Separating distinct structures of multiple macromolecular assemblies from cryo-EM projections

Eric J Verbeke,Yi Zhou,Andrew P Horton,Anna L Mallam,David W Taylor,Edward M Marcotte

doi:10.1016/j.jsb.2019.107416

Eric J Verbeke, Yi Zhou + Show 4 more

Open Access

https://doi.org/10.1016/j.jsb.2019.107416

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Abstract

Single particle analysis for structure determination in cryo-electron microscopy is traditionally applied to samples purified to near homogeneity as current reconstruction algorithms are not designed to handle heterogeneous mixtures of structures from many distinct macromolecular complexes. We extend on long established methods and demonstrate that relating two-dimensional projection images by their common lines in a graphical framework is sufficient for partitioning distinct protein and multiprotein complexes within the same data set. The feasibility of this approach is first demonstrated on a large set of synthetic reprojections from 35 unique macromolecular structures spanning a mass range of hundreds to thousands of kilodaltons. We then apply our algorithm on cryo-EM data collected from a mixture of five protein complexes and use existing methods to solve multiple three-dimensional structures ab initio. Incorporating methods to sort single particle cryo-EM data from extremely heterogeneous mixtures will alleviate the need for stringent purification and pave the way toward investigation of samples containing many unique structures.

Highlights

Cryo-electron microscopy has undergone a revolutionary shift in the past few years.Increased signal in electron micrographs, as a result of direct electron detectors, has allowed for the near-atomic and atomic resolution structure determination of many macromolecules of various shapes and sizes (Kühlbrandt, 2014)
A major challenge facing “shotgun”-style Cryo-electron microscopy (cryo-EM) is to reconstruct models from projection images arising from multiple distinct structures present in a mixture
These similarity scores can be put into a graphical framework and clustering algorithms can be applied to group related 2D projection images for subsequent 3D

Summary

Introduction

Cryo-electron microscopy (cryo-EM) has undergone a revolutionary shift in the past few years.Increased signal in electron micrographs, as a result of direct electron detectors, has allowed for the near-atomic and atomic resolution structure determination of many macromolecules of various shapes and sizes (Kühlbrandt, 2014). We showed that it was possible to reconstruct macromolecular machines from the lysate of a single C. elegans embryo (Yi et al, 2018) These studies were limited to the identification of only the most abundant and identifiable protein and protein–nucleic acid complexes due to a lack of methods to efficiently categorize which two-dimensional (2D) projection images derive from which threedimensional (3D) assemblies on the basis of their structural features. While a number of 3D classification schemes exist, all failed to produce reliable reconstructions for the majority of particles in these complicated mixtures This obstacle emphasizes the long-standing need to sort mixtures of structures in addition to their conformational and compositional heterogeneity

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