We present HepatoNet1, a manually curated large-scale metabolic network of the human hepatocyte that encompasses >2500 reactions in six intracellular and two extracellular compartments.Using constraint-based modeling techniques, the network has been validated to replicate numerous metabolic functions of hepatocytes corresponding to a reference set of diverse physiological liver functions.Taking the detoxification of ammonia and the formation of bile acids as examples, we show how these liver-specific metabolic objectives can be achieved by the variable interplay of various metabolic pathways under varying conditions of nutrients and oxygen availability.
The liver has a pivotal function in metabolic homeostasis of the human body. Hepatocytes are the principal site of the metabolic conversions that underlie diverse physiological functions of the liver. These functions include provision and homeostasis of carbohydrates, amino acids, lipids and lipoproteins in the systemic blood circulation, biotransformation, plasma protein synthesis and bile formation, to name a few. Accordingly, hepatocyte metabolism integrates a vast array of differentially regulated biochemical activities and is highly responsive to environmental perturbations such as changes in portal blood composition (Dardevet et al, 2006). The complexity of this metabolic network and the numerous physiological functions to be achieved within a highly variable physiological environment necessitate an integrated approach with the aim of understanding liver metabolism at a systems level. To this end, we present HepatoNet1, a stoichiometric network of human hepatocyte metabolism characterized by (i) comprehensive coverage of known biochemical activities of hepatocytes and (ii) due representation of the biochemical and physiological functions of hepatocytes as functional network states. The network comprises 777 metabolites in six intracellular (cytosol, endoplasmic reticulum and Golgi apparatus, lysosome, mitochondria, nucleus, and peroxisome) and two extracellular compartments (bile canaliculus and sinusoidal space) and 2539 reactions, including 1466 transport reactions. It is based on the manual evaluation of >1500 original scientific research publications to warrant a high-quality evidence-based model. The final network is the result of an iterative process of data compilation and rigorous computational testing of network functionality by means of constraint-based modeling techniques. We performed flux-balance analyses to validate whether for >300 different metabolic objectives a non-zero stationary flux distribution could be established in the network. Figure 1 shows one such functional flux mode associated with the synthesis of the bile acid glycochenodeoxycholate, one important hepatocyte-specific physiological liver function. Besides those pathways directly linked to the synthesis of the bile acid, the mevalonate pathway and the de novo synthesis of cholesterol, the flux mode comprises additional pathways such as gluconeogenesis, the pentose phosphate pathway or the ornithine cycle because the calculations were routinely performed on a minimal set of exchangeable metabolites, that is all reactants were forced to be balanced and all exportable intermediates had to be catabolized into non-degradable end products. This example shows how HepatoNet1 under the challenges of limited exchange across the network boundary can reveal numerous cross-links between metabolic pathways traditionally perceived as separate entities. For example, alanine is used as gluconeogenic substrate to form glucose-6-phosphate, which is used in the pentose phosphate pathway to generate NADPH. The glycine moiety for bile acid conjugation is derived from serine. Conversion of ammonia into non-toxic nitrogen compounds is one central homeostatic function of hepatocytes. Using the HepatoNet1 model, we investigated, as another example of a complex metabolic objective dependent on systemic physiological parameters, how the consumption of oxygen, glucose and palmitate is affected when an external nitrogen load is converted in varying proportions to the non-toxic nitrogen compounds: urea, glutamine and alanine. The results reveal strong dependencies between the available level of oxygen and the substrate demand of hepatocytes required for effective ammonia detoxification by the liver.
Oxygen demand is highest if nitrogen is exclusively transformed into urea. At lower fluxes into urea, an intriguing pattern for oxygen demand is predicted: oxygen demand attains a minimum if the nitrogen load is directed to urea, glutamine and alanine with relative fluxes of 0.17, 0.43 and 0.40, respectively (Figure 2A). Oxygen demand in this flux distribution is four times lower than for the maximum (100% urea) and still 77 and 33% lower than using alanine and glutamine as exclusive nitrogen compounds, respectively. This computationally predicted tendency is consistent with the notion that the zonation of ammonia detoxification, that is the preferential conversion of ammonia to urea in periportal hepatocytes and to glutamine in perivenous hepatocytes, is dictated by the availability of oxygen (Gebhardt, 1992; Jungermann and Kietzmann, 2000). The decreased oxygen demand in flux distributions using higher proportions of glutamine or alanine is accompanied by increased uptake of the substrates glucose and palmitate (Figure 2B). This is due to an increased demand of energy and carbon for the amidation and transamination of glutamate and pyruvate to discharge nitrogen in the form of glutamine and alanine, respectively. In terms of both scope and specificity, our model bridges the scale between models constructed specifically to examine distinct metabolic processes of the liver and modeling based on a global representation of human metabolism. The former include models for the interdependence of gluconeogenesis and fatty-acid catabolism (Chalhoub et al, 2007), impairment of glucose production in von Gierke's and Hers' diseases (Beard and Qian, 2005) and other processes (Calik and Akbay, 2000; Stucki and Urbanczik, 2005; Ohno et al, 2008). The hallmark of these models is that each of them focuses on a small number of reactions pertinent to the metabolic function of interest embedded in a customized representation of the principal pathways of central metabolism. HepatoNet1, currently, outperforms liver-specific models computationally predicted (Shlomi et al, 2008) on the basis of global reconstructions of human metabolism (Duarte et al, 2007; Ma and Goryanin, 2008). In contrast to either of the aforementioned modeling scales, HepatoNet1 provides the combination of a system-scale representation of metabolic activities and representation of the cell type-specific physical boundaries and their specific transport capacities. This allows for a highly versatile use of the model for the analysis of various liver-specific physiological functions. Conceptually, from a biological system perspective, this type of model offers a large degree of comprehensiveness, whereas retaining tissue specificity, a fundamental design principle of mammalian metabolism. HepatoNet1 is expected to provide a structural platform for computational studies on liver function. The results presented herein highlight how internal fluxes of hepatocyte metabolism and the interplay with systemic physiological parameters can be analyzed with constraint-based modeling techniques. At the same time, the framework may serve as a scaffold for complementation of kinetic and regulatory properties of enzymes and transporters for analysis of sub-networks with topological or kinetic modeling methods.
We present HepatoNet1, the first reconstruction of a comprehensive metabolic network of the human hepatocyte that is shown to accomplish a large canon of known metabolic liver functions. The network comprises 777 metabolites in six intracellular and two extracellular compartments and 2539 reactions, including 1466 transport reactions. It is based on the manual evaluation of >1500 original scientific research publications to warrant a high-quality evidence-based model. The final network is the result of an iterative process of data compilation and rigorous computational testing of network functionality by means of constraint-based modeling techniques. Taking the hepatic detoxification of ammonia as an example, we show how the availability of nutrients and oxygen may modulate the interplay of various metabolic pathways to allow an efficient response of the liver to perturbations of the homeostasis of blood compounds.