Effect of acetate on glucose utilization by isolated rat thymocytes

The effects of acetate and ammonium salts on glucose metabolism, aminoisobutyric acid influx, and radioiodinated insulin binding in isolated thymocytes were studied. Acetate in the concentration range, 0.1–30 mm, was found to inhibit basal and insulin-stimulated CO₂ production whereas ammonium chloride at concentrations greater than 0.3 mm was slightly stimulatory. Ammonium salts inhibited glucose incorporation into glycogen and aminoisobutyric acid influx only at high concentration (30 mm). Neither acetate nor ammonium salts had significant effects on glucose incorporation into glycogen or aminoisobutyric acid influx at lower concentrations. No effect on insulin binding was observed. The observation that very low concentrations of acetate can perturb these biological assay systems suggests that other biological functions may be affected by trace amounts of buffer salts carried over from protein isolation steps.     

A fault detection service for wide area distributed computations

The potential for faults in distributed computing systems is a significant complicating factor for application developers. While a variety of techniques exist for detecting and correcting faults, the implementation of these techniques in a particular context can be difficult. Hence, we propose a fault detection service designed to be incorporated, in a modular fashion, into distributed computing systems, tools, or applications. This service uses well-known techniques based on unreliable fault detectors to detect and report component failure, while allowing the user to trade off timeliness of reporting against false positive rates. We describe the architecture of this service, report on experimental results that quantify its cost and accuracy, and describe its use in two applications, monitoring the status of system components of the GUSTO computational grid testbed and as part of the NetSolve network-enabled numerical solver. This revised version was published online in July 2006 with corrections to the Cover Date.     

Structural characterization of the peroxodiiron(III) intermediate generated during oxygen activation by the W48A/D84E variant of ribonucleotide reductase protein R2 from Escherichia coli

The diiron(II) cluster in the R2 subunit of Escherichia coli ribonucleotide reductase (RNR) activates oxygen to generate a mu-oxodiiron(III) cluster and the stable tyrosyl radical that is critical for the conversion of ribonucleotides to deoxyribonucleotides. Like those in other diiron carboxylate proteins, such as methane monooxygenase (MMO), the R2 diiron cluster is proposed to activate oxygen by formation of a peroxodiiron(III) intermediate followed by an oxidizing high-valent cluster. Substitution of key active site residues results in perturbations of the normal oxygen activation pathway. Variants in which the active site ligand, aspartate (D) 84, is changed to glutamate (E) are capable of accumulating a mu-peroxodiiron(III) complex in the reaction pathway. Using rapid freeze-quench techniques, this intermediate in a double variant, R2-W48A/D84E, was trapped for characterization by M?ssbauer and X-ray absorption spectroscopy. These samples contained 70% peroxodiiron(III) intermediate and 30% diferrous R2. An Fe-Fe distance of 2.5 A was found to be associated with the peroxo intermediate. As has been proposed for the structures of the higher valent intermediates in both R2 and MMO, carboxylate shifts to a mu-(eta(1),eta(2)) or a mu-1,1 conformation would most likely be required to accommodate the short 2.5 A Fe-Fe distance. In addition, the diferrous form of the enzyme present in the reacted sample has a longer Fe-Fe distance (3.5 A) than does a sample of anaerobically prepared diferrous R2 (3.4 A). Possible explanations for this difference in detected Fe-Fe distance include an O(2)-induced conformational change prior to covalent chemistry or differing O(2) reactivity among multiple diiron(II) forms of the cluster.     

Two approaches for metabolic pathway analysis?

Metabolic pathway analysis is becoming increasingly important for assessing inherent network properties in (reconstructed) biochemical reaction networks. Of the two most promising concepts for pathway analysis, one relies on elementary flux modes and the other on extreme pathways. These concepts are closely related because extreme pathways are a subset of elementary modes. Here, the common features, differences and applicability of these concepts are discussed. Assessing metabolic systems by the set of extreme pathways can, in general, give misleading results owing to the exclusion of possibly important routes. However, in certain network topologies, the sets of elementary modes and extreme pathways coincide. This is quite often the case in realistic applications. In our opinion, the unification of both approaches into one common framework for metabolic pathway analysis is necessary and achievable.     

Steady-State Differential Dose Response in Biological Systems

In pharmacology and systems biology, it is a fundamental problem to determine how biological systems change their dose-response behavior upon perturbations. In particular, it is unclear how topologies, reactions, and parameters (differentially) affect the dose response. Because parameters are often unknown, systematic approaches should directly relate network structure and function. Here, we outline a procedure to compare general non-monotone dose-response curves and subsequently develop a comprehensive theory for differential dose responses of biochemical networks captured by non-equilibrium steady-state linear framework models. Although these models are amenable to analytical derivations of non-equilibrium steady states in principle, their size frequently increases (super) exponentially with model size. We extract general principles of differential responses based on a model’s graph structure and thereby alleviate the combinatorial explosion. This allows us, for example, to determine reactions that affect differential responses, to identify classes of networks with equivalent differential, and to reject hypothetical models reliably without needing to know parameter values. We exemplify such applications for models of insulin signaling.     

Signaling cascades as cellular devices for spatial computations

Signaling networks usually include protein-modification cycles. Cascades of such cycles are the backbones of multiple signaling pathways. Protein gradients emerge from the spatial separation of opposing enzymes, such as kinases and phosphatases, or guanine nucleotide exchange factors (GEFs) and GTPase activating proteins (GAPs) for GTPase cycles. We show that different diffusivities of an active protein form and an inactive form leads to spatial gradients of protein abundance in the cytoplasm. For a cascade of cycles, using a discrete approximation of the space, we derive an analytical expression for the spatial gradients and show that it converges to an exact solution with decreasing the size of the quantization. Our results facilitate quantitative analysis of the dependence of spatial gradients on the network topology and reaction kinetics. We demonstrate how different cascade designs filter and process the input information to generate precise, complex spatial guidance for multiple GTPase effector processes. Thus, protein-modification cascades may serve as devices to compute complex spatial distributions of target proteins within intracellular space.     

Functional coupling in bovine ciliary epithelial cells is modulated by carbachol

The functional coupling of the ciliaryepithelium was studied in isolated pairs (couplets) of pigmentedciliary epithelial (PCE) and nonpigmented ciliary epithelial (NPCE)cells using the whole cell patch clamp and the fluorescent dye luciferyellow. One cell of the pair (usually the NPCE cell of a NPCE-PCE cell couplet) was accessed with a 2-5 M electrode, containing1-2 mM lucifer yellow, in the whole cell configuration of thepatch clamp. After voltage-clamp experiments were completed, cells were viewed under a fluorescent microscope to confirm that the cells werecoupled. The electrical coupling of the cells was also studied bycalculating the capacitance (using the time-domain technique), assuminga "supercell" model for coupled cells. The mean capacitance ofcoupled pairs was 79.8 ± 4.3 (SE) pF(n = 47) compared with single cellcapacitances of 36.8 ± 3.4 pF (n = 10) for PCE cells and 38.1 ± 3.1 pF(n = 15) for NPCE cells. Octanol,carbachol (CCh), and raised extracellularCa²⁺ concentration([Ca²⁺]_o)all caused uncoupling in pairs (couplets) of coupled NPCE and PCEcells. At room temperature (22-24°C), the capacitance of thecouplets decreased from 70.5 ± 8.0 to 48.0 ± 5.2 pF(n = 5) when exposed to octanol (1 mM), from 73.8 ± 9.2 to 43.2 ± 9.5 pF(n = 4) when exposed to CCh (100 µM), and from 80.5 ± 6.7 to 49.9 ± 7.8 pF(n = 4) when exposed to 10 mM[Ca²⁺]_o.The response to CCh was dose dependent; at higher temperatures of34-37°C, 10 µM CCh caused a 38% reduction in capacitance,from 53.7 ± 9.7 to 33.5 ± 3.3 pF(n = 7) with a half-time of 249 s, and100 µM CCh caused a 49% reduction in capacitance, from 51.3 ± 5.6 to 26.0 ± 2.4 pF (n = 7) witha half-time of 124 s. After pairs uncoupled and the uncoupling agentwas washed out, the cell pairs often exhibited an increase incapacitance that we interpreted as "recoupling" or a reopening ofthe gap junctional communication pathway; the half-time for thisprocess was 729 s after uncoupling with 100 µM CCh and 211 s afteruncoupling with 10 µM CCh. This interpretation was confirmedoptically by the spread of lucifer yellow into both cells of anuncoupled pair with a time course corresponding to the increase inelectrical coupling. The controllable coupling of ciliary epithelialcells extends the idea of a functional syncytium involved in activetransport. PCE cells take up solute and water from the blood, whichthen cross to NPCE cells via gap junctions and from there are secretedinto the posterior chamber of the eye. Modulation of the couplingbetween NPCE and PCE cells may provide a mechanism to controlsecretion.

     

Quantitative performance metrics for robustness in circadian rhythms

MOTIVATION: Sensitivity analysis provides key measures that aid in unraveling the design principles responsible for the robust performance of biological networks. Such metrics allow researchers to investigate comprehensively model performance, to develop more realistic models, and to design informative experiments. However, sensitivity analysis of oscillatory systems focuses on period and amplitude characteristics, while biologically relevant effects on phase are neglected. RESULTS: Here, we introduce a novel set of phase-based sensitivity metrics for performance: period, phase, corrected phase and relative phase. Both state- and phase-based tools are applied to free-running Drosophila melanogaster and Mus musculus circadian models. Each metric produces unique sensitivity values used to rank parameters from least to most sensitive. Similarities among the resulting rank distributions strongly suggest a conservation of sensitivity with respect to parameter function and type. A consistent result, for instance, is that model performance of biological oscillators is more sensitive to global parameters than local (i.e. circadian specific) parameters. Discrepancies among these distributions highlight the individual metrics' definition of performance as specific parametric sensitivity values depend on the defined metric, or output. AVAILABILITY: An implementation of the algorithm in MATLAB (Mathworks, Inc.) is available from the authors. SUPPLEMENTARY INFORMATION: Supplementary Data are available at Bioinformatics online.