bioRxivMolecular BiologyPreprint
CLOSING THE CONFORMATIONAL CYCLE OF THE BETA-BARREL ASSEMBLY MACHINERY
Takaaki KatoiD, Hideki ShigematsuiD, Koh TakeuchiiD, Masato SuzukiiD, Ryo NittaiD, Tsuyoshi ImasakiiD
Abstract
The {beta}-barrel assembly machinery (BAM) catalyzes the folding and insertion of {beta}-barrel outer membrane proteins (OMPs) in Gram-negative bacteria without an external energy source. BAM comprises the central subunit BamA and associated lipoproteins, with BamA forming a conformationally dynamic lateral gate. Although substrate-engaged structures have revealed key steps in OMP assembly, how substrate-free BamA closes its lateral gate and which conformations it adopts in a lipid bilayer remain unclear. Here, we determined cryo-EM structures of the Escherichia coli (E. coli) BAM complex in three detergents and in Saposin A nanodiscs composed of E. coli polar lipids. In addition to the canonical outward-open (OO) state, we identified an occluded (OC) state in which both the lateral gate and the periplasmic opening of the BamA barrel are closed. OC predominated in lipid-reconstituted BAM that retained OMP-folding activity, indicating that this state is substantially populated in a functional BAM ensemble within a lipid bilayer. We also identified a semi-occluded (sOC) state in which {beta}1-{beta}2 adopts an OC-like closed position while rearrangement of {beta}16 remains incomplete. Comparison of OO, sOC, and OC reveals asynchronous rearrangements of the {beta}1-{beta}2 and {beta}16 regions, with {beta}1-{beta}2 movement occurring without complete repositioning of {beta}16. Re-examination of previously reported lipid-embedded BAM structures further highlights the importance of local map quality at the gate region for conformational assignment. Together, our findings expand the BamA conformational landscape beyond the conventional OO-inward-open (IO) framework to include OC and sOC as distinct structural states associated with lateral-gate closure following OMP insertion.
- organism: E. coli
- assay: electronic health records
- research focus: protein structure prediction
- approach: experimental assay
- Citations
- 0
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