https://3demmethods.i2pc.es/index.php?action=history&feed=atom&title=2022Hohle_Ice 2026-05-24T18:16:29Z Revision history for this page on the wiki MediaWiki 1.44.2 https://3demmethods.i2pc.es/index.php?title=2022Hohle_Ice&diff=4333&oldid=prev 2023-06-15T05:43:48Z

<p>Created page with &quot;== Citation == Hohle, Markus Matthias / Lammens, Katja / Gut, Fabian / Wang, Bingzhi / Kahler, Sophia / Kugler, Kathrin / Till, Michael / Beckmann, Roland / Hopfner, Karl-Pet...&quot;</p> <p><b>New page</b></p><div>== Citation ==<br /> <br /> Hohle, Markus Matthias / Lammens, Katja / Gut, Fabian / Wang, Bingzhi / Kahler, Sophia / Kugler, Kathrin / Till, Michael / Beckmann, Roland / Hopfner, Karl-Peter / Jung, Christophe.<br /> Ice thickness monitoring for cryo-EM grids by interferometry imaging.<br /> 2022. Scientific Reports, Vol. 12, No. 1, p. 1-11 <br /> <br /> == Abstract ==<br /> <br /> While recent technological developments contributed to breakthrough advances in single particle<br /> cryo-electron microscopy (cryo-EM), sample preparation remains a significant bottleneck for the<br /> structure determination of macromolecular complexes. A critical time factor is sample optimization<br /> that requires the use of an electron microscope to screen grids prepared under different conditions to<br /> achieve the ideal vitreous ice thickness containing the particles. Evaluating sample quality requires<br /> access to cryo-electron microscopes and a strong expertise in EM. To facilitate and accelerate the<br /> selection procedure of probes suitable for high-resolution cryo-EM, we devised a method to assess<br /> the vitreous ice layer thickness of sample coated grids. The experimental setup comprises an optical<br /> interferometric microscope equipped with a cryogenic stage and image analysis software based<br /> on artificial neural networks (ANN) for an unbiased sample selection. We present and validate this<br /> approach for different protein complexes and grid types, and demonstrate its performance for<br /> the assessment of ice quality. This technique is moderate in cost and can be easily performed on a<br /> laboratory bench. We expect that its throughput and its versatility will contribute to facilitate the<br /> sample optimization process for structural biologists.<br /> <br /> == Keywords ==<br /> <br /> == Links ==<br /> <br /> https://www.nature.com/articles/s41598-022-16978-7<br /> <br /> == Related software ==<br /> <br /> == Related methods ==<br /> <br /> == Comments ==</div>

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