Large-scale validation of methods for cytotoxic T-lymphocyte epitope prediction

<p>Abstract</p> <p>Background</p> <p>Reliable predictions of Cytotoxic T lymphocyte (CTL) epitopes are essential for rational vaccine design. Most importantly, they can minimize the experimental effort needed to identify epitopes. NetCTL is a web-based tool designed for predicting human CTL epitopes in any given protein. It does so by integrating predictions of proteasomal cleavage, TAP transport efficiency, and MHC class I affinity. At least four other methods have been developed recently that likewise attempt to predict CTL epitopes: EpiJen, MAPPP, MHC-pathway, and WAPP. In order to compare the performance of prediction methods, objective benchmarks and standardized performance measures are needed. Here, we develop such large-scale benchmark and corresponding performance measures and report the performance of an updated version 1.2 of NetCTL in comparison with the four other methods.</p> <p>Results</p> <p>We define a number of performance measures that can handle the different types of output data from the five methods. We use two evaluation datasets consisting of known HIV CTL epitopes and their source proteins. The source proteins are split into all possible 9 mers and except for annotated epitopes; all other 9 mers are considered non-epitopes. In the RANK measure, we compare two methods at a time and count how often each of the methods rank the epitope highest. In another measure, we find the specificity of the methods at three predefined sensitivity values. Lastly, for each method, we calculate the percentage of known epitopes that rank within the 5% peptides with the highest predicted score.</p> <p>Conclusion</p> <p>NetCTL-1.2 is demonstrated to have a higher predictive performance than EpiJen, MAPPP, MHC-pathway, and WAPP on all performance measures. The higher performance of NetCTL-1.2 as compared to EpiJen and MHC-pathway is, however, not statistically significant on all measures. In the large-scale benchmark calculation consisting of 216 known HIV epitopes covering all 12 recognized HLA supertypes, the NetCTL-1.2 method was shown to have a sensitivity among the 5% top-scoring peptides above 0.72. On this dataset, the best of the other methods achieved a sensitivity of 0.64. The NetCTL-1.2 method is available at <url>http://www.cbs.dtu.dk/services/NetCTL</url>.</p> <p>All used datasets are available at <url>http://www.cbs.dtu.dk/suppl/immunology/CTL-1.2.php</url>.</p

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

Breath Biopsy Assessment of Liver Disease Using an Exogenous Volatile Organic Compound-Toward Improved Detection of Liver Impairment.

INTRODUCTION: Liver cirrhosis and its complication - hepatocellular carcinoma (HCC) - have been associated with increased exhaled limonene. It is currently unclear whether this increase is more strongly associated with the presence of HCC or with the severity of liver dysfunction. METHODS: We compared the exhaled breath of 40 controls, 32 cirrhotic patients, and 12 cirrhotic patients with HCC using the Breath Biopsy platform. Breath samples were analyzed by thermal desorption-gas chromatography-mass spectrometry. Limonene levels were compared between the groups and correlated to bilirubin, albumin, prothrombin time international normalized ratio, and alanine aminotransferase. RESULTS: Breath limonene concentration was significantly elevated in subjects with cirrhosis-induced HCC (M: 82.1 ng/L, interquartile range [IQR]: 16.33-199.32 ng/L) and cirrhosis (M: 32.6 ng/L, IQR: 6.55-123.07 ng/L) compared with controls (M: 6.2 ng/L, IQR: 2.62-9.57 ng/L) (P value = 0.0005 and 0.0001, respectively) with no significant difference between 2 diseased groups (P value = 0.37). Levels of exhaled limonene correlated with serum bilirubin (R = 0.25, P value = 0.0016, r = 0.51), albumin (R = 0.58, P value = 5.3e-8, r = -0.76), and international normalized ratio (R = 0.29, P value = 0.0003, r = 0.51), but not with alanine aminotransferase (R = 0.01, P value = 0.36, r = 0.19). DISCUSSION: Exhaled limonene levels are primarily affected by the presence of cirrhosis through reduced liver functional capacity, as indicated by limonene correlation with blood metrics of impaired hepatic clearance and protein synthesis capacity, without further alterations observed in subjects with HCC. This suggests that exhaled limonene is a potential non-invasive marker of liver metabolic capacity (see Visual abstract, Supplementary Digital Content 1, http://links.lww.com/CTG/A388).Owlstone Medical Lt

A Macintosh software package for simulation of human red blood cell metabolism

We have developed a computer software package for Macintosh to simulate the metabolism and hemoglobin binding affinity of human red blood cell. The model is capable of simulating hemoglobin binding of ligands, metabolite concentrations, and metabolic fluxes at physiological steady state and in response to extracellular parameter variations, such as pH, osmolarity, glucose, and adenine concentrations. The kinetic parameters of enzymes, extracellular conditions, and initial intracellular metabolite concentrations can be specified by the user in order to model a particular situation. The software is use friendly, utilizing menu, window, and mouse to interact with the user. It also provides a pathway map of the red cell, which allows a direct access to enzyme kinetics by clicking the enzymes in the map.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/29919/1/0000276.pd

A quick guide for building a successful bioinformatics community

“Scientific community” refers to a group of people collaborating together on scientific-research-related activities who also share common goals, interests, and values. Such communities play a key role in many bioinformatics activities. Communities may be linked to a specific location or institute, or involve people working at many different institutions and locations. Education and training is typically an important component of these communities, providing a valuable context in which to develop skills and expertise, while also strengthening links and relationships within the community. Scientific communities facilitate: (i) the exchange and development of ideas and expertise; (ii) career development; (iii) coordinated funding activities; (iv) interactions and engagement with professionals from other fields; and (v) other activities beneficial to individual participants, communities, and the scientific field as a whole. It is thus beneficial at many different levels to understand the general features of successful, high-impact bioinformatics communities; how individual participants can contribute to the success of these communities; and the role of education and training within these communities. We present here a quick guide to building and maintaining a successful, high-impact bioinformatics community, along with an overview of the general benefits of participating in such communities. This article grew out of contributions made by organizers, presenters, panelists, and other participants of the ISMB/ECCB 2013 workshop “The ‘How To Guide’ for Establishing a Successful Bioinformatics Network” at the 21st Annual International Conference on Intelligent Systems for Molecular Biology (ISMB) and the 12th European Conference on Computational Biology (ECCB)

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

<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Results</p> <p>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 <it>Escherichia coli </it>(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.</p> <p>Conclusion</p> <p>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.</p

Targeting pathogen metabolism without collateral damage to the host

The development of drugs that can inactivate disease-causing cells (e.g. cancer cells or parasites) without causing collateral damage to healthy or to host cells is complicated by the fact that many proteins are very similar between organisms. Nevertheless, due to subtle, quantitative differences between the biochemical reaction networks of target cell and host, a drug can limit the flux of the same essential process in one organism more than in another. We identified precise criteria for this â €network-based' drug selectivity, which can serve as an alternative or additive to structural differences. We combined computational and experimental approaches to compare energy metabolism in the causative agent of sleeping sickness, Trypanosoma brucei, with that of human erythrocytes, and identified glucose transport and glyceraldehyde-3-phosphate dehydrogenase as the most selective antiparasitic targets. Computational predictions were validated experimentally in a novel parasite-erythrocytes co-culture system. Glucose-transport inhibitors killed trypanosomes without killing erythrocytes, neurons or liver cells

Mathematical modeling of intracellular signaling pathways

Dynamic modeling and simulation of signal transduction pathways is an important topic in systems biology and is obtaining growing attention from researchers with experimental or theoretical background. Here we review attempts to analyze and model specific signaling systems. We review the structure of recurrent building blocks of signaling pathways and their integration into more comprehensive models, which enables the understanding of complex cellular processes. The variety of mechanisms found and modeling techniques used are illustrated with models of different signaling pathways. Focusing on the close interplay between experimental investigation of pathways and the mathematical representations of cellular dynamics, we discuss challenges and perspectives that emerge in studies of signaling systems

Cell signalling by reactive lipid species: new concepts and molecular mechanisms

The process of lipid peroxidation is widespread in biology and is mediated through both enzymatic and non-enzymatic pathways. A significant proportion of the oxidized lipid products are electrophilic in nature, the RLS (reactive lipid species), and react with cellular nucleophiles such as the amino acids cysteine, lysine and histidine. Cell signalling by electrophiles appears to be limited to the modification of cysteine residues in proteins, whereas non-specific toxic effects involve modification of other nucleophiles. RLS have been found to participate in several physiological pathways including resolution of inflammation, cell death and induction of cellular antioxidants through the modification of specific signalling proteins. The covalent modification of proteins endows some unique features to this signalling mechanism which we have termed the ‘covalent advantage’. For example, covalent modification of signalling proteins allows for the accumulation of a signal over time. The activation of cell signalling pathways by electrophiles is hierarchical and depends on a complex interaction of factors such as the intrinsic chemical reactivity of the electrophile, the intracellular domain to which it is exposed and steric factors. This introduces the concept of electrophilic signalling domains in which the production of the lipid electrophile is in close proximity to the thiol-containing signalling protein. In addition, we propose that the role of glutathione and associated enzymes is to insulate the signalling domain from uncontrolled electrophilic stress. The persistence of the signal is in turn regulated by the proteasomal pathway which may itself be subject to redox regulation by RLS. Cell death mediated by RLS is associated with bioenergetic dysfunction, and the damaged proteins are probably removed by the lysosome-autophagy pathway

Simfit: A microcomputer software-toolkit for modelistic studies in biochemistry

A software package suitable for personal computers and designed to handle simulation and fitting problems related to the study of biomolecules under pre-steady and steady state conditions is presented, and its overall architecture as well as the implemented algorithms illustrated. The peculiar features of the package are: (i) integrated capability of simulating dynamic models and fitting to them experimental data; (ii) handling of stiff problems; (iii) free use of algebraic as well as differential equations; (iv) objective comparison of models of different complexity. The above features are discussed through a number of examples taken from the direct experience of the authors in enzyme kinetics and ligand binding