Flow-distributed spikes for Schnakenberg kinetics

We study a system of reaction–diffusion–convection equations which combine a reaction–diffusion system with Schnakenberg kinetics and the convective flow equations. It serves as a simple model for flow-distributed pattern formation. We show how the choice of boundary conditions and the size of the flow influence the positions of the emerging spiky patterns and give conditions when they are shifted to the right or to the left. Further, we analyze the shape and prove the stability of the spikes. This paper is the first providing a rigorous analysis of spiky patterns for reaction-diffusion systems coupled with convective flow. The importance of these results for biological applications, in particular the formation of left–right asymmetry in the mouse, is indicated.     

An Efficient, Nonlinear Stability Analysis for Detecting Pattern Formation in Reaction Diffusion Systems

Reaction diffusion systems are often used to study pattern formation in biological systems. However, most methods for understanding their behavior are challenging and can rarely be applied to complex systems common in biological applications. I present a relatively simple and efficient, nonlinear stability technique that greatly aids such analysis when rates of diffusion are substantially different. This technique reduces a system of reaction diffusion equations to a system of ordinary differential equations tracking the evolution of a large amplitude, spatially localized perturbation of a homogeneous steady state. Stability properties of this system, determined using standard bifurcation techniques and software, describe both linear and nonlinear patterning regimes of the reaction diffusion system. I describe the class of systems this method can be applied to and demonstrate its application. Analysis of Schnakenberg and substrate inhibition models is performed to demonstrate the methods capabilities in simplified settings and show that even these simple models have nonlinear patterning regimes not previously detected. The real power of this technique, however, is its simplicity and applicability to larger complex systems where other nonlinear methods become intractable. This is demonstrated through analysis of a chemotaxis regulatory network comprised of interacting proteins and phospholipids. In each case, predictions of this method are verified against results of numerical simulation, linear stability, asymptotic, and/or full PDE bifurcation analyses.     

A simplified approach for modeling diffusion into cells

Regulation of the intracellular concentration of substrates is essential for the maintenance of a stable cellular environment. Diffusion and reaction processes supply and consume substrates within cells and determine their steady-state concentrations. To realistically represent these processes by computer simulation they must be modeled in three dimensions. Yet three-dimensional models are inherently computing intensive. This study describes a method, which substantially simplifies the modeling of diffusion into a polyhedral body (a cube), that was used as a model representation of a cell. The method is applied to a case study of oxygen diffusion into nitrogen-fixing, rhizobia-infected cells in legume nodules. The method involved generating a one-dimensional representation of the three-dimensional problem to provide a "surface area profile" of three-dimensional diffusion. The one-dimensional models were significantly easier to program, several orders of magnitude faster to solve and in this study were validated by assessing their results against those of comparable three-dimensional models of diffusion into the same body. The results show the one-dimensional method to be a close approximation of a three-dimensional source-sink problem with systematic differences below 10% for fractional oxygenation of leghemoglobin, cell respiration and nitrogenase activity. Larger differences between models (up to 45%) in the predicted average and innermost O(2)concentrations had no effects on the physiological conclusions of the study, but were attributed to the poorer resolution of the three- than the one-dimensional model, and to an inherent simplification in the derivation of the one-dimensional surface area profiles. The one-dimensional modeling approach was found to be a simple, yet powerful tool for the study of diffusion and reaction in biological systems.     

生物数学中的反应扩散系统奇摄动问题

研究了一类具有非线性捕食-被捕食反应扩散系统奇摄动问题,利用微分不等式理论,讨论了问题解的渐近性态。     

On the analysis of oxygen diffusion and reaction in biological systems

An analysis of oxygen diffusion and reaction in multiregion biological systems is presented. This analysis considers a time-dependent flux boundary condition and oxygen consumption governed by Michaelis-Menten kinetics. The mathematical problem is developed in a uniform fashion, so as to include both the single cell and anisotropic systems with distinct regions which are characteristic of either a multicell spheroid or a tumor mass. Both transient and steady-state solutions are obtained, based on orthogonal collocation. Literature results on single-cell analysis are corroborated, and detailed transient solutions are presented for the oxygenation of a multicell spheroid, and for systemic oxygenation of both small and large tumors.     

A multiscale theoretical model for diffusive mass transfer in cellular biological media

An integrated methodology is developed for the theoretical analysis of solute transport and reaction in cellular biological media, such as tissues, microbial flocs, and biofilms. First, the method of local spatial averaging with a weight function is used to establish the equation which describes solute conservation at the cellular biological medium scale, starting with a continuum-based formulation of solute transport at finer spatial scales. Second, an effective-medium model is developed for the self-consistent calculation of the local diffusion coefficient in the cellular biological medium, including the effects of the structural heterogeneity of the extra-cellular space and the reversible adsorption to extra-cellular polymers. The final expression for the local effective diffusion coefficient is: D(Abeta)=lambda(beta)D(Aupsilon), where D(Aupsilon) is the diffusion coefficient in water, and lambda(beta) is a function of the composition and fundamental geometric and physicochemical system properties, including the size of solute molecules, the size of extra-cellular polymer fibers, and the mass permeability of the cell membrane. Furthermore, the analysis sheds some light on the function of the extra-cellular hydrogel as a diffusive barrier to solute molecules approaching the cell membrane, and its implications on the transport of chemotherapeutic agents within a cellular biological medium. Finally, the model predicts the qualitative trend as well as the quantitative variability of a large number of published experimental data on the diffusion coefficient of oxygen in cell-entrapping gels, microbial flocs, biofilms, and mammalian tissues.     

Carrier facilitated diffusion

The concept of a mobile carrier combining reversibly with a substrate is considered as a possible mechanism for facilitated transport across biological membranes. The mathematical model is a system of three reaction diffusion equations with certain boundary conditions. Two limiting cases are discussed in detail: The case of a "thin" membrane where the diffusion of bound and unbound carrier from one surface to the other may be simulated by a single jump. If the diffusion rate of the substance to be transported is small, then an approximate stationary solution is derived using singular perturbation theory. Finally, the results of numerical simulations are presented for a wide range of parameters.     

Reaction rate enhancement by surface diffusion of adsorbates.

Ligands can be captured by a surface target through either direct bulk diffusion or surface diffusion following reversible adsorption to the surface. We have solved a steady state boundary value problem for a perfect sink disk target in the surface, taking into account bulk and surface diffusion coefficients D and Ds and adsorption/desorption kinetic rate constants ka and kd at non-target regions. Solutions have been successfully found by numerical computation. The results show that the rate of capture from the surface depends non-linearly on Ds, D, ka, kd and geometrical dimensions. In particular, we demonstrate that not only is the non-target region equilibrium constant Keq (= ka/kd) important in determining the rate of capture from the surface, but so are the kinetic rate constants ka and kd separately. In all cases, the surface adsorption/diffusion combination enhances the total rate of capture. The results should be useful for predicting reaction rates of biological membrane bound receptor clusters and substrate-immobilized enzymes.     

Diffusion exchange between a membrane-bounded sphere and its surrounding

The diffusion equation is solved for a membrane-bounded sphere situated in an infinite medium with different diffusion properties. The formal solution is obtained through Laplace transformation in the time variable. It is not possible to find a closed form solution in terms of analytical functions, and therefore a numerical inversion technique is applied to obtain the final solution. The application on a biological problem is discussed.     

Dynamic membrane structure induces temporal pattern formation

The understanding of temporal pattern formation in biological systems is essential for insights into regulatory processes of cells. Concerning this problem, the present work introduces a model to explain the attachment/detachment cycle of MARCKS and PKC at the cell membrane, which is crucial for signal transduction processes. Our model is novel with regard to its driving mechanism: Structural changes within the membrane fuel an activator–inhibitor based global density oscillation of membrane related proteins. Based on simulated results of our model, phase diagrams were generated to illustrate the interplay of MARCKS and PKC. They predict the oscillatory behavior in the form of the number of peaks, the periodic time, and the damping constant depending on the amounts of MARCKS and PKC, respectively. The investigation of the phase space also revealed an unexpected intermediate state prior to the oscillations for high amounts of MARCKS in the system. The validation of the obtained results was carried out by stability analysis, which also accounts for further enhanced understanding of the studied system. It was shown, that the occurrence of the oscillating behavior is independent of the diffusion and the consumption of the reactants. The diffusion terms in the used reaction–diffusion equations only act as modulating terms and are not required for the oscillation. The hypothesis of our work suggests a new mechanism of temporal pattern formation in biological systems. This mechanism includes a classical activator–inhibitor system, but is based on the modifications of the membrane structure, rather than a reaction–diffusion system.     

生物数学中的反应扩散系统的同伦映射方法

本文研究了一类非线性捕食-被捕食反应扩散系统,利用同伦映射理论,得到了初边值问题解的近似表示式。     

The impact of diffusion and stirring on the dynamics of interacting populations

We investigate the combined effects of diffusion and stirring on the dynamics of interacting populations which have spatial structure. Specifically we consider the marine phytoplankton and zooplankton populations, and model them as an excitable medium. The results are applicable to other biological and chemical systems. Under certain conditions the combination of diffusion and stirring is found to enhance the excitability, and hence population growth of the system. Diffusion is found to play an important role: too much and initial perturbations are smoothed away, too little and insufficient mixing takes place before the reaction is over. A key time-scale is the mix-down time, the time it takes for the spatial scale of a population to be reduced to that of a diffusively controlled filament. If the mix-down time is short compared to the reaction time-scale, then excitation of the system is suppressed. For intermediate values of the mix-down time the peak population can attain values many times that of a population without spatial structure. We highlight the importance of the spatial scale of the initial disturbance to the system.     

A new method for choosing the computational cell in stochastic reaction–diffusion systems

How to choose the computational compartment or cell size for the stochastic simulation of a reaction–diffusion system is still an open problem, and a number of criteria have been suggested. A generalized measure of the noise for finite-dimensional systems based on the largest eigenvalue of the covariance matrix of the number of molecules of all species has been suggested as a measure of the overall fluctuations in a multivariate system, and we apply it here to a discretized reaction–diffusion system. We show that for a broad class of first-order reaction networks this measure converges to the square root of the reciprocal of the smallest mean species number in a compartment at the steady state. We show that a suitably re-normalized measure stabilizes as the volume of a cell approaches zero, which leads to a criterion for the maximum volume of the compartments in a computational grid. We then derive a new criterion based on the sensitivity of the entire network, not just of the fastest step, that predicts a grid size that assures that the concentrations of all species converge to a spatially-uniform solution. This criterion applies for all orders of reactions and for reaction rate functions derived from singular perturbation or other reduction methods, and encompasses both diffusing and non-diffusing species. We show that this predicts the maximal allowable volume found in a linear problem, and we illustrate our results with an example motivated by anterior-posterior pattern formation in Drosophila, and with several other examples.     

描述细菌生长的反应扩散方程组的奇摄动

本文考虑一个描述细菌生长的反应扩散方程组的初边值问题,构造该问题解的任 意次精度的渐近展开式,讨论展开式的一致有效性及解的性质．     

Measurement of mass transport and reaction parameters in bulk solution using photobleaching. Reaction limited binding regime.

Fluorescence recovery after photobleaching (FRAP) has been used previously to investigate the kinetics of binding to biological surfaces. The present study adapts and further develops this technique for the quantification of mass transport and reaction parameters in bulk media. The technique's ability to obtain the bulk diffusion coefficient, concentration of binding sites, and equilibrium binding constant for ligand/receptor interactions in the reaction limited binding regime is assessed using the B72.3/TAG-72 monoclonal antibody/tumor associated antigen interaction as a model in vitro system. Measurements were independently verified using fluorometry. The bulk diffusion coefficient, concentration of binding sites and equilibrium binding constant for the system investigated were 6.1 +/- 1.1 x 10(-7) cm2/s, 4.4 +/- 0.6 x 10(-7) M, and 2.5 +/- 1.6 x 10(7) M-1, respectively. Model robustness and the applicability of the technique for in vivo quantification of mass transport and reaction parameters are addressed. With a suitable animal model, it is believed that this technique is capable of quantifying mass transport and reaction parameters in vivo.     

Fluorescence correlation spectroscopy and photobleaching recovery of multiple binding reactions. I. Theory and FCS measurements

Fluorescence correlation spectroscopy (FCS) and fluorescence photobleaching recovery (FPR) are two methods that may be used to measure diffusion and chemical reaction kinetics in small, labile systems such as biological cells. These methods are here applied to systems in which a fluorescent ligand can bind to a polyvalent substrate molecule in a multistep reaction sequence. The analytical theory for both FCS and FPR is extended to allow analysis of these kinds of systems. Experimental measurements of the binding of ethidium bromide to DNA by FCS confirm the theoretical analysis. (FPR measurements on the same system are reported in the accompanying paper.) The analysis shows that FCS and FPR perceive multivalent binding reactions differently. This difference results from the selective effect of the photobleaching process in the chemical reaction system. The development and results we report could have useful applications to a wide range of biopolymeric binding and assembly process.     

Identification of dynamic mass-action biochemical reaction networks using sparse Bayesian methods

Identifying the reactions that govern a dynamical biological system is a crucial but challenging task in systems biology. In this work, we present a data-driven method to infer the underlying biochemical reaction system governing a set of observed species concentrations over time. We formulate the problem as a regression over a large, but limited, mass-action constrained reaction space and utilize sparse Bayesian inference via the regularized horseshoe prior to produce robust, interpretable biochemical reaction networks, along with uncertainty estimates of parameters. The resulting systems of chemical reactions and posteriors inform the biologist of potentially several reaction systems that can be further investigated. We demonstrate the method on two examples of recovering the dynamics of an unknown reaction system, to illustrate the benefits of improved accuracy and information obtained.