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A review of strategies for untargeted urinary metabolomic analysis using gas chromatography–mass spectrometry

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Abstract

Background

Human urine gives evidence of the metabolism in the body and contains different metabolites at various concentrations. A number of analytical techniques including mass spectrometry (MS) and nuclear magnetic resonance (NMR) have been used to obtain metabolites levels in urine samples. However, gas chromatography–mass spectrometry (GC–MS) is one of the most widely used techniques for urinary metabolomics studies due to its higher sensitivity, resolution, reproducibility, reliability, relatively low cost and ease of operation compared to liquid chromatography–mass spectrometry and NMR.

Aim of Review

This review looks at various aspects of urine preparation prior to analysis by GC–MS including sample storage, urease pretreatment, derivatization, use of internal standard and quality control samples for data correction. In addition, most common types of inlet liners, ionization techniques and columns are discussed and a summary of mass analyzers are also highlighted. Lastly, the role of retention index in metabolite identification and data normalization methods are presented.

Key scientific concepts of review

The purpose of this review is summarizing methods of sample storage, pretreatment, and GC–MS analysis that are mostly used in urine metabolomics studies. Specific emphasis is given to the critical steps within the GC–MS urine metabolomics that those new to this field need to be aware of and the remaining challenges that require further attention and studies.

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References

  • Ahn, J. K., Kim, J., Hwang, J., Song, J., Kim, K. H., & Cha, H.-S. (2017). Urinary metabolomic profiling to identify potential biomarkers for the diagnosis of Behcet’s disease by gas chromatography/time-of-flight−mass spectrometry. International Journal of Molecular Sciences,18(11), 2309.

    Article  PubMed Central  CAS  Google Scholar 

  • Allen, F., Pon, A., Greiner, R., & Wishart, D. (2016). Computational prediction of electron ionization mass spectra to assist in GC/MS compound identification. Analytical Chemistry,88(15), 7689–7697.

    Article  CAS  PubMed  Google Scholar 

  • Aurelie Roux, E. A. T., Seguin, F., Olivier, M.-F., & Junot, C. (2014). Impact of collection conditions on the metabolite content of human urine samples as analyzed by liquid chromatography coupled to mass spectrometry and nuclear magnetic resonance spectroscopy. Metabolomics,11(5), 1095–1105.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Bernini, P., Bertini, I., Luchinat, C., Nincheri, P., Staderini, S., & Turano, P. (2011). Standard operating procedures for pre-analytical handling of blood and urine for metabolomic studies and biobanks. Journal of Biomolecular NMR,49(3–4), 231–243.

    Article  CAS  PubMed  Google Scholar 

  • Bhatia, A., Sarma, S. J., Lei, Z., & Sumner, L. W. (2019). UHPLC-QTOF-MS/MS-SPE-NMR: a solution to the metabolomics grand challenge of higher-throughput, confident metabolite identifications. In NMR-Based Metabolomics (pp. 113–133). Springer.

  • Bouatra, S., Aziat, F., Mandal, R., Guo, A. C., Wilson, M. R., Knox, C., et al. (2013). The human urine metabolome. PLoS ONE,8(9), e73076.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Broadhurst, D., Goodacre, R., Reinke, S. N., Kuligowski, J., Wilson, I. D., Lewis, M. R., et al. (2018). Guidelines and considerations for the use of system suitability and quality control samples in mass spectrometry assays applied in untargeted clinical metabolomic studies. Metabolomics,14(6), 72.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Bruheim, P., Kvitvang, H. F. N., & Villas-Boas, S. G. (2013). Stable isotope coded derivatizing reagents as internal standards in metabolite profiling. Journal of Chromatography A,1296, 196–203.

    Article  CAS  PubMed  Google Scholar 

  • Caban, M., & Stepnowski, P. (2018). Silylation of acetaminophen by trifluoroacetamide-based silylation agents. Journal of Pharmaceutical and Biomedical Analysis,154, 433–437.

    Article  CAS  PubMed  Google Scholar 

  • Cala, M., Aldana, J., Sánchez, J., Guio, J., & Meesters, R. J. W. (2018). Urinary metabolite and lipid alterations in Colombian Hispanic women with breast cancer: A pilot study. Journal of Pharmaceutical and Biomedical Analysis,152, 234–241.

    Article  CAS  PubMed  Google Scholar 

  • De Castro, M. D. L., & Ferna, M. A. (2012). Preparation of urine samples prior to targeted or untargeted metabolomics mass-spectrometry analysis. Trends in Analytical Chemistry,41, 75–85.

    Article  CAS  Google Scholar 

  • Chen, J., Xie, J., Zeng, L., Zhou, C., Zheng, P., & Xie, P. (2019). Urinary metabolite signature in bipolar disorder patients during depressive episode. Aging,11(3), 1008.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Chen, Y., Shen, G., Zhang, R., He, J., Zhang, Y., Xu, J., et al. (2013). Combination of injection volume calibration by creatinine and MS signals’ normalization to overcome urine variability in LC-MS-based metabolomics studies. Analytical Chemistry,85(16), 7659–7665.

    Article  CAS  PubMed  Google Scholar 

  • Chetwynd, A. J., Dunn, W. B., & Rodriguez-Blanco, G. (2017). Collection and preparation of clinical samples for metabolomics. In Metabolomics: from fundamentals to clinical applications (pp. 19–44). Springer.

  • Cho, K., Mahieu, N., Ivanisevic, J., Uritboonthai, W., Chen, Y.-J., Siuzdak, G., et al. (2014). isoMETLIN: A database for isotope-based metabolomics. Analytical Chemistry,86(19), 9358–9361.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Christou, C., Gika, H. G., Raikos, N., & Theodoridis, G. (2014). GC-MS analysis of organic acids in human urine in clinical settings: A study of derivatization and other analytical parameters. Journal of Chromatography B,964, 195–201.

    Article  CAS  Google Scholar 

  • Chun, E., Chan, Y., Pasikanti, K. K., & Nicholson, J. K. (2011). Global urinary metabolic profiling procedures using gas chromatography—mass spectrometry. Nature Protocols,6(9), 1483–1499.

    Article  CAS  Google Scholar 

  • Dagley, M. J., & McConville, M. J. (2018). DExSI: A new tool for the rapid quantitation of 13C-labelled metabolites detected by GC-MS. Bioinformatics,34(11), 1957–1958.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • De Paepe, E., Van Meulebroek, L., Rombouts, C., Huysman, S., Verplanken, K., Lapauw, B., et al. (2018). A validated multi-matrix platform for metabolomic fingerprinting of human urine, feces and plasma using ultra-high performance liquid-chromatography coupled to hybrid orbitrap high-resolution mass spectrometry. Analytica Chimica Acta,1033, 108–118.

    Article  PubMed  CAS  Google Scholar 

  • Dervilly-pinel, C. C. J. G., & Bizec, B. L. (2015). Global urine fingerprinting by LC-ESI ( + ) -HRMS for better characterization of metabolic pathway disruption upon anabolic practices in bovine. Metabolomics,11(1), 184–197.

    Article  CAS  Google Scholar 

  • Dettmer, K., Stevens, A. P., Fagerer, S. R., Kaspar, H., & Oefner, P. J. (2019). Amino acid analysis in physiological samples by GC-MS with propyl chloroformate derivatization and iTRAQ-LC-MS/MS. In Amino Acid Analysis (pp. 173–190). Springer.

  • Dudzik, D., Barbas-Bernardos, C., García, A., & Barbas, C. (2018). Quality assurance procedures for mass spectrometry untargeted metabolomics. A review. Journal of Pharmaceutical and Biomedical Analysis,147, 149–173.

    Article  CAS  PubMed  Google Scholar 

  • Dunn, W. B., Broadhurst, D., Begley, P., Zelena, E., Francis-McIntyre, S., Anderson, N., et al. (2011). Procedures for large-scale metabolic profiling of serum and plasma using gas chromatography and liquid chromatography coupled to mass spectrometry. Nature Protocols,6(7), 1060.

    Article  CAS  PubMed  Google Scholar 

  • Dunn, W. B., Broadhurst, D., Ellis, D. I., Brown, M., Halsall, A., O’hagan, S., et al. (2008). A GC-TOF-MS study of the stability of serum and urine metabolomes during the UK Biobank sample collection and preparation protocols. International Journal of Epidemiology,37, 23–30.

    Article  Google Scholar 

  • Dunn, W. B., Wilson, I. D., Nicholls, A. W., & Broadhurst, D. (2012). The importance of experimental design and QC samples in large-scale and MS-driven untargeted metabolomic studies of humans. Bioanalysis,4(18), 2249–2264.

    Article  CAS  PubMed  Google Scholar 

  • Edmands, W. M. B., Ferrari, P., & Scalbert, A. (2014). Normalization to specific gravity prior to analysis improves information recovery from high resolution mass spectrometry metabolomic profiles of human urine. Analytical Chemistry,86(21), 10925–10931.

    Article  CAS  PubMed  Google Scholar 

  • Eisinger, S. W., Schwartz, M., Dam, L., & Riedel, S. (2013). Evaluation of the BD Vacutainer Plus Urine C&S Preservative Tubes compared with nonpreservative urine samples stored at 4 C and room temperature. American Journal of Clinical Pathology,140(3), 306–313.

    Article  PubMed  Google Scholar 

  • Eshima, J., Ong, S., Davis, T. J., Miranda, C., Krishnamurthy, D., Nachtsheim, A., et al. (2019). Monitoring changes in the healthy female metabolome across the menstrual cycle using GC× GC-TOFMS. Journal of Chromatography B,1121, 48–57.

    Article  CAS  Google Scholar 

  • Fan, S., Yeon, A., Shahid, M., Anger, J. T., Eilber, K. S., Fiehn, O., et al. (2018). Sex-associated differences in baseline urinary metabolites of healthy adults. Scientific Reports,8(1), 11883.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Feres, M. C., Bini, R., Cristina, M., Martino, D., Biagini, S. P., Lino, A., et al. (2011). Implications for the use of acid preservatives in 24-hour urine for measurements of high demand biochemical analytes in clinical laboratories. Clinica Chimica Acta,412, 2322–2325.

    Article  CAS  Google Scholar 

  • Ferraz, R. R. N., Baxmann, A. C., Ferreira, L. G., Nishiura, J. L., Siliano, P. R., Gomes, S. A., et al. (2006). Preservation of urine samples for metabolic evaluation of stone-forming patients. Urological Research,34(5), 329–337.

    Article  PubMed  Google Scholar 

  • Fiehn, O. (2016). Metabolomics by gas chromatography–mass spectrometry: Combined targeted and untargeted profiling. Current Protocols in Molecular Biology,114, 30–34.

    Article  PubMed  PubMed Central  Google Scholar 

  • Freund, D. M., & Hegeman, A. D. (2017). Recent advances in stable isotope-enabled mass spectrometry-based plant metabolomics. Current Opinion in Biotechnology,43, 41–48.

    Article  CAS  PubMed  Google Scholar 

  • Gagnebin, Y., Tonoli, D., Lescuyer, P., Ponte, B., de Seigneux, S., Martin, P.-Y., et al. (2017). Metabolomic analysis of urine samples by UHPLC-QTOF-MS: Impact of normalization strategies. Analytica Chimica Acta,955, 27–35.

    Article  CAS  PubMed  Google Scholar 

  • González-Domínguez, R., Castilla-Quintero, R., García-Barrera, T., & Gómez-Ariza, J. L. (2014). Development of a metabolomic approach based on urine samples and direct infusion mass spectrometry. Analytical Biochemistry,465, 20–27.

    Article  PubMed  CAS  Google Scholar 

  • Hammerl, R., Frank, O., Schmittnägel, T., Ehrmann, M. A., & Hofmann, T. (2019). Functional metabolome analysis of Penicillium roqueforti by means of differential Off-Line LC–NMR. Journal of Agricultural and Food Chemistry,67(18), 5135–5146.

    Article  CAS  PubMed  Google Scholar 

  • He, M., Yan, P., Yang, Z., Ye, Y., Cao, D., Hong, L., et al. (2018). Multi-analytical strategy for unassigned peaks using physical/mathematical separation, fragmental rules and retention index prediction: An example of sesquiterpene metabolites characterization in Cyperus rotundus. Journal of Pharmaceutical and Biomedical Analysis,154, 476–485.

    Article  CAS  PubMed  Google Scholar 

  • Hogan, M. C., Lieske, J. C., Lienczewski, C. C., Nesbitt, L. L., Wickman, L. T., Heyer, C. M., et al. (2015). Strategy and rationale for urine collection protocols employed in the NEPTUNE study. BMC Nephrology,16(1), 190.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Huestis, M. A., Blount, B. C., Milan, D. F., Newmeyer, M. N., Schroeder, J., & Smith, M. L. (2019). Correlation of creatinine-and specific gravity-normalized free and glucuronidated urine cannabinoid concentrations following smoked, vaporized, and oral cannabis in frequent and occasional cannabis users. Drug Testing and Analysis,11(7), 968–975.

    Article  CAS  PubMed  Google Scholar 

  • Iyer, S. S., Zhang, Z.-P., Kellogg, G. E., & Karnes, H. T. (2004). Evaluation of deuterium isotope effects in normal-phase LC-MS-MS separations using a molecular modeling approach. Journal of Chromatographic Science,42(7), 383–387.

    Article  CAS  PubMed  Google Scholar 

  • Jáčová, J., Jořenek, M., Pospíšková, K., Najdekr, L., Zajoncová, L., Friedecký, D., et al. (2019). Urease-immobilized magnetic microparticles in urine sample preparation for metabolomic analysis by gas chromatography-mass spectrometry. Journal of Chromatography A,1605, 360355.

    Article  PubMed  CAS  Google Scholar 

  • Karpievitch, Y. V., Nikolic, S. B., Wilson, R., Sharman, J. E., & Edwards, L. M. (2014). Metabolomics data normalization with EigenMS. PLoS ONE,9(12), e116221.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Kaspar, H., Dettmer, K., Gronwald, W., & Oefner, P. J. (2008). Automated GC-MS analysis of free amino acids in biological fluids. Journal of Chromatography B: Analytical Technologies in the Biomedical and Life Sciences,870(2), 222–232.

    Article  CAS  PubMed  Google Scholar 

  • Keppler, E. A. H., Jenkins, C. L., Davis, T. J., & Bean, H. D. (2018). Advances in the application of comprehensive two-dimensional gas chromatography in metabolomics. TrAC Trends in Analytical Chemistry,109, 275–286.

    Article  CAS  PubMed  Google Scholar 

  • Khamis, M. M., Adamko, D. J., Purves, R. W., & El-Aneed, A. (2019). Quantitative determination of potential urine biomarkers of respiratory illnesses using new targeted metabolomic approach. Analytica Chimica Acta,1047, 81–92.

    Article  CAS  PubMed  Google Scholar 

  • Khamis, M. M., Holt, T., Awad, H., El-Aneed, A., & Adamko, D. J. (2018). Comparative analysis of creatinine and osmolality as urine normalization strategies in targeted metabolomics for the differential diagnosis of asthma and COPD. Metabolomics,14(9), 115.

    Article  PubMed  CAS  Google Scholar 

  • Kim, H. K., & Verpoorte, R. (2010). Sample preparation for plant metabolomics. Phytochemical Analysis,21, 4–13.

    Article  CAS  PubMed  Google Scholar 

  • Kim, J., Ahn, J. K., Cheong, Y. E., Lee, S.-J., Cha, H.-S., & Kim, K. H. (2020). Systematic re-evaluation of the long-used standard protocol of urease-dependent metabolome sample preparation. PLoS ONE,15(3), e0230072.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Kim, K., Aronov, P., Zakharkin, S. O., Anderson, D., Perroud, B., Thompson, I. M., et al. (2009). Urine metabolomics analysis for kidney cancer detection and biomarker discovery. Molecular & Cellular Proteomics,8(3), 558–570.

    Article  CAS  Google Scholar 

  • Kind, T., Cho, E., Park, T. D., Deng, N., Liu, Z., Lee, T., et al. (2016). Interstitial cystitis-associated urinary metabolites identified by mass-spectrometry based metabolomics analysis. Scientific Reports,6, 39227.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Kind, T., Tolstikov, V., Fiehn, O., & Weiss, R. H. (2007). A comprehensive urinary metabolomic approach for identifying kidney cancer. Analytical Biochemistry,363(2), 185–195.

    Article  CAS  PubMed  Google Scholar 

  • Koek, M. M., Muilwijk, B., van der Werf, M. J., & Hankemeier, T. (2006). Microbial metabolomics with gas chromatography/mass spectrometry. Analytical Chemistry,78(4), 1272–1281.

    Article  CAS  PubMed  Google Scholar 

  • Koo, I., Shi, X., Kim, S., & Zhang, X. (2014). iMatch2: Compound identification using retention index for analysis of gas chromatography–mass spectrometry data. Journal of Chromatography A,1337, 202–210.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Kovàts, E. (1958). Characterization of organic compounds by gas chromatography. Part 1. Retention indices of aliphatic halides, alcohols, aldehydes and ketones. Helvetica Chimica Acta,41(7), 1915–1932.

    Article  Google Scholar 

  • Kubinec, R., Kotora, P., Ferenczy, V., Blaško, J., Podolec, P., Hengerics Szabó, A., et al. (2017). Simultaneous analysis of carbohydrates, polyols and amines in urine samples using chemical ionization gas chromatography with tandem mass spectrometry. Journal of Separation Science,41(2), 1–10.

    Google Scholar 

  • Kvitvang, H. F. N., Andreassen, T., Adam, T., Villas-Bôas, S. G., & Bruheim, P. (2011). Highly sensitive GC/MS/MS method for quantitation of amino and nonamino organic acids. Analytical Chemistry,83(7), 2705–2711.

    Article  CAS  PubMed  Google Scholar 

  • Laparre, J., Kaabia, Z., Mooney, M., Buckley, T., Sherry, M., Le Bizec, B., et al. (2017). Impact of storage conditions on the urinary metabolomics fingerprint. Analytica Chimica Acta,951, 99–107.

    Article  CAS  PubMed  Google Scholar 

  • Lee, S. H., An, J. H., Park, H.-M., & Jung, B. H. (2012). Investigation of endogenous metabolic changes in the urine of pseudo germ-free rats using a metabolomic approach. Journal of Chromatography B,887, 8–18.

    Article  CAS  Google Scholar 

  • Liebeke, M., & Puskás, E. (2019). Drying enhances signal intensities for global GC–MS metabolomics. Metabolites,9(4), 68.

    Article  CAS  PubMed Central  Google Scholar 

  • Lien, S. K., Kvitvang, H. F. N., & Bruheim, P. (2012). Utilization of a deuterated derivatization agent to synthesize internal standards for gas chromatography-tandem mass spectrometry quantification of silylated metabolites. Journal of Chromatography A,1247, 118–124.

    Article  CAS  PubMed  Google Scholar 

  • Liesenfeld, D. B., Habermann, N., Toth, R., Owen, R. W., Frei, E., Böhm, J., et al. (2015). Changes in urinary metabolic profiles of colorectal cancer patients enrolled in a prospective cohort study (ColoCare). Metabolomics,11(4), 998–1012.

    Article  CAS  PubMed  Google Scholar 

  • Lisec, J., Schauer, N., Kopka, J., Willmitzer, L., & Fernie, A. R. (2006). Gas chromatography mass spectrometry–based metabolite profiling in plants. Nature Protocols,1(1), 387.

    Article  CAS  PubMed  Google Scholar 

  • Liu, X., & Locasale, J. W. (2017). Metabolomics: A primer. Trends in Biochemical Sciences,42(4), 274–284.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Magalhães, W. S., Garrido, B. C., Cavalcanti, G. A., Padilha, M. C., Casilli, A., Pereira, H. M. G., et al. (2019). Human metabolism of the anabolic steroid methasterone: Detection and kinetic excretion of new phase I urinary metabolites and investigation of phase II metabolism by GC-MS and UPLC-MS/MS. Journal of the Brazilian Chemical Society,30(6), 1150–1160.

    Google Scholar 

  • Maher, A. D., Zirah, F. M., Holmes, E., & Nicholson, J. K. (2007). Experimental and analytical variation in human urine in 1 H NMR spectroscopy-based metabolic phenotyping studies. Analytical Chemistry,79(14), 5204–5211.

    Article  CAS  PubMed  Google Scholar 

  • Mattarucchi, E., Baraldi, E., & Guillou, C. (2012). Metabolomics applied to urine samples in childhood asthma; differentiation between asthma phenotypes and identification of relevant metabolites. Biomedical Chromatography,26(1), 89–94.

    Article  CAS  PubMed  Google Scholar 

  • Megías-Pérez, R., Ruiz-Matute, A. I., Corno, M., & Kuhnert, N. (2019). Analysis of minor low molecular weight carbohydrates in cocoa beans by chromatographic techniques coupled to mass spectrometry. Journal of Chromatography A,1584, 135–143.

    Article  PubMed  CAS  Google Scholar 

  • Mizuno, H., Ueda, K., Kobayashi, Y., Tsuyama, N., Todoroki, K., Min, J. Z., et al. (2017). The great importance of normalization of LC–MS data for highly-accurate non-targeted metabolomics. Biomedical Chromatography,31(1), e3864.

    Article  CAS  Google Scholar 

  • Moldoveanu, S. C., & David, V. (2018). Derivatization methods in GC and GC/MS. In Gas chromatography derivatization, sample preparation, application. IntechOpen. https://doi.org/10.5772/intechopen.81954

  • Moreno, I., Barroso, M., Martinho, A., Cruz, A., & Gallardo, E. (2015). Determination of ketamine and its major metabolite, norketamine, in urine and plasma samples using microextraction by packed sorbent and gas chromatography-tandem mass spectrometry. Journal of Chromatography B,1004, 67–78.

    Article  CAS  Google Scholar 

  • Moros, G., Chatziioannou, A. C., Gika, H. G., Raikos, N., & Theodoridis, G. (2017a). Investigation of the derivatization conditions for GC–MS metabolomics of biological samples. Bioanalysis,9(1), 53–65.

    Article  CAS  PubMed  Google Scholar 

  • Moros, G., Chatziioannou, A. C., Gika, H. G., Raikos, N., & Theodoridis, G. (2017b). Investigation of the derivatization conditions for GC-MS metabolomics of biological samples. Bioanalysis,9(1), 53–65.

    Article  CAS  PubMed  Google Scholar 

  • Moros, G., & Helen, G. (2017). Investigation of the derivatization conditions for GC-MS metabolomics of biological samples. Bioanalysis,9(1), 53–65.

    Article  CAS  PubMed  Google Scholar 

  • Newman, M., Pratt, S. M., Curran, D. A., & Stanczyk, F. Z. (2019). Evaluating urinary estrogen and progesterone metabolites using dried filter paper samples and gas chromatography with tandem mass spectrometry (GC–MS/MS). BMC Chemistry,13(1), 20.

    Article  PubMed  PubMed Central  Google Scholar 

  • O’Shea, K., & Misra, B. B. (2020). Software tools, databases and resources in metabolomics: Updates from 2018 to 2019. Metabolomics,16(3), 1–23.

    Article  CAS  Google Scholar 

  • Palmas, F., Mussap, M., & Fattuoni, C. (2018). Urine metabolome analysis by gas chromatography–mass spectrometry (GC–MS): Standardization and optimization of protocols for urea removal and short-term sample storage. Clinica Chimica Acta,485(June), 236–242.

    Article  CAS  Google Scholar 

  • Pasikanti, K. K., Ho, P. C., & Chan, E. C. Y. (2008). Development and validation of a gas chromatography/mass spectrometry metabonomic platform for the global profiling of urinary metabolites. Rapid Communications in Mass Spectrometry: An International Journal Devoted to the Rapid Dissemination of Up-to-the-Minute Research in Mass Spectrometry,22(19), 2984–2992.

    Article  CAS  Google Scholar 

  • Piper, T., Schänzer, W., & Thevis, M. (2016). Revisiting the metabolism of 19-nortestosterone using isotope ratio and high resolution/high accuracy mass spectrometry. The Journal of steroid Biochemistry and Molecular Biology,162, 80–91.

    Article  CAS  PubMed  Google Scholar 

  • Poole, C. F. (2013). Alkylsilyl derivatives for gas chromatography. Journal of Chromatography A,1296, 2–14.

    Article  CAS  PubMed  Google Scholar 

  • Primec, M., Mičetić-Turk, D., & Langerholc, T. (2017). Analysis of short-chain fatty acids in human feces: A scoping review. Analytical Biochemistry,526, 9–21.

    Article  CAS  PubMed  Google Scholar 

  • Qiu, Y., Moir, R., Willis, I., Beecher, C., Tsai, Y.-H., Garrett, T. J., et al. (2016). Isotopic ratio outlier analysis of the S. cerevisiae metabolome using accurate mass gas chromatography/time-of-flight mass spectrometry: a new method for discovery. Analytical Chemistry,88(5), 2747–2754.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Raro, M., Portolés, T., Pitarch, E., Sancho, J. V., Hernández, F., Garrostas, L., et al. (2016). Potential of atmospheric pressure chemical ionization source in gas chromatography tandem mass spectrometry for the screening of urinary exogenous androgenic anabolic steroids. Analytica Chimica Acta,906, 128–138.

    Article  CAS  PubMed  Google Scholar 

  • Ren, S., Hinzman, A. A., Kang, E. L., Szczesniak, R. D., & Lu, L. J. (2015). Computational and statistical analysis of metabolomics data. Metabolomics,11(6), 1492–1513.

    Article  CAS  Google Scholar 

  • Rotter, M., Brandmaier, S., Prehn, C., & Adam, J. (2017). Stability of targeted metabolite profiles of urine samples under different storage conditions. Metabolomics,13(1), 4.

    Article  PubMed  CAS  Google Scholar 

  • Sawant, P. D., Kumar, S. A., Wankhede, S., & Rao, D. D. (2018). Creatinine as a normalization factor to estimate the representativeness of urine sample-Intra-subject and inter-subject variability studies. Applied Radiation and Isotopes,136, 121–126.

    Article  CAS  PubMed  Google Scholar 

  • Schroeder, J. L., Marinetti, L. J., Smith, R. K., Brewer, W. E., Clelland, B. L., & Morgan, S. L. (2008). The analysis of Δ9-tetrahydrocannabinol and metabolite in whole blood and 11-nor-Δ9-tetrahydrocannabinol-9-carboxylic acid in urine using disposable pipette extraction with confirmation and quantification by gas chromatography-mass spectrometry. Journal of Analytical Toxicology,32(8), 659–666.

    Article  CAS  PubMed  Google Scholar 

  • Schummer, C., Delhomme, O., Appenzeller, B. M. R., Wennig, R., & Millet, M. (2009). Comparison of MTBSTFA and BSTFA in derivatization reactions of polar compounds prior to GC/MS analysis. Talanta,77(4), 1473–1482.

    Article  CAS  PubMed  Google Scholar 

  • Shin, H. J., Park, N. H., Lee, W., Choi, M. H., Chung, B. C., & Hong, J. (2017). Metabolic profiling of tyrosine, tryptophan, and glutamate in human urine using gas chromatography–tandem mass spectrometry combined with single SPE cleanup. Journal of Chromatography B,1051, 97–107.

    Article  CAS  Google Scholar 

  • Struck-Lewicka, W., Kordalewska, M., Bujak, R., Mpanga, A. Y., Markuszewski, M., Jacyna, J., et al. (2015). Urine metabolic fingerprinting using LC–MS and GC–MS reveals metabolite changes in prostate cancer: A pilot study. Journal of Pharmaceutical and Biomedical Analysis,111, 351–361.

    Article  CAS  PubMed  Google Scholar 

  • Tumanov, S., Zubenko, Y., Obolonkin, V., Greenwood, D. R., Shmanai, V., & Villas-Bôas, S. G. (2016). Calibration curve-free GC–MS method for quantitation of amino and non-amino organic acids in biological samples. Metabolomics,12(4), 64.

    Article  CAS  Google Scholar 

  • Vanden, D. H., & Kratz, P. D. (1963). A generalization of the retention index system including linear temperature programmed gas-liquid partition chromatography. Journal of Chromatography,11, 463–471.

    Article  Google Scholar 

  • Villas-Bôas, S. G., Smart, K. F., Sivakumaran, S., & Lane, G. A. (2011). Alkylation or silylation for analysis of amino and non-amino organic acids by GC-MS? Metabolites,1(1), 3–20.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Vinaixa, A. M., Schymanski, E. L., & Neumann, S. (2015). Mass spectral databases for LC/MSGC/MS-based. Trends in Analytical Chemistry. https://doi.org/10.1016/j.trac.2015.09.005.

    Article  Google Scholar 

  • Vlaanderen, J. J., Janssen, N. A., Hoek, G., Keski-Rahkonen, P., Barupal, D. K., Cassee, F. R., et al. (2017). The impact of ambient air pollution on the human blood metabolome. Environmental Research,156, 341–348.

    Article  CAS  PubMed  Google Scholar 

  • Wang, X., Gu, H., Palma-Duran, S. A., Fierro, A., Jasbi, P., Shi, X., et al. (2019). Influence of storage conditions and preservatives on metabolite fingerprints in urine. Metabolites,9(10), 203.

    Article  CAS  PubMed Central  Google Scholar 

  • Warrack, B. M., Hnatyshyn, S., Ott, K.-H., Reily, M. D., Sanders, M., Zhang, H., et al. (2009). Normalization strategies for metabonomic analysis of urine samples. Journal of Chromatography B,877(5–6), 547–552.

    Article  CAS  Google Scholar 

  • Webb-Robertson, B. J., Kim, Y. M., Zink, E. M., Hallaian, K. A., Zhang, Q., Madupu, R., et al. (2014). A statistical analysis of the effects of urease pre-treatment on the measurement of the urinary metabolome by gas chromatography-mass spectrometry. Metabolomics,10(5), 897–908.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Wieling, J. (2002). LC-MS-MS experiences with internal standards. Chromatographia,55(1), S107–S113.

    Article  CAS  Google Scholar 

  • Wishart, D. S. (2019). NMR metabolomics: A look ahead. Journal of Magnetic Resonance,306, 155–161.

    Article  CAS  PubMed  Google Scholar 

  • Wu, A. H. B., & Colby, J. (2016). High-resolution mass spectrometry for untargeted drug screening. In Clinical applications of mass spectrometry in drug analysis (pp. 153–166). Springer.

  • Wu, W., Yang, D., Tiselius, H.-G., Ou, L., Mai, Z., Chen, K., et al. (2015). Collection and storage of urine specimens for measurement of urolithiasis risk factors. Urology,85(2), 299–303.

    Article  PubMed  Google Scholar 

  • Yang, Q., Lin, S.-S., Yang, J.-T., Tang, L.-J., & Yu, R.-Q. (2017). Detection of inborn errors of metabolism utilizing GC-MS urinary metabolomics coupled with a modified orthogonal partial least squares discriminant analysis. Talanta,165, 545–552.

    Article  CAS  PubMed  Google Scholar 

  • Zamora-Ros, R., Rabassa, M., Cherubini, A., Urpi-Sarda, M., Llorach, R., Bandinelli, S., et al. (2011). Comparison of 24-h volume and creatinine-corrected total urinary polyphenol as a biomarker of total dietary polyphenols in the Invecchiare InCHIANTI study. Analytica Chimica Acta,704(1–2), 110–115.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Zhang, J., Zheng, C.-H., Xia, Y., Wang, B., & Chen, P. (2017). Optimization enhanced genetic algorithm-support vector regression for the prediction of compound retention indices in gas chromatography. Neurocomputing,240, 183–190.

    Article  Google Scholar 

  • Zhang, T., & Watson, D. G. (2015). A short review of applications of liquid chromatography mass spectrometry based metabolomics techniques to the analysis of human urine. Analyst,140(9), 2907–2915.

    Article  CAS  PubMed  Google Scholar 

  • Zhao, L., Ni, Y., Su, M., Li, H., Dong, F., Chen, W., et al. (2017). High throughput and quantitative measurement of microbial metabolome by gas chromatography/mass spectrometry using automated alkyl chloroformate derivatization. Analytical Chemistry,89(10), 5565–5577.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Zheng, Y. Z., Pearce, R. W., Novotny, A., Hu, B., & Wang, S. (2019). Solving a myth: Does boric acid stabilize aldosterone in urine at typical clinical laboratory storage conditions? Clinical Biochemistry,73, 112–114.

    Article  CAS  PubMed  Google Scholar 

  • Zhu, K., Gu, B., Kerry, M., Mintert, M., Luong, J., & Pursch, M. (2017). Elimination of N, O -bis ( trimethylsilyl ) trifluoroacetamide interference by base treatment in derivatization gas chromatography mass spectrometry determination of parts per billion of alcohols in a food additive. Journal of Chromatography A,1490, 74–79.

    Article  CAS  PubMed  Google Scholar 

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Funding

MK was supported by a post-doctoral support fund awarded to MP by vice-chancellery for research, Isfahan University of Medical Sciences, Isfahan, Iran (Grant No: 197073).

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  1. Department of Clinical Biochemistry, School of Pharmacy & Pharmaceutical Sciences, Isfahan University of Medical Sciences, Isfahan, Iran

    Mohammad Khodadadi & Morteza Pourfarzam

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  1. Mohammad Khodadadi
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  2. Morteza Pourfarzam
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MP designed the research. MK conducted the literature review and wrote the first draft of the manuscript. MP critically appraised the manuscript. All authors were involved in writing and read and approved the manuscript.

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Correspondence to Morteza Pourfarzam.

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Khodadadi, M., Pourfarzam, M. A review of strategies for untargeted urinary metabolomic analysis using gas chromatography–mass spectrometry. Metabolomics 16, 66 (2020). https://doi.org/10.1007/s11306-020-01687-x

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