Dataset Information

Metabolomic and lipidomic analysis of serum from mice exposed to an internal emitter, cesium-137, using a shotgun LC-MS(E) approach.

ABSTRACT: In this study ultra performance liquid chromatography (UPLC) coupled to time-of-flight mass spectrometry in the MS(E) mode was used for rapid and comprehensive analysis of metabolites in the serum of mice exposed to internal exposure by Cesium-137 ((137)Cs). The effects of exposure to (137)Cs were studied at several time points after injection of (137)CsCl in mice. Over 1800 spectral features were detected in the serum of mice in positive and negative electrospray ionization modes combined. Detailed statistical analysis revealed that several metabolites associated with amino acid metabolism, fatty acid metabolism, and the TCA cycle were significantly perturbed in the serum of (137)Cs-exposed mice compared with that of control mice. While metabolites associated with the TCA cycle and glycolysis increased in their serum abundances, fatty acids such as linoleic acid and palmitic acid were detected at lower levels in serum after (137)Cs exposure. Furthermore, phosphatidylcholines (PCs) were among the most perturbed ions in the serum of (137)Cs-exposed mice. This is the first study on the effects of exposure by an internal emitter in serum using a UPLC-MS(E) approach. The results have put forth a panel of metabolites, which may serve as potential serum markers to (137)Cs exposure.

SUBMITTER: Goudarzi M

PROVIDER: S-EPMC4286155 | biostudies-literature | 2015 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Metabolomic and lipidomic analysis of serum from mice exposed to an internal emitter, cesium-137, using a shotgun LC-MS(E) approach.

Goudarzi Maryam M Weber Waylon M WM Mak Tytus D TD Chung Juijung J Doyle-Eisele Melanie M Melo Dunstana R DR Brenner David J DJ Guilmette Raymond A RA Fornace Albert J AJ

Journal of proteome research 20141105 1

In this study ultra performance liquid chromatography (UPLC) coupled to time-of-flight mass spectrometry in the MS(E) mode was used for rapid and comprehensive analysis of metabolites in the serum of mice exposed to internal exposure by Cesium-137 ((137)Cs). The effects of exposure to (137)Cs were studied at several time points after injection of (137)CsCl in mice. Over 1800 spectral features were detected in the serum of mice in positive and negative electrospray ionization modes combined. Deta ...[more]

PMID: 25333951

Similar Datasets

Project description:Cesium-137 is a fission product of uranium and plutonium in nuclear reactors and is released in large quantities during nuclear explosions or detonation of an improvised device containing this isotope. This environmentally persistent radionuclide undergoes radioactive decay with the emission of beta particles as well as gamma radiation. Exposure to (137)Cs at high doses can cause acute radiation sickness and increase risk for cancer and death. The serious health risks associated with (137)Cs exposure makes it critical to understand how it affects human metabolism and whether minimally invasive and easily accessible samples such as urine and serum can be used to triage patients in case of a nuclear disaster or a radiologic event. In this study, we have focused on establishing a time-dependent metabolomic profile for urine collected from mice injected with (137)CsCl. The samples were collected from control and exposed mice on days 2, 5, 20 and 30 after injection. The samples were then analyzed by ultra-performance liquid chromatography coupled to time-of-flight mass spectrometry (UPLC/TOFMS) and processed by an array of informatics and statistical tools. A total of 1,412 features were identified in ESI(+) and ESI(-) modes from which 200 were determined to contribute significantly to the separation of metabolomic profiles of controls from those of the different treatment time points. The results of this study highlight the ease of use of the UPLC/TOFMS platform in finding urinary biomarkers for (137)Cs exposure. Pathway analysis of the statistically significant metabolites suggests perturbations in several amino acid and fatty acid metabolism pathways. The results also indicate that (137)Cs exposure causes: similar changes in the urinary excretion levels of taurine and citrate as seen with external-beam gamma radiation; causes no attenuation in the levels of hexanoylglycine and N-acetylspermidine; and has unique effects on the levels of isovalerylglycine and tiglylglycine.

Project description:BackgroundThe analysis of LC-MS metabolomic datasets appears to be a challenging task in a wide range of disciplines since it demands the highly extensive processing of a vast amount of data. Different LC-MS data analysis packages have been developed in the last few years to facilitate this analysis. However, most of these strategies involve chromatographic alignment and peak shaping and often associate each "feature" (i.e., chromatographic peak) with a unique m/z measurement. Thus, the development of an alternative data analysis strategy that is applicable to most types of MS datasets and properly addresses these issues is still a challenge in the metabolomics field.ResultsHere, we present an alternative approach called ROIMCR to: i) filter and compress massive LC-MS datasets while transforming their original structure into a data matrix of features without losing relevant information through the search of regions of interest (ROIs) in the m/z domain and ii) resolve compressed data to identify their contributing pure components without previous alignment or peak shaping by applying a Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) analysis. In this study, the basics of the ROIMCR method are presented in detail and a detailed description of its implementation is also provided. Data were analyzed using the MATLAB (The MathWorks, Inc., www.mathworks.com ) programming and computing environment. The application of the ROIMCR methodology is described in detail, with an example of LC-MS data generated in a lipidomic study and with other examples of recent applications.ConclusionsThe methodology presented here combines the benefits of data filtering and compression based on the searching of ROI features, without the loss of spectral accuracy. The method has the benefits of the application of the powerful MCR-ALS data resolution method without the necessity of performing chromatographic peak alignment or modelling. The presented method is a powerful alternative to other existing data analysis approaches that do not use the MCR-ALS method to resolve LC-MS data. The ROIMCR method also represents an improved strategy compared to the direct applications of the MCR-ALS method that use less-powerful data compression strategies such as binning and windowing. Overall, the strategy presented here confirms the usefulness of the ROIMCR chemometrics method for analyzing LC-MS untargeted metabolomics data.

Dataset Information

Metabolomic and lipidomic analysis of serum from mice exposed to an internal emitter, cesium-137, using a shotgun LC-MS(E) approach.

Publications

Metabolomic and lipidomic analysis of serum from mice exposed to an internal emitter, cesium-137, using a shotgun LC-MS(E) approach.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets