Steroid hormones are involved in the regulation of a variety of processes like embryonic development, sex differentiation, metabolism, immune responses, circadian rhythms, stress response, and reproduction in vertebrates. Teleost fishes and humans show a remarkable conservation in many developmental and physiological aspects, including the endocrine system in general and the steroid hormone related processes in particular. This review provides an overview of the current knowledge about steroid hormone biosynthesis and the steroid hormone receptors in teleost fishes and compares the findings to the human system. The impact of the duplicated genome in teleost fishes on steroid hormone biosynthesis and perception is addressed. Additionally, important processes in fish physiology regulated by steroid hormones, which are most dissimilar to humans, are described. We also give a short overview on the influence of anthropogenic endocrine disrupting compounds on steroid hormone signaling and the resulting adverse physiological effects for teleost fishes. By this approach, we show that the steroidogenesis, hormone receptors, and function of the steroid hormones are reasonably well understood when summarizing the available data of all teleost species analyzed to date. However, on the level of a single species or a certain fish-specific aspect of physiology, further research is needed.

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IntroductionGlobal metabolomics analyses using body fluids provide valuable results for the understanding and prediction of diseases. However, the mechanism of a disease is often tissue-based and it is advantageous to analyze metabolomic changes directly in the tissue. Metabolomics from tissue samples faces many challenges like tissue collection, homogenization, and metabolite extraction.ObjectivesWe aimed to establish a metabolite extraction protocol optimized for tissue metabolite quantification by the targeted metabolomics AbsoluteIDQ™ p180 Kit (Biocrates). The extraction method should be non-selective, applicable to different kinds and amounts of tissues, monophasic, reproducible, and amenable to high throughput.MethodsWe quantified metabolites in samples of eleven murine tissues after extraction with three solvents (methanol, phosphate buffer, ethanol/phosphate buffer mixture) in two tissue to solvent ratios and analyzed the extraction yield, ionization efficiency, and reproducibility.ResultsWe found methanol and ethanol/phosphate buffer to be superior to phosphate buffer in regard to extraction yield, reproducibility, and ionization efficiency for all metabolites measured. Phosphate buffer, however, outperformed both organic solvents for amino acids and biogenic amines but yielded unsatisfactory results for lipids. The observed matrix effects of tissue extracts were smaller or in a similar range compared to those of human plasma.ConclusionWe provide for each murine tissue type an optimized high-throughput metabolite extraction protocol, which yields the best results for extraction, reproducibility, and quantification of metabolites in the p180 kit. Although the performance of the extraction protocol was monitored by the p180 kit, the protocol can be applicable to other targeted metabolomics assays.Electronic supplementary materialThe online version of this article (10.1007/s11306-017-1312-x) contains supplementary material, which is available to authorized users.

IntroductionAlthough cultured cells are nowadays regularly analyzed by metabolomics technologies, some issues in study setup and data processing are still not resolved to complete satisfaction: a suitable harvesting method for adherent cells, a fast and robust method for data normalization, and the proof that metabolite levels can be normalized to cell number.ObjectivesWe intended to develop a fast method for normalization of cell culture metabolomics samples, to analyze how metabolite levels correlate with cell numbers, and to elucidate the impact of the kind of harvesting on measured metabolite profiles.MethodsWe cultured four different human cell lines and used them to develop a fluorescence-based method for DNA quantification. Further, we assessed the correlation between metabolite levels and cell numbers and focused on the impact of the harvesting method (scraping or trypsinization) on the metabolite profile.ResultsWe developed a fast, sensitive and robust fluorescence-based method for DNA quantification showing excellent linear correlation between fluorescence intensities and cell numbers for all cell lines. Furthermore, 82–97 % of the measured intracellular metabolites displayed linear correlation between metabolite concentrations and cell numbers. We observed differences in amino acids, biogenic amines, and lipid levels between trypsinized and scraped cells.ConclusionWe offer a fast, robust, and validated normalization method for cell culture metabolomics samples and demonstrate the eligibility of the normalization of metabolomics data to the cell number. We show a cell line and metabolite-specific impact of the harvesting method on metabolite concentrations.Electronic supplementary materialThe online version of this article (doi:10.1007/s11306-016-1104-8) contains supplementary material, which is available to authorized users.

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