Rapid and Highly Accurate Detection of Steryl Glycosides by

With regard to chromatographic techniques, ultraperformance liquid .... Each chromatographic peak was integrated using Mass-Lynx 4.1 software (Waters)...
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Rapid and Highly Accurate Detection of Steryl Glycosides by Ultraperformance Liquid Chromatography−Quadrupole Time-ofFlight Mass Spectrometry (UPLC-Q-TOF-MS) Selina R. Oppliger,∥ Linda H. Münger,∥ and Laura Nyström* ETH Zurich Institute of Food, Nutrition and Health, Schmelzbergstrasse 9, CH-8092 Zurich, Switzerland ABSTRACT: This study describes the development and validation of a fast, accurate, and precise UPLC-Q-TOF-MS method for the analysis of steryl glycosides (SGs). The best combination of separation and sensitivity was obtained with a methanol/ water gradient and formic acid as additive, using electrospray ionization (ESI). SGs were detected almost exclusively as sodiated adducts, allowing identification of the intact molecule, including the sugar moiety. The TOF-MS system offered high mass accuracy (1.3 ppm), providing a valuable tool for SG identification. The method was used to quantify single SG species in oat bran and whole wheat, and it was demonstrated that reliable quantification requires accounting for the matrix effect, which may reduce the SG signal by up to 50% in some samples. The level of matrix effect also depends on food matrices with various SG contents, indicating that it should be individually considered for each sample. KEYWORDS: quadrupole time-of-flight, mass spectrometry, steryl glycosides, ultraperformance liquid chromatography



INTRODUCTION Phytosterols are steroid compounds that occur in plants and have a structure similar to that of cholesterol. They are found as free sterols (FSs) or conjugated sterols, such as steryl esters (SEs), steryl glycosides (SGs), or acylated steryl glycosides (ASGs). In plants, SGs are essential structural components that affect the permeability and fluidity of membranes.1 The most common SGs are glucosides of sitosterol, campesterol, and stigmasterol.2 It is widely acknowledged that SGs are associated with several health benefits. In addition to the most prominent function of lowering cholesterol absorption, reduction of benign prostate hyperplasia and enhancement of T-cell proliferation have been reported.3,4 In the food industry, the ability to reduce total serum cholesterol is of special interest, as high blood cholesterol levels are associated with atherosclerosis and cardiovascular disease. Lin et al.5 demonstrated that intake of glycosylated sterols decreased cholesterol absorption by 37.6%, which was comparable to the reduction obtained after the intake of SEs (30.6%). Compared to other sterol conjugates, SGs also have unique physicochemical properties originating from their molecular structures. Their amphiphilic properties, resulting from the hydrophilic sugar moiety and the lipophilic sterol backbone, imply better solubility in more polar solvents when compared to FSs or SEs. Hence, SGs could be introduced into foods with higher water content than the sterol-enriched functional foods that are currently available on the market (margarine, yogurt, etc.). Furthermore, as SGs can contribute to almost 60% of total sterols in certain nonfortified foods,2 it is crucial to include them in total sterol content when sterol intakes from foods are evaluated. However, glycosylated sterols are significantly less studied than other sterol species, mainly as a result of limitations in common analytical procedures. Either SGs are not included in total sterol analysis (when acid hydrolysis is © 2014 American Chemical Society

omitted) or inaccuracies in the sterol composition are caused by the sample preparation (acid-catalyzed isomerization).6,7 Currently, the two main methods for SG separation used for reliable identification and quantification are gas chromatography (GC) and high-performance liquid chromatography (HPLC). Common gas chromatographic methods for SG analysis require acid hydrolysis to analyze the single SG species as FSs. The major disadvantage of this approach is that acid conditions may lead to isomerization of labile sterols (e.g., Δ5avenasterol)7 and, moreover, information about the nature of the sugar is lost. Furthermore, an additional labor-intensive step must be included because derivatization is required to increase the volatility of the released FS. On the other hand, HPLC is well suited for SG analysis because intact SGs can be detected with high selectivity and sensitivity.8 In normal phase (NP) HPLC, total SG content can be quantified,6 whereas in reverse phase (RP) single SG species are separated and the composition of the SG fraction is obtained. Common HPLC methods are combined with ultraviolet (UV), refractive index (RI), or evaporative light scattering detection (ELSD).9,10 With those detectors, identification of individual SG species is difficult due to the lack of pure standard compounds. To overcome this problem, RP-HPLC can be combined with mass spectrometry (MS). The benefits of MS as a detector are its high sensitivity, due to improved signal-to-noise ratio, and its specificity to monitor accurate masses, thereby enabling reliable identification of SGs based on their elemental composition. For HPLC-MS, electrospray ionization (ESI) and atmospheric pressure chemical ionization (APCI) are the two main ionization methods that have been reported for SG analysis.8,11,12 In Received: Revised: Accepted: Published: 9410

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as the organic mobile phase was injected in partial loop mode. All measurements for method development were carried out with the same UPLC gradient from 30% water + additive (A) and 70% organic solvent + additive (B) to 100% B in 3 min, followed by isocratic condition of 100% B for 2 min (total run time = 5 min). Column temperature was maintained at 40 °C with a flow rate of 0.3 mL/min. Each run was followed by re-equilibration period of 3 min with a mobile phase composition of 30% A and 70% B. UPLC Gradient Used for Food Analysis. For a more precise injection volume, 10 μL of the sample was injected in full loop mode. The analysis was performed using the following gradient elution: 50% water + 0.1% (v/v) formic acid (A) and 50% methanol + 0.1% (v/v) formic acid (B) for 1 min changing to 87.5% B during 2 min. During the next 2 min, B was increased to 90% and finally during the next 2 min to 100%, which was kept for 3 min. The total run time was 10 min. The flow rate was 0.3 mL/min and the column temperature, 40 °C. Each run was followed by a re-equilibration period of 3 min with 50% B. MS Conditions. Optimization of Ionization Parameters by Direct Infusion and in Combination with LC. For optimization of the ionization parameters a standard mixture of SG (3 μM, concentration calculated on the basis of the mass of sitosteryl glucoside) was injected by direct infusion into the MS using ESI. For ESI positive-ion mode the voltages of capillary, sample cone, and extraction cone were set at 3000, 60, and 4 V, respectively. The desolvation gas flow rate was 900 L/h at 550 °C. Source temperature was 130 °C. Cone gas flow was 10 L/h. For ESI negative-ion mode the voltages of capillary, sample cone, and extraction cone were set at 2000, 30, and 4.5 V, respectively. The desolvation gas flow rate was 950 L/h at 500 °C. Source temperature was 130 °C. Cone gas flow was 20 L/h. APCI was performed using ESCI multi-mode ionization source. This mode switched between ESI and APCI at a high speed and, thus, made it possible to measure both ionization modes within the same chromatographic run. The ionization parameters were adopted from ESI with the addition of a corona current of 5 μA. Nitrogen served as desolvation gas and as cone gas for both ESI and APCI measurements. Full scan mass spectra were acquired from m/z 50 to 1200 at a scan rate of 0.5 s. EIC of sodium adducts and [M − H + Hac]− were used for method evaluation (Table 1). Peaks were identified on the basis of

comparison to ESI, APCI is a less soft ionization technique that generates more fragment ions relative to the parent ion. Furthermore, the quadrupole time-of-flight (Q-TOF) analyzer is a suitable tool for screening for known and unknown SGs, whereas triple quadrupole (QqQ) is advisible only for monitoring targeted SGs.13 Previously, Wewer et al. reported quantification of SGs by nanospray direct infusion by Q-TOF MS/MS experiments.14 However, no chromatographic separation was conducted in that study prior to MS analysis, which makes the differentiation between isomers impossible. Rocio et al.15 used HPLC-TOF-MS, and Van Gerpen et al.16 used MALDI-TOF-MS for identification of SGs; however, MS-based quantification was not performed. With regard to chromatographic techniques, ultraperformance liquid chromatography (UPLC) is the newest state-of-the-art technology providing higher resolution, optimized signal-to-noise ratio, and shorter run times as compared to HPLC. To the best of our knowledge, no UPLC methods for SGs have been published so far. In this study, the highly efficient separation af single, intact SG species by RP-UPLC was combined with detection by a QTOF analyzer, which led to high mass accuracy. The UPLC-QTOF-MS method was developed, optimized, and validated to enable rapid, mass accurate, and highly sensitive SG detection as the sodiated adduct of the molecular ion. Furthermore, the applicability of the validated method was demonstrated for selected foods (oat bran and whole wheat) with various SG amounts and profiles and including consideration of the matrix effect.



MATERIALS AND METHODS

Reagents. Acetone, acetic acid, ammonium acetate, formic acid of LC-MS grade, and cholesterol β-D-glucoside (≥97% purity) were purchased from Sigma-Aldrich (Buchs, Switzerland). LC-MS grade acetonitrile, isopropanol, methanol, and water were from Biosolve (Dieuze, France). The commercial mixture of steryl glycosides (>98% purity) used as reference substances was from Matreya Inc. (Pleasant Gap, PA, USA) containing approximately 56% sitosteryl glucoside, 25% campesteryl glucoside, 18% stigmasteryl glucoside, and 1% Δ5avenasteryl glucoside. HPLC grade hexane and isopropanol used for sample extraction were from Fluka (Buchs, Switzerland). Instrumentation and Chromatographic Conditions. The UPLC system was a Waters Acquity UPLC System equipped with an Acquity UPLC BEH C18 column (50 mm × 2.1 mm, i.d., 1.7 μm). The MS system (Synapt G2) was composed of an electrospray ionization source and a Q-TOF analyzer (Waters Corp., Milford, MA, USA). Selection of the Mobile Phase and Additive. The mobile phases for method development in positive mode consisted of acetonitrile, methanol, or a mixture of 50% acetonitrile and 50% isopropanol combined with water to which either 0.1% (v/v) acetic acid or formic acid was added, leading to suitable acidic conditions for positive mode (see Table 2). Less acidic conditions obtained by a buffered solution with 0.1% (v/v) acetic acid and 1 mM ammonium acetate solved in water and acetonitrile on the other hand allowed measurements in both positive- and negative-ion modes. Another advantage of the buffered system is an increased solubility of ammonium acetate in acetonitrile.17 The resolution and sensitivity were assessed by extracted ion chromatograms (EIC) of sodiated ions of the two isomers stigmasteryl glucoside and Δ5-avenasteryl glucoside, with equal masses (m/z 597.4131 as [M + Na]+), that occur in the SG standard (Figure 2). For better comparability, the same ESI parameters and mobile phase gradient were used for all measurements in positive mode. For the optimization of the UPLC mobile phase composition, 5 μL of the SG standard with a concentration of 9 μM (calculated on the basis of the mass of sitosteryl glucoside) dissolved in the same solvent

Table 1. Mass-to-Charge Ratio m/z of Targeted SGs as [M + Na]+ in Positive and as [M − H + Hac]− in Negative Scan Mode compound

[M + Na]+

[M − H + Hac]−

cholesteryl glucoside campesteryl glucoside Δ5-avenasteryl glucoside Δ7-avenasteryl glucoside stigmasteryl glucoside sitosteryl glucoside

571.3975 585.4131 597.4131 597.4131 597.4131 599.4288

607.4210 621.4366 633.4366 633.4366 633.4366 635.4523

the mass-to-charge ratio (m/z) of the compounds and comparison of the relative retention time to cholesteryl glucoside. Each chromatographic peak was integrated using Mass-Lynx 4.1 software (Waters) without smoothing. Data evaluation was conducted with a mass range window of 0.02 Da (equivalent to approximately 33 ppm for sodiated SG adducts). ESI Conditions Used for SG Analysis in Foods. The final optimized conditions used for the validation and analysis of samples were all carried out in positive ionization mode. The voltages of capillary, sample cone, and extraction cone were set at 3000, 60, and 4.5 V, respectively. The desolvation gas flow rate was 850 L/h at 520 °C. The source temperature was 130 °C. Cone gas flow was 20 L/h. Full scan mass spectra were acquired from m/z 350 to 1200 at a scan rate of 0.5 s. Internal Standard Preparation and Method Validation. A stock solution of the internal standard cholesterol glucoside was prepared at a concentration of 4.8 μg/mL in methanol. The seven9411

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Figure 1. ESI (A) and APCI (B) mass spectra of sitosteryl glucoside ([M + Na]+ = m/z 599.4288, [aglycone + H − H2O]+ = m/z 397.3834) in SG standard solution measured in one UPLC-MS analysis run using ESCI multi-mode ionization and MeOH/water gradient + 0.1% (v/v) formic acid acquired in positive scan mode. of Stahnke et al. with small adaptions.18 In short, the matrix effect was defined as the alteration of the signal intensity of the target analyte (postcolumn infusion) caused by injected food compounds compared to an injected reference sample. Therefore, SGs extracted from oat and wheat as well as a reference sample (pure methanol) were measured in triplicates with the final UPLC-Q-TOF-MS method while a SG solution (2.4 μg/mL cholesteryl glucoside and 2.8 μg/mL SG standard solution with 8.2 ng/mL sodium acetate and 0.1% (v/v) formic acid) was continuously postcolumn infused. As the food samples naturally contained SG, they were additionally measured without postcolumn infusion, and the signal intensities were subtracted from the detected signal intensities of the infused SGs. The calculation of the matrix effect profile of particular sample matrices including smoothing of the data (f = 0.6) was performed according to the method of Stahnke et al.18 Second, the matrix profile of the wheat and oat samples was evaluated by postcolumn infusion using cholesterol glucoside as monitor substance. The infused solution was composed of 2.4 μg/mL cholesteryl glucoside in methanol, 8.2 ng/mL sodium acetate, and 0.1% (v/v) formic acid. The matrix effect profile of wheat was determined for 1 g per 500 mL and per 25 mL, whereas oat was measured at the concentrations of 1 g per 1000 mL and per 100 mL. The four most common SGs (sitosteryl, campesteryl, stigmasteryl, and Δ5-avenasteryl glucoside) and Δ7-avenasteryl glucoside were identified on the basis of the relative retention times to cholesteryl glucoside and their m/z (extracted ion chromatograms of [M + Na]+). The SG contents of oat bran and whole wheat were quantified on the basis of the internal standard including matrix effect compensation at the retention time of each analyte of interest. Because the peak width had to be included, the mean of the 11 data points around the retention time of each analyte was used for the calculation.

point calibration curve of cholesteryl glucoside in 100% methanol was determined at the following levels: 14.4, 43.2, 72.0, 108.0, 144.0, 180.0, and 216.0 ng/mL, each measured in triplicate with an injection volume of 10 μL. The calibration curve was weighted by 1/x, and the point of origin was excluded from the equation. To determine the interday and intraday variabilities, five repetitive analyses of quality control samples containing 54 and 90 ng/mL cholesteryl glucoside were performed on three different days. The limit of detection (LOD) and the limit of quantification (LOQ) were defined as 3 and 10 times the noise signal in the region of cholesteryl glucoside in the chromatogram, respectively. The determination of the LOD and LOQ was based on a calibration curve with lower cholesteryl glucoside levels (0.72, 1.44, 2.88, 5.76, and 14.40 ng/mL) all run in triplicate. For quantification of the SGs in food samples the lowest point of the calibration curve (14.4 ng/mL) was used as the LOQ. Sample Preparation for the Analysis of Steryl Glycosides Extracted from Foods. Whole wheat flour was bought from a local grocery store, and oat bran (Oatwell 28%) was obtained from DSM Nutritional Products Ltd. (Kaiseraugst, Switzerland). For sample preparation the method described by Nyström et al. was used with small adaptions.2 First, accelerated solvent extractor (ASE) was performed to extract the lipids. Afterward, 5 and 10 mL of the internal standard stock solution of 4.8 μg/mL were added to the wheat and oat extract, respectively. Next the extracts were evaporated to dryness and redissolved in a hexane/isopropanol mixture at a ratio of 95:5. To separate SGs from other sterols and neutral lipids, a fractionation by solid phase extraction (SPE) was performed with hexane and isopropanol. After evaporation under a gentle nitrogen stream at 50 °C of the SG fraction, the residue was dissolved in methanol. Determination of Matrix Effect Profile by Postcolumn Infusion. First, the impact of the matrix effect on different SG species was evaluated by postcolumn infusion according to the method 9412

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Data acquisition and processing was performed using Mass-Lynx and Quan-Lynx software with automatic Savitzky−Golay smoothing (smoothing parameters were iterations = 1 and width = 2). A mass range window of 0.02 Da was used with a scan time of 0.5 s. For the matrix effect evaluation and application on food samples, all data points were considered, whereas for graphical illustration only onefourth of the data were used. Statistical Analysis. All experiments were carried out in triplicates. Results were presented as mean values ± standard deviation. For data analysis SPSS 20.0 statistical software was used. One-way ANOVA, together with Tukey’s test, was performed using a confidence interval of 95%.

as other oligoglycosides as reported, for instance, in rice and adzuki beans.21−23 In this study, we were able to show that different SG species have the same ionization behavior, which allows evaluation of only one ion species while enabling calculation of SG content. The [aglycone + H − H2O]+ signal was between 0.5 and 6% compared to the [M + Na]+ signal for the different investigated SGs (sitosteryl, campesteryl, stigmasteryl, Δ5-avenasteryl, cholesteryl, and Δ7-avenasteryl glucoside). This led to the conclusion that different SG species demonstrate the same ionization behavior under the conditions applied. The most abundant ion species of SGs and their respective m/z, in positive and negative mode, are listed in Table 1. [M + Na]+ was the predominant ion species observed in positive mode. Earlier studies, by Schrick et al.11 using ESI and by Wewer et al.14 using nanospray, have reported the formation of NH4+ adducts. They both used direct infusion without chromatographic separation and enhanced the [M + NH4]+ formation by adding ammonium acetate to the sample. In the present study, [M − H + Hac]− was the most abundant ion species in negative mode. Comparison of APCI to ESI for the Analysis of Steryl Glycosides. The usage of APCI for the analysis of SGs was shown to be inferior when compared to ESI. With APCI (Figure 1B), 10 times lower intensity of [M + Na]+ and more fragment ions were obtained than with ESI (Figure 1A). APCI was used by Rudell et al.,19 Yamauchi et al.,12 and Rozenberg et al.,8 who all detected the aglycone ion as the predominant ion species. In our study, APCI was harsher and caused more fragmentation, whereas ESI was shown to be milder. Therefore, ESI was the method of choice for the analysis of intact SG and led to higher intensity of targeted species and, thus, provided higher sensitivity. Furthermore, a major benefit of the Q-TOF MS system used in this study was the high mass accuracy. In ESI and APCI modes, the mass accuracies of the sodiated SG were 1.7 and 0.3 ppm, respectively, and 1.0 and 2.3 ppm, respectively, for the aglycone ion (Figure 1). The mass accuracy of the method on average was 1.3 ppm (equivalent to approximately 0.76 mDa) for SG detection. Thus, our method was shown to be highly reliable for the identification of SGs based on their elemental composition. Effect of Mobile Phase and Additive of Sodiated Steryl Glycoside Ion Separation. To compare the effects of different mobile phases and additives on sensitivity and resolution, a solution of purified SG standard mixture was used. In addition to the four SGs declared by the distributor, another SG with m/z 597 was detected. This peak was tentatively identified as Δ7-avenasteryl glucoside, on the basis of the observations of Breinhölder et al.9 on relative retention time (RRT) order of the SGs used in this study, also using a C18 column. Additionally, the retention time of cholesteryl glucoside was identified on the basis of the standard compound. Thus, the order of elution using the UPLC BEH C18 column was Δ7-avenasteryl glucoside (RRT = 0.99), cholesteryl glucoside (RRT = 1.00), Δ5-avenasteryl glucoside (RRT = 1.00), campesteryl glucoside (RRT = 1.03), stigmasteryl glucoside (RRT = 1.03), and sitosteryl glucoside (RRT = 1.06). All SGs were separated, except for stigmasteryl and campesteryl glucosides, Δ5-avenasteryl, and cholesteryl glucosides, which coeluted, but which could still be distinguished by their m/z values.



RESULTS AND DISCUSSION To optimize the methodology for the analysis of SG using UPLC-MS, we evaluated a range of conditions and their effects on the separation and ionization efficacy of the SG species. First, the ESI and APCI parameters were modified to reach the highest signal intensity of intact SG, using sitosteryl glucoside, campesteryl glucoside, and the three isomers stigmasteryl, Δ5avenasteryl, and Δ7-avenasteryl glucoside as the target analytes. Second, the mobile phase and the additive were selected for UPLC separation, and the whole method was optimized, validated, and used to analyze SG contents and profiles in foods. Optimization of Ionization Parameters To Detect the Intact Steryl Glycosides. We observed that the ESI parameters, assessed by direct infusion of the SG standard solution, had a significant impact on ionization efficiency, as shown by the varying intensities of the targeted ion species. Before optimization, SG ion species with the highest intensity were the aglycone ions [aglycone + H − H2O]+, the sodiated adducts [M + Na]+, and the potassiated adducts [M + K]+, as well as [2 M + Na]+ (in decreasing order of intensity), when experiments were performed with lower sample cone voltage (40 V), lower desolvation temperature (200 °C), and lower source temperature (100 °C) than the final optimized ionization parameters. A high intensity of the molecular ion of SG was targeted; however, [M + H]+ was not formed in high abundance under any conditions tested. Thus, the ionization conditions were optimized to obtain the highest abundance of sodiated ion species [M + Na]+. Formation of [M + Na]+ in SG analysis was also reported by Yamauchi et al.12 when using positive mode APCI analyzing bell pepper samples and by Van Gerpen et al.16 measuring purified biodiesel residue with MALDI in positive mode. The advantage of adducts is their stability toward high ionization voltage, whereas nonadduct ion species are less stable and, thus, eliminated at high energy input. This makes quantitative analysis more reliable and increases reproducibility. In this study, high formation of sodiated SG adducts [M + Na]+ was accomplished by increasing the cone voltage to 60 V, and the respective aglycone [aglycone + H − H2O]+ was detected only at a small intensity (Figure 1A). This was a major improvement compared to previous reports of APCI and nanospray ionization methods for SG, which have mainly enabled the detection of the aglycone ions, but not the respective molecular ions.8,12,19 Although Strobl20 demonstrated an improved signal for SG molecular ions with APCI using a QqQ analyzer, a high percentage of aglycone still occurred. The advantage of measuring the intact SG is the possibility of identifying the type of sugar attached, given the fact that both hexoses and pentoses have been identified in SGs. 21 Furthermore, SGs exist not only as monoglycosides but also 9413

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Table 2. Mobile Phases and Additives Evaluated for UPLC-QTOF-ESI-MS Analysisa ion mode A B C D E F G H

positive positive positive positive positive positive positive negative

mobile phase A H2O H2O H2O H2O H2O H2O H2O H2O

mobile phase B d

IPA/ACN ACN MeOH ACN IPA/ACNd ACN MeOH ACN

additive added to phases A + Bb 0.1% 0.1% 0.1% 0.1% 0.1% 0.1% 0.1% 0.1%

FA FA FA AcOH + 1 mM NH4Ac AcOH AcOH AcOH AcOH + 1 mM NH4Ac

area of peak cc 973 1645 20126 566 1752 312 22682 581

± ± ± ± ± ± ± ±

43a 116a 2328b 16a 166a 79a 5525b 22a

peak c/noisec 106 286 1880 163 177 45 1856 302

± ± ± ± ± ± ± ±

35c 143c 696d 48c 50c 9c 965d 38c

resolutionc (b:c) 2.5 4.6 0.7 5.3 2.3 3.8 0.8 4.3

± ± ± ± ± ± ± ±

0.1e 0.3f 0.1g 0.1h 0.1e 0.1i 0.0g 0.4fi

Calculation of peak area and signal-to-noise ratio based on stigmasteryl glucoside (peak c) and resolution between Δ5-avenasteryl glucoside (peak b) and stigmasteryl glucoside (peak c). Different letters within peak area, signal-to-noise ratio, and resolution denote a sigificant difference. bNH4Ac, ammonium acetate; FA, formic acid; % (v/v). cMean values ± standard deviation (n = 3). d50% IPA/50% ACN. a

Figure 2. Extracted ion chromatograms (EIC) of m/z 597.4131 (A−G) as [M + Na]+ in ESI positive mode and m/z 633.4366 (H) as [M − H + Hac]− in negative mode using different mobile phase compositions. Details of mobile phase compositions A−H are described in Table 2. The SG standard solution used contained three isomeric SGs: (a) Δ7-avenasteryl glucoside; (b) Δ5-avenasteryl glucoside; (c) stigmasteryl glucoside. No smoothing applied. ACN, acetonitrile; FA, formic acid; IPA, isopropanol; MeOH, methanol.

[M − H + Hac]− was the most abundant ion species in negative mode in this study (Table 1). Analysis of SGs in negative mode did not lead to any improvement when compared to the methods that showed best results with regard to resolution and sensitivity. The sensitivity obtained using a methanol/water gradient was superior to that of the other systems tested. The area of the stigmasteryl glucoside peak in methanol/water systems was >10 times higher and the peak-to-noise ratio >6 times higher than with other eluents. These high values imply that detection and quantification of lower concentrations of SG are possible with methanol-based eluents. The improvement of LOD of the analytes with methanol has been previously reported for LCESI measurements of peptides.24 In that study, the signal-tonoise ratio with methanol was 2.2−6.9 times higher than with acetonitrile. We detected an even greater increase, specifically 6.6−41.2 times higher with methanol compared to acetonitrile. Due to this advantage, methanol was chosen as the organic mobile phase component. Water and methanol were also used as mobile phases in other studies for SG analysis using HPLC combined with UV, ELSD, or MS detection.8,12,16,25 The

The separation and sensitivity of SGs were highly affected by the composition of the mobile phase (Table 2; Figure 2). The shortest retention time for stigmasteryl glucoside (3.07 min) was obtained with and isopropanol/acetonitrile mixture as the organic mobile phase at a flow rate of 0.3 mL/min. This mixture has a high eluting strength, whereas SGs were more retained with methanol. Selection of the mobile phase, and in the case of acetonitrile in positive mode, choice of the additive, had a significant influence on the resolution. The highest resolutions of 4.3−5.3 between the two isomers stigmasteryl glucoside and Δ5-avenasteryl glucoside were achieved using an acetonitrile/water gradient. Δ5-Avenasteryl glucoside and stigmasteryl glucoside were baseline separated, and a third peak, tentatively identified as Δ7-avenasteryl glucoside, eluted prior to Δ5-avenasteryl glucoside. Moreover, with the buffered system of acetic acid and ammonium acetate, an improvement in resolution and peak shape was observed as compared to those from formic acid or acetic acid. These improvements of the buffered system have been previously reported for HPLCESI-MS measurements of peptides.17 9414

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Figure 3. UPLC separation of targeted compounds as [M + Na]+ obtained by measuring SG standard solution (sitosteryl glucoside, campesteryl glucoside, stigmasteryl glucoside, Δ5-avenasteryl glucoside, and Δ7-avenasteryl glucoside) and cholesteryl glucoside detected by Q-TOF-MS in positive ESI mode, obtained with optimized method (MeOH/water gradient + 0.1% (v/v) formic acid, BEH C18 column, total run time = 10 min). Savitzky−Golay smoothing was applied (iteration = 1 and width = 2).

height) was improved from 3.9 to 1.7 by method optimization. The major benefit of this UPLC method is that efficient separation was obtained with only 10 min runs, thus being far more rapid than conventional HPLC methods, which require 30 min per run.8,19 The calibration curve ranging from 14.4 to 216 ng/mL showed linear behavior with a correlation coefficient R2 >0.993. The LOD and LOQ were 1 and 3 ng/mL, respectively. These values improved on earlier results, by >500-fold, where the LOD achieved by GC-FID or by HPLC-ELSD was in the lower micrograms per milliliter range.25−28 However, it should be mentioned that the LOD was determined using methanol solutions without any sample matrix. The LOQ determined in this study was even lower than the LOQ of 27.4 ng/mL achieved by Q-TOF MS/MS.14

addition of formic acid and acetic acid did not lead to significantly different results, and of these two, formic acid was chosen for further experiments. UPLC-Q-TOF-MS Method Optimization and Validation. Peaks were assigned with respect to the m/z of the compounds and the relative retention times to cholesteryl glucoside. Extracted ion chromatograms for the five SGs occurring in the SG standard mixture obtained under final UPLC-Q-TOF-MS conditions are shown in Figure 3. With adjusted gradient and run time, the resolution between Δ5avenasteryl glucoside and stigmasteryl glucoside increased from 0.7 to 1.4. This provided suitable resolution for quantification using peak area, although the peaks were not baseline separated. Furthermore, the asymmetric factor As (10% height) was improved from 3.1 to 2.0, and the tailing factor Tf (5% 9415

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Table 3. Intra- and Interday Accuracy and Precision of Quantification Using Optimized UPLC-ESI-Q-TOF-MS Method Based on Pure Cholesteryl Glucoside (m/z 571.3975) Solution interday variation (3 days, n = 15)

intraday variation (n = 5)

a

QCa (ng/mL)

meanb (μg/mL)

RSD (%)

accuracy (%)

QCa (ng/mL)

meanb (μg/mL)

RSD (%)

accuracy (%)

54 90

56.94 88.66

2.74 2.75

105.4 98.5

54 90

56.68 91.06

4.51 3.33

105.0 101.2

Targeted concentration of quality control sample (QC). bMean observed concentration.

Figure 4. Postcolumn infusion matrix effect profile of sitosteryl glucoside, campesteryl glucoside, cholesteryl glucoside, and the isomers stigmasteryl glucoside, Δ5-avenasteryl glucoside, and Δ7-avenasteryl glucoside of SG extracts from whole wheat and oat bran (A); matrix effect profile of more (B) and less (C) concentrated wheat and oat SG extracts obtained by postcolumn infusion of cholesteryl glucoside. The bigger the gray area, the more pronounced the matrix effect at a given retention time (positive values, enhancement; negative values, suppression). SGs elute between 6.6 and 7.4 min (demonstrated with gray lines).

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Table 4. Total SG Content, Percentage SG Composition, and IS Recovery of More and Less Concentrated Wheat and Oat Bran SG Extracts with and without Inclusion of Matrix Effect Compensation wheat total SGs (μg/g DM) sitosteryl glucoside (%) campesteryl glucoside (%) stigmasteryl glucoside (%) Δ5-avenasteryl glucoside (%) Δ7-avenasteryl glucoside (%) recovery less concentratedb (%) recovery more concentratedc (%)

oat

− matrix effecta

+ matrix effecta

− matrix effecta

+ matrix effecta

164.9* ± 1.8 74.2* ± 0.1 16.7* ± 0.4 2.1* ± 0.2 5.5* ± 0.2 1.5 ± 0.2 93.3* ± 2.8 36.8* ± 1.6

184.4* ± 3.2 75.5* ± 0.1 15.3* ± 0.4 3.3* ± 0.3 4.6* ± 0.1 1.2 ± 0.1 110.7* ± 3.2 67.1* ± 2.9

310.9 ± 17.4 52.7* ± 0.9 10.3* ± 0.3 2.1* ± 0.3 31.0* ± 0.4 3.9* ± 0.3 96.7 ± 13.1 56.6* ± 1.8

330.7 ± 8.9 59.0* ± 0.8 7.5* ± 0.3 1.6* ± 0.2 28.8* ± 0.4 3.1* ± 0.2 102.8 ± 13.8 105.6* ± 5.8

a Mean values ± standard deviation (n = 3). *, statistically significant difference between with and without ME compensation. bPer g/500 mL (wheat) and g/1000 mL (oat). cPer g/25 mL (wheat) and g/100 mL (oat).

For wheat and oat bran, two different dilutions were selected for quantification of the SG content, and two different matrix effect profiles were produced, as the profile is highly dependent on the matrix concentration.31 Therefore, cholesteryl glucoside, used as monitor substance, was infused postcolumn to the more concentrated (Figure 4B) and less concentrated (Figure 4C) oat and wheat samples. As expected, the more diluted samples showed less ion suppression, with inhibition between 3 and 25% around SG elution from the column, whereas in the less diluted samples the signal suppression was between 30 and 68%. The two different food samples generated different matrix effect profiles as a result of their different matrix compositions. Furthermore, it was also observed that some background matrix compounds were still eluting during the re-equilibration period, as ion suppression continued to occur between 10 and 13 min (Figure 4). The SG composition and the IS recovery in wheat and oat samples were calculated with and without matrix effect correction (Table 4). By including compensation for the matrix effect, the IS recovery rates of the concentrated extracts experiencing higher matrix effect were increased from 36.8 and 56.6 to 67.1 and 105.6% in wheat and oat bran, respectively. Thus, ion suppression could be compensated, and inclusion of the matrix effect was highly necessary for concentrated samples. Furthermore, time dependence of the matrix effect was observed. The ionization of the early eluting Δ7-avenasteryl glucoside was inhibited by 39%, whereas the later eluting stigmasteryl glucoside signal was reduced 68% by the matrix in the concentrated wheat sample. Due to the variation of suppression of the different SGs, the SG composition changed significantly by inclusion of matrix effect correction. Furthermore, applying compensation for the matrix effect increased the total SGs quantified in wheat by about 12% from 164.9 to 184.4 μg/g DM. With consideration of the matrix effect, the total SG content in whole wheat was 184.4 μg/g DM and was composed of 75.5, 15.3, 4.6, 3.3, and 1.2% of sitosteryl, campesteryl, Δ5avenasteryl, stigmasteryl, and Δ7-avenasteryl glucosides, respectively. Compared to the results of our earlier study, the proportions of different sterols were similar, but in the current study more than double the amount of total SGs was detected.2 Sugawara et al. detected 54 μg/g total SGs in wheat by HPLCELSD, which is only a third of what we measured.26 These differences may, however, be due to analytical variability because Ruibal-Mendieta et al. measured steryl glycosides (SG + ASG) in winter wheat at a similar concentration to this study by HPLC-MS.32

The accuracy and precision of the method were determined by an intra- and interday variation test of two QC samples containing 54 and 90 ng/mL of cholesteryl glucoside. The accuracies of the detected concentrations were always >94%, and the highest standard deviations were 4.51% for interday and 2.75% for intraday measurements (Table 3). Therefore, good reproducibility and high accuracy of the investigated method were demonstrated. Quantification of Steryl Glycosides Extracted from Food Samples. In a final step, the optimized and validated method was applied to analyze SG in whole wheat and oat bran samples. Although glycosylated cholesterol can occur in plant samples,10,23,29 cholesteryl glucoside was selected as internal standard (IS) because it is essentially the only single SG commercially available as pure standard. To demonstrate the applicability of the IS for food samples with different SG profiles, containing high or low SG concentrations and containing cholesteryl glucoside or not, food samples of whole wheat and oat bran were selected. Wheat was found to contain low SG concentrations, and cholesteryl glucoside was detected only in traces. Oat bran contained a high concentration of SGs and cholesteryl glucoside in significant amounts, and therefore sample spiking was performed. When the SG content in extracts of wheat and oat bran was analyzed, the recovery of the IS was only between 36 and 97% due to ion suppression produced by coeluting matrix compounds. This matrix effect is a well-known limitation of MS methods. Usually this effect can be reduced or eliminated by improved extraction and sample cleanup or by chromatographic separation of the investigated analytes from the food matrix compounds.30 However, the matrix effect is timedependent and therefore varies for different SGs. Due to a lack of pure standards, the reduction of the ion suppression cannot be evaluated for individual SG. Hence, another strategy, including matrix effect quantification and application to data as a correction, was chosen. Therefore, the matrix effects of our samples were assessed by permanent postcolumn infusion of cholesteryl glucoside and of the SG standard based on the method by Stahnke et al.18 In this way, the matrix effect profile was detected throughout the whole run time and the reequilibration period. The various SG species were similarly suppressed or enhanced, allowing the usage of a single monitoring substance representing other SGs (Figure 4A). Even though the postcolumn infused SG standard consists of SGs at different concentrations, they showed similar signal inhibitions. Thus, the matrix effect was independent of the abundance of the individual SGs in the sample (Figure 4A). 9417

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(5) Lin, X. B.; Ma, L.; Racette, S. B.; Spearie, C. L. A.; Ostlund, R. E. Phytosterol glycosides reduce cholesterol absorption in humans. Am. J. Physiol.: Gastrointest. Liver Physiol. 2009, 296, G931−G935. (6) Nyström, L. Analysis methods of phytosterols. In Analysis of Antioxidant-Rich Phytochemicals; Wiley-Blackwell: Hoboken, NJ, USA, 2012; pp 313−351. (7) Kamal-Eldin, A.; Mäaẗ tä, K.; Toivo, J.; Lampi, A. M.; Piironen, V. Acid-catalyzed isomerization of fucosterol and Δ(5)-avenasterol. Lipids 1998, 33, 1073−1077. (8) Rozenberg, R.; Ruibal-Mendieta, N. L.; Petitjean, G.; Cani, P.; Delacroix, D. L.; Delzenne, N. M.; Meurens, M.; Quetin-Leclercq, J.; Habib-Jiwan, J. L. Phytosterol analysis and characterization in spelt (Triticum aestivum ssp spelta L.) and wheat (T. aestivum L.) lipids by LC/APCI-MS. J. Cereal Sci. 2003, 38, 189−197. (9) Breinhölder, P.; Mosca, L.; Lindner, W. Concept of sequential analysis of free and conjugated phytosterols in different plant matrices. J. Chromatogr., B 2002, 777, 67−82. (10) Kesselmeier, J.; Eichenberger, W.; Urban, B. High performance liquid chromatography of molecular species from free sterols and sterylglycosides isolated from oat leaves and seeds. Plant Cell Physiol. 1985, 26, 463−471. (11) Schrick, K.; Shiva, S.; Arpin, J. C.; Delimont, N.; Isaac, G.; Tamura, P.; Welti, R. Steryl glucoside and acyl steryl glucoside analysis of arabidopsis seeds by electrospray ionization tandem mass spectrometry. Lipids 2012, 47, 185−193. (12) Yamauchi, R.; Aizawa, K.; Inakuma, T.; Kato, K. Analysis of molecular species of glycolipids in fruit pastes of red bell pepper (Capsicum annuum L.) by high-performance liquid chromatographymass spectrometry. J. Agric. Food Chem. 2001, 49, 622−627. (13) Hernandez, F.; Pozo, O. J.; Sancho, J. V.; Lopez, F. J.; Marin, J. M.; Ibanez, M. Strategies for quantification and confirmation of multiclass polar pesticides and transformation products in water by LC-MS2 using triple quadrupole and hybrid quadrupole time-of-flight analyzers. TrAC, Trends Anal. Chem. 2005, 24, 596−612. (14) Wewer, V.; Dombrink, I.; vom Dorp, K.; Dormann, P. Quantification of sterol lipids in plants by quadrupole time-of-flight mass spectrometry. J. Lipid Res. 2011, 52, 1039−1054. (15) Chavez-Santoscoy, R. A.; Tovar, A. R.; Serna-Saldivar, S. O.; Torres, N.; Gutierrez-Uribe, J. A. Conjugated and free sterols from black bean (Phaseolus vulgaris L.) seed coats as cholesterol micelle disruptors and their effect on lipid metabolism and cholesterol transport in rat primary hepatocytes. Genes Nutr. 2014, 9, DOI: 10.1007/s12263-013-0367-1. (16) Van Gerpen, J.; He, B. B.; Duff, K. Measurement and Control Strategies for Sterol Glucosides to Improve Biodiesel Quality − Year 2; University of Idaho, National Institute for Advanced Transportation Technology: Moscow, ID, USA, 2011 (17) Leitner, A.; Emmert, J.; Boerner, K.; Lindner, W. Influence of solvent additive composition on chromatographic separation and sodium adduct formation of peptides in HPLC-ESI MS. Chromatographia 2007, 65, 649−653. (18) Stahnke, H.; Reemtsma, T.; Alder, L. Compensation of matrix effects by postcolumn infusion of a monitor substance in multiresidue analysis with LC-MS/MS. Anal. Chem. 2009, 81, 2185−2192. (19) Rudell, D. R.; Buchanan, D. A.; Leisso, R. S.; Whitaker, B. D.; Mattheis, J. P.; Zhu, Y. M.; Varanasi, V. Ripening, storage temperature, ethylene action, and oxidative stress alter apple peel phytosterol metabolism. Phytochemistry 2011, 72, 1328−1340. (20) Strobl, M. Δ-7-Sterole und Δ-7-Sterolglykoside aus Samen von Cucurbita pepo L.: Isolierung und Strukturaufklärung. Dissertation, Faculty of Chemistry and Pharmacy, LMU, München, Germany, 2004. (21) Kovganko, N. V.; Kashkan, Z. N. Sterol glycosides and acylglycosides. Chem. Nat. Compd. 1999, 35, 479−497. (22) Fujino, Y.; Ohnishi, M. Isolation and structure of diglycosylsterols and triglycosylsterols in rice bran. Biochim. Biophys. Acta 1979, 574, 94−102. (23) Kojima, M.; Ohnishi, M.; Ito, S.; Fujino, Y. Characterization of acylmonoglycosylsterol, monoglycosylsterol, diglycosylsterol, triglyco-

The total SG content of oat bran under consideration of the matrix effect was 330.7 μg/g DM, demonstrating that the oat bran analyzed is a better source for SGs than whole wheat. Oat bran SGs consisted of 59.0, 7.5, 28.8, 1.6, and 3.1% of sitosteryl, campesteryl, Δ5-avenasteryl, stigmasteryl, and Δ7-avenasteryl glucosides, respectively. Kesselmeier et al. measured SGs in oat seed samples by HPLC-UV.10 They found that sitosteryl glycoside and Δ5-avenasteryl glycoside are the two most abundant glycosylated sterols (in SG + ASG). These two accounted for 82% of the total SG content, which is in great accordance with our result (sitosteryl and Δ5-avenasteryl glucoside contributing 81% of the total SG content in oat). A mild analysis method, like the one developed in this study, is important for the analysis of oat SGs because Δ5-avenasteryl glycoside is a labile SG that is easily degraded or isomerized by the acidic hydrolysis included in several GC procedures. To conclude, we developed a rapid, highly sensitive, and accurate UPLC-ESI-MS method for the detection of molecular ions of SGs as sodiated adducts. The possibility to separate SGs on the basis of different polarities, in combination with high sensitivity and mass accurate detection, makes this method a powerful tool for full screening of SG profiles in foods and other biological samples, even those with low SG content. Furthermore, we demonstrated that evaluation of the matrix effect is extremely important for accurate quantification of SGs in complex food samples.



AUTHOR INFORMATION

Corresponding Author

*(L.N.) Phone: +41 44 632 91 65. E-mail: laura.nystroem@ hest.ethz.ch. Author Contributions ∥

S.R.O. and L.H.M contributed equally to this work.

Funding

This study was funded by the Swiss National Science Foundation (SNSF) and ETH Zurich. Notes

The authors declare no competing financial interest.



ABBREVIATIONS USED ASG, acylated steryl glycosides; APCI, atmospheric pressure chemical ionization; DM, dry matter; ESCI, electrospray chemical ionization; ESI, electrospray ionization; FS, free sterols; Q-TOF, quadrupole time-of flight; SE, steryl esters; SG, steryl glycosides; UPLC, ultraperformance liquid chromatography



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