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EMPIAR-10673 Tutorial

Calculating a 3.5 angstrom map of a GPCR in 1.5h

(This page is currently under development & will be updated soon)

  • Time requirement: 1.5 h compute time | 30 min manual time
  • Goal: Determine a 3.5 angstrom structure of GLP1-R.

This tutorial will walk you through the analysis of the EMPIAR dataset 10673 containing GLP1-R.

Creating a Project​

To start, you need to create a new project. Navigate to the Project view by clicking on the Project tab in the left sidebar. To Create a new Project, click on the top right button "+Add new project". Enter a name and specify the type (SPA for this tutorial).

Once you confirm, the project grid will open automatically.

Linking a dataset​

To run any type of analysis in a CryoCloud project, you need to link a dataset to your project.

Click on the "Datasets" tab on the top left, and select Empiar-10673.

Pre-processing​

This section focuses on the jobs you can run in the pre-processing column.

Motion Correction​

To set up a motion correction, click on the "+" tile in the Pre-processing column. The job type (Motion Correction) and the linked dataset will already be pre-selected in the dropdowns, so you just need to confirm the selection.

Once confirmed, the Job setup form will open. The movies.star will be already pre-selected as it was created for the linked Empiar dataset during upload - there is no need to run a separate Import Job on CryoCloud, as the .star files will be automatically created during dataset upload.

Specfy the following parameters

  • Input movies STAR: datasets/<N>/movies.star
  • gain reference: datasets/<N>/gainref.mrc

After that, confirm the setup and submit the job by clicking "Save & Run" on the bottom right. The job status will change to submitted, and analysis will start in 3-5 min, during which an instance is spun up for you. The Motion Correction job itself should finish in 14 min.

CTF Estimation​

Queuing

You can queue a job to a running job or a job draft. Simply click on the "+" sign on the top right of a job tile. After setting up and submitting the job, its status will be shown as queued and it will automatically start when the previous job has finished.

After submitting the MotionCor job, you can go back to the overview and set up the next CTF Estimation job - there is no need to wait for the previous job to be finished, as you can queue the CTF Estimation job to the running MotionCor job.

Simply click on the "+" in the top right corner of the MotionCor Job, select CTF Estimation/Find job with the MotionCor job as a parent, and specify all parameters in the job view. For this job, you can keep all default parameters - so if you like simply jump to the bottom and click "Save & Run".

The Job should finish in about 1 minutes. After it is completed, you can inspect the results by clicking on the completed job's tile, selecting "Micrographs" tab and then opening one of the micrographs in the table. It should look as follows:

Example banner

Micrograph Selection​

The Micrograph Table should also show that most Micrographs have a maximum resolution of 3-4.5 Angstrom. For the next steps, we want to exclude micrographs with a resolution lower than 3.5 Å, as done in the publication by Danev et al. Setup a Select job, and specify the following parameters:

This results in 213 selected micrographs.

Particle Picking​

Set up a particle picking job, either as before by clicking on the "+" of the CTF job, or by hovering over the Pre-Processing column, clicking the "+" sign and specifying the CTF job as input. For this dataset, you can use the default values with the LoG picker. You just need to specify the minimum and maximum diameter as 100 angstrom and 160 angstrom respectively:

  • Min. diameter for LoG filter (A): 100
  • Max. diameter for LoG filter (A): 180

Just like for the CTF job, you can inspect the results of your picking job once it's finished in the results section. The picking should have resulted in about 175k particles.

Extract Particles​

To analyze your picked particles you need to extract them first. Set up an "Extract Particle" job via the "+" sign on the Picking job tile, and specify the following parameters:

  • Micrograph STAR file: jobs/CtfFind/<N>/micrographs_ctf.star (from CTF Estimation job)
  • Input coordinates: jobs/AutoPick/<N>/coords_suffix_autopick.star (from AutoPick job)
  • Particle box size (pix): 256
  • Rescale particles: Yes
  • Rescaled box size (pix): 70

You can keep the default values for the other settings and submit the job.

Class3D​

This section focuses on the jobs you can run in the Class3D column.

Uploading a reference map​

Before we go to the 3D classification step, you need to upload a reference map to your project.

In CryoCloud, all references, masks and other auxiliary files can be uploaded to the Project's Archive located next to Datasets on the top left. You can use these files as input for jobs that require external data (masks, references, high resolution maps for model building).

Simply click on the "Archive" button. This will open a Side Panel that allows you to upload new files and inspect all current files in the Archive. You can download the following reference and mask and upload it to the project's archive by clicking on "Upload file" on the Side Panel:

3D Classification​

For this dataset, we will go directly to the 3D classification step as was done by the authors.

Specify the following parameters:

  • Input images STAR file: jobs/Extract/<N>/particles.star, where N is the previous job's number and is set automatically.
  • Reference map: archive/<downloaded-reference>.mrc
  • Initial low-pass filter: 20
  • Number of classes: 3
  • Mask diameter (A): 160
  • Use Blush regularization: Yes

All other parameters can be kept at their default values. The 3D classification job should finish in about 50 minutes.

Select​

Once the 3D classification job is finished, set up a Select job on top of the previous job tile Class 3D.

As the job's input, select the last iteration from the parent job, it should look like this:

  • Select classes from model.star: jobs/Class3D/<N>/run_it<X>_model.star, where N is previous job's number and X is the last iteration (in the previous step we set it to 25)

Click "Load selector" to load the 3D class averages. You can then interactively select the correct classes (shown below).

Once you selected all classes, click the "Save & Run" at the bottom to submit the job.

Example banner

Refine3D​

In this section, we switch to Refine3D column for 3D refinement.

3D Refinement​

Use the selected particles from the Class 3D job and the uploaded reference in the archive as input for the Refine 3D job:

  • Input images STAR file: jobs/Select/<N>/particles.star
  • Reference map: archive/<downloaded-reference.mrc>
  • Mask: archive/<downloaded-mask.mrc

Additionally, you need to specify the following parameters:

  • Initial low-pass filter: 12
  • Mask Diameter (A): 160
  • Use solvent-flattened FSCs: Yes

You can keep all other settings as default, and submit the job.

Next Steps​

Feel free to download the resulting map from the "Refine3D" job, create a mask using the "Mask create" job from "Refine3D" column and run a "Post-Processing" job from the "Post-Processing" column. Note that both jobs need to be run on top of the "Refine 3D" job.

You can also run polishing and CTF refinement jobs with the available data.

If you have any input or questions during the tutorial, let us know via the in-app messenger or an email to hi@cryocloud.io.

If you have read through the tutorial but not signed up for a free 30-day CryoCloud trial, you can do that here.