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Human plasma and serum are widely used matrices in clinical and biological studies. However, different collecting procedures and the coagulation cascade influence concentrations of both proteins and metabolites in these matrices. The effects on metabolite concentration profiles have not been fully characterized. We analyzed the concentrations of 163 metabolites in plasma and serum samples collected simultaneously from 377 fasting individuals. To ensure data quality, 41 metabolites with low measurement stability were excluded from further analysis. In addition, plasma and corresponding serum samples from 83 individuals were re-measured in the same plates and mean correlation coefficients (r) of all metabolites between the duplicates were 0.83 and 0.80 in plasma and serum, respectively, indicating significantly better stability of plasma compared to serum (p = 0.01). Metabolite profiles from plasma and serum were clearly distinct with 104 metabolites showing significantly higher concentrations in serum. In particular, 9 metabolites showed relative concentration differences larger than 20%. Despite differences in absolute concentration between the two matrices, for most metabolites the overall correlation was high (mean r = 0.81±0.10), which reflects a proportional change in concentration. Furthermore, when two groups of individuals with different phenotypes were compared with each other using both matrices, more metabolites with significantly different concentrations could be identified in serum than in plasma. For example, when 51 type 2 diabetes (T2D) patients were compared with 326 non-T2D individuals, 15 more significantly different metabolites were found in serum, in addition to the 25 common to both matrices. Our study shows that reproducibility was good in both plasma and serum, and better in plasma. Furthermore, as long as the same blood preparation procedure is used, either matrix should generate similar results in clinical and biological studies. The higher metabolite concentrations in serum, however, make it possible to provide more sensitive results in biomarker detection.

Natural products comprise a rich reservoir for innovative drug leads and are a constant source of bioactive compounds. To find pharmacological targets for new or already known natural products using modern computer-aided methods is a current endeavor in drug discovery. Nature’s treasures, however, could be used more effectively. Yet, reliable pipelines for the large-scale target prediction of natural products are still rare. We developed an in silico workflow consisting of four independent, stand-alone target prediction tools and evaluated its performance on dihydrochalcones (DHCs)—a well-known class of natural products. Thereby, we revealed four previously unreported protein targets for DHCs, namely 5-lipoxygenase, cyclooxygenase-1, 17β-hydroxysteroid dehydrogenase 3, and aldo-keto reductase 1C3. Moreover, we provide a thorough strategy on how to perform computational target predictions and guidance on using the respective tools.

Stress, the physiological reaction to a stressor, is initiated in teleost fish by hormone cascades along the hypothalamus-pituitary-interrenal (HPI) axis. Cortisol is the major stress hormone and contributes to the appropriate stress response by regulating gene expression after binding to the glucocorticoid receptor. Cortisol is inactivated when 11β-hydroxysteroid dehydrogenase (HSD) type 2 catalyzes its oxidation to cortisone. In zebrafish, Danio rerio, cortisone can be further reduced to 20β-hydroxycortisone. This reaction is catalyzed by 20β-HSD type 2, recently discovered by us. Here, we substantiate the hypothesis that 20β-HSD type 2 is involved in cortisol catabolism and stress response. We found that hsd11b2 and hsd20b2 transcripts were up-regulated upon cortisol treatment. Moreover, a cortisol-independent, short-term physical stressor led to the up-regulation of hsd11b2 and hsd20b2 along with several HPI axis genes. The morpholino-induced knock down of hsd20b2 in zebrafish embryos revealed no developmental phenotype under normal culture conditions, but prominent effects were observed after a cortisol challenge. Reporter gene experiments demonstrated that 20β-hydroxycortisone was not a physiological ligand for the zebrafish glucocorticoid or mineralocorticoid receptor but was excreted into the fish holding water. Our experiments show that 20β-HSD type 2, together with 11β-HSD type 2, represents a short pathway in zebrafish to rapidly inactivate and excrete cortisol. Therefore, 20β-HSD type 2 is an important enzyme in stress response.

The expanded use of second-generation antiandrogens revolutionized the treatment landscape of progressed prostate cancer. However, resistances to these novel drugs are already the next obstacle to be solved. Various previous studies depicted an involvement of the enzyme AKR1C3 in the process of castration resistance as well as in the resistance to 2nd generation antiandrogens like enzalutamide. In our study, we examined the potential of natural AKR1C3 inhibitors in various prostate cancer cell lines and a three-dimensional co-culture spheroid model consisting of cancer cells and cancer-associated fibroblasts (CAFs) mimicking enzalutamide resistant prostate cancer. One of our compounds, named MF-15, expressed strong antineoplastic effects especially in cell culture models with significant enzalutamide resistance. Furthermore, MF-15 exhibited a strong effect on androgen receptor (AR) signaling, including significant inhibition of AR activity, downregulation of androgen-regulated genes, lower prostate specific antigen (PSA) production, and decreased AR and AKR1C3 expression, indicating a bi-functional effect. Even more important, we demonstrated a persisting inhibition of AR activity in the presence of AR-V7 and further showed that MF-15 non-competitively binds within the DNA binding domain of the AR. The data suggest MF-15 as useful drug to overcome enzalutamide resistance.

Differentiation of preadipocytes into mature adipocytes is a highly complex cellular process. At lipidome level, the adipogenesis remains poorly characterized. To investigate the lipidomic changes during human adipogenesis, we used the LipidyzerTM assay, which quantified 743 lipid species from 11 classes. The undifferentiated human SGBS cell strain showed a heterogeneous lipid class composition with the most abundant classes, phosphatidylethanolamines (PE), phosphatidylcholines (PC), and sphingomyelins (SM). The differentiation process was accompanied by increased ceramide concentrations. After completion of differentiation around day 4, massive lipid remodeling occurred during maturation, characterized by substantial synthesis of diacylglycerols (DAG), lysophosphatidylethanolamines (LPE), PC, PE, SM, and triacylglycerols (TAG). Lipid species composition became more homogeneous during differentiation to highly concentrated saturated and monounsaturated long-chain fatty acids (LCFA), with the four most abundant being C16:0, C16:1, C18:0, and C18:1. Simultaneously, the amount of polyunsaturated and very long-chain fatty acids (VLCFA) markedly decreased. High negative correlation coefficients between PE and PC species containing VLCFA and TAG species as well as between ceramides and SM imply that PE, PC, and ceramides might have served as additional sources for TAG and SM synthesis, respectively. These results highlight the enormous remodeling at the lipid level over several lipid classes during adipogenesis.

Naturally occurring substances are valuable resources for drug development. In this respect, chalcones are known to be antiproliferative agents against prostate cancer cell lines through various mechanisms or targets. Based on the literature and preliminary results, we aimed to study and optimise the efficiency of a series of chalcones to inhibit androgen-converting AKR1C3, known to promote prostate cancer. A total of 12 chalcones with different substitution patterns were synthesised. Structure–activity relationships associated with these modifications on AKR1C3 inhibition were analysed by performing enzymatic assays and docking simulations. In addition, the selectivity and cytotoxicity of the compounds were assessed. In enzymatic assays, C-6′ hydroxylated derivatives were more active than C-6′ methoxylated derivatives. In contrast, C-4 methylation increased activity over C-4 hydroxylation. Docking results supported these findings with the most active compounds fitting nicely in the binding site and exhibiting strong interactions with key amino acid residues. The most effective inhibitors were not cytotoxic for HEK293T cells and selective for 17β-hydroxysteroid dehydrogenases not primarily involved in steroid hormone metabolism. Nevertheless, they inhibited several enzymes of the steroid metabolism pathways. Favourable substitutions that enhanced AKR1C3 inhibition of chalcones were identified. This study paves the way to further develop compounds from this series or related flavonoids with improved inhibitory activity against AKR1C3.

Under the label of the German Mouse Clinic (GMC), a concept has been developed and implemented that allows the better understanding of human diseases on the pathophysiological and molecular level. This includes better understanding of the crosstalk between different organs, pleiotropy of genes, and the systemic impact of envirotypes and drugs. In the GMC, experts from various fields of mouse genetics and physiology, in close collaboration with clinicians, work side by side under one roof. The GMC is an open-access platform for the scientific community by providing phenotypic analysis in bilateral collaborations (“bottom-up projects”) and as a partner and driver in international large-scale biology projects (“top-down projects”). Furthermore, technology development is a major topic in the GMC. Innovative techniques for primary and secondary screens are developed and implemented into the phenotyping pipelines (e.g., detection of volatile organic compounds, VOCs).

Steroid-related cancers can be treated by inhibitors of steroid metabolism. In searching for new inhibitors of human 17beta-hydroxysteroid dehydrogenase type 1 (17beta-HSD 1) for the treatment of breast cancer or endometriosis, novel substances based on 15-substituted estrone were validated. We checked the specificity for different 17beta-HSD types and species. Compounds were tested for specificity in vitro not only towards recombinant human 17beta-HSD types 1, 2, 4, 5 and 7 but also against 17beta-HSD 1 of several other species including marmoset, pig, mouse, and rat. The latter are used in the processes of pharmacophore screening. We present the quantification of inhibitor preferences between human and animal models. Profound differences in the susceptibility to inhibition of steroid conversion among all 17beta-HSDs analyzed were observed. Especially, the rodent 17beta-HSDs 1 were significantly less sensitive to inhibition compared to the human ortholog, while the most similar inhibition pattern to the human 17beta-HSD 1 was obtained with the marmoset enzyme. Molecular docking experiments predicted estrone as the most potent inhibitor. The best performing compound in enzymatic assays was also highly ranked by docking scoring for the human enzyme. However, species-specific prediction of inhibitor performance by molecular docking was not possible. We show that experiments with good candidate compounds would out-select them in the rodent model during preclinical optimization steps. Potentially active human-relevant drugs, therefore, would no longer be further developed. Activity and efficacy screens in heterologous species systems must be evaluated with caution.

Fibroblast growth factor (Fgf) signalling plays a crucial role in many developmental processes. Among the Fgf pathway ligands, Fgf9 (UniProt: P54130) has been demonstrated to participate in maturation of various organs and tissues including skeleton, testes, lung, heart, and eye. Here we establish a novel Fgf9 allele, discovered in a dominant N-ethyl-N-nitrosourea (ENU) screen for eye-size abnormalities using the optical low coherence interferometry technique. The underlying mouse mutant line Aca12 was originally identified because of its significantly reduced lens thickness. Linkage studies located Aca12 to chromosome 14 within a 3.6 Mb spanning interval containing the positional candidate genes Fgf9 (MGI: 104723), Gja3 (MGI: 95714), and Ift88 (MGI: 98715). While no sequence differences were found in Gja3 and Ift88, we identified an A→G missense mutation at cDNA position 770 of the Fgf9 gene leading to an Y162C amino acid exchange. In contrast to previously described Fgf9 mutants, Fgf9(Y162C) carriers were fully viable and did not reveal reduced body-size, male-to-female sexual reversal or skeletal malformations. The histological analysis of the retina as well as its basic functional characterization by electroretinography (ERG) did not show any abnormality. However, the analysis of head-tracking response of the Fgf9(Y162C) mutants in a virtual drum indicated a gene-dosage dependent vision loss of almost 50%. The smaller lenses in Fgf9(Y162C) suggested a role of Fgf9 during lens development. Histological investigations showed that lens growth retardation starts during embryogenesis and continues after birth. Young Fgf9(Y162C) lenses remained transparent but developed age-related cataracts. Taken together, Fgf9(Y162C) is a novel neomorphic allele that initiates microphakia and reduced vision without effects on organs and tissues outside the eye. Our data point to a role of Fgf9 signalling in primary and secondary lens fiber cell growth. The results underline the importance of allelic series to fully understand multiple functions of a gene.

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.