Urine is an ideal biofluid for metabolomics studies since it is obtained noninvasively, and its composition is affected by genetic and environmental factors reflecting the physiology of multiple organs. However, urine dilution effects and instrumental variation from the analytical method play a significant confounding role when one attempts to characterize biological and physiological factors through NMR and MS measurements of small molecule concentrations. Several normalization approaches have been used for urinary metabolomics studies and normalization to osmolality or to total useful MS signal have been proposed. When dealing with urinary metabolome analysis in cattle, freeze-drying (FD) is the method commonly used for normalization purposes. Herein, normalization to specific gravity, which provides a fair estimation of urine osmolality, was compared to the time consuming FD step and to the normalization to total useful MS signal in order to assess if this approach could be used as normalization strategy to differentiate control from anabolic treated animals. The results revealed that ~80 % of the metabolites detected as constituting the acquired MS fingerprints for the freeze-dried samples and for the samples normalized to both specific gravity (SG) and total useful MS signal were in common. In addition, similar information from the multivariate statistical analysis was obtained by both normalization approaches. We demonstrate, therefore, that SG can be used as normalization approach for urinary metabolome analysis in cattle resulting in a high sample throughput procedure when compared with the FD step.
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This work was financially supported by the Italian Ministry of Health (RF-IZV-2008-1175188). Authors thank Merck Animal Health for kindly providing the implant Revalor-XS®.
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The authors have declared no conflicts of interest in the submission of this manuscript.
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Jacob, C.C., Dervilly-Pinel, G., Biancotto, G. et al. Evaluation of specific gravity as normalization strategy for cattle urinary metabolome analysis. Metabolomics 10, 627–637 (2014). https://doi.org/10.1007/s11306-013-0604-z
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