Filament sample's bos size and refinement problem

Helical Processing
1

Dear
Recently, I got a sample that could form the filament. I meet a few questions.

  1. I treated it as the common sample cause it was not filled with the images(shown in Figure 1, I got 3,000 movies in total). I didn’t use the filament tracer. I just chose a normal routine and it did work. However, the box size was the point that confused me for a long time. 256,320,384,640, I tried all. But none of them is good. The 2D classification looked good but the final resolution is just 6A(Fig2&3). So, which size should I choose?
  2. When I use the different box sizes and min. separation distance, I found some parts were picked more than one time and I am not sure that would have an impact on the final result AND I am not sure if should i use “remove the replicated particles” or not.
  3. The refinement problem. I found it could be the highest resolution in theory (the pixel is 1.067, and the shown is 2.14A, as Fig4). But when I downloaded the map, it showed very poor resolution. So, any way to avoid this?
    image
    image1478×1036 368 KB

    2D_1
    2D_2
    refinement

And any suggestion is welcome! Thank you very much

Best
quwujian

1 Like
2

You absolutely should. That FSC curve is showing the classic signs of duplicate particles.

Helical reconstruction is tricky, and a lot of care must be taken to avoid this issue. If you follow a processing pipeline designed for helical work (filament picking, etc) it has some safeguards. :slight_smile:

If you remove duplicates, I suspect you’ll see the FSC curve drop to zero around 6 Angstrom.

The CryoSPARC guide has some guidance regarding helical reconstruction.

1 Like
3

Thank you for your reply. I will try it. But I am also confusing why it is hard to get the high resolution. Not enough particles? Need I should collect more images? Or preferred orientation problem? Thank you again.

4

With correctly applied helical symmetry, if the sample isn’t contaminated or heterogeneous, you’ll probably find that the resolution improves dramatically. :slight_smile:

Preferred orientation isn’t really an issue with helical processing because of the symmetry application. :wink: The guide covers how to estimate the parameters necessary to apply, and then how to optimise them. But local minima are a real danger in helical work, so be cautious and best of luck with your processing!

Perhaps the CryoSPARC helical processing tutorial (a link is on the page I linked above) would be a good idea to run through? There’s lots of extra things to be careful about with helical processing beyond the normal concerns of SPA.

2 Likes
5

Well, thank you. The sample is fine. I have built the model based on one map, so I am sure there is no contamination. I tried D2 symmetry before and it did be better before. However, our lab member suggested not using symmetry easily. Now I will follow your advice, read the tutorial and try it. Thank you very much.

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