Metal-responsive gene regulation and metal transport in Helicobacter species

Helicobacter species are among the most successful colonizers of the mammalian gastrointestinal and hepatobiliary tract. Colonization is usually lifelong, indicating that Helicobacter species have evolved intricate mechanisms of dealing with stresses encountered during colonization of host tissues, like restriction of essential metal ions. The recent availability of genome sequences of the human gastric pathogen Helicobacter pylori, the murine enterohepatic pathogen Helicobacter hepaticus and the unannotated genome sequence of the ferret gastric pathogen Helicobacter mustelae has allowed for comparitive genome analyses. In this review we present such analyses for metal transporters, metal-storage and metal-responsive regulators in these three Helicobacter species, and discuss possible contributions of the differences in metal metabolism in adaptation to the gastric or enterohepatic niches occupied by Helicobacter species

Common variants of the TCF7L2 gene are associated with increased risk of type 2 diabetes mellitus in a UK-resident South Asian population

Background Recent studies have implicated variants of the transcription factor 7-like 2 (TCF7L2) gene in genetic susceptibility to type 2 diabetes mellitus in several different populations. The aim of this study was to determine whether variants of this gene are also risk factors for type 2 diabetes development in a UK-resident South Asian cohort of Punjabi ancestry. Methods We genotyped four single nucleotide polymorphisms (SNPs) of TCF7L2 (rs7901695, rs7903146, rs11196205 and rs12255372) in 831 subjects with diabetes and 437 control subjects. Results The minor allele of each variant was significantly associated with type 2 diabetes; the greatest risk of developing the disease was conferred by rs7903146, with an allelic odds ratio (OR) of 1.31 (95% CI: 1.11 – 1.56, p = 1.96 × 10-3). For each variant, disease risk associated with homozygosity for the minor allele was greater than that for heterozygotes, with the exception of rs12255372. To determine the effect on the observed associations of including young control subjects in our data set, we reanalysed the data using subsets of the control group defined by different minimum age thresholds. Increasing the minimum age of our control subjects resulted in a corresponding increase in OR for all variants of the gene (p ≤ 1.04 × 10-7). Conclusion Our results support recent findings that TCF7L2 is an important genetic risk factor for the development of type 2 diabetes in multiple ethnic groups

Reconstructing ‘the Alcoholic’: Recovering from Alcohol Addiction and the Stigma this Entails

Public perception of alcohol addiction is frequently negative, whilst an important part of recovery is the construction of a positive sense of self. In order to explore how this might be achieved, we investigated how those who self-identify as in recovery from alcohol problems view themselves and their difficulties with alcohol and how they make sense of others’ responses to their addiction. Semi-structured interviews with six individuals who had been in recovery between 5 and 35 years and in contact with Alcoholics Anonymous were analysed using Interpretative Phenomenological Analysis. The participants were acutely aware of stigmatising images of ‘alcoholics’ and described having struggled with a considerable dilemma in accepting this identity themselves. However, to some extent they were able to resist stigma by conceiving of an ‘aware alcoholic self’ which was divorced from their previously unaware self and formed the basis for a new more knowing and valued identity

Insight in modulation of inflammation in response to diclofenac intervention: a human intervention study

Background. Chronic systemic low-grade inflammation in obese subjects is associated with health complications including cardiovascular diseases, insulin resistance and diabetes. Reducing inflammatory responses may reduce these risks. However, available markers of inflammatory status inadequately describe the complexity of metabolic responses to mild anti-inflammatory therapy. Methods. To address this limitation, we used an integrative omics approach to characterize modulation of inflammation in overweight men during an intervention with the non-steroidal anti-inflammatory drug diclofenac. Measured parameters included 80 plasma proteins, >300 plasma metabolites (lipids, free fatty acids, oxylipids and polar compounds) and an array of peripheral blood mononuclear cells (PBMC) gene expression products. These measures were submitted to multivariate and correlation analysis and were used for construction of biological response networks. Results. A panel of genes, proteins and metabolites, including PGE2 and TNF-alpha, were identified that describe a diclofenac-response network (68 genes in PBMC, 1 plasma protein and 4 plasma metabolites). Novel candidate markers of inflammatory modulation included PBMC expression of annexin A1 and caspase 8, and the arachidonic acid metabolite 5,6-DHET. Conclusion. In this study the integrated analysis of a wide range of parameters allowed the development of a network of markers responding to inflammatory modulation, thereby providing insight into the complex process of inflammation and ways to assess changes in inflammatory status associated with obesity. Trial registration. The study is registered as NCT00221052 in clinicaltrials.gov database. © 2010 van Erk et al; licensee BioMed Central Ltd

Ruthenium polypyridyl complexes and their modes of interaction with DNA : is there a correlation between these interactions and the antitumor activity of the compounds?

Various interaction modes between a group of six ruthenium polypyridyl complexes and DNA have been studied using a number of spectroscopic techniques. Five mononuclear species were selected with formula [Ru(tpy) L1L2](2-n)?, and one closely related dinuclear cation of formula [{Ru(apy)(tpy)}2{l-H2N(CH2)6NH2}]4?. The ligand tpy is 2,20:60,200-terpyridine and the ligand L1 is a bidentate ligand, namely, apy (2,20-azobispyridine), 2-phenylazopyridine, or 2-phenylpyridinylmethylene amine. The ligand L2 is a labile monodentate ligand, being Cl-, H2O, or CH3CN. All six species containing a labile L2 were found to be able to coordinate to the DNA model base 9-ethylguanine by 1H NMR and mass spectrometry. The dinuclear cationic species, which has no positions available for coordination to a DNA base, was studied for comparison purposes. The interactions between a selection of four representative complexes and calf-thymus DNA were studied by circular and linear dichroism. To explore a possible relation between DNA-binding ability and toxicity, all compounds were screened for anticancer activity in a variety of cancer cell lines, showing in some cases an activity which is comparable to that of cisplatin. Comparison of the details of the compound structures, their DNA binding, and their toxicity allows the exploration of structure–activity relationships that might be used to guide optimization of the activity of agents of this class of compounds

Built Shallow to Maintain Homeostasis and Persistent Infection: Insight into the Transcriptional Regulatory Network of the Gastric Human Pathogen Helicobacter pylori

Transcriptional regulatory networks (TRNs) transduce environmental signals into coordinated output expression of the genome. Accordingly, they are central for the adaptation of bacteria to their living environments and in host–pathogen interactions. Few attempts have been made to describe a TRN for a human pathogen, because even in model organisms, such as Escherichia coli, the analysis is hindered by the large number of transcription factors involved. In light of the paucity of regulators, the gastric human pathogen Helicobacter pylori represents a very appealing system for understanding how bacterial TRNs are wired up to support infection in the host. Herein, we review and analyze the available molecular and “-omic” data in a coherent ensemble, including protein–DNA and protein–protein interactions relevant for transcriptional control of pathogenic responses. The analysis covers ∼80% of the annotated H. pylori regulators, and provides to our knowledge the first in-depth description of a TRN for an important pathogen. The emerging picture indicates a shallow TRN, made of four main modules (origons) that process the physiological responses needed to colonize the gastric niche. Specific network motifs confer distinct transcriptional response dynamics to the TRN, while long regulatory cascades are absent. Rather than having a plethora of specialized regulators, the TRN of H. pylori appears to transduce separate environmental inputs by using different combinations of a small set of regulators

(R)-[11C]Verapamil PET studies to assess changes in P-glycoprotein expression and functionality in rat blood-brain barrier after exposure to kainate-induced status epilepticus

<p>Abstract</p> <p>Background</p> <p>Increased functionality of efflux transporters at the blood-brain barrier may contribute to decreased drug concentrations at the target site in CNS diseases like epilepsy. In the rat, pharmacoresistant epilepsy can be mimicked by inducing status epilepticus by intraperitoneal injection of kainate, which leads to development of spontaneous seizures after 3 weeks to 3 months. The aim of this study was to investigate potential changes in P-glycoprotein (P-gp) expression and functionality at an early stage after induction of status epilepticus by kainate.</p> <p>Methods</p> <p><it>(R)</it>-[¹¹C]verapamil, which is currently the most frequently used positron emission tomography (PET) ligand for determining P-gp functionality at the blood-brain barrier, was used in kainate and saline (control) treated rats, at 7 days after treatment. To investigate the effect of P-gp on <it>(R)</it>-[¹¹C]verapamil brain distribution, both groups were studied without or with co-administration of the P-gp inhibitor tariquidar. P-gp expression was determined using immunohistochemistry in post mortem brains. <it>(R)</it>-[¹¹C]verapamil kinetics were analyzed with approaches common in PET research (Logan analysis, and compartmental modelling of individual profiles) as well as by population mixed effects modelling (NONMEM).</p> <p>Results</p> <p>All data analysis approaches indicated only modest differences in brain distribution of <it>(R)</it>-[¹¹C]verapamil between saline and kainate treated rats, while tariquidar treatment in both groups resulted in a more than 10-fold increase. NONMEM provided most precise parameter estimates. P-gp expression was found to be similar for kainate and saline treated rats.</p> <p>Conclusions</p> <p>P-gp expression and functionality does not seem to change at early stage after induction of anticipated pharmacoresistant epilepsy by kainate.</p

Knowledge driven decomposition of tumor expression profiles

<p>Abstract</p> <p>Background</p> <p>Tumors have been hypothesized to be the result of a mixture of oncogenic events, some of which will be reflected in the gene expression of the tumor. Based on this hypothesis a variety of data-driven methods have been employed to decompose tumor expression profiles into component profiles, hypothetically linked to these events. Interpretation of the resulting data-driven components is often done by post-hoc comparison to, for instance, functional groupings of genes into gene sets. None of the data-driven methods allow the incorporation of that type of knowledge directly into the decomposition.</p> <p>Results</p> <p>We present a linear model which uses knowledge driven, pre-defined components to perform the decomposition. We solve this decomposition model in a constrained linear least squares fashion. From a variety of options, a lasso-based solution to the model performs best in linking single gene perturbation data to mouse data. Moreover, we show the decomposition of expression profiles from human breast cancer samples into single gene perturbation profiles and gene sets that are linked to the hallmarks of cancer. For these breast cancer samples we were able to discern several links between clinical parameters, and the decomposition weights, providing new insights into the biology of these tumors. Lastly, we show that the order in which the Lasso regularization shrinks the weights, unveils consensus patterns within clinical subgroups of the breast cancer samples.</p> <p>Conclusion</p> <p>The proposed lasso-based constrained least squares decomposition provides a stable and relevant relation between samples and knowledge-based components, and is thus a viable alternative to data-driven methods. In addition, the consensus order of component importance within clinical subgroups provides a better molecular characterization of the subtypes.</p