Toward bacterial protein sub-cellular location prediction:single-class discrimminant models for all gram- and gram+ compartments

Based on Bayesian Networks, methods were created that address protein sequence-based bacterial subcellular location prediction. Distinct predictive algorithms for the eight bacterial subcellular locations were created. Several variant methods were explored. These variations included differences in the number of residues considered within the query sequence - which ranged from the N-terminal 10 residues to the whole sequence - and residue representation - which took the form of amino acid composition, percentage amino acid composition, or normalised amino acid composition. The accuracies of the best performing networks were then compared to PSORTB. All individual location methods outperform PSORTB except for the Gram+ cytoplasmic protein predictor, for which accuracies were essentially equal, and for outer membrane protein prediction, where PSORTB outperforms the binary predictor. The method described here is an important new approach to method development for subcellular location prediction. It is also a new, potentially valuable tool for candidate subunit vaccine selection.

Three-factor models versus time series models:quantifying time-dependencies of interactions between stimuli in cell biology and psychobiology for short longitudinal data

Signal integration determines cell fate on the cellular level, affects cognitive processes and affective responses on the behavioural level, and is likely to be involved in psychoneurobiological processes underlying mood disorders. Interactions between stimuli may subjected to time effects. Time-dependencies of interactions between stimuli typically lead to complex cell responses and complex responses on the behavioural level. We show that both three-factor models and time series models can be used to uncover such time-dependencies. However, we argue that for short longitudinal data the three factor modelling approach is more suitable. In order to illustrate both approaches, we re-analysed previously published short longitudinal data sets. We found that in human embryonic kidney 293 cells cells the interaction effect in the regulation of extracellular signal-regulated kinase (ERK) 1 signalling activation by insulin and epidermal growth factor is subjected to a time effect and dramatically decays at peak values of ERK activation. In contrast, we found that the interaction effect induced by hypoxia and tumour necrosis factor-alpha for the transcriptional activity of the human cyclo-oxygenase-2 promoter in HEK293 cells is time invariant at least in the first 12-h time window after stimulation. Furthermore, we applied the three-factor model to previously reported animal studies. In these studies, memory storage was found to be subjected to an interaction effect of the beta-adrenoceptor agonist clenbuterol and certain antagonists acting on the alpha-1-adrenoceptor / glucocorticoid-receptor system. Our model-based analysis suggests that only if the antagonist drug is administer in a critical time window, then the interaction effect is relevant.

Small cationic DDA:TDB liposomes as protein vaccine adjuvants obviate the need for TLR agonists in inducing cellular and humoral responses

Most subunit vaccines require adjuvants in order to induce protective immune responses to the targeted pathogen. However, many of the potent immunogenic adjuvants display unacceptable local or systemic reactogenicity. Liposomes are spherical vesicles consisting of single (unilamellar) or multiple (multilamellar) phospholipid bi-layers. The lipid membranes are interleaved with an aqueous buffer, which can be utilised to deliver hydrophilic vaccine components, such as protein antigens or ligands for immune receptors. Liposomes, in particular cationic DDA:TDB vesicles, have been shown in animal models to induce strong humoral responses to the associated antigen without increased reactogenicity, and are currently being tested in Phase I human clinical trials. We explored several modifications of DDA:TDB liposomes--including size, antigen association and addition of TLR agonists--to assess their immunogenic capacity as vaccine adjuvants, using Ovalbumin (OVA) protein as a model protein vaccine. Following triple homologous immunisation, small unilamellar vesicles (SUVs) with no TLR agonists showed a significantly higher capacity for inducing spleen CD8 IFN? responses against OVA in comparison with the larger multilamellar vesicles (MLVs). Antigen-specific antibody reponses were also higher with SUVs. Addition of the TLR3 and TLR9 agonists significantly increased the adjuvanting capacity of MLVs and OVA-encapsulating dehydration-rehydration vesicles (DRVs), but not of SUVs. Our findings lend further support to the use of liposomes as protein vaccine adjuvants. Importantly, the ability of DDA:TDB SUVs to induce potent CD8 T cell responses without the need for adding immunostimulators would avoid the potential safety risks associated with the clinical use of TLR agonists in vaccines adjuvanted with liposomes.

Hypoxia-inducible factor (HIF) network:insights from mathematical models

Oxygen is a crucial molecule for cellular function. When oxygen demand exceeds supply, the oxygen sensing pathway centred on the hypoxia inducible factor (HIF) is switched on and promotes adaptation to hypoxia by up-regulating genes involved in angiogenesis, erythropoiesis and glycolysis. The regulation of HIF is tightly modulated through intricate regulatory mechanisms. Notably, its protein stability is controlled by the oxygen sensing prolyl hydroxylase domain (PHD) enzymes and its transcriptional activity is controlled by the asparaginyl hydroxylase FIH (factor inhibiting HIF-1).To probe the complexity of hypoxia-induced HIF signalling, efforts in mathematical modelling of the pathway have been underway for around a decade. In this paper, we review the existing mathematical models developed to describe and explain specific behaviours of the HIF pathway and how they have contributed new insights into our understanding of the network. Topics for modelling included the switch-like response to decreased oxygen gradient, the role of micro environmental factors, the regulation by FIH and the temporal dynamics of the HIF response. We will also discuss the technical aspects, extent and limitations of these models. Recently, HIF pathway has been implicated in other disease contexts such as hypoxic inflammation and cancer through crosstalking with pathways like NF?B and mTOR. We will examine how future mathematical modelling and simulation of interlinked networks can aid in understanding HIF behaviour in complex pathophysiological situations. Ultimately this would allow the identification of new pharmacological targets in different disease settings.

Cross-linking of cellular proteins by tissue transglutaminase during necrotic cell death:a mechanism for maintaining tissue integrity

Tissue transglutaminase (tTG) is a Ca2+-dependent enzyme which cross-links proteins via e(g-glutamyl)lysine bridges. There is increasing evidence that tTG is involved in wound repair and tissue stabilization, as well as in physiological mechanisms leading to cell death. To investigate the role of this enzyme in tissue wounding leading to loss of Ca2+ homoeostasis, we initially used a model involving electroporation to reproduce cell wounding under controlled conditions. Two cell models were used whereby tTG expression is regulated either by antisense silencing in ECV 304 cells or by using transfected Swiss 3T3 cells in which tTG expression is under the control of the tet regulatory system. Using these cells, loss of Ca2+ homoeostasis following electroporation led to a tTG-dependent formation of highly cross-linked proteinaceous shells from intracellular proteins. Formation of these structures is dependent on elevated intracellular Ca2+, but it is independent of intracellular proteases and is near maximal after only 20min post-wounding. Using labelled primary amines as an indicator of tTG activity within these 'wounded cells', we demonstrate that tTG modifies a wide range of proteins that are present in both the perinuclear and intranuclear spaces. The demonstration of entrapped DNA within these shell structures, which showed limited fragmentation, provides evidence that the high degree of transglutaminase cross-linking results in the prevention of DNA release, which may serve to dampen any subsequent inflammatory response. Comparable observations were shown when monolayers of cells were mechanically wounded by scratching. In this second model of cell wounding, redistribution of tTG activity to the extracellular matrix was also demonstrated, an effect which may serve to stabilize tissues post-trauma, and thus contribute to the maintenance of tissue integrity.

Developing accurate models of the human airways

Objectives Particle delivery to the airways is an attractive prospect for many potential therapeutics, including vaccines. Developing strategies for inhalation of particles provides a targeted, controlled and non-invasive delivery route but, as with all novel therapeutics, in vitro and in vivo testing are needed prior to clinical use. Whilst advanced vaccine testing demands the use of animal models to address safety issues, the production of robust in vitro cellular models would take account of the ethical framework known as the 3Rs (Replacement, Reduction and Refinement of animal use), by permitting initial screening of potential candidates prior to animal use. There is thus a need for relevant, realistic in vitro models of the human airways. Key findings Our laboratory has designed and characterised a multi-cellular model of human airways that takes account of the conditions in the airways and recapitulates many salient features, including the epithelial barrier and mucus secretion. Summary Our human pulmonary models recreate many of the obstacles to successful pulmonary delivery of particles and therefore represent a valid test platform for screening compounds and delivery systems.

Quantitative prediction of mouse class I MHC peptide binding affinity using support vector machine regression (SVR) models

Background - The binding between peptide epitopes and major histocompatibility complex proteins (MHCs) is an important event in the cellular immune response. Accurate prediction of the binding between short peptides and the MHC molecules has long been a principal challenge for immunoinformatics. Recently, the modeling of MHC-peptide binding has come to emphasize quantitative predictions: instead of categorizing peptides as "binders" or "non-binders" or as "strong binders" and "weak binders", recent methods seek to make predictions about precise binding affinities. Results - We developed a quantitative support vector machine regression (SVR) approach, called SVRMHC, to model peptide-MHC binding affinities. As a non-linear method, SVRMHC was able to generate models that out-performed existing linear models, such as the "additive method". By adopting a new "11-factor encoding" scheme, SVRMHC takes into account similarities in the physicochemical properties of the amino acids constituting the input peptides. When applied to MHC-peptide binding data for three mouse class I MHC alleles, the SVRMHC models produced more accurate predictions than those produced previously. Furthermore, comparisons based on Receiver Operating Characteristic (ROC) analysis indicated that SVRMHC was able to out-perform several prominent methods in identifying strongly binding peptides. Conclusion - As a method with demonstrated performance in the quantitative modeling of MHC-peptide binding and in identifying strong binders, SVRMHC is a promising immunoinformatics tool with not inconsiderable future potential.

The use of erythrocytic and animal models in the study of protein phosphorylation

Phosphorylation processes are common post-transductional mechanisms, by which it is possible to modulate a number of metabolic pathways. Proteins are highly sensitive to phosphorylation, which governs many protein-protein interactions. The enzymatic activity of some protein tyrosine-kinases is under tyrosine-phosphorylation control, as well as several transmembrane anion-fluxes and cation exchanges. In addition, phosphorylation reactions are involved in intra and extra-cellular 'cross-talk' processes. Early studies adopted laboratory animals to study these little known phosphorylation processes. The main difficulty encountered with these animal techniques was obtaining sufficient kinase or phosphatase activity suitable for studying the enzymatic process. Large amounts of biological material from organs, such as the liver and spleen were necessary to conduct such work with protein kinases. Subsequent studies revealed the ubiquity and complexity of phosphorylation processes and techniques evolved from early rat studies to the adaptation of more rewarding in vitro models. These involved human erythrocytes, which are a convenient source both for the enzymes, we investigated and for their substrates. This preliminary work facilitated the development of more advanced phosphorylative models that are based on cell lines. © 2005 Elsevier B.V. All rights reserved.