The human hepatocyte cell lines IHH and HepaRG: models to study glucose, lipid and lipoprotein metabolism

Metabolic diseases reach epidemic proportions. A better knowledge of the associated alterations in the metabolic pathways in the liver is necessary. These studies need in vitro human cell models. Several human hepatoma models are used, but the response of many metabolic pathways to physiological stimuli is often lost. Here, we characterize two human hepatocyte cell lines, IHH and HepaRG, by analysing the expression and regulation of genes involved in glucose and lipid metabolism. Our results show that the glycolysis pathway is activated by glucose and insulin in both lines. Gluconeogenesis gene expression is induced by forskolin in IHH cells and inhibited by insulin in both cell lines. The lipogenic pathway is regulated by insulin in IHH cells. Finally, both cell lines secrete apolipoprotein B-containing lipoproteins, an effect promoted by increasing glucose concentrations. These two human cell lines are thus interesting models to study the regulation of glucose and lipid metabolism.     

Chloroplast lipid biosynthesis is fine-tuned to thylakoid membrane remodeling during light acclimation

Reprogramming metabolism, in addition to modifying the structure and function of the photosynthetic machinery, is crucial for plant acclimation to changing light conditions. One of the key acclimatory responses involves reorganization of the photosynthetic membrane system including changes in thylakoid stacking. Glycerolipids are the main structural component of thylakoids and their synthesis involves two main pathways localized in the plastid and the endoplasmic reticulum (ER); however, the role of lipid metabolism in light acclimation remains poorly understood. We found that fatty acid synthesis, membrane lipid content, the plastid lipid biosynthetic pathway activity, and the degree of thylakoid stacking were significantly higher in plants grown under low light compared with plants grown under normal light. Plants grown under high light, on the other hand, showed a lower rate of fatty acid synthesis, a higher fatty acid flux through the ER pathway, higher triacylglycerol content, and thylakoid membrane unstacking. We additionally demonstrated that changes in rates of fatty acid synthesis under different growth light conditions are due to post-translational regulation of the plastidic acetyl-CoA carboxylase activity. Furthermore, Arabidopsis mutants defective in one of the two glycerolipid biosynthetic pathways displayed altered growth patterns and a severely reduced ability to remodel thylakoid architecture, particularly under high light. Overall, this study reveals how plants fine-tune fatty acid and glycerolipid biosynthesis to cellular metabolic needs in response to long-term changes in light conditions, highlighting the importance of lipid metabolism in light acclimation.

Lipid metabolism is fine-tuned to cellular metabolic demands during thylakoid membrane remodeling in response to long-term changes in light intensity.     

Dynamic in vivo metabolome response of Saccharomyces cerevisiae to a stepwise perturbation of the ATP requirement for benzoate export

Although much information is available on in vitro role of ATP in regulation, the in vivo kinetics of reactions in which ATP plays a role are only partly known. In order to study such reactions, it is therefore necessary to study the role of ATP in vivo. This study presents an in vivo, targeted perturbation of the ATP flux in aerobic glucose-limited chemostat cultures of Saccharomyces cerevisiae, which was accomplished by transiently (20 min) changing the extracellular undissociated benzoic acid concentration via the pH of the culture. The performed pH shifts resulted in, within about 20 s, a 40% decrease (pH upshift) or a 23% increase (pH downshift) of the calculated ATP consumption rate while the specific glucose uptake rate did not change because of the glucose-limited condition. The pH upshift resulted in a strong decrease in the glycolytic and TCA cycle fluxes; carbon and energy balances indicated an increased flux toward storage carbohydrates. As expected, the pH downshift leads to the opposite effects. Overall, consistent responses were observed in the metabolic fluxes, the off gas concentrations of O(2) and CO(2) and intracellular metabolite concentrations, except for the concentrations of adenosine nucleotides which unexpectedly only showed minor dynamics. This demonstrates that our knowledge of the regulation of the ATP level, the storage metabolism, and central carbon metabolism of yeast is still incomplete. The new dynamic metabolite datasets obtained in this study will prove of great value in developing kinetic models.     

Sources for structure formation and switches in metabolic pathways.

Zonation of function, i.e. localization of metabolic activity in certain regions of histologically uniform tissues, is an often observed phenomenon. Moreover, experiments show that such metabolic patterns are highly dynamical. Since in the pathways of intermediary metabolism no autocatalytic reactions are observed, different types of metabolic regulation are sources of the non-linearities necessary for structure formation. Two models of biochemical reactions frequently encountered in metabolic pathways, namely a bisubstrate kinetics model with substrate inhibition, and an allosteric model with product regulation, are presented. It is shown, that they are well-suited to reproduce the dynamical behavior suggested by experimental findings, like their capability to act as switches, or their ability for spatio-temporal pattern formation in mature tissues.     

Monte-Carlo Modeling of the Central Carbon Metabolism of Lactococcus lactis: Insights into Metabolic Regulation

Metabolic pathways are complex dynamic systems whose response to perturbations and environmental challenges are governed by multiple interdependencies between enzyme properties, reactions rates, and substrate levels. Understanding the dynamics arising from such a network can be greatly enhanced by the construction of a computational model that embodies the properties of the respective system. Such models aim to incorporate mechanistic details of cellular interactions to mimic the temporal behavior of the biochemical reaction system and usually require substantial knowledge of kinetic parameters to allow meaningful conclusions. Several approaches have been suggested to overcome the severe data requirements of kinetic modeling, including the use of approximative kinetics and Monte-Carlo sampling of reaction parameters. In this work, we employ a probabilistic approach to study the response of a complex metabolic system, the central metabolism of the lactic acid bacterium Lactococcus lactis, subject to perturbations and brief periods of starvation. Supplementing existing methodologies, we show that it is possible to acquire a detailed understanding of the control properties of a corresponding metabolic pathway model that is directly based on experimental observations. In particular, we delineate the role of enzymatic regulation to maintain metabolic stability and metabolic recovery after periods of starvation. It is shown that the feedforward activation of the pyruvate kinase by fructose-1,6-bisphosphate qualitatively alters the bifurcation structure of the corresponding pathway model, indicating a crucial role of enzymatic regulation to prevent metabolic collapse for low external concentrations of glucose. We argue that similar probabilistic methodologies will help our understanding of dynamic properties of small-, medium- and large-scale metabolic networks models.     

Stress eating and tuning out: Cancer cells re-wire metabolism to counter stress

Abstract

Cancer cells reprogram metabolism to maintain rapid proliferation under often stressful conditions. Glycolysis and glutaminolysis are two central pathways that fuel cancer metabolism. Allosteric regulation and metabolite driven post-translational modifications of key metabolic enzymes allow cancer cells glycolysis and glutaminolysis to respond to changes in nutrient availability and the tumor microenvironment. While increased aerobic glycolysis (the Warburg effect) has been a noted part of cancer metabolism for over 80 years, recent work has shown that the elevated levels of glycolytic intermediates are critical to cancer growth and metabolism due to their ability to feed into the anabolic pathways branching off glycolysis such as the pentose phosphate pathway and serine biosynthesis pathway. The key glycolytic enzymes phosphofructokinase-1 (PFK1), pyruvate kinase (PKM2) and phosphoglycerate mutase 1 (PGAM1) are regulated by upstream and downstream metabolites to balance glycolytic flux with flux through anabolic pathways. Glutamine regulation is tightly controlled by metabolic intermediates that allosterically inhibit and activate glutamate dehydrogenase, which fuels the tricarboxylic acid cycle by converting glutamine derived glutamate to α-ketoglutarate. The elucidation of these key allosteric regulatory hubs in cancer metabolism will be essential for understanding and predicting how cancer cells will respond to drugs that target metabolism. Additionally, identification of the structures involved in allosteric regulation will inform the design of anti-metabolism drugs which bypass the off-target effects of substrate mimics. Hence, this review aims to provide an overview of allosteric control of glycolysis and glutaminolysis.     

Proteomic survey of copper-binding proteins in Arabidopsis roots by immobilized metal affinity chromatography and mass spectrometry

To plants, copper is vitally essential at low concentrations but extremely toxic at elevated concentrations. Plants have evolved a suite of mechanisms that modulate the uptake, distribution, and utilization of copper ions. These mechanisms require copper-interacting proteins for transporting, chelating, and sequestrating copper ions. In this study, we have systematically screened for copper-interacting proteins in Arabidopsis roots via copper-immobilized metal affinity chromatography (Cu-IMAC). We also compared Arabidopsis root metalloproteomes with affinity to Cu-IMAC and Zn-IMAC. From the identities of 38 protein spots with affinity to Cu-IMAC, 35 unique proteins were identified. Functional classification of these proteins includes redox/hydrolytic reactions, amino acid metabolism, glutathione metabolism, phosphorylation, translation machinery, membrane-associated proteins, and vegetative storage proteins. Potential copper-interacting motifs were predicted and scored. Six candidate motifs, H-(X)5 -H, H-(X)7 -H, H-(X)12 -H, H-(X)6 -M, M-(X)7 -H, and H-(X)3 -C, are present in Cu-IMAC-isolated proteins with higher frequency than in the whole Arabidopsis proteome.     

Non-linear reduction for kinetic models of metabolic reaction networks

Kinetic models of metabolic networks are essential for predicting and optimizing the transient behavior of cells in culture. However, such models are inherently high dimensional and stiff due to the large number of species and reactions involved and to kinetic rate constants of widely different orders of magnitude. In this paper we address the problem of deriving non-stiff, reduced-order non-linear models of the dominant dynamics of metabolic networks with fast and slow reactions. We present a method, based on singular perturbation analysis, which allows the systematic identification of quasi-steady-state conditions for the fast reactions, and the derivation of explicit non-linear models of the slow dynamics independent of the fast reaction rate expressions. The method is successfully applied to detailed models of metabolism in human erythrocytes and Saccharomyces cerevisiae.     

Integrating cybernetic modeling with pathway analysis provides a dynamic, systems-level description of metabolic control

Cybernetic modeling strives to uncover the inbuilt regulatory programs of biological systems and leverage them toward computational prediction of metabolic dynamics. Because of its focus on incorporating the global aims of metabolism, cybernetic modeling provides a systems-oriented approach for describing regulatory inputs and inferring the impact of regulation within biochemical networks. Combining cybernetic control laws with concepts from metabolic pathway analysis has culminated in a systematic strategy for constructing cybernetic models, which was previously lacking. The newly devised framework relies upon the simultaneous application of local controls that maximize the net flux through each elementary flux mode and global controls that modulate the activities of these modes to optimize the overall nutritional state of the cell. The modeling concepts are illustrated using a simple linear pathway and a larger network representing anaerobic E. coli central metabolism. The E. coli model successfully describes the metabolic shift that occurs upon deleting the pta-ackA operon that is responsible for fermentative acetate production. The model also furnishes predictions that are consistent with experimental results obtained from additional knockout strains as well as strains expressing heterologous genes. Because of the stabilizing influence of the included control variables, the resulting cybernetic models are more robust and reliable than their predecessors in simulating the network response to imposed genetic and environmental perturbations.     

Elevated pCO2 affects the lactate metabolic shift in CHO cell culture processes

The shift from lactate production to consumption in CHO cell metabolism is a key event during cell culture cultivations and is connected to increased culture longevity and final product titers. However, the mechanisms controlling this metabolic shift are not yet fully understood. Variations in lactate metabolism have been mainly reported to be induced by process pH and availability of substrates like glucose and glutamine. The aim of this study was to investigate the effects of elevated pCO₂ concentrations on the lactate metabolic shift phenomena in CHO cell culture processes. In this publication, we show that at elevated pCO₂ in batch and fed‐batch cultures, the lactate metabolic shift was absent in comparison to control cultures at lower pCO₂ values. Furthermore, through metabolic flux analysis we found a link between the lactate metabolic shift and the ratio of NADH producing and regenerating intracellular pathways. This ratio was mainly affected by a reduced oxidative capacity of cultures at elevated pCO₂. The presented results are especially interesting for large‐scale and perfusion processes where increased pCO₂ concentrations are likely to occur. Our results suggest, that so far unexplained metabolic changes may be connected to increased pCO₂ accumulation in larger scale fermentations. Finally, we propose several mechanisms through which increased pCO₂ might affect the cell metabolism and briefly discuss methods to enable the lactate metabolic shift during cell cultivations.