GP0.4 from bacteriophage T7: in silico characterisation of its structure and interaction with E. coli FtsZ.

BackgroundProteins produced by bacteriophages can have potent antimicrobial activity. The study of phage-host interactions can therefore inform small molecule drug discovery by revealing and characterising new drug targets. Here we characterise in silico the predicted interaction of gene protein 0.4 (GP0.4) from the Escherichia coli (E. coli) phage T7 with E. coli filamenting temperature-sensitive mutant Z division protein (FtsZ). FtsZ is a tubulin homolog which plays a key role in bacterial cell division and that has been proposed as a drug target.ResultsUsing ab initio, fragment assembly structure modelling, we predicted the structure of GP0.4 with two programs. A structure similarity-based network was used to identify a U-shaped helix-turn-helix candidate fold as being favoured. ClusPro was used to dock this structure prediction to a homology model of E. coli FtsZ resulting in a favourable predicted interaction mode. Alternative docking methods supported the proposed mode which offered an immediate explanation for the anti-filamenting activity of GP0.4. Importantly, further strong support derived from a previously characterised insertion mutation, known to abolish GP0.4 activity, that is positioned in close proximity to the proposed GP0.4/FtsZ interface.ConclusionsThe mode of interaction predicted by bioinformatics techniques strongly suggests a mechanism through which GP0.4 inhibits FtsZ and further establishes the latter's druggable intrafilament interface as a potential drug target

Design of a Guarded Hot Plate for Measuring Thin Specimens of Polymer and Composite Materials

The National Physical Laboratory (NPL) has developed a new design of guarded hot plate apparatus specifically for absolute measurements on thin specimens of medium thermal conductivity materials, such as the polymer composites that are becoming more widely used in aerospace and other advanced manufacturing sectors. Although NPL has an existing measurement facility based on a commercially manufactured apparatus conforming to ASTM E1530, this current facility is not based on an absolute measurement technique and is not able to provide the low measurement uncertainty or flexibility that is increasingly being demanded by industrial users of this NPL service. The target specification for this new NPL guarded hot plate is the measurement of materials with thermal conductivity in the range 0.1–10 W·m−1·K−1 using specimens with thickness of 1–20 mm and over the temperature range −100°C to 250°C. This is achieved using a new design of guarded heater plate and a temperature-controlled environmental chamber. This chamber can be evacuated and specific gases can be introduced, enabling measurements on porous materials under a wide range of environments. It can be used in either a single specimen or a double specimen configuration, and with specimen diameters of either 75 mm or 50.8 mm that is used in many older styles of comparative measurement apparatus. During the commissioning of this new measurements facility, it is planned to investigate various approaches for reducing thermal contact resistance between the specimen and plates. This facility will then provide the flexibility for meeting a wider range of requirements from industrial customers

On the use of the Gram matrix for multivariate functional principal components analysis

Dimension reduction is crucial in functional data analysis (FDA). The key tool to reduce the dimension of the data is functional principal component analysis. Existing approaches for functional principal component analysis usually involve the diagonalization of the covariance operator. With the increasing size and complexity of functional datasets, estimating the covariance operator has become more challenging. Therefore, there is a growing need for efficient methodologies to estimate the eigencomponents. Using the duality of the space of observations and the space of functional features, we propose to use the inner-product between the curves to estimate the eigenelements of multivariate and multidimensional functional datasets. The relationship between the eigenelements of the covariance operator and those of the inner-product matrix is established. We explore the application of these methodologies in several FDA settings and provide general guidance on their usability.Comment: 23 pages, 12 figure

Modifiable factors influencing relatives’ decision to offer organ donation: systematic review

Objective To identify modifiable factors that influence relatives’ decision to allow organ donation

Helical ensembles outperform ideal helices in molecular replacement

The conventional approach in molecular replacement (MR) is the use of a related structure as a search model. However, this is not always possible as the availability of such structures can be scarce for poorly characterised families of proteins. In these cases, alternative approaches can be explored, such as the use of small ideal fragments that share high albeit local structural similarity with the unknown protein. Earlier versions of AMPLE enabled the trialling of a library of ideal helices, which worked well for largely helical proteins at suitable resolution. Here we explore the performance of libraries of helical ensembles created by clustering helical segments. The impacts of different B-factor treatments and different degrees of structural heterogeneity are explored. We observed a 30% increase in the number of solutions obtained by AMPLE when using this new set of ensembles compared to performance with ideal helices. The boost of performance was notable across three different folds: transmembrane, globular and coiled-coil structures. Furthermore, the increased effectiveness of these ensembles was coupled to a reduction of the time required by AMPLE to reach a solution. AMPLE users can now take full advantage of this new library of search models by activating the “helical ensembles” mode

Assessment of Offspring DNA Methylation across the Lifecourse Associated with Prenatal Maternal Smoking Using Bayesian Mixture Modelling

A growing body of research has implicated DNA methylation as a potential mediator of the effects of maternal smoking in pregnancy on offspring ill-health. Data were available from a UK birth cohort of children with DNA methylation measured at birth, age 7 and 17. One issue when analysing genome-wide DNA methylation data is the correlation of methylation levels between CpG sites, though this can be crudely bypassed using a data reduction method. In this manuscript we investigate the effect of sustained maternal smoking in pregnancy on longitudinal DNA methylation in their offspring using a Bayesian hierarchical mixture model. This model avoids the data reduction used in previous analyses. Four of the 28 previously identified, smoking related CpG sites were shown to have offspring methylation related to maternal smoking using this method, replicating findings in well-known smoking related genes MYO1G and GFI1. Further weak associations were found at the AHRR and CYP1A1 loci. In conclusion, we have demonstrated the utility of the Bayesian mixture model method for investigation of longitudinal DNA methylation data and this method should be considered for use in whole genome applications

Serine-arginine protein kinase 1 (SRPK1), a determinant of angiogenesis, is upregulated in prostate cancer and correlates with disease stage and invasion

Vascular endothelial growth factor (VEGF) undergoes alternative splicing to produce both proangiogenic and antiangiogenic isoforms. Preferential splicing of proangiogenic VEGF is determined by serine-arginine protein kinase 1 (SRPK1), which is upregulated in a number of cancers. In the present study, we aimed to investigate SRPK1 expression in prostate cancer (PCa) and its association with cancer progression. SRPK1 expression was assessed using immunohistochemistry of PCa tissue extracted from radical prostatectomy specimens of 110 patients. SRPK1 expression was significantly higher in tumour compared with benign tissue (p<0.00001) and correlated with higher pT stage (p=0.004), extracapsular extension (p=0.003) and extracapsular perineural invasion (p=0.008). Interestingly, the expression did not correlate with Gleason grade (p=0.21), suggesting that SRPK1 facilitates the development of a tumour microenvironment that favours growth and invasion (possibly through stimulating angiogenesis) while having little bearing on the morphology or function of the tumour cells themselves

Perioperative Levosimendan Infusion in Patients With End-Stage Heart Failure Undergoing Left Ventricular Assist Device Implantation

Left ventricular assist device (LVAD) therapy has been instrumental in saving lives of patients with end-stage heart failure (HF). Recent generation devices have short-to-mid-term survival rates close to heart transplantation. Unfortunately, up to 1 in 4 patients develop a life-threatening right-sided HF (RHF) early post LVAD implantation, with high morbidity and mortality rate, necessitating prolonged ICU stay, prolonged inotropic support, and implantation of a right-ventricular assist device. Pre-operative optimization of HF therapy could help in prevention, and/or mitigation of RHF. Levosimendan (LEVO) is a non-conventional inotropic agent that works by amplifying calcium sensitivity of troponin C in cardiac myocytes, without increasing the intra-cellular calcium or exacerbating ischemia. LEVO acts as an inodilator, which reduces the cardiac pre-, and after-load. LEVO administration is associated with hemodynamic improvements. Despite decades long of the use of LVAD and more than two decades of the use of LEVO for HF, the literature on LEVO use in LVAD is very limited. In this paper, we sought to conduct a systematic review to synthesize evidence related to the use of LEVO for the mitigation and/or prevention of RHF in patients undergoing LVAD implantation