Structure,Dynamics, and Substrate Specificity of the OprO Porin from Pseudomonas aeruginosa

The outer membrane (OM) of Gram-negative bacteria functions as a selective permeability barrier between cell and environment. For nutrient acquisition, the OM contains a number of channels that mediate uptake of small molecules by diffusion. Many of these channels are specific, i.e., they prefer certain substrates over others. In electrophysiological experiments, the OM channels OprP and OprO from Pseudomonas aeruginosa show a specificity for phosphate and diphosphate, respectively. In this study we use x-ray crystallography, free-energy molecular dynamics (MD) simulations, and electrophysiology to uncover the atomic basis for the different substrate specificity of these highly similar channels. A structural analysis of OprP and OprO revealed two crucial differences in the central constriction region. In OprP there are two tyrosine residues, Y62 and Y114, whereas the corresponding residues in OprO are phenylalanine F62 and aspartate D114. To probe the importance of these two residues in generating the different substrate specificities, the double mutants were generated in silico and in vitro. Applied-field MD simulations and electrophysiological experiments demonstrated that the double mutations interchange the phosphate and diphosphate specificities of OprP and OprO. Our findings outline a possible strategy to rationally design channel specificity by modification of a small number of residues that may be applicable to other pores as well.     

Disease-Dependent Local IL-10 Production Ameliorates Collagen Induced Arthritis in Mice

Rheumatoid arthritis (RA) is a chronic destructive autoimmune disease characterised by periods of flare and remission. Today’s treatment is based on continuous immunosuppression irrespective of the patient’s inflammatory status. When the disease is in remission the therapy is withdrawn but withdrawal attempts often results in inflammatory flares, and re-start of the therapy is commenced when the inflammation again is prominent which leads both to suffering and increased risk of tissue destruction. An attractive alternative treatment would provide a disease-regulated therapy that offers increased anti-inflammatory effect during flares and is inactive during periods of remission. To explore this concept we expressed the immunoregulatory cytokine interleukin (IL)-10 gene under the control of an inflammation dependent promoter in a mouse model of RA - collagen type II (CII) induced arthritis (CIA). Haematopoetic stem cells (HSCs) were transduced with lentiviral particles encoding the IL-10 gene (LNT-IL-10), or a green fluorescence protein (GFP) as control gene (LNT-GFP), driven by the inflammation-dependent IL-1/IL-6 promoter. Twelve weeks after transplantation of transduced HSCs into DBA/1 mice, CIA was induced. We found that LNT-IL-10 mice developed a reduced severity of arthritis compared to controls. The LNT-IL-10 mice exhibited both increased mRNA expression levels of IL-10 as well as increased amount of IL-10 produced by B cells and non-B APCs locally in the lymph nodes compared to controls. These findings were accompanied by increased mRNA expression of the IL-10 induced suppressor of cytokine signalling 1 (SOCS1) in lymph nodes and a decrease in the serum protein levels of IL-6. We also found a decrease in both frequency and number of B cells and serum levels of anti-CII antibodies. Thus, inflammation-dependent IL-10 therapy suppresses experimental autoimmune arthritis and is a promising candidate in the development of novel treatments for RA.     

QTL fine mapping with Bayes C(π): a simulation study

Background

Accurate QTL mapping is a prerequisite in the search for causative mutations. Bayesian genomic selection models that analyse many markers simultaneously should provide more accurate QTL detection results than single-marker models. Our objectives were to (a) evaluate by simulation the influence of heritability, number of QTL and number of records on the accuracy of QTL mapping with Bayes Cπ and Bayes C; (b) estimate the QTL status (homozygous vs. heterozygous) of the individuals analysed. This study focussed on the ten largest detected QTL, assuming they are candidates for further characterization.

Methods

Our simulations were based on a true dairy cattle population genotyped for 38 277 phased markers. Some of these markers were considered biallelic QTL and used to generate corresponding phenotypes. Different numbers of records (4387 and 1500), heritability values (0.1, 0.4 and 0.7) and numbers of QTL (10, 100 and 1000) were studied. QTL detection was based on the posterior inclusion probability for individual markers, or on the sum of the posterior inclusion probabilities for consecutive markers, estimated using Bayes C or Bayes Cπ. The QTL status of the individuals was derived from the contrast between the sums of the SNP allelic effects of their chromosomal segments.

Results

The proportion of markers with null effect (π) frequently did not reach convergence, leading to poor results for Bayes Cπ in QTL detection. Fixing π led to better results. Detection of the largest QTL was most accurate for medium to high heritability, for low to moderate numbers of QTL, and with a large number of records. The QTL status was accurately inferred when the distribution of the contrast between chromosomal segment effects was bimodal.

Conclusions

QTL detection is feasible with Bayes C. For QTL detection, it is recommended to use a large dataset and to focus on highly heritable traits and on the largest QTL. QTL statuses were inferred based on the distribution of the contrast between chromosomal segment effects.     

Craniosynostosis and low middle frequency perceptive deafness in mother and son. A distinct entity?

A distinct entity?: In this report we describe the hitherto unreported association of low and middle frequency perceptive deafness and craniosynostosis in mother and son. The occurrence of hearing loss in the craniosynostosis syndromes is briefly reviewed.     

Until death do us part? In-depth insights into Dutch consumers’ considerations about product lifetimes and lifetime extension

Long-lasting electronic products contribute to a sustainable society; however, both expected and actual lifetimes are in decline. This research provides in-depth insights into consumers’ considerations about product lifetimes, barriers to extending lifetimes, and responses to a product lifetime label. Results of interviews (n = 22) with Dutch consumers suggest a positive view on long-lasting products. Nevertheless, their products’ value depreciated during their lifetimes. Consumers consider themselves unable to estimate how long products should last, which can be detrimental as low expectations tend to negatively influence actual lifetimes. Also, use intensity and consumers’ care(less) behavior influence the lifetime. To extend product lifetimes, consumers often disregard the option of repairing malfunctioning products. They have limited knowledge and ability, and believe repair provides poor value for money. Lifetime extension can also be hindered by market-related factors, such as convenient replacement services, new technological developments, and (attractive) deals. We suggest a product lifetime label should contain relevant and reliable information; furthermore, we recommend including (extended) warranty information. When information about repairability is included, potential negative responses should be considered. Finally, raising awareness about the environmental impact of short-lived products via a label may have a positive effect but requires more research attention.     

Wolbachia Reduces the Transmission Potential of Dengue-Infected Aedes aegypti

BackgroundDengue viruses (DENV) are the causative agents of dengue, the world’s most prevalent arthropod-borne disease with around 40% of the world’s population at risk of infection annually. Wolbachia pipientis, an obligate intracellular bacterium, is being developed as a biocontrol strategy against dengue because it limits replication of the virus in the mosquito. The Wolbachia strain wMel, which has been introduced into the mosquito vector, Aedes aegypti, has been shown to invade and spread to near fixation in field releases. Standard measures of Wolbachia’s efficacy for blocking virus replication focus on the detection and quantification of virus in mosquito tissues. Examining the saliva provides a more accurate measure of transmission potential and can reveal the extrinsic incubation period (EIP), that is, the time it takes virus to arrive in the saliva following the consumption of DENV viremic blood. EIP is a key determinant of a mosquito’s ability to transmit DENVs, as the earlier the virus appears in the saliva the more opportunities the mosquito will have to infect humans on subsequent bites.Conclusions/SignificanceThe saliva-based traits reported here offer more disease-relevant measures of Wolbachia’s effects on the vector and the virus. The lengthening of EIP highlights another means, in addition to the reduction of infection frequencies and DENV titers in mosquitoes, by which Wolbachia should operate to reduce DENV transmission in the field.     

Early detection surveillance for an emerging plant pathogen: a rule of thumb to predict prevalence at first discovery

Emerging plant pathogens are a significant problem for conservation and food security. Surveillance is often instigated in an attempt to detect an invading epidemic before it gets out of control. Yet in practice many epidemics are not discovered until already at a high prevalence, partly due to a lack of quantitative understanding of how surveillance effort and the dynamics of an invading epidemic relate. We test a simple rule of thumb to determine, for a surveillance programme taking a fixed number of samples at regular intervals, the distribution of the prevalence an epidemic will have reached on first discovery (discovery-prevalence) and its expectation E(q*). We show that E(q*) = r/(N/Δ), i.e. simply the rate of epidemic growth divided by the rate of sampling; where r is the epidemic growth rate, N is the sample size and Δ is the time between sampling rounds. We demonstrate the robustness of this rule of thumb using spatio-temporal epidemic models as well as data from real epidemics. Our work supports the view that, for the purposes of early detection surveillance, simple models can provide useful insights in apparently complex systems. The insight can inform decisions on surveillance resource allocation in plant health and has potential applicability to invasive species generally.