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Pore-Resolved High-Throughput Quantification of Amyloid Aggregation and Amplification

Preprint Created on 19 Jun 2026 bioRxiv

Amyloid fibrils are implicated in a wide spectrum of neurodegenerative and systemic disorders, yet their biological consequences are governed not only by total fibril content but also by how fibrillar species are organized, clustered, and amplified within heterogeneous populations. Conventional thioflavin T (ThT)-based assays provide sensitive sample-level readouts of {beta}-sheet-rich material but offer limited access to the local population structure underlying amyloid aggregation and amplification. Here, we introduce the Amyloid Pore Quantification (APQ) chip, a pore-resolved geometric partitioning platform that converts heterogeneous amyloid assembly states into fluorescence intensity distributions across thousands of defined pore-level units. Using hen egg-white lysozyme as a model amyloid-forming protein, we combine length-controlled truncated amyloid nanofibrils with vacuum-assisted ThT infiltration to establish a reproducible pore fluorescence intensity reference. APQ provided quantitative concentration-dependent calibration across a 50-fold concentration range, enabling bulk-comparable quantification while preserving pore-level distribution information. Deviations from this reference resolved pH-dependent fibril clustering near the isoelectric point as pore-signal suppression and accessibility loss, captured pepsin-associated fibrillar amplification as a population-wide increase in pore intensity, and distinguished monomer- and oligomer-driven fibril processing through coupled amplification-aggregation fingerprints. When benchmarked against ensemble fluorescence measurements and AFM morphological analysis, APQ revealed assembly-state changes that were not fully represented by sample-level ThT intensity alone. These results establish APQ as a high-throughput, distribution-aware analytical framework for translating amyloid aggregation and amplification into quantitative pore-resolved fingerprints.

Roh, S., Han, S., Bae, M., Song, E., Lee, T., Kang, D., Cheong, D. Y., Lee, H., Kim, S., Lee, G.

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