{"language":[{"iso":"eng"}],"article_number":"102139","_id":"9205","ec_funded":1,"article_type":"original","citation":{"ieee":"D. Kampjut, J. Steiner, and L. A. Sazanov, “Cryo-EM grid optimization for membrane proteins,” <i>iScience</i>, vol. 24, no. 3. Elsevier, 2021.","mla":"Kampjut, Domen, et al. “Cryo-EM Grid Optimization for Membrane Proteins.” <i>IScience</i>, vol. 24, no. 3, 102139, Elsevier, 2021, doi:<a href=\"https://doi.org/10.1016/j.isci.2021.102139\">10.1016/j.isci.2021.102139</a>.","short":"D. Kampjut, J. Steiner, L.A. Sazanov, IScience 24 (2021).","ista":"Kampjut D, Steiner J, Sazanov LA. 2021. Cryo-EM grid optimization for membrane proteins. iScience. 24(3), 102139.","apa":"Kampjut, D., Steiner, J., &#38; Sazanov, L. A. (2021). Cryo-EM grid optimization for membrane proteins. <i>IScience</i>. Elsevier. <a href=\"https://doi.org/10.1016/j.isci.2021.102139\">https://doi.org/10.1016/j.isci.2021.102139</a>","chicago":"Kampjut, Domen, Julia Steiner, and Leonid A Sazanov. “Cryo-EM Grid Optimization for Membrane Proteins.” <i>IScience</i>. Elsevier, 2021. <a href=\"https://doi.org/10.1016/j.isci.2021.102139\">https://doi.org/10.1016/j.isci.2021.102139</a>.","ama":"Kampjut D, Steiner J, Sazanov LA. Cryo-EM grid optimization for membrane proteins. <i>iScience</i>. 2021;24(3). doi:<a href=\"https://doi.org/10.1016/j.isci.2021.102139\">10.1016/j.isci.2021.102139</a>"},"external_id":{"isi":["000631646000012"],"pmid":["33665558"]},"publication_identifier":{"eissn":["25890042"]},"doi":"10.1016/j.isci.2021.102139","has_accepted_license":"1","publication":"iScience","author":[{"full_name":"Kampjut, Domen","id":"37233050-F248-11E8-B48F-1D18A9856A87","first_name":"Domen","last_name":"Kampjut"},{"first_name":"Julia","last_name":"Steiner","id":"3BB67EB0-F248-11E8-B48F-1D18A9856A87","full_name":"Steiner, Julia"},{"orcid":"0000-0002-0977-7989","id":"338D39FE-F248-11E8-B48F-1D18A9856A87","full_name":"Sazanov, Leonid A","first_name":"Leonid A","last_name":"Sazanov"}],"ddc":["570"],"project":[{"_id":"2564DBCA-B435-11E9-9278-68D0E5697425","name":"International IST Doctoral Program","grant_number":"665385","call_identifier":"H2020"}],"acknowledgement":"We thank the Electron Microscopy Facilities at the Institute of Science and Technology Austria and at the Vienna Biocenter for providing access and training for the electron microscopes. This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement no. 665385 .","isi":1,"file_date_updated":"2021-03-03T07:38:14Z","year":"2021","acknowledged_ssus":[{"_id":"EM-Fac"}],"intvolume":"        24","volume":24,"department":[{"_id":"LeSa"}],"abstract":[{"text":"Cryo-EM grid preparation is an important bottleneck in protein structure determination, especially for membrane proteins, typically requiring screening of a large number of conditions. We systematically investigated the effects of buffer components, blotting conditions and grid types on the outcome of grid preparation of five different membrane protein samples. Aggregation was the most common type of problem which was addressed by changing detergents, salt concentration or reconstitution of proteins into nanodiscs or amphipols. We show that the optimal concentration of detergent is between 0.05 and 0.4% and that the presence of a low concentration of detergent with a high critical micellar concentration protects the proteins from denaturation at the air-water interface. Furthermore, we discuss the strategies for achieving an adequate ice thickness, particle coverage and orientation distribution on free ice and on support films. Our findings provide a clear roadmap for comprehensive screening of conditions for cryo-EM grid preparation of membrane proteins.","lang":"eng"}],"publication_status":"published","date_published":"2021-03-19T00:00:00Z","issue":"3","article_processing_charge":"No","month":"03","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode","image":"/images/cc_by_nc_nd.png","name":"Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)","short":"CC BY-NC-ND (4.0)"},"date_updated":"2023-08-07T13:54:06Z","pmid":1,"file":[{"date_updated":"2021-03-03T07:38:14Z","file_id":"9219","success":1,"date_created":"2021-03-03T07:38:14Z","file_size":7431411,"relation":"main_file","checksum":"50585447386fe5842f07ab9b3a66e7e9","content_type":"application/pdf","file_name":"2021_iScience_Kampjut.pdf","access_level":"open_access","creator":"dernst"}],"type":"journal_article","license":"https://creativecommons.org/licenses/by-nc-nd/4.0/","day":"19","title":"Cryo-EM grid optimization for membrane proteins","quality_controlled":"1","status":"public","publisher":"Elsevier","scopus_import":"1","oa":1,"oa_version":"Published Version","user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","date_created":"2021-02-28T23:01:24Z"}