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Metabolomic screening using ESI-FT MS identifies potential radiation-responsive molecules in mouse urine.

ABSTRACT: The demand for establishment of high-throughput biodosimetric methods is increasing. Our aim in this study was to identify low-molecular-weight urinary radiation-responsive molecules using electrospray ionization Fourier transform mass spectrometry (ESI-FT MS), and our final goal was to develop a sensitive biodosimetry technique that can be applied in the early triage of a radiation emergency medical system. We identified nine metabolites by statistical comparison of mouse urine before and 8 h after irradiation. Time-course analysis showed that, of these metabolites, thymidine and either thymine or imidazoleacetic acid were significantly increased dose-dependently 8 h after radiation exposure; these molecules have already been reported as potential radiation biomarkers. Phenyl glucuronide was significantly decreased 8 h after radiation exposure, irrespective of the dose. Histamine and 1-methylhistamine were newly identified by MS/MS and showed significant, dose-dependent increases 72 h after irradiation. Quantification of 1-methylhistamine by enzyme-linked immunosorbent assay (ELISA) analysis also showed a significant increase 72 h after 4 Gy irradiation. These results suggest that urinary metabolomics screening using ESI-FT MS can be a powerful tool for identifying promising radiation-responsive molecules, and that urinary 1-methylhistamine is a potential radiation-responsive molecule for acute, high-dose exposure.

SUBMITTER: Iizuka D

PROVIDER: S-EPMC5619916 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:IntroductionThis study sought to compare between metabolomic changes of human urine and plasma to investigate which one can be used as best tool to identify metabolomic profiling and novel biomarkers associated to the potential effects of ultraviolet (UV) radiation.MethodA pilot study of metabolomic patterns of human plasma and urine samples from four adult healthy individuals at before (S1) and after (S2) exposure (UV) and non-exposure (UC) were carried out by using liquid chromatography-mass spectrometry (LC-MS).ResultsThe best results which were obtained by normalizing the metabolites to their mean output underwent to principal components analysis (PCA) and Orthogonal Partial least squares-discriminant analysis (OPLS-DA) to separate pre-from post-of exposure and non-exposure of UV. This separation by data modeling was clear in urine samples unlike plasma samples. In addition to overview of the scores plots, the variance predicted-Q2 (Cum), variance explained-R2X (Cum) and p-value of the cross-validated ANOVA score of PCA and OPLS-DA models indicated to this clear separation. Q2 (Cum) and R2X (Cum) values of PCA model for urine samples were 0.908 and 0.982, respectively, and OPLS-DA model values were 1.0 and 0.914, respectively. While these values in plasma samples were Q2 = 0.429 and R2X = 0.660 for PCA model and Q2 = 0.983 and R2X = 0.944 for OPLS-DA model. LC-MS metabolomic analysis showed the changes in numerous metabolic pathways including: amino acid, lipids, peptides, xenobiotics biodegradation, carbohydrates, nucleotides, Co-factors and vitamins which may contribute to the evaluation of the effects associated with UV sunlight exposure.ConclusionsThe results of pilot study indicate that pre and post-exposure UV metabolomics screening of urine samples may be the best tool than plasma samples and a potential approach to predict the metabolomic changes due to UV exposure. Additional future work may shed light on the application of available metabolomic approaches to explore potential predictive markers to determine the impacts of UV sunlight.

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Metabolomic screening using ESI-FT MS identifies potential radiation-responsive molecules in mouse urine.

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