The capacity of the liver to convert the metabolic input received from the incoming portal and arterial blood into the metabolic output of the outgoing venous blood has three major determinants: The intra-hepatic blood flow, the transport of metabolites between blood vessels (sinusoids) and hepatocytes and the metabolic capacity of hepatocytes. These determinants are not constant across the organ: Even in the normal organ, but much more pronounced in the fibrotic and cirrhotic liver, regional variability of the capillary blood pressure, tissue architecture and the expression level of metabolic enzymes (zonation) have been reported. Understanding how this variability may affect the regional metabolic capacity of the liver is important for the interpretation of functional liver tests and planning of pharmacological and surgical interventions. Here we present a mathematical model of the sinusoidal tissue unit (STU) that is composed of a single sinusoid surrounded by the space of Disse and a monolayer of hepatocytes. The total metabolic output of the liver (arterio-venous glucose difference) is obtained by integration across the metabolic output of a representative number of STUs. Application of the model to the hepatic glucose metabolism provided the following insights: (i) At portal glucose concentrations between 6-8 mM, an intra-sinusoidal glucose cycle may occur which is constituted by glucose producing periportal hepatocytes and glucose consuming pericentral hepatocytes, (ii) Regional variability of hepatic blood flow is higher than the corresponding regional variability of the metabolic output, (iii) a spatially resolved metabolic functiogram of the liver is constructed. Variations of tissue parameters are equally important as variations of enzyme activities for the control of the arterio-venous glucose difference.

The bile fluid contains various lipids that are secreted at the canalicular membrane of hepatocytes. As the secretion mechanism is still a matter of debate and a direct experimental observation of the secretion process is not possible so far, we used a mathematical model to simulate the extraction of the major bile lipids cholesterol, phosphatidylcholine and sphingomyelin from the outer leaflet of the canalicular membrane. Lipid diffusion was modeled as random movement on a triangular lattice governed by next-neighbor interaction energies. Phase separation in liquid-ordered and liquid-disordered domains was modeled by assigning two alternative ordering states to each lipid species and minimization of next-neighbor ordering energies. Parameterization of the model was performed such that experimentally determined diffusion rates and phases in ternary lipid mixtures of model membranes were correctly recapitulated. The model describes the spontaneous formation of nanodomains in the external leaflet of the canalicular membrane in a time window between 0.1 ms to 10 ms at varying lipid proportions. The extraction of lipid patches from the bile salt soluble nanodomain into the bile reproduced observed biliary phospholipid compositions for a physiological membrane composition. Comparing the outcome of model simulations with available experimental observations clearly favors the extraction of tiny membrane patches composed of about 100-400 lipids as the likely mechanism of biliary lipid secretion.

SUMMARY: CySBML is a plugin designed to work with Systems Biology Markup Language (SBML) in Cytoscape having the following features: SBML import, support of the SBML layout and qualitative model packages, navigation in network layouts based on SBML structure, access to MIRIAM and SBO-based annotations and SBML validation. CySBML includes an importer for BioModels to load SBML from standard repositories. AVAILABILITY AND IMPLEMENTATION: Freely available for non-commercial purposes through the Cytoscape plugin manager or for download at http://sourceforge.net/projects/cysbml/. CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Tutorial, usage guide, installation instructions and additional figures are available for download at http://www.charite.de/sysbio/people/koenig/software/cysbml/.

Despite the crucial role of the liver in glucose homeostasis, a detailed mathematical model of human hepatic glucose metabolism is lacking so far. Here we present a detailed kinetic model of glycolysis, gluconeogenesis and glycogen metabolism in human hepatocytes integrated with the hormonal control of these pathways by insulin, glucagon and epinephrine. Model simulations are in good agreement with experimental data on (i) the quantitative contributions of glycolysis, gluconeogenesis, and glycogen metabolism to hepatic glucose production and hepatic glucose utilization under varying physiological states. (ii) the time courses of postprandial glycogen storage as well as glycogen depletion in overnight fasting and short term fasting (iii) the switch from net hepatic glucose production under hypoglycemia to net hepatic glucose utilization under hyperglycemia essential for glucose homeostasis (iv) hormone perturbations of hepatic glucose metabolism. Response analysis reveals an extra high capacity of the liver to counteract changes of plasma glucose level below 5 mM (hypoglycemia) and above 7.5 mM (hyperglycemia). Our model may serve as an important module of a whole-body model of human glucose metabolism and as a valuable tool for understanding the role of the liver in glucose homeostasis under normal conditions and in diseases like diabetes or glycogen storage diseases.

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: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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.

Monitoring cholesterol levels is strongly recommended to identify patients at risk for myocardial infarction. However, clinical markers beyond "bad" and "good" cholesterol are needed to precisely predict individual lipid disorders. Our work contributes to this aim by bringing together experiment and theory. We developed a novel computer-based model of the human plasma lipoprotein metabolism in order to simulate the blood lipid levels in high resolution. Instead of focusing on a few conventionally used predefined lipoprotein density classes (LDL, HDL), we consider the entire protein and lipid composition spectrum of individual lipoprotein complexes. Subsequently, their distribution over density (which equals the lipoprotein profile) is calculated. As our main results, we (i) successfully reproduced clinically measured lipoprotein profiles of healthy subjects; (ii) assigned lipoproteins to narrow density classes, named high-resolution density sub-fractions (hrDS), revealing heterogeneous lipoprotein distributions within the major lipoprotein classes; and (iii) present model-based predictions of changes in the lipoprotein distribution elicited by disorders in underlying molecular processes. In its present state, the model offers a platform for many future applications aimed at understanding the reasons for inter-individual variability, identifying new sub-fractions of potential clinical relevance and a patient-oriented diagnosis of the potential molecular causes for individual dyslipidemia.

The dynamics of radioactive tracers in metabolic systems can be mathematically modelled by coupled systems of differential equations for both the concentrations and the specific radioactivities of the metabolites involved. Computer simulations, i.e. direct fitting of numerical solutions of these equations to observed time-courses of metabolites and specific radioactivities, enables one to estimate unknown kinetic parameters of the system. The theoretical fundamentals of this approach and the main steps towards the quantitative assessment of flux rates in stationary metabolic systems are outlined. An application of the method to the purine nucleotide metabolism of Ehrlich ascites tumor cells is given based on a simplified model of this pathway. The obtained steady-state flux rates indicate a marked increase in the metabolism of the adenine nucleotides during the proliferating phase in comparison to the resting phase of tumor growth.

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.