Cloning and characterization of zRICH, a 2',3'-cyclic-nucleotide 3'-phosphodiesterase induced during zebrafish optic nerve regeneration

We previously reported cloning of cDNAs encoding both components of a protein doublet induced during goldfish optic nerve regeneration. The predicted protein sequences showed significant homology with the mammalian 2',3'-cyclic-nucleotide 3'-phosphodiesterases (CNPases). CNPases are well-established markers of mammalian myelin; hence, the cDNAs were designated gRICH68 and gRICH70 (for goldfish Regeneration-Induced CNPase Homologues of 68 and 70 kDa). Homologous cDNAs have now been isolated from zebrafish encoding a highly related protein, which we have termed zRICH. RNase protection assays show that zRICH mRNA is induced significantly (fivefold) in optic nerve regenerating zebrafish retinas 7 days following nerve crush. Western blots show a single band in zebrafish brain and retina extracts, with immunoreactivity increasing three-fold in regenerating retinas 21 days postcrush. Immunohistochemical analysis indicated that this increase in zRICH protein expression is localized to the retinal ganglion cell layer in regenerating retina. We have characterized and evaluated the relevance of a conserved beta-ketoacyl synthase motif in zRICH to CNPase activity by means of site-directed mutagenesis. Two residues within the motif, H334 and T336, are critical for enzymatic activity. A cysteine residue within the motif, which corresponds to a critical residue for beta-ketoacyl synthase, does not appear to participate in the phosphodiesterase activity.     

Parameters Influencing Baseline HIV-1 Genotypic Tropism Testing Related to Clinical Outcome in Patients on Maraviroc

ObjectivesWe analysed the impact of different parameters on genotypic tropism testing related to clinical outcome prediction in 108 patients on maraviroc (MVC) treatment.Methods87 RNA and 60 DNA samples were used. The viral tropism was predicted using the geno2pheno_[coreceptor] and T-CUP tools with FPR cut-offs ranging from 1%-20%. Additionally, 27 RNA and 28 DNA samples were analysed in triplicate, 43 samples with the ESTA assay and 45 with next-generation sequencing. The influence of the genotypic susceptibility score (GSS) and 16 MVC-resistance mutations on clinical outcome was also studied.ResultsConcordance between single-amplification testing compared to ESTA and to NGS was in the order of 80%. Concordance with NGS was higher at lower FPR cut-offs. Detection of baseline R5 viruses in RNA and DNA samples by all methods significantly correlated with treatment success, even with FPR cut-offs of 3.75%-7.5%. Triple amplification did not improve the prediction value but reduced the number of patients eligible for MVC. No influence of the GSS or MVC-resistance mutations but adherence to treatment, on the clinical outcome was detected.ConclusionsProviral DNA is valid to select candidates for MVC treatment. FPR cut-offs of 5%-7.5% and single amplification from RNA or DNA would assure a safe administration of MVC without excluding many patients who could benefit from this drug. In addition, the new prediction system T-CUP produced reliable results.     

Design and synthesis of long acting inhaled corticosteroids for the treatment of asthma

In this Letter we present data for a novel series of ICS for the treatment of asthma. 'Inhalation by design' principles have been applied to a series of highly potent steroidal GR agonists, with a focus on optimising the potential therapeutic index in human. Pharmacokinetic properties were tuned with high intrinsic clearance and low oral bioavailability in mind, to minimise systemic exposure and reduce systemically driven adverse events. High CYP mediated clearance as well as glucuronidation were targeted to achieve high intrinsic clearance coupled with multiple routes of clearance to minimise drug-drug interactions. Furthermore, pharmaceutical properties such as stability, crystallinity and solubility were considered to ensure compatibility with a dry powder inhaler. This work culminated in the identification of the clinical candidate 15, which demonstrates preclinically the desired efficacy and safety profiles confirming its potential as an inhaled agent for the treatment of asthma.     

Pareto Optimization Identifies Diverse Set of Phosphorylation Signatures Predicting Response to Treatment with Dasatinib

Multivariate biomarkers that can predict the effectiveness of targeted therapy in individual patients are highly desired. Previous biomarker discovery studies have largely focused on the identification of single biomarker signatures, aimed at maximizing prediction accuracy. Here, we present a different approach that identifies multiple biomarkers by simultaneously optimizing their predictive power, number of features, and proximity to the drug target in a protein-protein interaction network. To this end, we incorporated NSGA-II, a fast and elitist multi-objective optimization algorithm that is based on the principle of Pareto optimality, into the biomarker discovery workflow. The method was applied to quantitative phosphoproteome data of 19 non-small cell lung cancer (NSCLC) cell lines from a previous biomarker study. The algorithm successfully identified a total of 77 candidate biomarker signatures predicting response to treatment with dasatinib. Through filtering and similarity clustering, this set was trimmed to four final biomarker signatures, which then were validated on an independent set of breast cancer cell lines. All four candidates reached the same good prediction accuracy (83%) as the originally published biomarker. Although the newly discovered signatures were diverse in their composition and in their size, the central protein of the originally published signature — integrin β4 (ITGB4) — was also present in all four Pareto signatures, confirming its pivotal role in predicting dasatinib response in NSCLC cell lines. In summary, the method presented here allows for a robust and simultaneous identification of multiple multivariate biomarkers that are optimized for prediction performance, size, and relevance.     

Wortmannin Blocks Goldfish Retinal Phosphatidylinositol 3-Kinase and Neurite Outgrowth

The goldfish retina has been used extensively for the study of nerve regeneration. A role for phosphatidylinositol 3-kinase (PI3K) in neurite outgrowth from goldfish retinal explants has been examined by means of wortmannin (WT), a selective inhibitor of the enzyme. The presence of PI3K in retinal extracts was determined by means of immunoprecipitation as well as by an in vitro assay system for catalytic activity. The relative amount of the p85 subunit of PI3K detected by western blot in the retina following optic nerve crush was unchanged. WT inhibited goldfish brain PI3K activity at concentrations as low as 10^–9 M, approximating that reported for inhibition of mammalian PI3K's. Daily addition of 10^–8 M WT to retinal explants, activated by prior crush of the optic nerve, significantly inhibited neurite outgrowth during a 7 day in vitro culture period, while a single addition of WT to freshly explanted retina had no effect on neurite outgrowth. These results suggest that a PI3K-mediated process may be critical for nerve regrowth.     

The Effects of Vaccination and Immunity on Bacterial Infection Dynamics In Vivo

Salmonella enterica infections are a significant global health issue, and development of vaccines against these bacteria requires an improved understanding of how vaccination affects the growth and spread of the bacteria within the host. We have combined in vivo tracking of molecularly tagged bacterial subpopulations with mathematical modelling to gain a novel insight into how different classes of vaccines and branches of the immune response protect against secondary Salmonella enterica infections of the mouse. We have found that a live Salmonella vaccine significantly reduced bacteraemia during a secondary challenge and restrained inter-organ spread of the bacteria in the systemic organs. Further, fitting mechanistic models to the data indicated that live vaccine immunisation enhanced both the bacterial killing in the very early stages of the infection and bacteriostatic control over the first day post-challenge. T-cell immunity induced by this vaccine is not necessary for the enhanced bacteriostasis but is required for subsequent bactericidal clearance of Salmonella in the blood and tissues. Conversely, a non-living vaccine while able to enhance initial blood clearance and killing of virulent secondary challenge bacteria, was unable to alter the subsequent bacterial growth rate in the systemic organs, did not prevent the resurgence of extensive bacteraemia and failed to control the spread of the bacteria in the body.     

Nested Sampling for Bayesian Model Comparison in the Context of Salmonella Disease Dynamics

Understanding the mechanisms underlying the observed dynamics of complex biological systems requires the statistical assessment and comparison of multiple alternative models. Although this has traditionally been done using maximum likelihood-based methods such as Akaike''s Information Criterion (AIC), Bayesian methods have gained in popularity because they provide more informative output in the form of posterior probability distributions. However, comparison between multiple models in a Bayesian framework is made difficult by the computational cost of numerical integration over large parameter spaces. A new, efficient method for the computation of posterior probabilities has recently been proposed and applied to complex problems from the physical sciences. Here we demonstrate how nested sampling can be used for inference and model comparison in biological sciences. We present a reanalysis of data from experimental infection of mice with Salmonella enterica showing the distribution of bacteria in liver cells. In addition to confirming the main finding of the original analysis, which relied on AIC, our approach provides: (a) integration across the parameter space, (b) estimation of the posterior parameter distributions (with visualisations of parameter correlations), and (c) estimation of the posterior predictive distributions for goodness-of-fit assessments of the models. The goodness-of-fit results suggest that alternative mechanistic models and a relaxation of the quasi-stationary assumption should be considered.