(141b) Comparative Analysis of the Cerebellar Metabolic Physiology Between Sexes in a Mouse Model of Adult Onset Hypothyroidism Using GC-MS Metabolomics

In the systems biology era, the high-throughput “omic” technologies have enabled the holistic analysis of the various molecular levels of cellular function through the simultaneous measurement of hundreds to thousands of relevant molecular quantities. Metabolomics refers to the quantification and analysis of the (relative) concentration profile of the free small metabolites, which provides a fingerprint of the metabolic state of a biological system. Among the advantages of the metabolomic analysis is that it can be easily used to monitor transient metabolic conditions without requiring extensive knowledge of the structure and regulation of the investigated metabolic networks. This characteristic is especially advantageous for the analysis of brain metabolism, considering the anatomical, morphological and phenotypic complexity of this organ and our current shortages in understanding its metabolic mechanisms. For the effect of adult onset hypothyroidism (AOH) on brain metabolism in particular, the current knowledge remains fragmented, concerning different experimental setups and recovered from various brain regions. Therefore, a holistic view of the metabolic response of particular brain regions to AOH is expected to significantly enhance the current knowledge about the disease. In this context, we used metabolomics to study the metabolic physiology of mouse cerebellum in a prolonged AOH model. This was the first metabolomic analysis of brain tissue in a prolonged AOH mouse model [1]. We extended our analysis to both sexes to investigate potential differences of the effect of prolonged AOH on the cerebellar metabolic physiology between male and female.

The prolonged AOH was induced by a 64-day treatment with 1% potassium perchlorate in the drinking water of Balb/cJ mice, as described in our published study [1]. The raw metabolic profiles were normalized and appropriately filtered based on the methodology of Kanani and Klapa [2]. The normalized metabolic profiles were analyzed using the open-source TM4/MeV software (www.tm4.org/mev) for the multivariate statistical analysis of “omic” data. The acquired results were interpreted in the context of an appropriately reconstructed metabolic network for the mouse cerebellum based on the metabolic databases, KEGG (www.kegg.com) and Expasy (enzyme.expasy.org), and a plethora of information mined from the literature. The analysis of the acquired metabolic profiles provided strong evidence that the mammalian cerebellum is metabolically responsive to prolonged AOH [1]. Specifically, it indicated a general decline in the metabolic activity of cerebellum in the hypothyroid compared to the euthyroid animals, with the observed effect for the particular AOH mouse model being stronger in the male compared to the female. Our results enhanced the currently available “omic” dataset for the brain physiology under prolonged AOH and indicated directions for further research to improve our understanding of AOH effect on brain metabolism. Integration with other omic, in particular proteomic, data would be of great value.

References

1. Constantinou C., Chrysanthopoulos P., Margarity M. and Klapa MI. (2011) GC-MS metabolic analysis reveals significant alternations in cerebellar metabolic physiology in a mouse model of adult onset hypothyroidism. J. Proteome Res.10:869-879 (Epub 2010 Dec 8)
2. Kanani H., Klapa MI. (2007) Data Correction Strategy for metabolomic analysis using Gas Chromatography-Mass Spectrometry. Metab. Eng. 9: 39-51.