Metabolic flux analysis of cultured hepatocytes exposed to plasma

Clinical stratification improves the diagnostic accuracy of small omics datasets within machine learning and genome-scale metabolic modelling methods

BACKGROUND

Recently, multi-omic machine learning architectures have been proposed for the early detection of cancer. However, for rare cancers and their associated small datasets, it is still unclear how to use the available multi-omics data to achieve a mechanistic prediction of cancer onset and progression, due to the limited data available. Hepatoblastoma is the most frequent liver cancer in infancy and childhood, and whose incidence has been lately increasing in several developed countries. Even though some studies have been conducted to understand the causes of its onset and discover potential biomarkers, the role of metabolic rewiring has not been investigated in depth so far.

METHODS

Here, we propose and implement an interpretable multi-omics pipeline that combines mechanistic knowledge from genome-scale metabolic models with machine learning algorithms, and we use it to characterise the underlying mechanisms controlling hepatoblastoma.

RESULTS AND CONCLUSIONS

While the obtained machine learning models generally present a high diagnostic classification accuracy, our results show that the type of omics combinations used as input to the machine learning models strongly affects the detection of important genes, reactions and metabolic pathways linked to hepatoblastoma. Our method also suggests that, in the context of computer-aided diagnosis of cancer, optimal diagnostic accuracy can be achieved by adopting a combination of omics that depends on the patient's clinical characteristics.

Metabolic Changes in Different Stages of Liver Fibrosis: In vivo Hyperpolarized 13C MR Spectroscopy and Metabolic Imaging

PURPOSE

The objective was to assess metabolic changes in different stages of liver fibrosis using hyperpolarized C-13 magnetic resonance spectroscopy (MRS) and metabolic imaging.

PROCEDURES

Mild and severe liver fibrosis were induced in C3H/HeN mice (n = 14) by injecting thioacetamide (TAA). Other C3H/HeN mice (n = 7) were injected with phosphate buffer saline (PBS) (7.4 pH) as normal controls. Hyperpolarized C-13 MRS was performed on the livers of the mice, which was accompanied by intravoxel incoherent motion (IVIM) diffusion-weighted imaging with 12 b values. The differential metabolite ratios, apparent diffusion coefficient values, and IVIM parameters among the three groups were analyzed by a one-way analysis of variance test.

RESULTS

The ratios of [1-¹³C]lactate/pyruvate, [1-¹³C]lactate/total carbon (tC), [1-¹³C]alanine/pyruvate, and [1-¹³C] alanine/tC were significantly higher in both the mild and severe fibrosis groups than in the normal control group (p < 0.05). While the [1-¹³C]lactate/pyruvate and [1-¹³C]lactate/tC ratios were not significantly different between mild and severe fibrosis groups, the ratios of [1-¹³C]alanine/pyruvate and [1-¹³C]alanine/tC were significantly higher in the severe fibrosis group than in the mild fibrosis group (p < 0.05). In addition, D^* showed a significantly lower value in the severe fibrosis group than in the normal or mild fibrosis groups and negatively correlated with the levels of [1-¹³C] lactate and [1-¹³C]alanine.

CONCLUSIONS

Our findings suggest that it might be possible to differentiate mild from severe liver fibrosis using the cellular metabolic changes with hyperpolarized C-13 MRS and metabolic imaging.

Systems biology analysis of hepatitis C virus infection reveals the role of copy number increases in regions of chromosome 1q in hepatocellular carcinoma metabolism

Hepatitis C virus (HCV) infection is a worldwide healthcare problem; however, traditional treatment methods have failed to cure all patients, and HCV has developed resistance to new drugs. Systems biology-based analyses could play an important role in the holistic analysis of the impact of HCV on hepatocellular metabolism. Here, we integrated HCV assembly reactions with a genome-scale hepatocyte metabolic model to identify metabolic targets for HCV assembly and metabolic alterations that occur between different HCV progression states (cirrhosis, dysplastic nodule, and early and advanced hepatocellular carcinoma (HCC)) and healthy liver tissue. We found that diacylglycerolipids were essential for HCV assembly. In addition, the metabolism of keratan sulfate and chondroitin sulfate was significantly changed in the cirrhosis stage, whereas the metabolism of acyl-carnitine was significantly changed in the dysplastic nodule and early HCC stages. Our results explained the role of the upregulated expression of BCAT1, PLOD3 and six other methyltransferase genes involved in carnitine biosynthesis and S-adenosylmethionine metabolism in the early and advanced HCC stages. Moreover, GNPAT and BCAP31 expression was upregulated in the early and advanced HCC stages and could lead to increased acyl-CoA consumption. By integrating our results with copy number variation analyses, we observed that GNPAT, PPOX and five of the methyltransferase genes (ASH1L, METTL13, SMYD2, TARBP1 and SMYD3), which are all located on chromosome 1q, had increased copy numbers in the cancer samples relative to the normal samples. Finally, we confirmed our predictions with the results of metabolomics studies and proposed that inhibiting the identified targets has the potential to provide an effective treatment strategy for HCV-associated liver disorders.

Reconciled rat and human metabolic networks for comparative toxicogenomics and biomarker predictions

The laboratory rat has been used as a surrogate to study human biology for more than a century. Here we present the first genome-scale network reconstruction of Rattus norvegicus metabolism, iRno, and a significantly improved reconstruction of human metabolism, iHsa. These curated models comprehensively capture metabolic features known to distinguish rats from humans including vitamin C and bile acid synthesis pathways. After reconciling network differences between iRno and iHsa, we integrate toxicogenomics data from rat and human hepatocytes, to generate biomarker predictions in response to 76 drugs. We validate comparative predictions for xanthine derivatives with new experimental data and literature-based evidence delineating metabolite biomarkers unique to humans. Our results provide mechanistic insights into species-specific metabolism and facilitate the selection of biomarkers consistent with rat and human biology. These models can serve as powerful computational platforms for contextualizing experimental data and making functional predictions for clinical and basic science applications.

The rat is a widely-used model for human biology, but we must be aware of metabolic differences. Here, the authors reconstruct the genome-scale metabolic network of the rat, and after reconciling it with an improved human metabolic model, demonstrate the power of the models to integrate toxicogenomics data, providing species-specific biomarker predictions in response to a panel of drugs.

Nuclear receptors control pro-viral and antiviral metabolic responses to hepatitis C virus infection

Viruses lack the basic machinery needed to replicate and therefore must hijack the host's metabolism to propagate. Virus-induced metabolic changes have yet to be systematically studied in the context of host transcriptional regulation, and such studies shoul offer insight into host-pathogen metabolic interplay. In this work we identified hepatitis C virus (HCV)-responsive regulators by coupling system-wide metabolic-flux analysis with targeted perturbation of nuclear receptors in primary human hepatocytes. We found HCV-induced upregulation of glycolysis, ketogenesis and drug metabolism, with glycolysis controlled by activation of HNF4α, ketogenesis by PPARα and FXR, and drug metabolism by PXR. Pharmaceutical inhibition of HNF4α reversed HCV-induced glycolysis, blocking viral replication while increasing apoptosis in infected cells showing virus-induced dependence on glycolysis. In contrast, pharmaceutical inhibition of PPARα or FXR reversed HCV-induced ketogenesis but increased viral replication, demonstrating a novel host antiviral response. Our results show that virus-induced changes to a host's metabolism can be detrimental to its life cycle, thus revealing a biologically complex relationship between virus and host.

Metabolic Flux Distribution during Defatting of Steatotic Human Hepatoma (HepG2) Cells

Methods that rapidly decrease fat in steatotic hepatocytes may be helpful to recover severely fatty livers for transplantation. Defatting kinetics are highly dependent upon the extracellular medium composition; however, the pathways involved are poorly understood. Steatosis was induced in human hepatoma cells (HepG2) by exposure to high levels of free fatty acids, followed by defatting using plain medium containing no fatty acids, or medium supplemented with a cocktail of defatting agents previously described before. We measured the levels of 28 extracellular metabolites and intracellular triglyceride, and fed the data into a steady-state mass balance model to estimate strictly intracellular fluxes. We found that during defatting, triglyceride content decreased, while beta-oxidation, the tricarboxylic acid cycle, and the urea cycle increased. These fluxes were augmented by defatting agents, and even more so by hyperoxic conditions. In all defatting conditions, the rate of extracellular glucose uptake/release was very small compared to the internal supply from glycogenolysis, and glycolysis remained highly active. Thus, in steatotic HepG2 cells, glycolysis and fatty acid oxidation may co-exist. Together, these pathways generate reducing equivalents that are supplied to mitochondrial oxidative phosphorylation.

Genome-scale metabolic modelling of hepatocytes reveals serine deficiency in patients with non-alcoholic fatty liver disease

Several liver disorders result from perturbations in the metabolism of hepatocytes, and their underlying mechanisms can be outlined through the use of genome-scale metabolic models (GEMs). Here we reconstruct a consensus GEM for hepatocytes, which we call iHepatocytes2322, that extends previous models by including an extensive description of lipid metabolism. We build iHepatocytes2322 using Human Metabolic Reaction 2.0 database and proteomics data in Human Protein Atlas, which experimentally validates the incorporated reactions. The reconstruction process enables improved annotation of the proteomics data using the network centric view of iHepatocytes2322. We then use iHepatocytes2322 to analyse transcriptomics data obtained from patients with non-alcoholic fatty liver disease. We show that blood concentrations of chondroitin and heparan sulphates are suitable for diagnosing non-alcoholic steatohepatitis and for the staging of non-alcoholic fatty liver disease. Furthermore, we observe serine deficiency in patients with NASH and identify PSPH, SHMT1 and BCAT1 as potential therapeutic targets for the treatment of non-alcoholic steatohepatitis.

Reduction of proteinuria through podocyte alkalinization

Podocytes are highly differentiated cells and critical elements for the filtration barrier of the kidney. Loss of their foot process (FP) architecture (FP effacement) results in urinary protein loss. Here we show a novel role for the neutral amino acid glutamine in structural and functional regulation of the kidney filtration barrier. Metabolic flux analysis of cultured podocytes using genetic, toxic, and immunologic injury models identified increased glutamine utilization pathways. We show that glutamine uptake is increased in diseased podocytes to couple nutrient support to increased demand during the disease state of FP effacement. This feature can be utilized to transport increased amounts of glutamine into damaged podocytes. The availability of glutamine determines the regulation of podocyte intracellular pH (pHi). Podocyte alkalinization reduces cytosolic cathepsin L protease activity and protects the podocyte cytoskeleton. Podocyte glutamine supplementation reduces proteinuria in LPS-treated mice, whereas acidification increases glomerular injury. In summary, our data provide a metabolic opportunity to combat urinary protein loss through modulation of podocyte amino acid utilization and pHi.

Prediction of therapeutic microRNA based on the human metabolic network

MOTIVATION

MicroRNA (miRNA) expression has been found to be deregulated in human cancer, contributing, in part, to the interest of the research community in using miRNAs as alternative therapeutic targets. Although miRNAs could be potential targets, identifying which miRNAs to target for a particular type of cancer has been difficult due to the limited knowledge on their regulatory roles in cancer. We address this challenge by integrating miRNA-target prediction, metabolic modeling and context-specific gene expression data to predict therapeutic miRNAs that could reduce the growth of cancer.

RESULTS

We developed a novel approach to simulate a condition-specific metabolic system for human hepatocellular carcinoma (HCC) wherein overexpression of each miRNA was simulated to predict their ability to reduce cancer cell growth. Our approach achieved >80% accuracy in predicting the miRNAs that could suppress metastasis and progression of liver cancer based on various experimental evidences in the literature. This condition-specific metabolic system provides a framework to explore the mechanisms by which miRNAs modulate metabolic functions to affect cancer growth. To the best of our knowledge, this is the first computational approach implemented to predict therapeutic miRNAs for human cancer based on their functional role in cancer metabolism. Analyzing the metabolic functions altered by the miRNA-identified metabolic genes essential for cell growth and proliferation that are targeted by the miRNAs.

AVAILABILITY AND IMPLEMENTATION

See supplementary protocols and http://www.egr.msu.edu/changroup/Protocols%20Index.html CONTACT: krischan@egr.msu.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Effect of fasting on the metabolic response of liver to experimental burn injury

Liver metabolism is altered after systemic injuries such as burns and trauma. These changes have been elucidated in rat models of experimental burn injury where the liver was isolated and perfused ex vivo. Because these studies were performed in fasted animals to deplete glycogen stores, thus simplifying quantification of gluconeogenesis, these observations reflect the combined impact of fasting and injury on liver metabolism. Herein we asked whether the metabolic response to experimental burn injury is different in fed vs. fasted animals. Rats were subjected to a cutaneous burn covering 20% of the total body surface area, or to similar procedures without administering the burn, hence a sham-burn. Half of the animals in the burn and sham-burn groups were fasted starting on postburn day 3, and the others allowed to continue ad libitum. On postburn day 4, livers were isolated and perfused for 1 hour in physiological medium supplemented with 10% hematocrit red blood cells. The uptake/release rates of major carbon and nitrogen sources, oxygen, and carbon dioxide were measured during the perfusion and the data fed into a mass balance model to estimate intracellular fluxes. The data show that in fed animals, injury increased glucose output mainly from glycogen breakdown and minimally impacted amino acid metabolism. In fasted animals, injury did not increase glucose output but increased urea production and the uptake of several amino acids, namely glutamine, arginine, glycine, and methionine. Furthermore, sham-burn animals responded to fasting by triggering gluconeogenesis from lactate; however, in burned animals the preferred gluconeogenic substrate was amino acids. Taken together, these results suggest that the fed state prevents the burn-induced increase in hepatic amino acid utilization for gluconeogenesis. The role of glycogen stores and means to increase and/or maintain internal sources of glucose to prevent increased hepatic amino acid utilization warrant further studies.

Metabolomics-on-a-chip and metabolic flux analysis for label-free modeling of the internal metabolism of HepG2/C3A cells

In vitro microfluidic systems are increasingly used as an alternative to standard Petri dishes in bioengineering and metabolomic investigations, as they are expected to provide cellular environments close to the in vivo conditions. In this work, we combined the recently developed "metabolomics-on-a-chip" approach with metabolic flux analysis to model the metabolic network of the hepatoma HepG2/C3A cell line and to infer the distribution of intracellular metabolic fluxes in standard Petri dishes and microfluidic biochips. A high pyruvate reduction to lactate was observed in both systems, suggesting that the cells operate in oxygen-limited environments. Our results also indicate that HepG2/C3A cells in the biochip are characterized by a higher consumption rate of oxygen, presumably due to a higher oxygenation rate in the microfluidic environment. This leads to a higher entry of the ultimate glycolytic product, acetyl-CoA, into the Krebs cycle. These findings are supported by the transcriptional activity of HepG2/C3A cells in both systems since we observed that genes regulated by a HIF-1 (hypoxia-regulated factor-1) transcriptional factor were over expressed under the Petri conditions, but to a lesser extent in the biochip.

Advanced stoichiometric analysis of metabolic networks of mammalian systems

Metabolic engineering tools have been widely applied to living organisms to gain a comprehensive understanding about cellular networks and to improve cellular properties. Metabolic flux analysis (MFA), flux balance analysis (FBA), and metabolic pathway analysis (MPA) are among the most popular tools in stoichiometric network analysis. Although application of these tools into well-known microbial systems is extensive in the literature, various barriers prevent them from being utilized in mammalian cells. Limited experimental data, complex regulatory mechanisms, and the requirement of more complex nutrient media are some major obstacles in mammalian cell systems. However, mammalian cells have been used to produce therapeutic proteins, to characterize disease states or related abnormal metabolic conditions, and to analyze the toxicological effects of some medicinally important drugs. Therefore, there is a growing need for extending metabolic engineering principles to mammalian cells in order to understand their underlying metabolic functions. In this review article, advanced metabolic engineering tools developed for stoichiometric analysis including MFA, FBA, and MPA are described. Applications of these tools in mammalian cells are discussed in detail, and the challenges and opportunities are highlighted.

Stoichiometry based steady-state hepatic flux analysis: computational and experimental aspects

: The liver has many complex physiological functions, including lipid, protein and carbohydrate metabolism, as well as bile and urea production. It detoxifies toxic substances and medicinal products. It also plays a key role in the onset and maintenance of abnormal metabolic patterns associated with various disease states, such as burns, infections and major traumas. Liver cells have been commonly used in in vitro experiments to elucidate the toxic effects of drugs and metabolic changes caused by aberrant metabolic conditions, and to improve the functions of existing systems, such as bioartificial liver. More recently, isolated liver perfusion systems have been increasingly used to characterize intrinsic metabolic changes in the liver caused by various perturbations, including systemic injury, hepatotoxin exposure and warm ischemia. Metabolic engineering tools have been widely applied to these systems to identify metabolic flux distributions using metabolic flux analysis or flux balance analysis and to characterize the topology of the networks using metabolic pathway analysis. In this context, hepatic metabolic models, together with experimental methodologies where hepatocytes or perfused livers are mainly investigated, are described in detail in this review. The challenges and opportunities are also discussed extensively.

Optimality and thermodynamics determine the evolution of transcriptional regulatory networks

Transcriptional motifs are small regulatory interaction patterns that regulate biological functions in highly-interacting cellular networks. Recently, attempts have been made to explain the significance of transcriptional motifs through dynamic function. However, fundamental questions remain unanswered. Why are certain transcriptional motifs with similar dynamic function abundant while others occur rarely? What are the criteria for topological generalization of these motifs into complex networks? Here, we present a novel paradigm that combines non-equilibrium thermodynamics with multiobjective-optimality for network analysis. We found that energetic cost, defined herein as specific dissipation energy, is minimal at the optimal environmental conditions and it correlates inversely with the abundance of the network motifs obtained experimentally for E. coli and S. cerevisiae. This yields evidence that dissipative energetics is the underlying criteria used during evolution for motif selection and that biological systems during transcription tend towards evolutionary selection of subgraphs which produces minimum specific heat dissipation under optimal conditions, thereby explaining the abundance/rare occurrence of some motifs. We show that although certain motifs had similar dynamical functionality, they had significantly different energetic cost, thus explaining the abundance/rare occurrence of these motifs. The presented insights may establish global thermodynamic analysis as a backbone in designing and understanding complex networks systems, such as metabolic and protein interaction networks.

Metabolic network analysis of perfused livers under fed and fasted states: incorporating thermodynamic and futile-cycle-associated regulatory constraints

Isolated liver perfusion systems have been extensively used to characterize intrinsic metabolic changes in liver under various conditions, including systemic injury, hepatotoxin exposure, and warm ischemia. Most of these studies were performed utilizing fasted animals prior to perfusion so that a simplified metabolic network could be used in order to determine intracellular fluxes. However, fasting induced metabolic alterations might interfere with disease related changes. Therefore, there is a need to develop a "unified" metabolic flux analysis approach that could be similarly applied to both fed and fasted states. In this study we explored a methodology based on elementary mode analysis in order to determine intracellular fluxes and active pathways simultaneously. In order to decrease the solution space, thermodynamic constraints, and enzymatic regulatory properties for the formation of futile cycles were further considered in the model, resulting in a mixed integer quadratic programming problem. Given the published experimental observations describing the perfused livers under fed and fasted states, the proposed approach successfully determined that gluconeogenesis, glycogenolysis and fatty acid oxidation were active in both states. However, fasting increased the fluxes in gluconeogenic reactions whereas it decreased fluxes associated with glycogenolysis, TCA cycle, fatty acid oxidation and electron transport reactions. This analysis further identified that more pathways were found to be active in fed state while their weight values were relatively lower compared to fasted state. Glucose, lactate, glutamine, glutamate and ketone bodies were also found to be important external metabolites whose extracellular fluxes should be used in the hepatic metabolic network analysis. In conclusion, the mathematical formulation explored in this study is an attractive tool to analyze the metabolic network of perfused livers under various disease conditions. This approach could be simultaneously applied to both fasted and fed data sets.

Metabolic response of perfused livers to various oxygenation conditions

Isolated liver perfusion systems have been used to characterize intrinsic metabolic changes in liver as a result of various perturbations, including systemic injury, hepatotoxin exposure, and warm ischemia. Most of these studies were done using hyperoxic conditions (95% O(2)) but without the use of oxygen carriers in the perfusate. Prior literature data do not clearly establish the impact of oxygenation, and in particular that of adding oxygen carriers to the perfusate, on the metabolic functions of the liver. Therefore, herein the effects of oxygen delivery in the perfusion system on liver metabolism were investigated by comparing three modes of oxygenation. Rat livers were perfused via the portal and hepatic veins at a constant flow rate of 3 mL/min/g liver in a recirculating perfusion system. In the first group, the perfusate was equilibrated in a membrane oxygenator with room air (21% O(2)) before entering the liver. In the second group, the perfusate was equilibrated with a 95% O(2)/5% CO(2) gas mixture. In the third group, the perfusate was supplemented with washed bovine red blood cells (RBCs) at 10% hematocrit and also equilibrated with the 95% O(2)/5% CO(2) gas mixture. Oxygen and CO(2) gradients across the liver were measured periodically with a blood gas analyzer. The rate of change in the concentration of major metabolites in the perfusate was measured over time. Net extracellular fluxes were calculated from these measurements and applied to a stoichiometric-based optimization problem to determine the intracellular fluxes and active pathways in the perfused livers. Livers perfused with RBCs consumed oxygen at twice the rate observed using hyperoxic (95% O(2)) perfusate without RBCs, and also produced more urea and ketone bodies. At the flow rate used, the oxygen supply in perfusate without RBCs was just sufficient to meet the average oxygen demand of the liver but would be insufficient if it increased above baseline, as is often the case in response to environmental perturbations. Metabolic pathway analysis suggests that significant anaerobic glycolysis occurred in the absence of RBCs even using hyperoxic perfusate. Conversely, when RBCs were used, glucose production from lactate and glutamate, as well as pathways related to energy metabolism were upregulated. RBCs also reversed an increase in PPP fluxes induced by the use of hyperoxic perfusate alone. In conclusion, the use of oxygen carriers is required to investigate the effect of various perturbations on liver metabolism.

Metabolic profiling based quantitative evaluation of hepatocellular metabolism in presence of adipocyte derived extracellular matrix

The elucidation of the effect of extracellular matrices on hepatocellular metabolism is critical to understand the mechanism of functional upregulation. We have developed a system using natural extracellular matrices [Adipogel] for enhanced albumin synthesis of rat hepatocyte cultures for a period of 10 days as compared to collagen sandwich cultures. Primary rat hepatocytes isolated from livers of female Lewis rats recover within 4 days of culture from isolation induced injury while function is stabilized at 7 days post-isolation. Thus, the culture period can be classified into three distinct stages viz. recovery stage [day 0–4], pre-stable stage [day 5–7] and the stable stage [day 8–10]. A Metabolic Flux Analysis of primary rat hepatocytes cultured in Adipogel was performed to identify the key metabolic pathways modulated as compared to collagen sandwich cultures. In the recovery stage [day 4], the collagen-soluble Adipogel cultures shows an increase in TriCarboxylic Acid [TCA] cycle fluxes; in the pre-stable stage [day 7], there is an increase in PPP and TCA cycle fluxes while in the stable stage [day 10], there is a significant increase in TCA cycle, urea cycle fluxes and amino acid uptake rates concomitant with increased albumin synthesis rate as compared to collagen sandwich cultures throughout the culture period. Metabolic analysis of the collagen-soluble Adipogel condition reveals significantly higher transamination reaction fluxes, amino acid uptake and albumin synthesis rates for the stable vs. recovery stages of culture. The identification of metabolic pathways modulated for hepatocyte cultures in presence of Adipogel will be a useful step to develop an optimization algorithm to further improve hepatocyte function for Bioartificial Liver Devices. The development of this framework for upregulating hepatocyte function in Bioartificial Liver Devices will facilitate the utilization of an integrated experimental and computational approach for broader applications of Adipogel in tissue e engineering and regenerative medicine.

Computational reconstruction of tissue-specific metabolic models: application to human liver metabolism

The first computational approach for the rapid generation of genome-scale tissue-specific models from a generic species model.

A genome scale model of human liver metabolism, which is comprehensively tested and validated using cross-validation and the ability to carry out complex hepatic metabolic functions.

The model's flux predictions are shown to correlate with flux measurements across a variety of hormonal and dietary conditions, and are successfully used to predict biomarker changes in genetic metabolic disorders, both with higher accuracy than the generic human model.

The study of normal human metabolism and its alterations is central to the understanding and treatment of a variety of human diseases, including diabetes, metabolic syndrome, neurodegenerative disorders, and cancer. A promising systems biology approach for studying human metabolism is through the development and analysis of large-scale stoichiometric network models of human metabolism. The reconstruction of these network models has followed two main paths: the former being the reconstruction of generic (non-tissue specific) models, characterizing the complete metabolic potential of human cells, based mostly on genomic data to trace enzyme-coding genes (Duarte et al, 2007; Ma et al, 2007), and the latter is the reconstruction of cell type- and tissue-specific models (Wiback and Palsson, 2002; Chatziioannou et al, 2003; Vo et al, 2004), based on a similar methodology to that described above, with the extra complexity of manual curation of literature evidence for the cell/system specificity of metabolic enzymes and pathways.

On this background, we present in this study, to the best of our knowledge, the first computational approach for a rapid generation of genome-scale tissue-specific models. The method relies on integrating the previously reconstructed generic human models with a variety of high-throughput molecular ‘omics' data, including transcriptomic, proteomic, metabolomic, and phenotypic data, as well as literature-based knowledge, characterizing the tissue in hand (Figure 1). Hence, it can be readily used to quite rapidly build and use a large array of human tissue-specific models. The resulting model satisfies stoichiometric, mass-balance, and thermodynamic constraints. It serves as a functional metabolic network that can then be used to explore the metabolic state of a tissue under various genetic and physiological conditions, simulating enzymatic inhibition or drug applications through standard constraint-based modeling methods, without requiring additional context-specific molecular data.

We applied this approach to build a genome scale model of liver metabolism, which is then comprehensively tested and validated. The model is shown to be able to simulate complex hepatic metabolic functions, as well as depicting the pathological alterations caused by urea cycle deficiencies. The liver model was applied to predict measured intra-cellular metabolic fluxes given measured metabolite uptake and secretion rates at different hepatic metabolic conditions. The predictions were tested using a comprehensive set of flux measurements performed by (Chan et al, 2003), showing that the liver model obtained more accurate predictions compared to those obtained by the original, generic human model (an overall prediction accuracy of 0.67 versus 0.46). Furthermore, it was applied to identify metabolic biomarkers for liver in-born errors of metabolism—once again, displaying superiority vs. the predictions generated by the generic human model (accuracy of 0.67 versus 0.59).

From a biotechnological standpoint, the liver model generated here can serve as a basis for future studies aiming to optimize the functioning of bio artificial liver devices. The application of the method to rapidly construct metabolic models of other human tissues can obviously lead to many other important clinical insights, e.g., concerning means for metabolic salvage of ischemic heart and brain tissues. Last but not least, the application of the new method is not limited to the realm of human modeling; it can be used to generate tissue models for any multi-tissue organism for which a generic model exists, such as the Mus musculus (Quek and Nielsen, 2008; Sheikh et al, 2005) and the model plant Arabidopsis thaliana (Poolman et al, 2009).

The computational study of human metabolism has been advanced with the advent of the first generic (non-tissue specific) stoichiometric model of human metabolism. In this study, we present a new algorithm for rapid reconstruction of tissue-specific genome-scale models of human metabolism. The algorithm generates a tissue-specific model from the generic human model by integrating a variety of tissue-specific molecular data sources, including literature-based knowledge, transcriptomic, proteomic, metabolomic and phenotypic data. Applying the algorithm, we constructed the first genome-scale stoichiometric model of hepatic metabolism. The model is verified using standard cross-validation procedures, and through its ability to carry out hepatic metabolic functions. The model's flux predictions correlate with flux measurements across a variety of hormonal and dietary conditions, and improve upon the predictive performance obtained using the original, generic human model (prediction accuracy of 0.67 versus 0.46). Finally, the model better predicts biomarker changes in genetic metabolic disorders than the generic human model (accuracy of 0.67 versus 0.59). The approach presented can be used to construct other human tissue-specific models, and be applied to other organisms.

Pathway analysis of liver metabolism under stressed condition

Pathway analysis is a useful tool which reveals important metabolic network properties. However, the big challenge is to propose an objective function for estimating active pathways, which represent the actual state of network. In order to provide weight values for all possible pathways within the metabolic network, this study presents different approaches, considering the structural and physiological properties of the metabolic network, aiming at a unique decomposition of the flux vector into pathways. These methods were used to analyze the hepatic metabolism considering available data sets obtained from the perfused livers of fasted rats receiving burn injury. Utilizing unique decomposition techniques and different fluxes revealed that higher weights were always attributed to short pathways. Specific pathways, including pyruvate, glutamate and oxaloacetate pools, and urea production from arginine, were found to be important or essential in all methods and experimental conditions. Moreover the pathways, including serine production from glycine and conversion between acetoacetate and B-OH-butyrate, were assigned higher weights. Pathway analysis was also used to identify the main sources for the production of certain products in the hepatic metabolic network to gain a better understanding of the effects of burn injury on liver metabolism.

Effects of glucose and insulin on HepG2-C3A cell metabolism

HepG2, hepatocellular carcinoma cells, are used in drug toxicity studies and have also been explored for bioartificial livers. For these applications, the cells are under variable levels of nutrients and hormones, the effects of which on metabolism are poorly understood. In this study, HepG2-C3A cells were cultured under varying levels of glucose (high, low, and glucose-free) and insulin (without and with physiological levels of insulin) for 5 days. Cell growth was found to be comparable between high and low glucose media and lowest for glucose-free medium. Several features of central metabolism were affected profoundly by the medium glucose levels. Glucose consumption was greater for low glucose medium compared to high glucose medium, consistent with known glucose feedback regulation mechanisms. Urea productivity was highest in glucose-free medium. Further, it was seen that lactate acted as an alternative carbon source in the absence of glucose, whereas it acted as a sink for the high and low glucose media. Using a metabolic network flexibility analysis (MNFA) framework with stoichiometric and thermodynamic constraints, intracellular fluxes under varying levels of glucose and insulin were evaluated. The analysis indicates that urea production in HepG2-C3A cells arises via the arginase II pathway rather than from ammonia detoxification. Further, involvement of the putrescine metabolism with glutamine metabolism caused higher urea production in glucose-free medium consistent with higher glutamine uptake. MNFA indicated that in high and low glucose media, glycolysis, glutaminolysis, and oxidative phosphorylation were the main sources of energy (NADH, NADPH, and ATP). In the glucose-free medium, due to very low glycolytic flux, higher malate to pyruvate glutaminolytic flux and TCA cycle contributed more significantly to energy metabolism. The presence of insulin lowered glycerol uptake and corresponding fluxes involved in lipid metabolism for all glucose levels but otherwise exerted negligible effect on metabolism. HepG2-C3A cells thus show distinct differences from primary hepatocytes in terms of energy metabolism and urea production. This knowledge can be used to design media supplements and metabolically engineer cells to restore necessary hepatic functions to HepG2-C3A cells for a range of applications.

Transcriptional and metabolic flux profiling of triadimefon effects on cultured hepatocytes

Conazoles are a class of azole fungicides used to prevent fungal growth in agriculture, for treatment of fungal infections, and are found to be tumorigenic in rats and/or mice. In this study, cultured primary rat hepatocytes were treated to two different concentrations (0.3 and 0.15 mM) of triadimefon, which is a tumorigenic conazole in rat and mouse liver, on a temporal basis with daily media change. Following treatment, cells were harvested for microarray data ranging from 6 to 72 h. Supernatant was collected daily for three days, and the concentrations of various metabolites in the media and supernatant were quantified. Gene expression changes were most significant following exposure to 0.3 mM triadimefon and were characterized mainly by metabolic pathways related to carbohydrate, lipid and amino acid metabolism. Correspondingly, metabolic network flexibility analysis demonstrated a switch from fatty acid synthesis to fatty acid oxidation in cells exposed to triadimefon. It is likely that fatty acid oxidation is active in order to supply energy required for triadimefon detoxification. In 0.15 mM triadimefon treatment, the hepatocytes are able to detoxify the relatively low concentration of triadimefon with less pronounced changes in hepatic metabolism.

Soft constraints-based multiobjective framework for flux balance analysis

The current state of the art for linear optimization in Flux Balance Analysis has been limited to single objective functions. Since mammalian systems perform various functions, a multiobjective approach is needed when seeking optimal flux distributions in these systems. In most of the available multiobjective optimization methods, there is a lack of understanding of when to use a particular objective, and how to combine and/or prioritize mutually competing objectives to achieve a truly optimal solution. To address these limitations we developed a soft constraints based linear physical programming-based flux balance analysis (LPPFBA) framework to obtain a multiobjective optimal solutions. The developed framework was first applied to compute a set of multiobjective optimal solutions for various pairs of objectives relevant to hepatocyte function (urea secretion, albumin, NADPH, and glutathione syntheses) in bioartificial liver systems. Next, simultaneous analysis of the optimal solutions for three objectives was carried out. Further, this framework was utilized to obtain true optimal conditions to improve the hepatic functions in a simulated bioartificial liver system. The combined quantitative and visualization framework of LPPFBA is applicable to any large-scale metabolic network system, including those derived by genomic analyses.

Adipocyte-derived basement membrane extract with biological activity: applications in hepatocyte functional augmentation in vitro

Natural and synthetic biomaterials utilized in tissue engineering applications require a dynamic interplay of complex macromolecular compositions of hydrated extracellular matrices (ECMs) and soluble growth factors. The challenges in utilizing synthetic ECMs is the effective control of temporal and spatial complexity of multiple signal presentation, as compared to natural ECMs that possess the inherent properties of biological recognition, including presentation of receptor-binding ligands, susceptibility to cell-triggered proteolytic degradation, and remodeling. We have developed a murine preadipocyte differentiation system for generating a natural basement membrane extract (Adipogel) comprising ECM proteins (collagen IV, laminin, hyaluronan, and fibronectin) and including relevant growth factors (hepatocyte growth factor, vascular endothelial growth factor, and leukemia inhibitory factor). We have shown the effective utilization of the growth factor-enriched extracellular matrix for enhanced albumin synthesis rate of primary hepatocyte cultures for a period of 10 d as compared to collagen sandwich cultures and comparable or higher function as compared to Matrigel cultures. We have also demonstrated comparable cytochrome P450 1A1 activity for the collagen-Adipogel condition to the collagen double-gel and Matrigel culture conditions. A metabolic analysis revealed that utilization of Adipogel in primary hepatocyte cultures increased serine, glycine, threonine, alanine, tyrosine, valine, methionine, lysine, isoleucine, leucine, phenylalanine, taurine, cysteine, and glucose uptake rates to enhance hepatocyte protein synthesis as compared to collagen double-gel cultures. The demonstrated synthesis, isolation, characterization, and application of Adipogel provide immense potential for tissue engineering and regenerative medicine applications.

A rational design approach for amino acid supplementation in hepatocyte culture

Improvement of culture media for mammalian cells is conducted via empirical adjustments, sometimes aided by statistical design methodologies. Here, we demonstrate a proof of principle for the use of constraints-based modeling to achieve enhanced performance of liver-specific functions of cultured hepatocytes during plasma exposure by adjusting amino acid supplementation and hormone levels in the medium. Flux balance analysis (FBA) is used to determine an amino acid flux profile consistent with a desired output; this is used to design an amino acid supplementation. Under conditions of no supplementation, empirical supplementation, and designed supplementation, hepatocytes were exposed to plasma and their morphology, specific cell functions (urea, albumin production) and lipid metabolism were measured. Urea production under the designed amino acid supplementation was found to be increased compared with previously reported (empirical) amino acid supplementation. Not surprisingly, the urea production attained was less than the theoretical value, indicating the existence of pathways or constraints not present in the current model. Although not an explicit design objective, albumin production was also increased by designed amino acid supplementation, suggesting a functional linkage between these outputs. In conjunction with traditional approaches to improving culture conditions, the rational design approach described herein provides a novel means to tune the metabolic outputs of cultured hepatocytes.

Quantification of statin effects on hepatic cholesterol synthesis by transient (13)C-flux analysis

The present work is the first to deal with the determination of cholesterol synthesis rates in primary rat hepatocytes using transient (13)C-flux analysis. The effects of statins on cholesterol biosynthesis and central carbon fluxes were quantified at a therapeutic concentration of 50 nM atorvastatin using carbon-labeled glutamine. The flux through the cholesterol pathway decreased from 0.27 to 0.08 mmol/l(cv)h in response to the administration of the hypolipidemic drug. Isotopic steady state was reached within 4h in the central carbon metabolism but not in the cholesterol pathway, regardless of whether atorvastatin was administered or not. Marked channeling was observed for the symmetrical tricarboxylic acid cycle intermediates, succinate and fumarate. Non-stationary (13)C-based flux identification delivers both intracellular fluxes and intermediate levels, which was for the first time utilized for investigating systems-level effects of the administered drug by quantifying the flux control of the 3-hydroxy-3-methylglutaryl-coenzyme A reductase.

Insights into the Central Metabolism of Spodoptera frugiperda (Sf-9) and Trichoplusia ni BTI-Tn-5B1-4(Tn-5) Insect Cells by Radiolabeling Studies

The insect cell baculovirus expression vector system (BEVS) is one of the most commonly used expression systems for recombinant protein production. This system is also widely used for the production of recombinant virus and virus-like particles. Although several published reports exist on recombinant protein expression using insect cells, information dealing with their metabolism in vitro is relatively scarce. In this work we have analyzed the metabolism of glucose and glutamine, the main carbon and/or energy compounds, of the two most commonly used insect cell lines, Spodoptera frugiperda (Sf-9) and the Trichoplusia ni BTI-Tn-5B1-4 (Tn-5). Radiolabeled substrates have been used to determine the flux of glucose carbon entering the tricarboxylic acid cycle (TCA) and the pentose phosphate (PP) pathway by direct measurement of 14CO2 produced. The percentage of total glucose metabolized to CO2 via the TCA cycle was higher in the case of the Sf-9 (2.7%) compared to Tn-5 (0.6%) cells, while the percentage of glucose that is metabolized via the PP pathway was comparable at 14% and 16% for the two cell lines, respectively. For both cell lines, the remaining 83% of glucose is metabolized through other pathways generating, for example, lactate, alanine, etc. The percentage of glutamine oxidized in the TCA cycle was approximately 5-fold higher in the case of the Tn-5 (26.1%) as compared to the Sf-9 cells (4.6%). Furthermore, the changes in the metabolic fluxes of glucose and glutamine in Tn-5-PYC cells, which have been engineered to express a cytosolic pyruvate carboxylase, have been studied and compared to the unmodified cells Tn-5. As a result of this metabolic engineering, significant increase in the percentage of glucose oxidized in the TCA cycle (3.2%) as well as in the flux through the PP pathway (34%) of the Tn-5-PYC were observed.

Identification of metabolic fluxes in hepatic cells from transient 13C-labeling experiments: Part II. Flux estimation

This contribution addresses the identification of metabolic fluxes and metabolite concentrations in mammalian cells from transient (13)C-labeling experiments. Whilst part I describes experimental set-up and acquisition of required metabolite and (13)C-labeling data, part II focuses on setting up network models and the estimation of intracellular fluxes. Metabolic fluxes were determined in glycolysis, pentose-phosphate pathway (PPP), and citric acid cycle (TCA) in a hepatoma cell line grown in aerobic batch cultures. In glycolytic and PPP metabolite pools isotopic stationarity was observed within 30 min, whereas in the TCA cycle the labeling redistribution did not reach isotopic steady state even within 180 min. In silico labeling dynamics were in accordance with in vivo (13)C-labeling data. Split ratio between glycolysis and PPP was 57%:43%; intracellular glucose concentration was estimated at 101.6 nmol per 10(6) cells. In contrast to isotopic stationary (13)C-flux analysis, transient (13)C-flux analysis can also be applied to industrially relevant mammalian cell fed-batch and batch cultures.

Application of metabolic flux analysis to identify the mechanisms of free fatty acid toxicity to human hepatoma cell line

Chronic exposure to elevated levels of free fatty acids (FFAs) has been shown to cause cell death (lipotoxicity), but the underlying mechanisms of lipotoxicity in hepatocytes remain unclear. We have previously shown that the saturated FFAs cause much greater toxicity to human hepatoma cells (HepG2) than the unsaturated ones (Srivastava and Chan, 2007). In this study, metabolic flux analysis (MFA) was applied to identify the metabolic changes associated with the cytotoxicity of saturated FFA. Measurements of the fluxes revealed that the saturated FFA, palmitate, was oxidized to a greater extent than the non-toxic oleate and had comparatively less triglyceride synthesis and reduced cystine uptake. Although fatty acid oxidation had a high positive correlation to the cytotoxicity, inhibitor experiments indicated that the cytotoxicity was not due to the higher fatty acid oxidation. Application of MFA revealed that cells exposed to palmitate also had a consistently reduced flux of glutathione (GSH) synthesis but greater de novo ceramide synthesis. These predictions were experimentally confirmed. In silico sensitivity analyses identified that the GSH synthesis was limited by the uptake of cysteine. Western blot analyses revealed that the levels of the cystine transporter xCT, but not that of the GSH-synthesis enzyme glutamyl-cysteine synthase (GCS), were reduced in the palmitate cultures, suggesting the limitation of cysteine import as the cause of the reduced GSH synthesis. Finally, supplementing with N-acetyl L-cysteine (NAC), a cysteine-provider whose uptake does not depend on xCT levels, reduced the FFA-toxicity significantly. Thus, the metabolic alterations that contributed to the toxicity and suggested treatments to reduce the toxicity were identified, which were experimentally validated.

Postburn trauma insulin resistance and fat metabolism

Hyperglycemia and insulin resistance have long been recognized in severe burn patients. More recently, it has been observed that controlling hyperglycemia, or alleviating insulin resistance, is associated with improved outcomes. This has led to a renewed interest in the etiology of insulin resistance in this population. The postinjury hyperglycemic response appears to be associated with multiple metabolic abnormalities, such as elevated basal energy expenditure, increased protein catabolism, and, notably, significant alterations in fat metabolism. The synergy of all of the responses is not understood, although many studies have been conducted. In this article we will review the present understanding of the relationship between fat metabolism and insulin resistance posttrauma, and discuss some of the recent discoveries and potential therapeutic measures. We propose that the insulin resistance is likely related to the development of "ectopic" fat stores, i.e., triglyceride (TG) storage in sites such as the liver and muscle cells. Deposition of TG in ectopic sites is due to an increase in free fatty acid delivery secondary to catecholamine-induced lipolysis, in conjunction with decreased beta-oxidation within muscle and decreased hepatic secretion of fats. The resultant increases in intracellular TG or related lipid products may in turn contribute to alterations in insulin signaling.

Investigation of metabolic objectives in cultured hepatocytes

Using optimization based methods to predict fluxes in metabolic flux balance models has been a successful approach for some microorganisms, enabling construction of in silico models and even inference of some regulatory motifs. However, this success has not been translated to mammalian cells. The lack of knowledge about metabolic objectives in mammalian cells is a major obstacle that prevents utilization of various metabolic engineering tools and methods for tissue engineering and biomedical purposes. In this work, we investigate and identify possible metabolic objectives for hepatocytes cultured in vitro. To achieve this goal, we present a special data-mining procedure for identifying metabolic objective functions in mammalian cells. This multi-level optimization based algorithm enables identifying the major fluxes in the metabolic objective from MFA data in the absence of information about critical active constraints of the system. Further, once the objective is determined, active flux constraints can also be identified and analyzed. This information can be potentially used in a predictive manner to improve cell culture results or clinical metabolic outcomes. As a result of the application of this method, it was found that in vitro cultured hepatocytes maximize oxygen uptake, coupling of urea and TCA cycles, and synthesis of serine and urea. Selection of these fluxes as the metabolic objective enables accurate prediction of the flux distribution in the system given a limited amount of flux data; thus presenting a workable in silico model for cultured hepatocytes. It is observed that an overall homeostasis picture is also emergent in the findings.

Contribution of gene expression to metabolic fluxes in hypermetabolic livers induced through burn injury and cecal ligation and puncture in rats

Severe injury activates many stress-related and inflammatory pathways that can lead to a systemic hypermetabolic state. Prior studies using perfused hypermetabolic rat livers have identified intrinsic metabolic flux changes that were not dependent upon the continual presence of elevated stress hormones and substrate loads. We investigated the hypothesis that such changes may be due to persistent alterations in gene expression. A systemic hypermetabolic response was induced in rats by applying a moderate burn injury followed 2 days later by cecum ligation and puncture (CLP) to produce sepsis. Control animals received a sham-burn followed by CLP, or a sham-burn followed by sham-CLP. Two days after CLP, livers were analyzed for gene expression changes using DNA microarrays and for metabolism alterations by ex vivo perfusion coupled with Metabolic Flux Analysis. Burn injury prior to CLP increased fluxes while decreases in gene expression levels were observed. Conversely, CLP alone significantly increased metabolic gene expression, but decreased many of the corresponding metabolic fluxes. Burn injury combined with CLP led to the most dramatic changes, where concurrent changes in fluxes and gene expression levels occurred in about 1/3 of the reactions. The data are consistent with the notion that in this model, burn injury prior to CLP increased fluxes through post-translational mechanisms with little contribution of gene expression, while CLP treatment up-regulated the metabolic machinery by transcriptional mechanisms. Overall, these data show that mRNA changes measured at a single time point by DNA microarray analysis do not reliably predict metabolic flux changes in perfused livers.

Integrated energy and flux balance based multiobjective framework for large-scale metabolic networks

Flux balance analysis (FBA) provides a framework for the estimation of intracellular fluxes and energy balance analysis (EBA) ensures the thermodynamic feasibility of the computed optimal fluxes. Previously, these techniques have been used to obtain optimal fluxes that maximize a single objective. Because mammalian systems perform various functions, a multi-objective approach is needed when seeking optimal flux distributions in such systems. For example, hepatocytes perform several metabolic functions at various levels depending on environmental conditions; furthermore, there is a potential benefit to enhance some of these functions for applications such as bioartificial liver (BAL) support devices. Herein we developed a multi-objective optimization approach that couples the normalized Normal Constraint (NC) with both FBA and EBA to obtain multi-objective Pareto-optimal solutions. We investigated the Pareto frontiers in gluconeogenic and glycolytic hepatocytes for various combinations of liver-specific objectives (albumin synthesis, glutathione synthesis, NADPH synthesis, ATP generation, and urea secretion). Next, we evaluated the impact of experimental flux measurements on the Pareto frontiers. We found that measurements induce dramatic changes in Pareto frontiers and further constrain the network fluxes. This multi-objective optimality analysis may help explain certain features of the metabolic control of hepatocytes, which is relevant to the response to hepatocytes and liver to various physiological stimuli and disease states.

Sodium butyrate-treated embryonic stem cells yield hepatocyte-like cells expressing a glycolytic phenotype

Embryonic stem cells serve as a promising technology to obtain specific cell types for a number of biomedical applications. Because traditional techniques, such as embryoid body formation result in a wide array of differentiated cells such as hepatic, neuronal, and cardiac lineages, strategies have been utilized which favor cell-specific differentiation to generate more uniformity. In the present study, we have investigated the use of sodium butyrate in a monolayer culture configuration to mediate hepatocyte differentiation of murine embryonic stem cells. Several functional assays used to characterize hepatocyte function (viz. urea secretion, intracellular albumin content, cytokeratin 18, and glycogen staining) were used to analyze the differentiating cell population, suggesting the presence of an enriched population of hepatocyte-like cells. Since mature hepatocytes mediate energy metabolism predominantly through oxidative means as opposed to hepatocyte precursors, which are primarily glycolytic, we have performed a kinetic analysis of glycolytic and functional capacity to characterize the differentiated cells. In conjunction with mitochondrial mass and activity measurements, we show that Na-butyrate-mediated differentiated cells mediate energy metabolism predominantly through glycolysis. This metabolic and mitochondrial characterization can assist in evaluating stem cell differentiation and may prove useful in identifying key regulatory molecules in mediating further differentiation.

Estradiol stimulates the biosynthetic pathways of breast cancer cells: detection by metabolic flux analysis

Selective estrogen receptor (ER) modulators are highly successful breast cancer therapies, but they are not effective in patients with ER negative and selective estrogen receptor modulator (SERM)-resistant tumors. Understanding the mechanisms of estrogen-stimulated proliferation may provide a route to design estrogen-independent therapies that would be effective in these patients. In this study, metabolic flux analysis was used to determine the intracellular fluxes that are significantly affected by estradiol stimulation in MCF-7 breast cancer cells. Intracellular fluxes were calculated from nuclear magnetic resonance (NMR)-generated isotope enrichment data and extracellular metabolite fluxes, using a specific flux analysis algorithm. The metabolic pathway model used by the algorithm includes glycolysis, the tricarboxylic acid cycle (TCA cycle), the pentose phosphate pathway, glutamine catabolism, pyruvate carboxylase, and malic enzyme. The pathway model also incorporates mitochondrial compartmentalization and reversible trans-mitochondrial membrane reactions to more accurately describe the role of mitochondria in cancer cell proliferation. Flux results indicate that estradiol significantly increases carbon flow through the pentose phosphate pathway and increases glutamine consumption. In addition, intra-mitochondrial malic enzyme was found to be inactive and the malate-aspartate shuttle (MAS) was only minimally active. The inactivity of these enzymes indicates that glutamine is not oxidized within mitochondria, but is consumed primarily to provide biosynthetic precursors. The excretion of glutamine carbons from the mitochondria has the secondary effect of limiting nicotinamide adenine dinucleotide (NADH) recycle, resulting in NADH buildup in the cytosol and the excretion of lactate. The observed dependence of breast cancer cells on pentose phosphate pathway activity and glutamine consumption for estradiol-stimulated biosynthesis suggests that these pathways may be targets for estrogen-independent breast cancer therapies.

Alginate-PLL microencapsulation: effect on the differentiation of embryonic stem cells into hepatocytes

The emergence of hepatocyte based clinical and pharmaceutical technologies, has been limited by the absence of a stable hepatocyte cell source. Embryonic stem cells may represent a potential solution to this cell source limitation problem since they are highly proliferative, renewable, and pluripotent. Although many investigators have described techniques to effectively differentiate stem cells into a variety of mature cell lineages, their practicality is limited by: (1) low yields of fully differentiated cells, (2) absence of large scale processing considerations, and (3) ineffective downstream enrichment protocols. Thus, a differentiation platform that may be modified to induce and sustain differentiated cell function and scaled to increase differentiated cell yield would improve current stem cell differentiation strategies. Microencapsulation provides a vehicle for the discrete control of key cell culture parameters such as the diffusion of growth factors, metabolites, and wastes. In addition, both cell seeding density and bead composition may be manipulated. In order to assess the feasibility of directing stem cell differentiation via microenvironment regulation, we have developed a murine embryonic stem cell (ES) alginate poly-l-lysine microencapsulation hepatocyte differentiation system. Our results indicate that the alginate microenvironment maintains cell viability, is conducive to ES cell differentiation, and maintains differentiated cellular function. This system may ultimately assist in developing scalable stem cell differentiation strategies.

Cellular to tissue informatics: approaches to optimizing cellular function of engineered tissue

Tissue engineering is a rapidly expanding, multi-disciplinary field in biomedicine. It provides the ability to manipulate living cells and biomaterials for the purpose of restoring, maintaining, and enhancing tissue and organ function. Scientists have engineered various tissues in the body, from skin substitutes to artificial nerves to heart tissues, with varying degrees of success. Although the field of tissue engineering has come a long way since its first successful demonstration by Bisceglie in the 1930s, methods of coaxing them into functional tissues have been predominantly empirical to date. To successfully develop tissue-engineered organs, it is important to understand how to maintain the cells under conditions that maximize their ability to perform their physiological roles, regardless of their environment. In that context, a methodology that combines empirical data with mathematical and statistical techniques, such as metabolic engineering and cellular informatics, to systematically determine the optimal (1) type of cell to use, (2) scaffold properties and the corresponding processing conditions to achieve those properties, and (3) the required types and levels of environmental factors and the operating conditions needed in the bioreactor, will enable the design of viable and functional tissues tailored to the specific requirements of individual situations.

Novel quantitative tools for engineering analysis of hepatocyte cultures in bioartificial liver systems

Extracorporeal bioartificial liver devices (BAL) are perhaps among the most promising technologies for the treatment of liver failure, but significant technical challenges remain in order to develop systems with sufficient processing capacity and of manageable size. One key limitation is that during BAL operation, when the device is exposed to plasma from the patient, hepatocytes are prone to accumulate intracellular lipids and exhibit poor liver-specific functions. Based on hepatic intermediary metabolism, we have utilized mathematical programming techniques to optimize the biochemical environment of hepatocyte cultures towards the desired effect of increased albumin and urea synthesis. To investigate the feasible range of optimal hepatic function, we have obtained a Pareto optimal set of solutions corresponding to liver-specific functions of urea and albumin secretion in the metabolic framework using multiobjective optimization. The importance of amino acids in the supplementation and the criticality of the metabolic pathways have been investigated using logic-based programming techniques. Since the metabolite measurements are bound to be patient specific, and hence subject to variability, uncertainty has to be integrated with system analysis to improve the prediction of hepatic function. We have used the concept of two stage stochastic programming to obtain robust solutions by considering extracellular variability. The proposed analysis represents a new systematic approach to analyze behavior of hepatocyte cultures and optimize different operating parameters for an extracorporeal device based on real-time conditions.

Insulin Concentration during Preconditioning Mediates the Regulation of Urea Synthesis during Exposure to Amino Acid-Supplemented Plasma

Understanding the effects of preconditioning on cellular metabolism is important in providing insight into how cells and tissues may behave when confronted with alterations in their environment. Previously, elevated accumulation of lipids and a correspondingly reduced rate of urea synthesis were found in primary heptocytes preconditioned in culture medium containing high levels of insulin and then exposed to plasma. Subsequent studies found that preconditioning primary hepatocytes in medium containing low levels of insulin before exposure to plasma supplemented with amino acids was able to confer resistance to the lipid-accumulating effect of plasma exposure and restored urea synthesis. In the current study, we investigated the effects of insulin preconditioning and amino acid supplementation on the gene expression profile of the urea cycle and fatty acid metabolism enzymes. We found that insulin preconditioning mediates the effects of amino acids in the plasma exposure period on urea synthesis. Urea synthesis is regulated by insulin and amino acids through both short-term and long-term control. Possible mechanisms of long-term control through transcriptional regulation of urea synthesis by insulin, amino acids, and enzymes and transcription factors associated with lipid metabolism are discussed.

Hepatic tissue engineering for adjunct and temporary liver support: critical technologies

The severe donor liver shortage, high cost, and complexity of orthotopic liver transplantation have prompted the search for alternative treatment strategies for end-stage liver disease, which would require less donor material, be cheaper, and less invasive. Hepatic tissue engineering encompasses several approaches to develop adjunct internal liver support methods, such as hepatocyte transplantation and implantable hepatocyte-based devices, as well as temporary extracorporeal liver support techniques, such as bioartificial liver assist devices. Many tissue engineered liver support systems have passed the "proof of principle" test in preclinical and clinical studies; however, they have not yet been found sufficiently reliably effective for routine clinical use. In this review we describe, from an engineering perspective, the progress and remaining challenges that must be resolved in order to develop the next generation of implantable and extracorporeal devices for adjunct or temporary liver assist.

Expression profiling analysis of the metabolic and inflammatory changes following burn injury in rats

Burn injury initiates an inflammatory response as part of the healing process that is associated with extensive metabolic adjustments. While most studies have focused on understanding these changes from a biochemical perspective, not much work has been done to characterize these processes at the gene expression level. As a first step, we have comprehensively analyzed changes in gene expression in rat livers during the first 24 h after burn injury using Affymetrix GeneChips, which showed 339 genes to be differentially expressed at a statistical significance of P < 0.05 and changed at least twofold. Functional classification based on gene ontology terms indicated that two categories, metabolism (28%) and inflammation (14%), accounted for nearly 42%. Detailed analysis of the metabolism group of genes indicated that fatty acid (FA) and triglyceride (TG) biosynthesis in the liver were unchanged, whereas TG utilization, FA import, and beta-oxidation increased after burn injury. The increased FA pools after burn injury appear to serve as substrates for ATP production. Following burn injury, the cholesterol biosynthetic pathway was suppressed while cholesterol was increasingly imported and converted into bile acids. The inflammatory genes that were altered included several classic acute phase response markers, as well as genes involved in the complement, kinin, clotting, and fibrinolytic protein systems. These temporally coordinated changes in gene expression were also corroborated by biochemical measurements for FA, TG, cholesterol, and ATP. Together, these data indicate that FA are increasingly imported and oxidized in the liver to meet the enhanced energy demands arising from an inflammatory response during the first 24 h after burn injury.