Stochastic self-assembly of reaction-diffusion patterns in synaptic membranes

2021 ◽  
Vol 104 (1) ◽  
Author(s):  
Everest Law ◽  
Yiwei Li ◽  
Osman Kahraman ◽  
Christoph A. Haselwandter
1998 ◽  
Vol 4 (1) ◽  
pp. 25-40 ◽  
Author(s):  
Jens Breyer ◽  
Jörg Ackermann ◽  
John McCaskill

Recently, new types of coupled isothermal polynucleotide amplification reactions for the investigation of in vitro evolution have been established that are based on the multi-enzyme 3SR reaction. Microstructured thin-film open bioreactors have been constructed in our laboratory to run these reactions spatially resolved in flow experiments. Artificial DNA/RNA chemistries close to the in vitro biochemistry of these systems have been developed, which we have studied in computer simulations in configurable hardware (NGEN). These artificial chemistries are described on the level of individual polynucleotide molecules, each with a defined sequence, and their complexes. The key feature of spatial pattern formation provides a weak stabilization of cooperative catalytic properties of the evolving molecules. Of great interest is the step to include extended self-assembly processes of flexible structures—allowing the additional stabilization of cooperation through semipermeable, flexible, self-organizing membrane boundaries. We show how programmable matter simulations of experimentally relevant molecular in vitro evolution can be extended to include the influence of self-assembling flexible membranes.


2017 ◽  
Vol 8 (1) ◽  
Author(s):  
Matija Lovrak ◽  
Wouter E. J. Hendriksen ◽  
Chandan Maity ◽  
Serhii Mytnyk ◽  
Volkert van Steijn ◽  
...  

Abstract Self-assembly provides access to a variety of molecular materials, yet spatial control over structure formation remains difficult to achieve. Here we show how reaction–diffusion (RD) can be coupled to a molecular self-assembly process to generate macroscopic free-standing objects with control over shape, size, and functionality. In RD, two or more reactants diffuse from different positions to give rise to spatially defined structures on reaction. We demonstrate that RD can be used to locally control formation and self-assembly of hydrazone molecular gelators from their non-assembling precursors, leading to soft, free-standing hydrogel objects with sizes ranging from several hundred micrometres up to centimeters. Different chemical functionalities and gradients can easily be integrated in the hydrogel objects by using different reactants. Our methodology, together with the vast range of organic reactions and self-assembling building blocks, provides a general approach towards the programmed fabrication of soft microscale objects with controlled functionality and shape.


2019 ◽  
pp. 326-350
Author(s):  
Troy Shinbrot

Effects of combining reaction with diffusion are examined, and the resulting self-assembly of ordered patterns is overviewed. Turing patterns and limit cycle oscillations are shown to result from these considerations, and future avenues for research into these topics are briefly discussed. Additional topics include reaction-diffusion equations, and limit cycles wave solution, and the limit cycle.


2021 ◽  
Author(s):  
Bhavya Mishra ◽  
Margaret E. Johnson

AbstractSelf-assembly is often studied in a three-dimensional (3D) solution, but a significant fraction of binding events involve proteins that can reversibly bind and diffuse along a two-dimensional (2D) surface. In a recent study, we quantified how proteins can exploit the reduced dimension of the membrane to trigger complex formation. Here, we derive a single expression for the characteristic timescale of this multi-step assembly process, where the change in dimensionality renders rates and concentrations effectively time-dependent. We find that proteins can accelerate complex formation due to an increase in relative concentration, driving more frequent collisions which often wins out over slow-downs due to diffusion. Our model contains two protein populations that associate with one another and use a distinct site to bind membrane lipids, creating a complex reaction network. However, by identifying two major rate-limiting pathways to reach an equilibrium steady-state, we derive an accurate approximation for the mean first passage time when lipids are in abundant supply. Our theory highlights how the ‘sticking rate’, or effective adsorption coefficient of the membrane is central in controlling timescales. We also derive a corrected localization rate to quantify how the geometry of the system and diffusion can reduce rates of localization. We validate and test our results using kinetic and reaction-diffusion simulations. Our results establish how the speed of key assembly steps can shift by orders-of-magnitude when membrane localization is possible, which is critical to understanding mechanisms used in cells.


2019 ◽  
Author(s):  
Matthew J. Varga ◽  
Spencer Loggia ◽  
Yiben Fu ◽  
Osman N Yogurtcu ◽  
Margaret E. Johnson

AbstractCurrently, a significant barrier to building predictive models of cell-based self-assembly processes is that molecular models cannot capture minutes-long cellular dynamics that couple distinct components with active processes, while reaction-diffusion models lack sufficient detail for capturing assembly structures. Here we introduce the Non-Equilibrium Reaction-Diffusion Self-assembly Simulator (NERDSS), which addresses this gap by integrating a structure-resolved reaction-diffusion algorithm with rule-based model construction. By representing proteins as rigid, multi-site molecules that adopt well-defined orientations upon binding, NERDSS simulates formation of large reversible structures with sites that can be acted on by reaction rules. We show how NERDSS allows for directly comparing and optimizing models of multi-component assembly against time-dependent experimental data. Applying NERDSS to assembly steps in clathrin-mediated endocytosis, we capture how the formation of clathrin caged structures can be driven by modulating the strength of clathrin-clathrin interactions, by adding cooperativity, or by localizing clathrin to the membrane. NERDSS further predicts how clathrin lattice disassembly can be driven by enzymes that irreversibly change lipid populations on the membrane. By modeling viral lattice assembly and recapitulating oscillations in protein expression levels for a circadian clock model, we illustrate the wide usability and adaptability of NERDSS. NERDSS simulates user-defined assembly models that were previously inaccessible to existing software tools, with broad applications to predicting self-assembly in vivo and designing high-yield assemblies in vitro.


2015 ◽  
Vol 92 (3) ◽  
Author(s):  
Christoph A. Haselwandter ◽  
Mehran Kardar ◽  
Antoine Triller ◽  
Rava Azeredo da Silveira

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