Hi. Recently, I was processing data o fa small protein, whose molecular weight is about 120kDa, for many rounds of refinement, but the problem of orientation advantage still exists. Strategies that have been tried so far are:
How does the map look? do you see obvious streaking or anisotropy in real space, does it impede map interpretation?
that is a pretty bad example of the issue. I strongly suggest using view_select to encompass several distinct regions that are NOT the dominant view (even though there are no obvious “hotspots”), running 2D classification with ~10-30 classes for each subset, then training a topaz picker for any 2D that looks different from preferred view. Simultaneously you should consider other ways to prepare grids (LEA? grid type/coating? detergents?) as this might not be insurmountable. In future if you have prepared multiple grids and you can manage to identify strong preferential orientation early, consider screening another - sometime’s the strong bias is grid-specific as it happens very quickly post-blot and is dependent on ice thickness and time.
Currently the main view is that the bottom and top information is missing
ok,I’m going to try view select, trying to separate out the non-dominant view with 2D.
Maybe I can try it. Could you tell me exactly how to do it？
I wonder if by view_select you mean select_2D select the non-dominant view? Or some other job I don’t know about.
It is an extra program, and it can be found at the link in the other topic (put it in my post)
If I want to add detergent to the sample, which detergent should be used for DNA-bound proteins? What is the final concentration of this detergent?
several published resources: Detergents and alternatives in cryo-EM studies of membrane proteins: Detergents and alternatives in cryo-EM studies of membrane proteins - PMC
Cryo-EM Vitrification Detergents, & Surfactants | MiTeGen
Eliminating effects of particle adsorption to the air/water interface in single-particle cryo-electron microscopy: Bacterial RNA polymerase and CHAPSO - ScienceDirect
chapso, amphipols, lmng, ddt.
Thank you for your suggestion.I will see which one is more suitable.
I just looked at the topic of your home page, but I didn’t see this link about view_select. Could you please help me find it？
You can also try “Rebalance orientations” in CryoSPARC itself.
Thank you for your suggestion, I have tried it, but the effect is not very obvious.
Often, you need to adjust the threshold for removal for optimal results. If it’s not helping at all, given the distribution of particles in that plot, I would run a quick 2D to check for junk.
From the result of rebalance orientation,this seemed to be an improvement, but after running Nu_refine, I found that the resolution and cloud images were worse.
github.com/robertstass/ViewSelect
you desperately need more particles picked from a different view. I would revisit picking strategy and try to find any unique particles and use Topaz to select for more of them, iterating a few times to continue getting more and more
Thank you very much for your suggestion. I will try it right away.
