3JCI

2.9 Angstrom Resolution Cryo-EM 3-D Reconstruction of Close-packed PCV2 Virus-like Particles


ELECTRON MICROSCOPY

Refinement

RMS Deviations
KeyRefinement Restraint Deviation
f_dihedral_angle_d17.151
f_angle_d0.817
f_chiral_restr0.054
f_bond_d0.01
f_plane_restr0.006
Sample
Porcine circovirus PCV2 virus-like particles
Sample Components
Porcine circovirus 2 (PCV2)
Specimen Preparation
Sample Aggregation StatePARTICLE
Vitrification InstrumentGATAN CRYOPLUNGE 3
Cryogen NameETHANE
Sample Vitrification DetailsBlot for 5 seconds before plunging into liquid ethane (GATAN CRYOPLUNGE 3).
3D Reconstruction
Reconstruction MethodSINGLE PARTICLE
Number of Particles50352
Reported Resolution (Å)2.9
Resolution MethodFSC 0.143 CUT-OFF
Other DetailsFor 3D reconstruction, whole datasets were divided into even and odd halves and the initial de novo models and subsequent iterative refinements were a ...For 3D reconstruction, whole datasets were divided into even and odd halves and the initial de novo models and subsequent iterative refinements were all independently performed for each half dataset. Particles were selected from scanned micrograph images using e2boxer.py in EMAN2. The TEM instrument contrast transfer function parameters were determined automatically using fitctf2.py in JSPR and were then visually validated using the EMAN ctfit program. The datasets were then divided into two subsets (even and odd) and processed completely independently, including both de novo initial models and refinements. The images were first binned 4x to obtain initial models and particle parameters assuming icosahedral symmetry. De novo initial models were built using the random model approach. Random subsets of particles were assigned random initial orientations and iteratively refined until convergence. Multi-model competitive refinements were used to choose the winning model (with most assigned particles) as corrective initial models for subsequent refinement. Particles with inconsistent/unstable view parameters in the initial refinements were excluded in further image processing. The orientation and center parameters were then transferred to the un-binned images for high-resolution refinements which included Simplex method-based orientation/center optimization and grid search-based refinement of defocus, astigmatism, beam tilt, and overall and anisotropic magnification of the images. All image refinement and reconstructions were performed with JSPR software that was built on EMAN2 and EMAN library functions and programs. (Single particle details: The particles were selected using the e2boxer.py program in EMAN2. CTF parameters were determined using fitctf2.py in JSPR.) (Single particle--Applied symmetry: I)
Refinement Type
Symmetry TypePOINT
Point SymmetryI
Map-Model Fitting and Refinement
Id1
Refinement Space
Refinement Protocol
Refinement Target
Overall B Value
Fitting Procedure
Details
Data Acquisition
Detector TypeKODAK SO-163 FILM
Electron Dose (electrons/Å**2)25
Imaging Experiment1
Date of Experiment2011-02-22
Temperature (Kelvin)90
Microscope ModelFEI TITAN KRIOS
Minimum Defocus (nm)200
Maximum Defocus (nm)2500
Minimum Tilt Angle (degrees)
Maximum Tilt Angle (degrees)
Nominal CS2.7
Imaging ModeBRIGHT FIELD
Specimen Holder ModelFEI TITAN KRIOS AUTOGRID HOLDER
Nominal Magnification59000
Calibrated Magnification587963
SourceFIELD EMISSION GUN
Acceleration Voltage (kV)300
Imaging Details
EM Software
TaskSoftware PackageVersion
RECONSTRUCTIONEMAN2
RECONSTRUCTIONjspr
Image Processing
CTF Correction TypeCTF Correction DetailsNumber of Particles SelectedParticle Selection Details
Each particle