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Image-based deep learning reveals the responses of human motor neurons to stress and VCP-related ALS

Verzat, C; Harley, J; Patani, R; Luisier, R; (2022) Image-based deep learning reveals the responses of human motor neurons to stress and VCP-related ALS. Neuropathology and Applied Neurobiology , 48 (2) , Article e12770. 10.1111/nan.12770. Green open access

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Abstract

OBJECTIVES: Although morphological attributes of cells and their substructures are recognized readouts of physiological or pathophysiological states, these have been relatively understudied in amyotrophic lateral sclerosis (ALS) research. MATERIALS AND METHODS: In this study, we integrate multichannel fluorescence high-content microscopy data with deep-learning imaging methods to reveal - directly from unsegmented images - novel neurite-associated morphological perturbations associated with (ALS-causing) VCP-mutant human motor neurons (MNs). RESULTS: Surprisingly, we reveal that previously unrecognized disease-relevant information is withheld in broadly used and often considered 'generic' biological markers of nuclei (DAPI) and neurons (β III-tubulin). Additionally, we identify changes within the information content of ALS-related RNA binding protein (RBP) immunofluorescence imaging that is captured in VCP-mutant MN cultures. Furthermore, by analysing MN cultures exposed to different extrinsic stressors, we show that heat stress recapitulates key aspects of ALS. CONCLUSIONS: Our study therefore reveals disease-relevant information contained in a range of both generic and more specific fluorescent markers, and establishes the use of image-based deep learning methods for rapid, automated and unbiased identification of biological hypotheses.

Type: Article
Title: Image-based deep learning reveals the responses of human motor neurons to stress and VCP-related ALS
Location: England
Open access status: An open access version is available from UCL Discovery
DOI: 10.1111/nan.12770
Publisher version: https://doi.org/10.1111/nan.12770
Language: English
Additional information: Copyright © 2021 The Authors. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Department of Neuromuscular Diseases
URI: https://discovery.ucl.ac.uk/id/eprint/10135935
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