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:
-
- 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)
- 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.
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
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.
@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}
}
Web of Science
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