, the function of achieving organic content reduction through precipitation is met. 3.2. Evaluation of matrix effect in cereals Within the framework of mass spectrometry, protein precipitation represents a key purification strategy applied to address ion signal enhancement or suppression effects due to the presence of co-extractants originating from a complex food matrix such as wheat. Wheat is produced in the miller through a series of processing steps including cleaning, blending, conditioning, breaking, sifting, bleaching and enriching, amongst others, to obtain the final flour (Martin, Leonard, & Stamp, 1976). Although the wheat milling process would eliminate those portions of the wheat kernel such as bran, germ, and shorts that are richest in proteins, vitamins, lipids and minerals, we expect some percentage of protein to remain in the final flour (Wang et al., 2008). For a wheat sample extracted using a solvent system comprised of 20% weakly acidified water, we expect interference originating from components such as water soluble amino acids in the flour (from endosperm that forms the bulk of cereal flours) and water soluble albumins to be significant when electrospray ionisation was applied. Indeed, the albumin represents 9% of weed seed proteins (Singh & Skerritt, 2001). For example, molecular weights of albumins range from 12 to 64 kDa, with the high molecular weight albumins in the range of 45–65 kDa (Bean & Tilley, 2003; Majoul, Bancel, Triboi, Hamida, & Branlard, 2004; Singh & Skerritt, 2001). Owing to the unavailability of a suitable labelled isotopic standard for a small molecule such as moniliformin, sample purification achieved through the removal of these soluble proteins becomes an important step for quantitative analysis. To do this, we applied a new protein purification column known as ‘‘PHREE’’ after sample dilution was performed. The principle of ‘‘PHREE’’ purification system is based on protein size exclusion. For a small molecule such as moniliformin, we do not expect losses due to the application of ‘‘PHREE’’ purification to be significant. Matrix effect was therefore examined. Table 1 summaries the ion signal enhancement/suppression effects for different concentrations of moniliformin made in individual cereal extract. To better quantify the significance of applying ‘‘PHREE’’ purification strategy, we applied paired t-test at 95% confidence interval because sample purification was made using the same sample extract that received no purification. From Table 1, the application of ‘‘PHREE’’ purification strategy would benefit cereal extract of wheat, rye, barley and oat significantly (p < 0.05). Interestingly, corn sample extract did not benefit significantly from the application of ‘‘PHREE’’ column purification, as judged basing on matrix effects data shown in Table 1. Although the application of our sample extract purification strategy implies not all cereal extracts would benefit significantly, fine particulate yellow coextractants of corn origin was visibly removed. Indeed, the benefit of applying sample purification is evident by the absence of precipitate depositing around the periphery of the orifice on the curtain plate on the MS instrument. Excessive deposits that formed around
Table 1 Matrix effects on LC–MS/MS detection of Moniliformin in individual cereal extracts of wheat, corn, rye, oats and barley by applying MRM-transition quantitation strategies at six concentration levels of 8, 40, 80, 200, 400, 600 ng g1, before and after applying PHREE purification. Concentration ng ml1 (ng g1)
%, Matrix effecta for MRM (97 > 41) Wheat
Before PHREE purification 1 (8) 5 (40) 10 (80) 25 (200) 50 (400) 75 (600) After PHREE purification 1 (8) 5 (40) 10 (80) 25 (200) 50 (400) 75 (600)
Rye
Barley
Oat
Corn
140 121 120 116 119 119
127 128 129 129 124 126
166 132 129 126 124 125
224 140 123 116 114 115
366 165 132 118 114 115
123* 110* 110* 110* 109* 110*
113* 116* 115* 115* 113* 116*
112* 110* 115* 110* 110* 110*
163* 115* 111* 105* 104* 106*
227 125 114 106 105 105
a The ion signal suppression (<100) or enhancement effect (>100) was assessed as [(peak area of matrix-matched standard)/(peak area of matrix-free standard)] 100 in percent. * Indicates significantly different from those before PHREE purification, (p < 0.05) at 95% confidence interval using paired t-test.
the periphery of the orifice imply a through-path to the mass detector is now made less accessible. For sample extracts that received little purification, it was necessary to include curtainplate cleaning protocol using ultra-pure water after approximately every 50–60 injections were made. Clearly, the application of our chemical precipitation and purification protocol provided the benefits of significantly reduced ion signal enhancement effect (except for corn) and uninterrupted measurements to be made in a single analysis. 3.3. Evaluation of recovery, linearity, intra-day and inter-day repeatability Although the application of our modified precipitation workflow implies the analysis of other important analytes in complex food matrices would be applicable as well, it is also necessary to examine the effects of competing co-occurring processes such as protein encapsulation (Chen, Lim, & Chan, 2014) and analyte extraction on recovery performance. To do this, we examined the recovery performance of moniliformin in cereal extracts of wheat, rye, barley, oat and corn. Sample purification was achieved by applying drop-wise dilution described under ‘‘sample preparation and extraction’’. In order to quantify the effects of applying drop-wise dilution strategy on recovery performance, spiking experiments were made at three concentration levels of 40, 80, and 200 ng g1. Table 2 showed recovery performance of moniliformin in individual cereal flour ranged from 81% to 108%. Intra-day and inter-day variation yielded satisfactory results, ranged from 2% to 15%. Based on the recovery results shown in Table 2, there is insufficient evidence to show protein encapsulation can occur for moniliformin in cereals. In comparison to analytical methods involving the use of stable carbon labelled isotopic dilution strategy (Von Bargen et al., 2012) to address recovery challenges for mycotoxins assessment, the application of our validated protocol implies direct access to satisfactory data quality using a simple, efficient and low-cost chemical precipitation pathway is now available. Simply, synthetic pathway described previously to produce labelled isotopic standards of moniliformin to address recovery losses in cereals (Von Bargen et al., 2012) would become redundant. Further, recovery losses due to drying down and reconstitution step reported previously
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Table 2 Mean recovery (in percent) of spiking experiments made at three concentration levels of 5, 10 and 25 ng mL1 (40, 80 and 200 ng g1) in cereal flours, assessed using matrix-free calibrant. Intra-day and inter-day RSD values (n = 6) are shown in brackets. Cereals
Wheat Rye Barley Oat Corn
Mean recovery of moniliformin (RSDintra-day, RSDinter-day) 5 ng mL1 (40 ng g1)
10 ng mL1 (80 ng g1)
25 ng mL1 (200 ng g1)
LOD (lg g1)
LOQ (lg g1)
98 (2, 2) 100 (5, 5) 100 (3, 4) 103 (7, 7) 90 (3, 3)
102 (8, 104 (6, 102 (8, 106 (6, 84 (13,
98 (5, 6) 108 (6, 6) 91 (7, 7) 81 (6, 6) 81 (13, 15)
0.5 1 0.5 0.5 1
1.5 3 1.5 1.5 3
4) 6) 5) 8) 5)
by Scarpino et al. (2013) is now circumvented since a simple dilution step prior to the application of ‘‘PHREE’’ purification would be fit-for-purpose. In this paper, time and effort required to perform SPE column pre-conditioning reported previously (Munimbazi & Bullerman, 1998; Sørensen et al., 2007; Von Bargen et al., 2012) for MON detection was conserved. The recovery range reported in our study represented an improvement over those reported previously using non-protein exclusion column, with values ranged from 57% to 74% in maize (Jin et al., 2010; Sørensen et al., 2007). Matrix-free and matrix-matched calibration curves were linear over the relevant working range with correlation coefficient values of between 0.9990 and 0.9998, as assessed basing on individual residual-plots and goodness-of-fit test. LOD and LOQ values in cereals were determined as 1 and 3 ng g1, respectively, with rye and corn flours providing the least sensitive LOD and LOQ values. These LOD and LOQ values are comparable with the results presented by Von Bargen et al. (2012). 3.4. Evaluation of moniliformin stability In our study, we report for the first time on moniliformin stability when prepared in water-enriched mobile phase B. The same set of sample vials containing calibrants and spiked experiments were measured 2 weeks after recovery performance was assessed. Samples vials were stored at 4 °C when not in use. For comparison purpose, a fresh set of calibrants made in mobile phase B was prepared. Uninterrupted measurements were made in a single analysis. For the same set of sample vials (2 weeks old) containing spiked solutions of moniliformin, the recovery values ranged from 144% to 198% (Table 3). When the same set of sample vials were read against a set of freshly prepared calibrants, recovery values ranged from 52% to 108% (Table 3). These widely ranging recovery values suggested moniliformin underwent significant (p < 0.05) degradation when prepared in mobile phase B, amongst others. Therefore, we recommend practicing fresh preparation of moniliformin calibrant as a quality control strategy when made in water-enriched solvent system such as mobile phase B. Table 3 Moniliformin stability study (2 weeks) showing mean recovery (in percent, n = 6) of spiking experiments made at three concentration levels of 5, 10 and 25 ng mL1 (40, 80 and 200 ng g1) in cereal flours, assessed using matrix-free calibrants. Mean recovery values (in percent, n = 6) determined using freshly prepared Moniliformin calibrants on 2 weeks old sample vials are shown in brackets. Cereals
Wheat Rye Barley Oat Corn
Mean recovery of moniliformin2 weeks old calibrants ðRFresh calibrants Þ 5 ng mL1 (40 ng g1)
10 ng mL1 (80 ng g1)
25 ng mL1 (200 ng g1)
179 181 179 198 144
162 183 182 191 148
161 183 179 184 145
(74) (76) (74) (86) (52)
(83) (97) (96) (102) (74)
(95) (108) (106) (109) (81)
3.5. Measurement uncertainty In this paper, we applied an adapted protocol for uncertainty evaluation reported previously (Pantazopoulos, 2001). For the assessment of moniliformin in cereal extracts of wheat, rye, barley, oat and corn, the relative expanded uncertainty (with 95% of confidence level) was significantly larger (p < 0.05) in samples that received no ‘‘PHREE’’ purification. The application of ‘‘PHREE’’ purification strategy equipped analyst with lower uncertainty range. This was represented by the combined uncertainty in cereal extracts of wheat, rye, barley, oat and corn at less than 18%. For cereal extracts that received no ‘‘PHREE’’ purification, the corresponding combined uncertainty was determined to be about 40%. Amongst cereal extracts of wheat, rye, barley, oat and corn, corn contributed significantly towards the largest uncertainty for bias. The application of ‘‘PHREE’’ purification would provide a significant improvement for method bias, which represented the major contributing factor towards uncertainty calculation. We can therefore conclude that chemical precipitation aided by ‘‘PHREE’’ purification pathway improved measurement uncertainty in a single workflow by providing greater accuracy in the quantitation of moniliformin in cereals. 3.6. Selection of confirmation MS technique The single salient mass fragment of moniliformin implies a high resolution confirmation technique is required to achieve the minimum identification point of 3.0 (Commission Decision 2002/657/ EC). To fulfil this criterion, we considered and applied a readily accessible 5600+ Q-TOF instrument housed (remotely) within ABSciex facility in Singapore. Experimental conditions related to LC column, gradient separation, MS conditions (with off-set value for collision cell energy of 35 eV) and mobile phases were reproduced using the same set of sample vials. For the purpose of performing method robustness assessment, 52 cereals samples were first screened by using the QTrap 5500. Suspect samples were then confirmed using the 5600+ Q-TOF instrument. This way, an accurate and time efficient workflow involving suspect sample identification and confirmation can be achieved to benefit a laboratory with wide analytical base. 3.7. Assessment of real samples 52 cereals samples comprised of a mixture of individual wheat, rye, barley, oat and corn flours were analysed using our validated protocol. Amongst the cereals samples analysed, two samples of corn and oats flours of non-asian origin provided a single salient peak matched to moniliformin standard retention time when MRM-transition was applied on the Qtrap 5500. For this reason, we performed an information dependent analysis on both suspect samples. Briefly, the Analyst TF software on the 5600+ Q-TOF was programmed to perform an enhanced product ion scan when the MRM-transition parameters used on the Qtrap 5500 were fulfilled. Using the scan spectrum generated by the enhanced product ion scan on the 5600+ Q-TOF for individual suspect sample, we performed a match against the scan spectrum obtained when pure standard of moniliformin was used. From Fig. 2a, pure moniliformin standard (about 50 ng mL1) produced two distinctive ‘‘peaks’’ when an HRMS scan (m/z 40–620) was applied to determine its exact mass [MH]. These base values were m/z 96.9929 (mass error of 2.2 ppm) and 96.9602, respectively, for moniliformin and the unknown contaminant. Owing to the unavailability of stable carbon-labelled isotopic standard solution of moniliformin, isotopic fingerprint matching could not be performed experimentally, as reported previously (Von Bargen et al., 2012). For this reason, we could not apply the guidelines recommended by Commission Deci-
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(a) Moniliformin standard
HRMS-Scan
HRMS/MS-Scan 41.0034
96.9929 (12C 96.9931)
97.9963 (13C1 97.9965)
96.9602
Abundance (counts)
Impuries
(b) Suspect oats/corn
96.9602
Absent
Absent
Fragmentaon pathway
(c) Spiked suspect oats/corn
96.9929 (A)
96.9602
41.0034 (B)
(A) C4HO3-
(B) C2HO-
97.9963 m/z
Fig. 2. Scan spectra representing HRMS-Scan and HRMS/MS-Scan of (a) Moniliformin standard (about 50 ng mL1), (b) suspect oats and corn samples, and (c) spiked suspect oats and corn samples at 10 ng g1 (limits of detection). Theoretically calculated values are shown in brackets. Moniliformin fragmentation pathway presented inset.
sion 2002/657/EC of the European Commission that accepts 50% variation of labelled moniliformin ratio relative to its unlabelled form. Rather, we performed a scan on the moniliformin standard and matched its isotopic fingerprint to the theoretical values 12C (m/z 96.9931) and 13C1 (m/z 97.9965). We could not see the 13C2 peak in our scan spectrum and therefore, no mass error value was reported. This way, mass errors of 2.2 and 2.1 ppm were reported for 12C (m/z 96.9929) and 13C1 (m/z 97.9963), respectively. Enhanced product ion scan was also performed to obtain the remaining 2.5 identification points basing on transition ion (m/z 41.0034). From Fig. 2a, moniliformin standard would produce a single salient transition ion of m/z 41.0034. The appearance of two additional product ions of m/z 79.9577 and 78.9604 was attributed to impurities present in the working solution. These impurity product ions (such as m/z 79.9577 and 78.9604) were also detected in both mobile phases and extraction solvent. When both mobile phases and extraction solvent were assessed using the Qtrap 5500, no moniliformin peak was identified. We observed the appearance of these additional impurity-related transition ions on the 5600+ Q-TOF instrument because a wide scan range of m/z 40–620 was applied. When MS/MS scan was performed on the suspect flours of corn and oats using information dependent analysis function available on the Analyst TF software, only two impurity-related product ions m/z 79.9577 and 78.9604 were detected (Fig. 2b).
The transition attributed to moniliformin standard at m/z 41.0034 was not detected. By performing a direct spiking (at LOD of 10 ng g1) into the suspect sample and the analysis repeated using the 5600+ TripleTOF instrument, unambiguous identification and confirmation can be achieved, as shown in Fig. 2c. Clearly, the improved resolution offered by 5600+ TripleTOF enabled analyst to clearly identify a co-eluting impurity and distinguish it from the moniliformin standard. This way, suspect samples shortlisted by applying the Qtrap 5500 MS instrument can be confirmed. Indeed, by comparing individual ion chromatogram (Fig. 3, Qtrap 5500) of the suspect sample (for example corn flour) against the moniliformin standard, we observed a significant difference (p < 0.05) in the base peak-widths (indicated by the unshaded arrows). The application of 5600+ Q-TOF as a confirmation tool therefore transforms arbitrary visual ion chromatogram inspection (on Qtrap 5500) into distinctive quantitative benefits through exact mass identification, isotopic fingerprint matching and transition ion matching functions. The need to utilise a high resolution MS tool so that analysts can become equipped with the confidence needed to distinguish moniliformin from interfering ion implies results obtained by using non-specific ultraviolet or diode array techniques becomes questionable today. For a laboratory without immediate and direct access to a HRMS tool, complete chromatographic separation may perhaps remain the single analytical tool needed to combat the pitfalls of false positive due to co-eluents
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References
Abundance (Counts)
Qtrap 5500
Suspect sample
Qtrap 5500
Moniliformin 10 ng mL-1
Time (min) Fig. 3. Ion chromatogram (Qtrap 5500) of suspect sample with (approximately twice) enlarged base-peak width compared to moniliformin standard made at 10 ng mL1.
originating from the cereal samples. Within the entirety of our experiment, we depended solely on the stationary phase surface chemistry to retain moniliformin because the analyte was eluted on a 100% acidified water-dominant chromatographic gradient. 4. Conclusion In conclusion, our study successfully validated a MS workflow fit-for-purpose for the accurate determination of moniliformin in cereals. Method accuracy, precision, selectivity, sensitivity, repeatability, robustness and analyte stability were examined and found to be highly satisfactory. A simple, easy and cost-efficient sample purification strategy using step-wise protein precipitation pathway, aided by ‘‘PHREE’’ purification provided the single solution to address challenges presented by ion signal enhancement when MS was applied as the analytical method of choice for moniliformin detection. Isotopic dilution is not required to compensate for matrix effect in all cereal extracts of wheat, rye, barley, oat and corn. The application of a simple size-exclusion ‘‘PHREE’’ purification step would sufficiently address the need for regular instrument maintenance due to precipitate depositing along the periphery of the orifice on the curtain plate, thereby enabling uninterrupted measurements to be made. Quantitative degradation of moniliformin (in acidified water) was reported for the first time. For suspect samples, confirmation using high resolution MS is required because the MRM-transition using single ion pair as identifier did not provide sufficient identification points. A simple, easy and validated analytical workflow aided by high resolution mass spectrometry becomes available for the assessment of important cereals of wheat, rye, barley, oat and corn. 5. Conflict of interest The authors declare there are no conflicts of interest. Acknowledgement The authors would like to thank HSA-FSD for providing the funding to support this in-house method validation study.
Bean, S. R., & Tilley, M. (2003). Separation of water-soluble proteins from cereals by high-performance capillary electrophoresis (HPCE). Cereal Chemistry, 80, 505–510. Chelkowski, J. (Ed.). (1989). Mycotoxins associated with maize cob fusariosis. Fusarium-mycotoxins, taxonomy, and pathogenicity. Amsterdam: Elsevier, p. 53–62. Chelkowski, J., Zajkowli, P., Zawadzki, M., & Perkowski, J. (1987). Moniliformin, deoxynivalenol, 3acetyldeoxynivalenol and zearalenone-mycotoxins associated with maize cob fusariosis in Poland. Mycotoxin Research Special Issue, 3, 25–27. Chen, Y. H., Lim, C. W., & Chan, S. H. (2014). Evaluation of triple stage mass spectrometry as a robust and accurate diagnostic tool for determination of free cordycepin in designer egg. Food Chemistry, 150, 213–219. European Commission (2006). No 401/2006 Laying down the methods of sampling and analysis for the official control of the levels of mycotoxins in foodstuffs. Official Journal of the European Union, L 70, 1–12. European Food Safety Authority (EFSA) Request for a scientific opinion on the risks for public health related to the presence of moniliformin in feed and food, Mandate M-2010-0312, Reception date 21-07-2010, Acception Date 09-092010. Jestoi, M., Rokka, M., Rizzo, A., & Peltonen, K. (2003). Moniliformin in finnish grains: Analysis with LC–MS/MS. Aspects of Applied Biology, 68, 211–216. Jin, P. G., Han, Z., Cai, Z. X., Wu, Y. J., & Ren, Y. P. (2010). Simultaneous determination of 10 mycotoxins in grain by ultra-high-performance liquid chromatographytandem mass spectrometry using 13C15-deoxynivalenol as internal standard. Food Additives & Contaminants: Part A, 27, 1701–1713. Khiu, K. W., Lim, C. W., Lee, L. M., Yap, W. K., & Chan, S. H. (2014). Triple-stage mass spectrometry as the go-to physic-chemical tool for the accurate assessment of multi-mycotoxins in processed chilli of Asian origin. World Mycotoxin Journal, (in press). Kurowska, E., & Bushuk, W. (1988). Solubility of flour and gluten protein in a solvent of acetic acid, urea, and cetyltrimethylammonium bromide, and its relationship to dough strength. Cereal Chemistry, 65, 156–158. Lamprecht, S. C., Marasas, W. F. O., Thiel, P. G., Schneider, D. J., & Knox-Davis, P. S. (1986). Incidence an toxigenicity of seedborne Fusarium species from Annual Medicago species in South Africa. Phytopathology, 76, 1040–1041. Lew, H, Chelkowski, J., Pronczuk, P., & Edinger, W. (1996). Occurrence of the Mycotoxin moniliformin in maize (Zea mays L.) ears infected by Fusarium subglutinans (Wollenw & Reinking) Nelson et al. Food Additives and Contaminants, 13, 321–324. Lim, C. W., & Chan, S. H. (2013). Single laboratory method validation comparing MS3 with FI/MS fingerprinting, and quantitation strategies for the accurate determination of ochratoxins in beer. World Mycotoxin Journal. http:// dx.doi.org/10.3920/WMJ2012.1522. Lim, C. W., Tai, S. H., & Chan, S. H. (2012). A flow-injection mass spectrometry fingerprinting scaffold for feature selection and quantitation of Cordyceps and Ganoderma extracts in beverage: A predictive artificial neural network modeling strategy. AMB Express, 2, 43. Lim, C. W., Tai, S. H., Lee, L. M., & Chan, S. H. (2011). Analytical method for the accurate determination of trichothecenes in grains using LC–MS/MS: A comparison between MRM transition and MS3 quantitation. Analytical and Bioanalytical Chemistry, 403, 2801–2806. Majoul, T., Bancel, E., Triboi, E., Hamida, J. B., & Branlard, G. (2004). Proteomic analysis of the effect of heat stress on hexaploid wheat grain: Characterisation of heat-responsive from non-prolamins fraction. Proteomics, 4, 505–513. Martin, J. H., Leonard, W. H., & Stamp, D. L. (1976). Principles of field crop production (3rd ed.). New York, NY: Macmillan publishing Co., Inc. Munimbazi, C., & Bullerman, L. B. (1998). High-performance liquid chromatographic method for the determination of moniliformin in corn. Journal of the Association of Official Analytical Chemists International, 81, 999–1004. Pantazopoulos, P. (2001). Uncertainty estimate for: Procedure ONT-FCL-0024 determination of ochratoxin A in wine and grape juice by high performance liquid chromatography with fluorescence detection. Food Laboratory Division, Ontario Region, 17–22. Scarpino, V., Blandino, M., Negre, M., Reyneri, A., & Vanara, F. (2013). Moniliformin analysis in maize samples from North-West Italy using multifunctional cleanup columns and the LC–MS/MS detection method. Food Additives & Contaminants: Part A, 30, 776–884. Scott, P. M., Abbas, H. K., Mirocha, C. J., Lawrence, G. A., & Weber, D. (1987). Formation of moniliformin by Fusarium sporotrichioides and Fusarium culmorum. Applied and Environmental Microbiology, 53, 196–197. Sewram, V., Nieuwoudt, T. W., Marasas, W. F. O., Sheperd, G. S., & Ritieni, A. (1999). Determination of the Mycotoxin moniliformin in cultures of Fusarium subglutinans and in naturally contaminated maize by high-performance liquid chromatography-atmospheric pressure chemical ionization mass spectrometry. Journal of Chromatography A, 848, 185–191. Shepherd, M. J., & Gilbert, J. (1986). Method for the analysis in maize of the Fusarium mycotoxin moniliformin employing ion-pairing extraction and high performance liquid chromatography. Journal of Chromatography, 358, 415–422. Singh, J., & Skerritt, J. H. (2001). Chromosomal control of albumins and globulins in wheat grain assessed using different fractionation procedures. Journal of Cereal Science, 33, 163–181.
C.W. Lim et al. / Food Chemistry 174 (2015) 372–379 Sørensen, J. L., Nielsen, K. F., & Trange, U. (2007). Analysis of moniliformin in maize plants using hydrophilic interaction chromatography. Journal of Agricultural and Food Chemistry, 55, 9764–9768. Steyn, M., Thiel, P. G., & Van Shalkwyk, G. C. (1978). Isolation and purification of moniliformin. Journal of the Association of Official Anaytical Chemists, 61, 578–580. Sulyok, M., Berthiller, F., Krska, R., & Schuhmacher, R. (2006). Development and validation of a liquid chromatography/tandem mass spectrometric method for the determination of 39 mycotoxins in wheat and maize. Rapid Communications in Mass Spectrometry, 20, 2649–2659. Thalman, A., Matzenauer, S., & Gruber-Schley, S. (1985). Untersuchungen über das Vorkommem von Fusarientoxinen in Getreide. Ber über Landwirtsch, 63, 257–272. Thiel, P. G., Meyer, C. J., & Marasas, W. F. O. (1982). Natural occurrence of moniliformin together with deoxynivalenol and zearalenone in Transkeian maize. Journal of Agricultural and Food Chemistry, 30, 308–317.
379
Ting, L., Rad, R., Gygi, A. P., & Hass, W. (2012). MS3 eliminates ratio distortion in isobaric labelling-based multiplexed quantitative proteomics. Nature Methods, 8, 937–940. Trufelli, H., Palma, P., Famiglini, G., & Cappiello, A. (2011). An overview of matrix effects in liquid chromatography–mass spectrometry. Mass spectrometry Reviews, 30, 491–509. Von Bargen, K. W., Lohrey, L., Cramer, B., & Humpf, H. U. (2012). Analysis of the fusarium mycotoxin moniliformin in cereal samples using 13C2-Moniliformin and high-resolution mass spectrometry. Journal of Agricultural and Food Chemistry, 60, 3586–3591. Wang, A. L., Pei, Y. H., Li, X. H., Zhang, Y. Z., Zhang, Q., He, Z. H., et al. (2008). Rapid separation and characterisation of grain water-soluble proteins in bread wheat cultivars (Triticum asestivum L.) by capillary electrophoresis. Canadian Journal of Plant Science, 88, 843–848.
Contents lists available at ScienceDirect
Food Chemistry journal homepage: www.elsevier.com/locate/foodchem
Analytical Methods
Quantitative assessment of moniliformin in cereals via alternative precipitation pathways, aided by LC-LIT-MS and LC-Q-TOF-MS Chee Wei Lim a,⇑, Kit Yee Lai a, Jie Fang Yeo a, Siew Hoon Tai b, Sheot Harn Chan a a b
Food Safety Laboratory, Applied Sciences Group, Health Sciences Authority, 11 Outram Road, Singapore 169078, Singapore AB SCIEX (Distribution), 10 Biopolis Road, #03-06, Chromos, Singapore 138670, Singapore
a r t i c l e
i n f o
Article history: Received 12 June 2014 Received in revised form 25 September 2014 Accepted 11 November 2014 Available online 15 November 2014 Keywords: Moniliformin Cereals Diagnostic PHREE purification Mass spectrometry
a b s t r a c t The availability of a simple chemical precipitation workflow aided by targeted and untargeted mass spectrometry would provide an accurate diagnostic platform for the direct determination of moniliformin in cereals for food safety control. In-house method validation was performed at six concentration levels of 8, 40, 80, 200, 400, and 600 ng g1 in cereal flours of wheat, corn, rye, oats and barley. Spiking experiments were made at three concentration levels of 20, 40 and 100 ng g1. Protein precipitation and ‘‘PHREE’’ column cleanup strategy provided recoveries of 81–108% for all cereals matrices using external calibrants. ‘‘PHREE’’ purification provided significant (p < 0.05) ion signal enhancement reduction advantage for all matrices except corn flour. Moniliformin underwent significant (p < 0.05) degradation over 2 weeks when prepared in acidified water. A simple, low-cost and fit-for-purpose procedure for the identification and quantitation of moniliformin in cereals becomes available to support prospective regulatory function. Ó 2014 Elsevier Ltd. All rights reserved.
1. Introduction Moniliformin is a mycotoxin produced by several Fusarium species on cereals crops and has been widely reported to be present in localised pockets across three continents including Europe, North America and Pacific Rim (Chelkowski, 1989; Chelkowski, Zajkowli, Zawadzki, & Perkowski, 1987; Lamprecht, Marasas, Thiel, Schneider, & Knox-Davis, 1986; Lew, Chelkowski, Pronczuk, & Edinger, 1996; Scott, Abbas, Mirocha, Lawrence, & Weber, 1987; Thalman, Matzenauer, & Gruber-Schley, 1985; Thiel, Meyer, & Marasas, 1982). Although moniliformin is reported to inflict toxicological effects on several avian species such as cockerels and ducklings (Scarpino, Blandino, Negre, Reyneri, & Vanara, 2013; Von Bargen, Lohrey, Cramer, & Humpf, 2012), the European Food Safety Authority (EFSA) is currently working on a scientific opinion on the risk of moniliformin for public health (EFSA, 2010). As a small and highly polar molecule, moniliformin exists as a water-soluble sodium or potassium salt in nature (Steyn, Thiel, & Van Shalkwyk, 1978). Several analytical methods were reported previously for moniliformin identification and quantitation. They include the application of hyphenated liquid chromatograph coupled to different detectors such as ultraviolet (UV), diode array ⇑ Corresponding author. Tel.: +65 6213 0756; fax: +65 6213 0749. E-mail addresses: [email protected], [email protected] (C.W. Lim). http://dx.doi.org/10.1016/j.foodchem.2014.11.069 0308-8146/Ó 2014 Elsevier Ltd. All rights reserved.
detector (DAD), electrospray ionisation (ESI) and atmospheric pressure chemical ionisation (APCI) mass spectrometry (Jin, Han, Cai, Wu, & Ren, 2010; Munimbazi & Bullerman, 1998; Scarpino et al., 2013; Sewram, Nieuwoudt, Marasas, Sheperd, & Ritieni, 1999; Sørensen, Nielsen, & Trange, 2007). Common to these analytical methods, an independent HRMS confirmation tool was not applied to address analyte specificity needs. The absence of a confirmation technique with high analyte specificity could create identification challenges to analysts because in real samples, interference due to co-elution can occur. To improve method sensitivity and specificity, a high resolution mass spectrometry (HRMS) aided by carbon labelled isotopic dilution strategy was reported recently (Von Bargen et al., 2012). The application of HRMS as the go-to analytical tool of choice for moniliformin detection reflects the demand for high quality data needed to support health policy formulation. For this reason, we developed a novel cereals purification workflow aided by HRMS without the need to apply isotopic dilution. A modified protein precipitation-mediated pathway that bears on cereals composition was introduced for the first time, aided by the application of a protein exclusion purification column known as ‘‘PHREE’’ (a brand from Phenomenex, Torrance, CA). The application of strong anion exchanger (SAX) columns (Munimbazi & Bullerman, 1998; Sørensen et al., 2007; Von Bargen et al., 2012), as well as non-polar C18-columns (Shepherd & Gilbert, 1986) for moniliformin detection were reported previously. For Jin et al.
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(2010) and Scarpino et al. (2013), respectively, home-make SPE columns and commercially available MycoSepÒ 240 moniliformin clean-up column were used for moniliformin detection. Common to these publications, no statistical data treatment (at 95% confidence interval) was reported to quantify the benefits of applying SPE purifications for moniliformin detection. In our study, we applied paired t-test to quantify the benefits of applying ‘‘PHREE’’ purification at 95% confidence interval. So, for the first time, method accuracy, precision, selectivity, sensitivity, repeatability and moniliformin stability in individual major cereal flours of maize, oats, wheat, barley and rye were examined. Measurement uncertainty was used to quantify the benefits of applying ‘‘PHREE’’ purification. Method robustness was assessed using 52 real cereals flours. For the purpose of performing confirmation, a Q-TOF instrument was used. This way, a clear scoring system for the accurate determination of moniliformin in cereals can be achieved to support regulatory function. 2. Materials and methods 2.1. Instrumentation In this paper, we selected two independent techniques for the accurate identification and quantitation of moniliformin in cereals. For experiments involving method validation, we selected multiple-reaction-monitoring transition (MRM-transition) quantitation strategy as our primary analytical method of choice. An Agilent model 1290 infinity LC (Palo Alto, CA, USA) coupled to a Qtrap 5500 MS instrument (AB SCIEX, Foster City, CA, USA) mass spectrometer was applied. The LC system comprised of four solvent reservoirs, a built-in degasser, two binary pumps and a refrigerated auto-sampler. In order to extend the servicing life of the LC column, as well as to minimise potential contamination to the MS instrument, an inline filter (0.3 lm, Agilent Technologies, Palo Alto, CA, USA) was used. Briefly, moniliformin was separated using a Gemini column (a brand from Phenomenex, C6-Phenyl, 3 lm, 50 2 mm Torrence, CA, USA) with a flow rate of 0.4 mL min1. The LC column was maintained at room temperature for all experiments. Mobile phases A and B consisted of methanol and ultrapure water respectively, each containing 0.1% acetic acid. Gradient elution was applied as follows: 100% B hold 2 min, 100–0 in 0.5 min and hold 1.5 min, 0–100% in 0.5 min and hold 1.5 min. The separated analyte was then ionised using electrospray ionisation and detected by tandem mass spectrometry. Electrospray ionisation was performed in negative ionisation mode under MRM-transition condition because moniliformin produced a single salient product ion identified as mass-to-charge ratio (m/z) 41 (Jestoi, Rokka, Rizzo, & Peltonen, 2003; Von Bargen et al., 2012) when infusion was performed by using a 100 ng mL1 standard solution made in mobile phase B. Electrospray voltage was set to 5.5 kV. Source temperature and nitrogen gas flows (GS1 and GS2) were set to 500 °C and 45 psi, respectively. Collision cell energy was optimised as 23 eV. Dwell time and scan rate were set to 200 ms and 1000 da s1, respectively, for the entire duration of the experiment. For experiments involving suspect sample confirmation, we employed the 5600+ Q-TOF (AB SCIEX, Foster City, CA, USA). MS conditions related to ion spray voltage floating (in kV), temperature (in °C) and nitrogen gas flow (GS1 and GS2) were reproduced from QTRAP 5500 settings for MRM-transition experiments, with the exception of collision cell energy (CE = 35 eV). The HRMS method file comprised of two experiments in a single period. The first and second experiments in the MS method file were programmed to perform full scan IDA (mass range from 80–65) and MS/MS (mass range from 40–650) data acquisition, respectively.
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Accumulation times for IDA and MS/MS experiments were 150 and 200 ms, respectively. HRMS scan resolution power was approximately 20,000 fwhm based on m/z 609.28066 (C33H40N2O9, reserpine). By applying this HRMS method programming strategy, for example, an MS/MS scan will be triggered when an m/z value of 96.99 (for moniliformin, [MH]) was detected during the full scan mode. 2.2. Materials and reagents Moniliformin of 99.0% purity was purchased from Sigma– Aldrich and received in neat form. Methanol and acetic acid were of HPLC grade from Labscan. Acetic acid was prepared as 0.1% acetic acid in ultrapure water, purified by passing through a Purelab Option-Q water purification system (a brand from Elga, UK). Methanol was used to prepare moniliformin standard stock solution. From this stock solution, fresh calibrants of moniliformin were prepared by dilution using ultrapure water (containing 0.1% acetic acid) at six concentration levels of 1, 5, 10, 25, 50, and 75 ng mL1, as required. Moniliformin standard was used as-received without further purification. Unused standards were discarded immediately. Cereal flours of wheat, rye, barley, oat and corn were purchased from a local confectionary and tested for the presence of moniliformin before use. A single batch of cereal flours was used to perform method development and validation. For method robustness assessment, random retail sampling was performed for a total of 52 cereal flours comprised of a random mixture of wheat, rye, barley, oat and corn. For all cereals samples, homogenisation was performed by blending prior to use. Sample extraction solvent was prepared as 80% acetonitrile in mobile phase B. 2.3. Sample preparation and extraction Extraction was performed by applying a modified workflow published previously for trichothecenes in grains analysis (Lim, Tai, Lee, & Chan, 2011). For the purpose of performing method validation and unknown sample assessment, 5-g (w) sample weight was taken. Briefly, 20 mL (v1) of extraction solvent was added to an aliquot cereal flour sample and shaken for 30 min. The mixture was centrifuged at 8000 rpm (3226g) for 6 min at room temperature. An aliquot of the supernatant was diluted using an equal volume (v2) of mobile phase B. Next, the diluted supernatant was shaked vigorously and 1 mL (v3) purified using a commercially available ‘‘PHREE’’ column (a brand from Phenomenex, Torrence, CA, USA). No ‘‘PHREE’’ column conditioning required before use. 5 lL of the final purified supernatant was injected into the LCMSMS/Q-TOF for analysis. This way, a solute to solvent ratio of 1:8 can be achieved. The ‘‘PHREE’’ columns were originally designed to remove proteins and phospholipids from plasma samples. In this study, we evaluated the feasibility of applying ‘‘PHREE’’ purification as a solution to address ion signal enhancement for moniliformin detection in cereals using MS. 2.4. Evaluation of signal enhancement/suppression effect and detection limit Matrix effect assessment provides information related to ion signal enhancement/suppression due to co-extractants over a practical concentration range. For this reason, spiking experiments were made at six concentration levels of 1, 5, 10, 25, 50, and 75 ng mL1 (S). By performing post-extraction spiking experiments, it is possible to identify and distinguish interference due to co-extractants from effects due to recovery. Spiking concentration levels (C, in ng g1) were determined as:
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C ¼ ðS=wÞ ðv 1 þ v 2Þ v 3;
ð1Þ
By applying the formula in Eq. (1), the six spiking concentration levels of 8, 40, 80, 200, 400, and 600 ng g1 (n = 3) can be made in individual cereal extract. Ion signal enhancement/suppression (M) was assessed as:
ð2Þ
Linearity was assessed using a residual plot and statistical test for goodness-of-fit. LOD and LOQ were calculated as (2.33 standard deviation)/Gradient of slope and LOD + (1.64 standard deviation)/Gradient of slope, respectively (European Commission, 2006). 2.5. Recovery, intra-day and inter-day repeatability studies A 5-g aliquot of individual cereal flour was spiked with moniliformin at three concentration levels of 5, 10 and 25 ng mL1 (40, 80 and 200 ng g1) and extracted using protocols described under ‘‘sample preparation and extraction’’. Recovery (R) performance was assessed and expressed as:
Abundance (counts)
M ¼ ðArea of matrix-matched standard =Area of matrix-free standardÞ 100;
Polar modified C18
C6-Phenyl
R ¼ ðMean concentration; n ¼ 6intraday;interday =Spiked concentrationÞ 100;
ð3Þ
3. Results and discussion 3.1. Analytical approach The intention of this study was to develop an analytical workflow fit-for-purpose for the direct detection of moniliformin in cereals. To fulfil this objective, we divided our experiments into three phases, namely analyte retention, sample purification and confirmation MS technique selection. Analyte separation represents a fundamental stage for any analytical method development, with the exception of model driven quantitative small molecules analysis (Lim & Chan, 2013; Lim, Tai, & Chan, 2012). For a polar small molecule such as moniliformin, analyte separation is important because interference originating from coextractants present in complex sample matrices implies challenges to accurate quantitative analysis. For this reason, we evaluated two potential LC column candidates of similar dimensions, represented by Gemini C6 Phenyl column (Phenomenex, Torrence, CA, USA) and Synergi polar C18 column (Phenomenex, Torrence, CA, USA). Analyte retention was applied as assessment criterion. Owing to differences in LC column stationary phase between the two candidates examined, chromatographic separation conditions such as flow rate and elution time were individually optimised. Fig. 1 summarises the chromatographic performance of applying Gemini C6 Phenyl column as the LC column of choice over Synergi Polar C18 column. Our observation that Gemini C6 Phenyl column offers superior performance for moniliformin retention is consistent with report published previously (Von Bargen et al., 2012). Within the framework of analytical chemistry, it is established that analyte separation can be achieved via two strategies. They include physical separation using classical method such as LC column to perform chromatographic separation, as well as using the enhanced analyte specificity offered by triple-stage mass spectrometry (Khiu, Lim, Lee, Yap, & Chan, 2014; Lim & Chan, 2013; Ting, Rad, Gygi, & Hass, 2012). In this work, however, moniliformin produced a single salient daughter ion fragment of m/z 41. Due to its inherently small ion fragment (m/z smaller than 50), triple-stage mass spectrometry becomes an unsuitable candidate for moniliformin assessment. Moreover,
Time (min) Fig. 1. Ion chromatograms comparing retention times of moniliformin using C6Phenyl column and polar modified C18 column.
the linear-ion-trap is designed to measure ion fragments greater than or equal to m/z 50. The adaptation of Gemini C6 Phenyl column as the LC column of choice implies user confidence in moniliformin identification via its retention time can be achieved. With challenges related to analyte retention addressed, we examined the next phase of our experiment involving sample purification. Here, we applied a modified workflow published previously for trichothecene assessment (Lim et al., 2012). Instead of using pure acetonitrile as the extraction solvent of choice, 20% ultra-pure water acidified using acetic acid was added. The motivation for using an 80:20 acetonitrile/water composition is consistent with the analytical strategy applied for the recovery of multi-mycotoxins from maize and grains published previously (Sulyok, Berthiller, Krska, & Schuhmacher, 2006). The presence of 0.1% acetic acid to the extraction solvent implies some soluble flour and gluten protein would be co-extracted as well (Kurowska & Bushuk, 1988). The presence of solubilised protein or gluten in the sample extract would present technical challenges when MS is applied as the analytical tool of choice. Therefore we can expect to observe some ion signal variation effects since solubilised compounds such as protein or gluten originating from cereals can interfere with the electrospray ionisation processes, such as via mechanisms published previously (Trufelli et al., 2011). For these reasons, a simple and easy sample purification procedure is required, such as the sample purification strategy reported by Scarpino et al. (2013) using MycoSepÒ 240 moniliformin cleanup
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column. Two experiments were made to investigate the dominant physical phenomena when sample extraction was performed by using extraction solvent alone and when 1:1 dilution using mobile phase B was applied. For the first experiment involving direct extraction, a solute to solvent ratio of 1:4 was applied; performing 1:1 dilution would produce a solute to solvent ratio of 1:8. In the former experiment, no apparent precipitate was observed for all cereal flours of wheat, corn, rye, oats and barley. When 1:1 dilution was performed, white/pale yellow precipitate was observed for all cereal extracts except corn. Although the analytical approach for precipitation applied in our study is reversed in comparison to conventional protein precipitation involving the application of 80% or greater fractions of acetonitrile content, the function of achieving organic content reduction through precipitation is met. 3.2. Evaluation of matrix effect in cereals Within the framework of mass spectrometry, protein precipitation represents a key purification strategy applied to address ion signal enhancement or suppression effects due to the presence of co-extractants originating from a complex food matrix such as wheat. Wheat is produced in the miller through a series of processing steps including cleaning, blending, conditioning, breaking, sifting, bleaching and enriching, amongst others, to obtain the final flour (Martin, Leonard, & Stamp, 1976). Although the wheat milling process would eliminate those portions of the wheat kernel such as bran, germ, and shorts that are richest in proteins, vitamins, lipids and minerals, we expect some percentage of protein to remain in the final flour (Wang et al., 2008). For a wheat sample extracted using a solvent system comprised of 20% weakly acidified water, we expect interference originating from components such as water soluble amino acids in the flour (from endosperm that forms the bulk of cereal flours) and water soluble albumins to be significant when electrospray ionisation was applied. Indeed, the albumin represents 9% of weed seed proteins (Singh & Skerritt, 2001). For example, molecular weights of albumins range from 12 to 64 kDa, with the high molecular weight albumins in the range of 45–65 kDa (Bean & Tilley, 2003; Majoul, Bancel, Triboi, Hamida, & Branlard, 2004; Singh & Skerritt, 2001). Owing to the unavailability of a suitable labelled isotopic standard for a small molecule such as moniliformin, sample purification achieved through the removal of these soluble proteins becomes an important step for quantitative analysis. To do this, we applied a new protein purification column known as ‘‘PHREE’’ after sample dilution was performed. The principle of ‘‘PHREE’’ purification system is based on protein size exclusion. For a small molecule such as moniliformin, we do not expect losses due to the application of ‘‘PHREE’’ purification to be significant. Matrix effect was therefore examined. Table 1 summaries the ion signal enhancement/suppression effects for different concentrations of moniliformin made in individual cereal extract. To better quantify the significance of applying ‘‘PHREE’’ purification strategy, we applied paired t-test at 95% confidence interval because sample purification was made using the same sample extract that received no purification. From Table 1, the application of ‘‘PHREE’’ purification strategy would benefit cereal extract of wheat, rye, barley and oat significantly (p < 0.05). Interestingly, corn sample extract did not benefit significantly from the application of ‘‘PHREE’’ column purification, as judged basing on matrix effects data shown in Table 1. Although the application of our sample extract purification strategy implies not all cereal extracts would benefit significantly, fine particulate yellow coextractants of corn origin was visibly removed. Indeed, the benefit of applying sample purification is evident by the absence of precipitate depositing around the periphery of the orifice on the curtain plate on the MS instrument. Excessive deposits that formed around
Table 1 Matrix effects on LC–MS/MS detection of Moniliformin in individual cereal extracts of wheat, corn, rye, oats and barley by applying MRM-transition quantitation strategies at six concentration levels of 8, 40, 80, 200, 400, 600 ng g1, before and after applying PHREE purification. Concentration ng ml1 (ng g1)
%, Matrix effecta for MRM (97 > 41) Wheat
Before PHREE purification 1 (8) 5 (40) 10 (80) 25 (200) 50 (400) 75 (600) After PHREE purification 1 (8) 5 (40) 10 (80) 25 (200) 50 (400) 75 (600)
Rye
Barley
Oat
Corn
140 121 120 116 119 119
127 128 129 129 124 126
166 132 129 126 124 125
224 140 123 116 114 115
366 165 132 118 114 115
123* 110* 110* 110* 109* 110*
113* 116* 115* 115* 113* 116*
112* 110* 115* 110* 110* 110*
163* 115* 111* 105* 104* 106*
227 125 114 106 105 105
a The ion signal suppression (<100) or enhancement effect (>100) was assessed as [(peak area of matrix-matched standard)/(peak area of matrix-free standard)] 100 in percent. * Indicates significantly different from those before PHREE purification, (p < 0.05) at 95% confidence interval using paired t-test.
the periphery of the orifice imply a through-path to the mass detector is now made less accessible. For sample extracts that received little purification, it was necessary to include curtainplate cleaning protocol using ultra-pure water after approximately every 50–60 injections were made. Clearly, the application of our chemical precipitation and purification protocol provided the benefits of significantly reduced ion signal enhancement effect (except for corn) and uninterrupted measurements to be made in a single analysis. 3.3. Evaluation of recovery, linearity, intra-day and inter-day repeatability Although the application of our modified precipitation workflow implies the analysis of other important analytes in complex food matrices would be applicable as well, it is also necessary to examine the effects of competing co-occurring processes such as protein encapsulation (Chen, Lim, & Chan, 2014) and analyte extraction on recovery performance. To do this, we examined the recovery performance of moniliformin in cereal extracts of wheat, rye, barley, oat and corn. Sample purification was achieved by applying drop-wise dilution described under ‘‘sample preparation and extraction’’. In order to quantify the effects of applying drop-wise dilution strategy on recovery performance, spiking experiments were made at three concentration levels of 40, 80, and 200 ng g1. Table 2 showed recovery performance of moniliformin in individual cereal flour ranged from 81% to 108%. Intra-day and inter-day variation yielded satisfactory results, ranged from 2% to 15%. Based on the recovery results shown in Table 2, there is insufficient evidence to show protein encapsulation can occur for moniliformin in cereals. In comparison to analytical methods involving the use of stable carbon labelled isotopic dilution strategy (Von Bargen et al., 2012) to address recovery challenges for mycotoxins assessment, the application of our validated protocol implies direct access to satisfactory data quality using a simple, efficient and low-cost chemical precipitation pathway is now available. Simply, synthetic pathway described previously to produce labelled isotopic standards of moniliformin to address recovery losses in cereals (Von Bargen et al., 2012) would become redundant. Further, recovery losses due to drying down and reconstitution step reported previously
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Table 2 Mean recovery (in percent) of spiking experiments made at three concentration levels of 5, 10 and 25 ng mL1 (40, 80 and 200 ng g1) in cereal flours, assessed using matrix-free calibrant. Intra-day and inter-day RSD values (n = 6) are shown in brackets. Cereals
Wheat Rye Barley Oat Corn
Mean recovery of moniliformin (RSDintra-day, RSDinter-day) 5 ng mL1 (40 ng g1)
10 ng mL1 (80 ng g1)
25 ng mL1 (200 ng g1)
LOD (lg g1)
LOQ (lg g1)
98 (2, 2) 100 (5, 5) 100 (3, 4) 103 (7, 7) 90 (3, 3)
102 (8, 104 (6, 102 (8, 106 (6, 84 (13,
98 (5, 6) 108 (6, 6) 91 (7, 7) 81 (6, 6) 81 (13, 15)
0.5 1 0.5 0.5 1
1.5 3 1.5 1.5 3
4) 6) 5) 8) 5)
by Scarpino et al. (2013) is now circumvented since a simple dilution step prior to the application of ‘‘PHREE’’ purification would be fit-for-purpose. In this paper, time and effort required to perform SPE column pre-conditioning reported previously (Munimbazi & Bullerman, 1998; Sørensen et al., 2007; Von Bargen et al., 2012) for MON detection was conserved. The recovery range reported in our study represented an improvement over those reported previously using non-protein exclusion column, with values ranged from 57% to 74% in maize (Jin et al., 2010; Sørensen et al., 2007). Matrix-free and matrix-matched calibration curves were linear over the relevant working range with correlation coefficient values of between 0.9990 and 0.9998, as assessed basing on individual residual-plots and goodness-of-fit test. LOD and LOQ values in cereals were determined as 1 and 3 ng g1, respectively, with rye and corn flours providing the least sensitive LOD and LOQ values. These LOD and LOQ values are comparable with the results presented by Von Bargen et al. (2012). 3.4. Evaluation of moniliformin stability In our study, we report for the first time on moniliformin stability when prepared in water-enriched mobile phase B. The same set of sample vials containing calibrants and spiked experiments were measured 2 weeks after recovery performance was assessed. Samples vials were stored at 4 °C when not in use. For comparison purpose, a fresh set of calibrants made in mobile phase B was prepared. Uninterrupted measurements were made in a single analysis. For the same set of sample vials (2 weeks old) containing spiked solutions of moniliformin, the recovery values ranged from 144% to 198% (Table 3). When the same set of sample vials were read against a set of freshly prepared calibrants, recovery values ranged from 52% to 108% (Table 3). These widely ranging recovery values suggested moniliformin underwent significant (p < 0.05) degradation when prepared in mobile phase B, amongst others. Therefore, we recommend practicing fresh preparation of moniliformin calibrant as a quality control strategy when made in water-enriched solvent system such as mobile phase B. Table 3 Moniliformin stability study (2 weeks) showing mean recovery (in percent, n = 6) of spiking experiments made at three concentration levels of 5, 10 and 25 ng mL1 (40, 80 and 200 ng g1) in cereal flours, assessed using matrix-free calibrants. Mean recovery values (in percent, n = 6) determined using freshly prepared Moniliformin calibrants on 2 weeks old sample vials are shown in brackets. Cereals
Wheat Rye Barley Oat Corn
Mean recovery of moniliformin2 weeks old calibrants ðRFresh calibrants Þ 5 ng mL1 (40 ng g1)
10 ng mL1 (80 ng g1)
25 ng mL1 (200 ng g1)
179 181 179 198 144
162 183 182 191 148
161 183 179 184 145
(74) (76) (74) (86) (52)
(83) (97) (96) (102) (74)
(95) (108) (106) (109) (81)
3.5. Measurement uncertainty In this paper, we applied an adapted protocol for uncertainty evaluation reported previously (Pantazopoulos, 2001). For the assessment of moniliformin in cereal extracts of wheat, rye, barley, oat and corn, the relative expanded uncertainty (with 95% of confidence level) was significantly larger (p < 0.05) in samples that received no ‘‘PHREE’’ purification. The application of ‘‘PHREE’’ purification strategy equipped analyst with lower uncertainty range. This was represented by the combined uncertainty in cereal extracts of wheat, rye, barley, oat and corn at less than 18%. For cereal extracts that received no ‘‘PHREE’’ purification, the corresponding combined uncertainty was determined to be about 40%. Amongst cereal extracts of wheat, rye, barley, oat and corn, corn contributed significantly towards the largest uncertainty for bias. The application of ‘‘PHREE’’ purification would provide a significant improvement for method bias, which represented the major contributing factor towards uncertainty calculation. We can therefore conclude that chemical precipitation aided by ‘‘PHREE’’ purification pathway improved measurement uncertainty in a single workflow by providing greater accuracy in the quantitation of moniliformin in cereals. 3.6. Selection of confirmation MS technique The single salient mass fragment of moniliformin implies a high resolution confirmation technique is required to achieve the minimum identification point of 3.0 (Commission Decision 2002/657/ EC). To fulfil this criterion, we considered and applied a readily accessible 5600+ Q-TOF instrument housed (remotely) within ABSciex facility in Singapore. Experimental conditions related to LC column, gradient separation, MS conditions (with off-set value for collision cell energy of 35 eV) and mobile phases were reproduced using the same set of sample vials. For the purpose of performing method robustness assessment, 52 cereals samples were first screened by using the QTrap 5500. Suspect samples were then confirmed using the 5600+ Q-TOF instrument. This way, an accurate and time efficient workflow involving suspect sample identification and confirmation can be achieved to benefit a laboratory with wide analytical base. 3.7. Assessment of real samples 52 cereals samples comprised of a mixture of individual wheat, rye, barley, oat and corn flours were analysed using our validated protocol. Amongst the cereals samples analysed, two samples of corn and oats flours of non-asian origin provided a single salient peak matched to moniliformin standard retention time when MRM-transition was applied on the Qtrap 5500. For this reason, we performed an information dependent analysis on both suspect samples. Briefly, the Analyst TF software on the 5600+ Q-TOF was programmed to perform an enhanced product ion scan when the MRM-transition parameters used on the Qtrap 5500 were fulfilled. Using the scan spectrum generated by the enhanced product ion scan on the 5600+ Q-TOF for individual suspect sample, we performed a match against the scan spectrum obtained when pure standard of moniliformin was used. From Fig. 2a, pure moniliformin standard (about 50 ng mL1) produced two distinctive ‘‘peaks’’ when an HRMS scan (m/z 40–620) was applied to determine its exact mass [MH]. These base values were m/z 96.9929 (mass error of 2.2 ppm) and 96.9602, respectively, for moniliformin and the unknown contaminant. Owing to the unavailability of stable carbon-labelled isotopic standard solution of moniliformin, isotopic fingerprint matching could not be performed experimentally, as reported previously (Von Bargen et al., 2012). For this reason, we could not apply the guidelines recommended by Commission Deci-
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(a) Moniliformin standard
HRMS-Scan
HRMS/MS-Scan 41.0034
96.9929 (12C 96.9931)
97.9963 (13C1 97.9965)
96.9602
Abundance (counts)
Impuries
(b) Suspect oats/corn
96.9602
Absent
Absent
Fragmentaon pathway
(c) Spiked suspect oats/corn
96.9929 (A)
96.9602
41.0034 (B)
(A) C4HO3-
(B) C2HO-
97.9963 m/z
Fig. 2. Scan spectra representing HRMS-Scan and HRMS/MS-Scan of (a) Moniliformin standard (about 50 ng mL1), (b) suspect oats and corn samples, and (c) spiked suspect oats and corn samples at 10 ng g1 (limits of detection). Theoretically calculated values are shown in brackets. Moniliformin fragmentation pathway presented inset.
sion 2002/657/EC of the European Commission that accepts 50% variation of labelled moniliformin ratio relative to its unlabelled form. Rather, we performed a scan on the moniliformin standard and matched its isotopic fingerprint to the theoretical values 12C (m/z 96.9931) and 13C1 (m/z 97.9965). We could not see the 13C2 peak in our scan spectrum and therefore, no mass error value was reported. This way, mass errors of 2.2 and 2.1 ppm were reported for 12C (m/z 96.9929) and 13C1 (m/z 97.9963), respectively. Enhanced product ion scan was also performed to obtain the remaining 2.5 identification points basing on transition ion (m/z 41.0034). From Fig. 2a, moniliformin standard would produce a single salient transition ion of m/z 41.0034. The appearance of two additional product ions of m/z 79.9577 and 78.9604 was attributed to impurities present in the working solution. These impurity product ions (such as m/z 79.9577 and 78.9604) were also detected in both mobile phases and extraction solvent. When both mobile phases and extraction solvent were assessed using the Qtrap 5500, no moniliformin peak was identified. We observed the appearance of these additional impurity-related transition ions on the 5600+ Q-TOF instrument because a wide scan range of m/z 40–620 was applied. When MS/MS scan was performed on the suspect flours of corn and oats using information dependent analysis function available on the Analyst TF software, only two impurity-related product ions m/z 79.9577 and 78.9604 were detected (Fig. 2b).
The transition attributed to moniliformin standard at m/z 41.0034 was not detected. By performing a direct spiking (at LOD of 10 ng g1) into the suspect sample and the analysis repeated using the 5600+ TripleTOF instrument, unambiguous identification and confirmation can be achieved, as shown in Fig. 2c. Clearly, the improved resolution offered by 5600+ TripleTOF enabled analyst to clearly identify a co-eluting impurity and distinguish it from the moniliformin standard. This way, suspect samples shortlisted by applying the Qtrap 5500 MS instrument can be confirmed. Indeed, by comparing individual ion chromatogram (Fig. 3, Qtrap 5500) of the suspect sample (for example corn flour) against the moniliformin standard, we observed a significant difference (p < 0.05) in the base peak-widths (indicated by the unshaded arrows). The application of 5600+ Q-TOF as a confirmation tool therefore transforms arbitrary visual ion chromatogram inspection (on Qtrap 5500) into distinctive quantitative benefits through exact mass identification, isotopic fingerprint matching and transition ion matching functions. The need to utilise a high resolution MS tool so that analysts can become equipped with the confidence needed to distinguish moniliformin from interfering ion implies results obtained by using non-specific ultraviolet or diode array techniques becomes questionable today. For a laboratory without immediate and direct access to a HRMS tool, complete chromatographic separation may perhaps remain the single analytical tool needed to combat the pitfalls of false positive due to co-eluents
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References
Abundance (Counts)
Qtrap 5500
Suspect sample
Qtrap 5500
Moniliformin 10 ng mL-1
Time (min) Fig. 3. Ion chromatogram (Qtrap 5500) of suspect sample with (approximately twice) enlarged base-peak width compared to moniliformin standard made at 10 ng mL1.
originating from the cereal samples. Within the entirety of our experiment, we depended solely on the stationary phase surface chemistry to retain moniliformin because the analyte was eluted on a 100% acidified water-dominant chromatographic gradient. 4. Conclusion In conclusion, our study successfully validated a MS workflow fit-for-purpose for the accurate determination of moniliformin in cereals. Method accuracy, precision, selectivity, sensitivity, repeatability, robustness and analyte stability were examined and found to be highly satisfactory. A simple, easy and cost-efficient sample purification strategy using step-wise protein precipitation pathway, aided by ‘‘PHREE’’ purification provided the single solution to address challenges presented by ion signal enhancement when MS was applied as the analytical method of choice for moniliformin detection. Isotopic dilution is not required to compensate for matrix effect in all cereal extracts of wheat, rye, barley, oat and corn. The application of a simple size-exclusion ‘‘PHREE’’ purification step would sufficiently address the need for regular instrument maintenance due to precipitate depositing along the periphery of the orifice on the curtain plate, thereby enabling uninterrupted measurements to be made. Quantitative degradation of moniliformin (in acidified water) was reported for the first time. For suspect samples, confirmation using high resolution MS is required because the MRM-transition using single ion pair as identifier did not provide sufficient identification points. A simple, easy and validated analytical workflow aided by high resolution mass spectrometry becomes available for the assessment of important cereals of wheat, rye, barley, oat and corn. 5. Conflict of interest The authors declare there are no conflicts of interest. Acknowledgement The authors would like to thank HSA-FSD for providing the funding to support this in-house method validation study.
Bean, S. R., & Tilley, M. (2003). Separation of water-soluble proteins from cereals by high-performance capillary electrophoresis (HPCE). Cereal Chemistry, 80, 505–510. Chelkowski, J. (Ed.). (1989). Mycotoxins associated with maize cob fusariosis. Fusarium-mycotoxins, taxonomy, and pathogenicity. Amsterdam: Elsevier, p. 53–62. Chelkowski, J., Zajkowli, P., Zawadzki, M., & Perkowski, J. (1987). Moniliformin, deoxynivalenol, 3acetyldeoxynivalenol and zearalenone-mycotoxins associated with maize cob fusariosis in Poland. Mycotoxin Research Special Issue, 3, 25–27. Chen, Y. H., Lim, C. W., & Chan, S. H. (2014). Evaluation of triple stage mass spectrometry as a robust and accurate diagnostic tool for determination of free cordycepin in designer egg. Food Chemistry, 150, 213–219. European Commission (2006). No 401/2006 Laying down the methods of sampling and analysis for the official control of the levels of mycotoxins in foodstuffs. Official Journal of the European Union, L 70, 1–12. European Food Safety Authority (EFSA) Request for a scientific opinion on the risks for public health related to the presence of moniliformin in feed and food, Mandate M-2010-0312, Reception date 21-07-2010, Acception Date 09-092010. Jestoi, M., Rokka, M., Rizzo, A., & Peltonen, K. (2003). Moniliformin in finnish grains: Analysis with LC–MS/MS. Aspects of Applied Biology, 68, 211–216. Jin, P. G., Han, Z., Cai, Z. X., Wu, Y. J., & Ren, Y. P. (2010). Simultaneous determination of 10 mycotoxins in grain by ultra-high-performance liquid chromatographytandem mass spectrometry using 13C15-deoxynivalenol as internal standard. Food Additives & Contaminants: Part A, 27, 1701–1713. Khiu, K. W., Lim, C. W., Lee, L. M., Yap, W. K., & Chan, S. H. (2014). Triple-stage mass spectrometry as the go-to physic-chemical tool for the accurate assessment of multi-mycotoxins in processed chilli of Asian origin. World Mycotoxin Journal, (in press). Kurowska, E., & Bushuk, W. (1988). Solubility of flour and gluten protein in a solvent of acetic acid, urea, and cetyltrimethylammonium bromide, and its relationship to dough strength. Cereal Chemistry, 65, 156–158. Lamprecht, S. C., Marasas, W. F. O., Thiel, P. G., Schneider, D. J., & Knox-Davis, P. S. (1986). Incidence an toxigenicity of seedborne Fusarium species from Annual Medicago species in South Africa. Phytopathology, 76, 1040–1041. Lew, H, Chelkowski, J., Pronczuk, P., & Edinger, W. (1996). Occurrence of the Mycotoxin moniliformin in maize (Zea mays L.) ears infected by Fusarium subglutinans (Wollenw & Reinking) Nelson et al. Food Additives and Contaminants, 13, 321–324. Lim, C. W., & Chan, S. H. (2013). Single laboratory method validation comparing MS3 with FI/MS fingerprinting, and quantitation strategies for the accurate determination of ochratoxins in beer. World Mycotoxin Journal. http:// dx.doi.org/10.3920/WMJ2012.1522. Lim, C. W., Tai, S. H., & Chan, S. H. (2012). A flow-injection mass spectrometry fingerprinting scaffold for feature selection and quantitation of Cordyceps and Ganoderma extracts in beverage: A predictive artificial neural network modeling strategy. AMB Express, 2, 43. Lim, C. W., Tai, S. H., Lee, L. M., & Chan, S. H. (2011). Analytical method for the accurate determination of trichothecenes in grains using LC–MS/MS: A comparison between MRM transition and MS3 quantitation. Analytical and Bioanalytical Chemistry, 403, 2801–2806. Majoul, T., Bancel, E., Triboi, E., Hamida, J. B., & Branlard, G. (2004). Proteomic analysis of the effect of heat stress on hexaploid wheat grain: Characterisation of heat-responsive from non-prolamins fraction. Proteomics, 4, 505–513. Martin, J. H., Leonard, W. H., & Stamp, D. L. (1976). Principles of field crop production (3rd ed.). New York, NY: Macmillan publishing Co., Inc. Munimbazi, C., & Bullerman, L. B. (1998). High-performance liquid chromatographic method for the determination of moniliformin in corn. Journal of the Association of Official Analytical Chemists International, 81, 999–1004. Pantazopoulos, P. (2001). Uncertainty estimate for: Procedure ONT-FCL-0024 determination of ochratoxin A in wine and grape juice by high performance liquid chromatography with fluorescence detection. Food Laboratory Division, Ontario Region, 17–22. Scarpino, V., Blandino, M., Negre, M., Reyneri, A., & Vanara, F. (2013). Moniliformin analysis in maize samples from North-West Italy using multifunctional cleanup columns and the LC–MS/MS detection method. Food Additives & Contaminants: Part A, 30, 776–884. Scott, P. M., Abbas, H. K., Mirocha, C. J., Lawrence, G. A., & Weber, D. (1987). Formation of moniliformin by Fusarium sporotrichioides and Fusarium culmorum. Applied and Environmental Microbiology, 53, 196–197. Sewram, V., Nieuwoudt, T. W., Marasas, W. F. O., Sheperd, G. S., & Ritieni, A. (1999). Determination of the Mycotoxin moniliformin in cultures of Fusarium subglutinans and in naturally contaminated maize by high-performance liquid chromatography-atmospheric pressure chemical ionization mass spectrometry. Journal of Chromatography A, 848, 185–191. Shepherd, M. J., & Gilbert, J. (1986). Method for the analysis in maize of the Fusarium mycotoxin moniliformin employing ion-pairing extraction and high performance liquid chromatography. Journal of Chromatography, 358, 415–422. Singh, J., & Skerritt, J. H. (2001). Chromosomal control of albumins and globulins in wheat grain assessed using different fractionation procedures. Journal of Cereal Science, 33, 163–181.
C.W. Lim et al. / Food Chemistry 174 (2015) 372–379 Sørensen, J. L., Nielsen, K. F., & Trange, U. (2007). Analysis of moniliformin in maize plants using hydrophilic interaction chromatography. Journal of Agricultural and Food Chemistry, 55, 9764–9768. Steyn, M., Thiel, P. G., & Van Shalkwyk, G. C. (1978). Isolation and purification of moniliformin. Journal of the Association of Official Anaytical Chemists, 61, 578–580. Sulyok, M., Berthiller, F., Krska, R., & Schuhmacher, R. (2006). Development and validation of a liquid chromatography/tandem mass spectrometric method for the determination of 39 mycotoxins in wheat and maize. Rapid Communications in Mass Spectrometry, 20, 2649–2659. Thalman, A., Matzenauer, S., & Gruber-Schley, S. (1985). Untersuchungen über das Vorkommem von Fusarientoxinen in Getreide. Ber über Landwirtsch, 63, 257–272. Thiel, P. G., Meyer, C. J., & Marasas, W. F. O. (1982). Natural occurrence of moniliformin together with deoxynivalenol and zearalenone in Transkeian maize. Journal of Agricultural and Food Chemistry, 30, 308–317.
379
Ting, L., Rad, R., Gygi, A. P., & Hass, W. (2012). MS3 eliminates ratio distortion in isobaric labelling-based multiplexed quantitative proteomics. Nature Methods, 8, 937–940. Trufelli, H., Palma, P., Famiglini, G., & Cappiello, A. (2011). An overview of matrix effects in liquid chromatography–mass spectrometry. Mass spectrometry Reviews, 30, 491–509. Von Bargen, K. W., Lohrey, L., Cramer, B., & Humpf, H. U. (2012). Analysis of the fusarium mycotoxin moniliformin in cereal samples using 13C2-Moniliformin and high-resolution mass spectrometry. Journal of Agricultural and Food Chemistry, 60, 3586–3591. Wang, A. L., Pei, Y. H., Li, X. H., Zhang, Y. Z., Zhang, Q., He, Z. H., et al. (2008). Rapid separation and characterisation of grain water-soluble proteins in bread wheat cultivars (Triticum asestivum L.) by capillary electrophoresis. Canadian Journal of Plant Science, 88, 843–848.