Multi-curve fitting and tubulin-lattice signal removal for structure determination of large microtubule-based motors

Abstract

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.