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Current Metabolomics and Systems Biology (Discontinued)

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ISSN (Print): 2666-3384
ISSN (Online): 2666-3392

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Research Article

Comparison of Different Sample Preparation Techniques for Untargeted Metabolomics Utilizing Q-TOF LC/MS and MetaboAnalyst 4.0

Author(s): Ozan Kaplan, Engin Koçak and Mustafa Çelebier*

Volume 8, Issue 1, 2021

Published on: 14 June, 2020

Page: [53 - 60] Pages: 8

DOI: 10.2174/2666338408999200614155440

Price: $65

Abstract

Background: Profiling the whole metabolome with a single injection is not an easy process because the chemical and physical properties of metabolites are totally different with each other and the analytical methodologies and data mining procedures need lots of effort to make such an approach in real. This reality leads researchers to select an already applied methodology for metabolite profiling and analyze the samples through identical techniques.

Objective: In this study, it was focused on answer the question the sample preparation techniques on human blood samples prior to Q-TOF LC/MS analysis affect the number of detectable peaks and analyze the matched metabolites for these peaks. The results were compared with each other.

Methods: Precipitation of proteins with methanol, ultrafiltration (Amicon® Ultra 3 kDa 0.5 mL Centrifugal Filters), liquid-phase extraction (EXtrelut® NT 3 cartridges) and solid-phase extraction (Supelco HybridSPE®-Phospholipid Cartridge) were used for sample preparation on commercial pooled plasma samples. C18 column (Agilent Zorbax 1.8 μM, 50 x 2.1 mm) was used as the chromatography column. Q-TOF LC/MS analysis was performed on positive ionization mode. XCMS and MetaboAnalyst 4.0 - MS Peaks to Pathways utility were used to evaluate the raw data.

Results: Although the number of detected peaks through precipitation of proteins with methanol was the highest one (624 peaks), the detected peaks observed through ultrafiltration- based sample preparation technique matched with the highest number of metabolite peaks (151 metabolites). The number of the matched peaks with metabolites on liquid phase extraction (81 metabolites) was higher than the ones for solid phase extraction (29 metabolites).

Conclusion: The results in this study may provide a novel perspective for analytical chemists working with clinicians to select their sample preparation technique prior to Q-TOF LC/MS based untargeted metabolomic approaches.

Keywords: Metabolomics, XCMS, MetaboAnalyst, Q-TOF LC/MS, sample preparation, metabolic pathway analysis.

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[1]
Dunn, W.B. Current trends and future requirements for the mass spectrometric investigation of microbial, mammalian and plant metabolomes. Phys. Biol., 2008, 5(1), 011001.
[http://dx.doi.org/10.1088/1478-3975/5/1/011001] [PMID: 18367780]
[2]
Dunn, W.B.; Erban, A.; Weber, R.J.; Creek, D.J.; Brown, M.; Breitling, R.; Hankemeier, T.; Goodacre, R.; Neumann, S.; Kopka, J. Mass appeal: Metabolite identification in mass spectrometry-focused untargeted metabolomics. Metabolomics, 2013, 9(1), 44-66.
[http://dx.doi.org/10.1007/s11306-012-0434-4]
[3]
Alonso, A.; Marsal, S.; Julià, A. Analytical methods in untargeted metabolomics: State of the art in 2015. Front. Bioeng. Biotechnol., 2015, 3, 23.
[http://dx.doi.org/10.3389/fbioe.2015.00023] [PMID: 25798438]
[4]
Drouin, N.; Rudaz, S.; Schappler, J. Sample preparation for polar metabolites in bioanalysis. Analyst (Lond.), 2017, 143(1), 16-20.
[http://dx.doi.org/10.1039/C7AN01333G] [PMID: 29215666]
[5]
Reyes-Garcés, N.; Gionfriddo, E. Recent developments and applications of solid phase microextraction as a sample preparation approach for mass-spectrometry-based metabolomics and lipidomics. Trends Analyt. Chem., 2019, 113, 172-181.
[http://dx.doi.org/10.1016/j.trac.2019.01.009]
[6]
Gika, H.; Theodoridis, G. Sample preparation prior to the LC-MS-based metabolomics/metabonomics of blood-derived samples. Bioanalysis, 2011, 3(14), 1647-1661.
[http://dx.doi.org/10.4155/bio.11.122] [PMID: 21756097]
[7]
Tulipani, S.; Llorach, R.; Urpi-Sarda, M.; Andres-Lacueva, C. Comparative analysis of sample preparation methods to handle the complexity of the blood fluid metabolome: when less is more. Anal. Chem., 2013, 85(1), 341-348.
[http://dx.doi.org/10.1021/ac302919t] [PMID: 23190300]
[8]
Skov, K.; Hadrup, N.; Smedsgaard, J.; Frandsen, H. LC-MS analysis of the plasma metabolome--a novel sample preparation strategy. J. Chromatogr. B Analyt. Technol. Biomed. Life Sci., 2015, 978-979, 83-88.
[http://dx.doi.org/10.1016/j.jchromb.2014.11.033] [PMID: 25531874]
[9]
Çelebier, M.; Ibáñez, C.; Simó, C.; Cifuentes, A. A foodomics approach: CE-MS for comparative metabolomics of colon cancer cells treated with dietary polyphenols.Protein Electrophoresis; Springer, 2012, pp. 185-195.
[http://dx.doi.org/10.1007/978-1-61779-821-4_15]
[10]
Eliasson, M.; Rännar, S.; Madsen, R.; Donten, M.A.; Marsden-Edwards, E.; Moritz, T.; Shockcor, J.P.; Johansson, E.; Trygg, J. Strategy for optimizing LC-MS data processing in metabolomics: A design of experiments approach. Anal. Chem., 2012, 84(15), 6869-6876.
[http://dx.doi.org/10.1021/ac301482k] [PMID: 22823568]
[11]
Kaplan, O.; Çelebier, M. Evaluation of recent data processing strategies on Q-TOF LC/MS based untargeted metabolomics. Mass Spectrometry Lett, 2020, 11(1), 1-5.
[12]
Holman, J. D.; Tabb, D. L.; Mallick, P. Employing ProteoWizard to convert raw mass spectrometry data. Curr. Prot. Bioinformatics, 2014, 46(1), 13.24.1-13.24.9.
[http://dx.doi.org/10.1002/0471250953.bi1324s46]
[13]
Tautenhahn, R.; Patti, G.J.; Rinehart, D.; Siuzdak, G. XCMS Online: A web-based platform to process untargeted metabolomic data. Anal. Chem., 2012, 84(11), 5035-5039.
[http://dx.doi.org/10.1021/ac300698c] [PMID: 22533540]
[14]
Libiseller, G.; Dvorzak, M.; Kleb, U.; Gander, E.; Eisenberg, T.; Madeo, F.; Neumann, S.; Trausinger, G.; Sinner, F.; Pieber, T.; Magnes, C. IPO: A tool for automated optimization of XCMS parameters. BMC Bioinformatics, 2015, 16(1), 118.
[http://dx.doi.org/10.1186/s12859-015-0562-8] [PMID: 25888443]
[15]
Kamburov, A.; Cavill, R.; Ebbels, T.M.; Herwig, R.; Keun, H.C. Integrated pathway-level analysis of transcriptomics and metabolomics data with IMPaLA. Bioinformatics, 2011, 27(20), 2917-2918.
[http://dx.doi.org/10.1093/bioinformatics/btr499] [PMID: 21893519]
[16]
Raterink, R.J.; Lindenburg, P.W.; Vreeken, R.J.; Ramautar, R.; Hankemeier, T. Recent developments in sample-pretreatment techniques for mass spectrometry-based metabolomics. Trends Analyt. Chem., 2014, 61, 157-167.
[http://dx.doi.org/10.1016/j.trac.2014.06.003]
[17]
Sitnikov, D.G.; Monnin, C.S.; Vuckovic, D. Systematic assessment of seven solvent and solid-phase extraction methods for metabolomics analysis of human plasma by LC-MS. Sci. Rep., 2016, 6(1), 38885.
[http://dx.doi.org/10.1038/srep38885] [PMID: 28000704]
[18]
Becker, S.; Kortz, L.; Helmschrodt, C.; Thiery, J.; Ceglarek, U. LC-MS-based metabolomics in the clinical laboratory. J. Chromatogr. B Analyt. Technol. Biomed. Life Sci., 2012, 883-884, 68-75.
[http://dx.doi.org/10.1016/j.jchromb.2011.10.018] [PMID: 22074957]
[19]
Liu, R.; Chou, J.; Hou, S.; Liu, X.; Yu, J.; Zhao, X.; Li, Y.; Liu, L.; Sun, C. Evaluation of two-step liquid-liquid extraction protocol for untargeted metabolic profiling of serum samples to achieve broader metabolome coverage by UPLC-Q-TOF-MS. Anal. Chim. Acta, 2018, 1035, 96-107.
[http://dx.doi.org/10.1016/j.aca.2018.07.034] [PMID: 30224149]
[20]
Vuckovic, D. Current trends and challenges in sample preparation for global metabolomics using liquid chromatography-mass spectrometry. Anal. Bioanal. Chem., 2012, 403(6), 1523-1548.
[http://dx.doi.org/10.1007/s00216-012-6039-y] [PMID: 22576654]

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