Combining metabolic flux analysis tools and 13C NMR to estimate intracellular fluxes of cultured astrocytes

Acidosis Maintains the Function of Brain Mitochondria in Hypoxia-Tolerant Triplefin Fish: A Strategy to Survive Acute Hypoxic Exposure?

The vertebrate brain is generally very sensitive to acidosis, so a hypoxia-induced decrease in pH is likely to have an effect on brain mitochondria (mt). Mitochondrial respiration (JO₂) is required to generate an electrical gradient (ΔΨm) and a pH gradient to power ATP synthesis, yet the impact of pH modulation on brain mt function remains largely unexplored. As intertidal fishes within rock pools routinely experience hypoxia and reoxygenation, they would most likely experience changes in cellular pH. We hence compared four New Zealand triplefin fish species ranging from intertidal hypoxia-tolerant species (HTS) to subtidal hypoxia-sensitive species (HSS). We predicted that HTS would tolerate acidosis better than HSS in terms of sustaining mt structure and function. Using respirometers coupled to fluorimeters and pH electrodes, we titrated lactic-acid to decrease the pH of the media, and simultaneously recorded JO₂, ΔΨm, and H⁺ buffering capacities within permeabilized brain and swelling of mt isolated from non-permeabilized brains. We then measured ATP synthesis rates in the most HTS (Bellapiscus medius) and the HSS (Forsterygion varium) at pH 7.25 and 6.65. Mitochondria from HTS brain did have greater H⁺ buffering capacities than HSS mt (∼10 mU pH.mg_protein ^-1). HTS mt swelled by 40% when exposed to a decrease of 1.5 pH units, and JO₂ was depressed by up to 15% in HTS. However, HTS were able to maintain ΔΨm near -120 mV. Estimates of work, in terms of charges moved across the mt inner-membrane, suggested that with acidosis, HTS mt may in part harness extra-mt H⁺ to maintain ΔΨm, and could therefore support ATP production. This was confirmed with elevated ATP synthesis rates and enhanced P:O ratios at pH 6.65 relative to pH 7.25. In contrast, mt volumes and ΔΨm decreased downward pH 6.9 in HSS mt and paradoxically, JO₂ increased (∼25%) but ATP synthesis and P:O ratios were depressed at pH 6.65. This indicates a loss of coupling in the HSS with acidosis. Overall, the mt of these intertidal fish have adaptations that enhance ATP synthesis efficiency under acidic conditions such as those that occur in hypoxic or reoxygenated brain.

Glutamine-Glutamate Cycle Flux Is Similar in Cultured Astrocytes and Brain and Both Glutamate Production and Oxidation Are Mainly Catalyzed by Aspartate Aminotransferase

The glutamine-glutamate cycle provides neurons with astrocyte-generated glutamate/γ-aminobutyric acid (GABA) and oxidizes glutamate in astrocytes, and it returns released transmitter glutamate/GABA to neurons after astrocytic uptake. This review deals primarily with the glutamate/GABA generation/oxidation, although it also shows similarity between metabolic rates in cultured astrocytes and intact brain. A key point is identification of the enzyme(s) converting astrocytic α-ketoglutarate to glutamate and vice versa. Most experiments in cultured astrocytes, including those by one of us, suggest that glutamate formation is catalyzed by aspartate aminotransferase (AAT) and its degradation by glutamate dehydrogenase (GDH). Strongly supported by results shown in Table 1 we now propose that both reactions are primarily catalyzed by AAT. This is possible because the formation occurs in the cytosol and the degradation in mitochondria and they are temporally separate. High glutamate/glutamine concentrations abolish the need for glutamate production from α-ketoglutarate and due to metabolic coupling between glutamate synthesis and oxidation these high concentrations render AAT-mediated glutamate oxidation impossible. This necessitates the use of GDH under these conditions, shown by insensitivity of the oxidation to the transamination inhibitor aminooxyacetic acid (AOAA). Experiments using lower glutamate/glutamine concentration show inhibition of glutamate oxidation by AOAA, consistent with the coupled transamination reactions described here.

Solution state nuclear magnetic resonance spectroscopy for biological metabolism and pathway intermediate analysis

Using nuclear magnetic resonance (NMR) spectroscopy in the study of metabolism has been immensely popular in medical- and health-related research but has yet to be widely applied to more fundamental biological problems. This review provides some NMR background relevant to metabolism, describes why ¹H NMR spectra are complex as well as introducing relevant terminology and definitions. The applications and practical considerations of NMR metabolic profiling and ¹³C NMR-based flux analyses are discussed together with the elegant 'enzyme trap' approach for identifying novel metabolic pathway intermediates. The importance of sample preparation and data analysis are also described and explained with reference to data precision and multivariate analysis to introduce researchers unfamiliar with NMR and metabolism to consider this technique for their research interests. Finally, a brief glance into the future suggests NMR-based metabolism has room to expand in the 21st century through new isotope labels, and NMR technologies and methodologies.

Intracellular nucleic acid delivery by the supercharged dengue virus capsid protein

Supercharged proteins are a recently identified class of proteins that have the ability to efficiently deliver functional macromolecules into mammalian cells. They were first developed as bioengineering products, but were later found in the human proteome. In this work, we show that this class of proteins with unusually high net positive charge is frequently found among viral structural proteins, more specifically among capsid proteins. In particular, the capsid proteins of viruses from the Flaviviridae family have all a very high net charge to molecular weight ratio (> +1.07/kDa), thus qualifying as supercharged proteins. This ubiquity raises the hypothesis that supercharged viral capsid proteins may have biological roles that arise from an intrinsic ability to penetrate cells. Dengue virus capsid protein was selected for a detailed experimental analysis. We showed that this protein is able to deliver functional nucleic acids into mammalian cells. The same result was obtained with two isolated domains of this protein, one of them being able to translocate lipid bilayers independently of endocytic routes. Nucleic acids such as siRNA and plasmids were delivered fully functional into cells. The results raise the possibility that the ability to penetrate cells is part of the native biological functions of some viral capsid proteins.

Unraveling the complex metabolic nature of astrocytes

Since the initial description of astrocytes by neuroanatomists of the nineteenth century, a critical metabolic role for these cells has been suggested in the central nervous system. Nonetheless, it took several technological and conceptual advances over many years before we could start to understand how they fulfill such a role. One of the important and early recognized metabolic function of astrocytes concerns the reuptake and recycling of the neurotransmitter glutamate. But the description of this initial property will be followed by several others including an implication in the supply of energetic substrates to neurons. Indeed, despite the fact that like most eukaryotic non-proliferative cells, astrocytes rely on oxidative metabolism for energy production, they exhibit a prominent aerobic glycolysis capacity. Moreover, this unusual metabolic feature was found to be modulated by glutamatergic activity constituting the initial step of the neurometabolic coupling mechanism. Several approaches, including biochemical measurements in cultured cells, genetic screening, dynamic cell imaging, nuclear magnetic resonance spectroscopy and mathematical modeling, have provided further insights into the intrinsic characteristics giving rise to these key features of astrocytes. This review will provide an account of the different results obtained over several decades that contributed to unravel the complex metabolic nature of astrocytes that make this cell type unique.

Effects of hypoglycaemia on neuronal metabolism in the adult brain: role of alternative substrates to glucose

Hypoglycaemia is characterized by decreased blood glucose levels and is associated with different pathologies (e.g. diabetes, inborn errors of metabolism). Depending on its severity, it might affect cognitive functions, including impaired judgment and decreased memory capacity, which have been linked to alterations of brain energy metabolism. Glucose is the major cerebral energy substrate in the adult brain and supports the complex metabolic interactions between neurons and astrocytes, which are essential for synaptic activity. Therefore, hypoglycaemia disturbs cerebral metabolism and, consequently, neuronal function. Despite the high vulnerability of neurons to hypoglycaemia, important neurochemical changes enabling these cells to prolong their resistance to hypoglycaemia have been described. This review aims at providing an overview over the main metabolic effects of hypoglycaemia on neurons, covering in vitro and in vivo findings. Recent studies provided evidence that non-glucose substrates including pyruvate, glycogen, ketone bodies, glutamate, glutamine, and aspartate, are metabolized by neurons in the absence of glucose and contribute to prolong neuronal function and delay ATP depletion during hypoglycaemia. One of the pathways likely implicated in the process is the pyruvate recycling pathway, which allows for the full oxidation of glutamate and glutamine. The operation of this pathway in neurons, particularly after hypoglycaemia, has been re-confirmed recently using metabolic modelling tools (i.e. Metabolic Flux Analysis), which allow for a detailed investigation of cellular metabolism in cultured cells. Overall, the knowledge summarized herein might be used for the development of potential therapies targeting neuronal protection in patients vulnerable to hypoglycaemic episodes.

Estimation of dynamic flux profiles from metabolic time series data

Background

Advances in modern high-throughput techniques of molecular biology have enabled top-down approaches for the estimation of parameter values in metabolic systems, based on time series data. Special among them is the recent method of dynamic flux estimation (DFE), which uses such data not only for parameter estimation but also for the identification of functional forms of the processes governing a metabolic system. DFE furthermore provides diagnostic tools for the evaluation of model validity and of the quality of a model fit beyond residual errors. Unfortunately, DFE works only when the data are more or less complete and the system contains as many independent fluxes as metabolites. These drawbacks may be ameliorated with other types of estimation and information. However, such supplementations incur their own limitations. In particular, assumptions must be made regarding the functional forms of some processes and detailed kinetic information must be available, in addition to the time series data.

Results

The authors propose here a systematic approach that supplements DFE and overcomes some of its shortcomings. Like DFE, the approach is model-free and requires only minimal assumptions. If sufficient time series data are available, the approach allows the determination of a subset of fluxes that enables the subsequent applicability of DFE to the rest of the flux system. The authors demonstrate the procedure with three artificial pathway systems exhibiting distinct characteristics and with actual data of the trehalose pathway in Saccharomyces cerevisiae.

Conclusions

The results demonstrate that the proposed method successfully complements DFE under various situations and without a priori assumptions regarding the model representation. The proposed method also permits an examination of whether at all, to what degree, or within what range the available time series data can be validly represented in a particular functional format of a flux within a pathway system. Based on these results, further experiments may be designed to generate data points that genuinely add new information to the structure identification and parameter estimation tasks at hand.

Rat brain slices oxidize glucose at high rates: a (13)C NMR study

Since glucose is the main cerebral substrate, we have characterized the metabolism of various (13)C glucose isotopomers in rat brain slices. For this, we have used our cellular metabolomic approach that combines enzymatic and carbon 13 NMR techniques with mathematical models of metabolic pathways. We identified the fate and the pathways of the conversion of glucose carbons into various products (pyruvate, lactate, alanine, aspartate, glutamate, GABA, glutamine and CO(2)) and determined absolute fluxes through pathways of glucose metabolism. After 60 min of incubation, lactate and CO(2) were the main end-products of the metabolism of glucose which was avidly metabolized by the slices. Lactate was also used at high rates by the slices and mainly converted into CO(2). High values of flux through pyruvate carboxylase, which were similar with glucose and lactate as substrate, were observed. The addition of glutamine, but not of acetate, stimulated pyruvate carboxylation, the conversion of glutamate into succinate and fluxes through succinate dehydrogenase, malic enzyme, glutamine synthetase and aspartate aminotransferase. It is concluded that, unlike brain cells in culture, and consistent with high fluxes through PDH and enzymes of the tricarboxylic acid cycle, rat brain slices oxidized both glucose and lactate at high rates.

A comprehensive metabolic profile of cultured astrocytes using isotopic transient metabolic flux analysis and C-labeled glucose

Metabolic models have been used to elucidate important aspects of brain metabolism in recent years. This work applies for the first time the concept of isotopic transient 13C metabolic flux analysis (MFA) to estimate intracellular fluxes in primary cultures of astrocytes. This methodology comprehensively explores the information provided by 13C labeling time-courses of intracellular metabolites after administration of a 13C-labeled substrate. Cells were incubated with medium containing [1-13C]glucose for 24 h and samples of cell supernatant and extracts collected at different time points were then analyzed by mass spectrometry and/or high performance liquid chromatography. Metabolic fluxes were estimated by fitting a carbon labeling network model to isotopomer profiles experimentally determined. Both the fast isotopic equilibrium of glycolytic metabolite pools and the slow labeling dynamics of TCA cycle intermediates are described well by the model. The large pools of glutamate and aspartate which are linked to the TCA cycle via reversible aminotransferase reactions are likely to be responsible for the observed delay in equilibration of TCA cycle intermediates. Furthermore, it was estimated that 11% of the glucose taken up by astrocytes was diverted to the pentose phosphate pathway. In addition, considerable fluxes through pyruvate carboxylase [PC; PC/pyruvate dehydrogenase (PDH) ratio = 0.5], malic enzyme (5% of the total pyruvate production), and catabolism of branched-chained amino acids (contributing with ∼40% to total acetyl-CoA produced) confirmed the significance of these pathways to astrocytic metabolism. Consistent with the need of maintaining cytosolic redox potential, the fluxes through the malate–aspartate shuttle and the PDH pathway were comparable. Finally, the estimated glutamate/α-ketoglutarate exchange rate (∼0.7 μmol mg prot−1 h−1) was similar to the TCA cycle flux. In conclusion, this work demonstrates the potential of isotopic transient MFA for a comprehensive analysis of energy metabolism.

Primary metabolism in the new human cell line AGE1.HN at various substrate levels: increased metabolic efficiency and α1-antitrypsin production at reduced pyruvate load

Metabolic responses of the new neuronal human cell line AGE1.HN to various substrate levels were analyzed in this study showing that reduced substrate and especially pyruvate load improves metabolic efficiency, leading to improved growth and α(1)-antitrypsin (A1AT) production. The adaptation of the metabolism to different pyruvate and glutamine concentrations was analyzed in detail using a full factorial design. The most important finding was an increasingly inefficient use of substrates as well as the reduction of cell proliferation with increasing pyruvate concentrations in the medium. Cultivations with different feeding profiles showed that the highest viable cell density and A1AT concentration (167% of batch) was reached in the culture with the lowest glucose level and without pyruvate feeding. Analysis of metabolic fluxes in the differently fed cultures revealed a more efficient metabolic phenotype in the cultures without pyruvate feeding. The measured in vitro enzyme activities of the selected enzymes involved in pyruvate metabolism were lower in AGE1.HN compared with CHO cells, which might explain the higher sensitivity and different adaptation of AGE1.HN to increased pyruvate concentrations. The results indicate on the one hand that increasing the connectivity between glycolysis and the TCA cycle might improve substrate use and, finally, the production of A1AT. On the other hand, a better balanced substrate uptake promises a reduction of energy spilling which is increased with increasing substrate levels in this cell line. Overall, the results of this study provide important insights into the regulation of primary metabolism and into the adaptation of AGE1.HN to different substrate levels, providing guidance for further optimization of production cell lines and applied process conditions.

Metabolic flux analysis in systems biology of mammalian cells

Reaction rates or metabolic fluxes reflect the integrated phenotype of genome, transcriptome and proteome interactions, including regulation at all levels of the cellular hierarchy. Different methods have been developed in the past to analyse intracellular fluxes. However, compartmentation of mammalian cells, varying utilisation of multiple substrates, reversibility of metabolite uptake and production, unbalanced growth behaviour and adaptation of cells to changing environment during cultivation are just some reasons that make metabolic flux analysis (MFA) in mammalian cell culture more challenging compared to microorganisms. In this article MFA using the metabolite balancing methodology and the advantages and disadvantages of (13)C MFA in mammalian cell systems are reviewed. Application examples of MFA in the optimisation of cell culture processes for the production of biopharmaceuticals are presented with a focus on the metabolism of the main industrial workhorse. Another area in which mammalian cell culture plays a key role is in medical and toxicological research. It is shown that MFA can be used to understand pathophysiological mechanisms and can assist in understanding effects of drugs or other compounds on cellular metabolism.

Metabolic alterations induced by ischemia in primary cultures of astrocytes: merging 13C NMR spectroscopy and metabolic flux analysis

Disruption of brain energy metabolism is the hallmark of cerebral ischemia, a major cause of death worldwide. Astrocytes play a key role in the regulation of brain metabolism and their vulnerability to ischemia has been described. Aiming to quantify the effects of an ischemic insult in astrocytic metabolism, primary cultures of astrocytes were subjected to 5 h of oxygen and glucose deprivation in a bioreactor. Flux distributions, before and after ischemia, were estimated by metabolic flux analysis using isotopic information and the consumption/secretion rates of relevant extracellular metabolites as constraints. During ischemia and early recovery, 30% of cell death was observed; several metabolic alterations were also identified reflecting a metabolic response by the surviving cells. In the early recovery ( approximately 10 h), astrocytes up-regulated glucose utilization by 30% and increased the pentose phosphate pathway and tricarboxylic acid cycle fluxes by three and twofold, respectively. Additionally, a two to fivefold enhancement in branched-chain amino acids catabolism suggested the importance of anaplerotic molecules to the fast recovery of the energetic state, which was corroborated by measured cellular ATP levels. Glycolytic metabolism was predominant in the late recovery. In summary, this work demonstrates that changes in fluxes of key metabolic pathways are implicated in the recovery from ischemia in astrocytes.

Recent developments in parameter estimation and structure identification of biochemical and genomic systems

The organization, regulation and dynamical responses of biological systems are in many cases too complex to allow intuitive predictions and require the support of mathematical modeling for quantitative assessments and a reliable understanding of system functioning. All steps of constructing mathematical models for biological systems are challenging, but arguably the most difficult task among them is the estimation of model parameters and the identification of the structure and regulation of the underlying biological networks. Recent advancements in modern high-throughput techniques have been allowing the generation of time series data that characterize the dynamics of genomic, proteomic, metabolic, and physiological responses and enable us, at least in principle, to tackle estimation and identification tasks using 'top-down' or 'inverse' approaches. While the rewards of a successful inverse estimation or identification are great, the process of extracting structural and regulatory information is technically difficult. The challenges can generally be categorized into four areas, namely, issues related to the data, the model, the mathematical structure of the system, and the optimization and support algorithms. Many recent articles have addressed inverse problems within the modeling framework of Biochemical Systems Theory (BST). BST was chosen for these tasks because of its unique structural flexibility and the fact that the structure and regulation of a biological system are mapped essentially one-to-one onto the parameters of the describing model. The proposed methods mainly focused on various optimization algorithms, but also on support techniques, including methods for circumventing the time consuming numerical integration of systems of differential equations, smoothing overly noisy data, estimating slopes of time series, reducing the complexity of the inference task, and constraining the parameter search space. Other methods targeted issues of data preprocessing, detection and amelioration of model redundancy, and model-free or model-based structure identification. The total number of proposed methods and their applications has by now exceeded one hundred, which makes it difficult for the newcomer, as well as the expert, to gain a comprehensive overview of available algorithmic options and limitations. To facilitate the entry into the field of inverse modeling within BST and related modeling areas, the article presented here reviews the field and proposes an operational 'work-flow' that guides the user through the estimation process, identifies possibly problematic steps, and suggests corresponding solutions based on the specific characteristics of the various available algorithms. The article concludes with a discussion of the present state of the art and with a description of open questions.

System estimation from metabolic time-series data

MOTIVATION

At the center of computational systems biology are mathematical models that capture the dynamics of biological systems and offer novel insights. The bottleneck in the construction of these models is presently the identification of model parameters that make the model consistent with observed data. Dynamic flux estimation (DFE) is a novel methodological framework for estimating parameters for models of metabolic systems from time-series data. DFE consists of two distinct phases, an entirely model-free and assumption-free data analysis and a model-based mathematical characterization of process representations. The model-free phase reveals inconsistencies within the data, and between data and the alleged system topology, while the model-based phase allows quantitative diagnostics of whether--or to what degree--the assumed mathematical formulations are appropriate or in need of improvement. Hallmarks of DFE are the facility to: diagnose data and model consistency; circumvent undue compensation of errors; determine functional representations of fluxes uncontaminated by errors in other fluxes and pinpoint sources of remaining errors. Our results suggest that the proposed approach is more effective and robust than presently available methods for deriving metabolic models from time-series data. Its avoidance of error compensation among process descriptions promises significantly improved extrapolability toward new data or experimental conditions.

Structure, mechanism and regulation of pyruvate carboxylase

PC (pyruvate carboxylase) is a biotin-containing enzyme that catalyses the HCO(3)(-)- and MgATP-dependent carboxylation of pyruvate to form oxaloacetate. This is a very important anaplerotic reaction, replenishing oxaloacetate withdrawn from the tricarboxylic acid cycle for various pivotal biochemical pathways. PC is therefore considered as an enzyme that is crucial for intermediary metabolism, controlling fuel partitioning toward gluconeogenesis or lipogenesis and in insulin secretion. The enzyme was discovered in 1959 and over the last decade there has been much progress in understanding its structure and function. PC from most organisms is a tetrameric protein that is allosterically regulated by acetyl-CoA and aspartate. High-resolution crystal structures of the holoenzyme with various ligands bound have recently been determined, and have revealed details of the binding sites and the relative positions of the biotin carboxylase, carboxyltransferase and biotin carboxyl carrier domains, and also a unique allosteric effector domain. In the presence of the allosteric effector, acetyl-CoA, the biotin moiety transfers the carboxy group between the biotin carboxylase domain active site on one polypeptide chain and the carboxyltransferase active site on the adjacent antiparallel polypeptide chain. In addition, the bona fide role of PC in the non-gluconeogenic tissues has been studied using a combination of classical biochemistry and genetic approaches. The first cloning of the promoter of the PC gene in mammals and subsequent transcriptional studies reveal some key cognate transcription factors regulating tissue-specific expression. The present review summarizes these advances and also offers some prospects in terms of future directions for the study of this important enzyme.