Massively parallel unsupervised single-particle cryo-EM data clustering via statistical manifold learning.

Structural heterogeneity in single-particle cryo-electron microscopy (cryo-EM) data represents a major challenge for high-resolution structure determination. Unsupervised classification may serve as the first step in the assessment of structural heterogeneity. However, traditional algorithms for unsupervised classification, such as K-means clustering and maximum likelihood optimization, may classify images into wrong classes with decreasing signal-to-noise-ratio (SNR) in the image data, yet demand increased computational costs. Overcoming these limitations requires further development of clustering algorithms for high-performance cryo-EM data processing. Here we introduce an unsupervised single-particle clustering algorithm derived from a statistical manifold learning framework called generative topographic mapping (GTM). We show that unsupervised GTM clustering improves classification accuracy by about 40% in the absence of input references for data with lower SNRs. Applications to several experimental datasets suggest that our algorithm can detect subtle structural differences among classes via a hierarchical clustering strategy. After code optimization over a high-performance computing (HPC) environment, our software implementation was able to generate thousands of reference-free class averages within hours in a massively parallel fashion, which allows a significant improvement on ab initio 3D reconstruction and assists in the computational purification of homogeneous datasets for high-resolution visualization.

Conformational Landscape of the p28-Bound Human Proteasome Regulatory Particle.

The proteasome holoenzyme is activated by its regulatory particle (RP) consisting of two subcomplexes, the lid and the base. A key event in base assembly is the formation of a heterohexameric ring of AAA-ATPases, which is guided by at least four RP assembly chaperones in mammals: PAAF1, p28/gankyrin, p27/PSMD9, and S5b. Using cryogenic electron microscopy, we analyzed the non-AAA structure of the p28-bound human RP at 4.5 Å resolution and determined seven distinct conformations of the Rpn1-p28-AAA subcomplex within the p28-bound RP at subnanometer resolutions. Remarkably, the p28-bound AAA ring does not form a channel in the free RP and spontaneously samples multiple "open" and "closed" topologies at the Rpt2-Rpt6 and Rpt3-Rpt4 interfaces. Our analysis suggests that p28 assists the proteolytic core particle to select a specific conformation of the ATPase ring for RP engagement and is released in a shoehorn-like fashion in the last step of the chaperone-mediated proteasome assembly.

Structural basis for dynamic regulation of the human 26S proteasome.

The proteasome is the major engine of protein degradation in all eukaryotic cells. At the heart of this machine is a heterohexameric ring of AAA (ATPases associated with diverse cellular activities) proteins that unfolds ubiquitylated target proteins that are concurrently translocated into a proteolytic chamber and degraded into peptides. Using cryoelectron microscopy, we determined a near-atomic-resolution structure of the 2.5-MDa human proteasome in its ground state, as well as subnanometer-resolution structures of the holoenzyme in three alternative conformational states. The substrate-unfolding AAA-ATPase channel is narrowed by 10 inward-facing pore loops arranged into two helices that run in parallel with each other, one hydrophobic in character and the other highly charged. The gate of the core particle was unexpectedly found closed in the ground state and open in only one of the alternative states. Coordinated, stepwise conformational changes of the regulatory particle couple ATP hydrolysis to substrate translocation and regulate gating of the core particle, leading to processive degradation.