Yasin El Abiead

The repertoire of modifications to bile acids and related steroidal lipids by host and microbial metabolism remains incompletely characterized. To address this knowledge gap, we created a reusable resource of tandem mass spectrometry (MS/MS) spectra by filtering 1.2 billion publicly available MS/MS spectra for bile-acid-selective ion patterns. Thousands of modifications are distributed throughout animal and human bodies as well as microbial cultures. We employed this MS/MS library to identify polyamine bile amidates, prevalent in carnivores. They are present in humans, and their levels alter with a diet change from a Mediterranean to a typical American diet. This work highlights the existence of many more bile acid modifications than previously recognized and the value of leveraging public large-scale untargeted metabolomics data to discover metabolites. The availability of a modification-centric bile acid MS/MS library will inform future studies investigating bile acid roles in health and disease.

RETURN TO ISSUEPREVReviewNEXTRecurrent Topics in Mass Spectrometry-Based Metabolomics and Lipidomics—Standardization, Coverage, and ThroughputEvelyn RamplerEvelyn RamplerDepartment of Analytical Chemistry, Faculty of Chemistry, University of Vienna, Währinger Str. 38, 1090 Vienna, AustriaVienna Metabolomics Center (VIME), University of Vienna, Althanstraße 14, 1090 Vienna, AustriaUniversity of Vienna, Althanstraße 14, 1090 Vienna, AustriaMore by Evelyn RamplerView Biographyhttp://orcid.org/0000-0002-9429-7663, Yasin El AbieadYasin El AbieadDepartment of Analytical Chemistry, Faculty of Chemistry, University of Vienna, Währinger Str. 38, 1090 Vienna, AustriaMore by Yasin El AbieadView Biography, Harald SchoenyHarald SchoenyDepartment of Analytical Chemistry, Faculty of Chemistry, University of Vienna, Währinger Str. 38, 1090 Vienna, AustriaMore by Harald SchoenyView Biographyhttp://orcid.org/0000-0001-8696-481X, Mate RuszMate RuszDepartment of Analytical Chemistry, Faculty of Chemistry, University of Vienna, Währinger Str. 38, 1090 Vienna, AustriaInstitute of Inorganic Chemistry, University of Vienna, Währinger Straße 42, 1090 Vienna, AustriaMore by Mate RuszView Biography, Felina HildebrandFelina HildebrandDepartment of Analytical Chemistry, Faculty of Chemistry, University of Vienna, Währinger Str. 38, 1090 Vienna, AustriaMore by Felina HildebrandView Biography, Veronika FitzVeronika FitzDepartment of Analytical Chemistry, Faculty of Chemistry, University of Vienna, Währinger Str. 38, 1090 Vienna, AustriaMore by Veronika FitzView Biography, and Gunda Koellensperger*Gunda KoellenspergerDepartment of Analytical Chemistry, Faculty of Chemistry, University of Vienna, Währinger Str. 38, 1090 Vienna, AustriaVienna Metabolomics Center (VIME), University of Vienna, Althanstraße 14, 1090 Vienna, AustriaUniversity of Vienna, Althanstraße 14, 1090 Vienna, Austria*Email: [email protected]. Phone: +43-1-4277-52303.More by Gunda KoellenspergerView Biographyhttp://orcid.org/0000-0002-1460-4919Cite this: Anal. Chem. 2021, 93, 1, 519–545Publication Date (Web):November 28, 2020Publication History Published online28 November 2020Published inissue 12 January 2021https://doi.org/10.1021/acs.analchem.0c04698Copyright © 2020 American Chemical SocietyRIGHTS & PERMISSIONSACS AuthorChoicewith CC-BYlicenseArticle Views7341Altmetric-Citations10LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InReddit PDF (5 MB) Get e-AlertsSUBJECTS:Lipids,Metabolomics,Metabolism,Fungi,Materials Get e-Alerts

microbeMASST, a taxonomically informed mass spectrometry (MS) search tool, tackles limited microbial metabolite annotation in untargeted metabolomics experiments. Leveraging a curated database of >60,000 microbial monocultures, users can search known and unknown MS/MS spectra and link them to their respective microbial producers via MS/MS fragmentation patterns. Identification of microbe-derived metabolites and relative producers without a priori knowledge will vastly enhance the understanding of microorganisms' role in ecology and human health.

Lipid identification and quantification are essential objectives in comprehensive lipidomics studies challenged by the high number of lipids, their chemical diversity, and their dynamic range. In this work, we developed a tailored method for profiling and quantification combining (1) isotope dilution, (2) enhanced isomer separation by C30 fused-core reversed-phase material, and (3) parallel Orbitrap and ion trap detection by the Orbitrap Fusion Lumos Tribid mass spectrometer. The combination of parallelizable ion analysis without time loss together with different fragmentation techniques (HCD/CID) and an inclusion list led to higher quality in lipid identifications exemplified in human plasma and yeast samples. Moreover, we used lipidome isotope-labeling of yeast (LILY)—a fast and efficient in vivo labeling strategy in Pichia pastoris—to produce (nonradioactive) isotopically labeled eukaryotic lipid standards in yeast. We integrated the 13C lipids in the LC-MS workflow to enable relative and absolute compound-specific quantification in yeast and human plasma samples by isotope dilution. Label-free and compound-specific quantification was validated by comparison against a recent international interlaboratory study on human plasma SRM 1950. In this way, we were able to prove that LILY enabled quantification leads to accurate results, even in complex matrices. Excellent analytical figures of merit with enhanced trueness, precision and linearity over 4–5 orders of magnitude were observed applying compound-specific quantification with 13C-labeled lipids. We strongly believe that lipidomics studies will benefit from incorporating isotope dilution and LC-MSn strategies.