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High-throughput UHPLC-MS to screen metabolites in feces for gut metabolic health

View ORCID ProfileAndressa de Zawadzki, View ORCID ProfileMaja Thiele, View ORCID ProfileTommi Suvitaival, Asger Wretlind, Min Kim, View ORCID ProfileMina Ali, Annette F. Bjerre, Karin Stahr, Ismo Matilla, View ORCID ProfileTorben Hansen, Aleksander Krag, View ORCID ProfileCristina Legido-Quigley
doi: https://doi.org/10.1101/2021.12.22.473790
Andressa de Zawadzki
1Steno Diabetes Center Copenhagen, Herlev, Denmark
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Maja Thiele
2Department of Gastroenterology and Hepatology, Odense University Hospital, Odense, Denmark
3Department of Clinical Medicine, University of Southern Denmark, Odense, Denmark
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Tommi Suvitaival
1Steno Diabetes Center Copenhagen, Herlev, Denmark
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Asger Wretlind
1Steno Diabetes Center Copenhagen, Herlev, Denmark
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Min Kim
1Steno Diabetes Center Copenhagen, Herlev, Denmark
4Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, Denmark
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Mina Ali
1Steno Diabetes Center Copenhagen, Herlev, Denmark
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Annette F. Bjerre
1Steno Diabetes Center Copenhagen, Herlev, Denmark
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Karin Stahr
1Steno Diabetes Center Copenhagen, Herlev, Denmark
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Ismo Matilla
1Steno Diabetes Center Copenhagen, Herlev, Denmark
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Torben Hansen
5Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
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Aleksander Krag
2Department of Gastroenterology and Hepatology, Odense University Hospital, Odense, Denmark
3Department of Clinical Medicine, University of Southern Denmark, Odense, Denmark
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Cristina Legido-Quigley
1Steno Diabetes Center Copenhagen, Herlev, Denmark
6Institute of Pharmaceutical Science, King’s College London, London, UK
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  • For correspondence: cristina.legido.quigley@regionh.dk
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Abstract

Background Feces are the product of our diets and have been linked to diseases of the gut, including Chron’s disease and metabolic diseases such as diabetes. For screening metabolites in heterogeneous samples such as feces, it is necessary to use fast and reproducible analytical methods that maximize metabolite detection.

Methods As sample preparation is crucial to obtain high quality data in MS-based clinical metabolomics, we developed a novel, efficient and robust method for preparing fecal samples for analysis with a focus in reducing aliquoting and detecting both polar and non-polar metabolites. Fecal samples (n= 475) from patients with alcohol-related liver disease and healthy controls were prepared according to the proposed method and analyzed in an UHPLC-QQQ targeted platform in order to obtain a quantitative profile of compounds that impact liver-gut axis metabolism.

Results MS analyses of the prepared fecal samples have shown reproducibility and coverage of n=28 metabolites, mostly comprising bile acids and amino acids. We report metabolite-wise relative standard deviation (RSD) in quality control samples, inter-day repeatability, LOD, LOQ and range of linearity. The average concen-trations for 135 healthy participants are reported here for clinical applications.

Conclusions our high-throughput method provides an efficient tool for investigating gut-liver axis metabolism in liver-related diseases using a noninvasive collected sample.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted December 23, 2021.
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High-throughput UHPLC-MS to screen metabolites in feces for gut metabolic health
Andressa de Zawadzki, Maja Thiele, Tommi Suvitaival, Asger Wretlind, Min Kim, Mina Ali, Annette F. Bjerre, Karin Stahr, Ismo Matilla, Torben Hansen, Aleksander Krag, Cristina Legido-Quigley
bioRxiv 2021.12.22.473790; doi: https://doi.org/10.1101/2021.12.22.473790
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High-throughput UHPLC-MS to screen metabolites in feces for gut metabolic health
Andressa de Zawadzki, Maja Thiele, Tommi Suvitaival, Asger Wretlind, Min Kim, Mina Ali, Annette F. Bjerre, Karin Stahr, Ismo Matilla, Torben Hansen, Aleksander Krag, Cristina Legido-Quigley
bioRxiv 2021.12.22.473790; doi: https://doi.org/10.1101/2021.12.22.473790

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