Sensitivity of feature-based analysis methods of storm tracks to the form of background field removal

For the tracking of extrema associated with weather systems to be applied to a broad range of fields it is necessary to remove a background field that represents the slowly varying, large spatial scales. The sensitivity of the tracking analysis to the form of background field removed is explored for the Northern Hemisphere winter storm tracks for three contrasting fields from an integration of the U. K. Met Office's (UKMO) Hadley Centre Climate Model (HadAM3). Several methods are explored for the removal of a background field from the simple subtraction of the climatology, to the more sophisticated removal of the planetary scales. Two temporal filters are also considered in the form of a 2-6-day Lanczos filter and a 20-day high-pass Fourier filter. The analysis indicates that the simple subtraction of the climatology tends to change the nature of the systems to the extent that there is a redistribution of the systems relative to the climatological background resulting in very similar statistical distributions for both positive and negative anomalies. The optimal planetary wave filter removes total wavenumbers less than or equal to a number in the range 5-7, resulting in distributions more easily related to particular types of weather system. For the temporal filters the 2-6-day bandpass filter is found to have a detrimental impact on the individual weather systems, resulting in the storm tracks having a weak waveguide type of behavior. The 20-day high-pass temporal filter is less aggressive than the 2-6-day filter and produces results falling between those of the climatological and 2-6-day filters.

No impact of malaria infection or immunisation on the expression of the immune GTPase GIMAP1 at the protein or mRNA levels (Article no. 53)

GIMAP (GTPase of the immunity-associated protein family) proteins are a family of putative GTPases believed to be regulators of cell death in lymphomyeloid cells. GIMAP1 was the first reported member of this gene family, identified as a gene up-regulated at the RNA level in the spleens of mice infected with the malarial parasite, Plasmodium chabaudi. Methods A monoclonal antibody against mouse GIMAP1 was developed and was used to analyse the expression of the endogenous protein in tissues of normal mice and in defined sub-populations of cells prepared from lymphoid tissues using flow cytometry. It was also used to assess the expression of GIMAP1 protein after infection and/or immunization of mice with P. chabaudi. Real-time PCR analysis was employed to measure the expression of GIMAP1 for comparison with the protein level analysis. Results GIMAP1 protein expression was detected in all lineages of lymphocytes (T, B, NK), in F4/80+ splenic macrophages and in some lymphoid cell lines. Additional evidence is presented suggesting that the strong expression by mature B cells of GIMAP1 and other GIMAP genes and proteins seen in mice may be a species-dependent characteristic. Unexpectedly, no increase was found in the expression of GIMAP1 in P. chabaudi infected mice at either the mRNA or protein level, and this remained so despite applying a number of variations to the protocol. Conclusion The model of up-regulation of GIMAP1 in response to infection/immunization with P. chabaudi is not a robustly reproducible experimental system. The GIMAP1 protein is widely expressed in lymphoid cells, with an interesting increase in expression in the later stages of B cell development. Alternative approaches will be required to define the functional role of this GTPase in immune cells.

Proteomic analysis of redox- and ErbB2-dependent changes in mammary luminal epithelial cells using cysteine- and lysine-labelling two-dimensional difference gel electrophoresis

Differential protein expression analysis based on modification of selected amino acids with labelling reagents has become the major method of choice for quantitative proteomics. One such methodology, two-dimensional difference gel electrophoresis (2-D DIGE), uses a matched set of fluorescent N-hydroxysuccinimidyl (NHS) ester cyanine dyes to label lysine residues in different samples which can be run simultaneously on the same gels. Here we report the use of iodoacetylated cyanine (ICy) dyes (for labelling of cysteine thiols, for 2-D DIGE-based redox proteomics. Characterisation of ICy dye labelling in relation to its stoichiometry, sensitivity and specificity is described, as well as comparison of ICy dye with NHS-Cy dye labelling and several protein staining methods. We have optimised conditions for labelling of nonreduced, denatured samples and report increased sensitivity for a subset of thiol-containing proteins, allowing accurate monitoring of redox-dependent thiol modifications and expression changes. Cysteine labelling was then combined with lysine labelling in a multiplex 2-D DIGE proteomic study of redox-dependent and ErbB2-dependent changes in epithelial cells exposed to oxidative stress. This study identifies differentially modified proteins involved in cellular redox regulation, protein folding, proliferative suppression, glycolysis and cytoskeletal organisation, revealing the complexity of the response to oxidative stress and the impact that overexpression of ErbB2 has on this response.

Proteomic analysis of redox- and ErbB2-dependent changes in mammary luminal epithelial cells using cysteine- and lysine-labelling two-dimensional difference gel electrophoresis

Differential protein expression analysis based on modification of selected amino acids with labelling reagents has become the major method of choice for quantitative proteomics. One such methodology, two-dimensional difference gel electrophoresis (2-D DIGE), uses a matched set of fluorescent N-hydroxysuccinimidyl (NHS) ester cyanine dyes to label lysine residues in different samples which can be run simultaneously on the same gels. Here we report the use of iodoacetylated cyanine (ICy) dyes (for labelling of cysteine thiols, for 2-D DIGE-based redox proteomics. Characterisation of ICy dye labelling in relation to its stoichiometry, sensitivity and specificity is described, as well as comparison of ICy dye with NHS-Cy dye labelling and several protein staining methods. We have optimised conditions for labelling of nonreduced, denatured samples and report increased sensitivity for a subset of thiol-containing proteins, allowing accurate monitoring of redox-dependent thiol modifications and expression changes, Cysteine labelling was then combined with lysine labelling in a multiplex 2-D DIGE proteomic study of redox-dependent and ErbB2-dependent changes in epithelial cells exposed to oxidative stress. This study identifies differentially modified proteins involved in cellular redox regulation, protein folding, proliferative suppression, glycolysis and cytoskeletal organisation, revealing the complexity of the response to oxidative stress and the impact that overexpression of ErbB2 has on this response.

Evaluation of peak-picking algorithms for protein mass spectrometry

Peak picking is an early key step in MS data analysis. We compare three commonly used approaches to peak picking and discuss their merits by means of statistical analysis. Methods investigated encompass signal-to-noise ratio, continuous wavelet transform, and a correlation-based approach using a Gaussian template. Functionality of the three methods is illustrated and discussed in a practical context using a mass spectral data set created with MALDI-TOF technology. Sensitivity and specificity are investigated using a manually defined reference set of peaks. As an additional criterion, the robustness of the three methods is assessed by a perturbation analysis and illustrated using ROC curves.

What are the baselines for protein fold recognition?

What constitutes a baseline level of success for protein fold recognition methods? As fold recognition benchmarks are often presented without any thought to the results that might be expected from a purely random set of predictions, an analysis of fold recognition baselines is long overdue. Given varying amounts of basic information about a protein—ranging from the length of the sequence to a knowledge of its secondary structure—to what extent can the fold be determined by intelligent guesswork? Can simple methods that make use of secondary structure information assign folds more accurately than purely random methods and could these methods be used to construct viable hierarchical classifications?

FunFOLDQA: a quality assessment tool for protein-ligand binding site residue predictions

The estimation of prediction quality is important because without quality measures, it is difficult to determine the usefulness of a prediction. Currently, methods for ligand binding site residue predictions are assessed in the function prediction category of the biennial Critical Assessment of Techniques for Protein Structure Prediction (CASP) experiment, utilizing the Matthews Correlation Coefficient (MCC) and Binding-site Distance Test (BDT) metrics. However, the assessment of ligand binding site predictions using such metrics requires the availability of solved structures with bound ligands. Thus, we have developed a ligand binding site quality assessment tool, FunFOLDQA, which utilizes protein feature analysis to predict ligand binding site quality prior to the experimental solution of the protein structures and their ligand interactions. The FunFOLDQA feature scores were combined using: simple linear combinations, multiple linear regression and a neural network. The neural network produced significantly better results for correlations to both the MCC and BDT scores, according to Kendall’s τ, Spearman’s ρ and Pearson’s r correlation coefficients, when tested on both the CASP8 and CASP9 datasets. The neural network also produced the largest Area Under the Curve score (AUC) when Receiver Operator Characteristic (ROC) analysis was undertaken for the CASP8 dataset. Furthermore, the FunFOLDQA algorithm incorporating the neural network, is shown to add value to FunFOLD, when both methods are employed in combination. This results in a statistically significant improvement over all of the best server methods, the FunFOLD method (6.43%), and one of the top manual groups (FN293) tested on the CASP8 dataset. The FunFOLDQA method was also found to be competitive with the top server methods when tested on the CASP9 dataset. To the best of our knowledge, FunFOLDQA is the first attempt to develop a method that can be used to assess ligand binding site prediction quality, in the absence of experimental data.

Towards data warehousing and mining of protein unfolding simulation data

OBJECTIVES: The prediction of protein structure and the precise understanding of protein folding and unfolding processes remains one of the greatest challenges in structural biology and bioinformatics. Computer simulations based on molecular dynamics (MD) are at the forefront of the effort to gain a deeper understanding of these complex processes. Currently, these MD simulations are usually on the order of tens of nanoseconds, generate a large amount of conformational data and are computationally expensive. More and more groups run such simulations and generate a myriad of data, which raises new challenges in managing and analyzing these data. Because the vast range of proteins researchers want to study and simulate, the computational effort needed to generate data, the large data volumes involved, and the different types of analyses scientists need to perform, it is desirable to provide a public repository allowing researchers to pool and share protein unfolding data. METHODS: To adequately organize, manage, and analyze the data generated by unfolding simulation studies, we designed a data warehouse system that is embedded in a grid environment to facilitate the seamless sharing of available computer resources and thus enable many groups to share complex molecular dynamics simulations on a more regular basis. RESULTS: To gain insight into the conformational fluctuations and stability of the monomeric forms of the amyloidogenic protein transthyretin (TTR), molecular dynamics unfolding simulations of the monomer of human TTR have been conducted. Trajectory data and meta-data of the wild-type (WT) protein and the highly amyloidogenic variant L55P-TTR represent the test case for the data warehouse. CONCLUSIONS: Web and grid services, especially pre-defined data mining services that can run on or 'near' the data repository of the data warehouse, are likely to play a pivotal role in the analysis of molecular dynamics unfolding data.

The Gly482Ser genotype at the PPARGC1A gene and elevated blood pressure: a meta-analysis involving 13,949 individuals.

The protein encoded by the PPARGC1A gene is expressed at high levels in metabolically active tissues and is involved in the control of oxidative stress via reactive oxygen species detoxification. Several recent reports suggest that the PPARGC1A Gly482Ser (rs8192678) missense polymorphism may relate inversely with blood pressure. We used conventional meta-analysis methods to assess the association between Gly482Ser and systolic (SBP) or diastolic blood pressures (DBP) or hypertension in 13,949 individuals from 17 studies, of which 6,042 were previously unpublished observations. The studies comprised cohorts of white European, Asian, and American Indian adults, and adolescents from South America. Stratified analyses were conducted to control for population stratification. Pooled genotype frequencies were 0.47 (Gly482Gly), 0.42 (Gly482Ser), and 0.11 (Ser482Ser). We found no evidence of association between Gly482Ser and SBP [Gly482Gly: mean = 131.0 mmHg, 95% confidence interval (CI) = 130.5-131.5 mmHg; Gly482Ser mean = 133.1 mmHg, 95% CI = 132.6-133.6 mmHg; Ser482Ser: mean = 133.5 mmHg, 95% CI = 132.5-134.5 mmHg; P = 0.409] or DBP (Gly482Gly: mean = 80.3 mmHg, 95% CI = 80.0-80.6 mmHg; Gly482Ser mean = 81.5 mmHg, 95% CI = 81.2-81.8 mmHg; Ser482Ser: mean = 82.1 mmHg, 95% CI = 81.5-82.7 mmHg; P = 0.651). Contrary to previous reports, we did not observe significant effect modification by sex (SBP, P = 0.966; DBP, P = 0.715). We were also unable to confirm the previously reported association between the Ser482 allele and hypertension [odds ratio: 0.97, 95% CI = 0.87-1.08, P = 0.585]. These results were materially unchanged when analyses were focused on whites only. However, statistical evidence of gene-age interaction was apparent for DBP [Gly482Gly: 73.5 (72.8, 74.2), Gly482Ser: 77.0 (76.2, 77.8), Ser482Ser: 79.1 (77.4, 80.9), P = 4.20 x 10(-12)] and SBP [Gly482Gly: 121.4 (120.4, 122.5), Gly482Ser: 125.9 (124.6, 127.1), Ser482Ser: 129.2 (126.5, 131.9), P = 7.20 x 10(-12)] in individuals <50 yr (n = 2,511); these genetic effects were absent in those older than 50 yr (n = 5,088) (SBP, P = 0.41; DBP, P = 0.51). Our findings suggest that the PPARGC1A Ser482 allele may be associated with higher blood pressure, but this is only apparent in younger adults.

Study of tyrosine kinases and protein tyrosine phosphorylation

In recent years, our increased understanding of the complex signal transduction mechanisms that regulate cellular function has fueled huge advances in all aspects of biomedical science and cell biology. Platelet and megakaryocyte function is no exception to this. In the last 10 yr our understanding of the receptor biochemistry and the systems that they control has been pivotal in the development of new strategies to inhibit platelet function and thereby prevent thrombosis. Experimental techniques have become more and more elegant, however; the basic toolbox that a researcher requires to study signaling in platelets and megakaryoctes is described in this and several subsequent chapters.

Difference gel electrophoresis

DIGE is a protein labelling and separation technique allowing quantitative proteomics of two or more samples by optical fluorescence detection of differentially labelled proteins that are electrophoretically separated on the same gel. DIGE is an alternative to quantitation by MS-based methodologies and can circumvent their analytical limitations in areas such as intact protein analysis, (linear) detection over a wide range of protein abundances and, theoretically, applications where extreme sensitivity is needed. Thus, in quantitative proteomics DIGE is usually complementary to MS-based quantitation and has some distinct advantages. This review describes the basics of DIGE and its unique properties and compares it to MS-based methods in quantitative protein expression analysis.

Platelets release novel thiol isomerase enzymes which are recruited to the cell surface following activation

The thiol isomerase enzymes protein disulphide isomerase (PDI) and endoplasmic reticulum protein 5 (ERp5) are released by resting and activated platelets. These re-associate with the cell surface where they modulate a range of platelet responses including adhesion, secretion and aggregation. Recent studies suggest the existence of yet uncharacterised platelet thiol isomerase proteins. This study aimed to identify which other thiol isomerase enzymes are present in human platelets. Through the use of immunoblotting, flow cytometry, cell-surface biotinylation and gene array analysis, we report the presence of five additional thiol isomerases in human and mouse platelets and megakaryocytes, namely; ERp57, ERp72, ERp44, ERp29 and TMX3. ERp72, ERp57, ERp44 and ERp29 are released by platelets and relocate to the cell surface following platelet activation. The transmembrane thiol isomerase TMX3 was also detected on the platelet surface but does not increase following activation. Extracellular PDI is also implicated in the regulation of coagulation by the modulation of tissue factor activity. ERp57 was identified within platelet-derived microparticle fractions, suggesting that ERp57 may also be involved in the regulation of coagulation as well as platelet function. These data collectively implicate the expanding family of platelet-surface thiol isomerases in the regulation of haemostasis.

Bifurcation Analysis of Eigenstructure Assignment Control in a Simple Nonlinear Aircraft Model

Aircraft systems are highly nonlinear and time varying. High-performance aircraft at high angles of incidence experience undesired coupling of the lateral and longitudinal variables, resulting in departure from normal controlled � ight. The construction of a robust closed-loop control that extends the stable and decoupled � ight envelope as far as possible is pursued. For the study of these systems, nonlinear analysis methods are needed. Previously, bifurcation techniques have been used mainly to analyze open-loop nonlinear aircraft models and to investigate control effects on dynamic behavior. Linear feedback control designs constructed by eigenstructure assignment methods at a � xed � ight condition are investigated for a simple nonlinear aircraft model. Bifurcation analysis, in conjunction with linear control design methods, is shown to aid control law design for the nonlinear system.

Predicting protein structures and structural annotation of proteomes

Protein structure prediction methods aim to predict the structures of proteins from their amino acid sequences, utilizing various computational algorithms. Structural genome annotation is the process of attaching biological information to every protein encoded within a genome via the production of three-dimensional protein models.