Experimental concerns in tracer kinetic investigations of apolipoprotein metabolism

The complexity of the metabolism of the plasma lipoproteins makes it impossible to integrate the details of the reactions of specific apolipoproteins and their associated lipids without the use of computerized modeling methods. Because apolipoproteins impart specificity in the transport and chemical processing of plasma lipids, they have been the focus of many in vivo kinetic tracer investigations. The analysis of such kinetic data by modeling techniques has provided important advances in understanding lipoprotein metabolism. An example is the Delipidation Chain, an hypothesis explaining VLDL metabolism in terms of a sequential delipidation process. As a consequence of the advance in knowledge of apolipoprotein structure and metabolism, coupled with progress in computerized modeling of large systems, it has become important to refine the design of in vivo tracer kinetic investigations of the apolipoproteins. Considerations of particular importance include the selection of apolipoprotein tracers which can be shown to undergo the same reactions as the apolipoproteins whose metabolism they trace. If the physical and chemical processes which convert apolipoproteins from one metabolic pool to another are to be analyzed correctly, it is necessary to describe precisely and to measure accurately these pools. Current methods for delineating metabolic pools of apolipoproteins in vivo need to be refined. When accomplished, this will provide new opportunities to investigate the metabolic pathways of the apolipoproteins and their associated lipids. A very important challenge is to design experiments which will differentiate transfer processes, which result in net transport of a reactant, from exchange processes, whereby a tracer and a tracee are exchanged between pools without a net transport event occuring. Since both types of processes occur readily with apolipoproteins, it is important to develop methods to examine them separately. Computerized kinetic modeling provides a means for describing and understanding the complexities of lipoprotein metabolism. A major challenge is for the experimentalist to acquire data which accurately reflect the physiological processes involved in lipoprotein metabolism.     

New methodologies for studying lipid synthesis and turnover: Looking backwards to enable moving forwards

Our ability to understand the pathogenesis of problems surrounding lipid accretion requires attention towards quantifying lipid kinetics. In addition, studies of metabolic flux should also help unravel mechanisms that lead to imbalances in inter-organ lipid trafficking which contribute to dyslipidemia and/or peripheral lipid accumulation (e.g. hepatic fat deposits). This review aims to outline the development and use of novel methods for studying lipid kinetics in vivo. Although our focus is directed towards some of the approaches that are currently reported in the literature, we include a discussion of the older literature in order to put “new” methods in better perspective and inform readers of valuable historical research. Presumably, future advances in understanding lipid dynamics will benefit from a careful consideration of the past efforts, where possible we have tried to identify seminal papers or those that provide clear data to emphasize essential points. This article is part of a Special Issue entitled: Modulation of Adipose Tissue in Health and Disease.     

Heterogeneity of kinetic parameters of enzymes in situ in rat liver lobules

In the present review, metabolic compartmentation in liver lobules is discussed as being dynamic and more complex than thus far assumed on the basis of numbers of mRNA or protein molecules or the capacity (zero-order activity) of enzymes. Isoenzyme distribution patterns and local kinetic parameters of enzymes may vary over the different zones of liver lobules. As a consequence, metabolic fluxes in vivo at physiological substrate concentrations may be completely different from those that are assumed on the basis of the number of molecules or the capacity of enzymes present in zones of liver lobules. For a more correct estimation of the levels of metabolic processes in the different compartments of liver tissue, local kinetic parameters and substrate concentrations have to be determined to calculate local metabolic fluxes. direct measurements of metabolic fluxes in vivo with the use of noninvasive techniques is a promising alternative and the techniques will become increasingly important in future metabolic research.This paper was presented at the symposium Metabolic Zonation of the Liver: New Answers to Old Questions held in honour of Prof. Dr. D. Sasse's 60th birthday, 26 August 1994, in Basel     

Application of fuzzy-logic models for metabolic control analysis

A priori information or valuable qualitative knowledge can be incorporated explicitly to describe enzyme kinetics making use of fuzzy-logic models. Although restricted to linear relationships, it is shown that fuzzy-logic augmented models are not only able to capture non-linear features of enzyme kinetics but also allow the proper mathematical treatment of metabolic control analysis. The explicit incorporation of valuable qualitative knowledge is crucial, particularly when handling data estimated from in vivo kinetics studies, since this experimental information is scarce and usually contains measurement errors. Therefore, data-driven techniques, such as the one presented in this work, form a serious alternative to established kinetics approaches.     

Single-filament kinetic studies provide novel insights into regulation of actin-based motility

Polarized assembly of actin filaments forms the basis of actin-based motility and is regulated both spatially and temporally. Cells use a variety of mechanisms by which intrinsically slower processes are accelerated, and faster ones decelerated, to match rates observed in vivo. Here we discuss how kinetic studies of individual reactions and cycles that drive actin remodeling have provided a mechanistic and quantitative understanding of such processes. We specifically consider key barbed-end regulators such as capping protein and formins as illustrative examples. We compare and contrast different kinetic approaches, such as the traditional pyrene-polymerization bulk assays, as well as more recently developed single-filament and single-molecule imaging approaches. Recent development of novel biophysical methods for sensing and applying forces will in future allow us to address the very important relationship between mechanical stimulus and kinetics of actin-based motility.     

Microalgal kinetics — a guideline for photobioreactor design and process development

Kinetics generally describes bio‐(chemical) reaction rates in dependence on substrate concentrations. Kinetics for microalgae is often adapted from heterotrophs and lacks mechanistic foundation, e.g. for light harvesting. Using and understanding kinetic equations as the representation of intracellular mechanisms is essential for reasonable comparisons and simulations of growth behavior. Summarizing growth kinetics in one equation does not yield reliable models. Piecewise linear or rational functions may mimic photosynthesis irradiance response curves, but fail to represent the mechanisms. Our modeling approach for photoautotrophic growth comprises physical and kinetic modules with mechanistic foundation extracted from the literature. Splitting the light submodel into the modules for light distribution, light absorption, and photosynthetic sugar production with independent parameters allows the transfer of kinetics between different reactor designs. The consecutive anabolism depends among others on nutrient concentrations. The nutrient uptake kinetics largely impacts carbon partitioning in the reviewed stoichiometry range of cellular constituents. Consecutive metabolic steps mask each other and demand a maximum value understandable as the minimum principle of growth. These fundamental modules need to be clearly distinguished, but may be modified or extended based on process conditions and progress in research. First, discussion of kinetics helps to understand the physiological situation, for which ranges of parameter values are given. Second, kinetics should be used for photobioreactor design, but also for gassing and nutrient optimization. Numerous examples are given for both aspects. Finally, measuring kinetics more comprehensively and precisely will help in improved process development.     

In vivo approaches and rationale for quantifying kinetics and imaging brain lipid metabolic pathways

Developing a kinetic strategy to examine rates of lipid metabolic pathways can help to elucidate the roles that lipids play in tissue function and structure in health and disease. This review summarizes such a strategy, and shows how it has been applied to quantify different kinetic aspects of brain lipid metabolism in animals and humans. Methods involve injecting intravenously a radioactive or heavy isotope labeled substrate that will be incorporated into a lipid metabolic pathway, and using chemical analytical and/or imaging procedures (e.g., quantitative autoradiography or positron emission tomography) to determine tracer distribution in brain regions and their lipid compartments as a function of time. From the measurements, fluxes, turnover rates, half-lives and ATP consumption rates can be calculated, and incorporation rates can be imaged. Experimental changes in these kinetic parameters can help to identify changes in the expression of regulatory enzymes, and thus aid in drug targeting. Cases that are discussed are arachidonic acid turnover and imaging of neuroreceptor-initiated phospholipase A2 activation, ether phospholipid biosynthesis, and kinetics of the phosphatidylinositol cycle.     

Transport-limited reactions in microbial systems

Predicting microbial metabolic rates and emergent biogeochemical fluxes remains challenging due to the many unknown population dynamical, physiological and reaction-kinetic parameters and uncertainties in species composition. Here, we show that the need for these parameters can be eliminated when population dynamics and reaction kinetics operate at much shorter time scales than physical mixing processes. Such scenarios are widespread in poorly mixed water columns and sediments. In this ‘fast-reaction-transport’ (FRT) limit, all that is required for predictions are chemical boundary conditions, the physical mixing processes and reaction stoichiometries, while no knowledge of species composition, physiology or population/reaction kinetic parameters is needed. Using time-series data spanning years 2001–2014 and depths 180–900 m across the permanently anoxic Cariaco Basin, we demonstrate that the FRT approach can accurately predict the dynamics of major electron donors and acceptors (Pearson r ≥ 0.9 in all cases). Hence, many microbial processes in this system are largely transport limited and thus predictable regardless of species composition, population dynamics and kinetics. Our approach enables predictions for many systems in which microbial community dynamics and kinetics are unknown. Our findings also reveal a mechanism for the frequently observed decoupling between function and taxonomy in microbial systems.     

Application of Magnetic Resonance Spectroscopy in metabolic research

The etiology of metabolic disease in humans is far from understood, and even though potential pathways are identified in animal models and cell studies, it is often difficult to determine their relevance in humans, as the possibilities of tissue sampling are limited. The application of non-invasive imaging techniques can provide essential metabolic information and this mini review focuses on the opportunities of Magnetic Resonance Spectroscopy (MRS) to add to our understanding of the metabolic processes during health and disease. MRS is a volatile technique that can give us information about the concentrations of endogenous metabolites in a completely non-invasive way. In this mini review we discuss the opportunities that MRS is giving us by describing how the investigation of ectopic fat depots has gained a lot of attention and has really taken off after ¹H-MRS for quantification of lipid content became widely available. We furthermore discuss how other MRS techniques, such as ³¹P-MRS and ¹³C-MRS can add valuable information and especially highlight the strength of MRS to be applied dynamically and therefore monitor metabolic changes during physiological challenges such as exercise or meal tests.     

Mathematical modelling of metabolism

Mathematical models of the cellular metabolism have a special interest within biotechnology. Many different kinds of commercially important products are derived from the cell factory, and metabolic engineering can be applied to improve existing production processes, as well as to make new processes available. Both stoichiometric and kinetic models have been used to investigate the metabolism, which has resulted in defining the optimal fermentation conditions, as well as in directing the genetic changes to be introduced in order to obtain a good producer strain or cell line. With the increasing availability of genomic information and powerful analytical techniques, mathematical models also serve as a tool for understanding the cellular metabolism and physiology.     

Circadian and infradian aspects of the cell cycle: from past to future

A review of some aspects of circadian and infradian rhythms of the cell cycle is given. The background is that the research of the last decade has given entirely new insights into the cell cycle as a dynamic process which occurs in waves. After some short historical notes on the development of methodology for study of cell kinetics, it is reviewed how the strong variability of this function was recognized from the 1960's. This again led to an increasing understanding of the rhythmic pattern of cell renewal in various tissues of the body. Conventional methods for studying cell population kinetics gave general insights into both circadian and infradian rhythms, but were hampered by several shortcomings. The techniques were time consuming, and usually one and only one parameter could be studied at a time. However, this general knowledge both had a strong impact on the understanding of cell kinetics and provided a basis for designing cancer chemotherapy. Today we are facing a new area in the study of cell population kinetics. New, rapid and automated methods for multiparameter studies of both cell kinetics and other biological properties of cell populations have given entirely new possibilities for cell kinetic research. Methods, mainly connected to analytical cytology, can discriminate subpopulations with varying kinetic properties, and also enable monitoring of cell proliferation in normal and malignant tissues of patients. Chronobiology has had a strong impact on the understanding of cell population kinetics in the body. In the light of the new developments in the fields of growth factors and their regulatory influences on the cell cycle, important and fundamental aspects of biological rhythms are now being elucidated.     

Proteome profiling and its use in metabolic and cellular engineering

Proteome profiling of microorganisms makes it possible to generate valuable knowledge that can be used for the development of metabolic and cellular engineering strategies, which consequently are used to enhance the yield and productivity of native or foreign bioproducts and to modify cellular properties to improve mid-stream and down-stream processes. Advances in two-dimensional gel electrophoresis technology combined with mass spectrometry allow the creation of global scale proteome contents which can be used to elucidate valuable information on the dynamics of the metabolic, signaling and regulatory networks apart from understanding the physiological changes. In this paper, we review the approaches of exploiting the proteome profiling results to the development of the strategies for the metabolic and cellular engineering of microorganisms.     

Placental transport and utilization of amino acids and carbohydrates

Uteroplacental tissues have been shown to have a high rate of metabolism under in vivo steady-state conditions. Fully two-thirds of the glucose and one-half of the oxygen consumed by the uterus are utilized by these tissues rather than by the fetus. Its high metabolic rate must be borne in mind in any analysis of tracer kinetics, which prohibits the exclusion of these tissues and the use of a two-compartment model for analysis of carbohydrate and amino acid metabolism. Current techniques permit determination of utilization rates of nutrients in all three compartments (fetal, uteroplacental, and maternal) with considerable precision. Using tracer amino acids one can determine rates of protein synthesis and protein breakdown as well as rates of amino acid oxidation. These techniques should prove useful in investigating the role of various trophic factors in fetal life and in assessing the impact of changes in placental function or maternal nutritional state on fetal growth and metabolism.     

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.     

Reaction velocities in vivo: standardization of kinetic "constants" by correction for blood flow

1. The results of kinetic studies in vitro are difficult to apply to metabolic reactions in vivo. 2. In living vertebrates reaction rates are usually first-order and for a particular reaction the rate "constant", k, varies with the several thousand-fold variations in metabolic rate. 3. Therefore, in the kinetic equation (formula: see text) since K varies with metabolic rate, Vmax and/or Km will aslo vary. 4. However, reaction rates for a series of different substrates were similar in animals varying widely in metabolic rate if corrections were made for differences in blood flow. 5. The observation that metabolic rate (reaction rate) is directly dependent on blood flow (Coulson et al., 1977) allowed derivation of new kinetic constants which were valid in vivo. 6. Introduction of a flow term into the observed first-order equations yields an "affinity constant", K, or a "flow constant", KF, somewhat analogous to Km, which allows one to predict reaction rates in animals of different metabolic rates. 7. The defining equations are (formula: see text) where V = reaction velocity in mmol/hr/kg tissue, [S] = millimolar substrate concentration in the blood, k = In 2/tau (tau the half-life) and F = blood flow in 1/hr/kg tissue. 8. Thus, K = k/F = 1/KF. The KF's for the initial step in the degradation of 17 amino acids in rats, dogs, lizards, turtles and alligators were similar, demonstrating the similarity of enzyme affinities in different species.     

From Enzyme Kinetics to Metabolic Network Modeling – Visualization Tool for Enhanced Kinetic Analysis of Biochemical Network Models

Model‐based analysis of enzyme kinetics allows the determination of optimal conditions for their use in biocatalysis. For biotransformations or fermentative approaches the modeling of metabolic pathways or complex metabolic networks is necessary to obtain model‐based predictions of steps which limit product formation within the network. To set up adequate kinetic models, relevant mechanistic information about enzyme properties is required and can be taken from in vitro studies with isolated enzymes or from in vivo investigations using stimulus‐response experiments which provide a lot of kinetic information about the metabolic network. But with increasing number of reaction steps and regulatory interdependencies in the network structure the amount of simulation data dramatically increases and the simulation results from the dynamic models become difficult to analyze and interpret. Demonstrated for an Escherichia coli model of the central carbon metabolism, methods for visualization and animation of simulation data were applied and extended to facilitate model analysis and biological interpretation. The dynamic metabolite pool and metabolic flux changes were visualized simultaneously by a software tool. In addition, a new quantification method for enzyme activation/inhibition was proposed, and this information was implemented in the metabolic visualization.     

Green pathways: Metabolic network analysis of plant systems

Metabolic engineering of plants with enhanced crop yield and value-added compositional traits is particularly challenging as they probably exhibit the highest metabolic network complexity of all living organisms. Therefore, approaches of plant metabolic network analysis, which can provide systems-level understanding of plant physiology, appear valuable as guidance for plant metabolic engineers. Strongly supported by the sequencing of plant genomes, a number of different experimental and computational methods have emerged in recent years to study plant systems at various levels: from heterotrophic cell cultures to autotrophic entire plants. The present review presents a state-of-the-art toolbox for plant metabolic network analysis. Among the described approaches are different in silico modeling techniques, including flux balance analysis, elementary flux mode analysis and kinetic flux profiling, as well as different variants of experiments with plant systems which use radioactive and stable isotopes to determine in vivo plant metabolic fluxes. The fundamental principles of these techniques, the required data input and the obtained flux information are enriched by technical advices, specific to plants. In addition, pioneering and high-impacting findings of plant metabolic network analysis highlight the potential of the field.