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      Cryo-EM structures of amyloid-β filaments with the Arctic mutation (E22G) from human and mouse brains

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          Abstract

          The Arctic mutation, encoding E693G in the amyloid precursor protein (APP) gene [E22G in amyloid-β (Aβ)], causes dominantly inherited Alzheimer’s disease. Here, we report the high-resolution cryo-EM structures of Aβ filaments from the frontal cortex of a previously described case ( Aβ PParc1) with the Arctic mutation. Most filaments consist of two pairs of non-identical protofilaments that comprise residues V12–V40 (human Arctic fold A) and E11–G37 (human Arctic fold B). They have a substructure (residues F20–G37) in common with the folds of type I and type II Aβ42. When compared to the structures of wild-type Aβ42 filaments, there are subtle conformational changes in the human Arctic folds, because of the lack of a side chain at G22, which may strengthen hydrogen bonding between mutant Aβ molecules and promote filament formation. A minority of Aβ42 filaments of type II was also present, as were tau paired helical filaments. In addition, we report the cryo-EM structures of Aβ filaments with the Arctic mutation from mouse knock-in line App NL−G−F . Most filaments are made of two identical mutant protofilaments that extend from D1 to G37 ( App NL−G−F murine Arctic fold). In a minority of filaments, two dimeric folds pack against each other in an anti-parallel fashion. The App NL−G−F murine Arctic fold differs from the human Arctic folds, but shares some substructure.

          Supplementary Information

          The online version contains supplementary material available at 10.1007/s00401-022-02533-1.

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          Most cited references40

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          MotionCor2: anisotropic correction of beam-induced motion for improved cryo-electron microscopy

          MotionCor2 software corrects for beam-induced sample motion, improving the resolution of cryo-EM reconstructions.
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            New tools for automated high-resolution cryo-EM structure determination in RELION-3

            Here, we describe the third major release of RELION. CPU-based vector acceleration has been added in addition to GPU support, which provides flexibility in use of resources and avoids memory limitations. Reference-free autopicking with Laplacian-of-Gaussian filtering and execution of jobs from python allows non-interactive processing during acquisition, including 2D-classification, de novo model generation and 3D-classification. Per-particle refinement of CTF parameters and correction of estimated beam tilt provides higher resolution reconstructions when particles are at different heights in the ice, and/or coma-free alignment has not been optimal. Ewald sphere curvature correction improves resolution for large particles. We illustrate these developments with publicly available data sets: together with a Bayesian approach to beam-induced motion correction it leads to resolution improvements of 0.2–0.7 Å compared to previous RELION versions.
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              CTFFIND4: Fast and accurate defocus estimation from electron micrographs.

              CTFFIND is a widely-used program for the estimation of objective lens defocus parameters from transmission electron micrographs. Defocus parameters are estimated by fitting a model of the microscope's contrast transfer function (CTF) to an image's amplitude spectrum. Here we describe modifications to the algorithm which make it significantly faster and more suitable for use with images collected using modern technologies such as dose fractionation and phase plates. We show that this new version preserves the accuracy of the original algorithm while allowing for higher throughput. We also describe a measure of the quality of the fit as a function of spatial frequency and suggest this can be used to define the highest resolution at which CTF oscillations were successfully modeled.
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                Author and article information

                Contributors
                mg@mrc-lmb.cam.ac.uk
                scheres@mrc-lmb.cam.ac.uk
                Journal
                Acta Neuropathol
                Acta Neuropathol
                Acta Neuropathologica
                Springer Berlin Heidelberg (Berlin/Heidelberg )
                0001-6322
                1432-0533
                7 January 2023
                7 January 2023
                2023
                : 145
                : 3
                : 325-333
                Affiliations
                [1 ]GRID grid.42475.30, ISNI 0000 0004 0605 769X, Medical Research Council Laboratory of Molecular Biology, ; Cambridge, UK
                [2 ]GRID grid.474690.8, RIKEN Brain Science Institute, ; Saitama, Japan
                [3 ]GRID grid.257413.6, ISNI 0000 0001 2287 3919, Department of Pathology and Laboratory Medicine, , Indiana University School of Medicine, ; Indianapolis, IN USA
                [4 ]GRID grid.4714.6, ISNI 0000 0004 1937 0626, Department of Neurobiology, Care Sciences and Society, , Karolinska Institutet, ; Stockholm, Sweden
                [5 ]GRID grid.24381.3c, ISNI 0000 0000 9241 5705, Theme Inflammation and Aging, , Karolinska University Hospital, ; Stockholm, Sweden
                [6 ]GRID grid.83440.3b, ISNI 0000000121901201, Present Address: Medical Research Council Prion Unit and Institute of Prion Diseases, , University College London, ; London, UK
                [7 ]GRID grid.5335.0, ISNI 0000000121885934, Present Address: Dementia Research Institute, Department of Clinical Neurosciences, , University of Cambridge, ; Cambridge, UK
                [8 ]GRID grid.260433.0, ISNI 0000 0001 0728 1069, Present Address: Department of Neurocognitive Science, , Nagoya City University, ; Nagoya, Japan
                Author information
                http://orcid.org/0000-0002-0462-6540
                Article
                2533
                10.1007/s00401-022-02533-1
                9925504
                36611124
                d90756c4-c6e6-4bce-804b-c8e3d69bb480
                © The Author(s) 2023

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 2 November 2022
                : 15 December 2022
                : 15 December 2022
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100000268, Biotechnology and Biological Sciences Research Council;
                Funded by: FundRef http://dx.doi.org/10.13039/501100000265, Medical Research Council;
                Award ID: MC_UP_A025-1013
                Award ID: MC_U105184291
                Award Recipient :
                Funded by: US National Institute of Health
                Award ID: UO1-NS110457
                Award Recipient :
                Categories
                Original Paper
                Custom metadata
                © Springer-Verlag GmbH Germany, part of Springer Nature 2023

                Neurology
                alzheimer’s disease,amyloid-beta,arctic mutation,electron cryo-microscopy,mouse appnl−g−f knock-in line,tau

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