Biological processes, from cell motility to signal transduction, require large heterogeneous assemblies that undergo dynamic changes. Unfortunately, no single biophysical method yields continuous views of these large biological complexes at atomic resolution. However, single-particle cryo-EM is capable of visualizing these complexes in discrete physiological or biochemical states.
It is now relatively common for cryo-EM to achieve subnanometer resolutions (reviewed in ref. 1
). To date, ~20% of all entries in the EM DataBank (EMDB, http://emdatabank.org/
), ranging from ion channels to infectious viruses, have achieved resolutions better than 10 Å. Unfortunately, at resolutions between 5 and 10 Å, atomic models cannot be constructed directly from the cryo-EM density map. However, distinct features in the density map are evident. At subnanometer resolutions, secondary structure elements (SSEs) are visible: α-helices appear as long cylinders, whereas β-sheets appear as thin planes1
. Using feature detection and computational geometry algorithms, SSEs can be reliably identified and quantified2,3
. The spatial description of SSEs has also been used to infer structure and/or function of individual protein domains, as was done in identifying an annexin-like domain in the HSV-1 major capsid protein4
and the pore structure of RyR1(ref. 5
Recently, the structure of several biological assemblies have been resolved to better than 4.6 Å resolution with single-particle cryo-EM6–16
. In these near-atomic resolution structures, the pitch of α-helices, the separation of β-strands and the densities that connect them can be seen. In these relatively high-resolution structures, many of the bulky side chains can also be seen. However, it should be noted that these structures still do not have the resolution to use standard X-ray crystallographic methods for automatic model construction. In fact, the de novo
models built from these structures rely almost entirely on visual interpretation of the density, and on manual structure assignment in cases in which no homologous structures are available9,10,13,16
. However, in each of these cases, significant insight into functional mechanisms and interactions can be reliably obtained from the models; thus providing an excellent framework for future research.
Here, we present our protocol for generating a near-atomic resolution cryo-EM density map, analyzing the salient features of the density map and building an atomic model. This protocol has been used in the construction of a complete atomic model for a group II chaperonin from Methanococcus maripaludis
, but is generally applicable to other single-particle specimens imaged with cryo-EM. For instance, the recent 4 Å resolution structure of the chaperonin TRiC/CCT with eight distinct subunits was elucidated with a similar protocol without imposing any symmetry, resolving a longstanding question as to how the eight subunits are arranged in each of the two rings8
The following protocol is divided into three modules. The first module (Steps 1–13) describes the steps to generate a near-atomic resolution density map from raw two-dimensional (2D) images (). The second module (Steps 14–25) details the procedure for generating a Cα backbone trace directly from the cryo-EM density map (), whereas the third module (Steps 26–33) describes a method for building an atomic model with side chain assignments from the initial Cα backbone trace ().
Figure 1 The cryo-EM density map reconstruction process. An outline of the procedure used for the reconstruction of Mm-cpn is shown. Steps involving the 2D particle images are highlighted in blue, whereas steps involving the 3D density map are shown in green. (more ...)
Figure 2 Cα backbone model generation. The procedure to generate an initial backbone model from a near-atomic resolution cryo-EM density is shown. The steps are colored as in ; red highlighting has been added to indicate steps involving atoms. (more ...)
Atomic model generation. The procedure for generating an atomic model from a Cα backbone is shown. Steps are color coded as described in and . The final subunit model for Mm-cpn is shown on the right.
In the first module, we provide an overview of how the reconstruction of Mm-cpn was achieved at near-atomic resolution. As there are many details and subtleties in approaching a refinement on a new specimen, we suggest running the EMAN17
program and following the four-step tutorial to get more detailed advice for specific projects. This protocol is for EMAN1, which was used for all of our published structures at the time of writing this paper. EMAN2 (ref. 18
) is now available and is easier to use for many of these steps (see Box 1
for further information).
Box 1. EMAN1 VS. EMAN2
EMAN2 is the successor to EMAN1, and although it still follows most of the same principles as EMAN1, the specific details of how it should be used are substantially different from EMAN1. It incorporates a completely new CTF model, has an integrated workflow for image processing and a new modular infrastructure, giving users much more flexibility as they process their data. Note that EMAN2 is still in its very early release. All of our published near-atomic resolution structures were completed with EMAN1 (refs. 8
). Moving forward, it is worth considering using EMAN2, although EMAN1 remains the more proven platform at this point in time. Regardless of platform, the material in this protocol will still provide useful information about the issues involved during processing, even if the specific commands have changed.
In the second set of steps, we will describe how to construct a model from a near-atomic resolution cryo-EM density map, depending on the availability of known or related atomic models. When a known or related structure for one or more of the components in a macromolecular assembly is known, the model can be fit to the density map and provide initial positioning of atoms in the density map. This requires either previous knowledge or sequence analysis tools to identify structural homologous. Alternatively, if no known or homologous structures are available, the de novo modeling steps (Steps 19–21) can generate an initial Cα backbone model for components of the macro-molecular assembly. If an atomic model is available, Steps 19–21 are not necessary.
In the final set of steps, side chains are added and the entire model is optimized to fit the density while maintaining reasonable geometry. Generally, these steps should only be used when a large percentage of side chains are visible in the density map. Anecdotally, in our 4.2 Å resolution structure of the chaperonin GroEL10
, only ~10% of side chain densities were visible and thus a complete model with side chains was not constructed. However, in Mm-cpn, > 65% of side chain densities were observed and thus an entire atomic model could be constructed. Despite similar resolutions, data quality (Mm-cpn images had higher contrast at higher resolution) and differences in the reconstruction steps may have affected the visibility of side chains in GroEL and Mm-cpn. However, the final decision on placement of side chains is at the user’s discretion and should be made on the basis of the visible features of the map and not merely on the stated resolution.