COPASAAR – A database for proteomic analysis of single amino acid repeats

BACKGROUND: Single amino acid repeats make up a significant proportion in all of the proteomes that have currently been determined. They have been shown to be functionally and medically significant, and are associated with cancers and neuro-degenerative diseases such as Huntington's Chorea, where a poly-glutamine repeat is responsible for causing the disease. The COPASAAR database is a new tool to facilitate the rapid analysis of single amino acid repeats at a proteome level. The database aims to simplify the comparison of repeat distributions between proteomes in order to provide a better understanding of their function and evolution. RESULTS: A comparative analysis of all proteomes in the database (currently 244) shows that single amino acid repeats account for about 12–14% of the proteome of any given species. They are more common in eukaryotes (14%) than in either archaea or bacteria (both 13%). Individual analyses of proteomes show that long single amino acid repeats (6+ residues) are much more common in the Eukaryotes and that longer repeats are usually made up of hydrophilic amino acids such as glutamine, glutamic acid, asparagine, aspartic acid and serine. CONCLUSION: COPASAAR is a useful tool for comparative proteomics that provides rapid access to amino acid repeat data that can be readily data-mined. The COPASAAR database can be queried at the kingdom, proteome or individual protein level. As the amount of available proteome data increases this will be increasingly important in order to automate proteome comparison. The insights gained from these studies will give a better insight into the evolution of protein sequence and function

Preliminary X-ray analysis of a new crystal form of the vanadium-dependent bromoperoxidase from Corallina officinalis.

Journal ArticleResearch Support, Non-U.S. Gov'tA new crystal form of the vanadium-dependent bromoperoxidase from Corallina officinalis has been obtained. The crystals exhibit a 'teardrop' morphology and are grown from 2 M ammonium dihydrogen phosphate pH and diffract to beyond 1.7 A resolution. They are in tetragonal space group P4222 with unit-cell dimensions of a = b = 201.9, c = 178.19 A, alpha = beta = gamma = 90 degrees. A 2.3 A resolution native data set has been collected at the Hamburg Synchrotron. A mercury derivative data set has also been collected, and the heavy-atom positions have been determined. The self-rotation function and the positions of the heavy atoms are consistent with the molecule being a dodecamer with local 23 symmetry.Biotechnology and Biological Research Council

Structure of a phosphoglycerate mutase:3-phosphoglyceric acid complex at 1.7 A.

Journal ArticleResearch Support, Non-U.S. Gov'tThe crystal structure of the tetrameric glycolytic enzyme phosphoglycerate mutase from the yeast Saccharomyces cerevisiae has been determined to 1.7 A resolution in complex with the sugar substrate. The difference map indicates that 3-phosphoglycerate is bound at the base of a 12 A cleft, positioning C2 of the substrate within 3.5 A of the primary catalytic residue, histidine 8.BBSR

RNA Recognition by the DNA End-Binding Ku Heterodimer

Most nucleic acid-binding proteins selectively bind either DNA or RNA, but not both nucleic acids. The Saccharomyces cerevisiae Ku heterodimer is unusual in that it has two very different biologically relevant binding modes: (1) Ku is a sequence-nonspecific double-stranded DNA end-binding protein with prominent roles in nonhomologous end-joining and telomeric capping, and (2) Ku associates with a specific stem–loop of TLC1, the RNA subunit of budding yeast telomerase, and is necessary for proper nuclear localization of this ribonucleoprotein enzyme. TLC1 RNA-binding and dsDNA-binding are mutually exclusive, so they may be mediated by the same site on Ku. Although dsDNA binding by Ku is well studied, much less is known about what features of an RNA hairpin enable specific recognition by Ku. To address this question, we localized the Ku-binding site of the TLC1 hairpin with single-nucleotide resolution using phosphorothioate footprinting, used chemical modification to identify an unpredicted motif within the hairpin secondary structure, and carried out mutagenesis of the stem–loop to ascertain the critical elements within the RNA that permit Ku binding. Finally, we provide evidence that the Ku-binding site is present in additional budding yeast telomerase RNAs and discuss the possibility that RNA binding is a conserved function of the Ku heterodimer

Elucidation of critical pH-dependent structural changes in Botulinum Neurotoxin E

Botulinum Neurotoxins (BoNT) are the most potent toxins currently known. However, they also have therapeutic applications for an increasing number of motor related conditions due to their specificity, and low diffusion into the system. Although the start- and end- points for the BoNT mechanism of action are well-studied, a critical step remains poorly understood. It is theorised that BoNTs undergo a pH-triggered conformational shift, activating the neurotoxin by priming it to form a transmembrane (TM) channel. To test this hypothesis, we combined molecular dynamic (MD) simulations and small-angle x-ray scattering (SAXS), revealing a new conformation of BoNT/E. This conformation was exclusively observed in simulations below pH 5.5, as determined by principal component analysis (PCA), and its theoretical SAXS profile matched an experimental SAXS profile obtained at pH 4. Additionally, a localised secondary structural change was observed in MD simulations below pH 5.5, in a region previously identified as instrumental for membrane insertion for BoNT/A. These changes were found at a critical pH value for BoNTs in vivo, and may be relevant for their therapeutic use

Novel statistical approaches for non-normal censored immunological data: analysis of cytokine and gene expression data

Background: For several immune-mediated diseases, immunological analysis will become more complex in the future with datasets in which cytokine and gene expression data play a major role. These data have certain characteristics that require sophisticated statistical analysis such as strategies for non-normal distribution and censoring. Additionally, complex and multiple immunological relationships need to be adjusted for potential confounding and interaction effects. Objective: We aimed to introduce and apply different methods for statistical analysis of non-normal censored cytokine and gene expression data. Furthermore, we assessed the performance and accuracy of a novel regression approach in order to allow adjusting for covariates and potential confounding. Methods: For non-normally distributed censored data traditional means such as the Kaplan-Meier method or the generalized Wilcoxon test are described. In order to adjust for covariates the novel approach named Tobit regression on ranks was introduced. Its performance and accuracy for analysis of non-normal censored cytokine/gene expression data was evaluated by a simulation study and a statistical experiment applying permutation and bootstrapping. Results: If adjustment for covariates is not necessary traditional statistical methods are adequate for non-normal censored data. Comparable with these and appropriate if additional adjustment is required, Tobit regression on ranks is a valid method. Its power, type-I error rate and accuracy were comparable to the classical Tobit regression. Conclusion: Non-normally distributed censored immunological data require appropriate statistical methods. Tobit regression on ranks meets these requirements and can be used for adjustment for covariates and potential confounding in large and complex immunological datasets

Sandbox university: Estimating influence of institutional action

The approach presented in this article represents a generalizable and adaptable methodology for identifying complex interactions in educational systems and for investigating how manipulation of these systems may affect educational outcomes of interest. Multilayer Minimum Spanning Tree and Monte-Carlo methods are used. A virtual Sandbox University is created in order to facilitate effective identification of successful and stable initiatives within higher education, which can affect students' credits and student retention - something that has been lacking up until now. The results highlight the importance of teacher feedback and teacher-student rapport, which is congruent with current educational findings, illustrating the methodology's potential to provide a new basis for further empirical studies of issues in higher education from a complex systems perspective

Mathematical modelling of polyamine metabolism in bloodstream-form trypanosoma brucei: An application to drug target identification

© 2013 Gu et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are creditedThis article has been made available through the Brunel Open Access Publishing Fund.We present the first computational kinetic model of polyamine metabolism in bloodstream-form Trypanosoma brucei, the causative agent of human African trypanosomiasis. We systematically extracted the polyamine pathway from the complete metabolic network while still maintaining the predictive capability of the pathway. The kinetic model is constructed on the basis of information gleaned from the experimental biology literature and defined as a set of ordinary differential equations. We applied Michaelis-Menten kinetics featuring regulatory factors to describe enzymatic activities that are well defined. Uncharacterised enzyme kinetics were approximated and justified with available physiological properties of the system. Optimisation-based dynamic simulations were performed to train the model with experimental data and inconsistent predictions prompted an iterative procedure of model refinement. Good agreement between simulation results and measured data reported in various experimental conditions shows that the model has good applicability in spite of there being gaps in the required data. With this kinetic model, the relative importance of the individual pathway enzymes was assessed. We observed that, at low-to-moderate levels of inhibition, enzymes catalysing reactions of de novo AdoMet (MAT) and ornithine production (OrnPt) have more efficient inhibitory effect on total trypanothione content in comparison to other enzymes in the pathway. In our model, prozyme and TSHSyn (the production catalyst of total trypanothione) were also found to exhibit potent control on total trypanothione content but only when they were strongly inhibited. Different chemotherapeutic strategies against T. brucei were investigated using this model and interruption of polyamine synthesis via joint inhibition of MAT or OrnPt together with other polyamine enzymes was identified as an optimal therapeutic strategy.The work was carried out under a PhD programme partly funded by Prof. Ray Welland, School of Computing Science, University of Glasgo

Locating mathematics within post-16 vocational education in England

The political importance of mathematics in post-16 education is clear. Far less clear is how mathematics does and should relate to vocational education. Successive mathematics curricula (e.g. core skills, key skills) have been developed in England with vocational learners in mind. Meanwhile, general mathematics qualifications remain largely disconnected from vocational learning. Following a brief historical survey of mathematics within vocational education, the paper presents findings from a nested case study of student groups in three large Further Education colleges in England. The primary unit of analysis herein is student groups learning Functional Mathematics in two vocational areas: construction and hairdressing. We show how approaches to organising teaching, developing connected curricula and classroom pedagogy tend to isolate or integrate mathematics from/with the vocational experience. Integrated approaches are shown to impact positively on student engagement and attitudes to learning mathematics. The paper concludes by discussing the potential impact of academic qualifications displacing vocationally relevant mathematics

Analysis of gene expression data from non-small celllung carcinoma cell lines reveals distinct sub-classesfrom those identified at the phenotype level

Microarray data from cell lines of Non-Small Cell Lung Carcinoma (NSCLC) can be used to look for differences in gene expression between the cell lines derived from different tumour samples, and to investigate if these differences can be used to cluster the cell lines into distinct groups. Dividing the cell lines into classes can help to improve diagnosis and the development of screens for new drug candidates. The micro-array data is first subjected to quality control analysis and then subsequently normalised using three alternate methods to reduce the chances of differences being artefacts resulting from the normalisation process. The final clustering into sub-classes was carried out in a conservative manner such that subclasses were consistent across all three normalisation methods. If there is structure in the cell line population it was expected that this would agree with histological classifications, but this was not found to be the case. To check the biological consistency of the sub-classes the set of most strongly differentially expressed genes was be identified for each pair of clusters to check if the genes that most strongly define sub-classes have biological functions consistent with NSCLC