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A collection of yeast cellular electron cryotomography data.
GigaScience ( IF 11.8 ) Pub Date : 2019-06-01 , DOI: 10.1093/gigascience/giz077
Lu Gan 1 , Cai Tong Ng 1 , Chen Chen 1 , Shujun Cai 1
Affiliation  

BACKGROUND Cells are powered by a large set of macromolecular complexes, which work together in a crowded environment. The in situ mechanisms of these complexes are unclear because their 3D distribution, organization, and interactions are largely unknown. Electron cryotomography (cryo-ET) can address these knowledge gaps because it produces cryotomograms-3D images that reveal biological structure at ∼4-nm resolution. Cryo-ET uses no fixation, dehydration, staining, or plastic embedment, so cellular features are visualized in a life-like, frozen-hydrated state. To study chromatin and mitotic machinery in situ, we subjected yeast cells to genetic and chemical perturbations, cryosectioned them, and then imaged the cells by cryo-ET. FINDINGS Here we share >1,000 cryo-ET raw datasets of cryosectioned budding yeast Saccharomyces cerevisiaecollected as part of previously published studies. These data will be valuable to cell biologists who are interested in the nanoscale organization of yeasts and of eukaryotic cells in general. All the unpublished tilt series and a subset of corresponding cryotomograms have been deposited in the EMPIAR resource for the community to use freely. To improve tilt series discoverability, we have uploaded metadata and preliminary notes to publicly accessible Google Sheets, EMPIAR, and GigaDB. CONCLUSIONS Cellular cryo-ET data can be mined to obtain new cell-biological, structural, and 3D statistical insights in situ. These data contain structures not visible in traditional electron-microscopy data. Template matching and subtomogram averaging of known macromolecular complexes can reveal their 3D distributions and low-resolution structures. Furthermore, these data can serve as testbeds for high-throughput image-analysis pipelines, as training sets for feature-recognition software, for feasibility analysis when planning new structural-cell-biology projects, and as practice data for students.

中文翻译:

酵母细胞电子冷冻断层扫描数据的集合。

背景技术细胞由大量大分子复合物提供动力,所述大分子复合物在拥挤的环境中一起工作。这些复合物的原位机理尚不清楚,因为它们的3D分布,组织和相互作用在很大程度上是未知的。电子体层摄影术(cryo-ET)可以解决这些知识方面的空白,因为它可以产生3D图像的体层摄影术3D图像,从而揭示生物结构的分辨率约为4 nm。Cryo-ET不使用固定剂,脱水剂,染色剂或塑料包埋物,因此细胞特征以逼真的冷冻水合状态显示。为了就地研究染色质和有丝分裂机制,我们对酵母细胞进行了遗传和化学扰动,对其进行了冷冻切片,然后通过cryo-ET对细胞进行了成像。结果在这里,我们分享> 1,作为先前发表的研究的一部分,收集了冷冻切片出芽的酿酒酵母Saccharomyces cerevisiae的000个cryo-ET原始数据集。这些数据对于通常对酵母和真核细胞的纳米级组织感兴趣的细胞生物学家来说是有价值的。所有未发布的倾斜序列和相应的冷冻描记图的子集都已存储在EMPIAR资源中,供社区自由使用。为了提高倾斜序列的可发现性,我们已将元数据和初步注释上载到可公开访问的Google表格,EMPIAR和GigaDB。结论可以提取细胞cryo-ET数据,以获得原位的新的细胞生物学,结构和3D统计见解。这些数据包含在传统电子显微镜数据中不可见的结构。已知高分子复合物的模板匹配和子图平均可以揭示其3D分布和低分辨率结构。此外,这些数据可以用作高通量图像分析管道的试验台,特征识别软件的培训集,在计划新的结构细胞生物学项目时的可行性分析以及学生的实践数据。
更新日期:2019-06-27
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