MS Assay for Protein Amino Acids and Metabolically Related

Oct 5, 2007 - LC−MS/MS Assay for Protein Amino Acids and Metabolically Related Compounds for Large-Scale Screening of Metabolic Phenotypes .... Pest...
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Anal. Chem. 2007, 79, 8067-8075

LC-MS/MS Assay for Protein Amino Acids and Metabolically Related Compounds for Large-Scale Screening of Metabolic Phenotypes Liping Gu,†,‡ A. Daniel Jones,*,†,§ and Robert L. Last†,‡

Departments of Biochemistry and Molecular Biology, Chemistry, and Plant Biology, Michigan State University, East Lansing, Michigan 48824

A modified LC-MS/MS method for large-scale screening of metabolic phenotypes was developed and validated. Twenty amino acids and 5 metabolically related compounds are measured within 4 min using multiple reaction monitoring (MRM) transitions selective for each compound. Separation with a short C18 column and rapid gradient using the ion-pairing reagent perfluoroheptanoic acid allows chromatographic resolution of the isomers Ile and Leu and improved chromatographic peak shapes for Lys, Arg, and His. MRM transitions were established with capability to distinguish isomers Leu from Ile and Thr from homoserine even when chromatographic resolution is incomplete. The reproducibility of the assay was tested by adding eight stable isotope-labeled amino acid standards (AA*) to extracts of Arabidopsis thaliana seeds. In intra- and interday assay comparisons, mean coefficients of variation of the peak area ratios of AA/AA* were less than 5% for all but Gly/Gly-D2-15N1. Recoveries of these eight amino acids ranged from 62 to 94% and suppression of signal by the matrix were 31-65%. Dilution of seed extracts reduced ion suppression for earlyeluting amino acids but had minimal effects for those eluting later. The intra- and interday accuracies for these eight amino acids were 77-131 and 88-133% of nominal concentrations, respectively. Amino acids are required by all living organisms because they serve as the building blocks of proteins and precursor for the synthesis of nucleic acids.1,2 Amino acids are also biosynthetic precursors of many other essential molecules, such as coenzymes (e.g., S-adenosylmethionine and NAD+), antioxidants (glutathione and vitamin E), and neurotransmitters (GABA and serotonin). Free amino acid profiles are important indicators for some metabolic disorders or physiological processes. For instance, human serotonin deficiency syndrome is one of the most common and widespread disorders and is characterized by insufficient dietary Trp uptake, inefficient transport across the blood-brain barrier,3 or defects in conversion of Trp to serotonin.4 Phenylke* To whom correspondence should be addressed. Tel.: 517-432-7126. Fax: 517-353-9334. E-mail: [email protected]. † Department of Biochemistry and Molecular Biology. ‡ Department of Plant Biology. § Department of Chemistry. (1) Shibata, H.; Ochiai, H.; Sawa, Y.; Miyoshi, S. Plant Physiol. 1986, 80, 126129. (2) Williamson, C. L.; Slocum, R. D. Plant Physiol. 1994, 105, 377-384. (3) Fernstrom, J. D. J. Nutr. 2005, 135, 1539S-1546S. 10.1021/ac070938b CCC: $37.00 Published on Web 10/05/2007

© 2007 American Chemical Society

tonuria is a hereditary disease causing mental retardation and poor muscle coordination because of defects in Phe metabolism.5 Amino acids can stimulate protein synthesis in liver.6 Abnormal plasma free amino acid profiles for cancer patients have been documented and can serve as biological markers for cancer diagnosis.7,8 Amino acids also play a central role in plant biochemistry as precursors of macromolecules and other metabolites. As expected, mutations that decrease the activity of amino acid biosynthetic enzymes reduce the vigor of plants, with the most severe defects causing auxotrophy, or requirement for supplementation with the affected amino acid for normal growth.9,10 In addition to their roles in protein synthesis, amino acids also serve as precursors to specialized metabolites of importance in plant growth and stress adaptation. For example, the essential hormone auxin (indole-3acetic acid) is derived from tryptophan.11 Many important compounds are derived from Phe and Tyr, including structural lignin compounds and structurally diverse aromatic specialized (secondary) metabolites such as hydroxycinnamic acids and flavonoids, some of which have demonstrated roles in protecting plants from abiotic stresses.12,13 Taken together, free amino acids are essential compounds and key regulators in addition to their roles in animal nutrition. Despite extensive research, prediction of the functions of plant genes remains elusive, in part because of the diversity of plant metabolites and the complex dynamic behavior of metabolic networks. So far, the identities of most of the plant enzymes involved in the synthesis and degradation of amino acids have (4) Zhang, X.; Beaulieu, J. M.; Gainetdinov, R. R.; Caron, M. G. Cell. Mol. Life Sci. 2006, 63, 6-11. (5) Kozak, L.; Hrabincova, E.; Kintr, J.; Horky, O.; Zapletalova, P.; Blahakova, I.; Mejstrik, P.; Prochazkova, D. Mol. Genet. Metab. 2006, 89, 300-309. (6) Jaleel, A.; Nair, K. S. Am. J. Physiol. Endocrinol. Metab. 2004, 286, E950E957. (7) Cascino, A.; Muscaritoli, M.; Cangiano, C.; Conversano, L.; Laviano, A.; Ariemma, S.; Meguid, M. M.; Rossi Fanelli, F. Anticancer Res. 1995, 15, 507-510. (8) Lai, H. S.; Lee, J. C.; Lee, P. H.; Wang, S. T.; Chen, W. J. Semin. Cancer Biol. 2005, 15, 267-276. (9) Radwanski, E. R.; Last, R. L. Plant Cell 1995, 7, 921-934. (10) Coruzzi, G. M.; Last, R. L. Amino acids. In Biochemistry and Molecular Biology of Plants; Buchanan, B. B., Gruissem, W., Jones, R, L., Eds.; American Society of Plant Physiologists: Rockville, MD, 2000. (11) Normanly, J.; Bartel, B. Curr. Opin. Plant Biol. 1999, 2, 207-213. (12) Landry, L. G.; Chapple, C. C.; Last, R. L. Plant Physiol. 1995, 109, 11591166. (13) Li, J.; Ou-Lee, T. M.; Raba, R.; Amundson, R. G.; Last, R. L. Plant Cell 1993, 5, 171-179.

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been demonstrated or inferred based upon amino acid sequence similarity to enzymes in microorganisms. This approach limits our ability to discover novel plant-specific mechanisms for regulation of amino acid levels. Recent technological advances have enabled high-throughput metabolic screening of large numbers of genetic variants to find genetic modifications that have significant influence on biochemical composition.14,15 Results from such screens accelerate the discovery of gene functions important to plant productivity and health. Three aspects of metabolite analysis are vital to successful large-scale metabolite profiling: (1) analyses must incur minimal analysis time and cost per sample, (2) procedures should generate precise and accurate measurements, and (3) protocols should resolve and quantify many metabolites over a wide range of concentrations. To date, the most commonly used protocols for the separation and analysis of amino acids are liquid chromatography coupled with pre-16,17 or postcolumn18 derivatization. These methods are relatively time-consuming, and the requirement for derivatization may cause problems due to inconsistent production of expected derivatives, compound stability, and solubility. Recently, liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) has been shown to be a very specific and sensitive technique for amino acid analysis without derivatization.19,20 However, while a high-throughput HPLC-MS/MS method was developed by Jander et al.,14 the method was not capable of resolving isoleucine (Ile) and leucine (Leu). Furthermore, it was difficult to precisely quantify Lys in plant seed extracts as its retention time was only 0.14 min after the more abundant Gln, which has the same nominal mass (m/z 147 for [M + H]+). Methods developed by Petritis et al.21 and Qu et al.22 are capable of resolving these amino acids but require 20-40 min analysis time per sample, reducing their utility for analysis of large numbers of samples required for mutant screening or other “omic”-scale projects. The current study extends and refines earlier approaches14 and explores the importance of matrix effects on quantification of amino acids and related metabolites extracted from plant seeds. This method employs reversed-phase chromatography with the ion pairing agent perfluoroheptanoic acid in the mobile phase with electrospray ionization/tandem mass spectrometry to allow detection and quantitation of 20 proteinogenic amino acids as well as γ-aminobutyric acid (GABA), hydroxyproline (HPro), and the biosynthetic pathway intermediates anthranilate, homoserine (HSer), and S-methylmethionine (SMM). Because this LC-MS/ MS determination method uses multiple reaction monitoring (14) Jander, G.; Norris, S. R.; Joshi, V.; Fraga, M.; Rugg, A.; Yu, S.; Li, L.; Last, R. L. Plant J. 2004, 39, 465-475. (15) Van Eenennaam, A. L.; Lincoln, K.; Durrett, T. P.; Valentin, H. E.; Shewmaker, C. K.; Thorne, G. M.; Jiang, J.; Baszis, S. R.; Levering, C. K.; Aasen, E. D.; Hao, M.; Stein, J. C.; Norris, S. R.; Last, R. L. Plant Cell 2003, 15, 3007-3019. (16) Deyl, Z.; Hyanek, J.; Horakova, M. J. Chromatogr. 1986, 379, 177-250. (17) Sarwar, G.; Botting, H. G. J. Chromatogr. 1993, 615, 1-22. (18) Moore, S.; Spackman, D. H.; Stein, W. H. Fed. Proc. 1958, 17, 1107-1115. (19) Chaimbault, P.; Petritis, K.; Elfakir, C.; Dreux, M. J. Chromatogr. A 1999, 855, 191-202. (20) Petritis, K.; Valleix, A.; Elfakir, C.; Dreux, M. J. Chromatogr., A 2001, 913, 331-340. (21) Petritis, K. N. C., P.; Elfakir, C.; Dreux, M. J. Chromatogr., A 1999, 833, 147-155. (22) Qu, J.; Wang, Y.; Luo, G.; Wu, Z.; Yang, C. Anal. Chem. 2002, 74, 20342040.

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(MRM) to monitor transitions of the protonated molecules to their specific product ions, the 25 compounds can be quantified simultaneously using a 96-well microtiter plate format from samples prepared using aqueous extraction23 followed by filtration to eliminate cell debris. This quantitative method was validated using eight stable isotope-labeled amino acids as representatives. EXPERIMENTAL SECTION Liquid Chromatography and Mass Spectrometry. A Waters (Milford, MA) Quattro micro mass spectrometer coupled to a Shimadzu (Columbia, MD) LC-20AD HPLC system and SIL-5000 autosampler was used. A Waters Symmetry C18 column (2.1 × 100 mm, 3.5-µm particle size) was used with column oven temperature at 30 °C. The injection volume was 10 µL, and the HPLC flow rate was 0.3 mL/min using the gradient shown in Table S1 (Supporting Information). Mass spectra were acquired using electrospray ionization in positive ion mode and MRM. The capillary voltage, extractor voltage, and rf lens setting were set at 3.17 kV, 4 V, and 0.3, respectively. The flow rates of cone gas and desolvation gas were 20 and 400 L/h, respectively. The source temperature and desolvation temperature were 110 and 350 °C, respectively. Collision-induced dissociation employed argon as collision gas at a manifold pressure of 2 × 10-3 mbar, and collision energies and source cone potentials were optimized for each transition using Waters QuanOptimize software. This method was composed of two ESI+ functions (0-1.8 and 1.8-6.0 min) covering full run time to allow for adequate dwell time for each analyte. Data were acquired with MassLynx 4.0 and processed for calibration and for quantification of the analytes with QuanLynx software. Standard Solutions. Ala-D4, Asp-D3, Glu-D3, Gly-D2-15N1, Lys15N , Phe-D , Ser-D , and Val-D were purchased from Cambridge 1 8 3 8 Isotope Laboratories (Andover, MA); the 20 amino acids, anthranilate, GABA, HPro, HSer, and SMM were from Sigma (St. Louis, MO). Each chemical was dissolved in water to make individual stock solution at 0.5-100 mM concentrations, depending upon their water solubility, and stored at - 20 °C. Master mixtures consisted of 200 µM 8AA* (200 µM each Ala-D4, Asp-D3, Glu-D3, Gly-D2-15N1, Lys-15N1, Phe-D8, Ser-D3, and Val-D8), 200 µM 8AA (200 µM each Ala, Asp, Glu, Gly, Lys, Phe, Ser, and Val), and 100 µM 25 AA+ (100 µM each of the 20 amino acids, anthranilate, GABA, HPro, HSer, and SMM) were prepared from the stocks with water. As it was not possible to find plant extracts lacking these 25 compounds for making matrix-matched calibration curves, we used a series of 6 working standards with concentrations range from 0 to 50 µM 25 AA+ plus 10 µM Phe-D8 and 10 µM Val-D8 as internal standards in water. Data from analyses of these standards were used to create the calibration curves for each compound by plotting AA concentrations as x-axis and peak area ratio of AA/ Phe-D8 as y-axis using linear regression. The same internal standards were also included in the seed extracts for quantification of endogenous metabolites. Chromatographic resolution of Glu from Gln and Asp from Asn was not always achieved, and the contributions of the naturally occurring heavy isotopomer of Asn to the Asp channel and Gln (23) Streatfield, S. J.; Weber, A.; Kinsman, E. A.; Hausler, R. E.; Li, J.; PostBeittenmiller, D.; Kaiser, W. M.; Pyke, K. A.; Flugge, U. I.; Chory, J. Plant Cell 1999, 11, 1609-1622.

to the Glu channel were evaluated. For the Asp and Glu concentration correction, a series of working standards with concentrations ranging from 0 to 40 µM Asp/Glu or Asn/Gln in water were prepared. The calibration curves were created for each compound by plotting AA concentrations as x-axis and peak areas at m/z 134 > 74 (Asp/Asn) or 148 > 84 (Glu/Gln) transitions as y-axis using linear regression. Analysis of Plant Extracts. Approximately 3 mg of Arabidopsis seed samples were homogenized in 240 µL of H2O and 30 µL of 100 µM Phe-D8 (internal standard for quantification) by vigorous shaking with two 3-mm stainless steel balls (CCR Products LLC, West Hartford, CT) for 5 min on a S2200 paint shaker (Hero Products Group, Delta, BC, Canada). After 10-min incubation at 90 °C, extracts were centrifuged and the supernatants were filtered through 0.45-µm Low-Binding Hydrophilic PTFE (Millipore, Billerica, MA). Ten microliters of 100 µM ValD8 (the internal standard used as injection loading control) was added to 90 µL of the cleared filtrate to make extracts with final concentrations of 10 µM Phe-D8 and 10 µM Val-D8 in each sample. The endogenous concentrations of the 25 compounds were calculated according to the slope and intercept from the standard curves and the peak area ratio of AA/Phe-D8 in the extract. Method Validation Studies. A series of working standards with concentrations ranging from 0 to 50 µM 8AA with 10 µM 8AA* as internal standards were prepared by making serial dilutions of stocks containing 200 µM 8AA and 200 µM 8AA*. Calibration curves for each amino acid were generated by plotting AA concentrations as x-axis versus responses (AA peak area or peak area ratio of AA/AA*) as y-axis using linear regression. Preextracts. To measure the efficiency of recovery of the target compounds from plant seed extracts, 8AA* were added to extraction buffer to make final preextracts with 10 µM 8AA* in each sample. Postextracts. To measure matrix effects for the eight labeled amino acids and provide a comparison with the preextracts, we evaluated the effects of adding 8AA* directly to filtered seed extract to make final postextracts with 10 µM 8AA* in the sample. To evaluate analytical accuracy and quantify ion suppression, the same postextracts (1×) were diluted with equal volume (0.5×) or 3 volumes (0.25×) of water. Then, three quality control lines with four different spiked concentrations were prepared by the addition of 8AA along with 8AA* to achieve final extracts with the additions of 0, 1, 3, or 5 µM 8AA and 10 µM 8AA* as internal standards in the samples. Matrix-matched calibration curves were prepared by plotting the added AA concentrations as x-axis and responses (AA peak area or peak area ratio of AA/AA*) as y-axis using linear regression. RESULTS AND DISCUSSION Method Development for Quantifying 25 Metabolites in Arabidopsis Seeds. The quantitative analysis of amino acids was achieved using Phe-D8 and Val-D8 as internal standards for quantitation and loading controls, respectively. The method was also designed to measure the Asp-derived amino acid pathway intermediates HSer and SMM, and Trp biosynthesis precursor anthranilate, as well as HPro and GABA. In total, 25 unlabeled compounds (AA+), plus two stable isotopically labeled internal standard amino acids (Phe-D8 and Val-D8) were included in our assay. First, ion pair reversed-phase liquid chromatography with

Table 1. MRM Transitions, Optimized Source Cone Voltages, Collision Cell Voltages, and Analyte Retention Times

compd

precursor ion > cone collision product ion voltage voltage retention function (m/z) (V) (V) time (min) no.

Ala Arg Asn Asp Cys Gln Glu Gly His Ile/Leu

90 > 44 175 > 70 133 > 87 134 > 74 122 > 76 147 > 130 148 > 84 76 > 30 156 > 110 132 > 86

18 26 26 18 18 18 18 18 18 18

15 20 20 15 15 15 15 40 15 15

Ile Leu Lys Met Phe Pro Ser Thr Trp Tyr Val anthranilate GABA HPro HSer SMM Phe-D8 Val-D8

132 > 69 132 > 30 147 > 84 150 > 104 166 > 120 116 > 70 106 > 60 120 > 57 205 > 188 182 > 136 118 > 72 138 > 120 104 > 87 132 > 86 120 > 44 164 > 118 174 > 128 126 > 80

18 18 18 18 18 26 18 26 18 18 18 18 18 18 26 18 18 18

15 15 15 15 15 15 20 25 15 15 15 15 15 15 20 15 15 15

1.56 3.96 1.18 1.16 1.39 1.26 1.32 1.30 3.52 2.76 and 2.95 2.76 2.95 3.76 2.17 3.17 1.54 1.20 1.37 3.65 2.11 2.08 3.11 2.43 1.16 1.35 2.45 3.15 2.08

1 2 1 1 1 1 1 1 2 2 2 2 2 2 2 1 1 1 2 2 2 2 2 1 1 2 2 2

gradient elution (Table S1) was developed. Hydrophobic amino acids (Trp, Phe) and the basic amino acids Lys, Arg, and His elute relatively late, consistent with reversed-phase separation using the anionic ion pairing agent perfluoroheptanoate. Second, MRM detection conditions for 27 AA+ standards were optimized for determination of the most abundant product ion at its optimal collision energy and ion source cone voltage for each analyte. Third, to improve the overall performance, the data acquisition was split into two functions with the first running from 0 to 1.8 min and the second from 1.8 to 6.0 min, as no target compounds eluted between 1.6 and 2.1 min. Twelve MRM transitions were included in function 1 and 16 in function 2. The HPLC retention times and optimized MRM parameters for these 27 compounds are summarized in Table 1. Next, to confirm that the selected peak signal was from the compound of interest in a biological matrix, 25 µM of each individual standard amino acid was spiked into an Arabidopsis seed extract and compared with the unadulterated seed extract by monitoring change in the peak area using the MRM parameters described in Table 1. A significant increase in the area of the predicted peak was observed following addition of each compound (data not shown), suggesting that this LCMS/MS system is capable of detecting all 25 compounds in a complex biological matrix. Experiments with mixed authentic standards were performed to evaluate lowest limits of detection for this analytical method. For the lowest concentration (1 pmol injected), signal-to-noise (rms) ratios ranged from 5 for Gly to 730 for Pro. Therefore, the analytical method is capable of detecting these compounds Analytical Chemistry, Vol. 79, No. 21, November 1, 2007

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Figure 1. Collision-induced dissociation MS/MS spectra of product ions derived from the protonated molecule (m/z 120) for threonine and homoserine using collision cell potentials of 25 and 20 V, respectively. Isomers threonine and homoserine are not separated by HPLC, and their product ion spectra share the common ions at m/z 74 and 56. However, they yield isomer-selective product ions at m/z 57 and 44, respectively.

Figure 2. Coeluting isomers Thr and HSer quantified by their selective transitions m/z 120 > 57 (Thr) and 120 > 44 (HSer). Extracted ion chromatograms of an Arabidopsis thaliana seed extract alone (A and B), spiked with 20 µM Thr (C and D) or HSer (E and F) monitored using transitions of m/z 120 > 57 (A, C, and E) and 120 > 44 (B, D, and F), respectively. Values of absolute signal intensity corresponding to 100% are presented in the top left corner of each graph. Increases in intensities were observed for m/z 120 > 57 Thr (C) and 120 > 44 HSer (F) when spiking standard Thr and HSer to the Arabidopsis seed extracts, respectively.

in the range of hundreds of femtomoles injected for nearly all analytes. To test whether other reversed-phase LC columns are compatible with this MS/MS method, we tested the performance of three additional columns: a Thermo Hypersil GOLD (2.1 × 50 mm, 1.9-µm particles), a Waters Atlantis dC18 column (2.1 × 100 mm, 3.5-µm particles), and a Restek Allure C18 (1 × 150 mm, 5-µm particles). We were able to detect all 25 compounds with all columns tested, with the Hypersil GOLD column giving the narrowest peaks. Thus, the selective MRM transitions allow this approach to be used with a variety of columns. The creation and validation of the assays was complicated by the presence of two pairs of isomers (Thr/HSer and Ile/Leu). As shown in Figure S1 (Supporting Information), Thr and HSer 8070 Analytical Chemistry, Vol. 79, No. 21, November 1, 2007

coelute during chromatography. Therefore, a search for product ions specific for Thr and HSer was made by generating MS/MS product ion spectra for each [M + H]+ ion at different collision energies. As shown in Figure 1, there are two product ions common to both isomers at m/z 56 and 74, as well as isomerselective product ions at m/z 57 (Thr) and 44 (HSer). Thus, MRM transition channels m/z 120 > 57 and 120 > 44 were used for Thr and HSer detection, respectively. As shown in Figure 2, the instrument response for the m/z 120 > 57 transition increased ∼7-fold in 20 µM Thr-spiked extract (C), but addition of 20 µM HSer gave no change in analytical response (E), relative to the nonspiked extract (A). The converse is also true: the peak area for the m/z 120 > 44 transition increased more than 30-fold in HSer-spiked extract (F), but gave minimal change in the Thr-

Figure 3. Leu and Ile quantified individually despite overlapping elution on HPLC. Extracted ion chromatograms of an Arabidopsis seed extract alone (A-C), spiked with 20 µM Ile (D-F), or Leu (G-I) monitoring m/z 132 > 86 transition (A, D, and G), 132 > 69 transition (B, E, and H), or 132 > 30 transition (C, F, and I), respectively. Values of absolute signal intensity corresponding to 100% are presented in the top left corner of each graph. When the transition m/z 132 > 86 was monitored, both Ile (D) and Leu (G) spiked samples showed increased peak intensity compared with nonspiked seed extract (A). In contrast, significant increases in signal intensity were observed only for transition m/z 132 > 69 for Ile-spiked seed samples (compare Ile-spiked seed extract E with B and H) and only for transition m/z 132 > 30 (compare Leuspiked seed extract I with C and F) when seed extracts were spiked with Leu standard.

spiked extract (D), indicating that the m/z 120 > 57 and 120 > 44 transitions are selective for Thr and HSer, respectively, and can be used for their quantification. Add-in experiments were conducted to find MRM transitions that would permit quantification of Ile and Leu under conditions giving overlapping elution. Although these compounds were chromatographically resolved when standard solutions were analyzed (see Figure S1), adding 20 µM Ile or Leu standard to the extract caused column overloading, and the minor isomer could not be resolved from the major isomer (Figure 3D and G), whereas both were partially resolved in the nonspiked extract (Figure 3A). To solve this problem, we tested the use of m/z 132 > 69 and 132 > 30 transitions for Ile and Leu confirmation, respectively. As seen in Figure 3, adding 20 µM Ile standard to the Arabidopsis seed extracts caused significant increases in peak intensity for m/z 132 > 86 (Figure 3D) and 132 > 69 (E). In contrast, addition of 20 µM Leu resulted in increased response for both m/z 132 > 86 (G) and 132 > 30 (I), respectively. Thus, the m/z 132 > 69 and 132 > 30 transitions can be chosen as backup measurements while using the more sensitive m/z 132 > 86 transition, either when there is good chromatographic separation of these compounds or it is not necessary to distinguish between Ile and Leu.

One challenge presented in these analyses is the similar chromatographic retention of Asp with Asn, and the analogous situation with Glu and Gln. Because of overlapping elution of the Glu/Gln pair (at ∼1.3 min) and Asp/Asn pair (at ∼1.17 min; see Figure S1), the ability to accurately quantify each amino acid depends upon quantitatively accounting for cross talk between the respective MRM transitions. Naturally occurring heavy stable isotopes such as 13C cause the amide side-chain amino acids Asn and Gln to generate signals at the same m/z values as unlabeled Asp and Glu, respectively. To determine the extent to which heavy isotopomers of Asn and Gln contributed to signals used to measure Asp and Glu, the purity of Asn and Gln was first confirmed by conducting GC/MS24,25 analyses of the amino acid standards as their trimethylsilyl derivatives. Next, the LC-MS/MS peak areas were generated for Asn standard solutions ranging from 0 to 40 µM Asn using the m/z 134 > 74 transition recorded by LC-MS/MS and converted to concentrations using the slope of the Asp standard curve (generated by plotting the responses for 0-40 µM Asp concentration at m/z 134 > 74 transition). The contribution of the heavy (24) Chaves Das Neves, H. J.; Vasconcelos, A. M. J. Chromatogr. 1987, 392, 249-258. (25) Schwender, J.; Ohlrogge, J. B. Plant Physiol. 2002, 130, 347-361.

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Table 2. Intra- and Interday HPLC Retention Times of Eight Amino Acidsa HPLC retention times (min.) intraday assay day 1 (n ) 76)

intraday assay day 2 (n ) 76)

intraday assay day 3 (n ) 76)

interday assay days 1, 2, 3 (n ) 228)

comd

precursor ion >product ion (m/z)

mean ( SD

CV (%)

mean ( SD

CV (%)

mean ( SD

CV (%)

mean ( SD

CV (%)

Ala-D4 Asp-D3 Glu-D3 Gly-D2-15N1 Lys-15N1 Phe-D8 Ser-D3 Val-D8

94 > 48 137 > 75 151 > 87 79 > 33 148 > 85 174 > 128 109 > 63 126 > 80

1.55 ( 0.00 1.14 ( 0.01 1.25 ( 0.02 1.32 ( 0.01 3.77 ( 0.01 3.18 ( 0.01 1.21 ( 0.00 2.07 ( 0.01

0.2 0.6 1.3 0.7 0.4 0.3 0.0 0.4

1.55 ( 0.00 1.16 ( 0.00 1.27 ( 0.01 1.32 ( 0.01 3.77 ( 0.01 3.18 ( 0.01 1.22 ( 0.01 2.07 ( 0.01

0.3 0.3 1.1 0.8 0.3 0.2 0.8 0.4

1.55 ( 0.00 1.16 ( 0.00 1.28 ( 0.01 1.32 ( 0.01 3.77 ( 0.01 3.18 ( 0.01 1.22 ( 0.01 2.06 ( 0.01

0.3 0.4 1.2 0.7 0.3 0.3 0.8 0.4

1.55 ( 0.00 1.16 ( 0.01 1.27 ( 0.02 1.32 ( 0.01 3.77 ( 0.01 3.18 ( 0.01 1.22 ( 0.01 2.07 ( 0.01

0.3 0.9 1.6 0.7 0.3 0.3 0.8 0.5

a Optimized MRM parameters for these 8 compounds were the same as their unlabeled analogues shown in Table 1; the MRM transitions are listed in this table.

Table 3. Intra- and Interday Precision of Peak Area Ratios of Eight Amino Acids vs Their Individual Stable Isotopic Internal Standard intraday assay (n ) 4)

compd/ added Ala/Ala-D4

Asp/Asp-D3

Glu/Glu-D3

Gly/Gly-D2-15N1

Lys/Lys-15N1

Phe/Phe-D8

Ser/Ser-D3

Val/Val-D8

added AA conc (µM)

mean AA/AA* peak area ratio

(

SD

0 1 3 5 0 1 3 5 0 1 3 5 0 1 3 5 0 1 3 5 0 1 3 5 0 1 3 5 0 1 3 5

3.60 3.70 4.18 4.52 0.59 0.69 0.93 1.17 4.17 4.34 4.89 5.27 0.25 0.30 0.34 0.46 0.28 0.41 0.66 0.89 0.31 0.42 0.64 0.84 0.50 0.59 0.77 0.98 0.19 0.25 0.37 0.49

( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( (

0.15 0.10 0.05 0.12 0.03 0.01 0.02 0.02 0.04 0.05 0.14 0.08 0.02 0.04 0.01 0.06 0.00 0.01 0.01 0.01 0.00 0.01 0.00 0.01 0.01 0.01 0.01 0.04 0.00 0.00 0.01 0.00

Asn isotopomer to the Asp signal was assessed from separate LCMS/MS analyses of the individual standards and comparison of the slopes of the calibration curves. From this information, it was determined that the actual Asp concentration can be derived by the following equation: [Asp]actual ) [Asp]measured 0.0603[Asn]reported. Similarly, the contribution of the heavy Gln isotopomer to the Glu channel can be assessed by the Gln responses at the m/z 148 > 84 transition, and the Glu concentra8072

interday assay (n ) 12)

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CV (%)

mean AA/AA* peak area ratio

(

SD

CV (%)

4.0 2.7 1.3 2.6 4.6 1.8 1.8 2.0 1.0 1.2 2.8 1.5 7.3 12.4 3.1 13.7 1.5 1.4 1.5 0.9 0.5 1.4 0.4 0.7 2.2 1.0 1.7 3.9 0.9 0.9 1.6 0.9

3.54 3.75 4.12 4.55 0.58 0.71 0.95 1.17 4.24 4.45 4.95 5.35 0.22 0.27 0.35 0.43 0.29 0.42 0.67 0.91 0.32 0.43 0.64 0.85 0.50 0.59 0.78 0.98 0.19 0.25 0.37 0.49

( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( (

0.11 0.16 0.16 0.23 0.03 0.03 0.03 0.04 0.12 0.12 0.12 0.15 0.03 0.05 0.04 0.05 0.01 0.01 0.02 0.02 0.01 0.01 0.02 0.02 0.02 0.01 0.03 0.03 0.00 0.00 0.01 0.01

3.0 4.2 3.8 5.0 4.4 3.6 3.6 3.4 2.9 2.7 2.5 2.8 13.1 17.7 10.3 12.0 2.5 2.9 2.8 2.5 2.5 2.7 2.8 2.5 3.5 2.5 3.6 3.4 1.5 1.1 1.4 1.3

tion can be corrected by the equation: [Glu]actual ) [Glu]measured - 0.053[Gln]reported. Method Validation. To determine the accuracy and reproducibility of the assay for different classes of compounds, eight representative deuterium- or 15N-labeled amino acids (collectively designated AA*) were chosen to represent a variety of retention times and chemical properties: nonpolar (Ala-D4, Gly-D2-15N1, and Val-D8), polar uncharged (Ser-D3), positively (Lys-15N1) and

Figure 4. Ion suppression of eight amino acids in different concentrations of Arabidopsis seed extract (n ) 16, the coefficients of variation of eight amino acids are 2.5-15.1%).

negatively charged (Asp-D3 and Glu-D3), and aromatic (Phe-D8) amino acids. To address the reproducibility of the system, assays were performed over three contiguous days. Retention times of the 8AA* were analyzed both in standard solutions and following spiking into different concentrations of seed extracts. The retention times only shifted (0.01 min for most of the amino acids, and the interday retention time precision (CV) ranged from 0.3 to 1.6% (Table 2). These results indicate that the HPLC conditions are reproducible from run to run. Next, the intra- and interday precisions of peak area ratios of eight amino acids versus their individual stable isotopically labeled internal standard were examined to evaluate the reproducibility of the system (Table 3). The intra- and interday CVs of seven AA* were less than or equal to 5%. Gly was the exception, with 3.1-14 and 10-18% for the intra- and interday precisions, respectively. This high variation is attributed to poor ionization of Gly that is a consequence of its hydrophilicity and to its low mass, which increases the likelihood of interference from solvent clusters. These data indicate that the peak area ratio serves as a reproducible measure of amino acid concentrations. Next, amino acid stability in seed extracts was evaluated by comparing the results of days 1, 2, and 3 (at 10 °C in the autosampler) and day 60 (stored -80 °C freezer). The ratios of the eight amino acid concentrations of days 2, 3, and 60 to day 1 ranged from 0.97 to 1.01, 0.98 to 1.00, and 0.99 to 1.02 with CV less than or equal to 6.1% (n ) 76) for seven amino acids. Although mean data were highly reproducible for Gly measurements, sample-to-sample variability was more variable (the mean ( SD of Gly concentration ratio of days 2, 3, and 60 to day 1 were 1.03 ( 0.30, 1.04 ( 0.28, and 1.04 ( 0.36, respectively), consistent with the higher analytical variability described above. These data

strongly indicate that most amino acids are quite stable in the biological matrix prepared using the simple water extraction and filtration method. As is commonly seen in LC-MS/MS methods, suppression of ion signals by the sample matrix was observed in plant extracts in the form of lower peak areas for the Phe-D8 and Val-D8 internal standards in matrixes other than in standards prepared in pure water. To further investigate the matrix effect (ME %), recovery (RE %), and process efficiency (PE %), samples containing 10 µM 8AA* in neat standard, in preextracts and in postextracts, were prepared and the peak areas were analyzed. ME, RE, and PE were calculated according to Matuszewski et al.26 (Table 4), with ME (%) ) 100 (areaspiked after extraction/areastandard solution), RE (%) ) 100(areaspiked before extraction/areaspiked after extraction), and PE (%) ) 100(areaspiked before extraction/areastandard solution). Ala-D4, Lys-15N1, PheD8, and Val-D8 gave ME values of ∼60% in seed extracts, while early-eluting Asp-D3, Glu-D3, Gly-D2-15N1, and Ser-D3 gave ME of ∼40% (note that higher ME values indicate lower ion suppression due to the matrix). These results support our expectation that the early-eluting compounds had higher ion suppression owing to coelution with other minimally retained substances. However, recovery characteristics are compound dependent, with Ala-D4, Glu-D3, Gly-D2-15N1, Phe-D8, Ser-D3, and Val-D8 demonstrating very good recoveries (>87%), Lys-15N1 approximately 73% and Asp-D3 62%. The overall process efficiencies ranged from 29 to 61%. These data indicate that different compounds have different recoveries (presumably largely due to differential interaction with the filtration medium) and susceptibilities to matrix effects. No evidence was observed for process efficiencies greater than 100% as might be expected if coeluting substances contributed to the detected signal for any amino acids. However, the magnitudes of analyte losses and matrix effects lead to the conclusion that it is necessary to have stable isotope-labeled amino acids as internal standards for the most accurate defining of their absolute concentrations in the extracts. To address whether extract dilution could dramatically reduce ion suppression, the 1× postextract sample was diluted with equal volume (0.5×) or 3 volumes (0.25×) of ddH2O and spiked with 10 µM 8AA*. As shown in Figure 4, ion suppression of the earlyeluting compounds (Asp-D3, Glu-D3, Gly-D2-15N1, and Ser-D3) decreases in diluted extracts, as is consistent with suppression of ionization by salts and other minimally retained substances. For instance, Glu-D3 ion suppression dropped from 66 to 51% in 0.25× dilution. Ion suppression, even in diluted seed extracts, was at least 30% in all cases. Ion suppression effects were also assessed using the method of standard additions, whereby additions of unlabeled amino acids were made to seed extracts at different dilutions to increase individual amino acid concentrations by 1, 3, and 5 µM. Slopes of the resulting plots of areaAA/areaIS were compared for different dilutions. The dependence of the slope upon extract concentration serves to indicate the magnitude of ion suppression by the sample matrix. Data presented in Table S2 (Supporting Information, left panel) show the slopes of plots of the analyte peak area versus concentration for eight amino acids. The slopes of Ala, Lys, Phe, and Val showed minimal dependence on extract dilution. In (26) Matuszewski, B. K.; Constanzer, M. L.; Chavez-Eng, C. M. Anal. Chem. 2003, 75, 3019-3030.

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Table 4. Matrix Effect (ME %), Recovery (RE %), Process Efficiency (PE %) of the Eight Amino Acids intraday assay (n ) 4) ME (%)a

interday assay (n ) 12)

RE (%)b

PE (%)c

ME (%)a

RE (%)b

PE(%)c

compd

mean

CV (%)

mean

CV (%)

mean

CV (%)

mean

CV (%)

mean

CV (%)

mean

CV (%)

Ala-D4 Asp-D3 Glu-D3 Gly-D2-15N1 Lys-15N1 Phe-D8 Ser-D3 Val-D8

63.6 43.6 35.9 45.9 65.1 66.7 38.5 57.8

8.6 10.6 6.4 13.1 10.5 8.9 8.2 4.3

91.5 63.0 91.8 88.4 74.3 95.8 88.6 95.0

5.2 2.4 3.1 7.1 3.0 3.6 2.3 2.1

60.0 28.7 33.1 40.6 48.9 61.0 35.2 52.5

8.7 11.6 5.7 12.9 8.5 8.1 9.2 2.5

63.4 47.1 35.2 45.8 65.6 66.4 40.3 61.1

6.2 16.2 5.0 8.4 9.3 8.6 8.6 8.6

91.7 62.1 88.7 86.7 73.3 94.4 89.2 94.2

4.8 3.9 4.0 8.6 2.7 2.6 2.7 1.7

58.4 30.3 31.6 39.9 48.3 59.5 36.5 55.0

5.6 16.8 6.5 10.3 6.1 6.6 9.8 6.8

a

Matrix effect. b Recovery efficiency. c Process efficiency.

Table 5. Intra- and Interday Accuracy (%) in Different Dilutions of Arabidopsis Seed Extract intraday assay (n ) 4) 1×R

: added AA Ala

Asp

Glu

Gly

Lys

Phe

Ser

Val

a

µM

measured [AA], µM

0 1 3 5 0 1 3 5 0 1 3 5 0 1 3 5 0 1 3 5 0 1 3 5 0 1 3 5 0 1 3 5

0.07 1.09 2.63 5.20 -0.17 1.17 3.07 4.93 0.05 0.97 2.94 5.04 -0.17 0.77 3.88 4.52 -0.05 1.02 3.08 4.95 -0.04 1.03 3.03 4.97 0.04 0.93 3.05 4.99 -0.02 1.02 3.03 4.98

interday assay (n ) 12)

0.5× acc, % 109 88 104 117 102 99 97 98 101 77 129 90 102 103 99 103 101 100 93 102 100 102 101 100

measured [AA], µM -0.18 1.27 2.89 5.01 -0.02 1.02 3.00 5.00 -0.06 1.04 3.05 4.96 -0.15 1.30 2.76 5.08 -0.04 1.02 3.05 4.96 -0.02 1.00 3.04 4.97 -0.03 1.01 3.05 4.97 -0.05 1.01 3.09 4.95

0.25× acc, % 127 96 100 102 100 100 104 102 99 130 92 102 102 102 99 100 101 100 101 102 99 101 103 99

measured [AA], µM -0.09 1.11 3.00 4.98 -0.05 1.05 3.02 4.98 -0.48 1.14 3.92 4.42 0.00 1.20 2.58 5.21 -0.02 1.00 3.03 4.98 0.00 1.00 3.00 5.00 -0.01 1.03 2.97 5.01 0.00 1.00 3.00 5.00

1× acc, % 111 100 100 105 101 100 115 131 88 121 86 104 101 101 100 100 100 100 103 99 100 100 100 100

measured [AA], µM 0.01 1.04 2.90 5.05 -0.07 1.05 3.07 4.95 0.00 0.92 3.16 4.92 -0.16 1.16 3.08 4.93 -0.04 1.02 3.06 4.96 -0.04 1.03 3.04 4.97 0.02 1.00 2.94 5.04 -0.02 1.01 3.03 4.98

0.5× acc, % 104 97 101 105 102 99 92 105 98 116 103 99 102 102 99 103 101 99 100 98 101 101 101 100

measured [AA], µM -0.15 1.21 2.97 4.98 0.00 0.99 3.02 4.99 -0.02 1.03 2.98 5.00 0.08 0.93 2.95 5.05 -0.04 1.02 3.06 4.96 -0.01 1.00 3.03 4.98 -0.02 1.00 3.06 4.97 -0.04 1.01 3.07 4.95

0.25× acc, % 121 99 100 99 101 100 103 100 100 93 98 101 102 102 99 100 101 100 100 102 99 101 102 99

measured [AA], µM -0.13 1.17 2.97 4.98 -0.02 1.01 3.02 4.99 -0.46 1.08 3.99 4.39 0.02 1.10 2.75 5.14 -0.02 1.01 3.05 4.97 0.00 1.00 3.00 5.00 -0.01 1.01 3.00 5.00 0.00 1.01 2.98 5.01

acc, % 118 99 100 101 101 100 108 133 88 110 92 103 101 102 100 100 100 100 101 100 100 101 99 100

Dilutions.

contrast, Asp, Glu, and Ser slopes dramatically decreased as the matrix concentration increased. It may not be coincidental that Asp and Glu are two of the three amino acids with the greatest effects of matrix upon ionization, as the acidic amino acids can be expected to form more [M + Na]+ and [M + K]+ from association with alkali metal ions in the sample extracts owing to their low pKa values. To precisely quantify these analytes, calibration curves plotted by the analyte concentration versus peak area ratio of AA/AA* should be applied. In this case, the matrix effects to AA and AA* were cancelled so that the slopes in different 8074

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concentration matrices will be same (Table S2, right panel). Meanwhile, doubled intercepts were obtained when the matrix concentration was doubled, as expected. Thus, good linearity and reproducibility were achieved for most of the amino acids within the matrix concentration range tested. The accuracy of the method was also examined by analyzing quality control samples in Arabidopsis seed extracts using the method of standard additions. Four different concentrations of unlabeled 8AA mix (0, 1, 3, or 5 µM) with fixed concentration of 8AA* internal standards (10 µM) were spiked in 1×, 0.5×, and

0.25× extracts for four replicates. Standard curves (Table S2) were generated by plotting the added AA concentration versus peak area ratio of AA/AA* (Table 3) and the intra- and interday accuracies were calculated by the following equation: accuracy (%) ) 100 × calculated concentration/nominal concentration. As shown in Table 5, Lys, Phe, Ser, and Val gave the best results, with 93-103 and 98-103% intra- and interday accuracy, respectively. Asp had high accuracies in 0.5× (99-102%) and 0.25× (100-105%), as did Glu in 1× (100-105%) and 0.5× (100105%) extracts. Taken together, within the extract concentration range tested, 1/2 extract dilution showed high accuracy for most of the amino acids. Therefore, 1/2 dilution or using 200 µL of extraction buffer/mg Arabidopsis seeds was proposed to be an appropriate procedure to minimize matrix effects for this LCMS/MS method. CONCLUSIONS An accurate and reproducible LC-MS/MS method for quantifying 25 amino acids and metabolically related compounds in a biological matrix was developed and evaluated, with analysis times of 6 min/sample. Standard deviations of the retention times were within 0.02 min, and intra- and interday precisions within 5% for most of the compounds. The matrix effect ranged from 35 to 69%, and dilution of extracts diminished the ion suppression for the early-eluting compounds, but had minimal effects for late-eluting ones. The isomers Ile and Leu, as well as 17 other amino acids and 4 metabolically related compounds, were separated within 4 min. Monitoring the transition of m/z 132 > 86 is suitable when Ile and Leu are chromatographically resolved, but m/z 132 > 69 and 132 > 30 transitions provide alternative means of isomerselective measurement of Ile and Leu, respectively, when these metabolites are not resolved. The coeluting Thr and HSer isomers can be quantified using m/z 120 > 57 (Thr) and 120 > 44 (HSer) transitions. Sample preparation procedures were simplified and recoveries greater than 62% were achieved for the eight amino acids tested. After dilution, ion suppression was consistent among

diverse amino acids. This finding eliminates the need for isotopically labeled standards for each metabolite in every sample and allows use of Phe-D8 as internal standard for quantification of all metabolites. These findings highlight ways that improved chromatographic separations and selective ion fragmentation can improve measurements of target metabolites in large-scale screening programs where sample throughput and cost controls are necessary. The described method is suitable for quantifying underivatized amino acids and related metabolites in Arabidopsis seed tissue with good reproducibility, high accuracy, and low intra- and interday variation. These procedures have already been used to analyze 2000 seed and leaf extracts during the past year (http://plastid.msu.edu/). Findings from these studies will be reported separately. This approach may also fulfill the requirements for the diagnosis of amino acid metabolismrelated disorders in clinical fields, analysis of fermentation processes, and for food analysis once matrix effects are evaluated for each new sample matrix. ACKNOWLEDGMENT We thank Lijun Chen of the Michigan State University Mass Spectrometry Core, Eva Collakova of the Michigan State University Plant Biology Department, and Yan Lu in the Last Laboratory for assistance in various stages of the project. This project was supported by National Science Foundation grant MCB-0519740 (to R.L.L). SUPPORTING INFORMATION AVAILABLE Additional information as noted in text. This material is available free of charge via the Internet at http://pubs.acs.org.

Received for review May 9, 2007. Accepted August 7, 2007. AC070938B

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