Computational toolbox for ultrastructural quantitative analysis of filament networks in cryo-ET data

Dimchev, Georgi; Amiri, Behnam; Fäßler, Florian; Falcke, Martin; Schur, F.K.M.

doi:10.1016/j.jsb.2021.107808

Cited by 25 publications

(19 citation statements)

References 47 publications

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“…Binned tomograms were filtered using a SIRT-like (simultaneous iterative reconstruction technique) filter with two iterations in IMOD and were imported in Amira where the RNA tracing was performed using its filament tracing functionality, a functionality that has been shown to allow quantification and structural analysis of filaments ( Rigort et al, 2012 ; Dimchev et al, 2021 ). Single spherules were cropped from the imported tomograms, and a non-local means filter was applied to the cropped subtomograms with parameters selected to yield a clear contrast between the filament contained in the spherules and the background.…”

Section: Methodsmentioning

confidence: 99%

Architecture of the chikungunya virus replication organelle

Laurent

Kumar

Liese

et al. 2022

eLife

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Alphaviruses are mosquito-borne viruses that cause serious disease in humans and other mammals. Along with its mosquito vector, the Alphavirus chikungunya virus (CHIKV) has spread explosively in the last 20 years, and there is no approved treatment for chikungunya fever. On the plasma membrane of the infected cell, CHIKV generates dedicated organelles for viral RNA replication, so-called spherules. Whereas structures exist for several viral proteins that make up the spherule, the architecture of the full organelle is unknown. Here, we use cryo-electron tomography to image CHIKV spherules in their cellular context. This reveals that the viral protein nsP1 serves as a base for the assembly of a larger protein complex at the neck of the membrane bud. Biochemical assays show that the viral helicase-protease nsP2, while having no membrane affinity on its own, is recruited to membranes by nsP1. The tomograms further reveal that full-sized spherules contain a single copy of the viral genome in double-stranded form. Finally, we present a mathematical model that explains the membrane remodeling of the spherule in terms of the pressure exerted on the membrane by the polymerizing RNA, which provides a good agreement with the experimental data. The energy released by RNA polymerization is found to be sufficient to remodel the membrane to the characteristic spherule shape.

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Section: Methodsmentioning

confidence: 99%

Architecture of the chikungunya virus replication organelle

Laurent

Kumar

Liese

et al. 2022

eLife

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“…Quantitative characterization of ice thickness, 3D shape, and particle distribution has also helped assessing issues (e.g., air-water interface) when performing SPA tomography ( Noble et al, 2018a ; Noble et al, 2018b ). Furthermore, a quantitative analysis of cytoskeletal elements has provided insights into the macromolecular networks they form and their role in motility, trafficking, and cell cycle ( Rigort et al, 2012 ; Xu et al, 2015 ; Anderson et al, 2017 ; Dimchev et al, 2021 ). Membrane parameterization has been also essential to achieve a quantitative ultrastructural analysis of subcellular features ( Salfer et al, 2020 ; Barad et al, 2022 ).…”

Section: Quantitative Cryo-electron Tomographymentioning

confidence: 99%

“…Membrane parameterization has been also essential to achieve a quantitative ultrastructural analysis of subcellular features ( Salfer et al, 2020 ; Barad et al, 2022 ). The consolidation of such analyses into integrative computational toolboxes highly facilitates the quantitative ultrastructural analysis of cryo-ET data in a time-efficient manner ( Dimchev et al, 2021 ; Barad et al, 2022 ), and appears as the fittest modality for future quantitative cryo-ET research.…”

Section: Quantitative Cryo-electron Tomographymentioning

confidence: 99%

Quantitative Cryo-Electron Tomography

Navarro

2022

Front. Mol. Biosci.

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The three-dimensional organization of biomolecules important for the functioning of all living systems can be determined by cryo-electron tomography imaging under native biological contexts. Cryo-electron tomography is continually expanding and evolving, and the development of new methods that use the latest technology for sample thinning is enabling the visualization of ever larger and more complex biological systems, allowing imaging across scales. Quantitative cryo-electron tomography possesses the capability of visualizing the impact of molecular and environmental perturbations in subcellular structure and function to understand fundamental biological processes. This review provides an overview of current hardware and software developments that allow quantitative cryo-electron tomography studies and their limitations and how overcoming them may allow us to unleash the full power of cryo-electron tomography.

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“…In recent years, several computational groups have focused on automatically detecting and segmenting biomolecular shapes in such tomograms by using techniques such as deep learning [ 2 , 3 , 4 ]. Furthermore, a number of toolboxes have been developed for tomography analysis [ 5 , 6 , 7 ]. These efforts have mainly been aimed at improving the signal-to-noise ratio by averaging multiple particles in subtomogram averaging [ 8 ]; however, the averaging approach is unsuitable for long cytoskeletal filaments that exhibit variable shapes.…”

Section: Introductionmentioning

confidence: 99%

Spaghetti Tracer: A Framework for Tracing Semiregular Filamentous Densities in 3D Tomograms

Sazzed

Scheible

et al. 2022

Biomolecules

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Within cells, cytoskeletal filaments are often arranged into loosely aligned bundles. These fibrous bundles are dense enough to exhibit a certain regularity and mean direction, however, their packing is not sufficient to impose a symmetry between—or specific shape on—individual filaments. This intermediate regularity is computationally difficult to handle because individual filaments have a certain directional freedom, however, the filament densities are not well segmented from each other (especially in the presence of noise, such as in cryo-electron tomography). In this paper, we develop a dynamic programming-based framework, Spaghetti Tracer, to characterizing the structural arrangement of filaments in the challenging 3D maps of subcellular components. Assuming that the tomogram can be rotated such that the filaments are oriented in a mean direction, the proposed framework first identifies local seed points for candidate filament segments, which are then grown from the seeds using a dynamic programming algorithm. We validate various algorithmic variations of our framework on simulated tomograms that closely mimic the noise and appearance of experimental maps. As we know the ground truth in the simulated tomograms, the statistical analysis consisting of precision, recall, and F1 scores allows us to optimize the performance of this new approach. We find that a bipyramidal accumulation scheme for path density is superior to straight-line accumulation. In addition, the multiplication of forward and backward path densities provides for an efficient filter that lifts the filament density above the noise level. Resulting from our tests is a robust method that can be expected to perform well (F1 scores 0.86–0.95) under experimental noise conditions.

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Computational toolbox for ultrastructural quantitative analysis of filament networks in cryo-ET data

Cited by 25 publications

References 47 publications

Architecture of the chikungunya virus replication organelle

Architecture of the chikungunya virus replication organelle

Quantitative Cryo-Electron Tomography

Spaghetti Tracer: A Framework for Tracing Semiregular Filamentous Densities in 3D Tomograms

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