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Title: Autonomous Metabolomics for Rapid Metabolite Identification in Global Profiling

Abstract

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.

Authors:
 [1];  [1];  [2];  [1];  [1];  [3];  [1];  [4];  [5];  [6];  [7];  [8];  [3];  [2];  [9]
+ Show Author Affiliations
  1. Scripps Research Inst., La Jolla, CA (United States). Scripps Center for Metabolomics and Mass Spectrometry
  2. Washington Univ., St. Louis, MO (United States). Dept. of Chemistry
  3. Montana State Univ., Bozeman, MT (United States). Dept. of Microbiology and Immunology and Center for Biofilm Engineering
  4. Scripps Research Inst., La Jolla, CA (United States). The Skaggs Inst. for Chemical Biology
  5. Scripps Research Inst., La Jolla, CA (United States). Scripps Center for Metabolomics and Mass Spectrometry; Inst. of Bioinformatics, Bangalore (India)
  6. AB SCIEX, Redwod City, CA (United States)
  7. Scripps Research Inst., La Jolla, CA (United States). Scripps Center for Metabolomics and Mass Spectrometry; Thermo Fisher Scientific, San Jose, CA (United States)
  8. Agilent Technologies, La Jolla, CA (United States)
  9. Scripps Research Inst., La Jolla, CA (United States)
Publication Date:
Research Org.:
Scripps Research Inst., La Jolla, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER)
OSTI Identifier:
1344895
Grant/Contract Number:  
AC02-05CH11231
Resource Type:
Accepted Manuscript
Journal Name:
Analytical Chemistry
Additional Journal Information:
Journal Volume: 87; Journal Issue: 2; Journal ID: ISSN 0003-2700
Publisher:
American Chemical Society (ACS)
Country of Publication:
United States
Language:
English
Subject:
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY; 59 BASIC BIOLOGICAL SCIENCES

Citation Formats

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., and Siuzdak, Gary. Autonomous Metabolomics for Rapid Metabolite Identification in Global Profiling. United States: N. p., 2014. Web. doi:10.1021/ac5025649.
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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. Autonomous Metabolomics for Rapid Metabolite Identification in Global Profiling. United States. https://doi.org/10.1021/ac5025649
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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., and Siuzdak, Gary. Fri . "Autonomous Metabolomics for Rapid Metabolite Identification in Global Profiling". United States. https://doi.org/10.1021/ac5025649. https://www.osti.gov/servlets/purl/1344895.
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@article{osti_1344895,
title = {Autonomous Metabolomics for Rapid Metabolite Identification in Global Profiling},
author = {Benton, H. Paul and Ivanisevic, Julijana and Mahieu, Nathaniel G. and Kurczy, Michael E. and Johnson, Caroline H. and Franco, Lauren and Rinehart, Duane and Valentine, Elizabeth and Gowda, Harsha and Ubhi, Baljit K. and Tautenhahn, Ralf and Gieschen, Andrew and Fields, Matthew W. and Patti, Gary J. and Siuzdak, Gary},
abstractNote = {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.},
doi = {10.1021/ac5025649},
journal = {Analytical Chemistry},
number = 2,
volume = 87,
place = {United States},
year = {Fri Dec 12 00:00:00 EST 2014},
month = {Fri Dec 12 00:00:00 EST 2014}
}
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Challenges and opportunities of metabolomics
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MassBank: a public repository for sharing mass spectral data for life sciences
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CAMERA: An Integrated Strategy for Compound Spectra Extraction and Annotation of Liquid Chromatography/Mass Spectrometry Data Sets
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XCMS Online: A Web-Based Platform to Process Untargeted Metabolomic Data
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Toward ‘Omic Scale Metabolite Profiling: A Dual Separation–Mass Spectrometry Approach for Coverage of Lipid and Central Carbon Metabolism
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Interactive XCMS Online: Simplifying Advanced Metabolomic Data Processing and Subsequent Statistical Analyses
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Credentialing Features: A Platform to Benchmark and Optimize Untargeted Metabolomic Methods
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Bioinformatics: The Next Frontier of Metabolomics
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