Inverse association between Helicobacter pylori and pediatric asthma in a high-prevalence population

Background: Helicobacter pylori‐associated disease has led to aggressive diagnostic and eradication protocols that are partially responsible for the decrease in prevalence of H. pylori carriage. Recent evidence indicates that in low‐prevalence populations, H. pylori may have protective effects on allergic diseases. The aim of this study was to explore the relationship between pediatric asthma and H. pylori infection in a population with high prevalence of H. pylori infection. Materials and Methods: A national referral laboratory was screened for all ¹³C urea breath tests performed in children aged 5–18 years between 2007 and 2008, for patient demographics and physician‐diagnosed asthma. Data concerning asthma‐associated medication usage were extracted from electronic medical records and databases. Data were analyzed using a stepwise logistic regression model. Results: During the study period, 6959 patients underwent urea breath testing (average age 12.4 ± 3.5 years). Of these, 3175/6959 (45.6%) were positive for H. pylori, and 578/6959 (8.3%) had asthma. Rates of asthma in H. pylori‐positive and H. pylori‐negative children were 7.3 and 9.1%, respectively (odds ratio 0.82; 95% confidence interval (CI) 0.69–0.98; p = .032). We also confirmed that male gender, urban residence, and age are associated with childhood asthma. Conclusions: We demonstrate an inverse association between H. pylori and pediatric asthma in a population with a high prevalence of H. pylori.     

Defining the role of matrix compliance and proteolysis in three-dimensional cell spreading and remodeling

Recent studies have identified extracellular matrix (ECM) compliance as an influential factor in determining the fate of anchorage-dependent cells. We explore a method of examining the influence of ECM compliance on cell morphology and remodeling in three-dimensional culture. For this purpose, a biological ECM analog material was developed to pseudo-independently alter its biochemical and physical properties. A set of 18 material variants were prepared with shear modulus ranging from 10 to 700 Pa. Smooth muscle cells were encapsulated in these materials and time-lapse video microscopy was used to show a relationship between matrix modulus, proteolytic biodegradation, cell spreading, and cell compaction of the matrix. The proteolytic susceptibility of the matrix, the degree of matrix compaction, and the cell morphology were quantified for each of the material variants to correlate with the modulus data. The initial cell spreading into the hydrogel matrix was dependent on the proteolytic susceptibility of the materials, whereas the extent of cell compaction proved to be more correlated to the modulus of the material. Inhibition of matrix metalloproteinases profoundly affected initial cell spreading and remodeling even in the most compliant materials. We concluded that smooth muscle cells use proteolysis to form lamellipodia and tractional forces to contract and remodel their surrounding microenvironment. Matrix modulus can therefore be used to control the extent of cellular remodeling and compaction. This study further shows that the interconnection between matrix modulus and proteolytic resistance in the ECM may be partly uncoupled to provide insight into how cells interpret their physical three-dimensional microenvironment.     

Succession of bacterial communities during early plant development: transition from seed to root and effect of compost amendment

Compost amendments to soils and potting mixes are routinely applied to improve soil fertility and plant growth and health. These amendments, which contain high levels of organic matter and microbial cells, can influence microbial communities associated with plants grown in such soils. The purpose of this study was to follow the bacterial community compositions of seed and subsequent root surfaces in the presence and absence of compost in the potting mix. The bacterial community compositions of potting mixes, seed, and root surfaces sampled at three stages of plant growth were analyzed via general and newly developed Bacteroidetes-specific, PCR-denaturing gradient gel electrophoresis methodologies. These analyses revealed that seed surfaces were colonized primarily by populations detected in the initial potting mixes, many of which were not detected in subsequent root analyses. The most persistent bacterial populations detected in this study belonged to the genus Chryseobacterium (Bacteroidetes) and the family Oxalobacteraceae (Betaproteobacteria). The patterns of colonization by populations within these taxa differed significantly and may reflect differences in the physiology of these organisms. Overall, analyses of bacterial community composition revealed a surprising prevalence and diversity of Bacteroidetes in all treatments.     

Reconstitution and alignment by a magnetic field of a β-barrel membrane protein in bicelles

A protocol is described for the reconstitution of a transmembrane β-barrel protein domain, tOmpA, into lipid bicelles. tOmpA is the largest protein to be reconstituted in bicelles to date. Its insertion does not prevent bicelles from orienting with their plane either parallel or perpendicular to the magnetic field, depending on the absence or presence of paramagnetic ions. In the latter case, tOmpA is shown to align with the axis of the β-barrel parallel to the magnetic field, i.e. perpendicular to the plane of the bilayer, an orientation conforming to that in natural membranes and favourable to structural studies by solid-state NMR. Reconstitution into bicelles may offer an interesting approach for structural studies of membrane proteins in a medium resembling a biological membrane, using either NMR or other biophysical techniques. Our data suggest that alignment in the magnetic field of membrane proteins included into bicelles may be facilitated if the protein is folded as a β-barrel structure.     

Modelling and analysis of gene regulatory networks

Gene regulatory networks have an important role in every process of life, including cell differentiation, metabolism, the cell cycle and signal transduction. By understanding the dynamics of these networks we can shed light on the mechanisms of diseases that occur when these cellular processes are dysregulated. Accurate prediction of the behaviour of regulatory networks will also speed up biotechnological projects, as such predictions are quicker and cheaper than lab experiments. Computational methods, both for supporting the development of network models and for the analysis of their functionality, have already proved to be a valuable research tool.     

Computational problems in perfect phylogeny haplotyping: typing without calling the allele

A haplotype is an m-long binary vector. The XOR-genotype of two haplotypes is the m-vector of their coordinate-wise XOR. We study the following problem: Given a set of XOR-genotypes, reconstruct their haplotypes so that the set of resulting haplotypes can be mapped onto a perfect phylogeny (PP) tree. The question is motivated by studying population evolution in human genetics, and is a variant of the perfect phylogeny haplotyping problem that has received intensive attention recently. Unlike the latter problem, in which the input is "full" genotypes, here we assume less informative input, and so may be more economical to obtain experimentally. Building on ideas of Gusfield, we show how to solve the problem in polynomial time, by a reduction to the graph realization problem. The actual haplotypes are not uniquely determined by that tree they map onto, and the tree itself may or may not be unique. We show that tree uniqueness implies uniquely determined haplotypes, up to inherent degrees of freedom, and give a sufficient condition for the uniqueness. To actually determine the haplotypes given the tree, additional information is necessary. We show that two or three full genotypes suffice to reconstruct all the haplotypes, and present a linear algorithm for identifying those genotypes.     

MetaReg: a platform for modeling, analysis and visualization of biological systems using large-scale experimental data

MetaReg http://acgt.cs.tau.ac.il/metareg/application.html is a computational tool that models cellular networks and integrates experimental results with such models. MetaReg represents established knowledge about a biological system, available today mostly in informal form in the literature, as probabilistic network models with underlying combinatorial regulatory logic. MetaReg enables contrasting predictions with measurements, model improvements and studying what-if scenarios. By summarizing prior knowledge and providing visual and computational aids, it helps the expert explore and understand her system better.     

Omapatrilat,an Angiotensin-Converting Enzyme and Neutral Endopeptidase Inhibitor,Attenuates Early Atherosclerosis in Diabetic and in Nondiabetic Low-Density Lipoprotein Receptor–Deficient Mice

Omapatrilat inhibits both angiotensin-converting enzyme (ACE) and neutral endopeptidase (NEP). ACE inhibitors have been shown to inhibit atherosclerosis in apoE-deficient mice and in several other animal models but failed in low-density lipoprotein (LDL) receptor– deficient mice despite effective inhibition of the reninangiotensin- aldosterone system. The aim of the present study was to examine the effect of omapatrilat on atherogenesis in diabetic and nondiabetic LDL receptor–deficient mice. LDL receptor–deficient male mice were randomly divided into 4 groups (n = 11 each). Diabetes was induced in 2 groups by low-dose STZ, the other 2 groups served as nondiabetic controls. Omapatrilat (70 mg/kg/day) was administered to one of the diabetic and to one of the nondiabetic groups. The diabetic and the nondiabetic mice were sacrificed after 3 and 5 weeks, respectively. The aortae were examined and the atherosclerotic plaque area was measured. The atherosclerotic plaque area was significantly smaller in the omapatrilat-treated mice, both diabetic and nondiabetic, as compared to nontreated controls. The mean plaque area of omapatrilattreated nondiabetic mice was 9357 ± 7293 μm², versus 71977 ± 34610 μm² in the nontreated mice (P = .002). In the diabetic animals, the plaque area was 8887 ± 5386 μm² and 23220 ± 10400 μm², respectively for treated and nontreated mice (P = .001). Plasma lipids were increased by omapatrilat: Meanplasma cholesterol in treated mice, diabetic and nondiabetic combined, was 39.31 ± 6.00 mmol/L, versus 33.12 ± 7.64 mmol/L in the nontreated animals (P = .008). The corresponding combined mean values of triglycerides were 4.83 ± 1.93 versus 3.00 ± 1.26 mmol/L (P = .02). Omapatrilat treatment did not affect weight or plasma glucose levels. Treatment with omapatrilat inhibits atherogenesis in diabetic as well as nondiabetic LDL receptor–deficient mice despite an increase in plasma lipids, suggesting a direct effect on the arterial wall.