Multi-locus stepwise regression: a haplotype-based algorithm for finding genetic associations applied to atopic dermatitis

Background

Genome-wide association studies (GWAS) provide an increasing number of single nucleotide polymorphisms (SNPs) associated with diseases. Our aim is to exploit those closely spaced SNPs in candidate regions for a deeper analysis of association beyond single SNP analysis, combining the classical stepwise regression approach with haplotype analysis to identify risk haplotypes for complex diseases.

Methods

Our proposed multi-locus stepwise regression starts with an evaluation of all pair-wise SNP combinations and then extends each SNP combination stepwise by one SNP from the region, carrying out haplotype regression in each step. The best associated haplotype patterns are kept for the next step and must be corrected for multiple testing at the end. These haplotypes should also be replicated in an independent data set. We applied the method to a region of 259 SNPs from the epidermal differentiation complex (EDC) on chromosome 1q21 of a German GWAS using a case control set (1,914 individuals) and to 268 families with at least two affected children as replication.

Results

A 4-SNP haplotype pattern with high statistical significance in the case control set (p = 4.13 × 10^-7 after Bonferroni correction) could be identified which remained significant in the family set after Bonferroni correction (p = 0.0398). Further analysis revealed that this pattern reflects mainly the effect of the well-known FLG gene; however, a FLG-independent haplotype in case control set (OR = 1.71, 95% CI: 1.32-2.23, p = 5.6 × 10^-5) and family set (OR = 1.68, 95% CI: 1.18-2.38, p = 2.19 × 10^-3) could be found in addition.

Conclusion

Our approach is a useful tool for finding allele combinations associated with diseases beyond single SNP analysis in chromosomal candidate regions.

The virtual liver: a multidisciplinary, multilevel challenge for systems biology

The liver is the central metabolic organ in human physiology, with functions that are fundamentally important to the detoxification of xenobiotics (drugs), the maintenance of homeostasis of numerous blood metabolites, and the production of mediators of the acute phase response. Liver toxicity, whether actual or implied is the reason for the failure of a significant proportion of many promising novel medicines that consequently never reach the market, and diseases such as atherosclerosis, diabetes, and fatty liver diseases, that are a major burden on current health resources, are directly linked to functional and structural disorders of the liver. This article presents the concepts and approaches underpinning one of the most exciting and ambitious modeling projects in the field of systems biology and systems medicine. This major multidisciplinary research program is aimed at developing a whole-organ model of the human liver, representing its central physiological functions under normal and pathological conditions The model will be composed of a larger battery of interconnected submodels representing liver anatomy and physiology, integrating processes across hierarchical levels in space, time, and structural organization. In this article, we outline the general architecture of the liver model and present first step taken to reach this ambitious goal.

Metannogen: annotation of biological reaction networks

MOTIVATION

Semantic annotations of the biochemical entities constituting a biological reaction network are indispensable to create biologically meaningful networks. They further heighten efficient exchange, reuse and merging of existing models which concern present-day systems biology research more often. Two types of tools for the reconstruction of biological networks currently exist: (i) several sophisticated programs support graphical network editing and visualization. (ii) Data management systems permit reconstruction and curation of huge networks in a team of scientists including data integration, annotation and cross-referencing. We seeked ways to combine the advantages of both approaches.

RESULTS

Metannogen, which was previously developed for network reconstruction, has been considerably improved. From now on, Metannogen provides sbml import and annotation of networks created elsewhere. This permits users of other network reconstruction platforms or modeling software to annotate their networks using Metannogen's advanced information management. We implemented word-autocompletion, multipattern highlighting, spell check, brace-expansion and publication management, and improved annotation, cross-referencing and team work requirements. Unspecific enzymes and transporters acting on a spectrum of different substrates are efficiently handled. The network can be exported in sbml format where the annotations are embedded in line with the miriam standard. For more comfort, Metannogen may be tightly coupled with the network editor such that Metannogen becomes an additional view for the focused reaction in the network editor. Finally, Metannogen provides local single user, shared password protected multiuser or public access to the annotation data.

AVAILABILITY

Metannogen is available free of charge at: http://www.bioinformatics.org/strap/metannogen/ or http://3d-alignment.eu/metannogen/.

CONTACT

christoph.gille@charite.de

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Enzymatic features of the glucose metabolism in tumor cells

Many tumor types exhibit an impaired Pasteur effect, i.e. despite the presence of oxygen, glucose is consumed at an extraordinarily high rate compared with the tissue from which they originate - the so-called 'Warburg effect'. Glucose has to serve as the source for a diverse array of cellular functions, including energy production, synthesis of nucleotides and lipids, membrane synthesis and generation of redox equivalents for antioxidative defense. Tumor cells acquire specific enzyme-regulatory mechanisms to direct the main flux of glucose carbons to those pathways most urgently required under challenging external conditions such as varying substrate availability, presence of anti-cancer drugs or different phases of the cell cycle. In this review we summarize the currently available information on tumor-specific expression, activity and kinetic properties of enzymes involved in the main pathways of glucose metabolism with due regard to the explanation of the regulatory basis and physiological significance of the Warburg effect. We conclude that, besides the expression level of the metabolic enzymes involved in the glucose metabolism of tumor cells, the unique tumor-specific pattern of isozymes and accompanying changes in the metabolic regulation below the translation level enable tumor cells to drain selfishly the blood glucose pool that non-transformed cells use as sparingly as possible.

The influence of the chloride currents on action potential firing and volume regulation of excitable cells studied by a kinetic model

In excitable cells, the generation of an action potential (AP) is associated with transient changes of the intra- and extracellular concentrations of small ions such as Na(+), K(+) and Cl(-). If these changes cannot be fully reversed between successive APs cumulative changes of trans-membrane ion gradients will occur, impinging on the cell volume and the duration, amplitude and frequency of APs. Previous computational studies focused on effects associated with excitation-induced changes of potassium and sodium. Here we present a model based study on the influence of chloride on the fidelity of AP firing and cellular volume regulation during excitation. Our simulations show that depending on the magnitude of the basal chloride permeability two complementary types of responsiveness and volume variability exist: (i) At high chloride permeability (typical for muscle cells), large excitatory stimuli are required to elicit APs; repetitive stimuli of equal strength result in almost identical spike train patterns (Markovian behavior), however, long excitation may lead to after discharges due to an outward directed current of intracellular chloride ions which accumulate during excitation; cell volume changes are large. (ii) At low chloride permeability (e.g., neurons), small excitatory stimuli are sufficient to elicit APs, repetitive stimuli of equal strength produce spike trains with progressively changing amplitude, frequency and duration (short-term memory effects or non-Markovian behavior); cell volume changes are small. We hypothesize that variation of the basal chloride permeability could be an important mechanism of neuronal cells to adapt their responsiveness to external stimuli during learning and memory processes.

FASIMU: flexible software for flux-balance computation series in large metabolic networks

Background

Flux-balance analysis based on linear optimization is widely used to compute metabolic fluxes in large metabolic networks and gains increasingly importance in network curation and structural analysis. Thus, a computational tool flexible enough to realize a wide variety of FBA algorithms and able to handle batch series of flux-balance optimizations is of great benefit.

Results

We present FASIMU, a command line oriented software for the computation of flux distributions using a variety of the most common FBA algorithms, including the first available implementation of (i) weighted flux minimization, (ii) fitness maximization for partially inhibited enzymes, and (iii) of the concentration-based thermodynamic feasibility constraint. It allows batch computation with varying objectives and constraints suited for network pruning, leak analysis, flux-variability analysis, and systematic probing of metabolic objectives for network curation. Input and output supports SBML. FASIMU can work with free (lp_solve and GLPK) or commercial solvers (CPLEX, LINDO). A new plugin (faBiNA) for BiNA allows to conveniently visualize calculated flux distributions. The platform-independent program is an open-source project, freely available under GNU public license at http://www.bioinformatics.org/fasimu including manual, tutorial, and plugins.

Conclusions

We present a flux-balance optimization program whose main merits are the implementation of thermodynamics as a constraint, batch series of computations, free availability of sources, choice on various external solvers, and the flexibility on metabolic objectives and constraints.

Antimalarial drug targets in Plasmodium falciparum predicted by stage-specific metabolic network analysis

BACKGROUND

Despite enormous efforts to combat malaria the disease still afflicts up to half a billion people each year of which more than one million die. Currently no approved vaccine is available and resistances to antimalarials are widely spread. Hence, new antimalarial drugs are urgently needed.

RESULTS

Here, we present a computational analysis of the metabolism of Plasmodium falciparum, the deadliest malaria pathogen. We assembled a compartmentalized metabolic model and predicted life cycle stage specific metabolism with the help of a flux balance approach that integrates gene expression data. Predicted metabolite exchanges between parasite and host were found to be in good accordance with experimental findings when the parasite's metabolic network was embedded into that of its host (erythrocyte). Knock-out simulations identified 307 indispensable metabolic reactions within the parasite. 35 out of 57 experimentally demonstrated essential enzymes were recovered and another 16 enzymes, if additionally the assumption was made that nutrient uptake from the host cell is limited and all reactions catalyzed by the inhibited enzyme are blocked. This predicted set of putative drug targets, shown to be enriched with true targets by a factor of at least 2.75, was further analyzed with respect to homology to human enzymes, functional similarity to therapeutic targets in other organisms and their predicted potency for prophylaxis and disease treatment.

CONCLUSIONS

The results suggest that the set of essential enzymes predicted by our flux balance approach represents a promising starting point for further drug development.

Fluxviz - Cytoscape plug-in for visualization of flux distributions in networks

MOTIVATION

Methods like FBA and kinetic modeling are widely used to calculate fluxes in metabolic networks. For the analysis and understanding of simulation results and experimentally measured fluxes visualization software within the network context is indispensable.

RESULTS

We present Flux Viz, an open-source Cytoscape plug-in for the visualization of flux distributions in molecular interaction networks. FluxViz supports (i) import of networks in a variety of formats (SBML, GML, XGMML, SIF, BioPAX, PSI-MI) (ii) import of flux distributions as CSV, Cytoscape attributes or VAL files (iii) limitation of views to flux carrying reactions (flux subnetwork) or network attributes like localization (iv) export of generated views (SVG, EPS, PDF, BMP, PNG). Though FluxViz was primarily developed as tool for the visualization of fluxes in metabolic networks and the analysis of simulation results from FASIMU, a flexible software for batch flux-balance computation in large metabolic networks, it is not limited to biochemical reaction networks and FBA but can be applied to the visualization of arbitrary fluxes in arbitrary graphs.

AVAILABILITY

The platform-independent program is an open-source project, freely available at http://sourceforge.net/projects/fluxvizplugin/ under GNU public license, including manual, tutorial and examples.

Finding one's way in proteomics: a protein species nomenclature

Our knowledge of proteins has greatly improved in recent years, driven by new technologies in the fields of molecular biology and proteome research. It has become clear that from a single gene not only one single gene product but many different ones - termed protein species - are generated, all of which may be associated with different functions. Nonetheless, an unambiguous nomenclature for describing individual protein species is still lacking. With the present paper we therefore propose a systematic nomenclature for the comprehensive description of protein species. The protein species nomenclature is flexible and adaptable to every level of knowledge and of experimental data in accordance with the exact chemical composition of individual protein species. As a minimum description the entry name (gene name + species according to the UniProt knowledgebase) can be used, if no analytical data about the target protein species are available.

Uncovering metabolic objectives pursued by changes of enzyme levels

Expression profiling and proteomic techniques reveal significant variations in the levels of thousands of mRNAs and proteins in response to environmental changes such as substrate depletion, oxidative stress, and hormonal stimulation. However, in most cases the functional implications of these variations remain elusive. One crucial problem complicating the functional interpretation of high-throughput data is that changes of protein levels do not simply translate into equivalent changes in the rate of the associated chemical processes due to various modes of enzyme regulation and the instantaneous effect of changed metabolite concentrations on adjacent flux rates. Here, we outline a theoretical concept to exploit information on (relative) changes in the level of metabolic enzymes for the prediction of (relative) flux changes in the underlying metabolic network. Our approach rests on the assumption that size and direction of fluxes (flux distribution) in the network are determined by an optimization principle in that the production of the physiologically relevant output metabolites is accomplished with minimal total flux. The prediction method comprises two main steps. First, we approximate (unknown) flux changes by a linear combination of so-called minimal flux modes, each representing a specific flux distribution minimally required to accomplish the production of only one of the numerous functionally relevant output metabolites. Second, the unknown coefficients of this decomposition are chosen such that a maximal correlation with observed differential expression data is obtained. Based on simulated enzyme expression scenarios in a metabolic model of the human red blood cell, we demonstrate the predictive capacity of our method.

Polyubiquitin substrates allosterically activate their own degradation by the 26S proteasome

The 26S proteasome degrades polyubiquitylated (polyUb) proteins by an ATP-dependent mechanism. Here we show that binding of model polyUb substrates to the 19S regulator of mammalian and yeast 26S proteasomes enhances the peptidase activities of the 20S proteasome about two-fold in a process requiring ATP hydrolysis. Monoubiquitylated proteins or tetraubiquitin alone exert no effect. However, 26S proteasomes from the yeast alpha3DeltaN open-gate mutant and the rpt2YA and rpt5YA mutants with impaired gating can still be activated (approximately 1.3-fold to 1.8-fold) by polyUb-protein binding. Thus, binding of polyUb substrates to the 19S regulator stabilizes gate opening of the 20S proteasome and induces conformational changes of the 20S proteasome that facilitate channeling of substrates and their access to active sites. In consequence, polyUb substrates will allosterically stimulate their own degradation.

Characterizing the N-terminal processing motif of MHC class I ligands

Most peptide ligands presented by MHC class I molecules are the product of an intracellular pathway comprising protein breakdown in the cytosol, transport into the endoplasmic reticulum, and successive N-terminal trimming events. The efficiency of each of these processes depends on the amino acid sequence of the presented ligand and its precursors. Thus, relating the amino acid composition N-terminal of presented ligands to the sequence specificity of processes in the pathway gives insight into the usage of ligand precursors in vivo. Examining the amino acid composition upstream the true N terminus of MHC class I ligands, we demonstrate the existence of a distinct N-terminal processing motif comprising approximately seven residues and matching the known preferences of proteasome and TAP, two key players in ligand processing. Furthermore, we find that some residues, which are preferred by both TAP and the proteasome, are underrepresented at positions immediately preceding the N terminus of MHC class I ligands. Based on experimentally determined aminopeptidase activities, this pattern suggests trimming next to the final N terminus to take place predominantly in the endoplasmic reticulum.

Computer aided optimization of carbon atom labeling for tracer experiments

Isotopomer tracer experiments are indispensable for the determination of flux rates in already known pathways as well as for the identification of new pathways. The information gained from such experiments depends on the labeling of the feed tracer metabolite, i.e. the atom positions carrying a label. Here we present an algorithm and a software tool to find an optimal carbon labeling pattern that assures the label to disseminate predominantly into those parts of the network under study. Our implementation is based on carbon fate maps and distinguishes between homotopic and prochiral atoms. In addition, the software can be used to generate carbon transition probability matrices, which can be used for the study of biochemical reaction mechanisms. In this article we present the algorithms and show an application of the software for glycolysis and the TCA cycle.

A computational analysis of protein interactions in metabolic networks reveals novel enzyme pairs potentially involved in metabolic channeling

Protein-protein interactions are operative at almost every level of cell structure and function as, for example, formation of sub-cellular organelles, packaging of chromatin, muscle contraction, signal transduction, and regulation of gene expression. Public databases of reported protein-protein interactions comprise hundreds of thousands interactions, and this number is steadily growing. Elucidating the implications of protein-protein interactions for the regulation of the underlying cellular or extra-cellular reaction network remains a great challenge for computational biochemistry. In this work, we have undertaken a systematic and comprehensive computational analysis of reported enzyme-enzyme interactions in the metabolic networks of the model organisms Escherichia coli and Saccharomyces cerevisiae. We grouped all enzyme pairs according to the topological distance that the catalyzed reactions have in the metabolic network and performed a statistical analysis of reported enzyme-enzyme interactions within these groups. We found a higher frequency of reported enzyme-enzyme interactions within the group of enzymes catalyzing reactions that are adjacent in the network, i.e. sharing at least one metabolite. As some of these interacting enzymes have already been implicated in metabolic channeling our analysis may provide a useful screening for candidates of this phenomenon. To check for a possible regulatory role of interactions between enzymes catalyzing non-neighboring reactions, we determined potentially regulatory enzymes using connectivity in the network and absolute change of Gibbs free energy. Indeed a higher portion of reported interactions pertain to such potentially regulatory enzymes.

Molecular dioxygen enters the active site of 12/15-lipoxygenase via dynamic oxygen access channels

Cells contain numerous enzymes that use molecular oxygen for their reactions. Often, their active sites are buried deeply inside the protein, which raises the question whether there are specific access channels guiding oxygen to the site of catalysis. Choosing 12/15-lipoxygenase as a typical example for such oxygen-dependent enzymes, we determined the oxygen distribution within the protein and defined potential routes for oxygen access. For this purpose, we have applied an integrated strategy of structural modeling, molecular dynamics simulations, site-directed mutagenesis, and kinetic measurements. First, we computed the 3D free-energy distribution for oxygen, which led to identification of four oxygen channels in the protein. All channels connect the protein surface with a region of high oxygen affinity at the active site. This region is localized opposite to the nonheme iron providing a structural explanation for the reaction specificity of this lipoxygenase isoform. The catalytically most relevant path can be obstructed by L367F exchange, which leads to a strongly increased Michaelis constant for oxygen. The blocking mechanism is explained in detail by reordering the hydrogen-bonding network of water molecules. Our results provide strong evidence that the main route for oxygen access to the active site of the enzyme follows a channel formed by transiently interconnected cavities whereby the opening and closure are governed by side chain dynamics.

Including metabolite concentrations into flux balance analysis: thermodynamic realizability as a constraint on flux distributions in metabolic networks

BACKGROUND

In recent years, constrained optimization - usually referred to as flux balance analysis (FBA) - has become a widely applied method for the computation of stationary fluxes in large-scale metabolic networks. The striking advantage of FBA as compared to kinetic modeling is that it basically requires only knowledge of the stoichiometry of the network. On the other hand, results of FBA are to a large degree hypothetical because the method relies on plausible but hardly provable optimality principles that are thought to govern metabolic flux distributions.

RESULTS

To augment the reliability of FBA-based flux calculations we propose an additional side constraint which assures thermodynamic realizability, i.e. that the flux directions are consistent with the corresponding changes of Gibb's free energies. The latter depend on metabolite levels for which plausible ranges can be inferred from experimental data. Computationally, our method results in the solution of a mixed integer linear optimization problem with quadratic scoring function. An optimal flux distribution together with a metabolite profile is determined which assures thermodynamic realizability with minimal deviations of metabolite levels from their expected values. We applied our novel approach to two exemplary metabolic networks of different complexity, the metabolic core network of erythrocytes (30 reactions) and the metabolic network iJR904 of Escherichia coli (931 reactions). Our calculations show that increasing network complexity entails increasing sensitivity of predicted flux distributions to variations of standard Gibb's free energy changes and metabolite concentration ranges. We demonstrate the usefulness of our method for assessing critical concentrations of external metabolites preventing attainment of a metabolic steady state.

CONCLUSION

Our method incorporates the thermodynamic link between flux directions and metabolite concentrations into a practical computational algorithm. The weakness of conventional FBA to rely on intuitive assumptions about the reversibility of biochemical reactions is overcome. This enables the computation of reliable flux distributions even under extreme conditions of the network (e.g. enzyme inhibition, depletion of substrates or accumulation of end products) where metabolite concentrations may be drastically altered.

METANNOGEN: compiling features of biochemical reactions needed for the reconstruction of metabolic networks

Background

One central goal of computational systems biology is the mathematical modelling of complex metabolic reaction networks. The first and most time-consuming step in the development of such models consists in the stoichiometric reconstruction of the network, i. e. compilation of all metabolites, reactions and transport processes relevant to the considered network and their assignment to the various cellular compartments. Therefore an information system is required to collect and manage data from different databases and scientific literature in order to generate a metabolic network of biochemical reactions that can be subjected to further computational analyses.

Results

The computer program METANNOGEN facilitates the reconstruction of metabolic networks. It uses the well-known database of biochemical reactions KEGG of biochemical reactions as primary information source from which biochemical reactions relevant to the considered network can be selected, edited and stored in a separate, user-defined database. Reactions not contained in KEGG can be entered manually into the system. To aid the decision whether or not a reaction selected from KEGG belongs to the considered network METANNOGEN contains information of SWISSPROT and ENSEMBL and provides Web links to a number of important information sources like METACYC, BRENDA, NIST, and REACTOME. If a reaction is reported to occur in more than one cellular compartment, a corresponding number of reactions is generated each referring to one specific compartment. Transport processes of metabolites are entered like chemical reactions where reactants and products have different compartment attributes. The list of compartmentalized biochemical reactions and membrane transport processes compiled by means of METANNOGEN can be exported as an SBML file for further computational analysis. METANNOGEN is highly customizable with respect to the content of the SBML output file, additional data-fields, the graphical input form, highlighting of project specific search terms and dynamically generated Web-links.

Conclusion

METANNOGEN is a flexible tool to manage information for the design of metabolic networks. The program requires Java Runtime Environment 1.4 or higher and about 100 MB of free RAM and about 200 MB of free HD space. It does not require installation and can be directly Java-webstarted from .

Computational analysis of protein-protein interactions in metabolic networks of Escherichia coli and yeast

Protein-protein interactions are operative at almost every level of cell function. In the recent years high-throughput methods have been increasingly used to uncover protein-protein interactions at genome scale resulting in interaction maps for entire organisms. However, biochemical implications of high-throughput interactions are not always obvious. The question arises whether all interactions detected by in vitro experiments also play a functional role in the living cell. In this work we systematically analyze high-throughput protein-protein interactions stored in public databases in the context of metabolic networks. Classifying reaction pairs according to their topological distance revealed a significantly higher frequency of enzyme-enzyme interactions for directly neighbored reactions (distance = 1). To determine possible functional implications for these interactions we examined randomized networks using original enzyme interactions as well as randomly generated interaction data. A functional relevance of enzyme-enzyme interactions could be demonstrated for those reactions that exhibit low connectivity. As this is a characteristic of enzyme pairs in metabolic channeling we systematically searched the literature and indeed recovered a certain fraction of enzyme pairs that has already been implicated in metabolic channeling. However, a substantial number of enzyme pairs uncovered by our large-scale analysis remains that up to now has neither been functionally nor structurally classified and therefore present novel candidates of the metabolic channeling concept.

Pruning genome-scale metabolic models to consistent ad functionem networks

Metabolic networks represent a set of reactions and associated metabolites that may occur in a given cell or tissue. They are frequently reconstructed from pure genomic data without thorough biochemical validation. Such genome-scale metabolic networks may thus either lack relevant or contain non-existent reactions and metabolites. Filling gaps and removing falsely predicted reactions can be a cumbersome procedure. On the other hand, using the network to build mathematical models addressing a specific problem (e.g. analyzing changes in the level of cellular ATP at substrate depletion) it may turn out that the network comprises more reactions and metabolites than actually needed or, on the contrary, that essential reactions are missing. Therefore, we propose a method to prune the whole network to a smaller sub-network which contains no dead ends and blocked reactions, i.e reactions that may neither proceed in forward nor backward direction. Inspection of this reduced network reveals its actual functional capabilities in terms of producible metabolites. We apply our method to a genome-scale metabolic network of E. coli. Depending on the choice of the exchangeable metabolites, composition of the external medium, and type of thermodynamic constraints we obtain different reduced network variants that may serve as a basis for flux balance models.

Composition of metabolic flux distributions by functionally interpretable minimal flux modes (MinModes)

All cellular functions are ultimately linked to the metabolism which constitutes a highly branched network of thousands of enzyme-catalyzed chemical reactions and carrier-mediated transport processes. Depending on the prevailing functions (e.g. detoxification of a toxin or accumulation of biomass) the distribution of fluxes in the metabolic network may vary considerably. To better reveal and quantify this flux-function relationship we propose a novel computational approach which identifies distinct contributions--so called minimal flux modes (short: MinModes)--to a stationary flux distribution in the network. Each of these contributions is characterized by a single metabolic output. A MinMode is a minimal (according to a defined cost function) steady state flux distribution that enables the production of a single metabolite. We apply this concept to a metabolic network of Methylobacterium extorquens AM1 comprising of 95 reactions and 74 metabolites, 17 of these metabolites entering the biomass of the bacterium and are thus considered as the metabolic output of the network. MinModes represent a manageable set of fundamental flux modes in the network having a clear physiological meaning and--although not representing a basis in strict mathematical sense - provide a satisfactory approximation of the overall flux distribution in cases tested so far.

Quantifying the Contribution of Defective Ribosomal Products to Antigen Production: A Model-Based Computational Analysis

Antigenic peptides (epitopes) presented on the cell surface by MHC class I molecules derive from proteolytic degradation of endogenous proteins. Some recent studies have proposed that the majority of epitopes stem from so-called defective ribosomal products (DRiPs), i.e., freshly synthesized proteins that are unable to adopt the native conformation and thus undergo immediate degradation. However, a reliable computational analysis of the data underlying this hypothesis was lacking so far. Therefore, we have applied kinetic modeling to derive from existing kinetic data (Princiotta et al. 2003, Immunity 18, 343-354) the rates of the major processes involved in the cellular protein turnover and MHC class I-mediated Ag presentation. From our modeling approach, we conclude that in these experiments 1) the relative share of DRiPs in the total protein synthesis amounted to approximately 10% thus being much lower than reported so far, 2) DRiPs may become the decisive source of epitopes within an early phase after onset of the synthesis of a long-lived (e.g., virus derived) protein, and 3) inhibition of protein synthesis by the translation inhibitor cycloheximide appears to be paralleled with an instantaneous decrease of protein degradation down to approximately 1/3 of the normal value.

Structural biology of mammalian lipoxygenases: Enzymatic consequences of targeted alterations of the protein structure

Lipoxygenases form a heterogeneous family of lipid peroxidizing enzymes, which have been implicated in the pathogenesis of diseases with major health political relevance (bronchial asthma, atherosclerosis, cancer, and osteoporosis). The crystal structures of one mammalian lipoxygenase and of two plant isoenzymes have been solved and the structural bases of important enzyme properties (reaction specificity, membrane binding, and suicidal inactivation) have been investigated in the past. This review will briefly summarize our current understanding on the structural biology of the most important mammalian lipoxygenase isoforms and will also address selected mechanistic features of the lipoxygenase reaction.

The generalized flux-minimization method and its application to metabolic networks affected by enzyme deficiencies

The flux-minimization method [Holzhütter, H.G., 2004. The principle of flux-minimization and its application to calculate stationary fluxes in metabolic networks. Eur. J. Biochem. 271, 2905-2922] has been proposed as an alternative to kinetic modeling to calculate stationary fluxes in metabolic networks. Here a generalization of this method is proposed that takes into account possible limitations of internal fluxes, e.g. due to enzyme defects or partial inhibition of enzyme activities by drugs. The generalized method consists in the minimization of an objective function which expresses the compromise that has to be made between minimization of internal fluxes on one hand and maintenance of the metabolic output required for various cellular functions on the other. Fulfillment of the latter condition is measured through a fitness function, which evaluates the relative deviation of the output fluxes from demanded target values. The method is applied to assess the metabolic consequences caused by a deficiency of enzymes involved in the metabolism of erythrocytes. The obtained results are in good agreement with those obtained on the basis of a comprehensive kinetic model.

Dual role of oxygen during lipoxygenase reactions

Studying the oxygenation kinetics of (19R/S,5Z,8Z,11Z,14Z)-19-hydroxyeicosa-5,8,11,14-tetraenoic acid (19-OH-AA) by rabbit 15-lipoxygenase-1 we observed a pronounced oxygen dependence of the reaction rate, which was not apparent with arachidonic acid as substrate. Moreover, we found that peroxide-dependent activation of the lipoxygenase depended strongly on the oxygen concentration. These data can be described with a kinetic model that extends previous schemes of the lipoxygenase reaction in three essential aspects: (a) the product of 19-OH-AA oxygenation is a less effective lipoxygenase activator than (13S,9Z,11E)-13-hydroperoxyoctadeca-9,11-dienoic acid; (b) molecular dioxygen serves not only as a lipoxygenase substrate, but also impacts peroxide-dependent enzyme activation; (c) there is a leakage of radical intermediates from the catalytic cycle, which leads to the formation of inactive ferrous lipoxygenase. This enzyme inactivation can be reversed by another round of peroxide-dependent activation. Taken together our data indicate that both peroxide activation and the oxygen affinity of lipoxygenases depend strongly on the chemistry of the lipid substrate. These findings are of biological relevance as variations of the reaction conditions may turn the lipoxygenase reaction into an efficient source of free radicals.

Computational design of reduced metabolic networks

Cellular functions are based on thousands of chemical reactions and transport processes, most of them being catalysed and regulated by specific proteins. Systematic gene knockouts have provided evidence that this complex reaction network possesses considerable redundancy, that is, alternative routes exist along which signals and metabolic fluxes may be directed to accomplish an identical output behaviour. This property is of particular importance in cases where parts of the reaction network are transiently or permanently impaired, for example, due to an infection or genetic alterations. Here we present a computational concept to determine enzyme-reduced metabolic networks that are still sufficient to accomplish a given set of cellular functions. Our approach consists of defining an objective function that expresses the compromise that has to be made between successive reduction of the network by omission of enzymes and its decreasing thermodynamic and kinetic feasibility. Optimisation of this objective function results in a linear mixed-integer program. With increasing weight given to the reduction of the number of enzymes, the total flux in the network increases and some of the reactions have to proceed in thermodynamically unfavourable directions. The approach was applied to two metabolic schemes: the energy and redox metabolism of red blood cells and the carbon metabolism of Methylobacterium extorquens. For these two example networks, we determined various variants of reduced networks differing in the number and types of disabled enzymes and disconnected reactions. Using a comprehensive kinetic model of the erythrocyte metabolism, we assess the kinetic feasibility of enzyme-reduced subnetworks. The number of enzymes predicted to be indispensable amounts to 14 (out of 28) for the erythrocyte scheme and 13 (out of 77) for the bacterium scheme, the largest group of enzymes predicted to be simultaneously dispensable amounts to 3 and 37 for these two systems. Our approach might contribute to identifying potential target enzymes for rational drug design, to rationalising gene-expression profiles of metabolic enzymes and to designing synthetic networks with highly specialised metabolic functions.

Combining bioinformatics resources for the structural modelling of eukaryotic metabolic networks

The architecture of the cellular metabolic network is almost completely available from several databases. This has paved the way for computational analyses. Whereas kinetic modelling is still restrained to small metabolic sub-systems for which enzyme-kinetic details are known, so-called structural modelling techniques can be applied to complete metabolic networks even if the kinetics and regulation of the underlying enzymes is still unknown. Structural modelling requires detailed information on the presence of metabolic enzymes in a specific cell type of interest and the thermodynamics of the reactions, determining their direction under cellular conditions. If compartments are distinguished the sub-cellular compartmentation of reactions and enzymes and the membrane transporters exchanging metabolites between cellular compartments must be included. All this information cannot be taken from a single data base but has to be compiled from various Bioinformatics resources. Here we present an approach towards the organization of Bioinformatics data that enables the flux-balance analysis of comprehensive compartmentalized metabolic networks of eukaryotic cells with special focus on human hepatocytes.

Both lysine-clusters of the NH2-terminal prion-protein fragment PrP23-110 are essential for t-PA mediated plasminogen activation

We have recently shown that the NH(2)-terminal fragment (PrP23-110) of the human cellular prion protein (PrP(c) ) stimulates t-PA mediated plasminogen activation. PrP23-110 contains an N-terminal lysine cluster (LC1; K(23),K(24), K(27)) and a C-terminal one (LC2; K(101),K(104),K(106),K(110)). To study their biological function we have substituted all lysine residues of each cluster by alanine and generated the recombinant PrP proteins PrP23-110sLC1 and PrP23-110sLC2. The ability of the mutant proteins to stimulate plasminogen activation was assayed. We found that both lysine clusters are essential for t-PA mediated plasminogen activation. We further studied the binding of soluble PrP23-110 to immobilized t-PA or plasminogen using surface plasmon resonance. The recorded binding curves could not be modeled by classical 1:1 binding kinetics suggesting oligomerisation of PrP23-110. Further plasmon resonance studies show that indeed PrP23-110 binds to itself and that glycosaminoglycans modify this interaction. Binding of t-PA or plasminogen to PrP23-110 was no longer influenced by glycosaminoglycans when PrP23-110 was immobilized on the chip surface. Thus a possible role of heparin as a cofactor in the stimulation of plasminogen activation by t-PA could be the generation of a PrP23-110 form with both lysine clusters accessible for binding of t-PA and plasminogen.

The principle of flux minimization and its application to estimate stationary fluxes in metabolic networks

Cellular functions are ultimately linked to metabolic fluxes brought about by thousands of chemical reactions and transport processes. The synthesis of the underlying enzymes and membrane transporters causes the cell a certain 'effort' of energy and external resources. Considering that those cells should have had a selection advantage during natural evolution that enabled them to fulfil vital functions (such as growth, defence against toxic compounds, repair of DNA alterations, etc.) with minimal effort, one may postulate the principle of flux minimization, as follows: given the available external substrates and given a set of functionally important 'target' fluxes required to accomplish a specific pattern of cellular functions, the stationary metabolic fluxes have to become a minimum. To convert this principle into a mathematical method enabling the prediction of stationary metabolic fluxes, the total flux in the network is measured by a weighted linear combination of all individual fluxes whereby the thermodynamic equilibrium constants are used as weighting factors, i.e. the more the thermodynamic equilibrium lies on the right-hand side of the reaction, the larger the weighting factor for the backward reaction. A linear programming technique is applied to minimize the total flux at fixed values of the target fluxes and under the constraint of flux balance (= steady-state conditions) with respect to all metabolites. The theoretical concept is applied to two metabolic schemes: the energy and redox metabolism of erythrocytes, and the central metabolism of Methylobacterium extorquens AM1. The flux rates predicted by the flux-minimization method exhibit significant correlations with flux rates obtained by either kinetic modelling or direct experimental determination. Larger deviations occur for segments of the network composed of redundant branches where the flux-minimization method always attributes the total flux to the thermodynamically most favourable branch. Nevertheless, compared with existing methods of structural modelling, the principle of flux minimization appears to be a promising theoretical approach to assess stationary flux rates in metabolic systems in cases where a detailed kinetic model is not yet available.

Identifying MHC class I epitopes by predicting the TAP transport efficiency of epitope precursors

We are able to make reliable predictions of the efficiency with which peptides of arbitrary lengths will be transported by TAP. The pressure exerted by TAP on Ag presentation thus can be assessed by checking to what extent MHC class I (MHC-I)-presented epitopes can be discriminated from random peptides on the basis of predicted TAP transport efficiencies alone. Best discriminations were obtained when N-terminally prolonged epitope precursor peptides were included and the contribution of the N-terminal residues to the score were down-weighted in comparison with the contribution of the C terminus. We provide evidence that two factors may account for this N-terminal down-weighting: 1) the uncertainty as to which precursors are used in vivo and 2) the coevolution in the C-terminal sequence specificities of TAP and other agents in the pathway, which may vary among the various MHC-I alleles. Combining predictions of MHC-I binding affinities with predictions of TAP transport efficiency led to an improved identification of epitopes, which was not the case when predictions of MHC-I binding affinities were combined with predictions of C-terminal cleavages made by the proteasome.

Dermal and inhalation acute toxic class methods: test procedures and biometric evaluations for the Globally Harmonized Classification System

The acute toxic class (ATC) methods were developed for determining LD(50)/LC(50) estimates of chemical substances with significantly fewer animals than needed when applying conventional LD(50)/LC(50) tests. The ATC methods are sequential stepwise procedures with fixed starting doses/concentrations and a maximum of six animals used per dose/concentration. The numbers of dead/moribund animals determine whether further testing is necessary or whether the test is terminated. In recent years we have developed classification procedures for the oral, dermal and inhalation routes of administration by using biometric methods. The biometric approach assumes a probit model for the mortality probability of a single animal and assigns the chemical to that toxicity class for which the best concordance is achieved between the statistically expected and the observed numbers of dead/moribund animals at the various steps of the test procedure. In previous publications we have demonstrated the validity of the biometric ATC methods on the basis of data obtained for the oral ATC method in two-animal ring studies with 15 participants from six countries. Although the test procedures and biometric evaluations for the dermal and inhalation ATC methods have already been published, there was a need for an adaptation of the classification schemes to the starting doses/concentrations of the Globally Harmonized Classification System (GHS) recently adopted by the Organization for Economic Co-operation and Development (OECD). Here we present the biometric evaluation of the dermal and inhalation ATC methods for the starting doses/concentrations of the GHS and of some other international classification systems still in use. We have developed new test procedures and decision rules for the dermal and inhalation ATC methods, which require significantly fewer animals to provide predictions of toxicity classes, that are equally good or even better than those achieved by using the conventional LD(50)/LC(50) methods. In order to cope with rather narrow dose/concentration classes of the GHS we have, as in our previous publications, combined the outcome of all results that can be obtained during testing for the allocation to one of the defined toxicity classes of the GHS. Our results strongly recommend the deletion of the dermal LD(50) and the inhalation LC(50) test as regulatory tests and the adoption of the dermal and inhalation ATC methods as internationally accepted alternatives.

Stimulation of plasminogen activation by recombinant cellular prion protein is conserved in the NH2-terminal fragment PrP23-110

The cellular prion protein (PrP(c)), tissue-type plasminogen activator (t-PA) and plasminogen are expressed in synaptic membranes in vivo. In the central nervous system the fibrinolytic system is associated with excitotoxin-mediated neurotoxicity and Alzheimer's disease. Recently binding of the disease associated isoform of the prion protein (PrP(Sc)) to plasminogen and stimulation of t-PA activity have been reported. In this study the interaction of PrP(c) and plasminogen was investigated using chromogenic assays in vitro. We found that plasmin is able to cleave recombinant PrP(c) at lysine residue 110 generating an NH(2)-terminal truncated molecule that has previously been described as a major product of PrP(c) metabolism. We further characterized the proteolytic fragments with respect to their ability to stimulate plasminogen activation in vitro. Our results show that the NH(2)-terminal part of PrP(c) spanning amino acids 23-110 (PrP23-110) together with low molecular weight heparin stimulates t-PA mediated plasminogen activation in vitro. The apparent rate constant was increased 57 fold in the presence of 800 nM PrP23-110. Furthermore, we compared the stimulation of t-PA activity by PrP(c) and beta-amyloid peptide (1-42). While the activity of the beta-amyloid was independent of low molecular weight heparin, PrP23-110 was approximately 4- and 37 fold more active than beta-amyloid in the absence or presence of low molecular weight heparin. In summary, plasmin cleaves PrP(c) in vitro and the liberated NH(2)-terminal fragment accelerates plasminogen activation. Cleavage of PrP c has previously been reported. Thus cleavage of PrP(c) enhancing plasminogen activation at the cell surface could constitute a regulatory mechanism of pericellular proteolysis.

MAPPP: MHC class I antigenic peptide processing prediction

MAPPP is a bioinformatics tool for the prediction of potential antigenic epitopes presented on the cell surface by major histocompatibility complex class I (MHC I) molecules to CD8 positive T lymphocytes. It combines existing predictions for proteasomal cleavage with peptide anchoring to MHC I molecules.

Hepatitis B virus HBx peptide 116-138 and proteasome activator PA28 compete for binding to the proteasome alpha4/MC6 subunit

PA28 is a modulator of the 20S proteasome. The PA28 binding sites on the 20S proteasome are still not well defined. Using yeast two-hybrid interaction assays and proteasome inactivation kinetics we provide evidence that the proteasome alpha4 subunit is one of the PA28 binding sites. This finding is supported by the observation that a hepatitis B virus X protein-derived polypeptide habouring the alpha4 proteasome subunit binding motif impairs the activation of 20S proteasomes by PA28.

Prediction of temporal gene expression. Metabolic opimization by re-distribution of enzyme activities

A computational approach is used to analyse temporal gene expression in the context of metabolic regulation. It is based on the assumption that cells developed optimal adaptation strategies to changing environmental conditions. Time-dependent enzyme profiles are calculated which optimize the function of a metabolic pathway under the constraint of limited total enzyme amount. For linear model pathways it is shown that wave-like enzyme profiles are optimal for a rapid substrate turnover. For the central metabolism of yeast cells enzyme profiles are calculated which ensure long-term homeostasis of key metabolites under conditions of a diauxic shift. These enzyme profiles are in close correlation with observed gene expression data. Our results demonstrate that optimality principles help to rationalize observed gene expression profiles.

In vitro phototoxicity testing: development and validation of a new concentration response analysis software and biostatistical analyses related to the use of various prediction models

As demonstrated in several validation studies, the dermal phototoxic potential of chemicals in humans can be effectively assessed by in vitro methods. The core of these methods is to monitor dose-response curves of a chemical in the absence and presence of light, to quantify the difference between these two curves by appropriate measures (either the photo-irritancy factor [PIF], or the mean photo effect [MPE]), and to use these measures as predictors of in vivo phototoxicity. We present new concentration-response analysis software for in vitro phototoxicity testing, which runs on current personal computers, and takes into account all the limitations identified when using a former program. We also demonstrate the validity and robustness of this new software by applying it retrospectively to all data available from two phases of the EU/COLIPA validation trial for the 3T3 neutral red update in vitro phototoxicity test. Some frequently raised questions pertaining to the use of prediction models in phototoxicity testing are addressed, including: the necessity of using prediction models based on a cut-off; whether it is justifiable to use sharp prediction cut-off values; whether there is a biostatistical justification for the highest concentration of the test chemical; and whether repeated testing of a chemical is required.

Assessment of proteasomal cleavage probabilities from kinetic analysis of time-dependent product formation

Proteasomes are multicatalytic cellular protease complexes that degrade intracellular proteins into smaller peptides. Proteasomal in vitro digests have revealed that the various peptide bonds of a given substrate are cleaved in a highly selective manner. Regarding the key role of proteasomes as the main supplier of antigenic peptides for MHC class I-mediated antigen presentation, it is important to know to what extent these preferences for specific peptide bonds may vary among proteasomes of different cellular origin and of different subunit composition. Here, we quantify such cleavage rates by means of a kinetic proteasome model that relates the time-dependent changes of the amount of any generated peptide to the rates with which this peptide can be either generated from longer precursor peptides or degraded into smaller successor peptides. Numerical values for these rates are estimated by minimizing the distance between simulated and measured time-courses. The proposed method is applied to kinetic data obtained by combining HPLC fractionation and mass spectrometry (MS) to trace the degradation of two model peptides (pp89-25mer and LLO-27mer) by either the constitutive (T2) or immunoproteasome (T2.27). To convert the intensity of the MS signals into the respective peptide amounts, we use two methods leading to similar results: experimental calibration curves and theoretically determined linear scaling functions based on a novel approach using mass conservation rules. Comparison of the cleavage probabilities and procession rates obtained for the two types of proteasomes reveals that the striking differences between the time-dependent peptide profiles can be accounted for mainly by a generally higher turnover rate of the immunoproteasome. For the pp89-25mer, there is no significant change of the cleavage probabilities for any of the ten observed cleavage sites. For the LLO-27mer, there appears to be a significant change in the cleavage probabilities for four of the nine observed cleavage sites when switching from the constitutive to the immunoproteasome.

Identification of HLA-B27-restricted peptides from the Chlamydia trachomatis proteome with possible relevance to HLA-B27-associated diseases

The association of HLA-B27 with ankylosing spondylitis and reactive arthritis is the strongest one known between an MHC class I Ag and a disease. We have searched the proteome of the bacterium Chlamydia trachomatis for HLA-B27 binding peptides that are stimulatory for CD8(+) cells both in a model of HLA-B27 transgenic mice and in patients. This was done by combining two biomathematical computer programs, the first of which predicts HLA-B27 peptide binding epitopes, and the second the probability of HLA-B27 peptide generation by the proteasome system. After preselection, immunodominant peptides were identified by Ag-specific flow cytometry. Using this approach we have identified for the first time nine peptides derived from different C. trachomatis proteins that are stimulatory for CD8(+) T cells. Eight of these nine murine-derived peptides were recognized by cytotoxic T cells. The same strategy was used to identify B27-restricted chlamydial peptides in three patients with reactive arthritis. Eleven peptides were found to be stimulatory for patient-derived CD8(+) T cells, of which eight overlapped those found in mice. Additionally, we applied the tetramer technology, showing that a B27/chlamydial peptide containing one of the chlamydial peptides stained CD8(+) T cells in patients with Chlamydia-induced arthritis. This comprehensive approach offers the possibility of clarifying the pathogenesis of B27-associated diseases.

Stochastic simulation of hemagglutinin-mediated fusion pore formation

Studies on fusion between cell pairs have provided evidence that opening and subsequent dilation of a fusion pore are stochastic events. Therefore, adequate modeling of fusion pore formation requires a stochastic approach. Here we present stochastic simulations of hemagglutinin (HA)-mediated fusion pore formation between HA-expressing cells and erythrocytes based on numerical solutions of a master equation. The following elementary processes are taken into account: 1) lateral diffusion of HA-trimers and receptors, 2) aggregation of HA-trimers to immobilized clusters, 3) reversible formation of HA-receptor contacts, and 4) irreversible conversion of HA-receptor contacts into stable links between HA and the target membrane. The contact sites between fusing cells are modeled as superimposed square lattices. The model simulates well the statistical distribution of time delays measured for the various intermediates of fusion pore formation between cell-cell fusion complexes. In particular, these are the formation of small ion-permissive and subsequent lipid-permissive fusion pores detected experimentally (R. Blumenthal, D. P. Sarkar, S. Durell, D. E. Howard, and S. J., J. Cell Biol. 135:63-71). Moreover, by averaging the simulated individual stochastic time courses across a larger population of cell-cell-complexes the model also provides a reasonable description of kinetic measurements on lipid mixing in cell suspensions (T. Danieli, S. L. Pelletier, Y.I. Henis, and J. M. White, 1996, J. Cell Biol. 133:559-569).

A compartment model to calculate time-dependent concentration profiles of topically applied chemical compounds in the anterior compartments of the rabbit eye

Hitherto, none of the existing in vitro methods has been convincingly demonstrated to be suitable as a replacement for the Draize rabbit eye irritation test. We examine the hypothesis that one reason for this is that insufficient consideration has been given to the differences in the effective concentrations at which chemicals operate in vitro and in vivo. When a chemical is applied topically to the eye, the strength of the observed irritation that it elicits depends both on its toxic potential toward cells or tissues, and its effective concentration in the tissues of the eye. Most of the existing in vitro methods are based on isolated cells or tissues, and thus may be useful in assessing the cytotoxic potentials of chemicals. However, a reliable approach to assessing the effective concentrations of chemicals within the various tissues of the eye is lacking. A simplified compartment model is presented for calculating the time-dependent, intra-ocular concentration profiles of topically applied chemicals. The model encompasses the outer surface of the eye, three distinct segments of the cornea (subdivided into the epithelium, stroma and endothelium) and the conjunctiva. Transport through the membranes of these compartments is described as passive diffusion. For the transport coefficients, rate equations are established that contain, as free parameters, the molecular size and the partition coefficient of the chemical, as well as some intrinsic membrane parameters, such as thickness, viscosity and pore density. Numerical values for the unknown membrane parameters were estimated by fitting the theoretical rate equations to measured permeability coefficients. The compartment model was applied to an independent set of 52 test chemicals compiled from the European Commission/UK Home Office validation study. The calculated passage times (required to let 95% of the chemical reach the posterior eye tissues) varied between 0.33 minutes and 50.6 minutes, and are generally much shorter than the typical duration of observed impairments in the cornea or conjunctiva. This finding suggests that short-term contacts of the eye tissues with a chemical are sufficient to elicit long-term eye irritation. An example is given, showing how the conventional approach of using in vitro endpoints as predictors of eye irritation can be improved significantly by incorporating into the prediction the calculated intra-ocular concentration of a chemical.

Human T cell responses to endogenously presented HLA-A*0201 restricted peptides of Simian virus 40 large T antigen

Presence of the simian virus 40 (SV40) has recently been demonstrated in a relatively high percentage of human mesotheliomas and it is associated with the development of these malignancies in pleural cavities. Therefore, we have initiated a study to identify candidate peptides presented by the human HLA-A*0201 molecule for vaccination approaches against SV40 and monitoring of SV40 directed human immune responses. Initial screening of SV40 large T (Tag) domains required for transformation of cells for HLA-A*0201 binding motifs revealed ten possible binding peptides. Screening of these candidate peptides showed that seven of the ten peptides could bind and stabilize HLA-A*0201 molecules. In an in vitro immunization assay the two peptides with the highest binding affinity for HLA-A*0201, Tag aa 396-405 and aa 577-585, were tested for their ability to induce peptide specific cytotoxic T cells in two healthy donors. One donor developed cytotoxic T cells against Tag aa 396-405 and in T cell cultures of both donors Tag aa 577-585 specific T cells were initiated. The T cells against Tag aa 577-585 not only recognized and killed peptide pulsed cells, but, most importantly, SV40 transformed human mesothelial cells. This is the first demonstration of the induction of SV40 specific human cytotoxic T lymphocytes that recognize endogenously processed peptides from SV40. This peptide identification study opens the possibility to investigate immune responses against SV40 in mesothelioma patients and in individuals exposed to SV40.

Macrophage cholesteryl ester hydrolases and hormone-sensitive lipase prefer specifically oxidized cholesteryl esters as substrates over their non-oxidized counterparts

The oxidative modification of low-density lipoprotein (LDL) has been implicated as a pro-atherogenic process in the pathogenesis of atherosclerosis. Macrophages rapidly take up oxidized LDL via scavenger-receptor-mediated pathways and thereby develop into lipid-laden foam cells. The uptake mechanism has been studied extensively and several types of scavenger receptors have been identified. In contrast, the intracellular fate of oxidized LDL lipids is less well investigated. We studied the degradation of specifically oxidized cholesteryl esters by murine macrophages using an HPLC-based assay, and found that oxidized substrates are hydrolysed preferentially from a 1:1 molar mixture of oxidized and non-oxidized cholesteryl esters. This effect was observed at both neutral and acidic pH. Similar results were obtained with lysates of human monocytes and with pure recombinant human hormone-sensitive lipase. These data suggest that the intracellular oxidation of cholesteryl esters may facilitate intracellular cholesteryl ester hydrolysis, and thus may represent an anti-atherogenic process.

Kinetic evidences for facilitation of peptide channelling by the proteasome activator PA28

The activation kinetics of constitutive and IFNgamma-stimulated 20S proteasomes obtained with homomeric (recPA28alpha, recPA28beta) and heteromeric (recPA28alphabeta) forms of recombinant 11S regulator PA28 was analysed by means of kinetic modelling. The activation curves obtained with increasing concentrations of the individual PA28 subunits (RecP28alpha/RecP28beta/RecP28alpha + RecP28beta) exhibit biphasic characteristics which can be attributed to a low-level activation by PA28 monomers and full proteasome activation by assembled activator complexes. The dissociation constants do not reveal significant differences between the constitutive and the immunoproteasome. Intriguingly, the affinity of the proteasome towards the recPA28alphabeta complex is about two orders of magnitude higher than towards the homomeric PA28alpha and PA28beta complexes. Striking similarities can been revealed in the way how PA28 mediates the kinetics of latent proteasomes with respect to three different fluorogenic peptides probing the chymotrypsin-like, trypsin-like and peptidylglutamyl-peptide hydrolyzing like activity: (a) positive cooperativity disappears as indicated by a lack of sigmoid initial parts of the kinetic curves, (b) substrate affinity is increased, whereby (c), the maximal activity remains virtually constant. As these kinetic features are independent of the peptide substrates, we conclude that PA28 exerts its activating influence on the proteasome by enhancing the uptake (and release) of shorter peptides.

A kinetic model of vertebrate 20S proteasome accounting for the generation of major proteolytic fragments from oligomeric peptide substrates

There is now convincing evidence that the proteasome contributes to the generation of most of the peptides presented by major histocompatibility complex class I molecules. Here we present a model-based kinetic analysis of fragment patterns generated by the 20S proteasome from 20 to 40 residues long oligomeric substrates. The model consists of ordinary first-order differential equations describing the time evolution of the average probabilities with which fragments can be generated from a given initial substrate. First-order rate laws are used to describe the cleavage of peptide bonds and the release of peptides from the interior of the proteasome to the external space. Numerical estimates for the 27 unknown model parameters are determined across a set of five different proteins with known cleavage patterns. Testing the validity of the model by a jack knife procedure, about 80% of the observed fragments can be correctly identified, whereas the abundance of false-positive classifications is below 10%. From our theoretical approach, it is inferred that double-cleavage fragments of length 7-13 are predominantly cut out in "C-N-order" in that the C-terminus is generated first. This is due to striking differences in the further processing of the two fragments generated by the first cleavage. The upstream fragment exhibits a pronounced tendency to escape from second cleavage as indicated by a large release rate and a monotone exponential decline of peptide bond accessibility with increasing distance from the first scissile bond. In contrast, the release rate of the downstream fragment is about four orders of magnitude lower and the accessibility of peptide bonds shows a sharp peak in a distance of about nine residues from the first scissile bond. This finding strongly supports the idea that generation of fragments with well-defined lengths is favored in that temporary immobilization of the downstream fragment after the first cleavage renders it susceptible for a second cleavage.

Rapid flip-flop of phospholipids in endoplasmic reticulum membranes studied by a stopped-flow approach

The transbilayer movement of short-chain spin-labeled and fluorescent 7-nitrobenz-2-oxa-1,3-diazol-4-yl (NBD) phospholipid analogs in rat liver microsomes is measured by stopped-flow mixing of labeled microsomes with bovine serum albumin (BSA) solution. Extraction of analogs from the outer leaflet of microsomes to BSA can be directly monitored in conjunction with electron paramagnetic resonance or fluorescence spectroscopy by taking advantage of the fact that the signal of spin-labeled or fluorescent analogs bound to BSA is different from that of the analogs inserted into membranes. From the signal kinetics, the transbilayer movement and the distribution of analogs in microsomal membranes can be derived provided the extraction of analogs by BSA is much faster in comparison to the transbilayer movement of analogs. Half-times of the back-exchange for spin-labeled and fluorescent analogs were <3.5 and <9.5 s, respectively. The unprecedented time resolution of the assay revealed that the transbilayer movement of spin-labeled analogs is much faster than previously reported. The half-time of the movement was about 16 s or even less at room temperature. Transmembrane movement of NBD-labeled analogs was six- to eightfold slower than that of spin-labeled analogs.

How an inhibitor of the HIV-I protease modulates proteasome activity

The human immunodeficiency virus, type I protease inhibitor Ritonavir has been used successfully in AIDS therapy for 4 years. Clinical observations suggested that Ritonavir may exert a direct effect on the immune system unrelated to inhibition of the human immunodeficiency virus, type I protease. In fact, Ritonavir inhibited the major histocompatibility complex class I restricted presentation of several viral antigens at therapeutically relevant concentrations (5 microM). In search of a molecular target we found that Ritonavir inhibited the chymotrypsin-like activity of the proteasome whereas the tryptic activity was enhanced. In this study we kinetically analyzed how Ritonavir modulates proteasome activity and what consequences this has on cellular functions of the proteasome. Ritonavir is a reversible effector of proteasome activity that protected the subunits MB-1 (X) and/or LMP7 from covalent active site modification with the vinyl sulfone inhibitor(125)I-NLVS, suggesting that they are the prime targets for competitive inhibition by Ritonavir. At low concentrations of Ritonavir (5 microM) cells were more sensitive to canavanine but proliferated normally whereas at higher concentrations (50 microM) protein degradation was affected, and the cell cycle was arrested in the G(1)/S phase. Ritonavir thus modulates antigen processing at concentrations at which vital cellular functions of the proteasome are not yet severely impeded. Proteasome modulators may hence qualify as therapeutics for the control of the cytotoxic immune response.

The inhibition of mammalian 15-lipoxygenases by the anti-inflammatory drug ebselen: dual-type mechanism involving covalent linkage and alteration of the iron ligand sphere

Mammalian lipoxygenases have been implicated in inflammation and atherosclerosis and, thus, lipoxygenase inhibitors may be of pharmacological interest. In cells, lipoxygenases occur in a catalytically silent ground state that requires activation to become active. We found that the seleno-organic drug ebselen [2-phenyl-1, 2-benzisoselenazol-3(2H)-one], which exhibits anti-inflammatory properties, irreversibly inhibited pure rabbit 15-lipoxygenase, with an IC50 in the nM range when preincubated with the enzyme in the absence of fatty acid substrates. Subsequent dialysis, gel filtration, or substrate addition did not restore the enzyme activity, and experiments with [14C]ebselen indicated a covalent linkage of the drug. The presence of sulfhydryl compounds in the incubation mixture prevented both enzyme labeling and inactivation, but we did not see any reactivation when sulfhydryl compounds were added afterward. X-ray absorption studies indicated that ebselen did alter the geometry of the iron ligand sphere, and the data are consistent with an iron complexation by the drug. When fatty acid substrate was present during lipoxygenase-ebselen interaction, the inhibitory potency was strongly reduced and a competitive mode of action was observed. These data suggest that ebselen inactivated the catalytically silent ground-state lipoxygenase irreversibly by covalent linkage and alteration of the iron ligand sphere. In contrast, it functions as a competitive inhibitor of the catalytically active enzyme species. The pharmacological relevance of ebselen as a potential in vivo lipoxygenase inhibitor will be discussed.

A theoretical approach towards the identification of cleavage-determining amino acid motifs of the 20 S proteasome

Hitherto the mechanisms controlling the selective cleavage of peptide bonds by the 20 S proteasome have been poorly understood. The observation that peptide bond cleavage may eventually occur at the carboxyl site of either amino acid residue rules out a simple control of cleavage preferences by the P1 residue alone. Here, we follow the rationale that the presence of specific cleavage-determining amino acids motifs (CDAAMs) around the scissile peptide bond are required for the attainment of substrate conformations susceptible to cleavage. We present an exploratory search for these putative motifs based on empirical regression functions relating the cleavage probability for a given peptide bond to some selected side-chain properties of the flanking amino acid residues. Identification of the sequence locations of cleavage-determining residues relative to the scissile bond and of their optimal side-chain properties was carried out by fitting the cleavage probability to (binary) experimental observations on peptide bond cleavage gathered among a set of seven different peptide substrates with known patterns of proteolytic degradation products. In this analysis, all peptide bonds containing the same residue in the P1 position were assumed to be cleaved by the same active sites of the proteasome, and thus to be under control of the same CDAAMs. We arrived at a final set of ten different CDAAMs, accounting for the cleavage of one to five different groups of peptide bonds with an overall predictive correctness of 93 %. The CDAAM is composed of two to four "anchor" positions preferentially located between P5 and P5' around the scissile bond. This implies a length constraint for the usage of cleavage sites, which could considerably suppress the excision of shorter fragments and thus partially explain for the observed preponderance of medium-size cleavage products.

Omega-oxidation impairs oxidizability of polyenoic fatty acids by 15-lipoxygenases: consequences for substrate orientation at the active site

During oxygenation by 15-lipoxygenases, polyenoic fatty acids are bound at the active site in such a way that the omega-terminus of the fatty acids penetrates into the substrate binding pocket. In contrast, for arachidonic acid 5-lipoxygenation, an inverse head to tail orientation has been suggested. However, an inverse orientation may be hindered by the large energy barrier associated with burying the charged carboxylate group in the hydrophobic environment of the substrate binding cleft. We studied the oxygenation kinetics of omega-modified fatty acids by 15-lipoxygenases and found that omega-hydroxylation strongly impaired substrate affinity (higher Km), but only moderately altered Vmax. In contrast, omega-carboxylation completely prevented the lipoxygenase reaction; however, methylation of the additional carboxylate group restored the activity. Arg403 of the human 15-lipoxygenase has been implicated in fatty acid binding by forming a salt bridge with the carboxylate group, and thus mutation of this amino acid to an uncharged residue was supposed to favour an inverse substrate orientation. The prepared Arg403-->Leu mutant of the rabbit 15-lipoxygenase was found to be a less effective catalyst of linoleic acid oxygenation. However, the oxygenation rate of omega-hydroxyarachidonic acid was similar when the wild-type and mutant enzyme were compared, and the patterns of oxygenation products were identical for both enzyme species. These data suggest that introduction of a polar, or even charged residue, at the omega-terminus of substrate fatty acids in connection with mutation of Arg403 may not alter substrate alignment at the active site of 15-lipoxygenases.

A Study on UV Filter Chemicals from Annex VII of European Union Directive 76/768/EEC, in the In Vitro 3T3 NRU Phototoxicity Test

In 1996, the Scientific Committee on Cosmetology of DGXXIV of the European Commission asked the European Centre for the Validation of Alternative Methods to test eight UV filter chemicals from the 1995 edition of Annex VII of Directive 76/768/EEC in a blind trial in the in vitro 3T3 cell neutral red uptake phototoxicity (3T3 NRU PT) test, which had been scientifically validated between 1992 and 1996. Since all the UV filter chemicals on the positive list of EU Directive 76/768/EEC have been shown not to be phototoxic in vivo in humans under use conditions, only negative effects would be expected in the 3T3 NRU PT test. To balance the number of positive and negative chemicals, ten phototoxic and ten non-phototoxic chemicals were tested under blind conditions in four laboratories. Moreover, to assess the optimum concentration range for testing, information was provided on appropriate solvents and on the solubility of the coded chemicals. In this study, the phototoxic potential of test chemicals was evaluated in a prediction model in which either the Photoirritation Factor (PIF) or the Mean Photo Effect (MPE) were determined. The results obtained with both PIF and MPE were highly reproducible in the four laboratories, and the correlation between in vitro and in vivo data was almost perfect. All the phototoxic test chemicals provided a positive result at concentrations of 1μ/ml, while nine of the ten non-phototoxic chemicals gave clear negative results, even at the highest test concentrations. One of the UV filter chemicals gave positive results in three of the four laboratories only at concentrations greater than 100μ/ml; the other laboratory correctly identified all 20 of the test chemicals. An analysis of the impact that exposure concentrations had on the performance of the test revealed that the optimum concentration range in the 3T3 NRU PT test for determining the phototoxic potential of chemicals is between 0.1μg/ml and 10μg/ml, and that false positive results can be obtained at concentrations greater than 100μg/ml. Therefore, the positive results obtained with some of the UV filter chemicals only at concentrations greater than 100μg/ml do not indicate a phototoxic potential in vivo. When this information was taken into account during calculation of the overall predictivity of the 3T3 NRU PT test in the present study, an almost perfect correlation of in vitro versus in vivo results was obtained (between 95% and 100%), when either PIF or MPE were used to predict the phototoxic potential. The management team and participants therefore conclude that the 3T3 NRU PT test is a valid test for correctly assessing the phototoxic potential of UV filter chemicals, if the defined concentration limits are taken into account.