Combined untargeted and targeted fingerprinting by comprehensive two-dimensional gas chromatography: revealing fructose-induced changes in mice urinary metabolic signatures
This study exploits the information potential of comprehensive two-dimensional gas chromatography configured with a parallel dual secondary column-dual detection by mass spectrometry and flame ionization (GC×2GC-MS/FID) to study changes in urinary metabolic signatures of mice subjected to high-fructose diets. Samples are taken from mice fed with normal or fructose-enriched diets provided either in aqueous solution or in solid form and analyzed at three stages of the dietary intervention (1, 6, and 12 weeks). Automated Untargeted and Targeted fingerprinting for 2D data elaboration is adopted for the most inclusive data mining of GC×GC patterns. The UT fingerprinting strategy performs a fully automated peak-region features fingerprinting and combines results from pre-targeted compounds and unknowns across the sample-set. The most informative metabolites, with statistically relevant differences between sample groups, are obtained by unsupervised multivariate analysis (MVA) and cross-validated by multi-factor analysis (MFA) with external standard quantitation by GC-MS. Results indicate coherent clustering of mice urine signatures according to dietary manipulation. Notably, the metabolite fingerprints of mice fed with liquid fructose exhibited greater derangement in fructose, glucose, citric, pyruvic, malic, malonic, gluconic, cis-aconitic, succinic and 2-keto glutaric acids, glycine acyl derivatives (N-carboxy glycine, N-butyrylglycine, N-isovaleroylglycine, N-phenylacetylglycine), and hippuric acid. Untargeted fingerprinting indicates some analytes which were not a priori pre-targeted which provide additional insights: N-acetyl glucosamine, N-acetyl glutamine, malonyl glycine, methyl malonyl glycine, and glutaric acid. Visual features fingerprinting is used to track individual variations during experiments, thereby extending the panorama of possible data elaboration tools.
KeywordsComprehensive two-dimensional gas chromatography-mass spectrometry Parallel dual secondary column-dual detection Fructose-induced metabolic derangements Urine metabolic profiling Untargeted and targeted fingerprinting
Authors are indebted with Dr. Martina Carbone for the technical help.
This work was supported and funded by the University of Turin (Ricerca Locale 2016 and 2017), Regione Toscana (Bando Nutraceutica 2014), Project TAGIDISFRU, ERA-HDHL-ERANET Biomarkers for Nutrition and Health Implementing the JPG HDHL objectives”—Project “SALIVAGES.”
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interests.
The research was conducted in accordance with the European Directive 2010/63/EU on the protection of animals used for scientific purposes as well as the International Guiding Principles for Biomedical Research Involving Animals, issued by the Council for the International Organizations of Medical Sciences. Both the Turin University Ethics Committee (Prot. 6437 22/02/2016) and the Italian Ministry of Health (Prot. 42/2017-PR) approved the experimental protocol. All efforts were made to minimize animal suffering and to reduce the number of animals used.
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