Toward Single Particle Reconstruction without Particle Picking: Breaking the Detection Limit

Single-particle cryo-electron microscopy (cryo-EM) has recently joined X-ray crystallography and NMR spectroscopy as a high-resolution structural method to resolve biological macromolecules. In a cryo-EM experiment, the microscope produces images called micrographs. Projections of the molecule of interest are embedded in the micrographs at unknown locations, and under unknown viewing directions. Standard imaging techniques first locate these projections (detection) and then reconstruct the 3-D structure from them. Unfortunately, high noise levels hinder detection. When reliable detection is rendered impossible, the standard techniques fail. This is a problem, especially for small molecules. In this paper, we pursue a radically different approach: we contend that the structure could, in principle, be reconstructed directly from the micrographs, without intermediate detection. The aim is to bring small molecules within reach for cryo-EM. To this end, we design an autocorrelation analysis technique that allows one to go directly from the micrographs to the sought structures. This involves only one pass over the micrographs, allowing online, streaming processing for large experiments. We show numerical results and discuss challenges that lay ahead to turn this proof-of-concept into a complementary approach to state-of-the-art algorithms.

Automated summary

Single-particle cryo-electron microscopy (cryo-EM), together with X-ray crystallography and NMR spectroscopy, is a high-resolution structural method for studying biological macromolecules. However, the standard techniques of cryo-EM face challenges in detecting small molecules due to high noise levels. This paper proposes a new approach that directly reconstructs the structure from the micrographs without intermediate detection, aiming to make cryo-EM more applicable to small molecules. The authors introduce an autocorrelation analysis technique that allows for online processing and discuss future challenges in implementing this approach.