Single-particle cryo-electron microscopy (cryo-EM) has become a powerful technique in the field of structural biology. However, the inability to reliably produce pure, homogeneous membrane protein samples hampers the progress of their structural determination. Here, we develop a bottom-up iterative method, Build and Retrieve (BaR), that enables the identification and determination of cryo-EM structures of a variety of inner and outer membrane proteins, including membrane protein complexes of different sizes and dimensions, from a heterogeneous, impure protein sample. We also use the BaR methodology to elucidate structural information from Escherichia coli K12 crude membrane and raw lysate. The findings demonstrate that it is possible to solve high-resolution structures of a number of relatively small (<100 kDa) and less abundant (<10%) unidentified membrane proteins within a single, heterogeneous sample. Importantly, these results highlight the potential of cryo-EM for systems structural proteomics.
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Atomic coordinates and structure factors have been deposited with accession codes 6WTI (PDB) and EMD-21897 (EMDB) for cytochrome bo3; 6WU0 (PDB) and EMD-21901 (EMDB) for BpHpnN; 6WTZ (PDB) and EMD-21900 (EMDB) for OmpF; 6WU6 (PDB) and EMD-21906 (EMDB) for SQR (3.60 Å); 7JZ3 (PDB) and EMD-22529 (EMDB) for OmpC; 7JZ2 (PDB) and EMD-22528 (EMDB) for SQR (2.50 Å); 7JZ6 (PDB) and EMD-22530 (EMDB) for KatG; and 7JZH (PDB) and EMD-22531 (EMDB) for GadB. Source data are provided with this paper.
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We thank P. A. Klenotic for proofreading the manuscript. We are grateful to the Cryo-Electron Microscopy Core at the CWRU School of Medicine and K. Li for access to the sample preparation and Cryo-EM instrumentation. We thank D. Wu and T. El-Baba for help with proteomics analysis. This work was supported by NIH grant R01AI145069 (E.W.Y.) and MRC grant MR/N020413/1 (C.V.R.). This research was supported in part by the National Cryo-EM Facility of the National Cancer Institute at the Frederick National Laboratory for Cancer Research under contract HSSN261200800001E.
The authors declare no competing interests.
Peer review information Arunima Singh was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Flowchart of the ‘Build and Retrieve’ (BaR) iterative method.
Extended Data Fig. 2 Native mass spectrometry (nMS) and proteomics analysis suggest that the sample of B. pseudomallei HpnN was co-purified with several other proteins.
(a) SDS–PAGE of the purified sample where the gel bands were sliced and subjected to tryptic digestion to identify the proteins. Proteomics analysis clearly indicated the presence of HpnN, OmpF and different components of succinate dehydrogenase (SdhA and SdhB) and cytochrome bo3 oxidase (Subunit I, Subunit II and Subunit III). The protein bands were quantified and replicated three times using ImageJ (imagej.net), showing the abundance of 60.8% for BpHpnN, 9.4% for SdhA + GlmS, 9.7% for subunit I, 6.4% for ArnC + subunit II+PfkA + GatD + TDH+ OmpF, 6.7% for SdhB and 1.9% for subunit III. (b) Native mass spectra show several charge state distributions whose deconvoluted masses are shown in the Table. Among them, the 93,548 Da can be readily assigned to monomeric HpnN and the 133,853 Da to dimeric glucosamine-6-phosphate synthase (GlmS). While the masses 65,233 Da and 75,031 Da can be assigned to SdhA bound to FAD and Subunit I bound to heme b respectively based on the data from (a). Among the proteins identified in (a), PfkA and TDH are known to exist as tetramers. Therefore, the masses 139,385 Da and 149,545 Da can be assigned to the PfkA and TDH tetramers. The collisionally induced dissociated products shown in (c) further supported this assignment.
The 2D classification indicates that there are at least five different proteins coexist in the nanodisc sample.
(a) BaR processing flowchart. (b) Representative 2D classes. (c) Fourier Shell Correlation (FSC) curves. (d) Sharpened cryo-EM map of the cytochrome bo3 complex viewed in the membrane plane. (e) Sharpened cryo-EM map of the cytochrome bo3 complex viewed from the cytoplasmic side. (f) Local EM density map of cytochrome bo3.
(a) BaR processing flowchart. (b) Representative 2D classes. (c) Fourier Shell Correlation (FSC) curves. (d and e) Sharpened cryo-EM maps of the BpHpnN transporter viewed in the membrane plane. (f) Local EM density map of BpHpnN.
(a) BaR processing flowchart. (b) Representative 2D classes. (c) Fourier Shell Correlation (FSC) curves. (d) Sharpened cryo-EM map of the OmpF porin viewed in the membrane plane and from the periplasmic side. (e) Sharpened cryo-EM map of the OmpF viewed from the exterior side. (f) Local EM density map of OmpF.
(a) BaR processing flowchart. (b) Representative 2D classes. (c) Fourier Shell Correlation (FSC) curves. (d) Sharpened cryo-EM map of the SQR complex viewed in the membrane plane. (e) Sharpened cryo-EM map of the SQR complex viewed from the cytoplasmic side. (f) Local EM density map of SQR.
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Su, CC., Lyu, M., Morgan, C.E. et al. A ‘Build and Retrieve’ methodology to simultaneously solve cryo-EM structures of membrane proteins. Nat Methods 18, 69–75 (2021). https://doi.org/10.1038/s41592-020-01021-2