ArticleProceedings of the National Academy of Sciences of the United States of America2022
Single-molecule fluorescence imaging and deep learning reveal highly heterogeneous aggregation of amyloid-β 42.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 29 citations in OpenAlex.
- smDeepFLUOR: single-molecule deep learning fluorescence classification.Nature communications · 2026Article
- Differentiating Alzheimer's Aβ Isoforms Coaggregated in Cerebrospinal Fluid via Single-Particle Imaging.ACS chemical neuroscience · 2026Article
- Single-fibril Förster resonance energy transfer imaging and deep learning reveal concentration dependence of amyloid β 42 aggregation pathways.PNAS nexus · 2025Article
- Three-color single-molecule maximum likelihood analysis of folding and binding of diffusing molecules.Biophysical journal · 2025Article
- Article
- Characterizing heterogeneity in amyloid formation processes.Current opinion in structural biology · 2024Review
- Fluorescence-Based Monitoring of Early-Stage Aggregation of Amyloid-β, Amylin Peptide, Tau, and α-Synuclein Proteins.ACS chemical neuroscience · 2024Article
- A Perspective on How Fibrinaloid Microclots and Platelet Pathology May be Applied in Clinical Investigations.Seminars in thrombosis and hemostasis · 2024Review
- Structure of cytotoxic amyloid oligomers generated during disaggregation.Journal of biochemistry · 2024Review
- Co-translational formation of disulfides guides folding of the SARS-CoV-2 receptor binding domain.Biophysical journal · 2023Article
- Single-molecule FRET and molecular diffusion analysis characterize stable oligomers of amyloid-β 42 of extremely low population.PNAS nexus · 2023Article
- Energy landscapes of Aβ monomers are sculpted in accordance with Ostwald's rule of stages.Science advances · 2023Article
- Deep learning in single-molecule imaging and analysis: recent advances and prospects.Chemical science · 2022Review
- Toward high-throughput oligomer detection and classification for early-stage aggregation of amyloidogenic protein.Frontiers in chemistry · 2022Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Polymorphism in the structure of amyloid fibrils suggests the existence of many different assembly pathways. Characterization of this heterogeneity is the key to understanding the aggregation mechanism and toxicity, but in practice it is extremely difficult to probe individual aggregation pathways in a mixture. Here, we present development of a method combining single-molecule fluorescence lifetime imaging and deep learning for monitoring individual fibril formation in real time and their high-throughput analysis. A deep neural network (FNet) separates an image of highly overlapping fibrils into single fibril images, which allows for tracking the growth and changes in characteristics of individual fibrils. Using this method, we investigated aggregation of the 42-residue amyloid-β peptide (Aβ42). We demonstrate that highly heterogeneous fibril formation can be quantitatively characterized in terms of the number of cross-β subunits, elongation speed, growth polarity, and conformation of fibrils. Tracking individual fibril formation and growth also leads to the discovery of a general nucleation mechanism (termed heterogeneous secondary nucleation), where a fibril is formed on the surface of an oligomer with a different structure. Our development will be broadly applicable to characterization of heterogeneous aggregation processes of other proteins.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.