Towards quantitative prediction of proteasomal digestion patterns of proteins

We discuss the problem of proteasomal degradation of proteins. Though proteasomes are important for all aspects of the cellular metabolism, some details of the physical mechanism of the process remain unknown. We introduce a stochastic model of the proteasomal degradation of proteins, which accounts for the protein translocation and the topology of the positioning of cleavage centers of a proteasome from first principles. For this model we develop the mathematical description based on a master-equation and techniques for reconstruction of the cleavage specificity inherent to proteins and the proteasomal translocation rates, which are a property of the proteasome specie, from mass spectroscopy data on digestion patterns. With these properties determined, one can quantitatively predict digestion patterns for new experimental set-ups. Additionally we design an experimental set-up for a synthetic polypeptide with a periodic sequence of amino acids, which enables especially reliable determination of translocation rates.Comment: 14 pages, 4 figures, submitted to J. Stat. Mech. (Special issue for proceedings of 5th Intl. Conf. on Unsolved Problems on Noise and Fluctuations in Physics, Biology & High Technology, Lyon (France), June 2-6, 2008

Interpretation of non-invasive breath tests using 13C-labeled substrates - a preliminary report with 13C-methacetin

Non-invasive breath tests can serve as valuable diagnostic tools in medicine as they can determine particular enzymatic and metabolic functions in vivo. However, methodological pitfalls have limited the actual clinical application of those tests till today. A major challenge of non-invasive breath tests has remained the provision of individually reliable test results. To overcome these limitations, a better understanding of breath kinetics during non-invasive breaths tests is essential. This analysis compares the breath recovery of a 13C-methacetin breath test with the actual serum kinetics of the substrate. It is shown, that breath and serum kinetics of the same test are significantly different over a period of 60 minutes. The recovery of the tracer 13CO2 in breath seems to be significantly delayed due to intermediate storage in the bicarbonate pool. This has to be taken into account for the application of non-invasive breath test protocols. Otherwise, breath tests might display bicarbonate kinetics despite the metabolic capacity of the particular target enzyme

A novel variant of the 13C-methacetin liver function breath test that eliminates the confounding effect of individual differences in sytemic CO2 kinetics

The principle of dynamic liver function breath tests is founded on the administration of a 13C-labeled drug and subsequent monitoring of 13CO2 in the breath, quantified as time series delta over natural baseline 13CO2 (DOB) liberated from the drug during hepatic CYP-dependent detoxification. One confounding factor limiting the diagnostic value of such tests is that only a fraction of the liberated 13CO2 is immediately exhaled, while another fraction is taken up by body compartments from which it returns with delay to the plasma. The aims of this study were to establish a novel variant of the methacetin-based breath test LiMAx that allows to estimate and to eliminate the confounding effect of systemic 13CO2 distribution on the DOB curve and thus enables a more reliable assessment of the hepatic detoxification capacity compared with the conventional LiMAx test. We designed a new test variant (named "2DOB") consisting of two consecutive phases. Phase 1 is initiated by the intravenous administration of 13C-bicarbonate. Phase 2 starts about 30 min later with the intravenous administration of the 13C-labelled test drug. Using compartment modelling, the resulting 2-phasic DOB curve yields the rate constants for the irreversible elimination and the reversible exchange of plasma 13CO2 with body compartments (phase 1) and for the detoxification and exchange of the drug with body compartments (phase 2). We carried out the 2DOB test with the test drug 13C-methacetin in 16 subjects with chronic liver pathologies and 22 normal subjects, who also underwent the conventional LiMAx test. Individual differences in the systemic CO2 kinetics can lead to deviations up to a factor of 2 in the maximum of DOB curves (coefficient of variation CV ≈ 0.2) which, in particular, may hamper the discrimination between subjects with normal or mildly impaired detoxification capacities. The novel test revealed that a significant portion of the drug is not immediately metabolized, but transiently taken up into a storage compartment. Intriguingly, not only the hepatic detoxification rate but also the storage capacity of the drug, turned out to be indicative for a normal liver function. We thus used both parameters to define a scoring function which yielded an excellent disease classification (AUC = 0.95) and a high correlation with the MELD score (RSpearman = 0.92). The novel test variant 2DOB promises a significant improvement in the assessment of impaired hepatic detoxification capacity. The suitability of the test for the reliable characterization of the natural history of chronic liver diseases (fatty liver-fibrosis-cirrhosis) has to be assessed in further studies

Alterations of Central Liver Metabolism of Pediatric Patients with Non-Alcoholic Fatty Liver Disease

Non-alcoholic fatty liver disease (NAFLD) is the most common chronic liver disease in children and is associated with overweight and insulin resistance (IR). Almost nothing is known about in vivo alterations of liver metabolism in NAFLD, especially in the early stages of non-alcoholic steatohepatitis (NASH). Here, we used a complex mathematical model of liver metabolism to quantify the central hepatic metabolic functions of 71 children with biopsy-proven NAFLD. For each patient, a personalized model variant was generated based on enzyme abundances determined by mass spectroscopy. Our analysis revealed statistically significant alterations in the hepatic carbohydrate, lipid, and ammonia metabolism, which increased with the degree of obesity and severity of NAFLD. Histologic features of NASH and IR displayed opposing associations with changes in carbohydrate and lipid metabolism but synergistically decreased urea synthesis in favor of the increased release of glutamine, a driver of liver fibrosis. Taken together, our study reveals already significant alterations in the NASH liver of pediatric patients, which, however, are differently modulated by the simultaneous presence of IR

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

<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Results</p> <p>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 <url>http://www.bioinformatics.org/fasimu</url> including manual, tutorial, and plugins.</p> <p>Conclusions</p> <p>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.</p

Genetic determinants of steatosis and fibrosis progression in paediatric non‐alcoholic fatty liver disease

BACKGROUND AND AIMS: Non-alcoholic fatty liver disease (NAFLD) is the most common chronic liver disease in children and adolescents today. In comparison with adult disease, paediatric NAFLD may show a periportal localization, which is associated with advanced fibrosis. This study aimed to assess the role of genetic risk variants for histological disease pattern and severity in childhood NAFLD. METHODS: We studied 14 single nucleotide polymorphisms (SNP) in a cohort of 70 adolescents with biopsy-proven NAFLD. Genotype was compared to an adult control cohort (n = 200) and analysed in relation to histological disease severity and liver tissue proteomics. RESULTS: Three of the 14 SNPs were significantly associated with paediatric NAFLD after FDR adjustment, rs738409 (PNPLA3, P = 2.80 × 10-06 ), rs1044498 (ENPP1, P = 0.0091) and rs780094 (GCKR, P = 0.0281). The severity of steatosis was critically associated with rs738409 (OR=3.25; 95% CI: 1.72-6.52, FDR-adjusted P = 0.0070). The strongest variants associated with severity of fibrosis were rs1260326, rs780094 (both GCKR) and rs659366 (UCP2). PNPLA3 was associated with a portal pattern of steatosis, inflammation and fibrosis. Proteome profiling revealed decreasing levels of GCKR protein with increasing carriage of the rs1260326/rs780094 minor alleles and downregulation of the retinol pathway in rs738409 G/G carriers. Computational metabolic modelling highlighted functional relevance of PNPLA3, GCKR and UCP2 for NAFLD development. CONCLUSIONS: This study provides evidence for the role of PNPLA3 as a determinant of portal NAFLD localization and severity of portal fibrosis in children and adolescents, the risk variant being associated with an impaired hepatic retinol metabolism

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

HEPATOKIN1 is a biochemistry-based model of liver metabolism for applications in medicine and pharmacology

The epidemic increase of non-alcoholic fatty liver diseases (NAFLD) requires a deeper understanding of the regulatory circuits controlling the response of liver metabolism to nutritional challenges, medical drugs, and genetic enzyme variants. As in vivo studies of human liver metabolism are encumbered with serious ethical and technical issues, we developed a comprehensive biochemistry-based kinetic model of the central liver metabolism including the regulation of enzyme activities by their reactants, allosteric effectors, and hormone-dependent phosphorylation. The utility of the model for basic research and applications in medicine and pharmacology is illustrated by simulating diurnal variations of the metabolic state of the liver at various perturbations caused by nutritional challenges (alcohol), drugs (valproate), and inherited enzyme disorders (galactosemia). Using proteomics data to scale maximal enzyme activities, the model is used to highlight differences in the metabolic functions of normal hepatocytes and malignant liver cells (adenoma and hepatocellular carcinoma)

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

Partial inhibition and bilevel optimization in flux balance analysis

Motivation: Within Flux Balance Analysis, the investigation of complex subtasks, such as finding the optimal perturbation of the network or finding an optimal combination of drugs, often requires to set up a bilevel optimization problem. In order to keep the linearity and convexity of these nested optimization problems, an ON/OFF description of the effect of the perturbation (i.e. Boolean variable) is normally used. This restriction may not be realistic when one wants, for instance, to describe the partial inhibition of a reaction induced by a drug.Results: In this paper we present a formulation of the bilevel optimization which overcomes the oversimplified ON/OFF modeling while preserving the linear nature of the problem. A case study is considered: the search of the best multi-drug treatment which modulates an objective reaction and has the minimal perturbation on the whole network. The drug inhibition is described and modulated through a convex combination of a fixed number of Boolean variables. The results obtained from the application of the algorithm to the core metabolism of E.coli highlight the possibility of finding a broader spectrum of drug combinations compared to a simple ON/OFF modeling.Conclusions: The method we have presented is capable of treating partial inhibition inside a bilevel optimization, without loosing the linearity property, and with reasonable computational performances also on large metabolic networks. The more fine-graded representation of the perturbation allows to enlarge the repertoire of synergistic combination of drugs for tasks such as selective perturbation of cellular metabolism. This may encourage the use of the approach also for other cases in which a more realistic modeling is required. \ua9 2013 Facchetti and Altafini; licensee BioMed Central Ltd