Cryo-EM structures of mitochondrial respiratory complex I from Drosophila melanogaster
- University of Cambridge, United Kingdom
Abstract
Respiratory complex I powers ATP synthesis by oxidative phosphorylation, exploiting the energy from NADH oxidation by ubiquinone to drive protons across an energy-transducing membrane. Drosophila melanogaster is a candidate model organism for complex I due to its high evolutionary conservation with the mammalian enzyme, well-developed genetic toolkit, and complex physiology for studies in specific cell types and tissues. Here, we isolate complex I from Drosophila and determine its structure, revealing a 43-subunit assembly with high structural homology to its 45-subunit mammalian counterpart, including a hitherto unknown homologue to subunit NDUFA3. The major conformational state of the Drosophila enzyme is the mammalian-type 'ready-to-go' active resting state, with a fully ordered and enclosed ubiquinone-binding site, but a subtly altered global conformation related to changes in subunit ND6. The mammalian-type 'deactive' pronounced resting state is not observed: in two minor states the ubiquinone-binding site is unchanged, but a deactive-type p-bulge is present in ND6-TMH3. Our detailed structural knowledge of Drosophila complex I provides a foundation for new approaches to disentangle mechanisms of complex I catalysis and regulation in bioenergetics and physiology.
Data availability
Structural data have been deposited in the EMDB and PDB databases under the following accession codes: EMD-15936 and 8B9Z (Dm1; active), EMD-15937 and 8BA0 (Dm2; twisted), and EMD-15938 (Dm3; cracked).
Article and author information
Author details
Alvaro Sanchez-Martinez
Alexander J Whitworth
Funding
Medical Research Council (MC_UU_00015/6)
- Alexander J Whitworth
Medical Research Council (MC_UU_00028/6)
- Alexander J Whitworth
Medical Research Council (MC_UU_00015/2)
- Judy Hirst
Medical Research Council (MC_UU_00028/1)
- Judy Hirst
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2023, Agip et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Cryo-EM structures of mitochondrial respiratory complex I from Drosophila melanogaster
eLife 12:e84424.
https://doi.org/10.7554/eLife.84424
Further reading
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- Structural Biology and Molecular Biophysics
Images taken by transmission electron microscopes are usually affected by lens aberrations and image defocus, among other factors. These distortions can be modeled in reciprocal space using the contrast transfer function (CTF). Accurate estimation and correction of the CTF is essential for restoring the high-resolution signal in cryogenic electron microscopy (cryoEM). Previously, we described the implementation of algorithms for this task in the cisTEM software package (Grant et al., 2018). Here we show that taking sample characteristics, such as thickness and tilt, into account can improve CTF estimation. This is particularly important when imaging cellular samples, where measurement of sample thickness and geometry derived from accurate modeling of the Thon ring pattern helps judging the quality of the sample. This improved CTF estimation has been implemented in CTFFIND5, a new version of the cisTEM program CTFFIND. We evaluated the accuracy of these estimates using images of tilted aquaporin crystals and eukaryotic cells thinned by focused ion beam milling. We estimate that with micrographs of sufficient quality CTFFIND5 can measure sample tilt with an accuracy of 3° and sample thickness with an accuracy of 5 nm.
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- Structural Biology and Molecular Biophysics
Segmentation is a critical data processing step in many applications of cryo-electron tomography. Downstream analyses, such as subtomogram averaging, are often based on segmentation results, and are thus critically dependent on the availability of open-source software for accurate as well as high-throughput tomogram segmentation. There is a need for more user-friendly, flexible, and comprehensive segmentation software that offers an insightful overview of all steps involved in preparing automated segmentations. Here, we present Ais: a dedicated tomogram segmentation package that is geared towards both high performance and accessibility, available on GitHub. In this report, we demonstrate two common processing steps that can be greatly accelerated with Ais: particle picking for subtomogram averaging, and generating many-feature segmentations of cellular architecture based on in situ tomography data. Featuring comprehensive annotation, segmentation, and rendering functionality, as well as an open repository for trained models at aiscryoet.org, we hope that Ais will help accelerate research and dissemination of data involving cryoET.
