Abstract
In the recent years, the protein databank has been fueled by the exponential growth of high-resolution electron cryo-microscopy (cryo-EM) structures. This trend will be further accelerated through the continuous software and method developments and the increasing availability of imaging centers, which will open cryo-EM to a wide array of researchers with their diverse scientific goals and questions. Especially for structural biology of membrane proteins, cryo-EM offers significant advantages as it can overcome multiple limitations of classical methods. Most importantly, in cryo-EM, the sample is prepared as a vitrified suspension, which abolishes the need for crystallization, reduces the required sample amount and allows usage of a wide arsenal of hydrophobic environments. Despite recent improvements, high-resolution cryo-EM still poses some significant challenges, and standardized procedures, especially for the characterization of membrane proteins, are missing. While there can be no ultimate recipe toward a high-resolution cryo-EM structure for every membrane protein, certain factors seem to be universally relevant. Here, we share the protocols that have been successfully used in our laboratory. We hope that this may be a useful resource to other researchers in the field and may increase their chances of success.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Liao M, Cao E, Julius D, Cheng Y (2013) Structure of the TRPV1 ion channel determined by electron cryo-microscopy. Nature 504:107–112. https://doi.org/10.1038/nature12822
Madej MG, Ziegler CM (2018) Dawning of a new era in TRP channel structural biology by cryo-electron microscopy. Pflugers Arch Eur J Physiol 470:213–225
Liang YL, Khoshouei M, Radjainia M et al (2017) Phase-plate cryo-EM structure of a class B GPCR-G-protein complex. Nature 546:118–123. https://doi.org/10.1038/nature22327
Zhang Y, Sun B, Feng D et al (2017) Cryo-EM structure of the activated GLP-1 receptor in complex with a G protein. Nature 546:248–253. https://doi.org/10.1038/nature22394
García-Nafría J, Tate CG (2020) Cryo-electron microscopy: moving beyond X-ray crystal structures for drug receptors and drug development. Annu Rev Pharmacol Toxicol 60. https://doi.org/10.1146/annurev-pharmtox-010919-023545
Blees A, Januliene D, Hofmann T et al (2017) Structure of the human MHC-I peptide-loading complex. Nature 551:525–528. https://doi.org/10.1038/nature24627
Vinothkumar KR, Zhu J, Hirst J (2014) Architecture of mammalian respiratory complex I. Nature 515:80–84. https://doi.org/10.1038/nature13686
Gu J, Wu M, Guo R et al (2016) The architecture of the mammalian respirasome. Nature 537:639–643. https://doi.org/10.1038/nature19359
Fiedorczuk K, Letts JA, Degliesposti G et al (2016) Atomic structure of the entire mammalian mitochondrial complex i. Nature 538:406–410. https://doi.org/10.1038/nature19794
Agip A-NA, Blaza JN, Fedor JG, Hirst J (2019) Mammalian respiratory complex I through the lens of cryo-EM. Annu Rev Biophys 48:165–184. https://doi.org/10.1146/annurev-biophys-052118-115704
Zhou A, Rohou A, Schep DG et al (2015) Structure and conformational states of the bovine mitochondrial ATP synthase by cryo-EM. elife 4. https://doi.org/10.7554/eLife.10180
Allegretti M, Klusch N, Mills DJ et al (2015) Horizontal membrane-intrinsic α-helices in the stator a-subunit of an F-type ATP synthase. Nature 521:237–240. https://doi.org/10.1038/nature14185
Kühlbrandt W (2019) Structure and mechanisms of F-type ATP synthases. Annu Rev Biochem 88:515–549. https://doi.org/10.1146/annurev-biochem-013118-110903
Murphy BJ, Klusch N, Langer J et al (2019) Rotary substates of mitochondrial ATP synthase reveal the basis of flexible F1-Fo coupling. Science 364:eaaw9128
Lyons JA, Shahsavar A, Paulsen PA et al (2016) Expression strategies for structural studies of eukaryotic membrane proteins. Curr Opin Struct Biol 38:137–144. https://doi.org/10.1016/j.sbi.2016.06.011
Bayburt TH, Grinkova YV, Sligar SG (2002) Self-assembly of discoidal phospholipid bilayer nanoparticles with membrane scaffold proteins. Nano Lett 2:853–856. https://doi.org/10.1021/nl025623k
Frauenfeld J, Löving R, Armache JP et al (2016) A saposin-lipoprotein nanoparticle system for membrane proteins. Nat Methods 13:345–351. https://doi.org/10.1038/nmeth.3801
Carlson ML, Young JW, Zhao Z et al (2018) The peptidisc, a simple method for stabilizing membrane proteins in detergent-free solution. elife 7. https://doi.org/10.7554/eLife.34085
Tribet C, Audebert R, Popot JL (1996) Amphipols: polymers that keep membrane proteins soluble in aqueous solutions. Proc Natl Acad Sci U S A 93:15047–15050. https://doi.org/10.1073/pnas.93.26.15047
Tao H, Lee SCC, Moeller A et al (2013) Engineered nanostructured β-sheet peptides protect membrane proteins. Nat Methods 10:759–761. https://doi.org/10.1038/nmeth.2533
Lee SC, Knowles TJ, Postis VLG et al (2016) A method for detergent-free isolation of membrane proteins in their local lipid environment. Nat Protoc 11:1149–1162. https://doi.org/10.1038/nprot.2016.070
Scheres SHW (2016) Processing of structurally heterogeneous cryo-EM data in RELION. In: Methods in enzymology. Academic, New York, NY, pp 125–157
Grant T, Rohou A, Grigorieff N (2018) CisTEM, user-friendly software for single-particle image processing. elife 7. https://doi.org/10.7554/eLife.35383
Punjani A, Rubinstein JL, Fleet DJ, Brubaker MA (2017) CryoSPARC: algorithms for rapid unsupervised cryo-EM structure determination. Nat Methods 14:290–296. https://doi.org/10.1038/nmeth.4169
Moriya T, Saur M, Stabrin M et al (2017) High-resolution single particle analysis from electron cryo-microscopy images using SPHIRE. J Vis Exp 2017. https://doi.org/10.3791/55448
Bell JM, Chen M, Baldwin PR, Ludtke SJ (2016) High resolution single particle refinement in EMAN2.1. Methods 100:25–34. https://doi.org/10.1016/j.ymeth.2016.02.018
Scheres SHW (2012) RELION: implementation of a Bayesian approach to cryo-EM structure determination. J Struct Biol 180:519–530. https://doi.org/10.1016/j.jsb.2012.09.006
Nakane T, Kimanius D, Lindahl E, Scheres SHW (2018) Characterisation of molecular motions in cryo-EM single-particle data by multi-body refinement in RELION. elife 7. https://doi.org/10.7554/eLife.36861
Hofmann S, Januliene D, Mehdipour AR et al (2019) Conformation space of a heterodimeric ABC exporter under turnover conditions. Nature 571:580–583
Henderson R (1995) The potential and limitations of neutrons, electrons and X-rays for atomic resolution microscopy of unstained biological molecules. Q Rev Biophys 28:171–193. https://doi.org/10.1017/S003358350000305X
Khoshouei M, Radjainia M, Baumeister W, Danev R (2017) Cryo-EM structure of haemoglobin at 3.2 Å determined with the Volta phase plate. Nat Commun 8. https://doi.org/10.1038/ncomms16099
Fan X, Wang J, Zhang X et al (2019) Single particle cryo-EM reconstruction of 52 kDa streptavidin at 3.2 Angstrom resolution. Nat Commun 10. https://doi.org/10.1038/s41467-019-10368-w
Wu S, Avila-Sakar A, Kim J et al (2012) Fabs enable single particle cryoEM studies of small proteins. Structure 20:582–592. https://doi.org/10.1016/j.str.2012.02.017
Uchański T, Masiulis S, Fischer B, et al (2021) Megabodies expand the nanobody toolkit for protein structure determination by single-particle cryo-EM. Nat Methods 18:60–68. https://doi.org/10.1038/s41592-020-01001-6
Kim J, Tan YZ, Wicht KJ et al (2019) Structure and drug resistance of the Plasmodium falciparum transporter PfCRT. Nature. https://doi.org/10.1038/s41586-019-1795-x
Merk A, Bartesaghi A, Banerjee S et al (2016) Breaking cryo-EM resolution barriers to facilitate drug discovery. Cell 165:1698–1707. https://doi.org/10.1016/j.cell.2016.05.040
Bartesaghi A, Aguerrebere C, Falconieri V et al (2018) Atomic resolution cryo-EM structure of β-galactosidase. Structure 26:848–856.e3. https://doi.org/10.1016/j.str.2018.04.004
Danev R, Yanagisawa H, Kikkawa M (2019) Cryo-electron microscopy methodology: current aspects and future directions. Trends Biochem Sci 44:837–848
Zivanov J, Nakane T, Forsberg BO et al (2018) New tools for automated high-resolution cryo-EM structure determination in RELION-3. elife 7. https://doi.org/10.7554/eLife.42166
Tan YZ, Aiyer S, Mietzsch M et al (2018) Sub-2 Å Ewald curvature corrected structure of an AAV2 capsid variant. Nat Commun 9. https://doi.org/10.1038/s41467-018-06076-6
Yip KM, Fischer N, Paknia E et al (2020) Atomic-resolution protein structure determination by cryo-EM. Nature 587:157–161. https://doi.org/10.1038/s41586-020-2833-4
Nakane T, Kotecha A Sente A et al (2020) Single-particle cryo-EM at atomic resolution. Nature 587:152–156. https://doi.org/10.1038/s41586-020-2829-0
Niesen FH, Berglund H, Vedadi M (2007) The use of differential scanning fluorimetry to detect ligand interactions that promote protein stability. Nat Protoc 2:2212–2221. https://doi.org/10.1038/nprot.2007.321
Mancusso R, Karpowich NK, Czyzewski BK, Wang DN (2011) Simple screening method for improving membrane protein thermostability. Methods 55:324–329. https://doi.org/10.1016/j.ymeth.2011.07.008
Chari A, Haselbach D, Kirves JM et al (2015) ProteoPlex: stability optimization of macromolecular complexes by sparse-matrix screening of chemical space. Nat Methods 12:859–865. https://doi.org/10.1038/nmeth.3493
Kawate T, Gouaux E (2006) Fluorescence-detection size-exclusion chromatography for precrystallization screening of integral membrane proteins. Structure 14:673–681. https://doi.org/10.1016/j.str.2006.01.013
Wittig I, Braun HP, Schägger H (2006) Blue native PAGE. Nat Protoc 1:418–428. https://doi.org/10.1038/nprot.2006.62
Stetefeld J, McKenna SA, Patel TR (2016) Dynamic light scattering: a practical guide and applications in biomedical sciences. Biophys Rev 8:409–427
Kang Y, Zhou XE, Gao X et al (2015) Crystal structure of rhodopsin bound to arrestin by femtosecond X-ray laser. Nature 523:561–567. https://doi.org/10.1038/nature14656
Gewering T, Januliene D, Ries AB, Moeller A (2018) Know your detergents: a case study on detergent background in negative stain electron microscopy. J Struct Biol 203:242–246. https://doi.org/10.1016/j.jsb.2018.05.008
Moeller A, Lee SC, Tao H et al (2015) Distinct conformational spectrum of homologous multidrug ABC transporters. Structure 23:450–460. https://doi.org/10.1016/j.str.2014.12.013
Russo CJ, Passmore LA (2014) Ultrastable gold substrates for electron cryomicroscopy. Science 346:1377–1380. https://doi.org/10.1126/science.1259530
Zi Tan Y, Baldwin PR, Davis JH et al (2017) Addressing preferred specimen orientation in single-particle cryo-EMthrough tilting. Nat Methods 14:793–796. https://doi.org/10.1038/nmeth.4347
Noble AJ, Wei H, Dandey VP et al (2018) Reducing effects of particle adsorption to the air–water interface in cryo-EM. Nat Methods 15:793–795. https://doi.org/10.1038/s41592-018-0139-3
D’Imprima E, Floris D, Joppe M et al (2019) Protein denaturation at the air-water interface and how to prevent it. elife 8. https://doi.org/10.7554/eLife.42747
Armstrong M, Han B-G, Gomez S et al (2019) Micro-scale fluid behavior during cryo-EM sample blotting. Biophys J. https://doi.org/10.1016/j.bpj.2019.12.017
Razinkov I, Dandey VP, Wei H et al (2016) A new method for vitrifying samples for cryoEM. J Struct Biol 195:190–198. https://doi.org/10.1016/j.jsb.2016.06.001
Arnold SA, Albiez S, Bieri A et al (2017) Blotting-free and lossless cryo-electron microscopy grid preparation from nanoliter-sized protein samples and single-cell extracts. J Struct Biol 197:220–226. https://doi.org/10.1016/j.jsb.2016.11.002
Rubinstein JL, Guo H, Ripstein ZA et al (2019) Shake-it-off: a simple ultrasonic cryo-EM specimen-preparation device. Acta Crystallogr D Struct Biol 75:1063–1070. https://doi.org/10.1107/S2059798319014372
Tan YZ, Rubinstein JL (2020) Through-grid wicking enables high-speed cryoEM specimen preparation. Acta Crystallogr Sect D Struct Biol 76:1092–1103. https://doi.org/10.1107/s2059798320012474
Ravelli RBG, Nijpels FJT, Henderikx RJM, et al (2020) Cryo-EM structures from sub-nl volumes using pin-printing and jet vitrification. Nat Commun 11:1–9. https://doi.org/10.1038/s41467-020-16392-5
Kontziampasis D, Klebl DP, Iadanza MG, et al (2019) A cryo-EM grid preparation device for time-resolved structural studies. IUCrJ 6:1024–1031. https://doi.org/10.1107/S2052252519011345
Naydenova K, Peet MJ, Russo CJ (2019) Multifunctional graphene supports for electron cryomicroscopy. Proc Natl Acad Sci U S A 116:11718–11724. https://doi.org/10.1073/pnas.1904766116
Han Y, Fan X, Wang H et al (2019) High-yield monolayer graphene grids for near-atomic resolution cryoelectron microscopy. Proc Natl Acad Sci 2019:201919114. https://doi.org/10.1073/pnas.1919114117
Liu N, Zhang J, Chen Y, et al (2019) Bioactive Functionalized Monolayer Graphene for High-Resolution Cryo-Electron Microscopy. J Am Chem Soc 141:4016–4025. https://doi.org/10.1021/jacs.8b13038
Cheng Y, Grigorieff N, Penczek PA, Walz T (2015) A primer to single-particle cryo-electron microscopy. Cell 161:438–449
Campbell MG, Cheng A, Brilot AF et al (2012) Movies of ice-embedded particles enhance resolution in electron cryo-microscopy. Structure 20:1823–1828. https://doi.org/10.1016/j.str.2012.08.026
Huang Z, Baldwin PR, Mullapudi S, Penczek PA (2003) Automated determination of parameters describing power spectra of micrograph images in electron microscopy. J Struct Biol 144:79–94. https://doi.org/10.1016/j.jsb.2003.10.011
Rohou A, Grigorieff N (2015) CTFFIND4: fast and accurate defocus estimation from electron micrographs. J Struct Biol 192:216–221. https://doi.org/10.1016/j.jsb.2015.08.008
Zhang K (2016) Gctf: real-time CTF determination and correction. J Struct Biol 193:1–12. https://doi.org/10.1016/j.jsb.2015.11.003
Van Heel M (1982) Detection of objects in quantum-noise-limited images. Ultramicroscopy 7:331–341. https://doi.org/10.1016/0304-3991(82)90258-3
Voss NR, Yoshioka CK, Radermacher M et al (2009) DoG Picker and TiltPicker: software tools to facilitate particle selection in single particle electron microscopy. J Struct Biol 166:205–213. https://doi.org/10.1016/j.jsb.2009.01.004
Bepler T, Morin A, Rapp M et al (2019) Positive-unlabeled convolutional neural networks for particle picking in cryo-electron micrographs. Nat Methods 16:1153–1160. https://doi.org/10.1038/s41592-019-0575-8
Wagner T, Merino F, Stabrin M et al (2019) SPHIRE-crYOLO is a fast and accurate fully automated particle picker for cryo-EM. Commun Biol 2. https://doi.org/10.1038/s42003-019-0437-z
Tegunov D, Cramer P (2019) Real-time cryo-electron microscopy data preprocessing with Warp. Nat Methods 16:1146–1152. https://doi.org/10.1038/s41592-019-0580-y
Lander GC, Stagg SM, Voss NR et al (2009) Appion: an integrated, database-driven pipeline to facilitate EM image processing. J Struct Biol 166:95–102. https://doi.org/10.1016/j.jsb.2009.01.002
Li X, Zheng S, Agard DA, Cheng Y (2015) Asynchronous data acquisition and on-the-fly analysis of dose fractionated cryoEM images by UCSFImage. J Struct Biol 192:174–178. https://doi.org/10.1016/j.jsb.2015.09.003
Fernandez-Leiro R, Scheres SHW (2017) A pipeline approach to single-particle processing in RELION. Acta Crystallogr Sect D Struct Biol 2017:496–502
Gómez-Blanco J, de la Rosa-Trevín JM, Marabini R et al (2018) Using Scipion for stream image processing at Cryo-EM facilities. J Struct Biol 204:457–463. https://doi.org/10.1016/j.jsb.2018.10.001
de la Rosa-Trevín JM, Otón J, Marabini R et al (2013) Xmipp 3.0: an improved software suite for image processing in electron microscopy. J Struct Biol 184:321–328. https://doi.org/10.1016/j.jsb.2013.09.015
Reboul CF, Kiesewetter S, Eager M et al (2018) Rapid near-atomic resolution single-particle 3D reconstruction with SIMPLE. J Struct Biol 204:172–181. https://doi.org/10.1016/j.jsb.2018.08.005
Van Heel M, Harauz G, Orlova EV et al (1996) A new generation of the IMAGIC image processing system. J Struct Biol 116:17–24. https://doi.org/10.1006/jsbi.1996.0004
Grigorieff N (2007) FREALIGN: high-resolution refinement of single particle structures. J Struct Biol 157:117–125. https://doi.org/10.1016/j.jsb.2006.05.004
Hohn M, Tang G, Goodyear G et al (2007) SPARX, a new environment for Cryo-EM image processing. J Struct Biol 157:47–55. https://doi.org/10.1016/j.jsb.2006.07.003
Baxter WT, Leith AD, Frank J (2007) SPIRE: the SPIDER reconstruction engine. J Struct Biol 157:56–63. https://doi.org/10.1016/j.jsb.2006.07.019
Heymann JB, Belnap DM (2007) Bsoft: Image processing and molecular modeling for electron microscopy. J Struct Biol 157:3–18. https://doi.org/10.1016/j.jsb.2006.06.006
Timcenko M, Lyons JA, Januliene D et al (2019) Structure and autoregulation of a P4-ATPase lipid flippase. Nature. https://doi.org/10.1038/s41586-019-1344-7
Booth DS, Avila-Sakar A, Cheng Y (2011) Visualizing proteins and macromolecular complexes by negative stain EM: from grid preparation to image acquisition. J Vis Exp. https://doi.org/10.3791/3227
Ohi M, Li Y, Cheng Y, Walz T (2004) Negative staining and image classification – powerful tools in modern electron microscopy. Biol Proced Online 6:23–34. https://doi.org/10.1251/bpo70
Briggs JAG, Huiskonen JT, Fernando KV et al (2005) Classification and three-dimensional reconstruction of unevenly distributed or symmetry mismatched features of icosahedral particles. J Struct Biol 150:332–339. https://doi.org/10.1016/j.jsb.2005.03.009
Serna M (2019) Hands on methods for high resolution cryo-electron microscopy structures of heterogeneous macromolecular complexes. Front Mol Biosci 6. https://doi.org/10.3389/fmolb.2019.00033
Kastner B, Fischer N, Golas MM et al (2008) GraFix: sample preparation for single-particle electron cryomicroscopy. Nat Methods 5:53–55. https://doi.org/10.1038/nmeth1139
Stark H (2010) GraFix: Stabilization of fragile macromolecular complexes for single particle Cryo-EM. Methods in Enzymology. Academic Press Inc., In, pp 109–126
Suloway C, Pulokas J, Fellmann D et al (2005) Automated molecular microscopy: the new Leginon system. J Struct Biol 151:41–60. https://doi.org/10.1016/j.jsb.2005.03.010
Zheng SQ, Palovcak E, Armache JP et al (2017) MotionCor2: anisotropic correction of beam-induced motion for improved cryo-electron microscopy. Nat Methods 14:331–332
Zivanov J, Nakane T, Scheres SHW (2019) A Bayesian approach to beam-induced motion correction in cryo-EM single-particle analysis. IUCrJ 6:5–17. https://doi.org/10.1107/S205225251801463X
Pettersen EF, Goddard TD, Huang CC, et al (2004) UCSF Chimera – A visualization system for exploratory research and analysis. J Comput Chem 25:1605–1612. https://doi.org/10.1002/jcc.20084
Punjani A, Zhang H, Fleet DJ (2020) Non-uniform refinement: adaptive regularization improves single-particle cryo-EM reconstruction. Nat Methods 17:1214–1221. https://doi.org/10.1038/s41592-020-00990-8
Acknowledgments
We are grateful for funding through the DFG Mo2752/2, the Cluster of Excellence Frankfurt EXC 115, as well as support from the Max Planck Society. We would like to thank Deryck Mills and Prof. Werner Kühlbrandt for their support and access to the outstanding cryo-EM facility.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Science+Business Media, LLC, part of Springer Nature
About this protocol
Cite this protocol
Januliene, D., Moeller, A. (2021). Single-Particle Cryo-EM of Membrane Proteins. In: Schmidt-Krey, I., Gumbart, J.C. (eds) Structure and Function of Membrane Proteins. Methods in Molecular Biology, vol 2302. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1394-8_9
Download citation
DOI: https://doi.org/10.1007/978-1-0716-1394-8_9
Published:
Publisher Name: Humana, New York, NY
Print ISBN: 978-1-0716-1393-1
Online ISBN: 978-1-0716-1394-8
eBook Packages: Springer Protocols