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. 2014 Sep 4:5:4808.
doi: 10.1038/ncomms5808.

An atomic model of brome mosaic virus using direct electron detection and real-space optimization

Zhao Wang  1 , Corey F Hryc  2 , Benjamin Bammes  3 , Pavel V Afonine  4 , Joanita Jakana  5 , Dong-Hua Chen  5 , Xiangan Liu  5 , Matthew L Baker  5 , Cheng Kao  6 , Steven J Ludtke  7 , Michael F Schmid  7 , Paul D Adams  8 , Wah Chiu  7
Affiliations

An atomic model of brome mosaic virus using direct electron detection and real-space optimization

Zhao Wang et al. Nat Commun. .

Abstract

Advances in electron cryo-microscopy have enabled structure determination of macromolecules at near-atomic resolution. However, structure determination, even using de novo methods, remains susceptible to model bias and overfitting. Here we describe a complete workflow for data acquisition, image processing, all-atom modelling and validation of brome mosaic virus, an RNA virus. Data were collected with a direct electron detector in integrating mode and an exposure beyond the traditional radiation damage limit. The final density map has a resolution of 3.8 Å as assessed by two independent data sets and maps. We used the map to derive an all-atom model with a newly implemented real-space optimization protocol. The validity of the model was verified by its match with the density map and a previous model from X-ray crystallography, as well as the internal consistency of models from independent maps. This study demonstrates a practical approach to obtain a rigorously validated atomic resolution electron cryo-microscopy structure.

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Figures

Figure 1
Figure 1. Assessment of particle movement and SSNR through the use of movie frames.
(a) Histogram showing particle movements assessed by comparing three-frame averages from the beginning, middle and end of each movie. The cumulative exposure was ~53 e− Å−2 accumulated over 1.5 s. (b) Left, a magnified portion of a summed frame (2–12). Right, the 1D SSNR of 92 BMV particles computed from that frame. (c) Same as b, from summed frames 2–36. (d) Same as c, from summed frames 2–36, with damage compensation for each frame.
Figure 2
Figure 2. Cryo-EM density maps of two independent data sets and 3D reconstructions after 38 refinement iterations.
With maps generated from data sets 1 and 2 (a) and their combined maps (b). The initial model for each data set/reconstruction was generated using EMAN1. Subsequent refinement was computed using MPSA. The final five iterations were completed in EMAN1, resulting in the final 3D density maps.
Figure 3
Figure 3. Resolution validation of the final cryo-EM density map.
(a) FSC curves computed using three different methods (as labelled) between two independent 3D reconstructions generated from two different data sets. (b) Gold-standard FSC curves of the final density maps before and after QES averaging. (c) Gold-standard FSC curves of density maps generated using different total numbers of particles. (d) Relationship between varying number of asymmetric units (equivalent to 60 × total number of particle per reconstruction) and the resolution for each reconstruction as determined in Fig. 3c. Each data point refers to the gold-standard resolution and the total number of particles for each reconstruction, respectively. A least-squares linear fit of this relationship resulted in an overall B-factor of 165 Å2.
Figure 4
Figure 4. Density maps and associated models of segmented subunits in an asymmetric unit.
(a) Segmented density of a single asymmetric unit from the final cryo-EM combined density map. Subunit A is blue, subunit B is green and subunit C is red. (b) Final optimized models are displayed with their corresponding segmented density maps. A varying number of amino acids were visible for the terminal arms within each subunit because of disordered regions of density.
Figure 5
Figure 5. Side-chain details from regions in subunit B shown with map and model.
Comparable regions from the other two capsid subunits are shown in Supplementary Fig. 5.
Figure 6
Figure 6. Model variation between two independent models derived from the independent data sets.
(a) A flow chart outlining the validation procedure used for two independent models. (b) Deviation between the independent models at the Cα level. Blue regions correspond to low deviation between the independent models and red regions correspond to greater deviation. (c) FSC curve between simulated densities generated from the molecular model (after assembling a complete capsid) and the experimental cryo-EM density map.
Figure 7
Figure 7. Comparisons of cryo-EM and X-ray BMV structures.
(a) Overlapping models of cryo-EM (in green, blue and red) and X-ray model (grey, PDB id: 1JS9). (b) Cα deviation between X-ray and cryo-EM derived models. Large deviations are shown in red, with small deviations shown in blue. Cryo-EM map and model (c) and X-ray 2Fo-Fc map (3.55 σ) and model (d) of the asymmetric unit.
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