Regulation der Phosphorylierung des NF-kB reprimierenden Faktors (NRF)

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HepatoNet1: a comprehensive metabolic reconstruction of the human hepatocyte for the analysis of liver physiology

We present HepatoNet1, a manually curated large-scale metabolic network of the human hepatocyte that encompasses >2500 reactions in six intracellular and two extracellular compartments.Using constraint-based modeling techniques, the network has been validated to replicate numerous metabolic functions of hepatocytes corresponding to a reference set of diverse physiological liver functions.Taking the detoxification of ammonia and the formation of bile acids as examples, we show how these liver-specific metabolic objectives can be achieved by the variable interplay of various metabolic pathways under varying conditions of nutrients and oxygen availability

IGERS: Inferring Gibbs Energy Changes of Biochemical Reactions from Reaction Similarities

Mathematical analysis and modeling of biochemical reaction networks requires knowledge of the permitted directionality of reactions and membrane transport processes. This information can be gathered from the standard Gibbs energy changes (ΔG0) of reactions and the concentration ranges of their reactants. Currently, experimental ΔG0 values are not available for the vast majority of cellular biochemical processes. We propose what we believe to be a novel computational method to infer the unknown ΔG0 value of a reaction from the known ΔG0 value of the chemically most similar reaction. The chemical similarity of two arbitrary reactions is measured by the relative number (T) of co-occurring changes in the chemical attributes of their reactants. Testing our method across a validated reference set of 173 biochemical reactions with experimentally determined ΔG0 values, we found that a minimum reaction similarity of T = 0.6 is required to infer ΔG0 values with an error of <10 kJ/mol. Applying this criterion, our method allows us to assign ΔG0 values to 458 additional reactions of the BioPath database. We believe our approach permits us to minimize the number of ΔG0 measurements required for a full coverage of a given reaction network with reliable ΔG0 values

Inhibition of NK cell activation by LLT1-mediated triggering of CD161.

<p>PBMC were isolated and co-cultivated for three hours with 293-mock or 293-LLT1 transfectants. Activation of NK cells was assessed by monitoring CD107a expression on gated CD3^-CD56⁺ and CD3^-CD56⁺CD161⁺/CD161^- cells. (A) Abrogation of inhibition by antibody-mediated blocking of CD161/LLT1 interactions. Co-cultivation of PBMC with 293 transfectants was performed in the presence of the anti-CD161 mAb 191B8 or an isotype-matched control antibody. (B) Frequency of activated NK cells after cultivation with 293-mock or 293-LLT1 cells. PBMC from nine individuals with CD161 TT and four carriers of CC were studied. (C) Diminished capacity of CD161 from CC carriers to inhibit NK cell activation. % Inhibition was calculated as follows: 100 - [(%CD107a⁺ NK cells in 293-LLT1 co-cultures / %CD107a⁺ NK cells in 293-mock co-cultures) x 100];*p<0.05 (Mann-Whitney). (D) LLT1 induced CD161 down-regulation on IL-12 activated NK cells. PBMC were co-cultured for three hours with either mock transfected 293 cells or cells expressing LLT1. CD161 expression was monitored on gated CD3^-CD56⁺ NK cells. Depicted histograms show CD161 expression in untreated NK cells (open) and after treatment with 293-LLT1 transfectants (filled histograms). The broken vertical line indicates the peak of CD161 observed in LLT1-treated NK cells from a TT individual. The graph summarizes data obtained in experiments using cells from five TT and three CC individuals (mean ± SEM).</p

Assessment of lymphocyte subsets in individuals carrying different CD161 genotypes.

<p>PBMC were isolated and stained with the antibody combinations CD161/CD3/CD4 or CD161/CD3/CD56. Analyses were performed in gated viable lymphocytes as defined by forward- and side-scatter characteristics. (A) CD161 expression patterns on CD3^- NK cells. Representative dot-plots obtained after staining of cells from one TT, TC, and CC individual are shown. Boxes indicate the CD56^brightCD161⁺CD3^- NK cell subset and the frequency. The numbers indicate % positive cells in each quadrant. (B) Decreased frequency of CD3^-CD56⁺ NK cells in CC carriers. PBMC from 27 TT, 51 TC, and 16 carriers of CC were analyzed. Results are expressed as % NK cells among gated lymphocytes; the mean value calculated for each cohort is indicated by the horizontal line; *p< 0.05 (ANOVA). (C) Ratios of CD56^dim to CD56^bright NK cells. The frequencies of CD56^dimCD161⁺CD3^- and CD56^brightCD161⁺CD3^- NK cells were determined in gated lymphocytes from 22 TT, 46 TC, and 15 carriers of CC. The horizontal broken line is an arbitrary cut-off value. (D) Level of CD161 expression. Data are expressed as mean fluorescence intensity/MFI on gated CD3^-CD56⁺ NK cells. (E) Proportion of NK cells co-expressing CD161. Data are expressed as % CD161⁺ cells in gated CD3^-CD56⁺ NK cells. (F) CD161 expression patterns on CD3⁺ T cells. The numbers indicate % positive cells in each quadrant. (G) Proportion of CD4⁺ T cells co-expressing CD161. (H) Proportion of CD8⁺ T cells co-expressing CD161^dim or CD161^bright.</p

Inhibition of NKp46-induced NK cell activation by antibody-mediated triggering of CD161.

<p>PBMC were isolated and stimulated for three hours with the anti-NKp46 mAb 9E2 combined with the anti-CD161 mAb 191B8 or an isotype matched control antibody. The antibodies had been coupled to Fc-receptors on P815 cells. Activation of NK cells was assessed by monitoring CD107a expression on gated CD3^-CD56⁺ cells. (A) Representative dot-plots showing weaker down-regulation of NK cell activation by anti-CD161 triggering in NK cells from a CC carrier compared to cells from a TT individual. (B) Frequency of activated NK cells after stimulation with anti-NKp46 plus isotype control and anti-NKp46 plus anti-CD161. PBMC from nine individuals with CD161 TT and nine carriers of CC were studied. (C) Diminished capacity of CD161 from CC carriers to inhibit NKp46-induced NK cell activation. % Inhibition was calculated as follows: 100 - [(%CD107a⁺ NK cells after stimulation with NKp46-CD161 / % CD107a⁺ NK cells after stimulation with NKp46-isotype) x 100]; *p<0.05 (Unpaired t-test).</p