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Selectivity evaluation using the co-feature ratio in LC/MS metabolomics: comparison of HILIC stationary phases’ performance for the analysis of plasma, urine and cell extracts.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Medicinal Chemistry, Analytical Pharmaceutical Chemistry.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Medicinal Chemistry, Analytical Pharmaceutical Chemistry.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Medicinal Chemistry, Analytical Pharmaceutical Chemistry.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Medicinal Chemistry, Analytical Pharmaceutical Chemistry.
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(English)Manuscript (preprint) (Other academic)
National Category
Medicinal Chemistry
Identifiers
URN: urn:nbn:se:uu:diva-318089OAI: oai:DiVA.org:uu-318089DiVA, id: diva2:1084249
Available from: 2017-03-24 Created: 2017-03-24 Last updated: 2018-01-13
In thesis
1. Selectivity in NMR and LC-MS Metabolomics: The Importance of Sample Preparation and Separation, and how to Measure Selectivity in LC-MS Metabolomics.
Open this publication in new window or tab >>Selectivity in NMR and LC-MS Metabolomics: The Importance of Sample Preparation and Separation, and how to Measure Selectivity in LC-MS Metabolomics.
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Until now, most metabolomics protocols have been optimized towards high sample throughput and high metabolite coverage, parameters considered to be highly important for identifying influenced biological pathways and to generate as many potential biomarkers as possible. From an analytical point of view this can be troubling, as neither sample throughput nor the number of signals relates to actual quality of the detected signals/metabolites. However, a method’s selectivity for a specific signal/metabolite is often closely associated to the quality of that signal, yet this is a parameter often neglected in metabolomics.

This thesis demonstrates the importance of considering selectivity when developing NMR and LC-MS metabolomics methods, and introduces a novel approach for measuring chromatographic and signal selectivity in LC-MS metabolomics.

Selectivity for various sample preparations and HILIC stationary phases was compared. The choice of sample preparation affected the selectivity in both NMR and LC-MS. For the stationary phases, selectivity differences related primarily to retention differences of unwanted matrix components, e.g. inorganic salts or glycerophospholipids. Metabolites co-eluting with these matrix components often showed an incorrect quantitative signal, due to an influenced ionization efficiency and/or adduct formation.

A novel approach for measuring selectivity in LC-MS metabolomics has been introduced. By dividing the intensity of each feature (a unique mass at a specific retention time) with the total intensity of the co-eluting features, a ratio representing the combined chromatographic (amount of co-elution) and signal (e.g. in-source fragmentation) selectivity is acquired. The calculated co-feature ratios have successfully been used to compare the selectivity of sample preparations and HILIC stationary phases.

In conclusion, standard approaches in metabolomics research might be unwise, as each metabolomics investigation is often unique.  The methods used should be adapted for the research question at hand, primarily based on any key metabolites, as well as the type of sample to be analyzed. Increased selectivity, through proper choice of analytical methods, may reduce the risks of matrix-associated effects and thereby reduce the false positive and false negative discovery rate of any metabolomics investigation.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2017. p. 40
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Pharmacy, ISSN 1651-6192 ; 232
Keywords
Metabolomics, NMR, LC-MS, HILIC, UHPLC, Q-ToF, selectivity, co-feature ratio, method evaluation, data evaluation
National Category
Pharmaceutical Sciences Analytical Chemistry
Research subject
Analytical Pharmaceutical Chemistry
Identifiers
urn:nbn:se:uu:diva-318296 (URN)978-91-554-9879-5 (ISBN)
Public defence
2017-05-19, B41, BMC, Husargatan 3, Uppsala, 10:15 (Swedish)
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Supervisors
Available from: 2017-04-26 Created: 2017-03-30 Last updated: 2018-01-13

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Elmsjö, AlbertHaglöf, JakobNestor, MarikaArvidsson, TorbjörnPettersson, Curt
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Analytical Pharmaceutical ChemistryDepartment of Immunology, Genetics and Pathology
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