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Cited by 209Metabolomics and Mass Spectrometry StudiesMass Spectrometry Techniques and ApplicationsAdvanced Proteomics Techniques and Applications

Expanding Lipidome Coverage Using LC-MS/MS Data-Dependent Acquisition with Automated Exclusion List Generation

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Koelmel, Jeremy P., Kroeger, Nicholas M., Gill, Emily L., Ulmer, Candice Z., Bowden, John A., Patterson, Rainey E., Yost, Richard A., Garrett, Timothy J.·2017·Journal of the American Society for Mass Spectrometry
DOI 10.1007/s13361-017-1608-0PMC PMC5408749
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Abstract

Untargeted omics analyses aim to comprehensively characterize biomolecules within a biological system. Changes in the presence or quantity of these biomolecules can indicate important biological perturbations, such as those caused by disease. With current technological advancements, the entire genome can now be sequenced; however, in the burgeoning fields of lipidomics, only a subset of lipids can be identified. The recent emergence of high resolution tandem mass spectrometry (HR-MS/MS), in combination with ultra-high performance liquid chromatography, has resulted in an increased coverage of the lipidome. Nevertheless, identifications from MS/MS are generally limited by the number of precursors that can be selected for fragmentation during chromatographic elution. Therefore, we developed the software IE-Omics to automate iterative exclusion (IE), where selected precursors using data-dependent topN analyses are excluded in sequential injections. In each sequential injection, unique precursors are fragmented until HR-MS/MS spectra of all ions above a user-defined intensity threshold are acquired. IE-Omics was applied to lipidomic analyses in Red Cross plasma and substantia nigra tissue. Coverage of the lipidome was drastically improved using IE. When applying IE-Omics to Red Cross plasma and substantia nigra lipid extracts in positive ion mode, 69% and 40% more molecular identifications were obtained, respectively. In addition, applying IE-Omics to a lipidomics workflow increased the coverage of trace species, including odd-chained and short-chained diacylglycerides and oxidized lipid species. By increasing the coverage of the lipidome, applying IE to a lipidomics workflow increases the probability of finding biomarkers and provides additional information for determining etiology of disease. Graphical Abstract ᅟ.

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  • To enhance the capacity to identify chemical features, a standard mix of authentic standards for expected compounds was injected and pooled unlabeled samples were analyzed in triplicate by data-dependent analysis.

    “To enhance our capacity to identify chemical features (i) a standard mix consisting of authentic standards for expected compounds was injected, and (ii) pooled samples of only unlabeled samples was analyzed in triplicate via data-dependent analysis mode (DDA) with IE omics scripts and R-Studio 58”

    From APOE4-drives brain bioenergetic shifts independent of Alzheimer’s disease pathology (2026) · cites this paper as [58]

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Authors
Koelmel, J. P., Kroeger, N. M., Gill, E. L., Ulmer, C. Z., Bowden, J. A., Patterson, R. E., Yost, R. A., & Garrett, T. J.
Affiliations
  • University of Florida (US)
  • National Institute of Standards and Technology (US)
ORCID
Venue
Journal of the American Society for Mass Spectrometry
Publisher
American Chemical Society (ACS)
Published
2017-03-06
Volume
28
Issue
5
Pages
908-917
ISSN
1044-0305 (ISSN-L)
DOI
10.1007/s13361-017-1608-0
PMC
PMC5408749
OpenAlex
W2593533643
Cited by
209
References
0
Citations by year
2026: 23 · 2025: 14 · 2024: 25 · 2023: 25 · 2022: 28 · 2021: 37 · 2020: 19 · 2019: 18 · 2018: 12 · 2017: 8
FWCI
6.20
Type
journal article
Language
en
Open access
Licence
www.springer.com/tdm (unspecified)
Locations
  • Journal of the American Society for Mass Spectrometry (publishedVersion)
  • PubMed (publishedVersion)
  • Europe PMC (PubMed Central) (acceptedVersion)
  • PubMed Central (acceptedVersion)
Funders
  • National Institutes of Health (UL1TR001427)
  • National Institute of Diabetes and Digestive and Kidney Diseases (U24DK097209)
  • National Center for Advancing Translational Sciences
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Metabolomics and Mass Spectrometry Studies
  • Physical Sciences › Chemistry › Spectroscopy › Mass Spectrometry Techniques and Applications
  • Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
Keywords
lipidomics, data-dependent acquisition, high-resolution tandem mass spectrometry, substantia nigra, diacylglycerol, oxidized lipids, biomarker discovery

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