[en] While many laboratories take appropriate care, there are still cases where the performances of untargeted profiling methods suffer from a lack of design, control, and articulation of the various steps involved. This is particularly harmful to modern comprehensive analytical instrumentations that otherwise provide an unprecedented coverage of complex matrices. In this work, we present a global analytical workflow based on comprehensive two-dimensional gas chromatography coupled to high-resolution time-of-flight mass spectrometry. It was optimized for sample preparation and chromatographic separation and validated on in-house quality control (QC) and NIST SRM 1950 samples. It also includes a QC procedure, a multiapproach data (pre)processing workflow, and an original bias control procedure. Compounds of interest were identified using mass, retention, and biological information. As a proof of concept, 35 serum samples representing three subgroups of Crohn's disease (with high, low, and quiescent endoscopic activity) were analyzed along with 33 healthy controls. This led to the selection of 33 unique candidate biomarkers able to classify the Crohn's disease and healthy samples with an orthogonal partial least-squares discriminant analysis Q(2) of 0.48 and a receiver-operating-characteristic area under the curve of 0.85 (100% sensitivity and 82% specificity in cross validation). Fifteen of these 33 candidates were reliably annotated (Metabolomics Standards Initiative level 2).
Disciplines :
General & internal medicine Chemistry Gastroenterology & hepatology
Author, co-author :
Di Giovanni, Nicolas ; Université de Liège - ULiège > Département de chimie (sciences) > Chimie analytique, organique et biologique
MEUWIS, Marie-Alice ; Centre Hospitalier Universitaire de Liège - CHU > Département de médecine interne > Recherche translationnelle en gastroentérologie
Louis, Edouard ; Université de Liège - ULiège > Département des sciences cliniques > Hépato-gastroentérologie
Focant, Jean-François ; Université de Liège - ULiège > Département de chimie (sciences) > Chimie analytique, organique et biologique
Language :
English
Title :
Untargeted Serum Metabolic Profiling by Comprehensive Two-Dimensional Gas Chromatography-High-Resolution Time-of-Flight Mass Spectrometry.
Publication date :
2020
Journal title :
Journal of Proteome Research
ISSN :
1535-3893
eISSN :
1535-3907
Publisher :
American Chemical Society, United States - District of Columbia
scite shows how a scientific paper has been cited by providing the context of the citation, a classification describing whether it supports, mentions, or contrasts the cited claim, and a label indicating in which section the citation was made.
Bibliography
Pauling, L.; Robinson, A. B.; Teranishi, R.; Cary, P. Quantitative Analysis of Urine Vapor and Breath by Gas-Liquid Partition Chromatography. Proc. Natl. Acad. Sci. U. S. A. 1971, 68, 2374-2376, 10.1073/pnas.68.10.2374
Oliver, S. G.; Winson, M. K.; Kell, D. B.; Baganz, F. Systematic Functional Analysis of the Yeast Genome. Trends Biotechnol. 1998, 16, 373-378, 10.1016/S0167-7799(98)01214-1
Zhang, A.; Sun, H.; Wang, X. Serum Metabolomics as a Novel Diagnostic Approach for Disease: A Systematic Review. Anal. Bioanal. Chem. 2012, 404, 1239-1245, 10.1007/s00216-012-6117-1
Bedair, M.; Sumner, L. W. Current and Emerging Mass-Spectrometry Technologies for Metabolomics. TrAC, Trends Anal. Chem. 2008, 27, 238-250, 10.1016/j.trac.2008.01.006
Li, X.; Xu, Z.; Lu, X.; Yang, X.; Yin, P.; Kong, H.; Yu, Y.; Xu, G. Comprehensive Two-Dimensional Gas Chromatography/Time-of-Flight Mass Spectrometry for Metabonomics: Biomarker Discovery for Diabetes Mellitus. Anal. Chim. Acta 2009, 633, 257-262, 10.1016/j.aca.2008.11.058
Mohler, R. E.; Dombek, K. M.; Hoggard, J. C.; Young, E. T.; Synovec, R. E. Comprehensive Two-Dimensional Gas Chromatography Time-of-Flight Mass Spectrometry Analysis of Metabolites in Fermenting and Respiring Yeast Cells. Anal. Chem. 2006, 78, 2700-2709, 10.1021/ac052106o
Kouremenos, K. A.; Pitt, J.; Marriott, P. J. Metabolic Profiling of Infant Urine Using Comprehensive Two-Dimensional Gas Chromatography: Application to the Diagnosis of Organic Acidurias and Biomarker Discovery. J. Chromatogr. A 2010, 1217, 104-111, 10.1016/j.chroma.2009.10.033
Pierce, K. M.; Hoggard, J. C.; Hope, J. L.; Rainey, P. M.; Hoofnagle, A. N.; Jack, R. M.; Wright, B. W.; Synovec, R. E. Fisher Ratio Method Applied to Third-Order Separation Data to Identify Significant Chemical Components of Metabolite Extracts. Anal. Chem. 2006, 78, 5068-5075, 10.1021/ac0602625
Welthagen, W.; Shellie, R. A.; Spranger, J.; Ristow, M.; Zimmermann, R.; Fiehn, O. Comprehensive Two-Dimensional Gas Chromatography-Time-of-Flight Mass Spectrometry (GC × GC-TOF) for High Resolution Metabolomics: Biomarker Discovery on Spleen Tissue Extracts of Obese NZO Compared to Lean C57BL/6 Mice. Metabolomics 2005, 1, 65-73, 10.1007/s11306-005-1108-2
Almstetter, M. F.; Oefner, P. J.; Dettmer, K. Comprehensive Two-Dimensional Gas Chromatography in Metabolomics. Anal. Bioanal. Chem. 2012, 402, 1993-2013, 10.1007/s00216-011-5630-y
Hyötylaïnen, T. Analytical Methodologies Utilized in the Search for Chronic Disease Biomarkers. Bioanalysis 2010, 2, 919-923, 10.4155/bio.10.38
Winnike, J. H.; Wei, X.; Knagge, K. J.; Colman, S. D.; Gregory, S. G.; Zhang, X. Comparison of GC-MS and GC×GC-MS in the Analysis of Human Serum Samples for Biomarker Discovery. J. Proteome Res. 2015, 14, 1810-1817, 10.1021/pr5011923
Koek, M. M.; Muilwijk, B.; van Stee, L. L. P.; Hankemeier, T. Higher Mass Loadability in Comprehensive Two-Dimensional Gas Chromatography-Mass Spectrometry for Improved Analytical Performance in Metabolomics Analysis. J. Chromatogr. A 2008, 1186, 420-429, 10.1016/j.chroma.2007.11.107
Lebedev, A. T.; Polyakova, O. V.; Mazur, D. M.; Artaev, V. B. The Benefits of High Resolution Mass Spectrometry in Environmental Analysis. Analyst 2013, 138, 6946-6953, 10.1039/C3AN01237A
Sangster, T.; Major, H.; Plumb, R.; Wilson, A. J.; Wilson, I. D. A Pragmatic and Readily Implemented Quality Control Strategy for HPLC-MS and GC-MS-Based Metabonomic Analysis. Analyst 2006, 131, 1075-1078, 10.1039/B604498K
Dunn, W. B.; Wilson, I. D.; Nicholls, A. W.; Broadhurst, D. The Importance of Experimental Design and QC Samples in Large-Scale and MS-Driven Untargeted Metabolomic Studies of Humans. Bioanalysis 2012, 4, 2249-2264, 10.4155/bio.12.204
Broadhurst, D.; Goodacre, R.; Reinke, S. N.; Kuligowski, J.; Wilson, I. D.; Lewis, M. R.; Dunn, W. B. Guidelines and Considerations for the Use of System Suitability and Quality Control Samples in Mass Spectrometry Assays Applied in Untargeted Clinical Metabolomic Studies. Metabolomics 2018, 14, 72, 10.1007/s11306-018-1367-3
Gullberg, J.; Jonsson, P.; Nordström, A.; Sjöström, M.; Moritz, T. Design of Experiments: An Efficient Strategy to Identify Factors Influencing Extraction and Derivatization of Arabidopsis Thaliana Samples in Metabolomic Studies with Gas Chromatography/Mass Spectrometry. Anal. Biochem. 2004, 331, 283-295, 10.1016/j.ab.2004.04.037
Banerjee, K.; Patil, S. H.; Dasgupta, S.; Oulkar, D. P.; Patil, S. B.; Savant, R.; Adsule, P. G. Optimization of Separation and Detection Conditions for the Multiresidue Analysis of Pesticides in Grapes by Comprehensive Two-Dimensional Gas Chromatography-Time-of-Flight Mass Spectrometry. J. Chromatogr. A 2008, 1190, 350-357, 10.1016/j.chroma.2008.03.017
Kind, T.; Fiehn, O. Seven Golden Rules for Heuristic Filtering of Molecular Formulas Obtained by Accurate Mass Spectrometry. BMC Bioinf. 2007, 8, 105, 10.1186/1471-2105-8-105
van den Berg, R. A.; Hoefsloot, H. C. J.; Westerhuis, J. A.; Smilde, A. K.; van der Werf, M. J. Centering, Scaling, and Transformations: Improving the Biological Information Content of Metabolomics Data. BMC Genomics 2006, 7, 142, 10.1186/1471-2164-7-142
Madsen, R.; Lundstedt, T.; Trygg, J. Chemometrics in Metabolomics-A Review in Human Disease Diagnosis. Anal. Chim. Acta 2010, 659, 23-33, 10.1016/j.aca.2009.11.042
Dunn, W. B.; Broadhurst, D.; Begley, P.; Zelena, E.; Francis-Mcintyre, S.; Anderson, N.; Brown, M.; Knowles, J. D.; Halsall, A.; Haselden, J. N. et al. Procedures for Large-Scale Metabolic Profiling of Serum and Plasma Using Gas Chromatography and Liquid Chromatography Coupled to Mass Spectrometry. Nat. Protoc. 2011, 6, 1060-1083, 10.1038/nprot.2011.335
Bro, R. PARAFAC. Tutorial and Applications. Chemom. Intell. Lab. Syst. 1997, 38, 149-171, 10.1016/S0169-7439(97)00032-4
Xia, J.; Sinelnikov, I. V.; Han, B.; Wishart, D. S. MetaboAnalyst 3.0-Making Metabolomics More Meaningful. Nucleic Acids Res. 2015, 43, W251-W257, 10.1093/nar/gkv380
Wei, X.; Shi, X.; Koo, I.; Kim, S.; Schmidt, R. H.; Arteel, G. E.; Watson, W. H.; McClain, C.; Zhang, X. MetPP: A Computational Platform for Comprehensive Two-Dimensional Gas Chromatography Time-of-Flight Mass Spectrometry-Based Metabolomics. Bioinformatics 2013, 29, 1786-1792, 10.1093/bioinformatics/btt275
Christou, C.; Gika, H. G.; Raikos, N.; Theodoridis, G. GC-MS Analysis of Organic Acids in Human Urine in Clinical Settings: A Study of Derivatization and Other Analytical Parameters. J. Chromatogr., B 2014, 964, 195-201, 10.1016/j.jchromb.2013.12.038
Dunn, W. B.; Erban, A.; Weber, R. J. M.; Creek, D. J.; Brown, M.; Breitling, R.; Hankemeier, T.; Goodacre, R.; Neumann, S.; Kopka, J. et al. Mass Appeal: Metabolite Identification in Mass Spectrometry-Focused Untargeted Metabolomics. Metabolomics 2013, 9, 44-66, 10.1007/s11306-012-0434-4
Fang, M.; Ivanisevic, J.; Benton, H. P.; Johnson, C. H.; Patti, G. J.; Hoang, L. T.; Uritboonthai, W.; Kurczy, M. E.; Siuzdak, G. Thermal Degradation of Small Molecules: A Global Metabolomic Investigation. Anal. Chem. 2015, 87, 10935-10941, 10.1021/acs.analchem.5b03003
de Castro, M. D. L.; Izquierdo, A. Lyophilization: A Useful Approach to the Automation of Analytical Processes?. J. Autom. Chem. 1990, 12, 267-279, 10.1155/S1463924690000347
Fiehn, O. Metabolomics: Prospects and Pitfalls. Answers to Common Questions http://files.pharmtech.com/alfresco_images/pharma/2017/04/04/9b3abb1d-a43b-45e8-a45a-6c9694a15ba9/LEC0315_ebook.pdf (accessed Jul 18, 2019).
Kalla, R.; Ventham, N. T.; Satsangi, J.; Arnott, I. D. R. Crohn's Disease. Br. Med. J. 2014, 349, g6670, 10.1136/bmj.g6670
Molodecky, N. A.; Soon, I. S.; Rabi, D. M.; Ghali, W. A.; Ferris, M.; Chernoff, G.; Benchimol, E. I.; Panaccione, R.; Ghosh, S.; Barkema, H. W. et al. Increasing Incidence and Prevalence of the Inflammatory Bowel Diseases With Time, Based on Systematic Review. Gastroenterology 2012, 142, 46-54.e42, 10.1053/j.gastro.2011.10.001
Louis, E.; Baumgart, D. C.; Ghosh, S.; Gomollón, F.; Hanauer, S.; Hart, A.; Irving, P. What Changes in Inflammatory Bowel Disease Management Can Be Implemented Today?. J. Crohn's Colitis 2012, 6, S260-S267, 10.1016/S1873-9946(12)60506-6
Bjerrum, J. T.; Wang, Y.; Hao, F.; Coskun, M.; Ludwig, C.; Günther, U.; Nielsen, O. H. Metabonomics of Human Fecal Extracts Characterize Ulcerative Colitis, Crohn's Disease and Healthy Individuals. Metabolomics 2015, 11, 122-133, 10.1007/s11306-014-0677-3
Stephens, N. S.; Siffledeen, J.; Su, X.; Murdoch, T. B.; Fedorak, R. N.; Slupsky, C. M. Urinary NMR Metabolomic Profiles Discriminate Inflammatory Bowel Disease from Healthy. J. Crohn's Colitis 2013, 7, e42-e48, 10.1016/j.crohns.2012.04.019
Schicho, R.; Shaykhutdinov, R.; Ngo, J.; Nazyrova, A.; Schneider, C.; Panaccione, R.; Kaplan, G. G.; Vogel, H. J.; Storr, M. Quantitative Metabolomic Profiling of Serum, Plasma, and Urine by 1H NMR Spectroscopy Discriminates between Patients with Inflammatory Bowel Disease and Healthy Individuals. J. Proteome Res. 2012, 11, 3344-3357, 10.1021/pr300139q
Marchesi, J. R.; Holmes, E.; Khan, F.; Kochhar, S.; Scanlan, P.; Shanahan, F.; Wilson, I. D.; Wang, Y. Rapid and Noninvasive Metabonomic Characterization of Inflammatory Bowel Disease. J. Proteome Res. 2007, 6, 546-551, 10.1021/pr060470d
Williams, H. R. T.; Willsmore, J. D.; Cox, I. J.; Walker, D. G.; Cobbold, J. F. L.; Taylor-Robinson, S. D.; Orchard, T. R. Serum Metabolic Profiling in Inflammatory Bowel Disease. Dig. Dis. Sci. 2012, 57, 2157-2165, 10.1007/s10620-012-2127-2
Williams, H. R. T.; Cox, I. J.; Walker, D. G.; North, B. V.; Patel, V. M.; Marshall, S. E.; Jewell, D. P.; Ghosh, S.; Thomas, H. J. W.; Teare, J. P. et al. Characterization of Inflammatory Bowel Disease with Urinary Metabolic Profiling. Am. J. Gastroenterol. 2009, 104, 1435-1444, 10.1038/ajg.2009.175
Jansson, J.; Willing, B.; Lucio, M.; Fekete, A.; Dicksved, J.; Halfvarson, J.; Tysk, C.; Schmitt-Kopplin, P. Metabolomics Reveals Metabolic Biomarkers of Crohn's Disease. PLoS One 2009, 4, e6386, 10.1371/journal.pone.0006386
Murdoch, T. B.; Fu, H.; MacFarlane, S.; Sydora, B. C.; Fedorak, R. N.; Slupsky, C. M. Urinary Metabolic Profiles of Inflammatory Bowel Disease in Interleukin-10 Gene-Deficient Mice. Anal. Chem. 2008, 80, 5524-5531, 10.1021/ac8005236
Lin, H.-M.; Edmunds, S. J.; Helsby, N. A.; Ferguson, L. R.; Rowan, D. D. Nontargeted Urinary Metabolite Profiling of a Mouse Model of Crohn ' s Disease Research Articles. J. Proteome Res. 2009, 2045-2057, 10.1021/pr800999t
Schicho, R.; Nazyrova, A.; Shaykhutdinov, R.; Duggan, G.; Vogel, H. J.; Storr, M. Quantitative Metabolomic Profiling of Serum and Urine in DSS-Induced Ulcerative Colitis of Mice by 1 H NMR Spectroscopy. J. Proteome Res. 2010, 9, 6265-6273, 10.1021/pr100547y
Chen, C.; Shah, Y. M.; Morimura, K.; Krausz, K. W.; Miyazaki, M.; Richardson, T. A.; Morgan, E. T.; Ntambi, J. M.; Idle, J. R.; Gonzalez, F. J. Metabolomics Reveals That Hepatic Stearoyl-CoA Desaturase 1 Downregulation Exacerbates Inflammation and Acute Colitis. Cell Metab. 2008, 7, 135-147, 10.1016/j.cmet.2007.12.003
Le Gall, G.; Noor, S. O.; Ridgway, K.; Scovell, L.; Jamieson, C.; Johnson, I. T.; Colquhoun, I. J.; Kemsley, E. K.; Narbad, A. Metabolomics of Fecal Extracts Detects Altered Metabolic Activity of Gut Microbiota in Ulcerative Colitis and Irritable Bowel Syndrome. J. Proteome Res. 2011, 10, 4208-4218, 10.1021/pr2003598
Minamoto, Y.; Otoni, C. C.; Steelman, S. M.; Buÿükleblebici, O.; Steiner, J. M.; Jergens, A. E.; Suchodolski, J. S. Alteration of the Fecal Microbiota and Serum Metabolite Profiles in Dogs with Idiopathic Inflammatory Bowel Disease. Gut Microbes 2015, 6, 33-47, 10.1080/19490976.2014.997612
Ponnusamy, K.; Choi, J. N.; Kim, J.; Lee, S.-Y.; Lee, C. H. Microbial Community and Metabolomic Comparison of Irritable Bowel Syndrome Faeces. J. Med. Microbiol. 2011, 60, 817-827, 10.1099/jmm.0.028126-0
Kolho, K.-L.; Pessia, A.; Jaakkola, T.; de Vos, W. M.; Velagapudi, V. Faecal and Serum Metabolomics in Paediatric Inflammatory Bowel Disease. J. Crohn's Colitis 2016, 11, 321-334, 10.1093/ecco-jcc/jjw158
Dawiskiba, T.; Deja, S.; Mulak, A.; Zabek, A.; Jawień, E.; Pawełka, D.; Banasik, M.; Mastalerz-Migas, A.; Balcerzak, W.; Kaliszewski, K. et al. Serum and Urine Metabolomic Fngerprinting in Diagnostics of Inflammatory Bowel Diseases. World J. Gastroenterol. 2014, 20, 163-174, 10.3748/wjg.v20.i1.163
Balasubramanian, K.; Kumar, S.; Singh, R. R.; Sharma, U.; Ahuja, V.; Makharia, G. K.; Jagannathan, N. R. Metabolism of the Colonic Mucosa in Patients with Inflammatory Bowel Diseases: An in Vitro Proton Magnetic Resonance Spectroscopy Study. Magn. Reson. Imaging 2009, 27, 79-86, 10.1016/j.mri.2008.05.014
Varma, S.; Bird, R.; Eskin, M.; Dolenko, B.; Raju, J.; Bezabeh, T. Detection of Inflammatory Bowel Disease by Proton Magnetic Resonance Spectroscopy (1H MRS) Using an Animal Model. J. Inflammation 2007, 4, 24, 10.1186/1476-9255-4-24
Sharma, U.; Singh, R. R.; Ahuja, V.; Makharia, G. K.; Jagannathan, N. R. Similarity in the Metabolic Profile in Macroscopically Involved and Un-Involved Colonic Mucosa in Patients with Inflammatory Bowel Disease: An in Vitro Proton (1H) MR Spectroscopy Study. Magn. Reson. Imaging 2010, 28, 1022-1029, 10.1016/j.mri.2010.03.039
Ooi, M.; Nishiumi, S.; Yoshie, T.; Shiomi, Y.; Kohashi, M.; Fukunaga, K.; Nakamura, S.; Matsumoto, T.; Hatano, N.; Shinohara, M. et al. GC/MS-Based Profiling of Amino Acids and TCA Cycle-Related Molecules in Ulcerative Colitis. Inflammation Res. 2011, 60, 831-840, 10.1007/s00011-011-0340-7
Barding, G. A., Jr.; Béni, S.; Fukao, T.; Bailey-Serres, J.; Larive, C. K. Comparison of GC-MS and NMR for Metabolite Profiling of Rice Subjected to Submergence Stress. J. Proteome Res. 2013, 12, 898-909, 10.1021/pr300953k
Bhinderwala, F.; Wase, N.; DiRusso, C.; Powers, R. Combining Mass Spectrometry and NMR Improves Metabolite Detection and Annotation. J. Proteome Res. 2018, 17, 4017-4022, 10.1021/acs.jproteome.8b00567
Psychogios, N.; Hau, D. D.; Peng, J.; Guo, A. C.; Mandal, R.; Bouatra, S.; Sinelnikov, I.; Krishnamurthy, R.; Eisner, R.; Gautam, B. et al. The Human Serum Metabolome. PLoS One 2011, 6, e16957, 10.1371/journal.pone.0016957
Zhou, B.; Xiao, J. F.; Tuli, L.; Ressom, H. W. LC-MS-Based Metabolomics. Mol. BioSyst. 2012, 8, 470-481, 10.1039/c1mb05350g
Murgia, A.; Hinz, C.; Liggi, S.; Denes, J.; Hall, Z.; West, J.; Santoru, M. L.; Piras, C.; Manis, C.; Usai, P. et al. Italian Cohort of Patients Affected by Inflammatory Bowel Disease Is Characterised by Variation in Glycerophospholipid, Free Fatty Acids and Amino Acid Levels. Metabolomics 2018, 14, 140, 10.1007/s11306-018-1439-4
Alghamdi, A.; Gerasimidis, K.; Blackburn, G.; Akinci, D.; Edwards, C.; Russell, R. K.; Watson, D. G. Untargeted Metabolomics of Extracts from Faecal Samples Demonstrates Distinct Differences between Paediatric Crohn's Disease Patients and Healthy Controls but No Significant Changes Resulting from Exclusive Enteral Nutrition Treatment. Metabolites 2018, 8, 82, 10.3390/metabo8040082
Baur, P.; Martin, F.-P.; Gruber, L.; Bosco, N.; Brahmbhatt, V.; Collino, S.; Guy, P.; Montoliu, I.; Rozman, J.; Klingenspor, M. et al. Metabolic Phenotyping of the Crohn's Disease-like IBD Etiopathology in the TNFÎ"ARE/WT Mouse Model. J. Proteome Res. 2011, 10, 5523-5535, 10.1021/pr2007973
Daniluk, U.; Daniluk, J.; Kucharski, R.; Kowalczyk, T.; Pietrowska, K.; Samczuk, P.; Filimoniuk, A.; Kretowski, A.; Lebensztejn, D.; Ciborowski, M. Untargeted Metabolomics and Inflammatory Markers Profiling in Children With Crohn's Disease and Ulcerative Colitis-A Preliminary Study. Inflammatory Bowel Dis. 2019, 25, 1120-1128, 10.1093/ibd/izy402
Teahan, O.; Gamble, S.; Holmes, E.; Waxman, J.; Nicholson, J. K.; Bevan, C.; Keun, H. C. Impact of Analytical Bias in Metabonomic Studies of Human Blood Serum and Plasma. Anal. Chem. 2006, 78, 4307-4318, 10.1021/ac051972y
Phinney, K. W.; Ballihaut, G.; Bedner, M.; Benford, B. S.; Camara, J. E.; Christopher, S. J.; Davis, W. C.; Dodder, N. G.; Eppe, G.; Lang, B. E. et al. Development of a Standard Reference Material for Metabolomics Research. Anal. Chem. 2013, 85, 11732-11738, 10.1021/ac402689t
Nishiumi, S.; Kobayashi, T.; Ikeda, A.; Yoshie, T.; Kibi, M.; Izumi, Y.; Okuno, T.; Hayashi, N.; Kawano, S.; Takenawa, T. et al. A Novel Serum Metabolomics-Based Diagnostic Approach for Colorectal Cancer. PLoS One 2012, 7, e40459 10.1371/journal.pone.0040459
Villas-Boâs, S. G.; Smart, K. F.; Sivakumaran, S.; Lane, G. A. Alkylation or Silylation for Analysis of Amino and Non-Amino Organic Acids by GC-MS?. Metabolites 2011, 1, 3-20, 10.3390/metabo1010003
Leardi, R. Experimental Design in Chemistry: A Tutorial. Anal. Chim. Acta 2009, 652, 161-172, 10.1016/j.aca.2009.06.015
Mostafa, A.; Edwards, M.; Górecki, T. Optimization Aspects of Comprehensive Two-Dimensional Gas Chromatography. J. Chromatogr. A 2012, 1255, 38-55, 10.1016/j.chroma.2012.02.064
Kowalski, J.; Misselwitz, M.; Cochran, J. Investigating GC×GC Separations Using Selective Column Chemistry and Compound Derivatization Pairings for Common Metabolomics Chemical Compounds. In 4th Multidimensional Chromatography Workshop; Restek Corporation: Toronto, Canada, 2013, 36.
Reichenbach, S. E.; Tian, X.; Cordero, C.; Tao, Q. Features for Non-Targeted Cross-Sample Analysis with Comprehensive Two-Dimensional Chromatography. J. Chromatogr. A 2012, 1226, 140-148, 10.1016/j.chroma.2011.07.046
Reichenbach, S. E.; Tian, X.; Tao, Q.; Ledford, E. B., Jr.; Wu, Z.; Fiehn, O. Informatics for Cross-Sample Analysis with Comprehensive Two-Dimensional Gas Chromatography and High-Resolution Mass Spectrometry (GC×GC-HRMS). Talanta 2011, 83, 1279-1288, 10.1016/j.talanta.2010.09.057
Noctor, G.; Bergot, G.; Mauve, C.; Thominet, D.; Lelarge-Trouverie, C.; Prioul, J.-L. A Comparative Study of Amino Acid Measurement in Leaf Extracts by Gas Chromatography-Time of Flight-Mass Spectrometry and High Performance Liquid Chromatography with Fluorescence Detection. Metabolomics 2007, 3, 161-174, 10.1007/s11306-007-0057-3
Fiehn, O. Metabolomics by Gas Chromatography-Mass Spectrometry: Combined Targeted and Untargeted Profiling. Curr. Protoc. Mol. Biol. 2016, 114, 30-34, 10.1002/0471142727.mb3004s114
Hendriks, M. M. W. B.; van Eeuwijk, F. A.; Jellema, R. H.; Westerhuis, J. A.; Reijmers, T. H.; Hoefsloot, H. C. J.; Smilde, A. K. Data-Processing Strategies for Metabolomics Studies. TrAC, Trends Anal. Chem. 2011, 30, 1685-1698, 10.1016/j.trac.2011.04.019
Zelena, E.; Dunn, W. B.; Broadhurst, D.; Francis-McIntyre, S.; Carroll, K. M.; Begley, P.; O'Hagan, S.; Knowles, J. D.; Halsall, A.; Wilson, I. D. et al. Development of a Robust and Repeatable UPLC-MS Method for the Long-Term Metabolomic Study of Human Serum. Anal. Chem. 2009, 81, 1357-1364, 10.1021/ac8019366
Xia, J.; Wishart, D. S. Using MetaboAnalyst 3.0 for Comprehensive Metabolomics Data Analysis. Curr. Protoc. Mol. Biol. 2016, 55, 14-10, 10.1002/cpbi.11
Rakotomalala, R. TANAGRA: Une Plate-Forme d ' Expérimentation Pour La Fouille de Donneés. Rev. Modul. 2005, 70-85
Mierswa, I.; Klinkenberg, R.; Fischer, S.; Ritthoff, O. A Flexible Platform for Knowledge Discovery Experiments: YALE-Yet Another Learning Environment; University of Dortmund: Germany, 2003.
R Core Team. R: A Language and Environment for Statistical Computing. https://www.r-project.org/(accessed Jul 18, 2019).
Castillo, S.; Mattila, I.; Miettinen, J.; Orešič, M.; Hyötylaïnen, T. Data Analysis Tool for Comprehensive Two-Dimensional Gas Chromatography/Time-of-Flight Mass Spectrometry. Anal. Chem. 2011, 83, 3058-3067, 10.1021/ac103308x
Wishart, D. S.; Jewison, T.; Guo, A. C.; Wilson, M.; Knox, C.; Liu, Y.; Djoumbou, Y.; Mandal, R.; Aziat, F.; Dong, E. et al. HMDB 3.0-The Human Metabolome Database in 2013. Nucleic Acids Res. 2013, 41, D801-D807, 10.1093/nar/gks1065
Kanehisa, M.; Furumichi, M.; Tanabe, M.; Sato, Y.; Morishima, K. KEGG: New Perspectives on Genomes, Pathways, Diseases and Drugs. Nucleic Acids Res. 2017, 45, D353-D361, 10.1093/nar/gkw1092
Bean, H. D.; Hill, J. E.; Dimandja, J.-M. D. Improving the Quality of Biomarker Candidates in Untargeted Metabolomics via Peak Table-Based Alignment of Comprehensive Two-Dimensional Gas Chromatography-Mass Spectrometry Data. J. Chromatogr. A 2015, 1394, 111-117, 10.1016/j.chroma.2015.03.001
Bekele, E. A.; Annaratone, C. E. P.; Hertog, M. L. A. T. M.; Nicolai, B. M.; Geeraerd, A. H. Multi-Response Optimization of the Extraction and Derivatization Protocol of Selected Polar Metabolites from Apple Fruit Tissue for GC-MS Analysis. Anal. Chim. Acta 2014, 824, 42-56, 10.1016/j.aca.2014.03.030
Schummer, C.; Delhomme, O.; Appenzeller, B. M. R.; Wennig, R.; Millet, M. Comparison of MTBSTFA and BSTFA in Derivatization Reactions of Polar Compounds Prior to GC/MS Analysis. Talanta 2009, 77, 1473-1482, 10.1016/j.talanta.2008.09.043
Food and Drug Administration; Centre for Drug Validation and Research (CDER). Bioanalytical Method Validation. Guidance for Industry. https://www.fda.gov/files/drugs/published/Bioanalytical-Method-Validation-Guidance-for-Industry.pdf (accessed Jul 18, 2019).
National Institute of Standards & Technology. Certificate of Analysis. Standard Reference Material 1950. Metabolites in Frozen Human Plasma. https://www-s.nist.gov/srmors/certificates/1950.pdf (accessed Jul 18, 2019).
Jiye, A.; Trygg, J.; Gullberg, J.; Johansson, A. I.; Jonsson, P.; Antti, H.; Marklund, S. L.; Moritz, T. Extraction and GC/MS Analysis of the Human Blood Plasma Metabolome. Anal. Chem. 2005, 77, 8086-8094, 10.1021/ac051211v
Koek, M. M.; Muilwijk, B.; Van Der Werf, M. J.; Hankemeier, T. Microbial Metabolomics with Gas Chromatography/Mass Spectrometry. Anal. Chem. 2006, 78, 1272-1281, 10.1021/ac051683+
Kiser, M. M.; Dolan, J. W. Selecting the Best Curve Fit. LCGC North Am. 2004, 22, 112-117
Stone, D.; Ellis, J. Calibration and Linear Regression Analysis: A Self-Guided Tutorial (Part 2). https://sites.chem.utoronto.ca/chemistry/coursenotes/analsci/LinRegr2a.pdf (accessed Jul 18, 2019).
Gustavo González, A.; ángeles Herrador, M. A Practical Guide to Analytical Method Validation, Including Measurement Uncertainty and Accuracy Profiles. TrAC, Trends Anal. Chem. 2007, 26, 227-238, 10.1016/j.trac.2007.01.009
Ducauze, C.; Baillet-Guffroy, A.; Bui, T. X. Choix et Validation d'une Méthode d'Analyse http://www2.agroparistech.fr/IMG/pdf/Choix_et_Validation_Methode-2.pdf (accessed Jul 18, 2019).
Taverniers, I.; De Loose, M.; Van Bockstaele, E. Trends in Quality in the Analytical Laboratory. II. Analytical Method Validation and Quality Assurance. TrAC, Trends Anal. Chem. 2004, 23, 535-552, 10.1016/j.trac.2004.04.001
Bressanello, D.; Liberto, E.; Collino, M.; Reichenbach, S. E.; Benetti, E.; Chiazza, F.; Bicchi, C.; Cordero, C. Urinary Metabolic Fingerprinting of Mice with Diet-Induced Metabolic Derangements by Parallel Dual Secondary Column-Dual Detection Two-Dimensional Comprehensive Gas Chromatography. J. Chromatogr. A 2014, 1361, 265-276, 10.1016/j.chroma.2014.08.015
Redestig, H.; Fukushima, A.; Stenlund, H.; Moritz, T.; Arita, M.; Saito, K.; Kusano, M. Compensation for Systematic Cross-Contribution Improves Normalization of Mass Spectrometry Based Metabolomics Data. Anal. Chem. 2009, 81, 7974-7980, 10.1021/ac901143w
Sysi-Aho, M.; Katajamaa, M.; Yetukuri, L.; Orešič, M. Normalization Method for Metabolomics Data Using Optimal Selection of Multiple Internal Standards. BMC Bioinf. 2007, 8, 93, 10.1186/1471-2105-8-93
Shewhart, W. A. Quality Control Charts. Bell Syst. Tech. J. 1926, 5, 593-603, 10.1002/j.1538-7305.1926.tb00125.x
Almstetter, M. F.; Appel, I. J.; Gruber, M. A.; Lottaz, C.; Timischl, B.; Spang, R.; Dettmer, K.; Oefner, P. J. Integrative Normalization and Comparative Analysis for Metabolic Fingerprinting by Comprehensive Two-Dimensional Gas Chromatography-Time-of-Flight Mass Spectrometry. Anal. Chem. 2009, 81, 5731-5739, 10.1021/ac900528b
Gromski, P. S.; Xu, Y.; Hollywood, K. A.; Turner, M. L.; Goodacre, R. The Influence of Scaling Metabolomics Data on Model Classification Accuracy. Metabolomics 2015, 11, 684-695, 10.1007/s11306-014-0738-7
Enot, D. P.; Lin, W.; Beckmann, M.; Parker, D.; Overy, D. P.; Draper, J. Preprocessing, Classification Modeling and Feature Selection Using Flow Injection Electrospray Mass Spectrometry Metabolite Fingerprint Data. Nat. Protoc. 2008, 3, 446-470, 10.1038/nprot.2007.511
Becker, L. A. Effect Size Calculators. https://www.uccs.edu/lbecker/(accessed Jul 18, 2019).
Ellis, P. D. Effect Size Calculators. https://www.polyu.edu.hk/mm/effectsizefaqs/calculator/calculator.html (accessed Jul 18, 2019).
Broadhurst, D. I.; Kell, D. B. Statistical Strategies for Avoiding False Discoveries in Metabolomics and Related Experiments. Metabolomics 2006, 2, 171-196, 10.1007/s11306-006-0037-z
Dunn, W. B.; Lin, W.; Broadhurst, D.; Begley, P.; Brown, M.; Zelena, E.; Vaughan, A. A.; Halsall, A.; Harding, N.; Knowles, J. D. et al. Molecular Phenotyping of a UK Population: Defining the Human Serum Metabolome. Metabolomics 2015, 11, 9-26, 10.1007/s11306-014-0707-1
Tu, J. V. Advantages and Disadvantages of Using Artificial Neural Networks versus Logistic Regression for Predicting Medical Outcomes. J. Chronic Dis. 1996, 49, 1225-1231, 10.1016/S0895-4356(96)00002-9
Ransohoff, D. F. Rules of Evidence for Cancer Molecular-Marker Discovery and Validation. Nat. Rev. Cancer 2004, 4, 309-314, 10.1038/nrc1322
Rakotomalala, R. Analyse Discriminante Lineaíre. http://eric.univ-lyon2.fr/~ricco/cours/slides/analyse_discriminante.pdf. (accessed Jul 18, 2019).
Xia, J.; Broadhurst, D. I.; Wilson, M.; Wishart, D. S. Translational Biomarker Discovery in Clinical Metabolomics: An Introductory Tutorial. Metabolomics 2013, 9, 280-299, 10.1007/s11306-012-0482-9
Miyake, N.; Otsuke, Y.; Kurata, T. Autoxidation Reaction Mechanism for L-Ascorbic Acid in Methanol without Metal Ion Catalysis. Biosci., Biotechnol., Biochem. 1997, 61, 2069-2075, 10.1271/bbb.61.2069
Roux, A.; Thévenot, E. A.; Seguin, F.; Olivier, M.-F.; Junot, C. 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 2015, 11, 1095-1105, 10.1007/s11306-014-0764-5
Sumner, L. W.; Amberg, A.; Barrett, D.; Beale, M. H.; Beger, R.; Daykin, C. A.; Fan, T. W.-M.; Fiehn, O.; Goodacre, R.; Griffin, J. L. et al. Proposed Minimum Reporting Standards for Chemical Analysis Chemical Analysis Working Group (CAWG) Metabolomics Standards Initiative (MSI). Metabolomics 2007, 3, 211-221, 10.1007/s11306-007-0082-2
Salek, R. M.; Steinbeck, C.; Viant, M. R.; Goodacre, R.; Dunn, W. B. The Role of Reporting Standards for Metabolite Annotation and Identification in Metabolomic Studies. Gigascience 2013, 2, 13, 10.1186/2047-217X-2-13
Halket, J. M.; Waterman, D.; Przyborowska, A. M.; Patel, R. K. P.; Fraser, P. D.; Bramley, P. M. Chemical Derivatization and Mass Spectral Libraries in Metabolic Profiling by GC/MS and LC/MS/MS. J. Exp. Bot. 2005, 56, 219-243, 10.1093/jxb/eri069
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