Identifying essential genes in bacterial metabolic networks with machine learning methods

Background  

Identifying essential genes in bacteria supports to identify potential drug targets and an understanding of minimal requirements for a synthetic cell. However, experimentally assaying the essentiality of their coding genes is resource intensive and not feasible for all bacterial organisms, in particular if they are infective.     

State-of-the art data normalization methods improve NMR-based metabolomic analysis

Extracting biomedical information from large metabolomic datasets by multivariate data analysis is of considerable complexity. Common challenges include among others screening for differentially produced metabolites, estimation of fold changes, and sample classification. Prior to these analysis steps, it is important to minimize contributions from unwanted biases and experimental variance. This is the goal of data preprocessing. In this work, different data normalization methods were compared systematically employing two different datasets generated by means of nuclear magnetic resonance (NMR) spectroscopy. To this end, two different types of normalization methods were used, one aiming to remove unwanted sample-to-sample variation while the other adjusts the variance of the different metabolites by variable scaling and variance stabilization methods. The impact of all methods tested on sample classification was evaluated on urinary NMR fingerprints obtained from healthy volunteers and patients suffering from autosomal polycystic kidney disease (ADPKD). Performance in terms of screening for differentially produced metabolites was investigated on a dataset following a Latin-square design, where varied amounts of 8 different metabolites were spiked into a human urine matrix while keeping the total spike-in amount constant. In addition, specific tests were conducted to systematically investigate the influence of the different preprocessing methods on the structure of the analyzed data. In conclusion, preprocessing methods originally developed for DNA microarray analysis, in particular, Quantile and Cubic-Spline Normalization, performed best in reducing bias, accurately detecting fold changes, and classifying samples.

     

Toll-like receptor 4 deficiency: Smaller infarcts,but nogain in function

Backgound  

It has been reported that Toll-like receptor 4 (TLR4) deficiency reduces infarct size after myocardial ischemia/reperfusion (MI/R). However, measurement of MI/R injury was limited and did not include cardiac function. In a chronic closed-chest model we assessed whether cardiac function is preserved in TLR4-deficient mice (C3H/HeJ) following MI/R, and whether myocardial and systemic cytokine expression differed compared to wild type (WT).     

Extracellular ATP and adenosine modulate tumor necrosis factor-induced lysis of L929 cells in the presence of actinomycin D

Extracellular ATP in concentrations of 0.5 to 2.5 mM modulates TNF-induced cytolysis of L929 cells in the presence of actinomycin D. When present throughout the entire assay period, it inhibits the TNF-induced cytolysis. ADP was less active whereas AMP and GTP were nonreactive. However, inhibition was also achieved by adenosine that was nearly as active as ATP. Yet, the inhibitory effect of ATP was not due to hydrolysis by ectoenzymes to form adenosine. Thus, the nonhydrolyzable ATP analogue adenyl(beta-gamma-methylendiphosphate) was equally effective in inhibiting TNF-induced cytolysis. Moreover, no conversion of ATP into adenosine was observed during the entire assay period. However, inhibition no longer occurred when the TNF and ATP containing medium was removed after 5 h and replaced by a fresh medium containing TNF and no ATP. We now observed substantial enhancement of the TNF-induced cytolysis by ATP. Finally, treatment with N6-(R-phenylisopropyl)adenosine or with aminophylline, which are thought to downregulate adenosine receptors and to prevent binding of ligands to adenosine receptors, respectively, abolishes adenosine and ATP-mediated inhibition. Again, substantial enhancement of the TNF-induced cytolysis was observed by ATP and only a minor effect by adenosine. The results together suggest that ATP interacts with purinoceptors on the plasma membrane and is capable to enhance and inhibit TNF-induced cytolysis under appropriate conditions. The outcome of the ATP-induced modulation may be influenced by adenosine receptors.     

Raman spectroscopic investigation of the interaction of gramicidin A with dipalmitoyl phosphatidylcholine liposomes.

The interaction of gramicidin A with dipalmitoyl phosphatidylcholine liposomes is investigated by Laser-Raman spectroscopy. As revealed by the methylene C-H stretching mode the phase transition of the hydrocarbon chains near 40 degree C is eliminated in the presence of gramicidin A. Liposomes prepared from a mixture of lecithin and cholesterol seem to be unaffected by gramicidin A and show only the normal broadened phase transition.