Modified method for determination of sulfur metabolites in plant tissues

Analytical Biochemistry 442 (2013) 24–33

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Modified method for determination of sulfur metabolites in plant tissues by stable isotope dilution-based liquid chromatography–electrospray ionization–tandem mass spectrometry Ya-Lan Chang a, Chin-Lin Hsieh a, Yao-Moan Huang b, Wen-Liang Chiou c, Yueh-Hsiung Kuo d, Mei-Hwei Tseng a,⇑ a

Department of Applied Physics and Chemistry, University of Taipei, Taipei 10048, Taiwan Division of Silviculture, Taiwan Forestry Research Institute, Taipei 10066, Taiwan c Division of Botanical Garden, Taiwan Forestry Research Institute, Taipei 10066, Taiwan d Department of Chinese Pharmaceutical Science and Chinese Medicine Resources, China Medical University, Taichung 404, Taiwan b

a r t i c l e

i n f o

Article history: Received 25 November 2012 Received in revised form 18 July 2013 Accepted 19 July 2013 Available online 31 July 2013 Keywords: Sulfur metabolites LC–MS/MS 34 S metabolic labeling

a b s t r a c t A wide variety of sulfur metabolites play important roles in plant functions. We have developed a precise and sensitive method for the simultaneous measurement of several sulfur metabolites based on liquid chromatography coupled with tandem mass spectrometry (LC–MS/MS) and 34S metabolic labeling of sulfur-containing metabolites in Arabidopsis thaliana seedlings. However, some sulfur metabolites were unstable during the extraction procedure. Our proposed method does not allow for the detection of the important sulfur metabolite homocysteine because of its instability during sample extraction. Stable isotope-labeled sulfur metabolites of A. thaliana shoot were extracted and utilized as internal standards for quantification of sulfur metabolites with LC–MS/MS using S-adenosylmethionine (SAM), S-adenosylhomocysteine (SAH), methionine (Met), glutathione (GSH), and glutathione disulfide (GSSG) as example metabolites. These metabolites were detected using electrospray ionization in positive mode. Standard curves were linear (r2 > 0.99) over a range of concentrations (SAM 0.01–2.0 lM, SAH 0.002–0.10 lM, Met 0.05–4.0 lM, GSH 0.17–20.0 lM, GSSG 0.07–20.0 lM), with limits of detection for SAM, SAH, Met, GSH, and GSSG of 0.83, 0.67, 10, 0.56, and 1.1 nM, respectively; and the within-run and between-run coefficients of variation based on quality control samples were less than 8%. Ó 2013 Elsevier Inc. All rights reserved.

Sulfur is an essential element for all organisms; plants are able to absorb inorganic sulfate and incorporate it into organic compounds, which are present in a wide variety of metabolites that possess distinct biological functions [1,2]. There has been substantial progress in the elucidation of the pathways involved in sulfur uptake and assimilation and the roles of sulfur metabolites in plant functions, including adaptation to abiotic and biotic stress [3–11]. Sensitive and specific methods are required to accurately quantify sulfur metabolites in plant tissues. There have been several reported methods for analyzing sulfur metabolites. These methods include enzymatic and fluorescence assays [12–14]; chromatographic methods that include HPLC with electrochemical detection [15–17]; spectrophotometric [18,19], fluorescence [20,21], and capillary electrophoresis methods [22]; gas chromatography–mass spectrometry [23,24]; and liquid chromatography–mass spectrometry with sample derivatization [25–27]. However, these methods ⇑ Corresponding author. Fax: +886 2 23814067. E-mail address: [email protected] (M.-H. Tseng). 0003-2697/$ - see front matter Ó 2013 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.ab.2013.07.026

often suffer from poor sensitivity or selectivity and may require time-consuming sample pretreatment such as derivatization with fluorescent reagents. Recent developments in LC–MS/MS1 provide more sensitive and selective methods for samples without derivatization [28–32]. Because of its high selectivity and sensitivity, LC–MS/MS is widely used to identify and quantify plant metabolites in plant tissues [33–35], drugs in biological samples [36,37], pollutants in the environment [38], and toxins in food [39–41]. Ion suppression/enhancement effects caused by coeluting compounds from samples are a major qualitative and quantitative concern in LC–MS/MS detections [42–46]. It has been shown that the unique strength of mass spectrometry to detect and accurately quantify a coeluting stable 1 Abbreviations used: CV, coefficient of variation; FW, fresh weight; GSH, glutathione; GSSG, glutathione disulfide; IS, internal standard; LC–ESI–MS/MS, liquid chromatography, electrospray ionization, and tandem mass spectrometry; LOD, limit of detection; LOQ, limit of quantification; PCA, perchloric acid; QC, quality control; SAH, S-adenosylhomocysteine; SAM, S-adenosylmethionine; SIL, stable isotope labeled.

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Modified method for determination of sulfur metabolites / Y.-L. Chang et al. / Anal. Biochem. 442 (2013) 24–33

isotope-labeled internal standard (SIL IS) provides an easy solution to the problem of interference by coeluting compounds [42–46]. Ideally, an SIL IS used to correct for the effects of possible ion suppression/enhancement is identical with respect to the physicochemical properties of the analyte of interest in sample pretreatment, chromatographic separation, and mass spectrometry detection. However, a broad, stable isotope dilution method to measure a wide variety of sulfur metabolites does not exist because of the limited variety of commercially available stable isotope-labeled sulfur metabolites. The method for in vivo stable isotope labeling in cell culture, which enables the biosynthesis of SIL ISs for LC–MS/MS, has been reported [47–50]. We have developed a biosynthetic method to generate isotopically labeled sulfur metabolites using hydroponic culture for the in vivo 34S metabolic labeling of sulfur-containing metabolites in Arabidopsis thaliana [51]. However, SAM and SAH were unstable during the extraction procedure using the previous method [51], resulting in incorrect metabolite determination of plant tissues. In the present study, an ice-cold perchloric acid (PCA) solution was used during the extraction procedure without heating to maintain metabolite stability. The proposed modified method allows the simultaneous determination of stable and unstable sulfur metabolites and remarkably improves the accuracy of determination of sulfur metabolites in plant tissues. 34S metabolites extracted from 34S-labeled A. thaliana were investigated for use as ISs for LC–ESI–MS/MS analysis of sulfur metabolites in A. thaliana samples and spores of rare fern species using SAM, SAH, methionine (Met), GSH, and GSSG as example metabolites. In addition, an LC–ESI–MS/MS method for determination of SAM, SAH, Met, GSH, and GSSG using these 34S metabolites as ISs was developed and validated. Materials and methods Materials SAM, SAH, Met, GSH, GSSG, and PCA were purchased from Sigma (St. Louis, MO, USA). Na234SO4 was purchased from ICON Isotope (Summit, NJ, USA; the minimum isotope enrichment is 92%). All chemicals used for the Murashige and Skoog nutrient medium were obtained from Sigma, Acros Organics, and Merck (Darmstadt, Germany). Formic acid, acetonitrile, and methanol were purchased from J.K. Baker. Water was deionized and filtered through a Millipore Milli-Q water purification system. Spore storage and germination tests Fresh Osmunda cinnamomea L. spores were obtained from 12 fertile fronds growing in a marsh at Tsao-Pi (24°450 N, 121°330 E), Ilan County, in northeastern Taiwan. Fertile fronds were collected, transported to the laboratory, and air-dried on sheets of smooth paper for 3 days until the spores were released. Spores were isolated from sporangium sacs and then transferred to microtubes (Labcon screw-cap microcentrifuge tubes, 2.0 ml) for dry storage. The tubes were stored in the dark at room temperature (18– 25 °C), 4 °C, or 80 °C for 1, 2, 3, 4, 8, or 12 weeks. The cooling rate for storage of spore cells in a 80 °C Ultra Low freezer (Nuaire, NU6511, USA) was monitored using thermocouples (RKC Instrument, CB100, Japan). The cooling rate was 1.28 °C/min. Spores stored at room temperature, 4 °C, or 80 °C were sown onto sheets of membrane filter (pore 0.45 lm, 47 mm in diameter; Gelman Laboratory) after 1, 2, 3, 4, 8, or 12 weeks of dry storage. Each sheet was laid on a 4-cm-thick layer of moist sphagnum moss in a plastic box (W D H: 114 86 102 mm3; Phytatray II; Sigma). All cultures were incubated under white fluorescent

illumination at approximately 25–35 lmol m2 s1 for 12 h day1 at 20 ± 1 °C. There were four replicates of each treatment. The percentage of spores that germinated was recorded each week for 5 weeks. Germination was considered to have occurred if the spore wall was broken and the first rhizoid had emerged. Germination rate (%) was calculated based on a count of 50 randomly chosen spores from each replicate. Preparation of plant samples A hydroponic setup was used for the in vivo 34S metabolic labeling of sulfur-containing metabolites in A. thaliana L. Columbia-0; the 34S-labeled metabolites biosynthesized in A. thaliana were extracted by a modified version of an extraction procedure described in [51]. To stop enzyme activity, the microtubes containing tissue powder were cooled with liquid nitrogen to keep the samples frozen at all times. Then, 0.6% (v/v) PCA and then methanol were added to the tubes. The microtubes were thoroughly shaken for about 2 min at room temperature using a TRIO HM-2 tube mixer, a product of As One, Inc. The homogenates were centrifuged at 18,000g for 30 min at 4 °C. The supernatants were collected and the pellet was resuspended with 100 ll of 0.1% PCA. The resuspended pellet was centrifuged again under the same conditions. The second and third supernatants were combined with the first and stored at 80 °C until analysis. The 34S-labeled A. thaliana tissues were prepared and extracted using the same procedure. Standard solutions Stock solutions were prepared individually by dissolving SAM, SAH, Met, GSH, or GSSG in 0.1% (v/v) PCA at 1 mg/ml. Serial dilutions containing SAM, SAH, Met, GSH, and GSSG were prepared for calibration and quality control (QC) samples by adding 0.1% (v/v) PCA to the required amounts of stock solutions in volumetric flasks, which were then vortexed-mixed, divided into aliquots, and stored at 80 °C. The calibration standard levels were 0.01, 0.05, 0.10, 0.50, 1.0, and 2.0 lM for SAM; 0.002, 0.004, 0.01, 0.02, 0.04, and 0.10 lM for SAH; 0.05, 0.20, 0.4, 1.0, 2.0, and 4.0 lM for Met; 0.17, 0.25, 1.0, 2.0, 10.0, and 20.0 lM for GSH; and 0.07, 0.1, 1.0, 2.0, 4.0, and 20.0 lM for GSSG. QC samples were prepared at concentrations of 0.03 and 1.52 lM for SAM, 0.004 and 0.086 lM for SAH, 0.09 and 3.37 lM for Met, 0.5 and 17.4 lM for GSH, 0.20 and 17.4 lM for GSSG. Calibration curves corrected using thaliana as ISs

34

S metabolites from

34

S-labeled A.

For isotope dilution mass spectrometry analysis, 34S-labeled shoot tissue extracts were added to the calibration standards, QC samples, and plant samples in a fixed ratio. The amount of 34S-labeled plant extract used to spike the samples was around 180 lg of FW of the 34S-labeled tissue (for one injection). The ratio of the unlabeled and 34S-labeled metabolites in the samples and the calibration standards was subsequently determined by measuring peak areas corresponding to the ion fragment masses M + 0 and M + 2N (where N is the number of sulfur atoms of the metabolite or its ion fragments). Calibration lines were obtained when the area ratios between the 32S and the 34S metabolites were plotted against the known concentrations of 32S metabolites in the calibration standard. Instrument conditions Chromatographic separations of sulfur metabolites were performed on a Thermo Accela LC system using a Thermo Hypercarb

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Table 1 Mass spectrometry parameters with transition pairs in MRM mode and normalized collision energy (%). Compound 32

[ S]Met [34S]Met [32S]GSSG [34S]GSSG [32S]GSH [34S]GSH [32S]SAH [34S]SAH [32S]SAMa [34S]SAMa a

[MH]+

Transition pairs

%

150 152 613 617 308 310 385 387 399 401

m/z m/z m/z m/z m/z m/z m/z m/z m/z m/z

35 35 35 35 35 35 35 35 35 35

150 ? 104 152 ? 106 613 ? 484 617 ? 488 308 ? 179 310 ? 181 385 ? 250 387 ? 252 399 ? 250 401 ? 250

SAM is measured as [M]+.

column (5 lm, 2.1 150 mm) with Hypercarb Drop-in Guards pk2 (5 lm, 10 2.1 mm). Separations were performed under gradient conditions at a flow rate of 0.25 ml min1. The gradient elution was composed of 0.1% formic acid in water (eluent A) and 0.1% formic acid in acetonitrile (eluent B). The gradient started with 95% A, followed by an increase to 75% B after 15 min. The column was then flushed with an increasing gradient from 75% B to 95% B for 1 min, followed by 95% B for 4 min, and equilibrated with 95% A for another 3 min. ESI–MS/MS analysis was performed on an LTQ Velos mass spectrometer (Thermo Fisher Scientific). Metabolites were detected in positive ionization mode using multiple reaction monitoring scanning mode. The spray voltage was set to 3.5 kV, the ion-transfer capillary temperature was set to 280 °C, the sheath gas

pressure was set to 50 (arbitrary units), and the auxiliary gas pressure was set to 15 (arbitrary units). Collision energy set at 35% was used for each metabolite (Table 1). Validation Linearity and low limit of quantification and detection A line (y = ax + b) was fitted through the standard curve and ranged by weighted linear regression (weight = 1/x) of the peak area ratio of SAM, SAH, Met, GSH, or GSSG to SIL IS (y) from 34S-labeled tissue extracts versus the actual concentration of the analyte (x). LOQ is the concentration of the lowest standard on the calibration curve for which the analyte response is reproducible with a precision less than 20% and accuracy better than ±20%. The precision was determined by calculating the coefficient of variation (CV%), and the accuracy was assessed by determining the mean relative percentage deviation (DEV%) from the nominal concentration. The LOD was estimated at a signal-to-noise ratio of >3 by injecting a series of samples of known concentrations. Accuracy and precision Accuracy and precision were evaluated by measuring each analyte in five replicates of two QC samples of differing concentrations on 3 different days. Intrarun precision and accuracy were determined by repeated analyses of a group of standards from one batch (n = 5). Interrun precision and accuracy were determined by repeated analyses (n = 3) on different days. The concentration of each

Fig.1. ESI–MS/MS spectra obtained in positive-ion mode for (A) SAM and [34S]SAM and (B) SAH and [34S]SAH. Data for SAM and SAH were acquired from the injection of 2.0 lM each analyte in a 0.1% PCA solution. Data for [34S]SAM and [34S]SAH were acquired from the injection of tissue extract of 34S-labeled A. thaliana.


sample was determined using the calibration curve prepared and analyzed from the same batch as the sample. Recovery The recovery after the extraction procedure and LC–MS/MS analysis was determined at two different concentration levels with five replicates at each level. At the beginning of the extraction procedure, plant samples (or H2O for the control) were added to a known amount of analytes in PCA solution for recovery analysis. Recovery was calculated by dividing the quantity of analyte in the spiked sample by the sum of the analyte in the sample plus the amount of added analyte. The concentrations used for the evaluation of recovery were set at 0.087 and 0.44 lmol/L for SAM, 0.009 and 0.087 lmol/L for SAH, 0.087 and 0.44 lmol/L for Met, 6.96 lmol/L for GSH, and 0.70 and 1.30 lmol/L for GSSG. Statistics One-way analysis of variance was performed using Duncan’s test with the statistical software SPSS 19. The results were expressed as the mean ± SD, and P < 0.05 was considered significant. Pearson’s correlation analysis (Excel) was used to measure the relationship between two variables. Results and discussion Mass spectra and ion chromatogram The ion trap MS/MS spectra obtained in positive-ion mode for SAM and SAH are shown in Fig. 1; the results of MS/MS spectra for Met, GSH, and GSSG were the same as in our previous study [51]. As previously reported [30], the ion [M]+ of SAM at m/z 399.3 decomposes into two major products, the ions at m/z 298.2

27

and 250.1, and less abundant products at m/z 264.2 and 136.1 (Fig. 1A). The presence of [34S] SAM in extracts of 34S-labeled A. thaliana was identified by ion fragments m/z 401.3, 300.2, 266.2, 250.1, and 136.1 (Fig. 1A). The presence of SAH in standard solution was identified by [M+H]+ ions m/z 385.3 and the fragment ions m/z 250.1 and 136.0 (Fig. 1B). The presence of ion m/z 250.1 was most probably due to the loss of neutral adenine (135 Da), which is subsequently protonated to generate the ion at m/z 136.0 [29,30]. The presence of [34S] SAH in extracts from 34S-labeled A. thaliana was identified by ion fragments m/z 387.3, 252.1, and 136.0 (Fig. 1B). Ion chromatograms of 32S standard analytes/34S plant extract are presented in Fig. 2. Both 32S and 34S metabolites of SAM, GSH, Met, GSSG, and SAH exhibited the same retention times of 2.37, 3.03, 3.06, 4.70, and 5.56 min, respectively (Fig. 2). The peak height of SAM (m/z 399 ? 250), 2.0 lM, was 2.89 104; the peak height of GSH (m/z 308 ? 179), 80 lM, was 1.32 107; the peak height of Met (m/z 150 ? 104), 10 lM, was 2.51 105; the peak height of GSSG (m/z 613 ? 484), 20 lM, was 1.33 106; the peak height of SAH (m/z 385 ? 250), 0.2 lM, was 1.57 104 (supplementary data). Sample preparation To prevent oxidation or decomposition of sulfur metabolites under basic or neutral conditions [28,52,53] and avoid using a strong acidic solution (such as 0.1 N hydrochloric acid [54] or 10% trichloroacetic acid [52]), the use of 0.1% PCA (pH 2) appeared to offer the best compromise between metabolite stability and column specification based on previously published procedures [49,51]. However, SAM was significantly unstable and SAH was slightly unstable during the extraction procedure of our preliminary test when boiled in 0.1% PCA. The DEV% of the QC samples of SAM and SAH were near 30 and 10%, respectively. Therefore an ice-cold PCA solution at a higher concentration and methanol

Fig. 2. Ion chromatography was used to analyze (A) Met (m/z 150 ? 104), 10 lM; (C) GSH (m/z 308 ? 179), 80 lM; (E) SAH (m/z 385 ? 250), 0.2 lM; (G) SAM (m/z 399 ? 250), 2.0 lM; and (I) GSSG (m/z 613 ? 484), 20 lM in standard solution. Analyses of (B) [34S]Met (m/z 152 ? 106), (D) [34S]GSH (m/z 310 ? 181), (F) [34S]SAH (m/z 387 ? 252), (H) [34S]SAM (m/z 401 ? 250), and (J) [34S]GSSG (m/z 617 ? 488) were performed for extractions obtained from 34S-labeled A. thaliana tissue.

28


were used to inactivate enzyme activity during the extraction procedure without heating. After extraction, samples were carefully kept in an ice bath until LC–MS/MS analysis or stored at 80 °C. Similar results were obtained for the quantification of SAM and SAH by using 0.2, 0.4, or 0.6% (v/v) PCA for extraction (data not shown, supplementary data). Method validation Selectivity In the case of molecules containing one or two sulfur atoms, the natural occurrence of stable isotopes such as 13C (1.09%), 15N (0.40%), 18O (0.20%), 33S (0.76%), or 34S (4.22%) in unlabeled metabolites could produce a significant signal at [M+2] or [M+4] that could affect the differentiation and quantification of labeled metabolites. For selectivity, sample analysis was conducted from plant extracts of A. thaliana grown in medium containing Na232SO4 or Na234SO4. First, plant extracts from 32S-labeled A. thaliana were analyzed to evaluate the presence of interference during detection of 34S metabolites. Signals were detected at [M+2] for SAM (5.5%), SAH (5.5%), Met (3.5%), and GSH (5.6%) and at [M+4] for GSSG (0.5%); these signals correspond to the contributions of stable isotopes that naturally occur in the metabolites. An identical evaluation was performed for the analysis of 34S-labeled tissue extract. Signals were observed from the chromatograms (supplementary data) for [32S]SAM (3.8%), [32S]SAH (3.0%), [32S]Met (3.7%), [32S]GSH (3.1%), and [32S]GSSG (0.1%); these signals may be due to impurities assimilated from the Na234SO4 salt and culture medium. Taken together, our results demonstrate that 32S and 34S

Table 2 Peak areas of

a b

32

S and

34

metabolites can be selectively monitored with a low level of interference that does not affect the validity of quantitative analyses. Calibration curves corrected using 34S metabolites from 34S-labeled A. thaliana as ISs To investigate the ability of 34S metabolites from 34S-labeled A. thaliana to be used as ISs to correct for the effect of ion suppression/enhancement, a zero sample and six non-zero standard samples were prepared. A fixed amount of extracts of 34S-labeled A. thaliana was added to each of these standard samples and analyzed by LC–ESI–MS/MS. Table 2 shows the peak areas, the calculated%ion suppression or enhancement of 34S metabolites caused by their own 32S metabolites, and peak area ratios (32S/34S). Calibration lines were obtained when the peak area ratios between the 32S and the 34S metabolites were plotted against the known concentrations of 32S metabolites in the calibration standard (y = 2.2501x + 0.0396 (r2 = 0.9982) for SAM, y = 41.8074x + 0.0255 (r2 = 0.9907) for SAH, y = 1.1533x + 0.0363 (r2 = 0.9988) for Met, y = 0.0827x + 0.0299 (r2 = 0.9916) for GSH, and y = 0.2667x + 0.0001 (r2 = 0.9993) for GSSG). These analytes are essential metabolites in plants. Matrix effects for SAM, SAH, Met, GSH, and GSSG were not measured, as it was impossible to find a matrix without naturally incurred SAM, SAH, Met, GSH, and GSSG. As shown in Table 3, the deviation from the nominal concentrations for all samples fell within acceptable limits (between 5.78 and 5.11% for SAM, 15.0 and 7.16% for SAH, 8.03 and 4.94% for Met, 10.30 and 12.0% for GSH, 3.37 and 10.7% for GSSG). The coefficient of variation ranged from 4.59 to 17.4% for SAM, from 4.22 to 9.84 for SAH, from 3.21 to

S metabolites as ISs and calculated %-ion suppression or enhancement of ISs caused by

Metabolite

Concentration (lM)

32

SAM SAM SAM SAM SAM SAM SAM SAH SAH SAH SAH SAH SAH SAH Met Met Met Met Met Met Met GSH GSH GSH GSH GSH GSH GSH GSSG GSSG GSSG GSSG GSSG GSSG GSSG

0 0.01 0.05 0.10 0.50 1.00 2.00 0 0.002 0.004 0.01 0.02 0.04 0.10 0 0.05 0.20 0.40 1.00 2.00 4.00 0 0.17 0.25 1.00 2.00 10.0 20.0 0 0.07 0.10 1.00 2.00 4.00 20.0

4,330 6,393 13,182 24,524 112,696 227,588 454,541 270 1,388 2,499 6,098 11,554 23,519 57,028 5,836 14,152 39,055 77,783 201,335 431,588 942,693 106,232 140,791 160,025 335,345 575,985 2,368,426 4,832,032 2,133 33,139 41,966 439,673 913,061 1,869,286 11,498,271

S metabolite peak area

a

34

S metabolite peak area

111,322 97,803 93,280 93,442 97,372 99,836 113,707 11,309 12,290 11,630 12,436 12,832 12,888 14,408 157,267 154,466 154,326 157,911 167,830 181,491 203,577 3,310,466 3,093,488 3,189,726 3,068,324 2,952,608 3,190,352 3,305,318 1,774,782 1,755,326 1,583,534 1,634,336 1,667,155 1,748,815 2,154,745

a

32

S metabolites. %-Ion suppression or enhancement of IS caused by 32S metaboliteb

Ratio (32S/34S)

12 16 16 13 10 2

0.065 0.141 0.262 1.157 2.280 3.997

9 3 10 14 14 27

0.113 0.215 0.490 0.900 1.825 3.958

2 2 0.4 7 15 30

0.092 0.253 0.493 1.200 2.378 4.631

7 4 7 11 4 0.2

0.046 0.050 0.109 0.195 0.742 1.462

1 11 8 6 2 21

0.019 0.027 0.278 0.548 1.069 5.336

Peak areas are average values obtained from five injections of SAM, SAH, or Met standard samples or from two injections of GSH and GSSG standard samples. %-Ion suppression or enhancement was calculated for each 34S metabolite using the following equation: 100 (IS area/IS area in zero sample) 100.

29

Modified method for determination of sulfur metabolites / Y.-L. Chang et al. / Anal. Biochem. 442 (2013) 24–33 Table 3 Precision and accuracy of calibration samples.a Nominal concentration (lM)

Mean

SD

(A) SAM concentration from calibration curve 0.01 0.01 0.002 0.05 0.05 0.003 0.10 0.10 0.005 0.50 0.50 0.034 1.00 1.02 0.048 2.00 1.92 0.112

Table 4 Intra- and interrun precision and accuracy of QC samples.a PRE (CV%)b 17.4 5.32 4.59 6.82 4.67 5.85

ACC (DEV%)c

Concentration (lM)

5.11 5.78 0.24 0.03 1.63 3.96

(B) SAH concentration from calibration curve 0.002 0.002 0.0002 0.004 0.004 0.0002 0.01 0.01 0.001 0.02 0.02 0.001 0.04 0.04 0.003 0.10 0.09 0.007

9.84 4.22 5.10 5.36 6.56 7.05

15.0 3.33 1.33 7.16 6.83 7.07

(C) Met concentration from calibration curve 0.05 0.05 0.009 0.20 0.18 0.009 0.40 0.38 0.012 1.00 1.02 0.056 2.00 2.10 0.100 4.00 4.20 0.248

17.1 5.03 3.21 5.55 4.78 5.90

2.53 8.03 4.16 1.47 4.86 4.94

(D) GSH concentration from calibration curve 0.17 0.19 0.026 0.25 0.25 0.013 1.00 1.01 0.046 2.00 2.02 0.069 10.0 9.70 0.591 20.0 17.9 1.088

14.1 5.37 4.55 3.42 6.09 6.06

12.0 0.15 1.10 0.87 2.96 10.3

(E) GSSG concentration from calibration curve 0.07 0.07 0.011 0.10 0.10 0.003 1.00 1.00 0.022 2.00 2.04 0.046 4.00 4.05 0.122 20.0 19.3 0.729

14.7 2.62 2.23 2.22 3.01 3.77

10.7 1.12 0.00 2.23 1.35 3.37

Precision (CV%)

b

Interrun (n = 15) c

Accuracy (DEV%)

Precision (CV%)

Accuracy (DEV%)

SAM 0.03 1.52

4.68 2.06

5.48 2.92

6.78 0.97

2.67 2.07

SAH 0.004 0.086

7.43 4.24

10.7 1.07

1.11 6.92

7.73 4.02

Met 0.09 3.37

2.48 5.90

5.52 0.54

5.07 1.20

2.78 5.05

GSH 0.50 17.4

4.91 1.34

10.4 7.37

7.24 3.40

4.79 5.36

GSSG 0.20 17.4

1.68 1.41

3.5 8.23

3.74 3.21

0.44 5.82

a

n = 5 for each of three runs. [Standard deviation/mean concentration measured] 100. c [(Mean concentration measured nominal concentration)/nominal concentration] 100. b

Table 5 Recovery of metabolites spiked into A. thaliana tissue extracts. Metabolite

Abbreviations used: PRE, precision; ACC, accuracy. a n = 6. b [Standard deviation/mean concentration measured] 100. c [(Mean concentration measured nominal concentration)/nominal concentration] 100.

Intrarun (n = 5)

SAM SAH Met GSH GSSG a b

Spiked (lmol/L)

Recovery Averagea

CV%

0.087 0.009 0.087 6.96 0.70

99.2 ± 3.3 98.9 ± 3.6 102 ± 3 98.8 ± 1.0 109 ± 2

3.33 3.60 2.64 1.03 1.88

Spiked (lmol/L)

Recovery Averagea

CV%

0.44 0.087 0.44 —b 1.30

101 ± 2 101 ± 2 98.8 ± 2.2 — 104 ± 6

2.21 2.18 2.26 — 5.49

Data are presented as the mean ± SD (n = 5). Did not measure.

Table 6 Recovery of sulfur metabolites (SAM, SAH, Met, GSSG, and GSH) from O. cinnamomea spore extract.

17.1% for Met, from 3.42 to 14.1% for GSH, and from 2.22 to 14.7% for GSSG. Typical equations of calibration curves were as follows: y = 0.361x + 0.032 (r2 = 0.9977) for SAM, y = 7.71x + 0.038 (r2 = 0.9959) for SAH, y = 0.367x + 0.026 (r2 = 0.9948) for Met, y = 0.027x + 0.033 (r2 = 0.9996) for GSH, and y = 0.079x + 0.00008 (r2 = 0.9991) for GSSG. As shown in Tables 2 and 3, these results clearly show the ability of ISs in 34S-labeled A. thaliana extracts to compensate for ion suppression/enhancement effects.

Accuracy and precision The accuracy and precision of data from QC samples is shown in Table 4. The intra- and interrun precision and accuracy were