scholarly journals Crowding within synaptic junctions influence the degradation of adenoside nucleotides by CD39 and CD73 ectonucleotidases

2021 ◽  
Author(s):  
Hadi Rahmaninejad ◽  
Tom Pace ◽  
Peter Kekenes-Huskey
Keyword(s):  
Electrostatic Interactions ◽  
Configurational Entropy ◽  
Reaction Diffusion ◽  
Adenosine Monophosphate ◽  
Adenosine Diphosphate ◽  
Surprising Result ◽  
Surface Charges ◽  
Association Rate ◽  
Synaptic Junction ◽  
Reaction Diffusion Model

Synapsed cells can communicate using exocytosed nucleotides like adenosine triphosphate (ATP). Ectonucleotidases localized to a synaptic junction degradesuch nucleotides into metabolites like adenosine monophosphate (AMP) or adenosine, oftentimes in a sequential manner. CD39 and CD73 are a representativeset of coupled ectonucleotidases, where CD39 first converts ATP and adenosine diphosphate (ADP) into AMP, after which the AMP product is dephosphorylated into adenosine by CD73. Hence, CD39/CD73 help shape cellular responses to extracellular ATP. In a previous study [1] we demonstrated that the rates of coupled CD39/CD73 activity within synapse-like junctions are strongly controlled by the enzymes' co-localization, their surface charge densities, and the electrostatic potential of the surrounding cell membranes. In this study, we demonstrate that crowders within a synaptic junction, which can include globular proteins like cytokines and membrane-bound proteins, impact coupled CD39/CD73 electronucleotidase activity and in turn, the availability of intrasynapse ATP. Specifically, we simulated a spatially-explicit, reaction-diffusion model for the coupled conversion of ATP -> AMP and AMP -> adenosine in a model synaptic junction with crowders via the finite element method. Our modeling results suggest that the association rate for ATP to CD39 is strongly influenced by the density of intrasynaptic protein crowders, as increasing crowder density suppressed ATP association kinetics. Much of this suppression can be rationalized based on a loss of configurational entropy. The surface charges of crowders can further influence the association rate, with the surprising result that favorable crowder/nucleotide electrostatic interactions can yield CD39 association rates that are faster than crowder-free configurations. However, attractive crowder/nucleotide interactions decrease the rate and efficiency of adenosine production, which in turn increases the availability of ATP and AMP within the synapse relative to crowder-free configurations. These findings highlight how CD39/CD73 ectonucleotidase activity, electrostatics and crowding within synapses influence the availability of nucleotides for intercellular communication.

A stochastic reaction-diffusion model for protein aggregation on DNA

2017 ◽  
Vol 28 (08) ◽  
pp. 1750102 ◽  
Author(s):  
Nikolaos K. Voulgarakis
Keyword(s):  
Electrostatic Interactions ◽  
Reaction Diffusion ◽  
Control Parameters ◽  
Physical Mechanisms ◽  
Softening Behavior ◽  
Vital Functions ◽  
Reaction Diffusion Model ◽  
Proposed Model ◽  
Negative Supercoiling ◽  
Stochastic Reaction

Vital functions of DNA, such as transcription and packaging, depend on the proper clustering of proteins on the double strand. The present study investigates how the interplay between DNA allostery and electrostatic interactions affects protein clustering. The statistical analysis of a simple but transparent computational model reveals two major consequences of this interplay. First, depending on the protein and salt concentration, protein filaments exhibit a bimodal DNA stiffening and softening behavior. Second, within a certain domain of the control parameters, electrostatic interactions can cause energetic frustration that forces proteins to assemble in rigid spiral configurations. Such spiral filaments might trigger both positive and negative supercoiling, which can ultimately promote gene compaction and regulate the promoter. It has been experimentally shown that bacterial histone-like proteins assemble in similar spiral patterns and/or exhibit the same bimodal behavior. The proposed model can, thus, provide computational insights into the physical mechanisms used by proteins to control the mechanical properties of the DNA.

scholarly journals A new analyzing technique for nonlinear time fractional Cauchy reaction-diffusion model equations

2020 ◽  
Vol 19 ◽  
pp. 103462 ◽  
Author(s):  
Hijaz Ahmad ◽  
Tufail A. Khan ◽  
Imtiaz Ahmad ◽  
Predrag S. Stanimirović ◽  
Yu-Ming Chu
Keyword(s):  
Diffusion Model ◽  
Reaction Diffusion ◽  
Reaction Diffusion Model ◽  
Model Equations

Conditions for the local and global asymptotic stability of the time–fractional Degn–Harrison system

2020 ◽  
Vol 21 (7-8) ◽  
pp. 749-759
Author(s):  
Rachida Mezhoud ◽  
Khaled Saoudi ◽  
Abderrahmane Zaraï ◽  
Salem Abdelmalek
Keyword(s):  
Asymptotic Stability ◽  
Global Asymptotic Stability ◽  
Lyapunov Method ◽  
Sufficient Conditions ◽  
Reaction Diffusion ◽  
Linearization Method ◽  
Direct Lyapunov Method ◽  
Fractional Systems ◽  
Reaction Diffusion Model ◽  
Theoretical Results

AbstractFractional calculus has been shown to improve the dynamics of differential system models and provide a better understanding of their dynamics. This paper considers the time–fractional version of the Degn–Harrison reaction–diffusion model. Sufficient conditions are established for the local and global asymptotic stability of the model by means of invariant rectangles, the fundamental stability theory of fractional systems, the linearization method, and the direct Lyapunov method. Numerical simulation results are used to illustrate the theoretical results.

scholarly journals Multiscale modeling of glioma pseudopalisades: contributions from the tumor microenvironment

2021 ◽  
Vol 82 (6) ◽  
Author(s):  
Pawan Kumar ◽  
Jing Li ◽  
Christina Surulescu
Keyword(s):  
Multiscale Modeling ◽  
Reaction Diffusion ◽  
Tumor Grade ◽  
Invasive Potential ◽  
Macroscopic System ◽  
Active Particles ◽  
Reaction Diffusion Model ◽  
Different Types ◽  
Parabolic Scaling ◽  
Parameter Ranges

AbstractGliomas are primary brain tumors with a high invasive potential and infiltrative spread. Among them, glioblastoma multiforme (GBM) exhibits microvascular hyperplasia and pronounced necrosis triggered by hypoxia. Histological samples showing garland-like hypercellular structures (so-called pseudopalisades) centered around the occlusion site of a capillary are typical for GBM and hint on poor prognosis of patient survival. We propose a multiscale modeling approach in the kinetic theory of active particles framework and deduce by an upscaling process a reaction-diffusion model with repellent pH-taxis. We prove existence of a unique global bounded classical solution for a version of the obtained macroscopic system and investigate the asymptotic behavior of the solution. Moreover, we study two different types of scaling and compare the behavior of the obtained macroscopic PDEs by way of simulations. These show that patterns (not necessarily of Turing type), including pseudopalisades, can be formed for some parameter ranges, in accordance with the tumor grade. This is true when the PDEs are obtained via parabolic scaling (undirected tissue), while no such patterns are observed for the PDEs arising by a hyperbolic limit (directed tissue). This suggests that brain tissue might be undirected - at least as far as glioma migration is concerned. We also investigate two different ways of including cell level descriptions of response to hypoxia and the way they are related .

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