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Article

Lipid Annotator: Towards Accurate Annotation in Non-Targeted Liquid Chromatography High-Resolution Tandem Mass Spectrometry (LC-HRMS/MS) Lipidomics Using a Rapid and User-Friendly Software

1
Department of Pathology, Immunology and Laboratory Medicine, University of Florida, Gainesville, FL 32610, USA
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Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT 06520, USA
3
Agilent Technologies, Santa Clara, CA 95051, USA
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Department of Chemistry, University of Florida, Gainesville, FL 32611, USA
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RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan
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RIKEN Center for Sustainable Resource Science, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan
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Center for Environmental and Human Toxicology & Department of Physiological Sciences, University of Florida, Gainesville, FL 32611, USA
*
Author to whom correspondence should be addressed.
These authors contributed equally.
Metabolites 2020, 10(3), 101; https://doi.org/10.3390/metabo10030101
Received: 28 January 2020 / Revised: 28 February 2020 / Accepted: 6 March 2020 / Published: 12 March 2020
(This article belongs to the Special Issue Compound Identification of Small Molecules)
Lipidomics has great promise in various applications; however, a major bottleneck in lipidomics is the accurate and comprehensive annotation of high-resolution tandem mass spectral data. While the number of available lipidomics software has drastically increased over the past five years, the reduction of false positives and the realization of obtaining structurally accurate annotations remains a significant challenge. We introduce Lipid Annotator, which is a user-friendly software for lipidomic analysis of data collected by liquid chromatography high-resolution tandem mass spectrometry (LC-HRMS/MS). We validate annotation accuracy against lipid standards and other lipidomics software. Lipid Annotator was integrated into a workflow applying an iterative exclusion MS/MS acquisition strategy to National Institute of Standards and Technology (NIST) SRM 1950 Metabolites in Frozen Human Plasma using reverse phase LC-HRMS/MS. Lipid Annotator, LipidMatch, and MS-DIAL produced consensus annotations at the level of lipid class for 98% and 96% of features detected in positive and negative mode, respectively. Lipid Annotator provides percentages of fatty acyl constituent species and employs scoring algorithms based on probability theory, which is less subjective than the tolerance and weighted match scores commonly used by available software. Lipid Annotator enables analysis of large sample cohorts and improves data-processing throughput as compared to previous lipidomics software. View Full-Text
Keywords: lipidomics; lipid annotation; tandem mass spectrometry; liquid chromatography; metabolomics; ion mobility; metabolomics; automation; software; time-of-flight lipidomics; lipid annotation; tandem mass spectrometry; liquid chromatography; metabolomics; ion mobility; metabolomics; automation; software; time-of-flight
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MDPI and ACS Style

Koelmel, J.P.; Li, X.; Stow, S.M.; Sartain, M.J.; Murali, A.; Kemperman, R.; Tsugawa, H.; Takahashi, M.; Vasiliou, V.; Bowden, J.A.; Yost, R.A.; Garrett, T.J.; Kitagawa, N. Lipid Annotator: Towards Accurate Annotation in Non-Targeted Liquid Chromatography High-Resolution Tandem Mass Spectrometry (LC-HRMS/MS) Lipidomics Using a Rapid and User-Friendly Software. Metabolites 2020, 10, 101. https://doi.org/10.3390/metabo10030101

AMA Style

Koelmel JP, Li X, Stow SM, Sartain MJ, Murali A, Kemperman R, Tsugawa H, Takahashi M, Vasiliou V, Bowden JA, Yost RA, Garrett TJ, Kitagawa N. Lipid Annotator: Towards Accurate Annotation in Non-Targeted Liquid Chromatography High-Resolution Tandem Mass Spectrometry (LC-HRMS/MS) Lipidomics Using a Rapid and User-Friendly Software. Metabolites. 2020; 10(3):101. https://doi.org/10.3390/metabo10030101

Chicago/Turabian Style

Koelmel, Jeremy P., Xiangdong Li, Sarah M. Stow, Mark J. Sartain, Adithya Murali, Robin Kemperman, Hiroshi Tsugawa, Mikiko Takahashi, Vasilis Vasiliou, John A. Bowden, Richard A. Yost, Timothy J. Garrett, and Norton Kitagawa. 2020. "Lipid Annotator: Towards Accurate Annotation in Non-Targeted Liquid Chromatography High-Resolution Tandem Mass Spectrometry (LC-HRMS/MS) Lipidomics Using a Rapid and User-Friendly Software" Metabolites 10, no. 3: 101. https://doi.org/10.3390/metabo10030101

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