Studying membrane modulation mechanisms by electron cryo-tomography

Zabeo, Davide; Davies, Karen M.

doi:10.1016/j.sbi.2022.102464

Cited by 8 publications

(2 citation statements)

References 56 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This approach represents a remarkable breakthrough that unveils biological phenomena that could have been overlooked as a result of the limited scope of traditional structural methods, which only present a partial view of biological processes. In other groundbreaking work, cryo-ET formed an essential part of in-situ structural studies of membrane proteins (Dunstone and de Marco, 2017;Zabeo and Davies, 2022). Rapisarda et al (2019) successfully combined cryo-EM and cryo-ET to identify the type VI secretion system (T6SS) present in bacterial cell membranes.…”

Section: Structural Determination Of Macromolecules By Using Cryo-etmentioning

confidence: 99%

Cryo-electron tomography: a triumphant breakthrough in structural biology

Kim,

An,

Jung

2023

BIO DESIGN

View full text Add to dashboard Cite

Cryo-electron microscopy (Cryo-EM) has been offering impressive insights into the structures of macromolecules in the field of structural biology as a result of recent advancements in hardware and software technologies. This breakthrough has greatly aided our understanding of the cellular mechanisms of proteins and has triggered the dawn of an unprecedented golden age in structural biology. However, the technique still has inherent limitations owing to the dynamic tendency and tangled interactions of biomolecules. Attempts to overcome these limitations have led to the emergence of cryo-electron tomography (Cryo-ET) as a powerful technique in the field of structural biology, allowing for the three-dimensional visualization of the native conformation of biological specimens. This promising electron microscopy method has revolutionized our grasp of complex structures and their dynamic interactions, thereby providing unprecedented insights into the organization and function of macromolecular complexes within their native cellular environments. In this paper, we review state-of-the-art cryo-ET workflows, provide examples of biological applications, and discuss the fundamental necessity of boosting the potential applications of cryo-ET.

show abstract

Section: Structural Determination Of Macromolecules By Using Cryo-etmentioning

confidence: 99%

Cryo-electron tomography: a triumphant breakthrough in structural biology

Kim,

An,

Jung

2023

BIO DESIGN

View full text Add to dashboard Cite

show abstract

“…Macromolecular complexes can be identified in the tomogram, their spatial arrangement can be analyzed in the native environment, and their structure can potentially be determined to near-atomic resolution [1,2,3,4]. Cryo-ET has also proven particularly useful in tracing the abundant cellular membranes in 3D [7,8]. Membrane segmentations can be used to analyze a variety of membrane properties such as shape, curvature, or volume to understand morphological changes and biological function.…”

Section: Introductionmentioning

confidence: 99%

ColabSeg: An interactive tool for editing, processing, and visualizing membrane segmentations from cryo-ET data

Siggel

Jensen²,

Mahamid³

et al. 2023

Preprint

View full text Add to dashboard Cite

Cellular cryo-electron tomography (cryo-ET) has emerged as a key method to unravel the spatial and structural complexity of cells in their near-native state at unprecedented molecular resolution. To enable quantitative analysis of the complex shapes and morphologies of lipid membranes, the noisy three-dimensional (3D) volumes must be segmented. Despite recent advances, this task often requires considerable user intervention to curate the resulting segmentations. Here, we present ColabSeg, a Python-based tool for processing, visualizing, cleaning, and fitting membrane segmentations from cryo-ET data for downstream analysis. ColabSeg makes many well-established algorithms for point-cloud processing easily available to the broad community of structural biologists for applications in cryo-ET through its graphical user interface (GUI). We demonstrate the usefulness of the tool with a range of use cases and biological examples. Finally, for a large Mycoplasma pneumoniae dataset of 50 tomograms, we show how ColabSeg enables high-throughput membrane segmentation, which can be used as valuable training dataset for fully automated convolutional neural network (CNN)-based segmentation.

show abstract