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).     

Nerve Growth Factor Effect on Adenosine Transport in Cultured Chromaffin Cells

Chromaffin cells both recently isolated or in culture present a high-affinity adenosine transporter with a Km value of 1 microM. When cells were exposed to nerve growth factor (NGF; 10 ng/ml), the adenosine transporter affinity decreased to 3 microM. This value was maintained from 3 days after plating to the end of the culture period. A change in the transport capacity was observed, with a significant increase (approximately 200-260%) in NGF-cultured cells throughout the period studied.     

Modelling mass transfer and agitator performance in multiturbine fermentors

A methodology for mathematically analyzing agitator performance and mass transfer in large multiturbine production fermentors is presented. The application of this approach provides a method for determining axial dissolved oxygen profiles under conditions of known mass transfer rates as a function of agitation-aeration characteristics. A stagewise approach is used which divides the fermentor into a series of mixing cells. This allows for each turbine and mixing cell to be individually optimized. The model also permits the determination of the mass transfer coefficient for each turbine based upon limited dissolved oxygen data. The primary limitation of this approach rests in the limited data and correlations available for multiturbine systems. The structure of the modelling approach can serve as a basis for testing single turbine correlations and adapting them to multiturbine systems. The step-by-step details of the mathematical analysis are presented and interpreted. A series of computer simulations demonstrate the effect of typical fermentor operating variables on the axial dissolved oxygen profile. Further simulations demonstrate the effect of modifying agitator blade numbers on the dissolved oxygen profile and agitator power requirement.     

Amyloplasts are necessary for full gravitropic sensitivity in roots of Arabidopsis thaliana

The observation that a starchless mutant (TC7) of Arabidopsis thaliana (L.) Heynh. is gravitropic (T. Caspar and B.G. Pickard, 1989, Planta 177, 185–197) raises questions about the hypothesis that starch and amyloplasts play a role in gravity perception. We compared the kinetics of gravitropism in this starchless mutant and the wild-type (WT). Wild-type roots are more responsive to gravity than TC7 roots as judged by several parameters: (1) Vertically grown TC7 roots were not as oriented with respect to the gravity vector as WT roots. (2) In the time course of curvature after gravistimulation, curvature in TC7 roots was delayed and reduced compared to WT roots. (3) TC7 roots curved less than WT roots following a single, short (induction) period of gravistimulation, and WT, but not TC7, roots curved in response to a 1-min period of horizontal exposure. (4) Wild-type roots curved much more than TC7 roots in response to intermittent stimulation (repeated short periods of horizontal exposure); WT roots curved in response to 10 s of stimulation or less, but TC7 roots required 2 min of stimulation to produce a curvature. The growth rates were equal for both genotypes. We conclude that WT roots are more sensitive to gravity than TC7 roots. Starch is not required for gravity perception in TC7 roots, but is necessary for full sensitivity; thus it is likely that amyloplasts function as statoliths in WT Arabidopsis roots. Furthermore, since centrifugation studies using low gravitational forces indicated that starchless plastids are relatively dense and are the most movable component in TC7 columella cells, the starchless plastids may also function as statoliths.Abbreviations S2 story two - S3 story three - WT wild-type     

Effect of secretagogues on chromogranin A synthesis in bovine cultured chromaffin cells. Possible regulation by protein kinase C.

Chromogranin A is a major component of storage granules in many different secretory cell types. After [35S]methionine labelling of proteins from cultured bovine chromaffin cells, chromogranin A was immunoprecipitated with specific antibodies, and the radioactivity incorporated into chromogranin A was determined and used as an index of its synthesis rate. Depolarization of cells with nicotine or high K+ evoked a Ca2+-dependent increase in chromogranin A synthesis, whereas muscarine, which does not evoke significant Ca2+ influx from bovine chromaffin cells, had no effect on chromogranin A synthesis. Forskolin, an activator of adenylate cyclase, affected neither the basal nor the nicotine-stimulated rate of chromogranin A synthesis. In contrast, 12-O-tetradecanoylphorbol 13-acetate (TPA), an activator of protein kinase C, significantly enhanced the incorporation of radioactivity into chromogranin A. Sphingosine, an inhibitor of protein kinase C, abolished both nicotine-stimulated and TPA-induced chromogranin A synthesis. In addition, long-term treatment of chromaffin cells with TPA decreased protein kinase C activity and inhibited the nicotine-stimulated chromogranin A synthesis. These results suggest that protein kinase C may play an important role in the control of chromogranin A synthesis.