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10.3791/62383 http://scihub22266oqcxt.onion/10.3791/62383 33818563!ä!33818563 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       J+Vis+Exp 2021 ; ä (169): ä Nephropedia Template TP {{tp|p=33818563|t=2021. Strategies for Optimization of Cryogenic Electron Tomography Data Acquisition |pdf=|usr=}}{{33818563}} gab.com Text Strategies for Optimization of Cryogenic Electron Tomography Data Acquisition JO: J Vis Exp http://www.kidney.de/pget.php?&tw=1&pmid=33818563 #FOAvip Cryogenic electron tomography (cryoET) is a powerful method to study the 3D structure of biological samples in a close-to-native state. Current state-of-the-art cryoET combined with subtomogram averaging analysis enables the high-resolution structural determination of macromolecular complexes that are present in multiple copies within tomographic reconstructions. Tomographic experiments usually require a vast amount of tilt series to be acquired by means of high-end transmission electron microscopes with important operational running-costs. Although the throughput and reliability of automated data acquisition routines have constantly improved over the recent years, the process of selecting regions of interest at which a tilt series will be acquired cannot be easily automated and it still relies on the user's manual input. Therefore, the set-up of a large-scale data collection session is a time-consuming procedure that can considerably reduce the remaining microscope time available for tilt series acquisition. Here, the protocol describes the recently developed implementations based on the SerialEM package and the PyEM software that significantly improve the time-efficiency of grid screening and large-scale tilt series data collection. The presented protocol illustrates how to use SerialEM scripting functionalities to fully automate grid mapping, grid square mapping, and tilt series acquisition. Furthermore, the protocol describes how to use PyEM to select additional acquisition targets in off-line mode after automated data collection is initiated. To illustrate this protocol, its application in the context of high-end data collection of Sars-Cov-2 tilt series is described. The presented pipeline is particularly suited to maximizing the time-efficiency of tomography experiments that require a careful selection of acquisition targets and at the same time a large amount of tilt series to be collected. Twit Text FOAVip Strategies for Optimization of Cryogenic Electron Tomography Data Acquisition ????J Vis Exp http://www.kidney.de/pget.php?&tw=1&pmid=33818563 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33818563 #FOAvip English Wikipedia <ref>{{Cite pmid|33818563}}</ref> Strategies for Optimization of Cryogenic Electron Tomography Data Acquisition #MMPMID33818563 Weis F; Hagen WJH; Schorb M; Mattei S J Vis Exp 2021[Mar]; ä (169): ä PMID33818563show ga Cryogenic electron tomography (cryoET) is a powerful method to study the 3D structure of biological samples in a close-to-native state. Current state-of-the-art cryoET combined with subtomogram averaging analysis enables the high-resolution structural determination of macromolecular complexes that are present in multiple copies within tomographic reconstructions. Tomographic experiments usually require a vast amount of tilt series to be acquired by means of high-end transmission electron microscopes with important operational running-costs. Although the throughput and reliability of automated data acquisition routines have constantly improved over the recent years, the process of selecting regions of interest at which a tilt series will be acquired cannot be easily automated and it still relies on the user's manual input. Therefore, the set-up of a large-scale data collection session is a time-consuming procedure that can considerably reduce the remaining microscope time available for tilt series acquisition. Here, the protocol describes the recently developed implementations based on the SerialEM package and the PyEM software that significantly improve the time-efficiency of grid screening and large-scale tilt series data collection. The presented protocol illustrates how to use SerialEM scripting functionalities to fully automate grid mapping, grid square mapping, and tilt series acquisition. Furthermore, the protocol describes how to use PyEM to select additional acquisition targets in off-line mode after automated data collection is initiated. To illustrate this protocol, its application in the context of high-end data collection of Sars-Cov-2 tilt series is described. The presented pipeline is particularly suited to maximizing the time-efficiency of tomography experiments that require a careful selection of acquisition targets and at the same time a large amount of tilt series to be collected. |*SARS-CoV-2[MESH] |Cryoelectron Microscopy/*methods[MESH] |Electron Microscope Tomography/*methods[MESH] |Image Processing, Computer-Assisted/methods[MESH] |Macromolecular Substances[MESH] |Reproducibility of Results[MESH]Strategies for Optimization of Cryogenic Electron Tomography Data Acqu(epmc).pdf DeepDyve Pubget Overpricing