Analytica Chimica Acta 804 (2013) 180–189
Contents lists available at ScienceDirect
Analytica Chimica Acta journal homepage: www.elsevier.com/locate/aca
Metabolite profiling of human plasma by different extraction methods through gas chromatography–mass spectrometry—An objective comparison Syed Ghulam Musharraf a,b,∗ , Shumaila Mazhar b , Amna Jabbar Siddiqui b , M. Iqbal Choudhary a,b,c , Atta-ur-Rahman a,b a Dr. Panjwani Center for Molecular Medicine and Drug Research, International Center for Chemical and Biological Sciences, University of Karachi, Karachi 75270, Pakistan b H.E.J. Research Institute of Chemistry, International Center for Chemical and Biological Sciences, University of Karachi, Karachi 75270, Pakistan c Department of Chemistry, College of Science, King Saud University, Riyadh 1145, Saudi Arabia
h i g h l i g h t s
g r a p h i c a l
a b s t r a c t
• GC–MS
metabolite profiling of plasma using 10 different extraction techniques. • All methods were able to detect a wide range of endogenous metabolites. • Comprehensive metabolite profiling is offered by 2D-C18 and 2D-silica based methods. • Metabolite features of each extraction method are statistically compared.
a r t i c l e
i n f o
Article history: Received 6 July 2013 Received in revised form 8 October 2013 Accepted 11 October 2013 Available online 19 October 2013 Keywords: Gas chromatography–mass spectrometry Metabolite profiling Extraction methods Solid phase extraction Human plasma
a b s t r a c t For the comprehensive metabolite profiling of human plasma, sample preparation is a crucial step. In this investigation, we have compared 10 different extraction techniques for metabolite profiling by GC–MS. Six one-dimensional (1D) and four two-dimensional (2D) extraction techniques involving solvent precipitation, molecular weight cut off tube (MWCOT) and solid phase extraction (SPE) by using silica, RP C18, cation and anion were investigated. Pooled samples of 50 Healthy Male Plasma (HMP), 50 Healthy Female Plasma (HFP) and 100 Healthy Pakistani Plasma (HPP) were subjected to these extraction methods for comparison purposes. Metabolites obtained were identified through NIST mass spectral (Wiley registry), METLIN and Fiehn RTL libraries. XCMS Software was used for the detection of metabolic features, retention time correction, alignment, annotation and statistical analysis in each method. 116–34 peaks were detected by various methods and approx 33% of the peaks were characterized in each method. Hierarchical clustering of the 10 extraction methods showed a low similarity index (50.1%) which indicated different chemical nature of metabolites, resulting from different methods. Venn diagram highlights the GC–MS peaks (33–77%) common in various methods. Metabolites which were different in male and
Abbreviations: HMP-P, Healthy Male Plasma-Pool; HFP-P, Healthy Female Plasma-Pool; HPP-P, Healthy Pakistani Plasma-Pool; HMPG1-G4-P, Healthy Male Plasma Group 1-Group 4-Pool; HFPG1-G4-P, Healthy Female Plasma Group 1-Group 4-Pool; SPE, solid phase extraction; MWCOT, molecular weight cut off tube; Si, silica. ∗ Corresponding author at: Dr. Panjwani Center for Molecular Medicine and Drug Research, International Center for Chemical and Biological Sciences, University of Karachi, Karachi 75270, Pakistan. Tel.: +92 021 34824924/4819010; fax: +92 021 34819018 9. E-mail address: [email protected] (S.G. Musharraf). 0003-2670/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.aca.2013.10.025
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female groups were detected using a threshold value of p ≤ 0.0001, q ≤ 0.001 and fold change ≥3 by employing Welch’s t-test and identified through METLIN. Results indicated that 2D-C18 and 2D-silica offers a comprehensive metabolite profile in term of reproducibility, number of peaks and difference in metabolite pattern of male and female. © 2013 Elsevier B.V. All rights reserved.
1. Introduction
2. Materials and methods
Advancement in omics technology can lead to new biomarker identification for most of the diseases through genotypic and phenotypic level alteration. Genomics, transcriptomics and proteomics have long been applied for biomarker detection [1–3]. Recently, metabolomics is increasing interest in the diagnosis of a number of pathological conditions [4–8]. Identification and measurement of the metabolites, synthesized by a biological system, the metabolome, plays an important role in the assessment of genetic functions [9–11]. In metabolomics, diverse functional groups are present, ranging from volatile alcohols, ketones, amines, organic acids to complex lipids, carbohydrates and other secondary metabolites. The wide differences in chemical properties of the metabolites and their very low concentrations between milli to picomoles creates a major challenge in developing a generic, robust and reproducible global profiling methods [12]. Recent advances in NMR, GC/MS and LC/MS techniques have enabled the use of more global metabolomic approaches for the identification of novel biomarkers for specific diseases as well as new targets for drug discovery and development [13–15]. Among the recent techniques, GC/MS proved to be a significantly useful method due to its high sensitivity and resolution, reproducibility and cost effectiveness. Moreover, in comparison to LC/MS, the availability of a large GC/MS electron impact (EI) spectral library further aids the identification of biomarkers in various pathological conditions [16]. For the determination of the global metabolite profile of human plasma, sample preparation is a major factor [17–19]. Currently metabolites are extracted from plasma either with acetonitrile [20–22], ethanol [23,24] or methanol [25–27], followed by derivatization and GC/MS analysis. The effects of extraction solvents, derivatization protocol and extraction conditions on the human blood plasma metabolome by GC/MS has studied [26] while the efficiency of various solvents (methanol, ethanol, acetonitrile, acetone, chloroform) for metabolite extraction from mammalian cell culture have also evaluated [27]. Solid-phase extraction (SPE) technique and molecular weight cutoff tube has emerged as an alternative to solvent based extraction because strongly proteinbound metabolites are reluctant to recover by solvent precipitation method. Protein precipitation has been compared via methanol and acetonitrile with reversed phase SPE for plasma metabolite extraction followed by UPLC–MS analysis [28]. Similarly, a protocol for metabolites extraction of E. coli was also developed using acids, organic solvents and molecular weight cutoff tube [29]. In the present study, 10 different extraction methods were employed for metabolite enrichment. These small molecular weight metabolites posses physicochemical properties and acid/base characteristics. To resolve these analytes prior to GCMS detection, various 1D (one dimensional) or one step and 2D (two dimensional) or two steps extraction approaches were used including solvent precipitation, molecular weight cut off tube (MWCOT), silica, C-18, cation and anion SPEs. A comparison of the above mentioned approaches for metabolomic analysis of plasma have not been made yet to the best of our knowledge. Comparison was made, based on the numbers and types of metabolites, reproducibility and similarly index.
2.1. Solvents and reagents All solvents used for GC–MS analysis were of analytical grade. Methanol, n-hexane and ammonium hydroxide were purchased from Tedia (Tedia way, Fairfield, USA), while isopropanol and HCl (37%) were purchased from Fisher Scientific (Loughborough, Leicestershire, U.K.), formic acid and myristic-d27 acid were purchased from Sigma–Aldrich (Steinheim, Germany and St. Louis, MO, USA, respectively). BSTFA (N,O-bis (trimethylsilyl)trifluoroacetamide) with 1% TMCS (trimethylchlorosilane) and methoxylamine hydrochloride (98+%) were purchased from Acros Organic (New Jersey, USA). Deionized water (Milli-Q) was used throughout the study (Millipore, Billerica, MA, USA). 2.2. Sample collection statistics and pooling strategy Blood samples of total 100 subjects (50 male and 50 female) with body mass index 21.335 ± 5.2 kg m−2 in the age range of 20 to above 50 were collected from Karachi, Pakistan with consent. All the subjects were non-smokers, healthy and none were taking any prescribed medication. About 8 mL of the blood was drawn in the morning from the overnight fasting volunteers in BD Vacutainer tubes (BD Franklin Lakes, NJ, USA, REF 367856), containing K2 ethylenediaminetetraacetic acid as an anticoagulant. Plasma was separated immediately by centrifugation at 4500 rpm for 10 min at 4 ◦ C. Finally, the plasma was aliquoted and frozen at −80 ◦ C. Code was given to each sample. Sample collection description and codes are mentioned in Table S1 of supporting information. Blood sample of 100 healthy volunteers was pooled in three steps and named as Healthy Pakistani Plasma-Pool (HPP-P). Healthy Pakistani PlasmaPool (HPP-P) was prepared by 3 pooling steps. First the healthy male and female plasma-pool i.e. (HMPG1-4-P and HFPG1-4-P) of each age group was prepared. In the second pooling step, the healthy male and female plasma-pool, i.e. (HMP-P and HFP-P) were prepared. Finally, both healthy male and female pooled plasma was pooled to obtain HPP-P. The pooling strategy and details of each step are shown in Fig. 1. HPP-P, HMP-P and HFP-P samples were selected for further screening. The samples were kept at −80 ◦ C until analysis. 2.3. Sample preparation The samples were prepared by using various extraction approaches as mentioned below: 2.3.1. For 1D-solvent precipitation (Method-1) For the solvent precipitation method, aliquots of 100 L of plasma were mixed with 800 L of solvent MeOH, 20 L of internal standard myristic-d27 acid (1 mg mL−1 stock solution) was added, vortexed for 30 s and left on ice for 2 h for complete protein precipitation. The precipitated proteins were then removed by centrifugation at 12,000 rpm for 10 min (Eppendorf Centrifuge 5804C/R). Aliquots (400 L) of the resulting clear supernatants were then transferred into Eppendorf tubes and evaporated under N2 steam at room temperature. The dry samples were stored at 4 ◦ C for analysis.
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Fig. 1. Sample pooling Strategy, HMP-P (Healthy Male Plasma-Pool), HFP-P (Healthy Female Plasma-Pool), HPP-P (Healthy Pakistani Plasma-Pool).
2.3.2. For 1D-C18 SPE (Method-2) Samples were extracted onto a C18 SPE cartridge (Strata C18-E, 55 m pore size, 70 Å particle, 100 mg sorbent/1 mL Phenomenex, USA). Prior to extraction, the phase was activated with 2× 300 L of MeOH and then further conditioned with 2× 300 L of H2 O. Aliquots of 400 L of diluted plasma (100 L plasma diluted with 800 L H2 O and 20 L of internal standard myristic-d27 acid) were loaded onto the SPE and drawn through the solid phase under vacuum. The phase was then washed with 300 L water and eluted with 600 L of MeOH. The eluate was evaporated under N2 at room temperature. The dry samples were stored at 4 ◦ C until analysis. The SPE extractions were performed on solid phase extraction vacuum manifold AH0-7502 Phenomenex (USA). 2.3.3. For 1D-silica SPE (Method-3) Samples were extracted onto a silica SPE cartridge (Strata SI-1 Silica, 55 m pore size, 70 Å particle, 100 mg sorbent/1 mL Phenomenex, USA). Prior to extraction, the phase was activated with 2× 300 L of MeOH and then further conditioned with 2× 300 L of n-hexane. Aliquots of 400 L of diluted plasma (100 L plasma diluted with 800 L H2 O and 20 L of internal standard myristicd27 acid) were loaded onto the SPE and drawn through the solid phase under vacuum. The phase was then washed with 2× 300 L of 5% isopropanol in hexanes and eluted with 600 L of hexanes: isopropanol (1:1). The eluate was evaporated with N2 at room temperature. The dry samples were stored at 4 ◦ C until analysis. 2.3.4. For 1D-cation SPE (Method-4) Samples were extracted onto a mix mode cation SPE cartridge (Strata Screen C, 55 m pore size, 70 Å particle, 100 mg sorbent/1 mL Phenomenex, USA). Prior to extraction, the phase was activated with 2× 300 L of MeOH and then further conditioned with 2× 300 L of 0.1% acidic (formic acid) H2 O. Aliquots of 400 L of diluted plasma (100 L plasma diluted with 800 L H2 O and 20 L of internal standard myristic-d27 acid) were loaded onto the SPE and drawn through the solid phase under vacuum. The phase was then washed with 300 L of 0.1 M HCl in H2 O then with 300 L of 0.1 M HCl in CH3 COOH and eluted with 600 L of 5% NH4 OH. The eluate was evaporated with N2 at room temperature. The dry samples were stored at 4 ◦ C until analysis. 2.3.5. For 1D-anion SPE (Method-5) Samples were extracted onto mix mode anion exchange SPE cartridge (Strata Screen A, 55 m pore size, 70 Å particle, 100 mg sorbent/1 mL Phenomenex, USA). Prior to extraction, the phase was activated with 2× 300 L of MeOH and then further conditioned with 2× 300 L of H2 O. Aliquots of 400 L of diluted plasma (100 L plasma diluted with 800 L H2 O and 20 L of internal standard myristic-d27 acid) were loaded onto the SPE and drawn through the solid phase under vacuum. The phase was then washed with
300 L of 25 mM CH3 COONH4 then with 300 L MeOH and eluted with 600 L of 5% formic acid in MeOH. The eluate was evaporated with N2 at room temperature. The dry samples were stored at 4 ◦ C until analysis. 2.3.6. For 1D-MWCOT (Method-6) Samples were ultra filtered with a MWCOT (Molecular Weight Cut Off Tube pore size 1 kDa, Sigma–Aldrich, Steinheim, Germany). First the phase were activated with water and tube were inverted to flow water from pore by centrifuge at 5000 rpm for 5 min. Aliquots of 400 L of diluted plasma (100 L plasma diluted with 800 L H2 O and 20 L of internal standard myristic-d27 acid) was loaded and filtrate were collected by centrifuge at 5000 rpm for 5 min. The filtrates were evaporated with N2 at room temperature. The dry samples were stored at 4 ◦ C until analysis. 2.3.7. For 2D-approach In all the 2D methods, including 2D-C18 (method-7), 2D-silica (method-8), 2D-cation (method-9) and 2D-anion (method-10), first the solvent precipitation was carried out as mentioned in Method1 then 400 L of the resulting clear supernatants were subjected to SPE using C18, silica, cation and anion stationary phase. Then rest of the process was the same as discussed for 1D SPE. 2.4. Derivatization and GC/MS analysis The dried extract of all the methods were derivatized subsequently by adding 30 L methoxylamine hydrochloride in pyridine (15 g/L), vortexed and left for 16 h (oximation time was already optimized [26]) at room temperature. Then BSTFA was added with 1% TCMS and placed at room temperature for 60 min to form trimethylsilyl (TMS) derivatives [26]. For all the samples, 1.0 L of derivatized extract was injected for GC/MS analysis. Before injection, samples were centrifuged at 2000 rpm for 2 min to remove any solid particle. GC/MS Analyses were performed on a 7890A gas chromatography (Agilent technologies, USA) equipped with an Agilent Technology GC sampler 120 (PAL LHX-AG12) autosampler and coupled to an Agilent 7000 Triple Quad system (Agilent technologies, USA). An HP-5MS 30 m-250 mm (i.d.) fused-silica capillary column (Agilent J&W Scientific, Folsom, CA, USA), chemically bonded with a 5% diphenyl 95% dimethylpolysiloxane cross-linked stationary phase (0.25 mm film thickness) was used. Helium was used as the carrier gas at 1.0 mL min and the sample was injected in splitless mode. The injector and source temperatures were 250 ◦ C. The oven temperature was initially maintained at 40 ◦ C, and was then increased at 10 ◦ C min to 300 ◦ C and retained at 300 ◦ C for 9 min. In post run, temperature was further increased to 305 ◦ C, for remaining 1 min. Retention time was locked to myristic-d27 acid according to the published protocol at 15.168 min [30]. Electron ionization (EI) is used as an ionization source for the GC/MS
S.G. Musharraf et al. / Analytica Chimica Acta 804 (2013) 180–189
analysis at 70 eV. Data is acquired in the full scan mode from m/z 50 to 650 with a scan time of 0.5 s. Three replicate of each sample was performed then blank (hexane) was run in between each sample to remove any contamination. Perfluorotributylamine (PFTBA) was used for mass calibration Data processing was performed by using the Agilent Mass Hunter Qualitative Analysis (version B.04.00).
2.5. GC/MS data preprocessing and statistical analysis Metabolite profiling of blood samples were analyzed using the optimized GC/MS assay. Data processing was performed using the Agilent Mass Hunter Qualitative Analysis (version B.04.00). Data was normalized to internal standard. Peak integration and deconvolution were performed either directly on Mass Hunter or after export as mzData files to online XCMS software. For heat map and distribution of plasma metabolites of all the 10 methods, data was processed through Mass Hunter. The chromatographic deconvolution parameters on Mass Hunter are set as follows: SNR threshold 10.0, RT window size factor: 100.0, left m/z delta: 0.3 (amu), right m/z delta: 0.7 (amu), excluded m/z 28 (amu), sharpness threshold: 25.0% and chromatogram deconvolution compound filter parameter as relative area 1.0% of largest peak, absolute area 5000 counts. Putatively identity of GC/MS detected peaks was established by comparing the mass spectra of the peaks with those available in the NIST mass spectral (Wiley registry) and Fiehn RTL libraries. The peak lists obtained by Mass Hunter qualitative analysis report were further processed to construct a heatmap for some of the identified metabolite through Qlucore Software version 2.3. Distribution of identified plasma metabolites from all the 10 methods was plotted on Microsoft Excel 2007. To examine similarities in all 10 methods, GC/MS data of the six 1D and four 2D methods were first aligned through XCMS and a dendrogram was then produced by applying a hierarchical clustering algorithm (by applying Correlation Coefficient Distance, Complete Linkage) by Minitab software. Raw GC/MS data were converted into mzData on Mass Hunter and processed using online XCMS software. The XCMS parameters were default setting except for the following p value ≤1 × 10−4 and fold change ≥3. XCMS aligned data was further used for statistical analysis on Minitab software version 11.12. The average percent relative standard deviation (%RSD) for the intensity of all detected metabolite features from each method was evaluated. Welch’s t-test was employed to detect metabolites which were significantly different in male and female groups using a threshold value of p ≤ 0.0001, q ≤ 0.001 and fold change ≥3 and METLIN was used for the putative identification of these metabolite using XCMS software [31,32]. Metabolite features, observed in the different methods were evaluated through Venn diagram.
2.6. Method optimization Various parameters involved in sample preparation and GC–MS analysis were optimized. To optimize the protein precipitation, acetonitrile and methanol were checked for the extraction of the metabolite while extraction time for metabolites was optimized using 30 and 120 min. The derivatization step was optimized at different temperatures (30–90 ◦ C) and times (0.66–16 h) for oximation and silylation. Various instrumental parameters were also optimized for better separation of peaks. Different injection modes including splitless and split with various ratio (1:10, 1:20, 1:30, and 1:40) were also optimized. Similarly, two different temperature programing were also evaluated. In one program, initial oven temperature was adjusted at 40 ◦ C and increased at 10 ◦ C min to 300 ◦ C.
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In another temperature programming, the initial oven temperature was adjusted at 70 ◦ C and increased at 5 ◦ C min to 300 ◦ C. 3. Results and discussion Ten different extraction techniques were evaluated for metabolites extraction from human plasma and their affect on the numbers and types of metabolites as well as reproducibility. Methods were applied on pooled plasma sample of 100 healthy individuals named as Healthy Pakistani Plasma-Pool (HPP-P) followed by GC–MS analysis. Pooling of biological samples have been applied to investigate various types of analytes [33]. Metabolite features of each method were analyzed by XCMS online software. A metabolite feature was defined as a mass spectral peak in the mass region of m/z 50–650 with a signal-to-noise ratio exceeding 10:1. Retention time, m/z, and intensity values were recorded for each detected metabolite feature. Using this software, 1000 to 2000 mass features were detected by various extraction techniques. A “reproducible feature” was defined as a metabolite feature that was detected in all three GC/MS runs for a given extraction method. Individual features can be plotted as EICs to allow for visual comparison of alignment. An example of a well-aligned metabolite feature detected from all 30 runs is presented in Fig. S1 of supporting information. 3.1. Method optimization For protein precipitation, methanol was found better in terms of metabolites, as reported previously [25–28]. Best result was obtained with 2 h extraction time in term of high number of peaks and high precision. Samples were derivatized with BSTFA after oximation with methoxamine hydrochloride [19,27,34]. By introducing an oximation step prior to silylation, reduces the number of sugar tautomers [35]. Oximation (16 h) and silylation (1 h) were found to be the best in terms of the number of metabolites as previously reported [30]. Separation efficiency, peak symmetry and analysis time were optimized by changing various GC parameters including injection modes, initial temperature of oven and temperature gradient rate. Splitless mode with an initial temperature of 40 ◦ C and ramp time of 10 ◦ C min were found to be the best for the analysis. All other parameters of GC/MS analysis are same as described in the previous section. A total 140 peaks in 2D-C18, 115 in 1D-anion, 120 in 2D-anion, 30 in 2D-cation, 120 in 2D-Si, 90 in 1D-C18, 80 in 1D-Si, 69 in 1D-cation and 52 in solvent precipitation were detected using the GC chromatogram with intensity >1 × 106 . However GC separation still contained some overlapping peaks, therefore deconvolution was applied prior to library search. 3.2. Method reproducibility Visually, total ion chromatogram (TIC) of all 10 extraction techniques showed different peak patterns from 100 pooled plasma sample HPP-P (Figure S2 of supporting information). The standard deviation and percent relative standard deviation (%RSD) for the intensity of all detected metabolite features (1000–2000) after the XCMS alignment from each method were calculated. %RSD of each metabolite feature intensity was obtained from three replicates, where the average %RSD is the average value for all detected features in an individual method. Overall, 2D-Si, solvent induced precipitation, 2D-C18, 1D-cation, 1D-anion and 1D-MWCOT showed the least variations in feature intensity with an average RSD of i.e. 8.4, 10.0, 14.9, 11.5, 14.7 and 14.5%, respectively. 2D-Anion, 1D C-18 and 1D-Si showed %RSD of 16.4, 18.4% and 19.1%, respectively. It is important to note that as this is an average of 1000–2000 metabolite features, therefore individual metabolite %RSD values can greatly vary within each method [25]. For example, RSD values ranged from 1.2 to 137% within the 2D-Si samples
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Fig. 2. Statistical analysis of the three of the compounds identified in the different extraction method. Each bar represents standard deviation of the average of three independent run in each method.
with 1281 metabolite features. 2D-Si, solvent precipitation, 2DC18, 1D-cation, 1D-anion, 2D-cation and 1D-MWCOT showed RSDs of 30%, indicating that pooling only partially nullified the variance and it enhanced the common features which reduce the variation of data points in the 2nd component of PCA in the pooled samples.
Fig. 6. Venn diagrams highlighting the common GC–MS peaks observed in HPP-P sample with each extraction methods. In each case 2D-Si have been used as the benchmark.
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Fig. 7. (A) Score plot of Pakistani pooled (HPP-P), male pooled (HMP-P) and female pooled (HFP-P) samples, all the align feature (1615 metabolite feature) were plotted. (B) Score plot between Pakistani pooled (HPP-P) and individual samples, all the align feature (900 metabolite feature) were plotted. (C) Score plot between male pooled (HMP-P) and individual male samples, all the align feature (1442 metabolite feature) were plotted. (D) Score plot between female pooled (HFP-P) and individual female samples, all the align feature (1903 metabolite feature) were plotted.
4. Conclusion
Appendix A. Supplementary data
Metabolite profiling needs a comprehensive, straightforward, reproducible and efficient sample preparation method which can cover a wide range of metabolites. The results of the current study suggest that the sample preparation protocols based on 1D and 2D extraction, followed by GC/MS analysis were able to detect endogenous metabolites belonging to different chemical classes. Higher number of metabolites were detected in 2D-Si. Overall method reproducibility of most of the extraction technique is within RSDs
Contents lists available at ScienceDirect
Analytica Chimica Acta journal homepage: www.elsevier.com/locate/aca
Metabolite profiling of human plasma by different extraction methods through gas chromatography–mass spectrometry—An objective comparison Syed Ghulam Musharraf a,b,∗ , Shumaila Mazhar b , Amna Jabbar Siddiqui b , M. Iqbal Choudhary a,b,c , Atta-ur-Rahman a,b a Dr. Panjwani Center for Molecular Medicine and Drug Research, International Center for Chemical and Biological Sciences, University of Karachi, Karachi 75270, Pakistan b H.E.J. Research Institute of Chemistry, International Center for Chemical and Biological Sciences, University of Karachi, Karachi 75270, Pakistan c Department of Chemistry, College of Science, King Saud University, Riyadh 1145, Saudi Arabia
h i g h l i g h t s
g r a p h i c a l
a b s t r a c t
• GC–MS
metabolite profiling of plasma using 10 different extraction techniques. • All methods were able to detect a wide range of endogenous metabolites. • Comprehensive metabolite profiling is offered by 2D-C18 and 2D-silica based methods. • Metabolite features of each extraction method are statistically compared.
a r t i c l e
i n f o
Article history: Received 6 July 2013 Received in revised form 8 October 2013 Accepted 11 October 2013 Available online 19 October 2013 Keywords: Gas chromatography–mass spectrometry Metabolite profiling Extraction methods Solid phase extraction Human plasma
a b s t r a c t For the comprehensive metabolite profiling of human plasma, sample preparation is a crucial step. In this investigation, we have compared 10 different extraction techniques for metabolite profiling by GC–MS. Six one-dimensional (1D) and four two-dimensional (2D) extraction techniques involving solvent precipitation, molecular weight cut off tube (MWCOT) and solid phase extraction (SPE) by using silica, RP C18, cation and anion were investigated. Pooled samples of 50 Healthy Male Plasma (HMP), 50 Healthy Female Plasma (HFP) and 100 Healthy Pakistani Plasma (HPP) were subjected to these extraction methods for comparison purposes. Metabolites obtained were identified through NIST mass spectral (Wiley registry), METLIN and Fiehn RTL libraries. XCMS Software was used for the detection of metabolic features, retention time correction, alignment, annotation and statistical analysis in each method. 116–34 peaks were detected by various methods and approx 33% of the peaks were characterized in each method. Hierarchical clustering of the 10 extraction methods showed a low similarity index (50.1%) which indicated different chemical nature of metabolites, resulting from different methods. Venn diagram highlights the GC–MS peaks (33–77%) common in various methods. Metabolites which were different in male and
Abbreviations: HMP-P, Healthy Male Plasma-Pool; HFP-P, Healthy Female Plasma-Pool; HPP-P, Healthy Pakistani Plasma-Pool; HMPG1-G4-P, Healthy Male Plasma Group 1-Group 4-Pool; HFPG1-G4-P, Healthy Female Plasma Group 1-Group 4-Pool; SPE, solid phase extraction; MWCOT, molecular weight cut off tube; Si, silica. ∗ Corresponding author at: Dr. Panjwani Center for Molecular Medicine and Drug Research, International Center for Chemical and Biological Sciences, University of Karachi, Karachi 75270, Pakistan. Tel.: +92 021 34824924/4819010; fax: +92 021 34819018 9. E-mail address: [email protected] (S.G. Musharraf). 0003-2670/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.aca.2013.10.025
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female groups were detected using a threshold value of p ≤ 0.0001, q ≤ 0.001 and fold change ≥3 by employing Welch’s t-test and identified through METLIN. Results indicated that 2D-C18 and 2D-silica offers a comprehensive metabolite profile in term of reproducibility, number of peaks and difference in metabolite pattern of male and female. © 2013 Elsevier B.V. All rights reserved.
1. Introduction
2. Materials and methods
Advancement in omics technology can lead to new biomarker identification for most of the diseases through genotypic and phenotypic level alteration. Genomics, transcriptomics and proteomics have long been applied for biomarker detection [1–3]. Recently, metabolomics is increasing interest in the diagnosis of a number of pathological conditions [4–8]. Identification and measurement of the metabolites, synthesized by a biological system, the metabolome, plays an important role in the assessment of genetic functions [9–11]. In metabolomics, diverse functional groups are present, ranging from volatile alcohols, ketones, amines, organic acids to complex lipids, carbohydrates and other secondary metabolites. The wide differences in chemical properties of the metabolites and their very low concentrations between milli to picomoles creates a major challenge in developing a generic, robust and reproducible global profiling methods [12]. Recent advances in NMR, GC/MS and LC/MS techniques have enabled the use of more global metabolomic approaches for the identification of novel biomarkers for specific diseases as well as new targets for drug discovery and development [13–15]. Among the recent techniques, GC/MS proved to be a significantly useful method due to its high sensitivity and resolution, reproducibility and cost effectiveness. Moreover, in comparison to LC/MS, the availability of a large GC/MS electron impact (EI) spectral library further aids the identification of biomarkers in various pathological conditions [16]. For the determination of the global metabolite profile of human plasma, sample preparation is a major factor [17–19]. Currently metabolites are extracted from plasma either with acetonitrile [20–22], ethanol [23,24] or methanol [25–27], followed by derivatization and GC/MS analysis. The effects of extraction solvents, derivatization protocol and extraction conditions on the human blood plasma metabolome by GC/MS has studied [26] while the efficiency of various solvents (methanol, ethanol, acetonitrile, acetone, chloroform) for metabolite extraction from mammalian cell culture have also evaluated [27]. Solid-phase extraction (SPE) technique and molecular weight cutoff tube has emerged as an alternative to solvent based extraction because strongly proteinbound metabolites are reluctant to recover by solvent precipitation method. Protein precipitation has been compared via methanol and acetonitrile with reversed phase SPE for plasma metabolite extraction followed by UPLC–MS analysis [28]. Similarly, a protocol for metabolites extraction of E. coli was also developed using acids, organic solvents and molecular weight cutoff tube [29]. In the present study, 10 different extraction methods were employed for metabolite enrichment. These small molecular weight metabolites posses physicochemical properties and acid/base characteristics. To resolve these analytes prior to GCMS detection, various 1D (one dimensional) or one step and 2D (two dimensional) or two steps extraction approaches were used including solvent precipitation, molecular weight cut off tube (MWCOT), silica, C-18, cation and anion SPEs. A comparison of the above mentioned approaches for metabolomic analysis of plasma have not been made yet to the best of our knowledge. Comparison was made, based on the numbers and types of metabolites, reproducibility and similarly index.
2.1. Solvents and reagents All solvents used for GC–MS analysis were of analytical grade. Methanol, n-hexane and ammonium hydroxide were purchased from Tedia (Tedia way, Fairfield, USA), while isopropanol and HCl (37%) were purchased from Fisher Scientific (Loughborough, Leicestershire, U.K.), formic acid and myristic-d27 acid were purchased from Sigma–Aldrich (Steinheim, Germany and St. Louis, MO, USA, respectively). BSTFA (N,O-bis (trimethylsilyl)trifluoroacetamide) with 1% TMCS (trimethylchlorosilane) and methoxylamine hydrochloride (98+%) were purchased from Acros Organic (New Jersey, USA). Deionized water (Milli-Q) was used throughout the study (Millipore, Billerica, MA, USA). 2.2. Sample collection statistics and pooling strategy Blood samples of total 100 subjects (50 male and 50 female) with body mass index 21.335 ± 5.2 kg m−2 in the age range of 20 to above 50 were collected from Karachi, Pakistan with consent. All the subjects were non-smokers, healthy and none were taking any prescribed medication. About 8 mL of the blood was drawn in the morning from the overnight fasting volunteers in BD Vacutainer tubes (BD Franklin Lakes, NJ, USA, REF 367856), containing K2 ethylenediaminetetraacetic acid as an anticoagulant. Plasma was separated immediately by centrifugation at 4500 rpm for 10 min at 4 ◦ C. Finally, the plasma was aliquoted and frozen at −80 ◦ C. Code was given to each sample. Sample collection description and codes are mentioned in Table S1 of supporting information. Blood sample of 100 healthy volunteers was pooled in three steps and named as Healthy Pakistani Plasma-Pool (HPP-P). Healthy Pakistani PlasmaPool (HPP-P) was prepared by 3 pooling steps. First the healthy male and female plasma-pool i.e. (HMPG1-4-P and HFPG1-4-P) of each age group was prepared. In the second pooling step, the healthy male and female plasma-pool, i.e. (HMP-P and HFP-P) were prepared. Finally, both healthy male and female pooled plasma was pooled to obtain HPP-P. The pooling strategy and details of each step are shown in Fig. 1. HPP-P, HMP-P and HFP-P samples were selected for further screening. The samples were kept at −80 ◦ C until analysis. 2.3. Sample preparation The samples were prepared by using various extraction approaches as mentioned below: 2.3.1. For 1D-solvent precipitation (Method-1) For the solvent precipitation method, aliquots of 100 L of plasma were mixed with 800 L of solvent MeOH, 20 L of internal standard myristic-d27 acid (1 mg mL−1 stock solution) was added, vortexed for 30 s and left on ice for 2 h for complete protein precipitation. The precipitated proteins were then removed by centrifugation at 12,000 rpm for 10 min (Eppendorf Centrifuge 5804C/R). Aliquots (400 L) of the resulting clear supernatants were then transferred into Eppendorf tubes and evaporated under N2 steam at room temperature. The dry samples were stored at 4 ◦ C for analysis.
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Fig. 1. Sample pooling Strategy, HMP-P (Healthy Male Plasma-Pool), HFP-P (Healthy Female Plasma-Pool), HPP-P (Healthy Pakistani Plasma-Pool).
2.3.2. For 1D-C18 SPE (Method-2) Samples were extracted onto a C18 SPE cartridge (Strata C18-E, 55 m pore size, 70 Å particle, 100 mg sorbent/1 mL Phenomenex, USA). Prior to extraction, the phase was activated with 2× 300 L of MeOH and then further conditioned with 2× 300 L of H2 O. Aliquots of 400 L of diluted plasma (100 L plasma diluted with 800 L H2 O and 20 L of internal standard myristic-d27 acid) were loaded onto the SPE and drawn through the solid phase under vacuum. The phase was then washed with 300 L water and eluted with 600 L of MeOH. The eluate was evaporated under N2 at room temperature. The dry samples were stored at 4 ◦ C until analysis. The SPE extractions were performed on solid phase extraction vacuum manifold AH0-7502 Phenomenex (USA). 2.3.3. For 1D-silica SPE (Method-3) Samples were extracted onto a silica SPE cartridge (Strata SI-1 Silica, 55 m pore size, 70 Å particle, 100 mg sorbent/1 mL Phenomenex, USA). Prior to extraction, the phase was activated with 2× 300 L of MeOH and then further conditioned with 2× 300 L of n-hexane. Aliquots of 400 L of diluted plasma (100 L plasma diluted with 800 L H2 O and 20 L of internal standard myristicd27 acid) were loaded onto the SPE and drawn through the solid phase under vacuum. The phase was then washed with 2× 300 L of 5% isopropanol in hexanes and eluted with 600 L of hexanes: isopropanol (1:1). The eluate was evaporated with N2 at room temperature. The dry samples were stored at 4 ◦ C until analysis. 2.3.4. For 1D-cation SPE (Method-4) Samples were extracted onto a mix mode cation SPE cartridge (Strata Screen C, 55 m pore size, 70 Å particle, 100 mg sorbent/1 mL Phenomenex, USA). Prior to extraction, the phase was activated with 2× 300 L of MeOH and then further conditioned with 2× 300 L of 0.1% acidic (formic acid) H2 O. Aliquots of 400 L of diluted plasma (100 L plasma diluted with 800 L H2 O and 20 L of internal standard myristic-d27 acid) were loaded onto the SPE and drawn through the solid phase under vacuum. The phase was then washed with 300 L of 0.1 M HCl in H2 O then with 300 L of 0.1 M HCl in CH3 COOH and eluted with 600 L of 5% NH4 OH. The eluate was evaporated with N2 at room temperature. The dry samples were stored at 4 ◦ C until analysis. 2.3.5. For 1D-anion SPE (Method-5) Samples were extracted onto mix mode anion exchange SPE cartridge (Strata Screen A, 55 m pore size, 70 Å particle, 100 mg sorbent/1 mL Phenomenex, USA). Prior to extraction, the phase was activated with 2× 300 L of MeOH and then further conditioned with 2× 300 L of H2 O. Aliquots of 400 L of diluted plasma (100 L plasma diluted with 800 L H2 O and 20 L of internal standard myristic-d27 acid) were loaded onto the SPE and drawn through the solid phase under vacuum. The phase was then washed with
300 L of 25 mM CH3 COONH4 then with 300 L MeOH and eluted with 600 L of 5% formic acid in MeOH. The eluate was evaporated with N2 at room temperature. The dry samples were stored at 4 ◦ C until analysis. 2.3.6. For 1D-MWCOT (Method-6) Samples were ultra filtered with a MWCOT (Molecular Weight Cut Off Tube pore size 1 kDa, Sigma–Aldrich, Steinheim, Germany). First the phase were activated with water and tube were inverted to flow water from pore by centrifuge at 5000 rpm for 5 min. Aliquots of 400 L of diluted plasma (100 L plasma diluted with 800 L H2 O and 20 L of internal standard myristic-d27 acid) was loaded and filtrate were collected by centrifuge at 5000 rpm for 5 min. The filtrates were evaporated with N2 at room temperature. The dry samples were stored at 4 ◦ C until analysis. 2.3.7. For 2D-approach In all the 2D methods, including 2D-C18 (method-7), 2D-silica (method-8), 2D-cation (method-9) and 2D-anion (method-10), first the solvent precipitation was carried out as mentioned in Method1 then 400 L of the resulting clear supernatants were subjected to SPE using C18, silica, cation and anion stationary phase. Then rest of the process was the same as discussed for 1D SPE. 2.4. Derivatization and GC/MS analysis The dried extract of all the methods were derivatized subsequently by adding 30 L methoxylamine hydrochloride in pyridine (15 g/L), vortexed and left for 16 h (oximation time was already optimized [26]) at room temperature. Then BSTFA was added with 1% TCMS and placed at room temperature for 60 min to form trimethylsilyl (TMS) derivatives [26]. For all the samples, 1.0 L of derivatized extract was injected for GC/MS analysis. Before injection, samples were centrifuged at 2000 rpm for 2 min to remove any solid particle. GC/MS Analyses were performed on a 7890A gas chromatography (Agilent technologies, USA) equipped with an Agilent Technology GC sampler 120 (PAL LHX-AG12) autosampler and coupled to an Agilent 7000 Triple Quad system (Agilent technologies, USA). An HP-5MS 30 m-250 mm (i.d.) fused-silica capillary column (Agilent J&W Scientific, Folsom, CA, USA), chemically bonded with a 5% diphenyl 95% dimethylpolysiloxane cross-linked stationary phase (0.25 mm film thickness) was used. Helium was used as the carrier gas at 1.0 mL min and the sample was injected in splitless mode. The injector and source temperatures were 250 ◦ C. The oven temperature was initially maintained at 40 ◦ C, and was then increased at 10 ◦ C min to 300 ◦ C and retained at 300 ◦ C for 9 min. In post run, temperature was further increased to 305 ◦ C, for remaining 1 min. Retention time was locked to myristic-d27 acid according to the published protocol at 15.168 min [30]. Electron ionization (EI) is used as an ionization source for the GC/MS
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analysis at 70 eV. Data is acquired in the full scan mode from m/z 50 to 650 with a scan time of 0.5 s. Three replicate of each sample was performed then blank (hexane) was run in between each sample to remove any contamination. Perfluorotributylamine (PFTBA) was used for mass calibration Data processing was performed by using the Agilent Mass Hunter Qualitative Analysis (version B.04.00).
2.5. GC/MS data preprocessing and statistical analysis Metabolite profiling of blood samples were analyzed using the optimized GC/MS assay. Data processing was performed using the Agilent Mass Hunter Qualitative Analysis (version B.04.00). Data was normalized to internal standard. Peak integration and deconvolution were performed either directly on Mass Hunter or after export as mzData files to online XCMS software. For heat map and distribution of plasma metabolites of all the 10 methods, data was processed through Mass Hunter. The chromatographic deconvolution parameters on Mass Hunter are set as follows: SNR threshold 10.0, RT window size factor: 100.0, left m/z delta: 0.3 (amu), right m/z delta: 0.7 (amu), excluded m/z 28 (amu), sharpness threshold: 25.0% and chromatogram deconvolution compound filter parameter as relative area 1.0% of largest peak, absolute area 5000 counts. Putatively identity of GC/MS detected peaks was established by comparing the mass spectra of the peaks with those available in the NIST mass spectral (Wiley registry) and Fiehn RTL libraries. The peak lists obtained by Mass Hunter qualitative analysis report were further processed to construct a heatmap for some of the identified metabolite through Qlucore Software version 2.3. Distribution of identified plasma metabolites from all the 10 methods was plotted on Microsoft Excel 2007. To examine similarities in all 10 methods, GC/MS data of the six 1D and four 2D methods were first aligned through XCMS and a dendrogram was then produced by applying a hierarchical clustering algorithm (by applying Correlation Coefficient Distance, Complete Linkage) by Minitab software. Raw GC/MS data were converted into mzData on Mass Hunter and processed using online XCMS software. The XCMS parameters were default setting except for the following p value ≤1 × 10−4 and fold change ≥3. XCMS aligned data was further used for statistical analysis on Minitab software version 11.12. The average percent relative standard deviation (%RSD) for the intensity of all detected metabolite features from each method was evaluated. Welch’s t-test was employed to detect metabolites which were significantly different in male and female groups using a threshold value of p ≤ 0.0001, q ≤ 0.001 and fold change ≥3 and METLIN was used for the putative identification of these metabolite using XCMS software [31,32]. Metabolite features, observed in the different methods were evaluated through Venn diagram.
2.6. Method optimization Various parameters involved in sample preparation and GC–MS analysis were optimized. To optimize the protein precipitation, acetonitrile and methanol were checked for the extraction of the metabolite while extraction time for metabolites was optimized using 30 and 120 min. The derivatization step was optimized at different temperatures (30–90 ◦ C) and times (0.66–16 h) for oximation and silylation. Various instrumental parameters were also optimized for better separation of peaks. Different injection modes including splitless and split with various ratio (1:10, 1:20, 1:30, and 1:40) were also optimized. Similarly, two different temperature programing were also evaluated. In one program, initial oven temperature was adjusted at 40 ◦ C and increased at 10 ◦ C min to 300 ◦ C.
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In another temperature programming, the initial oven temperature was adjusted at 70 ◦ C and increased at 5 ◦ C min to 300 ◦ C. 3. Results and discussion Ten different extraction techniques were evaluated for metabolites extraction from human plasma and their affect on the numbers and types of metabolites as well as reproducibility. Methods were applied on pooled plasma sample of 100 healthy individuals named as Healthy Pakistani Plasma-Pool (HPP-P) followed by GC–MS analysis. Pooling of biological samples have been applied to investigate various types of analytes [33]. Metabolite features of each method were analyzed by XCMS online software. A metabolite feature was defined as a mass spectral peak in the mass region of m/z 50–650 with a signal-to-noise ratio exceeding 10:1. Retention time, m/z, and intensity values were recorded for each detected metabolite feature. Using this software, 1000 to 2000 mass features were detected by various extraction techniques. A “reproducible feature” was defined as a metabolite feature that was detected in all three GC/MS runs for a given extraction method. Individual features can be plotted as EICs to allow for visual comparison of alignment. An example of a well-aligned metabolite feature detected from all 30 runs is presented in Fig. S1 of supporting information. 3.1. Method optimization For protein precipitation, methanol was found better in terms of metabolites, as reported previously [25–28]. Best result was obtained with 2 h extraction time in term of high number of peaks and high precision. Samples were derivatized with BSTFA after oximation with methoxamine hydrochloride [19,27,34]. By introducing an oximation step prior to silylation, reduces the number of sugar tautomers [35]. Oximation (16 h) and silylation (1 h) were found to be the best in terms of the number of metabolites as previously reported [30]. Separation efficiency, peak symmetry and analysis time were optimized by changing various GC parameters including injection modes, initial temperature of oven and temperature gradient rate. Splitless mode with an initial temperature of 40 ◦ C and ramp time of 10 ◦ C min were found to be the best for the analysis. All other parameters of GC/MS analysis are same as described in the previous section. A total 140 peaks in 2D-C18, 115 in 1D-anion, 120 in 2D-anion, 30 in 2D-cation, 120 in 2D-Si, 90 in 1D-C18, 80 in 1D-Si, 69 in 1D-cation and 52 in solvent precipitation were detected using the GC chromatogram with intensity >1 × 106 . However GC separation still contained some overlapping peaks, therefore deconvolution was applied prior to library search. 3.2. Method reproducibility Visually, total ion chromatogram (TIC) of all 10 extraction techniques showed different peak patterns from 100 pooled plasma sample HPP-P (Figure S2 of supporting information). The standard deviation and percent relative standard deviation (%RSD) for the intensity of all detected metabolite features (1000–2000) after the XCMS alignment from each method were calculated. %RSD of each metabolite feature intensity was obtained from three replicates, where the average %RSD is the average value for all detected features in an individual method. Overall, 2D-Si, solvent induced precipitation, 2D-C18, 1D-cation, 1D-anion and 1D-MWCOT showed the least variations in feature intensity with an average RSD of i.e. 8.4, 10.0, 14.9, 11.5, 14.7 and 14.5%, respectively. 2D-Anion, 1D C-18 and 1D-Si showed %RSD of 16.4, 18.4% and 19.1%, respectively. It is important to note that as this is an average of 1000–2000 metabolite features, therefore individual metabolite %RSD values can greatly vary within each method [25]. For example, RSD values ranged from 1.2 to 137% within the 2D-Si samples
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Fig. 2. Statistical analysis of the three of the compounds identified in the different extraction method. Each bar represents standard deviation of the average of three independent run in each method.
with 1281 metabolite features. 2D-Si, solvent precipitation, 2DC18, 1D-cation, 1D-anion, 2D-cation and 1D-MWCOT showed RSDs of 30%, indicating that pooling only partially nullified the variance and it enhanced the common features which reduce the variation of data points in the 2nd component of PCA in the pooled samples.
Fig. 6. Venn diagrams highlighting the common GC–MS peaks observed in HPP-P sample with each extraction methods. In each case 2D-Si have been used as the benchmark.
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Fig. 7. (A) Score plot of Pakistani pooled (HPP-P), male pooled (HMP-P) and female pooled (HFP-P) samples, all the align feature (1615 metabolite feature) were plotted. (B) Score plot between Pakistani pooled (HPP-P) and individual samples, all the align feature (900 metabolite feature) were plotted. (C) Score plot between male pooled (HMP-P) and individual male samples, all the align feature (1442 metabolite feature) were plotted. (D) Score plot between female pooled (HFP-P) and individual female samples, all the align feature (1903 metabolite feature) were plotted.
4. Conclusion
Appendix A. Supplementary data
Metabolite profiling needs a comprehensive, straightforward, reproducible and efficient sample preparation method which can cover a wide range of metabolites. The results of the current study suggest that the sample preparation protocols based on 1D and 2D extraction, followed by GC/MS analysis were able to detect endogenous metabolites belonging to different chemical classes. Higher number of metabolites were detected in 2D-Si. Overall method reproducibility of most of the extraction technique is within RSDs
