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

ABSTRACT:

Aims

Although morphological attributes of cells and their substructures are recognised readouts of physiological or pathophysiological states, these have been relatively understudied in amyotrophic lateral sclerosis (ALS) research.

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 unrecognised 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

SUBMITTER: Verzat C 

PROVIDER: S-EPMC9298273 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature