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Dynamics of oligomer populations formed during the aggregation of Alzheimer’s Aβ42 peptide

An Author Correction to this article was published on 17 April 2020

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Abstract

Oligomeric species populated during the aggregation of the Aβ42 peptide have been identified as potent cytotoxins linked to Alzheimer’s disease, but the fundamental molecular pathways that control their dynamics have yet to be elucidated. By developing a general approach that combines theory, experiment and simulation, we reveal, in molecular detail, the mechanisms of Aβ42 oligomer dynamics during amyloid fibril formation. Even though all mature amyloid fibrils must originate as oligomers, we found that most Aβ42 oligomers dissociate into their monomeric precursors without forming new fibrils. Only a minority of oligomers converts into fibrillar structures. Moreover, the heterogeneous ensemble of oligomeric species interconverts on timescales comparable to those of aggregation. Our results identify fundamentally new steps that could be targeted by therapeutic interventions designed to combat protein misfolding diseases.

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Fig. 1: Experimental procedures for the quantitative measurement of Aβ42 oligomer populations during an ongoing amyloid fibril self-assembly reaction using 3H labelling or MS.
Fig. 2: Kinetic analysis of Aβ42 oligomer populations elucidates the molecular pathways of their dynamics during amyloid aggregation.
Fig. 3: Concentration dependence of the molecular pathways of Aβ42 oligomer dynamics.
Fig. 4: Schematic illustration of the reaction pathways of oligomers during amyloid aggregation and the associated reaction rates determined in this work for Aβ42.

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The authors confirm that all data generated and analysed during this study are included in this published article and its Supplementary Information. Data are also available from the corresponding authors upon request.

Code availability

All the simulation and data analysis codes are included in this article and its Supplementary Information. Codes are available from the corresponding authors upon request.

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Acknowledgements

We acknowledge support from Peterhouse (T.C.T.M.), the Swiss National Science foundation (T.C.T.M.), the Royal Society (A.Š.), the Academy of Medical Sciences (A.Š.), the UCL Institute for the Physics of Living Systems (S.C.), Sidney Sussex College (G.M.), the Wellcome Trust (A.Š., M.V., C.M.D. and T.P.J.K.), the Schiff Foundation (A.J.D.), the Cambridge Centre for Misfolding Diseases (M.V., C.M.D. and T.P.J.K.), the BBSRC (C.M.D. and T.P.J.K.), the Frances and Augustus Newman Foundation (T.P.J.K.), the Swedish Research Council (S.L.) and the ERC grant MAMBA (S.L., agreement no. 340890). The research that led to these results received funding from the European Research Council under the European Union’s Seventh Framework Programme (FP7/2007-2013) through the ERC grant PhysProt (agreement no. 337969).

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All the authors were involved in the design of the study; T.C.T.M. developed the theoretical model and performed the kinetic analysis; S.L. and K.B. performed the experiments; A.Š. and S.C. performed computer simulations; all the authors participated in interpreting the results and writing the paper.

Corresponding authors

Correspondence to Michele Vendruscolo, Sara Linse or Tuomas P. J. Knowles.

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Supplementary information

Supplementary Information

Experimental methods, details on computer simulations, definition and solution of mathematical models of oligomer dynamics, details on data analysis, Supplementary Figs. 1–19, Tables 1 and 2, and Video 1.

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Michaels, T.C.T., Šarić, A., Curk, S. et al. Dynamics of oligomer populations formed during the aggregation of Alzheimer’s Aβ42 peptide. Nat. Chem. 12, 445–451 (2020). https://doi.org/10.1038/s41557-020-0452-1

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