A detailed genome-wide reconstruction of mouse metabolism based on human Recon 1

Background  

Well-curated and validated network reconstructions are extremely valuable tools in systems biology. Detailed metabolic reconstructions of mammals have recently emerged, including human reconstructions. They raise the question if the various successful applications of microbial reconstructions can be replicated in complex organisms.     

Carboxylesterases in lipid metabolism: from mouse to human

Mammalian carboxylesterases hydrolyze a wide range of xenobiotic and endogenous compounds, including lipid esters. Physiological functions of carboxylesterases in lipid metabolism and energy homeostasis in vivo have been demonstrated by genetic manipulations and chemical inhibition in mice, and in vitro through (over)expression, knockdown of expression, and chemical inhibition in a variety of cells. Recent research advances have revealed the relevance of carboxylesterases to metabolic diseases such as obesity and fatty liver disease, suggesting these enzymes might be potential targets for treatment of metabolic disorders. In order to translate pre-clinical studies in cellular and mouse models to humans, differences and similarities of carboxylesterases between mice and human need to be elucidated. This review presents and discusses the research progress in structure and function of mouse and human carboxylesterases, and the role of these enzymes in lipid metabolism and metabolic disorders.     

Homologous recombination: from model organisms to human disease

Recent experiments show that properly controlled recombination between homologous DNA molecules is essential for the maintenance of genome stability and for the prevention of tumorigenesis.     

MitoCore: a curated constraint-based model for simulating human central metabolism

Background

The complexity of metabolic networks can make the origin and impact of changes in central metabolism occurring during diseases difficult to understand. Computer simulations can help unravel this complexity, and progress has advanced in genome-scale metabolic models. However, many models produce unrealistic results when challenged to simulate abnormal metabolism as they include incorrect specification and localisation of reactions and transport steps, incorrect reaction parameters, and confounding of prosthetic groups and free metabolites in reactions. Other common drawbacks are due to their scale, making them difficult to parameterise and simulation results hard to interpret. Therefore, it remains important to develop smaller, manually curated models.

Results

We present MitoCore, a manually curated constraint-based computer model of human metabolism that incorporates the complexity of central metabolism and simulates this metabolism successfully under normal and abnormal physiological conditions, including hypoxia and mitochondrial diseases. MitoCore describes 324 metabolic reactions, 83 transport steps between mitochondrion and cytosol, and 74 metabolite inputs and outputs through the plasma membrane, to produce a model of manageable scale for easy interpretation of results. Its key innovations include a more accurate partitioning of metabolism between cytosol and mitochondrial matrix; better modelling of connecting transport steps; differentiation of prosthetic groups and free co-factors in reactions; and a new representation of the respiratory chain and the proton motive force. MitoCore’s default parameters simulate normal cardiomyocyte metabolism, and to improve usability and allow comparison with other models and types of analysis, its reactions and metabolites have extensive annotation, and cross-reference identifiers from Virtual Metabolic Human database and KEGG. These innovations—including over 100 reactions absent or modified from Recon 2—are necessary to model central metabolism more accurately.

Conclusion

We anticipate MitoCore as a research tool for scientists, from experimentalists looking to interpret their data and test hypotheses, to experienced modellers predicting the consequences of disease or using computationally intensive methods that are infeasible with larger models, as well as a teaching tool for those new to modelling and needing a small, manageable model on which to learn and experiment.

     

From humanized mice to human disease: guiding extrapolation from model to target

Extrapolation from a well-understood base population to a less-understood target population can fail if the base and target populations are not sufficiently similar. Differences between laboratory mice and humans, for example, can hinder extrapolation in medical research. Mice that carry a partial or complete human physiological system, known as humanized mice, are supposed to make extrapolation more reliable by simulating a variety of human diseases. But what justifies our belief that these mice are similar enough to their human counterparts to simulate human disease? I argue that, unless three requirements are met in the process of humanizing mice, very little does. My requirements are not meant to provide necessary and sufficient conditions that guarantee a particular outcome. Instead, they serve as a heuristic for guiding scientific judgments involving extrapolation. In developing each requirement, I engage with philosophical issues concerning the nature of model-based science and the mechanistic approach (and its limits) to making generalizations in the life sciences.     

Genome-scale models of bacterial metabolism: reconstruction and applications

Genome-scale metabolic models bridge the gap between genome-derived biochemical information and metabolic phenotypes in a principled manner, providing a solid interpretative framework for experimental data related to metabolic states, and enabling simple in silico experiments with whole-cell metabolism. Models have been reconstructed for almost 20 bacterial species, so far mainly through expert curation efforts integrating information from the literature with genome annotation. A wide variety of computational methods exploiting metabolic models have been developed and applied to bacteria, yielding valuable insights into bacterial metabolism and evolution, and providing a sound basis for computer-assisted design in metabolic engineering. Recent advances in computational systems biology and high-throughput experimental technologies pave the way for the systematic reconstruction of metabolic models from genomes of new species, and a corresponding expansion of the scope of their applications. In this review, we provide an introduction to the key ideas of metabolic modeling, survey the methods, and resources that enable model reconstruction and refinement, and chart applications to the investigation of global properties of metabolic systems, the interpretation of experimental results, and the re-engineering of their biochemical capabilities.     

3D reconstruction and manufacture of real abdominal aortic aneurysms: from CT scan to silicone model

Abdominal aortic aneurysm (AAA) can be defined as a permanent and irreversible dilation of the infrarenal aorta. AAAs are often considered to be an aorta with a diameter 1.5 times the normal infrarenal aorta diameter. This paper describes a technique to manufacture realistic silicone AAA models for use with experimental studies. This paper is concerned with the reconstruction and manufacturing process of patient-specific AAAs. 3D reconstruction from computed tomography scan data allows the AAA to be created. Mould sets are then designed for these AAA models utilizing computer aided designcomputer aided manufacture techniques and combined with the injection-moulding method. Silicone rubber forms the basis of the resulting AAA model. Assessment of wall thickness and overall percentage difference from the final silicone model to that of the computer-generated model was performed. In these realistic AAA models, wall thickness was found to vary by an average of 9.21%. The percentage difference in wall thickness recorded can be attributed to the contraction of the casting wax and the expansion of the silicone during model manufacture. This method may be used in conjunction with wall stress studies using the photoelastic method or in fluid dynamic studies using a laser-Doppler anemometry. In conclusion, these patient-specific rubber AAA models can be used in experimental investigations, but should be assessed for wall thickness variability once manufactured.     

Cholesterol metabolism: from lipidomics to immunology

Oxysterols, the oxidized forms of cholesterol or of its precursors, are formed in the first steps of cholesterol metabolism. Oxysterols have interested chemists, biologists, and physicians for many decades, but their exact biological relevance in vivo, other than as intermediates in bile acid biosynthesis, has long been debated. However, in the first quarter of this century, a role for side-chain oxysterols and their C-7 oxidized metabolites has been convincingly established in the immune system. 25-Hydroxycholesterol has been shown to be synthesized by macrophages in response to the activation of Toll-like receptors and to offer protection against microbial pathogens, whereas 7α,25-dihydroxycholesterol has been shown to act as a chemoattractant to lymphocytes expressing the G protein-coupled receptor Epstein-Barr virus-induced gene 2 and to be important in coordinating the action of B cells, T cells, and dendritic cells in secondary lymphoid tissue. There is a growing body of evidence that not only these two oxysterols but also many of their isomers are of importance to the proper function of the immune system. Here, we review recent findings related to the roles of oxysterols in immunology.     

Preliminary model for human lipoprotein metabolism in hyperlipoproteinemia.

A model is proposed for the metabolism of plasma lipoprotein apoproteins based on studies of a hyperlipoproteinemic subject who received 2.5 mCi[3H]leucine intravenously. Measurements included apoprotein specific activities (apo-B and apo-C) of very low density lipoprotein (VLDL) and of three low density lipoprotein (LDL) subspecies, Sf 17 LDL, Sf 10 LDL, and Sf 4 LDL. Activities of plasma albumin were also determined. The data were analyzed using a compartmental model and the SAAM computer program. A chain-like series of compartments were necessary to simulate plasma VLDL kinetics, suggesting a multistep delipidation process. The data are consistent with the notion that VLDL is the dominant LDL precursor. Two modes of conversion from VLDL to LDL are required. After partial delipidation some VLDL is converted to the Sf 17 LDL, while the remainder undergoes further delipidation before being converted to Sf 4 LDL, the major plasma LDL component. Some direct release of LDL into plasma had to be introduced to fit the data, about 24% of total LDL production. The three LDL subspecies follow a precursor-product relationship (Sf 17 leads to Sf 10 leads to Sf 4). The analysis also indicates that in using labeled leucine as a tracer, the slow exchange of leucine with the total body protein pool must be considered in trying to resolve the LDL subsystem and in the estimation of steady-state apoprotein levels. In view of the fact that the proposed model is based predominantly on the data from a single patient, no generalizations can be made about parameter values. The study is most valuable, however, in pointing out metabolic pathways not considered before and in calling attention to variables that must be considered in the design of experiments to study lipoprotein kinetics.     

Systems biology of lipid metabolism: From yeast to human

Lipid metabolism is highly relevant as it plays a central role in a number of human diseases. Due to the highly interactive structure of lipid metabolism and its regulation, it is necessary to apply a holistic approach, and systems biology is therefore well suited for integrated analysis of lipid metabolism. In this paper it is demonstrated that the yeast Saccharomyces cerevisiae serves as an excellent model organism for studying the regulation of lipid metabolism in eukaryotes as most of the regulatory structures in this part of the metabolism are conserved between yeast and mammals. Hereby yeast systems biology can assist to improve our understanding of how lipid metabolism is regulated.     

Quantifying the contribution of the liver to glucose homeostasis: a detailed kinetic model of human hepatic glucose metabolism

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.     

Microbiome: from community metabolism to host diseases

正Microorganisms live in almost every habitat on the earth from the poles to the equator,from forest to desert,from mountain to deep sea,from geysers to karst structures,as well as the body of almost all multicellular organisms from plants to animals.Essentially,species among the microbial populations interact in different ways,as predators and prey,or as symbionts in the form of communities,so adapt to hosts     

Resistin: A journey from metabolism to cancer

Resistin, a small secretory molecule, has been implicated to play an important role in the development of insulin resistance under obese condition. For the past few decades, it has been linked to various cellular and metabolic functions. It has been associated with diseases like metabolic disorders, cardiovascular diseases and cancers. Numerous clinical studies have indicated an increased serum resistin level in pathological disorders which have been reported to increase mortality rate in comparison to low resistin expressing subjects. Various molecular studies suggest resistin plays a pivotal role in proliferation, metastasis, angiogenesis, inflammation as well as in regulating metabolism in cancer cells. Therefore, understanding the role of resistin and elucidating its’ associated molecular mechanism will give a better insight into the management of these disorders. In this article, we summarize the diverse roles of resistin in pathological disorders based on the available literature, clinicopathological data, and a compiled study from various databases. The article mainly provides comprehensive information of its role as a target in different treatment modalities in pre as well as post-clinical studies.     

Stoichiometric model of folate-dependent metabolism of one-carbon units in human placenta

The work is dedicated to creation of the mathematical model of folate-dependent one-carbon unit metabolism (FOCM) and study of its function in human placenta under homocysteine load and the most common mutations in the genes of methylenetetrahydrofolate reductase (MTHFR) and cystathionine beta-synthase (CBS). In the model we have taken into account specific features of placental expression of genes that encode enzymes of FOCM. Using software tools Metatool and COBRAToolbox we have identified key metabolites, elementary modes and metabolic fluxes through different reactions of the system. It is shown that the most vulnerable links in the system are the folate cycle and synthesis of precursors of nucleic acids, inosine monophosphate and thymidyne monophosphates, which are changing in the broad range from significant inhibition to activation depending on the imposed conditions. The most stable links in the system are the reactions of glutathione and taurine synthesis. Simulation results coincide with the results obtained in similar experimental conditions. Under certain imposed conditions non-obvious relationships between the system links are revealed, and this becomes the basis for a purposeful test of predictions generated by the model.     

Systemic investigation of a brain-centered model of the human energy metabolism

The regulation of the human energy metabolism is crucial to ensure the functionality of the entire organism. Deregulations may lead to severe pathologies such as diabetes mellitus and obesity. The decisive role of the brain as active controller and heavy consumer in the complex whole-body energy metabolism is the object of recent research. Latest studies suggest the priority of the brain energy supply in the competition between brain and body periphery for the available energy resources. In this paper, a systemic investigation of the human energy metabolism is presented which consists of a compartment model including periphery, blood, and brain as well as signaling paths via insulin, appetite, and ingestion. The presented dynamical system particularly contains the competition for energy between brain and body periphery. Characteristically, the hormone insulin is regarded as central feedback signal of the brain. The model realistically reproduces the qualitative behavior of the energy metabolism. Short-time observations demonstrate the physiological periodic food intake generating the typical oscillating blood glucose variations. Integration over the daily cycle yields a long-term model which shows a stable behavior in accordance with the homeostatic regulation of the energy metabolism on a long-time scale. Two types of abstract constitutive equations describing the interaction between compartments and signals are taken into consideration. These are nonlinear and linear representatives from the class of feasible relations. The robustness of the model against the choice of the representative relation is linked to evolutionary stability of existing organisms.     

Development of a compartmental model of human zinc metabolism: identifiability and multiple studies analyses

A compartmental model of zinc metabolism has been developed from stable isotope tracer studies of five healthy adults. Multiple isotope tracers were administered orally and intravenously, and the resulting enrichment was measured in plasma, erythrocytes, urine, and feces for as long as 3 wk. Data from total zinc measurements and model-independent calculations of various steady-state parameters were also modeled with the kinetic data. A structure comprised of 14 compartments and as many as 25 unknown kinetic parameters was developed to adequately model the data from each of the individual studies. The structural identifiability of the model was established using the GLOBI2 identifiability analysis software. Numerical identifiability of parameter estimates was evaluated using statistical data provided by SAAM. A majority of the model parameters was estimated with sufficient statistical certainty to be considered well determined. After the fitting of the model and data from the individual studies using SAAM/CONSAM, results were submitted to SAAM extended multiple studies analysis for aggregation into a single set of population parameters and statistics. The model was judged to be valid based on criteria described elsewhere.