Dataset Information

De Novo Structural Pattern Mining in Cellular Electron Cryotomograms.

ABSTRACT: Electron cryotomography enables 3D visualization of cells in a near-native state at molecular resolution. The produced cellular tomograms contain detailed information about a plethora of macromolecular complexes, their structures, abundances, and specific spatial locations in the cell. However, extracting this information in a systematic way is very challenging, and current methods usually rely on individual templates of known structures. Here, we propose a framework called "Multi-Pattern Pursuit" for de novo discovery of different complexes from highly heterogeneous sets of particles extracted from entire cellular tomograms without using information of known structures. These initially detected structures can then serve as input for more targeted refinement efforts. Our tests on simulated and experimental tomograms show that our automated method is a promising tool for supporting large-scale template-free visual proteomics analysis.

SUBMITTER: Xu M

PROVIDER: S-EPMC7542605 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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De Novo Structural Pattern Mining in Cellular Electron Cryotomograms.

Xu Min M Singla Jitin J Tocheva Elitza I EI Chang Yi-Wei YW Stevens Raymond C RC Jensen Grant J GJ Alber Frank F

Structure (London, England : 1993) 20190207 4

Electron cryotomography enables 3D visualization of cells in a near-native state at molecular resolution. The produced cellular tomograms contain detailed information about a plethora of macromolecular complexes, their structures, abundances, and specific spatial locations in the cell. However, extracting this information in a systematic way is very challenging, and current methods usually rely on individual templates of known structures. Here, we propose a framework called "Multi-Pattern Pursui ...[more]

PMID: 30744995

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Project description:Cellular senescence is characterized by replication arrest in response to stress stimuli. Senescent cells accumulate in aging tissues and can trigger organ-specific and possibly systemic dysfunction. Although senescent cell populations are heterogeneous, a key feature is that they exhibit epigenetic changes. Epigenetic changes such as loss of repressive constitutive heterochromatin could lead to subsequent LINE-1 derepression, a phenomenon often described in the context of senescence or somatic evolution. LINE-1 elements decode the retroposition machinery and reverse transcription generates cDNA from autonomous and non-autonomous TEs that can potentially reintegrate into genomes and cause structural variants. Another feature of cellular senescence is mitochondrial dysfunction caused by mitochondrial damage. In combination with impaired mitophagy, which is characteristic of senescent cells, this could lead to cytosolic mtDNA accumulation and, as a genomic consequence, integrations of mtDNA into nuclear DNA (nDNA), resulting in mitochondrial pseudogenes called numts. Thus, both phenomena could cause structural variants in aging genomes that go beyond epigenetic changes. We therefore compared proliferating and senescent IMR-90 cells in terms of somatic de novo numts and integrations of a non-autonomous composite retrotransposons - the so-called SVA elements-that hijack the retropositional machinery of LINE-1. We applied a subtractive and kinetic enrichment technique using proliferating cell DNA as a driver and senescent genomes as a tester for the detection of nuclear flanks of de novo SVA integrations. Coupled with deep sequencing we obtained a genomic readout for SVA retrotransposition possibly linked to cellular senescence in the IMR-90 model. Furthermore, we compared the genomes of proliferative and senescent IMR-90 cells by deep sequencing or after enrichment of nuclear DNA using AluScan technology. A total of 1,695 de novo SVA integrations were detected in senescent IMR-90 cells, of which 333 were unique. Moreover, we identified a total of 81 de novo numts with perfect identity to both mtDNA and nuclear hg38 flanks. In summary, we present evidence for possible age-dependent structural genomic changes by paralogization that go beyond epigenetic modifications. We hypothesize, that the structural variants we observe potentially impact processes associated with replicative aging of IMR-90 cells.

Dataset Information

De Novo Structural Pattern Mining in Cellular Electron Cryotomograms.

Publications

De Novo Structural Pattern Mining in Cellular Electron Cryotomograms.

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