Resch, G. P. | bioRxiv Science

bioRxiv2021

UVC inactivation of pathogenic samples suitable for cryoEM analysis

Cryo-electron microscopy has become an essential tool to understand structure and function of biological samples, from individual proteins to whole cells. Especially for pathogens, such as disease-causing bacteria and viruses, insights gained by cryo-EM can aid in developing cures. However, due to the biosafety restrictions of human pathogens, samples are often treated by chemical fixation to render the pathogen inert, affecting the delicate ultrastructure of the sample. Alternatively, researchers use in vitro or ex vivo models, which are non-pathogenic but lack the complexity of the pathogen of interest. Here we show that ultraviolet-C (UVC) radiation at cryogenic temperatures can be used to eliminate or dramatically reduce the infectivity of two model organisms, a pathogenic bacterium (Vibrio cholerae) and a virus-like particle (the ICP1 bacteriophage). We show no discernable structural impact of this treatment of either sample using two cryo-EM methods: cryo-electron tomography (cryo-ET) followed by sub-tomogram averaging (STA), and single particle analysis (SPA). Additionally, we applied the UVC irradiation to the protein apoferritin (ApoF), which is a widely used test sample for high resolution SPA studies. The UVC-treated ApoF sample resulted in a 2.1 [A] structure that did not reveal any discernable structural damage. Together, these results show that the UVC irradiation dose that effectively inactivates cryo-EM samples does not negatively impact their structure. This research demonstrates that UVC treatment is an effective and inexpensive addition to the cryo-EM sample preparation toolbox.

molecular biology↗

bioRxiv2020

Optimized data acquisition workflow by sample thickness determination

Sample thickness is a known key parameter in cryo-electron microscopy (cryo-EM) and can affect the amount of high-resolution information retained in the image. Yet, common data acquisition approaches in single particle cryo-EM do not take it into account. Here, we demonstrate how the sample thickness can be determined before data acquisition, allowing to identify optimal regions and restrict automated data collection to images with preserved high-resolution details. This quality over quantity approach, almost entirely eliminates the time- and storage-consuming collection of suboptimal images, which are discarded after a recorded session or during early image processing due to lack of high-resolution information. It maximizes data collection efficiency and lowers the electron microscopy time required per dataset. This strategy is especially useful, if the speed of data collection is restricted by the microscope hardware and software, or if microscope access time, data transfer, data storage and computational power are a bottleneck. SynopsisSample thickness is a key parameter in single particle cryo-electron microscopy. Determining sample thickness before data acquisition allows to target optimal areas and maximize data output quality of single particle cryo-electron microscopy sessions. Scripts and optimized workflows for EPU and SerialEM are presented and available as open-source.

biophysics↗