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Bottom-up structural proteomics: cryoEM of protein complexes enriched from the cellular milieu

Nature Methods volume 17, pages 79–85 (2020)Cite this article

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Abstract

X-ray crystallography often requires non-native constructs involving mutations or truncations, and is challenged by membrane proteins and large multicomponent complexes. We present here a bottom-up endogenous structural proteomics approach whereby near-atomic-resolution cryo electron microscopy (cryoEM) maps are reconstructed ab initio from unidentified protein complexes enriched directly from the endogenous cellular milieu, followed by identification and atomic modeling of the proteins. The proteins in each complex are identified using cryoID, a program we developed to identify proteins in ab initio cryoEM maps. As a proof of principle, we applied this approach to the malaria-causing parasite Plasmodium falciparum, an organism that has resisted conventional structural-biology approaches, to obtain atomic models of multiple protein complexes implicated in intraerythrocytic survival of the parasite. Our approach is broadly applicable for determining structures of undiscovered protein complexes enriched directly from endogenous sources.

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Fig. 1: Endogenous structural proteomics workflow.
Fig. 2: Simplified six-letter code.
Fig. 3: Searching in cryoID.
Fig. 4: CryoEM structures of proteins enriched directly from P. falciparum parasite lysates.
Fig. 5: Details of the M18 aspartyl aminopeptidase and glutamine synthetase monomers.

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Data availability

The atomic models and the cryoEM density maps are deposited to the Protein Data Bank and the Electron Microscopy Data Bank, with the accession numbers 6PEV, 6PEW, EMD-20333 and EMD-20334. For raw image data, please contact the corresponding author. The proteomics data have been deposited to the ProteomeXchange Consortium (http://proteomecentral.proteomexchange.org) via the MassIVE partner repository with the dataset identifier PDX014263.

Code availability

cryoID is an open source program under the MIT license, available for download at github (https://github.com/EICN-UCLA/cryoID).

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Acknowledgements

This research was supported in part by grants from National Institutes of Health (R01GM071940/AI094386/DE025567 to Z.H.Z. and K99/R00 HL133453 to J.R.B.). C.M.H. acknowledges funding from the Ruth L. Kirschstein National Research Service Award (AI007323). X.L. acknowledges funding from the China Scholarship Council (CSC). We thank the UCLA Proteome Research Center for assistance in mass spectrometry and acknowledge the use of resources in the Electron Imaging Center for Nanomachines supported by UCLA and grants from NIH (S10RR23057, S10OD018111 and U24GM116792) and NSF (DBI-1338135 and DMR-1548924).

Author information

Author notes

  1. These authors contributed equally: Chi-Min Ho, Xiaorun Li.

Authors and Affiliations

  1. The Molecular Biology Institute, University of California, Los Angeles, CA, USA

    Chi-Min Ho & Z. Hong Zhou

  2. Department of Microbiology, Immunology, & Molecular Genetics, University of California, Los Angeles, CA, USA

    Chi-Min Ho, Mason Lai & Z. Hong Zhou

  3. California NanoSystems Institute, University of California, Los Angeles, CA, USA

    Chi-Min Ho, Xiaorun Li, Mason Lai & Z. Hong Zhou

  4. Hefei National Laboratory for Physical Sciences at the Microscale, School of Life Sciences, University of Science and Technology of China, Hefei, Anhui, China

    Xiaorun Li

  5. Los Alamos National Laboratory and the New Mexico Consortium, Los Alamos, NM, USA

    Thomas C. Terwilliger

  6. Departments of Medicine and Molecular Microbiology, Washington University School of Medicine in St. Louis, St. Louis, MO, USA

    Josh R. Beck & Daniel E. Goldberg

  7. Department of Biomedical Sciences, Iowa State University, Ames, IA, USA

    Josh R. Beck

  8. Department of Biological Chemistry, David Geffen School of Medicine, University of California, Los Angeles, CA, USA

    James Wohlschlegel

  9. Zuckerman Institute, Columbia Medical School, New York, NY, USA

    Anthony W. P. Fitzpatrick

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Contributions

C.M.H., A.W.P.F. and Z.H.Z. initiated the project; J.R.B. cultured and harvested parasite material; C.M.H. purified the sample from parasite pellets, screened purified samples by negative stain, optimized sample freezing conditions for cryoEM, acquired and processed the cryoEM data, interpreted the structures, designed the endogenous structural proteomics workflow, helped design cryoID and wrote the paper; M.L. built and refined the atomic models and helped interpret the structures; J.A.W. performed the mass spectrometry; C.M.H., X.L. and M.L. designed the cryoID workflow. X.L. developed and benchmarked cryoID and helped write the paper. X.L. and C.M.H. worked with T.C.T. to write and optimize the Phenix tool sequence_from_map. Z.H.Z. supervised the cryoEM aspects of the project, interpreted the structures and wrote the paper; D.E.G. supervised parasitology aspects of the project. A.W.P.F., M.L., T.C.T., J.R.B., J.A.W. and D.E.G. helped edit the paper; all authors approved the paper.

Corresponding author

Correspondence to Z. Hong Zhou.

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The authors declare no competing interests.

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Peer review information Allison Doerr was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team

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Integrated supplementary information

Supplementary Fig. 1 Evaluation of sucrose gradient fractions by SDS–PAGE and negative-stain EM.

a, Silver-stained SDS–PAGE of fractions from P. falciparum lysate sucrose gradient fractionation. b–e, Comparison of non-promising (b) and promising (d) negative-stain TEM images and their corresponding 2D class averages (c,e).

Supplementary Fig. 2

Manual inspection in Coot via the cryoID GUI.

Supplementary Fig. 3 Representative results from benchmarking of cryoID using simulated data.

a–d, The test results for query conditions (m,n) of 4,8 (a), 4,10 (b) 4,15 (c) and 4,30 (d) are shown. In each case, the top 10 candidates identified by cryoID are shown. The bar shown for each candidate represents 1,000 independent runs using unique sets of queries randomly generated from full length P. falciparum protein sequences (one-sided statistics test: P(f) < 0.005, n = 1,000, P value < 0.0067, α < 0.01). In each case, the bar shown for the correct protein is indicated with a star. The gap between the correct protein and the next closest match is indicated. The query condition shown in a is suboptimal, as cryoID identified multiple protein candidates that exhibit 100% identity with the queries. In optimal query conditions, shown in b–d, a clear gap is visible in percentage identity between the correct protein candidate (100% identity with queries) and the next closest matching candidate. This gap increases as m and n increase.

Supplementary Fig. 4 Endogenous cryoEM structures of the P. falciparum 20S proteasome in two conformations were obtained from the same proof-of-principle fraction analyzed and presented in our manuscript.

a–h, The first structure is of a full 20S proteasome containing all 14 α and all 14 β subunits (pink, a–d), while in the second structure (indigo, e–h), four β subunits appear to be disordered (the density corresponding to the β2 and β5 subunits is broken). Full surface front (a,e) and side (c,g) views and central slice front (b,f) and side (d,h) views of the two structures are shown. Models for the two structures are shown superposed with the maps in the central slice views. In g and h, a copy of the map has been low-pass filtered and is displayed as a translucent blue envelope, superposed over the unfiltered map, in order to show the disordered density.

Supplementary Fig. 5 Comparison of glutamine synthetase from P. falciparum (by endogenous cryoEM) and S. enterica (by X-ray crystallography).

The active sites, shown in light pink in both models, is well conserved. One region in which the two structures diverge is highlighted in red in the P. falciparum structure and green in the S. enterica structure.

Supplementary Information

Supplementary Information

Supplementary Figures 1–5, Supplementary Tables 1–4 and 6–7 and Supplementary Notes 1 and 2

Reporting Summary

Supplementary Table 5

Results of the mass spectrometry analysis of the sucrose gradient fractionated P. falciparum lysate.

Supplementary Video 1

Details of the Plasmodium falciparum M18 aspartyl aminopeptidase (PfM18AA) cryoEM Density Map. A 360° view of the cryoEM density map and atomic model of the PfM18AA dodecamer, including detailed cutaway views of the density map overlaid with the model.

Supplementary Video 2

Details of the Plasmodium falciparum glutamine synthetase (PfGS); cryoEM Density Map. A 360° view of the cryoEM density map and atomic model of the PfGS dodecamer, including detailed views of side-chain densities (mesh) superposed with the PfGS atomic model.

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Ho, CM., Li, X., Lai, M. et al. Bottom-up structural proteomics: cryoEM of protein complexes enriched from the cellular milieu. Nat Methods 17, 79–85 (2020). https://doi.org/10.1038/s41592-019-0637-y

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