Exploring the spatial and temporal organization of a cell's proteome.
Exploring the spatial and temporal organization of a cell's proteome.
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DOI：
10.1016/j.jsb.2010.11.011
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发表时间：
2011-03
影响因子：
3
通讯作者：
Alber, Frank
中科院分区：
文献类型：
--
作者：
Beck, Martin;Topf, Maya;Frazier, Zachary;Tjong, Harianto;Xu, Min;Zhang, Shihua;Alber, Frank
关键词：
为了增加我们目前对细胞过程的理解，如细胞信号传导和分裂，需要了解蛋白质组在不同组织水平上的空间和时间组织。这些水平涵盖了广泛的长度和时间尺度：从推断其分子功能的大分子的原子结构，到对其丰度和在细胞中的分布的定量描述。新兴的新实验技术极大地增加了活细胞中分子组织的空间信息的可用性。本文综述了三个对我们理解蛋白质组的时空组织有重要贡献的领域：首先，确定单个大分子组装体的结构方法，特别是将原子结构拟合到电子显微镜技术生成的密度图中；其次，利用冷冻电子断层扫描技术结合计算图像处理技术，在细胞背景下可视化这些复合物的空间分布；第三，蛋白质组动态组织的空间建模方法，特别是那些模拟蛋白质和复合物在拥挤的细胞内液体中的反应和扩散的方法。长期目标是将有关蛋白质组组织的各种数据整合到一个空间明确的细胞过程预测模型中。
To increase our current understanding of cellular processes, such as cell signaling and division, knowledge is needed about the spatial and temporal organization of the proteome at different organizational levels. These levels cover a wide range of length and time scales: from the atomic structures of macromolecules for inferring their molecular function, to the quantitative description of their abundance, and distribution in the cell. Emerging new experimental technologies are greatly increasing the availability of such spatial information on the molecular organization in living cells. This review addresses three fields that have significantly contributed to our understanding of the proteome’s spatial and temporal organization: first, methods for the structure determination of individual macromolecular assemblies, specifically the fitting of atomic structures into density maps generated from electron microscopy techniques; second, research that visualizes the spatial distributions of these complexes within the cellular context using cryo electron tomography techniques combined with computational image processing; and third, methods for the spatial modeling of the dynamic organization of the proteome, specifically those methods for simulating reaction and diffusion of proteins and complexes in crowded intracellular fluids. The long-term goal is to integrate the varied data about a proteome’s organization into a spatially explicit, predictive model of cellular processes.
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影响因子：
48
作者：
Beck, Martin;Malmstroem, Johan A.;Lange, Vinzenz;Schmidt, Alexander;Deutsch, Eric W.;Aebersold, Ruedi
通讯作者：
Aebersold, Ruedi
影响因子：
5.6
作者：
Chacón, P;Wriggers, W
通讯作者：
Wriggers, W
影响因子：
3.6
作者：
Briegel, Ariane;Ding, H. Jane;Jensen, Grant J.
通讯作者：
Jensen, Grant J.
影响因子：
2
作者：
Andrews, SS;Bray, D
通讯作者：
Bray, D
影响因子：
4.4
作者：
Banchio, AJ;Brady, JF
通讯作者：
Brady, JF