Biswapriya B Misra1,2, Ekong Bassey3, Andrew C Bishop2, David T Kusel3, Laura A Cox1,2,4, Michael Olivier1,2,4. 1. Center for Precision Medicine, Department of Internal Medicine, Section of Molecular Medicine, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC, 27157, USA. 2. Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX, 78227, USA. 3. Thermo Fisher Scientific, 355 River Oaks Parkway, San Jose, CA, 95134, USA. 4. Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio, TX, 78227, USA.
Abstract
RATIONALE: Metabolomics analyses using gas chromatography/mass spectrometry (GC/MS)-based metabolomics are heavily impeded by the lack of high-resolution mass spectrometers and limited spectral libraries to complement the excellent chromatography that GC platforms offer, a challenge that is being addressed with the implementation of high-resolution (HR) platforms such as 1D-GC/Orbitrap-MS. METHODS: We used serum samples from a non-human primate (NHP), a baboon (Papio hamadryas), with suitable quality controls to quantify the chemical space using an advanced HRMS platform for confident metabolite identification and robust quantification to assess the suitability of the platform for routine clinical metabolomics research. In a complementary approach, we also analyzed the same serum samples using two-dimensional gas chromatography/time-of-flight mass spectrometry (2D-GC/TOF-MS) for metabolite identification and quantification following established standard protocols. RESULTS: Overall, the 2D-GC/TOF-MS (~5000 peaks per sample) and 1D-GC/Orbitrap-MS (~500 peaks per sample) analyses enabled identification and quantification of a total of 555 annotated metabolites from the NHP serum with a spectral similarity score Rsim ≥ 900 and signal-to-noise (S/N) ratio of >25. A common set of 30 metabolites with HMDB and KEGG IDs was quantified in the serum samples by both platforms where 2D-GC/TOF-MS enabled quantification of a total 384 metabolites (118 HMDB IDs) and 1D-GC/Orbitrap-MS analysis quantification of a total 200 metabolites (47 HMDB IDs). Thus, roughly 30-70% of the peaks remain unidentified or un-annotated across both platforms. CONCLUSIONS: Our study provides insights into the benefits and limitations of the use of a higher mass resolution and mass accuracy instrument for untargeted GC/MS-based metabolomics with multi-dimensional chromatography in future studies addressing clinical conditions or exposome studies.
RATIONALE: Metabolomics analyses using gas chromatography/mass spectrometry (GC/MS)-based metabolomics are heavily impeded by the lack of high-resolution mass spectrometers and limited spectral libraries to complement the excellent chromatography that GC platforms offer, a challenge that is being addressed with the implementation of high-resolution (HR) platforms such as 1D-GC/Orbitrap-MS. METHODS: We used serum samples from a non-human primate (NHP), a baboon (Papio hamadryas), with suitable quality controls to quantify the chemical space using an advanced HRMS platform for confident metabolite identification and robust quantification to assess the suitability of the platform for routine clinical metabolomics research. In a complementary approach, we also analyzed the same serum samples using two-dimensional gas chromatography/time-of-flight mass spectrometry (2D-GC/TOF-MS) for metabolite identification and quantification following established standard protocols. RESULTS: Overall, the 2D-GC/TOF-MS (~5000 peaks per sample) and 1D-GC/Orbitrap-MS (~500 peaks per sample) analyses enabled identification and quantification of a total of 555 annotated metabolites from the NHP serum with a spectral similarity score Rsim ≥ 900 and signal-to-noise (S/N) ratio of >25. A common set of 30 metabolites with HMDB and KEGG IDs was quantified in the serum samples by both platforms where 2D-GC/TOF-MS enabled quantification of a total 384 metabolites (118 HMDB IDs) and 1D-GC/Orbitrap-MS analysis quantification of a total 200 metabolites (47 HMDB IDs). Thus, roughly 30-70% of the peaks remain unidentified or un-annotated across both platforms. CONCLUSIONS: Our study provides insights into the benefits and limitations of the use of a higher mass resolution and mass accuracy instrument for untargeted GC/MS-based metabolomics with multi-dimensional chromatography in future studies addressing clinical conditions or exposome studies.
Authors: Joachim Kopka; Nicolas Schauer; Stephan Krueger; Claudia Birkemeyer; Björn Usadel; Eveline Bergmüller; Peter Dörmann; Wolfram Weckwerth; Yves Gibon; Mark Stitt; Lothar Willmitzer; Alisdair R Fernie; Dirk Steinhauser Journal: Bioinformatics Date: 2004-12-21 Impact factor: 6.937
Authors: Jiye A; Johan Trygg; Jonas Gullberg; Annika I Johansson; Pär Jonsson; Henrik Antti; Stefan L Marklund; Thomas Moritz Journal: Anal Chem Date: 2005-12-15 Impact factor: 6.986
Authors: Warwick B Dunn; David Broadhurst; David I Ellis; Marie Brown; Anthony Halsall; Steven O'Hagan; Irena Spasic; Andrew Tseng; Douglas B Kell Journal: Int J Epidemiol Date: 2008-04 Impact factor: 7.196
Authors: Giovanni Berardi; Laura Frey-Law; Kathleen A Sluka; Emine O Bayman; Christopher S Coffey; Dixie Ecklund; Carol G T Vance; Dana L Dailey; John Burns; Asokumar Buvanendran; Robert J McCarthy; Joshua Jacobs; Xiaohong Joe Zhou; Richard Wixson; Tessa Balach; Chad M Brummett; Daniel Clauw; Douglas Colquhoun; Steven E Harte; Richard E Harris; David A Williams; Andrew C Chang; Jennifer Waljee; Kathleen M Fisch; Kristen Jepsen; Louise C Laurent; Michael Olivier; Carl D Langefeld; Timothy D Howard; Oliver Fiehn; Jon M Jacobs; Panshak Dakup; Wei-Jun Qian; Adam C Swensen; Anna Lokshin; Martin Lindquist; Brian S Caffo; Ciprian Crainiceanu; Scott Zeger; Ari Kahn; Tor Wager; Margaret Taub; James Ford; Stephani P Sutherland; Laura D Wandner Journal: Front Med (Lausanne) Date: 2022-04-25
Authors: Lorenzo Bertolone; Hye K Shin; Davide Stefanoni; Jin Hyen Baek; Yamei Gao; Evan J Morrison; Travis Nemkov; Tiffany Thomas; Richard O Francis; Eldad A Hod; James C Zimring; Tatsuro Yoshida; Matthew Karafin; Joseph Schwartz; Krystalyn E Hudson; Steven L Spitalnik; Paul W Buehler; Angelo D'Alessandro Journal: Front Physiol Date: 2020-10-23 Impact factor: 4.566