Cybernetic modeling and regulation of metabolic pathways in multiple steady states of hybridoma cells

Hybridoma cells utilize a pair of complementary and partially substitutable substrates, glucose and glutamine, for growth. It has been shown that cellular metabolism shifts under different culture conditions. When those cultures at different metabolic states are switched to a continuous mode, they reach different steady states under the same operating conditions. A cybernetic model was constructed to describe the complementary and partial substitutable nature of substrate utilization. The model successfully predicted the metabolic shift and multiple steady-state behavior. The results are consistent with the experimental observation that the history of the culture affects the resulting steady state.     

Infrared microspectroscopy of individual human cervical cancer (HeLa) cells

We report infrared (IR) spectra observed for individual, cultured human cervical cancer (HeLa) cells. Spectra were collected microscopically, in reflection/absorption modes, from cells deposited and dried on microscope slides or from cells grown directly on slides. Within the spectra of the dried cells, significant spectral heterogeneity exists that was previously attributed to different stages of the cell cycle [Boydston-White. S., et al., Biospectroscopy 1999, 5, 219-227; Holman, H. Y., et al., Biopolymers Biospectrosc 2000, 57, 329-335; Tobin, M. J., et al., in First BASIE Workshop, Karlsruhe, Germany, 2003]. The results reported here confirm earlier findings and present the possibility of determining the abundance of cells within each stage of the cycle from the IR spectra. In an accompanying paper, we show that the spectra of cells in suspension exhibit spectral intensity distributions that are different from that of the dried cells. This result has far-reaching implications for the use of infrared microspectroscopy to screen dried cell preparations for the presence of abnormal cells.     

Exacting predictions by cybernetic model confirmed experimentally: Steady state multiplicity in the chemostat

We demonstrate strong experimental support for the cybernetic model based on maximizing carbon uptake rate in describing the microorganism's regulatory behavior by verifying exacting predictions of steady state multiplicity in a chemostat. Experiments with a feed mixture of glucose and pyruvate show multiple steady state behavior as predicted by the cybernetic model. When multiplicity occurs at a dilution (growth) rate, it results in hysteretic behavior following switches in dilution rate from above and below. This phenomenon is caused by transient paths leading to different steady states through dynamic maximization of the carbon uptake rate. Thus steady state multiplicity is a manifestation of the nonlinearity arising from cybernetic mechanisms rather than of the nonlinear kinetics. The predicted metabolic multiplicity would extend to intracellular states such as enzyme levels and fluxes to be verified in future experiments. © 2012 American Institute of Chemical Engineers Biotechnol. Prog., 2012     

Role of afferent input in muscle atrophy.

It is well known that soleus muscle of rat atrophies following spaceflight or hindlimb suspension (Ohira et al., 1992). It is, further, reported that the electromyogram (EMG) of soleus muscle disappears immediately in response to unloading by exposure to actual micro-g environment (Kawano et al., 2002; Leterme and Falempin, 1998) and by hindlimb suspension of rats (Alford et al., 1987; Ohira et al., 2000). However, the EMG level is increased gradually to the control level following 7-10 days of continuous hindlimb suspension (Alford et al., 1987; Ohira, 2000), while muscle atrophy is progressing (Winiarski et al., 1987). We previously reported that reduction of the EMG level of rat soleus in response to actual micro-g environment, created by a parabolic flight of a jet airplane, was closely associated with a decrease of the afferent input recorded at the L5 segmental level of spinal cord (Kawano et al., 2002). However, it is still unclear how the EMG level of soleus muscle adapts to unloading condition. The current study was performed to investigate the responses of soleus EMG and both afferent and efferent neurogram at the L5 segmental level of spinal cord to acute (20 seconds) and chronic (14 days) unloading.     

Metabolic modeling of Saccharomyces cerevisiae using the optimal control of homeostasis: a cybernetic model definition

A model is presented to describe the observed behavior of microorganisms that aim at metabolic homeostasis while growing and adapting to their environment in an optimal way. The cellular metabolism is seen as a network with a multiple controller system with both feedback and feedforward control, i.e., a model based on a dynamic optimal metabolic control. The dynamic network consists of aggregated pathways, each having a control setpoint for the metabolic states at a given growth rate. This set of strategies of the cell forms a true cybernetic model with a minimal number of assumptions. The cellular strategies and constraints were derived from metabolic flux analysis using an identified, biochemically relevant, stoichiometry matrix derived from experimental data on the cellular composition of continuous cultures of Saccharomyces cerevisiae. Based on these data a cybernetic model was developed to study its dynamic behavior. The growth rate of the cell is determined by the structural compounds and fluxes of compounds related to central metabolism. In contrast to many other cybernetic models, the minimal model does not consist of any assumed internal kinetic parameters or interactions. This necessitates the use of a stepwise integration with an optimization of the fluxes at every time interval. Some examples of the behavior of this model are given with respect to steady states and pulse responses. This model is very suitable for describing semiquantitatively dynamics of global cellular metabolism and may form a useful framework for including structured and more detailed kinetic models.     

Parametric sensitivity analysis and reduction of a detailed nutritional model of plant cell cultures

A kinetic model of plant nutrition described by Cloutier et al. (Cloutier et al., 2008. Biotechnol Bioeng 99:189-200) is progressively simplified so as to obtain a predictive model that describes the evolution of the biomass and the extracellular and intracellular concentrations of three determining nutrients, that is, free intracellular nitrogen, phosphate, and carbohydrate compounds. Three techniques of global sensitivity analysis are successively applied to assess the model parameter influence and potential correlation. The resulting dynamic model is able to predict plant growth for the two most encountered plant bioprocesses, namely suspension cells and hairy roots.     

Effect of mixing on the washout and steady-state performance of continuous cultures

The effects of mixing on the critical mean holding time for washout and the steady state performance of growth processes in continuous flow reactors are investigated. Macromixing, micromixing, and cell recycle arc considered. The tanks-in-series model composed of N completely mixed flow reactors, the dispersion model, the plug flow model, and a combined model composed of a plug flow reactor and a continuous stirred tank flow reactor connected in series arc used to represent the macro-mixing or residence time distribution. The extreme cases of micromixing, namely, complete segregation and maximum mixedness, as well as intermediate states of micromixing are investigated to determine their effects on washout and the occurence of multiple steady states. A technique for predicting the maximum mixedness washout condition from a knowledge of the residence time distribution is presented and used to determine the washout condition for the dispersion model under maximum mixedness conditions.     

Metal hyperaccumulation: a model system for coevolutionary studies

Recent years have seen a flurry of research activity concerning the hyperaccumulation of heavy metals by plants. Much of the interest in hyperaccumulation has been fueled by the commercial potential of phytoremediation, the use of plants to clean up contaminated soils (Baker et al ., 1994; Salt et al ., 1995; Chaney et al ., 1997, 2000). These applications have in turn spurred many studies of the genetics and physiology of metal uptake (e.g. Krämer et al ., 1996; Lasat et al ., 1996; Salt & Krämer, 1999; Baker et al ., 2000; see also Krämer, 2000; Lombi et al ., 2000). Although phytoremediation provides an intriguing and potentially profitable backdrop, the ecology and evolution of hyperaccumulation in natural populations are interesting subjects in their own right. Two papers in this issue (Ghaderian et al ., pp. 219–224; Davis & Boyd, pp. 211–217) are exciting contributions to the growing consensus that hyperaccumulation may act as a defense against herbivores and pathogens, and suggest that hyperaccumulation may become a model system for research in this area.     

Circadian control of neurogenesis

The life-long addition of new neurons has been documented in many regions of the vertebrate and invertebrate brain, including the hippocampus of mammals (Altman and Das, 1965; Eriksson et al., 1998; Jacobs et al., 2000), song control nuclei of birds (Alvarez-Buylla et al., 1990), and olfactory pathway of rodents (Lois and Alvarez-Buylla, 1994), insects (Cayre et al., 1996) and crustaceans (Harzsch and Dawirs, 1996; Sandeman et al., 1998; Harzsch et al., 1999; Schmidt, 2001). The possibility of persistent neurogenesis in the neocortex of primates is also being widely discussed (Gould et al., 1999; Kornack and Rakic, 2001). In these systems, an effort is underway to understand the regulatory mechanisms that control the timing and rate of neurogenesis. Hormonal cycles (Rasika et al., 1994; Harrison et al., 2001), serotonin (Gould, 1999; Brezun and Daszuta, 2000; Beltz et al., 2001), physical activity (Van Praag et al., 1999) and living conditions (Kemperman and Gage, 1999; Sandeman and Sandeman, 2000) influence the rate of neuronal proliferation and survival in a variety of organisms, suggesting that mechanisms controlling life-long neurogenesis are conserved across a range of vertebrate and invertebrate species. The present article extends these findings by demonstrating circadian control of neurogenesis. Data show a diurnal rhythm of neurogenesis among the olfactory projection neurons in the crustacean brain, with peak proliferation during the hours surrounding dusk, the most active period for lobsters. These data raise the possibility that light-controlled rhythms are a primary regulator of neuronal proliferation, and that previously-demonstrated hormonal and activity-driven influences over neurogenesis may be secondary events in a complex circadian control pathway.     

Comparison of metabolic flux distributions for MDCK cell growth in glutamine- and pyruvate-containing media

In mammalian cell cultures, ammonia that is released into the medium as a result of glutamine metabolism and lactate that is excreted due to incomplete glucose oxidation are both known to essentially inhibit the growth of cells. For some cell lines, for example, hybridoma cells, excreted ammonia also has an effect on product formation. Although glutamine has been generally considered as the major energy source for mammalian cells, it was recently found that various adherent cell lines (MDCK, CHO-K1, and BHK21) can grow as well in glutamine-free medium, provided glutamine is substituted with pyruvate. In such a medium the level of both ammonia and lactate released was significantly reduced. In this study, metabolic flux analysis (MFA) was applied to Madin Darby Canine Kidney (MDCK) cells cultivated in glutamine-containing and glutamine-free medium. The results of the MFA allowed further investigation of the influence of glutamine substitution with pyruvate on the metabolism of MDCK cells during different growth stages of adherent cells, e.g., early exponential and late contact-inhibited phase. Pyruvate seemed to directly enter the TCA cycle, whereas most of the glucose consumed was excreted as lactate. Although the exact mechanisms are not clear so far, this resulted in a reduction of the glucose uptake necessary for cellular metabolism in glutamine-free medium. Furthermore, consumption of ATP by futile cycles seemed to be significantly reduced when substituting glutamine with pyruvate. These findings imply that glutamine-free medium favors a more efficient use of nutrients by cells. However, a number of metabolic fluxes were similar in the two cultivations considered, e.g., most of the amino acid uptake and degradation rates or fluxes through the branch of the TCA cycle converting alpha-ketoglutarate to malate, which is responsible for the mitochondrial ATP synthesis. Besides, the specific rate of cell growth was approximately the same in both cultivations. Thus, the switch from glutamine-containing to glutamine-free medium with pyruvate provided a series of benefits without dramatic changes of cellular metabolism.     

Novel biochemical pathways of endoglin in vascular cell physiology

The broad role of the transforming growth factor beta (TGFbeta) signaling pathway in vascular development, homeostasis, and repair is well appreciated. Endoglin is emerging as a novel, complex, and poorly understood regulatory component of the TGFbeta receptor complex, whose importance is underscored by its recognition as the site of mutations causing hereditary hemorrhagic telangiectasia (HHT) [McAllister et al., 1994]. Extensive analyses of endoglin function in normal developmental mouse models [Bourdeau et al., 1999; Li et al., 1999; Arthur et al., 2000] and in HHT animal models [Bourdeau et al., 2000; Torsney et al., 2003] exemplify the importance of understanding endoglin's biochemical functions. However, novel mechanisms underlying the regulation of these pathways continue to emerge. These mechanisms include modification of TGFbeta receptor signaling at the ligand and receptor activation level, direct effects of endoglin on cell adhesion and migration, and emerging roles for endoglin in the determination of stem cell fate and tissue patterning. The purpose of this review is to highlight the cellular and molecular studies that underscore the central role of endoglin in vascular development and disease.     

Structural bistability of the GAL regulatory network and characterization of its domains of attraction

Bistability is a system-level property, exploited by many biomolecular interaction networks as a key mechanism to accomplish different cellular functions (e.g., differentiation, cell cycle, switch-like response to external stimuli). Bistability has also been experimentally found to occur in the regulatory network of the galactose metabolic pathway in the model organism Saccharomyces cerevisiae. In this yeast, bistability generates a persistent memory of the type of carbon source available in the extracellular medium: under the same experimental conditions, cells previously grown with different nutrients generate different responses and get stably locked into two distinct steady states. The molecular interactions of the GAL regulatory network have been thoroughly dissected through wet-lab experiments; thus, this system provides a formidable benchmark to our ability to characterize and reproduce in silico the behavior of bistable biological systems. To this aim, a number of models have been proposed in the literature; however, we found that they are not able to replicate the persistent memory behavior observed in (Acar et al., 2005 ). The present study proposes a novel model of the GAL regulatory network, which, in addition to reproducing in silico the experimental findings, can be formally analyzed for structural multistability of the network, using chemical reaction network theory (CRNT), and allows the characterization of the domains of attraction (DA). This work provides further insights into the GAL system and proposes an easily generalizable approach to the study of bistability-associated behaviors in biological systems.     

Using robotics to fold proteins and dock ligands

The problems of protein folding and ligand docking have been explored largely using molecular dynamics or Monte Carlo methods. These methods are very compute intensive because they often explore a much wider range of energies, conformations and time than necessary. In addition, Monte Carlo methods often get trapped in local minima. We initially showed that robotic motion planning permitted one to determine the energy of binding and dissociation of ligands from protein binding sites (Singh et al., 1999). The robotic motion planning method maps complicated three-dimensional conformational states into a much simpler, but higher dimensional space in which conformational rearrangements can be represented as linear paths. The dimensionality of the conformation space is of the same order as the number of degrees of conformational freedom in three-dimensional space. We were able to determine the relative energy of association and dissociation of a ligand to a protein by calculating the energetics of interaction for a few thousand conformational states in the vicinity of the protein and choosing the best path from the roadmap. More recently, we have applied roadmap planning to the problem of protein folding (Apaydin et al., 2002a). We represented multiple conformations of a protein as nodes in a compact graph with the edges representing the probability of moving between neighboring states. Instead of using Monte Carlo simulation to simulate thousands of possible paths through various conformational states, we were able to use Markov methods to calculate the steady state occupancy of each conformation, needing to calculate the energy of each conformation only once. We referred to this Markov method of representing multiple conformations and transitions as stochastic roadmap simulation or SRS. We demonstrated that the distribution of conformational states calculated with exhaustive Monte Carlo simulations asymptotically approached the Markov steady state if the same Boltzman energy distribution was used in both methods. SRS permits one to calculate contributions from all possible paths simultaneously with far fewer energy calculations than Monte Carlo or molecular dynamics methods. The SRS method also permits one to represent multiple unfolded starting states and multiple, near-native, folded states and all possible paths between them simultaneously. The SRS method is also independent of the function used to calculate the energy of the various conformational states. In a paper to be presented at this conference (Apaydin et al., 2002b) we have also applied SRS to ligand docking in which we calculate the dynamics of ligand-protein association and dissociation in the region of various binding sites on a number of proteins. SRS permits us to determine the relative times of association to and dissociation from various catalytic and non-catalytic binding sites on protein surfaces. Instead of just following the best path in a roadmap, we can calculate the contribution of all the possible binding or dissociation paths and their relative probabilities and energies simultaneously.     

Transient responses of hybridoma cells to lactate and ammonia pulse and step changes in continuous culture

Ammonia and lactate are the major byproducts from mammalian cells grown in medium containing glutamine and glucose. Both can be toxic to cells, and may limit the productivity of commercial bioreactors. The transient and steady-state responses of hybridoma growth and metabolism to lactate and ammonia pulse and step changes in continuous suspension culture have been examined. No inhibition was observed at 40 mM lactate. Cell growth was inhibited by 5 mM ammonia, but the cells were able to adapt to ammonia concentrations as high as 8.2 mM. Ammonia production decreased and alanine production increased in response to higher ammonia concentrations. Increased ammonia concentrations also inhibited glutamine and oxygen consumption. The specific oxygen consumption rate decreased by an order of magnitude after an ammonia pulse to 18 mM. Under these conditions, over 90% of the estimated ATP production was due to glycolysis and a large fraction of glutamine was converted to lactate.     

Metabolic engineering from a cybernetic perspective: aspartate family of amino acids

Using the modular cybernetic framework developed by Varner and Ramkrishna (Varner and Ramkrishna; 1998a, b) a cybernetic model is formulated that describes the time evolution of the aspartate family of amino acids in Corynebacterium lactofermentum ATCC 21799. The network model formulation is employed in the role of a diagnostic tool for the overproduction of threonine. More precisely, having determined a parameter set that describes the time evolution of a base strain (lysine producer), the model predicted response to genetic perturbations, designed to enhance the level of threonine, are simulated using an appropriately modified cybernetic model and compared with the experimental results of Stephanopoulos and Sinskey (Colón et al., 1995a, Appl. Environ. Microbiol. 61, 74-78) for identical genetic perturbations. It is found that the model predicted response to enzymatic over-expression in the aspartate pathway agrees, for the most part, with experimental observations within the experimental error bounds. This result lends credence to the hypothesis that cybernetic models can be employed to predict the local response of a metabolic network to genetic perturbation, thereby, affording cognizance of the potential pitfalls of a particular genetic alteration strategy a priori.     

Linkage and association studies of QTL for nuclear families by mixed models

The transmission disequilibrium test (TDT) has been utilized to test the linkage and association between a genetic trait locus and a marker. Spielman et al. (1993) introduced TDT to test linkage between a qualitative trait and a marker in the presence of association. In the presence of linkage, TDT can be applied to test for association for fine mapping (Martin et al., 1997; Spielman and Ewens, 1996). In recent years, extensive research has been carried out on the TDT between a quantitative trait and a marker locus (Allison, 1997; Fan et al., 2002; George et al., 1999; Rabinowitz, 1997; Xiong et al., 1998; Zhu and Elston, 2000, 2001). The original TDT for both qualitative and quantitative traits requires unrelated offspring of heterozygous parents for analysis, and much research has been carried out to extend it to fit for different settings. For nuclear families with multiple offspring, one approach is to treat each child independently for analysis. Obviously, this may not be a valid method since offspring of one family are related to each other. Another approach is to select one offspring randomly from each family for analysis. However, with this method much information may be lost. Martin et al. (1997, 2000) constructed useful statistical tests to analyse the data for qualitative traits. In this paper, we propose to use mixed models to analyse sample data of nuclear families with multiple offspring for quantitative traits according to the models in Amos (1994). The method uses data of all offspring by taking into account their trait mean and variance-covariance structures, which contain all the effects of major gene locus, polygenic loci and environment. A test statistic based on mixed models is shown to be more powerful than the test statistic proposed by George et al. (1999) under moderate disequilibrium for nuclear families. Moreover, it has higher power than the TDT statistic which is constructed by randomly choosing a single offspring from each nuclear family.