近日，美国普林斯顿大学教授Ellen D. Zhong课题组报道了CryoDRGN-ET，用于可视化细胞内动态生物分子的深度重构生成网络。2024年7月18日出版的《自然—方法学》发表了这项成果。

课题组研究人员引入了cryoDRGN-ET用于cryo-ET亚层图的异质重建。CryoDRGN-ET直接从亚层析成像倾斜序列图像中，学习三维密度图的深度生成模型，可以捕获不同组成和构象的状态。研究人员通过原位恢复肺炎支原体核糖体的已知翻译状态，来验证这种方法。然后，研究小组对低温聚焦离子束碾磨的酿酒酵母细胞进行低温cryo-ET。

CryoDRGN-ET揭示了酿酒酵母核糖体在翻译过程中的结构图谱，并捕获了细胞内脂肪酸合成酶复合物的连续运动。该方法在cryoDRGN软件中是公开可用的。

据悉，低温电子断层扫描技术(cryo-ET)的进步，为观察细胞环境中动态大分子的结构提供了新的机会。虽然cryo-ET可以在分子分辨率上揭示结构，但图像处理算法仍然是解决生物分子结构原位异质性的瓶颈。

附：英文原文

Title: CryoDRGN-ET: deep reconstructing generative networks for visualizing dynamic biomolecules inside cells

Author: Rangan, Ramya, Feathers, Ryan, Khavnekar, Sagar, Lerer, Adam, Johnston, Jake D., Kelley, Ron, Obr, Martin, Kotecha, Abhay, Zhong, Ellen D.

Issue&Volume: 2024-07-18

Abstract: Advances in cryo-electron tomography (cryo-ET) have produced new opportunities to visualize the structures of dynamic macromolecules in native cellular environments. While cryo-ET can reveal structures at molecular resolution, image processing algorithms remain a bottleneck in resolving the heterogeneity of biomolecular structures in situ. Here, we introduce cryoDRGN-ET for heterogeneous reconstruction of cryo-ET subtomograms. CryoDRGN-ET learns a deep generative model of three-dimensional density maps directly from subtomogram tilt-series images and can capture states diverse in both composition and conformation. We validate this approach by recovering the known translational states in Mycoplasma pneumoniae ribosomes in situ. We then perform cryo-ET on cryogenic focused ion beam–milled Saccharomyces cerevisiae cells. CryoDRGN-ET reveals the structural landscape of S. cerevisiae ribosomes during translation and captures continuous motions of fatty acid synthase complexes inside cells. This method is openly available in the cryoDRGN software.

DOI: 10.1038/s41592-024-02340-4

Source: https://www.nature.com/articles/s41592-024-02340-4