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A structural study of the AcrB protein complex by single particle cryo-EM

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Hielkema,  Lisa
Department of Structural Biology, Max Planck Institute of Biophysics, Max Planck Society;

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Hielkema, L. (2016). A structural study of the AcrB protein complex by single particle cryo-EM. Master Thesis, University of Groningen, Groningen.


Cite as: https://hdl.handle.net/21.11116/0000-000F-F3C9-C
Abstract
Multidrug resistance is a major public health threat. Causes underlying this problem are the excessive
and abundant use of antibiotics, and the challenges of developing new antimicrobials. Antibiotic
resistant bacteria have a wide variety of intrinsic and acquired mechanisms to circumvent the action
of antibiotics. One of these mechanisms is the increased efflux of the antibiotic compound by
multidrug resistance (MDR) pumps. One of the most extensively studied MDR pumps is the
homotrimeric secondary active antiporter AcrB, belonging to the RND family, which has a broad
substrate specificity. The AcrB monomers can adopt different conformations, with which it carries out
an alternating site functional rotation transport mechanism.
To our knowledge, only crystal structures of the AcrB protein complex have been published, and
most of the asymmetric structures have been induced by adding DARPins. Single particle cryo-electron
microscopy (cryo-EM) would not need the use of additives to observe asymmetry in a protein. In
addition to that, no structure of AcrB the complex with a carbapenem antibiotic is available. While
carbapenem resistance is mainly caused by increased efflux.
Here we present a cryo-EM map of the AcrB protein complex, with the carbapenem antibiotic
meropenem as a substrate, at a resolution of 6.4 Å. With this model, we could show that the protein
complex is asymmetric in solution (without the addition of DARPins), and that there is an indication
that the substrate is present in the substrate binding pocket. In addition to that, we compared movie
processing methods needed for cryo-EM, and the application of a new focused classification method
on our data.