Cryo-electron tomography for the structural study of mitochondrial translation

Englmeier, Robert; Förster, Friedrich

doi:10.1016/j.tice.2018.08.009

Cited by 9 publications

(6 citation statements)

References 85 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…[34][35][36] The dynamics can be seen in sub-nanometer resolution with cryoelectron tomography. 32,33 There may be unique orientations and distribution in different types of cells, and a close association with microtubules in some regions. 37,38 In sites where the energy requirements are relatively high, mitochondria may appear more static and provide ATP directly on-site.…”

Section: Mitochondrial Ultrastructurementioning

confidence: 99%

See 1 more Smart Citation

Mitochondrial Dynamics during Development

Maheshwari¹,

He²,

Tronstad³

2023

Newborn

View full text Add to dashboard Cite

Mitochondria are dynamic membrane-bound organelles in eukaryotic cells. These are important for the generation of chemical energy needed to power various cellular functions and also support metabolic, energetic, and epigenetic regulation in various cells. These organelles are also important for communication with the nucleus and other cellular structures, to maintain developmental sequences and somatic homeostasis, and for cellular adaptation to stress. Increasing information shows mitochondrial defects as an important cause of inherited disorders in different organ systems. In this article, we provide an extensive review of ontogeny, ultrastructural morphology, biogenesis, functional dynamics, important clinical manifestations of mitochondrial dysfunction, and possibilities for clinical intervention. We present information from our own clinical and laboratory research in conjunction with information collected from an extensive search in the databases PubMed, EMBASE, and Scopus.

show abstract

Section: Mitochondrial Ultrastructurementioning

confidence: 99%

“…1C ) with active division and fusion. 32 , 33 The mitochondrial content and morphology are altered by cellular stress. In living cells, the net mitochondrial content or the mitochondrial mass depends on the balance between mitochondrial biogenesis and degradation.…”

Section: Introductionmentioning

confidence: 99%

Mitochondrial Dynamics during Development

Maheshwari¹,

He²,

Tronstad³

2023

Newborn

View full text Add to dashboard Cite

show abstract

“…This technique is versatile, allowing for the examination of a wide array of macromolecular complexes in vitro [7] and in situ [8], including amyloid filaments [9][10][11][12][13][14] and enveloped viruses such as SARS-CoV-2 [15]. CryoET can also probe the structure of other clinically-relevant samples ranging from individual organelles [16,17] and cells [18,19] to complex tissue sections [20][21][22][23][24]. Insights from cryoET data analysis can facilitate understanding dynamic molecular processes such as viral infections [25][26][27][28][29][30], enable pathology diagnosis [31,32], and reveal the impacts of potential therapeutic interventions [19], among other biomedical applications.…”

Section: Introductionmentioning

confidence: 99%

Missing Wedge Completion via Unsupervised Learning with Coordinate Networks

Van Veen,

Galaz-Montoya,

Shen

et al. 2024

Preprint

View full text Add to dashboard Cite

Cryogenic electron tomography (cryoET) is a powerful tool in structural biology, enabling detailed 3D imaging of biological specimens at a resolution of nanometers. Despite its potential, cryoET faces challenges such as the missing wedge problem, which limits reconstruction quality due to incomplete data collection angles. Recently, supervised deep learning methods with convolutional neural networks (CNNs) have considerably addressed this issue; however, their pretraining renders them susceptible to inaccuracies and artifacts, particularly when representative training data is scarce. To overcome these limitations, we introduce a proof-of-concept unsupervised learning approach using coordinate networks (CNs) that optimizes network weights directly against input projections. This eliminates the need for pretraining, reducing reconstruction runtime by 3−20×compared to supervised methods. Our results from benchmarksin silicoshow improved shape completion and reduction of missing wedge artifacts, assessed through several voxel-based image quality metrics in real space and a novel directional Fourier Shell Correlation (FSC) metric. Our study illuminates benefits and considerations of both supervised and unsupervised approaches, guiding the development of improved reconstruction strategies.

show abstract

“…Cryoelectron tomography (cryoET) has obvious relevance for such a task [15]. However, since we basically have only single specimens in cryoET (setting aside the method of subtomogram averaging [15] that still requires many identical molecules), we cannot perform averaging to improve signal-to-noise ratio (SNR) and the resolution remains to be ≈ 3 − 5 nm [16]. This value falls just short of about ≈ 2 − 3 nm that is needed for identification of protein molecules in the tomogram [17].…”

Section: Introductionmentioning

confidence: 99%