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A computational suite for the structural and functional characterization of amyloid aggregates.

Accepted version
Peer-reviewed

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Type

Article

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Authors

Xia, Zengjie 
Wu, Yunzhao 
Lam, Jeff Yui Long 
Zhang, Ziwei 
Burke, Melanie 

Abstract

We developed the aggregate characterization toolkit (ACT), a fully automated computational suite based on existing and widely used core algorithms to measure the number, size, and permeabilizing activity of recombinant and human-derived aggregates imaged with diffraction-limited and super-resolution microscopy methods at high throughput. We have validated ACT on simulated ground-truth images of aggregates mimicking those from diffraction-limited and super-resolution microscopies and showcased its use in characterizing protein aggregates from Alzheimer's disease. ACT is developed for high-throughput batch processing of images collected from multiple samples and is available as an open-source code. Given its accuracy, speed, and accessibility, ACT is expected to be a fundamental tool in studying human and non-human amyloid intermediates, developing early disease stage diagnostics, and screening for antibodies that bind toxic and heterogeneous human amyloid aggregates.

Description

Keywords

Image processing, analysis automation, fluorescence microscopy, neurodegenerative disease, protein aggregate characterisation, super-resolution imaging, Humans, Protein Aggregates, Alzheimer Disease, Amyloid, Amyloidogenic Proteins, Algorithms

Journal Title

Cell Rep Methods

Conference Name

Journal ISSN

2667-2375
2667-2375

Volume Title

Publisher

Elsevier BV
Sponsorship
UK Dementia Research Institute (PILOT2020-DANIAL)