arXiv subjects

Martijn Wehrens

Publications and source records attributed to Martijn Wehrens.

3 recordsLinked to original sources

arXiv2022

Defect dynamics in growing bacterial colonies

Colonies of rod-shaped bacteria constitute a system of colloidal active matter with nematic properties. As a single initial bacterium multiplies through repeated divisions, the resulting colony quickly loses long-range orientational order, but retains locally ordered domains. At the boundaries of these domains, topological defects emerge, which move around randomly as the colony grows. In both experiments and simulations, we find that these defects are created at a rate that corresponds to the exponential growth of the colony, resulting in a stable defect density. Both this defect density and the colony's correlation length are regulated by the aspect ratio of the rod-shaped particles. Moreover, we find that the defect dynamics are well described by a Gamma distribution, which is due to repeated divisions and subsequent re-orientations of the bacteria.

physics.bio-ph↗

arXiv2017

eGFRD in all dimensions

Biochemical reactions typically occur at low copy numbers, but at once in crowded and diverse environments. Space and stochasticity therefore play an essential role in biochemical networks. Spatial-stochastic simulations have become a prominent tool for understanding how stochasticity at the microscopic level influences the macroscopic behavior of such systems. However, while particle-based models guarantee the level of detail necessary to accurately describe the microscopic dynamics at very low copy numbers, the algorithms used to simulate them oftentimes imply trade-offs between computational efficiency and accuracy. eGFRD (enhanced Green's Function Reaction Dynamics) is an exact algorithm that evades such trade-offs by partitioning the N-particle system into M<N analytically tractable one- and two-particle systems; the analytical solutions (Green's functions) then are used to implement an event-driven particle-based scheme that allows particles to make large jumps in time and space while retaining access to their state variables at any moment. Here we present "eGFRD2", a new eGFRD version that implements the principle of eGFRD in all dimensions, enabling efficient simulation of biochemical reaction-diffusion processes in the 3D cytoplasm, on 2D planes representing membranes, and on 1D elongated cylinders representative of, e.g., cytoskeletal tracks or DNA; in 1D, it also incorporates convective motion used to model active transport. We find that, for low particle densities, eGFRD2 is up to 3 orders of magnitude faster than optimized Brownian Dynamics. We exemplify the capabilities of eGFRD2 by simulating an idealized model of Pom1 gradient formation, which involves 3D diffusion, active transport on microtubules, and autophosphorylation on the membrane, confirming recent results on this system and demonstrating that it can efficiently operate under genuinely stochastic conditions.

q-bio.MN↗

arXiv2014

Positive feedback can lead to dynamic nanometer-scale clustering on cell membranes

Clustering of molecules on biological membranes is a widely observed phenomenon. In some cases, such as the clustering of Ras proteins on the membranes of mammalian cells, proper cell signaling is critically dependent on the maintenance of these clusters. Yet, the mechanism by which clusters form and are maintained in these systems remains unclear. Recently, it has been discovered that activated Ras promotes further Ras activation. Here we show using particle-based simulation that this positive feedback is sufficient to produce persistent clusters of active Ras molecules at the nanometer scale via a dynamic nucleation mechanism. Furthermore, we find that our cluster statistics are consistent with experimental observations of the Ras system. Interestingly, we show that our model does not support a Turing regime of macroscopic reaction-diffusion patterning, and therefore that the clustering we observe is a purely stochastic effect, arising from the coupling of positive feedback with the discrete nature of individual molecules. These results underscore the importance of stochastic and dynamic properties of reaction diffusion systems for biological behavior.

q-bio.MN↗