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TLRs are innate immune receptors that recognize pathogen-associated structures. Binding of ligands to different TLRs can induce the production of proinflammatory cytokines in a synergistic manner. We have analyzed the molecular mechanisms of synergy in TLR ligand-stimulated human monocyte-derived macrophages and dendritic cells (moDCs). Stimulation of moDCs with the TLR8 ligand together with the TLR3 or TLR4 ligand led to synergistic IL-6, IL-10, IL-12, and TNF-alpha mRNA expression and cytokine production. DNA-binding assays showed that TLR3 and TLR8 stimulation induced binding of multiple IFN regulatory factor (IRF) and STAT transcription factors to the IL-12p35 gene promoter IFN-stimulated response element in moDCs and macrophages but with different binding profiles and kinetics. We also demonstrate that NF-kappaB, MAPKs and PI-3K pathways have an important role in TLR-induced cytokine gene expression, as pharmacological inhibitors of these signaling pathways inhibited TLR3, TLR4, and TLR8 ligand-induced cytokine mRNA expression and protein production. Especially, synergistic IL-12p70 production was abolished completely in NF-kappaB, MAPK p38, and PI-3K inhibitor-treated moDCs. Our data suggest that TLR-dependent, synergistic cytokine gene expression results from enhanced activation and cooperation among NF-kappaB, IRF, MAPK, PI-3K, and STAT signaling pathways.

BackgroundA key challenge in metabonomics is to uncover quantitative associations between multidimensional spectroscopic data and biochemical measures used for disease risk assessment and diagnostics. Here we focus on clinically relevant estimation of lipoprotein lipids by 1H NMR spectroscopy of serum.ResultsA Bayesian methodology, with a biochemical motivation, is presented for a real 1H NMR metabonomics data set of 75 serum samples. Lipoprotein lipid concentrations were independently obtained for these samples via ultracentrifugation and specific biochemical assays. The Bayesian models were constructed by Markov chain Monte Carlo (MCMC) and they showed remarkably good quantitative performance, the predictive R-values being 0.985 for the very low density lipoprotein triglycerides (VLDL-TG), 0.787 for the intermediate, 0.943 for the low, and 0.933 for the high density lipoprotein cholesterol (IDL-C, LDL-C and HDL-C, respectively). The modelling produced a kernel-based reformulation of the data, the parameters of which coincided with the well-known biochemical characteristics of the 1H NMR spectra; particularly for VLDL-TG and HDL-C the Bayesian methodology was able to clearly identify the most characteristic resonances within the heavily overlapping information in the spectra. For IDL-C and LDL-C the resulting model kernels were more complex than those for VLDL-TG and HDL-C, probably reflecting the severe overlap of the IDL and LDL resonances in the 1H NMR spectra.ConclusionThe systematic use of Bayesian MCMC analysis is computationally demanding. Nevertheless, the combination of high-quality quantification and the biochemical rationale of the resulting models is expected to be useful in the field of metabonomics.

Several plant estrogens, especially coumestrol and genistein, were found to reduce the conversion of [3H]estrone to [3H] 17 beta-estradiol catalyzed by estrogen-specific 17 beta-hydroxysteroid oxidoreductase Type 1 (E.C. 1.1.1.62) in vitro. Coumestrol, the most potent inhibitor in our experiments, is the best inhibitor of the enzyme known to date. All compounds with inhibitory effects were also estrogenic. However, structural demands for 17 beta-HSOR Type 1 inhibition and estrogenicity of tested compounds in breast cancer cells (judged by increased cell proliferation) were not identical. Zearalenone and diethylstilbestrol, both potent estrogens, did not inhibit 17 beta-HSOR Type 1. Thus, changes in the estrogen molecule may discriminate between active sites of 17 beta-HSOR Type 1 and estrogen binding sites of the ER. The effects of these compounds in vivo cannot be predicted on the basis of these results. Inhibition of 17 beta-HSOR Type 1 enzyme could lead to a decrease in the availability of the highly active endogenous estrogen. However, these compounds are estrogenic per se, and they may thus replace endogenous estrogens. Additional studies are needed to further understand the role of these plant estrogens in the etiology of hormone-dependent cancers. It is not easily conceivable how the chemopreventive action of Asian diets, possibly mediated by phytoestrogens in soya products, can be based on the inhibition of estrone reduction at the target cells by phytoestrogens or related compounds, unless they are "incomplete estrogens" (i.e., unable to induce all effects typical of endogenous estrogens).

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