Multi-curve fitting and tubulin-lattice signal removal for structure determination of large microtubule-based motors.
Multi-curve fitting and tubulin-lattice signal removal for structure determination of large microtubule-based motors.
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DOI：
10.1016/j.jsb.2022.107897
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发表时间：
2022-12
影响因子：
3
通讯作者：
Zhang, Kai
中科院分区：
文献类型：
--
作者：
Chai, Pengxin;Rao, Qinhui;Zhang, Kai
关键词：
揭示微管相关蛋白（MAP）的高分辨率结构对于理解它们在各种细胞活动中的基本作用至关重要，例如细胞运动和细胞内货物运输。然而，动态结合和释放微管网络的大型柔性分子马达对于冷冻电子显微镜（cryo-EM）是具有挑战性的。传统的结合微管的MAP的结构测定需要来自微管的重建的比对信息，这不能容易地应用于没有固定的结合模式的大MAP。在这里，我们开发了一种综合的方法来估计微管网络（多曲线拟合），建模微管蛋白晶格信号，并从原始cryo-EM显微照片中删除它们（微管蛋白晶格减法）。该方法不需要微管上MAP的有序结合模式，也不需要微管的重建。我们证明了我们的方法使用重组的外臂动力蛋白（OAD）结合微管双联体的能力。微管蛋白晶格减法改善OAD对齐，从而导致高分辨率重建。此外，多曲线拟合方法提供了一种精确的自动替代方法，以在2D图像和潜在的3D断层图像中拾取或分割细丝。我们的方法的准确性已经通过使用其他几种生物细丝得到了证明。我们的工作提供了一个新的工具，以确定高分辨率的结构大地图绑定到弯曲的微管网络。
Revealing high-resolution structures of microtubule-associated proteins (MAPs) is critical for understanding their fundamental roles in various cellular activities, such as cell motility and intracellular cargo transport. Nevertheless, large flexible molecular motors that dynamically bind and release microtubule networks are challenging for cryo-electron microscopy (cryo-EM). Traditional structure determination of MAPs bound to microtubules needs alignment information from the reconstruction of microtubules, which cannot be readily applied to large MAPs without a fixed binding pattern. Here, we developed a comprehensive approach to estimate the microtubule networks (multi-curve fitting), model the tubulin-lattice signals, and remove them (tubulin-lattice subtraction) from the raw cryo-EM micrographs. The approach does not require an ordered binding pattern of MAPs on microtubules, nor does it need a reconstruction of the microtubules. We demonstrated the capability of our approach using the reconstituted outer-arm dynein (OAD) bound to microtubule doublets. The tubulin-lattice subtraction improves the OAD alignment, thus leading to high-resolution reconstructions. In addition, the multi-curve fitting approach provides an accurate automatic alternative method to pick or segment filaments in 2D images and potentially in 3D tomograms. The accuracy of our approach has been demonstrated by using several other biological filaments. Our work provides a new tool to determine high-resolution structures of large MAPs bound to curved microtubule networks.
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影响因子：
16.8
作者：
Han, Long;Rao, Qinhui;Yang, Renbin;Wang, Yue;Chai, Pengxin;Xiong, Yong;Zhang, Kai
通讯作者：
Zhang, Kai
影响因子：
64.8
作者：
Chaaban S;Carter AP
通讯作者：
Carter AP
影响因子：
16.8
作者：
Gui M;Ma M;Sze-Tu E;Wang X;Koh F;Zhong ED;Berger B;Davis JH;Dutcher SK;Zhang R;Brown A
通讯作者：
Brown A
影响因子：
13.6
作者：
Cuveillier, Camille;Delaroche, Julie;Delphin, Christian
通讯作者：
Delphin, Christian
影响因子：
3
作者：
Kremer, JR;Mastronarde, DN;McIntosh, JR
通讯作者：
McIntosh, JR