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Application of Monolayer Graphene and Its Derivative in Cryo-EM Sample Preparation

期刊

出版社

MDPI
DOI: 10.3390/ijms22168940

关键词

cryo-EM; single-particle; sample preparation; graphene; graphene oxide; chemical modification

资金

  1. National Natural Science Foundation of China [31600593]
  2. Natural Science Foundation of Gansu Province [20JR5RA257]
  3. Foundation of the Ministry of Education Key Laboratory of Cell Activities and Stress Adaptations [lzujbky-2021-kb05]
  4. Guochang Funding in Lanzhou University

向作者/读者索取更多资源

Graphene has been used to improve frozen sample preparation, effectively preventing particles from adsorbing to the air-water interface, and enhancing the dispersion, adsorbed number, and orientation preference of frozen particles in the ice layer. Its excellent properties and thinner thickness can significantly reduce background noise, allowing high-resolution three-dimensional reconstructions.
Cryo-electron microscopy (Cryo-EM) has become a routine technology for resolving the structure of biological macromolecules due to the resolution revolution in recent years. The specimens are typically prepared in a very thin layer of vitrified ice suspending in the holes of the perforated amorphous carbon film. However, the samples prepared by directly applying to the conventional support membranes may suffer from partial or complete denaturation caused by sticking to the air-water interface (AWI). With the application in materials, graphene has also been used recently to improve frozen sample preparation instead of a suspended conventional amorphous thin carbon. It has been proven that graphene or graphene oxide and various chemical modifications on its surface can effectively prevent particles from adsorbing to the AWI, which improves the dispersion, adsorbed number, and orientation preference of frozen particles in the ice layer. Their excellent properties and thinner thickness can significantly reduce the background noise, allowing high-resolution three-dimensional reconstructions using a minimum data set.

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