Search

The endoplasmic reticulum (ER) in live cells is a highly mobile network whose structure dynamically changes on a number of timescales. The role of such drastic changes in any system is unclear, although there are correlations with ER function. A better understanding of the fundamental biophysical constraints on the system will allow biologists to determine the effects of molecular factors on ER dynamics. Previous studies have identified potential static elements that the ER may remodel around. Here, we use these structural elements to assess biophysical principles behind the network dynamics. By analyzing imaging data of tobacco leaf epidermal cells under two different conditions, i.e., native state (control) and latrunculin B (treated), we show that the geometric structure and dynamics of ER networks can be understood in terms of minimal networks. Our results show that the ER network is well modeled as a locally minimal-length network between the static elements that potentially anchor the ER to the cell cortex over longer timescales; this network is perturbed by a mixture of random and deterministic forces. The network need not have globally minimum length; we observe cases where the local topology may change dynamically between different Euclidean Steiner network topologies. The networks in the treated cells are easier to quantify, because they are less dynamic (the treatment suppresses actin dynamics), but the same general features are found in control cells. Using a Langevin approach, we model the dynamics of the nonpersistent nodes and use this to show that the images can be used to estimate both local viscoelastic behavior of the cytoplasm and filament tension in the ER network. This means we can explain several aspects of the ER geometry in terms of biophysical principles.

Extracting physical parameters from MD simulations of lipid membranes is crucial when comparing simulations with experimental observations. Unfortunately, the analysis of the trajectories may be problematic because of the size of the generated files and/or because extracting relevant data from atom coordinates stored in the trajectories may not be trivial.In order to overcome these difficulties, FATSLiM (“Fast Analysis Toolbox for Simulations of Lipid Membranes” - https://fatslim.github.io/) was developed. The main goal of this free open source software is to provide a fast and robust analytical tool to extract physical parameters such as bilayer thickness, area per lipid, lateral diffusion or lipid order parameter from molecular dynamics simulations of lipid membranes.FATSLiM is computationally efficient as it scales linearly with the number of lipids and is parallelized. As an illustration, on a 8-core machine, extracting both the thickness and the area per lipid from a 100-frame trajectory of a MD simulation of 12800 coarse-grained lipids takes about 15 seconds (35 seconds for All-Atom lipids) while needing 56 MB of memory (155 MB for All-Atom lipids). APL@voro, one the fastest tools, gives comparable results in 28 seconds (3.5 min for All-Atom lipids) but requires almost 1.6 GB of memory (11 GB for All-Atom lipids) and is not able to work with non-planar bilayers.Indeed, as opposed to other softwares, FATSLiM does not rely on any assumption regarding the bilayer planarity. In contrast, It calculates the local topology so it can then perform analysis on a planar membrane, an ondulating bilayer, or even a vesicle with the same accuracy and reliability. As such, it is perfectly suited to investigate the effect of a protein (on any molecule) on the properties/morphology of a membrane.