Sequential enzymatic reactions and stability of biomolecules immobilized onto phospholipid polymer nanoparticles

Polymer nanoparticles for sequential enzymatic reactions were prepared by combining a phospholipid polymer shell with a polystyrene core. The active ester groups for the bioconjugation and phospholipid polar groups were incorporated into the phospholipid polymer backbone using a novel active ester monomer and 2-methacryloyloxyethyl phosphorylcholine. For the sequential enzymatic reactions, acetylcholinesterase, choline oxidase, and horseradish peroxidase-labeled IgG were immobilized onto the nanoparticles. As substrates, acetylcholine chloride, choline chloride, and tetramethylbenzidine were added to the nanoparticle suspension, the acetylcholine chloride was converted to choline chloride, the choline chloride was oxidized by choline oxidase, and hydrogen peroxide was then formed as an enzymatic degradation product. The hydrogen peroxide was used for the next enzymatic reaction (oxidized by peroxidase) with tetramethylbenzidine. The sequential enzymatic reactions on the nanoparticles via degradation products (hydrogen peroxide) were significantly higher than that of the enzyme mixture. This result indicated that the diffusion pathway of the enzymatic products and the localization of the immobilized enzyme were important for these reactions. These nanoparticles were capable of facilitating sequential enzymatic reactions.     

Robustness analysis and behavior discrimination in enzymatic reaction networks

Characterizing the behavior and robustness of enzymatic networks with numerous variables and unknown parameter values is a major challenge in biology, especially when some enzymes have counter-intuitive properties or switch-like behavior between activation and inhibition. In this paper, we propose new methodological and tool-supported contributions, based on the intuitive formalism of temporal logic, to express in a rigorous manner arbitrarily complex dynamical properties. Our multi-step analysis allows efficient sampling of the parameter space in order to define feasible regions in which the model exhibits imposed or experimentally observed behaviors. In a first step, an algorithmic methodology involving sensitivity analysis is conducted to determine bifurcation thresholds for a limited number of model parameters or initial conditions. In a second step, this boundary detection is supplemented by a global robustness analysis, based on quasi-Monte Carlo approach that takes into account all model parameters. We apply this method to a well-documented enzymatic reaction network describing collagen proteolysis by matrix metalloproteinase MMP2 and membrane type 1 metalloproteinase (MT1-MMP) in the presence of tissue inhibitor of metalloproteinase TIMP2. For this model, our method provides an extended analysis and quantification of network robustness toward paradoxical TIMP2 switching activity between activation or inhibition of MMP2 production. Further implication of our approach is illustrated by demonstrating and analyzing the possible existence of oscillatory behaviors when considering an extended open configuration of the enzymatic network. Notably, we construct bifurcation diagrams that specify key parameters values controlling the co-existence of stable steady and non-steady oscillatory proteolytic dynamics.     

Human thrombin: enzymatic properties,stability and standardization of preparation

The work deals with estimation of thrombin preparation having such features as: sedimentation activity 3000-3200 NIH un. per 1 mg of protein and 97% of active centres. The enzyme isolated has been estimated according to the amidolytic activity on synthetic substrates S-2160 and BAPNA being equal 5200 and 185 milli un/mg of protein, respectively. According to the electrophoresis in PAAG in the presence of Ds-Na the preparation is homogenous, its molecular mass is 36000. The fibrinogen sedimentation time dependence on the isolated thrombin concentration has been estimated as well as the comparative analysis with the thrombin of the firm "Sigma" with the previously calibrated activity using the international standartion (coded P4) has been conducted. The absence of proportionality between the substrate sedimentation time and the preparation concentration has been determined. It has been revealed, that if the experimental findings are presented in the units 1/t against the thrombin units NIH the right lines are received within the limits used. The defreezing and secondary freezing of the preparation preserved under -20 degrees C have been showed as rendering an essential effect on thrombin activity. In order of the enzyme stabilizing at preserving the thrombin isolated has been concentrated applying the amycon membranes (MWCo: 30,000). While applying the thrombin water-saline solution in the conditions selected the preparation has showed itself practically stable during a year without utilizing any admixtures. The essential effect on thrombin has been found from the side of 1% glycin, 0.5% PEG, 1% saccharose and so on. The thrombin isolated high functional homogeneity, its stability permit to recommend the preparation as an operative standard.     

Rule-dynamical generalization of McCulloch-Pitts neuron networks

A new aspect for neuronal networks is presented. The aspect is based on the concept of ruledynamics which was originally proposed by one of the authors, Aizawa. The concept of ruledynamics were modeled on the two states cellular automata of neighborhood-three (CA(2/3)). A brief review of ruledynamics is also presented, because most publications of the authors so far have been in Japanese. Our concise assertion in the present paper is that a neuronal network realizes a kind of ruledynamics. This assertion is a speculation on the comparison of McCulloch-Pitts neuron networks with ruledynamics on CA(2/3). A trial is originally shown to demonstrate that a McCulloch-Pitts neuron network can be imitated by an extended version of ruledynamics on CA(2/3).     

Structure, conformational stability, and enzymatic properties of acylphosphatase from the hyperthermophile Sulfolobus solfataricus

The structure of AcP from the hyperthermophilic archaeon Sulfolobus solfataricus has been determined by (1)H-NMR spectroscopy and X-ray crystallography. Solution and crystal structures (1.27 A resolution, R-factor 13.7%) were obtained on the full-length protein and on an N-truncated form lacking the first 12 residues, respectively. The overall Sso AcP fold, starting at residue 13, displays the same betaalphabetabetaalphabeta topology previously described for other members of the AcP family from mesophilic sources. The unstructured N-terminal tail may be crucial for the unusual aggregation mechanism of Sso AcP previously reported. Sso AcP catalytic activity is reduced at room temperature but rises at its working temperature to values comparable to those displayed by its mesophilic counterparts at 25-37 degrees C. Such a reduced activity can result from protein rigidity and from the active site stiffening due the presence of a salt bridge between the C-terminal carboxylate and the active site arginine. Sso AcP is characterized by a melting temperature, Tm, of 100.8 degrees C and an unfolding free energy, DeltaG(U-F)H2O, at 28 degrees C and 81 degrees C of 48.7 and 20.6 kJ mol(-1), respectively. The kinetic and structural data indicate that mesophilic and hyperthermophilic AcP's display similar enzymatic activities and conformational stabilities at their working conditions. Structural analysis of the factor responsible for Sso AcP thermostability with respect to mesophilic AcP's revealed the importance of a ion pair network stabilizing particularly the beta-sheet and the loop connecting the fourth and fifth strands, together with increased density packing, loop shortening and a higher alpha-helical propensity.     

Some new stability properties of dynamic neural networks with different time-scales

Dynamic neural networks with different time-scales include the aspects of fast and slow phenomenons. Some applications require that the equilibrium points of these networks to be stable. The main contribution of the paper is that Lyapunov function and singularly perturbed technique are combined to access several new stable properties of different time-scales neural networks. Exponential stability and asymptotic stability are obtained by sector and bound conditions. Compared to other papers, these conditions are simpler. Numerical examples are given to demonstrate the effectiveness of the theoretical results.     

Trimethylene carbonate and epsilon-caprolactone based (co)polymer networks: mechanical properties and enzymatic degradation

High molecular weight trimethylene carbonate (TMC) and epsilon-caprolactone (CL) (co)polymers were synthesized. Melt pressed (co)polymer films were cross-linked by gamma irradiation (25 kGy or 50 kGy) in vacuum, yielding gel fractions of up to 70%. The effects of copolymer composition and irradiation dose on the cytotoxicity, surface properties, degradation behavior, and mechanical and thermal properties of these (co)polymers and networks were investigated. Upon incubation with cell culture medium containing extracts of (co)polymers and networks, human foreskin fibroblasts remained viable. For all (co)polymers and networks, cell viabilities were determined to be higher than 94%. The formed networks were flexible, with elastic moduli ranging from 2.7 to 5.8 MPa. Moreover, these form-stable networks were creep resistant under dynamic conditions. The permanent deformation after 2 h relaxation was as low as 1% after elongating to 50% strain for 20 times. The in vitro enzymatic erosion behavior of these hydrophobic (co)polymers and networks was investigated using aqueous lipase solutions. The erosion rates in lipase solution could be tuned linearly from 0.8 to 45 mg/(cm (2) x day) by varying the TMC to CL ratio and the irradiation dose. The copolymers and networks degraded essentially by a surface erosion mechanism.     

The enzymatic neuron as a reaction-diffusion network of cyclic nucleotides

Recent evidence suggests that the cyclic nucleotides play a central role in the intracellular processing of neural signals. The dynamics of this system may be seen as a realization of the enzymatic neuron model. Enzymatic neurons are formal neurons which map binary afferent signals into patterns of excitation across an abstract membrane. The distribution of enzyme-like elements called excitases enables a set of local threshold functions to determine the firing activity of the neuron. This paper analyzes the basic properties of enzymatic neurons in a simple continuous-time framework, and shows how they may be presented as reaction-diffusion networks which model the cyclic nucleotide system. We present the results of computer simulations of this neuron and discuss its implications for selectional learning and its relation to conventional two-factor systems. One fundamental property of the reaction-diffusion neuron is its so-called “double-dynamics” property; examination of this property and its contribution to the computing power of the neuron provides some insight into the obscure relation between microscopic and macroscopic models of computation.     

Information properties of neuron assemblies

Calculations are made of information parameters of neuron nets with binary plastic synapses of Hebb and Albus which are able to form and produce neuron assemblies. It has been shown that for such neuron nets Hebb synapses are more effective than Albus synapses.     

Logical networks and behavior

A method is developed, which is essentially an elaboration of the Pitts-McCulloch net, to give a systematic and effective account of behavior in mathematical terms. In particular, in this paper an interpretation is given of an expectancy-type theory of behavior with suggestions for its extension.     

Incorporation of hexose nucleoside analogues into oligonucleotides: synthesis, base-pairing properties and enzymatic stability.

Oligonucleotides containing 1-(2,4-dideoxy-beta-D-erythro-hexopyranosyl)thymine (2) and 1-(3,4-dideoxy-beta-D-erythro-hexopyranosyl)thymine (3) were synthesized on a solid support using the phosphoramidite approach. The properties of these oligonucleotides were compared with the earlier reported characteristics of oligonucleotides containing 1-(2,3-dideoxy-beta-D-erythro-hexopyranosyl) thymine (1). The order in enzymatic stability of end-substituted oligonucleotides is 3 greater than 1 much greater than 2. The hybridization properties of the modified oligonucleotides are in reverse order: 2 much greater than 1 greater than 3.     

Influences of membrane properties on phase response curve and synchronization stability in a model globus pallidus neuron

The activity patterns of the globus pallidus (GPe) and subthalamic nucleus (STN) are closely associated with motor function and dysfunction in the basal ganglia. In the pathological state caused by dopamine depletion, the STN–GPe network exhibits rhythmic synchronous activity accompanied by rebound bursts in the STN. Therefore, the mechanism of activity transition is a key to understand basal ganglia functions. As synchronization in GPe neurons could induce pathological STN rebound bursts, it is important to study how synchrony is generated in the GPe. To clarify this issue, we applied the phase-reduction technique to a conductance-based GPe neuronal model in order to derive the phase response curve (PRC) and interaction function between coupled GPe neurons. Using the PRC and interaction function, we studied how the steady-state activity of the GPe network depends on intrinsic membrane properties, varying ionic conductances on the membrane. We noted that a change in persistent sodium current, fast delayed rectifier Kv3 potassium current, M-type potassium current and small conductance calcium-dependent potassium current influenced the PRC shape and the steady state. The effect of those currents on the PRC shape could be attributed to extension of the firing period and reduction of the phase response immediately after an action potential. In particular, the slow potassium current arising from the M-type potassium and the SK current was responsible for the reduction of the phase response. These results suggest that the membrane property modulation controls synchronization/asynchronization in the GPe and the pathological pattern of STN–GPe activity.     

PNA-DNA chimeras containing 5-alkynyl-pyrimidine PNA units. Synthesis, binding properties, and enzymatic stability

Three chimeric dimer synthons (oeg_t(NH)T, oeg_up(NH)T and oeg_uh(NH)T) containing thymine (t), 5-(1-propynyl)-uracil (up) and 5-(1-hexyn-1-yl)-uracil (uh) PNA units with N-(2-hydroxyethyl)glycine (oeg) backbone were synthesized in solution and incorporated into T20 oligonucleotide analogues, using standard P-amidite chemistry. Insertion of dimer blocks led to destabilization of duplexes with dA20 target. The smallest Tm drops were found for chimeras containing oeg_up(NH)T dimers. Incorporation of the chimeric synthons into the 3'-end of T20 brought about growing resistance to 3'-exonucleolytic (SV PDE) cleavage in the order of oeg_t(NH)T < oeg_up(NH)T < oeg_uh(NH)T. Due to different endonuclease activities of 3'- and 5'-exonucleases applied, placing of five consecutive dimers at the 5'-terminus resulted in a relatively smaller, but also side-chain dependent, stabilization towards the hydrolysis by 5'-exonuclease (BS PDE). Neither exonucleases (SV and BS PDE) nor an endonuclease (Nuclease P1) could hydrolyse the unnatural phosphodiester bond linking the 3'-OH of thymidine to the terminal OH of N-(2-hydroxyethyl)glycine PNA backbone.     

单神经元分辨水平的小鼠全脑网络可视化

脑科学是当今国际科技研究的前沿领域。脑是最复杂的器官,其中尚有诸多重大的基础科学问题有待解决。开展脑科学研究需多学科人员协同攻关,对于建立新学科将有极大的促进作用,对于人类健康和社会发展具有巨大的推动作用。简述了神经科学在结构成像方面的基础性需求,介绍了小鼠全脑可视化的发展历程以及近几年的代表性研究,并展望了全脑可视化研究的发展趋势,对可能存在的难点予以说明。     

Reduced models of networks of coupled enzymatic reactions

The Michaelis-Menten equation has played a central role in our understanding of biochemical processes. It has long been understood how this equation approximates the dynamics of irreversible enzymatic reactions. However, a similar approximation in the case of networks, where the product of one reaction can act as an enzyme in another, has not been fully developed. Here we rigorously derive such an approximation in a class of coupled enzymatic networks where the individual interactions are of Michaelis-Menten type. We show that the sufficient conditions for the validity of the total quasi-steady state assumption (tQSSA), obtained in a single protein case by Borghans, de Boer and Segel can be extended to sufficient conditions for the validity of the tQSSA in a large class of enzymatic networks. Secondly, we derive reduced equations that approximate the network's dynamics and involve only protein concentrations. This significantly reduces the number of equations necessary to model such systems. We prove the validity of this approximation using geometric singular perturbation theory and results about matrix differentiation. The ideas used in deriving the approximating equations are quite general, and can be used to systematize other model reductions.     

Exploring multiplicity conditions in enzymatic reaction networks

In this work, a novel algorithmic approach to detect multiplicity of steady states in enzymatic reaction networks is presented. The method exploits the structural properties of networks derived from the Chemical Reaction Network Theory. In first instance, the space of parameters is divided in different regions according to the qualitative behavior induced by the parameters in the long term dynamics of the network. Once the regions are identified, a condition for the appearance of multiplicities is checked in the different regions by solving a given optimization problem. In this way, the method allows the characterization of the whole parameter space of biochemical networks in terms of the appearance or not of multistability. The approach is illustrated through a well‐known case of enzymatic catalysis with substrate inhibition. © 2009 American Institute of Chemical Engineers Biotechnol. Prog., 2009     

Biophysical stability and enzymatic recognition of oxanine in DNA

Oxanine (Oxa), which is one of the major products generated from guanine by nitrosative oxidation and is as long-lived as Gua in DNA, has been thought to be one of the major causes for NO-induced DNA damage. In the present study, using several synthetic Oxa-containing oligodeoxynucleotides, biophysical stability and enzymatic recognition of Oxa was investigated in DNA strands. It was found that Oxa did not mediate marked distortion in the whole DNA structure although Oxa pairing with 4 normal bases decreased thermal stability of the DNA duplexes compared to Gua:Cyt base pair. Regarding the responses of the DNA-relevant enzymes to Oxa, it was determined that Oxa was recognized as Gua except that DNA polymerases incorporated Thy as well as Cyt opposite Oxa. These results imply that Oxa tends to behave as a kind of naturally occurring base, Gua and therefore, would be involved in the genotoxic and cytotoxic threats of NO in cellular system.     

Steady state multiplicity and stability of enzymatic reaction systems

Several techniques for investigating the multiplicity and stability of open isothermal enzymatic reactors are discussed and some of the pitfalls in previous thinking pointed out. The example which is used to illustrate these methods exhibits several interesting features. Among these is the existence of a stable oscillatory state which surrounds a unique steady state which is asymptotically stable to certain finite disturbances.