Capillary LC Coupled with High-Mass Measurement Accuracy Mass

Anal. Chem. 2007, 79, 6081-6093

Capillary LC Coupled with High-Mass Measurement Accuracy Mass Spectrometry for Metabolic Profiling Jie Ding, Christina M. Sorensen, Qibin Zhang, Hongliang Jiang, Navdeep Jaitly, Eric A. Livesay, Yufeng Shen, Richard D. Smith, and Thomas O. Metz*

Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352

We have developed an efficient and robust high-pressure capillary LC-MS method for the identification of large numbers of metabolites in biological samples using both positive and negative ESI modes. Initial efforts focused on optimizing the separation conditions for metabolite extracts using various LC stationary phases in conjunction with multiple mobile-phase systems, as applied to the separation of 45 metabolite standards. The optimal mobile and stationary phases of those tested were determined experimentally (in terms of peak shapes, theoretical plates, retention of small, polar compounds, etc.), and both linear and exponential gradients were applied in the study of metabolite extracts from the cyanobacterium Cyanothece sp. ATCC 51142. Finally, an automated dual-capillary LC system was constructed and evaluated for the effectiveness and reproducibility of the chromatographic separations using the above samples. When coupled with a commercial LTQ-orbitrap MS, ∼900 features were reproducibly detected from Cyanothece sp. ATCC 51142 metabolite extracts. In addition, 12 compounds were tentatively identified, based on accurate mass, isotopic distribution, and MS/MS information. Metabolomics,1-5 or the identification and quantification of the low molecular weight metabolites and related species for a system of interest, is an emerging discipline in the postgenomics era. Quantitative metabolomic measurements that can cover a significant fraction of either the intracellular, extracellular, or biofluid metabolomes are key to understanding metabolism and regulation of biological systems and also complement gene expression and proteomic information. This coordination of genomic, proteomic, and metabolomic datasalso known as systems biologyscan provide a more complete understanding of biological systems and their responses to environmental perturbations. However, a single technological platform is not capable of detecting and quantifying * Corresponding author. Tel: 509-376-8333. Fax: 509-376-2303. E-mail: [email protected]. (1) Fiehn, O. Plant Mol. Biol. 2002, 48, 155-171. (2) Oliver, D. J.; Nikolau, B.; Wurtele, E. S. Metab. Eng. 2002, 4, 98-106. (3) Bino, R. J.; Hall, R. D.; Fiehn, O.; Kopka, J.; Saito, K.; Draper, J.; Nikolau, B. J.; Mendes, P.; Roessner-Tunali, U.; Beale, M. H.; Trethewey, R. N.; Lange, B. M.; Wurtele, E. S.; Sumner, L. W. Trends Plant Sci. 2004, 9, 418-425. (4) Dunn, W. B.; Bailey, N. J. C.; Johnson, H. E. Analyst 2005, 130, 606-625. (5) Shulaev, V. Brief Bioinf. 2006, 7, 128-139. 10.1021/ac070080q CCC: $37.00 Published on Web 07/18/2007

© 2007 American Chemical Society

the entire metabolome in a given analysis. Therefore, the majority of published metabolomics studies are essentially reports of the application of metabolic profiling1,5,6 to a given model system. While recent published studies have been promising, significant challenges remain that impact the practical implementation of metabolic profiling as an analytical tool. These include the sample chemical complexity and dynamic range, as well as the analytical and biological variance. Early studies have utilized either gas chromatography-mass spectrometry (GC/MS) or high-field nuclear magnetic resonance (NMR) spectroscopy. GC/MS was used to analyze uncommon metabolites of the plant Arabidopsis thaliana.7 Based on mass accuracy and isotopic ratios, elemental formulas of ∼70 compounds were determined, with more than 15 being structurally elucidated. Similarly, GC time-of-flight (TOF) MS was used to build a metabolomic mass spectral and retention time index database covering major organs of potato, tobacco, and A. thaliana comprising roughly 6000 components.8 Thus, GC/ MS represents a viable analytical method for metabolic profiling applications. However, the technique is limited to analyses of volatile compounds and requires chemical derivatization of small, polar molecules such as amino acids and sugars. Such sample processing can be a source of systematic error. NMR is a nondestructive analytical tool that can be used to study biological fluids and intact biomaterials without intensive sample processing.9-12 This technique provides chemical specificity for compounds containing elements or isotopes with nonzero (paramagnetic) magnetic moments such as 1H, 13C, and 15N. The necessity of paramagnetic nuclei places a restriction on metabolic profiling analyses by NMR. While 1H is the most abundant (99.9%) isotope of hydrogen found naturally, 13C and 15N represent only 1.1 and 0.37% of total carbon and nitrogen in nature, respectively, requiring stable isotopic labeling of samples with 13C and 15N if these nuclei are to be utilized for NMR experiments. Recent (6) Fiehn, O. Methods Mol. Biol. 2006, 323, 439-447. (7) Fiehn, O.; Kopka, J.; Trethewey, R. N.; Willmitzer, L. Anal. Chem. 2000, 72, 3573-3580. (8) Wagner, C.; Sefkow, M.; Kopka, J. Phytochemistry 2003, 62, 887-900. (9) Lindon, J. C.; Nicholson, J. K.; Holmes, E.; Everett, J. R. Concepts Magn. Reson. 2000, 12, 289-320. (10) Nicholson, J. K.; Connelly, J.; Lindon, J. C.; Holmes, E. Nat. Rev. Drug Discovery 2002, 1, 153-161. (11) Lindon, J. C.; Holmes, E.; Nicholson, J. K. Anal. Chem. 2003, 75, 385A391A. (12) Nicholls, A. W.; Mortishire-Smith, R. J.; Nicholson, J. K. Chem. Res. Toxicol. 2003, 16, 1395-1404.

Analytical Chemistry, Vol. 79, No. 16, August 15, 2007 6081

developments in technology such as cryogenically cooled sample probes13,14 and magic angle spinning15 have dramatically increased the sensitivity and throughput of 1H NMR. However, the sensitivity and achievable dynamic range of NMR-based metabolic profiling measurements are still relatively moderate compared to MS-based methods. Recently, capillary electrophoresis (CE) has been utilized in conjunction with UV or MS in metabolic profiling analyses.16-19 CE can provide very high separation efficiencies; nevertheless, multiple analyses are required for the detection of anionic, cationic, and neutral metabolites. Also, careful consideration is essential when interfacing CE with MS detection in order to maintain high MS sensitivity. For example, dilution of the analyte should be avoided, and volatile electrospray solvents must be used. Alternatively, direct infusion approaches using soft ionization techniques (electrospray ionization or atmospheric chemical ionization) coupled to Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS)20,21 or quadrupole time-of-flight mass spectrometry22 have been developed for metabolic fingerprinting studies. Direct infusion MS-based approaches provide high throughput but usually suffer from matrix effects (e.g., ion suppression or enhancement), which obviously generate bias in the results and may be inapplicable for quantitative metabolite analysis. Through utilization of soft ionization techniques (e.g., electrospray ionization, ESI), liquid chromatography-mass spectrometry (LC-MS) is increasingly used for metabolic profiling studies.23-26 For LC-MS-based studies, it is critical to maximize the chromatographic separation of complex samples prior to introduction to the MS detector in order to reduce ionization suppression and thereby increase the sensitivity, dynamic range, and identification coverage. No one single technology will be able to meet the requirements of metabolomics. Our goal is to develop a suitable high-efficiency liquid chromatography-high-mass accuracy measurement method in order to systematically identify as many metabolites as possible in a biological sample using both positive and negative ion modes. (13) Keun, H. C.; Beckonert, O.; Griffin, J. L.; Richter, C.; Moskau, D.; Lindon, J. C.; Nicholson, J. K. Anal. Chem. 2002, 74, 4588-4593. (14) Spraul, M.; Freund, A. S.; Nast, R. E.; Withers, R. S.; Maas, W. E.; Corcoran, O. Anal. Chem. 2003, 75, 1536-1541. (15) Wang, Y.; Bollard, M. E.; Keun, H.; Antti, H.; Beckonert, O.; Ebbels, T. M.; Lindon, J. C.; Holmes, E.; Tang, H.; Nicholson, J. K. Anal. Biochem. 2003, 323, 26-32. (16) Soga, T.; Ohashi, Y.; Ueno, Y.; Naraoka, H.; Tomita, M.; Nishioka, T. J. Proteome Res. 2003, 2, 488-494. (17) Sato, S.; Soga, T.; Nishioka, T.; Tomita, M. Plant J. 2004, 40, 151-163. (18) Soo, E. C.; Aubry, A. J.; Logan, S. M.; Guerry, P.; Kelly, J. F.; Young, N. M.; Thibault, P. Anal. Chem. 2004, 76, 619-626. (19) Ramautar, R.; Demirci, A.; de Jong, G. J. TrAC, Trends Anal. Chem. 2006, 25, 455-466. (20) Aharoni, A.; Ric de Vos, C. H.; Verhoeven, H. A.; Maliepaard, C. A.; Kruppa, G.; Bino, R.; Goodenowe, D. B. Omics 2002, 6, 217-234. (21) Brown, S. C.; Kruppa, G.; Dasseux, J.-L. Mass Spectrom. Rev. 2005, 24, 223-231. (22) Boernsen, K. O.; Gatzek, S.; Imbert, G. Anal. Chem. 2005, 77, 7255-7264. (23) Tolstikov, V. V.; Lommen, A.; Nakanishi, K.; Tanaka, N.; Feihn, O. Anal. Chem. 2003, 75, 6737-6740. (24) Wang, W.; Zhou, H.; Lin, H.; Roy, S.; Shaler, T. A.; Hill, L. R.; Norton, S.; Kumar, P.; Anderle, M.; Becker, C. H. Anal. Chem. 2003, 75, 4818-4826. (25) Shen, Y.; Zhang, R.; Moore, R. J.; Kim, J.; Metz, T. O.; Hixson, K. K.; Zhao, R.; Livesay, E. A.; Udseth, H. R.; Smith, R. D. Anal. Chem. 2005, 77, 30903100. (26) Lafaye, A.; Labarre, J.; Tabet, J.-C.; Ezan, E.; Junot, C. Anal. Chem. 2005, 77, 2026-2033.

6082

Analytical Chemistry, Vol. 79, No. 16, August 15, 2007

It is well-known that the sensitivity of ESI-mass spectrometry detection increases with decreasing LC flow rate;27 therefore, we have selected capillary LC coupled with MS. In order to determine the optimum chromatographic conditions of those tested for metabolic profiling separations, the following experiments were performed. First, various commercially available stationary phases were evaluated in conjunction with several mobile phases using a commercial LC system coupled with an ion trap MS. The selection of the best mobile phase and stationary phase was based on the separation efficiency of a 45-component metabolite mixture. Next, a manually operated single mixer, single-column, highpressure LC system was developed in order to evaluate the separation efficiency achieved by constant-pressure LC. Finally, an automated, high-pressure LC system was assembled and operated in parallel with a commercially available LC system under the optimum chromatographic conditions of those examined and using Cyanotheces as the model sample, in order to evaluate the separations obtained under constant pressure or constant flow rate, in addition to system robustness and reproducibility. EXPERIMENTAL SECTION Reagents and Materials. HPLC-grade (Optima) water, acetonitrile, and methanol were purchased from Fisher Scientific (Fair Lawn, NJ). HPLC-grade acetic acid and trifluoroacetic acid were purchased from Aldrich (St. Louis, MO). MS-grade ammonium acetate and triethylamine were obtained from Fluka (St. Louis, MO). Sample Preparation. (1) Metabolite Standard Mixture. All metabolite standards (Table 1) were purchased from Sigma Chemical Co. (St. Louis, MO) unless otherwise noted. Prostaglandin-E2, thromboxane-B2, and 6-keto-prostaglandin-f1R were obtained from Cayman Chemical (Ann Arbor, MI). Individual standard stock solutions were prepared by dissolving the appropriate amount of material in water/acetonitrile (50:50, v/v) to make a 1 mM solution. The combined metabolite standard was then prepared to 10 µM in water. The stock solutions were stored at -80 °C. (2) Cyanothece Species ATCC 51142 Metabolome. Cyanothece species ATCC 51142 cell lysates were received frozen on dry ice from the laboratory of Dr. Himadri Pakrasi at Washington University (St. Louis, MO). The Cyanothece metabolome was extracted using cold organic solvent. Briefly, 400 µL of cold (-20 °C) 2-propanol was added to 100 µL of cell lysate, and the mixture was vortexed for 10 s. The sample was then maintained at 4 °C for 15 min to aid protein precipitation. Proteins were isolated by centrifugation at 12 000 rpm for 10 min, and the supernatant was removed by pipetting into a sterile, siliconized Eppendorf tube. The sample was then dried in vacuo and reconstituted in 200 µL of mobile phase A, followed by centrifugation at 12 000 rpm for 5 min to remove particulates prior to analysis. Preparation of Packed Capillary Columns and Mobile Phases. All capillary LC columns in this study were slurry-packed in-house with 3-5-µm particles using a previously described procedure.28 Briefly, a stationary phase was added to a stainless steel reservoir, to which an empty fused-silica capillary (Polymicro (27) Abian, J.; Oosterkamp, A. J.; Gelpi, E. J. Mass Spectrom. 1999, 34, 244254.

Table 1. Composition of Metabolite Standard compound

logD

amino acid alanine aspartic acid cysteine leucine lysine threonine tryptophan

compound

logD

prostaglandin -3.2 -3.9 -2.3 -1.8 -4.5 -3.7 -1.5

6-keto-prostaglandin-F1R prostaglandin-E2 thromboxane-B2

-1.7 6.4

vitamin

0.1 1.1 1.4

coenzyme acetyl-CoA CoA FAD

-9.7 -9.8 -8.0

organic acid succinic acid palmitic acid amine creatinine 1-methylhistamine spermine taurine

-1.8 -4.4 -7.0 -5.0

L-carnitine

pantothenic acid pyridoxal 5′-phosphate pyridoxine riboflavin thiamine

-3.9 -1.9 -5.0 -1.4 -2.4 -1.8

nucleobase/nucleoside/ nucleotide sugar fructose 1,6bisphosphate glucosamine glucose glucose 1-phosphate UDP-glucose

-6.8 -4.8 -1.9 -3.9 -9.0

small peptide glutathione (oxidized) glutathione (reduced)

-4.1 -2.9

adenosine ADP cAMP ATP CMP CTP cytosine 2′-deoxyadenosine purine TTP UDP uracil UTP

-1.0 -7.3 -3.3a -9.5 -4.6 -11.0 -1.7 -0.5 -0.4 -10.5 -8.8 -0.7 -11.0

a The distribution coefficient for cAMP could not be calculated by the ACD/I-Lab Web service due to the cyclic phosphate group. Thus, the distribution coefficient for AMP is reported.

Technologies, Phoenix, AZ) was connected. The opposite end of the capillary was connected to a stainless steel union (Valco, Houston, TX) containing a stainless steel screen (2-µm mesh, Valco), which served as a frit. Acetonitrile was used as the packing solvent and was delivered at constant pressure by syringe pump (Isco, Lincoln, NE). Initially, a pressure of 100 psi was applied. The pressure was increased stepwise to and held constant at 7000 psi for 5-10 min under sonication. The commercial sources of nine stationary-phase materials and their properties are listed in Table 2. The choice of these stationary phases was dictated, in part, by the commercial availability of bulk material. Table 3 describes various mobile phases that were utilized in conjunction with the nine stationary phases to separate the metabolite standard mixture. Please note that mobile-phase system I is that typically used in our laboratory for routine proteomics separations.29 (28) Shen, Y.; Zhao, R.; Belov, M. E.; Conrads, T. P.; Anderson, G. A.; Tang, K.; Pasˇa-Tolic´, L.; Veenstra, T. D.; Lipton, M. S.; Udseth, H. R.; Smith, R. D. Anal. Chem. 2001, 73, 1766-1775. (29) Shen, Y.; Tolic´, N.; Zhao, R.; Pasˇa-Tolic´, L.; Li, L.; Berger, S. J.; Harkewicz, R.; Anderson, G. A.; Belov, M. E.; Smith, R. D. Anal. Chem. 2001, 73, 30113021.

Commercial LC System. An Agilent 1100 series NanoLC system (Agilent Technologies, Inc., Palo Alto, CA) was coupled with a LCQ-MS (Thermo Electron, San Jose, CA) and used in a preliminary evaluation of stationary-phase and mobile-phase systems. Various stationary-phase (Table 2) and mobile-phase combinations (Table 3) were explored in an attempt to identify the optimal combination of those tested for metabolic profiling separations, using the metabolite standard as the model sample. For these preliminary experiments, the LC column dimensions were 75 µm i.d. × 32 cm, and 1 µL of sample was injected each time. In subsequent experiments to compare linear to exponential gradients, the column dimensions were 150 µm i.d. × 60 cm, and 10 µL of sample was injected. The detailed chromatographic conditions for different column dimensions are listed in Table 4. While the maximum pressure limit on most commercial LC systems is ∼400 bar (∼5800 psi), our experience is that consistent operation of these systems at such high pressures results in premature failure of pump components. Manual High-Pressure LC System. Although our laboratory has successfully applied automated, high-pressure capillary LC systems in proteomics studies,29 no such system has been developed for metabolic profiling. In order to assess the practicality of developing an automated, high-pressure LC system devoted to metabolite separations, a manual capillary LC system was first used to evaluate the separation efficiency achieved by constantpressure LC. The detailed LC instrumentation has been described previously.28 Mobile-phase system V (Table 3) was used during evaluation of the manual high-pressure LC system. The LC system was equilibrated at 6000 psi with 100% mobile phase A prior to injecting 1 µL of freshly prepared metabolite extract onto the column (75 µm i.d. × 60 cm). Exponential gradient elution was initiated 5 min after sample loading with a column flow of ∼0.3 µL/min. The sample loop was bypassed during gradient elution in order to eliminate unnecessary void volume. Fused-silica capillaries (30-µm i.d. with various lengths) were used to manipulate the gradient speed by splitting the flow delivered from the stainless steel mixer (2.5 mL). Since mobile phase B is continuously delivered to the mixer during the separation, a faster split flow provides a faster flow of mobile phase B into the mixer. In other words, a faster split flow causes a faster gradient, which essentially controls the separation performance. A split flow of 27 µL/min was chosen based on the separation performance observed for the metabolite standard and Cyanothece metabolite extracts. The capillary LC was coupled on-line with an Agilent TOF-MS through a home-built ESI interface. Briefly, the commercial electrospray source was replaced with an electrodynamic ion funnel, which has been shown to provide up to 1 order of magnitude improved sensitivity.30 A stainless steel union was used to connect an ESI emitter to the capillary separation column without sheath gas or makeup liquid. The heated inlet capillary temperature and electrospray voltage were 200 °C and 1.8 kV, respectively. MS data were recorded over the m/z range 1001000 at a scan rate of 1 scan/s. Each run was followed by re(30) Kim, T.; Tolmachev, A. V.; Harkewicz, R.; Prior, D. C.; Anderson, G. A.; Udseth, H. R.; Smith, R. D.; Bailey, T. H.; Rakov, S.; Futrell, J. H. Anal. Chem. 2000, 72, 2247-2255.


6083

Table 2. Commercial Source and Properties of Stationary-Phase Packing Material name of packing material

particle size (µm)

pore size (Å)

Jupiter C18-RP Synergi Fusion-RP Synergi Hydro-RP Synergi Polar-RP Zorbax 300 SB-C18 Primesep B2

5 4 4 4 5 5

300 80 80 80 300 100

170 475 475 475 45 335

Primesep 100

5

100

335

Astec Inc., Whippany, NJ

Teicoplanin

5

100

310

PolyLC, Columbia, MD

HILIC

3

100

∼300

commericial sources Phenomenex, Torrance, CA

Agilent, Palo Alto, CA Allsep, Prospect Heights, IL

surface area (m2/g)

separation mode reversed phase reversed phase reversed phase reversed phase reversed phase reversed phase and anion exchange reversed phase and cation exchange reversed phase and polar organic hydrophilic interactions

Table 3. Mobile-Phase Compositions system I II III IV V VI VII VIII IX

mobile phase A 0.2% acetic acid + 0.05% trifluoroacetic acid in water 20 mM ammonium acetate in water, pH 6.8 20 mM ammonium acetate in water, pH 5.5 20 mM ammonium acetate in water, pH 5.5 10 mM ammonium acetate in water, pH 5.3 10 mM ammonium acetate in water, pH 5.3 10 mM ammonium acetate in 90:10 acetonitrile/H2O 35 mM ammonium acetate in 90:10 acetonitrile/H2O 10 mM ammonium acetate in water, pH 5.3

mobile phase B

stationary phases evaluated

0.1% trifluoroacetic acid in 90:10 acetonitrile/H2O acetonitrile

Jupiter C18; Teicoplanin

acetonitrile

Jupiter C18; Fusion

0.1% acetic acid in acetonitrile

Fusion

10 nM ammonium acetate in 90:10 acetonitrile/H2O 10 mM ammonium acetate in methanol 10 mM ammonium acetate in water, pH 5.3 35 mM ammonium acetate in water, pH 5.3 0.1% trifluoroacetic acid in methanol

Jupiter C18;Fusion; Hydro; Polar; Zorbax; Primesep B2; Primesep 100 Fusion; Hydro; Polar

equilibration of the column at 100% A for 100 min prior to the next injection. Automated High-Pressure, Dual-Column LC System. An automated dual-column LC system was constructed in order to increase sample throughput. The single-column, manual system is capable of ∼five 150-min analyses in 24 h, which will improve to eight analyses per 24 h by adopting a dual-column configuration. The detailed construction of the LC system has been previously described.29,31 Two 150 µm i.d. × 60 cm self-packed capillary columns were used with this system, and the mobile phases (mobile-phase system V, Table 3) were the same as was described for the manual high-pressure system. The LC system was equilibrated at 6000 psi with 100% mobile phase A prior to injecting 10 µL of sample. Exponential gradient elution was initiated 8 min after sample loading with an initial column flow of ∼1.2 µL/min. The dual-column system was coupled to an LTQ-orbitrap mass spectrometer (Thermo Electron) using an ESI interface without sheath gas or makeup liquid. The capillary temperature and electrospray voltage were 200 °C and 2.0 kV, respectively. MS data were recorded over the m/z range 100-1000 with an LTQorbitrap duty cycle of ∼1.6 s. In other experiments, the dualcolumn system was coupled to an LTQ-FT mass spectrometer (Thermo Electron), as described above. The capillary temperature and electrospray voltage were the same as for the LTQ-orbitrap, (31) Belov, M. E.; Anderson, G. A.; Wingerd, M. A.; Udseth, H. R.; Tang, K.; Prior, D. C.; Swanson, K. R.; Buschbach, M. A.; Strittmatter, E. F.; Moore, R. J.; Smith, R. D. J. Am. Soc. Mass Spectrom. 2004, 15, 212-232.

6084 Analytical Chemistry, Vol. 79, No. 16, August 15, 2007

Jupiter C18

HILIC HILIC Tecoplainin

and MS data were recorded over the m/z range 100-1000 with an LTQ-FT duty cycle of ∼1.0 s. LC-MS Data Processing, Alignment, and Normalization. LC-MS data were processed by first deisotoping the raw spectra, which are essentially converted to tables of masses and spectrum number (or elution times), followed by identification of LC-MS features characterized by monoisotopic mass and elution time, i.e., peak-picking. In this work, a deisotoping signal-to-noise threshold of 65 was specified in order to minimize the contribution of chemical noise to the total feature count. Additional information regarding deisotoping and peak-picking can be found in the recent review by Zimmer et al.32 Identified features were saved in tab-delimited format and opened with the in-house-developed software MultiAlign for subsequent retention time alignment and intensity normalization. MultiAlign is a stand-alone program that incorporates the LCMSWARP algorithm33 for nonlinear chromatographic alignment of multiple LC-MS data sets. Features reproducibly observed in multiple analyses were grouped by single linkage clustering in two dimensions, mass and normalized elution time (NET), based on user-defined options. For these data, mass and NET tolerances of (3 ppm and (0.02 NET (representing (3 min of a 150-min LC separation) were selected based on empirical observation of (32) Zimmer, J. S.; Monroe, M. E.; Qian, W.-J.; Smith, R. D. Mass Spectrom. Rev. 2006, 25, 450-482. (33) Jaitly, N.; Monroe, M. E.; Petyuk, V. A.; Clauss, T. R. W.; Adkins, J. N.; Smith, R. D. Anal. Chem. 2006, 78, 7397-7409.

Table 4. Chromatographic Conditions for Different Size Columns

column size

injection (µL)

flow rate (µL/min)

75 µm × 32 cm

1

0.3

150 µm × 60 cm

10

1

gradient t (min)

B (%)

0 3.5 33.5 43.5 46 76

2 2 100 100 2 2

0 10 150 180 182 282

0 0 90 90 0 0

mass spectrometer and LC system performance. A single data set was arbitrarily chosen as a baseline for alignment, and multiple data set alignment was accomplished in under 1 min. An additional option for data management and processing allows data sets to be subgrouped by the user. In this study, subgrouping was utilized to compare the inter- and intracolumn reproducibility of the dualcolumn, high-pressure LC system, as well as the commercial LC system. Subgroups were defined to include data sets from column 1, column 2, or both columns from the high-pressure LC system, as well as those from the commercial LC system. After chromatographic alignment, intensity normalization was applied using the expectation maximization algorithm. Briefly, this algorithm analyzes the histogram of log ratios of intensities of features common to two or more data sets and finds the peak apex of this distribution by assuming that the histogram is a mixture of a normal density corresponding to unchanged features and uniform density background corresponding to changed features. The expectation maximization algorithm is used for calculating the normal part and uniform part of the histogram, and the shift in intensity is applied to all features in the aligned data sets. Graphs are produced showing the alignment of the alignee(s) to the baseline and the log ratio intensity histogram of the count of features present in the alignee versus the log of alignee(s)/baseline; the normalized output (cluster number, mass, NET, and intensity) for subgroup levels can then be exported in tab-delimited format for subsequent data processing in programs such as Excel or MatLab. Prediction of Metabolite Distribution Coefficients. The octanol-water distribution coefficient (LogD) for each metabolite standard was predicted at pH 5.3 using the ACD/I-Lab Web service (ACD/LogD 8.02) available at http://www.acdlabs.com. RESULTS AND DISCUSSION Optimization of LC Chromatographic Conditions. Global metabolite extracts can be quite complex based on sample type and preparation method, but generally include small organic and amino acids, nucleotides, carbohydrates, vitamins, and lipids. Various secondary metabolites are also possible, depending on species of origin (e.g., plant versus mammal), which adds further complexity to the sample. The chemical complexity of a typical metabolite extract results in sample components with wide ranges of solubility and polarity, as well as a high dynamic range of

concentration. Therefore, a robust separation approach with high resolving power is required in order to separate complex samples into individual components. High-efficiency capillary LC separations in conjunction with high-mass accuracy MS measurements can address both the extreme chemical complexity and dynamic range of metabolite samples. Initial work involved the selection of a suitable stationary-phase and mobile-phase combination to separate a 45-component metabolite standard using a commercial LC system. The components of the metabolite standard were arbitrarily selected in an attempt to fill the chromatographic space of a typical reversed-phase separation and to generally represent the chemical complexity of sample metabolomes. While not every chemical class of metabolite expected in a sample is represented, the moderate chemical complexity represented by the standards was deemed sufficient for evaluating LC column performance. Much development work has been performed in our group to optimize the separations of complex peptide mixtures25,28,34-36 in order to increase peptide identifications by MS/MS. An initial attempt to utilize the stationary- and mobile-phase system (system I, Table 3) typically used in our laboratory for proteomics separations resulted in good peak shape for certain primary aminecontaining compounds, such as riboflavin and thiamine; however, it was observed that the majority of metabolite standards eluted either in the void volume or as a broad peak, which indicated poor retention for small polar molecules when using this stationary- and mobile-phase combination (data not shown). Therefore, eight additional silica-based packing materials (Table 2) were evaluated in conjunction with different mobile phases (Table 3) in order to optimize the chromatographic separation of the 45component metabolite standard. Among these eight packing materials, Synergi Fusion-RP, Synergi Hydro-RP, Synergi Polar-RP, and Zorbax 300 SB-C18, are various reversed-phase materials. Reversed-phase retention and separations are based upon analyte hydrophobicity, and the mobile-phase systems (Table 3) used in conjunction with the above materials are consistent with those typically used for reversedphase separations. In addition, our goal in the selection of 10 mM ammonium acetate (pH 5.3) as the mobile-phase modifier was to facilitate the use of the same mobile-phase composition and thus achieve identical chromatography, under both positive and negative ionization conditions.23,37 Because many compounds present in metabolite extracts are small, polar molecules (e.g., L-carnitine, thiamine, and taurine), they are only weakly retained on most reversed-phase materials. Our goal was to choose a material that provides balanced retention for both polar and hydrophobic metabolites. Table 5 shows chromatographic metrics calculated for 26 standards consistently identified during the evaluation of the Synergi and Zorbax reversed-phase materials analyzed in positive ESI; the remaining standards are more easily detected in negative ESI. In general, the Synergi materials showed increased retention of the standards with comparable peak width as compared to the Zorbax material (Figure 1). This is likely due (34) Gao, H.; Shen, Y.; Veenstra, T. D.; Harkewicz, R.; Anderson, G. A.; Bruce, J. E.; Pasa-Tolic, L.; Smith, R. D. J. Microcolumn Sep. 2000, 12, 383-390. (35) Shen, Y.; Zhao, R.; Berger, S. J.; Anderson, G. A.; Rodriguez, N.; Smith, R. D. Anal. Chem. 2002, 74, 4235-4249. (36) Shen, Y.; Moore, R. J.; Zhao, R.; Blonder, J.; Auberry, D. L.; Masselon, C.; Pasˇa-Tolic´, L.; Hixson, K. K.; Auberry, K. J.; Smith, R. D. Anal. Chem. 2003, 75, 3596-3605. (37) Tolstikov, V. V.; Fiehn, O. Anal. Biochem. 2002, 301, 298-307.


6085

Table 5. Chromatographic Metrics Determined for Zorbax and Synergi-RP Columns, Based on Detected Metabolite Standardsa Zorbax logD threonine CTP glutathione (oxidized) ADP ATP glutathione (reduced) L-carnitine glucosamine creatinine/cytosine

-3.7 -11.0 -4.1 -7.3 -9.5 -2.9 -3.9 -4.8 -1.8

taurine pantothenic acid pyridoxine purine coenzyme A acetyl CoA cysteine cAMP adenosine FAD 2′-deoxyadenosine tryptophan riboflavin prostaglandin-E2 6-keto-prostaglandin-F1a thromboxane-B2

m/z tR (M+H)b (min) fwhm Af

Fusion Nd

tR (min) fwhm

Af

Hydro N

tR (min) fwhm Af

Polar N

tR (min) fwhm Af

N

4.2 4.2 4.2 ndc nd 4.3 4.4 4.4 5.5

0.67 0.35 0.27 nd nd 0.22 0.72 0.64 0.76

3.2 1.1 1.1 nd nd 1.2 3.4 2.2 0.8

216 817 1353 nd nd 2146 205 259 291

4.5 4.4 4.4 4.8 4.8 4.8 4.9 4.9 7.7

0.80 0.77 0.64 0.19 0.45 0.26 0.62 0.50 0.54

2.5 0.97 0.6 1.2 0.85 1.4 1.7 1.1 0.5

178 184 267 3492 622 1888 340 541 1132

4.5 4.2 4.2 4.2 4.1 4.0 4.5 4.5 7.4

0.86 0.50 0.47 0.34 0.45 0.54 1.3 0.75 0.68

1.7 0.9 0.9 1.0 1.1 1.1 14 1.8 1.2

149 383 438 849 453 301 67 197 654

4.9 4.3 4.4 4.6 4.5 4.1 5.5 5.6 8.6

0.83 0.59 0.55 0.61 0.91 0.59 0.84 0.65 1.9

2.6 1.2 1.8 2.0 1.6 6.7 1.8 2.5 1.9

193 298 356 315 137 271 236 413 118

-5 -1.9 -1.4 -0.4 -9.8 -9.7 -2.3 -3.3 -1 -8 -0.5 -1.5 -2.4 1.1 0.1

120.0 483.9 613.1 428.0 508.0 308.0 162 180.0 114.0/ 112.0 126.0 220.0 170.0 121.0 768.1 810.1 122.0 330.0 268.1 786.1 252.1 205.0 377.1 353.2 393.2

6.0 6.0 7.6 8.8 11.6 12.5 11.0 12.3 12.7 13.6 13.0 12.4 15.8 18.4 19.9

1.2 1.5 1.1 1.1 0.20 0.19 2.7 0.18 0.18 0.20 0.29 0.27 0.16 0.29 0.51

8.7 0.5 1.8 2.4 2.4 2.2 13 1.2 2.1 1.3 3.4 1.1 0.9 2.3 1.9

126 92 246 353 18669 24017 89 25869 27492 25768 11116 11628 53750 22254 8392

nd 7.8 12.1 13.6 13.4 14.3 14.6 14.8 15.5 15.7 15.8 16.5 18.5 20.9 22.3

nd 0.32 2.2 0.67 0.19 0.22 0.71 0.13 0.18 0.16 0.23 0.12 0.11 0.32 0.35

nd 1.7 1.6 2.2 1.8 1.8 6.5 1.2 1.3 0.9 1.9 0.6 1.2 1.0 1.3

nd 3275 163 2289 27721 23341 2339 71998 40974 53206 26243 104107 156361 23655 22530

nd 7.4 12.0 12.4 nd 12.9 13.5 13.8 14.5 14.7 14.8 15.6 17.6 19.6 21.2

nd 0.52 1.8 0.70 nd 0.12 0.43 0.11 0.08 0.15 0.20 0.13 0.11 0.41 0.35

nd 2.8 1.7 2.5 nd 2.5 3.8 1.1 1.6 1.3 4.2 0.9 0.9 2.8 1.7

nd 1122 238 1747 nd 64220 5485 86563 182249 53134 30173 80186 141180 12686 20383

nd 5.4 11.6 14.6 nd 12.3 17.0 14.3 16.1 16.5 17.0 16.8 20.6 21.7 23.5

nd 0.73 2.3 1.0 nd 2.5 0.29 0.20 0.16 0.17 0.17 0.19 0.11 0.48 0.33

nd 1.6 8.1 4.0 nd 1.1 5.0 1.7 2.3 0.9 1.4 1.8 1.1 1.6 2.0

nd 307 139 1186 nd 141 19060 28164 56025 51873 55140 43313 193352 11312 27999

1.4

393.2

20.7

0.60

0.8 6569

23.3

0.22

0.2

62247

22.3

0.23

2.7 51892

24.5

0.20

1.4 83067

a t , retention time; fwhm, full width at half-maximum; A , asymmetry factor; N, number of theoretical plates. Standards are listed in order of R f elution on the Zorbax column. b L-Carnitine carries a formal charge and is detected as the M+ species. 6-Keto-prostaglandin-F1R and thromboxanec B2 were detected as sodiated adducts. nd indicates the standard was not detected due to ionization suppression. d Theoretical plates were calculated by assuming isocratic election as an indication of column performance.

to the combination of a smaller pore size (80 vs 300 Å), a larger surface area (475 vs 45 m2/g), and the surface properties of the Synergi materials. Metabolites are small molecules with high coefficients of diffusion. The larger surface area may provide higher absorption and partitioning of the analytes to the stationary phase. In addition, Synergi Fusion-RP contains proprietary embedded polar groups besides the hydrophobic C18 ligand, in order to provide improved retention and peak shape for polar analytes. Similarly, Synergi Hydro-RP is a C18-bonded phase end-capped with a proprietary polar group to provide improved retention of both polar and hydrophobic compounds. In contrast, Synergi Polar-RP is an ether-linked phenyl phase with hydrophilic endcapping to maximize retention and selectivity for polar and aromatic analytes. Careful comparisons of the separations were made using the same mobile-phase systems with the three Synergi materials, and it was determined that the Synergi Fusion-RP column (Figure 1) provided a higher number of theoretical plates, N (median of all standards detected for each column), compared to both Synergi Hydro-RP and Synergi Polar-RP, as well as Zorbax (Table 5). Similarly, the Synergi Fusion-RP provided an asymmetry factor, Af, of 1.3 versus 1.7, 1.8, and 1.9 (median of all standards detected for each column) for Synergi Hydro-RP, Synergi Polar-RP, and Zorbax, respectively, indicating better peak shape for this column. In terms of retention time reproducibility, the Zorbax, Synergi Fusion-RP, Synergi HydroRP, and Synergi Polar-RP columns provided median relative standard deviations of 0.32, 0.45, 0.63, and 1.00%, respectively, based on the retention times of the 26 compounds shown in 6086 Analytical Chemistry, Vol. 79, No. 16, August 15, 2007

Table 5 during replicate analysis (n ) 3) of the metabolite standard. For the Synergi Polar-RP column, a continuous rise in the baseline was observed when the organic modifier (acetonitrile) was over 70%. Two mixed-mode materials (Primesep B2 and Primesep 100) that include both reversed-phase and either anion- or cationexchange properties were also evaluated. Unfortunately, a relatively high MS background was observed for both materials when a blank gradient was run, as compared to the other materials evaluated. In addition, ion suppression effects were observed when the standard metabolite mixture was run. One hydrophilic interaction chromatography (HILIC) material (polyhydroxyethyl aspartamide) was tested using two mobilephase compositions. HILIC, also called aqueous normal-phase LC, was developed as a solution to the problem of poor retention of polar analytes during reversed-phase LC.38 The improved retention of polar analytes on HILIC materials is due primarily to their partition in to and out of an adsorbed water layer on the stationaryphase surface. As expected, this HILIC material provided reversed elution order for the components in the standard mixture. In other words, hydrophobic compounds eluted from the column earlier than polar compounds; thus, information complementary to a reversed-phase analysis of the same sample might be captured from HILIC separations. However, this HILIC material also presented with a relatively consistent and high MS background, as compared to other materials evaluated. This is likely due to (38) Alpert, A. J. J. Chromatogr. 1990, 499, 177-196.

Figure 1. Representative base peak chromatograms of the metabolite standard mixture separated on (a) Zorbax, (b) Synergi Fusion-RP, (c) Synergi Hydro-RP, and (d) Synergi Polar-RP columns (75 µm i.d. × 32 cm) using mobile phase V (see Table 4 for the gradient condition). Twenty-six standards from the 45-component standard mix were detected in positive-ion ESI and are listed in order of elution on the Zorbax column: 1, threonine; 2, CTP; 3, glutathione (oxidized); 4, ADP; 5, ATP; 6, glutathione (reduced); 7, L-carnitine; 8, glucosamine; 9, creatinine; 10, cytosine; 11, taurine; 12, pantothenic acid; 13, pyridoxine; 14, purine, 15, cysteine, 16, coenzyme A; 17, cAMP; 18, tryptophan; 19, acetyl CoA; 20, adenosine; 21, 2′-deoxyadenosine; 22, FAD; 23, riboflavin; 24, prostaglandin-E2; 25, 6-keto-prostaglandin-F1R; 26, thromboxane-B2.

the noncovalent bonding of the polyhydroxyethyl aspartamide onto the silica gel; the polymer can be washed off the silica gel and detected by ESI-MS under our operating conditions. This negates its utility for our applications. Last, a macrocyclic glycopeptide chiral stationary phase was evaluated in reversed-phase and polar organic modes without success in resolving most of the components in the metabolite standard. Of the nine materials initially evaluated, the Synergi FusionRP material provided the best separation (in terms of peak width, Af, N, resolution, and retention of polar analytes), of the metabolite standards (Table 5) under our operating conditions. After determining the optimum stationary-phase (Fusion-RP) and mobile-phase (V, Table 3) combination of those tested, a manually operated high-pressure (up to 10 000 psi) LC system was used to separate the metabolite standard, as well as complex metabolite samples. The advantages of this LC system include the following: (1) a higher pressure limit, which enables the use of longer capillary columns or smaller particles to provide higher chromatographic resolution; (2) support for the use of smaller inner diameter columns for increased sensitivity; (3) reduced solvent consumption and less waste generation due to lower split flow rate, as compared to some commercial capillary LC systems; and (4) more flexibility in improving throughput via construction of a multicolumn system. Various metabolite extracts were subsequently analyzed using both a commercial LC system and a home-built, high-pressure, single-column LC system. In general, our results indicate that the constant-pressure, exponential gradient is as effective as the

constant flow rate, linear gradient provided by the commercial LC for the separation of identical metabolite samples (results not shown). In addition, while each LC system provides a different gradient shape (see Figure 3), it has been demonstrated that chromatographic data from both systems can be effectively compared using a novel elution time warping algorithm.33 For the single-column, high-pressure LC system, column equilibration requires ∼100 min for a 75 µm i.d. × 60 cm column at a flow rate of ∼0.3 µL/min; therefore, one analysis duty cycle requires ∼250 min (the separation requires 150 min). For large numbers of samples, there is a great need to decrease the duty cycle time in order to achieve higher throughput. There are several ways to increase throughput while maintaining separation efficiency. For example, a shorter column packed with smaller particles can be used in conjunction with ultrahigh pressure (15 000 psi) and high temperature to achieve high peak capacity.39 In this study, an automated dual-column system was constructed as a solution. By using a dual-column approach, one column is equilibrating while the second column is subjected to gradient elution. Since the chromatographic parameters used in the dual-column system are the same as those of the manual high-pressure system, similar separation performance was expected. Comparison of Commercial and Home-Built Automated Dual-Column LC Systems. The developed LC separation method was applied to the analysis of Cyanothece sp. ATCC 51142 metabolite extracts. In order to test the effectiveness and the shortterm reproducibility of the commercial and automated dual-column (39) Plumb, R. S.; Rainville, P.; Smith, B. W.; Johnson, K. A.; Castro-Perez, J.; Wilson, I. D.; Nicholson, J. K. Anal. Chem. 2006, 78, 7278-7283.


6087

Figure 2. Base peak chromatograms of Cyanothece sp. ATCC 51142 metabolite extracts. (a) Automated high-pressure LC system; (b) Agilent 1100 nano LC system. LTQ-orbitrap MS was used for detection.

LC systems, both were coupled with a LTQ-orbitrap and utilized to separate identical Cyanothece sp. ATCC 51142 metabolite samples. First, replicate analyses were made on a 150 µm i.d. × 60 cm column using the commercial LC system with a flow rate of 1 µL/min. The gradient conditions are identical to those listed in Table 4 for the same dimension column. Next, five injections of an identical Cyanothece metabolite extract were made onto each column (150 µm i.d. × 60 cm) of the in-house-constructed, dualcolumn, high-pressure LC system with a constant pressure of 6000 psi. The separation conditions are described in the Experimental Section. Figure 2 shows examples of chromatograms obtained on the two LC systems. It is apparent that under our operating conditions most compounds elute more slowly (about 30-40-min delay) using the commercial LC system running a constant flow rate, linear gradient than on the automated high-pressure LC system running a constant-pressure, exponential gradient. Two factors contribute to this: (1) higher flow rates provided by the separation under constant pressure, particularly as the viscosity of the mobile phase decreases with increasing concentration of mobile phase B and (2) higher percentage of mobile phase B during the first half of the separation. See Figure 3 for plots of the linear gradient and predicted exponential gradient. From the plots, it is apparent that the percentage change of mobile phase B during the exponential gradient is larger than that of the linear gradient for the first 50 min of each separation and that the overall percentage of mobile phase B is higher during the exponential gradient for the first 95 min. In addition, the gradient reaches the column faster in the dual-column system due to a slightly higher flow rate (1.2 vs 1 µL/min). This explains the faster elution of the less hydrophobic compounds on the dual-column LC system. Also, a more uniform peak distribution (Figure 2) was 6088 Analytical Chemistry, Vol. 79, No. 16, August 15, 2007

observed on the dual-column LC system, which effectively minimized coelution of peaks and enabled detection of more analytes. Despite the differences in gradient shape inherent to each LC system, it has been demonstrated that chromatographic data from both systems can be effectively compared using a novel elution time warping algorithm.33 The peak capacity for the separation obtained by constant pressure and exponential gradient was calculated as ∼240 versus ∼168 for the constant flow rate and linear gradient separation. Table 7 shows chromatographic metrics calculated for 21 metabolite features (12 identified) detected in a representative data set from each LC system. The dual-column capillary LC system provided a higher N (median of all 21 features detected for each column) of 103 498 versus 99 761 for the commercial system, as well as a slightly lower Af of 1.1 versus 1.2 (median of all 21 features detected for each column). In addition, the dual-column capillary LC system offered narrower peaks, with a fwhm of 0.33 (median of all 21 features detected for each column) versus 0.96 for the commercial system. Interestingly, a lower number of common features were observed across both columns of the dualcolumn system versus each of the columns individually, indicating that individual column effects must be considered when conducting metabolic profiling studies utilizing multiple column LC systems. Water blanks injected between Cyanothece samples revealed negligible carryover for both systems. Approximately 350 features were identified in common across both columns (n ) 9) of the dual-column system and the commercial system (n ) 5). This number corresponds to roughly 45% of the features reproducibly detected on both columns of the dual-column system and 55% of the features reproducibly detected using the commercial system. Manual inspection of the chromatograms revealed that

Table 6. Features Observed by LC/LTQ-Orbitrap MS for Cyanothece sp. ATCC 51142 LC system commercial dual-column, column 1 dual-column, column 2 dual-column, columns 1 and 2 dual-column (columns 1 and 2) and commercial

number of features observed among replicates 1354 ( 41; 646 in common (n ) 5) 1839 ( 95; 963 in common (n ) 4)a 1476 ( 47; 888 in common (n ) 5) 784 in common (n ) 9)a 355 in common (n ) 14)a

a Five replicate analyses were made on column 1 of the dual-column LC system, but one data set was excluded from the analysis due to the presence of air bubbles during injection.

Figure 3. Gradient profile comparison. The dotted line and the solid line represent the exponential gradient provided by the constantpressure LC system and the linear gradient provided by the constant flow rate Agilent LC system, respectively. The arrow indicates the end of the exponential gradient in this study. See Experimental Section for the mobile-phase gradient conditions.

ionization suppression of lower abundance features was a factor and was observed when either LC system was used; although the constant-pressure separation overall was chromatographically more efficient than the constant flow rate separation (Table 7), various low-abundance features were more efficiently ionized in local regions of both separations. The reproducibility of both LC systems coupled with LTQorbitrap MS detection was evaluated for metabolite extracts of Cyanothece sp. ATCC 51142 using the MultiAlign software. Table 6 lists the number of features (defined by LC elution time and monoisotopic mass) reproducibly observed (n ) 5) for Cyanothece sp. ATCC 51142 by the two different LC systems coupled with LTQ-orbitrap MS. At least 242 additional features were detected on each column in the constant-pressure separations versus the constant flow rate separations. Further, an additional 138 features were reproducibly detected between both columns of the dualcolumn system, as compared to the commercial LC system. The difference in the number of features observed between the two LC systems is likely due to the improved chromatographic efficiency obtained with the dual-column system versus the commercial system under our operating conditions. Figure 4 illustrates the agreement of intensities for detected features of eight data sets relative to the baseline data set after chromato-

graphic alignment and intensity normalization for samples run on both columns of the dual-column system. The cluster intensity and intensity ratio histogram plots demonstrate the high reproducibility of these nine separations analyzed across two different columns. In general, the median CVs for all features reproducibly detected across all samples for columns 1 (963 features) and 2 (888 features) of the dual-column system were both 16%. When comparing those features reproducibly detected across all samples for both columns combined (784 features), the median CV was 17%. Similarly, the median CV for those features reproducibly detected across all samples for the commercial LC system (646 features) was 19%. Interestingly, while lowering the deisotoping signal-to-noise threshold from 65 to 7 increased the number of features reproducibly detected using both LC systems (∼2700 features for the commercial system vs ∼4000 features for each column of the home-built system), an increase in median CVs to ∼25% was observed for both LC systems. This was mainly due to an increase in the number of features derived from chemical noise during electrospray, which resulted in an increase in the width of the intensity distribution for all detected features in a given data set. While the higher deisotoping signal-to-noise threshold results in a much lower number of detected features, it also likely reduces the number of false metabolite feature identifications. Based on parallel analyses of Cyanothece extracts and sample blanks using a LTQ-FT MS, the contribution of sample carryover and chemical noise features to the total feature count was estimated at 6 after downstream data processing. In contrast, the 150 µm i.d. × 60 cm packed capillary column used in our study provided an N of ∼103 500 at a linear velocity of 1.1 mm/s. Also, well over 1000 metabolite features were reproducibly detected (Table 6) on each column of the dual-column system in a 150-min separation with a S/N of 65 after downstream data processing. This demonstrates the superior performance of our method over that reported by Tolstikov et al.; however, the numbers of detected metabolite features may vary based on the organism analyzed, the chosen metabolite extraction protocol, and the flow rate utilized for capillary LC separations. Alternatively, the use of ultraperformance liquid chromatography (UPLC)40-42 has emerged as a powerful separation technique, exploiting the use of sub-2µm particles and higher operating LC pressures for significantly improved chromatographic resolution at increased speed of analysis. Recently, Plumb et al.39 combined UPLC (1.7-µm particles and operating pressure of 11 000 psi) with elevated temperatures (90 °C) to achieve a peak capacity of ∼1000 in a 1-h separation of rat urine. However, the use of elevated temperatures resulted in an increase in the optimal linear velocity from 0.6 to 1.1 mL/min for the column used in this study. Thus, while the method results in extremely efficient separations (peak widths of 3-4 s and high peak capacities), the high flow rates employed (0.8 mL/min) will (40) Wilson, I. D.; Nicholson, J. K.; Castro-Perez, J.; Granger, J. H.; Johnson, K. A.; Smith, B. W.; Plumb, R. S. J. Proteome Res. 2005, 4, 591-598. (41) Plumb, R.; Castro-Perez, J.; Granger, J.; Beattie, I.; Joncour, K.; Wright, A. Rapid Commun. Mass Spectrom. 2004, 18, 2331-2337. (42) Plumb, R. S.; Granger, J. H.; Stumpf, C. L.; Johnson, K. A.; Smith, B. W.; Gaulitz, S.; Wilson, I. D.; Castro-Perez, J. Analyst 2005, 130, 844-849.

Figure 4. Reproducibility of the Cyanothece metabolite extract separations by the automated dual-column LC system coupled with LTQorbitrap MS detection. Five replicates of the same sample were analyzed on both columns, and nine data sets were used for comparative analyses (column 1, Rep A was utilized as a baseline for alignment and normalization purposes; column 1, Rep D was excluded from the data analysis due to the presence of air bubbles during injection). The upper panel illustrates the agreement between intensity measurements for individual features in the aligned and baseline data sets. The lower panel illustrates agreement between intensity measurements in the aligned and baseline data sets, in terms of an intensity ratio histogram. Reproduced from Biomarkers Med. 2007, 1, 159-185. Table 8. Reproducibility of Dual-Column LC System during Batch Analysis replicate set

common features

median CV

days between rep 1 and 2

days between rep 2 and 3

injections between rep 1 and 2

injections between rep 2 and 3

1 2 3 4 5 6 7 8 9 10 11 12

988 752 760 594 679 820 807 719 737 837 753 849

14.6 32.0 33.9 31.3 35.0 24.9 29.2 34.1 32.5 28.0 29.4 25.7

14.4 12.4 12.7 2.6 12.0 4.7 19.0 15.0 13.7 15.2 10.0 8.9

9.4 2.2 10.2 8.2 3.7 6.7 1.5 7.7 8.7 6.0 8.2 2.0

29 35 22 8 32 16 44 31 26 32 27 30

32 7 35 28 13 22 4 25 29 19 27 6

result in reduced MS sensitivity due to possible ion suppression by components of the mobile phase, as well as increased MS background due to solvent ions. Metabolite Identification. In a single LC-MS analysis of a metabolite extract, several thousand features may be detected, depending on the ion intensity or signal-to-noise thresholds in place for downstream data processing. The real challenge is to identify each one of these in a high-throughput manner to obtain relevant biological information from comparative samples. In our

study, metabolites were tentatively identified based on accurate mass measurements via LTQ-orbitrap MS, comparison of theoretical to observed isotopic distributions, targeted MS/MS experiments, or comparison to authentic standards (e.g., adenosine, flavin adenine dinucleotide, riboflavin, and tryptophan) as applicable. For Cyanothece samples analyzed in our study, 784 features were reproducibly observed on both columns of the dualcolumn LC system in a short-term reproducibility experiment. Among those large numbers of features, only 12 (1.5%) were Analytical Chemistry, Vol. 79, No. 16, August 15, 2007

6091

Table 9. Metabolites Tentatively Identified in Cyanothece Metabolite Extracts

metabolite adenosine AMP cytosine flavin adenine dinucleotide guanosine leucine/isoleucine nicotinamide adenine dinucleotide (oxidized) phenylalanine riboflavin tryptophan tyrosine valine

observed m/z

predicted m/z

mass error (ppm)

268.1047 348.0704 112.0505 786.1659 364.0659 132.1019 664.1176

268.1045 348.0709 112.0511 786.1649 364.0658 132.1024 664.1169

-0.7 1.4 5.2 -1.3 -0.3 3.8 -1.1

166.0864 377.1461 205.0978 182.0815 118.0863

166.0868 377.1476 205.0977 182.0817 118.0868

2.4 4.0 -0.5 1.1 4.2

identified (Table 9) in a 150-min separation. This illustrates both the strength and weakness of global, untargeted LC-MS-based metabolic profiling and metabolomic studies, i.e., high-efficiency separations coupled with sensitive ESI-MS enables deep coverage of the metabolome and the detection of many metabolite features. However, the chemical identities of these features may not be easily elucidated, particularly if they are novel and published work on the compound class is unavailable or a priori information is lacking otherwise. In addition, high-mass measurement accuracy data as provided by TOF and FTICR mass spectrometers is generally not sufficient for unequivocally determining the empirical formula of a metabolite feature. Kind and Fiehn recently performed a rigorous in silico evaluation of the level of mass accuracy required for unique elemental composition prediction for detected metabolites, enforcing strict chemical constraints in the determination of all chemically possible empirical formulas between a molecular mass of 20 and 500 Da.43 Their calculations indicate that the upper mass limit for determining the unique elemental composition of a metabolite with 1-3 ppm MMA is only 126.0000 Da. Importantly, the number of putative empirical formulas increases rapidly above this mass value, and they proposed that additional constraints are needed to limit the number of unique formulas that may correspond to a given mass measurement.43 They convincingly illustrated the utility of incorporating isotopic distribution information as an orthogonal filter to reduce the number of candidate empirical formulas. The final set of candidate formulas may then be queried against publicly available metabolite databases for possible matches. The success of these queries depends significantly on the maturity of the given database, in terms of the number of metabolite entries available for matching to experimentally derived empirical formulas. Alternatively, targeted MS/MS studies may be performed to provide structural information for metabolite features. However, not every compound studied in targeted MS/MS experiments will provide a rich and informative MS/MS spectrum amenable to structural elucidation. Thus, the increasing sensitivity of today’s mass spectrometers allows for deeper delving into the metabolome during global, untargeted analyses but also results in a higher percentage of features remaining structurally unidentified. Complementary approaches such as NMR should also be employed to facilitate the structural elucidation of detected metabolite features. (43) Kind, T.; Fiehn, O. BMC Bioinf. 2006, 7, 1-10.

6092


Negative ESI Analysis of the Metabolite Standard. Our goal in the selection of 10 mM ammonium acetate (pH 5.3) as the mobile-phase modifier was to facilitate the use of the same mobilephase composition and thus achieve identical chromatography, under both positive and negative ionization conditions.23,37 The advantage of this approach is that many metabolites can be detected in both positive- and negative-ESI, which provides complementary information for the same metabolite, as well as increased confidence during structural elucidation. LC-MS analyses of the metabolite standard in negative ionization mode were initially performed without sheath gas. Although most compounds in the standard can be detected in negative ionization mode without changing mobile-phase composition, unstable electrospray was observed through a camera during LC separations in the 300 nL/min to 1 µL/min flow rate regime, particularly during 30-60 min of the gradient separation. In order to obtain a stable electrospray under negative ionization mode, sulfur hexafluoride was applied as a sheath gas using a device similar to that reported by Gale and Smith.44 Wampler and colleagues have previously demonstrated that SF6 effectively suppresses the discharge effect during negative-ESI analyses of nucleotides,45 due to its efficient electron scavenging properties. However, during a 70-min separation of the metabolite standard, the most intense peak observed was m/z ) 126.95, corresponding to SF5-. This result is in agreement with previous mass spectrometric studies of negative ion formation in an SF6 corona.46,47 In general, several standards such as cAMP and FAD were detected; however, the intensity for these ions was very low. The severe matrix effect observed under our conditions makes the use of SF6 sheath gas impractical. More work is in progress to achieve higher quality negative ionization spectra throughout the LC separation. CONCLUSIONS An exponential gradient, reversed-phase capillary LC method coupled on-line to ESI-MS has been developed for metabolite profiling studies with various biological samples. Nine stationary phases have been evaluated for separation of metabolite samples, and Synergi Fusion-RP was found to provide the best separation performance in terms of peak shapes, resolution, and efficiency of the materials evaluated, under our operating conditions. In general, a material with small pore size (e.g., 400 m2/g) provides much improved retention of small, polar analytes; the peak shape may be further improved by imbedding in the C18 chain or end-capping residual silanols with a functional group designed to interact with polar analytes. Meanwhile, the optimum mobile phase and gradient were determined experimentally, and it was found that the best mobilephase compositions of those examined were as follows: (A) 10 mM ammonium acetate in water, pH 5.3 (adjusted with acetic acid) and (B) 10 mM ammonium acetate in 90% acetonitrile/10% water. Again, while other mobile-phase systems may further improve the separation of metabolite extracts, our choice of mobile-phase system allows for detection in both positive- and negative-ESI (44) Gale, D. C.; Smith, R. D. Rapid Commun. Mass Spectrom. 1993, 7, 10171021. (45) Wampler, F. M.; Blades, A. T.; Kebarle, P. J. Am. Soc. Mass Spectrom. 1993, 4, 289-295. (46) Sauers, I.; Harman, G. J. Phys. D: Appl. Phys. 1992, 25, 761-773. (47) Sauers, I.; Harman, G. J. Phys. D: Appl. Phys. 1992, 25, 774-782.

modes without altering the chromatographic separation. The exponential gradient offered better separation efficiency for the tested standard mixture and metabolite samples than the simple linear gradient. The automated, dual-column high-pressure LC system was successfully used for separation of metabolite samples and improved the analysis throughput. The developed method can be effectively used for the separation and identification of individual molecular species in biological samples. ACKNOWLEDGMENT We thank Allsep, Astec, and PolyLC for their kind donation of the stationary-phase packing materials. In addition, we thank Dr. Himadri Pakrasi for providing the Cyanothece samples. This research was performed as part of an EMSL Scientific Grand Challenge project at the W. R. Wiley Environmental Molecular Sciences Laboratory, a national scientific user facility located at Pacific Northwest National Laboratory and sponsored by the U.S. Department of Energy Office of Biological and Environmental Research program. Additional support for portions of this work

was provided by the NIH National Center for Research Resources (RR18522). NOTE ADDED AFTER ASAP PUBLICATION This article was released ASAP on July 18, 2007, with multiple errors in Table 3. The correct version was posted on July 20, 2007. SUPPORTING INFORMATION AVAILABLE Extracted ion chromatograms for the 26 components of the metabolite standard mixture that were detected in positive-ESI during evaluation of Zorbax, Synergi Fusion-RP, Synergi HydroRP, and Synergi Polar-RP. Extracted ion chromatograms for the 21 metabolite features detected in positive ESI during positiveESI analysis of Cyanothece metabolite extract using dual-column and commercial LC systems. This material is available free of charge via the Internet at http://pubs.acs.org. Received for review January 12, 2007. Accepted May 15, 2007. AC070080Q


6093

Capillary LC Coupled with High-Mass Measurement Accuracy Mass

Recommend Documents