Insights into the regulation of DMSP synthesis in the diatom Thalassiosira pseudonana through APR activity, proteomics and gene expression analyses on cells acclimating to changes in salinity, light and nitrogen

Despite the importance of dimethylsulphoniopropionate (DMSP) in the global sulphur cycle and climate regulation, the biological pathways underpinning its synthesis in marine phytoplankton remain poorly understood. The intracellular concentration of DMSP increases with increased salinity, increased light intensity and nitrogen starvation in the diatom Thalassiosira pseudonana. We used these conditions to investigate DMSP synthesis at the cellular level via analysis of enzyme activity, gene expression and proteome comparison. The activity of the key sulphur assimilatory enzyme, adenosine 5′- phosphosulphate reductase was not coordinated with increasing intracellular DMSP concentration. Under all three treatments coordination in the expression of sulphur assimilation genes was limited to increases in sulphite reductase transcripts. Similarly, proteomic 2D gel analysis only revealed an increase in phosphoenolpyruvate carboxylase following increases in DMSP concentration. Our findings suggest that increased sulphur assimilation might not be required for increased DMSP synthesis, instead the availability of carbon and nitrogen substrates may be important in the regulation of this pathway. This contrasts with the regulation of sulphur metabolism in higher plants, which generally involves upregulation of several sulphur assimilatory enzymes. In T. pseudonana changes relating to sulphur metabolism were specific to the individual treatments and, given that little coordination was seen in transcript and protein responses across the three growth conditions, different patterns of regulation might be responsible for the increase in DMSP concentration seen under each treatment

Illustrating risk difference and number needed to treat from a randomized controlled trial of spinal manipulation for cervicogenic headache

<p>Abstract</p> <p>Background</p> <p>The number needed to treat (NNT) for one participant to benefit is considered a useful, clinically meaningful way of reporting binary outcomes from randomized trials. Analysis of continuous data from our randomized controlled trial has previously demonstrated a significant and clinically important difference favoring spinal manipulation over a light massage control.</p> <p>Methods</p> <p>Eighty participants were randomized to receive spinal manipulation or a light massage control (n = 40/group). Improvements in cervicogenic headache pain (primary outcome), disability, and number in prior four weeks were dichotomized into binary outcomes at two thresholds: 30% representing minimal clinically important change and 50% representing clinical success. Groups were compared at 12 and 24-week follow-up using binomial regression (generalized linear models) to compute the adjusted risk difference (RD) between groups and number needed to treat (NNT) after adjusting for baseline differences between groups. Results were compared to logistic regression results.</p> <p>Results</p> <p>For headache pain, clinically important improvement (30% or 50%) was more likely for spinal manipulation: adjusted RD = 17% to 27% and NNT = 3.8 to 5.8 (p = .005 to .028). Some statistically significant results favoring manipulation were found for headache disability and number.</p> <p>Conclusion</p> <p>Spinal manipulation demonstrated a benefit in terms of a clinically important improvement of cervicogenic headache pain. The use of adjusted NNT is recommended; however, adjusted RD may be easier to interpret than NNT. The study demonstrated how results may depend on the threshold for dichotomizing variables into binary outcomes.</p> <p>Trial Registration</p> <p>ClinicalTrials.gov NLM identifier NCT00246350.</p

Calibrative approaches to protein solubility modeling of a mutant series using physicochemical descriptors

A set of physicochemical properties describing a protein of known structure is employed for a calibrative approach to protein solubility. Common hydrodynamic and electrophoretic properties routinely measured in the bio-analytical laboratory such as zeta potential, dipole moment, the second osmotic virial coefficient are first estimated in silico as a function a pH and solution ionic strength starting with the protein crystal structure. The utility of these descriptors in understanding the solubility of a series of ribonuclease Sa mutants is investigated. A simple two parameter model was trained using solubility data of the wild type protein measured at a restricted number of solution pHs. Solubility estimates of the mutants demonstrate that zeta potential and dipole moment may be used to rationalize solubility trends over a wide pH range. Additionally a calibrative model based on the protein’s second osmotic virial coefficient, B22 was developed. A modified DVLO type potential along with a simplified representation of the protein allowed for efficient computation of the second viral coefficient. The standard error of prediction for both models was on the order of 0.3 log S units. These results are very encouraging and demonstrate that these models may be trained with a small number of samples and employed extrapolatively for estimating mutant solubilities

Varicella zoster virus infection of highly pure terminally differentiated human neurons

In vitro analyses of varicella zoster virus (VZV) reactivation from latency in human ganglia have been hampered by the inability to isolate virus by explantation or cocultivation techniques. Furthermore, attempts to study interaction of VZV with neurons in experimentally infected ganglion cells in vitro have been impaired by the presence of nonneuronal cells, which become productively infected and destroy the cultures. We have developed an in vitro model of VZV infection in which highly pure (>95 %) terminally differentiated human neurons derived from pluripotent stem cells were infected with VZV. At 2 weeks post-infection, infected neurons appeared healthy compared to VZV-infected human fetal lung fibroblasts (HFLs), which developed a cytopathic effect (CPE) within 1 week. Tissue culture medium from VZV-infected neurons did not produce a CPE in uninfected HFLs and did not contain PCR-amplifiable VZV DNA, but cocultivation of infected neurons with uninfected HFLs did produce a CPE. The nonproductively infected neurons contained multiple regions of the VZV genome, as well as transcripts and proteins corresponding to VZV immediate-early, early, and late genes. No markers of the apoptotic caspase cascade were detected in healthy-appearing VZV-infected neurons. VZV infection of highly pure terminally differentiated human neurons provides a unique in vitro system to study the VZV-neuronal relationship and the potential to investigate mechanisms of VZV reactivation

Adaptive remodeling of the bacterial proteome by specific ribosomal modification regulates Pseudomonas infection and niche colonisation

Post-transcriptional control of protein abundance is a highly important, underexplored regulatory process by which organisms respond to their environments. Here we describe an important and previously unidentified regulatory pathway involving the ribosomal modification protein RimK, its regulator proteins RimA and RimB, and the widespread bacterial second messenger cyclic-di-GMP (cdG). Disruption of rimK affects motility and surface attachment in pathogenic and commensal Pseudomonas species, with rimK deletion significantly compromising rhizosphere colonisation by the commensal soil bacterium P. fluorescens, and plant infection by the pathogens P. syringae and P. aeruginosa. RimK functions as an ATP-dependent glutamyl ligase, adding glutamate residues to the C-terminus of ribosomal protein RpsF and inducing specific effects on both ribosome protein complement and function. Deletion of rimK in P. fluorescens leads to markedly reduced levels of multiple ribosomal proteins, and also of the key translational regulator Hfq. In turn, reduced Hfq levels induce specific downstream proteomic changes, with significant increases in multiple ABC transporters, stress response proteins and non-ribosomal peptide synthetases seen for both ΔrimK and Δhfq mutants. The activity of RimK is itself controlled by interactions with RimA, RimB and cdG. We propose that control of RimK activity represents a novel regulatory mechanism that dynamically influences interactions between bacteria and their hosts; translating environmental pressures into dynamic ribosomal changes, and consequently to an adaptive remodeling of the bacterial proteome

CodingQuarry: Highly accurate hidden Markov model gene prediction in fungal genomes using RNA-seq transcripts

Background: The impact of gene annotation quality on functional and comparative genomics makes gene prediction an important process, particularly in non-model species, including many fungi. Sets of homologous protein sequences are rarely complete with respect to the fungal species of interest and are often small or unreliable, especially when closely related species have not been sequenced or annotated in detail. In these cases, protein homology-based evidence fails to correctly annotate many genes, or significantly improve ab initio predictions. Generalised hidden Markov models (GHMM) have proven to be invaluable tools in gene annotation and, recently, RNA-seq has emerged as a cost-effective means to significantly improve the quality of automated gene annotation. As these methods do not require sets of homologous proteins, improving gene prediction from these resources is of benefit to fungal researchers. While many pipelines now incorporate RNA-seq data in training GHMMs, there has been relatively little investigation into additionally combining RNA-seq data at the point of prediction, and room for improvement in this area motivates this study. Results: CodingQuarry is a highly accurate, self-training GHMM fungal gene predictor designed to work with assembled, aligned RNA-seq transcripts. RNA-seq data informs annotations both during gene-model training and in prediction. Our approach capitalises on the high quality of fungal transcript assemblies by incorporating predictions made directly from transcript sequences. Correct predictions are made despite transcript assembly problems, including those caused by overlap between the transcripts of adjacent gene loci. Stringent benchmarking against high-confidence annotation subsets showed CodingQuarry predicted 91.3% of Schizosaccharomyces pombe genes and 90.4% of Saccharomyces cerevisiae genes perfectly. These results are 4-5% better than those of AUGUSTUS, the next best performing RNA-seq driven gene predictor tested. Comparisons against whole genome Sc. pombe and S. cerevisiae annotations further substantiate a 4-5% improvement in the number of correctly predicted genes. Conclusions: We demonstrate the success of a novel method of incorporating RNA-seq data into GHMM fungal gene prediction. This shows that a high quality annotation can be achieved without relying on protein homology or a training set of genes. CodingQuarry is freely available (https://sourceforge.net/projects/codingquarry/), and suitable for incorporation into genome annotation pipelines

Interactive Actor Analysis for Rural Water Management in The Netherlands

Recent developments in the policy sciences emphasize the social environment in which decisions are made. The ‘network metaphor’ is often used to describe the key role of interactions between interdependent actors involved in decision making. These interactions take place in a policy arena drawn up by actors with an interest in and control over decisions on the issues addressed. Interdependencies, caused by the need for actors to increase their means of realizing objectives, are the driving force behind these interactions. Dependency relations are of special interest to water management and river basin management because of the fundamental asymmetrical interdependencies that exist in river basins between upstream and downstream stakeholders. Coleman’s linear system of action models decision making process involving dependencies between multiple stakeholders as exchange of control over issues, while interactions are required to negotiate exchanges of control. We developed an interactive method for actor analysis based on Coleman’s linear system of action and applied it to the national rural water management policy domain in The Netherlands. The method is firmly rooted in mathematical sociology and defies the criticism that methods for actor and stakeholder analysis do not specify a theoretical basis explaining the causal relations between the variables analyzed and policy change. With the application to the rural water management policy arena we intended to increase our insight into the practical applicability of this analyticmethod in an interactive workshop, the acceptability of the approach for the participating actors, its contribution to the process of decision making and our understanding of the rural water management policy arena in The Netherlands. We found that the Association of Water Authorities, the Ministry of Public Works and the Ministry of Agriculture are the most powerful actor in the policy domain, while governance and cost and benefits of rural water management are the most salient issues. Progress in policy development for rural water management is probably most promising for the issues governance, costs and benefits, safety and rural living conditions through improved interaction between the Association of Water Authorities, the Ministry of Agriculture and the Rural Credit Bank. Besides these analytic results the interactive approach implemented increased the participants understanding of their dependency on other actors in the rural water management policy domain and supported them in developing a sound perspective on their dependency position. We concluded that the method developed is acceptable to real-world policy decision makers, can successfully be applied in an interactive setting, potentially contributes to the process of decision making by increasing the participants understanding of their dependency position, has the potential to delivers valuable advice for future decision-making and increases our understanding of policy development for rural water management in general