A. Baumannii MLA Complex

Dataset

• EMPIAR-10425

Learning objectives

Importing results into CryoSPARC, 3D classification techniques. Note: Use the outputs of the previous step as the inputs for the next step, unless otherwise noted.

1. Create a New Workspace

2. Import Particles

3. Downsample Particles

4. 2D Classification

5. Select 2D Classes

Choose a set of 2D classes (approximately 20) that look sharp and display secondary structure features.

You should end up with around 35-40K particles.

6. Ab-initio Reconstruction

Use default parameters

--- Queue the following two refinement jobs in parallel. ---

7. Homogeneous Refinement

8. Non-uniform Refinement

9. Mask Generation in UCSF Chimera

1. Download the refined volume from the previous Non-uniform Refinement job.
2. Open the map in UCSF Chimera, and note the opened structures model ID as <model_id> .
3. Decrease the threshold until you can clearly see both "lobes" (these are the MlaB domains, located opposite from the 6-fold symmetric MlaD domain). Note the threshold value <threshold_number> .
4. Open the Map Eraser (Under Tools > Volume Data > Volume Eraser ).
5. Erase the micelle and the 6-fold symmetric MlaD domain.
6. Use vop threshold to binarize the density map of the MlaB domain, to convert it to a mask.
   • Set all density values outside of the MlaB domain to 0: vop threshold #<model_id> minimum <threshold_number> set 0 modelId 99
   • Set all density values within the MlaB domain to 1: vop threshold #99 maximum <threshold_number> setMaximum 1 modelId 98
7. Save the mask to your home directory. In the Volume Viewer, select File -> Save map as -> baum_embolab_mask.mrc

10. Import Volumes

11. Volume Tools

--- Queue 3D classification and 3DVA in parallel. ---

12. 3D Classification

13. 3D Classification

14. 3D Variability Analysis

15. 3D Variability Display (1)

16. 3D Variability Display (2)