Abstracts F1-F3

Category F.  Drug Metabolism, Toxicity and Pharmacogenomics


F1.  Role of Carnosine in the Modulation of Nitric Oxide Production by RAW 264.7 Macrophages

Giuseppe Caruso1,2, Claudia G. Fresta1,2, Joseph M. Siegel1,2, Richard P. S. de Campos1,2,3, Manjula B. Wijesinghe1,2, Giuseppe Lazzarino4, and Susan M. Lunte1,2,5

1Ralph N. Adams Institute for Bioanalytical Chemistry,  2Department of Pharmaceutical Chemistry, University of Kansas, Lawrence, KS, USA;  3Department of Chemistry, State University of Campinas, Campinas, Brazil;  4Department of Biomedical and Biotechnological Sciences, University of Catania, Catania, Italy;  5Department of Chemistry, University of Kansas, Lawrence, KS, USA

Carnosine (β-alanyl-L-histidine) plays an important role in a number of physiological functions related to oxidative stress. Carnosine has been shown to be involved in many cellular defense mechanisms against oxidative stress, including nitric oxide (NO) detoxification. High concentrations of NO can be produced by inducible nitric oxide synthase (iNOS) in immune (macrophage) cells. Excess NO production in these cells can result in the formation of dangerous reactive nitrogen species, which disrupt cellular redox processes by reacting with important biomolecules. Therefore, the protective properties of carnosine are of great interest, especially regarding its antioxidant activity against reactive oxygen and nitrogen species that are involved in oxidative stress-driven disorders and pro-inflammatory disease. The goal of this research is to determine the role of carnosine on the production of intracellular and extracellular NO and nitrite (primary degradation product of NO) by macrophages under pro-inflammatory conditions. Using the Griess assay for the detection of nitrite, we found that carnosine affects nitrite production in RAW 264.7 macrophage cells in a concentration-dependent manner without affecting cell viability. Carnosine alone does not affect the cellular nitrite production, however, one hour pre-treatment with carnosine followed by 24 or 48 h stimulation of the cells with either lipopolysaccharide (LPS) alone or LPS with interferon-γ significantly increased both nitrite production and the amount of cell differentiation. It was found that inhibitors of iNOS drastically reduced the extracellular nitrite production in macrophages. Next, cells were incubated with 4,5-diaminofluorescein diacetate (DAF-FM DA) to determine intracellular NO production and cell lysates were analyzed by microchip electrophoresis with laser-induced fluorescence (ME-LIF). These results confirmed the production of a higher amount of NO by macrophages under simulated conditions compared to control. On the other hand, pre-treatment of the cells with carnosine significantly reduced the production of NO in stimulated cells. Preliminary experiments indicate that the mechanism of NO degradation in the presence of carnosine involves a direct chemical reaction between carnosine and NO.



F2.  Novel Microfluidic and Fluorescence Detection Approaches for the Determination of Superoxide and Nitric Oxide in Macrophage Cells

Claudia G. Fresta1,2, Richard P. S. de Campos1,2,3,4, Joseph M. Siegel1,2, Giuseppe Caruso1,2, José A. F. da Silva3,4, and Susan M. Lunte1,2,5

1Ralph N. Adams Institute for Bioanalytical Chemistry,  2Department of Chemistry, University of Kansas, Lawrence, KS, USA; 3Chemistry Institute, State University of Campinas, Campinas, Brazil; 4National Institute of Science and Technology in Bioanalytics (INCTBio), Campinas, Brazil; 5Department of Pharmaceutical Chemistry, University of Kansas, Lawrence, KS, USA

The anion superoxide is a reactive oxygen species (ROS) naturally produced in the human body. It is formed by the univalent reduction of O2 during various enzymatic reactions in mitochondrion and it is involved in many pathological and physiological signaling processes. An overproduction of superoxide can lead to oxidative damage to important biomolecules, such as DNA, lipids, and proteins. In living organisms, superoxide dismutase (SOD) protects the cell from the deleterious effects of superoxide, by catalyzing the dismutation of the superoxide radical into either ordinary molecular oxygen (O2) or hydrogen peroxide (H2O2). Quantitative information regarding intracellular superoxide production in living systems is difficult to obtain as a consequence of its high reactivity and low concentrations. Nitric oxide (NO) is an important gaseous molecule that transmits both intracellular and intercellular signals crucial for cell survival. Physiologically, NO is the most important vasodilator and regulator of the vascular tone and blood flow and is involved in several additional processes including platelet aggregation, neurotransmission, and the immune response. NO is generated in cells by a group of enzymes, known as nitric oxide synthases (NOS), which generates NO through the conversion of L-arginine to L-citrulline. NO can react with superoxide leading to the formation of a dangerous reactive nitrogen species, peroxynitrite. The first goal of this research is to determine changes in superoxide and nitric oxide production by macrophages cells following activation with proinflammatory agents (eg. LPS, IFN-γ, and PMA) using microchip electrophoresis (ME) coupled to laser-induced fluorescence (LIF). Macrophage cells were incubated with MitoSox (MitoHE) and DAF-FM DA to quantify superoxide and nitric oxide production, respectively. Additionally, the present work proposes to develop a methodology for a simultaneous detection and quantification of both superoxide and nitric oxide in the same cell lysate.



F3.  Single Cell Metabolite Fluctuation Predicts Growth Arrest

Huijing Wang, Christian J. Ray

Center for Computational Biology, University of Kansas, Lawrence, KS, USA

Pathogenic bacteria are one of the toughest enemies of human health because they can survive extreme stresses like antibiotic treatment by entering a dormant state. Pathogenic bacteria entering such a stationary state can cause stubborn chronic infections, and increase the chance of obtaining antibiotic resistance mechanisms. The ability to predict when cells enter a stationary state would enhance our ability to dynamically switch treatment strategies during infection to prevent the formation of chronic infections.

To identify dynamical characteristics of bacterial cell growth transitions, we are taking advantage of model-driven discovery process, which applies methods from signal processing to identify characteristic dynamics of biochemical networks that predict the cell growth transition.
In analogy to predictors of critical transitions in ecology, our central hypothesis is that metabolite fluctuations–"flickering"– in the metabolic network indicates an early warning sign of cellular growth transition. With a combination of signal processing analysis and stochastic simulation methods, we characterized several parameters that are closely related to metabolite kinetics in different systems.

We therefore characterized spike/flickering rates, the probability for having such flickering, the probability of enzyme saturation, the spike height, area, and various other kinetic parameters. We found two major types of systems with very different behavior, depending on the toxicity of the metabolite. Interestingly, the spikes behave differently when a cell is predicted to transition into stationary phase. Thus we conclude that the flickering in the system is indeed the dominant dynamic signature for predicting the cell growth transition.

We will further improve the generality of the model by exploring larger networks and more parameters to better understand metabolic predictors of the growth arrest transition.



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