<html><head><meta http-equiv="content-type" content="text/html; charset=utf-8"></head><body dir="auto"><div>Hi Yang,</div><div id="AppleMailSignature"><br></div><div id="AppleMailSignature">You could also try discarding a portion of large dataset to even out the population percentages. Alternatively, if there is a similar pdb available, you could try 2D backprojections of that structure and use projections as templates for automated picking (I prefer gAutomatch). This may help pick up poorly electron dense orientations that are not easily visible or not readily picked with auto threshold parameters.</div><div id="AppleMailSignature"><br></div><div id="AppleMailSignature">Hope this helps,</div><div id="AppleMailSignature">Jillian<br><br><br></div><div><br>On May 17, 2017, at 9:06 AM, Andreas Boland <<a href="mailto:aboland@mrc-lmb.cam.ac.uk">aboland@mrc-lmb.cam.ac.uk</a>> wrote:<br><br></div><blockquote type="cite"><div><meta http-equiv="Content-Type" content="text/html charset=us-ascii"><div class="">Dear Yang,</div><div class=""><br class=""></div><div class="">we have recently used graphene oxide as a support layer to increase our orientation distribution (compared to no support) for a separase-securin complex (<a href="http://www.nature.com/nsmb/journal/v24/n4/full/nsmb.3386.html" class="">http://www.nature.com/nsmb/journal/v24/n4/full/nsmb.3386.html</a>)</div><div class=""><br class=""></div><div class="">A protocol how to prepare graphene oxide coated girds can be found online here (<a href="https://figshare.com/articles/Graphene_Oxide_Grid_Preparation/3178669" class="">https://figshare.com/articles/Graphene_Oxide_Grid_Preparation/3178669</a>).</div><div class=""><br class=""></div><div class="">Also this topic has been discussed in many reviews. One example here:</div><div class=""><a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4409659/" class="">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4409659/</a></div><div class=""><br class=""></div><div class="">All the best,</div><div class=""><br class=""></div><div class="">Andreas </div><div class=""><br class=""></div><div><blockquote type="cite" class=""><div class="">On 17 May 2017, at 13:46, Yang Li <<a href="mailto:yanglixtal@gmail.com" class="">yanglixtal@gmail.com</a>> wrote:</div><br class="Apple-interchange-newline"><div class=""><div dir="ltr" class="">Dear colleagues,<div class=""><br class=""></div><div class="">We have a protein sample that suffers from severe orientation preference, that most of the particles cluster into two distinct orientations. This way we have to collect large amounts of data in order to obtain enough effective particles, which hiders us from reaching high resolution. We have tried to make thicker ice or adding tiny amount of detergent such as Tween20, but not working very well so far. I wonder if there are any tricks we can try to overcome this orientation preference issue? Thank you in advance for suggestions!</div><div class=""><br class=""></div><div class="">Best,</div><div class="">Yang </div></div>
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