Eukaryotic expression:Developments for structural proteomics

The production of sufficient quantities of protein is an essential prelude to a structure determination, but for many viral and human proteins this cannot be achieved using prokaryotic expression systems. Groups in the Structural Proteomics In Europe (SPINE) consortium have developed and implemented high-throughput (HTP) methodologies for cloning, expression screening and protein production in eukaryotic systems. Studies focused on three systems: yeast (Pichia pastoris and Saccharomyces cerevisiae), baculovirus-infected insect cells and transient expression in mammalian cells. Suitable vectors for HTP cloning are described and results from their use in expression screening and protein-production pipelines are reported. Strategies for co-expression, selenomethionine labelling (in all three eukaryotic systems) and control of glycosylation (for secreted proteins in mammalian cells) are assessed. © International Union of Crystallography, 2006.

MHC class II binding prediction:a little help from a friend

Vaccines are the greatest single instrument of prophylaxis against infectious diseases, with immeasurable benefits to human wellbeing. The accurate and reliable prediction of peptide-MHC binding is fundamental to the robust identification of T-cell epitopes and thus the successful design of peptide- and protein-based vaccines. The prediction of MHC class II peptide binding has hitherto proved recalcitrant and refractory. Here we illustrate the utility of existing computational tools for in silico prediction of peptides binding to class II MHCs. Most of the methods, tested in the present study, detect more than the half of the true binders in the top 5% of all possible nonamers generated from one protein. This number increases in the top 10% and 15% and then does not change significantly. For the top 15% the identified binders approach 86%. In terms of lab work this means 85% less expenditure on materials, labour and time. We show that while existing caveats are well founded, nonetheless use of computational models of class II binding can still offer viable help to the work of the immunologist and vaccinologist.

Characterisation of the plasma membrane subproteome of bloodstream form Trypanosoma brucei

Proteome analysis by conventional approaches is biased against hydrophobic membrane proteins, many of which are also of low abundance. We have isolated plasma membrane sheets from bloodstream forms of Trypanosoma brucei by subcellular fractionation, and then applied a battery of complementary protein separation and identification techniques to identify a large number of proteins in this fraction. The results of these analyses have been combined to generate a subproteome for the pellicular plasma membrane of bloodstream forms of T. brucei as well as a separate subproteome for the pellicular cytoskeleton. In parallel, we have used in silico approaches to predict the relative abundance of proteins potentially expressed by bloodstream form trypanosomes, and to identify likely polytopic membrane proteins, providing quality control for the experimentally defined plasma membrane subproteome. We show that the application of multiple high-resolution proteomic techniques to an enriched organelle fraction is a valuable approach for the characterisation of relatively intractable membrane proteomes. We present here the most complete analysis of a protozoan plasma membrane proteome to date and show the presence of a large number of integral membrane proteins, including 11 nucleoside/nucleobase transporters, 15 ion pumps and channels and a large number of adenylate cyclases hitherto listed as putative proteins.

Single-cell ELISA and flow cytometry as methods for highlighting potential neuronal and astrocytic toxicant specificity

The timeline imposed by recent worldwide chemical legislation is not amenable to conventional in vivo toxicity testing, requiring the development of rapid, economical in vitro screening strategies which have acceptable predictive capacities. When acquiring regulatory neurotoxicity data, distinction on whether a toxic agent affects neurons and/or astrocytes is essential. This study evaluated neurofilament (NF) and glial fibrillary acidic protein (GFAP) directed single-cell (S-C) ELISA and flow cytometry as methods for distinguishing cell-specific cytoskeletal responses, using the established human NT2 neuronal/astrocytic (NT2.N/A) co-culture model and a range of neurotoxic (acrylamide, atropine, caffeine, chloroquine, nicotine) and non-neurotoxic (chloramphenicol, rifampicin, verapamil) test chemicals. NF and GFAP directed flow cytometry was able to identify several of the test chemicals as being specifically neurotoxic (chloroquine, nicotine) or astrocytoxic (atropine, chloramphenicol) via quantification of cell death in the NT2.N/A model at cytotoxic concentrations using the resazurin cytotoxicity assay. Those neurotoxicants with low associated cytotoxicity are the most significant in terms of potential hazard to the human nervous system. The NF and GFAP directed S-C ELISA data predominantly demonstrated the known neurotoxicants only to affect the neuronal and/or astrocytic cytoskeleton in the NT2.N/A cell model at concentrations below those affecting cell viability. This report concluded that NF and GFAP directed S-C ELISA and flow cytometric methods may prove to be valuable additions to an in vitro screening strategy for differentiating cytotoxicity from specific neuronal and/or astrocytic toxicity. Further work using the NT2.N/A model and a broader array of toxicants is appropriate in order to confirm the applicability of these methods.

The design of novel antifolates against pneumocystis carinii

The pneumonia caused by Pneumocystis carinii is ultimately responsible for the death of many acquired immunodeficiency syndrome (AIDS) patients. Large doses of trimethoprim and pyrimethamine in combination with a sulphonamide and/or pentamidine suppress the infection but produce serious side-effects and seldom prevent recurrence after treatment withdrawal. However, the partial success of the aforementioned antifolates, and also trimetrexate used alone, does suggest dihydrofolate reductase (DHFR) as a target for the development of antipneumocystis agents. From the DHFR inhibitory activities of 3'-substituted pyrimethamine analogues it was suggested that the 3'-(3'',3''-dimethyltriazen-1''-yl) substituent may be responsible for the greater activity for the P.carinii over the mammalian enzyme. Crystallographic and molecular modeling studies revealed considerable geometrical and electronic differences between the triazene and the chemically related formamidine functions that may account for the differences in DHFR inhibitory profiles. Structural and electronic parameters calculated for a series of 3'-(3'',3''-disubstitutedtriazen-1''-yl) pyrimethamine analogues did not correlate with the DHFR inhibitory activities. However, the in vitro screening against P.carinii DHFR revealed that the 3''-hydroxyethyl-3''-benzyl analogue was the most active and selective. Models of the active sites of human and P.carinii DHFRs were constructed using DHFR sequence and structural homology data which had identified key residues involved in substrate and cofactor binding. Low energy conformations of the 3'',3''-dimethyl and 3''-hydroxyethyl-3''-benzyle analogues, determined from nuclear magnetic resonance studies and theoretical calculations, were docked by superimposing the diaminopyrimidine fragment onto a previously docked pyrimethamine analogue. Enzyme kinetic data supported the 3''-hydroxyethyl-3''-benzyl moiety being located in the NADPH binding groove. The 3''-benzyl substituent was able to locate to within 3 AA of a valine residue in the active site of P.carinii DHFR thereby producing a hydrophobic contact. The equivalent residue in human DHFR is threonine, more hydrophilic and less likely to be involved in such a contact. This difference may account for the greater inhibitory activity this analogue has for P.carinii DHFR and provide a basis for future drug design. From an in vivo model of PCP in immunosuppressed rats it was established that the 3"-hydroxyethyl-3"-benzyl analogue was able to reduce the.P.carinii burden more effectively with increasing doses, without causmg any visible signs of toxicity. However, equivalent doses were not as effective as pentamidine, a current treatment of choice for Pneumocystis carinii pneumonia.

Proteins accessible to immune surveillance show significant T-cell epitope depletion:implications for vaccine design

T cell activation is the final step in a complex pathway through which pathogen-derived peptide fragments can elicit an immune response. For it to occur, peptides must form stable complexes with Major Histocompatibility Complex (MHC) molecules and be presented on the cell surface. Computational predictors of MHC binding are often used within in silico vaccine design pathways. We have previously shown that, paradoxically, most bacterial proteins known experimentally to elicit an immune response in disease models are depleted in peptides predicted to bind to human MHC alleles. The results presented here, derived using software proven through benchmarking to be the most accurate currently available, show that vaccine antigens contain fewer predicted MHC-binding peptides than control bacterial proteins from almost all subcellular locations with the exception of cell wall and some cytoplasmic proteins. This effect is too large to be explained from the undoubted lack of precision of the software or from the amino acid composition of the antigens. Instead, we propose that pathogens have evolved under the influence of the host immune system so that surface proteins are depleted in potential MHC-binding peptides, and suggest that identification of a protein likely to contain a single immuno-dominant epitope is likely to be a productive strategy for vaccine design.

Multimodal characterisation of sensorimotor oscillations

The studies in this project have investigated the ongoing neuronal network oscillatory activity found in the sensorimotor cortex using two modalities: magnetoencephalography (MEG) and in vitro slice recordings. The results have established that ongoing sensorimotor oscillations span the mu and beta frequency region both in vitro and in MEG recordings, with distinct frequency profiles for each recorded laminae in vitro, while MI and SI show less difference in humans. In addition, these studies show that connections between MI and SI modulate the ongoing neuronal network activity in these areas. The stimulation studies indicate that specific frequencies of stimulation affect the ongoing activity in the sensorimotor cortex. The continuous theta burst stimulation (cTBS) study demonstrates that cTBS predominantly enhances the power of the local ongoing activity. The stimulation studies in this project show limited comparison between modalities, which is informative of the role of connectivity in these effects. However, independently these studies provide novel information on the mechanisms on sensorimotor oscillatory interaction. The pharmacological studies reveal that GABAergic modulation with zolpidem changes the neuronal oscillatory network activity in both healthy and pathological MI. Zolpidem enhances the power of ongoing oscillatory activity in both sensorimotor laminae and in healthy subjects. In contrast, zolpidem attenuates the “abnormal” beta oscillatory activity in the affected hemisphere in Parkinsonian patients, while restoring the hemispheric beta power ratio and frequency variability and thereby improving motor symptomatology. Finally we show that independent signals from MI laminae can be integrated in silico to resemble the aggregate MEG MI oscillatory signals. This highlights the usefulness of combining these two methods when elucidating neuronal network oscillations in the sensorimotor cortex and any interventions.

A dynamic model of the hypoxia-inducible factor 1α (HIF-1α) network

Activation of the hypoxia-inducible factor (HIF) pathway is a critical step in the transcriptional response to hypoxia. Although many of the key proteins involved have been characterised, the dynamics of their interactions in generating this response remain unclear. In the present study, we have generated a comprehensive mathematical model of the HIF-1a pathway based on core validated components and dynamic experimental data, and confirm the previously described connections within the predicted network topology. Our model confirms previous work demonstrating that the steps leading to optimal HIF-1a transcriptional activity require sequential inhibition of both prolyl- and asparaginyl-hydroxylases. We predict from our model (and confirm experimentally) that there is residual activity of the asparaginyl-hydroxylase FIH (factor inhibiting HIF) at low oxygen tension. Furthermore, silencing FIH under conditions where prolyl-hydroxylases are inhibited results in increased HIF-1a transcriptional activity, but paradoxically decreases HIF-1a stability. Using a core module of the HIF network and mathematical proof supported by experimental data, we propose that asparaginyl hydroxylation confers a degree of resistance upon HIF-1a to proteosomal degradation. Thus, through in vitro experimental data and in silico predictions, we provide a comprehensive model of the dynamic regulation of HIF-1a transcriptional activity by hydroxylases and use its predictive and adaptive properties to explain counter-intuitive biological observations.

On the comparative performance of socially responsible and Islamic mutual funds

This is the first study to provide comprehensive analyses of the relative performance of both socially responsible investment (SRI) and Islamic mutual funds. The analysis proceeds in two stages. In the first, the performance of the two categories of funds is measured using partial frontier methods. In the second stage, we use quantile regression techniques.By combining two variants of the Free Disposal Hull (FDH) methods (order-m and order-?) in the first stage of analysis and quantile regression in the second stage, we provide detailed analyses of the impact of different covariates across methods and across different quantiles. In spite of the differences in the screening criteria and portfolio management of both types of funds, variation in the performance is only found for some of the quantiles of the conditional distribution of mutual fund performance. We established that for the most inefficient funds the superior performance of SRI funds is significant. In contrast, for the best mutual funds this evidence vanished and even Islamic funds perform better than SRI.These results show the benefits of performing the analysis using quantile regression.

The antimicrobial action of pseudin-2

The amphibian antimicrobial peptide pseudin-2 is a peptide derived from the skin of the South-American frog Pseudis paradoxa (Olson et al., 2001). This peptide possesses tremendous potential as a therapeutic lead since it has been shown to possess both antimicrobial as well insulin-releasing properties (Olson et al., 2001; Abdel-Wahab et al., 2008). This study aimed to develop pseudin-2’s potential by understanding and improving its properties as an antimicrobial agent. The structure-function relationships of pseudin-2 were explored using a combination of in-vitro and in-silico techniques, with an aim to predict how the structure of the peptide may be altered in order to improve its efficacy. A library of pseudin-2 mutants was generated by randomizing codons at positions 10, 14 and 18 of a synthetic gene, using NNK saturation mutagenesis. Analysis of these novel peptides broadly confirmed, in line with literature precedent, that anti-microbial activity increases with increased positive charge. Specifically, 2 positively-charged residues at positions 10 and 14 and a hydrophobic at position 18 are preferred. However, substitution at position 14 with some polar, non-charged residues also created peptides with antimicrobial activity. Interestingly, the pseudin-2 analogue [10-E, 14-Q, 18-L] which is identical to pseudin-2, except that the residues at positions 10 and 14 are switched, showed no anti-microbial activity at all. Molecular dynamics simulations of pseudin-2 showed that the peptide possesses two equilibrium structures in a membrane environment: a linear and a kinked a-helix which both embed into the membrane at an angle. Biophysical characterization using circular dichroism spectroscopy confirmed that the peptide is helical within the membrane environment whilst linear dichroism established that the peptide has no defined orientation within the membrane. Collectively, these data indicate that Pseudin-2 exerts its antimicrobial activity via the carpet model.

On the comparative performance of socially responsible and Islamic mutual funds

This is the first study to provide comprehensive analyses of the relative performance of both socially responsible investment (SRI) and Islamic mutual funds. The analysis proceeds in two stages. In the first, the performance of the two categories of funds is measured using partial frontier methods. In the second stage, we use quantile regression techniques. By combining two variants of the Free Disposal Hull (FDH) methods (order- m and order- α) in the first stage of analysis and quantile regression in the second stage, we provide detailed analyses of the impact of different covariates across methods and across different quantiles. In spite of the differences in the screening criteria and portfolio management of both types of funds, variation in the performance is only found for some of the quantiles of the conditional distribution of mutual fund performance. We established that for the most inefficient funds the superior performance of SRI funds is significant. In contrast, for the best mutual funds this evidence vanished and even Islamic funds perform better than SRI. These results show the benefits of performing the analysis using quantile regression. © 2013 Elsevier B.V.

Harnessing bioinformatics to discover new vaccines

Vaccine design is highly suited to the application of in silico techniques, for both the discovery and development of new and existing vaccines. Here, we discuss computational contributions to epitope mapping and reverse vaccinology, two techniques central to the new discipline of immunomics. Also discussed are methods to improve the efficiency of vaccination, such as codon optimization and adjuvant discovery in addition to the identification of allergenic proteins. We also review current software developed to facilitate vaccine design.

Combining algorithms to predict bacterial protein sub-cellular location:parallel versus concurrent implementations

We describe a novel and potentially important tool for candidate subunit vaccine selection through in silico reverse-vaccinology. A set of Bayesian networks able to make individual predictions for specific subcellular locations is implemented in three pipelines with different architectures: a parallel implementation with a confidence level-based decision engine and two serial implementations with a hierarchical decision structure, one initially rooted by prediction between membrane types and another rooted by soluble versus membrane prediction. The parallel pipeline outperformed the serial pipeline, but took twice as long to execute. The soluble-rooted serial pipeline outperformed the membrane-rooted predictor. Assessment using genomic test sets was more equivocal, as many more predictions are made by the parallel pipeline, yet the serial pipeline identifies 22 more of the 74 proteins of known location.

Identifying candidate subunit vaccines using an alignment-independent method based on principal amino acid properties

Subunit vaccine discovery is an accepted clinical priority. The empirical approach is time- and labor-consuming and can often end in failure. Rational information-driven approaches can overcome these limitations in a fast and efficient manner. However, informatics solutions require reliable algorithms for antigen identification. All known algorithms use sequence similarity to identify antigens. However, antigenicity may be encoded subtly in a sequence and may not be directly identifiable by sequence alignment. We propose a new alignment-independent method for antigen recognition based on the principal chemical properties of protein amino acid sequences. The method is tested by cross-validation on a training set of bacterial antigens and external validation on a test set of known antigens. The prediction accuracy is 83% for the cross-validation and 80% for the external test set. Our approach is accurate and robust, and provides a potent tool for the in silico discovery of medically relevant subunit vaccines.

Predicting class I major histocompatibility complex (MHC) binders using multivariate statistics:comparison of discriminant analysis and multiple linear regression

The accurate in silico identification of T-cell epitopes is a critical step in the development of peptide-based vaccines, reagents, and diagnostics. It has a direct impact on the success of subsequent experimental work. Epitopes arise as a consequence of complex proteolytic processing within the cell. Prior to being recognized by T cells, an epitope is presented on the cell surface as a complex with a major histocompatibility complex (MHC) protein. A prerequisite therefore for T-cell recognition is that an epitope is also a good MHC binder. Thus, T-cell epitope prediction overlaps strongly with the prediction of MHC binding. In the present study, we compare discriminant analysis and multiple linear regression as algorithmic engines for the definition of quantitative matrices for binding affinity prediction. We apply these methods to peptides which bind the well-studied human MHC allele HLA-A*0201. A matrix which results from combining results of the two methods proved powerfully predictive under cross-validation. The new matrix was also tested on an external set of 160 binders to HLA-A*0201; it was able to recognize 135 (84%) of them.