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MISO: microfluidic protein isolation enables single-particle cryo-EM structure determination from a single cell colony

Nature Methods volume 22, pages 2563–2573 (2025)Cite this article

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Abstract

Single-particle cryogenic electron microscopy (cryo-EM) enables reconstruction of atomic-resolution 3D maps of proteins by visualizing thousands to millions of purified protein particles embedded in vitreous ice. This corresponds to picograms of purified protein, which can potentially be isolated from a few thousand cells. Hence, cryo-EM holds the potential of a very sensitive analytical method for delivering high-resolution protein structure as a readout. In practice, millions of times more starting biological material is required to prepare cryo-EM grids. Here we show that using a micro isolation (MISO) method, which combines microfluidics-based protein purification with cryo-EM grid preparation, cryo-EM structures of soluble bacterial and eukaryotic membrane proteins can be solved starting from less than 1 µg of a target protein and progressing from cells to cryo-EM grids within a few hours. This scales down the amount of starting biological material hundreds to thousands of times, opening possibilities for the structural characterization of hitherto inaccessible proteins.

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Fig. 1: MISO principle and method characterization.
Fig. 2: Purification and cryo-EM structure of β-galactosidase isolated from 20 μg-containing cell extract.
Fig. 3: Structure of β-galactosidase solved starting from a single E. coli colony.
Fig. 4: Preparation and structure determination of btTMEM206 by conventional and MISO purification approaches.
Fig. 5: Determination of mTMEM16F structure using one dish of HEK cells.
Fig. 6: Purification and identification of TRPC6 channel.

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Data availability

The protein models with the PDB accession codes 1F4A, 6P46 and 6UZ8 were used in this study. The newly generated cryo-EM-refined atomic models, density maps and raw data were deposited in the PDB, EMDB and EMPIAR databases under accession codes: βG from 20 μg 9HPL, EMD-52333, EMPIAR-12734; βG from 1 μg 9HPM, EMD-52334, EMPIAR-12740; btTMEM206 conventional 9HQN, EMD-52344, EMPIAR-12773; btTMEM206–YFP MISO 9HQO, EMD-52345, EMPIAR-12769; mTMEM16F–YFP 9HQP, EMD-52346, EMPIAR-12757; TRPC6 EMD-52486, EMD-52487, EMPIAR-12770. Source data are provided with this paper.

Code availability

The LabVIEW code to run MISO device is available at https://github.com/EfremovLab/MISO.

References

  1. de la Cruz, M. J. & Eng, E. T. Scaling up cryo-EM for biology and chemistry: the journey from niche technology to mainstream method. Structure 31, 1487–1498 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  2. Zhu, K.-F. et al. Applications and prospects of cryo-EM in drug discovery. Mil. Med. Res. 10, 10 (2023).

    CAS  PubMed  PubMed Central  Google Scholar 

  3. Henderson, R. The potential and limitations of neutrons, electrons and X-rays for atomic resolution microscopy of unstained biological molecules. Q. Rev. Biophys. 28, 171–193 (1995).

    Article  CAS  PubMed  Google Scholar 

  4. Vinothkumar, K. R. & Henderson, R. Single particle electron cryomicroscopy: trends, issues and future perspective. Q. Rev. Biophys. 49, e13 (2016).

    Article  PubMed  Google Scholar 

  5. Grigorieff, N. Direct detection pays off for electron cryo-microscopy. eLife 2, e00573 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  6. Suloway, C. et al. Automated molecular microscopy: the new Leginon system. J. Struct. Biol. 151, 41–60 (2005).

    Article  CAS  PubMed  Google Scholar 

  7. Mastronarde, D. N. Automated electron microscope tomography using robust prediction of specimen movements. J. Struct. Biol. 152, 36–51 (2005).

    Article  PubMed  Google Scholar 

  8. Bouvette, J. et al. Automated systematic evaluation of cryo-EM specimens with SmartScope. eLife 11, e80047 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Cheng, A. et al. Fully automated multi-grid cryoEM screening using Smart Leginon. IUCrJ 10, 77–89 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Punjani, A., Rubinstein, J. L., Fleet, D. J. & Brubaker, M. A. CryoSPARC: algorithms for rapid unsupervised cryo-EM structure determination. Nat. Methods 14, 290–296 (2017).

    Article  CAS  PubMed  Google Scholar 

  11. Gómez-Blanco, J. et al. Using Scipion for stream image processing at cryo-EM facilities. J. Struct. Biol. 204, 457–463 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  12. Kimanius, D., Dong, L., Sharov, G., Nakane, T. & Scheres, S. H. W. New tools for automated cryo-EM single-particle analysis in RELION-4.0. Biochem. J. 478, 4169–4185 (2021).

    Article  CAS  PubMed  Google Scholar 

  13. Jamali, K. et al. Automated model building and protein identification in cryo-EM maps. Nature 628, 450–457 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Croll, T. I. ISOLDE: a physically realistic environment for model building into low-resolution electron-density maps. Acta Crystallogr. D 74, 519–530 (2018).

    Article  CAS  Google Scholar 

  15. Zwart, P. H. et al. Automated structure solution with the PHENIX suite. Methods Mol. Biol. 426, 419–435 (2008).

    Article  CAS  PubMed  Google Scholar 

  16. Terwilliger, T. C. et al. Improved AlphaFold modeling with implicit experimental information. Nat. Methods 19, 1376–1382 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. McMullan, G. et al. Structure determination by cryoEM at 100 keV. Proc. Natl Acad. Sci. USA 120, e2312905120 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Karia, D. et al. Sub-3 Å resolution protein structure determination by single-particle cryo-EM at 100 keV. Structure 33, 1717–1727.e4 (2025).

    Article  CAS  PubMed  Google Scholar 

  19. D'Imprima, E. et al. Protein denaturation at the air-water interface and how to prevent it. eLife 8, e42747 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  20. Noble, A. J. et al. Reducing effects of particle adsorption to the air–water interface in cryo-EM. Nat. Methods 15, 793–795 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Noble, A. J. et al. Routine single particle cryoEM sample and grid characterization by tomography. eLife 7, e34257 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  22. Zheng, L. et al. Uniform thin ice on ultraflat graphene for high-resolution cryo-EM. Nat. Methods 20, 123–130 (2023).

    Article  CAS  PubMed  Google Scholar 

  23. Russo, C. J. & Passmore, L. A. Ultrastable gold substrates for electron cryomicroscopy. Science 346, 1377–1380 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Naydenova, K., Jia, P. & Russo, C. J. Cryo-EM with sub–1 Å specimen movement. Science 370, 223–226 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Huber, S. T. et al. Nanofluidic chips for cryo-EM structure determination from picoliter sample volumes. eLife 11, e72629 (2022).

  26. Naydenova, K., Peet, M. J. & Russo, C. J. Multifunctional graphene supports for electron cryomicroscopy. Proc. Natl Acad. Sci. USA 116, 11718–11724 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Pantelic, R. S., Meyer, J. C., Kaiser, U., Baumeister, W. & Plitzko, J. M. Graphene oxide: a substrate for optimizing preparations of frozen-hydrated samples. J. Struct. Biol. 170, 152–156 (2010).

    Article  CAS  PubMed  Google Scholar 

  28. Wang, F. et al. General and robust covalently linked graphene oxide affinity grids for high-resolution cryo-EM. Proc. Natl Acad. Sci. USA 117, 24269–24273 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Sader, K., Stopps, M., Calder, L. J. & Rosenthal, P. B. Cryomicroscopy of radiation sensitive specimens on unmodified graphene sheets: reduction of electron-optical effects of charging. J. Struct. Biol. 183, 531–536 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Jain, T., Sheehan, P., Crum, J., Carragher, B. & Potter, C. S. Spotiton: a prototype for an integrated inkjet dispense and vitrification system for cryo-TEM. J. Struct. Biol. 179, 68–75 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  31. Rubinstein, J. L. et al. Shake-it-off: a simple ultrasonic cryo-EM specimen-preparation device. Acta Crystallogr. D 75, 1063–1070 (2019).

    Article  CAS  Google Scholar 

  32. Dubochet, J. et al. Cryo-electron microscopy of vitrified specimens. Q. Rev. Biophys. 21, 129–228 (1988).

    Article  CAS  PubMed  Google Scholar 

  33. Henderikx, R. J. M. et al. VitroJet: new features and case studies. Acta Crystallogr. D 80, 232–246 (2024).

    Article  CAS  Google Scholar 

  34. Ravelli, R. B. G. et al. Cryo-EM structures from sub-nl volumes using pin-printing and jet vitrification. Nat. Commun. 11, 2563 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Arnold, S. A. et al. Total sample conditioning and preparation of nanoliter volumes for electron microscopy. ACS Nano 10, 4981–4988 (2016).

    Article  CAS  PubMed  Google Scholar 

  36. Arnold, S. A. et al. Blotting-free and lossless cryo-electron microscopy grid preparation from nanoliter-sized protein samples and single-cell extracts. J. Struct. Biol. 197, 220–226 (2016).

  37. Schmidli, C. et al. Microfluidic protein isolation and sample preparation for high-resolution cryo-EM. Proc. Natl Acad. Sci. USA 116, 15007–15012 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Kelly, D. F., Abeyrathne, P. D., Dukovski, D. & Walz, T. The affinity grid: a pre-fabricated EM grid for monolayer purification. J. Mol. Biol. 382, 423–433 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Yu, G., Li, K. & Jiang, W. Antibody-based affinity cryo-EM grid. Methods 100, 16–24 (2016).

  40. Arnold, S. A. et al. Miniaturizing EM sample preparation: opportunities, challenges and “visual proteomics”. Proteomics 18, 1700120–1700176 (2018).

  41. Duffy, D. C., McDonald, J. C., Schueller, O. J. A. & Whitesides, G. M. Rapid prototyping of microfluidic systems in poly(dimethylsiloxane). Anal. Chem. 70, 4974–4984 (1998).

    Article  CAS  PubMed  Google Scholar 

  42. Weerappuli, P., Kojima, T., Takayama, S. & Basu, A. Novel monolithic "slightly-open doormat" (SOD) valve enables efficient fabrication of highly-scalable microfluidic gas-on-gas multiplexer. Sens Actuators B 297, 126776 (2019).

    Article  CAS  Google Scholar 

  43. Datta, S. & Ghosal, S. Characterizing dispersion in microfluidic channels. Lab Chip 9, 2537 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Bartesaghi, A. et al. 2.2 Å resolution cryo-EM structure of β-galactosidase in complex with a cell-permeant inhibitor. Science 348, 1147–1151 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Torino, S., Dhurandhar, M., Stroobants, A., Claessens, R. & Efremov, R. G. Time-resolved cryo-EM using a combination of droplet microfluidics with on-demand jetting. Nat. Methods 20, 1400–1408 (2023).

    Article  CAS  PubMed  Google Scholar 

  46. Wetzl, B. K., Yarmoluk, S. M., Craig, D. B. & Wolfbeis, O. S. Chameleon labels for staining and quantifying proteins. Angew. Chem. Int. Ed. 43, 5400–5402 (2004).

    Article  CAS  Google Scholar 

  47. Juers, D. H. et al. High resolution refinement of beta-galactosidase in a new crystal form reveals multiple metal-binding sites and provides a structural basis for alpha-complementation. Protein Sci. 9, 1685–1699 (2000).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Mira, P., Yeh, P. & Hall, B. G. Estimating microbial population data from optical density. PLoS ONE 17, e0276040 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Ruan, Z., Osei-Owusu, J., Du, J., Qiu, Z. & Lü, W. Structures and pH-sensing mechanism of the proton-activated chloride channel. Nature 588, 350–354 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Deng, Z. et al. Cryo-EM structure of a proton-activated chloride channel TMEM206. Sci. Adv. 7, eabe5983 (2021).

  51. Wang, C., Polovitskaya, M. M., Delgado, B. D., Jentsch, T. J. & Long, S. B. Gating choreography and mechanism of the human proton-activated chloride channel ASOR. Sci. Adv. 8, 3942 (2022).

    Article  Google Scholar 

  52. Ullrich, F. et al. Identification of TMEM206 proteins as pore of PAORAC/ASOR acid-sensitive chloride channels. eLife 8, e49187 (2019).

  53. Suzuki, J., Umeda, M., Sims, P. J. & Nagata, S. Calcium-dependent phospholipid scrambling by TMEM16F. Nature 468, 834–838 (2010).

    Article  CAS  PubMed  Google Scholar 

  54. Lhermusier, T., Chap, H. & Payrastre, B. Platelet membrane phospholipid asymmetry: from the characterization of a scramblase activity to the identification of an essential protein mutated in Scott syndrome. J. Thromb. Haemost. 9, 1883–1891 (2011).

    Article  CAS  PubMed  Google Scholar 

  55. Braga, L. et al. Drugs that inhibit TMEM16 proteins block SARS-CoV-2 spike-induced syncytia. Nature 594, 88–93 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Alvadia, C. et al. Cryo-EM structures and functional characterization of the murine lipid scramblase TMEM16F. eLife 8, e44365 (2019).

  57. Brunner, J. D., Lim, N. K., Schenck, S., Duerst, A. & Dutzler, R. X-ray structure of a calcium-activated TMEM16 lipid scramblase. Nature 516, 207–212 (2014).

    Article  CAS  PubMed  Google Scholar 

  58. Mistry, J., Finn, R. D., Eddy, S. R., Bateman, A. & Punta, M. Challenges in homology search: HMMER3 and convergent evolution of coiled-coil regions. Nucleic Acids Res. 41, e121 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Giss, D., Kemmerling, S., Dandey, V., Stahlberg, H. & Braun, T. Exploring the interactome: microfluidic isolation of proteins and interacting partners for quantitative analysis by electron microscopy. Anal. Chem. 86, 4680–4687 (2014).

    Article  CAS  PubMed  Google Scholar 

  60. Kastner, B. et al. GraFix: sample preparation for single-particle electron cryomicroscopy. Nat. Methods 5, 53–55 (2007).

    Article  PubMed  Google Scholar 

  61. Hauer, F. et al. GraDeR: membrane protein complex preparation for single-particle cryo-EM. Structure 23, 1769–1775 (2015).

    Article  CAS  PubMed  Google Scholar 

  62. Lomeli, G. & Herr, A. E. Reducing cathodic drift during isoelectric focusing using microscale immobilized pH gradient gels. Anal. Chem. 96, 8648–8656 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Sharma, H. et al. A scalable high-throughput isoelectric fractionation platform for extracellular nanocarriers: comprehensive and bias-free isolation of ribonucleoproteins from plasma, urine, and saliva. ACS Nano 17, 9388–9404 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Bhattacharjee, S. et al. Time resolution in cryo-EM using a PDMS-based microfluidic chip assembly and its application to the study of HflX-mediated ribosome recycling. Cell 187, 782–796 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Rashid, S., Ward-Bond, J., Krupin, O. & Berini, P. Non-specific adsorption of protein to microfluidic materials. Colloids Surf. B 208, 112138 (2021).

    Article  CAS  Google Scholar 

  66. Ettre, L. S. Nomenclature for chromatography (IUPAC Recommendations 1993). Pure Appl. Chem. 65, 819–872 (1993).

    Article  CAS  Google Scholar 

  67. Meier, R. J., Steiner, M.-S., Duerkop, A. & Wolfbeis, O. S. SDS–PAGE of proteins using a chameleon-type of fluorescent prestain. Anal. Chem. 80, 6274–6279 (2008).

    Article  CAS  PubMed  Google Scholar 

  68. Geertsma, E. R. & Dutzler, R. A versatile and efficient high-throughput cloning tool for structural biology. Biochemistry 50, 3272–3278 (2011).

    Article  CAS  PubMed  Google Scholar 

  69. Casañal, A., Lohkamp, B. & Emsley, P. Current developments in Coot for macromolecular model building of electron cryo-microscopy and crystallographic data. Protein Sci. 29, 1069–1078 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  70. Liebschner, D. et al. Macromolecular structure determination using X-rays, neutrons and electrons: recent developments in Phenix. Acta Crystallogr. D 75, 861–877 (2019).

    Article  CAS  Google Scholar 

  71. Brown, A. et al. Tools for macromolecular model building and refinement into electron cryo-microscopy reconstructions. Acta Crystallogr. D 71, 136–153 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Feng, S. et al. Cryo-EM studies of TMEM16F calcium-activated ion channel suggest features important for lipid scrambling. Cell Rep. 28, 567–579 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Pettersen, E. F. et al. UCSF ChimeraX: structure visualization for researchers, educators, and developers. Protein Sci. 30, 70–82 (2021).

    Article  CAS  PubMed  Google Scholar 

  74. Bai, Y. et al. Structural basis for pharmacological modulation of the TRPC6 channel. eLife 9, e53311 (2020).

  75. Williams, C. J. et al. MolProbity: more and better reference data for improved all-atom structure validation. Protein Sci. 27, 293–315 (2018).

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

We thank P. Kolata for assistance with the assembly of the MISO device, R. Claessens for advising on the design of the light detector and M. Fislage for assistance with cryo-EM data collection. We acknowledge the funding provided by Vlaams Instituut Voor Biotechnologie, Fonds Wetenschappelijk Onderzoek (grant nos. G0H5916N, G054617N to R.G.E.), and by the European Research Council (grant no. 726436 to R.G.E.). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

Author information

Authors and Affiliations

  1. Center for Structural Biology, Vlaams Instituut voor Biotechnologie, Brussels, Belgium

    Gangadhar Eluru, Steven De Gieter, Stephan Schenck, Annelore Stroobants, Janine D. Brunner & Rouslan G. Efremov

  2. Structural Biology Brussels, Department of Bioengineering Sciences, Vrije Universiteit Brussel, Brussels, Belgium

    Gangadhar Eluru, Steven De Gieter, Stephan Schenck, Annelore Stroobants, Janine D. Brunner & Rouslan G. Efremov

  3. Protein Sciences, DSc, Biomedical Research, Novartis, Basel, Switzerland

    Binesh Shrestha & Paul Erbel

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Contributions

G.E. developed the microfluidic chip, instrument and software. G.E. and R.G.E. designed and constructed the plunger device. G.E. characterized and optimized the operation of MISO chips and the plunger. G.E. and S.D.G. characterized the MISO chip. A.S. fabricated MISO chips and prepared E. coli cells expressing βG. S.S. and J.D.B. designed the constructs for TMEM206 and TMEM16F, generated the stable cell lines, and established purification conditions for btTMEM206 and mTMEM16F. B.S. and P.E. provided cells and purification protocols for TRPC6. S.S. and J.D.B. purified and plunged btTMEM206 using the conventional approach. G.E. and S.D.G. optimized MISO purification protocols. G.E. performed MISO experiments with β-galactosidase, btTMEM206 and TMEM16F. S.D.G. performed MISO experiments with TRPC6. G.E., S.D.G. and J.D.B. collected and processed cryo-EM data. S.D.G. built, refined and validated atomic models. R.G.E. prepared the original paper draft. R.G.E., G.E., S.D.G., S.S. and J.D.B. prepared figures and reviewed and edited the paper. R.G.E. conceived, managed and supervised the project, and acquired funding.

Corresponding author

Correspondence to Rouslan G. Efremov.

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Competing interests

G.E. and R.G.E. are inventors on the patent application WO2023/232662/A1 disclosing the MISO instrument and chip design filed by VIB and VUB. The other authors declare no competing interests.

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Nature Methods thanks Thomas Braun and Arjen Jakobi for their contribution to the peer review of this work. Peer reviewer reports are available. Primary Handling Editor: Arunima Singh, in collaboration with the Nature Methods team.

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Extended data

Extended Data Fig. 1 Experimental setup.

a, An overview of the experimental setup. b, Close-up of the MISO chip and plunger module. Key elements are labeled.

Extended Data Fig. 2 Layout of MISO chips.

a, b, Chip photograph and schematics of chip elements for a 2-column MISO chip. c, d, Chip photograph and schematics of chip elements for a 1-column MISO chip. Three single-column microfluidics circuits with columns of 0.5, 3 and 10 μl were designed on a single chip. The valves are shown as red circles, and pneumatic channels are not shown in the schematics of the b and d panels. The following abbreviations are used: IN – inlet, WO – waste outlet, CF- column filling port, DZ – detection zone. In a and c, long graduations of the ruler correspond to 1 cm. The chip designs are provided as Supplementary Data 1.

Extended Data Fig. 3 Processing of β-galactosidase data for cryo-EM sample prepared starting from 20 μg βG containing cytoplasmic extract.

a, A micrograph; representative from n > 3000 micrographs. b, 2D class averages. The box size is 278 Å. c, Image processing scheme. d, Fourier Shell Correlation curves for unmasked and masked half-maps and between model and map. e, Heat map shows the distribution of particle orientations. f, 3D map surface colored by local resolution.

Extended Data Fig. 4 Processing of β-galactosidase data for cryo-EM sample prepared starting from 1 μg βG containing cytoplasmic extract.

a, A micrograph; representative from n > 5000 micrographs. b, 2D class averages. The box size is 280 Å. c, Image processing scheme. d, Fourier Shell Correlation curves for unmasked and masked half-maps and between model and map. e, Heat map shows distribution of particle orientations. f, 3D map surface colored by local resolution.

Extended Data Fig. 5 Processing of TMEM206 purified and plunged using the conventional approach.

a, A micrograph; representative from n > 5000 micrographs. b, Selected 2D class averages. The box size is 304 Å. c, Image processing scheme. d, Fourier Shell Correlation curves for unmasked and masked half-maps and between model and map. e, The heat map shows distribution of particle orientations. f, 3D map surface colored by local resolution.

Extended Data Fig. 6 Processing of TMEM206-YFP purified and plunged using MISO.

a, A micrograph; representative from n > 7000 micrographs. b, Selected 2D class averages. The box size is 278 Å. c, Image processing scheme. d, Fourier Shell Correlation curves for unmasked and masked half-maps and between model and map. e, Heat map shows the distribution of particle orientations. f, 3D map surface colored by local resolution.

Extended Data Fig. 7 Processing of TMEM16F-YFP purified and plunged using MISO.

a, A micrograph; representative from n > 12000 micrographs. b, Selected 2D class averages. The box size is 278 Å. c, Image processing scheme. d, Fourier Shell Correlation curves for unmasked and masked half-maps and between model and map. e, Heat map shows distribution of particle orientations. f, 3D map surface colored by local resolution.

Extended Data Fig. 8 Processing of TRPC6.

a, A cryo-EM micrograph (representative from n > 4000 micrographs) and, b 2D class averages. The box size is 288 Å. c, Image processing scheme. d, g, Heat maps show distribution of particle orientations for soluble domain and complete trans-membrane complex, respectively. e, h Fourier Shell Correlation curves for unmasked and masked half-maps. f, i, 3D map surfaces colored by local resolution.

Extended Data Fig. 9 Identification of the TRPC6 by sequencing cryo-EM map.

a, ModelAngelo modelled a sequence of 151 HHM segments into a reconstructed cryo-EM map of the protein of interest. TRPC6 was identified as the highest likelihood target upon HHM profiles searched against the HMMER v3.3 reference proteome database. hTRPC6 was refined into the density (pink) and superimposed onto hTRPC6 (PDB 6UZ8, grey). b, Examples of density map regions with ModelAngelo sculptured fragments. c, Examples of HMMR search results for 2 sequences against the database.

Extended Data Table 1 Cryo-EM data collection, refinement and validation statistics
Full size table

Supplementary information

Supplementary Information

Supplementary Note, Figs. 1–9 and uncropped scans of gels.

Reporting Summary

Peer Review File

Supplementary Video 1

Blotless deposition of protein solution on EM grid through capillary from MISO chip.

Supplementary Video 2

MISO protein deposition on EM grid, blotting and plunging.

Supplementary Data 1

AutoCAD files in.dwg format containing MISO chip designs.

Supplementary Data

Numerical source data for Supplementary Figs. 1 and 6.

Source data

Source Data Fig. 1

Chromatograms and plots.

Source Data Fig. 1

Unprocessed gels.

Source Data Fig. 2

Chromatogram.

Source Data Fig. 2

Unprocessed gels.

Source Data Fig. 3

Chromatogram.

Source Data Fig. 3

Unprocessed gels.

Source Data Fig. 4

Chromatogram.

Source Data Fig. 4

Unprocessed gels.

Source Data Fig. 5

Chromatogram.

Source Data Fig. 5

Unprocessed gels.

Source Data Fig. 6

Chromatogram.

Source Data Fig. 6

Unprocessed gels.

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Eluru, G., De Gieter, S., Schenck, S. et al. MISO: microfluidic protein isolation enables single-particle cryo-EM structure determination from a single cell colony. Nat Methods 22, 2563–2573 (2025). https://doi.org/10.1038/s41592-025-02894-x

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