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显微镜技术的进步揭示了细胞动力学。

Cell dynamics revealed by microscopy advances.

机构信息

Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, Chapel Hill, NC, USA.

Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.

出版信息

Curr Opin Cell Biol. 2024 Oct;90:102418. doi: 10.1016/j.ceb.2024.102418. Epub 2024 Aug 18.

DOI:10.1016/j.ceb.2024.102418
PMID:39159598
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11392612/
Abstract

Cell biology emerges from spatiotemporally coordinated molecular processes. Recent advances in live-cell microscopy, fueled by a surge in optical, molecular, and computational technologies, have enabled dynamic observations from single molecules to whole organisms. Despite technological leaps, there is still an untapped opportunity to fully leverage their capabilities toward biological insight. We highlight how single-molecule imaging has transformed our understanding of biological processes, with a focus on chromatin organization and transcription in the nucleus. We describe how this was enabled by the close integration of new imaging techniques with analysis tools and discuss the challenges to make a comparable impact at larger scales from organelles to organisms. By highlighting recent successful examples, we describe an outlook of ever-increasing data and the need for seamless integration between dataset visualization and quantification to realize the full potential warranted by advances in new imaging technologies.

摘要

细胞生物学源于时空协调的分子过程。近年来,由于光学、分子和计算技术的突飞猛进,活细胞显微镜技术取得了进展,使我们能够从单个分子到整个生物体进行动态观察。尽管技术有了飞跃,但仍有机会充分利用这些技术来深入了解生物学。我们重点介绍了单分子成像如何改变我们对生物过程的理解,特别是细胞核中的染色质组织和转录。我们描述了如何通过将新技术与分析工具紧密结合来实现这一目标,并讨论了在更大尺度上(从细胞器到生物体)产生类似影响所面临的挑战。通过突出最近的成功案例,我们描述了数据不断增加的前景,以及在数据集可视化和量化之间实现无缝集成的必要性,以充分发挥新成像技术进步带来的潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0816/11392612/acd63464b9be/nihms-2015129-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0816/11392612/acd63464b9be/nihms-2015129-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0816/11392612/acd63464b9be/nihms-2015129-f0001.jpg

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本文引用的文献

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Omega - harnessing the power of large language models for bioimage analysis.欧米茄——利用大语言模型的力量进行生物图像分析。
Nat Methods. 2024 Aug;21(8):1371-1373. doi: 10.1038/s41592-024-02310-w.
2
Correlative single molecule lattice light sheet imaging reveals the dynamic relationship between nucleosomes and the local chromatin environment.相关单分子晶格光片成像揭示了核小体与局部染色质环境之间的动态关系。
Nat Commun. 2024 May 16;15(1):4178. doi: 10.1038/s41467-024-48562-0.
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Motion of VAPB molecules reveals ER-mitochondria contact site subdomains.
VAPB 分子的运动揭示了内质网-线粒体接触位点亚区。
Nature. 2024 Feb;626(7997):169-176. doi: 10.1038/s41586-023-06956-y. Epub 2024 Jan 24.
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Machine learning interpretable models of cell mechanics from protein images.基于蛋白质图像的细胞力学可解释机器学习模型。
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Smart lattice light-sheet microscopy for imaging rare and complex cellular events.智能晶格光片显微镜用于成像罕见和复杂的细胞事件。
Nat Methods. 2024 Feb;21(2):301-310. doi: 10.1038/s41592-023-02126-0. Epub 2024 Jan 2.
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u-track3D: Measuring, navigating, and validating dense particle trajectories in three dimensions.u-track3D:三维中测量、导航和验证密集粒子轨迹。
Cell Rep Methods. 2023 Dec 18;3(12):100655. doi: 10.1016/j.crmeth.2023.100655. Epub 2023 Dec 1.
8
Chromatin organization drives the search mechanism of nuclear factors.染色质构象调控核小体搜索机制。
Nat Commun. 2023 Oct 13;14(1):6433. doi: 10.1038/s41467-023-42133-5.
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Smart microscopes of the future.未来的智能显微镜。
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10
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