Capturing actin assemblies in cells using in situ cryo-electron tomography

Simulating the Cellular Context in Synthetic Datasets for Cryo-Electron Tomography

Cryo-electron tomography (cryo-ET) allows to visualize the cellular context at macromolecular level. To date, the impossibility of obtaining a reliable ground truth is limiting the application of deep learning-based image processing algorithms in this field. As a consequence, there is a growing demand of realistic synthetic datasets for training deep learning algorithms. In addition, besides assisting the acquisition and interpretation of experimental data, synthetic tomograms are used as reference models for cellular organization analysis from cellular tomograms. Current simulators in cryo-ET focus on reproducing distortions from image acquisition and tomogram reconstruction, however, they can not generate many of the low order features present in cellular tomograms. Here we propose several geometric and organization models to simulate low order cellular structures imaged by cryo-ET. Specifically, clusters of any known cytosolic or membrane-bound macromolecules, membranes with different geometries as well as different filamentous structures such as microtubules or actin-like networks. Moreover, we use parametrizable stochastic models to generate a high diversity of geometries and organizations to simulate representative and generalized datasets, including very crowded environments like those observed in native cells. These models have been implemented in a multiplatform open-source Python package, including scripts to generate cryo-tomograms with adjustable sizes and resolutions. In addition, these scripts provide also distortion-free density maps besides the ground truth in different file formats for efficient access and advanced visualization. We show that such a realistic synthetic dataset can be readily used to train generalizable deep learning algorithms.

The third dimension of the actin cortex

The actin cortex, commonly described as a thin 2-dimensional layer of actin filaments beneath the plasma membrane, is beginning to be recognized as part of a more dynamic and three-dimensional composite material. In this review, we focus on the elements that contribute to the three-dimensional architecture of the actin cortex. We also argue that actin-rich structures such as filopodia and stress fibers can be viewed as specialized integral parts of the 3D actin cortex. This broadens our definition of the cortex, shifting from its simplified characterization as a thin, two-dimensional layer of actin filaments.

Untangling Irregular Actin Cytoskeleton Architectures in Tomograms of the Cell with Struwwel Tracer

In this work, we established, validated, and optimized a novel computational framework for tracing arbitrarily oriented actin filaments in cryo-electron tomography maps. Our approach was designed for highly complex intracellular architectures in which a long-range cytoskeleton network extends throughout the cell bodies and protrusions. The irregular organization of the actin network, as well as cryo-electron-tomography-specific noise, missing wedge artifacts, and map dimensions call for a specialized implementation that is both robust and efficient. Our proposed solution, Struwwel Tracer, accumulates densities along paths of a specific length in various directions, starting from locally determined seed points. The highest-density paths originating from the seed points form short linear candidate filament segments, which are further scrutinized and classified by users via inspection of a novel pruning map, which visualizes the likelihood of being a part of longer filaments. The pruned linear candidate filament segments are then iteratively fused into continuous, longer, and curved filaments based on their relative orientations, gap spacings, and extendibility. When applied to the simulated phantom tomograms of a Dictyostelium discoideum filopodium under experimental conditions, Struwwel Tracer demonstrated high efficacy, with F1-scores ranging from 0.85 to 0.90, depending on the noise level. Furthermore, when applied to a previously untraced experimental tomogram of mouse fibroblast lamellipodia, the filaments predicted by Struwwel Tracer exhibited a good visual agreement with the experimental map. The Struwwel Tracer framework is highly time efficient and can complete the tracing process in just a few minutes. The source code is publicly available with version 3.2 of the free and open-source Situs software package.

Exploring the Role of the Plant Actin Cytoskeleton: From Signaling to Cellular Functions

The plant actin cytoskeleton is characterized by the basic properties of dynamic array, which plays a central role in numerous conserved processes that are required for diverse cellular functions. Here, we focus on how actins and actin-related proteins (ARPs), which represent two classical branches of a greatly diverse superfamily of ATPases, are involved in fundamental functions underlying signal regulation of plant growth and development. Moreover, we review the structure, assembly dynamics, and biological functions of filamentous actin (F-actin) from a molecular perspective. The various accessory proteins known as actin-binding proteins (ABPs) partner with F-actin to finely tune actin dynamics, often in response to various cell signaling pathways. Our understanding of the significance of the actin cytoskeleton in vital cellular activities has been furthered by comparison of conserved functions of actin filaments across different species combined with advanced microscopic techniques and experimental methods. We discuss the current model of the plant actin cytoskeleton, followed by examples of the signaling mechanisms under the supervision of F-actin related to cell morphogenesis, polar growth, and cytoplasmic streaming. Determination of the theoretical basis of how the cytoskeleton works is important in itself and is beneficial to future applications aimed at improving crop biomass and production efficiency.