DeepContact: High-throughput quantification of membrane contact sites based on electron microscopy imaging.

The Journal of Cell Biology Pub Date : 2022-09-05 Epub Date: 2022-08-05 DOI:10.1083/jcb.202106190
Liqing Liu, Shuxin Yang, Yang Liu, Xixia Li, Junjie Hu, Li Xiao, Tao Xu
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引用次数: 4

Abstract

Membrane contact site (MCS)-mediated organelle interactions play essential roles in the cell. Quantitative analysis of MCSs reveals vital clues for cellular responses under various physiological and pathological conditions. However, an efficient tool is lacking. Here, we developed DeepContact, a deep-learning protocol for optimizing organelle segmentation and contact analysis based on label-free EM. DeepContact presents high efficiency and flexibility in interactive visualizations, accommodating new morphologies of organelles and recognizing contacts in versatile width ranges, which enables statistical analysis of various types of MCSs in multiple systems. DeepContact profiled previously unidentified coordinative rearrangements of MCS types in cultured cells with combined nutritional conditions. DeepContact also unveiled a subtle wave of ER-mitochondrial entanglement in Sertoli cells during the seminiferous epithelial cycle, indicating its potential in bridging MCS dynamics to physiological and pathological processes.

Abstract Image

Abstract Image

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深度接触:基于电子显微镜成像的膜接触部位的高通量定量。
膜接触位点(MCS)介导的细胞器相互作用在细胞中起着重要的作用。MCSs的定量分析揭示了在各种生理和病理条件下细胞反应的重要线索。然而,缺乏一种有效的工具。在这里,我们开发了DeepContact,一种深度学习协议,用于优化基于无标签EM的细胞器分割和接触分析。DeepContact在交互式可视化中表现出高效率和灵活性,适应细胞器的新形态并识别多种宽度范围的接触,从而能够对多个系统中各种类型的mcs进行统计分析。DeepContact分析了在联合营养条件下培养细胞中先前未确定的MCS类型的协调重排。DeepContact还揭示了在授精上皮周期中,Sertoli细胞中er -线粒体缠结的微妙波动,表明其在连接MCS动力学与生理和病理过程中的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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