A Strategy for Sensitive, Large Scale Quantitative Metabolomics

Overview

Journal J Vis Exp

Specialties Biology
General Medicine

Date 2014 Jun 5

PMID 24894601

Citations 17

Authors

Xiaojing Liu

Zheng Ser

Ahmad A Cluntun

Samantha J Mentch

Jason W Locasale

Affiliations

Soon will be listed here.

Abstract

Metabolite profiling has been a valuable asset in the study of metabolism in health and disease. However, current platforms have different limiting factors, such as labor intensive sample preparations, low detection limits, slow scan speeds, intensive method optimization for each metabolite, and the inability to measure both positively and negatively charged ions in single experiments. Therefore, a novel metabolomics protocol could advance metabolomics studies. Amide-based hydrophilic chromatography enables polar metabolite analysis without any chemical derivatization. High resolution MS using the Q-Exactive (QE-MS) has improved ion optics, increased scan speeds (256 msec at resolution 70,000), and has the capability of carrying out positive/negative switching. Using a cold methanol extraction strategy, and coupling an amide column with QE-MS enables robust detection of 168 targeted polar metabolites and thousands of additional features simultaneously. Data processing is carried out with commercially available software in a highly efficient way, and unknown features extracted from the mass spectra can be queried in databases.

Citing Articles

Tackling new psychoactive substances through metabolomics: UHPLC-HRMS study on natural and synthetic opioids in male and female murine models.

Di Francesco G, Montesano C, Vincenti F, Bilel S, Corli G, Petrella G Sci Rep. 2024; 14(1):9432.

PMID: 38658766 PMC: 11043364. DOI: 10.1038/s41598-024-60045-2.

EMT alterations in the solute carrier landscape uncover SLC22A10/A15 imposed vulnerabilities in pancreatic cancer.

Nayak D, Weadick B, Persaud A, Raj R, Shakya R, Li J iScience. 2022; 25(5):104193.

PMID: 35479410 PMC: 9036131. DOI: 10.1016/j.isci.2022.104193.

Global Transcriptional Regulators Fine-Tune the Translational and Metabolic Efficiency for Optimal Growth of Escherichia coli.

Iyer M, Pal A, Srinivasan S, Somvanshi P, Venkatesh K mSystems. 2021; 6(2).

PMID: 33785570 PMC: 8546960. DOI: 10.1128/mSystems.00001-21.

SUCLA2 mutations cause global protein succinylation contributing to the pathomechanism of a hereditary mitochondrial disease.

Gut P, Matilainen S, Meyer J, Pallijeff P, Richard J, Carroll C Nat Commun. 2020; 11(1):5927.

PMID: 33230181 PMC: 7684291. DOI: 10.1038/s41467-020-19743-4.

Evolved resistance to partial GAPDH inhibition results in loss of the Warburg effect and in a different state of glycolysis.

Liberti M, Allen A, Ramesh V, Dai Z, Singleton K, Guo Z J Biol Chem. 2019; 295(1):111-124.

PMID: 31748414 PMC: 6952593. DOI: 10.1074/jbc.RA119.010903.

References

Ramanathan R, Jemal M, Ramagiri S, Xia Y, Humpreys W, Olah T . It is time for a paradigm shift in drug discovery bioanalysis: from SRM to HRMS. J Mass Spectrom. 2011; 46(6):595-601. DOI: 10.1002/jms.1921. View

Jonsson P, Gullberg J, Nordstrom A, Kusano M, Kowalczyk M, Sjostrom M . A strategy for identifying differences in large series of metabolomic samples analyzed by GC/MS. Anal Chem. 2004; 76(6):1738-45. DOI: 10.1021/ac0352427. View

Want E, Wilson I, Gika H, Theodoridis G, Plumb R, Shockcor J . Global metabolic profiling procedures for urine using UPLC-MS. Nat Protoc. 2010; 5(6):1005-18. DOI: 10.1038/nprot.2010.50. View

Yuan M, Breitkopf S, Yang X, Asara J . A positive/negative ion-switching, targeted mass spectrometry-based metabolomics platform for bodily fluids, cells, and fresh and fixed tissue. Nat Protoc. 2012; 7(5):872-81. PMC: 3685491. DOI: 10.1038/nprot.2012.024. View

Ideker T, Thorsson V, Ranish J, Christmas R, Buhler J, Eng J . Integrated genomic and proteomic analyses of a systematically perturbed metabolic network. Science. 2001; 292(5518):929-34. DOI: 10.1126/science.292.5518.929. View

Lu D, Mulder H, Zhao P, Burgess S, Jensen M, Kamzolova S . 13C NMR isotopomer analysis reveals a connection between pyruvate cycling and glucose-stimulated insulin secretion (GSIS). Proc Natl Acad Sci U S A. 2002; 99(5):2708-13. PMC: 122412. DOI: 10.1073/pnas.052005699. View

Snyder N, Khezam M, Mesaros C, Worth A, Blair I . Untargeted metabolomics from biological sources using ultraperformance liquid chromatography-high resolution mass spectrometry (UPLC-HRMS). J Vis Exp. 2013; (75):e50433. PMC: 3711276. DOI: 10.3791/50433. View

Jonsson P, Johansson A, Gullberg J, Trygg J, A J, Grung B . High-throughput data analysis for detecting and identifying differences between samples in GC/MS-based metabolomic analyses. Anal Chem. 2005; 77(17):5635-42. DOI: 10.1021/ac050601e. View

Patel V, Eckel-Mahan K, Sassone-Corsi P, Baldi P . CircadiOmics: integrating circadian genomics, transcriptomics, proteomics and metabolomics. Nat Methods. 2012; 9(8):772-3. DOI: 10.1038/nmeth.2111. View

10.

Kitteringham N, Jenkins R, Lane C, Elliott V, Park B . Multiple reaction monitoring for quantitative biomarker analysis in proteomics and metabolomics. J Chromatogr B Analyt Technol Biomed Life Sci. 2008; 877(13):1229-39. DOI: 10.1016/j.jchromb.2008.11.013. View

11.

Mulleder M, Capuano F, Pir P, Christen S, Sauer U, Oliver S . A prototrophic deletion mutant collection for yeast metabolomics and systems biology. Nat Biotechnol. 2012; 30(12):1176-8. PMC: 3520112. DOI: 10.1038/nbt.2442. View

12.

Michalski A, Damoc E, Lange O, Denisov E, Nolting D, Muller M . Ultra high resolution linear ion trap Orbitrap mass spectrometer (Orbitrap Elite) facilitates top down LC MS/MS and versatile peptide fragmentation modes. Mol Cell Proteomics. 2011; 11(3):O111.013698. PMC: 3316736. DOI: 10.1074/mcp.O111.013698. View

13.

Michalski A, Damoc E, Hauschild J, Lange O, Wieghaus A, Makarov A . Mass spectrometry-based proteomics using Q Exactive, a high-performance benchtop quadrupole Orbitrap mass spectrometer. Mol Cell Proteomics. 2011; 10(9):M111.011015. PMC: 3284220. DOI: 10.1074/mcp.M111.011015. View

14.

Fiehn O . Combining genomics, metabolome analysis, and biochemical modelling to understand metabolic networks. Comp Funct Genomics. 2008; 2(3):155-68. PMC: 2447208. DOI: 10.1002/cfg.82. View

15.

Locasale J, Melman T, Song S, Yang X, Swanson K, Cantley L . Metabolomics of human cerebrospinal fluid identifies signatures of malignant glioma. Mol Cell Proteomics. 2012; 11(6):M111.014688. PMC: 3433896. DOI: 10.1074/mcp.M111.014688. View

16.

Wolf-Yadlin A, Hautaniemi S, Lauffenburger D, White F . Multiple reaction monitoring for robust quantitative proteomic analysis of cellular signaling networks. Proc Natl Acad Sci U S A. 2007; 104(14):5860-5. PMC: 1851582. DOI: 10.1073/pnas.0608638104. View

17.

Lu W, Clasquin M, Melamud E, Amador-Noguez D, Caudy A, Rabinowitz J . Metabolomic analysis via reversed-phase ion-pairing liquid chromatography coupled to a stand alone orbitrap mass spectrometer. Anal Chem. 2010; 82(8):3212-21. PMC: 2863137. DOI: 10.1021/ac902837x. View

18.

Weljie A, Newton J, Mercier P, Carlson E, Slupsky C . Targeted profiling: quantitative analysis of 1H NMR metabolomics data. Anal Chem. 2006; 78(13):4430-42. DOI: 10.1021/ac060209g. View

19.

Wiklund S, Johansson E, Sjostrom L, Mellerowicz E, Edlund U, Shockcor J . Visualization of GC/TOF-MS-based metabolomics data for identification of biochemically interesting compounds using OPLS class models. Anal Chem. 2007; 80(1):115-22. DOI: 10.1021/ac0713510. View

20.

Gika H, Theodoridis G, Wingate J, Wilson I . Within-day reproducibility of an HPLC-MS-based method for metabonomic analysis: application to human urine. J Proteome Res. 2007; 6(8):3291-303. DOI: 10.1021/pr070183p. View