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Elucidating the Molecular Determinants of Aβ Aggregation with Deep Mutational Scanning
Despite the importance of Aβ aggregation in Alzheimer’s disease etiology, our understanding of the sequence determinants of aggregation is sparse and largely derived from in vitro studies. For example, in vitro proline and alanine scanning mutagenesis of Aβ(40) proposed core regions important for ag...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Genetics Society of America
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6829127/ https://www.ncbi.nlm.nih.gov/pubmed/31558564 http://dx.doi.org/10.1534/g3.119.400535 |
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author | Gray, Vanessa E. Sitko, Katherine Kameni, Floriane Z. Ngako Williamson, Miriam Stephany, Jason J. Hasle, Nicholas Fowler, Douglas M. |
author_facet | Gray, Vanessa E. Sitko, Katherine Kameni, Floriane Z. Ngako Williamson, Miriam Stephany, Jason J. Hasle, Nicholas Fowler, Douglas M. |
author_sort | Gray, Vanessa E. |
collection | PubMed |
description | Despite the importance of Aβ aggregation in Alzheimer’s disease etiology, our understanding of the sequence determinants of aggregation is sparse and largely derived from in vitro studies. For example, in vitro proline and alanine scanning mutagenesis of Aβ(40) proposed core regions important for aggregation. However, we lack even this limited mutagenesis data for the more disease-relevant Aβ(42). Thus, to better understand the molecular determinants of Aβ(42) aggregation in a cell-based system, we combined a yeast DHFR aggregation assay with deep mutational scanning. We measured the effect of 791 of the 798 possible single amino acid substitutions on the aggregation propensity of Aβ(42). We found that ∼75% of substitutions, largely to hydrophobic residues, maintained or increased aggregation. We identified 11 positions at which substitutions, particularly to hydrophilic and charged amino acids, disrupted Aβ aggregation. These critical positions were similar but not identical to critical positions identified in previous Aβ mutagenesis studies. Finally, we analyzed our large-scale mutagenesis data in the context of different Aβ aggregate structural models, finding that the mutagenesis data agreed best with models derived from fibrils seeded using brain-derived Aβ aggregates. |
format | Online Article Text |
id | pubmed-6829127 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Genetics Society of America |
record_format | MEDLINE/PubMed |
spelling | pubmed-68291272019-11-06 Elucidating the Molecular Determinants of Aβ Aggregation with Deep Mutational Scanning Gray, Vanessa E. Sitko, Katherine Kameni, Floriane Z. Ngako Williamson, Miriam Stephany, Jason J. Hasle, Nicholas Fowler, Douglas M. G3 (Bethesda) Investigations Despite the importance of Aβ aggregation in Alzheimer’s disease etiology, our understanding of the sequence determinants of aggregation is sparse and largely derived from in vitro studies. For example, in vitro proline and alanine scanning mutagenesis of Aβ(40) proposed core regions important for aggregation. However, we lack even this limited mutagenesis data for the more disease-relevant Aβ(42). Thus, to better understand the molecular determinants of Aβ(42) aggregation in a cell-based system, we combined a yeast DHFR aggregation assay with deep mutational scanning. We measured the effect of 791 of the 798 possible single amino acid substitutions on the aggregation propensity of Aβ(42). We found that ∼75% of substitutions, largely to hydrophobic residues, maintained or increased aggregation. We identified 11 positions at which substitutions, particularly to hydrophilic and charged amino acids, disrupted Aβ aggregation. These critical positions were similar but not identical to critical positions identified in previous Aβ mutagenesis studies. Finally, we analyzed our large-scale mutagenesis data in the context of different Aβ aggregate structural models, finding that the mutagenesis data agreed best with models derived from fibrils seeded using brain-derived Aβ aggregates. Genetics Society of America 2019-09-26 /pmc/articles/PMC6829127/ /pubmed/31558564 http://dx.doi.org/10.1534/g3.119.400535 Text en Copyright © 2019 Gray et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Investigations Gray, Vanessa E. Sitko, Katherine Kameni, Floriane Z. Ngako Williamson, Miriam Stephany, Jason J. Hasle, Nicholas Fowler, Douglas M. Elucidating the Molecular Determinants of Aβ Aggregation with Deep Mutational Scanning |
title | Elucidating the Molecular Determinants of Aβ Aggregation with Deep Mutational Scanning |
title_full | Elucidating the Molecular Determinants of Aβ Aggregation with Deep Mutational Scanning |
title_fullStr | Elucidating the Molecular Determinants of Aβ Aggregation with Deep Mutational Scanning |
title_full_unstemmed | Elucidating the Molecular Determinants of Aβ Aggregation with Deep Mutational Scanning |
title_short | Elucidating the Molecular Determinants of Aβ Aggregation with Deep Mutational Scanning |
title_sort | elucidating the molecular determinants of aβ aggregation with deep mutational scanning |
topic | Investigations |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6829127/ https://www.ncbi.nlm.nih.gov/pubmed/31558564 http://dx.doi.org/10.1534/g3.119.400535 |
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