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Issue 11, 2020
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Sensitive mass spectrometric analysis of carbonyl metabolites in human urine and fecal samples using chemoselective modification

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Abstract

Metabolites with ketone or aldehyde functionalities comprise a large proportion of the human metabolome, most notably in the form of sugars. However, these reactive molecules are also generated through oxidative stress or gut microbiota metabolism and have been linked to disease development. The discovery and structural validation of this class of metabolites over the large concentration range found in human samples is crucial to identify their links to pathogenesis. Herein, we have utilized an advanced chemoselective probe methodology alongside bioinformatic analysis to identify carbonyl-metabolites in urine and fecal samples. In total, 99 metabolites were identified in urine samples and the chemical structure for 40 metabolites were unambiguously validated using a co-injection procedure. We also describe the preparation of a metabolite-conjugate library of 94 compounds utilized to efficiently validate these ketones and aldehydes. This method was used to validate 33 metabolites in a pooled fecal sample extract to demonstrate the potential for rapid and efficient metabolite detection over a wide metabolite concentration range. This analysis revealed the presence of six metabolites that have not previously been detected in either sample type. The constructed library can be utilized for straightforward, large-scale, and expeditious analysis of carbonyls in any sample type.

Graphical abstract: Sensitive mass spectrometric analysis of carbonyl metabolites in human urine and fecal samples using chemoselective modification

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Supplementary files

Article information


Submitted
19 Jan 2020
Accepted
13 Mar 2020
First published
12 May 2020

This article is Open Access

Analyst, 2020,145, 3822-3831
Article type
Paper

Sensitive mass spectrometric analysis of carbonyl metabolites in human urine and fecal samples using chemoselective modification

W. Lin, L. P. Conway, A. Block, G. Sommi, M. Vujasinovic, J.-Matthias Löhr and D. Globisch, Analyst, 2020, 145, 3822
DOI: 10.1039/D0AN00150C

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