Tau filaments from multiple cases of sporadic and inherited Alzheimer's disease adopt a common fold.

The ordered assembly of tau protein into abnormal filaments is a defining characteristic of Alzheimer's disease (AD) and other neurodegenerative disorders. It is not known if the structures of tau filaments vary within, or between, the brains of individuals with AD. We used a combination of electron cryo-microscopy (cryo-EM) and immuno-gold negative-stain electron microscopy (immuno-EM) to determine the structures of paired helical filaments (PHFs) and straight filaments (SFs) from the frontal cortex of 17 cases of AD (15 sporadic and 2 inherited) and 2 cases of atypical AD (posterior cortical atrophy). The high-resolution structures of PHFs and SFs from the frontal cortex of 3 cases of AD, 2 sporadic and 1 inherited, were determined by cryo-EM. We also used immuno-EM to study the PHFs and SFs from a number of cortical and subcortical brain regions. PHFs outnumbered SFs in all AD cases. By cryo-EM, PHFs and SFs were made of two C-shaped protofilaments with a combined cross-β/β-helix structure, as described previously for one case of AD. The higher resolution structures obtained here showed two additional amino acids at each end of the protofilament. The immuno-EM findings, which indicated the presence of repeats 3 and 4, but not of the N-terminal regions of repeats 1 and 2, of tau in the filament cores of all AD cases, were consistent with the cryo-EM results. These findings show that there is no significant variation in tau filament structures between individuals with AD. This knowledge will be crucial for understanding the mechanisms that underlie tau filament formation and for developing novel diagnostics and therapies

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

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 (AβPParc1) 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 AppNL−G−F. Most filaments are made of two identical mutant protofilaments that extend from D1 to G37 (AppNL−G−F murine Arctic fold). In a minority of filaments, two dimeric folds pack against each other in an anti-parallel fashion. The AppNL−G−F murine Arctic fold differs from the human Arctic folds, but shares some substructure

Cryo-EM structures of amyloid-β 42 filaments from human brains

Alzheimer’s disease is characterized by a loss of memory and other cognitive functions and the filamentous assembly of Aβ and tau in the brain. The assembly of Aβ peptides into filaments that end at residue 42 is a central event. Yang et al. used electron cryo–electron microscopy to determine the structures of Aβ42 filaments from human brain (see the Perspective by Willem and Fändrich). They identified two types of related S-shaped filaments, each consisting of two identical protofilaments. These structures will inform the development of better in vitro and animal models, inhibitors of Aβ42 assembly, and imaging agents with increased specificity and sensitivity. —SM

Correction to: Cryo-EM structures of tau filaments from Alzheimer's disease with PET ligand APN-1607.

A correction to this paper has been published: https://doi.org/10.1007/s00401-021-02303-5</jats:p

Cryo-EM structures of tau filaments from Alzheimer's disease with PET ligand APN-1607.

Tau and Aβ assemblies of Alzheimer's disease (AD) can be visualized in living subjects using positron emission tomography (PET). Tau assemblies comprise paired helical and straight filaments (PHFs and SFs). APN-1607 (PM-PBB3) is a recently described PET ligand for AD and other tau proteinopathies. Since it is not known where in the tau folds PET ligands bind, we used electron cryo-microscopy (cryo-EM) to determine the binding sites of APN-1607 in the Alzheimer fold. We identified two major sites in the β-helix of PHFs and SFs and a third major site in the C-shaped cavity of SFs. In addition, we report that tau filaments from posterior cortical atrophy (PCA) and primary age-related tauopathy (PART) are identical to those from AD. In support, fluorescence labelling showed binding of APN-1607 to intraneuronal inclusions in AD, PART and PCA. Knowledge of the binding modes of APN-1607 to tau filaments may lead to the development of new ligands with increased specificity and binding activity. We show that cryo-EM can be used to identify the binding sites of small molecules in amyloid filaments

Cryo-EM: A Unique Tool for the Visualization of Macromolecular Complexity.

3D cryo-electron microscopy (cryo-EM) is an expanding structural biology technique that has recently undergone a quantum leap progression in its achievable resolution and its applicability to the study of challenging biological systems. Because crystallization is not required, only small amounts of sample are needed, and because images can be classified in a computer, the technique has the potential to deal with compositional and conformational mixtures. Therefore, cryo-EM can be used to investigate complete and fully functional macromolecular complexes in different functional states, providing a richness of biological insight. In this review, we underlie some of the principles behind the cryo-EM methodology of single particle analysis and discuss some recent results of its application to challenging systems of paramount biological importance. We place special emphasis on new methodological developments that are leading to an explosion of new studies, many of which are reaching resolutions that could only be dreamed of just a couple of years ago

Cryo-EM: A Unique Tool for the Visualization of Macromolecular Complexity.

3D cryo-electron microscopy (cryo-EM) is an expanding structural biology technique that has recently undergone a quantum leap progression in its achievable resolution and its applicability to the study of challenging biological systems. Because crystallization is not required, only small amounts of sample are needed, and because images can be classified in a computer, the technique has the potential to deal with compositional and conformational mixtures. Therefore, cryo-EM can be used to investigate complete and fully functional macromolecular complexes in different functional states, providing a richness of biological insight. In this review, we underlie some of the principles behind the cryo-EM methodology of single particle analysis and discuss some recent results of its application to challenging systems of paramount biological importance. We place special emphasis on new methodological developments that are leading to an explosion of new studies, many of which are reaching resolutions that could only be dreamed of just a couple of years ago

Tau and neurodegeneration.

Publication status: PublishedFirst identified in 1975, tau was implicated in Alzheimer's disease 10 years later. Filamentous tangle inclusions were known to be made of hyperphosphorylated tau by 1991, with similar inclusions gaining recognition for being associated with other neurodegenerative diseases. In 1998, mutations in MAPT, the gene that encodes tau, were identified as the cause of a dominantly inherited form of frontotemporal dementia with abundant filamentous tau inclusions. While this result indicated that assembly of tau into aberrant filaments is sufficient to drive neurodegeneration and dementia, most cases of tauopathy are sporadic. More recent work in experimental systems showed that filamentous assemblies of tau may first form in one brain area, and then spread to others in a prion-like fashion. Beginning in 2017, work on human brains using high-resolution techniques has led to a structure-based classification of tauopathies, which has opened the door to a better understanding of the significance of tau filament formation

Automated model building and protein identification in cryo-EM maps.

Acknowledgements: We thank G. Ghanim, J. Greener, K. Naydenova, J. Schwab, Z. Sekne, S. Lövestam and K. Yamashita for discussions; M. Gui for contributions to atomic modelling of the ciliary axonemes; and J. Grimmett, T. Darling and I. Clayson for help with high-performance computing. This work was supported by the Medical Research Council as part of the United Kingdom Research and Innovation (MC_UP_A025_1013 to S.H.W.S.); the EU Horizon 2020 research and innovation programme (under grant agreement no. 895412 to D.K.); the National Institutes of Health (R01-GM141109 to A.B. and R01-GM138854 to R.Z.); and the Knut and Alice Wallenberg Foundation (2022.0032 to L.K.). For the purpose of open access, the MRC Laboratory of Molecular Biology has applied a CC BY public copyright license to any author accepted manuscript version arising.Interpreting electron cryo-microscopy (cryo-EM) maps with atomic models requires high levels of expertise and labour-intensive manual intervention in three-dimensional computer graphics programs1,2. Here we present ModelAngelo, a machine-learning approach for automated atomic model building in cryo-EM maps. By combining information from the cryo-EM map with information from protein sequence and structure in a single graph neural network, ModelAngelo builds atomic models for proteins that are of similar quality to those generated by human experts. For nucleotides, ModelAngelo builds backbones with similar accuracy to those built by humans. By using its predicted amino acid probabilities for each residue in hidden Markov model sequence searches, ModelAngelo outperforms human experts in the identification of proteins with unknown sequences. ModelAngelo will therefore remove bottlenecks and increase objectivity in cryo-EM structure determination

Automated model building and protein identification in cryo-EM maps.

Acknowledgements: We thank G. Ghanim, J. Greener, K. Naydenova, J. Schwab, Z. Sekne, S. Lövestam and K. Yamashita for discussions; M. Gui for contributions to atomic modelling of the ciliary axonemes; and J. Grimmett, T. Darling and I. Clayson for help with high-performance computing. This work was supported by the Medical Research Council as part of the United Kingdom Research and Innovation (MC_UP_A025_1013 to S.H.W.S.); the EU Horizon 2020 research and innovation programme (under grant agreement no. 895412 to D.K.); the National Institutes of Health (R01-GM141109 to A.B. and R01-GM138854 to R.Z.); and the Knut and Alice Wallenberg Foundation (2022.0032 to L.K.). For the purpose of open access, the MRC Laboratory of Molecular Biology has applied a CC BY public copyright license to any author accepted manuscript version arising.Interpreting electron cryo-microscopy (cryo-EM) maps with atomic models requires high levels of expertise and labour-intensive manual intervention in three-dimensional computer graphics programs1,2. Here we present ModelAngelo, a machine-learning approach for automated atomic model building in cryo-EM maps. By combining information from the cryo-EM map with information from protein sequence and structure in a single graph neural network, ModelAngelo builds atomic models for proteins that are of similar quality to those generated by human experts. For nucleotides, ModelAngelo builds backbones with similar accuracy to those built by humans. By using its predicted amino acid probabilities for each residue in hidden Markov model sequence searches, ModelAngelo outperforms human experts in the identification of proteins with unknown sequences. ModelAngelo will therefore remove bottlenecks and increase objectivity in cryo-EM structure determination