Autonomous Metabolomics for Rapid Metabolite Identification in Global Profiling

Benton, H. Paul; Ivanisevic, Julijana; Mahieu, Nathaniel G.; Kurczy, Michael E.; Johnson, Caroline H.; Franco, Lauren; Rinehart, Duane; Valentine, Elizabeth; Gowda, Harsha; Ubhi, Baljit K.; Tautenhahn, Ralf; Gieschen, Andrew; Fields, Matthew W.; Patti, Gary J.; Siuzdak, Gary

doi:10.1021/ac5025649

Title: Autonomous Metabolomics for Rapid Metabolite Identification in Global Profiling

Journal Article · Fri Dec 12 00:00:00 EST 2014 · Analytical Chemistry

DOI:https://doi.org/10.1021/ac5025649· OSTI ID:1344895

Benton, H. Paul ^[1]; Ivanisevic, Julijana ^[1]; Mahieu, Nathaniel G. ^[2]; Kurczy, Michael E. ^[1]; Johnson, Caroline H. ^[1]; Franco, Lauren ^[3]; Rinehart, Duane ^[1]; Valentine, Elizabeth ^[4]; Gowda, Harsha ^[5]; Ubhi, Baljit K. ^[6]; Tautenhahn, Ralf ^[7]; Gieschen, Andrew ^[8]; Fields, Matthew W. ^[3]; Patti, Gary J. ^[2]; Siuzdak, Gary ^[9]

Scripps Research Inst., La Jolla, CA (United States). Scripps Center for Metabolomics and Mass Spectrometry
Washington Univ., St. Louis, MO (United States). Dept. of Chemistry
Montana State Univ., Bozeman, MT (United States). Dept. of Microbiology and Immunology and Center for Biofilm Engineering
Scripps Research Inst., La Jolla, CA (United States). The Skaggs Inst. for Chemical Biology
Scripps Research Inst., La Jolla, CA (United States). Scripps Center for Metabolomics and Mass Spectrometry; Inst. of Bioinformatics, Bangalore (India)
AB SCIEX, Redwod City, CA (United States)
Scripps Research Inst., La Jolla, CA (United States). Scripps Center for Metabolomics and Mass Spectrometry; Thermo Fisher Scientific, San Jose, CA (United States)
Agilent Technologies, La Jolla, CA (United States)
Scripps Research Inst., La Jolla, CA (United States)

An autonomous metabolomic workflow combining mass spectrometry analysis with tandem mass spectrometry data acquisition was designed to allow for simultaneous data processing and metabolite characterization. Although previously tandem mass spectrometry data have been generated on the fly, the experiments described herein combine this technology with the bioinformatic resources of XCMS and METLIN. We can analyze large profiling datasets and simultaneously obtain structural identifications, as a result of this unique integration. Furthermore, validation of the workflow on bacterial samples allowed the profiling on the order of a thousand metabolite features with simultaneous tandem mass spectra data acquisition. The tandem mass spectrometry data acquisition enabled automatic search and matching against the METLIN tandem mass spectrometry database, shortening the current workflow from days to hours. Overall, the autonomous approach to untargeted metabolomics provides an efficient means of metabolomic profiling, and will ultimately allow the more rapid integration of comparative analyses, metabolite identification, and data analysis at a systems biology level.

View Accepted Manuscript (DOE)

Cite

Export

Save

Research Organization:: Scripps Research Inst., La Jolla, CA (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER)

Grant/Contract Number:: AC02-05CH11231

OSTI ID:: 1344895

Journal Information:: Analytical Chemistry, Vol. 87, Issue 2; ISSN 0003-2700

Publisher:: American Chemical Society (ACS)Copyright Statement

Country of Publication:: United States

Language:: English

Citation Metrics:

Cited by: 140 works

Citation information provided by
Web of Science

References (22)

Metabolomics: the apogee of the omics trilogy Patti, Gary J.; Yanes, Oscar; Siuzdak, Gary Nature Reviews Molecular Cell Biology, Vol. 13, Issue 4 https://doi.org/10.1038/nrm3314	journal	March 2012
Metabolite profiling for plant functional genomics Fiehn, Oliver; Kopka, Joachim; Dörmann, Peter Nature Biotechnology, Vol. 18, Issue 11 https://doi.org/10.1038/81137	journal	November 2000
Mass spectrometry-based metabolomics Dettmer, Katja; Aronov, Pavel A.; Hammock, Bruce D. Mass Spectrometry Reviews, Vol. 26, Issue 1 https://doi.org/10.1002/mas.20108	journal	January 2006
Looking back into the future: 30 years of metabolomics at TNO: LOOKING BACK INTO THE FUTURE van der Greef, Jan; van Wietmarschen, Herman; van Ommen, Ben Mass Spectrometry Reviews, Vol. 32, Issue 5 https://doi.org/10.1002/mas.21370	journal	April 2013
Challenges and opportunities of metabolomics Johnson, Caroline H.; Gonzalez, Frank J. Journal of Cellular Physiology, Vol. 227, Issue 8 https://doi.org/10.1002/jcp.24002	journal	April 2012
XCMS: Processing Mass Spectrometry Data for Metabolite Profiling Using Nonlinear Peak Alignment, Matching, and Identification Smith, Colin A.; Want, Elizabeth J.; O'Maille, Grace Analytical Chemistry, Vol. 78, Issue 3 https://doi.org/10.1021/ac051437y	journal	February 2006
XCMS Online: A Web-Based Platform to Process Untargeted Metabolomic Data Tautenhahn, Ralf; Patti, Gary J.; Rinehart, Duane Analytical Chemistry, Vol. 84, Issue 11 https://doi.org/10.1021/ac300698c	journal	June 2012
METLIN: A Metabolite Mass Spectral Database Smith, Colin A.; Maille, Grace O??; Want, Elizabeth J. Therapeutic Drug Monitoring, Vol. 27, Issue 6 https://doi.org/10.1097/01.ftd.0000179845.53213.39	journal	January 2005
An accelerated workflow for untargeted metabolomics using the METLIN database Tautenhahn, Ralf; Cho, Kevin; Uritboonthai, Winnie Nature Biotechnology, Vol. 30, Issue 9 https://doi.org/10.1038/nbt.2348	journal	September 2012
Liquid chromatography quadrupole time-of-flight mass spectrometry characterization of metabolites guided by the METLIN database Zhu, Zheng-Jiang; Schultz, Andrew W.; Wang, Junhua Nature Protocols, Vol. 8, Issue 3 https://doi.org/10.1038/nprot.2013.004	journal	February 2013
Interactive XCMS Online: Simplifying Advanced Metabolomic Data Processing and Subsequent Statistical Analyses Gowda, Harsha; Ivanisevic, Julijana; Johnson, Caroline H. Analytical Chemistry, Vol. 86, Issue 14 https://doi.org/10.1021/ac500734c	journal	June 2014
XCMS ² : Processing Tandem Mass Spectrometry Data for Metabolite Identification and Structural Characterization Benton, H. P.; Wong, D. M.; Trauger, S. A. Analytical Chemistry, Vol. 80, Issue 16 https://doi.org/10.1021/ac800795f	journal	July 2008
HMDB 3.0—The Human Metabolome Database in 2013 Wishart, David S.; Jewison, Timothy; Guo, An Chi Nucleic Acids Research, Vol. 41, Issue D1 https://doi.org/10.1093/nar/gks1065	journal	November 2012
MassBank: a public repository for sharing mass spectral data for life sciences Horai, Hisayuki; Arita, Masanori; Kanaya, Shigehiko Journal of Mass Spectrometry, Vol. 45, Issue 7 https://doi.org/10.1002/jms.1777	journal	July 2010
Overcoming the anaerobic hurdle in phenotypic microarrays: Generation and visualization of growth curve data for Desulfovibrio vulgaris Hildenborough Borglin, Sharon; Joyner, Dominique; Jacobsen, Janet Journal of Microbiological Methods, Vol. 76, Issue 2 https://doi.org/10.1016/j.mimet.2008.10.003	journal	February 2009
Toward ‘Omic Scale Metabolite Profiling: A Dual Separation–Mass Spectrometry Approach for Coverage of Lipid and Central Carbon Metabolism Ivanisevic, Julijana; Zhu, Zheng-Jiang; Plate, Lars Analytical Chemistry, Vol. 85, Issue 14 https://doi.org/10.1021/ac401140h	journal	July 2013
CAMERA: An Integrated Strategy for Compound Spectra Extraction and Annotation of Liquid Chromatography/Mass Spectrometry Data Sets Kuhl, Carsten; Tautenhahn, Ralf; Böttcher, Christoph Analytical Chemistry, Vol. 84, Issue 1 https://doi.org/10.1021/ac202450g	journal	December 2011
Bioinformatics: The Next Frontier of Metabolomics Johnson, Caroline H.; Ivanisevic, Julijana; Benton, H. Paul Analytical Chemistry, Vol. 87, Issue 1 https://doi.org/10.1021/ac5040693	journal	November 2014
Assigning Significance to Peptides Identified by Tandem Mass Spectrometry Using Decoy Databases Käll, Lukas; Storey, John D.; MacCoss, Michael J. Journal of Proteome Research, Vol. 7, Issue 1 https://doi.org/10.1021/pr700600n	journal	January 2008
X-Rank: A Robust Algorithm for Small Molecule Identification Using Tandem Mass Spectrometry Mylonas, Roman; Mauron, Yann; Masselot, Alexandre Analytical Chemistry, Vol. 81, Issue 18 https://doi.org/10.1021/ac900954d	journal	August 2009
Credentialing Features: A Platform to Benchmark and Optimize Untargeted Metabolomic Methods Mahieu, Nathaniel Guy; Huang, Xiaojing; Chen, Ying-Jr Analytical Chemistry, Vol. 86, Issue 19 https://doi.org/10.1021/ac503092d	journal	September 2014
Metabolic profiling on the right path Glassbrook, Norm; Beecher, Chris; Ryals, John Nature Biotechnology, Vol. 18, Issue 11 https://doi.org/10.1038/81116	journal	November 2000

Cited By (33)

Untargeted metabolomic on urine samples after α-lipoic acid and/or eicosapentaenoic acid supplementation in healthy overweight/obese women Romo-Hualde, Ana; Huerta, Ana E.; González-Navarro, Carlos J. Lipids in Health and Disease, Vol. 17, Issue 1 https://doi.org/10.1186/s12944-018-0750-4	journal	May 2018
Mass Isotopologue Distribution of dimer ion adducts of intracellular metabolites for potential applications in 13C Metabolic Flux Analysis Prasannan, Charulata B.; Mishra, Vivek; Jaiswal, Damini PLOS ONE, Vol. 14, Issue 8 https://doi.org/10.1371/journal.pone.0220412	journal	August 2019
Identification of metabolites from tandem mass spectra with a machine learning approach utilizing structural features Li, Yuanyue; Kuhn, Michael; Gavin, Anne-Claude Bioinformatics https://doi.org/10.1101/573790	journal	March 2019
A Study on Tissue-Specific Metabolite Variations in Polygonum cuspidatum by High-Resolution Mass Spectrometry-Based Metabolic Profiling Wu, Zhijun; Wang, Xiaowei; Chen, Mo Molecules, Vol. 24, Issue 6 https://doi.org/10.3390/molecules24061058	journal	March 2019
Arteriovenous Blood Metabolomics: A Readout of Intra-Tissue Metabostasis Ivanisevic, Julijana; Elias, Darlene; Deguchi, Hiroshi Scientific Reports, Vol. 5, Issue 1 https://doi.org/10.1038/srep12757	journal	August 2015
Promises and pitfalls of untargeted metabolomics Gertsman, Ilya; Barshop, Bruce A. Journal of Inherited Metabolic Disease, Vol. 41, Issue 3 https://doi.org/10.1007/s10545-017-0130-7	journal	March 2018
Antioxidant Activity of the Lignins Derived from Fluidized-Bed Fast Pyrolysis Qazi, Sohail; Li, Dongbing; Briens, Cedric Molecules, Vol. 22, Issue 3 https://doi.org/10.3390/molecules22030372	journal	March 2017
The Role of Metabolomics in Brain Metabolism Research Ivanisevic, Julijana; Siuzdak, Gary Journal of Neuroimmune Pharmacology, Vol. 10, Issue 3 https://doi.org/10.1007/s11481-015-9621-1	journal	July 2015
Data processing, multi-omic pathway mapping, and metabolite activity analysis using XCMS Online Forsberg, Erica M.; Huan, Tao; Rinehart, Duane Nature Protocols, Vol. 13, Issue 4 https://doi.org/10.1038/nprot.2017.151	journal	March 2018
An improved method for extraction of polar and charged metabolites from cyanobacteria Prasannan, Charulata B.; Jaiswal, Damini; Davis, Rose PLOS ONE, Vol. 13, Issue 10 https://doi.org/10.1371/journal.pone.0204273	journal	October 2018
Bulk phase resource ratio alters carbon steel corrosion rates and endogenously produced extracellular electron transfer mediators in a sulfate-reducing biofilm Krantz, Gregory P.; Lucas, Kilean; Wunderlich, Erica L. - Taylor & Francis https://doi.org/10.6084/m9.figshare.9505367.v1	text	January 2019
Updates in metabolomics tools and resources: 2014-2015: General Misra, Biswapriya B.; van der Hooft, Justin J. J. ELECTROPHORESIS, Vol. 37, Issue 1 https://doi.org/10.1002/elps.201500417	journal	November 2015
The proteomic and metabolomic characterization of exercise-induced sweat for human performance monitoring: A pilot investigation Harshman, Sean W.; Pitsch, Rhonda L.; Smith, Zachary K. PLOS ONE, Vol. 13, Issue 11 https://doi.org/10.1371/journal.pone.0203133	journal	November 2018
A Protocol to Compare Methods for Untargeted Metabolomics Wang, Lingjue; Naser, Fuad J.; Spalding, Jonathan L. Metabolic Signaling https://doi.org/10.1007/978-1-4939-8769-6_1	book	October 2018
LC–MS/MS-Based Metabolome Analysis of Biochemical Pathways Altered by Food Limitation in Larvae of Ivory Shell, Babylonia areolata Fu, Jingqiang; Shen, Minghui; Shen, Yawei Marine Biotechnology, Vol. 20, Issue 4 https://doi.org/10.1007/s10126-018-9808-6	journal	April 2018
An automated high-throughput sample preparation method using double-filtration for serum metabolite LC-MS analysis Joo, Minjoong; Park, Jong-Moon; Duong, Van-An Analytical Methods, Vol. 11, Issue 31 https://doi.org/10.1039/c9ay01137d	journal	January 2019
Using diphenyleneiodonium to induce a viable but non-culturable phenotype in Mycobacterium tuberculosis and its metabolomics analysis Yeware, Amar; Gample, Suwarna; Agrawal, Sonia PLOS ONE, Vol. 14, Issue 8 https://doi.org/10.1371/journal.pone.0220628	journal	August 2019
Identification of small molecules using accurate mass MS/MS search Kind, Tobias; Tsugawa, Hiroshi; Cajka, Tomas Mass Spectrometry Reviews, Vol. 37, Issue 4 https://doi.org/10.1002/mas.21535	journal	April 2017
From Samples to Insights into Metabolism: Uncovering Biologically Relevant Information in LC-HRMS Metabolomics Data Ivanisevic, Julijana; Want, Elizabeth J. Metabolites, Vol. 9, Issue 12 https://doi.org/10.3390/metabo9120308	journal	December 2019
Systems biology guided by XCMS Online metabolomics Huan, Tao; Forsberg, Erica M.; Rinehart, Duane Nature Methods, Vol. 14, Issue 5 https://doi.org/10.1038/nmeth.4260	journal	April 2017
Deciphering complex metabolite mixtures by unsupervised and supervised substructure discovery and semi-automated annotation from MS/MS spectra Rogers, Simon; Ong, Cher Wei; Wandy, Joe Faraday Discussions, Vol. 218 https://doi.org/10.1039/c8fd00235e	journal	January 2019
Copper oxide nanoparticle toxicity profiling using untargeted metabolomics Boyles, Matthew S. P.; Ranninger, Christina; Reischl, Roland Particle and Fibre Toxicology, Vol. 13, Issue 1 https://doi.org/10.1186/s12989-016-0160-6	journal	December 2015
Challenges and emergent solutions for LC-MS/MS based untargeted metabolomics in diseases Cui, Liang; Lu, Haitao; Lee, Yie Hou Mass Spectrometry Reviews, Vol. 37, Issue 6 https://doi.org/10.1002/mas.21562	journal	February 2018
Identification of metabolites from tandem mass spectra with a machine learning approach utilizing structural features Li, Yuanyue; Kuhn, Michael; Gavin, Anne-Claude Bioinformatics https://doi.org/10.1093/bioinformatics/btz736	journal	October 2019
Bulk phase resource ratio alters carbon steel corrosion rates and endogenously produced extracellular electron transfer mediators in a sulfate-reducing biofilm Krantz, Gregory P.; Lucas, Kilean; Wunderlich, Erica L. - Biofouling, Vol. 35, Issue 6 https://doi.org/10.1080/08927014.2019.1646731	journal	July 2019
Deciphering complex metabolite mixtures by unsupervised and supervised substructure discovery and semi-automated annotation from MS/MS spectra Rogers, Simon; Wei Ong, Cher; Wandy, Joe Faraday Discussions https://doi.org/10.1101/491506	journal	December 2018
Bulk phase resource ratio alters carbon steel corrosion rates and endogenously produced extracellular electron transfer mediators in a sulfate-reducing biofilm Krantz, Gregory P.; Lucas, Kilean; Wunderlich, Erica L. - Taylor & Francis https://doi.org/10.6084/m9.figshare.9505367	text	January 2019
Bar Coding MS² Spectra for Metabolite Identification Spalding, Jonathan L.; Cho, Kevin; Mahieu, Nathaniel G. Analytical Chemistry, Vol. 88, Issue 5 https://doi.org/10.1021/acs.analchem.5b04925	journal	February 2016
Systems-Level Annotation of Metabolomics Data Reduces 25,000 Features to Fewer than 1,000 Unique Metabolites Mahieu, Nathaniel G.; Patti, GAry J. Analytical Chemistry https://doi.org/10.1101/155895	journal	June 2017
Plasma metabolomic study in Chinese patients with wet age-related macular degeneration Luo, Dan; Deng, Tingting; Yuan, Wei BMC Ophthalmology, Vol. 17, Issue 1 https://doi.org/10.1186/s12886-017-0555-7	journal	September 2017
Metabolomics guided pathway analysis reveals link between cancer metastasis, cholesterol sulfate, and phospholipids Johnson, Caroline H.; Santidrian, Antonio F.; LeBoeuf, Sarah E. Cancer & Metabolism, Vol. 5, Issue 1 https://doi.org/10.1186/s40170-017-0171-2	journal	October 2017
Metabolic drift in the aging brain Ivanisevic, Julijana; Stauch, Kelly L.; Petrascheck, Michael Aging, Vol. 8, Issue 5 https://doi.org/10.18632/aging.100961	journal	May 2016
Plasma metabolic characterisation of dairy cows with inactive ovaries and oestrus during the peak of lactation Song, Yu-Xi; Hu, Pan; Bai, Yun-Long Journal of Veterinary Research, Vol. 63, Issue 3 https://doi.org/10.2478/jvetres-2019-0047	journal	September 2019

Linked Research (11)

Similar Records

Autonomous METLIN-Guided In-source Fragment Annotation for Untargeted Metabolomics

Journal Article · Fri Jan 25 00:00:00 EST 2019 · Analytical Chemistry · OSTI ID:1344895

Domingo-Almenara, Xavier; Montenegro-Burke, J. Rafael; Guijas, Carlos; +3 more

XCMS Online: A Web-Based Platform to Process Untargeted Metabolomic Data

Journal Article · Tue Jun 05 00:00:00 EDT 2012 · Analytical Chemistry · OSTI ID:1344895

Tautenhahn, Ralf; Patti, Gary J.; Rinehart, Duane; +1 more

Liquid chromatography quadrupole time-of-flight mass spectrometry characterization of metabolites guided by the METLIN database

Journal Article · Thu Feb 07 00:00:00 EST 2013 · Nature Protocols · OSTI ID:1344895

Zhu, Zheng-Jiang; Schultz, Andrew W.; Wang, Junhua; +4 more

Related Subjects

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY
59 BASIC BIOLOGICAL SCIENCES

Additional file 10 of Magnaporthe oryzae systemic defense trigger 1 (MoSDT1)-mediated metabolites regulate defense response in Rice Duan, Guihua; Li, Chunqin; Liu, Yanfang https://doi.org/10.6084/m9.figshare.13558654.v1 The current record is supplemented by this text	text	January 2021
Additional file 1 of Magnaporthe oryzae systemic defense trigger 1 (MoSDT1)-mediated metabolites regulate defense response in Rice Duan, Guihua; Li, Chunqin; Liu, Yanfang https://doi.org/10.6084/m9.figshare.13558657.v1 The current record is supplemented by this image	image	January 2021
Additional file 2 of Magnaporthe oryzae systemic defense trigger 1 (MoSDT1)-mediated metabolites regulate defense response in Rice Duan, Guihua; Li, Chunqin; Liu, Yanfang https://doi.org/10.6084/m9.figshare.13558660.v1 The current record is supplemented by this dataset	dataset	January 2021
Additional file 3 of Magnaporthe oryzae systemic defense trigger 1 (MoSDT1)-mediated metabolites regulate defense response in Rice Duan, Guihua; Li, Chunqin; Liu, Yanfang https://doi.org/10.6084/m9.figshare.13558663 The current record is supplemented by this text	text	January 2021
Additional file 4 of Magnaporthe oryzae systemic defense trigger 1 (MoSDT1)-mediated metabolites regulate defense response in Rice Duan, Guihua; Li, Chunqin; Liu, Yanfang https://doi.org/10.6084/m9.figshare.13558666 The current record is supplemented by this text	text	January 2021
Additional file 5 of Magnaporthe oryzae systemic defense trigger 1 (MoSDT1)-mediated metabolites regulate defense response in Rice Duan, Guihua; Li, Chunqin; Liu, Yanfang https://doi.org/10.6084/m9.figshare.13558669.v1 The current record is supplemented by this text	text	January 2021
Additional file 6 of Magnaporthe oryzae systemic defense trigger 1 (MoSDT1)-mediated metabolites regulate defense response in Rice Duan, Guihua; Li, Chunqin; Liu, Yanfang https://doi.org/10.6084/m9.figshare.13558672 The current record is supplemented by this text	text	January 2021
Additional file 7 of Magnaporthe oryzae systemic defense trigger 1 (MoSDT1)-mediated metabolites regulate defense response in Rice Duan, Guihua; Li, Chunqin; Liu, Yanfang https://doi.org/10.6084/m9.figshare.13558678 The current record is supplemented by this text	text	January 2021
Additional file 8 of Magnaporthe oryzae systemic defense trigger 1 (MoSDT1)-mediated metabolites regulate defense response in Rice Duan, Guihua; Li, Chunqin; Liu, Yanfang https://doi.org/10.6084/m9.figshare.13558681 The current record is supplemented by this text	text	January 2021
Additional file 9 of Magnaporthe oryzae systemic defense trigger 1 (MoSDT1)-mediated metabolites regulate defense response in Rice Duan, Guihua; Li, Chunqin; Liu, Yanfang https://doi.org/10.6084/m9.figshare.13558684.v1 The current record is supplemented by this dataset	dataset	January 2021
Magnaporthe oryzae systemic defense trigger 1 (MoSDT1)-mediated metabolites regulate defense response in Rice Duan, Guihua; Li, Chunqin; Liu, Yanfang https://doi.org/10.6084/m9.figshare.c.5265250 The current record is supplemented by this collection	collection	January 2021