Multiorigination of Chromatographic Peaks in Derivatized GC/MS Metabolomics: A Confounder That Influences Metabolic Pathway Interpretation Fengguo Xu,† Li Zou,†,‡ and Choon Nam Ong*,†,‡ Department of Epidemiology and Public Health, Yong Loo Lin School of Medicine, National University of Singapore, 16 Medical Drive, Singapore 117600, and Singapore-MIT Alliance for Research and Technology, 3 Science Drive 2, Singapore 117543 Received August 18, 2009
Abstract: GC/MS is one of the most commonly used analytical methods in metabolomic research. The originations of chromatographic peaks are crucial, especially for metabolic pathway interpretation. However, until now, this critical issue has not been discussed or investigated. This study aims to demonstrate one of the major pitfalls of derivatized GC/MS and their possible implications in metabolomic studies. In this investigation, a spectrum of structural and biological related endogenous species including phosphocholines (PC), lysophosphatidylcholines (LPC), diacylglycerol (DAG) and fatty acids were used as examples to illustrate the multiorigination and multipeak phenomena of derivatized GC/MS. The implications of these phenomena on metabolic pathway interpretations were also discussed. Our findings revealed that peaks of glycerol, phosphoric acid, fatty acids and some lipids fractions in derivatized GC/MS chromatogram of human blood were the result of contributions of structurally related compounds, in both free and conjugated form. It is believed that these phenomena could have been due to decomposition occurred during derivatization procedure and/or during GC analysis where the temperatures of certain GC parts were too high. To avoid misleading results and wrong conclusions in metabolomic investigations, combined use of GC/MS with other analytical instruments, such as NMR and/or LC/MS, should be considered. Keywords: derivatized GC/MS • LC/MS • metabolomics • multipeak phenomena • multiorigination phenomena • phospholipids
Introduction Metabolomics is the comprehensive study of the metabolome, the repertoire of biochemicals (or small molecules) present in cells, tissue, and body fluids, which was commonly * Correspondence to: C. N. Ong, Department of Epidemiology and Public Health, Yong Loo Lin School of Medicine, National University of Singapore, 16 Medical Drive, Singapore 117600. DID: 65-65164982. E-mail: Email:
[email protected]. † National University of Singapore. ‡ Singapore-MIT Alliance for Research and Technology. 10.1021/pr900738b CCC: $40.75
2009 American Chemical Society
defined as the “the quantitative measurement of the dynamic multiparametric response of a living system to pathophysiological stimuli or genetic manipulations”.1–4 In practice, the term “metabolomics” is often used interchangeable to “metabonomics” by scientists.3,4 Together with genomics, transcriptomics and proteomics,2,3,5,6 metabolomics is involved within the systems biology framework and is ever offering fresh insight into the life science fields such as disease diagnostic,7–12 drug development13–17 nutrition assessment18–20 and environmental exposure evaluation,21,22 and so forth. Nuclear magnetic resonance (NMR), gas chromatography/ mass spectrometry (GC/MS) and liquid chromatography/mass spectrometry (LC/MS) are the three most frequently used analytical techniques for metabolomic investigations, each with its own advantage and disadvantage23–25 for metabolomic studies. Metabolomics using 1H NMR spectrometry has evolved from early investigations of biofluid composition dating back to the 1980s. The characters of nondestructive, high throughput and little or no sample preparation requirement make NMR win the favor of many scientists for metabonomic studies.1,3,4,13,17,25 Recently, the development of high-resolution magic-angle spinning spectrometry (MAS) technique has extended its application to metabonomic profiling of intact tissues,4,25,26 but NMR has a relative low sensitivity and selectivity compared with mass spectrometry (MS). GC/MS2–6 and more recently GC×GC/MS27,28 provide an excellent system for performing global metabolic profiling based on its high sensitivity, peak resolution and reproducibility. Availability of GC/MS electron impact (EI) spectral library further facilitates the identification of diagnostic biomarkers and aids the subsequent mechanistic elucidation of the biological or pathological variations.29–34 However, a major prerequisite for GC/MS analysis is that the compound should be volatile and thermally stable. As most of the endogenous metabolites are polar and nonvolatile in nature, chemical derivatization is usually performed before GC/MS analysis. Silylation using BSTFA or MSTFA are conducted predominantly in metabolic profiling, especially for biofluid and tissue sample metabolomic investigations. To reduce or eliminate the conversion reactions during silylation, methoxamine hydrochloride may be used first for oximation reaction prior to silylation reaction.4,22–24,30–34 However, the introduction of another step usually leads to a more complex chromatogram with high Journal of Proteome Research 2009, 8, 5657–5665 5657 Published on Web 10/19/2009
technical notes background noise. It has been noted that silylation can cause conversion reactions; for example, arginine is converted into ornithine by reaction with BSTFA or MSTFA.35 Till recently, only few papers have been published regarding standardization of GC/MS method for metabolomic study, with main focuses on aspects of sample extraction, optimization of derivatization step and method validation.29–34 LC/MS is another MS based hyphenated techniques in metabolomics, which differs from GC/MS in distinct ways such as lower analysis temperature, no sample volatility requirement, no derivatization requirement.22–25,36–39 The bulk applications were performed using reversed-phase chromatography (RP), a mature technique for separation of nonpolar metabolites. The introduction of hydrophilic interaction chromatography (HILIC) extended its coverage to polar compounds.40 Besides, the applications of capillary and ultra performance liquid chromatography (UPLC) in metaboimics have improved the analysis efficiency dramatically.8,41,42 As no single methodology can detect the complete metabolome in one procedure, in order to acquire wider sample coverage with more information using the limited samples, these three analytical techniques are often in combination,26,43–45 which might also be considered as a strategy for cross validation to prevent wrong conclusions. Although these three analytical methods have been widely used for metabolomic investigations, there are still many puzzles yet to be resolved especially for derivatized GC/MS. In our recent human blood metabolic profiling investigation using derivatized GC/MS, we noted that multipeak as well as multiorigination was rather common phenomena when using PC and LPC reference standards. These observations have not been reported earlier and we realized that they could lead to data misinterpretation, and have important implications in metabolomic pathway interpretation. To confirm these observations, several biological and structurally related endogenous species including PC, LPC, DAG and fatty acids were selected as examples to explore the above-mentioned multiorigination phenomena and their potential influences on metabolic pathway interpretations. At the same time, LC/MS was used as a reference method to demonstrate the exits of PC, LPC, DAG and fatty acids species in human blood.
Materials and Methods Chemicals and Standards. PC (16:0/16:0), LPC (16:0/0:0), DAG (18:1/18:1/0:0), LPC (18:1/0:0), hexadecanoic acid (C16: 0), c-9-hexadecenoic acid (C16:1), octadecanoic acid (C18:0), c-9-octadecenoic acid (C18:1), c-9,12-octadecadienoic acid (C18:2), dodecanoic acid (C12:0), and tetradecanoic acid (C14: 0) reference standards were purchased from Sigma Chemical Co. Glycerol was purchased from Asia Pacific Specialty Chemicals Limited (Auckland, Zealand). HPLC grade methanol was purchased from APS (NSW, Australia). Formic acid was analytical grade from Merck (Darmstadt, Germany). Ultrapure water was prepared from a Mili-Q system (Milipore, Milford, MA). All other reagents and solvents were of commercially available analytical grades. Blood Sample Preparation Procedures. Pooled venous human whole blood (5 mL) from volunteers was used in the present study. A total of 0.35 mL of methanol was added into the blood (50 µL) and vortexed for 2 min. After 20 min of ultrasonic extraction in ice water, the mixture was vortexed for another 2 min. The samples were then centrifuged for 10 min (13 200 rpm). The supernatant was divided into two parts: one 5658
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Xu et al. 100 µL for LC/MS/MS analysis (injection volume 5 µL) directly and the other 100 µL for GC/MS analysis, which was first transferred to a glass vial and evaporated to dryness and then 100 µL of MSTFA was added to the residue for silylation derivatization at 37 °C for 18 h. The derivatives were centrifuged for 10 min (13 200 rpm) at 20 °C and the supernatant were then transferred into a GC vial. Reference Standards Preparation. PC (16:0/16:0), LPC (16: 0/0:0), DAG (18:1/18:1/0:0), LPC (18:1/0:0), hexadecanoic acid (C16:0), c-9-hexadecenoic acid (C16:1), octadecanoic acid (C18: 0), c-9-octadecenoic acid (C18:1), c-9,12-octadecadienoic acid (C18:2), dodecanoic acid (C12:0), and tetradecanoic acid (C14: 0) reference standards were dissolved in ethanol and each diluted to a final concentration of 500 µg/mL. Glycerol was diluted with ethanol to 1% (v/v). A total of 5 µL of each of the above standards solutions was injected to LC/MS/MS directly. Another 100 µL was prepared following the derivatization procedure described in Blood Sample Preparation Procedures. prior to GC/MS analysis. LC/MS Analysis. LC/MS analysis was performed on an Agilent 1200 HPLC system (Waldbronn, Germany) equipped with 6410 QQQ triple quadrupole mass detector and managed by a MassHunter workstation. The column used for the separation was an Agilent rapid resolution HT zorbax SB-C18 (2.1 × 50 mm, 1.8 µm) (Agilent Technologies, Santa Clara, CA). The column temperature was set at 50 °C. The gradient elution involved a mobile phase consisting of (A) 0.1% formic acid in water and (B) MeOH. The initial condition was set at 5% of B. The following solvent gradient was applied: from 95% A and 5% B to 10% A and 90% B within 10 min, hold for 10 min and then to 100% B within 5 min and hold for 10 min. Flow rate was set at 0.2 mL/min and 5 µL of samples was injected. The ESI-MS were acquired in positive and negative ion mode, respectively. The ion spray voltage was set at 4000 V. The heated capillary temperature was maintained at 350 °C. The drying gas and nebulizer nitrogen gas flow rates were 10 L/min and 30 psi, respectively. For full scan mode analysis spectra were stored from m/z 100 to 1500. Collision energy was set at 30 V when precursor; neutral loss and product ions scan modes were performed. PC and LPC in human blood were identified according to the following procedure.46,47 After the full scan analysis, the neutral loss scan of choline group 59 and precursor scan of phosphocholine headgroup diagnostic fragment ions at m/z 184 were performed to find the potential lipids with phosphocholine structure. The acquired [M + H]+ and [M + Na]+ adduct ions were then searched online using the HMDB (http:// www.hmdb.ca) and LIPID MAPS (http://www.lipidmaps.org) and (http://www.byrdwell.com) databases to identify the probable PC or LPC compounds. EIC of [M - H]- ions was used to locate potential major free fatty acids by referring to the online mass data (http:// www.lipidmaps.org) and (http://www.byrdwell.com/PhosphatidylCholine/ FattyAcids.html) in human blood,48,49 which were further confirmed with their reference standards. EIC of [M + Na]+ ions were used to search for major DAG species by referring to the online mass data (http://www.lipidmaps.org) and (http://www.byrdwell.com/PhosphatidylGlycerol/), which were then further confirmed according to the published LC/MS method.50 GC/MS Analysis. Derivatized sample (1.0 µL) was injected splitlessly with an Agilent 7683 Series autosampler into an Agilent 6890 GC system equipped with an Agilent 5973 Mass
Multiorigination of Chromatographic Peaks in Derivatized GC/MS
technical notes
Figure 1. Derivatized GC/MS chromatograms of (A) PC (16:0/16:0), (B) LPC (16:0/0:0), (C) hexadecanoic acid (16:0), (D) DAG (18:1/18: 1/0:0), (E) LPC (18:1/0:0) and (F) c-9-octadecenoic acid (18:1) reference standards. Peak 1-10 are the identified derivatives (corresponding chemical structures are inset in dotted box) of these six standard references. (1, trimethylsilyl ether of glycerol; 2, Silanol trimethylphosphate (3:1); 3, Phosphoric acid bis(trimethylsilyl) 2,3-bis[(Trimethylsilyl)oxy]propyl ester; 4, Hexadecanoic acid methyl ester; 5, Hexadecanoic acid ethyl ester; 6, Hexadecanoic acid trimethylsilyl ester; 7, Hexadecanoic acid 2,3-bis[(Trimethylsilyl)oxy]propyl ester; 8, Phosphoric acid 2-(trimethylsiloxy)-1-[(trimethylsiloxyl)methyl bis(trimethylsilyl) ester; 9, octadecenoic acid trimethylsilyl ester; 10, 1-monooleoylglycerol trimethylsilyl ether.)
Selective Detector. The inlet temperature was set at 250 °C. Separation was performed on a fused-silica capillary column HP-5MSI (30 m × 0.25 mm i.d., 0.25 µm film thickness). Helium was used as the carrier gas at a constant flow rate of 1.0 mL/ min. The column temperature was initially maintained at 70 °C for 1 min, and then increased to 250 °C at a rate of 10 °C/min and further increased at 25 °C/min to 300 °C where it remained for 5 min. The column effluent was introduced into the ion source of an Agilent Mass selective detector. The transfer line temperature was set at 280 °C and the ion source temperature at 230 °C. The mass spectrometer was operated in electron impact (EI) mode (70 eV). Data acquisition was performed in full scan mode from m/z 50 to 550 with a scan time of 0.5 s. The compounds were identified by comparison of mass spectra and retention time with those of reference standards, and those available in libraries (NIST 0.5).
Results Derivatized GC/MS Chromatograms of Representative PC, LPC, DAG and Corresponding Fatty Acid Reference Standards. Two groups of structural and biological related reference standards, that is, PC (16:0/16:0), LPC (16:0/0:0) and
hexadecanoic acid (C16:0) versus DAG (18:1/18:1/0:0), LPC (18: 1/0:0) and c-9-octadecenoic acid (C18:1) were first analyzed to explore the common behavior for multipeaks and multioriginations phenomena in derivatized GC/MS. The MSTFA derivatized GC/MS chromatograms of these six endogenous compounds are shown in Figure 1. The derivative peaks were identified by comparison of mass spectra and retention time with those of reference standards, as well as those that are available in libraries (NIST 0.5). Our results demonstrate that PC (16:0/16:0), LPC (16:0/0:0) and hexadecanoic acid (C16:0) could all produce the same peak of hexadecanoic acid trimethylsilyl ester (peak 6), the trimethylsilyl derivatives of hexadecanoic acid (C16:0), at 16.77 min. Similarly, DAG (18:1/18: 1), LPC (18:1/0:0) and c-9-octadecenoic acid (C18:1) also have the common peak of octadecenoic acid trimethylsilyl ester (peak 9) at 18.33 min. Further, peaks 1, 2, and 3 are the common derivatives for PC (16:0/16:0), LPC (16:0/0:0), DAG (18: 1/18:1/0:0) and LPC (18:1/0:0), which were identified as glycerol trimethylsilyl ether, Silanol trimethyl phosphate (3:1) and Phosphoric acid bis-(trimethylsilyl) 2,3-bis[(Trimethylsilyl)oxy]propyl ester, respectively. Besides, PC (16:0/16:0) and LPC (16:0/0:0) also share the common derivatives of hexadecanoic Journal of Proteome Research • Vol. 8, No. 12, 2009 5659
technical notes acid methyl ester (peak 4) and hexadecanoic acid ethyl ester (peak 5). DAG (18:1/18:1) and LPC (18:1/0:0) have the same derivative peak of phosphoric acid 2-(trimethylsiloxy)-1-[(trimethylsiloxyl) methyl bis(trimethylsilyl) ester (peak 8). Peak 7 and peak 10, the unique derivatives for PC (16:0/16:0) and DAG (18:1/18:1), are identified as Hexadecanoic acid, 2,3-bis[(Trimethylsilyl)oxy]propyl ester and 1-monooleoylglycerol trimethylsilyl ether, respectively. The structural details about these derivative peaks could be found in Table 1. The above results suggest that structural and biological related endogenous metabolites might result in the same peaks in derivatized GC/ MS chromatogram. Figure 2 summarizes the proposed common peaks of PC, LPC and GAG in MSTFA derivatized GC/ MS. PC, LPC, DAG and Fatty Acids Species Identified in Human Blood by LC/MS. In the present study, LC/MS was used as a reference method to demonstrate the presence of PC, LPC, DAG and free fatty acids species in human blood. These metabolites were identified based on the combination of LC/MS and online databases according to our and other researchers’ published literatures.46–50 Figure 3 shows the representative ESI (+) and ESI (-) full scan chromatograms of human blood. PC and LPC species detected in human blood by LC/MS are listed in Supp. 1 (Supporting Information). As a result, 17 LPCs with their sn-2 isomers and 28 PCs species were identified. LPCs gather together around the retention time of 13 min, while PCs show longer retention time and gather near 22 min. As shown (Supp. 1 in Supporting Information), fatty acids at different stages of saturation containing 16, 18, and 20 carbons were found usually attached to the sn-1 position in monoglycerophospholipid (LPC). Isomers of LPC with sn-2 position were also detected with shorter retention time compared with its corresponding LPC under the same HPLC conditions. Similar to LPC, PC detected in human blood also have many different combinations of fatty acids of varying lengths and of different saturation stages, attached to the sn-1 and sn-2 positions. In brief, fatty acids containing 16, 18, and 20 carbons are common for human blood PC and LPC. Seven major free fatty acids and 5 DAG species were found in human blood using LC/MS combined with online databases (http://www.hmdb.ca, http://www.lipidmaps.org and http:// www.byrdwell.com). These free fatty acids were all further confirmed using reference standards. The mass data of these two types of compounds were summarized in Supp. 2 (Supporting Information) and Supp. 3 (Supporting Information). Very similar to PC and LPC, 16, 18, and 20 carbons are also the most common free fatty acids and DAG species. The above results obtained using LC/MS demonstrated the presence of PC, LPC, DAG and fatty acids species in human blood. Metabolic Profiling of Human Blood by Derivatized GC/ MS. The metabolic profiling of human blood was investigated using MSTFA derivatized GC/MS to find the potential peaks with multioriginations. The compounds were identified by comparison of mass spectra and retention time with those of reference standards, as well as those available in libraries (NIST 0.5). Figure 4 shows the representative derivatized GC/MS chromatogram of human blood. More than 60 compounds were found and identified, most of which are amino acids, carbohydrates and different types of fatty acid, identical to those in published papers.32,51–53 In contrast, peaks corresponding to parent structures of PC, LPC, DAG or other lipid 5660
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Xu et al. species identified using LC/MS method were not found in the GC/MS chromatogram. It is believed that these heat-labile compounds have been fractionated to small pieces such as fatty acids and other phospholipids related fractions in derivatized GC/MS, based on the behaviors of PC (16:0/16:0), LPC (16:0/ 0:0), DAG (18:1/18:1/0:0), LPC (18:1/0:0), hexadecanoic acid (C16:0), and c-9-octadecenoic acid (C18:1) reference standards (Figures 1 and 2). Table 1 summarizes all the identified phospholipids related compounds (fractions) in human blood metabolic profiling acquired by derivatized GC/MS. The types of fatty acid detected by derivatized GC/MS are in consistence to those obtained using LC/MS (Supporting Information: Supp. 1, Supp. 2 and Supp. 3).
Discussion The term and idea of metabolomics have been introduced for over 10 years focusing on an improved understanding of biological networks by systematic and comprehensive analysis of metabolism, which was usually accomplished based on a robust and reliable analytical platform combined with multivariate statistical analysis.1–4 As the most commonly used analytical methods, NMR, GC/MS and LC/MS have been applied successfully for metabolomic studies.23–25 As each method has its own advantages and drawbacks, in depth understanding of the inherent properties of these analytical methods together with their specific sample preparation procedures, and appropriate use of the data obtained are essential for metabolic network interpretation. Derivatized GC/MS is useful for rapid metabolite profiling, by which several hundreds of chemically diverse compounds including organic acids, amino acids, sugars, sugar alcohols, aromatic amines and fatty acids could be simultaneously profiled.3–6,23–25,30–34,51–54 To make this method more robust and stable, several studies have been conducted regarding the method standardization focusing on sample extraction, optimization of derivatization step, and method validation.30–34 Although derivatized GC/MS methods for metobolomic studies have been widely used and well-investigated, there still exist many puzzles yet to be uncovered. First of all, biological samples are highly complex with extensive variations, and wide dynamic range. Second, GC/MS is known to be more sensitive to volatile and thermal stable compounds and may not be suitable for the wide range of biomolecules. Complex samples, highly specific instrumentation requirement, and with additional derivatization procedure formed a complex entity as the basis for derivatized GC/MS metablomic platform. Furthermore, the possibilities of sample decomposition during derivatization process or during GC analysis are questions that need to be answered. All these factors might affect our interpretation of metabolic pathway. Unfortunately, the current attentions of most metabolomic studies have been focused on compound identification, bioinformatics and applications of techniques. So far, no studies have been systematically performed to answer some of the fundamental and yet crucial issues in metabolomic investigations. To address some of the above-mentioned issues, we selected several representative biological compounds including LC, LPC, DAG and fatty acids, which are known to have some interrelationships for this investigation. Figure 5 summarizes the metabolic relationships among the PC, LPC, DAG and various fatty acids studied, according to previous publications. For details of these pathways, readers referred to the following Web sites: http:// www.genome.jp/kegg-bin/show_pathway?ko00564+C00157 (Glyc-
Multiorigination of Chromatographic Peaks in Derivatized GC/MS
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Table 1. Phospholipids Related Compounds (Fractions) Identified in Human Blood Metabolic Profiling Acquired by Derivatized GC/MSa
a
*Confirmed with reference standards; #Searched in libraries: NIST 0.5.
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technical notes
Figure 2. Proposed common peaks (fractions) of PC, LPC and DAG in derivatized GC/MS.
erophospholipid metabolism); http://www.genome.jp/kegg-bin/ show_pathway?ko00590+C00157 (Arachidonic acid metabolism); http://www.genome.jp/kegg-bin/show_pathway?ko00591+ C00157 (Linoleic acid metabolism); http://www.genome.jp/ kegg-bin/show_pathway?ko00592+C00157 (Alpha-Linolenic acid metabolism); http://www.genome.jp/kegg-bin/show_pathway? ko01100+C00157 (Full metabolic pathways); http://biocyc.org/ META/ NEW-IMAGE? type) PATHWAY&object) LIPASYN- PWY (Phospholipases). Phospholipase A1 (PLA1), phospholipase A2 (PLA2), phospholipase B (PLB), phospholipase C (PLC), and phospholipase D (PLD) are the four major types of phospholipases involved in the above metabolic nets. PLA1 and PLA2 specifically hydrolyze the sn-1 and sn-2 acyl ester bond of PC to produce fatty acids and LPC, respectively. With a combination of both PLA1 and PLA2 activities, PLB could cleave acyl chains from both sn-1 and sn-2 positions of phospholipids. PLC hydrolyzes phosphotidylinositol 4, 5-bisphosphate (PIP2) to inositol 1, 4, 5-triphosphate
Xu et al. and diacylglycerol, and are thus important in secondary messenger pathways. PLD catalyzes the hydrolysis of PC to form phosphatidic acid (PA), releasing the soluble choline headgroup into the cytosol. PA is a signal molecule and acts to recruit SK1 to cell membranes. PA is extremely short-lived and is rapidly hydrolyzed by the enzyme PA phosphohydrolase to form diacylglycerol (DAG). Therefore, if we wish to explore the response of the above metabolic pathways to any physiological or pathological changes, the analytical method should specifically express these compounds in its original status without any signal overlapping. As shown in Figures 1 and 2, the data clearly demonstrated that more than one peak was produced from each, and all of the above-mentioned metabolites. Different varities of these structurally related metabolites could be chemically transferred into the same structure analyte. In another word, there exists multiorigination phenomenon of chromatographic peaks in derivatized GC/MS metabolomics. The exact mechanisms are not clear at the present stage. This may be due to the decomposition during derivatization procedure and/or caused by the high temperature of various GC parts, such as the inlet, column, and so forth. The combination of Figures 2 and 5 provide the basis to demonstrate the multiorigination of glycerol, phosphoric acid, fatty acids and glycerophosphate that could affect the metabolic pathway interpretation involved these metabolites. Our findings thus suggest that, when only derivatized GC/ MS was used for metabolomic study, not only the data handling, but also the metabolic pathways elucidation need to be conducted with care. In this study, LC/MS was used as a reference method to indicate the existence of PC, LPC, DAG and various fatty acid species in human blood. The combination of results obtained using LC/MS and GC/MS confirms the multiorigination and multipeak phenomena in GC/MS chromatogram for these four major types of metabolic related compounds. The findings suggest that results based on derivatized GC/MS could lead to wrong conclusions in metabolomics.
Conclusions The multiorigination and multipeak phenomena when using derivatized GC/MS technique were addressed for the first time, in this paper. Their potential influences on metabolic pathway
Figure 3. Representative LC/MS full scan chromatograms of human blood acquired in ESI+ (upper) and ESI - (lower) modes, respectively. 5662
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technical notes
Multiorigination of Chromatographic Peaks in Derivatized GC/MS
Figure 4. Representative derivatized GC/MS chromatogram of human blood. The inset is the partial enlargement from 18.10 to 18.50 min. (1, trimethylsilyl ether of glycerol; 2, Silanol trimethyl-phosphate (3:1); 3, Phosphoric acid bis(trimethylsilyl) 2,3-bis[(Trimethylsilyl)oxy]propyl ester; 4, Hexadecanoic acid methyl ester; 5, Hexadecanoic acid ethyl ester; 6, Hexadecanoic acid trimethylsilyl ester; 9, octadecenoic acid trimethylsilyl ester; 11, Dodecanoic acid, trimethylsilyl ester; 12, Tetradecanoic acid trimethylsilyl ester; 13, Palmitelaidic acid trimethylsilyl ester; 14, 9,12-octadecadienoic acid (Z,Z)-trimethylsilyl ester; 15, 11-trans-octadecanoic acid trimethylsilyl ester; 16, Octadecanoic acid trimethylsilyl ester.)
Figure 5. Summarized rough metabolic pathways between PC, LPC, DAG and fatty acids.
interpretations were also systematically illustrated using a spectrum of structural and biological related endogenous species including PC, LPC, DAG and fatty acids as examples. The findings clearly demonstrated that care is to be exercised when only derivatized GC/MS method was used for metabolomic study. To avoid many of the potential errors and wrong interpretation, investigations combining the use of other analytical instruments, such as NMR and/or LC/MS should be
considered. Meanwhile, it has to be recognized that derivatized GC/MS approach is far more complex than we have explored especially for metabolites analysis. We are still a long way from explaining the originations of each chromatographic peak in derivatized GC/MS metabolomics.
Acknowledgment. Fengguo Xu and Li Zou contributed equally to the paper. The authors appreciate Journal of Proteome Research • Vol. 8, No. 12, 2009 5663
technical notes Ms. Jin Su and Mr. Eugene Ho for their valuable suggestions. This study was supported in part by the Life Sciences Institute and the Centre for Environmental and Occupational Health of the National University of Singapore.
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technical notes
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