Skip to main content
Log in

Optimizing Solvents and Derivatizing Agents for Metabolomic Profiling of Human Plasma Using GC–MS

  • Original
  • Published:
Chromatographia Aims and scope Submit manuscript

Abstract

Metabolites provide a rich source of information regarding individual physiological states influenced by differences in diet, disease, health, and lifestyle. Effective sample preparation is a crucial step for the development of a sensitive, effective, and robust analytical method. In the present study, the metabolite extraction and identification protocol was optimized to achieve a reliable sample preparation technique for human plasma metabolites using gas chromatography–mass spectrometry (GC–MS). We compared the response of different sample preparation techniques with several extraction solvents [chloroform (CHCl3), methanol (MeOH), acetonitrile (ACN), MeOH and ACN (50:50), MeOH/MeOH/water (MMW)] coupled with N, O-Bis (trimethylsilyl) trifluoroacetamide with 1% trimethylchlorosilane (BSTFA + 1% TMCS), and N-Methyl-N-(trimethylsilyl) trifluoroacetamide with 1% trimethylchlorosilane (MSTFA + 1% TMCS) derivatizing reagents. The suitability of the extraction solvent and derivatizing reagent was assessed for human plasma metabolite identification. We conclude that extraction of metabolites using methanol/methanol/water and 50 min silylation at 70 °C with N-methyl-N-(trimethylsilyl) trifluoroacetamide with 1% trimethylchlorosilane is efficient combination for proper derivatization and identification of metabolites. This protocol resulted in identifying a total of 87 metabolites including various amino acids, carboxylic acids, fatty acids, and polysaccharides. The optimized method provides an efficient, robust, and reproducible analytical method for metabolomic analysis in human plasma.

Graphical Abstract

Schematic representation of metabolite extraction and analysis using gas chromatography mass spectrometry

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

Availability of Data and Materials

The detailed protocols, data, and material are available upon request.

References

  1. Wang JH, Byun J, Pennathur S (2010) Analytical approaches to metabolomics and applications to systems biology. Semin Nephrol 30(5):500–511. https://doi.org/10.1016/j.semnephrol.2010.07.007

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Zhang A, Sun H, Wang P, Han Y, Wang X-J (2011) Modern analytical techniques in metabolomics analysis. Analyst 137:293–300. https://doi.org/10.1039/c1an15605e

    Article  CAS  PubMed  Google Scholar 

  3. Liu X, Locasale JW (2017) Metabolomics: a primer. Trends Biochem Sci 42(4):274–284. https://doi.org/10.1016/j.tibs.2017.01.004

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Chen Y, Xu J, Zhang R, Abliz Z (2016) Methods used to increase the comprehensive coverage of urinary and plasma metabolomes by MS. Bioanalysis 8(9):981–997. https://doi.org/10.4155/bio-2015-0010

    Article  CAS  PubMed  Google Scholar 

  5. Moros G, Chatziioannou AC, Gika HG, Raikos N, Theodoridis G (2016) Investigation of the derivatization conditions for GC–MS metabolomics of biological samples. Bioanalysis 9(1):53–65. https://doi.org/10.4155/bio-2016-0224

    Article  CAS  Google Scholar 

  6. Kvitvang H, Andreassen T, Adam T, Villas-Bôas S, Bruheim P (2011) Highly sensitive GC/MS/MS method for quantitation of amino and nonamino organic acids. Anal Chem 83:2705–2711. https://doi.org/10.1021/ac103245b

    Article  CAS  PubMed  Google Scholar 

  7. Wishart DS, Jewison T, Guo AC, Wilson M, Knox C, Liu Y, Djoumbou Y, Mandal R, Aziat F, Dong E, Bouatra S, Sinelnikov I, Arndt D, Xia J, Liu P, Yallou F, Bjorndahl T, Perez-Pineiro R, Eisner R, Allen F, Neveu V, Greiner R, Scalbert A (2013) HMDB 3.0–the human metabolome database in 2013. Nucleic Acids Res 41:D801-807. https://doi.org/10.1093/nar/gks1065

    Article  CAS  PubMed  Google Scholar 

  8. Klupczyńska A, Dereziński P, Kokot ZJ (2015) Metabolomics in medical sciences–trends challenges and perspectives. Acta Poloniae Pharm 72(4):629–641

    PubMed  Google Scholar 

  9. Dunn WB, Ellis DI (2005) Metabolomics: current analytical platforms and methodologies. TrAC Trends Anal Chem 24(4):285–294. https://doi.org/10.1016/j.trac.2004.11.021

    Article  CAS  Google Scholar 

  10. Yin P, Lehmann R, Xu G (2015) Effects of pre-analytical processes on blood samples used in metabolomics studies. Anal Bioanal Chem 407(17):4879–4892. https://doi.org/10.1007/s00216-015-8565-x

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Paiva M, Menezes H, Cardeal Z (2014) Sampling and analysis of metabolomes in biological fluids. Analyst 139:3683. https://doi.org/10.1039/c4an00583j

    Article  CAS  Google Scholar 

  12. Shriver LP (2016) Mass spectrometry-based metabolomics: a practical guide. J Am Soc Mass Spectrom 27(1):1–2. https://doi.org/10.1007/s13361-015-1246-3

    Article  CAS  Google Scholar 

  13. Khamis MM, Adamko DJ, El-Aneed A (2017) Mass spectrometric based approaches in urine metabolomics and biomarker discovery. Mass Spectrom Rev 36(2):115–134. https://doi.org/10.1002/mas.21455

    Article  CAS  PubMed  Google Scholar 

  14. Zhou B, Xiao JF, Tuli L, Ressom HW (2012) LC-MS-based metabolomics. Mol BioSyst 8(2):470–481. https://doi.org/10.1039/c1mb05350g

    Article  CAS  PubMed  Google Scholar 

  15. Lopes AS, Cruz EC, Sussulini A, Klassen A (2017) Metabolomic strategies involving mass spectrometry combined with liquid and gas chromatography. Adv Exp Med Biol 965:77–98. https://doi.org/10.1007/978-3-319-47656-8_4

    Article  CAS  PubMed  Google Scholar 

  16. Gowda GAN, Djukovic D (2014) Overview of mass spectrometry-based metabolomics: opportunities and challenges. Methods Mol Biol 1198:3–12. https://doi.org/10.1007/978-1-4939-1258-2_1

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Alonso A, Marsal S, Julià A (2015) Analytical methods in untargeted metabolomics: state of the art in 2015. Front Bioeng Biotechnol 3:23–23. https://doi.org/10.3389/fbioe.2015.00023

    Article  PubMed  PubMed Central  Google Scholar 

  18. Rodríguez-Morató J, Pozo ÓJ, Marcos J (2018) Targeting human urinary metabolome by LC-MS/MS: a review. Bioanalysis 10(7):489–516. https://doi.org/10.4155/bio-2017-0285

    Article  CAS  PubMed  Google Scholar 

  19. NIST20: Updates to the NIST Tandem and Electron Ionization Spectral Libraries. National Institute of Standards and Technology ( June 11, 2020, Updated June 12, 2020)

  20. Dettmer K, Aronov PA, Hammock BD (2007) Mass spectrometry-based metabolomics. Mass Spectrom Rev 26(1):51–78. https://doi.org/10.1002/mas.20108

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Nezami Ranjbar MR, Luo Y, Di Poto C, Varghese RS, Ferrarini A, Zhang C, Sarhan NI, Soliman H, Tadesse MG, Ziada DH, Roy R, Ressom HW (2015) GC-MS based plasma metabolomics for identification of candidate biomarkers for hepatocellular Carcinoma in Egyptian Cohort. PLoS ONE 10(6):e0127299–e0127299. https://doi.org/10.1371/journal.pone.0127299

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Sogin EM, Puskás E, Dubilier N, Liebeke M (2019) Marine metabolomics: a method for nontargeted measurement of metabolites in seawater by gas chromatography-mass spectrometry. mSystems 4(6):e00638-e1619. https://doi.org/10.1128/mSystems.00638-19

    Article  PubMed  PubMed Central  Google Scholar 

  23. Naz S, Moreira dos Santos DC, García A, Barbas C (2014) Analytical protocols based on LC-MS, GC-MS and CE-MS for nontargeted metabolomics of biological tissues. Bioanalysis 6(12):1657–1677. https://doi.org/10.4155/bio.14.119

    Article  CAS  PubMed  Google Scholar 

  24. Shareef A, Angove MJ, Wells JD (2006) Optimization of silylation using N-methyl-N-(trimethylsilyl)-trifluoroacetamide, N, O-bis-(trimethylsilyl)-trifluoroacetamide and N-(tert-butyldimethylsilyl)-N-methyltrifluoroacetamide for the determination of the estrogens estrone and 17alpha-ethinylestradiol by gas chromatography-mass spectrometry. J Chromatogr A 1108(1):121–128. https://doi.org/10.1016/j.chroma.2005.12.098

    Article  CAS  PubMed  Google Scholar 

  25. Pasikanti KK, Ho PC, Chan ECY (2008) Gas chromatography/mass spectrometry in metabolic profiling of biological fluids. J Chromatogr B 871(2):202–211. https://doi.org/10.1016/j.jchromb.2008.04.033

    Article  CAS  Google Scholar 

  26. Shareef A, Parnis CJ, Angove MJ, Wells JD, Johnson BB (2004) Suitability of N, O-bis(trimethylsilyl)trifluoroacetamide and N-(tert-butyldimethylsilyl)-N-methyltrifluoroacetamide as derivatization reagents for the determination of the estrogens estrone and 17alpha-ethinylestradiol by gas chromatography-mass spectrometry. J Chromatogr A 1026(1–2):295–300. https://doi.org/10.1016/j.chroma.2003.10.110

    Article  CAS  PubMed  Google Scholar 

  27. Salvatore M, Salvatore F (2015) A strategy for GC/MS quantification of polar compounds via their silylated surrogates: silylation and quantification of biological amino acids. J Analy Bioanal Techn 6:1–16. https://doi.org/10.4172/2155-9872.1000263

    Article  CAS  Google Scholar 

  28. Villas-Bôas SG, Smart KF, Sivakumaran S, Lane GA (2011) Alkylation or silylation for analysis of amino and non-amino organic acids by GC-MS? Metabolites 1(1):3–20. https://doi.org/10.3390/metabo1010003

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Abdel-Khalik J, Björklund E, Hansen M (2013) Simultaneous determination of endogenous steroid hormones in human and animal plasma and serum by liquid or gas chromatography coupled to tandem mass spectrometry. J Chromatogr B 928:58–77. https://doi.org/10.1016/j.jchromb.2013.03.013

    Article  CAS  Google Scholar 

  30. Fiehn O, Robertson D, Griffin J, van der Werf M, Nikolau B, Morrison N, Sumner LW, Goodacre R, Hardy NW, Taylor C, Fostel J, Kristal B, Kaddurah-Daouk R, Mendes P, van Ommen B, Lindon JC, Sansone S-A (2007) The metabolomics standards initiative (MSI). Metabolomics 3(3):175–178. https://doi.org/10.1007/s11306-007-0070-6

    Article  CAS  Google Scholar 

  31. Pang Z, Chong J, Zhou G, de Lima Morais DA, Chang L, Barrette M, Gauthier C, Jacques P-É, Li S, Xia J (2021) MetaboAnalyst 5.0: narrowing the gap between raw spectra and functional insights. Nucl Acids Res 49(1):388–396. https://doi.org/10.1093/nar/gkab382

    Article  CAS  Google Scholar 

  32. Moros G, Chatziioannou AC, Gika HG, Raikos N, Theodoridis G (2017) Investigation of the derivatization conditions for GC-MS metabolomics of biological samples. Bioanalysis 9(1):53–65. https://doi.org/10.4155/bio-2016-0224

    Article  CAS  PubMed  Google Scholar 

  33. Fang M, Ivanisevic J, Benton HP, Johnson CH, Patti GJ, Hoang LT, Uritboonthai W, Kurczy ME, Siuzdak G (2015) Thermal degradation of small molecules: a global metabolomic investigation. Anal Chem 87(21):10935–10941. https://doi.org/10.1021/acs.analchem.5b03003

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Fritsche-Guenther R, Gloaguen Y, Bauer A, Opialla T, Kempa S, Fleming CA, Redmond HP, Kirwan JA (2021) Optimized workflow for on-line derivatization for targeted metabolomics approach by gas chromatography-mass spectrometry. Metabolites 11(12):888. https://doi.org/10.3390/metabo11120888

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Funding

The laboratory of Dr. Ashutosh Shrivastava is supported by the King George’s Medical University Intramural Grant Award and a research grant from CCRH, Ministry of AYUSH, Government of India (Z.28015/01/2018-HPC-EMR-AYUSH-D). Alok Mishra is the recipient of senior research fellowship from the University Grant Commission, New Delhi, India.

Author information

Authors and Affiliations

Authors

Contributions

AS and AS conceptualized and planned the study. AS and AM conducted the experiments. AS, AS, and AM analyzed the data and wrote the manuscript. All authors agree with the final version of the manuscript.

Corresponding author

Correspondence to Ashutosh Shrivastava.

Ethics declarations

Conflict of Interest

The authors have No competing interests to declare.

Ethical Approval

The study was approved by the KGMU institutional ethics committee (Ref. Code: 107. ECM II B-Ph.D./P2). Informed consent was obtained from the subjects before collection of the samples.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 78 KB)

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Srivastava, A., Mishra, A. & Shrivastava, A. Optimizing Solvents and Derivatizing Agents for Metabolomic Profiling of Human Plasma Using GC–MS. Chromatographia 86, 523–534 (2023). https://doi.org/10.1007/s10337-023-04266-z

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10337-023-04266-z

Keywords

Navigation