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).     

Identification of Cell Cycle Dependent Interaction Partners of the Septins by Quantitative Mass Spectrometry

The septins are a conserved family of GTP-binding proteins that, in the baker''s yeast, assemble into a highly ordered array of filaments at the mother bud neck. These filaments undergo significant structural rearrangements during the cell cycle. We aimed at identifying key components that are involved in or regulate the transitions of the septins. By combining cell synchronization and quantitative affinity-purification mass-spectrometry, we performed a screen for specific interaction partners of the septins at three distinct stages of the cell cycle. A total of 83 interaction partners of the septins were assigned. Surprisingly, we detected DNA-interacting/nuclear proteins and proteins involved in ribosome biogenesis and protein synthesis predominantly present in alpha-factor arrested that do not display an assembled septin structure. Furthermore, two distinct sets of regulatory proteins that are specific for cells at S-phase with a stable septin collar or at mitosis with split septin rings were identified.Complementary methods like SPLIFF and immunoprecipitation allowed us to more exactly define the spatial and temporal characteristics of selected hits of the AP-MS screen.     

Oat mesophyll protoplasts: their response to various feeder cultures

Oat (Avena sativa L.) mesophyll protoplasts were recently demonstrated to be capable of dedifferentiation, repeated divisions, and colony formation. Since the development of oat mesophyll protoplasts is decisively influenced by the nature of the used feeder culture (species, variety and concentration), we conducted a systematic study of this parameter. Generally, graminaceous feeders promoted protoplast proliferation, while dicot species repressed protoplast divisions. The beneficial effect of those feeders that promote divisions was counterbalanced by a factor that causes necrosis. The correct balance between promotion of divisions or necrosis depended on the nature of the feeder and its plating density.     

The study of a French family with two duplicated C4A haplotypes

Summary The finding of two duplicated C4A haplotypes in a normal French family led to a detailed study of their C4 polymorphism. The father had an extremely rare A^*6A^*11, B^* QO haplotype inherited by all of his children and the mother had the more common A^*3A^*2, B^*QO haplotype. Two HLA identical daughters only have four C4A alleles. The father's A11 allotype expresses Ch: 1 (Chido) rather than Rg:1 (Rodgers) and represents a new Ch phenotype Ch: 1,-2,-3,-4,-5,-6. In order to clarify the genetic background in this unusual family, DNA studies of restriction fragment length polymorphisms (RFLPs) were undertake. The father's rare haplotype, which expresses two C4A allotypes, results from a long and a short C4 gene normally associated with the A^*6, B^*1 that also exhibits the BglII RFLP. As it travels in an extended MHC haplotype HLA A2, B57 (17), C2^*C, BF^*S, DR7 that is most frequently associated with A^*6, B^*1, we postulate that the short C4B has been converted in the chain region to a C4A gene which produces a C4A protein. This report of a short C4A gene is the first example in the complex polymorphism of C4.     

Complete maps of IS1, IS2, IS3, IS4, IS5, IS30 and IS150 locations in Escherichia coli K12

Summary In this paper complete distribution maps are presented of the seven IS elements 1, 2, 3, 4, 5, 30 and 150. These maps were obtained during the construction of an almost complete restriction map of the Escherichia coli genome of K12 strain BHB2600. The positions of IS elements were correlated to this map. The distribution of integration sites of all IS types is nonrandom. Besides a large gap from 79 min to 96 min, there is a pronounced IS cluster at 6 min and another at 97 min, map locations that have low gene incidences on the classical map. One cluster coincides with a region of IS induced rearrangements. The IS distribution pattern was compared to patterns of strains W3110 and HB101.