Статья

Heterogeneous multimeric metabolite ion species observed in LC-MS based metabolomics data sets

Yasin El AbieadDepartment of Analytical Chemistry, University of Vienna, 1090, Vienna, Austria. Electronic address: [email protected]Christoph BueschlDepartment of Analytical Chemistry, University of Vienna, 1090, Vienna, Austria; Institute of Bioanalytics and Agro-Metabolomics, Department of Agrobiotechnology IFA-Tulln, University of Natural Resources and Life Sciences, Vienna, 3430, Tulln, AustriaLisa PanzenboeckDepartment of Analytical Chemistry, University of Vienna, 1090, Vienna, AustriaMingxun WangDepartment of Computer Science and Engineering, University of California Riverside, 900 University Ave, Riverside, CA, 92521, USAMaria DopplerInstitute of Bioanalytics and Agro-Metabolomics, Department of Agrobiotechnology IFA-Tulln, University of Natural Resources and Life Sciences, Vienna, 3430, Tulln, Austria; Core Facility Bioactive Molecules: Screening and Analysis, University of Natural Resources and Life Sciences, Vienna, 3430, Tulln, AustriaBernhard SeidlInstitute of Bioanalytics and Agro-Metabolomics, Department of Agrobiotechnology IFA-Tulln, University of Natural Resources and Life Sciences, Vienna, 3430, Tulln, AustriaJürgen ZanghelliniDepartment of Analytical Chemistry, University of Vienna, 1090, Vienna, AustriaPieter C. DorresteinCollaborative Mass Spectrometry Innovation Center, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA; Department of Pharmacology, School of Medicine, University of California San Diego, La Jolla, CA, USA; Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA, USA; Center for Microbiome Innovation, University of California San Diego, La Jolla, CA, USAGunda KoellenspergerDepartment of Analytical Chemistry, University of Vienna, 1090, Vienna, Austria. Electronic address: [email protected]

2022en

ABI

Аннотация

Covalent or non-covalent heterogeneous multimerization of molecules associated with extracts from biological samples analyzed via LC-MS are quite difficult to recognize/annotate and therefore the prevalence of multimerization remains largely unknown. In this study, we utilized 13C labeled and unlabeled Pichia pastoris extracts to recognize heterogeneous multimers. More specifically, between 0.8% and 1.5% of the biologically-derived features detected in our experiments were confirmed to be heteromers, about half of which we could successfully annotate with monomeric partners. Interestingly, we found specific chemical classes such as nucleotides to disproportionately contribute to heteroadducts. Furthermore, we compiled these compounds into the first MS/MS library that included data from heteromultimers to provide a starting point for other labs to improve the annotation of such ions in other metabolomics data sets. Then, the detected heteromers were also searched in publicly accessible LC-MS datasets available in Metabolights, Metabolomics WB and GNPS/MassIVE to demonstrate that these newly annotated ions are also relevant to other public datasets. Furthermore, in additional datasets (Triticum aestivum, Fusarium graminearum, and Trichoderma reesei) our developed workflow also detected 0.5%-4.9% of metabolite features to originate from heterodimers, demonstrating heteroadducts to be present in metabolomics studies at a low percentage.

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Идентификаторы

DOI: 10.1016/j.aca.2022.340352

Цитирования и источники

Цитирований: 2Использованных источников: 0

Показатели — AkademScholar